Mechanism of Qihuang needle therapy in the management of tic disorders: a clinical trial protocol

BackgroundQihuang needle therapy is a newly developed acupuncture therapy to treat tic disorders in clinical practice. However, the mechanism to reduce tic severity remains unknown. Changes in intestinal flora and circulation metabolites are perhaps the potential pathogenesis of tic disorders. As a result, we present a protocol for a controlled clinical trial using multi-omics analysis to probe the mechanism of the Qihuang needle in managing tic disorders.MethodsThis is a matched-pairs design, controlled, clinical trial for patients with tic disorders. Participants will be allocated to either an experimental group or a healthy control group. The main acupoints are Baihui (GV20), Yintang (EX-HN3), and Jueyinshu (BL14). The experimental group will receive Qihuang needle therapy for a month, while the control group will receive no interventions.Expected outcomesThe change in the severity of the tic disorder is set as the main outcome. Secondary outcomes include gastrointestinal severity index and recurrence rate, which will be calculated after a 12-week follow-up. Gut microbiota, measured by 16S rRNA gene sequencing; serum metabolomics, assessed via LC/MS; and serum zonulin, assessed by enzyme-linked immunosorbent assay (ELISA), will be used as biological specimen analysis outcomes. The present study will investigate the possible interactions between intestinal flora and serum metabolites and the improvement of clinical profiles, which may elucidate the mechanism of Qihuang needle therapy for tic disorders.Trial registrationThis trial is registered at the Chinese Clinical Trial Registry (http://www.chictr.org.cn/). Registration number: ChiCTR2200057723, Date: 2022-04-14

Deep learning driven real time topology optimisation based on initial stress learning

Topology optimisation can facilitate engineers in proposing efficient and novel conceptual design schemes, but the traditional FEM based optimization demands significant computing power and makes the real time optimization impossible. Based on the convolutional neural network (CNN) method, a new deep learning approximate algorithm for real time topology optimisation is proposed. The algorithm learns from the initial stress (LIS), which is defined as the major principal stress matrix obtained from finite element analysis in the first iteration of classical topology optimisation. The initial major principal stress matrix of the structure is used to replace the load cases and boundary conditions of the structure as independent variables, which can produce topological prediction results with high accuracy based on a relatively small number of samples. Compared with the traditional topology optimisation method, the new method can produce a similar result in real time without repeated iterations. A classic short cantilever problem was used as an example, and the optimized topology of the cantilever structure is predicted successfully by the established approximate algorithm. By comparing the prediction results to the structural optimisation results obtained by the classical topology optimisation method, it is discovered that the two results are highly approximate, which verifies the validity of the established algorithm. Furthermore, a new algorithm evaluation method is proposed to evaluate the effects of using different methods to select samples on the prediction performance of the optimized topology, and the results were promising and concluded in the end

Correlations among the plasma concentrations of first-line anti-tuberculosis drugs and the physiological parameters influencing concentrations

Background: The plasma concentrations of the four most commonly used first-line anti-tuberculosis (TB) drugs, isoniazid (INH), rifampicin (RMP), ethambutol (EMB), and pyrazinamide (PZA), are often not within the therapeutic range. Insufficient drug exposure could lead to drug resistance and treatment failure, while excessive drug levels may lead to adverse reactions. The purpose of this study was to identify the physiological parameters influencing anti-TB drug concentrations.Methods: A retrospective cohort study was conducted. The 2-h plasma concentrations of the four drugs were measured by using the high-performance liquid chromatography-tandem mass spectrometry method.Results: A total of 317 patients were included in the study. The proportions of patients with INH, RMP, EMB, and PZA concentrations within the therapeutic range were 24.3%, 31.5%, 27.8%, and 18.6%, respectively. There were positive associations between the concentrations of INH and PZA and RMP and EMB, but negative associations were observed between the concentrations of INH and RMP, INH and EMB, RMP and PZA, and EMB and PZA. In the multivariate analysis, the influencing factors of the INH concentration were the PZA concentration, total bile acid (TBA), serum potassium, dose, direct bilirubin, prealbumin (PA), and albumin; those of the RMP concentration were PZA and EMB concentrations, weight, α-l-fucosidase (AFU), drinking, and dose; those of the EMB concentration were the RMP and PZA concentrations, creatinine, TBA and indirect bilirubin; and those of the PZA concentration were INH, RMP and EMB concentrations, sex, weight, uric acid and drinking.Conclusion: The complex correlations between the concentrations of the four first-line anti-TB drugs lead to a major challenge in dose adjustment to maintain all drugs within the therapeutic window. Levels of TBA, PA, AFU, and serum potassium should also be considered when adjusting the dose of the four drugs

Synthesis and Raman Performance Enhancement of Multilayer AuAg Heterostructures with Magnetic Resonance

Significant amplification of surface enhanced Raman scattering (SERS) signals can be achieved mainly by the electric field enhancement in metal core-shell nanostructures, and the enhanced magnetic field is rarely studied. In this study, we prepared multi-gap Au/AgAu core-shell hybrid nanostructures by using gold nanocup as the core. The overgrowth processes to grow one, two, and three layers of AgAu hybrid nanoshells can produce Au/AgAu1, Au/AgAu2, and Au/AgAu3 heteronanostructures. The strong plasmon coupling between the core and shell leads to significant electromagnetic field enhancement. Under the synergistic effect of electromagnetic plasmon resonance and plasmon coupling, Au/AgAu core-shell hybrid nanostructures exhibit excellent SERS signals. We also investigate the effect of the interstitial position of the rhodamine B (RhB) molecule on Raman enhancement in Au/AgAu3 heteronanostructures. This study can provide new ideas for the synthesis of multi-gap Raman signal amplifiers based on magnetic plasmon coupling

Anti-Invasion and Antimetastatic Effects of Porcine Recombinant NK-lysin on SMMC-7721 Human Hepatocellular Carcinoma Cells

The high invasion and metastasizing abilities of hepatocellular carcinoma (HCC) are the primary reasons for the high mortality rate of patients. Therefore, identification of agents to inhibit invasion and metastasis is very important for treatment of HCC. We analyzed the anti-invasion and antimetastatic effects of porcine recombinant NK-lysin, which was designed and expressed in vitro by our research group, on SMMC-7721 hepatocellular carcinoma cells via wound-healing assays, adhesion assays, invasion assays, real-time polymerase chain reaction (PCR), and Western blot analysis. MTT assay results indicated that NK-lysin inhibited the growth of SMMC-7721 cells in a dose- and time-dependent manner. NK-lysin reduced the ability of cell migration, adhesion, and invasion. Based on gene and protein expression analysis, NK-lysin decreased β-catenin and MMP-2 expression. These results suggested that NK-lysin has anti-invasion and antimetastatic effects on hepatocellular carcinoma cells in vitro by reducing the level of the β-catenin and MMP-2