This PDF file contains the front matter associated with SPIE Proceedings Volume 12839, including the Title Page, Copyright information, Table of Contents, and Conference Committee information.

Bone has complex hierarchical structure composed of mineral, collagen, lipids, water and non-collagenous proteins. Being able to probe at the ultrastructural level of bone hierarchy is important to understand age- and disease-related changes in the fracture resistance. Raman spectroscopy (RS) probes molecular vibration and is sensitive to advanced glycation end-products, damage to the bone matrix, thus fracture toughness properties. We studied effect of glycation and mechanical damage on characteristics of Amide I Band. N=20 cadaveric femurs were obtained from Vanderbilt Cadaver Program. We extracted medial and lateral quadrants of cortical bone (~50 mm) along the longitudinal axis of mid-shaft using saw. Dog-bone specimens were created for tensile tests while 2-rectangular beams for glycation incubation. a) For tensile tests, specimens were pulled-to-failure at 5mm/min using 1000 N load cell. b) For glycation, beam-1 (control) was incubated in 50 mM Na₃PO₄, 0.02% NaN₃, protease inhibitor cocktail, and beam-2 (Glucose) with same buffer plus 0.5 M glucose for 5-weeks at 45 °C, pH 7.6. RS acquired before and after both tests indicates that Amide I sub-peak ratio 1670/1640 significantly increased post tensile tests compared to baseline. 1670 and 1640 cm^-1 peaks are associated with random coils and alpha helix respectively. Thus, more disorganized structures are formed because of tensile damages. Glycated beams show lower 1670/1640 ratio compared to baseline and control. This in part due to increase in packing density of collagen molecules upon glycation. Overall, our results indicate that RS can assess cortical damage and sugar-mediated changes in the amide I band.

In this study, we evaluated surgical specimens obtained from patients for detecting resection merging in Hirschsprung’s disease. Conventional multivariate analyses successfully characterized Raman spectral data. Furthermore, the Raman spectroscopic approach combined with machine learning methods successfully predicted whether the target specimen was healthy or diseased by the decision algorithm. Toward practical use, we developed a portable Raman spectroscopic system and a fiber-optic Raman probe for laparoscopic surgery. we performed in vivo Raman measurement of abdominal organs using a live porcine during laparoscopy.

We combine an all-fiber dual wavelength, self-synchronized laser and a dedicated multi-channel detection unit to perform state-of-the-art multiplex Stimulated Raman Scattering (SRS) microscopy. The system covers the full CH spectrum in 1 μs reaching shot-noise limited performances with 25 μW per detection channel. This all-inone solution is based on a passively synchronized dual-wavelength laser source with shot-noise limited relative intensity noise from 600 kHz and a modular multi-channel lock-in detection unit. The synergistic design between laser source and detection system simplifies multiplex SRS implementation for real-time full-chemical imaging.

Chiral detection of glucose has been investigated with the surface-enhanced Raman scattering (SERS) of a reporter molecule, phenylalanine (Phe). The chiral-sensitive bimolecular interactions between glucose and Phe strongly perturb the surface adsorption of Phe on gold nanosurfaces via its carboxylate group, and the Raman intensities of the stretching and bending vibrations of carboxylate appear critical to the adsorption changes of Phe. The molecular-level understanding of SERS shows that SERS has great potential for further development of sensitive chiral detection methods for biomolecules.

Chronic pain encompasses a range of painful conditions such as migraines, fibromyalgia, or prolonged periods of pain without a specific etiological cause. In this context, a less complex, easily applicable therapy that reduces side effects and does not require a high investment from the patient becomes highly important. Currently, chronic pain treatment with topically applied endocannabinoids has been a subject of research. However, permeation studies are necessary to ensure efficacy, safety, and delivery of the active ingredient to the skin layers. Confocal Raman Spectroscopy (CRS) has emerged as an analytical method for the analysis of materials, including biological tissues. In this context, the present study brings an in vivo approach using Confocal Raman Spectroscopy to analyze in vivo the permeation of two formulations containing Cannabidiol (CBD). One formulation consists of nanoencapsulated CBD in transferosomes (TRANS), while the other is a nanolipid carrier containing nanoencapsulated CBD in transferosomes (CLN TRANS). The aim of this study is to explore the topical treatment of chronic pain using these formulations and assess their permeation characteristics. Raman data were collected from stratum corneum, epidermis and dermis at T0, T4 and T8h after topical application. It was possible to identify that both products showed to permeate to the dermis, but with different kinetics.

The ability to perform routine monitoring of bone quality is crucial for patients with bone diseases such as osteoporosis. Current assessments of bone quality are expensive and cannot be used regularly without exposing patients to ionizing radiation. Alternatively, visible-near infrared (Vis-NIR) spectroscopy is a non-invasive, non-ionizing technique that can be used to assess the compositional properties of bone. Recently, studies have reported agreement between transcutaneous Vis-NIR spectroscopic measures of bone quality and conventional radiographic measures collected from the second metacarpal bone of the hand. Computational simulations using Monte-Carlo (MC) modeling offer a valuable tool to better understand the relative contributions from the underlying bone in comparison with the superficial skin, as well as to investigate the relative benefits of specific fiberoptic illumination/collection geometries for transcutaneous measurement of metacarpal bone. To inform the model, skin from above the 2^nd metacarpal bone and the bone itself were dissected from human cadaver hands. Reflectance and transmittance measurements of the skin and bone tissues were taken using an integrating sphere setup in the range of 400 nm-1800 nm. Optical properties were estimated using the Inverse Adding Doubling (IAD) technique. MC models of skin-bone tissues were created using these estimated optical properties as well as physical measurements of tissue thickness, and simulations of fiber-optic Vis-NIR measurements were performed. Results indicate up to 30% of the absorbance signal arises from contributions from the bone in specific spectral ranges.

Convolutional neural network (CNN) based deep learning is used to analyze spectral data collected by visible resonance Raman (VRR) spectroscopy to distinguish human glioma tumors from healthy brain tissues using binary classification and identify the cancer grades of the glioma tumors using multi-class classification. Classification was performed using both raw spectral data and baseline-subtracted data for comparison. The classification using both datasets yielded high accuracy, with the results obtained from baseline subtracted spectra slightly better than that obtained from raw spectra. The study showed VRR combined with deep learning provides a robust molecular diagnostic tool for accurately distinguishing glioma tumors from normal tissues and glioma tumor tissues at different cancer grades. Deep learning aided VRR technique may be used for in-situ intraoperative diagnosis of brain cancer. It may help a surgeon to identify cancer margins and even cancer grades during surgery.

With the various forms of hair treatments, the challenge is to find oils that can better penetrate the hair fiber. The study aims to analyze the permeation of copaiba, andiroba, and coconut oil into human hair. Methods: Five untreated hair fibers were considered as a control, and five treated fibers for each oil were tested. The treatment consisted of depositing 10 μl of the test oil on the five fibers. Raman spectra were collected before and after 30 minutes of treatment with the oils, from the surface to a depth of 40 μm. After identifying the peaks, the concentration of the permeated oil was determined. Results: The calculation of the area under the curve revealed the average permeation profiles in the hair fiber. The quantification of the concentration of permeated oil showed proximity between copaiba oil (30.14 a.u.) and coconut oil (27.85 a.u.). However, andiroba oil, despite penetrating the deeper layer, had a lower concentration compared to other oils. Conclusion: This study demonstrated the efficiency of copaiba, coconut, and andiroba oils in terms of permeation in hair fibers, providing valuable information for the development of products capable of reaching specific layers of hair fibers.