Search

Abstract Deciphering how noncoding DNA determines gene expression is critical for decoding the functional genome. Understanding the transcription effects of noncoding genetic variants are still major unsolved problems, which is critical for downstream applications in human genetics and precision medicine. Here, we integrate regulatory-specific neural networks and tissue-specific gradient-boosting trees to build SVEN: a hybrid sequence-oriented architecture that can accurately predict tissue-specific gene expression level and quantify the tissue-specific transcriptomic impacts of structural variants across more than 350 tissues and cell lines. We further systematically screen a large-scale structural variants dataset derived from 3622 individuals and clinical structural variants from ClinVar, and provide an overview of transcriptomic impacts of structural variants in population. As a sequence-oriented model, SVEN is also able to predict regulatory effects for small noncoding variants. We expect that SVEN will enable more effective in silico analysis and interpretation of human genome-wide disease-related genetic variants.

Abstract While circular RNAs (circRNAs) exhibit lower abundance compared to corresponding linear RNAs, they demonstrate potent biological functions. Nevertheless, challenges arise from the low concentration and distinctive structural features of circRNAs, rendering existing methods operationally intricate and less sensitive. Here, we engineer an intelligent tetrahedral DNA framework (TDF) possessing precise spatial pattern-recognition properties with exceptional sensing speed and sensitivity for circRNAs. The signal output of TDF sensor occurs only when multivalent spatial pattern-recognition of a circRNA in unamplified samples. Using this sensor, we visualize the real-time response of endogenous circRNA expression in vitro neuronal cells and in vivo brain between pre-stroke and post-stroke male mice, identify the patients with acute ischemic stroke in clinical samples, as well as track the delivery of circRNA in photochromic stroked animal model. Thus, the TDF sensor provides a fast and sensitive tool for the detection of circRNA abundance in both physiological and pathophysiological conditions.

Abstract Spin-polarized edge states in two-dimensional materials hold promise for spintronics and quantum computing applications. Constructing stable edge states by tailoring two-dimensional semiconductor materials with bulk-boundary correspondence is a feasible approach. Recently layered NiI2 is suggested as a two-dimensional type-II multiferroic semiconductor with intrinsic spiral spin ordering and chirality-induced electric polarization. However, the one-dimensional spin-polarized edge states of multiferroic materials down to monolayer limit has not yet been studied. We report here that monolayer NiI2 was successfully synthesized on Au(111) by molecular beam epitaxy. Spin-polarized scanning tunneling microscopy/spectroscopy experiments visualize orientation-selective spin-polarized edge states in monolayer NiI2 islands. By performing first-principles calculations, we further confirm that spin-polarized edge states are selectively aligning along the Ni-terminated edges rather than the I-terminated edges. Our result will provide the opportunity to tune edge states by selected orientation and to develop spintronic devices in two-dimensional magnetic semiconductors.

The geothermal resource originating from the hot dry rock is a form of clean and renewable energy, which has the advantages of stable, efficient, and permanent. The foremost obstacle hindering its development resides in the construction of fracture channels for seepage and heat transfer within deep reservoirs characterized by low porosity and permeability. The conventional hydraulic fracturing method has high initiation pressure, single fracture shape, and difficult expansion under the constraint of deep high stress. Therefore, a liquid nitrogen cyclic cold shock method was proposed in this study. Liquid nitrogen is injected into the high-temperature rock periodically, inducing robust thermal stress through the temperature shock effect, thereby forming a complex fracture network. To study the damage mechanism of hot dry rock influenced by the temperature shock effect, the hot dry rock was subjected to a cyclic liquid nitrogen cooling treatment. The changes in temperature distribution, pore structure, and mechanical characteristics were tested and the cascade failure mechanism of “temperature shock-pore development-mechanical damage” was analyzed. The main conclusions are as follows: liquid nitrogen cold shock causes a temporal-spatial drastic change in the temperature field, marked by a high cooling rate and a large temperature gradient, and the induced thermal stress reaches up to 6.75 MPa. The number of pores increases, the size expands, and the increase in micro and mesopores is most significant, with a maximum porosity of 10.45%. Under the influence of high-temperature differences and multiple cold shocks, the number of macropores and fractures increases, giving rise to the formation of an interconnected network of fractures. This further increases the plasticity of the hot dry rock, reducing the tensile strength to only 1.70 MPa with a smaller damage threshold. Temperature shock induces mineral grain shrinkage, generating tensile stress at the boundaries between grains. When its value exceeds the tensile strength, tensile cracks will be generated. Pores and cracks mainly occur at the boundaries and within the interior of quartz grains. Temperature is the main controlling factor of hot dry rock damage, and the cyclic cold shocks serve to ensure sustained damage. The differences in the thermal expansion coefficients of mineral grains, the rapid cooling of liquid nitrogen, and the fatigue damage of cyclic shock are the main reasons for the damage of hot dry rock.

Abstract To enhance the accuracy of fine‐grained image classification and address challenges such as excessive interference factors within the dataset, inadequate extraction of local key features, and insufficient channel semantic association, a dual‐branch information interaction model that integrates convolutional neural networks (CNN) with Vision Transformers is proposed. This model leverages the Vision Transformer branch to extract global features, which are subsequently combined with the CNN branch to further augment the model's capability for local information extraction. In order to enhance the ability of the CNN branch to extract global information and reduce the loss of feature information, a feature enhancement module is added to the CNN branch. Since the Vision Transformer branch directly convolves with the convolution kernel will result in the inability to learn the underlying features of the image, a shallow feature extraction module is proposed, and the CNN and Vision Transformer branches interact with the information of the dual branches through the down‐sampling Down module and the up‐sampling UP module. The accuracy of the improved method on CUB‐200‐2011, Stanford Cars and FGVC‐Aircraft fine‐grained image classification datasets are 95.2%, 97.1% and 96.9%, respectively. The experimental results show that the method has good generalization on different datasets.

Abstract Blockchain trilemma is a considerable obstacle for today's decentralized systems. It is hard to achieve a perfect balance among decentralization, security, and scalability. Many popular blockchain platforms sacrifice scalability to preserve decentralization and security, resulting in low speed, reduced throughput, and poor real‐time performance (the time from transaction initiation to confirmation). Currently, there are several technologies, such as sharding, directed acyclic graph technology, sidechains, off‐chain state channels etc., that aim to improve throughput and real‐time performance. However, most of these solutions compromise the core feature of blockchain, which is decentralization, and introduce new security risks. In this paper, the authors propose a novel method, called MEchain, based on the Proof of Time Series Algorithm. MEchain consists of two models: the multi‐chain model and the elastic‐chain model. The authors’ experimental results show that these two models can enhance real‐time performance and throughput to a higher level in the industry.

Abstract Light, as an energy source for plant photosynthesis, can not only affect the growth and development of plants, but also affect their leaf color. This study used white (WL), red (RL), and blue light (BL) to treat tea cuttings, aiming to investigate the effect of light quality on the color of tea leaves. The results showed that tea leaves turned yellow under red light, the SPAD and Fv/Fm values were significantly lower than WL and BL. Full-length transcriptome was analyzed, photosynthesis and chlorophyll biosynthesis related genes such as PsbS, Psb28, HemL, and POR had the lowest expression levels under RLCarotenoid biosynthesis related genes ZEP, ABA2, and CRTISO had the higher expression levels under RL. This study revealed the molecular mechanism of RL induced leaf yellowing in tea plants, providing new insights for the application of light quality in tea plants.

