Mutual regulation of microglia and astrocytes after Gas6 inhibits spinal cord injury.

JOURNAL/nrgr/04.03/01300535-202502000-00032/figure1/v/2024-05-28T214302Z/r/image-tiff Invasive inflammation and excessive scar formation are the main reasons for the difficulty in repairing nervous tissue after spinal cord injury. Microglia and astrocytes play key roles in the spinal cord injury micro-environment and share a close interaction. However, the mechanisms involved remain unclear. In this study, we found that after spinal cord injury, resting microglia (M0) were polarized into pro-inflammatory phenotypes (MG1 and MG3), while resting astrocytes were polarized into reactive and scar-forming phenotypes. The expression of growth arrest-specific 6 (Gas6) and its receptor Axl were significantly down-regulated in microglia and astrocytes after spinal cord injury. In vitro experiments showed that Gas6 had negative effects on the polarization of reactive astrocytes and pro-inflammatory microglia, and even inhibited the cross-regulation between them. We further demonstrated that Gas6 can inhibit the polarization of reactive astrocytes by suppressing the activation of the Yes-associated protein signaling pathway. This, in turn, inhibited the polarization of pro-inflammatory microglia by suppressing the activation of the nuclear factor-κB/p65 and Janus kinase/signal transducer and activator of transcription signaling pathways. In vivo experiments showed that Gas6 inhibited the polarization of pro-inflammatory microglia and reactive astrocytes in the injured spinal cord, thereby promoting tissue repair and motor function recovery. Overall, Gas6 may play a role in the treatment of spinal cord injury. It can inhibit the inflammatory pathway of microglia and polarization of astrocytes, attenuate the interaction between microglia and astrocytes in the inflammatory microenvironment, and thereby alleviate local inflammation and reduce scar formation in the spinal cord.

Pyroptosis and mitochondrial function participated in miR-654-3p-protected against myocardial infarction.

Myocardial infarction (MI) is one of the leading causes of heart failure with highly complicated pathogeneses. miR-654-3p has been recognized as a pivotal regulator of controlling cell survival. However, the function of miR-654-3p in cardiomyocytes and MI has yet to be reported. This study aimed to identify the role of miR-654-3p in the regulation of myocardial infarction. To understand the contribution of miR-654-3p on heart function, we generated cardiac-specific knockdown and overexpression mice using AAV9 technology in MI injury. Mechanically, we combined cellular and molecular techniques, pharmaceutical treatment, RNA sequencing, and functional testing to elucidate the potential pathological mechanisms. We identified that mice subjected to MI decreased the expression of miR-654-3p in the border and infarcted area. Mice lacking miR-654-3p in the heart showed some inflammation infiltration and myocardial fibrosis, resulting in a mild cardiac injury. Furthermore, we found a deficiency of miR-654-3p in cardiomyocytes resulted in pyroptotic cell death but not other programmed cell death. Intriguingly, miR-654-3p deficiency aggravated MI-induced cardiac dysfunction, accompanied by higher myocardial fibrosis and cardiac enzymes and augmented pyroptosis activation. Cardiac elevating miR-654-3p prevented myocardial fibrosis and inflammation infiltration and decreased pyroptosis profile, thereby attenuating MI-induced cardiac damage. Using RNA sequence and molecular biological approaches, we found overexpression of miR-654-3p in the heart promoted the metabolic ability of the cardiomyocytes by promoting mitochondrial metabolism and mitochondrial respiration function. Our finding identified the character of miR-654-3p in protecting against MI damage by mediating pyroptosis and mitochondrial metabolism. These findings provide a new mechanism for miR-654-3p involvement in the pathogenesis of MI and reveal novel therapeutic targets. miR-654-3p expression was decreased after MI. Mice lacking miR-654-3p in the heart showed some inflammation infiltration and myocardial fibrosis, resulting in a mild cardiac injury. The deficiency of miR-654-3p in cardiomyocytes resulted in pyroptotic cell death. miR-654-3p deficiency aggravated MI-induced cardiac dysfunction, accompanied by higher myocardial fibrosis and cardiac enzymes and augmented pyroptosis activation. Overexpression of miR-654-3p prevented myocardial fibrosis and inflammation infiltration and decreased pyroptosis profile, thereby attenuating MI-induced cardiac damage. Overexpression of miR-654-3p in the heart promoted the metabolic ability of the cardiomyocytes by promoting mitochondrial metabolism and mitochondrial respiration function.

