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Medical & Biological Engineering & Computing

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17-07-2021 | Original Article

Characterization of the cylindrical electrospun nanofibrous polysulfone membrane for hemodialysis with modelling approach

Authors: Farideh Mohammadi, Farzaneh Mohammadi, Zeynab Yavari

Published in: Medical & Biological Engineering & Computing | Issue 7-8/2021

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Abstract

Electrospun nanofibrous membrane (ENM) is a membrane fabricated using electrospinning technique which has considerable characteristics such as high porosity, nanometer pore size, and simple process. Although ENMs are being evaluated in various medical applications, the effectiveness for hemodialysis (HD) has not been evaluated carefully. Thus, in this study, the cylindrical electrospun nanofibrous polysulfone (CENP) membrane was fabricated and its performance in the dialysis adequacy in HD patients was evaluated.

The CENP membrane was fabricated in a tabular shape. The physical characteristics of the membrane are examined using scanning electron microscope (SEM) images and the permporometry technique. Then, its efficiency in urea and creatinine removal from the blood serum of 21 HD patients was evaluated at a low blood flow rate (BFR) of 200 ml min^-1 and dialysate fluid rate (DFR) of 300 ml min^-1. Afterwards, the results were modeled and optimized using artificial neural network (ANN) and genetic algorithm (GA), respectively. Finally, sensitive analysis was performed via Spearman’s rank correlation coefficient. The highest dialysis adequacy was observed in membranes with an inner diameter of 3 mm. The CENP membrane belongs to the super high-flux membrane and it could be replaced with existing commercial hollow fiber membranes.

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Storr M, Ward RA (2018) Membrane innovation: closer to native kidneys. Nephrol Dial Transplant 33:22–27. https://doi.org/10.1093/ndt/gfy228CrossRef

Lim JH, Park Y, Yook JM et al (2020) Randomized controlled trial of medium cut-off versus high-flux dialyzers on quality of life outcomes in maintenance hemodialysis patients. Sci Rep 10:1–11. https://doi.org/10.1038/s41598-020-64622-zCrossRef

Ma L, Zhao S (2017) Risk factors for mortality in patients undergoing hemodialysis: a systematic review and meta-analysis. Int J Cardiol 238:151–158. https://doi.org/10.1016/j.ijcard.2017.02.095CrossRefPubMed

Maduell F, Broseta JJ, Rodas L et al (2020) Comparison of solute removal properties between high-efficient dialysis modalities in low blood flow rate. Ther Apher Dial 24:387–392. https://doi.org/10.1111/1744-9987.13440CrossRefPubMed

Daly MA, Vale L, Campbell M et al (2005) Cellulose, modified cellulose and synthetic membranes in the haemodialysis of patients with end-stage renal disease (Review). https://doi.org/10.1002/14651858.CD003234

Eswari JS, Naik S (2020) A critical analysis on various technologies and functionalized materials for manufacturing dialysis membranes. Mater Sci Energy Technol 3:116–126. https://doi.org/10.1016/j.mset.2019.10.011CrossRef

Cortez Tornello PR, Caracciolo PC, Igartúa Roselló JI, Abraham GA (2018) Electrospun scaffolds with enlarged pore size: porosimetry analysis. Mater Lett 227:191–193. https://doi.org/10.1016/j.matlet.2018.05.072CrossRef

Ronco C, Neri M, Lorenzin A et al (2017) Multidimensional classification of dialysis membranes. Contrib Nephrol 191:115–126. https://doi.org/10.1159/000479260CrossRefPubMed

Hoque ME, Nuge T, Yeow TK, Nordin N (2019) Electrospun matrices from natural polymers for skin regeneration. In: Nanostructured Polymer Composites for Biomedical Applications. Elsevier, pp 87–104

10.

Namekawa K, Tokoro Schreiber M, Aoyagi T, Ebara M (2014) Fabrication of zeolite–polymer composite nanofibers for removal of uremic toxins from kidney failure patients. Biomater Sci 2:674. https://doi.org/10.1039/c3bm60263jCrossRefPubMed

11.

Lu L, Samarasekera C, Yeow JTW (2015) Creatinine adsorption capacity of electrospun polyacrylonitrile (PAN)-zeolite nanofiber membranes for potential artificial kidney applications. J Appl Polym Sci 132:n/a-n/a. https://doi.org/10.1002/app.42418

12.

Yen SC, Liu ZW, Juang RS et al (2019) Carbon nanotube/conducting polymer hybrid nanofibers as novel organic bioelectronic interfaces for efficient removal of protein-bound uremic toxins. ACS Appl Mater Interfaces 11:43843–43856. https://doi.org/10.1021/acsami.9b14351CrossRefPubMed

13.

