Altered synaptic currents,mitophagy,mitochondrial dynamics in Alzheimer's disease models and therapeutic potential of Dengzhan Shengmai capsules intervention

Emerging research suggests a potential association of progression of Alzheimer's disease(AD)with alterations in synaptic currents and mitochondrial dynamics.However,the specific associations between these pathological changes remain unclear.In this study,we utilized Aβ42-induced AD rats and primary neural cells as in vivo and in vitro models.The investigations included behavioural tests,brain magnetic resonance imaging(MRI),liquid chromatography-tandem mass spectrometry(UPLC-MS/MS)analysis,Nissl staining,thioflavin-S staining,enzyme-linked immunosorbent assay,Golgi-Cox staining,transmission electron microscopy(TEM),immunofluorescence staining,proteomics,adenosine triphosphate(ATP)detection,mitochondrial membrane potential(MMP)and reactive oxygen species(ROS)assessment,mitochondrial morphology analysis,electrophysiological studies,Western blotting,and molecular docking.The results revealed changes in synaptic currents,mitophagy,and mitochondrial dynamics in the AD models.Remarkably,intervention with Dengzhan Shengmai(DZSM)capsules emerged as a pivotal element in this investigation.Aβ42-induced synaptic dysfunction was significantly mitigated by DZSM intervention,which notably amplified the frequency and amplitude of synaptic transmission.The cognitive impairment observed in AD rats was ameliorated and accompanied by robust protection against structural damage in key brain regions,including the hippocampal CA3,primary cingular cortex,prelimbic system,and dysgranular insular cortex.DZSM intervention led to increased IDE levels,augmented long-term potential(LTP)amplitude,and enhanced dendritic spine density and length.Moreover,DZSM intervention led to favourable changes in mitochondrial parameters,including ROS expression,MMP and ATP contents,and mitochondrial morphology.In conclusion,our findings delved into the realm of altered synaptic currents,mitophagy,and mitochondrial dynamics in AD,concurrently highlighting the therapeutic potential of DZSM intervention.

Effects of Honeysuckle Chlorogenic Acid on Secretory Enzymes,Lipoxygenase A4,and Biochemical Indicators inModel Mice with Aluminum Induced Alzheimer's Disease

[Objectives]To explore the effects of chlorogenic acid from honeysuckle on the secretion enzymes,lipoxygenase A4(LXA4),and blood biochemical indicators in mice with aluminum induced Alzheimer's disease(AD).[Methods]Chlorogenic acid was extracted from hon-eysuckle by ultrasound assisted alcohol extraction method.Seventy mice were randomly divided into normal group,model group,and low,me-dium and high dose groups of honeysuckle chlorogenic acid.All the mice in each group except for the normal group were given maltol aluminum by intraperitoneal injection to establish models of aluminum induced AD,continuously injected for 5 d and stopped for 2 d,totally poisoned for 8 weeks.Starting from the 5^(th) week of poisoning,the low,medium and high dose groups of honeysuckle chlorogenic acid were given honeysuck-le chlorogenc acid solution 40,80 and 160 mg/kg by gavage,respectively,while the normal group and the model group were fed with an equal volume of distilled water,all once daily,continuously gavaged until the end of the 8^(th) week.At the end of the experiment,the learning memory ability of the mice was tested by Y-type waler maze,and the number of tests required to reach the learning standard,the number of memory er-rors in 20 tests and the error rate of the mice were recorded.The brains of mice were taken to determine the contents of β-secretase,α-secre-tase,γ-secretase,LXA4 and acetylcholinesterase(AchE)in the homogenates of brain tissues by ELISA,and their blood was taken to deter-mine the biochemical indexes.[Results]Compared with the normal group,the number of learning tests,number of memory errors,error rate and the contents of β-secretase,γ-secretase and AchE in brain tissue of the mice in the model group were all significantly increased(all P<0.05),the contents of LXA4 in brain tissue were significantly decreased(all P<0.05),and the contents of α-secretase did not change significantly(all P>0.05);compared with the model group,the number of learning tests,the number of memory errors,the error rate and the content of β-secretase,γ-secretase and AchE in brain tissue were all significantly reduced(all P<0.05),the content of LXA4 in brain tissue of the high dose group of honeysuckle chlorogenic acid was significantly increased(P<0.05),and there was no significant change in the content of α-secretase in brain tissue of all groups of honeysuckle chlorogenic acid(all P>0.05).Compared with the normal group,the levels of blood glucose,TC,TG,ALT,BUN,Cr and UA in the model group and the levels of TC,TG and BUN in the low-and medium-dose groups of honeysuckle chlorogenic acid were significantly increased(all P<0.05),and the level of HDL-C in the model group and the levels of UA in the medium-and high-dose groups of honeysuckle chlorogenic acid were significantly decreased(all P<0.05);compared with the model group,the levels of blood glucose,ALT,BUN,UA in each group of honeysuckle chlorogenic acid,the levels of TC and Cr in medium and high dose groups of honeysuckle chlorogenic acid,and the level of TG in the high dose group of honeysuckle chlorogenic acid were all signifi-cantly lower(all P<0.05),while the level of HDL-C in the medium and high dose groups of honeysuckle chlorogenic acid and the level of to-tal protein in the high dose group of honeysuckle chlorogenic acid were all significantly higher(all P<0.05).[Conclusions]Chlorogenic acid from honeysuckle may improve AD induced by aluminum exposure via regulating related secretory enzymes,LXA4,and various biochemi-cal indicators.

