Fourier-transform infrared study on effects of ageing, oestrogen level and altered dietary loading on rat mandibular condylar cartilage.

OBJECTIVE: Mandibular condylar cartilage (MCC) of the rat was examined with the Fourier-transform infrared (FITR) spectroscopic imaging to study the effects of ageing, oestrogen level and altered dietary loading on the structure of MCC. MATERIALS AND METHODS: The Sprague-Dawley rats (n = 96) aged 5 and 14 months were divided into 12 subgroups according to age, oestrogen status (ovariectomized [OVX], non-ovariectomized [non-OVX)]) and diet (hard, normal, soft). Specimens of the MCC were examined with FTIR spectroscopic imaging to quantify the distribution of collagens and proteoglycans. MCC was divided sagittally into three segments: anterior, most superior and posterior. From each segment, the collagen and proteoglycan contents at different depths of cartilage were statistically compared between the groups using an N-way analysis of variance (ANOVA). RESULTS: The amount of collagen content was significantly associated with old age in the deep layer of the anterior segment and in the middle layer of the posterior segment of MCC. In the deep layer of the most superior segment, the collagen content also increased with ageing. The amount of proteoglycan content increased significantly when dietary loading increased, and the oestrogen level decreased in the deep layer of the most superior segment of MCC. CONCLUSION: Ageing, oestrogen level and altered dietary loading have a significant effect on the location and content of collagens and proteoglycans of rat MCC. Ageing significantly increased the amount of collagen content in the superior and posterior segments, being highest in the older soft-diet rats. Decreased oestrogen levels and increased dietary loading increased the amount of proteoglycan content.

Optimization of measurement mode and sample processing for FTIR microspectroscopy in skin cancer research.

The use of Fourier Transform Infrared (FTIR) microspectroscopy to study cancerous cells and tissues has gained popularity due to its ability to provide spatially resolved information at the molecular level. Transmission and transflection are the commonly used measurement modes for FTIR microspectroscopy, and the tissue samples measured in these modes are often paraffinized or deparaffinized. Previous studies have shown that variability in the spectra acquired using different measurement modes and sample processing methods affect the result of the analysis. However, there is no protocol that standardizes the mode of measurement and sample processing method to achieve the best classification result. This study compares the spectra of primary (IPC-298) and metastatic (SK-MEL-30) melanoma cell lines acquired in both transmission and transflection modes using paraffinized and deparaffinized samples to determine the optimal combination for accurate classification. Significant differences were observed in the spectra of the same cell line measured in different modes and with or without deparaffinization. The PLS-DA model built for the classification of two cell lines showed high accuracy in each case, suggesting that both modes and sample processing alternatives are suitable for differentiating cultured cell samples using supervised multivariate analysis. The biochemical information contained in the cells capable of discriminating two melanoma cell lines is present regardless of mode or sample type used. However, the paraffinized samples measured in transflection mode provided the best classification.

Preprocessing Strategies for Sparse Infrared Spectroscopy: A Case Study on Cartilage Diagnostics.

The aim of the study was to optimize preprocessing of sparse infrared spectral data. The sparse data were obtained by reducing broadband Fourier transform infrared attenuated total reflectance spectra of bovine and human cartilage, as well as of simulated spectral data, comprising several thousand spectral variables into datasets comprising only seven spectral variables. Different preprocessing approaches were compared, including simple baseline correction and normalization procedures, and model-based preprocessing, such as multiplicative signal correction (MSC). The optimal preprocessing was selected based on the quality of classification models established by partial least squares discriminant analysis for discriminating healthy and damaged cartilage samples. The best results for the sparse data were obtained by preprocessing using a baseline offset correction at 1800 cm-1, followed by peak normalization at 850 cm-1 and preprocessing by MSC.

Preclassification of Broadband and Sparse Infrared Data by Multiplicative Signal Correction Approach.

