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Veyssi, A.

Publications and source records attributed to Veyssi, A..

3 recordsLinked to original sources

Polycaprolactone-based shape memory foams as self-fitting vaginal stents

There is an urgent critical need for a patient-forward vaginal stent that can prevent debilitating vaginal stenosis that occurs in up to 75% of patients who undergo pelvic radiation treatments and adolescent patients after vaginal reconstruction. To this end, we developed a self-fitting vaginal stent based on a shape-memory polymer (SMP) foam that can assume a secondary, compressed shape for ease of deployment. Upon insertion, the change in temperature and hydration initiates foam expansion to shape fit to the individual patient and restore the lumen of the stent to allow egress of vaginal secretions. To achieve rapid actuation at physiological temperature, we investigated the effect of architecture of two photocurable, polycaprolactone (PCL) macromers. Star-PCL-tetraacrylate displayed reduced melting temperature in the target range as compared to the linear-PCL-diacrylate. Emulsion-templating was then used to fabricate foams from 75:25 water-in-oil (W/O) emulsions that were subsequently annealed to yield high-porosity SMP foams. Upon axial shape memory testing, both foams displayed excellent shape fixity (90%); however, only the PCL star-foams displayed shape recovery ([~]84%) at 37{degrees}C to its permanent shape. A custom mold and curing system was then used to fabricate PCL star- foams into hollow, cylindrical stents. The stent was crimped to its temporary insertion shape (50% reduction in diameter, OD [~] 11 mm) with a custom radial crimper and displayed excellent shape fixity for deployment (> 95%) and shape recovery ([~] 100%). To screen vaginal stents, we developed a custom benchtop pelvic model that simulated vaginal anatomy, temperatures, and pressures with an associated computational model. A hysteroscope was used to visualize stent expansion and deformation via a scope port near the cervix of the benchtop model. A crimped SMP vaginal stent was deployed in the model and expanded to walls of the canal ([~]70% increase in cross-sectional area) in less than 5 minutes after irrigation with warm water. The vaginal stent demonstrated retention of vaginal caliber with less than 1% decrease in cross-sectional area under physiological pressure. Collectively, this work demonstrates the potential for SMP foams as self-fitting vaginal stents to prevent stenosis. Additionally, this work provides new open-source tools for the iterative design of other gynecological devices. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=87 SRC="FIGDIR/small/577474v1_ufig1.gif" ALT="Figure 1"> View larger version (37K): org.highwire.dtl.DTLVardef@1bc3162org.highwire.dtl.DTLVardef@4e5657org.highwire.dtl.DTLVardef@1069d33org.highwire.dtl.DTLVardef@13aa9da_HPS_FORMAT_FIGEXP M_FIG C_FIG Created in BioRender

bioengineering↗

Bio-contaminated Plastic Micropipette Tip Sterilization Stations: Environmentally, Ecologically, and Energetically Viable Solution

Bioscientific research laboratories significantly contribute to global plastic waste production through their widespread use of plastic products, such as single-use micropipette tips. However, biologically contaminated pipette tips must undergo several washing and sterilization steps before being reused or recycled. Grenova Solutions provides such a decontamination station called TipNovus, which has been implemented by academic and government research labs to reuse pipette tips in sensitive biological assays. Despite this success, the high initial purchasing cost of these washing stations deter many laboratories from incorporating it into their workflow. Additionally, researchers are reluctant to reuse pipette tips due to concerns that the washing process may not thoroughly remove all contaminants. To mitigate these concerns, considering the University of Texas at Austin as an example, we performed a cost-benefit analysis of employing a university-wide washing station. We estimated that only single-time reuse of the pipette tips could result in a 100% return on investment from the equipment purchase cost within 3 months. Then, with our pilot experiments, we confirmed the TipNovus washing steps to be 100% efficient in sterilizing pipette tips contaminated with T7 bacteriophage, enabling their reuse in bacteriophage functionality assays. Finally, we proposed an alternative and more convenient autoclave-based sterilization method to decontaminate pipette tips. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=77 SRC="FIGDIR/small/572721v2_ufig1.gif" ALT="Figure 1"> View larger version (33K): org.highwire.dtl.DTLVardef@120ddceorg.highwire.dtl.DTLVardef@c222d6org.highwire.dtl.DTLVardef@17d496forg.highwire.dtl.DTLVardef@60444f_HPS_FORMAT_FIGEXP M_FIG C_FIG SYNOPSISSingle-use plastic micropipette tips discarded by bioresearch labs generate substantial waste. This study reports adopting standardized tip-washing and reuse systems in labs greatly reduces plastic waste and research expenditures.

bioengineering↗

sMAP: An interactive microarray data analysis tool for early-stage researchers

Microarray data enables biologists to extract differentially expressed genes (DEGs) across multiple phenotypes. While several pipelines and tools exist to perform microarray data analysis, they are targeted to users with moderate to advanced computational understanding and lack an easy-to-use, interactive and dynamic methodology to perform analysis assisted with comprehensive learning resources. In this study, we developed an interactive application "sMAP" (Standard Microarray Analysis Pipeline) to make transcriptome microarray data analysis more accessible in learning environments and to enable the identification of significant pathological biomarkers. In a case study of colorectal cancer, we showed that sMAP enabled us to reproduce previous findings and discover relevant pathways. sMAP provides a comprehensive set of tutorials and learning documentation to help early-stage researchers. The latest URLs of sMAPs hosting, tutorial, and frequently updated documentation can be found at https://github.com/BI-STEM-Away/sMAP.

bioinformatics↗