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1.
Poult Sci ; 100(7): 101210, 2021 Jul.
Article in English | MEDLINE | ID: covidwho-1283536

ABSTRACT

Avian infectious bronchitis (IB), caused by avian infectious bronchitis virus (IBV), is an acute and highly contagious disease that is extremely harmful to the poultry industry throughout the world. The cross-using of different attenuated live vaccine strains has led to the occurrence of diverse IBV serotypes. In this study, we isolated an IBV strain from a chicken farm in southwest China and designated it CK/CH/SCMY/160315. Construction of a phylogenetic tree based on full S1 gene sequence analysis suggested that CK/CH/SCMY/160315 bears similarity to GI-28, and further comparison of S1 amino acid residues revealed that CK/CH/SCMY/160315 showed mutations and deletions in many key positions between LDT3-A and other GI-28 reference strains. Importantly, CK/CH/SCMY/160315 was identified as a novel recombinant virus derived from live attenuated vaccine strains H120 (GI-1), 4/91 (GI-13), LDT3-A (GI-28), and the field strain LJL/08-1 (GI-19), identifying at least 5 recombination sites in both structural and accessory genes. Pathogenicity analysis indicated that CK/CH/SCMY/160315 caused listlessness, sneezing, huddling, head shaking, and increased antibody levels in the inoculated chickens. To further describe pathogenicity of this novel strain, we assessed viral load in different tissues and conducted hematoxylin and eosin (HE) staining of the trachea, lungs and kidneys. Our results provide evidence for the continuing evolution of IBV field strains via genetic recombination and mutation, leading to outbreaks in the vaccinated chicken populations in China.


Subject(s)
Coronavirus Infections , Infectious bronchitis virus , Poultry Diseases , Animals , Chickens , China , Coronavirus Infections/veterinary , Phylogeny
2.
Clin Infect Dis ; 72(9): e240-e248, 2021 05 04.
Article in English | MEDLINE | ID: covidwho-1216620

ABSTRACT

BACKGROUND: Recent studies have indicated that females with coronavirus disease 2019 (COVID-19) have a lower morbidity, severe case rate, and mortality and better outcome than those of male individuals. However, the reasons remained to be addressed. METHODS: To find the factors that potentially protect females from COVID-19, we recruited all confirmed patients hospitalized at 3 branches of Tongji Hospital (N = 1902), and analyzed the correlation between menstrual status (n = 509, including 68 from Mobile Cabin Hospital), female hormones (n = 78), and cytokines related to immunity and inflammation (n = 263), and the severity/clinical outcomes in female patients <60 years of age. RESULTS: Nonmenopausal female patients had milder severity and better outcome compared with age-matched men (P < .01 for both). Menopausal patients had longer hospitalization times than nonmenopausal patients (hazard ratio [HR], 1.91 [95% confidence interval {CI}, 1.06-3.46]; P = .033). Both anti-Müllerian hormone (AMH) and estradiol (E2) showed a negative correlation with severity of infection (adjusted HR, 0.146 [95% CI, .026-.824], P = .029 and 0.304 [95% CI, .092-1.001], P = .05, respectively). E2 levels were negatively correlated with interleukin (IL) 2R, IL-6, IL-8, and tumor necrosis factor alpha in the luteal phase (P = .033, P = .048, P = .054, and P = .023) and C3 in the follicular phase (P = .030). CONCLUSIONS: Menopause is an independent risk factor for female COVID-19 patients. AMH and E2 are potential protective factors, negatively correlated with COVID-19 severity, among which E2 is attributed to its regulation of cytokines related to immunity and inflammation.


Subject(s)
COVID-19 , SARS-CoV-2 , China/epidemiology , Cross-Sectional Studies , Female , Gonadal Steroid Hormones , Humans , Male , Retrospective Studies
3.
Front Med (Lausanne) ; 8: 635255, 2021.
Article in English | MEDLINE | ID: covidwho-1170094

ABSTRACT

Objective: This study was intended to investigate the relationship between COVID-19 disease and ovarian function in reproductive-aged women. Methods: Female COVID-19 patients of reproductive age were recruited between January 28 and March 8, 2020 from Tongji Hospital in Wuhan. Their baseline and clinical characteristics, as well as menstrual conditions, were recorded. Differentials in ovarian reserve markers and sex hormones (including anti-Müllerian hormone [AMH], follicle-stimulating hormone [FSH], the ratio of FSH to luteinizing hormone [LH], estradiol [E2], progesterone [P], testosterone [T], and prolactin [PRL] were compared to those of healthy women who were randomly selected and individually matched for age, region, and menstrual status. Uni- and multi-variable hierarchical linear regression analyses were performed to identify risk factors associated with ovarian function in COVID-19 women. Results: Seventy eight patients agreed to be tested for serum hormone, of whom 17 (21.79%) were diagnosed as the severe group and 39 (50%) were in the basal level group. Menstrual status (P = 0.55), menstrual volumes (P = 0.066), phase of menstrual cycle (P = 0.58), and dysmenorrhea history (P = 0.12) were similar without significant differences between non-severe and severe COVID-19 women. Significant lower serum AMH level/proportion (0.19/0.28 vs. 1.12 ng/ml, P = 0.003/0.027; AMH ≤ 1.1 ng/ml: 75/70.4 vs. 49.7%, P = 0.009/0.004), higher serum T (0.38/0.39 vs. 0.22 ng/ml, P < 0.001/0.001) and PRL (25.43/24.10 vs. 12.12 ng/ml, P < 0.001/0.001) levels were observed in basal level and the all-COVID-19 group compared with healthy age-matched control. When adjusted for age, menstrual status and parity variations in multivariate hierarchical linear regression analysis, COVID-19 disease was significantly associated with serum AMH (ß = -0.191; 95% CI: -1.177-0.327; P = 0.001), T (ß = 0.411; 95% CI: 11.154-22.709; P < 0.001), and PRL (ß = 0.497; 95% CI: 10.787-20.266; P < 0.001), suggesting an independent risk factor for ovarian function, which accounted for 3.2% of the decline in AMH, 14.3% of the increase in T, and 20.7% of the increase in PRL. Conclusion: Ovarian injury, including declined ovarian reserve and reproductive endocrine disorder, can be observed in women with COVID-19. More attention should be paid to their ovarian function under this pandemic, especially regarding reproductive-aged women. Clinical Trial Number: ChiCTR2000030015.

