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The efficient copper-mediated oxidative C–H alkynylation of benzhydrazides was accomplished with terminal alkynes. Thus, a heteroaromatic removable N-2-pyridylhydrazide allowed for domino C–H/N–H functionalization. The approach featured remarkable functional group compatibility and ample substrate scope. Thereby, highly functionalized aromatic and heteroaromatic isoindolin-1-ones were accessed with high efficacy with rate-limiting C–H cleavage.

The Qinghai–Tibet Plateau (QTP) is among one of the most sensitive regions to global environmental change worldwide. Although climate change and engineering construction on the QTP have jointly modified the regional vegetation activity, little is known about how this affects the vegetation variation. Using Moderate Resolution Imaging Spectroradiometer (MODIS) Enhanced Vegetation Index (EVI) data from 2000–2021, this study investigated the spatiotemporal variation of vegetation activity and the compound effects of climate change and reconstruction along the Tibetan section of the G318 national highway (TG318) through a novel contribution quantification model and partial correlation analysis, as well as through a structural equation model (SEM). The results showed that the mean growing-season EVI increased significantly at a rate of about 0.0020/year in the western side of the TG318 after reconstruction but fluctuated in the east. Reconstruction generally had a significant effect on the mean growing-season EVI, with contributions of 7.67%, 19.12%, 18.24%, and −4.15% in different sections of the TG318, whereas climate change contributed from −10.14% to 8.84% of the total variation. The mean growing-season EVI negatively correlated with snow cover and minimum temperature in humid and sub-humid regions, whereas it was positively related with vapor pressure in semi-arid regions. Moreover, there existed an obvious lag effect of climate change on the mean growing-season EVI, with lag time generally decreasing from west to east and apparent heterogeneity among different months and regions. These findings will help better understand the environmental impacts along the engineering corridors and provide a scientific basis for ecological conservation in the QTP regions.

Organelles play core roles in living beings, especially in internal cellular actions, but the hidden information inside the cell is difficult to extract in a label-free manner. In recent years, terahertz (THz) imaging has attracted much attention because of its penetration depth in nonpolar and non-metallic materials and label-free, non-invasive and non-ionizing ability to obtain the interior information of bio-samples. However, the low spatial resolution of traditional far-field THz imaging systems and the weak dielectric contrast of biological samples hinder the application of this technology in the biological field. In this paper, we used an advanced THz scattering near-field imaging method for detecting chloroplasts on gold substrate with nano-flatness combined with an image processing method to remove the background noise and successfully obtained the subcellular-grade internal reticular structure from an Arabidopsis chloroplast THz image. In contrast, little inner information could be observed in the tea chloroplast in similar THz images. Further, transmission electron microscopy (TEM) and mass spectroscopy (MS) were also used to detect structural and chemical differences inside the chloroplasts of Arabidopsis and tea plants. The preliminary results suggested that the interspecific different THz information is related to the internal spatial structures of chloroplasts and metabolite differences among species. Therefore, this method could open a new way to study the structure of individual organelles.

Abstract Background RNA cargo in exosomes, especially microRNAs (miRNAs), play an important role in the chemotherapy drug resistance of human cancers. However, the role and mechanism of exosomal miR-107 on multidrug resistance of gastric cancer cells was still not clear. In this study, we sought to explore whether exosomal miR-107 could reverse the resistance of gastric cancer cells to the chemotherapy drugs. Methods We extracted exosomes from sensitive (SGC-7901, MGC-803) and resistant (SGC-7901/5-FU) gastric cancer cells by ultracentrifugation and the isolated exosomes were identified using transmission electron microscopy (TEM) and dynamic light scattering analysis (DLS). The expression of miR-107 and high mobility group A2 (HMGA2) were detected by real-time quantitative PCR (RT-qPCR). MTT assay was used to investigate the effect of exosomes on gastric cancer cells growth in vitro. The uptake of exosomes by recipient cells were observed using a fluorescence microscope. The predicted target relationship between miR-107 and HMGA2 was verified by gauss-luciferase reporter assay. The expression of HMGA2, p-mTOR/mTOR, P-gp and other exosomal indicated marker proteins was detected by western blot. Results Our results indicated that the isolated exosomes were typically cup-like lipid bilayer membranes structure. SGC-7901/5-FU cells were cross-resistant to chemotherapy drug cisplatin (CDDP), and the sensitive cells-secreted exosomes drastically reversed the resistance of the resistant GC cells to the chemotherapeutic drugs, which was verified by exosomal inhibitor GW4896. Mechanistically, the reversal effect was mainly mediated by exosome-secreted miR-107 through downregulating the expression of target molecular HMGA2 and inhibiting HMGA2/mTOR/P-gp pathway, which were supported by results from luciferase reporter assay and rescue assay. Conclusions These findings demonstrated that exosome-transmitted miR-107 significantly enhanced the sensitivity of resistant gastric cancer cells to chemotherapeutic agents by mediating the HMGA2/mTOR/P-gp axis and exosomal miR-107 may be a novel target in gastric cancers treatment.

