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Attributing intensification extreme precipitation to anthropogenic factors on the regional scale is challenging, given the large fluctuations and the complexity of quantifying interactions among these anthropogenic factors. Here, we propose a new variance‐based method to investigate the roles of human‐induced greenhouse gas (GHG), aerosol (AER), and their interactions (GA) in shaping extreme precipitation on the Qinghai‐Tibet Plateau (QTP) at stational scale. In terms of contribution, GHG has the greatest impact on total wet‐day precipitation and simple daily intensity. In terms of significance, GA, and AER exert significant effects on all 10 extreme indices (P; < 0.05) over 48.3% and 44.8% of all stations, while GHG affects less (25.9%). Overall, GHG is not the only dominant factor, and GA and AER are expected to play vital roles in intensifying extreme precipitation over the QTP under SSP2‐4.5. These findings challenge the conventional insights that GHG is the primary anthropogenic driver of extreme precipitation. Plain Language Summary: Greenhouse gas (GHG) has long been regarded as the primary anthropogenic driver of the intensification of extreme precipitation. However, extreme precipitation is closely linked to the complex interplay of various anthropogenic influences, with contributions varying across regions due to differences in longitude, latitude, and altitude. Here, we propose a new method to robustly quantify the contributions of GHG, AER, and GA to extreme precipitation at each station on the Qinghai‐Tibet Plateau (QTP). The results show that the majority of the stations quantified by this method are statistically significant. Importantly, we find that complex interactions of GHG and AER will shape extreme precipitation over the QTP. These findings challenge the traditional understanding of climate change attributed solely to GHG and prompt a reconsideration of whether reducing GHG alone could effectively mitigate climate change. Key Points: We propose a new variance‐based factorial analysis method to quantify contributions of anthropogenic factors at each meteorological station over Qinghai‐Tibet Plateau (QTP)Extreme precipitation over the QTP is projected to increase in the upcoming centuryThe interaction between greenhouse gas and aerosol would play a key role in intensification extreme precipitation over QTP under SSP2‐4.5 [ABSTRACT FROM AUTHOR]

Japanese apricot is an important subtropical deciduous fruit tree in China, widely distributed in different altitude areas. How does it adapt to the different temperature environments in these areas? In this study, we identified a low‐temperature transcription factor PmCBF03 on chromosome 7 through adaptive analysis of populations at different altitudes, which has an early termination single nucleotide polymorphism mutation. There were two different types of variation, PmCBF03A type in high‐altitude areas and PmCBF03T type in low‐altitude areas. PmCBF03A gene increased the survival rate, Fv/Fm values, antioxidant enzyme activity, and expression levels of antioxidant enzyme genes, and reducing electrolyte leakage and accumulation of reactive oxygen species in transgenic Arabidopsis under low temperature and freezing stress. Simultaneously, PmCBF03A gene promoted the dormancy of transgenic Arabidopsis seeds than wild‐type. Biochemical analysis demonstrated that PmCBF03A directly bound to the DRE/CRT element in the promoters of the PmCOR413, PmDAM6 and PmABI5 genes, promoting their transcription and enhanced the cold resistance and dormancy of the overexpressing PmCBF03A lines. While PmCBF03T gene is unable to bind to the promoters of PmDAM6 and PmABI5 genes, leading to early release of dormancy to adapt to the problem of insufficient chilling requirement in low‐altitude areas. Summary statement: The PmCBF03 allele variation is involved in regulating the low‐temperature adaptability of Japanese apricots at different altitudes. [ABSTRACT FROM AUTHOR]

Collaborative management of the water‐energy‐food‐ecosystems (WEFE) nexus can contribute significantly to sustainable development. However, multiple decision‐making levels with diverse preferences and multiple uncertainties in different forms pose intractable challenges to the management process. In this study, a novel optimization method named as multi‐level chance‐constrained fuzzy programming (MCFP) is developed to jointly manage the WEFE nexus. MCFP has advantages in evaluating trade‐offs among multiple competitive decision makers, solving decentralized planning problems with hierarchical structure, and tackling uncertainties expressed as randomness and vagueness. MCFP is then applied to the WEFE nexus in Central Asia, where five countries, 43 states, six water sources, and eight water users are involved over a long‐term planning horizon (2021–2050). A set of scenarios are designed to reflect decision‐making preferences based on different irrigation efficiencies, food, ecological and electricity demands as well as constraint‐violation probability and system credibility levels. The major findings are: (a) the proportion of agricultural water allocation would reduce to 45.4%–56.6% by 2050 to save more water for ensuring ecological restoration and energy supply; and (b) in order to balance water demands and support regional sustainable development, policymakers should sacrifice some of the benefits, set strict arable land limits for cereal crops, improve irrigation efficiency through adopting drip and sprinkler irrigation, and avoid the effects of the irrigation efficiency paradox. The findings are helpful for policymakers in gaining insight into the interrelationships of water, energy, food and ecosystems as well as making decisions for collaborative management of the WEFE nexus system. Plain Language Summary: In Central Asia, water scarcity, food crisis, energy insecurity and ecological degradation are closely linked. Economic development and diminishing resources further exacerbate these problems. Therefore, a "nexus" concept is needed to analyze trade‐offs and synergize management to promote the efficient use of resources. However, the management process faces the problems of uncertain information and multiple decision makers with different preferences, which adds to the complexity of the management process. To address the above issues, this study develops a collaborative management model for the water‐energy‐food‐ecosystems (WEFE) nexus in Central Asia based on a multi‐level programming framework. Besides, the agricultural irrigation paradox is also considered in the developed model. The results find that to ensure food security and ecological restoration, decision makers need to forego some of the benefits and allocate more water resources to cereal crops and ecological uses. In addition, it is recommended that managers increase advanced irrigation methods, such as drip and sprinkler irrigation, but that care be taken to curb the irrigation efficiency paradox while increasing irrigation efficiency. Key Points: We proposed an optimization method to plan the water‐energy‐food‐ecosystems nexus for Central Asia over a long‐planning horizonThe uncertain information expressed as randomness and vagueness were tackled during the planning processThe agricultural irrigation paradox is considered during the collaborative management, thus providing decision support to managers [ABSTRACT FROM AUTHOR]

