Towards optimal design of patient isolation units in emergency rooms to prevent airborne virus transmission: From computational fluid dynamics to data-driven modeling.

BACKGROUND: Patient isolation units (PIUs) can be an effective method for effective infection control. Computational fluid dynamics (CFD) is commonly used for PIU design; however, optimizing this design requires extensive computational resources. Our study aims to provide data-driven models to determine the PIU settings, thereby promoting a more rapid design process. METHOD: Using CFD simulations, we evaluated various PIU parameters and room conditions to assess the impact of PIU installation on ventilation and isolation. We investigated particle dispersion from coughing subjects and airflow patterns. Machine-learning models were trained using CFD simulation data to estimate the performance and identify significant parameters. RESULTS: Physical isolation alone was insufficient to prevent the dispersion of smaller particles. However, a properly installed fan filter unit (FFU) generally enhanced the effectiveness of physical isolation. Ventilation and isolation performance under various conditions were predicted with a mean absolute percentage error of within 13%. The position of the FFU was found to be the most important factor affecting the PIU performance. CONCLUSION: Data-driven modeling based on CFD simulations can expedite the PIU design process by offering predictive capabilities and clarifying important performance factors. Reducing the time required to design a PIU is critical when a rapid response is required.

Melanoma Detection by AFM Indentation of Histological Specimens.

Melanoma is visible unlike other types of cancer, but it is still challenging to diagnose correctly because of the difficulty in distinguishing between benign nevus and melanoma. We conducted a robust investigation of melanoma, identifying considerable differences in local elastic properties between nevus and melanoma tissues by using atomic force microscopy (AFM) indentation of histological specimens. Specifically, the histograms of the elastic modulus of melanoma displayed multimodal Gaussian distributions, exhibiting heterogeneous mechanical properties, in contrast with the unimodal distributions of elastic modulus in the benign nevus. We identified this notable signature was consistent regardless of blotch incidence by sex, age, anatomical site (e.g., thigh, calf, arm, eyelid, and cheek), or cancer stage (I, IV, and V). In addition, we found that the non-linearity of the force-distance curves for melanoma is increased compared to benign nevus. We believe that AFM indentation of histological specimens may technically complement conventional histopathological analysis for earlier and more precise melanoma detection.

A development of a graph-based ensemble machine learning model for skin sensitization hazard and potency assessment.

Many defined approaches (DAs) for skin sensitization assessment based on the adverse outcome pathway (AOP) have been developed to replace animal testing because the European Union has banned animal testing for cosmetic ingredients. Several DAs have demonstrated that machine learning models are beneficial. In this study, we have developed an ensemble prediction model utilizing the graph convolutional network (GCN) and machine learning approach to assess skin sensitization. The model integrates in silico parameters and data from alternatives to animal testing of well-defined AOP to improve DA predictivity. Multiple ensemble models were created using the probability produced by the GCN with six physicochemical properties, direct peptide reactivity assay, KeratinoSens™, and human cell line activation test (h-CLAT), using a multilayer perceptron approach. Models were evaluated by predicting the testing set's human hazard class and three potency classes (strong, weak, and non-sensitizer). When the GCN feature was used, 11 models out of 16 candidates showed the same or improved accuracy in the testing set. The ensemble model with the feature set of GCN, KeratinoSens™, and h-CLAT produced the best results with an accuracy of 88% for assessing human hazards. The best three-class potency model was created with the feature set of GCN and all three assays, resulting in 64% accuracy. These results from the ensemble approach indicate that the addition of the GCN feature could provide an improved predictivity of skin sensitization hazard and potency assessment.

3D cell culture using a clinostat reproduces microgravity-induced skin changes.

