Citric acid is an important contributor to fruit flavor.The extremely significant differences in citric acid levels are observed among citrus species and varieties.The molecular basis of citric acid accumulation remai...Citric acid is an important contributor to fruit flavor.The extremely significant differences in citric acid levels are observed among citrus species and varieties.The molecular basis of citric acid accumulation remains largely unknown on the inter-species level.Here,we performed transcriptome analysis of five pairs of acidic and acidless variety fruits from kumquat(Citrus crassifolia),lemon(C.limon),pummelo(C.maxima),mandarin(C.reticulata),and sweet orange(C.sinensis)to investigate the common and specific genes related to citric acid accumulation in these citrus species.Transcript profiles of the citrate metabolism genes revealed that the mechanism of citric acid accumulation in kumquat differed from that in the other four species.The comparative analysis and weighted gene co-expression network analysis identified 61 candidate genes from lemon,pummelo,mandarin,and sweet orange.Vacuolar acidification regulated by CitPH4-CitAN1-CitPH5was a common mechanism underlying citric acid accumulation in these four species.In addition,gene network analysis indicated that CitPH4 was a central regulator,exhibiting a strong correlation with the genes involved in vacuolar trafficking and potassium(K^(+))transport.The co-expression and functional enrichment analyses showed that active sugar metabolism and increased citrate synthesis were mainly responsible for the accumulation of citric acid in kumquat.Twenty-four transcription factors were identified as candidate regulators,of which CitbHLH28 was found to regulate acidity level via transactivating CWINV2 and PK3 expressions.Overall,this study provides an insight into the mechanism of citric acid accumulation in citrus fruit and provides useful references for fruit quality improvement through acidity control in different citrus species.展开更多
Traditional meteorological downscaling methods face limitations due to the complex distribution of meteorological variables,which can lead to unstable forecasting results,especially in extreme scenarios.To overcome th...Traditional meteorological downscaling methods face limitations due to the complex distribution of meteorological variables,which can lead to unstable forecasting results,especially in extreme scenarios.To overcome this issue,we propose a convolutional graph neural network(CGNN)model,which we enhance with multilayer feature fusion and a squeeze-and-excitation block.Additionally,we introduce a spatially balanced mean squared error(SBMSE)loss function to address the imbalanced distribution and spatial variability of meteorological variables.The CGNN is capable of extracting essential spatial features and aggregating them from a global perspective,thereby improving the accuracy of prediction and enhancing the model's generalization ability.Based on the experimental results,CGNN has certain advantages in terms of bias distribution,exhibiting a smaller variance.When it comes to precipitation,both UNet and AE also demonstrate relatively small biases.As for temperature,AE and CNNdense perform outstandingly during the winter.The time correlation coefficients show an improvement of at least 10%at daily and monthly scales for both temperature and precipitation.Furthermore,the SBMSE loss function displays an advantage over existing loss functions in predicting the98th percentile and identifying areas where extreme events occur.However,the SBMSE tends to overestimate the distribution of extreme precipitation,which may be due to the theoretical assumptions about the posterior distribution of data that partially limit the effectiveness of the loss function.In future work,we will further optimize the SBMSE to improve prediction accuracy.展开更多
Convolutional neural networks(CNNs) have been widely studied and found to obtain favorable results in statistical downscaling to derive high-resolution climate variables from large-scale coarse general circulation mod...Convolutional neural networks(CNNs) have been widely studied and found to obtain favorable results in statistical downscaling to derive high-resolution climate variables from large-scale coarse general circulation models(GCMs).However, there is a lack of research exploring the predictor selection for CNN modeling. This paper presents an effective and efficient greedy elimination algorithm to address this problem. The algorithm has three main steps: predictor importance attribution, predictor removal, and CNN retraining, which are performed sequentially and iteratively. The importance of individual predictors is measured by a gradient-based importance metric computed by a CNN backpropagation technique, which was initially proposed for CNN interpretation. The algorithm is tested on the CNN-based statistical downscaling of monthly precipitation with 20 candidate predictors and compared with a correlation analysisbased approach. Linear models are implemented as benchmarks. The experiments illustrate that the predictor selection solution can reduce the number of input predictors by more than half, improve the accuracy of both linear and CNN models,and outperform the correlation analysis method. Although the RMSE(root-mean-square error) is reduced by only 0.8%,only 9 out of 20 predictors are used to build the CNN, and the FLOPs(Floating Point Operations) decrease by 20.4%. The results imply that the algorithm can find subset predictors that correlate more to the monthly precipitation of the target area and seasons in a nonlinear way. It is worth mentioning that the algorithm is compatible with other CNN models with stacked variables as input and has the potential for nonlinear correlation predictor selection.展开更多
