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Record W2020748529 · doi:10.1007/s00547-005-2005-2

Involvement of calcineurin in ischemic myocardial damage

2006· article· en· W2020748529 on OpenAlexaff
Ashakumary Lakshmikuttyamma, Ponniah Selvakumar, Anil Sharma, Rajendra Sharma

Bibliographic record

VenueInternational Journal of Angiology · 2006
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicSignaling Pathways in Disease
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsMedicineCalcineurinAngiologyCardiologyInternal medicineTransplantation

Abstract

fetched live from OpenAlex

Calcineurin (CaN) has been reported as a critical mediator for cardiac hypertrophy and cardiac myocyte apoptosis. Ischemia is associated with multiple alterations in the extracellular and intracellular signaling of cardiomyocytes and may act as an inducer of apoptosis. Rat ischemic heart showed significant increase in CaN activity. In ischemic-reperfused hearts, the expression of CaN A was significantly low and immunoreactivity was observed in proteolytic bands of 46 kDa. Immunohistochemical studies showed strong staining of immunoreactivity in rat hearts that had undergone 30 minutes of ischemia followed by 30 minutes of reperfusion, similar to that found in human ischemic heart. To elucidate the mechanism of proteolysis of CaN A in ischemic-reperfused rat heart, in vitro proteolysis of bovine cardiac CaN by m-calpain was carried out. In the presence of Ca2+, the 60−kDa subunit (CaN A) was degraded to a 46-kDa immunoreactive fragment, whereas in the presence of Ca2+/CaM, immunoreactive fragments of 48 and 54 kDa were observed. Calpains are Ca2+-dependent cysteine proteases that regulate various enzymes, transcription factors, and structural proteins through limited proteolysis. The increase in CaN activity and strong immunostaining observed in ischemic-reperfused rat heart may be due to the calpain-mediated proteolysis of this CaM-dependent phosphatase. These studies remain an important area of in-depth investigation.

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 score0.029
Threshold uncertainty score0.261

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 head0.008
GPT teacher head0.263
Teacher spread0.255 · 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

Citations2
Published2006
Admission routes1
Has abstractyes

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