Inflammatory markers,oxidative stress,and mitochondrial dynamics:Repercussions on coronary artery disease in diabetes

Inflammatory markers and mediators that affect the development of cardiovascular diseases have been the focus of recent scientific work.Thus,the purpose of this editorial is to promote a critical debate about the article titled“Nε-carboxymethyl-lysine and inflammatory cytokines,markers,and mediators of coronary artery disease progression in diabetes”,published in the World Journal of Diabetes in 2024.This work directs us to reflect on the role of advanced glycation end products,which are pro-inflammatory products arising from the metabolism of fatty acids and sugars whose main marker in tissues is Nε-carboxymethyllysine(NML).Recent studies have linked high levels of pro-inflammatory agents with the development of coronary artery disease(CAD),especially tumor necrosis factor alpha,interleukins,and C-reactive protein.These inflammatory agents increase the production of reactive oxygen species(ROS),of which people with diabetes are known to have an increased production.The increase in ROS promotes lipid peroxidation,which causes damage to myocytes,promoting myocardial damage.Furthermore,oxidative stress induces the binding of NML to its receptor RAGE,which in turn activates the nuclear factor-kB,and consequently,inflammatory cytokines.These inflammatory cytokines induce endothelial dysfunction,with increased expression of adhesion molecules,changes in endothelial permeability and changes in the expression of nitric oxide.In this sense,the therapeutic use of monoclonal antibodies(inflammatory reducers such as statins and sodium-glucose transport inhibitors)has demonstrated positive results in the regression of atherogenic plaques and consequently CAD.On the other hand,many studies have demonstrated a relationship between mitochondrial dynamics,diabetes,and cardiovascular diseases.This link occurs since ROS have their origin in the imbalance in glucose metabolism that occurs in the mitochondrial matrix,and this imbalance can have its origin in inadequate diet as well as some pathologies.Photobiomodulation(PBM)has recently been considered a possible therapeutic agent for cardiovascular diseases due to its effects on mitochondrial dynamics and oxidative stress.In this sense,therapies such as PBM that act on pro-inflammatory mediators and mitochondrial modulation could benefit those with cardiovascular diseases.

Emerging structures and dynamic mechanisms ofγ-secretase for Alzheimer’s disease

γ-Secretase,called“the proteasome of the membrane,”is a membrane-embedded protease complex that cleaves 150+peptide substrates with central roles in biology and medicine,including amyloid precursor protein and the Notch family of cell-surface receptors.Mutations inγ-secretase and amyloid precursor protein lead to early-onset familial Alzheimer’s disease.γ-Secretase has thus served as a critical drug target for treating familial Alzheimer’s disease and the more common late-onset Alzheimer’s disease as well.However,critical gaps remain in understanding the mechanisms of processive proteolysis of substrates,the effects of familial Alzheimer’s disease mutations,and allosteric modulation of substrate cleavage byγ-secretase.In this review,we focus on recent studies of structural dynamic mechanisms ofγ-secretase.Different mechanisms,including the“Fit-Stay-Trim,”“Sliding-Unwinding,”and“Tilting-Unwinding,”have been proposed for substrate proteolysis of amyloid precursor protein byγ-secretase based on all-atom molecular dynamics simulations.While an incorrect registry of the Notch1 substrate was identified in the cryo-electron microscopy structure of Notch1-boundγ-secretase,molecular dynamics simulations on a resolved model of Notch1-boundγ-secretase that was reconstructed using the amyloid precursor protein-boundγ-secretase as a template successfully capturedγ-secretase activation for proper cleavages of both wildtype and mutant Notch,being consistent with biochemical experimental findings.The approach could be potentially applied to decipher the processing mechanisms of various substrates byγ-secretase.In addition,controversy over the effects of familial Alzheimer’s disease mutations,particularly the issue of whether they stabilize or destabilizeγ-secretase-substrate complexes,is discussed.Finally,an outlook is provided for future studies ofγ-secretase,including pathways of substrate binding and product release,effects of modulators on familial Alzheimer’s disease mutations of theγ-secretase-substrate complexes.Comprehensive understanding of the functional mechanisms ofγ-secretase will greatly facilitate the rational design of effective drug molecules for treating familial Alzheimer’s disease and perhaps Alzheimer’s disease in general.

