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Abstract Consecutive photoinduced electron transfer (conPET) processes accumulate the energies of two photons to overcome the thermodynamic limit of traditional photoredox catalysis. However, the excitation wavelength of conPET systems mainly focused on short wavelength visible light, leading to photodamage and incompatibility with large-scale reactions. Herein, we report on conPET systems triggered by near-infrared (NIR) and red light. Specifically, a blue-absorbing conPET photocatalyst, perylene diimide (PDI) is sensitized by a palladium-based photosensitizer to triplet excited state (3PDI*), which generates PDI radical anion (PDI•– ) over 100-fold faster than that in the conventional conPET. Accordingly, photoreduction with superior reaction rate and penetration depth, as well as reduced photodamage is detected. More importantly, our work offers comprehensive design rules for the triplet-mediated conPET strategy, whose versatility is confirmed by metal-free dye pairs and NIR-active PtTNP/PDI. Notably, our work achieves NIR-driven atom transfer radical polymerization using an inert aromatic halide as the initiator.

Abstract Background Accumulating studies have highlighted the significant role of circulating metabolomics in the etiology of reproductive system disorders. However, the causal effects between genetically determined metabolites (GDMs) and reproductive diseases, including primary ovarian insufficiency (POI), polycystic ovary syndrome (PCOS), and abnormal spermatozoa (AS), still await thorough clarification. Methods With the currently most comprehensive genome-wide association studies (GWAS) data of metabolomics, systematic two-sample Mendelian randomization (MR) analyses were conducted to disclose causal associations between 1,091 blood metabolites and 309 metabolite ratios with reproductive disorders. The inverse-variance weighted (IVW) method served as the primary analysis approach, and multiple effective MR methods were employed as complementary analyses including MR-Egger, weighted median, constrained maximum likelihood (cML-MA), contamination mixture method, robust adjusted profile score (MR-RAPS), and debiased inverse-variance weighted method. Heterogeneity and pleiotropy were assessed via MR-Egger intercept and Cochran’s Q statistical analysis. Outliers were detected by Radial MR and MR-PRESSO methods. External replication and metabolic pathway analysis were also conducted. Results Potential causal associations of 63 GDMs with POI were unearthed, and five metabolites with strong causal links to POI were emphasized. Two metabolic pathways related to the pathogenesis of POI were pinpointed. Suggestive causal effects of 70 GDMs on PCOS were detected, among which 7 metabolites stood out for strong causality with elevated PCOS risk. Four metabolic pathways associated with PCOS mechanisms were recognized. For AS, 64 GDMs as potential predictive biomarkers were identified, particularly highlighting two metabolites for their strong causal connections with AS. Three pathways underneath the AS mechanism were identified. Multiple assessments were conducted to further confirm the reliability and robustness of our causal inferences. Conclusion By extensively assessing the causal implications of circulating GDMs on reproductive system disorders, our study underscores the intricate and pivotal role of metabolomics in reproductive ill-health, laying a theoretical foundation for clinical strategies from metabolic insights.

Abstract Missing labels in multi-label datasets are a common problem, especially for minority classes, which are more likely to occur. This limitation hinders the performance of classifiers in identifying and extracting information from minority classes. Oversampling is an effective method for addressing imbalanced multi-label problems by generating synthetic instances to create a class-balanced dataset. However, the existing oversampling algorithms mainly focus on the location of the generated data, and there is a lack of design on how to complete the labels of the synthetic data. To address this issue, we propose MLAWSMOTE, a synthetic data generation algorithm based on matrix factorization weights. We introduce a weak supervised learning method in the oversampling method, optimize the weights of features and labels by using label correlation, and iteratively learn the ideal label weights. The mapping relationship between features and labels is learned from the dataset and the label correlation matrix. The oversampling ratio is defined based on the discrepancy between observed labels and the ideal label of synthetic instances. It mitigates the impact of missing minority labels on the model’s predictions. The labeling of synthetic instances is performed based on label prediction, and the potential labeling distribution is complemented. Experimental results on multiple multi-label datasets under different label missing ratios demonstrate the effectiveness of the proposed method in terms of ACC, Hamming loss, MacroF1 and MicroF1. In the validation of the four classifiers, MacroF1 decreased by 24.78%, 17.81%, 3.8% and 19.56%, respectively, with the increase of label loss rate. After applying MLAWSMOTE only decreased by 15.79%, 13.63%, 3.78% and 15.21%.

Objective: To elucidate the biological basis of the heart qi deficiency (HQD) pattern, an in-depth understanding of which is essential for improving clinical herbal therapy. Methods: We predicted and characterized HQD pattern genes using the new strategy, TCM-HIN2Vec, which involves heterogeneous network embedding and transcriptomic experiments. First, a heterogeneous network of traditional Chinese medicine (TCM) patterns was constructed using public databases. Next, we predicted HQD pattern genes using a heterogeneous network-embedding algorithm. We then analyzed the functional characteristics of HQD pattern genes using gene enrichment analysis and examined gene expression levels using RNA-seq. Finally, we identified TCM herbs that demonstrated enriched interactions with HQD pattern genes via herbal enrichment analysis. Results: Our TCM-HIN2Vec strategy revealed that candidate genes associated with HQD pattern were significantly enriched in energy metabolism, signal transduction pathways, and immune processes. Moreover, we found that these candidate genes were significantly differentially expressed in the transcriptional profile of mice model with heart failure with a qi deficiency pattern. Furthermore, herbal enrichment analysis identified TCM herbs that demonstrated enriched interactions with the top 10 candidate genes and could potentially serve as drug candidates for treating HQD. Conclusion: Our results suggested that TCM-HIN2Vec is capable of not only accurately identifying HQD pattern genes, but also deciphering the basis of HQD pattern. Furthermore our finding indicated that TCM-HIN2Vec may be further expanded to develop other patterns, leading to a new approach aimed at elucidating general TCM patterns and developing precision medicine.

Abstract Antibodies to Ebola virus glycoprotein (EBOV GP) represent an important correlate of the vaccine efficiency and infection survival. Both neutralization and some of the Fc-mediated effects are known to contribute the protection conferred by antibodies of various epitope specificities. At the same time, the role of the complement system remains unclear. Here, we compare complement activation by two groups of representative monoclonal antibodies (mAbs) interacting with the glycan cap (GC) or the membrane-proximal external region (MPER) of GP. Binding of GC-specific mAbs to GP induces complement-dependent cytotoxicity (CDC) in the GP-expressing cell line via C3 deposition on GP in contrast to MPER-specific mAbs. In the mouse model of EBOV infection, depletion of the complement system leads to an impairment of protection exerted by one of the GC-specific, but not MPER-specific mAbs. Our data suggest that activation of the complement system represents an important mechanism of antiviral protection by GC antibodies.

Abstract Historical urban districts are imbued with a multitude of elements, including historical heritage, cultural significance, social relationships, and daily activities, making them of significant research value. Through a review of previous literature, it is evident that research on the protection and renewal of historical urban districts has mostly focused on macro-level planning and development. Addressing the lack of spatial morphology quantification research at the meso-level, this paper proposes a method suitable for quantifying interface morphology in historical streets. Using the historical cultural street district of Xijie in Quanzhou, Fujian Province as a case study, this research employs parameters such as Distance-Height Ratio, Interface Density, Build-To-Line Rate, and Near-Line Rate to quantify and summarize the morphology of street interfaces. It then proposes transformation strategies to guide the protection and renewal of streets in the future. The study validates the feasibility of this quantification method and provides valuable insights for the protection and renewal of historical urban districts.

