METTL3 aggravates cell damage induced by Streptococcus pneumoniae via the NEAT1/CTCF/MUC19 axis.

Disruption of the alveolar barrier can trigger acute lung injury. This study elucidated the association of methyltransferase-like 3 (METTL3) with Streptococcus pneumoniae (SP)-induced apoptosis and inflammatory injury of alveolar epithelial cells (AECs). AECs were cultured and then infected with SP. Furthermore, the expression of METTL3, interleukin (IL)-10, IL-6, tumor necrosis factor-alpha (TNF-α), monocyte chemoattractant protein-1 (MCP-1), long noncoding RNA nuclear paraspeckle assembly transcript 1 (NEAT1), mucin 19 (MUC19), N6-methyladenosine (m6A), and NEAT1 after m6A modification were detected by qRT-PCR, Western blot, and enzyme-linked immunosorbent, m6A quantification, and methylated RNA immunoprecipitation-qPCR analyses, respectively. Moreover, the subcellular localization of NEAT1 was analyzed by nuclear/cytosol fractionation assay, and the binding between NEAT1 and CCCTC-binding factor (CTCF) was also analyzed. The results of this investigation revealed that SP-induced apoptosis and inflammatory injury in AECs and upregulated METTL3 expression. In addition, the downregulation of METTL3 alleviated apoptosis and inflammatory injury in AECs. METTL3-mediated m6A modification increased NEAT1 and promoted its binding with CTCF to facilitate MUC19 transcription. NEAT1 or MUC19 overexpression disrupted their protective role of silencing METTL3 in AECs, thereby increasing apoptosis and inflammatory injury. In conclusion, this is the first study to suggest that METTL3 aggravates SP-induced cell damage via the NEAT1/CTCF/MUC19 axis.

Medium-term exposure to size-fractioned particulate matter and asthma exacerbations in China: A longitudinal study of asthmatics with poor medication adherence.

BACKGROUND: Studies have shown that short- and long-term exposure to particulate matter (PM) can increase the risk of asthma morbidity and mortality. However, the effect of medium-term exposure remains unknown. We aim to examine the effect of medium-term exposure to size-fractioned PM on asthma exacerbations among asthmatics with poor medication adherence. METHODS: We conducted a longitudinal study in China based on the National Mobile Asthma Management System Project that specifically and routinely followed asthma exacerbations in asthmatics with poor medication adherence from April 2017 to May 2019. High-resolution satellite remote-sensing data were used to estimate each participant's medium-term exposure (on average 90 days) to size-fractioned PM (PM1, PM2.5, and PM10) based on the residential address and the date of the follow-up when asthma exacerbations (e.g., hospitalizations and emergency room visits) occurred or the end of the follow-up. The Cox proportional hazards model was employed to examine the hazard ratio of asthma exacerbations associated with each PM after controlling for sex, age, BMI, education level, geographic region, and temperature. RESULTS: Modelling results revealed nonlinear exposure-response associations of asthma exacerbations with medium-term exposure to PM1, PM2.5, and PM10. Specifically, for emergency room visits, we found an increased hazard ratio for PM1 above 22.8 µg/m3 (1.060, 95 % CI: 1.025-1.096, per 1 µg/m3 increase), PM2.5 above 38.2 µg/m3 (1.032, 95 % CI: 1.010-1.054), and PM10 above 78.6 µg/m3 (1.019, 95 % CI: 1.006-1.032). For hospitalizations, we also found an increased hazard ratio for PM1 above 20.3 µg/m3 (1.055, 95 % CI: 1.001-1.111) and PM2.5 above 39.2 µg/m3 (1.038, 95 % CI: 1.003-1.074). Furthermore, the effects of PM were greater for a longer exposure window (90-180 days) and among participants with a high BMI. CONCLUSION: This study suggests that medium-term exposure to PM is associated with an increased risk of asthma exacerbations in asthmatics with poor medication adherence, with a higher risk from smaller PM.

Molecular and metabolic insights into purplish leaf coloration through the investigation of two mulberry (Morus alba) genotypes.

