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Record W2160580322 · doi:10.3389/fphar.2013.00049

After the chemotherapy: potential mechanisms for chemotherapy-induced delayed skeletal muscle dysfunction in survivors of acute lymphoblastic leukaemia in childhood

2013· article· en· W2160580322 on OpenAlexaff
Celena Scheede‐Bergdahl, R. Thomas Jagoe

Bibliographic record

VenueFrontiers in Pharmacology · 2013
Typearticle
Languageen
FieldMedicine
TopicChildhood Cancer Survivors' Quality of Life
Canadian institutionsMcGill UniversityJewish General Hospital
Fundersnot available
KeywordsMedicineChemotherapyChildhood cancerOncologyLymphoblastic LeukemiaInternal medicineCancerBioinformaticsPediatricsLeukemiaBiology

Abstract

fetched live from OpenAlex

There is evidence that survivors of childhood cancers, such as acute lymphoblastic leukemia (ALL), have increased rates of long-term skeletal muscle dysfunction. This places them at higher risk of physical restriction and functional impairment as well as potentially contributing to observed increases in cardiovascular disease and insulin resistance in later life. The mechanisms underlying these changes in skeletal muscle are unknown but chemotherapy drugs used in treatment for ALL are strongly implicated. Normal skeletal muscle growth, development, and function are dependent on correctly functioning muscle satellite cells, muscle motor neurons, and muscle mitochondria. Each of these key components is potentially susceptible to damage by chemotherapy in childhood, particularly prolonged courses including repeated administration of combination chemotherapy. If this chemotherapy-induced damage is not fully reversible, impairment of satellite cells, muscle motor innervation, and mitochondria could, either singly or together, lead to the emergence of delayed or persistent skeletal muscle dysfunction many years later. The known effects of individual drugs used in the treatment of ALL are outlined and the need for specific targeted studies to investigate the mechanisms underlying persistent muscle dysfunction in survivors of ALL and other childhood cancers is highlighted.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.776
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
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 head0.007
GPT teacher head0.266
Teacher spread0.258 · 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.

Study designObservational
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

Citations64
Published2013
Admission routes1
Has abstractyes

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