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Record W3015598733 · doi:10.3390/ijms21072568

Role of Somatostatin in the Regulation of Central and Peripheral Factors of Satiety and Obesity

2020· review· en· W3015598733 on OpenAlexafffund
Ujendra Kumar, Sneha Singh

Bibliographic record

VenueInternational Journal of Molecular Sciences · 2020
Typereview
Languageen
FieldNeuroscience
TopicRegulation of Appetite and Obesity
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health Research
KeywordsOrexigenicObesityAppetiteHormoneEndocrinologyBiologyInternal medicineGhrelinSomatostatinReceptorFood intakeNeuroscienceNeuropeptideMedicineNeuropeptide Y receptor

Abstract

fetched live from OpenAlex

Obesity is one of the major social and health problems globally and often associated with various other pathological conditions. In addition to unregulated eating behaviour, circulating peptide-mediated hormonal secretion and signaling pathways play a critical role in food intake induced obesity. Amongst the many peptides involved in the regulation of food-seeking behaviour, somatostatin (SST) is the one which plays a determinant role in the complex process of appetite. SST is involved in the regulation of release and secretion of other peptides, neuronal integrity, and hormonal regulation. Based on past and recent studies, SST might serve as a bridge between central and peripheral tissues with a significant impact on obesity-associated with food intake behaviour and energy expenditure. Here, we present a comprehensive review describing the role of SST in the modulation of multiple central and peripheral signaling molecules. In addition, we highlight recent progress and contribution of SST and its receptors in food-seeking behaviour, obesity (orexigenic), and satiety (anorexigenic) associated pathways and mechanism.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.027
GPT teacher head0.303
Teacher spread0.276 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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

Citations75
Published2020
Admission routes2
Has abstractyes

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Same venueInternational Journal of Molecular SciencesSame topicRegulation of Appetite and ObesityFrench-language works237,207