[Objective] This study aimed to investigate the hereditary stability of sFat-1 transgenic pigs and the differences in disease susceptivity between sFat-1 transgenic pigs and non-transgenic pigs. [Method] The integrati...[Objective] This study aimed to investigate the hereditary stability of sFat-1 transgenic pigs and the differences in disease susceptivity between sFat-1 transgenic pigs and non-transgenic pigs. [Method] The integration of sFat-1 gene in pigs was detected by PCR; the infection of transgenic pig to pseudorabies, leptospirosis, swine dysentery, brucellosis, Mycobacterium tuberculosis, rotavirus and mycoplasma hyopneumoniae was detected by using ELISA and PCR. [Result] The positive ratio of F3 generation sFat-1 transgenic pigs was 18.5%; the susceptivity of positive sFat- 1 transgenic and negative pigs to seven infectious diseases showed no significant difference. [Conclusion] Exogenous gene in sFat-1 transgenic pigs can not be stably inherited. The overall physical condition of positive transgenic and negative pigs was similar.展开更多
BACKGROUND Transforming growth factor-β(TGF-β)superfamily plays an important role in tumor progression and metastasis.Activin A receptor type 1C(ACVR1C)is a TGF-βtype I receptor that is involved in tumorigenesis th...BACKGROUND Transforming growth factor-β(TGF-β)superfamily plays an important role in tumor progression and metastasis.Activin A receptor type 1C(ACVR1C)is a TGF-βtype I receptor that is involved in tumorigenesis through binding to dif-ferent ligands.AIM To evaluate the correlation between single nucleotide polymorphisms(SNPs)of ACVR1C and susceptibility to esophageal squamous cell carcinoma(ESCC)in Chinese Han population.METHODS In this hospital-based cohort study,1043 ESCC patients and 1143 healthy controls were enrolled.Five SNPs(rs4664229,rs4556933,rs77886248,rs77263459,rs6734630)of ACVR1C were assessed by the ligation detection reaction method.Hardy-Weinberg equilibrium test,genetic model analysis,stratified analysis,linkage disequi-librium test,and haplotype analysis were conducted.RESULTS Participants carrying ACVR1C rs4556933 GA mutant had significantly decreased risk of ESCC,and those with rs77886248 TA mutant were related with higher risk,especially in older male smokers.In the haplotype analysis,ACVR1C Trs4664229Ars4556933Trs77886248Crs77263459Ars6734630 increased risk of ESCC,while Trs4664229Grs4556933Trs77886248Crs77263459Ars6734630 was associated with lower susceptibility to ESCC.CONCLUSION ACVR1C rs4556933 and rs77886248 SNPs were associated with the susceptibility to ESCC,which could provide a potential target for early diagnosis and treatment of ESCC in Chinese Han population.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
According to the instantaneous growth rate (dN/dt) of E. coli CVCC249 growing in batch culture, the entire growth progress was distinguished into four phases: accelerating growth phase, constant growth phase, decelera...According to the instantaneous growth rate (dN/dt) of E. coli CVCC249 growing in batch culture, the entire growth progress was distinguished into four phases: accelerating growth phase, constant growth phase, decelerating growth phase; declining phase, in each of which obvious variation in physiological; biochemical properties was detected, including total DNA, total protein,; MTT-dehydrogenase activity, etc., that led to difference in their antibiotic susceptivity. Antibiotic susceptivity of the population sampled from each phase was tested by Concentration-killing Curve (CKC) approach following the formula N=N 0/{1+exp[r·(x-BC 50)]}, showing as normal distribution at the individual cell level for an internal population, in which the median bactericidal concentration BC 50 represents the mean level of susceptivity, while the bactericidal span BC 199=(2lnN 0)/r indicates the variation degree of the antibiotic susceptivity. Furthermore, tested by CKC approach, the antibiotic susceptivity of E. coli CVCC249 population in each physiological phase to gentamicin or enoxacin was various: susceptivity of the population in the constant growth phase; declining phase all increased compared with that in the accelerating growth phase for gentamicin but declined for enoxacin. The primary investigations revealed that the physiological phase should be taken into account in the context of antibiotic susceptivity; research into antimicrobial mechanism. However there are few reports concerned with this study. Further research using different kinds of antibiotics with synchronized continuous culture of different bacterial strains is required.展开更多
