Occupational therapy is an important part of rehabilitation medicine. There is movement, feel, swallowing, speech, vision,cognitive, psychological and social relations dysfunction in stroke patients. Occupational therapy play an important part in the whole processof intervention for stroke patients, and help them improve their quality of life.

Objective To observe the effect of psychological support therapy on anxiety resulted from pain after stroke. Methods 40 patients with anxiety after stroke were divided equally into psychological support treatment group and control group. They were assessed with Hamilton Anxiety Scale (HAMA) and Visual Analogue Scale (VAS) of pain before and after treatment. Results The scores of HAMA and VAS improved more in treatment group than in control group (P<.01). Conclusion The psychological support therapy can reduce the anxiety and pain after stroke.

ObjectiveTo assess the effects of constraint-induced movement therapy(CIMT) on sub-acute stroke patients with upper extremity motor dysfunction.Methods63 patients with hemiplegia after stroke were divided into two groups: control group(31 cases) and CIMT group(32 casese). The two groups received the regular rehabilitation training for 14 d. Then the control group went on the the regular rehabilitation training, while the CIMT group received CIMT for 14 d. All patients were assessed by the Action Research Arm Test(ARAT) and Fugl-Meyer(FMA) on the first day, the 15th day and the 30th day after the treatment.ResultsARAT score and FMA scores were higher in CIMT group than in the control group 30 d after the treatment and in CIMT group 15 days after the treatment(P<0.001).ConclusionCIMT is more effective to improve the upper limb motor function of the sub-acute stroke patients than the regular rehabilitation training.

【Objective】 To select and identify miRNA signatures to predict TMB level in gastric cancer based on The Cancer Genome Atlas (TCGA) database and machine learning methods. 【Methods】 MiRNA expression and somatic mutation profiles of gastric cancer (GC) were downloaded from TCGA database. R "limma" package was performed to select differentially expressed miRNAs between high-TMB and low-TMB groups. Two machine learning algorisms, random forest (RF), and Support Vector Machine-Recursive Feature Elimination were utilized to identify miRNAs with the highest discriminative ability. ROC was used to test the predictive ability of these signatures in multiple datasets. Besides, immune cells of different TMB levels were compared by the CIBERSORT method. 【Results】 A total of 56 differentially expressed miRNAs (DE-miRNAs) were filtered. Functional enrichment analysis showed that these DE miRNAs are mainly enriched in signaling pathways related to tumor occurrence and development as well as immunity-related biological processes. The RF and SVM-RFE algorithms jointly identified 10 diagnostic features of miRNAs, among which only hsa-miR-210-3p is considered the most relevant predictive biomarker for TMB classification. The AUC value of hsa-miR-210-3p in the training, testing, and total sets is 0.822, 0.721, and 0.793, respectively, and has been validated in other cancer types. Besides, CIBERSORT analysis suggests differences in immune cell infiltration between high- and low-TMB groups. Meanwhile, there is a significant positive correlation between the expression of immune checkpoint related genes and mismatch repair related genes and hsa-miR-210-3p. 【Conclusion】 This study successfully identified hsa-miR-210-3p as a predictive biomarker for TMB classification, which can effectively predict TMB values in gastric cancer and other cancer patients and may provide some guidance for immunotherapy.