Facing the challenge of achieving the goal of carbon neutrality, China is decoupling the currently close dependence of its economy on coal use. The energy supply and demand decarbonization has substantial influence on the resilience of the coal supply. However, a general understanding of the precise impact of energy decarbonization on the resilience of the coal energy supply is still lacking. Here, from the perspective of network science, we propose a theoretical framework to explore the resilience of the coal market of China. We show that the processes of increasing the connectivity and the competition between the coal enterprises, which are widely believed to improve the resilience of the coal market, can undermine the sustainability of the coal supply. Moreover, our results reveal that the policy of closing small-sized coal mines may not only reduce the safety accidents in the coal production but also improve the resilience of the coal market network. Using our model, we also suggest a few practical policies for minimizing the systemic risk of the coal energy supply.

With the development of artificial intelligence and breakthroughs in deep learning, large-scale foundation models (FMs), such as generative pre-trained transformer (GPT), Sora, etc., have achieved remarkable results in many fields including natural language processing and computer vision. The application of FMs in autonomous driving holds considerable promise. For example, they can contribute to enhancing scene understanding and reasoning. By pre-training on rich linguistic and visual data, FMs can understand and interpret various elements in a driving scene, and provide cognitive reasoning to give linguistic and action instructions for driving decisions and planning. Furthermore, FMs can augment data based on the understanding of driving scenarios to provide feasible scenes of those rare occurrences in the long tail distribution that are unlikely to be encountered during routine driving and data collection. The enhancement can subsequently lead to improvement in the accuracy and reliability of autonomous driving systems. Another testament to the potential of FMs’ applications lies in world models, exemplified by the DREAMER series, which showcases the ability to comprehend physical laws and dynamics. Learning from massive data under the paradigm of self-supervised learning, world models can generate unseen yet plausible driving environments, facilitating the enhancement in the prediction of road users’ behaviors and the off-line training of driving strategies. In this paper, we synthesize the applications and future trends of FMs in autonomous driving. By utilizing the powerful capabilities of FMs, we strive to tackle the potential issues stemming from the long-tail distribution in autonomous driving, consequently advancing overall safety in this domain.

Consumption of fried foods is highly prevalent in the Western dietary pattern. Western diet has been unfavorably linked with high risk of developing cardiovascular diseases. Heart failure (HF) as a cardiovascular disease subtype is a growing global pandemic with high morbidity and mortality. However, the causal relationship between long-term fried food consumption and incident HF remains unclear. Our population-based study revealed that frequent fried food consumption is strongly associated with 15% higher risk of HF. The causal relationship may be ascribed to the dietary acrylamide exposure in fried foods. Further cross-sectional study evidenced that acrylamide exposure is associated with an increased risk of HF. Furthermore, we discover and demonstrate that chronic acrylamide exposure may induce HF in zebrafish and mice. Mechanistically, we reveal that acrylamide induces energy metabolism disturbance in heart due to the mitochondria dysfunction and metabolic remodeling. Moreover, acrylamide exposure induces myocardial apoptosis via inhibiting NOTCH1-phosphatidylinositol 3-kinase/AKT signaling. In addition, acrylamide exposure could affect heart development during early life stage, and the adverse effect of acrylamide exposure is a threat for next generation via epigenetic change evoked by DNA methyltransferase 1 (DNMT1). In this study, we reveal the adverse effects and underlying mechanism of fried foods and acrylamide as a typical food processing contaminant on HF from population-based observations to experimental validation. Collectively, these results both epidemiologically and mechanistically provide strong evidence to unravel the mechanism of acrylamide-triggered HF and highlight the significance of reducing fried food consumption for lower the risk of HF.

Addressing the urgent need for innovative depression treatments, this study heralds a breakthrough in major depressive disorder (MDD) therapy by intertwining clinical observations with neurobiological advancements. We analyzed brain-derived neurotrophic factor (BDNF) levels in serum exosomes from a diverse group of 60 individuals, including first-episode, drug-free MDD patients, medicated MDD patients, and healthy controls. Our results revealed a significant decrease in BDNF levels within MDD patients’ exosomes, which notably increased post-medication, highlighting BDNF’s potential as a biomarker for both MDD diagnosis and treatment efficacy. Advancing these clinical findings, we developed RVG-modified exosomes engineered to overexpress BDNF (RVG-BDNF-Exos), designed to directly target neuronal cells. Our findings demonstrate that these engineered exosomes can successfully traverse the blood–brain barrier, targeting neurons in the hippocampus and prefrontal cortex. In our mouse model of depression induced by lipopolysaccharide, RVG-BDNF-Exos treatment led to a significant increase of BDNF in these key brain regions, crucial for mood regulation and neurogenesis. This intervention modulated the BDNF/TrkB/AKT signaling pathway, central to neural plasticity and implicated in depression’s pathogenesis. Behavioral assessments exhibited substantial improvements in depressive-like behaviors in mice treated with RVG-BDNF-Exos, including reduced immobility in Tail Suspension and Forced Swim Tests. Additionally, our treatment effectively decreased neuroinflammation, as evidenced by the reduction in microglia and astrocyte numbers. Moreover, RVG-BDNF-Exos treatment enhanced neurogenesis and regulated synaptic plasticity, as indicated by the increased expression of neuronal markers MAP2 and DCX, and synaptic proteins PSD95 and Syn-1. In conclusion, this study not only underscores the clinical potential of serum exosomal BDNF as a diagnostic and therapeutic marker for MDD but also demonstrates the efficacy of RVG-BDNF-Exos in alleviating depressive symptoms. Our findings pave the way for future targeted, personalized psychiatric treatments, offering a promising direction in MDD therapy.

