Epidemiological characteristics of COVID-19 caused by Delta SARS-CoV-2 variant in Xi'an in December 2021

OBJECTIVE: To understand the epidemiological characteristics of confirmed cases of COVID-19 in Xi 'an, Shaanxi Province during cluster outbreak and explore the prevention and control strategies for the epidemic caused by the Delta SARS-CoV-2 variant. METHODS: The confirmed cases of COVID-19 who were treated in Xi'an People's Hospital, a designated hospital, were enrolled in the study, the data of the patients such as baseline data, diagnostic types and initial symptoms were retrospectively reviewed. RESULTS: Among 703 confirmed cases of COVID-19, the gender ratio of male to female was 1.16:1, the age ranged between 10 months and 94 years old, with the median age 33 years old;the patients with mild symptoms(58.46%) and the patients with common symptoms(39.12%) were dominant. 70.13% of the patients were vaccinated with 2 doses of COVID-19 vaccine, 13.51% have not been vaccinated. In terms of the initial symptoms of COVID-19, the patients with cough accounted for 42.96%, the patients with pharyngeal symptoms accounted for 29.87%, and the patients with fever accounted for 25.60%. Totally 129 patients did not have obvious symptoms during the initial stage. There was significant difference in the influence of age and vaccination on severity of disease(P<0.05). The patients aged no less than 60 years old were the high-risk population for the severe(57.14%) and critically severe(66.67%) symptoms;the morbidity rates of severe symptoms(50.00%) and critically severe symptoms(66.67%) were high among the patients without vaccination. CONCLUSION: The local cluster outbreak caused by Delta SARS-CoV-2 variant in Xi 'an, Shaanxi province are characterized by strong transmission power and fast transmission. It is necessary to focus on the prevention and control among the populations of infants and old people, enhance the epidemiological surgery, precisely trace and isolate close contacts, identify and take interventions to illness condition in early stage. In daily prevention and control, fever, as a typical symptom, should be monitored, and it is necessary to boost the comprehensiveness and sensitivity of symptom monitoring. Universal vaccination remains one of the effective measures for protection of vulnerable populations.

Robust Covalent Aptamer Strategy Enables Sensitive Detection and Enhanced Inhibition of SARS-CoV-2 Proteins.

Aptamer-based detection and therapy have made substantial progress with cost control and easy modification. However, the conformation lability of an aptamer typically causes the dissociation of aptamer-target complexes during harsh washes and other environmental stresses, resulting in only moderate detection sensitivity and a decreasing therapeutic effect. Herein, we report a robust covalent aptamer strategy to sensitively detect nucleocapsid protein and potently neutralize spike protein receptor binding domain (RBD), two of the most important proteins of SARS-CoV-2, after testing different cross-link electrophilic groups via integrating the specificity and efficiency. Covalent aptamers can specifically convert aptamer-protein complexes from the dynamic equilibrium state to stable and irreversible covalent complexes even in harsh environments. Covalent aptamer-based ELISA detection of nucleocapsid protein can surpass the gold standard, antibody-based sandwich ELISA. Further, covalent aptamer performs enhanced functional inhibition to RBD protein even in a blood vessel-mimicking flowing circulation system. The robust covalent aptamer-based strategy is expected to inspire more applications in accurate molecular modification, disease biomarker discovery, and other theranostic fields.

Characteristics and influencing factors for Stenotrophomonas maltophilia infection in a tertiary general hospital of Sanya city and drug resistance from 2016 to 2020

