Butyrophilin 3A1 binds phosphorylated antigens and stimulates human γδ T cells.

Human T cells that express a T cell antigen receptor (TCR) containing γ-chain variable region 9 and δ-chain variable region 2 (Vγ9Vδ2) recognize phosphorylated prenyl metabolites as antigens in the presence of antigen-presenting cells but independently of major histocompatibility complex (MHC), the MHC class I-related molecule MR1 and antigen-presenting CD1 molecules. Here we used genetic approaches to identify the molecule that binds and presents phosphorylated antigens. We found that the butyrophilin BTN3A1 bound phosphorylated antigens with low affinity, at a stoichiometry of 1:1, and stimulated mouse T cells with transgenic expression of a human Vγ9Vδ2 TCR. The structures of the BTN3A1 distal domain in complex with host- or microbe-derived phosphorylated antigens had an immunoglobulin-like fold in which the antigens bound in a shallow pocket. Soluble Vγ9Vδ2 TCR interacted specifically with BTN3A1-antigen complexes. Accordingly, BTN3A1 represents an antigen-presenting molecule required for the activation of Vγ9Vδ2 T cells.

Innovative suspended ring core fiber for SERS application.

Solid core photonic crystal fibers (SC-PCFs) have garnered attention as probes for surface-enhanced Raman spectroscopy (SERS) due to their potential as optofluidic devices, offering heightened sensitivity and reliability compared to traditional planar/colloidal nanoparticle-based SERS platforms. A smaller core allows for more light interaction but might compromise sensitivity and reliability due to reduced surface area for interaction. Here, we introduce an innovative SC-PCF design aimed at resolving the trade-off between increasing the evanescent field fraction and the core surface area. By substituting a suspended silica rod with a suspended thin-silica ring, we augment the surface area for attached nanoparticles by one order of magnitude while retaining a substantial amount of evanescent light interaction with the analyte. Experimental findings showcase an improved sensitivity in SERS signal compared to previously reported top-performing PCF sensor designs. Importantly, with necessary refinement and optimization, this innovative fiber design extends beyond SERS applications, potentially amplifying the sensitivity of various other fiber-based sensing platforms.

Reliable and easy-to-use SERS spectroscopy probe using a tapered opto-fluidic photonic crystal fiber.

Surface enhanced Raman spectroscopy (SERS) is one of the most sensitive biosensing techniques that offers label free detection for a variety of applications. Generally, SERS spectroscopy is performed on nano-functionalized planar substrates with plasmonic structures or colloidal nanoparticles. Recently, photonic crystal fibers (PCFs) have gained great interest for SERS based bio sensing applications due to the immense advantages such as improved sensitivity, flexibility and remote sensing capability that it offers compared to the planar substrates. However, the use of PCF based biosensors demand the alignment of it under a microscope, which can affect the reliability of SERS measurements and could be restrictive for practical end use applications. Herein, we aim to develop a tapered suspended core PCF fiber (Tapered-SuC-PCF) that represents an improvement in coupling efficiency and measurement reliability as well as it opens the way to the development of an easy-to-use bio-sensing probes with a plug and play option with conventional Raman spectrometers. We have fabricated several samples of the optimized tapered-SuC-PCF and demonstrated its superior SERS performance compared to standard SuC-PCF fibers with 2 µm core diameter. An excellent SERS measurement reliability is demonstrated using such a fiber in a plug and play type system demonstrating its versatility for practical end use applications.

Simultaneous Dual-Wavelength Source Raman Spectroscopy with a Handheld Confocal Probe for Analysis of the Chemical Composition of In Vivo Human Skin.

