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Abstract Edible traditional Chinese medicines (TCMs) have a long‐standing history in tackling obesity, diabetes, and metabolic diseases, which, in turn, significantly promotes the exploration of functional food products derived from edible TCMs with lower toxicity and reduced side effects. However, most of bioactive components from TCMs and their mechanisms in regulating blood glucose and lipids remain elusive, which poses a challenge for the development of safer and more effective TCM products. In this context, the development of high‐throughput screening methods has become even more important for the identification of active components and the in‐depth evaluation of hypoglycemic and hypolipidemic activity in vitro and in vivo. Therefore, this work provides an overview of edible TCMs for managing glucose and lipid metabolism disorders and summarizes the most recent progresses in identifying hypoglycemic and hypolipidemic bioactive compounds in edible TCMs through various screening methods. One significant approach involves the utilization of multitarget‐based ultrafiltration liquid chromatography coupled with mass spectrometry. This technique enables the concurrent screening and identification of potential pharmacodynamically active components in TCMs, as well as the investigation of their mechanisms of action. The bioactive compounds identified may serve as crucial active agents in reducing blood glucose and lipids, exhibiting promising potential for incorporation into functional foods or natural health products.

Abstract Background Occupational voice users frequently face the challenge of vocal fatigue, impacting their overall well-being and job performance. This study aimed to investigate the knowledge, attitude, and practice (KAP) toward vocal fatigue among occupational voice users. Methods This web-based cross-sectional study was conducted among occupational voice users between July and October 2023 in Shenzhen People’s Hospital, utilizing a self-administered questionnaire to examine the KAP of vocal fatigue. A total of 920 valid questionnaires were collected with 248 males and 672 females, with 34.35% aged between 21 and 30 years. Results The mean (standard deviation) scores were 15.1 (5.3) for knowledge (range: 0–24), 31.6 (3.6) for attitude (range: 8–40), and 45.0 (7.5) for practice (range: 13–65). A graduate degree or higher was positively associated with knowledge (odds ratio [OR] = 1.596, P = 0.007). Negative associations with knowledge included being a salesperson (OR = 0.342, P

Abstract Background Immunoglobulin A nephropathy (IgAN) is a major cause of chronic kidney disease (CKD) and kidney failure. Necroptosis is a novel type of programmed cell death that has been proved to be associated with the pathogenesis of infectious disease, cardiovascular disease, neurological disorders and so on. However, the role of necroptosis in IgAN remains unclear. Methods In this study, we explored the role of necroptosis-related genes in the pathogenesis of IgAN using a comprehensive bioinformatics method. Microarray datasets GSE93798 and GSE115857 were downloaded from Gene Expression Omnibus (GEO). “limma” package of R software was employed to identify necroptosis-related differentially expressed genes (NRDEGs) between IgAN and healthy controls. GO and KEGG functional enrichment analysis was performed by Clusterprofiler. Least absolute shrinkage and selection operator (LASSO) regression analysis identified hub NRDEGs. We further established a diagnostic model consisting of 7 diagnostic hub NRDEGs and validated the efficacy by an external dataset. The expression of hub genes was confirmed in sc-RNA dataset GSE171314. Immune infiltration, gene set enrichment analysis and transcription factor binding motifs enrichment analysis were conducted to further uncover their roles. Results 1076 differentially expressed genes were identified between healthy individuals and IgAN patients from RNA-seq dataset GSE9379. Then we cross-linked them with necroptosis-related genes to obtain 9 NRDEGs. LASSO regression analysis screened out 7 hub genes (JUN, CD274, SERTAD1, NFKBIA, H19, UCHL1 and EZH2) of IgAN. We further conducted functional enrichment analysis and constructed the diagnostic model based on dataset GSE93798. GSE115857 was used as the independent validation cohort and indicated a great predictive efficacy. Immune infiltration, gene set enrichment analysis and transcription factor binding motifs enrichment analysis revealed their potential function. Finally, we screened out four drugs that were predicted to have therapeutic value of IgAN. Conclusions In summary, we identified 7 hub necroptosis-associated genes, which can be used as potential genetic biomarkers for IgAN prediction and treatment. Four drugs were predicted as the potential therapeutic solutions. Collectively, we provided insights into the necroptosis-related mechanisms and treatment of IgAN at the transcriptome level.

Abstract Previously, a synchrotron‐based horizontal proton beamline (87.2 MeV) was successfully commissioned to deliver radiation doses in FLASH and conventional dose rate modes to small fields and volumes. In this study, we developed a strategy to increase the effective radiation field size using a custom robotic motion platform to automatically shift the positions of biological samples. The beam was first broadened with a thin tungsten scatterer and shaped by customized brass collimators for irradiating cell/organoid cultures in 96‐well plates (a 7‐mm‐diameter circle) or for irradiating mice (1‐cm2 square). Motion patterns of the robotic platform were written in G‐code, with 9‐mm spot spacing used for the 96‐well plates and 10.6‐mm spacing for the mice. The accuracy of target positioning was verified with a self‐leveling laser system. The dose delivered in the experimental conditions was validated with EBT‐XD film attached to the 96‐well plate or the back of the mouse. Our film‐measured dose profiles matched Monte Carlo calculations well (1D gamma pass rate >95% with the criteria of 2%/1 mm/2% dose threshold). The FLASH dose rates were 113.7 Gy/s for cell/organoid irradiation and 191.3 Gy/s for mouse irradiation. These promising results indicate that this robotic platform can be used to effectively increase the field size for preclinical experiments with proton FLASH.

Abstract In recent years, large-scale artificial intelligence (AI) models have become a focal point in technology, attracting widespread attention and acclaim. Notable examples include Google’s BERT and OpenAI’s GPT, which have scaled their parameter sizes to hundreds of billions or even tens of trillions. This growth has been accompanied by a significant increase in the amount of training data, significantly improving the capabilities and performance of these models. Unlike previous reviews, this paper provides a comprehensive discussion of the algorithmic principles of large-scale AI models and their industrial applications from multiple perspectives. We first outline the evolutionary history of these models, highlighting milestone algorithms while exploring their underlying principles and core technologies. We then evaluate the challenges and limitations of large-scale AI models, including computational resource requirements, model parameter inflation, data privacy concerns, and specific issues related to multi-modal AI models, such as reliance on text-image pairs, inconsistencies in understanding and generation capabilities, and the lack of true “multi-modality”. Various industrial applications of these models are also presented. Finally, we discuss future trends, predicting further expansion of model scale and the development of cross-modal fusion. This study provides valuable insights to inform and inspire future future research and practice.

Abstract Aims End‐stage hypertrophic cardiomyopathy (ES‐HCM) is a disease with severe complications and a poor prognosis. This study aimed to explore the influencing and prognostic factors of ES‐HCM. Methods and results A total of 1282 patients with HCM who were hospitalized for the first time at Fujian Medical University Union Hospital between 1 January 2013 and 30 September 2021 were recorded. The patients with HCM and left ventricular ejection fraction (LVEF)

A differential game guidance scheme with obstacle avoidance, based on the formulation of a combined linear quadratic and norm-bounded differential game, is designed for a three-player engagement scenario, which includes a pursuer, an interceptor, and an evader. The confrontation between the players is divided into four phases (P1–P4) by introducing the switching time, and proposing different guidance strategies according to the phase where the static obstacle is located: the linear quadratic game method is employed to devise the guidance scheme for the energy optimization when the obstacle is located in the P1 and P3 stages; the norm-bounded differential game guidance strategy is presented to satisfy the acceleration constraint under the circumstance that the obstacle is located in the P2 and P4 phases. Furthermore, the radii of the static obstacle and the interceptor are taken as the design parameters to derive the combined guidance strategy through the dead-zone function, which guarantees that the pursuer avoids the static obstacle, and the interceptor, and attacks the evader. Finally, the nonlinear numerical simulations verify the performance of the game guidance strategy.

