A Bayesian framework for modeling COVID-19 case numbers through longitudinal monitoring of SARS-CoV-2 RNA in wastewater.

Wastewater-based surveillance has become an important tool for research groups and public health agencies investigating and monitoring the COVID-19 pandemic and other public health emergencies including other pathogens and drug abuse. While there is an emerging body of evidence exploring the possibility of predicting COVID-19 infections from wastewater signals, there remain significant challenges for statistical modeling. Longitudinal observations of viral copies in municipal wastewater can be influenced by noisy datasets and missing values with irregular and sparse samplings. We propose an integrative Bayesian framework to predict daily positive cases from weekly wastewater observations with missing values via functional data analysis techniques. In a unified procedure, the proposed analysis models severe acute respiratory syndrome coronavirus-2 RNA wastewater signals as a realization of a smooth process with error and combines the smooth process with COVID-19 cases to evaluate the prediction of positive cases. We demonstrate that the proposed framework can achieve these objectives with high predictive accuracies through simulated and observed real data.

Surveillance for SARS-CoV-2 and its variants in wastewater of tertiary care hospitals correlates with increasing case burden and outbreaks.

Wastewater-based SARS-CoV-2 surveillance enables unbiased and comprehensive monitoring of defined sewersheds. We performed real-time monitoring of hospital wastewater that differentiated Delta and Omicron variants within total SARS-CoV-2-RNA, enabling correlation to COVID-19 cases from three tertiary-care facilities with >2100 inpatient beds in Calgary, Canada. RNA was extracted from hospital wastewater between August/2021 and January/2022, and SARS-CoV-2 quantified using RT-qPCR. Assays targeting R203M and R203K/G204R established the proportional abundance of Delta and Omicron, respectively. Total and variant-specific SARS-CoV-2 in wastewater was compared to data for variant specific COVID-19 hospitalizations, hospital-acquired infections, and outbreaks. Ninety-six percent (188/196) of wastewater samples were SARS-CoV-2 positive. Total SARS-CoV-2 RNA levels in wastewater increased in tandem with total prevalent cases (Delta plus Omicron). Variant-specific assessments showed this increase to be mainly driven by Omicron. Hospital-acquired cases of COVID-19 were associated with large spikes in wastewater SARS-CoV-2 and levels were significantly increased during outbreaks relative to nonoutbreak periods for total SARS-CoV2, Delta and Omicron. SARS-CoV-2 in hospital wastewater was significantly higher during the Omicron-wave irrespective of outbreaks. Wastewater-based monitoring of SARS-CoV-2 and its variants represents a novel tool for passive COVID-19 infection surveillance, case identification, containment, and potentially to mitigate viral spread in hospitals.

Detecting PCOS susceptibility loci from genome-wide association studies via iterative trend correlation based feature screening.

BACKGROUND: Feature screening plays a critical role in handling ultrahigh dimensional data analyses when the number of features exponentially exceeds the number of observations. It is increasingly common in biomedical research to have case-control (binary) response and an extremely large-scale categorical features. However, the approach considering such data types is limited in extant literature. In this article, we propose a new feature screening approach based on the iterative trend correlation (ITC-SIS, for short) to detect important susceptibility loci that are associated with the polycystic ovary syndrome (PCOS) affection status by screening 731,442 SNP features that were collected from the genome-wide association studies. RESULTS: We prove that the trend correlation based screening approach satisfies the theoretical strong screening consistency property under a set of reasonable conditions, which provides an appealing theoretical support for its outperformance. We demonstrate that the finite sample performance of ITC-SIS is accurate and fast through various simulation designs. CONCLUSION: ITC-SIS serves as a good alternative method to detect disease susceptibility loci for clinic genomic data.

Urine cell-free DNA as a promising biomarker for early detection of non-small cell lung cancer.

