Long-term antagonistic effect of increased precipitation and nitrogen addition on soil respiration in a semiarid steppe

Changes in water and nitrogen (N) availability due to climate change and atmospheric N deposition could have significant effects on soil respiration, a major pathway of carbon (C) loss from terrestrial ecosystems. A manipulative experiment simulating increased precipitation and atmospheric N deposition has been conducted for 9 years (2005–2013) in a semiarid grassland in Mongolian Plateau, China. Increased precipitation and N addition interactively affect soil respiration through the 9 years. The interactions demonstrated that N addition weakened the precipitation-induced stimulation of soil respiration, whereas increased precipitation exacerbated the negative impacts of N addition. The main effects of increased precipitation and N addition treatment on soil respiration were 15.8% stimulated and 14.2% suppressed, respectively. Moreover, a declining pattern and 2-year oscillation were observed for soil respiration response to N addition under increased precipitation. The dependence of soil respiration upon gross primary productivity and soil moisture, but not soil temperature, suggests that resources C substrate supply and water availability are more important than temperature in regulating interannual variations of soil C release in semiarid grassland ecosystems. The findings indicate that atmospheric N deposition may have the potential to mitigate soil C loss induced by increased precipitation, and highlight that long-term and multi-factor global change studies are critical for predicting the general patterns of terrestrial C cycling in response to global change in the future

Seeing Beyond the Brain: Conditional Diffusion Model with Sparse Masked Modeling for Vision Decoding

Decoding visual stimuli from brain recordings aims to deepen our understanding of the human visual system and build a solid foundation for bridging human and computer vision through the Brain-Computer Interface. However, reconstructing high-quality images with correct semantics from brain recordings is a challenging problem due to the complex underlying representations of brain signals and the scarcity of data annotations. In this work, we present MinD-Vis: Sparse Masked Brain Modeling with Double-Conditioned Latent Diffusion Model for Human Vision Decoding. Firstly, we learn an effective self-supervised representation of fMRI data using mask modeling in a large latent space inspired by the sparse coding of information in the primary visual cortex. Then by augmenting a latent diffusion model with double-conditioning, we show that MinD-Vis can reconstruct highly plausible images with semantically matching details from brain recordings using very few paired annotations. We benchmarked our model qualitatively and quantitatively; the experimental results indicate that our method outperformed state-of-the-art in both semantic mapping (100-way semantic classification) and generation quality (FID) by 66% and 41% respectively. An exhaustive ablation study was also conducted to analyze our framework.Comment: 8 pages, 9 figures, 2 tables, accepted by CVPR2023, see https://mind-vis.github.io/ for more informatio

Transcriptome Analysis Identified Genes for Growth and Omega-3/-6 Ratio in Saline Tilapia

Growth and omega-3/-6 ratio are important traits in aquaculture. The mechanisms underlying quick growth and high omega-3/-6 ratio in fish are not fully understood. The consumption of the meat of tilapia suffers a bad reputation due to its low omega-3/-6 ratio. To facilitate the improvement of these traits and to understand more about the mechanisms underlying quick growth and high omega-3/-6 ratio, we conducted transcriptome analysis in the muscle and liver of fast- and slow-growing hybrid saline tilapia generated by crossing Mozambique tilapia and red tilapia. A transcriptome with an average length of 963 bp was generated by using 486.65 million clean 100 bp paired-end reads. A total of 42,699 annotated unique sequences with an average length of 3.4 kb were obtained. Differentially expressed genes (DEGs) in the muscle and liver were identified between fast- and slow-growing tilapia. Pathway analysis classified these genes into many pathways. Ten genes, including foxK1, sparc, smad3, usp38, crot, fadps, sqlea, cyp7b1, impa1, and gss, from the DEGs were located within QTL for growth and omega-3, which were previously detected content in tilapia, suggesting that these ten genes could be important candidate genes for growth and omega-3 fatty acid content. Analysis of SNPs in introns 1 and 2 of foxK1 revealed that the SNPs were significantly associated with growth and omega-3/-6 ratio. This study lays the groundwork for further investigation of the molecular mechanisms underlying the phenotypic variation of these two traits and provides SNPs for selecting these traits at fingerling stage

Complex responses of spring vegetation growth to climate in a moisture-limited alpine meadow.

Since 2000, the phenology has advanced in some years and at some locations on the Qinghai-Tibetan Plateau, whereas it has been delayed in others. To understand the variations in spring vegetation growth in response to climate, we conducted both regional and experimental studies on the central Qinghai-Tibetan Plateau. We used the normalized difference vegetation index to identify correlations between climate and phenological greening, and found that greening correlated negatively with winter-spring time precipitation, but not with temperature. We used open top chambers to induce warming in an alpine meadow ecosystem from 2012 to 2014. Our results showed that in the early growing season, plant growth (represented by the net ecosystem CO2 exchange, NEE) was lower in the warmed plots than in the control plots. Late-season plant growth increased with warming relative to that under control conditions. These data suggest that the response of plant growth to warming is complex and non-intuitive in this system. Our results are consistent with the hypothesis that moisture limitation increases in early spring as temperature increases. The effects of moisture limitation on plant growth with increasing temperatures will have important ramifications for grazers in this system

N-(4-Bromo­phen­yl)-2-[(1-cyclo­hexyl­meth­yl-1H-1,2,4-triazol-3-yl)sulfanyl]­acetamide

The title compound, C17H21BrN4OS, was synthesized as a potential reverse transcriptase (RT) inhibitor of the human immunodeficiency virus type 1 (HIV-1). In the molecule, there is an N—H⋯S hydrogen bond making a five-membered ring. In the crystal, mol­ecules are connected into centrosymmetric dimers via pairs of N—H⋯N and weak C—H⋯N hydrogen bonds. The crystal structure also features C—H⋯O inter­actions

