MétaCan
Menu
Back to cohort
Record W3113031554 · doi:10.3390/cancers12123669

Getting Lost in the Cell–Lysosomal Entrapment of Chemotherapeutics

2020· review· en· W3113031554 on OpenAlexaff
Xingjian Zhai, Yassine El Hiani

Bibliographic record

VenueCancers · 2020
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCalcium signaling and nucleotide metabolism
Canadian institutionsDalhousie University
Fundersnot available
KeywordsCompartmentalization (fire protection)ExtracellularCell biologyAnticancer drugIntracellularCellBiologyCancer researchDrugNeurosciencePharmacologyEnzymeBiochemistry

Abstract

fetched live from OpenAlex

Despite extensive research, resistance to chemotherapy still poses a major obstacle in clinical oncology. An exciting strategy to circumvent chemoresistance involves the identification and subsequent disruption of cellular processes that are aberrantly altered in oncogenic states. Upon chemotherapeutic challenges, lysosomes are deemed to be essential mediators that enable cellular adaptation to stress conditions. Therefore, lysosomes potentially hold the key to disarming the fundamental mechanisms of chemoresistance. This review explores modes of action of classical chemotherapeutic agents, adaptive response of the lysosomes to cell stress, and presents physiological and pharmacological insights pertaining to drug compartmentalization, sequestration, and extracellular clearance through the lens of lysosomes.

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 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 score0.994
Threshold uncertainty score0.628

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 head0.027
GPT teacher head0.298
Teacher spread0.271 · 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 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

Citations16
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueCancersSame topicCalcium signaling and nucleotide metabolismFrench-language works237,207