Longitudinally consistent registration and parcellation of cortical surfaces using semi-supervised learning.

Temporally consistent and accurate registration and parcellation of longitudinal cortical surfaces is of great importance in studying longitudinal morphological and functional changes of human brains. However, most existing methods are developed for registration or parcellation of a single cortical surface. When applying to longitudinal studies, these methods independently register/parcellate each surface from longitudinal scans, thus often generating longitudinally inconsistent and inaccurate results, especially in small or ambiguous cortical regions. Essentially, longitudinal cortical surface registration and parcellation are highly correlated tasks with inherently shared constraints on both spatial and temporal feature representations, which are unfortunately ignored in existing methods. To this end, we unprecedentedly propose a novel semi-supervised learning framework to exploit these inherent relationships from limited labeled data and extensive unlabeled data for more robust and consistent registration and parcellation of longitudinal cortical surfaces. Our method utilizes the spherical topology characteristic of cortical surfaces. It employs a spherical network to function as an encoder, which extracts high-level cortical features. Subsequently, we build two specialized decoders dedicated to the tasks of registration and parcellation, respectively. To extract more meaningful spatial features, we design a novel parcellation map similarity loss to utilize the relationship between registration and parcellation tasks, i.e., the parcellation map warped by the deformation field in registration should match the atlas parcellation map, thereby providing extra supervision for the registration task and augmented data for parcellation task by warping the atlas parcellation map to unlabeled surfaces. To enable temporally more consistent feature representation, we additionally enforce longitudinal consistency among longitudinal surfaces after registering them together using their concatenated features. Experiments on two longitudinal datasets of infants and adults have shown that our method achieves significant improvements on both registration/parcellation accuracy and longitudinal consistency compared to existing methods, especially in small and challenging cortical regions.

Unlocking Mixed-Metal Oxides Active Centers via Acidity Regulation for K&SO2 Poisoning Resistance: Self-Detoxification Mechanism of Zeolite-Confined deNOx Catalysts.

Selective catalytic reduction of nitrogen oxides (NOx) with ammonia (NH3-SCR) is an efficient NOx reduction strategy, while the denitrification (deNOx) catalysts suffer from serious deactivation due to the coexistence of multiple poisoning substances, such as alkali metal (e.g., K), SO2, etc., in industrial flue gases. It is essential to understand the interaction among various poisons and their effects on the deNOx process. Herein, the ZSM-5 zeolite-confined MnSmOx mixed (MnSmOx@ZSM-5) catalyst exhibited better deNOx performance after the poisoning of K, SO2, and/or K&SO2 than the MnSmOx and MnSmOx/ZSM-5 catalysts, the deNOx activity of which at high temperature (H-T) increased significantly (>90% NOx conversion in the range of 220-480 °C). It has been demonstrated that K would occupy both redox and acidic sites, which severely reduced the reactivity of MnSmOx/ZSM-5 catalysts. The most important, K element is preferentially deposited at -OH on the surface of ZSM-5 carrier due to the electrostatic attraction (-O-K). As for the K&SO2 poisoning catalyst, SO2 preferred to be combined with the surface-deposited K (-O-K-SO2ads) according to XPS and density functional theory (DFT) results, the poisoned active sites by K would be released. The K migration behavior was induced by SO2 over K-poisoned MnSmOx@ZSM-5 catalysts, and the balance of surface redox and acidic site was regulated, like a synergistic promoter, which led to K-poisoning buffering and activity recovery. This work contributes to the understanding of the self-detoxification interaction between alkali metals (e.g., K) and SO2 on deNOx catalysts and provides a novel strategy for the adaptive use of one poisoning substance to counter another for practical NOx reduction.