BACKGROUND: Leaf coloration in plants, attributed to anthocyanin compounds, plays a crucial role in various physiological functions, and also for pharmaceutical and horticultural uses. However, the molecular mechanisms governing leaf coloration and the physiological significance of anthocyanins in leaves remain poorly understood. RESULTS: In this study, we investigated leaf color variation in two closely related mulberry genotypes, one with purplish-red young leaves (EP) and another with normal leaf color (EW). We integrated transcriptomic and metabolomic approaches to gain insights into the metabolic and genetic basis of purplish-red leaf development in mulberry. Our results revealed that flavonoid biosynthesis, particularly the accumulation of delphinidin-3-O-glucoside, is a key determinant of leaf color. Additionally, the up-regulation of CHS genes and transcription factors, including MYB family members, likely contributes to the increased flavonoid content in purplish-red leaves. CONCLUSION: These findings enhance our understanding of the molecular mechanisms responsible for the purplish coloration observed in mulberry leaves and also offer supporting evidence for the hypothesis that anthocyanins serve a protective function in plant tissues until the processes of light absorption and carbon fixation reach maturity, thereby ensuring a balanced equilibrium between energy capture and utilization.

Short-term residential exposure to air pollution and risk of acute myocardial infarction deaths at home in China.

Air pollution remains a major threat to cardiovascular health and most acute myocardial infarction (AMI) deaths occur at home. However, currently established knowledge on the deleterious effect of air pollution on AMI has been limited to routinely monitored air pollutants and overlooked the place of death. In this study, we examined the association between short-term residential exposure to China's routinely monitored and unmonitored air pollutants and the risk of AMI deaths at home. A time-stratified case-crossover analysis was undertaken to associate short-term residential exposure to air pollution with 0.1 million AMI deaths at home in Jiangsu Province (China) during 2016-2019. Individual-level residential exposure to five unmonitored and monitored air pollutants including PM1 (particulate matter with an aerodynamic diameter ≤ 1 µm) and PM2.5 (particulate matter with an aerodynamic diameter ≤ 2.5 µm), SO2 (sulfur dioxide), NO2 (nitrogen dioxide), and O3 (ozone) was estimated from satellite remote sensing and machine learning technique. We found that exposure to five air pollutants, even below the recently released stricter air quality standards of the World Health Organization (WHO), was all associated with increased odds of AMI deaths at home. The odds of AMI deaths increased by 20% (95% confidence interval: 8 to 33%), 22% (12 to 33%), 14% (2 to 27%), 13% (3 to 25%), and 7% (3 to 12%) for an interquartile range increase in PM1, PM2.5, SO2, NO2, and O3, respectively. A greater magnitude of association between NO2 or O3 and AMI deaths was observed in females and in the warm season. The greatest association between PM1 and AMI deaths was found in individuals aged ≤ 64 years. This study for the first time suggests that residential exposure to routinely monitored and unmonitored air pollutants, even below the newest WHO air quality standards, is still associated with higher odds of AMI deaths at home. Future studies are warranted to understand the biological mechanisms behind the triggering of AMI deaths by air pollution exposure, to develop intervention strategies to reduce AMI deaths triggered by air pollution exposure, and to evaluate the cost-effectiveness, accessibility, and sustainability of these intervention strategies.

The Regulatory Networks of the Circadian Clock Involved in Plant Adaptation and Crop Yield.

Global climatic change increasingly threatens plant adaptation and crop yields. By synchronizing internal biological processes, including photosynthesis, metabolism, and responses to biotic and abiotic stress, with external environmental cures, such as light and temperature, the circadian clock benefits plant adaptation and crop yield. In this review, we focus on the multiple levels of interaction between the plant circadian clock and environmental factors, and we summarize recent progresses on how the circadian clock affects yield. In addition, we propose potential strategies for better utilizing the current knowledge of circadian biology in crop production in the future.

Subcutaneous Adipose Tissue Is Associated with Acute Kidney Injury after Abdominal Trauma Based on the Generalized Propensity Score Approach: A Retrospective Cohort Study.

