Dysregulation of glutamine/glutamate metabolism in COVID-19 patients: A metabolism study in African population and mini meta-analysis.

Coronavirus disease 2019 (COVID-19) remains a serious global threat. The metabolic analysis had been successfully applied in the efforts to uncover the pathological mechanisms and biomarkers of disease severity. Here we performed a quasi-targeted metabolomic analysis on 56 COVID-19 patients from Sierra Leone in western Africa, revealing the metabolomic profiles and the association with disease severity, which was confirmed by the targeted metabolomic analysis of 19 pairs of COVID-19 patients. A meta-analysis was performed on published metabolic data of COVID-19 to verify our findings. Of the 596 identified metabolites, 58 showed significant differences between severe and nonsevere groups. The pathway enrichment of these differential metabolites revealed glutamine and glutamate metabolism as the most significant metabolic pathway (Impact = 0.5; -log10P = 1.959). Further targeted metabolic analysis revealed six metabolites with significant intergroup differences, with glutamine/glutamate ratio significantly associated with severe disease, negatively correlated with 10 clinical parameters and positively correlated with SPO2 (rs = 0.442, p = 0.005). Mini meta-analysis indicated elevated glutamate was related to increased risk of COVID-19 infection (pooled odd ratio [OR] = 2.02; 95% confidence interval [CI]: 1.17-3.50) and severe COVID-19 (pooled OR = 2.28; 95% CI: 1.14-4.56). In contrast, elevated glutamine related to decreased risk of infection and severe COVID-19, the pooled OR were 0.30 (95% CI: 0.20-0.44), and 0.44 (95% CI: 0.19-0.98), respectively. Glutamine and glutamate metabolism are associated with COVID-19 severity in multiple populations, which might confer potential therapeutic target of COVID-19, especially for severe patients.

Effect of invasive mechanical ventilation on the diversity of the pulmonary microbiota.

Pulmonary microbial diversity may be influenced by biotic or abiotic conditions (e.g., disease, smoking, invasive mechanical ventilation (MV), etc.). Specially, invasive MV may trigger structural and physiological changes in both tissue and microbiota of lung, due to gastric and oral microaspiration, altered body posture, high O2 inhalation-induced O2 toxicity in hypoxemic patients, impaired airway clearance and ventilator-induced lung injury (VILI), which in turn reduce the diversity of the pulmonary microbiota and may ultimately lead to poor prognosis. Furthermore, changes in (local) O2 concentration can reduce the diversity of the pulmonary microbiota by affecting the local immune microenvironment of lung. In conclusion, systematic literature studies have found that invasive MV reduces pulmonary microbiota diversity, and future rational regulation of pulmonary microbiota diversity by existing or novel clinical tools (e.g., lung probiotics, drugs) may improve the prognosis of invasive MV treatment and lead to more effective treatment of lung diseases with precision.

Thrombocytopenia and increased risk of adverse outcome in COVID-19 patients.

Background: Thrombocytopenia was common in the coronavirus disease 2019 (COVID-19) patients during the infection, while the role of thrombocytopenia in COVID-19 pathogenesis and its relationship with systemic host response remained obscure. The study aimed to systematically evaluate the relationship between thrombocytopenia in COVID-19 patients and clinical, haematological and biochemical markers of the disease as well as adverse outcomes. Methods: To assess the relationship between abnormal platelet levels and disease progression, a multi-center retrospective cohort study was conducted. COVID-19 patients with thrombocytopenia and a sub-cohort of matched patients without thrombocytopenia were compared for their clinical manifestations, haematological disorders, biochemical parameters, inflammatory markers and clinical outcome. Results: Thrombocytopenia was present in 127 of 2,209 analyzed patients on admission. Compared with the control group, thrombocytopenia patients developed significantly higher frequency of respiratory failure (41.9% vs. 22.6%, P = 0.020), intensive care unit entrance (25.6% vs. 11.5%, P = 0.012), disseminated intravascular coagulation (45.2% vs. 10.6%, P < 0.001), more altered platelet morphology indexes and coagulation perturbation, higher levels of inflammatory markers. In addition, a significantly increased all-cause mortality (hazard ratio 3.08, 95% confidence interval 2.26-4.18, P < 0.001) was also observed in the patients with thrombocytopenia. Late development of thrombocytopenia beyond 14 days post-symptom was observed in 61 patients, from whom a comparable mortality rate yet longer duration to death was observed compared to those with early thrombocytopenia. Conclusions: Our finding from this study adds to previous evidence that thrombocytopenia is associated with adverse outcome of the disease and recommend that platelet count and indices be included alongside other haematological, biochemical and inflammatory markers in COVID-19 patients' assessment during the hospital stay.

