Landslides pose a formidable natural hazard across the Qinghai-Tibet Plateau(QTP),endangering both ecosystems and human life.Identifying the driving factors behind landslides and accurately assessing susceptibility ar...Landslides pose a formidable natural hazard across the Qinghai-Tibet Plateau(QTP),endangering both ecosystems and human life.Identifying the driving factors behind landslides and accurately assessing susceptibility are key to mitigating disaster risk.This study integrated multi-source historical landslide data with 15 predictive factors and used several machine learning models—Random Forest(RF),Gradient Boosting Regression Trees(GBRT),Extreme Gradient Boosting(XGBoost),and Categorical Boosting(CatBoost)—to generate susceptibility maps.The Shapley additive explanation(SHAP)method was applied to quantify factor importance and explore their nonlinear effects.The results showed that:(1)CatBoost was the best-performing model(CA=0.938,AUC=0.980)in assessing landslide susceptibility,with altitude emerging as the most significant factor,followed by distance to roads and earthquake sites,precipitation,and slope;(2)the SHAP method revealed critical nonlinear thresholds,demonstrating that historical landslides were concentrated at mid-altitudes(1400-4000 m)and decreased markedly above 4000 m,with a parallel reduction in probability beyond 700 m from roads;and(3)landslide-prone areas,comprising 13%of the QTP,were concentrated in the southeastern and northeastern parts of the plateau.By integrating machine learning and SHAP analysis,this study revealed landslide hazard-prone areas and their driving factors,providing insights to support disaster management strategies and sustainable regional planning.展开更多
The effect from the interaction of the alternating current(AC)magnetic field with kilogram-level test mass(TM)limits the detectivity of the TianQin space-based gravitational wave detection.The quantifed effect require...The effect from the interaction of the alternating current(AC)magnetic field with kilogram-level test mass(TM)limits the detectivity of the TianQin space-based gravitational wave detection.The quantifed effect requires the determination of the AC magnetic susceptibilityχ(f)of the TM.A torque method is proposed to measure theχ(f)of kg-level samples at the mHz band with a precision of 1×10^(-7).Combined with our previous work[Phys.Rev.Appl.18044010(2022)],the general frequency-dependent susceptibility of the alloy cube with side length L and electrical conductivityσis determined asχ(f)=χ0+(0.24±0.01)σμ0L^(2)f from 0.1 mHz to 1 Hz.The determination is helpful for the preliminary estimation of the in-band eddy current efect in the TianQin noise budget.The technique can be adopted to accurately measureχ(f)of the actual TM in other precision experiments,where the magnetic noise is a signifcant detection limit.展开更多
The 2019 Typhoon Lekima triggered extensive landslides in Zhejiang Province.To explore the impact of typhoon paths on the distribution of landslide susceptibility,this study proposes a spatiotemporal zoning assessment...The 2019 Typhoon Lekima triggered extensive landslides in Zhejiang Province.To explore the impact of typhoon paths on the distribution of landslide susceptibility,this study proposes a spatiotemporal zoning assessment framework based on typhoon paths and inner rainbands.According to the typhoon landing path and its rainfall impact range,the study area is divided into the typhoon event period(TEP)and the annual non-typhoon period(ANP).The model uses 14 environmental factors,with the only difference between TEP and ANP being the rainfall index:TEP uses 48-hour rainfall during the typhoon,while ANP uses multi-year average annual rainfall.Modeling and comparative analysis were conducted using six machine learning models including random forest(RF)and support vector machine(SVM).The results show that the distribution pattern of high-risk landslide areas during TEP is significantly correlated with typhoon intensity:when the intensity is level 12,high-risk areas are radially distributed;at levels 10-11,they tend to concentrate asymmetrically along the coast;and when the intensity drops to below level 9,the overall susceptibility decreases significantly.During ANP,the distribution of landslides is relatively uniform with no obvious spatial concentration.Analysis on the factor contribution rate indicates that the rainfall weight in TEP is as high as 32.1%,making it the dominant factor;in ANP,the rainfall weight drops to 13.6%while the influence of factors such as slope and topographic wetness index increases,revealing differences in landslide formation mechanisms between the two periods.This study demonstrates that the spatiotemporal zoning method based on typhoon paths can effectively characterize the spatial susceptibility patterns of landslides and improve disaster identification capabilities under extreme weather conditions.The finally generated annual susceptibility zoning map divides the study area into four types of risk regions,providing a reference for dynamic monitoring and differentiated risk management of landslides in typhoon-prone areas.展开更多
This study was aimed to prepare landslide susceptibility maps for the Pithoragarh district in Uttarakhand,India,using advanced ensemble models that combined Radial Basis Function Networks(RBFN)with three ensemble lear...This study was aimed to prepare landslide susceptibility maps for the Pithoragarh district in Uttarakhand,India,using advanced ensemble models that combined Radial Basis Function Networks(RBFN)with three ensemble learning techniques:DAGGING(DG),MULTIBOOST(MB),and ADABOOST(AB).This combination resulted in three distinct ensemble models:DG-RBFN,MB-RBFN,and AB-RBFN.Additionally,a traditional weighted method,Information Value(IV),and a benchmark machine learning(ML)model,Multilayer Perceptron Neural Network(MLP),were employed for comparison and validation.The models were developed using ten landslide conditioning factors,which included slope,aspect,elevation,curvature,land cover,geomorphology,overburden depth,lithology,distance to rivers and distance to roads.These factors were instrumental in predicting the output variable,which was the probability of landslide occurrence.Statistical analysis of the models’performance indicated that the DG-RBFN model,with an Area Under ROC Curve(AUC)of 0.931,outperformed the other models.The AB-RBFN model achieved an AUC of 0.929,the MB-RBFN model had an AUC of 0.913,and the MLP model recorded an AUC of 0.926.These results suggest that the advanced ensemble ML model DG-RBFN was more accurate than traditional statistical model,single MLP model,and other ensemble models in preparing trustworthy landslide susceptibility maps,thereby enhancing land use planning and decision-making.展开更多
Landslide susceptibility prediction(LSP)is significantly affected by the uncertainty issue of landslide related conditioning factor selection.However,most of literature only performs comparative studies on a certain c...Landslide susceptibility prediction(LSP)is significantly affected by the uncertainty issue of landslide related conditioning factor selection.However,most of literature only performs comparative studies on a certain conditioning factor selection method rather than systematically study this uncertainty issue.Targeted,this study aims to systematically explore the influence rules of various commonly used conditioning factor selection methods on LSP,and on this basis to innovatively propose a principle with universal application for optimal selection of conditioning factors.An'yuan County in southern China is taken as example considering 431 landslides and 29 types of conditioning factors.Five commonly used factor selection methods,namely,the correlation analysis(CA),linear regression(LR),principal component analysis(PCA),rough set(RS)and artificial neural network(ANN),are applied to select the optimal factor combinations from the original 29 conditioning factors.The factor selection results are then used as inputs of four types of common machine learning models to construct 20 types of combined models,such as CA-multilayer perceptron,CA-random forest.Additionally,multifactor-based multilayer perceptron random forest models that selecting conditioning factors based on the proposed principle of“accurate data,rich types,clear significance,feasible operation and avoiding duplication”are constructed for comparisons.Finally,the LSP uncertainties are evaluated by the accuracy,susceptibility index distribution,etc.Results show that:(1)multifactor-based models have generally higher LSP performance and lower uncertainties than those of factors selection-based models;(2)Influence degree of different machine learning on LSP accuracy is greater than that of different factor selection methods.Conclusively,the above commonly used conditioning factor selection methods are not ideal for improving LSP performance and may complicate the LSP processes.In contrast,a satisfied combination of conditioning factors can be constructed according to the proposed principle.展开更多
