Web Portal Research Articles

A new atlas to study embryonic cell types in Xenopus

This paper introduces a single-cell atlas for pivotal developmental stages in Xenopus, encompassing gastrulation, neurulation, and early tailbud. Notably surpassing its predecessors, the new atlas enhances gene mapping, read counts, and gene/cell type nomenclature. Leveraging the latest Xenopus tropicalis genome version, alongside advanced alignment pipelines and machine learning for cell type assignment, this release maintains consistency with previous cell type annotations while rectifying nomenclature issues. Employing an unbiased approach for cell type assignment proves especially apt for embryonic contexts, given the considerable number of non-terminally differentiated cell types. An alternative cell type attribution here adopts a fuzzy, non-deterministic stance, capturing the transient nature of early embryo progenitor cells by presenting an ensemble of types in superposition. The value of the new resource is emphasized through numerous examples, with a focus on previously unexplored germ cell populations where we uncover novel transcription onset features. Offering interactive exploration via a user-friendly web portal and facilitating complete data downloads, this atlas serves as a comprehensive and accessible reference.

RCSB Protein Data Bank: supporting research and education worldwide through explorations of experimentally determined and computationally predicted atomic level 3D biostructures.

The Protein Data Bank (PDB) was established as the first open-access digital data resource in biology and medicine in 1971 with seven X-ray crystal structures of proteins. Today, the PDB houses >210 000 experimentally determined, atomic level, 3D structures of proteins and nucleic acids as well as their complexes with one another and small molecules (e.g. approved drugs, enzyme cofactors). These data provide insights into fundamental biology, biomedicine, bioenergy and biotechnology. They proved particularly important for understanding the SARS-CoV-2 global pandemic. The US-funded Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB) and other members of the Worldwide Protein Data Bank (wwPDB) partnership jointly manage the PDB archive and support >60 000 `data depositors' (structural biologists) around the world. wwPDB ensures the quality and integrity of the data in the ever-expanding PDB archive and supports global open access without limitations on data usage. The RCSB PDB research-focused web portal at https://www.rcsb.org/ (RCSB.org) supports millions of users worldwide, representing a broad range of expertise and interests. In addition to retrieving 3D structure data, PDB `data consumers' access comparative data and external annotations, such as information about disease-causing point mutations and genetic variations. RCSB.org also provides access to >1 000 000 computed structure models (CSMs) generated using artificial intelligence/machine-learning methods. To avoid doubt, the provenance and reliability of experimentally determined PDB structures and CSMs are identified. Related training materials are available to support users in their RCSB.org explorations.

Wasm-iCARE: a portable and privacy-preserving web module to build, validate, and apply absolute risk models.

Absolute risk models estimate an individual's future disease risk over a specified time interval. Applications utilizing server-side risk tooling, the R-based iCARE (R-iCARE), to build, validate, and apply absolute risk models, face limitations in portability and privacy due to their need for circulating user data in remote servers for operation. We overcome this by porting iCARE to the web platform. We refactored R-iCARE into a Python package (Py-iCARE) and then compiled it to WebAssembly (Wasm-iCARE)-a portable web module, which operates within the privacy of the user's device. We showcase the portability and privacy of Wasm-iCARE through 2 applications: for researchers to statistically validate risk models and to deliver them to end-users. Both applications run entirely on the client side, requiring no downloads or installations, and keep user data on-device during risk calculation. Wasm-iCARE fosters accessible and privacy-preserving risk tools, accelerating their validation and delivery.

Towards building a trustworthy pipeline integrating Neuroscience Gateway and Open Science Chain.

