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Abstract The wearable exoskeleton system is a typical strongly coupled human–robotic system. Human–robotic is the environment for each other. The two support each other and compete with each other. Achieving high human–robotic compatibility is the most critical technology for wearable systems. Full structural compatibility can improve the intrinsic safety of the exoskeleton, and precise intention understanding and motion control can improve the comfort of the exoskeleton. This paper first designs a physiologically functional bionic lower limb exoskeleton based on the study of bone and joint functional anatomy and analyzes the drive mapping model of the dual closed-loop four-link knee joint. Secondly, an exoskeleton dual closed-loop controller composed of a position inner loop and a force outer loop is designed. The inner loop of the controller adopts the PID control algorithm, and the outer loop adopts the adaptive admittance control algorithm based on human–robot interaction force (HRI). The controller can adaptively adjust the admittance parameters according to the HRI to respond to dynamic changes in the mechanical and physical parameters of the human–robot system, thereby improving control compliance and the wearing comfort of the exoskeleton system. Finally, we built a joint simulation experiment platform based on SolidWorks/Simulink to conduct virtual prototype simulation experiments and recruited volunteers to wear rehabilitation exoskeletons to conduct related control experiments. Experimental results show that the designed physiologically functional bionic exoskeleton and adaptive admittance controller can significantly improve the accuracy of human–robotic joint motion tracking, effectively reducing human–machine interaction forces and improving the comfort and safety of the wearer. This paper proposes a dual-closed loop four-link knee joint exoskeleton and a variable admittance control method based on HRI, which provides a new method for the design and control of exoskeletons with high compatibility.

Abstract Lung Cancer remains the leading cause of cancer deaths in the USA and worldwide. Non-small cell lung cancer (NSCLC) harbors high transcriptomic intratumor heterogeneity (RNA-ITH) that limits the reproducibility of expression-based prognostic models. In this study, we used multiregional RNA-seq data (880 tumor samples from 350 individuals) from both public (TRACERx) and internal (MDAMPLC) cohorts to investigate the effect of RNA-ITH on prognosis in localized NSCLC at the gene, signature, and tumor microenvironment levels. At the gene level, the maximal expression of hazardous genes (expression negatively associated with survival) but the minimal expression of protective genes (expression positively associated with survival) across different regions within a tumor were more prognostic than the average expression. Following that, we examined whether multiregional expression profiling can improve the performance of prognostic signatures. We investigated 11 gene signatures collected from previous publications and one signature developed in this study. For all of them, the prognostic prediction accuracy can be significantly improved by converting the regional expression of signature genes into sample-specific expression with a simple function—taking the maximal expression of hazardous genes and the minimal expression of protective genes. In the tumor microenvironment, we found a similar rule also seems applicable to immune ITH. We calculated the infiltration levels of major immune cell types in each region of a sample based on expression deconvolution. Prognostic analysis indicated that the region with the lowest infiltration level of protective or highest infiltration level of hazardous immune cells determined the prognosis of NSCLC patients. Our study highlighted the impact of RNA-ITH on the prognostication of NSCLC, which should be taken into consideration to optimize the design and application of expression-based prognostic biomarkers and models. Multiregional assays have the great potential to significantly improve their applications to prognostic stratification.

The vigorous development of wind power generation technology is the core path for the country to promote the low-carbon energy transformation and realize the "dual-carbon" (carbon peaking and carbon neutrality) goals. With the gradual saturation of the development of onshore and offshore wind power resources, wind power development from the near-shore to the distant deep sea is the inevitable trend of the future development of the wind power industry. The research and development and optimization of floating offshore wind turbine (FOWT) platforms is the key to promoting the development of offshore wind power in distant deep sea areas. Based on an analysis of the current development status of FOWT platforms at home and abroad, this paper further analyzes the current research status of aerodynamic loads, hydrodynamic loads, mooring systems, coupling analysis methods and commonly used numerical simulation tools in the design of FOWT platforms, and focuses on sorting out the key technological ideas and constitutive features of FOWT platforms that are driven by the enhancement of structural stability and the reduction of costs. By summarizing the current research status of FOWT platform optimization, we can forecast the problems and challenges in the design of FOWT platforms with a view to providing technical references for researchers in related fields.

Abstract Adenoid cystic carcinoma (ACC) is a rare, usually slow-growing yet aggressive head and neck malignancy. Despite its clinical significance, our understanding of the cellular evolution and microenvironment in ACC remains limited. We investigated the intratumoral microbiomes of 50 ACC tumor tissues and 33 adjacent normal tissues using 16S rRNA gene sequencing. This allowed us to characterize the bacterial communities within the ACC and explore potential associations between the bacterial community structure, patient clinical characteristics, and tumor molecular features obtained through RNA sequencing. The bacterial composition in the ACC was significantly different from that in adjacent normal salivary tissue, and the ACC exhibited diverse levels of species richness. We identified two main microbial subtypes within the ACC: oral-like and gut-like. Oral-like microbiomes, characterized by increased diversity and abundance of Neisseria, Leptotrichia, Actinomyces, Streptococcus, Rothia, and Veillonella (commonly found in healthy oral cavities), were associated with a less aggressive ACC-II molecular subtype and improved patient outcomes. Notably, we identified the same oral genera in oral cancer and head and neck squamous cell carcinomas. In both cancers, they were part of shared oral communities associated with a more diverse microbiome, less aggressive tumor phenotype, and better survival that reveal the genera as potential pancancer biomarkers for favorable microbiomes in ACC and other head and neck cancers. Conversely, gut-like intratumoral microbiomes, which feature low diversity and colonization by gut mucus layer-degrading species, such as Bacteroides, Akkermansia, Blautia, Bifidobacterium, and Enterococcus, were associated with poorer outcomes. Elevated levels of Bacteroides thetaiotaomicron were independently associated with significantly worse survival and positively correlated with tumor cell biosynthesis of glycan-based cell membrane components.

Abstract Background The Bric-a-Brac/Tramtrack/Broad Complex (BTB) gene family plays essential roles in various biological processes in plants. These genes encode proteins that contain a conserved BTB domain, which is involved in protein-protein interactions and regulation of gene expression. However, there is no systematic reports on the BTB gene family in G.max. Results In total, 122 soybean BTB genes were identified, which were classified into four groups based on the phylogenetic analysis. Gene structures analysis indicated that the number of exon–intron in GmBTBs ranges from 0 to18. Cis-element analysis revealed that most GmBTB genes contained cis-elements related to an abiotic stress response. In addition, qRT-PCR analyses indicated that most GmBTBs are significantly up-regulated under salinity, drought, and nitrate stresses. They suggested their potential for targeted improvement of soybean response to multiple abiotic stresses and nitrate availability. Conclusion These results provide valuable information for identifying the members of the GmBTB gene family in soybean and could provide a functional characterization of GmBTB genes in further research.

Abstract Light-emitting diodes (LEDs) based on perovskite semiconductor materials with tunable emission wavelength in visible light range as well as narrow linewidth are potential competitors among current light-emitting display technologies, but still suffer from severe instability driven by electric field. Here, we develop a stable, efficient and high-color purity hybrid LED with a tandem structure by combining the perovskite LED and the commercial organic LED technologies to accelerate the practical application of perovskites. Perovskite LED and organic LED with close photoluminescence peak are selected to maximize photon emission without photon reabsorption and to achieve the narrowed emission spectra. By designing an efficient interconnecting layer with p-type interface doping that provides good opto-electric coupling and reduces Joule heating, the resulting green emitting hybrid LED shows a narrow linewidth of around 30 nm, a peak luminance of over 176,000 cd m−2, a maximum external quantum efficiency of over 40%, and an operational half-lifetime of over 42,000 h.

