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Abstract The accumulation of α-synuclein induces neuronal loss in midbrain nuclei and leads to the disruption of motor circuits, while the pathology of α-synuclein in cortical regions remains elusive. To better characterize cortical synucleinopathy, here we generate a mouse model with the overexpression of human α-synuclein in the primary motor cortex (M1) of mice. A combination of molecular, in vivo recording, and behavioral approaches reveal that cortical expression of human α-synuclein results in the overexcitation of cortical pyramidal neurons (PNs), which are regulated by the decreased inhibitory inputs from parvalbumin-interneurons (PV-INs) to impair complex motor skill learning. Further mechanistic dissections reveal that human α-synuclein aggregation activates ferroptosis, contributing to PV-IN degeneration and motor circuit dysfunction. Taken together, the current study adds more knowledge to the emerging role and pathogenic mechanism of ferroptosis in neurodegenerative diseases.

Abstract Background This study aimed to develop a comprehensive model based on five GLIM variables to predict the individual survival and provide more appropriate patient counseling. Methods This retrospective cohort study included 301 gastric cancer (GC) patients undergoing radical resection. C-reactive protein (CRP) as an inflammatory marker was included in GLIM criteria and a nomogram for predicting 5-year overall survival (OS) in GC patients was established. The Bootstrap repeated sampling for 1000 times was used for internal validation. Results Of the total 301 patients, 20 (6.64%) died within 5 years. CRP improved the sensitivity and accuracy of the survival prediction model (AUC = 0.782, 0.694 to 0.869 for the model without CRP; AUC = 0.880, 0.809 to 0.950 for the model adding CRP). Besides, a GLIM-based nomogram was established with an AUC of 0.889. The C-index for predicting OS was 0.878 (95% CI: 0.823 to 0.934), and the calibration curve fitted well. Decision curve analysis (DCA) showed the clinical utility of the nomogram based on GLIM. Conclusion The addition of CRP improved the sensitivity and accuracy of the survival prediction model. The 5-year survival probability of GC patients undergoing radical resection can be reliably predicted by the nomogram presented in this study.

The effect of a tilted-dipole three-dimensional corotating interaction region (CIR) on the transport and acceleration of solar energetic particles (SEPs) is studied. In this work, we discussed how the particle intensity longitudinal and radial dependence might be influenced by the background structures. Moreover, we investigate how the spectral index distribution is modulated by the CIR structure. We use the focused transport equation (FTE) to describe the propagation and acceleration of SEPs in a tilt-dipole 3D CIR, generated by the high-resolution 3D magnetohydrodynamic (MHD) model. The forward stochastic differential method is used to solve the FTE. The protons with the \begin{document}$ E^{-4.4} $\end{document} spectrum from 0.5 to 15 MeV are injected uniformly at the heliographic equator of 0.15 AU. Physical quantities are extracted along each interplanetary magnetic field (IMF) line to show the results. In the tilted-dipole CIR background, if injected from the solar equator at the inner boundary, particles in the slow flow are transported to higher latitudes due to the extension of the IMF lines to higher latitudes. The longitudinal patterns of the particles are dominated by the density of IMF lines. The focusing effect modulates the longitudinal variation of the particle intensity and gives rise to new longitudinal intensity peaks. The adiabatic effect largely increases the intensity fluctuation along the longitude. The structure of the solar wind can also lead to the difference of the index \begin{document}$ \alpha $\end{document} in the empirical function \begin{document}$ I_{{\mathrm{max}}}=kR^{-\alpha} $\end{document}, describing the radial variation of peak intensity according to our simulation. Under the influence of the CIR structure, the index \begin{document}$ \alpha $\end{document} varies from 1.9 to 3.4 at 0.3−1.0 AU. The variation of the solar wind speed should be considered when estimating the radial dependence of the SEP peak intensity. The spectra indices rise near the CIR boundaries and drop near the stream interface (SI). The adiabatic effect makes the spatial variability of the spectral index larger. The spectral index could be similar at different radial distances in the CIR structure.

Abstract Long-lasting La Niña events (including double-year and triple-year La Niña events) have become more frequent in recent years. How the multi-year La Niña events affect tropical cyclone (TC) activities in the western North Pacific (WNP) and whether they differ from single-year La Niña events are unknown. Here we show that TCs are more active over the far-WNP (FWNP, 110°–150°E), leading to marked high risks at China coasts during the second decaying summer of double-year La Niña events. The anomalous TC activities are directly related to the enhanced cyclonic anomaly over the FWNP, possibly a result of large-scale remote forcing initiated by the tropical North Atlantic (TNA) cooling. The persistent TNA cooling from the decaying winter to summer of double-year La Niña events drives westerlies over the Indo-western Pacific through Kelvin waves, which induce the cooling over the north Indian Ocean via the wind-evaporation-sea surface temperature effect, favoring the asymmetric heat distribution pattern and stimulating an anomalous vertical circulation over the eastern Indian Ocean to FWNP. The cooling over the north Indian Ocean also excites Gill responses, magnifying the TNA-induced westerlies and boosting the anomalous vertical circulation, and thus gives rise to the strong cyclonic circulation anomaly over the FWNP in summer. We suggest that the key point of the process is the strong TNA cooling related to the persistent negative Pacific-North American pattern (PNA) and positive North Atlantic Oscillation (NAO) while double-year La Niña events decay, distinct from the rapid decline of PNA and NAO during single-year La Niña events. The work provides a unique perspective on understanding TC activities over the WNP related to the El Niño-Southern Oscillation.

Abstract Due to the swift advancement of the Internet of Things (IoT), there has been a significant surge in the quantity of interconnected IoT devices that send and exchange vital data across the network. Nevertheless, the frequency of attacks on the Internet of Things is steadily rising, posing a persistent risk to the security and privacy of IoT data. Therefore, it is crucial to develop a highly efficient method for detecting cyber threats on the Internet of Things. Nevertheless, several current network attack detection schemes encounter issues such as insufficient detection accuracy, the curse of dimensionality due to excessively high data dimensions, and the sluggish efficiency of complex models. Employing metaheuristic algorithms for feature selection in network data represents an effective strategy among the myriad of solutions. This study introduces a more comprehensive metaheuristic algorithm called GQBWSSA, which is an enhanced version of the Salp Swarm Algorithm with several strategy improvements. Utilizing this algorithm, a threshold voting-based feature selection framework is designed to obtain an optimized set of features. This procedure efficiently decreases the number of dimensions in the data, hence preventing the negative effects of having a high number of dimensions and effectively extracting the most significant and crucial information. Subsequently, the extracted feature data is combined with the LightGBM algorithm to form a lightweight and efficient ensemble learning scheme for IoT attack detection. The proposed enhanced metaheuristic algorithm has superior performance in feature selection compared to the recent metaheuristic algorithms, as evidenced by the experimental evaluation conducted using the NSLKDD and CICIoT2023 datasets. Compared to current popular ensemble learning solutions, the proposed overall solution exhibits excellent performance on multiple key indicators, including accuracy, precision, as well as training and detection time. Especially on the large-scale dataset CICIoT2023, the proposed scheme achieves an accuracy rate of 99.70% in binary classification and 99.41% in multi classification.

Background: Our previous study synthesized the analgesic effects of repetitive Transcranial Magnetic Stimulation (rTMS) over the dorsolateral prefrontal cortex (DLPFC) trials up to 2019. There has been a significant increase in pain trials in the past few years, along with methodological variabilities such as sample size, stimulation intensity, and rTMS paradigms. Objectives/Methods: This study therefore updated the effects of DLPFC-rTMS on chronic pain and quantified the impact of methodological differences across studies. Results: A total of 36 studies were included. Among them, 26 studies were clinical trials (update = 9, 307/711 patients), and 10 (update = 1, 34/249 participants) were provoked pain studies. The updated meta-analysis does not support an effect on neuropathic pain after including the additional trials (pshort-term = 0.20, pmid-term = 0.50). However, there is medium-to-large analgesic effect in migraine trials extending up to six weeks follow-up (SMDmid-term = −0.80, SMDlong-term = −0.51), that was not previously reported. Methodological differences wthine the studies were considered. DLPFC-rTMS also induces potential improvement in the emotional aspects of pain (SMDshort-term = −0.28). Conclusions: The updated systematic meta-analysis continues to support analgesic effects for chronic pain overall. However, the updated results no longer support DLPFC-rTMS for pain relief in neuropathic pain, and do supports DLPFC-rTMS in the management of migraine. There is also evidence for DLPFC-rTMS to improve emotional aspects of pain.