Abstract Background Recent studies have highlighted the significant role of the NF-κB signaling pathway in the initiation and progression of cancer. Furthermore, long noncoding RNAs (lncRNAs) have been identified as pivotal regulators in sustaining the NF-κB signaling pathway’s functionality. Despite these findings, the underlying molecular mechanisms through which lncRNAs influence the NF-κB pathway remain largely unexplored. Methods Bioinformatic analyses were utilized to investigate the differential expression and prognostic significance of XTP6. The functional roles of XTP6 were further elucidated through both in vitro and in vivo experimental approaches. To estimate the interaction between XTP6 and NDH2, RNA pulldown and RNA Immunoprecipitation (RIP) assays were conducted. The connection between XTP6 and the IκBα promoter was examined using Chromatin Isolation by RNA Purification (ChIRP) assays. Additionally, Chromatin Immunoprecipitation (ChIP) assays were implemented to analyze the binding affinity of c-myc to the XTP6 promoter, providing insights into the regulatory mechanisms at play. Results XTP6 was remarkedly upregulated in glioblastoma multiforme (GBM) tissues and was connected with adverse prognosis in GBM patients. Our investigations revealed that XTP6 can facilitate the malignant progression of GBM both in vitro and in vivo. Additionally, XTP6 downregulated IκBα expression by recruiting NDH2 to the IκBα promoter, which resulted in elevated levels of H3K27me3, thereby reducing the transcriptional activity of IκBα. Moreover, the progression of GBM was further driven by the c-myc-mediated upregulation of XTP6, establishing a positive feedback loop with IκBα that perpetuated the activation of the NF-κB signaling pathway. Notably, the application of an inhibitor targeting the NF-κB signaling pathway effectively inhibited the continuous activation induced by XTP6, leading to a significant reduction in tumor formation in vivo. Conclusion The results reveal that XTP6 unveils an innovative epigenetic mechanism instrumental in the sustained activation of the NF-κB signaling pathway, suggesting a promising therapeutic target for the treatment of GBM.

Objective It is unclear whether less acetabular coverage is associated with the failure of core decompression (CD) for osteonecrosis of the femoral head (ONFH). This study aimed to investigate the clinical outcomes of CD for ONFH with small‐ or medium‐sized pre‐collapse lesions, and determine what factors, especially acetabular anatomical parameters, predict the failure of CD. Methods Between January 2010 and December 2022, we retrospectively reviewed 269 consecutive CDs in 188 patients diagnosed with ONFH with small‐ or medium‐sized pre‐collapse lesions. The Kaplan–Meier method was used to evaluate the survival rate of CD for ONFH with progression of collapse or conversion to total hip arthroplasty (THA) as the endpoint. Univariate and multivariate logistic regression analyses were conducted to identify the potential risk factors for the failure of CD. Receiver operating characteristic (ROC) curve analysis was further performed with conversion to THA as the endpoint to determine the predictive value of these factors. Results The overall 5‐year survival rate of CD for ONFH with small‐ or medium‐sized pre‐collapse lesions was 74.3% (95% confidence interval (CI) 69.0%–81.1%) with progression of collapse as the endpoint and 83.9% (95% CI 79.3%–88.7%) with conversion to THA as the endpoint. Univariate logistic regression analysis showed that bilateral affected hips was significantly associated with progression of collapse, and center‐edge angle (CEA), sharp angle, acetabular head index (AHI), as well as acetabular depth ratio (ADR) were significantly associated with both progression of collapse and conversion to THA. Multivariate logistic regression analysis further indicated that CEA and AHI were independent risk factors for both progression of collapse and conversion to THA. ROC curve analysis with conversion to THA as the endpoint revealed that the cutoff values for CEA and AHI were 26.8° (sensitivity = 74.4%, specificity = 78.6%, area under the curve (AUC) = 0.809) and 79.8 (sensitivity = 78.4%, specificity = 73.8%, AUC = 0.818), respectively. Conclusions CD showed satisfactory clinical outcomes for ONFH with small‐ or medium‐sized pre‐collapse lesions where less acetabular coverage with a CEA

Traditional villages serve as witnesses to history and culture and as the centers of production and life. Studying their spatial characteristics and influencing factors can provide profound insights into their formation, development, and inheritance. Taking CAI’s ancient residential buildings in Zhangli Village, Quanzhou as a case study, this paper utilizes space syntax and abstract topological relations to quantitatively analyze three morphological characteristics of public space: (1) “Ancestral halls” and “Academies” are situated at the core of visual space, representing significant spatial elements within the village, with high visual appeal and status; (2) The spatial layout of “roadways” and “gates” caters to the needs of internal settlements, with their accessibility significantly varying in different directions. However, the high topological depth restricts exploration within the internal space; (3) The village provides residents with spaces for various types of public activities. Furthermore, this paper qualitatively explores the factors influencing the spatial form of Cai’s ancient dwellings from the perspectives of nature, economy, and culture, including topography, hierarchical order, geomancy principles, ethnic economic development, production, and lifestyle. Accordingly, the paper proposes corresponding protection and development strategies, offering a reference for the sustainable development of traditional villages in the future.

Abstract H2O dissociation plays a crucial role in solar-driven catalytic CO2 methanation, demanding high temperature even for solar-to-chemical conversion efficiencies

Abstract The Internet of Things (IoT) devices spawn growing diverse social platforms and online data at the network edge, propelling the development of cross-platform applications. To integrate cross-platform data, user identity linkage is envisioned as a promising technique by detecting whether different accounts from multiple social networks belong to the same identity. The profile and social relationship information of IoT users may be inconsistent, which deteriorates the reliability of the effectiveness of identity linkage. To this end, we propose a topic and knowledge-enhanced model for edge-enabled IoT user identity linkage across social networks, named TKM, which conducts feature representation of user generated contents from both post-level and account-level for identity linkage. Specifically, a topic-enhanced method is designed to extract features at the post-level. Meanwhile, we develop an external knowledge-based Siamese neural network for user-generated content alignment at the account-level. Finally, we show the superiority of TKM over existing methods on two real-world datasets. The results demonstrate the improvement in prediction and retrieval performance achieved by utilizing both post-level and account-level representation for identity linkage across social networks.

Abstract Excessive production of reactive oxygen species (ROS) and inflammation are the key problems that impede diabetic wound healing. In particular, dressings with ROS scavenging capacity play a crucial role in the process of chronic wound healing. Herein, Zr-based large-pore mesoporous metal–organic frameworks (mesoMOFs) were successfully developed for the construction of spatially organized cascade bioreactors. Natural superoxide dismutase (SOD) and an artificial enzyme were spatially organized in these hierarchical mesoMOFs, forming a cascade antioxidant defense system, and presenting efficient intracellular and extracellular ROS scavenging performance. In vivo experiments demonstrated that the SOD@HMUiO-MnTCPP nanoparticles (S@M@H NPs) significantly accelerated diabetic wound healing. Transcriptomic and western blot results further indicated that the nanocomposite could inhibit fibroblast senescence and ferroptosis as well as the stimulator of interferon genes (STING) signaling pathway activation in macrophages mediated by mitochondrial oxidative stress through ROS elimination. Thus, the biomimetic multi-enzyme cascade catalytic system with spatial ordering demonstrated a high potential for diabetic wound healing, where senescence, ferroptosis, and STING signaling pathways may be potential targets. Graphical Abstract Schematic diagram showing the proposed mechanism that S@M@H NPs promoted diabetic wound healing

Two-dimensional particle-in-cell simulations are performed to study the coupling between ion and electron motions in collisionless magnetic reconnection. The electron diffusion region (EDR), where the electron motions are demagnetized, is found to have a two-layer structure: an inner EDR near the reconnection site and an outer EDR that is elongated to nearly 10 ion inertial lengths in the outflow direction. In the inner EDR, the speed of the electron outflow increases when the electrons move away from the X line. In the outer EDR, the speed of the electron outflow first increases and then decreases until the electrons reach the boundary of the outer EDR. In the boundary of the outer EDR, the magnetic field piles up and forms a depolarization front. From the perspective of the fluid, a force analysis on the formation of electron and ion outflows has also been investigated. Around the X line, the electrons are accelerated by the reconnection electric field in the out-of-plane direction. When the electrons move away from the X line, we find that the Lorentz force converts the direction of the accelerated electrons to the x direction, forming an electron outflow. Both electric field forces and electron gradient forces tend to drag the electron outflow. Ion acceleration along the x direction is caused by the Lorentz force, whereas the pressure gradient force tends to decelerate the ion outflow. Although these two terms are important, their effects on ions are almost offset. The Hall electric field force does positive work on ions and is not negligible. The ions are continuously accelerated, and the ion and electron outflow velocities are almost the same near the depolarization front.