When the scientific dataset evolves or is reused in workflows creating derived datasets, the integrity of the dataset with its metadata information, including provenance, needs to be securely preserved while providing assurances that they are not accidentally or maliciously altered during the process. Providing a secure method to efficiently share and verify the data as well as metadata is essential for the reuse of the scientific data. The National Science Foundation (NSF) funded Open Science Chain (OSC) utilizes consortium blockchain to provide a cyberinfrastructure solution to maintain integrity of the provenance metadata for published datasets and provides a way to perform independent verification of the dataset while promoting reuse and reproducibility. The NSF- and National Institutes of Health (NIH)-funded Neuroscience Gateway (NSG) provides a freely available web portal that allows neuroscience researchers to execute computational data analysis pipeline on high performance computing resources. Combined, the OSC and NSG platforms form an efficient, integrated framework to automatically and securely preserve and verify the integrity of the artifacts used in research workflows while using the NSG platform. This paper presents the results of the first study that integrates OSC-NSG frameworks to track the provenance of neurophysiological signal data analysis to study brain network dynamics using the Neuro-Integrative Connectivity tool, which is deployed in the NSG platform. Database URL: https://www.opensciencechain.org.

510 Addressing the Regulatory Needs and Challenges of Academic Researchers by Creating a One-Stop Shop Web Portal

OBJECTIVES/GOALS: To identify challenges faced by academic researchers in accessing online regulatory information and/or tools to advance their research work to develop a free, publicly accessible, interactive web portal that provides regulatory support. METHODS/STUDY POPULATION: The Regulatory Knowledge and Support core of the Southern California Clinical and Translational Science Institute interviewed five local research professionals. These interviews guided the development of a Qualtrics survey, consisting of multiple responses and open-ended questions, submitted to our local institutional review board (IRB). After receiving IRB approval, the survey was disseminated via email, newsletters, flyers, and presentations targeting researchers at academic institutions and members of clinical and translational science hubs. Survey data will be used to identify the challenges academic researchers face in finding regulatory resources and to compile the types of regulatory information or tools they would find helpful for their research. RESULTS/ANTICIPATED RESULTS: According to the interviews, researchers with extensive involvement in clinical trials found regulatory resources easily accessible compared to those with less experience. Additionally, they all stated having a colleague or regulatory specialist whom they can consult about regulatory requirements. Insights from these initial interviews confirmed the need to obtain a comprehensive view across research professionals. Anticipated results will show the challenges in accessibility, source, and type of regulatory resources researchers typically encounter. It is also anticipated that researchers will share what kinds of resources they would find most useful for their work. Ultimately, the information and tools identified as essential by survey takers will be collected and incorporated into the web portal. DISCUSSION/SIGNIFICANCE: Academic researchers find navigating through regulatory hurdles persistently challenging when translating their work from bench to clinic, especially since academia is typically resource-constrained. Findings from this study will allow the creation of a web portal for researchers that is broadly accessible and meets their regulatory needs.

Enhancing Malware Detection Efficiency through CNN-Based Image Classification in a User-Friendly Web Portal

The proposed CNN-based malware detection web portal classifies images on a unique, self-made dataset to identify malware files as input. There are many different types of malware out there, but no method can detect them all. An anti-virus programme could be created that enforces malware image classification for the aforementioned scenarios as opposed to the traditional signature-based methods used by the majority of anti-virus programmes currently available in the market, which are time-consuming and ineffective because they rely just on signatures of previous malware attacks and need to be updated regularly. The fact that some malware is encrypted and requires a significant amount of computing power to decrypt makes this strategy ineffective for identifying all malware that accesses the network. As a result, fresh malware cannot be detected because this method simulates the behavior of malware samples and matches it to new programs. An online portal with a candid user interface will be used to deploy the proposed Deep-learning based malware detection algorithm. The file to be tested or classified will be uploaded onto the website

The digital climate atlas of the Canary Islands: A tool to improve knowledge of climate and temperature and precipitation trends in the Atlantic islands

