Prevalence and risk factors of epiretinal membrane: Data from the Korea National Health and Nutrition Examination Survey VII (2017-2018).

BACKGROUND: To determine the prevalence and risk factors of epiretinal membrane (ERM) utilising spectral-domain optical coherence tomography (SD-OCT). METHODS: We investigated data from the 2017 to 2018 Korea National Health and Nutrition Examination Survey. Individuals aged ≥40 years with readable fundus photographs and SD-OCT results were included. ERM was diagnosed by fundus photography and OCT. The following data was collected: demographics, health interview, health examination, and nutritional survey results. The prevalence of ERM was estimated and risk factors for ERM were analysed. RESULTS: A total of 6807 participants were finally included. Adjusted prevalence of ERM was 7.0% (95% confidence interval, 6.3%-7.8%). Multivariate logistic regression analysis revealed that age ≥ 50 years (p < 0.001 for all age groups), history of cataract surgery (p < 0.001), well-controlled hypertension (p = 0.006), and diabetic retinopathy (p = 0.041) were risk factors for ERM. CONCLUSIONS: The estimated prevalence of ERM was 7.0%, which was higher than that of previous reports using fundus photography only in an East Asian population. Possible risk factors for ERM were older age, history of cataract surgery, hypertension, and diabetic retinopathy.

A Transparent Nanopatterned Chemiresistor: Visible-Light Plasmonic Sensor for Trace-Level NO2 Detection at Room Temperature.

The highly selective detection of trace gases using transparent sensors at room temperature remains challenging. Herein, transparent nanopatterned chemiresistors composed of aligned 1D Au-SnO2 nanofibers, which can detect toxic NO2 gas at room temperature under visible light illumination is reported. Ten straight Au-SnO2 nanofibers are patterned on a glass substrate with transparent electrodes assisted by direct-write, near-field electrospinning, whose extremely low coverage of sensing materials (≈0.3%) lead to the high transparency (≈93%) of the sensor. The sensor exhibits a highly selective, sensitive, and reproducible response to sub-ppm levels of NO2 , and its detection limit is as low as 6 ppb. The unique room-temperature NO2 sensing under visible light emanates from the localized surface plasmonic resonance effect of Au nanoparticles, thereby enabling the design of new transparent oxide-based gas sensors without external heaters or light sources. The patterning of nanofibers with extremely low coverage provides a general strategy to design diverse compositions of gas sensors, which can facilitate the development of a wide range of new applications in transparent electronics and smart windows wirelessly connected to the Internet of Things.

Prolonged water immersion alters resistance to sliding of aesthetic orthodontic coated wires.

OBJECTIVE: The objective of this study was to compare the resistance to sliding of aesthetic orthodontic coated wires after prolonged water immersion for up to 4 weeks. SETTING AND SAMPLE POPULATION: An in vitro study of commercially available orthodontic appliances. MATERIALS AND METHODS: Aesthetic coated stainless-steel wires (Parylene-coated, epoxy-coated and Teflon-coated) (0.019" × 0.025") and an uncoated control were immersed in distilled-deionized water for zero, two or four weeks at 37°C and then were subjected to resistance-to-sliding tests through a three-bracket system of sapphire ceramic brackets (0.022" × 0.028" slot) and clear-coloured elastic ligatures at a contact angle of 0° or 3°. Maximal and average resistance to sliding was analysed by a three-way analysis of variance, two general linear models and a post hoc Tukey's honest significant difference test. RESULTS: Water immersion time, contact angle, wire group and their interactions had statistically significant effects on the resistance to sliding of tested orthodontic wires. Various coated wires had distinct timely changes in the maximal and average resistance to sliding after water immersion for 2 to 4 weeks. When compared to the uncoated control in most of the experimental conditions, epoxy-coated wires had lower or non-significant differences in resistance to sliding, while Parylene-coated wire had higher resistances. CONCLUSIONS: Prolonged water immersion for weeks alters the resistance to sliding of aesthetic orthodontic wires coated with Parylene, epoxy or Teflon. Based on their resistance to sliding, different designs in orthodontic biomechanics should be considered for the different aesthetic orthodontic coated wires.

