Wind energy has emerged as a potential replacement for fossil fuel-based energy sources.To harness maximum wind energy,a crucial decision in the development of an efficient wind farm is the optimal layout design.This ...Wind energy has emerged as a potential replacement for fossil fuel-based energy sources.To harness maximum wind energy,a crucial decision in the development of an efficient wind farm is the optimal layout design.This layout defines the specific locations of the turbines within the wind farm.The process of finding the optimal locations of turbines,in the presence of various technical and technological constraints,makes the wind farm layout design problem a complex optimization problem.This problem has traditionally been solved with nature-inspired algorithms with promising results.The performance and convergence of nature-inspired algorithms depend on several parameters,among which the algorithm termination criterion plays a crucial role.Timely convergence is an important aspect of efficient algorithm design because an inefficient algorithm results in wasted computational resources,unwarranted electricity consumption,and hardware stress.This study provides an in-depth analysis of several termination criteria while using the genetic algorithm as a test bench,with its application to the wind farm layout design problem while considering various wind scenarios.The performance of six termination criteria is empirically evaluated with respect to the quality of solutions produced and the execution time involved.Due to the conflicting nature of these two attributes,fuzzy logic-based multi-attribute decision-making is employed in the decision process.Results for the fuzzy decision approach indicate that among the various criteria tested,the criterion Phi achieves an improvement in the range of 2.44%to 32.93%for wind scenario 1.For scenario 2,Best-worst termination criterion performed well compared to the other criteria evaluated,with an improvement in the range of 1.2%to 9.64%.For scenario 3,Hitting bound was the best performer with an improvement of 1.16%to 20.93%.展开更多
Aiming to solve the steering instability and hysteresis of agricultural robots in the process of movement,a fusion PID control method of particle swarm optimization(PSO)and genetic algorithm(GA)was proposed.The fusion...Aiming to solve the steering instability and hysteresis of agricultural robots in the process of movement,a fusion PID control method of particle swarm optimization(PSO)and genetic algorithm(GA)was proposed.The fusion algorithm took advantage of the fast optimization ability of PSO to optimize the population screening link of GA.The Simulink simulation results showed that the convergence of the fitness function of the fusion algorithm was accelerated,the system response adjustment time was reduced,and the overshoot was almost zero.Then the algorithm was applied to the steering test of agricultural robot in various scenes.After modeling the steering system of agricultural robot,the steering test results in the unloaded suspended state showed that the PID control based on fusion algorithm reduced the rise time,response adjustment time and overshoot of the system,and improved the response speed and stability of the system,compared with the artificial trial and error PID control and the PID control based on GA.The actual road steering test results showed that the PID control response rise time based on the fusion algorithm was the shortest,about 4.43 s.When the target pulse number was set to 100,the actual mean value in the steady-state regulation stage was about 102.9,which was the closest to the target value among the three control methods,and the overshoot was reduced at the same time.The steering test results under various scene states showed that the PID control based on the proposed fusion algorithm had good anti-interference ability,it can adapt to the changes of environment and load and improve the performance of the control system.It was effective in the steering control of agricultural robot.This method can provide a reference for the precise steering control of other robots.展开更多
Optimizing convolutional neural networks(CNNs)for IoT attack detection remains a critical yet challenging task due to the need to balance multiple performance metrics beyond mere accuracy.This study proposes a unified...Optimizing convolutional neural networks(CNNs)for IoT attack detection remains a critical yet challenging task due to the need to balance multiple performance metrics beyond mere accuracy.This study proposes a unified and flexible optimization framework that leverages metaheuristic algorithms to automatically optimize CNN configurations for IoT attack detection.Unlike conventional single-objective approaches,the proposed method formulates a global multi-objective fitness function that integrates accuracy,precision,recall,and model size(speed/model complexity penalty)with adjustable weights.This design enables both single-objective and weightedsum multi-objective optimization,allowing adaptive selection of optimal CNN configurations for diverse deployment requirements.Two representativemetaheuristic algorithms,GeneticAlgorithm(GA)and Particle Swarm Optimization(PSO),are employed to optimize CNNhyperparameters and structure.At each generation/iteration,the best configuration is selected as themost balanced solution across optimization objectives,i.e.,the one achieving themaximum value of the global objective function.Experimental validation on two benchmark datasets,Edge-IIoT and CIC-IoT2023,demonstrates that the proposed GA-and PSO-based models significantly enhance detection accuracy(94.8%–98.3%)and generalization compared with manually tuned CNN configurations,while maintaining compact architectures.The results confirm that the multi-objective framework effectively balances predictive performance and computational efficiency.This work establishes a generalizable and adaptive optimization strategy for deep learning-based IoT attack detection and provides a foundation for future hybrid metaheuristic extensions in broader IoT security applications.展开更多
Optimization is the key to obtaining efficient utilization of resources in structural design.Due to the complex nature of truss systems,this study presents a method based on metaheuristic modelling that minimises stru...Optimization is the key to obtaining efficient utilization of resources in structural design.Due to the complex nature of truss systems,this study presents a method based on metaheuristic modelling that minimises structural weight under stress and frequency constraints.Two new algorithms,the Red Kite Optimization Algorithm(ROA)and Secretary Bird Optimization Algorithm(SBOA),are utilized on five benchmark trusses with 10,18,37,72,and 200-bar trusses.Both algorithms are evaluated against benchmarks in the literature.The results indicate that SBOA always reaches a lighter optimal.Designs with reducing structural weight ranging from 0.02%to 0.15%compared to ROA,and up to 6%–8%as compared to conventional algorithms.In addition,SBOA can achieve 15%–20%faster convergence speed and 10%–18%reduction in computational time with a smaller standard deviation over independent runs,which demonstrates its robustness and reliability.It is indicated that the adaptive exploration mechanism of SBOA,especially its Levy flight–based search strategy,can obviously improve optimization performance for low-and high-dimensional trusses.The research has implications in the context of promoting bio-inspired optimization techniques by demonstrating the viability of SBOA,a reliable model for large-scale structural design that provides significant enhancements in performance and convergence behavior.展开更多
The etiopathogenesis of gastrointestinal diseases is varied in nature.Various etiogenic factors described are infective,inflammatory,viral,bacterial,parasitic,dietary and lifestyle change.Rare causative agents are imm...The etiopathogenesis of gastrointestinal diseases is varied in nature.Various etiogenic factors described are infective,inflammatory,viral,bacterial,parasitic,dietary and lifestyle change.Rare causative agents are immunological,and others associated as idiopathic,are undiagnosed by all possible means.Some of the rare diseases are congenital in nature,passing from the parent to the child.Many of the undiagnosed diseases are now being diagnosed as genetic and the genes have been implicated as a causative agent.There is a search for newer treatments for such diseases,which is called genomic medicine.Genomic medicine is an emerging medical discipline that involves the use of genomic information about an individual.This is used both for diagnostic as well as therapeutic decisions to improve the current health domain and pave the way for policymakers for its clinical use.In the developing era of precision medicine,genomics,epigenomics,environmental exposure,and other data would be used to more accurately guide individual diagnosis and treatment.Genomic medicine is already making an impact in the fields of oncology,pharmacology,rare,infectious and many undiagnosed diseases.It is beginning to fuel new approaches in certain medical specialties.Oncology is at the leading edge of incorporating genomics,as diagnostics for genetic and genomic markers are