Simple and cost-effective way to make mobile antibiotic cement spacer: hand-made silicone mold.

BACKGROUND: Two-stage exchange arthroplasty is considered the most common approach for the management of prosthetic joint infections. There has been plentiful evidence to support the superiority of the mobile spacers over the static ones. Unfortunately, articulating options are not available in our low-resource environment, which motivated us to come up with an affordable way to create a mobile cement spacer. After experimenting with a variety of materials and producing methods, we realized that silicone is a favorable material for mold building and established a simple process of making a handmade silicone mold. We demonstrate the clinical outcomes of three prosthetic joint infections by using these spacers in the hope of spreading the idea to our colleagues who work in the circumstances of a developing country. Construction of the spacer molds: The molds, consisting of two parts, were shaped by using high viscosity addition silicone (elite HD+ putty soft, Zhermack SpA, Italy) as material, and previously removed implants as template. They were sterilized using ethylene oxide treatment before being ready for casting antibiotic-loaded bone cement spacer. CASE REPORT: Three cases of prosthetic infection were treated with two-stage revision, using antibiotic-impregnated cement spacer cast in hand-made silicone molds. We sought to determine intraoperative complications, postoperative range of motion, and functional scores. All the patients were regularly followed up to identify fractures or dislocation of the spacer, and reinfection. RESULTS: At the end of the follow-up, all three patients had the infection eradicated. The three patients could sit comfortably with bent knees, walk with partial weight-bearing, and achieve 75-80 degrees of knee flexion in the first week after surgery. Follow-up X-rays revealed no fractures or dislocation in any of the spacers. CONCLUSION: Silicone molds offer a simple and cost-effective alternative to costly commercial products in producing articulating spacers. Treating infected joints arthroplasty with these spacers allows for early motion and partial weight bearing and improves patient satisfaction and life quality before reimplantation without significant complications.

Smart Low Level Laser Therapy System for Automatic Facial Dermatological Disorder Diagnosis.

Computer-aided diagnosis using dermoscopy images is a promising technique for improving the efficiency of facial skin disorder diagnosis and treatment. Hence, in this study, we propose a low-level laser therapy (LLLT) system with a deep neural network and medical internet of things (MIoT) assistance. The main contributions of this study are to (1) provide a comprehensive hardware and software design for an automatic phototherapy system, (2) propose a modified-U2Net deep learning model for facial dermatological disorder segmentation, and (3) develop a synthetic data generation process for the proposed models to address the issue of the limited and imbalanced dataset. Finally, a MIoT-assisted LLLT platform for remote healthcare monitoring and management is proposed. The trained U2-Net model achieved a better performance on untrained dataset than other recent models, with an average Accuracy of 97.5%, Jaccard index of 74.7%, and Dice coefficient of 80.6%. The experimental results demonstrated that our proposed LLLT system can accurately segment facial skin diseases and automatically apply for phototherapy. The integration of artificial intelligence and MIoT-based healthcare platforms is a significant step toward the development of medical assistant tools in the near future.

A Flexible, Wearable, and Wireless Biosensor Patch with Internet of Medical Things Applications.

Monitoring the vital signs and physiological responses of the human body in daily activities is particularly useful for the early diagnosis and prevention of cardiovascular diseases. Here, we proposed a wireless and flexible biosensor patch for continuous and longitudinal monitoring of different physiological signals, including body temperature, blood pressure (BP), and electrocardiography. Moreover, these modalities for tracking body movement and GPS locations for emergency rescue have been included in biosensor devices. We optimized the flexible patch design with high mechanical stretchability and compatibility that can provide reliable and long-term attachment to the curved skin surface. Regarding smart healthcare applications, this research presents an Internet of Things-connected healthcare platform consisting of a smartphone application, website service, database server, and mobile gateway. The IoT platform has the potential to reduce the demand for medical resources and enhance the quality of healthcare services. To further address the advances in non-invasive continuous BP monitoring, an optimized deep learning architecture with one-channel electrocardiogram signals is introduced. The performance of the BP estimation model was verified using an independent dataset; this experimental result satisfied the Association for the Advancement of Medical Instrumentation, and the British Hypertension Society standards for BP monitoring devices. The experimental results demonstrated the practical application of the wireless and flexible biosensor patch for continuous physiological signal monitoring with Internet of Medical Things-connected healthcare applications.

Enhanced precision of real-time control photothermal therapy using cost-effective infrared sensor array and artificial neural network.

