Search

Background: Allergic rhinitis is a common health concern that affects quality of life. This study aims to examine the online search trends of allergic rhinitis in China before and after the COVID-19 epidemic and to explore the association between the daily air quality and online search volumes of allergic rhinitis in Beijing., Methods: We extracted the online search data of allergic rhinitis-related keywords from the Baidu index database from January 23, 2017 to June 23, 2022. We analyzed and compared the temporal distribution of online search behaviors across different themes of allergic rhinitis before and after the COVID-19 pandemic in mainland China, using the Baidu search index (BSI). We also obtained the air quality index (AQI) data in Beijing and assessed its correlation with daily BSIs of allergic rhinitis., Results: The online search for allergic rhinitis in China showed significant seasonal variations, with two peaks each year in spring from March to May and autumn from August and October. The BSI of total allergic rhinitis-related searches increased gradually from 2017 to 2019, reaching a peak in April 2019, and declined after the COVID-19 pandemic, especially in the first half of 2020. The BSI for all allergic rhinitis themes was significantly lower after the COVID-19 pandemic than before (all p values < 0.05). The results also revealed that, in Beijing, there was a significant negative association between daily BSI and AQI for each allergic rhinitis theme during the original variant strain epidemic period and a significant positive correlation during the Omicron variant period., Conclusion: Both air quality and the interventions used for COVID-19 pandemic, including national and local quarantines and mask wearing behaviors, may have affected the incidence and public concern about allergic rhinitis in China. The online search trends can serve as a valuable tool for tracking real-time public concerns about allergic rhinitis. By complementing traditional disease monitoring systems of health departments, these search trends can also offer insights into the patterns of disease outbreaks. Additionally, they can provide references and suggestions regarding the public's knowledge demands related to allergic rhinitis, which can further be instrumental in developing targeted strategies to enhance population-based disease education on allergic diseases., (© 2024. The Author(s).)

Mitophagy, a central process guarding mitochondrial quality, is commonly impaired in human diseases such as Parkinson's disease, but its impact in adaptive immunity remains unclear. The differentiation and survival of memory CD8 + T cells rely on oxidative metabolism, a process that requires robust mitochondrial quality control. Here, we found that Parkinson's disease patients have a reduced frequency of CD8 + memory T cells compared with healthy donors and failed to form memory T cells upon vaccination against COVID-19, highlighting the importance of mitochondrial quality control for memory CD8 + T cell formation. We further uncovered that regulators of mitophagy, including Parkin and NIX, were up-regulated in response to interleukin-15 (IL-15) for supporting memory T cell formation. Mechanistically, Parkin suppressed VDAC1-dependent apoptosis in memory T cells. In contrast, NIX expression in T cells counteracted ferroptosis by preventing metabolic dysfunction resulting from impaired mitophagy. Together, our results indicate that the mitophagy machinery orchestrates survival and metabolic dynamics required for memory T cell formation, as well as highlight a deficit in T cell-mediated antiviral responses in Parkinson's disease patients.

Purpose: To investigate information-seeking behavior related to urticaria before and during the COVID-19 pandemic in China., Methods: Search query data for terms related to urticaria were retrieved using Baidu Index database from October 23, 2017 to April 23, 2022, and daily COVID-19 vaccination doses data were obtained from the website of the Chinese Center for Disease Control and Prevention. Among the 23 eligible urticaria search terms, four urticaria themes were generated as classification, symptom, etiology, and treatment of urticarial, respectively. Baidu Search Index (BSI) value for each term were extracted to analyze and compare the spatial and temporal distribution of online search behavior for urticaria before and after the COVID-19 pandemic, and to also explore the correlation between search query and daily COVID-19 vaccination doses., Results: The classification of urticaria accounted for nearly half of the urticaria queries on the internet. Regular seasonal patterns of BSI were observed in urticaria-related online search, by attaining its highest level in spring and summer and lowest level in winter. The BSIs of all urticaria themes significantly increased after the COVID-19 pandemic than that before the pandemic (all P <0.05). Xizang, Qinghai and Ningxia are the most active geographical areas for increased urticaria-searching activities after the COVID-19 pandemic. There was also a significant positive correlation between daily BSIs and daily COVID-19 vaccination doses in each urticaria theme. Cross-correlation analysis found that the search of symptom, etiology, and treatment attained their strongest correlation with daily COVID-19 vaccination doses at 11-27 days before the injection of vaccine, imply vaccination hesitation related to concerns of urticaria., Conclusions: This study used the internet as a proxy to provide evidence of public search interest and spatiotemporal characteristics of urticaria, and revealed that the search behavior of urticaria have increased significantly after the COVID-19 pandemic and COVID-19 vaccination. It is anticipated that the findings about such increase in search behavior, as well as the behavior of urticaria-related vaccine-hesitancy, will help guide public health education and policy regulation., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Zhang, Yu, He, Yao, He, Wu, Xu and Ye.)

