Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
482
datasets available to search
ShareScore release 0.9.0
Dataset results
482 results for “Pituitary”
Primary cilia are required for cell-type determination and angiogenesis in the pituitary development
GEO Series GSE267748. Mus musculus. 2 samples. Type: Expression profiling by high throughput sequencing.
Transcriptomic effects of early life and peripubertal dietary vitamin D deficiency on mouse ovaries and pituitary glands
GEO Series GSE48170. Mus musculus. 24 samples. Type: Expression profiling by array.
Effect of dioxin on pituitary mRNAs in maternal rats at postpartum day 7
GEO Series GSE135932. Rattus norvegicus. 8 samples. Type: Expression profiling by array.
Dataset related to article "Impact of age on postsurgical outcomes of nonfunctioning pituitary adenomas"
<p>This record contains data related to article "Impact of age on postsurgical outcomes of nonfunctioning pituitary adenomas"</p> <p>Abstract</p> <p><strong>Purpose: </strong> The management of pituitary adenomas in the elderly has become a relevant clinical issue, in relationship with improved life expectancy and spreading use of imaging techniques. In this single-center and retrospective study, we investigated the impact of age on peri- and postsurgical outcomes in patients undergoing transnasal sphenoidal (TNS) surgery for pituitary adenomas.</p> <p><strong>Methods: </strong> One-hundred-sixty-nine patients (62% males) undergoing endoscopic transphenoidal (TNS) surgery for nonfunctioning pituitary adenomas (NFPAs) were enrolled. Patients were subdivided into three groups according to age tertiles: ≤56 (group 1), 57-69 (group 2), and ≥70 (group 3) years. Postsurgical and endocrinological outcomes were evaluated and compared among the three age groups.</p> <p><strong>Results: </strong> 37/169 patients (21.9%) developed at least one perisurgical complication, without significant association with the patients' age (P = 0.838), Charlson co-morbidity score (P = 0.326), and American Society of Anesthesiologist score (P = 0.616). In the multivariate regression analysis, the adenoma size resulted the only determinant of perisurgical complication (odds ratio [OR] 1.07, 95% confidence interval [C.I.] 1.00-1.13; P = 0.044). The development and the recovery of at least one pituitary hormone deficiency were observed in 12.2% and 14.2% of patients, respectively. The risk of developing new pituitary hormone deficiencies was correlated with cavernous sinus invasion as evaluated by magnetic resonance imaging (hazard ratio [HR] 4.19, 95% C.I. 1.39-12.66; P = 0.010), whereas the probability to normalize at least one pituitary hormone deficiency was significantly correlated with younger age of patients (HR 0.27, 95% CI 0.12-0.61; P = 0.002).</p> <p><strong>Conclusions: </strong> The results of this study reinforce the concept that endoscopic TNS surgery is a safe therapeutic option in the elderly patients with NFPA, even in presence of comorbidities and high anesthetic risk.</p>
Validation of a clinicopathological classification for predicting outcomes of pituitary tumours: retrospective cohort study in a pituitary tumour centre of excellence, 2013–2023
<p><strong>Simple Summary:</strong> This retrospective study aims to classify a series of pituitary neuroendocrine tumours (PitNETs), typified according to the WHO 2017 recommendations, using Trouillas et al.’s clinicopathological classification from 2013. We analysed 166 patients who underwent PitNET surgery from 2013 to 2023. The tumours were identified according to the gene and immunohistochemistry expression of pituitary transcription factors and adenohypophyseal hormones. The PitNETs were graded based on the invasion observed in MRI and the Ki-67 index. The study found that grade 2a and 2b tumours, T2 signal intensity ratio (SIR), and silent corticotroph tumours were associated with lower progression-free survival rates. Tumour volume and T2 SIR were independent predictors of recurrence/progression, with a T2 SIR of 2 or more showing a significantly higher risk. These findings emphasise the prognostic value of the five-grade classification and underscore the importance of radiological evaluation for managing PitNETs.</p> <p> </p> <p><strong>Abstract: </strong>Immunostaining of transcription factors allows a more exact classification of pituitary neuroendocrine tumours (PitNETs), but not a better prediction of their clinical behaviour. This retrospective, single-centre study aims to classify a series of PitNETs using Trouillas et al.’s clinicopathological classification from 2013. We analysed 166 patients undergoing PitNET surgery in 2013–2023. Tumours were identified according to the gene and immunohistochemical expression of PitNET transcription factors plus adenohypophyseal hormones. Tumours were classified according to a grading system based on MRI invasion and Ki-67 index. Eighty-one (48.8%) patients had grade 2a tumours; 71 (42.8%), grade 1a; 8 (4.8%), 2b; and 6 (3.6%), 1b. At a mean follow-up of 57.8 (standard deviation 30) months, 13.9% (n=23) showed recurrence/progression; independent predictors of recurrence were tumour volume (p=0.031) and T2 signal intensity ratio (SIR) (p<0.001). This risk was 18.6-fold higher for a T2 SIR of 2 or more. Grade 2a and 2b tumours, T2 SIR, and silent corticotroph adenomas (SCAs) were associated with lower progression-free survival. Our results add more evidence to the prognostic value of the five-grade PitNET classification and suggest higher clinical surveillance of patients with SCAs is warranted. The MRI findings highlight the increasing value of radiological evaluation for managing PitNETs.</p>
Identification of reproductive performance-related genes in the bovine hypothalamus and pituitary gland and analysis of the regulatory network
GEO Series GSE160721. Bos taurus. 18 samples. Type: Expression profiling by high throughput sequencing.
