Research最新文献

Acute respiratory distress syndrome (ARDS) survivors often suffer from long-term psychiatric disorders such as depression, but the underlying mechanisms remain unclear. Here, we found marked alterations in the composition of gut microbiota in both ARDS patients and mouse models. We investigated the role of one of the dramatically changed bacteria-Akkermansia muciniphila (AKK), whose abundance was negatively correlated with depression phenotypes in both ARDS patients and ARDS mouse models. Specifically, while fecal transplantation from ARDS patients into naive mice led to depressive-like behaviors, microglial activation, and intestinal barrier destruction, colonization of AKK or oral administration of its metabolite-propionic acid-alleviated these deficits in ARDS mice. Mechanistically, AKK and propionic acid decreased microglial activation and neuronal inflammation through inhibiting the Toll-like receptor 4/nuclear factor κB signaling pathway. Together, these results reveal a microbiota-dependent mechanism for ARDS-related depression and provide insight for developing a novel preventative strategy for ARDS-related psychiatric symptoms.

Gain-of-function mutations of Notch2 cause the rare autosomal dominant disorder known as Hajdu-Cheney syndrome (HCS). Most patients with HCS develop congenital heart disease; however, the precise mechanisms remain elusive. Here, a murine model expressing the human Notch2 intracellular domain (hN2ICD) in cardiomyocytes (hN2ICD-Tg^CM) was generated and the mice spontaneously developed ventricular diastolic dysfunction with preserved ejection fraction and cardiac hypertrophy. Ectopic hN2ICD expression promoted cardiomyocyte hypertrophy by suppressing adenylosuccinate lyase (ADSL)-mediated adenosine 5'-monophosphate (AMP) generation, which further enhanced the activation of the mammalian target of rapamycin complex 1 pathway by reducing AMP-activated kinase activity. Hairy and enhancer of split 1 silencing abrogated hN2ICD-induced cardiomyocyte hypertrophy by increasing Adsl transcription. Importantly, pharmacological activation of AMP-activated kinase ameliorated cardiac hypertrophy and dysfunction in hN2ICD-Tg^CM mice. The frameshift mutation in Notch2 exon 34 (c.6426dupT), which causes early-onset HCS, induces AC16 human cardiomyocyte hypertrophy through suppressing ADSL-mediated AMP generation. Thus, targeting Notch2-mediated purine nucleotide metabolism may be an attractive therapeutic approach to heart failure treatment.

Disruption of acylcarnitine homeostasis results in life-threatening outcomes in humans. Carnitine-acylcarnitine translocase deficiency (CACTD) is a scarce autosomal recessive genetic disease and may result in patients' death due to heart arrest or respiratory insufficiency. However, the reasons and mechanism of CACTD inducing respiratory insufficiency have never been elucidated. Herein, we employed lipidomic techniques to create comprehensive lipidomic maps of entire lungs throughout both prenatal and postnatal developmental stages in mice. We found that the acylcarnitines manifested notable variations and coordinated the expression levels of carnitine-acylcarnitine translocase (Cact) across these lung developmental stages. Cact-null mice were all dead with a symptom of respiratory distress and exhibited failed lung development. Loss of Cact resulted in an accumulation of palmitoyl-carnitine (C16-acylcarnitine) in the lungs and promoted the proliferation of mesenchymal progenitor cells. Mesenchymal cells with elevated C16-acylcarnitine levels displayed minimal changes in energy metabolism but, upon investigation, revealed an interaction with sterile alpha motif domain and histidine-aspartate domain-containing protein 1 (Samhd1), leading to decreased protein abundance and enhanced cell proliferation. Thus, our findings present a mechanism addressing respiratory distress in CACTD, offering a valuable reference point for both the elucidation of pathogenesis and the exploration of treatment strategies for neonatal respiratory distress.

