3D Genome of macaque fetal brain reveals evolutionary innovations during primate corticogenesis.

Elucidating the regulatory mechanisms of human brain evolution is essential to understanding human cognition and mental disorders. We generated multi-omics profiles and constructed a high-resolution map of 3D genome architecture of rhesus macaque during corticogenesis. By comparing the 3D genomes of human, macaque, and mouse brains, we identified many human-specific chromatin structure changes, including 499 topologically associating domains (TADs) and 1,266 chromatin loops. The human-specific loops are significantly enriched in enhancer-enhancer interactions, and the regulated genes show human-specific expression changes in the subplate, a transient zone of the developing brain critical for neural circuit formation and plasticity. Notably, many human-specific sequence changes are located in the human-specific TAD boundaries and loop anchors, which may generate new transcription factor binding sites and chromatin structures in human. Collectively, the presented data highlight the value of comparative 3D genome analyses in dissecting the regulatory mechanisms of brain development and evolution.

Code Similarity Prediction Model for Industrial Management Features Based on Graph Neural Networks.

The code of industrial management software typically features few system API calls and a high number of customized variables and structures. This makes the similarity of such codes difficult to compute using text features or traditional neural network methods. In this paper, we propose an FSPS-GNN model, which is based on graph neural networks (GNNs), to address this problem. The model categorizes code features into two types, outer graph and inner graph, and conducts training and prediction with four stages-feature embedding, feature enhancement, feature fusion, and similarity prediction. Moreover, differently structured GNNs were used in the embedding and enhancement stages, respectively, to increase the interaction of code features. Experiments with code from three open-source projects demonstrate that the model achieves an average precision of 87.57% and an F0.5 Score of 89.12%. Compared to existing similarity-computation models based on GNNs, this model exhibits a Mean Squared Error (MSE) that is approximately 0.0041 to 0.0266 lower and an F0.5 Score that is 3.3259% to 6.4392% higher. It broadens the application scope of GNNs and offers additional insights for the study of code-similarity issues.

Metabolomics integrated network pharmacology reveals the mechanism of Ma-Mu-Ran Antidiarrheal Capsules on acute enteritis mice.

Acute enteritis (AE) is a type of digestive disease caused by biochemical factors that irritate the intestinal tract or pathogenic bacteria that infect it. In China, Ma-Mu-Ran Antidiarrheal Capsules (MMRAC) have been applied against diarrhea caused by AE and bacillary dysentery for many years, but the underlying mechanisms of their beneficial effects are not known. In the present study, network pharmacology and metabolomics were performed to clarify the active ingredients of MMRAC and explore the specific mechanism of MMRAC on AE mice. A total of 43 active components of MMRAC with 87 anti-AE target genes were identified, and these target genes were enriched in IL-17 and HIF-1 signaling pathways. Integration analysis revealed that purine metabolism was the critical metabolic pathway by which MMRAC exerted its therapeutic effect against AE. Specifically, MAPK14, MMP9, PTGS2, HIF1A, EGLN1, NOS2 were the pivotal targets of MMRAC for the treatment of AE, and Western blot analysis revealed MMRAC to decrease protein levels of these pro-inflammatory signaling molecules. According to molecular docking, these key targets have a strong affinity with the MMRAC compounds. Collectively, MMRAC relieved the colon inflammation of AE mice via regulating inflammatory signaling pathways to reduce hypoxia and improved energy metabolism.

Integrated network pharmacology and metabolomics analyses of the mechanism underlying the efficacy of Ma-Mu-Ran Antidiarrheal Capsules against dextran sulfate sodium-induced ulcerative colitis.