Under the public spotlight,uranyl(UO22+)ions has attracted considerable attention for the extreme radioactive and chemical toxicity to ourselves and our environment.Herein,we present a simple and effective ratiometric...Under the public spotlight,uranyl(UO22+)ions has attracted considerable attention for the extreme radioactive and chemical toxicity to ourselves and our environment.Herein,we present a simple and effective ratiometric fluorescence imaging method for the visualizing and quantitative detection UO22+ions by cellphone-based optical platform.The sensing solution was prepared by mixing label-free red carbon dots(r-CDs)and blue carbon dots(b-CDs)together with a fixed photoluminescence intensity ratio of 4:1.When UO22+ions were added,the fluorescence of r-CDs can be selectively quenched,while the fluorescence of b-CDs remains stable without spectral cha nges.With the gradually increase the amounts of UO22+ions,the different response of dual-color CDs resulted in a signification color evolution from deep red to dark purple under the ultraviolet(UV)light illumination.Then,a cellphone-based optical platform was constructed for directly imaging the color change of the samples,and the built-in Colorpicker APP quickly output the red,green and blue(RGB)channel values of these images within one second.Interesting,there was a linear relationship between the ratio of red and blue(R/B)channel values and UO22+ions concentration from 0μmol/L to 30.0μmol/L(R^2=0.92804)with the detection limit of^8.15μmol/L(signal-to-noise ratio of 3).In addition,the optical platform has also been applied to the quantification of UO22+ions in tap water and river water sample.With the advantage of low-cost,portable,easy to operation,we anticipate that this method would greatly improve the accessibility of UO22+ions detection even in resource-limited areas.展开更多
The fruit of chestnut rose(Rosa roxburghii Tratt.)contains exceptionally high levels of L-ascorbic acid(AsA)(∼1762 mg/100 g fresh weight),approximately 40-fold higher than those found in sweet orange(Citrus sinensis)...The fruit of chestnut rose(Rosa roxburghii Tratt.)contains exceptionally high levels of L-ascorbic acid(AsA)(∼1762 mg/100 g fresh weight),approximately 40-fold higher than those found in sweet orange(Citrus sinensis),which is well known for its high AsA content.However,the molecular mechanisms driving such high accumulation in chestnut rose remain unclear.Here,we report that the genes R.roxburghii PECTIN METHYLESTERASE(RroxPME),D-GALACTURONATE REDUCTASE(RroxGalUR),and DEHYDROASCORBATE REDUCTASE 2(RroxDHAR2)play crucial roles in AsA accumulation in chestnut rose fruit.By comparing R.roxburghii with the closely related Rosa multiflora,which has low AsA concentrations,we identified a 545-bp insertion in the promoter of RroxGalUR.We found that TRANSPARENT TESTA GLABRA 2(RroxTTG2),a well-known key regulator of trichome development,binds to the W-box-containing inserted region of the RroxGalUR promoter as well as the promoters of RroxPME and RroxDHAR2.In contrast,in sweet orange,CsTTG2 can bind only to CsPME.Furthermore,RroxTTG2 retains its conserved role in the regulation of trichome development during early fruit development,suggesting its spatiotemporal specificity in regulating both trichome development and AsA biosynthesis.To evaluate the application value of this pathway in other species,we heterologously expressed RroxTTG2,RroxPME,RroxGalUR,and RroxDHAR2 in lettuce(Lactuca sativa L.),which increased AsA concentrations in the transgenic lines by up to 355%(an increase from approximately 2 to 10 mg/100 g fresh weight).This study provides insights into mechanisms underlying AsA accumulation in chestnut rose and the spatiotemporal transcriptional regulation of AsA biosynthesis and trichome development.展开更多
Dear Editor,The genus Citrus comprises more than 30 species worldwide(Swingle,1943).However,citrus genetics and traditional breeding are hindered due to asexual reproduction,long generation time,and empirical utilizat...Dear Editor,The genus Citrus comprises more than 30 species worldwide(Swingle,1943).However,citrus genetics and traditional breeding are hindered due to asexual reproduction,long generation time,and empirical utilization of the germplasm.The whole-genome information of different citrus species accelerates the genetic studies and improves the breeding efficiency by high-density markers.展开更多
Dwarfing is a pivotal agronomic trait affecting both yield and quality.Citrus species exhibit substantial variation in plant height,among which internode length is a core element.However,the molecular mechanism govern...Dwarfing is a pivotal agronomic trait affecting both yield and quality.Citrus species exhibit substantial variation in plant height,among which internode length is a core element.However,the molecular mechanism governing internode elongation remains unclear.Here,we unveiled that the transcriptional cascade consisting of B-BOX DOMAIN PROTEIN 22(BBX22)and ELONGATED HYPOCOTYL 5(HY5)finely tunes plant height and internode elongation in citrus.Loss-of-function mutations of BBX22 in an early-flowering citrus(Citrus hindsii“SJG”)promoted internode elongation and reduced pigment accumulation,whereas ectopic expression of BBX22 in SJG,sweet orange(C.sinensis),pomelo(C.maxima)or heterologous expression of BBX22 in tomato(Solanum lycopersicum)significantly decreased internode length.Furthermore,exogenous application of gibberellin A3(GA3)rescued the shortened internode and dwarf phenotype caused by BBX22overexpression.Additional experiments revealed that BBX22 played a dual role in regulation internode elongation and pigmentation in citrus.On the one hand,it directly bound to and activated the expression of HY5,GA metabolism gene(GA2 OXIDASE 8,GA2ox8),carotenoid biosynthesis gene(PHYTOENE SYNTHASE 1,PSY1)and anthocyanin regulatory gene(Ruby1,a MYB DOMAIN PROTEIN).On the other hand,it acted as a cofactor of HY5,enhancing the ability of HY5 to regulate target genes expression.Together,our results reveal the critical role of the transcriptional cascade consisting of BBX22 and HY5 in controlling internode elongation and pigment accumulation in citrus.Unraveling the crosstalk regulatory mechanism between internode elongation and fruit pigmentation provides key genes for breeding of novel types with both dwarf and health-beneficial fortification in citrus.展开更多