Preclassification of raw infrared spectra has often been neglected in scientific literature. Separating spectra of low spectral quality, due to low signal-to-noise ratio, presence of artifacts, and low analyte presence, is crucial for accurate model development. Furthermore, it is very important for sparse data, where it becomes challenging to visually inspect spectra of different natures. Hence, a preclassification approach to separate infrared spectra for sparse data is needed. In this study, we propose a preclassification approach based on Multiplicative Signal Correction (MSC). The MSC approach was applied on human and the bovine knee cartilage broadband Fourier Transform Infrared (FTIR) spectra and on a sparse data subset comprising of only seven wavelengths. The goal of the preclassification was to separate spectra with analyte-rich signals (i.e., cartilage) from spectra with analyte-poor (and high-matrix) signals (i.e., water). The human datasets 1 and 2 contained 814 and 815 spectra, while the bovine dataset contained 396 spectra. A pure water spectrum was used as a reference spectrum in the MSC approach. A threshold for the root mean square error (RMSE) was used to separate cartilage from water spectra for broadband and the sparse spectral data. Additionally, standard noise-to-ratio and principle component analysis were applied on broadband spectra. The fully automated MSC preclassification approach, using water as reference spectrum, performed as well as the manual visual inspection. Moreover, it enabled not only separation of cartilage from water spectra in broadband spectral datasets, but also in sparse datasets where manual visual inspection cannot be applied.

Mineralization of dental tissues and caries lesions detailed with Raman microspectroscopic imaging.

Dental caries is the most common oral disease that causes demineralization of the enamel and later of the dentin. Depth-wise assessment of the demineralization process could be used to help in treatment planning. In this study, we aimed to provide baseline information for the development of a Raman probe by characterizing the mineral composition of the dental tissues from large composition maps (6 × 3 mm2 with 15 µm step size) using Raman microspectroscopy. Ten human wisdom teeth with different stages of dental caries lesions were examined. All of the teeth were cut in half at representative locations of the caries lesions and then imaged with a Raman imaging microscope. The pre-processed spectral maps were combined into a single data matrix, and the spectra of the enamel, dentin, and caries were identified by K-means cluster analysis. Our results showed that unsupervised identification of dental caries is possible with the K-means clustering. The compositional analysis revealed that the carious lesions are less mineralized than the healthy enamel, and when the lesions extend into the dentin, they are even less mineralized. Furthermore, there were more carbonate imperfections in the mineral crystal lattice of the caries tissues than in healthy tissues. Interestingly, we observed gradients in the sound enamel showing higher mineralization and greater mineral crystal perfection towards the tooth surface. To conclude, our results provide a baseline for the methodological development aimed at clinical diagnostics for the early detection of active caries lesions.

Critical-sized cartilage defects in the equine carpus.

AIM: The horse joint, due to its similarity with the human joint, is the ultimate model for translational articular cartilage repair studies. This study was designed to determine the critical size of cartilage defects in the equine carpus and serve as a benchmark for the evaluation of new cartilage treatment options. MATERIAL AND METHODS: Circular full-thickness cartilage defects with a diameter of 2, 4, and 8 mm were created in the left middle carpal joint and similar osteochondral (3.5 mm in depth) defects in the right middle carpal joint of 5 horses. Spontaneously formed repair tissue was examined macroscopically, with MR and µCT imaging, polarized light microscopy, standard histology, and immunohistochemistry at 12 months. RESULTS: Filling of 2 mm chondral defects was good (77.8 ± 8.5%), but proteoglycan depletion was evident in Safranin-O staining and gadolinium-enhanced MRI (T1Gd). Larger chondral defects showed poor filling (50.6 ± 2.7% in 4 mm and 31.9 ± 7.3% in 8 mm defects). Lesion filling in 2, 4, and 8 mm osteochondral defects was 82.3 ± 3.0%, 68.0 ± 4.6% and 70.8 ± 15.4%, respectively. Type II collagen staining was seen in 9/15 osteochondral defects but only in 1/15 chondral defects. Subchondral bone pathologies were evident in 14/15 osteochondral samples but only in 5/15 chondral samples. Although osteochondral lesions showed better neotissue quality than chondral lesions, the overall repair was deemed unsatisfactory because of the subchondral bone pathologies. CONCLUSION: We recommend classifying 4 mm as critical osteochondral lesion size and 2 mm as critical chondral lesion size for cartilage repair research in the equine carpal joint model.

Quantitative susceptibility mapping of articular cartilage: Ex vivo findings at multiple orientations and following different degradation treatments.

