Population genetic characteristics of Aedes aegypti in 2019 and 2020 under the distinct circumstances of dengue outbreak and the COVID-19 pandemic in Yunnan Province, China.

Introduction: Since Aedes aegypti invaded Yunnan Province in 2002, its total population has continued to expand. Shi et al. used microsatellite and mitochondrial molecular markers to study the Ae. aegypti populations in Yunnan Province in 2015 and 2016, found that it showed high genetic diversity and genetic structure. However, there are few studies on the population genetic characteristics of Ae. aegypti in Yunnan Province under different levels of human intervention. This study mainly used two common types of molecular markers to analyze the genetic characteristics of Ae. aegypti, revealing the influence of different input, prevention and control pressures on the genetic diversity and structure of this species. Understanding the genetic characteristics of Ae. aegypti populations and clarifying the diversity, spread status, and source of invasion are essential for the prevention, control and elimination of this disease vector. Methods: We analyzed the genetic diversity and genetic structure of 22 populations sampled in Yunnan Province in 2019 and 17 populations sampled in 2020 through nine microsatellite loci and COI and ND4 fragments of mitochondrial DNA. In 2019, a total of 22 natural populations were obtained, each containing 30 samples, a total of 660 samples. In 2020, a total of 17 natural populations were obtained. Similarly, each population had 30 samples, and a total of 510 samples were obtained. Results: Analysis of Ae. aegypti populations in 2019 and 2020 based on microsatellite markers revealed 67 and 72 alleles, respectively. The average allelic richness of the populations in 2019 was 3.659, while that in 2020 was 3.965. The HWE analysis of the 22 populations sampled in 2019 revealed significant departure only in the QSH-2 population. The 17 populations sampled in 2020 were all in HWE. The average polymorphic information content (PIC) values were 0.546 and 0.545, respectively, showing high polymorphism. The average observed heterozygosity of the 2019 and 2020 populations was 0.538 and 0.514, respectively, and the expected average heterozygosity was 0.517 and 0.519, showing high genetic diversity in all mosquito populations. By analyzing the COI and ND4 fragments in the mitochondrial DNA of Ae. aegypti, the populations sampled in 2019 had a total of 10 COI haplotypes and 17 ND4 haplotypes. A total of 20 COI haplotypes were found in the populations sampled in 2020, and a total of 24 ND4 haplotypes were obtained. STRUCTURE, UPGMA and DAPC cluster analyses and a network diagram constructed based on COI and ND4 fragments showed that the populations of Ae. aegypti in Yunnan Province sampled in 2019 and 2020 could be divided into two clusters. At the beginning of 2020, due to the impact of COVID-19, the flow of goods between the port areas of Yunnan Province and neighboring countries was reduced, and the sterilization was more effective when goods enter the customs, leading to different immigration pressures on Ae. aegypti population in Yunnan Province between 2019 and 2020, the source populations of the 2019 and 2020 populations changed. Mantel test is generally used to detect the correlation between genetic distance and geographical distance, the analysis indicated that population geographic distance and genetic distance had a moderately significant correlation in 2019 and 2020 (2019: p < 0.05 R2 = 0.4807, 2020: p < 0.05 R2 = 0.4233). Conclusion: Ae. aegypti in Yunnan Province maintains a high degree of genetic diversity. Human interference is one reason for the changes in the genetic characteristics of this disease vector.

Huashi baidu granule in the treatment of pediatric patients with mild coronavirus disease 2019: A single-center, open-label, parallel-group randomized controlled clinical trial.

Background: Since late February 2022, a wave of coronavirus disease 2019 (COVID-19) mainly caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron variant rapidly appeared in Shanghai, China. Traditional Chinese medicine treatment is recommended for pediatric patients; however, the safety and efficacy remain to be confirmed. We conducted a single-center, open-label, parallel-group randomized controlled trial to assess the efficacy and safety of a Chinese herb compound, Huashi Baidu granule (HSBDG) in pediatric patients with laboratory-confirmed mild COVID-19. Methods: 108 recruited children (aged 3-18 years) with laboratory-confirmed mild COVID-19 were randomly allocated 2:1 to receive oral HSBDG for five consecutive days (intervention group) and to receive compound pholcodine oral solution for five consecutive days (control group). The negative conversion time of SARS-CoV-2 nucleic acid and symptom scores were recorded. Results: The median negative conversion time of SARS-CoV-2 nucleic acid was significantly shorter in the intervention group than in the control group (median days [interquartile range (IQR)]: 3 [3-5] vs. 5 [3-6]; p = 0.047). The median total symptom score on day 3 was significantly lower in the intervention group than in the control group (median total symptom score [IQR]: 1 [0-2] vs. 2 [0-3]; p = 0.036). There was no significant differences in the frequency of antibiotic use and side effects between the two groups. Conclusion: HSBDG is a safe, effective oral Chinese herbal compound granule, which shows a good performance within the Omicron wave among pediatric patients.

