The rapid rise of cyberattacks and the gradual failure of traditional defense systems and approaches led to using artificial intelligence(AI)techniques(such as machine learning(ML)and deep learning(DL))to build more e...The rapid rise of cyberattacks and the gradual failure of traditional defense systems and approaches led to using artificial intelligence(AI)techniques(such as machine learning(ML)and deep learning(DL))to build more efficient and reliable intrusion detection systems(IDSs).However,the advent of larger IDS datasets has negatively impacted the performance and computational complexity of AI-based IDSs.Many researchers used data preprocessing techniques such as feature selection and normalization to overcome such issues.While most of these researchers reported the success of these preprocessing techniques on a shallow level,very few studies have been performed on their effects on a wider scale.Furthermore,the performance of an IDS model is subject to not only the utilized preprocessing techniques but also the dataset and the ML/DL algorithm used,which most of the existing studies give little emphasis on.Thus,this study provides an in-depth analysis of feature selection and normalization effects on IDS models built using three IDS datasets:NSL-KDD,UNSW-NB15,and CSE–CIC–IDS2018,and various AI algorithms.A wrapper-based approach,which tends to give superior performance,and min-max normalization methods were used for feature selection and normalization,respectively.Numerous IDS models were implemented using the full and feature-selected copies of the datasets with and without normalization.The models were evaluated using popular evaluation metrics in IDS modeling,intra-and inter-model comparisons were performed between models and with state-of-the-art works.Random forest(RF)models performed better on NSL-KDD and UNSW-NB15 datasets with accuracies of 99.86%and 96.01%,respectively,whereas artificial neural network(ANN)achieved the best accuracy of 95.43%on the CSE–CIC–IDS2018 dataset.The RF models also achieved an excellent performance compared to recent works.The results show that normalization and feature selection positively affect IDS modeling.Furthermore,while feature selection benefits simpler algorithms(such as RF),normalization is more useful for complex algorithms like ANNs and deep neural networks(DNNs),and algorithms such as Naive Bayes are unsuitable for IDS modeling.The study also found that the UNSW-NB15 and CSE–CIC–IDS2018 datasets are more complex and more suitable for building and evaluating modern-day IDS than the NSL-KDD dataset.Our findings suggest that prioritizing robust algorithms like RF,alongside complex models such as ANN and DNN,can significantly enhance IDS performance.These insights provide valuable guidance for managers to develop more effective security measures by focusing on high detection rates and low false alert rates.展开更多
Quantitative real-time reverse transcription-polymerase chain reaction （qRT-PCR） is widely used in studies of gene expression. In most of these studies, housekeeping genes are used as internal references without val...Quantitative real-time reverse transcription-polymerase chain reaction （qRT-PCR） is widely used in studies of gene expression. In most of these studies, housekeeping genes are used as internal references without validation. To identify appropriate reference genes for qRT-PCR in Pacific abalone Haliotis discus hannai, we examined the transcription stability of six housekeeping genes in abalone tissues in the presence and absence of bacterial infection. For this purpose, abalone were infected with the bacterial pathogen Fibrio anguillarum for 12 h and 48 h. The mRNA levels of the housekeeping genes in five tissues （digestive glands, foot muscle, gill, hemocyte, and mantle） were determined by qRT-PCR. The PCR data was subsequently analyzed with the geNorm and NormFinder algorithms. The results show that in the absence of bacterial infection, elongation factor-l-alpha and beta-actin were the most stably expressed genes in all tissues, and thus are suitable as cross-tissue type normalization factors. However, we did not identify any universal reference genes post infection because the most stable genes varied between tissue types. Furthermore, for most tissues, the optimal reference genes identified by both algorithms at 12 h and 48 h post-infection differed. These results indicate that bacterial infection induced significant changes in the expression of abalone housekeeping genes in a manner that is dependent on tissue type and duration of infection. As a result, different normalization factors must be used for different tissues at different infection points.展开更多
Under the National Innovation-Driven Development Strategy,establishing a scientifically sound evaluation system for normal university students’innovation and entrepreneurship capabilities serves as a crucial foundati...Under the National Innovation-Driven Development Strategy,establishing a scientifically sound evaluation system for normal university students’innovation and entrepreneurship capabilities serves as a crucial foundation for optimizing innovation education models and enhancing teacher candidates’comprehensive competencies.Based on existing indicator frameworks,we designed a questionnaire and applied exploratory factor analysis(EFA)to screen indicators,reduce dimensionality,and analyze weighting.This process identified key metrics for evaluating pedagogical students’innovation capacities,ultimately constructing a targeted assessment system for normal university students.The study provides theoretical support for cultivating teacher trainees’innovative capabilities while contributing to the national innovation strategy implementation.展开更多
Spinal cord injury represents a severe form of central nervous system trauma for which effective treatments remain limited.Microglia is the resident immune cells of the central nervous system,play a critical role in s...Spinal cord injury represents a severe form of central nervous system trauma for which effective treatments remain limited.Microglia is the resident immune cells of the central nervous system,play a critical role in spinal cord injury.Previous studies have shown that microglia can promote neuronal survival by phagocytosing dead cells and debris and by releasing neuroprotective and anti-inflammatory factors.However,excessive activation of microglia can lead to persistent inflammation and contribute to the formation of glial scars,which hinder axonal regeneration.Despite this,the precise role and mechanisms of microglia during the acute phase of spinal cord injury remain controversial and poorly understood.To elucidate the role of microglia in spinal cord injury,we employed the colony-stimulating factor 1 receptor inhibitor PLX5622 to deplete microglia.We observed that sustained depletion of microglia resulted in an expansion of the lesion area,downregulation of brain-derived neurotrophic factor,and impaired functional recovery after spinal cord injury.Next,we generated a transgenic mouse line with conditional overexpression of brain-derived neurotrophic factor specifically in microglia.We found that brain-derived neurotrophic factor overexpression in microglia increased angiogenesis and blood flow following spinal cord injury and facilitated the recovery of hindlimb motor function.Additionally,brain-derived neurotrophic factor overexpression in microglia reduced inflammation and neuronal apoptosis during the acute phase of spinal cord injury.Furthermore,through using specific transgenic mouse lines,TMEM119,and the colony-stimulating factor 1 receptor inhibitor PLX73086,we demonstrated that the neuroprotective effects were predominantly due to brain-derived neurotrophic factor overexpression in microglia rather than macrophages.In conclusion,our findings suggest the critical role of microglia in the formation of protective glial scars.Depleting microglia is detrimental to recovery of spinal cord injury,whereas targeting brain-derived neurotrophic factor overexpression in microglia represents a promising and novel therapeutic strategy to enhance motor function recovery in patients with spinal cord injury.展开更多
Fine particulatematter(PM_(2.5))samples were collected in two neighboring cities,Beijing and Baoding,China.High-concentration events of PM_(2.5) in which the average mass concentration exceeded 75μg/m^(3) were freque...Fine particulatematter(PM_(2.5))samples were collected in two neighboring cities,Beijing and Baoding,China.High-concentration events of PM_(2.5) in which the average mass concentration exceeded 75μg/m^(3) were frequently observed during the heating season.Dispersion Normalized Positive Matrix Factorization was applied for the source apportionment of PM_(2.5) as minimize the dilution effects of meteorology and better reflect the source strengths in these two cities.Secondary nitrate had the highest contribution for Beijing(37.3%),and residential heating/biomass burning was the largest for Baoding(27.1%).Secondary nitrate,mobile,biomass burning,district heating,oil combustion,aged sea salt sources showed significant differences between the heating and non-heating seasons in Beijing for same period(2019.01.10–2019.08.22)(Mann-Whitney Rank Sum Test P<0.05).In case of Baoding,soil,residential heating/biomass burning,incinerator,coal combustion,oil combustion sources showed significant differences.The results of Pearson correlation analysis for the common sources between the two cities showed that long-range transported sources and some sources with seasonal patterns such as oil combustion and soil had high correlation coefficients.Conditional Bivariate Probability Function(CBPF)was used to identify the inflow directions for the sources,and joint-PSCF(Potential Source Contribution Function)was performed to determine the common potential source areas for sources affecting both cities.These models facilitated a more precise verification of city-specific influences on PM_(2.5) sources.The results of this study will aid in prioritizing air pollution mitigation strategies during the heating season and strengthening air quality management to reduce the impact of downwind neighboring cities.展开更多
