Web Tool Research Articles

Anti‐Epileptic Drug‐Lipid Conjugates for Delivery to the Brain: In Silico ADMET Prediction, Molecular Docking and Molecular Dynamics Simulations

AbstractNeurological disease epilepsy has unfortunately become widespread, affecting around 50 million individuals worldwide. Levetiracetam (LVM) is a newer‐generation drug but its hydrophilic nature restricts its BBB (blood‐brain barrier) permeability. This results in increased dose, dosing frequency, and side effects. Therefore, different lipid‐drug conjugates (LDCs) were studied to identify the compound capable of BBB permeation. The binding potential of LDCs with human brain fatty‐acid binding protein (HBFABP) (PDB id: 1FDQ) was determined by molecular docking through extra‐precision (XP) algorithm of Maestro. In simulations, OPLS3e force field was applied. The ADMET prediction was performed by QikProp and pkCSM web tool. The selected compounds were investigated for LDC‐BFABP complex stability through molecular dynamics (MD) study. All compounds indicated good pharmacokinetic profiles. The LVM‐palmitic acid and LVM‐stearic acid conjugates indicated higher docking scores and greater stability than LVM alone. Thus, they can be selected as potential molecules for further drug development to obtain clinically useful LDC for treatment of CNS disorder.

Lies and Liabilities: Computational Assessment of High-Throughput Screening Hits to Identify Artifact Compounds.

Hits from high-throughput screening (HTS) of chemical libraries are often false positives due to their interference with assay detection technology. In response, we generated the largest publicly available library of chemical liabilities and developed "Liability Predictor," a free web tool to predict HTS artifacts. More specifically, we generated, curated, and integrated HTS data sets for thiol reactivity, redox activity, and luciferase (firefly and nano) activity and developed and validated quantitative structure-interference relationship (QSIR) models to predict these nuisance behaviors. The resulting models showed 58-78% external balanced accuracy for 256 external compounds per assay. QSIR models developed and validated herein identify nuisance compounds among experimental hits more reliably than do popular PAINS filters. Both the models and the curated data sets were implemented in "Liability Predictor," publicly available at https://liability.mml.unc.edu/. "Liability Predictor" may be used as part of chemical library design or for triaging HTS hits.

VenomPred 2.0: A Novel In Silico Platform for an Extended and Human Interpretable Toxicological Profiling of Small Molecules.

The application of artificial intelligence and machine learning (ML) methods is becoming increasingly popular in computational toxicology and drug design; it is considered as a promising solution for assessing the safety profile of compounds, particularly in lead optimization and ADMET studies, and to meet the principles of the 3Rs, which calls for the replacement, reduction, and refinement of animal testing. In this context, we herein present the development of VenomPred 2.0 (http://www.mmvsl.it/wp/venompred2/), the new and improved version of our free of charge web tool for toxicological predictions, which now represents a powerful web-based platform for multifaceted and human-interpretable in silico toxicity profiling of chemicals. VenomPred 2.0 presents an extended set of toxicity endpoints (androgenicity, skin irritation, eye irritation, and acute oral toxicity, in addition to the already available carcinogenicity, mutagenicity, hepatotoxicity, and estrogenicity) that can be evaluated through an exhaustive consensus prediction strategy based on multiple ML models. Moreover, we also implemented a new utility based on the Shapley Additive exPlanations (SHAP) method that allows human interpretable toxicological profiling of small molecules, highlighting the features that strongly contribute to the toxicological predictions in order to derive structural toxicophores.

Overexpressed FAM111B degrades GSDMA to promote esophageal cancer tumorigenesis and cisplatin resistance.

