Care patterns and Traditional Chinese Medicine constitution as factors of depression and anxiety in patients with systemic sclerosis: A cross-sectional study during the COVID-19 pandemic.

Objective: Care patterns and Traditional Chinese Medicine (TCM) constitution affects the emotion and health of patients with systemic sclerosis (SSc) while the prevalence of COVID-19 may aggravate such patients' emotion and health. We investigated the depression and anxiety levels of patients with SSc during the pandemic to identify the correlation between care patterns, TCM constitution, and patients' emotion. Materials and methods: This was a cross-sectional study. Patients with SSc and healthy individuals were surveyed using the patient health questionnaire-9, generalized anxiety disorder-7, and constitution in Chinese medicine questionnaire and a modified care pattern questionnaire. Factors correlated with depression and anxiety were screened using univariate and multivariate logistic regression analyses. Results: A total of 273 patients with SSc and 111 healthy individuals were included in the analysis. The proportion of patients with SSc who were depressed was 74.36%, who had anxiety was 51.65%, and who experienced disease progression during the pandemic was 36.99%. The proportion of income reduction in the online group (56.19%) was higher than that in the hospital group (33.33%) (P = 0.001). Qi-deficiency [adjusted odds ratio (OR) = 2.250] and Qi-stagnation (adjusted OR = 3.824) constitutions were significantly associated with depression. Remote work during the outbreak (adjusted OR = 1.920), decrease in income (adjusted OR = 3.556), and disease progression (P = 0.030) were associated with the occurrence of depression. Conclusion: Chinese patients with SSc have a high prevalence of depression and anxiety. The COVID-19 pandemic has changed the care patterns of Chinese patients with SSc, and work, income, disease progression, and change of medications were correlates of depression or anxiety in patients with SSc. Qi-stagnation and Qi-deficiency constitutions were associated with depression, and Qi-stagnation constitution was associated with anxiety in patients with SSc. Trial registration: http://www.chictr.org.cn/showproj.aspx?proj=62301, identifier ChiCTR2000038796.

Recent developments in the immunopathology of COVID-19.

There has been an important change in the clinical characteristics and immune profile of Coronavirus disease 2019 (COVID-19) patients during the pandemic thanks to the extensive vaccination programs. Here, we highlight recent studies on COVID-19, from the clinical and immunological characteristics to the protective and risk factors for severity and mortality of COVID-19. The efficacy of the COVID-19 vaccines and potential allergic reactions after administration are also discussed. The occurrence of new variants of concerns such as Omicron BA.2, BA.4, and BA.5 and the global administration of COVID-19 vaccines have changed the clinical scenario of COVID-19. Multisystem inflammatory syndrome in children (MIS-C) may cause severe and heterogeneous disease but with a lower mortality rate. Perturbations in immunity of T cells, B cells, and mast cells, as well as autoantibodies and metabolic reprogramming may contribute to the long-term symptoms of COVID-19. There is conflicting evidence about whether atopic diseases, such as allergic asthma and rhinitis, are associated with a lower susceptibility and better outcomes of COVID-19. At the beginning of pandemic, the European Academy of Allergy and Clinical Immunology (EAACI) developed guidelines that provided timely information for the management of allergic diseases and preventive measures to reduce transmission in the allergic clinics. The global distribution of COVID-19 vaccines and emerging severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants with reduced pathogenic potential dramatically decreased the morbidity, severity, and mortality of COVID-19. Nevertheless, breakthrough infection remains a challenge for disease control. Hypersensitivity reactions (HSR) to COVID-19 vaccines are low compared to other vaccines, and these were addressed in EAACI statements that provided indications for the management of allergic reactions, including anaphylaxis to COVID-19 vaccines. We have gained a depth knowledge and experience in the over 2 years since the start of the pandemic, and yet a full eradication of SARS-CoV-2 is not on the horizon. Novel strategies are warranted to prevent severe disease in high-risk groups, the development of MIS-C and long COVID-19.