Exposure to microgravity affects human physiology in various ways, and astronauts frequently report skin-related problems. Skin rash and irritation are frequent complaints during space missions, and skin thinning has also been reported after returning to Earth. However, spaceflight missions for studying the physiological changes in microgravity are impractical. Thus, we used a previously developed 3D clinostat to simulate a microgravity environment and investigate whether physiological changes of the skin can be reproduced in a 3D in vitro setting. Our results showed that under time-averaged simulated microgravity (taSMG), the thickness of the endothelial cell arrangement increased by up to 59.75%, indicating skin irritation due to vasodilation, and that the diameter of keratinocytes and fibroblast co-cultured spheroids decreased by 6.66%, representing skin thinning. The α1 chain of type I collagen was upregulated, while the connective tissue growth factor was downregulated under taSMG. Cytokeratin-10 expression was significantly increased in the taSMG environment. The clinostat-based 3D culture system can reproduce physiological changes in the skin similar to those under microgravity, providing insight for understanding the effects of microgravity on human health before space exploration.

Sequential dual-drug delivery of BMP-2 and alendronate from hydroxyapatite-collagen scaffolds for enhanced bone regeneration.

The clinical use of bioactive molecules in bone regeneration has been known to have side effects, which result from uncontrolled and supraphysiological doses. In this study, we demonstrated the synergistic effect of two bioactive molecules, bone morphogenic protein-2 (BMP-2) and alendronate (ALN), by releasing them in a sequential manner. Collagen-hydroxyapatite composite scaffolds functionalized using BMP-2 are loaded with biodegradable microspheres where ALN is encapsulated. The results indicate an initial release of BMP-2 for a few days, followed by the sequential release of ALN after two weeks. The composite scaffolds significantly increase osteogenic activity owing to the synergistic effect of BMP-2 and ALN. Enhanced bone regeneration was identified at eight weeks post-implantation in the rat 8-mm critical-sized defect. Our findings suggest that the sequential delivery of BMP-2 and ALN from the scaffolds results in a synergistic effect on bone regeneration, which is unprecedented. Therefore, such a system exhibits potential for the application of cell-free tissue engineering.

Enhanced predictive capacity using dual-parameter chip model that simulates physiological skin irritation.

Current alternatives to animal testing methods for skin irritation evaluation such as reconstructed human epidermis models are not fully representing physiological response caused by skin irritants. Skin irritation is physiologically induced by the dilation and increased permeability of endothelial cells. Thus, our objectives were to mimic physiological skin irritation using a skin-on-a-chip model and compare predictive capacities with a reconstructed human epidermis model to evaluate its effectiveness. To achieve our goals, the skin-on-a-chip model, consisting of three layers representing the epidermal, dermal and endothelial components, was adapted. Cell viability was measured using the OECD TG 439 protocol for test substance evaluation. The tight junctions of endothelial cells were also observed and measured to assess physiological responses to test substances. These parameters were used to physiologically evaluate cell-to-cell interactions induced by test substances and quantify model accuracy, sensitivity, and specificity. Based on in vivo data, the classification accuracy of twenty test substances using a dual-parameter chip model was 80%, which is higher than other methods. Besides, the chip model was more suitable for simulating human skin irritation. Therefore, it is important to note that the dual-parameter chip model possesses an enhanced predictive capacity and could serve as an alternative to animal testing for skin irritation.

Covalently Grafted 2-Methacryloyloxyethyl Phosphorylcholine Networks Inhibit Fibrous Capsule Formation around Silicone Breast Implants in a Porcine Model.

The surface of human silicone breast implants is covalently grafted at a high density with a 2-methacryloyloxyethyl phosphorylcholine (MPC)-based polymer. Addition of cross-linkers is essential for enhancing the density and mechanical durability of the MPC graft. The MPC graft strongly inhibits not only adsorption but also the conformational deformation of fibrinogen, resulting in the exposure of a buried amino acid sequence, γ377-395, which is recognized by inflammatory cells. Furthermore, the numbers of adhered macrophages and the amounts of released cytokines (MIP-1α, MIP-1ß, IL-8, TNFα, IL-1α, IL-1ß, and IL-10) are dramatically decreased when the MPC network is introduced at a high density on the silicone surface (cross-linked PMPC-silicone). We insert the MPC-grafted human silicone breast implants into Yorkshire pigs to analyze the in vivo effect of the MPC graft on the capsular formation around the implants. After 6 month implantation, marked reductions of inflammatory cell recruitment, inflammatory-related proteins (TGF-ß and myeloperoxidase), a myoblast marker (α-smooth muscle actin), vascularity-related factors (blood vessels and VEGF), and, most importantly, capsular thickness are observed on the cross-linked PMPC-silicone. We propose a mechanism of the MPC grafting effect on fibrous capsular formation around silicone implants on the basis of the in vitro and in vivo results.