Wildfires significantly disrupt the physical and hydrologic conditions of the environment,leading to vegetation loss and altered surface geo-material properties.These complex dynamics promote post-fire gully erosion,y...Wildfires significantly disrupt the physical and hydrologic conditions of the environment,leading to vegetation loss and altered surface geo-material properties.These complex dynamics promote post-fire gully erosion,yet the key conditioning factors(e.g.,topography,hydrology)remain insufficiently understood.This study proposes a novel artificial intelligence(AI)framework that integrates four machine learning(ML)models with Shapley Additive Explanations(SHAP)method,offering a hierarchical perspective from global to local on the dominant factors controlling gully distribution in wildfireaffected areas.In a case study of Xiangjiao catchment burned on March 28,2020,in Muli County in Sichuan Province of Southwest China,we derived 21 geoenvironmental factors to assess the susceptibility of post-fire gully erosion using logistic regression(LR),support vector machine(SVM),random forest(RF),and convolutional neural network(CNN)models.SHAP-based model interpretation revealed eight key conditioning factors:topographic position index(TPI),topographic wetness index(TWI),distance to stream,mean annual precipitation,differenced normalized burn ratio(d NBR),land use/cover,soil type,and distance to road.Comparative model evaluation demonstrated that reduced-variable models incorporating these dominant factors achieved accuracy comparable to that of the initial-variable models,with AUC values exceeding 0.868 across all ML algorithms.These findings provide critical insights into gully erosion behavior in wildfire-affected areas,supporting the decision-making process behind environmental management and hazard mitigation.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
Nosocomial pathogen carbapenem-resistant Klebsiella pneumoniae(CRKP)poses a heightened risk to public health through carbapenem resistance and virulence convergence,particularly in China’s dominant sequence type 11(S...Nosocomial pathogen carbapenem-resistant Klebsiella pneumoniae(CRKP)poses a heightened risk to public health through carbapenem resistance and virulence convergence,particularly in China’s dominant sequence type 11(ST11)clone[1,2].Monoclonal K.pneumoniae exhibits within-host diversity during prolonged infections[3–5],with certain variants surviving through adaptation[4,6].CRKP strains from the blood of a single patient are heterogeneous in terms of antibiotic susceptibility,capsular polysaccharide production,and mucoviscosity[3].Intra-host evolution drives novel resistance via cumulative mutations(e.g.,the transcriptional regulator gene ramR mutations and the outer membrane porin gene OmpK35 loss)[4].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
BACKGROUND Antibiotic resistance is a growing global health threat,and understanding local trends in bacterial isolates and their susceptibility patterns is crucial for effective infection control and antimicrobial st...BACKGROUND Antibiotic resistance is a growing global health threat,and understanding local trends in bacterial isolates and their susceptibility patterns is crucial for effective infection control and antimicrobial stewardship.The coronavirus disease 2019(COVID-19)pandemic has introduced additional complexities,potentially influencing these patterns.AIM To analyze trends in bacterial isolates and their antibiotic susceptibility patterns at Salmaniya Medical Complex from 2018 to 2023,with a specific focus on the impact of the COVID-19 pandemic on these trends.METHODS A retrospective analysis of microbiological data was conducted,covering the period from 2018 to 2023.The study included key bacterial pathogens such as Escherichia coli(E.coli),Klebsiella pneumoniae,Acinetobacter baumannii,Pseudomonas aeruginosa,and Staphylococcus aureus,among others.The antibiotic susceptibility profiles of these isolates were assessed using standard laboratory methods.To contextualize the findings,the findings were compared with similar studies from other regions,including China,India,Romania,Saudi Arabia,the United Arab Emirates,Malaysia,and United States.RESULTS The study revealed fluctuating trends in the prevalence of bacterial isolates,with notable changes during the COVID-19 pandemic.For example,a significant increase in the prevalence of Staphylococcus aureus was observed during the pandemic years,while the prevalence of E.coli showed a more variable pattern.Antibiotic resistance rates varied among the different pathogens,with a concerning rise in resistance to commonly used antibiotics,particularly among Klebsiella pneumoniae and E.coli.Additionally,the study identified an alarming increase in the prevalence of multidrug-resistant(MDR)strains,especially within Klebsiella pneumoniae and E.coli isolates.The impact of the COVID-19 pandemic on these trends was evident,with shifts in the frequency,resistance patterns,and the emergence of MDR bacteria among several key pathogens.CONCLUSION This study highlights the dynamic nature of bacterial isolates and their antibiotic susceptibility patterns at Salmaniya Medical Complex,particularly in the context of the COVID-19 pandemic.The findings underscore the need for continuous monitoring and effective anti-microbial stewardship programs to combat the evolving threat of antibiotic resistance.Further research and policy initiatives are required to address the identified challenges and improve patient outcomes in the face of these ongoing challenges.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
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