The current study utilizes a comprehensive network pharmacology and metabolomics analysis to investigate the mechanism of action of Ma-Mu-Ran Antidiarrheal Capsules (MMRAC) for the treatment of ulcerative colitis (UC). In this study, we established a mouse model of UC using dextran sulfate sodium. Colonic tissues were collected from mice and then subjected to hematoxylin and eosin staining, as well as histopathological analysis, to assess the therapeutic effect of MMRAC. Furthermore, we assessed the mechanisms through which MMRAC combats UC by employing integrated metabolomics and network pharmacology strategies. Lastly, we validated the key targets identified through western blot and molecular docking. An integrated network of metabolomics and network pharmacology was constructed using Cytoscape to identify eight endogenous metabolites involved in the therapeutic action of MMRAC on UC. Further comprehensive analyses were focused on four key targets and their associated core metabolites and pathways. The results of western blot and molecular docking demonstrated that MMRAC could modulate key targets and their expression levels. The cumulative results indicated that MMRAC restored intestinal function in UC, reduced inflammatory responses, and alleviated oxidative stress by influencing the methionine and cysteine metabolic pathways, as well as the urea cycle. In addition, it had an impact on arginine, proline, glutamate, aspartate, and asparagine metabolic pathways and their associated targets.

Pattern of lifestyle behaviors and associated risk of being bullied at schools: A latent class analysis of 25,379 adolescents in Jiangsu Province of China.

School bullying is a worldwide problem. Although previous studies examined the association between different lifestyle behaviors and bullying victimization, the complex co-occurrence of these behaviors was not identified, and their association with the risk of being bullied remains unclear. We aimed to identify the behavioral patterns of adolescents and to explore their association with bullying victimization. This cross-sectional study employed data from the "Surveillance for Common Diseases and Health Risk Factors among Students" project implemented in Jiangsu Province of China in 2019, and a total of 25,379 school-enrolled students were included. We used a latent class analysis to identify behavioral patterns and a regression mixture model to explore various demographic characteristics, such as age, sex, and family structure in relation to bullying victimization across different patterns. We considered respondents having targeted behaviors, including smoking, alcohol consumption, illicit drug use, sugar consumption, no fruit consumption, low physical activity, electronic media use, and insufficient sleep. Four behavioral patterns were identified, including the "adolescents without apparent targeted behaviors" (19.65%), "substance and electronic media users" (12.76%), "typical electronic media users" (54.49%), and "typical substance users" (8.10%). The risk of being bullied was the highest in the "substance and electronic media users" (probability: 0.33), tripled that in "adolescents without apparent targeted behaviors" (odds ratio: 3.60, 95% confidence interval: 3.01-4.30). Risk of being bullied was reduced for those "substance and electronic media users" living with a nuclear family. Behavioral patterns and their association with being bullied differ between groups of school-aged adolescents. To better inform decision-making based on the current real-world findings, the implementation of bullying prevention programs could target specific behavioral patterns.

Protective Effects of Three Flavonoids from Dendrobium huoshanense Flowers on Alcohol-Induced Hepatocyte Injury via Activating Nrf2 and Inhibiting NF-κB Pathways.

Dendrobium huoshanense flowers have been widely used for liver protection in China. This work was aimed to discover the natural products with activity of mitigating alcoholic hepatocyte injury from Dendrobium huoshanense flowers via bioactivity-guided isolation, and to clarify the underlying mechanisms of these natural products. As a result, three flavonoids, 3'-O-methylquercetin-3-O-ß-D-galactopyranoside (1), 3'-O-methylquercetin-3-O-ß-D-glucopyranoside (2) and quercetin-3-O-ß-D-glucopyranoside (3), were firstly isolated from D. huoshanense flowers. Results exhibited that flavonoids 1-3 could enhance the cell viability, decrease the expression of ALT and AST, inhibit the cell apoptosis, alleviate the oxidative stress, and mitigate the inflammatory response of alcohol-induced L02 cells. Mechanism study exhibited that flavonoids 1-3 could increase the expression of Nrf2 as well as its downstream antioxidation genes of alcohol-induced L02 cells, while ML-385 (Nrf2 inhibitor) could abolish the inhibitory effects of 1-3 on alcohol-induced hepatocyte injury. Flavonoids 1-3 could also reduce the phosphorylation levels of IκBα and NF-κB p65 of alcohol-induced L02 cells, while SC75741 (NF-κB inhibitor) could not enhance the inhibitory effects of 1-3 on alcohol-induced L02 cells injury. The data above indicated that flavonoids 1-3 could inhibit alcohol-induced hepatocyte injury, which might be attributed to alleviating oxidative stress and mitigating inflammatory response by activating Nrf2 and inhibiting NF-κB pathways.

