The NVMeVirt paper analyzes the implication of storage performance on database engine performance to promote the tunable performance of NVMeVirt. They perform analysis on two very popular database engines, MariaDB and PostgreSQL. The result shows that MariaDB is more efficient when the storage is slow, but PostgreSQL outperforms MariaDB as I/O bandwidth increases. Although this verifies that NVMeVirt can support advanced storage bandwidth configurations, the paper does not provide a clear explanation of why two database engines react very differently to the storage performance. To understand why the above two database engines have different performance characteristics, we conduct a study of the database engine's internals. We focus on three major differences in Multi-version concurrency control (MVCC) implementations: version storage, garbage collection, and index management. We also evaluated each scheme's I/O overhead using OLTP workload. Our analysis identifies the reason why MariaDB outperforms PostgreSQL when the bandwidth is low.
Gut dysbiosis is widely recognized as a contributor to autoimmune diseases, as it can lead to the expression of microbial antigens that disrupt immune regulation through specific molecular mechanisms. However, existing resources do not systematically link gut microbial antigen sequences to the specific autoimmune mechanisms through which they act. Here, we present GUTAID (Gut Microbes in Autoimmune Disorders), a literature-curated database of gut microbial antigens annotated with experimentally supported autoimmune mechanisms. Peer-reviewed studies published from October 1970 to September 2024 were manually screened, yielding 73 potential antigens that operate through nine molecular mechanisms, including protein citrullination, epitope spreading, molecular mimicry, and immune modulation, amongst others. The corresponding protein sequences were retrieved from UniProtKB, and redundancy was removed with MMseqs2. For the database implementation, data were delivered through a lightweight LAMP (Linux-Apache-MySQL/MariaDB-PHP) stack with server-side HTML/Bootstrap rendering, MySQL indexing, and HTTPS-secured downloads. Users can browse, keyword-search, or bulk-download sequence archives via a five-tab interface (Home, Downloads, Search, Team, and About). GUTAID thus enables mechanism-oriented exploration of gut microbial antigens and supports downstream biomarker and therapeutic discovery in autoimmune research. Database URL:  https://gutaid.mgdiscoverylab.com/.
Haemonchus contortus is a highly pathogenic gastrointestinal nematode of ruminants and a major cause of production losses in small livestock systems. Its rapid life cycle and blood-feeding habit make it one of the most damaging helminths affecting sheep and goats worldwide. Control relies mainly on anthelmintics, particularly benzimidazoles, macrocyclic lactones, and levamisole; however, resistance to these drug classes has become widespread. Benzimidazole resistance in H. contortus is strongly associated with mutations in the β-tubulin 1 gene, particularly at codons 167, 198, and 200. In this study, all publicly available H. contortus β-tubulin 1 sequences deposited in GenBank (n = 439) were compiled and screened for resistance-associated variants. Records were retrieved programmatically using Biopython and organized within a structured SQL/MariaDB database for downstream analysis. Multiple sequence alignment was performed using ClustalX and verified in BioEdit. After excluding sequences lacking complete coverage of the three target codons, 270 sequences were retained for analysis. Within this GenBank-derived dataset, 38.9% of analyzed sequences contained at least one resistance-associated substitution, reflecting the composition of available database records rather than true field prevalence. Double mutations were rare and no triple mutations were detected. Patterns observed within the available GenBank dataset showed variation across recorded collection years, countries, and host species. Among sequences with geographic metadata, resistant alleles were most frequently observed in records from Brazil and the United States, while many sequences lacked location or host information. Within the available GenBank dataset, host-associated summaries indicated higher proportions of resistance markers among sequences derived from goats and sheep compared with cattle and buffalo. These results provide a systematic overview of benzimidazole resistance markers present in publicly available H. contortus β-tubulin 1 sequences. Because GenBank submissions are not based on systematic field sampling, the observed patterns should be interpreted as database-derived summaries rather than estimates of true global prevalence.