Abstract N 6-methyladenosine (m6A) plays critical roles in regulating mRNA metabolism. However, comprehensive m6A methylomes in different plant tissues with single-base precision have yet to be reported. Here, we present transcriptome-wide m6A maps at single-base resolution in different tissues of rice and Arabidopsis using m6A-SAC-seq. Our analysis uncovers a total of 205,691 m6A sites distributed across 22,574 genes in rice, and 188,282 m6A sites across 19,984 genes in Arabidopsis. The evolutionarily conserved m6A sites in rice and Arabidopsis ortholog gene pairs are involved in controlling tissue development, photosynthesis and stress response. We observe an overall mRNA stabilization effect by 3’ UTR m6A sites in certain plant tissues. Like in mammals, a positive correlation between the m6A level and the length of internal exons is also observed in plant mRNA, except for the last exon. Our data suggest an active m6A deposition process occurring near the stop codon in plant mRNA. In addition, the MTA-installed plant mRNA m6A sites correlate with both translation promotion and translation suppression, depicting a more complicated regulatory picture. Our results therefore provide in-depth resources for relating single-base resolution m6A sites with functions in plants and uncover a suppression-activation model controlling m6A biogenesis across species.

Accurate identification of potato diseases is crucial for reducing yield losses. To address the issue of low recognition accuracy caused by the mismatch between target domain and source domain due to insufficient samples, the effectiveness of Multi-Source Unsupervised Domain Adaptation (MUDA) method in disease identification is explored. A Multi-Source Domain Feature Adaptation Network (MDFAN) is proposed, employing a two-stage alignment strategy. This method first aligns the distribution of each source-target domain pair within multiple specific feature spaces. In this process, multi-representation extraction and subdomain alignment techniques are utilized to further improve alignment performance. Secondly, classifier outputs are aligned by leveraging decision boundaries within specific domains. Taking into account variations in lighting during image acquisition, a dataset comprising field potato disease images with five distinct disease types is created, followed by comprehensive transfer experiments. In the corresponding transfer tasks, MDFAN achieves an average classification accuracy of 92.11% with two source domains and 93.02% with three source domains, outperforming all other methods. These results not only demonstrate the effectiveness of MUDA but also highlight the robustness of MDFAN to changes in lighting conditions.

Abstract Designing bifunctional catalysts to reduce the oxygen evolution reaction (OER) and oxygen reduction reaction (ORR) reaction barriers while accelerating the reaction kinetics is perceived to be a promising strategy to improve the performance of Zinc–air batteries. Unsymmetric configuration in single‐atom catalysts has attracted attention due to its unique advantages in regulating electron orbitals. In this work, a seesaw effect in unsymmetric Fe–Co bimetallic monoatomic configurations is proposed, which can effectively improve the OER/ORR bifunctional activity of the catalyst. Compared with the symmetrical model of Fe–Co, a strong charge polarization between Co and Fe atoms in the unsymmetric model is detected, in whom the spin‐down electrons around Co atoms are much higher than those spin‐up electrons. The seesaw effect occurred between Co atoms and Fe atoms, resulting in a negative shift of the d‐band center, which means that the adsorption of oxygen intermediates is weakened and more conducive to their dissociation. The optimized reaction kinetics of the catalyst leads to excellent performance in ZABs, with a peak power density of 215 mW cm−2 and stable cycling for >1300 h and >4000 cycles. Flexible Zinc–air batteries have also gained excellent performance to demonstrate their potential in the field of flexible wearables.

Deep networks play a crucial role in the recognition of agricultural diseases. However, these networks often come with numerous parameters and large sizes, posing a challenge for direct deployment on resource-limited edge computing devices for plant protection robots. To tackle this challenge for recognizing cotton diseases on the edge device, we adopt knowledge distillation to compress the big networks, aiming to reduce the number of parameters and the computational complexity of the networks. In order to get excellent performance, we conduct combined comparison experiments from three aspects: teacher network, student network and distillation algorithm. The teacher networks contain three classical convolutional neural networks, while the student networks include six lightweight networks in two categories of homogeneous and heterogeneous structures. In addition, we investigate nine distillation algorithms using spot-adaptive strategy. The results demonstrate that the combination of DenseNet40 as the teacher and ShuffleNetV2 as the student show best performance when using NST algorithm, yielding a recognition accuracy of 90.59% and reducing FLOPs from 0.29 G to 0.045 G. The proposed method can facilitate the lightweighting of the model for recognizing cotton diseases while maintaining high recognition accuracy and offer a practical solution for deploying deep models on edge computing devices.

Abstract Leveraging the ultra‐wideband advantages of the terahertz band, Integrated sensing and communication (ISAC) facilitates high‐precision sensing demands in human smart home applications. ISAC channel characteristics are the basis for ISAC system design. Currently, the ISAC channel is divided into target and background channels. Existing researches primarily focus on the attributes of human target itself, e.g. radar cross‐section and micro‐Doppler effect. However, the impact of human target on neither the pathloss characteristic of background channel nor the multipath propagation characteristic of target channel is considered. To address the gap, we conduct indoor channel measurements at 105 GHz to investigate the ISAC channel characteristics with the impact of human target. Firstly, by analysing the power angular delay profiles with and without human target, the changes in quantity and power of multipath components (MPCs) are observed. Then, a parameter called power control factor is proposed to evaluate the human target impact on pathloss, thereby modifying the existing pathloss model of background channel. Eventually, the MPCs belonging to target channel are extracted within target‐oriented power delay profile to count the power proportion of each bounce MPCs of the target‐Rx link, which supports the necessity of multi‐bounce (indirect) paths modelling in target channel.

Abstract Background Pleural fluid is one of the common complications of thoracic diseases, and tuberculous pleural effusion (TPE) is the most common cause of pleural effusion in TB-endemic areas and the most common type of exudative pleural effusion in China. In clinical practice, distinguishing TPE from pleural effusion caused by other reasons remains a relatively challenging issue. The objective of present study was to explore the clinical significance of the pleural fluid lactate dehydrogenase/adenosine deaminase ratio (pfLDH/pfADA) in the diagnosis of TPE. Methods The clinical data of 618 patients with pleural effusion were retrospectively collected, and the patients were divided into 3 groups: the TPE group (412 patients), the parapneumonic pleural effusion (PPE) group (106 patients), and the malignant pleural effusion (MPE) group (100 patients). The differences in the ratios of pleural effusion-related and serology-related indicators were compared among the three groups, and receiver operating characteristic curves were drawn to analyze the sensitivity and specificity of the parameter ratios of different indicators for the diagnosis of TPE. Results The median serum ADA level was higher in the TPE group (13 U/L) than in the PPE group (10 U/L, P

Abstract Neoantigens derived from somatic mutations in Kirsten Rat Sarcoma Viral Oncogene Homolog (KRAS), the most frequently mutated oncogene, represent promising targets for cancer immunotherapy. Recent research highlights the potential role of human leukocyte antigen (HLA) allele A*11:01 in presenting these altered KRAS variants to the immune system. In this study, we successfully generate and identify murine T-cell receptors (TCRs) that specifically recognize KRAS8–16 G12V from three predicted high affinity peptides. By determining the structure of the tumor-specific 4TCR2 bound to KRASG12V-HLA-A*11:01, we conduct structure-based design to create and evaluate TCR variants with markedly enhanced affinity, up to 15.8-fold. This high-affinity TCR mutant, which involved only two amino acid substitutions, display minimal conformational alterations while maintaining a high degree of specificity for the KRASG12V peptide. Our research unveils the molecular mechanisms governing TCR recognition towards KRASG12V neoantigen and yields a range of affinity-enhanced TCR mutants with significant potential for immunotherapy strategies targeting tumors harboring the KRASG12V mutation.

