Anti-tumor effects of CIK combined with oxaliplatin in human oxaliplatin-resistant gastric cancer cells in vivo and in vitro

<p>Abstract</p> <p>Background</p> <p>Drug resistance remains a great challenge in the treatment of gastric cancer. The goal of this study was to explore the anti-tumor effects and mechanism of cytokine-induced killer (CIK) cell combined with oxaliplatin (L-OHP) in human oxaliplatin-resistant gastric cancer cells.</p> <p>Methods</p> <p>After producing oxaliplatin-resistant gastric cancer cells, cell morphology, growth and doubling time were observed, followed by detection of cell cycle distribution and apoptosis, drug sensitivity (e.g., L-OHP) and expression of P-gp and livin. MTT assay, in vivo pharmacodynamics and pathomorphology experiments were used to detect killing activities of CIK combined with L-OHP.</p> <p>Results</p> <p>Compared with parental gastric cancer cells, oxaliplatin-resistant gastric cancer cells in S phase were reduced and cell apoptosis rate was increased (P < 0.05), the inhibition rate of 10 chemotherapeutics on oxaliplatin-resistant gastric cancer cells was significantly lower and the expression of P-gp was significantly higher (P < 0.05). However, there was no significant difference in livin expression between parental gastric cancer cells and oxaliplatin-resistant gastric cancer cells (P > 0.05). The in vitro killing activity of CIK combined with L-OHP on parental cells and oxaliplatin-resistant cells were significantly enhanced compared with L-OHP or CIK alone. And it showed greater synergetic effects against oxaliplatin-resistant cells compared with parental cells (P < 0.05). In addition, survival rate, abdominal circumference and pathomorphology results revealed stronger in vivo anti-tumor effects when the two therapies were combined.</p> <p>Conclusions</p> <p>The mechanism of oxaliplatin-resistant cell secondary multidrug resistance was correlated with the variation of cell cycle distribution, extension of doubling time and upregulation of P-gp expression. The synergistic effect of CIK in combination with L-OHP on killing activity against oxaliplatin-resistant cells was shown in vivo and in vitro.</p

Pre-training with Aspect-Content Text Mutual Prediction for Multi-Aspect Dense Retrieval

Grounded on pre-trained language models (PLMs), dense retrieval has been studied extensively on plain text. In contrast, there has been little research on retrieving data with multiple aspects using dense models. In the scenarios such as product search, the aspect information plays an essential role in relevance matching, e.g., category: Electronics, Computers, and Pet Supplies. A common way of leveraging aspect information for multi-aspect retrieval is to introduce an auxiliary classification objective, i.e., using item contents to predict the annotated value IDs of item aspects. However, by learning the value embeddings from scratch, this approach may not capture the various semantic similarities between the values sufficiently. To address this limitation, we leverage the aspect information as text strings rather than class IDs during pre-training so that their semantic similarities can be naturally captured in the PLMs. To facilitate effective retrieval with the aspect strings, we propose mutual prediction objectives between the text of the item aspect and content. In this way, our model makes more sufficient use of aspect information than conducting undifferentiated masked language modeling (MLM) on the concatenated text of aspects and content. Extensive experiments on two real-world datasets (product and mini-program search) show that our approach can outperform competitive baselines both treating aspect values as classes and conducting the same MLM for aspect and content strings. Code and related dataset will be available at the URL \footnote{https://github.com/sunxiaojie99/ATTEMPT}.Comment: accepted by cikm202

Forest stand spectrum reconstruction using spectrum spatial feature gathering and multilayer perceptron