On-device Artificial Intelligence(AI)accelerators capable of not only inference but also training neural network models are in increasing demand in the industrial AI field,where frequent retraining is crucial due to f...On-device Artificial Intelligence(AI)accelerators capable of not only inference but also training neural network models are in increasing demand in the industrial AI field,where frequent retraining is crucial due to frequent production changes.Batch normalization(BN)is fundamental to training convolutional neural networks(CNNs),but its implementation in compact accelerator chips remains challenging due to computational complexity,particularly in calculating statistical parameters and gradients across mini-batches.Existing accelerator architectures either compromise the training accuracy of CNNs through approximations or require substantial computational resources,limiting their practical deployment.We present a hardware-optimized BN accelerator that maintains training accuracy while significantly reducing computational overhead through three novel techniques:(1)resourcesharing for efficient resource utilization across forward and backward passes,(2)interleaved buffering for reduced dynamic random-access memory(DRAM)access latencies,and(3)zero-skipping for minimal gradient computation.Implemented on a VCU118 Field Programmable Gate Array(FPGA)on 100 MHz and validated using You Only Look Once version 2-tiny(YOLOv2-tiny)on the PASCALVisualObjectClasses(VOC)dataset,our normalization accelerator achieves a 72%reduction in processing time and 83%lower power consumption compared to a 2.4 GHz Intel Central Processing Unit(CPU)software normalization implementation,while maintaining accuracy(0.51%mean Average Precision(mAP)drop at floating-point 32 bits(FP32),1.35%at brain floating-point 16 bits(bfloat16)).When integrated into a neural processing unit(NPU),the design demonstrates 63%and 97%performance improvements over AMD CPU and Reduced Instruction Set Computing-V(RISC-V)implementations,respectively.These results confirm that our proposed BN hardware design enables efficient,high-accuracy,and power-saving on-device training for modern CNNs.Our results demonstrate that efficient hardware implementation of standard batch normalization is achievable without sacrificing accuracy,enabling practical on-device CNN training with significantly reduced computational and power requirements.展开更多
Renormalization group analysis has been proposed to eliminate secular terms in perturbation solutions of differential equations and thus expand the domain of their validity.Here we extend the method to treat periodic ...Renormalization group analysis has been proposed to eliminate secular terms in perturbation solutions of differential equations and thus expand the domain of their validity.Here we extend the method to treat periodic orbits or limit cycles.Interesting normal forms could be derived through a generalization of the concept'resonance',which offers nontrivial analytic approximations.Compared with traditional techniques such as multi-scale methods,the current scheme proceeds in a very straightforward and simple way,delivering not only the period and the amplitude but also the transient path to limit cycles.The method is demonstrated with several examples including the Duffing oscillator,van der Pol equation and Lorenz equation.The obtained solutions match well with numerical results and with those derived by traditional analytic methods.展开更多
In recent decades,brain tumors have emerged as a serious neurological disorder that often leads to death.Hence,Brain Tumor Segmentation(BTS)is significant to enable the visualization,classification,and delineation of ...In recent decades,brain tumors have emerged as a serious neurological disorder that often leads to death.Hence,Brain Tumor Segmentation(BTS)is significant to enable the visualization,classification,and delineation of tumor regions in Magnetic Resonance Imaging(MRI).However,BTS remains a challenging task because of noise,non-uniform object texture,diverse image content and clustered objects.To address these challenges,a novel model is implemented in this research.The key objective of this research is to improve segmentation accuracy and generalization in BTS by incorporating Switchable Normalization into Faster R-CNN,which effectively captures the fine-grained tumor features to enhance segmentation precision.MRI images are initially acquired from three online datasets:Dataset 1—Brain Tumor Segmentation(BraTS)2018,Dataset 2—BraTS 2019,and Dataset 3—BraTS 2020.Subsequently,the Switchable Normalization-based Faster Regions with Convolutional Neural Networks(SNFRC)model is proposed for improved BTS in MRI images.In the proposed model,Switchable Normalization is integrated into the conventional architecture,enhancing generalization capability and reducing overfitting to unseen image data,which is essential due to the typically limited size of available datasets.The network depth is increased to obtain discriminative semantic features that improve segmentation performance.Specifically,Switchable Normalization captures the diverse feature representations from the brain images.The Faster R-CNN model develops end-to-end training and effective regional proposal generation,with an enhanced training stability using Switchable Normalization,to perform an effective segmentation in MRI images.From the experimental results,the proposed model attains segmentation accuracies of 99.41%,98.12%,and 96.71%on Datasets 1,2,and 3,respectively,outperforming conventional deep learning models used for BTS.展开更多
BACKGROUND Research has shown that several factors can influence postoperative abnormal liver function;however,most studies on this issue have focused specifically on hepatic and cardiac surgeries,leaving limited rese...BACKGROUND Research has shown that several factors can influence postoperative abnormal liver function;however,most studies on this issue have focused specifically on hepatic and cardiac surgeries,leaving limited research on contributing factors in other types of surgeries.AIM To identify the risk factors for early postoperative abnormal liver function in multiple surgery types and construct a risk prediction model.METHODS This retrospective cohort study involved 3720 surgical patients from 5 surgical departments at Guangdong Provincial Hospital of Traditional Chinese Medicine.Patients were divided into abnormal(n=108)and normal(n=3612)groups based on liver function post-surgery.Univariate analysis and LASSO regression screened variables,followed by logistic regression to identify risk factors.A prediction model was constructed based on the variables selected via logistic re-gression.The goodness-of-fit of the model was evaluated using the Hosm-er–Lemeshow test,while discriminatory ability was measured by the area under the receiver operating characteristic curve.Calibration curves were plotted to visualize the consistency between predicted probabilities and observed outcomes.RESULTS The key factors contributing to abnormal liver function after surgery include elevated aspartate aminotransferase and alanine aminotransferase levels and reduced platelet counts pre-surgery,as well as the sevoflurane use during the procedure,among others.CONCLUSION The above factors collectively represent notable risk factors for postoperative liver function injury,and the prediction model developed based on these factors demonstrates strong predictive efficacy.展开更多
BACKGROUND Ischemic stroke is one of the leading global causes of disability and death.Despite advances in modern medical technology that improve acute treatment and rehabilitation measures,post-stroke anxiety and dep...BACKGROUND Ischemic stroke is one of the leading global causes of disability and death.Despite advances in modern medical technology that improve acute treatment and rehabilitation measures,post-stroke anxiety and depression(PSD)do not receive sufficient attention.AIM To systematically evaluate risk factors and early identification markers for PSD for more precise screening and intervention strategies in clinical practice.METHODS This retrospective study analyzed clinical data from 112 patients with ischemic stroke admitted between January 2022 and December 2024.Based on assessments using the Hamilton Rating Scale for Anxiety(HAMA)and Hamilton Rating Scale for Depression(HAMD)at 2 weeks(±3 days)post-stroke,patients were classified into the PSD group(HAMA≥7 and/or HAMD≥7)and the non-PSD group(HAMA<7 and HAMD<7).Observation indicators included psychological assessment,demographic and clinical characteristics,stroke-related clinical indicators,neuroimaging assessments,and laboratory biomarkers.Multivariate logistic regression analysis was used to identify independent risk factors for PSD,and receiver operating characteristic curve analysis was used to evaluate the diagnostic value of potential biomarkers.RESULTS Of the 112 patients,46(41.1%)were diagnosed with PSD.Multivariate analysis identified five independent risk factors:Female gender[Odds ratio(OR)=2.32,95%confidence interval(CI):1.56-3.45],history of mental disorders prior to stroke(OR=3.17,95%CI:1.89-5.32),infarct location in the frontal lobe or limbic system(OR=2.86,95%CI:1.73-4.71),stroke severity with National Institutes of Health Stroke Scale≥8 at admission(OR=2.54,95%CI:1.62-3.99),and low social support(Social Support Rating Scale<35,OR=2.18,95%CI:1.42-3.36).Subgroup analysis showed that depression patients more commonly had left hemisphere lesions(68.4%vs 45.2%),while anxiety patients more frequently presented with right hemisphere lesions(59.5%vs 39.5%).The PSD group exhibited larger infarct volumes(8.7 cm^(3) vs 5.3 cm^(3)),more severe white matter hyperintensities,and more pronounced frontal lobe atrophy.Analysis of inflammatory markers showed significantly elevated levels of interleukin-6(7.8 pg/mL vs 4.5 pg/mL)and tumor necrosis factor-alpha(15.6 pg/mL vs 9.8 pg/mL)in the PSD group,while hypothalamicpituitary-adrenal axis function assessment revealed higher cortisol levels(386.5±92.3 nmol/L vs 328.7±75.6 nmol/L)and flattened diurnal rhythm in the PSD group.CONCLUSION PSD is a complex neuropsychiatric consequence of stroke involving disruption of the frontal-limbic circuitry,neuroinflammatory responses,and dysfunction of the hypothalamic-pituitary-adrenal axis.展开更多
