Lithium-Ion-Doped Eutectogel for Surface-Capacitive Sensing Touch Panel.

Touch panels are deemed as a critical platform for the future of human--computer interaction. Recently, flexible touch panels have attracted much attention due to their superior adhesivity and integratability to the human body. However, hydrogel- or organogel-based devices suffer from instability due to liquid evaporation or low-conductivity substrates. It demands an alternative functional touch panel featuring temperature tolerance, high conductivity, and stretchability. Here, we introduce an eutectogel by immobilizing a novel deep eutectic solvent (DES) within 2-hydroxyethyl acrylate (HEA) covalently cross-linked polymer scaffolds. In this DES (ethylene carbonate(EC)-LiTFSI), the C═O group of EC is unique as an electron donor exhibiting strong coordination interactions with Li+, promoting the dissociation of Li+ from LiTFSI to achieve excellent conductivity. Benefiting from their traits, eutectogel presents high conductivity, transmittance, antifreezing, and mechanical strength. In addition, using the surface-capacitive sensing mechanism, the eutectogel can be designed as a 1D strip and 2D rectangular touch panel which can achieve high-resolution touching tracks, even in a low-temperature environment and pressure-then-recovered state. This eutectogel strategy is envisioned to facilitate the development of next-generation intelligent devices, especially in extreme stretching and low-temperature application scenarios.

Formation of a Porous Crystalline Mg1‒ x Al2O y Overlayer on Metal Catalysts via Controlled Solid-State Reactions for High-temperature Stable Catalysis.

Catalyst deactivation by sintering and coking is a long-standing issue in metal-catalyzed harsh high-temperature hydrocarbon reactions. Ultrathin oxide coatings of metal nanocatalysts have recently appeared attractive to address this issue, while the porosity of the overlayer is difficult to control to preserve the accessibility of embedded metal nanoparticles, thus often leading to a large decrease in activity. Here, we report that a nanometer-thick alumina coating of MgAl2O4-supported metal catalysts followed by high-temperature reduction can transform a nonporous amorphous alumina overlayer into a porous Mg1‒xAl2Oy crystalline spinel structure with a pore size of 2‒3 nm and weakened acidity. The high porosity stems from the restrained Mg migration from the MgAl2O4 support to the alumina overlayer through solid-state reactions at high temperatures. The resulting Ni/MgAl2O4 and Pt/MgAl2O4 catalysts with a porous crystalline Mg1‒xAl2Oy overlayer achieved remarkably high stability while preserving much higher activity than the corresponding alumina-coated Ni and Pt catalysts on MgO and Al2O3 supports in the reactions of dry reforming of methane and propane dehydrogenation, respectively.

Feature fusion method for pulmonary tuberculosis patient detection based on cough sound.

Since the COVID-19, cough sounds have been widely used for screening purposes. Intelligent analysis techniques have proven to be effective in detecting respiratory diseases. In 2021, there were up to 10 million TB-infected patients worldwide, with an annual growth rate of 4.5%. Most of the patients were from economically underdeveloped regions and countries. The PPD test, a common screening method in the community, has a sensitivity of as low as 77%. Although IGRA and Xpert MTB/RIF offer high specificity and sensitivity, their cost makes them less accessible. In this study, we proposed a feature fusion model-based cough sound classification method for primary TB screening in communities. Data were collected from hospitals using smart phones, including 230 cough sounds from 70 patients with TB and 226 cough sounds from 74 healthy subjects. We employed Bi-LSTM and Bi-GRU recurrent neural networks to analyze five traditional feature sets including the Mel frequency cepstrum coefficient (MFCC), zero-crossing rate (ZCR), short-time energy, root mean square, and chroma_cens. The incorporation of features extracted from the speech spectrogram by 2D convolution training into the Bi-LSTM model enhanced the classification results. With traditional futures, the best TB patient detection result was achieved with the Bi-LSTM model, with 93.99% accuracy, 93.93% specificity, and 92.39% sensitivity. When combined with a speech spectrogram, the classification results showed 96.33% accuracy, 94.99% specificity, and 98.13% sensitivity. Our findings underscore that traditional features and deep features have good complementarity when fused using Bi LSTM modelling, which outperforms existing PPD detection methods in terms of both efficiency and accuracy.

Peroxidase like Zn doped Prussian blue facilitates salinity tolerance in winter wheat through seed dressing.