PURPOSE: We investigated the feasibility of quantitative susceptibility mapping (QSM) for assessing degradation of articular cartilage by measuring ex vivo bovine cartilage samples subjected to different degradative treatments. Specimens were scanned at several orientations to study if degradation affects the susceptibility anisotropy. T2*-mapping, histological stainings, and polarized light microscopy were used as reference methods. Additionally, simulations of susceptibility in layered geometry were performed. METHODS: Samples (n = 9) were harvested from the patellae of skeletally mature bovines. Three specimens served as controls, and the rest were artificially degraded. MRI was performed at 9.4T using a 3D gradient echo sequence. QSM and T2* images and depth profiles through the centers of the samples were compared with each other and the histological findings. A planar isotropic model with depth-wise susceptibility variation was used in the simulations. RESULTS: A strong diamagnetic contrast was seen in the deep and calcified layers of cartilage, while T2* maps reflected the typical trilaminar structure of the collagen network. Anisotropy of susceptibility in cartilage was observed and was found to differ from the T2* anisotropy. Slight changes were observed in QSM and T2* following the degradative treatments. In simulations, anisotropy was observed. CONCLUSIONS: The results suggest that QSM is not sensitive to cartilage proteoglycan content, but shows sensitivity to the amount of calcification and to the integrity of the collagen network, providing potential for assessing osteoarthritis. The simulations suggested that the anisotropy of susceptibility might be partially explained by the layered geometry of susceptibility in cartilage.

Aggravated Postinfarct Heart Failure in Type 2 Diabetes Is Associated with Impaired Mitophagy and Exaggerated Inflammasome Activation.

Type 2 diabetes mellitus (T2DM) is a major risk factor for heart disease. Mortality rates after myocardial infarction (MI) are significantly increased in T2DM patients because of dysfunctional left ventricle (LV). However, molecular pathways underlying accelerated heart failure (HF) after MI in T2DM remain unclear. We investigated the underlying mechanisms by inducing MI in a well-established model of T2DM and control mice. Cardiac imaging revealed a significantly decreased global left ventricular ejection fraction in parallel with increased mortality after MI in T2DM mice compared with control mice. Genome-wide mRNA sequencing, immunoblot, electron microscopy, together with immunofluorescence staining for LC3 and p62 indicated an impaired mitophagy in peri-infarct regions of LV in T2DM mice compared with control mice. Furthermore, defective mitophagy was associated with an increased release of mitochondrial DNA, resulting in Aim2 and NLRC4 inflammasome and caspase-I hyperactivation in cardiomyocytes and cardiac macrophages in peri-infarct regions of LV in T2DM mice. Consistent with inflammasome and caspase-I hyperactivation, cardiomyocyte death and IL-18 secretion were increased in T2DM mice. Our results indicate that T2DM aggravates HF after MI through defective mitophagy, associated exaggerated inflammasome activation, cell death, and IL-18 secretion, suggesting that restoring mitophagy and inhibiting inflammasome activation may serve as novel targets for the prevention and treatment of HF in T2DM.

Correlations of low-field NMR and variable-field NMR parameters with osteoarthritis in human articular cartilage under load.

NMR experiments carried out at magnetic fields below 1 T provide new relaxation parameters unavailable with conventional clinical scanners. Contrast of T1 generally becomes larger towards low fields, as slow molecular reorientation processes dominate relaxation at the corresponding Larmor frequencies. This advantage has to be considered in the context of lower sensitivity and frequently reduced spatial resolution. The layered structure of cartilage is one example where a particularly strong variation of T1 across the tissue occurs, being affected by degenerative diseases such as osteoarthritis (OA). Furthermore, the presence of 1 H-14  N cross-relaxation, leading to so-called quadrupolar dips in the 1 H relaxation time dispersion, provide insight into the concentration and mobility of proteoglycans and collagen in cartilage, both being affected by OA. In this study, low-field imaging and variable-field NMR relaxometry were combined for the first time for tissue samples, employing unidirectional load to probe the mechanical properties. 20 human knee cartilage samples were placed in a compression cell, and studied by determining relaxation profiles without and with applied pressure (0.6 MPa) at 50 µm in-plane resolution, and comparing with volume-averaged T1 dispersion. Samples were subsequently stored in formalin, prepared for histology and graded according to the Mankin score system. Quadrupolar dips and thickness change under load showed the strongest correlation with Mankin grade. Average T1 and change of maximum T1 under load, as well as its position, correlate with thickness and thickness change. Furthermore, T1 (ω) above 25 mT was found to correlate with thickness change. While volume-averaged T1 is not a suitable indicator for OA, its change due to mechanical load and its extreme values are suggested as biomarkers available in low-field MRI systems. The shape of the dispersion T1 (ω) represents a promising access to understanding and quantifying molecular dynamics in tissue, pointing toward future in vivo tissue studies.

Micro-computed Tomography-Based Collagen Orientation and Anisotropy Analysis of Rabbit Articular Cartilage.

