Expression Suppression and Activity Inhibition of TRPM7 Regulate Cytokine Production and Multiple Organ Dysfunction Syndrome During Endotoxemia: a New Target for Sepsis
Bibliographic record
Abstract
BACKGROUND: Main pathological features detected during sepsis and endotoxemia include over-secretion of pro-inflammatory cytokines and multiorgan dysfunction syndrome (MODS). Unfortunately, current clinical efforts to treat sepsis are unsatisfactory, and mortality remains high. Interestingly, transient receptor potential (TRP) melastatin 7 (TRPM7) ion channel controlling Ca2+ and Mg2+ permeability is involved in cytokine production and inflammatory response. Furthermore, TRPM7 downregulation has been shown to alleviate local symptoms in some models of sepsis, but its effects at a systemic level remain to be explored. OBJECTIVE: To test whether TRPM7 mediates cytokine production and MODS during endotoxemia. METHODS: Endotoxemic and sham-endotoxemic rats were subjected to pharmacological inhibition of TRPM7 using carvacrol, or to expression suppression by adenovirus delivery of shRNA (AdVshTRPM7). Then, cytokine and MODS levels in the blood were measured. RESULTS: Inhibition of TRPM7 with carvacrol and suppression with AdVshTRPM7 were both efficient in inhibiting the over-secretion of pro-inflammatory cytokines TNF-α, IL-1β, IL-6, and IL-12, in endotoxemic rats, without inducing downregulation in blood levels of antiinflammatory cytokines IL-10 and IL-4. Additionally, the use of carvacrol and AdVshTRPM7 significantly prevented liver and pancreas dysfunction, altered metabolic function, and hypoglycemia, induced by endotoxemia. Furthermore, muscle mass wasting and cardiac muscle damage were also significantly reduced by the use of carvacrol and AdVshTRPM7 in endotoxemic rats. CONCLUSION: Our results indicate TRPM7 ion channel as a key protein regulating inflammatory responses and MODS during sepsis. Moreover, TRPM7 appears as a novel molecular target for the management of sepsis.
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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 | 0.001 |
| 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".