Genome editing of a rice CDP-DAG synthase confers multipathogen resistance.

The discovery and application of genome editing introduced a new era of plant breeding by giving researchers efficient tools for the precise engineering of crop genomes1. Here we demonstrate the power of genome editing for engineering broad-spectrum disease resistance in rice (Oryza sativa). We first isolated a lesion mimic mutant (LMM) from a mutagenized rice population. We then demonstrated that a 29-base-pair deletion in a gene we named RESISTANCE TO BLAST1 (RBL1) caused broad-spectrum disease resistance and showed that this mutation caused an approximately 20-fold reduction in yield. RBL1 encodes a cytidine diphosphate diacylglycerol synthase that is required for phospholipid biosynthesis2. Mutation of RBL1 results in reduced levels of phosphatidylinositol and its derivative phosphatidylinositol 4,5-bisphosphate (PtdIns(4,5)P2). In rice, PtdIns(4,5)P2 is enriched in cellular structures that are specifically associated with effector secretion and fungal infection, suggesting that it has a role as a disease-susceptibility factor3. By using targeted genome editing, we obtained an allele of RBL1, named RBL1Δ12, which confers broad-spectrum disease resistance but does not decrease yield in a model rice variety, as assessed in small-scale field trials. Our study has demonstrated the benefits of editing an LMM gene, a strategy relevant to diverse LMM genes and crops.

Machine-learning-based plasma metabolomic profiles for predicting long-term complications of cirrhosis.

BACKGROUND AND AIMS: The complications of liver cirrhosis occur after long asymptomatic stages of progressive fibrosis and are generally diagnosed late. We aimed to develop a plasma metabolomic-based score tool to predict these events. APPROACH AND RESULTS: We enrolled 64,005 UK biobank participants with metabolomic profiles. Participants were randomly divided into the training (n=43,734) and validation cohorts (n=20,271). Liver cirrhosis complications were defined as hospitalization for liver cirrhosis or presentation with HCC. An interpretable machine-learning framework was applied to learn the metabolomic states extracted from 168 circulating metabolites in the training cohort. An integrated nomogram was developed and compared to conventional and genetic risk scores. We created 3 groups: low-risk, middle-risk, and high-risk through selected cutoffs of the nomogram. The predictive performance was validated through the area under a time-dependent receiver operating characteristic curve (time-dependent AUC), calibration curves, and decision curve analysis. The metabolomic state model could accurately predict the 10-year risk of liver cirrhosis complications in the training cohort (time-dependent AUC: 0.84 [95% CI: 0.82-0.86]), and outperform the fibrosis-4 index (time-dependent AUC difference: 0.06 [0.03-0.10]) and polygenic risk score (0.25 [0.21-0.29]). The nomogram, integrating metabolomic state, aspartate aminotransferase, platelet count, waist/hip ratio, and smoking status showed a time-dependent AUC of 0.930 at 3 years, 0.889 at 5 years, and 0.861 at 10 years in the validation cohort, respectively. The HR in the high-risk group was 43.58 (95% CI: 27.08-70.12) compared with the low-risk group. CONCLUSIONS: We developed a metabolomic state-integrated nomogram, which enables risk stratification and personalized administration of liver-related events.

Cooperative interaction of CST and RECQ4 resolves G-quadruplexes and maintains telomere stability.

Human CST (CTC1-STN1-TEN1) is a ssDNA-binding complex that interacts with the replisome to aid in stalled fork rescue. We previously found that CST promotes telomere replication to maintain genomic integrity via G-quadruplex (G4) resolution. However, the detailed mechanism by which CST resolves G4s in vivo and whether additional factors are involved remains unclear. Here, we identify RECQ4 as a novel CST-interacting partner and show that RECQ4 can unwind G4 structures in vitro using a FRET assay. Moreover, G4s accumulate at the telomere after RECQ4 depletion, resulting in telomere dysfunction, including the formation of MTSs, SFEs, and TIFs, suggesting that RECQ4 is crucial for telomere integrity. Furthermore, CST is also required for RECQ4 telomere or chromatin localization in response to G4 stabilizers. RECQ4 is involved in preserving genomic stability by CST and RECQ4 disruption impairs restart of replication forks stalled by G4s. Overall, our findings highlight the essential roles of CST and RECQ4 in resolving G-rich regions, where they collaborate to resolve G4-induced replication deficiencies and maintain genomic homeostasis.