Background:Patients with extensive burns usually develop pro-coagulation soon after the injury if there is no sepsis occurred.We describe the case of an extensive burn adult suffering from hypocoagulation not related ...Background:Patients with extensive burns usually develop pro-coagulation soon after the injury if there is no sepsis occurred.We describe the case of an extensive burn adult suffering from hypocoagulation not related to sepsis,but secondary to antibiotic treatment.Case presentation:Here,we report a case of an adult male patient suffering from flame burns of 45%total body surface area(40%full thickness)combined with inhalation injury.Hypocoagulopathy with soaring prolonged activated partial thromboplastin time value occurred on third week post-burn while systemic infection had been under control by application of broad-spectrum antibiotics.Investigations showed that not the infection but vitamin K-related coagulation factor deficiency were responsible for unexpected bleeding.However,supplemental vitamin K was not the key as we expected,which prompted us trying to decode the underlying cause of coagulation disturbance in this patient and pick out the most effective treatment for live-saving.After the withdrawal of highly suspected broad-spectrum antibiotic,Meropenem^(■),disturbed vitamin K related coagulation factors gradually restored to their optimal levels so as to maintain normal coagulation status.Therefore,surgical procedures without further risk of bleeding could be carried out in time for wound recovery.The patient was discharged on post-burn day 67 and transferred to a secondary hospital for his rehabilitation.Conclusion:Hypocoagulopathy may be devoted to different reasons other than sepsis in extensive burns.Early recognition of the cause for coagulation disturbance is critical to make appropriate treatment and save patients’lives.This case illustrated the importance of unveiling the mist cause for coagulation disturbance occurred in extensive burn patient,which paved the way for optimal life-saving treatments.And we also recommend burn surgeons to be alerted to antibiotic-induced vitamin K deficiency-related coagulopathy among critical burn patients.展开更多
Background:The relationship between perfusion index(PI)and organ dysfunction in patients in the intensivecare unit(ICU)is not clear.This study aimed to explore the relationship between PI and renal function in theperi...Background:The relationship between perfusion index(PI)and organ dysfunction in patients in the intensivecare unit(ICU)is not clear.This study aimed to explore the relationship between PI and renal function in theperioperative critical care setting and evaluate the predictive efficiency of PI on patients with acute kidney injury(AKI)in the ICU.Methods:This retrospective analysis involved 12,979 patients who had undergone an operation and were admitted to the ICU in Peking Union Medical College Hospital from January 2014 to December 2019.The distributionof average PI in the first 24 h after ICU admission and its correlation with AKI was calculated by Cox regression.Receiver operating characteristic(ROC)curves were generated to compare the ability of PI,mean arterial pressure(MAP),creatinine,blood urea nitrogen(BUN),and central venous pressure(CVP)to discriminate AKI in thefirst 48 h in all perioperative critically ill patients.Results:Average PI in the first 24 h served as an independent protective factor of AKI(Odds ratio[OR]=0.786,95%confidence interval[CI]:0.704–0.873,P<0.0001).With a decrease in PI by one unit,the incidence of AKIincreased 1.74 times.Among the variables explored for the prediction of AKI(PI,MAP,creatine,BUN,and CVP),PI yielded the highest area under the ROC curve,with a sensitivity of 64.34%and specificity of 70.14%.A cut-offvalue of PI≤2.12 could be used to predict AKI according to the Youden index.Moreover,patients in the low PIgroup(PI≤2.12)exhibited a marked creatine elevation at 24–48 h with a slower decrease compared with thosein the high PI group(PI>2.12).Conclusions:As a local blood flow indicator,the initial 24-h average PI for perioperative critically ill patients canpredict AKI during their first 120 h in the ICU.展开更多
Phase transition and floral induction in citrus requires several years of juvenility after germination.Such a long period of juvenility has been a major hindrance to its genetic improvement program.Studies have shown ...Phase transition and floral induction in citrus requires several years of juvenility after germination.Such a long period of juvenility has been a major hindrance to its genetic improvement program.Studies have shown that miR156 along with its downstream genes SQUAMOSA PROMOTER BINDING PROTEINS(SBP)and SBP-LIKE(SPL)mediate the phase transition and floral induction process in plants.Our current study has systematically analyzed SPLs in 15 different citrus-related species,systematically annotated them based on their close homology to their respective Arabidopsis orthologs,and confirmed the functional attributes of the selected members in floral precocity.The majority of the species harbored 15 SPLs.Their cis-element assessment suggested the involvement of the SPLs in diverse developmental and physiological processes in response to different biotic and abiotic cues.Among all,SPL5,SPL9,and SPL11 stood out as consistently differentially expressed SPLs in the adult and young tissues of different citrusrelated species.Independent overexpression of their F.hindsii orthologs(FhSPL5,FhSPL9,and FhSPL11)brought an enhanced expression of endogenous FLOWERING LOCUS T leading to the significantly precocious flowering in transgenic Arabidopsis lines.Future study of the genes in the citrus plant itself is expected to conclude the assessments made in the current study.展开更多