Strokes include both ischemic stroke,which is mediated by a blockade or reduction in the blood supply to the brain,and hemorrhagic stroke,which comprises intracerebral hemorrhage and subarachnoid hemorrhage and is cha...Strokes include both ischemic stroke,which is mediated by a blockade or reduction in the blood supply to the brain,and hemorrhagic stroke,which comprises intracerebral hemorrhage and subarachnoid hemorrhage and is characterized by bleeding within the brain.Stroke is a lifethreatening cerebrovascular condition characterized by intricate pathophysiological mechanisms,including oxidative stress,inflammation,mitochondrial dysfunction,and neuronal injury.Critical transcription factors,such as nuclear factor erythroid 2-related factor 2 and nuclear factor kappa B,play central roles in the progression of stroke.Nuclear factor erythroid 2-related factor 2 is sensitive to changes in the cellular redox status and is crucial in protecting cells against oxidative damage,inflammatory responses,and cytotoxic agents.It plays a significant role in post-stroke neuroprotection and repair by influencing mitochondrial function,endoplasmic reticulum stress,and lysosomal activity and regulating metabolic pathways and cytokine expression.Conversely,nuclear factor-kappa B is closely associated with mitochondrial dysfunction,the generation of reactive oxygen species,oxidative stress exacerbation,and inflammation.Nuclear factor-kappa B contributes to neuronal injury,apoptosis,and immune responses following stroke by modulating cell adhesion molecules and inflammatory mediators.The interplay between these pathways,potentially involving crosstalk among various organelles,significantly influences stroke pathophysiology.Advancements in single-cell sequencing and spatial transcriptomics have greatly improved our understanding of stroke pathogenesis and offer new opportunities for the development of targeted,individualized,cell typespecific treatments.In this review,we discuss the mechanisms underlying the involvement of nuclear factor erythroid 2-related factor 2 and nuclear factor-kappa B in both ischemic and hemorrhagic stroke,with an emphasis on their roles in oxidative stress,inflammation,and neuroprotection.展开更多
Let G be a finite group and H a subgroup of G.The normal index of H in G is defined as the order of K/H_(G),where K is a normal supplement of H in G such that|K|is minimal and H_(G)≤K■G.Let p be a prime which divide...Let G be a finite group and H a subgroup of G.The normal index of H in G is defined as the order of K/H_(G),where K is a normal supplement of H in G such that|K|is minimal and H_(G)≤K■G.Let p be a prime which divides the order of a group G.In this paper,some characterizations of G being p-solvable or p-supersolvable were obtained by analyzing the normal index of certain subgroups of G.These results can be viewed as local version of recent results in the literature.展开更多
Nerve trauma commonly results in chronic neuropathic pain. This is by triggering the release of proinflammatory mediators from local and invading cells that induce inflammation and nociceptive neuron hyperexcitability...Nerve trauma commonly results in chronic neuropathic pain. This is by triggering the release of proinflammatory mediators from local and invading cells that induce inflammation and nociceptive neuron hyperexcitability. Even without apparent inflammation, injury sites are associated with increased inflammatory markers. This review focuses on how it might be possible to reduce neuropathic pain by reducing inflammation. Physiologically, pain is resolved by a combination of the out-migration of pro-inflammatory cells from the injury site, the down-regulation of the genes underlying the inflammation, up-regulating genes for anti-inflammatory mediators, and reducing nociceptive neuron hyperexcitability. While various techniques reduce chronic neuropathic pain, the best are effective on < 50% of patients, no technique reliably or permanently eliminates neuropathic pain. This is because most techniques are predominantly aimed at reducing pain, not inflammation. In addition, while single factors reduce pain, increasing evidence indicates significant and longer-lasting pain relief requires multiple factors acting simultaneously. Therefore, it is not surprising that extensive data indicate that the application of platelet-rich plasma provides more significant and longer-lasting pain suppression than other techniques, although its analgesia is neither complete nor permanent. However, several case reports indicate that platelet-rich plasma can induce permanent neuropathic pain elimination when the platelet concentration is significantly increased and is applied to longer nerve lengths. This review examines the primary triggers of the development and maintenance of neuropathic pain and techniques that reduce chronic neuropathic pain. The application of plateletrich plasma holds great promise for providing complete and permanent chronic neuropathic pain elimination.展开更多
BACKGROUND Post-transplant tertiary hyperparathyroidism(PT-tHPT)is a well-recognized complication following kidney transplantation,characterized by persistent excessive secretion of parathyroid hormone(PTH)despite imp...BACKGROUND Post-transplant tertiary hyperparathyroidism(PT-tHPT)is a well-recognized complication following kidney transplantation,characterized by persistent excessive secretion of parathyroid hormone(PTH)despite improved renal function.It is potentially associated with an increased risk of cardiovascular events,renal osteodystrophy,pathologic fractures,graft loss,and mortality.AIM To evaluate the incidence,risk factors,and outcomes of PT-tHPT amongst kidney transplant recipients.METHODS A total of 887 transplant recipients who underwent transplantation between 2000 and 2020 were evaluated.Univariable and multivariable logistic regression was performed to determine the predictors of tertiary hyperparathyroidism.Graft and recipient outcomes were assessed using multivariable Cox regression.A separate multivariable Cox regression was performed to determine the effect of treatment strategies on outcomes.RESULTS PT-tHPT,defined as elevated PTH(>65 ng/L)and persistent hypercalcemia(>2.60 mmol/L),was diagnosed in 14%of recipients.Risk factors for PT-tHPT included older age[odds ratio(OR)=1.36,P<0.001],Asian ethnicity(OR=0.33,P=0.006),total ischemia time(OR=1.03,P=0.048 per hour),pre-transplant serum calcium(OR=1.38,P<0.001)per decile increase,pre-transplant PTH level(OR=1.31,P<0.001)per decile increase,longer dialysis duration(OR=1.12,P=0.002)per year,history of acute rejection(OR=2.37,P=0.012),and slope of estimated glomerular filtration rate change(OR=0.91,P=0.001).There were a 3.4-fold higher risk of death-censored graft loss and a 1.9-fold greater risk of recipient death with PT-tHPT.The three treatment strategies of conservative management,calcimimetic and parathyroidectomy did not significantly change the graft or patient outcome.CONCLUSION Pretransplant elevated calcium and PTH levels,older age and dialysis duration are associated with PT-tHPT.While PT-tHPT significantly affects graft and recipient survival,the treatment strategies did not affect survival.展开更多
BACKGROUND Aseptic loosening remains the leading cause of revision in primary total hip arthroplasty(pTHA).However,the literature demonstrates significant variability regarding the relative contributions of different ...BACKGROUND Aseptic loosening remains the leading cause of revision in primary total hip arthroplasty(pTHA).However,the literature demonstrates significant variability regarding the relative contributions of different factors.AIM To investigate the key determinants of aseptic loosening,we performed a systematic review and meta-analysis.METHODS A comprehensive search of PubMed,Web of Science,EMBASE,and the Cochrane Library was conducted,encompassing studies from database inception to January 1,2025.Meta-analyses were performed to evaluate factors associated with aseptic loosening following pTHA.Inclusion and exclusion criteria were systematically applied at each stage to ensure methodological transparency and reproducibility.Study quality was assessed using standardized categories.Pooled odds ratio(OR)with corresponding 95%confidence interval were calculated with random-or fixed-effects models to generate reliability estimates,and study heterogeneity was visualized using forest plots.Ten factors,categorized into patient-,surgeon-,and device-related domains,were reviewed and meta-analyzed.Funnel plot analysis demonstrated a relatively symmetrical distribution,suggesting minimal publication bias.RESULTS A meta-analysis of 20 studies(520789 participants)found a pooled prevalence of 1.96%.Significant risk factors for aseptic loosening after pTHA included elevated body mass index(OR=1.116,P<0.001),higher Charlson comorbidity index(OR=1.378,P<0.001),prosthesis-related factors(OR=1.497,P<0.001),and adverse lifestyles(OR=2.198,P=0.037).Protective factors were non-white race(OR=0.445,P<0.001)and favorable genetics(OR=0.723,P<0.001).Male sex increased risk(OR=1.232,P=0.016),while age and anatomy were not significant.Surgical expertise showed a slight protective effect(OR=1.048,P<0.001).A comprehensive understanding of the modifiable and non-modifiable factors contributing to aseptic loosening after pTHA requires consideration of patient-related factors,surgical expertise,and prosthesis characteristics.CONCLUSION The identification of these factors is critical for risk mitigation.High-risk patients should receive targeted counseling regarding individualized profiles.Further studies are warranted to establish clearer causal relationships and identify additional contributing factors.展开更多
