Search

Abstract A fundamental objective of genomics is to track variations in gene expression program. While metabolic RNA labeling-based single-cell RNA sequencing offers insights into temporal biological processes, its limited applicability only to in vitro models challenges the study of in vivo gene expression dynamics. Herein, we introduce Dyna-vivo-seq, a strategy that enables time-resolved dynamic transcription profiling in vivo at the single-cell level by examining new and old RNAs. The new RNAs can offer an additional dimension to reveal cellular heterogeneity. Leveraging new RNAs, we discern two distinct high and low metabolic labeling populations among proximal tubular (PT) cells. Furthermore, we identify 90 rapidly responding transcription factors during the acute kidney injury in female mice, highlighting that high metabolic labeling PT cells exhibit heightened susceptibility to injury. Dyna-vivo-seq provides a powerful tool for the characterization of dynamic transcriptome at the single-cell level in living organism and holds great promise for biomedical applications.

In recent years, the Dataset for Object deTection in Aerial images (DOTA) dataset has played a pivotal role in advancing object detection in aerial images (ODAI). Despite its significance, there hasn’t been a comprehensive review summarizing its research developments. Addressing this gap, this paper offers the first comprehensive overview on the subject. Within this review, we begin by examining prevalent object detection datasets of natural scene images alongside object detection datasets of remote sensing images (RSIs). We then present an in-depth comparative analysis between these datasets and the DOTA dataset, supported by numerous charts and tables. We proceed to outline both traditional techniques for ODAI and methods rooted in deep learning. Subsequently, we provide a recap of the latest advancements in the field achieved using the DOTA dataset. Concluding our review, we delve into the current challenges facing ODAI and propose potential future research directions.

Our research team previously reported the immunomodulatory effects of kombucha fermentation liquid. This study investigated the protective effects of turmeric kombucha (TK) against lipopolysaccharide (LPS)-induced sepsis and its impact on the intestinal microbiota of mice. A turmeric culture medium without kombucha served as the control (TW). Non-targeted metabolomics analysis was employed to analyze the compositional differences between TK and TW. Qualitative analysis identified 590 unique metabolites that distinguished TK from TW. TK improved survival from 40 to 90%, enhanced thermoregulation, and reduced pro-inflammatory factor expression and inflammatory cell infiltration in the lung tissue, suppressing the NF-κB signaling pathway. TK also altered the microbiome, promoting Allobaculum growth. Our findings shed light on the protective effects and underlying mechanisms of TK in mitigating LPS-induced sepsis, highlighting TK as a promising anti-inflammatory agent and revealing new functions of kombucha prepared through traditional fermentation methods.

Study region: The Xiying River Basin is a typical inland mountainous watershed located in the Qilian Mountains. Study focus: This article reveals the change of runoff stable isotopes and their control mechanisms based on isotope data of different water bodies (precipitation, runoff, groundwater, and glacial snowmelt) in the Xiying River Basin from 2016 to 2021, combined with relevant meteorological observation data and the Normalized Vegetation Index (NDVI). New hydrological insights for the region: The results show that (1) meteorological factors control runoff isotope variations through controlling the evaporation process of runoff and the isotopic characteristics of recharge sources. (2) In areas with low vegetation cover, surface landscape features influence runoff isotopic composition by altering the isotopic characteristics of recharge sources. (3) In areas with high vegetation cover, surface vegetation cover affects runoff stable isotopes by controlling evapotranspiration processes. This study connects vegetation cover and runoff isotopes to explain the surface landscape control of runoff stable isotopes. It offers a more powerful reference for elucidating the factors influencing runoff isotopes in inland mountain watersheds.

In arid oasis regions, water resources are severely scarce, with agricultural water usage far exceeding that of more humid areas. As a result, assessing non-productive water losses in farmland becomes crucial for estimating the water requirements reliant on irrigation for oasis cultivation. From April 2018 to October 2021, we established an observation system in the Minqin Oasis farmland. By utilizing hydrogen and oxygen isotopes in precipitation, soil water, and maize stem xylem water, we quantified the non-productive water loss (FE) and soil water infiltration rate (fe) in maize fields. Our findings indicate: (1) The average non-productive losses from rainfall and irrigation in arid maize fields were 39 %, with peak losses reaching 58 %; (2) Non-productive losses due to evapotranspiration were mainly observed in June and July, while losses from infiltration predominantly occurred in April-May and August-September; (3) Crop evapotranspiration capacity emerged as a significant factor influencing evaporation losses, while individual irrigation amounts and rainfall determined soil infiltration losses. We believe that judiciously managing irrigation volume and adjusting irrigation strategies in arid farmlands could unlock substantial potential for conserving water resources.

