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Metabolic and Cardiovascular Actions of Nesfatin-1: Implications in Health and Disease

2017· review· en· W2584092725 on OpenAlexafffund
Naresh Ramesh, Kavishankar Gawli, Venkata Kiran Pasupulleti, Suraj Unniappan

Bibliographic record

VenueCurrent Pharmaceutical Design · 2017
Typereview
Languageen
FieldNeuroscience
TopicRegulation of Appetite and Obesity
Canadian institutionsUniversity of Saskatchewan
FundersCanadian Institutes of Health Research
KeywordsHomeostasisEndocrine systemDiseaseEndocrinologyBiologyGlucose homeostasisInternal medicinePancreasMedicinePhysiologyDiabetes mellitusHormoneInsulin resistance

Abstract

fetched live from OpenAlex

BACKGROUND: Metabolic homeostasis is achieved by proper functioning of a complex endocrine milieu, comprising of signals arising from the brain and peripheral tissues. Our knowledge of the factors regulating such balance is rapidly evolving, as new signaling molecules are being characterized. Of central interest is nesfatin-1, owing to its multifunctional tissue specific actions regulating food intake, body weight, blood glucose and cardiac functions. METHOD: This review discusses the tissue/system wide distribution and actions of nesfatin-1 in regulating metabolic and cardiovascular functions in healthy conditions and diseases. RESULTS: Nesfatin-1 is an 82 amino acid peptide encoded in the secreted precursor, nucleobinin-2 (NUCB2). It was first reported as a novel anorexigen and a fat reducing orphan ligand. Research to date has established nesfatin-1 in the regulation of food intake via modulation of neuropeptides in the feeding centers of brain. Nesfatin-1 expression was also reported to have a spectrum of peripheral tissue specific actions, which includes insulin secretion (pancreas), fat and glucose modulation (adipocyte), gastric motility and gastric acid secretion (stomach), hormone secretion and transit time (intestine) and mean arterial pressure and cardiac injury (heart). Abnormal levels of nesfatin-1 in circulation and/or variations in tissue specific expression have been observed in obesity, diabetes and cardiovascular diseases. CONCLUSION: The multifunctional biological actions of nesfatin-1 propelled this peptide as a therapeutic target, and as a potential biomarker of diseases. However, a better and comprehensive understanding of tissue specific effects of nesfatin-1 is critical prior to exploring its possible use in the detection and treatment of diseases.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.996
Threshold uncertainty score0.892

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.524
GPT teacher head0.505
Teacher spread0.019 · 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 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

Citations24
Published2017
Admission routes2
Has abstractyes

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