A novel biomarker associated with distress in humans: calcium-binding protein, spermatid-specific 1 (CABS1)
Bibliographic record
Abstract
Calcium-binding protein spermatid-specific 1 (CABS1) is expressed in the human submandibular gland and has an anti-inflammatory motif similar to that in submandibular rat 1 in rats. Here, we investigate CABS1 in human saliva and its association with psychological and physiological distress and inflammation in humans. Volunteers participated across three studies: 1) weekly baseline measures; 2) a psychosocial speech and mental arithmetic stressor under evaluative threat; and 3) during academic exam stress. Salivary samples were analyzed for CABS1 and cortisol. Additional measures included questionnaires of perceived stress and negative affect; exhaled nitric oxide; respiration and cardiac activity; lung function; and salivary and nasal inflammatory markers. We identified a CABS1 immunoreactive band at 27 kDa in all participants and additional molecular mass forms in some participants. One week temporal stability of the 27-kDa band was satisfactory (test–retest reliability estimate = 0.62–0.86). Acute stress increased intensity of 18, 27, and 55 kDa bands; 27-kDa increases were associated with more negative affect and lower heart rate, sympathetic activity, respiration rate, and minute ventilation. In both acute and academic stress, changes in 27 kDa were positively associated with salivary cortisol. The 27-kDa band was also positively associated with VEGF and salivary leukotriene B4 levels. Participants with low molecular weight CABS1 bands showed reduced habitual stress and negative affect in response to acute stress. CABS1 is readily detected in human saliva and is associated with psychological and physiological indicators of stress. The role of CABS1 in inflammatory processes, stress, and stress resilience requires careful study.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".