Lithium Pollution and Its Associated Health Risks in the Largest Lithium Extraction Industrial Area in China.

Lithium (Li) is an important resource that drives sustainable mobility and renewable energy. Its demand is projected to continue to increase in the coming decades. However, the risk of Li pollution has also emerged as a global concern. Here, we investigated the pollution characteristics, sources, exposure levels, and associated health risks of Li in the Jinjiang River basin, the largest area for Li2CO3 production in China. Our results revealed the dominant role of Li extraction activities in the pollution of the river, with over 95% of dissolved Li in downstream river water being emitted from this source. Moreover, the Li concentration in aquatic plants (i.e., water hyacinth) and animals (i.e., fish) significantly increased from upstream to downstream areas, indicating a significant risk to local aquatic ecosystems. More importantly, our study found that local residents were suffering potential chronic noncarcinogenic health risks primarily from consuming contaminated water and vegetables. We also investigated the pollution characteristics of associated elements present in Li ores (e.g., Rb, Cs, Ni, and F-). By uncovering the remarkable impact of Li extraction activities on the Li content in ecosystems for the first time, our study emphasizes the importance of evaluating Li pollution from Li-related industrial activities, including mining, extraction, and recovery.

Insights Into Pre-aggregation Control of Y-series Non-fullerene Acceptors in Liquid State for Highly Efficient Binary Organic Solar Cells.

Leveraging breakthroughs in Y-series non-fullerene acceptors (NFAs), organic solar cells (OSCs) have achieved impressive power conversion efficiencies (PCEs) exceeding 19%. However, progress in advancing OSCs has decelerated due to constraints in realizing the full potential of the Y-series NFAs. Herein, a simple yet effective solid additive-induced pre-aggregation control method employing 2-chloro-5-iodopyridine (PDCI) is reported to unlock the full potential of the Y-series NFAs. Specifically, PDCI interacts predominantly with Y-series NFAs enabling enhanced and ordered phase-aggregation in solution. This method leads to a notable improvement and a red-shifted absorption of the acceptor phase during film formation, along with improved crystallinity. Moreover, the PDCI-induced pre-aggregation of NFAs in the solution enables ordered molecule packing during the film-formation process through delicate intermediate states transition. Consequently, the PDCI-induced pre-aggregated significantly improves the PCE of PM6:Y6 OSCs from 16.12% to 18.12%, among the best values reported for PM6:Y6 OSCs. Importantly, this approach is universally applicable to other Y-series NFA-based OSCs, achieving a champion PCE of 19.02% for the PM6:BTP-eC9 system. Thus, our pre-aggregation control strategy further unlocks the potential of Y-series NFAs, offering a promising avenue for enhancing the photovoltaic performance of Y-series NFA-based OSCs. This article is protected by copyright. All rights reserved.

Navigating the environmental dynamics, toxicity to aquatic organisms and human associated risks of an emerging tire wear contaminant 6PPD quinone.