Landslide susceptibility mapping(LSM)plays a crucial role in assessing geological risks.The current LSM techniques face a significant challenge in achieving accurate results due to uncertainties associated with region...Landslide susceptibility mapping(LSM)plays a crucial role in assessing geological risks.The current LSM techniques face a significant challenge in achieving accurate results due to uncertainties associated with regional-scale geotechnical parameters.To explore rainfall-induced LSM,this study proposes a hybrid model that combines the physically-based probabilistic model(PPM)with convolutional neural network(CNN).The PPM is capable of effectively capturing the spatial distribution of landslides by incorporating the probability of failure(POF)considering the slope stability mechanism under rainfall conditions.This significantly characterizes the variation of POF caused by parameter uncertainties.CNN was used as a binary classifier to capture the spatial and channel correlation between landslide conditioning factors and the probability of landslide occurrence.OpenCV image enhancement technique was utilized to extract non-landslide points based on the POF of landslides.The proposed model comprehensively considers physical mechanics when selecting non-landslide samples,effectively filtering out samples that do not adhere to physical principles and reduce the risk of overfitting.The results indicate that the proposed PPM-CNN hybrid model presents a higher prediction accuracy,with an area under the curve(AUC)value of 0.85 based on the landslide case of the Niangniangba area of Gansu Province,China compared with the individual CNN model(AUC=0.61)and the PPM(AUC=0.74).This model can also consider the statistical correlation and non-normal probability distributions of model parameters.These results offer practical guidance for future research on rainfall-induced LSM at the regional scale.展开更多
Dysregulation of neurotransmitter metabolism in the central nervous system contributes to mood disorders such as depression, anxiety, and post–traumatic stress disorder. Monoamines and amino acids are important types...Dysregulation of neurotransmitter metabolism in the central nervous system contributes to mood disorders such as depression, anxiety, and post–traumatic stress disorder. Monoamines and amino acids are important types of neurotransmitters. Our previous results have shown that disco-interacting protein 2 homolog A(Dip2a) knockout mice exhibit brain development disorders and abnormal amino acid metabolism in serum. This suggests that DIP2A is involved in the metabolism of amino acid–associated neurotransmitters. Therefore, we performed targeted neurotransmitter metabolomics analysis and found that Dip2a deficiency caused abnormal metabolism of tryptophan and thyroxine in the basolateral amygdala and medial prefrontal cortex. In addition, acute restraint stress induced a decrease in 5-hydroxytryptamine in the basolateral amygdala. Additionally, Dip2a was abundantly expressed in excitatory neurons of the basolateral amygdala, and deletion of Dip2a in these neurons resulted in hopelessness-like behavior in the tail suspension test. Altogether, these findings demonstrate that DIP2A in the basolateral amygdala may be involved in the regulation of stress susceptibility. This provides critical evidence implicating a role of DIP2A in affective disorders.展开更多
Infrastructure in mountainous regions is particularly vulnerable when exposed to socio-natural hazards associated with extreme events,especially flood events involving the transport of large volumes of sediment and wo...Infrastructure in mountainous regions is particularly vulnerable when exposed to socio-natural hazards associated with extreme events,especially flood events involving the transport of large volumes of sediment and woody debris.In this context,understanding how such processes affect the structural stability of bridges is crucial for effective risk management and the planning of resilient infrastructure.This study examines the impacts of river floods,including large wood and sediment transport,on the“El Blanco Bridge”over the Blanco River in Chaitén,Chilean Patagonia,and the resulting susceptibility of the structure.The 2D Iber model,which solves the shallow water equations,was employed to simulate different flood scenarios as bi-phasic flows(i.e.,water,inorganic and organic sediments,the latter are referred to as large wood,LW),evaluating the hydrodynamic loadings(i.e.pressure distributions and forces)on piers and their susceptibility to sliding,overturning and scouring.Critical flood scenarios that could pose a potential risk of infrastructure failure were identified by separately determining the associated peak discharge,sediment transport rates,LW loads and bed elevation changes.Compared to clear water flows,LW transport resulted in a reduction of the factor of safety against overturning and sliding,indicating higher hydrodynamic loads on the exposed structure.When sediment transport was considered,increasing flood flows slightly augmented maximum scour depth at the base of the piers.This study underscores the significance of hydrodynamic modeling of the Blanco River for natural risk management,and highlights the importance of considering LW transport when quantifying the safety of structures,especially in catchments where easily transportable LW sources may be found(e.g.,in catchments following fires or volcanic eruptions).展开更多
With the rapid urbanization process,ground collapses caused by anthropogenic activities occur frequently.Accurate susceptibility mapping is of great significance for disaster prevention and control.In this study,1198 ...With the rapid urbanization process,ground collapses caused by anthropogenic activities occur frequently.Accurate susceptibility mapping is of great significance for disaster prevention and control.In this study,1198 ground collapse cases in Shenzhen from 2017 to 2020 were collected.Eight effective factors(elevation,relief,clay proportion,average annual precipitation,distance from water,land use type,building density,and road density)were selected to construct the evaluation index system.Ground collapse susceptibility was analyzed and mapped using the normalized frequency ratio(NFR),logistic regression(LR),and NFR-LR coupling models.Finally,the result rationality and performance of the three models were compared through frequency ratio(FR)and ROC curve.The results indicate that all three models can effectively evaluate the ground collapse susceptibility(AUC>0.7),and the NFR-LR model result is more rational and has the best performance(AUC=0.791).The very high and high susceptibility zones cover a total area of 545.68 km^(2) and involve Nanshan,Luohu,and Futian District,as well as some areas of Baoan,Guangming,and Longgang District.The ground collapses in Shenzhen mainly occurred in the built-up areas,and the greater intensity of anthropogenic activities,the more susceptible to the disaster.展开更多
Amid growing typhoon risks driven by climate change with projected shifts in precipitation intensity and temperature patterns,Taiwan faces increasing challenges in flood risk.In response,this study proposes a geograph...Amid growing typhoon risks driven by climate change with projected shifts in precipitation intensity and temperature patterns,Taiwan faces increasing challenges in flood risk.In response,this study proposes a geographic information system(GIS)-based artificial intelligence(AI)model to assess flood susceptibility in Keelung City,integrating geospatial and hydrometeorological data collected during Typhoon Krathon(2024).The model employs the random forest(RF)algorithm,using seven environmental variables excluding average elevation,slope,topographic wetness index(TWI),frequency of cumulative rainfall threshold exceedance,normalized difference vegetation index(NDVI),flow accumulation,and drainage density,with the number of flood events per unit area as the output.The RF model demonstrates high accuracy,achieving the accuracy of 97.45%.Feature importance indicates that NDVI is the most critical predictor,followed by flow accumulation,TWI,and rainfall frequency.Furthermore,under the IPCC AR5 RCP8.5 scenarios,projected 50-year return period rainfall in Keelung City increases by 42.40%-64.95%under+2℃to+4℃warming.These projections were integrated into the RF model to simulate future flood susceptibility.Results indicate two districts in the study area face the greatest increase in flood risk,emphasizing the need for targeted climate adaptation in vulnerable urban areas.展开更多