Abstract This study is to analyse the failure patterns and long-term survival after stereotactic body radiotherapy (SBRT) in patients with T1-3N0M0 inoperable non-small cell lung cancer (NSCLC). Early-stage NSCLC patitents who received SBRT at Zhejiang Cancer Hospital from January 2012 to September 2018 were retrospectively analyzed. The primary endpoint were the patterns of disease progression, which were divided into local recurrence, regional failure, and distant metastasis. Kaplan-Meier method survival analysis was used to calculate overall survival (OS), progression-free survival (PFS). Cox model was used for univariate analysis and multivariate analysis. A total of 215 patients with 224 lesions were enrolled. After the median follow-up time of 50.8 months (1.0-117.9 months), 76 (35.3%) patients progressed, with regional progression occurring in 4 cases (1.8%), local and local-regional progression in 17 cases (7.9%), various distant metastases developing in 55 cases (25.6%). The OS rates at 1, 3, and 5 years were 97.1%, 80.9%, and 63.8%, respectively, with a median OS of 92.2 months (95%CI, 61.5-122.9 months). The PFS rates at 1, 3, and 5 years were 87.5%, 65.9%, and 50.8%, respectively, with a median PFS of 62.2 months (95% CI, 45.0-59.4 months). There was no significant difference in OS (P = 0.832) and PFS (P = 0.672) between the two groups with or without pathology. Multivariate analysis showed that BED and patient age were independent prognostic factors affecting early-stage lung cancer survival (all P

Abstract Objective This study aims to review and summarize the ultrasound characteristics of alveolar soft part sarcoma (ASPS) in children. Methods We retrospectively analyzed 20 pediatric ASPS cases confirmed by surgery or biopsy at our hospital between January 2014 and January 2024. Clinical data, including age, sex, symptoms, and tumor location, were collected. Ultrasound reports and images were reviewed to extract data on tumor size, boundaries, echogenicity, and vascularity. Results The study included 20 children with ASPS. The tumors were located in the trunk and limbs (50%), as well as in the head and neck (50%). Compared with tumors in the trunk and limbs, head and neck tumors were smaller in size, had more pronounced symptoms, and had a lower incidence of metastasis. Ultrasound features predominantly included hypoechoic masses with clear boundaries, heterogeneous echogenicity, and rich internal and surrounding vascularity, often with tortuous and dilated blood vessels. Eight patients had distant metastases at diagnosis, seven of which involved the lungs. There was a moderate correlation between tumor size and the risk of distant metastasis (r = 0.64). Conclusion Understanding the clinical and ultrasound characteristics of pediatric ASPS can facilitate earlier and more accurate diagnosis.

Abstract Piezoelectricity, a fundamental property of perovskite ferroelectrics, endows the materials at the heart of electromechanical systems spanning from macro to micro/nano scales. Defect engineering strategies, particularly involving heterovalent trace impurities and derived vacancies, hold great potential for adjusting piezoelectric performance. Despite the prevalent use of defect engineering for modification, a comprehensive understanding of the specific features that positively impact material properties is still lacking, this knowledge gap impedes the advancement of a universally applicable defect selection and design strategy. In this work, we select perovskite KTa1−x Nb x O3 single crystals with orthorhombic phase as the matrix and introduce Fe and Mn elements, which are commonly used in “hard” ferroelectrics as dopants. We investigate how transition-metal doping modifies piezoelectric properties from the perspective of intrinsic polarization behaviors. Interestingly, despite both being doped into the B-site as an acceptor, Mn doping enhances the local structural heterogeneity, greatly bolstering the piezoelectric coefficient beyond 1000 pC/N, whereas Fe doping tends to stabilize the polarization, leading to a substantial improvement in the mechanical quality factor up to 700. This work deciphers the diverse impacts of transition metal impurities on regulating polarization structures and modifying piezoelectric properties, providing a good paradigm for strategically designing perovskite ferroelectrics.

Abstract Synaptic ribbons, recognized for their pivotal role in conveying sensory signals in the visual pathway, are intricate assemblages of presynaptic proteins. Complexin (CPX) regulates synaptic vesicle fusion and neurotransmitter release by modulating the assembly of the soluble NSF attachment protein receptor (SNARE) complex, ensuring precise signal transmission in the retina and the broader central nervous system (CNS). While CPX1 or CPX2 isoforms (CPX1/2) play crucial roles in classical CNS synapses, CPX3 or CPX4 isoforms (CPX3/4) specifically regulate retinal ribbon synapses. These isoforms are essential for sustaining synaptic plasticity related to light signaling, adapting to changes in circadian rhythms, and dynamically regulating visual function under varying light conditions. This review explores the regulation of synaptic vesicle release by CPX in both the CNS and retinal ribbon synapses, with a focus on the mechanisms governing CPX3/4 function in the retina. Additionally, by reviewing the role of CPX and ribbon synapse dysfunction in non-retinal diseases, we further hypothesize the potential mechanisms of CPX in retinal diseases and propose therapeutic strategies targeting CPX to address retinal and CNS disorders associated with synaptic dysfunction.

Abstract Point cloud completion is a crucial task in the field of 3D imaging and is becoming a current research hotspot. However, traditional point cloud completion methods often fail to accurately restore the local details of objects due to the lack of detailed descriptions of the missing parts. This paper proposes a performance enhancement scheme for point cloud completion using tactile information. By employing a U-Net-based tactile feature extraction and fusion module, we enhance point cloud completion through the integration of tactile information. We validated our proposed network on the 3DVT dataset, and the experimental results demonstrate that our method effectively improves the performance of point cloud completion. Additionally, we conducted simulation experiments to mimic real-world scenarios where a robotic arm contacts objects, obtaining tactile point clouds using a mounted tactile simulator. These tactile point clouds were then used in related point cloud completion experiments, and the results were evaluated. The experimental results indicate that our proposed method significantly enhances the performance of point cloud completion and improves the local detail of the completed point clouds.

Abstract Due to the intermittency and volatility of distributed power sources, the microgrid system has poor stability and high operation cost. Therefore, the study proposes an economic optimization scheduling strategy based on the chaotic mapping butterfly optimization algorithm and the mathematical model of microgrid group system. The study creates simulation trials of function poles and microgrid group operation to confirm the strategy’s efficacy. According to the experimental findings, the multimodal function of the enhanced butterfly optimization method had a variance of 0.0000E + 00, and the function’s optimal value was less than 10–30, and the calculation time is 4.5s. The variance on the fixed dimensional function was 0.0000E + 00 and the optimal value of the function was 10 − 3.5,and the calculation time is 4.7s. The algorithmic curve all digging depth was maximum and convergence speed was fastest. The microgrid group system had the lowest economic cost of 4029.32 yuan in the grid-connected mode and 3343.39 yuan in the off-grid mode. The study proves that the energy coordination and economic management of this strategy are greatly optimized, which can effectively protect the energy storage equipment and guarantee the smooth power consumption of the system. This provides an innovative theoretical basis for optimization scheduling of microgrid group.