This paper presents the Interactive Digital Climate Atlas of the Canary Islands, a web portal based on geographic information systems for the dissemination of climate information. It provides citizens and public and private administrations with high spatial resolution maps (100 m) of different climate variables such as temperature, rainfall, relative humidity, cloudiness frequency and wind velocity. Also available are Köppen climate classification maps and decadal trends of temperature and precipitation in a context of climate change. This spatial resolution is suitable for the detailed climatic description of small and orographically complex islands. For this purpose, climate series from databases of different public institutions as well as data from remote sensing and reanalysis systems were employed. A statistical process involving data filtering and the detection and correction of inhomogeneous segments was carried out as a preparatory step. Then, a spatial interpolation model was developed using a multiple linear regression method for the generation of the high spatial resolution climate cartography. The results are annual and monthly maps of the climate variables in Canary Islands at 100 m spatial resolution and with different time periods depending on the availability of data on the different variables, but in most cases between 1991 and 2020. Following the European Directive INSPIRE (Directive 2007/2/CE, Infrastructure for Spatial Information in Europe), both map visualisation and downloading in GeoTIFF and NetCDF format are permitted, as well as consultation of the data and metadata of the climatic series used.

Data Processing Engine (DPE): data analysis tool for particle tracking and mixed radiation field characterization with pixel detectors Timepix

Hybrid semiconductor pixelated detectors from the Timepix family are advanced detectors for online particle tracking, offering energy measurement and precise time stamping capabilities for particles of various types and energies. This inherent capability makes them highly suitable for various applications, including imaging, medical fields such as radiotherapy and particle therapy, space-based applications aboard satellites and the International Space Station, and industrial applications. The data generated by these detectors is complex, necessitating the development and deployment of various analytical techniques to extract essential information.For this purpose, and to aid the Timepix user community, it was designed and developed the“Data Processing Engine” (DPE) as an advanced tool for data processing designed explicitly for Timepix detectors. The functionality of the DPE is structured into three distinct processing levels: i) Pre-processing: this phase involves clusterization and the application of necessary calibrations and corrections. ii) Processing: this stage includes particle classification, employing machine learning algorithms, and the recognition of radiation fields. iii) Post-processing: involves various analyses, such as directional analysis, coincidence analysis, frame analysis, Compton directional analysis, and the generation of physics products, are performed. The core of the DPE is supported by an extensive experimental database containing calibrations and referential radiation fields of typical environments, including protons, ions, electrons, gamma rays and X rays, as well as thermal and fast neutrons. To enhance accessibility, the DPE is implemented into various user interface platforms such as a command-line tool, an application programming interface, and as a graphical user interface in the form of a web portal. The DPE's broad utility is exemplified through its integration into various applications and developments.

Med rec double check: Inpatient psychiatry medication errors identified on admission using Medicaid Web portals and electronic pharmaceutical claims data.

The role of pharmacists during medication reconciliation (MR) is well established, with a number of reports describing this in the context of psychiatric hospitalizations. However, medication errors (MEs) are common during transitions of care, with no exception during psychiatric hospitalizations. Our institution uses pharmacy-performed MR processes using patient interviews and reviewing objective sources, such as electronic pharmaceutical claims data (EPCD), which includes Medicaid Web portals. The inpatient psychiatric pharmacist reviews EPCD sources against previously pharmacy-completed MRs for new admissions, where if discrepancies are found, the patient is reinterviewed to identify and correct MEs. We performed a prospective quality improvement project during 28 days to evaluate the quantity and classification of MEs upon admission to a 22-bed inpatient psychiatry unit. Of 52 included patients, where a cumulative 426 medications were reviewed, a total of 29 MEs in 16 patients were identified. Eight patients had discrepancies on their home medication lists when compared to EPCD, where 7 of these had at least 1 ME due to inaccurate MR. Of all the MEs identified, the greatest quantity was found secondary to the EPCD "double-check" method. The most common MEs in all patients were the omission of home medications (34%), wrong frequency (28%), and ordering medication the patient is not taking (10%). All patients admitted on long-acting injection antipsychotics had errors in last dose received. No MEs resulted in patient harm, and they were identified and corrected by the psychiatric pharmacist 97% of the time.