A systematic two-sample and bidirectional MR process highlights a unidirectional genetic causal effect of allergic diseases on COVID-19 infection/severity.

BACKGROUND: Allergic diseases (ADs) such as asthma are presumed risk factors for COVID-19 infection. However, recent observational studies suggest that the assumed correlation contradicts each other. We therefore systematically investigated the genetic causal correlations between various ADs and COVID-19 infection/severity. METHODS: We performed a two-sample, bidirectional Mendelian randomization (MR) study for five types of ADs and the latest round of COVID-19 GWAS meta-analysis datasets (critically ill, hospitalized, and infection cases). We also further validated the significant causal correlations and elucidated the potential underlying molecular mechanisms. RESULTS: With the most suitable MR method, asthma consistently demonstrated causal protective effects on critically ill and hospitalized COVID-19 cases (OR < 0.93, p < 2.01 × 10-2), which were further confirmed by another validated GWAS dataset (OR < 0.92, p < 4.22 × 10-3). In addition, our MR analyses also observed significant causal correlations of food allergies such as shrimp allergy with the risk of COVID-19 infection/severity. However, we did not find any significant causal effect of COVID-19 phenotypes on the risk of ADs. Regarding the underlying molecular mechanisms, not only multiple immune-related cells such as CD4+ T, CD8+ T and the ratio of CD4+/CD8+ T cells showed significant causal effects on COVID-19 phenotypes and various ADs, the hematology traits including monocytes were also significantly correlated with them. Conversely, various ADs such as asthma and shrimp allergy may be causally correlated with COVID-19 infection/severity by affecting multiple hematological traits and immune-related cells. CONCLUSIONS: Our systematic and bidirectional MR analyses suggest a unidirectional causal effect of various ADs, particularly of asthma on COVID-19 infection/severity, but the reverse is not true. The potential underlying molecular mechanisms of the causal effects call for more attention to clinical monitoring of hematological cells/traits and may be beneficial in developing effective therapeutic strategies for allergic patients following infection with COVID-19.

Switching ubiquitous and muscle-specific isoforms of mitochondrial respiratory complex IV in skeletal muscle fine-tunes complex IV activity.

Respiratory complex IV (CIV, cytochrome c oxidase) is the terminal enzyme of the mitochondrial electron transport chain. Some CIV subunits have two or more isoforms, which are ubiquitously expressed or are expressed in specific tissues like the lung, muscle, and testis. Among the tissue-specific CIV isoforms, the muscle-specific isoforms are expressed in adult cardiac and skeletal muscles. To date, the physiological and biochemical association between the muscle-specific CIV isoforms and aerobic respiration in muscles remains unclear. In this study, we profiled the CIV organization and expression pattern of muscle-specific CIV isoforms in different mouse muscle tissues. We found extensive CIV-containing supramolecular organization in murine musculature at advanced developmental stages, while a switch in the expression from ubiquitous to muscle-specific isoforms of CIV was also detected. Such a switch was confirmed during the in vitro differentiation of mouse C2C12 myoblasts. Unexpectedly, a CIV expression decrease was observed during C2C12 differentiation, which was probably due to a small increase in the expression of muscle-specific isoforms coupled with a dramatic decrease in the ubiquitous isoforms. We also found that the enzymatic activity of CIV containing the muscle-specific isoform COX6A2 was higher than that with COX6A1 in engineered HEK293T cells. Overall, our results indicate that switching the expression from ubiquitous to muscle-specific CIV isoforms is indispensable for optimized oxidative phosphorylation in mature skeletal muscles. We also note that the in vitro C2C12 differentiation model is not suitable for the study of muscular aerobic respiration due to insufficient expression of muscle-specific CIV isoforms.

Serological characteristics and clinical implications of IgG subclasses in visceral leishmaniasis.