Abstract Background The COVID-19 pandemic have impacts on the prevalence of other pathogens and people’s social lifestyle. This study aimed to compare the pathogen, allergen and micronutrient characteristics of pediatric inpatients with pneumonia prior to and during the COVID-19 pandemic in a large tertiary hospital in Shanghai, China. Methods Patients with pneumonia admitted to the Department of Pediatric Pulmonology of Xinhua Hospital between March-August 2019 and March-August 2020 were recruited. And clinical characteristics of the patients in 2019 were compared with those in 2020. Results Hospitalizations for pneumonia decreased by 74% after the COVID-19 pandemic. For pathogens, virus, mycoplasma pneumoniae (MP) and mixed infection rates were all much lower in 2020 than those in 2019 (P

Abstract Background Hamartoma is a common benign tumor that usually occurs in the kidney, liver, lung, and pancreas. Large renal hamartomas may spontaneously rupture and hemorrhage, which is potentially life-threatening. Case presentation This report describes a 46-year-old Han Chinese female patient with multiple renal and hepatic hamartomas with rupture and hemorrhage of giant hamartoma in the left kidney. She underwent arterial embolization three times successively, and her condition was stable during the 2-year follow-up. This report includes a review of the relevant literature Conclusions the findings in this report and previous literature suggest that arterial embolization can not only rapidly treat hamartoma hemorrhage in the acute phase but can also effectively control multiple lesions in the long term after repeated multisite arterial embolization.

Abstract While we recognize the prognostic importance of clinicopathological measures and circulating tumor DNA (ctDNA), the independent contribution of quantitative image markers to prognosis in non-small cell lung cancer (NSCLC) remains underexplored. In our multi-institutional study of 394 NSCLC patients, we utilize pre-treatment computed tomography (CT) and 18F-fluorodeoxyglucose positron emission tomography (FDG-PET) to establish a habitat imaging framework for assessing regional heterogeneity within individual tumors. This framework identifies three PET/CT subtypes, which maintain prognostic value after adjusting for clinicopathologic risk factors including tumor volume. Additionally, these subtypes complement ctDNA in predicting disease recurrence. Radiogenomics analysis unveil the molecular underpinnings of these imaging subtypes, highlighting downregulation in interferon alpha and gamma pathways in the high-risk subtype. In summary, our study demonstrates that these habitat imaging subtypes effectively stratify NSCLC patients based on their risk levels for disease recurrence after initial curative surgery or radiotherapy, providing valuable insights for personalized treatment approaches.

[Introduction] Under the background of "carbon peak and neutrality" target and "ocean power" strategy, the integration of ocean renewable energy represented by offshore wind power and ocean resources represented by marine ranch is the new direction, new situation and new opportunity for the future development and utilization of ocean resources. The article reviews and analyzes the integrated development mode and key technical problems of offshore wind power and marine pasture, in order to provide technical references to the relevant research and engineering projects in China. [Method] Taking the integration of China's marine resources development needs as the guide, the global development trend of offshore wind power and marine ranch integration was analyzed, and the current situation and shortcomings of China's wind-fishery integration development were clarified. On this basis, the integration mode, equipment design, engineering cases and key technical problems of the integration development of offshore wind power and ocean ranch were analyzed in detail. Finally, a future outlook on the integration development of offshore wind power and ocean ranch in China was discussed. [Result] Through the analysis of the integrated development mode and key technical problems of the integration of offshore wind power and marine ranch development, the bottlenecks and technical challenges are clarified, and the key breakthrough directions are pointed out, providing scientific guidance and reference basis for the comprehensive development and utilization of offshore resources in China. [Conclusion] The article illustrates the necessity and feasibility of integrating the development of offshore wind power and marine ranch, and proposes a feasible way to integrate offshore wind power and marine ranch in China.

Jasmonic acid is a crucial phytohormone that plays a pivotal role, serving as a regulator to balancing plant development and resistance. However, there are analogous and distinctive characteristics exhibited in JA biosynthesis, perception, and signal transduction pathways in both herbaceous and woody plants. Moreover, the majority of research subjects have predominantly focused on the function of JA in model or herbaceous plants. Consequently, there is a significant paucity of studies investigating JA regulation networks in woody plants, particularly concerning post-transcriptional regulatory events such as alternative splicing (AS). This review article aims to conduct a comprehensive summary of advancements that JA signals regulate plant development across various woody species, comparing the analogous features and regulatory differences to herbaceous counterparts. In addition, we summarized the involvement of AS events including splicing factor (SF) and transcripts in the JA regulatory network, highlighting the effectiveness of high-throughput proteogenomic methods. A better understanding of the JA signaling pathway in woody plants has pivotal implications for forestry production, including optimizing plant management and enhancing secondary metabolite production.

Spikelet degeneration is a critical physiological issue that limits grain yield in rice (Oryza sativa L.), influenced by soil moisture conditions during meiosis. The study aimed to investigate the role and mechanism of moderate soil drying in spikelet degeneration and grain yield, as well as to establish a strategy and irrigation regime for suppressing spikelet degeneration to increase grain yield in rice. Field experiments were conducted involving two irrigation regimes: conventional well-watered (C-WW) and moderate soil drying (M-SD) during meiosis. Transgenic rice lines and chemical regulators were employed to elucidate the underlying partial biological mechanisms of this process. The results showed that M-SD regime effectively reduced spikelet degeneration rate and increased grain yield compared to C-WW. This improvement under M-SD regime was primarily attributed to the enhanced proline and aquaporin-mediated osmotic balance and redox homeostasis in young rice panicles, as well as the increased root activity during meiosis. The increased levels of brassinosteroids (BRs) and decreased levels of ethylene (ETH) in young panicles under the M-SD were closely associated with the enhanced proline and aquaporin-mediated osmotic balance and redox homeostasis, decreased oxidative damage, and reduced spikelet degeneration rate. The intrinsic relationship among key aquaporin genes expression and proline levels, osmotic balance and redox homeostasis, spikelet degeneration rate, as well as BRs and ETH levels, was further confirmed through the use of transgenic rice lines and chemical regulators. Collectively, an M-SD regime during meiosis can effectively suppress spikelet degeneration and thereby enhance grain yield, primarily through well-maintained osmotic balance and redox homeostasis in rice.

This paper establishes a high-fidelity and efficient Computational Fluid Dynamics (CFD) numerical method (AL-LDS-Ωnew) for wind turbine wake by combining the actuator line (AL), the localized dynamic Smagorinsky (LDS) sub-grid scale (SGS), and the new generation Ωnew vortex identification method under the framework of large eddy simulation. The model advantages are encouraging: 1) In terms of turbine modeling, the AL model is adopted to replace the traditional three-dimensional solid model, which avoids solving the boundary layer on the blade surface and improves computational efficiency; 2) In terms of wake simulation, the LDS SGS model is used to model turbulence, reducing vortex dissipation and further improving the refinement of turbine wake; 3) In terms of vortex identification, the new generation Ωnew vortex identification method avoids the difficult threshold selection in previous vortex identification and captures more refined vortex structures. The accuracy of the model is validated against published data of a NREL 5 MW wind turbine, and then extended to simulate the wake interference of tandem twin-rotor turbines by changing the pitch angle of the upstream wind turbine (WT1). The influence mechanisms between array wake interference and energy conversion efficiency under the pitch strategy are explored, demonstrating the AL-LDS-Ωnew coupling method is computationally accurate and efficient for simulating the complex wake interference. From analyses, the pitch strategy can effectively suppress the wake effect of the upstream turbine (WT1) and increase the power output of the downstream turbine (WT2), thus improving the overall output power of the array farm. Compared with the non-pitch condition (0 pitch angle), a pitch angle of (2°) maximizes the global energy conversion efficiency of the twin-rotor array: power augmentation by 0.29%, and thrust reduction by 5%. This optimal state reduces the fatigue load of the turbine and is more conducive to long-term operation. The findings, whilst preliminary, encourage the use of turbine pitch strategies in the wind farm planning and operation.

