Multi-subject collaborative prevention and control of adolescent myopia in China

Improving the system of adolescent myopia prevention and control and promoting adolescent healthy development is one of the main directions of healthy China construction in the new era. The paper reviewed national myopia policies and local practices, and proposed reflections on the high burden and complex etiology of myopia among adolescents, as well as unclear role and lack of coordination mandate during the COVID-19 epidemic. Based on the synergy theory, through the analysis of the functional positioning of multiple subjects in the prevention and control of myopia, the paper highlighted the multi-party linkage of government, schools, medical institutions, communities, families and markets, profiling the resources and advantages of each subject, as well as dynamic management of adolescent myopia, as well as a multi-subject collaborative prevention and control system with national unity, clear rights and responsibilities, and long-term cooperation.

Has perceived corporate social responsibility attracted job seekers during the COVID-19 pandemic?

The traditional corporate employment relationship in China has changed under the impact of the COVID-19 pandemic, but how to attract core talent remains an urgent challenge for companies to address. Using the stereotype content model, we constructed a moderated mediation model to explore the mechanism and boundary conditions of the effect of perceived corporate social responsibility (CSR) on job seekers. We conducted two mock recruitment experiments with Chinese undergraduates and graduates who were seeking jobs, and found that perceived CSR significantly and positively affected organizational attractiveness, and that the relationship between perceptions of warmth and competence and CSR were mediated by corporate nature. These findings provide guidance and suggestions for managers to carry out CSR and for human resource recruitment practices in the postpandemic era. [ FROM AUTHOR] Copyright of Social Behavior & Personality: an international journal is the property of Society for Personality Research and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Reviewing immunopathology characteristics of SARS-CoV-2 for cancer entwisted with SARS-CoV-2.

In December 2019, the outbreak of a novel coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), infection that started in Wuhan, Hubei Province, China, has spread to all world. Based on the accumulated data and knowledge on the coronavirus infection and immunology characteristics, this review would hope to give some hints on human immune response to SARS-CoV-2 infection in cancer patients. This insight may help in designing the appropriate immune intervention for treatment and the prophylactic/therapeutic methods against cancer under current coronavirus from immunopathology characteristics of SARS-CoV-2 and cancer entwisted with it. We should achieve accurate diagnosis and treatment for cancer patients through advantages of multidisciplinary diagnosis and treatment team. It is believed that we will eventually overcome the epidemic and win in the future.

Continuous diagnosis and prognosis by controlling the update process of deep neural networks.

Continuous diagnosis and prognosis are essential for critical patients. They can provide more opportunities for timely treatment and rational allocation. Although deep-learning techniques have demonstrated superiority in many medical tasks, they frequently forget, overfit, and produce results too late when performing continuous diagnosis and prognosis. In this work, we summarize the four requirements; propose a concept, continuous classification of time series (CCTS); and design a training method for deep learning, restricted update strategy (RU). The RU outperforms all baselines and achieves average accuracies of 90%, 97%, and 85% on continuous sepsis prognosis, COVID-19 mortality prediction, and eight disease classifications, respectively. The RU can also endow deep learning with interpretability, exploring disease mechanisms through staging and biomarker discovery. We find four sepsis stages, three COVID-19 stages, and their respective biomarkers. Further, our approach is data and model agnostic. It can be applied to other diseases and even in other fields.

Effectiveness of inactivated COVID-19 vaccines against mild disease, pneumonia, and severe disease among persons infected with SARS-CoV-2 Omicron variant: Real-world study in Jilin Province, China.