The metabolic characteristics of COVID-19 disease are still largely unknown. Here, 44 patients with COVID-19 (31 mild COVID-19 patients and 13 severe COVID-19 patients), 42 healthy controls (HC), and 42 patients with community-acquired pneumonia (CAP), were involved in the study to assess their serum metabolomic profiles. We used widely targeted metabolomics based on an ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS). The differentially expressed metabolites in the plasma of mild and severe COVID-19 patients, CAP patients, and HC subjects were screened, and the main metabolic pathways involved were analyzed. Multiple mature machine learning algorithms confirmed that the metabolites performed excellently in discriminating COVID-19 groups from CAP and HC subjects, with an area under the curve (AUC) of 1. The specific dysregulation of AMP, dGMP, sn -glycero-3-phosphocholine, and carnitine was observed in the severe COVID-19 group. Moreover, random forest analysis suggested that these metabolites could discriminate between severe COVID-19 patients and mild COVID-19 patients, with an AUC of 0.921. This study may broaden our understanding of pathophysiological mechanisms of COVID-19 and may offer an experimental basis for developing novel treatment strategies against it., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Liu, Li, Lu, Yu, Zhang, Ke, Zhang and Li.)

Productive T cell responses to infection and cancer rely on coordinated metabolic reprogramming and epigenetic remodeling among the immune cells. In particular, T cell effector and memory differentiation, exhaustion, and senescence/aging are tightly regulated by the metabolism-epigenetics axis. In this review, we summarize recent advances of how metabolic circuits combined with epigenetic changes dictate T cell fate decisions and shape their functional states. We also discuss how the metabolic-epigenetic axis orchestrates T cell exhaustion and explore how physiological factors, such as diet, gut microbiota, and the circadian clock, are integrated in shaping T cell epigenetic modifications and functionality. Furthermore, we summarize key features of the senescent/aged T cells and discuss how to ameliorate vaccination- and COVID-induced T cell dysfunctions by metabolic modulations. An in-depth understanding of the unexplored links between cellular metabolism and epigenetic modifications in various physiological or pathological contexts has the potential to uncover novel therapeutic strategies for fine-tuning T cell immunity., Competing Interests: Declaration of interests P.-C.H. received research grants from Elixron Immunotherapeutics and serves as scientific adviser for Elixiron Immunotherapeutics and Novartis., (Copyright © 2022 Elsevier Inc. All rights reserved.)

Numerous studies have suggested that the titers of antibodies against SARS-CoV-2 are associated with the COVID-19 severity, however, the types of antibodies associated with the disease maximum severity and the timing at which the associations are best observed, especially within one week after symptom onset, remain controversial. We attempted to elucidate the antibody responses against SARS-CoV-2 that are associated with the maximum severity of COVID-19 in the early phase of the disease, and to investigate whether antibody testing might contribute to prediction of the disease maximum severity in COVID-19 patients. We classified the patients into four groups according to the disease maximum severity (severity group 1 (did not require oxygen supplementation), severity group 2a (required oxygen supplementation at low flow rates), severity group 2b (required oxygen supplementation at relatively high flow rates), and severity group 3 (required mechanical ventilatory support)), and serially measured the titers of IgM, IgG, and IgA against the nucleocapsid protein, spike protein, and receptor-binding domain of SARS-CoV-2 until day 12 after symptom onset. The titers of all the measured antibody responses were higher in severity group 2b and 3, especially severity group 2b, as early as at one week after symptom onset. Addition of data obtained from antibody testing improved the ability of analysis models constructed using a machine learning technique to distinguish severity group 2b and 3 from severity group 1 and 2a. These models constructed with non-vaccinated COVID-19 patients could not be applied to the cases of breakthrough infections. These results suggest that antibody testing might help physicians identify non-vaccinated COVID-19 patients who are likely to require admission to an intensive care unit., Competing Interests: The present study was a collaborative research project among The University of Tokyo, Shenzhen YHLO Biotech Co., Ltd, and Medical & Biological Laboratories Co., Ltd. FX, FH, LZ, and YYu are employees of Shenzhen YHLO Biotech Co., Ltd and YK, JO, and HO are employees of Medical & Biological Laboratories Co., Ltd. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Kurano, Ohmiya, Kishi, Okada, Nakano, Yokoyama, Qian, Xia, He, Zheng, Yu, Jubishi, Okamoto, Moriya, Kodama and Yatomi.)