4.
Nat Commun ; 11(1): 5033, 2020 10 06.
Article in English | MEDLINE | ID: covidwho-834877

ABSTRACT

Soaring cases of coronavirus disease (COVID-19) are pummeling the global health system. Overwhelmed health facilities have endeavored to mitigate the pandemic, but mortality of COVID-19 continues to increase. Here, we present a mortality risk prediction model for COVID-19 (MRPMC) that uses patients' clinical data on admission to stratify patients by mortality risk, which enables prediction of physiological deterioration and death up to 20 days in advance. This ensemble model is built using four machine learning methods including Logistic Regression, Support Vector Machine, Gradient Boosted Decision Tree, and Neural Network. We validate MRPMC in an internal validation cohort and two external validation cohorts, where it achieves an AUC of 0.9621 (95% CI: 0.9464-0.9778), 0.9760 (0.9613-0.9906), and 0.9246 (0.8763-0.9729), respectively. This model enables expeditious and accurate mortality risk stratification of patients with COVID-19, and potentially facilitates more responsive health systems that are conducive to high risk COVID-19 patients.


Subject(s)
Coronavirus Infections/mortality , Machine Learning , Pandemics , Pneumonia, Viral/mortality , Aged , Betacoronavirus , COVID-19 , China/epidemiology , Female , Humans , Logistic Models , Male , Middle Aged , Neural Networks, Computer , Risk Assessment , SARS-CoV-2 , Support Vector Machine
5.
EClinicalMedicine ; 25: 100471, 2020 Aug.
Article in English | MEDLINE | ID: covidwho-689274

ABSTRACT

BACKGROUND: The ferocious global assault of COVID-19 continues. Critically ill patients witnessed significantly higher mortality than severe and moderate ones. Herein, we aim to comprehensively delineate clinical features of COVID-19 and explore risk factors of developing critical disease. METHODS: This is a Mini-national multicenter, retrospective, cohort study involving 2,387 consecutive COVID-19 inpatients that underwent discharge or death between January 27 and March 21, 2020. After quality control, 2,044 COVID-19 inpatients were enrolled. Electronic medical records were collected to identify the risk factors of developing critical COVID-19. FINDINGS: The severity of COVID-19 climbed up straightly with age. Critical group was characterized by higher proportion of dyspnea, systemic organ damage, and long-lasting inflammatory storm. All-cause mortality of critical group was 85•45%, by contrast with 0•58% for severe group and 0•18% for moderate group. Logistic regression revealed that sex was an effect modifier for hypertension and coronary heart disease (CHD), where hypertension and CHD were risk factors solely in males. Multivariable regression showed increasing odds of critical illness associated with hypertension, CHD, tumor, and age ≥ 60 years for male, and chronic obstructive pulmonary disease (COPD), chronic kidney disease (CKD), tumor, and age ≥ 60 years for female. INTERPRETATION: We provide comprehensive front-line information about different severity of COVID-19 and insights into different risk factors associated with critical COVID-19 between sexes. These results highlight the significance of dividing risk factors between sexes in clinical and epidemiologic works of COVID-19, and perhaps other coronavirus appearing in future. FUNDING: 10.13039/100000001 National Science Foundation of China.

8.
Science ; 368(6494): 1016-1020, 2020 05 29.
Article in English | MEDLINE | ID: covidwho-45712

ABSTRACT

Severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) causes the infectious disease COVID-19 (coronavirus disease 2019), which was first reported in Wuhan, China, in December 2019. Despite extensive efforts to control the disease, COVID-19 has now spread to more than 100 countries and caused a global pandemic. SARS-CoV-2 is thought to have originated in bats; however, the intermediate animal sources of the virus are unknown. In this study, we investigated the susceptibility of ferrets and animals in close contact with humans to SARS-CoV-2. We found that SARS-CoV-2 replicates poorly in dogs, pigs, chickens, and ducks, but ferrets and cats are permissive to infection. Additionally, cats are susceptible to airborne transmission. Our study provides insights into the animal models for SARS-CoV-2 and animal management for COVID-19 control.


Subject(s)
Animals, Domestic , Betacoronavirus/physiology , Coronavirus Infections , Disease Models, Animal , Disease Susceptibility , Ferrets , Pandemics , Pneumonia, Viral , Animals , Antibodies, Viral/blood , Betacoronavirus/immunology , Betacoronavirus/isolation & purification , COVID-19 , Cats , Chickens , Coronavirus Infections/transmission , Coronavirus Infections/virology , Dogs , Ducks , Feces/virology , Female , Male , Pneumonia, Viral/transmission , Pneumonia, Viral/virology , RNA, Viral/isolation & purification , Respiratory System/virology , SARS-CoV-2 , Species Specificity , Sus scrofa , Virus Attachment , Virus Replication
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