Background At present,it is insufficient to understand the basic data characteristics of the correlated X-ray scattering.And there is a great challenge about how to master the nature of the data.So it is difficult to ...Background At present,it is insufficient to understand the basic data characteristics of the correlated X-ray scattering.And there is a great challenge about how to master the nature of the data.So it is difficult to use and analyze the experimental data more effectively.In addition,there are many reasons,for the experimental artifacts such as whether the shutter is on or off,whether there is the beam line or not,the swaying of the nozzle and the shadow of the detector.So it is rather challenging to analyze the scattering patterns.Purpose The purpose of this paper was to develop a method to filter the invalid scattering data and provide the theoretical and experiment fundamentals for studying the X-ray scattering data of the complex biological sample further.Methods The heliummolecules were scattered by the X-ray free-electron laser in Spring8 in Japan.Andmillions of scattering patterns were obtained from the X-ray free-electron laser experiment.Through the analysis of the scattering data,the sum,mean,median and variance of the scattering intensity were obtained.Then different clusters were obtained with the densitybased spatial clustering of applications with noise(DBSCAN)algorithm.Results Based on the DBSCAN,some of the scattering patterns with high artifacts were removed and different clusters were clarified.So the experimental scattering data could be analyzed more effectively.Conclusion The theoretical and experiment fundamentals for comprehensively studying the X-ray scattering data of the complex biological sample were provided.After the data filtering,the angular autocorrelation of different clusters with Kam’s method will be computed and analyzed effectively.展开更多
Shape descriptors have recently gained popularity in shape matching,statistical shape modeling,etc.Their discriminative ability and efficiency play a decisive role in these tasks.In this paper,we first propose a novel...Shape descriptors have recently gained popularity in shape matching,statistical shape modeling,etc.Their discriminative ability and efficiency play a decisive role in these tasks.In this paper,we first propose a novel handcrafted anisotropic spectral descriptor using Chebyshev polynomials,called the anisotropic Chebyshev descriptor(ACD);it can effectively capture shape features in multiple directions.The ACD inherits many good characteristics of spectral descriptors,such as being intrinsic,robust to changes in surface discretization,etc.Furthermore,due to the orthogonality of Chebyshev polynomials,the ACD is compact and can disambiguate intrinsic symmetry sinces everal directions are considered.To improve the ACD’s discrimination ability,we construct a Chebyshev spectral manifold convolutional neural network(CSMCNN)that optimizes the ACD and produces a learned ACD.Our experimental results show that the ACD outperforms existing state-of-the-art handcrafted descriptors.The combination of the ACD and the CSMCNN is better than other state-of-the-art learned descriptors in terms of discrimination,efficiency,and robustness to changes in shape resolution and discretization.展开更多
基金financially supported by the National Natural Science Foundation of China(Grant No.31925034)the National Key Research and Development Program of China(Grant No.2022YFF1003100)+1 种基金the Foundation of Hubei Hongshan Laboratory(Grant No.2021hszd016)Key project of Hubei provincial Natural Science Foundation(Grant No.2021CFA017)。
文摘Citric acid is an important contributor to fruit flavor.The extremely significant differences in citric acid levels are observed among citrus species and varieties.The molecular basis of citric acid accumulation remains largely unknown on the inter-species level.Here,we performed transcriptome analysis of five pairs of acidic and acidless variety fruits from kumquat(Citrus crassifolia),lemon(C.limon),pummelo(C.maxima),mandarin(C.reticulata),and sweet orange(C.sinensis)to investigate the common and specific genes related to citric acid accumulation in these citrus species.Transcript profiles of the citrate metabolism genes revealed that the mechanism of citric acid accumulation in kumquat differed from that in the other four species.The comparative analysis and weighted gene co-expression network analysis identified 61 candidate genes from lemon,pummelo,mandarin,and sweet orange.Vacuolar acidification regulated by CitPH4-CitAN1-CitPH5was a common mechanism underlying citric acid accumulation in these four species.In addition,gene network analysis indicated that CitPH4 was a central regulator,exhibiting a strong correlation with the genes involved in vacuolar trafficking and potassium(K^(+))transport.The co-expression and functional enrichment analyses showed that active sugar metabolism and increased citrate synthesis were mainly responsible for the accumulation of citric acid in kumquat.Twenty-four transcription factors were identified as candidate regulators,of which CitbHLH28 was found to regulate acidity level via transactivating CWINV2 and PK3 expressions.Overall,this study provides an insight into the mechanism of citric acid accumulation in citrus fruit and provides useful references for fruit quality improvement through acidity control in different citrus species.