Chemotherapeutic agents such as cisplatin are commonly used in patients with clinically unresectable or recurrent esophageal cancer (ESCA). However, patients often develop resistance to cisplatin, which in turn leads to a poor prognosis. Studies have shown that FAM111B may be involved in the development of tumors as an oncogene or tumor suppressor gene. However, the pathological role and corresponding mechanism of FAM111B in ESCA are still unclear. The GEPIA web tool, ENCORI Pan-Cancer Analysis Platform and UALCAN-TCGA database were used to study the expression of FAM111B in ESCA. CCK-8, angiogenesis, Transwell and xenograft assays were applied to explore the biological function of FAM111B in ESCA. Western blot, RT-qPCR, and RNA-seq analyses were applied to study the FAM111B/GSDMA axis in the progression of ESCA cells. CCK-8 and xenograft assays were used to study the role of the FAM111B/GSDMA axis in determining the sensitivity of ESCA to cisplatin. Our results demonstrated that FAM111B is highly expressed in ESCA tissues compared to normal tissues. We showed that FAM111B promotes the progression of ESCC cells by binding to GSDMA and that the trypsin protease domain is essential for the activity of FAM111B. Furthermore, we showed that the FAM111B/GSDMA axis regulates cisplatin sensitivity in ESCA. Overall, we identified a novel FAM111B/GSDMA axis regulating ESCA tumorigenesis and chemosensitivity, at least in ESCC cells.

Assessment of antidiabetic activity of three Phenylspirodrimanes from fungus Stachybotrys chartarum MUT 3308 by ADME, QSAR, molecular docking and molecular dynamics simulation studies against protein tyrosine phosphatase 1B (PTP1B)

Phenylspirodrimanes (PSD) are the sesquiterpene quinone type meroterpenoids found in nature. PSDs are found to exhibit inhibitory activity against immunocomplex diseases, and tyrosine kinase receptors. Three of the different PSDs C1, C2, and C3 that have been reported to be isolated from the sponge-associated fungus Stachybotrys chartarum MUT 3308 are selected for studying their possible inhibitory effect against type 2 diabetes mellitus. Mechanistically, blocking protein tyrosine phosphatase 1B (PTP1B) helps to reduce the insulin resistance induction caused by the high expression of PTP1B. The QSAR, ADME, toxicity (T) study was carried out to predict the pharmacokinetic properties and the biological activities of the PSDs. PASS prediction web tool was used to find and select the target proteins 1NNY, and 2HNP. According to the molecular docking simulations, C1 and C2 showed better binding affinity of −8.5 kcal/mol, and −8.1 kcal/mol respectively against 1NNY compared to the control ligand. RMSD, RMSF, Rg, and SASA analysis revealed that both C1, and C2 showed better stability, minor conformational changes, and minor fluctuation upon binding to PTP1B. Protein contact analysis was carried out to validate the residues that are in contact with the ligands according to molecular docking studies. Overall, C1, and C2 could be proposed as novel natural hits to be developed and small modifications of these PSDs could result in inducing the binding affinity significantly, although experimental validation is required for further evaluation of the work. Communicated by Ramaswamy H. Sarma

Communicating results and uncertainties of radioecological modelling – a transdisciplinary workshop