The response of Hypoxia Inducible Gene Domain (HIGD) proteins to hypoxia plays a crucial role in plant development. However, the research on this gene family in soybean has been lacking. In this study, we aimed to identify and comprehensively analyze soybean HIGD genes using the Glycine max genome database. As a result, six GmHIGD genes were successfully identified, and their phylogeny, gene structures, and putative conserved motifs were analyzed in comparison to Arabidopsis and rice. Collinearity analysis indicated that the HIGD gene family in soybean has expanded to some extent when compared to Arabidopsis. Additionally, the cis-elements in the promoter regions of GmHIGD and the transcription factors potentially binding to these regions were identified. All GmHIGD genes showed specific responsiveness to submergence and hypoxic stresses. Expression profiling through quantitative real-time PCR revealed that these genes were significantly induced by PEG treatment in root tissue. Co-expressed genes of GmHIGD were primarily associated with oxidoreductase and dioxygenase activities, as well as peroxisome function. Notably, one of GmHIGD genes, GmHIGD3 was found to be predominantly localized in mitochondria, and its overexpression in Arabidopsis led to a significantly reduction in catalase activity compared to wild-type plants. These results bring new insights into the functional role of GmHIGD in terms of subcellular localization and the regulation of oxidoreductase activity.

Background: Pediatric pneumonia presents a significant global health challenge, particularly in low- and middle-income countries. This study aimed to investigate the incidence of pneumonia in preschool children in Urumqi and its association with indoor environmental factors. Methods: This case-control study collected data from December 2018 to December 2019 on 1522 preschool children in Urumqi (779 boys and 743 girls) who were diagnosed with pneumonia by a physician. A control group of children who had never had pneumonia was matched in a 1:1 ratio based on gender, age, and ethnicity. Using questionnaires, data were collected on children's general characteristics, passive smoking, types of housing, flooring materials, and indoor dampness, analyzing potential factors associated with the incidence of pediatric pneumonia. Results: Multivariate analysis revealed that cesarean birth (odds ratio [OR] = 1.27; 95 % confidence interval [95%CI] = 1.08–1.48), being an only child (OR = 1.32; 95%CI = 1.13–1.55), antibiotic treatment during the first year of life (OR = 2.51; 95%CI = 1.98–3.19), passive smoking during the mother's pregnancy (OR = 1.62; 95%CI = 1.24–2.13), living in multi-family apartment housing (OR = 1.64; 95%CI = 1.28–2.10) and other types of housing (OR = 1.47; 95%CI = 1.09–1.99), laminate flooring (OR = 1.31; 95%CI = 1.01–1.72), and tile/stone/cement flooring flooring (OR = 1.31; 95%CI = 1.06–1.61), and dampness in dwelling (during first year of mother's pregnancy) (OR = 1.30; 95%CI = 1.04–1.63) were risk factors for pediatric pneumonia. The use of fresh air filtration systems in children's residences (OR = 0.66; 95%CI = 0.50–0.86) was identified as a protective factor. Conclusion: This study underscores the importance of indoor environmental factors in the prevention of pediatric pneumonia. Public health strategies should consider these factors to reduce the incidence of pneumonia in children. Future research needs to be conducted over a broader geographical range and consider a more comprehensive range of factors influencing pediatric pneumonia.

Abstract Background Lung cancer remains the foremost reason of cancer‐related mortality, with invasion and metastasis profoundly influencing patient prognosis. N‐acetyltransferase 10 (NAT10) catalyzes the exclusive N (4)‐acetylcytidine (ac4C) modification in eukaryotic RNA. NAT10 dysregulation is linked to various diseases, yet its role in non‐small cell lung cancer (NSCLC) invasion and metastasis remains unclear. Our study delves into the clinical significance and functional aspects of NAT10 in NSCLC. Methods We investigated NAT10's clinical relevance using The Cancer Genome Atlas (TCGA) and a group of 98 NSCLC patients. Employing WB, qRT‐PCR, and IHC analyses, we assessed NAT10 expression in NSCLC tissues, bronchial epithelial cells (BECs), NSCLC cell lines, and mouse xenografts. Further, knockdown and overexpression techniques (siRNA, shRNA, and plasmid) were employed to evaluate NAT10's effects. A series of assays were carried out, including CCK‐8, colony formation, wound healing, and transwell assays, to elucidate NAT10's role in proliferation, invasion, and metastasis. Additionally, we utilized lung cancer patient‐derived 3D organoids, mouse xenograft models, and Remodelin (NAT10 inhibitor) to corroborate these findings. Results Our investigations revealed high NAT10 expression in NSCLC tissues, cell lines and mouse xenograft models. High NAT10 level correlated with advanced T stage, lymph node metastasis and poor overall survive. NAT10 knockdown curtailed proliferation, invasion, and migration, whereas NAT10 overexpression yielded contrary effects. Furthermore, diminished NAT10 levels correlated with increased E‐cadherin level whereas decreased N‐cadherin and vimentin expressions, while heightened NAT10 expression displayed contrasting results. Notably, Remodelin efficiently attenuated NSCLC proliferation, invasion, and migration by inhibiting NAT10 through the epithelial‐mesenchymal transition (EMT) pathway. Conclusions Our data underscore NAT10 as a potential therapeutic target for NSCLC, presenting avenues for targeted intervention against lung cancer through NAT10 inhibition.

Cotton, a vital textile raw material, is intricately linked to people’s livelihoods. Throughout the cotton cultivation process, various diseases threaten cotton crops, significantly impacting both cotton quality and yield. Deep learning has emerged as a crucial tool for detecting these diseases. However, deep learning models with high accuracy often come with redundant parameters, making them challenging to deploy on resource-constrained devices. Existing detection models struggle to strike the right balance between accuracy and speed, limiting their utility in this context. This study introduces the CDDLite-YOLO model, an innovation based on the YOLOv8 model, designed for detecting cotton diseases in natural field conditions. The C2f-Faster module replaces the Bottleneck structure in the C2f module within the backbone network, using partial convolution. The neck network adopts Slim-neck structure by replacing the C2f module with the GSConv and VoVGSCSP modules, based on GSConv. In the head, we introduce the MPDIoU loss function, addressing limitations in existing loss functions. Additionally, we designed the PCDetect detection head, integrating the PCD module and replacing some CBS modules with PCDetect. Our experimental results demonstrate the effectiveness of the CDDLite-YOLO model, achieving a remarkable mean average precision (mAP) of 90.6%. With a mere 1.8M parameters, 3.6G FLOPS, and a rapid detection speed of 222.22 FPS, it outperforms other models, showcasing its superiority. It successfully strikes a harmonious balance between detection speed, accuracy, and model size, positioning it as a promising candidate for deployment on an embedded GPU chip without sacrificing performance. Our model serves as a pivotal technical advancement, facilitating timely cotton disease detection and providing valuable insights for the design of detection models for agricultural inspection robots and other resource-constrained agricultural devices.