INTRODUCTION: Obesity is associated with an increased risk of acute kidney injury (AKI) after trauma. However, the associations between different adipose tissue depots and AKI remain unknown. Our study aimed to quantify the effect of abdominal adiposity on AKI in trauma patients. METHODS: We performed a retrospective cohort study of abdominal trauma patients who were admitted to our hospital from January 2010 to March 2020. Abdominal visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT) were measured at the level of the third lumbar vertebra using computed tomography. Causal modeling based on the generalized propensity score was used to quantify the effects of body mass index (BMI), VAT, and SAT on AKI. RESULTS: Among 324 abdominal trauma patients, 67 (20.68%) patients developed AKI. Patients with AKI had higher BMI (22.46 kg/m2 vs. 22.04 kg/m2, p = 0.014), higher SAT areas (89.06 cm2 vs. 83.39 cm2, p = 0.151), and higher VAT areas (140.02 cm2 vs. 91.48 cm2, p = 0.001) than those without AKI. By using causal modeling, we found that the risk of developing AKI increased by 8.3% (p = 0.001) and 4.8% (p = 0.022) with one unit increase in BMI (per 1 kg/m2) and ten units increase in SAT (per 10 cm2), respectively. However, VAT did not show a significant association with AKI (p = 0.327). CONCLUSION: SAT, but not VAT, increased the risk of AKI among abdominal trauma patients. Measurement of SAT might help identify patients at higher risk of AKI.

Real-Time Prediction of Sepsis in Critical Trauma Patients: Machine Learning-Based Modeling Study.

BACKGROUND: Sepsis is a leading cause of death in patients with trauma, and the risk of mortality increases significantly for each hour of delay in treatment. A hypermetabolic baseline and explosive inflammatory immune response mask clinical signs and symptoms of sepsis in trauma patients, making early diagnosis of sepsis more challenging. Machine learning-based predictive modeling has shown great promise in evaluating and predicting sepsis risk in the general intensive care unit (ICU) setting, but there has been no sepsis prediction model specifically developed for trauma patients so far. OBJECTIVE: To develop a machine learning model to predict the risk of sepsis at an hourly scale among ICU-admitted trauma patients. METHODS: We extracted data from adult trauma patients admitted to the ICU at Beth Israel Deaconess Medical Center between 2008 and 2019. A total of 42 raw variables were collected, including demographics, vital signs, arterial blood gas, and laboratory tests. We further derived a total of 485 features, including measurement pattern features, scoring features, and time-series variables, from the raw variables by feature engineering. The data set was randomly split into 70% for model development with stratified 5-fold cross-validation, 15% for calibration, and 15% for testing. An Extreme Gradient Boosting (XGBoost) model was developed to predict the hourly risk of sepsis at prediction windows of 4, 6, 8, 12, and 24 hours. We evaluated model performance for discrimination and calibration both at time-step and outcome levels. Clinical applicability of the model was evaluated with varying levels of precision, and the potential clinical net benefit was assessed with decision curve analysis (DCA). A Shapley additive explanation algorithm was applied to show the effect of features on the prediction model. In addition, we trained an L2-regularized logistic regression model to compare its performance with XGBoost. RESULTS: We included 4603 trauma patients in the study, 1196 (26%) of whom developed sepsis. The XGBoost model achieved an area under the receiver operating characteristics curve (AUROC) ranging from 0.83 to 0.88 at the 4-to-24-hour prediction window in the test set. With a ratio of 9 false alerts for every true alert, it predicted 73% (386/529) of sepsis-positive timesteps and 91% (163/179) of sepsis events in the subsequent 6 hours. The DCA showed our model had a positive net benefit in the threshold probability range of 0 to 0.6. In comparison, the logistic regression model achieved lower performance, with AUROC ranging from 0.76 to 0.84 at the 4-to-24-hour prediction window. CONCLUSIONS: The machine learning-based model had good discrimination and calibration performance for sepsis prediction in critical trauma patients. Using the model in clinical practice might help to identify patients at risk of sepsis in a time window that enables personalized intervention and early treatment.

Impact of Human Mobility on COVID-19 Transmission According to Mobility Distance, Location, and Demographic Factors in the Greater Bay Area of China: Population-Based Study.