The spatial transcriptome has enabled researchers to resolve transcriptome expression profiles while preserving information about cell location to better understand the complex biological processes that occur in organisms. Due to technical limitations, the current high-throughput spatial transcriptome sequencing methods (known as next-generation sequencing with spatial barcoding methods or spot-based methods) cannot achieve single-cell resolution. A single measurement site, called a spot, in these technologies frequently contains multiple cells of various types. Computational tools for determining the cellular composition of a spot have emerged as a way to break through these limitations. These tools are known as deconvolution tools. Recently, a couple of deconvolution tools based on different strategies have been developed and have shown promise in different aspects. The resulting single-cell resolution expression profiles and/or single-cell composition of spots will significantly affect downstream data mining; thus, it is crucial to choose a suitable deconvolution tool. In this review, we present a list of currently available tools for spatial transcriptome deconvolution, categorize them based on the strategies they employ, and explain their advantages and limitations in detail in order to guide the selection of these tools in future studies.

Soil organic carbon is very important to increase crop yield. Understanding the composition changes and migration characteristics of SOC under different irrigation conditions in arid oasis areas is of great significance for the sustainable development of agro-ecosystem and the estimation of carbon balance of farmland ecosystem in arid areas. In this paper, classical statistics and geostatistics were used to study the leaching characteristics and migration laws of soil organic carbon under different irrigation conditions in Minqin Oasis, and the leaching amount and loss process and mechanism of SOC under different irrigation conditions were quantified. The research results showed that: (1) Irrigation increased the average 0–100 cm SOC content. After irrigation, SOC content decreased first and then increased with the increase in soil depth, with the maximum value of 8.56 g/kg and the minimum value of 1.82 g/kg. Compared with that before irrigation, SOC content in 0–30 cm surface layer was in leaching state, SOC content in 30–70 cm surface layer was accumulated, and SOC content in 70–100 cm surface layer had no obvious change. (2) Water was an important factor affecting soil carbon. The greater the irrigation amount, the higher the carbon leaching rate and the greater the migration amount. The SOC content in 0–30 cm soil layer was most significantly affected by irrigation, and the migration amount of SOC gradually decreased with the increase in soil depth. The maximum leaching rate of SOC was 36.8%, the minimum leaching rate was 13.5%, and its average leaching rate was 23.4%. (3) Due to the influence of soil infiltration rate under water, SOC content in different irrigation periods showed that the greatest SOC occurred in the 0–70 cm layer, and SOC content in soil was basically the same as that in non-irrigated areas on the fifth day after irrigation. (4) Precipitation, plastic film mulching, soil physical and chemical properties and other environmental factors were important factors affecting the migration and change in SOC content.

AbstractPopulation-specific, positive selection promotes the diversity of populations and drives local adaptations in the population. However, little is known about population-specific, recent positive selection in the populations of cultivated cucumber (Cucumis sativus

The Yellow River Basin is essential to China’s economic and social development and ecological security. In order to assess the temporal and spatial distribution of cloud water in the Yellow River Basin, we analyzed the distribution characteristics of water vapor content and cloud water content using ERA5 monthly averaged data from 1980 to 2019. The results showed that the high-value area of the annual average atmospheric water vapor content distribution was concentrated above the North China Plain in the eastern part of the basin, and the value was mostly between 21 and 24 mm. The low-value areas were mainly centered above the high mountain areas in the western part of the basin, and the value mostly fell between 3 and 6 mm. The seasonal distribution characteristics of the annual average water vapor content were relatively consistent with the annual average distribution characteristics. The high-value cloud ice water content area was in the northeastern part of the Qinghai-Tibet Plateau (4.5 g·m−2), while the low-value area appeared on the Loess Plateau (2 g·m−2). The high-value area of cloud liquid water content was on the north side of the West Qinling Mountains (12 g·m−2). The low-value area appeared on the Loess Plateau and the northern part of the Qinghai-Tibet Plateau (3 g·m−2). The cloud water content was higher in the eastern region than in the western region in the overall spatial distribution, and the content of cloud liquid water was higher than that of cloud ice water. The average annual atmospheric water vapor content was increasing, and the annual average content of cloud ice water and cloud liquid water was declining. The change in the total amount and spatial distribution of cloud water was not obvious in the Yellow River Basin.

Gravity Recovery and Climate Experiment (GRACE) satellite data are widely used in drought studies. In this study, we quantified drought severity based on land terrestrial water storage (TWS) changes in GRACE data. We used the water storage deficit (WSD) and water storage deficit index (WSDI) to identify the drought events and evaluate the drought severity. The WSDI calculated by GRACE provides an effective assessment method when assessing the extent of drought over large areas under a lack of site data. The results show a total of 22 drought events in the central Asian dry zone during the study period. During spring and autumn, the droughts among these incidents occurred more frequently and severely. The longest and most severe drought occurred near the Caspian Sea. In the arid area of central Asia, the north of the region tended to be moist (the WSDI value was 0.04 year−1), and the south, east, and Caspian Sea area tended to be drier (the WSDI values were −0.07 year−1 in the south, −0.11 year−1 in the east, and −0.19 year−1 in the Caspian Sea). These study results can provide a key scientific basis for agricultural development, food security, and climate change response in the Asian arid zone.

