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Background: We assessed the potential role of serial circulating tumor DNA (ctDNA) as a biomarker to monitor treatment response to primary systemic therapy (PST) in breast cancer and evaluated the predictive value of ctDNA to further identify patients with residual disease. Methods: We prospectively enrolled 208 plasma samples collected at three time points (before PST, after 2 cycles of treatment, before surgery) of 72 patients with stage Ⅱ-III breast cancer. Somatic mutations in plasma samples were identified using a customized 128-gene capture panel with next-generation sequencing. The correlation between early change in ctDNA levels and treatment response or long-term clinical outcomes was assessed. Results: 37 of 72 (51.4%) patients harbored detectable ctDNA alterations at baseline. Patients with complete response showed a larger decrease in ctDNA levels during PST. The median relative change of variant allele fraction (VAF) was −97.4%, −46.7%, and +21.1% for patients who subsequently had a complete response (n = 11), partial response (n = 11), and no response (n = 15) (p = 0.0012), respectively. In addition, the relative change of VAF between the pretreatment and first on-treatment blood draw exhibited the optimal predictive value to tumor response after PST (area under the curve, AUC = 0.7448, p = 0.02). More importantly, early change of ctDNA levels during treatment have significant prognostic value for patients with BC, there was a significant correlation between early decrease of VAF and longer recurrence-free survival compared to those with an VAF increase (HR = 12.54; 95% CI, 2.084 to 75.42, p = 0.0063). Conclusion: Early changes of ctDNA are strongly correlated with therapeutic efficacy to PST and clinical outcomes in BC patients. The integration of preoperative ctDNA evaluation could help improving the perioperative management for BC patients receiving PST.

Survey of road cracks in a timely, complete, and accurate way is pivotal to pavement maintenance planning. Motivated by the increasingly heavy task of identifying cracks, researchers have developed extensive crack segmentation models based on Deep learning (DL) methods with significantly different levels of accuracy, efficiency, and generalizing capacity. Although many of the models provide satisfying detection performance, why these models work still needs to be determined. The objective of this study is to survey recent advances in automated DL crack recognition and provide evidence for their underlying working mechanism. We first reviewed 54 DL crack recognition methods to summarize critical factors in these models. Then, we conducted a performance evaluation of fourteen famous semantic segmentation models using the quantitative metrics: F-1 score and mIoU. Then, the effective receptive field and class activation map of the included models are visualized to demonstrate the training results as qualitative evaluation. Based on the literature review and comparison results, larger kernel size, feature fusion, and attention module all contribute to the improvement of model performance. Striking a balance between increasing the effective receptive field and computational/memory efficiency is the key to designing DL crack segmentation models. Finally, some potential directions and suggestions for future development are provided, such as developing semi-supervised or unsupervised learning for the high cost of pixel-level labeling.

Warm-mix asphalt (WMA) has been gaining popularity in sustainable road engineering due to its reduced environmental impacts. However, uncertainties remain regarding its long-term pavement performance compared to hot mix asphalt (HMA). Especially, the critical factors influencing the field performance of WMA are yet to be determined. Hence, this study analyzes the long-term field performance of pavement overlaid with WMA, using data from the Specific Pavement Studies 10 (SPS-10) of the long-term pavement performance (LTPP) program. The evaluation includes 58 field sections from nine projects across the United States, encompassing two WMA types (foaming processing and chemical additive) and their corresponding HMA control sections. Performance indicators such as alligator cracking, longitudinal cracking in the wheel path, transverse cracking, rutting, and roughness (measured by the international roughness index, IRI) were considered. Per-state and per-climate region Bayesian multilevel models were built to account for site- and region-level heterogeneity. The study results demonstrated that pavement with WMA performed equally well to the HMA counterparts under similar conditions, indicating that their potential for widespread application in meeting both performance standards and environmental conservation requirements. Also, WMA technologies did not differ in pavement performance, and thus the field performance of WMA was not a dominant factor in deciding WMA technology types. Furthermore, Bayesian multilevel models proved highly effective in performance data varying across construction sites and regions.