Predicting the Hate: A GSTM Model based on COVID-19 Hate Speech Datasets

COVID-19 crisis has been accompanied by copious hate speeches widespread on social media. It reinforces the fragmentation of the world, resulting in more significant racial discrimination and distrust between people, leading to crimes, and injuring individuals spiritually or physically. Hate speech is hard to crack for a global recovery in the post-epidemic era. Conducting with Twitter datasets, this paper aims to find the key indicators that influence the trend of hate speech, then builds a Gaussian Spatio-Temporal Mixture (GSTM) model for trends prediction based on the pre-analysis. Findings show that in the early period, the participation of influential users is closely related to the emergence of sentiment peaks, and the interval time is around one week. After hate speech waves up, the indicator of total exposure becomes more critical, suggesting that grass-root release influences at this stage. Compared with three classical time-series predicting models, the GSTM model shows better peak prediction ability and lower residual mean. This work enriches the approaches of predicting unknown but foreseeable hate speeches accompanied by future pandemics.

The Influence of Personality and Demographic Characteristics on Aggressive Driving Behaviors in Eastern Chinese Drivers.

PURPOSE: Road safety research is important due to the large number of road traffic fatalities globally. This study investigated the influences of age, driving experience and other covariates on aggressive driving behavior. METHODS: A cross-sectional survey was conducted in Yixing City, Wuxi City, Jiangsu Province, China. Regression analysis was applied to explore the influences of age and driving experience and their interactions with other covariates on aggressive driving behavior. Two analyses methodologies were used to assess the simple effect of the interactions. Firstly, the Jamovi automatic analysis classification program was used to calculate the simple slope test. Second, the SPSS macro program was also used to calculate the simple slope test also. RESULTS: A total of 570 drivers (247 males, 282 females) participated in the survey. A negative correlation was found between age and aggressive driving behaviors, and a positive correlation was found between neuroticism and aggressive driving behaviors in the multiple regression analysis. Significant associations were also found between age, driving experience, and depression, as well as age, driving experience, and neuroticism. Simple slope tests showed that depressive symptoms could increase aggressive behaviors in the elderly and experienced drivers. When experiencing neuroticism, individuals with higher driving experience were more aggressive in driving than shorter experienced drivers. CONCLUSION: Age and neuroticism influenced aggressive driving behaviors. Veteran drivers could be aggressive drivers when experiencing depressive symptoms or neuroticism. Mobile intervention could be sent to the potentially risky drivers, which would be safe and broadly feasible to prevent aggressive driving behavior in the background of COVID-19.

Merbromin is a mixed-type inhibitor of 3-chyomotrypsin like protease of SARS-CoV-2.

3-chyomotrypsin like protease (3CLpro) has been considered as a promising target for developing anti-SARS-CoV-2 drugs. Herein, about 6000 compounds were analyzed by high-throughput screening using enzyme activity model, and Merbromin, an antibacterial agent, was identified as a potent inhibitor of 3CLpro. Merbromin strongly inhibited the proteolytic activity of 3CLpro but not the other three proteases Proteinase K, Trypsin and Papain. Michaelis-Menten kinetic analysis showed that Merbromin was a mixed-type inhibitor of 3CLpro, due to its ability of increasing the KM and decreasing the Kcat of 3CLpro. The binding assays and molecular docking suggested that 3CLpro possessed two binding sites for Merbromin. Consistently, Merbromin showed a weak binding to the other three proteases. Together, these findings demonstrated that Merbromin is a selective inhibitor of 3CLpro and provided a scaffold to design effective inhibitors of SARS-CoV-2.

