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Understanding the mechanical characteristics of rocks when subjected to direct tension is crucial for assessing the stability of rock formations. Within the scope of this research, a series of tests was conducted using Tage tuff to assess the deformation behavior and crack extension of rock under direct tension. The axial, lateral, and shear strain fields as well as crack propagation, localized deformation behavior, and failure mode of the rocks were analyzed using three-dimensional digital image correlation method. The results showed that the axial strain fields on the specimen surface were heterogeneous, with different locations and localization occurring in the pre-peak stage, which was similar to the evolution of shear strain, whereas the lateral strain only showed slight changes. The crack extension direction was inferred, indicating that both tensile and shear stress occurred in the tests. Furthermore, different stress–strain responses were observed for the inside and outside of the localized bands. Then, the surface patterns of specimen failure were scanned and analyzed to assess the failure mode and residual strength of the specimen under direct tensile stress. Finally, the results of direct tension, uniaxial compression, and Brazilian split tests for Tage tuff were compared, and the complete stress–strain curve of uniaxial tension (UT) was simulated using a nonlinear-variable-compliance constitutive equation. This study provides a deeper understanding into the damage behavior of rocks under direct tension. [ABSTRACT FROM AUTHOR]

A compression module system placed under a microscope was utilized to conduct uniaxial compression testing of sandstone samples. The test system can acquire the image of crack propagation on the specimen surface in real time. The focus of this study was to analyze how the motion of sandstone composition particles affect the failure mechanism of the samples under minimal loading rates. The results indicate that the load displacement curves align with the macroscopic failure laws under different loading rates. Furthermore, the lower the loading rate, the greater the deformation and crushing degree of sandstone during failure. The failure mode becomes more complex and gradually transitions from tension failure to shear-tension failure. The crack evolution of sandstone was caused by the uncoordinated movement of its components, and the weak structure induces cracks under the action of external load. Microcracks are initially generated at the interface between mineral particles and the sandstone matrix and propagate along the boundary between mineral and matrix. The interaction between component particles in sandstone leads to the connection break between particles which forms microcracks, and results in local deformation of the sample. The aggregation of multiple cracks leads to the instability and failure of sandstone. [ABSTRACT FROM AUTHOR]

Cytoskeleton is extensively recruited by flaviviruses for their infection. In this study, we uncovered an essential role of a nuclear membrane protein, SAD1/UNC84 domain protein 2 (SUN2) linking cytoskeleton and nucleoskeleton in the flavivirus replication. CRISPR/Cas9-mediated knockout of SUN2, but not SUN1, significantly reduces the replication of Zika virus (ZIKV), dengue virus (DENV), and Japanese encephalitis virus (JEV). In contrast, SUN2 does not affect the infection of non-flaviviridae RNA viruses. All three regions of SUN2 are required for its proviral effect. Mechanistically, SUN2 facilitates rearrangement of cytoskeleton and formation of replication organelles induced by viral infection, and hence promotes viral RNA synthesis. SUN2 is required for the interaction between cytoskeleton actin and ZIKV nonstructural protein 1 (NS1). Expression of dominant negative Nesprin-1 and Nesprin-2, which connect SUN2 to cytoskeleton proteins, alleviates the interaction between actin and NS1 and reduces viral replication levels. In a neonatal mouse infection model, SUN2 knockout dramatically alleviates the in vivo ZIKV replication and development of neuropathology. This work elucidates that recruitment of cytoskeleton proteins by flavivirus is coordinated by nuclear membrane proteins SUN2 and Nesprins, providing evidence for a link between nuclear membrane proteins and flavivirus infection. Here, Huang et al. show that nuclear membrane proteins SUN2 and Nesprins are required for the in vitro and in vivo replication of Zika virus, through directing the cytoskeleton remodeling and formation of replication organelles mediated by viral NS1. [ABSTRACT FROM AUTHOR]

