Lipidomics and metabolomics communities comprise various informatics tools; however, software programs handling multimodal mass spectrometry (MS) data with structural annotations guided by the Lipidomics Standards Initiative are limited. Here, we provide MS-DIAL 5 for in-depth lipidome structural elucidation through electron-activated dissociation (EAD)-based tandem MS and determining their molecular localization through MS imaging (MSI) data using a species/tissue-specific lipidome database containing the predicted collision-cross section values. With the optimized EAD settings using 14 eV kinetic energy, the program correctly delineated lipid structures for 96.4% of authentic standards, among which 78.0% had the sn-, OH-, and/or C = C positions correctly assigned at concentrations exceeding 1 μM. We showcased our workflow by annotating the sn- and double-bond positions of eye-specific phosphatidylcholines containing very-long-chain polyunsaturated fatty acids (VLC-PUFAs), characterized as PC n-3-VLC-PUFA/FA. Using MSI data from the eye and n-3-VLC-PUFA-supplemented HeLa cells, we identified glycerol 3-phosphate acyltransferase as an enzyme candidate responsible for incorporating n-3 VLC-PUFAs into the sn1 position of phospholipids in mammalian cells, which was confirmed using EAD-MS/MS and recombinant proteins in a cell-free system. Therefore, the MS-DIAL 5 environment, combined with optimized MS data acquisition methods, facilitates a better understanding of lipid structures and their localization, offering insights into lipid biology.

• MeSH
• Data Mining * methods   MeSH
• Phosphatidylcholines metabolism   chemistry   MeSH
• HeLa Cells MeSH
• Mass Spectrometry methods   MeSH
• Humans MeSH
• Lipidomics * methods   MeSH
• Lipids chemistry   analysis   MeSH
• Metabolomics methods   MeSH
• Fatty Acids, Unsaturated metabolism   chemistry   MeSH
• Software MeSH
• Tandem Mass Spectrometry methods   MeSH
• Animals MeSH
• Check Tag
• Humans MeSH
• Animals MeSH
• Publication type
• Journal Article MeSH

This quasi-experimental study used a nonrandomized, control group pre-test post-test research design to determine the effect of a motor behavior course with a social justice perspective on undergraduate students' attitudes toward people with disabilities, alignment with the medical and social models of disability, and mobility beliefs. Undergraduate students enrolled at a public university (n=714) completed survey measures before and after participation in a 10-week course. Intervention group participants (n=357) were drawn from a required course for Kinesiology students that included social justice topics and video-based contact with people with disabilities. Control group participants (n=357) were drawn from a required course for all students that did not include social justice content. Separate one-way ANCOVAs were conducted to identify differences in outcomes between groups, controlling for baseline measures and demographic characteristics. Results indicate that participants in the intervention group reported more favorable attitudes toward people with disabilities, lower medical model scores, higher social model scores, and more favorable views toward self-directed mobility as a human right. Integrating social justice concepts into the classroom may be an important addition to undergraduate Kinesiology curriculums and a valuable intervention strategy to positively influence Kinesiology student attitudes.

• MeSH
• Kinesiology, Applied education   MeSH
• Humans MeSH
• Motor Activity MeSH
• Persons with Disabilities * MeSH
• Attitude to Health * MeSH
• Sentiment Analysis MeSH
• Social Justice MeSH
• Students, Medical psychology   MeSH
• Education, Medical MeSH
• Check Tag
• Humans MeSH

This work presents an automated data-mining model for age-at-death estimation based on 3D scans of the auricular surface of the pelvic bone. The study is based on a multi-population sample of 688 individuals (males and females) originating from one Asian and five European identified osteological collections. Our method requires no expert knowledge and achieves similar accuracy compared to traditional subjective methods. Apart from data acquisition, the whole procedure of pre-processing, feature extraction and age estimation is fully automated and implemented as a computer program. This program is a part of a freely available web-based software tool called CoxAGE3D. This software tool is available at https://coxage3d.fit.cvut.cz/ Our age-at-death estimation method is suitable for use on individuals with known/unknown population affinity and provides moderate correlation between the estimated age and actual age (Pearson's correlation coefficient is 0.56), and a mean absolute error of 12.4 years.

• MeSH
• Data Mining MeSH
• Facies MeSH
• Humans MeSH
• Face MeSH
• Pelvic Bones * diagnostic imaging   MeSH
• Software MeSH
• Check Tag
• Humans MeSH
• Male MeSH
• Female MeSH
• Publication type
• Journal Article MeSH

This interpretive study explored participants' perceptions of their child's involvement in Equine-Assisted Activities and Therapies (EAAT). EAAT is implemented with a horse and is based on the notion that interacting with the horse has positive benefits. Such activity is nearly always reported to have positive effects on the child. Few studies have investigated the perceptions of the parents of their children's participation in horseback riding activities. The purpose of this study is to determine how parents and/or guardians perceive how EAAT impacts their young riders, and the epiphanic ways in which the parents view those changes. Seven parents of participating children were purposefully sampled. Riders included five girls (5-10 years old) and six boys (6-16 years old) with cognitive and/or emotional disabilities including Post-Traumatic Stress Disorder (PTSD), Autism Spectrum Disorder, Down syndrome, and more. Findings were analyzed through an interpretive lens of epiphany. Participants spoke of the positive ways in which they and their children were accepted, and discussed improvements in children's strength, social development, and specific individual needs. Parents' views of the impact on their children are essential to improving service and advocacy for their children.

