ABSTRACT
The H6H6 subtype avian influenza virus (AIV) is currently prevalent in wild birds and poultry. Its host range has gradually expanded to mammals, such as swines. Some strains have even acquired the ability to bind to human-like SAα-2,6 Gal receptors, thus increasing the risk of animal to human transmission. To investigate whether the H6N6 AIV can overcome interspecies barriers from poultry to mammals and even to humans, we have assessed the molecular characteristics, receptor-binding preference, replication in mice and human lungs of three chicken-originated H6N6 strains. Among these, the A/CK/Zhangzhou/346/2014 (ZZ346) virus with the P186T, H156R, and S263G mutations of the hemagglutinin molecule showed the ability to bind to avian-like SAα-2,3 Gal and human-like SAα-2,6 Gal receptors. Moreover, H6N6 viruses, especially the ZZ346 strain, could replicate and infect mice and human lungs. Our study showed the H6N6 virus binding to both avian-like and human-like receptors, confirming its ability to cross the species barrier to infect mice and human lungs without prior adaptation. This study emphasizes the importance of continuous and intense monitoring of the H6N6 evolution in terrestrial birds.
ABSTRACT
Background: Diabetic foot ulcer (DFU) in patients with type 2 diabetes mellitus (T2D) often leads to amputation. Early intervention to prevent DFU is urgently necessary. So far, there have been no studies on predictive models associated with DFU risk factors. Our study aimed to quantify the predictive risk value of DFU, promote health education, and further develop behavioral interventions to reduce the incidence of DFU. Methods: Data from 973 consecutive patients with T2D was collected from two hospitals. Patients from the Guangxi Medical University First Affiliated Hospital formed the training cohort (n = 853), and those from the Wuming Hospital of Guangxi Medical University formed the validation cohort (n = 120). Independent variable grouping analysis and multivariate logistic regression analysis were used to determine the risk factors of DFUs. The prediction model was established according to the related risk factors. In addition, the accuracy of the model was evaluated by specificity, sensitivity, predictive value, and predictive likelihood ratio. Results: In total, 369 of the 853 patients (43.3%) and 60 of the 120 (50.0%) were diagnosed with DFUs in the two hospitals. The factors associated with DFU were old age, male gender, lower body mass index (BMI), longer duration of diabetes, history of foot disease, cardiac insufficiency, no use of oral hypoglycemic agent (OHA), high white blood cell count, high platelet count, low hemoglobin level, low lymphocyte absolute value, and high postprandial blood glucose. After incorporating these 12 factors, the nomogram drawn achieved good concordance indexes of 0.89 [95% confidence interval (CI): 0.87 to 0.91] in the training cohort and 0.84 (95% CI: 0.77 to 0.91) in the validation cohort in predicting DFUs and had well-fitted calibration curves. Patients who had a nomogram score of ≥180 were considered to have a low risk of DFU, whereas those having ≥180 were at high risk. Conclusions: A nomogram was constructed by combining 12 identified risk factors of DFU. These 12 risk factors are easily available in hospitalized patients, so the prediction of DFU in hospitalized patients with T2D has potential clinical significance. The model provides a reliable prediction of the risk of DFU in patients with T2D.
