Refractive index of human articular cartilage varies with tissue structure and composition.

Optical properties of biological tissues, such as refractive index, are fundamental properties, intrinsically linked to a tissue's composition and structure. This study aims to investigate the variation of refractive index (RI) of human articular cartilage along the tissue depth (via collagen fibril orientation and optical density) and integrity (based on Mankin and Osteoarthritis Research Society International (OARSI) scores). The results show the relationship between RI and PG content (p=0.042), collagen orientation (p=0.037), and OARSI score (p=0.072). When taken into account, the outcome of this study suggests that the RI of healthy cartilage differs from that of pathological cartilage (p=0.072). This could potentially provide knowledge on how progressive tissue degeneration, such as osteoarthritis, affects changes in cartilage RI, which can, in turn, be used as a potential optical biomarker of tissue pathology.

Coherent terahertz laser feedback interferometry for hydration sensing in leaves.

The response of terahertz to the presence of water content makes it an ideal analytical tool for hydration monitoring in agricultural applications. This study reports on the feasibility of terahertz sensing for monitoring the hydration level of freshly harvested leaves of Celtis sinensis by employing a imaging platform based on quantum cascade lasers and laser feedback interferometry. The imaging platform produces wide angle high resolution terahertz amplitude and phase images of the leaves at high frame rates allowing monitoring of dynamic water transport and other changes across the whole leaf. The complementary information in the resulting images was fed to a machine learning model aiming to predict relative water content from a single frame. The model was used to predict the change in hydration level over time. Results of the study suggest that the technique could have substantial potential in agricultural applications.

Terahertz imaging of human skin pathologies using laser feedback interferometry with quantum cascade lasers.

Early detection of skin pathologies with current clinical diagnostic tools is challenging, particularly when there are no visible colour changes or morphological cues present on the skin. In this study, we present a terahertz (THz) imaging technology based on a narrow band quantum cascade laser (QCL) at 2.8 THz for human skin pathology detection with diffraction limited spatial resolution. THz imaging was conducted for three different groups of unstained human skin samples (benign naevus, dysplastic naevus, and melanoma) and compared to the corresponding traditional histopathologic stained images. The minimum thickness of dehydrated human skin that can provide THz contrast was determined to be 50 µm, which is approximately one half-wavelength of the THz wave used. The THz images from different types of 50 µm-thick skin samples were well correlated with the histological findings. The per-sample locations of pathology vs healthy skin can be separated from the density distribution of the corresponding pixels in the THz amplitude-phase map. The possible THz contrast mechanisms relating to the origin of image contrast in addition to water content were analyzed from these dehydrated samples. Our findings suggest that THz imaging could provide a feasible imaging modality for skin cancer detection that is beyond the visible.

Nondestructive Evaluation of Mechanical and Histological Properties of the Human Aorta With Near-Infrared Spectroscopy.

INTRODUCTION: Ascending aortic dilatation is a well-known risk factor for aortic rupture. Indications for aortic replacement in its dilatation concomitant to other open-heart surgery exist; however, cut-off values based solely on aortic diameter may fail to identify patients with weakened aortic tissue. We introduce near-infrared spectroscopy (NIRS) as a diagnostic tool to nondestructively evaluate the structural and compositional properties of the human ascending aorta during open-heart surgeries. During open-heart surgery, NIRS could provide information regarding tissue viability in situ and thus contribute to the decision of optimal surgical repair. MATERIALS AND METHODS: Samples were collected from patients with ascending aortic aneurysm (n = 23) undergoing elective aortic reconstruction surgery and from healthy subjects (n = 4). The samples were subjected to spectroscopic measurements, biomechanical testing, and histological analysis. The relationship between the near-infrared spectra and biomechanical and histological properties was investigated by adapting partial least squares regression. RESULTS: Moderate prediction performance was achieved with biomechanical properties (r = 0.681, normalized root-mean-square error of cross-validation = 17.9%) and histological properties (r = 0.602, normalized root-mean-square error of cross-validation = 22.2%). Especially the performance with parameters describing the aorta's ultimate strength, for example, failure strain (r = 0.658), and elasticity (phase difference, r = 0.875) were promising and could, therefore, provide quantitative information on the rupture sensitivity of the aorta. For the estimation of histological properties, the results with α-smooth muscle actin (r = 0.581), elastin density (r = 0.973), mucoid extracellular matrix accumulation(r = 0.708), and media thickness (r = 0.866) were promising. CONCLUSIONS: NIRS could be a potential technique for in situ evaluation of biomechanical and histological properties of human aorta and therefore useful in patient-specific treatment planning.

