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Filgotinib has been approved for the treatment of rheumatoid arthritis (RA) in adults who respond inadequately to disease-modifying antirheumatic drugs (DMARDs) in Europe and Japan. Several randomized controlled trials (RCTs) have investigated its efficacy and safety in adult patients with RA. This meta-analysis aimed to study the efficacy and safety of filgotinib in patients with RA withan inadequate response to methotrexateor other DMARDs.A systematic literature search was conducted to identify articles in PubMed, MEDLINE, EMBASE, and Cochrane Library from inceptionto December 1, 2021. Outcomes of interest included ACR20/50/70 responses, DAS28-CRP ≤ 3.2, SF-36 PCS Score, FACIT-fatigue, SDAI,CDAI, and HAQ-DI, which were assessed after treatment. The safety outcomes included treatment-emergent adverse events (TEAEs) and serious TEAEs. Odds ratios (ORs) with 95% confidence intervals (CI) were pooled for categorical variables, and the mean difference with 95%CI were pooled for continuous variables. We used Review Manager 5.3 for the standard meta-analysis. This study followed the guidelines of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA).Four RCTs comparing filgotinib (200 and 100 mg once daily) with placebo were identified. Compared with placebo, 200 and 100 mg filgotinib was more effective in achieving ACR20/50/70 responses and other outcomes at weeks 12 and 24 (Plt; 0.05), with no significant difference in safety outcomes (Pgt; 0.05). Filgotinib 200 mg performed better than filgotinib 100 mg in terms of ACR20/50 responses, DAS28-CRP ≤ 3.2, SDAI, and CDAI at weeks 12 and 24, and caused fewer serious TEAEs than the 100 mg dose.Filgotinib is effective in the treatment of RA, and the 200 mg dose has a more beneficialprofile thanthe 100 mg dose.

To explore the genetic basis for a child with mental retardation.The child was subjected to chromosomal microarray analysis (CMA) and targeted capture next-generation sequencing for the exons of genes related to genetic and metabolic diseases. Candidate variants were verified by Sanger sequencing of the child and his parents.CMA suggested that the child has a 47,XYY karyotype. Next-generation sequencing revealed that the child has harbored compound heterozygous variants of the AUH gene, including c.677GA (p.R226H) and c.373CT (p.R125W), which were respectively inherited from his parents. Based on the American college of Medical Genetics and Genomics (ACMG) standards and guidelines, the c.677GA (P.r226h) variant was predicted as variant of uncertain significance (PM2+PP4+PP3), whilst the c.373CT (P.R125W) variant was predicted as likely pathogenic (PM1+PM2+PP3+PP4).The child had XYY syndrome in conjunct with 3-methylglutaenedioic aciduria type I due to biallelic pathogenic variants of the AUH gene.

To investigate the relationship of mild-to-moderate simple bilateral fetal ventriculomegaly with postnatal neurological development.Cases of simple lateral ventricular dilatation (273) were divided into bilateral mild dilatation (10.0-12.0 mm, 62), bilateral moderate dilatation (12.1-15.0 mm, 29), unilateral mild dilatation (133), and unilateral moderate dilatation (49) groups. The control group comprised 50 normal fetuses. Neurological development was assessed using Gesell Developmental Schedules (GDS) at postnatal 3, 6, 12, and 18 months.At postnatal 6, 12, and 18 months, the GDS score was higher for bilateral than for unilateral dilatation (At postnatal month 6, the GDS evaluation results of the bilateral dilatation groups were significantly inferior compared to those of the unilateral dilatation group.

