Strongylocentrotus nudus egg polysaccharide (SEP) suppresses HBV replication via activation of TLR4-induced immune pathway.

Chronic hepatitis B virus (HBV) infection is a worldwide public health problem that causes significant liver-related morbidity and mortality. In our previous study, Strongylocentrotus nudus eggs polysaccharide (SEP), extracted from sea urchins, had immunomodulatory and antitumor effects. Whether SEP has anti-HBV activity is still obscure. This study demonstrated that SEP decreased the secretion of hepatitis B surface antigen (HBsAg) and e antigen (HBeAg), as well as the replication and transcription of HBV both in vitro and in vivo. Immunofluorescence and immunohistochemistry results showed that the level of HBV core antigen (HBcAg) was clearly reduced by SEP treatment. Mechanistically, RT-qPCR, western blot, and confocal microscopy analysis showed that SEP significantly increased the expression of toll-like receptor 4 (TLR4) and co-localization with TLR4. The downstream molecules of TLR4, including NF-κb and IRF3, were activated and the expression of IFN-ß, TNF-α, IL-6, OAS, and MxA were also increased, which could suppress HBV replication. Moreover, SEP inhibited other genotypes of HBV and hepatitis C virus (HCV) replication in vitro. In summary, SEP could be investigated as a potential anti-HBV drug capable of modulating the innate immune.

Temporal-spatial dynamic functional connectivity analysis in schizophrenia classification.

With the development of resting-state functional magnetic resonance imaging (rs-fMRI) technology, the functional connectivity network (FCN) which reflects the statistical similarity of temporal activity between brain regions has shown promising results for the identification of neuropsychiatric disorders. Alteration in FCN is believed to have the potential to locate biomarkers for classifying or predicting schizophrenia (SZ) from healthy control. However, the traditional FCN analysis with stationary assumption, i.e., static functional connectivity network (SFCN) at the time only measures the simple functional connectivity among brain regions, ignoring the dynamic changes of functional connectivity and the high-order dynamic interactions. In this article, the dynamic functional connectivity network (DFCN) is constructed to delineate the characteristic of connectivity variation across time. A high-order functional connectivity network (HFCN) designed based on DFCN, could characterize more complex spatial interactions across multiple brain regions with the potential to reflect complex functional segregation and integration. Specifically, the temporal variability and the high-order network topology features, which characterize the brain FCNs from region and connectivity aspects, are extracted from DFCN and HFCN, respectively. Experiment results on SZ identification prove that our method is more effective (i.e., obtaining a significantly higher classification accuracy, 81.82%) than other competing methods. Post hoc inspection of the informative features in the individualized classification task further could serve as the potential biomarkers for identifying associated aberrant connectivity in SZ.

Genetic Diagnostic Yield and Novel Causal Genes of Congenital Heart Disease.

Congenital heart disease (CHD) is the most common congenital malformation in fetuses and neonates, which also represents a leading cause of mortality. Although significant progress has been made by emerging advanced technologies in genetic etiology diagnosis, the causative genetic mechanisms behind CHD remain poorly understood and more than half of CHD patients lack a genetic diagnosis. Unlike carefully designed large case-control cohorts by multicenter trials, we designed a reliable strategy to analyze case-only cohorts to utilize clinical samples sufficiently. Combined low-coverage whole-genome sequencing (WGS) and whole-exome sequencing (WES) were simultaneously conducted in a patient-only cohort for identifying genetic etiologies and exploring candidate, or potential causative CHD-related genes. A total of 121 sporadic CHD patients were recruited and 34.71% (95% CI, 26.80 to 43.56) was diagnosed with genetic etiologies by low-coverage WGS and WES. Chromosomal abnormalities and damaging variants of CHD-related genes could explain 24.79% (95% CI, 17.92 to 33.22) and 18.18% (95% CI, 12.26 to 26.06) of CHD patients, separately, and 8.26% (95% CI, 4.39 to 14.70) of them have simultaneously detected two types of variants. Deletion of chromosome 22q11.2 and pathogenic variants of the COL3A1 gene were the most common recurrent variants of chromosomal abnormalities and gene variants, respectively. By in-depth manual interpretation, we identified eight candidate CHD-causing genes. Based on rare disease-causing variants prediction and interaction analysis with definitive CHD association genes, we proposed 86 genes as potential CHD-related genes. Gene Ontology (GO) enrichment analysis of the 86 genes revealed regulation-related processes were significantly enriched and processes response to regulation of muscle adaptation might be one of the underlying molecular mechanisms of CHD. Our findings and results provide new insights into research strategies and underlying mechanisms of CHD.

A Polysaccharide From Eupolyphaga sinensis Walker With Anti-HBV Activities In Vitro and In Vivo.