Objective:Neuroblastoma is the most common extracranial solid tumor in children and has complex genetic underpinnings.Previous genome-wide association studies(GWASs)have identified many loci associated with neuroblast...Objective:Neuroblastoma is the most common extracranial solid tumor in children and has complex genetic underpinnings.Previous genome-wide association studies(GWASs)have identified many loci associated with neuroblastoma susceptibility;however,their application in risk prediction for Chinese children has not been systematically explored.This study seeks to enhance neuroblastoma risk prediction by validating these loci and evaluating their performance in polygenic risk models.Methods:We validated 35 GWAS-identified neuroblastoma susceptibility loci in a cohort of Chinese children,consisting of 402 neuroblastoma patients and 473 healthy controls.Genotyping these polymorphisms was conducted via the TaqMan method.Univariable and multivariable logistic regression analyses revealed the genetic loci significantly associated with neuroblastoma risk.We constructed polygenic risk models by combining these loci and assessed their predictive performance via area under the curve(AUC)analysis.We also established a polygenic risk scoring(PRS)model for risk prediction by adopting the PLINK method.Results:Fourteen loci,including ten protective polymorphisms from CASC15,BARD1,LMO1,HSD17B12,and HACE1,and four risk variants from BARD1,RSRC1,CPZ and MMP20 were significantly associated with neuroblastoma risk.Compared with single-gene model,the 8-gene model(AUC=0.72)and 13-gene model(AUC=0.73)demonstrated superior predictive performance.Additionally,a PRS incorporating six significant loci achieved an AUC of 0.66,effectively stratifying individuals into distinct risk categories regarding neuroblastoma susceptibility.A higher PRS was significantly associated with advanced International Neuroblastoma Staging System(INSS)stages,suggesting its potential for clinical risk stratification.Conclusions:Our findings validate multiple loci as neuroblastoma risk factors in Chinese children and demonstrate the utility of polygenic risk models,particularly the PRS,in improving risk prediction.These results suggest that integrating multiple genetic variants into a PRS can enhance neuroblastoma risk stratification and potentially improve early diagnosis by guiding targeted screening programs for high-risk children.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
The pandemic SARS-CoV-2 has become an undying virus to spread a sustainable disease named COVID-19 for upcoming few years.Mortality rates are rising rapidly as approved drugs are not yet available.Isolation from the i...The pandemic SARS-CoV-2 has become an undying virus to spread a sustainable disease named COVID-19 for upcoming few years.Mortality rates are rising rapidly as approved drugs are not yet available.Isolation from the infected person or community is the preferred choice to protect our health.Since humans are the only carriers,it might be possible to control the positive rate if the infected population or host carriers are isolated from each other.Isolation alone may not be a proper solution.These are the resolutions of previous research work carried out on COVID-19 throughout the world.The present scenario of the world and public health is knocking hard with a big question of critical uncertainty of COVID-19 because of its imprecise database as per daily positive cases recorded all over the world and in India as well.In this research work,we have pre-sented an optimal control model for COVID-19 using granular differentiability based on fuzzy dynamical systems.In the first step,we created a fuzzy Susceptible-Exposed-Infected-Asymptomatic-Hospitalized-Recovered-Death(SEIAHRD)model for COVID-19,analyzed it using granular differentiability,and reported disease dynamics for time-independent disease control parameters.In the second step,we upgraded the fuzzy dynamical system and granular differentiability model related to time-dependent disease control parameters as an optimal control problem invader.Theoretical studies have been validated with some practical data from the epidemic COVID-19 related to the Indian perspective during first wave and early second wave.展开更多
Congenital scoliosis(CS)is a prevalent spinal deformity with a multifaceted etiology that remains incompletely understood.Recent advances in genetic and epigenetic research have provided novel insights into CS pathoge...Congenital scoliosis(CS)is a prevalent spinal deformity with a multifaceted etiology that remains incompletely understood.Recent advances in genetic and epigenetic research have provided novel insights into CS pathogenesis.Herein,we review the current progress in genetics and epigenetics to examine genetic variants,susceptibility factors,and the epigenetic regulatory mechanisms implicated in CS.Through an analysis of diverse genetic markers,chromosomal abnormalities,and epigenetic modifications,the correlation between genetic predisposition and environmental influences in CS pathogenesis is elucidated.By integrating these genetic and epigenetic findings,this study aims to clarify the underlying etiology of CS to provide guidance on future clinical interventions and promote the development of personalized therapeutic strategies.展开更多
