Search

Abstract Background Attention-deficit/hyperactivity disorder (ADHD) is a prevalent mental disorder characterized by hyperactivity, impulsivity, and inattention. This study aims to develop a verifiable and interpretable machine learning model to identify ADHD and its subtypes in children using clinical assessment scales data. Methods This study utilized the ADHD-200 dataset, including demographic data, Behavioral Rating Scale, and Wechsler Intelligence Scale assessments, to train and validate our models. The model’s performance was evaluated using 10-fold cross-validation within the internal dataset, and the best model will be used for external validation. Seven machine learning models were evaluated. The SHapley Additive exPlanations (SHAP) method was employed for model interpretation. Finally, a web application will deploy the prediction model to provide ADHD probabilities based on user input. Results The Random Forest (RF) model performing best in identifying ADHD and the Support Vector Machine (SVM) model excelling in distinguishing ADHD subtypes. The RF model achieved an AUC of 0.99 in 10-fold cross-validation and an AUC of 0.99 in external validation, and the SVM model achieved a micro-average AUC of 0.96 and an accuracy of 0.83 in internal validation and a micro-average AUC of 0.96 and an accuracy of 0.85 in external validation. We used SHAP to interpret the models, revealing that higher ADHD Index pushed the model towards ADHD classification. Additionally, lower IQ scores were correlated with a higher likelihood of ADHD, consistent with previous studies. The dependency analysis found that the model can identify different behavioral scales. We deployed the final model online using a web application and showed users how the model made decisions. Conclusions Our findings highlight the potential of using machine learning and clinical assessment scales to support the diagnosis and subtype identification of ADHD in children, offering a practical solution for improving diagnostic accuracy and efficiency in clinical settings.

Abstract Background Rheumatoid arthritis (RA) is a common chronic, inflammatory autoimmune disease, and early clinical diagnosis is crucial for its treatment. CXCR4 expression was characterized in arthritic mouse models and joints of RA patients, and [18 F]AIF-NOTA-QHA-04 specificity was assessed in non-malignant cells with elevated CXCR4 expression. This study explored the application of CXCR4-targeted PET probe [18 F]AIF-NOTA-QHA-04 in monitoring disease activity and therapeutic efficacy in RA. To this aim, the metabolic characteristics of [18 F]AIF-NOTA-QHA-04 and correlation of [18 F]AIF-NOTA-QHA-04 uptake with arthritis severity were evaluated by PET imaging in arthritic mice. [18 F]AIF-NOTA-QHA-04 potential in evaluating therapeutic efficacy was further investigated in arthritic mice following methotrexate (MTX) and etanercept (ETC) treatment. Results CXCR4 expression was significantly increased in the inflamed joints of collagen-induced arthritis (CIA) and collagen-antibody induced arthritic (CAIA) mice, and in synovial tissues of RA patients. [18 F]AIF-NOTA-QHA-04 showed high specificity for CXCR4, with increased probe uptake in arthritic joints that was strongly correlated with arthritis severity scores. PET imaging revealed that increased uptake of [18 F]AIF-NOTA-QHA-04 in arthritic joints paralleled disease activity, with uptake decreasing upon remission. Furthermore, [18 F]AIF-NOTA-QHA-04 PET imaging provided earlier and more sensitive assessments of the efficacy of MTX and ETC compared to traditional methods. Conclusion The CXCR4-targeted PET probe [18 F]AIF-NOTA-QHA-04 is a promising tool for RA diagnosis and monitoring, with high specificity and sensitivity. The potential of this probe as a biomarker for disease activity and therapeutic response underscores its value in personalized medication strategies for the management of RA.

Abstract Background Clinical practice guidelines (CPGs) are intended to offer appropriate recommendations for clinical practice based on the available evidence while acknowledging existing gaps and uncertainties. The quality of CPGs for gastric precancerous lesions (GPL), distribution of evidence quality, and strength of recommendations are unknown. Objective Systematically evaluate the quality of CPGs for GPL and identify areas for improvement in the development process. Methods PubMed, Embase, Cochrane Library, Cumulative Index to Nursing and Allied Health Literature, and six online CPG repositories were systematically searched for CPGs related to GPL. Three researchers independently assessed the methodological quality of the included CPGs by using the AGREE II tool. The reporting and recommendation quality of the CPGs were evaluated using the RIGHT and AGREE-REX tools through consensus. Evidence-based CPGs were analyzed using the Grading of Recommendation Assessment, Development, and Evaluation system to determine the distribution of quality of evidence and strength of recommendations. Results A total of 4046 records were identified; nine CPGs met the eligibility criteria for this study. The mean overall score for the methodological quality of the CPGs was 46.22%. Among the six domains, the mean score for clarity of presentation was the highest (71.67%), while the mean score for applicability was the lowest (24.56%). Among the nine CPGs, only one was considered high quality. Regarding reporting quality, domains 1, 3, and 4 had mean reporting rates equal to or higher than 60%. The mean overall score for the recommendation quality was 19.11%. In total, 235 recommendations were identified through the screening process, of which 64.4% were classified as strong. However, only 17.5% of the strong recommendations were supported by high-quality evidence. Conclusion The overall quality of CPGs for GPL was poor, with uneven quality across domains. In addition, the consistency between the strength of recommendations and the quality of evidence was poor.

Abstract Previous deep learning-based brain network research has made significant progress in understanding the pathophysiology of schizophrenia. However, it ignores the three-dimensional spatial characteristics of EEG signals and cannot dynamically learn the interactions between nodes. To address this issue, a schizophrenia classification model based on a three-dimensional adaptive graph convolutional neural network (3D-AGCN) is proposed. Each subject’s EEG data is divided into various segment lengths and frequency bands for the experiment. The attention mechanism is then used to integrate the node features in the spatial, feature, and frequency band dimensions. The resulting adaptive brain functional network features are then constructed and fed into the GAT + GCN model. This adaptive approach eliminates the human-specified criteria for feature selection and brain network construction. The trial results demonstrated that, when using a 6-second segment length and time-domain and frequency-domain features, patients with first-episode schizophrenia achieved the highest classification accuracy of 87.64% This method outperforms other feature selection and brain network modeling approaches, providing new insights and directions for the early diagnosis and recognition of schizophrenia.

Abstract Ultralow-absorption laser films have critical applications in high-power continuous-laser and gravitational-wave-detection systems. During film deposition, the ionic oxygen concentration significantly affects the absorption loss of the film. In this study, Ta2O5 monolayers were deposited using an ion-assisted electron beam evaporation technique, and the weak absorption at 1064 nm, temperature rise, optical band gap, element content, and binding energy were tested and analyzed. The band structure and microdefects of the Ta2O5 films were characterized, and their correlation with the absorption properties was established. The analyses revealed that the primary mechanism responsible for reducing the absorption loss in Ta2O5 films was an appropriate ionic oxygen concentration, which improved the optical band gap and stoichiometric ratio and reduced oxygen vacancy defects. For Ta2O5 monolayers deposited with the optimal ionic oxygen concentration, the weak absorption was approximately 7.2 ppm and the temperature rise was approximately 0.6 °C, 1/4 and 1/3 of the values of those deposited with an excessive concentration, respectively—an important finding in the preparation of ultralow-absorption laser films.