Various genetic association studies have identified numerous single nucleotide polymorphisms(SNPs)associated with nasopharyngeal carcinoma(NPC)risk.However,these studies have predominantly focused on common variants,l...Various genetic association studies have identified numerous single nucleotide polymorphisms(SNPs)associated with nasopharyngeal carcinoma(NPC)risk.However,these studies have predominantly focused on common variants,leaving the contribution of rare variants to the“missing heritability”largely unexplored.Here,we integrate genotyping data from 3925 NPC cases and 15,048 healthy controls to identify a rare SNP,rs141121474,resulting in a Glu510Lys mutation in KLHDC4 gene linked to increased NPC risk.Subsequent analyses reveal that KLHDC4 is highly expressed in NPC and correlates with poorer prognosis.Functional characterizations demonstrate that KLHDC4 acts as an oncogene in NPC cells,enhancing their migratory and metastatic capabilities,with these effects being further augmented by the Glu510Lys mutation.Mechanistically,the Glu510Lys mutant exhibits increased interaction with Vimentin compared to the wild-type KLHDC4(KLHDC4-WT),leading to elevated Vimentin protein stability and modulation of the epithelial-mesenchymal transition process,thereby promoting tumor metastasis.Moreover,Vimentin knockdown significantly mitigates the oncogenic effects induced by overexpression of both KLHDC4-WT and the Glu510Lys variant.Collectively,our findings highlight the critical role of the rare KLHDC4 variant rs141121474 in NPC progression and propose its potential as a diagnostic and therapeutic target for NPC patients.展开更多
The rice stem borer,Chilo suppressalis(Walker)(Lepidoptera:Crambidae),is one of the most serious pests in rice-growing areas,and it has developed resistance to most insecticides currently used in the field.Cyproflanil...The rice stem borer,Chilo suppressalis(Walker)(Lepidoptera:Crambidae),is one of the most serious pests in rice-growing areas,and it has developed resistance to most insecticides currently used in the field.Cyproflanilide is a novel meta-diamide insecticide that has shown high activities to multiple pests.Evaluating the risk of resistance to cyproflanilide in C.suppressalis is necessary for its preventive resistance management.Here we established the baseline susceptibility of C.suppressalis to cyproflanilide by the rice-seedling dipping method and topical application,and the LC_(50) and LD_(50) values were 0.026 mg L^(-1) and 0.122 ng/larva,respectively.The LC_(50) values of cyproflanilide in 37 field populations ranged from 0.012 to 0.061 mg L^(-1),and 25 field populations exhibited resistance to chlorantraniliprole with the highest LC_(50) value of 3,770.059 mg L^(-1).In addition,a logistic distribution model analysis indicated that only 0.048 mg L^(-1) of cyproflanilide was required to kill 90% field chlorantraniliprole-resistant populations of C.suppressalis,compared to 2,087.764 mg L^(-1) of chlorantraniliprole for a similar level of control.Resistance screening over 19 generations did not result in resistance to cyproflanilide(RR=3.1-fold).The realized heritability(h^(2))of resistance was estimated as 0.067 by using threshold trait analysis,suggesting a low risk of cyproflanilide resistance development in susceptible strains.The Cypro-SEL population(F_(10))had no obvious fitness cost(relative fitness=0.96),and no significant changes in sensitivity to seven tested insecticides.These findings suggested that cyproflanilide is a promising insecticide for the management of chlorantraniliprole-resistant C.suppressalis.Moreover,this integrated risk assessment provides scientific application guidelines for the sustainable resistance management of cyproflanilide for controlling C.suppressalis.展开更多
Monkeypox virus(MPXV),a member of the Orthopoxvirus genus,caused a large-scale global outbreak in 2022.Developing mouse models for MPXV infection is crucial for advancing research on vaccines and therapeutic intervent...Monkeypox virus(MPXV),a member of the Orthopoxvirus genus,caused a large-scale global outbreak in 2022.Developing mouse models for MPXV infection is crucial for advancing research on vaccines and therapeutic interventions.To address this,we conducted a comparative study on the susceptibility of six mouse strains—severe combined immune-deficiency(SCID),nude,genetically diabetic(db/db)and obese(ob/ob),C57BL/6J,and BALB/c—to MPXV infection.Mouse strains were infected with MPXV via intranasal inoculation,and body weight changes and mortality were monitored post-infection.Additionally,the tissue distribution of MPXV and the pathological changes in the lung tissues of the infected mice were evaluated.The results demonstrated that SCID and nude mice exhibited significant weight loss following MPXV infection,with 100%mortality observed in SCID mice,while no mortality occurred in nude mice.In contrast,the other mouse strains showed no significant weight loss or mortality.Notably,the viral load in the lung tissues of SCID and nude mice was the highest among the tested strains.Furthermore,we investigated the impact of different inoculation routes—intranasal(I.N.),intraperitoneal(I.P.),and intravenous(I.V.)—on the pathogenicity of MPXV in mice.The results revealed that the intravenous route induced more pronounced pathogenic effects compared to the intranasal and intraperitoneal routes.In summary,this study provides valuable insights into the development of MPXV-infected mouse models,offering a foundation for further research on MPXV pathogenesis and therapeutic drug development.展开更多
BACKGROUND Folate metabolism gene polymorphisms may play an important role in the pathogenesis of autism spectrum disorder(ASD).However,most studies have primarily used single candidate gene typing strategies(such as ...BACKGROUND Folate metabolism gene polymorphisms may play an important role in the pathogenesis of autism spectrum disorder(ASD).However,most studies have primarily used single candidate gene typing strategies(such as targeted polymerase chain reaction technology),and current findings remain inconsistent.AIM To investigate the association of folate metabolism gene polymorphisms with ASD susceptibility and symptom severity among Chinese children.METHODS Whole-exome sequencing(WES)was conducted to systematically screen for coding region variants of key genes in the folate metabolism pathway among children with ASD,focusing on identifying polymorphisms with high mutation frequencies and potential pathogenic effects.A case-control study was then conducted to explore the association of candidate folate metabolism gene polymorphisms with the susceptibility and severity of ASD.RESULTS WES was performed on 70 children with ASD,and the case-control study included 170 children with ASD and 170 healthy controls.WES revealed that 84.3%(59/70)of children with ASD carried potentially pathogenic variants enriched in folate metabolism pathways.MTHFR C677T and MTRR A66G were significantly associated with an increased risk of ASD in both codominant and dominant models(P<0.05).The dominant model of MTRR A66G was also significantly associated with higher scores in the domains of social relations,body and object use,social and adaptive skills,total scores on the Autism Behavior Checklist,as well as emotional reactivity,nonverbal communication,and activity level on the Childhood Autism Rating Scale(P<0.05).CONCLUSION Most children with ASD carry deleterious variants in folate metabolism-related pathways.MTHFR C677T and MTRR A66G mutations are significantly associated with ASD.展开更多
BACKGROUND Nasopharyngeal carcinoma(NPC),exhibiting high incidence in southern China,is linked to genetic and environmental factors.Vitamin D metabolism,involving transport[group-specific component(GC)protein]and acti...BACKGROUND Nasopharyngeal carcinoma(NPC),exhibiting high incidence in southern China,is linked to genetic and environmental factors.Vitamin D metabolism,involving transport[group-specific component(GC)protein]and activation[25-hydroxylase(CYP2R1)enzyme],may influence NPC susceptibility and radiotherapy response.Polymorphisms in GC and CYP2R1 genes affect protein function and serum 25-hydroxyvitamin D[25(OH)D]levels,and are implicated in other cancers.However,their role in NPC-particularly in high-risk Han Chinese populations-and interaction with vitamin D status remains unclear.This case control study(360 NPC patients,550 controls)investigates these relationships to inform prevention and personalized therapy.AIM To investigate the association between vitamin D binding protein(GC)and CYP2R1 gene polymorphisms with susceptibility to NPC and radiotherapy response.METHODS A case control study design was adopted,and 360 patients with NPC and 550 healthy controls were included.TaqMan method was used to perform genotyping on GC gene loci rs4588,rs7041,and CYP2R1 gene loci rs10741657,rs12794714.Serum 25(OH)D levels were detected,and the relationship between gene polymorphisms and NPC risk and radiotherapy response was analyzed.RESULTS The GC gene rs4588 TT genotype was significantly associated with the risk of NPC in both the codominant model[odds ratio(OR)=1.68,95%CI:1.15-2.45,P=0.007]and the recessive model(OR=1.56,95%CI:1.02-2.38,P=0.039).The association between the rs4588 TT genotype and the risk of NPC was more significant in the male subgroup(OR=1.87,95%CI:1.11-3.15,P=0.019)and the squamous cell carcinoma subgroup(OR=1.89,95%CI:1.19-3.00,P=0.007).The serum 25(OH)D level of the rs7041 AA genotype carriers was significantly lower than that of the CC genotype(P<0.001).The CYP2R1 gene rs10741657 AA genotype was associated with higher serum 25(OH)D levels(P=0.003).The rs12794714 AA genotype was associated with radiotherapy resistance(OR=1.76,95%CI:1.18-2.63,P=0.005).Stratified analysis showed that the association between rs4588 and rs12794714 was significant only in the subgroup with higher 25(OH)D levels.CONCLUSION GC and CYP2R1 genes polymorphisms are associated with NPC susceptibility and radiotherapy response,and this association may be affected by serum 25(OH)D levels.This study provides a new idea for the prevention and individualized treatment in NPC.展开更多