TIMA SLAM: Tracking Independently and Mapping Altogether for an Uncalibrated Multi-Camera System.

We present a novel simultaneous localization and mapping (SLAM) system that extends the state-of-the-art ORB-SLAM2 for multi-camera usage without precalibration. In this system, each camera is tracked independently on a shared map, and the extrinsic parameters of each camera in the fixed multi-camera system are estimated online up to a scalar ambiguity (for RGB cameras). Thus, the laborious precalibration of extrinsic parameters between cameras becomes needless. By optimizing the map, the keyframe poses, and the relative poses of the multi-camera system simultaneously, observations from the multiple cameras are utilized robustly, and the accuracy of the shared map is improved. The system is not only compatible with RGB sensors but also works on RGB-D cameras. For RGB cameras, the performance of the system tested on the well-known EuRoC/ASL and KITTI datasets that are in the stereo configuration for indoor and outdoor environments, respectively, as well as our dataset that consists of three cameras with small overlapping regions. For the RGB-D tests, we created a dataset that consists of two cameras for an indoor environment. The experimental results showed that the proposed method successfully provides an accurate multi-camera SLAM system without precalibration of the multi-cameras.

FBG-referenced interrogating system using a double-ring erbium-doped fiber laser for high power and broadband.

In this study, a double-ring erbium-doped fiber (EDF) laser with an optical switch and a fiber Bragg grating (FBG)-referenced interrogating system was developed and demonstrated. This double-ring configuration can achieve high power amplified spontaneous emission, enabling laser oscillation even within the L-band. The output range and signal-to-noise ratio (SNR) of the double-ring EDF laser were measured to be 1512-1610 nm and 55 dB. In addition, the interrogating system using FBGs for reference resulted in precision improvement of ∼25 pm over those achieved in previous studies, reaching a precision of about 7 pm. The high power, broad tuning range, and sufficiently high precision of the proposed interrogating system make it promising for use in FBG-based sensing applications.

Wearable Hand Module and Real-Time Tracking Algorithms for Measuring Finger Joint Angles of Different Hand Sizes with High Accuracy using FBG Strain Sensor.

This paper presents a wearable hand module which was made of five fiber Bragg grating (FBG) strain sensor and algorithms to achieve high accuracy even when worn on different hand sizes of users. For real-time calculation with high accuracy, FBG strain sensors move continuously according to the size of the hand and the bending of the joint. Representatively, four algorithms were proposed; point strain (PTS), area summation (AREA), proportional summation (PS), and PS/interference (PS/I or PS/I_α). For more accurate and efficient assessments, 3D printed hand replica with different finger sizes was adopted and quantitative evaluations were performed for index~little fingers (77 to 117 mm) and thumb (68~78 mm). For index~little fingers, the optimized algorithms were PS and PS/I_α. For thumb, the optimized algorithms were PS/I_α and AREA. The average error angle of the wearable hand module was observed to be 0.47 ± 2.51° and mean absolute error (MAE) was achieved at 1.63 ± 1.97°. These results showed that more accurate hand modules than other glove modules applied to different hand sizes can be manufactured using FBG strain sensors which move continuously and algorithms for tracking this movable FBG sensors.

Ultra-high curvature sensors for multi-bend structures using fiber Bragg gratings.

Measuring high curvatures is essential in various applications such as structural engineering, medical treatment, and robotics. Herein, we present a novel ultra-high curvature sensor with an ultra-thin and highly flexible structure incorporating fiber Bragg gratings (FBGs). The sensor can measure curvature of bidirectional bending up to 200 m-1. In addition, the multi-bend curvature sensor in conjunction with the proposed calibration scheme enables the accurate reconstruction of a curve with varying curvature. The sensitivity and the accuracy of the curvature sensor are investigated for different sensor designs. Finally, we demonstrate the accurate shape sensing of various 2-D patterns using the multi-bend curvatures sensor.

Micro-scale roughening of glass substrates using carbon nanotube-driven templates for enhancements in white luminescence characteristics.

