Search Results (332)

The rapid adoption of electric vehicles (EVs) has driven a strong need for optimizing locations of electric vehicle charging stations (EVCSs). Previous methods for locating EVCSs rely on statistical and optimization models, but these methods have limitations in capturing complex nonlinear relationships and spatial dependencies among factors influencing EVCS locations. To address this research gap and better understand the spatial impacts of urban activities on EVCS placement, this study presents a spatially aware machine learning (SAML) method that combines a multi-layer perceptron (MLP) model with a spatial loss function to optimize EVCS sites. Additionally, the method uses the Shapley additive explanation (SHAP) technique to investigate nonlinear relationships embedded in EVCS placement. Using the city of Wuhan as a case study, the SAML method reveals that parking site (PS), road density (RD), population density (PD), and commercial residential (CR) areas are key factors in determining optimal EVCS sites. The SAML model classifies these grid cells into no EVCS demand (0 EVCS), low EVCS demand (from 1 to 3 EVCSs), and high EVCS demand (4+ EVCSs) classes. The model performs well in predicting EVCS demand. Findings from ablation tests also indicate that the inclusion of spatial correlations in the model’s loss function significantly enhances the model’s performance. Additionally, results from case studies validate that the model is effective in predicting EVCSs in other metropolitan cities. Full article

Purpose: The identification of cardiovascular risk factors in metastatic prostate cancer (PCa) patients prior to the initiation of androgen receptor pathway inhibitors (ARPIs) is important yet challenging. Methods and Results: A nationwide cohort study was conducted utilizing data from the National Health Insurance Research Database containing the Taiwan Cancer Registry. The study population comprised 4739 PCa patients who received abiraterone or enzalutamide between 1 January 2014, and 28 February 2022. The cohort was divided into a training set (n = 3318) and a validation set (n = 1421). Machine learning techniques with random survival forest (RSF) model incorporating 16 variables was developed to predict major adverse cardiovascular events (MACEs). Over a mean follow-up period of 2.1 years, MACEs occurred in 10.9% and 11.3% of the training and validation cohorts, respectively. The RSF model identified five key predictive indicators: age < 65 or ≥75 years, heart failure, stroke, hypertension, and myocardial infarction. The model exhibited robust performance, achieving an area under the curve (AUC) of 85.1% in the training set and demonstrating strong external validity with an AUC of 85.5% in the validation cohort. A positive correlation was observed between the number of risk factors and the incidence of MACEs. Conclusions: This machine learning approach identified five predictors of MACEs in PCa patients receiving ARPIs. These findings highlight the need for comprehensive cardiovascular risk assessment and vigilant monitoring in this patient population. Full article

Ectomycorrhizal symbiosis is a cornerstone of ecosystem health, facilitating nutrient uptake, stress tolerance, and biodiversity maintenance in trees. Optimizing Pinus armandii–Tuber indicum mycorrhizal synthesis enhances the ecological stability of coniferous forests while supporting high-value truffle cultivation. This study conducted a pot experiment to compare the effects of three root nutrient regulations—Aolu 318S (containing N-P₂O₅-K₂O in a ratio of 15-9-11 (w/w%)), Aolu 328S (11-11-18), and Youguduo (19-19-19)—on the mycorrhizal synthesis of P. armandii–T. indicum. The results showed that root nutrient supplementation significantly improved the seedling crown, plant height, ground diameter, biomass dry weight, and mycorrhizal infection rate of both the control and mycorrhizal seedlings, with the slow-release fertilizers Aolu 318S and 328S outperforming the quick-release fertilizer Youguduo. The suitable substrate composition in this experiment was as follows: pH 6.53–6.86, organic matter content 43.25–43.49 g/kg, alkali-hydrolyzable nitrogen 89.25–90.3 mg/kg, available phosphorus 83.69–87.32 mg/kg, available potassium 361.5–364.65 mg/kg, exchangeable magnesium 1.17–1.57 mg/kg, and available iron 33.06–37.3 mg/kg. It is recommended to mix the Aolu 318S and 328S solid fertilizers evenly into the substrate, with a recommended dosage of 2 g per plant. These results shed light on the pivotal role of a precise N-P-K ratio regulation in fostering sustainable ectomycorrhizal symbiosis, offering a novel paradigm for integrating nutrient management with mycorrhizal biotechnology to enhance forest restoration efficiency in arid ecosystems. Full article