Abstract Vibrio vulnificus, a significant marine pathogen, undergoes opaque (Op)-translucent (Tr) colony switching based on whether capsular polysaccharide (CPS) is produced. CPS phase variation is sometime accompanied by genetic variation or down-regulation of particular genes, such as wzb. In addition, CPS prevents biofilm formation and is important to the virulence of V. vulnificus. However, the extent to which there is a difference in gene expression between Tr and Op colonies and the impact of CPS phase variation on other behaviors of V. vulnificus remain unknown. In this work, the data have shown that CPS phase variation of V. vulnificus is affected by incubation time. Tr and Op strains exhibited similar growth rates. However, Tr strains had enhanced biofilm formation capacities but reduced swimming motility compared to Op strains. The RNA-seq assay revealed 488 differentially expressed genes, with 214 downregulated and 274 upregulated genes, between Tr and Op colonies. Genes associated with Tad pili and CPS were downregulated, whereas those involved in flagellum were upregulated, in Tr colonies compared with Op colonies. In addition, 9 putative c-di-GMP metabolism-associated genes and 28 genes encoding putative regulators were significantly differentially expressed, suggesting that CPS phase variation is probably strictly regulated in V. vulnificus. Moreover, 8 genes encoding putative porins were also differentially expressed between the two phenotypic colonies, indicating that bacterial outer membrane was remodeled during CPS phase variation. In brief, this work highlighted the gene expression profiles associated with CPS phase variation, but more studies should be performed to disclose the intrinsic mechanisms in the future.

Abstract In addition to focal lesions, diffusely abnormal white matter (DAWM) is seen on brain MRI of multiple sclerosis (MS) patients and may represent early or distinct disease processes. The role of MRI-observed DAWM is understudied due to a lack of automated assessment methods. Supervised deep learning (DL) methods are highly capable in this domain, but require large sets of labeled data. To overcome this challenge, a DL-based network (DAWM-Net) was trained using semi-supervised learning on a limited set of labeled data for segmentation of DAWM, focal lesions, and normal-appearing brain tissues on multiparametric MRI. DAWM-Net segmentation performance was compared to a previous intensity thresholding-based method on an independent test set from expert consensus (N = 25). Segmentation overlap by Dice Similarity Coefficient (DSC) and Spearman correlation of DAWM volumes were assessed. DAWM-Net showed DSC > 0.93 for normal-appearing brain tissues and DSC > 0.81 for focal lesions. For DAWM-Net, the DAWM DSC was 0.49 ± 0.12 with a moderate volume correlation (ρ = 0.52, p

Abstract Purpose This study evaluates the efficacy of intrauterine hCG perfusion for RIF, as defined by ESHRE 2023 guidelines, highlighting hCG as a cost-effective alternative to other immunotherapies, especially suitable for less developed regions. It aims to clarify treatment guidance amidst previous inconsistencies. Methods This meta-analysis, registered with PROSPERO (CRD42024443241) and adhering to PRISMA guidelines, assessed the efficacy and safety of intrauterine hCG perfusion in enhancing implantation and pregnancy outcomes in RIF. Comprehensive literature searches were conducted through December 2023 in major databases including PubMed, Web of Science, Embase, the Cochrane Library, and key Chinese databases, without language restrictions. Inclusion and exclusion criteria were strictly aligned with the 2023 ESHRE recommendations, with exclusions for studies lacking robust control, clear outcomes, or adequate data integrity. The risk of bias was evaluated using the Newcastle-Ottawa Scale, ROBINS-I, and RoB2 tools. Data analysis was performed in R using the ‘meta’ package, employing both fixed and random effect models to account for study variability. Subgroup analyses by dosage, volume, hCG concentration, timing of administration, and type of embryo transfer were conducted to deepen insights, enhancing the reliability and depth of the meta-analysis in elucidating the role of hCG perfusion in RIF treatments. Results Data from 13 studies, comprising six retrospective and six prospective studies from single centers, along with one multi-center RCT, totaling 2,157 participants, were synthesized to evaluate the effectiveness of intrauterine hCG perfusion in enhancing implantation and pregnancy outcomes in patients with RIF. Significant improvements were observed in clinical pregnancy and embryo implantation rates across various dosages, timing of administration, and embryo developmental stages, without impacting miscarriage rates. Notably, the most significant efficacy within subgroups occurred with a 500 IU dosage and perfusion parameters of ≤ 500µL volume and ≥ 2 IU/µL concentration. Additionally, a limited number of studies showed no significant increases in ectopic pregnancy or multiple pregnancy rates, and a modest improvement in live birth rates, although the small number of these studies precludes definitive conclusions. Conclusions The analysis suggests that intrauterine hCG perfusion probably enhances embryo implantation, clinical pregnancy, and live birth rates slightly in RIF patients. Benefits are indicated with a dosage of 500 IU and a maximum volume of 500µL at concentrations of at least 2 IU/µL. However, substantial heterogeneity from varying study types and the limited number of studies necessitate cautious interpretation. These findings underscore the need for more rigorously designed RCTs to definitively assess the efficacy and safety.

Abstract Many studies have reported metabolomic analysis of different bio-specimens from Parkinson’s disease (PD) patients. However, inconsistencies in reported metabolite concentration changes make it difficult to draw conclusions as to the role of metabolism in the occurrence or development of Parkinson’s disease. We reviewed the literature on metabolomic analysis of PD patients. From 74 studies that passed quality control metrics, 928 metabolites were identified with significant changes in PD patients, but only 190 were replicated with the same changes in more than one study. Of these metabolites, 60 exclusively increased, such as 3-methoxytyrosine and glycine, 54 exclusively decreased, such as pantothenic acid and caffeine, and 76 inconsistently changed in concentration in PD versus control subjects, such as ornithine and tyrosine. A genome-scale metabolic model of PD and corresponding metabolic map linking most of the replicated metabolites enabled a better understanding of the dysfunctional pathways of PD and the prediction of additional potential metabolic markers from pathways with consistent metabolite changes to target in future studies.

IntroductionDespite extensive studies on soil microbial community structure and functions, the significance of plant-associated microorganisms, especially endophytes, has been overlooked. To comprehensively anticipate future changes in forest ecosystem function under future climate change scenarios, it is imperative to gain a thorough understanding of the community structure, diversity, and function of both plant-associated microorganisms and soil microorganisms.MethodsIn our study, we aimed to elucidate the structure, diversity, and function of leaf endophytes, root endophytes, rhizosphere, and soil microbial communities in boreal forest. The microbial structure and composition were determined by high-throughput sequencing. FAPROTAX and FUNGuild were used to analyze the microbial functional groups.ResultsOur findings revealed significant differences in the community structure and diversity of fungi and bacteria across leaves, roots, rhizosphere, and soil. Notably, we observed that the endophytic fungal or bacterial communities associated with plants comprised many species distinct from those found in the soil microbial communities, challenging the assumption that most of endophytic fungal or bacterial species in plants originate from the soil. Furthermore, our results indicated noteworthy differences in the composition functional groups of bacteria or fungi in leaf endophytes, root endophytes, rhizosphere, and soil, suggesting distinct roles played by microbial communities in plants and soil.DiscussionThese findings underscore the importance of recognizing the diverse functions performed by microbial communities in both plant and soil environments. In conclusion, our study emphasizes the necessity of a comprehensive understanding of the structure and function microbial communities in both plants and soil for assessing the functions of boreal forest ecosystems.

BackgroundThe risk of congestive heart failure (CHF) is significantly affected by obesity. However, data on the association between visceral obesity and the risk of CHF remain limited. We explored the relationship between CHF and cardiometabolic index (CMI).MethodsDrawing from the National Health and Nutrition Examination Survey (NHANES) for 2011–2018, we enrolled 9,008 participants in a cross-sectional study. We calculated the CMI as triglyceride (TG)/high density lipid-cholesterol (HDL-C) × weight-to-height ratio (WHtR), and CMI-age as CMI × age. Then, we analyzed CMI and CMI-age as categorical and continuous variables to assess its correlation with CHF. To assess the relationships of CMI and CMI-age with CHF, we used multiple logistic regression models and performed subgroup analysis. To examine the predictive ability of CMI and CMI-age on patients with CHF, we used receiver operating characteristic (ROC) curves.ResultsThe overall prevalence of CHF was 3.31%. The results revealed significant differences in demographic data, comorbidities, lifestyle variables, standing height, BMI, WC, WHtR, TG, and HDL-C among the four groups classified by CMI quartile and CMI-age quartile. When indicators were analyzed as continuous variables, CMI and CMI-age showed positive correlations with CHF in both the crude and adjusted models (all P 0.05). The areas under the ROC curve (AUCs) of CMI and CMI-age in predicting CHF were 0.610 (95% CI, 0.578–0.642) and 0.697 (95% CI, 0.668–0.725) separately, suggesting that CMI-age was significantly better than the CMI in predicting CHF (P