Flooding remains one of the most destructive natural disasters,posing significant risks to both human lives and infrastructure.In India,where a large area is susceptible to flood hazards,the importance of accurate flo...Flooding remains one of the most destructive natural disasters,posing significant risks to both human lives and infrastructure.In India,where a large area is susceptible to flood hazards,the importance of accurate flood frequency analysis(FFA)and flood susceptibility mapping cannot be overstated.This study focuses on the Haora River basin in Tripura,a region prone to frequent flooding due to a combination of natural and anthropogenic factors.This study evaluates the suitability of the Log-Pearson Type Ⅲ(LP-Ⅲ)and Gumbel Extreme Value-1(EV-1)distributions for estimating peak discharges and delineates floodsusceptible zones in the Haora River basin,Tripura.Using 40 years of peak discharge data(1984-2023),the LP-Ⅲ distribution was identified as the most appropriate model based on goodness-of-fit tests.Flood susceptibility mapping,integrating 16 thematic layers through the Analytical Hierarchy Process,identified 8%,64%,and 26%of the area as high,moderate,and low susceptibility zones,respectively,with a model success rate of 0.81.The findings highlight the need for improved flood management strategies,such as enhancing river capacity and constructing flood spill channels.These insights are critical for designing targeted flood mitigation measures in the Haora basin and other flood-prone regions.展开更多
Identifying the factors that contribute to individual susceptibility to cancer is essential for both prevention and treatment.The advancement of biotechnologies,particularly next-generation sequencing,has accelerated ...Identifying the factors that contribute to individual susceptibility to cancer is essential for both prevention and treatment.The advancement of biotechnologies,particularly next-generation sequencing,has accelerated the discovery of genetic variants linked to cancer susceptibility.While hundreds of cancer-susceptibility genes have been identified,they only explain a small fraction of the overall cancer risk,a phenomenon known as"missing heritability".Despite progress,even considering factors such as epistasis,epigenetics,and gene-environment interactions,the missing heritability remains unresolved.Recent research has revealed that an individual's microbiome composition plays a significant role in cancer susceptibility through several mechanisms,such as modulating immune cell activity and influencing the presence or removal of environmental carcinogens.In this review,we examine the multifaceted roles of the microbiome in cancer risk and explore gene-microbiome and environment-microbiome interactions that may contribute to cancer susceptibility.Additionally,we highlight the importance of experimental models,such as collaborative cross mice,and advanced analytical tools,like artificial intelligence,in identifying microbial factors associated with cancer risk.Understanding these microbial determinants can open new avenues for interventions aimed at reducing cancer risk and guide the development of more effective cancer treatments.展开更多
Gold-platinum(Au-Pt)alloy has aroused considerable attention due to its ultra-low magnetic susceptibility(MS)in testing mass(TM)on spacecraft.However,the effect of Au content on the properties of the alloy has not yet...Gold-platinum(Au-Pt)alloy has aroused considerable attention due to its ultra-low magnetic susceptibility(MS)in testing mass(TM)on spacecraft.However,the effect of Au content on the properties of the alloy has not yet been understood.In this study,the composition design of Au-Pt alloy with ultra-low MS was achieved through density functional theory(DFT)and experimental methods.The elastic,thermal properties and electronic structure were systematically investigated,the composition range was further optimized and Au75Pt25 was determined to be the most suitable alloy for TM material.The phase composition of this alloy after cold rolling and solid solution was characterized,indicating a single-phase FCC structure.In addition,there is a good validation between the experimental Vickers hardness and the DFT results.This work provides new insights into the compositional optimization of Au-Pt alloys and lays the foundation for alloy development.展开更多
Rationale:Primary immunodeficiency disorders can be fatal especially in infants.Prompt recognition with a comprehensive medical history,genetic evaluation,and appropriate treatment can be lifesaving in a few subtypes....Rationale:Primary immunodeficiency disorders can be fatal especially in infants.Prompt recognition with a comprehensive medical history,genetic evaluation,and appropriate treatment can be lifesaving in a few subtypes.Patient concerns:A 4-month-old male infant presented with axillary swelling,fever,and ulcerative lesions.Despite care at multiple facilities,symptoms persisted,raising concern for an underlying immunodeficiency.The patient's sibling had similar symptoms and died at six months,suggesting a genetic predisposition.Diagnosis:Mendelian susceptibility to mycobacterial disease,IFNGR2 deficiency.Interventions:The patient was treated with tailored anti-tubercular therapy and azithromycin prophylaxis.Outcomes:Following treatment,the patient’s symptoms have resolved.At 20 months,he is thriving with normal development.Lessons:This case highlights the importance of a thorough medical history and genetic testing in infants with recurrent or unusual infections.Early diagnosis of mendelian susceptibility to mycobacterial disease can lead to effective treatment and better outcomes.展开更多
Landslides pose a significant threat to both human society and environmental sustainability,yet,their spatiotemporal evolution and impacts on global scales in the context of a warming climate remain poorly understood....Landslides pose a significant threat to both human society and environmental sustainability,yet,their spatiotemporal evolution and impacts on global scales in the context of a warming climate remain poorly understood.In this study,we projected global landslide susceptibility under four shared socioeconomic pathways(SSPs)from 2021 to 2100,utilizing multiple machine learning models based on precipitation data from the Coupled Model Intercomparison Project Phase 6(CMIP6)Global Climate Models(GCMs)and static metrics.Our results indicate an overall upward trend in global landslide susceptibility under the SSPs compared to the baseline period(2001–2020),with the most significant increase of about 1%in the very far future(2081–2100)under the high emissions scenario(SSP5-8.5).Currently,approximately 13%of the world’s land area is at very high risk of landslide,mainly in the Cordillera of the Americas and the Andes in South America,the Alps in Europe,the Ethiopian Highlands in Africa,the Himalayas in Asia,and the countries of East and South-East Asia.Notably,India is the country most adversely affected by climate change,particularly during 2081–2100 under SSP3-7.0,with approximately 590 million people—23 times the global average—living in areas categorized as having very high susceptibility.展开更多
基金The National Key Research and Development Program of China,No.2023YFC3206601。
文摘Landslides pose a formidable natural hazard across the Qinghai-Tibet Plateau(QTP),endangering both ecosystems and human life.Identifying the driving factors behind landslides and accurately assessing susceptibility are key to mitigating disaster risk.This study integrated multi-source historical landslide data with 15 predictive factors and used several machine learning models—Random Forest(RF),Gradient Boosting Regression Trees(GBRT),Extreme Gradient Boosting(XGBoost),and Categorical Boosting(CatBoost)—to generate susceptibility maps.The Shapley additive explanation(SHAP)method was applied to quantify factor importance and explore their nonlinear effects.The results showed that:(1)CatBoost was the best-performing model(CA=0.938,AUC=0.980)in assessing landslide susceptibility,with altitude emerging as the most significant factor,followed by distance to roads and earthquake sites,precipitation,and slope;(2)the SHAP method revealed critical nonlinear thresholds,demonstrating that historical landslides were concentrated at mid-altitudes(1400-4000 m)and decreased markedly above 4000 m,with a parallel reduction in probability beyond 700 m from roads;and(3)landslide-prone areas,comprising 13%of the QTP,were concentrated in the southeastern and northeastern parts of the plateau.By integrating machine learning and SHAP analysis,this study revealed landslide hazard-prone areas and their driving factors,providing insights to support disaster management strategies and sustainable regional planning.
