Research on long-term migration behaviors of heavy metals after close-distance coal seam backfill mining.

The backfill mining of coal-based solid waste in goaf poses a potential risk of heavy metal pollution to the groundwater environment, and the migration behavior of heavy metals differs significantly under the disturbance of backfill mining in close-distance multi-layer coal seams and single-layer coal seams. In this study, a migration model of heavy metals after solid backfilling in the goaf of shallow-buried close-distance thick coal seams was established, and the impact of the overburden damage and the layered distribution of the filling body on the long-term migration behavior of heavy metals were analyzed. The results show that the migration of heavy metals after close-distance coal seam backfill mining exhibits a higher risk of heavy metal pollution. The peak permeability of overburden after close-distance coal seam backfill mining is about 600 × 10-19 m2 higher than that after single-layer coal seam backfill mining. The migration distance of heavy metals in the floor after backfill mining of close-distance coal seams is 7.41 m farther than that of single-layer coal seam backfill mining, and its migration time of heavy metals to the surface is 27 a earlier than that of single-layer coal seam. This research provides theoretical and empirical support for the ecological risk assessment and heavy metal pollution control in close-distance coal seam backfill mining. ENVIRONMENTAL IMPLICATION: The main filling material of close-distance coal seams backfill mining is coal gangue. Heavy metal elements such as Mn and Cr will be released in the underground environment for a long time, and the migration behavior of heavy metal elements will have an impact on the groundwater environment for more than 1000 years. This research provides theoretical and empirical support for the ecological risk assessment of close-distance coal seam backfill mining and the mitigation of heavy metal pollution.

Choroidal Vascularity Index and Choroidal Structural Changes in Children With Nephrotic Syndrome.

Purpose: To investigate the choroidal vascularity index (CVI) and choroidal structural changes in children with nephrotic syndrome. Methods: This was a cross-sectional study involving 45 children with primary nephrotic syndrome and 40 normal controls. All participants underwent enhanced depth imaging-optical coherence tomography examinations. An automatic segmentation method based on deep learning was used to segment the choroidal vessels and stroma, and the choroidal volume (CV), vascular volume (VV), and CVI within a 4.5 mm diameter circular area centered around the macular fovea were obtained. Clinical data, including blood lipids, serum proteins, renal function, and renal injury indicators, were collected from the patients. Results: Compared with normal controls, children with nephrotic syndrome had a significant increase in CV (nephrotic syndrome: 4.132 ± 0.464 vs. normal controls: 3.873 ± 0.574; P = 0.024); no significant change in VV (nephrotic syndrome: 1.276 ± 0.173 vs. normal controls: 1.277 ± 0.165; P = 0.971); and a significant decrease in the CVI (nephrotic syndrome: 0.308 [range, 0.270-0.386] vs. normal controls: 0.330 [range, 0.288-0.387]; P < 0.001). In the correlation analysis, the CVI was positively correlated with serum total protein, serum albumin, serum prealbumin, ratio of serum albumin to globulin, and 24-hour urine volume and was negatively correlated with total cholesterol, low-density lipoprotein cholesterol, urinary protein concentration, and ratio of urinary transferrin to creatinine (all P < 0.05). Conclusions: The CVI is significantly reduced in children with nephrotic syndrome, and the decrease in the CVI parallels the severity of kidney disease, indicating choroidal involvement in the process of nephrotic syndrome. Translational Relevance: Our findings contribute to a deeper understanding of how nephrotic syndrome affects the choroid.

Research on coal mining intensity based on the DPSIR-SPA model.