Abstract. Compared with geological structures, many processes and fluctuations in the biosphere take place on much shorter timescales and are difficult, often nearly impossible to predict over long periods of time. Consequently, modelling results are subject to tremendous uncertainties. While German regulations require biosphere modelling for dose estimations as part of the site selection procedure for a nuclear waste repository, they also recognize those uncertainties by stating that the calculated dose estimates are not an actual prognosis of the effective dose used in practical radiation protection but merely an indicator for the safety of the repository (BASE, 2022, p. 6). In addition to the complex technical aspects, this subtle but important distinction might pose an additional difficulty in understanding the meaning of dose modelling results and their uncertainties when presented to an interested public. Within a transdisciplinary online workshop on safety indicators in nuclear waste management, relevant aspects for communicating dose estimates and uncertainties were evaluated. As the target group, the Citizens' Working Group (CWG) of the TRANSENS research project was chosen. TRANSENS is a transdisciplinary project addressing socio-technical questions concerning the disposal of nuclear waste (TRANSENS, 2023). As an “extended peer community”, the CWG is an important part of the transdisciplinary research approach (Seidl et al., 2021). Currently, the group consists of 14 citizens with a diverse distribution of age, profession and degree of (scientific) education. By design, citizens with no stakes and no particular expertise concerning nuclear waste or radioactivity were recruited. However, the members of the CWG acquired ever-increasing knowledge about the subject in over 2 years of regular meetings and workshops within the project. Thus, the CWG can be seen as a proxy for members of the public with high interest in nuclear waste disposal but potentially without distinct scientific education. The workshop took place over two days as a virtual meeting and covered the full modelling chain from the confinement providing rock zone to the biosphere. Here, mainly results concerning the radioecological modelling will be presented. As a central element we investigated the use of an interactive web tool to illustrate the effects of parameter uncertainties on dose estimates. The web tool, created specifically for this workshop, consists of some slide controls, allowing the user to select values from a given range for four parameters relevant for biosphere modelling. From the selected parameter combination, a dose estimate based on the biosphere model described in the German regulations (BASE, 2022) is calculated and displayed. Additionally, a probability is displayed for each combination, which results from (not necessarily scientifically accurate) underlying probability distributions assumed for each parameter. This rather abstract numerical value, which varies over many orders of magnitude, is in addition visualized by a density plot. The user is asked to rate the information regarding dose value and probability on a scale from “very concerning” to “very reassuring” in an input form at the lower end of the screen. After an introductory presentation on the concepts of effective dose and radioecological modelling, the participants had time to try out the web tool in breakout rooms of three to four people followed by a free discussion on various aspects connected to the tool. Afterwards, the CWG members were asked to collect decisions that need to be made when designing such a tool together with available options (e.g. “Which colour should the slide controls have” → “red, green, blue …”). For inspiration, two alternative designs were shown as examples. A subsequent multiple-choice survey found that the employment of explanatory information boxes, the indication of (legal) references values and the annotation of the dose axis were perceived as the most important aspects within the group. Each of these questions was then revisited in a silent discussion collecting advantages and disadvantages for multiple options on how to address these issues. In the last part of the workshop, the effective dose was compared to two other safety-related indicators resulting from modelling calculations (porosity of the backfill material and radionuclide concentration in groundwater). For this purpose, the participants were asked to discuss to what extent each of the three indicators matched a number of desirable features identified in a previous part of the workshop. The workshop was planned, conducted and evaluated by a team of engineers and natural scientists with support of CWG's coordination team offering psychological and social–scientific expertise as well as experience from a number of previous workshops with the CWG.

Use of Video Streaming and Video Hosting by US University Libraries to Support Educational and Research Activities

The purpose of the article is to reveal the peculiarities and identify the current problems of using video streaming and video hosting within the framework of the American university libraries aimed to support the educational and scientific activities of students and faculty at the modern stage. The research methodology is based on the application of general scientific and special methods of cognition, in particular, terminological, systematic approach, analysis, synthesis, and logical method. The theory of active systems and theoretical approaches to the formation and functioning of the information and educational environment of the university are also used. The scientific novelty of the article lies in expanding the concept of the university library as a technological system and its contribution to the formation of the information and educational environment of a higher educational institution through such web tools as video streaming and video hosting. Conclusions. In the twenty-first century, university libraries are becoming catalysts of innovation and key structural units of higher educational institutions and “active systems” that increase the efficiency of educational and research activities of faculty and students by creating physical and virtual centres for the consumption and production of knowledge. Based on the analysis of the activities of American universities and colleges at the present stage, it is found that they are actively mastering video streaming and video hosting to support research, teaching and sharing their video collections. The American experience has revealed many progressive steps in the use of video streaming and video hosting by university libraries, as well as current problems related to copyright protection, licensing terms and costs, availability of streaming formats, and image quality. Video streaming and video hosting will continue to play an increasingly important role in the development of video collections of university libraries. Key words: the USA, university library, video streaming, video hosting, library services, video content.

