A growing global population and the increasing prevalence of diet-related health issues such as“hidden hunger”,obesity,hypertension,and diabetes necessitate a fundamental rethinking of crop design and breeding.Synth...A growing global population and the increasing prevalence of diet-related health issues such as“hidden hunger”,obesity,hypertension,and diabetes necessitate a fundamental rethinking of crop design and breeding.Synthetic metabolic engineering offers a method to modify and redesign metabolic pathways to increase the nutritional value of crops.We summarize recent advances in the biofortification of key nutrients including provitamin A,vitamin C,vitamin B9,iron,zinc,anthocyanins,flavonoids,and unsaturated fatty acids.We discuss the potential of multi-gene stacking,gene editing,enzyme engineering,and artificial intelligence in synthetic metabolic engineering.We propose future research directions and potential solutions centered on leveraging AI-driven systems biology,precision gene editing,enzyme engineering,agrobacterium-mediated genotype-independent transformation,and modular metabolic engineering strategies to develop next-generation nutritionally enhanced super crops and transform global food systems.展开更多
1.Introduction Crop breeding is transitioning to engineering by synthetic biology.Conventional breeding,constrained by limited genetic variation and lengthy development cycles,cannot meet the challenges of micronutrie...1.Introduction Crop breeding is transitioning to engineering by synthetic biology.Conventional breeding,constrained by limited genetic variation and lengthy development cycles,cannot meet the challenges of micronutrient malnutrition and yield reductions from climate change with sufficient speed or precision[1].Consequently,agriculture is transitioning from selection-based breeding to designbased engineering.Synthetic biology enables the precision modification of metabolic pathways and the construction of novel trait combinations[1,2].This special issue,Synthetic Biology for Crop Improvement,brings together 26 articles that showcase the field’s transition from laboratory curiosity to field-validated agricultural technology.The collection spans 13 plant species,from staple grains and major industrial crops to horticultural and medicinal plants,demonstrating the universal applicability of metabolic engineering.These studies reveal maturation toward field readiness:independent groups achieving reproducible results in identical pathways,greenhouse concepts advancing to multi-season field trials,and engineered traits delivering measurable agronomic value.This progression answers the central question in crop synthetic biology,shifting the paradigm from asking“can it work?”to demonstrating“how it works,and here are the yields”.This transformation is grounded in understanding and manipulating plant metabolism at molecular resolution[3].展开更多
Betalain,an economically valuable water-soluble natural plant pigment,is prized for its strong antioxidant activity,making it popular as a dietary supplement and a visual marker for plant transformation.However,market...Betalain,an economically valuable water-soluble natural plant pigment,is prized for its strong antioxidant activity,making it popular as a dietary supplement and a visual marker for plant transformation.However,market demand significantly outstrips current production capacity.This study reports the development of an efficient push-and-pull multigene strategy based on polycistronic expression and metabolic flux regulation to enhance betalain biosynthesis in transgenic maize(Zea mays L.)endosperm.We engineered a novel enhanced RUBY(eRUBY)system derived from the original polycistronic RUBY construct(CYP76AD1P2ADODA1P2ADOPA5GT unit,abbreviated CDG)by introducing arogenate dehydrogenase(ADHα)to increase the L-tyrosine substrate supply.All the genes were driven by the endosperm-specific promoter.Fusion of ADHαinto a single polycistronic eRUBY construct(CDGA)produced significantly higher betanin(6.88 mg g−1 dry weight)and isobetanin(1.81 mg g−1 dry weight)levels than in CDG+A,which stacked the ADHαcassette independently with CDG.The high betalain accumulation in CDGA lines(which also exhibited higher transgene copy number)resulted in a 2.85–7.58-fold improvement in endosperm antioxidant capacity compared to WT(versus 2.48–2.80-fold in CDG+A).Importantly,transgenic plants maintained a normal phenotype.Transcriptome and metabolome analyses further indicated that metabolism of phenylalanine,alanine,aspartate,and glutamate contributes to betalain production.Hybridization with sweet corn successfully created a high-sugar eRUBY maize variety.Collectively,these results demonstrate the successful development of a novel maize germplasm with significantly enhanced nutritional value through high betalain accumulation.展开更多
As we welcome the spring of 2026,we extend our sincere greetings and best wishes to colleagues worldwide in the field of crop science,our partners,and all those committed to sustainable agricultural development!The Ye...As we welcome the spring of 2026,we extend our sincere greetings and best wishes to colleagues worldwide in the field of crop science,our partners,and all those committed to sustainable agricultural development!The Year of the Horse symbolizes endeavor and far-reaching journeys,reflecting our own spirit of continuous exploration and breakthrough innovation on the path of crop science.Here,I extendmysincere appreciation to all our authors and reviewers for their invaluable time,expertise,and dedication,which are instrumental in the success of The Crop Journal,establishing it as a premier platform for the global crop science research community.The Crop Journal publishes its 2026 first issue as a special issue themed“Synthetic Biology for Crop Improvement”,ably vip-edited by four young scientists.The issue provides a comprehensive overview of major advances in the field.In the past few years,crop science has made long strides in metabolic engineering of important pathways in secondary metabolism.The achievements expedite the emergence of synthetic biology as a potent methodology for crop breeding and represent a fundamental paradigm shift from“deciphering crops”to“designing crops”,which is further empowered by artificial intelligence(AI).At this turning point of the New Year,I would like to take this opportunity to provide a brief retrospective and future perspective.展开更多
Synthetic speech detection is an essential task in the field of voice security,aimed at identifying deceptive voice attacks generated by text-to-speech(TTS)systems or voice conversion(VC)systems.In this paper,we propo...Synthetic speech detection is an essential task in the field of voice security,aimed at identifying deceptive voice attacks generated by text-to-speech(TTS)systems or voice conversion(VC)systems.In this paper,we propose a synthetic speech detection model called TFTransformer,which integrates both local and global features to enhance detection capabilities by effectively modeling local and global dependencies.Structurally,the model is divided into two main components:a front-end and a back-end.The front-end of the model uses a combination of SincLayer and two-dimensional(2D)convolution to extract high-level feature maps(HFM)containing local dependency of the input speech signals.The back-end uses time-frequency Transformer module to process these feature maps and further capture global dependency.Furthermore,we propose TFTransformer-SE,which incorporates a channel attention mechanism within the 2D convolutional blocks.This enhancement aims to more effectively capture local dependencies,thereby improving the model’s performance.The experiments were conducted on the ASVspoof 2021 LA dataset,and the results showed that the model achieved an equal error rate(EER)of 3.37%without data augmentation.Additionally,we evaluated the model using the ASVspoof 2019 LA dataset,achieving an EER of 0.84%,also without data augmentation.This demonstrates that combining local and global dependencies in the time-frequency domain can significantly improve detection accuracy.展开更多
