Rapid diagnosis of canine respiratory coronavirus, canine influenza virus, canine distemper virus and canine parainfluenza virus with a Taqman probe-based multiplex real-time PCR.

Canine Infectious Respiratory Disease Complex (CIRDC) is a highly infectious diseases. Canine respiratory coronavirus (CRCoV), Canine influenza virus (CIV), Canine distemper virus (CDV), and Canine parainfluenza virus (CPiV) are crucial pathogens causing CIRDC. Due to the similar clinical symptoms induced by these viruses, differential diagnosis based solely on symptoms can be challenging. In this study, a multiplex real-time PCR assay was developed for detecting the four RNA viruses of CIRDC. Specific primers and probes were designed to target M gene of CRCoV, M gene of CIV, N gene of CDV and NP gene of CPiV. The detection limit is 10 copies/µL for CIV or CRCoV, while the detection limit of CDV or CPiV is 100 copies/µL. Intra-group and inter-group repeatability coefficient of variation (CV) were both less than 2 %. A total of 341 clinical canine samples were analyzed, and the results indicated that the method developed in our study owns a good consistency and better specificity compared with the conventional reverse transcription PCR. This study provides a new method to enable the simultaneous detection of all four pathogens in a single reaction, improving the efficiency for monitoring the prevalence of four viruses in CIRDC, which benefits the control of CIRDC.

Dietary Flavonoids Consumption and Health: An Umbrella Review.

SCOPE: The current evidence between dietary flavonoids consumption and multiple health outcomes is inadequate and inconclusive. To summarize and evaluate the evidence for dietary flavonoids consumption and multiple health outcomes, an umbrella review of meta-analyses and systematic reviews is conducted. METHODS AND RESULTS: PubMed, Ovid-EMBASE, and the Cochrane Database of Systematic Reviews are searched up to January 2024. The study includes a total of 32 articles containing 24 unique health outcomes in this umbrella review. Meta-analyses are recalculated by using a random effects model. Separate analyses are performed based on the kind of different flavonoid subclasses. The study finds some unique associations such as flavonol and gastric cancer, isoflavone and uterine fibroids and endometrial cancer, total flavonoids consumption and lung cancer, ovarian cancer, and prostate cancer. Overall, the study confirms the negative associations between dietary flavonoids consumption and type 2 diabetes mellitus, cardiovascular diseases, breast cancer, colorectal cancer, lung cancer, and mortality, while positive associations are observed for prostate cancer and uterine fibroids. CONCLUSION: Although dietary flavonoids are significantly associated with many outcomes, firm generalizable conclusions about their beneficial or harmful effects cannot be drawn because of the low certainty of evidence for most of outcomes. More well-designed primary studies are needed.

Ultrasound-targeted microbubble destruction rapidly improves left ventricular function in rats with ischemic cardiac dysfunction.

BACKGROUND: Previous studies have demonstrated the efficacy of ultrasound-targeted microbubble destruction (UTMD) in the treatment of ischemic heart failure (HF). The purpose of this study was to explore the mechanism by which UTMD improves ischemic HF. METHODS: An ischemic heart failure model was established using Sprague-Dawley rats. Rats were randomly divided into 7 groups: sham group, HF group, HF + MB group, HF + ultrasound (US) group, HF + UTMD group, HF + UTMD+LY294002 group, and HF + LY294002 group. Serum BNP level and echocardiographic parameters were measured to evaluate cardiac function. PI3K/Akt/eNOS signaling pathway protein levels were detected by immunohistochemistry (IHC) and western blotting. The concentrations of nitrous oxide (NO) and ATP were detected by ELISA, and hematoxylin and eosin (HE) staining was used to evaluate myocardial tissue. RESULTS: UTMD rapidly improved ejection fraction (EF) (HF: 37.16 ± 1.21% vs. HF + UTMD: 46.31 ± 3.00%, P < 0.01) and fractional shortening (FS) (HF: 18.53 ± 0.58% vs. HF + UTMD: 24.05 ± 1.84%, P < 0.01) in rats with ischemic HF. UTMD activated the PI3K/AKT/eNOS signaling pathway (HF vs. HF + UTMD, P < 0.01) and promoted the release of NO and ATP (HF vs. HF + UTMD, both, P < 0.05). Inhibition of the PI3K/AKT/eNOS signaling pathway by LY294002 worsened EF (HF: 37.16 ± 1.21% vs. HF + LY294002: 32.73 ± 3.05%, P < 0.05), and the release of NO and ATP by UTMD (HF + UTMD vs. HF + UTMD+LY294002, P < 0.05). CONCLUSIONS: UTMD can rapidly improve cardiac function in ischemic HF by activating the PI3K/Akt/eNOS signaling pathway and promoting the release of NO and ATP.