Near-Infrared Spectroscopy Enables Arthroscopic Histologic Grading of Human Knee Articular Cartilage.

Purpose: To develop the means to estimate cartilage histologic grades and proteoglycan content in ex vivo arthroscopy using near-infrared spectroscopy (NIRS). Methods: In this experimental study, arthroscopic NIR spectral measurements were performed on both knees of 9 human cadavers, followed by osteochondral block extraction and in vitro measurements: reacquisition of spectra and reference measurements (proteoglycan content, and three histologic scores). A hybrid model, combining principal component analysis and linear mixed-effects model (PCA-LME), was trained for each reference to investigate its relationship with in vitro NIR spectra. The performance of the PCA-LME model was validated with ex vivo spectra before and after the exclusion of outlying spectra. Model performance was evaluated based on Spearman rank correlation (ρ) and root-mean-square error (RMSE). Results: The PCA-LME models performed well (independent test: average ρ = 0.668, RMSE = 0.892, P < .001) in the prediction of the reference measurements based on in vitro data. The performance on ex vivo arthroscopic data was poorer but improved substantially after outlier exclusion (independent test: average ρ = 0.462 to 0.614, RMSE = 1.078 to 0.950, P = .019 to .008). Conclusions: NIRS is capable of nondestructive evaluation of cartilage integrity (i.e., histologic scores and proteoglycan content) under similar conditions as in clinical arthroscopy. Clinical Relevance: There are clear clinical benefits to the accurate assessment of cartilage lesions in arthroscopy. Visual grading is the current standard of care. However, optical techniques, such as NIRS, may provide a more objective assessment of cartilage damage.

Wall Shear Stress Predicts Media Degeneration and Biomechanical Changes in Thoracic Aorta.

Objectives: In thoracic aortic aneurysm (TAA) of the ascending aorta (AA), AA is progressively dilating due to the weakening of the aortic wall. Predicting and preventing aortic dissections and ruptures in TAA continues to be challenging, and more accurate assessment of the AA dilatation, identification of high-risk patients, and timing of repair surgery are required. We investigated whether wall shear stress (WSS) predicts pathological and biomechanical changes in the aortic wall in TAA. Methods: The study included 12 patients with bicuspid (BAV) and 20 patients with the tricuspid aortic valve (TAV). 4D flow magnetic resonance imaging (MRI) was performed a day before aortic replacement surgery. Biomechanical and histological parameters, including assessing of wall strength, media degeneration, elastin, and cell content were analyzed from the resected AA samples. Results: WSSs were greater in the outer curves of the AA compared to the inner curves in all TAA patients. WSSs correlated with media degeneration of the aortic wall (ρ = -0.48, p < 0.01), elastin content (ρ = 0.47, p < 0.01), and aortic wall strength (ρ = -0.49, p = 0.029). Subsequently, the media of the outer curves was thinner, more rigid, and tolerated lower failure strains. Failure values were shown to correlate with smooth muscle cell (SMC) density (ρ = -0.45, p < 0.02), and indicated the more MYH10+ SMCs the lower the strength of the aortic wall structure. More macrophages were detected in patients with severe media degeneration and the areas with lower WSSs. Conclusion: The findings indicate that MRI-derived WSS predicts pathological and biomechanical changes in the aortic wall in patients with TAA and could be used for identification of high-risk patients.

Assessment of Ligament Viscoelastic Properties Using Raman Spectroscopy.

