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There is a major challenge to attach nanostructures on to the electrode surface while retaining their engineered morphology, high surface area, physiochemical features for promising sensing applications. In this study, we have grown vertically-aligned ZnO nanorods (NRs) on fluorine doped tin oxide (FTO) electrodes and decorated with CuO to achieve high-performance non-enzymatic glucose sensor. This unique CuO-ZnO NRs hybrid provides large surface area and an easy substrate penetrable structure facilitating enhanced electrochemical features towards glucose oxidation. As a result, fabricated electrodes exhibit high sensitivity (2961.7 μA mM −1  cm −2 ), linear range up to 8.45 mM, low limit of detection (0.40 μM), and short response time (<2 s), along with excellent reproducibility, repeatability, stability, selectivity, and applicability for glucose detection in human serum samples. Circumventing, the outstanding performance originating from CuO modified ZnO NRs acts as an efficient electrocatalyst for glucose detection and as well, provides new prospects to biomolecules detecting device fabrication.

Nano-structural optical filters embedded in elastomers having high mechanical tunability provide the geometric degree of freedom for selective light manipulation. The active control of spectral information in typical structural optical filters is highly limited due to the substrate rigidity. Herein, we present mechanochromic transmissive optical filters by employing flexible and stretchable polymer-embedded silicon nanostructures. Si-based nanowire arrays (Si-NWAs) have been introduced to exhibit parametric resonance characteristics by controlling the period and/or diameter. Furthermore, the spectral shift phenomenon by increased diffraction efficiency was observed after the application of a uniaxial tensile force, which depends on the period of Si-NWAs with a large index contrast between the silicon nanowire and elastomer. The strain-sensitive properties of tunable Si-NWAs filters induced by light diffraction were calculated by simulation based on wave optics. The spectral tunability and light filtering features were simply demonstrated by stretching the Si-NWAs’ optical filters. Our proposed structure provides potential opportunities for a wide variety of applications, including dynamic color display, visual strain sensor and anti-counterfeiting.

Perovskite microcells have a great potential to be applied to diverse types of optoelectronic devices including light-emitting diodes, photodetectors, and solar cells. Although several perovskite fabrication methods have been researched, perovskite microcells without a significant efficiency drop during the patterning and fabrication process could not be developed yet. We herein report the fabrication of high-efficiency perovskite microcells using swelling-induced crack propagation and the application of the microcells to colored solar windows. The key procedure is a swelling-induced lift-off process that leads to patterned perovskite films with high-quality interfaces. Thus, a power conversion efficiency (PCE) of 20.1 % could be achieved with the perovskite microcell, which is nearly same as the PCE of our unpatterned perovskite photovoltaic device (PV). The semi-transparent PV based on microcells exhibited a light utilization efficiency of 4.67 and a color rendering index of 97.5 %. The metal–insulator–metal structure deposited on the semi-transparent PV enabled to fabricate solar windows with vivid colors and high color purity. Perovskite microcells can be applied to various types of optoelectronic devices. Here, authors report high efficiency perovskite microcells fabricated using swelling-induced crack propagation and demonstrate solar windows using the microcells.

Artificial intelligence (AI) techniques can be a solution for delayed or misdiagnosed pneumothorax. This study developed, a deep-learning-based AI model to estimate the pneumothorax amount on a chest radiograph and applied it to a treatment algorithm developed by experienced thoracic surgeons. U-net performed semantic segmentation and classification of pneumothorax and non-pneumothorax areas. The pneumothorax amount was measured using chest computed tomography (volume ratio, gold standard) and chest radiographs (area ratio, true label) and calculated using the AI model (area ratio, predicted label). Each value was compared and analyzed based on clinical outcomes. The study included 96 patients, of which 67 comprised the training set and the others the test set. The AI model showed an accuracy of 97.8%, sensitivity of 69.2%, a negative predictive value of 99.1%, and a dice similarity coefficient of 61.8%. In the test set, the average amount of pneumothorax was 15%, 16%, and 13% in the gold standard, predicted, and true labels, respectively. The predicted label was not significantly different from the gold standard (p = 0.11) but inferior to the true label (difference in MAE: 3.03%). The amount of pneumothorax in thoracostomy patients was 21.6% in predicted cases and 18.5% in true cases.

The engineering of structural colors is currently a promising, rapidly emerging research field because structural colors of outstanding spatial resolution and durability can be generated using a sustainable production method. However, the restricted and saturated color range in micro/nano-fabricated structural ‘pigments’ has hindered the dissemination of structural color printing. Here, this article presents a spectral mixing color filter (SMCF), which is the concept of fine-tunable color systems, capable of addressing the current issues in structural color engineering, by stacking a vertical silicon nanowire array embedded in a transparent polymer onto ultrathin optical coating layers. These two photonic structures enable independent tuning the optical resonance of each structure, depending on geometrical parameters, such as the diameter of nanowires and thickness of absorbing medium. Hence, the SMCF facilitates the linear combination of two resonant spectra, thereby enabling fine-tuning and widening of the color gamut. Theoretical studies and experimental results reveal the detailed working mechanisms and extraordinary mechanical feature of the SMCF. Based on the analyses, the concept of flexible optical device, e . g ., a reflective anti-counterfeiting sticker, is demonstrated. Successful characterization demonstrates that the proposed strategy can promote the color controllability/purity of structural color and the applicability as flexible optical device.