This study attempted to evaluate the potential for biofilm formation and the probiotic properties of lactic acid bacteria (LAB) isolated from the Carassius auratus intestine and to determine their antibacterial activity against crucial injurious bacteria of fish. The biological features test was carried out to obtain LAB with well-resistant pH, trypsin, bile and antibiotic challenge, and biofilm formation capacity. The most promising LAB isolates, y11 and y78 were identified as Lactobacillus johnsonii and Weissella confusa using 16S ribosomal RNA gene sequencing. We discovered that oral LAB additives improved immunity in the C. auratus by increasing immune-related expression of immunoglobulin M (IgM), superoxide dismutase (SOD), alkaline phosphatase (AKP), and lysozyme (LYS) in serum and interleukins (IL-10 and IL-1β), interferon-γ (IFN-γ), and tumor necrosis factor-α (TNF-α) in organs. After the introduction of Aeromonas veronii TH0426 for 15 days, the survival rate of C. auratus was determined as follows: the protection rate of group y11 was 45 %, and group y78 was 65 % when challenged with 109 CFU/mL density. This experiment successfully selected two LAB strains as the bioprotective agents and provided theoretical support for further LAB application in aquaculture.

Introduction: Contrary to the traditional recognition that CO2 has large injectivity (the ratio of CO2 injection volume to pressure drop) in low permeability oil reservoirs to keep the formation pressure at a high level, the CO2 injection rate usually cannot attain the set value. It is essential to study the factors that influence CO2 injectivity and propose the optimal strategies to improve the CO2 injectivity.Methods: Therefore, in this study, several core samples collected from low permeability oil reservoirs are used to experimentally investigate the influences of CO2 injection rate, formation permeability, pressure and water saturation on CO2 injectivity, and the corresponding pressure drop, oil and gas production are examined. To determine the primary factor that influences the CO2 injectivity, orthogonal experimental design (ODE) and numerical simulations are utilized. In addition, to improve CO2 injectivity, the techniques of mini-fracturing and radial perforation are presented, and the threshold values for these two parameters are determined.Result and discussion: The results demonstrate that according to the magnitude of the extent that influences CO2 injectivity, the rank for the above factors is CO2 injection rate, reservoir pressure, formation water saturation and permeability. The oil recovery is mainly influenced by CO2 injection rate and formation permeability, and the influences of reservoir pressure and water saturation on oil recovery are smaller. The threshold values for radial perforation and fracture half-length are 25 m and 50m, respectively, which can provide some guidance for the strategies that should be taken to improve the CO2 injectivity and recover more oil from low permeability oil reservoirs.

As terrestrial oilfields continue to be explored, the difficulty of exploring new oilfields is constantly increasing. The ocean, which contains abundant oil and gas resources, has become a new field for oil and gas resource development. It is estimated that the total amount of oil resources contained in ocean areas accounts for 33% of the global total, while the corresponding natural gas resources account for 32% of the world’s resources. Current prediction methods, tailored to land oilfields, struggle with offshore differences, hindering accurate forecasts. With oilfield advancements, a vast amount of rapidly generated, complex, and valuable data has piled up. This paper uses AI and GRN-VSN NN to predict offshore oilfield indicators, focusing on model-based formula fitting. It selects highly correlated input indicators for AI-driven prediction of key development metrics. Afterwards, the Shapley additive explanations (SHAP) method was introduced to explain the artificial intelligence model and achieve a reasonable explanation of the measurement’s results. In terms of crude-oil extraction degree, the performance levels of the Long Short-Term Memory (LSTM) neural network, BP neural network, and ResNet-50 neural network are compared. LSTM excels in crude-oil extraction prediction due to its monotonicity, enabling continuous time-series forecasting. Artificial intelligence algorithms have good prediction effects on key development indicators of offshore oilfields, and the prediction accuracy exceeds 92%. The SHAP algorithm offers a rationale for AI model parameters, quantifying input indicators’ contributions to outputs.

Eucommia ulmoides (E. ulmoides) is a relict plant belonging to the Eucommiaceae family. Each part of E. ulmoides including the bark, leaf, staminate flower, and seed, contains various active ingredients, that are edible and have medicinal value. This review summarizes the literatures on the functional properties of flavonoids, phenols, terpenoids, and polysaccharides in different parts of E. ulmoides. The prospects for application of the different parts of E. ulmoides as functional foods are also discussed. This review provides a reference for further research and development of the medicinal application of E. ulmoides.

