Web Tool Research Articles

Exploring the Credibility and Trustworthiness of Web 2.0 Tools during Covid-19 from the Eyes of Information Providers

Background: In addition to posing serious obstacles to international health systems, the coronavirus (COVID-19) has created a deluge of false information. During COVID-19, the librarian must have the most recent information available in their capacity as an information manager. The use and methods used by librarians to assess the validity of information and the legitimacy of Web 2.0 technology providers are examined in this study. Aim: Using a survey approach, the reliability and trustworthiness of web tools were investigated in this quantitative study during COVID-19. Method: The study's 82% response rate was sustained. In terms of representation, men remained in the majority over women. Study population: Pakistani university librarians in the public sector. It's clear that the bulk of responders 59.48% attend universities in Punjab, followed by those in Islamabad (17.24%), KPK (13.79%), Sindh (6.9%), Balochistan 1.72%), and GilgitBaltistan 0.86%. Results: The results demonstrate that web 2.0 tools had a significant impact on librarians' knowledge of health information seeking behaviors during COVID-19; however, the information they accessed on social media during the pandemic was shared information about the disease and came from discussion groups. Among other things, during COVID, web 2.0 tools' credibility and trustworthiness greatly improved, and the importance of message credibility also increased. Conclusion: The study found that web 2.0 tools for health information during Covid-19 were mainly trusted by information professionals, with discussion groups on social media being the main source of health information. The majority of respondents (59.48%) were aged 26-35, with a high trustworthiness ratio in Balochistan, Sindh, and Punjab. The study also found a high ratio in Sindh. Key words: Trustworthiness, Credibility, Web 2.0 tools, Information Providers, health information

The Current Status and Potential Development of Genetic Resources of Indigenous Toraya Spotted Buffalo in Indonesia: A Systematic Review

Buffaloes are integral to the Asiatic market as they are crucial for agricultural work and transportation and provide a significant source of dairy and meat, contributing to various industries, local economies, and cultural practices across the region. Indonesia is a mega biodiversity country abundant in livestock genetic resources, including indigenous, local, and introduced breeds that play a crucial role in agriculture and the livestock industry. These genetic resources offer the potential for selective breeding and improving the quality of livestock populations through well-designed breeding programs, ensuring sustainable livestock production for the future. The current study was performed using the “Publish or Perish” software, and the data obtained was analyzed using the CADIMA web tool. The Toraya buffalo population is the largest in the Tana Toraja and North Toraja regencies and is widely distributed within South Sulawesi Province, Indonesia. The population of Toraya buffalo in this region reached 43674 heads. Toraya buffaloes exhibit diverse body color characteristics, such as black, gray, white, and mixed. Moreover, Toraya buffaloes possess distinct quantitative traits that set them apart from other swamp buffalo breeds. Although there are limited studies on Toraya buffaloes, the potential for broader and more comprehensive studies offers opportunities to uncover new information on the characteristics, genetics, reproduction, health, and management of Toraya buffaloes. The development of Toraya buffalo farms also holds significant economic promise, as it can lead to increased agricultural productivity and improved livelihoods for local communities by enhancing the quality by implementing well-planned breeding programs and leveraging reproductive technology, and genetics-based selection, growth, and productivity can be produced. To increase the population and productivity of Toraya buffaloes, a well-structured breeding program integrating reproductive technology and selection based on quantitative and molecular genetics is essential. The development potential of Toraya buffalo is vast, not only due to its high cultural value but also its superior quantitative traits compared to common swamp buffalo, positioning it as a potential national meat provider. The present review article aimed to discuss the characteristics and development potential of Toraya buffaloes, along with the implementation of reproductive biotechnology and molecular genetics to enhance the population, productivity, and quality of Toraya buffaloes in Indonesia.