Efficient reduction of fibrous capsule formation around silicone breast implants densely grafted with 2-methacryloyloxyethyl phosphorylcholine (MPC) polymers by heat-induced polymerization.

Implants based on silicone elastomers, polydimethylsiloxane (PDMS), have been widely used for breast augmentation and reconstruction, but excessive foreign body reactions around implants often cause serious side effects such as capsular contracture. In our previous study, we covalently grafted 2-methacryloyloxyethyl phosphorylcholine (MPC)-based polymers on the surface of PDMS blocks by UV-induced polymerization and showed effective reduction of capsular formation around the MPC-grafted PDMS in rats. In the present study, we examined the efficacy of heat-induced polymerization of MPC grafting on silicone breast implants intended for humans, and analyzed the in vivo inhibitory effect against capsular formation and inflammation in pigs, which are closely related to humans in terms of epidermal structures and fibrotic processes. The heat-induced polymerization provided a thicker MPC-grafted surface and was more effective than UV-induced polymerization for the grafting of complex shaped non-transparent implants. After 24-week implantation in the submuscular pockets of Yorkshire pigs, the heat-induced MPC-grafted breast implants showed 45% smaller capsular thickness and 20-30% lower levels of inflammatory markers such as myeloperoxidase (MPO), transforming growth factor-ß (TGF-ß), and α-smooth muscle actin (α-SMA) in surrounding tissues compared to non-grafted implants. This study provides important information for future clinical trials of MPC-grafted silicone implants.

The Effect of Temperature and Exposure Time on Stability of Cholesterol and Squalene in Latent Fingermarks Deposited on PVDF Membrane.

Cholesterol and squalene are fatty materials of latent fingermarks that can be utilized for dating methodologies and visualization techniques. Previous studies have suggested these compounds undergo degradation in fingermarks as a function of time (days) and light at ambient temperature. However, studies assessing how their composition changes at low and high temperatures over short periods of time (hours) have not been published previously. Here, we performed quantitative analysis of cholesterol and squalene in natural fingermark residue using PVDF membrane, after exposure to a range of temperatures (-20 to 100°C) for 4 and 8 h. We found that levels of both fatty materials remained constant at -20 to 60°C, but both showed significant reduction at 100°C, over short exposure times. These results indicate that cholesterol and squalene are detectable at -20 to 60°C, whereas at 100°C or higher, both are lost due to rapid thermal degradation.

Optimization and validation of a method to identify skin sensitization hazards using IL-1 α and IL-6 secretion from HaCaT.

Although many methods to assess sensitization have been investigated to replace animal testing, it is still imperative to develop an in vitro method to minimize the use of animals and to classify sensitizers. Recently, an assay using the human keratinocyte cell line (HaCaT) was developed as an alternative method. Our aim was to optimize this method and validate its ability to assess sensitization. The highest dose that resulted in 75% cell viability was determined for each test substance. Then, serial dilutions of the dose were applied to measure the levels of secreted proinflammatory cytokines. To optimize the assay, statistical analyses were performed to determine whether all of the doses tested were necessary to maintain the predictive values. Exclusion of the 0.5× dose did not change the predictive values drastically. To validate the optimized method, 22 substances were evaluated without the 0.5× dose, resulting in overall predictive values of 83.3% for sensitivity, 80.0% for specificity, and 81.8% for accuracy, which are comparable to results from other validated assays. These results suggest that statistical analysis can assist in development of alternative in vitro methods and that the optimized HaCaT cell assay is reproducible.

A Facial Recognition Mobile App for Patient Safety and Biometric Identification: Design, Development, and Validation.