Background: To establish a predictive model based on multisequence magnetic resonance imaging (MRI) using deep learning to identify wild-type (WT) epidermal growth factor receptor (EGFR), EGFR exon 19 deletion (19Del), and EGFR exon 21-point mutation (21L858R) simultaneously. Methods: A total of 399 patients with proven brain metastases of non-small cell lung cancer (NSCLC) were retrospectively enrolled and divided into training (n = 306) and testing (n = 93) cohorts separately based on two timepoints. All patients underwent 3.0-T brain MRI including T2-weighted, T2-weighted fluid-attenuated inversion recovery, diffusion-weighted imaging, and contrast-enhanced T1-weighted sequences. Radiomics features were extracted from each lesion based on four sequences. An algorithm combining radiomics approach with graph convolutional networks architecture (Radio-GCN) was designed for the prediction of EGFR mutation status and subtype. The area under the curve (AUC) at receiver operating characteristic analysis was used to evaluate the predication capabilities of each model. Results: We extracted 1,290 radiomics features from each MRI sequence. The AUCs of the Radio-GCN model for identifying EGFR 19Del, 21L858R, and WT for the lesion-wise analysis were 0.996 ± 0.004, 0.971 ± 0.013, and 1.000 ± 0.000 on the independent testing cohort separately. It also yielded AUCs of 1.000 ± 0.000, 0.991 ± 0.009, and 1.000 ± 0.000 for predicting EGFR mutations respectively for the patient-wise analysis. The κ coefficients were 0.735 and 0.812, respectively. Conclusions: The constructed Radio-GCN model is a new potential tool to predict the EGFR mutation status and subtype in NSCLC patients with brain metastases. Relevance statement: The study demonstrated that a deep learning approach based on multisequence MRI can help to predict the EGFR mutation status in NSCLC patients with brain metastases, which is beneficial to guide a personalized treatment. Key points: • This is the first study to predict the EGFR mutation subtype simultaneously. • The Radio-GCN model holds the potential to be used as a diagnostic tool. • This study provides an imaging surrogate for identifying the EGFR mutation subtype. [ABSTRACT FROM AUTHOR]

This document provides concise summaries of several research studies related to medical imaging techniques and their applications in diagnosing and treating various diseases. The studies cover a wide range of topics, including the use of AI algorithms in breast cancer detection, the effectiveness of diffusion tensor imaging in diagnosing brain tumors, and the use of PET imaging in detecting neurodegenerative diseases. The studies offer valuable insights into the potential benefits and limitations of these imaging techniques, but further research and validation are needed to confirm these findings. [Extracted from the article]

The frozen section (FS) diagnoses of pathology experts are used in China to determine whether sentinel lymph nodes of breast cancer have metastasis during operation. Direct implementation of a deep neural network (DNN) in clinical practice may be hindered by misdiagnosis of the algorithm, which affects a patient's treatment decision. In this study, we first obtained the prediction result of the commonly used patch-DNN, then we present a relative risk classification and regression tree (RRCART) to identify the misdiagnosed whole-slide images (WSIs) and recommend them to be reviewed by pathologists. Applying this framework to 2362 WSIs of breast cancer lymph node metastasis, test on frozen section results in the mean area under the curve (AUC) reached 0.9851. However, the mean misdiagnosis rate (0.0248), was significantly higher than the pathologists' misdiagnosis rate (p < 0.01). The RRCART distinguished more than 80% of the WSIs as a high-accuracy group with an average accuracy reached to 0.995, but the difference with the pathologists' performance was not significant (p > 0.01). However, the other low-accuracy group included most of the misdiagnoses of DNN models. Our research shows that the misdiagnosis from deep learning model can be further enriched by our method, and that the low-accuracy WSIs must be selected for pathologists to review and the high-accuracy ones may be ready for pathologists to give diagnostic reports. [ABSTRACT FROM AUTHOR]

