Tracking the first SARS-CoV-2 Omicron BA.5.1.3 outbreak in China.

The SARS-CoV-2 is still undergoing rapid evolution, resulting in the emergence of several variants of concern, especially the Omicron variants (B.1.1.529), which are surging worldwide. In this study, we tracked Omicron subvariant BA.5.1.3 as the causative agent in the Hainan Province wave in China, which started on 1 August 2022. This was China's first case of Omicron subvariant BA.5.1.3 and led to an indefinite total lockdown in Hainan with more than 8,500 confirmed cases. We obtained 391 whole genomes from positive nasopharyngeal swab samples in the city of Sanya in Hainan Province, which was the center of this outbreak. More than half of the infected cases were female (58%, 227/391) with a median age of 37.0 years (IQR 23.0-53.0). Median Ct values were 24.9 (IQR 22.6-27.3) and 25.2 (IQR 22.9-27.6) for ORF1ab and N genes, respectively. The total single-nucleotide polymorphism (SNP) numbers of Omicron BA.5.1.3 sampled in Sanya (median 69.0, IQR = 69.0-70.0) compared to those worldwide (median 63.0, IQR = 61.0-64.0) showed a significant difference (p < 0.05). Unique core mutations, including three non-synonymous mutations in ORF1ab (Y1064N, S2844G, and R3574K) and one synonymous mutation in ORF3a (S74S), were found. Phylogenetic analysis showed that virus from Sanya formed an independent sub-clade within the BA.5.1.3 subvariant, and could be divided into 15 haplotypes based on the S gene. The most recent common ancestor for the virus from Sanya was estimated as appearing on 5 July 2022, with 95% HPD ranging from 15 May to 20 September 2022. Thanks to our results, we were also able to delineate the mutational profile of this outbreak and highlight the importance of global genomic surveillance and data sharing.

Beneficial Effects of Melatonin on Periodontitis Management: Far More Than Oral Cavity.

Periodontitis as a highly prevalent chronic infection/inflammatory disease can eventually lead to tooth loss and masticatory dysfunction. It also has a negative impact on general health and largely impairs quality of life. The tissue destruction during periodontitis is mainly caused by the excessive immune-inflammatory response; hence, how to modulate the host's reaction is of profound importance for effective periodontal treatment and tissue protection. Melatonin, as an endogenous hormone exhibiting multiple biological functions such as circadian rhythm regulation, antioxidant, and anti-inflammation, has been widely used in general healthcare. Notably, the past few years have witnessed increasing evidence for the application of melatonin as an adjunctive approach in the treatment of periodontitis and periodontitis-related systemic comorbidities. The detailed underlying mechanisms and more verification from clinical practice are still lacking, however, and further investigations are highly required. Importantly, it is essential to establish standard guidelines in the near future for the clinical administration of melatonin for periodontal health and general wellbeing.

Personal GHG emissions accounting and the driving forces decomposition in the past 10 years

Personal greenhouse gas (PGHG) emissions were crucial for achieving carbon peak and neutrality targets. The accounting methodology and driving forces identification of PGHG emissions were helpful for the quantification and the reduction of the PGHG emissions. In this study, the methodology of PGHG emissions was developed from resource obtaining to waste disposal, and the variations of Shanghainese PGHG emissions from 2010 to 2020 were evaluated, with the driving forces analysis based on Logarithmic Mean Divisia Index (LMDI) model. It showed that the emissions decreased from 3796.05 (2010) to 3046.87 kg carbon dioxides (CO2) (2014) and then increased to 3411.35 kg CO2 (2018). The emissions from consumptions accounted for around 62.1% of the total emissions, and that from waste disposal were around 3.1%, which were neglected in most previous studies. The PGHG emissions decreased by around 0.53 kg CO2 (2019) and 405.86 kg CO2 (2020) compared to 2018 and 2019, respectively, which were mainly affected by the waste forced source separation policy and the COVID-19 pandemic. The income level and consumption GHG intensity were two key factors influencing the contractively of GHG emissions from consumption, with the contributing rate of 169.3% and − 188.1%, respectively. Energy consumption was the main factor contributing to the growth of the direct GHG emissions (296.4%), and the energy GHG emission factor was the main factor in suppressing it (− 92.2%). Green consumption, low carbon lifestyles, green levy programs, and energy structure optimization were suggested to reduce the PGHG emissions. Supplementary Information The online version contains supplementary material available at 10.1007/s43979-023-00045-9. Highlights ● The boundary of PGHG emissions developed from resource obtaining to waste disposal. ● Shanghainese PGHG emissions varied from 3004.64 to 3796.05 kgCO2 in 2010-2020. ● Around 405.86 kg CO2 decreased with the reduced consumption by COVID-19 lockdown. ● Energy consumption was the main contributor to DPGHG emissions (296.4%) increase. ● The GHG intensity was the main contributor to IPGHG emissions reduction (− 188.1%). Supplementary Information The online version contains supplementary material available at 10.1007/s43979-023-00045-9.