BACKGROUND: : It is critical to determine the real-world performance of vaccines against coronavirus disease 2019 (COVID-19) so that appropriate treatments and policies can be implemented. There was a rapid wave of infections by the Omicron variant in Jilin Province (China) during spring 2022. We examined the effectiveness of inactivated vaccines against Omicron using real-world data from this epidemic. METHODS: . This retrospective case-case study of vaccine effectiveness (VE) examined infected patients who were quarantined and treated from April 16 to June 8, 2022 and responded to an electronic questionnaire. Data were analyzed by univariable and multivariable analyses. RESULTS: . A total of 2968 cases with SARS-CoV-2 infections (asymptomatic: 1029, mild disease: 1858, pneumonia: 108, severe disease: 21) were enrolled in the study. Multivariable regression indicated that the risk for pneumonia or severe disease was greater in those who were older or had underlying diseases, but was less in those who received COVID-19 vaccines. Relative to no vaccination, VE against the composite of pneumonia and severe disease was significant for those who received 2 doses (60.1%, 95%CI: 40.0%, 73.5%) or 3 doses (68.1%, 95%CI: 44.6%, 81.7%), and VE was similar in the subgroups of males and females. However, VE against the composite of all three classes of symptomatic diseases was not significant overall, nor after stratification by sex. There was no statistical difference in the VE of vaccines from different manufacturers. CONCLUSION: . The inactivated COVID-19 vaccines protected patients against pneumonia and severe disease from Omicron infection, and booster vaccination enhanced this effect.

Association of nirmatrelvir/ritonavir treatment on upper respiratory SARS-CoV-2 RT-PCR negative conversion rates among high-risk patients with COVID-19.

BACKGROUND: Acceleration of negative respiratory conversion of SARS-CoV-2 in patients with coronavirus disease 2019 (COVID-19) might reduce viral transmission. Nirmatrelvir/ritonavir is a new antiviral agent recently approved for treatment of COVID-19 that has the potential to facilitate negative conversion. METHODS: A cohort of hospitalized adult patients with mild-to-moderate COVID-19 who had a high-risk for progression to severe disease were studied. These patients presented with COVID-19 symptoms between March 5 and April 5, 2022. The time from positive to negative upper respiratory RT-PCR conversion was assessed by Kaplan-Meier plots and Cox proportional hazards regression with the adjustment for patients baseline demographic and clinical characteristics. RESULTS: There were 258 patients treated with nirmatrelvir/ritonavir and 224 non-treated patients who had mild-to-moderate COVID-19. The median (interquartile range) time for patients who converted from positive to negative RT-PCR was 10 days (7-12 days) in patients treated ≤5 days after symptom onset and 17 days (12-21 days) in non-treated patients, respectively. The proportions of patients with a negative conversion at day 15 were 89.7% and 42.0% in treated patients and non-treated patients, corresponding to a hazard ratio of 4.33 (95% CI, 3.31-5.65). Adjustment for baseline differences between the groups had little effect on the association. Subgroup analysis on treated patients suggests that time to negative conversion did not vary with the patients' baseline characteristics. CONCLUSION: This cohort study of high-risk patients with mild-to-moderate COVID-19 found an association between nirmatrelvir/ritonavir treatment and accelerated negative RT-PCR respiratory SARS-CoV-2 conversion that might reduce the risk of viral shedding and disease transmission.

Milder symptoms and shorter course in patients with re-positive COVID-19: A cohort of 180 patients from Northeast China.

China experienced another widespread Coronavirus disease 2019 (COVID-19) outbreak recently caused by the Omicron variant, which is less severe but far more contagious than the other COVID-19 variants, leading local governments to focus efforts on eliminating the spread of the disease. Previous studies showed that after "recovering" from the virus, some patients could re-test positive for COVID-19 with nucleic acid tests, challenging the control of disease spread. In this study, we aimed to analyze the clinical and laboratory characteristics of re-positive COVID-19 patients in Northeast China. We retrospectively analyzed data from confirmed reverse transcription polymerase chain reaction (RT-PCR) re-positive COVID-19 patients who were admitted to the First Hospital of Jilin University, Jilin Province, China, from March to June 2022. Detailed clinical symptoms, medical history, anti-Corona Virus (CoV) IgG and IgM levels, and CoV nucleic acid cycle threshold (Ct) values during the re-positive period were collected and analyzed. A total of 180 patients were included in this study, including 62 asymptomatic cases and 118 mild cases. The cohort included 113 men and 67 women, with an average age of 45.73 years. The median time between recovery from the virus and re-positivity was 13 days. Our results showed that the proportion of re-positive patients with symptoms was lower, and the nucleic acid test-positive duration was shorter during the re-positive period. Furthermore, in patients with underlying disease, the proportion of patients with symptoms was higher, anti-CoV IgG levels were lower, and the total disease duration was longer. In conclusion, during the re-positive period, the symptoms were milder, and the CoV nucleic acid test-positive course was shorter. The concomitant underlying disease is an important factor associated with clinical symptoms, and the overall course of COVID-19 re-positive patients may be associated with lower anti-CoV IgG levels. Large-scale and multicenter studies are recommended to better understand the pathophysiology of recurrence in patients with COVID-19.