Injuries to the ligaments of the knee commonly impact vulnerable and physically active individuals. These injuries can lead to the development of degenerative diseases such as post-traumatic osteoarthritis (PTOA). Non-invasive optical modalities, such as infrared and Raman spectroscopy, provide means for quantitative evaluation of knee joint tissues and have been proposed as potential quantitative diagnostic tools for arthroscopy. In this study, we evaluate Raman spectroscopy as a viable tool for estimating functional properties of collateral ligaments. Artificial trauma was induced by anterior cruciate ligament transection (ACLT) in the left or right knee joint of skeletally mature New Zealand rabbits. The corresponding contralateral (CL) samples were extracted from healthy unoperated joints along with a separate group of control (CNTRL) animals. The rabbits were sacrificed at 8 weeks after ACLT. The ligaments were then harvested and measured using Raman spectroscopy. A uniaxial tensile stress-relaxation testing protocol was adopted for determining several biomechanical properties of the samples. Partial least squares (PLS) regression models were then employed to correlate the spectral data with the biomechanical properties. Results show that the capacity of Raman spectroscopy for estimating the biomechanical properties of the ligament samples varies depending on the target property, with prediction error ranging from 15.78% for tissue cross-sectional area to 30.39% for stiffness. The hysteresis under cyclic loading at 2 Hz (RMSE = 6.22%, Normalized RMSE = 22.24%) can be accurately estimated from the Raman data which describes the viscous damping properties of the tissue. We conclude that Raman spectroscopy has the potential for non-destructively estimating ligament biomechanical properties in health and disease, thus enhancing the diagnostic value of optical arthroscopic evaluations of ligament integrity.

Near infrared spectroscopic evaluation of biochemical and crimp properties of knee joint ligaments and patellar tendon.

Knee ligaments and tendons play an important role in stabilizing and controlling the motions of the knee. Injuries to the ligaments can lead to abnormal mechanical loading of the other supporting tissues (e.g., cartilage and meniscus) and even osteoarthritis. While the condition of knee ligaments can be examined during arthroscopic repair procedures, the arthroscopic evaluation suffers from subjectivity and poor repeatability. Near infrared spectroscopy (NIRS) is capable of non-destructively quantifying the composition and structure of collagen-rich connective tissues, such as articular cartilage and meniscus. Despite the similarities, NIRS-based evaluation of ligament composition has not been previously attempted. In this study, ligaments and patellar tendon of ten bovine stifle joints were measured with NIRS, followed by chemical and histological reference analysis. The relationship between the reference properties of the tissue and NIR spectra was investigated using partial least squares regression. NIRS was found to be sensitive towards the water (R2CV = .65) and collagen (R2CV = .57) contents, while elastin, proteoglycans, and the internal crimp structure remained undetectable. As collagen largely determines the mechanical response of ligaments, we conclude that NIRS demonstrates potential for quantitative evaluation of knee ligaments.

Biomechanical, biochemical, and near infrared spectral data of bovine knee ligaments and patellar tendon.

Knee joint ligaments and patellar tendon are rope-like tissues that enable the proper function of the knee by connecting the bones that form the joint. A better understanding of ligament structure-function relationships is needed to develop objective and reliable diagnostic methods for ligaments. Recently, arthroscopic near infrared spectroscopy (NIR) has shown the potential to quantitatively evaluate the health of the cartilages and menisci of the knee. In this dataset, we present a unique combination of NIR spectral data, biomechanical properties, and biochemical composition of bovine primary knee ligaments and patellar tendon (10 knees, 50 tissue samples). NIR spectral data were measured at 5 locations in each sample, biomechanical properties were obtained with tensile testing, and biochemical composition was quantified using colorimetric biochemical methods. The data can be reused for investigations of structure-function relationships of knee ligaments and patellar tendon, for the development of NIR spectroscopic methods to quantify the health of these tissues, and to develop new computational models to describe ligament and tendon biomechanics.

Characterization of connective tissues using near-infrared spectroscopy and imaging.