Abstract Anomaly detection poses a significant challenge in the industry and knowledge distillation constructed using a frozen teacher network and a trainable student network is the prevailing approach for detecting suspicious regions. Forward and reverse distillation are the main ways to achieve anomaly detection. To design an effective model and aggregate detection results, we propose a dual-student knowledge distillation (DSKD) based on forward and reverse distillation. Taking advantage of the priority of reverse distillation to obtain high-level representation, we combine a skip connection and an attention module to build a reverse distillation student network that simultaneously focuses on high-level representation and low-level features. DSKD uses a forward distillation network as an auxiliary to allow the student network to preferentially obtain the query image. For different anomaly score maps obtained by the dual-student network, we use synthetic noise enhancement in combination with image segmentation loss to adaptively learn the weight scores of individual maps. Empirical experiments conducted on the MVTec dataset show that the proposed DSKD method achieves good performance on texture images as well as competitive results on object images compared with other state-of-the-art methods. Meanwhile, ablation experiments and a visualization analysis validate the contributions of each of the model’s components.

Objective: To elucidate the effects of chlorogenic acid (CGA), a bioactive polyphenol compound prevalent in traditional Chinese medicine and various foods, including Lonicera japonica Thunb. (Jin Yin Hua), Eucommia ulmoides Oliv. (Du Zhong Ye), tea, and coffee, on cardiomyocyte ferroptosis and heart failure. Methods: We assessed the effect of CGA on cardiac function using a mouse model of heart failure induced by transverse aortic constriction (TAC). These indicators included the left ventricular ejection fraction (LVEF), fractional shortening (LVFS), end-systolic volume (LVESV), end-diastolic volume (LVEDV), end-systolic diameter (LVESD), and end-diastolic diameter (LVEDD). An isoprenaline hydrochloride (ISO)-induced H9c2 cardiomyocyte cell model was also established, and the cells were treated with various concentrations of CGA. To assess the effect of CGA on ferroptosis in cardiomyocytes, we measured cell viability and evaluated the levels of intracellular reactive oxygen species (ROS), ferrous ions (Fe2+), and lipid peroxidation using fluorescent staining. To clarify the ferroptosis signaling pathway regulated by CGA, western blotting was used to examine the expression of ferroptosis biomarkers, specifically solute carrier family 7 member 11 (SLC7A11) and glutathione peroxidase 4 (GPX4), in H9c2 cardiomyocytes and mouse myocardial tissues. Results: CGA significantly enhanced cardiac performance indices such as LVEF, LVFS, LVESV, LVEDV, LVESD, and LVEDD. H9c2 cardiomyocytes exposed to ISO showed decreased cell viability and increased ROS levels, Fe2+ content, and lipid peroxidation levels. However, CGA treatment significantly ameliorated these changes. Additionally, in both H9c2 cardiomyocytes and myocardial tissue obtained from mice with TAC, CGA increased the expression of ferroptosis-related proteins, including SLC7A11 and GPX4. Conclusion: CGA has the potential to enhance cardiac function and diminish lipid peroxidation and ROS levels in cardiomyocytes via the SLC7A11/GPX4 signaling pathway. This process alleviates ferroptosis in cardiomyocytes. These results provide new insights into the clinical use of CGA and the management of heart failure.

Abstract Photo-crosslinking polymerization stands as a fundamental pillar in the domains of chemistry, biology, and medicine. Yet, prevailing strategies heavily rely on ultraviolet/visible (UV/Vis) light to elicit in situ crosslinking. The inherent perils associated with UV radiation, namely the potential for DNA damage, coupled with the limited depth of tissue penetration exhibited by UV/Vis light, severely restrict the scope of photo-crosslinking within living organisms. Although near-infrared light has been explored as an external excitation source, enabling partial mitigation of these constraints, its penetration depth remains insufficient, particularly within bone tissues. In this study, we introduce an approach employing X-ray activation for deep-tissue hydrogel formation, surpassing all previous boundaries. Our approach harnesses a low-dose X-ray-activated persistent luminescent phosphor, triggering on demand in situ photo-crosslinking reactions and enabling the formation of hydrogels in male rats. A breakthrough of our method lies in its capability to penetrate deep even within thick bovine bone, demonstrating unmatched potential for bone penetration. By extending the reach of hydrogel formation within such formidable depths, our study represents an advancement in the field. This application of X-ray-activated polymerization enables precise and safe deep-tissue photo-crosslinking hydrogel formation, with profound implications for a multitude of disciplines.

Abstract Laser wakefield acceleration, as an advanced accelerator concept, has attracted great attentions for its ultrahigh acceleration gradient and the capability to produce high brightness electron bunches. The three-dimensional (3D) density serves as an evaluation metric for the particle bunch quality and is intrinsically related to the applications of an accelerator. Despite its significance, this parameter has not been experimentally measured in the investigation of laser wakefield acceleration. We report on an electro-optic 3D snapshot of a laser wakefield electron bunch at a position outside the plasma. The 3D shape of the electron bunch was detected by simultaneously performing optical transition radiation imaging and electro-optic sampling. Detailed 3D structures to a few micrometer levels were reconstructed using a genetic algorithm. The electron bunch possessed a transverse size of less than 30 micrometers. The current profile shows a multi-peak structure. The main peak had a duration of < 10 fs and a peak current > 1 kA. The maximum electron 3D number density was ~ 9 × 1021 m -3. This research demonstrates a feasible way of 3D density monitoring on femtosecond kilo-ampere electron bunches, at any position of a beam transport line for relevant applications.

Abstract The disintegration of red-bed soft rock exhibits a strong correlation with various geological disasters. However, the investigation into the evolutionary mechanisms underlying disintegration breakage has not yet received extensive exploration. In order to comprehensively examine the disintegration characteristics of red-bed soft rock, the slake durability tests were conducted to red-bed soft rocks of varying burial depths. Subsequently, an investigation was carried out to examine the disintegration characteristics and the evolution of disintegration parameters, including the coefficient of uniformity (Cu), coefficient of curvature (Cc), disintegration rate (DRE), disintegration ratio (Dr), and fractal dimension (D), throughout the disintegration process. Finally, employing the energy dissipation theory, an energy dissipation model was developed to predicate the disintegration process of samples at various burial depths. The findings demonstrate a decrease in the abundance of large particles and a concurrent increase in the abundance of small particles as the number of drying-wetting cycles increases. Furthermore, as the number of drying-wetting cycles increases, a significant alteration is observed in the content of particles larger than 10 mm, whereas the content of particles smaller than 10 mm undergoes only minor changes. The disintegration parameters, including the curvature coefficient, non-uniformity coefficient, disintegration rate, and fractal dimension, exhibit a positive correlation with the number of drying-wetting cycles. Conversely, the disintegration index demonstrates a decreasing trend with the increasing number of cycles. Nevertheless, as the burial depth increases, a notable trend emerges in the disintegration process, characterized by a gradual increase in the content of large particles alongside a progressive decrease in the content of small particles. Concurrently, the curvature coefficient, non-uniformity coefficient, disintegration rate, and fractal dimension exhibit a gradual decline, while the durability index experiences a gradual increase. In addition, based on the principle of energy dissipation, it is revealed that the surface energy increment of red-bed soft rock increases with the increase of the number of drying-wetting cycles, but decreases with the increase of burial depth. Ultimately, by leveraging the outcomes of energy dissipation analyses, a theoretical model is constructed to elucidate the correlation between surface energy and both the number of drying-wetting cycles and burial depth. This model serves as a theoretical reference for predicting the disintegration behavior of samples, offering valuable insights for future research endeavors.