SARS-CoV-2 RNA is identified as a pivotal player to bolster energizing zones of COVID-19 detection. Herein, we develop a rapid and unamplified nanosensing platform for detection of SARS-CoV-2 RNA in human throat swab specimens. A gold nanoparticle (AuNP)-decorated graphene field-effect transistor (G-FET) sensor was fabricated, after which complementary phosphorodiamidate morpholino oligos (PMO) probe was immobilized on the AuNP surface. This sensor allowed for highly sensitive testing of SARS-CoV-2 RdRp as PMO does not have charges, leading to low background signal. Not only did the method present a low limit of detection in PBS (0.37 fM), throat swab (2.29 fM), and serum (3.99 fM), but also it achieved a rapid response to COVID-19 patients' samples within 2 min. The developed nanosensor was capable of analyzing RNA extracts from 30 real clinical samples. The results show that the sensor could differentiate the healthy people from infected people, which are in high agreement with RT-PCR results (Kappa index = 0.92). Furthermore, a well-defined distinction between SARS-CoV-2 RdRp and SARS-CoV RdRp was also made. Therefore, we believe that this work provides a satisfactory, attractive option for COVID-19 diagnosis., (Copyright © 2021 Elsevier B.V. All rights reserved.)

Context: Pioneering empirical studies show that people bereaved due to COVID-19 experience elevated acute grief, posttraumatic stress, anxiety, and depressive symptom levels, which relate to functional impairment. However, studies focused on Western samples and multivariate analyses of relations between potential risk factors and mental health in this population are lacking., Objectives: To assess the mental health of Chinese adults bereaved due to COVID-19. To elucidate the associations of demographic and loss-related characteristics with mental health after COVID-19 bereavement., Methods: Four hundred twenty-two Chinese adults (56% male; Mean age: 32.73 years) recently bereaved due to COVID-19 completed an online survey. Demographic and loss-related characteristics and prolonged grief, posttraumatic stress, anxiety, and depressive symptoms were assessed., Results: Clinically relevant prolonged grief (49%, n = 207), posttraumatic stress (22%, n = 92), depressive (70%; n = 294), and anxiety symptoms (65%; n = 272) were reported by a substantial group of participants. In four multiple regressions predicting each mental health indicator, Fs(15,406) = 5.08-7.74, Ps < 0.001, loss-characteristics (i.e., a shorter time since loss, βs =  -.12-.11, loss of a first-degree relative, βs =  .18-.37) and subjective loss experiences (i.e., feeling traumatized by the loss, βs =  .13-.18, or a close and/or conflictual relation with the deceased, βs =  .12-.23) related most consistently to mental health problems., Conclusion: Many Chinese adults bereaved due to COVID-19 experience severe mental health problems. The recent loss of first-degree relatives, feeling traumatized by the loss, and having a close and/or conflictual relationship with the deceased may elevate risk for these mental health problems, which could require indicated psychological treatment., (Copyright © 2021 American Academy of Hospice and Palliative Medicine. Published by Elsevier Inc. All rights reserved.)