Abstract In the era of cloud service popularization, the trustworthiness of service is particularly important. If users cannot prevent the potential trustworthiness problem of the service during long-term use, once the trustworthiness problem occurs, it will cause significant losses. In order to objectively assess the cloud service trustworthiness, and predict its change, this paper establishes a special hierarchical model of cloud service trustworthiness attributes. This paper proposes corresponding management countermeasures around the model, defines the cloud service trustworthiness level, defines the cloud service trusted state based on fuzzy entropy and Markov chain, constructs the membership function of the cloud service trusted state, and realizes the assessment of cloud service trustworthiness and its changes according to the prediction method of Markov chain. Through case analysis and method comparison, it shows that the method proposed in this paper is effective and feasible. This method can provide objective and comprehensive assessment data for the cloud service trustworthiness and its change, makes up the deficiency of fuzzy entropy assessment method. This research has important reference value and significance for the research of cloud service trustworthiness assessment.

Aluminum alloys are widely used in aerospace, transportation, and many other fields due to their excellent properties such as lightweight, ultra-strength, and high toughness. This paper analyzed the influence mechanism of friction stir on the microstructure, texture, and mechanical properties to realize the strength and toughness of 7055 aluminum alloys and optimize their deformation process. The results show that the aluminum alloys change from uneven banded grains to uniform and fine equiaxed grains after friction stir processing, and the grain size is refined from 14 μm to 0.71 μm. The high-angle grain boundary and texture intensity present an initial increase but a subsequent decrease due to the combined effect of recrystallization and high-temperature softening caused by the heat input of friction stir processing. The total texture intensity and volume fraction of the friction stir processed aluminum alloys decrease significantly, and the intensity of RtG {110} , A {110} , E {110} , and F {111} texture significantly decrease or disappear, while the Brass (B) {110} texture increases. The yield strength of FSP aluminum alloys decreases with increasing heat input (w/v), which mainly depends on the weakening of the texture strengthening effect. However, the increase of geometrically necessary dislocations (GND) caused by grain boundary sliding leads to the significant improvement of the deformation hardening ability and plasticity of the material. In addition, the effect of texture on the plasticity of aluminum alloys was calculated by using Schmid law. It is found that the equivalent slip factor (ESF) and maximum Schmid factor (μmax) of A, E, and Cu textures are equal to 0. The small ESF and μmax of the S texture are not conducive to the plastic deformation property of materials, while the 1000 × 70 sample with more ESF (8) and μmax (0.41) of the Cube texture ({001} ) shows better plasticity.

Colonoscopy is an important technical means for screening early colorectal cancer lesions. Accurate segmentation of intestinal polyps helps improve the accuracy of screening. Early screening for lesions is of great significance for the prevention of colorectal cancer, and the segmentation of intestinal polyps is an important research direction. Although intestinal polyp segmentation based on deep learning has achieved acceptable performance, the color variation among intestinal endoscopic images significantly affects it. Based on the ResNet architecture, this study proposes an advanced PE-ResNet in which histogram equalization is used to reduce color influence. Experimental results on five datasets, including ClinicDB, demonstrate that the PE-ResNet model achieves improved performance in intestinal polyp segmentation.

Abstract Living cells can rapidly adjust their metabolic activities in response to external stimuli, leading to fluctuations in intracellular temperature and reactive oxygen species (ROS) levels. Monitoring these parameters is essential for understanding cellular metabolism, particularly during dynamic biological processes. In this study, we present a bifunctional nanoprobe capable of simultaneous measurement of ROS levels and temperature within single cells. The nanoprobe features two individually addressable nanoelectrodes, with platinum (Pt) and nickel (Ni) coatings on both sides. At the tip, these two metal layers form a nano-thermocouple, enabling precise intracellular temperature measurements, while the Pt layer facilitates selective ROS detection. This dual functionality allows for real-time monitoring of cellular responses during synergistic chemo-photothermal therapy of cancer cells and zebrafish embryos subjected to mitochondrial toxic stress. Our results demonstrate that the nanoprobe effectively measures increases in temperature and ROS levels in HeLa cells undergoing chemo-photothermal therapy, as well as in chemically stimulated zebrafish embryos. By providing detailed analysis of submicrometer-scale temperature and ROS variations within living cells, this nanoprobe offers valuable insights into cellular processes and holds promise for early disease detection and drug development.

Abstract The low-potential aldehyde oxidation reaction can occur at low potential (~0 VRHE) and release H2 at the anode, enabling hydrogen production with less than one-tenth of the energy consumption required for water splitting. Nevertheless, the activity and stability of Cu catalysts remain inadequate due to the oxidative deactivation of Cu-based materials. Herein, we elucidate the deactivation and reactivation cycle of Cu electrocatalyst and develop a self-reactivating PdCu catalyst that exhibits significantly enhanced stability. Initially, in-situ Raman spectroscopy confirm the cycle involved in electrochemical oxidation and non-electrochemical reduction. Subsequently, in-situ Raman spectroscopy and X-ray absorption fine structure reveal that the Pd component accelerates the rate of the non-electrochemical reduction, thereby enhancing the stability of the Cu-based electrocatalyst. Finally, a bipolar hydrogen production device is assembled utilizing the PdCu electrocatalyst, which can deliver a current of 400 mA cm−2 at 0.42 V and operate continuously for 120 h. This work offers guidance to enhance the stability of the Cu-based electrocatalyst in a bipolar hydrogen production system.

Abstract Optical patterning of colloidal particles is a scalable and cost-effective approach for creating multiscale functional structures. Existing methods often use high-intensity light sources and customized optical setups, making them less feasible for large-scale microfabrication processes. Here, we report an optical patterning method for semiconductor nanoparticles by light-triggered modulation of their surface charge. Rather than using light as the primary energy source, this method utilizes UV-induced cleavage of surface ligands to modify surface charges, thereby facilitating the self-assembly of nanoparticles on a charged substrate via electrostatic interactions. By using citrate-treated ZnO nanoparticles, uniform ZnO patterns with variable thicknesses can be achieved. These multilayered ZnO patterns are fabricated into a UV detector with an on/off ratio exceeding 104. Our results demonstrate a simple yet effective way to pattern semiconductor nanoparticles, facilitating the large-scale integration of functional nanomaterials into emerging flexible and robotic microdevices.

Abstract The electrocatalytic reduction of CO2 to CO is slowed by the energy cost of the hydrogenation step that yields adsorbed *COOH intermediate. Here, we report a hydrogen radical (H•)-transfer mechanism that aids this hydrogenation step, enabled by constructing Ni-partnered hetero-diatomic pairs, and thereby greatly enhancing CO2-to-CO conversion kinetics. The partner metal to the Ni (denoted as M) catalyzes the Volmer step of the water/proton reduction to generate adsorbed *H, turning to H•, which reduces CO2 to carboxyl radicals (•COOH). The Ni partner then subsequently adsorbs the •COOH in an exothermic reaction, negating the usual high energy-penalty for the electrochemical hydrogenation of CO2. Tuning the H adsorption strength of the M site (with Cd, Pt, or Pd) allows for the optimization of H• formation, culminating in a markedly improved CO2 reduction rate toward CO production, offering 97.1% faradaic efficiency (FE) in aqueous electrolyte and up to 100.0% FE in an ionic liquid solution.

Abstract Quantum entanglement acts as a crucial part in quantum computation and quantum information, hence quantifying unknown entanglement is an important task. Due to the fact that the amount of entanglement cannot be achieved directly by measuring any physical observables, it remains an open problem to quantify entanglement experimentally. In this work, we provide an effective way to quantify entanglement for the unknown quantum states via artificial neural networks. By choosing the expectation values of measurements as input features and the values of entanglement measures as labels, we train artificial neural network models to predict the entanglement for new quantum states accurately. Our method does not require the full information about unknown quantum states, which highlights the effectiveness and versatility of machine learning in exploring quantum entanglement.

