Landscape ecological risk assessment and its driving factors in the Weihe River basin,China

Weihe River basin is of great significance to analyze the changes of land use pattern and landscape ecological risk and to improve the ecological basis of regional development.Based on land use data of the Weihe River basin in 2000,2010,and 2020,with the support of Aeronautical Reconnaissance Coverage Geographic Information System(ArcGIS),GeoDa,and other technologies,this study analyzed the spatial-temporal characteristics and driving factors of land use pattern and landscape ecological risk.Results showed that land use structure of the Weihe River basin has changed significantly,with the decrease of cropland and the increase of forest land and construction land.In the past 20 a,cropland has decreased by 7347.70 km2,and cropland was mainly converted into forest land,grassland,and construction land.The fragmentation and dispersion of ecological landscape pattern in the Weihe River basin were improved,and land use pattern became more concentrated.Meanwhile,landscape ecological risk of the Weihe River basin has been improved.Severe landscape ecological risk area decreased by 19,177.87 km2,high landscape ecological risk area decreased by 3904.35 km2,and moderate and low landscape ecological risk areas continued to increase.It is worth noting that landscape ecological risks in the upper reaches of the Weihe River basin are still relatively serious,especially in the contiguous areas of high ecological risk,such as Tianshui,Pingliang,Dingxi areas and some areas of Ningxia Hui Autonomous Region.Landscape ecological risk showed obvious spatial dependence,and high ecological risk area was concentrated.Among the driving factors,population density,precipitation,normalized difference vegetation index(NDVI),and their interactions are the most important factors affecting the landscape ecological risk of the Weihe River basin.The findings significantly contribute to our understanding of the ecological dynamics in the Weihe River basin,providing crucial insights for sustainable management in the region.

Prediction and driving factors of forest fire occurrence in Jilin Province,China

Forest fires are natural disasters that can occur suddenly and can be very damaging,burning thousands of square kilometers.Prevention is better than suppression and prediction models of forest fire occurrence have developed from the logistic regression model,the geographical weighted logistic regression model,the Lasso regression model,the random forest model,and the support vector machine model based on historical forest fire data from 2000 to 2019 in Jilin Province.The models,along with a distribution map are presented in this paper to provide a theoretical basis for forest fire management in this area.Existing studies show that the prediction accuracies of the two machine learning models are higher than those of the three generalized linear regression models.The accuracies of the random forest model,the support vector machine model,geographical weighted logistic regression model,the Lasso regression model,and logistic model were 88.7%,87.7%,86.0%,85.0%and 84.6%,respectively.Weather is the main factor affecting forest fires,while the impacts of topography factors,human and social-economic factors on fire occurrence were similar.

Biological factors driving colorectal cancer metastasis

Approximately 20%of colorectal cancer(CRC)patients present with metastasis at diagnosis.Among Stage I-III CRC patients who undergo surgical resection,18%typically suffer from distal metastasis within the first three years following initial treatment.The median survival duration after the diagnosis of metastatic CRC(mCRC)is only 9 mo.mCRC is traditionally considered to be an advanced stage malignancy or is thought to be caused by incomplete resection of tumor tissue,allowing cancer cells to spread from primary to distant organs;however,increa-sing evidence suggests that the mCRC process can begin early in tumor development.CRC patients present with high heterogeneity and diverse cancer phenotypes that are classified on the basis of molecular and morphological alterations.Different genomic and nongenomic events can induce subclone diversity,which leads to cancer and metastasis.Throughout the course of mCRC,metastatic cascades are associated with invasive cancer cell migration through the circulatory system,extravasation,distal seeding,dormancy,and reactivation,with each step requiring specific molecular functions.However,cancer cells presenting neoantigens can be recognized and eliminated by the immune system.In this review,we explain the biological factors that drive CRC metastasis,namely,genomic instability,epigenetic instability,the metastatic cascade,the cancer-immunity cycle,and external lifestyle factors.Despite remarkable progress in CRC research,the role of molecular classification in therapeutic intervention remains unclear.This review shows the driving factors of mCRC which may help in identifying potential candidate biomarkers that can improve the diagnosis and early detection of mCRC cases.