BackgroundThe interplay between gut microbiota and metabolites in the early stages of sepsis-induced acute kidney injury (SA-AKI) is not yet clearly understood. This study explores the characteristics and interactions of gut microbiota, and blood and urinary metabolites in patients with SA-AKI.MethodsUtilizing a prospective observational approach, we conducted comparative analyses of gut microbiota and metabolites via metabolomics and metagenomics in individuals diagnosed with SA-AKI compared to those without AKI (NCT06197828). Pearson correlations were used to identify associations between microbiota, metabolites, and clinical indicators. The Comprehensive Antibiotic Resistance Database was employed to detect antibiotic resistance genes (ARGs), while Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways informed on metabolic processes and microbial resistance patterns.ResultsOur study included analysis of four patients with SA-AKI and five without AKI. Significant disparities in bacterial composition were observed, illustrated by diversity indices (Shannon index: 2.0 ± 0.4 vs. 1.4 ± 0.6, P = 0.230; Simpson index: 0.8 ± 0.1 vs. 0.6 ± 0.2, P = 0.494) between the SA-AKI group and the non-AKI group. N6, N6, N6-Trimethyl-L-lysine was detected in both blood and urine metabolites, and also showed significant correlations with specific gut microbiota (Campylobacter hominis and Bacteroides caccae, R > 0, P < 0.05). Both blood and urine metabolites were enriched in the lysine degradation pathway. We also identified the citrate cycle (TCA cycle) as a KEGG pathway enriched in sets of differentially expressed ARGs in the gut microbiota, which exhibits an association with lysine degradation.ConclusionsSignificant differences in gut microbiota and metabolites were observed between the SA-AKI and non-AKI groups, uncovering potential biomarkers and metabolic changes linked to SA-AKI. The lysine degradation pathway may serve as a crucial link connecting gut microbiota and metabolites.

Abstract Noncontact humidity sensor overcomes the limitations of its contact sensing counterparts, including mechanical wear and cross infection, which becomes a promising candidate in healthcare and human-machine interface application. However, current humidity sensors still suffer the ubiquitous issue of uncomfortable wear and skin irritation hindering the long-term use. In this study, we report a skin-conformal and breathable humidity sensor assembled by anchoring MXenes-based composite into electrospun elastomer nanofibers coated with a patterned electrode. This composite is highly sensitive to the water molecules due to its large specific surface area and abundant water-absorbing hydroxyl groups, while the elastomeric nanofibers provide an ultrathin, highly flexible, and permeable substrate to support the functional materials and electrodes. This sensor presents not only excellent air permeability (0.078 g cm−2 d−1), high sensitivity (S = 704), and fast response/recovery (0.9 s/0.9 s), but also high skin conformability and biocompatibility. Furthermore, this humidity sensor is confirmed to realize the recognition of motional states and emotional modes, which provides a way for the advanced noncontact human-machine interface.

Abstract Objective Rheumatoid arthritis (RA) is a chronic, progressive autoimmune disease with a complex pathogenesis that has not yet been fully elucidated, and T-cell pyroptosis is an important pathogenetic factor in RA. This study aimed to investigate the role of endoplasmic reticulum aminopeptidase 2 (ERAP2) in the pyroptosis of CD4+ T cells in RA and the specific molecular mechanism. Methods Peripheral venous blood was collected from human subjects, and CD4+ T cells were isolated and activated to measure the level of pyroptosis and ERAP2 expression. Pyroptosis levels were assessed using immunofluorescence, flow cytometry, qRT-PCR, and Western blotting. Changes in pyroptosis levels were observed upon knockdown or overexpression of ERAP2. To detect activated Caspase-1 in tissues, chimeric mice were engrafted with human synovial tissue and reconstituted with human CD4+ T cells. CD4 + T cells were treated with GLI1 antagonists and SMO receptor agonists to detect changes in pyroptosis levels. Results CD4+ T cell levels undergoing pyroptosis were found to be elevated in the blood and synovium of RA patients. The gene and protein expression of ERAP2 were significantly higher in CD4+ T cells from RA patients. Deletion of ERAP2 suppressed pyroptosis of these cells, attenuated the activation of Caspase-1 in tissue T cells, and reduced tissue inflammatory responses. Reciprocally, overexpression of ERAP2 triggered inflammasome assembly, activated Caspase-1, and induced pyroptosis in CD4+ T cells. Mechanistically, ERAP2 inhibits the Hedgehog signaling pathway and upregulates the expression of nucleotide-binding oligomerization segment-like receptor family 3(NLRP3), cleaved Caspase-1, and Gasdermin D to promote pyroptosis in CD4+ T cells. Conclusions Taken together, our results identify a novel mechanism by which ERAP2 regulates RA development and document the effect of the ERAP2/Hedgehog signaling axis on pyroptosis of CD4+ T cells from RA patients.

This paper reports a performance optimized operational amplifier (OPAMP) using transconductance enhancement topology based on the amorphous indium- gallium-zinc-oxide (a-IGZO) thin-film transistors (TFTs). The performance of TFTs is enhanced by N2O plasma treatment that presents electrical characteristics suitable for accomplishing an OPAMP. The circuit consists of 19 TFTs with measured phase margin (PM) and unity-gain frequency (UGF) of 35.8° and 200 kHz, respectively. The DC power consumption (PDC) is 0.68 mW. Notably, it exhibits a high voltage gain (Av) of 32.67 dB and bandwidth (BW) of 15 kHz with 15 V DC supply voltage. Scarcely any work was reported with such a high gain while having a sufficient BW. The OPAMP demonstrates excellent performance among all a-IGZO literature and provides substantial support for the future development of TFT-based integrated circuits (ICs).

Al2O3, as one of the gate dielectric materials for thin film transistors (TFTs), has been extensively investigated because of its large bandgap, high breakdown field, and good thermal stability. However, the further development of Al2O3 thin films is limited by the presence of defects such as oxygen vacancies, self-interstitial atoms, or impurity elements. To overcome this obstacle, we have developed a novel method for fabricating Al2O3 thin films by using the atomic layer deposition (ALD) technique. This method replaces the conventional Trimethylaluminium (TMA)/H2O cycles with TMA/TMA/H2O/H2O cycles (referred to as ‘double cycles’), to deposit the Al2O3. The 5-nm ultrathin Al2O3 film showed a high areal capacitance of 660 nF/cm2 at 20 Hz, and a relatively low current density of 10−8 A/cm2 at 1 MV/cm. InGaZnO (IGZO) TFTs with ultrathin Al2O3 gate dielectric grown by double cycles exhibited outstanding performances, such as a near theoretical limit subthreshold swing (SS) of 70 mV/decade, a higher on/off current ratio $(I_{\mathrm{ on}} / I_{\mathrm{ off}}$ ) of 106, an increased field-effect mobility ( $\mu $ ) of 6.5 cm2/Vs, a lower threshold voltage $(V_{\mathrm{ th}})$ of 0.2 V, and a low operating voltage of 3 V. These results are superior to the IGZO TFTs with Al2O3 dielectrics deposited using the single TMA/H2O cycle. Therefore, the implementation of ‘double cycles’ in the fabrication of dielectrics through ALD demonstrates considerable potential for future application in low-power electronic devices.