基金supported by the National Key R&D Program of China(Grant No.2020YFC2200500)the Key Laboratory of Tian Qin Project(Sun Yat-sen University),Ministry of Education+1 种基金the National Natural Science Foundation of China(Grant Nos.12075325,12005308,and 11605065)the Doctoral Research Foundation Project of Hubei University of Arts and Science(Grant No.kyqdf2059017)。
文摘The effect from the interaction of the alternating current(AC)magnetic field with kilogram-level test mass(TM)limits the detectivity of the TianQin space-based gravitational wave detection.The quantifed effect requires the determination of the AC magnetic susceptibilityχ(f)of the TM.A torque method is proposed to measure theχ(f)of kg-level samples at the mHz band with a precision of 1×10^(-7).Combined with our previous work[Phys.Rev.Appl.18044010(2022)],the general frequency-dependent susceptibility of the alloy cube with side length L and electrical conductivityσis determined asχ(f)=χ0+(0.24±0.01)σμ0L^(2)f from 0.1 mHz to 1 Hz.The determination is helpful for the preliminary estimation of the in-band eddy current efect in the TianQin noise budget.The technique can be adopted to accurately measureχ(f)of the actual TM in other precision experiments,where the magnetic noise is a signifcant detection limit.
基金supported by the project of National Natural Science Foundation of China(Grant No.42371203 and U21A2032)the project Financial Fund of Sichuan Institute of Geological Survey(SCIGSCZDXM-2024008)+1 种基金Sichuan Provincial Science and Technology Department Program Funding(No.2025YFHZ0010)Science and Technology Program of Aba City(NO.R24YYJSYJ0001)。
文摘The 2019 Typhoon Lekima triggered extensive landslides in Zhejiang Province.To explore the impact of typhoon paths on the distribution of landslide susceptibility,this study proposes a spatiotemporal zoning assessment framework based on typhoon paths and inner rainbands.According to the typhoon landing path and its rainfall impact range,the study area is divided into the typhoon event period(TEP)and the annual non-typhoon period(ANP).The model uses 14 environmental factors,with the only difference between TEP and ANP being the rainfall index:TEP uses 48-hour rainfall during the typhoon,while ANP uses multi-year average annual rainfall.Modeling and comparative analysis were conducted using six machine learning models including random forest(RF)and support vector machine(SVM).The results show that the distribution pattern of high-risk landslide areas during TEP is significantly correlated with typhoon intensity:when the intensity is level 12,high-risk areas are radially distributed;at levels 10-11,they tend to concentrate asymmetrically along the coast;and when the intensity drops to below level 9,the overall susceptibility decreases significantly.During ANP,the distribution of landslides is relatively uniform with no obvious spatial concentration.Analysis on the factor contribution rate indicates that the rainfall weight in TEP is as high as 32.1%,making it the dominant factor;in ANP,the rainfall weight drops to 13.6%while the influence of factors such as slope and topographic wetness index increases,revealing differences in landslide formation mechanisms between the two periods.This study demonstrates that the spatiotemporal zoning method based on typhoon paths can effectively characterize the spatial susceptibility patterns of landslides and improve disaster identification capabilities under extreme weather conditions.The finally generated annual susceptibility zoning map divides the study area into four types of risk regions,providing a reference for dynamic monitoring and differentiated risk management of landslides in typhoon-prone areas.
基金the University of Transport Technology under the project entitled“Application of Machine Learning Algorithms in Landslide Susceptibility Mapping in Mountainous Areas”with grant number DTTD2022-16.
文摘This study was aimed to prepare landslide susceptibility maps for the Pithoragarh district in Uttarakhand,India,using advanced ensemble models that combined Radial Basis Function Networks(RBFN)with three ensemble learning techniques:DAGGING(DG),MULTIBOOST(MB),and ADABOOST(AB).This combination resulted in three distinct ensemble models:DG-RBFN,MB-RBFN,and AB-RBFN.Additionally,a traditional weighted method,Information Value(IV),and a benchmark machine learning(ML)model,Multilayer Perceptron Neural Network(MLP),were employed for comparison and validation.The models were developed using ten landslide conditioning factors,which included slope,aspect,elevation,curvature,land cover,geomorphology,overburden depth,lithology,distance to rivers and distance to roads.These factors were instrumental in predicting the output variable,which was the probability of landslide occurrence.Statistical analysis of the models’performance indicated that the DG-RBFN model,with an Area Under ROC Curve(AUC)of 0.931,outperformed the other models.The AB-RBFN model achieved an AUC of 0.929,the MB-RBFN model had an AUC of 0.913,and the MLP model recorded an AUC of 0.926.These results suggest that the advanced ensemble ML model DG-RBFN was more accurate than traditional statistical model,single MLP model,and other ensemble models in preparing trustworthy landslide susceptibility maps,thereby enhancing land use planning and decision-making.
基金funded by the Natural Science Foundation of China(Grant Nos.42377164 and 41972280)the Badong National Observation and Research Station of Geohazards(Grant No.BNORSG-202305).
文摘Landslide susceptibility prediction(LSP)is significantly affected by the uncertainty issue of landslide related conditioning factor selection.However,most of literature only performs comparative studies on a certain conditioning factor selection method rather than systematically study this uncertainty issue.Targeted,this study aims to systematically explore the influence rules of various commonly used conditioning factor selection methods on LSP,and on this basis to innovatively propose a principle with universal application for optimal selection of conditioning factors.An'yuan County in southern China is taken as example considering 431 landslides and 29 types of conditioning factors.Five commonly used factor selection methods,namely,the correlation analysis(CA),linear regression(LR),principal component analysis(PCA),rough set(RS)and artificial neural network(ANN),are applied to select the optimal factor combinations from the original 29 conditioning factors.The factor selection results are then used as inputs of four types of common machine learning models to construct 20 types of combined models,such as CA-multilayer perceptron,CA-random forest.Additionally,multifactor-based multilayer perceptron random forest models that selecting conditioning factors based on the proposed principle of“accurate data,rich types,clear significance,feasible operation and avoiding duplication”are constructed for comparisons.Finally,the LSP uncertainties are evaluated by the accuracy,susceptibility index distribution,etc.Results show that:(1)multifactor-based models have generally higher LSP performance and lower uncertainties than those of factors selection-based models;(2)Influence degree of different machine learning on LSP accuracy is greater than that of different factor selection methods.Conclusively,the above commonly used conditioning factor selection methods are not ideal for improving LSP performance and may complicate the LSP processes.In contrast,a satisfied combination of conditioning factors can be constructed according to the proposed principle.