Multidisciplinary approach for the management of term pregnancy complicated by Eisenmenger syndrome.

Pregnancy in patients with Eisenmenger syndrome (ES) is associated with high maternal mortality rates of 30%‒50%, or even up to 65% in the case of a cesarean section (Yuan, 2016). Here, we report a case of term pregnancy complicated with ES and severe pulmonary artery hypertension (PAH), which was managed by a multidisciplinary team (MDT) and resulted in an uncomplicated delivery via elective cesarean section. The goal of this study is to emphasize the importance of multidisciplinary approach in the management of pregnancy with ES, which can profoundly improve maternal and infant outcomes.

Differences in Characteristics and Length of Stay of Elderly Emergency Patients before and after the Outbreak of COVID-19.

(1) Background: COVID-19 has spread worldwide and affected Taiwan's medical system and people's lives. This study aimed to explore the impact of medical utilization on the characteristics and length of stay (LOS) of elderly emergency department (ED) patients before and after COVID-19; (2) Methods: We gathered ED visits from January to September 2019 (pre-pandemic group) and from January to September 2020 (pandemic group). The data analysis methods included descriptive statistics, the Pearson's chi-square test, the independent sample t-test, and binary logistic regression; (3) Results: In 2020, during COVID-19, a significant decrease in ED monthly visits occurred from January; the maximum decrease was 32% in March. The average LOS during COVID-19 was shortened, with a significant reduction in diagnoses compared with the pre-pandemic period; (4) Conclusions: The threat of COVID-19 has changed the elderly's behavior in ED visits and shortened the LOS of ED. The study's results emphasize the importance of analyzing the medical utilization of elderly ED patients and understanding the medical quality of healthcare institutions. With Taiwan's rapidly aging society, the demand for healthcare increases from time to time. The overcrowding of medical attention is often a problem. The results recommend that the overcrowding problem has the opportunity to be solved.

Hyperamylasemia Caused by the Hantaan Virus: A Retrospective Study of 101 Patients with Hemorrhagic Fever with Renal Syndrome in West China.

Background: Hyperamylasemia (HA) is an inconspicuous manifestation of hemorrhagic fever with renal syndrome (HFRS) in Baoji city, West China. Hantaan virus (HTNV) is the only pathogen-caused HFRS in this region, but the knowledge about HA in the local HFRS patients has been limited. The aim of this study was to investigate the characteristics of HA and its predictive risk factors for doctors to engage in timely monitoring and dealing with the possible serious changes prewarned by HA in the early stages of the disease to improve the final outcome. Methods: All HFRS patients with and without HA (HA and nHA groups, respectively) were treated in Baoji People's Hospital. The clinical characteristics between the two groups were compared by Student's t-test or Chi-square test. The risk factors for prognosis were measured by the logistic regression analysis. The predictive effects of prognosis in clinical and laboratory parameters were analyzed by the receiver operating characteristic curves. Results: 46.53% of the patients demonstrated HA, among which 71.7% were severe and critical types of HFRS, greater than that in the nHA group (19.57%, P < 0.001). The hospitalization day and the general incidence of acute pancreatitis (AP) were longer or greater in the HA group than in the nHA group (P < 0.01). Age and the time from the onset of the first symptom to the patient being admitted to hospital (T OA) were the predictive risk factors for HA. The best cut-off values were the age of 54 years and T OA of 5.5 days. Conclusion: HTNV-induced HA is a common clinical presentation of HFRS patients in West China. It can increase the severity, the hospitalization days of patients, and the incidence of AP in HFRS. Age and T OA constituted independent risk factors for HA caused by HTNV.

