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Programming of a Pro‐Adipogenic Phenotype in Offspring Born to Metabolically Compromised Pregnancies

2020· article· en· W3016995610 on OpenAlexaffabout
Anna Mikolajczak, Nada A. Sallam, Cini Mathew John, Radha Dutt Singh, Sarah Easson, Jennifer Thompson

Bibliographic record

VenueThe FASEB Journal · 2020
Typearticle
Languageen
FieldMedicine
TopicBirth, Development, and Health
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsOffspringAdipose tissueEndocrinologyInternal medicineAdipogenesisAdiponectinInsulin resistanceLeptinAdipocyteMedicineStromal vascular fractionHyperinsulinemiaType 2 diabetesDyslipidemiaBiologyPregnancyDiabetes mellitusObesity

Abstract

fetched live from OpenAlex

Objectives Determine the role of adipose tissue dysfunction in programming of cardiovascular disease risk in offspring born to dams with metabolic dysfunction. Methods The female mouse heterozygous for leptin receptor deficiency (Het db ) was used as a model of maternal metabolic dysfunction. These females exhibit higher adiposity, dyslipidemia and hyperinsulinemia during pregnancy. Our data show that this model reproduces programming of early‐onset cardiovascular disease risk reported in human offspring born to obese or diabetic mothers. We sought to test the hypothesis that programming of cardiovascular disease risk is attributable to perturbed adipose tissue development leading to later‐life adipose tissue dysfunction. Wild type (Wt) offspring from both Wt and Het db pregnancies were studied as neonates and adults. At 7 weeks of age, offspring were placed on either a control or high fat/sugar (HF/HS) diet. Adipogenic potential was examined in preadipocytes isolated from the stromal vascular fraction (SVF) of inguinal subcutaneous adipose tissue (iSAT) in both neonatal and adult Wt offspring. After induction of differentiation, Oil Red O staining was used to measure lipid droplet accumulation and qPCR was used to measure adipogenic markers. Flow cytometry was utilized to quantify adipogenic progenitors in SVF. Adipokine secretion was measured with ELISA. Several indices of adipose tissue function were measured in adult offspring, including adipose tissue insulin resistance (Adipo‐IR). Results NMR whole‐body fat mass was 1.3 fold higher (p < 0.01) and plasma resistin levels were 1.7 fold higher (p < 0.01) in Wt neonates born to Het db pregnancies. The iSAT of Wt neonates and adults born to Het db vs. Wt dams exhibited a shift in the cell size distribution from smaller adipocytes to larger adipocytes (p < 0.05), indicating that adipogenesis was accelerated in the iSAT of Het db neonates. The percentage of CD31‐CD45‐CD29+CD34+ viable SVF cells was higher in neonates from the Het db vs. Wt pregnancy. Preadipocytes isolated from Het db offspring exhibited a pro‐adipogenic phenotype in early life that persisted into adulthood. After HF/HS feeding, preadipocytes isolated from Wt female (p < 0.05) and male (p < 0.05) adult offspring born to Het db pregnancies accumulated more lipid during differentiation. Heightened adipogenesis in adult offspring was also accompanied by impaired insulin‐stimulated inhibition of lipolysis. Conclusions Adipose tissue dysfunction in offspring born to metabolically adverse pregnancies stems from in utero programming of a pro‐adipogenic phenotype in preadipocytes. Support or Funding Information Canadian Institutes of Health Research, Alberta Children’s Hospital Research Institute, Heart & Stroke Foundation of Canada and Libin Cardiovascular Institute of Alberta

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.044
GPT teacher head0.291
Teacher spread0.247 · 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 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

Citations0
Published2020
Admission routes2
Has abstractyes

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