MétaCan
Menu
Back to cohort
Record W2077669333 · doi:10.1016/j.devcel.2013.05.001

TIGAR Is Required for Efficient Intestinal Regeneration and Tumorigenesis

2013· article· en· W2077669333 on OpenAlexfundno aff
Eric C. Cheung, Dimitris Athineos, Pearl Lee, Rachel A. Ridgway, Wendy Lambie, Colin Nixon, Douglas Strathdee, Karen Blyth, Owen J. Sansom, Karen H. Vousden

Bibliographic record

VenueDevelopmental Cell · 2013
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer Research and Treatments
Canadian institutionsnot available
FundersBeatson Institute for Cancer ResearchMedical Research CouncilCanadian Institutes of Health ResearchMauritius Research CouncilCancer Research UK
KeywordsBiologyCarcinogenesisRegeneration (biology)Cell biologyComputational biologyGeneticsCancer

Abstract

fetched live from OpenAlex

Regulation of metabolic pathways plays an important role in controlling cell growth, proliferation, and survival. TIGAR acts as a fructose-2,6-bisphosphatase, potentially promoting the pentose phosphate pathway to produce NADPH for antioxidant function and ribose-5-phosphate for nucleotide synthesis. The functions of TIGAR were dispensable for normal growth and development in mice but played a key role in allowing intestinal regeneration in vivo and in ex vivo cultures, where growth defects due to lack of TIGAR were rescued by ROS scavengers and nucleosides. In a mouse intestinal adenoma model, TIGAR deficiency decreased tumor burden and increased survival, while elevated expression of TIGAR in human colon tumors suggested that deregulated TIGAR supports cancer progression. Our study demonstrates the importance of TIGAR in regulating metabolism for regeneration and cancer development and identifies TIGAR as a potential therapeutic target in diseases such as ulcerative colitis and intestinal cancer.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.002

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 head0.014
GPT teacher head0.249
Teacher spread0.235 · 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 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

Citations184
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueDevelopmental CellSame topicCancer Research and TreatmentsFrench-language works237,207