• MeSH
• Psychology, Child MeSH
• Humans MeSH
• Children with Disabilities psychology   rehabilitation   MeSH
• Sentiment Analysis MeSH
• Parents * psychology   MeSH
• Social Perception MeSH
• Patient Satisfaction MeSH
• Youth Sports MeSH
• Sports for Persons with Disabilities MeSH
• Equine-Assisted Therapy * MeSH
• Treatment Outcome MeSH
• Check Tag
• Humans MeSH

BACKGROUND: The advancement of sequencing technologies today has made a plethora of whole-genome re-sequenced (WGRS) data publicly available. However, research utilizing the WGRS data without further configuration is nearly impossible. To solve this problem, our research group has developed an interactive Allele Catalog Tool to enable researchers to explore the coding region allelic variation present in over 1,000 re-sequenced accessions each for soybean, Arabidopsis, and maize. RESULTS: The Allele Catalog Tool was designed originally with soybean genomic data and resources. The Allele Catalog datasets were generated using our variant calling pipeline (SnakyVC) and the Allele Catalog pipeline (AlleleCatalog). The variant calling pipeline is developed to parallelly process raw sequencing reads to generate the Variant Call Format (VCF) files, and the Allele Catalog pipeline takes VCF files to perform imputations, functional effect predictions, and assemble alleles for each gene to generate curated Allele Catalog datasets. Both pipelines were utilized to generate the data panels (VCF files and Allele Catalog files) in which the accessions of the WGRS datasets were collected from various sources, currently representing over 1,000 diverse accessions for soybean, Arabidopsis, and maize individually. The main features of the Allele Catalog Tool include data query, visualization of results, categorical filtering, and download functions. Queries are performed from user input, and results are a tabular format of summary results by categorical description and genotype results of the alleles for each gene. The categorical information is specific to each species; additionally, available detailed meta-information is provided in modal popups. The genotypic information contains the variant positions, reference or alternate genotypes, the functional effect classes, and the amino-acid changes of each accession. Besides that, the results can also be downloaded for other research purposes. CONCLUSIONS: The Allele Catalog Tool is a web-based tool that currently supports three species: soybean, Arabidopsis, and maize. The Soybean Allele Catalog Tool is hosted on the SoyKB website ( https://soykb.org/SoybeanAlleleCatalogTool/ ), while the Allele Catalog Tool for Arabidopsis and maize is hosted on the KBCommons website ( https://kbcommons.org/system/tools/AlleleCatalogTool/Zmays and https://kbcommons.org/system/tools/AlleleCatalogTool/Athaliana ). Researchers can use this tool to connect variant alleles of genes with meta-information of species.

• MeSH
• Alleles * MeSH
• Arabidopsis * genetics   MeSH
• Data Mining * methods   MeSH
• Datasets as Topic * MeSH
• Gene Frequency MeSH
• Genotype MeSH
• Glycine max * genetics   MeSH
• Internet * MeSH
• Zea mays * genetics   MeSH
• Metadata MeSH
• Mutation MeSH
• Pigmentation genetics   MeSH
• Genes, Plant genetics   MeSH
• Software * MeSH
• Amino Acid Substitution MeSH
• Plant Dormancy genetics   MeSH
• Data Visualization MeSH
• Publication type
• Journal Article MeSH

Nedávné technologické pokroky biomedicínského výzkumu umožnily zkoumat základní biologické procesy v živých organismech při různých rozlišeních a z různých úhlů pohledu. Zatímco množství produkovaných dat v průběhu let dramaticky roste, tempo našich získávaných znalostí spíše zaostává, což ukazuje na neschopnost současných výpočetních nástrojů umožnit extrakci znalostí z velkého množství zašuměných dat. NEUROMINER poskytne rámec pro strojové učení a dolování z obrazových dat se zvláštním důrazem na neurovědní výzkum. Tři hlavní osy projektu odpovídají problémům, pro které v současné době není známo řešení: (1) extrakce a selekce příznaků se silnou diskriminačních schopností z mnohorozměrných dat, (2) nepřeučené systémy učící se z mnohorozměrných dat (3) rigorózní postup pro statistické validace modelů. Navrhovatelé projektu jsou experty ve zpracování analýze medicínských obrazů, biostatistice a strojovém učení.; The recent technological advances enabled the biomedical research to explore the underlying biological processes of the living organisms at various resolutions and from different perspectives. While the amount of produced data grew dramatically over the years, the pace at which our knowledge lagged behind - an indication of inability of the current computational tools to extract knowledge from the large pool of noisy data. NEUROMINER will provide a framework for machine learning and data mining, with a special emphasis on neuroscience research. The project has three main axes of research, each corresponding to a currently unmet need: (1) extraction and selection of features with strong discrimination properties, (2) systems able to learn from high-dimensional data and not suffering from overfitting problems, and (3) rigorous statistical model assessment procedure. The applicants are experts in medical image processing and analysis, biostatistics and machine learning.