High-intensity mining has become a major trend in future coal mining. However, it will unavoidably worsen the harm done to the natural environment of mining sites by coal mining, which is already prone to doing so. So, how may coal mining intensity (CMI) be decreased? Minimize the harm that coal mining causes to the environment and offer a theoretical basis for protecting the environment in mining sites. In order to achieve this, based on the existing literature on CMI, we first redefine the concept of CMI, analyze its influencing factors, propose an evaluation index system, and introduce the theory of set pair analysis (SPA) to build a quantitative evaluation model of CMI. We then propose an adjustment strategy for the CMI and conduct a verification analysis using the Halagou Coal Mine and Caojiatan Coal Mine as an example. The results show that the Halagou and Caojiatan Coal Mine belong to the higher-intensity mining stage. It is consistent with existing research. Moreover, the development trend of CMI in the Halagou Coal Mine is analyzed in conjunction with the set pair potential theory, and specific measures to reduce CMI are given, from the perspective of coal mining. It provides the basis for the source protection of the ecological environment in the mining area. Theoretically, this study can help both the quantitative assessment of mining intensity and the source protection of the mining ecological environment. Besides, it offers specific guidelines for building environmentally friendly mines.

Comparison of the morphological characteristics of the choroidal sublayer between idiopathic macular holes and epiretinal membranes with automatic analysis.

PURPOSE: To compare the choroidal sublayer morphologic features between idiopathic macular hole (IMH) and idiopathic epiretinal membrane (iERM) on spectral-domain optical coherent tomography (SD-OCT) using an automatic segmentation model. METHODS: Thirty-three patients with idiopathic IMHs and 44 with iERMs who underwent vitrectomies were involved. The enhanced depth imaging mode of SD-OCT was used to obtain the B-scan image after single line scanning of the macular fovea. The choroidal sublayer automatic analysis model divides the choroidal into the choroidal large vessel layer, the middle vessel layer and the small vessel layer (LVCL, MVCL and SVCL, respectively) and calculates the choroidal thickness (overall, LVCL, MVCL and SVCL) and vascular index (overall, LVCL, MVCL and SVCL). The morphological characteristics of the choroidal sublayer in the ERM eyes and the IMH eyes were compared. RESULTS: The mean choroidal thickness in the macular centre of the IMH eyes was significantly thinner than that of the ERM eyes (206.35 ± 81.72 vs. 273.33 ± 82.31 µm; P < 0.001). The analysis of the choroidal sublayer showed that the MVCL and SVCL macular centres and 0.5-1.5 mm of the nasal and temporal macula were significantly thinner in the IMH eyes than in the ERM eyes (P < 0.05), and there was a difference in the macular centre of the LVCL between the two groups (P < 0.05). In contrast, the choroidal vascular index of the macular centre in the IMH eyes was significantly higher than that in iERM eyes (0.2480 ± 0.0536 vs. 0.2120 ± 0.0616; P < 0.05). There was no significant difference in the CVI of other parts of the macula, the LVCL or MVCL between the two groups. CONCLUSION: The choroidal thickness of the IMH eyes was significantly thinner than that of the iERM eyes, which was mainly observed in 3 mm of the macular centre and the MVCL and SVCL layers of the choroid. The choroidal vascular index of the IMH eyes was higher than that of the iERM eyes. These findings suggest that the choroid may be involved in the pathogenesis of IMH and iERM.

Research on coal mine safety management based on digital twin.

Coal mine safety management is the foundation and decisive factor of coal mining. The manual detection model is the main way for traditional coal mine safety management, which has problems such as inefficient identification of safety risks in coal mines, poor control accuracy and slow response measures and so on. Therefore, to make up for the shortcomings in the traditional coal mine safety management model, this paper introduces digital twin technology into coal mine safety management to achieve intelligent and efficient management of coal mine safety accidents. Firstly, we introduce the digital twin technology, select the five-dimensional model as the modeling basis, based on the existing twin model architecture, analyze the types of coal mine accidents and disasters, select the most destructive gas accidents as the research object, construct a twin safety management model for coal mine gas accidents using the digital twin five-dimensional model. Secondly, analyses of the actual operation mechanism of the digital twin model, and the advantages of the twin model in achieving prior prevention, rapid response and accurate control of gas incidents are pointed out. Finally, the house of quality of the gas accident digital twin model is established through the quality functional deployment tool, and key technical requirements for the construction of the twin model are given to accelerate the application of the gas accident twin model in the field. This study innovatively introduces digital twin technology into the field of coal mine safety management, proposes the application scenarios of emerging technologies such as digital twins in the coal mine field, and provides the possibility of multi-scene application of smart mine construction and technologies such as digital twins.

