Redundancy between Cysteine Cathepsins in Murine Experimental Autoimmune Encephalomyelitis
Bibliographic record
Abstract
The cysteine cathepsins B, S, and L are functionally linked to antigen processing, and hence to autoimmune disorders such as multiple sclerosis. Stemming from several studies that demonstrate that mice can be protected from experimental autoimmune encephalomyelitis (EAE) through the pharmacologic inhibition of cysteine cathepsins, it has been suggested that targeting these enzymes in multiple sclerosis may be of therapeutic benefit. Utilizing mice deficient in cysteine cathepsins both individually and in combination, we found that the myelin-associated antigen myelin oligodendrocyte glycoprotein (MOG) was efficiently processed and presented by macrophages to CD4+ T cells in the individual absence of cathepsin B, S or L. Similarly, mice deficient in cathepsin B or S were susceptible to MOG-induced EAE and displayed clinical progression and immune infiltration into the CNS, similar to their wild-type counterparts. Owing to a previously described CD4+ T cell deficiency in mice deficient in cathepsin L, such mice were protected from EAE. When multiple cysteine cathepsins were simultaneously inhibited via genetic deletion of both cathepsins B and S, or by a cathepsin inhibitor (LHVS), MHC-II surface expression, MOG antigen presentation and EAE were attenuated or prevented. This study demonstrates the functional redundancy between cathepsin B, S and L in EAE, and suggests that the inhibition of multiple cysteine cathepsins may be needed to modulate autoimmune disorders such as multiple sclerosis.
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 | 0.001 | 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 | 0.001 |
| 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".