Grievance Redressal Portal

Abstract: Our aim is to address and streamline the grievance resolution process within the university setting, focusing on issues pertinent to the academic, administrative, and infrastructural domains. This web portal is user friendly interface. Thus the users will feel very easy to work on it. By using this system admin can manage all the data of students, teachers and parents. The students, teachers and parents of students create a new account before logging in or he/she can log into the system with his/her created account. The portal incorporates a refined categorization system to precisely classify grievances within the unique context of LNMU. By categorizing issues related to academics, administration, and infrastructure, the portal ensures that each grievance is directed to the relevant authority for swift resolution. The portal offers a systematic and transparent approach to grievance resolution. The research explores the design, functionalities, and impact of the portal in fostering a responsive and accountable campus environment.

Preventing Fraudulent Vehicle Listings: Digital ADS Detection

Abstract: With the increasing popularity of online selling platforms for vehicles, the risk of fraudulent advertisements has also risen significantly. This research paper addresses the challenge of detecting and preventing digital fraud ads, particularly those related to vehicle listings, on typical online vehicle selling web portals. The proposed approach leverages advanced algorithms to identify and filter out fraudulent vehicle ads, including unregistered vehicles and unnecessary spam ads posted by sellers. One of the key techniques employed in this research is pattern matching, which involves comparing the details of posted vehicles with the records from Regional Transport Offices (RTOs) to determine their registration status. By analyzing the vehicle details provided in the ads and cross-referencing them with RTO data, the system can flag unregistered vehicles, thus mitigating the risk of fraudulent listings. Additionally, the study incorporates the use of the You Only Look Once (YOLO) algorithm for object detection in the images accompanying the ads. By applying YOLO, the system can accurately identify vehicles in the images and extract relevant information, such as make, model, and license plate details. This allows for further validation of the authenticity of the listings and helps in filtering out spam ads containing irrelevant or misleading images.

Enhanced Empowering Futures through Online Job Portal

This research aims to develop a job web portal for the students in the Faculty of Computer Science and Information Technology. The main aims of this portal are to connect with industries and act as an online recruitment tool to support students in finding the right IT job after graduation. Furthermore, this system enhances the understanding of the concept and importance of the job portal for students in universities. A survey was conducted to identify the students’ problems with the existing portal of the faculty and to gather their requirements, which can be incorporated into the portal to be developed.

Does nutritional support under programmatic settings result in weight and body mass index changes among tuberculosis patients? Evidence on the impact of nutritional support through Pradhan Mantri Tuberculosis Mukt Bharat Abhiyan under national tuberculosis elimination programme from Ramgarh district of Jharkhand

Background: To increase community participation in tuberculosis (TB) elimination efforts, the government of India has launched ‘Pradhan Mantri TB Mukt Bharath Abhiyan’ (PMTBMBA) under the national TB elimination programme. The scheme allows interested parties (Ni-kshay mitras) to offer nutritional support to TB patients. This study aims to understand the impact of such a support in improving weight and body mass index (BMI) among TB patients as most available evidence comes from research settings. Methods: This is a retrospective cross-sectional study carried out in Ramgarh district of Jharkhand, India, for the period first quarter 2023. Relevant data was extracted from Ni-kshay web portal and TB treatment cards. The data is analyzed using excel 365. Results: Of the 114 participants, 69 received nutritional support during the entire duration of treatment and 45 received support partially. Single factor ANOVA on weight and BMI gain revealed statistically significant difference in mean weight/BMI between the two groups with F (1, 110)=35.4660, p=3.16×10-08 and F (1, 110)=22.9994, p=5.12×10-06. Correlation analysis showed a moderate correlation between the number of nutritional kits received and the weight/BMI gain with correlation coefficients r=0.5, p=1.07×10-07 and r=0.4, p=1.65×10-05 respectively. Conclusions: The study concludes that the impact of nutritional supplementation in programmatic setting is comparable with that of implementation research study settings.

