Pre-treatment of acupuncture stimulation of ST36 (Zusanli) significantly attenuates CAT-2, CAT-2B and GTPCH transcription in septic rat lungs.
Bibliographic record
Abstract
BACKGROUND: The isozymes of type-2 cationic amino acid transporter (including CAT-2 and CAT-2B) and guanosine triphosphate cyclohydrolase I (GTPCH) constitute part of the down-stream regulatory pathways that regulate nitric oxide (NO) production mediated by inducible NO synthase (iNOS). We sought to evaluate the effects of acupuncture stimulation of ST36 (Zusanli) on the expression of CAT-2, CAT-2B, and GTPCH in lipopolysaccharide (LPS)-stimulated rat lungs. METHODS: Sixty rats were randomized into 6 groups (n = 10 in each group): 1) LPS, 2) Normal saline (N/S), 3) LPS + ST36, 4) ST36, 5) LPS + Sham, and 6) Sham groups. Manual acupuncture stimulation of ST36 (designated as "ST36") or a "nonacupoint" (designated as "Sham") was performed in lightly immobilized rats for 30 minutes. Then, LPS injection was performed to induce the expressions of iNOS, CAT-2, CAT-2B, and GTPCH in rat lungs. Rats were sacrificed 6 hours after LPS injection and the expressions of these enzymes were assayed. RESULTS: Reverse transcription and polymerase chain reaction (RT-PCR) data revealed that the expressions of iNOS, CAT-2, CAT-2B, and GTPCH in N/S-stimulated rat lungs were low. Exposure to LPS significantly induced the expressions of iNOS, CAT-2, CAT-2B, and GTPCH. In addition, the pre-treatment of ST36 acupuncture significantly attenuated the LPS-induced expressions of iNOS, CAT-2, CAT-2B, and GTPCH in stimulated rat lungs. CONCLUSIONS: Pre-treatment of acupuncture stimulation of ST36 had significantly inhibitory effects on LPS-induced iNOS, CAT-2, CAT-2B, and GTPCH expressions in septic rat lungs.
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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) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".