BackgroundThe pathogenesis of silicosis is complex and treatment methods are limited. SiO2-induced increase of transforming growth factor-β1 (TGF-β1) can activate fibroblasts to promote collagen deposition, ultimately leading to fibrosis. Previous studies have confirmed that lipid metabolism plays an important role in the progression of silicosis. Peroxisome proliferator-activated receptor γ coactivator 1α (PGC1α) mediates mitochondrial dysfunction and lipid metabolism pathways in diabetic models, but its role in silicosis has not been elucidated. ObjectiveTo investigate the effect of PGC1α on lipid metabolism disorder of macrophages induced by SiO2 and its effect on the progression of silicosis fibrosis. Methods(1) Macrophages were divided into four groups by transfecting and silencing PGC1α and its control sequence in macrophages and followed by SiO2 stimulation: negative control group (transfected with si-NC for 48 h), si-PGC1α group (transfected with si-PGC1α for 48 h), SiO2 stimulation group (stimulated with 50 μg·mL−1 SiO2 for 36 h after transfection with si-NC for 48 h), and si-PGC1α+SiO2 group (stimulated with 50 μg·mL−1 SiO2 for 36 h after transfection with si-PGC1α for 48 h). Western blot and cell immunofluorescence were used to test PGC1α expression, 4,4-difluoro-1,3,5,7,8-pentamethyl-4-bora-3a,4a-diaza-s-indacene (BODIPY 493/503) and total cholesterol (TC) and free cholesterol (FC) kits were used to test lipid accumulation, and the Oroboros2k-Oxygraph respiratory test system (O2K) was used to assess the effects of PGC1α on mitochondrial respiratory chain. ELISA kits were used to test TGF-β1 expressed in the macrophage supernatant. (2) Lung fibroblasts were divided into the same four groups as above, and stimulated with the supernatant of macrophages in the above groups. The expression of collagen Ι (COL Ι), E-cadherin (Eca), and fibronectin (FN) were detected by cell immunofluorescence and Western blot to further evaluate the effect of silencing PGC1α on fibrosis. ResultsThe protein expression level of PGC1α stimulated by SiO2 was decreased, and the relative expression level of PGC1α was 0.78 times that of the control group (P

Abstract Aiming at the problem of multi-object detection such as target occlusion and tiny targets in road scenes, this paper proposes an improved YOLOv5 multi-object detection model based on ML-AFP (multi-level aggregation feature perception) mechanism. Since tiny targets such as non-motor vehicle and pedestrians are not easily detected, this paper adds a micro target detection layer and a double head mechanism to improve the detection ability of tiny targets. Varifocal loss is used to achieve a more accurate ranking in the process of non-maximum suppression to solve the problem of target occlusion, and this paper also proposes a ML-AFP mechanism. The adaptive fusion of spatial feature information at different scales improves the expression ability of network model features, and improves the detection accuracy of the model as a whole. Our experimental results on multiple challenging datasets such as KITTI, BDD100K, and show that the accuracy, recall rate and mAP value of the proposed model are greatly improved, which solves the problem of multi-object detection in crowded road scenes.

Traffic load identification for bridges is of great significance for overloaded vehicle control as well as the structural management and maintenance in bridge engineering. Unlike the conventional load identification methods that always encounter problems of ill-condition and difficulties in identifying multi parameters simultaneously when solving the motion equations inversely, a novel strategy is proposed based on smart sensing combing intelligent algorithm for real-time traffic load monitoring. An array of lead zirconium titanate sensors is applied to capture the dynamic responses of a beam bridge, while the Long Short-Term Memory (LSTM) neural network is employed to establish the mapping relations between the dynamic responses of the bridge and the traffic load through data mining. The results reveal that, with the real-time strain responses fed into the LSTM network, the speed and magnitude of the moving load may be identified simultaneously with high accuracy when compared to the practically applied load. The current method may facilitate highly efficient identification of the time-varying characteristics of moving loads and may provide a useful tool for long-term traffic load monitoring and traffic control for in-service bridges.

The effects of ball milling on the physicochemical, functional, and emulsification characteristics of Polygonatum sibiricum insoluble dietary fiber (PIDF) were investigated. Through controlling milling time (4, 5, 6, 7, and 8 h), five PIDFs (PIDF-1, PIDF-2, PIDF-3, PIDF-4, and PIDF-5) were obtained. The results showed that ball milling effectively decreased the particle size and increased the zeta-potential of PIDF. Scanning electron microscope results revealed that PIDF-5 has a coarser microstructure. All PIDF samples had similar FTIR and XRD spectra. The functional properties of PIDF were all improved to varying degrees after ball milling. PIDF-3 had the highest water-holding capacity (5.12 g/g), oil-holding capacity (2.83 g/g), water-swelling capacity (3.83 mL/g), total phenol (8.12 mg/g), and total flavonoid (1.91 mg/g). PIDF-4 had the highest ion exchange capacity. Fat and glucose adsorption capacity were enhanced with ball milling time prolongation. PIDF-5 exhibited a contact angle of 88.7° and lower dynamic interfacial tension. Rheological results showed that PIDF-based emulsions had shear thinning and gel-like properties. PE-PIDF-5 emulsion had the smallest particle size and the highest zeta-potential value. PE-PIDF-5 was stable at pH 7 and high temperature. The findings of this study are of great significance to guide the utilization of the by-products of Polygonatum sibiricum.