The collagen network is the highly organized backbone of articular cartilage providing tissue tensile stiffness and restricting proteoglycan bleaching out of the tissue. Osteoarthritis (OA) diminishes proper collagen network adaptation. Our aim was to provide quantitative three-dimensional (3D) information of the cartilage collagen network adaptation in early osteoarthritis using high resolution micro-computed tomography (µCT)-imaging. Osteochondral samples from the femoral condyles were collected from healthy (N = 8, both legs) and experimental OA rabbit model with anterior cruciate ligament transection (N = 14, single leg). Samples were processed for cartilage µCT-imaging and histological evaluation with polarized light microscopy (PLM). Structure tensor analysis was used to analyse the collagen fibre orientation and anisotropy of the µCT-images, and PLM was used as a validation for structural changes. Depth-wise comparison of collagen fibre orientation acquired with µCT-imaging and PLM correlated well, but the values obtained with PLM were systematically greater than those measured with µCT-imaging. Structure tensor analysis allowed for 3D quantification of collagen network anisotropy. Finally, µCT-imaging revealed only minor differences between the control and experimental groups.

Clustering of infrared spectra reveals histological zones in intact articular cartilage.

OBJECTIVE: Articular cartilage (AC) exhibits specific zonal structure that follows the organization of collagen network and concentration of tissue constituents. The aim of this study was to investigate the potential of unsupervised clustering analysis applied to Fourier transform infrared (FTIR) microspectroscopy to detect depth-dependent structural and compositional differences in intact AC. METHOD: Seven rabbit and eight bovine intact patellae AC samples were imaged using FTIR microspectroscopy and normalized raw spectra were clustered using the fuzzy C-means algorithm. Differences in mean spectra of clusters were investigated by quantitative estimation of collagen and proteoglycan (PG) contents, as well as by careful visual investigation of locations of spectral changes. RESULTS: Clustering revealed the typical layered structure of AC in both species. However, more distinct clusters were found for rabbit samples, whereas bovine AC showed more complex layered structure. In both species, clustering structure corresponded with that in polarized light microscopic (PLM) images; however, some differences were also observed. Spectral differences between clusters were identified at the same spectral locations for both species. Estimated PG/collagen ratio decreased significantly from superficial to middle or deep zones, which might explain the difference in clustering results compared to PLM. CONCLUSION: FTIR microspectroscopy in combination with cluster analysis allows detailed examination of spatial changes in AC. As far as we know, no previous single technique could reveal a layered structure of AC without any a priori information.

Diagnostic performance of attenuated total reflection Fourier-transform infrared spectroscopy for detecting COVID-19 from routine nasopharyngeal swab samples.

Attenuated total reflection Fourier-transform infrared (ATR-FTIR) spectroscopy coupled with machine learning-based partial least squares discriminant analysis (PLS-DA) was applied to study if severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) could be detected from nasopharyngeal swab samples originally collected for polymerase chain reaction (PCR) analysis. Our retrospective study included 558 positive and 558 negative samples collected from Northern Finland. Overall, we found moderate diagnostic performance for ATR-FTIR when PCR analysis was used as the gold standard: the average area under the receiver operating characteristics curve (AUROC) was 0.67-0.68 (min. 0.65, max. 0.69) with 20, 10 and 5 k-fold cross validations. Mean accuracy, sensitivity and specificity was 0.62-0.63 (min. 0.60, max. 0.65), 0.61 (min. 0.58, max. 0.65) and 0.64 (min. 0.59, max. 0.67) with 20, 10 and 5 k-fold cross validations. As a conclusion, our study with relatively large sample set clearly indicate that measured ATR-FTIR spectrum contains specific information for SARS-CoV-2 infection (P < 0.001 for AUROC in label permutation test). However, the diagnostic performance of ATR-FTIR remained only moderate, potentially due to low concentration of viral particles in the transport medium. Further studies are needed before ATR-FTIR can be recommended for fast screening of SARS-CoV-2 from nasopharyngeal swab samples.

Suitable Cathode NMP Replacement for Efficient Sustainable Printed Li-Ion Batteries.