The release of host mitochondrial cardiolipin is believed to be the main factor that contributes to the production of anti-cardiolipin antibodies in syphilis. However, the precise mechanism by which mitochondria release cardiolipin in this context remains elusive. This study aimed to elucidate the mechanisms underlying mitochondrial cardiolipin release in syphilis. We conducted a cardiolipin quantitative assay and immunofluorescence analysis to detect mitochondrial cardiolipin release in human microvascular endothelial cells (HMEC-1), with and without Treponema pallidum (Tp) infection. Furthermore, we explored apoptosis, a key mechanism for mitochondrial cardiolipin release. The potential mediator molecules were then analyzed through RNA-sequence and subsequently validated using in vitro knockout techniques mediated by CRISPR-Cas9 and pathway-specific inhibitors. Our findings confirm that live-Tp is capable of initiating the release of mitochondrial cardiolipin, whereas inactivated-Tp does not exhibit this capability. Additionally, apoptosis detection further supports the notion that the release of mitochondrial cardiolipin occurs independently of apoptosis. The RNA-sequencing results indicated that microtubule-associated protein2 (MAP2), an axonogenesis and dendrite development gene, was up-regulated in HMEC-1 treated with Tp, which was further confirmed in syphilitic lesions by immunofluorescence. Notably, genetic knockout of MAP2 inhibited Tp-induced mitochondrial cardiolipin release in HMEC-1. Mechanically, Tp-infection regulated MAP2 expression via the MEK-ERK-HES1 pathway, and MEK/ERK phosphorylation inhibitors effectively block Tp-induced mitochondrial cardiolipin release. This study demonstrated that the infection of live-Tp enhanced the expression of MAP2 via the MEK-ERK-HES1 pathway, thereby contributing to our understanding of the role of anti-cardiolipin antibodies in the diagnosis of syphilis.

BackgroundLower limb motor dysfunction is one of the most serious consequences of stroke; however, there is insufficient evidence for optimal rehabilitation strategies. Improving lower limb motor function through effective rehabilitation strategies is a top priority for stroke patients. Neuroplasticity is a key factor in the recovery of motor function. The extent to which neuroplasticity-based rehabilitation therapy using brain-computer interface (BCI) is effective in treating lower limb motor dysfunction in acute ischemic stroke patients has not been extensively investigated.ObjectiveThis study aimed to assess the impact of BCI rehabilitation on lower limb motor dysfunction in individuals with acute ischemic stroke by evaluating motor function, walking ability, and daily living activities.MethodsThis study was conducted in a randomized controlled trial, involving 64 patients with acute ischemic stroke who experienced lower limb motor dysfunction. All patients were divided into two groups, with 32 patients assigned to the control group was given conventional rehabilitation once a day for 70 min, 5 times a week for 2 weeks, and the experimental group (n = 32) was given BCI rehabilitation on top of the conventional rehabilitation for 1 h a day, 30 min of therapy in the morning and an additional 30 min in the afternoon, for a total of 20 sessions over a two-week period. The primary outcome was lower extremity motor function, which was assessed using the lower extremity portion of the Fugl-Meyer Rating Scale (FMA-LE), and the secondary endpoints were the Functional Ambulation Scale (FAC), and the Modified Barthel index (MBI).ResultsAfter 20 sessions of treatment, both groups improved in motor function, walking function, and activities of daily living, and the improvements in FMA-LE scores (p

Diabetic peripheral neuropathy (DPN) is a complication of diabetes mellitus that lacks specific treatment, its high prevalence and disabling neuropathic pain greatly affects patients’ physical and mental health. Schwann cells (SCs) are the major glial cells of the peripheral nervous system, which play an important role in various inflammatory and metabolic neuropathies by providing nutritional support, wrapping axons and promoting repair and regeneration. Increasingly, high glucose (HG) has been found to promote the progression of DPN pathogenesis by targeting SCs death regulation, thus revealing the specific molecular process of programmed cell death (PCD) in which SCs are disrupted is an important link to gain insight into the pathogenesis of DPN. This paper is the first to review the recent progress of HG studies on apoptosis, autophagy, pyroptosis, ferroptosis and necroptosis pathways in SCs, and points out the crosstalk between various PCDs and the related therapeutic perspectives, with the aim of providing new perspectives for a deeper understanding of the mechanisms of DPN and the exploration of effective therapeutic targets.

Background: Emerging evidence has shown the potential involvement of phthalates (PAEs) exposure in the development of dementia with Lewy bodies (DLB). Metabolomics can reflect endogenous metabolites variation in the progress of disease after chemicals exposure. However, little is known about the association between PAEs, gut microbiota and metabolome in DLB. Objective: We aim to explore the intricate relationship among urinary PAEs metabolites (mPAEs), dysbiosis of gut bacteria, and metabolite profiles in DLB. Methods: A total of 43 DLB patients and 45 normal subjects were included in this study. Liquid chromatography was used to analyze the levels of mPAEs in the urine of the two populations. High-throughput sequencing and liquid chromatography-mass spectrometry were used to analyze gut microbiota and the profile of gut metabolome, respectively. The fecal microbiota transplantation (FMT) experiment was performed to verify the potential role of mPAEs on gut dysbiosis contribute to aggravating cognitive dysfunction in α-synuclein tg DLB/PD mice. Results: The DLB patients had higher DEHP metabolites (MEOHP, MEHHP and MEHP), MMP and MnBP, lower MBP and MBzP than the control group and different microbiota. A significantly higher abundance of Ruminococcus gnavus and lower Prevotella copri, Prevotella stercorea and Bifidobacterium were observed in DLB. Higher 3 DEHP metabolites, MMP, MnBP and lower MBP and MBzP were significantly negatively associated with Prevotella copri, Prevotella stercorea and Bifidobacterium. Additionally, using metabolomics, we found that altered bile acids, short-chain fatty acids and amino acids metabolism are linked to these mPAEs. We further found that FMT of fecal microbiota from highest DEHP metabolites donors significantly impaired cognitive function in the germ-free DLB/PD mice. Conclusion: Our study suggested that PAEs exposure may alter the microbiota-gut-brain axis and providing novel insights into the interactions among environmental perturbations and microbiome-host in pathogenesis of DLB.

Abstract Objective IR emerges as a feature in the pathophysiology of PCOS, precipitating ovulatory anomalies and endometrial dysfunctions that contribute to the infertility challenges characteristic of this condition. Despite its clinical significance, a consensus on the precise mechanisms by which IR exacerbates PCOS is still lacking. This study aims to harness bioinformatics tools to unearth key IR-associated genes in PCOS patients, providing a platform for future therapeutic research and potential intervention strategies. Methods We retrieved 4 datasets detailing PCOS from the GEO, and sourced IRGs from the MSigDB. We applied WGCNA to identify gene modules linked to insulin resistance, utilizing IR scores as a phenotypic marker. Gene refinement was executed through the LASSO, SVM, and Boruta feature selection algorithms. qPCR was carried out on selected samples to confirm findings. We predicted both miRNA and lncRNA targets using the ENCORI database, which facilitated the construction of a ceRNA network. Lastly, a drug-target network was derived from the CTD. Results Thirteen genes related to insulin resistance in PCOS were identified via WGCNA analysis. LASSO, SVM, and Boruta algorithms further isolated CAPN2 as a notably upregulated gene, corroborated by biological verification. The ceRNA network involving lncRNA XIST and hsa-miR-433-3p indicated a possible regulatory link with CAPN2, supported by ENCORI database. Drug prediction analysis uncovered seven pharmacological agents, most being significant regulators of the endocrine system, as potential candidates for addressing insulin resistance in PCOS. Conclusions This study highlights the pivotal role of CAPN2 in insulin resistance within the context of PCOS, emphasizing its importance as both a critical biomarker and a potential therapeutic target. By identifying CAPN2, our research contributes to the expanding evidence surrounding the CAPN family, particularly CAPN10, in insulin resistance studies beyond PCOS. This work enriches our understanding of the mechanisms underlying insulin resistance, offering insights that bridge gaps in the current scientific landscape.