Salt stress severely limits the growth and yield of wheat in saline-alkali soil. While nanozymes have shown promise in mitigating abiotic stress by scavenging reactive oxygen species (ROS) in plants, their application in alleviating salt stress for wheat is still limited. This study synthesized a highly active nanozyme catalyst known as ZnPB (Zn-modified Prussian blue) to improve the yield and quality of wheat in saline soil. According to the Michaelis-Menten equation, ZnPB demonstrates exceptional peroxidase-like enzymatic activity, thereby mitigating oxidative damage caused by salt stress. Additionally, studies have shown that the ZnPB nanozyme is capable of regulating intracellular Na+ efflux and K+ retention in wheat, resulting in a decrease in proline and soluble protein levels while maintaining the integrity of macromolecules within the cell. Consequently, field experiments demonstrated that the ZnPB nanozyme increased winter wheat yield by 12.15 %, while also significantly enhancing its nutritional quality. This research offers a promising approach to improving the salinity tolerance of wheat, while also providing insights into its practical application.

Streptococcus pneumoniae endopeptidase O induces trained immunity and confers protection against various pathogenic infections.

Antibiotic resistance and the surge of infectious diseases during the pandemic present significant threats to human health. Trained immunity emerges as a promising and innovative approach to address these infections. Synthetic or natural fungal, parasitic and viral components have been reported to induce trained immunity. However, it is not clear whether bacterial virulence proteins can induce protective trained immunity. Our research demonstrates Streptococcus pneumoniae virulence protein PepO, is a highly potent trained immunity inducer for combating broad-spectrum infection. Our findings showcase that rPepO training confers robust protection to mice against various pathogenic infections by enhancing macrophage functionality. rPepO effectively re-programs macrophages, re-configures their epigenetic modifications and bolsters their immunological responses, which is independent of T or B lymphocytes. In vivo and in vitro experiments confirm that trained macrophage-secreted complement C3 activates peritoneal B lymphocyte and enhances its bactericidal capacity. In addition, we provide the first evidence that granulocyte colony-stimulating factor (G-CSF) derived from trained macrophages plays a pivotal role in shaping central-trained immunity. In summation, our research demonstrates the capability of rPepO to induce both peripheral and central trained immunity in mice, underscoring its potential application in broad-spectrum anti-infection therapy. Our research provides a new molecule and some new target options for infectious disease prevention.

Carbon coated Na3+xV2-xCux(PO4)3@C cathode for high-performance sodium ion batteries.

Na3V2(PO4)3 is considered as one of the most promising cathodes for sodium ion batteries owing to its fast Na+ diffusion, good structural stability and high working potential. However, its practical application is limited by its low intrinsic electronic conductivity. Herein, a carbon coated Cu2+-doped Na3V2(PO4)3 cathode was prepared. The carbon coating not only improve its apparent conductivity, but also inhibit crystal growth and prevent agglomeration of particles. Moreover, Cu2+ doping contributes to an enhanced intrinsic conductivity and decreased Na+ diffusion energy barrier, remarkably boosting its charge transfer kinetics. Based on the structure characterizations, electrochemical performances tests, charge transfer kinetics analyses and theoretical calculations, it's proved that such an elaborate design ensures the excellent rate performances (116.9 mA h g-1 at 0.1C; 92.6 mA h g-1 at 10C) and distinguished cycling lifespan (95.8 % retention after 300 cycles at 1C; 84.8 % retention after 3300 cycles at 10C). Besides, a two-phase reaction mechanism is also confirmed via in-situ XRD. This research is expected to promote the development of Na3V2(PO4)3-based sodium ion batteries with high energy/power density and excellent cycling lifespan.

Research Note: Analysis of microbial diversity on the shell surface of eggs collected from geographically distinct farms in China.

Micro-organisms on the eggshell surface of affect the quality of the egg. Sometimes, these microbes even pose a serious threat to the health of the egg's consumer. Bacterial 16S rDNA and fungal internal transcribed spacer region were sequenced to analyze the microbial diversity on the shell surface of the eggs collected from 4 distinct regions of China: Guyuan (GY; 1.5 million hens), Langfang (LF; 0.1 million hens), Beihai (BH; 1.2 million hens), and Dongguan (DG; 0.2 million hens). The results showed a higher bacterial and fungal abundance on the eggs collected from the northern and southern China farms, respectively. The dominant bacterial phylum detected across all egg samples was Firmicutes. In addition, the shell surfaces of the DG and LF samples harbored abundant levels of Proteobacteria. The dominant fungal phyla detected across all egg samples were Ascomycota and Basidiomycota. The bacterial compositions on eggshell surfaces differed significantly across all geographic regions, and the fungal composition differed significantly between samples collected from the southern and northern farms (P < 0.05). The abundance and composition of microbial colonies on the eggshell surface varied based on their geographical location (climate and environment) and farming scale (management). Our findings provide an important reference for optimizing the cleaning and disinfection methods for fresh eggs collected from different sources.