Islet transplantation has now become a promising treatment for insulin-deficient diabetes mellitus. Compared to traditional diabetes treatments, cell therapy can restore endogenous insulin supplementation, but its large-scale clinical application is impeded by donor shortages, immune rejection, and unsuitable transplantation sites. To overcome these challenges, an increasing number of studies have attempted to transplant hydrogel-encapsulated islet cells to treat diabetes. This review mainly focuses on the strategy of hydrogel-encapsulated pancreatic islet cells for diabetic cell therapy, including different cell sources encapsulated in hydrogels, encapsulation methods, hydrogel types, and a series of accessorial manners to improve transplantation outcomes. In addition, the formation and application challenges as well as prospects are also presented.

Navigating the intricate and narrow vascular pathways of the body remains a formidable challenge in vascular embolization, often limiting the maneuverability and steerability of traditional catheters. This study, by T.T. Xu and co-workers, introduces dual-responsive reconfigurable miniature fiberbots, which are capable of catheter-assisted deployment, navigation, and embolization in vascular systems. Through meticulous design and magnetic control, this work successfully validates a multistage vascular embolization approach in the renal artery of rabbits in vivo. The experiments not only overcome the existing limitations of conventional catheterization techniques but also open new avenues for minimally invasive treatments.

The menace of drought has persistently loomed over global crop production, posing a serious threat to agricultural sustainability. Research on drought stress highlights the important role of the phytohormone abscisic acid (ABA) in orchestrating plant responses to drought conditions. ABA regulates various drought/dehydration-responsive genes, initiates stomatal closure, and influences cellular responses to drought stress. Additionally, plants employ a phosphate starvation response (PSR) mechanism to manage phosphate (Pi) deficiency, with ABA playing a role in its regulation. However, despite intensive research in these fields, the precise connection among PSRs, drought stress, and ABA signaling still needs to be determined. Recently, PSR-related gene induction has been reported to occur before the induction of ABA-responsive genes under progressive mild drought. Mild drought decreases Pi uptake and contents in plants, triggering PSRs, which play an important role in plant growth during mild drought. Both ABA-responsive and PSR-related gene expression could indicate plant perception of external moisture conditions. Thus, integrating the information regarding their associated gene expression with soil moisture contents and thermographic data can enable timely irrigation optimization to mitigate the effect of drought on crop productivity.

Organic polymer materials, as the most abundantly produced materials, possess a flammable nature, making them potential hazards to human casualties and property losses. Target polymer design is still hindered due to the lack of a scientific foundation. Herein, we present a robust, generalizable, yet intelligent polymer discovery framework, which synergizes diverse capabilities, including the in situ burning analyzer, virtual reaction generator, and material genomic model, to achieve results that surpass the sum of individual parts. Notably, the high-throughput analyzer created for the first time, grounded in multiple spectroscopic principles, enables in situ capturing of massive combustion intermediates; then, the created realistic apparatus transforming to the virtual reaction generator acquires exponentially more intermediate information; further, the proposed feature engineering tool, which embedded both polymer hierarchical structures and massive intermediate data, develops the generalizable genomic model with excellent universality (adapting over 20 kinds of polymers) and high accuracy (88.8%), succeeding discovering series of novel polymers. This emerging approach addresses the target polymer design for flame-retardant application and underscores a pivotal role in accelerating polymeric materials discovery.

Colon cancer is increasing worldwide and is commonly regarded as hormone independent, yet recent reports have implicated sex hormones in its development. Nevertheless, the role of hormones from the hypothalamus–hypophysis axis in colitis-associated colorectal cancer (CAC) remains uncertain. In this study, we observed a significant reduction in the expression of the oxytocin receptor (OXTR) in colon samples from both patient with colitis and patient with CAC. To investigate further, we generated mice with an intestinal-epithelium-cell-specific knockout of OXTR. These mice exhibited markedly increased susceptibility to dextran-sulfate-sodium-induced colitis and dextran sulfate sodium/azoxymethane-induced CAC compared to wild-type mice. Our findings indicate that OXTR depletion impaired the inner mucus of the colon epithelium. Mechanistically, oxytocin was found to regulate Mucin 2 maturation through β₁-3-N-acetylglucosaminyltransferase 7 (B3GNT7)-mediated fucosylation. Interestingly, we observed a positive correlation between B3GNT7 expression and OXTR expression in human colitis and CAC colon samples. Moreover, the simultaneous activations of OXTR and fucosylation by l-fucose significantly alleviated tumor burden. Hence, our study unveils oxytocin’s promising potential as an affordable and effective therapeutic intervention for individuals affected by colitis and CAC.

Protein loop modeling is a challenging yet highly nontrivial task in protein structure prediction. Despite recent progress, existing methods including knowledge-based, ab initio, hybrid, and deep learning (DL) methods fall substantially short of either atomic accuracy or computational efficiency. To overcome these limitations, we present KarmaLoop, a novel paradigm that distinguishes itself as the first DL method centered on full-atom (encompassing both backbone and side-chain heavy atoms) protein loop modeling. Our results demonstrate that KarmaLoop considerably outperforms conventional and DL-based methods of loop modeling in terms of both accuracy and efficiency, with the average RMSDs of 1.77 and 1.95 Å for the CASP13+14 and CASP15 benchmark datasets, respectively, and manifests at least 2 orders of magnitude speedup in general compared with other methods. Consequently, our comprehensive evaluations indicate that KarmaLoop provides a state-of-the-art DL solution for protein loop modeling, with the potential to hasten the advancement of protein engineering, antibody–antigen recognition, and drug design.