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Record W4386243494 · doi:10.1101/2023.08.28.555135

Ketogenic diet alters microglial morphology and changes the hippocampal lipidomic profile distinctively in stress susceptible <i>versus</i> resistant male mice upon repeated social defeat

2023· preprint· en· W4386243494 on OpenAlexafffund
Fernando Gonzàlez Ibáñez, Torin Halvorson, Kaushik Sharma, Chloe McKee, Micaël Carrier, Katherine Picard, Nathalie Vernoux, Kanchan Bisht, Jessica Deslauriers, Maciej Łałowski, Marie‐Ève Tremblay

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2023
Typepreprint
Languageen
FieldNeuroscience
TopicTryptophan and brain disorders
Canadian institutionsMcGill UniversityUniversity of British ColumbiaUniversité LavalUniversity of Victoria
FundersFonds de Recherche du Québec - SantéNatural Sciences and Engineering Research Council of CanadaConsejo Nacional de Ciencia y TecnologíaNational Institutes of HealthUniversity of VictoriaGenome British ColumbiaUniversité Laval
KeywordsKetogenic dietHippocampal formationSocial defeatMorphology (biology)EndocrinologyNeuroscienceInternal medicineBiologyPhysiologyMedicineZoologyEpilepsy

Abstract

fetched live from OpenAlex

Abstract Psychological stress confers an increased risk for several diseases including psychiatric conditions. The susceptibility to psychological stress is modulated by various factors, many of them being modifiable lifestyle choices. The ketogenic diet (KD) has emerged as a dietary regime that offers positive outcomes on mood and health status. Psychological stress and elevated inflammation are common features of neuropsychiatric disorders such as certain types of major depressive disorder. KD has been attributed anti-inflammatory properties that could underlie its beneficial consequences on the brain and behavior. Microglia are the main drivers of inflammation in the central nervous system. They are known to respond to both dietary changes and psychological stress, notably by modifying their production of cytokines and relationships among the brain parenchyma. To assess the interactions between KD and the stress response, including effects on microglia, we examined adult male mice on control diet (CD) versus KD that underwent 10 days of repeated social defeat (RSD) or remained non-stressed (controls; CTRLs). Through a social interaction test, stressed mice were classified as susceptible (SUS) or resistant (RES) to RSD. The mouse population fed a KD tended to have a higher proportion of individuals classified as RES following RSD. Microglial morphology and ultrastructure were then analyzed in the ventral hippocampus CA1, a brain region known to present structural alterations as a response to psychological stress. Distinct changes in microglial soma and arborization linked to the KD, SUS and RES phenotypes were revealed. Ultrastructural analysis by electron microscopy showed a clear reduction of cellular stress markers in microglia from KD fed animals. Furthermore, ultrastructural analysis showed that microglial contacts with synaptic elements were reduced in the SUS compared to the RES and CTRL groups. Hippocampal lipidomic analyses lastly identified a distinct lipid profile in SUS animals compared to CTRLs. These key differences, combined with the distinct microglial responses to diet and stress, indicate that unique metabolic changes may underlie the stress susceptibility phenotypes. Altogether, our results reveal novel mechanisms by which a KD might improve the resistance to psychological stress. Highlights Ketogenic diet tends to promote resistance to psychological stress Hippocampal microglia show morphological adaptations to stress and diet Microglia of stress-susceptible mice make less synaptic contacts Microglia of ketogenic diet-fed mice show less signs of cellular stress Lipids are differentially regulated in the hippocampi of susceptible mice

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 score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.032
GPT teacher head0.244
Teacher spread0.212 · 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

Citations2
Published2023
Admission routes2
Has abstractyes

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