Wind energy has grown rapidly in recent years as a measure to control carbon emissions and mitigate climate change. Extreme wind can damage wind turbines, cause losses to wind power plants, limit economic benefits of wind energy facilities, and disrupt regional grid balance. Therefore, an accurate assessment of extreme wind speeds at wind turbine hub height and their spatiotemporal variation under climate change is critical for the planning of wind energy and for guaranteeing regional energy security. In this study, the 100‐m extreme wind speeds in China are estimated using an empirical downscaling and Bayesian model averaging ensemble method with the latest ERA5 reanalysis and 20 global climate models (GCMs) from the Coupled Model Intercomparison Project phase 6 (CMIP6). Two shared socioeconomic pathways (SSP), that is, SSP2‐4.5 and SSP5‐8.5, are considered to account for the uncertainty in anthropogenic emissions. According to the results, the highest extreme wind speeds are primarily found in Inner Mongolia, northeast China, western Tibet, and the eastern coastal region. Extreme wind speeds in central and southeastern China are projected to increase by approximately 2% in the middle (2031–2060) and the end (2071–2100) of the 21st century relative to the baseline period (1985–2014). Summer extreme wind speeds in northwestern Tibet are expected to increase by more than 9% at the end of the century. The findings of this study indicate that it is important to take the present and projected changes in local wind extremes into account when choosing locations for wind power plants and wind energy installations. Plain Language Summary: Wind energy is one of the key renewable energy sources and has been widely developed worldwide to mitigate global warming. Extreme wind can damage wind turbines and jeopardize the reliability of wind power generation, disturbing the stability of regional power supplies. Therefore, understanding the spatial and temporal variability of extreme wind speeds at wind turbine hub height under climate change is essential for the development of local wind power. This study examines the spatial and temporal patterns of 100‐m extreme wind speeds in China using empirical downscaling and Bayesian model averaging ensemble methods driven by several global climate models and reanalysis data. The results show that Inner Mongolia, northeastern China, western Tibet, and eastern coastal areas are the areas in China where high extreme wind speeds are most prevalent. This spatial pattern will typically persist in the future, but extreme wind speeds in Tibet, Qinghai, and Sichuan will drop dramatically by the end of the 21st century. Extreme wind speeds are considerably higher in winter and autumn than in the other two seasons. Local governments should take measures to prevent regional energy disparities due to the deterioration of wind turbines because of the anticipated wind extremes under climate change. Key Points: An empirical downscaling Bayesian ensemble projection model is constructed to investigate extreme wind speed variationsExtreme wind speeds in central and southeastern China are projected to increase in future periodsExtreme wind speeds are considerably higher in winter and autumn than in the other two seasons [ABSTRACT FROM AUTHOR]

In this study, an ensemble Bayesian inference‐based copula approach (EBICA) has been proposed to evaluate the joint risk of extreme precipitation indices under climate change. EBICA incorporates GCMs, quantile delta mapping‐based bias correction method, Monte Carlo Markov Chain (MCMC)‐based Bayesian inference method, and copula functions into an integration, where 17 GCMs and 3 copulas are explored EBICA can reflect the inherent uncertainties in GCM and copula selections, as well as deal with the uncertainty caused by copula parameters when modelling the dependent structures. Ensemble results of GCMs and copulas are also analysed to promote the projection accuracy of dynamic features of extreme precipitation (characterized by precipitation intensity, very heavy precipitation amount and frequency, and maximum 1 or 5‐day precipitation amount). EBICA is then applied to Fujian Province to investigate climate change impacts on extreme precipitation during 2021–2099. Major findings can be summarized as (a) GCM is the primary source of uncertainties that impacts extreme precipitation projection, and the ensemble of GCMs suggests that climate change would exacerbate future precipitation intensity, amount, and frequency over Fujian Province; (b) mountainous area in Fujian is more easily encountered with very heavy precipitation amount and coastal area is more easily faced with maximum 1‐day or consecutive 5‐day precipitation under climate change; (c) Fujian Province would averagely encounter with shorter co‐occurrence period of [SDII, R95p] and [R20mm, R95p], corresponding to higher risk level in very heavy precipitation amount and frequency, especially in the north part. Generally, these findings could help lay the foundation for forecasting and warning of extreme precipitation events and reducing associated risk losses. [ABSTRACT FROM AUTHOR]