Safety of inactivated SARS-CoV-2 vaccines in myasthenia gravis: A survey-based study.

Background: Vaccination remains the most effective measure to prevent SARS-CoV-2 infection and worse outcomes. However, many myasthenia gravis (MG) patients are hesitant to receive vaccine due to fear of worsening. Methods: MG patients were consecutively enrolled in two MG centers in North China. The "worsening" after vaccination was self-reported by MG patients, and severity was measured with a single simple question. The general characteristics and disease status immediately prior to the first dose were compared between the worsening and non-worsening groups. Independent factors associated with worsening were explored with multivariate regression analysis. Results: One hundred and seven patients were included. Eleven patients (10.3%) reported worsening after vaccination, including eight patients with mild or moderate worsening and three patients with severe worsening. Only one of them (0.9%) needed an escalation of immunosuppressive treatments. There were significant differences between the worsening and non-worsening groups in terms of Myasthenia Gravis Foundation of America classes immediately before the first dose and intervals since the last aggravation. Precipitating factors might contribute to the worsening in some patients. Logistic regression revealed that only interval since the last aggravation ≤6 months was associated with worsening after SARS-CoV-2 vaccination (P = 0.01, OR = 8.62, 95% CI: 1.93-38.46). Conclusion: SARS-CoV-2 vaccines (an overwhelming majority were inactivated vaccines) were found safe in milder Chinese MG patients who finished two doses. Worsening after vaccination was more frequently seen in patients who were presumed as potentially unstable (intervals since last aggravation ≤6 months). However, mild worsening did occur in patients who were presumed to be stable. Precipitating factors should still be sought and treated for better outcome.

Convalescent plasma therapy for patients with severe COVID-19: A case series study.

Coronavirus disease 2019 (COVID-19) is a novel acute respiratory infectious disease that can lead to multiple-organ dysfunction in patients with severe disease. However, there is a lack of effective antiviral drugs for COVID-19. Herein, we investigated the efficacy and safety of convalescent plasma (CP) therapy for treating severe COVID-19 in an attempt to explore new therapeutic methods. The clinical data of 3 imported patients with severe COVID-19 who underwent treatment with CP and who were quarantined and treated in a designated COVID-19 hospital from March 2020 to April 2020 were collected and analyzed. The 3 patients, including a 57-year-old male, 65-year-old female, and 59-year-old female, were clinically classified as having severe COVID-19. The main underlying diseases included hypertension, diabetes, sequelae of cerebral infarction, and postoperative thyroid adenoma. The common symptoms included cough, fever, and shortness of breath. All patients received antiviral drugs and other supportive treatments. Additionally, CP treatment was administered. At 48 to 72 hours after the CP transfusion, all 3 of the patients exhibited an improvement and alleviation of symptoms, an elevated arterial oxygen saturation, and decreased C-reactive protein and interleukin-6 levels. The counts of the total lymphocytes and T lymphocytes (CD3+) and their subsets (CD4 + and CD8+) were also obviously increased. Repeated chest computed tomography also revealed obvious absorption of the lesions in the bilateral lungs. Only 1 patient had a mild allergic reaction during the CP infusion, but no severe adverse reactions were observed. The early treatment with CP in patients with severe COVID-19 can rapidly improve the condition of the patients, and CP therapy is generally effective and safe.