Confocal Raman spectroscopy (CRS) is a powerful tool that has been widely used for biological tissue analysis because of its noninvasive nature, high specificity, and rich biochemical information. However, current commercial CRS systems suffer from limited detection regions (450-1750 cm-1), bulky sizes, nonflexibilities, slow acquisitions by consecutive excitations, and high costs if using a Fourier transform (FT) Raman spectroscopy with an InGaAs detector, which impede their adoption in clinics. In this study, we developed a portable CRS system with a simultaneous dual-wavelength source and a miniaturized handheld probe (120 mm × 60 mm × 50 mm) that can acquire spectra in both fingerprint (FP, 450-1750 cm-1) and high wavenumber (HW, 2800-3800 cm-1) regions simultaneously. An innovative design combining 671 and 785 nm lasers for simultaneous excitation through a compact and high-efficiency (>90%) wavelength combiner was implemented. Moreover, to decouple the fused FP and HW spectra, a first-of-its-kind precise Raman spectra separation algorithm (PRSSA) was developed based on the maximum a posteriori probability (MAP) estimate. The accuracy of spectra separation was greater than 99%, demonstrated in both phantom experiments and in vivo human skin measurements. The total data acquisition time was reduced by greater than 50% compared to other CRS systems. The results proved our proposed CRS system and PRSSA's superior capability in fast and ultrawideband spectra acquisition will significantly improve the integration of CRS in the clinical workflow.

A triple-network organization for the mouse brain.

The triple-network model of psychopathology is a framework to explain the functional and structural neuroimaging phenotypes of psychiatric and neurological disorders. It describes the interactions within and between three distributed networks: the salience, default-mode, and central executive networks. These have been associated with brain disorder traits in patients. Homologous networks have been proposed in animal models, but their integration into a triple-network organization has not yet been determined. Using resting-state datasets, we demonstrate conserved spatio-temporal properties between triple-network elements in human, macaque, and mouse. The model predictions were also shown to apply in a mouse model for depression. To validate spatial homologies, we developed a data-driven approach to convert mouse brain maps into human standard coordinates. Finally, using high-resolution viral tracers in the mouse, we refined an anatomical model for these networks and validated this using optogenetics in mice and tractography in humans. Unexpectedly, we find serotonin involvement within the salience rather than the default-mode network. Our results support the existence of a triple-network system in the mouse that shares properties with that of humans along several dimensions, including a disease condition. Finally, we demonstrate a method to humanize mouse brain networks that opens doors to fully data-driven trans-species comparisons.

An Investigation of Signal Preprocessing for Photoacoustic Tomography.

Photoacoustic tomography (PAT) is increasingly being used for high-resolution biological imaging at depth. Signal-to-noise ratios and resolution are the main factors that determine image quality. Various reconstruction algorithms have been proposed and applied to reduce noise and enhance resolution, but the efficacy of signal preprocessing methods which also affect image quality, are seldom discussed. We, therefore, compared common preprocessing techniques, namely bandpass filters, wavelet denoising, empirical mode decomposition, and singular value decomposition. Each was compared with and without accounting for sensor directivity. The denoising performance was evaluated with the contrast-to-noise ratio (CNR), and the resolution was calculated as the full width at half maximum (FWHM) in both the lateral and axial directions. In the phantom experiment, counting in directivity was found to significantly reduce noise, outperforming other methods. Irrespective of directivity, the best performing methods for denoising were bandpass, unfiltered, SVD, wavelet, and EMD, in that order. Only bandpass filtering consistently yielded improvements. Significant improvements in the lateral resolution were observed using directivity in two out of three acquisitions. This study investigated the advantages and disadvantages of different preprocessing methods and may help to determine better practices in PAT reconstruction.

Machine Learning Assisted Handheld Confocal Raman Micro-Spectroscopy for Identification of Clinically Relevant Atopic Eczema Biomarkers.