BACKGROUND: Mobility restriction was one of the primary measures used to restrain the spread of COVID-19 globally. Governments implemented and relaxed various mobility restriction measures in the absence of evidence for almost 3 years, which caused severe adverse outcomes in terms of health, society, and economy. OBJECTIVE: This study aimed to quantify the impact of mobility reduction on COVID-19 transmission according to mobility distance, location, and demographic factors in order to identify hotspots of transmission and guide public health policies. METHODS: Large volumes of anonymized aggregated mobile phone position data between January 1 and February 24, 2020, were collected for 9 megacities in the Greater Bay Area, China. A generalized linear model (GLM) was established to test the association between mobility volume (number of trips) and COVID-19 transmission. Subgroup analysis was also performed for sex, age, travel location, and travel distance. Statistical interaction terms were included in a variety of models that express different relations between involved variables. RESULTS: The GLM analysis demonstrated a significant association between the COVID-19 growth rate ratio (GR) and mobility volume. A stratification analysis revealed a higher effect of mobility volume on the COVID-19 GR among people aged 50-59 years (GR decrease of 13.17% per 10% reduction in mobility volume; P<.001) than among other age groups (GR decreases of 7.80%, 10.43%, 7.48%, 8.01%, and 10.43% for those aged ≤18, 19-29, 30-39, 40-49, and ≥60 years, respectively; P=.02 for the interaction). The impact of mobility reduction on COVID-19 transmission was higher for transit stations and shopping areas (instantaneous reproduction number [Rt] decreases of 0.67 and 0.53 per 10% reduction in mobility volume, respectively) than for workplaces, schools, recreation areas, and other locations (Rt decreases of 0.30, 0.37, 0.44, and 0.32, respectively; P=.02 for the interaction). The association between mobility volume reduction and COVID-19 transmission was lower with decreasing mobility distance as there was a significant interaction between mobility volume and mobility distance with regard to Rt (P<.001 for the interaction). Specifically, the percentage decreases in Rt per 10% reduction in mobility volume were 11.97% when mobility distance increased by 10% (Spring Festival), 6.74% when mobility distance remained unchanged, and 1.52% when mobility distance declined by 10%. CONCLUSIONS: The association between mobility reduction and COVID-19 transmission significantly varied according to mobility distance, location, and age. The substantially higher impact of mobility volume on COVID-19 transmission for longer travel distance, certain age groups, and specific travel locations highlights the potential to optimize the effectiveness of mobility restriction strategies. The results from our study demonstrate the power of having a mobility network using mobile phone data for surveillance that can monitor movement at a detailed level to measure the potential impacts of future pandemics.

Longitudinal D-Dimer Trajectories and the Risk of Mortality in Abdominal Trauma Patients: A Group-Based Trajectory Modeling Analysis.

This study aimed to identify the long-term D-dimer trajectory patterns and their associations with in-hospital all-cause mortality in abdominal trauma patients. This is a retrospective cohort study of general adult abdominal trauma patients admitted to Jinling Hospital (Nanjing, China) between January 2010 and April 2020. Group-based trajectory modeling was applied to model D-dimer trajectories over the first 50 days post-trauma. A multivariable logistic regression was performed to estimate the associations between D-dimer trajectories and in-hospital all-cause mortality. A total of 309 patients were included. We identified four distinct D-dimer trajectories: group 1 (57.61%; "stable low"), group 2 (28.16%; "moderate-decline"), group 3 (8.41%; "high-rapid decline"), and group 4 (5.83%; "high-gradual decline"). The SOFA score (p = 0.005) and ISS (p = 0.001) were statistically higher in groups 3 and 4 than in groups 1 and 2. The LMWH and UFH did not differ between groups 3 and 4. Compared with the patients in group 1, only the patients in group 4 were at a higher risk of in-hospital all-cause mortality (OR = 6.94, 95% CI: 1.20-40.25). The long-term D-dimer trajectories post-trauma were heterogeneous and associated with mortality. An initially high and slowly-resolved D-dimer might function as the marker of disease deterioration, and specific interventions are needed.

High Fat-to-Muscle Ratio Was Associated with Increased Clinical Severity in Patients with Abdominal Trauma.