Sex- and time-specific associations of obesity with glycaemic traits: A two-step multivariate Mendelian randomization study.

AIM: To assess the sex- and time-specific causal effects of obesity-related anthropometric traits on glycaemic traits. MATERIALS AND METHODS: We used univariate and multivariate Mendelian randomization to assess the causal associations of anthropometric traits (gestational variables, birth weight, childhood body mass index [BMI], BMI, waist-to-hip ratio [WHR], BMI-adjusted WHR [WHRadj BMI]) with fasting glucose and insulin in Europeans from the Early Growth Genetics Consortium (n ≤ 298 142), the UK Biobank, the Genetic Investigation of Anthropometric Traits Consortium (n ≤ 697 734; females: n ≤ 434 794; males: n ≤ 374 754) and the Meta-Analyses of Glucose and Insulin-related traits Consortium (n ≤ 151 188; females: n ≤ 73 089; males: n ≤ 67 506), adjusting for maternal genetic effects, smoking, alcohol consumption, and age at menarche. RESULTS: We observed a null association for gestational variables, a negative association for birth weight, and positive associations for childhood BMI and adult traits (BMI, WHR, and WHRadj BMI). In female participants, increased birth weight causally decreased fasting insulin (betaIVW , -0.07, 95% confidence interval [CI] -0.11 to -0.03; p = 1.92 × 10-3 ), but not glucose levels, which was annulled by adjusting for age at menarche. In male participants, increased birth weight causally decreased fasting glucose (betainverse-variance-weighted (IVW) , -0.07, 95% CI -0.11 to -0.03; p = 3.22 × 10-4 ), but not insulin levels. In time-specific analyses, independent effects of birth weight were absent in female participants, and were more pronounced in male participants. Independent effects of childhood BMI were attenuated in both sexes; independent effects of adult traits differed by sex. CONCLUSIONS: Our findings provide evidence for causal and independent effects of sex- and time-specific anthropometric traits on glycaemic variables, and highlight the importance of considering multiple obesity exposures at different time points in the life course.

Effects of adding adjuvants to propofol on the post-anesthesia cognitive function in patients undergoing gastroscopy/colonoscopy: a systematic review and meta-analysis.

OBJECTIVES: This study aimed to elucidate the effects of propofol plus adjuvants on postoperative cognitive dysfunction (POCD) and patient satisfaction. METHODS: Studies published up to September 2023 on the Chinese National Knowledge Infrastructure (CNKI), Wanfang Data, Sinomed, PubMed, Embase, Cochrane Library, Web of Science, and Clinictrials.gov websites were searched. Binary summary of results was used for meta-analyses. RESULTS: We included 18 studies (2691 patients). The combined sedation did not affect the processing speed (ES = 0.02, 95%CI: -0.01, 0.04; I2 = 79.3%, p < 0.001), attention (ES = 0.02, 95%CI: -0.02, 0.05; I2 = 95.0%, p < 0.001), nor working memory (ES = 0.02, 95%CI: -0.03, 0.06; I2 = 94.4%, p < 0.001) in CogState brief battery tool. A significant effect of combined sedation was observed in the domain of visual learning in CogState tool (ES = -0.03, 95%CI: -0.04, -0.02; I2 = 15.8%, p = 0.306). The TDT (ES = 4.96, 95%CI: 2.92, 7.00) indicates that combined sedation would increase error rates in the tests of cognitive function. The DSST (ES = 0.16, 95% CI: -0.44, 0.75) shown that combined sedation does not affect cognitive function. In addition, an insignificant difference in patient satisfaction between combined sedation and propofol alone was observed (ES = -0.03, 95%CI: -0.09, 0.02). CONCLUSION: The available evidence suggests that propofol combined with adjuvants may affect POCD but not patient satisfaction. REGISTRATION NUMBER: INPLASY2023110092.

