The real-time remote testing and programming of cardiac implantable electronic devices: A case series report.

Minimizing the number of personnel in the cardiac catheterization laboratory (CCL) and the times of CCL door openings contribute to reduce the infection risk of medical staff and patients, particularly during the COVID-19 pandemic. The usage of 5G-CTP system enables device specialists to conduct remote parameter testing and programming without entering the CCL, potentially reducing the exposure risk of medical staff and patients to COVID-19 infection.

Application of Postoperative Remote Follow-Up of CIED Based on the 5G Cloud Technology Support Platform in Areas With Underdeveloped Medical Resources.

Postoperative follow-up is crucial for the clinical management of patients carrying cardiovascular implantable electronic devices (CIED). However, in a plethora of underdeveloped areas of China, due to limited medical resources and associated economic costs, geographical restrictions, the outbreak of the COVID-19 pandemic, and various other reasons, the medical system is unable to meet the ever-increasing demand for long-term clinical follow-up and telemedicine services. Based on these challenges, postoperative remote follow-up of CIED based on the 5G-cloud technology support platform (5G-CTP) may have the potential to optimize the allocation of medical resources and provide patients with high-quality CIED follow-up services locally. These unique characteristics of CIED follow-up utilizing 5G-CTP are qualified to protect the safety of the patients in terms of both clinical safety and cyber security. Furthermore, during the COVID-19 pandemic, remote follow-up of CIED significantly reduces the risk of viral exposure to patients and medical staff while having the potential to improve the current situation of CIED postoperative follow-up.

HiFuse: Hierarchical Multi-Scale Feature Fusion Network for Medical Image Classification (preprint)

Medical image classification has developed rapidly under the impetus of the convolutional neural network (CNN). Due to the fixed size of the receptive field of the convolution kernel, it is difficult to capture the global features of medical images. Although the self-attention-based Transformer can model long-range dependencies, it has high computational complexity and lacks local inductive bias. Much research has demonstrated that global and local features are crucial for image classification. However, medical images have a lot of noisy, scattered features, intra-class variation, and inter-class similarities. This paper proposes a three-branch hierarchical multi-scale feature fusion network structure termed as HiFuse for medical image classification as a new method. It can fuse the advantages of Transformer and CNN from multi-scale hierarchies without destroying the respective modeling so as to improve the classification accuracy of various medical images. A parallel hierarchy of local and global feature blocks is designed to efficiently extract local features and global representations at various semantic scales, with the flexibility to model at different scales and linear computational complexity relevant to image size. Moreover, an adaptive hierarchical feature fusion block (HFF block) is designed to utilize the features obtained at different hierarchical levels comprehensively. The HFF block contains spatial attention, channel attention, residual inverted MLP, and shortcut to adaptively fuse semantic information between various scale features of each branch. The accuracy of our proposed model on the ISIC2018 dataset is 7.6% higher than baseline, 21.5% on the Covid-19 dataset, and 10.4% on the Kvasir dataset. Compared with other advanced models, the HiFuse model performs the best. Our code is open-source and available from https://github.com/huoxiangzuo/HiFuse.

Application of Postoperative Remote Follow-Up of CIED Based on the 5G Cloud Technology Support Platform in Areas With Underdeveloped Medical Resources

Postoperative follow-up is crucial for the clinical management of patients carrying cardiovascular implantable electronic devices (CIED). However, in a plethora of underdeveloped areas of China, due to limited medical resources and associated economic costs, geographical restrictions, the outbreak of the COVID-19 pandemic, and various other reasons, the medical system is unable to meet the ever-increasing demand for long-term clinical follow-up and telemedicine services. Based on these challenges, postoperative remote follow-up of CIED based on the 5G-cloud technology support platform (5G-CTP) may have the potential to optimize the allocation of medical resources and provide patients with high-quality CIED follow-up services locally. These unique characteristics of CIED follow-up utilizing 5G-CTP are qualified to protect the safety of the patients in terms of both clinical safety and cyber security. Furthermore, during the COVID-19 pandemic, remote follow-up of CIED significantly reduces the risk of viral exposure to patients and medical staff while having the potential to improve the current situation of CIED postoperative follow-up.

