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Record W3085970850 · doi:10.3390/biology9090293

Maternal Obesity Does Not Exacerbate the Effects of LPS Injection on Pregnancy Outcomes in Mice

2020· article· en· W3085970850 on OpenAlexafffund
Natasha Virginkar, Julian K. Christians

Bibliographic record

VenueBiology · 2020
Typearticle
Languageen
FieldImmunology and Microbiology
TopicReproductive System and Pregnancy
Canadian institutionsBC Children's HospitalWomen's Health Research InstituteSimon Fraser University
FundersNatural Sciences and Engineering Research Council of CanadaSimon Fraser University
KeywordsLipopolysaccharidePregnancyBiologyFetusGestationEndocrinologyInternal medicineObesityAbortionInflammationOdds ratioPhysiologyImmunologyMedicine

Abstract

fetched live from OpenAlex

Obesity increases the risk of a number of pregnancy complications, potentially due to chronic inflammation. We predicted that an obesogenic high-fat diet (HFD) in mice would create an inflammatory environment that would exacerbate the effects of lipopolysaccharide (LPS), an inflammatory insult, administered during pregnancy. Females were placed on a HFD or a low-fat diet (LFD) prior to mating, injected with 2 µg LPS or control on gestational day 7 and collected on day 14. Treatment with LPS increased the odds that a female thought to be pregnant at injection had no conceptuses at day 14 (p = 0.024), suggesting that injection with LPS was more likely to induce complete abortion. However, there was no effect of diet on the odds of having no conceptuses at day 14 and no interaction between diet and LPS injection. Diet and LPS injection had no effect on the number of viable fetuses in females still pregnant at day 14. For fetal weight, there was a significant interaction between diet and treatment (p = 0.017), whereby LPS reduced fetal weight in HFD females but not in LFD females. However, LPS treatment of HFD females reduced fetal weight to that observed in control-injected LFD females. Although LPS increased the odds of abortion, there was little evidence that a HFD exacerbated the effects of LPS.

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)0.000
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 score0.032
Threshold uncertainty score0.303

Codex and Gemma teacher scores by category

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 integrity0.0000.000
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 head0.012
GPT teacher head0.239
Teacher spread0.227 · 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

Citations0
Published2020
Admission routes2
Has abstractyes

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