A better understanding of the association between sedentary behavior and heart failure is essential for the development of interventions to improve patients' outcomes. Therefore, a systematic review was conducted to determine the association between sedentary behavior and all-cause mortality, health-related quality of life, and depression in heart failure patients. We searched Web of Science, PubMed, Embase, and Cochrane Library and articles in references on 7 May 2021. The search results were limited to articles on heart failure patients over the age of 18, observational studies investigating the association between sedentary behavior and heart failure, and studies reporting one or more outcomes of interest. Two reviewers independently screened the literature and extracted data. Strengthening the Reporting of Observational Studies in Epidemiology was used to assess the quality of articles. Nine observational studies were included, of which, four were of high quality. Four cohort studies indicated that sedentary behavior was significantly associated with increased all-cause mortality (hazard ratio: 1.97; 95% confidence interval: 1.60 to 2.44; I2 = 38.9%). In addition, subgroup analysis based on geographical regions was conducted (hazard ratio: 1.82; 95% confidence interval: 1.46 to 2.29; I2 = 0%). Sedentary behavior was associated with worse health-related quality of life in patients with heart failure, and the regression coefficients ranged from 0.004 to 0.033 (95% confidence interval: 0.0004 to 0.055). Although sedentary behavior was associated with increased all-cause mortality and worse quality of life in patients with heart failure, further studies are needed to determine whether this association is causal. [ABSTRACT FROM AUTHOR]

The dynamic characteristics of high sensitivity temperature sensor are studied by using siphon method to fill the air hole near the core of the hollow photonic crystal fiber with Cargille matching liquid, and the two ends are fused with single-mode fiber in this work. We analyzed the working principle of filled photonic crystal fiber sensor by using the standard coupling mode theory of directional coupler. The coupling process was simulated by COMSOL software. When the photonic crystal fiber filled with 10 mm liquid was scanned by tunable laser, the temperature sensitivity was 7.50 nm /°C, the average temperature response time was 0.317 s, the average release time was 3.732 s, and the temperature variation linearity was 100%. The experimental results show that the liquid filled photonic crystal fiber has the advantages of high temperature sensitivity, fast response time and good linearity. [ABSTRACT FROM AUTHOR]

A high-sensitive methane sensor based on a twin-core photonic crystal fiber (PCF) is proposed and analyzed. Two ultra-large side-holes of the PCF are polished and coated with methane-sensitive film to achieve fast response and high sensitivity. The finite element method is used to investigate the relationship between gas sensing performance and structural parameters. With the increase of the methane concentration from 0 to 3%, the gas sensitivity and low detection limit can reach to 4.60 nm/% and 435 ppm, respectively. The proposed sensor with high sensitivity and simple structure has great practical value and application prospects for environmental gas monitoring. [ABSTRACT FROM AUTHOR]

In order to study the effect of water-rock interactions on shear strength characteristics, we performed shearing tests under varying hydrochemical environments. Moreover, a custom meso-shear test equipment for coal rock was used for the tests. Through 3D scanning of the shear fractures and scanning electron microscope imaging, we studied the effect of different pH chemical solutions on the shear strength and fracture characteristics of sandstones. We obtained three main results. With increasing solution acidity or alkalinity, water-hemical solution corrosivity increases. Moreover, the shear strength of sandstones reduces almost linearly and the fracture surfaces become smoother. The erosive effect is evidenced by the decrease in fracture surface fluctuations, roughness and the high-order microbulges, and scaling of the grain structure. A collection of characteristic parameters, including the maximum height Sh, the root mean square deviation Sq, the area ratio SA, and the slope root mean square S∆q, can be used to quantitatively describe the rough and irregular texture of the fracture surface. [ABSTRACT FROM AUTHOR]

A highly sensitive and temperature-compensated methane sensor based on a liquid-infiltrated photonic crystal fiber (PCF) is proposed. Two bigger holes near the core area are coated with a methane-sensitive compound film, and specific cladding air holes are infiltrated into the liquid material to form new defective channels. The proposed sensor can achieve accurate measurement of methane concentration through temperature compensation. The sensitivity can reach to 20.07 nm/% with a high linearity as the methane concentration is within the range of 0%–3.5% by volume. The proposed methane sensor can not only improve the measurement accuracy, but also reduce the metrical difficulty and simplify the process. [ABSTRACT FROM AUTHOR]