Crack detection accuracy in computer vision is often constrained by limited annotated datasets.Although Generative Adversarial Networks(GANs)have been applied for data augmentation,they frequently introduce blurs and ...Crack detection accuracy in computer vision is often constrained by limited annotated datasets.Although Generative Adversarial Networks(GANs)have been applied for data augmentation,they frequently introduce blurs and artifacts.To address this challenge,this study leverages Denoising Diffusion Probabilistic Models(DDPMs)to generate high-quality synthetic crack images,enriching the training set with diverse and structurally consistent samples that enhance the crack segmentation.The proposed framework involves a two-stage pipeline:first,DDPMs are used to synthesize high-fidelity crack images that capture fine structural details.Second,these generated samples are combined with real data to train segmentation networks,thereby improving accuracy and robustness in crack detection.Compared with GAN-based approaches,DDPM achieved the best fidelity,with the highest Structural Similarity Index(SSIM)(0.302)and lowest Learned Perceptual Image Patch Similarity(LPIPS)(0.461),producing artifact-free images that preserve fine crack details.To validate its effectiveness,six segmentation models were tested,among which LinkNet consistently achieved the best performance,excelling in both region-level accuracy and structural continuity.Incorporating DDPM-augmented data further enhanced segmentation outcomes,increasing F1 scores by up to 1.1%and IoU by 1.7%,while also improving boundary alignment and skeleton continuity compared with models trained on real images alone.Experiments with varying augmentation ratios showed consistent improvements,with F1 rising from 0.946(no augmentation)to 0.957 and IoU from 0.897 to 0.913 at the highest ratio.These findings demonstrate the effectiveness of diffusion-based augmentation for complex crack detection in structural health monitoring.展开更多
Source-sink coordination serves as the foundation for improving crop yield.Current research primarily focuses on individual factors,such as increasing the source or expanding the sink,which often leads to disrupted so...Source-sink coordination serves as the foundation for improving crop yield.Current research primarily focuses on individual factors,such as increasing the source or expanding the sink,which often leads to disrupted source-sink balance,causing trade-offs among photosynthesis,yield,and stress response.To address these limitations,we present an integrated synthetic biological framework that synergistically enhances photosynthetic efficiency(source capacity),sink optimization,and abiotic stress tolerance.We developed an editing-overexpression coupling(EOC)vector system enabling simultaneous overexpression of four photosynthesis-enhancing genes(Cyt c6,PsbA,FBPase,OsMGT3),knockout of three yield-limiting genes(GS3,Gn1a,OsAAP5),and self-excision of selection markers,gene-editing modules,and fragment deletion cassettes.Field evaluations of CFMP-gga transgenic lines revealed significant physiological improvements,including 13%–17%increase in photosynthetic rates,improved chlorophyll fluorescence parameters,and increased stomatal conductance.These enhancements translated into remarkable agronomic gains,including 18.7%–22.3%higher grain yield,23.1%–26.1%increased biomass,and improved panicle architecture(increased grain size and grain number per panicle).The engineered lines maintained superior thermotolerance(under 42°C stress)and alkali tolerance(at pH 10)compared to wild-type controls.This study provides a strategy for enhancing crop yield by demonstrating that coordinated multi-gene regulation of source-sink dynamics,coupled with stress resilience engineering,achieves concurrent improvements.展开更多
The unique advantage of x-ray ghost imaging(XGI)is its potential in low dose radiology.One of the practical ways to reduce the radiation exposure is to reduce the measurements while remaining sufficient image quality....The unique advantage of x-ray ghost imaging(XGI)is its potential in low dose radiology.One of the practical ways to reduce the radiation exposure is to reduce the measurements while remaining sufficient image quality.Synthetic aperture x-ray ghost imaging(SAXGI)is invented to achieve megapixel XGI with limited measurements,which is expected to implement XGI simultaneously with large field of view and low radiation exposure.In this paper,we experimentally investigate the effect of measurements reduction on the spatial resolution and image quality of SAXGI with standard sample and biomedical specimen.The results with a resolution chart demonstrated that at 360 measurements,SAXGI successfully retrieved the sample image of 1960×1960 pixels with spatial resolution of 4μm.With measurement reduction,the spatial resolution deteriorates but the sparser structures are still discernable.Even with measurements reduced to 10,a spatial resolution of 10μm can still be achieved by SAXGI.A biomedical sample of a fish specimen is employed to evaluate the method and the fish image of 2000×1000 pixels with an SSIM of 0.962 is reconstructed by SAXGI with 770measurements,corresponding to an accumulative exposure reduction of more than 2 times.With the measurements reduced to 10 which corresponds to 1/160 of the accumulative radiation exposure for conventional radiology,bulky structure like the fish skeleton can still be definitely discerned and the SSIM for the reconstructed image still retained 0.9179.Results of this paper demonstrate that measurements reduction is practicable for the radiation exposure reduction of the sample,which implicates that SAXGI with limited measurements is an efficient solution for low dose radiology.展开更多
Plant synthetic biology has emerged as a transformative field in agriculture,offering innovative solutions to enhance food security,provide resilience to climate change,and transition to sustainable farming practices....Plant synthetic biology has emerged as a transformative field in agriculture,offering innovative solutions to enhance food security,provide resilience to climate change,and transition to sustainable farming practices.By integrating advanced genetic tools,computational modeling,and systems biology,researchers can precisely modify plant genomes to enhance traits such as yield,stress tolerance,and nutrient use efficiency.The ability to design plants with specific characteristics tailored to diverse environmental conditions and agricultural needs holds great potential to address global food security challenges.Here,we highlight recent advancements and applications of plant synthetic biology in agriculture,focusing on key areas such as photosynthetic efficiency,nitrogen fixation,drought tolerance,pathogen resistance,nutrient use efficiency,biofortification,climate resilience,microbiology engineering,synthetic plant genomes,and the integration of artificial intelligence with synthetic biology.These innovations aim to maximize resource use efficiency,reduce reliance on external inputs,and mitigate environmental impacts associated with conventional agricultural practices.Despite challenges related to regulatory approval and public acceptance,the integration of synthetic biology in agriculture holds immense promise for creating more resilient and sustainable agricultural systems,contributing to global food security and environmental sustainability.Rigorous multi-field testing of these approaches will undoubtedly be required to ensure reproducibility.展开更多
Synthetic aperture radar(SAR)aboard SEASAT was first launched in 1978.At the beginning of the 21st century,the Chinese remote sensing community recognized the urgent need to develop domestic SAR capabilities.Unlike sc...Synthetic aperture radar(SAR)aboard SEASAT was first launched in 1978.At the beginning of the 21st century,the Chinese remote sensing community recognized the urgent need to develop domestic SAR capabilities.Unlike scatterometers and al-timeters,space-borne SAR offers high-resolution images of the ocean,regardless of weather conditions or time of day.SAR imagery provides rich information about the sea surface,capturing complicated dynamic processes in the upper layers of the ocean,particular-ly in relation to tropical cyclones.Over the past four decades,the advantages of SAR have been increasingly recognized,leading to notable marine applications,especially in the development of algorithms for retrieving wind and wave data from SAR images.This study reviews the history,progress,and future outlook of SAR-based monitoring of sea surface wind and waves.In particular,the ap-plicability of various SAR wind and wave algorithms is systematically investigated,with a particular focus on their performance un-der extreme sea conditions.展开更多