SUMMARY: Analysis of electricity consumption behaviors lays the foundation for power grid planning, demand‐side response, electricity pricing, and energy efficiency improvement. In this study, we used the principal component analysis (PCA) to reduce the dimensionality of electricity load data and used the density peak clustering algorithm based on K‐nearest neighbors and shared nearest neighbor similarity (DPC‐KS) for cluster analysis of load profiles so as to obtain the electricity consumption behaviors of customers. In DPC‐KS, the local density was defined by integrating the idea of K‐nearest neighbors to find the density peaks, which promoted the accuracy of the cluster centers found. Also, a sample similarity measure criterion of shared nearest neighbor similarity was defined, a sample similarity matrix was built, and the samples were allocated accordingly, which enables a more accurate allocation of the remaining samples. Additionally, PCA and DPC‐KS were used to conduct cluster analysis for the electricity load data of 315 dedicated substation customers in a region, and four types of electricity consumption behaviors were obtained and analyzed. The experiments validated the effectiveness of DPC‐KS, and DPC‐KS provided technical support for intelligent decision‐making in the power grid. [ABSTRACT FROM AUTHOR]

SUMMARY: Japanese apricot (Prunus mume) is an attractive fruit tree originating from China, and its cultivation history dates back 7000 years. In this study, we investigated the genetic diversity, population structure, and genetic relationship of Japanese apricots in different regions of China and Japan. The analyses of the genetic variation between wild and cultivated populations improved our understanding of the general mechanisms of domestication and improvement. A total of 146 accessions of Japanese apricot from different geographic locations were sequenced. The genetic diversity of wild and domesticated accessions (3.60 × 10−3 and 3.51 × 10−3, respectively) from China was high, and the effect of artificial selection pressure on domesticated accessions was small; however, the genetic diversity of artificially bred accessions decreased significantly (2.68 × 10−3) compared to domesticated accessions, which had an obvious improvement bottleneck effect. The chloroplast genome results showed that 41 haplotypes were detected, and Japanese apricots from the Yunnan region had the most haplotypes and the highest genetic diversity. The results revealed the dissemination route of Japanese apricot, not only along the Yangtze River basin system (from southwest China to Hunan, Jiangxi, and Anhui, and finally to the Jiangsu, Zhejiang, and Shanghai areas). Additionally, we discovered a second route for Japanese apricot dispersion, which was mostly in the Pearl River basin system, from southwest China to Libo of Guizhou and then to the Guangdong, Fujian, and Taiwan areas. This also showed that Japanese‐bred accessions originated from Zhejiang, China. In addition, selective sweep analysis showed that most of the high‐impact single nucleotide polymorphisms were identified in genes related to glucose metabolism, aromatic compound metabolism, flowering time, dormancy, and resistance to abiotic stress during the domestication and improvement of Japanese apricot. Significance Statement: Japanese apricot was widely distributed in different regions of China. As for how to disseminate in different regions, there has been a great controversy in the academic circles. This study provided novel insight into the evolution and dissemination of Japanese apricot and a greater number of valuable genome resources for the genetic improvement and effective utilization of Japanese apricot. [ABSTRACT FROM AUTHOR]

Heatwave events over Guangdong have attracted recent attention under changing climate conditions. It is desired to explore the future changes of heatwave due to its associated consequences on society economy and environment. In this study, a stepwise‐clustered heatwave downscaling approach (i.e., SCHW) was developed for the projection of HWs in Guangdong. The heatwave indicators (occurrence, duration, magnitude, intensity, frequency, and accumulated intensity) were investigated from both the absolute and relative definitions of heatwave events (i.e., AHWs and RHWs) based on the multi‐model ensemble of 13 coupled model intercomparison projected phase 5 (CMIP5) global climate models (GCMs) under two representative concentration pathways (RCPs). The trends (i.e., 0.18–0.29°C per decade under RCP4.5 and 0.30–0.58°C per decade under RCP8.5) of the projected daily maximum temperature indicate that Guangdong would experience continuous warming in the future. The occurrence, frequency, and accumulated intensity of heatwave would increase by 198%, 272%, and 346% in the 2080s (i.e., 2066–2095) under RCP8.5 compared to the historical period (i.e., 1976–2005), respectively. Moreover, the three indicators of HWs are projected to have more substantial increases over inland Guangdong than its costal parts. The spatial variation of occurrence of absolute and relative heatwave under RCP8.5 (2.80 and 2.78) is larger than these under RCP4.5 (2.50 and 2.32) during 2080s (i.e., 2066–2095). The projections of future HWs can help provide valuable information for assessing extreme climate change and identifying desired adaptation strategies. [ABSTRACT FROM AUTHOR]