Background: There is still little research on the anti-aging effect of Pogostemon cablin Benth (PCB) on human skin. In this paper, the mechanism of the anti-aging effect of PCB on human skin was studied by using network pharmacology and molecular docking methods. Objective: To analyze the pharmacological mechanism of PCB in the treatment of skin aging to provide a reference for new drug development and clinical application. Methods: Active ingredients and related targets of PCB and skin aging-related disease targets are obtained through public databases, and the "drug-disease-target" and protein-protein interaction (PPI) network diagrams were constructed with the help of software to screen the core targets; then GO analysis and KEGG pathway analyses were performed on the target; finally, the molecular docking between the components and the targets were verified. Results: 112 intersection targets of active compounds of skin aging and PCB were obtained after the screening. GO, and KEGG enrichment analysis found that these biological processes mainly focus on epithelial cell proliferation, aging, growth factors, longevity regulation pathway, cancer pathway, AGE-RAGE signal pathway, PI3K Akt signal pathway and IL-17 signal pathway. The molecular docking results showed quercetin, apigenin, irisnepalensis isoflavone, 3,23-dihydroxy- 12-oleorene-28-oleic acid, 5-hydroxy-7,4'- dimethoxyflavone and other major compounds were connected with TP53, JUN, HSP90AAL, AKT1 and MAPK1 through hydrogen bonds, and there was high binding energy between them. Conclusion: Through multi-target prediction and molecular docking verification, it shows that PCB has a strong effect in the treatment of skin aging, which provides a reference for further research.

Huanglongbing (HLB) is a highly destructive disease that decreases the yield and quality of Citrus medica L. var. sarcodactylis Swingle (C. medica var. sarcodactylis) and poses a great threat to the development of the global citrus industry. To explore the influence of HLB infection on C. medica var. sarcodactylis, levels of photosynthetic pigments, malondialdehyde (MDA), and carbohydrates, as well as antioxidant enzyme activities, were measured. The results show that HLB infection decreased photosynthetic pigment content, increased MDA content and antioxidant enzyme activities, and caused various changes in carbohydrate levels in stem, fruit, and leaf tissues. Transcriptomic analysis of C. medica var. sarcodactylis was also used to identify key genes related to the carbohydrate metabolic synthesis pathway in C. medica var. sarcodactylis. The C. medica var. sarcodactylis ADP-glucose pyrophosphorylase1 (CmAGP1), CmAGP2, C. medica var. sarcodactylis Granule-bound starch synthase (CmGBSS), C. medica var. sarcodactylis Sucrose synthases1 (CmSUS1), CmSUS2, C. medica var. sarcodactylis Sucrose phosphate synthase (CmSPS), C. medica var. sarcodactylis alkaline/neutral invertase1 (CmNi1), CmNi2, CmNi3 and CmNi4 were successfully cloned and identified, and differential expression analysis showed that HLB infection significantly upregulated these genes in stems and leaves. In conclusion, HLB infection causes cellular damage, a reduction in photosynthetic capacity, decreased pathogen resistance, and severe disorders in carbohydrate metabolism in C. medica var. sarcodactylis. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s12298-022-01129-z.

Background Long non-coding RNAs (lncRNAs), which are key regulators of gene expression, are involved in lung cancer progression. Although numerous differentially expressed lncRNAs have been reported, merely a limited number of studies have been performed to verify their functions in lung cancer. Methods RNA sequencing data were re-analyzed to investigate the GATA6-AS1 expression in lung cancer. RT-qPCR was performed to verify the expression of GATA6-AS1 in collected tissue samples and cell lines. CCK-8 and transwell assays were carried out to evaluate the role of GATA6-AS1 in lung cancer cells. Dual-luciferase reporter assay and bioinformatic analysis were used to explore the miRNA which can be sponged by GATA6-AS1 in lung cancer cells. Results Currently, we focused on exploring the role and mechanisms of GATA6-AS1 in lung cancer. Expression of GATA6-AS1 was decreased in lung cancer based on the analysis of RNA sequencing dataset, TCGA data and RT-qPCR of clinical tissue samples. Via overexpression of GATA6-AS1, it was revealed that GATA6-AS1 inhibited lung cancer cell proliferation and invasion. Oncogene miR-324-5p was predicted to interact with GATA6-AS1. RT-qPCR and dual-luciferase reporter assay verified the regulation of miR-324-5p by GATG6-AS1 in lung cancer cells. Overexpression of GATA6-AS1 increased the expression of FBXO11 and SP1, two target genes of miR-324-5p. We further showed that miR-324-5p mimic reversed the effect of GATA6-AS1 overexpression in lung cancer cells. Conclusion Overall, our findings demonstrated GATA6-AS1 as a novel tumor suppressor in lung cancer.