Systemic inflammation mediates the association between environmental tobacco smoke and depressive symptoms: A cross-sectional study of NHANES 2009-2018.

BACKGROUND: Depression is associated with both environmental tobacco smoke (ETS) and inflammation. However, whether systemic inflammation mediates the ETS-depression relationship is unclear. METHODS: We analyzed 19,612 participants from the 2009-2018 National Health and Nutrition Examination Survey (representing approximately 206,284,711 USA individuals), utilizing data of depressive symptoms (assessed by Patient Health Questionnaire-9), blood cotinine level (an ETS biomarker), dietary inflammatory index (DII, assessed by 24-h dietary recall) and inflammation, represented by immune-inflammation index (SII) and systemic inflammation response index (SIRI). RESULTS: Weighted multivariable logistic regression showed that a higher blood cotinine level is significantly associated with a higher depressive symptoms risk (OR = 1.79, 1.35-2.38). After adjusting for covariates, the effect in smokers (OR = 1.220, 95 % CI: 1.140-1.309) is larger than that in non-smokers (OR = 1.150, 95 % CI: 1.009-1.318). Compared to the lowest level, depressive symptoms risks in participants with the highest level of SII, SIRI and DII are 19 % (OR = 1.19, 1.05-1.35), 15 % (OR = 1.15, 1.01-1.31) and 88 % (OR = 1.88, 1.48-2.39) higher, respectively. Weighted linear regression demonstrated positive correlations of SII (ß = 0.004, 0.001-0.006), SIRI (ß = 0.009, 0.005-0.012) and DII (ß = 0.213, 0.187-0.240) with blood cotinine level. Restricted cubic splines model showed a linear dose-response relationship between blood cotinine and depressive symptoms (Pnon-linear = 0.410), with decreasing risk for lower DII. And SII and SIRI respectively mediate 0.21 % and 0.1 % of the association between blood cotinine and depressive symptoms. LIMITATION: Cross-sectional design, and lack of medication data for depression. CONCLUSIONS: Positive association of ETS (blood cotinine) with depressive symptoms risk is partly mediated by systemic inflammation, and anti-inflammatory diet could be beneficial.

Effects of bromine-containing counterion salts in directing the structures of medium-sized silver nanoclusters.

The preparation and structural determination of silver nanoclusters (especially the medium-sized Ag clusters) remain more challenging relative to those of their gold counterparts because of the comparative instability of the former. In this work, three medium-sized Ag clusters were controllably synthesized and structurally determined, namely, [Ag52(S-Adm)30Br4H20]2- (Ag52 for short), Ag54(S-Adm)30Br4H20 (Ag54 for short), and [Ag58(S-Adm)30Br4(NO3)2H22]2+ (Ag58 for short) nanoclusters. Specifically, the introduction of PPh4Br gave rise to the generation of Ag52 and Ag54 nanoclusters with homologous compositions and configurations, while the TOABr salt selected Ag58 as the sole cluster product, whose geometric structure was completely different from those of Ag52 and Ag54 nanoclusters. In addition, the optical absorptions and emissions of the three medium-sized silver nanoclusters were compared. The findings in this work not only provide three uniquely medium-sized nanoclusters to enrich the silver cluster family but also point out a new approach (i.e., changing the counterion salt) for the preparation of new nanoclusters with novel structures.

Shared Genetics and Comorbid Genes of Amyotrophic Lateral Sclerosis and Parkinson's Disease.

