Challenges and Practical Solutions to MRI and Histology Matching and Measurements Using Available ImageJ Software Tools.
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ABSTRACT:
SUBMITTER: Khodanovich MY
PROVIDER: S-EPMC9313422 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:METHODS:Muscle sections were stained for cell boundary (laminin) and myofiber type (myosin heavy chain isoforms). Myosoft, running in the open access software platform FIJI (ImageJ), was used to analyze myofiber size and type in transverse sections of entire gastrocnemius/soleus muscles. RESULTS:Myosoft provides an accurate analysis of hundreds to thousands of muscle fibers within 25 minutes, which is >10-times faster than manual analysis. We demonstrate that Myosoft is capable of handling high-content images even when image or staining quality is suboptimal, which is a marked improvement over currently available and comparable programs. CONCLUSIONS:Myosoft is a reliable, accurate, high-throughput, and convenient tool to analyze high-content muscle histology. Myosoft is freely available to download from Github at https://github.com/Hyojung-Choo/Myosoft/tree/Myosoft-hub.
| S-EPMC7055860 | biostudies-literature
Project description:IntroductionThe field of metabolomics has expanded greatly over the past two decades, both as an experimental science with applications in many areas, as well as in regards to data standards and bioinformatics software tools. The diversity of experimental designs and instrumental technologies used for metabolomics has led to the need for distinct data analysis methods and the development of many software tools.ObjectivesTo compile a comprehensive list of the most widely used freely available software and tools that are used primarily in metabolomics.MethodsThe most widely used tools were selected for inclusion in the review by either ? 50 citations on Web of Science (as of 08/09/16) or the use of the tool being reported in the recent Metabolomics Society survey. Tools were then categorised by the type of instrumental data (i.e. LC-MS, GC-MS or NMR) and the functionality (i.e. pre- and post-processing, statistical analysis, workflow and other functions) they are designed for.ResultsA comprehensive list of the most used tools was compiled. Each tool is discussed within the context of its application domain and in relation to comparable tools of the same domain. An extended list including additional tools is available at https://github.com/RASpicer/MetabolomicsTools which is classified and searchable via a simple controlled vocabulary.ConclusionThis review presents the most widely used tools for metabolomics analysis, categorised based on their main functionality. As future work, we suggest a direct comparison of tools' abilities to perform specific data analysis tasks e.g. peak picking.
| S-EPMC5550549 | biostudies-literature
Project description:About 46.6 million Americans have mental illnesses, yet profound treatment gaps exist in this country. Among those receiving treatment, most are treated solely with medication, even though >50% prefer to include psychotherapy in treatment. Other countries have changed policies to enhance access to evidence-based psychotherapy, resulting in availability and utilization reflective of patient preferences. To improve access to these treatments, the U.S. health care system would need to seek agreement among stakeholders regarding what constitutes effective treatment; enhance training, credentialing, and continuing education requirements; implement quality measures; integrate services into nontraditional venues; and incentivize best practices.
| S-EPMC9192142 | biostudies-literature
Project description:The event study or event study method (ESM) is an empirical technique for capturing investors' reaction to an event affecting one or more publicly traded firms. The ESM has been little employed in international business (IB) research despite its frequency in accounting, economics, and finance; for example, only two percent of the empirical articles in JIBS over 1970-2019 include an event study. While this scarcity could indicate a lack of demand, we argue that the field of IB studies offers many interesting and important research opportunities for an event study. We believe that the challenges arise primarily from the supply side, because conducting an event study involves overcoming a variety of data and analytical hurdles. We examine these methodological challenges and offer practical solutions designed to encourage adoption of the ESM. An online appendix with coding and examples provides additional resources.Supplementary informationThe online version contains supplementary material available at 10.1057/s41267-022-00509-7.
| S-EPMC8968242 | biostudies-literature
Project description:The analytes qualified as biomarkers are potent tools to diagnose various diseases, monitor therapy responses, and design therapeutic interventions. The early assessment of the diverseness of human disease is essential for the speedy and cost-efficient implementation of personalized medicine. We developed g3mclass, the Gaussian mixture modeling software for molecular assay data classification. This software automates the validated multiclass classifier applicable to single analyte tests and multiplexing assays. The g3mclass achieves automation using the original semi-constrained expectation-maximization (EM) algorithm that allows inference from the test, control, and query data that human experts cannot interpret. In this study, we used real-world clinical data and gene expression datasets (ERBB2, ESR1, PGR) to provide examples of how g3mclass may help overcome the problems of over-/underdiagnosis and equivocal results in diagnostic tests for breast cancer. We showed the g3mclass output’s accuracy, robustness, scalability, and interpretability. The user-friendly interface and free dissemination of this multi-platform software aim to ease its use by research laboratories, biomedical pharma, companion diagnostic developers, and healthcare regulators. Furthermore, the g3mclass automatic extracting information through probabilistic modeling is adaptable for blending with machine learning and artificial intelligence.