基金partially funded by the National Natural Science Foundation of China(U2142205)the Guangdong Major Project of Basic and Applied Basic Research(2020B0301030004)+1 种基金the Special Fund for Forecasters of China Meteorological Administration(CMAYBY2020-094)the Graduate Student Research and Innovation Program of Central South University(2023ZZTS0347)。
文摘Traditional meteorological downscaling methods face limitations due to the complex distribution of meteorological variables,which can lead to unstable forecasting results,especially in extreme scenarios.To overcome this issue,we propose a convolutional graph neural network(CGNN)model,which we enhance with multilayer feature fusion and a squeeze-and-excitation block.Additionally,we introduce a spatially balanced mean squared error(SBMSE)loss function to address the imbalanced distribution and spatial variability of meteorological variables.The CGNN is capable of extracting essential spatial features and aggregating them from a global perspective,thereby improving the accuracy of prediction and enhancing the model's generalization ability.Based on the experimental results,CGNN has certain advantages in terms of bias distribution,exhibiting a smaller variance.When it comes to precipitation,both UNet and AE also demonstrate relatively small biases.As for temperature,AE and CNNdense perform outstandingly during the winter.The time correlation coefficients show an improvement of at least 10%at daily and monthly scales for both temperature and precipitation.Furthermore,the SBMSE loss function displays an advantage over existing loss functions in predicting the98th percentile and identifying areas where extreme events occur.However,the SBMSE tends to overestimate the distribution of extreme precipitation,which may be due to the theoretical assumptions about the posterior distribution of data that partially limit the effectiveness of the loss function.In future work,we will further optimize the SBMSE to improve prediction accuracy.
基金supported by the following grants: National Basic R&D Program of China (2018YFA0606203)Strategic Priority Research Program of Chinese Academy of Sciences (XDA23090102 and XDA20060501)+2 种基金Guangdong Major Project of Basic and Applied Basic Research (2020B0301030004)Special Fund of China Meteorological Administration for Innovation and Development (CXFZ2021J026)Special Fund for Forecasters of China Meteorological Administration (CMAYBY2020094)。
文摘Convolutional neural networks(CNNs) have been widely studied and found to obtain favorable results in statistical downscaling to derive high-resolution climate variables from large-scale coarse general circulation models(GCMs).However, there is a lack of research exploring the predictor selection for CNN modeling. This paper presents an effective and efficient greedy elimination algorithm to address this problem. The algorithm has three main steps: predictor importance attribution, predictor removal, and CNN retraining, which are performed sequentially and iteratively. The importance of individual predictors is measured by a gradient-based importance metric computed by a CNN backpropagation technique, which was initially proposed for CNN interpretation. The algorithm is tested on the CNN-based statistical downscaling of monthly precipitation with 20 candidate predictors and compared with a correlation analysisbased approach. Linear models are implemented as benchmarks. The experiments illustrate that the predictor selection solution can reduce the number of input predictors by more than half, improve the accuracy of both linear and CNN models,and outperform the correlation analysis method. Although the RMSE(root-mean-square error) is reduced by only 0.8%,only 9 out of 20 predictors are used to build the CNN, and the FLOPs(Floating Point Operations) decrease by 20.4%. The results imply that the algorithm can find subset predictors that correlate more to the monthly precipitation of the target area and seasons in a nonlinear way. It is worth mentioning that the algorithm is compatible with other CNN models with stacked variables as input and has the potential for nonlinear correlation predictor selection.
