A Data Mining Study for Analysis of Acupoint Selection and Combinations in Acupuncture Treatment of Carpal Tunnel Syndrome.

Background: Carpal tunnel syndrome (CTS) is the most prevalent upper limb compressive neuropathy. A considerable number of clinical trials and meta-analyses have provided evidence supporting the effectiveness of acupuncture in treating CTS. Nevertheless, the ideal choice of acupoints remains ambiguous. Objective: A data mining analysis was conducted with the objective of determining the most effective acupoint combinations and selection for CTS. Methods: A search was conducted across seven Chinese and English electronic bibliographic databases spanning from their inception to March 2023. Selected were clinical trials that evaluated the efficacy of acupuncture therapy for CTS, with or without randomised controlled methods. Data extraction mainly included acupoint prescriptions. Information such as first author, study design and study setting were also extracted. The principal outcomes comprised the clinical manifestations linked to CTS. Statistical descriptions were generated using Excel 2019. The analysis of association rules was conducted using SPSS Modeler 18.0. Using SPSS Statistics 26.0, exploratory factor analysis and cluster analysis were conducted. Results: 142 trials (including 86 RCTs and 56 non RCTs) were identified, and 193 groups of effective prescriptions involving 68 acupoints were extracted. The most frequently used acupoints were Da-ling (PC7), Nei-guan (PC6), He-gu (LI4), Wai-guan (TE5), and Yang-xi (LI5). The most frequently used meridians were the pericardial meridian and the large intestine meridian. The majority of special acupoints used were Five-shu points and Yuan-source points, with acupoints on the upper limbs being the most frequently used. The core acupoint groups were analyzed and 11 groups of association rules, 8 factors, and 5 effective cluster groups were obtained. Conclusion: The evidence-based acupoint selection and combinations of acupuncture therapy for carpal tunnel syndrome were provided by the findings of this study.

Bioinformatics-based and multiscale convolutional neural network screening of herbal medicines for improving the prognosis of liver cancer: a novel approach.

Background: Liver cancer is one of the major diseases threatening human life and health, and this study aims to explore new methods for treating liver cancer. Methods: A deep learning model for the efficacy of clinical herbal medicines for liver cancer was constructed based on NDCNN, combined with the natural evolutionary rules of a genetic algorithm to obtain the herbal compound for liver cancer treatment. We obtained differential genes between liver cancer tissues and normal tissues from the analysis of TCGA database, screened the active ingredients and corresponding targets of the herbal compound using the TCMSP database, mapped the intersection to obtain the potential targets of the herbal compound for liver cancer treatment in the Venny platform, constructed a PPI network, and conducted GO analysis and KEGG analysis on the targets of the herbal compound for liver cancer treatment. Finally, the key active ingredients and important targets were molecularly docked. Results: The accuracy of the NDCNN training set was 0.92, and the accuracy of the test set was 0.84. After combining with the genetic algorithm for 1,000 iterations, a set of Chinese herbal compound prescriptions was finally the output. A total of 86 targets of the herbal compound for liver cancer were obtained, mainly five core targets of IL-6, ESR1, JUN, IL1ß, and MMP9. Among them, quercetin, kaempferol, and stigmasterol may be the key active ingredients in hepatocellular carcinoma, and the herbal compound may be participating in an inflammatory response and the immune regulation process by mediating the IL-17 signaling pathway, the TNF signaling pathway, and so on. The anticancer effects of the herbal compound may be mediated by the IL-17 signaling pathway, the TNF signaling pathway, and other signaling pathways involved in inflammatory response and immune regulation. Molecular docking showed that the three core target proteins produced stable binding to the two main active ingredients. Conclusion: The screening of effective herbal compounds for the clinical treatment of liver cancer based on NDCNN and genetic algorithms is a feasible approach and will provide ideas for the development of herbal medicines for the treatment of liver cancer and other cancers.

Acupuncture Methods for Piriformis Syndrome: A Protocol for Systematic Review and Network Meta-Analysis.

Background: Piriformis syndrome (PS) is a common disease that is difficult to clinically treat, which seriously affects people's health and living quality. Multiple clinical studies have demonstrated that acupuncture therapy is an effective treatment for PS, but the optimal method of various acupuncture methods has remained unknown. The aim of this study protocol is to compare the efficacy and the safety of different acupuncture methods for PS. Methods: We will search seven electronic bibliographic databases (PubMed, Embase, Cochrane Library, China National Knowledge Infrastructure, Wanfang Database, Chinese Biomedical Literature Database, and Chongqing VIP Database) from inception to June 2023. Randomized controlled trials (RCTs) will be selected for assessing the effectiveness of acupuncture therapy on PS. Primary outcome measure for this study is pain intensity, and the secondary outcomes are clinical symptoms and signs, physical activity, effective rate, and adverse events. Study selection, data extraction, and risk of bias assessment will be independently completed by at least two reviewers. Then, standard pairwise meta-analysis and network meta-analysis will be conducted using Revman 5.3, Stata V.15.1 and OpenBUGS V.3.2.3. The heterogeneity will be explored by subgroup, meta-regression, and sensitivity analysis, if applicable. Finally, Grading of Recommendations, Assessment, Development and Evaluation (GRADE) pro system will be used to evaluate the quality of evidence. Results: Our systematic review and network meta-analysis will identify the best acupuncture treatment method for PS patients. Conclusion: The results of our review will help decision-makers make educated choices regarding evidence-based acupuncture management options for PS. Prospero Registration Number: No. CRD42022335028.