A novel way of roughening the surface of a glass substrate using a carbon nanotube-driven template is introduced to enhance the white luminescence characteristics of a printed (Ba,Sr,Ca)2SiO4:Eu2+ yellow silicate phosphor layer. The distribution of closed pores in the template layer induces selective etching and micro-scale roughening. As a result, a substantial improvement of ∼22.5% in the luminous efficacy was achieved when both sides of the substrate were roughened. This is attributed to the reductions of both the total internal reflection of rays at the glass-air interface and the specular reflection at the phosphor-glass interface.

Structure-From-Motion in 3D Space Using 2D Lidars.

This paper presents a novel structure-from-motion methodology using 2D lidars (Light Detection And Ranging). In 3D space, 2D lidars do not provide sufficient information for pose estimation. For this reason, additional sensors have been used along with the lidar measurement. In this paper, we use a sensor system that consists of only 2D lidars, without any additional sensors. We propose a new method of estimating both the 6D pose of the system and the surrounding 3D structures. We compute the pose of the system using line segments of scan data and their corresponding planes. After discarding the outliers, both the pose and the 3D structures are refined via nonlinear optimization. Experiments with both synthetic and real data show the accuracy and robustness of the proposed method.

A New Strategy for Humidity Independent Oxide Chemiresistors: Dynamic Self-Refreshing of In2 O3 Sensing Surface Assisted by Layer-by-Layer Coated CeO2 Nanoclusters.

The humidity dependence of the gas sensing characteristics of metal oxide semiconductors has been one of the greatest obstacles for gas sensor applications during the last five decades because ambient humidity dynamically changes with the environmental conditions. Herein, a new and novel strategy is reported to eliminate the humidity dependence of the gas sensing characteristics of oxide chemiresistors via dynamic self-refreshing of the sensing surface affected by water vapor chemisorption. The sensor resistance and gas response of pure In2 O3 hollow spheres significantly change and deteriorate in humid atmospheres. In contrast, the humidity dependence becomes negligible when an optimal concentration of CeO2 nanoclusters is uniformly loaded onto In2 O3 hollow spheres via layer-by-layer (LBL) assembly. Moreover, In2 O3 sensors LBL-coated with CeO2 nanoclusters show fast response/recovery, low detection limit (500 ppb), and high selectivity to acetone even in highly humid conditions (relative humidity 80%). The mechanism underlying the dynamic refreshing of the In2 O3 sensing surfaces regardless of humidity variation is investigated in relation to the role of CeO2 and the chemical interaction among CeO2 , In2 O3 , and water vapor. This strategy can be widely used to design high performance gas sensors including disease diagnosis via breath analysis and pollutant monitoring.

Designs and processes toward high-aspect-ratio nanostructures at the deep nanoscale: unconventional nanolithography and its applications.

The patterning of high-resolution-featured deep-nanoscale structures with a high aspect ratio (AR) has received increasing attention in recent years as a promising technique for a wide range of applications, including electrical, optical, mechanical and biological systems. Despite extensive efforts to develop viable nanostructure fabrication processes, a superior technique enabling defect-free, high-resolution control over a large area is still required. In this review, we focus on recent important advances in the designs and processes of high-resolution nanostructures possessing a high AR, including hierarchical and 3D patterns. The unique applications of these materials are also discussed.

UV-curable silicate phosphor planar films printed on glass substrate for white light-emitting diodes.

We suggest a simple way of forming a nonconventional remote phosphor layer for white light-emitting diodes. A printing technology using a paste consisting of yellow (Ba,Sr,Ca)(2)SiO(4):Eu(2+) silicate phosphor and ultraviolet (UV)-curable polymer is applied to form solid planar films on a common soda lime silicate glass substrate through UV radiation. Relative content of the phosphor was adjusted for the best dispersion of the phosphor particles in the polymer matrix with better emission and luminescence performance. As a result, the 70 wt. % phosphor-embedded film has a luminous efficacy of ∼70.1 lm/W at 200 mA.

Usefulness of Noninvasive Positive-pressure Ventilation During Surgery of Flaccid Neuromuscular Scoliosis.

