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In Vitro and in Silico Binding Studies of Chromeno-Pyrimidine Derivatives With Biological Important Protein-Part III

In Vitro and in Silico Binding Studies of Chromeno-Pyrimidin...

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ieee symposium on bioinformatics and bioengineering (BIBE)

作者： Danijela Stojković Sandra Jovičić Milić Dušica Simijonović Edina Avdović Tamara Mladenović Zoran Marković Department of Science Institute for Information Technologies University of Kragujevac Kragujevac Serbia Department of Natural Science and Mathematics State University of Novi Pazar Novi Pazar Serbia

ISBN: (数字)9798331518622

ISBN: (纸本)9798331518639

In this study, in vitro and in silico interactions of bovine serum albumin with chromeno-pyrimidine derivatives (CP), 5-(7- bromo-2,4-dioxo-1,3,4,5-tetrahydro-2H-chromeno-[2,3-d]pyrimidin-5-yl)pyrimidine2,4,6(1H,3H,5H)-tri-one (CP1) and 8,9-dihydroxy-2H-chromeno[2,3-d] pyrimidine $2,4(3 H)$ dione (CP-2), are investigated. the high value of in vitro obtained binding constants are the result of good binding of the investigated compounds to BSA. Molecular docking results explain the interactions of BSA to the tested compounds and it is consistent with the experimentally obtained results.

关键词： Proteins Bovine Biology Compounds In vitro bioinformatics Biomedical engineering

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Biomimetic Natural Electrospun Gelatin Scaffolds for Skin Regeneration

Biomimetic Natural Electrospun Gelatin Scaffolds for Skin Re...

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ieee symposium on bioinformatics and bioengineering (BIBE)

作者： Katarina Virijević Marko Živanović Jelena Pavić Tamara Mladenović Hilal Girgin OZ Jana Baščarević Nenad Filipović Bioengineering Laboratory Institute for Information Technologies Kragujevac Serbia Department of Natural Science Institute for Information Technologies Kragujevac Serbia Department of Bioengineering Faculty of Engineering and Natural Sciences Bursa Turkey Faculty of Engineering Bioengineering Research and Development Center University of Kragujevac Kragujevac Serbia

ISBN: (数字)9798331518622

ISBN: (纸本)9798331518639

Recent advances in regenerative medicine provide encouraging strategies to produce artificial skin substitutes. Gelatin scaffolds are successfully used as wound dressing materials due to their superior properties, such as biocompatibility and the ability to mimic the extracellular matrix of the surrounding environment. In this study, five gelatin combination solutions were prepared and successfully electrospun using an electrospinning technique. After careful screening, the optimal concentration of the most promising combination was selected for further investigation. the obtained scaffolds were crosslinked with $\mathbf{2 5 \%}$ glutaraldehyde vapor and characterized by Scanning Electron Microscopy (SEM). the incorporation of antibiotic agents such as ciprofloxacin hydrochloride and gentamicin sulfate into gelatin membranes improved the already existing antibacterial properties of antibiotic-free gelatin scaffolds against bacteria. Also, the outcomes of the in vivo model study revealed that skin regeneration was significantly accelerated with gelatin/ciprofloxacin scaffold treatment. Finally, the combination of gelatin's extracellular matrix and antibacterial agents in the scaffold suggests its potential for effective wound healing treatments, emphasizing the importance of gelatin scaffolds in tissue engineering.

关键词： Scanning electron microscopy In vivo Biomimetics Tissue engineering Wounds Antibacterial activity Skin Matrices Nanostructures Extracellular

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Depression Diagnosis: bioinformatics Uncovers Cellular Abnormalities in Female-Specific Genes With Ai-Driven Blood Biomarker-Based Prediction

Depression Diagnosis: Bioinformatics Uncovers Cellular Abnor...