Synthetic phenolic antioxidants(SPAs)are widely used in diverse industries due to their exceptional antioxidant characteristics.However,human exposure to SPAs may cause health problems.In this study,226 dust samples w...Synthetic phenolic antioxidants(SPAs)are widely used in diverse industries due to their exceptional antioxidant characteristics.However,human exposure to SPAs may cause health problems.In this study,226 dust samples were collected from 10 provinces in China,and six SPAs(three parent SPAs and their three transformation products)were analyzed.The concentrations of6SPAs(the sum of six target compounds)ranged from 15.4 to 3210 ng/g(geometric mean(GM):169 ng/g).The highest concentration of6SPAswas found in Sichuan Province(GM:349 ng/g),which was approximately 4 times higher than that in Hubei Province(81.6 ng/g)(p<0.05).The concentrations of butylated hydroxytoluene(BHT),2,2'-methylene bis(4-methyl-6–tert-butylphenol)(AO2246),2,6-di–tert–butyl–1,4-benzoquinone(BHT-Q),2,6-di–tert–butyl–4-(hydroxymethyl)phenol(BHT-OH),and ∑_(p)-SPAs were substantially higher in dust from urban areas than rural areas(p<0.05).AO2246 concentration in dust from homes(GM:0.400 ng/g)was about 4 times higher than that in workplaces(0.116 ng/g)(p<0.01).Significantly higherp-SPAs concentrations were found in dust from homes(GM:17.5 ng/g)than workplaces(11.4 ng/g)(p<0.01).The estimated daily intakes(EDIs)of ∑_(6)SPAs exposed through dust ingestion were 0.582,0.342,0.197,0.076,and 0.080 ng/kg bw/day in different age groups,and exposed through dermal contact was 0.358,0.252,0.174,0.167,and 0.177 ng/kg bw/day.EDIs showed that the exposure risks of SPAs decreased with age.This is the first work to determine SPAs in dust from10 provinces in China and investigate the spatial distribution of SPAs in those regions.展开更多
Nonperiodic interrupted sampling repeater jamming(ISRJ)against inverse synthetic aperture radar(ISAR)can obtain two-dimensional blanket jamming performance by joint fast and slow time domain interrupted modulation,whi...Nonperiodic interrupted sampling repeater jamming(ISRJ)against inverse synthetic aperture radar(ISAR)can obtain two-dimensional blanket jamming performance by joint fast and slow time domain interrupted modulation,which is obviously dif-ferent from the conventional multi-false-target deception jam-ming.In this paper,a suppression method against this kind of novel jamming is proposed based on inter-pulse energy function and compressed sensing theory.By utilizing the discontinuous property of the jamming in slow time domain,the unjammed pulse is separated using the intra-pulse energy function diffe-rence.Based on this,the two-dimensional orthogonal matching pursuit(2D-OMP)algorithm is proposed.Further,it is proposed to reconstruct the ISAR image with the obtained unjammed pulse sequence.The validity of the proposed method is demon-strated via the Yake-42 plane data simulations.展开更多
An efficient and practical synthetic process for Daprodustat was developed.Starting with N,N'-dicyclohexylcarbodiimide(DCC)and malonic acid,the key intermediate 1,3-dicyclohexylpyrimidine-2,4,6(1H,3H,5H)-trione wa...An efficient and practical synthetic process for Daprodustat was developed.Starting with N,N'-dicyclohexylcarbodiimide(DCC)and malonic acid,the key intermediate 1,3-dicyclohexylpyrimidine-2,4,6(1H,3H,5H)-trione was synthesized via condensation reaction with 91%yield.Subsequent activation of this intermediate by 1,1'-carbonyldiimidazole(CDI),followed by a one-pot reaction with glycine ethyl ester hydrochloride,directly afforded Daprodustat in 92%yield with>99.8%HPLC purity.The process achieved an overall yield of 84%upon validation at 62-gram scale.Structural confirmation of the key intermediate was accomplished through nuclear magnetic resonance(NMR)spectroscopy and high-resolution mass spectrometry(HRMS).Compared with existing methods,this streamlined protocol demonstrates advantages including simplified operation,reduced reaction time,and lower production costs,offering significant potential for industrial-scale synthesis of Daprodustat.展开更多
The use of synthetic biology technology to develop cosmetic ingredients is attracting widespread attention due to its effectiveness,safety,and environmental friendliness.This article explains the concept of synthetic ...The use of synthetic biology technology to develop cosmetic ingredients is attracting widespread attention due to its effectiveness,safety,and environmental friendliness.This article explains the concept of synthetic biology and its key technologies and current status in the production of cosmetic ingredients.It also briefly analyzes the regulatory approaches to synthetic biology-based cosmetic ingredients in different countries and regions,providing guidance for the management of this field in China.The goal is to ensure product safety,enhance consumer trust,and promote the healthy development of the industry.展开更多
There is a growing body of clinical research on the utility of synthetic data derivatives,an emerging research tool in medicine.In nephrology,clinicians can use machine learning and artificial intelligence as powerful...There is a growing body of clinical research on the utility of synthetic data derivatives,an emerging research tool in medicine.In nephrology,clinicians can use machine learning and artificial intelligence as powerful aids in their clinical decision-making while also preserving patient privacy.This is especially important given the epidemiology of chronic kidney disease,renal oncology,and hypertension worldwide.However,there remains a need to create a framework for guidance regarding how to better utilize synthetic data as a practical application in this research.展开更多
Imbalanced multiclass datasets pose challenges for machine learning algorithms.They often contain minority classes that are important for accurate predictions.However,when the data is sparsely distributed and overlaps...Imbalanced multiclass datasets pose challenges for machine learning algorithms.They often contain minority classes that are important for accurate predictions.However,when the data is sparsely distributed and overlaps with data points fromother classes,it introduces noise.As a result,existing resamplingmethods may fail to preserve the original data patterns,further disrupting data quality and reducingmodel performance.This paper introduces Neighbor Displacement-based Enhanced Synthetic Oversampling(NDESO),a hybridmethod that integrates a data displacement strategy with a resampling technique to achieve data balance.It begins by computing the average distance of noisy data points to their neighbors and adjusting their positions toward the center before applying random oversampling.Extensive evaluations compare 14 alternatives on nine classifiers across synthetic and 20 real-world datasetswith varying imbalance ratios.This evaluation was structured into two distinct test groups.First,the effects of k-neighbor variations and distance metrics are evaluated,followed by a comparison of resampled data distributions against alternatives,and finally,determining the most suitable oversampling technique for data balancing.Second,the overall performance of the NDESO algorithm was assessed,focusing on G-mean and statistical significance.The results demonstrate that our method is robust to a wide range of variations in these parameters and the overall performance achieves an average G-mean score of 0.90,which is among the highest.Additionally,it attains the lowest mean rank of 2.88,indicating statistically significant improvements over existing approaches.This advantage underscores its potential for effectively handling data imbalance in practical scenarios.展开更多
