8th International Conference on the Development of Biomedical Engineering in Vietnam

This paper presents a massage-treatment prototype on acupuncture points whose method of detecting is based on differences of blood oxygen saturation ratio. Sensor MAX30100 is used to measure blood oxygen saturation (SpO2) of more than 20 people in bright room conditions with an intensity of 115 lx and an ideal dark room condition. Then based on Beer's law of absorbance and experiment, we determined that the points with SPO2 concentration over 99.2% are the locations of the acupuncture ones in order to perform biological massaging pulse. The main scientific principle is the diffuse remittances of diverse red led from meridian and acupuncture point that make blood oxygen saturation levels higher than other areas. In the experiment, we also consider prudently the results of tissues surrounding acupuncture points with the distance of 5, 10 and 20 mm and the influence of that to the final outcome. In general, the final result is reliable with moderate accuracy. However, there are some drawbacks in this system such as errors for people who have inappropriate skin surface for optical detection.

This paper presents a wireless health care device to monitor the patients’ heart rate. There are a variety of methods to measure cardiac cycle: optical sensor, one lead of ECG, sound sensor, etc. This proposed general algorithm is to measure the sounds of the heart rhythm transmitted from the heart to the patient's chest, and these sound signals are used to calculate the heart rate. This chosen method is simpler and lower cost compared to the others. The most important necessary thing is that the designed device has high accuracy shown in the results. This device is used to replace the workday routine of the doctors. Although they do not need to visit the patient’s room, the doctors can still receive information about their patients’ heart rate. These data can transfer from the measuring devices to the display devices. By following this method, doctors or nurses can always update the status of patients and immediately improvise them. This system can be worn easily on the patients’ chest. The patients can wear it all the time while still feeling so comfortable. This device is expected to be used in the hospitals to monitor the heart rate of the patients for a long time. At the hospital settings where medical equipment is quite limited, this device is a good solution because it is compact, convenient and affordable.

Respiratory rate is always evaluated as an indispensable physiological parameter to know about the health status of a person. Also, the monitoring of human breathing activity for a long period has numerous foundational applications in medicine. This paper proposes a prototype whose functions are measuring respiration rate and detecting sleep apnea periods with a view to monitoring sleep quality. The main principle of this device is using an infrared sensor to detect respiratory activity based on the movement of the abdomen. The distance between the sensor and the patient is from 20 to 35 cm. The distance permits supervising the breathing activity without any awareness by the subject and any modification of the sleep quality, which is very important for sleep disorders diagnostic applications. The experiments were conducted on three people during about 10 minutes each, one of whom has no sleep apnea syndrome while two others are suffering from such disease. The average accuracy of the proposed system is 95.72%, the average sensitivity is 94.57%, and the average specificity is 96.92% in terms of respiratory measurement. The sleep apnea detection reaches high average parameters which are 100%. Generally speaking, the results obtained are moderately acceptable with high precision. However, the proposed system only performs well if the users sleep stably on their back, and there is no obstacle, such as a thick blanket between them and the sensor. These problems need improving in further research to create an optimal product which offers potential application in home and mobile healthcare.

Most hospitals and patients in low/middle-income countries (LMICs) cannot afford the current pricing schedules of commercial mechanical ventilators. This has resulted in a marked restriction of their availability and left patients with respiratory failure with restricted access to this life-saving treatment. Here, we present and discuss a novel, especially designed low-cost and easy-to-build non-invasive bilevel pressure ventilator that should reduce the serious shortage of ventilators in LMICs. The ventilator is built using off-the-shelf components available via e-commerce and is based on a high-pressure blower, two pressure transducers and an Arduino Nano controller with a digital display (total retail cost < 75 US$). The designed ventilator allows independent setting of inspiratory and expiratory pressures up to 20 and 10 cmH2O, respectively, selectable cycling threshold and a back-up rescue frequency (assisted-controlled ventilation mode). All construction details are provided following an open-source hardware and code approach for free replication. This non-invasive ventilator, with equivalent performance to high-quality commercial devices, could facilitate the application of this life-saving therapy to LMIC patients who otherwise would not be treated.

Nowadays, there has been an enormous rise in the request for polymeric nanofibers, which are encouraging candidates for numerous applications, namely blood vessels, drug delivery, tissue engineering, etc. Therefore, the development of electrospinning is also compulsory for the growing of tissue engineering area in Vietnam. The majority parts of electrospinning involve a collector, a syringe pump, a DC-high-voltage source. In this research, we aim to implement a low-cost grounded collector that is a crucial component in an electrospinning machine. The mechanical design includes a collector, ground facility and electrical control panel box. The hardware consists of motor driver boards. The firmware is developed based on stm32f103rbt6 microcontroller IC with the PID algorithm to automatically apply an accurate and responsive correction to a speed control function when the desired speed is the unequal set speed with the error about ± 3 rpm. The rotational speed can be adjusted from 0 to 2000 rpm for both random and aligned nanofiber applications. As expected, the prototype is a user-friendly and cost-effective platform; its cost is much less than the commercial laboratory devices one. The system has been undergoing experimental electrospinning processes with different polymer concentration at different collector speed. This system is also examined the quality and investigate in a set of electrospinning parameters that suit a variety of applications requiring different average diameter and the fiber's alignment degree.

Real-time Polymerase Chain Reaction (realtime PCR) is an important medical diagnostic technique in which target DNA is amplified and the amplification process is monitored in realtime. However, most realtime PCR systems are expensive, especially for laboratories in developing countries. To increase accessibility to the realtime PCR technique, we developed a low-cost and portable real-time PCR system. The system was composed of two main parts: a thermocycler and an optical system. The thermocycler's core was a Peltier and a heatsink fan, in tandem with an electronic circuit to control the heating process’s temperature. A custom-made fluorescence optical setup was built using a blue LED chip (450 nm), an excitation filter, a dichroic mirror, an emission filter, and a CMOS camera. The results were displayed on a screen connected to a Raspberry Pi module. The thermocycler worked stably and accurately under the control of a PID controller. The system’s performance was tested using samples of rice phospholipase D (PLD) gene and maize Bt11 gene. The results showed that, at the end of the amplification process, fluorescence signals from positive samples were significantly higher than from negative samples. Nucleic acid amplification products were verified using gel electrophoresis. With the cost of ~$320 USD, the system could be a suitable candidate for realtime PCR tests in laboratories in rural and remote areas of developing countries.

During the electrospinning process, the most crucial and impactful factors affecting the quality of the PCL membrane on collectors include humidity, temperature, syringe pump speed. Additionally, some buffers may generate toxic gas that must be immediately evacuated from the environment, and the high voltage part of the device is dangerous that must be safely isolated from the users. Therefore, designing a complete electrospinning system that generates high-quality membranes and safety to use becomes vital. We designed a complete electrospinning system that includes: a protecting glass chamber equipped, an electronic controller to supervise and display environmental parameters. The chamber was built from profiled aluminum and glass, and a fume hood ventilator was used to suck gas out of the chamber. A controller system consisting of hardware design and firmware programming was implemented to measure temperature and humidity in electrospinning chamber; to control factors affecting the nanofiber membrane such as drum collector speed, syringe pump, temperature, and humidity. The zero-crossing technique was used to control temperature and speed of fume hood fan. Furthermore, the PID controller was applied to regulate the rotational movement of drum collector. We successfully built the complete electrospinning system. The temperature and humidity ranges varied from −40 to +125 °C and 0–100% RH, respectively. Rotational speed of the aluminum drum was from 0 to 2000 rpm. And the volume error of the electrical syringe pump on the average is 0.60% and the speed is from 0.1 to 20 ml/h.

The state-of-the-art field of bio-inspired soft robotics promises emergent and inventive methods to utilize robots made from soft, flexible materials in a wide range of applications. This research is on-trend, describes an advancement in the design of a wearable robotic glove to assist people suffering from hand impairments regain their ability to control their environment. This study built a streamlined, inexpensive electro-pneumatic system that can work with small and simple actuators to increase for finger movement flexibility. The use of pneumatic pressure to stretch and bend the actuators through inflation or deformation of elastic chambers, making this glove work effectively. The designed pneumatic device consists of STM32F101C8T6 microcontroller combined with a series of pumps and a matrix of solenoid valves. Along with the electro-pneumatic system, we also applied it to develop a wearable robotic glove (made from Ecoflex™ rubbers) which is suitable for the pneumatic system by the series of experiments that mechanically characterize the actuators. The results gathered in this study validate the feasibility of the first prototype of our soft robotic glove as an effective device to assist hand function in individuals. However, performance and ease of use of the system should be improved further in future development phases.

Vein detection technology has significant applications in many areas such as healthcare, security and aesthetics. In healthcare, vein visualization is highly necessary for making an accurate venipuncture. This work demonstrates a portable hand vein finder system using noninvasive infrared technology that can display the real-time venous image on a monitor. The skin surface is illuminated by a near-infrared (NIR) light source that contains 5 LEDs (850 nm) and 5 LEDs (940 nm). These LEDs are arranged alternately in a circular form. Under NIR light exposition, vein and surrounding tissues are distinguished due to their difference in the brightness and contrast. A 3 MP camera is used to capture the illuminated skin area, and the obtained signal is then transferred to a Raspberry Pi 4 for image processing. The input image is processed with median filtering and contrast-limited adaptive histogram equalization (CLAHE) for displaying on a monitor. After processing, venous images with much better contrast are observed. To project the venous patterns on the skin surface, local adaptive threshold and subsequent morphological image processing are used. After the first algorithm, the venous patterns are segmented out of the image. Then, morphological processing, which has rarely been widely used for vein visualization, further reduces the noise signal, such as hair on the hand thus clearer and sharper venous patterns are obtained. Our work provides an effective and low-cost solution for nursing staff in low and middle-income countries to perform a safe and accurate venipuncture.

In modern society, the ever-growing prevalence of stroke or hand disability, putting an extreme burden on the limited financial resources and capacities of health care providers in some of the Low and Middle-Income Countries (LMIC). Due to the large scale of flexibility and adaptability, soft robots turn into a smart solution for hand rehabilitation, especially soft pneumatic actuators. In this paper, we proposed a general design of soft robotic glove for hand rehabilitation with functional grasp pathologies by applying soft pneumatic actuator technology. Soft actuator included integrated channel connect each chamber to lead the air to go through the entire actuator and produce bending motion conforms with human finger shape and motion. Base on this aspect, before fabrication, a Finite Element Model (FEM) was built to analyze the bending curvature of these actuators. The soft actuator is cast in 3D printing molds using low-cost elastomer Ecoflex™ 0050. We carried out empirical tests to validate the findings of experimental actuators and compared them to FEM data displaying strong agreement. Finally, the design of a wearable for patients to practice rehabilitative activities such as grasping patterns. The outcome of this paper shows that the design of rehabilitation glove using soft actuator technology gave a successful solution for the health care system with low-cost material.

Phase angle (PA), related to bioelectrical impedance, detects changes in tissue electrical properties. Because of being dependent on body cell mass and cell membrane functions, PA has been considered a prognostic indicator in several clinical diseases such as HIV, chronic pulmonary disease, colorectal cancer, and breast cancer. PA has attracted considerable interest and has been frequently referred to as a global health marker within the clinical nutrition community research on cellular health. Therefore, this study is aimed to design a system for automatically measuring the phase angle with high accuracy of an individual body segment after excitation by a current source. The phase angle measuring system comprised a sine-wave generator, a low-intensity, high-frequency (100 kHz) current pump, a phase difference-to-voltage converter, and a high-resolution analog-to-digital converter (ADC). The design of the phase difference-to-voltage converter was based on a high-precision analog multiplier and a peak detector. The phase difference-to-voltage converter’s performance assessment was conducted by applying two programmable phase-difference signals generated by the pulse generator to ensure the accuracy of the phase angle difference. The converted phase angle was then read by a 16-bit ADC and displayed. The two identical-frequency sine-wave signals were programmatically generated with phase angle difference step of 10° ranged from 10° to 90° for phase difference to voltage converter inputs. The measurement showed the error of 0.5° ± 0.2° (mean ± standard deviation) for the overall nine phase angle difference steps.