Розробка інтелектуальних інформаційно-аналітичних вебпорталів на основі семантичних вікітехнологій: проблеми та перспективи

We analyse the main functions of modern web portals that differ them from other types of sites. In this work we consider intelligent information-analytical web portals as a specific subset of intelligent information-analytical systems, and their features and development trends that have an influence on their semanticization are analysed. As a part of such analysis we considered knowledge models and technologies of their processing that can be used for this aim. We determine standards and tools of the Semantic Web that can be used for the semanticization of web portals and describe the ways of such use on practical examples. Some basic requirements for technologies and instrumental tools used for development of semantic portals are considered. We analyse and classify typical problems related to the processing, structuring, and analysis of large volumes of data that arise in the process of creating and deploying such portals, and the criteria for evaluating the development opportunities of existing web portals are considered. On example of web portal based on semantic Wiki technologies we investigate practical problems of implementation and scaling of portal knowledge processing tools and services and propose some ways of their prevention and solution.

STNWeb: A new visualization tool for analyzing optimization algorithms

STNWeb (https://www.stn-analytics.com/) is a new web tool for the visualization of the behavior of optimization algorithms such as metaheuristics. It allows for the graphical analysis of multiple runs of multiple algorithms on the same problem instance and, in this way, it facilitates the understanding of algorithm behavior. It may help, for example, in identifying the reasons for a rather low algorithm performance. This, in turn, can help the algorithm designer to change the algorithm in order to improve its performance. STNWeb is designed to be user-friendly. Moreover, it is offered for free to the research community. An article summarizing STNWeb has been recently published in the Software Impacts Journal.

Tabby2: a user-friendly web tool for forecasting state-level TB outcomes in the United States

BackgroundIn the United States, the tuberculosis (TB) disease burden and associated factors vary substantially across states. While public health agencies must choose how to deploy resources to combat TB and latent tuberculosis infection (LTBI), state-level modeling analyses to inform policy decisions have not been widely available.MethodsWe developed a mathematical model of TB epidemiology linked to a web-based user interface — Tabby2. The model is calibrated to epidemiological and demographic data for the United States, each U.S. state, and the District of Columbia. Users can simulate pre-defined scenarios describing approaches to TB prevention and treatment or create their own intervention scenarios. Location-specific results for epidemiological outcomes, service utilization, costs, and cost-effectiveness are reported as downloadable tables and customizable visualizations. To demonstrate the tool’s functionality, we projected trends in TB outcomes without additional intervention for all 50 states and the District of Columbia. We further undertook a case study of expanded treatment of LTBI among non-U.S.–born individuals in Massachusetts, covering 10% of the target population annually over 2025-2029.ResultsBetween 2022 and 2050, TB incidence rates were projected to decline in all states and the District of Columbia. Incidence projections for the year 2050 ranged from 0.03 to 3.8 cases (median 0.95) per 100,000 persons. By 2050, we project that majority (> 50%) of TB will be diagnosed among non-U.S.–born persons in 46 states and the District of Columbia; per state percentages range from 17.4% to 96.7% (median 83.0%). In Massachusetts, expanded testing and treatment for LTBI in this population was projected to reduce cumulative TB cases between 2025 and 2050 by 6.3% and TB-related deaths by 8.4%, relative to base case projections. This intervention had an incremental cost-effectiveness ratio of $180,951 (2020 USD) per quality-adjusted life year gained from the societal perspective.ConclusionsTabby2 allows users to estimate the costs, impact, and cost-effectiveness of different TB prevention approaches for multiple geographic areas in the United States. Expanded testing and treatment for LTBI could accelerate declines in TB incidence in the United States, as demonstrated in the Massachusetts case study.

Why do we do what we do?