采用STAMP-24Model的多组织事故分析

安全生产事故往往由多组织交互、多因素耦合造成,事故原因涉及多个组织。为预防和遏制多组织生产安全事故的发生,基于系统理论事故建模与过程模型(Systems-Theory Accident Modeling and Process,STAMP)、24Model,构建一种用于多组织事故分析的方法,并以青岛石油爆炸事故为例进行事故原因分析。结果显示:STAMP-24Model可以分组织,分层次且有效、全面、详细地分析涉及多个组织的事故原因,探究多组织之间的交互关系;对事故进行动态演化分析,可得到各组织不安全动作耦合关系与形成的事故失效链及管控失效路径,进而为预防多组织事故提供思路和参考。

基于改进24Model-ISM-SNA建筑工人不安全行为关联路径研究

建筑施工现场环境复杂,为有效控制不安全行为发生,基于行为安全“2-4”模型对360份具有代表性的建筑安全事故调查报告进行分析,提取出22个不安全行为的主要影响因素。利用灰色关联分析方法(GRA)改进的集成ISM-SNA模型,将不安全行为风险因素划分为表层、过渡层与深层,然后对风险因素进行可视化分析、中心度分析及凝聚子群分析,揭示了各致因因素间的关联关系和传导路径。结果表明,建筑工人不安全行为影响因素可划分成7级3阶的多级递阶结构,安全意识、现场监管、外部环境是建筑工人不安全行为的关键影响因素,同时现场监管和隐患排查到位能有效降低不安全行为的发生。

Targeting autophagy in Alzheimer's disease:Animal models and mechanisms

Alzheimer's disease(AD)is an age-related progressive neurodegenerative disorder that leads to cognitive impairment and memory loss.Emerging evidence suggests that autophagy plays an important role in the pathogenesis of AD through the regulation of amyloid-beta(Aβ)and tau metabolism,and that autophagy dysfunction exacerbates amyloidosis and tau pathology.Therefore,targeting autophagy may be an effective approach for the treatment of AD.Animal models are considered useful tools for investigating the pathogenic mechanisms and therapeutic strategies of diseases.This review aims to summarize the pathological alterations in autophagy in representative AD animal models and to present recent studies on newly discovered autophagy-stimulating interventions in animal AD models.Finally,the opportunities,difficulties,and future directions of autophagy targeting in AD therapy are discussed.