Near-infrared (NIR) spectroscopy is a powerful analytical method for rapid, non-destructive and label-free assessment of biological materials. Compared to mid-infrared spectroscopy, NIR spectroscopy excels in penetration depth, allowing intact biological tissue assessment, albeit at the cost of reduced molecular specificity. Furthermore, it is relatively safe compared to Raman spectroscopy, with no risk of laser-induced photothermal damage. A typical NIR spectroscopy workflow for biological tissue characterization involves sample preparation, spectral acquisition, pre-processing and analysis. The resulting spectrum embeds intrinsic information on the tissue's biomolecular, structural and functional properties. Here we demonstrate the analytical power of NIR spectroscopy for exploratory and diagnostic applications by providing instructions for acquiring NIR spectra, maps and images in biological tissues. By adapting and extending this protocol from the demonstrated application in connective tissues to other biological tissues, we expect that a typical NIR spectroscopic study can be performed by a non-specialist user to characterize biological tissues in basic research or clinical settings. We also describe how to use this protocol for exploratory study on connective tissues, including differentiating among ligament types, non-destructively monitoring changes in matrix formation during engineered cartilage development, mapping articular cartilage proteoglycan content across bovine patella and spectral imaging across the depth-wise zones of articular cartilage and subchondral bone. Depending on acquisition mode and experiment objectives, a typical exploratory study can be completed within 6 h, including sample preparation and data analysis.

Structure, composition and fibril-reinforced poroviscoelastic properties of bovine knee ligaments and patellar tendon.

Tissue-level stress-relaxation of ligaments and tendons in the toe region is characterized by fast and long-term relaxations and an increase in relaxation magnitude with strain. Characterizing the compositional and structural origins of these phenomena helps in the understanding of mechanisms of ligament and tendon function and adaptation in health and disease. A three-step tensile stress-relaxation test was conducted on dumbbell-shaped pieces of bovine knee ligaments and patellar tendon (PT) (n = 10 knees). Their mechanical behaviour was characterized by a fibril-reinforced poroviscoelastic material model, able to describe characteristic times and magnitudes of fast and long-term relaxations. The crimp angle and length of tissues were measured with polarized light microscopy, while biochemical contents were determined by colorimetric biochemical methods. The long-term relaxation time was longer in the anterior cruciate ligament (ACL) and PT compared with collateral ligaments (p < 0.05). High hydroxyproline content predicted greater magnitude and shorter time of both fast and long-term relaxation. High uronic acid content predicted longer time of long-term relaxation, whereas high crimp angle predicted higher magnitude of long-term relaxation. ACL and PT are better long-term stabilizers than collateral ligaments. The long-term relaxation behaviour is affected or implied by proteoglycans and crimp angle, possibly relating to slow structural reorganization of the tissue.

Open-source python module for automated preprocessing of near infrared spectroscopic data.

Near infrared spectroscopy (NIRS) is an analytical technique for determining the chemical composition or structure of a given sample. For several decades, NIRS has been a frequently used analysis tool in agriculture, pharmacology, medicine, and petrochemistry. The popularity of NIRS is constantly growing as new application areas are discovered. Contrary to mid infrared spectral region, the absorption bands in near infrared spectral region are often non-specific, broad, and overlapping. Analysis of NIR spectra requires multivariate methods which are highly subjective to noise arising from instrumentation, scattering effects, and measurement setup. NIRS measurements are also frequently performed outside of a laboratory which further contributes to the presence of noise. Therefore, preprocessing is a critical step in NIRS as it can vastly improve the performance of multivariate models. While extensive research regarding various preprocessing methods exists, selection of the best preprocessing method is often determined through trial-and-error. A more powerful approach for optimizing preprocessing in NIRS models would be to automatically compare a large number of preprocessing techniques (e.g., through grid-search or hyperparameter tuning). To enable this, we present, nippy, an open-source Python module for semi-automatic comparison of NIRS preprocessing methods (available at https://github.com/uef-bbc/nippy). We provide here a brief overview of the capabilities of nippy and demonstrate the typical usage through two examples with public datasets.

Dataset on equine cartilage near infrared spectra, composition, and functional properties.