Abstract Under the influence of environmental pollution and energy scarcity, integrated energy systems (IES) have received extensive attention in the field of energy supply due to their ability to consume renewable energy and enhance energy utilization. In the context of low‐carbon scheduling for IES, numerous studies calculate the system's carbon emissions based on the carbon emission coefficients of energy devices. However, IES is a multi‐energy coupling system in which a device's energy input can originate from multiple sources with varying degrees of carbon emissions, making it difficult to accurately calculate the resulting carbon emissions using fixed coefficients. Consequently, a carbon emission flow (CEF) model is constructed for the system to calculate carbon emissions. In addition to the basic input–output CEF model, the CEF model for energy storage devices is considered, and carbon emission constraints during system operation are formulated based on the CEF model. Furthermore, many studies on low‐carbon scheduling of IES overlook the uncertainties associated with load and renewable energy. Therefore, a two‐stage scheduling model consisting of day‐ahead stage and intra‐day stage is developed to achieve reliable energy supply. Finally, through experiments, the low‐carbon performance and reliability of the model are validated.

Abstract Superconductors play a crucial role in the advancement of high-field electromagnets. Unfortunately, their performance can be compromised by thermomagnetic instabilities, wherein the interplay of rapid magnetic and slow heat diffusion can result in catastrophic flux jumps, eventually leading to irreversible damage. This issue has long plagued high-J c Nb3Sn wires at the core of high-field magnets. In this study, we introduce a large-scale GPU-optimized algorithm aimed at tackling the complex intertwined effects of electromagnetism, heating, and strain acting concomitantly during the quenching process of superconducting coils. We validate our model by conducting comparisons with magnetization measurements obtained from short multifilamentary Nb3Sn wires and further experimental tests conducted on solenoid coils while subject to ramping transport currents. Furthermore, leveraging our developed numerical algorithm, we unveil the dynamic propagation mechanisms underlying thermomagnetic instabilities (including flux jumps and quenches) within the coils. Remarkably, our findings reveal that the velocity field of flux jumps and quenches within the coil is correlated with the cumulated Joule heating over a time interval rather than solely being dependent on instantaneous Joule heating power or maximum temperature. These insights have the potential to optimize the design of next-generation superconducting magnets, thereby directly influencing a wide array of technologically relevant and multidisciplinary applications.

Objective Based on the varying number and relative positions of cervical disc replacement (CDR) and anterior cervical discectomy and fusion (ACDF) procedures, three‐segment hybrid surgery (HS) presents a diverse structural approach. Currently, the potential differential effects of HS with different segment combinations and surgical procedures on overloaded vertebral body (OVB) occurrence remain unexplored. The purpose of this retrospective study is to compare the clinical and radiological outcomes of HS and ACDF in treating cervical degenerative disc disease (CDDD), aiming to provide further insights into OVB. Methods This study included patients with three‐level CDDD who underwent ACDF or HS at our institution. Eligible patients were divided into three groups: Type I (one‐level CDR and two‐level ACDF), Type II (two‐level CDR and one‐level ACDF), and ACDF (three‐level ACDF). For radiographic analysis, patients were further divided into the Replacement Segment Group and the Nonreplacement Segment Group based on the presence of replacement segments above and below the OVB. Clinical outcomes were evaluated using visual analog scale (VAS) scores for neck and arm pain, Japanese Orthopedic Association (JOA) scores, and neck disability index (NDI) scores. The cervical radiological parameters assessed included (1) vertebral cross‐sectional area (CSA), (2) wedge angle (WA), (3) anterior vertebral height (AH), (4) posterior vertebral height (PH), and (5) Hounsfield unit (HU) values. Statistical methods included paired t‐test, ANOVA test, and chi‐square test. Independent samples t‐test, Mann–Whitney U test, and Wilcoxon signed‐rank test were used to compare the differences between two groups according to the results of normal distribution test. Results A total of 123 patients, evenly distributed among three groups, were included and were well matched in terms of demographic characteristics. The likelihood of vertebral body collapse (VBC) was notably higher in the ACDF group (41.5%) compared with the Type I (17.9%) and Type II (8.9%) groups (p

Purpose: Our previous study in 2009 concluded that glutamine may shorten the length of hospital stay (LOS) in patients with severe burns. Recent large-scale studies have suggested a decline in the effectiveness of glutamine in treating patients with severe burns over the last decade. Therefore, we conducted this systematic review and meta-analysis to update the status of glutamine uses in patients with severe burns. Methods: We retrieved related literature prior to December 2022 from the PubMed, Web of Science, Cochrane Library, Embase, SinoMed, Wanfang, and CNKI databases. Terms such as glutamine, enteral and burn were linked for searching. Adults patients with severe burns were included and non-randomized controlled trials were excluded. Data from studies that compared enteral glutamine for severe burns with a control group were extracted. The primary outcomes of mortality and infectious morbidities were pooled and analyzed. The modified Jadad scale and Cochrane collaboration's tool were used to assess the risk of bias in RCTs, and the Review Manager 5.4 was used to pool and analyze the data. Results: Six randomized controlled trials involving 1398 patients were included in the analysis. There were no significant differences in overall mortality (risk ratio (RR) = 0.37; 95% confidence interval (CI): 0.06 − 2.37; p = 0.300) or infectious morbidities (RR = 0.73; 95% CI: 0.41 − 1.31; p = 0.290). The incidence of multiple organ dysfunction syndrome was similar between the 2 groups (RR = 0.27; 95% CI: 0.03 − 2.24; p = 0.220). The LOS (mean difference (MD) = -8.97; 95% CI: -15.22 to -2.71; p = 0.005) and LOS/total burn surface area (MD = -0.27; 95% CI: -0.54 to 0.00; p = 0.050) decreased in the enteral glutamine group. The incidence of wound infection was significantly reduced (RR = 0.42; 95% CI: 0.16 − 1.06; p = 0.070). Conclusion: Compared to the control group, enteral glutamine administration may not improve the mortality, although it may be associated with a shorter LOS, a lower LOS/total burn surface area ratio, and may reduce the risk of wound infection in patients with severe burns.

AIM: To explore the current application and research frontiers of global ophthalmic optical coherence tomography (OCT) imaging artificial intelligence (AI) research. METHODS: The citation data were downloaded from the Web of Science Core Collection database (WoSCC) to evaluate the articles in application of AI in ophthalmic OCT published from January 1, 2012 to December 31, 2023. This information was analyzed using CiteSpace 6.2.R2 Advanced software, and high-impact articles were analyzed. RESULTS: In general, 877 articles from 65 countries were studied and analyzed, of which 261 were published by the United States and 252 by China. The centrality of the United States is 0.33, the H index is 38, and the H index of two institutions in England reaches 20. Ophthalmology, computer science, and AI are the main disciplines involved. Hot keywords after 2018 include deep learning (DL), AI, macular degeneration, and automatic segmentation. CONCLUSION: The annual number of articles on AI applications in ophthalmic OCT has grown rapidly. The United States holds a prominent position. Institutions like the University of California System and the University of London are spearheading advancements. Initial researches centered on the automatic recognition and diagnosis of ocular diseases leveraging traditional machine learning (ML) technology and OCT images. Nowadays, the imaging process algorithm selection has shifted its focus towards DL. Concurrently, optical coherence tomography angiography (OCTA) and computer-aided diagnosis (CAD) have emerged as key areas of contemporary research.