Design and Implementation of Real-Time Localization System (RTLS) Based on UWB and TDoA Algorithm.

Nowadays, accurate localization plays an essential role in many fields, such as target tracking and path planning. The challenges of indoor localization include inadequate localization accuracy, unreasonable anchor deployment in complex scenarios, lack of stability, and the high cost. So, the universal positioning technologies cannot meet the real application requirements scarcely. To overcome these shortcomings, a comprehensive ultra wide-band (UWB)-based real-time localization system (RTLS) is presented in this paper. We introduce the architecture of a real-time localization system, then propose a new wireless clock synchronization (WCS) scheme, and finally discuss the time difference of arrival (TDoA) algorithm. We define the time-base selection strategy for the TDoA algorithm, and we analyze the relationship between anchor deployment and positioning accuracy. The extended Kalman filter (EKF) method is presented for non-linear dynamic localization estimation, and it performs well in terms of stability and accuracy on moving targets.

Ridge cropping and furrow irrigation pattern improved spring maize (Zea mays L.) yield and water productivity in Hetao irrigation area of north-western China.

BACKGROUND: Improving irrigation water productivity is vital for sustaining high maize yield in Hetao irrigated area of northwest China. Whether ridge cropping and furrow irrigation systems (planting both on ridges and in furrows) fulfill water-saving and maize yield-increasing is unclear. A 2-year trial was conducted to reveal the influence of irrigation with three levels (270, 225, 180 mm, represented as I270 , I225 , I180 , respectively) under two planting systems [traditional flat planting system (TFI) and ridge cropping and furrow irrigation system (RFI)] on maize growth, grain yield, water use efficiency (WUE) and irrigation water use efficiency (IUE). RESULTS: RFI system increased soil water storage in 0-100 cm layer (P < 0.05), but did not cause excess water consumption, compared to TFI system. Logistic equation simulation showed that RFI system advanced the time of maximum dry matter growth rate (Tmax , 2.6-4.9 days) and prolonged the duration of dry matter accumulation (Td , 3.2-4.7 days), ultimately obtained a 4.2-9.5% improvement of dry matter. Compared with TFI system, RFI system increased WUE by 8.0-21.2%, IUE by 8.3-20.5% and grain yield increased by 9.4-21.4%. RFI225 satisfied water-saving by 16.6% and yield-increasing by 3.6-14.7%. CONCLUSION: Ridge cropping and furrow irrigation systems brought an improvement of soil water storage and dry matter accumulation and kernel per spike, and ultimately obtained an increase of grain yield and water productivity. © 2022 Society of Chemical Industry.

Long-term exposure to ambient air pollution and obesity in school-aged children and adolescents in Jiangsu province of China.

Studies have shown that ambient air pollution is associated with obesity in adults, but epidemiological evidence is scarce for children and adolescents. This study sought to examine the association between long-term exposure to ambient air pollution and obesity in a large population of children and adolescents in China. A cross-sectional analysis was performed from a school-based health lifestyles intervention project between September 1, 2019 and November 31, 2019, including 36,456 participants aged 9-17 years in Jiangsu province of China. Exposure to air pollutants (nitrogen dioxide (NO2), ozone (O3), particulate matter with aerodynamic diameters ≤10 µm (PM10), and ≤2.5 µm (PM2.5)) were measured based on the nearest air monitoring station for each selected school. Data on each participant's weight and height was also recorded. Demographic and obesity-related behavioral information was collected using a self-reported questionnaire. We used the multivariate regression model to estimate the effects of three-year (2016-2018) average concentrations and the exceedance concentration days (ECD) of air pollutants on obesity after adjusting potential confounders. The ECD was defined as daily concentration exceeding the Chinese National Ambient Air Quality Standard and World Health Organization Ambient Air Quality Guidelines. We observed that higher concentrations of PM2.5, NO2, and O3 were associated with elevated likelihood of obesity. For each 10 µg/m3 increment in concentration, odds ratio of obesity was 1.185 (95% confidence interval (CI): 1.054, 1.333) for PM2.5, 1.127 (95%CI: 1.042, 1.219) for NO2, and 1.041 (95%CI: 1.001, 1.082) for O3, respectively. A significant association between the ECD and obesity was also found for PM2.5 and O3. Effects of air pollutants on obesity were stronger in males, low economic level regions, and age subgroups of 9-11 and 15-17 years. Our findings suggest that long-term exposures to PM2.5, NO2, and O3 were associated with higher prevalence of obesity in children and adolescents. Continuous efforts to reduce air pollution level could help ease the increasing prevalence of obesity within a region.