Abstract Independently performing activities of daily living (ADLs) is vital for maintaining one’s quality of life. Losing this ability can significantly impact an individual’s overall health status, including their mental health and social well-being. Aging is an important factor contributing to the loss of ADL abilities, and our study focuses on investigating the trajectories of functional decline and recovery in older adults. Employing trajectory analytics methodologies, this research delves into the intricate dynamics of ADL pathways, unveiling their complexity, diversity, and inherent characteristics. The study leverages a substantial dataset encompassing ADL assessments of nursing home residents with diverse disability profiles in the United States. The investigation begins by transforming these assessments into sequences of disability combinations, followed by applying various statistical measures, indicators, and visual analytics. Valuable insights are gained into the typical disability states, transitions, and patterns over time. The results also indicate that while predicting the progression of ADL disabilities presents manageable challenges, the duration of these states proves more complicated. Our findings hold significant potential for improving healthcare decision-making by enabling clinicians to anticipate possible patterns, develop targeted and effective interventions that support older patients in preserving their independence, and enhance overall care quality.

Abstract Background Ubiquitination is a critical post-translational modification which can be reversed with an enzyme family known as deubiquitinating enzymes (DUBs). It has been reported that dysregulation of deubiquitination leads to carcinogenesis. As a member of the DUBs family, proteasome 26 S subunit non-ATPase 7 (PSMD7) serves as an underlying tumour-promoting factor in multiple cancers. However, the clinical significance and biological functions of PSMD7 in pancreatic cancer (PC) remain unclear. Results In this study, we first reported frequent overexpression of PSMD7 in PC tissues, and high levels of PSMD7 were markedly linked to shorter survival and a malignant phenotype in PC patients. An array of in vitro and in vivo gain/loss-of-function tests revealed that PSMD7 facilitates the progression of PC cells. Additionally, we found that PSMD7 promotes PC cell progression by activating the Notch homolog 1 (Notch1) signalling. Interestingly, in PC cells, the inhibitory effect of PSMD7 knockdown on cellular processes was comparable to that observed upon Notch1 knockdown. Mechanistically, PSMD7 deubiquitinated and stabilised sex determining region Y (SRY)-box 2 (SOX2), a key mediator of Notch1 signalling. The stabilisation of SOX2, mediated by PSMD7, dramatically increased SOX2 protein levels, subsequently activating the Notch1 pathway. Finally, restoration of SOX2 expression abrogated the PSMD7-silenced antitumour effect. Conclusions Taken together, our work identifies and validates PSMD7 as a promoter of PC progression through augmentation of the Notch1 signalling pathway mediated by SOX2. This finding suggests that PSMD7 holds promise as a potential therapeutic target for the management of this refractory disease.

Abstract Mechanical antennas have garnered considerable attention due to their ability to address the challenges posed by the significant size and high energy consumption associated with traditional electric antennas when operating at low frequencies. Here, a compact and structurally stable mechanical antenna design is presented. The proposed antenna is constructed using cylindrical piezoelectric ceramics, which have dimensions smaller than 1/1000 of the wavelength. The scrutiny of the influence exerted by the antenna feed area and material thickness on the radiation performance was undertaken, followed by an exhaustive discourse on these effects. Experimental measurements demonstrate the practical functionalities of signal coding, transmission, and reception in the low‐frequency communication system. Notably, at a frequency of 288 kHz, a single proposed antenna achieves an effective information transmission distance of 60 m using binary information coding. This remarkable outcome underscores the potential of this design in facilitating the development of portable and cost‐effective wireless communication equipment for low‐frequency applications.

Litchi, a succulent and perishable fruit, presents a narrow annual harvest window of under two weeks. The advent of smart agriculture has driven the adoption of visually-guided, automated litchi harvesting techniques. However, conventional approaches typically rely on laboratory-based, high-performance computing equipment, which presents challenges in terms of size, energy consumption, and practical application within litchi orchards. To address these limitations, we propose a real-time litchi detection methodology for complex environments, utilizing portable, low-energy edge computing devices. Initially, the litchi orchard imagery is collected to enhance data generalization. Subsequently, a convolutional neural network (CNN)-based single-stage detector, YOLOx, is constructed to accurately pinpoint litchi fruit locations within the images. To facilitate deployment on portable, low-energy edge devices, we employed channel pruning and layer pruning algorithms to compress the trained model, reducing its size and parameters. Additionally, the knowledge distillation technique is harnessed to fine-tune the network. Experimental findings demonstrated that our proposed method achieved a 97.1% compression rate, yielding a compact litchi detection model of a mere 6.9 MB, while maintaining 94.9% average precision and 97.2% average recall. Processing 99 frames per second (FPS), the method exhibited a 1.8-fold increase in speed compared to the unprocessed model. Consequently, our approach can be readily integrated into portable, low-computational automatic harvesting equipment, ensuring real-time, precise litchi detection within orchard settings.

Multispectral Imaging has been used in many fields. In the medical field, Multispectral Imaging is still in its infancy. However, due to its excellent potential, it will also become one of the most important medical imaging in the future. This paper is the first bibliometric study in this field. The study comprehensively searched all relevant documents in Web of Science Core Collection from Jan 1, 1999 to Dec 31, 2022, systematically sorted out the author, journal, country and institution in this field, and analyzed the keywords. Based on this, the study suggests that researchers and healthcare workers should strengthen cooperation to apply Multispectral Imaging to more medical fields while further developing related technologies. At the same time, in the future, this field should focus on non-ex vivo tissue detection and the combination of Multispectral Imaging and artificial intelligence.

This study investigated influences of faba bean (Vicia faba L.) supplementary diet (VFSD) on tilapia muscle texture through muscle-gut axis. Tilapia were fed diets with varying VSFD contents for 60 days. Results indicated no significantly growth changes across groups. However, VFSD increased muscle hardness and chewiness, with higher collagen deposition between muscle fibers. Transcriptome revealed an increase in differentially-expressed genes (DEGs) related to myofibril component and TGF-β, MAPK, FOXO, insulin pathways. Crucial DEGs among interaction network between these pathways, including foxo3, mitf, smad1, smad7, and flt1, were validated via qPCR. Gut microbiota analysis showed VFSD decreased Pseudomonas, Ralstonia, and Aurantimicrobium abundance, while increased Rhodobacter, Akkermansia, and Propionibacteriaceae, which significantly impacting quorum sensing and ABC transporters. Microbiota variation highly correlated with muscle DEGs, suggesting a link between muscle phenotype and gut microbiota. In summary, VFSD alters meat texture by influencing collagen deposition and myofibril reconstruction, which may be regulated by LPS- and ROS-related pathways through altering the composition of the microbial community.