Terahertz Spectroscopy and Imaging Techniques for Herbal Medicinal Plants Detection: A Comprehensive Review.

Herbal medicine (HM), derived from various therapeutic plants, has garnered considerable attention for its remarkable effectiveness in treating diseases. However, numerous issues including improved varieties selection, hazardous residue detection, and concoction management affect herb quality throughout the manufacturing process. Therefore, a practical, rapid, nondestructive detection technology is necessary. Terahertz (THz) spectroscopy, with low energy, penetration, and fingerprint features, becomes preferable method for herb quality appraisal. There are three parts in our review. THz techniques, data processing, and modeling methods were introduced in Part I. Three primary applications (authenticity, composition and active ingredients, and origin detection) of THz in medicinal plants quality detection in industrial processing and marketing were detailed in Part II. A thorough investigation and outlook on the well-known applications and advancements of this field were presented in Part III. This review aims to bring new enlightenment to the in-depth THz application research in herbal medicinal plants.

Rapid qualitative detection of titanium dioxide adulteration in persimmon icing using portable Raman spectrometer and Machine learning.

Persimmon icing is the white crystalline powder that adheres to the surface of persimmon cakes when the sugar in the persimmon spills over during processing, which is considered the essence of persimmon. Titanium dioxide is a food additive that is commonly added to the surface of persimmon cakes to impersonate high-quality persimmon cakes. However, excessive titanium dioxide can be harmful to humans, so a quick method is needed to identify persimmon cakes as adulterated. Raman spectroscopy with distinctive advantages of water-insensitivity, real-time, field-deployable, label-free, and fingerprinting-identification has been rapidly developed and used in food quality assurance and safety monitoring. In this study, we investigated Raman spectroscopy integrated with machine learning to assess titanium dioxide adulteration in dried persimmon icing. The adaptive iterative reweighting partial least squares (air-PLS) algorithm as an effective algorithm was used to remove fluorescent background signals in raw Raman spectroscopy. Principal components analysis (PCA) was employed to analyze the spectral data and determine the class memberships, and results showed that 99.9% of information could be explained by PC-1 and PC-2. Compared with extreme learning machine (ELM), support vector machine (SVM), back propagation artificial neural network (BP-ANN), and random forest (RF) models, one-dimensional stack auto encoder convolutional neural network (1D-SAE-CNN) could provide the highest detection accuracy of 0.9825, precision of 0.9824, recall of 0.9825, and f1-score of 0.9824. This study shows that Raman spectroscopy coupled with 1D-SAE-CNN is a promising method to detect titanium dioxide adulteration in persimmon icing.

Optical imaging spectroscopy coupled with machine learning for detecting heavy metal of plants: A review.

Heavy metal elements, which inhibit plant development by destroying cell structure and wilting leaves, are easily absorbed by plants and eventually threaten human health via the food chain. Recently, with the increasing precision and refinement of optical instruments, optical imaging spectroscopy has gradually been applied to the detection and reaction of heavy metals in plants due to its in-situ, real-time, and simple operation compared with traditional chemical analysis methods. Moreover, the emergence of machine learning helps improve detection accuracy, making optical imaging spectroscopy comparable to conventional chemical analysis methods in some situations. This review (a): summarizes the progress of advanced optical imaging spectroscopy techniques coupled with artificial neural network algorithms for plant heavy metal detection over ten years from 2012-2022; (b) briefly describes and compares the principles and characteristics of spectroscopy and traditional chemical techniques applied to plants heavy metal detection, and the advantages of artificial neural network techniques including machine learning and deep learning techniques in combination with spectroscopy; (c) proposes the solutions such as coupling with other analytical and detection methods, portability, to address the challenges of unsatisfactory sensitivity of optical imaging spectroscopy and expensive instruments.

