Browse Articles

Metabolic profiling and antibacterial activity of secondary metabolites extracted from the endophytic bacteria of Combretum erythrophyllum

Prevalence, clinical reasons and associated factors of extended treatment duration for drug susceptible tuberculosis – a real-world experience

Neural processing of laughter in depression

Abstract Laughter can convey social intent ranging from acceptance (friendly inclusive laughter) to rejection (malign taunting laughter). We investigated perception of auditory and visual laughter in patients with major depressive disorder (MDD) versus healthy controls (HC). 48 MDD patients and 52 HC rated 60 laughter recordings presented auditorily or visually regarding the expressed social intent during an fMRI experiment at 3T. Depression severity was assessed based on questionnaires. MDD patients rated the perceived social intent of the laughter significantly more negative than HC across both modalities. The individual magnitude of this negativity bias of social intent attribution significantly correlated with both depression severity as well as activation in anteromedial prefrontal cortex (AMPFC) during perception of auditory laughter. MDD patients also exhibited a significantly reduced activation in AMPFC and depression severity partially mediated effects on rating of auditory laughter as evidenced by mediation analysis. Our results demonstrate altered perception of social intent expressed by laughter in MDD. Neuroimaging data point to the AMPFC for mediation of this effect as its activity was correlated with both depression severity and a negative attribution bias during perception of auditory laughter. Furthermore, at group level activity in this area was reduced in MDD patients.

Mixed adverse ergonomic factors exposure in relation to work-related musculoskeletal disorders: a multicenter cross-sectional study of Chinese medical personnel

Chacma baboon natural anticoagulants and factor VIII activities

Implementation of pooled testing to increase access to routine viral load monitoring for people living with HIV on antiretroviral therapy

A multi-scale remote sensing semantic segmentation model with boundary enhancement based on UNetFormer

Abstract The precise execution of semantic segmentation on remote sensing data is a pivotal factor. It determines the achievements and impact of geoscience endeavors and their applications. However, challenges caused by target edge blurring and scale variability in high-resolution remote sensing imagery hinder the improvement of segmentation accuracy. In this work, to address these issues, a Boundary-Enhanced Multi-Scale Semantic Segmentation Network (BEMS-UNetFormer) based on UNetFormer is proposed for remote sensing data. Firstly, an improved Boundary Awareness Module (BAM) is used to extract the edge information of the target from the low-level features to enhance the recognition of the target edges. Secondly, the improved Boundary-Guided Fusion Module (BFM) incorporates the edge information from BAM into subsequent decoding, further refining the precise representation of boundary regions. Finally, at the pivotal junction between the encoder and decoder, the Multi-Scale Cascaded Atrous Spatial Pyramid Pooling (MSC-ASPP) is designed, capable of deeply mining and integrating multi-scale deep features. The method was tested on two mainstream datasets, Potsdam and Vaihingen, achieving 86.12% and 83.10% MIoU, respectively, improving by 1.38% and 1.79% over the baseline model. Notably, the IoU and F1 Score for the small-scale target “Car” in the Potsdam dataset reached 91.20% and 95.57%, respectively, while the “Building” and “LowVeg” categories in the Vaihingen dataset achieved the highest IoU and F1 Score. The experimental results indicate that the proposed method demonstrates higher precision in segmenting small-scale targets and target boundaries, surpassing mainstream methods overall.

Hydrogen can both move or pin dislocations in body-centered cubic metals

Unveiling the regulatory role of GRP7 in ABA signal-mediated mRNA translation efficiency regulation

Investigations into cyanobacterial photoacclimation processes address longstanding proposals for improving crop yields

Perturbing local steroidogenesis to improve breast cancer immunity

Abstract Breast cancer, particularly triple-negative breast cancer (TNBC), evades the body’s immune defences, in part by cultivating an immunosuppressive tumour microenvironment. Here, we show that suppressing local steroidogenesis can augment anti-tumour immunity against TNBC. Through targeted metabolomics of steroids coupled with immunohistochemistry, we profiled the existence of immunosuppressive steroids in TNBC patient tumours and discerned the steroidogenic activity in immune-infiltrating regions. In mouse, genetic inhibition of immune cell steroidogenesis restricted TNBC tumour progression with a significant reduction in immunosuppressive components such as tumour associated macrophages. Steroidogenesis inhibition appears to bolster anti-tumour immune responses in dendritic and T cells by impeding glucocorticoid signalling. Undertaking metabolic modelling of the single-cell transcriptomics and targeted tumour-steroidomics, we pinpointed the predominant steroidogenic cells. Inhibiting steroidogenesis pharmacologically using a identified drug, posaconazole, curtailed tumour expansion in a humanised TNBC mouse model. This investigation paves the way for targeting steroidogenesis and its signalling pathways in breast cancer affected by immune-steroid maladaptation.