In the fifty years since I became a scientist, there have been many changes in the way we work, in the tools we use, in the software we have available to us and much more. But our motivation to “Do what we do” hasn’t really changed at all. A survey carried out many years ago in Brazil asked biologists why they became biologists. Answers included going to the beach with the family and making shell collections and then trying to identify them; being involved in backyard bird surveys; catching butterflies in the local meadows, etc. In my own case, it was working on the farm with my father who, at least to me at the time, knew every native plant in the area as well as the grasses and crop plants. I began collecting and pressing grasses at a young age, and those collections are now housed in the herbaria of the University of New England and James Cook University of North Queensland. I am sure that most of you here have similar stories. In this presentation, I talk about the changes that I have seen over those fifty years in the way we work, including working at the Australian Biodiversity Resources Study (ABRS) on the Australian Plant Name Index (APNI) and the Flora of Australia; the Environmental Resources Information Network (ERIN) on digitisation projects; environmental, species and climate change modelling; data quality and decision support systems; with the Centro de Referência em Informação Ambiental (CRIA) on data quality and niche modelling; and on projects for the Global Biodiversity Information Facility (GBIF), The Global Environment Facility of the World Bank, United Nations Environment Programme (UNEP), Bioversity International, and others on a range of topics including on the conservation of crop wild relatives, reserve selection, rapid biodiversity assessment, data quality, and georeferencing—and, of course, Biodiversity Information Standards (TDWG). I’ll also touch on working with citizen science and tools such as iNaturalist. One key change in the way we work now compared to those early years is in the way we collaborate. A lot of that collaboration has been enhanced and made possible by the Internet: email, the World Wide Web, video conferencing, and chat tools like Zoom. Previously we published some research and then later another person would see that research and add to it, etc. This could take years for advancements to take place. Now, we collaborate: across institutions, countries and across the globe and that has sped up the rate our science can advance. TDWG has been a great example of that collaboration, along with agencies such as GBIF. So where will our science take us over the next fifty years? I have no idea, but the advances are likely to be at least as great as the last fifty, so I envy the young scientists in the audience just starting out and getting to grips with artificial intelligence (AI) and all that is likely to bring. We should be wary of AI—but not scared of it—just like computing fifty years ago. In conclusion, what then motivates us to continue to “Do what we do” well past retirement age? In my own case, my motivation throughout my life, has been to add to the biodiversity knowledge base so that those who come after me start at a far better knowledge level than would otherwise have been the case.

ParSe 2.0: A web tool to identify drivers of protein phase separation at the proteome level.

We have developed an algorithm, ParSe, which accurately identifies from the primary sequence those protein regions likely to exhibit physiological phase separation behavior. Originally, ParSe was designed to test the hypothesis that, for flexible proteins, phase separation potential is correlated to hydrodynamic size. While our results were consistent with that idea, we also found that many different descriptors could successfully differentiate between three classes of protein regions: folded, intrinsically disordered, and phase-separating intrinsically disordered. Consequently, numerous combinations of amino acid property scales can be used to make robust predictions of protein phase separation. Built from that finding, ParSe 2.0 uses an optimal set of property scales to predict domain-level organization and compute a sequence-based prediction of phase separation potential. The algorithm is fast enough to scan the whole of the human proteome in minutes on a single computer and is equally or more accurate than other published predictors in identifying proteins and regions within proteins that drive phase separation. Here, we describe a web application for ParSe 2.0 that may be accessed through a browser by visiting https://stevewhitten.github.io/Parse_v2_FASTA to quickly identify phase-separating proteins within large sequence sets, or by visiting https://stevewhitten.github.io/Parse_v2_web to evaluate individual protein sequences.

Regulation of IGF1R by MicroRNA-15b Contributes to the Anticancer Effects of Calorie Restriction in a Murine C3-TAg Model of Triple-Negative Breast Cancer.

