Objective To explore the correlation between skeletal muscle fat content and insulin resistance(IR)in patients with type 2 diabetes mellitus(T2DM),and to evaluate the diagnostic value of skeletal muscle fat quantitative parameters for IR.Methods During January 2018 to January 2021,150 T2DM patients as observation group(T2DM group)and 100 healthy subjects as control group(NC group)were selected.All subjects underwent magnetic resonance imaging quantitatively analyzed skeletal muscle fat content,including intermuscular fat(IMAT),adipose tissue beneath fascia(SFAT)and subcutaneous fat(SCAT).Receiver operating characteristic(ROC)curve was used to analyze the diagnostic value of skeletal muscle fat quantitative parameters for IR in T2DM patients.Results The levels of IMAT and SFAT were higher in T2DM group than those in NC group[(10.05±1.34)%vs(7.16±2.06)%,(3.64±0.54)%vs(3.40±0.75)%,P<0.05],while the level of SCAT was lower than in T2DM group than in NC group[(20.16±6.34)%vs(24.97±6.57)%,P<0.05].Pearson correlation analysis showed that IMAT and SFAT were positively correlated with HbA1c and HOMA-IR(P<0.05),while SCAT was negatively correlated with HbA1c and HOMA-IR(P<0.05).ROC curve analysis showed that the area under the curve of IMAT,SFAT,and SCAT for the diagnostic value of T2DM combined with IR were 0.716,0.667 and 0.736,with sensitivities of 75.4%,72.9%and 76.4%,and specificity of 71.4%,65.2%and 68.1%.Conclusion Skeletal muscle fat contentis associated with IR.The quantitative parameters of skeletal muscle fat have good diagnostic efficacy for T2DM complicated with IR.

Recently, deep learning has achieved impressive results in medical image tasks. However, this method usually requires large-scale annotated data, and medical images are expensive to annotate, so it is a challenge to learn efficiently from the limited annotated data. Currently, the two commonly used methods are transfer learning and self-supervised learning. However, these two methods have been little studied in multimodal medical images, so this study proposes a contrastive learning method for multimodal medical images. The method takes images of different modalities of the same patient as positive samples, which effectively increases the number of positive samples in the training process and helps the model to fully learn the similarities and differences of lesions on images of different modalities, thus improving the model's understanding of medical images and diagnostic accuracy. The commonly used data augmentation methods are not suitable for multimodal images, so this paper proposes a domain adaptive denormalization method to transform the source domain images with the help of statistical information of the target domain. In this study, the method is validated with two different multimodal medical image classification tasks: in the microvascular infiltration recognition task, the method achieves an accuracy of (74.79 ± 0.74)% and an F1 score of (78.37 ± 1.94)%, which are improved as compared with other conventional learning methods; for the brain tumor pathology grading task, the method also achieves significant improvements. The results show that the method achieves good results on multimodal medical images and can provide a reference solution for pre-training multimodal medical images.
Humans ; Algorithms ; Brain/diagnostic imaging* ; Brain Neoplasms/diagnostic imaging* ; Recognition, Psychology

Hepatocellular carcinoma (HCC) is the most common liver malignancy, where HCC segmentation and prediction of the degree of pathological differentiation are two important tasks in surgical treatment and prognosis evaluation. Existing methods usually solve these two problems independently without considering the correlation of the two tasks. In this paper, we propose a multi-task learning model that aims to accomplish the segmentation task and classification task simultaneously. The model consists of a segmentation subnet and a classification subnet. A multi-scale feature fusion method is proposed in the classification subnet to improve the classification accuracy, and a boundary-aware attention is designed in the segmentation subnet to solve the problem of tumor over-segmentation. A dynamic weighted average multi-task loss is used to make the model achieve optimal performance in both tasks simultaneously. The experimental results of this method on 295 HCC patients are superior to other multi-task learning methods, with a Dice similarity coefficient (Dice) of (83.9 ± 0.88)% on the segmentation task, while the average recall is (86.08 ± 0.83)% and an F1 score is (80.05 ± 1.7)% on the classification task. The results show that the multi-task learning method proposed in this paper can perform the classification task and segmentation task well at the same time, which can provide theoretical reference for clinical diagnosis and treatment of HCC patients.
Humans ; Carcinoma, Hepatocellular ; Liver Neoplasms ; Learning