Abstract Aims Heart failure (HF) has shared genetic architecture with its risk factors: atrial fibrillation (AF), body mass index (BMI), coronary heart disease (CHD), systolic blood pressure (SBP), and type 2 diabetes (T2D). We aim to assess the association and risk prediction performance of risk‐factor polygenic risk scores (PRSs) for incident HF and its subtypes in bi‐racial populations. Methods and results Five PRSs were constructed for AF, BMI, CHD, SBP, and T2D in White participants of the Atherosclerosis Risk in Communities (ARIC) study. The associations between PRSs and incident HF and its subtypes were assessed using Cox models, and the risk prediction performance of PRSs was assessed using C statistics. Replication was performed in the ARIC study Black and Cardiovascular Health Study (CHS) White participants. In 8624 ARIC study Whites, 1922 (31% cumulative incidence) HF cases developed over 30 years of follow‐up. PRSs of AF, BMI, and CHD were associated with incident HF (P

High-quality lacustrine shale beds within the Paleogene Hetaoyuan Formation in the Biyang Sag, Nanxiang Basin, exhibit significant potential for shale oil resources. Previous studies on the oil-bearing potential and hydrocarbon occurrence of shales in the Biyang Sag were relatively limited, potentially hindering advancements for shale oil exploration. This study focuses on the shales found in the third sub-member of the third member within the Hetaoyuan Formation in well Y1, which locates in the southern area of the Biyang Sag. Through various geochemical analyses such as Rock-Eval pyrolysis, multi-temperature pyrolysis and X-ray diffraction, this research systematically investigates the shale oil contents, hydrocarbon occurrence characteristics, and influencing factors. These results indicate that the lithofacies assemblages of the shale primarily consist of felsic shale facies, dolomitic shale facies and mixed shale facies, with a well-developed laminar structure. The source rock quality is classified as good to excellent, and the thermal maturity stage of oil window. The predominant organic maceral is sapropelic, with organic matter types ranging from Ⅰ to Ⅱ1. Oil content increases with burial depth, ranged from adsorbed hydrocarbons in the upper section to free hydrocarbons in the lower section. Detrital mineral content and total organic carbon (TOC) content are identified as the main factors influencing free and adsorbed hydrocarbon content, respectively. Overall, the oil saturation index (OSI) of the shale in the lower section of the Hetaoyuan Formation exceeds 100 mg/g, with an average free hydrocarbon content over 3 mg/g, indicating promising prospects for shale oil exploration and development.

Abstract Background Fluvoxamine is one of the selective serotonin reuptake inhibitors (SSRIs) that are regarded as the first-line drugs to manage mental disorders. It has been also recognized with the potential to treat inflammatory diseases and viral infection. However, the effect of fluvoxamine on autoimmune diseases, particularly type 1 diabetes (T1D) and the related cellular and molecular mechanisms, are yet to be addressed. Method Herein in this report, we treated NOD mice with fluvoxamine for 2 weeks starting from 10-week of age to dissect the impact of fluvoxamine on the prevention of type 1 diabetes. We compared the differences of immune cells between 12-week-old control and fluvoxamine-treated mice by flow cytometry analysis. To study the mechanism involved, we extensively examined the characteristics of CD4+ T cells with fluvoxamine stimulation using RNA-seq analysis, real-time PCR, Western blot, and seahorse assay. Furthermore, we investigated the relevance of our data to human autoimmune diabetes. Result Fluvoxamine not only delayed T1D onset, but also decreased T1D incidence. Moreover, fluvoxamine-treated NOD mice showed significantly attenuated insulitis coupled with well-preserved β cell function, and decreased Th1 and Th17 cells in the peripheral blood, pancreatic lymph nodes (PLNs), and spleen. Mechanistic studies revealed that fluvoxamine downregulated glycolytic process by inhibiting phosphatidylinositol 3-kinase (PI3K)-AKT signaling, by which it restrained effector T (Teff) cell differentiation and production of proinflammatory cytokines. Conclusion Collectively, our study supports that fluvoxamine could be a viable therapeutic drug against autoimmunity in T1D setting.

Objective Investigation of explainable deep learning methods for graph neural networks to predict HIV infections with social network information and performing domain adaptation to evaluate model transferability across different datasets.Methods Network data from two cohorts of younger sexual minority men (SMM) from two U.S. cities (Chicago, IL, and Houston, TX) were collected between 2014 and 2016. Feature importance from graph attention network (GAT) models were determined using GNNExplainer. Domain adaptation was performed to examine model transferability from one city dataset to the other dataset, training with 100% of the source dataset with 30% of the target dataset and prediction on the remaining 70% from the target dataset.Results Domain adaptation showed the ability of GAT to improve prediction over training with single city datasets. Feature importance analysis with GAT models in single city training indicated similar features across different cities, reinforcing potential application of GAT models in predicting HIV infections through domain adaptation.Conclusion GAT models can be used to address the data sparsity issue in HIV study populations. They are powerful tools for predicting individual risk of HIV that can be further explored for better understanding of HIV transmission.

The incompletely eliminated Treponema pallidum (T. pallidum) during primary syphilis chancre infection can result in the progression of secondary, tertiary, or latent syphilis in individuals, suggesting that T. pallidum has successfully evaded the immune response and spread to distant sites. The mechanism underlying the dissemination of T. pallidum is unclear. Here, a syphilitic rabbit model dorsal-injected with recombinant Tp0136 protein or Tp0136 antibody subcutaneously was used to demonstrate the role of Tp0136 protein in promoting the dissemination of T. pallidum to the testis and angiogenesis in vivo; vascular endothelial cell line HMEC-1 was employed to display that Tp0136 protein enhances the angiogenesis. Furthermore, the three-dimensional microfluidic angiogenesis system showed that the angiogenesis would heighten vascular permeability. Then transcriptome sequencing analysis, in conjunction with cell-level validation, elucidated the critical role of the PI3K-AKT signaling pathway in the promotion of angiogenesis by Tp0136 protein, resulting in heightened permeability. These findings elucidate the strategy employed by T. pallidum in evading immune clearance.

Background: Amauroderma rugosum (AR) is a medicinal mushroom commonly used to treat inflammation, gastric disorders, epilepsy, and cancers due to its remarkable anti-inflammatory and anti-oxidative properties. This study was designed to evaluate the pharmacological effects of AR and its underlying mechanism of action against ulcerative colitis (UC) in vitro and in vivo. Methods: A UC mouse model was established by administration of dextran sulfate sodium (DSS). AR extract was administered intragastrically to mice for 7 days. At the end of the experiment, histopathology, macrophage phenotype, oxidative stress, and inflammatory status were examined in vivo. Furthermore, RAW 264.7, THP-1, and Caco-2 cells were used to elucidate the mechanism of action of AR in vitro. Results: AR extract (0.5–2 mg/mL) significantly suppressed lipopolysaccharide (LPS) and interferon-gamma (IFN-γ)-induced M1 macrophage (pro-inflammatory) polarization in both RAW 264.7 and THP-1 cells. LPS-induced pro-inflammatory mediators (nitric oxide, TNF-α, IL-1β, MCP-1, and IL-6) were reduced by AR extract in a concentration-dependent manner. Similarly, AR extract downregulated MAPK signaling activity in LPS-stimulated RAW 264.7 cells. AR extract elicited a concentration-dependent increase in the mRNA expression of M2 (anti-inflammatory) phenotype markers (CD206, Arg-1, Fizz-1, and Ym-1) in RAW 264.7 cells. Moreover, AR extract suppressed DSS-induced ROS generation and mitochondrial dysfunction in Caco-2 cells. The in vivo experiment revealed that AR extract (200 mg/kg) increased colon length compared to the DSS-treated group. In addition, disease activity index, spleen ratio, body weight, oxidative stress, and colonic inflammation were markedly improved by AR treatment in DSS-induced UC mice. Finally, AR suppressed M1 and promoted M2 macrophage polarization in UC mice. Conclusion: The AR extract protected against DSS-induced UC by regulating macrophage polarization and suppressing oxidative stress. These valuable findings suggest that adequate intake of AR can prevent and/or treat UC.

Summary: High salt (HS) consumption is a risk factor for multiple autoimmune disorders via disturbing immune homeostasis. Nevertheless, the exact mechanisms by which HS exacerbates rheumatoid arthritis (RA) pathogenesis remain poorly defined. Herein, we found that heightened phosphorylation of PDPK1 and SGK1 upon HS exposure attenuated FoxO1 expression to enhance the glycolytic capacity of CD4 T cells, resulting in strengthened Th17 but compromised Treg program. GSK2334470 (GSK), a dual PDPK1/SGK1 inhibitor, effectively mitigated the HS-induced enhancement in glycolytic capacity and the overproduction of IL-17A. Therefore, administration of GSK markedly alleviated HS-exacerbated RA progression in collagen-induced arthritis (CIA) model. Collectively, our data indicate that HS consumption subverts Th17/Treg homeostasis through the PDPK1-SGK1-FoxO1 signaling, while GSK could be a viable drug against RA progression in clinical settings.

