Analysis and prediction of central nervous system tumor burden in China during 1990-2030.

Central nervous system (CNS) tumors, due to their unique locations, pose a serious threat to human health and present challenges to modern medicine. These tumors exhibit notable epidemiological characteristics across various ethnicities, regions, and age groups. This study investigated the trend of disease burden of CNS tumors in China from 1990-2019 and predicted the incidence and death rate from 2020-2030. Employing data from the 2019 Global Burden of Disease (GBD) database, we utilized key indicators to scrutinize the disease burden associated with CNS tumors in China. The analysis employed the Joinpoint model to track the trend in disease burden, calculating both the annual percentage change (APC) and average annual percentage change (AAPC). Additionally, the Matlab software facilitated the creation of a gray model to forecast the incidence and death rate of CNS tumors in China spanning from 2020 to 2030." In 2019, the age-standardized incidence rate, prevalence rate, death rate, and disability-adjusted life years (DALYs) associated with CNS tumors in China were among the high level in the world. The standardized prevalence rate and DALYs of CNS tumors in China residents showed a stable fluctuation trend with age; however, age-standardized death and incidence rate demonstrated a generally upward trend with age. In China, the age-standardized prevalence and incidence rate of males were lower than those for female residents, while the age-standardized death rate and DALYs among males surpassed those of females. From 1990-2019, the age-standardized prevalence and incidence rate of CNS tumors in China exhibited an increasing trend. The age-standardized death rate and DALYs showed a contrasting trend. According to the gray model's prediction, incidence rate of CNS tumors would continue rising while the death rate is expected to decline in China from 2020-2023. The burden of CNS tumors in China has shown an upward trajectory, posing significant challenges to their treatment. It is necessary to pay attention to tertiary prevention, start from the perspective of high-risk groups and high-risk factors to reduce the burden of disease, and achieve "early detection, early diagnosis, and early treatment".

Neutrophil extracellular traps in bacterial infections and evasion strategies.

Neutrophils are innate immune cells that have a vital role in host defense systems. Neutrophil extracellular traps (NETs) are one of neutrophils' defense mechanisms against pathogens. NETs comprise an ejected lattice of chromatin associated with histones, granular proteins, and cytosolic proteins. They are thought to be an efficient strategy to capture and/or kill bacteria and received intensive research interest in the recent years. However, soon after NETs were identified, it was observed that certain bacteria were able to evade NET entrapment through many different mechanisms. Here, we outline the recent progress of NETs in bacterial infections and the strategies employed by bacteria to evade or withstand NETs. Identifying the molecules and mechanisms that modulate NET release will improve our understanding of the functions of NETs in infections and provide new avenues for the prevention and treatment of bacterial diseases.

Reduced coupling between global signal and cerebrospinal fluid inflow in patients with depressive disorder: A resting state functional MRI study.

BACKGROUND: Depressed patients often suffer from sleep disturbance, which has been recognized to be responsible for glymphatic dysfunction. The purpose of this study was to investigate the coupling strength of global blood­oxygen-level-dependent (gBOLD) signals and cerebrospinal fluid (CSF) inflow dynamics, which is a biomarker for glymphatic function, in depressed patients and to explore its potential relationship with sleep disturbance by using resting-state functional MRI. METHODS: A total of 138 depressed patients (112 females, age: 34.70 ± 13.11 years) and 84 healthy controls (29 females, age: 36.6 ± 11.75 years) participated in this study. The gBOLD-CSF coupling strength was calculated to evaluate glymphatic function. Sleep disturbance was evaluated using the insomnia items (item 4 for insomnia-early, item 5 for insomnia-middle, and item 6 for insomnia-late) of The 17-item Hamilton Depression Rating Scale for depressed patients, which was correlated with the gBOLD-CSF coupling strength. RESULTS: The depressed patients exhibited weaker gBOLD-CSF coupling relative to healthy controls (p = 0.022), possibly due to impairment of the glymphatic system. Moreover, the gBOLD-CSF coupling strength correlated with insomnia-middle (r = 0.097, p = 0.008) in depressed patients. Limitations This study is a cross-sectional study. CONCLUSION: Our findings shed light on the pathophysiology of depression, indicating that cerebral waste clearance system deficits are correlated with poor sleep quality in depressed patients.