Effect of Kerogen Maturity, Water Content for Carbon Dioxide, Methane, and Their Mixture Adsorption and Diffusion in Kerogen: A Computational Investigation.

The adsorption behavior of CO2, CH4, and CO2/CH4 mixtures in four different mature kerogens in the absence/presence of water was studied using grand canonical Monte Carlo and classical molecular dynamics methods. The results exhibit that the adsorption isotherms of single-component CO2 or CH4 in kerogen present similar trends and show type I Langmuir adsorption behavior according to the IUPAC classification; the total adsorbed amount of both gases follows the order of type II-A < type II-B < type II-C < type II-D kerogen under the same conditions. The changing behavior of isosteric heat decreases first and then increases, which can explain the heterogeneous characteristic of the kerogen pore surface. The Coulombic and van der Waals interactions between CO2 and kerogens play an important role on adsorption, while for CH4 adsorption, the electrostatic effect is very small, even negligible. The N-, S-, and O-containing groups in kerogen have more remarkable influence on adsorption of CO2 than CH4 because of their strong adsorption energy, therefore notably improving the selectivity of CO2 over CH4 and following the order of type II-A > type II-B > type II-C > type II-D, which is beneficial to carbon capture and storage. Both pressure and temperature have an obvious impact on gas molecule diffusion, and low pressure and high temperature correspond to a large diffusion coefficient. In addition, preabsorbed water has a negative effect on the adsorption of CO2/CH4, and for the same amount of water molecules, the effect follows the order of type II-A > type II-B > type II-C > type II-D kerogens. The binding energy of water-kerogen is stronger than that of pure CH4 or CO2-kerogen. The selectivity of CO2 over CH4 on kerogen increases with an increasing water content.

The distribution of refraction by age and gender in a non-myopic Chinese children population aged 6-12 years.

BACKGROUND: The Prevalence of myopia is increasing in China. This study aimed to explore the distribution of spherical equivalent (SE) and its association with age, body mass index (BMI), gender in a non-myopic Chinese children population aged 6 to 12 years. METHODS: A total of 6362 students were recruited for ophthalmological investigation. Demographic and myopia related behavioral information was collected. SE value was measured by the Topcon RM-8900 or KR-800autorefractors. Potential independent risk factors were determined with Odds Ratio (OR) and 95% Confidence Interval (CI) by logistic regression analysis. We further constructed the nomogram model to predict future onset of myopia. RESULTS: Among the study population, 3900 (61.3%) were non-myopic. The prevalence of myopia is 38.0% for boys and 39.5% for girls. The average SE values were 0.50 ± 0.70 D for boys and 0.60 ± 0.80 D for girls. The mean SE values decreased with age, and the value of height and BMI took on a stable trend. Threshold values for myopia varied across age groups and gender. Paternal myopia (OR: 1.22, 95%CI: 1.01-1.48), near-work activities on weekends (2.56, 1.17-5.61), and outdoor activities (0.68, 0.54-0.86) were associated with potential myopic in students. CONCLUSION: A series of age-gender based SE threshold values were established to predict myopia in Chinese children aged 6 to 12 years. High risk factors for myopia included paternal myopia, near-work activities on weekends, and outdoor activities. Countermeasures are encouraged to reverse the increasing trend of myopia in children.

Epithelial to mesenchymal transition is involved in ethanol promoted hepatocellular carcinoma cells metastasis and stemness.