BACKGROUND: Comorbidity exists between amyotrophic lateral sclerosis (ALS) and Parkinson's disease (PD), but the role of genetic factors is unclear. OBJECTIVE: We aim to investigate genetic correlation, causal relationship, and comorbid genes between ALS and PD. METHODS: Leveraging the largest genome-wide association study data (ALS: 27,205 cases, 110,881 controls; PDG: 33,674 cases, 449,056 controls), we used linkage disequilibrium score regression and Mendelian randomization analysis for genetic correlation and causal inference. We performed genome-wide cross-trait analysis via Multi-Trait Analysis of Genome-Wide Association Studies and Cross-Phenotype Association to identify specific single-nucleotide polymorphisms, followed by functional mapping and annotation. Integrating expression quantitative trait loci data from 13 brain regions, we conducted a transcriptome-wide association study via functional summary-based imputation and joint-tissue imputation to explore comorbid genes, followed by pathway enrichment analysis. RESULTS: We found that PD positively correlates with ALS (rg = 0.144, P = 0.026) and confers a causal effect (odds ratio = 1.09, 95% confidence interval: 1.03-1.15, P = 3.00 × 10-3 ). We identified nine single-nucleotide polymorphisms (eight new), associating with three risk loci (chromosomes 4, 10, and 17) and seven genes (TMEM175, MAPT, NSF, LRRC37A2, ARHGAP27, GAK, and FGFRL1). In transcriptome-wide association study analysis, we showed six previously unreported pleiotropic genes (KANSL1, ARL17B, EFNA1, WNT3, ERCC8, and ADAM15), and we found these candidate genes are mainly enriched in negative regulation of neuron projection development (GO:0010977). CONCLUSIONS: Our work demonstrates shared genetic architecture between ALS and PD, reports new pleiotropic genes, and sheds light on the comorbid mechanism. © 2023 International Parkinson and Movement Disorder Society.

Investigating the shared genetic architecture of post-traumatic stress disorder and gastrointestinal tract disorders: a genome-wide cross-trait analysis.

BACKGROUND: Observational studies suggest a correlation between post-traumatic stress disorder (PTSD) and gastrointestinal tract (GIT) disorders. However, the genetic overlap, causal relationships, and underlining mechanisms between PTSD and GIT disorders were absent. METHODS: We obtained genome-wide association study statistics for PTSD (23 212 cases, 151 447 controls), peptic ulcer disease (PUD; 16 666 cases, 439 661 controls), gastroesophageal reflux disease (GORD; 54 854 cases, 401 473 controls), PUD and/or GORD and/or medications (PGM; 90 175 cases, 366 152 controls), irritable bowel syndrome (IBS; 28 518 cases, 426 803 controls), and inflammatory bowel disease (IBD; 7045 cases, 449 282 controls). We quantified genetic correlations, identified pleiotropic loci, and performed multi-marker analysis of genomic annotation, fast gene-based association analysis, transcriptome-wide association study analysis, and bidirectional Mendelian randomization analysis. RESULTS: PTSD globally correlates with PUD (rg = 0.526, p = 9.355 × 10-7), GORD (rg = 0.398, p = 5.223 × 10-9), PGM (rg = 0.524, p = 1.251 × 10-15), and IBS (rg = 0.419, p = 8.825 × 10-6). Cross-trait meta-analyses identify seven genome-wide significant loci between PTSD and PGM (rs13107325, rs1632855, rs1800628, rs2188100, rs3129953, rs6973700, and rs73154693); three between PTSD and GORD (rs13107325, rs1632855, and rs3132450); one between PTSD and IBS/IBD (rs4937872 and rs114969413, respectively). Proximal pleiotropic genes are mainly enriched in immune response regulatory pathways, and in brain, digestive, and immune systems. Gene-level analyses identify five candidates: ABT1, BTN3A2, HIST1H3J, ZKSCAN4, and ZKSCAN8. We found significant causal effects of GORD, PGM, IBS, and IBD on PTSD. We observed no reverse causality of PTSD with GIT disorders, except for GORD. CONCLUSIONS: PTSD and GIT disorders share common genetic architectures. Our work offers insights into the biological mechanisms, and provides genetic basis for translational research studies.

Slice Visualization for Imaging Nanocluster Transformations.