Detecting obstacles is always a difficult task for visually impaired people when they move. External guidance such as human, trained dog, or white cane, a.k.a. blind stick, plays an important role in the decision making of blind people. Due to its low cost, white cane is often used by visually impaired people. However, traditional white canes cannot accurately detect obstacles above knee level or at distance beyond the white cane’s length. Our goal is to create an affordable, smart blind stick that can help blind people to navigate. The device consists of an ultrasonic sensor and infrared sensors for detection of obstacles in front of blind user and vibration motor + buzzer for alarming. One of the biggest challenges for blind people when they move indoor is to go up and downstair. We aim to address the challenge by integrating into our blind stick a function that alarms user in the presence of staircase. Moreover, this device also has a built-in GPS module and a GSM module that allows the device’s and its user’s location to be tracked and displayed on a smartphone app, a desirable feature for many family members of blind people. Ultrasonic and infrared sensors allowed our smart blind stick to detect obstacles at a distance from 5 cm to 150 cm from the user. Our design has several advantages including low-cost, capability to detect obstacles above knee level, staircase detection, location tracking via smartphone app, etc. In future work, more tests need to be conducted to determine its accuracy and reliability in real-world settings.

The study aims to determine the effect of polishing parameters as well as polishing speed, abrasive sizes and electric current on surface roughness of titan alloy in the magnetorheological polishing (MRP) methods. When the electric field is applied, the rheological properties of MRP fluid will be changed in the machining process. As a result, the viscosity and shear yield stress of MRP fluid was greatly improved under applied electric current. The workpiece surface can be polished by the abrasive particles with adhering to MR fluid. The influence of polishing parameters on the surface roughness was investigated by experiments. The experimental results indicated that the polishing speed has a great influence on the surface roughness of workpiece. With the increase of the polishing speed, the best surface roughness can be obtained by using the MRP method. The abrasive size had very little effect on surface quality improvement when it was changed in the experimental process. In addition, the electric current also has a strong effect on the surface quality of workpiece. As a result, the surface roughness of ball titan alloy workpiece (Ø32 mm) was reduced rapidly from Ra = 120 nm to Ra = 18 nm under the appropriate machining conditions.

The objective of this study is to experimentally examine the effect of applied load and surface texture on friction of UHMWPE in total joint replacement by measuring the coefficient of friction (COF) between CoCrMo pin and UHMWPE discs. A CoCrMo pin with the dimensions of 11 mm in diameter and 18 mm in length was machined to obtain the surface roughness of 0.25 µm. For preparing different surface texture, ten UHMWPE discs with the dimensions of 88 mm in diameter and 5 mm in thickness were machined by two different machining processes of milling and turning to obtain two roughness values of 2.5 and 0.25 µm. 25 mg/ml BSA was made by mixing BSA powder in 10% PBS. A frictional testing apparatus was developed and carried out for the calculation of COF. Results show that the COF increases with the increase of the applied load in both cases of the UHMWPE roughness of 0.25 and 2.5 µm. With the UHMWPE roughness of 0.25 µm, the COF decreases when the surface texture machined by milling compared to that by turning in both cases of the applied loads of 4 and 16 N; however, with the UHMWPE roughness of 2.5 µm, the COF increases when the surface textures machined by milling compared to that by turning. These results suggest that both the applied loads and the surface textures have important effects on the friction of UHMWPE.

Polarization is an elementary property of light waves and has many applications in medicine and health sciences. In this research, an automatic control UV light source Stokes polarimeter system is built using simple and inexpensive optical devices. The optical system includes one UV laser source, three polarizers, two quarter-waveplate, and one optical sensor applying the Mueller-Stokes decomposition for extracting linear birefringence (LB), linear dichroism (LD), circular birefringence (CB), circular dichroism (CD), linear depolarization (L-Dep), and circular depolarization (C-Dep) of a biological sample. The system can measure the intensity of 180 data points then calculate the output Stokes vector of measured samples from 4 inputs polarized lights (i.e., 0°, 45°, 90° of linear polarized lights and right-hand circular). The experimental results showed that the system could automatically measure Stokes parameters of a biological sample with the accuracy at ±5% to compare with the commercial device, Stokes polarimeter. Therefore, the designed system has the benefits not only of extracting the optical parameters of the biological samples but also of improving the accuracy of results by reducing the error effect on the measurement.

Beta has been scarcely defined as a potential feature for motor imagery-based Brain-Computer Interface use due to its unstable nature in the temporal and spectral domain. Specifying or narrowing down beta sub-bands cannot detect beta occurring non-uniformly in time and frequency for different tasks. This study aims to evaluate beta response quantitatively in terms of event-related synchronization during 3 continuous stages (pre-task, on-task and post-task) of each single imagery trial. Electroencephalogram of thirteen healthy college-aged students were measured on 3 channels (C3, Cz and C4) while the subject performs 3 imagery movements (left hand, right hand and feet). The study proposes an alternative statistical approach utilizing standard event-related synchronization analysis and Fast Fourier Transform based on summarizing all measurement data sets. Broad beta power spectrum, varying from 13 to 35 Hz, is analyzed in order to get trial-channel-specific beta frequency response, and is visualized by using time–frequency color map. The new approach shows the mean percentage of beta response during on-task stage when combining all tasks are 21.8%, 23.1% and 21.1%, for 3 channels C3, Cz and C4, respectively. The results from ANOVA analysis shows that there is a significant difference (p < 0.0001) in the percentage of beta response during 3 continuous stages for all 3 tasks. Besides, feet imagery task has a difference in the percentage of beta response in 3 channels, while left/right hand task has no difference. Lastly, the most common beta frequency response is found to be different (p < 0.05) during 3 continuous stages for left hand task, while the right hand and feet task has no difference.

Temperature and humidity are crucial to food manufacture and preservation processes. The traditional way to acquire this information is to enter the food storage and perform measurements manually. This approach could be relatively time-consuming compromising the desired isolation of food storage with the outside environment, yet it cannot provide real-time data. This paper presents a sufficient, concrete design of an automated system whose objective is to monitor temperature and humidity in real-time to reduce such shortcomings. The system consists of a handset and multiple sensor nodes. It operates on an established wireless local area network in the user's facility and is highly scalable in the number of sensor nodes. To prove the design, a prototype was built and evaluated of data accuracy, data latency and power consumption: the MAE of temperature is 0.5 °C, of relative humidity is 1.0375%, of data latency is less than 1 s, and of power consumption is 1020 mW. This result is sufficient for our intended application. After the experiments, we realized it is possible to generalize the design to monitor and record any environment property for further analysis. To uncover that possibility, the various aspects of such a system have been discussed: data integrity, ease of deployment, security concern, robustness, scalability, and extensibility. These discussions should help the creation of formal technical specifications to guide industry-level implementation.

The measurement of non-invasive blood pressure (NIBP) parameters is currently being used in many medical facilities for examination and treatment. In addition, the need to use these devices at home for patients to check their own blood pressure is also increasing. However, the measurement of blood pressure values at home is only for the purpose of patient's reference. Meanwhile, if this data is sent back to the doctor regularly, it will be a very useful source of information for doctors to monitor, analyze and recommend a good treatment regimen for patients with hypertension. This article presents the design of a system that continuously measures and sends blood pressure values to the doctor by combining a personal blood pressure device with a smartphone. The result of system design includes an application on the smartphone for the patient, able to connect to receive data from iChoice blood pressure monitor; a database used to store measurement results on the server and a smartphone application for doctors to analyze and process data. The system has been deployed in trial measurement on five volunteers with a total of 100 measurements. Test results show that the system works very stable, accurate and reliable, has practical applications to support the diagnosis and treatment of blood pressure diseases.

Vietnam has about 2 million visual impairments people. In which only 8% go to school, 15% are trained in vocational centers and 20% have job opportunities. The blinds have many difficulties in living as well as learning and socializing. For the blind, learning Braille is the best way to minimize difficulties in all aspects of life. Each Braille is made up of 6 points; these points form a rectangular frame of two columns and three rows. The combination of six floatingsink points creates encoding for all characters. The scientific and technological solution that we have proposed with the goal of supporting Braille children to learn Braille in IoT applications. The product system includes many Braille coding devices for the blind; each module is used by a blind person. Each device is connected to the system’s server which is designed on the internet.

The production potential of Atlantic salmon in Norway is influenced by a large number of variables that may best be controlled if it is possible to follow representative samples, collected randomly from fish that are still alive inside the production plant. The most optimal or objective way to follow stress or well-being of a fish is to be able to analyze in-vitro, different molecular changes within representative samples automatically. The first generation of automated fish sample collection system was developed to combine with refining technology from the partner in the CtrlAQUA center ( www.ctrlaqua.no ) in order to give a high analytical sensitivity, a low enough number of false negatives and positives. Result of the experiments illustrates that non-clogging separation and high concentration ratio can be achieved.

Cardiovascular disease and stroke due to high blood pressure continue to be one of the leading causes of death in Vietnam and elsewhere. Continuous control of patients’ blood pressures plays, hence, a vital role in reducing the risks of these diseases. We implemented a telemedicine system to monitor the blood pressure of hypertensive patients in Binh Duong province. This cyber medical system consisted of a Tele-Blood Pressure device, a software program for servers, and an application for smartphones. Besides, it provided considerable utilities for doctors to better take care of patients. In the project described here, we evaluated the efficiency. First, two groups (control and treatment) of 100 patients each who had histories of high blood pressure were selected using randomized controlled trials (RCT) method. Second, pretest–posttest experiments were conducted. During 18 months both groups were monitored by the same 3 physicians and 4 nurses from the beginning to the end. The obtained results were compared using paired t-test or chi-square test. At the end of the study, a survey of the satisfaction of all aspect of the system was conducted to all patients of the treatment group, physicians and nurses. The percentages of satisfactions were well above 82%. This study will be extended at a larger scale, especially in the remote areas where the healthcare needs to be improved.

Chronic inflammation plays a central role in challenging ailments, from cardiovascular diseases to cancer. The connection has been made in progressed inflammation and the overproduction of reactive oxygen species (ROS), or oxidative stress, through various inflammatory pathways. Curcumin is well-recognized as a natural supplement with diverse pharmacological effects, especially antioxidant and anti-inflammatory activities. However, curcumin’s extremely poor bioavailability and rapid oxidation by ROS has hindered promising clinical applications. Previously, silica-containing redox nanoparticles (siRNP) was developed and prepared from amphiphilic block copolymer possessing drug absorptive silica moiety and ROS-scavenging nitroxide radical moiety in the hydrophobic segment. In this research, curcumin loaded siRNP (CUR@siRNP) with the size of about 120 nm in diameter were employed as an efficient nanocarrier for curcumin via dialysis method. After encapsulation, CUR@siRNP showed a great improvement in solubility while drug release assay in varying pH demonstrated a slightly pH-sensitive property of siRNP in the gastric medium. The CUR@siRNP also showed an enhancement in antioxidant activity, which was confirmed through 2,2-diphenyl-1-picrylhydrazyl assay. The anti-inflammatory effect was also evaluated in vitro using albumin denaturation inhibition assay. The CUR@siRNP combination showed the potential to be further investigated and developed for a novel antioxidant and anti-inflammatory nano-formulation in treatment of chronic inflammation.

Chitosan (CS) has been widely studied as polycation to form the polyion complex (PIC) micelles, which have emerged as promising delivery systems for sustained release of hydrophilic drugs. However, poor solubility in aqueous solutions limits the application of CS. In this study, trimethyl chitosan (TMC), the partially quaternized derivative of CS, was synthesized and investigated the PIC formation coupled with poly(acrylic acid) (PAA) at different cationic: anionic ratios (named as TMC/PAA micelles). The encapsulation of hydrophilic anticancer drug, doxorubicin (DOX), release profile, and cytotoxicity against murine colon cancer cells were also evaluated. The results showed that the sustained release of DOX from TMC/PAA micelles was confirmed. We found that the release of DOX from TMC/PAA micelles in acidic pH buffer (pH 5.5) was significantly higher than in physiological pH (7.4). Finally, the anticancer activity of DOX-loaded TMC/PAA micelles was remarkably higher than that of DOX. The results in this study suggest the potential application of TMC/PAA micelles as controlled drug delivery for cancer therapy.