Novel Regulators and Developmental Pathways of Pituitary Thyrotrope Subpopulations
GEO Series GSE205418. Mus musculus. 2 samples. Type: Expression profiling by high throughput sequencing.
Fundamental mechanisms causing pituitary stem cell aging in mice and humans
GEO Series GSE299835. Mus musculus. 4 samples. Type: Expression profiling by high throughput sequencing.
Transcriptomic effects of medical treatment on gene expression of growth hormone secreting pituitary neruoendocrine tumour biology
GEO Series GSE200175. Rattus norvegicus; Homo sapiens. 165 samples. Type: Expression profiling by high throughput sequencing.
The transcriptomic profile of porcine anterior pituitary cells is influenced by adiponectin
GEO Series GSE122311. Sus scrofa domesticus; Sus scrofa. 4 samples. Type: Expression profiling by array.
Pituitary RNA-seq in Egr1cKO mice
GEO Series GSE217927. Mus musculus. 24 samples. Type: Expression profiling by high throughput sequencing.
Effect of maternal dioxin exposure on pituitary mRNAs in fetal rats at gestational day 18
GEO Series GSE138694. Rattus norvegicus. 12 samples. Type: Expression profiling by array.
The pituitary hormonal changes related to feed efficiency in pigs
GEO Series GSE132522. Sus scrofa. 16 samples. Type: Expression profiling by high throughput sequencing.
Transcriptional changes associated with functioning and non-functioning Pituitary adenomas.
GEO Series GSE201439. Homo sapiens. 25 samples. Type: Expression profiling by high throughput sequencing.
The effects of phoenixin-14 on the hypothalamic-pituitary-gonadal (HPG) axis and spawning in green-spotted puffer (Dichotomyctere nigroviridis)
GEO Series GSE183029. Dichotomyctere nigroviridis. 22 samples. Type: Expression profiling by high throughput sequencing.
Comparative anterior pituitary miRNA and mRNA expression profiles of Bama minipigs and Landrace pigs reveal potential molecular network involved in animal postnatal growth [mRNA-Seq]
GEO Series GSE68490. Sus scrofa. 2 samples. Type: Expression profiling by high throughput sequencing.
miR-34a is upregulated in AIP mutated pituitary adenomas and induces octreotide-resistant cell proliferation and growth hormone secretion
GEO Series GSE140604. Homo sapiens; synthetic construct. 21 samples. Type: Expression profiling by array.
Disruption of the Wnt-antagonist APC in the pituitary stem cells drives adamantinomatous craniopharyngioma
GEO Series GSE282683. Mus musculus. 11 samples. Type: Expression profiling by high throughput sequencing.
Scanning and Mining of High Fecundity Genes by Oxford Nanopore Technologies (ONT) in Sheep (Ovis aries) Pituitary
GEO Series GSE275684. Ovis aries. 6 samples. Type: Expression profiling by high throughput sequencing.
Single-cell analysis of mouse pituitaries
GEO Series GSE215111. Mus musculus. 3 samples. Type: Expression profiling by high throughput sequencing.
ScienceDex guides
Understand access before you commit
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.