The percentage precipitation anomaly was used to index the effect of drought on winter wheat grown in Henan Province for the years 2011–2020. Of interest was the effect of drought on winter wheat yield and the accurate assessment of the damage done to winter wheat by drought events in order to improve the risk management of winter wheat in the context of drought hazards. The spatial and temporal variability of winter wheat drought risk in Henan Province was determined by analysis of climate data, winter wheat yield, cultivated area, and socio-economic data across three dimensions: exposure or susceptibility to drought, economic–environmental sensitivity to drought, and capacity to resist drought. A drought vulnerability assessment model, based on the entropy value method and a comprehensive fuzzy evaluation, was developed to assess the drought vulnerability of winter wheat in Henan Province compared with the percentage precipitation anomaly model. (1) There were significant spatial differences in the frequency of the five drought categories devised. (2) Areas in which there was a high frequency of mild drought events were mainly in northern and western Henan and southwestern Henan, with the frequency ranging from 17% to 29%. (3) Areas in which there was a high frequency of moderate drought events were mainly in northwestern, central, and southeastern Henan. (4) Areas in which there was a high frequency of severe and extreme drought were mainly in Anyang in northern Henan, Zhengzhou in central Henan, and Xinyang and surrounding areas in southern Henan, with the frequency ranging from 7% to 9.70%. (5) Winter wheat drought vulnerability shows an overall annually increasing trend. The susceptibility dimension had the greatest influence of the three dimensions, followed by economic–environmental sensitivity and then drought resistance, which had the least impact. The model created in this study shows the influence of drought on winter wheat production more intuitively than a conventional fuzzy synthesis, and the results can inform decision-making in winter wheat drought risk assessment and management.

High-resolution crop type mapping is of importance for site-specific agricultural management and food security in smallholder farming regions, but is challenging due to limited data availability and the need for image-based algorithms. In this paper, we developed an efficient object- and pixel-based mapping algorithm to generate a 10 m resolution crop type map over large spatial domains by integrating time series optical images (Sentinel-2) and synthetic aperture radar (SAR) images (Sentinel-1) using the Google Earth Engine (GEE) platform. The results showed that the proposed method was reliable for crop type mapping in the study area with an overall accuracy (OA) of 93.22% and a kappa coefficient (KC) of 0.89. Through experiments, we also found that the monthly median values of the vertical transmit/vertical receive (VV) and vertical transmit/horizontal receive (VH) bands were insensitive to crop type mapping itself, but adding this information to supplement the optical images improved the classification accuracy, with an OA increase of 0.09–2.98%. Adding the slope of vegetation index change (VIslope) at the critical period to crop type classification was obviously better than that of relative change ratio of vegetation index (VIratio), both of which could make an OA improvement of 2.58%. These findings not only highlighted the potential of the VIslope and VIratio indices during the critical period for crop type mapping in small plots, but suggested that SAR images could be included to supplement optical images for crop type classification.