Berberine is widely used in Eastern countries thanks to low cost and various biological activities. However, low solubility has limited its bioavailability. The purpose of this study is to prepare and evaluate solid dispersion loading berberine—β-cyclodextrin complex to improve the effective treatment of berberine. Two techniques, inclusion complex and solid dispersion, are applied to increase the bioavailability of berberine for further applications. The inclusion complex is prepared by grinding berberine and β-cyclodextrin with various ratios. Solid dispersion loading berberine—β-cyclodextrin complex is fabricated from polyethylene glycol (PEG 6000) by melting completely and then spray-drying with lactose for powder formation. The complex and solid dispersion is evaluated about solubility and drug release in distilled water. Moreover, the final product is also analyzed with powder X-ray diffraction (PXRD). As a result, the complex which has ratio 1:1 between berberine and β-cyclodextrin expresses the highest solubility and optimal dissolution profiles in distilled water in comparison with pure berberine. Solid dispersion samples show many advantages in solubility and dissolution rate compared to pure berberine; the solubility reaches nearly three times over pure berberine. The results of the sample of incorporation of the β-cyclodextrin complex into solid dispersion have significant improvement compared to pure berberine. In general, solid dispersion containing berberine β-cyclodextrin complex expresses the considerable enhancement in vitro bioavailability of berberine. Hence, it could be applied as a promising system for improving the therapeutic treatment of berberine.

Berberine is commonly used in Eastern countries due to its various biological activities and low cost. However, low permeability has limited its bioavailability. This study was conducted to fabricate solid lipid nanoparticles (SLNs) containing berberine by spray-drying method to enhance its absorption in the human body. SLNs containing berberine was prepared by stearic acid as a solid lipid base and various surfactants. Then, the aqueous dispersion of SLNs was converted into powders to be stored over a long time by the spray-drying method with carbohydrate carriers. The spray-drying parameters such as the inlet and outlet temperatures, the blower speed, the atomizing pressure, the feeding rate were optimized. The nanoparticles physicochemical properties were evaluated before and after the spraying process. The lipid nanoparticles containing berberine were successfully prepared by the spray-drying method with a small particle size (around 230 nm), zeta potential (approximately −30 mV), and homogenous dispersion (polydispersity index just above 0.12). The optimized spray drying parameters were Tinlet/outlet of 110/65 °C, the blower of 0.58 m3/min, atomizing of 20 kPa, and feeding rate of 0.1 L/h. The resulted SLNs exhibited good physical stability and redispersion. The collected SLNs by spray-drying could be considered a potential drug delivery system to enhance berberine absorption into our human body.

Rutin is a flavonoid which has a high effect on strengthening blood vessels, antioxidant, anti-inflammation, and even preventing cancer. However, the critical physicochemical properties of rutin limit its therapeutic effectiveness. This project aims to prepare two lipid-based nanoparticles: phytosome and niosome to increase the bioavailability of rutin. Lipid-based vesicles containing rutin were prepared by the thin-film hydration method. Rutin phytosome and niosome were formed by phospholipid, cholesterol, and surfactants. The effect of excipient combination and fabrication process parameters on the size and zeta potential were evaluated. Drug loading capacity and encapsulation efficiency were also investigated. Both phytosome and niosome formed nanosize vesicles which approximate 200–300 nm with an acceptable polydispersity index (PDI) (0.22–0.23) and zeta potential (absolute value nearly 30 mV), that indicates the good homogeneity and electronic surface interaction. Furthermore, these nanocarriers have succeeded in drug-loading and encapsulation, specifically, the percentages of loading drugs are from 26 to 31%, and the efficiency of encapsulation is 64 and 66%. Lipid-based vesicles were successfully prepared with lecithin in phytosome and Span 60 in niosome. Phytosome and niosome loading rutin are potential nano-drug delivery systems which can be practically applied in cosmetics and medicine.

A series of pH/temperature-sensitive OS-PLA-PEG-PLA-OS copolymers that could create in situ hydrogels are synthesized by combining thermoresponsive PLA-PEG-PLA (poly lactide-poly ethylene glycol-poly lactide) with OS (oligoester serine—a pH-sensitive component). The characteristic features of the copolymers were systematically evaluated by analyzing the chemical structure, morphology, sol–gel transition, and in vitro degradation. Thanking to sulfonamide groups of OS blocks with excellent pH-sensitive property, the pentablock copolymers (OS-PLA-PEG-PLA-OS) possessed better stability related to pH and nature in buffer solution than those of the triblock copolymers (PLA-PEG-PLA). It is also found that the OS-PLA1960-PEG1750-PLA1960-OS hydrogel only exhibited the thermoresponsive behavior due to too long hydrophobic block in its structure, whereas, the OS-PLA1750-PEG1750-PLA1750-OS hydrogel (30 wt%) demonstrated dual pH/temperature-sensitive properties with superior characteristics including a safe gel range under pH ranging from 6.0 to 7.8 at the temperature of 37 °C and slow degradation rate. We believe that the present pH/temperature-sensitive hydrogel has a potential application as an injectable carrier for prolonged release of drugs.

Tetracycline is a broad-spectrum antibiotic that can help control microbial infections in human and veterinary. Excessive use of tetracycline in veterinary medicine and animal feeds as antibiotics and growth promotors could lead to antibiotic residues in foodstuff. Tetracycline residues in the food chain can be responsible for undesirable side effects on human health and emergence of antibiotic resistance strains of bacteria in both veterinary and human. Therefore, there is an urgent need to develop a simple, rapid method for determination and quantification of antibiotic residues in animal-derived foods. In this study, a colorimetric aptasensor was designed for sensitive and fast detection of tetracycline based on aggregation of silver nanoparticles with a low cost. Our detection method exploits tetracycline-specific DNA aptamer as the recognition element of an optical sensor. In the absence of tetracycline, silver nanoparticles are still well—dispersed, stable against salt-induced aggregation. In the presence of tetracycline, DNA aptamers detach from the nanoparticle’s surface and bind to its target, leading to the aggregation of silver nanoparticles by salt and a noticeable color change from yellow to colorless. The presented aptasensor showed high sensitivity and selectivity toward tetracycline with a limit of detection as low as 100 nM with an analysis time of ~ 20 min. With regard to demonstrating sensitivity and specificity of the sensor, our sensing platform shows a great potential application in rapid detection of antibiotics in the field of biomedicine and food safety.

Staphylococcus aureus is one of the ubiquitous bacterial pathogens in human that are able to cause various diseases from skin infections to serious diseases. This pathogen can make seven types of bacterial toxins that are accountable for food poisoning. Moreover, the pandemic of methicillin-resistant Staphylococcus aureus has been globally dangerous for chronically infectious diseases, and nosocomial infections with life-threatening problems, because of their resistance to most antibiotics. Therefore, rapid and accurate detection of S. aureus has emerged as an urgent need in fields of clinical diagnostics, biodefense and food safety. However, the current rapid tests are challenging with being limited their capacities in on-site detection for the increase of prevention results. In this study, we report an aptamer-based sensor for fast detection of S. aureus. Instead of trying to capture bacterial cells on the substrate or nanoparticle surface, our detection method allows the DNA aptamer to detach from the silver nanoparticle when interacting with bacteria and bind to its target, leading to the aggregation of silver nanoparticle by salt. The strategy dramatically enhances the selectivity and sensitivity of whole-cell based biosensor. The results demonstrated that aptasensor could detect S. aureus with a detection limit of ~ 105 CFU/mL within 20 min. The detection method showed many advantages compared with conventional methods with respect to cost, simplicity and analysis time. This biosensor can be used as a powerful bio-analytical tool for whole-cell detection.

Vancomycin is a primary regimen for treating MRSA and other Gram-positive $$\upbeta$$ β -lactam–resistant organisms. But the problem is the resistance to vancomycin, the clinical and microbiological characteristics in which it is used is always changing. Therefore, we conducted this retrospective study to analysis benefits of Vancomycin TDM in clinical outcomes and discovered the factors affecting on the vancomycin maintenance dose. We conducted a follow-up on 137 patients using vancomycin divided into two groups, including the TDM and non-TDM users. The evaluation criteria included panoramic vancomycin use, infection status, renal function and treatment results after ten days. The total number of samples taken from 79 patients applied TDM were 116 and 73.3% of the samples reached the target trough concentration. Compared to 58 patients of the non-TDM group, applying TDM will reduce c-reactive protein (CRP) and improve treatment outcome. We also found that the vancomycin trough concentration, creatinine clearance, and weight contributed significantly (24.7%, 16.8% and 26.6%, respectively) to the inter-individual variability in vancomycin dose. The multiple linear regression model for vancomycin maintenance dose was built as the formula: Vancomycin maintenance dose (mg/kg) = 21.4 + 0.24 * vancomycin trough concentration (µg/mL) + 0.17 * Clcr(mL/min) − 0.26 * weight(kg) + 0.17 * age(years) − 0.03 * ΔCRP. Our study demonstrated the benefits of vancomycin TDM technology on clinical outcomes and improvement of infection situation. Furthermore, we have successfully indicated a strong relationship between vancomycin trough concentration, creatinine clearance, age, weight, ΔCRP and maintenance dose of vancomycin. Clinicians in the process of designing a regimen dose of vancomycin should comprehensively consider these factors in order to optimize the dose and reduce the adverse effect of vancomycin.

The aim of this research is to customize the porosity of biofabricated chitosan membrane (CM) employing co-assembled polystyrene nanoparticles (np) as a sacrificial template. CM with np (CM-np) was manufactured inside the microfluidic chip using the flow-assembly technique. Glutaraldehyde was used to crosslink the fabricated CM-np were then dissolved with dimethyl sulfoxide, leaving the porous chitosan membrane (pCM). The growth rate of CM and CM-np was investigated to determine the effects of np incorporation on the growth of the fabricated membrane. The morphology of the biofabricated CM and pCM were evaluated using scanning electron microscopy. The mass transport tests were also conducted to confirm the increase in pores size of pCM in comparison with pure CM. Thus, in this study, we have demonstrated the capability to manipulate the porosity of the biofabricared CM manufactured by flows inside microfluidic chips and characterized the properties of the fabricated membranes. This tuning process is promising and can enhance the applicability of biopolymer CM in biochemistry and biology researches.

The mortality and morbidity caused by vascular diseases has resulted in an ever-persistent demand for artificial vascular graft replacing injured vessels. The electrospun combination of polyurethane (PU) and polycaprolactone (PCL) has proved its potential for the application as vascular graft but it lacks sufficient antithrombotic properties. Based on its biological properties and sustainable costs, virgin coconut oil (VCO) could be a promising additional anticoagulant agent for the PU/PCL composite.This research fabricates PU/PCL electrospun scaffold loaded with various concentrations of VCO. The parameters of electrospinning were varied to obtain suitable membranes. The effects of these parameters and the VCO on the morphological and mechanical properties of PU/PCL were investigated by scanning electron microscope and tensile strength assay.It was revealed that the condition set of 12 cm tip-to-collector, 20 kV applied and 0.5 mL/h flow rate yielded suitable electrospun membranes with various VCO percentages. The loaded VCO decreased the mechanical strength of the membranes. The ultimate stress and strain of the membranes decreased accordingly with higher content of VCO but did not drop below the acceptable limit. This study has obtained the electrospun PU/PCL membrane loaded with VCO processing appropriate morphology and mechanical properties. The loading of VCO altered the fabricated membranes but they still satisfied vascular graft requirements. Therefore, the PU/PCL loaded with VCO membranes are promising for further research as artificial blood vessels.

Electrospinning is a preferable technique to fabricate scaffold, which have the ability to mimic the structure of extracellular matrix. Small-diameter vascular grafts have been developed by co-electrospinning PCL and elastic PU. Among the suitable materials used to engineer small diameter vascular prosthesis, the polycaprolactone (PCL) and polyurethane (PU) are two appropriate candidates for artificial blood vessels application approved by Food and Drug Administration for biomedical applications with good mechanical properties and high biocompatibility. This electospun graft was adopted with long degradation time and high mechanical strength. PU/PCL nanofibrous membrane were successfully fabricated by the electrospinning system design by Biomedical Engineering School, International University, Ho Chi Minh National University (BME-IU). However, the fabrication of electrospun hollow tube at small diameter was affected by many parameters including applied voltage, distance from needle to collector, pumping speed, collector’s rotation speed and the type of solvent. This research studies the parameters’ effect of tubular electrospun system designed by BME-IU on the morphological properties of these vascular scaffolds using SEM and diameter analysis.