基于24Model-D-ISM的地铁站火灾疏散影响因素研究

为预防地铁站火灾事故,深入了解地铁站火灾人员疏散影响因素间的内在联系与层次结构,基于第6版“2-4”模型(24Model)分析63起地铁站火灾疏散事故,充分考虑各个因素之间的交互作用,提取19个影响地铁站人员疏散的关键因素,建立地铁站火灾人员疏散影响因素指标体系;采用算子客观赋权法(C-OWA)改进决策试验与评价实验法(DEMATEL),确定地铁站火灾人员疏散的重要影响因素;在此基础上,采用解释结构模型(ISM)分析各个因素间的层次结构及相互作用路径,构建地铁站火灾人员疏散影响因素的多级递阶结构模型。研究结果表明:疏散引导、恐慌从众行为、人员拥挤为地铁站火灾人员疏散的关键影响因素;地铁站火灾人员疏散受表层因素、中间层因素、深层因素共同作用的影响,其中,疏散教育与培训、设施维护与检查、疏散预案等因素是根源影响因素,重视根源影响因素的改善有利于从本质上预防和控制事故的发生。

24Model与LCM原因因素定义对比研究

为探究损失致因模型(LCM)原因因素定义与事故致因“2-4”模型(24Model)存在的异同和优缺点,梳理2个模型各层面原因和结果的定义,对比定义内容及其对事故原因分析等安全实务的指导作用,并以一起瓦斯爆炸事故为例加以实证分析,获得二者分析结果之间的差异。研究结果表明:LCM是首个将管理因素纳入事故致因分析的一维事件序列模型,可明确各层面原因因素的定义和因素间的逻辑关系,但部分定义存在交叉重复的问题,并没有揭示安全工作指导思想等深层次事故致因因素;24Model作为系统性事故致因模型,对各类因素的定义均以组织为主体,描述事件、事故、安全的概念内涵,划分个体安全动作、安全能力和组织安全管理体系的类别并给出含义解析,探究组织安全文化层面的问题并以32个元素体现;2个模型的事故原因分析方法均建立在对各层级原因因素定义的基础上,并适用于模型理论体系本身。

Tau truncation in the pathogenesis of Alzheimer's disease:a narrative review

Alzheimer's disease is characterized by two major neuropathological hallmarks—the extracellularβ-amyloid plaques and intracellular neurofibrillary tangles consisting of aggregated and hyperphosphorylated Tau protein.Recent studies suggest that dysregulation of the microtubuleassociated protein Tau,especially specific proteolysis,could be a driving force for Alzheimer's disease neurodegeneration.Tau physiologically promotes the assembly and stabilization of microtubules,whereas specific truncated fragments are sufficient to induce abnormal hyperphosphorylation and aggregate into toxic oligomers,resulting in them gaining prion-like characteristics.In addition,Tau truncations cause extensive impairments to neural and glial cell functions and animal cognition and behavior in a fragment-dependent manner.This review summarizes over 60 proteolytic cleavage sites and their corresponding truncated fragments,investigates the role of specific truncations in physiological and pathological states of Alzheimer's disease,and summarizes the latest applications of strategies targeting Tau fragments in the diagnosis and treatment of Alzheimer's disease.

Impact of apolipoprotein E isoforms on sporadic Alzheimer's disease:beyond the role of amyloid beta

The impact of apolipoprotein E(ApoE)isoforms on sporadic Alzheimer's disease has long been studied;however,the influences of apolipoprotein E gene(APOE)on healthy and pathological human brains are not fully understood.ApoE exists as three common isoforms(ApoE2,ApoE3,and ApoE4),which differ in two amino acid residues.Traditionally,ApoE binds cholesterol and phospholipids and ApoE isoforms display diffe rent affinities for their receptors,lipids transport and distribution in the brain and periphery.The role of ApoE in the human depends on ApoE isoforms,brain regions,aging,and neural injury.APOE E4 is the strongest genetic risk factor for sporadic Alzheimer's disease,considering its role in influencing amyloid-beta metabolism.The exact mechanisms by which APOE gene variants may increase or decrease Alzheimer's disease risk are not fully understood,but APOE was also known to affect directly and indirectly tau-mediated neurodegeneration,lipids metabolism,neurovascular unit,and microglial function.Consistent with the biological function of ApoE,ApoE4 isoform significantly alte red signaling pathways associated with cholesterol homeostasis,transport,and myelination.Also,the rare protective APOE variants confirm that ApoE plays an important role in Alzheimer's disease pathogenesis.The objectives of the present mini-review were to describe classical and new roles of various ApoE isoforms in Alzheimer's disease pathophysiology beyond the deposition of amyloid-beta and to establish a functional link between APOE,brain function,and memory,from a molecular to a clinical level.APOE genotype also exerted a heterogeneous effect on clinical Alzheimer's disease phenotype and its outcomes.Not only in learning and memory but also in neuro psychiatric symptoms that occur in a premorbid condition.Cla rifying the relationships between Alzheimer's disease-related pathology with neuropsychiatric symptoms,particularly suicidal ideation in Alzheimer's disease patients,may be useful for elucidating also the underlying pathophysiological process and its prognosis.Also,the effects of anti-amyloid-beta drugs,recently approved for the treatment of Alzheimer's disease,could be influenced by the APOE genotype.