Near infrared (NIR) spectroscopy is a well-established technique that is widely employed in agriculture, chemometrics, and pharmaceutical engineering. Recently, the technique has shown potential in clinical orthopaedic applications, for example, assisting in the diagnosis of various knee-related diseases (e.g., osteoarthritis) and their pathologies. NIR spectroscopy (NIRS) could be especially useful for determining the integrity and condition of articular cartilage, as the current arthroscopic diagnostics is subjective and unreliable. In this work, we present an extensive dataset of NIRS measurements for evaluating the condition, mechanical properties, structure, and composition of equine articular cartilage. The dataset contains NIRS measurements from 869 different locations across the articular surfaces of five equine fetlock joints. A comprehensive library of reference values for each measurement location is also provided, including results from a mechanical indentation testing, digital densitometry imaging, polarized light microscopy, and Fourier transform infrared spectroscopy. The published data can either be used as a model of human cartilage or to advance equine veterinary research.

Near Infrared Spectroscopic Evaluation of Ligament and Tendon Biomechanical Properties.

Knee ligaments and tendons are collagen-rich viscoelastic connective tissues that provide vital mechanical stabilization and support to the knee joint. Deterioration of ligaments has an adverse effect on the health of the knee and can eventually lead to ligament rupture and osteoarthritis. In this study, the feasibility of near infrared spectroscopy (NIRS) was, for the first time, tested for evaluation of ligament and tendon mechanical properties by performing measurements on bovine stifle joint ligament (N = 40) and patellar tendon (N = 10) samples. The mechanical properties of the samples were determined using a uniaxial tensile testing protocol. Partial least squares regression models were then developed to determine if morphological, viscoelastic, and quasi-static properties of the samples could be predicted from the NIR spectra. Best performance of NIRS in predicting mechanical properties was observed for toughness at yield point (median [Formula: see text], median normalized [Formula: see text]), toughness at failure point (median [Formula: see text], median normalized [Formula: see text]), and the ultimate strength of the ligament/tendon (median [Formula: see text], median normalized [Formula: see text]). Thus, we show that NIRS is capable of estimating ligament and tendon biomechanical properties, especially in parameters related to tissue failure. We believe this method could substantially enhance the currently limited arthroscopic evaluation of ligaments and tendons.

Cardiac measures of nuclear power plant operator stress during simulated incident and accident scenarios.

Maintaining optimal performance in demanding situations is challenged by stress-induced alterations in performance. Here, we quantified the stress of nuclear power plant (NPP) operators (N = 20) during a full-scale simulator training for incident and accident scenarios. We compared the ambulatory electrocardiography measurements of heart rate (HR) and heart rate variability (HRV), and self-reported stress during baselines and simulated scenarios. Perceived (scale 0-10) and physiologically measured stress were low during baseline after the scenarios and normal NPP operation (means 1.8-2.2, mean HR 75-80 bpm). During a cognitively challenging scenario simulating a sensor malfunction, the operators' stress was mild to moderate (mean 3.4; HR + 12% from baseline). During simulations of severe accidents of fire and radioactive steam leakage, the experienced stress and cardiac activity were on a moderate to high level (means 4.2 and 4.6; HR + 23% and + 14% from baseline, respectively). Cardiac activity paralleled the self-reported stress: correlation of self-reported stress to HR was 0.61 (p < .001) and to HRV features RMSSD, HF, LF/HF, SD1, and SD1/SD2 were -0.26, -0.28, 0.35, -0.40, and -0.39 (p < .01), respectively. The low shared variance (22%) between HR and physical activity further support the interpretation that the cardiac activity was strongly linked to the experience of stress and not accountable by operators' movement within the simulator. Cardiac measurements in naturalistic settings can thus reveal relevant information on acute stress with the benefit of not interrupting the primary task.

Cognitive Collaboration Found in Cardiac Physiology: Study in Classroom Environment.

It is known that periods of intense social interaction result in shared patterns in collaborators' physiological signals. However, applied quantitative research on collaboration is hindered due to scarcity of objective metrics of teamwork effectiveness. Indeed, especially in the domain of productive, ecologically-valid activity such as programming, there is a lack of evidence for the most effective, affordable and reliable measures of collaboration quality. In this study we investigate synchrony in physiological signals between collaborating computer science students performing pair-programming exercises in a class room environment. We recorded electrocardiography over the course of a 60 minute programming session, using lightweight physiological sensors. We employ correlation of heart-rate variability features to study social psychophysiological compliance of the collaborating students. We found evident physiological compliance in collaborating dyads' heart-rate variability signals. Furthermore, dyads' self-reported workload was associated with the physiological compliance. Our results show viability of a novel approach to field measurement using lightweight devices in an uncontrolled environment, and suggest that self-reported collaboration quality can be assessed via physiological signals.

