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Record W3192951577 · doi:10.1210/endrev/bnab022

Mechanisms of Weight Loss After Obesity Surgery

2021· review· en· W3192951577 on OpenAlexaff
Elina Akalestou, Alexander D. Miras, Guy A. Rutter, Carel W. le Roux

Bibliographic record

VenueEndocrine Reviews · 2021
Typereview
Languageen
FieldMedicine
TopicBariatric Surgery and Outcomes
Canadian institutionsUniversité de Montréal
FundersFP7 HealthBiotechnology and Biological Sciences Research CouncilMedical Research CouncilRosetrees TrustEuropean CommissionInnovative Medicines InitiativeImperial College Healthcare NHS TrustImperial College LondonIrish Research CouncilDepartment of Health and Social CareNovo NordiskNational Institute for Health and Care ResearchEuropean Federation of Pharmaceutical Industries and AssociationsImperial College Healthcare CharityDiabetes UKBritish Society for NeuroendocrinologyHealth Research BoardWellcome Trust
KeywordsWeight lossObesityAppetiteMedicineGastrointestinal tractWeight Loss SurgeryEnergy expenditurePsychological interventionObesity SurgeryIntensive care medicineBioinformaticsPhysiologySurgeryEndocrinologyInternal medicineGastric bypassBiologyPsychiatry

Abstract

fetched live from OpenAlex

Obesity surgery remains the most effective treatment for obesity and its complications. Weight loss was initially attributed to decreased energy absorption from the gut but has since been linked to reduced appetitive behavior and potentially increased energy expenditure. Implicated mechanisms associating rearrangement of the gastrointestinal tract with these metabolic outcomes include central appetite control, release of gut peptides, change in microbiota, and bile acids. However, the exact combination and timing of signals remain largely unknown. In this review, we survey recent research investigating these mechanisms, and seek to provide insights on unanswered questions over how weight loss is achieved following bariatric surgery which may eventually lead to safer, nonsurgical weight-loss interventions or combinations of medications with surgery.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.063
GPT teacher head0.345
Teacher spread0.282 · 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

Citations129
Published2021
Admission routes1
Has abstractyes

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