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ieee symposium on bioinformatics and bioengineering (BIBE)

作者： Neda Firoz Nivedita Yadav Olga Grigorievna Beresteneva Sergey Aksyonov Vladimirovich Institute of Applied Mathematics and Computer Science Tomsk State Univeristy Tomsk Russia Indian biological data center Regional Centre for Biotechnology Faridabad India Tomsk Polytechnic Univeristy Tomsk Russia

ISBN: (数字)9798331518622

ISBN: (纸本)9798331518639

With an estimated 264 million people affected by MDD globally, there is an urgent need for novel approaches to diagnosis and treatment. this study explored the complex gene expression profiles linked to Major Depressive Disorder (MDD) using state-of-the-art Next-Generation Sequencing (NGS), namely RNA-Seq. there is a need for accurate, non-invasive diagnostics, particularly through gender-specific biomarker research in female RNA-Seq data. To address this disparity, RNA-Seq data was analyzed using Machine Learning (ML) techniques to categorize female-specific MDD, identifying 10 critical biomarkers and utilizing Artificial Intelligence (AI) and bioinformatics to extract transcriptome data from publicly available datasets, while employing Generative Adversarial Networks (GANs) for data augmentation due to the limited availability of large RNA-Seq datasets. Gene set enrichment analysis (GSEA) and other bioinformatics analyses further demonstrated that genes differentially expressed in MDD patients were enriched in pathways related to the cell cycle, neutrophil degranulation, resolution of sister chromatid cohesion, and the formation of mitotic spindles by EML4 and NUDC. Ten important biomarkers associated with MDD were identified by an integrative bioinformatics investigation: IGHV3-64D, IGHV5-10-1, IFI27, LILRB5, PBK, SIGLEC1, IFI44L, CDCA5, and SLC4A1. Machine learning models based on these genes achieved $95 \%$ accuracy, highlighting potential of RNA-Seq and ML to enhance MDD diagnosis and reveal its molecular mechanisms.

关键词： Sequential analysis Accuracy Biological system modeling RNA Medical treatment Depression bioinformatics Blood Next generation networking Overfitting

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Application of Machine Learning in the Analysis of Gene Expression in Colorectal Cancer Cells Treated With Chemotherapeutics

Application of Machine Learning in the Analysis of Gene Expr...

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ieee symposium on bioinformatics and bioengineering (BIBE)

作者： Jelena Pavić Marko Živanović Ognjen Pavić Katarina Virijević Tamara Mladenović Irena Tanasković Nenad Filipović Bioengineering Laboratory Institute for Information Technologies Kragujevac Serbia Department of Histology and Embryology Faculty of Medical Sciences University of Kragujevac Kragujevac Serbia Faculty of Engineering University of Kragujevac Bioengineering Research and Development Center Kragujevac Serbia

ISBN: (数字)9798331518622

ISBN: (纸本)9798331518639

Colorectal cancer is a leading cause of cancerrelated deaths, and understanding its molecular mechanisms is key to improving treatments. this study applies machine learning algorithms to analyze the expression of genes related to redox balance, apoptosis, and cell migration in HCT-116 colorectal cancer cells treated with chemotherapeutics (5fluorouracil, oxaliplatin, irinotecan, and leucovorin). the analyzed genes include those for redox homeostasis (GPX1, GPX2, GPX3, GPX4, TXNRD1, GSTP1, NFE2L2, NFKB1, HIF1A), apoptosis (CASP3, CASP8, CASP9, FAS, BCL-2, BAX), and genes coding cytoskeleton proteins (CDH1, CTNNB1, CDH2). Machine learning models, such as decision trees and random forests were used to analyze gene expression changes based on qPCR data. Notably, GPX4 and BAX were linked to chemoresistance, while CDH1 upregulation suggested an effect on cancer cell migration. this study demonstrates the potential of machine learning in identifying gene expression patterns and aiding in the development of personalized CRC treatments.

关键词： Proteins Analytical models Refining Colorectal cancer Redox Gene expression Decision trees Stress Random forests Biological cells

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Biogenic Silver Nanoparticles Causes Cell Death by Inducing Oxidative Stress in MRC-5 Cell Line

Biogenic Silver Nanoparticles Causes Cell Death by Inducing ...