Vibrio parahaemolyticus is widely distributed in marine ecosystems. Magnesium ion (Mg2+) is the second most abundant metal cation in seawater, and plays important roles in the growth and gene expression of V. parahaemolyticus, but lacks the detailed mechanisms. In this study, the RNA sequencing data demonstrated that a total of 1494 genes was significantly regulated by Mg2+. The majority of the genes associated with lateral flagella, exopolysaccharide, type III secretion system 2, type VI secretion system (T6SS) 1, T6SS2, and thermostable direct hemolysin were downregulated. A total of 18 genes that may be involved in c-di-GMP metabolism and more than 80 genes encoding putative regulators were also significantly and differentially expressed in response to Mg2+, indicating that the adaptation process to Mg2+ stress may be strictly regulated by complex regulatory networks. In addition, Mg2+ promoted the proliferative speed, swimming motility and cell adhesion of V. parahaemolyticus, but inhibited the swarming motility, biofilm formation, and c-di-GMP production. However, Mg2+ had no effect on the production of capsular polysaccharide and cytoxicity against HeLa cells. Therefore, Mg2+ had a comprehensive impact on the physiology and gene expression of V. parahaemolyticus.

[INLINE:1] Epilepsy frequently leads to cognitive dysfunction and approaches to treatment remain limited. Although regular exercise effectively improves learning and memory functions across multiple neurological diseases, its application in patients with epilepsy remains controversial. Here, we adopted a 14-day treadmill-exercise paradigm in a pilocarpine injection-induced mouse model of epilepsy. Cognitive assays confirmed the improvement of object and spatial memory after endurance training, and electrophysiological studies revealed the maintenance of hippocampal plasticity as a result of physical exercise. Investigations of the mechanisms underlying this effect revealed that exercise protected parvalbumin interneurons, probably via the suppression of neuroinflammation and improved integrity of blood-brain barrier. In summary, this work identified a previously unknown mechanism through which exercise improves cognitive rehabilitation in epilepsy.

Abstract Background Highly carbonized energy use in ecologically fragile areas of Northwest China seriously endangers the health of residents and the ecological environment. However, poor energy affordability remains a major obstacle to the promotion of clean energy use in rural households in this region. Methods Based on survey data of 1118 households in ecologically fragile areas of Northwest China, this study constructed a household-level database of energy use, measured energy affordability in two dimensions: endogenous income (annual per capita household income) and external inputs (government energy subsidies). It uses logistic and threshold regression to empirically test the impact, threshold, and heterogeneity of energy affordability on the decision-making of rural households regarding clean energy use for cooking, heating, and heating water. Results (1) The energy use structures of rural households in different ecologically fragile areas differ because of different household characteristics. (2) Energy affordability affects cooking significantly more than it affects heating and subsidy growth is a stronger incentive than income growth. Moreover, for both cooking and heating, energy affordability has a greater impact on electricity use than on gas use. (3) The thresholds for energy transformation for heating are greater than those for cooking and heating water. When the subsidy increases by 2400 yuan/year, heating can catch up to other types of use, whereas, based on the current level of income growth, it requires more than 5 years. (4) This effect is higher in high-income, purely agricultural, highly educated, young, and middle-aged households. Conclusions Promoting the use of clean energy in rural households only by increasing income will be a slow process. Subsidies should be used to accelerate this process by improving the energy affordability of rural households and a compensation policy should be implemented considering the energy types and periods. Taking into account the differences in the basic characteristics of rural households in different ecologically fragile areas, clean energy policies should be adopted from various perspectives to better leverage the enhancement effect of energy affordability.

Abstract Gaining continuous trust from mobile banking customers is a critical step in retaining customers for their usage of the provided services. The current study aims to investigate how customers’ continuous trust is formed at the continuous-use stage. Online survey responses from 450 frequent mobile banking users are collected. The data were analysed using structural equation modelling (SEM) based on a proposed model that predicts trust. The findings successfully validated the model and its reduced form. Based on the model, customers’ continuous trust can be predicted by mobile banking apps’ perceived ease of use, privacy assurance and security features, organisation reputation, customer support, and customers’ previous experience. Furthermore, the interactive relationships among these proposed factors are proposed and validated in the model. By studying trust in mobile banking past the initial adoption stage, we provide evidence to support the theoretical framework of investigating mobile banking continuous trust from the three constructs—mobile app (perceived ease of use, privacy assurance, security features), organisation (reputation, customer support), and customer (prior experience).

Abstract Worldwide, primary liver cancer is the third leading cause of cancer-related death. Hepatocellular carcinoma (HCC) accounts for the majority of primary liver cancers. Recent studies have shown that circular RNAs (circRNAs) that interact with microRNAs (miRNAs) are involved in the occurrence and development of various tumours. Transcriptional profile analysis was used to analyse expression of circRNAs in HCC in this study. The top ten upregulated circRNAs were selected and validated by quantitative reverse transcription polymerase chain reaction (qRT-PCR) in another 34 HCC patients. MiRNAs and mRNAs downstream of these circRNAs were explored through database analysis, and finally, the competitive endogenous RNA (ceRNA) networks were constructed for 5 selected circRNAs. We identified 9658 differentially expressed circRNAs by transcriptional profile analysis. QRT-PCR was performed to validate the top ten upregulated circRNAs, and five circRNAs were selected for further analysis. The miRNAs and mRNAs downstream of these five circRNAs were predicted to construct ceRNA network diagrams. Further analysis revealed five circRNA–miRNA–mRNA axes that correlate negatively with HCC prognosis. Numerous differentially expressed circRNAs exist in HCC, and they can regulate the biological behaviour of HCC through ceRNA networks. Bioinformatics analysis showed that ceRNA regulatory axes involved in HCC have high diagnostic and prognostic value and deserve further exploration.

Aquatic animals are an important source of food for humans, yet little is known about their potential to transfer zoonotic viruses. Multiple recent cases of SARS-CoV-2 from cold-chain aquatic food and environmental samples has evoked worldwide concerns, and even though these cases pale in comparison to poultry and livestock. To investigate the potential threat of food from aquatic animals, we map their transcriptomes to the genomes of human respiratory- and intestine-related viruses. Analyses only find an influenza virus sequence in a salmon (Salmo salar) skin transcriptome. BLAST and phylogenetic analyses identify this sequence as influenza A, and this likely owes to contamination from a worker. Thus, when prepared properly, aquatic animals can provide great nutritional benefits to humans while posing minimal health risks.

The rural energy reform, which is caused by the rapid development of renewable energy, will significantly impact rural residents’ energy use behaviors. The willingness of rural residents to adjust energy use is critical for realizing the rural energy reform. In this study, a questionnaire survey was implemented to ask residents to consider three virtual electricity pricing scenarios and investigate residents’ willingness to adjust energy use behaviors. Scenario PVR (Peak–valley rate) involved applying the peak–valley rate electricity price. Scenario PVS (Photovoltaic systems) involved building photovoltaic systems. Scenario OFR (Original flat-rate) involved maintaining the original flat-rate electricity price. The extended theory of planned behavior was then used to conduct a multi-group analysis to assess the factors influencing rural residents’ willingness to adjust energy use. The field research results for 533 rural households in the Guanzhong Plain in China indicated that (1) The proportions of rural residents choosing Scenario PVR, Scenario PVS, and Scenario OFR were 45.22%, 22.89%, and 31.89%, respectively. (2) The rural residents choosing Scenario PVS and Scenario OFR showed the strongest and the weakest willingness to adjust energy use, respectively. (3) Social capital significantly affected residents’ attitude and perceived behavioral control about their willingness to adjust energy use; however, there is a discrepancy in the impact mechanism for different residents. (4) For rural residents choosing Scenario PVS, their willingness to adjust energy use was significantly affected by policies and regulations; the impact was less significant for residents choosing the other scenarios.

Abstract Background Sepsis is a life-threatening disease with a poor prognosis, and metabolic disorders play a crucial role in its development. This study aims to identify key metabolites that may be associated with the accurate diagnosis and prognosis of sepsis. Methods Septic patients and healthy individuals were enrolled to investigate metabolic changes using non-targeted liquid chromatography-high-resolution mass spectrometry metabolomics. Machine learning algorithms were subsequently employed to identify key differentially expressed metabolites (DEMs). Prognostic-related DEMs were then identified using univariate and multivariate Cox regression analyses. The septic rat model was established to verify the effect of phenylalanine metabolism-related gene MAOA on survival and mean arterial pressure after sepsis. Results A total of 532 DEMs were identified between healthy control and septic patients using metabolomics. The main pathways affected by these DEMs were amino acid biosynthesis, phenylalanine metabolism, tyrosine metabolism, glycine, serine and threonine metabolism, and arginine and proline metabolism. To identify sepsis diagnosis-related biomarkers, support vector machine (SVM) and random forest (RF) algorithms were employed, leading to the identification of four biomarkers. Additionally, analysis of transcriptome data from sepsis patients in the GEO database revealed a significant up-regulation of the phenylalanine metabolism-related gene MAOA in sepsis. Further investigation showed that inhibition of MAOA using the inhibitor RS-8359 reduced phenylalanine levels and improved mean arterial pressure and survival rate in septic rats. Finally, using univariate and multivariate cox regression analysis, six DEMs were identified as prognostic markers for sepsis. Conclusions This study employed metabolomics and machine learning algorithms to identify differential metabolites that are associated with the diagnosis and prognosis of sepsis patients. Unraveling the relationship between metabolic characteristics and sepsis provides new insights into the underlying biological mechanisms, which could potentially assist in the diagnosis and treatment of sepsis. Trial registration This human study was approved by the Ethics Committee of the Research Institute of Surgery (2021–179) and was registered by the Chinese Clinical Trial Registry (Date: 09/12/2021, ChiCTR2200055772).