Abstract Background With the rapid increase of chest computed tomography (CT) images, the workload faced by radiologists has increased dramatically. It is undeniable that the use of artificial intelligence (AI) image‐assisted diagnosis system in clinical treatment is a major trend in medical development. Therefore, in order to explore the value and diagnostic accuracy of the current AI system in clinical application, we aim to compare the detection and differentiation of benign and malignant pulmonary nodules between AI system and physicians, so as to provide a theoretical basis for clinical application. Methods Our study encompassed a cohort of 23 336 patients who underwent chest low‐dose spiral CT screening for lung cancer at the Health Management Center of West China Hospital. We conducted a comparative analysis between AI‐assisted reading and manual interpretation, focusing on the detection and differentiation of benign and malignant pulmonary nodules. Results The AI‐assisted reading exhibited a significantly higher screening positive rate and probability of diagnosing malignant pulmonary nodules compared with manual interpretation (p

Abstract Background Idiopathic pulmonary fibrosis (IPF) is a chronic and progressive interstitial lung disease of unknown etiology. Despite the increasing global incidence and poor prognosis, the exact pathogenic mechanisms remain elusive. Currently, effective therapeutic targets and treatment methods for this disease are still lacking. This study tried to explore the pathogenic mechanisms of IPF. We found elevated expression of SULF1 in lung tissues of IPF patients compared to normal control lung tissues. SULF1 is an enzyme that modifies heparan sulfate chains of heparan sulfate proteoglycans, playing a critical role in biological regulation. However, the effect of SULF1 in pulmonary fibrosis remains incompletely understood. Our study aimed to investigate the impact and mechanisms of SULF1 in fibrosis. Methods We collected lung specimens from IPF patients for transcriptome sequencing. Validation of SULF1 expression in IPF patients was performed using Western blotting and RT-qPCR on lung tissues. ELISA experiments were employed to detect SULF1 concentrations in IPF patient plasma and TGF-β1 levels in cell culture supernatants. We used lentiviral delivery of SULF1 shRNA to knock down SULF1 in HFL1 cells, evaluating its effects on fibroblast secretion, activation, proliferation, migration, and invasion capabilities. Furthermore, we employed Co-Immunoprecipitation (Co-IP) to investigate the regulatory mechanisms involved. Results Through bioinformatic analysis of IPF transcriptomic sequencing data (HTIPF) and datasets GSE24206, and GSE53845, we identified SULF1 may potentially play a crucial role in IPF. Subsequently, we verified that SULF1 was upregulated in IPF and predominantly increased in fibroblasts. Furthermore, SULF1 expression was induced in HFL1 cells following exposure to TGF-β1. Knockdown of SULF1 suppressed fibroblast secretion, activation, proliferation, migration, and invasion under both TGF-β1-driven and non-TGF-β1-driven conditions. We found that SULF1 catalyzes the release of TGF-β1 bound to TGFβRIII, thereby activating the TGF-β1/SMAD pathway to promote fibrosis. Additionally, TGF-β1 induces SULF1 expression through the TGF-β1/SMAD pathway, suggesting a potential positive feedback loop between SULF1 and the TGF-β1/SMAD pathway. Conclusions Our findings reveal that SULF1 promotes fibrosis through the TGF-β1/SMAD pathway in pulmonary fibrosis. Targeting SULF1 may offer a promising therapeutic strategy against IPF.

Abstract Although septal myectomy is the preferred treatment for medication-refractory hypertrophic obstructive cardiomyopathy (HOCM), the procedure remains subjective. A preoperative planning procedure is proposed using computational fluid dynamics simulations and shape optimization to assist in the objective assessment of the adequacy of the resection. 3 patients with HOCM were chosen for the application of the proposed procedure. The geometries of the preoperative left ventricular outflow tract (LVOT) of patients in the systolic phase were reconstructed from medical images. Computaional fluid dynamics (CFD) simulations were performed to assess hemodynamics within LVOT. Sensitivity analysis was performed to determine the resection extent on the septal wall, and the depth of the resection was optimized to relieve LVOT obstruction while minimizing damage to the septum. The optimized resection was then transferred from systole to diastole to provide surgeons with instructive guidance for septal myectomy. Comparison between preoperative and postoperative hemodynamics showed an evident improvement with respect to the pressure gradient throughout the LVOT. The resected myocardium in the diastolic phase is more extended and thinner than its state in the systolic phase. The proposed preoperative planning procedure may be a viable addition to the current preoperative assessment of patients with HOCM.

Abstract Background This study explores the relationship between serum uric acid(UA) levels and depression. UA is the final product of purine metabolism in the human body, possessing certain physiological functions such as blood pressure regulation, antioxidation, DNA protection, and anti-aging, thereby drawing attention for its potential role in preventing and treating depression. Methods This cross-sectional study includes 32,424 participants aged ≥ 20 years from the National Health and Nutrition Examination Survey (NHANES) conducted between 2005 and 2018, generating a nationally representative database. Depressive symptoms were assessed using the Patient Health Questionnaire-9. Serum uric acid concentration was measured using the uricase-peroxidase coupled method, and participants were divided into quartiles of serum uric acid concentration. Weighted data were calculated according to analysis guidelines. The association between serum uric acid and depressive symptoms was analyzed using weighted multivariable logistic regression models and restricted cubic spline regression analyses. Subgroup analyses were also performed. Results Among 32,424 participants, 3,421 were defined as having depressive symptoms. The crude prevalence of depressive symptoms was 10.5% (weighted prevalence: 9.086% [95% confidence interval: 9.032–9.139%]). Compared with the first quartile, individuals with higher UA levels had a decreased risk of depressive symptoms by 9% (OR: 0.910, 95% CI: 0.797–10.40), 14.6% (OR: 0.854, 95% CI: 0.741–0.983), and 20.5% (OR: 7795, 95% CI: 0.680–0.930), respectively. Further restricted cubic spline regression analysis revealed a nonlinear association between UA and depressive symptoms, with an inflection point of 319.72 µmol/L. Subgroup multivariable weighted logistic regression analysis found that the association between UA and the risk of depressive symptoms remained consistent across all subgroups, demonstrating high stability and reliability. Conclusion This study emphasizes a significant nonlinear negative correlation between serum uric acid and depressive symptoms. This suggests that proper control of serum uric acid levels may play a role in preventing and treating depression.

Abstract Background Systemic lupus erythematosus (SLE) is an autoimmune disease that currently cannot be completely cured with a great health burden. Since the production of autoantibodies plays a key role in the pathogenesis of SLE, discovering the underlying immunoregulation mechanism of B cells will be helpful for developing promising immunotherapy for SLE. In recent studies, dopamine receptors (DRDs), G protein-coupled receptors that include D1-like and D2-like subtypes, are expressed on B cells and participate in various physiological processes, involving immune responses. However, the regulatory effect of DRDs on B cells has not been determined. Methods This study explored the expression of DRDs on B-cell subsets from SLE patients and healthy individuals. The effects of D1-like receptor on B-cell activation and differentiation were further explored using D1-like receptor agonists or antagonists. RNA-seq and bioinformatics analyses were used to identify specific molecular mechanisms involved. Results The D1-like DRDs on B cells of SLE patients were highly expressed compared with those of healthy controls (HCs). D1-like receptor agonist treatment exacerbated lupus-like symptoms in pristane-induced lupus-like mice, while D1-like receptor antagonists alleviated the lupus-like phenotypes. Inhibition of D1-like receptor signals impeded B-cell differentiation, while activation of D1-like receptor signals could promote B cell differentiation. Further RNA-seq confirmed that PTGS2, a gene related to B-cell differentiation, was up-regulated once the D1-like receptor signals were activated, while BMP6 and IL-24 were up-regulated once the D1-like receptor signals were inhibited. Conclusion D1-like receptors probably promote B-cell differentiation through the PTGS2/PRDM1 pathway.

Highlights Introduce the role of bioelectricity and the endogenous electric field in bone tissue and summarize different techniques to electrically stimulate cells and tissue. Highlight the latest progress in exploring electroactive hybrid biomaterials as well as self-powered systems such as triboelectric and piezoelectric-based nanogenerators and photovoltaic cell-based devices in bone tissue engineering. Emphasize the significance of simulating the target tissue’s electrophysiological microenvironment and propose the opportunities and challenges faced by electroactive hybrid biomaterials and self-powered bioelectronics.