BACKGROUND: While blood-derived cell-free DNA has been shown to be a candidate biomarker able to provide diagnostic and prognostic insight in cancer patients, little is known regarding the potential application of urine cell-free DNA (ucfDNA) in diagnosis of cancer. Thus, the aim of this study was to investigate ucfDNA concentration and integrity index as potential biomarkers for early detection of non-small-cell lung cancer (NSCLC). METHODS: Urine samples were collected from 35 healthy controls and 55 NSCLC patients at various tumor node metastasis (TNM) stages. Two long interspersed nuclear element 1 (LINE1) fragments (LINE1-97 and 266 bp) were quantified via quantitative real-time PCR (qPCR). DNA integrity index was calculated as the ratio of LINE1-266/LINE-97. RESULTS: LINE1 fragments concentrations of ucfDNA (LINE1-97, 266 bp) were significantly higher in NSCLC patients with stage III/IV than in stage I/II and in healthy controls. The receiver operating characteristic (ROC) curves for discriminating patients with stage III/IV from healthy controls had areas under the curves (AUC) of 0.84 and 0.886, respectively. Moreover, ucfDNA integrity LINE1-266/97 was significantly higher in patients with stage III/IV than in stage I/II and in healthy controls. The AUC of ROC curve for discriminating patients with stage III/IV from healthy controls was 0.800. Furthermore, LINE1-266 fragment concentration was significantly higher in lymph node metastasis (LNM)-positive patients relative to LNM-negative patients. The ROC curve for discriminating LNM-positive from LNM-negative patients had an AUC of 0.822. CONCLUSION: UcfDNA could serve as a promising biomarker for early detection of NSCLC.

[Neurobehavioral development of 25 254 children with different gestational ages at birth in three cities of China].

OBJECTIVE: To study the effect of gestational age at birth on the neurobehavioral development of preschool children. METHODS: A total of 25 254 preschool children from Ma'anshan of Anhui Province, Taizhou of Zhejiang Province, and Yangzhou of Jiangsu Province were enrolled. The preschool children were divided into three groups based on their gestational ages at birth: preterm group (2 760 cases; 28-36+6 weeks), early term group (6 005 cases; 37-38+6 weeks), and full term group (16 489 cases; ≥39 weeks). The Ages and Stages Questionnaires-Third Edition (ASQ-3) was employed to evaluate the children's neurobehavioral development. RESULTS: The preterm group had significantly lower scores of the five domains of ASQ-3, communication, gross motor, fine motor, problem solving, and personal-social, than the full term group (P<0.05), and significantly lower scores of communication, gross motor, fine motor, and problem solving than the early term group (P<0.05). There were no significant differences in the scores of the five domains of ASQ-3 between the early term and full term groups (P>0.05). The multiple linear regression analysis indicated a significant positive correlation between gestational age and the five domains of ASQ-3 after adjustment for confounding factors including sex, age, body mass index, and parental education level (P<0.01). CONCLUSIONS: Children born preterm have poorer neurobehavioral development than those born full term and early term, whereas children born full term and early term have similar neurobehavioral development. Gestational age at birth is an independent influencing factor for neurobehavioral development in preschool children.

An adaptive threshold determination method of feature screening for genomic selection.

BACKGROUND: Although the dimension of the entire genome can be extremely large, only a parsimonious set of influential SNPs are correlated with a particular complex trait and are important to the prediction of the trait. Efficiently and accurately selecting these influential SNPs from millions of candidates is in high demand, but poses challenges. We propose a backward elimination iterative distance correlation (BE-IDC) procedure to select the smallest subset of SNPs that guarantees sufficient prediction accuracy, while also solving the unclear threshold issue for traditional feature screening approaches. RESULTS: Verified through six simulations, the adaptive threshold estimated by the BE-IDC performed uniformly better than fixed threshold methods that have been used in the current literature. We also applied BE-IDC to an Arabidopsis thaliana genome-wide data. Out of 216,130 SNPs, BE-IDC selected four influential SNPs, and confirmed the same FRIGIDA gene that was reported by two other traditional methods. CONCLUSIONS: BE-IDC accommodates both the prediction accuracy and the computational speed that are highly demanded in the genomic selection.

Bisdemethoxycurcumin sensitizes cisplatin-resistant lung cancer cells to chemotherapy by inhibition of CA916798 and PI3K/AKT signaling.

Curcumin, a dietary supplement or herbal medicine from Curcuma longa, has shown antitumor activity in different cancer cell lines and clinical trials. CA916798, a novel protein, is overexpressed in multidrug-resistant tumor cells. This study aimed to assess the effects of curcumin on regulating chemosensitivity in cisplatin-resistant non-small cell lung cancer (NSCLC) cells in vitro and to explore the underlying molecular mechanisms. Human cisplatin-sensitive A549 and cisplatin-resistant A549/CDDP lung adenocarcinoma cells were treated with curcumin to assess cell viability and gene modulations using quantitative reverse transcription-polymerase chain reaction (qRT-PCR) and western blotting. CA916798 shRNA and point mutations were used to assess the CA916798 functions and phosphorylation sites. Bisdemethoxycurcumin sensitized cisplatin-resistant lung cancer cells to various chemotherapeutic agents, including cisplatin. Bisdemethoxycurcumin reduced the levels of CA916798 mRNA and protein in A549 and A549/CDDP cells, while it also suppressed phosphatidylinositol-3-kinase (PI3K)/AKT signaling. CA916798, as a downstream gene, interacted with AKT after bisdemethoxycurcumin treatment in A549 and A549/CDDP cells. Moreover, A549/CDDP cells expressing the point-mutated CA916798-S20D protein were more resistant to cisplatin and bisdemethoxycurcumin, whereas tumor cells expressing CA916798-S20A, CA916798-S31A, CA916798-S60A, CA916798-S93A, or CA916798-T97A (different sites of amino acid phosphorylation) showed similar sensitivity or resistance to cisplatin and bisdemethoxycurcumin, compared with the control cells. Bisdemethoxycurcumin is able to sensitize cisplatin-resistant NSCLC cells to chemotherapeutic agents by inhibition of CA916798 and PI3K/AKT activities. Moreover, phosphorylation of CA916798 at the S20 residue plays a critical role in mediating bisdemethoxycurcumin antitumor activity.

Quantitative gene-gene and gene-environment mapping for leaf shape variation using tree-based models.

Leaf shape traits have long been a focus of many disciplines, but the complex genetic and environmental interactive mechanisms regulating leaf shape variation have not yet been investigated in detail. The question of the respective roles of genes and environment and how they interact to modulate leaf shape is a thorny evolutionary problem, and sophisticated methodology is needed to address it. In this study, we investigated a framework-level approach that inputs shape image photographs and genetic and environmental data, and then outputs the relative importance ranks of all variables after integrating shape feature extraction, dimension reduction, and tree-based statistical models. The power of the proposed framework was confirmed by simulation and a Populus szechuanica var. tibetica data set. This new methodology resulted in the detection of novel shape characteristics, and also confirmed some previous findings. The quantitative modeling of a combination of polygenetic, plastic, epistatic, and gene-environment interactive effects, as investigated in this study, will improve the discernment of quantitative leaf shape characteristics, and the methods are ready to be applied to other leaf morphology data sets. Unlike the majority of approaches in the quantitative leaf shape literature, this framework-level approach is data-driven, without assuming any pre-known shape attributes, landmarks, or model structures.

Lymphocyte-derived microparticles induce apoptosis of airway epithelial cells through activation of p38 MAPK and production of arachidonic acid.

The airway epithelium is critical for the normal integrity and function of the respiratory system. Excessive epithelial cell apoptosis contributes to cell damage and airway inflammation. We previously demonstrated that lymphocyte-derived microparticles (LMPs) induce apoptosis of human bronchial epithelial cells. However, the underlying mechanisms contributing to LMPs-evoked epithelial cell death are largely unknown. Here we used bronchial and lung tissue cultures to confirm the pro-apoptotic effects of LMPs. In cell culture experiments, we found that LMPs induced human airway epithelial cell apoptosis with associated increases in caspase-3 activity. In addition, LMPs treatment triggered oxidative stress in epithelial cells by enhancing production of malondialdehyde, superoxide, and reactive oxygen species (ROS), and by inhibiting production of the antioxidant glutathione. Moreover, decreasing cellular ROS with the antioxidant N-acetylcysteine rescued epithelial cell viability. Together, these results demonstrate an important role for oxidative stress in LMPs-induced cell death. In epithelial cells, LMPs treatment induced phosphorylation of p38 MAPK and arachidonic acid accumulation. Moreover, arachidonic acid was significantly cytotoxic towards LMPs-treated epithelial cells, whereas inhibition of p38 MAPK was protective against these cytotoxic effects. Similarly, inhibition of arachidonic acid production led to decreased caspase-3 activity, thus rescuing airway epithelial cells from LMPs-induced cell death. In conclusion, our results show that LMPs induce airway epithelial cell apoptosis by activating p38 MAPK signaling and stimulating production of arachidonic acid, with consequent increases in oxidative stress and caspase-3 activity. As such, LMPs may be regarded as deleterious markers of epithelial cell damage in respiratory diseases.

The role of circadian rhythms and sleep in the aetiology of autism spectrum disorder and attention-deficit/hyperactivity disorder: New evidence from bidirectional two-sample Mendelian randomization analysis.

LAY ABSTRACT: Research shows that people with autism spectrum disorder and attention-deficit/hyperactivity disorder often have sleep issues and problems with the body's natural daily rhythms, known as circadian rhythms. By exploring the genetic variants associated with these rhythms and the conditions, this study reveals that these rhythm changes and sleep patterns are directly linked to autism spectrum disorder and attention-deficit/hyperactivity disorder. It found that the timing of one's most active hours can increase the likelihood of having both autism spectrum disorder and attention-deficit/hyperactivity disorder. Importantly, it also shows that good sleep quality might protect against autism spectrum disorder, while disturbed sleep in people with attention-deficit/hyperactivity disorder seems to be a result rather than the cause of the condition. This understanding can help doctors and researchers develop better treatment approaches that focus on the specific ways sleep and body rhythms affect those with autism spectrum disorder and attention-deficit/hyperactivity disorder, considering their unique associations with circadian rhythms and sleep patterns. Understanding these unique links can lead to more effective, personalized care for those affected by these conditions.

Autologous transplantation of P63+ lung progenitor cells for chronic obstructive pulmonary disease therapy.

Adult lung resident stem/progenitor cells, including P63+ progenitor cells, have demonstrated the capacity for regeneration of lung epithelium in preclinical models. Here, we report a clinical trial of intrapulmonary P63+ progenitor cell transplantation in 28 participants with stage II to IV chronic obstructive pulmonary disease (COPD). Autologous P63+ progenitor cells were isolated from the airway basal layer of participants in the intervention group via bronchoscopic brushing, cultured for 3 to 5 weeks, and then transplanted back into the lungs via bronchoscopy at 0.7 × 106 to 5.2 × 106 cells per kilogram of body weight. Twenty patients were evaluable at the end of the study (intervention group, n = 17; control group, n = 3). No grade 3 to 5 adverse events (AEs) or serious AEs occurred. Although bronchoscopy-associated AEs were recorded in participants in the intervention group, other AEs were not substantial different between groups. Twenty-four weeks after transplantation, participants in the intervention group displayed improvement in gas transfer capacity [diffusing capacity of the lung for carbon monoxide (DLCO) change from baseline: +18.2%], whereas the control group experienced a decrease (DLCO change from baseline: -17.4%; P = 0.008). Furthermore, participants in the intervention group showed >30-meter increase in walking distance within 6 minutes. Transcriptomic analysis of progenitor cells isolated from responding and nonresponding individuals in the intervention group showed that higher expression of P63 was associated with treatment efficacy. In conclusion, transplantation of cultured P63+ lung progenitor cells was safe and might represent a potential therapeutic strategy for COPD.

A Bayesian genomic selection approach incorporating prior feature ordering and population structures with application to coronary artery disease.

Coronary artery disease is one of the most common types of cardiovascular disease. Death from coronary heart disease is influenced by genetic factors in both women and men. In this article, we propose a novel Bayesian variable selection framework for the identification of important genetic variants associated with coronary artery disease disease status. Instead of treating each feature independently as in conventional Bayesian variable selection methods, we propose an innovative prior for the inclusion probabilities of genetic variants that accounts for their ordering structure. We assume that neighboring variants are more likely to be selected together as they tend to be highly correlated and have similar biological functions. Additionally, we propose to group participating subjects based on underlying population structure and fit separate regressions, so that the regression coefficients can better reflect different disease risks in different population groups. Our approach borrows strength across regression models through an innovative prior inspired by the Markov random fields. The proposed framework can improve variable selection and prediction performances as demonstrated in the simulation studies. We also apply the proposed framework to the CATHeterization GENetics data with binary Coronary artery disease disease status.

Wastewater-based surveillance can be used to model COVID-19-associated workforce absenteeism.

Wastewater-based surveillance (WBS) of infectious diseases is a powerful tool for understanding community COVID-19 disease burden and informing public health policy. The potential of WBS for understanding COVID-19's impact in non-healthcare settings has not been explored to the same degree. Here we examined how SARS-CoV-2 measured from municipal wastewater treatment plants (WWTPs) correlates with workforce absenteeism. SARS-CoV-2 RNA N1 and N2 were quantified three times per week by RT-qPCR in samples collected at three WWTPs servicing Calgary and surrounding areas, Canada (1.4 million residents) between June 2020 and March 2022. Wastewater trends were compared to workforce absenteeism using data from the largest employer in the city (>15,000 staff). Absences were classified as being COVID-19-related, COVID-19-confirmed, and unrelated to COVID-19. Poisson regression was performed to generate a prediction model for COVID-19 absenteeism based on wastewater data. SARS-CoV-2 RNA was detected in 95.5 % (85/89) of weeks assessed. During this period 6592 COVID-19-related absences (1896 confirmed) and 4524 unrelated absences COVID-19 cases were recorded. A generalized linear regression using a Poisson distribution was performed to predict COVID-19-confirmed absences out of the total number of absent employees using wastewater data as a leading indicator (P < 0.0001). The Poisson regression with wastewater as a one-week leading signal has an Akaike information criterion (AIC) of 858, compared to a null model (excluding wastewater predictor) with an AIC of 1895. The likelihood-ratio test comparing the model with wastewater signal with the null model shows statistical significance (P < 0.0001). We also assessed the variation of predictions when the regression model was applied to new data, with the predicted values and corresponding confidence intervals closely tracking actual absenteeism data. Wastewater-based surveillance has the potential to be used by employers to anticipate workforce requirements and optimize human resource allocation in response to trackable respiratory illnesses like COVID-19.

Campus node-based wastewater surveillance enables COVID-19 case localization and confirms lower SARS-CoV-2 burden relative to the surrounding community.

Wastewater-based surveillance (WBS) has been established as a powerful tool that can guide health policy at multiple levels of government. However, this approach has not been well assessed at more granular scales, including large work sites such as University campuses. Between August 2021 and April 2022, we explored the occurrence of SARS-CoV-2 RNA in wastewater using qPCR assays from multiple complimentary sewer catchments and residential buildings spanning the University of Calgary's campus and how this compared to levels from the municipal wastewater treatment plant servicing the campus. Real-time contact tracing data was used to evaluate an association between wastewater SARS-CoV-2 burden and clinically confirmed cases and to assess the potential of WBS as a tool for disease monitoring across worksites. Concentrations of wastewater SARS-CoV-2 N1 and N2 RNA varied significantly across six sampling sites - regardless of several normalization strategies - with certain catchments consistently demonstrating values 1-2 orders higher than the others. Relative to clinical cases identified in specific sewersheds, WBS provided one-week leading indicator. Additionally, our comprehensive monitoring strategy enabled an estimation of the total burden of SARS-CoV-2 for the campus per capita, which was significantly lower than the surrounding community (p≤0.001). Allele-specific qPCR assays confirmed that variants across campus were representative of the community at large, and at no time did emerging variants first debut on campus. This study demonstrates how WBS can be efficiently applied to locate hotspots of disease activity at a very granular scale, and predict disease burden across large, complex worksites.

Discussion of tumor mutation burden as an indicator to predict efficacy of immune checkpoint inhibitors: A case report.

There are many treatment options for advanced lung cancer, among which immunotherapy has developed rapidly and benefited a lot of patients. However, immunotherapy can only benefit a subgroup of patients, and how to select patients suitable for this therapy is critical. Tumor mutation burden (TMB) is one of the important reference indicators for immune checkpoint inhibitors (ICIs). However, there are many factors influencing the usage of this indicator, which will lead to considerable consequences if not treated well. In this study, we performed a case study on a male advanced lung squamous cell carcinoma patient of age 83. The patient suffered from "cough and sputum", and did chest CT scans on 24 October 2018, which showed "a mass-like mass in the anterior segment of the right lung upper lobe, about 38mm×28mm". He was treated with systemic chemotherapy; however, the tumor was still under progression. Although PD-L1 was not tested in gene testing, he had a TMB value of 10.26 mutations/Mb with a quantile value 88.63%. Thus, "toripalimab injection" was added as immunotherapy and the size of the lesion decreased. In summary, we adopted a clinical case as the basis to explore the value and significance of TMB in immunotherapy in this study. We hope that more predictive molecular markers will be discovered, which will bring more treatment methods for advanced lung cancer.

The sibling effect on neurodevelopment of preschoolers under China's newly relaxed child policy: A national retrospective cohort study.

Introduction: The change in Chinese fertility policy brings new challenges and considerations for children's health outcomes; however, very little is known about the interaction between siblings, family socioeconomic status (SES), and neurodevelopment in the Chinese preschool-age population. Therefore, this study aimed to develop a new explanatory pathway from sibling effect to early childhood development and explored the mediation effect of family SES in the pathway. Methods: From April 2018 to December 2019, we conducted a national retrospective cohort study in 551 cities in China, and a total of 115,915 preschool-aged children were selected for the final analysis. Children's neurodevelopment, including Communication, Gross motor, Fine motor, Problem-solving, and Personal-social, was assessed with the Ages & Stages Questionnaires, Third Edition (ASQ-3). Hypothesis tests and multilevel regression models were used to assess the associations and their strength between sibling effect and neurodevelopmental delay. Pathway analysis was used to verify the mediation effect of SES. Results: The results showed that there were significant risk effects of a sibling on preschoolers' overall neurodevelopment including communication, gross motor, fine motor, and problem-solving delay. The adjustment of family SES, however, brought a reversal of this association. The results of the mediation model illustrated a direct, protective effect of one-sibling status (ßASQ-delay = -0.09; ßASQ-scores = 0.07; p < 0.001), and an indirect, risk effect from one-sibling status through family SES to neurodevelopment outcomes (ßASQ-delay =0.12; ßASQ-scores = -0.12; p < 0.001). The total sibling effect was weakened but remained negative (ßASQ-delay =0.03; ßASQ-scores = -0.05; p < 0.001). Discussion: This study concluded that family SES mediated the negative effects of one sibling on early child development. To enhance the positive influence of sibling addition, we suggested providing more resources and instructions to the families with less educated and poorer employed parents under the coming multi-child era.

Statistical framework to support the epidemiological interpretation of SARS-CoV-2 concentration in municipal wastewater.

The ribonucleic acid (RNA) of the severe acute respiratory syndrome coronavirus 2 (SARS-Cov-2) is detectable in municipal wastewater as infected individuals can shed the virus in their feces. Viral concentration in wastewater can inform the severity of the COVID-19 pandemic but observations can be noisy and sparse and hence hamper the epidemiological interpretation. Motivated by a Canadian nationwide wastewater surveillance data set, unlike previous studies, we propose a novel Bayesian statistical framework based on the theories of functional data analysis to tackle the challenges embedded in the longitudinal wastewater monitoring data. By employing this framework to analyze the large-scale data set from the nationwide wastewater surveillance program covering 15 sampling sites across Canada, we successfully detect the true trends of viral concentration out of noisy and sparsely observed viral concentrations, and accurately forecast the future trajectory of viral concentrations in wastewater. Along with the excellent performance assessment using simulated data, this study shows that the proposed novel framework is a useful statistical tool and has a significant potential in supporting the epidemiological interpretation of noisy viral concentration measurements from wastewater samples in a real-life setting.

