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Record W2064412759 · doi:10.1182/blood-2005-07-2970

The hematopoietic stem compartment consists of a limited number of discrete stem cell subsets

2005· article· en· W2064412759 on OpenAlexaff
Hans B. Sieburg, Rebecca H. Cho, Brad Dykstra, Naoyuki Uchida, Connie J. Eaves, Christa E. Müller‐Sieburg

Bibliographic record

VenueBlood · 2005
Typearticle
Languageen
FieldMedicine
TopicHematopoietic Stem Cell Transplantation
Canadian institutionsUniversity of British ColumbiaBC Cancer Agency
FundersNational Institute of Diabetes and Digestive and Kidney DiseasesNational Institute on AgingU.S. Public Health Service
KeywordsStem cellHaematopoiesisBiologyTransplantationImmunologyHematopoietic stem cellBone marrowPopulationHomogeneousRepopulationCell biologyGeneticsInternal medicineMedicineCombinatorics

Abstract

fetched live from OpenAlex

Hematopoietic stem cells (HSCs) display extensive heterogeneity in their behavior even when isolated as phenotypically homogeneous populations. It is not clear whether this heterogeneity reflects inherently diverse subsets of HSCs or a homogeneous population of HSCs diversified by their response to different external stimuli. To address this, we analyzed 97 individual HSCs in long-term transplantation assays. HSC clones were obtained from unseparated bone marrow (BM) through limiting dilution approaches. Following transplantation into individual hosts, donor-type cells in blood were measured bimonthly and the resulting repopulation kinetics were grouped according to overall shape. Only 16 types of repopulation kinetics were found among the HSC clones even though combinatorially 54 groups were possible. All HSC clones, regardless of their origin, could be assigned to this subset of groups, and the probability of finding new patterns is negligible. Thus, the full repertoire of repopulating HSCs was covered. These data indicate that the HSC compartment consists of a limited number of distinct HSC subsets, each with predictable behavior. Enrichment of HSCs (Lin- Rho- SP) changes the representation of HSC types by selecting for distinct subsets of HSCs. These data from the steady-state HSC repertoire could provide a basis for the diagnosis of perturbed patterns of HSCs potentially caused by disease or aging.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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)0.0010.001

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 head0.018
GPT teacher head0.266
Teacher spread0.248 · 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 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

Citations243
Published2005
Admission routes1
Has abstractyes

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