The 6 GHz band plays a crucial role in the development of the 6G. A profound comprehension of channel reciprocity is essential for designing time division duplexing/frequency division duplexing (TDD/FDD) systems within this band. Firstly, in an indoor corridor scenario, precise and impartial measurements are conducted for both the uplink (UL) and downlink (DL) channels in the 6 GHz band; A denoising algorithm is proposed to extract multipath components (MPCs) from the measurement data, enabling a more equitable assessment of channel reciprocity; Then, a comprehensive analysis of channel reciprocity has been conducted, focusing on four aspects: path loss, delay spread, cluster-based correlation coefficient (CBCC), and multipath power dissimilarity (MPD). The findings indicate that TDD systems demonstrate nearly perfect reciprocity, whereas FDD systems exhibit partial reciprocity in indoor scenarios. Specifically, in TDD systems, the CBCCs between UL and DL exceed 95%, while in FDD systems, they fluctuate between 80% and 90%. Additionally, a model has been provided to depict the relationship between MPD and center frequency, as well as frequency interval; Finally, a comparative analysis of measured and ray-tracing simulated results reveals the presence of numerous public MPCs, which share the same propagation delay and spatial angle between the UL and DL in FDD systems, as well as private MPCs that exist exclusively in either the UL or DL. They collectively influence the channel reciprocity.

Nitrogen (N) is the major nutrient limiting rice (Oryza sativa L.) production. Avoiding excessive N use without compromising yields has long been a priority for both research and government policy in China. Nitrogen use efficiency (NUE) reflects the relationship between dry matter production or economic yield and the quantity of N applied. As an important organ for nutrient absorption, the root system of rice is closely related to NUE. We hypothesized that NUE could be improved by optimizing the root system. Here, we described and compared the evaluation methods of NUE in rice and discussed the relationship of rice root morphological (quantity, weight, length, surface area, number, diameter, volume, distribution, and structure) and physiological (root oxidation activity, active absorbing area or rate, hormones, composition and concentration of root bleeding and root exudates, nutrition concentration, and NH4+/NH3− flux) characteristics with N absorption and utilization. The key agronomic practices were proposed to improve NUE from several aspects, including adoption of N-efficient varieties and improvements in N and water management, farming systems, and soil properties. Further research is needed to clarify the root-soil interface principle based on efficient N uptake, reveal the root-shoot interaction mechanism based on efficient N utilization, and explore the integrative management strategy of high yield and efficient N utilization through maximizing the root system of rice. Our objective in this review is to provide ideas to further exploit potentialities of the root system through variety selection and cultivation management to improve NUE.

Abstract The development of advanced sustainable biomedical materials with superior biosafety and bioactivity for clinical applications is highly desirable. In the present investigation, biomass-based nanoparticles (NPs) were assembled through the Mannich reaction between the plant polyphenols and the broad-spectrum antibiotic tigecycline (TG). The fabricated NPs with uniform size demonstrated excellent oxidative balance effects, pH-responsive release properties and antibacterial performances. Furthermore, the intracellular and in vivo studies confirmed that the NPs are capable of reducing oxidative damage to cells and significantly repairing tissue injury in mice with peritonitis. This work presents an effective method and idea for constructing biomass-based materials for the treatment of infection-induced diseases. Graphical Abstract

Abstract Mitochondria morphology and function, and their quality control by mitophagy, are essential for heart function. We investigated whether these are influenced by time of the day (TOD), sex, and fed or fasting status, using transmission electron microscopy (EM), mitochondrial electron transport chain (ETC) activity, and mito-QC reporter mice. We observed peak mitochondrial number at ZT8 in the fed state, which was dependent on the intrinsic cardiac circadian clock, as hearts from cardiomyocyte-specific BMAL1 knockout (CBK) mice exhibit different TOD responses. In contrast to mitochondrial number, mitochondrial ETC activities do not fluctuate across TOD, but decrease immediately and significantly in response to fasting. Concurrent with the loss of ETC activities, ETC proteins were decreased with fasting, simultaneous with significant increases of mitophagy, mitochondrial antioxidant protein SOD2, and the fission protein DRP1. Fasting-induced mitophagy was lost in CBK mice, indicating a direct role of BMAL1 in regulating mitophagy. This is the first of its kind report to demonstrate the interactions between sex, fasting, and TOD on cardiac mitochondrial structure, function and mitophagy. These studies provide a foundation for future investigations of mitochondrial functional perturbation in aging and heart diseases.

Abstract Background To study whether the four locus gene model consisting of ADRB2 rs1042713, IL4 rs2243250, FCER1B rs569108 and L13 rs20541 can predict asthma of the Kazak children in Xinjiang, China. Methods Four single nucleotide polymorphisms about the 4 genes were genotyped in asthma group and control group of Han children and Kazak children respectively. The frequencies of different genotypes and alleles were compared between the asthma group and the control group in the two nationalities. Different risk genotypes for asthma were evaluated in the two nationalities. Results The differences about frequencies of genotypes in ADRB2 rs1042713 and IL4 rs2243250 and IL13 rs20541 between asthma group and control group were statistically significant in Han children, as were the frequencies of alleles in the 3 single nucleotide polymorphisms, but there were no statistical differences in FCER1B rs569108(P > 0.05). For the Kazak children, no differences were existed among all the genotypes and alleles in asthma group and control group. For the Han children, more children were asthma high risk genotype in the asthma group than those in the control group and no difference was found in the Kazak children. Conclusions The four locus gene model consisting of ADRB2 rs1042713, IL4 rs2243250, FCER1B rs569108 and L13 rs20541 can predict asthma of Han children but not for the Kazak children in Xinjiang, which illustrating that the difference of asthma prevalence between different races is closely related to the genetic background.

Drawing on the social capital theory, the research examines the impact of network size, network centrality, trust, and regulation on the knowledge integration and robustness of emergency medical logistics. Additionally, the research seeks to provide deeper insight into the link between the variables by studying how knowledge integration mediates the relationship between independent variables and the robustness of emergency medical logistics. The study utilized structural equation modeling to assess the underlying assumptions of the research model. A total of 465 valid questionnaires were collected from government departments, hospitals, social teams, and enterprises. The data processing and analysis were conducted using SPSS 23.0 and AMOS 24.0 software. The study’s outcome indicated that network size and network centrality have indirect effects on the robustness of emergency medical logistics through the intermediate variable of knowledge integration, but neither has a direct effect. Moreover, knowledge integration has a significant positive impact on the robustness of emergency medical logistics. Both trust and regulation have positive effects on the robustness of emergency medical logistics, and they also have positive effects on the robustness of emergency medical logistics through knowledge integration. This study is the inaugural exploration of the correlation between knowledge integration and the robustness of emergency medical logistics. It adds to the literature by providing evidence that knowledge integration is an essential emergency organization’s aide in promoting the robustness of emergency medical logistics. The findings of this study establish a strong theoretical foundation and practical significance for ensuring and improving the level of effectiveness in emergency medical logistics management.

Pigs play vital roles in the food supply, economic development, agricultural recycling, bioenergy, and social culture. Pork serves as a primary meat source and holds extensive applications in various dietary cultures, making pigs indispensable to human dietary structures. Manual pig counting, a crucial aspect of pig farming, suffers from high costs and time-consuming processes. In this paper, we propose the PDC-YOLO network to address these challenges, dedicated to detecting pigs in complex farming environments for counting purposes. Built upon YOLOv7, our model incorporates the SPD-Conv structure into the YOLOv7 backbone to enhance detection under varying lighting conditions and for small-scale pigs. Additionally, we replace the neck of YOLOv7 with AFPN to efficiently fuse features of different scales. Furthermore, the model utilizes rotated bounding boxes for improved accuracy. Achieving a mAP of 91.97%, precision of 95.11%, and recall of 89.94% on our collected pig dataset, our model outperforms others. Regarding technical performance, PDC-YOLO exhibits an error rate of 0.002 and surpasses manual counting significantly in speed.

