Oral Decoctions Based on Qi-Yin Syndrome Differentiation After Adjuvant Chemotherapy in Resected Stage ΙΙΙA Non-Small Cell Lung Cancer: A Randomized Controlled Trial.

OBJECTIVE: Powerful adjuvant strategies are required to improve the survival of patients with completely resected stage ΙΙΙA non-small cell lung cancer (NSCLC). We aimed to compare the efficacy of traditional Chinese medicine (TCM) treatment versus observation after adjuvant chemotherapy in these patients. METHODS: Eligible patients were randomized 1:1 to receive either oral decoctions based on Qi-Yin syndrome differentiation (TCM group) or observation (observation group). The intervention lasted for 12 months. The primary endpoint was 1-year disease-free survival (DFS). Secondary endpoints were DFS, quality of life, regulatory T cells (Tregs), and cytotoxic T lymphocyte-associated antigen-4 (CTLA-4) on the surface of Tregs in peripheral blood. We used EORTC QLQ-LC43 to evaluate quality of life. RESULTS: Between Apr 29, 2019, and Nov 11, 2021, 75 patients were randomly assigned to oral decoctions based on Qi-Yin syndrome differentiation (n = 38) or observation (n = 37). The full analysis set included 35 patients in the TCM group and 35 in the observation group. After a median follow-up of 24.2 months, oral decoctions based on Qi-Yin syndrome differentiation improved DFS compared with observation (HR 0.378, 95% CI: 0.157-0.912; P = .03). One-year DFS was 82.1% in the TCM group and 61.9% in the observation group (P = .06). Three months after randomization, scores of total health, role function, emotional function, and social function in the TCM group were higher than those in the observation group (P < .01 for all), scores of fatigue, pain, insomnia, appetite loss, constipation, cough, and chest pain were lower than those in the observation group (P < .05 for all); there was no significant difference in the proportion of Tregs between the TCM group and the observation group (P = .58); the proportion of CTLA-4+Tregs in the TCM group was lower than that in the observation group (P = .046). There were no adverse events that occurred in both groups. CONCLUSIONS: Oral decoctions based on Qi-Yin syndrome differentiation after adjuvant chemotherapy prolonged DFS, reduced the risk of disease recurrence and metastasis, improved quality of life, and down-regulated the proportion of CTLA-4+Tregs in completely resected stage ΙΙΙA NSCLC patients. TRIAL REGISTRATION: Chinese Clinical Trial Register, No. ChiCTR1800019396. Date of registration: 9 November 2018.

Inhibition of p38 MAPK/NF-κB p65 signaling pathway activity by rare ginsenosides ameliorates cyclophosphamide-induced premature ovarian failure and KGN cell injury.

ETHNOPHARMACOLOGICAL RELEVANCE: Panax ginseng C. A. Mey., one of the most used herbs in the world, shows effective treatment in reproductive injury. Recent studies have proven that the processed product, red ginseng, which is more active than ginseng itself. Therefore, it is speculated that its main functional component, rare ginsenosides (heat-transformed saponin, HTS), may be effective in treating premature ovarian failure (POF), but its efficacy has not yet been experimentally confirmed. AIM OF THE STUDY: To evaluate whether HTS could attenuate cyclophosphamide-induced inflammation and oxidative damage in POF model rats and the human granulosa-like KGN cell line and protect granulosa cell proliferation. MATERIAL AND METHODS: HTS were isolated from ginsenosides and high performance liquid chromatography (HPLC) analysis was used to analyze the HTS components. Cyclophosphamide (CP) was used to establish a POF rat model and KGN cell injury model. Reactive oxygen species (ROS) and antioxidant enzyme production was determined using specific assays, while inflammatory cytokine secretion was measured by enzyme-linked immunosorbent assay (ELISA). The proliferative function of granulosa cells was assessed using high-content screening and immunohistochemistry to determine the Ki67 protein level. Protein expression in ovarian tissues and KGN cells was analyzed by Western blotting, quantitative real-time PCR (qRT-PCR) was used to determine the transcriptional changes in ovarian tissues and KGN cells. RESULTS: In CP-treated POF model rats, HTS significantly decreased malondialdehyde (MDA), interleukin-6 (IL-6), and tumor necrosis factor-α (TNF-α) levels, increased glutathione oxidase (GSH) levels, and upregulated Ki67 expression in ovarian granulosa cells. In addition, HTS significantly increased cell survival and Ki67 expression levels in CP-treated cells, and superoxide dismutase (SOD) levels were significantly increased. HTS significantly downregulated IL-6, TNF-α, and interleukin-1ß (IL-1ß) mRNA expression and significantly inhibited nuclear factor kappa-B p65 (NF-κB p65) and p38 mitogen activated protein kinase (p38 MAPK) phosphorylation in POF model rats and KGN cells. Moreover, NF-κB p65 and p38 MAPK levels were significantly increased in ovarian granulosa cells. p65 and p38 protein and gene expression was significantly downregulated. CONCLUSION: HTS ameliorated CP-induced POF and human granulosa cell injury, possibly by inhibiting inflammation and oxidative damage mediated by the p38 MAPK/NF-κB p65 signaling pathway.

Artificial intelligence in the risk prediction models of cardiovascular disease and development of an independent validation screening tool: a systematic review.

BACKGROUND: A comprehensive overview of artificial intelligence (AI) for cardiovascular disease (CVD) prediction and a screening tool of AI models (AI-Ms) for independent external validation are lacking. This systematic review aims to identify, describe, and appraise AI-Ms of CVD prediction in the general and special populations and develop a new independent validation score (IVS) for AI-Ms replicability evaluation. METHODS: PubMed, Web of Science, Embase, and IEEE library were searched up to July 2021. Data extraction and analysis were performed for the populations, distribution, predictors, algorithms, etc. The risk of bias was evaluated with the prediction risk of bias assessment tool (PROBAST). Subsequently, we designed IVS for model replicability evaluation with five steps in five items, including transparency of algorithms, performance of models, feasibility of reproduction, risk of reproduction, and clinical implication, respectively. The review is registered in PROSPERO (No. CRD42021271789). RESULTS: In 20,887 screened references, 79 articles (82.5% in 2017-2021) were included, which contained 114 datasets (67 in Europe and North America, but 0 in Africa). We identified 486 AI-Ms, of which the majority were in development (n = 380), but none of them had undergone independent external validation. A total of 66 idiographic algorithms were found; however, 36.4% were used only once and only 39.4% over three times. A large number of different predictors (range 5-52,000, median 21) and large-span sample size (range 80-3,660,000, median 4466) were observed. All models were at high risk of bias according to PROBAST, primarily due to the incorrect use of statistical methods. IVS analysis confirmed only 10 models as "recommended"; however, 281 and 187 were "not recommended" and "warning," respectively. CONCLUSION: AI has led the digital revolution in the field of CVD prediction, but is still in the early stage of development as the defects of research design, report, and evaluation systems. The IVS we developed may contribute to independent external validation and the development of this field.