Controlling effect of TiO2 carrier on formed vanadium species for effective catalytic oxidization of chlorobenzene

Catalytic oxidization of the dioxins is critical to the atmosphere since medical-waste incineration is globally increased due to COVID-19. Vanadium supported TiO2 is the most-widely investigated catalyst. However, previous reports usually investigated V-Ti relationships after vanadate was loaded on TiO2 and an activation was completed. In comparison, this work emphasizes on the influence of TiO2 surface chemistries on properties of formed vanadium species during a thermal activation. The vanadate loaded TiO2 are detailedly analyzed by both experimental characterizations and theoretical calculations. As a result, TiO2 with more Ti4+ is inclined to be reductive, and promotes the formation of more low-valence vanadium and surface vacancies. On the contrary, TiO2 with more Ti3+ is inclined to be oxidative, and promotes the formation of more lattice oxygens and high-valence vanadium. When they were compared in catalytic oxidization of chlorobenzene, the Ti4+-induced catalyst attains a conversion of 98.0 % at 250 °C, far bigger than that (11.3 %) of the Ti3+-induced catalyst. The main result of this work helps readers to understand the process of the catalyst preparation, which is in favor of producing a more effective catalyst by regulating the catalyst carrier.

Recent developments in the immunopathology of COVID-19 (preprint)

There has been an important change in the clinical characteristics and immune profile of COVID-19 patients during the pandemic thanks to the extensive vaccination programs. Here, we highlight recent studies on COVID-19, from the clinical and immunological characteristics to the protective and risk factors for severity and mortality of COVID-19. The efficacy COVID-19 vaccines and potential allergic reactions after administration are also discussed. The occurrence of new variants of concerns such as Omicron BA.2, BA.4 and BA.5 and the global administration of COVID-19 vaccines have changed the clinical scenario of COVID-19. Multisystem inflammatory syndrome in children (MIS-C) has been identified as an important cause of death of children with COVID-19. Perturbations in immunity of T cells, B cells, and mast cells, as well as autoantibodies and metabolic reprogramming may contribute to the long-term symptoms of COVID-19. Atopic diseases, such as allergic asthma and rhinitis, have been shown to be associated with a lower susceptibility and better outcomes of COVID-19. At the beginning of pandemic, EAACI developed guidelines that provided timely information for the management of allergic diseases and preventive measures to reduce transmission in the allergic clinics. The global distribution of COVID-19 vaccines and emerging SARS-CoV-2 variants with reduced pathogenic potential dramatically decreased the morbidity, severity, and mortality of COVID-19. Nevertheless, breakthrough infection remains a challenge for disease control. Hypersensitivity reactions (HSR) to COVID-19 vaccines are low compared to other vaccines, and these were addressed in EAACI statements that provided indications for the management of allergic reactions, including anaphylaxis to COVID-19 vaccines. We have gained a depth knowledge and experience in the over 2 years since the start of the pandemic, and yet a full eradication of SARS-CoV-2 is not on the horizon. Novel strategies are warranted to prevent severe disease in high-risk groups, the development of MIS-C and long COVID.

Care patterns and TCM constitution as factors of depression and anxiety in systemic scleroderma: a cross- sectional study during the COVID-19 pandemic (preprint)

