Bibliographic record
Abstract
The neonatal lupus syndromes (NLS), while quite rare, carry significant mortality and morbidity in cases of cardiac manifestations. Although anti-SSA/Ro-SSB/La antibodies are detected in > 85% of mothers whose fetuses are identified with congenital heart block (CHB) in a structurally normal heart, when clinicians applied this testing to their pregnant patients, the risk for a woman with the candidate antibodies to have a child with CHB was at or below 1 in 50. While the precise pathogenic mechanism of antibody-mediated injury remains unknown, it is clear that the antibodies alone are insufficient to cause disease and fetal factors are likely contributory. In vivo and in vitro evidence supports a pathologic cascade involving apoptosis of cardiocytes, surface translocation of Ro and La antigens, binding of maternal autoantibodies, secretion of profibrosing factors (e.g., TGFbeta) from the scavenging macrophages and modulation of cardiac fibroblasts to a myofibroflast scarring phenotype. The spectrum of cardiac abnormalities continues to expand, with varying degrees of block identified in utero and reports of late onset cardiomyopathy (some of which display endocardial fibroelastosis). Moreover, there is now clear documentation that incomplete blocks (including those improving in utero with dexamethasone) can progress postnatally, despite the clearance of the maternal antibodies from the neonatal circulation. Better echocardiographic measurements which identify first degree block in utero may be the optimal means of approaching pregnant women at risk. Prophylactic therapies, including treatment with intravenous immunoglobulin, await larger trials. In order to achieve advances at both the bench and bedside, national research registries established in the US and Canada are critical.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.024 | 0.005 |
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".