N-1,3-Dimethylbutyl-N'-phenyl-p-quinone diamine (6PPDQ) is a derivative of 6PPD, a synthetic antioxidant used in tire manufacturing to control the degradation caused by oxidation and heat aging. Its discovery in 2020 has raised important environmental concern, particularly regarding its association with acute mortality in coho salmon, prompting surge in research on its occurrence, fate, and transport in aquatic ecosystems. Despite this attention, there remain notable gaps in grasping the knowledge, demanding an in depth overview. Thus, this review consolidates recent studies to offer a thorough investigation of 6PPDQ's environmental dynamics, pathways into aquatic ecosystems, toxicity to aquatic organisms, and human health implications. Various aquatic species exhibit differential susceptibility to 6PPDQ toxicity, manifesting in acute mortalities, disruption of metabolic pathways, oxidative stress, behavioral responses, and developmental abnormalities. Whereas, understanding the species-specific responses, molecular mechanisms, and broader ecological implications requires further investigation across disciplines such as ecotoxicology, molecular biology, and environmental chemistry. Integration of findings emphasizes the complexity of 6PPDQ toxicity and its potential risks to human health. However, urgent priorities should be given to the measures like long-term monitoring studies to evaluate the chronic effects on aquatic ecosystems and the establishment of standardized toxicity testing protocols to ensure the result comparability and reproducibility. This review serves as a vital resource for researchers, policymakers, and environmental professionals seeking appraisals into the impacts of 6PPDQ contamination on aquatic ecosystems and human health.

HOT-GAN: Hilbert Optimal Transport for Generative Adversarial Network.

Generative adversarial network (GAN) has achieved remarkable success in generating high-quality synthetic data by learning the underlying distributions of target data. Recent efforts have been devoted to utilizing optimal transport (OT) to tackle the gradient vanishing and instability issues in GAN. They use the Wasserstein distance as a metric to measure the discrepancy between the generator distribution and the real data distribution. However, most optimal transport GANs define loss functions in Euclidean space, which limits their capability in handling high-order statistics that are of much interest in a variety of practical applications. In this article, we propose a computational framework to alleviate this issue from both theoretical and practical perspectives. Particularly, we generalize the optimal transport-based GAN from Euclidean space to the reproducing kernel Hilbert space (RKHS) and propose Hilbert Optimal Transport GAN (HOT-GAN). First, we design HOT-GAN with a Hilbert embedding that allows the discriminator to tackle more informative and high-order statistics in RKHS. Second, we prove that HOT-GAN has a closed-form kernel reformulation in RKHS that can achieve a tractable objective under the GAN framework. Third, HOT-GAN's objective enjoys the theoretical guarantee of differentiability with respect to generator parameters, which is beneficial to learn powerful generators via adversarial kernel learning. Extensive experiments are conducted, showing that our proposed HOT-GAN consistently outperforms the representative GAN works.

Global profiling of functional histidines in live cells using small-molecule photosensitizer and chemical probe relay labelling.

Recent advances in chemical proteomics have focused on developing chemical probes that react with nucleophilic amino acid residues. Although histidine is an attractive candidate due to its importance in enzymatic catalysis, metal binding and protein-protein interaction, its moderate nucleophilicity poses challenges. Its modification is frequently influenced by cysteine and lysine, which results in poor selectivity and narrow proteome coverage. Here we report a singlet oxygen and chemical probe relay labelling method that achieves high selectivity towards histidine. Libraries of small-molecule photosensitizers and chemical probes were screened to optimize histidine labelling, enabling histidine profiling in live cells with around 7,200 unique sites. Using NMR spectroscopy and X-ray crystallography, we characterized the reaction mechanism and the structures of the resulting products. We then applied this method to discover unannotated histidine sites key to enzymatic activity and metal binding in select metalloproteins. This method also revealed the accessibility change of histidine mediated by protein-protein interaction that influences select protein subcellular localization, underscoring its capability in discovering functional histidines.

Cang-ai volatile oil alleviates nasal inflammation via Th1/Th2 cell imbalance regulation in a rat model of ovalbumin-induced allergic rhinitis.