Overweight and moderate obesity confer a survival benefit in chronic diseases such as coronary artery disease and chronic kidney disease, which has been termed the "obesity paradox". However, whether this phenomenon exists in trauma patients remains controversial. We performed a retrospective cohort study in abdominal trauma patients admitted to a Level I trauma center in Nanjing, China between 2010 and 2020. In addition to the traditional body mass index (BMI) based measures, we further examined the association between body composition-based indices with clinical severity in trauma populations. Body composition indices including skeletal muscle index (SMI), fat tissue index (FTI), and total fat-to-muscle ratio (FTI/SMI) were measured using computed tomography. Our study found that overweight was associated with a four-fold risk of mortality (OR, 4.47 [95% CI, 1.40-14.97], p = 0.012) and obesity was associated with a seven-fold risk of mortality (OR, 6.56 [95% CI, 1.07-36.57], p = 0.032) compared to normal weight. Patients with high FTI/SMI had a three-fold risk of mortality (OR, 3.06 [95% CI, 1.08-10.16], p = 0.046) and double the risk of an intensive care unit length of stay ≥ 5 d (OR, 1.75 [95% CI, 1.06-2.91], p = 0.031) compared to patients with low FTI/SMI. The obesity paradox was not observed in abdominal trauma patients, and high FTI/SMI ratio was independently associated with increased clinical severity.

Changed epidemiology of narcolepsy before, during, and after the 2009 H1N1 pandemic: a nationwide narcolepsy surveillance network study in mainland China, 1990-2017.

STUDY OBJECTIVES: Increased incidence of narcolepsy was reported in children during the 2009 H1N1 pandemic following Pandemrix, a H1N1 flu vaccine. A link with A(H1N1) pdm09 infections remains controversial. Using nationwide surveillance data from China (1990 to 2017), the epidemiology of narcolepsy was analyzed. METHODS: Individual records of narcolepsy patients were collected from 15 of 42 hospitals across China known to diagnose cases. Incidence was estimated assuming the representativeness of these hospitals. Age-specific incidence, epidemiological and clinical characteristics of patients were evaluated before, during, and after the 2009 H1N1 pandemic. Sensitivity analyses were conducted by including NT1 cases only and excluding the effect of the 2009 H1N1 vaccination. RESULTS: Average annual incidence was 0.79 per 100 000 person-years (PY) from 1990 to 2017 and 1.08 per 100 000 PY from 2003 to 2017. Incidence increased 4.17 (95% CI 4.12, 4.22) and 1.42 (95% CI 1.41, 1.44) fold during and after the 2009 H1N1 pandemic when compared to baseline. These results were robust in sensitivity analyses. Patients with the onset of narcolepsy during the pandemic period were younger (notably in 5-9-year-old strata), and the age shift toward younger children reversed to baseline following the pandemic. CONCLUSIONS: Increased incidence of narcolepsy was observed during the 2009 H1N1 pandemic period. This is likely to be associated with the circulation of the wild type A(H1N1)pdm09 virus. This observation should be considered for future influenza pandemic preparedness plans.

Engineering Cytochrome P450BM3 Enzymes for Direct Nitration of Unsaturated Hydrocarbons.

Applications of the peroxidase activity of cytochrome P450 enzymes in synthetic chemistry remain largely unexplored. We present herein a protein engineering strategy to increase cytochrome P450BM3 peroxidase activity for the direct nitration of aromatic compounds and terminal aryl-substituted olefins in the presence of a dual-functional small molecule (DFSM). Site-directed mutations of key active-site residues allowed the efficient regulation of steric effects to limit substrate access and, thus, a significant decrease in monooxygenation activity and increase in peroxidase activity. Nitration of several phenol and aniline compounds also yielded ortho- and para-nitration products with moderate-to-high total turnover numbers. Besides direct aromatic nitration by P450 variants using nitrite as a nitrating agent, we also demonstrated the use of the DFSM-facilitated P450 peroxidase system for the nitration of the vinyl group of styrene and its derivatives.

Urban-rural disparity in heatwave effects on diabetes mortality in eastern China: A case-crossover analysis in 2016-2019.