Abstract Salmonella Enteritidis is a major foodborne pathogen throughout the world and the increase in antibiotic resistance of Salmonella poses a significant threat to public safety. Natural nanobodies exhibit high affinity, thermal stability, ease of production, and notably higher diversity, making them widely applicable for the treatment of viral and bacterial infections. Recombinant expression using Lactococcus lactis leverages both acid resistance and mucosal colonization properties of these bacteria, allowing the effective expression of exogenous proteins for therapeutic effects. In this study, nine specific nanobodies against the flagellar protein FliC were identified and expressed. In vitro experiments demonstrated that FliC-Nb-76 effectively inhibited the motility of S. Enteritidis and inhibited its adhesion to and invasion of HIEC-6, RAW264.7, and chicken intestinal epithelial cells. Additionally, a recombinant L. lactis strain secreting the nanobody, L. lactis-Nb76, was obtained. Animal experiments confirmed that it could significantly reduce the mortality rates of chickens infected with S. Enteritidis, together with alleviating the inflammatory response caused by the pathogen. These results provide a novel strategy for the treatment of antibiotic-resistant S. Enteritidis infection in the intestinal tract. Graphical Abstract

Abstract Systemic lupus erythematosus (SLE) is an autoimmune disorder that commonly affects the skin, kidneys, joints, and various other systemic tissues, with its development intricately linked to the process of immunosenescence. Quercetin (QC), a phytochemical that occurs naturally, demonstrates many different biological capabilities, such as antibacterial, antioxidant, and anti-inflammatory activities. Our investigation found that QC effectively reduced kidney damage and relieved mesenteric lymph nodes (mLNs) swelling in MRL/lpr lupus mice. Moreover, QC has been found to decrease the number of senescent follicular helper T (Tfh) cells, a pivotal kind of T cells that contribute to the progression of SLE. In vitro, QC exhibited the capacity to modulate mRNA expression levels, with the downregulation of IL-6, IL21-AS1, IL-27, BCL6, and BCL2L12, and the upregulation of FOXP1 and BIM. This modulation resulted in the suppression of Tfh cells differentiation and the enhancement of apoptosis in senescent CD4+ T cells. In addition, the HuProtTM Human Proteome Microarray revealed that QC can directly bind to BCL-2 protein and therefore promote the apoptosis of senescent CD4+ T cell. As a result, our investigative elucidate the potent inhibitory action of QC on the ontogeny of Tfh cells, along with its capacity to abrogate the immunosenescent phenotype. This positions QC as a promising therapeutic strategy for treating SLE.

Abstract Background Alveolar echinococcosis (AE), a fatal disease caused by Echinococcus multilocularis, often affects the liver, with tumor-like growth. However, the mechanism by which E. multilocularis evades host immune surveillance remains unclear. Methods We collected liver specimens from hepatic alveolar echinococcosis (HAE) patients and established a mouse model of E. multilocularis infection. Immunofluorescence staining and flow cytometry were performed to analyze programmed cell death protein 1 (PD-1) and cytotoxic T lymphocyte associated antigen 4 (CTLA-4) expression in human samples, while flow cytometry and quantitative real-time polymerase chain reaction (PCR) were performed for similar analyses in mouse samples. Cell proliferation and protoscolex (PSC) killing assays were designed to explore how E. multilocularis induces host immunosuppression. Results An inflammatory reaction band with high PD-1 and CTLA-4 expression was found in close liver tissue (CLT). The ratio of regulatory T cells (Tregs) was higher in CLT than in distant liver tissue (DLT), and Tregs in CLT tended to express higher levels of PD-1 and CTLA-4 than those in DLT from HAE patients. Echinococcus multilocularis-infected mice showed significantly elevated expression of PD-1 and CTLA-4 on splenocytes and peritoneal cells. PD-1/PD-L1 or CTLA-4 pathway blockade could relieve the immunosuppressive effects of Tregs from infected mice and enhance PSC killing by mouse splenocytes. Conclusions E. multilocularis regulated the function of T cells via the PD-1/PD-L1- and CTLA-4-dependent pathways and subsequently evaded host immune attacks. These findings provide insights for investigating the pathogenic mechanism of AE. Graphical Abstract

Abstract Recent years have seen increased interest in object detection‐based applications for fire detection in digital images and videos from edge devices. The environment's complexity and variability often lead to interference from factors such as fire and smoke characteristics, background noise, and camera settings like angle, sharpness, and exposure, which hampers the effectiveness of fire detection applications. Limited picture data for fire and smoke scenes further challenges model accuracy and robustness, resulting in high false detection and leakage rates. To address the need for efficient detection and adaptability to various environments, this paper focuses on (1) proposing a cloud‐edge collaborative architecture for real‐time fire and smoke detection, incorporating an iterative transfer learning strategy based on user feedback to enhance adaptability; (2) improving the detection capabilities of the base model YOLOv8 by enhancing the data augmentation method and introducing the coordinate attention mechanism to improve global feature extraction. The improved algorithm shows a 2‐point accuracy increase. After three iterations of transfer learning in the production environment, accuracy improves from 93.3% to 96.4%, and mAP0.5:0.95 increases by nearly 5 points. This program effectively addresses false detection issues in fire and smoke detection systems, demonstrating practical applicability.

Abstract Electroceuticals, through the selective modulation of peripheral nerves near target organs, are promising for treating refractory diseases. However, the small sizes and the delicate nature of these nerves present challenges in simplifying the fixation and stabilizing the electrical-coupling interface for neural electrodes. Herein, we construct a robust neural interface for fine peripheral nerves using an injectable bio-adhesive hydrogel bioelectronics. By incorporating a multifunctional molecular regulator during network formation, we optimize the injectability and conductivity of the hydrogel through fine-tuning reaction kinetics and multi-scale interactions within the conductive network. Meanwhile, the mechanical and electrical stability of the hydrogel is achieved without compromising its injectability. Minimal tissue damage along with low and stable impedance of the injectable neural interface enables chronic vagus neuromodulation for myocardial infarction therapy in the male rat model. Our highly-stable, injectable, conductive hydrogel bioelectronics are readily available to target challenging anatomical locations, paving the way for future precision bioelectronic medicine.

Abstract Lithium is key for a clean energy transition but faces sustainability challenges in the global supply. Here, we use a bottom-up approach to study the evolution of the global lithium-ion battery industry from 2023 to 2050. The supply and demand trends are predicted to determine the supply potential and allocation structure of primary and secondary lithium. The results indicate a projected global lithium demand of 1.93 million metric tons in 2050, a significant increase of 26.2 times compared to 2023. In the process of global lithium resources shifting from underground reserves to in-use stocks, population and Gross Domestic Product (GDP) influence regions’ lithium endowment and per capita primary consumption, respectively. If the European Union’s new battery regulation is implemented globally, then it is projected to reduce global primary lithium consumption by 1.03 million metric tons by 2050, with a 53.48% decrease in the proportion of primary lithium consumption.

Abstract Background Neurocognitive disorders frequently occur in patients with cyanotic congenital heart disease (CCHD) because of the hemodynamic abnormalities induced by preoperative cardiac structural changes. We aimed to evaluate subcortical nuclei volume changes and cognition in postoperative tetralogy of Fallot (TOF) children, and analyze their relationship with preoperative cardiac structural changes. Methods This case-control study involved thirty-six children with repaired TOF and twenty-nine healthy controls (HCs). We utilized three-dimensional (3D) T1-weighted high-resolution structural images alongside the Wechsler Preschool and Primary Scale of Intelligence-Fourth Edition (WPPSI-IV) to evaluate the cognitive differences between the TOF and HC group. Results We observed notable differences in subcortical nuclei volume between the TOF and HC group, specifically in the left amygdala nucleus (LAM, TOF: 1292.60 ± 155.57; HC: 1436.27 ± 140.62, p

Abstract In the domain of control engineering, effectively tuning the parameters of proportional-integral-derivative (PID) controllers has persistently posed a challenge. This study proposes a hybrid algorithm (HGJGSO) that combines golden jackal optimization (GJO) and golden sine algorithm (Gold-SA) for tuning PID controllers. To accelerate the convergence of GJO, a nonlinear parameter adaptation strategy is incorporated. The improved GJO is combined with Gold-SA, capitalizing on the expedited convergence speed offered by the improved GJO, coupled with the global optimization and precise search capabilities of Gold-SA. HGJGSO maximizes the strengths of two algorithms, facilitating a comprehensive and balanced exploration and exploitation. The effectiveness of HGJGSO is assessed through tuning the PID controllers for three typical systems. The results indicate that HGJGSO surpasses the comparison tuning methods. To evaluate the applicability of HGJGSO, it is used to tune the cascade PID controllers for trajectory tracking in a quadrotor UAV. The results demonstrate the superiority of HGJGSO in addressing practical challenges.

