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Record W3101931934 · doi:10.1136/bmjgh-2020-003979

India’s syndemic of tuberculosis and COVID-19

2020· editorial· en· W3101931934 on OpenAlexaff
Rukmini Shrinivasan, Saurabh Rane, Madhukar Pai

Bibliographic record

VenueBMJ Global Health · 2020
Typeeditorial
Languageen
FieldMedicine
TopicSARS-CoV-2 and COVID-19 Research
Canadian institutionsMcGill University
Fundersnot available
KeywordsProteostasisBiologyGenome instabilityRibosome biogenesisChromatinRibosomal RNACell biologyRibosomal proteinRNARibosomeGeneticsDNADNA damageGene

Abstract

fetched live from OpenAlex

Summary Chromatin instability and loss of protein homeostasis (proteostasis) are two well-established hallmarks of aging, which have been considered largely independent of each other. Using microfluidics and single-cell imaging approaches, we observed that, during the replicative aging of S.cerevisiae, proteostasis decline occurred specifically in the fraction of cells with decreased stability at the ribosomal DNA (rDNA) region. A screen of 170 yeast RNA-binding proteins identified ribosomal RNA (rRNA)- binding proteins as the most enriched group that aggregate upon a decrease in rDNA stability. We further found that loss of rDNA stability contributes to age-dependent aggregation of rRNA-binding proteins through aberrant overproduction of rRNAs. These aggregates negatively impact nucleolar integrity and global proteostasis and hence limit cellular lifespan. Our findings reveal a mechanism underlying the interconnection between chromatin instability and proteostasis decline and highlight the importance of cell-to-cell variability in aging processes.

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)0.003
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.011
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.010
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0020.001
Science and technology studies0.0020.001
Scholarly communication0.0040.003
Open science0.0020.001
Research integrity0.0110.014
Insufficient payload (model declined to judge)0.0100.008

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 head0.044
GPT teacher head0.456
Teacher spread0.412 · 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 designNot applicable
Domainnot available
GenreEditorial

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

Citations71
Published2020
Admission routes1
Has abstractyes

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