STUDY DESIGN: This is a retrospective study. OBJECTIVE: To assess the effects of noninvasive positive-pressure ventilation (NIPPV) through evaluations of outcomes and incidences of postoperative pulmonary complications among patients with flaccid neuromuscular scoliosis for pulmonary support in the perioperative periods. BACKGROUND DATA: There is no report on the effects of NIPPV on neuromuscular scoliosis patient during the perioperative periods. METHODS: We retrospectively reviewed 73 patients diagnosed with neuromuscular scoliosis who underwent staged anterior and posterior spinal surgery and instrumentations for deformity correction from 2003 to 2010. A total of 73 patients were divided depending on whether they had received NIPPV treatment or not during the perioperative period. Twenty-eight patients who received NIPPV for respiratory support and 45 patients with no mechanical ventilation were compared according to age, sex, body mass index, number of fusion levels, and end-tidal pressure of CO(2) and forced vital capacity values. The incidence of pulmonary complications associated with either group (pneumonia, atelectasis, pneumothorax, prolonged ventilator support, and postoperative tracheostomy) was then evaluated. RESULTS: In between the 2 groups, the forced vital capacity (41% vs. 64%, P<0.0001) were observed to be significantly decreased with the use of NIPPV. End-tidal pressure of CO(2) was not statistically different between the 2 groups. Although statistically not significant, patients in the non-NIPPV group had a higher incidence of pulmonary complications (38% vs. 21%, P=0.1584). None of the aforementioned patients required tracheostomy. In addition, no other mortality or neurological complications were noted postoperatively. CONCLUSIONS: There is a definite advantage of using NIPPV, because the incidence of postoperative pulmonary complications and the need for tracheostomy in patients with severely decreased pulmonary function are not increased from the use of NIPPV.

BNNT vs. CNT: influence of structural defects on damping characteristics of nanocomposites.

The viscoelastic damping of nanocomposites reinforced with BNNTs and CNTs was compared. MD simulations revealed that the interfacial damping of pristine-CNT was superior to that of pristine-BNNT. The contrasting effects of structural defects were elucidated using interfacial adhesion, interphase, and overlapping phonon density of states in the nanotubes and polymers.

Dysregulation of histone deacetylases in ocular diseases.

Ocular diseases are a growing global concern and have a significant impact on the quality of life. Cataracts, glaucoma, age-related macular degeneration, and diabetic retinopathy are the most prevalent ocular diseases. Their prevalence and the global market size are also increasing. However, the available pharmacotherapy is currently limited. These diseases share common pathophysiological features, including neovascularization, inflammation, and/or neurodegeneration. Histone deacetylases (HDACs) are a class of enzymes that catalyze the removal of acetyl groups from lysine residues of histone and nonhistone proteins. HDACs are crucial for regulating various cellular processes, such as gene expression, protein stability, localization, and function. They have also been studied in various research fields, including cancer, inflammatory diseases, neurological disorders, and vascular diseases. Our study aimed to investigate the relationship between HDACs and ocular diseases, to identify a new strategy for pharmacotherapy. This review article explores the role of HDACs in ocular diseases, specifically focusing on diabetic retinopathy, age-related macular degeneration, and retinopathy of prematurity, as well as optic nerve disorders, such as glaucoma and optic neuropathy. Additionally, we explore the interplay between HDACs and key regulators of fibrosis and angiogenesis, such as TGF-ß and VEGF, highlighting the potential of targeting HDAC as novel therapeutic strategies for ocular diseases.

Accuracy of posteroanterior cephalogram landmarks and measurements identification using a cascaded convolutional neural network algorithm: A multicenter study.