Resilience studies for water distribution systems(WDS)coupled with other interdependent infrastructure systems attract increasing attention from stakeholders and researchers.However,most existing large-scale WDS model...Resilience studies for water distribution systems(WDS)coupled with other interdependent infrastructure systems attract increasing attention from stakeholders and researchers.However,most existing large-scale WDS models are single infrastructure-based without consideration of other infrastructure systems.This is due to a lack of needed information on systems coupling,the structure of the simulator used,and the computation load involved.To address these gaps,this paper presents a synthetic modeling framework for a real-world WDS as coordinating with other infrastructure systems via a building-mediated clustering approach through consideration of physical distance and node capacity.First,the WDS network topology and operation parameters are inferred via bulk open-source information.A building-mediated clustering approach is designed to systematically derive the interdependence between the WDS and the power system similarly created as a case study.Second,a novel linearization method is developed in formulating the WDS model that can relieve computation load while maintaining accuracy.Finally,a disruption-recovery framework is developed to demonstrate the proposed methodology in modelling WDS resilience.The framework is applied to a neighborhood in Queenstown,Singapore,an area of 20.43 km^(2) and 96,000 population.The near-real-time simulations on the coupled system involving 308 nodes and 384 links showcase the effectiveness and application of the proposed synthetic modeling and formulation.展开更多
The earthquake early warning(EEW)system provides advance notice of potentially damaging ground shaking.In EEW,early estimation of magnitude is crucial for timely rescue operations.A set of thirty-four features is extr...The earthquake early warning(EEW)system provides advance notice of potentially damaging ground shaking.In EEW,early estimation of magnitude is crucial for timely rescue operations.A set of thirty-four features is extracted using the primary wave earthquake precursor signal and site-specific information.In Japan's earthquake magnitude dataset,there is a chance of a high imbalance concerning the earthquakes above strong impact.This imbalance causes a high prediction error while training advanced machine learning or deep learning models.In this work,Conditional Tabular Generative Adversarial Networks(CTGAN),a deep machine learning tool,is utilized to learn the characteristics of the first arrival of earthquake P-waves and generate a synthetic dataset based on this information.The result obtained using actual and mixed(synthetic and actual)datasets will be used for training the stacked ensemble magnitude prediction model,MagPred,designed specifically for this study.There are 13295,3989,and1710 records designated for training,testing,and validation.The mean absolute error of the test dataset for single station magnitude detection using early three,four,and five seconds of P wave are 0.41,0.40,and 0.38 MJMA.The study demonstrates that the Generative Adversarial Networks(GANs)can provide a good result for single-station magnitude prediction.The study can be effective where less seismic data is available.The study shows that the machine learning method yields better magnitude detection results compared with the several regression models.The multi-station magnitude prediction study has been conducted on prominent Osaka,Off Fukushima,and Kumamoto earthquakes.Furthermore,to validate the performance of the model,an inter-region study has been performed on the earthquakes of the India or Nepal region.The study demonstrates that GANs can discover effective magnitude estimation compared with non-GAN-based methods.This has a high potential for wide application in earthquake early warning systems.展开更多
Synthetic biology(SynBio)is an emerging field of study with great potential in designing,engineering,and constructing new microbial synthetic cells that do not pre-exist in nature or re-engineering existing cells to a...Synthetic biology(SynBio)is an emerging field of study with great potential in designing,engineering,and constructing new microbial synthetic cells that do not pre-exist in nature or re-engineering existing cells to accomplish industrial purposes.Systems biology seeks to understand biology at multiple dimensions,beginning with the molecular and cellular level and progressing to the tissues and organismal level and characterizes cells as complex information-processing systems.SynBio,on the other hand,toggles further and strives to develop and create its systems from scratch.SynBio is now applied in the development of novel therapeutic drugs for the prevention of human diseases,scale up industrial processes,and accomplish previously unfeasible industrial outcomes.This is made possible through significant breakthroughs in DNA sequencing and synthesis technology,as well as insights gained from synthetic chemistry and systems biology.SynBio technologies have allowed for the introduction of improved and synthetic metabolic functionalities in microorganisms to enable the synthesis of a range of pharmacologically-relevant compounds for pharmaceutical exploration.SynBio applications range from finding new ways to making industrial chemical synthesis processes more sustainable as well as the microbial synthesis of improved therapeutic modalities.Hence,this study underpins several innovations,auspicious potentials,and future directions afforded by SynBio that proposes improved industrial microbial synthesis for pharmaceutical exploration.展开更多
Synthetic phenolic antioxidants(SPAs)and parabens,particularly the high-molecularweight(HMW)SPAs and long alkyl chain(LAC)parabens with higher environmental persistence and toxicities,are widely produced and applied w...Synthetic phenolic antioxidants(SPAs)and parabens,particularly the high-molecularweight(HMW)SPAs and long alkyl chain(LAC)parabens with higher environmental persistence and toxicities,are widely produced and applied worldwide.However,their occurrence and potential risks in aquatic environments remain largely unknown.This work investigated 11 HMW SPAs and 3 LAC parabens in the river and treated industrial wastewater samples along the Yangtze River,the largest river and most important source water in China.For convenience of comparison,6 short alkyl chain(SAC)parabens were also included.In 15 industrial wastewater treatment plant effluents(effluent-IWTPs)and 34 surface water monitoring sections along the river,19 out of 20 target compounds were detected with total concentrations(TCs)from 152.5 to 1955.5 ng/L and 141.3 to 1364.9 ng/L in effluent-IWTPs and surface water,respectively.HMW SPAs 1,3,5-tris-[(3,5-di–tert–butyl–4-hydroxyphenyl)methyl]-1,3,5-triazinane-2,4,6-trione(AO3114)and octadecyl 3-(3,5-di–tert–butyl–4-hydroxyphenyl)propionate(AO1076)were the dominant ones.HMWSPAs bis(3–tert–butyl–4–hydroxy-5-methylphenyl)propionate(AO245)and 4,4'-sulfanediylbis(2–tert–butyl–5-methylphenol)(AO-TBM6)and SAC parabens propylparaben(PrP)and butylparaben(BuP)posed medium to high potential ecological risks in 27 surface water monitoring sections.Additionally,AO-TBM6 also exhibited potential health risks in 2 out of 11 drinking water sources.Though the ecotoxicity data are very limited,the ubiquitous presence of the LAC parabens including hexylparaben(HeP)and octylparaben(OcP)in surface water should be of concern since these compounds usually exhibit stronger estrogen potencies than the SAC ones.Finally,kernel density analysis revealed that regulation of industrial discharges is necessary to mitigate the HMW SPA and paraben contamination.展开更多
基金supported by grants from the Guangxi Science and Technology Major Project(GKAA24206023)the Biological Breeding-National Science and Technology Major Project(2024ZD04077)+2 种基金the National Natural Science Foundation of China(32272120)the National Key Research and Development Program of China(2024YFF1000800)the Guangdong Basic Research Center of Excellence for Precise Breeding of Future Crops Major Project(FCBRCE-202502,FCBRCE-202504).