The rhizosheath, the layer of soil tightly attached to the roots, protects plants against abiotic stress and other adverse conditions by providing a bridge from the plant root system to the soil. It reduces the formation of air gaps between the root and soil and facilitates the transportation of water at the root–soil interface. It also serves as a favourable niche for plant-growth-promoting rhizobacteria in the surrounding soil, which facilitate the absorption of soil water and nutrients. This review compares the difference between the rhizosheath and rhizosphere, and summarises the molecular and physiological mechanisms of rhizosheath formation, and identifying the causes of rhizosheath formation/non-formation in plants. We summarise the chemical and physical factors (root hair, soil-related factors, root exudates, and microorganisms) that determine rhizosheath formation, and focus on the important functions of the rhizosheath in plants under abiotic stress, especially in drought stress, phosphorus deficiency, aluminium stress, and salinity stress. Understanding the roles played by the rhizosheath and the mechanisms of its formation provides new perspectives for improving plant stress tolerance in the field, which will mitigate the increasing environmental stress conditions associated with on-going global climate change.

The small brown planthopper (SBPH), Laodelphax striatellus (Fallén) (Hemiptera: Delphacidae), is an increasing threat to Gramineae crops, posing significant risks to both the environment and food safety. β-asarone, as a promising green alternative to chemical insecticides, possesses wide application prospects in the crop protection field. To enhance the insecticidal activity of β-asarone, a series of derivatives were prepared through an active substructure splicing strategy, and their insecticidal activities against SBPH were evaluated. Among the 7 commercial compounds with chemical structures similar to β-asarone and 12 structural derivatives of β-asarone, compound 10, which incorporates the 2-chloropyridine functional group from flupyrimin, exhibited the most potent insecticidal activity against SBPH, with an 8.31-fold increase in insecticidal activity compared to β-asarone. Furthermore, transcriptome analysis showed that among the selected genes that may play important roles in insecticidal activity, an ABC transporter gene, MDR49, was most significantly down-regulated. MDR49 was highly expressed in the 4th-instar nymphs, with the highest expression level in the fat body, midgut, and abdomen. RNA interference (RNAi) against MDR49 significantly reduced susceptibility to compound 10 in SBPH, which revealed that MDR49 may be the candidate insecticidal target of compound 10. Additionally, the insecticidal spectrum revealed that compound 10 showed excellent efficacy against Bemisia tabaci (Gennadius) (Hemiptera: Aleyrodidae) and Tetranychus cinnabarinus (Boisduval) (Acarina: Tetranychidae). This study indicates that compound 10 could be further developed as a novel eco-friendly pesticide.

The synthetic peptide of lumican C-terminal 13 amino acids with the cysteine replaced by an alanine, hereafter referred to as lumikine (LumC13C-A: YEALRVANEVTLN), binds to TGFβ type I receptor/activin-like kinase5 (TBR1/ALK5) in the activated TGFβ receptor complex to promote corneal epithelial wound healing. The present study aimed to identify the minimum essential amino acid epitope necessary to exert the effects of lumikine via ALK5 and to determine the role of the Y (tyrosine) residue for promoting corneal epithelium wound healing. This study also aimed to determine the signaling pathway(s) triggered by lumican–ALK5 binding. For such, adult Lum knockout (Lum−/−) mice (~8–12 weeks old) were subjected to corneal epithelium debridement using an Agerbrush®. The injured eyes were treated with 10 µL eye drops containing 0.3 µM synthetic peptides designed based on the C-terminal region of lumican for 5–6 h. To unveil the downstream signaling pathways involved, inhibitors of the Alk5 and EGFR signaling pathways were co-administered or not. Corneas isolated from the experimental mice were subjected to whole-mount staining and imaged under a ZEISS Observer to determine the distance of epithelium migration. The expression of EGFR ligands was determined following a scratch assay with HTCE (human telomerase-immortalized cornea epithelial cells) in the presence or not of lumikine. Results indicated that shorter LumC-terminal peptides containing EVTLN and substitution of Y with F in lumikine abolishes its capability to promote epithelium migration indicating that Y and EVTLN are essential but insufficient for Lum activity. Lumikine activity is blocked by inhibitors of Alk5, EGFR, and MAPK signaling pathways, while EGF activity is only suppressed by EGFR and MAPK inhibitors. qRT-PCR of scratched HTCE cells cultures treated with lumikine showed upregulated expression of several EGFR ligands including epiregulin (EREG). Treatment with anti-EREG antibodies abolished the effects of lumikine in corneal epithelium debridement healing. The observations suggest that Lum/lumikine binds Alk5 and promotes the noncanonical Smad-independent TGFβ/TBRs signaling pathways during the healing of corneal epithelium debridement.

Rice (Oryza sativa L.) stands as one of the most critical staple crops globally, with its yield and water use efficiency (WUE) being pivotal for food security. This study aimed to evaluate the agronomic and physiological traits and WUE of six rice varieties under two irrigation regimes: alternate wetting and drying (AWD) and conventional irrigation (CI). The results showed the significant improvements in grain yield and WUE with variety improvement under both irrigation treatments. Under AWD, high water use efficiency varieties (HWVs) demonstrated pronounced enhancements, including tillers and spikelet production, filled grain rate, 1000-grain weight, harvest index, leaf area index, non-structural carbohydrate remobilization, photosynthesis and catalase and peroxidase activities of leaf, root and shoot biomass, and root activity. AWD was observed to synchronize and amplify grain yield (2–14%) and WUE, including both leaf-level (13.94–20.72%) and yield-level (23.20–30.87%) water use efficiencies (WUEL and WUEY). The water use potential for HWVs was substantially enhanced under AWD. The integration of variety improvement with AWD irrigation strategies effectively achieves the dual objectives of high yield and WUE, offering a promising approach for sustainable rice production.

In this paper, a room-temperature NO2 sensor based on a polyaniline (PANI)/black phosphorus (BP) composite material was proposed to solve the power consumption problem of traditional metal-oxide sensors operating at high temperatures. PANI was synthesized by chemical oxidative polymerization, whereas BP was synthesized by low-pressure mineralization. The PANI/BP composite materials were prepared via ultrasonic exfoliation and mixing. Various characterization techniques, including scanning electron microscope (SEM), X-ray diffraction (XRD), Fourier-transform infrared spectroscopy (FTIR), and X-ray photoelectron spectroscopy (XPS), confirmed the successful preparation of the PANI/BP composites and their excellent structural properties. The sensor demonstrated outstanding gas sensitivity in the NO2 concentration range of 2–60 ppm. In particular, the sensor showed a response exceeding 2200% at 60 ppm NO2 concentration when using a 1:1 mass ratio of PANI to BP in the composite material.

Compute‐in‐memory (CIM) is a pioneering approach using parallel data processing to eliminate traditional data transmission bottlenecks for faster, energy‐efficient data handling. Crossbar arrays with two‐terminal devices such as memristors and phase‐change memory are commonly employed in CIM, but they encounter challenges such as leakage current and increased power usage. Three‐terminal transistor arrays have potential solutions, yet large‐scale electrolyte‐gated transistors (EGTs) demonstrations are uncommon due to compatibility issues with existing photolithography processes. Herein, a 20 × 20 EGTs array is designed using indium‐gallium‐zinc‐oxide as the semiconductor channel and polyacrylonitrile (PAN) doped with C2F6LiNO4S2 as the electrolyte. Each transistor unit in the array can serve as a synapse, exhibiting a large conductance range, low energy consumption (6.984 fJ) for read–write operations, excellent repeatability, and quasilinear update characteristics. It has been confirmed that the EGTs array not only enables precise device programming but also virtually eliminates signal interference between neighboring devices during the programming process. Using 54 transistors in the EGTs array, unsupervised learning with a winner‐takes‐all neural network is successfully demonstrated. After 50 training iterations, the neural network achieves perfect 100% accuracy in classifying test‐set letters. The work demonstrates the potential of EGTs for constructing large‐scale integration synaptic array toward efficient computing architectures.