China's urban population will increase by 268 million from 2010 to 2030, with the consumption of a large number of resource‐intensive products. Quantitative analysis of the environmental impacts (water, energy and carbon) of urban agglomerations can make trade‐offs among water conservation, energy use, climate change mitigation, and urban development. In this study, a multi‐layer water‐energy‐carbon production path analysis (MWPPA) model is developed for identifying the key final demands, sectors and supply chain paths of the Pearl River Delta urban agglomeration (PUA). Results show that, water, energy and carbon‐emission intensities respectively reduced by 27.3%, 35.6% and 27.6% in 2015, compared to the levels in 2012. More than half of the water‐energy‐carbon (WEC) footprints are export‐driven, where Guangzhou, Shenzhen and Foshan dominate the WEC footprints of PUA. Results also disclose that Shenzhen is the main recipient of water‐energy, while Jiangmen and Huizhou are the main providers of water and energy, respectively. Policy makers are suggested that each industry actively integrate into global value chains in order to leverage its comparative advantage, and Huizhou should take full advantage of its fossil base to form a complete industry chain from the R&D end to the production end around the energy industry. Plain Language Summary: Not only do urban areas consume large amounts of water and energy, they are also the specific implementation units of carbon reduction policies. The United Nations Sustainable Development goals (UN SDGs) make it clear that water conservation, energy access, climate change mitigation, and urbanization development are important parts of its agenda. As one of the most developed urban agglomerations in China, the Pearl River Delta urban agglomeration (PUA) is also the main consumer of water, energy and carbon (WEC). This study reveals that more than half of the WEC footprints are export‐driven, and Guangzhou, Shenzhen and other developed economies dominate the WEC footprints of PUA. Compared to 2012, the consumption intensity of WEC was reduced in 2015. The results also find that light industry and equipment manufacture play key roles in the WEC system. Results suggest that greener production needs to be adopted not only within but also outside of urban agglomerations, while individual cities need to actively promote the integration of each industry into global supply chains. Key Points: A multi‐layer water‐energy‐carbon production path analysis model is developedExports drive more than half of water, energy and carbon footprints in the Pearl River DeltaIn the Pearl River Delta, cities of Jiangmen and Huizhou supply the most water and energy, and Huizhou and Dongguan provide the most carbon [ABSTRACT FROM AUTHOR]

Land plants have a unique vascular bundle system that ranges in length from a few centimeters to hundreds of meters. These systems integrate the various organs of the whole plant, perform material exchange between different plant tissues and mediate the transmission of signals between cells or over long distances. Grafting and parasitism can reshape the vascular tissues of different ecotypes or species and represent two important systems for studying plant systemic signaling. In recent years, with the advancement of genomics and sequencing technology, the transportation, identification, and function of systemic plant macromolecules have been extensively studied. Here, we review the current body of knowledge of the transport pathways and regulatory mechanisms of macromolecules in plants and assess systemic, long‐distance signal trafficking that mediates stress responses, and plant–environment or plant–insect community interactions. Additionally, we propose several methods for identifying mobile mRNAs and proteins. Finally, we discuss the challenges facing systemic signaling research and put forth the most urgent questions that need to be answered to advance our understanding of plant systemic signaling. [ABSTRACT FROM AUTHOR]

With a changing climate, drought has become a common natural disaster. In our study, population exposure to drought over the Pearl River Basin (PRB) under climate change is investigated. Drought frequency is evaluated through the Standardized Precipitation Evapotranspiration Index (SPEI). The data needed for SPEI calculation are obtained based on the ensemble of multiple global climate model (GCM) outputs. Population exposure to drought for the future is assessed by combining drought frequency under two emission scenarios (RCP4.5 and RCP8.5) with three downscaled population scenarios (SSP1, SSP2, and SSP3). Moreover, the main contribution (and their interactions) of GCM, RCP, and SSP to the sources of uncertainty on population exposure projections is explored through multilevel factorial analysis. Results indicate that the temperature and precipitation would continually increase for the future, and the increase in drought frequency is more substantial during the 2080s than in the 2050s. Meanwhile, population exposure to drought accounts for 21.60% of the total population in 1976–2005 over the PRB area. During the 2050s, it would decrease to 11.98–12.28% under RCP4.5 and 14.15–14.40% under RCP8.5, respectively. By the 2080s, population exposure would slightly reduce under RCP4.5 and increase to 28.86–29.44% under RCP8.5. GCM is the primary uncertainty source of drought exposure in the 2050s, with contribution rates of 72.41%, 57.47%, 51.10%, and 78.71% to the four responses. In comparison, by the 2080s, RCP is the primary contributing factor, with contribution rates of 53.91%, 44.92%, 64.20%, and 48.00%, respectively. Plain Language Summary: Climate change has an extensive impact on future drought conditions in the Pearl River Basin. Therefore, the projection of population exposure to drought is essential for making informed decisions toward climate change mitigation and adaptation. This study aims at exploring the changes in population exposure to droughts (e.g., moderate, severe, and extreme) under multiple emission‐population scenarios and quantifying the main contribution (and their interactions) of global climate model (GCM), RCP, and SSP to the sources of uncertainty on population exposure. The temperature and precipitation would continually increase for the future, and the increase in drought frequency is more substantial during the 2080s than in the 2050s. As a result, future population exposure to moderate, severe, and extreme drought would decrease in the 2050s, under two RCPs. While during the 2080s, there is a slight decrease under RCP4.5 and an apparent increase under RCP8.5. GCM is the primary uncertainty source of drought exposure in the 2050s to the four responses. In comparison, by the 2080s, RCP is the major contributing factor. Key Points: Population exposure to drought for the future is projected through the combination of multiple emission‐population scenariosPopulation exposure to drought would increase apparently in the 2080s under RCP8.5Global climate model (GCM) and RCP are the primary uncertainty sources of drought exposure in the 2050s and 2080s, respectively [ABSTRACT FROM AUTHOR]

