Different composition and distribution patterns of mineral-protected versus hydrolyzable lipids in shrubland soils

Mineral protection is known as an important mechanism stabilizing soil organic carbon (SOC). However, the composition, sources, and variations of mineral-protected SOC remain poorly constrained. To fill this knowledge gap, we used hydrofluoric acid to demineralize soil matrix and compared the sources and distribution of mineral-protected lipids (ML) versus hydrolyzable lipids (HL) of four typical Chinese shrubland soils. ML was found to represent a sizable fraction (9-32%) of total aliphatic lipids (including n-alkanols; n-alkanoic acids; ,-alkanedioic acids; hydroxyalkanoic acids; and midchain-substituted acids) in all soils. Based on carbon chain length and branch positions, microbe- and plant-derived lipids were distinguished. No significant difference was found in the ratio of microbe- to plant-derived lipids in ML versus HL, implying that plant and microbial inputs are equally important for the mineral-associated soil lipids. However, ML contained a higher proportion of nonspecific lipids, especially at depths. Furthermore, to evaluate key environmental variable(s) controlling the distribution of different lipid components, a multiple stepwise regression analysis was conducted. Notably, ML was mainly affected by SOC-to-nitrogen ratio instead of mineralogical properties, implying that the accrual of mineral-associated soil lipids relies strongly on organic matter properties. Collectively, our findings provide novel insights on sources and accumulation mechanisms of mineral-protected soil lipids. SOC decomposition and subsequent accretion of degradation products appear to be vital for the sequestration of mineral-associated soil lipids and warrant better recognition in the investigations of stable soil carbon accumulation mechanisms

Clinical nurses’ compassion fatigue psychological experience process: a constructivist grounded theory study

Abstract Background Clinical nurses are susceptible to compassion fatigue when exposed to various types of traumatic events in patients for extended periods of time. However, the developmental process, staging, and psychological responses distinct to each stage of compassion fatigue in nurses are not fully clarified. This study aimed to explore the processes of compassion fatigue and the psychological experiences specific to each phase of compassion fatigue among clinical nurses. Methods Charmaz’s Constructivist Grounded Theory methodology was used in this qualitative research. Semi-structured interviews were conducted with 13 clinical nurses with varying degrees of compassion fatigue from December 2020 to January 2021. Interview data were analyzed using grounded theory processes. Results The data were categorized into five separate categories and 22 sub-categories. This study found that the process of compassion fatigue is dynamic and cumulative, which was classified into five phases: compassion experience period, compassion decrement period, compassion discomfort period, compassion distress period, and compassion fatigue period. Conclusion Clinical nurses who experience compassion fatigue may go through five stages that are stage-specific and predictable. The findings can shed light on local and global applications to better understand the problem of nurses’ compassion fatigue. The interventions for addressing compassion fatigue in clinical nurses should be stage-specific, targeted, and individualized

The relationship between the variants in the 5′-untranslated regions of equine chorionic gonadotropin genes and serum equine chorionic gonadotropin levels

Objective An experiment was conducted to study the association between the single nucleotide polymorphisms (SNPs) in 5′-untranslated regions (5′-UTR) of equine chorionic gonadotropin (eCG) genes and the serum eCG levels. Methods SNPs in 5′-UTR of eCG genes were screened across 10 horse breeds, including 7 Chinese indigenous breeds and 3 imported breeds using iPLEX chemistry, and the association between the serum eCG levels of 174 pregnant Da’an mares and their serum eCG levels (determined with ELISA) was analyzed. Results Four SNPs were identified in the 5′-UTR of the eCGα gene, and one of them was unique in the indigenous breeds. There were 2 SNPs detected at the 5′ end of the eCGβ subunit gene, and one of them was only found in the Chinese breeds. The SNP g.39948246T>C at the 5′-UTR of eCGα was associated significantly with eCG levels of 75-day pregnant mare serum (pC mutation causes appearance of the specific binding site of hepatocyte nuclear factor 3 forkhead homolog 2 (HFH-2), which is a transcriptional repressor belonging to the forkhead protein family of transcription factors. Conclusion The SNP g.39948246T>C at the 5′-UTR of eCGα is associated with eCG levels of 75-day pregnant mare serum (p<0.05)