Network pharmacology and molecular dynamics study of the effect of the Astragalus-Coptis drug pair on diabetic kidney disease

BACKGROUND Diabetic kidney disease(DKD)is the primary cause of end-stage renal disease.The Astragalus-Coptis drug pair is frequently employed in the management of DKD.However,the precise molecular mechanism underlying its therapeutic effect remains elusive.AIM To investigate the synergistic effects of multiple active ingredients in the Astragalus-Coptis drug pair on DKD through multiple targets and pathways.METHODS The ingredients of the Astragalus-Coptis drug pair were collected and screened using the TCMSP database and the SwissADME platform.The targets were predicted using the SwissTargetPrediction database,while the DKD differential gene expression analysis was obtained from the Gene Expression Omnibus database.DKD targets were acquired from the GeneCards,Online Mendelian Inheritance in Man database,and DisGeNET databases,with common targets identified through the Venny platform.The protein-protein interaction network and the“disease-active ingredient-target”network of the common targets were constructed utilizing the STRING database and Cytoscape software,followed by the analysis of the interaction relationships and further screening of key targets and core active ingredients.Gene Ontology(GO)function and Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway enrichments were performed using the DAVID database.The tissue and organ distributions of key targets were evaluated.PyMOL and AutoDock software validate the molecular docking between the core ingredients and key targets.Finally,molecular dynamics(MD)simulations were conducted to simulate the optimal complex formed by interactions between core ingredients and key target proteins.RESULTS A total of 27 active ingredients and 512 potential targets of the Astragalus-Coptis drug pair were identified.There were 273 common targets between DKD and the Astragalus-Coptis drug pair.Through protein-protein interaction network topology analysis,we identified 9 core active ingredients and 10 key targets.GO and KEGG pathway enrichment analyses revealed that Astragalus-Coptis drug pair treatment for DKD involves various biological processes,including protein phosphorylation,negative regulation of apoptosis,inflammatory response,and endoplasmic reticulum unfolded protein response.These pathways are mainly associated with the advanced glycation end products(AGE)-receptor for AGE products signaling pathway in diabetic complications,as well as the Lipid and atherosclerosis.Molecular docking and MD simulations demonstrated high affinity and stability between the core active ingredients and key targets.Notably,the quercetin-AKT serine/threonine kinase 1(AKT1)and quercetin-tumor necrosis factor(TNF)protein complexes exhibited exceptional stability.CONCLUSION This study demonstrated that DKD treatment with the Astragalus-Coptis drug pair involves multiple ingredients,targets,and signaling pathways.We propose a novel approach for investigating the molecular mechanism underlying the therapeutic effects of the Astragalus-Coptis drug pair on DKD.Furthermore,we suggest that quercetin is the most potent active ingredient and specifically targets AKT1 and TNF,providing a theoretical foundation for further exploration of pharmacologically active ingredients and elucidating their molecular mechanisms in DKD treatment.

Transmission Dynamics and Optimal Control Strategies of a Hand-Foot-Mouth Disease Model with Treatment and Vaccination Interventions

In this article, the transmission dynamics of a Hand-Foot-Mouth disease model with treatment and vaccination interventions are studied. We calculated the basic reproduction number and proved the global stability of disease-free equilibrium when R0 R0 > 1. Meanwhile, we obtained the optimal control strategies minimizing the cost of intervention and minimizing the infected person. We also give some numerical simulations to verify our theoretical results.

Brain Functional Networks with Dynamic Hypergraph Manifold Regularization for Classification of End-Stage Renal Disease Associated with Mild Cognitive Impairment

The structure and function of brain networks have been altered in patients with end-stage renal disease(ESRD).Manifold regularization(MR)only considers the pairing relationship between two brain regions and cannot represent functional interactions or higher-order relationships between multiple brain regions.To solve this issue,we developed a method to construct a dynamic brain functional network(DBFN)based on dynamic hypergraph MR(DHMR)and applied it to the classification of ESRD associated with mild cognitive impairment(ESRDaMCI).The construction of DBFN with Pearson’s correlation(PC)was transformed into an optimization model.Node convolution and hyperedge convolution superposition were adopted to dynamically modify the hypergraph structure,and then got the dynamic hypergraph to form the manifold regular terms of the dynamic hypergraph.The DHMR and L_(1) norm regularization were introduced into the PC-based optimization model to obtain the final DHMR-based DBFN(DDBFN).Experiment results demonstrated the validity of the DDBFN method by comparing the classification results with several related brain functional network construction methods.Our work not only improves better classification performance but also reveals the discriminative regions of ESRDaMCI,providing a reference for clinical research and auxiliary diagnosis of concomitant cognitive impairments.