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ieee symposium on bioinformatics and bioengineering (BIBE)

作者： Safi Ur Rehman Qamar Jelena Košarić Marko Živanović Nenad Filipović Bioengineering Research and Development Centre (BioIRC) Kragujevac Serbia Faculty of Engineering University of Kragujevac Kragujevac Serbia Institute for Information Technologies Kragujevac University of Kragujevac Kragujevac Serbia

ISBN: (数字)9798331518622

ISBN: (纸本)9798331518639

this study showcases the synthesis of silver nanoparticles (AgNPs) by the utilization of Borovnica extract (Vaccinium myrtillus) and Bosiljak extract (Ocimum basilicum) in a simple and non-toxic one-step procedure. the method is described as eco-friendly, uncomplicated, and economical, utilizing a water-based plant extract that acts as both a reducing and stabilizing agent for AgNPs. the VM-AgNPs and OB-AgNPs were characterized by UV-Vis spectroscopy, field emission scanning electron microscopy (FESEM), and transmission electron microscopy (TEM). UV-Vis spectroscopy detected surface plasmon resonance (SPR) at a wavelength of 305 nm and 344 nm in the VM-AgNPs and OB-AgNPs solutions, respectively. the investigation of VM-AgNPs and OB-AgNPs using FESEM revealed the presence of oval-shaped NPs with average sizes of 52 nm and 55 nm, respectively. While TEM analysis showed similar observation with average size of 80 nm and 35 nm, respectively. Both VM-AgNPs and OB-AgNPs showed cytotoxic properties against healthy lung pleura fibroblasts (MRC-5), resulting in a reduction in cell viability that was dependent on the dosage. the inhibitory concentration (IC50) in VM-AgNPs and OB-AgNPs treated group was calculated to be 25.89 ± 1.41 μg/ml and 8.41 ± 1.00 μg/ml, respectively. Moreover, the study investigated the involvement of reactive oxygen species (ROS) in the toxicity to cells. It was noted that both NPs induce oxidative stress over time in MRC-5 cell lines in a dose-depended manner.

关键词： Nanoparticles Spectroscopy Silver Scanning electron microscopy Toxicology Transmission electron microscopy Lungs Fibroblasts Surface plasmon resonance Stress

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Particle-Based Segmentation Of Extended Objects On Curved Biological Membranes

Particle-Based Segmentation Of Extended Objects On Curved Bi...

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ieee International symposium on Biomedical Imaging

作者： A. Solomatina Y. Kalaidzidis A. Cezanne K. Soans C. Norden M. Zerial I. F. Sbalzarini Faculty of Computer Science Technische Universität Dresden Dresden Germany Max Planck Institute of Molecular Cell Biology and Genetics Dresden Germany Center for Systems Biology Dresden Dresden Germany Faculty of Bioengineering and Bioinformatics Moscow State University Moscow Russia Cluster of Excellence Physics of Life TU Dresden Dresden Germany Instituto Gulbenkian de Ciência (IGC) Oeiras Portugal

We present a novel method for model-based segmentation of extended, blob-like objects on curved surfaces. Our method addresses several challenges arising when imaging curved biological membrane, such as out-of-membrane signal and geometry-induced background variations. We use a particle-based reconstruction of the membrane geometry, moment-conserving intensity interpolation from pixels to surface particles, and model-based in-surface segmentation. Our method denoises and deconvolves images, corrects for background variations, and quantifies the number, size, and intensity of segmented objects. We benchmark the accuracy of the method and present two applications to (1) neuroepithelial focal adhesion sites during optic cup morphogenesis in zebrafish and (2) reconstituted membrane domains bearing the small GTPase Rab5 on spherical beads.