This study investigated the effects of adding various concentrations of cholesterol and soy lecithin to feed on the growth performance, physiology, biochemistry, and serum metabolomics of Cyprinus carpio var. Two cholesterol concentrations (1 % and 2 %) and four soy lecithin concentrations (0 %, 2 %, 4 %, and 6 %) were employed, resulting in eight experimental groups (C1S0, C1S2, C1S4, C1S6, C2S0, C2S2, C2S4, and C2S6) that were cultivated for 60 days. The addition of C2S2 to the feeds enhanced the growth (WGR and SGR), antioxidant capacity (CAT, SOD, MDA, T-AOC, and GSH-Px), and lipid metabolism (TG, LDL-C, HDL-C, LPL, and HL) in C. carpio var. A significant interaction (P < 0.05) was observed between cholesterol and soy lecithin concentrations for WGR, SGR, and FCR, and a highly significant interaction (P < 0.01) was observed for CAT, SOD, T-AOC, GSH-Px, TG, LDL-C, and HDL-C in C. carpio var. Based on these results, three comparisons (C1S4-vs-C1S0, C2S2-vs-C2S0, and C2S2-vs-C1S2) were selected to analyze the serum metabolic profiles of C. carpio var. through LC-MS. The differential metabolites screened included amino acids and their metabolites, nucleotides and their metabolites, bile acids, fatty acids, carbohydrates and their metabolites. The metabolic pathways involved were purine metabolism, glycine, serine, and threonine metabolism, arginine and proline metabolism, and ABC transporter proteins. In summary, the interaction between cholesterol and soy lecithin significantly influenced the growth performance, antioxidant capacity, and cholesterol metabolism of C. carpio var. The most beneficial effects on growth and lipid metabolism were observed when both cholesterol and soy lecithin were added at a concentration of 2 %. The present study provides theoretical guidance for the appropriate concentrations of cholesterol and lecithin in aquafeeds.

Eukaryotic elongation factors (eEFs) are protein factors that mediate the extension of peptide chain, among which eukaryotic elongation factor 1 alpha (eEF1A) is one of the most abundant protein synthesis factors. Previously we showed that the P3 protein of Soybean mosaic virus (SMV), one of the most destructive and successful viral pathogens of soybean, targets a component of the soybean translation elongation complex to facilitate its pathogenesis. Here, we conducted a systematic analyses of the soybean eEF (GmeEF) gene family in soybean and examinedits role in virus resistance. In this study, GmeEF family members were identified and characterized based on sequence analysis. The 42 members, which were unevenly distributed across the 15 chromosomes, were renamed according to their chromosomal locations. The GmeEF members were further divided into 12 subgroups based on conserved motif, gene structure, and phylogenetic analyses. Analysis of the promoter regions showed conspicuous presence of myelocytomatosis (MYC) and ethylene-responsive (ERE) cis-acting elements, which are typically involved in drought and phytohormone response, respectively, and thereby in plant stress response signaling. Transcriptome data showed that the expression of 15 GmeEF gene family members changed significantly in response to SMV infection. To further examine EF1A function in pathogen response, three different Arabidopsis mutants carrying T-DNA insertions in orthologous genes were analyzed for their response to Turnip crinkle virus (TCV) and Cucumber mosaic virus (CMV). Results showed that there was no difference in viral response between the mutants and the wild type plants. This study provides a systematic analysis of the GmeEF gene family through analysis of expression patterns and predicted protein features. Our results lay a foundation for understanding the role of eEF gene in soybean anti-viral response.

BackgroundHealth literacy is an important means to improve health outcomes and reduce health disparities. It plays an important role in promoting multiple health-related behaviors of individuals. Numerous studies have demonstrated a number of sociodemographic and school characteristics, and family related factors were related to health literacy among college students. However, these characteristics and factors were relatively unchangeable. Research on the relationship between factors, that can be intervened, and health literacy remains scarce. This study aims to explore the association between personal and changeable environmental factors, and the level of health literacy in college students.MethodsA cross-sectional study, which used a stratified random sampling method, was conducted at a university in Wuhan (N = 447). The survey questionnaire included sociodemographic characteristics, the School Environment Questionnaire, the Family Environment Questionnaire, the General Self-Efficacy Scale Questionnaire, and the Health Literacy Questionnaire. We used Spearman correlation tests, and Student’s tests or analyses of variance to describe the relationship among continuous variables. In addition, we employed linear regression analysis to test the mediating effect based on the bias-corrected nonparametric percentile Bootstrap method.ResultsFactors related to socioeconomic status, such as living costs (p = 0.011), residential area (p = 0.003), annual household income (p = 0.001), and parents’ education level (fathers: p = 0.001; mothers: p = 0.01) and occupation type (fathers: p

Abstract Graphitic carbon nitride (CN), as a nonmetallic photocatalyst, has gained considerable attention for its cost‐effectiveness and environmentally friendly nature in catalyzing solar‐driven CO2 conversion into valuable products. However, the photocatalytic efficiency of CO2 reduction with CN remains low, accompanied by challenges in achieving desirable product selectivity. To address these limitations, a two‐step hydrothermal‐calcination tandem synthesis strategy is presented, introducing carbon quantum dots (CQDs) into CN and forming ultra‐thin CQD/CN nanosheets. The integration of CQDs induces a distinct work function with CN, creating a robust interface electric field after the combination. This electric field facilitates the accumulation of photoelectrons in the CQDs region, providing an abundant source of reduced electrons for the photocatalytic process. Remarkably, the CQD/CN nanosheets exhibit an average CO yield of 120 µmol g−1, showcasing an outstanding CO selectivity of 92.8%. The discovery in the work not only presents an innovative pathway for the development of high‐performance photocatalysts grounded in non‐metallic CN materials employing CQDs but also opens new avenues for versatile application prospects in environmental protection and sustainable cleaning energy.

With the increasing impact of global climate change, the frequency of extreme arid climates worldwide is rising. These extreme arid conditions can have adverse effects on expansive soil embankments. In this study, the digital image technology is used to study the crack development characteristics of expansive soil embankments. The findings indicate that the crack development process in expansive soil can be divided into three stages: slow development, rapid development, and stable development. During the drying process, cracks develop differently on the waterward side, the top of the embankment, and the backwater side of the embankment. Initially, cracks appear on the top of the embankment, and their degree of development is the highest in this area. The crack degree on the top of the embankment is approximately 2 to 3 times greater than that on the waterward and backwater sides. Furthermore, longitudinal cracks on the top of the embankment have been analyzed from both macro and micro perspectives. This study is expected to help analyze the underlying formation mechanisms of desiccation cracking-inducing geohazards and access the long-term performance of expansive soil embankments in arid climates.

Abstract A M6.8 earthquake struck the High Atlas Mountains in Morocco on 8 September 2023, ending a 63‐year seismic silence. We herein attempt to clarify the seismogenic fault and explore the underlying mechanism for this seismic event based on multiple data sets. Utilizing probabilistic Bayesian inversion on interferometric radar data, we determine a seismogenic fault plane centered at a depth of 26 km, striking 251° and dipping 72°, closely aligned with the Tizi n’Test fault system. Given a hypocenter at the Moho depth, the joint inversion of radar and teleseismic data reveals that the rupture concentrates between depths of 12 and 36 km, offsetting the Mohorovičić discontinuity (Moho) at ∼32 km. Considering a strong link between magma activity and failure in lower crust, we propose that the triggering of the earthquake possibly was mantle upwelling that also supports the high topography.

Abstract We report in situ observation of magnetic reconnection between magnetic flux rope (MFR) and magnetic hole (MH) in the magnetosheath by the Magnetospheric Multiscale mission. The MFR was rooted in the magnetopause and could be generated by magnetopause reconnection therein. A thin current sheet was generated due to the interaction between MFR and MH. The sub‐Alfvénic ion bulk flow and the Hall field were detected inside this thin current sheet, indicating an ongoing reconnection. An elongated electron diffusion region characterized by non‐frozen‐in electrons, magnetic‐to‐particle energy conversion, and crescent‐shaped electron distribution was detected in the reconnection exhaust. The observation provides a mechanism for the dissipation of MFRs and thus opens a new perspective on the evolution of MFRs at the magnetopause. Our work also reveals one potential fate of the MHs in the magnetosheath which could reconnect with the MFRs and further merge into the magnetopause.