This work theoretically proposes a novel surface plasmon polaritons nanolaser enhanced by 2D black phosphorus (BP) nanosheets, which can greatly enhance the local electric field and reduce the normalized mode area. The plasmonic nanolaser is created by integrating few‐layered BP nanosheets into a hybrid waveguide structure consisting of a cadmium sulfide (CdS) semiconductor nanowire, a low‐index dielectric MgF2 buffer film, and a silver substrate. Both the electric field distribution and mode parameters originating from the proposed hybrid structure are systematically studied. The simulation results show that, under the optimal conditions with r = 95 nm, hgap = 2 nm, and d = 1 nm, three key mode parameters (effective mode area, gain threshold, and propagation distance) can be determined to be 0.008 λ2, 0.5997 µm−1, and 3309 nm, respectively. Moreover, the figure of merit of the proposed nanolaser is enhanced by almost 2.3 times compared with the model without BP nanosheets. It can be expected that the proposed plasmonic nanolaser shows great potential in exploring ultrahigh density photonic integrated circuit. [ABSTRACT FROM AUTHOR]

Frequent drought events under climate change are endangering food security and sustainable agricultural development. Quantitative assessment of crop yield anomalies under drought conditions is essential for effective water resources management and adaptative drought risk mitigation strategies. In this study, a copula‐based bivariate probabilistic framework model is developed to assess the impacts of drought events on crop yield, where the correlation of crop yield anomalies and standardized precipitation evapotranspiration index (SPEI) at multi‐month lags are quantified. This model has advantages in quantifying the impacts of drought scales on crop yield through the joint probability of the corresponding series. Then, the model is applied to Xinjiang Province in Northwestern China, an arid region with extensive agricultural activities. SPEI and yield anomalies of wheat, maize and cotton during 1984–2015 are firstly identified, and then copula‐based framework is constructed to quantify probabilistic crop yield losses caused by drought events. Finally, crop water amounts and irrigation requirements under different drought severity conditions are compared and analysed. Our findings are: (a) wheat and maize yield anomalies are vulnerable to long drought time‐scales, with exceedance probabilities of required yield anomalies returning to normal are 19.3% for wheat and 21.1% for maize, while cotton is susceptible to short drought time‐scales, with exceedance probability of 42.3% for drought recovery; (b) response of wheat crop yield anomalies to the SPEI at 1‐, 3‐, 6‐ and 12‐month scales is the most sensitive, followed by maize, and cotton is the least; (c) under extreme drought conditions, the probability of cotton yield reduction is lower than that of wheat and maize. Results may enhance our understanding of the impacts of drought scales on crops during the growing season, thus providing general guidance for rational irrigation management of crops and incentives for irrigation to mitigate drought risk, ultimately promoting sustainable agricultural development. [ABSTRACT FROM AUTHOR]

As one of the most pressing issues in the world, climate change has already caused evident impacts on natural and human systems (e.g., hydrological cycle, eco‐environment and socio‐economy) in recent decades. In this study, an integrated multi‐GCMs Bayesian‐neural‐network hydrological analysis (MBHA) method is developed for quantifying climate change impacts on runoff. MBHA incorporates multiple global climate models (multi‐GCMs), hydrological model (HBV‐light), and Bayesian neural network (BNN) within a general framework. MBHA can provide the reliable prediction for runoff as well as reflect the impact of climate change on data scarcity catchments. MBHA is applied to the Amu Darya River basin in Central Asia. Climate data are derived from multiple GCMs (i.e., GFDL‐ESM2G, HadGEM2‐AO and NorESM1‐M) under RCP4.5 and RCP8.5. Several findings can be summarized: (1) during 2021–2100, both precipitation and temperature would increase, with more precipitation falling as rain instead of snow; (2) by 2100, glacier areas are predicted to reduce by 62.3% (RCP4.5) and 71.9% (RCP8.5); (3) under RCP8.5, monthly runoff would increase by 11.2% in 2021–2060 and reduce by 5.0% in 2061–2100; this is because the glaciers would rapidly disappear with the rising temperature after 2060. The findings suggest that the shrinked glacier and the reduced runoff threaten the water availability especially in summer seasons as well as affect the agricultural irrigation in the downstream of the Amu Darya River. [ABSTRACT FROM AUTHOR]

Summary: Fruit colour affects consumer preference and is an important trait for breeding in strawberry. Previously, we isolated the Reduced Anthocyanins in Petioles (RAP) gene encoding a glutathione S‐transferase (GST) that binds anthocyanins to facilitate their transport from cytosol to vacuole in the diploid strawberry Fragaria vesca. The parent of rap was the F. vesca variety 'Yellow Wonder' that develops white fruit due to a natural mutation in the FveMYB10 gene. Here, we investigated the application potential of RAP in modulating fruit colours by overexpression of RAP in F. vesca and knockout of RAP in the cultivated strawberry Fragaria × ananassa. Unexpectedly, the RAP overexpression in Yellow Wonder background caused formation of red fruit. In addition, the red coloration occurs precociously at floral stage 10 and continues in the receptacle during early fruit development. Transcriptome analysis revealed that the anthocyanin biosynthesis genes were not up‐regulated in RAP‐ox; rap myb10 flowers at anthesis and largely inhibited at the turning stage in fruit, suggesting a coloration mechanism independent of FveMYB10. Moreover, we used CRISPR/Cas9 to knockout RAP in cultivated strawberry which is octoploid. Six copies of RAP were simultaneously knocked out in the T0 generation leading to the green stem and white‐fruited phenotype. Several T1 progeny have segregated away the CRISPR/Cas9 transgene but maintain the green stem trait. Our results indicate that enhancing the anthocyanin transport could redirect the metabolic flux from proanthocyanidin to anthocyanin production at early developmental stages of fruit and that RAP is one promising candidate gene in fruit colour breeding of strawberry. [ABSTRACT FROM AUTHOR]

