Genetic loci on New Zealand black chromosome 1 lead to increased generation of T follicular helper and TH17 cells (47.23)
Bibliographic record
Abstract
Abstract Genetic loci on NZB c1 lead to antinuclear antibody (Ab) production and glomerulonephritis (GN). Using subcongenic lines, we found at least 5 genetic loci within a 35-106cM interval modulate disease. Notably, mice with a 70-100cM interval (c1(70-100cM)) develop high titre anti-dsDNA Ab, increased numbers of large germinal centers and severe GN a characteristic feature of lupus-prone mice with abnormalities of T follicular helper (TFH) and Th17 cells. In this study we determined whether variations in disease severity in c1 subcongenic mice are associated with differences in these subsets. The proportion of splenic TFH cells was significantly increased in c1(70-100) mice. Splenocytes from all c1 congenic mouse strains demonstrated increased production of IL-21 and IL-17 following anti-CD3/CD28 crosslinking which was greatest in c1(70-100) mice. The majority of IL-21 producing cells were TFH, many of which also secreted IFN-γ, but not IL-17. Immunization of 8-wk-old pre-autoimmune mice with ovalbumin (OVA) led to increased generation of TFH and Th17 cells in c1 (70-100) mice. This appeared to result in part from altered T cell function, as adoptively transferred OVA-specific TCR transgenic c1(70-100) T cells and naïve c1(70-100) T cells cultured in-vitro, demonstrated enhanced differentiation to TFH and IL-17-producing cells. Thus, genetic loci on NZB c1 promote differentiation of T cells to TFH and Th17 cells and this capacity correlates with the severity of disease.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".