Abstract Polyamorphic transition (PT) is a compelling and pivotal physical phenomenon in the field of glass and materials science. Understanding this transition is of scientific and technological significance, as it offers an important pathway for effectively tuning the structure and property of glasses. In contrast to the PT observed in conventional metallic glasses (MGs), which typically exhibit a pronounced first-order nature, herein we report a continuous PT (CPT) without first-order characteristics in high-entropy MGs (HEMGs) upon heating. This CPT behavior is featured by the continuous structural evolution at the atomic level and an increasing chemical concentration gradient with temperature, but no abrupt reduction in volume and energy. The continuous transformation is associated with the absence of local favorable structures and chemical heterogeneity caused by the high configurational entropy, which limits the distance and frequency of atomic diffusion. As a result of the CPT, numerous glass states can be generated, which provides an opportunity to understand the nature, atomic packing, formability, and properties of MGs. Moreover, this discovery highlights the implication of configurational entropy in exploring polyamorphic glasses with an identical composition but highly tunable structures and properties.

Abstract Background Pulsed electromagnetic fields (PEMFs) show promise as a treatment for knee osteoarthritis (KOA) by reducing inflammation and promoting chondrogenic differentiation of bone marrow-derived mesenchymal stem cells (BMSCs). Purpose To identify the efficacy window of PEMFs to induce BMSCs chondrogenic differentiation and explore the cellular mechanism under chondrogenesis of BMSCs in regular and inflammatory microenvironments. Methods BMSCs were exposed to PEMFs (75 Hz, 1.6/2/3/3.8 mT) for 7 and 14 days. The histology, proliferation, migration and chondrogenesis of BMSCs were assessed to identify the optimal parameters. Using these optimal parameters, transcriptome analysis was performed to identify target genes and signaling pathways, validated through immunohistochemical assays, western blotting, and qRT-PCR, with or without the presence of IL-1β. The therapeutic effects of PEMFs and the effective cellular signaling pathways were evaluated in vivo. Results BMSCs treated with 3 mT PEMFs showed the optimal chondrogenesis on day 7, indicated by increased expression of ACAN, COL2A, and SOX9, and decreased levels of MMP3 and MMP13 at both transcriptional and protein levels. The advantages of 3 mT PEMFs diminished in the 14-day culture groups. Transcriptome analysis identified sFRP3 as a key molecule targeted by PEMF treatment, which competitively inhibited Wnt/β-catenin signaling, regardless of IL-1β presence or duration of exposure. This inhibition of the Wnt/β-catenin pathway was also confirmed in a KOA mouse model following PEMF exposure. Conclusions PEMFs at 75 Hz and 3 mT are optimal in inducing early-stage chondrogenic differentiation of BMSCs. The induction and chondroprotective effects of PEMFs are mediated by sFRP3 and Wnt/β-catenin signaling, irrespective of inflammatory conditions.

Abstract Background The co-infection of human immunodeficiency virus (HIV)/acquired immune deficiency syndrome (AIDS) and tuberculosis (TB) poses a significant clinical challenge and is a major global public health issue. This study aims to elucidate the disease burden of HIV-TB co-infection in global, regions and countries, providing critical information for policy decisions to curb the HIV-TB epidemic. Methods The ecological time-series study used data from the Global Burden of Disease (GBD) Study 2021. The data encompass the numbers of incidence, prevalence, mortality, and disability-adjusted life year (DALY), as well as age-standardized incidence rate (ASIR), prevalence rate (ASPR), mortality rate (ASMR), and DALY rate for HIV-infected drug-susceptible tuberculosis (HIV-DS-TB), HIV-infected multidrug-resistant tuberculosis (HIV-MDR-TB), and HIV-infected extensively drug-resistant tuberculosis (HIV-XDR-TB) from 1990 to 2021. from 1990 to 2021. The estimated annual percentage change (EAPC) of rates, with 95% confidence intervals (CIs), was calculated. Results In 2021, the global ASIR for HIV-DS-TB was 11.59 per 100,000 population (95% UI: 0.37–13.05 per 100,000 population), 0.55 per 100,000 population (95% UI: 0.38–0.81 per 100,000 population), for HIV-MDR-TB, and 0.02 per 100,000 population (95% UI: 0.01–0.03 per 100,000 population) for HIV-XDR-TB. The EAPC for the ASIR of HIV-MDR-TB and HIV-XDR-TB from 1990 to 2021 were 4.71 (95% CI: 1.92–7.59) and 13.63 (95% CI: 9.44–18.01), respectively. The global ASMR for HIV-DS-TB was 2.22 per 100,000 population (95% UI: 1.73–2.74 per 100,000 population), 0.21 per 100,000 population (95% UI: 0.09–0.39 per 100,000 population) for HIV-MDR-TB, and 0.01 per 100,000 population (95% UI: 0.00–0.03 per 100,000 population) for HIV-XDR-TB in 2021. The EAPC for the ASMR of HIV-MDR-TB and HIV-XDR-TB from 1990 to 2021 were 4.78 (95% CI: 1.32–8.32) and 10.00 (95% CI: 6.09–14.05), respectively. Conclusions The findings indicate that enhancing diagnostic and treatment strategies, strengthening healthcare infrastructure, increasing access to quality medical care, and improving public health education are essential to combat HIV-TB co-infection. Graphical Abstract

Abstract The deformation law of pipelines crossing landslide areas is an important prerequisite for the scientific design of pipelines. Most current studies find it difficult to simulate the real stress and strain state of pipelines on site. This study conducted two centrifuge model tests to observe pipeline failure indicators (deformation, stress, strain) and slope failure indicators (crack width, soil pressure, landslide displacement) in response to changes in acceleration. The experimental findings align with the results obtained from numerical simulations. The findings indicate that slope failure with high moisture content is more serious. At a moisture content of 15%, the slope has a maximum displacement of 70 mm in close reach to the buried pipeline. The pipeline has a “bimodal distribution” of strain along its axial length. The largest amount of deformation occurs at a distance of L/4 from the center of the pipeline, and the deformation value is 9000 με. Moreover, the maximum deformation in the mid-span is 21 mm, which corresponds to the result accumulated from the numerical simulation. Thus, the pipeline needs to improve the disaster prevention capabilities at the mid-span and L/4 of the pipeline.

Abstract Photoacoustic tomography offers a powerful tool to visualize biologically relevant molecules and understand processes within living systems at high resolution in deep tissue, facilitated by the conversion of incident photons into low-scattering acoustic waves through non-radiative relaxation. Although current endogenous and exogenous photoacoustic contrast agents effectively enable molecular imaging within deep tissues, their broad absorption spectra in the visible to near-infrared (NIR) range limit photoacoustic multiplexed imaging. Here, we exploit the distinct ultrasharp NIR absorption peaks of lanthanides to engineer a series of NIR photoacoustic nanocrystals. This engineering involves precise host and dopant material composition, yielding nanocrystals with sharply peaked photoacoustic absorption spectra (~3.2 nm width) and a ~10-fold enhancement in NIR optical absorption for efficient deep tissue imaging. By combining photoacoustic tomography with these engineered nanocrystals, we demonstrate photoacoustic multiplexed differential imaging with substantially decreased background signals and enhanced precision and contrast.