IntroductionThree-dimensional spectral distributions of forest stands can provide spatial information on the physiological and biochemical status of forests, which is vital for forest management. However, three-dimensional spectral studies of forest stands are limited.MethodsIn this study, LiDAR and multispectral data were collected from Masson pine stands in southern Fujian Province, China, and a method was proposed for inverting forest spectra using point clouds as a unit. First, multispectral values were mapped to a point cloud, and the isolated forest algorithm combined with K-means clustering was applied to characterize fusion data. Second, five deep learning algorithms were selected for semantic segmentation, and the overall accuracy (oAcc) and mean intersection ratio (mIoU) were used to evaluate the performance of various algorithms on the fusion data set. Third, the semantic segmentation model was used to reconfigure the class 3D spectral distribution, and the model inversion outcomes were evaluated by the peaks and valleys of the curve of the predicted values and distribution gaps.ResultsThe results show that the correlations between spectral attributes and between spatial attributes were both greater than 0.98, while the correlation between spectral and spatial attributes was 0.43. The most applicable method was PointMLP, highest oAcc was 0.84, highest mIoU was 0.75, peak interval of the prediction curve tended to be consistent with the true values, and maximum difference between the predicted value and the true value of the point cloud spectrum was 0.83.DiscussionExperimental data suggested that combining spatial fusion and semantic segmentation effectively inverts three-dimensional spectral information for forest stands. The model could meet the accuracy requirements of local spectral inversion, and the NIR values of stands in different regions were correlated with the vertical height of the canopy and the distance from the tree apex in the region. These findings improve our understanding of the precise three-dimensional spectral distribution of forests, providing a basis for near-earth remote sensing of forests and the estimation of forest stand health

Effect of heat treatment on microstructure and mechanical behaviours of 18Ni-300 maraging steel manufactured by selective laser melting

Selective laser melting (SLM) of 18Ni-300 maraging steel is an important research area in view of its numerous applications in the automotive domain. Heat treatment plays a significant role in the microstructure and mechanical behaviour of maraging steels and is a major area of interest. This paper investigated the effect of heat treatment on microstructure and mechanical behaviour of SLM-built 18Ni-300 maraging steel. The experimental results showed that the densest parts with the smallest number of defects were fabricated at optimum laser energy density of 70 J/mm3 and laser power of 275 W. When the laser power was fixed at 275 W, lower laser energy density resulted in the formation of balling and irregular pores, while higher laser energy density induced spherical pores and microcracks. The as-built samples consisted of cellular and columnar microstructures due to the fast cooling and solidification rates during SLM. However, solution treatment led to changes in the typical microstructure and massive lath martensite phase. The tensile strength and microhardness decreased slightly due to grain growth and residual stress relief upon solution treatment; an opposite effect was observed when the samples were subjected to solution treatment followed by aging at 490 °C for 2 h. With regard to the tensile anisotropy, yield strength and ultimate tensile strength of the horizontally-built samples slightly exceeded those vertically-built. These findings are significant as they allow an informed prediction about the effect of various heat treatments on the microstructure and mechanical behaviour of components manufactured from 18Ni-300 maraging steel using the SLM process

Entering the Era of Earth Observation-Based Landslide Warning Systems: A novel and exciting framework

Landslide early warning remains a grand challenge due to the high human cost of catastrophic landslides globally and the difficulty of identifying a diverse range of landslide triggering factors. There have been only a very limited number of success stories to date. However, recent advances in earth observation (EO) from ground, aircraft and space have dramatically improved our ability to detect and monitor active landslides and a growing body of geotechnical theory suggests that prefailure behavior can provide clues to the location and timing of impending catastrophic failures. In this paper, we use two recent landslides in China as case studies, to demonstrate that (i) satellite radar observations can be used to detect deformation precursors to catastrophic landslide occurrence, and (ii) early warning can be achieved with real-time in-situ observations. A novel and exciting framework is then proposed to employ EO technologies to build an operational landslide early warning system.This work was supported by the National Natural Science Foundation of China under grants 41801391, 41874005, and 41929001; the National Science Fund for Outstanding Young Scholars of China under grant 41622206; the Fund for International Cooperation under grant NSFCRCUK_NERC; Resilience to Earthquake-Induced Landslide Risk in China under grant 41661134010; the open fund of State Key Laboratory of Geodesy and Earth’s Dynamics (SKLGED2018-5-3-E); Sichuan Science and Technology Plan Project under grant 2019YJ0404; State Key Laboratory of Geohazard Prevention and Geoenvironment Protection Independent Research Project under grant SKLGP2018Z019; the Spanish Ministry of Economy and Competitiveness, the State Agency of Research, and the European Funds for Regional Development under projects TEC2017-85244-C2-1-P and TIN2014-55413-C2-2-P; and the Spanish Ministry of Education, Culture, and Sport under project PRX17/00439. This work was also partially supported by the U.K. Natural Environment Research Council through the Center for the Observation and Modeling of Earthquakes, Volcanoes, and Tectonics under come30001 and the Looking Inside the Continents From Space and Community Earthquake Disaster Risk Reduction in China projects under NE/K010794/1 and NE/N012151/1, respectively, and by the European Space Agency through the ESA-MOST DRAGON-4 project (32244 [4]). Roland Bürgmann acknowledges support by the NASA Earth Surface and Interior focus area