Cell therapy is a promising strategy for acute liver failure (ALF), while its therapeutic efficacy is often limited by cell loss and poor arrangement. Here, inspired by liver microunits, we propose a novel spatially ordered multicellular lobules for the ALF treatment by using a microfluidic continuous spinning technology. The microfluidics with multiple microchannels was constructed by assembling parallel capillaries. Sodium alginate (Alg) solution encapsulating human umbilical vein endothelial cells (HUVECs), hepatocytes, and mesenchymal stem cells (MSCs) are introduced into the middle channel and the 6 parallel outer channels of the microfluidics, respectively. Simultaneously, Ca²⁺-loaded solutions are pumped through the innermost and outermost channels, forming a hollow microfiber with hepatocytes and MSCs alternately surrounding the HUVECs. These microfibers could highly resemble the cord-like structure of liver lobules, bringing about outstanding liver-like functions. We have demonstrated that in ALF rats, our biomimetic lobules can effectively suppress excessive inflammatory responses, decrease cell necrosis, and promote regenerative pathways, leading to satisfied therapeutic efficacy. These findings underscore the potential of spatially ordered multicellular microfibers in treating related diseases and improving traditional clinical methods.

Takeover safety draws increasing attention in the intelligent transportation as the new energy vehicles with cutting-edge autopilot capabilities vigorously blossom on the road. Despite recent studies highlighting the importance of drivers' emotions in takeover safety, the lack of emotion-aware takeover datasets hinders further investigation, thereby constraining potential applications in this field. To this end, we introduce ViE-Take, the first Vision-driven (Vision is used since it constitutes the most cost-effective and user-friendly solution for commercial driver monitor systems) dataset for exploring the Emotional landscape in Takeovers of autonomous driving. ViE-Take enables a comprehensive exploration of the impact of emotions on drivers' takeover performance through 3 key attributes: multi-source emotion elicitation, multi-modal driver data collection, and multi-dimensional emotion annotations. To aid the use of ViE-Take, we provide 4 deep models (corresponding to 4 prevalent learning strategies) for predicting 3 different aspects of drivers' takeover performance (readiness, reaction time, and quality). These models offer benefits for various downstream tasks, such as driver emotion recognition and regulation for automobile manufacturers. Initial analysis and experiments conducted on ViE-Take indicate that (a) emotions have diverse impacts on takeover performance, some of which are counterintuitive; (b) highly expressive social media clips, despite their brevity, prove effective in eliciting emotions (a foundation for emotion regulation); and (c) predicting takeover performance solely through deep learning on vision data not only is feasible but also holds great potential.

Plant diseases caused by vegetable viruses are an important threat to global food security, presenting a major challenge for the development of antiviral agrochemicals. Functional proteins of plant viruses play a crucial role in the viral life cycle, and targeted inhibition of these proteins has emerged as a promising strategy. However, the current discovery of antiviral small molecules is hampered by the limitations of synthetic approaches and the narrow range of targets. Herein, we report a practical application of organocatalysis for serving pesticide discovery that bears a unique molecular basis. An N-heterocyclic carbene-modulated reaction is first designed to asymmetrically functionalize diverse natural phenols with phthalides. Our designed method is capable of producing a series of new phthalidyl ethers under mild conditions with good yields, enantioselectivity, and functional group tolerance. Among these, compound (R)-3w exhibits excellent and enantioselectivity-preferred curative activity against potato virus Y (PVY). Mechanistically, it is proposed that (R)-3w interacts with the nuclear inclusion body A (Nia) protein of PVY at the His150 residue. This binding impairs Nia's function to cleavage polyprotein, thereby inhibiting formation of viral replication complex. The study provides insights into advancing synthetic protocol to facilitate agrochemical discovery, and our identified (R)-3w may serve as a potential lead for future research and development PVY-Nia inhibitors.