We previously revealed that Cang-ai volatile oil (CAVO) regulates T-cell activity, enhancing the immune response in people with chronic respiratory diseases. However, the effects of CAVO on allergic rhinitis (AR) have not been investigated. Herein, we established an ovalbumin (OVA)-induced AR rat model to determine these effects. Sprague-Dawley (SD) rats were exposed to OVA for 3 weeks. CAVO or loratadine (positive control) was given orally once daily for 2 weeks to OVA-exposed rats. Behavior modeling nasal allergies was observed. Nasal mucosa, serum, and spleen samples of AR rats were analyzed. CAVO treatment significantly reduced the number of nose rubs and sneezes, and ameliorated several hallmarks of nasal mucosa tissue remodeling: inflammation, eosinophilic infiltration, goblet cell metaplasia, and mast cell hyperplasia. CAVO administration markedly upregulated expressions of interferon-γ, interleukin (IL)-2, and IL-12, and downregulated expressions of serum tumor necrosis factor-α, IL-4, IL-5, IL-6, IL-13, immunoglobulin-E, and histamine. CAVO therapy also increased production of IFN-γ and T-helper type 1 (Th1)-specific T-box transcription factor (T-bet) of the cluster of differentiation-4+ T-cells in splenic lymphocytes, and protein and mRNA expressions of T-bet in nasal mucosa. In contrast, levels of the Th2 cytokine IL-4 and Th2-specific transcription factor GATA binding protein-3 were suppressed by CAVO. These cumulative findings demonstrate that CAVO therapy can alleviate AR by regulating the balance between Th1 and Th2 cells.

Expert consensus on One Health for establishing an enhanced and integrated surveillance system for key infectious diseases.

China has been continuously improving its monitoring methods and strategies to address key infectious diseases (KIDs). After the severe acute respiratory syndrome epidemic in 2003, China established a comprehensive reporting system for infectious diseases (IDs) and public health emergencies. The relatively lagging warning thresholds, limited warning information, and outdated warning technology are insufficient to meet the needs of comprehensive monitoring for modern KIDs. Strengthening early monitoring and warning capabilities to enhance the public health system has become a top priority, with increasing demand for early warning thresholds, information, and techniques, thanks to constant innovation and development in molecular biology, bioinformatics, artificial intelligence, and other identification and analysis technologies. A panel of 31 experts has recommended a fourth-generation comprehensive surveillance system targeting KIDs (41 notifiable diseases and emerging IDs). The aim of this surveillance system is to systematically monitor the epidemiology and causal pathogens of KIDs in hosts such as humans, animals, and vectors, along with associated environmental pathogens. By integrating factors influencing epidemic spread and risk assessment, the surveillance system can serve to detect, predict, and provide early warnings for the occurrence, development, variation, and spread of known or novel KIDs. Moreover, we recommend comprehensive ID monitoring based on the fourth-generation surveillance system, along with a data-integrated monitoring and early warning platform and a consortium pathogen detection technology system. This series of considerations is based on systematic and comprehensive monitoring across multiple sectors, dimensions, factors, and pathogens that is supported by data integration and connectivity. This expert consensus will provides an opportunity for collaboration in various fields and relies on interdisciplinary application to enhance comprehensive monitoring, prediction, and early warning capabilities for the next generation of ID surveillance. This expert consensus will serve as a reference for ID prevention and control as well as other related activities.

Molecular distinctions of bronchoalveolar and alveolar organoids under differentiation conditions.

The bronchoalveolar organoid (BAO) model is increasingly acknowledged as an ex-vivo platform that accurately emulates the structural and functional attributes of proximal airway tissue. The transition from bronchoalveolar progenitor cells to alveolar organoids is a common event during the generation of BAOs. However, there is a pressing need for comprehensive analysis to elucidate the molecular distinctions characterizing the pre-differentiated and post-differentiated states within BAO models. This study established a murine BAO model and subsequently triggered its differentiation. Thereafter, a suite of multidimensional analytical procedures was employed, including the morphological recognition and examination of organoids utilizing an established artificial intelligence (AI) image tracking system, quantification of cellular composition, proteomic profiling and immunoblots of selected proteins. Our investigation yielded a detailed evaluation of the morphologic, cellular, and molecular variances demarcating the pre- and post-differentiation phases of the BAO model. We also identified of a potential molecular signature reflective of the observed morphological transformations. The integration of cutting-edge AI-driven image analysis with traditional cellular and molecular investigative methods has illuminated key features of this nascent model.

