Effects of Tai Chi Chuan on Cognitive Function in Adults 60 Years or Older With Type 2 Diabetes and Mild Cognitive Impairment in China: A Randomized Clinical Trial.

Importance: Type 2 diabetes (T2D) is associated with the progression of cognitive dysfunction. Physical activity benefits cognition, but no evidence from randomized clinical trials has shown whether tai chi chuan has better long-term benefits than fitness walking in cognitive function for patients with T2D and mild cognitive impairment (MCI). Objective: To compare the effectiveness of tai chi chuan, a mind-body exercise, for improving cognitive function in older adults with T2D and MCI, with fitness walking. Design, Setting, and Participants: This randomized clinical trial was conducted between June 1, 2020, and February 28, 2022, at 4 sites in China. Participants included 328 adults (aged ≥60 years) with a clinical diagnosis of T2D and MCI. Interventions: Participants were randomized in a 1:1:1 ratio to a tai chi chuan group, a fitness walking group, or a control group. The tai chi chuan group received 24-form simplified tai chi chuan. The fitness walking group received fitness walking training. Both exercise groups took the training for 60 min/session, 3 times/wk, for 24 weeks in a supervised setting. All 3 groups were provided with a 30-minute diabetes self-management education session, once every 4 weeks for 24 weeks. The participants were followed up for 36 weeks. Main Outcomes and Measures: The primary outcome was the global cognitive function measured at 36 weeks by the Montreal Cognitive Assessment (MoCA). Secondary outcomes included MoCA at 24 weeks and other cognitive subdomain measures and blood metabolic indices at 24 and 36 weeks. Results: A total of 328 participants (mean [SD] age, 67.55 [5.02] years; mean [SD] T2D duration, 10.48 [6.81] years; 167 [50.9%] women) were randomized to the tai chi chuan group (n = 107), fitness walking group (n = 110), or control group (n = 111) and included in the intention-to-treat analysis. At 36 weeks, the tai chi chuan group showed improved MoCA scores compared with the fitness walking group (mean [SD], 24.67 [2.72] vs 23.84 [3.17]; between-group mean difference, 0.84 [95% CI, 0.02-1.66]; P = .046) in the intention-to-treat analysis. The per-protocol analysis data set and subgroup analysis at 36 weeks showed similar results. Based on the generalized linear models, the treatment effects were similar in each group after adjusting for self-reported dietary calories and physical activity. There were 37 nonserious adverse events (tai chi chuan group, 8; fitness walking group, 13; control group, 16) unrelated to the study with no statistically significant difference among the 3 groups (P = .26). Conclusions and Relevance: In this randomized clinical trial including older adults with T2D and MCI, tai chi chuan was more effective than fitness walking in improving global cognitive function. The findings support a long-term benefit, suggesting the potential clinical use of tai chi chuan as an exercise intervention to improve cognitive function for older adults with T2D and MCI. Trial Registration: ClinicalTrials.gov Identifier: NCT04416841.

Model prediction of herbicide residues in soybean oil: Relationship between physicochemical properties and processing factors.

The distribution and processing factors (PFs) of herbicides in cold-/hot-pressed soybean samples (n = 3) were studied on the laboratory scale. The hot-pressing process was found to have a significant effect on herbicide degradation in soybean samples. Specifically, for highly water-soluble pesticides with pKow > 2 in soybean oil, the PF values were generally > 1. Nonlinear curve fitting revealed that the PFs of herbicides in soybean oil were positively correlated with their octanol-water partition coefficients, but negatively correlated with their water solubility and melting points. A principal component analysis confirmed the dominant parameters among the herbicide PFs during soybean oil production. Using the physicochemical parameters of pesticides, the developed multiple linear regression model gave a fitting accuracy of ≥0.80 for predicting the theoretical PF values of pesticides in soybean oil products (0.39 < RMSE < 0.58). Thus, this model may be applicable for safety risk assessments and establishing maximum residue limits for pesticides in processed products.

A Core Drug Discovery Framework from Large-Scale Literature for Cold Pathogenic Disease Treatment in Traditional Chinese Medicine.