Chitosan oligomer (OCS) captured much attention for diverse applications in the biomedical and pharmaceutical fields. In this study, OCS, as an antimicrobial agent, was coated onto dressing based electrospun polycaprolactone (PCL) membrane to enhance the bio-function and physical properties of materials. The various content of the OCS coating layer in terms of concentration (2, 4, 8, 16%) or coating times (1, 3, and 6 times) was concerned in this study. A Fourier-transform infrared was used to analyze the functional structure OCS derived from chitosan. Agar diffusion test was performed to pretest the antibacterial ability of OCS coating solution with gram-positive (S. aureus) and gram-negative (P. aeruginosa). The morphology and physical strength of PCL membranes and OCS coating layer were observed by Scanning Electron Microscope (SEM) and the uniaxial tension, respectively. From the agar diffusion test, OCS with a low concentration (2%) inhibited both mentioned pathogens. SEM evaluation displayed the irregular surface by the OCS multi-coating layer, while smoother morphology by one-layer coating with high OCS concentration. In the physical test, the membrane became more inflexible as the higher OCS content in both the coating method as the different mechanical strength between PCL substrate and OCS coating film.

Fibronectin (FN) is an important adhesive extracellular matrix protein. It forms a fibrillar matrix on cell surface which controls cell morphology, adhesion, migration and proliferation. This study aimed to analyze the effect of in vitro cell-free formed fibrillar fibronectin with different morphologies on mouse fibroblasts L929 cells migration. To evaluate fibrils morphology on cell function, fibroblast L929 were cultured on surface pre-coated with FN and FN fibrils at concentration of 0.25 and 0.75 mg/mL at 4 °C overnight, then cell migration assay were performed. Migration speed of cells monolayers grown on different fibronectin surfaces was measured by using snapshot pictures with a regular inverted microscope at 0, 12, 48 and 72 h. Our cell-free FN fibrillogenesis indicated that at different concentrations, fibronectin organized into various structural matrix. Our data showed that large fibronectin fibrils decreased the rate of cell migration while small fibronectin fibrils (0.25 mg/mL) did not, compared with native plasma fibronectin. These data demonstrate that there is a strong relationship between structure and function of fibronectin. Taken together, our data draws new attention towards controlling biological function of fibronectin by its fibrillar structure.

Naïve induced pluripotent stem (iPS) cells are useful for drug development, disease model and regenerative medicine. In female cells, X chromosome reactivation (XCR) is closely linked to the acquisition of naïve iPSCs. To visualize the status of X chromosome in living cells and further analyze XCR mechanism, we established a novel noninvasive detection system of XCR. Here we established female mouse embryonic stem cell (mESC) lines whose allele of both X chromosomes carry each of different fluorescent protein genes [Kusabira Orange (KO) and Enhanced green fluorescent protein (EGFP)]. These mESC clones, initially displaying yellow fluorescence owing to two active X chromosomes, generate chimeric cluster of cells showing either orange or green fluorescence (KO+ or EGFP+), indicating that X chromosome inactivation (XCI) occurs in these mESC clones during differentiation. When the single colored cells were reprogrammed, the iPS colonies displayed yellow (KO+/EGFP+) fluorescence, indicating XCR upon reprogramming. Our work reveals generated female KO+/EGFP+ mESC lines can be used for monitoring X chromosome status during differentiation and/or reprogramming. This novel system is also potential for tracking acquisition of pluripotency of iPSCs during reprogramming and screening for factors or culture conditions which promote this event.

The decellularized extracellular matrix (ECM) has been established as an ideal biomaterial in tissue engineering applications with potential clinical translation. In the present study, we aimed to generate a hydrogel from decellularized adipose tissue. Adipose tissue samples were collected from the liposuction procedure and subjected to undergo a series of delipidation and decellularization. Oil Red O staining illustrated the complete removal of lipid, whereas the absence of cellular nuclei in histology staining and low DNA residual content indicated an acellular matrix. Decellularized adipose tissue was further fabricated into a hydrogel. Histological evaluation and scanning electron images demonstrated a fibrous ultrastructure of the hydrogel. Furthermore, short-term in vivo observation detected the gelation after 2 h being implanted subcutaneously, which demonstrated dAT hydrogel was capable of self-assembling under physiological condition. Taken together, these results indicated the potential approach of hydrogel from decellularized adipose tissue in tissue engineering.

Grafting of conjugated linoleic acid (CLA) was an effective approach to improve surface hemocompatibility while preserving the initial mechanical properties and morphology. However, its effect on the crystallinity and thermal properties of synthetic polymeric materials were not investigated. Thus, this study aimed to evaluate and compare these properties of the non-grafted and the CLA-grafted polymeric membranes. The membranes were subjected to X-ray diffraction analysis, thermal gravimetric analysis, and differential scanning calorimetry. Moreover, the coagulation of blood plasma exposure to the membranes was evaluated to understand the antithrombotic mechanism of CLA on the membrane surface. The results showed that generally, the grafting caused no substantial impact on the properties being assessed, successfully preserved the initial state of the base materials. Moreover, the CLA exhibited slight obstruction on plasma coagulation cascade, specifically on the intrinsic pathway. Thus, CLA grafting could be a prospective approach to improve the hemocompatibility of a surface while preserving other properties.

Breast cancer (BC) is the leading cancer-causing death for women worldwide. Among BC-causing genes, ERCC5 plays an important role in DNA damage repair. The cancer risk can be modified by Single Nucleotide Polymorphisms (SNPs), and thus, SNPs may be considered as potential markers of carcinogenesis. Among SNPs of the ERCC5 gene, rs751402 (A/G) had been found related to BC risk in the Chinese and Thailand populations. This study aims to develop the genotyping condition for rs751402 and then to predict the relation to BC risk in a Vietnamese population. 50 BC blood samples were examined. High Resolution Melting (HRM) genotyping method was optimized for rs751402. The allelic and genotypic frequencies of rs751402 in this study were compared with its data of Kinh Vietnamese in 1000Genomes as controls to predict the association with BC risk. The HRM genotyping assay was constructed with high sensitivity, specificity, and stability. The results revealed the minor allele frequency was 31.91%, indicating rs751402 is high polymorphism. The predicted association with BC showed rs751402 A allele tends to confer protection against BC (OR = 0.75) but not statistically significant (P-value = 0.28). Even so, rs75140 is still considered as a potential marker for further association studies with BC risk in the Vietnamese population due to its high polymorphism. 1000Genomes has certain reference value; however, some concern remains. Consequently, a further genotyping assay is proposed to conduct in a proper control group and larger sample size to confirm the relationship between rs751402 and BC risk in Vietnamese women.

Alpha-fetoprotein (AFP) is a sera protein that involves in fetal development, produced by the fetal liver and yolk sac. Human AFP (hAFP) is not detected in adults but it is increased in cases of hepatocellular carcinoma (HCC), cirrhosis and other cancers like germ cell cancer, stomach and intestine cancer. hAFP has been used as an important marker for HCC serological diagnosis and it has recently become a target for HCC immunization studies. Umbilical cord blood has approximately 150–250 μg/ml hAFP but it is usually discarded in hospitals. In order to take advantage of human umbilical cord blood as hAFP nature material, this study have established a three-step chromatography process for hAFP purification including removal of albumin by Hitrap blue HP column, hAFP captured chromatography using rabbit anti-hAFP IgG column, and filtration chromatography through Sephacryl S100 HR column. By native-PAGE, western blotting and bradford assays, the hAFP purity was showed more than 95% and 80 μg of hAFP per mL of initial cord plasma was recovered. Our established hAFP purification process can be performed on a larger scale for later applications in the serodiagnosis of HCC and other hAFP related diseases.

Type 2 diabetes mellitus (T2DM) is increasing worldwide, characterized by insulin resistance and hyperglycemia. The results of previous studies have demonstrated that high D-glucose concentrations alter the characteristic and function of adipose tissue-derived mesenchymal stem cells (AT-MSCs). Besides, early growth response factor-1 (EGR-1) and insulin resistance mediators (PTEN and GGPS-1) were highly upregulated in diabetic AT-MSCs (dAT-MSCs) compared with non-diabetic AT-MSCs (nAT-MSCs). In this research, we examined the effect of high glucose concentrations on nAT-MSCs in comparison to dAT-MSCs on the expression of EGR-1, PTEN, and GGPS-1 involved in insulin resistance of human AT-MSCs. The expression of insulin resistance-related genes and EGR-1 protein were analyzed by reverse transcription-quantitative polymerase chain reaction (RT-qPCR) and Western blot, respectively. The results show that the high D-Glucose concentrations (25, 50, and 100 mM) enhanced the expression of EGR-1 and insulin resistance-related genes in nAT-MSCs compared with non-treated nAT-MSCs and dAT-MSCs. Notably, the increase of high D-Glucose concentration remarkably upregulated the expression of EGR-1, PTEN, and GGPS-1 in both nAT-MSCs and dAT-MSCs. The effect of high D-glucose concentration (100 mM) remarkably increased the expression of EGR-1, PTEN, and GGPS-1 in human AT-MSCs. The results of this study will expand our knowledge about the impact of high glucose concentration on insulin resistance in human AT-MSCs for the improvement in diabetic treatment.

Reactive oxygen species (ROS) that attack biomolecules leading to many health disorders. Chitooligosaccharides (COSs) is a natural antioxidant that has a positive effect against ROS. It may be applied in the functional food and pharmaceutical industries. In recent years, importance has been given to synthesize functionalized COSs by chemical modifications to improve the bioactivities of COSs while keeping intact the basic chemical properties. Therefore, this work aims to develop a novel COSs derivatives by conjugation of syringic acid onto plain COSs to improve the antioxidant activity of COSs. In this study, the syringic acid was grafted onto COSs by a free radical mediated grafting method with an ascorbic acid/hydrogen peroxide redox catalysis pair. Antioxidant effects of the novel COSs derivatives were determined by reducing power, free radical scavenging ability, and the inhibition of cellular macromolecules’ oxidation, such as lipid and DNA in RAW264.7 cells. The result showed that free radical scavenging effects and inhibitory effects of the novel derivatives of biomacromolecules oxidation were significative improved more than free COSs. These results suggest that the novel COSs derivatives can be potentially used as a free radical scavenger to protect biomacromolecules in cellular systems. Besides, the research is a foundation for further study of other activities such as the anti-inflammatory properties of these derivatives.

Plant disease is known as the largest intimidation, which directly affects on production and causes economic loss. Traditionally, human experience is used in defining the class of plant disease, but this often leads to wrong recognition. Thanks to the rapid development of modern technology, many machine-based methods with high efficiency and accuracy can be easily developed. Recently, computer vision has been widely used in various applications which have become intelligent supporters of human. This paper proposes an image-based method using Gray Level Co-occurrence Matrix (GLCM) and Local Binary Pattern (LBP) feature extraction for plant disease recognition. Contrast enhancement is used to increase the visual quality in the pre-processing stage. Finally, the classification is done by Support Vector Machine (SVM), and different schemes are used to justify the performance. Overall, the obtained result demonstrates that the proposed approach can identify six classes of plant-based on leaves.

Bacterial resistance is getting more and more serious, and Vietnam is one of the high bacterial resistance prevalent countries in the world. Hence, the development of new antimicrobial agents, domestically, is urgently needed. During the course of our screening program, the ethyl acetate extract of a marine-derived fungus strain (Penicillium chrysogenum M612), isolated from sediment collected in Bai Tu Long sea, showed good inhibition activities against tested clinical important microbial pathogens. Subsequent analysis of the extracts prepared from the strain M612’s culture broth (50L) led to the isolation of seven cyclodipeptides. Structure of isolated compounds was determined, based on MS; NMR spectroscopic data analysis and compared with literature, as cyclo-(L-Pro-L-Leu) (1), cyclo-(L-Pro-L-Val) (2), cyclo-(L-Ala-L-Pro) (3), cyclo-(L-Pro-L-ILe) (4), cyclo-(L-Pro-L-Phe) (5), cyclo-(D-Pro-D-Phe) (6) and cyclo-(L-Pro-L-Tyr) (7). All the compounds were previously reported to have antimicrobial activities. The obtained results suggested that strain M612 can be further studied to develop an antimicrobial agent.