The Dual Roles of Activating Transcription Factor 3 (ATF3) in Inflammation, Apoptosis, Ferroptosis, and Pathogen Infection Responses.

Transcription factors are pivotal regulators in the cellular life process. Activating transcription factor 3 (ATF3), a member of the ATF/CREB (cAMP response element-binding protein) family, plays a crucial role as cells respond to various stresses and damage. As a transcription factor, ATF3 significantly influences signal transduction regulation, orchestrating a variety of signaling pathways, including apoptosis, ferroptosis, and cellular differentiation. In addition, ATF3 serves as an essential link between inflammation, oxidative stress, and immune responses. This review summarizes the recent advances in research on ATF3 activation and its role in regulating inflammatory responses, cell apoptosis, and ferroptosis while exploring the dual functions of ATF3 in these processes. Additionally, this article discusses the role of ATF3 in diseases related to pathogenic microbial infections. Our review may be helpful to better understand the role of ATF3 in cellular responses and disease progression, thus promoting advancements in clinical treatments for inflammation and oxidative stress-related diseases.

Modulation Effects of the CEP128 Gene on Radiotherapy-Related Brain Injury: A Longitudinal Structural Study Using Multi-Parametric Brain MR Images.

BACKGROUND: The promoter variant rs17111237 in the CEP128 closely relates to radiotherapy (RT)-related brain necrosis in nasopharyngeal carcinoma (NPC) patients. PURPOSE: To explore RT-related dynamic alterations in brain morphology and their potential genetic mechanism, and to explore the modulatory effects of CEP128 genetic variants on RT-related brain morphological alterations in NPC patients. STUDY TYPE: Prospective, longitudinal. POPULATION: One hundred one patients with histopathologic ally-proven NPC (age 41.64 ± 9.63, 46 male), analyzed at baseline (pre-RT), 3-months post-RT and 6 months post-RT, and 19 sex-, age- and education-matched healthy controls. FIELD STRENGTH/SEQUENCE: 3D gradient echo brain volume (3D-BRAVO) and diffusion-weighted single-shot spin-echo echo-planar sequences at 3.0 T. ASSESSMENT: rs17111237 in CEP128 was detected by Sanger sequencing. Structural and diffusion images were processed with FreeSurfer and FSL. Morphometric similarity network (MSN) was constructed with nine cortical indices derived from structural and diffusion images. STATISTICAL TESTS: One-way ANOVA, chi-square test. Pearson's correlation analysis was conducted to measure the relationship between CEP128 gene-expression level in human brain and MSN alterations. Repeated analysis of variance performed to assess group differences in MSN and the modulatory effects of the CEP128 gene within patients. Significance level: P < 0.05, false-discovery rate correction. RESULTS: RT-related significant widespread MSN alterations were observed in the cortices of NPC patients. Notably, regional MSN alterations had a weak but significant negative correlation with the cortical pattern of CEP128 gene expression (r = -0.152). Furthermore, rs17111237 in the CEP128 had significant modulatory effects on the observed MSN alterations in NPC patients, with the modulatory effects being most obvious at 3 months post-RT. CONCLUSIONS: MSN has potential to serve as a sensitive biomarker to detect RT-related brain injury. Inter-brain regional and inter-patient variability of RT-related brain injuries may be attributed to the cortical expression of the CEP128 gene and the modulatory effects of the promoter variant rs17111237 in CEP128. EVIDENCE LEVEL: 2 TECHNICAL EFFICACY: Stage 2.

Comparison of Perioperative Safety of Carotid Artery Stenting and Endarterectomy in the Treatment of Carotid Artery Stenosis: A Meta-Analysis of Randomized Controlled Trials.