Abstract Background Tuberculosis (TB) is a major infectious disease with significant public health implications. Its widespread transmission, prolonged treatment duration, notable side effects, and high mortality rate pose severe challenges. This study examines the epidemiological characteristics of TB globally and across major regions, providing a scientific basis for enhancing TB prevention and control measures worldwide. Methods The ecological study used data from the Global Burden of Disease (GBD) Study 2021. It assessed new incidence cases, deaths, disability-adjusted life years (DALYs), and trends in age-standardized incidence rates (ASIRs), mortality rates (ASMRs), and DALY rates for drug-susceptible tuberculosis (DS-TB), multidrug-resistant tuberculosis (MDR-TB), and extensively drug-resistant tuberculosis (XDR-TB) from 1990 to 2021. A Bayesian age-period-cohort model was applied to project ASIR and ASMR. Results In 2021, the global ASIR for all HIV-negative TB was 103.00 per 100,000 population [95% uncertainty interval (UI): 92.21, 114.91 per 100,000 population], declining by 0.40% (95% UI: − 0.43, − 0.38%) compared to 1990. The global ASMR was 13.96 per 100,000 population (95% UI: 12.61, 15.72 per 100,000 population), with a decline of 0.44% (95% UI: − 0.61, − 0.23%) since 1990. The global age-standardized DALY rate for HIV-negative TB was 580.26 per 100,000 population (95% UI: 522.37, 649.82 per 100,000 population), showing a decrease of 0.65% (95% UI: − 0.69, − 0.57 per 100,000 population) from 1990. The global ASIR of MDR-TB has not decreased since 2015, instead, it has shown a slow upward trend in recent years. The ASIR of XDR-TB has exhibited significant increase in the past 30 years. The projections indicate MDR-TB and XDR-TB are expected to see significant increases in both ASIR and ASMR from 2022 to 2035, highlighting the growing challenge of drug-resistant TB. Conclusions This study found that the ASIR of MDR-TB and XDR-TB has shown an upward trend in recent years. To reduce the TB burden, it is essential to enhance health infrastructure and increase funding in low-SDI regions. Developing highly efficient, accurate, and convenient diagnostic reagents, along with more effective therapeutic drugs, and improving public health education and community engagement, are crucial for curbing TB transmission. Graphical Abstract

Abstract Background Delirium, marked by acute cognitive decline, poses a life-threatening issue among older individuals, especially after cardiac surgery, with prevalence ranging from 15 to 80%. Postoperative delirium is linked to increased morbidity and mortality. Although clinical trials suggest preventability, there is limited research on intranasal insulin (INI) for cardiac surgery-related delirium. INI has shown promise in managing cognitive disorders. It rapidly elevates brain hormone levels, enhancing memory even in non-impaired individuals. While effective in preventing delirium in gastrointestinal surgery, its impact after cardiac surgery remains understudied, especially for middle-aged patients. Method This is a prospective randomized, double-blind, single-center controlled trial. A total of 76 eligible participants scheduled for elective on-pump cardiac surgery will be enrolled and randomly assigned in a 1:1 ratio to either receive Intranasally administered insulin (INI) or intranasally administered normal saline. The primary outcome of our study is the incidence of postoperative delirium (POD). Secondary outcomes include duration of ICU, postoperative hospital length of stay, all in-hospital mortality, the change in MMSE scores pre- and post-operation, and incidence of postoperative cognitive dysfunction at 1 month, 3 months, and 6 months after operation. Moreover, we will subjectively and objectively evaluate perioperative sleep quality to investigate the potential impact of nasal insulin on the development of delirium by influencing sleep regulation. Discussion Our study will aim to assess the impact of intranasal administration of insulin on the incidence of postoperative delirium in middle-aged patients undergoing on-pump elective cardiac surgery. If intranasal insulin proves to be more effective, it may be considered as a viable alternative for preventing postoperative delirium. Trial registration ChiCTR ChiCTR2400081444. Registered on March 1, 2024.

Underwater optical sensor networks offer significant advantages over traditional acoustic sensor networks, such as high bandwidth and low latency, making them a research hotspot to realize high-speed and real-time transmission of underwater data in sea-air cross-domain communication. However, traditional routing protocols for underwater sensor networks often encounter problems such as routing holes and redundant data transmission due to the transmission obstruction and directional alignment of underwater optical nodes. To address these issues, a fuzzy logic-based opportunistic routing protocol for underwater optical sensor networks was proposed. Firstly, a fuzzy logic-based algorithm was proposed to evaluate the underwater optical channel links. Combined with the modeling of an underwater complex communication environment, the multi-factor fusion evaluation of routing metrics was designed. Additionally, a dynamic mechanism was designed to set the node data forwarding probability and data packet retention time based on real-time link evaluation data. Finally, a probabilistic redundant suppression forwarding algorithm was proposed. Simulation results demonstrate that the proposed routing protocol effectively improves transmission efficiency and reduces end-to-end latency in typical marine communication environments, exhibiting good network dynamic adaptability.

Irradiation with X-rays has been widely utilized in the clinical treatment of solid tumors and certain hematopoietic malignancies. However, this method fails to completely distinguish between malignant and normal cells. Prolonged or repeated exposure to radiation, whether due to occupational hazards or therapeutical interventions, can cause damage to normal tissues, particularly impacting the hematopoietic system. Therefore, it is important to investigate the effects of total body irradiation on the hematopoietic system of mice and to compare the inhibitory effects of various doses of irradiation on this system. In this study, we primarily employed flow cytometry to analyze mature lineage cells in the peripheral blood, as well as immature hematopoietic stem and progenitor cells (HSPCs) in the bone marrow and spleen. Additionally, we evaluated the multilineage differentiation capacity of HSPCs through colony-forming cell assays. Our results indicated that peripheral B and T cells demonstrated increased sensitivity to irradiation, with significant cell death observed 1-day post-irradiation. Common lymphoid progenitor cells exhibited greater radiotolerance compared to other progenitor cell types, enabling them to maintain a certain population even at elevated doses. Moreover, notable differences were observed between intramedullary and extramedullary hematopoietic stem cells and common lymphoid progenitor cells regarding the extent of damage and recovery rate following irradiation. The multilineage differentiation capacity of HSPCs was also compromised during radiation exposure. In conclusion, different types of mature blood cells, along with immature HSPCs, exhibited varying degrees of sensitivity and tolerance to irradiation, resulting in distinct alterations in cell percentages and numbers.

ObjectiveIntracerebral hemorrhage (ICH) is a common cerebrovascular disease characterized by high mortality and disability rates. Neuritin, significantly expressed in injured brain tissues, is implicated in the molecular mechanisms underlying acute brain injury. We aimed to explore the prognostic and predictive value of serum neuritin in ICH.MethodsIn this prospective cohort study, serum neuritin levels were measured at admission in 202 patients, on post-ICH days 1, 3, 5, 7, and 10 in 54 of these patients, and at the time of enrollment in 100 healthy controls. The Glasgow Coma Scale (GCS) and hematoma volume were used as severity indicators. A poor prognosis was defined as a modified Rankin Scale (mRS) score of 3–6 at 90 days after ICH. END was defined as a decrease of ≥2 points in the GCS score within 24 h of admission. A multivariate logistic regression model was used to assess the independent relationships between serum neuritin levels, END, and poor prognosis.ResultsSerum neuritin levels were significantly increased at the time of patient admission, continued to rise on day 1, peaked on day 3, and then gradually diminished from day 5 until day 10. The levels remained substantially higher in patients compared to healthy controls throughout the 10-day period. The levels were independently related to GCS scores and hematoma volume. In subgroup analyses, the levels showed a linear relationship with the likelihood of experiencing END and poor prognosis at the 90-day mark after ICH. Additionally, the levels were independently associated with END, ordinal mRS scores, and poor prognosis. Under receiver operating characteristic (ROC) curve analysis, serum neuritin levels effectively predicted both END and poor prognosis. Two models incorporating GCS, hematoma volume, and serum neuritin levels were developed and represented using two nomograms separately to estimate END risks and poor prognosis. These models demonstrated clinical efficiency, stability, and validity in ROC, calibration, and decision curve analyses. Internal validation of the models was conducted using a randomly extracted subset of 101 patients. Furthermore, two specific weighted scoring systems were developed to optimize clinical prediction of poor prognosis and END after ICH.ConclusionElevated serum neuritin levels are strongly associated with disease severity, END, and 90-day poor neurological outcomes following ICH, establishing serum neuritin as a potential prognostic biomarker for ICH.