Safety of inactivated SARS-CoV-2 vaccines in myasthenia gravis: A survey-based study

Background Vaccination remains the most effective measure to prevent SARS-CoV-2 infection and worse outcomes. However, many myasthenia gravis (MG) patients are hesitant to receive vaccine due to fear of worsening. Methods MG patients were consecutively enrolled in two MG centers in North China. The “worsening” after vaccination was self-reported by MG patients, and severity was measured with a single simple question. The general characteristics and disease status immediately prior to the first dose were compared between the worsening and non-worsening groups. Independent factors associated with worsening were explored with multivariate regression analysis. Results One hundred and seven patients were included. Eleven patients (10.3%) reported worsening after vaccination, including eight patients with mild or moderate worsening and three patients with severe worsening. Only one of them (0.9%) needed an escalation of immunosuppressive treatments. There were significant differences between the worsening and non-worsening groups in terms of Myasthenia Gravis Foundation of America classes immediately before the first dose and intervals since the last aggravation. Precipitating factors might contribute to the worsening in some patients. Logistic regression revealed that only interval since the last aggravation ≤6 months was associated with worsening after SARS-CoV-2 vaccination (P = 0.01, OR = 8.62, 95% CI: 1.93–38.46). Conclusion SARS-CoV-2 vaccines (an overwhelming majority were inactivated vaccines) were found safe in milder Chinese MG patients who finished two doses. Worsening after vaccination was more frequently seen in patients who were presumed as potentially unstable (intervals since last aggravation ≤6 months). However, mild worsening did occur in patients who were presumed to be stable. Precipitating factors should still be sought and treated for better outcome.

Urban monitoring, evaluation and application of COVID-19 listed vaccine effectiveness: a health code blockchain study.

OBJECTIVE: By using health code blockchain, cities can maximise the use of personal information while maximising the protection of personal privacy in the monitoring and evaluation of the effectiveness of listed vaccines. DESIGN: This study constructs an urban COVID-19 listed vaccine effectiveness (VE) monitoring, evaluation and application system based on the health code blockchain. This study uses this system and statistical simulation to analyse three urban application scenarios, namely evaluating the vaccination rate (VR) and determining the optimal vaccination strategy, evaluating herd immunity and monitoring the VE on variant. MAIN OUTCOME MEASURES: The primary outcomes first establish an urban COVID-19 listed VE monitoring, evaluation and application system by using the health code blockchain, combined with the dynamic monitoring model of VE, the evaluation index system of VE and the monitoring and evaluation system of personal privacy information use, and then three measures are analysed in urban simulation: one is to take the index reflecting urban population mobility as the weight to calculate the comprehensive VR, the second is to calculate the comprehensive basic reproduction number (R) in the presence of asymptomatic persons, the third is to compare the difference between the observed effectiveness and the true effectiveness of listed vaccines under virus variation. RESULTS: Combining this system and simulation, this study finds: (1) The comprehensive VR, which is weighted to reflect urban population mobility, is more accurate than the simple VR which does not take into account urban population mobility. Based on population mobility, the algorithm principle of urban optimal vaccination strategy is given. In the simulation of urban listed vaccination involving six regions, programmes 1 and 5 have the best protective effect among the eight vaccination programmes, and the optimal vaccination order is 3-5-2-4-6-1. (2) In the presence of asymptomatic conditions, the basic reproduction number, namely R0*(1-VR*VE), does not accurately reflect the effect of herd immunity, but the comprehensive basic reproduction number (R) should be used. The R is directly proportional to the proportion of asymptomatic people (aw) and the duration of the incubation period (ip), and inversely proportional to the VR, the VE and the number of days transmitted in the ip (k). In the simulation analysis, when symptomatic R0=3, even with aw=0.2, the R decreases to nearly 1 until the VR reaches 95%. When aw=0.8, even when the entire population is vaccinated, namely VR=1, the R is 1.688, and still significantly greater than 1. If the R is to be reduced to 1, the VE needs to be increased to 0.87. (3) This system can more comprehensively and accurately grasp the impact of the variant virus on urban VE. The traditional epidemiological investigation can lose the contacts of infected persons, which leads to the deviation between the observed effectiveness and the true effectiveness. Virus variation aggravates the loss, and then increases the deviation. Simulation case 1 assumes the unvaccinated rate of 0.8, the ongoing VR of 0.1, the completed VR of 0.1 and an average infection rate of 2% for the variant virus. If a vaccine is more than 90% effectiveness against the premutant virus, but only 80% effectiveness against the mutant virus, and because 80% of the unvaccinated people who are not infected are not observed, the observed effectiveness of the vaccine is 91.76%, it will lead to the wrong judgement that the VE against the variant virus is not decreased. Simulation case 2 assumes the unvaccinated rate of 0.8, the ongoing VR of 0.1, the completed VR of 0.1 and an average infection rate of 5% for the variant virus. Simulation finds that the higher the proportion of unvaccinated infected people who are not observed, the lower the estimate of observed effectiveness; and the lower the true effectiveness, the larger the gap between observed effectiveness and true effectiveness. Simulation case 3 assumes the unvaccinated rate of 0.2, the ongoing VR of 0.2, the completed VR of 0.6 and an average infection rate of 2% for the variant virus. Simulation finds that the higher the proportion of unobserved completed vaccination patients who are not infected, the lower the estimate of observed effectiveness; and the lower the true effectiveness, the larger the gap between observed effectiveness and true effectiveness. Simulation case 4 assumes the unvaccinated rate of 0.2, the ongoing VR of 0.2, the completed VR of 0.6 and an average infection rate of 5% for the variant virus. If a vaccine is more than 90% effectiveness against the premutant virus, but only 80% effectiveness against the mutant virus, and because 80% of the infected people with complete vaccination are not observed, the observed effectiveness of the vaccine is 91.95%, similar to case 1, it will lead to the wrong judgement that the VE against the variant virus is not decreased. CONCLUSION: Compared with traditional epidemiological investigation, this system can meet the challenges of accelerating virus variation and a large number of asymptomatic people, dynamically monitor and accurately evaluate the effectiveness of listed vaccines and maximise personal privacy without locking down the relevant area or city. This system established in this study could serve as a universal template for monitoring and evaluating the effectiveness of COVID-19 listed vaccines in cities around the world. If this system can be promoted globally, it will promote countries to strengthen unity and cooperation and enhance the global ability to respond to COVID-19.

