The effect of Bletilla striata polysaccharide on the physical and healing properties of curdlan-based hydrogel for wound healing.

Bletilla striata polysaccharide (BSP) was added to curdlan to form a blend hydrogel through a simple heating-cooling procedure to improve the hydrophilicity and healing efficacy of curdlan-based hydrogel used in wound healing. We explored the interplay between BSP and curdlan, studied how BSP concentration affects the physical properties and microstructures of hydrogels, and examined the biocompatibility and healing properties of the blend hydrogel. It was proved that the hydrogel framework was primarily formed by ordered arranged curdlan molecules, with BSP uniformly dispersed and intertwined with curdlan through hydrogen bonding. This effectively improved its hydrophilicity and strengthened the microstructure. Curdlan was found to be compatible with BSP. The blend hydrogel B3Cd3 (containing 1.5% BSP and 1.5% curdlan, w/v) was identified as the optimal formulation based on its higher water adsorption, water retention, thermal stability and interconnected microstructure, and was thus selected for further research. In vitro experiments revealed the highest cell viability of L929 in B3Cd3 extracts compared to those extracts of single-component curdlan hydrogel (Cd). In vivo, animal studies indicated that the B3Cd3 accelerated wound healing compared to the control group by improving re-epithelialization and blood vessel regeneration. On Days 3 and 11, the therapeutic benefits of B3Cd3 exceeded those of the Cd group, and no significant differences were observed in wound healing rates between the B and B3Cd3 groups from Day 7. The study proves that BSP enhances the physical and healing properties, as well as cell proliferation, of the curdlan-based hydrogel. The blend hydrogel B3Cd3, with its exceptional properties, holds potential for future application as a material for non-infected wound healing.

Temperature-Immune, Wide-Range Flexible Robust Pressure Sensors for Harsh Environments.

Flexible pressure sensors possess vast potential for various applications such as new energy batteries, aerospace engines, and rescue robots owing to their exceptional flexibility and adaptability. However, the existing sensors face significant challenges in maintaining long-term reliability and environmental resilience when operating in harsh environments with variable temperatures and high pressures (∼MPa), mainly due to possible mechanical mismatch and structural instability. Here, we propose a composite scheme for a flexible piezoresistive pressure sensor to improve its robustness by utilizing material design of near-zero temperature coefficient of resistance (TCR), radial gradient pressure-dividing microstructure, and flexible interface bonding process. The sensing layer comprising multiwalled carbon nanotubes (MWCNTs), graphite (GP), and thermoplastic polyurethane (TPU) was optimized to achieve a near-zero temperature coefficient of resistance over a temperature range of 25-70 °C, while the radial gradient microstructure layout based on pressure division increases the range of pressure up to 2 MPa. Furthermore, a flexible interface bonding process introduces a self-soluble transition layer by direct-writing TPU bonding solution at the bonding interface, which enables the sensor to achieve signal fluctuations as low as 0.6% and a high interface strength of up to 1200 kPa. Moreover, it has been further validated for its capability of monitoring the physiological signals of athletes as well as the long-term reliable environmental resilience of the expansion pressure of the power cell. This work demonstrates that the proposed scheme sheds new light on the design of robust pressure sensors for harsh environments.

One-step fabrication of high-performance graphene composites from graphite solution for bio-scaffolds and flexible strain sensors.

Graphene composites possess great application potential in various fields including flexible electrodes, wearable sensors and biomedical devices owing to their excellent mechanical and electrical properties. However, it remains challenging to fabricate graphene composites-based devices with high consistency due to the gradual aggression effect of graphene during fabrication process. Herein, we propose a method for one-step fabricating graphene/polymer composite-based devices from graphite/polymer solution by using electrohydrodynamic (EHD) printing with the Weissenberg effect (EPWE). Taylor-Couette flows with high shearing speed were generated to exfoliate high-quality graphene with a rotating steel microneedle coaxially set in a spinneret tube. The effects of the rotating speed of the needle, spinneret size and precursor ingredients on the graphene concentration were discussed. As a proof of concept, EPWE was used to successfully fabricate graphene/polycaprolactone (PCL) bio-scaffolds with good biocompatibility and graphene/thermoplastic polyurethane strain sensor for detecting human motions with a maximum gauge factor more than 2400 from 40% to 50% strain. As such, this method sheds a new light on one-stepin situfabrication of graphene/polymer composite-based devices from graphite solution with low cost.

UV-fluorescence imaging for real-time non-destructive monitoring of pork freshness.

This study aimed to develop a cost-effective fluorescence imaging system to rapidly monitor pork freshness indicators during chilled storage. The system acquired fluorescence images of pork and the color features were extracted from these images to establish partial least squares regression (PLSR) models to predict total volatile basic nitrogen (TVB-N), total viable count (TVC), pH for pork. For TVB-N, TVC and pH values, Rp were 0.92, 0.88 and 0.74, residual predictive deviation (RPD) were 2.24, 2.03, and 1.19, respectively. For TVB-N and TVC indicators showed that the predictive ability of this model was largely comparable to that of fluorescence hyperspectral imaging. However, combining fluorescence and color imaging improved the model's predictive ability. For TVB-N, TVC and pH, Rp were 0.94, 0.93 and 0.85, RPD were 2.62, 2.59, and 1.95, respectively. Therefore, this study developed a system with great potential for detecting the value of most pork quality indicators in real-time.