基金funding support from the National Natural Science Foundation of China(Grant Nos.U22A20594,52079045)Hong-Zhi Cui acknowledges the financial support of the China Scholarship Council(Grant No.CSC:202206710014)for his research at Universitat Politecnica de Catalunya,Barcelona.
文摘Landslide susceptibility mapping(LSM)plays a crucial role in assessing geological risks.The current LSM techniques face a significant challenge in achieving accurate results due to uncertainties associated with regional-scale geotechnical parameters.To explore rainfall-induced LSM,this study proposes a hybrid model that combines the physically-based probabilistic model(PPM)with convolutional neural network(CNN).The PPM is capable of effectively capturing the spatial distribution of landslides by incorporating the probability of failure(POF)considering the slope stability mechanism under rainfall conditions.This significantly characterizes the variation of POF caused by parameter uncertainties.CNN was used as a binary classifier to capture the spatial and channel correlation between landslide conditioning factors and the probability of landslide occurrence.OpenCV image enhancement technique was utilized to extract non-landslide points based on the POF of landslides.The proposed model comprehensively considers physical mechanics when selecting non-landslide samples,effectively filtering out samples that do not adhere to physical principles and reduce the risk of overfitting.The results indicate that the proposed PPM-CNN hybrid model presents a higher prediction accuracy,with an area under the curve(AUC)value of 0.85 based on the landslide case of the Niangniangba area of Gansu Province,China compared with the individual CNN model(AUC=0.61)and the PPM(AUC=0.74).This model can also consider the statistical correlation and non-normal probability distributions of model parameters.These results offer practical guidance for future research on rainfall-induced LSM at the regional scale.
基金supported by the STI 2030—Major Projects 2021ZD0204000,No.2021ZD0204003 (to XZ)the National Natural Science Foundation of China,Nos.32170973 (to XZ),32071018 (to ZH)。
文摘Dysregulation of neurotransmitter metabolism in the central nervous system contributes to mood disorders such as depression, anxiety, and post–traumatic stress disorder. Monoamines and amino acids are important types of neurotransmitters. Our previous results have shown that disco-interacting protein 2 homolog A(Dip2a) knockout mice exhibit brain development disorders and abnormal amino acid metabolism in serum. This suggests that DIP2A is involved in the metabolism of amino acid–associated neurotransmitters. Therefore, we performed targeted neurotransmitter metabolomics analysis and found that Dip2a deficiency caused abnormal metabolism of tryptophan and thyroxine in the basolateral amygdala and medial prefrontal cortex. In addition, acute restraint stress induced a decrease in 5-hydroxytryptamine in the basolateral amygdala. Additionally, Dip2a was abundantly expressed in excitatory neurons of the basolateral amygdala, and deletion of Dip2a in these neurons resulted in hopelessness-like behavior in the tail suspension test. Altogether, these findings demonstrate that DIP2A in the basolateral amygdala may be involved in the regulation of stress susceptibility. This provides critical evidence implicating a role of DIP2A in affective disorders.
基金funded by the ANID Fondecyt Nr.1200091"Unravelling the dynamics and impacts of sediment-laden flows in urban areas in southern Chile as a basis for innovative adaptation(SEDIMPACT)"by principal investigator Bruno Mazzorana.
文摘Infrastructure in mountainous regions is particularly vulnerable when exposed to socio-natural hazards associated with extreme events,especially flood events involving the transport of large volumes of sediment and woody debris.In this context,understanding how such processes affect the structural stability of bridges is crucial for effective risk management and the planning of resilient infrastructure.This study examines the impacts of river floods,including large wood and sediment transport,on the“El Blanco Bridge”over the Blanco River in Chaitén,Chilean Patagonia,and the resulting susceptibility of the structure.The 2D Iber model,which solves the shallow water equations,was employed to simulate different flood scenarios as bi-phasic flows(i.e.,water,inorganic and organic sediments,the latter are referred to as large wood,LW),evaluating the hydrodynamic loadings(i.e.pressure distributions and forces)on piers and their susceptibility to sliding,overturning and scouring.Critical flood scenarios that could pose a potential risk of infrastructure failure were identified by separately determining the associated peak discharge,sediment transport rates,LW loads and bed elevation changes.Compared to clear water flows,LW transport resulted in a reduction of the factor of safety against overturning and sliding,indicating higher hydrodynamic loads on the exposed structure.When sediment transport was considered,increasing flood flows slightly augmented maximum scour depth at the base of the piers.This study underscores the significance of hydrodynamic modeling of the Blanco River for natural risk management,and highlights the importance of considering LW transport when quantifying the safety of structures,especially in catchments where easily transportable LW sources may be found(e.g.,in catchments following fires or volcanic eruptions).
基金jointed supported by the National Natural Science Foundation of China(Nos.41920104007,41731284)。
文摘With the rapid urbanization process,ground collapses caused by anthropogenic activities occur frequently.Accurate susceptibility mapping is of great significance for disaster prevention and control.In this study,1198 ground collapse cases in Shenzhen from 2017 to 2020 were collected.Eight effective factors(elevation,relief,clay proportion,average annual precipitation,distance from water,land use type,building density,and road density)were selected to construct the evaluation index system.Ground collapse susceptibility was analyzed and mapped using the normalized frequency ratio(NFR),logistic regression(LR),and NFR-LR coupling models.Finally,the result rationality and performance of the three models were compared through frequency ratio(FR)and ROC curve.The results indicate that all three models can effectively evaluate the ground collapse susceptibility(AUC>0.7),and the NFR-LR model result is more rational and has the best performance(AUC=0.791).The very high and high susceptibility zones cover a total area of 545.68 km^(2) and involve Nanshan,Luohu,and Futian District,as well as some areas of Baoan,Guangming,and Longgang District.The ground collapses in Shenzhen mainly occurred in the built-up areas,and the greater intensity of anthropogenic activities,the more susceptible to the disaster.
基金supported by the National Science and Technology Council(NSTC),Taiwan(NSTC 114-2119-M-019-003).
文摘Amid growing typhoon risks driven by climate change with projected shifts in precipitation intensity and temperature patterns,Taiwan faces increasing challenges in flood risk.In response,this study proposes a geographic information system(GIS)-based artificial intelligence(AI)model to assess flood susceptibility in Keelung City,integrating geospatial and hydrometeorological data collected during Typhoon Krathon(2024).The model employs the random forest(RF)algorithm,using seven environmental variables excluding average elevation,slope,topographic wetness index(TWI),frequency of cumulative rainfall threshold exceedance,normalized difference vegetation index(NDVI),flow accumulation,and drainage density,with the number of flood events per unit area as the output.The RF model demonstrates high accuracy,achieving the accuracy of 97.45%.Feature importance indicates that NDVI is the most critical predictor,followed by flow accumulation,TWI,and rainfall frequency.Furthermore,under the IPCC AR5 RCP8.5 scenarios,projected 50-year return period rainfall in Keelung City increases by 42.40%-64.95%under+2℃to+4℃warming.These projections were integrated into the RF model to simulate future flood susceptibility.Results indicate two districts in the study area face the greatest increase in flood risk,emphasizing the need for targeted climate adaptation in vulnerable urban areas.