The identification of low-abundance serum proteins in human sera can be severely affected by high-abundance proteins (HAPs), so many protein-depletion kits have been developed for enhancing the efficiency of identifying them. The ProteoSpin™ Abundant Serum Protein Depletion Kit is a fast, simple, and budget-friendly kit for the depletion of HAPs including albumin, alpha-antitrypsin, transferrin, and haptoglobin from serum and plasma samples but its depletion efficiency has not been investigated. Our study aimed to evaluate the efficiency of this kit in processing a pooled serum of hepatocellular carcinoma patients. We conducted a thorough evaluation following criteria: (i) protein recovery rate after depletion, (ii) efficacy of depletion, (iii) specificity of depletion using ProteoSpin™ Kit. Quantitative determination of total proteins, depleted proteins, and HAPs was performed. SDS-PAGE was used to analyze the serum samples before and after depletion while Shotgun LC–MS/MS was conducted to identify proteins from the depleted serum. The results then were compared with previous research to evaluate the efficiency of depletion. Our results indicated that the ProteoSpin™ Kit was efficient to deplete HAPs by revealing a protein recovery rate of 5.73% and the identification of 251 serum proteins. It reduced albumin, IgG, transferrin, fibrinogen, haptoglobin, and transthyretin by approximately 60%. The depletion efficacy of ProteoSpin™ Kit was comparable or even superior to some other commercial kits. It has significantly eliminated HAPs and enhanced the number of identified proteins in a serum sample. Our study can help to facilitate the choice of optimal products for HAP depletion in studying serum proteins.

Pharmacogenetics has become one of the leading areas of personalized medicine to increase both the prescribed drug’s efficacy and safety. To implement pharmacogenetics into routine clinical practice, genotyping assay needs provide a rapid, simple, reliable and cost-saving method. A number of the kits commercially available contain limited coverage, omitting significant variations relevant for Asian populations. In response to this problem, we aimed to develop in-house SNaPshot multiplex assay for genotyping multiple SNP loci in the Vietnamese population and translate the pharmacogenetic results into clinical action. Polymerase chain reaction (PCR) with the extracted DNAs from 10 dried blood spot (DBS) samples across were analyzed the major polymorphisms of including both pharmacokinetic and pharmacodynamic genomic panels such as CYP2D6, CYP2C9, VKORC1, CYP4F2, CYP2C19, HLA-B, HLA-A, HLA-DRB1, HLA-DOA1, TPMT, G6PD, NUDT15, DPYD, UGT1A1, C11orf65, SLCO1B1, ABCG2, ACE, COQ2, KCNJ11, NEDD4L, SLC14A2, ADRA1A, AGTR1, GNB3, MMP3, PTGS2. The variants were selected using PharmGKB. Gen-Drug interaction is leveled on drug labels, clinical guidelines, and literature. We found that 100% of subjects carry one or more variants. The major alleles detected include HLA-B*1502, HLA*5701, HLA*5801, HLA-A*3303, CYP2C19*1, CYP2C9*10 and VKORC1 G/A. The genotypes were translated to inform the prescribing decision by creating the patient-centred results report. In this study, we developed not only an appropriate panel relevant to the prescription patterns and genotype prevalence but also an easy-to-understand report of the patient’s drug—gene interactions information to recommend drug dosing.

Breast cancer (BC) is the most dangerous cancer in women worldwide. Among well—known BC penetrant genes, LincRNA plays an important role in the cellular processes. Single Nucleotide Polymorphisms (SNPs) may be regarded as potential markers of carcinogenesis because its appearance can change gene’s function. Among SNPs of LincRNA, rs12325489 was demonstrated to have an association with BC in Chinese. This study aims to develop the genotyping method for rs12325489 in 50 BC cases and predict whether it relates to BC risk in Vietnamese. This genotyping condition was then evaluated based on its sensitivity, specificity, and stability. The predicted association between rs12325489 and BC risk was conducted, using the allelic and genotypic frequencies of this SNP in Kinh-Vietnamese from 1000Genomes as controls. The results showed that the genotyping assay was successfully developed with high sensitivity, specificity, and stability. The minor allele of rs12325489 is 41.11% indicating that this SNP is high polymorphism in Vietnamese. The prediction of this SNP was increased with the BC risk by 1.43 times (OR (Odds Ratio) = 1.43), not statistically significant (P = 0.17). Because rs12325489 has high polymorphism in both patient and control group, it is considered as a potential marker for further association studies between this SNP and breast cancer in Vietnamese. Although the online database has certain reference values in this study, there are remaining concerns. Thus, further studies need to be conducted in proper healthy samples and a larger sample size to confirm the association of this SNP with BC risk in Vietnamese.

Persistent hyperglycemia causes many microvascular and macrovascular complications in type 2 diabetics. Chronic wounds are one of the most common complications. Adipose tissue-derived mesenchymal stem cells (AT-MSCs) shows great potential for chronic wound healing because of their ability to secrete many factors to stimulate migration, growth, angiogenic. In previous research, we were determined that diabetic AT-MSCs (dAT-MSCs) impaired the ability of wound healing compared with non-diabetic AT-MSCs (nAT-MSCs). In this study, we aim to examine the effect of high D-glucose concentration on the mobility of nAT-MSCs and wound healing in vitro. The expression of migratory genes was determined by reverse transcription quantitative polymerase chain reaction (RT-qPCR). In vitro scratch assay was used to examine the healing ability of nAT-MSCs under the influence of high D-glucose concentration. The results show that high D-glucose treated-nAT-MSCs were reduced the expression of migration factors (SDF-1 and CXCR-4), which suggested the high D-glucose treated-nAT-MSCs may decrease their migration mobility compared with those of non-treated nAT-MSCs. Moreover, the wound healing ability in vitro was impaired high D-glucose treated-nAT-MSCs compared with those of non-treated nAT-MSCs. Interestingly, the migration mobility of nAT-MSCs under the effect of high D-glucose condition was similar to those of dAT-MSCs. Our study provides further insight into the impact of high D-glucose levels on reducing wound healing ability of nAT-MSCs in supporting of the improving AT-MSC function in the treatment of diabetic complications.

Circulating cell-free RNA (cf-RNA) holds great potential as effective diagnostic and prognostic biomarkers, especially for neurodegenerative disorders such as Alzheimer’s disease (AD). However, low yield, integrity, and contaminants can alter the final RNA quality and concentration, which hinders the application of cf-RNA. This study aims to: (1) evaluate different cf-RNA extraction methods, (2) optimize the protocols to achieve the optimal cf-RNA quality and quantity, and (3) evaluate hemolysis, which is the main cause of cellular RNA contamination to the final product. Two different types of blood-containing tubes (Norgen and Streck) were compared to evaluate their effects on hemolysis and RNA products. cf-RNA samples were extracted from plasma using Trizol and Zymo cf-RNA extraction kits. We also tested whether the addition of glycogen (20 mg/ml) or combination with RNeasy mini kit to the Trizol protocol will increase the yield of cf-RNA. cf-RNA was then converted to cDNA and examined with PCR and qPCR. The original Trizol protocol resulted in almost no detectable cf-RNA. Adding glycogen significantly increased the yield of cf-RNA to 4–15 ug/ml. Zymo kit’s RNA yield was about 5–18 ug/ml. No trace of genomic DNA contamination was identified. Minimal hemolysis was still detected by spectrometer measurement and visual inspection; contamination of cellular RNA has not been determined. Interestingly, despite the high cf-RNA yield, we were not able to consistently detect the housekeeping gene beta-actin (ACTB) or Alzheimer-related transcripts using Trizol and Trizol-glycogen cDNA. Reliable detection of housekeeping gene ACTB and inconsistent detection of Alzheimer’s related transcripts, namely CNTF and MAG were achieved when using cDNA samples from Zymo-kit. Concentration of cDNA is highly correlated with the ΔCt values of real-time PCR reactions for ACTB primers, suggesting the high integrity of cDNA products from Zymo-kit. Our preliminary data show that the Zymo outperformed the Trizol original and modified methods in both yield and integrity measures.

Alpinia chinensis Rosc. was widely used as spices and medicines. Leaves, stems and rhizomes of the plant contain essential oils, provide a useful habitat for endophytic fungi groups differently. This study has isolated endogenous A. terreus—RTN3 strain from young stems of Alpinia chinensis Rosc.-Zingiberaceae family. Cultivating and extracting compounds containing metabolites that are resistant to Staphylococcus aureus and Methicillin-resistant Staphylococcus aureus (MRSA). Determining the number of antibacterial compounds in the crude extract by thin-layer chromatography and vacuum liquid chromatography. The research has isolated pure MM1 compound with high antioxidant activity and spectral resolution to find the structure compound MM1 (methyl 2-acetyl-5-methoxy-4-oxo-4H-chromen-7-carboxylate). This is a new compound that has not been announced in any works before. MM1 compound has a high antioxidant activity, the ability to catch α,α-diphenyl-β-picrylhydrazyl (DPPH) free radicals increases linearly by concentration, at concentration 400 ppm of MM1 is capable of capturing over 80% of DPPH free radicals. The results showed that MM1 compound's ability to inhibit cancer cell lines increased linearly, at concentrations of 100 µg/mL of MM1 compound, which inhibited nearly 80% of cancer cell lines and was highest in liver cancer cell line HepG2 (inhibited 86.82%). The MM1 compound has also been shown to inhibit cancer cells through the ability to induce apoptosis on the NCI-H460 lung cancer cell line under the investigated conditions.

The effectiveness of the treatment of endodontic infections with antiseptics is highly dependent on the occurrence of bacterial etiologies associated with endodontic pathology. However, the distribution of bacterial etiologies associated with endodontic pathology varies across regions of the world. This study aimed to determine the bacteria profile in root canals of teeth with chronic periapical lesions in order to help physicians select suitable irrigating agents and intra-canal medicament for endodontic treatment. Forty-seven teeth with chronic periapical lesions were collected from patients for this study. Specimens used for microbiological culture were collected using a paper cone. Bacteria growing on blood and chocolate medium were then identified by 16S rRNA gene sequencing. Forty-five different cultivable bacteria were successfully cultured and identified by 16S rRNA gene sequencing in all samples, in which each canal found one to nine bacteria species. Facultative anaerobic bacteria were the highest proportion (79.31%) including Streptococcus, Neisseria, Haemophilus, Actinomyces (proportion: 78.7%, 27.66%; 17.02% and 17.02% respectively. Followed by obligate anaerobic bacteria distributed for 11.72% with Prevotella, Veillonella, Campylobacter, Oribacterium, Fusobacterium, Dialister. The number of aerobic bacteria was only 8.97%, of which mainly Bacillus species. Bacillus, Haemophilus, Actinomyces, Streptococcus were presented in most of the teeth with chronic apical periodontitis showing pain and swelling. This is the first data on the microbiology species in root canals of teeth with chronic periapical lesions of Vietnamese people. Our data identified facultative anaerobic as the most common species in root canals of teeth with chronic periapical lesions, and four main microorganisms notably occurred in case with pain and swelling. This data has important implications for the effective treatment of root canal infections with antiseptics.

Cell-free RNA (cf-RNA) is released from cells and circulated in the body via the circulatory and endocrine systems. Subsequently, cf-RNA can be extracted from different biofluids by various extraction methods. This review aims to: (1) clarify the clinical role of cf-RNA and methods of extraction, (2) introduce the evaluation parameters and methods, (3) summarize the evaluation of several common extraction methods and propose optimizing solutions for them. Eighty articles on the application of cf-RNA in diagnosing diseases and cf-RNA extraction published in journals with good impact factor (higher than 2) were then summarized and sorted into groups based on their targeted disease: (1) Cancers and (2) Neurodegenerative diseases since the cf-RNA is being studied mainly in these two fields. The general design of these studies is comparing cf-RNA to the current means of diagnosis, which are considered as standards such as endoscopy, biopsy, CSF analysis. By quantifying cf-RNA using qRT-PCR, previous studies were able to detect several cancers and neurodegenerative diseases. The key advantage of using the cf-RNA as a biomarker is reducing the risks and invasiveness without losing sensitivity since it can be extracted in the peripheral area. Furthermore, cf-RNA expression levels vary according to disease stages, suggesting its potential as prognostic markers. The main challenge in using cf-RNA is achieving the optimal yield, purity, integrity with minimal contamination. The current methods like Trizol LS, miR-Neasy, mirVANA have yielded unsatisfying results; therefore, they require modifications to optimize their results. miRCURY kit has the highest RNA yield but has been discontinued. In conclusion, cf-RNA holds excellent promises as a promising biomarker in the future. However, due to certain challenges, the use of cf-RNA is currently limited to clinical studies due to the instability in yield and integrity, requiring supporting studies and extraction methods evaluation.