文摘A growing global population and the increasing prevalence of diet-related health issues such as“hidden hunger”,obesity,hypertension,and diabetes necessitate a fundamental rethinking of crop design and breeding.Synthetic metabolic engineering offers a method to modify and redesign metabolic pathways to increase the nutritional value of crops.We summarize recent advances in the biofortification of key nutrients including provitamin A,vitamin C,vitamin B9,iron,zinc,anthocyanins,flavonoids,and unsaturated fatty acids.We discuss the potential of multi-gene stacking,gene editing,enzyme engineering,and artificial intelligence in synthetic metabolic engineering.We propose future research directions and potential solutions centered on leveraging AI-driven systems biology,precision gene editing,enzyme engineering,agrobacterium-mediated genotype-independent transformation,and modular metabolic engineering strategies to develop next-generation nutritionally enhanced super crops and transform global food systems.
文摘1.Introduction Crop breeding is transitioning to engineering by synthetic biology.Conventional breeding,constrained by limited genetic variation and lengthy development cycles,cannot meet the challenges of micronutrient malnutrition and yield reductions from climate change with sufficient speed or precision[1].Consequently,agriculture is transitioning from selection-based breeding to designbased engineering.Synthetic biology enables the precision modification of metabolic pathways and the construction of novel trait combinations[1,2].This special issue,Synthetic Biology for Crop Improvement,brings together 26 articles that showcase the field’s transition from laboratory curiosity to field-validated agricultural technology.The collection spans 13 plant species,from staple grains and major industrial crops to horticultural and medicinal plants,demonstrating the universal applicability of metabolic engineering.These studies reveal maturation toward field readiness:independent groups achieving reproducible results in identical pathways,greenhouse concepts advancing to multi-season field trials,and engineered traits delivering measurable agronomic value.This progression answers the central question in crop synthetic biology,shifting the paradigm from asking“can it work?”to demonstrating“how it works,and here are the yields”.This transformation is grounded in understanding and manipulating plant metabolism at molecular resolution[3].
基金supported by grants from the Biological Breeding-National Science and Technology Major Project(2024ZD04077)the Invigorate the Seed Industry of Guangdong Province(2024-NPY-00-044)+3 种基金the National Natural Science Foundation of China(32272120)the Guangxi Science and Technology Major Project(GKAA24206023)the National Key Research and Development Program of China(2024YFF1000800)the Guangdong Basic Research Center of Excellence for Precise Breeding of Future Crops Major Project(FCBRCE-202502,FCBRCE-202504).
文摘Betalain,an economically valuable water-soluble natural plant pigment,is prized for its strong antioxidant activity,making it popular as a dietary supplement and a visual marker for plant transformation.However,market demand significantly outstrips current production capacity.This study reports the development of an efficient push-and-pull multigene strategy based on polycistronic expression and metabolic flux regulation to enhance betalain biosynthesis in transgenic maize(Zea mays L.)endosperm.We engineered a novel enhanced RUBY(eRUBY)system derived from the original polycistronic RUBY construct(CYP76AD1P2ADODA1P2ADOPA5GT unit,abbreviated CDG)by introducing arogenate dehydrogenase(ADHα)to increase the L-tyrosine substrate supply.All the genes were driven by the endosperm-specific promoter.Fusion of ADHαinto a single polycistronic eRUBY construct(CDGA)produced significantly higher betanin(6.88 mg g−1 dry weight)and isobetanin(1.81 mg g−1 dry weight)levels than in CDG+A,which stacked the ADHαcassette independently with CDG.The high betalain accumulation in CDGA lines(which also exhibited higher transgene copy number)resulted in a 2.85–7.58-fold improvement in endosperm antioxidant capacity compared to WT(versus 2.48–2.80-fold in CDG+A).Importantly,transgenic plants maintained a normal phenotype.Transcriptome and metabolome analyses further indicated that metabolism of phenylalanine,alanine,aspartate,and glutamate contributes to betalain production.Hybridization with sweet corn successfully created a high-sugar eRUBY maize variety.Collectively,these results demonstrate the successful development of a novel maize germplasm with significantly enhanced nutritional value through high betalain accumulation.
文摘As we welcome the spring of 2026,we extend our sincere greetings and best wishes to colleagues worldwide in the field of crop science,our partners,and all those committed to sustainable agricultural development!The Year of the Horse symbolizes endeavor and far-reaching journeys,reflecting our own spirit of continuous exploration and breakthrough innovation on the path of crop science.Here,I extendmysincere appreciation to all our authors and reviewers for their invaluable time,expertise,and dedication,which are instrumental in the success of The Crop Journal,establishing it as a premier platform for the global crop science research community.The Crop Journal publishes its 2026 first issue as a special issue themed“Synthetic Biology for Crop Improvement”,ably vip-edited by four young scientists.The issue provides a comprehensive overview of major advances in the field.In the past few years,crop science has made long strides in metabolic engineering of important pathways in secondary metabolism.The achievements expedite the emergence of synthetic biology as a potent methodology for crop breeding and represent a fundamental paradigm shift from“deciphering crops”to“designing crops”,which is further empowered by artificial intelligence(AI).At this turning point of the New Year,I would like to take this opportunity to provide a brief retrospective and future perspective.
基金supported by project ZR2022MF330 supported by Shandong Provincial Natural Science Foundationthe National Natural Science Foundation of China under Grant No.61701286.
