Development of a trench cutting re-mixing deep wall method model test device

The trench cutting re-mixing deep wall (TRD) is a new type of underground waterproof curtain. Mixing uniformity is the key index affecting the efficiency and quality of this method. However, because of many influencing factors, existing theories cannot be used to express the relationship between various factors and mixing uniformity. By analyzing the cutting and mixing process of the TRD method, the main factors affecting the uniformity of the mixing were obtained. A model test device was designed and manufactured, based on Buckingham's pi theorem. The validity of the model test device was verified through a comparative analysis of model and field test results. The model test device was demonstrated to be able to simulate the mixing process of the TRD method. The results provide guidance for promotion and better application of the TRD method

Accurate Single Stage Detector Using Recurrent Rolling Convolution

Most of the recent successful methods in accurate object detection and localization used some variants of R-CNN style two stage Convolutional Neural Networks (CNN) where plausible regions were proposed in the first stage then followed by a second stage for decision refinement. Despite the simplicity of training and the efficiency in deployment, the single stage detection methods have not been as competitive when evaluated in benchmarks consider mAP for high IoU thresholds. In this paper, we proposed a novel single stage end-to-end trainable object detection network to overcome this limitation. We achieved this by introducing Recurrent Rolling Convolution (RRC) architecture over multi-scale feature maps to construct object classifiers and bounding box regressors which are "deep in context". We evaluated our method in the challenging KITTI dataset which measures methods under IoU threshold of 0.7. We showed that with RRC, a single reduced VGG-16 based model already significantly outperformed all the previously published results. At the time this paper was written our models ranked the first in KITTI car detection (the hard level), the first in cyclist detection and the second in pedestrian detection. These results were not reached by the previous single stage methods. The code is publicly available.Comment: CVPR 201

Estrogen Enhances the Expression of the Multidrug Transporter Gene ABCG2-Increasing Drug Resistance of Breast Cancer Cells through Estrogen Receptors.

BACKGROUND: Multidrug resistance is a major obstacle in the successful therapy of breast cancer. Studies have proved that this kind of drug resistance happens in both human cancers and cultured cancer cell lines. Understanding the molecular mechanisms of drug resistance is important for the reasonable design and use of new treatment strategies to effectively confront cancers. RESULTS: In our study, ATP-binding cassette sub-family G member 2 (ABCG2), adenosine triphosphate (ATP) synthase and cytochrome c oxidase subunit VIc (COX6C) were over-expressed more in the MCF-7/MX cell line than in the normal MCF7 cell line. Therefore, we believe that these three genes increase the tolerance of MCF7 to mitoxantrone (MX). The data showed that the high expression of COX6C made MCF-7/MX have more stable on mitochondrial membrane potential (MMP) and reactive oxygen species (ROS) expression than normal MCF7 cells under hypoxic conditions. The accumulation of MX was greater in the ATP-depleted treatment MCF7/MX cells than in normal MCF7/MX cells. Furthermore, E2 increased the tolerance of MCF7 cells to MX through inducing the expression of ABCG2. However, E2 could not increase the expression of ABCG2 after the inhibition of estrogen receptor α (ERα) in MCF7 cells. According to the above data, under the E2 treatment, MDA-MB231, which lacks ER, had a higher sensitivity to MX than MCF7 cells. CONCLUSIONS: E2 induced the expression of ABCG2 through ERα and the over-expressed ABCG2 made MCF7 more tolerant to MX. Moreover, the over-expressed ATP synthase and COX6c affected mitochondrial genes and function causing the over-expressed ABCG2 cells pumped out MX in a concentration gradient from the cell matrix. Finally lead to chemoresistance

Integrated glycomic analysis of ovarian cancer side population cells

Additional file 2. The category of representative lectins for glycan profiling

High levels of serum macrophage migration inhibitory factor and interleukin 10 are associated with a rapidly fatal outcome in patients with severe sepsis

SummaryObjectivesThe aim of this study was to delineate the association between high macrophage migration inhibitory factor (MIF) and interleukin 10 (IL-10) levels in the early phase of sepsis and rapidly fatal outcome.MethodsOne hundred and fifty-three adult subjects with the main diagnosis of severe sepsis (including septic shock) admitted directly from the emergency department of two tertiary medical centers and one regional teaching hospital between January 2009 and December 2011, were included prospectively. MIF and IL-10 levels were measured and outcomes were analyzed by Cox regression analysis according to the following outcomes: rapidly fatal outcome (RFO, death within 48h), late fatal outcome (LFO, death between 48h and 28 days), and survival at 28 days.ResultsAmong the three outcome groups, IL-10 levels were significantly higher in the RFO group (p < 0.001) and no significant differences were seen between the LFO and survivor groups. After Cox regression analysis, each incremental elevation of 1000 pg/ml in both IL-10 and MIF was independently associated with RFO in patients with severe sepsis. Each incremental elevation of 1000 pg/ml in IL-10 increased the RFO risk by a factor of 1.312 (95% confidence interval 1.094–1.575; p=0.003); this was the most significant factor leading to RFO in patients with severe sepsis.ConclusionsPatients with RFO exhibited simultaneously high MIF and IL-10 levels in the early phase of severe sepsis. Incremental increases in both IL-10 and MIF levels were associated with RFO in this patient group, and of the two, IL-10 was the most significant factor linked to RFO

Cartilage tissue healing and regeneration based on biocompatible materials: a systematic review and bibliometric analysis from 1993 to 2022

Cartilage, a type of connective tissue, plays a crucial role in supporting and cushioning the body, and damages or diseases affecting cartilage may result in pain and impaired joint function. In this regard, biocompatible materials are used in cartilage tissue healing and regeneration as scaffolds for new tissue growth, barriers to prevent infection and reduce inflammation, and deliver drugs or growth factors to the injury site. In this article, we perform a comprehensive bibliometric analysis of literature on cartilage tissue healing and regeneration based on biocompatible materials, including an overview of current research, identifying the most influential articles and authors, discussing prevailing topics and trends in this field, and summarizing future research directions