Histone methylation plays an important regulatory role in the drought response of many plants, but its regulatory mechanism in the drought response of the tea plant remains poorly understood. Here, drought stress was shown to induce lower relative water content and significantly downregulate the methylations of histone H3K4 in the tea plant. Based on our previous analysis of the SET Domain Group (SDG) gene family, the full-length coding sequence (CDS) of CsSDG36 was cloned from the tea cultivar ‘Fuding Dabaicha’. Bioinformatics analysis showed that the open reading frame (ORF) of the CsSDG36 gene was 3138 bp, encoding 1045 amino acids and containing the conserved structural domains of PWWP, PHD, SET and PostSET. The CsSDG36 protein showed a close relationship to AtATX4 of the TRX subfamily, with a molecular weight of 118,249.89 Da, and a theoretical isoelectric point of 8.87, belonging to a hydrophilic protein without a transmembrane domain, probably located on the nucleus. The expression of CsSDG36 was not detected in the wild type, while it was clearly detected in the over-expression lines of Arabidopsis. Compared with the wild type, the over-expression lines exhibited lower hyperosmotic resistance by accelerating plant water loss, increasing reactive oxygen species (ROS) pressure, and increasing leaf stomatal density. RNA-seq analysis suggested that the CsSDG36 overexpression caused the differential expression of genes related to chromatin assembly, microtubule assembly, and leaf stomatal development pathways. qRT-PCR analysis revealed the significant down-regulation of stomatal development-related genes (BASL, SBT1.2(SDD1), EPF2, TCX3, CHAL, TMM, SPCH, ERL1, and EPFL9) in the overexpression lines. This study provides a novel sight on the function of histone methyltransferase CsSDG36 under drought stress.

Typhoons frequently occur in the summer in the northwestern Pacific Ocean, and the responses of the upper ocean to typhoons have drawn extensive attention for decades. In the present work, a modified grid-based maximum response (GMR) method was proposed to estimate the sea surface cooling (SSC) caused by typhoons. The current algorithm (CA) is different from the original GMR method mainly in two aspects: (1) it uses a 5 day average rather than a 2 day average of the sea surface temperature (SST) before the typhoon as the reference temperature; (2) it modifies the fixed radius of 400 km to the level-7 Beaufort scale wind-force (~17.1 m/s) radius to determine the area where the SSC should be calculated. Then the MW-IR OISST data derived from satellite observations were used to compare the SSC estimated by different algorithms in four typhoon cases, Megi, LionRock, Trami and KongRey. The results show that, in all cases, maximum response methods have approached similar results, while the others seemed to have underestimated the SSC in degrees. In the slow-moving LionRock case, grid-based methods were found to have better performance, while in the successive typhoon cases, Trami and KongRey, CA showed an improved result in representing the pre-existing sea surface status before the typhoon KongRey by using the pentad mean SST as the reference temperature. In addition, the use of level-7 wind-force coverage made the results much livelier. In a word, the algorithm proposed here is valid in general. It has advantages in estimating the SSC caused by both slow-moving typhoons and successive typhoons, and should be further applied to related research.

An understanding of the response of interannual vegetation variations to climate change is critical for the future projection of ecosystem processes and developing effective coping strategies. In this study, the spatial pattern of interannual variability in the growing season normalized difference vegetation index (NDVI) for different biomes and its relationships with climate variables were investigated in Inner Mongolia during 1982–2015 by jointly using linear regression, geographical detector, and geographically weighted regression methodologies. The result showed that the greatest variability of the growing season NDVI occurred in typical steppe and desert steppe, with forest and desert most stable. The interannual variability of NDVI differed monthly among biomes, showing a time gradient of the largest variation from northeast to southwest. NDVI interannual variability was significantly related to that of the corresponding temperature and precipitation for each biome, characterized by an obvious spatial heterogeneity and time lag effect marked in the later period of the growing season. Additionally, the large slope of NDVI variation to temperature for desert implied that desert tended to amplify temperature variations, whereas other biomes displayed a capacity to buffer climate fluctuations. These findings highlight the relationships between vegetation variability and climate variability, which could be used to support the adaptive management of vegetation resources in the context of climate change.

