Calcium-binding protein, spermatid-specific 1 is expressed in human salivary glands and contains an anti-inflammatory motif
Bibliographic record
Abstract
Salivary glands are involved in the production and exocrine and endocrine secretion of biologically active proteins, polypeptides, and hormones involved in growth and differentiation, homeostasis, and digestion. We have previously studied the prohormone submandibular rat 1 (SMR1), product of the Vcsa1 gene, which is highly expressed in the testes and salivary glands of rats, and can be cleaved to produce polypeptides with analgesic, erectile function, and anti-inflammatory activities. Humans lack the Vcsa1 gene, but homologous sequences and functions for analgesia and erectile function exist in the human genes Prol1, SMR3a, and SMR3b located on the human chromosomal region close to where Vcsa1 lies in the rat. Here we show the human protein calcium-binding protein spermatid-specific 1 (CABS1) contains a similar sequence to the anti-inflammatory sequence in rat SMR1, thus CABS1 may be another human gene with homologous function to Vcsa1. Using Western blot and PCR, we discovered that the human protein CABS1, previously thought to only be expressed in the testes, is also expressed in the salivary glands and lung, in a tissue-specific manner. Peptides derived from CABS1 were tested in an in vivo mouse model of lipopolysaccharide (LPS)-induced neutrophilia and an ex vivo rat model of antigen-induced intestinal anaphylaxis and significantly reduced both neutrophil accumulation in bronchoalveolar lavage fluid and antigen-induced ileal contractions, respectively. Thus human CABS1 has a peptide motif homologous to the anti-inflammatory peptide sequence of rat SMR1. Whether this similarity of CABS1 extends to the neuroendocrine regulation of the anti-inflammatory activity seen for SMR1 remains to be determined.
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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 | 0.000 | 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 | 0.000 |
| 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".