Huashi baidu granule in the treatment of pediatric patients with mild coronavirus disease 2019: A single-center, open-label, parallel-group randomized controlled clinical trial

Background: Since late February 2022, a wave of coronavirus disease 2019 (COVID-19) mainly caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron variant rapidly appeared in Shanghai, China. Traditional Chinese medicine treatment is recommended for pediatric patients;however, the safety and efficacy remain to be confirmed. We conducted a single-center, open-label, parallel-group randomized controlled trial to assess the efficacy and safety of a Chinese herb compound, Huashi Baidu granule (HSBDG) in pediatric patients with laboratory-confirmed mild COVID-19. Methods: 108 recruited children (aged 3–18 years) with laboratory-confirmed mild COVID-19 were randomly allocated 2:1 to receive oral HSBDG for five consecutive days (intervention group) and to receive compound pholcodine oral solution for five consecutive days (control group). The negative conversion time of SARS-CoV-2 nucleic acid and symptom scores were recorded. Results: The median negative conversion time of SARS-CoV-2 nucleic acid was significantly shorter in the intervention group than in the control group (median days [interquartile range (IQR)]: 3 [3–5] vs. 5 [3–6];p = 0.047). The median total symptom score on day 3 was significantly lower in the intervention group than in the control group (median total symptom score [IQR]: 1 [0–2] vs. 2 [0–3];p = 0.036). There was no significant differences in the frequency of antibiotic use and side effects between the two groups. Conclusion: HSBDG is a safe, effective oral Chinese herbal compound granule, which shows a good performance within the Omicron wave among pediatric patients.

Stress, Burnout, and Coping Strategies of Frontline Nurses During the COVID-19 Epidemic in Wuhan and Shanghai, China.

Background: Nurses at the frontline of caring for COVID-19 patients might experience mental health challenges and supportive coping strategies are needed to reduce their stress and burnout. The aim of this study was to identify stressors and burnout among frontline nurses caring for COVID-19 patients in Wuhan and Shanghai and to explore perceived effective morale support strategies. Method: A cross-sectional survey was conducted in March 2020 among 110 nurses from Zhongshan Hospital, Shanghai, who were deployed at COVID-19 units in Wuhan and Shanghai. A COVID-19 questionnaire was adapted from the previous developed "psychological impacts of SARS" questionnaire and included stressors (31 items), coping strategies (17 items), and effective support measures (16 items). Burnout was measured with the Maslach Burnout Inventory. Results: Totally, 107 (97%) nurses responded. Participants mean age was 30.28 years and 90.7% were females. Homesickness was most frequently reported as a stressor (96.3%). Seven of the 17 items related to coping strategies were undertaken by all participants. Burnout was observed in the emotional exhaustion and depersonalization subscales, with 78.5 and 92.5% of participants presenting mild levels of burnout, respectively. However, 52 (48.6%) participants experienced a severe lack of personal accomplishment. Participants with longer working hours in COVID-19 quarantine units presented higher emotional exhaustion (OR = 2.72, 95% CI 0.02-5.42; p = 0.049) and depersonalization (OR = 1.14, 95% CI 0.10-2.19; p = 0.033). Participants with younger age experienced higher emotional exhaustion (OR = 2.96, 95% CI 0.11-5.82; p = 0.042) and less personal accomplishment (OR = 3.80, 95% CI 0.47-7.13; p = 0.033). Conclusions: Nurses in this study experienced considerable stress and the most frequently reported stressors were related to families. Nurses who were younger and those working longer shift-time tended to present higher burnout levels. Psychological support strategies need to be organized and implemented to improve mental health among nurses during the COVID-19 pandemic.