Non-invasive measurement of tumor immune microenvironment and prediction of survival and chemotherapeutic benefits from 18F fluorodeoxyglucose PET/CT images in gastric cancer.

Background: The tumor immune microenvironment could provide prognostic and predictive information. It is necessary to develop a noninvasive radiomics-based biomarker of a previously validated tumor immune microenvironment signature of gastric cancer (GC) with immunohistochemistry staining. Methods: A total of 230 patients (training (n = 153) or validation (n = 77) cohort) with gastric cancer were subjected to (Positron Emission Tomography-Computed Tomography) radiomics feature extraction (80 features). A radiomics tumor immune microenvironment score (RTIMS) was developed to predict the tumor immune microenvironment signature with LASSO logistic regression. Furthermore, we evaluated its relation with prognosis and chemotherapy benefits. Results: A 8-feature radiomics signature was established and validated (area under the curve=0.692 and 0.713). The RTIMS signature was significantly associated with disease-free survival and overall survival both in the training and validation cohort (all P<0.001). RTIMS was an independent prognostic factor in the Multivariate analysis. Further analysis revealed that high RTIMS patients benefitted from adjuvant chemotherapy (for DFS, stage II: HR 0.208(95% CI 0.061-0.711), p=0.012; stage III: HR 0.321(0.180-0.570), p<0.001, respectively); while there were no benefits from chemotherapy in a low RTIMS patients. Conclusion: This PET/CT radiomics model provided a promising way to assess the tumor immune microenvironment and to predict clinical outcomes and chemotherapy response. The RTIMS signature could be useful in estimating tumor immune microenvironment and predicting survival and chemotherapy benefit for patients with gastric cancer, when validated by further prospective randomized trials.

Indirect comparison between powered and manual circular staplers for left-sided colorectal anastomoses: clinical and economic outcomes in China.

AIMS: This study aimed to examine the economic and clinical benefits of a new powered circular stapler for left-sided colorectal construction in China. METHODS: A decision analysis model was constructed for a cohort of adult patients who underwent left-sided colorectal anastomoses, using either the Echelon Circular Powered (ECP) stapler) or the conventional manual circular staplers (MCS). The complications rates and healthcare resource utilization in the ECP cohort were obtained from the single-arm ECP trial (NCT03326895). For the MCS cohort, retrospective data from 20 Chinese hospitals were analyzed. Listing prices were used to estimate the costs of the staplers in China. Propensity score matching (PSM) was employed to adjust for the imbalance between the two cohorts. Anastomotic leak rate, length of stay (LOS), 90-day readmission rate, and direct medical costs were used for the decision analysis model parameters. A budget impact analysis was conducted to compare the total hospitalization expenditure between ECP and manual circular staplers from the hospital's perspective in China. RESULTS: Assuming 100 procedures per year, the anastomotic leak rate was 1.79 and 29.76 per 100 procedures in the ECP and MCS cohorts, respectively. LOS was 1,426.91 days in the ECP cohort, compared to 1,702.38 days in the MCS cohort. The 90-day readmission rate was also lower in the ECP cohort than the MCS cohort (19.10 vs. 26.19 per 100 procedures). For the 100 procedures, the annual total hospitalization costs for left-sided colorectal anastomosis were reduced from ¥7,152,251 using manual circular staplers to ¥6,919,306 using ECP. Despite a higher acquisition cost of ECP compared to the manual staplers (¥711,200 vs. ¥441,700), an annual saving of ¥232,945in the total cost resulted from lower rates of complications and shorter LOS. Sensitivity analyses presented consistent savings using ECP, and the ECP cost and cost of the index hospitalization with anastomotic leak were found the most influencing factors. CONCLUSIONS: There were clinical and economic benefits of ECP, compared to manual circular staplers for left-sided colorectal anastomoses. Further direct comparative studies on the use of ECP in practice in Chinese hospital settings are warranted.

Microscopic fabric evolution and macroscopic deformation response of gangue solid waste filler considering block shape under different confining pressures.

