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Record W1984109394 · doi:10.1089/ars.2007.1919

Cysteine-Rich Protein Reverses Weight Loss in Lung Cancer Patients Receiving Chemotherapy or Radiotherapy

2007· article· en· W1984109394 on OpenAlexaff
Richard Tozer, Patricia Tai, Wilma Falconer, Thiérry Ducruet, Annie Karabadjian, Gustavo Bounous, John H. Molson, Wulf Dröge

Bibliographic record

VenueAntioxidants and Redox Signaling · 2007
Typearticle
Languageen
FieldMedicine
TopicNutrition and Health in Aging
Canadian institutionsCollège BoréalMcGill UniversityOutotec (Canada)Saskatchewan Cancer AgencyHamilton Regional Laboratory Medicine Program
Fundersnot available
KeywordsMedicineChemotherapyLung cancerAdverse effectRadiation therapyWeight lossInternal medicineCancerOxidative stressGastroenterologyCaseinSurgeryOncologyBiologyObesity

Abstract

fetched live from OpenAlex

Oxidative stress plays a role in the tumor-cytotoxic effect of cancer chemotherapy and radiotherapy and also in certain adverse events. In view of these conflicting aspects, a double-blind trial over a 6-month period was performed to determine whether a cysteine-rich protein (IMN1207) may have a positive or negative effect on the clinical outcome if compared with casein, a widely used protein supplement low in cysteine. Sixty-six patients with stage IIIB-IV non-small cell lung cancer were randomly assigned to IMN1207 or casein. Included were patients with a previous involuntary weight loss of > or =3%, Karnofsky status > or =70, and an estimated survival of >3 months. Thirty-five lung cancer patients remained on study at 6 weeks. Overall compliance was not different between treatment arms (42-44% or 13 g/day). The patients treated with the cysteine-rich protein had a mean increase of 2.5% body weight, whereas casein-treated patients lost 2.6% (p = 0.049). Differences in secondary endpoints included an increase in survival, hand-grip force, and quality of life. Adverse events were mild or moderate. Further studies will have to show whether the positive clinical effects can be confirmed and related to specific parameters of oxidative stress in the host.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.029
Threshold uncertainty score0.602

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.015
GPT teacher head0.322
Teacher spread0.307 · 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 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

Citations57
Published2007
Admission routes1
Has abstractyes

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