Photoacoustic spectroscopy has been shown to be a promising tool for non-invasive blood glucose monitoring. However, the repeatability of such a method is susceptible to changes in skin condition, which is dependent on hand washing and drying due to the high absorption of infrared excitation light to the skin secretion products or water. In this paper, we present a method to meet the challenges of mid-infrared photoacoustic spectroscopy for non-invasive glucose monitoring. By obtaining the microscopic spatial information of skin during the spectroscopy measurement, the skin region where the infrared spectra is insensitive to skin condition can be locally selected, which enables reliable prediction of the blood glucose level from the photoacoustic spectroscopy signals. Our raster-scan imaging showed that the skin condition for in vivo spectroscopic glucose monitoring had significant inhomogeneities and large variability in the probing area where the signal was acquired. However, the selective localization of the probing led to a reduction in the effects of variability due to the skin secretion product. Looking forward, this technology has broader applications not only in continuous glucose monitoring for diabetic patient care, but in forensic science, the diagnosis of malfunctioning sweat pores, and the discrimination of tumors extracted via biopsy.

The quantitative label-free detection of neurotransmitters provides critical clues in understanding neurological functions or disorders. However, the identification of neurotransmitters remains challenging for surface-enhanced Raman spectroscopy (SERS) due to the presence of noise. Here, we report spread spectrum SERS (ss-SERS) detection for the rapid quantification of neurotransmitters at the attomolar level by encoding excited light and decoding SERS signals with peak autocorrelation and near-zero cross-correlation. Compared to conventional SERS measurements, the experimental result of ss-SERS shows an exceptional improvement in the signal-to-noise ratio of more than three orders of magnitude, thus achieving a high temporal resolution of over one hundred times. The ss-SERS measurement further allows the attomolar SERS detection of dopamine, serotonin, acetylcholine, γ-aminobutyric acid, and glutamate without Raman reporters. This approach opens up opportunities not only for investigating the early diagnostics of neurological disorders or highly sensitive biomedical SERS applications but also for developing low-cost spectroscopic biosensing applications.

Cardiac markers in human serum with concentrations less than 0.1 ng/mL were analyzed by use of a guided-mode resonance (GMR) biosensor. Cardiac troponin I (cTnI), creatine kinase MB (CK-MB), and myoglobin (MYO) were monitored in the serum of both patients and healthy controls. Dose-response curves ranging from 0.05 to 10 ng/mL for cTnI, from 0.1 to 10 ng/mL for CK-MB, and from 0.03 to 1.7 μg/mL for MYO were obtained. The limits of detection (LOD) for cTnI, CK-MB, and MYO were less than 0.05, 0.1, and 35 ng/mL, respectively. Analysis time was 30 min, which is short enough to meet clinical requirements. Antibody immobilization and the hydrophilic properties of the guided-mode resonance filter (GMRF) surface were investigated by X-ray photoelectron spectroscopy (XPS) and by monitoring the peak wavelength shift and water contact angle (CA). Both assays used to evaluate the surface density of the immobilized antibodies, a sandwich enzyme-linked immunosorbent assay (ELISA) and a sandwich immunogold assay, showed that the antibodies were successfully immobilized and sufficiently aligned to detect the low concentration of biomarkers. Our results show that the GMR biosensor will be very useful in developing low-cost portable biosensors that can screen for cardiac diseases.

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