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Record W2122407910 · doi:10.1242/jeb.01211

Time-dependent expression of heat shock proteins 70 and 90 in tissues of the anoxic western painted turtle

2004· article· en· W2122407910 on OpenAlexaff
Valeria Ramaglia, Leslie T. Buck

Bibliographic record

VenueJournal of Experimental Biology · 2004
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHeat shock proteins research
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPainted turtleHeat shock proteinHsp90Anoxic watersDownregulation and upregulationBiologyTurtle (robot)Hsp70Skeletal muscleInternal medicineShock (circulatory)Cardiac muscleEndocrinologyProtein expressionIntracellularCell biologyEcologyMedicineBiochemistryGene

Abstract

fetched live from OpenAlex

Expression of the constitutive Hsp73, inducible Hsp72 and Hsp90 was investigated in brain, heart, liver and skeletal muscle of the anoxia-tolerant western painted turtle Chrysemys picta bellii in response to 2, 6, 12, 18, 24 and 30 h forced dives and following 1 h recovery from 12, 24 and 30 h forced dives at 17 degrees C. During a dive, expression of all three Hsps examined remained at control levels for at least 12 h in all tissues examined except the liver, where Hsp72 showed a decrease at 12 h, reaching a significant threefold decrease by 24 h. Brain and liver Hsp73, 72 and 90 expression increased two- to threefold at 18, 24 and 30 h. Heart and muscle Hsp73 and heart Hsp90 expression remained at normoxic levels throughout the entire dive, while heart and muscle Hsp72 and muscle Hsp90 increased two- to fourfold at 24 and 30 h. Following reoxygenation, Hsp expression increased in all tissues examined. These data indicate that increased Hsp expression is not critical in the early adaptation to anoxic survival and that short-term anoxia is probably not a stress for species adapted to survive long periods without oxygen. However, the late upregulation of heat shock proteins during anoxia suggests that stress proteins play a role in promoting long-term anoxia tolerance.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.279

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 head0.013
GPT teacher head0.310
Teacher spread0.297 · 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 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

Citations68
Published2004
Admission routes1
Has abstractyes

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