Abstract Type I-E CRISPR (clustered regularly interspaced short palindromic repeats)–Cas (CRISPR-associated proteins) system is one of the most extensively studied RNA-guided adaptive immune systems in prokaryotes, providing defense against foreign genetic elements. Unlike the previously characterized Cas3 nuclease, which exhibits progressive DNA cleavage in the typical type I-E system, a recently identified HNH-comprising Cascade system enables precise DNA cleavage. Here, we present several near-atomic cryo-electron microscopy (cryo-EM) structures of the Candidatus Cloacimonetes bacterium Cas5-HNH/Cascade complex, both in its DNA-bound and unbound states. Our analysis reveals extensive interactions between the HNH domain and adjacent subunits, including Cas6 and Cas11, with mutations in these key interactions significantly impairing enzymatic activity. Upon DNA binding, the Cas5-HNH/Cascade complex adopts a more compact conformation, with subunits converging toward the center of nuclease, leading to its activation. Notably, we also find that divalent ions such as zinc, cobalt, and nickel down-regulate enzyme activity by destabilizing the Cascade complex. Together, these findings offer structural insights into the assembly and activation of the Cas5-HNH/Cascade complex.

Abstract Epilepsy is one of the common chronic neurological diseases, affecting more than 70 million people worldwide. The brains of people with epilepsy exhibit a pathological and persistent propensity for recurrent seizures. Epilepsy often coexists with cardiovascular disease, cognitive dysfunction, depression, etc., which seriously affects the patient's quality of life. Although our understanding of epilepsy has advanced, the pathophysiological mechanisms leading to epileptogenesis, drug resistance, and associated comorbidities remain largely unknown. The use of newer antiepileptic drugs has increased, but this has not improved overall outcomes. We need to deeply study the pathogenesis of epilepsy and find drugs that can not only prevent the epileptogenesis and interfere with the process of epileptogenesis but also treat epilepsy comorbidities. Sphingosine‐1‐phosphate (S1P) is an important lipid molecule. It not only forms the basis of cell membranes but is also an important bioactive mediator. It can not only act as a second messenger in cells to activate downstream signaling pathways but can also exert biological effects by being secreted outside cells and binding to S1P receptors on the cell membrane. Fingolimod (FTY720) is the first S1P receptor modulator developed and approved for the treatment of multiple sclerosis. More and more studies have proven that the S1P signaling pathway is closely related to epilepsy, drug‐resistant epilepsy, epilepsy comorbidities, or other epilepsy‐causing diseases. However, there is much controversy over the role of certain natural molecules in the pathway and receptor modulators (such as FTY720) in epilepsy. Here, we summarize and analyze the role of the S1P signaling pathway in epilepsy, provide a basis for finding potential therapeutic targets and/or epileptogenic biomarkers, analyze the reasons for these controversies, and put forward our opinions. Plain Language Summary This article combines the latest research literature at home and abroad to review the sphingosine 1‐phosphate signaling pathway and epileptogenesis, drug‐resistant epilepsy, epilepsy comorbidities, other diseases that can cause epilepsy, as well as the sphingosine‐1‐phosphate signaling pathway regulators and epilepsy, with the expectation of providing a certain theoretical basis for finding potential epilepsy treatment targets and/or epileptogenic biomarkers in the sphingosine‐1‐phosphate signaling pathway.

Abstract. Emerging evidence suggests that dysbiosis of the gut microbiota is associated with the pathogenesis of Parkinson’s disease (PD), a prevalent neurodegenerative disorder. The microbiota–gut–brain axis plays a crucial role in the development and progression of PD, and numerous studies have demonstrated the potential therapeutic benefits of modulations in the intestinal microbiota. This review provides insights into the characterization of the gut microbiota in patients with PD and highlights associations with clinical symptoms and underlying mechanisms. The discussion underscores the increased influence of the gut microbiota in the pathogenesis of PD. While the relationship is not fully elucidated, existing research demonstrates a strong correlation between changes in the composition of gut microbiota and disease development, and further investigation is warranted to explain the specific underlying mechanisms.

Hourly global solar radiation data is an important factor for solar energy utilization. Due to the lack of solar radiation observation stations in many areas, some hourly solar radiation models are proposed to predict hourly solar radiation. However, the existing models perform poorly in heavy fog-haze areas because the weakening effect of fog-haze on solar radiation is not considered. Thus, in this paper, hourly global solar radiation prediction models are developed considering air quality index (AQI) using XGBoost algorithm. The results show a general improvement in the accuracy of models with AQI as an additional input (Model B1-B6) compared to models that do not consider AQI (Model A1-A6). Compared to Model A, Model B have an increase in R value from 0.927 to 0.948, a decrease in RMSE value from 0.300 to 0.282 and a decrease in MAPE value from 0.159 to 0.145. In addition, for hourly solar radiation prediction, the six most important inputs are the day of the year, air temperature difference, surface temperature difference, hour, AQI, and total cloud cover.

The ever-increasing demand for data centers and high-performance computing systems necessitate power-efficient, low-latency, and high-density interconnect design. This article reviews and analyzes recent design challenges and advances of optical transceiver, phase-locked loop (PLL), and clock and data recovery (CDR) for data center applications with a distance of ~100 m. At the transmitter side, nonidealities of the widely used vertical-cavity surface-emitting laser (VCSEL) are described, followed by reviews on existing compensation techniques for those nonidealities. At the receiver side, tradeoffs between gain, bandwidth (BW), noise, and linearity in PAM-4 optical receiver design are introduced, and design methods to improve the power efficiency and BW density are particularly discussed. Regarding clock generation which directly affects the performance of the transceiver, compact PLL design techniques focusing on in-band phase noise reduction and low-jitter performance are described. The signal integrity of PAM-4 signal becomes more susceptible to noise and jitter due to reduced signal level spacing. To address the uncorrelated jitter accumulation within the CDR which limits the signal quality and transmission distance, jitter compensation schemes in CDR design are described. And the clock distribution techniques for multilane transceiver systems are discussed.

Abstract Background Toxic heavy metal elements in soils are major global environmental issues and easily migrate to crop grains to cause severe problems in human health, whereas moderately essential elements such as selenium are beneficial for human health. The accumulation of heavy metals and essential elements in rice grains and their genetic mechanisms are still poorly understood. Results We conducted genetic dissection of four toxic heavy metal elements (lead, cadmium, mercury, and chromium), one quasi metallic element (arsenic), and one essential element (selenium) in grains of 290 Xian and 308 Geng rice accessions through a genome-wide association study (GWAS) based on three statistical models and assays of element concentrations from three environments. A total of 99 quantitative trait loci (QTLs) were identified. Among these QTLs, 18.2% overlapped between/among two or more elements, indicating that some QTLs related to the accumulation of certain elements may depend on other heavy metal elements or be involved in the collaborative transport of other elements. Moreover, at least 14 QTLs/regions were identified in the same regions, containing 12 cloned genes reported to be associated with element accumulation or tolerance-related traits, while the remaining 85 were new QTLs. A total of 62 promising candidate genes were identified from 50 major QTLs, of which 25 genes were newly discovered in this study. More importantly, population genetic analysis revealed 26 and 15 intraspecies divergent regions affecting element concentrations in the Xian and Geng subspecies, respectively, including 25 QTLs identified in this study and 13 previously reported and cloned genes. Conclusions Our findings will facilitate further gene cloning and dissection of the genetic mechanisms of element accumulation in rice grains to improve grain quality.

Sandy beaches are the most wide distributed coastal type worldwide, serving as a crucial transitional zone between land and sea. However, accurately mapping the intertidal zone of sandy beaches poses challenges due to water-level fluctuations and limited in-situ measurements in sparsely populated areas. Leveraging free-access Sentinel-2 optical imagery and station-based water-level data in coastal zones, we explored the integration of Sentinel-2 satellite imagery and water-level data to derive the intertidal topography of sandy beaches. Our study conducted in Texas, USA, demonstrates the generation of a detailed Digital Elevation Model (DEM) with an accuracy of 0.42 m. This satellite-derived intertidal topography offers valuable insights for mapping coastal lowlands and estimating coastal slopes of sandy beaches. In the future, our method holds significant potential for global-scale applications in generating intertidal topography, coastal slopes, and lowland areas for sandy beaches. Furthermore, our method can enhance our understanding of these important coastal environments and support decision-making for conservation and management efforts.