Exploring the influencing factors of construction quality management is the key to ensuring the quality of rural drinking water safety projects. Based on grounded theory, the influencing factors were identified and 65 relevant staff were selected by the objective sampling method for in-depth interviews to obtain the original data. In this study, 34 initial concepts, 18 main categories, and five core categories were collected and extracted for the rural drinking water project's safety engineering and construction quality management evaluation system. Furthermore, the incremental model of influencing factors on construction quality management performance of rural drinking water safety projects was established by the Decision-Making Trial and Evaluation Laboratory–Interpretive Structural Modeling (DEMATEL-ISM) model. Through calculation and analysis, the key influencing factors of construction quality management performance of rural drinking water safety projects were identified as controls on common quality problems, quality specification implementation, leadership level, acceptance management, design disclosure and modification, and human environment. Countermeasures and suggestions are proposed to improve the construction quality management performance of rural drinking water safety construction projects. HIGHLIGHTS Construction quality management evaluation systems for rural drinking water safety projects were established based on grounded theory.; Based on the DEMATEL-ISM model, the quality management performance evaluation model of rural drinking water safety project construction was constructed, which is convenient for clarifying the relationship between influencing elements at different levels in the system.;

Steam flooding is an important thermal recovery method for heavy oil reservoirs, and convective heating technology is used to fracture oil shale reservoirs with good results. This paper reviews the main prediction methods, optimization approaches for steam flooding performance, and its application in fractured oil shale reservoirs. The prediction methods include experimental, numerical simulation, and statistical models. These provide insights into steam override, heat transfer, and production dynamics. To optimize steam flooding, parameters like quality, temperature, injection rate, and allocation need to be coordinated based on reservoir conditions and monitoring data. Real-time injection control, economic analysis, and sweep efficiency improvements should also be considered in optimization workflows. Although progress has been made, more field studies are needed to establish systematic optimization practices utilizing advanced technologies. This review summarizes the key developments in steam flooding modeling and optimization, providing a reference for further research and field applications.

Highlights 1. CHCHD4 was highly expressed in LUAD. 2. Knockdown of CHCHD4 suppressed the malignant phenotype of LUAD. 3. USF1 upregulated CHCHD4 and promoted LUAD progression. 4. Knockdown of CHCHD4 inhibited LUAD progression.

Objective This meta-analysis aimed to update knowledge about the association between the SLC4A7 variant rs4973768 and breast cancer incidence. Methods Studies were identified from relevant digital databases. Fixed- or random-effects models were used to calculate odds ratios and 95% confidence intervals. Statistical Q and I 2 tests and sensitivity analyses were used to detect interstudy heterogeneity and test the statistical stability of overall estimates, respectively. Egger’s tests were applied to detect publication bias among included studies. In silico analysis was used to ascertain increased expression of SLC4A7 mRNA in rs4973768 with the mutant allele. Trial sequential analysis was used to calculate the study’s sample size. Results The overall odds ratios reflected a positive correlation between the SLC4A7 rs4973768 polymorphism and susceptibility to breast cancer in five genetic comparisons of alleles T and C, and tests revealed significant heterogeneity in the allele comparison. After stratification by ethnicity, heterogeneity in Asian and White populations substantially decreased (Ph = 0.984, I 2 = 0%) and remained stable (Ph = 0.083, I 2 = 46.3%), respectively. The mutant allele was associated with increased expression of SLC4A7 mRNA in rs4973768. The cumulative z curve indicated that our conclusions were robust. Conclusions Our updated consequence shows that the SLC4A7 rs4973768 polymorphism is associated with increased breast cancer risk.

The timely identification of differential settlement of track foundations is of great significance for the safety of train operation and the maintenance of track structures. However, traditional monitoring techniques cannot meet the requirements of efficient, real-time, and automatic monitoring of track foundation settlement. In order to solve these problems, a real-time identification method based on a gated recurrent unit (GRU) neural network is proposed for the differential settlement of track foundations monitoring. According to parameter sensitivity analysis, the vertical acceleration of the vehicle is selected as the known data fed into the GRU network for differential settlement identification. Then the GRU network is employed to establish the nonlinear relationship between the vertical acceleration of the vehicle and the differential settlement of the track foundation. The results indicate that the longitudinal continuous differential settlement distribution curve of track foundations could be accurately identified with GRU neural network through the real-time vibration response of the vehicle–track. The current method may provide a new means for the real-time and efficient identification of the differential settlement of track foundations.