increasingly included in cancer screening,and to guide tailored treatment strategies.Genetics and genetic medicine have been reported to play a role in gastroenterology in several ways,including genetic testing(hereditary pancreatitis and hereditary gastrointestinal cancer syndromes).Genetic testing can also help subtype diseases,such as classifying pancreatitis as idiopathic or hereditary.Gene therapy is a promising approach for treating gastrointestinal diseases that are not effectively treated by conventional pharmaceuticals and surgeries.Gene therapy strategies include gene addition,gene editing,messenger RNA therapy,and gene silencing.Understanding genetic determinants,advances in genetics,have led to a better understanding of the genetic factors that contribute to human disease.Family-member risk stratification and genetic diagnosis can help identify family members who are at risk,which can lead to preventive treatments,lifestyle recommendations,and routine follow ups.Selecting target genes helps identify the gene targets associated with each gastrointestinal disease.Common gastrointestinal diseases associated with genetic abnormalities include-inflammatory bowel disease,gastroesophageal reflux disease,non-alcoholic fatty liver disease,and irritable bowel syndrome.With advancing tools and technology,research in the search of newer and individualized treatment,genes and genetic medicines are expected to play a significant role in human health and gastroenterology.展开更多
Successful ex situ conservation of plant populations requires a high degree of genetic representativeness.However,spatially biased sampling in ex situ conservation efforts may fail to capture all wild genetic clusters...Successful ex situ conservation of plant populations requires a high degree of genetic representativeness.However,spatially biased sampling in ex situ conservation efforts may fail to capture all wild genetic clusters for species with range-wide genetic structure.To investigate the extent of spatially biased sampling in living collections and the coverage of wild genetic clusters in plant populations under ex situ conservation worldwide,we combined a global synthesis of ex situ conservation efforts with a case study of an endangered riparian plant species,Myricaria laxiflora.Our analysis of ex situ conservation worldwide revealed that the majority(82.6%)of ex situ populations fail to cover all wild genetic clusters,largely due to spatially biased sampling with low geographic coverage.Our case study of M.laxiflora showed that genetic diversity differed between the ex situ and upstream populations,while it was comparable between ex situ populations and other wild populations.However,current ex situ populations did not cover all wild genetic clusters,as the upstream genetic cluster was previously uncollected.Our study suggests that the failure to cover all wild genetic clusters in ex situ populations is a widespread issue,and ex situ populations with high genetic diversity can also fail to cover all wild genetic clusters.In future ex situ conservation programs,both the importance of high genetic diversity and the high coverage of wild genetic clusters should be prioritized.展开更多
In this paper,we propose a new privacy-aware transmission scheduling algorithm for 6G ad hoc networks.This system enables end nodes to select the optimum time and scheme to transmit private data safely.In 6G dynamic h...In this paper,we propose a new privacy-aware transmission scheduling algorithm for 6G ad hoc networks.This system enables end nodes to select the optimum time and scheme to transmit private data safely.In 6G dynamic heterogeneous infrastructures,unstable links and non-uniform hardware capabilities create critical issues regarding security and privacy.Traditional protocols are often too computationally heavy to allow 6G services to achieve their expected Quality-of-Service(QoS).As the transport network is built of ad hoc nodes,there is no guarantee about their trustworthiness or behavior,and transversal functionalities are delegated to the extreme nodes.However,while security can be guaranteed in extreme-to-extreme solutions,privacy cannot,as all intermediate nodes still have to handle the data packets they are transporting.Besides,traditional schemes for private anonymous ad hoc communications are vulnerable against modern intelligent attacks based on learning models.The proposed scheme fulfills this gap.Findings show the probability of a successful intelligent attack reduces by up to 65%compared to ad hoc networks with no privacy protection strategy when used the proposed technology.While congestion probability can remain below 0.001%,as required in 6G services.展开更多
Oral immunization is an alternative or supplementary approach that can significantly improve dog vaccination coverage,especially for free-roaming dogs.Safe and effective oral rabies vaccines for dogs are still being s...Oral immunization is an alternative or supplementary approach that can significantly improve dog vaccination coverage,especially for free-roaming dogs.Safe and effective oral rabies vaccines for dogs are still being sought.In our previous studies,we generated a genetically modified rabies virus(RABV) ERA strain,rERAG_(333E),containing a mutation from arginine(Arg,R) to glutamic acid(Glu,E) at residue 333 of the G protein(G_(333E)).Our previous results demonstrated that rERAG_(333E) was safe for adult mice and dogs,and oral vaccination with rERAG_(333E) induced a strong and long-lasting protective immune response in dogs.Here,we further investigated the safety and immunogenicity of rERAG_(333E) in nontarget species,including suckling mice,rhesus monkeys,foxes,raccoon dogs,piglets,goats,and sheep.Suckling mice studies demonstrated that the G_(333E) mutation significantly reduced the virulence of the ERA strain.All of the suckling mice aged 10 days and above survived and showed no apparent signs of disease after intracerebral inoculation with rERAG_(333E).Animal studies demonstrated that rERAG_(333E) was safe in rhesus monkeys,foxes,raccoon dogs,piglets,goats,and sheep.None of those animals inoculated orally with 10 times the intended field dose of rERAG_(333E) showed abnormal clinical signs before and after the booster immunization with Rabvac 3,an inactivated rabies vaccine.Meanwhile,oral inoculation with rERAG_(333E) induced strong neutralizing antibody(NA) responses to RABV in rhesus monkeys,foxes,raccoon dogs,and piglets.These results demonstrated that rERAG_(333E) has the potential to serve as a safe oral rabies vaccine for dogs.展开更多
Flowering time is a critical agronomic trait with a profound effect on the productivity and adaptabillity of rapeseed(Brassica napus L.).Strategically advancing flowering time can reduce the risk of yield losses due t...Flowering time is a critical agronomic trait with a profound effect on the productivity and adaptabillity of rapeseed(Brassica napus L.).Strategically advancing flowering time can reduce the risk of yield losses due to extreme climatic conditions and facilitate the cultivation of subsequent crops on the same land,thereby enhancing overall agricultural efficiency.In this review,we synthesize current information on flowering time regulation in rapeseed through an integrated analysis of its genetic,hormonal,and environmental dimensions,emphasizing their crosstalk and implications for yield.We consolidate multi-omics evidence from population genetics,functional genomics,and systems biology to create a haplotype-based framework that overcomes the trade-off between flowering time and yield,providing support for the precision breeding of early-maturing cultivars.The insights presented here could inform future research on flowering time regulation and guide strategies for increasing rapeseed productivity.展开更多
Populus species,important economic species combining rapid growth with broad ecological adaptability,play a critical role in sustainable forestry and bioenergy production.In this study,we performed whole-genome resequ...Populus species,important economic species combining rapid growth with broad ecological adaptability,play a critical role in sustainable forestry and bioenergy production.In this study,we performed whole-genome resequencing of 707 individuals from a full-sib family to develop comprehensive single nucleotide polymorphism(SNP)markers and constructed a high-density genetic linkage map of 19 linkage groups.The total genetic length of the map reached 3623.65 cM with an average marker interval of 0.34 cM.By integrating multidimensional phenotypic data,89 quantitative trait loci(QTL)associated with growth,wood physical and chemical properties,disease resistance,and leaf morphology traits were identified,with logarithm of odds(LOD)scores ranging from 3.13 to 21.72 Notably,pleiotropic analysis revealed significant colocaliza and phenotypic variance explained between 1.7% and 11.6%.-tion hotspots on chromosomes LG1,LG5,LG6,LG8,and LG14,with epistatic interaction network analysis confirming genetic basis of coordinated regulation across multiple traits.Functional annotation of 207 candidate genes showed that R2R3-MYB and bHLH transcription factors and pyruvate kinase-encoding genes were significantly enriched,suggesting crucial roles in lignin biosynthesis and carbon metabolic pathways.Allelic effect analysis indicated that the frequency of favorable alleles associated with target traits ranged from 0.20 to 0.55.Incorporation of QTL-derived favorable alleles as random effects into Bayesian-based genomic selection models led to an increase in prediction accuracy ranging from 1% to 21%,with Bayesian ridge regression as the best predictive model.This study provides valuable genomic resources and genetic insights for deciphering complex trait architecture and advancing molecular breeding in poplar.展开更多