Background: Care patterns and TCM constitution affects systemic scleroderma (SSc) patients’ emotion and health while the prevalence of covid-19 may aggravate this situation. Thus, we investigated depression and anxiety level in SSc patients during the COVID-19 pandemic to identify the correlation between care patterns, TCM constitution and patients' emotion. Methods: This was a cross-sectional study. SSc patients and healthy individuals were surveyed through the Patient Health Questionnaire-9, Generalized Anxiety Disorder-7, the Constitution in Chinese Medicine Questionnaire and a modified care pattern questionnaire. Factors correlated with depression and anxiety were screened by univariate and multivariate logistic regression. Results: A total of 273 SSc patients and 111 healthy individuals were included. The median age was 45 years in both patient and healthy groups. 74.36% of SSc patients were in depression and 51.65% were in anxiety. 69.60% worked remotely and 50.92% experienced a decrease in income, which were both higher than in the healthy group (38.74%, 29.73%). The proportion of income reduction in the online group (56.19%) was higher than that in the hospital group (33.33%) (P = 0.001). 36.99% of SSc patients had disease progression during the pandemic. Yang-deficiency constitution (82.05%) was the TCM constitution characteristic of SSc patients, while Qi-deficiency(73.63%) and Blood-stasis constitution (57.14%) were also more common. TCM constitution of patients from different sources distributed roughly similar. Qi-deficiency (adjusted OR=2.250) and Qi-stagnation (adjusted OR= 3.824) constitution were significantly associated with depression. The major constitution of dampness-heat was associated with a decrease in depression (adjusted OR=0.160). Remote work during the outbreak (adjusted OR= 1.920), decreasing in income (adjusted OR=3.556), and disease progression (P=0.030) were associated with the occurrence of depression. Conclusion: Chinese SSc patients have a high prevalence of depression and anxiety. The COVID-19 pandemic has changed the care patterns of Chinese SSc patients in terms of work, income, and ways of getting medical support. Within the care patterns, work, income, disease and change of medications were correlates of depression or anxiety in SSc patients. Qi-stagnation and Qi-deficiency constitution were associated with depression, and Qi-stagnation constitution was associated with anxiety in SSc patients. Further research is needed. Trial registration: ChiCTR, ChiCTR2000038796, Registered 02 October 2020, http://www.chictr.org.cn/showproj.aspx?proj=62301

Assisting scalable diagnosis automatically via CT images in the combat against COVID-19.

The pandemic of Coronavirus Disease 2019 (COVID-19) is causing enormous loss of life globally. Prompt case identification is critical. The reference method is the real-time reverse transcription PCR (RT-PCR) assay, whose limitations may curb its prompt large-scale application. COVID-19 manifests with chest computed tomography (CT) abnormalities, some even before the onset of symptoms. We tested the hypothesis that the application of deep learning (DL) to 3D CT images could help identify COVID-19 infections. Using data from 920 COVID-19 and 1,073 non-COVID-19 pneumonia patients, we developed a modified DenseNet-264 model, COVIDNet, to classify CT images to either class. When tested on an independent set of 233 COVID-19 and 289 non-COVID-19 pneumonia patients, COVIDNet achieved an accuracy rate of 94.3% and an area under the curve of 0.98. As of March 23, 2020, the COVIDNet system had been used 11,966 times with a sensitivity of 91.12% and a specificity of 88.50% in six hospitals with PCR confirmation. Application of DL to CT images may improve both efficiency and capacity of case detection and long-term surveillance.

COVIDPEN: A Novel COVID-19 Detection Model using Chest X-Rays and CT Scans (preprint)

The trending global pandemic of COVID-19 is the fastest ever impact which caused people worldwide by severe acute respiratory syndrome~(SARS)-driven coronavirus. However, several countries suffer from the shortage of test kits and high false negative rate in PCR test. Enhancing the chest X-ray or CT detection rate becomes critical. The patient triage is of utmost importance and the use of machine learning can drive the diagnosis of chest X-ray or CT image by identifying COVID-19 cases. To tackle this problem, we propose~COVIDPEN~-~a transfer learning approach on Pruned EfficientNet-based model for the detection of COVID-19 cases. The proposed model is further interpolated by post-hoc analysis for the explainability of the predictions. The effectiveness of our proposed model is demonstrated on two systematic datasets of chest radiographs and computed tomography scans. Experimental results with several baseline comparisons show that our method is on par and confers clinically explicable instances, which are meant for healthcare providers.