Abstract Background Hepatocellular carcinoma (HCC), abbreviated as liver cancer, is one of the most common cancers in clinics. HCC has a wider spread and higher incidence due to its high malignancy and metastasis. In HCC, effective strategies to block cancer cell migration, invasion, and neovascularization need to be further studied. Consumption of flavonoid-rich Oroxylum indicum (OI) has been associated with multiple beneficial effects, including anti-inflammatory and anticancer properties, but the potential effects on HCC have not been thoroughly investigated. Objective In this study, we aimed to reveal the effect of OI on HCC and its potential mechanism through microfluidic technology. Methods We designed microfluidic chips for cell migration, invasion, and neovascularization to evaluate the effect of OI on HepG2 cells. To further explore the mechanism of its anti-liver cancer action, the relevant signaling pathways were studied by microfluidic chips, RT‒qPCR and immunofluorescence techniques. Compared to the control group, cell migration, invasion, and angiogenesis were significantly reduced in each administration group. According to the P53 and VEGF pathways predicted by network pharmacology, RT‒qPCR and immunofluorescence staining experiments were conducted. Results The results showed that OI upregulated the expression of Bax, P53 and Caspase-3 and downregulated the expression of Bcl-2 and MDM2. It has been speculated that OI may directly or indirectly induce apoptosis of HepG2 cells by regulating apoptosis-related genes. OI blocks the VEGF signaling pathway by downregulating the expression levels of VEGF, HIF-1α and EGFR and inhibits the migration and invasion of HepG2 cells and the formation of new blood vessels. Conclusion Our findings suggest that OI may inhibit the migration, invasion, and neovascularization of HepG2 cells, and its regulatory mechanism may be related to the regulation of the P53 and VEGF pathways.

Abstract The vast majority of Parkinson’s disease cases are idiopathic. Unclear etiology and multifactorial nature complicate the comprehension of disease pathogenesis. Identification of early transcriptomic and metabolic alterations consistent across different idiopathic Parkinson’s disease (IPD) patients might reveal the potential basis of increased dopaminergic neuron vulnerability and primary disease mechanisms. In this study, we combine systems biology and data integration approaches to identify differences in transcriptomic and metabolic signatures between IPD patient and healthy individual-derived midbrain neural precursor cells. Characterization of gene expression and metabolic modeling reveal pyruvate, several amino acid and lipid metabolism as the most dysregulated metabolic pathways in IPD neural precursors. Furthermore, we show that IPD neural precursors endure mitochondrial metabolism impairment and a reduced total NAD pool. Accordingly, we show that treatment with NAD precursors increases ATP yield hence demonstrating a potential to rescue early IPD-associated metabolic changes.

Abstract SUMOylation is an evolutionary conserved regulatory mechanism, in which Ubc9 is the only E2 conjugating enzyme. Previous studies demonstrated that SUMOylation is involved in multiple biological processes, but its role in dendritic cells (DCs) remains to be fully addressed. Herein in this report, we found that DCs deficient in Ubc9 protected mice from dextran sulfate sodium (DSS)-induced colitis, as evidenced by the ameliorated weight loss, colon length, and disrupted colon structure. Mechanistically, Ubc9 mediated SUMOylation of RBPJ, by which it stabilized RBPJ from ubiquitin-mediated degradation to enhance its transcriptional activity, while Ciita, a critical transcription factor, is a direct target downstream of RBPJ, which forms an enhanceosome complex to transcribe the expression of MHC II genes. Therefore, loss of Ubc9 abolished RBPJ SUMOylation, which was coupled with reduced Ciita transcription, thereby attenuating the expression of MHC class II genes. As a consequence of defective MHC II expression, Ubc9 -/- DCs were featured by the impaired capability to process antigen and to prime effector CD4+ T cells, thereby protecting mice from DSS-induced colitis. Together, our results shed novel insight into the understanding of SUMOylation in the regulation of DC functions in pathological conditions.

Epsilon toxin (ETX), a potential agent of biological and toxic warfare, causes the death of many ruminants and threatens human health. It is crucial to understand the toxic mechanism of such a highly lethal and rapid course toxin. In this study, we detected the effects of ETX on the proteome and phosphoproteome of MDCK cells after 10 min and 30 min. A total of 44 differentially expressed proteins (DEPs) and 588 differentially phosphorylated proteins (DPPs) were screened in the 10 min group, while 73 DEPs and 489 DPPs were screened in the 30 min group. ETX-induced proteins and phosphorylated proteins were mainly located in the nucleus, cytoplasm, and mitochondria, and their enrichment pathways were related to transcription and translation, virus infection, and intercellular junction. Meanwhile, the protein–protein interaction network screened out several hub proteins, including SRSF1/2/6/7/11, SF3B1/2, NOP14/56, ANLN, GTPBP4, THOC2, and RRP1B. Almost all of these proteins were present in the spliceosome pathway, indicating that the spliceosome pathway is involved in ETX-induced cell death. Next, we used RNAi lentiviruses and inhibitors of several key proteins to verify whether these proteins play a critical role. The results confirmed that SRSF1, SF3B2, and THOC2 were the key proteins involved in the cytotoxic effect of ETX. In addition, we found that the common upstream kinase of these key proteins was SRPK1, and a reduction in the level of SRPK1 could also reduce ETX-induced cell death. This result was consistent with the phosphorylated proteomics analysis. In summary, our study demonstrated that ETX induces phosphorylation of SRSF1, SF3B2, THOC2, and SRPK1 proteins on the spliceosome pathway, which inhibits normal splicing of mRNA and leads to cell death.

Green space improves outdoor thermal comfort and promotes the residents’ physical and mental health. Currently, many cities are using green volume indicators to evaluate the quality of residential green space and to help form the latest evaluation standards. However, from the perspective of plant green volume, the impact of green space structures on thermal mitigation has not been emphasized. Furthermore, the cost of green space will change with the green space structures. Therefore, we evaluate the impact of changes in green space structures on thermal mitigation and costs from the perspective of plant green volume and aim to find suitable allocations of plant green volume, which balance thermal mitigation with cost savings. This study analyzed the regional climate and residential green space structures. Then, we discussed the relationship between thermal mitigation and the costs of different structures. The analytical results indicated that thermal comfort improves as the green volume of trees increases, with costs also increasing. Where the green volume exceeds 70%, no “extreme heat stress” moments occur for the whole day. When the green volume of trees increases from 20% to 60%, the thermal mitigation is 3.62 °C. However, the mitigation is only 1.74 °C when the green volume increases from 60% to 100%, which is less than half of the former, numerically. This study suggests that the green volume of trees in residential green spaces should be controlled at 60%–70% and the corresponding green volume of shrubs should be 30%–40%. This study rationally balances the thermal mitigation and costs of residential green space, which will directly guide residential green space planning in real situations.

Regulator of G-protein signaling (RGS) proteins are regulators of signal transduction mediated by G protein-coupled receptors (GPCRs). Current studies have shown that some molecules in the RGS gene family are related to the occurrence, development and poor prognosis of malignant tumors. However, the RGS gene family has been rarely studied in gastric cancer. In this study, we explored the mutation and expression profile of RGS gene family in gastric cancer, and evaluated the prognostic value of RGS expression. Then we established a prognostic model based on RGS gene family and performed functional analysis. Further studies showed that RGS4, as an independent prognostic predictor, may play an important role in regulating fibroblasts in the immune microenvironment. In conclusion, this study explores the value of RGS gene family in gastric cancer, which is of great significance for predicting the prognosis and guiding the treatment of gastric cancer.