Analysis of the Spatiotemporal Variation Characteristics and Driving Factors of Land Vegetation GPP in a Certain Region of Asia

Gross primary productivity (GPP) of vegetation is a critical indicator of ecosystem growth and carbon sequestration. The spatiotemporal variation characteristics of land vegetation GPP trends in a specific region of Asia from 2001 to 2020 were analyzed by Sen and MK trend analysis methods in this study .Moreover , a GPP change attribution model was established to explore the driving influences of factors such as Leaf Area Index (LAI), Land Surface Temperature (LST), Vapor Pressure Deficit (VPD), Soil Moisture, Solar Radiation and Wind Speed on GPP. The results indicate that summer GPP values are significantly higher than those in other months, accounting for 60.8% of the annual total GPP;spring and autumn contribute 18.91% and 13.04%, respectively. In winter, due to vegetation being nearly dormant, the contribution is minimal at 7.19%. Spatially, GPP shows a decreasing trend from southeast to northwest. LAI primarily drives the spatial and seasonal variations of regional GPP, while VPD, surface temperature, solar radiation, and soil moisture have varying impacts on GPP across different dimensions. Additionally, wind speed exhibits a minor contribution to GPP across different dimensions.

Land use change and its driving factors in the ecological function area:A case study in the Hedong Region of the Gansu Province,China

Land use and cover change(LUCC)is important for the provision of ecosystem services.An increasing number of recent studies link LUCC processes to ecosystem services and human well-being at different scales recently.However,the dynamic of land use and its drivers receive insufficient attention within ecological function areas,particularly in quantifying the dynamic roles of climate change and human activities on land use based on a long time series.This study utilizes geospatial analysis and geographical detectors to examine the temporal dynamics of land use patterns and their underlying drivers in the Hedong Region of the Gansu Province from 1990 to 2020.Results indicated that grassland,cropland,and forestland collectively accounted for approximately 99% of the total land area.Cropland initially increased and then decreased after 2000,while grassland decreased with fluctuations.In contrast,forestland and construction land were continuously expanded,with net growth areas of 6235.2 and 455.9 km^(2),respectively.From 1990 to 2020,cropland was converted to grassland,and both of them were converted to forestland as a whole.The expansion of construction land primarily originated from cropland.From 2000 to 2005,land use experienced intensified temporal dynamics and a shift of relatively active zones from the central to the southeastern region.Grain yield,economic factors,and precipitation were the major factors accounting for most land use changes.Climatic impacts on land use changes were stronger before 1995,succeeded by the impact of animal husbandry during 1995-2000,followed by the impacts of grain production and gross domestic product(GDP)after 2000.Moreover,agricultural and pastoral activities,coupled with climate change,exhibited stronger enhancement effects after 2000 through their interaction with population and economic factors.These patterns closely correlated with ecological restoration projects in China since 1999.This study implies the importance of synergy between human activity and climate change for optimizing land use via ecological patterns in the ecological function area.

Surface ozone in global cities:A synthesis of basic features,exposure risk,and leading meteorological driving factors

Long-term exposure to high surface ozone(O_(3))concentrations,a complex oxidative atmospheric pollutant,can adversely impact human health.Based on O_(3)monitoring data from 261 cities worldwide in 2020,generalized additive model(GAM)and spatial data analysis(SDA)methods were applied in this study to quantitatively evaluate the spatiotemporal distribution of O_(3)concentration,exposure risk,and dominant meteorological factors.Results indicated that over 40%of the cities worldwide were exposed to harmful O_(3)concentration ranges(40-60μg/m^(3)),with most cities distributed in China and India.Moreover,significant seasonal variations in global O_(3)concentrations were observed,presenting as summer(45.6μg/m^(3))>spring(47.3μg/m^(3))>autumn(38.0μg/m^(3))>winter(33.6μg/m^(3)).Exposure analysis revealed that approximately 12.2%of the population in 261 cities were exposed to an environment with high O_(3)concentrations(80-160μg/m^(3)),with about 36.32 million people in major countries.Thus,the persistent increase in high O_(3)levels worldwide is a critical factor contributing to threats to human health.Furthermore,GAM results indicated temperature,relative humidity,and wind speed as primary determinants of O_(3)variability.The synergy of meteorological factors is critical for understanding O_(3)changes.Our findings are important for enforcing robust air quality policies and mitigating public risk.

