Chronic Interpersonal Stress Predicts Activation of Pro- and Anti-Inflammatory Signaling Pathways 6 Months Later
Bibliographic record
Abstract
OBJECTIVE: To understand the mechanisms underlying chronic interpersonal difficulties and their detrimental influence on mental and physical health. METHODS: A total of 103 healthy young women (mean age = 17 years) were administered a structured interview to assess the degree of chronic interpersonal stress in their lives. At the same time, blood was drawn to measure systemic inflammation, the expression of signaling molecules that regulate immune activation, and leukocyte production of the cytokine interleukin-6 after ex vivo stimulation with lipopolysaccharide. All of the immunologic assessments were repeated 6 months later. RESULTS: To the extent subjects were high in chronic interpersonal stress at baseline, their leukocytes displayed greater increases in messenger ribonucleic acid (mRNA) for the proinflammatory transcription factor nuclear factor-kappaB (NF-kappaB) over the next 6 months. They also showed larger increases in mRNA for inhibitor of kappaB, a molecule that sequesters NF-kappaB in the cytoplasm and minimizes its proinflammatory activities. Chronic interpersonal stress at baseline was unrelated to changes in biomarkers of systemic inflammation but was associated with increasingly pronounced interleukin-6 responses to lipopolysaccharide. These associations were independent of demographics, lifestyle variables, and depressive symptoms. CONCLUSIONS: These findings suggest that chronic interpersonal difficulties accentuate expression of pro- and anti-inflammatory signaling molecules. Although this process does not result in systemic inflammation under quiescent conditions, it does accentuate leukocytes' inflammatory response to microbial challenge. These dynamics may underlie the excess morbidity associated with social stress, particularly in inflammation-sensitive diseases like depression and atherosclerosis.
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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) | 0.000 | 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) | 0.003 | 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".