OBJECTIVES: Visceral leishmaniasis (VL) represents the most severe form of Leishmaniasis infection, often resulting in fatality without timely treatment. Previous studies have found that immunosuppression increases the risk of VL disease progression and mortality, and the total immunoglobulin G (IgG) levels in peripheral blood vary before and after treatment. However, the distinct levels and roles of IgG subclasses in VL have not been documented yet. This study aims to elucidate the characteristics and clinical significance of IgG subclasses in VL. METHODS: A total of 43 cases newly-diagnosed with VL were enrolled in the cohort. We measured the levels of IgG subclasses before and after standard treatment and conducted assessments of bone marrow features. In addition, we analysed other haematological indices and examined the variations in IgG subclasses, as well as their correlation with clinical and laboratory factors. RESULTS: The levels of total IgG, IgG1, and the ratios of both IgG1/IgG and IgG1/IgG2 decreased significantly after treatment, whereas the ratios of IgG2/ IgG showed an obvious increase. The VL patients without hyperglobulinemia displayed significant lower IgG1/IgG2 ratios, but higher IgG2/IgG ratios compared with those with hyperglobulinemia. In addition, VL patients with positive bone marrow amastigotes had significant higher IgG1/IgG and IgG1/IgG2 ratios, but lower IgG2/IgG ratios. IgG subclasses were correlated with abnormal blood test results, particularly immunological elements including IgM and Complement 4 (C4). CONCLUSIONS: IgG1 and IgG2 exhibited contrasting changes after treatment in VL patients. The features of bone marrow and laboratory tests indicated that IgG1 and IgG2 serve different roles in the progression of VL. The ratios of IgG subclasses may be more precise indicators to evaluate immune reaction in VL than traditional total IgG.

Establishment of a mild cognitive impairment risk model in middle-aged and older adults: a longitudinal study.

BACKGROUND: Early identification individuals at high risk of mild cognitive impairment (MCI) is essential for prevention and intervention strategies of dementia, such as Alzheimer's disease. MCI prediction considering the interdependence of predictors in longitudinal data needs to be further explored. We aimed to employ machine learning (ML) to develop and verify a prediction model of MCI. METHODS: In a longitudinal population-based cohort of China Health and Retirement Longitudinal Study (CHARLS), 8390 non-MCI participants were enrolled. The diagnosis of MCI was based on the aging-associated cognitive decline (AACD), and 13 factors (gender, education, marital status, residence, diabetes, hypertension, depression, hearing impairment, social isolation, physical activity, drinking status, body mass index and expenditure) were finally selected as predictors. We implemented a long short-term memory (LSTM) to predict the MCI risks in middle-aged and older adults within 7 years. The Receiver Operating Characteristic curve (ROC) and calibration curve were used to evaluate the performance of the model. RESULTS: Through 7 years of follow-up, 1925 participants developed MCI. The model for all incident MCI achieved an AUC of 0.774, and its deployment to the participants followed 2, 4, and 7 years achieved results of 0.739, 0.747, and 0.750, respectively. The model was well-calibrated with predicted probabilities plotted against the observed proportions of cognitive impairment. Education level, gender, marital status, and depression contributed most to the prediction of MCI. CONCLUSIONS: This model could be widely applied to medical institutions, even in the community, to identify middle-aged and older adults at high risk of MCI.

Psychological distress and uterine fibroids: a bidirectional two-sample mendelian randomization study.

BACKGROUND: Observational data indicates a connection between emotional discomfort, such as anxiety and depression, and uterine fibroids (UFs). However, additional investigation is required to establish the causal relationship between them. Hence, we assessed the reciprocal causality between four psychological disorders and UFs utilizing two-sample Mendelian randomization (MR). METHODS: To evaluate the causal relationship between four types of psychological distress (depressive symptoms, severe depression, anxiety or panic attacks, mood swings) and UFs, bidirectional two-sample MR was employed, utilizing single nucleotide polymorphisms (SNPs) associated with these conditions. Both univariate MR (UVMR) and multivariate MR (MVMR) primarily applied inverse variance weighted (IVW) as the method for estimating potential causal effects. Complementary approaches such as MR Egger, weighted median, simple mode, and weighted mode were utilized to validate the findings. To assess the robustness of our MR results, we conducted sensitivity analyses using Cochran's Q-test and the MR Egger intercept test. RESULTS: The results of our UVMR analysis suggest that genetic predispositions to depressive symptoms (Odds Ratio [OR] = 1.563, 95% Confidence Interval [CI] = 1.209-2.021, P = 0.001) and major depressive disorder (MDD) (OR = 1.176, 95% CI = 1.044-1.324, P = 0.007) are associated with an increased risk of UFs. Moreover, the IVW model showed a nominally significant positive correlation between mood swings (OR: 1.578; 95% CI: 1.062-2.345; P = 0.024) and UFs risk. However, our analysis did not establish a causal relationship between UFs and the four types of psychological distress. Even after adjusting for confounders like body mass index (BMI), smoking, alcohol consumption, and number of live births in the MVMR, the causal link between MDD and UFs remained significant (OR = 1.217, 95% CI = 1.039-1.425, P = 0.015). CONCLUSIONS: Our study presents evidence supporting the causal relationship between genetic susceptibility to MDD and the incidence of UFs. These findings highlight the significance of addressing psychological health issues, particularly depression, in both the prevention and treatment of UFs.