Peanuts(Arachis hypogaea) are important sources of vegetable oil,protein,and forage.The genus Arachis comprises nine intrageneric taxonomic sections encompassing 84 species.Most Arachis species are wild plants that se...Peanuts(Arachis hypogaea) are important sources of vegetable oil,protein,and forage.The genus Arachis comprises nine intrageneric taxonomic sections encompassing 84 species.Most Arachis species are wild plants that serve widely as forage and turfgrass.Furthermore,wild Arachis species provide valuable gene resources for broadening the genetic diversity of cultivated peanuts.To date,several key genes have been identified through the use of recombinant inbred lines derived from interspecific crosses within Arachis.Despite this progress,the application of genetic engineering to enhance peanut traits remains limited.This limitation arises primarily from the absence of a robust and reliable genetic transformation protocol for Arachis species.Nevertheless,evidence indicates that successful genetic transformation of Arachis plants was first reported approximately 30 years ago.Thus,a notable discrepancy exists between early reports of transformation success and the ongoing challenges in stably transferring candidate genes into Arachis genotypes.This review summarizes existing methods for regeneration and genetic transformation in Arachis,aiming to advance understanding of transgenic technologies applicable to this genus.展开更多
Bread wheat(Triticum aestivum L.)is a staple hexaploid crop with numerous wild relatives.However,domestication and modern breeding have significantly narrowed its genetic diversity,diminishing its capacity to adapt to...Bread wheat(Triticum aestivum L.)is a staple hexaploid crop with numerous wild relatives.However,domestication and modern breeding have significantly narrowed its genetic diversity,diminishing its capacity to adapt to climate change.Wild relatives of wheat serve as a vital reservoir of genetic diversity,offering traits thatenhance its resistance to various biotic and abiotic stresses.Over recent decades,remarkable progress has been made in utilizing superior genes from wild relatives to bolster wheat's defenses against diseases and pests,though the exploration of genes conferring abiotic stress tolerance has lagged behind.In this review,we summarize key advancements in the utilization of wild relatives for wheat enhancement over the past century,emphasizing both theoretical and technological innovations.Furthermore,we evaluate the potential contributions of wild relatives to address production challenges posed by climate change.We also explore strategies for isolating superior genes and developing prebreeding germplasm to support the future development of climate-resilient wheat varieties.展开更多
Stichopus chloronotus is a tropical sea cucumber with facultative asexual reproduction in the Indo-Western Pacific,yet its wild populations are decreasing due to extensive harvesting.Understanding the species’genetic...Stichopus chloronotus is a tropical sea cucumber with facultative asexual reproduction in the Indo-Western Pacific,yet its wild populations are decreasing due to extensive harvesting.Understanding the species’genetic characteristics is essential for effective management and conservation.To develop novel microsatellite markers and assess the genetic diversity,clonality,and genetic structure of eight populations of S.chloronotus in the South China Sea,193 individuals from eight populations across Wuzhizhou and Fenjiezhou(Boundary)islands were analyzed using nine newly developed microsatellite markers and five previously established markers.RNA-Seq was employed to obtained 62662 unigenes and identified 16926 microsatellite loci.Fourteen polymorphic microsatellite loci were developed,of which 11 were highly polymorphic(polymorphic information content>0.5).The number of alleles(N_(a))ranged from 3 to 6 per locus,and the average Shannon diversity index(I)was 1.107.All the populations exhibited asexual reproduction,with regional variations in reproductive modes.Asexual reproduction was predominant in the northwestern Wuzhizhou Island population(SY 7)and the Fenjiezhou Island population(LS 8),where four and five predominant clones represented more than 89%of the individuals,which led to reduced genetic diversity.Overall,genetic diversity was moderately low,with significant genetic differentiation among populations(F_(ST)=0.33;P<0.001),suggesting limited gene flow(the number of migrants(N_(m))<1).These findings highlight the role of reproductive strategies in shaping fine-scale genetic differentiation in S.chloronotus.The limited recruitment success of sexually produced larvae and habitat heterogeneity likely constrain clone dispersal,contributing to distinct genetic restructuring.This study provided key insights into the interplay between reproductive strategies and genetic patterns in sea cucumbers,offering a scientific basis for targeted conservation efforts.展开更多
Accurate prediction of flood events is important for flood control and risk management.Machine learning techniques contributed greatly to advances in flood predictions,and existing studies mainly focused on predicting...Accurate prediction of flood events is important for flood control and risk management.Machine learning techniques contributed greatly to advances in flood predictions,and existing studies mainly focused on predicting flood resource variables using single or hybrid machine learning techniques.However,class-based flood predictions have rarely been investigated,which can aid in quickly diagnosing comprehensive flood characteristics and proposing targeted management strategies.This study proposed a prediction approach of flood regime metrics and event classes coupling machine learning algorithms with clustering-deduced membership degrees.Five algorithms were adopted for this exploration.Results showed that the class membership degrees accurately determined event classes with class hit rates up to 100%,compared with the four classes clustered from nine regime metrics.The nonlinear algorithms(Multiple Linear Regression,Random Forest,and least squares-Support Vector Machine)outperformed the linear techniques(Multiple Linear Regression and Stepwise Regression)in predicting flood regime metrics.The proposed approach well predicted flood event classes with average class hit rates of 66.0%-85.4%and 47.2%-76.0%in calibration and validation periods,respectively,particularly for the slow and late flood events.The predictive capability of the proposed prediction approach for flood regime metrics and classes was considerably stronger than that of hydrological modeling approach.展开更多
BACKGROUND Familial adenomatous polyposis(FAP)is a disorder of autosomal dominant inheritance that is responsible for around 1%of colorectal cancer(CRC)cases.AIM To determine the mutation profile of FAP-specific to th...BACKGROUND Familial adenomatous polyposis(FAP)is a disorder of autosomal dominant inheritance that is responsible for around 1%of colorectal cancer(CRC)cases.AIM To determine the mutation profile of FAP-specific to the Hungarian population.METHODS This prospective single-center study enrolled patients with clinically suspected FAP or attenuated FAP(aFAP).Whole-exome next-generation sequencing was performed to detect variants of 50 FAP priority genes and 173 CRC predisposing genes or other CRC disease-associated genes.To identify larger deletions and insertions,a multiplex amplifiable probe hybridization technique was used.The identified genes were then classified according to the American College of Medical Genetics and Genomics guidelines.RESULTS A total of 26 index patients with clinically suspected FAP(n=21)and aFAP(n=5)were enrolled.APC gene alterations were confirmed in 92.31%of the cases(region 1B deletion,n=2;whole-gene deletion,n=4;frameshift mutation,n=2;nonsense mutation,n=5,and splice mutation,n=1),with the remaining two cases having CHEK2 and MSH3 gene alterations.According to pathogenicity,21 cases had pathogenic mutations,6 cases had likely pathogenic mutations,and 16 cases had variants of unknown significance(VUS).The most frequent of the latter were the POLE(n=5)and PIEZO1(n=4)gene variants.CONCLUSION Germline mutations in the APC gene were confirmed in more than 90%of Hungarian patients with clinically suspected FAP.Although the role of VUS genes is unclear,they are highly likely to play a role in the development of CRC.展开更多
