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A new dynamic load balancing method based on roulette wheel selection in multi-services network was pro-posed.There were two stages in the method,static resource configuration and dynamic route selection.In the first,the optimization distribution of traffic trunk on parallel LSP was obtained by offline optimization algorithm.In the second,the LSP was selected by roulette wheel selection.The simulation results show that the method is able not only to guaran-tee QoS of the services but also balance the network load dynamically.

Tuberculosis (TB) is still an urgent global public health problem. Notably, mucosal‐associated invariant T (MAIT) cells play an important role in early anti‐TB immune response. Targeted control of them may be an effective method to improve vaccine efficacy and TB treatment. However, the biology and signal regulation mechanisms of MAIT cells in TB patients are still poorly understood. Previous studies have been limited by the lack of reagents to specifically identify MAIT cells. In addition, the use of alternative markers may subsume non‐MAIT cell into MAIT cell populations. In this study, the human MR1 tetramer which can specifically identify MAIT cells was used to further explore the effect and mechanism of MAIT cells in anti‐TB immune response. Our results showed that the tetramer+ MAIT cells in peripheral blood of TB patients were mainly CD8+ or CD4−CD8− cells, and very few were CD4+ cells. After BCG infecting autologous antigen‐presenting cells, MAIT cells in patients produced significantly higher levels of cytokines, lysis and proliferation compared with healthy controls. After suppression of mTORC1 by the mTORC1‐specific inhibitor rapamycin, the immune response of MAIT cells in patients was significantly reduced. This study demonstrates that peripheral blood tetramer+ MAIT cells from TB patients have significant anti‐TB immune effect, which is regulated by mTORC1. This could provide ideas and potential therapeutic targets for the development of novel anti‐TB immunotherapy. [ABSTRACT FROM AUTHOR]

To systematically evaluate the risk factors for wound infection at the surgical site after neurosurgical craniotomy by meta‐analysis, and to provide an evidence‐based basis for preventing the occurrence of wound infection. A computerised search of PubMed, EMBASE, Cochrane Library, China National Knowledge Infrastructure and Wanfang database was conducted for relevant studies on risk factors for surgical site wound infection after neurosurgical craniotomy published from the database inception to November 2023. Two researchers independently screened the literature, extracted the data and performed quality assessment in strict accordance with the inclusion and exclusion criteria. STATA 17.0 software was applied for data analysis. Overall, 18 papers with 17 608 craniotomy patients were included, of which 905 patients developed wound infections. The analysis showed that underlying diseases [OR = 2.50, 95% CI (1.68, 3.72), p < 0.001] and emergency surgery [OR = 2.47, 95% CI (1.80, 3.38), p < 0.001] were the risk factors for developing wound infections after craniotomy, age < 60 years [OR = 0.72, 95% CI (0.52, 0.98), p = 0.039] was a protective factor for wound infections; whereas sex [OR = 1.11, 95% CI (0.98, 1.27), p = 0.112] and the antimicrobial use [OR = 1.30, 95% CI (0.81 2.09), p = 0.276] were not associated with the presence or absence of wound infection after craniotomy. Underlying disease and emergency surgery are risk factors for developing wound infections after craniotomy, whereas age < 60 years is a protective factor. Clinicians can reduce the occurrence of postoperative wound infections by communicating with patients in advance about the possibility of postoperative wound infections based on these factors, and by doing a good job of preventing postoperative wound infections. [ABSTRACT FROM AUTHOR]

BACKGROUND There is an urgent need to strengthen the testing and certification of geographically iconic foods, as well as to use discriminatory science and technology for their regulation and verification. Multi‐element and stable isotope analyses were combined to provide a new chemometric approach for improving the discrimination tea samples from different geographical origins. Different stoichiometric methods [principal component analysis (PCA), hierarchical cluster analysis (HCA), partial least squares‐discriminant analysis (PLS‐DA), back propagation based artificial neural network (BP‐ANN) and linear discriminant analysis (LDA)] were used to demonstrate this discrimination approach using Yongchuanxiuya tea samples in an experimental test. RESULTS: Multi‐element and stable isotope analyses of tea samples using inductively coupled plasma mass spectrometry and inductively coupled plasma optical emission spectrometry easily distinguished the geographical origins. However, the clustering ability of the two unsupervised learning methods (PCA and HCA) were worse compared to that of the three supervised learning methods (PLS‐DA, BP‐ANN and LDA). BP‐ANN and LDA, with 100% recognition and prediction abilities, were found to be better than PLS‐DA. 86Sr and 112Cd were the markers enabling the successful classification of tea samples according to their geographical origins. Under the validation by 'blind' dataset, the prediction accuracies of the BP‐ANN and LDA methods were all greater than 90%. The LDA method showed the best performance, with an accuracy of 100%. CONCLUSION: In summary, determination of mineral elements and stable isotopes using inductively coupled plasma mass spectrometry and inductively coupled plasma optical emission spectrometry techniques coupled with chemometric methods, especially the LDA method, is a good approach for improving the authentication of a diverse range of tea. The present study contributes toward generalizing the use of fingerprinting mineral elements and stable isotopes as a promising tool for testing the geographic roots of tea and food worldwide. © 2020 Society of Chemical Industry [ABSTRACT FROM AUTHOR]