Nanochemistry of gold: from surface engineering to dental healthcare applications.

Advancements in nanochemistry have led to the development of engineered gold nanostructures (GNSs) with remarkable potential for a variety of dental healthcare applications. These innovative nanomaterials offer unique properties and functionalities that can significantly improve dental diagnostics, treatment, and overall oral healthcare applications. This review provides an overview of the latest advancements in the design, synthesis, and application of GNSs for dental healthcare applications. Engineered GNSs have emerged as versatile tools, demonstrating immense potential across different aspects of dentistry, including enhanced imaging and diagnosis, prevention, bioactive coatings, and targeted treatment of oral diseases. Key highlights encompass the precise control over GNSs' size, crystal structure, shape, and surface functionalization, enabling their integration into sensing, imaging diagnostics, drug delivery systems, and regenerative therapies. GNSs, with their exceptional biocompatibility and antimicrobial properties, have demonstrated efficacy in combating dental caries, periodontitis, peri-implantitis, and oral mucosal diseases. Additionally, they show great promise in the development of advanced sensing techniques for early diagnosis, such as nanobiosensor technology, while their role in targeted drug delivery, photothermal therapy, and immunomodulatory approaches has opened new avenues for oral cancer therapy. Challenges including long-term toxicity, biosafety, immune recognition, and personalized treatment are under rigorous investigation. As research at the intersection of nanotechnology and dentistry continues to thrive, this review highlights the transformative potential of engineered GNSs in revolutionizing dental healthcare, offering accurate, personalized, and minimally invasive solutions to address the oral health challenges of the modern era.

Prediction of the risk of severe small bowel obstruction and effects of Houpu Paiqi mixture in patients undergoing surgery for small bowel obstruction.

AIM: Small bowel obstruction is a common condition that requires emergency surgery. Slow recovery of bowel function after surgery or the occurrence of one or more complications can exacerbate the disease and result in severe small bowel obstruction (SSBO), significantly impacting recovery. It is characterized by a failure to regain enteral nutrition promptly, requiring long-term intensive care. Therefore, it is necessary to identify factors that predict SSBO, to allow early intervention for patients likely to develop this condition. METHODS: Of the 260 patients who underwent emergency or elective surgery for small bowel obstruction between January 2018 and December 2022, 45 developed SSBO. The least absolute shrinkage and selection operator regression model was applied to optimize factor selection and multivariable logistic regression analysis was used to construct a predictive model. The performance and clinical utility of the nomogram were determined and internal validation was conducted. In addition, the effects of the Houpu Paiqi mixture on postoperative recovery were analyzed by comparing the clinical data of 28 patients who were treated with the mixture and 61patients who did not receive it. RESULTS: The predictors included in the prediction nomogram were age, peritonitis, intestinal resection and anastomosis, complications, operation time, Acute Physiology and Chronic Health Evaluation II score, white blood cell count, and procalcitonin level. The model had an area under the receiver operating characteristic curve of 0.948 (95% confidence interval: 0.814-0.956). Decision curve analysis demonstrated that the SSBO risk nomogram had a good net clinical benefit. In addition, treatment with the Houpu Paiqi mixture reduced postoperative exhaust time, postoperative defecation time, time to first postoperative liquid feed, and length of stay in hospital. CONCLUSIONS: We developed a nomogram that can assist clinicians in identifying patients at greater risk of SSBO, which may aid in early diagnosis and intervention. Additionally, we found that the Houpu Paiqi mixture promoted postoperative recovery.

A laser-engraved wearable gait recognition sensor system for exoskeleton robots.

As a reinforcement technology that improves load-bearing ability and prevents injuries, assisted exoskeleton robots have extensive applications in freight transport and health care. The perception of gait information by such robots is vital for their control. This information is the basis for motion planning in assistive and collaborative functions. Here, a wearable gait recognition sensor system for exoskeleton robots is presented. Pressure sensor arrays based on laser-induced graphene are developed with flexibility and reliability. Multiple sensor units are integrated into an insole to detect real-time pressure at key plantar positions. In addition, the circuit hardware and the algorithm are designed to reinforce the sensor system with the capability of gait recognition. The experimental results show that the accuracy of gait recognition by the proposed system is 99.85%, and the effectiveness of the system is further verified through testing on an exoskeleton robot.