Updates to the Alliance of Genome Resources central infrastructure.

The Alliance of Genome Resources (Alliance) is an extensible coalition of knowledgebases focused on the genetics and genomics of intensively studied model organisms. The Alliance is organized as individual knowledge centers with strong connections to their research communities and a centralized software infrastructure, discussed here. Model organisms currently represented in the Alliance are budding yeast, Caenorhabditis elegans, Drosophila, zebrafish, frog, laboratory mouse, laboratory rat, and the Gene Ontology Consortium. The project is in a rapid development phase to harmonize knowledge, store it, analyze it, and present it to the community through a web portal, direct downloads, and application programming interfaces (APIs). Here, we focus on developments over the last 2 years. Specifically, we added and enhanced tools for browsing the genome (JBrowse), downloading sequences, mining complex data (AllianceMine), visualizing pathways, full-text searching of the literature (Textpresso), and sequence similarity searching (SequenceServer). We enhanced existing interactive data tables and added an interactive table of paralogs to complement our representation of orthology. To support individual model organism communities, we implemented species-specific "landing pages" and will add disease-specific portals soon; in addition, we support a common community forum implemented in Discourse software. We describe our progress toward a central persistent database to support curation, the data modeling that underpins harmonization, and progress toward a state-of-the-art literature curation system with integrated artificial intelligence and machine learning (AI/ML).

ShinyExprPortal: a configurable 'shiny' portal for sharing analysis of molecular expression data.

The scale of omics research presents many obstacles to full sharing and access to analysis results. Current publication models impose limits on the number of pages and figures, requiring careful preparation and selection of content. At the same time, depositing data in open repositories significantly shifts the burden of access and reproduction to readers, who may include people who are not programmers or analysts. We introduce shinyExprPortal, an R package that implements omics web portals with minimal coding effort. The portals allow exploration of transcriptomic or proteomic expression data and phenotypes, showcasing results of various types of analysis including differential expression, co-expression and pathways analysis. The integration with bioinformatics workflows enables researchers to focus on their results and share findings using interactive and publication-quality plots. The shinyExprPortal package is available to download and install from CRAN and https://github.com/C4TB/shinyExprPortal.

Pruebas Térmicas de Sensibilidad Pulpar en Dientes Permanentes con Pulpitis: Valor Diagnóstico y Limitaciones

Introduction: The diagnostic process in endodontics begins with the recognition of the symptoms, the dental history and the objective clinical evaluation, where thermal pulp sensitivity tests are essential in the clinical routine to have an approximation of the pulp condition. However, understanding the nature of the diagnostic tests, and the pulp pathophysiology, are essential to correctly interpret their results. Objective: To recognize the diagnostic value and limitations of thermal pulp sensitivity tests during the endodontic evaluation of the permanent tooth affected with pulpitis. Materials and Methods: The development of this narrative review was carried out through a search strategy in the electronic database, consultation in specialized web portals, and, in addition, required a search for valuable primary articles and books. Results: 34 publications were selected for their contribution and relevance. Conclusions: The sensitivity test using the cold stimulus appropriately results in a high correspondence to rule out a vital or necrotic pulp. This high correspondence is also maintained for reversible pulpitis, with a slight decrease for cases of irreversible pulpitis, although it continues to have a high diagnostic value. However, their main drawbacks continue to be that they are based on a qualitative response from the patient, loaded with subjectivity, and necessarily require experience and skill on the part of the clinician for their execution and interpretation.