The project aims to develop and evaluate a cancer registration system specifically designed for lip and oral squamous cell cancer. First, a questionnaire created by the researcher was used to extract the registry design information pieces. Second, we designed the registry system using a variety of tools and technologies. PHP is selected as the server-side programming language, MariaDB is selected as the database management system, and CentOS 8 is selected as the base system. Web pages are designed and interacted with by users using HTML, CSS, and JavaScript. Thirdly, 21 clinical specialists who are the system's end users assessed the system using a standard questionnaire. Patient demographic and clinical data, information about medications administered, preliminary diagnostic evaluations, biopsy results, diagnosis-related tumor staging, clinical tumor features, surgical procedures, histopathological tumor features, pathologic stage classification, radiotherapy information, follow-up data, and disease registry functionalities are the main Minimum Data Sets (MDSs). The system is called "Oralcanreg," which is an acronym for the Oral Cancer Registry system. The software that was developed got data that was not always complete in all parts. The lowest one, "Diagnostic assessment," only made up 0.47% of the total data and had 96.8% missing values. This could be because these evaluations were not done or not recorded. Based on the average ratings for the system's overall scores in the [3-5] range, it can be said that the people who took part in the study regarded the registry's total function as "good." Disease registration design and implementation provide benefits such as timely access to medical records.
In a regional hospital in Southern Taiwan, an average of 25 heart surgeries are performed annually, with surgical education conducted one-on-one. This indicates that opportunities for paramedics to participate in surgical procedures are quite limited. Although 80 paramedics in the hospital can perform surgical procedures, 69 have more than two years of experience, and only 19 are selected by surgeons to perform surgical procedures. Consequently, paramedics without hands-on experience are likely to feel panicked and helpless. The present study employed a systematic software development approach to create a mobile application-based medical skill training system. Initially, we conducted a comprehensive needs analysis through in-depth interviews with cardiac surgery nurses and administrators to accurately identify the key training requirements. In the system architecture design phase, we chose Windows Server as the operating system, combined PHP and Apache to handle web service requests, used MariaDB for data storage and management, and applied FastAPI to facilitate data exchange with other services. Client-side development utilized the Flutter framework, ensuring a consistent user experience across iOS and Android platforms. We also designed complex data structures to accommodate testing and recording needs, including exam data, question types, and option records. For user flow implementation, we developed a complete process including user registration, subject management, test preparation, and evaluation. Finally, we implemented core functionalities such as the login interface, question selection, and test interface to ensure the system's comprehensiveness and practicality. This multi-stage development approach aimed to create an efficient, user-friendly, and adaptive training platform to meet the specific needs of cardiac surgery nursing staff. The development and implementation of the mobile application-based system for enhancing medical skill training has demonstrated significant potential in addressing the challenges of paramedics in cardiac surgery settings. While the initial results are promising, further long-term studies are needed to assess the impact on actual surgical outcomes and patient care quality.
Microbial secondary metabolites exhibit potential medicinal value. A large number of secondary metabolite biosynthetic gene clusters (BGCs) in the human gut microbiome, which exhibit essential biological activity in microbe-microbe and microbe-host interactions, have not been adequately characterized, making it difficult to prioritize these BGCs for experimental characterization. Here, we present the sBGC-hm, an atlas of secondary metabolite BGCs allows researchers to explore the potential therapeutic benefits of these natural products. One of its key features is the ability to assist in optimizing the BGC structure by utilizing the gene co-occurrence matrix obtained from Human Microbiome Project data. Results are viewable online and can be downloaded as spreadsheets. The database is openly available at https://www.wzubio.com/sbgc. The website is powered by Apache 2 server with PHP and MariaDB.
The purpose of this work is to enhance health tourism services for thermal sources in Greece. Within this research work, a website was developed to assist all interested people in searching for the appropriate thermal source for them. The content of the website is related to the health tourism ideas approach the historical foundation of health tourism and the alternative forms. The website was implemented based on the open-source CMS of Joomla. The server hosted by the CMS is based on open-source solutions such as Apache, MariaDB, and PHP.
Whole-genome sequencing (WGS) is a powerful method for detecting drug resistance, genetic diversity, and transmission dynamics of Mycobacterium tuberculosis. Implementation of WGS in public health microbiology laboratories is impeded by a lack of user-friendly, automated, and semiautomated pipelines. We present the COMBAT-TB Workbench, a modular, easy-to-install application that provides a web-based environment for Mycobacterium tuberculosis bioinformatics. The COMBAT-TB Workbench is built using two main software components: the IRIDA platform for its web-based user interface and data management capabilities and the Galaxy bioinformatics workflow platform for workflow execution. These components are combined into a single easy-to-install application using Docker container technology. We implemented two workflows, for M. tuberculosis sample analysis and phylogeny, in Galaxy. Building our workflows involved updating some Galaxy tools (Trimmomatic, snippy, and snp-sites) and writing new Galaxy tools (snp-dists, TB-Profiler, tb_variant_filter, and TB Variant Report). The irida-wf-ga2xml tool was updated to be able to work with recent versions of Galaxy and was further developed into IRIDA plugins for both workflows. In the case of the M. tuberculosis sample analysis, an interface was added to update the metadata stored for each sequence sample with results gleaned from the Galaxy workflow output. Data can be loaded into the COMBAT-TB Workbench via the web interface or via the command line IRIDA uploader tool. The COMBAT-TB Workbench application deploys IRIDA, the COMBAT-TB IRIDA plugins, the MariaDB database, and Galaxy using Docker containers (https://github.com/COMBAT-TB/irida-galaxy-deploy). IMPORTANCE While the reduction in the cost of WGS is making sequencing more affordable in lower- and middle-income countries (LMICs), public health laboratories in these countries seldom have access to bioinformaticians and system support engineers adept at using the Linux command line and complex bioinformatics software. The COMBAT-TB Workbench provides an open-source, modular, easy-to-deploy and -use environment for managing and analyzing M. tuberculosis WGS data and thereby makes WGS usable in practice in the LMIC context.