The Effectiveness of Web 2.0 Tools Training Workshop Using Canva and Figma in Developing Creative Visual Content

The Effectiveness of Web 2.0 Tools Training Workshop Using Canva and Figma in Developing Creative Visual Content

Unveiling promising immunogenic targets in Coxiella burnetii through in silico analysis: paving the way for novel vaccine strategies

BackgroundCoxiella burnetii, an intracellular pathogen, serves as the causative agent of zoonotic Q fever. This pathogen presents a significant threat due to its potential for airborne transmission, environmental persistence, and pathogenicity. The current whole-cell vaccine (WCV) utilized in Australia to combat Q fever exhibits notable limitations, including severe adverse reactions and limited regulatory approval for human use. This research employed the reverse vaccinology (RV) approach to uncover antigenic proteins and epitopes of C. burnetii, facilitating the development of more potent vaccine candidates.MethodsThe potential immunogenic proteins derived from C. burnetii RSA493/Nine Mile phase I (NMI) were extracted through manual, automated RV, and virulence factor database (VFDB) methods. Web tools and bioinformatics were used to evaluate physiochemical attributes, subcellular localization, antigenicity, allergenicity, human homology, B-cell epitopes, MHC I and II binding ratios, functional class scores, adhesion probabilities, protein-protein interactions, and molecular docking.ResultsOut of the 1850 proteins encoded by RSA493/NMI, a subset of 178 demonstrated the potential for surface or membrane localization. Following a series of analytical iterations, 14 putative immunogenic proteins emerged. This collection included nine proteins (57.1%) intricately involved in cell wall/membrane/envelope biogenesis processes (CBU_0197 (Q83EW1), CBU_0311 (Q83EK8), CBU_0489 (Q83E43), CBU_0939 (Q83D08), CBU_1190 (P39917), CBU_1829 (Q83AQ2), CBU_1412 (Q83BU0), CBU_1414 (Q83BT8), and CBU_1600 (Q83BB2)). The CBU_1627 (Q83B86 ) (7.1%) implicated in intracellular trafficking, secretion, and vesicular transport, and CBU_0092 (Q83F57) (7.1%) contributing to cell division. Additionally, three proteins (21.4%) displayed uncharacterized functions (CBU_0736 (Q83DJ4), CBU_1095 (Q83CL9), and CBU_2079 (Q83A32)). The congruent results obtained from molecular docking and immune response stimulation lend support to the inclusion of all 14 putative proteins as potential vaccine candidates. Notably, seven proteins with well-defined functions stand out among these candidates.ConclusionsThe outcomes of this study introduce promising proteins and epitopes for the forthcoming formulation of subunit vaccines against Q fever, with a primary emphasis on cellular processes and the virulence factors of C. burnetii.

The Role of β-Defensin 1 Against Porphyromonas gingivalis Lipopolysaccharide-Mediated Inflammation in the THP-1 Cell Line.

Introduction Porphyromonas gingivalis lipopolysaccharide (Pg-LPS) is one of the crucial virulence factors of periodontitis. Antimicrobial peptides (AMPs) are emerging as alternatives or adjuncts to antibiotics in the treatment of microbial infections. In this study, cytotoxicity, anti-inflammatory activity, anti-oxidative stress, cell cycle analysis, and apoptosis properties of AMP, β-defensin 1, were studied in Pg-LPS-stimulated THP-1 (Tohoku Hospital Pediatrics - 1) cell line. Methods The cytotoxic nature of Pg-LPS and β-defensin 1 was studied by the MTT (3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide) method. The cytotoxic effect of β-defensin 1 on Pg-LPS-stimulated THP-1 cells was also studied by the same method. The anti-inflammatory role of β-defensin 1 against cyclooxygenase (COX), lipoxygenase (LOX), myeloperoxidase (MPO), and inducible nitric oxide synthase activities were studied. The anti-oxidative nature of β-defensin 1 was analyzed by measuring reactive oxygen species (ROS) generation by dichlorodihydrofluorescein diacetate (DCFDA) assay. Cell cycle distribution and apoptosis were studied by flow cytometry. The hemolytic nature of β-defensin 1 was predicted using the HemoPred web tool. Results The results of the study demonstrated that Pg-LPS showed dose-dependent cytotoxicity to THP-1 cells. β-Defensin 1 had dose-dependent cytotoxicity to THP-1 cells and showed a protective effect on THP-cells up to 1 µg/mL of Pg-LPS, beyond which cell viability decreased. β-Defensin 1 inhibited COX, LOX, MPO, and inducible nitric oxide synthase activities in a concentration-dependent manner. β-Defensin 1 showed anti-oxidative activity by suppressing the generation of ROS measured through fluorescence intensity. From the cell cycle analysis, it was found that β-defensin 1 was able to reduce the Pg-LPS-induced cell cycle arrest at the G0/G1 phase. From the apoptosis profile, β-defensin 1 was found to increase the live cells when compared to THP-1 cells stimulated only with Pg-LPS, indicating that β-defensin 1 provided a protective role to THP-1 cells. β-Defensin 1 was found to be hemolytic in nature by the HemoPred web tool. Conclusion β-Defensin 1 exerted multifunctional activities and can be considered a promising agent for controlling periodontitis.

