Functionalized multi‐walled carbon nanotubes (FMWCNTs) have been incorporated into binary composites of poly(amide‐imide) (PAI) and polyaniline (PANI) to improve their conductive and mechanical performances. The conductivity of PAI/PANI/FMWCNTs ternary composites significantly increased from 10−3 to 8.3 S m−1 with increasing the weight ratio of FMWCNTs from 0 to 10 wt%, which is much higher than that of the sum of PAI/PANI and PAI/FMWCNTs binary composites. The enhanced conductivity is mainly ascribed to be the more intensive conductive percolating network formed in the PAI/PANI/FMWCNTs ternary composites due to the hydrogen bond interaction among PAI, PANI and FMWCNTs. On the other hand, the tensile strength has been improved by 40% from 25 to 35 MPa. The self‐extinguishing property and phase transition of the ternary films have also been investigated by thermal gravimetric analysis and differential scanning calorimetry, respectively. It is found that the weight ratio of FMWCNTs and the special morphology are the two important factors that induce such unusual properties. POLYM. ENG. SCI., 59:E224–E230, 2019. © 2018 Society of Plastics Engineers

Rationale: Atherosclerosis is characterized by lipid accumulation, plaque formation, and artery stenosis. The pharmacological treatment is a promising therapy for atherosclerosis, but this approach faces major challenges such as targeted drug delivery, controlled release, and non-specific clearance. Methods: Based on the finding that the cathepsin k (CTSK) enzyme is enriched in atherosclerotic lesions, we constructed an integrin α v β 3 targeted and CTSK-responsive nanoparticle to control the release of rapamycin (RAP) locally. The targeted and responsive nanoparticles (T/R NPs) were engineered by the self-assembly of a targeting polymer PLGA-PEG-c(RGDfC) and a CTSK-sensitive polymer PLGA-Pep-PEG. PLGA-Pep-PEG was also modified with a pair of FRET probe to monitor the hydrolysis events. Results: Our results indicated that RAP@T/R NPs accelerated the release of RAP in response to CTSK stimulation in vitro , which significantly inhibited the phagocytosis of OxLDL and the release of cytokines by inflammatory macrophages. Additionally, T/R NPs had prolonged blood retention time and increased accumulation in the early and late stage of atherosclerosis lesions. RAP@T/R NPs significantly blocked the development of atherosclerosis and suppressed the systemic and local inflammation in ApoE -/- mice. Conclusions: RAP@T/R NPs hold a great promise as a drug delivery system for safer and more efficient therapy of atherosclerosis.

Coronary stent placement inevitably causes mechanical damage to the endothelium, leading to endothelial denudation and in-stent restenosis (ISR). Re-endothelialization depends mainly on the migration of vascular endothelial cells (VECs) adjacent to the damaged intima, as well as the mobilization and adhesion of circulating VECs. To evaluate the combined contribution of VEC migration and adhesion to re-endothelialization under flow and the influence of stent, in vitro models were constructed to simulate various endothelial denudation scales (2 mm/5 mm/10 mm) and stent deployment depths (flat/groove/bulge). Our results showed that (1) in 2 mm flat/groove/bulge models, both VEC migration and adhesion combined completed the percentage of endothelial recovery about 27, 16, and 12%, and migration accounted for about 21, 15, and 7%, respectively. It was suggested that the flat and groove models were in favor of VEC migration. (2) With the augmentation of the injury scales (5 and 10 mm), the contribution of circulating VEC adhesion on endothelial repair increased. Taken together, endothelial restoration mainly depended on the migration of adjacent VECs when the injury scale was 2 mm. The adhered cells contributed to re-endothelialization in an injury scale-dependent way. This study is helpful to provide new enlightenment for surface modification of cardiovascular implants.

Object detection often costs a considerable amount of computation to get satisfied performance, which is unfriendly to be deployed in edge devices. To address the trade-off between computational cost and detection accuracy, this paper presents a dual path network, named DPNet, for efficient object detection with lightweight self-attention. In backbone, a single input/output lightweight self-attention module (LSAM) is designed to encode global interactions between different positions. LSAM is also extended into a multiple-inputs version in feature pyramid network (FPN), which is employed to capture cross-resolution dependencies in two paths. Extensive experiments on the COCO dataset demonstrate that our method achieves promising detection results. More specifically, DPNet obtains 29.0% AP on COCO test-dev, with only 1.14 GFLOPs and 2.27M model size for a 320 × 320 image.

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