BACKGROUND Pediatric candiduria is a frequently overlooked manifestation of healthcareassociated fungal infections.Candida species are increasingly being identified in the urine of neonates and infants,with non-albica...BACKGROUND Pediatric candiduria is a frequently overlooked manifestation of healthcareassociated fungal infections.Candida species are increasingly being identified in the urine of neonates and infants,with non-albicans Candida(NAC)species being more prevalent than Candida albicans.AIM To determine the rate of Candida species isolation among pediatric patients with suspected urinary tract infections(UTI)at a tertiary care hospital.METHODS A total of 436 children with a clinical suspicion of UTI were enrolled in this laboratory-based descriptive observational study.The samples were then subjected to urine mounting and subcultured on Sabouraud dextrose agar.Candida isolates were identified based on the color of the colonies on CHROM agar,Dalmau plate culture,and germ tube formation.The results were confirmed by matrix-assisted laser desorption ionization-time of flight mass spectrometry,followed by Antifungal susceptibility testing using Vitek®2 AST-YS07 cards.RESULTS A total of 79 Candida isolates(18.12%)were identified.Of these,39(49.37%)were neonates,with a male-to-female ratio of 3.39:1.The intensive care unit(ICU)recorded 52 patients(65.82%).Of the 79 patients,57(72.15%)received broadspectrum antibiotics for more than 7 days.Our study revealed a higher prevalence of NAC species,with Candida tropicalis accounting for 34 cases(43.04%).Amphotericin B showed the highest susceptibility,with 68 isolates(86.08%)being susceptible to this Antifungal agent.CONCLUSION Pediatric patients with Candiduria present atypical and vague symptoms.This may be the initial symptom of disseminated Candidiasis in the presence of predisposing factors.Isolation of these pathogens,along with their Antifungal susceptibility patterns,aids in a better prognosis.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
Background:Schistosomiasis is a parasitic disease.It is caused by a prevalent infection in tropical areas and is transmitted through contaminated water with larvae parasites.Schistosomiasis is the second most parasiti...Background:Schistosomiasis is a parasitic disease.It is caused by a prevalent infection in tropical areas and is transmitted through contaminated water with larvae parasites.Schistosomiasis is the second most parasitic disease globally,so investigating its prevention and treatment is crucial.Methods:This paper aims to suggest a time-fractional model of schistosomiasis disease(T-FMSD)in the sense of the Caputo operator.The T-FMSD considers the dynamics involving susceptible ones not infected with schistosomiasis(S_(h)(t)),those infected with the infection(Ih(t)),those recovering from the disease(R(t)),susceptible snails with and without schistosomiasis infection,respectively shown by I_(v)(t)and S_(v)(t).We use a new basis function,generalized Bernoulli polynomials,for the approximate solution of T-FMSD.The operational matrices are incorporated into the method of Lagrange multipliers so that the fractional problem can be transformed into an algebraic system of equations.Results:The existence and uniqueness of the solution,and the convergence analysis of the model are established.The numerical computations are graphically presented to depict the variations of the compartments with time for varied fractional order derivatives.Conclusions:The proposed method not only provides an accurate solution but also can accurately predict schistosomiasis transmission.The results of this study will assist medical scientists in taking necessary measures during screening and treatment processes.展开更多
Pain has been traditionally understood as a complex phenomenon involving various dimensions,including physical,sensory,cognitive,and emotional aspects,resulting in unpleasant sensations and affective responses.Individ...Pain has been traditionally understood as a complex phenomenon involving various dimensions,including physical,sensory,cognitive,and emotional aspects,resulting in unpleasant sensations and affective responses.Individual responses to pain can vary significantly,even when individuals are exposed to similar nociceptive stimuli or clinical conditions,with some individuals experiencing intense pain and others experiencing milder levels,suggesting the presence of pain resilience.Although recent advances in pain research have focused on susceptibility,the occurrence of pain,and related pathological mechanisms,there remains a dearth of comprehensive analysis of the neural mechanisms that underlie pain resilience,although peripheral mechanisms have begun to be revealed.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
基金Supported by National Major Program of Genetically Modified Organism for New Species Cultivation of China(2011ZX08011-004)Project from Hubei Agricultural Science and Technology Innovation Center(2011-620-001-003)~~
文摘[Objective] This study aimed to investigate the hereditary stability of sFat-1 transgenic pigs and the differences in disease susceptivity between sFat-1 transgenic pigs and non-transgenic pigs. [Method] The integration of sFat-1 gene in pigs was detected by PCR; the infection of transgenic pig to pseudorabies, leptospirosis, swine dysentery, brucellosis, Mycobacterium tuberculosis, rotavirus and mycoplasma hyopneumoniae was detected by using ELISA and PCR. [Result] The positive ratio of F3 generation sFat-1 transgenic pigs was 18.5%; the susceptivity of positive sFat- 1 transgenic and negative pigs to seven infectious diseases showed no significant difference. [Conclusion] Exogenous gene in sFat-1 transgenic pigs can not be stably inherited. The overall physical condition of positive transgenic and negative pigs was similar.