Objective:To explore the effect of Tai chi ball combined with Baduanjin in patients with acute myocardial infarction after PCI.Methods:From October 2018 to October 2019, a total of 118 patients with acute myocardial infarction after PCI in Department of Cardiology of Shangqiu First People's Hospital were selected as the research objects using the convenient sampling method, and divided into the observation group (57 cases) and the control group (61 cases) by the random number table method. The control group adopted conventional treatment and nursing, and the observation group conducted Tai Chi ball combined with Baduanjin exercise program on the basis of conventional treatment and nursing. One month after discharge, the ability of activity of daily living and quality of life were compared between the two groups.Results:One month after discharge, the total score of the ability of activity of daily living and the score of each dimension of the observation group were lower than those of the control group, and the differences were statistiocally significant ( P<0.05) ; the total score of the quality of life and the score of each dimension of the observation group were higher than those of the control group, and the differences were statistically significant ( P<0.05) . Conclusions:Tai Chi ball combined with Baduanjin can effectively improve the ability of activity of daily living and quality of life of patients with acute myocardial infarction after PCI.

Objective:To investigate the antigen-sparing effects of crude polysaccharides from Cistanche deserticola Y. C.Ma (CPCD) for influenza virus vaccine (IVV). Methods:ICR mice were immunized subcutaneously with CPCD combined with different doses of IVV (0.01 μg and 0.1 μg). Hemagglutinin inhibition (HI) assay was used to detect HI titers in serum samples. Indirect ELISA was performed to detect the levels of specific IgG antibodies and their subtypes in serum samples. The proliferation of splenic lymphocytes was detected by MTT assay. The percentages of CD4 + , CD8 + and CD44 + T cells and the levels of IFN-γ in splenic cells isolated from the vaccinated mice were analyzed by flow cytometry. Results:CPCD significantly increased HI titers (234.67±47.70 vs 149.33±47.70, P<0.05), promoted the production of IgG ( A450 value: 1.16±0.63 vs 0.30±0.21, P<0.05) and IgG1 ( A450 value: 1.09±0.60 vs 0.26±0.21, P<0.05) and enhanced splenic lymphocyte proliferation ( P<0.05). CPCD also significantly up-regulated the expression of CD4 + [(41.97±4.58)% vs (25.43±1.48)%, P<0.05], CD8 + [(12.67±0.33)% vs (9.02±1.07)%, P<0.05], CD4 + CD44 + [(11.77±0.69)% vs (8.64±0.71)%, P<0.05] and CD8 + CD44 + [(6.70±0.67)% vs (4.66±0.39)%, P<0.05] T cell subsets as well as the secretion of IFN-γ in CD4 + [(1.36±0.07)% vs (0.87±0.06)%, P<0.05] and CD8 + [(2.09±0.20)% vs (1.42±0.08)%, P<0.05] T cells. In addition, there was no significant difference between CPCD combined with low-dose IVV group and high-dose IVV alone group ( P>0.05), implying a 10-fold antigen sparing. Conclusions:CPCD, as an adjuvant for influenza virus vaccine, could enhance humoral and cellular immune responses and reduce antigen dose, which might be a potential adjuvant for seasonal or pandemic influenza vaccines.