Oscillatory Dynamics of Heterogeneous Stem Cell Regeneration

Stem cell regeneration is an essential biological process in the maintenance of tissue homeostasis;dysregulation of stem cell regeneration may result in dynamic diseases that show oscillations in cell numbers.Cell heterogeneity and plasticity are necessary for the dynamic equilibrium of tissue homeostasis;however,how these features may affect the oscillatory dynamics of the stem cell regeneration process remains poorly understood.Here,based on a mathematical model of heterogeneous stem cell regeneration that includes cell heterogeneity and random transition of epigenetic states,we study the conditions to have oscillation solutions through bifurcation analysis and numerical simulations.Our results show various model system dynamics with changes in different parameters associated with kinetic rates,cellular heterogeneity,and plasticity.We show that introducing heterogeneity and plasticity to cells can result in oscillation dynamics,as we have seen in the homogeneous stem cell regeneration system.However,increasing the cell heterogeneity and plasticity intends to maintain tissue homeostasis under certain conditions.The current study is an initiatory investigation of how cell heterogeneity and plasticity may affect stem cell regeneration dynamics,and many questions remain to be further studied both biologically and mathematically.

Advances in the research of intestinal fungi in Crohn's disease

This article reviews of the original research published by Wu et al in the World Journal of Gastroenterology,delving into the pivotal role of the gut microbiota in the pathogenesis of Crohn's disease(CD).Insights were gained from fecal microbiota transplantation(FMT)in mouse models,revealing the intricate interplay between the gut microbiota,mesenteric adipose tissue(MAT),and creeping fat.The study uncovered the characteristics of inflammation and fibrosis in the MAT and intestinal tissues of patients with CD;moreover,through the FMT mouse model,it observed the impact of samples from healthy patients and those with CD on symptoms.The pathogenesis of CD is complex,and its etiology remains unclear;however,it is widely believed that gut microbiota dysbiosis plays a significant role.Recently,with the development and application of next-generation sequen-cing technology,research on the role of fungi in the pathogenesis and chronicity of CD has deepened.This editorial serves as a supplement to the research by Wu et al who discussed advances related to the study of fungi in CD.

Dynamic-YOLOX:复杂背景下的苹果叶片病害检测模型

针对目前苹果叶片数据集的叶片病害种类不全以及图片背景单一等问题,构建了复杂背景下包括苹果叶部六种常见病害的苹果叶片病害数据集。针对目前主流苹果叶片病害检测模型检测精度不高、模型复杂和不满足实时监测等问题,提出了一种基于YOLOX-S(you only look once X-S)改进得到的复杂背景下的苹果叶片病害自适应检测模型Dynamic-YOLOX。设计并使用ECA-SPPFCSPC模块(efficient channel attention cross-stage partial fast spatial pyramid pooling module)更换YOLOX-S模型主干网络尾部Dark5中的空间金字塔池化(SPP)以及跨阶段局部网络(CSPNet)模块来增强模型关注深层语义特征、抑制无用信息的能力,并减少硬件内存开销。设计了动态跨阶段局部网络(ODCSP)模块,并用其更换YOLOX-S模型主干网络中Dark2、Dark3、Dark4部分以及颈部网络中所有的CSPNet模块,使得模型在面对不同输入特征时有更强的自适应性,在减少模型的参数量和计算量的同时提高了模型的平均检测精度。引入Varifocal Loss更换模型中分类置信度损失的BCEWithLogits Loss来提升模型对苹果叶片中密集小目标病害的检测精度。在自制数据集上Dynamic-YOLOX相对原始YOLOX-S模型的mAP提升了4.54个百分点,达到84.63%,同时模型的参数量和计算量分别下降了11.97%和13.45%,检测速度达到44.07 FPS。对比主流苹果叶片病害检测模型,Dynamic-YOLOX具有一定优越性。

Study on Ecological Change Remote Sensing Monitoring Method Based on Elman Dynamic Recurrent Neural Network

