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1.
Bioact Mater ; 39: 562-581, 2024 Sep.
Article in English | MEDLINE | ID: mdl-38883310

ABSTRACT

Oral ulcers can be managed using a variety of biomaterials that deliver drugs or cytokines. However, many patients experience minimal benefits from certain medical treatments because of poor compliance, short retention times in the oral cavity, and inadequate drug efficacy. Herein, we present a novel hydrogel patch (SCE2) composed of a biopolymer matrix (featuring ultraviolet-triggered adhesion properties) loaded with cuttlefish ink nanoparticles (possessing pro-healing functions). Applying a straightforward local method initiates the formation of a hydrogel barrier that adheres to mucosal injuries under the influence of ultraviolet light. SCE2 then demonstrates exceptional capabilities for near-infrared photothermal sterilization and neutralization of reactive oxygen species. These properties contribute to the elimination of bacteria and the management of the oxidation process, thus accelerating the healing phase's progression from inflammation to proliferation. In studies involving diabetic rats with oral ulcers, the SCE2 adhesive patch significantly quickens recovery by altering the inflamed state of the injured area, facilitating rapid re-epithelialization, and fostering angiogenesis. In conclusion, this light-sensitive hydrogel patch offers a promising path to expedited wound healing, potentially transforming treatment strategies for clinical oral ulcers.

2.
Adv Mater ; 35(48): e2306632, 2023 Nov.
Article in English | MEDLINE | ID: mdl-37803944

ABSTRACT

Current therapeutic protocols for diabetic foot ulcers (DFUs), a severe and rapidly growing chronic complication in diabetic patients, remain nonspecific. Hyperglycemia-caused inflammation and excessive reactive oxygen species (ROS) are common obstacles encountered in DFU wound healing, often leading to impaired recovery. These two effects reinforce each other, forming an endless loop. However, adequate and inclusive methods are still lacking to target these two aspects and break the vicious cycle. This study proposes a novel approach for treating DFU wounds, utilizing an immunomodulatory hydrogel to achieve self-cascade glucose depletion and ROS scavenging to regulate the diabetic microenvironment. Specifically, AuPt@melanin-incorporated (GHM3) hydrogel dressing is developed to facilitate efficient hyperthermia-enhanced local glucose depletion and ROS scavenging. Mechanistically, in vitro/vivo experiments and RNA sequencing analysis demonstrate that GHM3 disrupts the ROS-inflammation cascade cycle and downregulates the ratio of M1/M2 macrophages, consequently improving the therapeutic outcomes for dorsal skin and DFU wounds in diabetic rats. In conclusion, this proposed approach offers a facile, safe, and highly efficient treatment modality for DFUs.


Subject(s)
Diabetes Mellitus, Experimental , Diabetic Foot , Hyperthermia, Induced , Humans , Rats , Animals , Hydrogels/therapeutic use , Diabetic Foot/therapy , Reactive Oxygen Species/therapeutic use , Diabetes Mellitus, Experimental/therapy , Glucose , Inflammation/therapy
3.
PLoS One ; 18(8): e0286711, 2023.
Article in English | MEDLINE | ID: mdl-37578956

ABSTRACT

Haze is a typical weather phenomena that has a significant negative impact on transportation safety, particularly in the port, highways, and airport runway areas. A multi-scale U-shaped dehazing network is proposed in this research, which is based on our multi-channel feature fusion attention structure. With the help of the feature fusion attention techniques, the model can focus on the intriguing locations with higher haze concentration area. In conjunction with UNet, it can achieve multi-scale feature reuse and residual learning, allowing it to fully utilize the feature information of each layer for image restoration. Experimental resulsts show that our technique performs well on a variety of test datasets. On highway data sets, the PSNR / SSIM / L∞ error performance over the novel technique is increased by 0.52% / 0.5% / 30.84%, 4.68% / 0.78% / 26.19% and 13.84% / 9.05% / 55.57% respectively, when compared to DehazeFormer, MIRNetv2, and FSDGN methods. The findings suggest that our proposed method performs better on image dehazing, especially in terms of L∞ error performance.


Subject(s)
Airports , Learning , Transportation , Weather
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