The irregular shape of gangue blocks will affect the coordination structure between blocks in the crushed gangue accumulation body, and then affect the engineering mechanical properties of crushed gangue in the process of load-bearing compression. In this paper, through CT scanning experiment, particle flow numerical simulation experiment, and comprehensive application of image processing, 3D reconstruction, FLAC/PFC3D continuum-discrete coupling technology, the gangue digital 3D model and the numerical model of crushed gangue particle flow under triaxial compression condition considering the real shape of the block were obtained. The microscopic fabric evolution law and macroscopic deformation response characteristics of crushed gangue considering triaxial compression condition and different confining pressures were studied. The results show that: (1) the bearing capacity of crushed gangue materials increases with the increase of confining pressure; (2) the block aggregate in the gangue sample is gradually compacted, and the lateral deformation of the sample is changed from "extruding to the axis" to "bulging to the periphery"; (3) the vertical movement of the block decreases gradually from the top to the bottom of the sample, and there is a "triangle area" of block displacement at the top and bottom of the sample; the larger the confining pressure, the smaller the vertical displacement range at the top of the sample; (4) the process of "instability and failure-optimization and reconstruction" of skeleton force chain structure occurs constantly; as confining pressure increases, the stability of skeleton force chain structure and the bearing capacity of crushed gangue sample increases; (5) under the same strain state, the greater the confining pressure, the higher the fragmentation degree of the sample. This study reveals the internal mechanism of macro deformation of crushed gangue under the triaxial compression from the perspective of the mesoscopic fabric evolution. The research results are of great significance for the selection of crushed gangue in engineering application. In addition, the research results also have a significant impact on promoting the reasonable disposal and resource utilization of gangue solid waste and protecting the ecological environment of mining areas.

Surface-Enhanced Raman Scattering Spectroscopy Combined With Chemical Imaging Analysis for Detecting Apple Valsa Canker at an Early Stage.

Apple Valsa canker (AVC) with early incubation characteristics is a severe apple tree disease, resulting in significant orchards yield loss. Early detection of the infected trees is critical to prevent the disease from rapidly developing. Surface-enhanced Raman Scattering (SERS) spectroscopy with simplifies detection procedures and improves detection efficiency is a potential method for AVC detection. In this study, AVC early infected detection was proposed by combining SERS spectroscopy with the chemometrics methods and machine learning algorithms, and chemical distribution imaging was successfully applied to the analysis of disease dynamics. Results showed that the samples of healthy, early disease, and late disease sample datasets demonstrated significant clustering effects. The adaptive iterative reweighted penalized least squares (air-PLS) algorithm was used as the best baseline correction method to eliminate the interference of baseline shifts. The BP-ANN, ELM, Random Forest, and LS-SVM machine learning algorithms incorporating optimal spectral variables were utilized to establish discriminative models to detect of the AVC disease stage. The accuracy of these models was above 90%. SERS chemical imaging results showed that cellulose and lignin were significantly reduced at the phloem disease-health junction under AVC stress. These results suggested that SERS spectroscopy combined with chemical imaging analysis for early detection of the AVC disease was feasible and promising. This study provided a practical method for the rapidly diagnosing of apple orchard diseases.

Synergistically segmenting choroidal layer and vessel using deep learning for choroid structure analysis.

Objective. The choroid is the most vascularized structure in the human eye, whose layer structure and vessel distribution are both critical for the physiology of the retina, and disease pathogenesis of the eye. Although some works have used graph-based methods or convolutional neural networks to separate the choroid layer from the outer-choroid structure, few works focused on further distinguishing the inner-choroid structure, such as the choroid vessel and choroid stroma.Approach.Inspired by the multi-task learning strategy, in this paper, we propose a segmentation pipeline for choroid analysis which can separate the choroid layer from other structures and segment the choroid vessel synergistically. The key component of this pipeline is the proposed choroidal U-shape network (CUNet), which catches both correlation features and specific features between the choroid layer and the choroid vessel. Then pixel-wise classification is generated based on these two types of features to obtain choroid layer segmentation and vessel segmentation. Besides, the training process of CUNet is supervised by a proposed adaptive multi-task segmentation loss which adds a regularization term that is used to balance the performance of the two tasks.Main results.Experiments show the high performance (4% higher dice score) and less computational complexity (18.85 M lower size) of our proposed strategy.Significance.The high performance and generalization on both choroid layer and vessel segmentation indicate the clinical potential of our proposed pipeline.