In this paper, Hailin City of Heilongjiang Province, China is taken as the research area. As an important city in Heilongjiang Province, China, the sustainable development of its ecological environment is related to the opening up, economic prosperity and social stability of Northeast China. In this paper, the remote sensing ecological index (RSEI) of Hailin City in recent 20 years was calculated by using Landsat 5/8/9 series satellite images, and the temporal and spatial changes of the ecological environment in Hailin City were further analyzed and the influencing factors were discussed. From 2003 to 2023, the mean value of RSEI in Hailin City decreased and increased, and the ecological environment decreased slightly as a whole. RSEI declined most significantly from 2003 to 2008, and it increased from 2008 to 2013, decreased from 2013 to 2018, and increased from 2018 to 2023 again, with higher RSEI value in the south and lower RSEI value in the northwest. It is suggested to appropriately increase vegetation coverage in the northwest to improve ecological quality. As a result, the predicted value of Elman dynamic recurrent neural network model is consistent with the change trend of the mean value, and the prediction error converges quickly, which can accurately predict the ecological environment quality in the future study area.

Is Dynesys dynamic stabilization system superior to posterior lumbar fusion in the treatment of lumbar degenerative diseases?

Dynesys,a pedicle-based dynamic stabilization system,was introduced to overcome some undesirable complications of fusion procedures.Nevertheless,the theoretical advantages of Dynesys over fusion have not been clearly confirmed.The purpose of this editorial was to compare clinical and radiological outcomes of patients who underwent Dynesys system with those who underwent posterior lumbar fusion according to the existing literature and to see if the application of the Dynesys system is superior to the traditional lumbar fusion surgery.According to published clinical reports,the short-term effects of the Dynesys dynamic stabilization system are similar to that of traditional lumbar fusion surgery.Three comparative studies of Dynesys dynamic stabilization and fusion surgery with medium-term follow-up are encouraging.However,the results from four single-treatment-arm and small-sample studies of case series with long-term follow-up were not encouraging.In the present circumstances,it is not possible to conclude that the Dynesys dynamic stabilization system is superior to fusion surgery for lumbar degenerative diseases.

A Computer Software-Epitimulator~ for Simulating Temporal Dynamics of Plant Disease Epidemic Progress

The objective of the present study was to develop a computer software for simulating the temporal development of plant disease epidemics using Richards, logistic, Gompertz, monomolecular, and exponential functions, respectively, and for predicting disease with a fitted model. The software was programmed using Visual Basic （VB6.0） and packaged with the Wise Installation System. The Fibonacci （＇0.618＇） section strategy was used to find out the most appropriate value for the shape parameter （m） in Richards function simulation through looping procedures. The software program was repeatedly tested, debugged and edited until it was run through favorably and produced ideal outputs. It was named Epitimulator based on the phrase ＇epidemic time simulator＇ and has been registered by the National Copyright Department of China （Reg. no. 2007SR18489）. It can be installed and run on personal computers with all versions of Windows operational systems. Data of disease index and survey time are keyed in or imported from Access files. The output of fitted models and related data of parameters can be pasted into Microsoft Excel worksheet or into Word document for editing as required and the simulated disease progress curves can be stored in separate graphic files. After being finally tested and completed, Epitimulator was applied to simulate the epidemic progress of corn northern leaf blight （Exserohilum turcicum） with recorded data from field surveys of corn crops and the fitted models were output. Comparison of the simulation results showed that the disease progress was always best described by Richards function, which resulted in the most accurate simulation model. Result also showed that forecast of northern leaf blight development was highly accurate by using the computed progress model from Richards function.

Occurrence and Epidemic Dynamics and Accurate Prevention and Control of Important Sugarcane Pests and Diseases in the Sugarcane Areas of Yunnan

Based on investigation and research, according to the current actual production of sugarcane, the occurrence dynamics and outbreak causes of important pests and diseases that seriously affect sugarcane production were summarized, and accurate and efficient green prevention and control technology was put forward according to the occurrence and damage characteristics of important pests and diseases, such as strengthening sugarcane introduction and quarantine, breeding and selecting varieties resistant to diseases and pests, promoting the use of detoxified healthy seedlings vigorously, applying lamp trapping technology on a large scale, scientifically guiding and promoting biological prevention and control technology, practically promoting the precise and efficient application of slow-release long- acting and low toxic pesticides, strengthening field management, spraying pesticides in time at the early stage of a disease, and doing a good job of monitoring and emergency prevention and control of sudden pests.