Age-related driving mechanisms of retinal diseases and neuroprotection by transcription factor EB-targeted therapy

Retinal aging has been recognized as a significant risk factor for various retinal disorders,including diabetic retinopathy,age-related macular degeneration,and glaucoma,following a growing understanding of the molecular underpinnings of their development.This comprehensive review explores the mechanisms of retinal aging and investigates potential neuroprotective approaches,focusing on the activation of transcription factor EB.Recent meta-analyses have demonstrated promising outcomes of transcription factor EB-targeted strategies,such as exercise,calorie restriction,rapamycin,and metformin,in patients and animal models of these common retinal diseases.The review critically assesses the role of transcription factor EB in retinal biology during aging,its neuroprotective effects,and its therapeutic potential for retinal disorders.The impact of transcription factor EB on retinal aging is cell-specific,influencing metabolic reprogramming and energy homeostasis in retinal neurons through the regulation of mitochondrial quality control and nutrient-sensing pathways.In vascular endothelial cells,transcription factor EB controls important processes,including endothelial cell proliferation,endothelial tube formation,and nitric oxide levels,thereby influencing the inner blood-retinal barrier,angiogenesis,and retinal microvasculature.Additionally,transcription factor EB affects vascular smooth muscle cells,inhibiting vascular calcification and atherogenesis.In retinal pigment epithelial cells,transcription factor EB modulates functions such as autophagy,lysosomal dynamics,and clearance of the aging pigment lipofuscin,thereby promoting photoreceptor survival and regulating vascular endothelial growth factor A expression involved in neovascularization.These cell-specific functions of transcription factor EB significantly impact retinal aging mechanisms encompassing proteostasis,neuronal synapse plasticity,energy metabolism,microvasculature,and inflammation,ultimately offering protection against retinal aging and diseases.The review emphasizes transcription factor EB as a potential therapeutic target for retinal diseases.Therefore,it is imperative to obtain well-controlled direct experimental evidence to confirm the efficacy of transcription factor EB modulation in retinal diseases while minimizing its risk of adverse effects.

Spatiotemporal Characteristics of Typical Ecosystem Services and Their Spatial Responses to Driving Factors in Ecologically Fragile Areas in Upper Yellow River,China

The identification of dominant driving factors for different ecosystem services(ESs)is crucial for ecological conservation and sustainable development.However,the spatial heterogeneity of the dominant driving factors affecting various ESs has not been adequately elucidated,particularly in ecologically fragile regions.This study employed the integrated valuation of ESs and trade-offs(InVEST)model to evaluate four ESs,namely,water yield(WY),soil conservation(SC),habitat quality(HQ),and carbon storage(CS),and then to identify the dominant driving factors of spatiotemporal differentiation of ES and further to characterize the spatial heterogeneity characteristics of the dominant driving factors in the eco-fragile areas of the upper Yellow River,China from 2000 to 2020.The results demonstrated that WY exhibited northeast-high and northwest-low patterns in the upper Yellow River region,while high values of SC and CS were distributed in central forested areas and a high value of HQ was distributed in vast grassland areas.The CS,WY,and SC exhibited decreasing trends over time.The most critical factors affecting WY,SC,HQ,and CS were the actual evapotranspiration,precipitation,slope,and normalized difference vegetation index,respectively.In addition,the effects of different factors on various ESs exhibited spatial heterogeneity.These results could provide spatial decision support for eco-protection and rehabilitation in ecologically fragile areas.

Multi-scenario Simulation for 2060 and Driving Factors of the Eco-spatial Carbon Sink in the Beibu Gulf Urban Agglomeration, China