基金the National Natural Science Foundation of China(Nos.21976002,21675158,21507134,61603001,61705239 and 81773684)Natural Science Foundation of Anhui Province(Nos.1908085MB41,1908085QB75)+2 种基金Guangdong Natural Science Funds for Distinguished Young Scholars(No.2018B030306033)Pearl River S&T Nova Program of Guangzhou(No.201806010060)Pearl River Talent Program(No.2017GC010363)。
文摘Under the public spotlight,uranyl(UO22+)ions has attracted considerable attention for the extreme radioactive and chemical toxicity to ourselves and our environment.Herein,we present a simple and effective ratiometric fluorescence imaging method for the visualizing and quantitative detection UO22+ions by cellphone-based optical platform.The sensing solution was prepared by mixing label-free red carbon dots(r-CDs)and blue carbon dots(b-CDs)together with a fixed photoluminescence intensity ratio of 4:1.When UO22+ions were added,the fluorescence of r-CDs can be selectively quenched,while the fluorescence of b-CDs remains stable without spectral cha nges.With the gradually increase the amounts of UO22+ions,the different response of dual-color CDs resulted in a signification color evolution from deep red to dark purple under the ultraviolet(UV)light illumination.Then,a cellphone-based optical platform was constructed for directly imaging the color change of the samples,and the built-in Colorpicker APP quickly output the red,green and blue(RGB)channel values of these images within one second.Interesting,there was a linear relationship between the ratio of red and blue(R/B)channel values and UO22+ions concentration from 0μmol/L to 30.0μmol/L(R^2=0.92804)with the detection limit of^8.15μmol/L(signal-to-noise ratio of 3).In addition,the optical platform has also been applied to the quantification of UO22+ions in tap water and river water sample.With the advantage of low-cost,portable,easy to operation,we anticipate that this method would greatly improve the accessibility of UO22+ions detection even in resource-limited areas.
基金supported by a National Natural Science Foundation of China grant to Q.X.(nos.32494781 and 32525008)the Key Project of Hubei Provincial Natural Science Foundation grant to Q.X.(2025AFA006)+1 种基金the Foundation of Hubei Hongshan Laboratory grants to Q.X.and X.W.(nos.2021hszd016 and 2022hsqd010,respectively)a National Natural Science Foundation of China Youth Science Fund grant to G.L.(no.32302490).
文摘The fruit of chestnut rose(Rosa roxburghii Tratt.)contains exceptionally high levels of L-ascorbic acid(AsA)(∼1762 mg/100 g fresh weight),approximately 40-fold higher than those found in sweet orange(Citrus sinensis),which is well known for its high AsA content.However,the molecular mechanisms driving such high accumulation in chestnut rose remain unclear.Here,we report that the genes R.roxburghii PECTIN METHYLESTERASE(RroxPME),D-GALACTURONATE REDUCTASE(RroxGalUR),and DEHYDROASCORBATE REDUCTASE 2(RroxDHAR2)play crucial roles in AsA accumulation in chestnut rose fruit.By comparing R.roxburghii with the closely related Rosa multiflora,which has low AsA concentrations,we identified a 545-bp insertion in the promoter of RroxGalUR.We found that TRANSPARENT TESTA GLABRA 2(RroxTTG2),a well-known key regulator of trichome development,binds to the W-box-containing inserted region of the RroxGalUR promoter as well as the promoters of RroxPME and RroxDHAR2.In contrast,in sweet orange,CsTTG2 can bind only to CsPME.Furthermore,RroxTTG2 retains its conserved role in the regulation of trichome development during early fruit development,suggesting its spatiotemporal specificity in regulating both trichome development and AsA biosynthesis.To evaluate the application value of this pathway in other species,we heterologously expressed RroxTTG2,RroxPME,RroxGalUR,and RroxDHAR2 in lettuce(Lactuca sativa L.),which increased AsA concentrations in the transgenic lines by up to 355%(an increase from approximately 2 to 10 mg/100 g fresh weight).This study provides insights into mechanisms underlying AsA accumulation in chestnut rose and the spatiotemporal transcriptional regulation of AsA biosynthesis and trichome development.
基金the National Key Research and Development Program of China(2018YFD1000101)Hubei Provincial Natural Science Foundation of China(2021CFA017 and 2019CFA014)the National Natural ScienceFoundationof China(32001998).
文摘Dear Editor,The genus Citrus comprises more than 30 species worldwide(Swingle,1943).However,citrus genetics and traditional breeding are hindered due to asexual reproduction,long generation time,and empirical utilization of the germplasm.The whole-genome information of different citrus species accelerates the genetic studies and improves the breeding efficiency by high-density markers.