Abstract Background Traumatic brain injury (TBI) is characterized by high mortality and disability rates. Disease-associated microglia (DAM) are a newly discovered subtype of microglia. However, their presence and function in the acute phase of TBI remain unclear. Although glycolysis is important for microglial differentiation, its regulatory role in DAM transformation during the acute phase of TBI is still unclear. In this study, we investigated the functions of DAM-like cells in the acute phase of TBI in mice, as well as the relationship between their transformation and glycolysis. Methods In this study, a controlled cortical impact model was used to induce TBI in adult male wild-type (WT) C57BL/6 mice and adult male TREM2 knockout mice. Various techniques were used to assess the role of DAM-like cells in TBI and the effects of glycolysis on DAM-like cells, including RT‒qPCR, immunofluorescence assays, behavioural tests, extracellular acidification rate (ECAR) tests, Western blot analysis, cell magnetic sorting and culture, glucose and lactate assays, and flow cytometry. Results DAM-like cells were observed in the acute phase of TBI in mice, and their transformation depended on TREM2 expression. TREM2 knockout impaired neurological recovery in TBI mice, possibly due in part to their role in clearing debris and secreting VEGFa and BDNF. Moreover, DAM-like cells exhibited significantly increased glycolytic activity. TREM2 regulated the AKT‒mTOR‒HIF-1α pathway and glycolysis in microglia in the acute phase of TBI. The increase in glycolysis in microglia partially contributed to the transformation of DAM-like cells in the acute phase of TBI in mice. Conclusions Taken together, the results of our study demonstrated that DAM-like cells were present in the acute phase of TBI in mice. TREM2 might influence DAM-like cell transformation by modulating the glycolysis of microglia. Our results provide a new possible pathway for intervening TBI.

To enhance the hardness and wear resistance of Q235 substrate, an AlCoCrFeNi high-entropy alloy (HEA) coating was deposited onto the substrate surfaces by laser cladding. However, the performance of the AlCoCrFeNi HEA coating did not meet the desired requirements. Consequently, AlCoCrFeNiTix (x = 0, 0.25, 0.5, 0.75, and 1) HEA coatings were prepared by laser cladding to further improve the coating hardness and wear resistance. The influence of Ti content on the microstructure, hardness, and wear resistance of the coatings was studied. The results showed that Ti promoted the formation of a body-centered cubic (B2) phase, transforming the coating structure into a typical dendritic (DR)–inter-dendritic (ID) structure. The AlCoCrFeNiTi0.25 coating consisted of BCC1 phase and B2 phases. As the Ti content increases, Laves phases emerged in AlCoCrFeNiTix HEA coatings. Spinodal decomposition led to pronounced phase separation in the coating, with elongated nanoparticles of the BCC1 phase precipitating in the DR region and round block-like nanoparticles of the B2 phase precipitating in the ID region. The B2 and Laves phases strengthened the coatings and improved their hardness and wear resistance. The hardness of AlCoCrFeNiTi1 coating reached 828.35 HV0.1, which was 56.29 times higher than that of the AlCoCrFeNi coating, while its wear resistance was 80.7 times greater. Therefore, the addition of Ti effectively improved the hardness and wear resistance of the AlCoCrFeNi HEA coating.

Abstract Skillful seasonal climate prediction is critical for food and water security over the world’s heavily populated regions, such as in continental East Asia. Current models, however, face significant difficulties in predicting the summer mean rainfall anomaly over continental East Asia, and forecasting rainfall spatiotemporal evolution presents an even greater challenge. Here, we benefit from integrating the spatiotemporal evolution of rainfall to identify the most crucial patterns intrinsic to continental East-Asian rainfall anomalies. A physical-statistical prediction model is developed to capture the predictability offered by these patterns through a detection of precursor signals that describe slowly varying lower boundary conditions. The presented model demonstrates a prediction skill of 0.51, at least twice as high as that of the best dynamical models available (0.26), indicating improved prediction for both the spatiotemporal evolution and summer mean of rainfall anomalies. This advance marks a crucial step toward delivering skillful seasonal predictions to populations in need of new tools for managing risks of both near-term climate disasters, such as floods and droughts, and long-term climate change.

Abstract Effective detection is critical for terahertz applications, yet it remains hindered by the unclear mechanisms that necessitate a deeper understanding of photosensitive materials with exotic physical phenomena. Here, we investigate the terahertz detection capabilities of the two-dimensional antiferromagnetic semimetal NbFeTe2. Our study reveals that the interaction between antiferromagnetic magnetic moments and electron spin induces disordered carriers to hop between localized states, resulting in a nonlinear increase in responsivity as temperature decreases. We integrate asymmetric electrodes to generate a sufficient Seebeck potential, enabling carriers to overcome the barrier of localized states and achieve reordering at room temperature. Additionally, the self-powered performance of the NbFeTe₂/graphene heterojunction is optimized by the built-in electric field, achieving peak responsivity of 220 V W-1 and noise equivalent power of

Abstract Background Mining functional gene modules from genomic data is an important step to detect gene members of pathways or other relations such as protein-protein interactions. This work explores the plausibility of detecting functional gene modules by factorizing gene-phenotype association matrix from the phenotype ontology data rather than the conventionally used gene expression data. Recently, the hierarchical structure of phenotype ontologies has not been sufficiently utilized in gene clustering while functionally related genes are consistently associated with phenotypes on the same path in phenotype ontologies. Results This work demonstrates a hierarchical Nonnegative Matrix Factorization (NMF) framework, called Consistent Multi-view Nonnegative Matrix Factorization (CMNMF), which factorizes genome-phenome association matrix at consecutive levels of the hierarchical structure in phenotype ontology to mine functional gene modules. CMNMF constrains the gene clusters from the association matrices at two consecutive levels to be consistent since the genes are annotated with both the child-level phenotypes and the parent-level phenotypes in two levels. CMNMF also restricts the identified gene clusters to be densely connected in the phenotype ontology hierarchy. In the experiments on mining functionally related genes from mouse phenotype ontology and human phenotype ontology, CMNMF effectively improves clustering performance over the baseline methods. Gene ontology enrichment analysis is also conducted to verify its practical effectiveness to reveal meaningful gene modules. Conclusions Utilizing the information in the hierarchical structure of phenotype ontology, CMNMF can identify functional gene modules with more biological significance than conventional methods. CMNMF can also be a better tool for predicting members of gene pathways and protein-protein interactions.

Introduction: The design of precision antimicrobials aims to personalize the treatment of drug-resistant bacterial infections and avoid host microbiota dysbiosis. Objectives: This study aimed to propose an efficient de novo design strategy to obtain specifically targeted antimicrobial peptides (STAMPs) against methicillin-resistant Staphylococcus aureus (MRSA). Methods: We evaluated three strategies designed to increase the selectivity of antimicrobial peptides (AMPs) for MRSA and mainly adopted an advanced hybrid peptide strategy. First, we proposed a traversal design to generate sequences, and constructed machine learning models to predict the anti-S. aureus activity levels of unknown peptides. Subsequently, six peptides were predicted to have high activity, among which, a broad-spectrum AMP (P18) was selected. Finally, the two targeting peptides from phage display libraries or lysostaphin were used to confer specific anti-S. aureus activity to P18. STAMPs were further screened out from hybrid peptides based on their in vitro and in vivo activities. Results: An advanced hybrid peptide strategy can enhance the specific and targeted properties of broad-spectrum AMPs. Among 25 assessed peptides, 10 passed in vitro tests, and two peptides containing one bacterial-entrapping peptide (BEP) and one STAMP passed an in vivo test. The lead STAMP (P18E6) disrupted MRSA cell walls and membranes, eliminated established biofilms, and exhibited desirable biocompatibility, systemic distribution and efficacy, and immunomodulatory activity in vivo. Furthermore, a bacterial-entrapping peptide (BEP, SP5) modified from P18, self-assembled into nanonetworks and rapidly entrapped MRSA. SP5 synergized with P18E6 to enhance antibacterial activity in vitro and reduced systemic MRSA infections. Conclusions: This strategy may aid in the design of STAMPs against drug-resistant strains, and BEPs can serve as powerful STAMP adjuvants.

