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Record W2111816816 · doi:10.3389/fimmu.2012.00397

Myeloid nuclear differentiation antigen, neutrophil apoptosis and sepsis

2012· article· en· W2111816816 on OpenAlexafffund
Éric Milot, Nasser Fotouhi‐Ardakani, János G. Filep

Bibliographic record

VenueFrontiers in Immunology · 2012
Typearticle
Languageen
FieldImmunology and Microbiology
TopicNeutrophil, Myeloperoxidase and Oxidative Mechanisms
Canadian institutionsUniversité de MontréalHôpital Maisonneuve-Rosemont
FundersFonds de Recherche du Québec - SantéCanadian Institutes of Health Research
KeywordsMyeloid cellsSepsisMyeloidImmunologyApoptosisMedicineNeutrophil extracellular trapsAntigenInflammationBiologyGenetics

Abstract

fetched live from OpenAlex

Sepsis and septic shock are characterized by prolonged inflammation and delayed resolution, which are associated with suppression of neutrophil apoptosis. The role of the intrinsic apoptotic pathway and intracellular factors in regulation of neutrophil apoptosis remain incompletely understood. We previously reported that the nuclear factor MNDA (myeloid nuclear differentiation antigen) is fundamental to execution of the constitutive neutrophil death program. During neutrophil apoptosis MNDA is cleaved by caspases and relocated to the cytoplasm. However, when challenged with known mediators of sepsis, human neutrophils of healthy donors or neutrophils from patients with sepsis exhibited impaired MNDA relocation/cleavage parallel with myeloid cell leukemia-1 (MCL-1) accumulation and suppression of apoptosis. MNDA knockdown in a model cell line indicated that upon induction of apoptosis, MNDA promotes proteasomal degradation of MCL-1, thereby aggravating mitochondrial dysfunction. Thus, MNDA is central to a novel nucleus-mitochondrion circuit that promotes progression of apoptosis. Disruption of this circuit contributes to neutrophil longevity, thereby identifying MNDA as a potential therapeutic target in sepsis and other inflammatory pathologies.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.364
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.000
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 head0.009
GPT teacher head0.207
Teacher spread0.198 · 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.

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

Citations49
Published2012
Admission routes2
Has abstractyes

Explore more

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