IFI16 promotes the progression of clear cell renal cell carcinoma through the IL6/PI3K/AKT axis.

BACKGROUND: Clear cell renal cell carcinoma (ccRCC) is a common disease in the urinary system, with a high incidence and poor prognosis in advanced stages. Although γ-interferon-inducible protein 16 (IFI16) has been reported to play a role in various tumors, its involvement in ccRCC remains poorly documented, and the molecular mechanisms are not yet clear. METHODS: We conducted bioinformatics analysis to study the expression of IFI16 in ccRCC using public databases. Additionally, we analyzed and validated clinical specimens that we collected. Subsequently, we explored the impact of IFI16 on ccRCC cell proliferation, migration, and invasion through in vitro and in vivo experiments. Furthermore, we predicted downstream molecules and pathways using transcriptome analysis and confirmed them through follow-up experimental validation. RESULTS: IFI16 was significantly upregulated in ccRCC tissue and correlated with poor patient prognosis. In vitro, IFI16 promoted ccRCC cell proliferation, migration, and invasion, while in vivo, it facilitated subcutaneous tumor growth and the formation of lung metastatic foci. Knocking down IFI16 suppressed its oncogenic function. At the molecular level, IFI16 promoted the transcription and translation of IL6, subsequently activating the PI3K/AKT signaling pathway and inducing epithelial-mesenchymal transition (EMT). CONCLUSION: IFI16 induced EMT through the IL6/PI3K/AKT axis, promoting the progression of ccRCC.

Interstitial Fluid Shear Stress Induces the Synthetic Phenotype Switching of VSMCs to Release Pro-calcified Extracellular Vesicles via EGFR-MAPK-KLF5 Pathway.

Phenotypic switching (from contractile to synthetic) of vascular smooth muscle cells (VSMCs) is essential in the progression of atherosclerosis. The damaged endothelium in the atherosclerotic artery exposes VSMCs to increased interstitial fluid shear stress (IFSS). However, the precise mechanisms by which increased IFSS influences VSMCs phenotypic switching are unrevealed. Here, we employed advanced numerical simulations to calculate IFSS values accurately based on parameters acquired from patient samples. We then carefully investigated the phenotypic switching and extracellular vesicles (EVs) secretion of VSMCs under various IFSS conditions. By employing a comprehensive set of approaches, we found that VSMCs exhibited synthetic phenotype upon atherosclerotic IFSS. This synthetic phenotype is the upstream regulator for the enhanced secretion of pro-calcified EVs. Mechanistically, as a mechanotransducer, the epidermal growth factor receptor (EGFR) initiates the flow-based mechanical cues to MAPK signaling pathway, facilitating the nuclear accumulation of the transcription factor krüppel-like factor 5 (KLF5). Furthermore, pharmacological inhibiting either EGFR or MAPK signaling pathway blocks the nuclear accumulation of KLF5 and finally results in the maintenance of contractile VSMCs even under increased IFSS stimulation. Collectively, targeting this signaling pathway holds potential as a novel therapeutic strategy to inhibit VSMCs phenotypic switching and mitigate the progression of atherosclerosis.

Longitudinal ultrasound-based AI model predicts axillary lymph node response to neoadjuvant chemotherapy in breast cancer: a multicenter study.