Metal-based strategies for the fight against COVID-19.

The emerging COVID-19 pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has claimed over six million lives globally to date. Despite the availability of vaccines, the pandemic still cannot be fully controlled owing to rapid mutation of the virus that renders enhanced transmissibility and antibody evasion. This is thus an unmet need to develop safe and effective therapeutic options for COVID-19, in particular, remedies that can be used at home. Considering the great success of multi-targeted cocktail therapy for the treatment of viral infections, metal-based drugs might represent a unique and new source of antivirals that resemble a cocktail therapy in terms of their mode of actions. In this review, we first summarize the role that metal ions played in SARS-CoV-2 viral replication and pathogenesis, then highlight the chemistry of metal-based strategies in the fight against SARS-CoV-2 infection, including both metal displacement and chelation based approaches. Finally, we outline a perspective and direction on how to design and develop metal-based antivirals for the fight against the current or future coronavirus pandemic.

Multiplex metal-detection based assay (MMDA) for COVID-19 diagnosis and identification of disease severity biomarkers†‡ † Dedicated to Prof. Zhifang Chai on the occasion of his 80th birthday.‡ Electronic supplementary information (ESI) available. See DOI: 10.1039/d1sc05852e

The ongoing COVID-19 pandemic caused by SARS-CoV-2 highlights the urgent need to develop sensitive methods for diagnosis and prognosis. To achieve this, multidimensional detection of SARS-CoV-2 related parameters including virus loads, immune response, and inflammation factors is crucial. Herein, by using metal-tagged antibodies as reporting probes, we developed a multiplex metal-detection based assay (MMDA) method as a general multiplex assay strategy for biofluids. This strategy provides extremely high multiplexing capability (theoretically over 100) compared with other reported biofluid assay methods. As a proof-of-concept, MMDA was used for serologic profiling of anti-SARS-CoV-2 antibodies. The MMDA exhibits significantly higher sensitivity and specificity than ELISA for the detection of anti-SARS-CoV-2 antibodies. By integrating the high dimensional data exploration/visualization tool (tSNE) and machine learning algorithms with in-depth analysis of multiplex data, we classified COVID-19 patients into different subgroups based on their distinct antibody landscape. We unbiasedly identified anti-SARS-CoV-2-nucleocapsid IgG and IgA as the most potently induced types of antibodies for COVID-19 diagnosis, and anti-SARS-CoV-2-spike IgA as a biomarker for disease severity stratification. MMDA represents a more accurate method for the diagnosis and disease severity stratification of the ongoing COVID-19 pandemic, as well as for biomarker discovery of other diseases. A MMDA platform is developed by using metal-tagged antibodies as reporting probes combined with machine learning algorithms, as a general strategy for highly multiplexed biofluid assay.