BACKGROUND Esophageal cancer is highly malignant and frequently metastasizes to bones.Concomitant depression worsens prognosis;however,its incidence and determinants in this specific population remain poorly defined.A...BACKGROUND Esophageal cancer is highly malignant and frequently metastasizes to bones.Concomitant depression worsens prognosis;however,its incidence and determinants in this specific population remain poorly defined.AIM To determine the incidence of depression and its independent risk factors in patients with esophageal cancer and bone metastasis.METHODS A total of 100 consecutive eligible patients admitted between March 2022 and March 2025 were recruited.Depression was assessed with the Beck Depression Inventory-II;scores>4 defined the depression group(n=42)and scores≤4 the non-depression group(n=58).Demographic,clinical,and laboratory variables were compared between the groups.Multivariate logistic regression was used to identify independent risk factors.RESULTS Depression prevalence was 42.0%(42/100).Univariate analysis demonstrated significant differences in monthly per-capita household income,education level,social support,sleep disorders,and serum high-sensitivity C-reactive protein(all P<0.05);no differences were observed in sex,age,tumor characteristics,or other laboratory indices(all P>0.05).Multivariable analysis revealed the following independent risk factors for depression:Low income[odds ratio(OR)=2.66,95%confidence interval(CI):1.17-6.03],low education(OR=2.46,95%CI:1.08-5.61),low social support(OR=5.10,95%CI:1.81-14.39),sleep disorders(OR=2.79,95%CI:1.23-6.35),and elevated high-sensitivity C-reactive protein(OR=1.31 per unit increase,95%CI:1.18-1.46).CONCLUSION Depression is common among patients with esophageal cancer and bone metastasis.Low socioeconomic status,limited education,insufficient social support,sleep disturbances,and systemic inflammation were independent predictors.Interventions that address these modifiable factors may reduce depression risk in this population.展开更多
BACKGROUND Lumbar interbody fusion(LIF)is the primary treatment for lumbar degenerative diseases.Elderly patients are prone to anxiety and depression after undergoing surgery,which affects their postoperative recovery...BACKGROUND Lumbar interbody fusion(LIF)is the primary treatment for lumbar degenerative diseases.Elderly patients are prone to anxiety and depression after undergoing surgery,which affects their postoperative recovery speed and quality of life.Effective prevention of anxiety and depression in elderly patients has become an urgent problem.AIM To investigate the trajectory of anxiety and depression levels in elderly patients after LIF,and the influencing factors.METHODS Random sampling was used to select 239 elderly patients who underwent LIF from January 2020 to December 2024 in Shenzhen Pingle Orthopedic Hospital.General information and surgery-related indices were recorded,and participants completed measures of psychological status,lumbar spine dysfunction,and quality of life.A latent class growth model was used to analyze the post-LIF trajectory of anxiety and depression levels,and unordered multi-categorical logistic regression was used to analyze the influencing factors.RESULTS Three trajectories of change in anxiety level were identified:Increasing anxiety(n=26,10.88%),decreasing anxiety(n=27,11.30%),and stable anxiety(n=186,77.82%).Likewise,three trajectories of change in depression level were identified:Increasing depression(n=30,12.55%),decreasing depression(n=26,10.88%),and stable depression(n=183,76.57%).Regression analysis showed that having no partner,female sex,elevated Oswestry dysfunction index(ODI)scores,and reduced 36-Item Short Form Health Survey scores all contributed to increased anxiety levels,whereas female sex,postoperative opioid use,and elevated ODI scores all contributed to increased depression levels.CONCLUSION During clinical observation,combining factors to predict anxiety and depression in post-LIF elderly patients enables timely intervention,quickens recovery,and enhances quality of life.展开更多
BACKGROUND Ulcerative colitis(UC)is a chronic and treatment-resistant disorder requiring potent therapeutics that are effective and safe.Cedrol(CE)is a bioactive natural product present in many traditional Chinese med...BACKGROUND Ulcerative colitis(UC)is a chronic and treatment-resistant disorder requiring potent therapeutics that are effective and safe.Cedrol(CE)is a bioactive natural product present in many traditional Chinese medicines.It is known for its suppression of inflammation and mitigation of oxidative stress.Its therapeutic efficacy and mechanistic underpinnings in UC remain uncharacterized.AIM To investigate the therapeutic potential and mechanisms of CE in UC.METHODS The anti-inflammatory activity and intestinal barrier-repairing effects of CE were assessed in a dextran sulfate sodium-induced murine colitis model.Network pharmacology was employed to predict potential targets and pathways.Then molecular docking and dynamics simulations were utilized to confirm a stable interaction between CE and the toll-like receptor 4(TLR4)/myeloid differentiation factor 2(MD2)complex.The anti-inflammatory mechanisms were further verified using in vitro assays.Additionally,the gut microbiota composition was analyzed via 16S rRNA gene sequencing.RESULTS CE significantly alleviated colitis symptoms,mitigated histopathological damage,and suppressed inflammation.Moreover,CE restored intestinal barrier integrity by enhancing mucus secretion and upregulating tight junction proteins(zonula occludens 1,occludin,claudin-1).Mechanistically,CE stably bound to MD2,inhibiting lipopolysaccharide-induced TLR4 signaling in RAW264.7 cells.This led to suppression of the downstream mitogen-activated protein kinase and nuclear factor kappa B signaling pathways,downregulating the expression of tumor necrosis factor-alpha,interleukin-1β,and interleukin-6.Gut microbiota analysis revealed that CE reversed dextran sulfate sodium-induced dysbiosis with significant enrichment of butyrogenic Christensenella minuta.CONCLUSION CE acted on MD2 to suppress proinflammatory cascades,promoting mucosal barrier reconstitution and microbiota remodeling and supporting its therapeutic use in UC.展开更多
BACKGROUND Early renal artery thrombosis after kidney transplantation is rare but often leads to graft loss.Prompt diagnosis and intervention are essential,particularly in patients with inherited thrombophilias such a...BACKGROUND Early renal artery thrombosis after kidney transplantation is rare but often leads to graft loss.Prompt diagnosis and intervention are essential,particularly in patients with inherited thrombophilias such as factor V Leiden(FVL)mutation.CASE SUMMARY A kidney transplant recipient with FVL mutation developed an acute transplant renal artery thrombosis.The immediate post-operative Doppler ultrasonography revealed thrombosis of the main and inferior polar renal arteries.Emergent thrombectomy and separate arterial re-anastomoses were performed after cold perfusion with heparinized saline and vasodilator solution.Reperfusion was successful with immediate urine output and gradual improvement in renal function.The patient was discharged on direct oral anticoagulation therapy.CONCLUSION Early detection and surgical intervention can preserve graft function in posttransplant renal artery thrombosis even in patients at high risk.展开更多
The aging process is an inexorable fact throughout our lives and is considered a major factor in develo ping neurological dysfunctions associated with cognitive,emotional,and motor impairments.Aging-associated neurode...The aging process is an inexorable fact throughout our lives and is considered a major factor in develo ping neurological dysfunctions associated with cognitive,emotional,and motor impairments.Aging-associated neurodegenerative diseases are characterized by the progressive loss of neuronal structure and function.展开更多
文摘The rapid rise of cyberattacks and the gradual failure of traditional defense systems and approaches led to using artificial intelligence(AI)techniques(such as machine learning(ML)and deep learning(DL))to build more efficient and reliable intrusion detection systems(IDSs).However,the advent of larger IDS datasets has negatively impacted the performance and computational complexity of AI-based IDSs.Many researchers used data preprocessing techniques such as feature selection and normalization to overcome such issues.While most of these researchers reported the success of these preprocessing techniques on a shallow level,very few studies have been performed on their effects on a wider scale.Furthermore,the performance of an IDS model is subject to not only the utilized preprocessing techniques but also the dataset and the ML/DL algorithm used,which most of the existing studies give little emphasis on.Thus,this study provides an in-depth analysis of feature selection and normalization effects on IDS models built using three IDS datasets:NSL-KDD,UNSW-NB15,and CSE–CIC–IDS2018,and various AI algorithms.A wrapper-based approach,which tends to give superior performance,and min-max normalization methods were used for feature selection and normalization,respectively.Numerous IDS models were implemented using the full and feature-selected copies of the datasets with and without normalization.The models were evaluated using popular evaluation metrics in IDS modeling,intra-and inter-model comparisons were performed between models and with state-of-the-art works.Random forest(RF)models performed better on NSL-KDD and UNSW-NB15 datasets with accuracies of 99.86%and 96.01%,respectively,whereas artificial neural network(ANN)achieved the best accuracy of 95.43%on the CSE–CIC–IDS2018 dataset.The RF models also achieved an excellent performance compared to recent works.The results show that normalization and feature selection positively affect IDS modeling.Furthermore,while feature selection benefits simpler algorithms(such as RF),normalization is more useful for complex algorithms like ANNs and deep neural networks(DNNs),and algorithms such as Naive Bayes are unsuitable for IDS modeling.The study also found that the UNSW-NB15 and CSE–CIC–IDS2018 datasets are more complex and more suitable for building and evaluating modern-day IDS than the NSL-KDD dataset.Our findings suggest that prioritizing robust algorithms like RF,alongside complex models such as ANN and DNN,can significantly enhance IDS performance.These insights provide valuable guidance for managers to develop more effective security measures by focusing on high detection rates and low false alert rates.
