In China, the broad prevalence of H6 subtype influenza viruses, increasingly detected in aquatic birds, promotes their exchange materials with other highly pathogenic human-infecting H5N1, H5N6, and H7N9 influenza viruses. Strikingly, some H6 subtype viruses can infect pigs, dogs, and humans, posing risks to public health. In this study, 9 H6N2 viruses recovered from waterfowl species in the Guangdong province of China in 2018 were isolated and sequenced. Phylogenetic analysis revealed that the genome sequences of these H6N2 viruses belonged to Group I, except for the NP gene in Group III. Coalescent analyses demonstrated that the reassortment of NA and NS genes have occurred in two independent clusters, suggesting H6 subtype viruses had been undergoing a complex reassortant. To examine the evolutionary dynamics and the dissemination of the H6 subtype viruses, a Bayesian stochastic search variable selection was performed for results showing higher viral migration rates between closer provinces, including Guangdong, Jiangxi, Guangxi, and Fujian. Notably, the transmission routes of the H6 subtype viruses were concentrated in Jiangxi Province, the most frequent location for input and output transmission and a region containing Poyang Lake, a well-known wintering site for migration birds. We also found that the aquatic birds, especially ducks, were the most common input source of the viral transmission. In addition, we also found that eight positively selected amino acid sites were identified in HA protein. Given their continuous dissemination and the broad prevalence of the H6 subtype influenza viruses, continued surveillance is warranted in the future.

Angiotensin-converting enzyme (ACE) gene 2350G>A polymorphism has the most significant effect on plasma ACE concentrations. But the association between this polymorphism and myocardial infarction (MI) is presently unknown. We carried out a case-control study in the Chinese Han population. ACE2350G>A genotypes of 231 patients with MI and 288 healthy controls were detected by PCR-RFLP. Differences in frequencies of ACE genotypes and alleles and their associations with clinical features were assessed. The distribution of the ACE2350G>A genotypes (GG, GA, and AA) was 20.78%, 51.08%, and 28.14% in the MI group and 31.60%, 46.53%, and 21.87% in controls, respectively (P = .0167).The frequency of the A allele in the MI group was significantly higher than that in controls (53.68% vs 45.14%, P = .0062). The A allele carriers (GA + AA genotypes) had approximately 2-fold increased risk of MI when compared with the GG genotype (odds ratio = 1.76; 95% confidence interval = 1.24-3.52). There were no significant differences among the 3 genotypes in plasma levels of lipids, apolipoproteins, high-sensitivity C-reactive protein, and soluble CD40 ligand in either the MI group or the control group (P > .05). No statistical difference was observed between ACE2350G>A polymorphism and severity of the coronary lesions (P > .05). These results suggest that ACE2350G>A polymorphism is associated with acute MI, and A allele carrier is an independent risk factor for acute MI in the Chinese Han population.

Introduction Talaromyces marneffei ( T . marneffei ), a dimorphic fungus, causes local or disseminated infection in humans. We aimed to analyze the clinical characteristics, prognostic factors, and survival outcomes of patients with T . marneffei infection and compare the differences between human immunodeficiency virus (HIV)-positive and HIV-negative subgroups. Methods We retrospectively analyzed 241 patients with T . marneffei infection at the First Affiliated Hospital of Guangxi Medical University between January 2012 and January 2022. The overall population was stratified into HIV-positive ( n = 98) and HIV-negative ( n = 143) groups according to HIV status. Kaplan–Meier analysis and multivariate Cox regression models were used to determine the prognostic factors for overall survival (OS) and progression-free survival (PFS). Results With a median follow-up time of 58.9 months, 120 patients (49.8%) experienced disease progression and 85 patients (70.8%) died. The 5-year rates of OS and PFS were 61.4% (95% CI 55.0–68.6%) and 47.8% (95% CI 41.5–55.1%), respectively. As an independent factor, patients who were HIV positive had better PFS (HR 0.50, 95% CI 0.31–0.82; p < 0.01) than patients who were HIV negative. Compared with patients who were HIV positive, patients who were HIV negative were older and had more probabilities of underlying diseases, chest involvement, bone destruction, and higher count of neutrophils (all p < 0.05). Hemoglobin (PFS: HR 0.62; 95% CI 0.39–1.00; p < 0.05; OS: HR 0.45; 95% CI 0.22–0.89; p = 0.02) and lymphocyte count (PFS: HR 0.06; 95% CI 0.01–0.26; p < 0.01; OS: HR 0.08; 95% CI 0.01–0.40; p < 0.01) were independent prognostic factors for PFS and OS in patients who were HIV negative. Conclusions Patients with T . marneffei infection have a poor prognosis. Patients who are HIV positive and HIV negative have relatively independent clinical characteristics. Multiple organ involvement and disease progression are more common in patients who are HIV negative. Supplementary Information The online version contains supplementary material available at 10.1007/s40121-023-00801-5.

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To improve the coordination and complementarity of multiple energy sources, balancing the interests of different participants in a multi-energy system is of great importance. However, traditional centralized optimization can hardly reflect the game relationship between supply side and demand sides. A trading model based on the Stackelberg game model is proposed in this paper to balance the interests of the supply side and demand side and reduce the carbon emissions. First of all, the process of trading between the supply side and demand side based on smart contracts is described. A contractual consensus is obtained through an internal game, and the transaction is completed automatically. Secondly, a bilevel optimization model is established to coordinate the benefits of both parties based on the Stackelberg game model. The energy operator acts as a leader, and considers the two objectives, i.e., maximizing net income and minimizing carbon emissions, and uses the linear weighting method to convert the dual objectives into single objective. Users act as followers and aim to increase the comprehensive benefits, including energy cost and comfort. Then, Karush–Kuhn–Tucker optimality condition is used to transform the bilevel optimization model into an equivalent single-level model. Finally, simulation results show that the proposed method can coordinate the economic interests of both sides of supply and demand and effectively reduce the carbon emissions of the energy operator.

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