Following its commitment to Paris Agreement in 2015, China has started to explore potential renewable energy solutions with low carbon emissions to mitigate global warming. Though wind energy is one of the most cost‐effective solutions and has been favored for climate policy development around the world, its high sensitivity to climate change raises some critical issues for the long‐term effectiveness in providing sustainable energy supply. Particularly, how wind speed and its energy potential in China will change in the context of global warming is still not well understood. In this paper, we simulate the near‐surface wind speed over China using the PRECIS regional climate modeling system under different RCP emission scenarios for assessing the possible changes in wind speed and wind energy availability over China throughout the 21st century. Overall, the PRECIS model can reasonably reproduce the mesoscale climatological near‐surface wind speed and directions as documented in reanalysis data across most regions of China, while some local discrepancies are reported in the southwestern regions. In the future, the annual mean wind speed would be decreasing in most regions of China, except for a slightly increase in the southeast. The expected changes in wind speed are characterized with different amplitudes and rates under different RCP emission scenarios. The changes in the spatial distribution of wind speed seem to be sensitive for RCP climate emission scenarios, especially in the late 21st century. The spatiotemporal changes in wind energy potential exhibit a similar behavior to those in near‐surface wind speed, but the magnitudes of these changes are larger. In general, the wind power density is expected to increase by over 5% in winter in the major wind fields in China (ie, Northwest, Northcentral and Northeast), while significant decreases (by about 6% on average) are projected for other seasons (ie, spring, summer and autumn). By contrast, the wind energy potential in the northeast would increase over most months in the year, especially in winter and summer. The results of this research are of great importance for understanding where and to what extent the wind energy can be utilized to contribute renewable energy system development in China in support of its long‐term climate change mitigation commitment. [ABSTRACT FROM AUTHOR]

Summary: MicroRNAs (miRNAs) are a kind of short noncoding RNA (20–24 nt), playing versatile roles in plant growth and development. Strawberry generates leaves and flowers with unique features. However, few miRNAs have been functionally characterised in strawberry, especially for their developmental regulation.Here, we identified one ethyl methanesulfonate (EMS) mutant, deeply serrated (des), in the woodland strawberry Fragaria vesca that has wrinkled leaves with deeper serrations, serrated petals and deformed carpels. The causative mutation occurs in the 19th nucleotide of the FvemiR164a mature sequence. Overexpressing FveMIR164A rescued the phenotypes of des/fvemir164a except the petal serrations.Furthermore, we identified two allelic mutants of FveCUC2a, one target of FvemiR164a, which developed leaves with smooth margins and fused leaflets. Phenotypes of the double mutant fvemir164a fvecuc2a indicated that the two genes act linearly in leaf and carpel development, but synergistically in the development of other floral organs and inflorescence architecture.This work demonstrates the conserved and novel roles of the miR164‐CUC2 module in leaf and flower development in different plant species, and reveals that the 19th nucleotide of FvemiR164a is important for its processing. [ABSTRACT FROM AUTHOR]

Sorafenib is an inhibitor of a variety of tyrosine kinase receptors used to treat various cancers including hepatocellular, renal cell and thyroid carcinoma. It has been shown to change various targets associated with osteosarcoma, but the detailed mechanism remains unclear. In order to identify key genes, enriched pathways and important modules during the exposure of human osteosarcoma cells to sorafenib, data for gene expression profiles ( GSE53155) were downloaded from the GEO database. In total, 61 differentially expressed genes (DEGs) were identified by the R bioconductor packages. Functional and enrichment analyses of DEGs were performed using the DAVID database. These revealed that DEGs were enriched in biological processes, molecular function and KEGG pathway of inflammatory immune response and angiogenesis. A protein–protein interaction network was constructed by string and visualized in cytoscape, and eight genes were selected as hubs: IL8, CXCL2, PTGS2, FOS, CXCL1, C3, EHMT2 and PGF. Subsequently, only one cluster was identified by mcode, which consisted of six nodes (CXCL1, CXCL2, PTGS2, FOS, C3 and PGF) and nine edges. PGF was the seed gene in this cluster. In conclusion, the results of this data mining and integration should help in revealing new mechanisms and targets of sorafenib in inhibiting osteosarcoma. [ABSTRACT FROM AUTHOR]

An increasing number of phylogenetic studies have reported discordances among nuclear and mitochondrial markers. These discrepancies are highly relevant to widely used biodiversity assessment approaches, such as DNA barcoding, that rely almost exclusively on mitochondrial markers. Although the theoretical causes of mito-nuclear discordances are well understood, it is often extremely challenging to determine the principal underlying factor in a given study system. In this study, we uncovered significant mito-nuclear discordances in a pair of sibling caddisfly species. Application of genome sequencing, dd RAD and DNA barcoding revealed ongoing hybridization, as well as historical hybridization in Pleistocene refugia, leading us to identify introgression as the ultimate cause of the observed discordance pattern. Our novel genomic data, the discovery of a European-wide hybrid zone and the availability of established techniques for laboratory breeding make this species pair an ideal model system for studying species boundaries with ongoing gene flow. [ABSTRACT FROM AUTHOR]