Abstract 7423: BATCH-FLEX: Feature-level equalization of x-batch in heterogeneous cancer data

Abstract Purpose: Develop a shiny application to help integrate cancer datasets and guide researchers in selecting an appropriate method of correction for their technical artifacts. Description: Integrative analysis of heterogeneous expression data remains challenging due to variations in platform, RNA quality, sample processing, and other unknown technical effects. As the field performs omics profiling of samples from cancer patients and murine models, there is the need for harmonizing, identifying, and correcting these technical effects to ensure robust analysis on the treatment and conditional effects of the underlying genetics or biological events. However, selecting and implementing different approaches for removing unwanted batch effects can be a time-consuming and tedious process, especially for more biologically focused investigators. In this project, we present Shiny BATCH-FLEX, a Shiny app to rapidly visualize batch correction by established batch correction methods such as ComBat, Mean Centering, ComBatSeq, and Limma RemoveBatchEffect. With BATCH-FLEX, users can visualize the contribution of variance of a factor before and after correction using principal component analysis, relative log expression plots, heatmaps, and explanatory variables. Users can also save all plots and matrices as a single ZIP file for further downstream analysis. Results: As a proof of concept, we assessed BATCH-FLEX using simulated data generated from a linear model framework introduced by Gagnon-Bartsch and Speed, which assumes that gene expression measurements can be distilled to a combination of the biological signal, systemic nose, and random noise. BATCH-FLEX was able to successfully identify and remove the introduced effect using each of the batch correction methods listed above. Next, we evaluated BATCH-FLEX using a comprehensive collection of bladder cancer data consisting of microarray data from 13 studies spanning 1452 samples. Following the cleaning of study-dependent noise, BATCH-FLEX was successful in revealing the heterogeneity among bladder cancer based on known sample type annotations. Conclusion: We have developed BATCH-FLEX, a tool for oncologic researchers to rapidly assess, select, and implement commonly used batch correction methods. This tool is available at https://github.com/shawlab-moffitt/BATCH-FLEX. Our integrative web portal of a Bladder Cancer Resource for Translational Science (BEACON) will also be shared at the meeting. Citation Format: Joshua Davis, Alyssa Obermayer, Thac Duong, Rebecca Hesterberg, Xuefeng Wang, Mingxiang Teng, G. Daniel Grass, Timothy Shaw. BATCH-FLEX: Feature-level equalization of x-batch in heterogeneous cancer data [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 7423.

Abstract 3034: Krüppel-like factors in regulation of gastric cancer progression

Abstract Introduction: Gastric cancer (GC) is the third leading cause of cancer-associated mortality and the fifth most frequently diagnosed cancer worldwide. The development and progression of GC is a complicated multistage process subjected to dynamic changes in gene regulation. Investigating the effects of these changes is therefore critical for improving our knowledge about GC initiation and progression. Krüppel-like factors (KLFs) are evolutionarily conserved zinc finger-containing transcription factors with altered expressions and diverse regulatory functions in GC. We previously reported that there is loss of KLF4 in GC. Here we report that KLF4 is a crucial regulator of KLF5 expression and vice versa and together they regulate GC cell behavior. Methods: The Cancer Genome Atlas (TCGA) and pan cancer data of differential expressions of KLFs in GC was analyzed. TCGA RNAseq and clinical data for the differential expression status of KLF genes in normal and cancerous tissues and the clinicopathological association was accessed from the UALCAN web portal. The expressions of KLF4 and KLF5 in human normal stomach and GC and orthotopic xenografts were detected by immunohistochemistry (IHC). KLF4, KLF5 cross regulation was evaluated by gene manipulation of each gene individually and checking the expression of the other factor in GC cells. The effect of KLFs on GC cell proliferation, migration, and invasion was determined by Ki67 staining of tissues, PrestoBlue cell viability assay, scratch wound and transwell cell invasion assays. Results and Conclusion: Our results indicated that not only KLF4 and KLF5 have contrasting expressions and effects in GC but also these two factors cross regulate each other. While lower expressions of KLF4 was found in human GC and orthotopic xenografts, increased expression of KLF5 was found in both human GC tissue and orthotopic xenografts. KLF4 silencing and CRISPR/Cas9 knockdown in human GC cells resulted in increased expression of KLF5 which was associated with increased GC cell proliferation and invasiveness. Interestingly, KLF5 knockdown by CRISPR/Cas9 in human GC cells on the other hand resulted in increased expression of KLF4, which was associated with decreased GC cell growth. Our data therefore suggests that the differential expressions of KLF4 and KLF5 might serve as valuable prognostic markers in GC. Citation Format: Sooraj Kakkat, Prabhat Suman, Sandeep Goswami, Sujit Basu, Martin J. Heslin, Elba A. Turbat-Herrera, Veronica Ramirez Alcantara, Chandrani Sarkar, Debanjan Chakroborty. Krüppel-like factors in regulation of gastric cancer progression [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3034.