Hepatitis B virus (HBV) infection remains a major global threat to human health worldwide. Recently, the Chinese medicines with antiviral properties and low toxicity have been a concern. In our previous study, Eupolyphaga sinensis Walker polysaccharide (ESPS) has been isolated and characterized, while its antiviral effect on HBV remained unclear. The anti-HBV activity of ESPS and its regulatory pathway were investigated in vitro and in vivo. The results showed that ESPS significantly inhibited the production of HBsAg, HBeAg, and HBV DNA in the supernatants of HepG2.2.15 in a dose-dependent manner; HBV RNA and core protein expression were also decreased by ESPS. The in vivo studies using HBV transgenic mice further revealed that ESPS (20 and 40 mg/kg/2 days) significantly reduced the levels HBsAg, HBeAg, and HBV DNA in the serum, as well as HBV DNA and HBV RNA in mice liver. In addition, ESPS activated the Toll-like receptor 4 (TLR4) pathway; elevated levels of IFN-ß, TNF-α, and IL-6 in the serum were observed, indicating that the anti-HBV effect of ESPS was achieved by potentiating innate immunity function. In conclusion, our study shows that ESPS is a potential anti-HBV ingredient and is of great value in the development of new anti-HBV drugs.

Effects of food matrix elements (dietary fibres) on grapefruit peel flavanone profile and on faecal microbiota during in vitro fermentation.

Citrus fruits are a good source of flavanones. The present study aimed to assess the effect of food matrix elements [dietary fibres (DFs)] on the flavanone profile of grapefruit peel (GFP) and on the gut microbiota during in vitro digestion and simulated colonic fermentation. The contents of low-molecular-weight metabolites (dihydrocaffeic acid and 3-phenylpropionic acid) were increased by pectin, konjac and chitosan in medium- and high-viscosity matrices. Compared with the GFP group, the counts of Lactobacillus spp. and Clostridium leptum were significantly increased in medium-viscosity food matrices (konjac and chitosan) (p < 0.05). Moreover, the acetic and propionic acid contents were significantly elevated in the GFP + DF groups after 12 h of fermentation (p < 0.05). GFP flavanones were retained by DF, and the total phenolic content (TPC) and antioxidant potency composite (APC) index decreased during in vitro digestion. These findings indicate that medium-viscosity DFs (konjac and chitosan) could act as key food matrix elements for the retention of polyphenols.

Construction and investigation of a circRNA-associated ceRNA regulatory network in Tetralogy of Fallot.

BACKGROUND: As the most frequent type of cyanotic congenital heart disease (CHD), tetralogy of Fallot (TOF) has a relatively poor prognosis without corrective surgery. Circular RNAs (circRNAs) represent a novel class of endogenous noncoding RNAs that regulate target gene expression posttranscriptionally in heart development. Here, we investigated the potential role of the ceRNA network in the pathogenesis of TOF. METHODS: To identify circRNA expression profiles in TOF, microarrays were used to screen the differentially expressed circRNAs between 3 TOF and 3 control human myocardial tissue samples. Then, a dysregulated circRNA-associated ceRNA network was constructed using the established multistep screening strategy. RESULTS: In summary, a total of 276 differentially expressed circRNAs were identified, including 214 upregulated and 62 downregulated circRNAs in TOF samples. By constructing the circRNA-associated ceRNA network based on bioinformatics data, a total of 19 circRNAs, 9 miRNAs, and 34 mRNAs were further screened. Moreover, by enlarging the sample size, the qPCR results validated the positive correlations between hsa_circ_0007798 and HIF1A. CONCLUSIONS: The findings in this study provide a comprehensive understanding of the ceRNA network involved in TOF biology, such as the hsa_circ_0007798/miR-199b-5p/HIF1A signalling axis, and may offer candidate diagnostic biomarkers or potential therapeutic targets for TOF. In addition, we propose that the ceRNA network regulates TOF progression.

Respiratory syncytial virus infection in children and its correlation with climatic and environmental factors.

OBJECTIVE: In this study, we aimed to investigate the clinical epidemiology of lower respiratory tract infections with different respiratory syncytial virus (RSV) subtypes in hospitalized children in Suzhou and their correlation with climatic and environmental factors. METHOD: In this retrospective cross-sectional study, we collected nasopharyngeal secretion samples from children hospitalized with acute lower respiratory tract infection. We collected the clinical data of children with RSV infection, and compared and analyzed their epidemiological characteristics. RESULTS: RSV-B was the dominant strain in 2016. In 2018, RSV-A was the dominant strain. The positive detection rate of RSV-A was negatively correlated with monthly mean temperature, monthly mean wind speed, total monthly rainfall, and O3 concentration and positively correlated with PM2.5, PM10, and NO2, SO2, and CO concentrations. The positive detection rate of RSV-B was negatively correlated with monthly average temperature, monthly total rainfall, monthly sunshine duration, and O3 concentration and positively correlated with CO concentration. CONCLUSIONS: RSV-A was the main subtype detected in this study. The positive detection rate of RSV-A was related to temperature, wind speed, rainfall, PM2.5. PM10, and NO2, SO2, CO, and O3 concentrations. The positive detection rate of RSV-B was related to temperature, rainfall, sunshine time, and O3 concentration.

Dietary Vegetable Powders Modulate Immune Homeostasis and Intestinal Microbiota in Mice.