基金Supported by the Knowledge Innovation Program of Chinese Academy of Sciences(No.KSCX2-EW-G-12B)the Knowledge Innovation Program of the Chinese Academy of Sciences(No.KZCX2-EW-Q213)the National High Technology Research and Development Program of China (863 Program)(No.2012AA10A412)
文摘Quantitative real-time reverse transcription-polymerase chain reaction （qRT-PCR） is widely used in studies of gene expression. In most of these studies, housekeeping genes are used as internal references without validation. To identify appropriate reference genes for qRT-PCR in Pacific abalone Haliotis discus hannai, we examined the transcription stability of six housekeeping genes in abalone tissues in the presence and absence of bacterial infection. For this purpose, abalone were infected with the bacterial pathogen Fibrio anguillarum for 12 h and 48 h. The mRNA levels of the housekeeping genes in five tissues （digestive glands, foot muscle, gill, hemocyte, and mantle） were determined by qRT-PCR. The PCR data was subsequently analyzed with the geNorm and NormFinder algorithms. The results show that in the absence of bacterial infection, elongation factor-l-alpha and beta-actin were the most stably expressed genes in all tissues, and thus are suitable as cross-tissue type normalization factors. However, we did not identify any universal reference genes post infection because the most stable genes varied between tissue types. Furthermore, for most tissues, the optimal reference genes identified by both algorithms at 12 h and 48 h post-infection differed. These results indicate that bacterial infection induced significant changes in the expression of abalone housekeeping genes in a manner that is dependent on tissue type and duration of infection. As a result, different normalization factors must be used for different tissues at different infection points.
基金Mid-term Results of the 2024 Langfang Normal University Special Teaching Reform Project on Innovation and Entrepreneurship Education Reform,“Research on the Evaluation System of Innovation and Entrepreneurship Ability for Normal University Students Based on Big Data Application-A Case Study of Langfang Normal University”(Project No.:CXJG2024-06)。
文摘Under the National Innovation-Driven Development Strategy,establishing a scientifically sound evaluation system for normal university students’innovation and entrepreneurship capabilities serves as a crucial foundation for optimizing innovation education models and enhancing teacher candidates’comprehensive competencies.Based on existing indicator frameworks,we designed a questionnaire and applied exploratory factor analysis(EFA)to screen indicators,reduce dimensionality,and analyze weighting.This process identified key metrics for evaluating pedagogical students’innovation capacities,ultimately constructing a targeted assessment system for normal university students.The study provides theoretical support for cultivating teacher trainees’innovative capabilities while contributing to the national innovation strategy implementation.
基金supported by the National Natural Science Foundation of China,Nos.82072165 and 82272256(both to XM)the Key Project of Xiangyang Central Hospital,No.2023YZ03(to RM)。
文摘Spinal cord injury represents a severe form of central nervous system trauma for which effective treatments remain limited.Microglia is the resident immune cells of the central nervous system,play a critical role in spinal cord injury.Previous studies have shown that microglia can promote neuronal survival by phagocytosing dead cells and debris and by releasing neuroprotective and anti-inflammatory factors.However,excessive activation of microglia can lead to persistent inflammation and contribute to the formation of glial scars,which hinder axonal regeneration.Despite this,the precise role and mechanisms of microglia during the acute phase of spinal cord injury remain controversial and poorly understood.To elucidate the role of microglia in spinal cord injury,we employed the colony-stimulating factor 1 receptor inhibitor PLX5622 to deplete microglia.We observed that sustained depletion of microglia resulted in an expansion of the lesion area,downregulation of brain-derived neurotrophic factor,and impaired functional recovery after spinal cord injury.Next,we generated a transgenic mouse line with conditional overexpression of brain-derived neurotrophic factor specifically in microglia.We found that brain-derived neurotrophic factor overexpression in microglia increased angiogenesis and blood flow following spinal cord injury and facilitated the recovery of hindlimb motor function.Additionally,brain-derived neurotrophic factor overexpression in microglia reduced inflammation and neuronal apoptosis during the acute phase of spinal cord injury.Furthermore,through using specific transgenic mouse lines,TMEM119,and the colony-stimulating factor 1 receptor inhibitor PLX73086,we demonstrated that the neuroprotective effects were predominantly due to brain-derived neurotrophic factor overexpression in microglia rather than macrophages.In conclusion,our findings suggest the critical role of microglia in the formation of protective glial scars.Depleting microglia is detrimental to recovery of spinal cord injury,whereas targeting brain-derived neurotrophic factor overexpression in microglia represents a promising and novel therapeutic strategy to enhance motor function recovery in patients with spinal cord injury.
基金supported by the National Institute of Environmental Research(NIER)funded by the Ministry of Environment(No.NIER-2019-04-02-039)supported by Particulate Matter Management Specialized Graduate Program through the Korea Environmental Industry&Technology Institute(KEITI)funded by the Ministry of Environment(MOE).
文摘Fine particulatematter(PM_(2.5))samples were collected in two neighboring cities,Beijing and Baoding,China.High-concentration events of PM_(2.5) in which the average mass concentration exceeded 75μg/m^(3) were frequently observed during the heating season.Dispersion Normalized Positive Matrix Factorization was applied for the source apportionment of PM_(2.5) as minimize the dilution effects of meteorology and better reflect the source strengths in these two cities.Secondary nitrate had the highest contribution for Beijing(37.3%),and residential heating/biomass burning was the largest for Baoding(27.1%).Secondary nitrate,mobile,biomass burning,district heating,oil combustion,aged sea salt sources showed significant differences between the heating and non-heating seasons in Beijing for same period(2019.01.10–2019.08.22)(Mann-Whitney Rank Sum Test P<0.05).In case of Baoding,soil,residential heating/biomass burning,incinerator,coal combustion,oil combustion sources showed significant differences.The results of Pearson correlation analysis for the common sources between the two cities showed that long-range transported sources and some sources with seasonal patterns such as oil combustion and soil had high correlation coefficients.Conditional Bivariate Probability Function(CBPF)was used to identify the inflow directions for the sources,and joint-PSCF(Potential Source Contribution Function)was performed to determine the common potential source areas for sources affecting both cities.These models facilitated a more precise verification of city-specific influences on PM_(2.5) sources.The results of this study will aid in prioritizing air pollution mitigation strategies during the heating season and strengthening air quality management to reduce the impact of downwind neighboring cities.