Diversity of Macrophages in Lung Homeostasis and Diseases.

Lung macrophages play important roles in the maintenance of homeostasis, pathogen clearance and immune regulation. The different types of pulmonary macrophages and their roles in lung diseases have attracted attention in recent years. Alveolar macrophages (AMs), including tissue-resident alveolar macrophages (TR-AMs) and monocyte-derived alveolar macrophages (Mo-AMs), as well as interstitial macrophages (IMs) are the major macrophage populations in the lung and have unique characteristics in both steady-state conditions and disease states. The different characteristics of these three types of macrophages determine the different roles they play in the development of disease. Therefore, it is important to fully understand the similarities and differences among these three types of macrophages for the study of lung diseases. In this review, we will discuss the physiological characteristics and unique functions of these three types of macrophages in acute and chronic lung diseases. We will also discuss possible methods to target macrophages in lung diseases.

The impact of age on anxiety in Covid-19 patients in quarantine wardwards.

This study aimed to explore which age group out of the patients in quarantine wards with novel coronavirus pneumonia is the most susceptible to anxiety. The data of 32 Covid-19 patients isolated in the quarantine wards of the second Infectious Diseases Department of Baoding Hospital and 71 Covid-19 patients in Tangshan City Infectious Disease Hospital from January 24th to March 5th, 2020, a total of 103 patients, were analyzed. Among these patients, 97 isolated patients were scored with a self-rating anxiety scale (SAS) score seven days after quarantine, and the correlation between age and score was analyzed. These 97 isolated patients were then divided into three groups according to age: group A (up to 35 years old), group B (36-60 years), and group C (over 60 years). One-way analysis of variance was used to compare the scores among groups. The Q-test was used for pairwise comparison.P < 0.05 was considered statistically significant.There was a negative correlation between age and SAS score in isolated Covid-19 patients, and the differences in the score among groups were statistically significant. Patients under 35 years old were more prone to anxiety when they were isolated for seven days. Isolated patients aged up to 35 years old need more attention from quarantine medical staff, communication should be strengthened, and psychological intervention from psychotherapists should be given if necessary.

Risk factors for developing severe COVID-19 in China: an analysis of disease surveillance data.

BACKGROUND: COVID-19 has posed an enormous threat to public health around the world. Some severe and critical cases have bad prognoses and high case fatality rates, unraveling risk factors for severe COVID-19 are of significance for predicting and preventing illness progression, and reducing case fatality rates. Our study focused on analyzing characteristics of COVID-19 cases and exploring risk factors for developing severe COVID-19. METHODS: The data for this study was disease surveillance data on symptomatic cases of COVID-19 reported from 30 provinces in China between January 19 and March 9, 2020, which included demographics, dates of symptom onset, clinical manifestations at the time of diagnosis, laboratory findings, radiographic findings, underlying disease history, and exposure history. We grouped mild and moderate cases together as non-severe cases and categorized severe and critical cases together as severe cases. We compared characteristics of severe cases and non-severe cases of COVID-19 and explored risk factors for severity. RESULTS: The total number of cases were 12 647 with age from less than 1 year old to 99 years old. The severe cases were 1662 (13.1%), the median age of severe cases was 57 years [Inter-quartile range(IQR): 46-68] and the median age of non-severe cases was 43 years (IQR: 32-54). The risk factors for severe COVID-19 were being male [adjusted odds ratio (aOR) = 1.3, 95% CI: 1.2-1.5]; fever (aOR = 2.3, 95% CI: 2.0-2.7), cough (aOR = 1.4, 95% CI: 1.2-1.6), fatigue (aOR = 1.3, 95% CI: 1.2-1.5), and chronic kidney disease (aOR = 2.5, 95% CI: 1.4-4.6), hypertension (aOR = 1.5, 95% CI: 1.2-1.8) and diabetes (aOR = 1.96, 95% CI: 1.6-2.4). With the increase of age, risk for the severity was gradually higher [20-39 years (aOR = 3.9, 95% CI: 1.8-8.4), 40-59 years (aOR = 7.6, 95% CI: 3.6-16.3), ≥ 60 years (aOR = 20.4, 95% CI: 9.5-43.7)], and longer time from symtem onset to diagnosis [3-5 days (aOR = 1.4, 95% CI: 1.2-1.7), 6-8 days (aOR = 1.8, 95% CI: 1.5-2.1), ≥ 9 days(aOR = 1.9, 95% CI: 1.6-2.3)]. CONCLUSIONS: Our study showed the risk factors for developing severe COVID-19 with large sample size, which included being male, older age, fever, cough, fatigue, delayed diagnosis, hypertension, diabetes, chronic kidney diasease, early case identification and prompt medical care. Based on these factors, the severity of COVID-19 cases can be predicted. So cases with these risk factors should be paid more attention to prevent severity.

