Open source paradigm is becoming widely accepted in scientific communities and open source hardware is finding its steady place in chemistry research. In this review article, we provide the reader with the most up-to-date information on open source hardware and software resources enabling the construction and utilization of an "open source capillary electrophoresis instrument". While CE is still underused as a separation technique, it offers unique flexibility, low-cost, and high efficiency and is particularly suitable for open source instrumental development. We overview the major parts of CE instruments, such as high voltage power supplies, detectors, data acquisition systems, and CE software resources with emphasis on availability of the open source information on the web and in the scientific literature. This review is the first of its kind, revealing accessible blueprints of most parts from which a fully functional open source CE system can be built. By collecting the extensive information on open source capillary electrophoresis in this review article, the authors aim at facilitating the dissemination of knowledge on CE within and outside the scientific community, fosters innovation and inspire other researchers to improve the shared CE blueprints.

• Klíčová slova
• Capillary electrophoresis, Open source hardware, Open source software, Review,
• MeSH
• design vybavení MeSH
• elektroforéza kapilární přístrojové vybavení   MeSH
• elektronika přístrojové vybavení   MeSH
• software MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH
• přehledy MeSH

BACKGROUND: In-house built capillary electrophoresis (CE) systems represent a significant share of laboratory instrumentation. In most of these instruments, sample injection is effected manually with low to moderate precision and requires skilled operators. Although few automated samplers have been previously developed, typically only one sample at a time can be injected. If a series of samples is to be analyzed, manual intervention is required. In the present work, we developed and constructed a fully automated, open source, CE autosampler, able to handle up to 14 different samples that can be used as a modular component of any in-house built CE instrument. RESULTS: An inexpensive, 3D printed, open source, autosampler for CE was developed. The autosampler consists of two parts: an injection unit with carousel containing sample and electrolyte vials and a flushing unit, containing a miniature pressure/vacuum pump. The autosampler is operated by an Arduino Mega microcontroller and an Arduino code written in the laboratory. The injection sequence is entered through a keypad and LCD display by the user. The instrument can operate autonomously for extended periods of time. It was used for fully automated analysis and/or calibration of up to 14 samples with excellent injection repeatability reaching less than 2.7% RSD for peak areas. The sampler performance was tested with two independently built CE instruments, a CE system with contactless conductivity detection (C4D) and a CE system with laser induced fluorescence (LIF) detector. SIGNIFICANCE AND NOVELTY: A novel, 3D printed, Arduino-based autosampler for CE was developed. The autosampler allows autonomous hydrodynamic injection of up to 14 different samples with fully programmable injection sequence, including capillary flushing and high voltage and data acquisition control. It provides the missing instrumental sampling setup for laboratory made CE instruments. It can be simply constructed based on the open-source blueprints in any laboratory and be a useful and time-saving add-on to any modular CE instrument.

• Klíčová slova
• Arduino, Autosampler, Capillary electrophoresis, Open source hardware and software,
• Publikační typ
• časopisecké články MeSH

For decades, biologists have relied on software to visualize and interpret imaging data. As techniques for acquiring images increase in complexity, resulting in larger multidimensional datasets, imaging software must adapt. ImageJ is an open-source image analysis software platform that has aided researchers with a variety of image analysis applications, driven mainly by engaged and collaborative user and developer communities. The close collaboration between programmers and users has resulted in adaptations to accommodate new challenges in image analysis that address the needs of ImageJ's diverse user base. ImageJ consists of many components, some relevant primarily for developers and a vast collection of user-centric plugins. It is available in many forms, including the widely used Fiji distribution. We refer to this entire ImageJ codebase and community as the ImageJ ecosystem. Here we review the core features of this ecosystem and highlight how ImageJ has responded to imaging technology advancements with new plugins and tools in recent years. These plugins and tools have been developed to address user needs in several areas such as visualization, segmentation, and tracking of biological entities in large, complex datasets. Moreover, new capabilities for deep learning are being added to ImageJ, reflecting a shift in the bioimage analysis community towards exploiting artificial intelligence. These new tools have been facilitated by profound architectural changes to the ImageJ core brought about by the ImageJ2 project. Therefore, we also discuss the contributions of ImageJ2 to enhancing multidimensional image processing and interoperability in the ImageJ ecosystem.

