Ontology highlight
ABSTRACT:
PROVIDER: PRJNA762185 | ENA |
REPOSITORIES: ENA
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Project description:We show that DANCE-MaP permits measurement of state-specific per-nucleotide reactivities, direct secondary structure PAIRs, and tertiary RINGs for RNA structural ensembles. Here, we demonstrate DANCE-MaP on the V. vulnificus add riboswitch.
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Project description:Here we show that regions of the honeybee brain involved in visual processing and learning and memory show a genomic response to distance information. Using a method that separates effects of perceived distance from effects of actual distance flown, we found that individuals forced to shift from a short to a perceived long distance to reach a feeding site showed differences in gene expression in the optic lobes and mushroom bodies relative to individuals that continued to perceive flying a short distance.
2011-03-05 | E-TABM-910 | biostudies-arrayexpress
Project description:Increasing evidence suggests microRNAs (miRNAs) control levels of mRNA expression during development of the nervous system and during sensory elicited remodelling of the brain. We used an associative olfactory learning paradigm (proboscis extension response) in the honeybee Apis mellifera to detect gene expression changes in the brain. Transcriptome analysis of bees trained to associate an odor with a reward and control bees exposed to air without reward, helped us abstract mRNA-miRNA interactions for empirical testing. Functional studies, feeding cholesterol-conjugated antisense RNA to bees resulted in the inhibition of miR-210 and of miR-932 that is embedded within the neuroligin 2 (Nlg2) gene involved in synapse development. Loss of miR-932 prevents long-term memory formation but not learning. We validated 3M-bM-^@M-^YUTR target site interactions of miR-932 and show miR-932 dysregulates actin, a key cytoskeletal molecule involved in neuronal development and activity-dependent plasticity of the brain. The analysis used Air group (no odor learning) as control sample for comparison to two groups of odor-conditioned bees: linalool and floral mix.
2014-02-01 | E-GEOD-51795 | biostudies-arrayexpress
Project description:Interventions: Practice of Circular dance moves: Intervention: It will start with an experimental group and one control group.
Experimental Group: (Sample Number 90 individuals); Intervention period: 12( twelve) weeks; frequency: 02 (twice) a week; duration: 60 (sixty minutes); Location: Reference Center in Integrative Practices (CERPIS) located at Planaltina, Federal District. Also, the potential individuals to undergo the intervention shall fulfill a questionaire for assessing quality of life perception, sociodemographic profiling, clinical evaluation and an interview.
Control Group: (Sample Number 90 individuals) The potential individuals whom shall undergo the intervention shall take part on avery aspect of the intervention except for the circular dance moves; Location: Reference Center in Integrative Practices (CERPIS) located at Planaltina, Federal District. Also, the potential individuals to undergo the intervention shall fulfill a questionaire for assessing quality of life perception, sociodemographic profiling, clinical evaluation as well as laboratory assays and an interview.;Other;E02.190.888.374;I03.450.642.287
Primary outcome(s): The primary outcome measure being considered is the intervention of the practice of dance move that will have a period of 12 intervention (twelve) weeks.
Shall be considererd, quantitative changes in the spectrum of the evaluation of perception of quality of life questionnaire (COH-QOL-OQ - City of Hope - Quality of Life Ostomy Questionnaire)), requiring a change of, at least, 5% in the values obtained prior to the intervention as well as when compared to the control group.
Study Design: Randomized controlled trial, parallel open, with two arms, cross.
| 2561069 | ecrin-mdr-crc
Project description:In this publication, researchers investigated the intricate relationship between breast cancers and their microenvironment, specifically focusing on predicting treatment responses using multi-omic machine learning model. They collected diverse data types including clinical, genomic, transcriptomic, and digital pathology profiles from pre-treatment biopsies of breast tumors. Leveraging this comprehensive multi-omic dataset, the team developed ensemble machine learning models using different algorithms (Logistic Regression, SVM and Random Forest). These predictive models identifies patients likely to achieve a pathological complete response (pCR) to therapy, showcasing their potential to enhance treatment selection.
Please note that the authors also have an interactive dashboard to apply the fully-integrated NAT response model on new (or any desired) data. The user can find its link in their GitHub repository: https://github.com/micrisor/NAT-ML
For more information and clarification, please refer to the ReadMe_NAT-ML document in the files section.
2023-08-28 | BIOMD0000001075 | BioModels