Background: Esophageal squamous cell carcinoma (ESCC) is a fatal malignant tumor. Several studies have demonstrated that immune checkpoint inhibitors can provide clinical benefits to patients with ESCC. However, the single-agent efficacy of these agents remains limited. Although combination therapies (e.g., radiotherapy, chemotherapy) can help to overcome immunotherapy resistance in ESCC, their severe side effects limit clinical application. This study aimed to explore new resistance mechanisms to immunotherapy in ESCC and identify novel molecular targets to overcome immunotherapy resistance. Methods: We employed immunohistochemistry staining to examine the p-FGFR1^Y654 in tumor samples obtained from 103 patients with ESCC, in addition to evaluating CD8+ T cell infiltration. In vitro expression, western blotting, CCK-8, 5-bromo-2′-deoxyuridine incorporation assays, and migration assays were used to confirm the impact of AZD4547 on p-FGFR1^Y654 expression and the proliferation and migration in ESCC cell lines. Through RNA sequencing analysis, databases such as the Cancer Genome Atlas (TCGA) and Gene Set Cancer Analysis (GSCA), and the reconstruction of transgenic mice using the humanized immune system, we validated the correlation between the expression of p-FGFR1^Y654 and CD8+ T cell infiltration. We also explored how p-FGFR1^Y654 recruits myeloid-derived suppressor cells (MDSCs) through the CXCL8–CXCR2 axis to suppress the therapeutic efficacy of immunotherapy in ESCC. Finally, the tumor-suppressive effects of AZD4547 combined with immunotherapy were confirmed in vivo in tumor-bearing mice with a humanized immune system. Results: We found that the inhibition of p-FGFR1^Y654 expression in ESCC can enhance CD8+ T cell infiltration by suppressing the CXCL8-–XCR2 recruitment of MDSCs. AZD4547, combined with immunotherapy, further promotes immunotherapeutic efficacy in ESCC. Conclusions: In conclusion, our study presents a promising model for combination therapy in ESCC immunotherapy. Full article

Monkeypox virus (Mpox) has recently drawn global attention due to outbreaks beyond its traditional endemic regions. Understanding the immune response to Mpox infection is essential for improving disease management and guiding vaccine development. In this study, we used several machine learning algorithms to analyze time series gene expression data from macaques infected with Mpox, aiming to uncover key immune-related genes involved in different stages of infection. The dataset covered early infection, late infection, and rechallenge phases. We applied nine feature ranking methods to analyze the feature importance, obtaining nine feature lists. Then, the incremental feature selection method was applied to each list to extract key genes and build efficient prediction models and classification rules for each list. This procedure employed twelve classification algorithms and the Synthetic Minority Oversampling Technique. Key genes—such as CD19, MS4A1, and TLR10—were repeatedly identified from multiple feature lists, and are known to play vital roles in B-cell activation, antibody production, and innate immunity. Furthermore, we identified several novel key genes (HS3ST1, SPAG16, and MTARC2) that have not been reported previously. These findings offer valuable insights into the host immune response and highlight potential molecular targets for monitoring and intervention in Mpox infections. Full article

This paper introduces a novel approach to hand motion gesture recognition by integrating the Fourier transform with hypergraph convolutional networks (HGCNs). Traditional recognition methods often struggle to capture the complex spatiotemporal dynamics of hand gestures. HGCNs, which are capable of modeling intricate relationships among joints, are enhanced by Fourier transform to analyze gesture features in the frequency domain. A hypergraph is constructed to represent the interdependencies among hand joints, allowing for dynamic adjustments based on joint movements. Hypergraph convolution is applied to update node features, while the Fourier transform facilitates frequency-domain analysis. The T-Module, a multiscale temporal convolution module, aggregates features from multiple frames to capture gesture dynamics across different time scales. Experiments on the dynamic hypergraph (DHG14/28) and shape retrieval contest (SHREC’17) datasets demonstrate the effectiveness of the proposed method, achieving accuracies of 96.4% and 97.6%, respectively, and outperforming traditional gesture recognition algorithms. Ablation studies further validate the contributions of each component in enhancing recognition performance. Full article

