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Abstract Metabolic reprogramming, a key mechanism regulating the growth and recurrence of hepatocellular carcinoma (HCC) and cholangiocarcinoma (CCA), still lacks effective clinical strategies for its integration into the precise screening of primary liver cancer. This study utilized ultra-high-performance liquid chromatography with quadrupole time-of-flight mass spectrometry to conduct a comprehensive, non-targeted metabolomics analysis, revealing significant upregulation of lipid metabolites such as phosphatidylcholine and lysophosphatidylcholine in patients with HCC and CCA, particularly within the glycerophospholipid metabolic pathway. Hematoxylin and eosin and immunohistochemical staining demonstrated marked upregulation of phospholipase A2 in tumor tissues, further emphasizing the potential of lipid metabolism as a therapeutic target and its important part in the course of cancer. This work provides a new viewpoint for addressing the clinical challenges associated with HCC and CCA, laying the groundwork for the broad application of early diagnosis and personalized treatment strategies, and ultimately aiming to provide tailored and precise therapeutic options for patients.

Abstract The immunosuppressive residual tumor microenvironment (IRTM) is a key factor in the high recurrence and metastasis rates of hepatocellular carcinoma (HCC) after microwave ablation (MWA). Cholesterol‐rich tumor fragments significantly contribute to IRTM deterioration. This study developed a cholesterol‐targeted catalytic hydrogel, DA‐COD‐OD‐HCS, to enhance the synergy between MWA and immune checkpoint inhibitors (ICIs) for HCC treatment. Cholesterol oxidase (COD), modified with dimethyl maleic anhydride (DA) for release in acidic IRTM, is used to degrade cholesterol. Oxydextran (OD) and hemin‐chitosan (HCS) formed a dual network gel, ensuring long‐term fixation of COD and hemin in the IRTM post‐MWA. In both in vitro and in vivo HCC models, DA‐COD‐OD‐HCS effectively released COD, degraded cholesterol, and induced tumor cell ferroptosis, enhancing the antitumor immune response. Combined with anti‐PD‐L1 immunotherapy, this strategy inhibited primary tumor growth and distant metastases, without side effects on adjacent tissues. This work highlights that cholesterol‐targeting catalytic hydrogels fueled by tumor debris can significantly improve the efficacy of MWA and ICIs, offering a novel therapeutic approach for HCC.

Abstract Purpose of review Atherosclerosis, a highly pathogenic and lethal disease, is difficult to locate accurately via conventional imaging because of its scattered and deep lesions. However, second near-infrared (NIR-II) nanomaterials show great application potential in the tracing of atherosclerotic plaques due to their excellent penetration and angiographic capabilities. Recent findings With the development of nanotechnology, among many nanomaterials available for the visual diagnosis and treatment of cardiovascular diseases, optical nanomaterials provide strong support for various biomedical applications because of their advantages, such as noninvasive, nondestructive and molecular component imaging. Among optical nanomaterials of different wavelengths, NIR-II-range (900 ~ 1700 nm) nanomaterials have been gradually applied in the visual diagnosis and treatment of atherosclerosis and other vascular diseases because of their deep biological tissue penetration and limited background interference. Summary This review explored in detail the prospects and challenges of the biological imaging and clinical application of NIR-II nanomaterials in treating atherosclerosis. Graphical abstract