ObjectiveChest pain is a common symptom in patients with hypertrophic cardiomyopathy (HCM), causing difficulty determining whether there is coexistent coronary artery disease (CAD). We investigated whether coronary computed tomography angiography (CCTA) can assess the prevalence and clinical significance of CAD in adult patients with HCM showing chest pain through longitudinal follow-up.MethodsIn 238 adult patients with HCM, who underwent CCTA for chest pain, we analyzed the degree of stenosis and adverse plaque characteristics (APCs) as CCTA variables. Three prediction models for adverse cardiovascular events (ACEs: all-cause mortality, myocardial infarction, unstable angina, heart failure, implantable cardioverter-defibrillator implantation, and stroke) were assessed using the combination of clinical risk factors, echocardiographic parameters, and CCTA variables.ResultsThe prevalence of obstructive CAD (≥ 50% in luminal stenosis) and APC was 14.7% and 18.9%, respectively. During the follow-up period (median, 37 months; range, 2–108 months), there were 31 occurrences of ACEs (13.0%). Using multivariate Cox regression analysis, age, atrial fibrillation, low ejection fraction, obstructive CAD, and APCs were associated with ACEs (all p < 0.05). Among the prediction models for ACEs, the area under the curve (AUC) was higher (AUC = 0.92) when CCTA variables were added to the clinical (AUC = 0.84) and echocardiographic factors (AUC = 0.88) (p < 0.001).ConclusionsUsing CCTA, about 20% of symptomatic HCM patients were associated with clinically significant atherosclerosis. Adding these CCTA variables to the clinical and echocardiographic variables may increase the predictions of ACEs; therefore, evaluating coronary atherosclerosis using CCTA may be helpful for symptomatic HCM patients.Key Points• Chest pain in adult patients with hypertrophic cardiomyopathy (HCM) remains challenging to distinguish from coronary artery disease.• Coronary computed tomography angiography (CCTA) can assess the severity and characteristics of coronary atherosclerosis in symptomatic HCM patients.• Adding CCTA variables to clinical and echocardiographic factors may increase the predictions of adverse cardiac events in HCM patients, and thus evaluating coronary atherosclerosis using CCTA may be helpful for HCM patients with chest pain.

This retrospective study aimed to assess coronary artery calcium (CAC) progression in serial computed tomography measurements according to risk factor changes. In 448 asymptomatic adults who underwent CAC measurements with more than one-year intervals, CAC progression was assessed according to age, sex, variable traditional risk factors (diabetes mellitus, hypertension, hyperlipidemia, and smoking), and initial CAC score (0, 0.1–100, and >100). Univariate and multivariate logistic regression analyses were assessed for independent predictors of rapid CAC progression (ΔCAC/year > 20). During the 3.5-year follow-up, coronary artery calcifications occurred in 43 (12.8%) of 336 individuals with an initial CAC score of zero. Of 112 individuals with initial CAC presence, 60 (53.6%) had ΔCAC/year > 20. Age, male sex, body mass index, and all risk factors were significantly associated with ΔCAC/year > 20, but recently diagnosed hypertension (odds ratio [OR], 11.3) and initial CAC score (OR, 1.05) were significant independent predictors in multivariate regression analyses. CAC progression was affected by demographic and traditional risk factors; but, adjusting for these factors, recently diagnosed hypertension and initial CAC score were the most influential factors for rapid CAC progression. These findings suggest that individuals with higher initial CAC scores may benefit from more frequent follow-up scans and checks regarding risk factor changes.

ObjectivesTo evaluate the clinical significance of discrepant lesions between coronary computed tomography angiography (CCTA) and invasive coronary angiography (ICA) in a longitudinal study.MethodsIn 220 patients with suspected coronary artery disease (CAD) who underwent both 256-row CCTA and ICA, the obstructive CAD (≥ 50% stenosis) on CCTA was compared with that on ICA as the reference standard. We analysed the causes of the discrepancy between CCTA and ICA. During a 40-month follow-up period, major adverse cardiac events (MACE) were assessed.ResultsDiscordance between CCTA and ICA was observed in 121 of the 3166 coronary artery segments (3.8%). Common causes were calcification (45.9%) and positive remodelling (PR) (29.6%) in 83 false positive lesions, and noise (40.0%) and motion artefact (37.8%) in 38 false negative lesions. MACE occurred in seven lesions among the discrepant lesions; six among the 29 PR lesions (20.7%) and one among the 53 calcified lesions (1.9%). With respect to the prediction power of MACE in an intermediate stenosis, the CCTA-related value including PR was higher than the ICA-related value.ConclusionsPR was a frequent cause of MACE among the false positive lesions on CCTA. Therefore, the presence of PR on CCTA may suggest clinical significance, although it can be missed by ICA.Key Points• Compared to ICA, PR in CCTA may be cause of false positive lesion.• CCTA-related value including PR shows higher prediction power of MACE than ICA-related value.• PR reflects atherosclerotic burden that can be related to cardiac events.• PR in CCTA should be observed carefully, even if it is false positive.

Body-composition analysis (BCA) is gaining increasing clinical importance, because abnormalities in muscle and fat distribution are closely associated with patient outcomes for various diseases. Although several methods for assessing body composition are available, including bioelectrical impedance analysis, dual-energy X-ray absorptiometry, and magnetic resonance imaging, computed tomography (CT) has emerged as the most widely used imaging modality owing to its accuracy, accessibility, and artificial intelligence-driven automated analytical capabilities. CT-based BCA enables the precise quantification of skeletal muscle and adipose tissues, but its measurements can be influenced by various technical factors, such as the contrast phase, tube current and voltage, slice thickness, reconstruction algorithm, and scanner type. These parameters particularly affect attenuation-based metrics such as muscle density. Recent technological advancements, such as iterative reconstruction, dual-energy CT, and photon-counting CT, have resulted in new capabilities but may further introduce variability. This review summarizes the effects of CT parameters on BCA results and underscores the need for awareness and consistency when performing CT-based BCA. A better understanding of these factors may improve measurement reproducibility and support broader clinical and research applications.