文摘Synthetic speech detection is an essential task in the field of voice security,aimed at identifying deceptive voice attacks generated by text-to-speech(TTS)systems or voice conversion(VC)systems.In this paper,we propose a synthetic speech detection model called TFTransformer,which integrates both local and global features to enhance detection capabilities by effectively modeling local and global dependencies.Structurally,the model is divided into two main components:a front-end and a back-end.The front-end of the model uses a combination of SincLayer and two-dimensional(2D)convolution to extract high-level feature maps(HFM)containing local dependency of the input speech signals.The back-end uses time-frequency Transformer module to process these feature maps and further capture global dependency.Furthermore,we propose TFTransformer-SE,which incorporates a channel attention mechanism within the 2D convolutional blocks.This enhancement aims to more effectively capture local dependencies,thereby improving the model’s performance.The experiments were conducted on the ASVspoof 2021 LA dataset,and the results showed that the model achieved an equal error rate(EER)of 3.37%without data augmentation.Additionally,we evaluated the model using the ASVspoof 2019 LA dataset,achieving an EER of 0.84%,also without data augmentation.This demonstrates that combining local and global dependencies in the time-frequency domain can significantly improve detection accuracy.
基金the National Natural Science Foundation of China(Grant No.:52508343)the Fundamental Research Funds for the Central Universities(Grant No.:B250201004).
文摘Crack detection accuracy in computer vision is often constrained by limited annotated datasets.Although Generative Adversarial Networks(GANs)have been applied for data augmentation,they frequently introduce blurs and artifacts.To address this challenge,this study leverages Denoising Diffusion Probabilistic Models(DDPMs)to generate high-quality synthetic crack images,enriching the training set with diverse and structurally consistent samples that enhance the crack segmentation.The proposed framework involves a two-stage pipeline:first,DDPMs are used to synthesize high-fidelity crack images that capture fine structural details.Second,these generated samples are combined with real data to train segmentation networks,thereby improving accuracy and robustness in crack detection.Compared with GAN-based approaches,DDPM achieved the best fidelity,with the highest Structural Similarity Index(SSIM)(0.302)and lowest Learned Perceptual Image Patch Similarity(LPIPS)(0.461),producing artifact-free images that preserve fine crack details.To validate its effectiveness,six segmentation models were tested,among which LinkNet consistently achieved the best performance,excelling in both region-level accuracy and structural continuity.Incorporating DDPM-augmented data further enhanced segmentation outcomes,increasing F1 scores by up to 1.1%and IoU by 1.7%,while also improving boundary alignment and skeleton continuity compared with models trained on real images alone.Experiments with varying augmentation ratios showed consistent improvements,with F1 rising from 0.946(no augmentation)to 0.957 and IoU from 0.897 to 0.913 at the highest ratio.These findings demonstrate the effectiveness of diffusion-based augmentation for complex crack detection in structural health monitoring.
基金the National Key Research and Development Program of China(2020YFA0907600)National Natural Science Foundation of China(31100869)+1 种基金Central Public-interest Scientific Institutions Basal Research Fund for Zhang Zhiguo(Y2025YY06)the Fundamental Research Funds for Central Nonprofit Scientific Institutions for Lu Tiegang,and Cui Xuean.
文摘Source-sink coordination serves as the foundation for improving crop yield.Current research primarily focuses on individual factors,such as increasing the source or expanding the sink,which often leads to disrupted source-sink balance,causing trade-offs among photosynthesis,yield,and stress response.To address these limitations,we present an integrated synthetic biological framework that synergistically enhances photosynthetic efficiency(source capacity),sink optimization,and abiotic stress tolerance.We developed an editing-overexpression coupling(EOC)vector system enabling simultaneous overexpression of four photosynthesis-enhancing genes(Cyt c6,PsbA,FBPase,OsMGT3),knockout of three yield-limiting genes(GS3,Gn1a,OsAAP5),and self-excision of selection markers,gene-editing modules,and fragment deletion cassettes.Field evaluations of CFMP-gga transgenic lines revealed significant physiological improvements,including 13%–17%increase in photosynthetic rates,improved chlorophyll fluorescence parameters,and increased stomatal conductance.These enhancements translated into remarkable agronomic gains,including 18.7%–22.3%higher grain yield,23.1%–26.1%increased biomass,and improved panicle architecture(increased grain size and grain number per panicle).The engineered lines maintained superior thermotolerance(under 42°C stress)and alkali tolerance(at pH 10)compared to wild-type controls.This study provides a strategy for enhancing crop yield by demonstrating that coordinated multi-gene regulation of source-sink dynamics,coupled with stress resilience engineering,achieves concurrent improvements.
基金Project supported by the National Key Research and Development Program of China(Grant Nos.2022YFA1603601,2021YFF0601203,and 2021YFA1600703)。
文摘The unique advantage of x-ray ghost imaging(XGI)is its potential in low dose radiology.One of the practical ways to reduce the radiation exposure is to reduce the measurements while remaining sufficient image quality.Synthetic aperture x-ray ghost imaging(SAXGI)is invented to achieve megapixel XGI with limited measurements,which is expected to implement XGI simultaneously with large field of view and low radiation exposure.In this paper,we experimentally investigate the effect of measurements reduction on the spatial resolution and image quality of SAXGI with standard sample and biomedical specimen.The results with a resolution chart demonstrated that at 360 measurements,SAXGI successfully retrieved the sample image of 1960×1960 pixels with spatial resolution of 4μm.With measurement reduction,the spatial resolution deteriorates but the sparser structures are still discernable.Even with measurements reduced to 10,a spatial resolution of 10μm can still be achieved by SAXGI.A biomedical sample of a fish specimen is employed to evaluate the method and the fish image of 2000×1000 pixels with an SSIM of 0.962 is reconstructed by SAXGI with 770measurements,corresponding to an accumulative exposure reduction of more than 2 times.With the measurements reduced to 10 which corresponds to 1/160 of the accumulative radiation exposure for conventional radiology,bulky structure like the fish skeleton can still be definitely discerned and the SSIM for the reconstructed image still retained 0.9179.Results of this paper demonstrate that measurements reduction is practicable for the radiation exposure reduction of the sample,which implicates that SAXGI with limited measurements is an efficient solution for low dose radiology.
基金supported by the Strategic Priority Research Program of the Chinese Academy of Sciences(Category B,XDB1090000).
文摘Plant synthetic biology has emerged as a transformative field in agriculture,offering innovative solutions to enhance food security,provide resilience to climate change,and transition to sustainable farming practices.By integrating advanced genetic tools,computational modeling,and systems biology,researchers can precisely modify plant genomes to enhance traits such as yield,stress tolerance,and nutrient use efficiency.The ability to design plants with specific characteristics tailored to diverse environmental conditions and agricultural needs holds great potential to address global food security challenges.Here,we highlight recent advancements and applications of plant synthetic biology in agriculture,focusing on key areas such as photosynthetic efficiency,nitrogen fixation,drought tolerance,pathogen resistance,nutrient use efficiency,biofortification,climate resilience,microbiology engineering,synthetic plant genomes,and the integration of artificial intelligence with synthetic biology.These innovations aim to maximize resource use efficiency,reduce reliance on external inputs,and mitigate environmental impacts associated with conventional agricultural practices.Despite challenges related to regulatory approval and public acceptance,the integration of synthetic biology in agriculture holds immense promise for creating more resilient and sustainable agricultural systems,contributing to global food security and environmental sustainability.Rigorous multi-field testing of these approaches will undoubtedly be required to ensure reproducibility.
