Telomere maintenance in human B lymphocytes
Bibliographic record
Abstract
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 machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".