Objective: : To quantify the effects of midline-related landmark identification on midline deviation measurements in posteroanterior (PA) cephalograms using a cascaded convolutional neural network (CNN). Methods: : A total of 2,903 PA cephalogram images obtained from 9 university hospitals were divided into training, internal validation, and test sets (n = 2,150, 376, and 377). As the gold standard, 2 orthodontic professors marked the bilateral landmarks, including the frontozygomatic suture point and latero-orbitale (LO), and the midline landmarks, including the crista galli, anterior nasal spine (ANS), upper dental midpoint (UDM), lower dental midpoint (LDM), and menton (Me). For the test, Examiner-1 and Examiner-2 (3-year and 1-year orthodontic residents) and the Cascaded-CNN models marked the landmarks. After point-to-point errors of landmark identification, the successful detection rate (SDR) and distance and direction of the midline landmark deviation from the midsagittal line (ANS-mid, UDM-mid, LDM-mid, and Me-mid) were measured, and statistical analysis was performed. Results: : The cascaded-CNN algorithm showed a clinically acceptable level of point-to-point error (1.26 mm vs. 1.57 mm in Examiner-1 and 1.75 mm in Examiner-2). The average SDR within the 2 mm range was 83.2%, with high accuracy at the LO (right, 96.9%; left, 97.1%), and UDM (96.9%). The absolute measurement errors were less than 1 mm for ANS-mid, UDM-mid, and LDM-mid compared with the gold standard. Conclusions: : The cascaded-CNN model may be considered an effective tool for the auto-identification of midline landmarks and quantification of midline deviation in PA cephalograms of adult patients, regardless of variations in the image acquisition method.

Osteochondral Repair with Autologous Cartilage Transplantation with or without Bone Grafting: A Short Pilot Study in Mini-Pigs.

OBJECTIVE: Treatment strategies for osteochondral defects, for which particulated autologous cartilage transplantation (PACT) is an emerging treatment strategy, aim to restore the structure and function of the hyaline cartilage. Herein, we compared the efficacy of PACT with control or human transforming growth factor-ß (rhTGF-ß), and clarified the necessity of bone graft (BG) with PACT to treat shallow osteochondral defects in a porcine model. DESIGN: Two skeletally mature male micropigs received 4 osteochondral defects in each knee. The 16 defects were randomized to (1) empty control, (2) PACT, (3) PACT with BG, or (4) rhTGF-ß. Animals were euthanized after 2 months and histomorphometry, immunofluorescence analysis, semiquantitative evaluation (O'Driscoll score), and magnetic resonance observation of cartilage repair tissue (MOCART) score were performed. RESULTS: Hyaline cartilages, glycosaminoglycan synthesis, and collagen type II staining were more abundant in the PACT than in the control and rhTGF-ß groups. The O'Driscoll score was significantly different between groups (P < 0.001), with both PACT groups showing superiority (P = 0.002). PACT had the highest score (P = 0.002), with improved restoration of subchondral bone compared with PACT with BG. The MOCART score showed significant differences between groups (P = 0.021); MOCART and O'Driscoll scores showed high correlation (r = 0.847, P < 0.001). CONCLUSION: Treatment of osteochondral defects with PACT improved tissue quality compared with that with control or rhTGF-ß in a porcine model. BG, in addition to PACT, may be unnecessary for shallow osteochondral defects. Clinical Relevance. BG may not be necessary while performing PACT.

Orthognathic surgical planning using graph CNN with dual embedding module: External validations with multi-hospital datasets.

BACKGROUND AND OBJECTIVE: Despite recent development of AI, prediction of the surgical movement in the maxilla and mandible by OGS might be more difficult than that of tooth movement by orthodontic treatment. To evaluate the prediction accuracy of the surgical movement using pairs of pre-(T0) and post-surgical (T1) lateral cephalograms (lat-ceph) of orthognathic surgery (OGS) patients and dual embedding module-graph convolution neural network (DEM-GCNN) model. METHODS: 599 pairs from 3 institutions were used as training, internal validation, and internal test sets and 201 pairs from other 6 institutions were used as external test set. DEM-GCNN model (IEM, learning the lat-ceph images; LTEM, learning the landmarks) was developed to predict the amount and direction of surgical movement of ANS and PNS in the maxilla and B-point and Md1crown in the mandible. The distance between T1 landmark coordinates actually moved by OGS (ground truth) and predicted by DEM-GCNN model and pre-existed CNN-based Model-C (learning the lat-ceph images) was compared. RESULTS: In both internal and external tests, DEM-GCNN did not exhibit significant difference from ground truth in all landmarks (ANS, PNS, B-point, Md1crown, all P > 0.05). When the accumulated successful detection rate for each landmark was compared, DEM-GCNN showed higher values than Model-C in both the internal and external tests. In violin plots exhibiting the error distribution of the prediction results, both internal and external tests showed that DEM-GCNN had significant performance improvement in PNS, ANS, B-point, Md1crown than Model-C. DEM-GCNN showed significantly lower prediction error values than Model-C (one-jaw surgery, B-point, Md1crown, all P < 0.005; two-jaw surgery, PNS, ANS, all P < 0.05; B point, Md1crown, all P < 0.005). CONCLUSION: We developed a robust OGS planning model with maximized generalizability despite diverse qualities of lat-cephs from 9 institutions.