基金supported by the National Natural Science Foundation(82261160657,82102490,and 81572781)the Guangdong Basic and Applied Basic Research Foundation(2024A1515013061)+2 种基金the Sci-Tech Project Foundation of Guangzhou City(2023A04J2141)Chang Jiang Scholars Program(J.-X.B.)the Hong Kong Research Grant Council(RGC)Theme-based Research Scheme Funds(T12-703/22-R and T12-703/23-N).
文摘Various genetic association studies have identified numerous single nucleotide polymorphisms(SNPs)associated with nasopharyngeal carcinoma(NPC)risk.However,these studies have predominantly focused on common variants,leaving the contribution of rare variants to the“missing heritability”largely unexplored.Here,we integrate genotyping data from 3925 NPC cases and 15,048 healthy controls to identify a rare SNP,rs141121474,resulting in a Glu510Lys mutation in KLHDC4 gene linked to increased NPC risk.Subsequent analyses reveal that KLHDC4 is highly expressed in NPC and correlates with poorer prognosis.Functional characterizations demonstrate that KLHDC4 acts as an oncogene in NPC cells,enhancing their migratory and metastatic capabilities,with these effects being further augmented by the Glu510Lys mutation.Mechanistically,the Glu510Lys mutant exhibits increased interaction with Vimentin compared to the wild-type KLHDC4(KLHDC4-WT),leading to elevated Vimentin protein stability and modulation of the epithelial-mesenchymal transition process,thereby promoting tumor metastasis.Moreover,Vimentin knockdown significantly mitigates the oncogenic effects induced by overexpression of both KLHDC4-WT and the Glu510Lys variant.Collectively,our findings highlight the critical role of the rare KLHDC4 variant rs141121474 in NPC progression and propose its potential as a diagnostic and therapeutic target for NPC patients.
基金funded by the National Key Research and Developmental Program of China(2022YFD1700200).
文摘The rice stem borer,Chilo suppressalis(Walker)(Lepidoptera:Crambidae),is one of the most serious pests in rice-growing areas,and it has developed resistance to most insecticides currently used in the field.Cyproflanilide is a novel meta-diamide insecticide that has shown high activities to multiple pests.Evaluating the risk of resistance to cyproflanilide in C.suppressalis is necessary for its preventive resistance management.Here we established the baseline susceptibility of C.suppressalis to cyproflanilide by the rice-seedling dipping method and topical application,and the LC_(50) and LD_(50) values were 0.026 mg L^(-1) and 0.122 ng/larva,respectively.The LC_(50) values of cyproflanilide in 37 field populations ranged from 0.012 to 0.061 mg L^(-1),and 25 field populations exhibited resistance to chlorantraniliprole with the highest LC_(50) value of 3,770.059 mg L^(-1).In addition,a logistic distribution model analysis indicated that only 0.048 mg L^(-1) of cyproflanilide was required to kill 90% field chlorantraniliprole-resistant populations of C.suppressalis,compared to 2,087.764 mg L^(-1) of chlorantraniliprole for a similar level of control.Resistance screening over 19 generations did not result in resistance to cyproflanilide(RR=3.1-fold).The realized heritability(h^(2))of resistance was estimated as 0.067 by using threshold trait analysis,suggesting a low risk of cyproflanilide resistance development in susceptible strains.The Cypro-SEL population(F_(10))had no obvious fitness cost(relative fitness=0.96),and no significant changes in sensitivity to seven tested insecticides.These findings suggested that cyproflanilide is a promising insecticide for the management of chlorantraniliprole-resistant C.suppressalis.Moreover,this integrated risk assessment provides scientific application guidelines for the sustainable resistance management of cyproflanilide for controlling C.suppressalis.
基金financially supported by the National Key Research and Development Program of China(No.2023YFD1800403 and 2023YFD1800404)。
文摘Monkeypox virus(MPXV),a member of the Orthopoxvirus genus,caused a large-scale global outbreak in 2022.Developing mouse models for MPXV infection is crucial for advancing research on vaccines and therapeutic interventions.To address this,we conducted a comparative study on the susceptibility of six mouse strains—severe combined immune-deficiency(SCID),nude,genetically diabetic(db/db)and obese(ob/ob),C57BL/6J,and BALB/c—to MPXV infection.Mouse strains were infected with MPXV via intranasal inoculation,and body weight changes and mortality were monitored post-infection.Additionally,the tissue distribution of MPXV and the pathological changes in the lung tissues of the infected mice were evaluated.The results demonstrated that SCID and nude mice exhibited significant weight loss following MPXV infection,with 100%mortality observed in SCID mice,while no mortality occurred in nude mice.In contrast,the other mouse strains showed no significant weight loss or mortality.Notably,the viral load in the lung tissues of SCID and nude mice was the highest among the tested strains.Furthermore,we investigated the impact of different inoculation routes—intranasal(I.N.),intraperitoneal(I.P.),and intravenous(I.V.)—on the pathogenicity of MPXV in mice.The results revealed that the intravenous route induced more pronounced pathogenic effects compared to the intranasal and intraperitoneal routes.In summary,this study provides valuable insights into the development of MPXV-infected mouse models,offering a foundation for further research on MPXV pathogenesis and therapeutic drug development.
基金Supported by the National Key Research and Development Program of China,No.2024YFC2707801the Science and Technology Innovation Commission of Shenzhen,No.JCYJ20230807143800002.
文摘BACKGROUND Folate metabolism gene polymorphisms may play an important role in the pathogenesis of autism spectrum disorder(ASD).However,most studies have primarily used single candidate gene typing strategies(such as targeted polymerase chain reaction technology),and current findings remain inconsistent.AIM To investigate the association of folate metabolism gene polymorphisms with ASD susceptibility and symptom severity among Chinese children.METHODS Whole-exome sequencing(WES)was conducted to systematically screen for coding region variants of key genes in the folate metabolism pathway among children with ASD,focusing on identifying polymorphisms with high mutation frequencies and potential pathogenic effects.A case-control study was then conducted to explore the association of candidate folate metabolism gene polymorphisms with the susceptibility and severity of ASD.RESULTS WES was performed on 70 children with ASD,and the case-control study included 170 children with ASD and 170 healthy controls.WES revealed that 84.3%(59/70)of children with ASD carried potentially pathogenic variants enriched in folate metabolism pathways.MTHFR C677T and MTRR A66G were significantly associated with an increased risk of ASD in both codominant and dominant models(P<0.05).The dominant model of MTRR A66G was also significantly associated with higher scores in the domains of social relations,body and object use,social and adaptive skills,total scores on the Autism Behavior Checklist,as well as emotional reactivity,nonverbal communication,and activity level on the Childhood Autism Rating Scale(P<0.05).CONCLUSION Most children with ASD carry deleterious variants in folate metabolism-related pathways.MTHFR C677T and MTRR A66G mutations are significantly associated with ASD.
