Objective:To explore social support and personality characteristic of patients with clinically chronic pains to provide a new idea for clinical psycho-intervention.Method:45 patients with clinically chronic pains were evaluated by the Symptom Checklist(SCL-90),EPQ and SSRS,and compared with the control group.Results:Somatization,interpersonal sensitivity,anxiety,fear and psychotic factors have significant differences from those of the control group when being compared(p

Objective:To investigate the clinical efficacy of second-line therapy with dasatinib in the treatment of chronic myeloid leukemia.Methods:Sixty patients with chronic phase chronic myeloid leukemia who received treatment in Hongqi Hospital of Mudanjiang Medical University between January 2015 and January 2021 were included in this study. They were randomly divided into control and observation groups, with 30 patients in each group. The control group was treated with conventional chemotherapy, and the observation group was treated with conventional chemotherapy combined with oral dasatinib. All patients were treated for 6 months. Clinical efficacy, immune function indexes, quality of life score, and incidence of adverse reactions (abnormal liver function, rash, fatigue, peripheral edema, nausea and vomiting, alopecia) were compared between the two groups.Results:Objective response rate (ORR) in the observation group was significantly higher than that in the control group [83.33% (25/30) vs. 53.33% (16/30), χ2 = 6.23, P < 0.05). Before treatment, there were no significant difference in immune function indicators between the two groups ( t = 0.03, 0.20, 0.44, all P > 0.05). After treatment, CD 4/CD 8, CD 3+ and natural killer cells in the observation group were (1.03 ± 0.32), (43.77 ± 6.62)%, (31.12 ± 3.38)%, respectively, which were significantly higher than (0.74 ± 0.28), (35.79 ± 6.27)%, (28.22 ± 2.84)% in the control group ( t = 3.69, 4.78, 3.60, all P < 0.05). The scores of social functioning, material well-being life, mental health, somatic health in the observation group were (85.48 ± 6.25) points, (80.12 ± 6.34) points, (79.94 ± 6.48) points, and (77.92 ± 5.81) points, respectively, which were significantly higher than (72.79 ± 5.89) points, (63.47 ± 5.82) points, (68.87 ± 6.08) points, (63.14 ± 6.12) points in the control group ( t = 7.91, 10.59, 6.82, 9.59, all P < 0.05). The incidence of adverse reactions in the observation group was significantly lower than that in the control group [16.67% (5/30) vs. 40.00% (12/30), χ2 = 4.02, P < 0.05). Conclusion:Second-line therapy with dasatinib for chronic phase chronic myeloid leukemia is effective and safe. It can effectively improve the efficacy and safety of chemotherapy and can also improve immunological function and quality of life.

OBJECTIVE: We propose a novel region- level self-supervised contrastive learning method USRegCon (ultrastructural region contrast) based on the semantic similarity of ultrastructures to improve the performance of the model for glomerular ultrastructure segmentation on electron microscope images. METHODS: USRegCon used a large amount of unlabeled data for pre- training of the model in 3 steps: (1) The model encoded and decoded the ultrastructural information in the image and adaptively divided the image into multiple regions based on the semantic similarity of the ultrastructures; (2) Based on the divided regions, the first-order grayscale region representations and deep semantic region representations of each region were extracted by region pooling operation; (3) For the first-order grayscale region representations, a grayscale loss function was proposed to minimize the grayscale difference within regions and maximize the difference between regions. For deep semantic region representations, a semantic loss function was introduced to maximize the similarity of positive region pairs and the difference of negative region pairs in the representation space. These two loss functions were jointly used for pre-training of the model. RESULTS: In the segmentation task for 3 ultrastructures of the glomerular filtration barrier based on the private dataset GlomEM, USRegCon achieved promising segmentation results for basement membrane, endothelial cells, and podocytes, with Dice coefficients of (85.69 ± 0.13)%, (74.59 ± 0.13)%, and (78.57 ± 0.16)%, respectively, demonstrating a good performance of the model superior to many existing image-level, pixel-level, and region-level self-supervised contrastive learning methods and close to the fully- supervised pre-training method based on the large- scale labeled dataset ImageNet. CONCLUSION USRegCon facilitates the model to learn beneficial region representations from large amounts of unlabeled data to overcome the scarcity of labeled data and improves the deep model performance for glomerular ultrastructure recognition and boundary segmentation.
Humans ; Electrons ; Endothelial Cells ; Learning ; Podocytes ; Kidney Diseases