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Record W2052092420 · doi:10.2298/abs140124002m

Lymphocytes’ ‘last stand’ on the nuclear matrix after whole body exposure of rats to low-let ionizing radiation

2014· article· en· W2052092420 on OpenAlexaff
Vesna Martinović, Žarko Ivanović, Mirjana Mihailović, Svetlana Ivanović‐Matić, Goran Poznanović, Melita Vidaković

Bibliographic record

VenueArchives of Biological Sciences · 2014
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicDNA Repair Mechanisms
Canadian institutionsInstitute for Biological Sciences
FundersMinistarstvo Prosvete, Nauke i Tehnološkog Razvoja
KeywordsNuclear matrixDNA damageDNA repairComet assayIonizing radiationMatrix (chemical analysis)ApoptosisDNA fragmentationBiologyOxidative stressMolecular biologyPoly ADP ribose polymeraseProgrammed cell deathProliferating cell nuclear antigenFragmentation (computing)Cell biologyIrradiationChemistryDNABiochemistryChromatin

Abstract

fetched live from OpenAlex

We examined the functions of the rat lymphocyte nuclear matrix after a single exposure to total body irradiation with doses ranging from sublethal to lethal. Irradiation induced systemic oxidative stress, detected as increased activities of serum SOD and catalase, lymphocyte DNA damage, detected by the Comet assay, and apoptosis. After irradiation with lower doses, the recruitment of DNA repair centers on the matrix was observed by Western analysis as increased levels of matrix-associated PARP-1, p53 and PCNA. Augmented partitioning of the pro-survival transcription factor NF-?B on the matrix was also detected after irradiation. Exposure to a lethal dose caused breakdown of the matrix, observed as lamin B cleavage, and of the matrix-associated DNA repair centers, detected as caspase-mediated PARP-1 proteolysis and loss of protein associations with the matrix. These findings suggest that the nuclear matrix establishes functional 2 interactions in a defensive mechanism, integrated in a decision-making process that resolves cell fate.

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 score0.032
Threshold uncertainty score0.205

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 head0.010
GPT teacher head0.240
Teacher spread0.230 · 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

Citations0
Published2014
Admission routes1
Has abstractyes

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