Lineage Tree Analysis of Human Memory B Cells
Bibliographic record
Abstract
The human adaptive immune system relies on the diversity and specialization of B cells to mount an effective response against pathogens and antigens. Memory B cells represent distinct and functional subsets and isotypes with different origins and immunological roles within the human body. This study aims to investigate the clonal relationships and subset specific dynamics of human memory B cells by reconstructing immunoglobulin lineage trees derived from high throughput sequencing data. Three different B cell subsets, CD27+IgD+ (non-switched memory B cells), CD27+IgD- (switched memory B cells), and plasmablasts, from four healthy donors were used as a basis for the analysis conducted in this study. Raw immunoglobulin repertoire data was processed using MiXCR to generate clonotypes and to reconstruct the subsequent immunoglobulin lineage trees. These trees were then used to perform a comprehensive topographical and statistical analysis using R. The statistical analyses included subset and isotype comparisons, evaluations of the different topographical characteristics across subsets and isotypes, intra and interclonal diversity analyses and principal component analysis comparing samples with and without the plasmablast subset. The results demonstrated significant differences in lineage topology between the B cell subsets, with trees containing plasmablasts showing a greater variance in branch length and average depth, suggesting an increased clonal diversification consistent with an active immune response. Moreover, the interclonal and intraclonal diversity comparisons revealed a notable heterogeneity in the subset distribution and isotype usage, reflecting a varied immune history between the donors. It was also shown that the lineage trees containing the IgA isotype displayed a greater difference in characteristics associated with depth. These findings might contribute to a deeper understanding of the structural and functional dynamics of memory B cell subsets and help to underscore the utility of lineage tracing in immunological research.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 0.000 |
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.
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".