Artificial intelligence through the prism of thematic research on ResearchGate web portal

Different instances of generative artificial intelligence (GenAI) in a short time have made a significant impact on the world’s economic and political scene. Before October 2022, processes of automatization and robotization of manufacturing didn’t have an immediate connection with artificial intelligence in the minds of most people. But mass and sudden infiltration of GenAI into the everyday life of many people around the world caused an immediate reaction from scientists, public figures, politicians, managers and heads of whole sectors of the economy. Thousands of scientific articles on related topics were published in the last two years: everyone at once started talking about fantastic possibilities, and also threats, which this new technology can usher in for our societies. Thus, for public thinking GenAI finally linked automatization with artificial intelligence.
 This paper provides an analysis of problems and prospects, through which scientists are trying to understand different societal processes linked to adoption of AI. For this purpose, the author of this paper analyzed the contents of papers published on this topic on the ResearchGate web portal in 2023, with the choice of the source for representative material motivated by scientific credibility of ResearchGate combined with its wide reach. Ten most popular articles were specifically targeted for final analysis, through which societal trends brought on by AI adoption were described. Although a selective meta-analysis of articles published during the first year after ChatGPT release can’t provide a full understanding of AI potential and possible threats to society, the conclusion can still be reached that a cardinal shift in society’s attitudes towards its own future is required.
 From the ten articles analyzed, four are related to changes required to the education system, four are about AI’s influence on the labour market, one article talks about the possibility of AI-human competition and one is about the AI potential in agriculture. Most articles mention the need for legislative changes in terms of labor protection and education reforms in-line with new digital reality.

SOCIAL COMMUNICATIONS OF THE LOCAL GOVERNMENT IN WARTIME (ON THE EXAMPLE OF THE ODESA CITY COUNCIL)

The relevance of the study lies in the fact that during a full-scale war, the social communications of the authorities acquire special importance. Communication between authorities and citizens takes place at different levels, and various tools are used. When Russia invaded Ukraine on February 24, 2022, these communications links underwent a significant transformation, some were destroyed. Defending itself against aggression, the Ukrainian state has taken a number of steps in the information sphere. In particular, access to certain resources (state registers, etc.) was closed, as well as access to other open sources was restricted. Such actions caused concern among the active part of the society, because the legal grounds of state authorities and local self-government in this area are not clearly defined. Experts have also drawn attention to this problem. They defined the closure of access to some data posted on the website of the Odesa City Council as unfounded. The purpose of the author of the article was to investigate the methods of communication between representatives of the Odesa territorial community and the city council, its officials and officials during martial law, as well as to determine the level of effectiveness of such communication. The study made it possible to conclude that the remarks made by experts and public activists regarding the unfoundedness of restricting Internet users’ access to the resources of the Odesa City Council have generally been corrected. Most of the pages of the council’s web portal are available, in addition, employees of the relevant divisions of the local self-government body actively maintain social networks of the city council. Among the shortcomings should be attributed the non-working state of hyperlinks to individual resources of the authority, work with interruptions of some sources, as well as duplication of certain information on the Internet resources of the Odesa City Council and the Mayor of Odesa. The achieved results are planned to be developed through a more detailed study of social communications of the Odesa City Council in further scientific articles.