BACKGROUND: Patient verification by unique identification is an important procedure in health care settings. Risks to patient safety occur throughout health care settings by failure to correctly identify patients, resulting in the incorrect patient, incorrect site procedure, incorrect medication, and other errors. To avoid medical malpractice, radio-frequency identification (RFID), fingerprint scanners, iris scanners, and other technologies have been implemented in care settings. The drawbacks of these technologies include the possibility to lose the RFID bracelet, infection transmission, and impracticality when the patient is unconscious. OBJECTIVE: The purpose of this study was to develop a mobile health app for patient identification to overcome the limitations of current patient identification alternatives. The development of this app is expected to provide an easy-to-use alternative method for patient identification. METHODS: We have developed a facial recognition mobile app for improved patient verification. As an evaluation purpose, a total of 62 pediatric patients, including both outpatient and inpatient, were registered for the facial recognition test and tracked throughout the facilities for patient verification purpose. RESULTS: The app was developed to contain 5 main parts: registration, medical records, examinations, prescriptions, and appointments. Among 62 patients, 30 were outpatients visiting plastic surgery department and 32 were inpatients reserved for surgery. Whether patients were under anesthesia or unconscious, facial recognition verified all patients with 99% accuracy even after a surgery. CONCLUSIONS: It is possible to correctly identify both outpatients and inpatients and also reduce the unnecessary cost of patient verification by using the mobile facial recognition app with great accuracy. Our mobile app can provide valuable aid to patient verification, including when the patient is unconscious, as an alternative identification method.

Skin-on-a-chip model simulating inflammation, edema and drug-based treatment.

Recent advances in microfluidic cell cultures enable the construction of in vitro human skin models that can be used for drug toxicity testing, disease study. However, current in vitro skin model have limitations to emulate real human skin due to the simplicity of model. In this paper, we describe the development of 'skin-on-a-chip' to mimic the structures and functional responses of the human skin. The proposed model consists of 3 layers, on which epidermal, dermal and endothelial components originated from human, were cultured. The microfluidic device was designed for co-culture of human skin cells and each layer was separated by using porous membranes to allow interlayer communication. Skin inflammation and edema were induced by applying tumor necrosis factor alpha on dermal layer to demonstrate the functionality of the system. The expression levels of proinflammatory cytokines were analyzed to illustrate the feasibility. In addition, we evaluated the efficacy of therapeutic drug testing model using our skin chip. The function of skin barrier was evaluated by staining tight junctions and measuring a permeability of endothelium. Our results suggest that the skin-on-a-chip model can potentially be used for constructing in vitro skin disease models or for testing the toxicity of cosmetics or drugs.

Fabrication of three-dimensional scan-to-print ear model for microtia reconstruction.

BACKGROUND: Microtia is a congenital deformity of the external ear that occurs in 1 of every 5000 births. Microtia reconstruction using traditional two-dimensional templates does not provide highly detailed ear shapes. Here, we describe the feasibility of using a three-dimensional (3D) ear model as a reference. MATERIALS AND METHODS: Seven children aged from 11 to 16 (6 grade III and 1 grade II microtia) were recruited from Seoul National University Children's Hospital, Korea. We generated 3D-computer-aided design models of each patient's ear by performing 3D laser scanning for a mirror-transformed cast of their normal ear. The 3D-printed ear model was used in microtia reconstruction surgery following the Nagata technique, and its shape was compared with the casted ear model. RESULTS: One patient experienced irritation caused by accidently pouring resin into the external auditory meatus, and another had minor skin necrosis; both complications were successfully treated. The average percentage differences of the superior, inferior, anterior, posterior, and lateral views between the casted and 3D-printed ear models were 1.17%, 1.48%, 1.64%, 1.80%, and 5.44%, respectively (average: 2.31%), where the difference between the casted ear models and traditional two-dimensional templates were 16.03% in average. CONCLUSIONS: Our results show that simple microtia reconstruction can be performed using 3D ear models. The 3D-printed ear models of each patient were consistent and accurately represented the thickness, depth, and height of the normal ear. The availability of the 3D-printed ear model in the operating room reduced the amount of unnecessary work during surgery.