Vaccination with ChAdOx1 nCoV-19 is an important countermeasure to fight the COVID-19 pandemic. This vaccine enhances human immunoprotection against SARS-CoV-2 by inducing an immune response against the SARS-CoV-2 S protein. However, the immune-related genes induced by vaccination remain to be identified. This study employs feature ranking algorithms, an incremental feature selection method, and classification algorithms to analyze transcriptomic data from an experimental group vaccinated with the ChAdOx1 nCoV-19 vaccine and a control group vaccinated with the MenACWY meningococcal vaccine. According to different time points, vaccination status, and SARS-CoV-2 infection status, the transcriptomic data was divided into five groups, including a pre-vaccination group, ChAdOx1-onset group, MenACWY-onset group, ChAdOx1-7D group, and MenACWY-7D group. Each group contained samples with 13,383 RNA features and 1662 small RNA features. The results identified key genes that could indicate the efficacy of the ChAdOx1 nCoV-19 vaccine, and a classifier was developed to classify samples into the above groups. Additionally, effective classification rules were established to distinguish between different vaccination statuses. It was found that subjects vaccinated with ChAdOx1 nCoV-19 vaccine and infected with SARS-CoV-2 were characterized by up-regulation of HIST1H3G expression and down-regulation of CASP10 expression. In addition, IGHG1, FOXM1, and CASP10 genes were strongly associated with ChAdOx1 nCoV-19 vaccine efficacy. Compared with previous omics-driven studies, the machine learning algorithms used in this study were able to analyze transcriptome data faster and more comprehensively to identify potential markers associated with vaccine effect and investigate ChAdOx1 nCoV-19 vaccine-induced gene expression changes. These observations contribute to an understanding of the immune protection and inflammatory responses induced by the ChAdOx1 nCoV-19 vaccine during symptomatic episodes and provide a rationale for improving vaccine efficacy. Full article

The implementation of lean drilling and completion design techniques is a pivotal strategy for the petroleum and natural gas industry to achieve green, low-carbon, and intelligent transformation and innovation. These techniques significantly enhance oil and gas recovery rates. In shale gas development, the shale brittleness index plays a crucial role in evaluating fracturing ability during hydraulic fracturing. Indoor experiments on Gulong shale oil were conducted under a confining pressure of 30 MPa. Based on Rickman’s brittleness evaluation method, this study performed numerical simulations of triaxial compression tests on shale using the finite discrete element method. The fractal dimensions of the fractures formed during shale fragmentation were calculated using the box-counting method. Utilizing the obtained data, a multiple linear regression equation was established with elastic modulus and Poisson’s ratio as the primary variables, and the coefficients were normalized to propose a new brittleness evaluation method. The research findings indicate that the finite discrete element method can effectively simulate the rock fragmentation process, and the established multiple linear regression equation demonstrates high reliability. The weights reassigned for brittleness evaluation based on Rickman’s method are as follows: the coefficient for elastic modulus is 0.43, and the coefficient for Poisson’s ratio is 0.57. Furthermore, the new brittleness evaluation method exhibits a stronger correlation with the brittleness mineral index. The fractal characteristics of crack networks and the relationship between symmetry response and mechanical parameters offer a new theoretical foundation for brittle weight distribution. Additionally, the scale symmetry characteristics inherent in fractal dimensions can serve as a significant indicator for assessing complex crack morphology. Full article

This study investigated the effect of wearable ultrasound-imaging-based visual feedback (UVF) on assisting paretic ankle dorsiflexion training of chronic stroke survivors. Thirty-three participants with unilateral hemiplegia performed maximal isometric contractions on an isokinetic dynamometer in randomized conditions with and without UVF that provided by a wearable ultrasound imaging system. Torque parameters (mean, peak, percentage of maximal voluntary contraction) and tibialis anterior muscle thickness were analyzed across different contraction phases. Statistical comparisons were conducted using paired t-tests or Wilcoxon tests. Correlation analyses were performed using Pearson’s or Spearman’s tests. Results demonstrated that UVF significantly improved torque output, as evidence by the increased percentage of maximal voluntary contraction (%MVC) during entire contractions (p = 0.007), increased mean (p ≤ 0.022) and peak (p ≤ 0.044) torque and the %MVC (p ≤ 0.004) during mid and end phases, and larger muscle thickness during mid contraction (p = 0.045). Moderate correlations were found between torque and muscle thickness (r ≥ 0.30, p ≤ 0.049). These findings preliminarily supported the positive outcomes of real-time wearable UVFs in enhancing paretic ankle dorsiflexion strength and force control during isometric contractions in chronic stroke survivors. While the developed and validated new training protocol may potentially serve as a practical adjunct to existing rehabilitation approaches, further investigations emphasizing the functional outcomes and clinical translations are still needed to verify the clinical utility. Full article