Metal nanoclusters have served as an emerging class of modular nanomaterials. Several efficient strategies have been proposed for transforming cluster precursors into new nanoclusters with customized structures and enhanced performance. However, such nanocluster transformations have still been in a "blind box" state, meaning that the existing intermediates were hard to track with atomic precision. Herein, we present a "slice visualization" approach for in-depth imaging of the nanocluster transformation from Au1Ag24(SR)18 to Au1Ag30(SR)20. With this approach, two cluster intermediates, namely, Au1Ag26(SR)19 and Au1Ag28(SR)20, were monitored with atomic precision. The four nanoclusters constituted a correlated Au1Ag24+2n (n = 0, 1, 2, and 3) cluster series with comparable structural features─the same Au1Ag12 icosahedral kernel but evolutionary peripheral motif structures. The mechanism of nanocluster structure growth was mapped in detail─insertion of Ag2(SR)1 or Ag-induced assembly of surface subunits. The presented "slice visualization" approach not only contributes an ideal cluster platform for in-depth investigations of structure-property correlations but also hopefully acts as a powerful means for obtaining clear information on nanocluster structure evolution.

Machine Learning to Predict the Response to Lenvatinib Combined with Transarterial Chemoembolization for Unresectable Hepatocellular Carcinoma.

BACKGROUND: Lenvatinib and transarterial chemoembolization (TACE) are first-line treatments for unresectable hepatocellular carcinoma (HCC), but the objective response rate (ORR) is not satisfactory. We aimed to predict the response to lenvatinib combined with TACE before treatment for unresectable HCC using machine learning (ML) algorithms based on clinical data. METHODS: Patients with unresectable HCC receiving the combination therapy of lenvatinib combined with TACE from two medical centers were retrospectively collected from January 2020 to December 2021. The response to the combination therapy was evaluated over the following 4-12 weeks. Five types of ML algorithms were applied to develop the predictive models, including classification and regression tree (CART), adaptive boosting (AdaBoost), extreme gradient boosting (XGBoost), random forest (RF), and support vector machine (SVM). The performance of the models was assessed by the receiver operating characteristic (ROC) curve and area under the receiver operating characteristic curve (AUC). The Shapley Additive exPlanation (SHAP) method was applied to explain the model. RESULTS: A total of 125 unresectable HCC patients were included in the analysis after the inclusion and exclusion criteria, among which 42 (33.6%) patients showed progression disease (PD), 49 (39.2%) showed stable disease (SD), and 34 (27.2%) achieved partial response (PR). The nonresponse group (PD + SD) included 91 patients, while the response group (PR) included 34 patients. The top 40 most important features from all 64 clinical features were selected using the recursive feature elimination (RFE) algorithm to develop the predictive models. The predictive power was satisfactory, with AUCs of 0.74 to 0.91. The SVM model and RF model showed the highest accuracy (86.5%), and the RF model showed the largest AUC (0.91, 95% confidence interval (CI): 0.61-0.95). The SHAP summary plot and decision plot illustrated the impact of the top 40 features on the efficacy of the combination therapy, and the SHAP force plot successfully predicted the efficacy at the individualized level. CONCLUSIONS: A new predictive model based on clinical data was developed using ML algorithms, which showed favorable performance in predicting the response to lenvatinib combined with TACE for unresectable HCC. Combining ML with SHAP could provide an explicit explanation of the efficacy prediction.

Association of daytime napping frequency and schizophrenia: a bidirectional two-sample Mendelian randomization study.

BACKGROUND: The bidirectional causal association between daytime napping frequency and schizophrenia is unclear. METHODS: A bidirectional two-sample Mendelian randomization (MR) analysis was conducted with summary statistics of top genetic variants associated with daytime napping frequency and schizophrenia from genome-wide association studies (GWAS). The single nucleotide polymorphisms (SNPs) data of daytime napping frequency GWAS came from the UK Biobank (n = 452,633) and 23andMe study cohort (n = 541,333), while the schizophrenia GWAS came from the Psychiatric Genomics Consortium (PGC, 36,989 cases and 113,075 controls). The inverse variance weighted (IVW) analysis was the primary method, with the weighted median, MR-Robust Adjusted Profile Score (RAPS), Radial MR and MR-Pleiotropy Residual Sum Outlier (PRESSO) as sensitivity analysis. RESULTS: The MR analysis showed a bidirectional causal relationship between more frequent daytime napping and the occurrence of schizophrenia, with the odds ratio (OR) for one-unit increase in napping category (never, sometimes, usually) on schizophrenia was 3.38 (95% confidence interval [CI]: 2.02-5.65, P = 3.58 × 10-6), and the beta for the occurrence of schizophrenia on daytime napping frequency was 0.0112 (95%CI: 0.0060-0.0163, P = 2.04 × 10-5). The sensitivity analysis obtained the same conclusions. CONCLUSION: Our findings support the bidirectional causal association between more daytime napping frequency and schizophrenia, implying that daytime napping frequency is a potential intervention for the progression and treatment of schizophrenia.