Calorie restriction (CR) inhibits triple-negative breast cancer (TNBC) progression in several preclinical models in association with decreased insulin-like growth factor 1 (IGF1) signaling. To investigate the impact of CR on microRNAs (miRs) that target the IGF1/IGF1R pathway, we used the spontaneous murine model of TNBC, C3(1)/SV40 T-antigen (C3-TAg). In C3-TAg mice, CR reduced body weight, IGF1 levels, and TNBC progression. We evaluated the tumoral expression of 10 miRs. CR increased the expression of miR-199a-3p, miR-199a-5p, miR-486, and miR-15b. However, only miR-15b expression correlated with tumorigenicity in the M28, M6, and M6C C3-TAg cell lines of TNBC progression. Overexpressing miR-15b reduced the proliferation of mouse (M6) and human (MDA-MB-231) cell lines. Serum restriction alone or in combination with low levels of recombinant IGF1 significantly upregulated miR-15b expression and reduced Igf1r in M6 cells. These effects were reversed by the pharmacological inhibition of IGFR with BMS754807. In silico analysis using miR web tools predicted that miR-15b targets genes associated with IGF1/mTOR pathways and the cell cycle. Our findings suggest that CR in association with reduced IGF1 levels could upregulate miR-15b to downregulate Igf1r and contribute to the anticancer effects of CR. Thus, miR-15b may be a therapeutic target for mimicking the beneficial effects of CR against TNBC.

Computer‐aided evaluation of targets and biological activity spectra for new piperidine derivatives

<b>Background:</b> The unique ability of piperidine to combine with various molecular fragments makes it possible to use its chemical structure to create new drugs with potential pharmacological effects. However, preliminary studies are required to predict the activity of new compounds in order to determine the direction of further preclinical studies.<br /> <b>Aim: </b>This study aims at determining the potential targets and spectrum of biological activity of new piperidine derivatives by the <i>in silico</i> method.<br /> <b>Material and methods: </b>Prediction of the effects on targets and the spectrum of biological activity of three new piperidine derivatives synthesized at the Bekturov Institute of Chemical Sciences JSC was analyzed in this study. The chemical structures of these compounds were studied <i>in silico</i> using the web tool SwissTargetPrediction to identify the most likely protein targets. PASS (Prediction of Activity Spectra for Substances) online tool was used to predict the possible pharmacological activity of the studied compounds.<br /> <b>Results: </b>New modified piperidine derivatives are able to affect different enzymes, receptors, transport systems, voltage-gated ion channels, thereby providing a wide range of biological activities applicable in various fields of medicine. These substances represent interest in the treatment of cancer, central nervous system diseases, as local anesthetic, antiarrhythmic and antimicrobial agents, and are promising for pharmacological activity demonstration in preclinical studies.<br /> <b>Conclusion</b>: A comprehensive analysis of the above results leads to the conclusion that the compounds under study should be considered as potential substances for the design of new highly effective medicinal agents with a wide range of practical applications.

A three-stage eccDNA based molecular profiling significantly improves the identification, prognosis assessment and recurrence prediction accuracy in patients with glioma

Glioblastoma (GBM) progression is influenced by intratumoral heterogeneity. Emerging evidence has emphasized the pivotal role of extrachromosomal circular DNA (eccDNA) in accelerating tumor heterogeneity, particularly in GBM. However, the eccDNA landscape of GBM has not yet been elucidated. In this study, we first identified the eccDNA profiles in GBM and adjacent tissues using circle- and RNA-sequencing data from the same samples. A three-stage model was established based on eccDNA-carried genes that exhibited consistent upregulation and downregulation trends at the mRNA level. Combinations of machine learning algorithms and stacked ensemble models were used to improve the performance and robustness of the three-stage model. In stage 1, a total of 113 combinations of machine learning algorithms were constructed and validated in multiple external cohorts to accurately distinguish between low-grade glioma (LGG) and GBM in patients with glioma. The model with the highest area under the curve (AUC) across all cohorts was selected for interpretability analysis. In stage 2, a total of 101 combinations of machine learning algorithms were established and validated for prognostic prediction in patients with glioma. This prognostic model performed well in multiple glioma cohorts. Recurrent GBM is invariably associated with aggressive and refractory disease. Therefore, accurate prediction of recurrence risk is crucial for developing individualized treatment strategies, monitoring patient status, and improving clinical management. In stage 3, a large-scale GBM cohort (including primary and recurrent GBM samples) was used to fit the GBM recurrence prediction model. Multiple machine learning and stacked ensemble models were fitted to select the model with the best performance. Finally, a web tool was developed to facilitate the clinical application of the three-stage model.