OBJECTIVE: To investigate the characteristics and influencing factors for Stenotrophomonas maltophilia (SMA) infection in Sanya and analyze the drug resistance so as to provide guidance for prevention and control of infection in medical institutions. METHODS: The hospitalization data were collected from the patients with SMA infection who were hospitalized in three tertiary general hospitals of Sanya from 2016 to 2020. The characteristics of SMA infection and influencing factors for respiratory tract and non-respiratory tract SMA infection were retrospectively analyzed, and the result of drug susceptibility testing was observed. RESULTS: A total of 753 case times of patients had SMA infection, including 606 (80.48%) case times of respiratory tract infection and 147 (19.52%) case times of non-respiratory tract infection. The isolation rate was the highest in respiratory medicine department (16.73%), followed by critical care medicine department (15.67%) and neurosurgery department (12.35%). The percentages of the patients with advanced age, complications with hypertension and pulmonary diseases, tracheotomy were the higher in the respiratory tract infection group than in the non-respiratory tract infection group (P < 0.05);while the percentages of the patients with malignant tumors, bacteremia, surgery, urinary tract intubation, low immunity and use of antibiotics and immunosuppressants were the higher in the non-respiratory tract infection group than in the respiratory tract infection group (P < 0.05). The result of drug susceptibility testing showed that the drug resistance rate of the SMA strains to sulfamethoxazole-trimethoprim was only 2.39%, while the drug resistance rate to ceftazidime was as high as 74.50%. CONCLUSION: The major influencing factors for the respiratory tract SMA infection include pulmonary diseases, hypertension, advanced age and tracheotomy;the influencing factors for the non-respiratory tract SMA infection include malignant tumors, low immunity, long-term excessive use of immunosuppressants and broad-spectrum antibiotics, bacteremia, surgery and urinary tract intubation. The SMA strains isolated from the city are highly sensitive to sulfamethoxazole-trimethoprim but are highly resistant to ceftazidime and chloramphenicol. It is necessary for the hospital to reasonably use antibiotics based on the result of drug susceptibility testing.

Alterations in the Composition of Intestinal DNA Virome in Patients With COVID-19.

Patients with Coronavirus Disease 2019 (COVID-19), due to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection mainly present with respiratory issues and related symptoms, in addition to significantly affected digestive system, especially the intestinal tract. While several studies have shown changes in the intestinal flora of patients with COVID-19, not much information is available on the gut virome of such patients. In this study, we used the viromescan software on the latest gut virome database to analyze the intestinal DNA virome composition of 15 patients with COVID-19 and investigated the characteristic alternations, particularly of the intestinal DNA virome to further explore the influence of COVID-19 on the human gut. The DNA viruses in the gut of patients with COVID-19 were mainly crAss-like phages (35.48%), Myoviridae (20.91%), and Siphoviridae (20.43%) family of viruses. Compared with healthy controls, the gut virome composition of patients with COVID-19 changed significantly, especially the crAss-like phages family, from the first time of hospital admission. A potential correlation is also indicated between the change in virome and bacteriome (like Tectiviridae and Bacteroidaceae). The abundance of the viral and bacterial population was also analyzed through continuous sample collection from the gut of patients hospitalized due to COVID-19. The gut virome is indeed affected by the SARS-CoV-2 infection, and along with gut bacteriome, it may play an important role in the disease progression of COVID-19. These conclusions would be helpful in understanding the gut-related response and contribute to the treatment and prevention strategies of COVID-19.

Alterations in the Composition of Intestinal DNA Virome in Patients With COVID-19

Patients with Coronavirus Disease 2019 (COVID-19), due to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection mainly present with respiratory issues and related symptoms, in addition to significantly affected digestive system, especially the intestinal tract. While several studies have shown changes in the intestinal flora of patients with COVID-19, not much information is available on the gut virome of such patients. In this study, we used the viromescan software on the latest gut virome database to analyze the intestinal DNA virome composition of 15 patients with COVID-19 and investigated the characteristic alternations, particularly of the intestinal DNA virome to further explore the influence of COVID-19 on the human gut. The DNA viruses in the gut of patients with COVID-19 were mainly crAss-like phages (35.48%), Myoviridae (20.91%), and Siphoviridae (20.43%) family of viruses. Compared with healthy controls, the gut virome composition of patients with COVID-19 changed significantly, especially the crAss-like phages family, from the first time of hospital admission. A potential correlation is also indicated between the change in virome and bacteriome (like Tectiviridae and Bacteroidaceae). The abundance of the viral and bacterial population was also analyzed through continuous sample collection from the gut of patients hospitalized due to COVID-19. The gut virome is indeed affected by the SARS-CoV-2 infection, and along with gut bacteriome, it may play an important role in the disease progression of COVID-19. These conclusions would be helpful in understanding the gut-related response and contribute to the treatment and prevention strategies of COVID-19.

A Cluster Transmission of Coronavirus Disease 2019 and the Prevention and Control Measures in the Early Stage of the Epidemic in Xi'an, China, 2020.