The resonance enhanced InAs/GaSb type-II Superlattices (T2SLs) infrared detectors with diffraction rings is designed, and the photoelectric characteristics are calculated and studied in this paper. The diffraction rings are designed on the top surface of T2SLs detector to control the incident light inside the device by forming the resonant cavity. We designed the structure of the conventional PIN InAs/GaSb T2SLs photodetector, calculated the energy band structure of the absorption layer, and analyzed the influence of the thickness of the absorption layer on the photoelectric performance. It is proved that blindly increasing the thickness of the absorption layer cannot effectively improve the device performance. We further studied the quantum efficiency (QE) and electric field distribution of the device after adding the diffraction ring structure. The results show that the structure with diffraction rings can significantly improve the QE of the photodetector without increasing the dark current. The interaction between the diffraction ring and the metal contact layer will enhance the localization of the electric field and further increase the light absorption between the semiconductor layers.

ABSTRACT The rapid and effective identification of pathogens in patients with pulmonary infections has posed a persistent challenge in medicine, with conventional microbiological tests (CMTs) proving time-consuming and less sensitive, hindering early diagnosis of respiratory infections. While there has been some research on the clinical performance of targeted sequencing technologies, limited focus has been directed toward bronchoalveolar lavage fluid (BALF). This study primarily evaluates the pathogen detection capabilities of nanopore-targeted sequencing (NTS) in BALF, providing a comprehensive analysis. The retrospective study, spanning from January 2022 to November 2023, includes 223 patients exclusively sourced from a single center. We conducted a detailed comparative analysis among NTS, targeted next-generation sequencing (tNGS), and CMTs. Initially, we compared the detection capabilities of NTS and tNGS and found no significant differences in their sensitivity and specificity. Specifically, we observed that the sensitivity of NTS was significantly higher than that of CMTs (74.83% vs 33.11%, P < 0.001). Furthermore, NTS exhibited a higher positivity rate in common pulmonary infections (62.88% vs. 23.48%) and in clinically suspected tuberculosis patients compared to CMTs (87.18% vs. 48.72%). Additionally, NTS showed less susceptibility to antibiotic interference, indicating a more sensitive detection capability, especially in detecting fastidious organisms. It complements GeneXpert in tuberculosis diagnosis and offers excellent advantages in identifying pathogens challenging for CMTs, such as non-tuberculous mycobacteria and viruses. Moreover, NTS significantly shortens the reporting time and is only a quarter of the cost of metagenomic next-generation sequencing. Clearly, NTS can facilitate faster and more cost-effective early diagnosis of respiratory infections.IMPORTANCEThis study holds paramount significance in advancing the field of respiratory infection diagnostics. By assessing the pathogen detection capabilities in bronchoalveolar lavage fluid (BALF) of patients with pulmonary infections, we illuminate the promising potential of nanopore-targeted sequencing (NTS). The findings underscore NTS as a comparable yet distinct alternative to traditional methods like comprehensive conventional microbiological tests (CMTs). Notably, NTS demonstrates a pivotal edge, expanding the spectrum of identified pathogens, particularly excelling in the detection of challenging entities like non-tuberculous mycobacteria and viruses. The study also highlights the complementary role of NTS alongside GeneXpert in the identification of tuberculosis, providing a comprehensive overview of the diagnostic landscape for respiratory infections. This insight carries significant implications for clinicians seeking rapid, cost-effective, and accurate diagnostic tools in the realm of pulmonary infections.

Polarization-independent liquid-crystal (LC) phase modulators can significantly improve the efficiency and reduce the complexity of optical systems. However, achieving good polarization independence for LC phase modulators with a simple structure is difficult. A light-controlled azimuth angle (LCAA) process based on the optical rotatory effect of cholesteric liquid crystals (CLC) was developed for fabricating single-layer, multi-microdomain, orthogonally twisted (MMOT) structures. The developed LC phase modulator with a single-layer MMOT structure may have a low polarization dependence with a large phase depth. This device shows good potential for applications in optical communications, wearable devices, and displays.

Abstract A significant portion of tight sandstone reservoirs commonly displays intricate fluvial channels or fault systems. Despite various attempts at analytical/semi-analytical modeling of multistage-fractured horizontal wells (MFHWs) in unconventional reservoirs, the majority of studies have focused on scenarios with homogeneous original physical properties, neglecting cases where MFHWs traverse multiple regions in channelized heterogeneous reservoirs. Comprehending the influence of heterogeneous and leaky faults on the performance of MFHWs is essential for efficient development. This study presents an innovative semi-analytical model to analyze the pressure transient behavior of MFHWs with secondary fractures as they traverse multiple regions in banded channel heterogeneous reservoirs, particularly considering the presence of partially-communicating faults. The approach combines the source method and Green’s function method to obtain solutions, introducing a novel technique for discretizing fractures without discretizing interfaces. The effects of the reservoir heterogeneity, partially-communicating faults and fractures system on pressure behavior are analyzed. The results indicate that the pressure behavior of MFHWs passing through regions with different physical properties exhibits distinctive characteristics, differing from both the homogeneous case and the heterogeneous cases where the well does not traverse distinct regions. Permeability heterogeneity influences the curves of all other flow regimes, except the early and late flow regimes. Faults affect transient pressure behavior only when not positioned in the middle of each two primary fractures. Region area heterogeneity primarily influences the medium flow regimes. This work provides valuable insights into the performance of MFHWs in channelized heterogeneous reservoirs, offering technical support for well testing in these reservoirs.

Multiple parameter environment monitoring via wireless Internet of Thing sensors is growing rapidly, thanks to low power techniques of the node. More importantly, the ever more complex and highly efficient energy harvesting systems enable long-term continuous monitoring in inaccessible environments without needing to change the battery. This paper reviews existing energy harvesting modalities, including photovoltaic, piezoelectric, pyroelectric, electromagnetic, and vibration, together with circuit techniques of interfacing power management circuits for energy harvesters. Moreover, techniques used to interface with multiple mode energy harvesters to obtain a stable output power with optimal power efficiency are discussed as an emerging direction. The state-of-the-art energy harvesting systems together with future development trends are provided.

The solar insecticidal lamp (SIL) is an electronic device designed for physical pest control, widely utilized in orchards and farmland. Currently, the characteristic of the phototactic rhythm of pest is commonly ignored in the design of SILs, hindering pest control. This phenomenon is particularly evident in the prolonged turning on/offlamp, which leads to inefficient energy utilization due to the lack of adjustment for peak pest activity. To address this issue, four models based on the phototactic rhythm of pests are developed to adjust the insecticidal timing of SIL for precise pest control. These mathematical models are established considering the phototactic rhythm of four pests that exert the most significant impact on crops, namely Mythimna seperata, Helicoverpa armigera, Proxenus lepigone, and Cnaphalocrocis medinalis. The results indicate that mathematical modeling of the phototactic rhythm of the pest is valuable in capturing their nocturnal activity patterns. The proposed mathematical model can help to optimize the on/offtime of SIL for pest control. The integration of electronic devices, such as SIL in pest management represents a noteworthy advancement in agricultural electronics, contributing to the progress of smart and sustainable agriculture.