Supply forecasting and profiling of urban supermarket chains based on tensor quantization exponential regression for social governance.

Background: During the COVID-19 pandemic, the accurate forecasting and profiling of the supply of fresh commodities in urban supermarket chains may help the city government make better economic decisions, support activities of daily living, and optimize transportation to support social governance. In urban supermarket chains, the large variety of fresh commodities and the short shelf life of fresh commodities lead to the poor performance of the traditional fresh commodity supply forecasting algorithm. Methods: Unlike the classic method of forecasting a single type of fresh commodity, we proposed a third-order exponential regression algorithm incorporating the block Hankle tensor. First, a multi-way delay embedding transform was used to fuse multiple fresh commodities sales to a Hankle tensor, for aggregating the correlation and mutual information of the whole category of fresh commodities. Second, high-order orthogonal iterations were performed for tensor decomposition, which effectively extracted the high-dimensional features of multiple related fresh commodities sales time series. Finally, a tensor quantization third-order exponential regression algorithm was employed to simultaneously predict the sales of multiple correlated fresh produce items. Results: The experiment result showed that the provided tensor quantization exponential regression method reduced the normalized root mean square error by 24% and the symmetric mean absolute percentage error by 22%, compared with the state-of-the-art approaches.

The paradigm and future value of the metaverse for the intervention of cognitive decline.

Cognitive decline is a gradual neurodegenerative process that is affected by genetic and environmental factors. The doctor-patient relationship in the healthcare for cognitive decline is in a "shallow" medical world. With the development of data science, virtual reality, artificial intelligence, and digital twin, the introduction of the concept of the metaverse in medicine has brought alternative and complementary strategies in the intervention of cognitive decline. This article technically analyzes the application scenarios and paradigms of the metaverse in medicine in the field of mental health, such as hospital management, diagnosis, prediction, prevention, rehabilitation, progression delay, assisting life, companionship, and supervision. The metaverse in medicine has made primary progress in education, immersive consultation, dental disease, and Parkinson's disease, bringing revolutionary prospects for non-pharmacological complementary treatment of cognitive decline and other mental problems. In particular, with the demand for non-face-to-face communication generated by the global COVID-19 epidemic, the needs for uncontactable healthcare service for the elderly have increased. The paradigm of self-monitoring, self-healing, and healthcare experienced by the elderly through the metaverse in medicine, especially from meta-platform, meta-community, and meta-hospital, will be generated, which will reconstruct the service modes for the elderly people. The future map of the metaverse in medicine is huge, which depends on the co-construction of community partners.

The paradigm and future value of the metaverse for the intervention of cognitive decline

Cognitive decline is a gradual neurodegenerative process that is affected by genetic and environmental factors. The doctor-patient relationship in the healthcare for cognitive decline is in a “shallow” medical world. With the development of data science, virtual reality, artificial intelligence, and digital twin, the introduction of the concept of the metaverse in medicine has brought alternative and complementary strategies in the intervention of cognitive decline. This article technically analyzes the application scenarios and paradigms of the metaverse in medicine in the field of mental health, such as hospital management, diagnosis, prediction, prevention, rehabilitation, progression delay, assisting life, companionship, and supervision. The metaverse in medicine has made primary progress in education, immersive consultation, dental disease, and Parkinson's disease, bringing revolutionary prospects for non-pharmacological complementary treatment of cognitive decline and other mental problems. In particular, with the demand for non-face-to-face communication generated by the global COVID-19 epidemic, the needs for uncontactable healthcare service for the elderly have increased. The paradigm of self-monitoring, self-healing, and healthcare experienced by the elderly through the metaverse in medicine, especially from meta-platform, meta-community, and meta-hospital, will be generated, which will reconstruct the service modes for the elderly people. The future map of the metaverse in medicine is huge, which depends on the co-construction of community partners.

Discovery of genistein derivatives as potential SARS-CoV-2 main protease inhibitors by virtual screening, molecular dynamics simulations and ADMET analysis.