Prevention of biological invasion requires understanding how alien species invade native communities.Although studies have identified mechanisms that underlie plant invasion in some habitats,limited attention has focu...Prevention of biological invasion requires understanding how alien species invade native communities.Although studies have identified mechanisms that underlie plant invasion in some habitats,limited attention has focused on invasion patterns along elevational gradients.In this study,we asked which factors drive the global and regional distribution of the invasive plant Galinsoga quadriradiata along elevational gradients.To answer this question,we examined whether human activities(i.e.,roads)promote G.quadriradiata invasion,how seed dispersal-related traits of G.quadriradiata change along elevation gradients,and whether G.quadriradiata has adapted to high-elevation environments through phenotypic plasticity or genetic variation.On the global scale,we found that human activities and road density positively contribute to the G.quadriradiata expansion in mountainous areas.Field surveys in China revealed significant elevational differences in the seed dispersal traits of G.quadriradiata,with higher-elevation populations exhibiting lower dispersal ability and generally lower genetic diversity.Under common conditions,high-elevation populations showed higher leaf mass ratio but lower root mass ratio and reproductive allocation.This suggests that high-elevation environments create a barrier to dispersal for G.quadriradiata,and that G.quadriradiata has adapted phenotypically to these conditions.Our study indicates that the elevational invasion pattern of G.quadriradiata is shaped by multiple factors,particularly human activities and phenotypic adaptability.In addition,our finding that G.quadriradiata invasion at high elevations is not constrained by low genetic diversity indicates that monitoring and management of G.quadriradiata in mountainous areas should be strengthened.展开更多
The Fujian oyster(Crassostrea angulata) is an economically significant shellfish species distributed mainly along the Fujian coast, Southeast China. However, its genetic diversity and structure remain unclear. The mai...The Fujian oyster(Crassostrea angulata) is an economically significant shellfish species distributed mainly along the Fujian coast, Southeast China. However, its genetic diversity and structure remain unclear. The main distribution area of the C. angulata is located in Fujian, South China. In total, 420 C. angulata were collected from 14 natural habitats(populations) along the Fujian coast, and their genetic diversity and structure were analyzed in the mitochondrial COI and nuclear gene ITS2 sequences. Results reveal that all the 14 populations of C. angulata exhibited high levels of genetic diversity, with a total of 57(haplotype diversity: 0.811±0.016) and 124(haplotype diversity: 0.912±0.007) haplotypes revealed by COI and ITS2, respectively. Notably, significant intermediate level of genetic differentiations between the Ningde Zhujiang(ZJ) population(FS T by COI: 0.035–0.142, P<0.05;FS T by ITS2: 0.078–0.123, P<0.05) with other populations were observed for the first time, which is also supported by the results of molecular variance analysis(FC T by COI: 0.105, P<0.05;FC T by ITS2: 0.086, P<0.05) and the clustering of the ZJ population into distinct branches in the interpopulation genetic differentiation tree. Furthermore, the evolutionary tree and haplotype network analyses do not support the formation of a clear geographical genealogical structure among these 14 populations. In addition, the population dynamics analysis suggests that the C. angulata may have undergone expansion during the third ice age of the Pleistocene. These results provide a reference for the preservation and further genetic improvement of C. angulata.展开更多
Eggplant(Solanum melongena L.)is a globally important vegetable crop,renowned for its nutritional value and economic significance.It is abundant in bioactive compounds such as anthocyanins and chlorogenic acid,which h...Eggplant(Solanum melongena L.)is a globally important vegetable crop,renowned for its nutritional value and economic significance.It is abundant in bioactive compounds such as anthocyanins and chlorogenic acid,which have been associated with multiple health-promoting properties(Azuma et al.,2008;Gurbuz et al.,2018).Given its significant hybrid vigor,F1 hybrid varieties are widely preferred in commercial cultivation(Mistry et al.,2018).However,traditional breeding practices predominantly rely on phenotypic selection,a process that is not only labor-intensive but also time-consuming.展开更多
The growing recognition of the role of genetics in the development of amyotrophic lateral sclerosis is evident.However,there has yet to be a comprehensive analysis of the clinical characteristics and genetics of famil...The growing recognition of the role of genetics in the development of amyotrophic lateral sclerosis is evident.However,there has yet to be a comprehensive analysis of the clinical characteristics and genetics of familial amyotrophic lateral sclerosis in an Asian population.This study aimed to provide an in-depth analysis of the clinical features and genetic spectrum of familial amyotrophic lateral sclerosis over 15 years in a clinic-based cohort of patients from the Chinese mainland.Enrollment of 302 amyotrophic lateral sclerosis families from 28 provinces was undertaken from January 2008 to September 2023.A group-based trajectory model for disease progression based on amyotrophic lateral sclerosis Functional Rating Scale-Revised(ALSFRS-R)scores was validated using bootstrap internal validation in patients with familial amyotrophic lateral sclerosis,as well as patients with sporadic amyotrophic lateral sclerosis(matched at a 1:4 ratio,with replacement).DNA samples from 244 index patients were screened for variants in the pathogenic genes SOD1,FUS,TDP43,and C9ORF72,of which 146 were also subjected to genome-wide next-generation sequencing.Gene-level burden analysis was used to evaluate the distribution of rare variants in the cohort.We found that rapid dynamic disease progression was associated with an older age at onset,shorter diagnostic delay,lower body mass index,bulbar onset,and≥1 affected first-degree relative.Certain attributes,such as age at onset and time from onset to diagnosis,had comparable impacts on the clinical progression trajectories of both familial amyotrophic lateral sclerosis and sporadic amyotrophic lateral sclerosis.Harboring pathogenic/likely pathogenic variants in amyotrophic lateral sclerosis-causative genes reduced the age of onset of familial amyotrophic lateral sclerosis.Among the patients with familial amyotrophic lateral sclerosis,17.8%possessed≥2 pathogenic/likely pathogenic variants.Sequencing kernel association test analysis showed that the SOD1 rare variant burden(P=1.3e-15)was associated with a significant risk of familial amyotrophic lateral sclerosis.Our findings conclusively confirmed the clinical features and genetic spectrum of familial amyotrophic lateral sclerosis over 15 years in a clinical cohort from China,contributing to a deeper understanding of genotype-phenotype relationships in familial amyotrophic lateral sclerosis.This comprehensive evaluation of specific clinical characteristics,clinical prognosis,and genetic variants of amyotrophic lateral sclerosis based on detailed clinical and genetic information may lead to the development of genotype-specific treatment approaches.展开更多
Background Multibreed genomic prediction(MBGP)is crucial for improving prediction accuracy for breeds with small populations,for which limited data are often available.Recent studies have demonstrated that partitionin...Background Multibreed genomic prediction(MBGP)is crucial for improving prediction accuracy for breeds with small populations,for which limited data are often available.Recent studies have demonstrated that partitioning the genome into nonoverlapping blocks to model heterogeneous genetic(co)variance in multitrait models can achieve higher joint prediction accuracy.However,the block partitioning method,a key factor influencing model performance,has not been extensively explored.Results We introduce mbBayesABLD,a novel Bayesian MBGP model that partitions each chromosome into nonoverlapping blocks on the basis of linkage disequilibrium(LD)patterns.In this model,marker effects within each block are assumed to follow normal distributions with block-specific parameters.We employ simulated data as well as empirical datasets from pigs and beans to assess genomic prediction accuracy across different models using cross-validation.The results demonstrate that mbBayesABLD significantly outperforms conventional MBGP models,such as GBLUP and BayesR.For the meat marbling score trait in pigs,compared with GBLUP,which does not account for heterogeneous genetic(co)variance,mbBayesABLD improves the prediction accuracy for the small-population breed Landrace by 15.6%.Furthermore,our findings indicate that a moderate level of similarity in LD patterns between breeds(with an average correlation of 0.6)is sufficient to improve the prediction accuracy of the target breed.Conclusions This study presents a novel LD block-based approach for multibreed genomic prediction.Our work provides a practical tool for livestock breeding programs and offers new insights into leveraging genetic diversity across breeds for improved genomic prediction.展开更多
基金funded by King Fahd University of Petroleum&Minerals,Saudi Arabia under IRC-SES grant#INRE 2217.