Abstract Radiation‐induced heart disease (RIHD) is a heterogeneous, delayed, and potentially fatal adverse reaction to radiation that can damage all structures of the heart, including the pericardium, myocardium, coronary arteries, valves, and conduction system, leading to a series of diseases. Acute and chronic disease processes play a role in the development of RIHD, the onset times of which range from months to decades. However, the clinical manifestations of RIHD are usually insidious, overlap with several other diseases, and lack specificity. Cardiovascular imaging is essential for early diagnosis, follow‐up, and outcome assessment in patients with RIHD. This review first describes the pathogenesis and clinical manifestations of RIHD before providing an overview of the practical approaches and research advances in multimodal cardiovascular imaging in patients with RIHD, including echocardiography, cardiac magnetic resonance (CMR) and nuclear medicine, and cardiac computed tomography (CT). Then, the value of new cardiac imaging assessments for the early diagnosis of RIHD is described, particularly with relation to speckle‐tracking echocardiography, extracellular volume fraction assessment as a quantitative CMR technique, CMR myocardial strain assessment, positron emission tomography‐CT myocardial perfusion imaging, CT‐ECV, and CT strain assessment, amongst others. In addition, the advantages and disadvantages of each screening technique are compared with the aim of better guiding the follow‐up and diagnosis of subclinical RIHD and preventing cardiovascular events.

Bond performance served as a crucial foundation for the collaboration between concrete and steel rebar. This study investigated the bond performance between coal gasification slag (CGS) concrete, an environmentally friendly construction material, and steel rebar. The effects of fine aggregate type, steel rebar diameter, and anchorage length on bond performance were examined through bond-slip tests conducted on 16 groups of reinforced concrete specimens with different parameters. By utilizing experimental data, a formula for the bond strength between steel rebar and CGS concrete was derived. Additionally, the BPE bond-slip constitutive model was modified by introducing a correction factor (k) to account for relative protective layer thickness. Findings indicated that substituting 25% of manufactured sand with coal gasification slag did not cause significant adverse effects on concrete strength or bond stress between concrete and steel rebar. The effect of steel rebar diameter on the ultimate bond stress was not obvious, whereas when the steel rebar diameter was fixed; the increase in anchorage length led to uneven distribution of bond stress and eventually reduced the ultimate bond stress. The modified bond-slip constitutive model agreed well with the experimental values and was able to more accurately reflect the bond-slip performance between CGS concrete and steel rebar. This study provided a theoretical basis for the conversion of CGS into a resource and for the application of CGS concrete.

Collaborative filtering is one of the most widely used methods in recommender systems. In recent years, Graph Neural Networks (GNN) were naturally applied to collaborative filtering methods to model users' preference representation. However, empirical research has ignored the effects of different items on user representation, which prevented them from capturing fine-grained users' preferences. Besides, due to the problem of data sparsity in collaborative filtering, most GNN-based models conduct a large number of graph convolution operations in the user-item graph, resulting in an over-smoothing effect. To tackle these problems, Adaptive Preference Retention Graph Convolutional Collaborative Filtering Method (APR-GCCF) was proposed to distinguish the difference among the items and capture the fine-grained users' preferences. Specifically, the graph convolutional method was applied to model the high-order relationship on the user-item graph and an adaptive preference retention mechanism was used to capture the difference between items adaptively. To obtain a unified users' preferences representation and alleviate the over-smoothing effect, we employed a residual preference prediction mechanism to concatenate the representation of users' preferences generated by each layer of the graph neural network. Extensive experiments were conducted based on three real datasets and the experimental results demonstrate the effectiveness of the model.

The development of novel theranostic agents with outstanding diagnostic and therapeutic performances is still strongly desired in the treatment of hepatocellular carcinoma (HCC). Here, a fucoidan-modified mesoporous polydopamine nanoparticle dual-loaded with gadolinium iron and doxorubicin (FMPDA/Gd3+/DOX) was prepared as an effective theranostic agent for magnetic resonance imaging (MRI)-guided chemo-photothermal therapy of HCC. It was found that FMPDA/Gd3+/DOX had a high photothermal conversion efficiency of 33.4% and excellent T1−MRI performance with a longitudinal relaxivity (r1) value of 14.966 mM−1·s − 1. Moreover, the results suggested that FMPDA/Gd3+/DOX could effectively accumulate into the tumor foci by dual-targeting the tumor-infiltrated platelets and HCC cells, which resulted from the specific interaction between fucoidan and overexpressed p-selectin receptors. The excellent tumor-homing ability and MRI-guided chemo-photothermal therapy therefore endowed FMPDA/Gd3+/DOX with a strongest ability to inhibit tumor growth than the respective single treatment modality. Overall, our study demonstrated that FMPDA/Gd3+/DOX could be applied as a potential nanoplatform for safe and effective cancer theranostics