Bahramimehr F, Esmaeili A (2019) Producing hybrid nanofiber-based on /PAN/Fe3 O4 /zeolite/nettle plant extract/urease and a deformed coaxial natural polymer to reduce toxicity materials in the blood of dialysis patients. J Biomed Mater Res A jbm.a.36689. https://doi.org/10.1002/jbm.a.36689

14.

Maurmann N, Sperling LE, Pranke P (2018) Electrospun and electrosprayed scaffolds for tissue engineering. Advances in Experimental Medicine and Biology. Springer, New York LLC, pp 79–100

15.

Liu M, Zhang Y, Sun S et al (2019) Recent advances in electrospun for drug delivery purpose. J. Drug Target. 27:270–282CrossRef

16.

Park JA, Kim SB (2017) Antimicrobial filtration with electrospun poly(vinyl alcohol) nanofibers containing benzyl triethylammonium chloride: immersion, leaching, toxicity, and filtration tests. Chemosphere 167:469–477. https://doi.org/10.1016/j.chemosphere.2016.10.030CrossRefPubMed

17.

Chen H, Huang M, Liu Y et al (2020) Functionalized electrospun nanofiber membranes for water treatment: a review. Sci Total Environ 739

18.

Koh E, Lee YT (2020) Development of an embossed nanofiber hemodialysis membrane for improving capacity and efficiency via 3D printing and electrospinning technology. Sep Purif Technol 241:116657. https://doi.org/10.1016/j.seppur.2020.116657CrossRef

19.

Mohammadi F, Valipouri A, Semnani D, Alsahebfosoul F (2018) Nanofibrous tubular membrane for blood hemodialysis. Appl Biochem Biotechnol 186:443–458. https://doi.org/10.1007/s12010-018-2744-0CrossRefPubMed

20.

Rianjanu A, Kusumaatmaja A, Suyono EA, Triyana K (2018) Solvent vapor treatment improves mechanical strength of electrospun polyvinyl alcohol nanofibers. Heliyon 4:e00592. https://doi.org/10.1016/j.heliyon.2018.e00592CrossRefPubMedPubMedCentral

21.

Qi L, Guo C-Y, Huang Fu M-G et al (2019) Enhancement of solvent resistance of polyimide electrospun mat via the UV-assisted electrospinning and photosensitive varnish. Polymers (Basel) 11:2055. https://doi.org/10.3390/polym11122055CrossRefPubMedCentral

22.

Perez-Garcia R, Jaldo M, Alcázar R et al (2019) Unlike Kt, high Kt/V is associated with greater mortality: the importance of low V. Nefrologia 39:58–66. https://doi.org/10.1016/j.nefroe.2018.04.011CrossRefPubMed

23.

García-Alba J, Bárcena JF, Ugarteburu C, García A (2019) Artificial neural networks as emulators of process-based models to analyse bathing water quality in estuaries. Water Res 150:283–295. https://doi.org/10.1016/J.WATRES.2018.11.063CrossRefPubMed

24.

Ghezelbash A, Keynia F (2014) Design and implementation of artificial neural network system for stock exchange prediction

25.

Long J, Xueyuan K, Haihong H et al (2004) Study on the overfitting of the artificial neural network forecasting model *. Acta Meteorol Sin 19:216–225

26.

Mohammadi N, Mirabedini SJ (2018) Comparison of particle swarm optimization and backpropagation algorithms for training feedforward neural network. J Math Comput Sci 12:113–123. https://doi.org/10.22436/jmcs.012.02.03CrossRef

27.

Deng Y, Xiao H, Xu J, Wang H (2019) Prediction model of PSO-BP neural network on coliform amount in special food. Saudi J Biol Sci 26:1154–1160. https://doi.org/10.1016/j.sjbs.2019.06.016CrossRefPubMedPubMedCentral

28.

Jahangir MH, Mousavi Reineh SM, Abolghasemi M (2019) Spatial predication of flood zonation mapping in Kan River Basin, Iran, using artificial neural network algorithm. Weather Clim Extrem 25:100215. https://doi.org/10.1016/J.WACE.2019.100215CrossRef

29.

Fan M, Hu J, Cao R et al (2018) A review on experimental design for pollutants removal in water treatment with the aid of artificial intelligence. Chemosphere 200:330–343. https://doi.org/10.1016/J.CHEMOSPHERE.2018.02.111

30.

Lu H, Kim E, Gutierrez M (2019) Monte Carlo simulation (MCS)-based uncertainty analysis of rock mass quality Q in underground construction. Tunn Undergr Sp Technol 94. https://doi.org/10.1016/j.tust.2019.103089

31.

Lee GH, Song JC, Yoon KB (2010) Controlled wall thickness and porosity of polymeric hollow nanofibers by coaxial electrospinning. Macromol Res 18:571–576. https://doi.org/10.1007/s13233-010-0607-9CrossRef

32.