Since China announced its goal of becoming carbon-neutral by 2060, carbon neutrality has become a major target in the development of China's urban agglomerations. This study applied the Future Land Use Simulation(FLUS) model to predict the land use pattern of the ecological space of the Beibu Gulf urban agglomeration, in 2060 under ecological priority, agricultural priority and urbanized priority scenarios. The Integrated Valuation of Ecosystem Services and Trade-offs(In VEST) model was employed to analyse the spatial changes in ecological space carbon storage in each scenario from 2020 to 2060. Then, this study used a Geographically Weighted Regression(GWR) model to determine the main driving factors that influence the changes in land carbon sinking capacity. The results of the study can be summarised as follows: firstly, the agricultural and ecological priority scenarios will achieve balanced urban expansion and environmental protection of resources in an ecological space. The urbanized priority scenario will reduce the carbon sinking capacity. Among the simulation scenarios for 2060, carbon storage in the urbanized priority scenario will decrease by 112.26 × 10^(6) t compared with that for 2020 and the average carbon density will decrease by 0.96 kg/m^(2) compared with that for 2020. Carbon storage in the agricultural priority scenario will increase by 84.11 × 10^(6) t, and the average carbon density will decrease by 0.72 kg/m^(2). Carbon storage in the ecological priority scenario will increase by 3.03 × 10^(6) t, and the average carbon density will increase by 0.03 kg/m^(2). Under the premise that the population of the town will increases continuously, the ecological priority development approach may be a wise choice.Secondly, slope, distance to river and elevation are the most important factors that influence the carbon sink pattern of the ecological space in the Beibu Gulf urban agglomeration, followed by GDP, population density, slope direction and distance to traffic infrastructure.At the same time, urban space expansion is the main cause of the changes of this natural factors. Thirdly, the decreasing trend of ecological space is difficult to reverse, so reasonable land use policy to curb the spatial expansion of cities need to be made.

Characteristics and driving factors of abandoned cultivated land in the hilly regions of southern China:A case study in Longnan,Jiangxi Province

The abandonment of cultivated land in southern China was gradually obvious.This research aims to provide a reference for solving the abandonment of cultivated land in hilly regions and promote rural development in China.We examined Longnan county located in the hilly regions of southern China as an example,where abandoned cultivated land is very common.We analyzed its land use data with a field survey to identify the abandoned cultivated land and geospatial characteristics.From the two aspects of social and natural factors,we analyzed the factors driving cultivated land abandonment with the help of Geodetector.The results showed that in 2019,the total area of the abandoned cultivated land in Longnan county was 4,962.35 hm^(2),covering 39.51% of this region.Among the topographic factors,the abandonment rate is positively correlated with elevation and slope gradient,but not with slope direction.Among the land parcel conditions,the abandonment rate is positively correlated with the access to road network and cultivation distance from settlement.At the county level,the abandonment of cultivated land in study area was affected by multiple factors,among which,the direct factor was the reduction in the labor force,such as the decrease of farming laborers and the increase of female population,which made farming unsustainable.Changes in production factors also promoted transformations in farmers’motivation to engage in production,such as the decrease of grain crops and the increase of cash crops,which was the indirect factor affecting cultivated land abandonment.The development of the rural nonagricultural industry affected farmers’enthusiasm,such as the decrease of farming households,which was the fundamental factor leading to cultivated land abandonment in this area.

Spatiotemporal variations of drought and driving factors based on multiple remote sensing drought indices:A case study in karst areas of southwest China

Droughts are recurrent in southwest China due to the fragility and sensitivity of the karst environment.These events have serious impacts on local agricultural output,ecological diversity,and social stability.Understanding spatiotemporal variations and driving factors of drought in this area is of extreme importance for effective mitigation measures.The karst areas situated in southwest China were spatially divided into seven sub-regions according to the topography and degree of karst development.Drought indices,including vegetation condition index(VCI),temperature condition index(TCI),vegetation health index(VHI),normalized vegetation water supply index(NVSWI),and temperature vegetation drought index(TVDI),were calculated from MODIS data during 2000 and 2018for each sub-region,and drought patterns were examined.The results show that droughts were found to be concentrated in sub-regions such as karst basin,karst plateau,karst gorge,and karst depression areas.Furthermore,there were more drought conditions in karst areas than in non-karst areas.In addition,improvements to drought situation in the study period are significant(p<0.05),and mitigation areas respectively account for 80.1%(NVSWI),74.2%(VCI),74.2%(VHI),30.1%(TCI)and 33.2%(TVDI)of the study area,while drought expands slightly(<3.4%)in areas undergoing urban construction.Pearson's correlation coefficients between drought indices and temperature are generally above 0.5 in all sub-regions.However,the correlation coefficients between drought indices and precipitation mostly fall within the range of 0.3-0.4,indicating a weaker correlation.Our explanation for the spatiotemporal patterns of drought is that karst phenomena are the natural basis of drought and agricultural production is one of important driving forces.Positive changes of drought conditions have benefited from efforts to control rocky desertification and restore ecosystems over the past years.

