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Functional analysis of the <i>Drosophila</i> immune response during aging

2008· article· en· W2076397863 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueAging Cell · 2008
Typearticle
Languageen
FieldImmunology and Microbiology
TopicInvertebrate Immune Response Mechanisms
Canadian institutionsQueen's University
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health Research
KeywordsBiologyImmune systemSenescenceImmunityInflammationDrosophila (subgenus)ImmunosenescenceImmunologyDrosophila melanogasterFunction (biology)LongevityGeneEvolutionary biologyCell biologyGenetics

Abstract

fetched live from OpenAlex

One of the most dramatic changes associated with aging involves immunity. In aging mammals, immune function declines and chronic inflammation develops. The biological significance of this phenomenon and its relationship with aging is a priority for aging research. Drosophila is an invaluable tool in understanding the effects of aging on the immune response. Similar to the state of chronic inflammation in mammals, Drosophila exhibits a drastic up-regulation of immunity-related genes with age. However, it remains unclear whether immune function declines with age as seen in mammals. We evaluated the impact of aging on Drosophila immune function by examining across age the ability to eliminate and survive different doses of bacterial invaders. Our findings show that aging reduces the capacity to survive a bacterial infection. In contrast, we found no evidence that aging affects the ability to eliminate bacteria indicating that the mechanisms underlying immune senescence are not involved in eliminating bacteria or preventing their proliferation.

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.

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)0.001
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.215
Threshold uncertainty score0.583

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
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 head0.011
GPT teacher head0.198
Teacher spread0.187 · 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