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39) and a decreased GS (HR 3.55) were independently associated with an increased risk of poor prognosis. In addition to the hepatic functional reserve, a decreased GS was a poor prognostic factor in lenvatinib-treated u-HCC patients.Railway inspection has always been a critical task to guarantee the safety of the railway transportation. The development of deep learning technologies brings new breakthroughs in the accuracy and speed of image-based railway inspection application. In this work, a series of one-stage deep learning approaches, which are fast and accurate at the same time, are proposed to inspect the key components of railway track including rail, bolt, and clip. The inspection results show that the enhanced model, the second version of you only look once (YOLOv2), presents the best component detection performance with 93% mean average precision (mAP) at 35 image per second (IPS), whereas the feature pyramid network (FPN) based model provides a smaller mAP and much longer inference time. Besides, the detection performances of more deep learning approaches are evaluated under varying input sizes, where larger input size usually improves the detection accuracy but results in a longer inference time. Overall, the YOLO series models could achieve faster speed under the same detection accuracy.Breast cancer is the second leading cause of death in women above 60 years in the US. Screening mammography is recommended for women above 50 years; however, 22% of breast cancer cases are diagnosed in women below this age. We set out to develop a test based on the detection of cell-free RNA from saliva. To this end, we sequenced RNA from a pool of ten women. The 1254 transcripts identified were enriched for genes with an annotation of alternative pre-mRNA splicing. Pre-mRNA splicing is a tightly regulated process and its misregulation in cancer cells promotes the formation of cancer-driving isoforms. For these reasons, we chose to focus on splicing factors as biomarkers for the early detection of breast cancer. We found that the level of the splicing factors is unique to each woman and consistent in the same woman at different time points. selleck chemicals Next, we extracted RNA from 36 healthy subjects and 31 breast cancer patients. Recording the mRNA level of seven splicing factors in these samples demonstrated that the combination of all these factors is different in the two groups (p value = 0.005). Our results demonstrate a differential abundance of splicing factor mRNA in the saliva of breast cancer patients.The influence of the mass concentration of Ag on properties of Cu-Ni alloys is investigated. The effect of silver addition on the structure and properties of Cu-2Ni-1Si alloys is determined. The scientific aim of this research is to determine how the addition of silver affects the mechanisms of strengthening silver-modified supersaturated, deformed, and aged Cu-2Ni-1Si alloys. The applied thermo-derivative analysis has allowed us to determine a range of the temperature values for the beginning and the end of crystallization, the phases and eutectics, and the effects of the modification on the solid fraction of the solidified alloy. link2 In addition to the crystallization kinetics, the microstructure morphology, mechanical properties under real operating conditions, and the electrical conductivity have also been investigated. Moreover, the conducted research includes the impact of heat treatment and plastic deformation on the alloy structure and considers the type, share, and distribution of the intermetallic phases and structural stresses caused by coherent phases, as well as the effect of dislocations in the reinforcing phases during aging. Electron microscopy (SEM), micro-area analysis (EDS), optical microscopy, hardness measurements, and conductivity of the tested alloys are utilized to comment on these properties.This paper aims at reviewing the works published in the last five years (2016-2020) on polymer nanocomposites based on epoxy resins. The different nanofillers successfully added to epoxies to enhance some of their characteristics, in relation to the nature and the feature of each nanofiller, are illustrated. The organic-inorganic hybrid nanostructured epoxies are also introduced and their strong potential in many applications has been highlighted. The different methods and routes employed for the production of nanofilled/nanostructured epoxies are described. A discussion of the main properties and final performance, which comprise durability, of epoxy nanocomposites, depending on chemical nature, shape, and size of nanoparticles and on their distribution, is presented. It is also shown why an efficient uniform dispersion of the nanofillers in the epoxy matrix, along with strong interfacial interactions with the polymeric network, will guarantee the success of the application for which the nanocomposite is proposed. The mechanisms yielding to the improved properties in comparison to the neat polymer are illustrated. The most important applications in which these new materials can better exploit their uniqueness are finally presented, also evidencing the aspects that limit a wider diffusion.4-Hydroxyphenylpyruvate dioxygenase (HPPD) is an iron-dependent non-heme oxygenase involved in the catabolic pathway of tyrosine, which is an important enzyme in the transformation of 4-hydroxyphenylpyruvic acid to homogentisic acid, and thus being considered as herbicide target. Within this study, a set of multiple structure-based pharmacophore models for HPPD inhibitors were developed. The ZINC and natural product database were virtually screened, and 29 compounds were obtained. The binding mode of HPPD and its inhibitors obtained through molecular docking study showed that the residues of Phe424, Phe381, His308, His226, Gln307 