PIMFP: An accurate tool for the prediction of intramuscular fat percentage in live pigs using ultrasound images based on deep learning

Intramuscular fat (IMF) percentage is the proportion of fat between the muscle fibers of the loin eye, which contributes significantly to the flavor and tenderness of the pork. Traditional IMF percentage is measured after slaughter, which requires a high cost, and the slaughtered pig with high IMF percentage can not be directly retained for breeding. Instead of slaughter, using ultrasound images to predict IMF percentage has been gradually proposed as an alternative measurement. However, due to the high cost of dataset construction and limited feature extraction capability of traditional image analysis methods, there is still a lack of an accurate and robust method based on the large-scale dataset for predicting IMF percentage. Here, to establish an accurate model for non-invasive prediction of IMF percentage in pigs, a total number of 4,552 ultrasound images and their corresponding IMF percentage of 945 pigs are collected in this study. We proposed a general-purpose model, PIMFP, to accurately predict IMF percentage based on the deep convolutional neural network. The PIMFP model comprises three primary modules: image preprocessing, feature extraction, and IMF percentage prediction. The preprocessing procedures for the raw ultrasound images include channel conversion, region of interest selection, and contrast enhancement. The feature extraction module characterizes the preprocessed images using the residual neural network as the backbone to extract features. The image features are then delivered to the IMF percentage prediction module depending on the fully connected layer. Our proposed model exhibits significant advantages over existing models in predictive performance, computational speed, classification ability, robustness, and interpretability. For easier use, we also provide a user-friendly web tool for predicting IMF percentage automatically in a single step. In conclusion, our study demonstrates the power of the PIMFP model for predicting IMF percentage, which has great potential in future breeding and highlights the application of artificial intelligence algorithms in livestock.

The Impact of the Application of rhe Online Teaching Model on the Development of Digital Competencies of Future Preschool Teachers

In this study, the influence of the application of an online teaching model on the development of digital cometences of future teachers in preschool institutions was examined. The research that this study deals with was carried out on a sample consisting of N=125 students of the 3rd year of basic academic and professional studies in the study program of teacher in preschool institutions. As a research instrument, a five-point Likert-type scale of attitudes was used. The results show that there is a statistically significant difference in the attitudes of future teachers in preschool institutions when it comes to self-assessment of digital competencies before and after the implementation of online classes during the state of emergency in Serbia during the Sars-Cov-2 virus pandemic. The conclusion of the study is that the implementation of online teaching in processing the content of the Methodology of getting to know the environment affects the improvement of the digital competences of future educators when it comes to: 1) creating digital resources; 2) application of digital technologies in immediate educational work; 3) the role of digital technologies in professional development. The results of this research can be used to encourage teachers to step out of the usual pre-pandemic practice and enrich their pedagogical work with combined teaching (hybrid model) where part of the material would be analyzed in person, and part would be analyzed online using web tools, websites and videoconferencing applications.

In-silico Prediction Analysis of Polyphenolic Contents of Ethanolic Extract of Moringa oleifera Leaves

Introduction: Moringa oleifera is widely consumed as a source of nutrients and as traditional medicine for treating myriads of diseases in Southeast Asia, Africa, and South America. Polyphenols are abundantly found in the leaves of Moringa oleifera, particularly astragalin and quercetin, and have shown antioxidant and anti-inflammatory activities. In the present study, the polyphenols in Moringa oleifera leaves were identified and quantified, followed by in-silico pharmacokinetics prediction. Methods: Moringa oleifera ethanolic leaf extract (MOEE) was prepared by macerating dry powdered leaves of Moringa oleifera in 70% ethanol, then subjected to ultra-high-performance liquid chromatography-mass spectrometry (UPHLC-MS/MS) to identify polyphenols and quantification by HPLC. In-silico pharmacokinetic prediction analysis of the polyphenols was performed using the SwissADME web tool. Results: Eight polyphenols were identified, among which astragalin and quercetin were quantified. In-silico prediction analysis using SwissADME demonstrates the drug-likeness of the polyphenols in MOEE based on their physicochemical and ADME (absorption, distribution, metabolism and excretion) properties. MOEE contains polyphenols that can serve as lead compound to developing drugs, but only some are predicted to have high GI absorption index demonstrating their utility in oral medication drug development. Moreover, all the polyphenols determined in this study are predicted to be non-brain permeant, demonstrating their limited utility in developing drugs that target brain-related pathologies. Conclusion: Eight polyphenols were identified by UHPLC/MS analysis of Moringa oleifera leaves. Their ADME pharmacokinetics properties predicted some of the polyphenols as favourable candidates for drug development and lead optimisation, thus positioning the Moringa oleifera as an important source of small molecules for drug development.