Earth’s magnetopause is a thin boundary separating the shocked solar wind plasma from the magnetospheric plasmas, and it is also the boundary of the solar wind energy transport to the magnetosphere. Soft X-ray imaging allows investigation of the large-scale magnetopause by providing a two-dimensional (2-D) global view from a satellite. By performing 3-D global hybrid-particle-in-cell (hybrid-PIC) simulations, we obtain soft X-ray images of Earth’s magnetopause under different solar wind conditions, such as different plasma densities and directions of the southward interplanetary magnetic field. In all cases, magnetic reconnection occurs at low latitude magnetopause. The soft X-ray images observed by a hypothetical satellite are shown, with all of the following identified: the boundary of the magnetopause, the cusps, and the magnetosheath. Local X-ray emissivity in the magnetosheath is characterized by large amplitude fluctuations (up to 160%); however, the maximum line-of-sight-integrated X-ray intensity matches the tangent directions of the magnetopause well, indicating that these fluctuations have limited impact on identifying the magnetopause boundary in the X-ray images. Moreover, the magnetopause boundary can be identified using multiple viewing geometries. We also find that solar wind conditions have little effect on the magnetopause identification. The Solar wind Magnetosphere Ionosphere Link Explorer (SMILE) mission will provide X-ray images of the magnetopause for the first time, and our global hybrid-PIC simulation results can help better understand the 2-D X-ray images of the magnetopause from a 3-D perspective, with particle kinetic effects considered.

Abstract Background Angiogenesis is essential for tissue repair in ischemic diseases, relying on glycolysis as its primary energy source. Prolyl 4-hydroxylase subunit alpha 1 (P4HA1), the catalytic subunit of collagen prolyl 4-hydroxylase, is a glycolysis-related gene in cancers. However, its role in glycolysis-induced angiogenesis remains unclear. Methods P4HA1 expression was modulated using adenoviruses. Endothelial angiogenesis was evaluated through 5-ethynyl-2′-deoxyuridine incorporation, transwell migration, and tube formation assays in vitro. In vivo experiments measured blood flow and capillary density in the hindlimb ischemia (HLI) model. Glycolytic stress assays, glucose uptake, lactate production, and quantitative reverse transcription-polymerase chain reaction (RT-PCR) were employed to assess glycolytic capacity. Transcriptome sequencing, validated by western blotting and RT-PCR, was utilized to determine underlying mechanisms. Results P4HA1 was upregulated in endothelial cells under hypoxia and in the HLI model. P4HA1 overexpression promoted angiogenesis in vitro and in vivo, while its knockdown had the opposite effect. P4HA1 overexpression reduced cellular α-ketoglutarate (α-KG) levels by consuming α-KG during collagen hydroxylation. Downregulation of α-KG reduced the protein level of a DNA dioxygenase, ten–eleven translocation 2 (TET2), and its recruitment to the fructose-1,6-biphosphatase (FBP1) promoter, resulting in decreased FBP1 expression. The decrease in FBP1 enhanced glycolytic metabolism, thereby promoting endothelial angiogenesis. Conclusions Hypoxia-induced endothelial P4HA1 overexpression enhanced angiogenesis by promoting glycolytic metabolism reprogramming through the P4HA1/α-KG/TET2/FBP1 pathway. The study’s findings underscore the significance of P4HA1 in post-ischemic angiogenesis, suggesting its therapeutic potential for post-ischemic tissue repair.

Abstract There lacks real‐world study with a large sample size assessing olmesartan medoxomil‐amlodipine besylate (OM‐AML) tablet. Therefore, this study aimed to evaluate the efficacy and safety of OM‐AML tablet in patients with essential hypertension. Totally, 1341 patients from 36 medical centers with essential hypertension who took OM‐AML (20/5 mg) tablet were analyzed in the current prospective, single‐arm, multi‐center, real‐world study (SVK study). Seated systolic blood pressure (SeSBP) and seated diastolic blood pressure (SeDBP) at baseline, week (W)4 and W8 were measured. The mean (±SE) change of SeSBP/SeDBP was ‐10.8 ± 0.4/‐6.6 ± 0.3 mmHg at W4 and ‐12.7 ± 0.5/‐7.6 ± 0.3 mmHg at W8, respectively. At W4, 78.8% and 29.0% patients achieved BP target by China and American Heart Association (AHA) criteria; at W8, 84.7% and 36.5% patients reached blood pressure (BP) target by China and AHA criteria, accordingly. Meanwhile, 80.2% and 86.4% patients achieved BP response at W4 and W8, respectively. Home‐measured SeSBP and SeDBP decreased from W1 to W8 (both p

Background: Myokines play vital roles in both stable coronary artery disease (SCAD) and depression. Meanwhile, there is a pressing necessity to find effective biomarkers for early predictor of major adverse cardiovascular events (MACE) in SCAD patients with depressive symptoms. Methods: A single-center, 5-year follow-up study was investigated. MACE was defined as composite end points, including cardiovascular death, non-fatal stroke, non-fatal myocardial infarction, coronary artery revascularization, or hospitalization for unstable angina. Results: A total of 116 SCAD patients were enrolled, consisting of 30 cases (25.9%) without depressive symptoms and 86 cases (74.1%) with depressive symptoms. During the follow-up, 3 patients (2.6%) were lost. Out of 113 patients, 51 (45.1%) experienced MACE. In the subgroup of 84 SCAD patients with depressive symptoms, 44 cases (52.4%) of MACE were observed. Finally, mature brain-derived neurotrophic factor (mBDNF), pro-brain-derived neurotrophic factor, receptor activator of nuclear factor-κB ligand, smoking history, hypertension and cystatin C were incorporated into the predictive model. Conclusions: Depressive symptoms represent an independent risk factor for MACE in patients with SCAD. Additionally, low mBDNF expression may be an important early predictor for MACE in SCAD patients with depressive symptoms. The predictive model may exhibit a commendable predictive performance for MACE in SCAD patients with depressive symptoms.

BackgroundThe current clinical practice lacks sufficient objective indicators for evaluating thyroid-associated ophthalmopathy (TAO). This study aims to quantitatively assess TAO by evaluating levator palpebrae superioris (LPS) using Dixon-T2WI.MethodsThe retrospective study included 231 eyes (119 patients) in the TAO group and 78 eyes (39 volunteers) in the normal group. Dixon-T2WI provided data on maximum thickness of LPS (LPS_T) and signal intensity ratio (LPS_SIR) between the muscle and ipsilateral brain white matter. TAO diagnosis and assessment of its activity and severity were quantitatively determined using LPS_T and LPS_SIR.ResultsIn the TAO group, LPS_T and LPS_SIR were higher than those in the normal group (p < 2.2e-16). The upper lid retraction (ULR) ≥ 2 mm group exhibited higher LPS_T and LPS_SIR compared to the ULR < 2 mm and normal groups. Optimal diagnostic performance was achieved with an AUC of 0.91 for LPS_T (cutoff: 1.505 mm) and 0.81 for LPS_SIR (cutoff: 1.170). LPS_T (p = 2.8e-07) and LPS_SIR (p = 3.9e-12) in the active phase were higher than in the inactive phase. LPS_T and LPS_SIR showed differences among the mild, moderate-to-severe, and sight-threatening groups (p < 0.05). ROC showed an AUC of 0.70 for LPS_T (cutoff: 2.095 mm) in judging the active phase, and 0.78 for LPS_SIR (cutoff: 1.129). For judging the moderate-to-severe and above, AUC was 0.76 for LPS_T (cutoff: 2.095 mm) and 0.78 for LPS_SIR (cutoff: 1.197).ConclusionThe maximum thickness and SIR of LPS provide imaging indicators for assisting in the diagnosis and quantitative evaluation of TAO.

