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Record W2032226181 · doi:10.4239/wjd.v1.i3.89

Mechanisms of developmental programming of the metabolic syndrome and related disorders

2010· article· en· W2032226181 on OpenAlexafffund
Zhong‐Cheng Luo

Bibliographic record

VenueWorld Journal of Diabetes · 2010
Typearticle
Languageen
FieldMedicine
TopicBirth, Development, and Health
Canadian institutionsCentre Hospitalier Universitaire Sainte-Justine
FundersInstitute of Nutrition, Metabolism and DiabetesCanadian Institutes of Health Research
KeywordsMedicineBioinformaticsMetabolic syndromeInsulin resistanceLow birth weightBiomarkerEpigeneticsPregnancyDiseaseDiabetes mellitusEndocrinologyInternal medicineBiology

Abstract

fetched live from OpenAlex

There is consistent epidemiological evidence linking low birth weight, preterm birth and adverse fetal growth to an elevated risk of the metabolic syndrome (obesity, raised blood pressure, raised serum triglycerides, lowered serum high-density lipoprotein cholesterol and impaired glucose tolerance or insulin resistance) and related disorders. This "fetal or developmental origins/programming of disease" concept is now well accepted but the "programming" mechanisms remain poorly understood. We reviewed the major evidence, implications and limitations of current hypotheses in interpreting developmental programming and discuss future research directions. Major current hypotheses to interpret developmental programming include: (1) thrifty phenotype; (2) postnatal accelerated or catch-up growth; (3) glucocorticoid effects; (4) epigenetic changes; (5) oxidative stress; (6) prenatal hypoxia; (7) placental dysfunction; and (8) reduced stem cell number. Some hypothetical mechanisms (2, 4 and 8) could be driven by other upstream "driver" mechanisms. There is a lack of animal studies addressing multiple mechanisms simultaneously and a lack of strong evidence linking clinical outcomes to biomarkers of the proposed programming mechanisms in humans. There are needs for (1) experimental studies addressing multiple hypothetical mechanisms simultaneously; and (2) prospective pregnancy cohort studies linking biomarkers of the proposed mechanisms to clinical outcomes or surrogate biomarker endpoints. A better understanding of the programming mechanisms is a prerequisite for developing early life interventions to arrest the increasing epidemic of the metabolic syndrome, type 2 diabetes and other related disorders.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.164
Threshold uncertainty score0.258

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.008
GPT teacher head0.237
Teacher spread0.229 · 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 designObservational
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

Citations63
Published2010
Admission routes2
Has abstractyes

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