Biomaterials-based anti-inflammatory treatment strategies for Alzheimer's disease

The current therapeutic drugs for Alzheimer's disease only improve symptoms,they do not delay disease progression.Therefo re,there is an urgent need for new effective drugs.The underlying pathogenic factors of Alzheimer's disease are not clear,but neuroinflammation can link various hypotheses of Alzheimer's disease;hence,targeting neuroinflammation may be a new hope for Alzheimer's disease treatment.Inhibiting inflammation can restore neuronal function,promote neuro regeneration,reduce the pathological burden of Alzheimer's disease,and improve or even reverse symptoms of Alzheimer's disease.This review focuses on the relationship between inflammation and various pathological hypotheses of Alzheimer's disease;reports the mechanisms and characteristics of small-molecule drugs(e.g.,nonsteroidal anti-inflammatory drugs,neurosteroids,and plant extracts);macromolecule drugs(e.g.,peptides,proteins,and gene therapeutics);and nanocarriers(e.g.,lipid-based nanoparticles,polymeric nanoparticles,nanoemulsions,and inorganic nanoparticles)in the treatment of Alzheimer's disease.The review also makes recommendations for the prospective development of anti-inflammatory strategies based on nanocarriers for the treatment of Alzheimer's disease.

SIRT2 as a potential new therapeutic target for Alzheimer's disease

Alzheimer's disease is the most common cause of dementia globally with an increasing incidence over the years,bringing a heavy burden to individuals and society due to the lack of an effective treatment.In this context,sirtuin 2,the sirtuin with the highest expression in the brain,has emerged as a potential therapeutic target for neurodegenerative diseases.This review summarizes and discusses the complex roles of sirtuin 2 in different molecular mechanisms involved in Alzheimer's disease such as amyloid and tau pathology,microtubule stability,neuroinflammation,myelin formation,autophagy,and oxidative stress.The role of sirtuin 2 in all these processes highlights its potential implication in the etiology and development of Alzheimer's disease.However,its presence in different cell types and its enormous variety of substrates leads to apparently contra dictory conclusions when it comes to understanding its specific functions.Further studies in sirtuin 2 research with selective sirtuin2 modulators targeting specific sirtuin 2 substrates are necessary to clarify its specific functions under different conditions and to validate it as a novel pharmacological target.This will contribute to the development of new treatment strategies,not only for Alzheimer's disease but also for other neurodegenerative diseases.

Gut dysbiosis aggravates cognitive deficits,amyloid pathology and lipid metabolism dysregulation in a transgenic mouse model of Alzheimer's disease

Gut dysbiosis,a well-known risk factor to triggers the progression of Alzheimer's disease(AD),is strongly associated with metabolic disturbance.Trimethylamine N-oxide(TMAO),produced in the dietary choline metabolism,has been found to accelerate neurodegeneration in AD pathology.In this study,the cognitive function and gut microbiota of TgCRND8(Tg)mice of different ages were evaluated by Morris water maze task(MWMT)and 16S rRNA sequencing,respectively.Young pseudo germ-free(PGF)Tg mice that received faecal microbiota transplants from aged Tg mice and wild-type(WT)mice were selected to determine the role of the gut microbiota in the process of neuropathology.Excessive choline treatment for Tg mice was used to investigate the role of abnormal choline metabolism on the cognitive functions.Our results showed that gut dysbiosis,neuroinflammation response,Ab deposition,tau hyperphosphorylation,TMAO overproduction and cyclin-dependent kinase 5(CDK5)/transcription 3(STAT3)activation occurred in Tg mice age-dependently.Disordered microbiota of aged Tg mice accelerated AD pathology in young Tg mice,with the activation of CDK5/STAT3 signaling in the brains.On the contrary,faecal microbiota transplantation from WT mice alleviated the cognitive deficits,attenuated neuroinflammation,Ab deposition,tau hyperphosphorylation,TMAO overproduction and suppressed CDK5/STAT3 pathway activation in Tg mice.Moreover,excessive choline treatment was also shown to aggravate the cognitive deficits,Ab deposition,neuroinflammation and CDK5/STAT3 pathway activation.These findings provide a novel insight into the interaction between gut dysbiosis and AD progression,clarifying the important roles of gut microbiota-derived substances such as TMAO in AD neuropathology.