Influential factor and trend of specific IgG antibody titer in coronavirus disease 2019 convalescents. / 2019å† çŠ¶ç— æ¯’ç— åº·å¤è€ ç‰¹å¼‚æ€§IgGæŠ—ä½“æ•ˆä»·çš„å½±å“å› ç´ åŠå˜åŒ–è¶‹åŠ¿.

OBJECTIVES: To explore the influential factors and titer trend of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) specific IgG antibody in convalescent patients with coronavirus disease 2019 (COVID-19), and to provide theoretical basis for the feasibility of clinical treatment of convalescent plasma. METHODS: Colloidal gold immunochromatography assay was used to detect the SARS-CoV-2 specific IgG antibody and its titer in 113 convalescent patients with COVID-19 who were followed up from February 19, 2020 to April 6, 2020. The basic characteristics and treatment factors of patients in the high titer group (antibody titer≥1꞉160, n=22) and the low titer group (antibody titer <1꞉160, n=91) were analyzed. The IgG antibody titer in the high titer group was continuously monitored and the trend of titer was analyzed. RESULTS: The difference in the clinical type of COVID-19, onset time, first admission C-reactive protein, absolute value of lymphocyte, absolute value of CD19+CD3- lymphocytes, and the treatment of glucocorticoid were not statistically significant between the patients in the high titer group and the low titer group (all P>0.05). The male patients in the high titer group were more than those in the low titer group (P<0.05). The titer of SARS-CoV-2 specific IgG antibody in the high titer group decreased to less than 1꞉160 28 d after discharge. CONCLUSIONS: Male COVID-19 patients might be more likely to produce high titer SARS-CoV-2 specific IgG antibodies than female. The peak level of SARS-CoV-2 specific IgG antibody in convalescent patients is maintained for a short period. Using plasma from convalescent COVID-19 patients for treatment should be within 28 d after discharge.

Analysis of clinical characteristics of critically ill patients during prevention and control of new coronavirus pneumonia