Spinocerebellar Ataxia Type 3 Pathophysiology-Implications for Translational Research and Clinical Studies.

The spinocerebellar ataxias (SCA) comprise a group of inherited neurodegenerative diseases. Machado-Joseph Disease (MJD) or spinocerebellar ataxia 3 (SCA3) is the most common autosomal dominant form, caused by the expansion of CAG repeats within the ataxin-3 (ATXN3) gene. This mutation results in the expression of an abnormal protein containing long polyglutamine (polyQ) stretches that confers a toxic gain of function and leads to misfolding and aggregation of ATXN3 in neurons. As a result of the neurodegenerative process, SCA3 patients are severely disabled and die prematurely. Several screening approaches, e.g., druggable genome-wide and drug library screenings have been performed, focussing on the reduction in stably overexpressed ATXN3(polyQ) protein and improvement in the resultant toxicity. Transgenic overexpression models of toxic ATXN3, however, missed potential modulators of endogenous ATXN3 regulation. In another approach to identify modifiers of endogenous ATXN3 expression using a CRISPR/Cas9-modified SK-N-SH wild-type cell line with a GFP-T2A-luciferase (LUC) cassette under the control of the endogenous ATXN3 promotor, four statins were identified as potential activators of expression. We here provide an overview of the high throughput screening approaches yet performed to find compounds or genomic modifiers of ATXN3(polyQ) toxicity in different SCA3 model organisms and cell lines to ameliorate and halt SCA3 progression in patients. Furthermore, the putative role of cholesterol in neurodegenerative diseases (NDDs) in general and SCA3 in particular is discussed.

Long-term exposure to fine particulate matter constituents in relation to chronic kidney disease: evidence from a large population-based study in China.

The effects of long-term exposure to fine particulate matter (PM2.5) constituents on chronic kidney disease (CKD) are not fully known. This study sought to examine the association between long-term exposure to major PM2.5 constituents and CKD and look for potential constituents contributing substantially to CKD. This study included 81,137 adults from the 2018 to 2019 baseline survey of China Multi-Ethnic Cohort. CKD was defined by the estimated glomerular filtration rate. Exposure concentration data of 7 major PM2.5 constituents were assessed by satellite remote sensing. Logistic regression models were used to estimate the effect of each PM2.5 constituent exposure on CKD. The weighted quantile sum regression was used to estimate the effect of mixed exposure to all constituents. PM2.5 constituents had positive correlations with CKD (per standard deviation increase), with ORs (95% CIs) of 1.20 (1.02-1.41) for black carbon, 1.27 (1.07-1.51) for ammonium, 1.29 (1.08-1.55) for nitrate, 1.20 (1.01-1.43) for organic matter, 1.25 (1.06-1.46) for sulfate, 1.30 (1.11-1.54) for soil particles, and 1.63 (1.39-1.91) for sea salt. Mixed exposure to all constituents was positively associated with CKD (1.68, 1.32-2.11). Sea salt was the constituent with the largest weight (0.36), which suggested its importance in the PM2.5-CKD association, followed by nitrate (0.32), organic matter (0.18), soil particles (0.10), ammonium (0.03), BC (0.01). Sulfate had the least weight (< 0.01). Long-term exposure to PM2.5 sea salt and nitrate may contribute more than other constituents in increasing CKD risk, providing new evidence and insights for PM2.5-CKD mechanism research and air pollution control strategy.

Novel biallelic mutations in TMEM126B cause splicing defects and lead to Leigh-like syndrome with severe complex I deficiency.