基金supported by funding from the National Natural Science Foundation of China granted to Q.X.(number 31925034)the National Key Research and Development Program of China granted to Q.X.(number 2022YFF1003100)+3 种基金Major Special Projects and Key R&D Projects in Yunnan Province granted to Q.X.(202102AE090054)the Key Research and Development Program of Hubei granted to X.W.(number 2022BBA155)the Foundation of Hubei Hongshan Laboratory granted to Q.X.(number 2021hszd016)Key Project of Hubei Provincial Natural Science Foundation granted to Q.X.(number 2021CFA017)。
文摘Dwarfing is a pivotal agronomic trait affecting both yield and quality.Citrus species exhibit substantial variation in plant height,among which internode length is a core element.However,the molecular mechanism governing internode elongation remains unclear.Here,we unveiled that the transcriptional cascade consisting of B-BOX DOMAIN PROTEIN 22(BBX22)and ELONGATED HYPOCOTYL 5(HY5)finely tunes plant height and internode elongation in citrus.Loss-of-function mutations of BBX22 in an early-flowering citrus(Citrus hindsii“SJG”)promoted internode elongation and reduced pigment accumulation,whereas ectopic expression of BBX22 in SJG,sweet orange(C.sinensis),pomelo(C.maxima)or heterologous expression of BBX22 in tomato(Solanum lycopersicum)significantly decreased internode length.Furthermore,exogenous application of gibberellin A3(GA3)rescued the shortened internode and dwarf phenotype caused by BBX22overexpression.Additional experiments revealed that BBX22 played a dual role in regulation internode elongation and pigmentation in citrus.On the one hand,it directly bound to and activated the expression of HY5,GA metabolism gene(GA2 OXIDASE 8,GA2ox8),carotenoid biosynthesis gene(PHYTOENE SYNTHASE 1,PSY1)and anthocyanin regulatory gene(Ruby1,a MYB DOMAIN PROTEIN).On the other hand,it acted as a cofactor of HY5,enhancing the ability of HY5 to regulate target genes expression.Together,our results reveal the critical role of the transcriptional cascade consisting of BBX22 and HY5 in controlling internode elongation and pigment accumulation in citrus.Unraveling the crosstalk regulatory mechanism between internode elongation and fruit pigmentation provides key genes for breeding of novel types with both dwarf and health-beneficial fortification in citrus.
文摘Background:Patients with extensive burns usually develop pro-coagulation soon after the injury if there is no sepsis occurred.We describe the case of an extensive burn adult suffering from hypocoagulation not related to sepsis,but secondary to antibiotic treatment.Case presentation:Here,we report a case of an adult male patient suffering from flame burns of 45%total body surface area(40%full thickness)combined with inhalation injury.Hypocoagulopathy with soaring prolonged activated partial thromboplastin time value occurred on third week post-burn while systemic infection had been under control by application of broad-spectrum antibiotics.Investigations showed that not the infection but vitamin K-related coagulation factor deficiency were responsible for unexpected bleeding.However,supplemental vitamin K was not the key as we expected,which prompted us trying to decode the underlying cause of coagulation disturbance in this patient and pick out the most effective treatment for live-saving.After the withdrawal of highly suspected broad-spectrum antibiotic,Meropenem^(■),disturbed vitamin K related coagulation factors gradually restored to their optimal levels so as to maintain normal coagulation status.Therefore,surgical procedures without further risk of bleeding could be carried out in time for wound recovery.The patient was discharged on post-burn day 67 and transferred to a secondary hospital for his rehabilitation.Conclusion:Hypocoagulopathy may be devoted to different reasons other than sepsis in extensive burns.Early recognition of the cause for coagulation disturbance is critical to make appropriate treatment and save patients’lives.This case illustrated the importance of unveiling the mist cause for coagulation disturbance occurred in extensive burn patient,which paved the way for optimal life-saving treatments.And we also recommend burn surgeons to be alerted to antibiotic-induced vitamin K deficiency-related coagulopathy among critical burn patients.
基金This work was supported by the Excellence Program of Key Clinical Specialty of Beijing in 2020,Beijing Municipal Science and Technology Commission(grant number:Z201100005520051)China Health Information and HealthCare Big Data Association Severe Infection Analgesia and Sedation Big Data Special Fund(grant number:Z-2019-1-001)+2 种基金China International Medical Foundation Analgesia and Sedation Special Fund(grant number:Z-2017-24-2028-01)National NaturalScience Foundation of China(grant number:11801020)Beijing Municipal Natural Science Foundation(grant number:7192163).
文摘Background:The relationship between perfusion index(PI)and organ dysfunction in patients in the intensivecare unit(ICU)is not clear.This study aimed to explore the relationship between PI and renal function in theperioperative critical care setting and evaluate the predictive efficiency of PI on patients with acute kidney injury(AKI)in the ICU.Methods:This retrospective analysis involved 12,979 patients who had undergone an operation and were admitted to the ICU in Peking Union Medical College Hospital from January 2014 to December 2019.The distributionof average PI in the first 24 h after ICU admission and its correlation with AKI was calculated by Cox regression.Receiver operating characteristic(ROC)curves were generated to compare the ability of PI,mean arterial pressure(MAP),creatinine,blood urea nitrogen(BUN),and central venous pressure(CVP)to discriminate AKI in thefirst 48 h in all perioperative critically ill patients.Results:Average PI in the first 24 h served as an independent protective factor of AKI(Odds ratio[OR]=0.786,95%confidence interval[CI]:0.704–0.873,P<0.0001).With a decrease in PI by one unit,the incidence of AKIincreased 1.74 times.Among the variables explored for the prediction of AKI(PI,MAP,creatine,BUN,and CVP),PI yielded the highest area under the ROC curve,with a sensitivity of 64.34%and specificity of 70.14%.A cut-offvalue of PI≤2.12 could be used to predict AKI according to the Youden index.Moreover,patients in the low PIgroup(PI≤2.12)exhibited a marked creatine elevation at 24–48 h with a slower decrease compared with thosein the high PI group(PI>2.12).Conclusions:As a local blood flow indicator,the initial 24-h average PI for perioperative critically ill patients canpredict AKI during their first 120 h in the ICU.
