Detection of crowdedness in bus compartments based on ResNet algorithm and video images

Multimedia Tools and Applications - The crowding in bus is an important factor affecting passenger satisfaction and bus dispatching level. However, how to use video images to detect crowding...     

Three dimensional reconstruction of brain tumor along with space occupying in lesions

Multimedia Tools and Applications - The three-dimensional models of brain tumors serve as diagnostic assistance for physicians, surgeons, and radiologists. The proposed system establishes an...     

Designing optical glasses by machine learning coupled with a genetic algorithm

Engineering new glass compositions have experienced a sturdy tendency to move forward from (educated) trial-and-error to data- and simulation-driven strategies. In this work, we developed a computer program that combines data-driven predictive models (in this case, neural networks) with a genetic algorithm to design glass compositions with desired combinations of properties. First, we induced predictive models for the glass transition temperature (T_g) using a dataset of 45,302 compositions with 39 different chemical elements, and for the refractive index (n_d) using a dataset of 41,225 compositions with 38 different chemical elements. Then, we searched for relevant glass compositions using a genetic algorithm informed by a design trend of glasses having high n_d (1.7 or more) and low T_g (500 °C or less). Two candidate compositions suggested by the combined algorithms were selected and produced in the laboratory. These compositions are significantly different from those in the datasets used to induce the predictive models, showing that the used method is indeed capable of exploration. Both glasses met the constraints of the work, which supports the proposed framework. Therefore, this new tool can be immediately used for accelerating the design of new glasses. These results are a stepping stone in the pathway of machine learning-guided design of novel glasses.     

Eco-friendly and degradable red phosphorus nanoparticles for rapid microbial sterilization under visible light

Pathogens pose a serious challenge to environmental sanitation and a threat to public health.The frequent use of chemicals for sterilization in recent years has not only caused secondary damage to the environment but also increased pathogen resistance to drugs,which further threatens public health.To address this issue,the use of non-chemical antibacterial means has become a new trend for environmental disinfection.In this study,we developed red phosphorus nanoparticles(RPNPs),a safe and degradable photosensitive material with good photocatalytic and photothermal properties.The red phosphorus nanoparticles were prepared using a template method and ultrasonication.Under the irradiation of simulated sunlight for 20 min,the RPNPs exhibited an efficiency of 99.98%in killing Staphylococcus aureus due to their excellent photocatalytic and photothermal abilities.Transmission electron microscopy and ultraviolet–visible spectroscopy revealed that the RPNPs exhibited degradability within eight weeks.Both the RPNPs and their degradation products were nontoxic to fibroblast cells.Therefore,such RPNPs are expected to be used as a new type of low-cost,efficient,degradable,biocompatible,and eco-friendly photosensitive material for environmental disinfection.     

近源成藏——来自鄂尔多斯盆地延长组湖盆东部“边缘”延长组6段原油的地球化学证据

延安以东和以北的鄂尔多斯盆地东北部地区曾被认为位处三叠纪延长组7段（长7段）沉积期古湖盆的"边缘"，一些学者认为该区延长组烃源岩不发育，因而其油藏原油系湖盆中心生成的原油经长距离侧向运移而来；但也有研究认为，包括盆地边缘在内的整个鄂尔多斯盆地致密油藏均为近源成藏。为明确盆地东部地区延长组原油来源，对三叠纪湖盆"东缘"七里村油田的主力油层延长组6段（长6段）原油开展了原油地球化学和油源对比研究。七里村油田长6段原油具有高饱和烃、高饱芳比、低非烃和低沥青质的特征，正构烷烃呈前高单峰型，主峰碳为C₁₉，生物标志化合物分析显示长6段原油为同源成熟原油，生油母质以藻类等低等水生生物为主，混有陆源高等植物，母源沉积环境为偏还原性的淡水湖泊。七里村油田长6段原油与本地区长7段黑色泥页岩和暗色泥岩2种烃源岩均具有明显亲缘关系，而与志丹、富县等湖盆中心地区的长7段烃源岩在族组成、生物标志化合物和稳定碳同位素特征上均存在明显区别。综合分析认为七里村油田长6段原油并非湖盆中心长7段优质烃源岩所生油气经长距离运移而来，而主要为原位长7段烃源岩生成的原油经垂向运移和短距离侧向运移在长6段等储层中聚集成藏，属于近源成藏。     

Syndecan-1 (CD138), Carcinomas and EMT

Cell surface proteoglycans are known to be important regulators of many aspects of cell behavior. The principal family of transmembrane proteoglycans is the syndecans, of which there are four in mammals. Syndecan-1 is mostly restricted to epithelia, and bears heparan sulfate chains that are capable of interacting with a large array of polypeptides, including extracellular matrix components and potent mediators of proliferation, adhesion and migration. For this reason, it has been studied extensively with respect to carcinomas and tumor progression. Frequently, but not always, syndecan-1 levels decrease as tumor grade, stage and invasiveness and dedifferentiation increase. This parallels experiments that show depletion of syndecan-1 can be accompanied by loss of cadherin-mediated adhesion. However, in some tumors, levels of syndecan-1 increase, but the characterization of its distribution is relevant. There can be loss of membrane staining, but acquisition of cytoplasmic and/or nuclear staining that is abnormal. Moreover, the appearance of syndecan-1 in the tumor stroma, either associated with its cellular component or the collagenous matrix, is nearly always a sign of poor prognosis. Given its relevance to myeloma progression, syndecan-1-directed antibody—toxin conjugates are being tested in clinical and preclinical trials, and may have future relevance to some carcinomas.     

Inhibition of Autophagy Does Not Re-Sensitize Acute Myeloid Leukemia Cells Resistant to Cytarabine

Elevated activation of the autophagy pathway is currently thought to be one of the survival mechanisms allowing therapy-resistant cancer cells to escape elimination, including for cytarabine (AraC)-resistant acute myeloid leukemia (AML) patients. Consequently, the use of autophagy inhibitors such as chloroquine (CQ) is being explored for the re-sensitization of AraC-resistant cells. In our study, no difference in the activity of the autophagy pathway was detected when comparing AraC-Res AML cell lines to parental AraC-sensitive AML cell lines. Furthermore, treatment with autophagy inhibitors CQ, 3-Methyladenine (3-MA), and bafilomycin A1 (BafA1) did not re-sensitize AraC-Res AML cell lines to AraC treatment. However, in parental AraC-sensitive AML cells, treatment with AraC did activate autophagy and, correspondingly, combination of AraC with autophagy inhibitors strongly reduced cell viability. Notably, the combination of these drugs also yielded the highest level of cell death in a panel of patient-derived AML samples even though not being additive. Furthermore, there was no difference in the cytotoxic effect of autophagy inhibition during AraC treatment in matched de novo and relapse samples with differential sensitivity to AraC. Thus, inhibition of autophagy may improve AraC efficacy in AML patients, but does not seem warranted for the treatment of AML patients that have relapsed with AraC-resistant disease.