Automated crack detection and a web tool using image processing techniques in concrete structures

Cracks indicates the real time deformity in concrete structures. It is characterized as discontinuity in terms of shape and size of the concrete structures. To ensure the structural health and safety, crack detection is an important task. The traditional methods of crack detection include visual introspection, ultrasonic and hand-held testing of crack. These methods require a high human intervention along with an experienced and skilled inspector. Moreover, these methods are subjective and time-consuming process which fails to identify the crack of the complex concrete structures properly. To overcome these issues, a grab-cut with improved Sobel has been proposed for automatic crack detection from the concrete structures. The proposed method works as a two-step model where cracks regions are segmented in the first step and a precise crack assessment is performed in the second step. Furthermore, to improve the efficacy of Sobel, the mask is modified with the aid of local variance of the image instead of using conventional mask of the filter. For the experimentation study, the images of self-prepared concrete sample have been acquired. The effectiveness of the proposed method has been compared with respect to various pre-existing methods like Sobel, Prewitt, Robert, LoG, Zero Cross and Canny. The comparative qualitative result exhibits that the proposed method surpasses the outcomes of the other pre-existing methods. Additionally, for easy implementation and application point of view a web tool of the proposed method has been developed. The web tool can be utilised by the civil infrastructure maintenance agency and construction engineers in the task of structure maintenance.

Enhancement the Security by creating ontology-based Trust Management using Semantic Web tools

The most traditional policy models which do not consider dynamic nature of distribute systems and the limitation in addressing issues like adaptability, extensibility, and reasoning over security policies. The main cause of the flexibility and scalability issues in the environments of the Internet and dynamic networks is that there is no central control over the environments, and users are not predetermined. As a result, security and trust issues become critical in the various systems; enhancing the security of these environments would require adding trust to the existing security infrastructures. Few trust models have taken into account the semantic relationship for pervasive elements, despite the fact that numerous models have been proposed to address trust issues in dynamic environments; especially those who related to trust categories. In our work, we solve issues resulted from security and tracking the dynamics of participating communication devices in dynamic distributed networks. Through using ontology for trust management which it is define vocabularies used to described and represented an area of knowledge. For representation, we used semantic web's tools to represent the domain of the dynamic environment and we improv that the reasoning succusses in inference the trusted device and user exactly where we do query.

Toxicological Profiling of Potential Shikimate Kinase Inhibitors Against Mycobacterium tuberculosis.

Over the last decade, Mycobacterium tuberculosis has mutated into a putative 'superbug', as treatments against it have failed due to increasing antimicrobial resistance. As a result, the rising incidence of multidrug-resistant tuberculosis (MDR-TB) is posing a significant public health threat, thus, the need to develop effective drugs for MDR-TB has become an urgent priority. To identify new drug candidates for the treatment of MDR-TB, the present study was based on mycobacterial shikimate kinase (MtSK) as the pharmacological target. One hundred potential MtSK inhibitors were identified from literature and database searches to identify compounds that were designed to specifically function as MtSK antagonists. The ADME properties of these compounds were evaluated by using the SwissADME web tool. ProTox-II software was also used to investigate any potential endocrine disrupting effects, mediated through their interaction with oestrogenic and/or androgenic receptors. This study also aimed to predict LD50 values of potential drug candidates that would be active against the standard H37Rv strain of M. tuberculosis, by using the ProTox-II in silico tool. The molecules for which no structural hazard alerts were identified with these software tools were further subjected to molecular docking analyses and molecular dynamic simulations to estimate their ability to interact with the MtSK enzyme. Preliminary results from SwissADME indicated that 30 molecules were drug-like, due to their physicochemical and pharmacokinetic properties. However, subsequent analysis with ToxTree and ProTox-II indicated that only three of these 30 drug-like molecules were suitable for taking forward into further in vitro experiments. This study, which is based on the use of commonly used open-source in silico tools, identified new MtSK ligands for potential use in the development of new drugs for the therapeutic management of tuberculosis. An initial prediction of their safety profile was also generated.