Phycocyanin is a powerful natural antioxidant from Arthrospira platensis. In this study, crude phycocyanin (crPC) was extracted, and its ability to protect fibroblast from hydroxyl peroxide (H2O2) in vitro was determined. crPC was extracted from Spirulina by a step-by-step method: 1/cell breaking by a repeated freezing/thawing method; 2/contaminant removal by 8% active charcoal and ammonium sulfate 15%; 3/phycocyanin obtaining by ammonium sulfate 50% and dialysis. Abilities of crPC 6, 12.5, 25, 50 and 75 μg/mL in inducing cell proliferation and migration were tested on fibroblasts. The protective ability of crPC against oxidative stress of H2O2 was determined on fibroblasts as the following method: fibroblasts were pretreated with crPC 25 μg/mL for 24 h before exposing to H2O2 175 μM for 90 min (experimental group). Then cell viability, cell phase and senescence β-galactosidase expression were evaluated. The results showed that: PI of crPC was 2.79 ± 0.03 and concentration was 1.13 ± 0.05 (n = 5). crPC below 150 μg/ml was non-toxic to fibroblasts and crPC above 25 μg/mL stimulated cell proliferation (doubling time was 44.5 ± 1.2 h, n = 3) and migration (24 h, n = 3). Compared to control group (cells were treated only with H2O2 175 μM), cell viability in the experimental group was higher (79.3 ± 5.4% vs. 53.4 ± 2.3%, n = 3) and cell ratio in G0/G1 and senescence β-galactosidase expression was lower (78.7 ± 4.1% vs. 85.8 ± 6.1%) (22.8 ± 4.6% vs. 68.4 ± 6.8%). Conclusion: crPC was extracted successfully from Arthospira platensis, and crPC 25 μg/mL was able to protect fibroblast against oxidative stress of H2O2.

This study isolated antibacterial probiotic strains from sour shrimp, a Vietnamese traditional fermented food, and optimized culturing conditions for the chosen strain. Strain V101 was chosen for optimization experiments for its high antagonistic activity and production of strong antibacterial compounds against indicator harmful bacteria – Escherichia coli, and Staphylococcus aureus. Molecular identification of 16S rRNA sequencing showed that V101 strain was Lactobacillus paracasei. Optimization of culturing conditions found that this strain produces the highest biomass and acid accumulation on modified MRS at pH 5.5; temperature 37 °C in 60 h. Under optimum condition, biomass and acid production increased 76.61% and 10.69% respectively, and antibacterial activities against E. coli improved up to 20%. Pilot fermentation of L. paracasei V101 on production Vietnamese pickles, sour shrimp showed that the fermentation process was quicker, tastier, and fermented products could be preserved longer. These findings will be a potential prerequisite for further study on L. paracasei V101 as a strain not only good for food fermentation and preserving but also a helpful probiotic bacteria bring benefits to human health.

Nowadays, the modern living lifestyle made the number of stressful people increasing day by day. This strategy brought up a problem of overusing stress managing pills, whose side effects are weight gains, changes of appetite and sleep habits, frustration, etc. As a result, there is a need for natural antidepressant remedies for the community to reduce such stressful situations. Tea (Camellia sinensis) becomes one of the most popular drinks worldwide because of its effective medicinal properties such as antioxidant, antitumor, antidepression, cancer and cardiovascular diseases prevention, etc. However, fresh tea might be quite bitter due to high tannin content, hard to preserve and insomnia causing. Fortunately, fermented tea could be another better choice as it reduced tannin content, increased fragrant and eye-catching color, together with the richness of γ-aminobutyric acid (GABA), a neuro-benefit compound, could overcome those downsides. In this study, tea was screened for enzyme inactivation conditions, then fermented for good color ratios, lower tannin content, and higher GABA content. Oolong tea inoculated with 8% L. brevis and fermented in 4 days yielded better GABA content than fermentation of Oolong tea with and without Viscozyme L. Under these conditions, fermented tea had a good sensory assessment with color, flavor almost like Pu-erh tea. Other attributions of fermented tea would be TF/TR at 1/9.7, TC at 1.53%, tannin content at 13.72%, and GABA content at 302.38 mg/kg, almost 4 times higher than GABA content in raw material. This finding is a requisite for further production of GABA rich tea to create widely consuming and naturally stress suppressing drinks.

The major platelet integrin αIIbβ3 is polymorphic at residue 33, and the Pro33 isoform exhibits prothrombotic character. We explored via which pathways the Leu33/Pro33 polymorphism modulates integrin αIIbβ3 mediated outside-in signaling. We have investigated Src Y418 phosphorylation in human platelets adherent on fibrinogen in the presence or absence of divalent cation Mn2+ and of the soluble form of the CD40 ligand (sCD40L). Whereas HPA-1a/1a platelets did not show Src activation on 10 µg/ml immobilized fibrinogen even after 40 min, we observed a significant Src phosphorylation increase in the HPA-1b/1b isoform. Mn2+ alone also increased the Src activity in the platelets and addition of Mn2+ to platelets adherent on fibrinogen resulted in a synergism of Src Y418 phosphorylation in both isoforms, whereas after 40 min adhesion HPA-1b/1b platelets demonstrated a substantially (sixfold) higher Src kinase activation than HPA-1a/1a. Our observation that in the presence of Mn2+ the Src pY418 phosphorylation increases in both isoforms was independent of the fibrinogen concentration suggesting a dominant role of the Mn2+. Whereas sCD40L, another αIIbβ3 ligand, did not enhance the Src activity in HPA-1a/1a platelets adherent on fibrinogen, we observed a threefold Src kinase activation in HPA-1b/1b platelets in the presence of sCD40L.

Medical imaging is useful in the diagnosis and treatment of diseases. A wide range of pathologies have been discovered by identifying abnormalities of the object’s boundary in the medical image. Almost tokens of illness are shown in salient regions of objects, such as the intensity of color, connection together, etc. Therefore, the contour is a pressing-issue in the cutting-edge diagnose. This paper proposed a method for detecting contour of the object in medical images based on the saliency map combined with the active contour model. The proposed method detected salient regions of the medical image and activated the boundary of objects by energy reducing. The proposed method includes four steps: firstly, the pre-processing is applied for input images by the median filter. Secondly, the threshold of intensity is divided by super-pixels. Thirdly, the outstanding map is made by clustering the above super-pixels. Finally, the active contour model is built in salient regions of concerned about. We test results from DICOM images dataset, which includes high-quality and low-quality medical images. The accuracy of the proposed method is 97.52%, more than the results of the other methods, 5.0%.

In the development of image processing and computer vision field, visual tracking is considered as an attractive research field in regard to its practical characteristic in security surveillance, computer–human based interaction, motion and activity recognition in health care or control systems, etc. In a typical visual tracking model, the most difficult task is to handle the changes in the target objects’ appearances and their surrounding backgrounds. As a matter of fact, if the changes are severe, information extracted to detect the object in interest will be limited. In this paper, we enhance the robustness of a tracking model to adapt to these changes and increase the tracking accuracy level by exploiting local context information. In particular, the study implements an efficient tracking model that utilizes the spatio-temporal context information. The context model relation of the tracking target with its surrounding background is generated by computing a devolution task due to its spatial correlation. Then, the analyzed relationship is exploited to update a spatio-temporal context in subsequent frames. The tracking process is computed using a confidence map by integrating the information within the spatio-temporal context. The model also implements the exhaustive scale estimation method to calculate the target’s scale characteristic changes while maintaining computational efficiency. Finally, the TB-100 dataset is applied to evaluate the performance of the model.

Lung disease is a kind of infection that cannot be observed by human eyes, but it can be detected by X-ray images. Nevertheless, diagnostic accuracy from the look on these X-ray images is always a challenging task because it frequently relies on the experiences of the doctors. Hence, many computer vision techniques are developed to support medical staffs to perform lung disease detection. So as to encourage different detectors to identify different kinds of lung disease, this paper proposes a novel post-processing technique, a Weighted Box Fusion (WBF) ensembling algorithm, which may improve the efficiency in lung disease detection. This algorithm is applied to an available benchmarking dataset of X-ray chest in literature for justifying its performance.

Epilepsy is a group of neurological disorders characterized by recurrent epileptic seizures. According to the World Health Organization, there are about 50 million people who have epilepsy. Electroencephalography (EEG) is used as a powerful tool for doctors in diagnosis. By visualizing the EEG recordings, experts can initiate antiepileptic drug therapy and reduce the risk of future seizure. However, this current method is time-consuming and inflexible. With the development of deep learning, the problems can be solved. In this study, a 25-channel EEG data recorded at Neurology Department of 115 Hospital was converted into images after filtering, and a one-dimensional convolutional neural network (1-D CNN) model was applied to classify seizure states as seizure or non-seizure accurately. The accuracy of the model is about 90%. With the development of deep learning, it is more convenient to distinguish between different data of seizure and non-seizure without difficulties and consumption of time.

Brain-computer interface (BCI) provides opportunities for patients with severe motor impairment to regain their motor controls by decoding and converting Electroencephalogram (EEG) signals into the motor control signal. Existing processing schemes, including artifact removal and band-pass filtering, usually cause leakage of EOG artifacts. Hence, the preprocessing order in this paper was optimized for artifact removal in event-related desynchronization. To address this challenge, we implemented an algorithm to classify four different motor imagery tasks, including the left hand, right hand, both feet, and tongue movements. Here, we use Graz dataset A published in the BCI competition IV in 2008. Band-pass filter (7–30 Hz) with 5th order Butterworth IIR combined with linear regression was applied to remove the artifact of the signal. Mutual Information Best Individual Features (MIBIF) and Linear Discriminant Analysis (LDA) algorithms were used for selecting features and classifying the classes. The mean training kappa of our classifier is 0.57, and the mean evaluated kappa is 0.41. Besides, the application of the Common Spatial Pattern enhanced the kappa score (from 0.33 to 0.41). Those results are comparable to those from the BCI competition (range from 0.29 to 0.57). Hence, our approach could be the foundation for further development of motor imagery based BCI research. For future works, we propose to create an algorithm for the automatic procedure by automatically choosing proper frequency bands for band power features.

Gliomas is the most widely recognized essential brain cancer with particular degrees of aggressive, variable prediction and different heterogeneous histological sub-regions including: edema, necrotic center, enhancing and non-enhancing tumour core. Exact tumour division of sub-areas plays a crucial role for diagnosis, treatment planning and risk factor identification. This study was conducted by using the MultiResUnet architecture for computerized segmentation of gliomas in multimodal MRI scans (FLAIR, T1CE, T2). Previously, the images were enhanced through various preprocessing stages, then they were fed by the MultiResUnet network. From the 3D database gave by BraTS 2019, we extracted 2176 images to train and 1056 images to assess our network. The segmentation model performance was qualitatively evaluated with the accuracy and under the Dice score metrics. Our study suggested a model which Dice score accomplished 0.78, 0.82 and 0.88 on the training set and 0.63, 0.73 and 0.86 on the validation set for the enhancing tumour, the tumour core, and the entire tumour, separately. In general, the system sectioned the entire tumour more precisely than it accomplishes for the core of tumour or enhancing tumour. They are significantly harder to segment because of the closeness between all areas. We plan to further our network to improve the testing phase results and use sub-regions tumour on Radiomic Features extraction for tumour investigation and survival expectation.