ABSTRACT Background The systemic inflammatory response significantly influences the progression and prognosis of various cancers. The novel Inflammatory Burden Index (IBI) was recently introduced as a biomarker to gauge systemic inflammation and evaluate cancer patient prognosis. However, studies investigating the relationship between IBI and mortality rates in cancer patients remain limited. Methods This study analyzed data from 2748 cancer patients enrolled in the National Health and Nutrition Examination Surveys between 1999 and 2018. We used weighted Cox regression analysis and restricted cubic spline models to examine the relationship between the IBI and mortality due to all causes, cardiovascular disease (CVD), and cancer. Furthermore, we employed Kaplan‐Meier survival curves, subgroup analyses, and receiver operating characteristic curves to elaborate on these associations. Results Over a median follow‐up period of 112 months, the cohort experienced 1067 deaths, including 320 from cancer, 239 attributable to heart disease, and 508 from various other causes. The Kaplan‐Meier curve indicated that individuals in the higher quartiles of the IBI faced significantly increased mortality risks compared to those in lower quartiles. Analyses using weighted Cox proportional hazards models demonstrated that subjects in the top IBI quartile were at a substantially higher risk for all‐cause mortality (Hazard Ratio [HR] 2.09, 95% Confidence Interval [CI] 1.67–2.62, p

ObjectivePrevious studies have established a causal relationship between metabolites and breast cancer (BC), but the underlying mechanisms remain unclear. Thus, we aimed to investigate the genetic relationship between metabolites and BC, including its subtypes, using Mendelian randomization (MR) analysis.MethodsUtilizing the latest and most comprehensive summary statistics from genome-wide association studies we conducted an Mendelian randomization study. Data on 233 metabolites, used as exposure variables, were obtained from a study involving 136,016 participants. BC data, used as outcome variables, were sourced from a study comprising 122,977 cases and 105,974 controls. We used the inverse-variance weighted method as the primary approach, along with three supplementary methods, to assess the causal relationship. We also used Cochran’s Q test to detect heterogeneity and MR-Egger regression to examine the presence of horizontal pleiotropy.ResultsUpon analyzing 233 metabolites across 11 classes in relation to BC, we found six classes of metabolites (fatty acids glycerides and phospholipids, lipoprotein subclasses, lipids, apolipoproteins, and lipoprotein particle size) associated with overall BC. Five classes of metabolites (fatty acids glycerides and phospholipids, lipoprotein subclasses, lipids, and lipoprotein particle size) were related to estrogen receptor (ER) + BC, and eight classes of metabolites (fatty acids, amino acids, glycerides and phospholipids, lipoprotein subclasses, lipids, apolipoproteins, glycolysis-related metabolites, and lipoprotein particle size) were linked to ER- BC.ConclusionOur study demonstrates a genetic causal relationship between most metabolites and BC, confirming the link between these factors. This research provides a significant foundation for the prevention and treatment of BC.

Abstract Two indices, indicating the regional average stiffness and the pace of strain hardening respectively, are derived from the nonlinear stress–strain behavior obtained from biomechanical analysis of aneurysm. A comprehensive method based on electrocardiographic‐gated multidimensional dynamic computed tomography angiography (MD CTA) is developed for extracting these mechanical characteristics in vivo. The proposed indices are evaluated by 26 cases including 9 healthy, one aortosclerosis, and 16 abdominal aortic aneurysm cases. The difference of SSI and dSSI value between aneurysmal and healthy groups is up to orders in magnitude. Significant correlation of these indices with the clinical indicator of aneurysm diameter is found. Logistic models based on these indices are capable to sharply discriminate the healthy and the aneurysmal arteries with AUC>0.98. This work introduces new tools and new indices for aortic mechanical assessment which may shed light on understanding the mechanical condition, pathological state and eventually benefit clinical decision‐making.

Background: PFAS pose a significant threat to cardiovascular health and increase the risk of atherosclerotic cardiovascular disease (ASCVD). However, there is limited research evidence regarding the mechanisms by which PFAS affect the risk of ASCVD and the exposure-risk (E-R) relationship. The effect of kidney function in the relationship between PFAS and ASCVD risk has not been adequately validated. Objective: This study aims to explore the mechanisms by which four PFAS (Perfluorooctanoic acid (PFOA), Perfluorooctanesulfonic acid (PFOS), Perfluorohexanesulfonic acid (PFHS), and Perfluorononanoic acid (PFNA)) affect the risk of ASCVD and to verify and discuss the mediating effect of kidney function in this impact. Methods: This study utilizes data from 14,607 participants in the NHANES 2005–2018 to conduct a cross-sectional study. Initially, Generalized Linear Model (GLM) and Restricted Cubic Splines models are used to assess the impact of four PFAS on ASCVD risk and the E-R relationship. Subsequently, the Weighted Quantile Sum regression (WQS) model is used to evaluate the relationship between mixed four PFAS exposure and ASCVD risk. Finally, Directed Acyclic Graphs (DAG) and causal mediation models are used to confirm and analyze whether the decline in kidney function mediates the impact of four PFAS on ASCVD risk. Results: The results from GLM and WQS models indicate that both singular and mixed four PFAS exposures are associated with an increased risk of ASCVD. The E-R curves between four PFAS singular and mixed exposures and ASCVD risk are all characterized by nonlinearity. The results from DAG and causal mediation models clearly indicate that the decline in kidney function plays a significant mediating role in the relationship between four PFAS and ASCVD risk. Conclusion: Exposure levels of four PFAS do not significantly increase the risk of ASCVD unless they reach a certain threshold, and the decline in kidney function exerts a significant mediating effect in the relationship between four PFAS exposure and ASCVD risk.

BackgroundSystemic inflammation (SI) and insulin resistance (IR) are correlated to the progression of gastrointestinal (GI) cancer. Therefore, this study aimed to analyze the potential clinical value of the C-reactive protein-triglyceride-glucose index (CTI) in relation to SI and IR in patients with GI cancer.MethodsThis prospective cohort study included patients with GI cancer. Patient data were collected from Fujian Cancer Hospital as an external validation cohort. Prognostic AUC, time-dependent ROC curve, C-index, and calibration curve analyses were used to predict the efficacy and accuracy of CTI survival prediction. Multivariate survival analysis was performed to evaluate the potential prognostic value of the CTI. Multiple logistic regression was performed to evaluate the relationship between the CTI and 90-day and 180-day mortalities.ResultsWe divided 1520 patients with GI cancer (mean age, 60.39 ± 11.3 years; male sex, 67%) into a training cohort and internal validation cohort; the external validation cohort included 476 patients. Prognostic AUC, time-dependent ROC curve, C-index, and calibration curve analyses of all cohorts indicated that the CTI could reliably and accurately predict the short- and long-term survival outcomes of patients with GI cancer. Multivariate survival analysis showed that for each standard deviation increase in the CTI, the risk of death increased by 32%, 21%, and 40% in the training, internal validation, and external validation cohorts, respectively. A high CTI was correlated to worse survival in patients with GI cancer (training cohort, hazard ratio [HR]=1.67, 95% confidence interval [CI]=1.35–2.08; internal validation cohort, HR=1.51, 95% CI=1.07–2.14, and external validation cohort, HR=1.59, 95% CI=1.18–2.13). In different tumor subgroups, a high CTI predicted worse survival outcomes for upper GI cancer (HR=1.54, 95% CI=1.18–2.01) and lower GI cancer (HR=1.98, 95% CI=1.36–2.86). Multivariate logistic regression analysis showed that a high CTI was positively correlated with 90-day (odds ratio [OR]=3.25, 95% CI=1.75–6.23) and 180-day mortalities (OR=2.66, 95% CI=1.72–4.15).ConclusionsThe CTI is related to SI and IR and can predict the short- and long-term prognosis of patients with GI cancer. Evaluation of the CTI could provide clinicians with an effective tool for predicting the prognosis of patients with GI cancer.Clinical trial registrationhttps://www.chictr.org.cn/showproj.html?proj=31813, identifier ChiCTR1800020329.