Background: Due to the constant mutation of virus and the lack of specific therapeutic drugs, the coronavirus disease 2019 (COVID-19) pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) still poses a huge threat to the health of people, especially those with underlying diseases. Therefore, drug discovery against the SARS-CoV-2 remains of great significance. Methods: With the main protease of virus as the inhibitor target, 9,614 genistein derivatives were virtually screened by LeDock and AutoDock Vina, and the top 20 compounds with highest normalized scores were obtained. Molecular dynamics simulations were carried out for studying interactions between these 20 compounds and the target protein. The drug-like properties, activity, and ADMET of these compounds were also evaluated by DruLiTo software or online server. Results: Twenty compounds, including compound 11, were screened by normalized molecular docking, which could bind to the target through multiple non-bonding interactions. Molecular dynamics simulation results showed that compounds 2, 4, 5, 11, 13, 14, 17, and 18 had the best binding force with the target protein of SARS-CoV-2, and the absolute values of binding free energies all exceeded 50 kJ/mol. The drug-likeness properties indicated that a variety of compounds including compound 11 were worthy of further study. The results of bioactivity score prediction found that compounds 11 and 12 had high inhibitory activities against protease, which indicated that these two compounds had the potential to be further developed as COVID-19 inhibitors. Finally, compound 11 showed excellent predictive ADMET properties including high absorption and low toxicity. Conclusion: These in silico work results show that the preferred compound 11 (ZINC000111282222), which exhibited strong binding to SARS-CoV-2 main protease, acceptable drug-like properties, protease inhibitory activity and ADMET properties, has great promise for further research as a potential therapeutic agent against COVID-19.

A Human In Vitro Model to Study Adenoviral Receptors and Virus Cell Interactions.

To develop adenoviral cell- or tissue-specific gene delivery, understanding of the infection mechanisms of adenoviruses is crucial. Several adenoviral attachment proteins such as CD46, CAR and sialic acid have been identified and studied. However, most receptor studies were performed on non-human cells. Combining our reporter gene-tagged adenovirus library with an in vitro human gene knockout model, we performed a systematic analysis of receptor usage comparing different adenoviruses side-by-side. The CRISPR/Cas9 system was used to knockout CD46 and CAR in the human lung epithelial carcinoma cell line A549. Knockout cells were infected with 22 luciferase-expressing adenoviruses derived from adenovirus species B, C, D and E. HAdV-B16, -B21 and -B50 from species B1 as well as HAdV-B34 and -B35 were found to be CD46-dependent. HAdV-C5 and HAdV-E4 from species E were found to be CAR-dependent. Regarding cell entry of HAdV-B3 and -B14 and all species D viruses, both CAR and CD46 play a role, and here, other receptors or attachment structures may also be important since transductions were reduced but not completely inhibited. The established human knockout cell model enables the identification of the most applicable adenovirus types for gene therapy and to further understand adenovirus infection biology.

Gut microbiome alterations and gut barrier dysfunction are associated with host immune homeostasis in COVID-19 patients.

BACKGROUND: COVID-19 is an infectious disease characterized by multiple respiratory and extrapulmonary manifestations, including gastrointestinal symptoms. Although recent studies have linked gut microbiota to infectious diseases such as influenza, little is known about the role of the gut microbiota in COVID-19 pathophysiology. METHODS: To better understand the host-gut microbiota interactions in COVID-19, we characterized the gut microbial community and gut barrier function using metagenomic and metaproteomic approaches in 63 COVID-19 patients and 8 non-infected controls. Both immunohematological parameters and transcriptional profiles were measured to reflect the immune response in COVID-19 patients. RESULTS: Altered gut microbial composition was observed in COVID-19 patients, which was characterized by decreased commensal species and increased opportunistic pathogenic species. Severe illness was associated with higher abundance of four microbial species (i.e., Burkholderia contaminans, Bacteroides nordii, Bifidobacterium longum, and Blautia sp. CAG 257), six microbial pathways (e.g., glycolysis and fermentation), and 10 virulence genes. These severity-related microbial features were further associated with host immune response. For example, the abundance of Bu. contaminans was associated with higher levels of inflammation biomarkers and lower levels of immune cells. Furthermore, human-origin proteins identified from both blood and fecal samples suggested gut barrier dysfunction in COVID-19 patients. The circulating levels of lipopolysaccharide-binding protein increased in patients with severe illness and were associated with circulating inflammation biomarkers and immune cells. Besides, proteins of disease-related bacteria (e.g., B. longum) were detectable in blood samples from patients. CONCLUSIONS: Our results suggest that the dysbiosis of the gut microbiome and the dysfunction of the gut barrier might play a role in the pathophysiology of COVID-19 by affecting host immune homeostasis.