Atopic dermatitis (AD) is a common chronic inflammatory skin dermatosis condition due to skin barrier dysfunction that causes itchy, red, swollen, and cracked skin. Currently, AD severity clinical scores are subjected to intra- and inter-observer differences. There is a need for an objective scoring method that is sensitive to skin barrier differences. The aim of this study was to evaluate the relevant skin chemical biomarkers in AD patients. We used confocal Raman micro-spectroscopy and advanced machine learning methods as means to classify eczema patients and healthy controls with sufficient sensitivity and specificity. Raman spectra at different skin depths were acquired from subjects' lower volar forearm location using an in-house developed handheld confocal Raman micro-spectroscopy system. The Raman spectra corresponding to the skin surface from all the subjects were further analyzed through partial least squares discriminant analysis, a binary classification model allowing the classification between eczema and healthy subjects with a sensitivity and specificity of 0.94 and 0.85, respectively, using stratified K-fold (K = 10) cross-validation. The variable importance in the projection score from the partial least squares discriminant analysis classification model further elucidated the role of important stratum corneum proteins and lipids in distinguishing two subject groups.

Optimization and performance analysis of SERS-active suspended core photonic crystal fibers.

Recently, surface enhanced Raman spectroscopy (SERS)-active photonic crystal fiber (PCFs) probes have gained great interest for biosensing applications due to the tremendous advantages it has over the conventional planar substrate based SERS measurements, with improvements on the detection sensitivity and reliability in measurements. So far, two main approaches were employed to get the analyte molecule in the vicinity of nanoparticles (NPs) inside PCFs in order to achieve the SERS effect. In the first case, analyte and NPs are pre-mixed and injected inside the holes of the PCF prior to the measurement. In the second approach, controlled anchoring of the NPs inside the inner walls of the PCF was achieved prior to the incorporation of the analyte. Although many studies have been conducted using one configuration or the other, no clear trend is emerging on which one would be the best suited for optimizing the biosensing properties offered by SERS active-PCF. In this paper, we investigate the performances of both configurations along with their interplays with the core size of the PCF probe. We have fabricated several samples of a standard PCF design with different core sizes, and SERS measurements of a standard Raman-active molecule are realized in the same conditions for enabling direct comparisons of the SERS intensity and measurement reliabilities between each configuration, yielding clear directions on the optimization of the SERS-active PCF probe. We envision that this study will pave the way for next-generation clinical biosensors for body fluid analysis, as it exhibits high sensitivity and excellent reliability.

Multimodal imaging approach to monitor browning of adipose tissue in vivo.

The discovery that white adipocytes can undergo a browning process to become metabolically active beige cells has attracted significant interest in the fight against obesity. However, the study of adipose browning has been impeded by a lack of imaging tools that allow longitudinal and noninvasive monitoring of this process in vivo. Here, we report a preclinical imaging approach to detect development of beige adipocytes during adrenergic stimulation. In this approach, we expressed near-infrared fluorescent protein, iRFP720, driven under an uncoupling protein-1 (Ucp1) promoter in mice by viral transduction, and used multispectral optoacoustic imaging technology with ultrasound tomography (MSOT-US) to assess adipose beiging during adrenergic stimulation. We observed increased photoacoustic signal at 720 nm, coupled with attenuated lipid signals in stimulated animals. As a proof of concept, we validated our approach against hybrid positron emission tomography combined with magnetic resonance (PET/MR) imaging modality, and quantified the extent of adipose browning by MRI-guided segmentation of 2-deoxy-2-18F-fluoro-d-glucose uptake signals. The browning extent detected by MSOT-US and PET/MR are well correlated with Ucp1 induction. Taken together, these systems offer great opportunities for preclinical screening aimed at identifying compounds that promote adipose browning and translation of these discoveries into clinical studies of humans.

A Phase-Intensity Surface Plasmon Resonance Biosensor for Avian Influenza A (H5N1) Detection.