Diabetics are sensitive to high ambient temperature due to impaired thermoregulation. However, available evidence on the impact of prolonged high temperature (i.e., heatwave) on diabetes deaths is limited and whether urban and rural areas differ in heatwave vulnerability remains unknown so far. A time-stratified case-crossover analysis was employed to estimate the association between heatwaves and diabetes deaths in 1486 districts (509 urban and 977 rural areas) of eastern China (Jiangsu Province), 2016-2019. For each decedent, residential heatwave exposure was measured by matching daily mean temperatures to the geocoded residential address. We adopted nine-tiered heatwave definitions incorporating intensity and duration. Stratified analyses by decedents' characteristics (gender, age, and education) were also conducted. During the study period, there were 18,685 deaths from diabetes (urban proportion: 36.95 %, p-value for urban-rural difference < 0.05). Heatwaves were associated with an increased risk of diabetes deaths, with greater and longer-lasting effects in rural areas than urban areas [e.g., rural odds ratio (OR): 1.19 (95 % confidence interval (CI): 1.14, 1.25) vs. urban OR: 1.09 (95 % CI: 1.05, 1.12)]. Risk of diabetes deaths increased with the intensity of heatwaves in rural areas (p-value for trend <0.01), but not in urban areas. Stratified analyses in rural areas suggested that females and less-educated people were more vulnerable to heatwave-related diabetes deaths. Our findings revealed the urban-rural disparity in the risk of diabetes deaths associated with heatwaves. Rural diabetics should be made aware of the increased death risk posed by heatwaves in the context of warming climate.

The relationship between LRP5 rs556442 and rs638051 polymorphisms and mutations and their influence on bone metabolism in postmenopausal Xinjiang women with type 2 diabetes.

BACKGROUND: The Wnt/ß-catenin signaling pathway plays a crucial role in bone development and metabolism. The low-density lipoprotein receptor-related protein 5 (LRP5), an important receptor in the Wnt signaling pathway, promotes the osteogenesis of osteoblasts and curbs bone resorption by osteoclasts. OBJECTIVES: To determine the expression of LRP5 polymorphisms (rs556442 and rs638051) and their relationship with bone mineral density (BMD) and bone metabolism markers in postmenopausal patients with type 2 diabetes mellitus (T2DM) in Xinjiang, China. MATERIAL AND METHODS: According to dual-energy X-ray (DEXA) and oral glucose tolerance test (OGTT) results, 226 postmenopausal women from Xinjiang were divided into the following groups: normal glucose tolerance (NGT) + normal bone mass group (group A), NGT + abnormal bone mass group (group B), T2DM + normal bone mass group (group C), and T2DM + abnormal bone mass group (group D). RESULTS: Femoral neck BMD was lower in group B women with the AG/GG genotype (mutant type) compared to women with the AA genotype (wild-type) at rs556442. Alkaline phosphatase (ALP) levels were lower in group D women with the AG/GG genotype (mutant type) compared to women with the AA genotype (wild-type) at rs556442 and rs638051. The factors influencing BMD (lumbar spine vertebrae 1-4 (L1-L4)) were triglyceride (TG) levels, body mass index (BMI), menopausal transition age, and age for rs556442 patients, and TG levels and menopausal transition age for rs638051 patients in group D. The factors affecting BMD (hip) were TG levels, BMI and age for rs556442 patients, and TG levels and age for rs638051 patients. CONCLUSIONS: The LRP5 gene mutations are linked to bone metabolism disorders in postmenopausal women with T2DM and abnormal bone mass. High BMI and TG were positively associated with BMD, while increased age and menopausal transition age were negatively associated with BMD.

Aschoff's rule on circadian rhythms orchestrated by blue light sensor CRY2 and clock component PRR9.

Circadian pace is modulated by light intensity, known as the Aschoff's rule, with largely unrevealed mechanisms. Here we report that photoreceptor CRY2 mediates blue light input to the circadian clock by directly interacting with clock core component PRR9 in blue light dependent manner. This physical interaction dually blocks the accessibility of PRR9 protein to its co-repressor TPL/TPRs and the resulting kinase PPKs. Notably, phosphorylation of PRR9 by PPKs is critical for its DNA binding and repressive activity, hence to ensure proper circadian speed. Given the labile nature of CRY2 in strong blue light, our findings provide a mechanistic explanation for Aschoff's rule in plants, i.e., blue light triggers CRY2 turnover in proportional to its intensity, which accordingly releasing PRR9 to fine tune circadian speed. Our findings not only reveal a network mediating light input into the circadian clock, but also unmask a mechanism by which the Arabidopsis circadian clock senses light intensity.

The impact of multi-level interventions on the second-wave SARS-CoV-2 transmission in China.