OBJECTIVE: To analyze the clinical characteristics of critically ill patients during the prevention and control of new coronavirus pneumonia and to improve the diagnosis and treatment of critically ill patients with fever. METHODS: A retrospective case analysis method was used to collect clinical data of 80 patients admitted to the critically ill area of fever clinic in the first medical center of PLA general hospital from February to March,2020. Pharyngeal swab specimens were collected from all patients at 24 h intervals and tested for new coronavirus nucleic acid twice.At the same time, a combination of influenza A and B virus nucleic acid were determined, and lung computer tomography scan examination were performed. The differences in clinical data of patients with different blood leukocyte count groups were compared. RESULTS: All patients had negative results for new coronavirus nucleic acid tests, and 2 patients had a positive test for influnenza A virus nucleic acid. One patient was tested positive for hepatitis B virus nucleic acid. There were 60 patients(75.00%) with age over 65 years, 47 patients(58.75%) with more than two basic medical diseases, 70 patients(87.50%) with lung CT indicating lesions, 30 patients(37.50%) with acute kidney injury. Compared with patients with while blood cell count <1010~9/L, patients with WBC>=1010~9/L had higher incidence of diabetes mellitus WBC(P=0.024). There was no significant difference in retention time, body temperature, oxygenation index, and incidence of acute kidney injury between two groups of patients. CONCLUSION: The critically ill patients diagnosed in hospital had the characteristics of old age, many chronic diseases, widespread lung disease, and prone to acute kidney injury during screening. Nucleic acid detection is the most important differential diagnosis basis for the screening of new coronavirus infection.

Effect of transfusion convalescent recovery plasma in patients with coronavirus disease 2019. / 2019å† çŠ¶ç— æ¯’ç— æ‚£è€ è¾“æ³¨åº·å¤è€ æ¢å¤æœŸè¡€æµ†ç–—æ•ˆ.

OBJECTIVES: To evaluate curative effects of coronavirus disease 2019 (COVID-19) patients by the transfusion of other convalescent plasma. METHODS: Retrospective analysis of the clinical data of 18 patients with severe and critical COVID-19, who were hospitalized in the ICU of Xianghu Branch of the First Affiliated Hospital of Nanchang University from February 1 to March 15, 2020. Patients were subdivided into an experimental group (n=6, who had transfused the plasma) and an observation group (n=12, who had no plasma transfusion). Basic clinical data and prognosis indexes of these two groups were compared. Moreover, for the experimental group, the dynamic changes of blood oxygen saturation before and after the transfusion, the changes of lymphocyte absolute value 48 hours after the transfusion, and the detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) nucleic acid were analyzed. RESULTS: There were no significant differences in age, gender, blood type and other basic clinical data between the two groups (all P>0.05).There were no significant differences in ventilator machine weaning time, extracorporeal membrane oxygenation (ECMO) weaning time, body temperature recovery to normal time, and hospitalization days between these two groups (all P>0.05). For the experimental group, before, during and after the convalescent plasma transfusion, the blood oxygen saturation of all 6 patients at all time (1, 6, 8, 12, 24, 36, and 48 h) was more than 90%, and there was no significant fluctuation. There were 3 patients whose absolute value of lymphocyte was increased 48 hours after the transfusion, and the remaining was decreased. There were 5 patients whose SARS-CoV-2 nucleic acid detection turned negative 48 hours after the transfusion, accounting for 83.3%. CONCLUSIONS: Transfusion of convalescent plasma will not affect outcomesof COVID-19 patients, which can neutralize SARS-CoV-2 in patients and reduce the loading capacity of SARS-CoV-2.

Predictors of Health-Related Quality of Life and Influencing Factors for COVID-19 Patients, a Follow-Up at One Month.