BLASTphylo: An Interactive Web Tool for Taxonomic and Phylogenetic Analysis of Prokaryotic Genes.

Identifying a protein's function is crucial to reveal its role in the cellular complex. Computationally, the most common approach is to search for homologous proteins in a large database of proteins of known function using BLAST. One goal of such an analysis is the identification and visualization of the protein in the taxonomy of interest. Another goal is the reconstruction of the phylogenetic history of the protein. However, the BLAST result provides information about the occurrence of the protein in the taxonomy and its putative function mainly in a tabular format. This requires manual interventions and makes the taxonomic identification laborious. Although various tools exist to visualize and annotate large-scale trees, none of them intuitively and interactively visualizes the protein's occurrence in the taxonomy for different taxonomic ranks. To target this gap, we developed BLASTphylo, a web tool that combines BLAST with automatic taxonomic mapping and phylogenetic analysis and provides the results in interactive visualizations. We demonstrate the functionalities of BLASTphylo in two case studies.

EasySSR: a user-friendly web application with full command-line features for large-scale batch microsatellite mining and samples comparison.

Microsatellites, also known as SSRs or STRs, are polymorphic DNA regions with tandem repetitions of a nucleotide motif of size 1-6 base pairs with a broad range of applications in many fields, such as comparative genomics, molecular biology, and forensics. However, the majority of researchers do not have computational training and struggle while running command-line tools or very limited web tools for their SSR research, spending a considerable amount of time learning how to execute the software and conducting the post-processing data tabulation in other tools or manually-time that could be used directly in data analysis. We present EasySSR, a user-friendly web tool with command-line full functionality, designed for practical use in batch identifying and comparing SSRs in sequences, draft, or complete genomes, not requiring previous bioinformatic skills to run. EasySSR requires only a FASTA and an optional GENBANK file of one or more genomes to identify and compare STRs. The tool can automatically analyze and compare SSRs in whole genomes, convert GenBank to PTT files, identify perfect and imperfect SSRs and coding and non-coding regions, compare their frequencies, abundancy, motifs, flanking sequences, and iterations, producing many outputs ready for download such as PTT files, interactive charts, and Excel tables, giving the user the data ready for further analysis in minutes. EasySSR was implemented as a web application, which can be executed from any browser and is available for free at https://computationalbiology.ufpa.br/easyssr/. Tutorials, usage notes, and download links to the source code can be found at https://github.com/engbiopct/EasySSR.

The Use of Quizizz as Istiqraiyah-Based Nahwu Learning Media in the Digital Age

In this Digital Era, educators are required to integrate science and technology in all aspects of learning to create effective learning and make it easier for students to understand the material; besides that, with this technology, students can easily find sources of knowledge. One of the Web Tools that are suitable for learning in this Era is Quizizz. This study aims to determine the steps of using Quizizz as an Istiqraiyah-based nahwu learning medium in the Digital Age and to analyze students' perceptions of using Quizizz as an Istiqraiyah-based nahwu learning medium in the Digital Age. This study uses a descriptive qualitative approach. The data collection technique uses documentation and questionnaires. After the data is collected, a descriptive analysis is carried out using: 1) data collection, 2) data reduction, 3) data presentation and 4) conclusion/verification. The results of this study show the steps in using Quizizz as an Istiqraiyah-based nahwu learning media as follows: a). present an example, b). instructed to analyze the example, c). conclude from the examples observed d). make examples related to the material, e). give a quiz using quizizz f). directions for doing g). monitored the results of the answers and the majority of students responded positively to using Quizizz as an Istiqraiyah-based nahwu learning medium in this Digital Age.

Identification and validation of SERPINE1 as a prognostic and immunological biomarker in pan-cancer and in ccRCC.