One-point versus two-point fixation in the management of zygoma complex fractures.

BACKGROUND: The treatment of zygoma complex fractures is of crucial importance in the field of plastic surgery. However, surgical methods to correct zygoma complex fractures, including the number of fixation sites, differ among operators. Although several studies have compared two-point and three-point fixation, no comparative research has yet been conducted on one-point versus two-point fixation using computed tomography scans of surgical results. Therefore, the present study aimed to address this gap in the literature by comparing surgical results between one-point and two-point fixation procedures. METHODS: In this study, we randomly selected patients to undergo surgery using one of two surgical methods. We analyzed patients with unilateral zygoma complex fractures unaccompanied by other fractures according to whether they underwent one-point fixation of the zygomaticomaxillary buttress or two-point fixation of the zygomaticomaxillary buttress and the zygomaticofrontal suture. We then made measurements at three points-the zygomaticofrontal suture, inferior orbital wall, and malar height-using 3-month postoperative computed tomography images and performed statistical analyses to compare the results of the two methods. RESULTS: All three measurements (zygomaticofrontal suture, inferior orbital wall, and malar height) showed significant differences (p < 0.05) between one-point and two-point fixation. Highly significant differences were found for the zygomaticofrontal suture and malar height parameters. The difference in the inferior wall measurements was less meaningful, even though it also reached statistical significance. CONCLUSION: Using three parameters in a statistical analysis of imaging findings, this study demonstrated significant differences in treatment outcomes according to the number of fixations. The results indicate that bone alignment and continuity can be achieved to a greater extent by two-point fixation instead of one-point fixation.

Automated landmark identification for diagnosis of the deformity using a cascade convolutional neural network (FlatNet) on weight-bearing lateral radiographs of the foot.

Landmark detection in flatfoot radiographs is crucial in analyzing foot deformity. Here, we evaluated the accuracy and efficiency of the automated identification of flatfoot landmarks using a newly developed cascade convolutional neural network (CNN) algorithm, Flatfoot Landmarks AnnoTating Network (FlatNet). A total of 1200 consecutive weight-bearing lateral radiographs of the foot were acquired. The first 1050 radiographs were used as the training and tuning, and the following 150 radiographs were used as the test sets, respectively. An expert orthopedic surgeon (A) manually labeled ground truths for twenty-five anatomical landmarks. Two orthopedic surgeons (A and B, each with eight years of clinical experience) and a general physician (GP) independently identified the landmarks of the test sets using the same method. After two weeks, observers B and GP independently identified the landmarks once again using the developed deep learning CNN model (DLm). The X- and Y-coordinates and the mean absolute distance were evaluated. The average differences (mm) from the ground truth were 0.60 ± 0.57, 1.37 ± 1.28, and 1.05 ± 1.23 for the X-coordinate, and 0.46 ± 0.59, 0.97 ± 0.98, and 0.73 ± 0.90 for the Y-coordinate in DLm, B, and GP, respectively. The average differences (mm) from the ground truth were 0.84 ± 0.73, 1.90 ± 1.34, and 1.42 ± 1.40 for the absolute distance in DLm, B, and GP, respectively. Under the guidance of the DLm, the overall differences (mm) from the ground truth were enhanced to 0.87 ± 1.21, 0.69 ± 0.74, and 1.24 ± 1.31 for the X-coordinate, Y-coordinate, and absolute distance, respectively, for observer B. The differences were also enhanced to 0.74 ± 0.73, 0.57 ± 0.63, and 1.04 ± 0.85 for observer GP. The newly developed FlatNet exhibited better accuracy and reliability than the observers. Furthermore, under the FlatNet guidance, the accuracy and reliability of the human observers generally improved.