BACKGROUND At the beginning of the COVID-19 pandemic, a cluster outbreak caused by an imported case from Hubei Province was reported in Xi'an City, Shaanxi Province, China. Ten patients from 2 families and 1 hospital were involved in the transmission. MATERIAL AND METHODS We conducted an epidemiological investigation to identify the cluster transmission of COVID-19. The demographic, epidemiological, clinical, laboratory, and cluster characteristics were described and analyzed. RESULTS From January 27 to February 13, 2020, a total of 10 individuals were confirmed to be infected with SARS-CoV-2 by the nucleic acid testing of nasopharyngeal swabs from 2 families and 1 hospital. Among the confirmed cases, 7 had atypical clinical symptoms and 3 were asymptomatic. The median times from onset to diagnosis and to discharge were 3.5 days (range, 1-5 days) and 19.5 days (range, 16-38 days), respectively. There were 4 patients whose exposure dates were 1, 3, 3, and 2 days earlier than the onset dates of their previous-generation cases, respectively. Four prevention and control measures were effectively used to interrupt the disease transmission. CONCLUSIONS SARS-CoV-2 can be easily transmitted within families and in hospitals, and asymptomatic patients could act as a source of disease transmission. The results of this outbreak at the early epidemic stage support the recommendation that individuals with confirmed COVID-19 and all their close contacts should be subjected to medical quarantined observation and nucleic acid screening as early as possible, even if they do not have any symptoms. Meanwhile, people in high-risk areas should improve their protective measures.

Rapid One-Step Detection of Viral Particles Using an Aptamer-Based Thermophoretic Assay.

Rapid and sensitive identification of viral pathogens such as SARS-CoV-2 is a critical step to control the pandemic disease. Viral antigen detection can compete with gold-standard PCR-based nucleic acid diagnostics in terms of better reflection of viral infectivity and reduced risk of contamination from enzymatic amplification. Here, we report the development of a one-step thermophoretic assay using an aptamer and polyethylene glycol (PEG) for direct quantitative detection of viral particles. The assay relies on aptamer binding to the spike protein of SARS-CoV-2 and simultaneous accumulation of aptamer-bound viral particles in laser-induced gradients of temperature and PEG concentration. Using a pseudotyped lentivirus model, a limit of detection of ∼170 particles µL-1 (26 fM of the spike protein) is achieved in 15 min without the need of any pretreatment. As a proof of concept, the one-step thermophoretic assay is used to detect synthetic samples by spiking viral particles into oropharyngeal swabs with an accuracy of 100%. The simplicity, speed, and cost-effectiveness of this thermophoretic assay may expand the diagnostic tools for viral pathogens.

The clinical classification of patients with COVID-19 pneumonia was predicted by Radiomics using chest CT.

ABSTRACT: In 2020, the new type of coronal pneumonitis became a pandemic in the world, and has firstly been reported in Wuhan, China. Chest CT is a vital component in the diagnostic algorithm for patients with suspected or confirmed COVID-19 infection. Therefore, it is necessary to conduct automatic and accurate detection of COVID-19 by chest CT.The clinical classification of patients with COVID-19 pneumonia was predicted by Radiomics using chest CT.From the COVID-19 cases in our institution, 136 moderate patients and 83 severe patients were screened, and their clinical and laboratory data on admission were collected for statistical analysis. Initial CT Radiomics were modeled by automatic machine learning, and diagnostic performance was evaluated according to AUC, TPR, TNR, PPV and NPV of the subjects. At the same time, the initial CT main features of the two groups were analyzed semi-quantitatively, and the results were statistically analyzed.There was a statistical difference in age between the moderate group and the severe group. The model cohort showed TPR 96.9%, TNR 99.1%, PPV98.4%, NPV98.2%, and AUC 0.98. The test cohort showed TPR 94.4%, TNR100%, PPV100%, NPV96.2%, and AUC 0.97. There was statistical difference between the two groups with grade 1 score (P = .001), the AUC of grade 1 score, grade 2 score, grade 3 score and CT score were 0.619, 0.519, 0.478 and 0.548, respectively.Radiomics' Auto ML model was built by CT image of initial COVID -19 pneumonia, and it proved to be effectively used to predict the clinical classification of COVID-19 pneumonia. CT features have limited ability to predict the clinical typing of Covid-19 pneumonia.

Umbilical cord blood-derived microglia-like cells to model COVID-19 exposure.