Molecular Docking Studies of Boron‐Containing Compounds as Dual Inhibitors of SARS‐Cov‐2 Spike Receptor Binding Domain/ACE2 Complex and Main Protease and ADMET Investigations

AbstractThe severe acute respiratory syndrome SARS‐CoV‐2 is the causative agent of COVID‐19. Preventing binding of SARS‐CoV‐2 Spike glycoprotein to human ACE2 enzyme and inhibition of MPRO enzyme are still attractive drug targets for treatment of COVID‐19 infection. Boron atom‐containing compounds show anticancer, antibacterial, antiviral, antifungal, antiparasitic, anti‐inflammatory, antituberculosis, anti‐dermatophytic and anti‐fertility activities. In the current study, the ADMET properties of ligands were calculated by the aim of SwissADME and pkCSM pharmacokinetics web tools. The results revealed that the ligands meet drug‐likeness properties. Furthermore, we have performed molecular docking study of boron containing dioxaborepine and oxadiazaborole derivatives to investigate binding properties of ligands against SARS‐CoV‐2 Spike glycoprotein/ACE2 complex and inhibition of MPRO enzyme. Through the ligands a derivative of dioxaborepine showed best binding score against SARS‐CoV‐2 Spike glycoprotein/ACE2 complex with a binding score of −8.93 kcal/mol and a oxadiazaborole derivative exhibited a binding score value of −8.36 kcal which is the best binding ligand to the MPRO enzyme binding site. The analysis of binding poses of ligands and ligand‐residue interactions of the systems revealed that dioxaborepines and oxadiazaboroles could have block binding of Spike glycoprotein to human ACE2 enzyme and could have inhibition effects on MPRO enzyme.

Drug Responses in Plexiform Neurofibroma Type I (PNF1) Cell Lines Using High-Throughput Data and Combined Effectiveness and Potency.

Background: Neurofibromatosis type 1 (NF1) is a genetic disorder characterized by heterozygous germline NF1 gene mutations that predispose patients to developing plexiform neurofibromas, which are benign but often disfiguring tumors of the peripheral nerve sheath induced by loss of heterozygosity at the NF1 locus. These can progress to malignant peripheral nerve sheath tumors (MPNSTs). There are no approved drug treatments for adults with NF1-related inoperable plexiform neurofibromas, and only one drug (selumetinib), which is an FDA-approved targeted therapy for the treatment of symptomatic pediatric plexiform neurofibromas, highlighting the need for additional drug screening and development. In high-throughput screening, the effectiveness of drugs against cell lines is often assessed by measuring in vitro potency (AC50) or the area under the curve (AUC). However, the variability of dose-response curves across drugs and cell lines and the frequency of partial effectiveness suggest that these measures alone fail to provide a full picture of overall efficacy. Methods: Using concentration-response data, we combined response effectiveness (EFF) and potency (AC50) into (a) a score characterizing the effect of a compound on a single cell line, S = log[EFF/AC50], and (b) a relative score, ΔS, characterizing the relative difference between a reference (e.g., non-tumor) and test (tumor) cell line. ΔS was applied to data from high-throughput screening (HTS) of a drug panel tested on NF1-/- tumor cells, using immortalized non-tumor NF1+/- cells as a reference. Results: We identified drugs with sensitivity, targeting expected pathways, such as MAPK-ERK and PI3K-AKT, as well as serotonin-related targets, among others. The ΔS technique used here, in tandem with a supplemental ΔS web tool, simplifies HTS analysis and may provide a springboard for further investigations into drug response in NF1-related cancers. The tool may also prove useful for drug development in a variety of other cancers.