ObjectivesTo develop and validate a CT-based radiomics nomogram that can provide individualized pretreatment prediction of the response to platinum treatment in small cell lung cancer (SCLC).MaterialsA total of 134 SCLC patients who were treated with platinum as a first-line therapy were eligible for this study, including 51 patients with platinum resistance (PR) and 83 patients with platinum sensitivity (PS). The variance threshold, SelectKBest, and least absolute shrinkage and selection operator (LASSO) were applied for feature selection and model construction. The selected texture features were calculated to obtain the radiomics score (Rad-score), and the predictive nomogram model was composed of the Rad-score and the clinical features selected by multivariate analysis. Receiver operating characteristic (ROC) curves, calibration curves, and decision curves were used to assess the performance of the nomogram.ResultsThe Rad-score was calculated using 10 radiomic features, and the resulting radiomics signature demonstrated good discrimination in both the training set (area under the curve [AUC], 0.727; 95% confidence interval [CI], 0.627–0.809) and the validation set (AUC, 0.723; 95% CI, 0.562–0.799). To improve diagnostic effectiveness, the Rad-score created a novel prediction nomogram by combining CA125 and CA72-4. The radiomics nomogram showed good calibration and discrimination in the training set (AUC, 0.900; 95% CI, 0.844-0.947) and the validation set (AUC, 0.838; 95% CI, 0.534-0.735). The radiomics nomogram proved to be clinically beneficial based on decision curve analysis.ConclusionWe developed and validated a radiomics nomogram model for predicting the response to platinum in SCLC patients. The outcomes of this model can provide useful suggestions for the development of tailored and customized second-line chemotherapy regimens.

Thermal stimulation methods of hydrate exploitation with chemical self-heating solution began to be investigated in the recent years. However, the exothermic characteristics of chemical self-heating solution during the gas hydrate exploitation process was not investigated systematically now. In this work, the effects of reagent concentration, acid variety, acid concentration on the exothermic characteristics were investigated by a self-designed high pressure autoclave with a 11.75 L volume, whose diameter and length is 100 and 1,500 mm, respectively. The experimental results showed that the temperature of hydrate reservoir will change in a wide range (from 100°C to −3°C) during the injection process of self-heating solution which was a large challenge to control the rate of heat release. During the self-heating solution injection, the temperature decreased quickly because of the strong endothermic reaction of hydrate dissociation promoted by the salt effect of self-heating solution, and then the temperature increased quickly because of exothermic reaction of self-heating solution. The exothermic rate of self-heating solution increased with the increase of reagent concentration, the acid concentration and the acidity. In all of the experiments, the temperatures near the inlet entrance were much higher than that in the deeper area, which illustrated that the effective heating area is the areas near the entrance. In the end, the different injection mode of mixed injection and sectional injection was also investigated, and it was found that the temperature peak in the near area with mixed injection mode is higher than that with sectional injection mode, however, the exothermic performance with sectional injection mode is better than that with mixed injection in the area far away from the inlet entrance. The exothermic characteristics studies of self-heating solution in this work can lay the necessary foundation of the further studies of self-heating solution in the exploitation of natural gas hydrate.