• Klíčová slova
• Fiji, ImageJ, image analysis, imaging, microscopy, open source software,
• MeSH
• počítačové zpracování obrazu * MeSH
• software * MeSH
• umělá inteligence * MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH
• Research Support, N.I.H., Extramural MeSH

PREMISE OF THE STUDY: Fungal diversity (richness) trends at large scales are in urgent need of investigation, especially through novel situations that combine long-term observational with environmental and remotely sensed open-source data. METHODS: We modeled fungal richness, with collections-based records of saprotrophic (decaying) and ectomycorrhizal (plant mutualistic) fungi, using an array of environmental variables across geographical gradients from northern to central Europe. Temporal differences in covariables granted insight into the impacts of the shorter- versus longer-term environment on fungal richness. RESULTS: Fungal richness varied significantly across different land-use types, with highest richness in forests and lowest in urban areas. Latitudinal trends supported a unimodal pattern in diversity across Europe. Temperature, both annual mean and range, was positively correlated with richness, indicating the importance of seasonality in increasing richness amounts. Precipitation seasonality notably affected saprotrophic fungal diversity (a unimodal relationship), as did daily precipitation of the collection day (negatively correlated). Ectomycorrhizal fungal richness differed from that of saprotrophs by being positively associated with tree species richness. DISCUSSION: Our results demonstrate that fungal richness is strongly correlated with land use and climate conditions, especially concerning seasonality, and that ongoing global change processes will affect fungal richness patterns at large scales.

• Klíčová slova
• collections data, diversity, fungi, macroecology, open‐source, phenology records,
• Publikační typ
• časopisecké články MeSH

Open-source automated insulin delivery systems, commonly referred to as do-it-yourself automated insulin delivery systems, are examples of user-driven innovations that were co-created and supported by an online community who were directly affected by diabetes. Their uptake continues to increase globally, with current estimates suggesting several thousand active users worldwide. Real-world user-driven evidence is growing and provides insights into safety and effectiveness of these systems. The aim of this consensus statement is two-fold. Firstly, it provides a review of the current evidence, description of the technologies, and discusses the ethics and legal considerations for these systems from an international perspective. Secondly, it provides a much-needed international health-care consensus supporting the implementation of open-source systems in clinical settings, with detailed clinical guidance. This consensus also provides important recommendations for key stakeholders that are involved in diabetes technologies, including developers, regulators, and industry, and provides medico-legal and ethical support for patient-driven, open-source innovations.

• MeSH
• diabetes mellitus 1. typu * farmakoterapie   MeSH
• hypoglykemika terapeutické užití   MeSH
• inzulin * terapeutické užití   MeSH
• inzulinové infuzní systémy MeSH
• lidé MeSH
• zdravotnický personál MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH
• přehledy MeSH
• Research Support, N.I.H., Extramural MeSH
• Názvy látek
• hypoglykemika MeSH
• inzulin * MeSH

Scoring thermal tolerance traits live or with recorded video can be time consuming and susceptible to observer bias, and as with many physiological measurements, there can be trade-offs between accuracy and throughput. Recent studies show that automated particle tracking is a viable alternative to manually scoring videos, although some of the software options are proprietary and costly. In this study, we present a novel strategy for automated scoring of thermal tolerance videos by inferring motor activity with motion detection using an open-source Python command line application called DIME (detector of insect motion endpoint). We apply our strategy to both dynamic and static thermal tolerance assays, and our results indicate that DIME can accurately measure thermal acclimation responses, generally agrees with visual estimates of thermal limits, and can significantly increase throughput over manual methods.

• Klíčová slova
• Automated particle tracking, Automatic scoring, Bioassay, Motor performance, Thermal limits,
• MeSH
• aklimatizace * MeSH
• hmyz MeSH
• počítače MeSH
• pohyb těles MeSH
• software * MeSH
• zvířata MeSH
• Check Tag
• zvířata MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH
• Research Support, U.S. Gov't, Non-P.H.S. MeSH

MOTIVATION: Many diseases, such as cancer, are characterized by an alteration of cellular metabolism allowing cells to adapt to changes in the microenvironment. Stable isotope-resolved metabolomics (SIRM) and downstream data analyses are widely used techniques for unraveling cells' metabolic activity to understand the altered functioning of metabolic pathways in the diseased state. While a number of bioinformatic solutions exist for the differential analysis of SIRM data, there is currently no available resource providing a comprehensive toolbox. RESULTS: In this work, we present DIMet, a one-stop comprehensive tool for differential analysis of targeted tracer data. DIMet accepts metabolite total abundances, isotopologue contributions, and isotopic mean enrichment, and supports differential comparison (pairwise and multi-group), time-series analyses, and labeling profile comparison. Moreover, it integrates transcriptomics and targeted metabolomics data through network-based metabolograms. We illustrate the use of DIMet in real SIRM datasets obtained from Glioblastoma P3 cell-line samples. DIMet is open-source, and is readily available for routine downstream analysis of isotope-labeled targeted metabolomics data, as it can be used both in the command line interface or as a complete toolkit in the public Galaxy Europe and Workfow4Metabolomics web platforms. AVAILABILITY AND IMPLEMENTATION: DIMet is freely available at https://github.com/cbib/DIMet, and through https://usegalaxy.eu and https://workflow4metabolomics.usegalaxy.fr. All the datasets are available at Zenodo https://zenodo.org/records/10925786.