文摘Wind energy has emerged as a potential replacement for fossil fuel-based energy sources.To harness maximum wind energy,a crucial decision in the development of an efficient wind farm is the optimal layout design.This layout defines the specific locations of the turbines within the wind farm.The process of finding the optimal locations of turbines,in the presence of various technical and technological constraints,makes the wind farm layout design problem a complex optimization problem.This problem has traditionally been solved with nature-inspired algorithms with promising results.The performance and convergence of nature-inspired algorithms depend on several parameters,among which the algorithm termination criterion plays a crucial role.Timely convergence is an important aspect of efficient algorithm design because an inefficient algorithm results in wasted computational resources,unwarranted electricity consumption,and hardware stress.This study provides an in-depth analysis of several termination criteria while using the genetic algorithm as a test bench,with its application to the wind farm layout design problem while considering various wind scenarios.The performance of six termination criteria is empirically evaluated with respect to the quality of solutions produced and the execution time involved.Due to the conflicting nature of these two attributes,fuzzy logic-based multi-attribute decision-making is employed in the decision process.Results for the fuzzy decision approach indicate that among the various criteria tested,the criterion Phi achieves an improvement in the range of 2.44%to 32.93%for wind scenario 1.For scenario 2,Best-worst termination criterion performed well compared to the other criteria evaluated,with an improvement in the range of 1.2%to 9.64%.For scenario 3,Hitting bound was the best performer with an improvement of 1.16%to 20.93%.
文摘Aiming to solve the steering instability and hysteresis of agricultural robots in the process of movement,a fusion PID control method of particle swarm optimization(PSO)and genetic algorithm(GA)was proposed.The fusion algorithm took advantage of the fast optimization ability of PSO to optimize the population screening link of GA.The Simulink simulation results showed that the convergence of the fitness function of the fusion algorithm was accelerated,the system response adjustment time was reduced,and the overshoot was almost zero.Then the algorithm was applied to the steering test of agricultural robot in various scenes.After modeling the steering system of agricultural robot,the steering test results in the unloaded suspended state showed that the PID control based on fusion algorithm reduced the rise time,response adjustment time and overshoot of the system,and improved the response speed and stability of the system,compared with the artificial trial and error PID control and the PID control based on GA.The actual road steering test results showed that the PID control response rise time based on the fusion algorithm was the shortest,about 4.43 s.When the target pulse number was set to 100,the actual mean value in the steady-state regulation stage was about 102.9,which was the closest to the target value among the three control methods,and the overshoot was reduced at the same time.The steering test results under various scene states showed that the PID control based on the proposed fusion algorithm had good anti-interference ability,it can adapt to the changes of environment and load and improve the performance of the control system.It was effective in the steering control of agricultural robot.This method can provide a reference for the precise steering control of other robots.
文摘Optimizing convolutional neural networks(CNNs)for IoT attack detection remains a critical yet challenging task due to the need to balance multiple performance metrics beyond mere accuracy.This study proposes a unified and flexible optimization framework that leverages metaheuristic algorithms to automatically optimize CNN configurations for IoT attack detection.Unlike conventional single-objective approaches,the proposed method formulates a global multi-objective fitness function that integrates accuracy,precision,recall,and model size(speed/model complexity penalty)with adjustable weights.This design enables both single-objective and weightedsum multi-objective optimization,allowing adaptive selection of optimal CNN configurations for diverse deployment requirements.Two representativemetaheuristic algorithms,GeneticAlgorithm(GA)and Particle Swarm Optimization(PSO),are employed to optimize CNNhyperparameters and structure.At each generation/iteration,the best configuration is selected as themost balanced solution across optimization objectives,i.e.,the one achieving themaximum value of the global objective function.Experimental validation on two benchmark datasets,Edge-IIoT and CIC-IoT2023,demonstrates that the proposed GA-and PSO-based models significantly enhance detection accuracy(94.8%–98.3%)and generalization compared with manually tuned CNN configurations,while maintaining compact architectures.The results confirm that the multi-objective framework effectively balances predictive performance and computational efficiency.This work establishes a generalizable and adaptive optimization strategy for deep learning-based IoT attack detection and provides a foundation for future hybrid metaheuristic extensions in broader IoT security applications.
文摘Optimization is the key to obtaining efficient utilization of resources in structural design.Due to the complex nature of truss systems,this study presents a method based on metaheuristic modelling that minimises structural weight under stress and frequency constraints.Two new algorithms,the Red Kite Optimization Algorithm(ROA)and Secretary Bird Optimization Algorithm(SBOA),are utilized on five benchmark trusses with 10,18,37,72,and 200-bar trusses.Both algorithms are evaluated against benchmarks in the literature.The results indicate that SBOA always reaches a lighter optimal.Designs with reducing structural weight ranging from 0.02%to 0.15%compared to ROA,and up to 6%–8%as compared to conventional algorithms.In addition,SBOA can achieve 15%–20%faster convergence speed and 10%–18%reduction in computational time with a smaller standard deviation over independent runs,which demonstrates its robustness and reliability.It is indicated that the adaptive exploration mechanism of SBOA,especially its Levy flight–based search strategy,can obviously improve optimization performance for low-and high-dimensional trusses.The research has implications in the context of promoting bio-inspired optimization techniques by demonstrating the viability of SBOA,a reliable model for large-scale structural design that provides significant enhancements in performance and convergence behavior.
文摘The etiopathogenesis of gastrointestinal diseases is varied in nature.Various etiogenic factors described are infective,inflammatory,viral,bacterial,parasitic,dietary and lifestyle change.Rare causative agents are immunological,and others associated as idiopathic,are undiagnosed by all possible means.Some of the rare diseases are congenital in nature,passing from the parent to the child.Many of the undiagnosed diseases are now being diagnosed as genetic and the genes have been implicated as a causative agent.There is a search for newer treatments for such diseases,which is called genomic medicine.Genomic medicine is an emerging medical discipline that involves the use of genomic information about an individual.This is used both for diagnostic as well as therapeutic decisions to improve the current health domain and pave the way for policymakers for its clinical use.In the developing era of precision medicine,genomics,epigenomics,environmental exposure,and other data would be used to more accurately guide individual diagnosis and treatment.Genomic medicine is already making an impact in the fields of oncology,pharmacology,rare,infectious and many undiagnosed diseases.It is beginning to fuel new approaches in certain medical specialties.Oncology is at the leading edge of incorporating genomics,as diagnostics for genetic and genomic markers are increasingly included in cancer screening,and to guide tailored treatment strategies.Genetics and genetic medicine have been reported to play a role in gastroenterology in several ways,including genetic testing(hereditary pancreatitis and hereditary gastrointestinal cancer syndromes).Genetic testing can also help subtype diseases,such as classifying pancreatitis as idiopathic or hereditary.Gene therapy is a promising approach for treating gastrointestinal diseases that are not effectively treated by conventional pharmaceuticals and surgeries.Gene therapy strategies include gene addition,gene editing,messenger RNA therapy,and gene silencing.Understanding genetic determinants,advances in genetics,have led to a better understanding of the genetic factors that contribute to human disease.Family-member risk stratification and genetic diagnosis can help identify family members who are at risk,which can lead to preventive treatments,lifestyle recommendations,and routine follow ups.Selecting target genes helps identify the gene targets associated with each gastrointestinal disease.Common gastrointestinal diseases associated with genetic abnormalities include-inflammatory bowel disease,gastroesophageal reflux disease,non-alcoholic fatty liver disease,and irritable bowel syndrome.With advancing tools and technology,research in the search of newer and individualized treatment,genes and genetic medicines are expected to play a significant role in human health and gastroenterology.
基金supported by National Key Research and Development Program of China(2024YFF1307400)Hubei Provincial Natural Science Foundation and Three Gorges Innovation Development Joint Fund(Grant No.2023AFD195)China Three Gorges Corporation(NBZZ202300130).
文摘Successful ex situ conservation of plant populations requires a high degree of genetic representativeness.However,spatially biased sampling in ex situ conservation efforts may fail to capture all wild genetic clusters for species with range-wide genetic structure.To investigate the extent of spatially biased sampling in living collections and the coverage of wild genetic clusters in plant populations under ex situ conservation worldwide,we combined a global synthesis of ex situ conservation efforts with a case study of an endangered riparian plant species,Myricaria laxiflora.Our analysis of ex situ conservation worldwide revealed that the majority(82.6%)of ex situ populations fail to cover all wild genetic clusters,largely due to spatially biased sampling with low geographic coverage.Our case study of M.laxiflora showed that genetic diversity differed between the ex situ and upstream populations,while it was comparable between ex situ populations and other wild populations.However,current ex situ populations did not cover all wild genetic clusters,as the upstream genetic cluster was previously uncollected.Our study suggests that the failure to cover all wild genetic clusters in ex situ populations is a widespread issue,and ex situ populations with high genetic diversity can also fail to cover all wild genetic clusters.In future ex situ conservation programs,both the importance of high genetic diversity and the high coverage of wild genetic clusters should be prioritized.
