The lateral flow immunoassay (LFIA) is a paper-based platform with extensive application in point-of-care (POC) testing and many fields. However, its clinical application is severely limited due to the lack of quantitative ability of standard LFIA tests; this augmentation provides the system with quantifying the signal from magenta-colored AuNPs. To address this issue, we proposed an ultra-compact optical system that allowed LFIAs to be performed more accurately and objectively. The experimental setup consisted of multiple optical accessories manufactured by 3D printing (STEP files were included). A high-resolution printer was used to print out a magenta card model for the LFIA, whose color code, ranging from 255, 255, 255 to 255, 0, 255 in the RGB (red, green, blue) format, represents different levels of magenta color intensity (from 0% to 100%) and thus the results of LFIA test strips. A mathematical model was built using a calibration curve to describe the relationship between magenta color value and reflectance spectrum. In addition, a spectrum module was integrated into the proposed system to identify and quantify LFIA results. This integration represents a pioneering step in developing portable detection techniques that facilitate quantifying LFIA results. Finally, we expect this ultra-compact optical spectroscopy system to have great potential for novel clinical applications.

The COVID-19 pandemic has spread globally in a short period of time. It is known that antibody (nAb) level can effectively predict vaccine efficacy, which leads to the exploration of vaccine trials for efficacy assessment. Thus, the current study aimed to develop a platform to quantify nAb levels faster, at lower cost, and with better efficiency. A total of 69 sera samples were collected for the research, 28 of which were from unvaccinated participants. The other 27 samples and the remaining 14 samples were from the participants who had received the first and second dose, respectively, of AZ vaccine 1 month before. With cPass assays (Genscript cPass nAb ELISA assay) used as a criterion standard and lateral flow immunoassay kit (Healgen Scientific – LFIA test kit) coupled with a spectrometer (LFIA+S) for checking each specimen, we aimed to detect the presence of neutralizing antibodies in sera and to confirm the relationship between the inhibition rate from cPass assays and the nAb index from the LFIA+S. Data analysis of the research were taken from the certified ELISA and LFIA+S, which indicated a high consistency (Pearson’s r=0.864; ICC=0.90138) between the 2 methods. The dataset demonstrated that LFIA+S was affordable, had a strong correlation with results of the cPass nAbs detection kit, and has potential clinical applications, with an exclusive feature that allows non-experts to use it with ease. It is believed that the proposed platform can be promoted in the near future.

Growing concerns about the health risks of melamine adulteration in food products highlight the urgent need for reliable detection methods. However, the long-term effects of chronic low-level melamine exposure remain inadequately explored. This study introduces THE ONE InstantCare platform, a portable immunoassay analyzer integrating a SpectroChip-based spectral processing unit (SPU) with lateral flow immunoassay (LFIA) for sensitive and accurate quantification of melamine in human urine. This platform provides a cost-effective, rapid, and user-friendly point-of-care (POC) solution for melamine detection. Analytical evaluations across eight melamine concentrations (0–100 parts per billion, ppb) achieved a limit of detection (LOD) of 1.91 ppb. Validation with 24 human urine samples demonstrated strong concordance with liquid chromatography–mass spectrometry (LC-MS), yielding an intraclass correlation coefficient (ICC) of 0.9220, a Pearson correlation coefficient of 0.9389, and 95% agreement in Bland–Altman analysis. High reproducibility was observed, with an intraday coefficient of variation (CV) of 6.53% and acceptable interday CV values, while interference studies confirmed reliability in the presence of common biological substances. By delivering results in approximately 10 min, THE ONE InstantCare platform significantly reduces analysis time compared to LC-MS, which typically requires several hours. This novel platform enhances food safety surveillance and advances human health risk assessments, particularly for evaluating melamine-linked kidney damage. Its versatility and robust performance make it a promising tool for environmental monitoring and clinical diagnostics, enabling the detection of diverse biomarkers with high sensitivity and reproducibility.

This study introduced an innovative system for detecting neutralizing antibodies from serum samples, using optical spectroscopy. This system utilizes a compact optical chip to capture spectral data from LFIA. Researchers analyzed 265 serum samples sourced from MacKay Memorial Hospital in Taiwan. The presence of neutralizing antibodies was confirmed using the LFIA test kit. For validation, the study compared the results with those from the FDA-approved neutralizing antibody ELISA kit, considered the gold standard. Raw light intensity data was converted into reflectance data using a data processing procedure that prominently featured the Savitzky-Golay filter for data refinement. To predict neutralizing antibody levels, the study leveraged three machine learning algorithms: SVM, Random Forest, and MLP. Notably, the MLP model outperformed the others in classifying antibody levels from LFIA spectra, achieving an accuracy of 94.3%. The study advanced quantitative analyses using both conventional image processing and spectral machine learning regressors like SVR, Random Forest, and MLPR. Spectral methods outperformed image processing, achieving R ² values over 0.8. Moreover, a new hybrid model combining MLP classification with regression improved prediction accuracy (R ² of 0.923). This research underscores the efficacy of combining spectroscopy and machine learning to detect neutralizing antibodies, paving the way for a potential alternative to traditional laboratory testing.