To meet the remote-learning constraints imposed due to the COVID-19 pandemic, the Digital Science Platform was developed. Human anatomy courses require practical classes that involve working on prepared specimens, although access to such specimens has been restricted. Therefore, the aim was to prepare appropriate-quality, scanned 3D model databases of human bone specimens and an interactive web application for universal access to educational materials. The database is located on the pcn.cnt.edu.pl website and contains 412 three-dimensional osteological models created via a structured light scanner, tomography and microtomography. The webservice contains a search engine and enables interactive visualization of the models. The database can be accessed, without restrictions, by any student or researcher wishing to use the models for noncommercial purposes. The stored models can be visualized with the open-source VisNow platform, which is also available to download from the webservice. The MariaDB backend database was deployed, and an Apache server with a personal home page (PHP) frontend was used. The models in the database are unique due to the specific digitalization process and skeleton specimen origin. Further development of the Digital Science Platform is foreseen in the near future to digitize other valuable materials.
Bistable biochemical switches are key motifs in cellular state decisions and long-term storage of cellular 'memory'. There are a few known biological switches that have been well characterized, however, these examples are insufficient for systematic surveys of properties of these important systems. Here we present a resource of all possible bistable biochemical reaction networks with up to six reactions between three molecules, and three reactions between four molecules. Over 35 000 reaction topologies were constructed by identifying unique combinations of reactions between a fixed number of molecules. Then, these topologies were populated with rates within a biologically realistic range. The Searchable Web Interface for Topologies of CHEmical Switches (SWITCHES, https://switches.ncbs.res.in) provides a bistability and parameter analysis of over seven million models from this systematic survey of chemical reaction space. This database will be useful for theoreticians interested in analyzing stability in chemical systems and also experimentalists for creating robust synthetic biological switches. Freely available on the web at https://switches.ncbs.res.in. Website implemented in PHP, MariaDB, Graphviz and Apache, with all major browsers supported.
Photovoltaic (PV) energy is a renewable energy resource which is being widely integrated in intelligent power grids, smart grids, and microgrids. To characterize and monitor the behavior of PV modules, current-voltage (I-V) curves are essential. In this regard, Internet of Things (IoT) technologies provide versatile and powerful tools, constituting a modern trend in the design of sensing and data acquisition systems for I-V curve tracing. This paper presents a novel I-V curve tracer based on IoT open-source hardware and software. Namely, a Raspberry Pi microcomputer composes the hardware level, whilst the applied software comprises mariaDB, Python, and Grafana. All the tasks required for curve tracing are automated: load sweep, data acquisition, data storage, communications, and real-time visualization. Modern and legacy communication protocols are handled for seamless data exchange with a programmable logic controller and a programmable load. The development of the system is expounded, and experimental results are reported to prove the suitability and validity of the proposal. In particular, I-V curve tracing of a monocrystalline PV generator under real operating conditions is successfully conducted.
Cervical cancer is a common female malignant tumor. It has been increasing and rejuvenating in recent years. Early screening of cervical cancer is an effective control method to block cancer. In this study, a diffuse reflectance spectrum detection and analysis system based on LabWindows development software and MariaDB database was developed, which can acquire and save the spectral data to the database. The method of a neural network model based on spectral database was built to distinguish the cervical tissue and the normal tissue. The nude mouse tumor model test and human volunteer test were performed respectively, which verified that the system can distinguish between normal tissue and tumor tissue, and can be applied to the screening of cervical precancerous lesions.