Feasibility of an electrodermal activity ring prototype as a research tool.

Electrodermal activity is an indicator of sympathetic activation and a useful tool for investigating psychological and physiological arousal. Novel wearable skin conductivity sensors offer portable low-cost solutions for long-term monitoring. In this article we compare the similarity of signals between a prototype of the wearable Moodmetric EDA Ring and a laboratory-grade skin conductance sensor in a psychophysiological experiment. The similarity of the signals was estimated by calculating the cosine distance between phasic features extracted from decomposed signals. The similarity was on average 83.3% ± 16.4%. The compound error of the decomposition process was also investigated and no systematic bias was observed towards either device. We conclude that the prototype ring is a promising device for ecologically valid field studies.

Affective processing in natural scene viewing: valence and arousal interactions in eye-fixation-related potentials.

Attention is drawn to emotionally salient stimuli. The present study investigates processing of emotionally salient regions during free viewing of emotional scenes that were categorized according to the two-dimensional model comprising of valence (unpleasant, pleasant) and arousal (high, low). Recent studies have reported interactions between these dimensions, indicative of stimulus-evoked approach or withdrawal tendencies. We addressed the valence and arousal effects when emotional items were embedded in complex real-world scenes by analyzing both eye movement behavior and eye-fixation-related potentials (EFRPs) time-locked to the critical event of fixating the emotionally salient items for the first time. Both data sets showed an interaction between the valence and arousal dimensions. First, the fixation rates and gaze durations on emotionally salient regions were enhanced for unpleasant versus pleasant images in the high arousal condition. In the low arousal condition, both measures were enhanced for pleasant versus unpleasant images. Second, the EFRP results at 140-170 ms [P2] over the central site showed stronger responses for high versus low arousing images in the unpleasant condition. In addition, the parietal LPP responses at 400-500 ms post-fixation were enhanced for stimuli reflecting congruent stimulus dimensions, that is, stronger responses for high versus low arousing images in the unpleasant condition and stronger responses for low versus high arousing images in the pleasant condition. The present findings support the interactive two-dimensional approach, according to which the integration of valence and arousal recruits brain regions associated with action tendencies of approach or withdrawal.

Eye movement related brain responses to emotional scenes during free viewing.

Emotional stimuli are preferentially processed over neutral stimuli. Previous studies, however, disagree on whether emotional stimuli capture attention preattentively or whether the processing advantage is dependent on allocation of attention. The present study investigated attention and emotion processes by measuring brain responses related to eye movement events while 11 participants viewed images selected from the International Affective Picture System (IAPS). Brain responses to emotional stimuli were compared between serial and parallel presentation. An "emotional" set included one image with high positive or negative valence among neutral images. A "neutral" set comprised four neutral images. The participants were asked to indicate which picture-if any-was emotional and to rate that picture on valence and arousal. In the serial condition, the event-related potentials (ERPs) were time-locked to the stimulus onset. In the parallel condition, the ERPs were time-locked to the first eye entry on an image. The eye movement results showed facilitated processing of emotional, especially unpleasant information. The EEG results in both presentation conditions showed that the LPP ("late positive potential") amplitudes at 400-500 ms were enlarged for the unpleasant and pleasant pictures as compared to neutral pictures. Moreover, the unpleasant scenes elicited stronger responses than pleasant scenes. The ERP results did not support parafoveal emotional processing, although the eye movement results suggested faster attention capture by emotional stimuli. Our findings, thus, suggested that emotional processing depends on overt attentional resources engaged in the processing of emotional content. The results also indicate that brain responses to emotional images can be analyzed time-locked to eye movement events, although the response amplitudes were larger during serial presentation.