Alternative splicing ( AS) is a key post-transcriptional regulatory mechanism, yet little information is known about its roles in fruit crops. Here, AS was globally analyzed in the wild strawberry Fragaria vesca genome with RNA-seq data derived from different stages of fruit development. The AS landscape was characterized and compared between the single-molecule, real-time ( SMRT) and Illumina RNA-seq platform. While SMRT has a lower sequencing depth, it identifies more genes undergoing AS (57.67% of detected multiexon genes) when it is compared with Illumina (33.48%), illustrating the efficacy of SMRT in AS identification. We investigated different modes of AS in the context of fruit development; the percentage of intron retention ( IR) is markedly reduced whereas that of alternative acceptor sites ( AA) is significantly increased post-fertilization when compared with pre-fertilization. When all the identified transcripts were combined, a total of 66.43% detected multiexon genes in strawberry undergo AS, some of which lead to a gain or loss of conserved domains in the gene products. The work demonstrates that SMRT sequencing is highly powerful in AS discovery and provides a rich data resource for later functional studies of different isoforms. Further, shifting AS modes may contribute to rapid changes of gene expression during fruit set. [ABSTRACT FROM AUTHOR]

Due to climate change, rising temperature around the world will have a great potential to influence the global hydrologic cycle, thus leading to substantial changes in the spatial and temporal patterns of precipitation. In this study, the effects of global warming on the regional hydrologic cycle, particularly on the spatiotemporal patterns of precipitation, over China are investigated through a high-resolution regional climate ensemble. In detail, the PRECIS regional climate modeling system is employed to simulate the regional climate over China from 1950 to 2099 with a fine resolution of 25 km, driven by the boundary conditions from a four-member HadCM3-based perturbed-physics ensemble (i.e., HadCM3Q0, Q1, Q7, and Q13) and the ECHAM5 model. Historical simulations of the PRECIS ensemble are first compared to the observations to validate its performance in capturing both the spatial and temporal patterns of precipitation. The comparisons show that the PRECIS ensemble is likely to overestimate precipitation in the south and exhibits slight dry biases in the northwest and southeast coasts of China. The projections from the PRECIS ensemble for future periods (i.e., 2020s, 2050s, and 2080s) are then analyzed to help understand how the regional characteristics of precipitation will be affected in the context of global warming. It is shown that the annual mean precipitation over China is likely to increase throughout the 21st century (i.e., by 0.078 mm/d in 2020s, 0.218 mm/d in 2050s, and 0.360 mm/d in 2080s). This may suggest that the rising temperature due to climate change will intensify the regional hydrologic cycles in China. However, apparent spatial and temporal variations are also reported in the projected precipitations from the PRECIS ensemble. For example, bigger changes in precipitation are usually observed in summer; projected precipitation changes in the southeast are apparently higher than other regions. In addition, the results show that the fluctuation range of the ensemble simulations will increase with time periods from 2020s to 2080s, indicating that the longer the projecting periods, the more uncertain the projections will be. [ABSTRACT FROM AUTHOR]

Objectives: miRNAs play crucial roles in human tumourigenesis. This study was performed to measure expression and function of miR-762 in breast cancer. Materials and methods: Expression of miR-762 in breast tissues and cell lines (SK-BR-3, DA-MB-435s, MCF-7 and MDA-MB-231, HBL-100) was measured by using real-time RT-PCR. We restored expression of miR-762 in MCF-7 cells to measure its functional roles. Luciferase assays were performed to reveal the target gene of miR-762. Results: Expression of miR-762 was high in both breast cancer cell lines and specimens, and its overexpression increased breast cancer cell proliferation and invasion. Interferon regulatory factor 7 (IRF7) is a direct target of miR-762 and overexpression of miR-762 reduced expression of IRF7. Moreover, IRF7 was repressed, its levels inversely correlated to miR-762 expression. IRF7 rescued miR-762-induced cell invasion and proliferation. Conclusions: These results demonstrate that miR-762 tumour effect was achieved by targeting IRF7 in human breast cancer specimens. [ABSTRACT FROM AUTHOR]

Aims Advanced hepatocellular carcinoma ( HCC) with vascular invasion or extrahepatic metastasis has been considered a contraindication for transarterial chemoembolization ( TACE) treatment according to Barcelona Clinic Liver Cancer ( BCLC) staging classification. However, real clinical practice varies among different countries. In recent years another opinion has been developing that considers that TACE can be safely performed in advanced HCC patients. Methods All studies on the efficacy of TACE for patients with advanced HCC were identified via the Pub Med database. The primary items were TACE and HCC. Results We identified 15 studies in the treatment of TACE in advanced HCC patients. Most adverse events reported were treated successfully and in these studies there were no procedure-related deaths within 4 weeks of the TACE treatment. Four controlled studies reported that TACE increased survival rate and prolonged overall survival compared with conservative management. The most frequent prognostic factors were liver function and the degree of portal vein tumor thrombosis. Conclusion TACE can be safely performed in advanced HCC patients with vascular invasion or extrahepatic spread and may improve their overall survival. Patients with portal vein branch invasion and well-preserved liver function seemed to derive optimal benefit from treatment with TACE. Further studies are needed to provide strong evidence of the efficacy of TACE for advanced HCC patients to update the BCLC staging system. [ABSTRACT FROM AUTHOR]