Stainless steel is a notoriously difficult-to-machine material, with challenges such as hard-to-break chips and severe tool wear. To address these issues, a finishing indexable insert has been designed and developed specifically for stainless steel. This tool, named HMF, was compared to commercial tools (NF4, BF) in terms of its curved groove structure and cutting performance using SEM (scanning electron microscope Sigma500), 3D scanning (KEYENCE-VR 5000) and a profiler (Mitutoyo C-200). The HMF tool utilizes a curved edge with a curved chip breaker, and a chip-breaking bump on the tool nose. The groove parameters of the HMF insert are as follows: cutting edge angle of 12°, chip breaker groove width of 1.89 mm, back wall height of 0.095 mm, and anti-chip angle of 4°49’. 3D scanning of the chip break site reveals that the HMF chip break has a higher bump and a more pronounced chip rolling effect. HMF tool chip-breaking experiments show that it has ideal chip-breaking performance in the finishing range of ap = 0.6–1.0 mm, and f = 0.1–0.25 mm r ^−1 . Chip analysis shows that the HMF chip curl frequency increases and the chip curl is tighter as the feed rate increases, and the curl radius gradually decreases when the feed rate is greater than 0.15 mm r ^−1 . The results of the wear performance study are as follows: all three tools show rake face crater wear when cutting stainless steel. A small amount of built-up edge appears on the HMF cutting edge. The wear life of HMF is close to NF4 and better than BF; the wear of BF is faster in the later stages of wear.

Carbonate reservoirs are highly heterogeneous. During waterflooding stage, the channeling phenomenon of displacing fluid in high-permeability layers easily leads to early water breakthrough and high water-cut with low recovery rate. To quantitatively characterize the inter-well connectivity parameters (including conductivity and connected volume), we developed an inter-well connectivity model based on the principle of inter-well connectivity and the geological data and development performance of carbonate reservoirs. Thus, the planar water injection allocation factors and water injection utilization rate of different layers can be obtained. In addition, when the proposed model is integrated with automatic history matching method and production optimization algorithm, the real-time oil and water production can be optimized and predicted. Field application demonstrates that adjusting injection parameters based on the model outputs results in a 1.5% increase in annual oil production, which offers significant guidance for the efficient development of similar oil reservoirs. In this study, the connectivity method was applied to multi-layer real reservoirs for the first time, and the injection and production volume of injection-production wells were repeatedly updated based on multiple iterations of water injection efficiency. The correctness of the method was verified by conceptual calculations and then applied to real reservoirs. So that the oil field can increase production in a short time, and has good application value.

(1) Mud pulser carbide rotors, as a core component of ground communication in crude oil exploration, are often subjected to mud erosion and acid corrosion, resulting in pitting pits on the surface, which affects the accuracy. The purpose of this study was to investigate the acid corrosion and erosion behavior of cemented carbide materials and provide a reference for the wider application of cemented carbide materials in the petrochemical industry. (2) Experimental samples of tungsten–cobalt carbide were sintered at a low pressure by powder metallurgy. The petrochemical application environment was simulated by accelerated salt spray corrosion and solid slurry erosion with the aid of acidic copper, and the experimental phenomena were analyzed by SEM (scanning electron microscope), EDS (Energy Dispersive Spectroscopy), and XRD (X-ray diffraction). (3) The experimental results show that the coercivity of the pitted cobalt-cemented tungsten carbide prepared in this study was 17.89 KA/m, and the magnetic saturation strength was 14.42 G·cm3/g. The corrosion rate was the fastest during the acidic copper acceleration experiments from 4 h to 16 h, and the corrosion products of WCo3 and Co3O4 were generated on the corrosion surface. The maximum erosion rate of 0.00104 in the erosion experiment corresponds to a corrosion sample with a corrosion time of 36 h. (4) Therefore, the coercive magnetic force and magnetic saturation strength could be derived from the prepared carbide hard phase grains and carbon content in the appropriate range. The corrosion product in the corrosion process slowed the corrosion rate, and a large amount of cobalt and a small amount of tungsten was lost by oxidation during the corrosion process. The corrosion time had the greatest effect on the erosion performance of the carbide, and the long corrosion time led to surface sparseness, which reduced the erosion resistance.