OBJECTIVES: Since the outbreak of coronavirus disease 2019 (COVID-19), it has spread rapidly in China and many other countries. The rapid increase in the number of cases has caused widespread panic among people and has become the main public health problem in the world. Severe patients often have difficult breathing and/or hypoxemia after 1 week of onset. A few critically ill patients may not only rapidly develop into acute respiratory distress syndrome, but also may cause coagulopathy, as well as multiple organs failure (such as heart, liver and kidney) or even death. This article is to analyze the predictive role of clinical features in patients with COVID-19 for severe disease, so as to help doctor monitor the severity-related features, restrain the disease progress, and provide a reference for improvement of medical treatment. METHODS: The clinical data of 208 patients with COVID-19 who were isolated and treated in Changsha Public Health Treatment Center from January 17, 2020 to March 14, 2020 were collected. All patients were the mild and ordinary adult patients on admission, including 105 males and 103 females from 19 to 84 (median age 44) years old. According to the "Program for the diagnosis and treatment of novel coronavirus (COVID-19) infected pneumonia (Trial version 7)" issued by the General Office of National Health Committee and Office of State Administration of Traditional Chinese Medicine as the diagnostic and typing criteria. According to progression from mild to severe disease during hospitalization, the patients were divided into a mild group (=183) and a severe transformation group (=25). The clinical features such as age, underlying disease, blood routine, coagulation function, blood biochemistry, oxygenation index, and so on were analyzed. Among them, laboratory tests included white blood cell (WBC), lymphocytes (LYM), neutrophil (NEU), hemoglobin (Hb), platelet (PLT), prothrombin time (PT), plasma fibrinogen (Fib), activated partial prothrombin time (APTT), thrombin time (TT), -dimer, total bilirubin (TBIL), albumin (ALB), alanine aminotransferase (ALT), aspartate aminotransferase (AST), blood urea nitrogen (BUN), serum creatinine (Cr), creatine kinase (CK), creatine kinase isoenzyme-MB (CK-MB), lactate dehydrogenase (LDH), C-reactive protein (CRP), and oxygen partial pressure in arterial blood. Partial pressure of oxygen in arterial blood/fractional concentration of inspiratory oxygen (PaO/FiO) was calculated. The variables with statistical significance were analyzed by logistic regression analysis. RESULTS: Patients in the severe transformation group had more combined underlying diseases than those in the mild group (<0.05). From the perspective of disease distribution, patients in the severe transformation group had more combined hypertension (<0.05). In the severe transformation group, PT was significantly longer, the levels of Fib, ALT, AST, CK, LDH, and CRP were significantly higher than those in the mild group (<0.05 or <0.001), while LYM, ALB, and PaO/FiO were significantly lower than those in the mild group (<0.05 or <0.001). Logistic regression analysis was performed on clinical features with statistically significant differences. Combined with hypertension, LYM, PT, Fib, ALB, ALT, AST, CK, LDH, and CRP as independent variables, and having severe disease or not was the dependent variable. The results show that combined hypertension, decreased LYM, longer PT, and increased CK level were independent risk factors that affected the severity of COVID-19 (<0.05). CONCLUSIONS The patients with mild COVID-19 who are apt to develop severe diseases may be related to combined hypertension, decreased LYM, and longer PT, and increased CK level. For the mild patients with these clinical features, early intervention may effectively prevent the progression to severe diseases.
Adult ; Aged ; Aged, 80 and over ; Betacoronavirus ; China ; Coronavirus Infections ; diagnosis ; physiopathology ; Disease Progression ; Female ; Hospitalization ; Humans ; Male ; Middle Aged ; Pandemics ; Pneumonia, Viral ; diagnosis ; physiopathology ; Retrospective Studies ; Young Adult

Objective: To investigate the enhancement effect of Xinjiang wild Artemisia rupestris L. crude polysaccharides (WARCP) as an adjuvant on ovalbumin (OVA) vaccine in mice immunized intramuscularly. Methods: ICR mice were randomly divided into 6 groups (5 per group), including 9 g/L NaCl group (blank control), OVA group (10 μg OVA), low dose WARCP/OVA group (OVA+50 μg WARCP), medium dose WARCP/OVA group (OVA+200 μg WARCP), high dose WARCP/OVA group (OVA+400 μg WARCP), and aluminum adjuvant (Alum)/OVA group (positive control group, OVA+100 μg Alum). ICR mice were immunized intramuscularly and weighted. The OVA-specific antibodies and subtypes in serum were detected by enzyme linked immunosorbent assay (ELISA). T cells subsets from spleen and lymph nodes were detected by flow cytometry. Results: The medium-dose WARCP/OVA group enhanced IgG and IgG1 levels and increased early antibody levels (all P<0.05). The medium-dose WARCP/OVA group and the high-dose WARCP/OVA group significantly enhanced IgG2a levels (all P<0.05), but the difference was not statistically significant comparing with Alum/OVA group (P>0.05). The low-dose WARCP/OVA group enhanced the percentage of CD4⁺ T cells in spleen and CD4⁺ T, CD8⁺ T, CD4⁺CD44⁺ T cells in lymph nodes (all P<0.05). The medium dose WARCP/OVA group and the high dose WARCP/OVA group enhanced the CD4⁺ T, CD8⁺ T, CD4⁺CD44⁺ T, CD8⁺CD44⁺ T cells in spleen and CD8⁺CD44⁺ T cell in lymph nodes (all P<0.05). Conclusions Plant-derived WARCP as an OVA protein vaccine adjuvant can enhance cellular immunity and humoral immunity, and it is safe and reliable. The results in this study provide a theoretical basis for the popularization and application of WARCP.