基金funding from the European Commission by the Ruralities project(grant agreement no.101060876).
文摘In this paper,we propose a new privacy-aware transmission scheduling algorithm for 6G ad hoc networks.This system enables end nodes to select the optimum time and scheme to transmit private data safely.In 6G dynamic heterogeneous infrastructures,unstable links and non-uniform hardware capabilities create critical issues regarding security and privacy.Traditional protocols are often too computationally heavy to allow 6G services to achieve their expected Quality-of-Service(QoS).As the transport network is built of ad hoc nodes,there is no guarantee about their trustworthiness or behavior,and transversal functionalities are delegated to the extreme nodes.However,while security can be guaranteed in extreme-to-extreme solutions,privacy cannot,as all intermediate nodes still have to handle the data packets they are transporting.Besides,traditional schemes for private anonymous ad hoc communications are vulnerable against modern intelligent attacks based on learning models.The proposed scheme fulfills this gap.Findings show the probability of a successful intelligent attack reduces by up to 65%compared to ad hoc networks with no privacy protection strategy when used the proposed technology.While congestion probability can remain below 0.001%,as required in 6G services.
基金supported by the Natural Science Foundation of Heilongjiang Province,China (YQ2022C040)。
文摘Oral immunization is an alternative or supplementary approach that can significantly improve dog vaccination coverage,especially for free-roaming dogs.Safe and effective oral rabies vaccines for dogs are still being sought.In our previous studies,we generated a genetically modified rabies virus(RABV) ERA strain,rERAG_(333E),containing a mutation from arginine(Arg,R) to glutamic acid(Glu,E) at residue 333 of the G protein(G_(333E)).Our previous results demonstrated that rERAG_(333E) was safe for adult mice and dogs,and oral vaccination with rERAG_(333E) induced a strong and long-lasting protective immune response in dogs.Here,we further investigated the safety and immunogenicity of rERAG_(333E) in nontarget species,including suckling mice,rhesus monkeys,foxes,raccoon dogs,piglets,goats,and sheep.Suckling mice studies demonstrated that the G_(333E) mutation significantly reduced the virulence of the ERA strain.All of the suckling mice aged 10 days and above survived and showed no apparent signs of disease after intracerebral inoculation with rERAG_(333E).Animal studies demonstrated that rERAG_(333E) was safe in rhesus monkeys,foxes,raccoon dogs,piglets,goats,and sheep.None of those animals inoculated orally with 10 times the intended field dose of rERAG_(333E) showed abnormal clinical signs before and after the booster immunization with Rabvac 3,an inactivated rabies vaccine.Meanwhile,oral inoculation with rERAG_(333E) induced strong neutralizing antibody(NA) responses to RABV in rhesus monkeys,foxes,raccoon dogs,and piglets.These results demonstrated that rERAG_(333E) has the potential to serve as a safe oral rabies vaccine for dogs.
基金supported by the National Key Research and Development Program of China(2022YFD1200400)the National Natural Science Foundation of China(32272111)+4 种基金Special fund for youth team of the Southwest Universities(SWU-XJPY202306)Chongqing Natural Science Foundation(CSTB2024NSCQLZX0012)Modern Agro-industry Technology Research System(CARS-12)Chongqing Modern Agricultural Industry Technology System(COMAITS202504)Biological Breeding-National Science and Technology Major Project(2022ZD04008).We sincerely appreciate the Plant Editors team for English language editing of the manuscript,which significantly improved its clarity and overall quality.
文摘Flowering time is a critical agronomic trait with a profound effect on the productivity and adaptabillity of rapeseed(Brassica napus L.).Strategically advancing flowering time can reduce the risk of yield losses due to extreme climatic conditions and facilitate the cultivation of subsequent crops on the same land,thereby enhancing overall agricultural efficiency.In this review,we synthesize current information on flowering time regulation in rapeseed through an integrated analysis of its genetic,hormonal,and environmental dimensions,emphasizing their crosstalk and implications for yield.We consolidate multi-omics evidence from population genetics,functional genomics,and systems biology to create a haplotype-based framework that overcomes the trade-off between flowering time and yield,providing support for the precision breeding of early-maturing cultivars.The insights presented here could inform future research on flowering time regulation and guide strategies for increasing rapeseed productivity.
基金supported by the National Key Research and Development Plan of China(2021YFD2200202)the Key Research and Development Project of Jiangsu Province,China(BE2021366).
文摘Populus species,important economic species combining rapid growth with broad ecological adaptability,play a critical role in sustainable forestry and bioenergy production.In this study,we performed whole-genome resequencing of 707 individuals from a full-sib family to develop comprehensive single nucleotide polymorphism(SNP)markers and constructed a high-density genetic linkage map of 19 linkage groups.The total genetic length of the map reached 3623.65 cM with an average marker interval of 0.34 cM.By integrating multidimensional phenotypic data,89 quantitative trait loci(QTL)associated with growth,wood physical and chemical properties,disease resistance,and leaf morphology traits were identified,with logarithm of odds(LOD)scores ranging from 3.13 to 21.72 Notably,pleiotropic analysis revealed significant colocaliza and phenotypic variance explained between 1.7% and 11.6%.-tion hotspots on chromosomes LG1,LG5,LG6,LG8,and LG14,with epistatic interaction network analysis confirming genetic basis of coordinated regulation across multiple traits.Functional annotation of 207 candidate genes showed that R2R3-MYB and bHLH transcription factors and pyruvate kinase-encoding genes were significantly enriched,suggesting crucial roles in lignin biosynthesis and carbon metabolic pathways.Allelic effect analysis indicated that the frequency of favorable alleles associated with target traits ranged from 0.20 to 0.55.Incorporation of QTL-derived favorable alleles as random effects into Bayesian-based genomic selection models led to an increase in prediction accuracy ranging from 1% to 21%,with Bayesian ridge regression as the best predictive model.This study provides valuable genomic resources and genetic insights for deciphering complex trait architecture and advancing molecular breeding in poplar.
基金funded by the Key R&D Program of Shandong Province,China (2024LZGC035)the Start-up Foundation for High Talents of Qingdao Agricultural University,China (665/1120012)。
文摘Peanuts(Arachis hypogaea) are important sources of vegetable oil,protein,and forage.The genus Arachis comprises nine intrageneric taxonomic sections encompassing 84 species.Most Arachis species are wild plants that serve widely as forage and turfgrass.Furthermore,wild Arachis species provide valuable gene resources for broadening the genetic diversity of cultivated peanuts.To date,several key genes have been identified through the use of recombinant inbred lines derived from interspecific crosses within Arachis.Despite this progress,the application of genetic engineering to enhance peanut traits remains limited.This limitation arises primarily from the absence of a robust and reliable genetic transformation protocol for Arachis species.Nevertheless,evidence indicates that successful genetic transformation of Arachis plants was first reported approximately 30 years ago.Thus,a notable discrepancy exists between early reports of transformation success and the ongoing challenges in stably transferring candidate genes into Arachis genotypes.This review summarizes existing methods for regeneration and genetic transformation in Arachis,aiming to advance understanding of transgenic technologies applicable to this genus.
基金supported by the Biological Breeding-National Science and Technology Major Project(2023ZD04071)the National Key Research and Development Program of China(2023YFF1000600)and the National Natural Science Foundation of China(32272084,32372089,and 31971887).