BACKGROUND: Current management guidelines for the treatment of carotid stenosis are controversial. We performed this meta-analysis to evaluate the perioperative safety of carotid artery stenting (CAS) and endarterectomy. METHODS: We systematically searched EMBASE, PubMed, Web of Science, and the Cochrane Library from inception to November 10, 2022, for randomized controlled trials that compared CAS with carotid endarterectomy (CEA) among patients with carotid stenosis. The analyzed outcomes mainly included stroke, death, myocardial infarction (MI), cranial nerve palsy, the cumulative incidence of mortality, stroke, or MI and the cumulative incidence of death or stroke in the perioperative periods. The risk ratio (RR) and 95% confidence interval (95% CI) were calculated and pooled. Subgroup analyses were based on whether patients were symptomatic or asymptomatic. We assessed the certainty of evidence using the Grading of Recommendations Assessment, Development and Evaluation framework. RESULTS: Seventeen randomized controlled trials with 12,277 participants (6514 and 5763 in the CAS and CEA groups, respectively) were included. Pooled analysis demonstrated that compared with CEA, CAS was associated with decreased risks of perioperative MI (RR = 0.47, 95% CI = 0.29∼0.77) and perioperative cranial nerve palsy (RR = 0.02, 95% CI = 0.01∼0.06) but higher risks of perioperative stroke (RR = 1.48, 95% CI = 1.18∼1.87) and cumulative incidence of death or stroke (RR = 1.52, 95% CI = 1.20∼1.93). CONCLUSIONS: The perioperative safety was equivalent between CAS and CEA. However, CEA may be preferred when considering both procedural safety and long-term efficacy in preventing recurrent stroke.

DNA methylation aging signatures of multiple metals exposure and their mediation effects in metal-associated mortality: Evidence from the Dongfeng-Tongji cohort study.

Humans were exposed to multiple metals, but the impact of metals on DNA methylation-age (DNAm-age), a well-recognized aging measure, remains inconclusive. This study included 2942 participants from the Dongfeng-Tongji cohort. We detected their plasma concentrations of 23 metals and determined their genome-wide DNA methylation using the Illumina Human-MethylationEPIC BeadChip. Five DNAm-age acceleration indexes (DAIs), including HannumAge-Accel, HorvathAge-Accel, PhenoAge-Accel, GrimAge-Accel (residual from regressing corresponding DNAm-age on chronological age) and DNAm-mortality score (DNAm-MS), were separately calculated. We found that each 1-unit increase in ln-transformed copper (Cu) was associated with a separate 1.02-, 0.83- and 0.07-unit increase in PhenoAge-Accel, GrimAge-Accel, and DNAm-MS (all FDR<0.05). Each 1-unit increase in ln-transformed nickel (Ni) was associated with a 0.34-year increase in PhenoAge-Accel, while each 1-unit increase in ln-transformed strontium (Sr) was associated with a 0.05-unit increase in DNAm-MS. The Cu, Ni and Sr showed joint positive effects on above three DAIs. PhenoAge-Accel, GrimAge-Accel, and DNAm-MS mediated a separate 6.5%, 12.3%, 6.0% of the positive association between Cu and all-cause mortality; GrimAge-Accel mediated 14.3% of the inverse association of selenium with all-cause mortality. Our findings revealed the effects of Cu, Ni, Sr and their co-exposure on accelerated aging and highlighted mediation roles of DNAm-age on metal-associated mortality.

1% Tapinarof cream for the treatment of psoriasis: a network meta-analysis of randomized placebo- and calcipotriol- controlled trials.

Tapinarof is an aromatic hydrocarbon receptor inhibitor for the treatment of adult psoriasis, and with the completion of Phase III clinical trials for this drug, it is important to understand its place among the medications used in the treatment of psoriasis for clinical application. Networks were constructed for 1% tapinarof cream with positive control (calcipotriol) and negative control (placebo). Network meta-analysis was performed using Preferred Reporting Items for Systematic Reviews and Meta-analyses (PISMA) 2015. Relevant randomized clinical trials were searched from PubMed, Cochrane Library, and National Knowledge Infrastructure (CNKI) as of February 2023. Data were analyzed using the gemtc package in R software (RStudio) to evaluate the efficacy and safety of 1% tapinarof cream in the treatment of psoriasis in adults. A total of 2408 patients were enrolled in 8 clinical studies of 1% tapinarof cream, and 6874 patients were enrolled in 14 clinial studies of calciptriol. 1% tapinarof cream was superior to placebo [OR: 8.3 (5.5, 13.0), 8.3 (5.9, 13.0), 7.3 (5.1, 11.0)] and calcipotriol in the treatment of psoriasis at 4, 8, and 12 weeks, and the incidence of adverse events was higher than that with placebo [OR: 3.3 (2.6, 4.3)] and calcipotriol, with no serious systemic adverse events. 1% tapinarof cream is a safe and effective treatment for psoriasis.