With 2 figures and 1 table Abstract Brown spot (BS) caused by Alternaria alternata is one of the most destructive foliar diseases affecting tobacco ( Nicotiana tabacum L.) production and quality in China. Breeding of BS-resistant cultivars is difficult because the resistance has proved to be quantitatively inherited. To facilitate marker-assisted selection, we carried out a study of mapping quantitative trait loci (QTLs) for BS resistance. We developed an F2 population consisting of 213 individuals from a cross between a BS-susceptible cultivar 'Changbohuang' (CBH) and a BS-resistant cultivar 'Jinyehuang' (JYH) and constructed a genetic map consisting of 196 simple sequence repeat (SSR) markers based on this population. Using disease index (DI) as the indicator of BS resistance, we detected three QTLs located between SSR markers TM20534 and TM10737, TM10589 and TM10216, and TM10443 and PT60669, respectively. The resistant alleles of the three QTLs were all from the resistant parent JYH. The three QTLs together could explain ∼86% of the DI difference between the two parents in total, with ∼61% explained by their additive effects. Therefore, the three QTLs will be useful for BS-resistance breeding. [ABSTRACT FROM AUTHOR]

With 4 figures and 3 tables Abstract Endogenous non-coding small RNAs usually consist of 20-24 nucleotides, are found ubiquitously throughout the genome and play important regulatory roles in most eucaryotes. In this study, a new kind of PCR-based marker approach using multi-mapped small RNA sequences, called inter small R NA polymorphism (iSNAP), was developed. iSNAP primers were designed based on multi-mapped small RNA and its two end conserved flanking sequences. To demonstrate the marker system, 10 rice and 30 tobacco iSNAP primers were developed and used to construct a rice genetic map and to fingerprint eight tobacco varieties. The results indicate that this technique can be effectively applied in the mapping of rice and fingerprinting of species (such as tobacco) with extremely low genetic diversity and thus provides a new option of molecular marker techniques. [ABSTRACT FROM AUTHOR]

Retinoblastoma (RB) is the most common malignant tumor of the retina in human children. Although it has been hypothesized for a long time that RB derives from multipotent retinal stem cells (RSCs) or retinoblasts, the direct evidence that the presence of tumorigenic RSCs in RB tumors is still lacking. Some studies indicate that malignant tumors contain tumor stem cells similar to their normal tissue stem cell counterparts. With in vitro culture and differentiation method we demonstrate that tumorigenic retinal stem-like cells (RSLCs) indeed exist in RB lesions and that RB tumor-derived cultures encompass undifferentiated cells capable of extensive proliferation as clonal nonadherent neurospheres and can differentiate into different retinal cells in vitro. Interestingly, cultured cells expressed retinal development related genes including nestin, CD133, pax6, chx10 and Rx, and overexpressed Bmi-1, a gene required for self-renewal and proliferation of stem cells. Significantly, when these cultured cells were intraocularly transplanted into SCID mice, they gave rise to new tumors with histomorphological features and immunophenotypes similar to their parental primary RBs. The results show that RBs contain tumorigenic RSLCs that contribute to tumorigenesis. This study provides a new insight to investigate the histogenesis of RBs and establishes a model for other RB research. © 2007 Wiley-Liss, Inc. [ABSTRACT FROM AUTHOR]

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In this study, a dual‐interval two‐stage stochastic programming (DTSP) approach is developed for planning water resources through a market‐trading‐oriented mechanism under uncertainty. The DTSP method is used for policy analysis of water trading in the Kaidu‐kongque River Basin with the efficient and sustainable manners to relieve the pressures of economic development and population growth in northwestern China. The obtained results reveals that a market‐trading‐oriented mechanism under the adjustment/regulation by water managers would be a sustainable/effective manner to allocate water resources against the market failure. Meanwhile, the trade‐off between governmental regulation and market behavior has generated a more efficient trading mode with overall consideration of factors such as food safety, drinking safety, environmental protection, and regional development in a watershed system, which could bring about a number of beneficial impacts on regional water resources development. Moreover, the DTSP method is also appropriate for discriminating varied cases associated with various levels of economic influences since the penalties could be exercised with the recourses actions against any infeasibility. A dual‐interval two‐stage stochastic programming (DTSP) approach is developed for planning water resources management based on a market‐trading‐oriented mechanism under uncertainty. Its application to northwestern China can generate various results of policy analyses on the adjustment/regulation of water trading, which can help policymakers to obtain an optimal and sustainable water allocation plan in an arid region. [ABSTRACT FROM AUTHOR]

The article presents a case study of an 18-year-old boy who has experienced fatigue and developed jaundice of unknown cause five years prior to admission. The patient underwent magnetic resonance imaging of the brain which led to the diagnosis of Wilson disease. The article discusses the prevalence of Wilson disease in China, its diagnosis, and how it can lead to blindness.

Bi2Fe4O9 nanocrystals are precipitated from a HNO3 solution of Bi(NO3)3 and Fe(NO3)3 by addition of aqueous NaOH solution up to a pH value of 12 at room temperature. [ABSTRACT FROM AUTHOR]