In this paper, we present a phase-intensity surface plasmon resonance (SPR) biosensor and demonstrate its use for avian influenza A (H5N1) antibody biomarker detection. The sensor probes the intensity variation produced by the steep phase response at surface plasmon excitation. The prism sensor head is fixed between a pair of polarizers with a perpendicular orientation angle and a forbidden transmission path. At SPR, a steep phase change is introduced between the p- and s-polarized light, and this rotates the polarization ellipse of the transmission beam. This allows the light at resonance to be transmitted and a corresponding intensity change to be detected. Neither time-consuming interference fringe analysis nor a phase extraction process is required. In refractive index sensing experiments, the sensor resolution was determined to be 6.3 × 10-6 refractive index values (RIU). The sensor has been further applied for H5N1 antibody biomarker detection, and the sensor resolution was determined to be 193.3 ng mL-1, compared to 1 µg mL-1 and 0.5 µg mL-1, as reported in literature for influenza antibody detection using commercial Biacore systems. It represents a 517.3% and 258.7% improvement in detection limit, respectively. With the unique features of label-free, real-time, and sensitive detection, the phase-intensity SPR biosensor has promising potential applications in influenza detection.

Vibrational spectroscopy of metal carbonyls for bio-imaging and -sensing.

Transition metal carbonyls exhibit strong CO absorptions in the 2200-1800 cm(-1) region, which is free of interference from other functional groups. This feature has led to their applications in bio-imaging and -sensing, in particular through mid-IR, Raman and more recently, surface-enhanced Raman spectroscopy (SERS). Their use in mid-IR quantitative sensing based on vibrational intensities, and chemical sensing based on frequency shifts and vibrational lifetimes, is reviewed. Their development for Raman sensing following the breakthrough in SERS highlights the potential of coupling metal carbonyls to plasmonic nanostructures as novel optical materials for SERS-based bio-imaging and -sensing.

Non-invasive and label-free detection of oral squamous cell carcinoma using saliva surface-enhanced Raman spectroscopy and multivariate analysis.

Reported here is the application of silver nanoparticle-based surface-enhanced Raman spectroscopy (SERS) as a label-free, non-invasive technique for detection of oral squamous cell cancer (OSCC) using saliva and desquamated oral cells. A total of 180 SERS spectra were acquired from saliva and 120 SERS spectra from oral cells collected from normal healthy individuals and from confirmed oropharyngeal cancer patients. Notable biochemical peaks in the SERS spectra were tentatively assigned to various components. Data were subjected to multivariate statistical techniques including principal component analysis, linear discriminate analysis (PCA-LDA) and logistic regression (LR) revealing a sensitivity of 89% and 68% and a diagnostic accuracy of 73% and 60% for saliva and oral cells, respectively. The results from this study demonstrate the potential of saliva and oral cell SERS combined with PCA-LDA or PCA-LR diagnostic algorithms as a promising clinical adjunct for the non-invasive detection of oral cancer.

A rapid and label-free SERS detection method for biomarkers in clinical biofluids.

A metal carbonyl-functionalized nanostructured substrate can be used in a rapid and simple assay for the detection of A1AT, a potential biomarker for bladder cancer, in clinical urine samples. The assay involves monitoring changes in the carbonyl stretching vibrations of the metal carbonyl via surface-enhanced Raman spectroscopy (SERS). These vibrations lie in the absorption spectral window of 1800-2200 cm(-1), which is free of any spectral interference from biomolecules.

Recent progress in voltage-sensitive dye imaging for neuroscience.

Voltage-sensitive dye imaging (VSDi) enables visualization of information processing in different areas of the brain with reasonable spatial and temporal resolution. VSDi employs different chemical compounds to transduce neural activity directly into the changes in intrinsic optical signal. Physically, voltage-sensitive dyes (VSDs) are chemical probes that reside in the neural membrane and change their fluorescence or absorbance in response to membrane potential changes. Based on these features, VSDs can be divided into two groups-absorbance and fluorescence. The spatial and temporal resolution of the VSDi is limited mainly by the technical characteristics of the optical imaging setup (e.g., computer and light-sensitive device-charge-coupled device (CCD) camera or photodiode array). In this article, we briefly review the development of the VSD, technique of VSDi and applications in functional brain imaging.

