Predicting DNA-binding protein and coronavirus protein flexibility using protein dihedral angle and sequence feature.

The flexibility of protein structure is related to various biological processes, such as molecular recognition, allosteric regulation, catalytic activity, and protein stability. At the molecular level, protein dynamics and flexibility are important factors to understand protein function. DNA-binding proteins and Coronavirus proteins are of great concern and relatively unique proteins. However, exploring the flexibility of DNA-binding proteins and Coronavirus proteins through experiments or calculations is a difficult process. Since protein dihedral rotational motion can be used to predict protein structural changes, it provides key information about protein local conformation. Therefore, this paper introduces a method to improve the accuracy of protein flexibility prediction, DihProFle (Prediction of DNA-binding proteins and Coronavirus proteins flexibility introduces the calculated dihedral Angle information). Based on protein dihedral Angle information, protein evolution information, and amino acid physical and chemical properties, DihProFle realizes the prediction of protein flexibility in two cases on DNA-binding proteins and Coronavirus proteins, and assigns flexibility class to each protein sequence position. In this study, compared with the flexible prediction using sequence evolution information, and physicochemical properties of amino acids, the flexible prediction accuracy based on protein dihedral Angle information, sequence evolution information and physicochemical properties of amino acids improved by 2.2% and 3.1% in the nonstrict and strict conditions, respectively. And DihProFle achieves better performance than previous methods for protein flexibility analysis. In addition, we further analyzed the correlation of amino acid properties and protein dihedral angles with residues flexibility. The results show that the charged hydrophilic residues have higher proportion in the flexible region, and the rigid region tends to be in the angular range of the protein dihedral angle (such as the ψ angle of amino acid residues is more flexible than rigid in the range of 91°-120°). Therefore, the results indicate that hydrophilic residues and protein dihedral angle information play an important role in protein flexibility.

Clinical Value of Platelets and Coagulation Parameters in Predicting the Severity of Delta Variant SARS-CoV-2.

INTRODUCTION: The present study aimed to analyze the clinical features and laboratory markers of patients with Delta variant SARS-CoV-2 and explore the role of platelet in predicting the severity of Delta. METHODS: This retrospective, observational study was conducted on 863 patients laboratory-confirmed Delta variant SARS-CoV-2. These cases were sub-classified based on disease severity into mild (n = 304), moderate (n = 537), and severe (n = 22). A series of laboratory findings and clinical data were collected and analyzed during hospitalization. RESULTS: Of 863 hospitalized patients with Delta, the median age was 38 years (interquartile range, 30-51 years) and 471 (54.58%) were male. The most common clinical symptoms mainly included cough, fever, pharyngalgia, expectoration, dyspnea, fatigue, and headache, and the commonest comorbidities were hypertension and diabetes. Among the hematological variables, neutrophil count, red blood cell count, and hemoglobin, were found to be statistically significant with regard to subcategories based of disease severity (p < 0.05). Among coagulation parameters, there was a statistically significant difference in D-dimer, fibrinogen, international normalized ratio, and prothrombin time (p < 0.05). Statistically significant differences were observed in platelet markers including platelet count, large platelet count, and plateletcrit (p < 0.05). Additionally, there was strong correlation between platelet and other parameters with disease severity. Logistical regression analysis and ROC curves showed that D-dimer was a single best marker of disease severity (p = 0.005, p < 0.0001); however, platelet (p = 0.009, p = 0.002) and plateletcrit (p = 0.002, p = 0.001) could also predict severe disease. Platelet was identified as an independent risk factor for severe Delta. CONCLUSION: Low platelet may be a marker of disease severity in Delta variant SARS-CoV-2 and may contribute to determine the severity of patients infected with Delta.

Possible transmission of COVID-19 epidemic by a dog as a passive mechanical carrier of SARS-CoV-2, Chongqing, China, 2022.

An outbreak of coronavirus disease 2019 (COVID-19) was reported in Yongchuan district of Chongqing, China in March 2022, while the source was unknown. We aimed to investigate the origin and transmission route of the virus in the outbreak. We conducted field investigations for all cases and collected their epidemiological and clinical data. We performed gene sequencing and phylogenetic analysis for the cases, and draw the epidemic curve and the case relationship chart to analyze interactions and possible transmission mode of the outbreak. A total of 11 cases of COVID-19, including 5 patients and 6 asymptomatic cases were laboratory-confirmed in the outbreak. The branch of the virus was Omicron BA.2 which was introduced into Yongchuan district by a traveler in early March. Patient F and asymptomatic case G had never contact with other positive-infected individuals, but close contact with their pet dog that sniffed the discarded cigarette butts and stepped on the sputum of patient B. Laboratory test results showed that the dog hair and kennel were positive for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), and the 10 isolates were highly homologous to an epidemic strain in a province of China. The investigation suggested that the contaminated dog by SARS-CoV-2 can act as a passive mechanical carrier of the virus and might transmit the virus to humans through close contact. Our findings suggest that during the COVID-19 pandemic, increasing hygiene measures and hand washing after close contact with pets is essential to minimize the risk of community spread of the virus.

Lymphocyte blood levels that remain low can predict the death of patients with COVID-19.

