Similar to the findings of previous East Asian studies, this study showed that Klebsiella pneumoniae was the most common causative organism of endogenous endophthalmitis and liver abscess was the most common infection focus. Although endogenous endophthalmitis is generally associated with poor visual acuity outcomes, the prognosis depends mainly on the initial visual acuity and the pathogen.

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Surface-enhanced Raman scattering (SERS) is an ultrasensitive molecular screening technique with greatly enhanced Raman scattering signals from trace amounts of analytes near plasmonic nanostructures. However, research on the development of a sensor that balances signal enhancement, reproducibility, and uniformity has not yet been proposed for practical applications. In this study, we demonstrate the potential of the practical application for detecting or predicting asymptomatic breast cancer from human tears using a portable Raman spectrometer with an identification algorithm based on multivariate statistics. This potentiality was realized through the fabrication of a plasmonic SERS substrate equipped with a well-aligned, gold-decorated, hexagonal-close-packed polystyrene (Au/HCP-PS) nanosphere monolayer that provided femtomole-scale detection, giga-scale enhancement, and <5% relative standard deviation for reliability and reproducibility, regardless of the measuring site. Our results can provide a first step toward developing a noninvasive, real-time screening technology for detecting asymptomatic tumors and preventing tumor recurrence.

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Gold-decorated, vertically grown ZnO nanorods (NRs) on a flexible graphite sheet (Au/ZnONRs/G) were developed for surface-enhanced Raman scattering (SERS)-based biosensing to identify trace amounts of human aqueous humors. This Au/ZnONRs/G SERS-functionalized sensor was fabricated via two steps: hydrothermal synthesis-induced growth of ZnO NRs on graphite sheets for nanostructure fabrication, followed by e-beam evaporator-induced gold metallization on ZnONRs/G for SERS functionalization. The thickness of the Au layer and the height of the ZnO NRs for enhancing SERS performance were adjusted to maximize Raman intensity, and the optimized Au/ZnONRs/G nanostructures were verified by the electric finite element computational models to maximize the electric fields. The proposed Au/ZnONRs/G SERS sensor showed an enhancement factor of 2.3 × 10 via rhodamine 6G Raman probe and excellent reproducibility (relative standard deviation of <10%) via Raman mapping of a SERS active area with a square of 100 × 100 μm. To evaluate the actual bioapplicability of point-of-care-testing (POCT) analysis in clinics, SERS data acquisition was performed with an integration time of 1 s from a 1 μL analytic droplet of the sample. The performance of this Au/ZnONRs/G sensor was evaluated using human aqueous humors with cataract and two oxidative stress-induced eye diseases, age-related macular degeneration, and diabetic macular edema. These three eye diseases could be identified without any labeling or modification using the Au/ZnONRs/G SERS sensor and the computational algorithm incorporating a support vector machine and multivariate statistical prediction. Therefore, these findings indicate that our label-free, highly reproducible and flexible Au/ZnONRs/G SERS-functionalized sensor supported by a multivariate statistics-derived bioclassification method has great potential in POCT applications for identifying eye diseases.