Study on the distribution characteristics and ecological risk of heavy metal elements in coal gangue taken from 25 mining areas of China.

The long-term, high-yield production of coal has resulted in the large-scale accumulation of coal gangue on the ground surface, which causes serious environmental problems. Therefore, clean and environmental treatment of coal gangue is urgently needed. In this study, the inductively coupled plasma mass spectrometer and atomic fluorescence spectrometer were used to test the background values of ten heavy metals in coal gangue taken from 25 coal mines across China; the average content, distribution characteristics, and genesis of heavy metals in these coal gangue were investigated, and the ecological risk of heavy metals in coal gangue in different regions and different geological ages was analyzed and tested. The results show that the average contents of Hg, Pb, Cd, Cr, As, Cu, Zn, Mn, Se, and Be in the coal gangue are 0.081, 17.444, 0.234, 63.329, 2.658, 43.697, 59.290, 427.460, 1.205, and 1.819 mg/kg, respectively; the enrichment sequence of heavy metal elements of coal gangue in geographical areas and geological ages are ordered as follows: South China region > North China region > Northeast China region > Northwest China region, P2 > C2-P1 > K1 > J1-2 > E-N. The results also show that Hg has a strong pollution risk, Cd has a moderate pollution risk, and the remaining eight heavy metals have minor pollution risks, and the overall ecological risk indices (RI) of heavy metals in different geographical areas are ordered as [Formula: see text] (South China) > [Formula: see text] (North China) > [Formula: see text] (Northeast China) > [Formula: see text] (Northwest China). Moreover, the hydrothermal process occurring in unique sedimentary environments during the formation period is a key factor for the regional heavy metal enrichment in coal gangue.

Automated Analysis of Choroidal Sublayer Morphologic Features in Myopic Children Using EDI-OCT by Deep Learning.

Purpose: The purpose of this study was to analyze the choroidal sublayer morphologic features in emmetropic and myopic children using an automatic segmentation model, and to explore the relationship between choroidal sublayers and spherical equivalent refraction (SER). Methods: We collected data on 92 healthy children (92 eyes) from the Ophthalmology Department of Peking University First Hospital. The data were allocated to three groups: emmetropia (+0.50 diopters [D] to -0.50 D), low myopia (-0.75 D to -3.00 D), and moderate myopia (-3.25 D to -5.75 D). We performed standardized optical coherence tomography (OCT) and developed a new segmentation technique to measure choroidal thickness (CT), large-vessel choroidal layer (LVCL), medium-vessel choroidal layer (MVCL), and small-vessel choroidal layer thickness (SVCL), and evaluated the choroidal vascular system (choroidal vascular volume [VV], choroidal vascular index [CVI], and choroidal vascular density [CVD]). Results: All choroidal sublayers (LVCL, MVCL, and SVCL) were significantly thinner in myopic than in emmetropic eyes (P < 0.05), the thinnest choroidal region being the nasal outer subfield (P < 0.05). In all choroidal regions of SVCL, a positive correlation was found between SER and thickness ratio (P < 0.001). In most subfields of MVCL, a similar correlation was found (P < 0.050), the exceptions being the two nasal subfields (0.050 < P < 0.300). In contrast, the thickness ratio of LVCL decreased in all subfields (P < 0.050). VV correlated with SER negatively in LVCL in all subfields (all P < 0.001) and most subfields in MVCL except for two temporal subfields (0.050 < P < 0.200). However, no significant correlations were found between CVI and SER in LVCL (P > 0.050) and MVCL (with the exception being the temporal inner subfield, P = 0.011). Conclusions: Thickness of choroidal sublayers was reduced with higher myopic SER, whereas changes in thickness ratio varied between sublayers. No significant correlations between CVI and SER suggested that both choroidal stromal and vascular volume decreases proportionately. Translational Relevance: Automatic segmentation model will be helpful for future clinical trials to quantify choroidal sublayer morphologic features in myopia.