Stable isotopes in precipitation can effectively reveal the process of atmospheric water circulation, serving as an effective tool for hydrological and water resources research, climate change, and ecosystem studies. The scarcity of stable isotope data in precipitation has hindered comprehension of regional hydrology, climate, and ecology due to discontinuities on a temporal scale and unevenness on a spatial scale. To this end, we collated stable hydrogen and oxygen isotope data in precipitation from 1930 stations in Eurasia from 1961 to 2022, totalling 51,752 data records. Stable isotopes in precipitation across various regions of Eurasia, as a whole, decrease with increasing latitude and distance from the coast. In the summer, stable isotopes in precipitation are relatively enriched, while in winter, they are relatively depleted. In recent decades, the stable isotope values of Eurasian precipitation show an overall trend of increasing variation with the advancement of years, which is associated with global warming. Geographical location, underlying surface conditions, seasons, and atmospheric circulation are all factors that determine the characteristics of stable isotopes in precipitation. The dataset of stable isotopes in Eurasian precipitation provides a powerful tool for understanding changes in regional atmospheric water circulation and assists in conducting hydrological, meteorological, and ecological studies in related regions. [ABSTRACT FROM AUTHOR]

Stable hydrogen and oxygen isotopes in atmospheric precipitation have the potential to identify abnormal weather events, and climate change will cause more intense and frequent high-temperature events, which already pose a threat to human health and the development of the global economy. Based on precipitation isotope data from 37 high-temperature events that occurred in various global regions between 2010 and 2022, this article examines the impacts of high-temperature events on stable precipitation isotopes. The results show that (1) stable precipitation isotopes are more enriched under the influence of high-temperature events than in the same month of previous years; the slope and intercept of the precipitation local meteoric water line (LMWL) are lower than in the same month of previous years and the global meteoric water line (GMWL); and the precipitation d-excess is lower than the global average. (2) Temperature is the primary meteorological factor that produces abnormal variations in precipitation isotopes under the influence of high-temperature events, and the impact of temperature on precipitation isotopes is significantly amplified (P<0.05). (3) Furthermore, variations in atmospheric circulation patterns, water vapor transport fluxes, regional water vapor background, and surface morphology can lead to regional differences in anomalous variations in precipitation isotopes. This study reveals the impact of high temperatures on precipitation isotopes and their mechanisms, which is instructive for disentangling the influence of high-temperature events on water cycle processes. It may also offer fresh perspectives for the reconstruction of paleo-high-temperature events based on isotopes. [ABSTRACT FROM AUTHOR]

Climate change is the dominant factor affecting the hydrological process, it is of great significance to simulate and predict its influence on water resources management, socio-economic activities, and sustainable development in the future. In this paper, the Xiying River Basin was taken as the study area, China Atmospheric Assimilation Driven Data Set (CMADS) and observation data from the Jiutiaoling station were used to simulate runoff of the SWAT model and calibrate and verify model parameters. On this basis, runoff change of the basin under the future climate scenario of CMIP6 was predicted. Our research shows that: (1) The contribution rates of climate change and human activities to runoff increase of the Xiying River are 89.17% and 10.83%, respectively. Climate change is the most important factor affecting runoff change of the Xiying River. (2) In these three different emission scenarios of SSP1-2.6, SSP2-4.5 and SSP5-8.5 in CMIP6 climate model, the average temperature increased by 0.61, 1.09 and 1.74 °C, respectively, in the Xiying River Basin from 2017 to 2050. Average precipitation increased by 14.36, 66.88, and 142.73 mm, respectively, and runoff increased by 15, 24, and 35 million m³, respectively. The effect of climate change on runoff will continue to deepen in the future. [ABSTRACT FROM AUTHOR]

Mountainous areas are the main water-producing and source areas of rivers. Global climate change is transforming the distribution of plants and forms of water use. Therefore, a clear understanding of evapotranspiration in mountainous forest zone is key for understanding the ecohydrological effect of vegetation and its influence on the water cycle of the watershed. We quantified the evapotranspiration processes in the forest belts of the Qilian Mountains as well as their contribution to runoff yield and concentration based on precipitation, soil water, and plant water samples and experimental data. The study showed that transpiration of Qinghai spruce accounted for the highest proportion of evapotranspiration in the entire Qinghai spruce forest ecosystem, with an average of 79 %, which means that transpiration is much greater than evaporation. Soil water content and air humidity were the dominant factors influencing evapotranspiration in Qinghai spruce forest belts. The growing season of Qinghai spruce is characterized by greater evapotranspiration than precipitation in each month. Consequently, the forest zone does not yield flows in the eastern part of the Qilian Mountains. The warming of global temperatures and human activities are likely to trigger shifts in the distribution areas and evapotranspiration regimes of Qinghai spruce, which in turn will lead to a change in water resource patterns in the basin. [ABSTRACT FROM AUTHOR]

Copyright of Transformations in Business & Economics is the property of Vilnius University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Transformations in Business & Economics is the property of Vilnius University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)