Software for evaluation of immune cell activation (Application note)

Biological processes involving immune response exhibit nonlinearity due to complex interactions between different cells. The presented mathematical model considers the temporal development of immune reactions, and corresponding kinetic processes, including the interaction of cells/soluble immune factors in vitro. According to the M1/M2 paradigm of macrophage polarization, unbalanced macrophage activation in the human body can cause an excessive response to an antigen and associated long-term deleterious processes. Therefore, our simulation is based on the evaluation of parameters that describe the interaction of diverse immune factors interconnected within the framework of the M1/M2 paradigm, and taking into account the kinetics of expression of immune factors. A specific program and related web tool to assess the intensity of immune reactions in cell system in vitro were developed. AvailabilityIt is accessible through a web-link: https://www.biodevicesystems.com/immunology. ContactUsers can get information and apply for the service at info@biodevicesystems.com.

USE OF KAHOOT! AND JAMBOARD FOR THE REALIZATION AND ORGANIZATION OF CREATIVE SCHOOL ACTIVITIES DURING THE COVID-19 PANDEMIC

This mixed study analyzes the students’ perception about the use of Kahoot! and Jamboard in the teaching–learning process about the English language during the COVID-19 pandemic through data science. Kahoot! is a web tool that facilitates and promotes the participation between the educator and students through the realization of digital games and Jamboard is a virtual wall that allows the active role through the dissemination of information and exchange of ideas. The participants are 30 students of Design and Visual Communication who took the English Language course in the distance modality at the National Autonomous University of Mexico, Mexico, during the 2020 school year. The results of the machine learning technique indicate that the realization of digital games in Kahoot! and the dissemination and exchange of information in Jamboard positively influence the motivation, assimilation of knowledge and participation of the students during the Verbs Unit. Data science identified 6 predictive models on the use of these technological tools in the educational process about the English language through the decision tree technique. Finally, educators have the opportunity to create new virtual spaces and promote the active role of the students by incorporating Kahoot! and Jamboard in the school activities during the COVID-19 pandemic.

Circular RNAs Associated with Idiopathic Parkinson’s Disease: Case/Control Study Results on PPMI Dataset

AbstractBackgroundPD is the second most common neurodegenerative disease after AD, for which biomarkers do not exist. We aimed identify circular RNAs associated with Parkinson’s Disease (PD) in a longitudinal dataset and test their potential as Bioamrkers.MethodWe included 2507 European ancestry blood samples from PPMI participants, with transcriptomic data available and distributed across five time‐points. We aligned reads to the reference genome (GRCh38) using STAR in chimeric alignment mode. Annotation and quantification of circRNAs were performed using DCC, followed by a cross‐sectional differential expression analyses for each visit using DESeq2. Significance was assessed and corrected by FDR at the last visit, with nominal p‐value for the remaining visits. We used Circular RNA Interactome web tool to predict microRNA (miRNA) target sites within significantly dysregulated circRNAs. Subsequently, we performed pathway analyses using DIANA tools.ResultTwo circRNAs were significantly dysregulated in PD across all visits: circRHBDD1 (p = 3.34´10−4, Log2FC = ‐0.13) and circDHRSX (p = 1.03´10−3, Log2FC = 0.4). We identified twenty miRNAs that putatively interact with circRHBDD1. Pathway analyses showed that fourteen of them are involved in the Hippo signaling pathway, fifteen in oxytocin signaling pathway, and sixteen in the ErbB1 signaling pathway. We also identified one hundred and twenty‐eight miRNAs interacting with circDHRSX that are also part of the Hippo signaling pathway.ConclusionWe identified circRHBDD1 and circDHRSX to be dysregulated in PD across time. Both of them are enriched in binding sites for miRNAs that target the Hippo and ErbB1 signaling pathways. ErbB1 has already been associated with PD in brain studies, whereas the Hippo pathway is associated to neuronal cell death. We are conducting additional analyses in independent datasets and using mixed models to replicate the results and obtain the best predictive models.

Abstract A035: Comparing the clinical and genomic landscapes of acral, mucosal, and cutaneous metastatic melanomas treated with immune checkpoint inhibitors