基金Supported by The National Natural Science Foundation of China,No.82350127 and No.82241013the Shanghai Natural Science Foundation,No.20ZR1411600+2 种基金the Shanghai Shenkang Hospital Development Center,No.SHDC2020CR4039the Bethune Ethicon Excellent Surgery Foundation,No.CESS2021TC04Xuhui District Medical Research Project of Shanghai,No.SHXH201805.
文摘BACKGROUND Transforming growth factor-β(TGF-β)superfamily plays an important role in tumor progression and metastasis.Activin A receptor type 1C(ACVR1C)is a TGF-βtype I receptor that is involved in tumorigenesis through binding to dif-ferent ligands.AIM To evaluate the correlation between single nucleotide polymorphisms(SNPs)of ACVR1C and susceptibility to esophageal squamous cell carcinoma(ESCC)in Chinese Han population.METHODS In this hospital-based cohort study,1043 ESCC patients and 1143 healthy controls were enrolled.Five SNPs(rs4664229,rs4556933,rs77886248,rs77263459,rs6734630)of ACVR1C were assessed by the ligation detection reaction method.Hardy-Weinberg equilibrium test,genetic model analysis,stratified analysis,linkage disequi-librium test,and haplotype analysis were conducted.RESULTS Participants carrying ACVR1C rs4556933 GA mutant had significantly decreased risk of ESCC,and those with rs77886248 TA mutant were related with higher risk,especially in older male smokers.In the haplotype analysis,ACVR1C Trs4664229Ars4556933Trs77886248Crs77263459Ars6734630 increased risk of ESCC,while Trs4664229Grs4556933Trs77886248Crs77263459Ars6734630 was associated with lower susceptibility to ESCC.CONCLUSION ACVR1C rs4556933 and rs77886248 SNPs were associated with the susceptibility to ESCC,which could provide a potential target for early diagnosis and treatment of ESCC in Chinese Han population.
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Supported by the Natural Science Foundation of Shandong Province, China (Grant No. Y2005C58)the Natural Key Technology R&D Program of China (Grant No. 2006BAK02A03-6)the Youth Scientific Research Foundation of Shandong Academy of Agricultural Science (2005YQ035)
文摘According to the instantaneous growth rate (dN/dt) of E. coli CVCC249 growing in batch culture, the entire growth progress was distinguished into four phases: accelerating growth phase, constant growth phase, decelerating growth phase; declining phase, in each of which obvious variation in physiological; biochemical properties was detected, including total DNA, total protein,; MTT-dehydrogenase activity, etc., that led to difference in their antibiotic susceptivity. Antibiotic susceptivity of the population sampled from each phase was tested by Concentration-killing Curve (CKC) approach following the formula N=N 0/{1+exp[r·(x-BC 50)]}, showing as normal distribution at the individual cell level for an internal population, in which the median bactericidal concentration BC 50 represents the mean level of susceptivity, while the bactericidal span BC 199=(2lnN 0)/r indicates the variation degree of the antibiotic susceptivity. Furthermore, tested by CKC approach, the antibiotic susceptivity of E. coli CVCC249 population in each physiological phase to gentamicin or enoxacin was various: susceptivity of the population in the constant growth phase; declining phase all increased compared with that in the accelerating growth phase for gentamicin but declined for enoxacin. The primary investigations revealed that the physiological phase should be taken into account in the context of antibiotic susceptivity; research into antimicrobial mechanism. However there are few reports concerned with this study. Further research using different kinds of antibiotics with synchronized continuous culture of different bacterial strains is required.