基金supported by the National Nat-ural Science Foundation of China(No.42376174)the Natural Science Foundation of Shanghai(No.23ZR 1426900).
文摘Synthetic aperture radar(SAR)aboard SEASAT was first launched in 1978.At the beginning of the 21st century,the Chinese remote sensing community recognized the urgent need to develop domestic SAR capabilities.Unlike scatterometers and al-timeters,space-borne SAR offers high-resolution images of the ocean,regardless of weather conditions or time of day.SAR imagery provides rich information about the sea surface,capturing complicated dynamic processes in the upper layers of the ocean,particular-ly in relation to tropical cyclones.Over the past four decades,the advantages of SAR have been increasingly recognized,leading to notable marine applications,especially in the development of algorithms for retrieving wind and wave data from SAR images.This study reviews the history,progress,and future outlook of SAR-based monitoring of sea surface wind and waves.In particular,the ap-plicability of various SAR wind and wave algorithms is systematically investigated,with a particular focus on their performance un-der extreme sea conditions.
基金supported by the National Key Research and Development Program of China(No.2023YFC3706602)the National Natural Science Foundation of China(Nos.22225605 and 22193051)the Strategic Priority Research Program of the Chinese Academy of Sciences(No.XDB0750200).
文摘Synthetic phenolic antioxidants(SPAs)are widely used in diverse industries due to their exceptional antioxidant characteristics.However,human exposure to SPAs may cause health problems.In this study,226 dust samples were collected from 10 provinces in China,and six SPAs(three parent SPAs and their three transformation products)were analyzed.The concentrations of6SPAs(the sum of six target compounds)ranged from 15.4 to 3210 ng/g(geometric mean(GM):169 ng/g).The highest concentration of6SPAswas found in Sichuan Province(GM:349 ng/g),which was approximately 4 times higher than that in Hubei Province(81.6 ng/g)(p<0.05).The concentrations of butylated hydroxytoluene(BHT),2,2'-methylene bis(4-methyl-6–tert-butylphenol)(AO2246),2,6-di–tert–butyl–1,4-benzoquinone(BHT-Q),2,6-di–tert–butyl–4-(hydroxymethyl)phenol(BHT-OH),and ∑_(p)-SPAs were substantially higher in dust from urban areas than rural areas(p<0.05).AO2246 concentration in dust from homes(GM:0.400 ng/g)was about 4 times higher than that in workplaces(0.116 ng/g)(p<0.01).Significantly higherp-SPAs concentrations were found in dust from homes(GM:17.5 ng/g)than workplaces(11.4 ng/g)(p<0.01).The estimated daily intakes(EDIs)of ∑_(6)SPAs exposed through dust ingestion were 0.582,0.342,0.197,0.076,and 0.080 ng/kg bw/day in different age groups,and exposed through dermal contact was 0.358,0.252,0.174,0.167,and 0.177 ng/kg bw/day.EDIs showed that the exposure risks of SPAs decreased with age.This is the first work to determine SPAs in dust from10 provinces in China and investigate the spatial distribution of SPAs in those regions.
基金supported by the National Natural Science Foundation of China(62001481,61890542,62071475)the Natural Science Foundation of Hunan Province(2022JJ40561)the Research Program of National University of Defense Technology(ZK22-46).
文摘Nonperiodic interrupted sampling repeater jamming(ISRJ)against inverse synthetic aperture radar(ISAR)can obtain two-dimensional blanket jamming performance by joint fast and slow time domain interrupted modulation,which is obviously dif-ferent from the conventional multi-false-target deception jam-ming.In this paper,a suppression method against this kind of novel jamming is proposed based on inter-pulse energy function and compressed sensing theory.By utilizing the discontinuous property of the jamming in slow time domain,the unjammed pulse is separated using the intra-pulse energy function diffe-rence.Based on this,the two-dimensional orthogonal matching pursuit(2D-OMP)algorithm is proposed.Further,it is proposed to reconstruct the ISAR image with the obtained unjammed pulse sequence.The validity of the proposed method is demon-strated via the Yake-42 plane data simulations.
文摘An efficient and practical synthetic process for Daprodustat was developed.Starting with N,N'-dicyclohexylcarbodiimide(DCC)and malonic acid,the key intermediate 1,3-dicyclohexylpyrimidine-2,4,6(1H,3H,5H)-trione was synthesized via condensation reaction with 91%yield.Subsequent activation of this intermediate by 1,1'-carbonyldiimidazole(CDI),followed by a one-pot reaction with glycine ethyl ester hydrochloride,directly afforded Daprodustat in 92%yield with>99.8%HPLC purity.The process achieved an overall yield of 84%upon validation at 62-gram scale.Structural confirmation of the key intermediate was accomplished through nuclear magnetic resonance(NMR)spectroscopy and high-resolution mass spectrometry(HRMS).Compared with existing methods,this streamlined protocol demonstrates advantages including simplified operation,reduced reaction time,and lower production costs,offering significant potential for industrial-scale synthesis of Daprodustat.
文摘The use of synthetic biology technology to develop cosmetic ingredients is attracting widespread attention due to its effectiveness,safety,and environmental friendliness.This article explains the concept of synthetic biology and its key technologies and current status in the production of cosmetic ingredients.It also briefly analyzes the regulatory approaches to synthetic biology-based cosmetic ingredients in different countries and regions,providing guidance for the management of this field in China.The goal is to ensure product safety,enhance consumer trust,and promote the healthy development of the industry.
文摘There is a growing body of clinical research on the utility of synthetic data derivatives,an emerging research tool in medicine.In nephrology,clinicians can use machine learning and artificial intelligence as powerful aids in their clinical decision-making while also preserving patient privacy.This is especially important given the epidemiology of chronic kidney disease,renal oncology,and hypertension worldwide.However,there remains a need to create a framework for guidance regarding how to better utilize synthetic data as a practical application in this research.
文摘Imbalanced multiclass datasets pose challenges for machine learning algorithms.They often contain minority classes that are important for accurate predictions.However,when the data is sparsely distributed and overlaps with data points fromother classes,it introduces noise.As a result,existing resamplingmethods may fail to preserve the original data patterns,further disrupting data quality and reducingmodel performance.This paper introduces Neighbor Displacement-based Enhanced Synthetic Oversampling(NDESO),a hybridmethod that integrates a data displacement strategy with a resampling technique to achieve data balance.It begins by computing the average distance of noisy data points to their neighbors and adjusting their positions toward the center before applying random oversampling.Extensive evaluations compare 14 alternatives on nine classifiers across synthetic and 20 real-world datasetswith varying imbalance ratios.This evaluation was structured into two distinct test groups.First,the effects of k-neighbor variations and distance metrics are evaluated,followed by a comparison of resampled data distributions against alternatives,and finally,determining the most suitable oversampling technique for data balancing.Second,the overall performance of the NDESO algorithm was assessed,focusing on G-mean and statistical significance.The results demonstrate that our method is robust to a wide range of variations in these parameters and the overall performance achieves an average G-mean score of 0.90,which is among the highest.Additionally,it attains the lowest mean rank of 2.88,indicating statistically significant improvements over existing approaches.This advantage underscores its potential for effectively handling data imbalance in practical scenarios.