An AlCrSiWN coating was prepared on a cemented carbide substrate by the arc ion plating technology. The optimization of the coating process was carried out by matrix analysis of orthogonal experiments to calculate the influence of the process parameters on the hardness, bonding and roughness indexes of the coating, determine the optimal coating process parameters, and focus on the influence of the bias voltage on the microscopic morphology, mechanical properties and friction properties of the coating. The results showed that the influence of the process parameters on the indexes of the orthogonal experiments was in the following order: bias voltage > arc current > N2 flow rate. The optimal solution was achieved with an arc current of 160 A, a bias voltage of −80 V, and a N2 flow rate of 600 sccm. Properly increasing the bias voltage improved the microscopic morphology, mechanical properties and wear resistance of the coating. When the bias voltage was −80 V, the coating surface presented fewer large particles with a less uniform size and no obvious crater defects; in addition, the cross-sectional structure changed from grape-like to columnar, and the coating had higher hardness, lower roughness and better bond strength. In the friction performance test, coating at a −80 V bias voltage showed better wear resistance, which was reflected in lower friction coefficient and wear, and the wear mechanism mainly consisted of adhesion and oxidation wear.

Most multilayer sandstone reservoirs in the Bohai Sea have already entered the middle or high water cut production stage with large amounts of remaining oil being scattered distributed. Therefore, there is an urgent need to find a suitable countermeasure to reduce water cut and increase oil recovery. In this study, taking the narrow-channel reservoirs in the M oilfield as an example, we qualitatively described the sand body scale and the contact relationships between different sand bodies, in addition to carefully analyzing the material base and remaining oil distribution characteristics. Accordingly, we proposed a countermeasure based on the injection-production structural adjustment to reduce water cut and increase oil recovery from high water cut, narrow-channel reservoirs. Herein, three optimization strategies were developed based on the proposed development mode: a seepage field optimization strategy was developed based on the quantified injection-production index; a well pattern optimization strategy for narrow-channel reservoirs was developed to overcome the production energy refueling problem; an injection-production measure optimization strategy was developed to tap the different types of remaining oil. Additionally, the well pattern optimization and injection-production optimization strategies were integrated to optimize and adjust the seepage field system. The findings reported herein this paper help understand the development of similar offshore oilfields with a high water cut.

Background The homeobox gene family, encoding a specific nuclear protein, is essential for embryonic development, differentiation, and homeostasis. The role of the HOXB3 protein varies in different tumors. This study aims to explore the role of the HOXB3 gene in breast cancer. Method Differentially expressed genes were screened by analyzing metastatic breast cancer gene chip data from TCGA and GEO databases. The function of the selected HOXB3 gene was also analyzed in different databases and through molecular biology methods, such as qRT-PCR, western blot and IF to verify bioinformatics findings. Results Both bioinformatics analyses and western blot showed that HOXB3 was lost in breast cancer compared to normal breast tissue. Survival analysis also showed that lower expression of HOXB3 was associated with poor prognosis. Bioinformatics analyses further showed that HOXB3 was positively correlated with hormone receptors. Metascape for GO analysis of GEO data provided possible mechanisms that HOXB3 could positively regulate cell adhesion, inhibit cell proliferation and activate immune response in breast cancer; moreover, GSEA included several cancer-associated pathways. Conclusion In summary, HOXB3 expression was decreased in breast cancer, and it was associated with poor prognosis. It might become a new biomarker to predict prognosis of breast cancer.

Objective Body mass index (BMI) is a risk factor associated with breast cancer in postmenopausal women. This study aimed to identify the associations of BMI with clinical characteristics and management of breast cancer in female Chinese patients. Methods Clinicopathological information on 1296 women who were diagnosed with breast cancer was collected at our hospital. We recorded the clinicopathological characteristics, molecular phenotypes, manner of diagnosis, implementation rate of preoperative examinations, and surgical method used. Results Significant differences were found in the tumor size, disease stage, manner of diagnosis, implementation rate of preoperative examinations, and the surgical method among different BMI groups. In premenopausal patients, significant differences were found in the distribution of molecular phenotypes and surgical approach among different BMI groups. In postmenopausal patients, different BMI groups showed significant differences in the tumor size, disease stage, distribution of molecular phenotypes, manner of diagnosis, rate of implementation of preoperative mammography, and surgical method. Conclusion Higher BMI is associated with a larger tumor size, more advanced disease stage, diagnosis by physical examination, higher implementation rate of preoperative examinations, and lower radical surgery rate in Chinese women with breast cancer. However, the relationship between BMI and molecular phenotypes differs between pre- and postmenopausal women.

Three types of organic cage compounds, namely, cucurbit[6]uril (Q[6]), hemicucurbit[6]uril (HQ[6]), and β-cyclodextrin (BC), with different cavity structures as heterogeneous nucleation agents were selected for a polypropylene (PP) foaming injection molding process. The experimental results showed that Q[6] with a “natural” cavity structure possessed the best nucleation efficiency of these three cage compounds. The nucleation mechanism of organic cage compounds was explored through classical nucleation theory, molecular structure, and in situ visual injection molding analysis.