Considering the deep foundation pit of a car dumper room close to the Beijing–Baotou railway, the countermeasures of the foundation pit design are analyzed according to the surrounding environment and stratum conditions. Through Midas GTS software as well as field measured results, the construction effect on the adjacent railway subgrade is discussed. Therefore, the deformation characteristics of the foundation pit as well as the retaining structure, including the railway subgrade, caused by the excavation process, are revealed. The results show that the five-sided water-stop structure formed by cement piles around and at the bottom of the pit avoids the consolidation settlement of the adjacent railway subgrade caused by deep dewatering and also reduces the lateral displacement (i.e., in a horizontal direction) and the heave of the pit bottom. As a result, the lateral displacement near the railway side is larger than that of the retaining structure on the other side due to the subgrade on the pit side. The cross-lot bracing across the foundation pit will transfer the bias pressure of the subgrade to the retaining structure far away from the railway, while the transfer effect of the knee bracing is not obvious. The deformation of the railway subgrade and its evolution rate caused by the removal of internal bracing is significantly greater than the subgrade deformation and the change rate of deformation caused by excavation. The research results provide useful guidance for the deep foundation pit design.

All current recommendation algorithms, when modeling user–item interactions, basically use dot product. This dot product calculation is derived from matrix factorization. We argue that an inherent drawback of matrix factorization is that latent semantic vectors of users or items sometimes do not satisfy triangular inequalities, which may affect the performance of the recommendation. Recently, metric factorization was proposed to replace matrix factorization and has achieved some improvements in terms of recommendation accuracy. However, similar to matrix factorization, metric factorization still uses a simple, linear fashion. In this paper, we explore leveraging nonlinear deep neural networks to realize Euclidean distance interaction between users and items. We propose a generic Neural Metric Factorization Framework (NMetricF), which learns representations for users and items by incorporating Euclidean metric factorization into deep neural networks. Extensive experiments on six real-world datasets show that, compared to the previous recommendation algorithms based purely on rating data, NMetricF achieves the best performance.

Hyperbaric oxygen (HBO) therapy through breathing oxygen at the pressure of above 1 atmosphere absolute (ATA) is useful for varieties of clinical conditions, especially hypoxic-ischemic diseases. Because of generation of reactive oxygen species (ROS), breathing oxygen gas at high pressures can cause oxygen toxicity in the central nervous system, leading to multiple neurological dysfunction, which limits the use of HBO therapy. Studies have shown that Hydrogen gas (H2) can diminish oxidative stress and effectively reduce active ROS associated with diseases. However, the effect of H2 on ROS generated from HBO therapy remains unclear. In this study, we investigated the effect of H2 on ROS during HBO therapy using PC12 cells. PC12 cells cultured in medium were exposed to oxygen gas or mixed oxygen gas and H2 at 1 ATA or 5 ATA. Cells viability and oxidation products and ROS were determined. The data showed that H2 promoted the cell viability and inhibited the damage in the cell and mitochondria membrane, reduced the levels of lipid peroxidation and DNA oxidation, and selectively decreased the levels of •OH but not disturbing the levels of O2•-, H2O2, or NO• in PC12 cells during HBO therapy. These results indicated that H2 effectively reduced •OH, protected cells against oxygen toxicity resulting from HBO therapy, and had no effect on other ROS. Our data supported that H2 could be potentially used as an antioxidant during HBO therapy.

Pine wilt disease (PWD) poses a severe threat to the health of pine trees and has resulted in substantial losses to global pine forest resources. Due to the minute size of the pathogens and the concealed symptoms of PWD, early detection through remote sensing image technology is essential. However, in practical applications, remote sensing images are easily affected by factors, such as cloud cover and changes in illumination, resulting in significant noise and blurriness in the images. These interference factors significantly reduce the accuracy of existing object detection models. Therefore, this article presents a novel and highly robust methodology for detecting PWD, termed YOLOv8-RD. We synthesized the benefits of residual learning and fuzzy deep neural networks to develop a residual fuzzy module (ResFuzzy), which adeptly filters image noise and refines background features with enhanced smoothness. Simultaneously, we integrated a detail processing module into the ResFuzzy module to enhance the low-frequency detail features transmitted in residual learning. Furthermore, by incorporating the dynamic upsampling operator, our model can dynamically adjust the sampling step size based on the variations in the input feature map during the upsampling process, thereby effectively recovering detail from the feature map. Our model exhibited exceptional robustness to severe noise. When evaluated on a PWD dataset with 100% interference samples at an intensity of 0.07, our model achieved an average precision improvement of 4.9%, 6.3%, 7.3%, and 3.0% compared to four most representative models, making it well suited for PWD detection in interfering environments.