As the largest immune organ of the human body, the intestine also plays a vital role in nutrient digestion and absorption. Some vegetables are considered to have improvement effects on the intestine. This experiment explored the effects of freeze-dried asparagus, broccoli and cabbage powder on the intestinal immune homeostasis and microflora of mice. Thirty-two mice were divided into four groups (n = 8), including control group (fed normal diet), asparagus group (fed normal diet with 5% asparagus power), broccoli group (fed normal diet with 5% broccoli power) and cabbage group (fed normal diet with 5% cabbage power). The experiment lasted 21 days. The results showed that the serum immunoglobulin concentration (IgA and IgM) and intestinal cytokine content (like IFN-γ and TNF-α) were increased after vegetable powder supplement. The experiment also detected that vegetable powder supplementation changed intestinal flora and their metabolites (short-chain fatty acid), which showed that the abundance of Lachnospiraceae and Bacteroides were decreased, while the abundance of Firmicutes and Lactobacillus as well as propionic acid and butyric acid contents were increased. Together, these vegetable powders, especially cabbage, changed the intestinal immune response and microbial activity of mice.

Decoding Pigeon Behavior Outcomes during Goal-directed Decision Task by WSR Functional Network Analysis.

It is a hot research direction to reveal the working mechanism of brain by measuring the connection characteristics of brain function network. In this paper, to decode pigeon behavior outcomes in goal-directed decision task, an experiment based on plus maze was designed and the nidopallium caudolaterale (NCL) of the pigeon was selected as the target brain region. The local field potential (LFP) signals in the waiting area (WA) and turning area (TA) were recorded when the pigeons performed the goal-directed tasks. Then, the brain functional connection networks of the LFPs were constructed and the extracted features were applied to decode pigeon behavior outcomes. Firstly, continuous wavelet transform (CWT) was used to carried out time-frequency analysis and the task-related frequency band (40-60 Hz) was extracted. Then, weighted sparse representation (WSR) method was used to construct the functional connectivity network and the related network features were selected. Finally, k-nearest neighbor (kNN) algorithm was used to decode behavior outcomes. The results show that the energy difference between TA and WA in 40-60 Hz band is significantly higher than those in other bands. The selected features have good discriminability for the representation of the differences between WA and TA. The decoding results also suggest the classification performance of the different behavior outcomes. These results show the effectiveness of the WSR to construct the function network to decode behavior outcomes.

[Research on brain network for schizophrenia classification based on resting-state functional magnetic resonance imaging].

How to extract high discriminative features that help classification from complex resting-state fMRI (rs-fMRI) data is the key to improving the accuracy of brain disease recognition such as schizophrenia. In this work, we use a weighted sparse model for brain network construction, and utilize the Kendall correlation coefficient (KCC) to extract the discriminative connectivity features for schizophrenia classification, which is conducted with the linear support vector machine. Experimental results based on the rs-fMRI of 57 schizophrenia patients and 64 healthy controls show that our proposed method is more effective ( i.e., achieving a significantly higher classification accuracy, 81.82%) than other competing methods. Specifically, compared with the traditional network construction methods (Pearson's correlation and sparse representation) and the commonly used feature selection methods (two-sample t-test and Least absolute shrinkage and selection operator (Lasso)), the algorithm proposed in this paper can more effectively extract the discriminative connectivity features between the schizophrenia patients and the healthy controls, and further improve the classification accuracy. At the same time, the discriminative connectivity features extracted in the work could be used as the potential clinical biomarkers to assist the identification of schizophrenia.

Access to dihydropyrano[3,2-b]pyrrol-5-ones skeletons by N-heterocyclic carbene-catalyzed [3+3] annulations.

A novel and efficient NHC-catalyzed [3+3] annulation of enals with pyrrol-4-ones was developed, thus providing the dihydropyrano[3,2-b]pyrrol-5-one core structures with broad scope and good to excellent enantioselectivities. Notably, this strategy could also expand to the synthesis of axially chiral compounds and polysubstituted indoles.

A Two-Layer, Energy-Efficient Approach for Joint Power Control and Uplink-Downlink Channel Allocation in D2D Communication.

Energy efficiency (EE) is a critical performance indicator for the device-to-device (D2D) communication underlaying cellular networks due to limited battery capacity and serious interference between user equipment. In this study, we proposed a power control and channel allocation scheme for the EE maximization of the D2D pairs, while jointly reusing uplink-downlink resources and guaranteeing the cellular users' (CUs) quality of service (QoS). The formulated problem was a mixed-integer nonlinear programming (MINLP) problem, which is generally an unsolved non-deterministic polynomial-time hardness (NP-hard) problem within polynomial time. To make it tractable to solve, the original problem was divided into two sub-problems: power control and channel allocation. A power control algorithm based on the Lambert W function was proposed to maximize the EE of the individual D2D pair. Assigning either an uplink or downlink resource to reuse, the EE of each D2D pair was calculated using the power control results. A channel allocation scheme based on the Kuhn-Munkres algorithm utilized the EE weights to optimize the overall EE of the D2D pairs. The simulation results verified the theoretical analysis and proved that the proposed algorithm could remarkably improve the EE of D2D pairs while guaranteeing the QoS of the CUs.