OBJECTIVE: To survey the health-related quality of life (HRQoL) and its influencing factors among patients with COVID-19 in their first medical follow up. METHODS: All patients diagnosed with COVID-19 were discharged from 12 hospitals in Wenzhou, Zhejiang from Jan 17, 2020 to Mar 20, 2020. Prospectively collected and analyzed data included demographics, clinical symptoms, comorbidity, and chest CT imaging features at the first follow up, 1 month after discharge. All patients underwent the HRQoL evaluation with the Chinese version of Short-Form 36-item questionnaire (SF-36) as well as a general condition questionnaire. Factors associated with SF-36 were constructed using linear regression. Predictors of impaired physical component summary (PCS) and a mental component summary (MCS) were identified by logistic regression. RESULTS: SF-36 demonstrated a significant difference in HRQoL in patients with COVID-19, except in physical function (PF), when compared to the general Chinese population (p<0.05). The multiple linear regressions demonstrated that age was negatively associated with PF, role physical (RP), but positively associated with vitality (VT) (p<0.05). PF, bodily pain (BP), and role-emotional (RE) were negatively associated with the female sex (p<0.05). For mental health, the clinical subtypes were significant associated factors (p < 0.05). Length of stay (LOS) was strongly negatively associated with RE and RP, and positively associated with VT (p< 0.05). Logistical regression revealed that non-obese overweight (OR 3.71) and obesity (OR 3.94) were risk factors for a low PCS and female sex (OR 2.22) was a risk factor for a low MCS. CONCLUSIONS: Health-related quality of life was poor among COVID-19 patients at the 1 month follow-up. Patients suffered from significant physical and psychological impairment. Therefore, prospective monitoring of individuals exposed to SARS-CoV-2 is needed in order to fully understand the long-term impact of COVID-19, as well as to inform prompt and efficient interventions to alleviate suffering.

Mesenchymal stem cells: current clinical progress in ARDS and COVID-19.

Acute respiratory distress syndrome (ARDS) develops rapidly and has a high mortality rate. Survivors usually have low quality of life. Current clinical management strategies are respiratory support and restricted fluid input, and there is no suggested pharmacological treatment. Mesenchymal stromal cells (MSCs) have been reported to be promising treatments for lung diseases. MSCs have been shown to have a number of protective effects in some animal models of ARDS by releasing soluble, biologically active factors. In this review, we will focus on clinical progress in the use of MSCs as a cell therapy for ARDS, which may have clinical implications during the coronavirus disease 2019 (COVID-19) pandemic.

A Multicentre Study of 2019 Novel Coronavirus Disease Outcomes of Cancer Patients in Wuhan, China (preprint)

Background: At present, there is a global pandemic of coronavirus disease 2019 (COVID-19) pneumonia. Two previous case series from China have suggested that cancer patients are at a higher risk of COVID-19 pneumonia, but the reports were limited by small numbers and few clinical information. Objective: To study clinical characteristics and outcomes of cancer patients infected with COVID-19. Design: Retrospective study. Setting: Four designated COVID-16 hospitals in Wuhan, Hubei province, China. Participants: Medical records of 67 cancer patients admitted to hospitals between Jan 5, 2020 to Feb 18, 2020 were included. Measurements: Demographic, clinical, laboratory, radiological and treatment data were collected. Survival data of the cohort was cut-off on Mar 10, 2020. Results: Of the 67 patients (median age: 66 years), the median age of patients who had severe illness was older than that of patients who had mild symptoms (P<0.001). Forty-three (64.2%) patients had other concurrent chronic diseases, and the proportion of severe patients had co-morbidities was higher than patients with mild disease (P=0.004). Twenty-three (34.3%) patients were still at the anticancer treatment phase, but no tumour progression and recurrence was observed for all the patients during the treatment of COVID-19 pneumonia. About 70% of these patients had fever (n=53, 79.1%) and/or cough (n=50, 74.6%). Lymphocytopenia was the main laboratory finding accompanying increased C-reactive protein and procalcitonin in cancer patients, especially in severe cases. By Mar 10, 2020, 18 (26.9%) patients died from COVID-19, and 39 (58.2%) patients have been discharged. The median age of survivors was younger than that of deaths (P=0.014). Lung cancer (n=15, 22.4%) with COVID-19 was the most common cancer type and accounted for the highest proportion COVID-19 resulted deaths (33.3%, 5/15). We observed a tendency that patients at the follow-up phase had a better prognosis than that at anticancer treatment phase (P=0.095). Limitation: This is a retrospective study with only 67 cases from four hospitals. And some specific clinical information was insufficient. Conclusion: This study showed COVID-19 patients with cancer seem to have a higher proportion of severe cases and poorer prognosis. The tendency of poor prognosis was more obvious in patients at anticancer treatment phase. We should pay more intensive attentions to cancer patients infected with COVID-19.