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Record W4221080286 · doi:10.21856/j-pep.2022.1.10

CIRCADIAN DISRUPTION AS A FACTOR OF IMPAIRED ADAPTIVE T-CELL IMMUNITY RESPONSE

2022· article· en· W4221080286 on OpenAlexaff
A. R. Gevorkyan, Danyyl Ippolitov, Т.В. Бочарова

Bibliographic record

VenuePROBLEMS OF ENDOCRINE PATHOLOGY · 2022
Typearticle
Languageen
FieldNeuroscience
TopicCircadian rhythm and melatonin
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsCircadian rhythmCD8Internal medicineCD3EndocrinologyBiologyAcquired immune systemImmunityT cellCellular immunityImmune systemReceptorAndrologyImmunologyMedicine

Abstract

fetched live from OpenAlex

The study was carried out with the aim to evaluate the effects of continuous lightning (CL) and subsequent circadian rhythm disruption on CD4+/CD8+ populations of adaptive cell immunity. For further understanding of underlying processes that affect CD4+/CD8+ proliferation and differentiation, the expression levels of CD3+ and CD95+ cell receptors were evaluated. Chinchilla rabbits were exposed to shift work simulation - 24 hours of CL. We organized 5 time-related groups: 2, 4, 6, 12 months of CL respectively. The 5th group – corresponding control. Thymus derived slides were examined using immunofluorescence assay. A decrease in the expression of CD3+ and CD8+ and an increase in the expression of CD4+ lymphocytes, which was accompanied by an increase in the ratio of CD4+/CD8+ were found after 2 months of the experiment. After 4 and 6 months of CL, there was an increase in CD3+ expression and a decrease in CD4+ and CD8+ expression. The lowest levels of CD3+, CD4+ and CD8+ were recorded after 12 months of the experiment, which is a manifestation of significant immunosuppression due to premature aging of the thymus. The level of CD95+ lymphocytes was higher in the group after 12 months of CL, indicating the activation of apoptosis in thymocytes caused by circadian rhythms disruption under the influence of chronic light stress.

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)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.026
Threshold uncertainty score0.759

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0010.000

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 head0.274
Teacher spread0.240 · 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 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

Citations1
Published2022
Admission routes1
Has abstractyes

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