Hepatocellular Carcinoma (HCC) is a malignant tumor with high rate of relapse and metastasis. Ethanol is a well-known risk factor for HCC; it promotes the progression and aggressiveness of HCC. However, the underlying mechanism remains unclear. In clinic studies, we showed that alcohol consumption is positively correlated with TNM stage and vessel invasion; HCC patients with chronic drinking history had faster progression rate and poorer prognosis compared to non-drinkers. In experimental models, ethanol exposure enhanced the metastasis, and invasion of HCC cells. Ethanol exposure increased cancer stem cells (CSC) population and enhanced stemness of HCC cells in vitro and in vivo. Mechanically, we found that ethanol exposure induced epithelial to mesenchymal transition (EMT) through activating Wnt/ß-catenin signaling pathway in HCC cells. We further demonstrated that ß-catenin siRNA or salinomycin (an inhibitor of Wnt/ß-catenin pathway) partially rescued ethanol-induced EMT. In conclusion, this study suggested that ethanol exposure promotes the metastasis and stemness of HCC cells by inducing EMT.

Pedigree-based analysis of derivation of genome segments of an elite rice reveals key regions during its breeding.

Analyses of genome variations with high-throughput assays have improved our understanding of genetic basis of crop domestication and identified the selected genome regions, but little is known about that of modern breeding, which has limited the usefulness of massive elite cultivars in further breeding. Here we deploy pedigree-based analysis of an elite rice, Huanghuazhan, to exploit key genome regions during its breeding. The cultivars in the pedigree were resequenced with 7.6× depth on average, and 2.1 million high-quality single nucleotide polymorphisms (SNPs) were obtained. Tracing the derivation of genome blocks with pedigree and information on SNPs revealed the chromosomal recombination during breeding, which showed that 26.22% of Huanghuazhan genome are strictly conserved key regions. These major effect regions were further supported by a QTL mapping of 260 recombinant inbred lines derived from the cross of Huanghuazhan and a very dissimilar cultivar, Shuanggui 36, and by the genome profile of eight cultivars and 36 elite lines derived from Huanghuazhan. Hitting these regions with the cloned genes revealed they include numbers of key genes, which were then applied to demonstrate how Huanghuazhan were bred after 30 years of effort and to dissect the deficiency of artificial selection. We concluded the regions are helpful to the further breeding based on this pedigree and performing breeding by design. Our study provides genetic dissection of modern rice breeding and sheds new light on how to perform genomewide breeding by design.

Interaction of nNOS with PSD-95 negatively controls regenerative repair after stroke.

Stroke is a major public health concern. The lack of effective therapies heightens the need for new therapeutic targets. Mammalian brain has the ability to rewire itself to restore lost functionalities. Promoting regenerative repair, including neurogenesis and dendritic remodeling, may offer a new therapeutic strategy for the treatment of stroke. Here, we report that interaction of neuronal nitric oxide synthase (nNOS) with the protein postsynaptic density-95 (PSD-95) negatively controls regenerative repair after stroke in rats. Dissociating nNOS-PSD-95 coupling in neurons promotes neuronal differentiation of neural stem cells (NSCs), facilitates the migration of newborn cells into the injured area, and enhances neurite growth of newborn neurons and dendritic spine formation of mature neurons in the ischemic brain of rats. More importantly, blocking nNOS-PSD-95 binding during the recovery stage improves stroke outcome via the promotion of regenerative repair in rats. Histone deacetylase 2 in NSCs may mediate the role of nNOS-PSD-95 association. Thus, nNOS-PSD-95 can serve as a target for regenerative repair after stroke.

Theoretical Investigation of the Methanol Decomposition by Fe+)and Fe(C2H4)+: A π-Type Ligand Effect.

Density functional theory has been used to probe the mechanism of gas-phase methanol decomposition by bare Fe(+) and ligated Fe(C(2)H(4))(+) in both quartet and sextet states. For the Fe(+)/methanol system, Fe(+) could directly attach to the O and methyl-H atoms of methanol, respectively, forming two encounter isomers. The methanol reaction with Fe(+) prefers initial C-O bond activation to yield methyl with slight endothermicity, whereas CH(4) elimination is hindered by the strong endothermicity and high-energy barrier of hydroxyl-H shift. For the Fe(C(2)H(4))(+)/methanol system, the major product of H(2)O is formed through six elementary steps: encounter complexation, C-O bond activation, C-C coupling, ß-H shift, hydride H shift, and nonreactive dissociation. Both ligand exchange and initial C-O bond activation mechanisms could account for ethylene elimination with the ion products Fe(CH(3)OH)(+) and (CH(3))Fe(OH)(+), respectively. With the assistance of a π-type C(2)H(4) ligand, the metal center in the Fe(C(2)H(4))(+)/CH(3)OH system avoids formation of unfavorable multi-σ-type bonding and thus greatly enhances the reactivity compared to that of bare Fe(+).

