Effect of Tangnaikang on TGF-β1-induced transdifferentiation of human renal tubular epithelial HK-2 cells
Bibliographic record
Abstract
OBJECTIVE: To explore the function of Tangnaikang (TNK) in the prevention and treatment of renal interstitial fibrosis through transdifferentiation of the human renal tubular epithelial cell line HK-2 induced by transforming growth factor-beta1 (TGF-beta1). METHODS: HK-2 cells cultured in dulbecco's modified eagle medium/F12 (1 : 1) with 10% fetal calf serum were divided into six groups: blank control group, TGF-beta1 group (TGF-beta1 10 ng/mL), serum control group (TGF-beta1 10 ng/mL + 10% serum), treatment group 1 (TGF-beta1 10 ng/mL + 5% TNK serum), treatment group 2 (TGF-beta1 10 ng/mL + 10% TNK serum), and treatment group 3 (TGF-beta1 10 ng/mL + 20% TNK serum). Cell proliferation was detected by 4,5-Dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide assay. Expression of alpha-smooth muscle actin (alpha-SMA) and E-cadherin were observed by immunohistochemical assay. The contents of collagen I (Col I), collagen III (Col III), and fibronectin (FN) in the culture medium supernatant were detected by ELISA. RESULTS: E-cadherin was expressed and alpha-SMA was not expressed in normal HK-2 cells. In HK-2 cells cultured with TGF-beta1, alpha-SMA expression significantly increased, HK-2 cells significantly proliferated, and secretion of Col I, Col III, and FN significantly increased compared with the blank control group (all P < 0.05). In the HK-2 cells cultured with TGF-beta1 and TNK serum, the expression of alpha-SMA significantly decreased, the expression of E-cadherin significantly increased, and the cell proliferation and the secretion of Col I, Col III and FN were significantly inhibited compared with the TGF-beta1 group (all P < 0.05). CONCLUSION: TNK can inhibit cell proliferation and reduce secretion of Col I, Col III, and FN. This indicates that TNK can inhibit transdifferentiation of human renal tubular epithelial cells induced by TGF-beta1, with the effect of preventing and treating renal interstitial fibrosis.
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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 | 0.001 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".