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Record W3186836245 · doi:10.3389/fimmu.2021.696311

The Impact of Programmed Cell Death on the Formation of Tertiary Lymphoid Structures

2021· review· en· W3186836245 on OpenAlexafffund
Mélanie Dieudé, Imane Kaci, Marie‐Josée Hébert

Bibliographic record

VenueFrontiers in Immunology · 2021
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicExtracellular vesicles in disease
Canadian institutionsCentre Hospitalier de l’Université de MontréalUniversité de MontréalTranslational Research in Oncology
FundersCanadian Institutes of Health ResearchKidney Foundation of Canada
KeywordsGerminal centerImmune systemApoptosisInflammationProgrammed cell deathImmunologyLymphatic systemDendritic cellCancer researchMedicineBiologyCell biologyB cellAntibody

Abstract

fetched live from OpenAlex

Tertiary lymphoid structures are clusters of lymphoid tissue that develop post-natally at sites of chronic inflammation. They have been described in association with infection, autoimmune disorders, cancer, and allograft rejection. In their mature stage, TLS function as ectopic germinal centers, favoring the local production of autoantibodies and cytokines. TLS formation tends to parallel the severity of tissue injury and they are usually indicative of locally active immune responses. The presence of TLS in patients with solid tumors is usually associated with a better prognosis whereas their presence predicts increased maladaptive immunologic activity in patients with autoimmune disorders or allograft transplantation. Recent data highlight a correlation between active cell death and TLS formation and maturation. Our group recently identified apoptotic exosome-like vesicles, released by apoptotic cells, as novel inducers of TLS formation. Here, we review mechanisms of TLS formation and maturation with a specific focus on the emerging importance of tissue injury, programmed cell death and extracellular vesicles in TLS biogenesis.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.012
GPT teacher head0.282
Teacher spread0.270 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations20
Published2021
Admission routes2
Has abstractyes

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