Toll-like receptor 2 and Toll-like receptor 4 exhibit distinct regulation of cancer cell stemness mediated by cell death-induced high-mobility group box 1

Background: High-mobility group box 1 (HMGB1), a common extracellular damage associated molecular pattern molecule, is overexpressed in several solid tumors including pancreatic carcinoma. We previously observed that radiotherapy induced dying cells secrete HMGB1 and accelerate pancreatic carcinoma progression through an unclear mechanism.Methods: Using the Millicell system as an in vitro co-culture model, we performed quantitative reverse transcriptase-polymerase chain reaction, western blot and sphere forming ability analyses to access the effect of dying-cell-derived HMGB1 on CD133(+) cancer cell stemness in vitro and in vivo. Interactions between HMGB1 and Toll-like receptor 2(TLR2)/TLR4 were studied by co-immunoprecipitation. Western blot and short-hairpin RNA-based knockdown assays were conducted to detect HMGB1 and TLR2/TLR4 signaling activity.Findings: Radiation-associated, dying-cell-derived HMGB1 maintained stemness and contributed to CD133(+) cancer stemcell self-renewal in vitro and in vivo. In overexpressing and silencing experiments, we demonstrated that the process was activated by TLR2 receptor, whereas TLR4 antagonized HMGB1-TLR2 signaling. Wnt/beta-catenin signaling supported the HMGB1-TLR2 mediated stemness of CD133(+) cancer cells.Interpretation: Our results show how irradiation-induced cell death might enhance the stemness of resident cancer cells, and indicate HMGB1-TLR2 signaling as a potential therapeutic target for preventing pancreatic cancer recurrence. (c) 2018 Haitao Zhu. Published by Elsevier B.V

A supersensitive silicon nanowire array biosensor for quantitating tumor marker ctDNA

Cancer has become one of the major diseases threatening human health and life. Circulating tumor DNA (ctDNA) testing, as a practical liquid biopsy technique, is a promising method for cancer diagnosis, targeted therapy and prognosis. Here, for the first time, a field effect transistor (FET) biosensor based on uniformly sized high-response silicon nanowire (SiNW) array was studied for real-time, label-free, super-sensitive detection of PIK3CA E542K ctDNA. High-response 120-SiNWs array was fabricated on a (111) silicon-on-insulator (SOI) by the complementary metal oxide semiconductor (CMOS)-compatible microfabrication technology. To detecting ctDNA, we modified the DNA probe on the SiNWs array through silanization. The experimental results demonstrated that the as-fabricated biosensor had significant superiority in ctDNA detection, which achieved ultralow detection limit of 10 aM and had a good linearity under the ctDNA concentration range from 0.1 fM to 100 pM. This biosensor can recognize complementary target ctDNA from one/two/full-base mismatched DNA with high selectivity. Furthermore, the fabricated SiNW-array FET biosensor successfully detected target ctDNA in human serum samples, indicating a good potential in clinical applications in the future

Study on the evaluation of the clinical effects of traditional chinese medicine in heart failure by complex intervention: protocol of SECETCM-HF

<p>Abstract</p> <p>Background</p> <p>Experts in Traditional Chinese Medicine (TCM) have studied the TCM subject of the pathogenesis of heart failure (HF) for several decades. As a result, the general idea is <it>ben </it>deficiency and <it>biao </it>excess. However, the clinical evaluation system which combined the TCM and western medicine in HF has not been developed yet. The objective is to establish the evaluation index system for the integration of TCM and western medicine. The evaluation indexes which include TCM items will specify the research design and methods.</p> <p>Methods</p> <p>Nine medical centers in different cities in China will participate in the trial. A population of 340 patients with HF will be enrolled through a central randomized system for different test groups. Group A will be treated with only western medicine, while group B with western and Chinese medicine together. The study will last for 12 months from the date of enrollment. The cardiovascular death will be the primary outcome.</p> <p>Discussion</p> <p>By putting the protocol into practice, the clinical effects of TCM for HF will be identified scientifically, objectively as well as rationally. The proper index system which built in the study will be helpful for the clinical effect expression of HF by integrated medicine in future.</p> <p>Trial Registration</p> <p>ChiCTR-TRC-00000059</p