• MeSH
• Biostatistics MeSH
• Data Mining MeSH
• Brain diagnostic imaging   MeSH
• Neural Networks, Computer MeSH
• Neuroimaging MeSH
• Image Processing, Computer-Assisted MeSH
• Reproducibility of Results MeSH
• Schizophrenia diagnostic imaging   MeSH
• Machine Learning MeSH

• Conspectus
• Patologie. Klinická medicína
• NML Fields
• neurologie
• radiologie, nukleární medicína a zobrazovací metody
• lékařská informatika
• NML Publication type
• závěrečné zprávy o řešení grantu AZV MZ ČR

Age-at-death estimation of adult skeletal remains is a key part of biological profile estimation, yet it remains problematic for several reasons. One of them may be the subjective nature of the evaluation of age-related changes, or the fact that the human eye is unable to detect all the relevant surface changes. We have several aims: (1) to validate already existing computer models for age estimation; (2) to propose our own expert system based on computational approaches to eliminate the factor of subjectivity and to use the full potential of surface changes on an articulation area; and (3) to determine what age range the pubic symphysis is useful for age estimation. A sample of 483 3D representations of the pubic symphyseal surfaces from the ossa coxae of adult individuals coming from four European (two from Portugal, one from Switzerland and Greece) and one Asian (Thailand) identified skeletal collections was used. A validation of published algorithms showed very high error in our dataset-the Mean Absolute Error (MAE) ranged from 16.2 and 25.1 years. Two completely new approaches were proposed in this paper: SASS (Simple Automated Symphyseal Surface-based) and AANNESS (Advanced Automated Neural Network-grounded Extended Symphyseal Surface-based), whose MAE values are 11.7 and 10.6 years, respectively. Lastly, it was demonstrated that our models could estimate the age-at-death using the pubic symphysis over the entire adult age range. The proposed models offer objective age estimates with low estimation error (compared to traditional visual methods) and are able to estimate age using the pubic symphysis across the entire adult age range.

• MeSH
• Data Mining MeSH
• Adult MeSH
• Humans MeSH
• Forensic Anthropology methods   MeSH
• Pubic Symphysis * MeSH
• Age Determination by Skeleton methods   MeSH
• Imaging, Three-Dimensional MeSH
• Check Tag
• Adult MeSH
• Humans MeSH
• Publication type
• Journal Article MeSH

• MeSH
• Big Data MeSH
• Data Mining methods   MeSH
• Expert Systems MeSH
• Medical Informatics methods   trends   MeSH
• Data Accuracy MeSH
• Machine Learning MeSH
• Artificial Intelligence * MeSH

Human-nature relationships are an important aspect of leisure research. Previous studies also reported that nature-related activities have a health benefit. In this study, we surveyed US-American birdwatchers at two time points during the COVID pandemic (independent samples). During the beginning of the COVID pandemic in spring 2020, we analyzed their comments with an AI sentiment analysis. Approximately one year later (winter 2020/21), during the second wave, the study was repeated, and a second data set was analyzed. Here we show that during the ongoing pandemic, the sentiments became more negative. This is an important result because it shows that despite the positive impact of nature on mental health, the sentiments become more negative in the enduring pandemic.

• MeSH
• COVID-19 * MeSH
• Humans MeSH
• Pandemics MeSH
• Attitude MeSH
• Sentiment Analysis MeSH
• SARS-CoV-2 MeSH
• Social Media * MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH
• Geographicals
• United States MeSH

Developments in information technology have impacted on all areas of modern life and in particular facilitated the growth of globalisation in commerce and communication. Within the drugs area this means that both drugs discourse and drug markets have become increasingly digitally enabled. In response to this, new methods are being developed that attempt to research and monitor the digital environment. In this commentary we present three case studies of innovative approaches and related challenges to software-automated data mining of the digital environment: (i) an e-shop finder to detect e-shops offering new psychoactive substances, (ii) scraping of forum data from online discussion boards, (iii) automated sentiment analysis of discussions in online discussion boards. We conclude that the work presented brings opportunities in terms of leveraging data for developing a more timely and granular understanding of the various aspects of drug-use phenomena in the digital environment. In particular, combining the number of e-shops, discussion posts, and sentiments regarding particular substances could be used for ad hoc risk assessments as well as longitudinal drug monitoring and indicate "online popularity". The main challenges of digital data mining involve data representativity and ethical considerations.

• MeSH
• Data Mining MeSH
• Pharmaceutical Preparations * MeSH
• Humans MeSH
• Drug Monitoring MeSH
• Commerce MeSH
• Substance-Related Disorders * MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH