Human Breast Milk Exosomal miRNAs are Influenced by Premature Delivery and Affect Neurodevelopment.

SCOPE: This study investigates the exosomal microRNA (miRNA) profiles of term and preterm breast milk, including the most abundant and differentially expressed (DE) miRNAs, and their impact on neurodevelopment in infants. METHODS AND RESULTS: Mature milk is collected from the mothers of term and preterm infants. Using high-throughput sequencing and subsequent data analysis, exosomal miRNA profiles of term and preterm human breast milk (HBM) are acquired and it is found that the let-7 and miR-148 families are the most abundant miRNAs. Additionally, 23 upregulated and 15 downregulated miRNAs are identified. MiR-3168 is the most upregulated miRNA in preterm HBM exosome, exhibiting targeting activity toward multiple genes involved in the SMAD and MAPK signaling pathways and playing a crucial role in early neurodevelopment. Additionally, the effects of miR-3168 on neurodevelopment is confirmed and it is determined that it is an essential factor in the differentiation of neural stem cells (NSCs). CONCLUSION: This study demonstrates that miRNA expression in breast milk exosomes can be influenced by preterm delivery, thereby potentially impacting neurodevelopment in preterm infants.

Association between type 2 inflammatory diseases and neurodevelopmental disorders in low-birth-weight children and adolescents.

Background: Evidence of the association of certain neurodevelopmental disorder with specific type 2 inflammatory (T2) disease has been found. However, the association of various neurodevelopmental disorders with T2 diseases as a whole remains unclear in low-birth-weight (LBW) infants. Objective: To evaluate the association of type 2 inflammatory (T2) diseases with intellectual disability (ID), autism spectrum disorder (ASD), attention deficit hyperactivity disorder (ADHD), and learning disability (LD) in LBW children and adolescents. Methods: The study sample was derived from 2005 to 2018 National Health Interview Survey sample child files. LBW children and adolescents aged 3-17 were included. History of T2 diseases (including asthma and atopic dermatitis) and four neurodevelopmental disorders were reported by adults in families. The relationship between T2 diseases and the risk of four neurodevelopmental disorders was investigated through multiple-weighted logistic regression. Age, sex, race/ethnicity, region, highest education in family and ratio of family income to the poverty threshold were adjusted as covariates for model estimation. Subgroup analyses were conducted by age stratification (3-11 and 12-17 years), sex (male and female), and race (white and non-white). Results: 11,260 LBW children aged 3-17 years [mean age (SE), 9.73 (0.05) years] were included, in which 3,191 children had T2 diseases. History of T2 diseases was associated with an increased risk of neurodevelopmental disorders, with an OR of 1.35 (95% CI, 0.99-1.84) for ID, 1.47 (95% CI, 1.05-2.05) for ASD, 1.81 (95% CI, 1.51-2.16) for ADHD, and 1.74 (95% CI, 1.49-2.04) for LD following the adjustment of all the covariates. The correlations between T2 disorders and each of the four neurodevelopmental disorders were significantly different by sex and race (all P for interaction < 0.001), and no differences were found in age stratification (all P for interaction > 0.05). Conclusion: In a nationally representative sample of children, we found a significant association of T2 diseases with ASD, ADHD, and LD, even after adjusting for demographic baseline. We also found that the association of T2 disease with neurodevelopmental disorders differed between sex and race. Further investigation is needed to evaluate causal relationships and elucidate their potential mechanisms.

Digital health integration for noncommunicable diseases: Comprehensive process mapping for full-life-cycle management.

AIM: To create a systematic digital health process mapping framework for full-life-cycle noncommunicable disease management grounded in key stakeholder engagement. METHODS: A triphasic, qualitative methodology was employed to construct a process mapping framework for digital noncommunicable disease management in Shanghai, China. The first phase involved desk research to examine current guidance and practices. In the second phase, pivotal stakeholders participated in focus group discussions to identify prevalent digital touchpoints across lifetime noncommunicable disease management. In the final phase, the Delphi technique was used to refine the framework based on expert insights and obtain consensus. RESULTS: We identified 60 digital touchpoints across five essential stages of full-life-cycle noncommunicable disease management. Most experts acknowledged the rationality and feasibility of these touchpoints. CONCLUSIONS: This study led to the creation of a comprehensive digital health process mapping framework that encompasses the entire life cycle of noncommunicable disease management. The insights gained emphasize the importance of a systemic strategic, person-centered approach over a fragmented, purely technocentric approach. We recommend that healthcare professionals use this framework as a linchpin for efficient disease management and seamless technology incorporation in clinical practice.

Fetal overgrowth and weight trajectories during infancy and adiposity in early childhood.

BACKGROUND: Large-for-gestational age (LGA), a marker of fetal overgrowth, has been linked to obesity in adulthood. Little is known about how infancy growth trajectories affect adiposity in early childhood in LGA. METHODS: In the Shanghai Birth Cohort, we followed up 259 LGA (birth weight >90th percentile) and 1673 appropriate-for-gestational age (AGA, 10th-90th percentiles) children on body composition (by InBody 770) at age 4 years. Adiposity outcomes include body fat mass (BFM), percent body fat (PBF), body mass index (BMI), overweight/obesity, and high adiposity (PBF >85th percentile). RESULTS: Three weight growth trajectories (low, mid, and high) during infancy (0-2 years) were identified in AGA and LGA subjects separately. BFM, PBF and BMI were progressively higher from low- to mid-to high-growth trajectories in both AGA and LGA children. Compared to the mid-growth trajectory, the high-growth trajectory was associated with greater increases in BFM and the odds of overweight/obesity or high adiposity in LGA than in AGA children (tests for interactions, all P < 0.05). CONCLUSIONS: Weight trajectories during infancy affect adiposity in early childhood regardless of LGA or not. The study is the first to demonstrate that high-growth weight trajectory during infancy has a greater impact on adiposity in early childhood in LGA than in AGA subjects. IMPACT: Large-for-gestational age (LGA), a marker of fetal overgrowth, has been linked to obesity in adulthood, but little is known about how weight trajectories during infancy affect adiposity during early childhood in LGA subjects. The study is the first to demonstrate a greater impact of high-growth weight trajectory during infancy (0-2 years) on adiposity in early childhood (at age 4 years) in subjects with fetal overgrowth (LGA) than in those with normal birth size (appropriate-for-gestational age). Weight trajectory monitoring may be a valuable tool in identifying high-risk LGA children for close follow-ups and interventions to decrease the risk of obesity.

Targeted exome sequencing strategy (NeoEXOME) for Chinese newborns using a pilot study with 3423 neonates.

BACKGROUND: Newborn screening (NBS) aims to detect congenital anomalies, and next-generation sequencing (NGS) has shown promise in this aspect. However, the NBS strategy for monogenic inherited diseases in China remains insufficient. METHODS: We developed a NeoEXOME panel comprising 601 genes that are relevant to the Chinese population found through extensive research on available databases. An interpretation system to grade the results into positive (high-risk, moderate-risk, and low-risk genotypes), negative, and carrier according to the American College of Medical Genetics (ACMG) guidelines was also developed. We validated the panel to evaluate its efficacy by using data from the "1000 Genomes Project" and conducted a pilot multicenter study involving 3423 neonates. RESULTS: The NGS positive rate in the 1000 Genomes Project was 7.6% (23/301), whereas the rate was 12.0% in the multicenter study, including 3249 recruited neonates. Notably, in 200 neonates, positive per conventional NBS, 58.5% (69/118) showed results consistent with NGS. In the remaining 3049 neonates showing negative results in conventional NBS, 271 (8.9%) were positive per NGS, and nine of them were clinically diagnosed with diseases in the follow-up. CONCLUSION: We successfully designed a NeoEXOME panel for targeted sequencing of monogenic inherited diseases in NBS. The panel demonstrated high performance in the Chinese population, particularly for the early detection of diseases with no biochemical markers.

tRFtarget 2.0: expanding the targetome landscape of transfer RNA-derived fragments.

tRFtarget 1.0 (http://trftarget.net/) is a platform consolidating both computationally predicted and experimentally validated binding sites between transfer RNA-derived fragments (tRFs) and target genes (or transcripts) across multiple organisms. Here, we introduce a newly released version of tRFtarget 2.0, in which we integrated 6 additional tRF sources, resulting in a comprehensive collection of 2614 high-quality tRF sequences spanning across 9 species, including 1944 Homo sapiens tRFs and one newly incorporated species Rattus norvegicus. We also expanded target genes by including ribosomal RNAs, long non-coding RNAs, and coding genes >50 kb in length. The predicted binding sites have surged up to approximately 6 billion, a 20.5-fold increase than that in tRFtarget 1.0. The manually curated publications relevant to tRF targets have increased to 400 and the gene-level experimental evidence has risen to 232. tRFtarget 2.0 introduces several new features, including a web-based tool that identifies potential binding sites of tRFs in user's own datasets, integration of standardized tRF IDs, and inclusion of external links to contents within the database. Additionally, we enhanced website framework and user interface. With these improvements, tRFtarget 2.0 is more user-friendly, providing researchers a streamlined and comprehensive platform to accelerate their research progress.

Synthesis and evaluation of butylphthalide-scutellarein hybrids as multifunctional agents for the treatment of Alzheimer's disease.

A series of butylphthalide and scutellarein hybrids 3-(alkyl/alkenyl) hydroxyphthalide derivatives were designed, synthesized and evaluated as multifunctional agents against Alzheimer's disease. In vitro bioactivity assays indicated that most of the compounds displayed excellent antioxidant activity and moderate to good inhibition activities of self-induced Aß1-42 aggregation. Among them, compound 7c was demonstrated as a potential and balanced multifunctional candidate displaying the best inhibitory effects on self- and Cu2+-induced Aß1-42 aggregation (90.2 % and 35.4 %, respectively) and moderate activity for disaggregation of Aß1-42 aggregation (42.5 %). In addition, 7c also displayed excellent antioxidant (2.42 Trolox equivalents), metal ions chelating, oxidative stress alleviation, neuroprotective and anti-neuroinflammatory activities. Furthermore, in vivo study demonstrated that 7c could ameliorate the learning and memory impairment induced by sodium nitrite and Aß1-42 in the step-down passive avoidance test. These balanced multifunctional profiles supporting compound 7c as a novel potential candidate for the treatment of AD.

Automating General Movements Assessment with quantitative deep learning to facilitate early screening of cerebral palsy.

The Prechtl General Movements Assessment (GMA) is increasingly recognized for its role in evaluating the integrity of the developing nervous system and predicting motor dysfunctions, particularly in conditions such as cerebral palsy (CP). However, the necessity for highly trained professionals has hindered the adoption of GMA as an early screening tool in some countries. In this study, we propose a deep learning-based motor assessment model (MAM) that combines infant videos and basic characteristics, with the aim of automating GMA at the fidgety movements (FMs) stage. MAM demonstrates strong performance, achieving an Area Under the Curve (AUC) of 0.967 during external validation. Importantly, it adheres closely to the principles of GMA and exhibits robust interpretability, as it can accurately identify FMs within videos, showing substantial agreement with expert assessments. Leveraging the predicted FMs frequency, a quantitative GMA method is introduced, which achieves an AUC of 0.956 and enhances the diagnostic accuracy of GMA beginners by 11.0%. The development of MAM holds the potential to significantly streamline early CP screening and revolutionize the field of video-based quantitative medical diagnostics.

More patient-centered care, better healthcare: the association between patient-centered care and healthcare outcomes in inpatients.

Objective: The objective of this study is to explore the association between patient-centered care (PCC) and inpatient healthcare outcomes, including self-reported physical and mental health status, subjective necessity of hospitalization, and physician-induced demand behaviors. Methods: A cross-sectional survey was conducted to assess patient-centered care among inpatients in comprehensive hospitals through QR codes after discharge from September 2021 to December 2021 and had 5,222 respondents in Jiayuguan, Gansu. The questionnaire included a translated 6-item version of the PCC questionnaire, physician-induced behaviors, and patients' sociodemographic characteristics including gender, household registration, age, and income. Logistic regression analyses were conducted to assess whether PCC promoted self-reported health, the subjective necessity of hospitalization, and decreased physician-induced demand. The interactions between PCC and household registration were implemented to assess the effect of the difference between adequate and inadequate healthcare resources. Results: PCC promoted the patient's self-reported physical (OR = 4.154, p < 0.001) and mental health (OR = 5.642, p < 0.001) and subjective necessity of hospitalization (OR = 6.160, p < 0.001). Meanwhile, PCC reduced physician-induced demand in advising to buy medicines outside (OR = 0.415, p < 0.001), paying at the outpatient clinic (OR =0.349, p < 0.001), issuing unnecessary or repeated prescriptions and medical tests (OR = 0.320, p < 0.001), and requiring discharge and readmitting (OR = 0.389, p < 0.001). Conclusion: By improving health outcomes for inpatients and reducing the risk of physician-induced demand, PCC can benefit both patients and health insurance systems. Therefore, PCC should be implemented in healthcare settings.

Effects of a Nonwearable Digital Therapeutic Intervention on Preschoolers With Autism Spectrum Disorder in China: Open-Label Randomized Controlled Trial.

BACKGROUND: Autism spectrum disorder (ASD) is a neurodevelopmental disorder that can cause difficulty with communication and social interactions as well as complicated family dynamics. Digital health interventions can reduce treatment costs and promote healthy lifestyle changes. These therapies can be adjunctive or replace traditional treatments. However, issues with cooperation and compliance prevent preschool patients with ASD from applying these tools. In this open-label, randomized controlled trial, we developed a nonwearable digital therapy called virtual reality-incorporated cognitive behavioral therapy (VR-CBT). OBJECTIVE: The aim of this study was to assess the adjunctive function of VR-CBT by comparing the effects of VR-CBT plus learning style profile (LSP) intervention with those of LSP-only intervention in preschool children with ASD. METHODS: This trial was performed in China on 78 preschool children (age 3-6 years, IQ>70) diagnosed with ASD who were randomized to receive a 20-week VR-CBT plus LSP intervention (intervention group, 39/78, 50%) or LSP intervention only (control group, 39/78, 50%). The primary outcome was the change of scores from baseline to week 20, assessed by using the parent-rated Autism Behavior Checklist (ABC). Secondary outcomes included the Childhood Autism Rating Scale (CARS), Attention-Deficit/Hyperactivity Disorder Rating Scale-IV (ADHD-RS-IV), and behavioral performance data (accuracy and reaction time) in go/no-go tasks. All primary and secondary outcomes were analyzed in the intention-to-treat population. RESULTS: After the intervention, there was an intervention effect on total ABC (ß=-5.528; P<.001) and CARS scores (ß=-1.365; P=.02). A similar trend was observed in the ABC subscales: sensory (ß=-1.133; P=.047), relating (ß=-1.512; P=.03), body and object use (ß=-1.211; P=.03), and social and self-help (ß=-1.593; P=.03). The intervention also showed statistically significant effects in improving behavioral performance (go/no-go task, accuracy, ß=2.923; P=.04). Moreover, a significant improvement of ADHD hyperactivity-impulsivity symptoms was observed in 53 children with comorbid ADHD based on ADHD-RS-IV (ß=-1.269; P=.02). No statistically significant intervention effect was detected in the language subscale of ABC (ß=-.080; P=.83). Intervention group girls had larger improvements in ABC subscales, that is, sensory and body and object use and in the CARS score and accuracy of go/no-go task (all P<.05) than the control group girls. Statistically significant intervention effects could be observed in hyperactivity-impulsivity symptoms in the intervention group boys with comorbid ADHD compared with those in the control group boys (ß=-1.333; P=.03). CONCLUSIONS: We found potentially positive effects of nonwearable digital therapy plus LSP on core symptoms associated with ASD, leading to a modest improvement in the function of sensory, motor, and response inhibition, while reducing impulsivity and hyperactivity in preschoolers with both ASD and ADHD. VR-CBT was found to be an effective and feasible adjunctive digital tool. TRIAL REGISTRATION: Chinese Clinical Trial Registry ChiCTR2100053165; http://www.chictr.org.cn/showproj.aspx?proj=137016.

diseaseGPS: auxiliary diagnostic system for genetic disorders based on genotype and phenotype.

SUMMARY: The next-generation sequencing brought opportunities for the diagnosis of genetic disorders due to its high-throughput capabilities. However, the majority of existing methods were limited to only sequencing candidate variants, and the process of linking these variants to a diagnosis of genetic disorders still required medical professionals to consult databases. Therefore, we introduce diseaseGPS, an integrated platform for the diagnosis of genetic disorders that combines both phenotype and genotype data for analysis. It offers not only a user-friendly GUI web application for those without a programming background but also scripts that can be executed in batch mode for bioinformatics professionals. The genetic and phenotypic data are integrated using the ACMG-Bayes method and a novel phenotypic similarity method, to prioritize the results of genetic disorders. diseaseGPS was evaluated on 6085 cases from Deciphering Developmental Disorders project and 187 cases from Shanghai Children's hospital. The results demonstrated that diseaseGPS performed better than other commonly used methods. AVAILABILITY AND IMPLEMENTATION: diseaseGPS is available to freely accessed at https://diseasegps.sjtu.edu.cn with source code at https://github.com/BioHuangDY/diseaseGPS.

Factors Influencing the Sharing of Personal Health Data Based on the Integrated Theory of Privacy Calculus and Theory of Planned Behaviors Framework: Results of a Cross-Sectional Study of Chinese Patients in the Yangtze River Delta.

BACKGROUND: The health care system in China is fragmented, and the distribution of high-quality resources remains uneven and irrational. Information sharing is essential to the development of an integrated health care system and maximizing its benefits. Nevertheless, data sharing raises concerns regarding the privacy and confidentiality of personal health information, which affect the willingness of patients to share information. OBJECTIVE: This study aims to investigate patients' willingness to share personal health data at different levels of maternal and child specialized hospitals in China, to propose and test a conceptual model to identify key influencing factors, and to provide countermeasures and suggestions to improve the level of data sharing. METHODS: A research framework based on the Theory of Privacy Calculus and the Theory of Planned Behavior was developed and empirically tested through a cross-sectional field survey from September 2022 to October 2022 in the Yangtze River Delta region, China. A 33-item measurement instrument was developed. Descriptive statistics, chi-square tests, and logistic regression analyses were conducted to characterize the willingness of sharing personal health data and differences by sociodemographic factors. Structural equation modeling was used to assess the reliability and validity of the measurement as well as to test the research hypotheses. The STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) checklist for cross-sectional studies was applied for reporting results. RESULTS: The empirical framework had a good fit with the chi-square/degree of freedom (χ2/df)=2.637, root-mean-square residual=0.032, root-mean-square error of approximation=0.048, goodness-of-fit index=0.950, and normed fit index=0.955. A total of 2060 completed questionnaires were received (response rate: 2060/2400, 85.83%). Moral motive (ß=.803, P<.001), perceived benefit (ß=.123, P=.04), and perceived effectiveness of government regulation (ß=.110, P=.001) had a significantly positive association with sharing willingness, while perceived risk (ß=-.143, P<.001) had a significant negative impact, with moral motive having the greatest impact. The estimated model explained 90.5% of the variance in sharing willingness. CONCLUSIONS: This study contributes to the literature on personal health data sharing by integrating the Theory of Privacy Calculus and the Theory of Planned Behavior. Most Chinese patients are willing to share their personal health data, which is primarily motivated by moral concerns to improve public health and assist in the diagnosis and treatment of illnesses. Patients with no prior experience with personal information disclosure and those who have tertiary hospital visits were more likely to share their health data. Practical guidelines are provided to health policy makers and health care practitioners to encourage patients to share their personal health information.

Association of parabens and bisphenols with lung function in children aged 5-12 years from Shanghai, China.

Epidemiological studies have reported potential effects of individual paraben or bisphenol exposure on lung function, but few studies have estimated their joint effects. We conducted a cross sectional survey to investigate the associations of parabens and bisphenols exposure with lung function in 205 children aged 5-12 years from Shanghai, China. Urinary concentrations of six parabens [methyl-, ethyl-, propyl-, butyl-, benzyl-, and heptyl-paraben (MeP, EtP, PrP, BuP, BzP, and HeP)] and seven bisphenols [bisphenol A (BPA), bisphenol AF (BPAF), bisphenol AP (BPAP), bisphenol B (BPB), bisphenol P (BPP), bisphenol S (BPS), and bisphenol Z (BPZ)] were assessed by the high-performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS). Lung function, including forced expiratory volume in 1 s (FEV1), forced vital capacity (FVC), FEV1/FVC, peak expiratory flow (PEF), and forced expiratory flow between 25% and 75% of forced vital capacity (FEF25-75%), was further measured. Linear regression, bayesian kernel machine regression (BKMR), and weighted quantile sum regression (WQS) evaluated the individual and joint relationships of the parabens and bisphenols with the lung function parameters. Further, the analysis was stratified by child sex. Parabens (MeP, EtP, PrP, and BuP) and bisphenols (BPA, BPAP, BPB, and BPS) with detection rates >75% were included for analyses. In linear regressions, parabens (MeP, PrP, and BuP) were generally negatively associated with FEV1, FVC, PEF, and FEF25-75%, but no associations for bisphenols were found. The association of parabens with lung function was more pronounced in girls. The aforementioned negative associations between parabens and lung function were confirmed by both the BKMR and WQS, with MeP being considered most heavily weighing chemical. Our findings suggested that exposure to parabens, either individuals or as a mixture, were associated with decreased lung function in children aged 5-12 years, and these associations were stronger among girls. Considering the cross-sectional study design, large longitudinal studies are warranted to confirm our findings.

Altered gut microbiota and microbial metabolism in children with hepatic glycogen storage disease: a case-control study.

Background: Accumulating evidence has demonstrated that gut microbiota dysbiosis correlated with altered metabolism are implicated in liver metabolic diseases. However, data on pediatric hepatic glycogen storage disease (GSD) are limited. Here, we aimed to investigate the features of the gut microbiota and metabolites in hepatic GSD children from China. Methods: Totals of 22 hepatic GSD patients and 16 age- and gender-matched healthy children were enrolled from the Shanghai Children's Hospital, China. Pediatric GSD patients were confirmed as having hepatic GSD via genetic diagnosis and/or liver biopsy pathology. The control group comprised children without any history of chronic diseases or clinically relevant GSD or symptoms of any other metabolic diseases. The baseline characteristics of the two groups were gender- and age-matched matched using chi-squared test and the Mann-Whitney U test, respectively. The gut microbiota, bile acids (BAs), and short chain fatty acids (SCFAs) were determined from the feces using 16S ribosomal RNA (rRNA) gene sequencing, ultra-high performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS), and gas chromatography-mass spectrometry (GC-MS), respectively. Results: The alpha diversity of fecal microbiome was significantly lower in hepatic GSD patients [observed species richness (Sobs): P=0.011; abundance-based coverage estimator (ACE): P=0.011; Chao: P=0.011; Shannon: P<0.001], and their microbial community was more distanced from that of the control [principal coordinate analysis (PCoA) on genus level, unweighted UniFrac: P=0.011]. Relative abundances of phyla Firmicutes (P=0.030) and Bacteroidetes (P=0.029), families Lachnospiraceae (P=0.012), Ruminococcaceae (P=0.008), and Peptostreptococcaceare (P=0.031), genera Blautia (P=0.017), Eubacterium_hallii_group (P=0.032), and Faecalibacterium (P=0.017) were decreased, whereas phyla Actinobacteria (P=0.033), Proteobacteria (P=0.049), families Bifidobacteriaceae (P=0.030), Lactobacillaceae (P=0.034), and Veillonellaceae (P=0.033), genera Lactobacillus (P=0.011), Enterobater (P=0.034), and Veillonella (P=0.014) were increased in hepatic GSD. Altered microbial metabolisms were characterized by increased abundances of primary BAs (P=0.009) and decreased concentrations of SCFAs in hepatic GSD children. Furthermore, the altered bacterial genera were correlated with the changes of both fecal BAs and SCFAs. Conclusions: The hepatic GSD patients in this study presented with gut microbiota dysbiosis which correlated with altered BAs metabolism and fecal SCFAs changes. Further studies are needed to investigate the driver of these changes mediated by either the genetic defect, disease status, or diet therapy.

Higher greenspace exposure is associated with a decreased risk of childhood asthma in Shanghai - A megacity in China.

Inconsistent evidence exists about whether exposure to greenspace benefits childhood asthma. Previous studies have only focused on residential or school greenspace, and no research has combined greenspace exposures at both homes and schools to determine their link with childhood asthma. A population-based cross-sectional study was conducted among 16,605 children during 2019 in Shanghai, China. Self-reported questionnaires were used to collect information on childhood asthma and demographic, socioeconomic and behavioural factors. Environmental data including ambient temperature, particulate matter with aerodynamic diameter less than 1 µm (PM1), enhanced vegetation index (EVI), and normalized difference vegetation index (NDVI) were collected from satellite data. Binomial generalized linear models with a logit link were carried out to evaluate the association between greenspace exposure and children's asthma, as well as the effect modifiers. An interquartile range increment of whole greenspace (NDVI500, NDVI250, EVI500, and EVI250) exposure was associated with a reduced odds ratio of children's asthma (0.88, 95% CI: 0.78, 0.99; 0.89, 95% CI: 0.79, 1.01; 0.87, 95% CI: 0.77, 0.99; and 0.88, 95% CI: 0.78, 0.99, respectively) after controlling potential confounders. Low temperature, low PM1, males, vaginal delivery, suburban/rural area, and without family history of allergy appeared to enhance the greenspace-asthma association. Increased greenspace exposure was associated with a lower risk of childhood asthma, and the association was modified by a range of socio-environmental factors. These findings add to the body of evidence on the benefits of biodiversity and supporting the promotion of urban greenspace to protect children's health.

Discovery of novel 5-(2-hydroxyphenyl)-2-phthalide-3(3H)-pyrazolones as balanced multifunctional agents against Alzheimer's disease.

Based on previous work, a series of novel 5-(2-hydroxyphenyl)-2-phthalide-3(3H)-pyrazolones derivatives were identified as potential multifunctional therapeutic agents for Alzheimer's disease. Biological evaluation exhibited that these derivatives had great performance against MAO-B, Aß1-42 aggregation, oxidative stress and metal ion dyshomeostasis. Among them, 10x was selected as the optimal agent for its excellent MAO-B inhibitory activity (IC50 = 0.41 µM, SI > 24.4), good antioxidant activity (1.16 Trolox equivalent) and anti-Aß aggregation activity (56.03% and 57.51% for inhibition of self- and Cu2+-induced Aß1-42 aggregation; 81.91% and 82.40% for disaggregation of self- and Cu2+-induced Aß1-42 fibrils at 25.0 µM). Besides, 10x also exhibited obvious metal-ion chelating ability, anti-neuroinflammation (NO, TNF-α), neuroprotective activity and BBB permeability. More importantly, in vivo behavioral assessment demonstrated 10x could remarkably improve the memory and cognitive impairment in Aß1-42 induced AD mice model. Overall, these test results indicated 10x could serve as a balanced multifunctional anti-AD agent and deserved further research.

Altered gut microbiota composition in children and their caregivers infected with the SARS-CoV-2 Omicron variant.

BACKGROUND: Gut microbiota alterations have been implicated in the pathogenesis of coronavirus disease 2019 (COVID-19). This study aimed to explore gut microbiota changes in a prospective cohort of COVID-19 children and their asymptomatic caregivers infected with the severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) Omicron variant. METHODS: A total of 186 participants, including 59 COVID-19 children, 50 asymptomatic adult caregivers, 52 healthy children (HC), and 25 healthy adults (HA), were recruited between 15 April and 31 May 2022. The gut microbiota composition was determined by 16S rRNA gene sequencing in fecal samples collected from the participants. Gut microbiota functional profiling was performed by using Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt) software. RESULTS: The gut microbiota analysis of beta diversity revealed that the fecal microbial community of COVID-19 children remained far distantly related to HC. The relative abundances of the phyla Actinobacteria and Firmicutes were decreased, whereas Bacteroidetes, Proteobacteria, and Verrucomicrobiota were increased in COVID-19 children. Feces from COVID-19 children exhibited notably lower abundances of the genera Blautia, Bifidobacterium, Fusicatenibacter, Streptococcus, and Romboutsia and higher abundances of the genera Prevotella, Lachnoclostridium, Escherichia-Shigella, and Bacteroides than those from HC. The enterotype distributions of COVID-19 children were characterized by a high prevalence of enterotype Bacteroides. Similar changes in gut microbiota compositions were observed in asymptomatic caregivers. Furthermore, the microbial metabolic activities of KEGG (Kyoto Encyclopedia of Genes and Genomes) and COG (cluster of orthologous groups of proteins) pathways were perturbed in feces from subjects infected with the SARS-CoV-2 Omicron variant. CONCLUSION: Our data reveal altered gut microbiota compositions in both COVID-19 children and their asymptomatic caregivers infected with the SARS-CoV-2 Omicron variant, which further implicates the critical role of gut microbiota in COVID-19 pathogenesis.