Objective: This study aimed to evaluate bilateral sensorimotor function in patients with unilateral CAI. Furthermore, sensory reweighting ability and vestibular modulation were assessed. Methods: Twenty individuals with unilateral CAI and twenty healthy controls participated in this study. All participants executed ankle proprioception, plantar sensation, unilateral stance, Y balance, motor control test (MCT) and sensory organisation test (SOT) assessments. Proprioception assessment included joint position sense and force sense (FS), and plantar sensation evaluation consisted of light-touch, vibration and two-point discrimination (TPD) thresholds at the heel, head of the first metatarsal (1 MF), base of the fifth metatarsal (5 MF), centre of foot and forefoot. MCT and SOT tests were conducted using NeuroCom Balance Manager System. Except for SOT, all tests evaluated bilateral limbs, and the order of limbs was randomly selected. 2 (group) × 2 (limb) mixed model analyses of variance were performed for outcome measures of unilateral stance, Y balance and MCT, and independent t-test was used to analyse the outcomes of SOT between two groups. Mann–Whitney U and Wilcoxon test were applied to examine the differences in plantar sensation between groups and limbs. Results: For plantar sensation, increased light-touch threshold at heel and 1 MF and the TPD threshold at 1 MF were observed bilaterally in CAI group (p

Abstract Mesenchymal stem cells (MSCs) have shown a great potential role in treating liver injury. MSCs can promote liver regeneration by differentiating into hepatocytes, and can also secrete exosomes to participate in the repair of liver injury. Increasing evidence has shown that mesenchymal stem cell-derived exosomes (MSC-EXOs) play an important role in treating liver injury. In this review, the biogenesis and function of exosomes and the characteristics of MSC-EXOs were analyzed based on recent research results. MSC-EXOs are significant in liver injuries such as liver fibrosis, liver failure, hepatocellular carcinoma, oxidative stress, and lipid steatosis, and participate in the process of liver regeneration.

Abstract Due to the complex structures of multi-limbed parallel robots, conventional parallel robots generally have limited workspace, complex kinematics, and complex dynamics, which increases the application difficulty of parallel robot in industrial engineering. To solve the above problems, this paper proposes a single-loop Schönflies motion parallel robot with full cycle rotation, the robot can generate Schönflies motion by the most simplified structure. The novel Schönflies motion parallel robot is a two-limb parallel mechanism with least links and joints, and each limb is driven by a 2-degree of freedom (DOF) cylindrical driver (C-driver). The full cycle rotation of the output link is achieved by “…R-H…” structure, where the revolute (R) and helical (H) joints are coaxial. Mobility, kinematics, workspace and singularity analysis of the novel Schönflies motion parallel robot are analyzed. Then, dynamic model is formulated based on the principle of virtual work. Moreover, a pick-and-place task is implemented by the proposed Schönflies motion parallel robot and a serial SCARA robot, respectively. The simulation results verify the correctness of the theoretical model. Furthermore, dynamics performances of the proposed Schönflies motion parallel robot and a serial SCARA robot are compared, which reveal the performance merits of the proposed Schönflies motion parallel robot.

Abstract Studying the evolutionary history of plants in the Qinghai–Tibetan Plateau region provides a theoretical basis for the conservation and use of plant genetic resources. In this study, we analyzed five chloroplast gene fragments to examine the genetic diversity and phylogeography of Prunus mira in 577 individuals from 32 populations. The results indicated that P. mira populations exhibit high genetic diversity and significant phylogeographic structure (N ST > G ST ). High genetic differentiation (F ST = 0.979) and limited gene flow were detected among populations, likely due to geographic isolation. Neutrality tests and mismatch analysis indicated that the P. mira population has not experienced significant expansion during the historical period and remains relatively stable. Additionally, based on haplotype distribution and genetic diversity levels, we propose that P. mira had three refugia during the glacial period. Considering the genetic diversity of P. mira populations, we propose dividing all populations into two conservation units and prioritizing in situ conservation of populations with high genetic diversity within each unit. Furthermore, ex situ conservation of specific populations could prevent the loss of unique genes, such as those in populations with low genetic diversity but distinct haplotypes.

Abstract Background Developmental dysplasia of the hip is a common musculoskeletal disorder in newborns and young children, attracting considerable controversy. The purpose of the present study was to analyze the research trends and hotspots over the past three decades in this field. Methods All related publications were collected from the Web of Science Core Collection from 1994 to 2023. Of these, characteristics of the top 50 cited articles for each decade (1994–2003, 2004–2013 and 2014–2023) were evaluated in detail. Visualized studies were operated via VOSviewer. GraphPad Prism and Microsoft Excel were used to perform statistical analysis. The characteristic of the present study is a cross-sectional study. Results In total, 1,300 publications with 19,815 citations from 1994 to 2023 were selected. The number of publications increased significantly during the past three decades, from 23 in 1994 to 132 in 2023 (P

Abstract In the context of increasing renewable energy penetration and the imperative for efficient utilization, this paper explores the application of maximum power point tracking (MPPT) control for wind turbines. The objective is to optimize wind power generation by maximizing energy capture efficiency while addressing challenges associated with behind‐the‐meter renewables, load flexibility, and encouraging prosumers' participation. This paper proposes an adaptive integral sliding mode MPPT control strategy for wind turbines in the presence of external disturbance and model uncertainties. A new fixed‐time integral sliding mode manifold is constructed, such that the singularity problem can be avoided in the controller design without using any piecewise continuous functions. Then, an adaptive fixed‐time MPPT controller is developed to ensure that the tracking error can converge to a small neighbourhood around zero in fixed time, where the upper bound of the convergence time can be pre‐set based on actual engineering needs by selecting appropriate parameters. By designing update law, no prior knowledge on the upper bound of the lumped uncertainties is required anymore in advance. Stability analysis of the closed‐loop system is conducted using Lyapunov stability theory, and the effectiveness of the proposed strategy is validated through numerical simulations.

Abstract The power generation performance of wind turbines has consistently been a paramount concern for wind power operators, maintainers, and manufacturers, as it directly determines the profitability of wind farms. However, due to the combined influence of complex environmental conditions within wind farms and inherent deficiencies in wind turbine design, significant variations in power generation performance persist among turbines of the same model. This discrepancy can be attributed to two crucial factors: site conditions and operational efficiency. To achieve more precise and systematic diagnostic work on the power generation performance of wind turbines, this paper focuses on three factors: air density, turbulence intensity, and yaw adaptability. Based on this, three evaluation and diagnosis methods are proposed, including a conversion method for air density based on two‐dimensional interpolation, a turbulence correction method based on the zero‐turbulence curve, and a yaw adaptability diagnosis method based on the convergence degree. Finally, the effectiveness of these proposed methods is verified through the analysis of actual wind field data.

