Integrative analysis of the metabolome and transcriptome reveals the potential mechanism of fruit flavor formation in wild hawthorn(Crataegus chungtienensis)

Hawthorns are important medicinal and edible plants with a long history of health protection in China.Besides cultivated hawthorn,other wild hawthorns may also have excellent medicinal and edible value,such as Crataegus chungtienensis,an endemic species distributed in the Southwest of China.In this study,by integrating the flavor-related metabolome and transcriptome data of the ripening fruit of C.chungtienensis,we have developed an understanding of the formation of hawthorn fruit quality.The results show that a total of 849 metabolites were detected in the young and mature fruit of C.chungtienensis,of which flavonoids were the most detected metabolites.Among the differentially accumulated metabolites,stachyose,maltotetraose and cis-aconitic acid were significantly increased during fruit ripening,and these may be important metabolites affecting fruit flavor change.Moreover,several flavonoids and terpenoids were reduced after fruit ripening compared with young fruit.Therefore,using the unripe fruit of C.chungtienensis may allow us to obtain more medicinal active ingredients such as flavonoids and terpenoids.Furthermore,we screened out some differentially expressed genes(DEGs)related to fruit quality formation,which had important relationships with differentially accumulated sugars,acids,flavonoids and terpenoids.Our study provides new insights into flavor formation in wild hawthorn during fruit development and ripening,and at the same time this study lays the foundation for the improvement of hawthorn fruit flavor.

Predicting Carpark Prices Indices in Hong Kong Using AutoML

The aims of this study were threefold:1)study the research gap in carpark and price index via big data and natural language processing,2)examine the research gap of carpark indices,and 3)construct carpark price indices via repeat sales methods and predict carpark indices via the AutoML.By researching the keyword“carpark”in Google Scholar,the largest electronic academic database that coversWeb of Science and Scopus indexed articles,this study obtained 999 articles and book chapters from 1910 to 2019.It confirmed that most carpark research threw light on multi-storey carparks,management and ventilation systems,and reinforced concrete carparks.The most common research method was case studies.Regarding price index research,many previous studies focused on consumer,stock,press and futures,with many keywords being related to finance and economics.These indicated that there is no research predicting carpark price indices based on an AutoML approach.This study constructed repeat sales indices for 18 districts in Hong Kong by using 34,562 carpark transaction records from December 2009 to June 2019.Wanchai’s carpark price was about four times that of Yuen Long’s carpark price,indicating the considerable carpark price differences inHong Kong.This research evidenced the features that affected the carpark price indices models most:gold price ranked the first in all 19 models;oil price or Link stock price ranked second depending on the district,and carpark affordability ranked third.

Generating high-resolution climate maps from sparse and irregular observations using a novel hybrid RBF network

Sparse and irregular climate observations in many developing countries are not enough to satisfy the need of assessing climate change risks and planning suitable mitigation strategies.The wideused statistical downscaling model(SDSM)software tools use multi-linear regression to extract linear relations between largescale and local climate variables and then produce high-resolution climate maps from sparse climate observations.The latest machine learning techniques(e.g.SRCNN,SRGAN)can extract nonlinear links,but they are only suitable for downscaling low-resolution grid data and cannot utilize the link to other climate variables to improve the downscaling performance.In this study,we proposed a novel hybrid RBF(Radial Basis Function)network by embedding several RBF networks into new RBF networks.Our model can well incorporate climate and topographical variables with different resolutions and extract their nonlinear relations for spatial downscaling.To test the performance of our model,we generated high-resolution precipitation,air temperature and humidity maps from 34 meteorological stations in Bangladesh.In terms of three statistical indicators,the accuracy of high-resolution climate maps generated by our hybrid RBF network clearly outperformed those using a multi-linear regression(MLR),Kriging interpolation or a pure RBF network.

Computational Biology Approaches to Plant Metabolism and Photosynthesis:Applications for Corals in Times of Climate Change and Environmental Stress

Knowledge of factors that are important in reef resilience helps us to understand how reef ecosystems react following major anthropogenic and environmental disturbances. The symbiotic relationship between the photosynthetic zooxanthellae algal cells and corals is that the zooxanthellae provide the coral with carbon, while the coral provides protection and access to enough light for the zooxanthellae to photosynthesise. This article reviews some recent advances in computational biology relevant to photosynthetic organisms, including Beyesian approaches to kinetics, computational methods for flux balances in metabolic processes, and determination of clades of zooxanthallae. Application of these systems will be important in the conservation of coral reefs in times of climate change and environmental stress.