Analysis of Acupoint Selection and Combinations in Acupuncture Treatment of Carpal Tunnel Syndrome: A Protocol for Data Mining.

Background: Carpal tunnel syndrome (CTS), as the most common compression neuropathy in the upper limb, can lead to upper limb dysfunction in patients. The effectiveness of acupuncture in treating CTS has been validated based on numerous clinical trials and meta-analyses, but questions remain, such as how to select the best acupoints. Our purpose is to conduct the first data mining analysis to identify the most effective acupoint selection and combinations for treating CTS. Methods: We will search 7 electronic bibliographic databases (PubMed, Embase, Cochrane Library, China National Knowledge Infrastructure, Wanfang Database, Chinese Biomedical Literature Database and Chongqing VIP Database) from inception to March 2023. Clinical trials assessing the effectiveness of acupuncture therapy on the management of CTS will be selected. Reviews, protocols, animal trials, case reports, systematic reviews, and meta-analyses will be excluded. The primary outcome measure will be clinical result associated with CTS. Descriptive statistics will be performed in Excel 2019. Association rule analysis will be performed in SPSS Modeler 18.0. Exploratory factor analysis and cluster analysis will be performed in SPSS Statistics 26.0. Results: This study will investigate the most effective acupoint selection and combinations for patients with CTS. Conclusion: Our findings will provide evidence for the effectiveness and potential treatment prescriptions of acupoint application for patients with CTS, helping clinicians and patients make a more informed decision together.

Nanoparticle Delivery of Active Traditional Chinese Medicine Ingredients: A New Strategy for the Treatment of Liver Cancer.

The precise treatment of liver cancer is receiving much research attention. Surgery, chemoradiotherapy, and other methods remain the mainstream of this treatment, but many chemotherapeutic drugs used to treat advanced liver cancer cause adverse reactions and have unstable efficiencies. Active ingredients used in traditional Chinese medicine (TCM) have been examined widely in anti-cancer research due to their advantages of multi-pathway targeting and rich pharmacological effects. However, these active components have poor water solubility, bioavailability, and targeting efficiency. Nanomedicine has been applied to improve the efficacy of TCM ingredients in the treatment of liver cancer. Nanoparticles (NPs) show great potential in this context due to their excellent bioavailability, high controlled agent release efficiency, and clear targeting. This paper reviews the application of NPs loaded with active TCM ingredients in the treatment of liver cancer, with the aim of facilitating new vector development and improving the precision treatment of liver cancer.

Polysaccharide-modified liposomes and their application in cancer research.

Nanodrug delivery systems have been widely used in cancer treatment. Among these, liposomal drug carriers have gained considerable attention due to their biocompatibility, biodegradability, and low toxicity. However, conventional liposomes have several shortcomings, such as poor stability, rapid clearance, aggregation, fusion, degradation, hydrolysis, and oxidation of phospholipids. Polysaccharides are natural polymers of biological origin that exhibit structural stability, excellent biocompatibility and biodegradability, flexibility, non-immunogenicity, low toxicity, and targetability. Therefore, they represent a promising class of polymers for the modification of the surface properties of liposomes to overcome their shortcomings. In addition, polysaccharides can be readily combined with other materials to develop new composite materials. Hence, they represent the optimal choice for liposomal modification to improve pharmacokinetics and clinical utility. Polysaccharide-coated liposomes exhibit better stability, drug release kinetics, and cellular uptake than conventional liposomes. The oncologic application of polysaccharide-coated liposomes has become a research hotspot. We summarize the preparation, physicochemical properties, and antineoplastic effects of polysaccharide-coated liposomes to facilitate antitumor drug development.

Biodesulfurization of dibenzothiophene by growing cells of Gordonia sp. in batch cultures.

A new isolate, identified as Gordonia sp. ZD-7 by 16S rDNA sequence analysis, grew in n-hexadecane containing dibenzothiophene (DBT) which was degraded from 2.8 mM to 0.2 mM within 48 h. Biodesulfurization could be repeatedly performed for more than 190 h, with average desulfurization rates of 5 mmol DBT kg cells (dry wt)(-1) h(-1).

Desulfurization of dibenzothiophene by a newly isolated Corynebacterium sp. ZD-1 in aqueous phase.

Sulfur emission through fuel combustion is a global problem because it is a major cause of acid rain. Crud oil contains many heterocyclic organic sulfur compounds, among which dibenzothiophene (DBT) and DBTs bearing alkyl substitutions usually are representative compounds. A strain was isolated from refinery sludge and identified as Corynebacterium ZD-1. The behavior of DBT degradation by ZD-1 in aqueous phase was investigated. Corynebacterium ZD-1 could metabolize DBT to 2-hydroxybiphenyl(2-HBP) as the dead-end metabolite through a sulfur-specific pathway. In shake flask culture, ZD-1 had its maximal desulfurization activity in the late exponential growth phase and the specific production rate of 2-HBP was about 0.14 (mmol x kg dry cell(-1) x min(-1), mmol x KDC(-1) x min(-1)). Active resting cells for desulfurization should be prepared only in this period. 2-HBP inhibited the growth of strain ZD-1, the production of DBT degradation enzymes, and the activity of enzymes. Sulfate inhibited the production of dibenzothiophene (DBT) degradation enzymes but had no effect on the enzymes' activity. The production rates of 2-HBP at lower cell densities were higher and the maximum amount conversion of DBT to 2-HBP (0.067 mmol/L) after 8 h was gained at 9.2 g dry cell/L rather higher cell density. The results indicated that this newly isolated strain could be a promising biocatalyst for DBT desulfurization.