OBJECTIVES: Developing a deep learning radiomics model from longitudinal breast ultrasound and sonographer's axillary ultrasound diagnosis for predicting axillary lymph node (ALN) response to neoadjuvant chemotherapy (NAC) in breast cancer. METHODS: Breast cancer patients undergoing NAC followed by surgery were recruited from three centers between November 2016 and December 2022. We collected ultrasound images for extracting tumor-derived radiomics and deep learning features, selecting quantitative features through various methods. Two machine learning models based on random forest were developed using pre-NAC and post-NAC features. A support vector machine integrated these data into a fusion model, evaluated via the area under the curve (AUC), decision curve analysis, and calibration curves. We compared the fusion model's performance against sonographer's diagnosis from pre-NAC and post-NAC axillary ultrasonography, referencing histological outcomes from sentinel lymph node biopsy or axillary lymph node dissection. RESULTS: In the validation cohort, the fusion model outperformed both pre-NAC (AUC: 0.899 vs. 0.786, p < 0.001) and post-NAC models (AUC: 0.899 vs. 0.853, p = 0.014), as well as the sonographer's diagnosis of ALN status on pre-NAC and post-NAC axillary ultrasonography (AUC: 0.899 vs. 0.719, p < 0.001). Decision curve analysis revealed patient benefits from the fusion model across threshold probabilities from 0.02 to 0.98. The model also enhanced sonographer's diagnostic ability, increasing accuracy from 71.9% to 79.2%. CONCLUSION: The deep learning radiomics model accurately predicted the ALN response to NAC in breast cancer. Furthermore, the model will assist sonographers to improve their diagnostic ability on ALN status before surgery. CLINICAL RELEVANCE STATEMENT: Our AI model based on pre- and post-neoadjuvant chemotherapy ultrasound can accurately predict axillary lymph node metastasis and assist sonographer's axillary diagnosis. KEY POINTS: Axillary lymph node metastasis status affects the choice of surgical treatment, and currently relies on subjective ultrasound. Our AI model outperformed sonographer's visual diagnosis on axillary ultrasound. Our deep learning radiomics model can improve sonographers' diagnosis and might assist in surgical decision-making.

Major changes in prevalence and genotypes of rotavirus diarrhea in Beijing, China after RV5 rotavirus vaccine introduction.

To analyze the epidemiological characteristics of group A rotavirus (RVA) diarrhea in Beijing between 2019 and 2022 and evaluate the effectiveness of the RV5 vaccine. Stool specimens were collected from patients with acute diarrhea, and RVA was detected and genotyped. The whole genome of RVA was sequenced by fragment amplification and Sanger sequencing. Phylogenetic trees were constructed using Bayesian and maximum likelihood methods. Descriptive epidemiological methods were used to analyze the characteristics of RVA diarrhea. Test-negative design was used to evaluate the vaccine effectiveness (VE) of the RV5. Compared with 2011-2018, RVA-positive rates in patients with acute diarrhea under 5 years of age and adults decreased significantly between 2019 and 2022, to 9.45% (249/634) and 3.66% (220/6016), respectively. The predominant genotype of RVA had changed from G9-VIP[8]-III between 2019 and 2021 to G8-VP[8]-III in 2022, and P[8] sequences from G8-VP[8]-III strains formed a new branch called P[8]-IIIb. The complete genotype of G8-VP[8]-III was G8-P[8]-I2-R2-C2-M2-A2-N2-T2-E2-H2. The VE of 3 doses of RV5 was 90.4% (95% CI: 28.8%-98.7%) against RVA diarrhea. The prevalence of RVA decreased in Beijing between 2019 and 2022, and the predominant genotype changed to G8P[8], which may be related to RV5 vaccination. Continuous surveillance is necessary to evaluate vaccine effectiveness and improve vaccine design.

Early autism diagnosis based on path signature and Siamese unsupervised feature compressor.

Autism spectrum disorder has been emerging as a growing public health threat. Early diagnosis of autism spectrum disorder is crucial for timely, effective intervention and treatment. However, conventional diagnosis methods based on communications and behavioral patterns are unreliable for children younger than 2 years of age. Given evidences of neurodevelopmental abnormalities in autism spectrum disorder infants, we resort to a novel deep learning-based method to extract key features from the inherently scarce, class-imbalanced, and heterogeneous structural MR images for early autism diagnosis. Specifically, we propose a Siamese verification framework to extend the scarce data, and an unsupervised compressor to alleviate data imbalance by extracting key features. We also proposed weight constraints to cope with sample heterogeneity by giving different samples different voting weights during validation, and used Path Signature to unravel meaningful developmental features from the two-time point data longitudinally. We further extracted machine learning focused brain regions for autism diagnosis. Extensive experiments have shown that our method performed well under practical scenarios, transcending existing machine learning methods and providing anatomical insights for autism early diagnosis.