AIM: To establish a meaningful standard for diagnosing ocular metastasis (OM) in menopausal breast cancer (BC) women, and explore the relationship between CA-153, CA-125, apolipoprotein A, and OM. METHODS: A total of 1362 menopausal female BC patients with OM volunteered to take part in this study between July 2012 and July 2022. Women with BC who are menopausal were found to have an OM incidence of 1.6%. Furthermore, CA-153, CA-125, and apolipoprotein A (Apo A) all contributed to OM in women with BC who are postmenopausal according to binary logistic regression. Receiver operating curve (ROC) analysis was used to assess the diagnostic value of OM in patients with BC. RESULTS: Both CA-153 and CA-153+CA-125 showed a higher sensitivity of 95.45%, whereas CA-153+Apo A illustrated the highest specificity of 99.02%. Moreover, CA-153 and CA-153+CA-125 had higher areas under the curve (AUC) of 0.973. CONCLUSION: The data indicate that the serum concentrations of CA-153 exhibited the most significant predictors of the diagnosis of OM in menopausal women with BC. The current study researches the utility of risk factors in predicting of OM in menopausal BC women and put forward the latest suggestions on their clinical application.

Manual semen evaluation methods are subjective and time-consuming. In this study, a deep learning algorithmic framework was designed to enable non-invasive multidimensional morphological analysis of live sperm in motion, improve current clinical sperm morphology testing methods, and significantly contribute to the advancement of assisted reproductive technologies. We improved the FairMOT tracking algorithm by incorporating the distance and angle of the same sperm head movement in adjacent frames, as well as the head target detection frame IOU value, into the cost function of the Hungarian matching algorithm. For sperm morphology, we used the BlendMask segmentation method to segment individual sperm. SegNet was used to separate the head, midpiece, and principal piece comments from each sperm. Experienced in vivo sperm physicians confirmed a morphological accuracy percentage of 90.82%. A total of 1272 samples were collected from multiple tertiary hospitals for validation of the system, which were also evaluated by physicians. The results of our system were highly consistent with those of manual microscopy. This study realized the automated detection of progressive motility and morphology of sperm simultaneously, which is crucial for selection of morphologically normal and motile sperm for intracytoplasmic sperm injection.

Gray sufu is a traditional Chinese fermented soybean curd, and its flavor is significantly influenced by bacterial community. In this study, volatile flavor compounds (VFCs) were examined by headspace solid‐phase microextraction (HS-SPME) in conjunction with gas chromatography and mass spectrometry (GC‐MS). Additionally, bacterial community was analyzed using high-throughput sequencing. The results showed that, a total of 156 VFCs were tentatively identified, in which 8 esters, 6 S/N-containing compounds, 3 alcohols, 3 aldehydes, 1 ketone and 3 other compounds were recognized as the main characteristic VFCs. The abundant S/N-containing compounds are the most important flavor characteristics of gray sufu. A total of 4 phyla and 12 genera were revealed as dominant bacteria. Firmicutes and Proteobacteria were the most abundant phylum, whereas Bacillus, Tetragenococcus and Lactococcus were the prevailing genera. According to the KEGG pathway annotation, amino acid metabolism (26.98%) was the highest metabolic pathway. Among them, aromatic amino acids metabolism accounted for the highest proportion, up to 34.94%. Correlation analysis showed that Lactobacillus, Tetragenococcus, Bacillus, Pseudomonas and Halanaerobium were the top five positive flavor-producing bacteria. The results will be helpful for understanding the fermentation mechanism of gray sufu and improving flavor quality by developing microbial regulation strategies.

Data curation for a hospital-based cancer registry heavily relies on the labor-intensive manual abstraction process by cancer registrars to identify cancer-related information from free-text electronic health records. To streamline this process, a natural language processing system incorporating a hybrid of deep learning-based and rule-based approaches for identifying lung cancer registry-related concepts, along with a symbolic expert system that generates registry coding based on weighted rules, was developed. The system is integrated with the hospital information system at a medical center to provide cancer registrars with a patient journey visualization platform. The embedded system offers a comprehensive view of patient reports annotated with significant registry concepts to facilitate the manual coding process and elevate overall quality. Extensive evaluations, including comparisons with state-of-the-art methods, were conducted using a lung cancer dataset comprising 1428 patients from the medical center. The experimental results illustrate the effectiveness of the developed system, consistently achieving F1-scores of 0.85 and 1.00 across 30 coding items. Registrar feedback highlights the system’s reliability as a tool for assisting and auditing the abstraction. By presenting key registry items along the timeline of a patient’s reports with accurate code predictions, the system improves the quality of registrar outcomes and reduces the labor resources and time required for data abstraction. Our study highlights advancements in cancer registry coding practices, demonstrating that the proposed hybrid weighted neural-symbolic cancer registry system is reliable and efficient for assisting cancer registrars in the coding workflow and contributing to clinical outcomes.

The advent of single cell transposase-accessible chromatin sequencing (scATAC-seq) technology enables us to explore the genomic characteristics and chromatin accessibility of blood cells at the single-cell level. To fully make sense of the roles and regulatory complexities of blood cells, it is critical to collect and analyze these rapidly accumulating scATAC-seq datasets at a system level. Here, we present scBlood (https://bio.liclab.net/scBlood/), a comprehensive single-cell accessible chromatin database of blood cells. The current version of scBlood catalogs 770,907 blood cells and 452,247 non-blood cells from ∼400 high-quality scATAC-seq samples covering 30 tissues and 21 disease types. All data hosted on scBlood have undergone preprocessing from raw fastq files and multiple standards of quality control. Furthermore, we conducted comprehensive downstream analyses, including multi-sample integration analysis, cell clustering and annotation, differential chromatin accessibility analysis, functional enrichment analysis, co-accessibility analysis, gene activity score calculation, and transcription factor (TF) enrichment analysis. In summary, scBlood provides a user-friendly interface for searching, browsing, analyzing, visualizing, and downloading scATAC-seq data of interest. This platform facilitates insights into the functions and regulatory mechanisms of blood cells, as well as their involvement in blood-related diseases.

The rapid development of artificial intelligence has driven the transformation of educational evaluation into big data-driven. This study used a systematic literature review method to analyzed 44 empirical research articles on the evaluation of big data education. Firstly, it has shown an increasing trend year by year, and is mainly published in thematic journals such as educational technology, science education, and language teaching. Chinese and American researchers have made the greatest contributions in this field. Secondly, the algorithmic models for big data education evaluation research are diverse, the text modality is the most popular, the evaluation subjects are mainly college students, with fewer primary and secondary school students, and science is the discipline that most commonly applies big data education evaluation. The evaluation objectives of big data education evaluation mainly focus on five aspects: high-order thinking analysis, learning performance prediction, learning emotion recognition, teaching management decision-making, and evaluation mode optimization, and the text modality is widely used for data collection in high-order thinking analysis; regardless of the evaluation objectives, higher education students are the most widely evaluated objects; the science discipline is the main field of using big data technology to empower teaching evaluation. Thirdly, the current research topics of big data education evaluation mainly focus on online learning behavior and environmental participation evaluation, process assessment of learning motivation and emotional analysis, development and optimization of subject domain big data models, cognitive diagnosis and high-order thinking skills evaluation, and design of learning analysis frameworks based on data mining.

