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1,336
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ShareScore release 0.9.0
Dataset results
1,336 results for “congenital”
Differences in biliopancreatic duct development exist in Type I congenital biliary dilatation based on microarray expression analysis of mRNAs and long noncoding RNAs
GEO Series GSE216428. Homo sapiens. 36 samples. Type: Non-coding RNA profiling by high throughput sequencing.
Braf-mutant Schwann cells divert to a repair phenotype to induce congenital demyelinating neuropathy [ScN]
GEO Series GSE262047. Mus musculus. 16 samples. Type: Expression profiling by high throughput sequencing.
Loss of Maenli lncRNA expression causes engrailed-1 dependent congenital limb malformations [RNA-seq]
GEO Series GSE137329. Mus musculus. 6 samples. Type: Expression profiling by high throughput sequencing.
Loss of Maenli lncRNA expression causes engrailed-1 dependent congenital limb malformations [Derived Virtual 4C]
GEO Series GSE137334. Mus musculus. 3 samples. Type: Other.
Loss of Maenli lncRNA expression causes engrailed-1 dependent congenital limb malformations [ChIP-seq]
GEO Series GSE137331. Mus musculus. 39 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
Delineating the angiogenic gene expression profile prior to pulmonary vascular remodeling in a lamb model of congenital heart disease
GEO Series GSE22590. Bos taurus; Ovis aries. 16 samples. Type: Expression profiling by array.
Congenital heart disease in Csx/ Nkx2.5 mutant embryos
GEO Series GSE78. Mus musculus. 18 samples. Type: Expression profiling by array.
Mutations in Bcl9 and Pygo genes cause congenital heart defects by tissue-specific perturbation of Wnt/β-catenin signaling
GEO Series GSE108240. Danio rerio. 6 samples. Type: Expression profiling by high throughput sequencing.
Serial Inversions Induce Tissue-specific Architectural Stripes, Gene Misexpression and Congenital Malformations [ChIP-seq]
GEO Series GSE116790. Mus musculus. 7 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
NGS-based miRNome profile in cardiac muscle tissue of congenital heart disease patients
GEO Series GSE185565. Homo sapiens. 10 samples. Type: Non-coding RNA profiling by high throughput sequencing.
Loss of Maenli lncRNA expression causes engrailed-1 dependent congenital limb malformations [DamID-seq]
GEO Series GSE137332. Mus musculus. 4 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
Loss-of-function mutations TDRD7 lead to a rare novel syndrome combining congenital cataract and non-obstructive azoospermia in humans
GEO Series GSE100019. Homo sapiens. 1 samples. Type: Genome variation profiling by SNP array.
NK2 model of congenital heart disease
GEO Series GSE528. Mus musculus. 26 samples. Type: Expression profiling by array.
A Congenital Anemia Dissociates the Pleiotropic Functions of Master Transcription Factor GATA1 [Patient Cut&Run]
GEO Series GSE155253. Homo sapiens. 8 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
A Switch in Iron Transport Mechanisms Defines Novel Forms of Congenital Chronic Kidney Disease
GEO Series GSE100254. Mus musculus. 18 samples. Type: Expression profiling by high throughput sequencing.
Rhesus placenta transcriptome in the setting of congenital RhCMV infection
GEO Series GSE87395. Macaca mulatta. 7 samples. Type: Expression profiling by array.
Chronic perinatal hypoxia delays cardiac maturation in a mouse model for cyanotic congenital heart disease
GEO Series GSE169214. Mus musculus. 18 samples. Type: Expression profiling by array.
Mutations in Bcl9 and Pygo genes cause congenital heart defects by tissue-specific perturbation of Wnt/β-catenin signaling
GEO Series GSE110783. Mus musculus. 15 samples. Type: Genome binding/occupancy profiling by high throughput sequencing; Expression profiling by high throughput sequencing.
Mutations in Bcl9 and Pygo genes cause congenital heart defects by tissue-specific perturbation of Wnt/β-catenin signaling (RNA-seq data set)
GEO Series GSE110782. Mus musculus. 8 samples. Type: Expression profiling by high throughput sequencing.
Data set from the article Malavazos AE, Capitanio G, Chessa M, Matelloni IA, Milani V, Stella E, Al Kassem LF, Sironi F, Boveri S, Giamberti A, Masocco M, Ranucci M, Menicanti L, Morricone L. Body mass index stratification in hospitalized Italian adults with congenital heart disease in relation to complexity, diagnosis, sex and age. Nutr Metab Cardiovasc Dis. 2019 Apr;29(4):367-377. doi: 10.1016/j.numecd.2019.01.009. Epub 2019 Jan 29. PMID: 30795994.
<p>The data set refers on the article Malavazos AE, Capitanio G, Chessa M, Matelloni IA, Milani V, Stella E, Al Kassem LF, Sironi F, Boveri S, Giamberti A, Masocco M, Ranucci M, Menicanti L, Morricone L. Body mass index stratification in hospitalized Italian adults with congenital heart disease in relation to complexity, diagnosis, sex and age. Nutr Metab Cardiovasc Dis. 2019 Apr;29(4):367-377. doi: 10.1016/j.numecd.2019.01.009. Epub 2019 Jan 29. PMID: 30795994.</p> <p>This is the abstract:</p> <p><strong>Background and aims: </strong>Adults with congenital heart disease (ACHD) are at risk of overweight and obesity, two major health problems, though underweight can be a negative prognostic factor too. Awareness of the body mass index (BMI) in ACHD is very limited. The present study describes the use and prevalence of BMI in Italian symptomatic hospitalized ACHD patients in relation to complexity by Bethesda system classification, diagnosis, sex and age.</p> <p><strong>Methods and results: </strong>We classified 1388 ACHD patients, aged 18-69 years, on the basis of their BMI, and compared them to the Italian reference population. In our total ACHD population we found a significantly higher prevalence of underweight compared to the Italian reference population (6.34% vs 3.20%). ACHD women were more underweight than men. Underweight decreased with age. Overweight was significantly less frequent in the total ACHD population (26.73% compared to 31.70%) in the Italian reference population. Men were more likely to be overweight than women. In statistical terms obesity was similar in the Italian reference population (10.50%) and our ACHD population (9.58%). Both overweight and obesity increased with age. Results were comparable using a diagnostic anatomical-functional classification and the Bethesda system classification.</p> <p><strong>Conclusions: </strong>In our cohort of ACHD the prevalence of underweight was double that of the Italian reference population. The prevalence of overweight was lower, while obesity was similar. Since BMI does not account for differences in body fat distribution, a future aim will be to quantify the visceral component of the adipose tissue in ACHD patients and examine their body composition in order to reflect their risk of acquired cardiovascular disease better, and either to maintain or achieve an adequate visceral component.</p>
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.