A Novel Blade Vibration Monitoring Experimental System Based on Blade Tip Sensing.

Due to its non-intrusive manner, blade tip timing (BTT) is considered a potential tool for the condition monitoring of turbomachinery. The challenge of BTT relates to significant under-sampled signal processing, which is induced by a lower number of probes. Signal processing assumes that the ability of the hardware system can meet the requirements of the software algorithm. The abilities of the hardware, including the time resolution of the data acquisition system (DAS) and the dynamic characteristics of rigs, are compromised, particularly when the rotating speed increases. This increase in speed causes two problems for BTT: (1) the rig is less stable, due to the reduction of dynamic stiffness; (2) the time resolution of the DAS can be inadequate for identification. To promote the performance of the hardware system, here a BTT rig was designed with high dynamic performance, including a new DAS with a time resolution of 10 ns. A variety of commonly used BTT signal processing methods are used to analyze the experimental data and verify the good reliability and validity of the experimental platform.

Association between dried fruit intake and pan-cancers incidence risk: A two-sample Mendelian randomization study.

Background: Observational studies have revealed that dried fruit intake may be associated with cancer incidence; however, confounding factors make the results prone to be disturbed. Therefore, we conducted a two-sample Mendelian randomization (MR) study to explore the causal relationship between dried fruit intake and 11 site-specific cancers. Materials and methods: Forty-three single nucleoside polymers (SNPs) with robust genome-wide association study (GWAS) evidence, strongly correlated with dried fruit intake, were used as instrumental variables (IVs) in this study. The summary-level genetic datasets of site-specific cancers were obtained from the Oncoarray oral cavity and oropharyngeal cancer consortium, International Lung Cancer Consortium, Breast Cancer Association Consortium (BCAC), Ovarian Cancer Association Consortium, PanScan1, and GWAS of other scholars. We analyzed the causality between dried fruit intake and 11 site-specific cancers using the inverse-variance-weighted (IVW) and weighted median (WM) methods. For the results of the MR analysis, Cochran's Q test was used to check for heterogeneity, and multiplicative random effects were used to evaluate the heterogeneity further. Gene pleiotropy was tested using MR-Egger regression and MR-PRESSO methods. In addition, the main results of this study were validated by using the summary statistical data from the FinnGen and UK Biobank databases, and adjusted body mass index (BMI), years of education, fresh fruit intake, and vitamin C using multivariable MR analysis to ensure the stability of the research results. Results: The evidence from IVW analyses showed that each increase of dried fruit intake by one standard deviation was statistically significantly associated with 82.68% decrease of oral cavity/pharyngeal cancer incidence risk (P = 0.0131), 67.01% decrease of lung cancer incidence risk (P = 0.0011), 77% decrease of squamous cell lung cancer incidence risk (P = 0.0026), 53.07% decrease of breast cancer incidence risk (P = 4.62 × 10-5), 39.72% decrease of ovarian cancer incidence risk (P = 0.0183), 97.26% decrease of pancreatic cancer incidence risk (P = 0.0280), 0.53% decrease of cervical cancer incidence risk (P = 0.0482); however, there was no significant effect on lung adenocarcinoma (P = 0.4343), endometrial cancer (P = 0.8742), thyroid cancer (P = 0.6352), prostate cancer (P = 0.5354), bladder cancer (P = 0.8996), and brain cancer (P = 0.8164). In the validation part of the study results, the causal relationship between dried fruit intake and lung cancer (P = 0.0043), squamous cell lung cancer (P = 0.0136), and breast cancer (P = 0.0192) was determined. After adjusting for the potential impact of confounders, the causal relationship between dried fruit intake and lung cancer (P = 0.0034), squamous cell lung cancer (P = 0.046), and breast cancer (P = 0.0001) remained. The sensitivity analysis showed that our results were stable and reliable. Conclusion: The intake of dried fruits may have a protective effect against some site-specific cancers. Therefore, health education and a reasonable adjustment of dietary proportions may help in the primary prevention of cancer.