Alzheimer’s disease is a neurodegenerative disorder characterized by cognitive dysfunction and behavioral abnormalities. Neuroinflammatory plaques formed through the extracellular deposition of amyloid-β proteins, as well as neurofibrillary tangles formed by the intracellular deposition of hyperphosphorylated tau proteins, comprise two typical pathological features of Alzheimer’s disease. Besides symptomatic treatment, there are no effective therapies for delaying Alzheimer’s disease progression. MicroRNAs (miR) are small, non-coding RNAs that negatively regulate gene expression at the transcriptional and translational levels and play important roles in multiple physiological and pathological processes. Indeed, miR-146a, a NF-κB-regulated gene, has been extensively implicated in the development of Alzheimer’s disease through several pathways. Research has demonstrated substantial dysregulation of miR-146a both during the initial phases and throughout the progression of this disorder. MiR-146a is believed to reduce amyloid-β deposition and tau protein hyperphosphorylation through the TLR/IRAK1/TRAF6 pathway; however, there is also evidence supporting that it can promote these processes through many other pathways, thus exacerbating the pathological manifestations of Alzheimer’s disease. It has been widely reported that miR-146a mediates synaptic dysfunction, mitochondrial dysfunction, and neuronal death by targeting mRNAs encoding synaptic-related proteins, mitochondrial-related proteins, and membrane proteins, as well as other mRNAs. Regarding the impact on glial cells, miR-146a also exhibits differential effects. On one hand, it causes widespread and sustained inflammation through certain pathways, while on the other hand, it can reverse the polarization of astrocytes and microglia, alleviate neuroinflammation, and promote oligodendrocyte progenitor cell differentiation, thus maintaining the normal function of the myelin sheath and exerting a protective effect on neurons. In this review, we provide a comprehensive analysis of the involvement of miR-146a in the pathogenesis of Alzheimer’s disease. We aim to elucidate the relationship between miR-146a and the key pathological manifestations of Alzheimer’s disease, such as amyloid-β deposition, tau protein hyperphosphorylation, neuronal death, mitochondrial dysfunction, synaptic dysfunction, and glial cell dysfunction, as well as summarize recent relevant studies that have highlighted the potential of miR-146a as a clinical diagnostic marker and therapeutic target for Alzheimer’s disease.

Hydrogel-based patches have demonstrated their values in diabetic wounds repair, particularly those intelligent dressings with continuous repair promoting and monitoring capabilities. Here, we propose a type of dual physiological responsive structural color particles for wound repair. The particles are composed of a hyaluronic acid methacryloyl (HAMA)-sodium alginate (Alg) inverse opal scaffold, filled with oxidized dextran (ODex)/quaternized chitosan (QCS) hydrogel. The photo-polymerized HAMA and ionically cross-linked Ca-Alg constitute to the dual-network hydrogel with stable structural color. Furthermore, the ODex/QCS hydrogel, combined with glucose oxidase (GOX), exhibits pH/glucose dual responsiveness. Moreover, antimmicrobial peptide (AMP) plus vascular endothelial growth factor (VEGF) are comprised within the GOX-doped ODex/QCS hydrogel. In the high-glucose wound environment, GOX catalyzes glucose to generate acidic products, triggering rapid release of AMP and VEGF. Importantly, this process also leads to structural color changes of the particles, offering significant potential for wound monitoring. It has been demonstrated that such particles greatly promote the healing progress of diabetic wound in vivo. These results indicate that the present dual responsive particles would find valuable applications in diabetic wounds repair and the associated areas.

Cardiac arrest can lead to severe neurological impairment as a result of inflammation, mitochondrial dysfunction, and post-cardiopulmonary resuscitation neurological damage. Hypoxic preconditioning has been shown to improve migration and survival of bone marrow–derived mesenchymal stem cells and reduce pyroptosis after cardiac arrest, but the specific mechanisms by which hypoxia-preconditioned bone marrow–derived mesenchymal stem cells protect against brain injury after cardiac arrest are unknown. To this end, we established an in vitro co-culture model of bone marrow–derived mesenchymal stem cells and oxygen–glucose deprived primary neurons and found that hypoxic preconditioning enhanced the protective effect of bone marrow stromal stem cells against neuronal pyroptosis, possibly through inhibition of the MAPK and nuclear factor κB pathways. Subsequently, we transplanted hypoxia-preconditioned bone marrow–derived mesenchymal stem cells into the lateral ventricle after the return of spontaneous circulation in an 8-minute cardiac arrest rat model induced by asphyxia. The results showed that hypoxia-preconditioned bone marrow–derived mesenchymal stem cells significantly reduced cardiac arrest–induced neuronal pyroptosis, oxidative stress, and mitochondrial damage, whereas knockdown of the liver isoform of phosphofructokinase in bone marrow–derived mesenchymal stem cells inhibited these effects. To conclude, hypoxia-preconditioned bone marrow–derived mesenchymal stem cells offer a promising therapeutic approach for neuronal injury following cardiac arrest, and their beneficial effects are potentially associated with increased expression of the liver isoform of phosphofructokinase following hypoxic preconditioning.

Powder preparation, forming process, microstructure, oxide particles, and precipitates of FeCrAl-ODS (Oxide Dispersion Strengthened) alloy fabricated by Selective Laser Melting (SLM) were systematically studied in this paper. Results indicate that after adding 0.1 wt% Y₂O₃ via ball milling, the formed samples showed fewer defects and a 20 HV increase in hardness under the same parameters. The optimal process parameters were: laser power 250 W, scanning speed 900 mm/s, and hatch spacing 0.09 mm. The longitudinal section of the SLM-formed FeCrAl-ODS alloy exhibited a typical molten pool structure with a layered distribution characteristic of SLM-formed alloys. A higher laser coupling efficiency and melt pool temperature led to a lower proportion of subgrains composed of low-angle grain boundaries in the FeCrAl-ODS alloy. Independent α′ phase (Cr-rich phase) and α′ phase attached to Y₂O₃ were observed in the SLM-formed FeCrAl-ODS alloy. Thess results are of great significance for developing ODS alloys fabricated via additive manufacturing.

