Measurement of Adhesion Energy of Electrospun Polymer Membranes Using a Shaft-loaded Blister Test

This study aims to examine the adhesion work of electrospun polymer nano- and micro-fibers. The adhesion energy at the interface of electrospun membrane and a rigid substrate is characterized by a shaft-loaded blister test (SLBT). By controlling the processing parameters, polyvinylidene fluoride (PVDF) fibrous membranes are prepared with fiber diameters ranging from 201 ± 86 nm to 2,724 ± 587 nm. The adhesion energy between electrospun membrane and rigid substrate increases from 8.1 ± 0.7 mJ/m2 to 258.8 ± 43.5 mJ/m2 by use of smaller fiber diameters. Adhesion energies between electrospun PVDF membranes and SiC substrates made of different grain sizes are evaluated. Fibrous membrane produces an adhesion energy as high as 420.1 ± 62.9 mJ/m2 in contact with SiC substrate with a 68 μm grit size. The SLBT methodology is extended to understand the adhesion energy between electrospun membranes. The increase in adhesion work is attributed to an increased area between fiber delaminated surfaces and surface asperities

Familial Hemiplegic Migraine Type 3 (FHM3) With an SCN1A Mutation in a Chinese Family: A Case Report

Familial hemiplegic migraine (FHM) is a rare, monogenic, autosomal dominant subtype of migraine, in which three genes, CACNA1A, ATP1A2, and SCN1A, are currently known to be involved. The familial hemiplegic migraine type 3 (FHM3) is seldom caused by mutations in SCN1A. Here, we report a rare case of an SCN1A mutation leading to FHM3 in a Chinese family. This case report describes a 62-year-old female patient that was admitted to our clinic. She presented with recurrent attacks of hemiplegic migraine. Her symptoms were first suspicious of a transient ischemic attack (TIA), but they were eventually diagnosed as FHM with a c.4495T>C mutation being found in the SCN1A gene. This case highlights that when a patient presents at the clinic with TIA symptoms associated with migraine, the diagnosis of an FHM should be considered and a genetic test is indicated. The identification of SCN1A gene mutations may help us to further understand the FHM pathophysiology

ISA-Net: Improved spatial attention network for PET-CT tumor segmentation

Achieving accurate and automated tumor segmentation plays an important role in both clinical practice and radiomics research. Segmentation in medicine is now often performed manually by experts, which is a laborious, expensive and error-prone task. Manual annotation relies heavily on the experience and knowledge of these experts. In addition, there is much intra- and interobserver variation. Therefore, it is of great significance to develop a method that can automatically segment tumor target regions. In this paper, we propose a deep learning segmentation method based on multimodal positron emission tomography-computed tomography (PET-CT), which combines the high sensitivity of PET and the precise anatomical information of CT. We design an improved spatial attention network(ISA-Net) to increase the accuracy of PET or CT in detecting tumors, which uses multi-scale convolution operation to extract feature information and can highlight the tumor region location information and suppress the non-tumor region location information. In addition, our network uses dual-channel inputs in the coding stage and fuses them in the decoding stage, which can take advantage of the differences and complementarities between PET and CT. We validated the proposed ISA-Net method on two clinical datasets, a soft tissue sarcoma(STS) and a head and neck tumor(HECKTOR) dataset, and compared with other attention methods for tumor segmentation. The DSC score of 0.8378 on STS dataset and 0.8076 on HECKTOR dataset show that ISA-Net method achieves better segmentation performance and has better generalization. Conclusions: The method proposed in this paper is based on multi-modal medical image tumor segmentation, which can effectively utilize the difference and complementarity of different modes. The method can also be applied to other multi-modal data or single-modal data by proper adjustment

