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Expression of somatostatin receptors in splanchnic blood vessels of normal and cirrhotic rats

2007· article· en· W2074270225 on OpenAlexaff
Hendrik Reynaert, Elke Van Rossen, Naoki Uyama, Nirjhar Chatterjee, Ujendra Kumar, Daniël Urbain, Albert Geerts

Bibliographic record

VenueLiver International · 2007
Typearticle
Languageen
FieldMedicine
TopicNeuroendocrine Tumor Research Advances
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsSplanchnicSomatostatin receptorMedicinePortal venous pressureCirrhosisInternal medicineSomatostatinEndocrinologySomatostatin receptor 2Superior mesenteric arteryPortal hypertensionReceptorPathologyBlood flow

Abstract

fetched live from OpenAlex

BACKGROUND/AIMS: Somatostatin has been used for over two decades to treat acute variceal bleeding. Although it is assumed that somatostatin lowers portal pressure by constriction of the splanchnic arteries, little is known about the expression of somatostatin receptors (SSTR) in splanchnic blood vessels. In this study we investigated SSTR expression in splanchnic blood vessels from normal and cirrhotic rats. METHODS/RESULTS: Cirrhosis was induced by intraperitoneal injection of 50 mg thioacetamide twice a week for 14 weeks. In portal vein, mesenteric artery and aorta of normal and cirrhotic rats, mRNA for the five known SSTR was measured by quantitative reverse transcriptase-polymerase chain reaction. SSTR subtypes 1, 2, 3 and 4 were expressed, but subtype 5 was undetectable. In the portal vein of cirrhotic animals, SSTR1 was significantly down-regulated as compared with controls. Otherwise, no major differences in receptor expression between normal and cirrhotic animals were observed. Using immunohistochemistry, we identified all five receptors, although the staining of receptor 5 was very weak. CONCLUSION: All five SSTR are expressed in splanchnic blood vessels. Our results suggest that cirrhosis reduces expression of SSTR1 in portal vein. In other vessels, no major differences between the normal and cirrhotic state were noted.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.260
Threshold uncertainty score0.286

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.015
GPT teacher head0.309
Teacher spread0.294 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations12
Published2007
Admission routes1
Has abstractyes

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