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Objective. To explore the effect of a moxibustion instrument combined with intermediate frequency electrostatic therapy on pain and joint function in elderly patients with cold-dampness arthritis (KOA). Method. 200 patients with cold-dampness KOA treated in our hospital from May 2019 to September 2021 were selected. According to the random number table method, they were divided into the observation group ( n = 100 ) and control group ( n = 100 ). The observation group was treated with moxibustion combined with medium-frequency treatment, and the control group was treated with medium-frequency treatment. The clinical effects of the two groups were compared. The joint functions of the two groups were evaluated by the visualization scale of the osteoarthritis index (WOMAC index) of McMaster University in Western Ontario. The TCM symptom scores of the two groups were evaluated according to the guiding principles for clinical research of new traditional Chinese medicine. The visual analogue scale (VAS) was used to evaluate the pain degree of the two groups, and the microcirculatory blood perfusion (MBPU) and interleukin-1 were compared between the two groups, β (IL-1β) and tumor necrosis factor-α (TNF-α). The levels of matrix metalloproteinase-1 (MMP-1), serum bone morphogenetic protein-2 (BMP-2), cartilage oligomeric matrix protein (COMP), and serum type II collagen C-terminal peptide (CTX-II) were assessed by the comprehensive quality of life questionnaire-74. Result. The total effective rate of the observation group (92.00%) was higher than that of the control group (76.00%), and the difference was statistically significant ( P < 0.05 ) in β and TNF-α. The levels of MMP-3, BMP-2, comp, and CTX-II and the improvement of quality of life score in the control group were better than those in the control group ( P < 0.05 ). Conclusion. Moxibustion instrument combined with intermediate frequency electrostatic therapy can effectively improve the knee joint function, pain, blood perfusion, inflammatory reaction, and cartilage damage of the elderly patients with cold-dampness-type knee arthritis, and the therapeutic effect is good.

The Farm animal Genotype-Tissue Expression (FarmGTEx, https://www.farmgtex.org/) project has been established to develop a comprehensive public resource of genetic regulatory variants in domestic animal species, which is essential for linking genetic polymorphisms to variation in phenotypes, helping fundamental biology discovery and exploitation in animal breeding and human biomedicine. Here we present results from the pilot phase of PigGTEx (http://piggtex.farmgtex.org/), where we processed 9,530 RNA-sequencing and 1,602 whole-genome sequencing samples from pigs. We build a pig genotype imputation panel, characterize the transcriptional landscape across over 100 tissues, and associate millions of genetic variants with five types of transcriptomic phenotypes in 34 tissues. We study interactions between genotype and breed/cell type, evaluate tissue specificity of regulatory effects, and elucidate the molecular mechanisms of their action using multi-omics data. Leveraging this resource, we decipher regulatory mechanisms underlying about 80% of the genetic associations for 207 pig complex phenotypes, and demonstrate the similarity of pigs to humans in gene expression and the genetic regulation behind complex phenotypes, corroborating the importance of pigs as a human biomedical model.

This paper studies the adaptive optimal control problem for a class of linear time-delay systems described by delay differential equations (DDEs). A crucial strategy is to take advantage of recent developments in reinforcement learning and adaptive dynamic programming and develop novel methods to learn adaptive optimal controllers from finite samples of input and state data. In this paper, the data-driven policy iteration (PI) is proposed to solve the infinite-dimensional algebraic Riccati equation (ARE) iteratively in the absence of exact model knowledge. Interestingly, the proposed recursive PI algorithm is new in the present context of continuous-time time-delay systems, even when the model knowledge is assumed known. The efficacy of the proposed learning-based control methods is validated by means of practical applications arising from metal cutting and autonomous driving., 12 pages, 8 figures