Projecting Wintertime Newly Formed Arctic Sea Ice through Weighting CMIP6 Model Performance and Independence

Precipitous Arctic sea-ice decline and the corresponding increase in Arctic open-water areas in summer months give more space for sea-ice growth in the subsequent cold seasons. Compared to the decline of the entire Arctic multiyear sea ice,changes in newly formed sea ice indicate more thermodynamic and dynamic information on Arctic atmosphere–ocean–ice interaction and northern mid–high latitude atmospheric teleconnections. Here, we use a large multimodel ensemble from phase 6 of the Coupled Model Intercomparison Project(CMIP6) to investigate future changes in wintertime newly formed Arctic sea ice. The commonly used model-democracy approach that gives equal weight to each model essentially assumes that all models are independent and equally plausible, which contradicts with the fact that there are large interdependencies in the ensemble and discrepancies in models' performances in reproducing observations. Therefore, instead of using the arithmetic mean of well-performing models or all available models for projections like in previous studies, we employ a newly developed model weighting scheme that weights all models in the ensemble with consideration of their performance and independence to provide more reliable projections. Model democracy leads to evident bias and large intermodel spread in CMIP6 projections of newly formed Arctic sea ice. However, we show that both the bias and the intermodel spread can be effectively reduced by the weighting scheme. Projections from the weighted models indicate that wintertime newly formed Arctic sea ice is likely to increase dramatically until the middle of this century regardless of the emissions scenario.Thereafter, it may decrease(or remain stable) if the Arctic warming crosses a threshold(or is extensively constrained).

Magnesium-L-threonate treats Alzheimer's disease by modulating the microbiota-gut-brain axis

Disturbances in the microbiota-gut-brain axis may contribute to the development of Alzheimer's disease. Magnesium-L-threonate has recently been found to have protective effects on learning and memory in aged and Alzheimer's disease model mice. However, the effects of magnesium-L-threonate on the gut microbiota in Alzheimer's disease remain unknown. Previously, we reported that magnesium-L-threonate treatment improved cognition and reduced oxidative stress and inflammation in a double-transgenic line of Alzheimer's disease model mice expressing the amyloid-β precursor protein and mutant human presenilin 1(APP/PS1). Here, we performed 16S r RNA amplicon sequencing and liquid chromatography-mass spectrometry to analyze changes in the microbiome and serum metabolome following magnesium-Lthreonate exposure in a similar mouse model. Magnesium-L-threonate modulated the abundance of three genera in the gut microbiota, decreasing Allobaculum and increasing Bifidobacterium and Turicibacter. We also found that differential metabolites in the magnesiumL-threonate-regulated serum were enriched in various pathways associated with neurodegenerative diseases. The western blotting detection on intestinal tight junction proteins(zona occludens 1, occludin, and claudin-5) showed that magnesium-L-threonate repaired the intestinal barrier dysfunction of APP/PS1 mice. These findings suggest that magnesium-L-threonate may reduce the clinical manifestations of Alzheimer's disease through the microbiota-gut-brain axis in model mice, providing an experimental basis for the clinical treatment of Alzheimer's disease.