Since the scarcity of bandwidth resources has become increasingly critical in modern communication systems, orbital angular momentum (OAM) with a higher degree of freedom in information modulation has become a promising solution to alleviate the shortage of spectrum resources. Consequently, the integration of OAM with millimeter-wave technology has emerged as a focal point in next-generation communication research. Recently, programmable metasurfaces have gained considerable attention as essential devices for OAM generation due to real-time tunability, but their profiles are relatively high as a result of the external feed source. This paper proposes a conformal radiation-type programmable metasurface operating in the millimeter-wave band. By employing a series-parallel hybrid feed network to replace conventional external feed sources, the overall profile of the metasurface system can be reduced to less than 0.1λ. Furthermore, the proposed innovation design could also achieve a conformal cross-shaped architecture, which is ultraportable and very effective in integrating with the front ends of satellites or aircraft and eliminating issues such as feed source blockage as well as energy spillover losses in conventional metasurfaces. The proposed metasurface could achieve a realized gain of 22.54 dB with an aperture efficiency of 21.75%, thus generating high-purity OAM waves with topological charges of l = 0, l = +1, l = +2, and l = +3. Additionally, by incorporating beam scanning techniques, OAM waves could be deflected to accommodate scenarios with moving receivers, demonstrating substantial potential for future high-speed wireless communication applications.

The metaverse enables immersive virtual healthcare environments, presenting opportunities for enhanced care delivery. A key challenge lies in effectively combining multimodal healthcare data and generative artificial intelligence abilities within metaverse-based healthcare applications, which is a problem that needs to be addressed. This paper proposes a novel multimodal learning framework for metaverse healthcare, MMLMH, based on collaborative intra- and intersample representation and adaptive fusion. Our framework introduces a collaborative representation learning approach that captures shared and modality-specific features across text, audio, and visual health data. By combining modality-specific and shared encoders with carefully formulated intrasample and intersample collaboration mechanisms, MMLMH achieves superior feature representation for complex health assessments. The framework's adaptive fusion approach, utilizing attention mechanisms and gated neural networks, demonstrates robust performance across varying noise levels and data quality conditions. Experiments on metaverse healthcare datasets demonstrate MMLMH's superior performance over baseline methods across multiple evaluation metrics. Longitudinal studies and visualization further illustrate MMLMH's adaptability to evolving virtual environments and balanced performance across diagnostic accuracy, patient-system interaction efficacy, and data integration complexity. The proposed framework has a unique advantage in that a similar level of performance is maintained across various patient populations and virtual avatars, which could lead to greater personalization of healthcare experiences in the metaverse. MMLMH's successful functioning in such complicated circumstances suggests that it can combine and process information streams from several sources. They can be successfully utilized in next-generation healthcare delivery through virtual reality.

Exosomes (Exos) are emerging as noninvasive biomarkers for diagnosis and progression monitoring of gastric cancer (GC). However, the heterogeneity discrimination and ultrasensitive quantification of Exos presents a considerable analytical challenge, thereby impeding severely their clinical application. Herein, we propose an integrated terahertz metasensing platform for the discrimination of Exos in distinct subtypes of GC in a single step-through the simultaneous evaluation of the category and richness level of Exos membrane proteins. Characterized by dual-sided independent sensing capabilities with enhanced sensitivity (169 and 325 GHz per refractive index unit, respectively), the metasensor functionalized with antibodies simultaneously reflects the content of 2 membrane proteins in the terahertz spectral response. Our approach concurrently completes accurate differentiation and precise quantification of GC-subtype Exos by integrating dual-sided sensing information in merely a single assay. The dual-sided sensing design enhances the reliability of detection results. Moreover, combined with the signal amplification of gold nanoparticles, the platform experimentally demonstrates a superior dynamic response to Exos concentrations spanning from 1 × 10⁴ to 1 × 10⁸ particles/ml, with the limit of detection being 1 × 10⁴ particles/ml. This work provides new insights into multisensing metasurface design and paves the way for precise and personalized cancer treatment through the specific sensing of Exos.

Cardiovascular diseases constitute a marked threat to global health, and the emergence of spatial omics technologies has revolutionized cardiovascular research. This review explores the application of spatial omics, including spatial transcriptomics, spatial proteomics, spatial metabolomics, spatial genomics, and spatial epigenomics, providing more insight into the molecular and cellular foundations of cardiovascular disease and highlighting the critical contributions of spatial omics to cardiovascular science, and discusses future prospects, including technological advancements, integration of multi-omics, and clinical applications. These developments should contribute to the understanding of cardiovascular diseases and guide the progress of precision medicine, targeted therapies, and personalized treatments.