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Record W4399206083 · doi:10.1016/j.coisb.2024.100519

ODE-based models of signaling networks in autophagy

2024· article· en· W4399206083 on OpenAlex
Markus Galhuber, Kathrin Thedieck

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.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueCurrent Opinion in Systems Biology · 2024
Typearticle
Languageen
FieldMedicine
TopicAutophagy in Disease and Therapy
Canadian institutionsnot available
FundersDeutsche ForschungsgemeinschaftAustrian Science FundEuropean CommissionHORIZON EUROPE Framework ProgrammeMinistère de l'Économie, de la Science et de l'Innovation - Québec
KeywordsOdeAutophagyComputer scienceBiologyMathematicsGeneticsApplied mathematics

Abstract

fetched live from OpenAlex

Aberrant metabolism and nutrient processing are hallmarks in cancer. Autophagy is a catabolic process, clearing macromolecules and providing metabolite intermediates for anabolism. Autophagy safeguards healthy cells from tumorigenesis while mobilizing metabolites promoting tumor growth. Autophagy is controlled by the mTOR signaling network in conjunction with AMPK and ULK1. This kinase triad features highly intertwined feedback and feedforward mechanisms, complicating predictions on nutrient and drug response. ODE-based models offer a deterministic approach frequently used for the exploration of signaling dynamics. Recent ODE models of the mTOR-AMPK-ULK1 network revealed non-linear behaviors, bistable switches, and oscillatory patterns, shedding light on the robustness and adaptability of autophagy control. We highlight emerging perspectives on AMPK in mTORC1-ULK1 crosstalk and mechanisms for integration into future models.

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)0.000
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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.532
Threshold uncertainty score0.491

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.079
GPT teacher head0.378
Teacher spread0.299 · 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