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Record W2905062882 · doi:10.1136/thoraxjnl-2018-212680

TAKling GDF-15 and skeletal muscle atrophy in pulmonary hypertension: are we there yet?

2018· letter· en· W2905062882 on OpenAlexaff
Yen‐Chun Lai, Steeve Provencher, Elena A. Goncharova

Bibliographic record

VenueThorax · 2018
Typeletter
Languageen
FieldMedicine
TopicGDF15 and Related Biomarkers
Canadian institutionsInstitut Universitaire de Cardiologie et de Pneumologie de QuébecUniversité Laval
Fundersnot available
KeywordsMedicinePulmonary hypertensionAtrophySkeletal muscleCardiologyMuscle atrophyInternal medicine

Abstract

fetched live from OpenAlex

Pulmonary arterial hypertension (PAH) is a progressive, life-threatening disease characterised by intense pulmonary vascular remodelling leading to high pulmonary arterial pressure, right ventricular failure and death. Although recent advances in therapies have proven to be effective in alleviating disease symptoms and improving functional capacity and survival, patients with PAH continue to suffer from persistent dyspnoea and significant exercise intolerance, which negatively impact their quality of life. In recent years, it has been increasingly recognised that exercise limitation in PAH is not merely due to right heart dysfunction and respiratory impairment, but is also a consequence of skeletal muscle abnormalities.1–3 Impaired skeletal muscle function, including reduced volitional and nonvolitional muscle strength and endurance2 4 5 decreased contractility,6 reduced capillary density and impaired oxygenation at the microcirculation level,4 7 as well as a shift towards type 2 muscle fibres,1 3 5 have been repeatedly documented in human PAH. Skeletal muscle atrophy has been less frequently reported3 and underlying mechanisms are not well studied. To date, numerous metabolic and signalling abnormalities associated with muscle dysfunction in PAH have been uncovered. These include a shift from oxidative to glycolytic metabolism, suppression of signalling pathways responsible for a hypertrophic response (eg, Akt and S6K), elevation of negative regulators of muscle homeostasis (eg, myostatin and activin A) and engagement of ubiquitin–proteasome-mediated muscle proteolysis signalling (eg, atrogin-1 and MuRF1).3 8 9 Loss of skeletal muscle microcirculation mediated by microRNA-126 downregulation, as well as sirtuin-3/AMP-activated protein kinase inactivation, and cytokines (ie, tumour necrosis factor-α and interleukin-6)-regulated skeletal muscle insulin resistance and abnormalities of mitochondrial biogenesis have also been documented.4 8 10 The molecular mechanisms of skeletal muscle atrophy in PAH, however, are not well understood, and available human PAH-related data are limited by a small number of studies with only a few …

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)0.001
metaresearch head score (Gemma)0.003
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: none
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.009
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.004
Open science0.0010.001
Research integrity0.0050.003
Insufficient payload (model declined to judge)0.0090.002

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 head0.026
GPT teacher head0.248
Teacher spread0.222 · 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
GenreCommentary

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

Citations8
Published2018
Admission routes1
Has abstractyes

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