文摘Bread wheat(Triticum aestivum L.)is a staple hexaploid crop with numerous wild relatives.However,domestication and modern breeding have significantly narrowed its genetic diversity,diminishing its capacity to adapt to climate change.Wild relatives of wheat serve as a vital reservoir of genetic diversity,offering traits thatenhance its resistance to various biotic and abiotic stresses.Over recent decades,remarkable progress has been made in utilizing superior genes from wild relatives to bolster wheat's defenses against diseases and pests,though the exploration of genes conferring abiotic stress tolerance has lagged behind.In this review,we summarize key advancements in the utilization of wild relatives for wheat enhancement over the past century,emphasizing both theoretical and technological innovations.Furthermore,we evaluate the potential contributions of wild relatives to address production challenges posed by climate change.We also explore strategies for isolating superior genes and developing prebreeding germplasm to support the future development of climate-resilient wheat varieties.
基金Supported by the National Key Research and Development Program of China(Nos.2022YFD2401305,2022YFD2401303)the National Natural Science Foundation of China(Nos.42166005,42076097)。
文摘Stichopus chloronotus is a tropical sea cucumber with facultative asexual reproduction in the Indo-Western Pacific,yet its wild populations are decreasing due to extensive harvesting.Understanding the species’genetic characteristics is essential for effective management and conservation.To develop novel microsatellite markers and assess the genetic diversity,clonality,and genetic structure of eight populations of S.chloronotus in the South China Sea,193 individuals from eight populations across Wuzhizhou and Fenjiezhou(Boundary)islands were analyzed using nine newly developed microsatellite markers and five previously established markers.RNA-Seq was employed to obtained 62662 unigenes and identified 16926 microsatellite loci.Fourteen polymorphic microsatellite loci were developed,of which 11 were highly polymorphic(polymorphic information content>0.5).The number of alleles(N_(a))ranged from 3 to 6 per locus,and the average Shannon diversity index(I)was 1.107.All the populations exhibited asexual reproduction,with regional variations in reproductive modes.Asexual reproduction was predominant in the northwestern Wuzhizhou Island population(SY 7)and the Fenjiezhou Island population(LS 8),where four and five predominant clones represented more than 89%of the individuals,which led to reduced genetic diversity.Overall,genetic diversity was moderately low,with significant genetic differentiation among populations(F_(ST)=0.33;P<0.001),suggesting limited gene flow(the number of migrants(N_(m))<1).These findings highlight the role of reproductive strategies in shaping fine-scale genetic differentiation in S.chloronotus.The limited recruitment success of sexually produced larvae and habitat heterogeneity likely constrain clone dispersal,contributing to distinct genetic restructuring.This study provided key insights into the interplay between reproductive strategies and genetic patterns in sea cucumbers,offering a scientific basis for targeted conservation efforts.
基金National Key Research and Development Program of China,No.2023YFC3006704National Natural Science Foundation of China,No.42171047CAS-CSIRO Partnership Joint Project of 2024,No.177GJHZ2023097MI。
文摘Accurate prediction of flood events is important for flood control and risk management.Machine learning techniques contributed greatly to advances in flood predictions,and existing studies mainly focused on predicting flood resource variables using single or hybrid machine learning techniques.However,class-based flood predictions have rarely been investigated,which can aid in quickly diagnosing comprehensive flood characteristics and proposing targeted management strategies.This study proposed a prediction approach of flood regime metrics and event classes coupling machine learning algorithms with clustering-deduced membership degrees.Five algorithms were adopted for this exploration.Results showed that the class membership degrees accurately determined event classes with class hit rates up to 100%,compared with the four classes clustered from nine regime metrics.The nonlinear algorithms(Multiple Linear Regression,Random Forest,and least squares-Support Vector Machine)outperformed the linear techniques(Multiple Linear Regression and Stepwise Regression)in predicting flood regime metrics.The proposed approach well predicted flood event classes with average class hit rates of 66.0%-85.4%and 47.2%-76.0%in calibration and validation periods,respectively,particularly for the slow and late flood events.The predictive capability of the proposed prediction approach for flood regime metrics and classes was considerably stronger than that of hydrological modeling approach.
基金Supported by the Research Grants of the National Research,Development and Innovation Office,No.K125377,No.K134863 and No.K143549New National Excellence Program of the Ministry of Human Capacities,No.UNKP-20-5-SZTE-161,No.UNKP-22-3-SZTE-233,No.UNKP-23-5-SZTE-719,No.UNKP-22-4-SZTE-296 and No.UNKP-22-3-SZTE-278+1 种基金Janos Bolyai Research Grant,No.BO/00723/22the Géza Hetényi Research Grant by Albert Szent-Györgyi Medical School,University of Szeged.
文摘BACKGROUND Familial adenomatous polyposis(FAP)is a disorder of autosomal dominant inheritance that is responsible for around 1%of colorectal cancer(CRC)cases.AIM To determine the mutation profile of FAP-specific to the Hungarian population.METHODS This prospective single-center study enrolled patients with clinically suspected FAP or attenuated FAP(aFAP).Whole-exome next-generation sequencing was performed to detect variants of 50 FAP priority genes and 173 CRC predisposing genes or other CRC disease-associated genes.To identify larger deletions and insertions,a multiplex amplifiable probe hybridization technique was used.The identified genes were then classified according to the American College of Medical Genetics and Genomics guidelines.RESULTS A total of 26 index patients with clinically suspected FAP(n=21)and aFAP(n=5)were enrolled.APC gene alterations were confirmed in 92.31%of the cases(region 1B deletion,n=2;whole-gene deletion,n=4;frameshift mutation,n=2;nonsense mutation,n=5,and splice mutation,n=1),with the remaining two cases having CHEK2 and MSH3 gene alterations.According to pathogenicity,21 cases had pathogenic mutations,6 cases had likely pathogenic mutations,and 16 cases had variants of unknown significance(VUS).The most frequent of the latter were the POLE(n=5)and PIEZO1(n=4)gene variants.CONCLUSION Germline mutations in the APC gene were confirmed in more than 90%of Hungarian patients with clinically suspected FAP.Although the role of VUS genes is unclear,they are highly likely to play a role in the development of CRC.
基金supported by the National Natural Science Foundation of China(32271584 and 31600445)the Natural Science Basic Research Plan in Shaanxi Province of China(2020JM-286)+2 种基金the Fundamental Research Funds for the Central Universities(GK202103072,GK202103073)the National College Students'Innovative Entrepreneurial Training Plan Program(202310718085)Special Research Project in Philosophy and Social Sciences of Shaanxi Province(2022HZ1795).
文摘Prevention of biological invasion requires understanding how alien species invade native communities.Although studies have identified mechanisms that underlie plant invasion in some habitats,limited attention has focused on invasion patterns along elevational gradients.In this study,we asked which factors drive the global and regional distribution of the invasive plant Galinsoga quadriradiata along elevational gradients.To answer this question,we examined whether human activities(i.e.,roads)promote G.quadriradiata invasion,how seed dispersal-related traits of G.quadriradiata change along elevation gradients,and whether G.quadriradiata has adapted to high-elevation environments through phenotypic plasticity or genetic variation.On the global scale,we found that human activities and road density positively contribute to the G.quadriradiata expansion in mountainous areas.Field surveys in China revealed significant elevational differences in the seed dispersal traits of G.quadriradiata,with higher-elevation populations exhibiting lower dispersal ability and generally lower genetic diversity.Under common conditions,high-elevation populations showed higher leaf mass ratio but lower root mass ratio and reproductive allocation.This suggests that high-elevation environments create a barrier to dispersal for G.quadriradiata,and that G.quadriradiata has adapted phenotypically to these conditions.Our study indicates that the elevational invasion pattern of G.quadriradiata is shaped by multiple factors,particularly human activities and phenotypic adaptability.In addition,our finding that G.quadriradiata invasion at high elevations is not constrained by low genetic diversity indicates that monitoring and management of G.quadriradiata in mountainous areas should be strengthened.
