Novel approaches to the development of anti-sepsis drugs
Bibliographic record
Abstract
INTRODUCTION: Sepsis is the dysregulated systemic immune response to an infection. Experimental and clinical research provided detailed insight into the pathophysiology of the disease, but no pathway explored, so far, has been exploited to deliver effective therapies with regard to significant outcome improvement. Increasing incidence and high mortality of sepsis require novel approaches for the development of anti-sepsis drugs. AREAS COVERED: Since accurate assessment of the patient's condition in sepsis is the basis for the success of novel anti-sepsis drugs, the authors first review briefly biomarkers for improved diagnostics in sepsis. The authors then discuss specific pharmacological approaches with a focus on immune modulation, for example, Toll-like receptor 4 inhibition and modulation of the endocannabinoid system. The authors also cover iron chelation and uncoupling of the nitric oxide pathway. EXPERT OPINION: The failure of anti-sepsis treatments in the past is most likely related to wrong timing of the drugs due to missing reliable biomarkers to assess the condition of the patients. The authors believe that the development of anti-sepsis drugs using time-critical ('vertical') and continuous ('horizontal') approaches may provide the answer for future novel therapeutics.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".