BACKGROUND: A re-emergence of COVID-19 occurred in the northeast of China in early 2021. Different levels of non-pharmaceutical interventions, from mass testing to city-level lockdown, were implemented to contain the transmission of SARS-CoV-2. Our study is aimed to evaluate the impact of multi-level control measures on the second-wave SARS-CoV-2 transmission in the most affected cities in China. METHODS: Five cities with over 100 reported COVID-19 cases within one month from Dec 2020 to Feb 2021 were included in our analysis. We fitted the exponential growth model to estimate basic reproduction number (R0), and used a Bayesian approach to assess the dynamics of the time-varying reproduction number (Rt). We fitted linear regression lines on Rt estimates for comparing the decline rates of Rt across cities, and the slopes were tested by analysis of covariance. The effect of non-pharmaceutical interventions (NPIs) was quantified by relative Rt reduction and statistically compared by analysis of variance. RESULTS: A total of 2,609 COVID-19 cases were analyzed in this study. We estimated that R0 all exceeded 1, with the highest value of 3.63 (1.36, 8.53) in Haerbin and the lowest value of 2.45 (1.44, 3.98) in Shijiazhuang. Downward trends of Rt were found in all cities, and the starting time of Rt < 1 was around the 12th day of the first local COVID-19 cases. Statistical tests on regression slopes of Rt and effect of NPIs both showed no significant difference across five cities (P = 0.126 and 0.157). CONCLUSION: Timely implemented NPIs could control the transmission of SARS-CoV-2 with low-intensity measures for places where population immunity has not been established.

Chromosome-level Genomes Reveal the Genetic Basis of Descending Dysploidy and Sex Determination in Morus Plants.

Multiple plant lineages have independently evolved sex chromosomes and variable karyotypes to maintain their sessile lifestyles through constant biological innovation. Morus notabilis, a dioecious mulberry species, has the fewest chromosomes among Morus spp., but the genetic basis of sex determination and karyotype evolution in this species has not been identified. In this study, three high-quality genome assemblies were generated for Morus spp. [including dioecious M. notabilis (male and female) and Morus yunnanensis (female)] with genome sizes of 301-329 Mb and were grouped into six pseudochromosomes. Using a combination of genomic approaches, we found that the putative ancestral karyotype of Morus species was close to 14 protochromosomes, and that several chromosome fusion events resulted in descending dysploidy (2n = 2x = 12). We also characterized a ∼ 6.2-Mb sex-determining region on chromosome 3. Four potential male-specific genes, a partially duplicatedDNA helicase gene (named MSDH) and three Ty3_Gypsy long terminal repeat retrotransposons (named MSTG1/2/3), were identified in the Y-linked area and considered to be strong candidate genes for sex determination or differentiation. Population genomic analysis showed that Guangdong accessions in China were genetically similar to Japanese accessions of mulberry. In addition, genomic areas containing selective sweeps that distinguish domesticated mulberry from wild populations in terms of flowering and disease resistance were identified. Our study provides an important genetic resource for sex identification research and molecular breeding in mulberry.

In Silico Discovery of GPCRs and GnRHRs as Novel Binding Receptors of SARS-CoV-2 Spike Protein Could Explain Neuroendocrine Disorders in COVID-19.

Despite the intense research work since the beginning of the pandemic, the pathogenesis of COVID-19 is not yet clearly understood. The previous mechanism of COVID-19, based on ACE2 tropism and explained through a single receptor, is insufficient to explain the pathogenesis due to the absence of angiotensin-converting enzyme 2 (ACE2) receptors in most of the affected organs. In the current study, we used the PatchDock server to run a molecular docking study of both the gonadotropin-releasing hormone receptor (GnRHR) and G-protein-coupled-receptor (GPCR) with the SARS-CoV-2 spike protein. Molecular Dynamics (MD) simulations were run to analyze the stability of the complexes using the GROMACS package. The docking results showed a high affinity between the spike protein with the GnRHR (-1424.9 kcal/mol) and GPCR (-1451.8 kcal/mol). The results of the MD simulations revealed the significant stability of the spike protein with the GnRHR and GPCR up to 100 ns. The SARS-CoV-2 spike protein had strong binding interactions with the GPCRs and GnRHRs, which are highly expressed in the brain, endocrine organs, and olfactory neurons. This study paves the way towards understanding the complex mechanism of neuroendocrine involvement and peripheral organ involvement, may explain the changing symptoms in patients due to new variants, and may lead to the discovery of new drug targets for COVID-19. In vitro studies involving genetic engineering or gene knockdown of the GPCRs and GnRHRs are needed to further investigate the role of these receptors in COVID-19 pathogenesis.