Abstract Background The combination of anti‐PD‐1 antibody serplulimab and chemotherapy is considered standard first‐line therapy for advanced esophageal squamous cell carcinoma (ESCC), but few later‐line treatments are available. Here we evaluated the therapeutic efficacy of the recombinant, humanized anti‐EGFR antibody HLX07 when used alone or together with serplulimab and chemotherapy against advanced ESCC. Methods This open‐label, non‐randomized, two‐cohort, phase 2 trial involved patients 18‐75 years old with histologically or cytologically confirmed locally advanced, unresectable, or metastatic ESCC, and an Eastern Cooperative Oncology Group performance status of 0‐1. Patients who had failed first‐line immuno‐chemotherapy or at least two lines of other systemic therapy received HLX07 monotherapy intravenously at a dose of 1,000 mg once every 2 weeks (Q2W). Patients with no prior systemic therapy received HLX07 (1,000 mg, day 1) and serplulimab (200 mg, day 1) intravenously Q2W for up to 2 years, concurrently with cisplatin (50 mg/m2, day 1) for up to 8 cycles and 5‐fluorouracil (1,200 mg/m2, days 1‐2) for up to 12 cycles intravenously Q2W. The primary endpoints were progression‐free survival (PFS) and objective response rate (ORR). Results Overall, 50 patients were enrolled. In the HLX07 monotherapy group, ORR was 15.0% (3/20), and the median PFS was 1.5 months (95% confidence interval [CI], 1.3 to 3.7). The median duration of response was not reached, and the rate of patients showing an objective response lasting at least 6 months was 66.7% (95% CI, 5.4 to 94.5). Two (10.0%, 2/20) patients experienced grade 3‐4 treatment‐related adverse events (TRAEs), including hypomagnesemia, hypocalcemia, and fatigue. No patient experienced grade 5 TRAEs. In the HLX07 combination group, the ORR was 60.0% (18/30), and the median PFS was 7.8 months (95% CI, 3.3 to 9.1). Fourteen (46.7%, 14/30) patients experienced grade 3‐4 TRAEs, and one (3.3%, 1/30) patient died due to serplulimab‐related pneumonitis. Conclusions HLX07 monotherapy and its combination with serplulimab and chemotherapy showed manageable toxicity and promising antitumor activity in patients with recurrent or metastatic ESCC. Randomized controlled trials are warranted to further establish the safety and efficacy of HLX07 against ESCC. Trial registration This trial was registered at Clinicaltrials.gov (NCT05221658).

Abstract Weed recognition is an inevitable problem in smart agriculture, and to realise efficient weed recognition, complex background, insufficient feature information, varying target sizes and overlapping crops and weeds are the main problems to be solved. To address these problems, the authors propose a real‐time semantic segmentation network based on a multi‐branch structure for recognising crops and weeds. First, a new backbone network for capturing feature information between crops and weeds of different sizes is constructed. Second, the authors propose a weight refinement fusion (WRF) module to enhance the feature extraction ability of crops and weeds and reduce the interference caused by the complex background. Finally, a Semantic Guided Fusion is devised to enhance the interaction of information between crops and weeds and reduce the interference caused by overlapping goals. The experimental results demonstrate that the proposed network can balance speed and accuracy. Specifically, the 0.713 Mean IoU (MIoU), 0.802 MIoU, 0.746 MIoU and 0.906 MIoU can be achieved on the sugar beet (BoniRob) dataset, synthetic BoniRob dataset, CWFID dataset and self‐labelled wheat dataset, respectively.

Abstract Light field (LF) depth estimation is a key task with numerous practical applications. However, achieving high‐precision depth estimation in challenging scenarios, such as occlusions and detailed regions (e.g. fine structures and edges), remains a significant challenge. To address this problem, the authors propose a LF depth estimation network based on multi‐region selection and guided optimisation. Firstly, we construct a multi‐region disparity selection module based on angular patch, which selects specific regions for generating angular patch, achieving representative sub‐angular patch by balancing different regions. Secondly, different from traditional guided deformable convolution, the guided optimisation leverages colour prior information to learn the aggregation of sampling points, which enhances the deformable convolution ability by learning deformation parameters and fitting irregular windows. Finally, to achieve high‐precision LF depth estimation, the authors have developed a network architecture based on the proposed multi‐region disparity selection and guided optimisation module. Experiments demonstrate the effectiveness of network on the HCInew dataset, especially in handling occlusions and detailed regions.

Entrepreneurship education helps young people create their first job, typically through either experiential learning or education programs. Our study evaluated the effect of integrating both methods in a single intervention involving 40 people aged 18 to 25.Our research intervention was grounded in the Social Cognitive Theory. We assessed its impact via ANCOVA analyses. We looked for shifts in entrepreneurial self-efficacy (across six subdimensions) and intention of 20 intervention participants compared with an equal number of control participants. The results indicated statistically significant changes in all the measures except initiating investor relationships and building an innovative environment.To the best of the authors' knowledge, this study is the first to examine the effect of delivering entrepreneurial education in non-formal Chinese settings. It also pioneers exploring the impact of education programs and experiential learning in a single intervention. Finally, it assesses this impact over one year, sharply contrasting with the more typical exploring of relationships at a single time point.Our findings contribute to the ongoing discourse on the efficacy of entrepreneurship education programs in China, providing support for offering such programs outside formal education. Our results also emphasize the significance of comprehending the surroundings in which the programs are being delivered and the potential external forces that participants may be exposed to.

Abstract Chronic ischemia in moyamoya disease (MMD) impaired white matter microstructure and neural functional network. However, the coupling between cerebral blood flow (CBF) and functional connectivity and the association between structural and functional network are largely unknown. 38 MMD patients and 20 sex/age-matched healthy controls (HC) were included for T1-weighted imaging, arterial spin labeling imaging, resting-state functional MRI and diffusion tensor imaging. All patients had preoperative and postoperative digital subtraction angiography. Upon constructing the structural connectivity (SC) and functional connectivity (FC) networks, the SC-FC coupling was calculated. After obtaining the graph theoretical parameters, neurovascular coupling represented the spatial correlation between node degree centrality (DC) of functional networks and CBF. The CBF-DC coupling and SC-FC coupling were compared between MMD and HC groups. We further analyzed the correlation between coupling indexes and cognitive scores, as well as postoperative collateral formation. Compared with HC, CBF-DC coupling was decreased in MMD (p = 0.021), especially in the parietal lobe (p = 0.047). SC-FC coupling in MMD decreased in frontal, occipital, and subcortical regions. Cognitive scores were correlated with the CBF-DC coupling in frontal lobes (r = 0.394, p = 0.029) and SC-FC coupling (r = 0.397, p = 0.027). The CBF-DC coupling of patients with good postoperative collateral formation was higher (p = 0.041). Overall, neurovascular decoupling and structure-functional decoupling at the cortical level may be the underlying neuropathological mechanisms of MMD.