Cold pathogenic disease is a widespread disease in traditional Chinese medicine, which includes influenza and respiratory infection associated with high incidence and mortality. Discovering effective core drugs in Chinese medicine prescriptions for treating the disease and reducing patients' symptoms has attracted great interest. In this paper, we explore the core drugs for curing various syndromes of cold pathogenic disease from large-scale literature. We propose a core drug discovery framework incorporating word embedding and community detection algorithms, which contains three parts: disease corpus construction, drug network generation, and core drug discovery. First, disease corpus is established by collecting and preprocessing large-scale literature about the Chinese medicine treatment of cold pathogenic disease from China National Knowledge Infrastructure. Second, we adopt the Chinese word embedding model SSP2VEC for mining the drug implication implied in the literature; then, a drug network is established by the semantic similarity among drugs. Third, the community detection method COPRA based on label propagation is adopted to reveal drug communities and identify core drugs in the drug network. We compute the community size, closeness centrality, and degree distributions of the drug network to analyse the patterns of core drugs. We acquire 4681 literature from China national knowledge infrastructure. Twelve significant drug communities are discovered, in which the top-10 drugs in every drug community are recognized as core drugs with high accuracy, and four classical prescriptions for treating different syndromes of cold pathogenic disease are discovered. The proposed framework can identify effective core drugs for curing cold pathogenic disease, and the research can help doctors to verify the compatibility laws of Chinese medicine prescriptions.

The effectiveness and safety of Tai Chi for patients with essential hypertension: study protocol for an open-label single-center randomized controlled trial.

BACKGROUND: Evidence showed that Tai Chi may have beneficial effects among hypertensive individuals, although the results are not convincing. We aim to conduct a high-quality clinical trial with 24-h BP measurement to provide robust evidence of Tai Chi for essential hypertension. METHODS: This is an open-label single-center randomized controlled trial with 3 parallel arms. We will compare Tai Chi with walking and waiting-list control. We will recruit 234 hypertensive patients with mild to moderate essential hypertension and randomly assign them to 3 different groups. Participants in Tai Chi group will receive a group-format Yang style 24-form Tai Chi exercise program, 3 sessions per week for 12 weeks. The walking group will be asked to walk, 3 sessions per week for 12 weeks. The waiting-list group will not receive any interventions and/or exercise training. The primary outcome is the change in average 24-h systolic blood pressure (SBP) between baseline and 12 weeks after randomization. The secondary outcomes include 24-h Diastolic Blood Pressure (DBP), average SBP and average DBP during the daytime and night-time, blood pressure (BP) variability, SBP load and DBP load, circadian rhythm of BP, and morning BP surge, endothelial functional indicators, home measured BP, quality of life, adverse events and so on. DISCUSSION: We expect findings of this trial will provide important insight into application of Tai Chi as an effective and acceptable method for hypertensive patients. Successful completion of this proposed study will also contribute to promotion of Tai Chi in the community in the future. TRIAL REGISTRATION: Clinicaltrials.gov registry: https://clinicaltrials.gov/ct2/show/NCT04267471 , date: February 12, 2020.

A Semantic Analysis and Community Detection-Based Artificial Intelligence Model for Core Herb Discovery from the Literature: Taking Chronic Glomerulonephritis Treatment as a Case Study.

The Traditional Chinese Medicine (TCM) formula is the main treatment method of TCM. A formula often contains multiple herbs where core herbs play a critical therapeutic effect for treating diseases. It is of great significance to find out the core herbs in formulae for providing evidences and references for the clinical application of Chinese herbs and formulae. In this paper, we propose a core herb discovery model CHDSC based on semantic analysis and community detection to discover the core herbs for treating a certain disease from large-scale literature, which includes three stages: corpus construction, herb network establishment, and core herb discovery. In CHDSC, two artificial intelligence modules are used, where the Chinese word embedding algorithm ESSP2VEC is designed to analyse the semantics of herbs in Chinese literature based on the stroke, structure, and pinyin features of Chinese characters, and the label propagation-based algorithm LILPA is adopted to detect herb communities and core herbs in the herbal semantic network constructed from large-scale literature. To validate the proposed model, we choose chronic glomerulonephritis (CGN) as an example, search 1126 articles about how to treat CGN in TCM from the China National Knowledge Infrastructure (CNKI), and apply CHDSC to analyse the collected literature. Experimental results reveal that CHDSC discovers three major herb communities and eighteen core herbs for treating different CGN syndromes with high accuracy. The community size, degree, and closeness centrality distributions of the herb network are analysed to mine the laws of core herbs. As a result, we can observe that core herbs mainly exist in the communities with more than 25 herbs. The degree and closeness centrality of core herb nodes concentrate on the range of [15, 40] and [0.25, 0.45], respectively. Thus, semantic analysis and community detection are helpful for mining effective core herbs for treating a certain disease from large-scale literature.

[Prediction of drug-target interaction based on fingerprint similarity].

Drugs play the pharmacological effects by combining with target proteins. Identification of drug-target interactions is important for discovering new functions of drugs. In this paper, the target fingerprints based on molecular substructure and the drug-target similarity based on fingerprints are proposed to a random forest-based classification method, in order to identify the drug-target interactions. Experiments on enzymes, ion channels, G protein-coupled receptors and nuclear receptors proved the effectiveness of the proposed method. In addition, the proposed method is applied to predict the interactions between ingredients and targets of traditional Chinese medicines.