With many tablets produced everyday in manufacturing plants, the pharmaceutical industry needs automatic, highly accurate methods for inspection of tablet quality. Detecting defective tablets is of importance to reduce unqualified products to consumers. In this paper, we propose a deep learning method combining image processing and deep convolutional neural networks (DCNN) for detection of defective tablets using images captured by a multiple-camera inspection system. A dataset of 6000 images of tablets labelled either GOOD or NOT-GOOD were collected at a pharmaceutical factory using commercial camera inspection systems. After collecting and labelling, the images were preprocessed to normalize intensity values. The entire dataset was split into a training set (50%, 3000 images), a validation set (16.6%, 1000 images) and a testing set (33.3%, 2000 images). We trained DCNN ResNets (ResNet50, ResNet101) and DenseNets (DenseNet169, DenseNet201) models on the training set and validated them on the validation set. We applied transfer learning techniques by using pre-trained models that had been trained on the ImageNet dataset in combination with data augmentation and training strategies such as learning rate rescheduling overtime. We compared our deep learning methods with various machine-learning ones such as Support Vector Machine (SVM), K-Nearest-Neighbors (KNN), AdaBoost that used intensity histograms as features. Tuning hyperparameters were performed to seek the best hyper-parameters and algorithms. We achieved best performances using the deep learning models as the ResNet50, and DenseNet169 obtained 96.60% ± 4.9% and 94.13% ± 4.2% accuracies (ACC), respectively. In contrast, SVM achieved 87.75% ACC, KNN achieved 76.09% ± 7.7% ACC while AdaBoost achieved 81.25% ACC, respectively.

Medical images have made an important contribution to improving the accuracy and effectiveness of disease diagnosis, such as diseases related to lung, heart, liver, kidney, etc. Pneumonia has increased rapidly in the world in recent years. Chest X-ray image analysis is a common method for detecting lung diseases. An advanced artificial intelligence system will help doctors have accurate conclusions, timely treatment for patients and reducing mortality. Using machine learning on X-ray images is of great interest, but research results are still limited in accuracy. This paper proposed an adaptive technique for lung diseases image classification based on the deep learning method. We improved the convolutional neural network for lung diseases image classification, created a training model with a suitable number of hidden network layers and optimal algorithms to detect pneumonia images. As a result, the rate of correct detection of pneumonia image was 98.72%. We used chest X-ray images dataset that published by Kaggle, including 5863 chest X-ray images. The results of the proposed method are better than the other methods.

Alzheimer’s Disease (AD) is difficult to diagnose even with recent advanced diagnostic methods. Other mental disorders, such as frontotemporal lobe dementia or vascular dementia, could be misdiagnosed as AD. Various deep learning models for early detection of AD using MRI data have demonstrated promising results. However, the results of these methods are difficult to interpret as they did not identify specific structural changes that are related to the disease. Additionally, they require a large amount of data and computational resources. In this study, we proposed a machine learning framework for diagnosis of AD. Our framework employed FreeSurfer library to extract insightful features such as volumetric measures and voxel- or vertex-wise atrophy from structural MRI brain scans collected from Alzheimer’s Disease Neuroimaging Initiative. These extracted features were then fed into Extreme Gradient Boosting (XGBoost) which is an ensemble learning algorithm with a decision tree as a base learner to distinguish AD patients from cognitively normal subjects (CN). XGBoost also provides the concept of variable importance which was evaluated by various criteria such as information gain or feature frequency to give an insight on which structural features have critical impacts on the final diagnosis. Our model was trained on 144 features extracted from 924 sMRI images (462 images of AD and 462 images of CN) and achieved 91% Area Under the Curve (AUC) on average using 5-fold cross-validation. Based on feature ranking, we observed that the 3rd ventricle, intracranial and supratentorial volume were some of the most crucial brain structural features affected in AD. This information could assist doctors and experts in AD diagnosis. We propose a framework for AD diagnosis using XGBoost and brain structural atrophy. The feature extraction phase which consumed significant computational resources is currently the bottleneck of our diagnosis pipeline. In future, we plan to improve the feature extraction efficiency to reduce computational cost, yet maintaining diagnosis accuracy.

Changes in white blood cell, a.k.a. leukocyte, subtypes count are often indicator of medical conditions. Counting each of white blood cell subtypes is thus essential in blood tests. To do this, it is necessary to classify white blood cell images into different subtypes, namely, Eosinophils, Lymphocytes, Monocytes, Neutrophilic, etc. Traditional image processing techniques have been utilized to classify white blood cell images. However, in general, accuracy and stability of these techniques are sensitive to variations in image size, staining technique, and image quality. Recently, application of deep learning networks in white blood cell classification has drawn a lot of interest. In this work, we present two deep learning networks based on VGG16 and SqueezeNet convolutional neural networks (CNNs) that can automatically classify white blood cell images into different subtypes. The two networks were trained on a public dataset of leukocytes named Blood Cell Count and Detection (BCCD) and a self-built dataset named the Extended BCCD dataset. Although having relatively light-size, 16,005,884 and 35,858 parameters for VGG16 and SqueezeNet respectively, both models achieved ~ 97% accuracy in the BCCD dataset. In the extended BCCD dataset, the VGG16-based model achieved 97% accuracy, and the SqueezeNet-based model achieved 95% accuracy. These two models are thus potential candidates for deployment on computers and IoT devices with limited computational power for white blood cell classification task.

Accurate segmentation of Foveal Avascular Zone (FAZ) in Optical Coherence Tomography Angiography (OCTA) images is important for OCTA images analysis. In this work, we developed an algorithm for automatic segmentation of FAZ in OCTA images using a Hessian-based filter and an U-Net deep learning network. A total of 260 OCTA images were used to train and test the algorithm. The images were first enhanced by a Hessian-based filter and then fed into a U-Net deep learning network. Eighty percent of the dataset was used for training and twenty percent was used for testing. Our method achieved 87.8% Jaccard Index (Intersection over Union metric) with 6% false-negative error and 5% false-positive error. The results showed that U-Net deep learning network could achieve good accuracy in automatically segmenting FAZ in OCTA images despite a small training set. The study also showed that image preprocessing techniques such as Hessian-based filtering helped to improve accuracy of U-Net deep learning network.

Ascorbic acid (AA) is well known as a good radical scavenger and antioxidant. Here, the protection effects of AA against free radicals (mainly hydroxyl radicals) caused by low and high linear energy transfer radiation were examined. In this study, cobalt-60 gamma rays and helium ion beams were used as the sources of ionizing radiation. DNA strand breaks of PUC118 plasmid in the presence and absence of AA were monitored using agarose gel electrophoresis. Moreover, the survival rates of Saccharomyces cerevisiae yeast cells irradiated with different AA concentrations in growing medium were analysed using the linear quadratic survival model. Based on the results of DNA strand break experiments, the yield of strand breaks increased with an increase in absorbed dose. In the presence of AA, the yield of strand breaks decreased with an increase in AA concentration. In other words, the greater the additive concentration, the more effective the radiation-protective agent. On the other hand, in the survival rate experiments, the dependence on additive concentration was not similar to that of the DNA experiments. We consider that the main reason for our observations is the difference in additive concentration between the outside and inside of the cell membrane of yeast cells. These results suggest that AA plays an effective role as a radiation-protective agent for DNA and living cells against free radicals formed by radiation.

Airborne-mediated diseases like chickenpox, tuberculosis, influenza, influenza, measles, and rhinovirus represent major public health challenges. In the process of examining the causes related to the transmission of infection, studies on the airborne pathogen and the way it spread were carried out mainly in the medical field. In low-middle income countries, studies on the diffusion of air pollutants and virus diffusion in the hospital were limited. Short-wavelength ultraviolet C (UVC) light has an airborne antimicrobial great potential for preventing airborne transmission by inactivating the airborne pathogens. However, its widespread use in public areas is limited because conventional UVC light sources may risk skin cancers and eye damages. To overcome these problems, we propose a novel UVC air disinfection device and utilize the computational fluid dynamics (CFD) method to simulate the dispersion of airborne droplets in a double-bed hospital room. This paper reports the airborne pathogens spreading patterns according to the location of the proposed device. The transient simulation results concerning the airborne pathogen tracing combined with their concentration and distance provided evidence of the contaminant zones that should be checked and cleaned. The effectiveness of the proposed device was confirmed through the airborne pathogen tracing simulation and device's location analyses in a double-bed hospital room.

Mindfulness-Based Stress Reduction (MBSR) is a non-invasive psychological therapy based on mindfulness developed by Dr. Jon Kabat-Zinn in 1979. The potential of MBSR includes improving mental health, enhancing working performance, and reducing mental stress. This literature review aims to: evaluate the effect of MBSR on stress reduction in different subject groups and examine the outcome of MBSR on various physiological and structural measurements. The literature review is based on 40 articles then narrowed down to 25 articles published from 2010 to 2019. The keywords to search for these articles were: MBSR, Electroencephalogram signal, stress, functional Magnetic Resonance Imaging, cortisol, functional Near-Infrared Spectroscopy. Subjects participated in the MBSR course. These studied populations, selected based on standard criteria DSM-IV, included one control group and one intervention group. Measurement stage comprises pre- and post-intervention by using three types of questionnaires: Mental Health Scale (MHS) and Mindfulness Scale and other scales. Besides, several studies combined common physiological and structural assessments. The reviewed studies show that MBSR is effective in several subject groups, including Social Anxiety Disorder patients, employees, and students. Other groups with more severe psychological symptoms have not benefited significantly. The questionnaire score reflects a significant improvement, whereas biological measurements as heart rate, brain imaging, or cortisol level do not show consistent change. The limitation of these studies is that there is a lack of a control group. In conclusion, MBSR has effects on mental health and mindfulness for a wide range of subjects. It is suggested that people who have mild psychological disorders should practice MBSR frequently to reduce symptoms. For future studies, the control group and repeated measure designs should be implemented for better results.

Patient Health Questionnaire (PHQ–9) is a global tool that can be effective for depression screening, especially in the context of high prevalence of the disorder in medical students. The aims of this study are: (1) Translating and cultural adapting the Vietnamese version of PHQ-9; (2) Establishing reliability and (3) Identifying validity of PHQ-9 Vietnamese version within Vietnamese medical students. The process of establishing the PHQ-9 Vietnamese version strictly followed the international guideline for translation and cultural adaptation of psychometric instruments recommended by WHO. Four hundred two medical freshmen were involved in PHQ-9 study for internal reliability. After 10 days, 76 students from the former list were randomly selected for a structured interview with psychiatrists and underwent repeated PHQ-9 test. Records of the latter time were used to calculate test–retest reliability and criteria validity. ROC curve analysis was performed to evaluate diagnostic efficiency. High internal and test–retest consistency for PHQ-9 (Cronbach’s alpha as 0.81 and Spearman correlation coefficient as 0.83) were identified. The sensitivity and specificity at the cut-off 12 were 71% and 93%, and 7 was 82% and 71%, respectively. The reliability and validity of PHQ-9 Vietnamese version are advisable for applying in mental health management for medical freshmen. The cut-off score is 12 for epidemiological purposes and is 7 for screening purposes. Further researches should assess PHQ-9 Vietnamese version’s psychometric features towards other medical college groups or other forms of handling tests, listing as mobile apps or web-based systems.

Rapid maxillary skeletal expansion (RME) has been proposed as a treatment for Obstructive Sleep Apnea (OSA), and numerous studies exist on the effectiveness. However, conclusive results have not been obtained. The aim of this narrative review was to identify suitable studies to assess the effectiveness of maxillary skeletal expansion on airway and respiratory function. Studies were identified with the following search strategy: [Palatial expansion technique] AND [Respiratory function test OR pharyngeal volume] through four databases PubMed, Scopus, Cochrane and Google scholar. Inclusion criteria for studies included human in vivo studies and quantitative analysis. In the selected 9 studies, 6 studies primarily assessed function change with RME, and 3 studies primarily assessed dimensional change in the airway, most commonly the transverse dimension of the nasal valve. Not all studies were able to be accessed full-text, and only 4 studies were able to be included in the analysis. The significant increase was noted in the transverse dimension and nasal volume, as well as a decrease in inspiration and expiration resistance during breathing. We could conclude based on the available evidence that there was a positive increase in the volume of the airway, especially when an obstruction was caused due to nasal valve constriction, and reduction in nasal airflow resistance.