Real-world systems, ranging from social to infrastructural, can be abstracted into complex networks. Promoting the spreading of some typical information (for instance, the commercial message, vaccination guidance, innovation, and political movement) on these networked systems can bring benefits to all aspects of society. In this study, we propose an effective edge-based approach for promoting the spreading of information on complex networks. Specifically, we first quantify the potential influence that the addition of each latent edge (that is, edges that do not exist before) could cause to the information spreading dynamics. Then, we strategically add the latent edges to the original networks according to the potential influence of each latent edge. Numerical simulations verify the effectiveness of our strategy and demonstrate that our strategy outperforms several static strategies, namely, adding the latent edges between nodes with the largest degree or eigenvector centrality. This study provides an effective way to promote the spreading of information by modifying the network structure slightly and helps in understanding what a better network structure for the spreading dynamics is. Besides, the theoretical framework established in this study provides inspirations for the further investigations of edge-based promoting strategies for other spreading dynamics.

Extensive real-data reveals that individuals exhibit heterogeneous contacting frequency in social systems. We propose a mathematical model to investigate the effects of heterogeneous contacting for information spreading in metapopulation networks. In the proposed model, we assume the number of contacting (NOC) distribution follows a specific distribution, including the normal, exponential, and power-law distributions. We utilize the Markov chain method to study the information spreading dynamics and find that mean and variance display no significant effect on the outbreak threshold for all the considered distributions. Under the same values of NOC distribution’s mean and variance, the information prevalence is largest when the distribution of NOC follows the normal distribution and second-largest for the exponential distribution, the smallest for the power-law distribution. When the distribution of NOC obeys the normal distribution, experimental results show that the information prevalence will decrease with individual contact ability heterogeneity. We observe similar phenomena when the distribution of NOC follows a power-law and exponential distribution. Furthermore, a larger mean of individual contact capacity distribution will result in higher information prevalence.

Interactions in biology and social systems are not restricted to pairwise but can take arbitrary sizes. Extensive studies have revealed that the arbitrary-sized interactions significantly affect the spreading dynamics on networked systems. Competing spreading dynamics, i.e., several epidemics spread simultaneously and compete with each other, have been widely observed in the real world, yet the way arbitrary-sized interactions affect competing spreading dynamics still lacks systematic study. This study presents a model of two competing simplicial susceptible-infected-susceptible epidemics on a higher-order system represented by simplicial complex and analyzes the model's critical phenomena. In the proposed model, a susceptible node can only be infected by one of the two epidemics, and the transmission of infection to neighbors can occur through pairwise (i.e., an edge) and high-order (e.g., 2-simplex) interactions simultaneously. Through a mean-field (MF) theory analysis and numerical simulations, we show that the model displays rich dynamical behavior depending on the 2-simplex infection strength. When the 2-simplex infection strength is weak, the model's phase diagram is consistent with the simple graph, consisting of three regions: the absolute dominant regions for each epidemic and the epidemic-free region. With the increase of the 2-simplex infection strength, a new phase region called the alternative dominant region emerges. In this region, the survival of one epidemic depends on the initial conditions. Our theoretical analysis can reasonably predict the time evolution and steady-state outbreak size in each region. In addition, we further explore the model's phase diagram both when the 2-simplex infection strength is symmetrical and asymmetrical. The results show that the 2-simplex infection strength has a significant impact on the system phase diagram., 12 pages, 7 figures

In biology and technology systems, the proper functioning of agents may be mutually interdependent, where the failure of an agent can cause the dysfunctionality of other dependent agents. Usually, we adopt the dependence network to capture such dependency relations among agents; however, the interdependency relations are only pairwise but could be of higher-order. In other words, an agent’s failure can induce the failure of several other nodes in a high-order interaction (e.g., the same group or clique) simultaneously. In this paper, we propose a generalized k -core percolation model to investigate the robustness of the higher-order dependent networks. In particular, we consider higher-order multi-layered dependency networks where both the interlayer and intralayer dependency relations are of a high order. We study the model using percolation theory and numerical simulations and find that the k -core percolation threshold and phase transition type depend on the average degree. Increasing the average degree enhances the system robustness. The system exhibits a discontinuous phase transition with a small k -core percolation threshold for networks with small average degree. Meanwhile, for networks with large average degrees, the system can either shows a continuous phase transition with a small k -core percolation threshold or a discontinuous phase transition with a large percolation threshold. In addition, we find that the intralayer dependency enhances the robustness of the system. Finally, we reveal that the degree heterogeneity makes the network more fragile. The above stated phenomena are well predicted by our developed percolation theory.