Computational Insights Into the Effects of the R190K and N121Q Mutations on the SARS-CoV-2 Spike Complex With Biliverdin.

The SARS-CoV-2 spike has been regarded as the main target of antibody design against COVID-19. Two single-site mutations, R190K and N121Q, were deemed to weaken the binding affinity of biliverdin although the underlying molecular mechanism is still unknown. Meanwhile, the effect of the two mutations on the conformational changes of "lip" and "gate" loops was also elusive. Thus, molecular dynamics simulation and molecular mechanics/generalized Born surface area (MM/GBSA) free energy calculation were conducted on the wild-type and two other SARS-CoV-2 spike mutants. Our simulations indicated that the R190K mutation causes Lys190 to form six hydrogen bonds, guided by Asn99 and Ile101, which brings Lys190 closer to Arg102 and Asn121, thereby weakening the interaction energy between biliverdin and Ile101 as well as Lys190. For the N121Q mutation, Gln121 still maintained a hydrogen bond with biliverdin; nevertheless, the overall binding mode deviated significantly under the reversal of the side chain of Phe175. Moreover, the two mutants would stabilize the lip loop, which would restrain the meaningful upward movement of the lip. In addition, N121Q significantly promoted the gate loop deviating to the biliverdin binding site and compressed the site. This work would be useful in understanding the dynamics binding biliverdin to the SARS-CoV-2 spike.

Ultrasensitive Detection of COVID-19 Causative Virus (SARS-CoV-2) Spike Protein Using Laser Induced Graphene Field-Effect Transistor.

COVID-19 is a highly contagious human infectious disease caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), and the war with the virus is still underway. Since no specific drugs have been made available yet and there is an imbalance between supply and demand for vaccines, early diagnosis and isolation are essential to control the outbreak. Current nucleic acid testing methods require high sample quality and laboratory conditions, which cannot meet flexible applications. Here, we report a laser-induced graphene field-effect transistor (LIG-FET) for detecting SARS-CoV-2. The FET was manufactured by different reduction degree LIG, with an oyster reef-like porous graphene channel to enrich the binding point between the virus protein and sensing area. After immobilizing specific antibodies in the channel, the FET can detect the SARS-CoV-2 spike protein in 15 min at a concentration of 1 pg/mL in phosphate-buffered saline (PBS) and 1 ng/mL in human serum. In addition, the sensor shows great specificity to the spike protein of SARS-CoV-2. Our sensors can realize fast production for COVID-19 rapid testing, as each LIG-FET can be fabricated by a laser platform in seconds. It is the first time that LIG has realized a virus sensing FET without any sample pretreatment or labeling, which paves the way for low-cost and rapid detection of COVID-19.

Enhanced Antiviral Function of Magnesium Chloride-Modified Heparin on a Broad Spectrum of Viruses.

Previous studies reported on the broad-spectrum antiviral function of heparin. Here we investigated the antiviral function of magnesium-modified heparin and found that modified heparin displayed a significantly enhanced antiviral function against human adenovirus (HAdV) in immortalized and primary cells. Nuclear magnetic resonance analyses revealed a conformational change of heparin when complexed with magnesium. To broadly explore this discovery, we tested the antiviral function of modified heparin against herpes simplex virus type 1 (HSV-1) and found that the replication of HSV-1 was even further decreased compared to aciclovir. Moreover, we investigated the antiviral effect against the new severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) and measured a 55-fold decreased viral load in the supernatant of infected cells associated with a 38-fold decrease in virus growth. The advantage of our modified heparin is an increased antiviral effect compared to regular heparin.

Nonlinear response of nitrate to NOx reduction in China during the COVID-19 pandemic.