More and more researches have been carried out recently on Weigh-In-Motion (WIM) technology for solving the traffic safety problems caused by overload. In this article, we aim to study the measurement accuracy of the WIM system. Based on the electromechanical theory and elastic half-space method, we establish a theoretical model of multi-layer structure to investigate the correlation between the output voltage of the piezoelectric sensor and the applied force. In addition, we performed cyclic and moving load experiments to verify the accuracy of the analytical calculations. The load magnitude identified by this theoretical model matched the experiments very well, which shows that this model is effective for the WIM system. In addition, we proved that the load frequency is an important factor affecting the measurement accuracy of the sensor, which further enables us to design more suitable sensors for certain use scenarios.

Background and objective Traditional Chinese medicine is an approach for malignant tumor treatment with Chinese characteristics. The aim of this study is to investigate the inhibitory effects of Maimendong & qianjinweijing decoction extract on A549 human lung cancer cell line proliferation and explored its probable molecular mechanisms. Methods A549 cells were treated with drugs in different does and time. The effects on the proliferation of A549 cells were detected by MTT assay and clonogenic assay in vitro. Cell cycle was analyzed by flow cytometry. Morphological changes of the apoptosis of cancer cells were observed by Hochest 33258 staining. Western blot was performed to detect apoptosis-related gene expression. Results Ethyl acetate extract inhibited the growth of A549 cells but not in HFL-1 cells. Compared with controls, administration of 10 μg/mL ethyl acetate extract resulted in 73.86% decrease in colony formation (P < 0.01), apoptotic rates of 33.86% (P < 0.01), and morphological changes of apoptosis in A549 cells. The expression of anti-apoptotic protein EGFR and ERK were significantly down-regulated (P < 0.01). Conclusion Ethyl acetate extract might inhibit proliferation and induce apoptosis in A549 cells via downregulation of EGFR/ERK signal transduction pathway. Therefore, ethyl acetate extract should be further separated in order to identify the material fundamentals on anti-cancer effect.

Fracture-cave carbonate reservoirs occur widely in source rocks and are prospects for exploitation worldwide. However, the presence of massive caves and multiscale fracture systems results in extremely complex fluid flow patterns. Therefore, in this paper, a discrete network model for fracture-cave reservoirs was established to study fluid flow characteristics and pressure distributions in complex flow regimes. In this study, the cave system was treated as a free-flow region, and the fluid flow in fracture systems followed the Navier-Stokes and Darcy equations, respectively. After discrete modeling, the Galerkin finite element method was used for numerical calculation of the single-phase free flow; the method maintains a high-precision result with low grid orientations during the simulation. In addition, because only one linear equation requires solving at each step, the solution is obtained quickly. Moreover, based on the proposed discrete media network model of fracture-cave reservoirs and the finite element numerical calculation method, a corresponding simulator was also developed. The finite element numerical simulation method based on the characteristic-based split (CBS) algorithm has proven to be applicable to complex flow problems in fracture-cave reservoirs.

Railway tunnel clearance is directly related to the safe operation of trains and upgrading of freight capacity. As more and more railway are put into operation and the operation is continuously becoming faster, the railway tunnel clearance inspection should be more precise and efficient. In view of the problems existing in traditional tunnel clearance inspection methods, such as low density, slow speed and a lot of manual operations, this paper proposes a tunnel clearance inspection approach based on 3D point clouds obtained by a mobile laser scanning system (MLS). First, a dynamic coordinate system for railway tunnel clearance inspection has been proposed. A rail line extraction algorithm based on 3D linear fitting is implemented from the segmented point cloud to establish a dynamic clearance coordinate system. Second, a method to seamlessly connect all rail segments based on the railway clearance restrictions, and a seamless rail alignment is formed sequentially from the middle tunnel section to both ends. Finally, based on the rail alignment and the track clearance coordinate system, different types of clearance frames are introduced for intrusion operation with the tunnel section to realize the tunnel clearance inspection. By taking the Shuanghekou Tunnel of the Chengdu–Kunming Railway as an example, when the clearance inspection is carried out by the method mentioned herein, its precision can reach 0.03 m, and difference types of clearances can be effectively calculated. This method has a wide application prospects.