基金the National Natural Science Foundation of China(42377170,42407212)the National Funded Postdoctoral Researcher Program(GZB20230606)+3 种基金the Postdoctoral Research Foundation of China(2024M752679)the Sichuan Natural Science Foundation(2025ZNSFSC1205)the National Key R&D Program of China(2022YFC3005704)the Sichuan Province Science and Technology Support Program(2024NSFSC0100)。
文摘Wildfires significantly disrupt the physical and hydrologic conditions of the environment,leading to vegetation loss and altered surface geo-material properties.These complex dynamics promote post-fire gully erosion,yet the key conditioning factors(e.g.,topography,hydrology)remain insufficiently understood.This study proposes a novel artificial intelligence(AI)framework that integrates four machine learning(ML)models with Shapley Additive Explanations(SHAP)method,offering a hierarchical perspective from global to local on the dominant factors controlling gully distribution in wildfireaffected areas.In a case study of Xiangjiao catchment burned on March 28,2020,in Muli County in Sichuan Province of Southwest China,we derived 21 geoenvironmental factors to assess the susceptibility of post-fire gully erosion using logistic regression(LR),support vector machine(SVM),random forest(RF),and convolutional neural network(CNN)models.SHAP-based model interpretation revealed eight key conditioning factors:topographic position index(TPI),topographic wetness index(TWI),distance to stream,mean annual precipitation,differenced normalized burn ratio(d NBR),land use/cover,soil type,and distance to road.Comparative model evaluation demonstrated that reduced-variable models incorporating these dominant factors achieved accuracy comparable to that of the initial-variable models,with AUC values exceeding 0.868 across all ML algorithms.These findings provide critical insights into gully erosion behavior in wildfire-affected areas,supporting the decision-making process behind environmental management and hazard mitigation.
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Guangdong Basic and Applied Basic Research Foundation(grant number 2024A1515010319 to J.Q.)Science and Technology Program of Shenzhen(grant numbers KCXFZ20230731100901003 to J.Q.and L.L.,KJZD20230923115116032 to J.Q.,JCYJ20190809144005609 to J.Q.)+1 种基金Shenzhen Key Laboratory of Biochip(grant number ZDSYS201504301534057 to J.Q.)Shenzhen High-level Hospital Construction Fund(to J.Q.).
文摘Nosocomial pathogen carbapenem-resistant Klebsiella pneumoniae(CRKP)poses a heightened risk to public health through carbapenem resistance and virulence convergence,particularly in China’s dominant sequence type 11(ST11)clone[1,2].Monoclonal K.pneumoniae exhibits within-host diversity during prolonged infections[3–5],with certain variants surviving through adaptation[4,6].CRKP strains from the blood of a single patient are heterogeneous in terms of antibiotic susceptibility,capsular polysaccharide production,and mucoviscosity[3].Intra-host evolution drives novel resistance via cumulative mutations(e.g.,the transcriptional regulator gene ramR mutations and the outer membrane porin gene OmpK35 loss)[4].
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.
文摘BACKGROUND Antibiotic resistance is a growing global health threat,and understanding local trends in bacterial isolates and their susceptibility patterns is crucial for effective infection control and antimicrobial stewardship.The coronavirus disease 2019(COVID-19)pandemic has introduced additional complexities,potentially influencing these patterns.AIM To analyze trends in bacterial isolates and their antibiotic susceptibility patterns at Salmaniya Medical Complex from 2018 to 2023,with a specific focus on the impact of the COVID-19 pandemic on these trends.METHODS A retrospective analysis of microbiological data was conducted,covering the period from 2018 to 2023.The study included key bacterial pathogens such as Escherichia coli(E.coli),Klebsiella pneumoniae,Acinetobacter baumannii,Pseudomonas aeruginosa,and Staphylococcus aureus,among others.The antibiotic susceptibility profiles of these isolates were assessed using standard laboratory methods.To contextualize the findings,the findings were compared with similar studies from other regions,including China,India,Romania,Saudi Arabia,the United Arab Emirates,Malaysia,and United States.RESULTS The study revealed fluctuating trends in the prevalence of bacterial isolates,with notable changes during the COVID-19 pandemic.For example,a significant increase in the prevalence of Staphylococcus aureus was observed during the pandemic years,while the prevalence of E.coli showed a more variable pattern.Antibiotic resistance rates varied among the different pathogens,with a concerning rise in resistance to commonly used antibiotics,particularly among Klebsiella pneumoniae and E.coli.Additionally,the study identified an alarming increase in the prevalence of multidrug-resistant(MDR)strains,especially within Klebsiella pneumoniae and E.coli isolates.The impact of the COVID-19 pandemic on these trends was evident,with shifts in the frequency,resistance patterns,and the emergence of MDR bacteria among several key pathogens.CONCLUSION This study highlights the dynamic nature of bacterial isolates and their antibiotic susceptibility patterns at Salmaniya Medical Complex,particularly in the context of the COVID-19 pandemic.The findings underscore the need for continuous monitoring and effective anti-microbial stewardship programs to combat the evolving threat of antibiotic resistance.Further research and policy initiatives are required to address the identified challenges and improve patient outcomes in the face of these ongoing challenges.