Intensive anthropogenic activities may add to pollution risks to lakes and rivers, which can be revealed by the magnetic characteristics of sediments. The present study aims to assess the pollution status of the sediment of a typical reservoir in northwestern China by application of magnetic susceptibility. The values of magnetic susceptibility exhibited significant positive correlations with trace metals (Co, Cu, Mn, Ni, and V) and natural radionuclides (232Th and 40K). Multivariate statistical analysis indicated common sources and similar deposition characteristics of magnetic particles and trace metals. It was conformed that magnetic susceptibility could be used as an indicator to identify industrial sources of trace metals, but was not suitable to indicate the traffic or natural sources. Linear regression equations between the low-frequency magnetic susceptibility and the integrated pollution index as well as annual effective dose rate indicated a potential for using magnetic susceptibility in semi-quantitative assessment of trace metal pollution and radiological hazard in sediments. A three-step procedure is proposed for the use of magnetic susceptibility in pollution monitoring, which provides a fast and effective method for estimating the pollution extent and tracing the major sources of trace metals in the sediment of lakes and rivers. [ABSTRACT FROM AUTHOR]

The accumulation and source of heavy metals As, Ba, Co, Cr, Cu, Mn, Ni, Pb, V, and Zn in the surface sediment of a reservoir near an industrial park of northwest China were determined by enrichment factor and multi-variate statistical analysis. Multivariate statistical analyses, i.e., factor analysis, cluster analysis, and correlation coefficient analysis, were used to identify the possible sources of the heavy metals. The results show that the mean concentrations of As, Ba, Co, Cr, Cu, Mn, Ni, Pb, V, and Zn in the reservoir sediment are higher than their corresponding concentrations in the control sample, indicating all analyzed heavy metals accumulated in the surface sediments. The values of the mean concentrations of heavy metals in the surface sediment divided by their corresponding concentrations in the control sample increase in the order of Ba = Cr

The contents of Co, Cr, Cu, Mn, Ni, Pb and Zn in the dust samples collected from Changqing industrial park of Baoji city, NW China, were measured by XRF, while As and Hg in the dust samples were analyzed by AFS. Geo-accumulation index ( I), pollution index (PI) and integrated pollution index (IPI) were calculated to evaluate the heavy metal contamination level of dust. The health risk due to exposure to heavy metals in dust was analyzed by the Health Risk Assessment Model of US EPA. The results show that the arithmetic means of As, Co, Cr, Cu, Hg, Mn, Ni, Pb and Zn are 23.3, 16.4, 1591.8, 178.2, 0.243, 346.5, 40.2, 1,586.2 and 1,918.8 mg kg, respectively, which are higher than the background values of Shaanxi soil, especially for Cr, Cu, Hg, Pb, and Zn. The mean values of I reveal the order of Pb > Zn > Cr > Hg > Cu > As > Co > Ni > Mn. The high I of Cr, Cu, Hg, Pb and Zn in dust indicates that there is considerable pollution from Cr, Cu, Hg, Pb and Zn, while the low I of As, Co, Mn and Ni presents no pollution in dust. The assessment results of PI support the results of I, and IPI indicates heavy metals in dust polluted seriously. The health risk assessment shows that ingestion of dust particles is the route for exposure to heavy metals from dust, followed by dermal adsorption. Exposure to As, Cr and Pb from dust may pose a potential health threat to children and adults. The risk of cancer from As, Co, Cr and Ni due to dust exposure is low. [ABSTRACT FROM AUTHOR]

Concentrations of heavy metals and natural radionuclides in soil around a major coal-fired power plant of Xi'an, China were determined by using XRF and gamma ray spectrometry, respectively. The measured results of heavy metals show that the mean concentrations of Cu, Pb, Zn, Co and Cr in the studied soil samples are higher than their corresponding background values in Shaanxi soil, while the mean concentrations of Mn, Ni and V are close to the corresponding background values. The calculated results of pollution load index of heavy metals indicate that the studied soils presented heavy metal contamination. The concentrations of Ra, Th and K in the studied soil samples range from 27.6 to 48.8, 44.4 to 61.4 and 640.2 to 992.2 Bq kg with an average of 36.1, 51.1 and 733.9 Bq kg, respectively, which are slightly higher than the average of Shaanxi soil. The air absorbed dose rate and the annual effective dose equivalent received by the local residents due to the natural radionuclides in soil are slightly higher than the mean values of Shaanxi. Coal combustion for energy production has affected the natural radioactivity level and heavy metals (Cu, Pb, Zn, Co and Cr) concentrations of soil around the coal-fired power plant. [ABSTRACT FROM AUTHOR]