Factors driving surface deformations in plain area of eastern Zhengzhou City,China

With the rapid socio-economic development and urban expansion,land subsidence has emerged as a major environmental issue,impeding the high-quality development of the plain area in eastern Zhengzhou City,Henan Province,China.However,effective prevention and control of land subsidence in this region have been challenging due to the lack of comprehensive surface deformations monitoring and the quantitative analysis of the factors driving these deformations.In order to accurately identify the dominant factor driving surface deformations in the study area,this study utilized the Persistent Scattered Interferometric Synthetic Aperture Radar(PS-InSAR)technique to acquire the spatio-temporal distribution of surface deformations from January 2018 to March 2020.The acquired data was verified using leveling data.Subsequently,GIS spatial analysis was employed to investigate the responses of surface deformations to the driving factors.The findings are as follows:Finally,the geographical detector model was utilized to quantify the contributions of the driving factors and reveal the mechanisms of their interactions.The findings are as follows:(1)Surface deformations in the study area are dominated by land subsidence,concentrated mainly in Zhongmu County,with a deformation rate of−12.5–−37.1 mm/a.In contrast,areas experiencing surface uplift are primarily located downtown,with deformation rates ranging from 0 mm to 8 mm;(2)Groundwater level,lithology,and urban construction exhibit strong spatial correlations with cumulative deformation amplitude;(3)Groundwater level of the second aquifer group is the primary driver of spatially stratified heterogeneity in surface deformations,with a contributive degree of 0.5328.The contributive degrees of driving factors are significantly enhanced through interactions.Groundwater level and the cohesive soil thickness in the second aquifer group show the strongest interactions in the study area.Their total contributive degree increases to 0.5722 after interactions,establishing them as the primary factors influencing surface deformation patterns in the study area.The results of this study can provide a theoretical basis and scientific support for precise prevention and control measures against land subsidence in the study area,as well as contributing to research on the underlying mechanisms.

Evolutionary Decision-Making and Planning for Autonomous Driving Based on Safe and Rational Exploration and Exploitation

Decision-making and motion planning are extremely important in autonomous driving to ensure safe driving in a real-world environment.This study proposes an online evolutionary decision-making and motion planning framework for autonomous driving based on a hybrid data-and model-driven method.First,a data-driven decision-making module based on deep reinforcement learning(DRL)is developed to pursue a rational driving performance as much as possible.Then,model predictive control(MPC)is employed to execute both longitudinal and lateral motion planning tasks.Multiple constraints are defined according to the vehicle’s physical limit to meet the driving task requirements.Finally,two principles of safety and rationality for the self-evolution of autonomous driving are proposed.A motion envelope is established and embedded into a rational exploration and exploitation scheme,which filters out unreasonable experiences by masking unsafe actions so as to collect high-quality training data for the DRL agent.Experiments with a high-fidelity vehicle model and MATLAB/Simulink co-simulation environment are conducted,and the results show that the proposed online-evolution framework is able to generate safer,more rational,and more efficient driving action in a real-world environment.

Evaluation of Postoperative Psychological Distress and Its Driving Factors in Patients with Oral and Maxillofacial Malignant Tumors

Objective:To explore and analyze the evaluation and driving factors of postoperative psychological pain inpatients with oral and maxillofacial malignant tumors.Methods:Relevant data were collected from 80 patients with oral and maxillofacial malignant tumors who attended the outpatient clinic for follow-up consultations between May 2021 to May 2023.The patients used the psychological distress thermometer(DT)to circle words that best described their experiences in the past week,assigning a numerical value(0-10)to indicate their pain level on each day.The scoring results were employed to assess the psychological pain in these patients.A self-developed patient basic information questionnaire was utilized to record demographic details.Logistic regression analysis was employed to evaluate patients two weeks after surgery,focusing on the assessment of psychological distress and the identification and location of driving factors.Results:Following evaluation,the results revealed that the average postoperative DT score for the 80 patients with oral and maxillofacial malignant tumors was 4.53±1.98 points.Scores<4 points indicated no psychological pain(Group N)in 48 cases,while scores≥4 points indicated psychological pain(Group Y)in 32 cases.The differences in postoperative DT scores among patients with varying educational levels,fears and worries about disease progression,economic problems,sleep problems,level of hope,and oral pain were statistically significant(P<0.05).Multiple linear regression analysis results indicated that education level,fear and worry about disease progression,economic problems,sleep problems,level of hope,and oral pain are driving factors of postoperative psychological pain in patients with oral and maxillofacial malignant tumors(P<0.05).Conclusion:The postoperative psychological pain level in patients with oral and maxillofacial malignant tumors is at a moderate level.Educational level,fear and worry about disease progression,economic problems,sleep problems,level of hope,and oral pain were identified as driving factors for postoperative psychological pain in these patients.