Psychological resilience matters in the relationship between the decline in economic status and adults’ depression half a year after the outbreak of the COVID-19 pandemic

Background/objectiveThe outbreak of COVID-19 in China since 2019 has had a significant impact on the mental health of people in Hubei Province during the three-year pandemic period. Therefore, studying the prevalence of depression among the population of Hubei Province since the pandemic is of great significance.MethodsBased on opportunity and stress theory, we collected provincial-level data from Hubei (N = 3,285) to examine the impact of declining economic status on depressive symptoms and to investigate the moderating effect of psychological resilience during the period of economic adjustment.ResultsWe used propensity score matching to estimate the treatment effect of economic status decline on depression severity and confirmed the moderating effect of psychological resilience. We found that the more that an individual’s economic status declines, the more severe that his or her depressive symptoms become. Specifically, each unit decrease in economic status is associated with an increase of approximately 0.117 units in depression level. In addition, our results indicated that psychological resilience significantly moderated the relationship between economic decline and depression (−0.184*).Conclusions and implicationsOur study confirms the role of economic status in depressive symptoms. Compared with traditional research on the relationship between economic status and mental illness, this paper expands the research regarding the two in the context of a major public health emergency. Furthermore, we suggest ways to improve people’s mental health following the pandemic

Phase Control on Surface for the Stabilization of High Energy Cathode Materials of Lithium Ion Batteries.

The development of high energy electrode materials for lithium ion batteries is challenged by their inherent instabilities, which become more aggravated as the energy densities continue to climb, accordingly causing increasing concerns on battery safety and reliability. Here, taking the high voltage cathode of LiNi0.5Mn1.5O4 as an example, we demonstrate a protocol to stabilize this cathode through a systematic phase modulating on its particle surface. We are able to transfer the spinel surface into a 30 nm shell composed of two functional phases including a rock-salt one and a layered one. The former is electrochemically inert for surface stabilization while the latter is designated to provide necessary electrochemical activity. The precise synthesis control enables us to tune the ratio of these two phases, and achieve an optimized balance between improved stability against structural degradation without sacrificing its capacity. This study highlights the critical importance of well-tailored surface phase property for the cathode stabilization of high energy lithium ion batteries

Involvement of Indoleamine 2,3-Dioxygenase in Impairing Tumor-Infiltrating CD8+ T-Cell Functions in Esophageal Squamous Cell Carcinoma

The indoleamine 2,3-dioxygenase-(IDO-) mediated microenvironment plays an important role in tumor immune escape. However, the inhibitory effects of IDO on the CD8+ tumour-infiltrating lymphocytes (CD8+ TILs) in esophageal squamous cell carcinoma (ESCC) have not been clarified yet. Here, we found that the level of IDO expression in ESCC tumor specimens correlated with a reduction in the number of CD8+ TILs. Patients with high IDO expression and a low number of CD8+ TILs had significantly impaired overall survival time. IDO expression and functional enzyme activity in ESCC cell lines could be induced by IFNγ. When exposed to the milieu generated by IDO-expressing Eca109 cells, the CD8+ TILs were suppressed in proliferation, and their cytolytic functions against target tumor cells were lost. These results suggested that impairing CD8+ TIL functions by IDO expressed in ESCC possibly contributed to the finding that patients with higher IDO expression have more aggressive disease progression and shorter overall survival time

Polarization-based probabilistic discriminative model for quantitative characterization of cancer cells

We propose a polarization-based probabilistic discriminative model for deriving a set of new sigmoid-transformed polarimetry feature parameters, which not only enables accurate and quantitative characterization of cancer cells at pixel level, but also accomplish the task with a simple and stable model. By taking advantages of polarization imaging techniques, these parameters enable a low-magnification and wide-field imaging system to separate the types of cells into more specific categories that previously were distinctive under high magnification. Instead of blindly choosing the model, the L0 regularization method is used to obtain the simplified and stable polarimetry feature parameter. We demonstrate the model viability by using the pathological tissues of breast cancer and liver cancer, in each of which there are two derived parameters that can characterize the cells and cancer cells respectively with satisfactory accuracy and sensitivity. The stability of the final model opens the possibility for physical interpretation and analysis. This technique may bypass the typically labor-intensive and subjective tumor evaluating system, and could be used as a blueprint for an objective and automated procedure for cancer cell screening

Multi-scale analysis of schizophrenia risk genes, brain structure, and clinical symptoms reveals integrative clues for subtyping schizophrenia patients

Analysis linking directly genomics, neuroimaging phenotypes and clinical measurements is crucial for understanding psychiatric disorders, but remains rare. Here, we describe a multi-scale analysis using genome-wide SNPs, gene-expression, grey matter volume (GMV) and the Positive and Negative Syndrome Scale scores (PANSS) to explore the etiology of schizophrenia. With 72 drug-naive schizophrenic first episode patients (FEPs) and 73 matched heathy controls, we identified 108 genes, from schizophrenia risk genes, that correlated significantly with GMV, which are highly co-expressed in the brain during development. Among these 108 candidates, 19 distinct genes were found associated with 16 brain regions referred to as hot clusters (HCs), primarily in the frontal cortex, sensory-motor regions and temporal and parietal regions. The patients were subtyped into three groups with distinguishable PANSS scores by the GMV of the identified HCs. Furthermore, we found that HCs with common GMV among patient groups are related to genes that mostly mapped to pathways relevant to neural signaling, which are associated with the risk for schizophrenia. Our results provide an integrated view of how genetic variants may affect brain structures that lead to distinct disease phenotypes. The method of multi-scale analysis that was described in this research, may help to advance the understanding of the etiology of schizophrenia