A multiphysics model of the compactly-assembled industrial alkaline water electrolysis cell

Electrolysis occupies a dominant position in the long-term application of hydrogen energy, as it can use the power surplus directly from renewable energies to produce hydrogen. Alkaline water electrolysis (AWE) is a mature and reliable technology standing out from other types of electrolysis because of its simplicity and low cost. Several multiphysics processes inside the AWE cell, such as the electrochemical, thermal, and fluidic processes. Developing the multiphysics model to quantify the relationship between these physics fields is essential for cell design. This paper establishes a three-dimensional numerical model to consider the quantitative relationship between the electrochemical process and fluidic process inside the cell of industrial AWE. The model considers the structural design of industrial AWE equipment, revealing that the shunting current effect introduced by the structure design cannot be ignored in the model. The simulation results present that the multiphysics model considering the bubble effect can estimate the current–voltage (I-V) characteristic curve more accurately with a relative error smaller than 5%, especially at a current density higher than 2500 A/m2. The model established is supposed to advance the development of water electrolysis models and guide the electrolyzer design of industrial AWE cell.</p

Effects of size, neighbors, and site condition on tree growth in a subtropical evergreen and deciduous broad-leaved mixed forest, China

Successful growth of a tree is the result of combined effects of biotic and abiotic factors. It is important to understand how biotic and abiotic factors affect changes in forest structure and dynamics under environmental fluctuations. In this study, we explored the effects of initial size [diameter at breast height (DBH)], neighborhood competition, and site condition on tree growth, based on a 3-year monitoring of tree growth rate in a permanent plot (120x80m) of montane Fagus engleriana-Cyclobalanopsis multiervis mixed forest on Mt. Shennongjia, China. We measured DBH increments every 6months from October 2011 to October 2014 by field-made dendrometers and calculated the mean annual growth rate over the 3years for each individual tree. We also measured and calculated twelve soil properties and five topographic variables for 384 grids of 5x5m. We defined two distance-dependent neighborhood competition indices with and without considerations of phylogenetic relatedness between trees and tested for significant differences in growth rates among functional groups. On average, trees in this mixed montane forest grew 0.07cmyear(-1) in DBH. Deciduous, canopy, and early-successional species grew faster than evergreen, small-statured, and late-successional species, respectively. Growth rates increased with initial DBH, but were not significantly related to neighborhood competition and site condition for overall trees. Phylogenetic relatedness between trees did not influence the neighborhood competition. Different factors were found to influence tree growth rates of different functional groups: Initial DBH was the dominant factor for all tree groups; neighborhood competition within 5m radius decreased growth rates of evergreen trees; and site condition tended to be more related to growth rates of fast-growing trees (deciduous, canopy, pioneer, and early-successional species) than the slow-growing trees (evergreen, understory, and late-successional species).National Program on Key Basic Research Project [2014CB954004]; National Natural Science Foundation of China [31021001, 31470486]; &quot;Strategic Priority Research Program&quot; of Chinese Academy of Sciences [XDA05050301]SCI(E)[email protected]

Nitrogen and phosphorus concentrations and allocation strategies among shrub organs: the effects of plant growth forms and nitrogen-fixation types

We aimed to explore the influences of plant functional groups on nutrient concentrations and allocation strategies among shrub organs, as well as to examine the effects of climate, soil and species on nutrient concentrations in shrubs of different plant functional groups. We investigated the nitrogen (N) and phosphorus (P) concentrations in roots, stems and leaves and their influencing factors of 187 shrub species in the shrublands across southern China, and we also examined the relationships between N and P among various organs using scaling analysis. The scaling relationships of N and P tended to be allometric between leaf and non-leaf organs, while they tended to be isometric among non-leaf organs. Plant functional groups affected nutrient allocation among shrub organs, where a higher proportion of nutrients were present in the stems and roots of evergreen shrubs and non-legume shrubs when compared to deciduous shrubs and legume shrubs as nutrients within a plant increased. Among organs, N and P concentrations were higher in leaves than in stems and roots. Among functional groups, evergreen shrubs and legume shrubs were more P-limited than deciduous shrubs and non-legume shrubs, respectively. The N and P concentrations in evergreen shrubs were lower and more sensitive to environmental change than in deciduous shrubs. Both N and P contents in legume shrubs were higher and more homeostatic than those of non-legume shrubs. Plant growth forms and N-fixation types exerted strong effects on nutrient concentrations and allocations among shrub organs. The influences of climate and soil on shrub N and P concentrations differed by plant functional groups