Multiplex metal-detection based assay (MMDA) for COVID-19 diagnosis and identification of disease severity biomarkers.

The ongoing COVID-19 pandemic caused by SARS-CoV-2 highlights the urgent need to develop sensitive methods for diagnosis and prognosis. To achieve this, multidimensional detection of SARS-CoV-2 related parameters including virus loads, immune response, and inflammation factors is crucial. Herein, by using metal-tagged antibodies as reporting probes, we developed a multiplex metal-detection based assay (MMDA) method as a general multiplex assay strategy for biofluids. This strategy provides extremely high multiplexing capability (theoretically over 100) compared with other reported biofluid assay methods. As a proof-of-concept, MMDA was used for serologic profiling of anti-SARS-CoV-2 antibodies. The MMDA exhibits significantly higher sensitivity and specificity than ELISA for the detection of anti-SARS-CoV-2 antibodies. By integrating the high dimensional data exploration/visualization tool (tSNE) and machine learning algorithms with in-depth analysis of multiplex data, we classified COVID-19 patients into different subgroups based on their distinct antibody landscape. We unbiasedly identified anti-SARS-CoV-2-nucleocapsid IgG and IgA as the most potently induced types of antibodies for COVID-19 diagnosis, and anti-SARS-CoV-2-spike IgA as a biomarker for disease severity stratification. MMDA represents a more accurate method for the diagnosis and disease severity stratification of the ongoing COVID-19 pandemic, as well as for biomarker discovery of other diseases.

Orally administered bismuth drug together with N-acetyl cysteine as a broad-spectrum anti-coronavirus cocktail therapy.

The emergence of SARS-CoV-2 variants of concern compromises vaccine efficacy and emphasizes the need for further development of anti-SARS-CoV-2 therapeutics, in particular orally administered take-home therapies. Cocktail therapy has shown great promise in the treatment of viral infection. Herein, we reported the potent preclinical anti-SARS-CoV-2 efficacy of a cocktail therapy consisting of clinically used drugs, e.g. colloidal bismuth subcitrate (CBS) or bismuth subsalicylate (BSS), and N-acetyl-l-cysteine (NAC). Oral administration of the cocktail reduced viral loads in the lung and ameliorated virus-induced pneumonia in a hamster infection model. The mechanistic studies showed that NAC prevented the hydrolysis of bismuth drugs at gastric pH via the formation of the stable component [Bi(NAC)3], and optimized the pharmacokinetics profile of CBS in vivo. Combination of bismuth drugs with NAC suppressed the replication of a panel of medically important coronaviruses including Middle East respiratory syndrome-related coronavirus (MERS-CoV), Human coronavirus 229E (HCoV-229E) and SARS-CoV-2 Alpha variant (B.1.1.7) with broad-spectrum inhibitory activities towards key viral cysteine enzymes/proteases including papain-like protease (PLpro), main protease (Mpro), helicase (Hel) and angiotensin-converting enzyme 2 (ACE2). Importantly, our study offered a potential at-home treatment for combating SARS-CoV-2 and future coronavirus infections.

