IMPLICATION OF TOLL-LIKE RECEPTOR AND TUMOR NECROSIS FACTOR α SIGNALING IN SEPTIC SHOCK
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Septic shock is initiated by a systemic inflammatory response to microbial infection that frequently leads to impaired perfusion and multiple organ failure. Because of its high risk of death, septic shock is a major problem particularly for patients in the intensive care unit. In general, bacterial lipopolysaccharide (LPS) is a strong activator of various immune responses and stimulates monocytes/macrophages to release a variety of inflammatory cytokines. However, overproduction of inflammatory factors in response to bacterial infections is known to cause septic shock, similar to that induced by LPS. Studies of LPS-signaling pathways and downstream inflammatory cytokines may have critical implications in the treatment of sepsis. In recent years, there has been significant progress in understanding the signaling pathways activated by LPS and its receptor Toll-like receptor 4 (TLR4), as well as by tumor necrosis factor alpha (TNFalpha), a potent inflammatory cytokine induced by LPS stimulation. This review briefly summarizes our current knowledge of these signaling pathways and critical signal transducers. Characterization of key signal transducers may allow us to identify tractable, novel targets for the therapeutic interventions of sepsis.
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.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.001 | 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 it