The inverse problem of finding the optimal network structure for a specific type of dynamical process stands out as one of the most challenging problems in network science. Focusing on the susceptible-infected-susceptible type of dynamics on annealed networks whose structures are fully characterized by the degree distribution, we develop an analytic framework to solve the inverse problem. We find that, for relatively low or high infection rates, the optimal degree distribution is unique, which consists of no more than two distinct nodal degrees. For intermediate infection rates, the optimal degree distribution is multitudinous and can have a broader support. We also find that, in general, the heterogeneity of the optimal networks decreases with the infection rate. A surprising phenomenon is the existence of a specific value of the infection rate for which any degree distribution would be optimal in generating maximum spreading prevalence. The analytic framework and the findings provide insights into the interplay between network structure and dynamical processes with practical implications.

Mitochondrial fatty acid oxidation (FAO) is involved in myocardial damage after cardiopulmonary resuscitation (CPR). This study is aimed at investigating the effect of inhibiting mitochondrial FAO on myocardial injury and the underlying mechanisms of postresuscitation myocardial dysfunction. Rats were induced, subjected to 8 min of ventricular fibrillation, and underwent 6 min of CPR. Rats with return of spontaneous circulation (ROSC) were randomly divided into the Sham group, CPR group, and CPR + Trimetazidine (TMZ) group. Rats in the CPR + TMZ group were administered TMZ (10 mg/kg) at the onset of ROSC via the right external jugular vein, while rats in the CPR group were injected with equivalent volumes of vehicle. The sham rats were only administered equivalent volumes of vehicle. We found that the activities of enzymes related to cardiac mitochondrial FAO were partly improved after ROSC. TMZ, as a reversible inhibitor of 3-ketoacyl CoA thiolase, inhibited myocardial mitochondrial FAO after ROSC. In the CPR + TMZ group, the levels of mitochondrial injury in cardiac tissue were alleviated following attenuated myocardial damage and oxidative stress after ROSC. In addition, the disorder of cardiac mitochondrial metabolism was ameliorated, and specifically, the superfluous succinate related to mitochondrial reactive oxygen species (ROS) generation was decreased by inhibiting myocardial mitochondrial FAO with TMZ administration after ROSC. In conclusion, in the early period after ROSC, inhibiting cardiac mitochondrial FAO attenuated excessive cardiac ROS generation and preserved myocardial function, probably by alleviating the dysfunction of cardiac mitochondrial metabolism in a rat model of cardiac arrest.

The network-based cooperative information spreading is a widely existing phenomenon in the real world. For instance, the spreading of disease outbreak news and disease prevention information often coexist and interact with each other on the Internet. Promoting the cooperative spreading of information in network-based systems is a subject of great importance in both theoretical and practical perspectives. However, very limited attention has been paid to this specific research area so far. In this study, we propose an effective approach for identifying the influential latent edges (that is, the edges that do not originally exist) which, if added to the original network, can promote the cooperative susceptible-infected-recovered (co-SIR) dynamics. To be specific, we first obtain the probabilities of each nodes being in different node states by the message-passing approach. Then, based on the state probabilities of nodes obtained, we come up with an indicator, which incorporates both the information of network topology and the co-SIR dynamics, to measure the influence of each latent edge in promoting the co-SIR dynamics. Thus, the most influential latent edges can be located after ranking all the latent edges according to their quantified influence. We verify the rationality and superiority of the proposed indicator in identifying the influential latent edges of both synthetic and real-world networks by extensive numerical simulations. This study provides an effective approach to identify the influential latent edges for promoting the network-based co-SIR information spreading model and offers inspirations for further research on intervening the cooperative spreading dynamics from the perspective of performing network structural perturbations.