Establishing a Classification System for Predicting Flow-Limiting Dissection After Balloon Angioplasty Using Explainable Machine-Learning Models: A Multicenter Retrospective Cohort Study.

OBJECTIVE: Percutaneous transluminal angioplasty (PTA) is the primary method for treatment in peripheral arterial disease. However, some patients experience flow-limiting dissection (FLD) after PTA. We utilized machine learning and SHapley Additive exPlanations to identify and optimize a classification system to predict FLD after PTA. METHODS: This was a multi-center, retrospective, cohort study. The cohort comprised 407 patients who underwent treatment of the femoropopliteal (FP) arteries in 3 institutions between January 2021 and June 2023. Preoperative computed tomography angiography images were evaluated to identify FP artery grading, chronic total occlusion (CTO), and vessel calcification (peripheral artery calcium scoring system [PACSS]). After PTA, FLD was identified by angiography. We trained and validated 6 machine-learning models to estimate FLD occurrence after PTA, and the best model was selected. Then, the sum of the Shapley values for each of CTO, FP, and PACSS was calculated for each patient to produce the CTO-FP-PACSS value. The CTO-FP-PACSS classification system was used to classify the patients into classes 1 to 4. Univariate and multivariate analyses were performed to validate the effectiveness of the CTO-FP-PACSS classification system for predicting FLD. RESULTS: Overall, 407 patients were analyzed, comprising 189 patients with FLD and 218 patients without FLD. Differences in sex (71% males vs 54% males, p<0.001), CTO (72% vs 43%, p<0.001), FP (3.26±0.94 vs 2.66±1.06, p<0.001), and PACSS (2.39±1.40 vs 1.74±1.35, p<0.001) were observed between patients with and without FLD, respectively. The random forest model demonstrated the best performance (validation set area under the curve: 0.82). SHapley Additive exPlanations revealed CTO, PACSS, and FP as the 3 most influential FLD predictors, and the univariate and multivariate analyses confirmed CTO-FP-PACSS classification as an independent FLD predictor (multivariate hazard ratio 4.13; p<0.001). CONCLUSION: The CTO-FP-PACSS classification system accurately predicted FLD after PTA. This user-friendly system may guide surgical decision-making, helping choose between PTA and additional devices to reduce FLD in FP artery treatment. CLINICAL IMPACT: We utilised machine-learning techniques in conjunction with SHapley Additive exPlanations to develop a clinical classification system that predicts the probability of flow-limiting dissection (FLD) after plain old balloon angioplasty. This classification system categorises lesions into Classes 1-4 based on three factors: chronic total occlusion, femoropopliteal grading, and peripheral artery calcium scoring. Each class demonstrated a different probability of developing FLD. This classification system may be valuable for surgeons in their clinical practice, as well as serving as a source of inspiration for other researchers.

Physalin A Induces Apoptosis and Autophagy in Hepatocellular Carcinoma via Inhibition of PI3K/Akt Signaling Pathway.

Physalin A (PA) is a bioactive withanolide with multiple pharmacological properties and has been indicated to be cytotoxic to hepatocellular carcinoma (HCC) cell line HepG2. This study aims to explore the mechanisms underlying PA antitumor activity in HCC. HepG2 cells were exposed to various concentrations of PA. Cell counting kit-8 assay and flow cytometry were implemented for evaluating cell viability and apoptosis, respectively. Immunofluorescence staining was utilized for detecting autophagic protein LC3. Western blotting was employed for measuring levels of autophagy-, apoptosis- and phosphatidylinositol-3-kinase/protein kinase B (PI3K/Akt) signaling-related proteins. A xenograft mouse model was established to verify the antitumor activity of PA in vivo. PA impaired HepG2 cell viability, and triggered apoptosis as well as autophagy. Inhibiting autophagy augmented PA-evoked HepG2 cell apoptosis. PA repressed PI3K/Akt signaling in HCC cells and activating PI3K/Akt reversed PA-triggered apoptosis and autophagy. PA treatment inhibited tumor growth in tumor-bearing mice. PA triggers HCC cell apoptosis and autophagy by inactivating PI3K/Akt signaling.

LncRNA HCG18 affects aortic dissection through the miR-103a-3p/HMGA2 axis by modulating proliferation and apoptosis of vascular smoothing muscle cells.

BACKGROUND: Aortic Dissection (AD) is a vascular disease with a high mortality rate and limited treatment strategies. The current research analyzed the function and regulatory mechanism of lncRNA HCG18 in AD. METHODS: HCG18, miR-103a-3p, and HMGA2 levels in the aortic tissue of AD patients were examined by RT-qPCR. After transfection with relevant plasmids, the proliferation of rat aortic Vascular Smoothing Muscle Cells (VSMCs) was detected by CCK-8 and colony formation assay, Bcl-2 and Bax was measured by Western blot, and apoptosis was checked by flow cytometry. Then, the targeting relationship between miR-103a-3p and HCG18 or HMGA2 was verified by bioinformation website analysis and dual luciferase reporter assay. Finally, the effect of HCG18 was verified in an AD rat model induced by ß-aminopropionitrile. RESULTS: HCG18 and HMGA2 were upregulated and miR-103a-3p was downregulated in the aortic tissues of AD patients. Downregulating HCG18 or upregulating miR-103a-3p enhanced the proliferation of VSMCs and limited cell apoptosis. HCG18 promoted HMGA2 expression by competing with miR-103a-3p and restoring HMGA2 could impair the effect of HCG18 downregulation or miR-103a-3p upregulation in mediating the proliferation and apoptosis of VSMCs. In addition, down-regulation of HCG18 could improve the pathological injury of the aorta in AD rats. CONCLUSION: HCG18 reduces proliferation and induces apoptosis of VSMCs through the miR-103a-3p/HMGA2 axis, thus aggravating AD.