An Efficient Synthesis of Enantiomerically Pure γ-Aminobutyric Acid (GABA) Derivatives

Chiral γ-aminobutyric acid (GABA) derivatives are the normal inhibitory neurotransmitters in the mammalian central nervous system. In this paper, enantiopure GABA derivatives 6 were synthesized via reduction/cyclization/hydrolysis cascade reactions from the highly enantioselective β-aryl-γ- ni-troalkanes Michael adducts 4, which was obtained from asymmetric Michael addition of S, S’-diphenyldithiomalonate 2 to trans-β-nitroolefins 1, using novel chiral cinchona alkaloid-derived thioureas 3 as the organocatalysts. This synthesis represents an efficient, highly selective and environmental benign methodology for GABA derivatives.

Adipo8, a high-affinity DNA aptamer, can differentiate among adipocytes and inhibit intracellular lipid accumulation in vitro

Obesity is primarily caused by the excessive accumulation of white adipose tissues(WAT). We previously obtained an adipocyte-specific aptamer termed Adipo8 in vitro. In this present study, this adipocyte-specific aptamer Adipo8 was first chemically modified by introduction of phosphorothioate linkages(PS-linkages) and then conjugated to polyethylene glycol(PEG), we tested whether this modified aptamer could distinguish mature white adipocytes from 3T3-L1 preadipocytes or brown adipocytes. To verify the binding affinity of this aptamer to mature white adipocytes in vivo as well as in vitro, we tested whether modified Adipo8 could specifically bind to the WAT of Diet-Induced Obesity(DIO) C57BL/6 mice. Finally, we examined the effect of Adipo8 on the adipogenic differentiation of mature white adipocytes. Based on our results, PS-modified aptamer demonstrated its high binding affinity and specificity, and was able to distinguish white adipocytes from 3T3-L1 preadipocytes or brown adipocytes in vitro. PS-modified Adipo8 also demonstrated more biostability and prolonged binding time in biological fluids. Additionally, Adipo8 could inhibit adipogenic differentiation of adipose tissue, possibly by inhibiting the expression of PPAR-γ in adipose tissue. This modified aptamer holds great promise as a stable molecular recognition tool for targeted delivery to adipocytes and has potential in the treatment of obesity.

Combining gradual and abrupt analysis to detect variation of vegetation greenness on the loess areas of China

The annual peak growth and trend shift of vegetation are critical in characterizing the carbon sequestration capacity of ecosystems.As the well-known area with the fastest vegetation growth in the world,the Loess Plateau(LP)lands find an enhanced greening trend in the annual and growing-season.However,the spatiotemporal dynamics of vegetation peak growth and breakpoints characteristics on time series still needs to be explored.Here,we performed tendency analysis to characterize recent variations in annual peak vegetation growth through a satellite-derived vegetation index(NDVI_(max),Maximum Normalized Difference Vegetation Index)and then applied breakpoint analysis to capture abrupt points on the time series.The results demonstrated that the vegetation peak trend had been significantly increasing,with a growth rate at 0.68×10^(-2)·a^(-1) during 2001-2018,and most pixels(70.81%)have a positive linear greening trend over the entire LP.In addition,about 83%of the breakpoint type on the monthly NDVI time series is a monotonic increase at the pixel level,and most pixels(57%)have detected breakpoints after 2010.Our results also showed that the growth rate accelerates in the northwest and decelerates in the southeast after the breakpoint.This study indicates that combining abrupt analysis with gradual analysis can describe vegetation dynamics more effectively and comprehensively.The findings highlighted the importance of breakpoint analysis for monitor timing and shift using time series satellite data at a regional scale,which may help stakeholders to make reasonable and effective ecosystem management policies.

Storage,pattern and driving factors of soil organic carbon in the desert rangelands of northern Xinjiang,north-west China

Soil organic carbon(SOC)is a critical variable used to determine the carbon balance.However,large uncertainties arise when predicting the SOC stock in soil profiles in Chinese grasslands,especially on desert rangelands.Recent studies have shown that desert ecosystems may be potential carbon sinks under global climate change.Because of the high spatial heterogeneity,time-consuming sampling methods,and difficult acquisition process,the relationships the SOC storage and distribution have with driving factors in desert rangelands remain poorly understood.Here,we investigated and developed an SOC database from 3162 soil samples(collected at depths of 0−10 cm and 10−20 cm)across 527 sites,as well as the climate conditions,vegetation types,and edaphic factors associated with the sampling sites in the desert rangelands of northern Xinjiang,north-west China.This study aims to determine the SOC magnitude and drivers in desert rangelands.Our findings demonstrate that the SOC and SOC density(SOCD)were 0.05−37.13 g·kg^(-1)and 19.23−9740.62 g·m^(-2),respectively,with average values of 6.81±5.31 g·kg^(-1)and 1670.38±1202.52 g·m^(-2),respectively.The spatial distributions of SOC and SOCD all showed gradually decreasing trends from south-west to north-east.High-SOC areas were mainly distributed in the piedmont lowlands of the Ili valley,while low-SOC regions were mainly concentrated in the north-west area of Altay.The redundancy analysis results revealed that all environmental factors accounted for approximately 37.6%of the spatial variability in SOC;climate factors,vegetation factors,and soil properties explained 15.0%,1.7%,and 12.3%,respectively.The structural equation model(SEM)further indicated that evapotranspiration,average annual precipitation,and the SWC were the dominant factors affecting SOC accumulation,mainly through direct effects,although indirect effects were also delivered by the vegetation factors.Taken together,the results obtained herein updated the SOC data pool available for desert rangelands and clarified the main driving factors of SOC variations.This study provided supporting data for the sustainable use and management of desert rangelands and the global ecosystem carbon budget.