Multi-feature, Chinese-Western medicine-integrated prediction model for diabetic peripheral neuropathy based on machine learning and SHAP.

BACKGROUND: Clinical studies have shown that diabetic peripheral neuropathy (DPN) has been on the rise, with most patients presenting with severe and progressive symptoms. Currently, most of the available prediction models for DPN are derived from general clinical information and laboratory indicators. Several Traditional Chinese medicine (TCM) indicators have been utilised to construct prediction models. In this study, we established a novel machine learning-based multi-featured Chinese-Western medicine-integrated prediction model for DPN using clinical features of TCM. MATERIALS AND METHODS: The clinical data of 1581 patients with Type 2 diabetes mellitus (T2DM) treated at the Department of Endocrinology of the First Affiliated Hospital of Anhui University of Chinese Medicine were collected. The data (including general information, laboratory parameters and TCM features) of 1142 patients with T2DM were selected after data cleaning. After baseline description analysis of the variables, the data were divided into training and validation sets. Four prediction models were established and their performance was evaluated using validation sets. Meanwhile, the accuracy, precision, recall, F1 score and area under the curve (AUC) of ROC were calculated using ten-fold cross-validation to further assess the performance of the models. An explanatory analysis of the results of the DPN prediction model was carried out using the SHAP framework based on machine learning-based prediction models. RESULTS: Of the 1142 patients with T2DM, 681 had a comorbidity of DPN, while 461 did not. There was a significant difference between the two groups in terms of age, cause of disease, systolic pressure, HbA1c, ALT, RBC, Cr, BUN, red blood cells in the urine, glucose in the urine, and protein in the urine (p < 0.05). T2DM patients with a comorbidity of DPN exhibited diverse TCM symptoms, including limb numbness, limb pain, hypodynamia, thirst with desire for drinks, dry mouth and throat, blurred vision, gloomy complexion, and unsmooth pulse, with statistically significant differences (p < 0.05). Our results showed that the proposed multi-featured Chinese-Western medicine-integrated prediction model was superior to conventional models without characteristic TCM indicators. The model showed the best performance (accuracy = 0.8109, precision = 0.8029, recall = 0.9060, F1 score = 0.8511, and AUC = 0.9002). SHAP analysis revealed that the dominant risk factors that caused DPN were TCM symptoms (limb numbness, thirst with desire for drinks, blurred vision), age, cause of disease, and glycosylated haemoglobin. These risk factors were exerted positive effects on the DPN prediction models. CONCLUSIONS: A multi-feature, Chinese-Western medicine-integrated prediction model for DPN was established and validated. The model improves early-stage identification of high-risk groups for DPN in the diagnosis and treatment of T2DM, while also providing informative support for the intelligent management of chronic conditions such as diabetes.

Hyaluronic Acid-modified Liposomes for Ursolic Acid-targeted Delivery Treat Lung Cancer Based on p53/ARTS-mediated Mitochondrial Apoptosis.

Background: Chemotherapy drugs can cause drug resistance and other problems when treating lung cancer, which leads to treatment failure. Ursolic acid (UA) is used in formulations based on traditional Chinese medicine. UA has excellent anti-tumor effects, but they are limited by solubility and non-specificity to tumor cells. Objectives: To overcome these issues, we created a novel hyaluronic acid (HA)-targeted liposome system for delivering UA (HA-Lipo/UA) to explore the targeting and anti-tumor effects of UA. Methods: We constructed the HA-Lipo/UA delivery system by the thin film hydration method. The uptake and localization of UA were detected by flow cytometry and microscope. Cell proliferation of A549 cells was detected by MTT assays. Apoptosis and reactive oxygen species (ROS) expression of A549 cells were also evaluated after being treated with HA-Lipo/UA. Western blot analysis evaluated the anti-tumor mechanism of HA-Lipo/UA. Results: HA-Lipo/UA exhibited favorable targeting of the cluster of differentiation (CD)44-overexpressing A549 cells. HA-Lipo/UA exhibited significant inhibition of the proliferation of A549 cells and induced their apoptosis compared with the corresponding monotherapies. HA-Lipo/UA induced overexpression of reactive oxygen species and upregulated expression of p53 and apoptosis-related protein in the transforming growth factor-ß signaling (ARTS) pathway, which induced cytochrome-c release, activation of caspase-3, and promoted mitochondrial apoptosis in A549 cells. Conclusions: Taken together, these data suggested that HA-Lipo/UA could be used to target tumor cells.

[Prescription and medication rules of traditional Chinese medicine for prevention and treatment of diabetic microangiopathy based on literature mining].

This study explored the prescription and medication rules of traditional Chinese medicine(TCM) in the prevention and treatment of diabetic microangiopathy based on literature mining. Relevant literature on TCM against diabetic microangiopathy was searched and prescriptions were collected. Microsoft Excel 2021 software was used to establish a prescription database, and an analysis was conducted on the frequency, properties, flavors, meridian tropism, and efficacy classifications of drugs. Association rule analysis, cluster analysis, and factor analysis were performed using SPSS Modeler 18.0 and SPSS Statistics 26.0 software. The characteristic active components and mechanisms of action of medium-high frequency drugs in the analysis of medication rules were explored through li-terature mining. A total of 1 327 prescriptions were included in this study, involving 411 drugs, with a total frequency reaching 19 154 times. The top five high-frequency drugs were Astragali Radix, Angelicae Sinensis Radix, Poria, Salviae Miltiorrhizae Radix et Rhizoma, and Rehmanniae Radix. The cold and warm drugs were used in combination. Drugs were mainly sweet, followed by bitter and pungent, and acted on the liver meridian. The majority of drugs were effective in tonifying deficiency, clearing heat, activating blood, and resolving stasis. Association rule analysis identified the highly supported drug pair of Astragali Radix-Angelicae Sinensis Radix and the highly confident drug combination of Poria-Alismatis Rhizoma-Corni Fructus. The strongest correlation was found among Astragali Radix, Angelicae Sinensis Radix, Poria, and Salviae Miltiorrhizae Radix et Rhizoma through the complex network analysis. Cluster analysis identified nine categories of drug combinations, while factor analysis identified 16 common factors. The analysis of active components in high-frequency drugs for the treatment of diabetic microangiopathy revealed that these effective components mainly exerted their effects by inhibiting oxidative stress and suppressing inflammatory reactions. The study found that the pathogenesis of diabetic microangiopathy was primarily characterized by deficiency in origin, with a combination of deficiency and excess. Deficiency was manifested as Qi deficiency and blood deficiency, while excess as phlegm-heat and blood stasis. The key organ involved in the pathological changes was the liver. The treatment mainly focused on supplementing Qi and nourishing blood, supplemented by clearing heat, coo-ling blood, activating blood, and dredging collaterals. Commonly used formulas included Danggui Buxue Decoction, Liuwei Dihuang Pills, Erzhi Pills, and Buyang Huanwu Decoction. The mechanisms of action of high-frequency drugs in the treatment of diabetic microangiopathy were often related to the inhibition of oxidative stress and suppression of inflammatory reactions. These findings can provide references for the clinical treatment of diabetic microangiopathy and the development of targeted drugs.