Morphological Analyses and QTL Mapping of Mottled Leaf in Zucchini (Cucurbita pepo L.).

The mottled leaf is one of the agronomic traits of zucchini and can be applied as a marker trait in aggregation breeding. However, the genetic mechanism responsible for mottled leaf has yet to be elucidated. In the present study, we used two inbred lines (line '19': silver mottled leaf; line '113': normal leaf) as parents for the physiological and genetic analysis of mottled leaf. The synthesis and net photosynthetic rate of chlorophyll were not significantly affected in the mottled areas of leaves. However, we detected a large space between the palisade parenchyma in the leaf mottle area of line '19', which may have caused the mottled leaf phenotype. Light also plays an important role in the formation of mottled leaf, and receiving light during the early stages of leaf development is a necessary factor. Genetic analysis has previously demonstrated that mottled leaf is a quantitative trait that is controlled by multiple genes. Based on the strategy of quantitative trait locus sequencing (QTL-seq), two QTLs were identified on chromosomes 1 and 17, named CpML1.1 and CpML17.1, respectively. Two major loci were identified using R/qtl software version 1.66 under greenhouse conditions in April 2019 (2019A) and April 2020 (2020A) and under open cultivation conditions in May 2020 (2020M). The major QTL, CpML1.1, was located in a 925.2-kb interval on chromosome 1 and explained 10.51%-24.15% of the phenotypic variation. The CpML17.1 was located in a 719.7-kb interval on chromosome 17 and explained 16.25%-38.68% of the phenotypic variation. Based on gene annotation, gene sequence alignment, and qRT-PCR analysis, the Cp4.1LG01g23790 at the CpML1.1 locus encoding a protein of the TPX2 family (target protein of Xklp2) may be a candidate gene for mottled leaf in zucchini. Our findings may provide a theoretical basis for the formation of mottled leaf and provide a foundation for the fine mapping of genes associated with mottled leaf. Molecular markers closely linked to mottled leaf can be used in molecular-assisted selection for the zucchini mottled leaf breeding.

ROS-Induced Endothelial Dysfunction in the Pathogenesis of Atherosclerosis.

Various signaling pathways are regulated by reactive oxygen species (ROS), which are radical oxygen intermediates under normal physiological conditions. However, when the buffering capacity of antioxidant enzymes is exceeded by the accumulation of ROS, oxidative stress, and endothelial cell dysfunction occur, which have been recognized as key contributors to the development of atherosclerosis. In this review, an overview is provided on mechanisms underlying ROS generation in endothelial cells and the involved regulatory pathways. Further, we discuss the ROS induced endothelial cell dysfunction and its relationship with atherosclerosis. Current knowledge on ROS-induced endothelial impairment is presented, characterized by decreased NO bioavailability, intracellular dysfunction and ox-LDL accumulation. Furthermore, biomarkers such as oxidative products of lipid, protein, and nucleotide are discussed as measurements for ROS levels. Novel interventions targeting oxidative stress are listed as potential pharmacotherapies in clinical practice. In conclusion, this review presents a systematic analysis of the mechanisms underlying ROS generation and elucidates how manipulation of these mechanisms can safeguard endothelial cell function.

eIF2α-mediated integrated stress response links multiple intracellular signaling pathways to reprogram vascular smooth muscle cell fate in carotid artery plaque.

Background: Carotid arterial atherosclerotic stenosis is a well-recognized pathological basis of ischemic stroke; however, its underlying molecular mechanisms remain unknown. Vascular smooth muscle cells (VSMCs) play fundamental roles in the initiation and progression of atherosclerosis. Organelle dynamics have been reported to affect atherosclerosis development. However, the association between organelle dynamics and various cellular stresses in atherosclerotic progression remain ambiguous. Methods: In this study, we conducted transcriptomics and bioinformatics analyses of stable and vulnerable carotid plaques. Primary VSMCs were isolated from carotid plaques and subjected to histopathological staining to determine their expression profiles. Endoplasmic reticulum (ER), mitochondria, and lysosome dynamics were observed in primary VSMCs and VSMC cell lines using live-cell imaging. Moreover, the mechanisms underlying disordered organelle dynamics were investigated using comprehensive biological approaches. Results: ER whorls, a representative structural change under ER stress, are prominent dynamic reconstructions of VSMCs between vulnerable and stable plaques, followed by fragmented mitochondria and enlarged lysosomes, suggesting mitochondrial stress and lysosomal defects, respectively. Induction of mitochondrial stress alleviated ER stress and autophagy in an eukaryotic translation initiation factor (eIF)-2α-dependent manner. Furthermore, the effects of eIF2α on ER stress, mitochondrial stress, and lysosomal defects were validated using clinical samples. Conclusion: Our results indicate that morphological and functional changes in VSMC organelles, especially in ER whorls, can be used as reliable biomarkers for atherosclerotic progression. Moreover, eIF2α plays an important role in integrating multiple stress-signaling pathways to determine the behavior and fate of VSMCs.