Residential greenspace and childhood asthma: An intra-city study.

Interest in assessing the effects of exposure to greenspace on human health has been increasing due to rapid urbanization, and rising trends of physical inactivity and air pollution. However, findings on the link between greenspace and child respiratory health, especially asthma, are inconsistent. We investigated the association between greenspace surrounding residential addresses and asthma in children. A city-wide cross-sectional study was conducted, involving 16,605 children aged 3-12 years, in Shanghai, China. Data on asthma symptoms and covariates were collected from validated self-reported questionnaires. Residential greenspace was measured using satellite-derived normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI). Information on ambient temperature and particulate matter with dynamic diameter <1 µm (PM1) and 2.5 µm (PM2.5) was also collected from satellite data. Logistic regression models were performed to assess the associations of greenspace exposure with childhood asthma as well as the effect modification by covariates. The prevalence of current asthma in children was 4.8 % in this study. An interquartile range increase in mean NDVI from 2016 to 2018 was associated with decreased odds of asthma in 2019 at 500 m, and 250 m resolutions (0.82, 95 % confidence interval (CI): 0.74 to 0.93; and 0.82, 95 % CI: 0.72 to 0.94, respectively) after adjustment for covariates. The greenspace-asthma association was modified by ambient temperature and residential area. Sensitivity analyses using various models and EVI exposure showed the robustness of the results. In conclusion, higher individual-level exposure to greenspace was associated with decreased odds of asthma in children, and the association appeared to be modified by different environmental and socio-demographic factors. These findings provide additional evidence for promoting urban greenness to protect children's health and well-being.

Brain Age Prediction in Developing Childhood with Multimodal Magnetic Resonance Images.

It is well known that brain development is very fast and complex in the early childhood with age-based neurological and physiological changes of brain structure and function. The brain maturity is an important indicator for evaluating the normal development of children. In this paper, we propose a multimodal regression framework to combine the features from structural magnetic resonance imaging (sMRI) and diffusion tensor imaging (DTI) data for age prediction of children. First, three types of features are extracted from sMRI and DTI data. Second, we propose to combine the sparse coding and Q-Learning for feature selection from each modality. Finally, the ensemble regression is performed by random forest based on proximity measures to fuse multimodal features for age prediction. The proposed method is evaluated on 212 participants, including 76 young children less than 2 years old and 136 children aged from 2-15 years old recruited from Shanghai Children's Hospital. The results show that integrating multimodal features has achieved the highest accuracies with the root mean squared error (RMSE) of 0.208 years and mean absolute error (MAE) of 0.150 years for age prediction of young children (0-2), and RMSE of 1.666 years and MAE of 1.087 years for older children (2-15). We have shown that the selected features by Q-Learning can consistently improve the prediction accuracy. The comparison of prediction results demonstrates that the proposed method performs better than other competing methods.

Rapid Point-of-Care Assay by SERS Detection of SARS-CoV-2 Virus and Its Variants.

Addressing the spread of coronavirus disease 2019 (COVID-19) has highlighted the need for rapid, accurate, and low-cost diagnostic methods that detect specific antigens for SARS-CoV-2 infection. Tests for COVID-19 are based on reverse transcription PCR (RT-PCR), which requires laboratory services and is time-consuming. Here, by targeting the SARS-CoV-2 spike protein, we present a point-of-care SERS detection platform that specifically detects SARS-CoV-2 antigen in one step by captureing substrates and detection probes based on aptamer-specific recognition. Using the pseudovirus, without any pretreatment, the SARS-CoV-2 virus and its variants were detected by a handheld Raman spectrometer within 5 min. The limit of detection (LoD) for the pseudovirus was 124 TU µL-1 (18 fM spike protein), with a linear range of 250-10,000 TU µL-1. Moreover, this assay can specifically recognize the SARS-CoV-2 antigen without cross reacting with specific antigens of other coronaviruses or influenza A. Therefore, the platform has great potential for application in rapid point-of-care diagnostic assays for SARS-CoV-2.