文摘BACKGROUND Nasopharyngeal carcinoma(NPC),exhibiting high incidence in southern China,is linked to genetic and environmental factors.Vitamin D metabolism,involving transport[group-specific component(GC)protein]and activation[25-hydroxylase(CYP2R1)enzyme],may influence NPC susceptibility and radiotherapy response.Polymorphisms in GC and CYP2R1 genes affect protein function and serum 25-hydroxyvitamin D[25(OH)D]levels,and are implicated in other cancers.However,their role in NPC-particularly in high-risk Han Chinese populations-and interaction with vitamin D status remains unclear.This case control study(360 NPC patients,550 controls)investigates these relationships to inform prevention and personalized therapy.AIM To investigate the association between vitamin D binding protein(GC)and CYP2R1 gene polymorphisms with susceptibility to NPC and radiotherapy response.METHODS A case control study design was adopted,and 360 patients with NPC and 550 healthy controls were included.TaqMan method was used to perform genotyping on GC gene loci rs4588,rs7041,and CYP2R1 gene loci rs10741657,rs12794714.Serum 25(OH)D levels were detected,and the relationship between gene polymorphisms and NPC risk and radiotherapy response was analyzed.RESULTS The GC gene rs4588 TT genotype was significantly associated with the risk of NPC in both the codominant model[odds ratio(OR)=1.68,95%CI:1.15-2.45,P=0.007]and the recessive model(OR=1.56,95%CI:1.02-2.38,P=0.039).The association between the rs4588 TT genotype and the risk of NPC was more significant in the male subgroup(OR=1.87,95%CI:1.11-3.15,P=0.019)and the squamous cell carcinoma subgroup(OR=1.89,95%CI:1.19-3.00,P=0.007).The serum 25(OH)D level of the rs7041 AA genotype carriers was significantly lower than that of the CC genotype(P<0.001).The CYP2R1 gene rs10741657 AA genotype was associated with higher serum 25(OH)D levels(P=0.003).The rs12794714 AA genotype was associated with radiotherapy resistance(OR=1.76,95%CI:1.18-2.63,P=0.005).Stratified analysis showed that the association between rs4588 and rs12794714 was significant only in the subgroup with higher 25(OH)D levels.CONCLUSION GC and CYP2R1 genes polymorphisms are associated with NPC susceptibility and radiotherapy response,and this association may be affected by serum 25(OH)D levels.This study provides a new idea for the prevention and individualized treatment in NPC.
文摘Flooding remains one of the most destructive natural disasters,posing significant risks to both human lives and infrastructure.In India,where a large area is susceptible to flood hazards,the importance of accurate flood frequency analysis(FFA)and flood susceptibility mapping cannot be overstated.This study focuses on the Haora River basin in Tripura,a region prone to frequent flooding due to a combination of natural and anthropogenic factors.This study evaluates the suitability of the Log-Pearson Type Ⅲ(LP-Ⅲ)and Gumbel Extreme Value-1(EV-1)distributions for estimating peak discharges and delineates floodsusceptible zones in the Haora River basin,Tripura.Using 40 years of peak discharge data(1984-2023),the LP-Ⅲ distribution was identified as the most appropriate model based on goodness-of-fit tests.Flood susceptibility mapping,integrating 16 thematic layers through the Analytical Hierarchy Process,identified 8%,64%,and 26%of the area as high,moderate,and low susceptibility zones,respectively,with a model success rate of 0.81.The findings highlight the need for improved flood management strategies,such as enhancing river capacity and constructing flood spill channels.These insights are critical for designing targeted flood mitigation measures in the Haora basin and other flood-prone regions.
基金Supported by The United States Department of Defense Breast Cancer Research Program,No.BC190820the National Institutes of Health,No.R01ES031322.
文摘Identifying the factors that contribute to individual susceptibility to cancer is essential for both prevention and treatment.The advancement of biotechnologies,particularly next-generation sequencing,has accelerated the discovery of genetic variants linked to cancer susceptibility.While hundreds of cancer-susceptibility genes have been identified,they only explain a small fraction of the overall cancer risk,a phenomenon known as"missing heritability".Despite progress,even considering factors such as epistasis,epigenetics,and gene-environment interactions,the missing heritability remains unresolved.Recent research has revealed that an individual's microbiome composition plays a significant role in cancer susceptibility through several mechanisms,such as modulating immune cell activity and influencing the presence or removal of environmental carcinogens.In this review,we examine the multifaceted roles of the microbiome in cancer risk and explore gene-microbiome and environment-microbiome interactions that may contribute to cancer susceptibility.Additionally,we highlight the importance of experimental models,such as collaborative cross mice,and advanced analytical tools,like artificial intelligence,in identifying microbial factors associated with cancer risk.Understanding these microbial determinants can open new avenues for interventions aimed at reducing cancer risk and guide the development of more effective cancer treatments.
基金financially supported by the National Key R&D Program of China(No.2021YFC2202300)the National Natural Science Foundation of China(NSFC)(No.51974258)the National College Students Innovation and Entrepreneurship Training Program(No.S202210699134).
文摘Gold-platinum(Au-Pt)alloy has aroused considerable attention due to its ultra-low magnetic susceptibility(MS)in testing mass(TM)on spacecraft.However,the effect of Au content on the properties of the alloy has not yet been understood.In this study,the composition design of Au-Pt alloy with ultra-low MS was achieved through density functional theory(DFT)and experimental methods.The elastic,thermal properties and electronic structure were systematically investigated,the composition range was further optimized and Au75Pt25 was determined to be the most suitable alloy for TM material.The phase composition of this alloy after cold rolling and solid solution was characterized,indicating a single-phase FCC structure.In addition,there is a good validation between the experimental Vickers hardness and the DFT results.This work provides new insights into the compositional optimization of Au-Pt alloys and lays the foundation for alloy development.
文摘Rationale:Primary immunodeficiency disorders can be fatal especially in infants.Prompt recognition with a comprehensive medical history,genetic evaluation,and appropriate treatment can be lifesaving in a few subtypes.Patient concerns:A 4-month-old male infant presented with axillary swelling,fever,and ulcerative lesions.Despite care at multiple facilities,symptoms persisted,raising concern for an underlying immunodeficiency.The patient's sibling had similar symptoms and died at six months,suggesting a genetic predisposition.Diagnosis:Mendelian susceptibility to mycobacterial disease,IFNGR2 deficiency.Interventions:The patient was treated with tailored anti-tubercular therapy and azithromycin prophylaxis.Outcomes:Following treatment,the patient’s symptoms have resolved.At 20 months,he is thriving with normal development.Lessons:This case highlights the importance of a thorough medical history and genetic testing in infants with recurrent or unusual infections.Early diagnosis of mendelian susceptibility to mycobacterial disease can lead to effective treatment and better outcomes.
基金supported by the project of National Natural Science Foundation of China(Grant No.42371203 and U21A2032)the project of Sichuan Provincial Science and Technology Department Program Funding(Grant No.2025YFHZ0010)the project of the Science and Technology Program of Aba City(Grant NO.R24YYJSYJ0001).
文摘Landslides pose a significant threat to both human society and environmental sustainability,yet,their spatiotemporal evolution and impacts on global scales in the context of a warming climate remain poorly understood.In this study,we projected global landslide susceptibility under four shared socioeconomic pathways(SSPs)from 2021 to 2100,utilizing multiple machine learning models based on precipitation data from the Coupled Model Intercomparison Project Phase 6(CMIP6)Global Climate Models(GCMs)and static metrics.Our results indicate an overall upward trend in global landslide susceptibility under the SSPs compared to the baseline period(2001–2020),with the most significant increase of about 1%in the very far future(2081–2100)under the high emissions scenario(SSP5-8.5).Currently,approximately 13%of the world’s land area is at very high risk of landslide,mainly in the Cordillera of the Americas and the Andes in South America,the Alps in Europe,the Ethiopian Highlands in Africa,the Himalayas in Asia,and the countries of East and South-East Asia.Notably,India is the country most adversely affected by climate change,particularly during 2081–2100 under SSP3-7.0,with approximately 590 million people—23 times the global average—living in areas categorized as having very high susceptibility.