Two-kind boson mixture honeycomb Hamiltonian of Bloch exciton-polaritons

H.P., M.P., and N.Y.K. are supported by Industry Canada and the Ontario Ministry of Research & Innovation through Early Researcher Awards. This research was undertaken thanks in part to funding from the Canada First Research Excellence Fund (CFREF). H.P. thanks Z. Xie for the travel support to visit IQC. M.P. is a recipient of the Richard and Elizabeth Master Graduate Entrance Scholarship and Natural Sciences and Engineering Research Council (NSERC) Canada Graduate Scholarships-Master’s Program. K.W., A.S., M.M., M.K., S.K., C.S., and S.H. received support from the State of Bavaria.The electronic band structure of a solid is a collection of allowed bands separated by forbidden bands, revealing the geometric symmetry of the crystal structures. Comprehensive knowledge of the band structure with band parameters explains intrinsic physical, chemical, and mechanical properties of the solid. Here we report the artificial polaritonic band structures of two-dimensional honeycomb lattices for microcavity exciton-polaritons using GaAs semiconductors in the wide-range detuning values, from cavity photonlike (red-detuned) to excitonlike (blue-detuned) regimes. In order to understand the experimental band structures and their band parameters, such as gap energies, bandwidths, hopping integrals, and density of states, we originally establish a polariton band theory within an augmented plane wave method with two-kind bosons, cavity photons trapped at the lattice sites, and freely moving excitons. In particular, this two-kind band theory is absolutely essential to elucidate the exciton effect in the band structures of blue-detuned exciton-polaritons, where the flattened excitonlike dispersion appears at larger in-plane momentum values captured in our experimental access window. We reach an excellent agreement between theory and experiments in all detuning values.Publisher PDFPeer reviewe

31st Annual Meeting and Associated Programs of the Society for Immunotherapy of Cancer (SITC 2016) : part two

Background The immunological escape of tumors represents one of the main ob- stacles to the treatment of malignancies. The blockade of PD-1 or CTLA-4 receptors represented a milestone in the history of immunotherapy. However, immune checkpoint inhibitors seem to be effective in specific cohorts of patients. It has been proposed that their efficacy relies on the presence of an immunological response. Thus, we hypothesized that disruption of the PD-L1/PD-1 axis would synergize with our oncolytic vaccine platform PeptiCRAd. Methods We used murine B16OVA in vivo tumor models and flow cytometry analysis to investigate the immunological background. Results First, we found that high-burden B16OVA tumors were refractory to combination immunotherapy. However, with a more aggressive schedule, tumors with a lower burden were more susceptible to the combination of PeptiCRAd and PD-L1 blockade. The therapy signifi- cantly increased the median survival of mice (Fig. 7). Interestingly, the reduced growth of contralaterally injected B16F10 cells sug- gested the presence of a long lasting immunological memory also against non-targeted antigens. Concerning the functional state of tumor infiltrating lymphocytes (TILs), we found that all the immune therapies would enhance the percentage of activated (PD-1pos TIM- 3neg) T lymphocytes and reduce the amount of exhausted (PD-1pos TIM-3pos) cells compared to placebo. As expected, we found that PeptiCRAd monotherapy could increase the number of antigen spe- cific CD8+ T cells compared to other treatments. However, only the combination with PD-L1 blockade could significantly increase the ra- tio between activated and exhausted pentamer positive cells (p= 0.0058), suggesting that by disrupting the PD-1/PD-L1 axis we could decrease the amount of dysfunctional antigen specific T cells. We ob- served that the anatomical location deeply influenced the state of CD4+ and CD8+ T lymphocytes. In fact, TIM-3 expression was in- creased by 2 fold on TILs compared to splenic and lymphoid T cells. In the CD8+ compartment, the expression of PD-1 on the surface seemed to be restricted to the tumor micro-environment, while CD4 + T cells had a high expression of PD-1 also in lymphoid organs. Interestingly, we found that the levels of PD-1 were significantly higher on CD8+ T cells than on CD4+ T cells into the tumor micro- environment (p < 0.0001). Conclusions In conclusion, we demonstrated that the efficacy of immune check- point inhibitors might be strongly enhanced by their combination with cancer vaccines. PeptiCRAd was able to increase the number of antigen-specific T cells and PD-L1 blockade prevented their exhaus- tion, resulting in long-lasting immunological memory and increased median survival

Preparation and Application of Polymer Fibers Immobilized Catalysts

The development of highly active and recoverable catalysts has been the subject of research in recent decades. A systematic introduction of techniques for preparing polymer fibers immobilized catalysts, and a brief description of the it' s application are discussed. Compared with conventional non-polymer fibers immobilized catalysts, polymer fibers immobilized catalysts can meet high specific surface area,easy processing, easy separation and so on, and therefore possess a high catalytic activity and excellent cycle performance. Advances in techniques for preparing polymer fibers and methods for immobilizing catalysts significantly promote the progress of high-performance immobilized catalysts with polymer fibers for the carriers, so that the catalysts will exhibit important significance in air purification, sewage treatment, large-scale chemical production and other fields