SET8 suppression mediates high glucose-induced vascular endothelial inflammation via the upregulation of PTEN

Diabetes: Protein modulators of vascular inflammation High glucose levels in patients with diabetes trigger vascular inflammation by affecting the expression of key proteins in blood vessel linings. Elevated glucose causes inflammation of the endothelium, a thin layer of cells that lines blood and lymph vessels, leading to cardiovascular complications. The phosphatase and tensin homolog protein (PTEN) contributes to endothelial inflammation, but the precise mechanisms are unclear. Xuefang Shen at Fudan University in Shanghai, China, and co-workers demonstrated that elevated glucose increases PTEN expression, with increased levels of the protein found in peripheral blood cells of diabetic patients and aortic tissues of diabetic rats. In further experiments on rats, the researchers found that glucose also suppressed another protein called SET8, which contributed to increased PTEN levels. This suggests that SET8 is involved in PTEN modulation, and that both proteins influence vascular inflammation

C:N:P stoichiometry of Ericaceae species in shrubland biomes across Southern China: influences of climate, soil and species identity

Aims Carbon (C), nitrogen (N) and phosphorus (P) stoichiometry strongly affect functions and nutrient cycling within ecosystems. However, the related researches in shrubs were very limited. In this study, we aimed to investigate leaf stoichiometry and its driving factors in shrubs, and whether stoichiometry significantly differs among closely related species. Methods We analyzed leaf C, N and P concentrations and their ratios in 32 species of Ericaceae from 161 sites across southern China. We examined the relationships of leaf stoichiometry with environmental variables using linear regressions, and quantified the interactive and independent effects of climate, soil and species on foliar stoichiometry using general linear models (GLM). Important Findings The foliar C, N and P contents of Ericaceae were 484.66, 14.44 and 1.06 mg g(-1), respectively. Leaf C, N and P concentrations and their ratios in Ericaceae were significantly related with latitude and altitude, except the N:P insignificantly correlated with latitude. Climate (mean annual temperature and precipitation) and soil properties (soil C, N and P and bulk density) were significantly influenced element stoichiometry. The GLM analysis showed that soil exerted a greater direct effect on leaf stoichiometry than climate did, and climate affected leaf traits mainly via indirect ways. Further, soil properties had stronger influences on leaf P than on leaf C and N. Among all independent factors examined, we found species accounted for the largest proportion of the variation in foliar stoichiometry. These results suggest that species can largely influence foliar stoichiometry, even at a lower taxonomic level

Multispecies forest plantations outyield monocultures across a broad range of conditions

Multispecies tree planting has long been applied in forestry and landscape restoration in the hope of providing better timber production and ecosystem services; however, a systematic assessment of its effectiveness is lacking. We compiled a global dataset of matched single-species and multispecies plantations to evaluate the impact of multispecies planting on stand growth. Average tree height, diameter at breast height, and aboveground biomass were 5.4, 6.8, and 25.5% higher, respectively, in multispecies stands compared with single-species stands. These positive effects were mainly the result of interspecific complementarity and were modulated by differences in leaf morphology and leaf life span, stand age, planting density, and temperature. Our results have implications for designing afforestation and reforestation strategies and bridging experimental studies of biodiversity–ecosystem functioning relationships with real-world practices

Autonomous drone hunter operating by deep learning and all-onboard computations in GPS-denied environments.

This paper proposes a UAV platform that autonomously detects, hunts, and takes down other small UAVs in GPS-denied environments. The platform detects, tracks, and follows another drone within its sensor range using a pre-trained machine learning model. We collect and generate a 58,647-image dataset and use it to train a Tiny YOLO detection algorithm. This algorithm combined with a simple visual-servoing approach was validated on a physical platform. Our platform was able to successfully track and follow a target drone at an estimated speed of 1.5 m/s. Performance was limited by the detection algorithm's 77% accuracy in cluttered environments and the frame rate of eight frames per second along with the field of view of the camera