Time-restricted eating (TRE) has been shown to extent lifespans in drosophila and mouse models by affecting metabolic and anti-inflammatory activities. However, the effect of TRE on the human immune system, especially on immunosenescence, intestinal microbiome, and metabolism remains unclear. We conducted a 30-day 16:8 TRE single-arm clinical trial with 49 participants. Participants consumed daily meals from 9 a.m. to 5 p.m., provided by a nutrition canteen with a balanced, calorie-appropriate nutrition, which is designed by clinical nutritionists (ChiCTR2200058137). We monitored weight changes and weight-related parameters and focused on changes in the frequency of CD4+ senescent T cells, immune repertoire from peripheral blood, as well as serum metabolites and gut microbiota. We found that up to 95.9 % of subjects experienced sustained weight loss after TRE. The frequency of circulating senescent CD4+ T cells was decreased, while the frequency of Th1, Treg, Tfh-like, and B cells was increased. Regarding the immune repertoire, the proportions of T cell receptor alpha and beta chains were increased, whereas B cell receptor kappa and lambda chains were reduced. In addition, a reduced class switch recombination from immunoglobulin M (IgM) to immunoglobulin A (IgA) was observed. TRE upregulated the levels of anti-inflammatory and anti-aging serum metabolites named sphingosine-1-phosphate and prostaglandin-1. Additionally, several anti-inflammatory bacteria and probiotics were increased, such as Akkermansia and Rikenellaceae, and the composition of the gut microbiota tended to be “younger”. Overall, TRE showed multiple anti-aging effects, which may help humans maintain a healthy lifestyle to stay “young”. Clinical Trial Registration URL: https://www.chictr.org.cn/showproj.html?proj=159876.

Ultra High Performance Concrete (UHPC) is a new concrete material with excellent performance. Many practices have shown that UHPC tends to have excessive compressive properties but insufficient tensile properties. The electromagnetic alignment technology of steel fibers enhances the efficiency of steel fiber utilization. It greatly enhances the flexural strength, but the ductility of the flexural specimens is poor. Furthermore, it is required to use environmentally friendly fibers to partially replace steel fibers, as the incorporation of steel fibers adds to carbon emissions. This research explores the tensile behaviors of hybrid steel-macro basalt fiber UHPC to search for low-carbon construction materials with great mechanical behaviors. The effects of two key parameters, the alignment of steel fibers and the mixing ratio of steel-macro basalt fibers, on the tensile properties were systematically analyzed. Aligned steel fiber was classified as parallel to the tensile direction, vertical to the tensile direction, and undirected. In the steel-macro basalt fiber blend, the total volume doping of 1.5 % was kept unchanged, and a total of four groups of blend schemes were established. Uniaxial tensile tests were performed, and the elastic modulus, tensile strength, and tensile ductility coefficient of the specimens were calculated to produce the stress-strain relationship curves. The results reveal that the parallel orientation of steel fibers could significantly enhance the tensile strength, and the ductility of the material is increased considerably by blending macro basalt fibers. Carbon emissions can be effectively reduced while maintaining superior tensile properties through an optimized combination of steel fiber orientation and steel-macro basalt fiber blend ratio. Finally, the tensile strength prediction equations for this material are proposed by considering the impact of the two fibers on the tensile properties separately.

Abstract Background: Cognitive impairment is the most common long‐term complication in children with congenital heart disease (CHD) and is closely related to the brain network. However, little is known about the impact of CHD on brain network organization. This study aims to investigate brain structural network properties that may underpin cognitive deficits observed in children with Tetralogy of Fallot (TOF). Methods: In this prospective study, 29 preschool‐aged children diagnosed with TOF and 19 without CHD (non‐CHD) were enrolled. Participants underwent diffusion tensor imaging (DTI) scans alongside cognitive assessment using the Chinese version of the Wechsler Preschool and Primary Scale of Intelligence—fourth edition (WPPSI‐IV). We constructed a brain structural network based on DTI and applied graph analysis methodology to investigate alterations in diverse network topological properties in TOF compared with non‐CHD. Additionally, we explored the correlation between brain network topology and cognitive performance in TOF. Results: Although both TOF and non‐CHD exhibited small‐world characteristics in their brain networks, children with TOF significantly demonstrated increased characteristic path length and decreased clustering coefficient, global efficiency, and local efficiency compared with non‐CHD (p < 0.05). Regionally, reduced nodal betweenness and degree were found in the left cingulate gyrus, and nodal efficiency was decreased in the right precentral gyrus and cingulate gyrus, left inferior frontal gyrus (triangular part), and insula (p < 0.05). Furthermore, a positive correlation was identified between local efficiency and cognitive performance (p < 0.05). Conclusion: This study elucidates a disrupted brain structural network characterized by impaired integration and segregation in preschool TOF, correlating with cognitive performance. These findings indicated that the brain structural network may be a promising imaging biomarker and potential target for neurobehavioral interventions aimed at improving brain development and preventing lasting impairments across the lifetime.

Abstract Reversing the hepatic inflammatory and immunosuppressive microenvironment caused by gut microbiota‐derived lipopolysaccharides (LPS), accumulating to the liver through the gut‐liver axis, is crucial for suppressing hepatocellular carcinoma (HCC) and metastasis. However, synergistically manipulating LPS‐induced inflammation and gut microbiota remains a daunting task. Herein, a Trojan‐horse strategy is proposed using an oral dextran‐carbenoxolone (DEX‐CBX) conjugate, which combines prebiotic and glycyrrhetinic acid (GA) homologs, to targeted delivery GA to HCC through the gut‐liver axis for simultaneous modulation of hepatic inflammation and gut microbiota. In the orthotopic HCC model, a 95–45% reduction in the relative abundances of LPS‐associated microbiota is observed, especially Helicobacter, caused by DEX‐CBX treatment over phosphate‐buffered saline (PBS) treatment. Notably, a dramatic increase (37‐fold over PBS) in the abundance of Akkermansia, which is known to strengthen systemic immune response, is detected. Furthermore, DEX‐CBX significantly increased natural killer T cells (5.7‐fold) and CD8+ T cells (3.9‐fold) as well as decreased M2 macrophages (59% reduction) over PBS treatment, resulting in a tumor suppression rate of 85.4%. DEX‐CBX is anticipated to offer a novel strategy to precisely modulate hepatic inflammation and the gut microbiota to address both the symptoms and root causes of LPS‐induced immunosuppression in HCC.

The livestock industry has long been a hotspot environment for antibiotic resistance genes, with smallholder farming still holding a significant position in pig farming. However, the microbial antibiotic resistance and pathogen risks in pigs under the smallholder farming model remain unclear. We systematically analyzed the antibiotic resistance and microbial composition of pig feces from smallholder and large-scale farming models in Sichuan. The results indicated a lower abundance of antibiotic resistance genes (ARGs) and similar microbial composition in smallholder farming compared to large-scale farming. Beneficial bacteria were more abundant in small-scale farming, whereas large-scale farming exhibited more ARGs, virulence genes, and human pathogenic bacteria (HPBs), including ESBL Escherichia coli strains closely related to human strains, indicating higher zoonotic risk. The findings suggest that smallholder farming presents a relatively better microbial composition and resistance profile, highlighting its advantages over large-scale farming in terms of pig and human health. It is noteworthy that a considerable proportion of HPBs carrying ARGs still exist in the feces from smallholder farming, and given the openness of fecal handling, there remains a high risk of transmitting ARGs and pathogens to humans.