Three Specific Potential Epitopes That Could Be Recognized by T Cells of Convalescent COVID-19 Patients Were Identified From Spike Protein.

The current coronavirus disease 2019 (COVID-19) vaccines are used to prevent viral infection by inducing neutralizing antibody in the body, but according to the existing experience of severe acute respiratory syndrome coronavirus (SARS) infection, T-cell immunity could provide a longer durable protection period than antibody. The research on SARS-CoV-2-specific T-cell epitope can provide target antigen for the development and evaluation of COVID-19 vaccines, which is conducive to obtain COVID-19 vaccine that can provide long-term protection. For screening specific T-cell epitopes, a SARS-CoV-2 S protein peptide library with a peptide length of 15 amino acids was synthesized. Through flow cytometry to detect percentage of IFN-γ+ T cells after mixed COVID-19 convalescent patients' peripheral blood mononuclear cell with peptide library, seven peptides (P77, P14, P24, P38, P48, P74, and P84) that can be recognized by the T cells of COVID-19 convalescent patients were found. After excluding the nonspecific cross-reactions with unexposed population, three SARS-CoV-2-specific T-cell potential epitopes (P38, P48, and P84) were finally screened with the positive reaction rates between 15.4% and 48.0% in COVID-19 convalescent patients. This study also provided the HLA allele information of peptide-positive-response COVID-19 convalescent patients, thus predicting the population coverage of these three potential epitopes. Some HLA alleles showed higher frequency of occurrence in COVID-19 patients than in total Chinese population but no HLA alleles related to the T-cell peptide response and the severity of COVID-19. This research provides three potential T-cell epitopes that are helpful for the design and efficacy evaluation of COVID-19 vaccines. The HLA information provided by this research supplies reference significance for subsequent research such as finding the relation of HLA genotype with disease susceptibility.

mRNA Vaccine: How to Meet the Challenge of SARS-CoV-2.

Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) with high infectivity, pathogenicity, and variability, is a global pandemic that severely affected public health and the world economy. The development of safe and effective vaccines is crucial to the prevention and control of an epidemic. As an emerging technology, mRNA vaccine is widely used for infectious disease prevention and control and has significant safety, efficacy, and high production. It has received support and funding from many pharmaceutical enterprises and becomes one of the main technologies for preventing COVID-19. This review introduces the current status of SARS-CoV-2 vaccines, specifically mRNA vaccines, focusing on the challenges of developing mRNA vaccines against SARS-CoV-2, and discusses the relevant strategies.

Prognostic Factors for COVID-19 Hospitalized Patients with Preexisting Type 2 Diabetes.

BACKGROUND: Type 2 diabetes (T2D) as a worldwide chronic disease combined with the COVID-19 pandemic prompts the need for improving the management of hospitalized COVID-19 patients with preexisting T2D to reduce complications and the risk of death. This study aimed to identify clinical factors associated with COVID-19 outcomes specifically targeted at T2D patients and build an individualized risk prediction nomogram for risk stratification and early clinical intervention to reduce mortality. METHODS: In this retrospective study, the clinical characteristics of 382 confirmed COVID-19 patients, consisting of 108 with and 274 without preexisting T2D, from January 8 to March 7, 2020, in Tianyou Hospital in Wuhan, China, were collected and analyzed. Univariate and multivariate Cox regression models were performed to identify specific clinical factors associated with mortality of COVID-19 patients with T2D. An individualized risk prediction nomogram was developed and evaluated by discrimination and calibration. RESULTS: Nearly 15% (16/108) of hospitalized COVID-19 patients with T2D died. Twelve risk factors predictive of mortality were identified. Older age (HR = 1.076, 95% CI = 1.014-1.143, p=0.016), elevated glucose level (HR = 1.153, 95% CI = 1.038-1.28, p=0.0079), increased serum amyloid A (SAA) (HR = 1.007, 95% CI = 1.001-1.014, p=0.022), diabetes treatment with only oral diabetes medication (HR = 0.152, 95%CI = 0.032-0.73, p=0.0036), and oral medication plus insulin (HR = 0.095, 95%CI = 0.019-0.462, p=0.019) were independent prognostic factors. A nomogram based on these prognostic factors was built for early prediction of 7-day, 14-day, and 21-day survival of diabetes patients. High concordance index (C-index) was achieved, and the calibration curves showed the model had good prediction ability within three weeks of COVID-19 onset. CONCLUSIONS: By incorporating specific prognostic factors, this study provided a user-friendly graphical risk prediction tool for clinicians to quickly identify high-risk T2D patients hospitalized for COVID-19.

