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Characterization of the effects of exercise training on hematopoietic stem cell quantity and function

2012· article· en· W2146937965 on OpenAlexafffund
Michael De Lisio, Gianni Parise

Bibliographic record

VenueJournal of Applied Physiology · 2012
Typearticle
Languageen
FieldMedicine
TopicHematopoietic Stem Cell Transplantation
Canadian institutionsMcMaster University
FundersCanadian Institutes of Health Research
KeywordsStem cellHaematopoiesisPhysical exerciseHematopoietic stem cellFunction (biology)MedicineBiologyPhysical therapyCell biology

Abstract

fetched live from OpenAlex

The effect of exercise training on hematopoietic stem cells (HSC) is largely unknown. The aim of the present investigation was to determine whether exercise training could expand the bone marrow HSC pool and influence various aspects of HSC function. Mice were either exercise trained (EX; 1 h/day, 3 days/wk, for 8 wk) or remained sedentary (SED). Bone marrow (BM) from SED or EX mice was extracted from different HSC niches for cell cycle analysis, HSC (lineage(-), Sca-1(+), c-Kit(+)) quantification, and differentiation along various hematopoietic lineages via flow cytometry. Serum was collected for evaluation of cytokines known to regulate HSC. To determine HSC function, BM from EX and SED mice was transplanted into primary and secondary recipients in a BM transplant assay. EX increased HSC quantity in the vascular BM niche 20% vs. SED (P < 0.05) and increased the proportion of whole BM cells in G(2)/M phase of cell cycle (P < 0.05). The number of spleen colonies was 48% greater (P < 0.05) in recipients transplanted with BM from EX. Serum IL-6 levels were decreased 38% in EX, and differentiation along the lineage trended to increase (16%, P = 0.053 and 16%, P = 0.061, respectively). Short- or long-term engraftment and homing in primary recipients were not altered in EX. HSC self-renewal as analyzed by hematopoietic regeneration in secondary recipients was also unaffected by EX. Here we demonstrate that HSC quantity is increased in the BM niche associated with more activated, differentiated HSC, and that this expansion does not improve or impair HSC function.

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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.278
Threshold uncertainty score0.225

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.014
GPT teacher head0.231
Teacher spread0.216 · 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 designBench or experimental
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

Citations56
Published2012
Admission routes2
Has abstractyes

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