Research into mRNA vaccines is advancing rapidly, with proven efficacy against coronavirus disease 2019 and promising therapeutic potential against a variety of solid tumors. Adjuvants, critical components of mRNA vaccines, significantly enhance vaccine effectiveness and are integral to numerous mRNA vaccine formulations. However, the development and selection of adjuvant platforms are still in their nascent stages, and the mechanisms of many adjuvants remain poorly understood. Additionally, the immunostimulatory capabilities of certain novel drug delivery systems (DDS) challenge the traditional definition of adjuvants, suggesting that a revision of this concept is necessary. This review offers a comprehensive exploration of the mechanisms and applications of adjuvants and self-adjuvant DDS. It thoroughly addresses existing issues mentioned above and details three main challenges of immune-related adverse event, unclear mechanisms, and unsatisfactory outcomes in old age group in the design and practical application of cancer mRNA vaccine adjuvants. Ultimately, this review proposes three optimization strategies which consists of exploring the mechanisms of adjuvant, optimizing DDS, and improving route of administration to improve effectiveness and application of adjuvants and self-adjuvant DDS. [ABSTRACT FROM AUTHOR]

In this paper, we explore what the travel restrictions during the COVID-19 pandemic reveal about the changing geographies of mobilities and the making of homo sacer, the latter constituted through differentiated control of mobilities. Implemented to protect U.S. public health, travel restrictions imposed on travelers from Mainland China during the early days of the pandemic exemplify how sovereign power that declares a state of emergency and creates bare life can be readily applied to groups of people who previously had privileged access to global mobility. In this sense, bare life does not refer to fixed and disadvantaged social categories but is rather contingently and contextually constituted, through the works of hybrid sovereign regimes. At the same time, however, these travelers are not reduced to a state of zero-agency but reside within a liminal space between soft and hard cosmopolitanisms, as they can still deploy agency and cosmopolitan capital to achieve certain degrees of mobility. By examining how Chinese travelers navigated various travel restrictions and the constantly changing policies to travel to the U.S., this paper explores new spaces of exception and forms of bare life, and argues that homo sacer is dynamically, relationally and recursively constructed, both through apparatus of control and the agency of travelers. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has radically expanded the role of algorithmic governance in everyday mobility. In China, urban and provincial governments have introduced health codes app as a national contract tracing and quarantine enforcement method to restrict the movements of "risky" individuals through malls, subways, railways, as well as between regions. Yet the health codes have been implemented with uneven efficacy and unexpected consequences. Drawing on glitch politics, we read these unintended consequences as "bugs" emerging from the introduction of platform-based management into everyday life. These bugs mediated individuals' lived experiences of the digital app and the hybrid space constituted by population governance, individual digital navigation, and technology. Drawing on a database of posts scraped from Zhihu, a popular Chinese question-and-answer site, we examine three dimensions of the bug: the algorithmic bug, the territorial bug, and the corporeal bug. This paper sheds light on the significance of end-user experiences in digital infrastructure and contributes to our understanding of the digital geographies of bugs in algorithmic governance and platform urbanism. [ABSTRACT FROM AUTHOR]

Spodoptera frugiperda is a major agricultural pest that has invaded China since January 2019. Given that most of the individuals present in China carried the diagnostic rice-strain mtDNA (COI -RS), there was no efficient method to distinguish populations of S. frugiperda. In this study, we identified and characterized two variant microsatellite alleles in the mitochondrial NAD6 gene of S. frugiperda retrieved from the National Center for Biotechnology Center GenBank. We then sequenced partial NAD6 genes containing the microsatellite region and the diagnostic COI barcoding gene (used to distinguish the corn-strain and the rice-strain) of 429 invasive S. frugiperda individuals that were collected from the main infested regions in China during 2019–2020. Our data indicates that two kinds of interrupted repeat sequences, (ATA)4T(ATA)3 and (ATA)5T(ATA)3, exist in the microsatellite region which we defined as the deletion type (NAD6 -D), and the insertion type (NAD6 -I) based on the repeat units' differentiation, respectively. The presence of these two microsatellite types in the mtDNA genome of S. frugiperda was further confirmed with the sequencing results in 429 samples. Moreover, NAD6 -I and NAD6 -D types were both present in individuals with COI -RS, while only NAD6 -D type was detected in the COI -CS individuals. Interestingly, the two microsatellite types suggested a possible geographic distribution: the western migratory route (Yunan and Chongqing) was comprised exclusively of NAD6 -I type, while both NAD6 -I and NAD6 -D types were identified in the predicted eastern migration trajectories (Hainan, Guangxi, Shandong, etc.). These results suggested that NAD6 -D and NAD6 -I types may be useful in distinguishing between populations, analyzing the evolutionary mechanism of mtDNA microsatellite polymorphism, inferring the migratory route of S. frugiperda in China, and developing precise and integrated control strategies for S. frugiperda. [ABSTRACT FROM AUTHOR]