Dynamic Pathology and Antigen Location Study on Broiler Breeders with Coinfection of Marek's Disease Virus and Reticuloendotheliosis Virus

To further understand the generation and development of coinfection of Marek＇s disease virus （MDV） and reticuloendotheliosis virus （REV） in broiler breeders, and then find the method and optimal time of differential diagnosis for complex clinic multiple infection, the authors studied the pathohistological changes, apoptosis, immunohistochemistry （immunofluorescence）, and ultrastructure of tumor tissues of broiler breeders inoculated with MDV and REV. The study showed that proliferation of small lymphocytes was seen in the main organs at the age of 1 week, then immature lymphocytes, all kinds of lymphocytes, primitive reticulum cells, and Marek＇s disease cells （MDCs） were observed at 2-9 weeks. Apoptosis of lymphocytes could not be seen until the age of 10 weeks in the immune system. Immunohistochemistry detection showed that the positive signs of MDV and REV antigen were observed in the main organs at 2 weeks of age. Multi-morphology lymphocytes, MDV, and REV, mitotic figures and apoptosis of lymphocytes were observed with the help of transmission electron microscopy. MDV cooperating with REV promotes the course of disease of coinfection. Differential diagnosis can be done by immunohistochemistry in the early stage （before 2 weeks）, and histopathology in the late stage （post 4 weeks）. MDCs, primitive reticulum cells, immature lymphocytes, and two kinds of virions can serve as a basis for bistopathology differential diagnosis.

Abnormal characterization of dynamic functional connectivity in Alzheimer’s disease

Numerous studies have shown abnormal brain functional connectivity in individuals with Alzheimer’s disease(AD)or amnestic mild cognitive impairment(aMCI).However,most studies examined traditional resting state functional connections,ignoring the instantaneous connection mode of the whole brain.In this case-control study,we used a new method called dynamic functional connectivity(DFC)to look for abnormalities in patients with AD and aMCI.We calculated dynamic functional connectivity strength from functional magnetic resonance imaging data for each participant,and then used a support vector machine to classify AD patients and normal controls.Finally,we highlighted brain regions and brain networks that made the largest contributions to the classification.We found differences in dynamic function connectivity strength in the left precuneus,default mode network,and dorsal attention network among normal controls,aMCI patients,and AD patients.These abnormalities are potential imaging markers for the early diagnosis of AD.

Behavior as the dynamic unit between polar opposites--Health and Disease

The current definition of health of the World Health Organization (WHO), formulated in 1948, describes health as “a state of complete physical, mental and social well-being and not simply the absence of disease or infirmity”.[1] Although, this formulation was been revolutionary because it overcame the negative definition of health as the absence of disease and included physical, mental and social domains, it has been partially criticized over the past 60 years. This definition is in fact referred to the disease acute pattern, which is transient and limited in the time. Today, the number of people living with chronic diseases for decades is increasing worldwide.

Computational fluid dynamics modeling in intracranial atherosclerotic disease

Intracranial atherosclerotic disease(ICAD)is an important cause for ischemic stroke and transient ischemic stroke(TIA)throughout the world,especially in Asians,which is not fully appreciated,partly due to its inaccessibility and limitations of current neuroimaging methods.The computational fluid dynamics(CFD)modeling technique provides a novel approach to reveal the hemodynamic characteristics in ICAD,e.g.,the distributions of pressure,wall shear stress and flow velocity.In this review article,we aim to provide an overview of the general methodology of CFD modeling in arterial stenotic diseases,the established application of this technique in coronary artery disease,and more importantly,perspectives and challenges of this technique in the investigation of ICAD.Promising findings of preliminary studies using a CFD model for hemodynamic analysis in ICAD warrant verifications.Further studies in this area will help rectify loopholes in the current secondary prevention strategy,and inform individualized treatment for ICAD patients in the near future.

