Lack of elevation in plasma levels of pro‐inflammatory cytokines in common rodent models of pulmonary arterial hypertension: questions of construct validity for human patients
Bibliographic record
Abstract
Translational research depends on the relevance of animal models and how well they replicate human disease. Here, we investigated plasma levels of three important pro-inflammatory cytokines (TNFα, IL-6, and MCP-1), known to be elevated in human pulmonary arterial hypertension (PAH), and systematically assessed their levels in PAH patients compared to five different rodent models of pulmonary hypertension (PH). A consistent immunoassay platform (Luminex xMAP) and source (Millipore) was used to measure all specimens. PAH patients (n = 29) exhibited significant elevations in all three cytokines (median [IQR] pg/mL; TNFα, 7.0 [4.8-11.7]; IL-6, 9.2 [3.8-17.2]; MCP-1, 109 [65-142]) versus healthy participants (n = 20) (median [IQR] pg/mL; TNFα, 3.0 [2.0-3.6]; IL-6, 1.7 [0.5-7.2]; MCP-1, 79 [49-93]. In contrast, mice with PH established after three weeks of hypoxia (n = 18) or SU5416 plus hypoxia (n = 20) showed no significant change in their plasma cytokine levels versus controls (n = 16), based on three to four independent experiments per group. Similarly, plasma cytokine levels were not elevated in rats with PH established three weeks after monocrotaline (n = 23), eight weeks after SU5416 alone (n = 10) or six to eight weeks after SU5416 plus hypoxia (n = 21) versus controls (n = 36 rats), based on three to eight independent experiments per group. Positive biologic control specimens from sepsis patients (n = 9), cecal-ligation and puncture (CLP)-induced septic mice (n = 6), and lipopolysaccharide-induced septic rats (n = 4) showed robust elevations in all three cytokines. This study suggests that animal models commonly used for the development of novel diagnostic and therapeutic approaches for PAH may have limited construct validity with respect to markers of systemic immune activation seen in human patients.
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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 | 0.040 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".