2022-11-09 | GSE214540 | GEO
Project description:Single-molecule localisation microscopy (SMLM) uses software to extract super-resolved positions from microscope images of fluorescent molecules. These localisations can then be used to render super-resolution images or analysed to extract information about molecular behaviour. The GDSC SMLM software provides a set of tools for analysing SMLM data in a single cross-platform environment. The software identifies fluorescent molecules in raw microscope images and localises their positions using stages of spot detection, spot fitting and spot rejection. The resulting localisation data set can then be visualised, cropped and filtered. A suite of downstream analysis tools enable the user to perform single-particle tracking, cluster analysis and drift correction. In addition, GDSC SMLM also provides utility tools that enable modelling of EM-CCD and sCMOS cameras as well as point spread functions (PSFs) for data simulation. The software is written in Java and runs as a collection of plugins for the ImageJ software.
| S-EPMC10282564 | biostudies-literature
Project description:The advent of next-generation sequencing technologies is accompanied with the development of many whole-genome sequence assembly methods and software, especially for de novo fragment assembly. Due to the poor knowledge about the applicability and performance of these software tools, choosing a befitting assembler becomes a tough task. Here, we provide the information of adaptivity for each program, then above all, compare the performance of eight distinct tools against eight groups of simulated datasets from Solexa sequencing platform. Considering the computational time, maximum random access memory (RAM) occupancy, assembly accuracy and integrity, our study indicate that string-based assemblers, overlap-layout-consensus (OLC) assemblers are well-suited for very short reads and longer reads of small genomes respectively. For large datasets of more than hundred millions of short reads, De Bruijn graph-based assemblers would be more appropriate. In terms of software implementation, string-based assemblers are superior to graph-based ones, of which SOAPdenovo is complex for the creation of configuration file. Our comparison study will assist researchers in selecting a well-suited assembler and offer essential information for the improvement of existing assemblers or the developing of novel assemblers.
| S-EPMC3056720 | biostudies-literature
Project description:ObjectiveIn the wake of the coronavirus pandemic, teleneuropsychology utilization has increased. There is a need to characterize the first-hand experiences of individuals using teleneuropsychology, identify the common teleneuropsychology challenges, and devise practical strategies for mitigating/resolving these challenges.MethodSurvey data were collected from U.S. based neuropsychologists and other individuals (e.g., graduate students and research assistants) who were engaged in remote cognitive assessment with adults (n = 87). Frequency analyses were conducted to examine: how respondents used teleneuropsychology (e.g., duration of use, types of measures and devices/technology platforms used); challenges that were encountered with different technology platforms and teleneuropsychology use; and advice for navigating these challenges.ResultsMost respondents began using teleneuropsychology relatively recently in the context of the coronavirus pandemic, with home-to-home or clinic-to-home settings being the most frequently reported teleneuropsychology settings. Zoom®, Doxy.Me®, and MyChart® were the most frequently used platforms, largely due to workplace mandates and/or Health Insurance Portability and Accountability Act-compliant features. Common challenges with teleneuropsychology included internet connection issues and environmental distractions in examinees' homes, and examinees having limited-to-no access to technologies requisite for teleneuropsychology. Providing clear instructions to the examinee prior to the teleneuropsychology visit was the most common advice for ensuring a successful teleneuropsychology evaluation. Similar response patterns were generally noted for those who used TeleNP for clinical or research purposes.ConclusionsThese survey results reflect common experiences and challenges with teleneuropsychology and identify priority targets for increasing its feasibility, reliability, and validity. Findings provide context for the development of formal teleneuropsychology competencies.
| S-EPMC8513402 | biostudies-literature
Project description:ObjectiveTo compare two clinically available MR volumetry software, NeuroQuant® (NQ) and Inbrain® (IB), and examine the inter-method reliabilities and differences between them.Materials and methodsThis study included 172 subjects (age range, 55-88 years; mean age, 71.2 years), comprising 45 normal healthy subjects, 85 patients with mild cognitive impairment, and 42 patients with Alzheimer's disease. Magnetic resonance imaging scans were analyzed with IB and NQ. Mean differences were compared with the paired t test. Inter-method reliability was evaluated with Pearson's correlation coefficients and intraclass correlation coefficients (ICCs). Effect sizes were also obtained to document the standardized mean differences.ResultsThe paired t test showed significant volume differences in most regions except for the amygdala between the two methods. Nevertheless, inter-method measurements between IB and NQ showed good to excellent reliability (0.72 < r < 0.96, 0.83 < ICC < 0.98) except for the pallidum, which showed poor reliability (left: r = 0.03, ICC = 0.06; right: r = -0.05, ICC = -0.09). For the measurements of effect size, volume differences were large in most regions (0.05 < r < 6.15). The effect size was the largest in the pallidum and smallest in the cerebellum.ConclusionComparisons between IB and NQ showed significantly different volume measurements with large effect sizes. However, they showed good to excellent inter-method reliability in volumetric measurements for all brain regions, with the exception of the pallidum. Clinicians using these commercial software should take into consideration that different volume measurements could be obtained depending on the software used.
| S-EPMC7909859 | biostudies-literature
Project description:Single-cell transcriptomics allows the identification of cellular types, subtypes and states through cell clustering. In this process, similar cells are grouped before determining co-expressed marker genes for phenotype inference. The performance of computational tools is directly associated to their marker identification accuracy, but the lack of an optimal solution challenges a systematic method comparison. Moreover, phenotypes from different studies are challenging to integrate, due to varying resolution, methodology and experimental design. In this work we introduce matchSCore (https://github.com/elimereu/matchSCore), a measure to fastly match cell populations across tools, experiments and technologies. We compared 14 computational methods and evaluated their accuracy in clustering and gene marker identification in simulated data sets. Further, we used matchSCore to project cell type identities across mouse or human cell atlas projects. Despite originated from different technologies, cell populations could be matched across datasets, allowing the assignment of clusters to reference maps and their annotation.
2021-04-30 | GSE114138 | GEO