Novel ligand-based docking; molecular dynamic simulations;and absorption, distribution, metabolism, and excretion approach to analyzing potential acetylcholinesterase inhibitors for Alzheimer's disease

Acetylcholinesterase(AChE) plays an important role in Alzheimer's disease(AD). The excessive activity of AChE causes various neuronal problems, particularly dementia and neuronal cell deaths. Generally, antiAChE drugs induce some serious neuronal side effects in humans. Therefore, this study sought to identify alternative drug molecules from natural products with fewer side effects than those of conventional drugs for treating AD. To achieve this, we developed computational methods for predicting drug and target binding affinities using the Schrodinger suite. The target and ligand molecules were retrieved from established databases. The target enzyme has 539 amino acid residues in its sequence alignment. Ligand molecules of 20 bioactive molecules were obtained from different kinds of plants, after which we performed critical analyses such as molecular docking; molecular dynamic(MD) simulations; and absorption, distribution, metabolism, and excretion(ADME) analysis. In the docking studies, the natural compound rutin showed a superior docking score of à 12.335 with a good binding energy value ofà73.313 kcal/mol. Based on these findings, rutin and the target complex was used to perform MD simulations to analyze rutin stability at 30 ns. In conclusion, our study demonstrates that rutin is a superior drug candidate for AD. Therefore, we propose that this molecule is worth further investigation using in vitro studies.

Occurrence and Epidemic Dynamics and Control Countermeasures of Important Sugarcane Diseases in Rainy and Humid Season

The rainy and humid season from July to September is the crucial period for elongation and jointing and yield performance of sugarcane,and also a peak occurrence and damage period of many important sugarcane diseases. In order to prevent large-area outbreak of sugarcane diseases and ensure safe growth in late stage,the occurrence dynamics of important sugarcane diseases in the rainy and humid season was analyzed and discussed from the aspects of three epidemic outbreak elements of plant diseases: host plant,pathogen and environmental condition. Moreover,the corresponding control ideas and technical countermeasures were put forward according to the epidemic characteristic of sugarcane diseases and the actual sugarcane production.

Network Modeling of Inammatory Dynamics Induced by Biomass Smoke Leading to Chronic Obstructive Pulmonary Disease

Chronic obstructive pulmonary disease(COPD) is a chronic inflammatory disorder characterized by airflow obstruction and progressive damage of lung tissues. As currently more than 3 billion people use biomass fuel for cooking and heating worldwide, exposure to biomass smoke(BS) is recognized as a significant risk factor for COPD. Recent clinical data have shown that BS-COPD patients have a Th2-type inflammatory profile significantly different from that in COPD induced by cigarette smoke. As COPD is essentially proinflammatory,however, the mechanism underlying this Th2-type anti-inflammatory profile remains elusive.In this work, a network model is applied to study BS-induced inflammatory dynamics. The network model involves several positive feedback loops, activations of which are responsible for different mechanisms by which clinical phenotypes of COPD are produced. Our modeling study in this work has identified a subset of BS-COPD patients with a mixed M1-and Th2-type inflammatory profile. The model’s prediction is in good agreement with clinical experiments and our in silico knockout simulations have demonstrated several important network components that play an important role in the disease. Our modeling study provides novel insight into BS-COPD progression, offering a rationale for targeted therapy and personalized medicine for treatment of the disease in future.

An Eigenspace Method for Detecting Space-Time Disease Clusters with Unknown Population-Data

Space-time disease cluster detection assists in conducting disease surveillance and implementing control strategies.The state-of-the-art method for this kind of problem is the Space-time Scan Statistics(SaTScan)which has limitations for non-traditional/non-clinical data sources due to its parametric model assumptions such as Poisson orGaussian counts.Addressing this problem,an Eigenspace-based method called Multi-EigenSpot has recently been proposed as a nonparametric solution.However,it is based on the population counts data which are not always available in the least developed countries.In addition,the population counts are difficult to approximate for some surveillance data such as emergency department visits and over-the-counter drug sales,where the catchment area for each hospital/pharmacy is undefined.We extend the population-based Multi-EigenSpot method to approximate the potential disease clusters from the observed/reported disease counts only with no need for the population counts.The proposed adaptation uses an estimator of expected disease count that does not depend on the population counts.The proposed method was evaluated on the real-world dataset and the results were compared with the population-based methods:Multi-EigenSpot and SaTScan.The result shows that the proposed adaptation is effective in approximating the important outputs of the population-based methods.