Adeno-Associated Virus-Mediated Dorsal Root Ganglion Toxicity in the New Zealand White Rabbit.

Recombinant adeno-associated virus (AAV)-mediated degeneration of sensory neurons in the dorsal root ganglia (DRG) and trigeminal ganglia (TG) has been observed in non-human primates (NHPs) following intravenous (IV) and intrathecal (IT) delivery. Administration of recombinant AAV encoding a human protein transgene via a single intra-cisterna magna (ICM) injection in New Zealand white rabbits resulted in histopathology changes very similar to NHPs: mononuclear cell infiltration, degeneration/necrosis of sensory neurons, and nerve fiber degeneration of sensory tracts in the spinal cord and of multiple nerves. AAV-associated clinical signs and incidence/severity of histologic findings indicated that rabbits were equally or more sensitive than NHPs to sensory neuron damage. Another study using human and rabbit transgene constructs of the same protein demonstrated comparable changes suggesting that the effects are not an immune response to the non-self protein transgene. Rabbit has not been characterized as a species for general toxicity testing of AAV gene therapies, but these studies suggest that it may be an alternative model to investigate mechanisms of AAV-mediated neurotoxicity and test novel AAV designs mitigating these adverse effects.

Sokotrasterol Sulfate Suppresses IFN-γ-Induced PD-L1 Expression by Inhibiting JAK Activity.

PD-1/PD-L1 monoclonal antibodies exhibit promising therapeutic effectiveness in multiple cancers. However, developing a simple and efficient non-antibody treatment strategy using the PD-1/PD-L1 signaling pathway still remains challenging. In this study, we developed a flow cytometry assay to screen bioactive compounds with PD-L1 inhibitory activity. A total of 409 marine natural products were screened, and sokotrasterol sulfate (SKS) was found to efficiently suppress the IFN-γ-induced PD-L1 expression. SKS sensitizes the tumor cells to antigen-specific T-cell killing in the T cell-tumor cell coculture system. Mechanistically, SKS directly targeted Janus kinase (JAK) to inhibit the downstream activation of signal transducer and activator of transcription (STAT) and the subsequent transcription of PDL1. Our findings highlight the immunological role of SKS that may act as a basis for a potential immunotherapeutic agent.

Superimposed Semantic Communication for IoT-based Real-time ECG Monitoring.

Real-time electrocardiogram (ECG) monitoring and diagnosis through Internet of Things (IoT) are crucial for addressing the severity and timely treatment of cardiovascular diseases, enabling timely intervention and preventing life-threatening complications. However, current ECG monitoring research predominantly focuses on individual aspects such as signal compression, diagnostic analysis, or secure transmission, lacking joint optimization of various modules in IoT scenarios. To address this gap, this work proposes a novel framework based on superimposed semantic communication for real-time ECG monitoring in IoT. The framework comprises three hierarchical levels: the edge level for data collection and processing, the relay level for signal compression and coding, and the cloud level for data analysis and reconstruction. The proposed framework offers several unique advantages. By employing semantic encoding guided by ECG classification tasks, it selectively extracts crucial features within and between signals, improving compression ratio and adaptability to channel noise. The superimposed semantic encoding achieves content encryption without requiring any additional operations. Moreover, the framework utilizes lightweight anomaly detection neural networks, reducing edge device power consumption and conserving communication resources. Simulation and real experimental results demonstrate that the proposed method achieves real-time encoding and transmission of ECG signals with a compression ratio of 0.019 on the MIT-BIH dataset. Furthermore, it attains a heartbeat classification accuracy of 0.988 and a reconstruction error of 0.061.

Concomitant Thoracic Spinal Dural Arteriovenous Fistula and Spinal Cavernous Malformation.

Both spinal dural arteriovenous fistula (SDAVF) and spinal cavernous malformation (SCM) are uncommon vascular malformations. To our knowledge, such a case of SDAVF concomitant with SCM has not been reported. We encountered a case of a 55-year-old man who had weakness and numbness in both lower extremities. Magnetic resonance imaging showed a round-shape lesion identified as a cavernous malformation in the middle segment of the thoracic spine, with spinal edema and obvious flow voids. Diagnostic angiography revealed an SDAVF fed by the right T7 radicular artery with venous drainage. The intramedullary venous hypertension due to fistula was suspected of inducing the formation of SCM. This case may provide new insight into the pathogenesis of SCM.