A Magnetic Particle Imaging Approach for Minimally Invasive Imaging and Sensing With Implantable Bioelectronic Circuits.

Minimally-invasive and biocompatible implantable bioelectronic circuits are used for long-term monitoring of physiological processes in the body. However, there is a lack of methods that can cheaply and conveniently image the device within the body while simultaneously extracting sensor information. Magnetic Particle Imaging (MPI) with zero background signal, high contrast, and high sensitivity with quantitative images is ideal for this challenge because the magnetic signal is not absorbed with increasing tissue depth and incurs no radiation dose. We show how to easily modify common implantable devices to be imaged by MPI by encapsulating and magnetically-coupling magnetic nanoparticles (SPIOs) to the device circuit. These modified implantable devices not only provide spatial information via MPI, but also couple to our handheld MPI reader to transmit sensor information by modulating harmonic signals from magnetic nanoparticles via switching or frequency-shifting with resistive or capacitive sensors. This paper provides proof-of-concept of an optimized MPI imaging technique for implantable devices to extract spatial information as well as other information transmitted by the implanted circuit (such as biosensing) via encoding in the magnetic particle spectrum. The 4D images present 3D position and a changing color tone in response to a variable biometric. Biophysical sensing via bioelectronic circuits that take advantage of the unique imaging properties of MPI may enable a wide range of minimally invasive applications in biomedicine and diagnosis.

Hybrid Photoacoustic Ultrasound Imaging System for Cold-Induced Vasoconstriction and Vasodilation Monitoring.

Lewis hunting reaction refers to the alternating cold-induced vasoconstriction and dilation in extremities, whose underlying mechanism is complex. While numerous studies reported this intriguing phenomenon by measuring cutaneous temperature fluctuation under cold exposure, few of them tracked peripheral vascular responses in real-time, lacking a non-invasive and quantitative imaging tool. To better monitor hunting reaction and diagnose relevant diseases, we developed a hybrid photoacoustic ultrasound (PAUS) tomography system to monitor finger vessels' dynamic response to cold, together with simultaneous temperature measurement. We also came out a standard workflow for image analysis with self-defined indices. In the small cohort observational study, vascular changes in the first cycle of hunting reaction were successfully captured by the image series and quantified. Time difference between vasodilation and temperature recovery was noticed and reported for the first time, thanks to the unique capability of the PAUS imaging system in real-time and continuous vascular monitoring. The developed imaging system and indices enabled more objective and quantitative monitoring of peripheral vascular activities, indicating its great potential in numerous clinical applications.

Complete characterization of RNA biomarker fingerprints using a multi-modal ATR-FTIR and SERS approach for label-free early breast cancer diagnosis.

Breast cancer is a prevalent form of cancer worldwide, and the current standard screening method, mammography, often requires invasive biopsy procedures for further assessment. Recent research has explored microRNAs (miRNAs) in circulating blood as potential biomarkers for early breast cancer diagnosis. In this study, we employed a multi-modal spectroscopy approach, combining attenuated total reflection Fourier transform infrared (ATR-FTIR) and surface-enhanced Raman scattering (SERS) to comprehensively characterize the full-spectrum fingerprints of RNA biomarkers in the blood serum of breast cancer patients. The sensitivity of conventional FTIR and Raman spectroscopy was enhanced by ATR-FTIR and SERS through the utilization of a diamond ATR crystal and silver-coated silicon nanopillars, respectively. Moreover, a wider measurement wavelength range was achieved with the multi-modal approach than with a single spectroscopic method alone. We have shown the results on 91 clinical samples, which comprised 44 malignant and 47 benign cases. Principal component analysis (PCA) was performed on the ATR-FTIR, SERS, and multi-modal data. From the peak analysis, we gained insights into biomolecular absorption and scattering-related features, which aid in the differentiation of malignant and benign samples. Applying 32 machine learning algorithms to the PCA results, we identified key molecular fingerprints and demonstrated that the multi-modal approach outperforms individual techniques, achieving higher average validation accuracy (95.1%), blind test accuracy (91.6%), specificity (94.7%), sensitivity (95.5%), and F-score (94.8%). The support vector machine (SVM) model showed the best area under the curve (AUC) characterization value of 0.9979, indicating excellent performance. These findings highlight the potential of the multi-modal spectroscopy approach as an accurate, reliable, and rapid method for distinguishing between malignant and benign breast tumors in women. Such a label-free approach holds promise for improving early breast cancer diagnosis and patient outcomes.