Significant risk factors for intensive care unit-acquired weakness:A processing strategy based on repeated machine learning

BACKGROUND Intensive care unit-acquired weakness(ICU-AW)is a common complication that significantly impacts the patient's recovery process,even leading to adverse outcomes.Currently,there is a lack of effective preventive measures.AIM To identify significant risk factors for ICU-AW through iterative machine learning techniques and offer recommendations for its prevention and treatment.METHODS Patients were categorized into ICU-AW and non-ICU-AW groups on the 14th day post-ICU admission.Relevant data from the initial 14 d of ICU stay,such as age,comorbidities,sedative dosage,vasopressor dosage,duration of mechanical ventilation,length of ICU stay,and rehabilitation therapy,were gathered.The relationships between these variables and ICU-AW were examined.Utilizing iterative machine learning techniques,a multilayer perceptron neural network model was developed,and its predictive performance for ICU-AW was assessed using the receiver operating characteristic curve.RESULTS Within the ICU-AW group,age,duration of mechanical ventilation,lorazepam dosage,adrenaline dosage,and length of ICU stay were significantly higher than in the non-ICU-AW group.Additionally,sepsis,multiple organ dysfunction syndrome,hypoalbuminemia,acute heart failure,respiratory failure,acute kidney injury,anemia,stress-related gastrointestinal bleeding,shock,hypertension,coronary artery disease,malignant tumors,and rehabilitation therapy ratios were significantly higher in the ICU-AW group,demonstrating statistical significance.The most influential factors contributing to ICU-AW were identified as the length of ICU stay(100.0%)and the duration of mechanical ventilation(54.9%).The neural network model predicted ICU-AW with an area under the curve of 0.941,sensitivity of 92.2%,and specificity of 82.7%.CONCLUSION The main factors influencing ICU-AW are the length of ICU stay and the duration of mechanical ventilation.A primary preventive strategy,when feasible,involves minimizing both ICU stay and mechanical ventilation duration.

Are TrkB receptor agonists the right tool to fulfill the promises for a therapeutic value of the brain-derived neurotrophic factor?

Brain-derived neurotrophic factor signaling via its receptor tro pomyosin receptor kinase B regulates several crucial physiological processes.It has been shown to act in the brain,promoting neuronal survival,growth,and plasticity as well as in the rest of the body where it is involved in regulating for instance aspects of the metabolism.Due to its crucial and very pleiotro pic activity,reduction of brain-derived neurotrophic factor levels and alterations in the brain-derived neurotrophic factor/tropomyosin receptor kinase B signaling have been found to be associated with a wide spectrum of neurological diseases.Howeve r,because of its poor bioavailability and pharmacological properties,brain-derived neurotrophic factor itself has a very low therapeutic value.Moreover,the concomitant binding of exogenous brain-derived neurotrophic factor to the p75 neurotrophin receptor has the potential to elicit several unwanted and deleterious side effects.Therefo re,developing tools and approaches to specifically promote tropomyosin receptor kinase B signaling has become an important goal of translational research.Among the newly developed tools are different categories of tropomyosin receptor kinase B receptor agonist molecules.In this review,we give a comprehensive description of the diffe rent tro pomyosin receptor kinase B receptor agonist drugs developed so far and of the res ults of their application in animal models of several neurological diseases.Moreover,we discuss the main benefits of tropomyosin receptor kinase B receptor agonists,concentrating especially on the new tropomyosin receptor kinase B agonist antibodies.The benefits observed both in vitro and in vivo upon application of tropomyosin receptor kinase B receptor agonist drugs seem to predominantly depend on their general neuroprotective activity and their ability to promote neuronal plasticity.Moreover,tro pomyosin receptor kinase B agonist antibodies have been shown to specifically bind the tropomyosin receptor kinase B receptor and not p75 neurotrophin receptor.Therefore,while,based on the current knowledge,the tropomyosin receptor kinase B receptor agonists do not seem to have the potential to reve rse the disease pathology per se,promoting brainderived neurotrophic factor/tro pomyosin receptor kinase B signaling still has a very high therapeutic relevance.