Comparative untargeted and targeted metabonomics reveal discriminations in metabolite profiles between Mycoplasma capricolum subsp. capripneumoniae and Mycoplasma capricolum subsp. capricolum.

Background: Mycoplasmas are among the smallest prokaryotic microbes that can grow and proliferate on non-living media. They have reduced genomes, which may be associated with a concomitant reduction in their metabolic capacity. Mycoplasma capricolum subsp. capripneumoniae (Mccp) and Mycoplasma capricolum subsp. capricolum (Mcc), both belong to the Mycoplasma mycoides cluster, are significant important pathogenic Mycoplasma species in veterinary research field. They share high degree of genome homology but Mcc grows markedly faster and has higher growth titer than Mccp. Methods: This study investigated the metabolites of these two pathogenic bacteria from the middle and late stages of the logarithmic growth phase through liquid chromatography-mass spectrometry-based metabolomics and targeted energy metabolomics. The multivariate analysis was conducted to identify significant differences between the two important Mycoplasma species. Results: A total of 173 metabolites were identified. Of them, 33 and 34 metabolites involved in purine and pyrimidine, pyruvate metabolism, and amino acid synthesis were found to significantly differ in the middle and late stages, respectively. The abundance of fructose 1,6-bisphosphate, ADP, and pyruvate was higher in Mcc than in Mccp during the whole logarithmic period. Lactate was upregulated in slow-growing Mccp. The pH buffering agent N-[2-hydroxyethyl]piperazine-N'-[2-ethanesulfonic acid] added to media effectively prevented pH reduction and increase bacterial viability and protein biomass. The multivariate analysis revealed that the two Mycoplasma species significantly differed in glucose metabolism, growth factor transport and metabolism, cholesterol utilization, and environmental regulation. Conclusion: The study data are beneficial for understanding the metabolomic characteristics of these two crucial Mycoplasma species and shedding more light on mycoplasma metabolism, and serve as a resource for the pathogenesis and development of related vaccines.

Connectome architecture modulates the gray matter atrophy in major depression disorder patients with diverse suicidal ideations.

Gray matter (GM) atrophy is well documented in patients with major depressive disorder (MDD), but its underlying mechanism remains unknown. This study aimed to examine the GM atrophy in MDD patients with diverse suicidal ideations (SIs) and to explore whether those alterations were driven by connections. GM volume was estimated in 163 patients with recurrent MDD (comprising 122 with SI [MDDSI] and 41 without SI [MDDNSI]) and 134 health controls (HCs). A two-sample t-test was used to identify GM volume abnormalities in MDD patients and their subgroups. Functional connectivity was computed between pairs of aberrant GM in both patients and HCs, which were further compared with the connectivity of random brain regions. A permutation test was performed to assess its significance. Propensity score matching (PSM) was further performed to validate the main results. Compared with HCs, the MDDNSI group exhibited GM atrophy in 24 regions, with the largest effect sizes found in the frontal and parietal lobes, while the MDDSI group exhibited more widespread GM atrophy involving 49 regions, with the largest effect sizes in the frontal lobe, parietal lobe, temporal lobe, and the limbic system. Furthermore, patients and HCs exhibited significantly increased functional connectivity between regions with GM atrophy compared with randomly selected regions (p < 0.05). PSM analysis presented similar results to the main analysis. MDD patients had diverse GM atrophy features according to their SI tendency. Moreover, connectome architecture modulates the GM atrophy in MDD patients, implying the possibility that connections drive these pathological changes.

Multiphase and multiparameter MRI-based radiomics for prediction of tumor response to neoadjuvant therapy in locally advanced rectal cancer.