基金supported by the National Research Foundation of Korea(NRF)grant for RLRC funded by the Korea government(MSIT)(No.2022R1A5A8026986,RLRC)supported by Institute of Information&Communications Technology Planning&Evaluation(IITP)grant funded by the Korea government(MSIT)(No.2020-0-01304,Development of Self-Learnable Mobile Recursive Neural Network Processor Technology)+3 种基金supported by the MSIT(Ministry of Science and ICT),Republic of Korea,under the Grand Information Technology Research Center support program(IITP-2024-2020-0-01462,Grand-ICT)supervised by the IITP(Institute for Information&Communications Technology Planning&Evaluation)supported by the Korea Technology and Information Promotion Agency for SMEs(TIPA)supported by the Korean government(Ministry of SMEs and Startups)’s Smart Manufacturing Innovation R&D(RS-2024-00434259).
文摘On-device Artificial Intelligence(AI)accelerators capable of not only inference but also training neural network models are in increasing demand in the industrial AI field,where frequent retraining is crucial due to frequent production changes.Batch normalization(BN)is fundamental to training convolutional neural networks(CNNs),but its implementation in compact accelerator chips remains challenging due to computational complexity,particularly in calculating statistical parameters and gradients across mini-batches.Existing accelerator architectures either compromise the training accuracy of CNNs through approximations or require substantial computational resources,limiting their practical deployment.We present a hardware-optimized BN accelerator that maintains training accuracy while significantly reducing computational overhead through three novel techniques:(1)resourcesharing for efficient resource utilization across forward and backward passes,(2)interleaved buffering for reduced dynamic random-access memory(DRAM)access latencies,and(3)zero-skipping for minimal gradient computation.Implemented on a VCU118 Field Programmable Gate Array(FPGA)on 100 MHz and validated using You Only Look Once version 2-tiny(YOLOv2-tiny)on the PASCALVisualObjectClasses(VOC)dataset,our normalization accelerator achieves a 72%reduction in processing time and 83%lower power consumption compared to a 2.4 GHz Intel Central Processing Unit(CPU)software normalization implementation,while maintaining accuracy(0.51%mean Average Precision(mAP)drop at floating-point 32 bits(FP32),1.35%at brain floating-point 16 bits(bfloat16)).When integrated into a neural processing unit(NPU),the design demonstrates 63%and 97%performance improvements over AMD CPU and Reduced Instruction Set Computing-V(RISC-V)implementations,respectively.These results confirm that our proposed BN hardware design enables efficient,high-accuracy,and power-saving on-device training for modern CNNs.Our results demonstrate that efficient hardware implementation of standard batch normalization is achievable without sacrificing accuracy,enabling practical on-device CNN training with significantly reduced computational and power requirements.
文摘Renormalization group analysis has been proposed to eliminate secular terms in perturbation solutions of differential equations and thus expand the domain of their validity.Here we extend the method to treat periodic orbits or limit cycles.Interesting normal forms could be derived through a generalization of the concept'resonance',which offers nontrivial analytic approximations.Compared with traditional techniques such as multi-scale methods,the current scheme proceeds in a very straightforward and simple way,delivering not only the period and the amplitude but also the transient path to limit cycles.The method is demonstrated with several examples including the Duffing oscillator,van der Pol equation and Lorenz equation.The obtained solutions match well with numerical results and with those derived by traditional analytic methods.
基金supported by the Basic Science Research Program through the National Research Foundation of Korea(NRF)funded by the Ministry of Science and ICT(NRF-2022R1A2C2012243).
文摘In recent decades,brain tumors have emerged as a serious neurological disorder that often leads to death.Hence,Brain Tumor Segmentation(BTS)is significant to enable the visualization,classification,and delineation of tumor regions in Magnetic Resonance Imaging(MRI).However,BTS remains a challenging task because of noise,non-uniform object texture,diverse image content and clustered objects.To address these challenges,a novel model is implemented in this research.The key objective of this research is to improve segmentation accuracy and generalization in BTS by incorporating Switchable Normalization into Faster R-CNN,which effectively captures the fine-grained tumor features to enhance segmentation precision.MRI images are initially acquired from three online datasets:Dataset 1—Brain Tumor Segmentation(BraTS)2018,Dataset 2—BraTS 2019,and Dataset 3—BraTS 2020.Subsequently,the Switchable Normalization-based Faster Regions with Convolutional Neural Networks(SNFRC)model is proposed for improved BTS in MRI images.In the proposed model,Switchable Normalization is integrated into the conventional architecture,enhancing generalization capability and reducing overfitting to unseen image data,which is essential due to the typically limited size of available datasets.The network depth is increased to obtain discriminative semantic features that improve segmentation performance.Specifically,Switchable Normalization captures the diverse feature representations from the brain images.The Faster R-CNN model develops end-to-end training and effective regional proposal generation,with an enhanced training stability using Switchable Normalization,to perform an effective segmentation in MRI images.From the experimental results,the proposed model attains segmentation accuracies of 99.41%,98.12%,and 96.71%on Datasets 1,2,and 3,respectively,outperforming conventional deep learning models used for BTS.
基金Supported by Guangdong Provincial Hospital of Chinese Medicine Science and Technology Research Special Project,No.YN2023WSSQ01State Key Laboratory of Traditional Chinese Medicine Syndrome.
文摘BACKGROUND Research has shown that several factors can influence postoperative abnormal liver function;however,most studies on this issue have focused specifically on hepatic and cardiac surgeries,leaving limited research on contributing factors in other types of surgeries.AIM To identify the risk factors for early postoperative abnormal liver function in multiple surgery types and construct a risk prediction model.METHODS This retrospective cohort study involved 3720 surgical patients from 5 surgical departments at Guangdong Provincial Hospital of Traditional Chinese Medicine.Patients were divided into abnormal(n=108)and normal(n=3612)groups based on liver function post-surgery.Univariate analysis and LASSO regression screened variables,followed by logistic regression to identify risk factors.A prediction model was constructed based on the variables selected via logistic re-gression.The goodness-of-fit of the model was evaluated using the Hosm-er–Lemeshow test,while discriminatory ability was measured by the area under the receiver operating characteristic curve.Calibration curves were plotted to visualize the consistency between predicted probabilities and observed outcomes.RESULTS The key factors contributing to abnormal liver function after surgery include elevated aspartate aminotransferase and alanine aminotransferase levels and reduced platelet counts pre-surgery,as well as the sevoflurane use during the procedure,among others.CONCLUSION The above factors collectively represent notable risk factors for postoperative liver function injury,and the prediction model developed based on these factors demonstrates strong predictive efficacy.
文摘BACKGROUND Ischemic stroke is one of the leading global causes of disability and death.Despite advances in modern medical technology that improve acute treatment and rehabilitation measures,post-stroke anxiety and depression(PSD)do not receive sufficient attention.AIM To systematically evaluate risk factors and early identification markers for PSD for more precise screening and intervention strategies in clinical practice.METHODS This retrospective study analyzed clinical data from 112 patients with ischemic stroke admitted between January 2022 and December 2024.Based on assessments using the Hamilton Rating Scale for Anxiety(HAMA)and Hamilton Rating Scale for Depression(HAMD)at 2 weeks(±3 days)post-stroke,patients were classified into the PSD group(HAMA≥7 and/or HAMD≥7)and the non-PSD group(HAMA<7 and HAMD<7).Observation indicators included psychological assessment,demographic and clinical characteristics,stroke-related clinical indicators,neuroimaging assessments,and laboratory biomarkers.Multivariate logistic regression analysis was used to identify independent risk factors for PSD,and receiver operating characteristic curve analysis was used to evaluate the diagnostic value of potential biomarkers.RESULTS Of the 112 patients,46(41.1%)were diagnosed with PSD.Multivariate analysis identified five independent risk factors:Female gender[Odds ratio(OR)=2.32,95%confidence interval(CI):1.56-3.45],history of mental disorders prior to stroke(OR=3.17,95%CI:1.89-5.32),infarct location in the frontal lobe or limbic system(OR=2.86,95%CI:1.73-4.71),stroke severity with National Institutes of Health Stroke Scale≥8 at admission(OR=2.54,95%CI:1.62-3.99),and low social support(Social Support Rating Scale<35,OR=2.18,95%CI:1.42-3.36).Subgroup analysis showed that depression patients more commonly had left hemisphere lesions(68.4%vs 45.2%),while anxiety patients more frequently presented with right hemisphere lesions(59.5%vs 39.5%).The PSD group exhibited larger infarct volumes(8.7 cm^(3) vs 5.3 cm^(3)),more severe white matter hyperintensities,and more pronounced frontal lobe atrophy.Analysis of inflammatory markers showed significantly elevated levels of interleukin-6(7.8 pg/mL vs 4.5 pg/mL)and tumor necrosis factor-alpha(15.6 pg/mL vs 9.8 pg/mL)in the PSD group,while hypothalamicpituitary-adrenal axis function assessment revealed higher cortisol levels(386.5±92.3 nmol/L vs 328.7±75.6 nmol/L)and flattened diurnal rhythm in the PSD group.CONCLUSION PSD is a complex neuropsychiatric consequence of stroke involving disruption of the frontal-limbic circuitry,neuroinflammatory responses,and dysfunction of the hypothalamic-pituitary-adrenal axis.