Anisotropic time-dependent behaviors of shale under direct shearing and associated empirical creep models

Understanding the anisotropic creep behaviors of shale under direct shearing is a challenging issue.In this context,we conducted shear-creep and steady-creep tests on shale with five bedding orientations (i.e.0°,30°,45°,60°,and 90°),under multiple levels of direct shearing for the first time.The results show that the anisotropic creep of shale exhibits a significant stress-dependent behavior.Under a low shear stress,the creep compliance of shale increases linearly with the logarithm of time at all bedding orientations,and the increase depends on the bedding orientation and creep time.Under high shear stress conditions,the creep compliance of shale is minimal when the bedding orientation is 0°,and the steady-creep rate of shale increases significantly with increasing bedding orientations of 30°,45°,60°,and 90°.The stress-strain values corresponding to the inception of the accelerated creep stage show an increasing and then decreasing trend with the bedding orientation.A semilogarithmic model that could reflect the stress dependence of the steady-creep rate while considering the hardening and damage process is proposed.The model minimizes the deviation of the calculated steady-state creep rate from the observed value and reveals the behavior of the bedding orientation's influence on the steady-creep rate.The applicability of the five classical empirical creep models is quantitatively evaluated.It shows that the logarithmic model can well explain the experimental creep strain and creep rate,and it can accurately predict long-term shear creep deformation.Based on an improved logarithmic model,the variations in creep parameters with shear stress and bedding orientations are discussed.With abovementioned findings,a mathematical method for constructing an anisotropic shear creep model of shale is proposed,which can characterize the nonlinear dependence of the anisotropic shear creep behavior of shale on the bedding orientation.

Efficacy of exercise rehabilitation for managing patients with Alzheimer's disease

Alzheimer's disease(AD) is a progressive and degenerative neurological disease characterized by the deterioration of cognitive functions. While a definitive cure and optimal medication to impede disease progression are currently unavailable, a plethora of studies have highlighted the potential advantages of exercise rehabilitation for managing this condition. Those studies show that exercise rehabilitation can enhance cognitive function and improve the quality of life for individuals affected by AD. Therefore, exercise rehabilitation has been regarded as one of the most important strategies for managing patients with AD. Herein, we provide a comprehensive analysis of the currently available findings on exercise rehabilitation in patients with AD, with a focus on the exercise types which have shown efficacy when implemented alone or combined with other treatment methods, as well as the potential mechanisms underlying these positive effects. Specifically, we explain how exercise may improve the brain microenvironment and neuronal plasticity. In conclusion, exercise is a cost-effective intervention to enhance cognitive performance and improve quality of life in patients with mild to moderate cognitive dysfunction. Therefore, it can potentially become both a physical activity and a tailored intervention. This review may aid the development of more effective and individualized treatment strategies to address the challenges imposed by this debilitating disease, especially in low-and middle-income countries.

Development and validation of a prediction model for early screening of people at high risk for colorectal cancer

BACKGROUND Colorectal cancer(CRC)is a serious threat worldwide.Although early screening is suggested to be the most effective method to prevent and control CRC,the current situation of early screening for CRC is still not optimistic.In China,the incidence of CRC in the Yangtze River Delta region is increasing dramatically,but few studies have been conducted.Therefore,it is necessary to develop a simple and efficient early screening model for CRC.AIM To develop and validate an early-screening nomogram model to identify individuals at high risk of CRC.METHODS Data of 64448 participants obtained from Ningbo Hospital,China between 2014 and 2017 were retrospectively analyzed.The cohort comprised 64448 individuals,of which,530 were excluded due to missing or incorrect data.Of 63918,7607(11.9%)individuals were considered to be high risk for CRC,and 56311(88.1%)were not.The participants were randomly allocated to a training set(44743)or validation set(19175).The discriminatory ability,predictive accuracy,and clinical utility of the model were evaluated by constructing and analyzing receiver operating characteristic(ROC)curves and calibration curves and by decision curve analysis.Finally,the model was validated internally using a bootstrap resampling technique.RESULTS Seven variables,including demographic,lifestyle,and family history information,were examined.Multifactorial logistic regression analysis revealed that age[odds ratio(OR):1.03,95%confidence interval(CI):1.02-1.03,P<0.001],body mass index(BMI)(OR:1.07,95%CI:1.06-1.08,P<0.001),waist circumference(WC)(OR:1.03,95%CI:1.02-1.03 P<0.001),lifestyle(OR:0.45,95%CI:0.42-0.48,P<0.001),and family history(OR:4.28,95%CI:4.04-4.54,P<0.001)were the most significant predictors of high-risk CRC.Healthy lifestyle was a protective factor,whereas family history was the most significant risk factor.The area under the curve was 0.734(95%CI:0.723-0.745)for the final validation set ROC curve and 0.735(95%CI:0.728-0.742)for the training set ROC curve.The calibration curve demonstrated a high correlation between the CRC high-risk population predicted by the nomogram model and the actual CRC high-risk population.CONCLUSION The early-screening nomogram model for CRC prediction in high-risk populations developed in this study based on age,BMI,WC,lifestyle,and family history exhibited high accuracy.