Abstract Background Mitochondrial transcription elongation factor (TEFM) is a recently discovered factor involved in mitochondrial DNA replication and transcription. Previous studies have reported that abnormal TEFM expression can disrupt the assembly of mitochondrial respiratory chain and thus mitochondrial function. However, the role of TEFM on Uterine corpus endometrial carcinoma (UCEC) progression remains unclear. The present study aims to investigate the expression of TEFM in tumor tissue of UCEC and the effect of abnormal TEFM expression on malignant phenotype of UCEC cells. Methods The expressions of TEFM were measured in tumor tissues and cell lines of UCEC by immunohistochemistry, Western blotting, and real-time quantitative PCR assays. Besides, the effects of TEFM knockdown or overexpression on UCEC cell growth, metastasis, apoptosis, and autophagy were also determined using EdU, colony formation, flow cytometry, TUNEL, and transmission electron microscopy assays. Xenograft model was used to confirm the role of TEFM on proliferative potential of UECE cells in vivo. Results Our bioinformatics analysis of CPTAC data showed that TEFM is abnormally overexpressed in UCEC and its upregulation was significantly associated with poor survival of patients with UCEC. We found that TEFM upregulation significantly promoted the growth and metastasis of UCEC cells. Mechanically, TEFM upregulation impaired the function of mitochondria, decreased their membrane potential and activated the AKT-NFκB pathway by promoting reactive oxygen species (ROS) production, leading to enhanced intracellular autophagy and thus UCEC growth and metastasis. Conclusion This study demonstrates that TEFM positively regulates autophagy to promote the growth and metastasis of UCEC cells, which provides a potential prognostic biomarker and therapeutic target for the treatment of UCEC. Graphical Abstract

Abstract Purpose Antiangiogenesis therapy has become a hot field in cancer research. Given that tumor blood vessels often express specific markers related to angiogenesis, the study of these heterogeneous molecules in different tumor vessels holds promise for advancing anti-angiogenic therapy. Previously using phage display technology, we identified a targeting peptide named GX1 homing to gastric cancer vessels for the first time. However, GX1 also showed some non-specific binding with normal gastric vessels, which can lead to toxic side effects on normal endothelial cells. Therefore, we urgently need to adopt new screening strategies to avoid non-specific binding to normal vessels and obtain gastric cancer vascular targeting peptides with higher specificity. Methods In this study, we designed a new strategy which combined “positive screening” in vivo and “negative screening” in vitro for the first time. An in vivo positive screening was conducted using tumor bearing nude mice to identify peptides that were specifically enriched within the vasculature of gastric cancer. Concurrently, an in vitro negative screening process was conducted on normal vasculature endothelial cells, including human umbilical vein endothelial cells (HUVECs) and human microvascular endothelial cells (HMVECs), to eliminate peptides binding to normal vasculature. After four rounds of iterative screening, a targeting peptide specifically targeting gastric cancer vasculature was obtained. In addition, an in vitro co-culture model by culturing HUVEC in tumor conditioned medium (Co-HUVEC) was established to investigate the affinity of these peptides. The targeting peptide was labeled with fluorescein isothiocyanate (FITC) for competitive and inhibitory assays. Results Blood vessel density analysis confirmed redundant capillary vessels in the xenografts, indicating that the mouse model was suitable for positive screening. Following four rounds of panning, a significant enrichment for phages specifically binding to gastric cancer vasculature was observed, with minimal binding to normal endothelial cells. The peptide CNTGSPYEC exhibited the highest reproducibility. In vitro immunofluorescence staining confirmed that the peptide CNTGSPYEC could specifically enrich in Co-HUVECs while showing no binding to normal vascular endothelial cells. In vivo immunofluorescence staining revealed that the peptide CNTGSPYEC could only bind to vascular endothelial cells specifically in gastric cancer but show no non-specific binding with normal tissue. Competitive and inhibitory assay also verified the targeting characteristics of the peptide with the fluorescence intensity of 17.13. As the concentration increases, the competitive inhibition rate can be incrementally raised to 93% (p

Abstract Crystal symmetry, which governs the local atomic coordination and bonding environment, is one of the paramount constituents that intrinsically dictate materials’ functionalities. However, engineering crystal symmetry is not straightforward due to the isotropically strong covalent/ionic bonds in crystals. Layered two-dimensional materials offer an ideal platform for crystal engineering because of the ease of interlayer symmetry operations. However, controlling the crystal symmetry remains challenging due to the ease of gliding perpendicular to the Z direction. Herein, we proposed a substrate-guided growth mechanism to atomically fabricate AB′-stacked SnSe2 superlattices, containing alternating SnSe2 slabs with periodic interlayer mirror and gliding symmetry operations, by chemical vapor deposition. Some higher-order phases such as 6 R, 12 R, and 18 C can be accessed, exhibiting modulated nonlinear optical responses suggested by first-principle calculations. Charge transfer from mica substrates stabilizes the high-order SnSe2 phases. Our approach shows a promising strategy for realizing topological phases via stackingtronics.

Abstract Background Diabetes mellitus (DM) is a metabolic disorder with increasing prevalence and poor control rates, leading to adverse events. Prognostic nutritional value (PNI) has been identified as a protective factor in DM, but its role in uncontrolled DM remains unclear. Methods This study based on the representative cohort of National Health and Nutrition Examination Survey from 2005 to 2018. A total of 3,313 participants with uncontrolled DM were included in our analyses. PNI was calculated as 5×lymphocyte count (109/L)+ 10×serum albumin (g/L). The endpoints were DM-related and cardiovascular mortality, which were obtained from National Death Index. Univariable and multivariable cox proportional hazard regression were performed to investigate prognostic value of PNI. Results Among 3,313 patients with uncontrolled DM (mean age of 61.75 ± 12.78 years, 53.4% male), PNI level was negatively associated with inflammatory markers and positively associated with metabolic markers of lipid and protein. During a median follow-up of 77 months, 247 DM-related deaths and 205 cardiovascular deaths occurred. Higher PNI levels independently predicted low DM-related (adjusted Hazard ratio [HR] = 0.872, 95% confidence interval [CI] 0.840–0.906, P

Abstract. Cellular senescence, an irreversible state of cell cycle arrest characterized by phenotypic changes and a specific secretory profile, plays a dual role in liver health and disease. Under physiological conditions, senescence aids organ repair and regeneration, but its accumulation due to aging or pathological stress significantly contributes to chronic liver diseases, including alcoholic liver disease, metabolic dysfunction-associated steatohepatitis, liver fibrosis, and hepatocellular carcinoma. Senescence is identified by a range of cellular and molecular changes, such as morphological alterations, expression of cell cycle inhibitors, senescence-associated β-galactosidase activity, and nuclear membrane changes. The onset of senescence in organ cells can affect the entire organism, primarily through the senescence-associated secretory phenotype, which has autocrine, paracrine, and endocrine effects on tissue microenvironments. The objective of this review is to offer a contemporary overview of the pathophysiological events involving hepatic senescent cells and to elucidate their role in the onset and progression of liver diseases, particularly through mechanisms like telomere shortening, genomic and mitochondrial DNA damage, and inflammation. Additionally, this review discusses the emerging senolytic therapies aimed at targeting senescent cells to delay or mitigate liver disease progression. The therapeutic potential of these interventions, alongside their safety and effectiveness, highlights the need for further research to refine these approaches and address unresolved problems in the field of hepatic cellular senescence.

ABSTRACT Renovascular hypertension (RVH) is a primary cause of secondary hypertension, primarily driven by the activation of the renin–angiotensin–aldosterone system activation. Recently, growing studies suggested accessory renal artery (ARA) might also contribute to RVH. However, the treatment of ARA‐related hypertension and whether to take interventional treatment lack consensus. Herein, we report two cases of ARA‐related hypertension in our hospital. Imaging studies of both patients showed ARA stenosis. One patient had ARA occlusion well‐compensated through tortuous collateral branches, achieving normal blood pressure by medical treatment alone. The other patient had ARA stenosis coexisted with main renal artery stenosis, and revascularization of both arteries led to a significant postoperative reduction in blood pressure. A literature review was conducted to summarize overall treatment strategies for ARA‐related hypertension and clarify the relationship between ARA and hypertension. Recent research supported an association between ARA and hypertension. While medical therapy remains the first‐line treatment for ARA‐related hypertension, interventional procedures should be considered for patients whose blood pressure remains uncontrolled despite conservative management.