In recent years, nitrate plays an increasingly important role in haze pollution and strict emission control seems ineffective in reducing nitrate pollution in China. In this study, observations of gaseous and particulate pollutants during the COVID-19 lockdown, as well as numerical modelling were integrated to explore the underlying causes of the nonlinear response of nitrate mitigation to nitric oxides (NOx) reduction. We found that, due to less NOx titration effect and the transition of ozone (O3) formation regime caused by NOx emissions reduction, a significant increase of O3 (by ∼ 69%) was observed during the lockdown period, leading to higher atmospheric oxidizing capacity and facilitating the conversion from NOx to oxidation products like nitric acid (HNO3). It is proven by the fact that 26-61% reduction of NOx emissions only lowered surface HNO3 by 2-3% in Hebi and Nanjing, eastern China. In addition, ammonia concentration in Hebi and Nanjing increased by 10% and 40% during the lockdown, respectively. Model results suggested that the increasing ammonia can promote the gas-particle partition and thus enhance the nitrate formation by up to 20%. The enhanced atmospheric oxidizing capacity together with increasing ammonia availability jointly promotes the nitrate formation, thereby partly offsetting the drop of NOx. This work sheds more lights on the side effects of a sharp NOx reduction and highlights the importance of a coordinated control strategy.

Disease state prediction for 2019 novel coronavirus (COVID-19) pneumonia using CT manifestations and body temperature dynamic analysis: A SQUIRE-compliant study.

ABSTRACT: 2019 Novel Coronavirus (COVID-19) is a new acute infectious disease of respiratory system, posed a great threat to human health because of its strong infectivity and rapid progress. This study aimed to assess the severity of COVID-19 Pneumonia by analyzing the change of CT manifestations and body temperature.This retrospective review included 22 patients with COVID-19 pneumonia. The imaging manifestations and clinical features were observed and evaluated.Most of the infected patients were men (13/22, 59%). Fever (>38°C) (17/22, 77%) and cough (6/22, 27%) were the main symptoms. Leukocytes count decreased in 23% of patients and lymphocyte decreased in 41%. Twenty-one patients with pneumonia had abnormal findings on chest CT. The special CT manifestations were observed at the first CT examination when the lesions progressed, including a single ground glass nodule with uneven density, multiple ground glass opacities distributed in subpleural, and the ground glass opacities confined in superior lobe. The special CT manifestations were observed at the first CT examination when the lesions resolved, including ground glass opacities with homogeneous density. The lesion involved in the bilateral lungs and the absorption of the lesions mainly occurred in bilateral inferior lobes. Three patients had normalized body temperature increased more than 1°C within 1 to 2 days after admission. Ten patients fluctuated more than 1°C within 1 to 7 days after admission and the second CT scans showed the disease was at the progressive stage.Dynamic analysis of CT manifestations and body temperature have the potential to predict the severity of COVID-19 pneumonia.

Coronary artery calcification and risk of mortality and adverse outcomes in patients with COVID-19: a Chinese multicenter retrospective cohort study.

Background: Coronary artery calcification (CAC) is an independent risk factor of major adverse cardiovascular events; however, the impact of CAC on in-hospital death and adverse clinical outcomes in patients with coronavirus disease 2019 (COVID-19) remains unclear. Objective: To explore the association between CAC and in-hospital mortality and adverse events in patients with COVID-19. Methods: This multicenter retrospective cohort study enrolled 2067 laboratory-confirmed COVID-19 patients with definitive clinical outcomes (death or discharge) admitted from 22 tertiary hospitals in China between January 3, 2020 and April 2, 2020. Demographic, clinical, laboratory results, chest CT findings, and CAC on admission were collected. The primary outcome was in-hospital death and the secondary outcome was composed of in-hospital death, admission to intensive care unit (ICU), and requiring mechanical ventilation. Multivariable Cox regression analysis and Kaplan-Meier plots were used to explore the association between CAC and in-hospital death and adverse clinical outcomes. Results: The mean age was 50 years (SD,16) and 1097 (53.1%) were male. A total of 177 patients showed high CAC level, and compared with patients with low CAC, these patients were older (mean age: 49 vs. 69 years, P < 0.001) and more likely to be male (52.0% vs. 65.0%, P = 0.001). Comorbidities, including cardiovascular disease (CVD) ([33.3%, 59/177] vs. [4.7%, 89/1890], P < 0.001), presented more often among patients with high CAC, compared with patients with low CAC. As for laboratory results, patients with high CAC had higher rates of increased D-dimer, LDH, as well as CK-MB (all P < 0.05). The mean CT severity score in high CAC group was also higher than low CAC group (12.6 vs. 11.1, P = 0.005). In multivariable Cox regression model, patients with high CAC were at a higher risk of in-hospital death (hazard ratio [HR], 1.731; 95% CI 1.010-2.971, P = 0.046) and adverse clinical outcomes (HR, 1.611; 95% CL 1.087-2.387, P = 0.018). Conclusion: High CAC is a risk factor associated with in-hospital death and adverse clinical outcomes in patients with confirmed COVID-19, which highlights the importance of calcium load testing for hospitalized COVID-19 patients and calls for attention to patients with high CAC. Supplementary Information: The online version contains supplementary material available at 10.1007/s42058-021-00072-4.