Structural and functional imaging of psoriasis for severity assessment and quantitative monitoring of treatment response using high-resolution optoacoustic imaging.

Psoriasis is a chronic inflammatory skin disease, characterized by thick scaly plaques. It imposes a notable disease burden with varying levels of severity affecting the quality of life significantly. Current disease severity assessment relies on semi-objective visual inspection based on the Psoriasis Area and Severity index (PASI) score that might not be sensitive to sub-clinical changes. Histology of psoriasis skin lesions necessitate invasive skin biopsies. This indicates an unmet need for a non-invasive, objective and quantitative approach to assess disease severity serially. Herein, we employ multispectral Raster-Scanning Optoacoustic Mesoscopy (ms-RSOM) derived structural and microvascular functional imaging metrics to examine the lesional and non-lesional skin in psoriasis subjects across different severities and also evaluate the treatment outcome in a subject with topical steroids and biologics, such as adalimumab. ms-RSOM derived structural metrics like epidermal thickness and total blood volume (TBV) and microvascular functional information such as oxygen saturation (sO2) are evaluated by spectrally resolving the endogenous chromophores like melanin, oxy-, and deoxy-hemoglobin. Initial findings reveal an elevated sO2 and TBV with severity in lesional and non-lesional psoriasis skin, thus representing increasing inflammation. An increase in epidermal thickness is also noted with the degree of severity, corresponding to the inflammation and increased abnormal cell growth. As a marker to evaluate the treatment response, we observed a decrease in epidermal thickness, sO2, and TBV in a psoriasis patient post-treatment, which is consistent with the decrease in the PASI score from 4.1 to 1.9. We envision that ms-RSOM has a huge potential to be translated into routine clinical setting for the diagnosis of severity and assessment of treatment monitoring in psoriasis subjects.

Diffuse reflectance spectroscopy and imaging for non-invasive objective assessment of genitourinary syndrome of menopause: a pilot study.

The genitourinary symptom of menopause (GSM) affects up to 65% of women, resulting in symptoms such as vulvovaginal dryness, discomfort, and dysuria, which significantly impacts quality of life. The current assessment methods rely on subjective questionnaires that can be influenced by individual differences, as well as invasive measurements that are time-consuming and not easily accessible. In this study, we explore the potential of a non-invasive and objective assessment tool called diffuse reflectance spectroscopy and imaging (DRSI) to evaluate tissue chromophores, including water, lipid, oxyhemoglobin, and deoxyhemoglobin. These measurements provide information about moisture content, lipid levels, oxygen saturation, and blood fraction, which can serve as surrogate markers for genital estrogen levels. Our findings reveal distinct differences in these chromophores among pre, peri, and postmenopausal subjects. By using lipid and blood fraction tissue chromophores in a K-Nearest Neighbour classifier model, we achieved a prediction accuracy of 65% compared to vaginal maturation index (VMI) that is clinically used to assess estrogen-related hormonal changes. When age was included as the third feature, the accuracy increased to 78%. We believe that by refining the study protocol and configuring the fiber probe to examine tissue chromophores both in the superficial vulva skin for epidermal water content and the deeper layers, DRSI has the potential to provide objective diagnosis and aid in monitoring the treatment outcome of GSM.