关键词： Geometry Image segmentation Interpolation Surface reconstruction Biomedical optical imaging Biological system modeling Benchmark testing

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qLD: High-performance Computation of Linkage Disequilibrium on CPU and GPU

qLD: High-performance Computation of Linkage Disequilibrium ...

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ieee symposium on bioinformatics and bioengineering (BIBE)

作者： Charalampos theodoris Nikolaos Alachiotis Tze Meng Low Pavlos Pavlidis Technical University of Crete Greece University of Twente The Netherlands Carnegie Mellon University USA Foundation for Reseach and Technology-Hellas Greece

ISBN: (数字)9781728195742

ISBN: (纸本)9781728195759

Linkage disequilibrium (LD) is the non-random association between alleles at different loci. Assessing LD in thousands of genomes and/or millions of single-nucleotide poly-morphisms (SNPs) exhibits excessive time and memory requirements that can potentially hinder future large-scale genomic analyses. To this end, we introduce qLD (quickLD) (https//***/StrayLamb2lqLD), a highly optimized open-source software that assesses LD based on Pearson's correlation coefficient. qLD exploits the fact that the computational kernel for calculating LD can be cast in terms of dense linear algebra operations. In addition, the software employs memory-aware techniques to lower memory requirements, and parallel GPU architectures to further shorten analysis times. qLD delivers up to 5x faster processing than the current state-of-the-art software implementation when run on the same CPU, and up to 29x when computation is offloaded to a GPU. Furthermore, the software is designed to quantity allele associations between arbitrarily distant loci in a time-and memory-efficient way, thereby facilitating the evaluation of long-range LD and the detection of co-evolved genes. We showcase qLD on the analysis of 22,554 complete SARS-CoV-2 genomes.

关键词： Couplings Memory management Graphics processing units Genomics Central Processing Unit Kernel bioinformatics

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An intelligent web-based system for the detection and visualization of biomarkers in Microdeletion and Microduplication Syndromes

An intelligent web-based system for the detection and visual...

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ieee symposium on bioinformatics and bioengineering (BIBE)

作者： Konstantinos Stefanou Christos Bellos Georgios Stergios Alexandros Fyraridis Paris Ladias Prodromos Sakaloglou Charilaos Kostoulas Sofia Markoula Ioannis Georgiou Lime Technology Ioannina Greece Laboratory of Medical Genetics and Human Reproduction University of Ioannina Ioannina Greece

ISBN: (数字)9781728195742

ISBN: (纸本)9781728195759

Particular Microdeletion and Microduplication Syndromes (MMS) are rare recombinations, but as a whole (cumulatively) they represent a significant group of genetic abnormalities almost equal to aneuploidies. Some of them and in particular Di George Microdeletion can be found in frequencies second only to trisomy 21. Based on our database of MMS we found that almost all MMS span in length less than 5Mbs which is the cut-off point of resolution in standard cytogenetics. Furthermore, a significant percentage of them are in length less than 0. 5Mbs and all together, short and long MMS, have a high probability to harbor Holliday Junction sequence motifs and PRDM9 sequence ***, we propose that HJ sequence motifs and other recombination primers such as PRDM9 binding motif that exist in regions spanning MMS hotspots underlie a possible mechanism for their occurrence during probably in *** this context, we created the GeneScreening, a web-based system, a tool that allows for the advanced processing of user genomic data, along with visualization tools to identify and display the regions of interest regarding MMS in reference with the sequence motifs of HJs and PRDM9. this system will provide useful information for potential drug targets and new strategies for individual therapy as it serves as a prognostic tool for the MMS referenced in this paper.

关键词： Drugs Genomics Medical treatment Data visualization Tools bioinformatics Standards

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More Results on Experimental Evaluations of Some Algorithms for Block Sorting

More Results on Experimental Evaluations of Some Algorithms ...