Heterogeneity in Estimates of Incidence and Prevalence of Narcolepsy: A Systematic Review and Meta-Regression Analysis.

INTRODUCTION: Narcolepsy is a chronic neurological disorder. The diagnostic criteria of narcolepsy evolve from clinical symptoms to molecular biomarkers, along with the understanding of its clinical nature and pathogenesis. Estimates of incidence and prevalence of narcolepsy vary between studies, while the contribution of changing diagnostic criteria to the variation remains unclear. We aimed to explore sources of heterogeneity in estimates of incidence and prevalence, with a particular focus on diagnostic criteria. METHODS: We searched 5 databases for observational studies on the incidence or prevalence of narcolepsy published before October 14, 2021. Subgroup analyses and meta-regression were used to assess the impact of diagnostic criteria on incidence/prevalence of narcolepsy after adjusting for age-group, region, study period, vaccination status, index date, and type of narcolepsy. RESULTS: Thirty-five studies were selected from 2,833 articles. The estimates of incidence and prevalence were wide-ranging with high heterogeneity (incidence I2 = 99.8%; prevalence I2 = 99.7%), from 0.06 to 6.56 per 100,000 person-years for incidence and from 1.05 to 79.40 per 100,000 population for prevalence, respectively. Totally 10 diagnostic criteria were used, including the 1st revised edition of International Classification of Diseases (ICSD-1), ICSD-2, ICSD-3, the 8th revision of International Classification of Diseases (ICD-8), ICD-9, ICD-10, Brighton collaboration case definition (Brighton), Mayo classification, the Ullanlinna Narcolepsy Scale, and clinical symptoms with the multiple sleep latency test. ICD tended to provide higher estimates of incidence/prevalence than Brighton (incidence odds ratio [OR] 1.38, [95% CI: 1.02, 1.86]; prevalence OR 1.50, [95% CI: 1.04, 2.39]). No significant difference was found in estimates of two rates between ICSD and Brighton. The incidence was higher for children than adults (OR 1.61, [95% CI: 1.25, 2.07]) and for individuals vaccinated with Pandemrix than those unvaccinated (OR 6.49, [95% CI: 3.86, 10.91]). CONCLUSIONS: Estimates of incidence/prevalence of narcolepsy could not be pooled reliably with substantial heterogeneity. Incidence/prevalence studies using ICSD and Brighton provided lower estimates than studies using ICD and other criteria. Diagnostic criteria should be standardized when comparing or pooling the incidence/prevalence to understand the epidemiology of narcolepsy. Future studies are needed to focus on the at-risk population for the etiology investigation of narcolepsy.

Rice CIRCADIAN CLOCK ASSOCIATED 1 transcriptionally regulates ABA signaling to confer multiple abiotic stress tolerance.

The circadian clock facilitates the survival and reproduction of crop plants under harsh environmental conditions such as drought and osmotic and salinity stresses, mainly by reprogramming the endogenous transcriptional landscape. Nevertheless, the genome-wide roles of core clock components in rice (Oryza sativa L.) abiotic stress tolerance are largely uncharacterized. Here, we report that CIRCADIAN CLOCK ASSOCIATED1 (OsCCA1), a vital clock component in rice, is required for tolerance to salinity, osmotic, and drought stresses. DNA affinity purification sequencing coupled with transcriptome analysis identified 692 direct transcriptional target genes of OsCCA1. Among them, the genes involved in abscisic acid (ABA) signaling, including group A protein phosphatase 2C genes and basic region and leucine zipper 46 (OsbZIP46), were substantially enriched. Moreover, OsCCA1 could directly bind the promoters of OsPP108 and OsbZIP46 to activate their expression. Consistently, oscca1 null mutants generated via genome editing displayed enhanced sensitivities to ABA signaling. Together, our findings illustrate that OsCCA1 confers multiple abiotic stress tolerance likely by orchestrating ABA signaling, which links the circadian clock with ABA signaling in rice.