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 grants from the National Natural Science Foundation of China(No.82173593,32300473)Guangzhou Science and Technology Project(No.2025A04J4537,2025A04J4696)+1 种基金Guangdong Basic and Applied Basic Research Foundation(No.2023A1515220053)Postdoctoral Science Foundation of Jiangsu Province(No.2021K524C).
文摘Objective:Neuroblastoma is the most common extracranial solid tumor in children and has complex genetic underpinnings.Previous genome-wide association studies(GWASs)have identified many loci associated with neuroblastoma susceptibility;however,their application in risk prediction for Chinese children has not been systematically explored.This study seeks to enhance neuroblastoma risk prediction by validating these loci and evaluating their performance in polygenic risk models.Methods:We validated 35 GWAS-identified neuroblastoma susceptibility loci in a cohort of Chinese children,consisting of 402 neuroblastoma patients and 473 healthy controls.Genotyping these polymorphisms was conducted via the TaqMan method.Univariable and multivariable logistic regression analyses revealed the genetic loci significantly associated with neuroblastoma risk.We constructed polygenic risk models by combining these loci and assessed their predictive performance via area under the curve(AUC)analysis.We also established a polygenic risk scoring(PRS)model for risk prediction by adopting the PLINK method.Results:Fourteen loci,including ten protective polymorphisms from CASC15,BARD1,LMO1,HSD17B12,and HACE1,and four risk variants from BARD1,RSRC1,CPZ and MMP20 were significantly associated with neuroblastoma risk.Compared with single-gene model,the 8-gene model(AUC=0.72)and 13-gene model(AUC=0.73)demonstrated superior predictive performance.Additionally,a PRS incorporating six significant loci achieved an AUC of 0.66,effectively stratifying individuals into distinct risk categories regarding neuroblastoma susceptibility.A higher PRS was significantly associated with advanced International Neuroblastoma Staging System(INSS)stages,suggesting its potential for clinical risk stratification.Conclusions:Our findings validate multiple loci as neuroblastoma risk factors in Chinese children and demonstrate the utility of polygenic risk models,particularly the PRS,in improving risk prediction.These results suggest that integrating multiple genetic variants into a PRS can enhance neuroblastoma risk stratification and potentially improve early diagnosis by guiding targeted screening programs for high-risk children.
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).
文摘The pandemic SARS-CoV-2 has become an undying virus to spread a sustainable disease named COVID-19 for upcoming few years.Mortality rates are rising rapidly as approved drugs are not yet available.Isolation from the infected person or community is the preferred choice to protect our health.Since humans are the only carriers,it might be possible to control the positive rate if the infected population or host carriers are isolated from each other.Isolation alone may not be a proper solution.These are the resolutions of previous research work carried out on COVID-19 throughout the world.The present scenario of the world and public health is knocking hard with a big question of critical uncertainty of COVID-19 because of its imprecise database as per daily positive cases recorded all over the world and in India as well.In this research work,we have pre-sented an optimal control model for COVID-19 using granular differentiability based on fuzzy dynamical systems.In the first step,we created a fuzzy Susceptible-Exposed-Infected-Asymptomatic-Hospitalized-Recovered-Death(SEIAHRD)model for COVID-19,analyzed it using granular differentiability,and reported disease dynamics for time-independent disease control parameters.In the second step,we upgraded the fuzzy dynamical system and granular differentiability model related to time-dependent disease control parameters as an optimal control problem invader.Theoretical studies have been validated with some practical data from the epidemic COVID-19 related to the Indian perspective during first wave and early second wave.