Deep underground project takes place in an environment characterised by high water pressure and geostress. This poses a significant risk of disasters such as water surges and destabilisation of the peripheral rock body, especially under dynamic disturbances such as blasting. It is of paramount importance to investigate the evolution of rock energy and the damage characteristics resulting from the joint action of water pressure and geostress, both in theory and in engineering practice. Impact tests were conducted on red sandstone specimens using a self-developed rock dynamics test system that employs high hydraulic pressure and high stress. The specimens were subjected to various hydraulic pressures and axial static stresses while maintaining the same impact load. The resulting dynamic stress-strain curves were analysed to determine the evolution of energy reflectance, energy transmittance and energy dissipation rate with respect to water pressure and axial static stress. Furthermore, the strain rate effect on the energy dissipation rate of the rock was characterised. The rocks after impact were screened and the longitudinal wave velocity was measured, its fractal dimension and damage variables were determined, and the effects of varying water pressure and axial static stress on the rock (mass)'s damage and crushing properties were investigated. The findings indicate that as water pressure increases, the amplitude of reflected waves decreases whilst that of transmitted waves increases. Furthermore, the stress-strain curves of rocks transform from type I to type II. In addition, the reflectance of energy from red sandstone decreases rapidly at first before changing gradually as water pressure increases. The transmittance of energy, on the other hand, increases exponentially as the water pressure increases, and the axial static stress impacts the correlation between the two. As water pressure gradually increases from zero, the rate of energy dissipation initially increases briefly before continuously decreasing. The correlation between the two variables follows a reliable Gaussian function. Axial static stress impacts the relationship between the rate of energy dissipation in rocks and water pressure. As the axial static stress increases, so does the rate of energy dissipation. Additionally, the trend of increasing energy dissipation rate follows an increase and then a decrease in water pressure. The red sandstone energy dissipation rate displays a clear strain rate effect, whereby an increase in strain rate results in an overall increase followed by a decrease in the red sandstone energy dissipation rate. As water pressure increases, the dynamic damage of red sandstone decreases gradually. Furthermore, the fractal dimension depicts a trend of "gradual decrease-transient increase-sharp decrease to zero". Water pressure increases transiently as the fractal dimension of breakage increases in response to an increase in the axial static stress.

Objectives: This article reports a rare case of primary central nervous system lymphoma (PCNSL) found in a patient with thyroid cancer after surgery. Methods: The patient was initially misdiagnosed with brain metastases, and the diagnosis of PCNSL was later confirmed by pathology. Results: The analysis of this case and review of the relevant literature explores the possible mechanisms of the coexistence of thyroid cancer and PCNSL, as well as their diagnostic, differential diagnostic, and therapeutic challenges. Conclusions: The article suggests a possible correlation between the coexistence of multiple cancers and autoimmune diseases and emphasizes that disease cannot be only considered in a monolithic way.

Mg-Li alloys with high lithium concentrations possess a lightweight body-centered cubic (BCC) matrix structure (β-Li). Interspersed eutectics (primarily the reticulated I-phase) often form along phase boundaries (PBs) and grain boundaries (GBs) which strengthen the alloy but cause the loss of ductility due to the brittle behavior of I-phase. By modifying the Li content, we fabricated the (β+α) biphase Mg-Li alloy in which the α-Mg phase with a hexagonal close-packed structure (HCP) is embedded in β-Li matrix, significantly increasing interface density. The high-density interfaces mitigate the distribution and dimension of the I-phase along GBs and PBs. The alloy exhibits enhanced ductility (elongation (EL) = 17.8 %) compared with the alloy without the α-Mg phase (EL = 5.1 %). Structural characterizations unveil the strengthening mechanism of the nanoscale B2 (Li, Mg)3Zn-type precipitates in conjunction with the microscale I-phase. The (Li, Mg)3Zn nanophases augment the yield and ultimate tensile strength of the alloy without a discernible compromise in ductility, predominantly due to gliding dislocations cutting through the precipitates. In contrast, the microscale I-phase presents a formidable barrier to dislocation motion, facilitating dislocation pileups at interfaces and culminating in diminished ductility across the interface. In-situ stretching techniques were employed to scrutinize the microstructural evolution of alloys during tensile deformation, elucidating that the deformation compatibility of alloys correlates with the average size of the I-phase and their distribution along GBs and PBs. Corresponding to the orientation relationship (OR) between the α-Mg and β-Li phases {110}Li//{0001}Mg and Li //Mg, the slip continuity between α-Mg and β-Li on plane pairs of {123}Li-{112¯2}Mg and {112}Li-{112¯2}Mg assures the deformation compatibility through facilitating the deformation across interfaces. Simultaneously, during the stretching process, the dispersed I-phase instigates the emergence of sporadic microcracks, indicating gradual damage evolution. These discoveries offer novel insights into achieving exceptional strength-ductility amalgamations in Mg-Li alloys through microstructural adjustments.

Trehalose (TRE) was used to improve the gastrointestinal tolerance of Lactobacillus plantarum embedded with whey protein concentrate/pullulan (WPC/PUL) hydrogel and the embedded L. plantarum was applied to juice. The study indicated that 5% TRE significantly increased the viable counts of L. plantarum embedded in WPC/PUL hydrogel from (8.83 ± 0.03) to (9.14 ± 0.04) (lg (CFU/g)) in simulated gastric juice (SGJ) and from (9.13 ± 0.04) to (9.38 ± 0.04) (lg (CFU/g)) in simulated intestinal juice, respectively. The addition of TRE improved the glass transition temperature of WPC/PUL hydrogel and decreased the hardness and its solubility in SGJ, which may be responsible for the improved protection of WPC/PUL hydrogels on L. plantarum. In addition, TRE increased the viable counts of L. plantarum in WPC/PUL probiotic microcapsule juice at low pH and high temperature during storage.

Three new species of the genus Cicurina Menge, 1871 are described from Daba Mountain National Nature Reserve, Chongqing, China: C. chengkou sp. nov. (♂♀), C. dabashan sp. nov. (♂♀) and C. longihamata sp. nov. (♂♀). Morphological descriptions, photos and illustrations of copulatory organs are provided.

Abstract Objective Associations between serum lipid levels and osteoporosis and sarcopenia have been reported. However, few studies have reported a link between serum lipid levels and osteosarcopenia. In the present study, we investigated the association between serum high-density lipoprotein cholesterol (HDL-c) and osteosarcopenia. Methods A total of 1995 participants aged 50 years and above who underwent chest CT physical examinations from 2016 to 2019 were included. Demographic information, including age, sex, and body mass index, and laboratory data, including liver and kidney function, blood lipids (HDL-c, low-density lipoprotein cholesterol (LDL-c), triglyceride (TG), total cholesterol (TC), blood glucose, and serum albumin, were collected from the medical records system. Osteosarcopenia was defined on the basis of the presence of low bone mass (bone CT values

Abstract Trans-Himalayan winters are projected to become milder, with shifting precipitation patterns and freeze-thaw cycles; changing stressors for their lichen communities. Lichens from Antarctica and high latitudes are cryoresistant when dry, but susceptible to cell damage if frozen when wet, or subjected to repeated freeze-thaw events. Little is known regarding cryoresistance in high-elevation, mid-latitude lichens. We collected thalli of nine species of epiphytic lichenized fungi, from three regions of the trans-Himalayas; at ≈ 4000 m, 3400 m and 2400 m elevation. We subjected thalli to differing freezing (continuous − 18 °C and − 36 °C or freeze-thaw cycles in natural daylight) and moisture conditions. Even dry thalli suffered some damage. Frozen wet thalli had greater chlorophyll degradation and reduced chlorophyll content. There were no clear elevational trends in freeze-thaw susceptibility: it caused more damage than continuous freezing. The most freeze-thaw resilient lichens were Dolichousnea longissima (from 4000 m) and Usnea florida (from 2400 m). However, species from coldest sites were most resilient to extreme freezing. Under predicted climate change conditions these sites would experience fewer annual freeze-thaw cycles, annual sub-zero days and frost days. Reduced freezing constraints might allow range expansion of mid-elevation lichens, but increase competitive pressures and temperature stressors impacting high-elevation lichens.