文摘Resilience studies for water distribution systems(WDS)coupled with other interdependent infrastructure systems attract increasing attention from stakeholders and researchers.However,most existing large-scale WDS models are single infrastructure-based without consideration of other infrastructure systems.This is due to a lack of needed information on systems coupling,the structure of the simulator used,and the computation load involved.To address these gaps,this paper presents a synthetic modeling framework for a real-world WDS as coordinating with other infrastructure systems via a building-mediated clustering approach through consideration of physical distance and node capacity.First,the WDS network topology and operation parameters are inferred via bulk open-source information.A building-mediated clustering approach is designed to systematically derive the interdependence between the WDS and the power system similarly created as a case study.Second,a novel linearization method is developed in formulating the WDS model that can relieve computation load while maintaining accuracy.Finally,a disruption-recovery framework is developed to demonstrate the proposed methodology in modelling WDS resilience.The framework is applied to a neighborhood in Queenstown,Singapore,an area of 20.43 km^(2) and 96,000 population.The near-real-time simulations on the coupled system involving 308 nodes and 384 links showcase the effectiveness and application of the proposed synthetic modeling and formulation.
基金related to grant PM-31-22-626-414 from the Prime Minister's Research Fellows(PMRF)of the Indian Institute of Technology Roorkee。
文摘The earthquake early warning(EEW)system provides advance notice of potentially damaging ground shaking.In EEW,early estimation of magnitude is crucial for timely rescue operations.A set of thirty-four features is extracted using the primary wave earthquake precursor signal and site-specific information.In Japan's earthquake magnitude dataset,there is a chance of a high imbalance concerning the earthquakes above strong impact.This imbalance causes a high prediction error while training advanced machine learning or deep learning models.In this work,Conditional Tabular Generative Adversarial Networks(CTGAN),a deep machine learning tool,is utilized to learn the characteristics of the first arrival of earthquake P-waves and generate a synthetic dataset based on this information.The result obtained using actual and mixed(synthetic and actual)datasets will be used for training the stacked ensemble magnitude prediction model,MagPred,designed specifically for this study.There are 13295,3989,and1710 records designated for training,testing,and validation.The mean absolute error of the test dataset for single station magnitude detection using early three,four,and five seconds of P wave are 0.41,0.40,and 0.38 MJMA.The study demonstrates that the Generative Adversarial Networks(GANs)can provide a good result for single-station magnitude prediction.The study can be effective where less seismic data is available.The study shows that the machine learning method yields better magnitude detection results compared with the several regression models.The multi-station magnitude prediction study has been conducted on prominent Osaka,Off Fukushima,and Kumamoto earthquakes.Furthermore,to validate the performance of the model,an inter-region study has been performed on the earthquakes of the India or Nepal region.The study demonstrates that GANs can discover effective magnitude estimation compared with non-GAN-based methods.This has a high potential for wide application in earthquake early warning systems.
文摘Synthetic biology(SynBio)is an emerging field of study with great potential in designing,engineering,and constructing new microbial synthetic cells that do not pre-exist in nature or re-engineering existing cells to accomplish industrial purposes.Systems biology seeks to understand biology at multiple dimensions,beginning with the molecular and cellular level and progressing to the tissues and organismal level and characterizes cells as complex information-processing systems.SynBio,on the other hand,toggles further and strives to develop and create its systems from scratch.SynBio is now applied in the development of novel therapeutic drugs for the prevention of human diseases,scale up industrial processes,and accomplish previously unfeasible industrial outcomes.This is made possible through significant breakthroughs in DNA sequencing and synthesis technology,as well as insights gained from synthetic chemistry and systems biology.SynBio technologies have allowed for the introduction of improved and synthetic metabolic functionalities in microorganisms to enable the synthesis of a range of pharmacologically-relevant compounds for pharmaceutical exploration.SynBio applications range from finding new ways to making industrial chemical synthesis processes more sustainable as well as the microbial synthesis of improved therapeutic modalities.Hence,this study underpins several innovations,auspicious potentials,and future directions afforded by SynBio that proposes improved industrial microbial synthesis for pharmaceutical exploration.
基金supported by the National Key Research and Development Program of China(Nos.2021YFC3200801 and 2021YFC3200804).
文摘Synthetic phenolic antioxidants(SPAs)and parabens,particularly the high-molecularweight(HMW)SPAs and long alkyl chain(LAC)parabens with higher environmental persistence and toxicities,are widely produced and applied worldwide.However,their occurrence and potential risks in aquatic environments remain largely unknown.This work investigated 11 HMW SPAs and 3 LAC parabens in the river and treated industrial wastewater samples along the Yangtze River,the largest river and most important source water in China.For convenience of comparison,6 short alkyl chain(SAC)parabens were also included.In 15 industrial wastewater treatment plant effluents(effluent-IWTPs)and 34 surface water monitoring sections along the river,19 out of 20 target compounds were detected with total concentrations(TCs)from 152.5 to 1955.5 ng/L and 141.3 to 1364.9 ng/L in effluent-IWTPs and surface water,respectively.HMW SPAs 1,3,5-tris-[(3,5-di–tert–butyl–4-hydroxyphenyl)methyl]-1,3,5-triazinane-2,4,6-trione(AO3114)and octadecyl 3-(3,5-di–tert–butyl–4-hydroxyphenyl)propionate(AO1076)were the dominant ones.HMWSPAs bis(3–tert–butyl–4–hydroxy-5-methylphenyl)propionate(AO245)and 4,4'-sulfanediylbis(2–tert–butyl–5-methylphenol)(AO-TBM6)and SAC parabens propylparaben(PrP)and butylparaben(BuP)posed medium to high potential ecological risks in 27 surface water monitoring sections.Additionally,AO-TBM6 also exhibited potential health risks in 2 out of 11 drinking water sources.Though the ecotoxicity data are very limited,the ubiquitous presence of the LAC parabens including hexylparaben(HeP)and octylparaben(OcP)in surface water should be of concern since these compounds usually exhibit stronger estrogen potencies than the SAC ones.Finally,kernel density analysis revealed that regulation of industrial discharges is necessary to mitigate the HMW SPA and paraben contamination.