Surface-Enriched Room-Temperature Liquid Bismuth for Catalytic CO2 Reduction.

Bismuth-based electrocatalysts are effective for carbon dioxide (CO2) reduction to formate. However, at room temperature, these materials are only available in solid state, which inevitably suffers from surface deactivation, declining current densities, and Faradaic efficiencies. Here, the formation of a liquid bismuth catalyst on the liquid gallium surface at ambient conditions is shown as its exceptional performance in the electrochemical reduction of CO2 (i.e., CO2RR). By doping a trace amount of bismuth (740 ppm atomic) in gallium liquid metal, a surface enrichment of bismuth by over 400 times (30 at%) in liquid state is obtained without atomic aggregation, achieving 98% Faradic efficiency for CO2 conversion to formate over 80 h. Ab initio molecular simulations and density functional theory calculations reveal that bismuth atoms in the liquid state are the most energetically favorable sites for the CO2RR intermediates, superior to solid Bi-sites, as well as joint GaBi-sites. This study opens an avenue for fabricating high-performing liquid-state metallic catalysts that cannot be reached by elementary metals under electrocatalytic conditions.

Optimizing focus: switchable modes and sub-diffraction spots in inverse circular Airy beams.

We report an experimental investigation into the tight-focusing characteristics of linearly polarized inverse circular Airy beams (ICABs). Our study reveals that tightly focused ICABs exhibit Bessel-like, needle-like, or dual foci profiles depending on whether the main ring's radius is smaller than, equal to, or larger than the critical radius. The emergence of the dual foci structure is attributed to the constrained entrance aperture of the microscope objective (MO). In contrast to traditional Gaussian beams (GBs), ICABs demonstrate remarkable advantages in terms of focal spot size. Notably, we observe a focal spot with a size of 245 nm, representing a 26.4% reduction compared to the diffraction limit. These unique properties open up promising avenues for potential applications in optical multi-plane particle trapping, conveying, and super-resolution optical imaging.

PEG-crosslinked O-carboxymethyl chitosan films with degradability and antibacterial activity for food packaging.

This study developed a kind of PEG-crosslinked O-carboxymethyl chitosan (O-CMC-PEG) with various PEG content for food packaging. The crosslinking agent of isocyanate-terminated PEG was firstly synthesized by a simple condensation reaction between PEG and excess diisocyanate, then the crosslink between O-carboxymethyl chitosan (O-CMC) and crosslinking agent occurred under mild conditions to produce O-CMC-PEG with a crosslinked structure linked by urea bonds. FT-IR and 1H NMR techniques were utilized to confirm the chemical structures of the crosslinking agent and O-CMC-PEGs. Extensive research was conducted to investigate the impact of the PEG content (or crosslinking degree) on the physicochemical characteristics of the casted O-CMC-PEG films. The results illuminated that crosslinking and components compatibility could improve their tensile features and water vapor barrier performance, while high PEG content played the inverse effects due to the microphase separation between PEG and O-CMC segments. The in vitro degradation rate and water sensitivity primarily depended on the crosslinking degree in comparison with the PEG content. Furthermore, caused by the remaining -NH2 groups of O-CMC, the films demonstrated antibacterial activity against Escherichia coli and Staphylococcus aureus. When the PEG content was 6% (medium crosslinking degree), the prepared O-CMC-PEG-6% film possessed optimal tensile features, high water resistance, appropriate degradation rate, low water vapor transmission rate and fine broad-spectrum antibacterial capacity, manifesting a great potential for application in food packaging to extend the shelf life.