BackgroundSarcopenia, sarcopenic obesity, and hypertension are all widespread public health problems in middle-aged and older populations, and their association is controversial. The purpose of this study is to analyze the relationship between obesity, sarcopenia, and sarcopenic obesity with hypertension in a middle-aged and older community population in China through a large-scale longitudinal design.MethodsIn this cohort study with 7 years of follow-up, the study population was drawn from participants in the China Health and Retirement Longitudinal Study (CHARLS) in 2011 and followed up in 2013, 2015, and 2018. The diagnostic criteria for sarcopenia were based on the consensus recommendations issued by the Asian Working Group for Sarcopenia (AWGS) in 2019. The diagnosis of obesity is based on body mass index and waist circumference. Sarcopenic obesity is defined as the coexistence of sarcopenia and obesity. Cox proportional risk regression models were used to analyze the association of obesity, sarcopenia, and sarcopenic obesity with hypertension.ResultsA total of 7,301 participants with a mean age of 58 ± 8.8 were enrolled in the study, and 51.9% females. A total of 1,957 participants had a new onset of hypertension after 7 years of follow-up. In a multifactorial analysis, obesity and sarcopenic obesity were associated with hypertension; hazard ratios (HRs) and 95% confidence intervals (CIs) were 1.67 (1.43 ~ 1.96), p

The deep coal mining in the North China type of coalfield is generally threatened by the underlying limestone water of Taiyuan Formation and Ordovician. The occurrence of water inrush can be avoided effectively by applying grouting reinforcement technology to the coal floor. However, the reinforcement treatment of the coal floor belongs to underground concealment engineering, and it is of great significance for the safe production of the coal mine by scientifically and comprehensively evaluating the technical method of the grouting effect on the working face floor. In this study, the optimal transfer matrix is used to construct the judgment matrix that meets the consistency requirements; the analytic hierarchy process is improved; and the grouting effect of the working face floor is evaluated by fuzzy comprehensive evaluation based on several factors of the grouting effect. Taking the grouting engineering of the 15092 working face of the Guhanshan Mine as an example, the evaluation of the grouting effect based on four evaluatory indices have been refined: dynamic hydrological features, grout amount, grouting inspection hole, and geophysical prospecting have been refined. Based on the improved analytic hierarchy process (AHP), the result of the grouting effect can be divided into four levels: distinction, good, average, and poor. The study would play a very important role in the evaluation of the grouting reinforcement of the working face floor and the practice of coal mine production safety.

In view of difficult problems such as excavation, segment simulation, deformation, and force measurement in the small-scale model testing of deep composite stratum TBM tunnel, the TBM simulation experimental device, the model segment ring prefabrication device, and the digital photogrammetry technology were comprehensively adopted. Also, the calculation methods were proposed. The analysis of the deformation characteristics as well as rupture of surrounding rock revealed those space-time effects: (1) When no support existed, the space-time effect of the surrounding rock deformation was concentrated in the following case: with the development of time, the deformation of surrounding rock starts from the sides of the arch waist at the junction of the composite stratum, while four arcs were derived and shear sliding occurred, resulting in overall collapse and destruction. (2) Following the support application, the space-time effect of the surrounding rock deformation was concentrated on the three stages of the interaction between the surrounding rock and the support, namely, the preliminary stage, the equilibrium process, and the instability state. The spatial effect was concentrated in the area where the surrounding rock was deformed and destroyed. The most severe area was the shallow surrounding rock, while the sub-violent area was the corner of the sidewall.