Abstract Background: Melanoma is a melanocytic malignancy that is classified into different subtypes, including cutaneous (CM), acral (AM), and mucosal melanoma (MM). Immune checkpoint inhibitors (ICI) targeting PD-1 and/or CTLA-4 have emerged as the standard of care for advanced metastatic melanoma. We investigated responses to ICIs, genomic profiles, and molecular differences among these different subtypes of melanoma. Methods: We performed a multi-center retrospective cohort study including patients with metastatic melanoma who received anti-PD1 +/- CTLA4 inhibitor ICI for metastatic disease. We employed the AACR GENIE (v13.1) cancer database, DepMap portal, and Enrichr web tool with MSigDB Hallmark 2020 database to analyze the incidence and distribution of significant alterations, differentially expressed genes, and pathway enrichment within distinct melanoma subtypes. Results: We identified 337 patients with advanced melanoma who received anti-PD1 +/- anti-CTLA4 for metastatic disease. CM was the most frequent melanoma subtype (81%), followed by MM (12%), and AM (8%). Patients with AM had the shortest OS and PFS CM (OS 3.4 years, PFS of 1.1 years), AM median (OS 1.4 years, PFS 3.8 months), and MM (OS 1.7 years, PFS 6 months; OS, P= 0.028; PFS P=0.029). Patients with CM or MM experienced longer OS with anti-PD1 +/- CTLA4 vs. anti-PD1 monotherapy, but no survival advantage was observed in patients with AM. In the GENIE dataset, we identified 2015/374/177 samples with CM/MM/AM, respectively. AM and MM patients were significantly more likely to be Female, Black or Asian than CM patients. BRAF V600 mutations were most frequent in CM (40%), followed by MM (7%) and AM (14%). However, MM and AM had an increase in alterations in cell cycle regulator genes. The incidence of CDK4 and CCND1 amplification, respectively was highest in AM (17%, 16%), followed by MM (6%, 6%) and CM (2%, 3%). We compared the pathways represented by differentially altered genes in AM vs. CM: G2M-Checkpoint (Q<0.05) and E2F targets (Q<0.05) pathways were enriched in AM. We also compared RNAseq data from n=4) AM and n=20 CM cell lines, and found the same pathways enriched amongst genes that were differentially expressed between AM and CM: G2M-Checkpoint (Q<0.01) and E2F targets (Q<0.01) Conclusions: Our findings highlight comparatively poor outcomes with ICIs in Acral Melanoma. AM has lower rates of actionable BRAF mutations; as such, very few patients with metastatic AM have access to effective 1st or 2nd line therapies. Thus, there is an urgent need to explore alternative therapeutic targets. Our data implicate cell cycle inhibitors as potentially important components of novel treatment strategies that could augment immunotherapy efficacy for patients with metastatic AM. Citation Format: Sadaf Solati, April A. N. Rose, Anna Spreafico, Adrian Sacher, Denis Yahiaoui, Wilson H. Miller. Comparing the clinical and genomic landscapes of acral, mucosal, and cutaneous metastatic melanomas treated with immune checkpoint inhibitors [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Tumor Immunology and Immunotherapy; 2023 Oct 1-4; Toronto, Ontario, Canada. Philadelphia (PA): AACR; Cancer Immunol Res 2023;11(12 Suppl):Abstract nr A035.

СИСТЕМЫ ПОДГОТОВКИ И ВЫПУСКА ГИДРОЛОГИЧЕСКИХ ПРОГНОЗОВ ГИДРОМЕТЦЕНТРА РОССИИ

Nowadays operational forecasts of river flow are implemented in the form of automated systems for issuing forecasts, as well as delivering forecast products to users. Only within the framework of these systems, using modern software, the maximum efficiency is achieved from the use of hydrological models by automating all processes, combining them with operational database management systems, as well as with modern GIS and web tools for generating forecast products and delivering them to users. Over the past decade, the Hydrometeorological Research Center of the Russian Federation (Hydrometcenter of Russia) has been actively developed automated systems for issuing hydrological forecasts and communicating them to users. The systems are based on modern hydrological models, all available hydrometeorological information, including numerical weather forecasts, as well as modern software tools, including GIS and web technologies. Such systems have been implemented for large river basins, including the basin of the Kuban and the rivers of the Black Sea coast of Russia, the Amur and Volga basins. In recent years, the system has been developed for the entire territory of Russia. These systems are actively used by the Roshydromet operational forecasting divisions, as well as by specialists from the EMERCOM of Russia.