Abstract Industrial defect detection is an important part of intelligent manufacturing, and Internet of things (IoT)‐based defect detection is receiving more and more attention. Although deep learning (DL) can help defect detection reduce the cost and improve the accuracy of traditional manual quality inspection, DL requires huge computational resources and is difficult to be simply deployed on IoT devices with limited computational power and memory resources. Digital signal processor (DSP) is an important IoT device with small size, high performance and low energy consumption, which has been widely used in intelligent manufacturing. In order to perform accurate defect detection on DSP, the authors proposed various optimisation strategies and then used a parallel scheme to scale the model to execute on multiple cores. The authors’ method evaluated it on Northeastern University Surface Defect Dataset, Magnetic Tile Defect Dataset, Rail Surface Defect Dataset and Silk Cylinder Defect Dataset, and the experimental results showed that the authors’ method obtains faster speeds without accuracy loss compared to running the same Convolutional Neural Networks model on a mainstream desktop CPU. This means that the authors’ method can realise efficient and accurate defect detection on IoT devices with limited computational power and memory resources, which opens up new possibilities for future development in the field of smart manufacturing.

Background The prevention and prediction of sudden cardiac death (SCD) present persistent challenges, prompting exploration into common genetic variations for potential insights. T-box 5 (TBX5), a critical cardiac transcription factor, plays a pivotal role in cardiovascular development and function. This study systematically examined variants within the 500-bp region downstream of the TBX5 gene, focusing on their potential impact on susceptibility to SCD associated with coronary artery disease (SCD-CAD) in four different Chinese Han populations. Methods In a comprehensive case-control analysis, we explored the association between rs11278315 and SCD-CAD susceptibility using a cohort of 553 controls and 201 SCD-CAD cases. Dual luciferase reporter assays and genotype-phenotype correlation studies using human cardiac tissue samples as well as integrated in silicon analysis were applied to explore the underlining mechanism. Result Binary logistic regression results underscored a significantly reduced risk of SCD-CAD in individuals harboring the deletion allele (odds ratio = 0.70, 95% CI [0.55–0.88], p = 0.0019). Consistent with the lower transcriptional activity of the deletion allele observed in dual luciferase reporter assays, genotype-phenotype correlation studies on human cardiac tissue samples affirmed lower expression levels associated with the deletion allele at both mRNA and protein levels. Furthermore, our investigation revealed intriguing insights into the role of rs11278315 in TBX5 alternative splicing, which may contribute to alterations in its ultimate functional effects, as suggested by sQTL analysis. Gene ontology analysis and functional annotation further underscored the potential involvement of TBX5 in alternative splicing and cardiac-related transcriptional regulation. Conclusions In summary, our current dataset points to a plausible correlation between rs11278315 and susceptibility to SCD-CAD, emphasizing the potential of rs11278315 as a genetic risk marker for aiding in molecular diagnosis and risk stratification of SCD-CAD.

Background: Environmental factors serve as one of the important pathogenic factors for gliomas. Yet people focus only on the effect of electromagnetic radiation on its pathogenicity, while metals in the environment are neglected. This study aimed to investigate the relationship between metal ion stimulation and the clinical characteristics and immune status of GM patients. Methods: Firstly, mRNA expression profiles of GM patients and normal subjects were obtained from Chinese GM Genome Atlas (CGGA) and Gene Expression Omnibus (GEO) to identify differentially expressed metal ion stimulation-related genes(DEMISGs). Secondly, two molecular subtypes were identified and validated based on these DEMISGs using consensus clustering. Diagnostic and prognostic models for GM were constructed after screening these features based on machine learning. Finally, supervised classification and unsupervised clustering were combined to classify and predict the grade of GM based on SHAP values. Results: GM patients are divided into two different response states to metal ion stimulation, M1 and M2, which are related to the grade and IDH status of the GM. Six genes with diagnostic value were obtained: SLC30A3, CRHBP, SYT13, DLG2, CDK1, and WNT5A. The AUC in the external validation set was higher than 0.90. The SHAP value improves the performance of classification prediction. Conclusion: The gene features associated with metal ion stimulation are related to the clinical and immune characteristics of transgenic patients. XGboost/LightGBM Kmeans has a higher classification prediction accuracy in predicting glioma grades compared to using purely supervised classification techniques.

The remarkable skill of changing its grasp status and relocating its fingers to perform continuous in-hand manipulation is essential for a multifingered anthropomorphic hand. A commonly utilized method of manipulation involves a series of basic movements executed by a high-level controller. However, it remains unclear how these primitives evolve into sophisticated finger gaits during manipulation. Here, we propose an adaptive finger gait-based manipulation method that offers real-time regulation by dynamically changing the primitive interval to ensure the force/moment balance of the object. Successful manipulation relies on contact events that act as triggers for real-time online replanning of multifinger manipulation. We identify four basic motion primitives of finger gaits and create a heuristic finger gait that enables the continuous object rotation of a round cup. Our experimental results verify the effectiveness of the proposed method. Despite the constant breaking and reengaging of contact between the fingers and the object during manipulation, the robotic hand can reliably manipulate the object without failure. Even when the object is subjected to interfering forces, the proposed method demonstrates robustness in managing interference. This work has great potential for application to the dexterous operation of anthropomorphic multifingered hands.

Abstract Background Sestrin2 is a highly conserved stress-inducible protein with neuroprotective properties. Herein, we investigated the prognostic significance of serum sestrin2 in human intracerebral hemorrhage (ICH). Methods In this prospective observational longitudinal study, we enrolled 126 patients with supratentorial ICH as cases together with 126 healthy individuals as controls. Severity indicators were National Institutes of Health Stroke Scale (NIHSS) and hematoma volume. Prognostic parameters were early neurologic deterioration (END) and post-stroke 6-month poor prognosis [modified Rankin Scale (mRS) scores of 3–6]. Multivariate analysis was performed to assess relations of serum sestrin2 levels to severity and prognosis. Results Patients had statistically significantly higher serum sestrin2 levels than controls. Serum sestrin2 levels of patients were independently correlated with NIHSS scores and hematoma volume, as well as were substantially elevated in order of mRS scores from 0 to 6. Serum sestrin2 was identified as an independent predictor of END and poor prognosis. Based on the receiver operating characteristic curve, serum sestrin2 had a similar predictive ability for END and poor prognosis, as compared to NIHSS scores and hematoma volume. Prediction models of END and poor prognosis, in which serum sestrin2, NIHSS scores and hematoma volume were integrated, were visually described via nomogram, were reliable and stable under calibration curve and were of clinical benefit using decision curve analysis. Also, prediction model of poor prognosis showed dramatically higher discriminatory efficiency than any of NIHSS scores, hematoma volume and serum sestrin2. Conclusion Serum sestrin2 levels, which are obviously increased following acute ICH, are independently related to illness severity and poor clinical outcomes, substantializing serum sestrin2 as a clinically valuable prognostic biomarker of ICH.