Background: SERPINE1, a serine protease inhibitor involved in the regulation of the plasminogen activation system, was recently identified as a cancer-related gene. However, its clinical significance and potential mechanisms in pan-cancer remain obscure. Methods: In pan-cancer multi-omics data from public datasets, including The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx), and online web tools were used to analyze the expression of SERPINE1 in different cancers and its correlation with prognosis, genetic alteration, DNA promoter methylation, biological processes, immunoregulator expression levels, immune cell infiltration into tumor, tumor mutation burden (TMB), microsatellite instability (MSI), immunotherapy response and drug sensitivity. Further, two single-cell databases, Tumor Immune Single-cell Hub 2 (TISCH2) and CancerSEA, were used to explore the expression and potential roles of SERPINE1 at a single-cell level. The aberrant expression of SERPINE1 was further verified in clear cell renal cell carcinoma (ccRCC) through qRT-PCR of clinical patient samples, validation in independent cohorts using The Gene Expression Omnibus (GEO) database, and proteomic validation using the Clinical Proteomic Tumor Analysis Consortium (CPTAC) database. Results: The expression of SERPINE1 was dysregulated in cancers and enriched in endothelial cells and fibroblasts. Copy number amplification and low DNA promoter methylation could be partly responsible for high SERPINE1 expression. High SERPINE1 expression was associated with poor prognosis in 21 cancers. The results of gene set enrichment analysis (GSEA) indicated SERPINE1 involvement in the immune response and tumor malignancy. SERPINE1 expression was also associated with the expression of several immunoregulators and immune cell infiltration and could play an immunosuppression role. Besides, SERPINE1 was found to be related with TMB, MSI, immunotherapy response and sensitivity to several drugs in cancers. Finally, the high expression of SERPINE1 in ccRCC was verified using qRT-PCR performed on patient samples, six independent GEO cohorts, and proteomic data from the CPTAC database. Conclusion: The findings of the present study revealed that SERPINE1 exhibits aberrant expression in various types of cancers and is associated with cancer immunity and tumor malignancy, providing novel insights for individualized cancer treatment.

Implementation and evaluation of a complex intervention to improve information availability at the interface between inpatient and outpatient care in older patients with multimorbidity and polypharmacy (HYPERION-TransCare) — study protocol for a pilot and feasibility cluster-randomized controlled trial in general practice in Germany

BackgroundDespite attempts to improve the cross-sectoral flow of information, difficulties remain in routine healthcare. The resulting negative impact on continuity of care is often associated with poor health outcomes, especially in older patients. Our intervention aims to increase information availability with respect to medications and health conditions at the interface between inpatient and outpatient care and to contribute towards improving the quality of care in older patients. This pilot study focuses on feasibility and implementability.MethodsThe idea of the complex intervention has been developed in a previous study. This intervention will be tested in a prospective, multicenter, cluster-randomized (via web tool), controlled pilot trial with two parallel study arms (intervention and control group). The pilot study will be conducted in 20 general practices in Hesse and Saxony (Germany) and include 200 patients (≥ 65 years of age with multimorbidity and polypharmacy) recruited by the practices. Practice staff and patients will be blinded. We will use qualitative and quantitative methods to assess the feasibility and implementability of the intervention and the study design in a process evaluation covering topics ranging from expectations to experiences. In addition, the feasibility of proposed outcome parameters for the future definitive trial will be explored. The composite endpoint will include health-related patient outcomes (hospitalization, falls, and mortality using, e.g., the FIMA questionnaire), and we will assess information on medications (SIMS questionnaire), symptoms and side effects of the medication (pro-CTCAE questionnaire), and health literacy (HLQ questionnaire).Data will be collected at study begin (baseline) and after 6 months. Furthermore, the study will include surveys and interviews with patients, general practitioners, and healthcare assistants.DiscussionThe intervention was developed using a participatory approach involving stakeholders and patients. It aims to empower general practice teams as they provide patient-centered care and play a key role in the coordination and continuity of care. We aim to encourage patients to adopt an active role in their health care. Overall, we want to increase the availability of health-related information for patients and healthcare providers. The results of the pilot study will be used in the design and implementation of the future definitive trial.Trial registrationThe study was registered in DRKS-German Clinical Trials Register: registration number DRKS00027649 (date: 19 January 2022).Date and version identifier10.07.2023; Version 1.3