Background: Only a few studies have reported on chlorinated paraffin (CP) levels, especially long-chain chlorinated paraffins (LCCPs), in submicron particulate matter (PM₁) in the outdoor air around primary and secondary schools. Methods: This study examined concentrations of short-chain CPs (SCCPs), medium-chain CPs (MCCPs), and LCCPs in PM₁ samples from 96 schools across six cities in China’s Pearl River Delta region during the winter (October to December 2018). Results: The median total CP concentration was 34 ng/m³, with median values for SCCP, MCCP, and LCCP of 17.3, 15, and 0.7 ng/m³, respectively. The primary congeners were C₁₃Cl_6–8 for SCCPs, C₁₄Cl_6–9 for MCCPs, and C₁₈Cl_7–10 for LCCPs. The SCCPs and MCCPs largely originated from fugitive dust, whereas the LCCPs were mainly sourced from organic chemical industries. Air masses from the South China Sea contributed most to SCCP and MCCP levels, while those from the east coast accounted for the highest LCCP levels. The concentrations of CP in PM₁ were significantly positively correlated with PM₁ levels. Conclusions: The exposure risk assessments by age indicated a very low current health risk from PM₁-related CP inhalation, although prolonged pollution could raise these risks as CP concentrations in ambient PM may continue to increase. Full article

Long-range intercellular communication is essential for multicellular biological systems to regulate multiscale cell–cell interactions and maintain life. Growing evidence suggests that intercellular calcium waves (ICWs) act as a class of long-range signals that influence a broad spectrum of cellular functions and behaviors. Importantly, mechanical signals, ranging from single-molecule-scale to tissue-scale in vivo, can initiate and modulate ICWs in addition to relatively well-appreciated biochemical and bioelectrical signals. Despite these recent conceptual and experimental advances, the full nature of underpinning mechanotransduction mechanisms by which cells convert mechanical signals into ICW dynamics remains poorly understood. This review provides a systematic analysis of quantitative ICW dynamics around three main stages: initiation, propagation, and regeneration/relay. We highlight the landscape of upstream molecules and organelles that sense and respond to mechanical stimuli, including mechanosensitive membrane proteins and cytoskeletal machinery. We clarify the roles of downstream molecular networks that mediate signal release, spread, and amplification, including adenosine triphosphate (ATP) release, purinergic receptor activation, and gap junction (GJ) communication. Furthermore, we discuss the broad pathophysiological implications of ICWs, covering pathophysiological processes such as cancer metastasis, tissue repair, and developmental patterning. Finally, we summarize recent advances in optical imaging and artificial intelligence (AI)/machine learning (ML) technologies that reveal the precise spatial-temporal-functional dynamics of ICWs and ATP waves. By synthesizing these insights, we offer a comprehensive framework of ICW mechanobiology and propose new directions for mechano-therapeutic strategies in disease diagnosis, cancer immunotherapies, and drug discovery. Full article

Pneumatic soft manipulators are one of the current development trends in the field of manipulators. The soft manipulator that has been developed at present still has problems with single function and poor load-bearing capacity. This paper designs a composite soft finger inspired by the human middle finger, featuring a dual-chamber pneumatic drive and embedded steel sheet structure. Utilizing the principles of moment equilibrium and virtual work, a theoretical model for the bending behavior of the soft finger is developed, and the correlation between the bending angle and driving air pressure is derived. The determination process of key parameters and their influence on bending deformation are explained in detail through simulation. The bending experiment confirmed the reliability of the theoretical model. The fingertip force test indicates that the composite finger exerts a greater force than the ordinary one, with the extra force equivalent to 42.57% of the composite finger’s own fingertip force. Subsequent tests on the soft robotic hand measured the hooking quality, gripping diameter, and gripping force. The hooking experiment confirmed that composite fingers have a stronger load-bearing capacity than ordinary fingers, with an extra capacity equivalent to 31.25% of the composite finger’s own load-bearing capacity. Finally, the grasping experiment demonstrates that the soft manipulator can grasp objects of varying shapes and weights, indicating its strong adaptability and promising applications. Full article