Sorl1 knockout inhibits expression of brain-derived neurotrophic factor:involvement in the development of late-onset Alzheimer's disease

Sortilin-related receptor 1(SORL1)is a critical gene associated with late-onset Alzheimer’s disease.SORL1 contributes to the development and progression of this neurodegenerative condition by affecting the transport and metabolism of intracellularβ-amyloid precursor protein.To better understand the underlying mechanisms of SORL1 in the pathogenesis of late-onset Alzheimer s disease,in this study,we established a mouse model of SorI1 gene knockout using cluste red regularly inters paced short palindro mic repeats-associated protein 9 technology.We found that Sorl1-knocko ut mice displayed deficits in learning and memory.Furthermore,the expression of brain-derived neurotrophic factor was significantly downregulated in the hippocampus and co rtex,and amyloidβ-protein deposits were observed in the brains of 5orl1-knockout mice.In vitro,hippocampal neuronal cell synapses from homozygous Sorl1-knockout mice were impaired.The expression of synaptic proteins,including Drebrin and NR2B,was significantly reduced,and also their colocalization.Additionally,by knocking out the Sorl1 gene in N2a cells,we found that expression of the N-methyl-D-aspartate receptor,NR2B,and cyclic adenosine monophosphate-response element binding protein was also inhibited.These findings suggest that SORL1 participates in the pathogenesis of late-onset Alzheimer s disease by regulating the N-methyl-D-aspartate receptor NR2B/cyclic adenosine monophosphate-response element binding protein signaling axis.

Spatial-temporal differentiation and influencing factors of rural settlements in mountainous areas: an example of Liangshan Yi Autonomous Prefecture, Southwestern China

Rural settlement is the basic spatial unit for compact communities in rural area. Scientific exploration of spatial-temporal differentiation and its influencing factors is the premise of spatial layout rationalization. Based on land use data of Liangshan Yi Autonomous Prefecture(hereinafter referred to as Liangshan Prefecture) in Sichuan Province, China from 1980 to 2020, compactness index, fractal dimension, imbalance index, location entropy and the optimal parameters-based geographical detector(OPGD) model are used to analyze the spatial-temporal evolution of the morphological characteristics of rural settlements, and to explore the influence of natural geographical factors, socioeconomic factors, and policy factors on the spatial differentiation of rural settlements. The results show that:(1) From 1980 to 2020, the rural settlements area in Liangshan Prefecture increased by 15.96 km^(2). In space, the rural settlements are generally distributed in a local aggregation, dense in the middle and sparse around the periphery. In 2015, the spatial density and expansion index of rural settlements reached the peak.(2) From 1980 to 2020, the compactness index decreased from 0.7636 to 0.7496, the fractal dimension increased from 1.0283 to 1.0314, and the fragmentation index decreased from 0.1183 to 0.1047. The spatial morphological structure of rural settlements tended to be loose, the shape contour tended to be complex, the degree of fragmentation decreased, and the spatial distribution was significantly imbalanced.(3) The results of OPGD detection in 2015 show that the influence of each factor is slope(0.2371) > traffic accessibility(0.2098) > population(0.1403) > regional GDP(0.1325) > elevation(0.0987) > poverty alleviation(0). The results of OPGD detection in 2020 show that the influence of each factor is slope(0.2339) > traffic accessibility(0.2198) > population(0.1432) > regional GDP(0.1219) > poverty alleviation(0.0992) > elevation(0.093). Natural geographical factors(slope and elevation) are the basic factors affecting the spatial distribution of rural settlements, and rural settlements are widely distributed in the river valley plain and the second half mountain area. Socioeconomic factors(traffic accessibility, population, and regional GDP) have a greater impact on the spatial distribution of rural settlements, which is an important factor affecting the spatial distribution of rural settlements. Policy factors such as poverty alleviation relocation have an indispensable impact on the spatial distribution of rural settlements. The research results can provide decisionmaking basis for the spatial arrangement of rural settlements in Liangshan Prefecture, and optimize the implementation of rural revitalization policies.