Abstract Introduction The study aimed to establish meaningful thresholds at patient and group levels for the European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire CLL‐specific module (EORTC QLQ‐CLL17) domain scores in adults with relapsed or refractory (R/R) chronic lymphocytic leukaemia (CLL). Material and methods Data for the analysis were from the TRANSCEND CLL 004 study (NCT03331198). EORTC QLQ‐CLL17 and selected anchor measures were assessed at baseline and multiple postbaseline visits up to 24 months after treatment initiation. Thresholds for each of the three EORTC QLQ‐CLL17 domains were triangulated based on estimates derived from anchor‐ and distribution‐based analyses, in accordance with published guidance. Results The analysis included 62 patients with 240 observations across visits. Meaningful change thresholds for improvement and deterioration, respectively, at the patient level were determined to be −11/+11 for symptom burden, −16/+16 for physical condition/fatigue and −16/+13 for worries/fears on health and functioning. The meaningful change thresholds for improvement and deterioration at the group level mostly ranged between 0.3 and 0.5 of the standard deviation of baseline domain scores. Conclusions These thresholds, based on EORTC QLQ‐CLL17 domain scores, could help identify patients with meaningful changes in HRQOL and interpret treatment effects in future studies of treatments for adults with R/R CLL.

Abstract Background The frailty index based on laboratory tests (FI‐lab) can identify individuals at increased risk for adverse health outcomes. The association between the FI‐lab and all‐cause mortality in patients with heart failure (HF) in the intensive care unit (ICU) remains unknown. This study aimed to determine the correlation between FI‐lab and all‐cause mortality to evaluate the impact of FI‐lab on the prognosis of critically ill patients with HF. Methods This retrospective observational study utilized data extracted from the Medical Information Mart for Intensive Care IV database. The FI‐lab, which consists of 33 laboratory tests, was constructed. Patients were then grouped into quartiles (Q1–Q4) based on their FI‐lab scores. Kaplan–Meier analysis was used to compare all‐cause mortality among the four groups. A Cox proportional hazard analysis was conducted to examine the association between the FI‐lab score and all‐cause mortality. The incremental predictive value of adding FI‐lab to classical disease severity scores was assessed using Harrell's C statistic, integrated discrimination improvement (IDI) and net reclassification improvement (NRI). Results Among 3021 patients, 838 (27.74%) died within 28 days, and 1400 (46.34%) died within a 360 day follow‐up period. Kaplan–Meier analysis indicated that patients with higher FI‐lab scores had significantly higher risks of all‐cause mortality (log‐rank P

Abstract Background Patients with neuropathic pain (NP) have significantly lower quality of life. Because the pathophysiology of NP is not fully understood, there is a lack of effective treatment for it in clinic. This study set out to investigate the precise mechanism by which pulsed radiofrequency (PRF) alleviated NP. Method The rat models of chronic constriction injury of the sciatic nerve (CCI) were established to simulate the occurrence of NP, following with measuring MWT and TWL to evaluate the pain of the rats. HE staining was utilized to observe the rat spinal cord tissue pathology. The expression of MG53, ATF4 and CHOP was evaluated by qRT-PCR and WB, while the expression of inflammatory factors was measured by ELISA. In addition, immunofluorescence assay was used to detect the expression of MG53 and Iba-1. Result PRF treatment alleviated NP in CCI rats, as well as upregulating the expression of MG53 and inhibiting microglial activation. After MG53 knockdown, the remission of NP by PRF was significantly weakened, but microglial activation and endoplasmic reticulum stress (ERS) exhibited enhancement. Therefore, PRF inhibited microglial activation by upregulating MG53. After injection of ERS inducer in CCI rats, the inhibition effect of overexpressed MG53 on microglial activation and its alleviation effect on NP were reversed. Consequently, MG53 played a role in suppressing microglial activation by mediating the inhibition of ERS. Conclusion PRF attenuated microglial activation by upregulating MG53 to inhibit ERS, resulting in the alleviation of NP in CCI rats.

Abstract Knee osteoarthritis (KOA) is a major cause of disability in the elderly, with its pain primarily driving medical consultations. Despite numerous studies, the role of Vitamin D in managing KOA pain remains inconclusive. This study seeks to explore the association between serum Vitamin D levels and WOMAC pain scores, providing new insights into potential treatment strategies for KOA. Utilizing data from the Osteoarthritis Initiative (OAI) database, we conducted a cross-sectional analysis involving 524 participants. Serum levels of 25-hydroxyvitamin D were measured using liquid chromatography-tandem mass spectrometry. WOMAC pain scores served as the dependent variable. Multivariable linear regression models and restricted cubic splines were employed to assess the relationship between Vitamin D levels and KOA pain, with subgroup analyses stratified by sex. Higher Vitamin D levels were significantly associated with lower WOMAC pain scores in males across all models. For females, no significant associations were observed. The analysis suggests a nonlinear relationship between Vitamin D levels and KOA pain in the general cohort, which becomes non-significant after adjustment for covariates. Our findings indicate that Vitamin D is associated with reduced pain in male patients with KOA, highlighting a potential sex-specific therapeutic approach. The results warrant further investigation through longitudinal studies and randomized controlled trials to substantiate Vitamin D supplementation as a viable treatment for reducing KOA pain in males.

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

Abstract Background Colorectal cancer (CRC) is the third most common cancer worldwide and presents a significant challenge to public health. Metabolic syndrome (MetS) is a condition that is predominantly characterized by abdominal obesity and metabolic abnormalities such as hypertension, hyperglycemia, and hyperlipidemia, and it is one of the critical risk factors for CRC. Traditional anthropometric measures have limitations in accurately assessing the risk associated with abdominal obesity. This study aimed to investigate the association between “A Body Shape Index” (ABSI) and the risk of developing CRC among individuals with MetS utilizing data from the National Health and Nutrition Examination Survey (NHANES). Methods This cross-sectional study conducted a statistical analysis of all adult participants who met the diagnostic criteria for MetS in the NHANES data from 1999 to 2018. The ABSI was calculated to quantify abdominal obesity. ABSI is derived from a formula that incorporates waist circumference (WC), body mass index (BMI), and height, and is calculated as ABSI = WC / (BMI^(2/3) × Height^(1/2)). Multivariate logistic regression modeling was used to examine the independent association between ABSI and CRC incidence. Receiver Operating Characteristic (ROC) curves were employed to analyze the ability of ABSI compared to traditional metrics in identifying CRC risk. Results This study involved 16,018 MetS patients with a mean age of 51.8 years, of whom 50.3% were male and 49.7% were female. Logistic regression adjusted for confounders revealed a significant association between an elevated ABSI and an increased risk of developing CRC (odds ratio (OR): 1.433, 95% confidence interval (CI): 1.116 to 1.841; P = 0.005). ROC analyses confirmed that the predictive accuracy of the ABSI for the risk of developing CRC area under the curve (AUC): (0.668, 95% CI: 0.624 to 0.713) surpassed that of traditional measurement methods. Conclusion Among individuals with MetS, the ABSI is linked to an elevated risk of developing CRC. Compared with traditional anthropometric indices, the ABSI is a superior predictive marker for the risk of developing CRC.

Abstract The eco-industry is an effective path to achieve ecological and economic sustainable development. However, the role played by Rosa roxburghii Tratt (R. roxburghii) industry in karst desertification control still needs to be determined. In this study, we predict the suitability probability and driving variables of R. roxburghii's distribution through a Maximum Entropy model, combining climate, population, vegetation, and soil data, and conducted a sample plot survey in a high-suitability area to explore the role of the R. roxburghii industry in ecological services by using adjacent non-R. roxburghii patches as comparisons. The results showed that South China Karst, with its simultaneous rain and heat climate characteristics, was the most suitable area for the industrialization of R. roxburghii in the world. In South China Karst, the area of no, low, medium, and high suitability zones for R. roxburghii was 4.2 × 105, 6.12 × 105, 4.64 × 105, and 4.42 × 105 km2, respectively, and population distribution was the dominant variable controlling its distribution. The net primary productivity, soil conservation, water conservation, mean species abundance, and aboveground biomass of the R. roxburghii monoculture plot in the high-suitability area were significantly lower than those of adjacent non-R. roxburghii lands and forest patches. Furthermore, the monoculture had higher trade-offs between provision, regulation, and support service. This study found that the monoculture of R. roxburghii industry, dominated by human activities, failed to improve ecological services and exacerbated the trade-offs between services. Therefore, future karst desertification control still needs to follow the agroforestry development path.