Limited research exists on the correlation between sleep disorder breathing and TMD. The aim of this study is to assess the relation between TMJ noises generated using Joint Vibration Analysis (JVA) and the most common subtype of TMD; TMD and SDB, and variables amongst patients and TMD. This study is a 10-year retrospective analysis of 68 patients. Patients were selected for the study if they possessed a full set of dental records comprising of demographics, cone beam computed tomography (CBCT), and JVA data. Based on a clinical diagnosis of SDB, patients were divided into two groups, patients with SDB (n = 37) and those without SDB (n = 31). JVA was used to diagnose patients with TMD (n = 56) and those without TMD (n = 12) as well as to identify the most common subtype of TMD. SDB and non-SDB patient groups were compared to each other in order to identify whether a link concerning SDB and TMD and SDB versus other TMD subtypes. Finally, a multivariant analysis was done in order to identify a correlation between patient characteristics and TMD using Graph Pad Prism v8.2.0. The analysis of results indicated that ligamentous laxity was the most common diagnosis of TMD defined by JVA. No statistically significant association identified between SDB and TMD cohort (p = 0.7598); TMD subtypes in patients with SDB. However, multivariant analysis of patient characteristics below average patient oral hygiene was significantly associated with TMD (p = 0.0309). JVA successfully identified ligamentous laxity as the most common diagnosis of TMD. Due to limitations in this patient cohort, an association between TMD and SDB was not able to be established in this analysis. The correlation between TMD and SDB requires further research. If an association does exist, JVA represents a novel tool for the early identification of TMD, which may lead to earlier diagnosis and intervention for SDB.

Early and accurate diagnosis of Alzheimer’s disease (AD) is especially important for neurodegenerative disorders allowing patients, who exhibit different patterns of severity and progression risks, to take prevention and treatments before brain damages are shaped. Functional Near-Infrared Spectroscopy (fNIRS), as a clinical test, can be employed in an ecological setting to support AD diagnosis at early stages. In this study, we aimed to comprehensively study the hemodynamic response patterns among four subject groups from 140 participants by visualizing the 4-class distributions based on t-SNE visualization techniques and showing the fNIRS topographic mapping to have a pictorial representation on the surface of the prefrontal cortex region. We demonstrated that the changes in hemodynamic concentrations of oxygenated hemoglobin (HbO) and deoxygenated hemoglobin (Hb) from healthy controls to three stages of AD did exist during four stages of our experimental protocols. Results also revealed that various machine learning techniques were capable of both analyzing AD patterns and its related features and classifying multiple pathophysiologic mechanisms with the highest accuracies of 74.39 ± 4.7% and 84.91 ± 4.01% corresponding to raw and SMOTE-based features, respectively. These findings demonstrate the feasibility of fNIRS-based approaches to investigate the stages of AD progression.

In the health care field, doctors usually analyse some details presented in medical images to detect some diseases. If the doctor sees some changes related to the shape, colour or size of the retinal blood vessel. The doctor will guess early stage of dangerous sickness like age-related macular degeneration, diabetes, hypertension, arteriosclerosis. It is a good time for the doctor to build a treatment plan as soon as possible. One of the useful retinal blood vessel analysis ways is segmentation. The task should be done before other works are deployed to cure the patient. The paper proposed a method to segment retinal blood vessels by using histogram equalization combined with improving multi-scale line detection. This method uses histogram equalization to improve the quality of the input image, and then improving multi-scale line detection (MLD) technique to enhance the accuracy of vessels detection. Particularly, using the MLD technique to detect large vessels and small ones with adaptive window sizes finally combined. As a result, our method can work effectively to segment more vessels. The method is tested in quality and quantity on publicly available DRIVE datasets with an average accuracy reaching to 0.9515. The result of the proposed method is better than these other methods.

This study aimed to compare sleep architects and CAP parameters between patients with Narcolepsy and the normal person using the electroencephalogram signal (EEG) analysis. In this study, we analyzed sleep data from five Narcolepsy patients and fourteen normal controls. Participants’ macrostructure parameters and CAP parameters were calculated and compared to indicate the abnormal in narcoleptics’ nocturnal sleep. A prime abnormal in Narcolepsy patient’s sleep structures was the early onset of REM with significant shot REM latency; this phenomenon was observed in two out of five patients’ hypnograms. The nocturnal sleep of Narcolepsy patients was usually disturbed by sleep arousals that appeared regularly at night, which reduced the quality of nocturnal slumber. In this study, Narcolepsy individuals had a lower CAP/NREM rate, shorter CAP total time, and a decreased in the A1 index during NREM sleep compared to healthy individuals. The obtained results suggested that people with Narcolepsy be likely to have a short REM latency with fragmented night sleep that reduced sleep quality. The increase in the CAP ratio could relate to the instability of night sleep in Narcolepsy patients. A further study on EEG wave activity should be conducted to assist the inequality between a group of Narcolepsy patients and another group of normal subjects.

EOG is one of the major artifacts in EEG signal processing. There are varieties of methods have been proposed that aim to eliminate the influence of Occular artifacts on the EEG signals. However, the problem is the trade-off between their performance of removing EOG artifact and their simplicity. In this study, we propose a simple and reliable method but giving a good performance. The idea of this method is to use a multi-threshold technique to target EOG contaminated parts in the signal then selectively subtract it out in order to get a corrected signal with a minimum alteration on the uncontaminated parts. In this study, we used triple-threshold, both in time and frequency domain, to target the contaminated parts (or EOG artifact component). The result shows that besides its simplicity, this method also reliable and effective when selectively removed some typical EOG artifacts like blinks or eye movements without altering other clean parts in the EEG signals. More than that, our method is also able to extract the estimated EOG artifact component from the EEG signal. The need for this method is only one single prefrontal EEG channel, no need for an EOG reference channel for the input. The source code of this method is freely available to download in the form of a MATLAB function by request. We encourage the researchers to give it a try.

Contamination of EEG by ocular artifacts (EOG) is the major artifact that reduces the accuracy of applications using Electroencephalogram (EEG) signal. To resolve this issue, Independent Component Analysis (ICA) is a common method to remove EOG artifacts from EEG recordings, by decomposing multichannel EEG signals into maximally Independent Components (ICs). ICs representing ocular activities can be identified visually, then be eliminated to reconstruct EOG-free EEG signals. However, this approach requires prior domain knowledge, and hence, undermine reliability and reproducibility. To address this, our study proposed a method to remove EOG contamination by applying machine learning techniques. We acquired an EEG database of 20 healthy subjects using Alice 5 Polysomnography system to record signals from 12 electrodes. Randomly selected 15-s data segments from EEG channels were used to run ICA, which resulted in 10 ICs. For each IC, we plotted its topography map and labelled whether this IC is “EOG” or “non-EOG”. A total of 612 labelled data points of ICs, topography maps and labels were collected. After applying several classifiers for model training and evaluation using cross-validation, the best classifier, Extremely Randomized Tree, achieved an average accuracy of 92%, precision of 83%, recall of 71%, and F1 score of 76%. In conclusion, the proposed method showed promising results in identifying EOG components and attenuating ocular activity on reconstructed EEG signals. Compared with existing automated solutions, our proposed method only used a small number of channels and had the potential to be applied in real-time applications due to its fast computation.

Polysomnography (PSG) is considered the gold standard for sleep disorders diagnosis. However, its signals are difficult to read in the presence of artifacts. This study presents a biosignal processing method that can help to remove artifacts from PSG signals. The method consists of two main parts. Firstly, sleep diary and feature extraction using Fourier transform and Wavelet transforms were used to detect different artifacts in PSG signals including physiologic artifacts such as cardiac artifact, muscle artifact, movement artifact, ocular artifact...and non-physiologic artifacts. Secondly, ICA (Independent Component Analysis) and Wavelet transform were used to remove the detected artifacts and reconstruct the signal. The results indicate that our method could adequately remove ECG and EOG artifacts in 70%–80% of the cases and wandering baseline and 50 Hz artifacts in 100% of the cases. We hope this algorithm will become a useful tool in removing artifacts in PSG signals, thus helping to make PSG signal reading more straightforward.

Neuronavigations are real-time approaches implemented to help neurosurgeons precisely localize different intracerebral pathologies by using multiple neuroimaging modalities. However, current systems suffer from several shortcomings including time-consuming, 3D registration and segmentation accuracies as well as difficulties transferring 3D vessel imaging to the neuronavigation systems. In this work, we introduce a standalone platform for image-fusion, and semantic segmentation of MR angiography images supported for neurovascular interventions. The full-stack toolkit consists of two parts: back-end and front-end. At back-end, Tensorflow library and Ajax for application programming interface server request-response interactions are embedded. As to front-end, we implement C++_based Qt platform for GUI (Graphic User Interface) in Visual Studio integrated development environment. The toolkit provides 3D volume and slice-based visualizations of brain multimodal images. All medical images are archived in DICOM standard, then converted into NIfTI formats. Visualization Toolkit was used to render 3D MR images. The implemented volume-rendering techniques allow the direct visualization of vascular structures, thus reveal vessel abnormalities more faithfully. We provide GUI interface of the modality brain image registration and segmentation functionality. There are two machine-learning based automatic registration categories: (1) intensity-based, (2) geometry-based. The registration error in mm is computed by using Hausdorff Distance metric. As for cerebrovascular segmentation, a method that utilizes an enhanced vesselness filter which bases on multiscale Hessian eigenvalues is performed to extract neurovascular trees. The introduced toolkit is expected to be a validated platform that allows researchers to apply insightful results into the operating room for clinical evaluations.

The digital filters play an indispensable role in recording and displaying EEG data. Without filters, many segments of EEG would be virtually unreadable. The main benefit of filters is that it makes the EEG tracing cleaner, easier to interpret and observe. Specific filter settings can also be used to accentuate particular types of EEG activity. Filters can, however, be misused, and at times their use can lead to unintended consequences. In this study, we present and compare the conventional filter design methods applied to significant types of noises. We built a program with a friendly interface with effective noise filtering.

Sleep apnea syndrome poses many dangers to the cardiovascular, nervous and respiratory systems. Evaluating changes in anatomical features of facial bones on head X-ray was an accessible and helpful tool in assessing the severity of obstructive sleep apnea syndrome. A case–control study of 49 patients (case group: 33, control group: 16) with symptoms of loud snoring and/or evidence of suspected obstructive sleep apnea syndrome (OSAS) admitted to the Hue University of Medicine and Pharmacy’s Hospital, from May 2018 to May 2019. Sleep apnea syndrome was measured with StarDust II, Germany. X-ray was performed with Amrad ARM, USA. Average age of the study group: 71.47 ± 11.46 years. The average Epworth score of OSAS group (+) 7.64 ± 3.13 was higher than the OSAS group (−) 5.00 ± 2.13 (p < 0.05). High-risk Berlin scores accounted for 82.9% higher proportion in the OSAS group (+) than the OSAS group (−) (p < 0.05). SNA, SNB, ANB, MPH and PAS in OSAS group (+) differed from OSAS group (−) with p < 0.05. The average value of ANB and PAS were statistically significant, according to AHI with p < 0.05. There was a correlation between AHI and Epworth, SNB, ANB, MPH, PAS in the study group (p < 0.05). Among OSAS patients (+): Correlated between AHI and SNB, ANB, MPH, PAS was − 0.45 (p < 0.05), 0.58 (p < 0.05), 0.39 (p < 0.05), − 0.46 (p < 0.05), respectively. The lateral head X-ray provides SNB, ANB, MPH, PAS values correlated with AHI in obstructive sleep apnea syndrome patients.

Sleep apnea syndrome is a common sleep disorder, which has a negative impact on health and quality of life. Atrial fibrillation (AF) is the most common cardiac arrhythmia and is associated with significant morbidity and mortality. 52 patients with atrial fibrillation in the Department of Internal Cardiology at Hue University of Medicine and Pharmacy Hospital had loud snoring and/or evidence of sleep apnea. A case–control study of 52 patients (case group: 38, control group: 14) with symptoms of loud snoring and/or evidence of suspected obstructive sleep apnea syndrome (OSAS) admitted to the Hue University of Medicine and Pharmacy’s Hospital, from May 2018 to May 2019. Sleep apnea syndrome was measured with Embletta Gold, USA. Data analysis used SPSS 20.0 software. Common age is above 60 years old (69.7%); men account for the majority (63.46%). Loud snoring symptoms during sleep, daytime sleepiness and difficulty concentrating at work are the majority in patients with sleep apnea syndrome (71.80%, 82.60% and 92.40% respectively). There is a positive correlation between the AHI index and the severity of atrial fibrillation by EHRA (r = 0.485; p < 0.05), left atrial diameter (r = 0.020; p > 0.05) and cardiovascular factors (r = 0.354; p < 0.05). Atrial fibrillation patients have a higher incidence of sleep apnea syndrome due to the general population and a correlation between the severity of atrial fibrillation and the AHI index, with cardiovascular risk factors.