Abatract: Objectives: Recently, there has been extensive research on dual immunotherapy for advanced or metastatic non-small cell lung cancer (NSCLC), yet a comprehensive evaluation is lacking. This study aimed to rank the available treatment options and assess the efficacy and safety of dual immunotherapy regimens through the implementation of a Bayesian network meta-analysis (NMA). Materials and methods: A thorough search was conducted to recognize eligible randomized controlled trials (RCTs) on March 20, 2023. Overall survival (OS), progression-free survival (PFS), treatment-related adverse events (TRAEs) and grade ≥3 TRAEs were evaluated to identify the efficacy and safety of dual immunotherapy regimens. The surface under the cumulative ranking curve (SUCRA) and P score were employed to rank the treatments. Results: Eleven clinical trials involving six different regimens were included in this study. The combination of anti-programmed cell death protein 1/programmed cell death ligand 1 (PD-1/PD-L1) antibodies with anti-T-cell immunoglobulin and ITIM domain (TIGIT) antibodies emerged as the most promising regimen for improving OS and PFS, followed by anti-PD-1/PD-L1 + anti-cytotoxic T lymphocyte antigen 4 (CTLA-4) + chemotherapy treatment and anti-PD-1/PD-L1 + anti-CTLA-4 treatment. The forest plots demonstrated that these three regimens were all superior to chemotherapy. The above results were observed in both unselected treatment line and first-line settings. The least likely to be associated with TRAEs and grade ≥3 TRAEs were respectively anti-CTLA-4 treatment and anti-PD-1/PD-L1 + anti-TIGIT treatment, with anti-PD-1/PD-L1 + anti-CTLA-4 + chemotherapy treatment to be the worst. Conclusions: This NMA validated the promising efficacy and safety of dual immunotherapy in advanced or metastatic NSCLC. Among them, anti-PD-1/PD-L1 + anti-TIGIT regimen emerges as a highly potential therapeutic approach. Ongoing research efforts should focus on improving treatment regimens, identifying biomarkers, and managing TRAEs to optimize the patient benefits of dual immunotherapy.

Abstract The regulation of autoimmunity against pancreatic islet β cells for type 1 diabetes (T1D) onset is still unclear. NOD/ShiLtJ (NOD) mice are prone to the onset of autoimmune diabetes, but its congenic strain, ALR/Lt (ALR), is not. Here we show that dendritic cells (DC) in ALR mice have impaired migratory and T-cell priming capability. Genomic comparative analysis maps a 33-bp deletion in the ALR Myosin IXb (Myo9b) gene when compared with NOD genome; meanwhile, data from knock-in models show that this ALR Myo9b allele impairs phenotypic and functional maturation of DCs, and prevents the development and progression of spontaneous autoimmune diabetes in NOD mice. In parallel, while the ALR 33-bp deletion of Myo9b is not conserved in human, we find a MYO9B R133Q polymorphism associating with increased risk of T1D and enhanced DC function in patients with T1D. Our results thus hint that alterations in Myo9b may contribute to altered DC function and autoimmune diabetes onset.

Abstract Plasma miRNAs can characterize several diseases, including acute ischemic stroke (AIS), which is noninvasive and currently affordable in most laboratories worldwide. We aimed to demonstrate plasma miR‐140‐3p, miR‐130a‐3p, and miR‐320b as diagnostic biomarkers in AIS.GSE110993 and GSE86291 datasets were analyzed to obtain plasma differentially expressed miRNAs between AIS and healthy control subjects (HCs). We further applied RT‐qPCR for the validation in 85 AIS patients and 85 HCs. Receiver operating characteristic (ROC) curve were conducted to evaluate their diagnostic utility in AIS. Correlation was analyzed between DEmiRNAs and clinical and laboratory parameters, as well as inflammatory markers. The plasma levels of miR‐140‐3p, miR‐130a‐3p, and miR‐320b were found to be consistently altered in both GSE110993 and GSE86291 datasets. In comparison to HCs, AIS patients at admission exhibited lower levels of miR‐140‐3p and miR‐320b and higher level of miR‐130a‐3p in their plasma. The ROC analysis revealed that plasma miR‐140‐3p, miR‐130a‐3p, and miR‐320b had area under the curve values of 0.790, 0.831, and 0.907, respectively. When combined, these miRNAs showed superior discriminatory power with a sensitivity of 91.76% and specificity of 95.29%. Plasma miR‐140‐3p and miR‐320b negatively correlated glucose levels and inflammatory markers (IL‐6, MMP‐2, MMP‐9, and VEGF) in AIS patients. Conversely, plasma miR‐130a‐3p levels were positively associated with glucose levels and these markers. Plasma miR‐140‐3p, miR‐130a‐3p, and miR‐320b levels varied significantly among AIS patients with different NIHSS scores. Plasma miR‐140‐3p, miR‐130a‐3p, and miR‐320b had high diagnostic value in AIS patients, which were correlated with inflammation and severity in stroke.

Background: Excessive osteoclast formation disrupts bone homeostasis, thereby significantly contributing to pathological bone loss associated with a variety of diseases. Protein S-palmitoylation is a reversible post-translational lipid modification catalyzed by ZDHHC family of palmitoyl acyltransferases, which plays an important role in various physiological and pathological processes. However, the role of palmitoylation in osteoclastogenesis has never been explored. Consequently, it is unclear whether this process can be targeted to treat osteolytic bone diseases that are mainly caused by excessive osteoclast formation. Materials and methods: In this study, we employed acyl-biotin exchange (ABE) assay to reveal protein S-palmitoylation in differentiating osteoclasts (OCs). We utilized 2-bromopalmitic acid (2-BP), a pharmacological inhibitor of protein S-palmitoylation, to inhibit protein palmitoylation in mouse bone marrow-derived macrophages (BMMs), and tested its effect on receptor activator of nuclear factor κβ ligand (RANKL)-induced osteoclast differentiation and activity by TRAP staining, phalloidin staining, qPCR analyses, and pit formation assays. We also evaluated the protective effect of 2-BP against estrogen deficiency-induced bone loss and bone resorption in ovariectomized (OVX) mice using μCT, H&E staining, TRAP staining, and ELISA assay. Furthermore, we performed western blot analyses to explore the molecular mechanism underlying the inhibitory effect of 2-BP on osteoclastogenesis. Results: We found that many proteins were palmitoylated in differentiating OCs and that pharmacological inhibition of palmitoylation impeded RANKL-induced osteoclastogenesis, osteoclast-specific gene expression, F-actin ring formation and osteoclastic bone resorption in vitro, and to a lesser extent, osteoblast formation from MC3T3-E1 cells. Furthermore, we demonstrated that administration of 2-BP protected mice from ovariectomy-induced osteoporosis and bone resorption in vivo. Mechanistically, we showed that 2-BP treatment inhibited osteoclastogenesis partly by downregulating the expression of c-Fos and NFATc1 without overtly affecting RANKL-induced activation of osteoclastogenic AKT, MAPK, and NF-κB pathways. Conclusion: Pharmacological inhibition of palmitoylation potently suppresses RANKL-mediated osteoclast differentiation in vitro and protects mice against OVX-induced osteoporosis in vivo. Mechanistically, palmitoylation regulates osteoclast differentiation partly by promoting the expression of c-Fos and NFATc1. Thus, palmitoylation plays a key role in promoting osteoclast differentiation and activity, and could serve as a potential therapeutic target for the treatment of osteoporosis and other osteoclast-related diseases. The translational potential of this article: The translation potential of this article is that we first revealed palmitoylation as a key mechanism regulating osteoclast differentiation, and therefore provided a potential therapeutic target for treating osteolytic bone diseases.

With the emergence of spot electricity trading, market-oriented trading has been intensively carried out, forming a multi-cycle trading system. In this process, a large amount of fine-grained electricity trading data circulates on the trading platform. Trading data is an important basis for decision-making in the electricity spot market, which directly affects the trading profits of market entities, proper disclosure of this information is very important for market enterprises. Information disclosure must ensure the validity and security. However, it is hard to judge the security demand for trading data, and there is no suitable evaluation system for determining the security requirement of data, which will limit the electricity market’s further development. In this paper, we first design an indicator system for security requirements classification, which manages data risks from three aspects: data classification, data risk, and entity demand. This system will guide us in determining data security requirements and further help identify differentiated data security protection schemes. Then, based on this system, we propose the classification method of data security requirements through a hierarchical fuzzy Petri net. The lower network realizes a reasonable assessment of data risk with reference to the index system, and the upper network finally determines the level of security requirements through the fuzzy rule base. Last, two types of data are selected to judge their security requirements. The results show that our method can provide a reference for privacy protection in electricity market data.

