NIR spectroscopic determination of urine components in spot urine: preliminary investigation towards optical point-of-care test

Continuous spectroscopic monitoring of urinary catheter output: advancements and clinical implications

Urine diagnostics are crucial for identifying urological disorders and systemic diseases. Monitoring bladder catheters for urine output and early signs of urinary tract infections (UTIs) is essential but labor-intensive and prone to documentation errors. Recent advances in electronic monitoring and spectroscopy offer potential improvement in this process. This study introduces a novel smart sensor system for urinary catheters, enabling digital, continuous, automated real-time spectroscopic urine monitoring. A prototype consisting of a mini-spectrometer integrated with a custom lens array and hyperspectral illumination source was developed for urine analysis. It measures light intensity across 288 channels (340-850 nm) from multiple angles and exposure times, capturing detailed spectral data. Analyzing 401 urine samples from 168 patients, statistical models in R software were used to assess the dependency between spectral data and clinical laboratory values. The prototype accurately detected response variables like bilirubin, erythrocytes, pH, protein, specific gravity, and urobilinogen, with AUC values indicating good to very good discrimination. Response variables like glucose and nitrite, which do not absorb within the measured spectrum, showed minimal correlation. Our smart catheter system presents the potential for a significant advancement in urine monitoring, providing continuous, accurate analysis of parameters absorbing within the visible light spectrum.

Near-infrared spectroscopy analysis to predict urinary allantoin in dairy cows

Accurate quantification of rumen microbial proteins is essential in dairy cow nutrition to estimate the ruminal escape of dietary protein and microbial yield. Current quantification methods rely on indirect measurements using purine derivatives (PD). However, these methods require specialized laboratory equipment and trained personnel, resources which are often not available in farm settings. Near-infrared spectroscopy (NIR) has emerged as a powerful tool for predicting the attributes of biological samples, including meat, corn, soybeans, and liquids. Given that allantoin is the primary component in PD, this study aims to (1) develop a predictive model for allantoin levels in urine using NIR and (2) identify key spectral regions for future applications. A total of 182 urine samples were collected from 182 Holstein cows for colorimetric analysis of allantoin and spectral analysis. The raw spectra were preprocessed using scatter correlation methods and spectral derivatives. The partial least squares regression model achieved an R2 of 0.55, a concordance correlation coefficient of 0.73, and a root mean squared error of prediction (RMSEP) of 3.63 mmol/L to predict allantoin concentration from the spectra data set without preprocessing. However, the use of the first derivative (FirstDev) as a preprocessing step reduced the RMSEP from 3.63 mmol/L to 3.25 mmol/L and increased the R2 from 0.55 to 0.62. The FirstDev improves spectral resolution by eliminating the constant baseline, potentially explaining the improved model accuracy. Our method has the potential to evaluate the passage rate of microbial protein represented by the changes in urinary allantoin extraction and the potential to be used for AA dietary balance, thereby improving environmental sustainability and profitability in dairy farms.

Four-bands high-resolution integrated spectrometer

We present the concept and design of a novel integrated optical spectrometer able to operate over four different optical bands in the infrared that cover over 900 nm of aggregated bandwidth. The device, named integrated optical four bands spectrometer (IOFBS), consists of a single planar concave grating with 4 inputs waveguides, each corresponding to a different wavelength band, and 39 output channels that can be implemented on a silicon nitride platform. The inputs waveguides (IWGs) are optimized so that the echelle grating works in different diffraction orders to create constructive interference at the fixed output waveguides. The grating facets are engineered to maximize the diffraction efficiency of the beam launched from any of the four IWGs. The IOFBS works in the near infrared, the O-band, part of the S&E bands and the L-band. The simulated spectra feature an average insertion loss of -1.69 dB across the four bands and a crosstalk better than -32 dB with a 3-dB resolution as low as 0.37 nm and a channel spacing of ∼2.1 nm. The entire device covers an area of 5 mm x 4 mm. The versatility of the proposed design can reduce the cost of integrated spectrometers and make on-chip spectral analysis more accessible by taking advantage of batch fabrication to build a compact device with numerous potential applications.