An effective framework for predicting drug-drug interactions based on molecular substructures and knowledge graph neural network.

Drug-drug interactions (DDIs) play a central role in drug research, as the simultaneous administration of multiple drugs can have harmful or beneficial effects. Harmful interactions lead to adverse reactions, some of which can be life-threatening, while beneficial interactions can promote efficacy. Therefore, it is crucial for physicians, patients, and the research community to identify potential DDIs. Although many AI-based techniques have been proposed for predicting DDIs, most existing computational models primarily focus on integrating multiple data sources or combining popular embedding methods. Researchers often overlook the valuable information within the molecular structure of drugs or only consider the structural information of drugs, neglecting the relationship or topological information between drugs and other biological objects. In this study, we propose MSKG-DDI - a two-component framework that incorporates the Drug Chemical Structure Graph-based component and the Drug Knowledge Graph-based component to capture multimodal characteristics of drugs. Subsequently, a multimodal fusion neural layer is utilized to explore the complementarity between multimodal representations of drugs. Extensive experiments were conducted using two real-world datasets, and the results demonstrate that MSKG-DDI outperforms other state-of-the-art models in binary-class, multi-class, and multi-label prediction tasks under both transductive and inductive settings. Furthermore, the ablation analysis further confirms the practical usefulness of MSKG-DDI.

Rapid Discovery of Aß42 Fibril Disintegrators from Ganoderma lucidum via Ligand Fishing and Their Neuroprotective Effects on Alzheimer's Disease.

An amyloid-ß (Aß) fibril is a vital pathogenic factor of Alzheimer's disease (AD). Aß fibril disintegrators possess great potential to be developed into novel anti-AD agents. Here, a ligand fishing method was employed to rapidly discover Aß42 fibril disintegrators from Ganoderma lucidum using Aß42 fibril-immobilized magnetic beads, which led to the isolation of six Aß42 fibril disintegrators including ganodermanontriol, ganoderic acid DM, ganoderiol F, ganoderol B, ganodermenonol, and ergosterol. Neuroprotective evaluation in vitro exhibited that these Aß42 fibril disintegrators could significantly mitigate Aß42-induced neurotoxicity. Among these six disintegrators, ergosterol and ganoderic acid DM with stronger protecting activity were further selected to evaluate their neuroprotective effect on AD in vivo. Results showed that ergosterol and ganoderic acid DM could significantly alleviate Aß42-induced cognitive dysfunction and hippocampus neuron loss in vivo. Moreover, ergosterol and ganoderic acid DM could significantly inhibit Aß42-induced neuron apoptosis and Nrf2-mediated neuron oxidative stress in vitro and in vivo.

Ganoderic acid A mitigates dopaminergic neuron ferroptosis via inhibiting NCOA4-mediated ferritinophagy in Parkinson's disease mice.