基金Open access funding provided by Shanghai Jiao Tong Universitysupported by Major Special Projects and Key R&D Projects in Yunnan Province(NO.202102AE090054)+1 种基金the National Natural Science Foundation of China granted to Q.X.(numbers 31925034)Key project of Hubei provincial Natural Science Foundation(2021CFA017).
文摘Phase transition and floral induction in citrus requires several years of juvenility after germination.Such a long period of juvenility has been a major hindrance to its genetic improvement program.Studies have shown that miR156 along with its downstream genes SQUAMOSA PROMOTER BINDING PROTEINS(SBP)and SBP-LIKE(SPL)mediate the phase transition and floral induction process in plants.Our current study has systematically analyzed SPLs in 15 different citrus-related species,systematically annotated them based on their close homology to their respective Arabidopsis orthologs,and confirmed the functional attributes of the selected members in floral precocity.The majority of the species harbored 15 SPLs.Their cis-element assessment suggested the involvement of the SPLs in diverse developmental and physiological processes in response to different biotic and abiotic cues.Among all,SPL5,SPL9,and SPL11 stood out as consistently differentially expressed SPLs in the adult and young tissues of different citrusrelated species.Independent overexpression of their F.hindsii orthologs(FhSPL5,FhSPL9,and FhSPL11)brought an enhanced expression of endogenous FLOWERING LOCUS T leading to the significantly precocious flowering in transgenic Arabidopsis lines.Future study of the genes in the citrus plant itself is expected to conclude the assessments made in the current study.
基金National Institutes of Health research Grant 251 R01-GM097463Stanford NIH Biotechnology Training Grant No.5T32GM008412-20,US Department of Energy Office of Science under Contract No.DE-AC02-05CH11231National Nature Science Foundation of China for theoretical physics Grant No.11547238.
文摘Background At present,it is insufficient to understand the basic data characteristics of the correlated X-ray scattering.And there is a great challenge about how to master the nature of the data.So it is difficult to use and analyze the experimental data more effectively.In addition,there are many reasons,for the experimental artifacts such as whether the shutter is on or off,whether there is the beam line or not,the swaying of the nozzle and the shadow of the detector.So it is rather challenging to analyze the scattering patterns.Purpose The purpose of this paper was to develop a method to filter the invalid scattering data and provide the theoretical and experiment fundamentals for studying the X-ray scattering data of the complex biological sample further.Methods The heliummolecules were scattered by the X-ray free-electron laser in Spring8 in Japan.Andmillions of scattering patterns were obtained from the X-ray free-electron laser experiment.Through the analysis of the scattering data,the sum,mean,median and variance of the scattering intensity were obtained.Then different clusters were obtained with the densitybased spatial clustering of applications with noise(DBSCAN)algorithm.Results Based on the DBSCAN,some of the scattering patterns with high artifacts were removed and different clusters were clarified.So the experimental scattering data could be analyzed more effectively.Conclusion The theoretical and experiment fundamentals for comprehensively studying the X-ray scattering data of the complex biological sample were provided.After the data filtering,the angular autocorrelation of different clusters with Kam’s method will be computed and analyzed effectively.
基金supported by the National Natural Science Foundation of China(Nos.62172447,61876191)Hunan Provincial Natural Science Foundation of China(No.2021JJ30172)the Open Project Program of the National Laboratory of Pattern Recognition(NLPR)(No.202200025).
文摘Shape descriptors have recently gained popularity in shape matching,statistical shape modeling,etc.Their discriminative ability and efficiency play a decisive role in these tasks.In this paper,we first propose a novel handcrafted anisotropic spectral descriptor using Chebyshev polynomials,called the anisotropic Chebyshev descriptor(ACD);it can effectively capture shape features in multiple directions.The ACD inherits many good characteristics of spectral descriptors,such as being intrinsic,robust to changes in surface discretization,etc.Furthermore,due to the orthogonality of Chebyshev polynomials,the ACD is compact and can disambiguate intrinsic symmetry sinces everal directions are considered.To improve the ACD’s discrimination ability,we construct a Chebyshev spectral manifold convolutional neural network(CSMCNN)that optimizes the ACD and produces a learned ACD.Our experimental results show that the ACD outperforms existing state-of-the-art handcrafted descriptors.The combination of the ACD and the CSMCNN is better than other state-of-the-art learned descriptors in terms of discrimination,efficiency,and robustness to changes in shape resolution and discretization.