ABSTRACT: The outbreak of coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been rapidly spreading on a global scale and poses a great threat to human health. However, efficient indicators for disease severity have not been fully investigated. Here, we aim to investigate whether dynamic changes of lymphocyte counts can predict the deterioration of patients with COVID-19.We collected data from 2923 patients with laboratory-confirmed COVID-19. Patients were then screened, and we focused on 145 severe cases and 60 critical cases (29 recovered cases, 31 deaths). The length of hospitalization was divided into five time points, namely admission, 25%, 50%, 75% and discharge or death, according to the principle of interquartile distance. A series of laboratory findings and clinical data were collected and analyzed during hospitalization. The results showed that there were differences in levels of leukocytes, neutrophils and lymphocytes at almost every time point in the severe cases and 60 critical cases (29 recovered cases, 31 deaths). Further analysis showed that 70.2% of the COVID-19 cases had low circulating lymphocyte count, of which 64.1% were severe cases and 85.0% were critical cases (75.9% recovered cases and 93.5% died). Moreover, the lymphocyte count in dead cases was significantly lower than that of critical cases who recovered, at almost every time point in the critical groups. We also divided critical patients into group A (<1.1 × 109/L) and group B (>1.1 × 109/L) according to number of lymphocytes. Through survival analysis, we found that there was no significant difference in survival between group A and group B at admission (P = .3065). However, the survival rate according to lymphocyte levels in group A was significantly lower than that of group B at 25% hospital stay (on average day 6.5), 50% and 75% time points (P < .001).Lymphocyte counts that remain lower after the first week following symptom onset are highly predictive of in-hospital death of adults with COVID-19. This predictor may help clinicians identify patients with a poor prognosis and may be useful for guiding clinical decision-making at an early stage.

α-HBDH Is a Probably Higher Sensitive and Specific the Biomarkers of Poor Prognosis in Patients With COVID-19 (preprint)

Background: The coronavirus disease 2019 (COVID-19) that is caused by the severe acute respiratory syndrome-coronavirus2 (SARS-CoV2) has spread rapidly worldwide during the past nearly a year. SARS-CoV-2 particles spread through the respiratory mucosa and infect other cells, causing a storm of cytokines in the body 1 , producing a series of immune responses, and causing multiple organ dysfunction, including the heart. Some patients present with cardiovascular system damage, such as palpitations and shortness of breath as the first or secondary symptoms. Previous studies suggested that LDH, α-HBDH, CK and CK-MB reflect myocardial function. 2 Here, we aim to investigate whether these markers can predict poor prognosis of patients with COVID-19. Methods: : We collected data from 2338 patients with laboratory-confirmed COVID-19. Patients were then screened, and we focused on 49 moderate cases, 98 severe cases and 53 critical cases (27 recovered cases, 26 deaths). We divided these patients into non-critical group (n = 49) and critical group (n = 151). Then, we also divided the length of hospitalization into five time points, namely admission, 25%, 50%, 75% and discharge or death, according to the principle of interquartile distance. Blood was collected from patients on the above five time points. Patients with five blood tests were 49 moderate cases, 98 severe cases and 53 critical cases (27 recovered cases, 26 deaths). LDH, α-HBDH, CK and CK-MB of each group were collected for analysis. Results: : Our research found that α-HBDH and LDH of the critical groups significantly increased, diagnostic efficiency of LDH and α-HBDH have more advantages than that of CK and CK-MB compared with the non-critical group, and patients with α-HBDH greater than 182IU/L and LDH greater than 250IU/L at admission had lower survival rates. Then, CK, LDH, α-HBDH and CK-MB were observed dynamically in the 49 moderate cases, 98 severe cases and 53 critical cases (27 recovered cases, 26 deaths). It turns out that they increased progressively in the dead patients, while they decreased regularly in the severe case and the critical cases(recovered)(P＜0.001). Conclusions: : The prognosis of patients with abnormal α-HBDH was poor on admission. α-HBDH is a probably higher sensitive and specific the biomarkers of poor prognosis in patients with COVID-19. This predictor may help clinicians identify patients with a poor prognosis and may be useful for guiding clinical decision-making at an early stage.

Automated detection and quantification of COVID-19 pneumonia: CT imaging analysis by a deep learning-based software.

BACKGROUND: The novel coronavirus disease 2019 (COVID-19) is an emerging worldwide threat to public health. While chest computed tomography (CT) plays an indispensable role in its diagnosis, the quantification and localization of lesions cannot be accurately assessed manually. We employed deep learning-based software to aid in detection, localization and quantification of COVID-19 pneumonia. METHODS: A total of 2460 RT-PCR tested SARS-CoV-2-positive patients (1250 men and 1210 women; mean age, 57.7 ± 14.0 years (age range, 11-93 years) were retrospectively identified from Huoshenshan Hospital in Wuhan from February 11 to March 16, 2020. Basic clinical characteristics were reviewed. The uAI Intelligent Assistant Analysis System was used to assess the CT scans. RESULTS: CT scans of 2215 patients (90%) showed multiple lesions of which 36 (1%) and 50 patients (2%) had left and right lung infections, respectively (> 50% of each affected lung's volume), while 27 (1%) had total lung infection (> 50% of the total volume of both lungs). Overall, 298 (12%), 778 (32%) and 1300 (53%) patients exhibited pure ground glass opacities (GGOs), GGOs with sub-solid lesions and GGOs with both sub-solid and solid lesions, respectively. Moreover, 2305 (94%) and 71 (3%) patients presented primarily with GGOs and sub-solid lesions, respectively. Elderly patients (≥ 60 years) were more likely to exhibit sub-solid lesions. The generalized linear mixed model showed that the dorsal segment of the right lower lobe was the favoured site of COVID-19 pneumonia. CONCLUSION: Chest CT combined with analysis by the uAI Intelligent Assistant Analysis System can accurately evaluate pneumonia in COVID-19 patients.