Network Pharmacology and Molecular Docking Study of the Chinese Miao Medicine Sidaxue in the Treatment of Rheumatoid Arthritis.

PURPOSE: This study aimed to investigate the molecular mechanisms of Compound Sidaxue (SX), a prescription of Chinese Miao medicine, in treating rheumatoid arthritis (RA) using network pharmacology and in vivo experimental approaches. METHODS: Network pharmacology was adopted to detect the active components of four Traditional Chinese herbal medicine (TCM) of SX, and the key targets and signaling pathways in the treatment of RA were predicted, and the key components and targets were screened for molecular docking. The predicted targets and pathways were validated in bovine type II collagen and incomplete Freund's adjuvant emulsifier-induced rat RA model. RESULTS: In this study, we identified 33 active components from SX, predicted to act on 44 RA-associated targets by network pharmacology. PPI network demonstrated that TNF-α, VEGF-A, IL-2, IL-6, AKT, PI3K, STAT1 may serve as the key targets of SX for the treatment of RA. The main functional pathways involving these key targets include PI3K-AKT signaling pathway, TNF signaling pathway, NF-κB signaling pathway. Molecular docking analysis found that the active components ß-amyrin, cajanin, eleutheroside A have high affinity for TNF-α, VEGFA, IL-2, AKT, and PI3K, etc. SX can improve joint swelling in Collagen-induced arthritis (CIA) rats, reduce inflammatory cell infiltration and angiogenesis in joint synovial tissue, and down-regulate IL-2, IL-6, TNF-α, VEGF, PI3K, AKT, p-AKT, NF-κBp65, the expression of p-NF-κBp65, STAT1, and PTGS2 are used to control the exacerbation of inflammation and alleviate the proliferation of synovial pannus, and at the same time play the role of cartilage protection to achieve the effect of treating RA. CONCLUSION: Through a network pharmacology approach and animal study, we predicted and validated the active compounds of SX and their potential targets for RA treatment. The results suggest that SX can markedly alleviate CIA rat by modulating the VEGF/PI3K/AKT signaling pathway, TNF-α signaling pathway, IL/NF-κB signaling pathway.

Prenatal second-hand smoke exposure and the risk of suspected developmental coordination disorder in preschoolers: A nationwide retrospective cohort study in China.

Prenatal exposure to second-hand smoke (SHS) is associated with increased neurodevelopmental problems in children, however, its impact on the risk of developmental coordination disorder (DCD) in preschoolers have not been studied thoroughly. Herein, we probed this association based on a nationwide retrospective cohort study of 149,005 preschoolers in China. We divided the objects into the prenatal SHS-exposed group or the no prenatal smoke exposed group (NS-exposed group). Preschoolers were assessed for motor proficiency by the Chinese version of Little Developmental Coordination Disorder Questionnaire (LDCDQ). Multivariable logistic regression was used to evaluate the associations. The prevalence of prenatal SHS exposure was 23.89%. Generally, the prevalence of suspected DCD was significantly higher in prenatal SHS-exposed group (16.38% VS. 14.19%, P < 0.001). With the increase of age, the mean total scores of LDCDQ of both boys and girls increased gradually; and the prevalence of suspected DCD in girls was higher than that in boys in the same age group. After adjusting for covariates, prenatal SHS exposure had the negative association with the total score of LDCDQ and increased the risk of suspected DCD. Our results suggest a need for interventions designed to reduce maternal SHS exposure during pregnancy, early screen for DCD and increase targeted movement and coordination skill training for vulnerable children.