The psychological impacts of a COVID-19 outbreak on college students in China: a longitudinal study

An outbreak in Wuhan, China in late 2019 of a highly infectious new coronary pneumonia (COVID-19) led to the imposition of countrywide confinement measures from January to March 2020. This is a longitudinal study on changes in the mental health status of a college population before and after their COVID-19 confinement for the first two weeks, focusing on states of psychological distress, depression, anxiety and affectivity. The influence of possible stressors on their mental health were investigated, including inadequate supplies and fears of infection. Five hundred and fifty-five undergraduate students were recruited from Hebei Agricultural University in Baoding, China. The participants completed two online surveys-on anxiety and depression, and on positive and negative affect. One survey was conducted before the confinement and the other was conducted 15-17 days after the start of the confinement. Increases in negative affect and symptoms of anxiety and depression (p-values < 0.001) were observed after 2 weeks of confinement. Inadequate supplies of hand sanitizers, a higher year of study, and higher scores on anxiety and depression were common predictors of increased negative affect, anxiety, and depression across the confinement period. The results suggest that healthcare policymakers should carefully consider the appropriate confinement duration, and ensure adequate supplies of basic infection-control materials.

Substantial changes of chemical composition and sources of fine particles during the period of COVID-19 pandemic in Taiyuan, Northern China.

To better understand the effects of COVID-19 on air quality in Taiyuan, hourly in situ measurements of PM2.5(particulate matter with an aerodynamic diameter less than 2.5 mm) and chemical components (water-soluble ions, organic carbon (OC), elemental carbon (EC), and trace elements) were conducted before (P1: 1 January-23 January 2020) and during (P2: 24 January-15 February 2020) the coronavirus disease 2019 (COVID-19) outbreak. The average concentrations of PM2.5 dropped from 122.0 µg/m3 during P1 to 83.3 µg/m3 during P2. Compared with P1, except for fireworks burning-related chemical components (K+, Mg2+, K, Cu, Ba), the concentrations of other chemical components of PM2.5 decreased by14.9-69.8%. Although the large decrease of some emission sources, fireworks burning still resulted in the occurrence of pollution events during P2. The analysis results of positive matrix factorization model suggested that six PM2.5 sources changed significantly before and during the outbreak of the epidemic. The contributions of vehicle emission, industrial process, and dust to PM2.5 decreased from 23.1%, 3.5%, and 4.0% during P1 to 7.7%, 3.4%, and 2.3% during P2, respectively, whereas the contributions of secondary inorganic aerosol, fireworks burning, and coal combustion to PM2.5 increased from 62.0%, 1.8%, and 5.5% to 71.5%, 9.0%, and 6.2%, respectively. The source apportionment results were also affected by air mass transport. The largest reductions of vehicle emission, industrial process, and dust source were distinctly seen for the air masses from northwest. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11869-021-01082-y.

Predicting COVID-19 disease progression and patient outcomes based on temporal deep learning.

BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic has caused health concerns worldwide since December 2019. From the beginning of infection, patients will progress through different symptom stages, such as fever, dyspnea or even death. Identifying disease progression and predicting patient outcome at an early stage helps target treatment and resource allocation. However, there is no clear COVID-19 stage definition, and few studies have addressed characterizing COVID-19 progression, making the need for this study evident. METHODS: We proposed a temporal deep learning method, based on a time-aware long short-term memory (T-LSTM) neural network and used an online open dataset, including blood samples of 485 patients from Wuhan, China, to train the model. Our method can grasp the dynamic relations in irregularly sampled time series, which is ignored by existing works. Specifically, our method predicted the outcome of COVID-19 patients by considering both the biomarkers and the irregular time intervals. Then, we used the patient representations, extracted from T-LSTM units, to subtype the patient stages and describe the disease progression of COVID-19. RESULTS: Using our method, the accuracy of the outcome of prediction results was more than 90% at 12 days and 98, 95 and 93% at 3, 6, and 9 days, respectively. Most importantly, we found 4 stages of COVID-19 progression with different patient statuses and mortality risks. We ranked 40 biomarkers related to disease and gave the reference values of them for each stage. Top 5 is Lymph, LDH, hs-CRP, Indirect Bilirubin, Creatinine. Besides, we have found 3 complications - myocardial injury, liver function injury and renal function injury. Predicting which of the 4 stages the patient is currently in can help doctors better assess and cure the patient. CONCLUSIONS: To combat the COVID-19 epidemic, this paper aims to help clinicians better assess and treat infected patients, provide relevant researchers with potential disease progression patterns, and enable more effective use of medical resources. Our method predicted patient outcomes with high accuracy and identified a four-stage disease progression. We hope that the obtained results and patterns will aid in fighting the disease.