ObjectiveMuscle mass gradually declines with advancing age, and as an anti-aging protein, klotho may be associated with muscle mass. This study aims to explore the relationship between klotho levels and muscle mass in the middle-aged population.MethodsUtilizing data from the National Health and Nutrition Examination Survey (NHANES) spanning 2011 to 2018, we conducted a cross-sectional analysis on a cohort of individuals aged 40–59. Weighted multivariable analysis was employed to assess the correlation between klotho and low muscle mass, with stratified and Restricted Cubic Spline (RCS) analyses.ResultsThe cross-sectional investigation revealed a significant negative correlation between klotho levels and the risk of low muscle mass (Model 3: OR = 0.807, 95% CI: 0.712–0.915). A notable interaction between klotho and sex was observed, with a significant interaction effect (P for interaction = 0.01). The risk association was notably higher in females. The risk association was notably higher in females. Additionally, RCS analysis unveiled a significant linear relationship between klotho and low muscle mass (P for nonlinear = 0.9495, P for overall

Cardiovascular diseases (CVDs) are the leading cause of mortality worldwide. Others and our studies have shown that mechanical stresses (forces) including shear stress and cyclic stretch, occur in various pathological conditions, play significant roles in the development and progression of CVDs. Mitochondria regulate the physiological processes of cardiac and vascular cells mainly through adenosine triphosphate (ATP) production, calcium flux and redox control while promote cell death through electron transport complex (ETC) related cellular stress response. Mounting evidence reveal that mechanical stress-induced mitochondrial dysfunction plays a vital role in the pathogenesis of many CVDs including heart failure and atherosclerosis. This review summarized mitochondrial functions in cardiovascular system under physiological mechanical stress and mitochondrial dysfunction under pathological mechanical stress in CVDs (graphical abstract). The study of mitochondrial dysfunction under mechanical stress can further our understanding of the underlying mechanisms, identify potential therapeutic targets, and aid the development of novel treatments of CVDs.

Summary: Background: The public health burden of cardiomyopathies and competency in their management by health agencies in China are not well understood. Methods: This study adopted a multi-stage sampling method for hospital selection. In the first stage, nationwide tertiary hospital recruitment was performed. As a result, 88 hospitals with the consent of the director of cardiology and access to an established electronic medical records system, were recruited. In the second stage, we sampled 66 hospitals within each geographic-economic stratification through a random sampling process. Data on (1) the outpatient and inpatient visits for cardiomyopathies between 2017 and 2021 and (2) the competency in the management of patients with cardiomyopathies, were collected. The competency of a hospital to provide cardiomyopathy care was evaluated using a specifically devised scale. Findings: The outpatient and inpatient visits for cardiomyopathies increased between 2017 and 2021 by 38.6% and 33.0%, respectively. Most hospitals had basic facilities for cardiomyopathy assessment. However, access to more complex procedures was limited, and the integrated management pathway needs improvement. Only 4 (6.1%) of the 66 participating hospitals met the criteria for being designated as a comprehensive cardiomyopathy center, and only 29 (43.9%) could be classified as a primary cardiomyopathy center. There were significant variations in competency between hospitals with different administrative and economic levels. Interpretation: The health burden of cardiomyopathies has increased significantly between 2017 and 2021 in China. Although most tertiary hospitals in China can offer basic cardiomyopathy care, more advanced facilities are not yet universally available. Moreover, inconsistencies in the management of cardiomyopathies across hospitals due to differing administrative and economic levels warrants a review of the nation allocation of medical resources. Funding: This work was supported by the Chinese Academy of Medical Sciences (CAMS) Innovation Fund for Medical Sciences (2023-I2M-1-001) and the National High Level Hospital Clinical Research Funding (2022-GSP-GG-17).

This paper investigates the solubility behavior of digitoxin in supercritical carbon dioxide (CO2) through a comprehensive analysis employing ensemble learning techniques and various regression models. The dataset consists of temperature and pressure as input variables, with solvent density and digitoxin solubility as output variables. Utilizing bagging as the ensemble method, Gaussian process regression (GPR), Bayesian Ridge Regression (BRR), Orthogonal Matching Pursuit (OMP), and Polynomial Regression (PR) were employed as regression models. Hyper-parameter tuning was achieved through gradient-based optimization. Results revealed that Polynomial Regression (PR) emerges as the most effective model for predicting both solvent density and digitoxin solubility. For solubility prediction, BAG-PR yields an R2 score of 0.98527, with MSE and MAE of 1.4290E-03 and 3.40547E-02, respectively. Concerning solvent density, BAG-PR achieves an outstanding R2 of 0.99766, along with MSE and MAE of 7.4759E+01 and 7.33964E+00, respectively. These results show that ensemble learning, and polynomial regression can accurately predict solubility and solvent density, revealing digitoxin's behavior in supercritical CO2.

BackgroundPrimary ovarian insufficiency (POI) is a common clinical endocrine disorder with a high heterogeneity in both endocrine hormones and etiological phenotypes. However, the etiology of POI remains unclear. Herein, we unraveled the causality of genetically determined metabolites (GDMs) on POI through Mendelian randomization (MR) study with the overarching goal of disclosing underlying mechanisms.MethodsGenetic links with 486 metabolites were retrieved from GWAS data of 7824 European participants as exposures, while GWAS data concerning POI were utilized as the outcome. Via MR analysis, we selected inverse-variance weighted (IVW) method for primary analysis and several additional MR methods (MR-Egger, weighted median, and MR-PRESSO) for sensitivity analyses. MR-Egger intercept and Cochran’s Q statistical analysis were conducted to assess potential heterogeneity and pleiotropy. In addition, genetic variations in the key target metabolite were scrutinized further. We conducted replication, meta-analysis, and linkage disequilibrium score regression (LDSC) to reinforce our findings. The MR Steiger test and reverse MR analysis were utilized to assess the robustness of genetic directionality. Furthermore, to deeply explore causality, we performed colocalization analysis and metabolic pathway analysis.ResultsVia IVW methods, our study identified 33 metabolites that might exert a causal effect on POI development. X-11437 showed a robustly significant relationship with POI in four MR analysis methods (PIVW=0.0119; Pweighted-median =0.0145; PMR-Egger =0.0499; PMR-PRESSO =0.0248). Among the identified metabolites, N-acetylalanine emerged as the most significant in the primary MR analysis using IVW method, reinforcing its pivotal status as a serum biomarker indicative of an elevated POI risk with the most notable P-value (PIVW=0.0007; PMR-PRESSO =0.0022). Multiple analyses were implemented to further demonstrate the reliability and stability of our deduction of causality. Reverse MR analysis did not provide evidence for the causal effects of POI on 33 metabolites. Colocalization analysis revealed that some causal associations between metabolites and POI might be driven by shared genetic variants.ConclusionBy incorporating genomics with metabolomics, this study sought to offer a comprehensive analysis in causal impact of serum metabolome phenotypes on risks of POI with implications for underlying mechanisms, disease screening and prevention.

Background Maintaining machines effectively continues to be a challenge for industrial organisations, which frequently employ reactive or premeditated methods. Recent research has begun to shift its attention towards the application of Predictive Maintenance (PdM) and Digital Twins (DT) principles in order to improve maintenance processes. PdM technologies have the capacity to significantly improve profitability, safety, and sustainability in various industries. Significantly, precise equipment estimation, enabled by robust supervised learning techniques, is critical to the efficacy of PdM in conjunction with DT development. This study underscores the application of PdM and DT, exploring its transformative potential across domains demanding real-time monitoring. Specifically, it delves into emerging fields in healthcare, utilities (smart water management), and agriculture (smart farm), aligning with the latest research frontiers in these areas. Methodology Employing the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) criteria, this study highlights diverse modeling techniques shaping asset lifetime evaluation within the PdM context from 34 scholarly articles. Results The study revealed four important findings: various PdM and DT modelling techniques, their diverse approaches, predictive outcomes, and implementation of maintenance management. These findings align with the ongoing exploration of emerging applications in healthcare, utilities (smart water management), and agriculture (smart farm). In addition, it sheds light on the critical functions of PdM and DT, emphasising their extraordinary ability to drive revolutionary change in dynamic industrial challenges. The results highlight these methodologies’ flexibility and application across many industries, providing vital insights into their potential to revolutionise asset management and maintenance practice for real-time monitoring. Conclusions Therefore, this systematic review provides a current and essential resource for academics, practitioners, and policymakers to refine PdM strategies and expand the applicability of DT in diverse industrial sectors.