Bibliographic record
Abstract
In a recent issue of the New England Journal of Medicine, Srivastava and colleagues reported the presence of antibodies to the inward rectifying potassium channel 4.1 (anti-KIR4.1) in MS (7).The authors observed that purified serum immunoglobulin G (IgG) from MS patients, but not from patients with other neurological diseases, bound to a glial protein in human brain sections.Human brain lysate precipitated with IgG from MS patients revealed KIR4.1 to be the target antigen.Anti-KIR4.1 antibodies were found in serum samples of 47% of MS patients, 1% of patients with other neurologic diseases and in none of the samples from healthy controls.Moreover, anti-KIR4.1 antibodies were detected in the CSF of most MS patients tested.In all MS patients harboring anti-KIR4.1 antibodies, IgG isotypes capable of activating the complement cascade were found.Twenty-four hours after injection of anti-KIR4.1 antibodies and complement into the cisternae magnae of wild-type mice, the authors observed decreased expression of KIR4.1 and glial fibrillary acidic protein (GFAP), a protein expressed by astrocytes.In their study, Srivastava and colleagues provide data in support of autoantibodies to KIR4.1 as important mediators of inflammation and tissue damage in MS.Their work favors an autoimmune process to be the underlying cause of MS, since specific autoantibodies capable of causing structural damage in normal animals were present in a large number of MS patients.While classical features of MS lesion pathology such as demyelination, axonal loss, and microglial activation were not observed, the authors report evidence for cytotoxicity toward astrocytes.
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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".