Tooth-shaped plasmonic waveguide filters with nanometeric sizes

A novel nanometeric plasmonic filter in a tooth-shaped Metal-Insulator-Metal waveguide is proposed and demonstrated numerically. An analytic model based on the scattering matrix method is given. The result reveals that the single tooth-shaped filter has a wavelength filtering characteristic and an ultra-compact size in the length of a few hundred nanometers, compared to grating-like SPPs filters. Both analytic and simulation results show that the wavelength of the trough of the transmission has linear and nonlinear relationships with the tooth depth and the tooth width, respectively. The waveguide filter could be utilized to develop ultra-compact photonic filters for high integration.Comment: 16 pages, 5 figure

TM-NET: Deep Generative Networks for Textured Meshes

We introduce TM-NET, a novel deep generative model for synthesizing textured meshes in a part-aware manner. Once trained, the network can generate novel textured meshes from scratch or predict textures for a given 3D mesh, without image guidance. Plausible and diverse textures can be generated for the same mesh part, while texture compatibility between parts in the same shape is achieved via conditional generation. Specifically, our method produces texture maps for individual shape parts, each as a deformable box, leading to a natural UV map with minimal distortion. The network separately embeds part geometry (via a PartVAE) and part texture (via a TextureVAE) into their respective latent spaces, so as to facilitate learning texture probability distributions conditioned on geometry. We introduce a conditional autoregressive model for texture generation, which can be conditioned on both part geometry and textures already generated for other parts to achieve texture compatibility. To produce high-frequency texture details, our TextureVAE operates in a high-dimensional latent space via dictionary-based vector quantization. We also exploit transparencies in the texture as an effective means to model complex shape structures including topological details. Extensive experiments demonstrate the plausibility, quality, and diversity of the textures and geometries generated by our network, while avoiding inconsistency issues that are common to novel view synthesis methods

Multifunctional targeting micelle nanocarriers with both imaging and therapeutic potential for bladder cancer.

BackgroundWe previously developed a bladder cancer-specific ligand (PLZ4) that can specifically bind to both human and dog bladder cancer cells in vitro and in vivo. We have also developed a micelle nanocarrier drug-delivery system. Here, we assessed whether the targeting micelles decorated with PLZ4 on the surface could specifically target dog bladder cancer cells.Materials and methodsMicelle-building monomers (ie, telodendrimers) were synthesized through conjugation of polyethylene glycol with a cholic acid cluster at one end and PLZ4 at the other, which then self-assembled in an aqueous solution to form micelles. Dog bladder cancer cell lines were used for in vitro and in vivo drug delivery studies.ResultsCompared to nontargeting micelles, targeting PLZ4 micelles (23.2 ± 8.1 nm in diameter) loaded with the imaging agent DiD and the chemotherapeutic drug paclitaxel or daunorubicin were more efficient in targeted drug delivery and more effective in cell killing in vitro. PLZ4 facilitated the uptake of micelles together with the cargo load into the target cells. We also developed an orthotopic invasive dog bladder cancer xenograft model in mice. In vivo studies with this model showed the targeting micelles were more efficient in targeted drug delivery than the free dye (14.3×; P < 0.01) and nontargeting micelles (1.5×; P < 0.05).ConclusionTargeting micelles decorated with PLZ4 can selectively target dog bladder cancer cells and potentially be developed as imaging and therapeutic agents in a clinical setting. Preclinical studies of targeting micelles can be performed in dogs with spontaneous bladder cancer before proceeding with studies using human patients

Methological quality of systematic reviews and meta-analyses on acupuncture for stroke: a review of review

Objective: To assess the methodological quality of systematic reviews and meta-analyses regarding acupuncture intervention for stroke and the primary studies within them. Methods: Two researchers searched PubMed, Cumulative index to Nursing and Allied Health Literature, Embase, ISI Web of Knowledge, Cochrane, Allied and Complementary Medicine, Ovid Medline, Chinese Biomedical Literature Database, China National Knowledge Infrastructure, Wanfang and Traditional Chinese Medical Database to identify systematic reviews and meta-analyses about acupuncture for stroke published from the inception to December 2016. Review characteristics and the criteria for assessing the primary studies within reviews were extracted. The methodological quality of the reviews was assessed using adapted Oxman and Guyatt Scale. The methodological quality of primary studies was also assessed. Results: Thirty-two eligible reviews were identified, 15 in English and 17 in Chinese. The English reviews were scored higher than the Chinese reviews (P=0.025), especially in criteria for avoiding bias and the scope of search. All reviews used the quality criteria to evaluate the methodological quality of primary studies, but some criteria were not comprehensive. The primary studies, in particular the Chinese reviews, had problems with randomization, allocation concealment, blinding, dropouts and withdrawals, intent-to-treat analysis and adverse events. Conclusions: Important methodological flaws were found in Chinese systematic reviews and primary studies. It was necessary to improve the methodological quality and reporting quality of both the systematic reviews published in China and primary studies on acupuncture for stroke