Information on cardiovascular gene transcription is fragmented and far behind the present requirements of the systems biology field. To create a comprehensive source of data for cardiovascular gene regulation and to facilitate a deeper understanding of genomic data, the CardioTF database was constructed. The purpose of this database is to collate information on cardiovascular transcription factors (TFs), position weight matrices (PWMs), and enhancer sequences discovered using the ChIP-seq method. The Naïve-Bayes algorithm was used to classify literature and identify all PubMed abstracts on cardiovascular development. The natural language learning tool GNAT was then used to identify corresponding gene names embedded within these abstracts. Local Perl scripts were used to integrate and dump data from public databases into the MariaDB management system (MySQL). In-house R scripts were written to analyze and visualize the results. Known cardiovascular TFs from humans and human homologs from fly, Ciona, zebrafish, frog, chicken, and mouse were identified and deposited in the database. PWMs from Jaspar, hPDI, and UniPROBE databases were deposited in the database and can be retrieved using their corresponding TF names. Gene enhancer regions from various sources of ChIP-seq data were deposited into the database and were able to be visualized by graphical output. Besides biocuration, mouse homologs of the 81 core cardiac TFs were selected using a Naïve-Bayes approach and then by intersecting four independent data sources: RNA profiling, expert annotation, PubMed abstracts and phenotype. The CardioTF database can be used as a portal to construct transcriptional network of cardiac development. Database URL: http://www.cardiosignal.org/database/cardiotf.html.
The molecular diagnostics laboratory faces the challenge of improving test turnaround time (TAT). Low and consistent TATs are of great clinical and regulatory importance, especially for molecular virology tests. Laboratory information systems (LISs) contain all the data elements necessary to do accurate quality assurance (QA) reporting of TAT and other measures, but these reports are in most cases still performed manually: a time-consuming and error-prone task. The aim of this study was to develop a web-based real-time QA platform that would automate QA reporting in the molecular diagnostics laboratory at our institution, and minimize the time expended in preparing these reports. Using a standard Linux, Nginx, MariaDB, PHP stack virtual machine running atop a Dell Precision 5810, we designed and built a web-based QA platform, code-named Alchemy. Data files pulled periodically from the LIS in comma-separated value format were used to autogenerate QA reports for the human immunodeficiency virus (HIV) quantitation, hepatitis C virus (HCV) quantitation, and BK virus (BKV) quantitation. Alchemy allowed the user to select a specific timeframe to be analyzed and calculated key QA statistics in real-time, including the average TAT in days, tests falling outside the expected TAT ranges, and test result ranges. Before implementing Alchemy, reporting QA for the HIV, HCV, and BKV quantitation assays took 45-60 min of personnel time per test every month. With Alchemy, that time has decreased to 15 min total per month. Alchemy allowed the user to select specific periods of time and analyzed the TAT data in-depth without the need of extensive manual calculations. Alchemy has significantly decreased the time and the human error associated with QA report generation in our molecular diagnostics laboratory. Other tests will be added to this web-based platform in future updates. This effort shows the utility of informatician-supervised resident/fellow programming projects as learning opportunities and workflow improvements in the molecular laboratory.
Citizen science and data collected from various volunteers have an interesting potential in aiding the understanding of many biological and ecological processes. We describe a mobile application that allows the public to map and report occurrences of the odonata species (dragonflies and damselflies) found in the Czech Republic. The application also helps in species classification based on observation details such as date, GPS coordinates, and the altitude, biotope, suborder, and colour. Dragonfly Hunter CZ is a free Android application built on the open-source framework NativeScript using the JavaScript programming language which is now fully available on Google Play. The server side is powered by Apache Server with PHP and MariaDB SQL database. A mobile application is a fast and accurate way to obtain data pertaining to the odonata species, which can be used after expert verification for ecological studies and conservation basis like Red Lists and policy instruments. We expect it to be effective in encouraging Citizen Science and in promoting the proactive reporting of odonates. It can also be extended to the reporting and monitoring of other plant and animal species.
