MétaCan
Menu
Back to cohort
Record W2334026052 · doi:10.1097/wnr.0000000000000243

Unpredictable chronic mild stress not chronic restraint stress induces depressive behaviours in mice

2014· article· en· W2334026052 on OpenAlexafffund
Shenghua Zhu, Ruo‐Yang Shi, Junhui Wang, Junfeng Wang, Xin‐Min Li

Bibliographic record

VenueNeuroreport · 2014
Typearticle
Languageen
FieldNeuroscience
TopicStress Responses and Cortisol
Canadian institutionsHealth Sciences CentreUniversity of AlbertaUniversity of Manitoba
FundersManitoba Health Research Council
KeywordsChronic stressAnxietyOpen fieldPsychologyDepression (economics)NoveltyStress (linguistics)Clinical psychologyInternal medicineMedicinePsychiatryNeuroscience

Abstract

fetched live from OpenAlex

The chronic stress model was developed on the basis of the stress-diathesis hypothesis of depression. However, these behavioural responses associated with different stress paradigms are quite complex. This study examined the effects of two chronic stress regimens on anxiety-like and depressive behaviours. C57BL/6 mice were subjected to unpredictable chronic mild stress or to chronic restraint stress for 4 weeks. Subsequently, both anxiety-like behaviours (open field, elevated plus maze and novelty suppressed feeding) and depression-like behaviours (tail suspension, forced swim and sucrose preference) were evaluated. Both chronic stress models generated anxiety-like behaviours, whereas only unpredictable chronic mild stress could induce depressive behaviours such as increased immobility and decreased sucrose consumption. These results of the present study provide additional evidence on how chronic stress affects behavioural responses and point to the importance of the validity of animal models of chronic stress in studying depression.

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: Bench or experimental · Consensus signal: Bench or experimental
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)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
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 head0.034
GPT teacher head0.288
Teacher spread0.253 · 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".

Quick stats

Citations119
Published2014
Admission routes2
Has abstractyes

Explore more

Same venueNeuroreportSame topicStress Responses and CortisolFrench-language works237,207