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ieee symposium on bioinformatics and bioengineering (BIBE)

作者： Asai Asaithambi Swapnoneel Roy Sandhya Turlapaty School of Computing University of North Florida Jacksonville Florida

ISBN: (数字)9781728195742

ISBN: (纸本)9781728195759

BLOCK SORTING is an APX-hard combinatorial optimization problem motivated by applications in genome rearrangements. While previous works on block sorting have mainly focused on theoretical analyses of approximation algorithms, work we had previously developed an implementation framework for block sorting in the Java programming language in one of our earlier works [1]. We proposed a greedy heuristic for block sorting in that work. In this work, we use this framework to implement and experimentally evaluate five different algorithms for block sorting: 1) each block move guarantees a reduction of at least one block; 2) block moves are performed only on those blocks which are not members of the longest increasing subsequence (of blocks) in the original permutation; 3) each block move either reduces the number of blocks by two or three blocks, or reduces the number of reversals or inversions in the original permutation; 4) a previously designed algorithm for block sorting based on another problem, block merging; and 5) a theoretically conjectured more efficient version of the previous algorithm called efficient block merging. We analyze and compare these algorithms for their performance as the order of permutations is varied, using the measures of number of block moves and approximation ratios when sorting kernelized permutations of a given order. We also compare execution time of each algorithm over same set of inputs. Our experiments validate the efficiency of the greedy algorithm for block sorting presented in a companion paper [1], and brings out many practical insights of the problem. To the best of our knowledge this is the first work that is focused on implementation and experimental performance analysis of any existing algorithms for block sorting (e.g. block merging). We believe our results will be useful for researchers and practitioners working in this area.

关键词： Java Merging Approximation algorithms Performance analysis bioinformatics Optimization Sorting

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Predicting Kinase-Substrate Interactions in Medulloblastoma Subtypes

Predicting Kinase-Substrate Interactions in Medulloblastoma ...

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ieee symposium on bioinformatics and bioengineering (BIBE)

作者： Aparna Krishnan Kristin Leskoske Krystine Garcia-Mansfield Ritin Sharma Jessica Rusert Robert Wechsler-Reya Patrick Pirrotte Collaborative Center for Translational Mass Spectrometry Translational Genomics Research Institute Phoenix AZ USA Sanford Burnham Prebys Medical Discovery Institute La Jolla CA USA

ISBN: (数字)9781728195742

ISBN: (纸本)9781728195759

Medulloblastoma (MB), the most common malignant pediatric brain cancer, has four subtypes based on genomics profiling: Wingless (WNT), Sonic Hedgehog (SHH), Group 3, and Group 4. However, subtype heterogeneity and low mutation rates hinder the identification of actionable molecular targets within each group. Studies thus suggest a phosphoproteomics (study of protein phosphorylation), instead of a genomics approach, to better distinguish the MB subgroups. thus, this research will measure MB's irregular protein activity via protein phosphorylation patterns. Protein kinases phosphorylate proteins on specific amino acids, also known as substrates, to regulate their functions. Given that less than 5% of substrates have annotated kinase associations, it is difficult to identify the kinases in MB which irregularly phosphorylate their substrates in order to determine the most effective kinases for drugs to target. As a result, the publicly-available tool NetworKIN was employed to predict novel kinase-substrate interactions in this study to expand the currently limited annotated interactions. For a given dataset of substrates, NetworKIN will output kinase-substrate predictions, each receiving a confidence score (higher score = higher confidence) ranging from zero to the hundreds. To identify a score threshold for high confidence predictions, NetworKIN was run on the substrates in the Human PhosphoSite Plus Database (PSP), the largest curated database of experimentally verified kinase-substrate interactions in humans. three statistical thresholding methods were tested and the optimal cutoff score was determined to lie at 5.88. this threshold was applied to the predictions for the MB dataset, resulting in 774 novel high confidence kinase-substrate interactions. To understand how these interactions altered the enriched kinases across the MB subgroups, kinase activity scores before and after adding the predictions were calculated for all 20 samples using the tool Inference of Ki

关键词： Proteins Genomics Tools Prediction algorithms bioinformatics Substrates Cancer

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