Accurate 3D modelling of protein-protein interactions (PPI) is essential to compensate for the absence of experimentally determined complex structures. Here, we present a new set of commands within the ModelX toolsuite capable of generating atomic-level protein complexes suitable for interface design. Among these commands, the new tool ProteinFishing proposes known and/or putative alternative 3D PPI for a given protein complex. The algorithm exploits backbone compatibility of protein fragments to generate mutually exclusive protein interfaces that are quickly evaluated with a knowledge-based statistical force field. Using interleukin-10-R2 co-crystalized with interferon-lambda-3, and a database of X-ray structures containing interleukin-10, this algorithm was able to generate interleukin-10-R2/interleukin-10 structural models in agreement with experimental data. ProteinFishing is a portable command-line tool included in the ModelX toolsuite, written in C++, that makes use of an SQL (tested for MySQL and MariaDB) relational database delivered with a template SQL dump called FishXDB. FishXDB contains the empty tables of ModelX fragments and the data used by the embedded statistical force field. ProteinFishing is compiled for Linux-64bit, MacOS-64bit and Windows-32bit operating systems. This software is a proprietary license and is distributed as an executable with its correspondent database dumps. It can be downloaded publicly at http://modelx.crg.es/. Licenses are freely available for academic users after registration on the website and are available under commercial license for for-profit organizations or companies. javier.delgado@crg.eu or luis.serrano@crg.eu. Supplementary data are available at Bioinformatics online.
Primary Immunodeficiencies (PIDs) belong to the group of rare diseases. The European Society for Immunodeficiencies (ESID) operates an international research database application for continuous long-term documentation of patient data. The system is a web application which runs in a standard browser. Therefore, the system is easy to access from any location. Technically, the system is based on Gails backed by MariaDB with high standard security features to comply with the demands of a modern research platform. The ESID Online Database is accessible via the official website: https://esid.org/Working-Parties/Registry-Working-Party/ESID-Registry. A demo system is available via: https://cci-esid-reg-demo-app.uniklinik-freiburg.de/EERS with user demouser and password Demo-2019.
Performance is a critical characteristic of fundamental systems, such as Database Management Systems (DBMSs). Both academia and industry have invested decades in exploring efficient optimization algorithms. Despite these efforts, DBMSs are prone to performance issues, which incur suboptimal performance. Finding such issues is a longstanding challenge as no ground-truth performance is available. Existing work adopts black-box methods to examine performance consistency across executions, but cannot systematically test optimizations. In this work, we propose a novel, general white-box methodology, Branch Flip Analysis (BFA), to systematically and effectively uncover performance issues. BFA flips code branches to enforce or disable an optimization, and the performance is expected to be not significantly better. Otherwise, a performance issue exists. BFA provides a new perspective to finding performance issues and testing optimization logics in a fine-grained manner. We realized BFA in a prototype system QueryZen, and evaluated it on four widely-used and mature DBMSs: PostgreSQL, MySQL, CockroachDB, and MariaDB. QueryZen found 21 previously unknown and unique performance issues with the
Software configuration tuning is crucial for optimising system performance, and various optimisers have emerged over the last decade. Yet, the time required during the tuning process may vary across systems. In some systems (e.g., PostgreSQL), it may take a few minutes to measure a configuration, whereas in some others (e.g., MariaDB), it can take several hours. Moreover, even within the same system, users may have varying budgets and preferred settings. This naturally raises a question -- Given a budget level, which optimiser is the best choice for SE practitioners? This matters because optimisers usually have their own ``comfort zone'' and may perform very differently under distinct budgets. In this paper, we aim to answer this question. We systematically evaluate eight well-established optimisers across 22 configurable systems under varying budget levels. We find that, unsurprisingly, model-based optimisers (e.g., SMAC) are well-suited under tight budgets, and model-free optimisers (e.g., GAs) become superior with more generous budgets. However, interestingly, there is one optimiser, FLASH, that performs consistently well on most systems regardless of budgets. We lastly investig
Traditional database fuzzing techniques primarily focus on syntactic correctness and general SQL structures, leaving critical yet obscure DBMS features, such as system-level modes (e.g., GTID), programmatic constructs (e.g., PROCEDURE), advanced process commands (e.g., KILL), largely underexplored. Although rarely triggered by typical inputs, these features can lead to severe crashes or security issues when executed under edge-case conditions. In this paper, we present FuzzySQL, a novel LLM-powered adaptive fuzzing framework designed to uncover subtle vulnerabilities in DBMS special features. FuzzySQL combines grammar-guided SQL generation with logic-shifting progressive mutation, a novel technique that explores alternative control paths by negating conditions and restructuring execution logic, synthesizing structurally and semantically diverse test cases. To further ensure deeper execution coverage of the back end, FuzzySQL employs a hybrid error repair pipeline that unifies rule-based patching with LLM-driven semantic repair, enabling automatic correction of syntactic and context-sensitive failures. We evaluate FuzzySQL across multiple DBMSs, including MySQL, MariaDB, SQLite, Pos