基金supported by grants from the Zhejiang Provincial TCM Science and Technology Plan Project,No.2023ZL156(to YH)Ningbo Top Medical and Health Research Program,No.2022020304(to XG)+1 种基金the Natural Science Foundation of Ningbo,No.2023J019(to YH)Key Laboratory of Precision Medicine for Atherosclerotic Diseases of Zhejiang Province,No.2022E10026(to YH)。
文摘Strokes include both ischemic stroke,which is mediated by a blockade or reduction in the blood supply to the brain,and hemorrhagic stroke,which comprises intracerebral hemorrhage and subarachnoid hemorrhage and is characterized by bleeding within the brain.Stroke is a lifethreatening cerebrovascular condition characterized by intricate pathophysiological mechanisms,including oxidative stress,inflammation,mitochondrial dysfunction,and neuronal injury.Critical transcription factors,such as nuclear factor erythroid 2-related factor 2 and nuclear factor kappa B,play central roles in the progression of stroke.Nuclear factor erythroid 2-related factor 2 is sensitive to changes in the cellular redox status and is crucial in protecting cells against oxidative damage,inflammatory responses,and cytotoxic agents.It plays a significant role in post-stroke neuroprotection and repair by influencing mitochondrial function,endoplasmic reticulum stress,and lysosomal activity and regulating metabolic pathways and cytokine expression.Conversely,nuclear factor-kappa B is closely associated with mitochondrial dysfunction,the generation of reactive oxygen species,oxidative stress exacerbation,and inflammation.Nuclear factor-kappa B contributes to neuronal injury,apoptosis,and immune responses following stroke by modulating cell adhesion molecules and inflammatory mediators.The interplay between these pathways,potentially involving crosstalk among various organelles,significantly influences stroke pathophysiology.Advancements in single-cell sequencing and spatial transcriptomics have greatly improved our understanding of stroke pathogenesis and offer new opportunities for the development of targeted,individualized,cell typespecific treatments.In this review,we discuss the mechanisms underlying the involvement of nuclear factor erythroid 2-related factor 2 and nuclear factor-kappa B in both ischemic and hemorrhagic stroke,with an emphasis on their roles in oxidative stress,inflammation,and neuroprotection.
基金Supported by the National Natural Science Foundation of China(Grant No.12071092)Guangdong Basic and Applied Basic Research Foundation(Grant No.2025A1515012072)+1 种基金the Natural Science Research Project of Anhui Educational Committee(Grant No.2024AH051298)the Scientific Research Foundation of Bozhou University(Grant No.BYKQ202419).
文摘Let G be a finite group and H a subgroup of G.The normal index of H in G is defined as the order of K/H_(G),where K is a normal supplement of H in G such that|K|is minimal and H_(G)≤K■G.Let p be a prime which divides the order of a group G.In this paper,some characterizations of G being p-solvable or p-supersolvable were obtained by analyzing the normal index of certain subgroups of G.These results can be viewed as local version of recent results in the literature.
文摘Nerve trauma commonly results in chronic neuropathic pain. This is by triggering the release of proinflammatory mediators from local and invading cells that induce inflammation and nociceptive neuron hyperexcitability. Even without apparent inflammation, injury sites are associated with increased inflammatory markers. This review focuses on how it might be possible to reduce neuropathic pain by reducing inflammation. Physiologically, pain is resolved by a combination of the out-migration of pro-inflammatory cells from the injury site, the down-regulation of the genes underlying the inflammation, up-regulating genes for anti-inflammatory mediators, and reducing nociceptive neuron hyperexcitability. While various techniques reduce chronic neuropathic pain, the best are effective on < 50% of patients, no technique reliably or permanently eliminates neuropathic pain. This is because most techniques are predominantly aimed at reducing pain, not inflammation. In addition, while single factors reduce pain, increasing evidence indicates significant and longer-lasting pain relief requires multiple factors acting simultaneously. Therefore, it is not surprising that extensive data indicate that the application of platelet-rich plasma provides more significant and longer-lasting pain suppression than other techniques, although its analgesia is neither complete nor permanent. However, several case reports indicate that platelet-rich plasma can induce permanent neuropathic pain elimination when the platelet concentration is significantly increased and is applied to longer nerve lengths. This review examines the primary triggers of the development and maintenance of neuropathic pain and techniques that reduce chronic neuropathic pain. The application of plateletrich plasma holds great promise for providing complete and permanent chronic neuropathic pain elimination.
文摘BACKGROUND Post-transplant tertiary hyperparathyroidism(PT-tHPT)is a well-recognized complication following kidney transplantation,characterized by persistent excessive secretion of parathyroid hormone(PTH)despite improved renal function.It is potentially associated with an increased risk of cardiovascular events,renal osteodystrophy,pathologic fractures,graft loss,and mortality.AIM To evaluate the incidence,risk factors,and outcomes of PT-tHPT amongst kidney transplant recipients.METHODS A total of 887 transplant recipients who underwent transplantation between 2000 and 2020 were evaluated.Univariable and multivariable logistic regression was performed to determine the predictors of tertiary hyperparathyroidism.Graft and recipient outcomes were assessed using multivariable Cox regression.A separate multivariable Cox regression was performed to determine the effect of treatment strategies on outcomes.RESULTS PT-tHPT,defined as elevated PTH(>65 ng/L)and persistent hypercalcemia(>2.60 mmol/L),was diagnosed in 14%of recipients.Risk factors for PT-tHPT included older age[odds ratio(OR)=1.36,P<0.001],Asian ethnicity(OR=0.33,P=0.006),total ischemia time(OR=1.03,P=0.048 per hour),pre-transplant serum calcium(OR=1.38,P<0.001)per decile increase,pre-transplant PTH level(OR=1.31,P<0.001)per decile increase,longer dialysis duration(OR=1.12,P=0.002)per year,history of acute rejection(OR=2.37,P=0.012),and slope of estimated glomerular filtration rate change(OR=0.91,P=0.001).There were a 3.4-fold higher risk of death-censored graft loss and a 1.9-fold greater risk of recipient death with PT-tHPT.The three treatment strategies of conservative management,calcimimetic and parathyroidectomy did not significantly change the graft or patient outcome.CONCLUSION Pretransplant elevated calcium and PTH levels,older age and dialysis duration are associated with PT-tHPT.While PT-tHPT significantly affects graft and recipient survival,the treatment strategies did not affect survival.
基金Supported by the National Natural Science Foundation of China,No.82402789Beijing Jishuitan Hospital Youcai Plan,No.KYYC202402+2 种基金Beijing Jishuitan Research Funding,No.HL202402and Beijing Natural Science Foundation,No.L232062No.L222063.