Photothermal therapy (PTT) requires tight thermal dose control to achieve tumor ablation with minimal thermal injury on surrounding healthy tissues. In this study, we proposed a real-time closed-loop system for monitoring and controlling the temperature of PTT using a non-contact infrared thermal sensor array and an artificial neural network (ANN) to induce a predetermined area of thermal damage on the tissue. A cost-effective infrared thermal sensor array was used to monitor the temperature development for feedback control during the treatment. The measured and predicted temperatures were used as inputs of fuzzy control logic controllers that were implemented on an embedded platform (Jetson Nano) for real-time thermal control. Three treatment groups (continuous wave = CW, conventional fuzzy logic = C-Fuzzy, and ANN-based predictive fuzzy logic = P-Fuzzy) were examined and compared to investigate the laser heating performance and collect temperature data for ANN model training. The ex vivo experiments validated the efficiency of fuzzy control with temperature method on maintaining the constant interstitial tissue temperature (80 ± 1.4 °C) at a targeted surface of the tissue. The linear relationship between coagulation areas and the treatment time was indicated in this study, with the averaged coagulation rate of 0.0196 cm2/s. A thermal damage area of 1.32 cm2 (diameter ∼1.3 cm) was observed under P-Fuzzy condition for 200 s, which covered the predetermined thermal damage area (diameter ∼1 cm). The integration of real-time feedback temperature control with predictive ANN could be a feasible approach to precisely induce the preset extent of thermal coagulation for treating papillary thyroid microcarcinoma.

A smart LED therapy device with an automatic facial acne vulgaris diagnosis based on deep learning and internet of things application.

In low-level laser therapy, providing an optimal dosage and proposing a proper diagnosis before dermatological treatment are essential to reduce the side effects and potential dangers. In this article, a smart LED therapy system for automatic facial acne vulgaris diagnosis based on deep learning and Internet of Things application is proposed. The main goals of this study were to (1) develop an LED therapy device with different power densities and LED grid control; (2) propose a deep learning model based on modified ResNet50 and YOLOv2 for an automatic acne diagnosis; and (3) develop a smartphone application for facial photography image capture and LED therapy parameter configuration. Furthermore, a healthcare Internet of Things (H-IoT) platform for the connectivity between smartphone apps, the cloud server, and the LED therapy device is proposed to improve the efficiency of the treatment process. Experiments were conducted on test data sets divided by a cross-validation method to verify the feasibility of the proposed LED therapy system with automatic facial acne detection. The obtained results evidenced the practical application of the proposed LED therapy system for automatic acne diagnosis and H-IoT-based solutions.

Roles of Chitosan in Green Synthesis of Metal Nanoparticles for Biomedical Applications.

Chitosan (CS) is a well-known stabilizer for metal nanoparticles in biomedical engineering. However, very few studies have explored other important roles of CS including reducing, shape-directing, and size-controlling. This review aims to provide the latest and most comprehensive overview of the roles of CS in the green synthesis of metal nanoparticles for biomedical applications. To the best of our knowledge, this is the first review that highlights these potentialities of CS. At first, a brief overview of the properties and the bioactivity of CS is presented. Next, the benefits of CS for enhancing the physicochemical behaviors of metal nanoparticles are discussed in detail. The representative biomedical applications of CS-metal nanoparticles are also given. Lastly, the review outlines the perceptual vision for the future development of CS-metal nanoparticles in the biomedicine field.

A portable device with low-power consumption for monitoring mouse vital signs during in vivo photoacoustic imaging and photothermal therapy.

OBJECTIVE: The aim of this study was to monitor the physiological changes and cytotoxic effects of exogenous contrast agents during photoacoustic imaging (PAI) and photothermal therapy (PTT). In this paper, a low-power telemetric device for mouse vital signs monitoring was designed and demonstrated. APPROACH: The power consumption was optimized through hardware and software co-design with a 17% increased operating time compared with typical operation. To demonstrate the feasibility of the monitoring device, PAI and PTT experiments with chitosan-polypyrrole nanocomposites (CS-PPy NCs) as exogenous contrast agents were conducted. Herein, the physiological variation in groups of mice with different CS-PPy NC concentrations was observed and analyzed. MAIN RESULTS: The experimental results indicated the influence of CS-PPy NCs and anesthesia on mouse vital signs in PAI and PTT. Additionally, the association between core temperature, heart rate, and saturation of peripheral oxygen (SpO2) during PAI and PTT was shown. The strong near-infrared absorbance of exogenous contrast agents could account for the increase in mouse core temperature and tumor temperature in this study. Furthermore, high cross-correlation values between core temperature, heart rate, and SpO2 were demonstrated to explain the fluctuation of mouse vital signs during PAI and PTT. SIGNIFICANCE: A design of a vital signs monitoring device, with low power consumption, was introduced in this study. A high cross correlation coefficient of mouse vital signs and the effects of CS-PPy NCs were observed, which explained the mouse physiological variation during the PAI and PTT experiments.

Development of a LED light therapy device with power density control using a Fuzzy logic controller.

The biological effects of a light-emitting diode (LED) light therapy device are determined by irradiation parameters, mainly wavelength and power density. However, using a battery to provide power causes a problem in the variation of LED power density during battery discharge. As a result, maintaining a stable LED power density, along with extending battery life and operating time, are the primary concerns in designing a LED light therapy device. The present study aims to introduce a LED light therapy device design with different LED color power density control. A Fuzzy logic, based on the relationship between LED power density and operating time, was proposed to control constant power density in this design. The experimental results demonstrate that by using the designed controller, the LED light therapy device's power density (40 mW/cm2, 50 mW/cm2, 60 mW/cm2 for red, blue, and green light, respectively) can be controlled. The newly designed LED light therapy device could be considered an advanced version with energy savings and stabilized LED power emitting property under a broad range voltage variation.