Abstract Collagen fibers, one of the key load-bearing components of the extracellular matrix, contribute significantly to tissue integrity through their mechanical properties of strain-dependent stiffening. This study investigated the effects of bacterial collagenase on the mechanical behavior of individual bovine lung collagen fibers in the presence or absence of mechanical forces, with a focus on potential implications for emphysema, a condition associated with collagen degradation and alveolar wall rupture. Tensile tests were conducted on individual collagen fibers isolated from bovine lung tissue. The rate of degradation was characterized by the change in fiber Young’s modulus during 60 min of digestion under various mechanical conditions mimicking the mechanical stresses on the fibers during breathing. Compared to digestion without mechanical forces, a significantly larger drop of fiber modulus was observed in the presence of static or intermittent mechanical forces. Fiber yield stress was also reduced after digestion indicating compromised fiber failure. By incorporating fibril waviness obtained by scanning electron microscopic images, an analytic model allowed estimation of fibril modulus. A computational model that incorporated waviness and the results of tensile tests was also developed to simulate and interpret the data. The simulation results provided insights into the mechanical consequences of bacterial collagenase and mechanical forces on collagen fibers, revealing both fibril softening and rupture during digestion. These findings shed light on the microscale changes in collagen fiber structure and mechanics under enzymatic digestion and breathing-like mechanical stresses with implications for diseases that are impacted by collagen degradation such as emphysema.

Abstract Lack of health knowledge can be a main cause of barriers to early diagnosis and treatment, and it can also highlight the deficiencies in health education. Therefore, it is essential to understand the health knowledge needs of individuals and the related influencing factors in order to improve health education models. A total of 935 administrative staff (AS) were selected as study participants by convenience sampling in Yuxi City, China. An electronic questionnaire, comprising four parts—Health Knowledge Needs, Sociodemographic Characteristics, Health Psychology and Behavior, and Self-Reported Medical History—were used to collect data. Statistical analysis was conducted using an internal consistency test, Kruskal–Wallis test, principal component analysis, hierarchical clustering analysis, and binary logistic regression analysis, performed with SPSS version 19.0. The Health Knowledge Needs Questionnaire had a Cronbach’s α of 0.883 and a Guttman Split-Half coefficient of 0.907. The need rates for health knowledge exceeding 30% are as follows: Traditional Chinese Medicine, Hypertension, Weight Management, Dietary Nutrition and Food Hygiene, Hyperlipidemia, Gastrointestinal Diseases, Heart Diseases, and First Aid. Health knowledge needs were summarized into six dimensions: “Diseases with Low Health Knowledge Needs”, “Maternal and Child Health Care and Thyroid Diseases”, “Cardiovascular and Cerebrovascular Diseases and Malignancies”, “Health Preservation and First Aid”, “The Four Highs Syndrome”, and "Respiratory and Digestive Diseases”. Gender, self-rated economic pressure, family size, and self-reported number of diseases were identified as influencing factors of health knowledge needs (P

Abstract Wild species of crops serve as a valuable germplasm resource for breeding of modern cultivars. Rice (Oryza sativa L.) is a vital global staple food. However, research on genome evolution and diversity of wild rice species remains limited. Here, we present nearly complete genomes of 13 representative wild rice species. By integrating with four previously published genomes for pangenome analysis, a total of 101,723 gene families are identified across the genus, including 9834 (9.67%) core gene families. Additionally, 63,881 gene families absent in cultivated rice species but present in wild rice species are discovered. Extensive structural rearrangements, sub-genomes exchanges, widespread allelic variations, and regulatory sequence variations are observed in wild rice species. Interestingly, expanded but less diverse disease resistance genes in the genomes of cultivated rice, likely due to the loss of some resistance genes and the fixing and amplification of genes encoding resistance genes to specific diseases during domestication and artificial selection. This study not only reveals natural variations valuable for gene-level studies and breeding selection but also enhances our understanding on rice evolution and domestication.

Abstract Background Whether gastrointestinal hormones in patients with postprandial distress syndrome (PDS) are altered by acupuncture, and whether such alterations are related to the autonomic nervous system (ANS), remains an open question. Objective This study aims to investigate the effects of acupuncture on symptoms, serum hormones, and ANS in PDS patients. Methods This randomized controlled clinical trial was conducted at Beijing Hospital of Traditional Chinese Medicine affiliated with Capital Medical University. Sixty-two PDS patients were randomly assigned equally to acupuncture or sham acupuncture arm (3 sessions per week for 4-week). The main outcome measures which were evaluated at baseline and 4-week included cardinal symptoms, serum hormones including ghrelin, vasoactive intestinal peptide (VIP), substance P (SP), and ANS. Results Among the 62 randomly assigned participants, 51 (82%) were included in the baseline characteristics and outcome analysis. Gastrointestinal symptoms including response rate (p = 0.001) and dyspepsia symptom severity (p = 0.002) were significantly improved after acupuncture treatment. Serum ghrelin concentration was significantly higher in acupuncture group than in sham acupuncture group (8.34 ± 3.00 ng/ml versus 6.52 ± 2.00 ng/ml, p = 0.022) after 4-week treatment, instead of VIP and SP (p > 0.05). The acupuncture group had significantly higher vagal activity, showing with increasing of high-frequency component (HF, p ≤ 0.001) and decreasing of the ratio of low-frequency and HF (p ≤ 0.001). In relationship analysis, the HF component exhibited a significant inverse correlation with symptom severity (R = − 0.501, p ≤ 0.001), but not with ghrelin level (R = 0.026, p = 0.865). Conclusion Acupuncture may improve the symptoms and increase the ghrelin level of PDS patients, the therapeutic effect of acupuncture was associated with the alteration of vagal activity. Trial registration: The trial is registered with the ISRCTN registry, ISRCTN12511434. Registered 31 March 2017, https://www.isrctn.com/ .

Abstract Objective The weight-adjusted-waist index (WWI) is a novel obesity measurement indicator, and this study aims to determine the relationship between WWI and Familial hypercholesterolemia (FH). Methods Using data from the National Health and Nutrition Examination Survey (NHANES) from 2017 to March 2020, cross-sectional data from 3698 participants were analyzed. The study examined the correlation between WWI and FH using multivariate logistic regression and smooth curve fitting, and conducted subgroup analysis and interaction tests. Results The study sample consisted of 3698 subjects for whom the overall probable prevalence of FH was 5.43% and increased with WWI tertile (quantile 1: 4.00%; quantile 2: 4.94%; quantile 3: 7.34%); individuals with the highest WWI tertile were significantly more likely to have FH than those with the lowest tertile (OR = 4.60,95% CI: 2.00-10.60). Subgroup analysis and interaction tests showed significant significance between WWI and personal history of early Atherosclerotic cardiovascular disease (ASCVD), family history of early ASCVD and probable prevalence of FH (p

