Special electromagnetic field-treated water and far-infrared radiation alleviates lipopolysaccharide-induced acute respiratory distress syndrome in rats by regulating haptoglobin
Bibliographic record
Abstract
Special electromagnetic field-treated water (SEW) and far-infrared radiation (FIR) can reduce acute respiratory distress syndrome (ARDS) in rats inflicted by lipopolysaccharides (LPSs). However, little is known about its underlying molecular mechanism. Differentially expressed proteins (DEPs) of SEW and FIR interventions were obtained from a proteomics database. A total of 89 DEPs were identified. Enrichment analysis of DEPs was performed using the Database for Annotation, Visualization, and Integrated Discovery. These DEPs were associated with the responses to LPSs, acute inflammation, extracellular exosomes, glucocorticoids, and electrical stimuli. The protein-protein interaction network was set up using the STRING database. Modular analysis was performed using MCODE in the Cytoscape software. Proteins Haptoglobin, Apolipoprotein B, Transthyretin, and Fatty acid binding protein 1 were among the core networks. A tail vein injection of LPS was used to establish the rat model with ARDS. Parallel reaction monitoring confirmed Hp protein expression. Inflammatory pathway factors were detected using an enzyme-linked immunosorbent assay. This indicates that SEW and FIR can be considered as potential clinical treatment methods for ARDS treatment and that their functional mechanisms are related to the ability of alleviating lung inflammation through Hp protein adjustment.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.030 | 0.014 |
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".