Background: We compared the temporal changes of immunoglobulin M (IgM), IgG, and IgA antibodies against severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) nucleoprotein (N), spike 1 subunit (S1), and receptor‐binding domain (RBD), and neutralizing antibodies (NAbs) against SARS‐CoV‐2 in patients with coronavirus disease 2019 (COVID‐19) to understand the humoral immunity in COVID‐19 patients for developing drugs and vaccines for COVID‐19. Methods: A total of five confirmed COVID‐19 cases in Nissan Tamagawa Hospital in early August 2020 were recruited in this study. Using a fully automated chemiluminescence immunoassay analyzer, we measured the levels of IgG, IgA, and IgM against SARS‐CoV‐2 N, S1, and RBD and NAbs against SARS‐CoV‐2 in COVID‐19 patients' sera acquired multiple times in individuals from 0 to 76 days after symptom onset. Results: IgG levels against SARS‐CoV‐2 structural proteins increased over time in all cases but IgM and IgA levels against SARS‐CoV‐2 showed different increasing trends among individuals in the early stage. In particular, we observed IgA increasing before IgG and IgM in some cases. The NAb levels were more than cut‐off value in 4/5 COVID‐19 patients some of whose antibodies against RBD did not exceed the cut‐off value in the early stage. Furthermore, NAb levels against SARS‐CoV‐2 increased and kept above cut‐off value more than around 70 days after symptom onset in all cases. Conclusion: Our findings indicate COVID‐19 patients should be examined for IgG, IgA, and IgM against SARS‐CoV‐2 structural proteins and NAbs against SARS‐CoV‐2 to analyze the diversity of patients' immune mechanisms. [ABSTRACT FROM AUTHOR]

Narrow and closed spaces like high-speed train cabins are at great risk for airborne infectious disease transmission. With the threat of COVID-19 as well as other potential contagious diseases, it is necessary to protect passengers from infection. Except for the traditional preventions such as increasing ventilation or wearing masks, this paper proposes a novel measurement that optimizes passenger-to-car assignment schemes to reduce the infection risk for high-speed railway passengers. First, we estimated the probability of an infected person boarding the train at any station. Once infectors occur, the non-steady-state Wells–Riley equation is used to model the airborne transmission intercar cabin. The expected number of susceptible passengers infected on the train can be calculated, which is the so-called overall infection risk. The model to minimize overall infection risk, as a pure integer quadratic programming problem, is solved by LINGO software and tested on several scenarios compared with the classical sequential and discrete assignment strategies used in China. The results show that the proposed model can reduce 67.6% and 56.8% of the infection risk in the base case compared to the sequential and discrete assignment, respectively. In other scenarios, the reduction lies mostly between 10% and 90%. The optimized assignment scheme suggests that the cotravel itinerary among passengers from high-risk and low-risk areas should be reduced, as well as passengers with long- and short-distance trips. Sensitivity analysis shows that our model works better when the incidence is higher at downstream or low-flow stations. Increasing the number of cars and car service capacity can also improve the optimization effect. Moreover, the model is applicable to other epidemics since it is insensitive to the Wells–Riley equation parameters. The results can provide a guideline for railway operators during the post-COVID-19 and other epidemic periods. [ABSTRACT FROM AUTHOR]