Explanation of heavy metal pollution in coal mines of china from the perspective of coal gangue geochemical characteristics.

In the process of coal gangue surface accumulation and underground filling disposal, the heavy metals contained in coal gangue will inevitably precipitate out and migrate, which will cause serious environmental pollution. Seventy-five gangue samples of different geological ages are obtained from 25 coal mines in China. The contents of Hg, Pb, Cd, Cr, As, Cu, Zn, Mn, Se, and Be in gangue samples are determined. The enrichment coefficients of heavy metal elements in coal gangue are analyzed. The formation of heavy metal elements in gangue is studied by cluster analysis and principal component analysis. The results showed that the contents of Pb, Se, and As in gangue samples formed in Late Carboniferous and Early Permian are highest; the contents of Cr, Cd, Be, Cu, and Zn in gangue samples formed in Late Permian are highest. The later the formation age of coal gangue, the lower the overall enrichment of heavy metal elements. The contents of Cu, Be, Cd, Zn, and Cr in coal gangue are mainly controlled by sedimentation. The contents of Pb and Se are mainly affected by the affinity between heavy metal elements in coal gangue. The affinity between Mn and other heavy metal elements is weak, and sulfur had a certain influence on the content of Mn.

Preparation and Application of Self-Curing Magnesium Phosphate Cement Concrete with High Early Strength in Severe Cold Environments.

The early strength of magnesium phosphate cement (MPC) decreases sharply in severe cold environments ≤-10 °C, with the 2 h compressive strength falling to 3.5 MPa at-20 °C. Therefore, it cannot be used as a repair material for emergency repair construction in such environments. In this study, MPC is adapted for use in such cold environments by replacing part of the dead-burned magnesia (M) in the mixture with a small amount of light-burned magnesia (LBM) and introducing dilute phosphoric acid (PA) solution as the mixing water. The heat released by the highly active acid-base reaction of PA and LBM stimulates an MPC reaction. Moreover, the early strength of the MPC significantly improves with the increase in the Mg2+ concentration and the initial reaction temperature of the MPC paste, which enables MPC hardening in severe cold environments. Although the morphology of the reaction products of the MPC is poor and the grain plumpness and size of the struvite crystals are remarkably reduced, the early strength of MPC prepared in the severe cold environment is close to that of MPC prepared under normal temperature. Furthermore, the increases in the early reaction temperature and early strength of magnesium phosphate cement concrete (MPCC) are significantly improved when the PA concentration in the mixing water and the LBM/M ratio are 10% and 4-6% at -10 °C and 20% and 6-8% at -20 °C, respectively. Moreover, self-curing of MPCC can be realized even at -20 °C, at which temperature the 2 h and 24 h compressive strength of MPCC reach 36 MPa and 45 MPa, respectively.

Plasma Exosomal Long Noncoding RNA lnc-SLC2A12-10:1 as a Novel Diagnostic Biomarker for Gastric Cancer.