Toll-Like Receptor 4 Regulates Rabies Virus-Induced Humoral Immunity through Recruitment of Conventional Type 2 Dendritic Cells to Lymph Organs.

Rabies, caused by rabies virus (RABV), is fatal to both humans and animals around the world. Effective clinical therapy for rabies has not been achieved, and vaccination is the most effective means of preventing and controlling rabies. Although different vaccines, such as live attenuated and inactivated vaccines, can induce different immune responses, different expressions of pattern recognition receptors (PRRs) also cause diverse immune responses. Toll-like receptor 4 (TLR4) is a pivotal PRR that induces cytokine production and bridges innate and adaptive immunity. Importantly, TLR4 recognizes various virus-derived pathogen-associated molecular patterns (PAMPs) and virus-induced damage-associated molecular patterns (DAMPs), usually leading to the activation of immune cells. However, the role of TLR4 in the humoral immune response induced by RABV has not yet been revealed. Based on TLR4-deficient (TLR4-/-) and wild-type (WT) mouse models, we report that TLR4-dependent recruitment of the conventional type 2 dendritic cells (CD8α- CD11b+ cDC2) into secondary lymph organs (SLOs) is critical for antigen presentation. cDC2-initiated differentiation of follicular helper T (Tfh) cells promotes the proliferation of germinal center (GC) B cells, the formation of GCs, and the production of plasma cells (PCs), all of which contribute to the production of RABV-specific IgG and virus-neutralizing antibodies (VNAs). Collectively, our work demonstrates that TLR4 is necessary for the recruitment of cDC2 and for the induction of RABV-induced humoral immunity, which is regulated by the cDC2-Tfh-GC B axis. IMPORTANCE Vaccination is the most efficient method to prevent rabies. TLR4, a well-known immune sensor, plays a critical role in initiating innate immune response. Here, we found that TLR4-deficient (TLR4-/-) mice suppressed the induction of humoral immune response after immunization with rabies virus (RABV), including reduced production of VNAs and RABV-specific IgG compared to that occurred in wild-type (WT) mice. As a consequence, TLR4-/- mice exhibited higher mortality than that of WT mice after challenge with virulent RABV. Importantly, further investigation found that TLR4 signaling promoted the recruitment of cDC2 (CD8α+ CD11b-), a subset of cDCs known to induce CD4+ T-cell immunity through their MHC-II presentation machinery. Our results imply that TLR4 is indispensable for an efficient humoral response to rabies vaccine, which provides new insight into the development of novel rabies vaccines.

Identification and Validation of a Prognostic Prediction Model of m6A Regulator-Related LncRNAs in Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC) is a highly invasive malignancy prone to recurrence, and patients with HCC have a low 5-year survival rate. Long non-coding RNAs (lncRNAs) play a vital role in the occurrence and development of HCC. N6-methyladenosine methylation (m6A) is the most common modification influencing cancer development. Here, we used the transcriptome of m6A regulators and lncRNAs, along with the complete corresponding clinical HCC patient information obtained from The Cancer Genome Atlas (TCGA), to explore the role of m6A regulator-related lncRNA (m6ARlnc) as a prognostic biomarker in patients with HCC. The prognostic m6ARlnc was selected using Pearson correlation and univariate Cox regression analyses. Moreover, three clusters were obtained via consensus clustering analysis and further investigated for differences in immune infiltration, immune microenvironment, and prognosis. Subsequently, nine m6ARlncs were identified with Lasso-Cox regression analysis to construct the prognostic signature m6A-9LPS for patients with HCC in the training cohort (n = 226). Based on m6A-9LPS, the risk score for each case was calculated. Patients were then divided into high- and low-risk subgroups based on the cutoff value set by the X-tile software. m6A-9LPS showed a strong prognosis prediction ability in the validation cohort (n = 116), the whole cohort (n = 342), and even clinicopathological stratified survival analysis. Combining the risk score and clinical characteristics, we established a nomogram for predicting the overall survival (OS) of patients. To further understand the mechanism underlying the m6A-9LPS-based classification of prognosis differences, KEGG and GO enrichment analyses, competitive endogenous RNA (ceRNA) network, chemotherapeutic agent sensibility, and immune checkpoint expression level were assessed. Taken together, m6A-9LPS could be used as a precise prediction model for the prognosis of patients with HCC, which will help in individualized treatment of HCC.