ETHNOPHARMACOLOGICAL RELEVANCE: Ganoderma lucidum, a renowned tonic traditional Chinese medicine, is widely recognized for the exceptional activity in soothing nerves and nourishing the brain. It has been extensively employed to alleviate various neurological disorders, notably Parkinson's disease (PD). AIM OF THE STUDY: To appraise the antiparkinsonian effect of GAA, the main bioactive constituent of G. lucidum, and clarify the molecular mechanism through the perspective of ferritinophagy-mediated dopaminergic neuron ferroptosis. MATERIALS AND METHODS: PD mouse and cell models were established using 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) and 1-methyl-4-phenylpyridinium (MPP+), respectively. Cell viability, behavioral tests and immunofluorescence analysis were performed to evaluate the neurotoxicity, motor dysfunction and dopaminergic loss, respectively. Biochemical assay kits were used to determine the levels of iron, lipid reactive oxygen species (ROS), malondialdehyde (MDA), total ROS and glutathione (GSH). Western blot and immunofluorescence were applied to detect the expressions of nuclear receptor co-activator 4 (NCOA4), ferritin heavy chain 1 (FTH1), p62 and LC3B. Additionally, NCOA4-overexpressing plasmid vector was constructed to verify the inhibitory effect of GAA on the neurotoxicity and ferroptosis-related parameters in PD models. RESULTS: GAA significantly mitigated MPP+/MPTP-induced neurotoxicity, motor dysfunction and dopaminergic neuron loss (p＜0.01 or p＜0.05). In contrast to MPP+/MPTP treatment, GAA treatment decreased the levels of iron, MDA, lipid and total ROS, while increasing the GSH level. GAA also reduced the levels of NCOA4 and LC3B, and enhanced the expressions of FTH1 and p62 in PD models (p＜0.01 or p＜0.05). However, the protective effect of GAA against the neurotoxicity, NCOA4-mediated ferritinophagy and ferroptosis in PD model was abolished by the overexpression of NCOA4 (p＜0.01). CONCLUSION: GAA exerted a protective effect on PD, and this effect was achieved by suppressing dopaminergic neuron ferroptosis through the inhibition of NCOA4-mediated ferritinophagy.

Prognostic Value of Inflammatory Cytokines in Predicting Hospital Readmissions in Heart Failure with Preserved Ejection Fraction.

Purpose: The aim of this study was to explore the relationship between inflammatory cytokines and the risk of heart failure (HF) readmission in patients with heart failure with preserved ejection fraction (HFpEF). Patients and Methods: We enrolled 429 patients with HFpEF admitted to the cardiology department in our hospital from January 2020 to July 2022. The patients were divided into the readmission or non-readmission groups according to whether they were readmitted for heart failure within 1 year of discharge. The clinical features and laboratory date of the subjects were collected and analyzed. Multivariate cox regression analysis was used to identify predictors of HF readmission. In addition, receiver operating characteristic (ROC) curves were used to determine the prognostic value of each factor. Results: The levels of IL-1ß, IL-6, IL-10, IL-17, TNF-α, NT-proBNP, heart rate, total cholesterol and NYHA class were significantly higher in the readmission group than in the non-readmission group (p < 0.05). IL-1ß, IL-6, IL-17, TNF-α, NT-proBNP, heart rate and NYHA class were identified as independent predictors of HF readmission. Conclusion: Inflammatory markers, including IL-1ß, IL-6, IL-17 and TNF-α were related to the HF readmission in patients with HFpEF.

Association between breakfast patterns and executive function among adolescents in Shanghai, China.

Introduction: The aim of this cross-sectional study was to investigate the association between breakfast patterns and executive function among adolescents in Shanghai, China. Methods: In 2022, we randomly recruited 3,012 adolescents aged 12-13 years from all administrative districts in Shanghai. Breakfast information was collected by parents using a one-day recall method. Executive function was measured using the Behavior Rating Inventory of Executive Function-Parent Version. Latent Class Analysis was performed to identify breakfast patterns based on the food groups in the Diet Quality Questionnaire for China. Results: Breakfast patterns were classified into three categories: "Egg and milk foods", "Grain foods", and "Abundant foods", except for adolescents who skipped breakfast. Logistic regression was used to estimate the multivariate odds ratio (ORs) and 95% confidence intervals (95% CI) for the association between breakfast patterns and potential executive dysfunction. Adolescents in the "Abundant foods" class had a lower risk of executive dysfunction in terms of initiate (OR: 0.36; 95% CI: 0.17-0.76), and organization of materials (OR: 0.18; 95% CI: 0.04-0.94), compared to those who skipped breakfast. Similarly, the breakfast patterns of "Grain foods" and "Egg and milk foods" were associated with a lower risk of executive dysfunction, including initiate and working memory. Discussion: Our findings suggest that breakfast patterns were associated with executive function. The improvement of breakfast patterns among adolescents should be a significant public health intervention.