基金Supported by the National Natural Science Foundation of China(No.32172979)the Natural Science Foundation of Fujian Province(No.2021J05159)the 2023 Special Program for Promoting High-Quality Development of Marine and Fishery Industry in Fujian Province(No.PJHYF-L-2023-2)。
文摘The Fujian oyster(Crassostrea angulata) is an economically significant shellfish species distributed mainly along the Fujian coast, Southeast China. However, its genetic diversity and structure remain unclear. The main distribution area of the C. angulata is located in Fujian, South China. In total, 420 C. angulata were collected from 14 natural habitats(populations) along the Fujian coast, and their genetic diversity and structure were analyzed in the mitochondrial COI and nuclear gene ITS2 sequences. Results reveal that all the 14 populations of C. angulata exhibited high levels of genetic diversity, with a total of 57(haplotype diversity: 0.811±0.016) and 124(haplotype diversity: 0.912±0.007) haplotypes revealed by COI and ITS2, respectively. Notably, significant intermediate level of genetic differentiations between the Ningde Zhujiang(ZJ) population(FS T by COI: 0.035–0.142, P<0.05;FS T by ITS2: 0.078–0.123, P<0.05) with other populations were observed for the first time, which is also supported by the results of molecular variance analysis(FC T by COI: 0.105, P<0.05;FC T by ITS2: 0.086, P<0.05) and the clustering of the ZJ population into distinct branches in the interpopulation genetic differentiation tree. Furthermore, the evolutionary tree and haplotype network analyses do not support the formation of a clear geographical genealogical structure among these 14 populations. In addition, the population dynamics analysis suggests that the C. angulata may have undergone expansion during the third ice age of the Pleistocene. These results provide a reference for the preservation and further genetic improvement of C. angulata.
基金supported by Yuelushan Laboratory Breeding Program(Grant No.YLS-2025-ZY02013)The Project of National Key Laboratory for Tropical Crop Breeding(Grant No.NKLTCB202341)+4 种基金The New Variety Breeding Project of the Major Science and Technology Projects of Zhejiang(Grant No.2021C02065-1-3)Hunan Provincial Agricultural Science and Technology Innovation Fund Project(Grant No.2025CX115)Key R&D Projects in Hainan Province(Grant No.ZDYF2023XDNY041)Central Public-interest Scientific Institution Basal Research Fund(Grant No.1630062022003)2024 Sanya Technology Stars Program(Grant No.2024KJFX022).
文摘Eggplant(Solanum melongena L.)is a globally important vegetable crop,renowned for its nutritional value and economic significance.It is abundant in bioactive compounds such as anthocyanins and chlorogenic acid,which have been associated with multiple health-promoting properties(Azuma et al.,2008;Gurbuz et al.,2018).Given its significant hybrid vigor,F1 hybrid varieties are widely preferred in commercial cultivation(Mistry et al.,2018).However,traditional breeding practices predominantly rely on phenotypic selection,a process that is not only labor-intensive but also time-consuming.
基金supported by the Natural Science Foundation of Beijing,Nos.7244428(to WZ)and 7222215(to JH)the Peking University Medicine Sailing Program forYoung Scholars’Scientific and Technological Innovation,No.BMU2023YFJHPY034(to WZ)+4 种基金the National Natural Science Foundation of China,Nos.81873784,82071426(to DF),and81974197(to JH)the Clinical Cohort Construction Program of Peking University Third Hospital,No.BYSYDL2019002(to DF)Beijing Physician-Scientist TrainingProgram,No.BJPSTP-2024-03(to JH)the China Postdoctoral Science Foundation,Nos.2022TQ0014(to LX),2022M720284(to LX)the E-Town Cooperation&Development Foundation,No.YCXJ-JZ-2023-017(to LX).
文摘The growing recognition of the role of genetics in the development of amyotrophic lateral sclerosis is evident.However,there has yet to be a comprehensive analysis of the clinical characteristics and genetics of familial amyotrophic lateral sclerosis in an Asian population.This study aimed to provide an in-depth analysis of the clinical features and genetic spectrum of familial amyotrophic lateral sclerosis over 15 years in a clinic-based cohort of patients from the Chinese mainland.Enrollment of 302 amyotrophic lateral sclerosis families from 28 provinces was undertaken from January 2008 to September 2023.A group-based trajectory model for disease progression based on amyotrophic lateral sclerosis Functional Rating Scale-Revised(ALSFRS-R)scores was validated using bootstrap internal validation in patients with familial amyotrophic lateral sclerosis,as well as patients with sporadic amyotrophic lateral sclerosis(matched at a 1:4 ratio,with replacement).DNA samples from 244 index patients were screened for variants in the pathogenic genes SOD1,FUS,TDP43,and C9ORF72,of which 146 were also subjected to genome-wide next-generation sequencing.Gene-level burden analysis was used to evaluate the distribution of rare variants in the cohort.We found that rapid dynamic disease progression was associated with an older age at onset,shorter diagnostic delay,lower body mass index,bulbar onset,and≥1 affected first-degree relative.Certain attributes,such as age at onset and time from onset to diagnosis,had comparable impacts on the clinical progression trajectories of both familial amyotrophic lateral sclerosis and sporadic amyotrophic lateral sclerosis.Harboring pathogenic/likely pathogenic variants in amyotrophic lateral sclerosis-causative genes reduced the age of onset of familial amyotrophic lateral sclerosis.Among the patients with familial amyotrophic lateral sclerosis,17.8%possessed≥2 pathogenic/likely pathogenic variants.Sequencing kernel association test analysis showed that the SOD1 rare variant burden(P=1.3e-15)was associated with a significant risk of familial amyotrophic lateral sclerosis.Our findings conclusively confirmed the clinical features and genetic spectrum of familial amyotrophic lateral sclerosis over 15 years in a clinical cohort from China,contributing to a deeper understanding of genotype-phenotype relationships in familial amyotrophic lateral sclerosis.This comprehensive evaluation of specific clinical characteristics,clinical prognosis,and genetic variants of amyotrophic lateral sclerosis based on detailed clinical and genetic information may lead to the development of genotype-specific treatment approaches.
基金supported by the Biological Breeding-Major Projects in National Science and Technology(No.2023ZD0404405)the Earmarked Fund for China Agriculture Research System(No.CARS-pig-35)+2 种基金the National Natural Science Foundation of China(No.3227284,32302708)the 2115 Talent Development Program of China Agricultural University,the Chinese Universities Scientific Fund(No.2023TC196)the Seed Industry Revitalization Action Project of Guangdong Province(No.2024-XPY-06-001)。
文摘Background Multibreed genomic prediction(MBGP)is crucial for improving prediction accuracy for breeds with small populations,for which limited data are often available.Recent studies have demonstrated that partitioning the genome into nonoverlapping blocks to model heterogeneous genetic(co)variance in multitrait models can achieve higher joint prediction accuracy.However,the block partitioning method,a key factor influencing model performance,has not been extensively explored.Results We introduce mbBayesABLD,a novel Bayesian MBGP model that partitions each chromosome into nonoverlapping blocks on the basis of linkage disequilibrium(LD)patterns.In this model,marker effects within each block are assumed to follow normal distributions with block-specific parameters.We employ simulated data as well as empirical datasets from pigs and beans to assess genomic prediction accuracy across different models using cross-validation.The results demonstrate that mbBayesABLD significantly outperforms conventional MBGP models,such as GBLUP and BayesR.For the meat marbling score trait in pigs,compared with GBLUP,which does not account for heterogeneous genetic(co)variance,mbBayesABLD improves the prediction accuracy for the small-population breed Landrace by 15.6%.Furthermore,our findings indicate that a moderate level of similarity in LD patterns between breeds(with an average correlation of 0.6)is sufficient to improve the prediction accuracy of the target breed.Conclusions This study presents a novel LD block-based approach for multibreed genomic prediction.Our work provides a practical tool for livestock breeding programs and offers new insights into leveraging genetic diversity across breeds for improved genomic prediction.