Unlike existing studies focused on the causal relationship between electricity consumption and economic growth at the macro level, this paper uses monthly data from January 2006 to December 2015 and applies the correlation coefficient, as well as Kullback-Leibler (KL) divergence, to study the time difference relationship between sectoral electricity consumption and economic growth. The empirical results draw some main findings as follows: First, the time difference relationships show diversity at the sector level but will form a kind of overall characteristic between economic growth and total electricity consumption. Secondly, not all sectors have a remarkable correlation between sectoral electricity consumption and economic growth as only part of them have reasonable values to describe the time difference relationship. Thirdly, the results present both diversity and aggregation at the industry level, while lagging sectors mainly concentrate in the manufacturing industry. The relationship between sectoral electricity consumption and economic growth can be further explored and described from a new perspective based on the results. Further, the trend of economic development and sectoral electricity consumption can be predicted to help policy-makers formulate proper policies.

Introduction: Contrary to the traditional recognition that CO2 has large injectivity (the ratio of CO2 injection volume to pressure drop) in low permeability oil reservoirs to keep the formation pressure at a high level, the CO2 injection rate usually cannot attain the set value. It is essential to study the factors that influence CO2 injectivity and propose the optimal strategies to improve the CO2 injectivity. Methods: Therefore, in this study, several core samples collected from low permeability oil reservoirs are used to experimentally investigate the influences of CO2 injection rate, formation permeability, pressure and water saturation on CO2 injectivity, and the corresponding pressure drop, oil and gas production are examined. To determine the primary factor that influences the CO2 injectivity, orthogonal experimental design (ODE) and numerical simulations are utilized. In addition, to improve CO2 injectivity, the techniques of mini-fracturing and radial perforation are presented, and the threshold values for these two parameters are determined. Result and discussion: The results demonstrate that according to the magnitude of the extent that influences CO2 injectivity, the rank for the above factors is CO2 injection rate, reservoir pressure, formation water saturation and permeability. The oil recovery is mainly influenced by CO2 injection rate and formation permeability, and the influences of reservoir pressure and water saturation on oil recovery are smaller. The threshold values for radial perforation and fracture half-length are 25 m and 50m, respectively, which can provide some guidance for the strategies that should be taken to improve the CO2 injectivity and recover more oil from low permeability oil reservoirs. [ABSTRACT FROM AUTHOR]

The fractured-vuggy carbonate oil resources in the western basin of China are extremely rich. The connectivity of carbonate reservoirs is complex, and there is still a lack of clear understanding of the development and topological structure of the pore space in fractured-vuggy reservoirs. Thus, effective prediction of fractured-vuggy reservoirs is difficult. In view of this, this work employs adaptive point cloud technology to reproduce the shape and capture the characteristics of a fractured-vuggy reservoir. To identify the complex connectivity among pores, fractures, and vugs, a simplified one-dimensional connectivity model is established by using the meshless connection element method (CEM). Considering that different types of connection units have different flow characteristics, a sequential coupling calculation method that can efficiently calculate reservoir pressure and saturation is developed. By automatic history matching, the dynamic production data is fitted in real-time, and the characteristic parameters of the connection unit are inverted. Simulation results show that the three-dimensional connectivity model of the fractured-vuggy reservoir built in this work is as close as 90% of the fine grid model, while the dynamic simulation efficiency is much higher with good accuracy. [ABSTRACT FROM AUTHOR]

The study of heterogeneous and complex oil and gas reservoirs poses a significant challenge due to the problem of unstable seepage flow. This research investigates the non-linear seepage flow patterns in such reservoirs, with a particular focus on ultra-low permeability tight gas reservoirs, using fractal theory. By analysing the scale invariance in the seepage flow of ultra-low permeability tight gas reservoirs, we have derived a fractal geometric expression based on the capillary pressure curve. This expression was integrated with mercury intrusion porosimetry to study the fractal dimension of ultra-low permeability reservoirs. Our experimental results indicate the presence of fractal characteristics in ultra-low permeability tight gas reservoirs. Based on this, we have investigated the fractal nature of matrix porosity and fractures and their effect on the stress sensitivity of ultra-low permeability tight gas reservoirs. This led to the development of a new fractal model for seepage flow in these reservoirs, which takes into account the non-Darcy flow behaviour of gas in nanoscale pores. The mathematical model was simplified using point source solutions and regular perturbation methods. The analysis shows that the fractal parameters of the matrix and fractures, together with the adsorption coefficients and the permeability modulus, have a significant influence on the dynamic pressure behaviour. The effects of slip and diffusion coefficients and stress sensitivity on the dynamics were also investigated. The pressure dynamics curves of ultra-low permeability tight gas reservoirs show distinct differences from those of homogeneous reservoirs and conventional dual porosity reservoirs. This study not only reveals the unique dynamic pressure characteristics of ultra-low permeability tight gas reservoirs, but also shows that the traditional reservoir models are, under certain conditions, special cases of the model proposed in this paper. [ABSTRACT FROM AUTHOR]