It is reported that AML with RUNX1 mutations is associated with poorer response to conventional chemotherapy, lower rates of complete remission (CR), leukemia-free survival (LFS), and overall survival (OS). We aimed to evaluate the prognostic impact of RUNX1 mutations following allogeneic hematopoietic stem cell transplantation (allo-HSCT) by comparing clinical outcomes in AML patients with and without RUNX1 mutations. We retrospectively analyzed 91 AML patients (33 RUNX1+ and 58 RUNX1−) who received their first HSCT at Peking University People’s Hospital. The median age of the cohort was 38 years (range: 6–64), with 73 patients (80%) receiving Haploidentical HSCT and 18 patients (20%) receiving sibling-matched allo-HSCT. In univariate analyses, no significant differences in survival outcomes were observed. For the RUNX1-mutation group and RUNX1-wild-type group, the 2-year cumulative incidence of relapse (CIR) was (12.6% vs. 7.6%, p = 0.472), the 2-year non-relapse mortality (NRM) rate was (9.6% vs. 7.2%, p = 0.747), the 2-year LFS was (77.8% vs. 85.2%, p = 0.426), and the 2-year OS rate was (85.9% vs. 92.7%, p = 0.397). We did not observe any negative impact of RUNX1 mutations on clinical outcomes, suggesting that allo-HSCT (especially Haplo-HSCT) may mitigate the adverse prognostic influence of RUNX1 mutations in AML. Full article

Sugarcane (Saccharum officinarum L.) faces significant challenges in China, including labor-intensive cultivation, low yields, and environmental stresses. Enhancing root development and stress tolerance through phytohormones and molecular breeding is a promising approach to boosting productivity. Indole-3-butyric acid is a phytohormone known for promoting root development and stress resistance. However, its effects on sugarcane root development under low temperature remain poorly understood. This study demonstrated that IBA markedly promoted root initiation, elongation, and biomass under low temperature, and significantly increased the levels of phytohormones, including GA₃, ABA, JA, IAA, and ZT, suggesting the activation of multiple signaling pathways. Transcriptome analysis revealed numerous differentially expressed genes related to metabolic pathways such as glycolysis, the tricarboxylic acid cycle, and glutathione metabolism. Weighted gene co-expression network analysis identified core gene modules correlated with phytohormone activities, highlighting their role in the IBA-mediated stress response. Eleven core genes, including GSTU6, FAR1, and BCAT3, and nine hub genes, such as Ub-CEP52-1 and ACS1, were identified as critical components for IBA-induced root development and stress mitigation. These findings provide insights into the molecular mechanisms underlying IBA-induced root development and stress tolerance in sugarcane, offering candidate genes for breeding high-yield, stress-tolerant varieties and demonstrating IBA’s potential as a strategy to enhance productivity under challenging conditions. Full article

Urban waterfront streets are important mediators that reflect a city’s image and characteristics. They play a positive role in enhancing residents’ cohesion, mental and physical health, and social interactions. Human perceptions represent individuals’ psychological experiences and feelings toward the surrounding environment. Previous studies have explored the impact of urban street-built environmental factors on perceptions; however, research focusing on waterfront street environments and their impacts on human perceptions remains limited. Therefore, exploring the specific impact of waterfront street environmental characteristics on different dimensions of human perception is essential for guiding the development of livable cities. Based on Street View images (SVIs), this study applied artificial neural networks and machine learning semantic segmentation techniques to obtain physical feature data and human perception data of the Murasaki River waterfront line spaces in Kitakyushu, Japan. In addition, correlation and regression analyses were conducted to explore the specific impact of physical features on different dimensions of human perception in waterfront line spaces, and corresponding optimization strategies were proposed. The results show that street greenness significantly enhances perceptions of safety, wealth, and beauty, while effectively reducing boredom and depression. Furthermore, the building visual ratio contributes to increased street vitality. On the other hand, physical features such as openness, spatial indicators, and environmental color diversity have negative effects on positive perceptions, including safety and vitality. In particular, openness significantly increases boredom and depression. This study advances the exploration of urban waterfront street environments from the perspective of human perception, providing a theoretical foundation for improving the spatial quality of waterfront streets and offering references for human-centered urban planning and construction. Full article