The Interaction between Collagen 1 and High Mannose Type CD133 Up-Regulates Glutamine Transporter SLC1A5 to Promote the Tumorigenesis of Glioblastoma Stem Cells.

Targeting the niche components surrounding glioblastoma stem cells (GSCs) helps to develop more effective glioblastoma treatments. However, the mechanisms underlying the crosstalk between GSCs and microenvironment remain largely unknown. Clarifying the extracellular molecules binding to GSCs marker CD133 helps to elucidate the mechanism of the communication between GSCs and the microenvironment. Here, it is found that the extracellular domain of high mannose type CD133 physically interacts with Collagen 1 (COL1) in GSCs. COL1, mainly secreted by cancer-associated fibroblasts, is a niche component for GSCs. COL1 enhances the interaction between CD133 and p85 and activates Akt phosphorylation. Activation of Akt pathway increases transcription factor ATF4 protein level, subsequently enhances SLC1A5-dependent glutamine uptake and glutathione synthesis. The inhibition of CD133-COL1 interaction or down-regulation of SLC1A5 reduces COL1-accelerated GSCs self-renewal and tumorigenesis. Analysis of glioma samples reveals that the level of COL1 is correlated with histopathological grade of glioma and the expression of SLC1A5. Collectively, COL1, a niche component for GSCs, enhances the tumorigenesis of GSCs partially through CD133-Akt-SLC1A5 signaling axis, providing a new mechanism underlying the cross-talk between GSCs and extracellular matrix (ECM) microenvironment.

Autophagy protects mitochondrial health in heart failure.

The progression of heart failure is reported to be strongly associated with homeostatic imbalance, such as mitochondrial dysfunction and abnormal autophagy, in the cardiomyocytes. Mitochondrial dysfunction triggers autophagic and cardiac dysfunction. In turn, abnormal autophagy impairs mitochondrial function and leads to apoptosis or autophagic cell death under certain circumstances. These events often occur concomitantly, forming a vicious cycle that exacerbates heart failure. However, the role of the crosstalk between mitochondrial dysfunction and abnormal autophagy in the development of heart failure remains obscure and the underlying mechanisms are mainly elusive. The potential role of the link between mitochondrial dysfunction and abnormal autophagy in heart failure progression has recently garnered attention. This review summarized recent advances of the interactions between mitochondria and autophagy during the development of heart failure.

A noval pulmonary function evaluation method based on ResNet50 + SVR model and cough.

Traditionally, the clinical evaluation of respiratory diseases was pulmonary function testing, which can be used for the detection of severity and prognosis through pulmonary function parameters. However, this method is limited by the complex process, which is impossible for patients to monitor daily. In order to evaluate pulmonary function parameters conveniently with less time and location restrictions, cough sound is the substitute parameter. In this paper, 371 cough sounds segments from 150 individuals were separated into 309 and 62 as the training and test samples. Short-time Fourier transform (STFT) was applied to transform cough sound into spectrogram, and ResNet50 model was used to extract 2048-dimensional features. Through support vector regression (SVR) model with biological attributes, the data were regressed with pulmonary function parameters, FEV1, FEV1%, FEV1/FVC, FVC, FVC%, and the performance of this models was evaluated with fivefold cross-validation. Combines with deep learning and machine learning technologies, the better results in the case of small samples were achieved. Using the coefficient of determination (R2), the ResNet50 + SVR model shows best performance in five basic pulmonary function parameters evaluation as FEV1(0.94), FEV1%(0.84), FEV1/FVC(0.68), FVC(0.92), and FVC%(0.72). This ResNet50 + SVR hybrid model shows excellent evaluation of pulmonary function parameters during coughing, making it possible to realize a simple and rapid evaluation for pneumonia patients. The technology implemented in this paper is beneficial in judge the patient's condition, realize early screening of respiratory diseases, evaluate postoperative disease changes and detect respiratory infectious diseases without time and location restrictions.

AF automatic classification based on different time-delay values of the recurrence plot.

Recurrence plot (RP) has been widely used to transform 1D ECG waveforms into 2D images and explore the recurrence patterns of the electrical signals generated by the cardiac system. However, selecting the critical parameter time-delay τ for creating an RP has not been well-reported. In this work, we investigated the influence of different τ values on the RP-based AF prediction. And the results illustrated that the best classification performance could be achieved at τ=1 with full characters of the dynamic system.Clinical Relevance-This work established the AF classification system based on recurrence features and found the optimal parameters of the recurrence plot improving the ECG-based classification performance.