Analysis of the influencing factors and clinical related characteristics of pulmonary tuberculosis in patients with type 2 diabetes mellitus

BACKGROUND In China,the prevalence of type 2 diabetes mellitus(T2DM)among diabetic patients is estimated to be between 90%-95%.Additionally,China is among the 22 countries burdened by a high number of tuberculosis cases,with approximately 4.5 million individuals affected by active tuberculosis.Notably,T2DM poses a significant risk factor for the development of tuberculosis,as evidenced by the increased incidence of T2DM coexisting with pulmonary tuberculosis(T2DMPTB),which has risen from 19.3%to 24.1%.It is evident that these two diseases are intricately interconnected and mutually reinforcing in nature.AIM To elucidate the clinical features of individuals diagnosed with both T2DM and tuberculosis(T2DM-PTB),as well as to investigate the potential risk factors associated with active tuberculosis in patients with T2DM.METHODS T2DM-PTB patients who visited our hospital between January 2020 and January 2023 were selected as the observation group,Simple DM patients presenting to our hospital in the same period were the control group,Controls and case groups were matched 1:2 according to the principle of the same sex,age difference(±3)years and disease duration difference(±5)years,patients were investigated for general demographic characteristics,diabetes-related characteristics,body immune status,lifestyle and behavioral habits,univariate and multivariate analysis of the data using conditional logistic regression,calculate the odds ratio(OR)values and 95%CI of OR values.RESULTS A total of 315 study subjects were included in this study,including 105 subjects in the observation group and 210 subjects in the control group.Comparison of the results of both anthropometric and biochemical measures showed that the constitution index,systolic blood pressure,diastolic blood pressure and lymphocyte count were significantly lower in the case group,while fasting blood glucose and high-density lipoprotein cholesterol levels were significantly higher than those in the control group.The results of univariate analysis showed that poor glucose control,hypoproteinemia,lymphopenia,TB contact history,high infection,smoking and alcohol consumption were positively associated with PTB in T2DM patients;married,history of hypertension,treatment of oral hypoglycemic drugs plus insulin,overweight,obesity and regular exercise were negatively associated with PTB in T2DM patients.Results of multivariate stepwise regression analysis found lymphopenia(OR=17.75,95%CI:3.40-92.74),smoking(OR=12.25,95%CI:2.53-59.37),history of TB contact(OR=6.56,95%CI:1.23-35.03)and poor glycemic control(OR=3.37,95%CI:1.11-10.25)was associated with an increased risk of developing PTB in patients with T2DM,While being overweight(OR=0.23,95%CI:0.08-0.72)and obesity(OR=0.11,95%CI:0.02-0.72)was associated with a reduced risk of developing PTB in patients with T2DM.CONCLUSION T2DM-PTB patients are prone to worse glycemic control,higher infection frequency,and a higher proportion of people smoking,drinking alcohol,and lack of exercise.Lymphopenia,smoking,history of TB exposure,poor glycemic control were independent risk factors for T2DM-PTB,and overweight and obesity were associated with reduced risk of concurrent PTB in patients with T2DM.

Assessment of Dependent Performance Shaping Factors in SPAR-H Based on Pearson Correlation Coefficient

With the improvement of equipment reliability,human factors have become the most uncertain part in the system.The standardized Plant Analysis of Risk-Human Reliability Analysis(SPAR-H)method is a reliable method in the field of human reliability analysis(HRA)to evaluate human reliability and assess risk in large complex systems.However,the classical SPAR-H method does not consider the dependencies among performance shaping factors(PSFs),whichmay cause overestimation or underestimation of the risk of the actual situation.To address this issue,this paper proposes a new method to deal with the dependencies among PSFs in SPAR-H based on the Pearson correlation coefficient.First,the dependence between every two PSFs is measured by the Pearson correlation coefficient.Second,the weights of the PSFs are obtained by considering the total dependence degree.Finally,PSFs’multipliers are modified based on the weights of corresponding PSFs,and then used in the calculating of human error probability(HEP).A case study is used to illustrate the procedure and effectiveness of the proposed method.