• MeSH
• glioblastom metabolismus   MeSH
• izotopové značení * metody   MeSH
• lidé MeSH
• metabolomika * metody   MeSH
• nádorové buněčné linie MeSH
• software * MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH

To solve recurring problems in drug discovery, matched molecular pair (MMP) analysis is used to understand relationships between chemical structure and function. For the MMP analysis of large data sets (>10,000 compounds), available tools lack flexible search and visualization functionality and require computational expertise. Here, we present Matcher, an open-source application for MMP analysis, with novel search algorithms and fully automated querying-to-visualization that requires no programming expertise. Matcher enables unprecedented control over the search and clustering of MMP transformations based on both variable fragment and constant environment structure, which is critical for disentangling relevant and irrelevant data to a given problem. Users can exert such control through a built-in chemical sketcher and with a few mouse clicks can navigate between resulting MMP transformations, statistics, property distribution graphs, and structures with raw experimental data, for confident and accelerated decision making. Matcher can be used with any collection of structure/property data; here, we demonstrate usage with a public ChEMBL data set of about 20,000 small molecules with CYP3A4 and/or hERG inhibition data. Users can reproduce all examples demonstrated herein via unique links within Matcher's interface-a functionality that anyone can use to preserve and share their own analyses. Matcher and all its dependencies are open-source, can be used for free, and are available with containerized deployment from code at https://github.com/Merck/Matcher. Matcher makes large structure/property data sets more transparent than ever before and accelerates the data-driven solution of common problems in drug discovery.

• MeSH
• algoritmy * MeSH
• objevování léků metody   MeSH
• racionální návrh léčiv MeSH
• shluková analýza MeSH
• software * MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH

Benchmarking and monitoring of urban design and transport features is crucial to achieving local and international health and sustainability goals. However, most urban indicator frameworks use coarse spatial scales that either only allow between-city comparisons, or require expensive, technical, local spatial analyses for within-city comparisons. This study developed a reusable, open-source urban indicator computational framework using open data to enable consistent local and global comparative analyses. We show this framework by calculating spatial indicators-for 25 diverse cities in 19 countries-of urban design and transport features that support health and sustainability. We link these indicators to cities' policy contexts, and identify populations living above and below critical thresholds for physical activity through walking. Efforts to broaden participation in crowdsourcing data and to calculate globally consistent indicators are essential for planning evidence-informed urban interventions, monitoring policy effects, and learning lessons from peer cities to achieve health, equity, and sustainability goals.

• MeSH
• celosvětové zdraví * MeSH
• lidé MeSH
• prostorová analýza MeSH
• software MeSH
• velkoměsta MeSH
• zdravotní stav * MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH
• přehledy MeSH
• Research Support, N.I.H., Extramural MeSH
• Research Support, U.S. Gov't, P.H.S. MeSH
• Geografické názvy
• velkoměsta MeSH

Protein engineering is the discipline of developing useful proteins for applications in research, therapeutic, and industrial processes by modification of naturally occurring proteins or by invention of de novo proteins. Modern protein engineering relies on the ability to rapidly generate and screen diverse libraries of mutant proteins. However, design of mutant libraries is typically hampered by scale and complexity, necessitating development of advanced automation and optimization tools that can improve efficiency and accuracy. At present, automated library design tools are functionally limited or not freely available. To address these issues, we developed Mutation Maker, an open source mutagenic oligo design software for large-scale protein engineering experiments. Mutation Maker is not only specifically tailored to multisite random and directed mutagenesis protocols, but also pioneers bespoke mutagenic oligo design for de novo gene synthesis workflows. Enabled by a novel bundle of orchestrated heuristics, optimization, constraint-satisfaction and backtracking algorithms, Mutation Maker offers a versatile toolbox for gene diversification design at industrial scale. Supported by in silico simulations and compelling experimental validation data, Mutation Maker oligos produce diverse gene libraries at high success rates irrespective of genes or vectors used. Finally, Mutation Maker was created as an extensible platform on the notion that directed evolution techniques will continue to evolve and revolutionize current and future-oriented applications.

• Klíčová slova
• PCR-based accurate synthesis, directed evolution, gene synthesis, multi site-directed mutagenesis, protein design, protein engineering, site-scanning saturation mutagenesis, synthetic biology,
• MeSH
• algoritmy MeSH
• Escherichia coli genetika   MeSH
• genová knihovna MeSH
• kodon genetika   MeSH
• mutace * MeSH
• mutageneze cílená metody   MeSH
• mutageneze * MeSH
• mutantní proteiny MeSH
• oligonukleotidy genetika   MeSH
• počítačová simulace MeSH
• proteiny genetika   MeSH
• řízená evoluce molekul metody   MeSH
• software * MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH
• Názvy látek
• kodon MeSH
• mutantní proteiny MeSH
• oligonukleotidy MeSH
• proteiny MeSH