Learning geometric Jensen-Shannon divergence for tiny object detection in remote sensing images

Tiny objects in remote sensing images only have a few pixels, and the detection difficulty is much higher than that of regular objects. General object detectors lack effective extraction of tiny object features, and are sensitive to the Intersection-over-Union (IoU) calculation and the threshold setting in the prediction stage. Therefore, it is particularly important to design a tiny-object-specific detector that can avoid the above problems. This article proposes the network JSDNet by learning the geometric Jensen-Shannon (JS) divergence representation between Gaussian distributions. First, the Swin Transformer model is integrated into the feature extraction stage as the backbone to improve the feature extraction capability of JSDNet for tiny objects. Second, the anchor box and ground-truth are modeled as two two-dimensional (2D) Gaussian distributions, so that the tiny object is represented as a statistical distribution model. Then, in view of the sensitivity problem faced by the IoU calculation for tiny objects, the JSDM module is designed as a regression sub-network, and the geometric JS divergence between two Gaussian distributions is derived from the perspective of information geometry to guide the regression prediction of anchor boxes. Experiments on the AI-TOD and DOTA datasets show that JSDNet can achieve superior detection performance for tiny objects compared to state-of-the-art general object detectors

Controlling the status of corn cellulose solutions by ethanol to define fiber morphology during electrospinning

Residual ethanol was used as an activation agent to control the status of corn cellulose (CN cellulose) solution and thereby the morphology of CN cellulose fibers after electrospinning. A suitable amount of ethanol could combine with the CN cellulose chains to reduce their ionic absorbance, improving the migration ability of ions in the cellulose-N,N-dimethylacetamide (DMAc)/LiCl-ethanol system. As a result, the entanglement of the molecular chains of CN cellulose in solution was reduced. Excess ethanol reduced the migration ability of ions and enhanced the strong entanglement of CN cellulose in solution. By thus adjusting the status of the CN cellulose solution, the fiber morphology and diameter distribution after electrospinning could be controlled. Based on the experimental results, this approach represents an important and effective approach using ethanol as an activation and adjusting agent for CN cellulose to achieve formation of high-quality electrospun fibers

Adhesion Energy of Electrospun PVDF

Shaft loaded blaster test (SLBT) is utilized to characterize the adhesion energy of electrospun polyvinylidene fluoride (PVDF) membrane with rigid substrate in this paper. PVDF membrane prepared by electrospinning exhibits a uniform fiber morphology. At the membrane surface, the fiber diameter is 333 ± 59 nm and fiber density is roughly around 77%. When electrospun PVDF membrane is tested in SLBT, it shows full linear elastic response at the beginning. With the increase of central deflection up to 2 mm, the electrospun PVDF membrane exhibits obviously yielding. A clear yield point is observed in the debonding response curves. By analysis the elastic response of electrospun PVDF membrane, adhesion energy between the membrane and rigid substrate is calculated. The average adhesion energy is 210.1 ± 27.7 mJ/m2

How does epoxidized soybean oil improve the toughness of microcrystalline cellulose filled polylactide acid composites?

Chemical effect is mainly utilized to induce the accumulation of epoxide soybean oil (ESO) on the surface of microcrystalline cellulose (MCC) particles as the formation of flexible layer to produce superior toughness of polylactide acid (PLA) composites. MCC is firstly maleated to produce appropriate chemical reactivity with ESO and thus ESO is induced to form a flexible layer around MCC particles by chemical reaction happened in melt-blending, which is proved by the results from XPS and contact angle measurements. This flexible layer increases the interfacial adhesion and provides an easy deformation region. As a result, high toughness is provided. The elongation and impact strength of PLA/ESO/MCC ternary composites can be respectively improved to 38.5% and 31.7 KJ/m(2). This particular structure also helps to increase plasticization effect leading to a slightly decrease in T-g. The whole process elaborates a simple but an effective methodology to improve the toughness of PLA/cellulose composite in virtue of chemical effect. Toughness of PLA/ESO/MCC composites can be also controlled by the degree of chemical reaction (adjusted by the substitution degree of MA on MCC). Fully biodegradable PLA/ESO/MCC composite with high toughness is finally fabricated. (C) 2013 Elsevier Ltd. All rights reserved