Background: Several types of laboratory tests for COVID-19 have been established to date; however, the clinical significance of the serum SARS-CoV-2 nucleocapsid (N) antigen levels remains to be fully elucidated. In the present study, we attempted to elucidate the usefulness and clinical significance of the serum N antigen levels. Methods: We measured the serum N antigen levels in 391 serum samples collected from symptomatic patients with a confirmed diagnosis of COVID-19 and 96 serum samples collected from patients with non-COVID-19, using a fully automated chemiluminescence immunoassay analyzer. Results: Receiver operating characteristic analysis identified the optimal cutoff value of the serum N antigen level (cutoff index, based on Youden's index) as 0.255, which yielded a sensitivity and specificity for the diagnosis of COVID-19 of 91.0 and 81.3%, respectively. The serum N antigen levels were significantly higher in the patient groups with moderate and severe COVID-19 than with mild disease. Moreover, a significant negative correlation was observed between the serum N antigen levels and the SARS-CoV-2 IgG antibody titers, especially in patients with severe COVID-19. Conclusion: Serum N antigen testing might be useful both for the diagnosis of COVID-19 and for obtaining a better understanding of the clinical features of the disease. [ABSTRACT FROM AUTHOR]

A pandemic takes a toll on emotional health and tests psychological resilience. In particular, interpersonal interactions in military communities have been challenged by the COVID-19 pandemic. The military must focus resilience training away from the individual and towards the community. This study investigated the practical assistance rendered to soldiers in aid of their mental health. Specifically, this study analysed the development and implementation of a teaching action plan aimed at improving the psychological resilience of soldiers. The plan was based on the community counselling model, and it serves as a reference for social workers, especially in their conduct of educational programmes. [ABSTRACT FROM AUTHOR]

Cytokine storm resulting from SARS-CoV-2 infection is one of the leading causes of acute respiratory distress syndrome (ARDS) and lung fibrosis. We investigated the effect of inflammatory molecules to identify any marker that is related to lung fibrosis in coronavirus disease 2019 (COVID-19). Seventy-six COVID-19 patients who were admitted to Youan Hospital between January 21 and March 20, 2020 and recovered were recruited for this study. Pulmonary fibrosis, represented as fibrotic volume on chest CT images, was computed by an artificial intelligence (AI)-assisted program. Plasma samples were collected from the participants shortly after admission, to measure the basal inflammatory molecules levels. At discharge, fibrosis was present in 46 (60.5%) patients whose plasma interferon-γ (IFN-γ) levels were twofold lower than those without fibrosis (p > 0.05). The multivariate-adjusted logistic regression analysis demonstrated the inverse association risk of having lung fibrosis and basal circulating IFN-γ levels with an estimate of 0.43 (p = 0.02). Per the 1-SD increase of basal IFN-γ level in circulation, the fibrosis volume decreased by 0.070% (p = 0.04) at the discharge of participants. The basal circulating IFN-γ levels were comparable with c-reactive protein in the discrimination of the occurrence of lung fibrosis among COVID-19 patients at discharge, unlike circulating IL-6 levels. In conclusion, these data indicate that decreased circulating IFN-γ is a risk factor of lung fibrosis in COVID-19. [ABSTRACT FROM AUTHOR]

In this article, we analyze and report cases of three patients who were admitted to Renmin Hospital, Wuhan University, China, for treating COVID-19 pneumonia in February 2020 and were unresponsive to initial treatment of steroids. They were then received titrated steroids treatment based on the assessment of computed tomography (CT) images augmented and analyzed with the artificial intelligence (AI) tool and output. Three patients were finally recovered and discharged. The result indicated that sufficient steroids may be effective in treating the COVID-19 patients after frequent evaluation and timely adjustment according to the disease severity assessed based on the quantitative analysis of the images of serial CT scans. [ABSTRACT FROM AUTHOR]

Background: Patients with cancer have a higher risk of coronavirus disease 2019 (COVID-19) than noncancer patients. The authors conducted a multicenter retrospective study to investigate the clinical manifestations and outcomes of patients with cancer who are diagnosed with COVID-19.Methods: The authors reviewed the medical records of hospitalized patients who were treated at 5 hospitals in Wuhan City, China, between January 5 and March 18, 2020. Clinical parameters relating to cancer history (type and treatment) and COVID-19 were collected. The primary outcome was overall survival (OS). Secondary analyses were the association between clinical factors and severe COVID-19 and OS.Results: A total of 107 patients with cancer were diagnosed with COVID-19, with a median age of 66 years (range, 37-98 years). Lung (21 patients; 19.6%), gastrointestinal (20 patients; 18.7%), and genitourinary (20 patients; 18.7%) cancers were the most common cancer diagnoses. A total of 37 patients (34.6%) were receiving active anticancer treatment when diagnosed with COVID-19, whereas 70 patients (65.4%) were on follow-up. Overall, 52.3% of patients (56 patients) developed severe COVID-19; this rate was found to be higher among patients receiving anticancer treatment than those on follow-up (64.9% vs 45.7%), which corresponded to an inferior OS in the former subgroup of patients (hazard ratio, 3.365; 95% CI, 1.455-7.782 [P = .005]). The detrimental effect of anticancer treatment on OS was found to be independent of exposure to systemic therapy (case fatality rate of 33.3% [systemic therapy] vs 43.8% [nonsystemic therapy]).Conclusions: The results of the current study demonstrated that >50.0% of infected patients with cancer are susceptible to severe COVID-19. This risk is aggravated by simultaneous anticancer treatment and portends for a worse survival, despite treatment for COVID-19. [ABSTRACT FROM AUTHOR]