Abstract Background Sooty mold (SM), caused by Cladosporium species, is a pervasive threat to tea plant health, affecting both canopy structure and crop yield. Despite its significance, understanding the complex interplay between defense genes and metabolites in tea plants across various SM-infected canopy layers remains limited. Our study employed hyperspectral imaging, transcriptomic profiling, and metabolomic analysis to decipher the intricate mechanisms underlying the tea plant’s response to SM infection. Results Our hyperspectral imaging identified three critical wavelengths (552, 673, and 800 nm) inflection points associated with varying degrees of SM infection. This non-invasive method allows for the precise assessment of disease progression. Concurrently, transcriptome analysis revealed a wealth of differentially expressed genes (DEGs) enriched in metabolic pathways, secondary metabolite biosynthesis, and plant-pathogen interactions. Cluster analysis highlighted an intensified immune response in A2 and A3 samples. A comprehensive metabolomic profile identified 733 co-changed metabolites in SM-infected leaves, with alcohols, lipids (free fatty acids), hydrocarbons, and amino acids significantly accumulating in A1, while flavonoids were predominantly upregulated in A2 and A3. Weighted Gene Co-Expression Network Analysis (WGCNA) uncovered five hub genes (Dormancy-associated protein, Serine/threonine-protein phosphatase, ABC transporter, and some uncharacterized proteins) and two hub metabolites (D-Mannitol and 17-Hydroxylinolenic Acid) that exhibit significant relationships with DEGs and metabolites. Further co-expression analysis indicated that tea plants mainly employed genes and metabolites related to the biosynthesis of secondary metabolites, plant hormone signal transduction, and plant-pathogen interaction to combat SM. Conclusion This study establishes a foundation for understanding the immune mechanisms of tea plants across different canopy layers in response to SM infection. It not only sheds light on the complex defense strategies employed by tea plants but also identifies candidate genes and metabolites crucial for enhancing tea plant breeding and resistance to SM.

Abstract Background Circular RNAs (circRNAs) are differentially expressed in various cardiovascular diseases, including myocardial infarction (MI) injury. However, their functional role in necroptosis-induced loss of cardiomyocytes remains unclear. We identified a cardiac necroptosis-associated circRNA transcribed from the Cacna1c gene (circCacna1c) to investigate the involvement of circRNAs in cardiomyocyte necroptosis. Methods To investigate the role of circCacna1c during oxidative stress, H9c2 cells and neonatal rat cardiomyocytes were treated with hydrogen peroxide (H2O2) to induce reactive oxygen species (ROS)-induced cardiomyocyte death. The N 6-methyladenosine (m6A) modification level of circCacna1c was determined by methylated RNA immunoprecipitation quantitative polymerase chain reaction (MeRIP–qPCR) analysis. Additionally, an RNA pull-down assay was performed to identify interacting proteins of circCacna1c in cardiomyocytes, and the regulatory role of circCacna1c in target protein expression was tested using a western blotting assay. Furthermore, the MI mouse model was constructed to analyze the effect of circCacna1c on heart function and cardiomyocyte necroptosis. Results The expression of circCacna1c was found to be reduced in cardiomyocytes exposed to oxidative stress and in mouse hearts injured by MI. Overexpression of circCacna1c inhibited necroptosis of cardiomyocytes induced by hydrogen peroxide and MI injury, resulting in a significant reduction in myocardial infarction size and improved cardiac function. Mechanistically, circCacna1c directly interacts with heterogeneous nuclear ribonucleoprotein F (Hnrnpf) in the cytoplasm, preventing its nuclear translocation and leading to reduced Hnrnpf levels within the nucleus. This subsequently suppresses Hnrnpf-dependent receptor-interacting protein kinase 1 (RIPK1) expression. Furthermore, fat mass and obesity-associated protein (FTO) mediates demethylation of m6A modification on circCacna1c during necrosis and facilitates degradation of circCacna1c. Conclusion Our study demonstrates that circCacna1c can improve cardiac function following MI-induced heart injury by inhibiting the Hnrnpf/RIPK1-mediated cardiomyocyte necroptosis. Therefore, the FTO/circCacna1c/Hnrnpf/RIPK1 axis holds great potential as an effective target for attenuating cardiac injury caused by necroptosis in ischemic heart disease. Graphical Abstract

Highlights Metallic nanoparticles with excellent size controllability and high loading rate are obtained via ultrafast high temperature shock method. The Bi/CNRs-15 electrode exhibits an unprecedented rate performance (237.9 mAh g−1 at 2 A g−1) at − 60 °C, while the energy density of the full cell can reach to 181.9 Wh kg−1 at − 40 °C. A novel strategy of high-rate activation is proposed to obtain high capacity and superior stability at low temperature by creating new active sites for interfacial reaction.

Abstract Background To explore the value of computed tomography based radiomics in the differential diagnosis of drug-sensitive and drug-resistant pulmonary tuberculosis. Methods The clinical and computed tomography image data of 177 patients who were diagnosed with pulmonary tuberculosis through sputum culture and completed drug-susceptibility testing from April 2018 to December 2020 at the Second Hospital of Nanjing were retrospectively analyzed. Patients with drug-resistant pulmonary tuberculosis (n = 78) and drug-sensitive pulmonary tuberculosis (n = 99) were randomly divided into a training set (n = 124) and a validation set (n = 53) at a ratio of 7:3. Regions of interest were drawn to delineate the lesions and radiomics features were extracted from non-contrast computed tomography images. A radiomics signature based on the valuable radiomics features was constructed and a radiomics score was calculated. Demographic data, clinical symptoms, laboratory results and computed tomography imaging characteristics were evaluated to establish a clinical model. Combined with the Rad-score and clinical factors, a radiomics-clinical model nomogram was constructed. Results Thirteen features were used to construct the radiomics signature. The radiomics signature showed good discrimination in the training set (area under the curve (AUC), 0.891; 95% confidence interval (CI), 0.832–0.951) and the validation set (AUC, 0.803; 95% CI, 0.674–0.932). In the clinical model, the AUC of the training set was 0.780(95% CI, 0.700-0.859), while the AUC of the validation set was 0.692 (95% CI, 0.546–0.839). The radiomics-clinical model showed good calibration and discrimination in the training set (AUC, 0.932;95% CI, 0.888–0.977) and the validation set (AUC, 0.841; 95% CI, 0.719–0.962). Conclusions Simple radiomics signature is of great value in differentiating drug-sensitive and drug-resistant pulmonary tuberculosis patients. The radiomics-clinical model nomogram showed good predictive, which may help clinicians formulate precise treatments.

Enhancing the electrical conductivity of metals remains a critical challenge, as it directly determines the transmission efficiency of power electronic systems. Graphene-reinforced metal matrix composites have garnered widespread attention due to their exceptional electrical conductivity and low-temperature coefficient of resistance. This review thoroughly examines the intrinsic physical properties of Graphene and Cu, identifying specific obstacles in developing highly conductive composite materials. Despite the weak van der Waals interactions between Graphene and Cu, the work principle and interaction mechanism between Cu and Graphene are elucidated. The primary focus of this review is to explore methods for enhancing the electrical conductivity of Cu/Graphene composites through different design strategies and processing techniques. The more complex and critical factors encompass the quality of raw materials, processing techniques, dimensional precision, crystallographic orientation, and the interfacial properties between Graphene and Cu. The perspectives on the research gap and further development trends of Cu/Graphene composites are also discussed.