Matrix Kendall's tau in High-dimensions: A Robust Statistic for Matrix Factor Model (preprint)

In this article, we first propose generalized row/column matrix Kendall's tau for matrix-variate observations that are ubiquitous in areas such as finance and medical imaging. For a random matrix following a matrix-variate elliptically contoured distribution, we show that the eigenspaces of the proposed row/column matrix Kendall's tau coincide with those of the row/column scatter matrix respectively, with the same descending order of the eigenvalues. We perform eigenvalue decomposition to the generalized row/column matrix Kendall's tau for recovering the loading spaces of the matrix factor model. We also propose to estimate the pair of the factor numbers by exploiting the eigenvalue-ratios of the row/column matrix Kendall's tau. Theoretically, we derive the convergence rates of the estimators for loading spaces, factor scores and common components, and prove the consistency of the estimators for the factor numbers without any moment constraints on the idiosyncratic errors. Thorough simulation studies are conducted to show the higher degree of robustness of the proposed estimators over the existing ones. Analysis of a financial dataset of asset returns and a medical imaging dataset associated with COVID-19 illustrate the empirical usefulness of the proposed method.

Neutralizing Antibodies and Cellular Immune Responses Against SARS-CoV-2 Sustained One and a Half Years After Natural Infection.

Background: COVID-19 has caused more than 2.6 billion infections and several million deaths since its outbreak 2 years ago. We know very little about the long-term cellular immune responses and the kinetics of neutralizing antibodies (NAbs) to SARS-CoV-2 because it has emerged only recently in the human population. Methods: We collected blood samples from individuals who were from the first wave of the COVID-19 epidemic in Wuhan between December 30, 2019, and February 24, 2020. We analyzed NAbs to SARS-CoV-2 using pseudoviruses and IgG antibodies to SARS-CoV-2 spike (S) and nucleocapsid (N) protein using enzyme-linked immunosorbent assay in patients' sera and determined SARS-CoV-2-specific T-cell responses of patients with ELISpot assays. Results: We found that 91.9% (57/62) and 88.9% (40/45) of COVID-19 patients had NAbs against SARS-CoV-2 in a year (10-11 months) and one and a half years (17-18 months), respectively, after the onset of illness, indicating that NAbs against SARS-CoV-2 waned slowly and possibly persisted over a long period time. Over 80% of patients had IgG antibodies to SARS-CoV-2 S and N protein one and a half years after illness onset. Most patients also had robust memory T-cell responses against SARS-CoV-2 one and a half years after the illness. Among the patients, 95.6% (43/45) had an IFN-γ-secreting T-cell response and 93.8% (15/16) had an IL-2-secreting T-cell response. The T-cell responses to SARS-CoV-2 were positively correlated with antibodies (including neutralizing antibodies and IgG antibodies to S and N protein) in COVID-19 patients. Eighty percent (4/5) of neutralizing antibody-negative patients also had SARS-CoV-2-specific T-cell response. After long-term infection, protective immunity was independent of disease severity, sex, and age. Conclusions: We concluded that SARS-CoV-2 infection elicited a robust and persistent neutralizing antibody and memory T-cell response in COVID-19 patients, indicating that these sustained immune responses, among most SARS-CoV-2-infected people, may play a crucial role in protection against reinfection.

The Mental Health Status and Associated Factors Among Medical Students Engaged in Online Learning at Home During the Pandemic: A Cross-Sectional Study From China

Background: The purpose of this study was to assess the mental health status of medical students engaged in online learning at home during the pandemic, and explore the potential risk factors of mental health. Methods: A cross-sectional study was conducted via an online survey among 5,100 medical students from Wannan Medical College in China. The Depression, Anxiety and Stress scale (DASS-21) was used to measure self-reported symptoms of depression, anxiety, and stress among medical students during online learning in the pandemic. Results: In total, 4,115 participants were included in the study. The prevalence symptoms of depression, anxiety, and stress were 31.9, 32.9, and 14.6%, respectively. Depression was associated with gender, grade, length of schooling, relationship with father, students' daily online learning time, and students' satisfaction with online learning effects. Anxiety was associated with gender, length of schooling, relationship with father, relationship between parents, students' daily online learning time, and students' satisfaction with online learning effects. Stress was associated with grade, relationship with father, relationship between parents, students' daily online learning time, and students' satisfaction with online learning effects. Conclusions: Nearly one-third of medical students survived with varying degrees of depression, anxiety, and stress symptoms during online learning of the COVID-19 pandemic. Gender, grade, length of schooling, family environment, and online learning environment play vital roles in medical students' mental health. Families and schools should provide targeted psychological counseling to high-risk students (male, second-year and third-year, four-year program). The findings of this study can provide reference for educators to cope with the psychological problems and formulate the mental health curriculum construction among medical students during online learning.