Leigh syndrome (LS)/Leigh-like syndrome (LLS) is one of the most common mitochondrial disease subtypes, caused by mutations in either the nuclear or mitochondrial genomes. Here, we identified a novel intronic mutation (c.82-2 A > G) and a novel exonic insertion mutation (c.290dupT) in TMEM126B from a Chinese patient with clinical manifestations of LLS. In silico predictions, minigene splicing assays and patients' RNA analyses determined that the c.82-2 A > G mutation resulted in complete exon 2 skipping, and the c.290dupT mutation provoked partial and complete exon 3 skipping, leading to translational frameshifts and premature termination. Functional analysis revealed the impaired mitochondrial function in patient-derived lymphocytes due to severe complex I content and assembly defect. Altogether, this is the first report of LLS in a patient carrying mutations in TMEM126B. Our data uncovers the functional effect and the molecular mechanism of the pathogenic variants c.82-2 A > G and c.290dupT, which expands the gene mutation spectrum of LLS and clinical spectrum caused by TMEM126B mutations, and thus help to clinical diagnosis of TMEM126B mutation-related mitochondrial diseases.

Associations of healthy lifestyle and three latent socioeconomic status patterns with physical multimorbidity among middle-aged and older adults in China.

BACKGROUND: Multimorbidity is an emerging global public health concern. However, complex associations of healthy lifestyle and socioeconomic status (SES) with multimorbidity have not been identified. METHODS: This population-based prospective cohort study used data from four waves of the China Health and Retirement Longitudinal Study (CHARLS) to explore these relationships. Physical multimorbidity was measured using 12 non-communicable diseases. Latent class analysis (LCA) was conducted to determine the optimal SES patterns based on annual per-capita household expenditure, occupation, education level, and health insurance. The healthy lifestyle score (0-5) was constructed comprising information on smoking, drinking, physical activity, sleep, and body shape. RESULTS: Of 17,708 participants in the CHARLS, 7776 were eligible for inclusion in our analysis (13.3% with high SES, 26.1% with medium SES, and 60.6% with low SES). Compared with high SES participants, those with low SES had higher risks of incident physical multimorbidity (OR 1.22, 95% CI 1.05, 1.42), which was competitively mediated by lifestyle (mediation proportion, -10.17%, 95% CI -19.12%, -1.23%). Significant interactions were observed between lifestyle factors and SES in patients with incident diabetes. Participants with low SES and no or one healthy lifestyle factor had a higher risk of incident physical multimorbidity than those with high SES and four to five healthy lifestyle factors (OR 2.19, 95% CI 1.57, 3.04). CONCLUSION: Healthy lifestyles competitively mediate a fractional proportion of socioeconomic inequity in incident physical multimorbidity. Furthermore, healthy lifestyles were associated with lower multimorbidity risk in the SES subgroups, supporting the important role of lifestyle in reducing physical multimorbidity burden.

Low thyroid function is associated with an increased risk of advanced fibrosis in patients with metabolic dysfunction-associated fatty liver disease.

AIMS: Observational studies showed that low thyroid function may perturb liver function. We aimed to evaluate the association of low thyroid function with both metabolic dysfunction-associated fatty liver disease (MAFLD) and advanced hepatic fibrosis. METHODS: Participants who underwent abdominal ultrasonography and thyroid function test in a Chinese hospital from 2015 to 2021were enrolled. Fibrosis-4 index (FIB-4) > 2.67 and/or non-alcoholic fatty liver disease fibrosis score (NFS) > 0.676 were used to define advanced fibrosis. Descriptive analyses were performed to characterize the epidemiology of MAFLD according to levels of thyroid-stimulating hormone (TSH). The logistic regression model was applied to estimate the association of low thyroid function with MAFLD and advanced fibrosis. RESULTS: A total of 19,946 participants (52.78% males, mean age: 47.31 years, 27.55% MAFLD) were included, among which 14,789 were strict-normal thyroid function, 4,328 were low-normal thyroid function, 829 were subclinical hypothyroidism. TSH levels were significantly higher in MAFLD patients with a FIB-4 > 2.67 and /or NFS > 0.676 than their counterparts. The logistic regression model adjusted for age and sex showed that low-normal thyroid function increased the risk of MAFLD (odds ratio [OR] = 1.09; 95% confidence interval [CI] 1.01-1.18). Multivariable regression model adjusted for age, sex, body mass index, type 2 diabetes, and hypertension showed low-normal thyroid function increased the risk of advanced fibrosis in patients with MAFLD (FIB-4 > 2.67: OR = 1.41, 95% CI 1.02-1.93; NFS > 0.676: OR = 1.72, 95% CI 1.08-2.72). CONCLUSION: Elevated TSH concentrations are associated with advanced hepatic fibrosis, even in the euthyroid state.