The coronavirus disease 2019 (COVID-19) pandemic has triggered a new response involving public health surveillance. The popularity of personal wearable devices creates a new opportunity for tracking and precaution of spread of such infectious diseases. In this study, we propose a framework, which is based on the heart rate and sleep data collected from wearable devices, to predict the epidemic trend of COVID-19 in different countries and cities. In addition to a physiological anomaly detection algorithm defined based on data from wearable devices, an online neural network prediction modelling methodology combining both detected physiological anomaly rate and historical COVID-19 infection rate is explored. Four models are trained separately according to geographical segmentation, i.e., North China, Central China, South China, and South-Central Europe. The anonymised sensor data from approximately 1.3 million wearable device users are used for model verification. Our experiment's results indicate that the prediction models can be utilized to alert to an outbreak of COVID-19 in advance, which suggests there is potential for a health surveillance system utilising wearable device data. [ABSTRACT FROM AUTHOR]

Importance: An ongoing outbreak of COVID-19 has exhibited significant threats around the world. We found a significant decrease of T lymphocyte subsets and an increase of inflammatory cytokines of hospitalized patients with COVID-19 in clinical practice.Methods: We conducted a retrospective, single-center observational study of in-hospital adult patients with confirmed COVID-19 in Hubei Provincial Hospital of traditional Chinese and Western medicine (Wuhan, China) by Mar 1, 2020. Demographic, clinical, laboratory information, especially T lymphocyte subsets and inflammatory cytokines were reported. For patients who died or discharge from hospital, the associations of T lymphocyte subsets on admission were evaluated by univariate logistic regression with odds ratios (ORs) and 95% confidence intervals (CIs), warning values to predict in-hospital death were assessed by Receiver Operator Characteristic (ROC) curves.Results: A total of 187 patients were enrolled in our study from Dec 26, 2019 to Mar 1, 2020, of whom 145 were survivors (discharge = 117) or non-survivors (in-hospital death ==28). All patients exhibited a significant drop of T lymphocyte subsets counts with remarkably increasing concentrations of SAA, CRP, IL-6, and IL-10 compared to normal values. The median concentrations of SAA and CRP in critically-ill patients were nearly 4- and 10-fold than those of mild-ill patients, respectively. As the severity of COVID-19 getting worse, the counts of T lymphocyte drop lower.28 patients died in hospital, the median lymphocyte, CD3+ T-cell, CD4+ T-cell, CD8+ T-cell and B-cell were significantly lower than other patients. Lower counts (/uL) of T lymphocyte subsets lymphocyte (<500), CD3+T-cell (<200), CD4+ T-cell (<100), CD8+ T-cell (<100) and B-cell (<50) were associated with higher risks of in-hospital death of CIVID-19. The warning values to predict in-hospital death of lymphocyte, CD3+ T-cell, CD4+ T-cell, CD8+ T-cell, and B-cell were 559, 235, 104, 85 and 82, respectively.Conclusion: We find a significant decrease of T lymphocyte subset is positively correlated with in-hospital death and severity of illness. The decreased levels of T lymphocyte subsets reported in our study were similar with SARS but not common among other virus infection, which may be possible biomarkers for early diagnosis of COVID-19. Our findings may shed light on early warning of high risks of mortality and help early intervention and treatment of COVID-19. [ABSTRACT FROM AUTHOR]