Research on learning initiative Based on behavior quantization and potential value clustering

As an important learning mode, e-learning has become an important way of online learning, especially during the coronavirus pandemic. However, the separation of teaching and learning in time or space undoubtedly makes it difficult for teachers to master and supervise students' learning initiative. From the perspective of inquiry learning initiative, a learning problem model is constructed. To solve the problem of model timeliness, the learning behavior characteristics have been quantified with the guidance of time parameter. Furthermore, a cluster analysis method is proposed to group the students into different clusters, and a case study is given to verify the proposed scheme. The experimentalresults show that the proposed method can effectively identify the type of students and the degree of learning engagement.

Responses of aquatic organisms downstream from WWTPs to disinfectants and their by-products during the COVID-19 pandemic, Wuhan.

The outbreak of COVID-19 has led to the large-scale usage of chlorinated disinfectants in cities. Disinfectants and disinfection by-products (DBPs) enter rivers through urban drainage and surface runoff. We investigated the variations in residual chlorine, DBPs, and different aquatic organisms in the Hanjiang, Fuhe, and Qinglinghe Rivers in Wuhan during the COVID-19 pandemic. The sampling sites were from the wastewater treatment plant outlets to the downstream drinking water treatment plant intakes. Total residual chlorine and DBPs (dichloromethane and trichloromethane) detected in the river water ranged from 0 to 0.84 mg/L and 0 to 0.034 mg/L, respectively. The residual chlorine and DBPs showed a gradual reduction pattern related to water flow, and the concentration at intakes did not exceed the Chinese drinking water source quality standards. Phytoplankton and zooplankton densities were not significantly correlated with residual chlorine and DBPs. The fluctuations in phytoplankton resource use efficiency (RUE) and zooplankton RUE in the Fuhe River, with the highest residual chlorine, and the Qinglinghe River with the highest DBPs, were higher than those in the Hanjiang River. For benthic macroinvertebrates, the number of functional feeding groups in the Hanjiang River was higher than that in the Fuhe and Qinglinghe Rivers. The water and sediment bacterial communities in the Hanjiang River differed significantly from those in the Fuhe and Qingling Rivers. The denitrification function involved in N metabolism was stronger in the Fuhe and Qinglinghe Rivers. Structural equation modelling revealed that residual chlorine and DBPs impacted the diversity of benthos through direct and indirect effects on plankton. Although large-scale chlorine-containing disinfectants use occurred during the investigation, it did not harm the density of the detected aquatic organisms in water sources. With the regular use of chlorinated disinfectants for indoor and outdoor environments in response to the SARS-CoV-2 globally, it is still necessary to study the long-term and accumulated responses of water ecosystems exposed to chlorine-containing disinfectants.

A newly identified linear epitope on non-RBD region of SARS-CoV-2 spike protein improves the serological detection rate of COVID-19 patients.