文摘BACKGROUND Aseptic loosening remains the leading cause of revision in primary total hip arthroplasty(pTHA).However,the literature demonstrates significant variability regarding the relative contributions of different factors.AIM To investigate the key determinants of aseptic loosening,we performed a systematic review and meta-analysis.METHODS A comprehensive search of PubMed,Web of Science,EMBASE,and the Cochrane Library was conducted,encompassing studies from database inception to January 1,2025.Meta-analyses were performed to evaluate factors associated with aseptic loosening following pTHA.Inclusion and exclusion criteria were systematically applied at each stage to ensure methodological transparency and reproducibility.Study quality was assessed using standardized categories.Pooled odds ratio(OR)with corresponding 95%confidence interval were calculated with random-or fixed-effects models to generate reliability estimates,and study heterogeneity was visualized using forest plots.Ten factors,categorized into patient-,surgeon-,and device-related domains,were reviewed and meta-analyzed.Funnel plot analysis demonstrated a relatively symmetrical distribution,suggesting minimal publication bias.RESULTS A meta-analysis of 20 studies(520789 participants)found a pooled prevalence of 1.96%.Significant risk factors for aseptic loosening after pTHA included elevated body mass index(OR=1.116,P<0.001),higher Charlson comorbidity index(OR=1.378,P<0.001),prosthesis-related factors(OR=1.497,P<0.001),and adverse lifestyles(OR=2.198,P=0.037).Protective factors were non-white race(OR=0.445,P<0.001)and favorable genetics(OR=0.723,P<0.001).Male sex increased risk(OR=1.232,P=0.016),while age and anatomy were not significant.Surgical expertise showed a slight protective effect(OR=1.048,P<0.001).A comprehensive understanding of the modifiable and non-modifiable factors contributing to aseptic loosening after pTHA requires consideration of patient-related factors,surgical expertise,and prosthesis characteristics.CONCLUSION The identification of these factors is critical for risk mitigation.High-risk patients should receive targeted counseling regarding individualized profiles.Further studies are warranted to establish clearer causal relationships and identify additional contributing factors.
文摘BACKGROUND Esophageal cancer is highly malignant and frequently metastasizes to bones.Concomitant depression worsens prognosis;however,its incidence and determinants in this specific population remain poorly defined.AIM To determine the incidence of depression and its independent risk factors in patients with esophageal cancer and bone metastasis.METHODS A total of 100 consecutive eligible patients admitted between March 2022 and March 2025 were recruited.Depression was assessed with the Beck Depression Inventory-II;scores>4 defined the depression group(n=42)and scores≤4 the non-depression group(n=58).Demographic,clinical,and laboratory variables were compared between the groups.Multivariate logistic regression was used to identify independent risk factors.RESULTS Depression prevalence was 42.0%(42/100).Univariate analysis demonstrated significant differences in monthly per-capita household income,education level,social support,sleep disorders,and serum high-sensitivity C-reactive protein(all P<0.05);no differences were observed in sex,age,tumor characteristics,or other laboratory indices(all P>0.05).Multivariable analysis revealed the following independent risk factors for depression:Low income[odds ratio(OR)=2.66,95%confidence interval(CI):1.17-6.03],low education(OR=2.46,95%CI:1.08-5.61),low social support(OR=5.10,95%CI:1.81-14.39),sleep disorders(OR=2.79,95%CI:1.23-6.35),and elevated high-sensitivity C-reactive protein(OR=1.31 per unit increase,95%CI:1.18-1.46).CONCLUSION Depression is common among patients with esophageal cancer and bone metastasis.Low socioeconomic status,limited education,insufficient social support,sleep disturbances,and systemic inflammation were independent predictors.Interventions that address these modifiable factors may reduce depression risk in this population.
基金Supported by the Scientific Research Projects of the Health System in Pingshan District,No.2023122.
文摘BACKGROUND Lumbar interbody fusion(LIF)is the primary treatment for lumbar degenerative diseases.Elderly patients are prone to anxiety and depression after undergoing surgery,which affects their postoperative recovery speed and quality of life.Effective prevention of anxiety and depression in elderly patients has become an urgent problem.AIM To investigate the trajectory of anxiety and depression levels in elderly patients after LIF,and the influencing factors.METHODS Random sampling was used to select 239 elderly patients who underwent LIF from January 2020 to December 2024 in Shenzhen Pingle Orthopedic Hospital.General information and surgery-related indices were recorded,and participants completed measures of psychological status,lumbar spine dysfunction,and quality of life.A latent class growth model was used to analyze the post-LIF trajectory of anxiety and depression levels,and unordered multi-categorical logistic regression was used to analyze the influencing factors.RESULTS Three trajectories of change in anxiety level were identified:Increasing anxiety(n=26,10.88%),decreasing anxiety(n=27,11.30%),and stable anxiety(n=186,77.82%).Likewise,three trajectories of change in depression level were identified:Increasing depression(n=30,12.55%),decreasing depression(n=26,10.88%),and stable depression(n=183,76.57%).Regression analysis showed that having no partner,female sex,elevated Oswestry dysfunction index(ODI)scores,and reduced 36-Item Short Form Health Survey scores all contributed to increased anxiety levels,whereas female sex,postoperative opioid use,and elevated ODI scores all contributed to increased depression levels.CONCLUSION During clinical observation,combining factors to predict anxiety and depression in post-LIF elderly patients enables timely intervention,quickens recovery,and enhances quality of life.
基金Supported by the Provincial Key Cultivation Laboratory for Digestive Disease Research,No.2021SYS13Shanxi Province’s“Si Ge Yi Pi”Science and Technology Driven Medical Innovation Project,No.2021MX03Shanxi Provincial Basic Research Program,No.202403021222423.
文摘BACKGROUND Ulcerative colitis(UC)is a chronic and treatment-resistant disorder requiring potent therapeutics that are effective and safe.Cedrol(CE)is a bioactive natural product present in many traditional Chinese medicines.It is known for its suppression of inflammation and mitigation of oxidative stress.Its therapeutic efficacy and mechanistic underpinnings in UC remain uncharacterized.AIM To investigate the therapeutic potential and mechanisms of CE in UC.METHODS The anti-inflammatory activity and intestinal barrier-repairing effects of CE were assessed in a dextran sulfate sodium-induced murine colitis model.Network pharmacology was employed to predict potential targets and pathways.Then molecular docking and dynamics simulations were utilized to confirm a stable interaction between CE and the toll-like receptor 4(TLR4)/myeloid differentiation factor 2(MD2)complex.The anti-inflammatory mechanisms were further verified using in vitro assays.Additionally,the gut microbiota composition was analyzed via 16S rRNA gene sequencing.RESULTS CE significantly alleviated colitis symptoms,mitigated histopathological damage,and suppressed inflammation.Moreover,CE restored intestinal barrier integrity by enhancing mucus secretion and upregulating tight junction proteins(zonula occludens 1,occludin,claudin-1).Mechanistically,CE stably bound to MD2,inhibiting lipopolysaccharide-induced TLR4 signaling in RAW264.7 cells.This led to suppression of the downstream mitogen-activated protein kinase and nuclear factor kappa B signaling pathways,downregulating the expression of tumor necrosis factor-alpha,interleukin-1β,and interleukin-6.Gut microbiota analysis revealed that CE reversed dextran sulfate sodium-induced dysbiosis with significant enrichment of butyrogenic Christensenella minuta.CONCLUSION CE acted on MD2 to suppress proinflammatory cascades,promoting mucosal barrier reconstitution and microbiota remodeling and supporting its therapeutic use in UC.
文摘BACKGROUND Early renal artery thrombosis after kidney transplantation is rare but often leads to graft loss.Prompt diagnosis and intervention are essential,particularly in patients with inherited thrombophilias such as factor V Leiden(FVL)mutation.CASE SUMMARY A kidney transplant recipient with FVL mutation developed an acute transplant renal artery thrombosis.The immediate post-operative Doppler ultrasonography revealed thrombosis of the main and inferior polar renal arteries.Emergent thrombectomy and separate arterial re-anastomoses were performed after cold perfusion with heparinized saline and vasodilator solution.Reperfusion was successful with immediate urine output and gradual improvement in renal function.The patient was discharged on direct oral anticoagulation therapy.CONCLUSION Early detection and surgical intervention can preserve graft function in posttransplant renal artery thrombosis even in patients at high risk.
文摘The aging process is an inexorable fact throughout our lives and is considered a major factor in develo ping neurological dysfunctions associated with cognitive,emotional,and motor impairments.Aging-associated neurodegenerative diseases are characterized by the progressive loss of neuronal structure and function.
