MétaCan
Menu
Back to cohort
Record W1963495389 · doi:10.4161/auto.19738

Autophagy is active in normal colon mucosa

2012· article· en· W1963495389 on OpenAlexafffund
Jean‐François Groulx, Taoufik Khalfaoui, Yannick D. Benoit, Gérald Bernatchez, Julie Carrier, Nùria Basora, Jean‐François Beaulieu

Bibliographic record

VenueAutophagy · 2012
Typearticle
Languageen
FieldMedicine
TopicAutophagy in Disease and Therapy
Canadian institutionsUniversité de Sherbrooke
FundersCanadian Institutes of Health Research
KeywordsBECN1AutophagyBiologyIntestinal mucosaEpitheliumColorectal cancerCell biologyCellCancer researchCancerInternal medicineApoptosisMedicineBiochemistry

Abstract

fetched live from OpenAlex

Recently, autophagy has been found to be strongly activated in colon cancer cells, but few studies have addressed the normal colon mucosa. The aim of this study was to characterize autophagy in normal human intestinal cells. We used the expression of LC3-II and BECN1 as well as SQSTM1 as markers of autophagy activity. Using the normal human intestinal epithelial crypt (HIEC) cell experimental model, we found that autophagy was much more active in undifferentiated cells than in differentiated cells. In the normal adult colonic mucosa, BECN1 was found in the proliferative epithelial cells of the lower part of the gland while SQSTM1 was predominantly found in the differentiated cells of the upper part of the gland and surface epithelium. Interestingly, the weak punctate pattern of SQSTM1 expression in the lower gland colocalized with BECN1-labeled autophagosomes. The usefulness of SQSTM1 as an active autophagy marker was confirmed in colon cancer specimens at the protein and transcript levels. In conclusion, our results show that autophagy is active in the colonic gland and is associated with the intestinal proliferative/undifferentiated and progenitor cell populations.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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

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 head0.015
GPT teacher head0.301
Teacher spread0.286 · 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 designObservational
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

Citations49
Published2012
Admission routes2
Has abstractyes

Explore more

Same venueAutophagySame topicAutophagy in Disease and TherapyFrench-language works237,207