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Record W1603633056 · doi:10.18433/j3cg6g

Paradoxical Signaling Pathways in Developing Thymocytes

2011· review· en· W1603633056 on OpenAlexvenueno aff
Aws Alshamsan

Bibliographic record

VenueJournal of Pharmacy & Pharmaceutical Sciences · 2011
Typereview
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicPharmacological Effects of Natural Compounds
Canadian institutionsnot available
FundersDeanship of Scientific Research, King Saud UniversityKing Saud University
KeywordsMAPK/ERK pathwayCell biologySelection (genetic algorithm)BiologySignal transductionCancer researchComputer science

Abstract

fetched live from OpenAlex

Thymocytes are subjected to processes of selection during their life in the thymus; negative selection for autoreactive thymocytes and positive selection for self-MHC restricted self-tolerant cells. Interestingly, signals for positive or negative selection originate from the same receptor. More importantly, evidence showed that both death and survival signals are mediated by the MAPK pathway. The degree and order of ERK activation, but not other MAPK proteins, has been found to be different in either cases of cell fate. Therefore, it is suspected that the kinetics of ERK after activation may dictate cell death or survival. There are two important GEF proteins that are involved in Ras/ERK activation, RasGRP and SOS. It is thought that the level, order and kinetics of ERK are influenced upstream by the type of GEF. This review discusses the role of both GEF proteins in positive and negative selection and how this reflects on ERK activation.

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)0.000
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 score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
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 head0.512
GPT teacher head0.556
Teacher spread0.044 · 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

Citations3
Published2011
Admission routes1
Has abstractyes

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