Vegetation phenology plays a critical role in the dynamic response of terrestrial ecosystems to climate change. However, the relationship between the phenology of winter wheat and hydrothermal factors is inadequate, especially in typical agricultural areas. In this study, the possible effects of preseason climate changes on the green-up date (GUD) of winter wheat over the North China Plain (NCP) was investigated, using the MODIS EVI 8-day time-series data from 2000 to 2015, as well as the concurrent monthly mean temperature (Tm), mean maximum (Tmax) and minimum temperature (Tmin) and total precipitation (TP) data. Firstly, we quantitatively identified the time lag effects of winter wheat GUD responses to different climatic factors; then, the major driving factors for winter wheat GUD were further explored by applying multiple linear regression models. The results showed that the time lag effects of winter wheat GUD response to climatic factors were site- and climatic parameters-dependent. Negative temperature effects with about a 3-month time lag dominated in most of the NCP, whereas positive temperature effects with a zero-month lag were most common in some of the southern parts. In comparison, total precipitation had a negative zero-month lag effect in the northern region, but two lagged months occurred in the south. Regarding the time lag effects, the explanation power of climatic factors improved relatively by up to 77%, and the explanation area increased by 41.20%. Additionally, change in winter wheat GUD was primarily determined by temperature rather than by TP, with a marked spatial heterogeneity of the Tmax and Tmin effect. Our results confirmed different time lag effects from different climatic factors on phenological processes in spring, and further suggested that both Tmax and Tmin should be considered to improve the performance of spring phenology models.

Studying the interaction between the upper ocean and the typhoons is crucial to improve our understanding of heat and momentum exchange between the ocean and the atmosphere. In recent years, the upper ocean responses to typhoons have received considerable attention. The sea surface cooling (SSC) process has been repeatedly discussed. In the present work, case studies were examined on five strong and super typhoons that occurred in 2016—LionRock, Meranti, Malakas, Megi, and Chaba—to search for more evidence of SSC and new features of typhoons’ impact on sea surface features. Monitoring data from the Central Meteorological Observatory, China, sea surface temperature (SST) data from satellite microwave and infrared remote sensing, and sea level anomaly (SLA) data from satellite altimeters were used to analyze the impact of typhoons on SST, the relationship between SSC and pre-existing eddies, the distribution of cold and warm eddies before and after typhoons, as well as the relationship between eddies and the intensity of typhoons. Results showed that: (1) SSC generally occurred during a typhoon passage and the degree of SSC was determined by the strength and the translation speed of the typhoon, as well as the pre-existing sea surface conditions. Relatively lower sea level (or cold core eddy) favors causing intense SSC; (2) After a typhoon passed, the SLA obviously decreased along with the SSC. The pre-existing positive SLAs or warm eddies decreased or disappeared during the typhoon’s passage, whereas negative SLAs or cold eddies were enhanced. It is suggested that the presence of warm eddies on the path has intensified the typhoons; (3) A criterion based on the ratio of local inertial period to application time of the typhoon wind-forcing was raised to dynamically distinguish slow- and fast-moving typhoons. And subcritical (slow-moving) situations were found in the LionRock case at its turning points where a cold core eddy was generated by long-time forcing. Moreover, the LionRock developed into a super typhoon due to reduced negative feedback when it was stalling over a comparably warmer sea surface. Therefore, the distinctive LionRock case is worthy of further discussion.

Based on the normalized difference vegetation index (NDVI), we analyzed vegetation change of the six major biomes across Inner Mongolia at the growing season and the monthly timescales and estimated their responses to climate change between 1982 and 2006. To reduce disturbance associated with land use change, those pixels affected by land use change from the 1980s to 2000s were excluded. At the growing season scale, the NDVI increased weakly in the natural ecosystems, but strongly in cropland. Interannual variations in the growing season NDVI for forest was positively linked with potential evapotranspiration and temperature, but negatively correlated with precipitation. In contrast, it was positively correlated with precipitation, but negatively related to potential evapotranspiration for other natural biomes, particularly for desert steppe. Although monthly NDVI trends were characterized as heterogeneous, corresponding to monthly variations in climate change among biome types, warming-related NDVI at the beginning of the growing season was the main contributor to the NDVI increase during the growing season for forest, meadow steppe, and typical steppe, but it constrained the NDVI increase for desert steppe, desert, and crop. Significant one-month lagged correlations between monthly NDVI and climate variables were found, but the correlation characteristics varied greatly depending on vegetation type.