Geostatistical seismic inversion and 3D modelling of metric flow units,porosity and permeability in Brazilian presalt reservoir

Flow units(FU)rock typing is a common technique for characterizing reservoir flow behavior,producing reliable porosity and permeability estimation even in complex geological settings.However,the lateral extrapolation of FU away from the well into the whole reservoir grid is commonly a difficult task and using the seismic data as constraints is rarely a subject of study.This paper proposes a workflow to generate numerous possible 3D volumes of flow units,porosity and permeability below the seismic resolution limit,respecting the available seismic data at larger scales.The methodology is used in the Mero Field,a Brazilian presalt carbonate reservoir located in the Santos Basin,who presents a complex and heterogenic geological setting with different sedimentological processes and diagenetic history.We generated metric flow units using the conventional core analysis and transposed to the well log data.Then,given a Markov chain Monte Carlo algorithm,the seismic data and the well log statistics,we simulated acoustic impedance,decametric flow units(DFU),metric flow units(MFU),porosity and permeability volumes in the metric scale.The aim is to estimate a minimum amount of MFU able to calculate realistic scenarios porosity and permeability scenarios,without losing the seismic lateral control.In other words,every porosity and permeability volume simulated produces a synthetic seismic that match the real seismic of the area,even in the metric scale.The achieved 3D results represent a high-resolution fluid flow reservoir modelling considering the lateral control of the seismic during the process and can be directly incorporated in the dynamic characterization workflow.

耦合优化蚁群算法与P-Median model的选址模型设计

为节省城建部门对于公共体育设施的投入成本以及提高城市人民生活质量,以运动场所优化选址为例,提出一种新型设施选址模型。该模型主要基于P-Median model(最小化阻抗模型)根据需求点数量从全部候选设施选址中选择设施空间位置,让用户达到离自己最近设施距离成本总和最小的目的,对选址的基本原则和实际情况提出要求,构造目标函数用于优化后蚁群算法求解进行选址工作。优化蚁群算法实现基于Python语言模块,通过改进蚁群原始信息素,提升原有算法的收敛速度,求出目标函数最优解,可以很好地模拟对于运动场所的选址。用二者耦合进行优势互补所设计的选址模型来搜寻研究区蚁群信息素浓度残留最大的栅格像元,从而确定未被已有设施点服务半径覆盖的最佳设施点建立位置。实验结果表明,该新型选址模型相较于最小化阻抗模型与最大化覆盖模型,新增优化设施点使整体服务半径覆盖率分别高出10.42%和6.95%,适合求解较为精确且小规模空间下的选址问题。

Toward a Learnable Climate Model in the Artificial Intelligence Era

Artificial intelligence(AI)models have significantly impacted various areas of the atmospheric sciences,reshaping our approach to climate-related challenges.Amid this AI-driven transformation,the foundational role of physics in climate science has occasionally been overlooked.Our perspective suggests that the future of climate modeling involves a synergistic partnership between AI and physics,rather than an“either/or”scenario.Scrutinizing controversies around current physical inconsistencies in large AI models,we stress the critical need for detailed dynamic diagnostics and physical constraints.Furthermore,we provide illustrative examples to guide future assessments and constraints for AI models.Regarding AI integration with numerical models,we argue that offline AI parameterization schemes may fall short of achieving global optimality,emphasizing the importance of constructing online schemes.Additionally,we highlight the significance of fostering a community culture and propose the OCR(Open,Comparable,Reproducible)principles.Through a better community culture and a deep integration of physics and AI,we contend that developing a learnable climate model,balancing AI and physics,is an achievable goal.