Preliminary prediction of the control reproduction number of COVID-19 in Shaanxi Province, China.

OBJECTIVES: Firstly, according to the characteristics of COVID-19 epidemic and the control measures of the government of Shaanxi Province, a general population epidemic model is established. Then, the control reproduction number of general population epidemic model is obtained. Based on the epidemic model of general population, the epidemic model of general population and college population is further established, and the control reproduction number is also obtained. METHODS: For the established epidemic model, firstly, the expression of the control reproduction number is obtained by using the next generation matrix. Secondly, the real-time reported data of COVID-19 in Shaanxi Province is used to fit the epidemic model, and the parameters in the model are estimated by least square method and MCMC. Thirdly, the Latin hypercube sampling method and partial rank correlation coefficient (PRCC) are adopted to analyze the sensitivity of the model. CONCLUSIONS: The control reproduction number remained at 3 from January 23 to January 31, then gradually decreased from 3 to slightly greater than 0.2 by using the real-time reports on the number of COVID-19 infected cases from Health Committee of Shaanxi Province in China. In order to further control the spread of the epidemic, the following measures can be taken: (i) reducing infection by wearing masks, paying attention to personal hygiene and limiting travel; (ii) improving isolation of suspected patients and treatment of symptomatic individuals. In particular, the epidemic model of the college population and the general population is established, and the control reproduction number is given, which will provide theoretical basis for the prevention and control of the epidemic in the colleges.

Black Carbon Emission Reduction Due to COVID-19 Lockdown in China.

During the Lunar New Year Holiday of 2020, China implemented an unprecedented lockdown to fight the COVID-19 outbreak, which strongly affected the anthropogenic emissions. We utilized elemental carbon observations (equivalent to black carbon, BC) from 42 sites and performed inverse modeling to determine the impact of the lockdown on the weekly BC emissions and quantify the effect of the stagnant conditions on BC observations in densely populated eastern and northern China. BC emissions declined 70% (eastern China) and 48% (northern China) compared to the first half of January. In northern China, under the stagnant conditions of the first week of the lockdown, the observed BC concentrations rose unexpectedly (29%) even though the BC emissions fell. The emissions declined substantially thereafter until a week after the lockdown ended. On the contrary, in eastern China, BC emissions dropped sharply in the first week and recovered synchronously with the end of the lockdown.

Weakened Aerosol-PBL Interaction During COVID-19 Lockdown in Northern China.

Anthropogenic emissions were greatly constrained during COVID-19 lockdown in China. Nevertheless, observations still showed high loadings of fine particles (PM2.5) over northern China with secondary aerosols increasing by 15 µg/m3 yet a ∼10% drop in light-absorbing black carbon (BC). Such a chemical transition in aerosol composition tended to make the atmosphere more scattering, indicated by satellite-retrieved aerosol absorption optical depth falling by 60%. Comparison between weather forecast and radiosonde observations illustrated that, without upper-level heating induced by BC, the stabilized stratification diminished, which was conducive for planetary boundary layer (PBL) mixing and thus near-surface pollution dispersion. Furthermore, coupled dynamic-chemistry simulations estimated that emission reduction during the lockdown weakened aerosol-PBL interaction and thus a reduction of 25 µg/m3 (∼50%) in PM2.5 enhancement. Based on the unique natural experiment, this work observationally confirmed and numerically quantified the importance of BC-induced meteorological feedback, further highlighting the priority of BC control in haze mitigation.