Nitro-oleic acid enhances mitochondrial metabolism and ameliorates heart failure with preserved ejection fraction in mice

Abstract The prevalence of heart failure with preserved ejection fraction (HFpEF) is increasing, while treatment options are inadequate. Hypertension and obesity-related metabolic dysfunction contribute to HFpEF. Nitro-oleic acid (NO2-OA) impacts metabolic syndromes by improving glucose tolerance and adipocyte function. Here we show that treatment with NO2-OA ameliorates diastolic dysfunction and heart failure symptoms in a HFpEF mouse model induced by high-fat diet and inhibition of the endothelial nitric oxide synthase. Proteomic analysis of left ventricular tissue reveals that one-third of identified proteins, predominantly mitochondrial, are upregulated in hearts of NO2-OA-treated HFpEF mice compared to naïve and vehicle-treated HFpEF mice. Increased mitochondrial mass and numbers, and enhanced mitochondrial respiration are linked with this response, as assessed by transmission electron microscopy and high-resolution respirometry. Activation of the 5’-adenosine-monophosphate-activated-protein-kinase (AMPK) signaling pathway mediates the enhancement of mitochondrial dynamics in hearts of NO2-OA-treated HFpEF mice. These findings suggest that targeting mitochondrial function with NO2-OA may represent a promising therapeutic strategy for HFpEF.

Glucose-6-phosphate-dehydrogenase on old peroxisomes maintains self-renewal of epithelial stem cells after asymmetric cell division

Abstract Selective inheritance of sub-cellular components has emerged as a mechanism guiding stem cell fate after asymmetric cell divisions. Peroxisomes play a crucial role in multiple metabolic processes such as fatty acid metabolism and reactive oxygen species detoxification, but the apportioning of peroxisomes during stem cell division remains understudied. Here, we develop a mouse model and labeling technique to follow the dynamics of distinct peroxisome age-classes, and find that old peroxisomes are inherited by the daughter cell retaining full stem cell potency in mammary and epidermal stem cell divisions. Old peroxisomes carry Glucose-6-phosphate-dehydrogenase, whose specific location on the peroxisomal membrane promotes stem cell function by facilitating peroxisomal ether lipid synthesis. Our study demonstrates age-selective apportioning of peroxisomes in vivo, and unveils how functional heterogeneity of peroxisomes is utilized by asymmetrically dividing cells to metabolically divert the fate of the two daughter cells.

p53 protein degradation redefines the initiation mechanisms and drives transitional mutations in colorectal cancer

Both phytochrome A and phyB interact with PHYTOCHROME-INTERACTING FACTORs through an evolutionary conserved phyOPM-APA interaction

Catalytic enantioselective synthesis of inherently chiral calix[4]arenes via organocatalyzed aromatic amination enabled desymmetrization

Quantifying the global climate feedback from energy-based adaptation

Abstract Many behavioral responses to climate change are carbon-intensive, raising concerns that adaptation may cause additional warming. The sign and magnitude of this feedback depend on how increased emissions from cooling balance against reduced emissions from heating across space and time. We present an empirical approach that forecasts the effect of future adaptive energy use on global average temperature over the 21st century. We estimate that energy-based adaptation will lower global mean surface temperature in 2099 by 0.07 to 0.12 °C relative to baseline projections under Representative Concentration Pathways 4.5 and 8.5. This cooling avoids 0.6 to 1.8 trillion U.S. Dollars ($2019) in damages, depending on the baseline emissions scenario. Energy-based adaptation lowers business-as-usual emissions for 85% of countries, reducing the mitigation required to meet their unilateral Nationally Determined Contributions by 20% on average. These findings indicate that while business-as-usual adaptive energy use is unlikely to accelerate warming, it raises important implications for countries’ existing mitigation commitments.

Interactive symbolic regression with co-design mechanism through offline reinforcement learning

Structural basis for the activation of proteinase-activated receptors PAR1 and PAR2

Concerted catalysis of single atom and nanocluster enhances bio-ethanol activation and dehydrogenation

Abstract Single atom and nanocluster catalysts are extensively investigated in heterogeneous catalysis due to their high catalytic activity and atomic utilization, while their coexisting properties and potentially synergistic effect are yet to be clarified. Herein, we construct three systems of atomic-scale catalysts (xNi/Mo2TiAlC2, x = 0.5, 1, and 1.5) for bio-ethanol reforming, which correspond to single atoms, single atoms mixed with nanoclusters, and nanoclusters. The respective hydrogen utilization efficiency of mixed-form catalyst increases by 43.7% and 29.3% compared to single atom and nanocluster catalysts. Results demonstrate that the adjacent Ni single atom facilitates electron transfer from Mo2TiAlC2 to Ni-Mo interface and raises the d-band center, thus enhancing bio-ethanol adsorption and activation; while the existence of Ni nanoclusters contributes to lowering the energy barriers of CH3CHO* dehydrogenation. The catalytically active sites are Ni-Mo alloyed single atoms with adjacent Ni nanoclusters. This work provides new implications for highly activated catalytic site construction and advanced catalyst design.