Drug release rate and anti-microbial effect of controlled-diffusion biopolymer membranes

In this study, a series of fibrous membranes made from cellulose acetate (CA) and polyester urethane (PEU) by co-electrospining or blend-electrospining were evaluated for drug release kinetics, in vitro anti-microbial activity and in vivo would healing performance when used as wound dressings. To stop common clinical infections, an antibacterial agent, Polyhexamethylene Biguanide (PHMB) was incorporated into e-spun fibres. The presence of CA in the wound healing membrane was found to improve hydrophilicity and permeability to air and moisture. The in vivo tests indicated that the addition of PHMB and CA considerably improved the wound healing efficiency. CA fibres became slightly swollen upon contacting with the wound exudates. It can not only speed up the liquid evaporation but also create a moisture environment for wound recovery. The drug release dynamics of membranes was controlled by the structure of membranes and component rations within membranes. The lower ration of CA:PEU retained the sound mechanical properties of membranes, and also reduced the boost release effectively and slowed down diffusion of antibacterial agent during in vitro tests. The controlled-diffusion membranes exert long-term anti-infective effect

RadCool: a Web-enabled Simulation Tool for Radiative Cooling

Thermophotovoltaic (TPV) systems can generate electricity from high-temperature heat sources via thermal radiation. However, the intense heating of a photovoltaic (PV) cell can greatly reduce the overall efficiency of the system. Therefore, it is critical to develop techniques to keep the PV cells close to ambient temperature without consuming energy. Radiative cooling is a passive technique that dissipates heat into remote space via thermal radiation. A simulation tool to predict the performance of radiative cooling systems would be particularly helpful in designing new experiments. The current TPV model simulation tool, TPVexpt, can calculate the theoretical performance of the TPV system. However, it does not consider the thermal management of the PV cell. A new tool, Radcool, is created to complement TPVexpt as well as to predict the performance of a radiative cooling system in general. The main design considerations of Radcool include: (1) the area ratio between the PV cell and the cooling emitter, and (2) the cooling emitter materials. The cooling performance is evaluated by equilibrium heat transfer analysis. Radcool has been validated with the existing experiment, but more experiments need to be done to confirm the generality of the system and modeling approach. In the future, this radiative cooling model can be connected directly with the existing TPV model, so that TPV systems will become more efficient for real world applications. The radiative cooling technique is not limited to TPV systems; other potential applications include solar cell cooling, infrared detectors, and sensitive electronic devices that are used outdoors

Contrastive Transformer Learning with Proximity Data Generation for Text-Based Person Search

Given a descriptive text query, text-based person search (TBPS) aims to retrieve the best-matched target person from an image gallery. Such a cross-modal retrieval task is quite challenging due to significant modality gap, fine-grained differences and insufficiency of annotated data. To better align the two modalities, most existing works focus on introducing sophisticated network structures and auxiliary tasks, which are complex and hard to implement. In this paper, we propose a simple yet effective dual Transformer model for text-based person search. By exploiting a hardness-aware contrastive learning strategy, our model achieves state-of-the-art performance without any special design for local feature alignment or side information. Moreover, we propose a proximity data generation (PDG) module to automatically produce more diverse data for cross-modal training. The PDG module first introduces an automatic generation algorithm based on a text-to-image diffusion model, which generates new text-image pair samples in the proximity space of original ones. Then it combines approximate text generation and feature-level mixup during training to further strengthen the data diversity. The PDG module can largely guarantee the reasonability of the generated samples that are directly used for training without any human inspection for noise rejection. It improves the performance of our model significantly, providing a feasible solution to the data insufficiency problem faced by such fine-grained visual-linguistic tasks. Extensive experiments on two popular datasets of the TBPS task (i.e., CUHK-PEDES and ICFG-PEDES) show that the proposed approach outperforms state-of-the-art approaches evidently, e.g., improving by 3.88%, 4.02%, 2.92% in terms of Top1, Top5, Top10 on CUHK-PEDES. The codes will be available at https://github.com/HCPLab-SYSU/PersonSearch-CTLGComment: Accepted by IEEE T-CSV

Polyneuropathy as Novel Initial Manifestation in a Case of “Nonsecretory” POEMS Syndrome with Sjögren’s Syndrome

POEMS syndrome (polyneuropathy, organomegaly, endocrinopathy, monoclonal gammopathy, and skin changes) is a paraneoplastic syndrome driven by plasma cell dyscrasias. We report a patient with novel initial manifestation of polyneuropathy, which was considered due to Sjögren’s syndrome but with poor response to methylprednisolone (120 mg/d) and intravenous immunoglobulin (IVIg). Further investigation by imaging tests and following biopsy eventually confirmed the diagnosis of POEMS syndrome secondary to solitary plasmocytoma. To our knowledge, this is the first reported case of POEMS syndrome with Sjögren’s syndrome occurring in the absence of a peripheral monoclonal gammopathy, highlighting the diagnostic challenges posed by this disease and reviewing the diagnostic role of (18) F-FDG PET/CT in POEMS syndrome

Superfast Near-Infrared Light-Driven Polymer Multilayer Rockets

A gold nanoshell-functionalized polymer multilayer nanorocket performs self-propulsion upon the irradiation with NIR light in the absence of chemical fuel. Theoretical simulations reveal that the NIR light-triggered self-thermophoresis drives the propulsion of the nanorocket. The nanorocket also displays ­efficient NIR light-triggered propulsion in ­biofluids and thus holds considerable promise for various potential biomedical applications

Macroscale Chemotaxis from a Swarm of Bacteria-Mimicking Nanoswimmers

Inspired by the dynamics of bacterial swarming, we report a swarm of polymer‐brush‐grafted, glucose‐oxidase‐powered Janus gold nanoswimmers with a positive, macroscale chemotactic behavior. These nanoswimmers are prepared through the grafting of polymer brushes onto one side of gold nanoparticles, followed by functionalization with glucose oxidase on the other side. The resulting polymer‐brush‐functionalized Janus gold nanoswimmers exhibit efficient propulsion with a velocity of up to approximately 120 body lengths s−1 in the presence of glucose. The comparative analysis of their kinematic behavior reveals that the grafted polymer brushes significantly improve the translational diffusion of Janus gold nanoswimmers. Particularly, these bacteria‐mimicking Janus gold nanoswimmers display a collectively chemotactic motion along the concentration gradient of a glucose resource, which could be observed at the macroscale

Superfast Near-Infrared Light-Driven Polymer Multilayer Rockets

A gold nanoshell-functionalized polymer multilayer nanorocket performs self-propulsion upon the irradiation with NIR light in the absence of chemical fuel. Theoretical simulations reveal that the NIR light-triggered self-thermophoresis drives the propulsion of the nanorocket. The nanorocket also displays ­efficient NIR light-triggered propulsion in ­biofluids and thus holds considerable promise for various potential biomedical applications