Effects of Chinese Medicine on Symptoms, Syndrome Evolution, and Lung Inflammation Absorption in COVID-19 Convalescent Patients during 84-Day Follow-up after Hospital Discharge: A Prospective Cohort and Nested Case-Control Study.

OBJECTIVE: To observe the changes of symptoms, Chinese medicine (CM) syndrome, and lung inflammation absorption during convalescence in patients with coronavirus disease 2019 (COVID-19) who had not totally recovered after hospital discharge and whether CM could promote the improvement process. METHODS: This study was designed as a prospective cohort and nested case-control study. A total of 96 eligible patients with COVID-19 in convalescence were enrolled from Beijing Youan Hospital and Beijing Huimin Hospital and followed up from the hospital discharged day. Patients were divided into the CM (64 cases) and the control groups (32 cases) based on the treatment with or without CM and followed up at 14, 28, 56, and 84 days after discharge. In the CM group, patients received the 28-day CM treatment according to two types of CM syndrome. Improvements in clinical symptoms, CM syndrome, and absorption of lung inflammation were observed. RESULTS: All the 96 patients completed the 84-day follow-up from January 21 to March 28, 2020. By the 84th day of follow-up, respiratory symptoms were less than 5%. There was no significant difference in the improvement rates of symptoms, including fatigue, sputum, cough, dry throat, thirst, and upset, between the two groups (P>0.05). Totally 82 patients (85.42%) showed complete lung inflammation absorption at the 84-day follow-up. On day 14, the CM group had a significantly higher absorption rate than the control group (P<0.05) and the relative risk of absorption for CM vs. control group was 3.029 (95% confidence interval: 1.026-8.940). The proportions of CM syndrome types changed with time prolonging: the proportion of the pathogen residue syndrome gradually decreased, and the proportion of both qi and yin deficiency syndrome gradually increased. CONCLUSIONS: Patients with COVID-19 in convalescence had symptoms and lung inflammation after hospital discharge and recovered with time prolonging. CM could improve lung inflammation for early recovery. The types of CM syndrome can be transformed with time prolonging. (Registration No. ChiCTR2000029430).

Phase 2a, open-label, dose-escalating, multi-center pharmacokinetic study of favipiravir (T-705) in combination with oseltamivir in patients with severe influenza.

BACKGROUND: The pharmacokinetics and appropriate dose regimens of favipiravir are unknown in hospitalized influenza patients; such data are also needed to determine dosage selection for favipiravir trials in COVID-19. METHODS: In this dose-escalating study, favipiravir pharmacokinetics and tolerability were assessed in critically ill influenza patients. Participants received one of two dosing regimens; Japan licensed dose (1600 mg BID on day 1 and 600 mg BID on the following days) and the higher dose (1800 mg/800 mg BID) trialed in uncomplicated influenza. The primary pharmacokinetic endpoint was the proportion of patients with a minimum observed plasma trough concentration (Ctrough) ≥20 mg/L at all measured time points after the second dose. RESULTS: Sixteen patients were enrolled into the low dose group and 19 patients into the high dose group of the study. Favipiravir Ctrough decreased significantly over time in both groups (p <0.01). Relative to day 2 (48 hrs), concentrations were 91.7% and 90.3% lower in the 1600/600 mg group and 79.3% and 89.5% lower in the 1800/800 mg group at day 7 and 10, respectively. In contrast, oseltamivir concentrations did not change significantly over time. A 2-compartment disposition model with first-order absorption and elimination described the observed favipiravir concentration-time data well. Modeling demonstrated that less than 50% of patients achieved Ctrough ≥20 mg/L for >80% of the duration of treatment of the two dose regimens evaluated (18.8% and 42.1% of patients for low and high dose regimen, respectively). Increasing the favipravir dosage predicted a higher proportion of patients reaching this threshold of 20 mg/L, suggesting that dosing regimens of ≥3600/2600 mg might be required for adequate concentrations. The two dosing regimens were well-tolerated in critical ill patients with influenza. CONCLUSION: The two dosing regimens proposed for uncomplicated influenza did not achieve our pre-defined treatment threshold.