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Convergence of NF-κB-mediated inflammatory and HNF4α-mediated metabolic signaling networks in age-related thymic involution (HEM4P.229)

2014· article· en· W1563388124 on OpenAlexaff
Kenneth I. Weinberg, Dullei Min, Shivkumar Venkatasubrahmanyam, Brile Chung, Yujun Yang, Christine Goetz, Brent W. Winston, Mark R. Krampf, Jason Karamchandani, Bruce R. Blazar, Atul J. Butte

Bibliographic record

VenueThe Journal of Immunology · 2014
Typearticle
Languageen
FieldMedicine
TopicAdrenal Hormones and Disorders
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsTECThymic involutionBiologyInvolution (esoterism)ApoptosisFas ligandImmune systemImmunosenescenceInflammationCell biologyCancer researchImmunologyEndocrinologyInternal medicineProgrammed cell deathT cellGeneticsMedicine

Abstract

fetched live from OpenAlex

Abstract Thymic epithelial cell loss results in age-related thymic involution and immune deficiency. We investigated mechanisms of TEC loss during chronological aging (6 weeks, 7 months, 15 months) of normal C57BL6/J mice. Aged TEC showed replicative senescence with increased apoptosis, decreased proliferation, decreased telomerase activity and shortened telomere length. A subpopulation of aged TEC expressed Fas in response to pro-inflammatory cytokines (TNFα,IL-1β) made by aged thymocytes. Fas signaling and caspase-8 activation were induced by FasL selectively expressed by aged intrathymic memory T cells. Combined pharmacological inhibition of Caspase-8 and TEC growth stimulation by KGF restored thymopoiesis to neonatal levels. Aged TEC differentially expressed a 175-gene set predicted to be dually regulated by two transcription factors, NF-κB and HNF4α, which are activated by inflammatory cytokines and fatty acids, respectively. NF-κB and HNF4α signaling in aged TEC was confirmed by ChIP assays demonstrating binding to promoters of age-related genes, gene reporter assays, and synergistic induction of TEC apoptosis by inflammatory cytokines and fatty acids. TEC aging is mediated by the convergence of different TFs responsive to inflammatory and metabolic signals on shared promoters. Thymic regeneration in aging will require mitigation of the effects of non-autonomous inflammatory and metabolic signals, e.g., from infection and obesity, which drive TEC death and thymic involution.

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)0.001
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.869
Threshold uncertainty score0.429

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.007
GPT teacher head0.215
Teacher spread0.208 · 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".

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Citations0
Published2014
Admission routes1
Has abstractyes

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