Analysis of persistence rate of cognitive enhancers in Alzheimer’s disease using the common data model

AbstractBackgroundAchEIs are used by first‐diagnosed Alzheimer’s dementia patients. The effect of drug has been proven in safety and efficacy but it is known that the drug cannot be taken continuously due to side effects of about 10% in existing studies. However, studies report higher drug discontinuation rates. Cognitive function improvers or ‘nootropics’ such as choline alfocerate are used together with AchEI. Therefore, purpose of this study was to analyze the usage patterns of cognitive enhancers in Alzheimer’s patients and to confirm retention rate using a common data model.MethodFrom 2010 to 2019, using the data of Alzheimer’s patients registered in the common data model server of Kangwon National University Hospital, we will investigate the prescription rate of cognitive function improving drugs (choline alfocerate) and drug analysis patterns such as ChEI and combination therapy. The analysis is conducted using the FeederNet‐based ATLAS WEB tool, and additional analysis is compared with the results obtained through the DBMS approach using SQL.ResultAs a result of the analysis of treatment trends and persistence for 10 years, among 2,658 newly diagnosed patients with Alzheimer’s disease, donepezil was prescribed the most with 1,518 patients (57.11%), choline alfocerate with 654 patients (24.6%), and memantine with 214 patients. (8.05%), rivastigmine in 74 (2.78%), and galantamine in 147 (5.53%) each. During observation, trend of increasing prescriptions was Donepezil (31.5% in 2010 to 68.7% in 2019), Nootropics (24.6% in 2010 to 34.2% in 2019), Memantine (3.7% in 2010 to 7.9% in 2019), and Rivastigmine(0.53% in 2010 to 3.32% in 2019), while galantamine decreased (12.2% in 2010 to 0.3% in 2019). Persistence was approximately 50% for donepezil and memantine and approximately 40% for rivastigmine, galantamine and choline alfocerate over 12 monthsConclusionComparing treatment trends of cognitive function improvers, donepezil, memantine, ribistigmine, and choline alfocerate showed a tendency to increase, whereas galantamine showed a tendency to decrease. Also, donepezil and memantine were associated with longer persistence than rivastigmine and galantamine and choline alfocerate. In particular, in case of Nootropics, a high rate of initial prescription is given to patients with dementia, but rate of continuous prescription is not high.

Novel Pyrazinoindolones As Amyloid‐Beta Aggregation Inhibitors

AbstractBackgroundAlzheimer’s disease (AD) is a devastating neurodegenerative condition which primarily affects the elderly population. One of hallmarks of AD is the accumulation of protein aggregates known as amyloid‐beta (Aβ) that promotes neurotoxicity and cognitive decline. Recent discoveries in the field led to the accelerated market approval of anti‐Aβ antibodies aducanumab and lecanemab. These are exciting discoveries. However, considering the cost and patient compliance issues with these biological therapies, discovering novel anti‐Aβ therapies that are based on small molecules is highly desirable due to several advantages over biological therapies including the ease of oral administration, reduced cost involved in bulk manufacturing and better stability on storage.MethodA library of novel pyrazino[1,2‐a]indole‐1(2H)‐one derivatives were designed using the computational modeling software Discovery Studio Structure‐Based‐Design (Biovia Inc, San Diego USA). Then synthetic chemistry protocols were optimized to prepare small molecule library and were characterized by 1H and 13C NMR and Liquid Chromatography Mass Spectrometry studies. The anti‐Aβ activity of these novel molecules toward Aβ40 aggregation was evaluated by fluorescence spectroscopy using the thioflavin‐T based aggregation kinetic studies. In addition, the online web tool SwissADME was used to calculate the physicochemical properties of pyrazino[1,2‐a]indole‐1(2H)‐one derivatives to assess their drug‐likeness, blood‐brain barrier permeability and pharmacokinetics.ResultA novel library of pyrazino[1,2‐a]indole‐1(2H)‐one derivatives were prepared by optimizing a four step or two step synthesis protocol starting from either phenylhydrazine or indole‐2‐carboxylic acid to afford pyrazino[1,2‐a]indole‐1(2H)‐one derivatives 5a–f. In the Aβ40 (5 μM) aggregation kinetics assay, they exhibited 14‐59% inhibition when tested at a range of concentrations (1, 5, 10 and 25 μM), demonstrating their anti‐Aβ properties. Their physicochemical properties suggest their drug‐likeness.ConclusionStructure‐activity relationship studies demonstrate that the fused tricyclic pyrazino[1,2‐a]indole‐1(2H)‐one is a suitable template to i) develop novel chemical tools to study and understand the mechanisms of Aβ40 aggregation and ii) discover novel small molecules as potential therapies for AD.