BACKGROUND: To develop and validate radiomics models for prediction of tumor response to neoadjuvant therapy (NAT) in patients with locally advanced rectal cancer (LARC) using both pre-NAT and post-NAT multiparameter magnetic resonance imaging (mpMRI). METHODS: In this multicenter study, a total of 563 patients were included from two independent centers. 453 patients from center 1 were split into training and testing cohorts, the remaining 110 from center 2 served as an external validation cohort. Pre-NAT and post-NAT mpMRI was collected for feature extraction. The radiomics models were constructed using machine learning from a training cohort. The accuracy of the models was verified in a testing cohort and an independent external validation cohort. Model performance was evaluated using area under the curve (AUC), sensitivity, specificity, positive predictive value, and negative predictive value. RESULTS: The model constructed with pre-NAT mpMRI had favorable accuracy for prediction of non-response to NAT in the training cohort (AUC = 0.84), testing cohort (AUC = 0.81), and external validation cohort (AUC = 0.79). The model constructed with both pre-NAT and post-NAT mpMRI had powerful diagnostic value for pathologic complete response in the training cohort (AUC = 0.86), testing cohort (AUC = 0.87), and external validation cohort (AUC = 0.87). CONCLUSIONS: Models constructed with multiphase and multiparameter MRI were able to predict tumor response to NAT with high accuracy and robustness, which may assist in individualized management of LARC.

Revealing the role of double-layer microenvironments in pH-dependent oxygen reduction activity over metal-nitrogen-carbon catalysts.

A standing puzzle in electrochemistry is that why the metal-nitrogen-carbon catalysts generally exhibit dramatic activity drop for oxygen reduction when traversing from alkaline to acid. Here, taking FeCo-N6-C double-atom catalyst as a model system and combining the ab initio molecular dynamics simulation and in situ surface-enhanced infrared absorption spectroscopy, we show that it is the significantly distinct interfacial double-layer structures, rather than the energetics of multiple reaction steps, that cause the pH-dependent oxygen reduction activity on metal-nitrogen-carbon catalysts. Specifically, the greatly disparate charge densities on electrode surfaces render different orientations of interfacial water under alkaline and acid oxygen reduction conditions, thereby affecting the formation of hydrogen bonds between the surface oxygenated intermediates and the interfacial water molecules, eventually controlling the kinetics of the proton-coupled electron transfer steps. The present findings may open new and feasible avenues for the design of advanced metal-nitrogen-carbon catalysts for proton exchange membrane fuel cells.

Pretreatment MRI-Based Radiomics for Prediction of Rectal Cancer Outcome: A Discovery and Validation Study.

RATIONALE AND OBJECTIVES: Accurate prediction of local recurrence or distant metastasis is critical for developing individualized therapies for locally advanced rectal cancer (LARC) patients after standard therapy. This study aims to develop and validate a multiparameter MRI-based radiomics signature (RS) for prognostic prediction in LARC patients receiving neoadjuvant chemoradiotherapy (nCRT) and total mesorectal excision (TME) and to explore the ability of RS for personalized survival risk stratification. MATERIALS AND METHODS: In this multi-center study, 454 patients who received nCRT and TME and completed 3 years of follow-up participated. RS was constructed for prognostic prediction based on features extracted from pretreatment multiparameter MRI in a training cohort (TC; n = 298), which was tested in an internal validation cohort (IVC; n = 75) and further validated in an independent external validation cohort (EVC; n = 81). Furthermore, the ability of RS for personalized survival risk stratification was explored using the Kaplan-Meier survival curves. RESULTS: The RS model showed satisfactory accuracy for prognostic prediction with AUCs of 0.83, 0.81 and 0.82 in the TC, IVC and EVC, respectively. In addition, RS helped to refine risk stratification for LARC patients on the basis of significantly different 3-year disease-free survival rates, independent of their pathological stage, pre-surgery CEA, and even treatment modality. CONCLUSIONS: The proposed RS can be used not only to predict local recurrence or distant metastasis but also to serve as an effective postoperative survival risk stratification tool for clinicians to facilitate decision-making for LARC patients receiving standard treatment.

LppA is a novel plasminogen receptor of Mycoplasma bovis that contributes to adhesion by binding the host extracellular matrix and Annexin A2.

