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Record W2075508264 · doi:10.14740/gr617e

Cell Aging of Mouse Gastrointestinal Tract Observed by Light and Electron Microscopic Radioautography

2014· review· en· W2075508264 on OpenAlexvenueno aff
Nagata

Bibliographic record

VenueGastroenterology Research · 2014
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicDigestive system and related health
Canadian institutionsnot available
Fundersnot available
KeywordsGastrointestinal tractIn vivoCellDNARNAIn vitroDNA synthesisCell biologyMetabolismMacromoleculeBiologyChemistryBiochemistryGeneticsGene

Abstract

fetched live from OpenAlex

The term “cell aging” initially means how the cells change due to their aging. There are two meanings, i.e. how a cell changes when it is isolated from original animals such as in vitro cells in cell culture, otherwise how all the cells of an animal change in vivo due to the aging of the individual animal. We have been studying the latter changes from the viewpoint of the cell nutrients, the precursors for the macromolecular synthesis such as deoxyribonucleic acid (DNA), ribonucleic acid (RNA), proteins, glucides and lipids, which are incorporated and synthesized into various cells of individual animals. Therefore, this article deals with only the cell aging of animal cells in vivo , how the metabolism, i.e. incorporations and syntheses of respective nutrient precursors in various kinds of cells change due to the aging of individual experimental animals such as mice by means of microscopic radioautography to localize the RI-labeled precursors. The incorporations and syntheses of various precursors for macromolecules such as DNA, RNA, proteins, glucides, lipids and others in various kinds of cells of various organs in the gastrointestinal tract such as the mouth, esophagus, stomach and intestines are reviewed referring many original papers already published from our laboratory during these 60 years since the late 20th century. Gastroenterology Research. 2014;7(3-4):81-92 doi: http://dx.doi.org/10.14740/gr617e

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.879
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 integrity0.0000.001
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 head0.037
GPT teacher head0.364
Teacher spread0.326 · 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.

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

Citations0
Published2014
Admission routes1
Has abstractyes

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