The association between chemical constituents of ambient fine particulate matter and obesity in adults: A large population-based cohort study.

OBJECTIVES: Current evidence demonstrated that ambient fine particulate matter with an aerodynamic diameter ≤2.5 µm (PM2.5) and its constituents may be obesogenic in children, but evidence from adults is lacking. Our aim was to characterize the association between PM2.5 and its constituents and obesity in adults. METHODS: We included 68,914 participants from the China Multi-Ethnic Cohort (CMEC) baseline survey. Three-year average concentrations of PM2.5 and its constituents were evaluated by linking pollutant estimates to the geocoded residential addresses. Obesity was defined as body mass index (BMI) ≥ 28 kg/m2. Logistic regression was used to examine the relationship between PM2.5 and its constituents and obesity. We performed weighed quantile sum (WQS) regression to get the overall effect of PM2.5 and its constituents and the relative contribution of each constituent. RESULTS: Per-SD increase in PM2.5 (odds ratio [OR] = 1.43, 95% confidence interval [CI]: 1.37-1.49), black carbon (BC) (1.42, 1.36-1.48), ammonium (1.43, 1.37-1.49), nitrate (1.44, 1.38-1.50), organic matter (OM) (1.45, 1.39-1.51), sulfate (1.42, 1.35-1.48), and soil particles (SOIL) (1.31, 1.27-1.36) were positively associated with obesity, and SS (0.60, 0.55-0.65) was negatively associated with obesity. The overall effect (OR = 1.34, 95% CI: 1.29-1.41) of the PM2.5 and its constituents was positively associated with obesity, and ammonium made the most contribution to this relationship. Participants who were older, female, never smoked, lived in urban areas, had lower income or higher levels of physical activity were more significantly adversely affected by PM2.5, BC, ammonium, nitrate, OM, sulfate and SOIL compared to other individuals. CONCLUSION: Our study revealed that PM2.5 constituents except SS were positively associated with obesity, and ammonium played the most important role. These findings provided new evidence for public health interventions, especially the precise prevention and control of obesity.

Ultra-small lipid carriers with adjustable release profiles for synergistic treatment of drug-resistant ovarian cancer.

Multidrug resistance has dramatically compromised the effectiveness of paclitaxel (PTX). The combined application of PTX and tetrandrine (TET) is a promising avenue in drug-resistant cancer therapy. However, poor drug release and limited intracellular drug accumulation greatly impede this combinational antitumor therapy. To address this problem, we successfully developed a tunable controlled release lipid platform (PT@usNLC) for coordinated drug delivery. The drug release rate of PT@usNLC can be tuned by varying the lipid ratio, which has potential to maximize the therapeutic effects of combined drugs. The TET release rate from PT@usNLC was faster than PTX, which could restore the sensitivity of tumor cells to PTX and exert a synergistic antitumor effect. The appropriate size of PT@usNLC could effectively increase the intracellular drug accumulation. Bothin vitroandin vivostudies revealed that PT@usNLC significantly enhanced the therapeutic effect compared to conventional therapies. This study provides a new strategy for resistant ovarian cancer therapy.

A tighter generalization bound for reservoir computing.

While reservoir computing (RC) has demonstrated astonishing performance in many practical scenarios, the understanding of its capability for generalization on previously unseen data is limited. To address this issue, we propose a novel generalization bound for RC based on the empirical Rademacher complexity under the probably approximately correct learning framework. Note that the generalization bound for the RC is derived in terms of the model hyperparameters. For this reason, it can explore the dependencies of the generalization bound for RC on its hyperparameters. Compared with the existing generalization bound, our generalization bound for RC is tighter, which is verified by numerical experiments. Furthermore, we study the generalization bound for the RC corresponding to different reservoir graphs, including directed acyclic graph (DAG) and Erdos-R e´nyi undirected random graph (ER graph). Specifically, the generalization bound for the RC whose reservoir graph is designated as a DAG can be refined by leveraging the structural property (i.e., the longest path length) of the DAG. Finally, both theoretical and experimental findings confirm that the generalization bound for the RC of a DAG is lower and less sensitive to the model hyperparameters than that for the RC of an ER graph.

Wireless Sensing Technology Combined with Facial Expression to Realize Multimodal Emotion Recognition.