Microglia, the resident brain immune cells, play a critical role in normal brain development, and are impacted by the intrauterine environment, including maternal immune activation and inflammatory exposures. The COVID-19 pandemic presents a potential developmental immune challenge to the fetal brain, in the setting of maternal SARS-CoV-2 infection with its attendant potential for cytokine production and, in severe cases, cytokine storming. There is currently no biomarker or model for in utero microglial priming and function that might aid in identifying the neonates and children most vulnerable to neurodevelopmental morbidity, as microglia remain inaccessible in fetal life and after birth. This study aimed to generate patient-derived microglial-like cell models unique to each neonate from reprogrammed umbilical cord blood mononuclear cells, adapting and extending a novel methodology previously validated for adult peripheral blood mononuclear cells. We demonstrate that umbilical cord blood mononuclear cells can be used to create microglial-like cell models morphologically and functionally similar to microglia observed in vivo. We illustrate the application of this approach by generating microglia from cells exposed and unexposed to maternal SARS-CoV-2 infection. Our ability to create personalized neonatal models of fetal brain immune programming enables non-invasive insights into fetal brain development and potential childhood neurodevelopmental vulnerabilities for a range of maternal exposures, including COVID-19.

Pandemic aspect of dexamethasone: Molecular mechanisms and clinical application.

The rapid spread of coronavirus disease (COVID-19) in many countries has caused inconvenience in conducting daily life activities, and even deaths. Dexamethasone is a corticosteroid applied in clinical medicine since 1957, especially in immune therapy fields. Herein, we present the characteristics of Dexamethasone, from molecular mechanisms such as genomic and nongenomic pathways by cellular signal regulations, to clinical applications in various phases of the disease. During COVID-19 pandemic, Dexamethasone given to patients who required oxygen or ventilation therapy showed improved life efficacy.

Epidemiological characteristics of 55 patients with COVID-19 and influencing factors of critically ill patients

OBJECTIVE: To investigate the epidemiological characteristics of Corona virus disease 2019(COVID-19) and analyze the influencing factors of the critically ill patients. METHODS: The data of 55 patients with confirmed COVID-19 who were treated in Sanya Central Hospital(the Third People's Hospital of Hainan Province) were retrospectively investigated, the distribution of the infection in different populations, areas and time periods was observed, and the influencing factors of the critically ill patients were explored. RESULTS: Among the 55 patients with confirmed COVID-19, 20(36.4%) were males, and 35(63.6%) were females;32(58.2%) were more than 50 years old.As for the clinical classifications, there were 34(61.8%) patients with common type and 21(38.2%) patients with severe, critically severe type.60.0% of the confirmed cases had the history of exposure to Wuhan before the onset, and 30.9% were infected through contact with family members. Totally 53 cases were cured and discharged, with the cure rate 96.4%;2 cases died, with the mortality rate 3.6%. There was no significant difference in the distribution of genders between the patients with severe, critically severe COVID-19 and the patients with the common type. The incidence of severe, critically severe COVID-19 was associated with no less than 50 years of age, latent period no less than 7 days, delayed treatment, poor living condition, personal protection measures, underlying diseases and clinical symptoms such as fatigue complicated with chest distress(P<0.05). CONCLUSION: The history of exposure to Wuhan is the leading cause of second generation of recurrent cases. The influencing factors for the severe COVID-19 include no less than 50 years of age, latent period no less than 7 days, delayed treatment, poor living condition, poor personal protection, underlying diseases and clinical symptoms such as fatigue complicated with chest distress. It is necessary to take effective protection measures aiming at the influencing factors as early as possible so as to reduce the risk of severe COVID-19.

The study of automatic machine learning base on radiomics of non-focus area in the first chest CT of different clinical types of COVID-19 pneumonia.

To explore the possibility of predicting the clinical types of Corona-Virus-Disease-2019 (COVID-19) pneumonia by analyzing the non-focus area of the lung in the first chest CT image of patients with COVID-19 by using automatic machine learning (Auto-ML). 136 moderate and 83 severe patients were selected from the patients with COVID-19 pneumonia. The clinical and laboratory data were collected for statistical analysis. The texture features of the Non-focus area of the first chest CT of patients with COVID-19 pneumonia were extracted, and then the classification model of the first chest CT of COVID-19 pneumonia was constructed by using these texture features based on the Auto-ML method of radiomics, The area under curve(AUC), true positive rate(TPR), true negative rate (TNR), positive predictive value(PPV) and negative predictive value (NPV) of the operating characteristic curve (ROC) were used to evaluate the accuracy of the first chest CT image classification model in patients with COVID-19 pneumonia. The TPR, TNR, PPV, NPV and AUC of the training cohort and test cohort of the moderate group and the control group, the severe group and the control group, the moderate group and the severe group were all greater than 95% and 0.95 respectively. The non-focus area of the first CT image of COVID-19 pneumonia has obvious difference in different clinical types. The AUTO-ML classification model of Radiomics based on this difference can be used to predict the clinical types of COVID-19 pneumonia.