Duration of SARS-CoV-2 RNA shedding and factors associated with prolonged viral shedding in patients with COVID-19.

To investigate the factors associated with the duration of severe acute respiratory syndrome coronavirus 2 RNA shedding in patients with coronavirus disease 2019 (COVID-19). A retrospective cohort of COVID-19 patients admitted to a designated hospital in Beijing was analyzed to study the factors affecting the duration of viral shedding. The median duration of viral shedding was 11 days (IQR, 8-14.3 days) as measured from illness onset. Univariate regression analysis showed that disease severity, corticosteroid therapy, fever (temperature>38.5°C), and time from onset to hospitalization were associated with prolonged duration of viral shedding (P < .05). Multivariate regression analysis showed that fever (temperature>38.5°C) (OR, 5.1, 95%CI: 1.5-18.1), corticosteroid therapy (OR, 6.3, 95%CI: 1.5-27.8), and time from onset to hospitalization (OR, 1.8, 95%CI: 1.19-2.7) were associated with increased odds of prolonged duration of viral shedding. Corticosteroid treatment, fever (temperature>38.5°C), and longer time from onset to hospitalization were associated with prolonged viral shedding in COVID-19 patients.

Expert consensus on the safety prevention and control of nuclear medicine diagnosis and treatment during the outbreak of COVID-19 (1st edition): (translated from Chinese version).

In December 2019, an infectious disease caused by a new type of coronavirus infection was prevalent in Wuhan and across the country. On January 20, 2020, the National Health Commission of the People's Republic of China issued No.1 Announcement, which incorporated the novel coronavirus pneumonia into the Class B infectious disease according to the Law on Prevention and Control of Infectious Disease, but the disease should be adopted in the management of Class A infectious disease. In order to effectively control the source of infection, cut off the transmission route, protect the susceptible population, ensure the medical quality and medical safety, perform epidemic prevention and control, and comprehensively guarantee the life safety and physical health of medical staff, patients, and family members, it is very important to organize and carry out nuclear medicine diagnosis and treatment scientifically and safely. According to the national prevention and control policy, Chinese Society of Nuclear Medicine and editorial board of the Chinese Journal of Nuclear Medicine and Molecular Imaging organized professionals to formulate the expert consensus on the safety prevention process of nuclear medicine imaging and nuclide therapy during the period of new coronavirus infection.

Persistent SARS-CoV-2 presence is companied with defects in adaptive immune system in non-severe COVID-19 patients (preprint)

Background: COVID-19 has been widely spreading. We aim to examine adaptive immune cells in non-severe patients with persistent SARS-CoV-2 shedding. Methods 37 non-severe patients with persistent SARS-CoV-2 presence transferred to Zhongnan hospital of Wuhan University were retrospectively recruited to PP (persistently positive) group, which was further allocated to PPP group (n=19) and PPN group (n=18), according to their testing results after 7 days (N=negative). Epidemiological, demographic, clinical and laboratory data were collected and analyzed. Data from age- and sex-matched non-severe patients at disease onset (PA [positive on admission] patients, n=37), and lymphocyte subpopulation measurements from matched 54 healthy subjects were extracted for comparison. Results Compared with PA patients, PP patients had much improved laboratory findings, including WBCs, neutrophils, lymphocytes, neutrophil-to-lymphocyte ratio, albumin, AST, CRP, SAA, and IL-6. The absolute numbers of CD3+ T cells, CD4+ T cells, and NK cells were significantly higher in PP group than that in PA group, and were comparable to that in healthy controls. PPP subgroup had markedly reduced B cells and T cells compared to PPN group and healthy subjects. Finally, paired results of these lymphocyte subpopulations from 10 PPN patients demonstrated that the number of T cells and B cells significantly increased when the SARS-CoV-2 tests turned negative. Conclusion Persistent SARS-CoV-2 presence in non-severe COVID-19 patients is associated with reduced numbers of adaptive immune cells. Monitoring lymphocyte subpopulations could be clinically meaningful in identifying fully recovered COVID-19 patients. Abbreviations COVID-19: Coronavirus disease 2019; SARS-CoV-2: Severe acute respiratory syndrome coronavirus 2; HC: Healthy controls.