Steady-state and time-resolved upconversion photoluminescence in Yb3+-Er3+ co-doped transparent ceramics of YAG.

Transparent ceramics (TCs) represent a new family of functional hard materials. In this Letter, steady-state and time-resolved upconversion photoluminescence in Yb3+-Er3+ co-doped TC of yttrium aluminum garnet (TC-YAG) are reported for the first time, to the best of our knowledge. Under the excitation of near-infrared 940 nm laser at room temperature, the Yb3+-Er3+ co-doped TC-YAG emits intense multi-color luminescence consisting of cyan, green, and red groups of sharp lines. More excitingly, the green group of luminescence due to the transitions from 4S3/2 to 4I15/2 states of Er3+ are the prominent components with the average lifetime of ∼0.3ms. The internal quantum efficiency of the green luminescence is estimated to be 32.8%. A unique dual-resonance energy transfer from Yb3+ to Er3+ via the excited-state vibronic transitions is proposed as the principal mechanism of the strongest green luminescence of Er3+ ions in TC-YAG.

Wavelet Element Modelling for Inviscid Fluid-Solid Coupling Problem based on Partitioned Approach.

To provide a simple numerical formulation based on fixed grids, a wavelet element method for fluid-solid modelling is introduced in this work. Compared with the classical wavelet finite element method, the presented method can potentially handle more complex shapes. Considering the differences between the solid and fluid regions, a damping-like interface based on wavelet elements is designed, in order to ensure consistency between the two parts. The inner regions are constructed with the same wavelet function in space. In the time and spatial domains, a partitioned approach based on Jacobi iteration is combined with the pseudo-parallel calculation method. Numerical convergence analyses show that the method can serve as an alternative choice for fluid-solid coupling modelling.

Synthesis and catalytic performance of polydopamine supported metal nanoparticles.

Polydopamine (PDA) is an emerging nature-inspired biopolymer material that possesses many interesting properties including self-assembly and universal adhesion. PDA is also able to form coordination bonds with various metal ions, which can be reduced to metal nanoparticles (NPs) as a result of thermal annealing under protective environment. In this study, PDA has been utilized as a support material to synthesize Pt NPs in an aqueous solution at room temperature. The catalytic performance of the resulting PDA-Pt nanocomposite was evaluated using an electrochemical workstation which showed comparable activity to Pt/C material for hydrogen evolution reaction (HER). Furthermore, Cu, Ni, and Cu-Ni NPs supported on PDA were also obtained using this strategy with assistance of subsequent thermal annealing. The phase evolution of the NPs was studied by in-situ X-ray diffraction while the morphology of the nanoparticles was investigated using electron microscopic techniques. Preliminary results showed the NPs supported on PDA also possessed HER activity. This work demonstrates that PDA can be utilized as a potential support for synthesis of metal NPs that can be exploited in engineering applications such as catalysts.

Linking emotions to behaviors through deep transfer learning.

Human behavior refers to the way humans act and interact. Understanding human behavior is a cornerstone of observational practice, especially in psychotherapy. An important cue of behavior analysis is the dynamical changes of emotions during the conversation. Domain experts integrate emotional information in a highly nonlinear manner; thus, it is challenging to explicitly quantify the relationship between emotions and behaviors. In this work, we employ deep transfer learning to analyze their inferential capacity and contextual importance. We first train a network to quantify emotions from acoustic signals and then use information from the emotion recognition network as features for behavior recognition. We treat this emotion-related information as behavioral primitives and further train higher level layers towards behavior quantification. Through our analysis, we find that emotion-related information is an important cue for behavior recognition. Further, we investigate the importance of emotional-context in the expression of behavior by constraining (or not) the neural networks' contextual view of the data. This demonstrates that the sequence of emotions is critical in behavior expression. To achieve these frameworks we employ hybrid architectures of convolutional networks and recurrent networks to extract emotion-related behavior primitives and facilitate automatic behavior recognition from speech.