and Glu394 were crucial for activity. Molecular-mechanics-generalized born surface area (MM/GBSA) results showed that the coulomb force, lipophilic and van der Waals (vdW) interactions made major contributions to the binding affinity. These efforts will greatly contribute to design novel and effective HPPD inhibitory herbicides.This paper deals with the design of a decentralized guidance and control strategy for a swarm of unmanned aerial vehicles (UAVs), with the objective of maintaining a given connection topology with assigned mutual distances while flying to a target area. In the absence of obstacles, the assigned topology, based on an extended Delaunay triangulation concept, implements regular and connected formation shapes. In the presence of obstacles, this technique is combined with a model predictive control (MPC) that allows forming independent sub-swarms optimizing the formation spreading to avoid obstacles and collisions between neighboring vehicles. A custom numerical simulator was developed in a Matlab/Simulink environment to prove the effectiveness of the proposed guidance and control scheme in several 2D operational scenarios with obstacles of different sizes and increasing number of aircraft.Recently, the application of herbal medicine for the prevention and treatment of diseases has gained increasing attention. Essential oils (EOs) are generally known to exert various pharmacological effects, such as antiallergic, anticancer, anti-inflammatory, and immunomodulatory effects. Current literature involving in vitro and in vivo studies indicates the potential of various herbal essential oils as suitable immunomodulators for the alternative treatment of infectious or immune diseases. This review highlights the cellular effects induced by EOs, as well as the molecular impacts of EOs on cytokines, immunoglobulins, or regulatory pathways. The results reviewed in this article revealed a significant reduction in relevant proinflammatory cytokines, as well as induction of anti-inflammatory markers. Remarkably, very little clinical study data involving the immunomodulatory effects of EOs are available. Furthermore, several studies led to contradictory results, emphasizing the need for a multiapproach system to better characterize EOs. While immunomodulatory effects were reported, the toxic potential of EOs must be clearly considered in order to secure future applications.Ion channels play key roles in almost all facets of cellular physiology and have emerged as key host cell factors for a multitude of viral infections. A catalogue of ion channel-blocking drugs have been shown to possess antiviral activity, some of which are in widespread human usage for ion channel-related diseases, highlighting new potential for drug repurposing. The emergence of ion channel-virus interactions has also revealed the intriguing possibility that channelopathies may explain some commonly observed virus induced pathologies. This field is rapidly evolving and an up-to-date summary of new discoveries can inform future perspectives. We herein discuss the role of ion channels during viral lifecycles, describe the recently identified ion channel drugs that can inhibit viral infections, and highlight the potential contribution of ion channels to virus-mediated disease.The discrimination of micro-seismic events (events) and blasts is significant for monitoring and analyzing micro-seismicity in underground mines. To eliminate the negative effects of conventional discrimination methods, a waveform image discriminant method was proposed. Principal component analysis (PCA) was applied to extract the raw features of events and blasts through their waveform images that established by the recorded field data, and transform them into the new uncorrelated features. The amount of initial information retained in the derived features could be determined quantitatively by the contribution rate. The binary classification models were established by utilizing the support vector machine (SVM) algorithm and the PCA derived waveform image features. Results of four groups of cross validation show that the optimal values for the accuracy of events and blasts, total accuracy, and quality evaluation parameter MCC are 97.1%, 93.8%, 93.60%, and 0.8723, respectively. Moreover, the computation efficiency per accuracy (CEA) was introduced to quantitatively evaluate the effects of contribution rate on classification accuracy and computation efficiency. The optimal contribution rate was determined to be 0.90. The waveform image discriminant method can automatically classify events and blasts in underground mines, ensuring the efficient establishment of high-quality micro-seismic databases and providing adequate data for the subsequent seismicity analysis.Major histocompatibility complex class I-related (MR1) was first identified as a cell membrane protein involved in the development and expansion of a unique set of T cells expressing an invariant T-cell receptor (TCR) α-chain. These cells were initially discovered in mucosal tissues, such as the intestinal mucosa, so they are called mucosal-associated invariant T (MAIT) cells. MR1 senses the presence of intermediate metabolites of riboflavin and folic acid synthesis that have been chemically modified by the side-products of glycolysis, glyoxal or methylglyoxal. These modified metabolites form complexes with MR1 and translocate from the endoplasmic reticulum to the plasma membrane where MAIT cells' TCRs recognize them. Recent publications report that atypical MR1-restricted cytotoxic T cells, differing from MAIT cells in TCR usage, antigen, and transcription factor profile, recognize an as yet unknown cancer-specific metabolite presented by MR1 in cancer cells. link3 This metabolite may represent another class of neoantigens, beyond the neo-peptides arising from altered tumor proteins.