ObjectiveTo explore the association of short-term exposure to particulate matter ≤ 2.5 and ≤ 10 μm in aerodynamic diameter (PM2.5 and PM10) with hospitalization risk and excess expenses burden of unstable angina pectoris (UAP) patients for providing a reference to UAP prevention. MethodsMedical records of 11 334 UAP patients hospitalized from 2019 through 2021 were collected from 6 hospitals in Yichang city, Hubei province. Local data over the same period on daily ambient air pollutants and meteorological factors were also collected from five national automatic monitoring stations and municipal weather bureau. Time-stratified case-crossover design and conditional logistic regression model were adopted to analyze the association of each 10 μg/m3 change in ambient air PM2.5 and PM10 concentration with UAP hospitalization risk and excess economic burden. ResultsIn total, 11 334 UAP case days were matched to 38 540 control days. In single pollutant model analysis, a 10 μg/m3 increase in PM2.5 and PM10 was associated with the increased UAP hospitalization risk of 0.92% and 0.89% on lag day 0 (Lag0), 0.73% and 0.62% on Lag1, 1.00% and 0.92% over lag days 0 – 1 (Lag0 – 1), and 0.84% and 0.85% over Lag0 – 2, respectively. After adjusting for sulfur dioxide, nitrogen dioxide, carbon monoxide, ozone, temperature and relative humidity in multi-pollutant model analysis, PM2.5 was significantly associated with increased UAP hospitalization risk on days from Lag0 to Lag4 and over days from Lag0 – 1 to Lag0 – 5 and the highest increased risk was observed over Lag0 – 2 (excess risk [ER] = 1.86%, 95% confidence interval [95%CI]: 0.46% – 3.27%); PM10 showed a significant impact on UAP hospitalization risk on Lag0, Lag1, and over Lag0 – 1 and Lag0 – 2, and with the highest increased risk over Lag0 – 1 (ER = 1.19%, 95%CI: 0.23% – 2.16%). Further stratified analysis indicated that the significant association still existed for gender and seasonal subgroup patients. For males, PM2.5 and PM10 was associated with the highest increased risk over Lag0 – 1 (ER = 2.69%, 95%CI: 0.40% – 5.03%) and on Lag0 (ER = 1.59%, 95%CI: 0.47% – 2.72%). In warm season, PM2.5 and PM10 was associated with the highest increased risk over Lag0 – 2 (for PM2.5: ER = 2.69%, 95%CI: 0.40% – 5.03%; for PM10: ER = 1.59%, 95%CI: 0.47% – 2.72%). During 2019 – 2021 in Yichang city, the increments of ambient air PM2.5 and PM10 were associated with the increased UAP hospitalizations of 109 and 28 and excessive UAP-related economic burden of 1.554 and 0.373 million Chinese Yuan based on China's current secondary air quality control standards, respectively. Conclusion Short-term exposure to increased ambient air PM2.5 and PM10 can significantly increase hospitalization risk and excess expenditure of unstable angina pectoris patients in Yichang city.

Abstract The interplay between magnetism and electronic band topology enriches topological phases and has promising applications. However, the role of topology in magnetic fluctuations has been elusive. Here, we report evidence for topology stabilized magnetism above the magnetic transition temperature in magnetic Weyl semimetal candidate CeAlGe. Electrical transport, thermal transport, resonant elastic X-ray scattering, and dilatometry consistently indicate the presence of locally correlated magnetism within a narrow temperature window well above the thermodynamic magnetic transition temperature. The wavevector of this short-range order is consistent with the nesting condition of topological Weyl nodes, suggesting that it arises from the interaction between magnetic fluctuations and the emergent Weyl fermions. Effective field theory shows that this topology stabilized order is wavevector dependent and can be stabilized when the interband Weyl fermion scattering is dominant. Our work highlights the role of electronic band topology in stabilizing magnetic order even in the classically disordered regime.

To investigate the influence of the cubic crystal morphology on the thermal properties and sensitivity of 2,6-bis(picrylamino)-3,5-dinitropyridine (PYX), cubic PYX (CPYX) crystals were prepared using the antisolvent method. Scanning electron microscopy (SEM), laser particle size analysis, X-ray diffraction (XRD) and Fourier transform infrared spectroscopy (FT-IR) were used to characterize the morphology, particle size and structure of the prepared products. The thermal behavior, thermal decomposition kinetics, thermal safety parameters and thermal decomposition mechanism of CPYX were investigated by differential scanning calorimetry–thermogravimetry–mass spectrometry–Fourier transform infrared spectrometry (DSC-TG-MS-FT-IR) and in situ FT-IR experiments. Meanwhile, the mechanical sensitivity of CPYX was determined by means of the explosion probability method. The results showed that the product had a smooth cubic morphology and small crystal aspect ratio with an average particle size (d50) of 10.65 μm, but it had no distinct differences from the crystal structure of raw PYX (RPYX). The thermal decomposition peak temperature, the self-accelerating decomposition temperature and the critical temperature of the thermal explosion of CPYX increased by 7.2 °C, 6.1 °C and 10.4 °C, respectively, compared to RPYX. Similarly, the apparent activation energy increased by 15%. Besides these, the impact sensitivity and friction sensitivity of CPYX decreased by 36% and 20%, respectively, compared to RPYX. The decomposition process of CPYX contains two stages. The first stage involves the breakage of N-H bonds and -NO2 groups with the release of CO2, N2O, NO, HCN and H2O, followed by the thermal decomposition of the resulting intermediate and the release of CO2, N2O and HCN in the second stage.

Rabies virus (RABV) is a neurotropic virus that causes fatal neurological disease, raising serious public health issues and attracting extensive attention in society. To elucidate the molecular mechanism of RABV-induced neuronal damage, we used hematoxylin–eosin staining, transmission electron microscopy, transcriptomics analysis, and immune response factor testing to investigate RABV-infected neurons. We successfully isolated the neurons from murine brains. The specificity of the isolated neurons was identified by a monoclonal antibody, and the viability of the neurons was 83.53–95.0%. We confirmed that RABV infection induced serious damage to the neurons according to histochemistry and transmission electron microscope (TEM) scanning. In addition, the transcriptomics analysis suggested that multiple genes related to the pyroptosis pathway were significantly upregulated, including gasdermin D (Gsdmd), Nlrp3, caspase-1, and IL-1β, as well as the chemokine genes Ccl2, Ccl3, Ccl4, Ccl5, Ccl7, Ccl12, and Cxcl10. We next verified this finding in the brains of mice infected with the rRC-HL, GX074, and challenge virus standard strain-24 (CVS-24) strains of RABV. Importantly, we found that the expression level of the Gsdmd protein was significantly upregulated in the neurons infected with different RABV strains and ranged from 691.1 to 5764.96 pg/mL, while the basal level of mock-infected neurons was less than 100 pg/mL. Taken together, our findings suggest that Gsdmd-induced pyroptosis is involved in the neuron damage caused by RABV infection.

This paper delves into the realm of cryptographic analysis by employing mixed-integer linear programming (MILP), a powerful tool for automated cryptanalysis. Building on this foundation, we apply the division property method alongside MILP to conduct a comprehensive cryptanalysis of the IIoTBC (industrial Internet of Things block cipher) algorithm, a critical cipher in the security landscape of industrial IoT systems. Our investigation into IIoTBC System A has led to identifying a 14-round integral distinguisher, further extended to a 22-round key recovery. This significant finding underscores the cipher’s susceptibility to sophisticated cryptanalytic attacks and demonstrates the profound impact of combining the division property method with MILP in revealing hidden cipher weaknesses. In the case of IIoTBC System B, our innovative approach has uncovered a full-round distinguisher. We provide theoretical validation for this distinguisher and uncover a pivotal structural issue in the System B algorithm, specifically the non-diffusion of its third branch. This discovery sheds light on inherent security challenges within System B and points to areas for potential enhancement in its design. Our research, through its methodical examination and analysis of the IIoTBC algorithm, contributes substantially to the field of cryptographic security, especially concerning industrial IoT applications. By uncovering and analyzing the vulnerabilities within IIoTBC, we enhance the understanding of cipher robustness and pave the way for advancements in securing industrial IoT communications.

Machine learning (ML) techniques are extensively applied to practical maritime transportation issues. Due to the difficulty and high cost of collecting large volumes of data in the maritime industry, in many maritime studies, ML models are trained with small training datasets. The relative predictive performances of these trained ML models are then compared with each other and with the conventional model using the same test set. The ML model that performs the best out of the ML models and better than the conventional model on the test set is regarded as the most effective in terms of this prediction task. However, in scenarios with small datasets, this common process may lead to an unfair comparison between the ML and the conventional model. Therefore, we propose a novel process to fairly compare multiple ML models and the conventional model. We first select the best ML model in terms of predictive performance for the validation set. Then, we combine the training and the validation sets to retrain the best ML model and compare it with the conventional model on the same test set. Based on historical port state control (PSC) inspection data, we examine both the common process and the novel process in terms of their ability to fairly compare ML models and the conventional model. The results show that the novel process is more effective at fairly comparing the ML models with the conventional model on different test sets. Therefore, the novel process enables a fair assessment of ML models' ability to predict key performance indicators in the context of limited data availability in the maritime industry, such as predicting the ship fuel consumption and port traffic volume, thereby enhancing their reliability for real-world applications.