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Exercisenomics: A Wave of the Future?

2004· article· en· W1989286660 on OpenAlexaboutno aff
T. W. Balon

Bibliographic record

VenueMedicine & Science in Sports & Exercise · 2004
Typearticle
Languageen
FieldMedicine
TopicExercise and Physiological Responses
Canadian institutionsnot available
Fundersnot available
KeywordsWatsonClassicsMolecular Structure of Nucleic Acids: A Structure for Deoxyribose Nucleic AcidHistoryGeneticsMedicineGenealogyGerontologyBiology

Abstract

fetched live from OpenAlex

The year 2003 marked the 50th anniversary of the dissemination of James Watson and Francis Crick’s discovery paper on the structure of deoxyribose nucleic acid (DNA). Coincidentally, the American College of Sports Medicine (ACSM) also began celebration of its “Golden Anniversary.” Do these landmarks have anything in common? Superficially, one may not associate any relationship between these two events. However, if one “free associates” or “thinks outside the box,” it is incontestable that these two milestones celebrate not only extraordinary achievements but also dramatic developments in the areas of genetics, immunology, and endocrinology and how they relate to health and disease, respectively. Watson and Crick’s discovery served as a preamble and impetus to subsequent molecular biology studies by others, which have attempted to explore the different spheres including those of genetic information, inflammation, and endocrinology. Oh, how the field of exercise genetics has evolved from the early work of Ernst Jokl and Joseph Wolffe in the early 1950s to the elegant studies of Claude Bouchard and others of today! At the most recent ACSM meeting and in the latest articles that have been published in Medicine & Science in Sports & Exercise® terms like polymorphism, transcription factors, deletion allele, and sequence variants are simply everyday vernacular in certain sessions and manuscripts relating to genetics. Would this terminology have confused those pioneers? At the turn of the 20th century, the renowned Canadian physician, Sir Willliam Osler viewed that a common cold could only be treated with contempt. However, a series of more recent studies have determined that certain exercise regimens may cause specific immunological responses and have potential effects on the incidence and frequency of respiratory distress associated with the common cold. Challenges wait on the new frontiers of exercise endocrinology. Not to be overlooked is the relatively recent identification of a family of hormone receptors known as peroxisome proliferator activated receptors or PPARS. The possibility of skeletal fiber type switching and substrate mobilization being modulated by factors such as nitric oxide, endogenous ligands, or novel hormones, which are released by exercise and subsequently bind to these receptors, causing a unknown cascade of signaling events to occur and a subsequent altered physiological status remains unknown. To keep at the “cutting edge of science,” exercise physiologists have taken the cue from scientists who do not use exercise as an intervention. Capitalization of different technologies such as gene arrays, production of phosphospecific antibodies, plate readers, and robotics have allowed exercise physiologists to explore classical questions such as “What factors may be responsible for the increase in maximal aerobic capacity?” with an efficacy that a previous generation would have thought not only incredible but also impossible. While advances in technology are essential, collaboration and communication is of utmost importance to the further advancement of knowledge. ACSM, through scientific sessions including tutorials, symposia, and free communications at its Annual Meeting, keeps its membership informed of developments in the field through sponsorship of strong basic science components in these areas. The past sets the precedent for the present and the present will dictate the future. While genomics and proteonomics are currently emerging, exercisenomics may emerge in the future as a field where exercise scientists investigate a series of different factors at different stages in development. This new field may help discover the different factors that account for the potency and plasticity of the physiological changes and adaptations to exercise. Subsequently, the health benefits of exercise or the limits of performance for athletes may be fully realized. Whether an “exercise chip” will ever be fabricated to solve questions in the aforementioned areas remains to be determined, but the knowledge gleaned will only be limited by our hard work and imaginations.

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 score0.383
Threshold uncertainty score0.848

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0000.002
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 head0.019
GPT teacher head0.285
Teacher spread0.267 · 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

Citations1
Published2004
Admission routes1
Has abstractyes

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