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Longitudinal <sup>1</sup> H NMR Metabolomics Analysis Identifies Differences in Maternal Response to Pregnancy and Lactation between Lean and Diet‐Induced Obese Sprague‐Dawley Rats

2017· article· en· W4389023032 on OpenAlexafffund
Heather A. Paul, Marc R. Bomhof, Hans J. Vogel, Raylene A. Reimer

Bibliographic record

VenueThe FASEB Journal · 2017
Typearticle
Languageen
FieldMedicine
TopicBirth, Development, and Health
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health ResearchAlberta Innovates - Health Solutions
KeywordsLactationOffspringPregnancyEndocrinologyObesityInternal medicineGestationContext (archaeology)BiologyWeaningMedicine

Abstract

fetched live from OpenAlex

Maternal obesity adversely affects both maternal and offspring health and increases the risk of metabolic disease in offspring in later life. However, how lean versus obese mothers differ in their metabolic response to pregnancy and lactation and their significance in the context of programming of offspring metabolic disease remains to be determined. Here, using an animal model of maternal obesity, we sought to identify the longitudinal metabolic changes characterizing obese versus lean pregnant and lactating dams in order to identify key differences in how obese and lean dams respond to pregnancy and lactation and the potential impact on offspring metabolic health. Obesity was induced in female Sprague‐Dawley rats over 10 weeks using a high‐fat/sucrose diet. A lean control group was maintained on a standard AIN‐93 diet throughout the study. Diet‐induced obese and lean female Sprague‐Dawley rats were bred and maintained on their respective diets throughout gestation and lactation. At parturition, litters were culled to 10 pups. The study concluded at weaning of the pups. Metabolites in maternal serum collected pre‐pregnancy, on gestation day 14, and lactation day 19 were measured and quantified using proton nuclear magnetic resonance ( 1 H NMR) spectroscopy and analyzed using both univariate and multivariate statistical analysis. Maternal body weight, food intake, glycaemia, insulinaemia, and body composition was assessed. Pup body weight and body composition was also measured. Obese females were heavier than lean females throughout the study (p<0.05). Obese dams had higher caloric intake during gestation (p<0.05) but not lactation, and had higher fat weight and percent body fat at weaning (p<0.05). No differences in glycaemia and insulinaemia were detected during either pregnancy or lactation. Pups of obese dams weighed more by lactation day 7, remained heavier until weaning, and had higher percent body fat at weaning (p<0.05). Results indicate that though some overlap exists with respect to metabolic changes that occur as dams become pregnant and transition to lactation, some key differences are present. For example, when comparing changes in circulating levels of ketone bodies (beta‐hydroxybutyrate, acetate, acetoacetate) from pre‐pregnancy to gestation, the significance of the difference was higher in lean dams (p<1×10 −5 ) compared to obese dams (p<0.01), which contributed to a higher degree of similarity between pre‐pregnancy and gestational metabolic profiles in obese dams (R 2 =0.709, Q 2 =0.541) compared to lean dams (R 2 =0.889, Q 2 =0.847). In summary, longitudinal 1 H NMR metabolomics is a valuable tool in revealing key differences in metabolic adaptations to pregnancy and lactation between lean and obese dams that has the potential to improve understanding of the increased risk of adverse outcomes in mothers with obesity and their offspring. Support or Funding Information Funded by AIHS, NSERC, and CIHR

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 score0.003

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 head0.062
GPT teacher head0.327
Teacher spread0.265 · 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".

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Citations0
Published2017
Admission routes2
Has abstractyes

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