Emotions significantly impact human physical and mental health, and, therefore, emotion recognition has been a popular research area in neuroscience, psychology, and medicine. In this paper, we preprocess the raw signals acquired by millimeter-wave radar to obtain high-quality heartbeat and respiration signals. Then, we propose a deep learning model incorporating a convolutional neural network and gated recurrent unit neural network in combination with human face expression images. The model achieves a recognition accuracy of 84.5% in person-dependent experiments and 74.25% in person-independent experiments. The experiments show that it outperforms a single deep learning model compared to traditional machine learning algorithms.

Does technical progress curb India's carbon emissions? A novel approach of combining extended index decomposition analysis and production-theoretical decomposition analysis.

Technical progress is one of the best strategies to meet the dual challenges of economic growth and carbon emissions control in developing countries such as India. In this research, an empirical study of India's carbon emissions was conducted to understand the effects of various technical factors on total and industrial carbon emission intensity. Ten driving factors of carbon emission in 56 sectors of India are decomposed by combining Index Decomposition Analysis (IDA) and Production-theoretical Decomposition Analysis (PDA). The results reveal that (i) the pure carbon-reduction technical efficiency and the scale efficiency of carbon-reduction technology in India have not improved, and the technical progress of pure carbon-reduction and the scale efficiency of carbon-reduction technology has played a positive role in carbon emission. (ii) The scale efficiency of pure energy-saving technology progress is the most important factor in restraining carbon emissions, and pure energy-saving technology progress has had an overall promoting effect. However, the effect of energy-saving technology progress is not as effective as the scale efficiency through improving energy technology progress. (iii) Per capita value added and population size are powerful factors that promote carbon emissions. This study also makes a targeted analysis of the driving factors of carbon emissions in different industries, which provide a reference for the process of carbon-reduction in different industries.

Reduction in Allergenicity and Induction of Oral Tolerance of Glycated Tropomyosin from Crab.

Tropomyosin (TM) is an important crustacean (Scylla paramamosain) allergen. This study aimed to assess Maillard-reacted TM (TM-G) induction of allergenic responses with cell and mouse models. We analyzed the difference of sensitization and the ability to induce immune tolerance between TM and TM-G by in vitro and in vivo models, then we compared the relationship between glycation sites of TM-G and epitopes of TM. In the in vitro assay, we discovered that the sensitization of TM-G was lower than TM, and the ability to stimulate mast cell degranulation decreased from 55.07 ± 4.23% to 27.86 ± 3.21%. In the serum of sensitized Balb/c mice, the level of specific IgE produced by TM-G sensitized mice was significantly lower than TM, and the levels of interleukins 4 and interleukins 13 produced by Th2 cells in spleen lymphocytes decreased by 82.35 ± 5.88% and 83.64 ± 9.09%, respectively. In the oral tolerance model, the ratio of Th2/Th1 decreased from 4.05 ± 0.38 to 1.69 ± 0.19. Maillard reaction masked the B cell epitopes of TM and retained some T cell epitopes. Potentially, Maillard reaction products (MRPs) can be used as tolerance inducers for allergen-specific immunotherapy.

Spillover effects of the United States economic slowdown induced by COVID-19 pandemic on energy, economy, and environment in other countries.

The United States has become the country hardest hit by the COVID-19 pandemic. This pandemic has not only led to the largest decline in economic output but also caused a sharp decline in carbon emissions and energy consumption in the United States after World War II. This study aims to evaluate how to spillover effects of the US economic slowdown caused by the COVID-19 pandemic on the 3E (Energy Economy Environment) in other countries. To this end, the international 3E for 2000 and 2014, and nine indicators based on network analysis to dynamically study the changes in the degree of 3E impact between countries. And then, we analyzed the impact of the epidemic on the 3E of various countries, with focusing on the interaction between the United States and other countries. The results show that the internal carbon emission density and internal energy consumption density of the United States declined during 2010-2014, whereas the internal carbon emission density and internal energy consumption density of developing countries increased. Next, changes in US carbon emissions induced by the epidemic have a more significant impact on Canada, China, Mexico, the European Union, and Russia. Finally, the internal and external carbon emission indexes of most countries have decreased, which indicates that most countries are affected by the carbon reduction and energy consumption caused by the pandemic in the US. This information provides a new perspective for assessing the impact of 3E between countries suffered from the COVID-19 Pandemic.