PURPOSE: Exosomes participate in cellular communications by transmitting active molecules, including long noncoding RNAs (lncRNAs) and are regarded as suitable candidates for disease diagnosis. This study aimed to identify gastric cancer (GC)-specific exosomal lncRNA and investigate the potential diagnostic value of plasma exosomal lncRNA in GC. PATIENTS AND METHODS: Exosomes from the culture media (CM) of four GC cells (GCCs) and human gastric epithelial cells were isolated. Exosomal RNA was extracted, and lncRNA microarray assay was performed to identify GC-specific exosomal lncRNAs. The expression levels of the candidate exosomal lncRNAs were validated in 120 subjects via quantitative reverse transcription PCR (qRT-PCR). The receiver operating characteristic (ROC) curve and area under curve were used to estimate the diagnostic capacity. We investigated the potential relationship between plasma exosomal lncRNA expression and the clinicopathological parameters of GC. RESULTS: A total of 199 exosomal lncRNAs were expressed at considerable higher levels in GCCs than those in normal controls, among which the top 10 upregulated lncRNAs were selected for further validation in cell, CM, and plasma. qRT-PCR revealed that lnc-SLC2A12-10:1 was remarkably upregulated in exosomes derived from patients with GC and GCCs. The area under the ROC curve was 0.776, which was higher than the diagnostic accuracies of CEA, CA 19-9, and CA72-4. The expression level of exosomal lnc-SLC2A12-10:1 was also significantly correlated with tumor size, TNM stage, lymph node metastasis, and degree of differentiation. The postoperative expression levels of exosomal lnc-SLC2A12-10:1 were lower compared with those of preoperative levels. CONCLUSION: Our study suggested that exosomal lnc-SLC2A12-10:1 may be a potential noninvasive biomarker for the diagnosis and prognosis monitoring of GC. Further large-scale studies are necessary to validate its performance in GC progression.

Intratumoral and Peritumoral Radiomics of Contrast-Enhanced CT for Prediction of Disease-Free Survival and Chemotherapy Response in Stage II/III Gastric Cancer.

BACKGROUND: We evaluated the ability of radiomics based on intratumoral and peritumoral regions on preoperative gastric cancer (GC) contrast-enhanced CT imaging to predict disease-free survival (DFS) and chemotherapy response in stage II/III GC. METHODS: This study enrolled of 739 consecutive stage II/III GC patients. Within the intratumoral and peritumoral regions of CT images, 584 total radiomic features were computed at the portal venous-phase. A radiomics signature (RS) was generated by using support vector machine (SVM) based methods. Univariate and multivariate Cox proportional hazards models and Kaplan-Meier analysis were used to determine the association of the RS and clinicopathological variables with DFS. A radiomics nomogram combining the radiomics signature and clinicopathological findings was constructed for individualized DFS estimation. RESULTS: The radiomics signature consisted of 26 features and was significantly associated with DFS in both the training and validation sets (both P<0.0001). Multivariate analysis showed that the RS was an independent predictor of DFS. The signature had a higher predictive accuracy than TNM stage and single radiomics features and clinicopathological factors. Further analysis showed that stage II/III patients with high scores were more likely to benefit from adjuvant chemotherapy. CONCLUSION: The newly developed radiomics signature was a powerful predictor of DFS in GC, and it may predict which patients with stage II and III GC benefit from chemotherapy.

Triaxial compression behaviour of gangue solid wastes under effects of particle size and confining pressure.

Underground coal mining leads to environmental problems such as gangue pollution, surface subsidence and soil erosion, etc. Solid backfilling coal mining (SBCM) can control the strata movement, reducing gangue discharge and environmental pollution in mining areas. Gangue solid wastes (GSW) are backfilled into the goaf space as the supports for the overburden strata in solid backfilling coal mining. In this case, GSW are under triaxial compression. The deformation characteristics of the GSW under this loading condition are the key factors determining the control efficiency of strata movement and surface subsidence. The influence of the particle size grade and the confining pressure condition on the deformation and breakage characteristics of the GSW is studied based on large-scale triaxial compression tests in this paper. Also, the effect of particle breakage on the deformation of the GSW is revealed. The results indicate that in the triaxial compression process, the GSW exhibits strain hardening characteristics and volume decrease under compressive loading. The maximum load-bearing stress is more sensitive to the confining pressure condition but less sensitive to the particle size grade. The maximum load-bearing stress increases linearly with the confining pressure. Particle breakage of the GSW is notably influenced by the particle size grade but almost independent of the confining pressure condition. The S1 specimen with a reasonable proportion has the minimum relative breakage index, while the S3 specimen that mainly contains large particles has the maximum relative breakage index. The research outcomes are significant to the understanding of the mechanical characteristics of GSW, the selection and preparation of the backfilling materials in the field practices and the ensurence of the backfilling efficiency.