BACKGROUND: Serological test is helpful in confirming and tracking infectious diseases in large population with the advantage of fast and convenience. Using the specific epitope peptides identified from the whole antigen as the detection antigen is sensitive and relatively economical. The development of epitope peptide-based detection kits for COVID-19 patients requires comprehensive information about epitope peptides. But the data on B cell epitope of SARS-CoV-2 spike protein is still limited. More importantly, there is a lack of serological data on the peptides in the population. In this study, we aimed to identify the B cell epitope peptides of spike protein and detect the reactivity in serum samples, for further providing data support for their subsequent serological applications. RESULTS: Two B cell linear epitopes, P104 and P82, located in non-RBD region of SARS-CoV-2 S protein were identified by indirect ELISA screening of an overlapping peptide library of the S protein with COVID-19 patients' convalescent serum. And the peptides were verified by testing with 165 serum samples. P104 has not been reported previously; P82 is contained in peptide S21P2 reported before. The positive reaction rates of epitope peptides S14P5 and S21P2, the two non-RBD region epitopes identified by Poh et al., and P82 and P104 were 77.0%, 73.9%, 61.2% and 30.3%, respectively, for 165 convalescent sera, including 30 asymptomatic patients. Although P104 had the lowest positive rate for total patients (30.3%), it exhibited slight advantage for detection of asymptomatic infections (36.7%). Combination of epitopes significantly improved the positive reaction rate. Among all combination patterns, (S14P5 + S21P2 + P104) pattern exhibited the highest positive reaction rate for all patients (92.7%), as well as for asymptomatic infections (86.7%), confirming the feasibility of P104 as supplementary antigen for serological detection. In addition, we analyzed the correlation between epitopes with neutralizing antibody, but only S14P5 had a medium positive correlation with neutralizing antibody titre (rs = 0.510, P < 0.01). CONCLUSION: Our research proved that epitopes on non-RBD region are of value in serological detection especially when combination more than one epitope, thus providing serological reaction information about the four epitopes, which has valuable references for their usage.

Risk Factors Associated With Clinical Outcomes in 323 Coronavirus Disease 2019 (COVID-19) Hospitalized Patients in Wuhan, China.

BACKGROUND: With evidence of sustained transmission in more than 190 countries, coronavirus disease 2019 (COVID-19) has been declared a global pandemic. Data are urgently needed about risk factors associated with clinical outcomes. METHODS: A retrospective review of 323 hospitalized patients with COVID-19 in Wuhan was conducted. Patients were classified into 3 disease severity groups (nonsevere, severe, and critical), based on initial clinical presentation. Clinical outcomes were designated as favorable and unfavorable, based on disease progression and response to treatments. Logistic regression models were performed to identify risk factors associated with clinical outcomes, and log-rank test was conducted for the association with clinical progression. RESULTS: Current standard treatments did not show significant improvement in patient outcomes. By univariate logistic regression analysis, 27 risk factors were significantly associated with clinical outcomes. Multivariate regression indicated age >65 years (P < .001), smoking (P = .001), critical disease status (P = .002), diabetes (P = .025), high hypersensitive troponin I (>0.04 pg/mL, P = .02), leukocytosis (>10 × 109/L, P < .001), and neutrophilia (>75 × 109/L, P < .001) predicted unfavorable clinical outcomes. In contrast, the administration of hypnotics was significantly associated with favorable outcomes (P < .001), which was confirmed by survival analysis. CONCLUSIONS: Hypnotics may be an effective ancillary treatment for COVID-19. We also found novel risk factors, such as higher hypersensitive troponin I, predicted poor clinical outcomes. Overall, our study provides useful data to guide early clinical decision making to reduce mortality and improve clinical outcomes of COVID-19.

PTP-MEG2 regulates quantal size and fusion pore opening through two distinct structural bases and substrates.

Tyrosine phosphorylation of secretion machinery proteins is a crucial regulatory mechanism for exocytosis. However, the participation of protein tyrosine phosphatases (PTPs) in different exocytosis stages has not been defined. Here we demonstrate that PTP-MEG2 controls multiple steps of catecholamine secretion. Biochemical and crystallographic analyses reveal key residues that govern the interaction between PTP-MEG2 and its substrate, a peptide containing the phosphorylated NSF-pY83 site, specify PTP-MEG2 substrate selectivity, and modulate the fusion of catecholamine-containing vesicles. Unexpectedly, delineation of PTP-MEG2 mutants along with the NSF binding interface reveals that PTP-MEG2 controls the fusion pore opening through NSF independent mechanisms. Utilizing bioinformatics search and biochemical and electrochemical screening approaches, we uncover that PTP-MEG2 regulates the opening and extension of the fusion pore by dephosphorylating the DYNAMIN2-pY125 and MUNC18-1-pY145 sites. Further structural and biochemical analyses confirmed the interaction of PTP-MEG2 with MUNC18-1-pY145 or DYNAMIN2-pY125 through a distinct structural basis compared with that of the NSF-pY83 site. Our studies thus provide mechanistic insights in complex exocytosis processes.

Chinese herbal medicine reduces mortality in patients with severe and critical Coronavirus disease 2019: a retrospective cohort study.

