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Telomere maintenance in human B lymphocytes

2002· article· en· W2083141185 on OpenAlexaff
Uwe M. Martens, Volker Brass, Lucie Sedlacek, Milena Pantić, Carolin Exner, Yalin Guo, Monika Engelhardt, Peter M. Lansdorp, Cornelius F. Waller, W. Lange

Bibliographic record

VenueBritish Journal of Haematology · 2002
Typearticle
Languageen
FieldMedicine
TopicTelomeres, Telomerase, and Senescence
Canadian institutionsTerry Fox Research Institute
FundersDeutsche ForschungsgemeinschaftEuropean Commission
KeywordsTelomereBiologyCD19HaematopoiesisSenescenceLymphocyteFlow cytometryMolecular biologyImmunologyCell biologyStem cellGeneticsDNA

Abstract

fetched live from OpenAlex

Telomere shortening has been causally linked to replicative senescence in human cells. To characterize telomere-length heterogeneity in peripheral blood cells of normal individuals, we analysed the mean length of telomeric repeat sequences in subpopulations of peripheral blood leucocytes, using fluorescence in situ hybridization and flow cytometry (flow-FISH). Although the telomere length of most haematopoietic subsets was within the same range, the mean telomere length was found to be 15% higher in B compared with T lymphocytes in adult peripheral blood. Whereas telomere loss with ageing corresponded to 33 base pairs (bp) per year in T cells, telomere shortening was slower in B cells, corresponding to 15 bp per year. Separation of adult B-lymphocyte subpopulations based on CD27 expression revealed that telomere length was almost 2 kb longer in CD19+CD27+ (memory) compared with CD19+CD27- (naive) cells. Furthermore, peripheral blood B cells were activated in vitro. Whereas B-cell activation with Staphylococcus aureus Cowan strain (SAC) did not increase telomere length, a striking telomere elongation was observed when cells were stimulated with SAC and interleukin 2 to induce plasma cell differentiation. Our observations support the concept that telomere dynamics in B cells are distinct from other haematopoietic cell lineages and that telomere elongation may play an essential role in the generation of long-term B memory cells.

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: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.257
Threshold uncertainty score0.883

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0010.000

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 head0.020
GPT teacher head0.257
Teacher spread0.237 · 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 designCase report
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

Citations93
Published2002
Admission routes1
Has abstractyes

Explore more

Same venueBritish Journal of HaematologySame topicTelomeres, Telomerase, and SenescenceFrench-language works237,207