To promote the development of the domestic community mental health services, this paper introduced several foreign studies on the competencies of community mental health service providers of different professional backgrounds. The studies examined by this article inquire into the core competencies of community mental health service providers working with people of psychiatric disabilities, the core competencies of psychiatrists providing integrated care in the community setting, the competencies of psychologists in community mental health service, and the competency level of community mental health service providers in intervention activities. Drawing on foreign experience and strengthening cooperation among community mental health service providers of different professional backgrounds, and achieving complementary advantages, will help to promote service effectiveness.

Objective To investigate the impact of deep machine learning Pixel Shine (PS) algorithm on image quality of abdominal low-dose plain CT scanning in BMI≥25 kg/m2 patients.Methods A total of 59 patients (BMI≥25 kg/m2) who underwent abdominal CT scan were collected.The patients were divided into group A (100 kVp,n=30) and B (120 kVp,n=29) according to the tube voltage.According to different reconstruction algorithms and treatment methods,patients in group A were divided into A1 (FBP),A2 (FBP+PS),A3 (50％ASiR-V) and A4 (50％ASiR-V+PS) subgroups,while in group B were divided into B1 (FBP) and B2 (50％ASiR-V) subgroups.CT and SD values of right hepatic lobe and right erector spinae were measured,then SNR and CNR of liver and CT dose index of volume (CTDIvol) were calculated.The consistency of parameters measured by two observers was evaluated.Results The consistency of parameters measured by two observers was good (all ICC＞0.80).There was no statistical difference of CT values of liver and erector among A1-A4 subgroups (all P＞0.05),whereas statistical differences of SD values of liver and erector spinae,also of SNR and CNR of liver were found (all P＜0.001).Among A1-A4 subgroups,SDA4 ＜SDA2 ＜SDA3 ＜SDA1,SNRA4 ＞SNRA2 ＞SNRA3 ＞ SNRA1 (all P＜0.001) was observed.There was no significant difference of CNR between A1 and A3 subgroup (P=0.078),while CNRA4＞ CNRA2＞ CNRA3 or CNRA1 (P＜0.001) was noticed.SD values of the liver in subgroup A2 was lower than subgroup B1,and A4 was lower than B2 subgroup (all P＜0.001),and SNR and CNR increased significantly in A2 and A4 subgroups (all P＜0.001).CTDIvol of group A was lower than that of group B (P＜0.001).Conclusion Deep machine learning PS algorithm can improve image quality of abdominal low-dose plain CT scanning in high-BMI patients.

Objective To compare the immunopotentiating effects of polysaccharides extracted from wild/cultivate Cistanehe deserticola (WCDPS/CCDPS) in Xinjiang. Methods ICR mice were subcu-taneously injected twice with different doses(low,medium and high) of WCDPS and CCDPS in combination with ovalbumin (OVA). OVA-specific antibody IgG,as well as IgG1 and IgG2a subtypes, was determined by ELISA. OVA-specific lymphocyte proliferation was measured by MTT. Expression of CD4+T and CD8+T cells was analyzed by flow cytometry. Results Both WCDPS and CCDPS could significantly improve the production of OVA-specific IgG,IgG1 and IgG2a,promote the proliferation of OVA-specific lymphocytes and increase the expression of CD4+T and CD8+T cells(all P<0.05) with no significant difference between them at the same dosages (P>0.05). WCDPS and CCDPS had no influence on the body weight of mice after im-munization. Conclusion WCDSP and CCDPS could significantly enhance the OVA-specific humoral and cellular immune responses with no statistical difference and are characterized by high safety.