This study aimed to evaluate the efficacy of Chinese herbal medicine (CHM) in patients with severe/critical coronavirus disease 2019 (COVID-19). In this retrospective study, data were collected from 662 patients with severe/critical COVID-19 who were admitted to a designated hospital to treat patients with severe COVID-19 in Wuhan before March 20, 2020. All patients were divided into an exposed group (CHM users) and a control group (non-users). After propensity score matching in a 1:1 ratio, 156 CHM users were matched by propensity score to 156 non-users. No significant differences in seven baseline clinical variables were found between the two groups of patients. All-cause mortality was reported in 13 CHM users who died and 36 non-users who died. After multivariate adjustment, the mortality risk of CHM users was reduced by 82.2% (odds ratio 0.178, 95% CI 0.076-0.418; P < 0.001) compared with the non-users. Secondly, age (odds ratio 1.053, 95% CI 1.023-1.084; P < 0.001) and the proportion of severe/critical patients (odds ratio 0.063, 95% CI 0.028-0.143; P < 0.001) were the risk factors of mortality. These results show that the use of CHM may reduce the mortality of patients with severe/critical COVID-19.

[Analysis of medication regularity and pharmacodynamic characteristics of traditional Chinese medicine treatment in 444 severe cases of COVID-19].

The coronavirus disease 2019(COVID-19) is developing rapidly and posing great threat to public health. There is no effective intervention for the severe patients, and their prognosis is poor. It is worth noting that in the fight against COVID-19, China has always put equal emphasis on both Chinese and Western medicine. Traditional Chinese medicine has played an important role in the whole process. It is of great significance to discuss the rules and characteristics of the prescription of traditional Chinese medicine in the treatment of COVID-19. In this study, information was collected from 444 severe COVID-19 patients who were admitted to a hospital designated to treat patients with severe COVID-19 in Wuhan before March 20, 2020. We collected traditional Chinese medicine prescriptions for patients with severe COVID-19, referred to Chinese Pharmacopoeia to standardize the names of traditional Chinese medicine, and extract the property, flavor and channel tropism of traditional Chinese medicines to analyze the rules of the prescriptions. IBM SPSS Modeler 18.0 software was used to conduct correlation analysis of traditional Chinese medicine. Effective traditional Chinese medicines against COVID-19 was identified by the TCMATCOV platform. In the end, 1 532 effective prescriptions were included. Among them, the high-frequency drugs are Poria, Astragali Radix, Pogostemonis Herba, Armeniacae Semen Amarum, Atractylodis Macrocephalae Rhizoma, Pinelliae Rhizoma, Glycyrrhizae Radix et Rhizoma, Magnoliae Officinalis Cortex, Ephedrae Herba, Cinna-momi Ramulus. Most of the drugs have the following functions: resolving dampness, replenishing deficiency, resolving phlegm, cough, and asthma. The core combinations are Pogostemonis Herba-Poria, Astragali Radix-Pogostemonis Herba-Poria, Amomi Fructus-Poria, Amomi Fructus-Pogostemonis Herba, Amomi Fructus-Astragali Radix. The majority of the medicines are with cold and warm properties, and the proportions are 41.03% and 38.46%, respectively. The medicinal flavors are mainly concentrated in sweet and bitter, and the proportions are 34.71% and 30.58%, respectively. The meridian of the drug is more into the lung, stomach and spleen, with lung accounting for 22.87%. From the analysis of high-frequency drugs to the core combinations, one can see that the main treatment principle for severe COVID-19 is to remove internal and external dampness, protect the spleen and stomach, remove evil energy, and support righteousness. TCMATCOV platform was used to calculate the network disturbances of the high-frequency drugs. It was found that the traditional Chinese medicine with a high disturbance score accounted for a high proportion of the classic anti-COVID-19 prescriptions used by clinicians. Among them, the drugs with top scores are Ephedrae Herba, Citri Reticulatae Pericarpium, Eupatorii Herba, Platycodonis Radix, Cinnamomi Ramulus, Astragali Radix, Magnoliae Officinalis Cortex, Atractylodis Macrocephalae Rhizoma, Pogostemonis Herba, Scutellariae Radix. After a further exploration of the action targets, it was showed that disease-specific factor TNF was the target of the above ten drugs, and traditional Chinese medicine can exert anti-inflammatory and immune-modulating effects.