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A High Fat Diet in Pregnancy Modifies Mouse Maternal Behaviour

2020· article· en· W3017202111 on OpenAlexaff
Showall Moazzam, Noshin Noorjahan, Jessica S. Jarmasz, Yan Jin, Tabrez J. Siddiqui, Peter A. Cattini

Bibliographic record

VenueThe FASEB Journal · 2020
Typearticle
Languageen
FieldMedicine
TopicBirth, Development, and Health
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsPregnancyOvereatingFetusInternal medicineEndocrinologyMedicineObesityOffspringLactationGestationBreedPhysiologyBiologyAnimal science

Abstract

fetched live from OpenAlex

Background About a third of pregnant women of age 20–39 are obese, which carries significant risks for the mother and fetus, and adversely impacts pregnancy outcome. Specifically, women with obesity are at increased risk for peripartum depression. Maternal behaviour in mice is influenced by changes in hormone signaling in pregnancy, which is associated with effects on adult neurogenesis in the brain. Thus, we used mouse as a model system to gain further insight into the possible relationship between overeating/obesity and brain physiology and maternal behaviour. Objective To assess the ability of a high‐fat diet (HFD) versus a regular chow diet (CD), starting up to 10 weeks pre‐pregnancy, to modify glucose clearance before and during pregnancy and affect maternal behaviour in the CD1 mouse. Approach Two groups of 3–4 week‐old female CD1 mice were fed a HFD (fat=60 kcal%; carbohydrate=20 kcal%; protein=20 kcal%) or CD (fat=14 kcal%; carbohydrate=60 kcal%; protein=26 kcal%) and maintained on their respective diets throughout the study and weighed periodically. After at least 4 weeks of feeding on their diets, mice were allowed to breed. Glucose tolerance was tested using 2 g/kg of i.p. glucose at gestational day (GD) ‐1) after fasting (16 hours‐overnight) as well as during pregnancy at GD16.5. An even number of pregnant and non‐pregnant females were selected for each diet for maternal behaviour testing. Tests include an assessment of nest building at GD16.5–17 (use of nesting material and nest quality), and after birth pup retrieval at postpartum day (PD) 3, 4 and 5 (time of retrieval of each of the four pups within six minutes) using video capture. Results The HFD led to a significant increase in weight relative to mice fed a CD. HFD impaired glucose‐load clearances at GD ‐1 and 16.5 (p<0.05) compared to mice fed a CD. Mice fed on HFD performed poorly in the nest building task (p<0.01) as well as demonstrated a reduced completion rate on the pup retrieval test on PD3 (CD=8/10 vs. HFD 2/9 mice) but their retrieval response latency was improved by PD4 (CD=8/10 vs. HFD 8/9 mice) and PD5 (CD=7/10 vs. HFD 7/9 mice). Conclusions Initial observations suggest that a HFD for at least 4 weeks before and during pregnancy results in overweight CD1 mice with impaired glucose clearance, and a negative effect on maternal behaviour as assessed by nest‐building during pregnancy and pup retrieval postpartum; however, with regard to the latter, mice on the HFD show the ability to learn. Additional behavioural tests for locomotion, anxiety, risk avoidance and object recognition memory during or after pregnancy, as well as associated changes in hormonal signaling and adult neurogenesis are also currently under investigation.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.002

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 head0.043
GPT teacher head0.284
Teacher spread0.241 · 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 designBench or experimental
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
Published2020
Admission routes1
Has abstractyes

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