Sreedhara SS, Tata NR (2013) A novel method for measurement of porosity in nanofiber mat using pycnometer in filtration. J Eng Fiber Fabr 8:132–137. https://doi.org/10.1177/155892501300800408CrossRef

33.

Najafi M, Frey MW (2020) Electrospun nanofibers for chemical separation. Nanomaterials 10. https://doi.org/10.3390/nano10050982

34.

Haroon S, Davenport A (2018) Choosing a dialyzer: What clinicians need to know. Hemodial Int 22:S65–S74. https://doi.org/10.1111/hdi.12702CrossRefPubMed

35.

Ren J, Li Z, Wong FS (2006) A new method for the prediction of pore size distribution and MWCO of ultrafiltration membranes. J Memb Sci 279:558–569. https://doi.org/10.1016/j.memsci.2005.12.052CrossRef

36.

Tojo A, Kinugasa S (2012) Mechanisms of glomerular albumin filtration and tubular reabsorption. Int J Nephrol 2012:481520. https://doi.org/10.1155/2012/481520

37.

Magee CC, Tucker JK, Singh AK (2016) Core concepts in dialysis and continuous therapies. In: Core Concepts Dial Contin Ther. https://books.google.com.ua/books?id=ygBkDAAAQBAJ&pg=PA258&lpg=PA258&dq=pore+size+distribution+MWCO+MWRO&source=bl&ots=9O0licWce_&sig=ACfU3U1MCEZN7VCnV5zTk1a9uP50r5XkOg&hl=en&sa=X&ved=2ahUKEwiOgvd0LPrAhWHGewKHdxZDGw4ChDoATAEegQIARAB#v=onepage&q=poresize. Accessed 25 Aug 2020

38.

Boschetti-De-Fierro A, Voigt M, Storr M, Krause B (2013) Extended characterization of a new class of membranes for blood purification: the high cut-off membranes. https://doi.org/10.5301/ijao.5000220

39.

Zweigart C, Boschetti-de-Fierro A, Hulko M et al (2017) Medium cut-off membranes - closer to the natural kidney removal function. Int. J. Artif. Organs 40:328–334CrossRef

40.

Leypoldt JK, Cheung AK, Carroll CE et al (1999) Effect of dialysis membranes and middle molecule removal on chronic hemodialysis patient survival. Am J Kidney Dis 33:349–355. https://doi.org/10.1016/S0272-6386(99)70311-2CrossRefPubMed

41.

Ma K, Khan MA, Hussain A (2019) Haemodialysis membranes: a review. J Membr Sci Technol 9:205

42.

Leypoldt JK, Cheung AK, Agodoa LY et al (1997) Hemodialyzer mass transfer-area coefficients for urea increase at high dialysate flow rates. Kidney Int 51:2013–2017. https://doi.org/10.1038/ki.1997.274CrossRefPubMed

43.

Ahrenholz P, Winkler RE, Zendeh-Zartochti D (2015) The role of the dialysate flow rate in haemodialysis. In: Updates in Hemodialysis. InTech

44.

Vilar E, Fry AC, Wellsted D et al (2009) Long-term outcomes in online hemodiafiltration and high-flux hemodialysis: a comparative analysis. Clin J Am Soc Nephrol 4:1944–1953. https://doi.org/10.2215/CJN.05560809CrossRefPubMedPubMedCentral

45.

Moist LM, Hemmelgarn BR, Lok CE (2006) Relationship between blood flow in central venous catheters and hemodialysis adequacy. Clin J Am Soc Nephrol 1:965–971. https://doi.org/10.2215/CJN.01090306CrossRefPubMed

46.

Kim THY, Kim SH, Kim THY et al (2019) Removal of large middle molecules via haemodialysis with medium cut-off membranes at lower blood flow rates: an observational prospective study. BMC Nephrol 21:1–9. https://doi.org/10.1186/s12882-019-1669-3CrossRef

47.

Himmelfarb J, Ratner B (2020) Wearable artificial kidney: problems, progress and prospects. Nat Rev Nephrol 1–2

48.

Bahrami M, Akbari M, Bagherzadeh SA et al (2019) Develop 24 dissimilar ANNs by suitable architectures & training algorithms via sensitivity analysis to better statistical presentation: measure MSEs between targets & ANN for Fe–CuO/Eg–Water nanofluid. Phys A Stat Mech its Appl 519:159–168. https://doi.org/10.1016/j.physa.2018.12.031CrossRef

Title: Characterization of the cylindrical electrospun nanofibrous polysulfone membrane for hemodialysis with modelling approach
Authors: Farideh Mohammadi
Farzaneh Mohammadi
Zeynab Yavari
Publication date: 17-07-2021
Publisher: Springer Berlin Heidelberg
Published in: Medical & Biological Engineering & Computing / Issue 7-8/2021
Print ISSN: 0140-0118
Electronic ISSN: 1741-0444
DOI: https://doi.org/10.1007/s11517-021-02404-z

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