基金Supported by the National Natural Science Foundation of China,No.82460940Major Project of Gansu Province Joint Fund,No.23JRRA1519+2 种基金Key Science and Technology Project of Gansu Province,No.21ZD4FA009Natural Science Foundation of Gansu Province,No.24JRRA1040Gansu Province Famous Traditional Chinese Medicine Inheritance Studio Project。
文摘Congenital scoliosis(CS)is a prevalent spinal deformity with a multifaceted etiology that remains incompletely understood.Recent advances in genetic and epigenetic research have provided novel insights into CS pathogenesis.Herein,we review the current progress in genetics and epigenetics to examine genetic variants,susceptibility factors,and the epigenetic regulatory mechanisms implicated in CS.Through an analysis of diverse genetic markers,chromosomal abnormalities,and epigenetic modifications,the correlation between genetic predisposition and environmental influences in CS pathogenesis is elucidated.By integrating these genetic and epigenetic findings,this study aims to clarify the underlying etiology of CS to provide guidance on future clinical interventions and promote the development of personalized therapeutic strategies.
文摘BACKGROUND Pediatric candiduria is a frequently overlooked manifestation of healthcareassociated fungal infections.Candida species are increasingly being identified in the urine of neonates and infants,with non-albicans Candida(NAC)species being more prevalent than Candida albicans.AIM To determine the rate of Candida species isolation among pediatric patients with suspected urinary tract infections(UTI)at a tertiary care hospital.METHODS A total of 436 children with a clinical suspicion of UTI were enrolled in this laboratory-based descriptive observational study.The samples were then subjected to urine mounting and subcultured on Sabouraud dextrose agar.Candida isolates were identified based on the color of the colonies on CHROM agar,Dalmau plate culture,and germ tube formation.The results were confirmed by matrix-assisted laser desorption ionization-time of flight mass spectrometry,followed by Antifungal susceptibility testing using Vitek®2 AST-YS07 cards.RESULTS A total of 79 Candida isolates(18.12%)were identified.Of these,39(49.37%)were neonates,with a male-to-female ratio of 3.39:1.The intensive care unit(ICU)recorded 52 patients(65.82%).Of the 79 patients,57(72.15%)received broadspectrum antibiotics for more than 7 days.Our study revealed a higher prevalence of NAC species,with Candida tropicalis accounting for 34 cases(43.04%).Amphotericin B showed the highest susceptibility,with 68 isolates(86.08%)being susceptible to this Antifungal agent.CONCLUSION Pediatric patients with Candiduria present atypical and vague symptoms.This may be the initial symptom of disseminated Candidiasis in the presence of predisposing factors.Isolation of these pathogens,along with their Antifungal susceptibility patterns,aids in a better prognosis.
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.
文摘Background:Schistosomiasis is a parasitic disease.It is caused by a prevalent infection in tropical areas and is transmitted through contaminated water with larvae parasites.Schistosomiasis is the second most parasitic disease globally,so investigating its prevention and treatment is crucial.Methods:This paper aims to suggest a time-fractional model of schistosomiasis disease(T-FMSD)in the sense of the Caputo operator.The T-FMSD considers the dynamics involving susceptible ones not infected with schistosomiasis(S_(h)(t)),those infected with the infection(Ih(t)),those recovering from the disease(R(t)),susceptible snails with and without schistosomiasis infection,respectively shown by I_(v)(t)and S_(v)(t).We use a new basis function,generalized Bernoulli polynomials,for the approximate solution of T-FMSD.The operational matrices are incorporated into the method of Lagrange multipliers so that the fractional problem can be transformed into an algebraic system of equations.Results:The existence and uniqueness of the solution,and the convergence analysis of the model are established.The numerical computations are graphically presented to depict the variations of the compartments with time for varied fractional order derivatives.Conclusions:The proposed method not only provides an accurate solution but also can accurately predict schistosomiasis transmission.The results of this study will assist medical scientists in taking necessary measures during screening and treatment processes.
基金supported by grants from the National Natural Science Foundation of China(82304459).
文摘Pain has been traditionally understood as a complex phenomenon involving various dimensions,including physical,sensory,cognitive,and emotional aspects,resulting in unpleasant sensations and affective responses.Individual responses to pain can vary significantly,even when individuals are exposed to similar nociceptive stimuli or clinical conditions,with some individuals experiencing intense pain and others experiencing milder levels,suggesting the presence of pain resilience.Although recent advances in pain research have focused on susceptibility,the occurrence of pain,and related pathological mechanisms,there remains a dearth of comprehensive analysis of the neural mechanisms that underlie pain resilience,although peripheral mechanisms have begun to be revealed.
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.