Mycoplasma bovis is responsible for various inflammatory diseases in cattle. The prevention and control of M. bovis are complicated by the absence of effective vaccines and the emergence of multidrug-resistant strains, resulting in substantial economic losses worldwide in the cattle industry. Lipoproteins, vital components of the Mycoplasmas cell membrane, are deemed potent antigens for eliciting immune responses in the host upon infection. However, the functions of lipoproteins in M. bovis remain underexplored due to their low sequence similarity with those of other bacteria and the scarcity of genetic manipulation tools for M. bovis. In this study, the lipoprotein LppA was identified in all examined M. bovis strains. Utilizing immunoelectron microscopy and Western blotting, it was observed that LppA localizes to the surface membrane. Recombinant LppA demonstrated dose-dependent adherence to the membrane of embryonic bovine lung (EBL) cells, and this adhesion was inhibited by anti-LppA serum. In vitro binding assays confirmed LppA's ability to associate with fibronectin, collagen IV, laminin, vitronectin, plasminogen, and tPA, thereby facilitating the conversion of plasminogen to plasmin. Moreover, LppA was found to bind and enhance the accumulation of Annexin A2 (ANXA2) on the cell membrane. Disrupting LppA in M. bovis significantly diminished the bacterium's capacity to adhere to EBL cells, underscoring LppA's function as a bacterial adhesin. In conclusion, LppA emerges as a novel adhesion protein that interacts with multiple host extracellular matrix proteins and ANXA2, playing a crucial role in M. bovis's adherence to host cells and dissemination. These insights substantially deepen our comprehension of the molecular pathogenesis of M. bovis.

Materials Strategies Tackling Interfacial Issues in Catalyst Layers of Proton Exchange Membrane Fuel Cells.

The most critical challenge for the large-scale commercialization of proton exchange membrane fuel cells (PEMFCs), one of the primary hydrogen energy technologies, is to achieve decent output performance with low usage of platinum (Pt). Currently, the performance of PEMFCs is largely limited by two issues at the catalyst/ionomer interface, specifically, the poisoning of active sites of Pt by sulfonate groups and the extremely sluggish local oxygen transport toward Pt. In the past few years, emerging strategies are derived to tackle these interface problems through materials optimization and innovation. This perspective summarizes the latest advances in this regard, and in the meantime unveils the molecule-level mechanisms behind the materials modulation of interfacial structures. This paper starts with a brief introduction of processes and structures of catalyst/ionomer interfaces, which is followed by a detailed review of progresses in key materials toward interface optimization, including catalysts, ionomers, and additives, with particular emphasis on the role of materials structure in regulating the intermolecular interactions. Finally, the challenges for the application of the established materials and research directions to broaden the material library are highlighted.

The decisive role of electrostatic interactions in transport mode and phase segregation of lithium ions in LiFePO4.

Understanding the mechanism of slow lithium ion (Li+) transport kinetics in LiFePO4 is not only practically important for high power density batteries but also fundamentally significant as a prototypical ion-coupled electron transfer process. Substantial evidence has shown that the slow ion transport kinetics originates from the coupled transfer between electrons and ions and the phase segregation of Li+. Combining a model Hamiltonian analysis and DFT calculations, we reveal that electrostatic interactions play a decisive role in coupled charge transfer and Li+ segregation. The obtained potential energy surfaces prove that ion-electron coupled transfer is the optimal reaction pathway due to electrostatic attractions between Li+ and e- (Fe2+), while prohibitively large energy barriers are required for separate electron tunneling or ion hopping to overcome the electrostatic energy between the Li+-e- (Fe2+) pair. The model reveals that Li+-Li+ repulsive interaction in the [010] transport channels together with Li+-e- (Fe2+)-Li+ attractive interaction along the [100] direction cause the phase segregation of Li+. It explains why the thermodynamically stable phase interface between Li-rich and Li-poor phases in LiFePO4 is perpendicular to [010] channels.

Electric Double Layer Effects in Electrocatalysis: Insights from Ab Initio Simulation and Hierarchical Continuum Modeling.

Structures of the electric double layer (EDL) at electrocatalytic interfaces, which are modulated by the material properties, the electrolyte characteristics (e.g., the pH, the types and concentrations of ions), and the electrode potential, play crucial roles in the reaction kinetics. Understanding the EDL effects in electrocatalysis has attracted substantial research interest in recent years. However, the intrinsic relationships between the specific EDL structures and electrocatalytic kinetics remain poorly understood, especially on the atomic scale. In this Perspective, we briefly review the recent advances in deciphering the EDL effects mainly in hydrogen and oxygen electrocatalysis through a multiscale approach, spanning from the atomistic scale simulated by ab initio methods to the macroscale by a hierarchical approach. We highlight the importance of resolving the local reaction environment, especially the local hydrogen bond network, in understanding EDL effects. Finally, some of the remaining challenges are outlined, and an outlook for future developments in these exciting frontiers is provided.