Abstract Chimeric antigen receptor (CAR)-T cell therapy has emerged as one of the most rapidly evolving modalities of immunotherapy, with substantial success in the treatment of hematological malignancies and encouraging outcomes in solid tumors. Yet, the efficacy of CAR-T therapy is hindered by challenges such as suboptimal expansion and persistence, adverse events, a scarcity of ideal targets, high immunosuppression, and insufficient infiltration due to the intricate tumor microenvironment, all of which limit its application. The 2024 European Society for Medical Oncology (ESMO) Congress presented novel CAR-T cell therapies for hematologic and solid malignancies, focusing on strategies such as cytokine modulation, innovative targets, allogeneic development, mRNA vaccine synergy, in vivo delivery and conditional activation to surmount these challenges.

The incidence of early-onset colorectal cancer (EOCRC) has increased significantly worldwide. Uncovering biomarkers that are unique to EOCRC is of great importance to facilitate the prevention and detection of this growing cancer subtype. Although efforts have been made in the data curation about CRC, there is no integrated platform that gives access to data specifically related to young CRC patients. Here, we constructed a user-friendly open integrated resource called CRCDB (URL: http://crcdb-hust.com) which contains multi-omics data of 785 EOCRC, 4898 late-onset CRCs (LOCRC), and 1110 normal control samples from tissue, whole blood, platelets, and serum exosomes. CRCDB manages the differential analysis, survival analysis, co-expression analysis, and immune cell infiltration comparison analysis results in different CRC groups. Meta-analysis results were also provided for users for further data interpretation. Using the resource in CRCDB, we identified that genes associated with the metabolic process were less expressed in EOCRC patients, while up regulated genes most associated with the mitosis process might play an important role in the molecular pathogenesis of LOCRC. Survival-related genes were most enriched in oxidoreduction pathways in EOCRC while in immune-related pathways in LOCRC. With all the data gathered and processed, we anticipate that CRCDB could be a practical data mining platform to help explore potential applications of omics data and develop effective prevention and therapeutic strategies for the specific group of CRC patients.

The fibroblast growth factor receptor (FGFR) is a crucial receptor tyrosine kinase involved in essential biological processes, including growth, development, and tissue repair. However, FGFR gene mutations, including amplification, fusion, and mutation, can disrupt epigenetics, transcriptional regulation, and tumor microenvironment interactions, leading to cancer development. Targeting these kinase mutations with small molecule drugs or antibodies has shown clinical benefits. For example, erdafitinib is approved for treating locally advanced or metastatic urothelial cancer patients with FGFR2/FGFR3 mutations, and pemigatinib is approved for treating cholangiocarcinoma with FGFR2 fusion/rearrangement. Effective screening of FGFR variant patients is crucial for the clinical application of FGFR inhibitors. Various detection methods, such as polymerase chain reaction, next-generation sequencing, fluorescence in situ hybridization, and immunohistochemistry, are available, and their selection should be based on diagnostic and treatment decision-making needs. Our developed expert consensus aims to standardize the diagnosis and treatment process for FGFR gene mutations and facilitate the practical application of FGFR inhibitors in clinical practice.

Hypoxia, a prevalent characteristic of solid tumors, substantially impairs the efficacy of cancer treatments. However, there are no feasible clinical approaches for treating hypoxic tumors. Here, we develop metal-phenolic networks (CuGI) utilizing the natural glycolysis inhibitor (epigallocatechin gallate) and the essential metal element in the human body (copper ions), specifically targeting and annihilating hypoxic cancer cells. CuGI redirects the metabolic pathway of hypoxic cancer cells from anaerobic glycolysis to oxidative phosphorylation, thereby enhancing reactive oxygen species production and promoting oligomerization of lipoylated proteins in the tricarboxylic acid cycle. Through targeted induction of oxidative and proteotoxic stresses, CuGI induces apoptosis and cuproptosis specifically in cancer cells under hypoxic conditions while sparing normal cells. Moreover, cancer cell membrane-coated CuGI (CuGI@CM) exhibits enhanced tumor penetration effect and demonstrates commendable biocompatibility, effectively suppressing colorectal tumor growth. Importantly, CuGI@CM, when combined with vascular disruptors or radiotherapy which aggravate tumor hypoxia, synergistically potentiates therapeutic efficacy. Thus, CuGI represents a specific and potent nanotherapeutic capable of selectively eliminating hypoxic tumors, offering promise in combination therapies to address tumor hypoxia.

Many countries adopt carbon trading mechanism as the main policy tool to control carbon emissions. Although carbon trading systems have been established, there are still some ongoing problems such as inconsistent carbon accounting standards, data distortion and inefficient overall process within these systems. We propose an innovative blockchain model that integrates the carbon trading system, initial carbon allowance allocation by regulatory authorities, electricity consumers, and power generation firms into a unified framework. By connecting these components, the model facilitates government regulation, emission reduction by electricity companies, electricity purchasing by consumers, and trading of surplus carbon allowances in the carbon market. The key innovations of our model include the establishment of a standardized carbon accounting system, enhanced data transparency to reduce the risk of data falsification, and a two-stage differential game framework that optimizes social welfare through effective control of total carbon emissions. Our simulations demonstrate that this blockchain system can effectively stabilize carbon emissions at a desirable level, thereby contributing to more efficient pollution control.

This experiment aimed to examine how varying levels of Saccharomyces cerevisiae L3 protease impact protein hydrolysis, lipid oxidation, and the physicochemical traits of dry sausage during fermentation. The study also involved analyzing the quality of dry sausage using gas chromatography-mass spectrometry (GC-MS) and sensory evaluation techniques. The study found that S. cerevisiae L3 protease accelerated pH reduction in dry sausages. Compared with naturally fermented dry sausages, it accelerated the decrease in water content and water activity with increasing protease addition. At the same time, redness values (a*) and shear were significantly higher when protease was added (P

Clinically, infectious bone defects represent a significant threat, leading to osteonecrosis, severely compromising patient prognosis, and prolonging hospital stays. Thus, there is an urgent need to develop a bone graft substitute that combines broad-spectrum antibacterial efficacy and bone-inductive properties, providing an effective treatment option for infectious bone defects. In this study, the precision of digital light processing (DLP) 3D printing technology was utilized to construct a scaffold, incorporating zinc oxide nanoparticles (ZnO-NPs) modified barium titanate (BT) with hydroxyapatite (HA), resulting in a piezoelectric ceramic scaffold designed for the repair of infected bone defects. The results indicated that the addition of ZnO-NPs significantly improved the piezoelectric properties of BT, facilitating a higher HA content within the ceramic scaffold system, which is essential for bone regeneration. In vitro antibacterial assessments highlighted the scaffold's potent antibacterial capabilities. Moreover, combining the synergistic effects of low-intensity pulsed ultrasound (LIPUS) and piezoelectricity, results demonstrated that the scaffold promoted notable osteogenic and angiogenic potential, enhancing bone growth and repair. Furthermore, transcriptomics analysis results suggested that the early growth response-1 (EGR1) gene might be crucial in this process. This study introduces a novel method for constructing piezoelectric ceramic scaffolds exhibiting outstanding osteogenic, angiogenic, and antibacterial properties under the combined influence of LIPUS, offering a promising treatment strategy for infectious bone defects.