N-methyl-2-pyrrolidone (NMP) is the most common solvent for manufacturing cathode electrodes in the battery industry; however, it is becoming restricted in several countries due to its negative environmental impact. Taking into account that ∼99% of the solvent used during electrode fabrication is recovered, dimethylformamide (DMF) is a considerable candidate to replace NMP. The lower boiling point and higher ignition temperature of DMF lead to a significant reduction in the energy consumption needed for drying the electrodes and improve the safety of the production process. Additionally, the lower surface tension and viscosity of DMF enable improved current collector wetting and higher concentrations of the solid material in the cathode slurry. To verify the suitability of DMF as a replacement for NMP, we utilized screen printing, a fabrication method that provides roll-to-roll compatibility while allowing controlled deposition and creation of sophisticated patterns. The battery systems utilized NMC (LiNi x Mn y Co z O2) chemistry in two configurations: NMC523 and NMC88. The first, well-established NCM523, was used as a reference, while NMC88 was used to demonstrate the potential of the proposed method with high-capacity materials. The cathodes were used to create coin and pouch cell batteries that were cycled 1000 times. The achieved results indicate that DMF can successfully replace NMP in the NMC cathode fabrication process without compromising battery performance. Specifically, both the NMP blade-coated and DMF screen-printed batteries retained 87 and 90% of their capacity after 1000 (1C/1C) cycles for NMC523 and NMC88, respectively. The modeling results of the drying process indicate that utilizing a low-boiling-point solvent (DMF) instead of NMP can reduce the drying energy consumption fourfold, resulting in a more environmentally friendly battery production process.

Discrimination of melanoma cell lines with Fourier Transform Infrared (FTIR) spectroscopy.

Among skin cancers, melanoma is the lethal form and the leading cause of death in humans. Melanoma begins in melanocytes and is curable at early stages. Thus, early detection and evaluation of its metastatic potential are crucial for effective clinical intervention. Fourier transform infrared (FTIR) spectroscopy has gained considerable attention due to its versatility in detecting biochemical and biological features present in the samples. Changes in these features are used to differentiate between samples at different stages of the disease. Previously, FTIR spectroscopy has been mostly used to distinguish between healthy and diseased conditions. With this study, we aim to discriminate between different melanoma cell lines based on their FTIR spectra. Formalin-fixed paraffin embedded samples from three melanoma cell lines (IPC-298, SK-MEL-30 and COLO-800) were used. Statistically significant differences were observed in the prominent spectral bands of three cell lines along with shifts in peak positions. A partial least square discriminant analysis (PLS-DA) model built for the classification of three cell lines showed an overall accuracy of 92.6% with a sensitivity of 85%, 95.75%, 96.54%, and specificity of 97.80%, 92.14%, 98.64% for the differentiation of IPC-298, SK-MEL-30, and COLO-800, respectively. The results suggest that FTIR spectroscopy can differentiate between different melanoma cell lines and thus potentially characterize the metastatic potential of melanoma.

Infrared Fiber-Optic Spectroscopy Detects Bovine Articular Cartilage Degeneration.

OBJECTIVE: Joint injuries may lead to degeneration of cartilage tissue and initiate development of posttraumatic osteoarthritis. Arthroscopic surgeries can be used to treat joint injuries, but arthroscopic evaluation of articular cartilage quality is subjective. Fourier transform infrared spectroscopy combined with fiber optics and attenuated total reflectance crystal could be used for the assessment of tissue quality during arthroscopy. We hypothesize that fiber-optic mid-infrared spectroscopy can detect enzymatically and mechanically induced damage similar to changes occurring during progression of osteoarthritis. DESIGN: Bovine patellar cartilage plugs were extracted and degraded enzymatically and mechanically. Adjacent untreated samples were utilized as controls. Enzymatic degradation was done using collagenase and trypsin enzymes. Mechanical damage was induced by (1) dropping a weight impactor on the cartilage plugs and (2) abrading the cartilage surface with a rotating sandpaper. Fiber-optic mid-infrared spectroscopic measurements were conducted before and after treatments, and spectral changes were assessed with random forest, partial least squares discriminant analysis, and support vector machine classifiers. RESULTS: All models had excellent classification performance for detecting the different enzymatic and mechanical damage on cartilage matrix. Random forest models achieved accuracies between 90.3% and 77.8%, while partial least squares model accuracies ranged from 95.8% to 84.7%, and support vector machine accuracies from 91.7% to 80.6%. CONCLUSIONS: The results suggest that fiber-optic Fourier transform infrared spectroscopy attenuated total reflectance spectroscopy is a viable way to detect minor and major degeneration of articular cartilage. Objective measures provided by fiber-optic spectroscopic methods could improve arthroscopic evaluation of cartilage damage.

Effects of growth and exercise on composition, structural maturation and appearance of osteoarthritis in articular cartilage of hamsters.

Articular cartilage composition and structure are maintained and remodeled by chondrocytes under the influence of loading. Exercise-induced changes in the composition, structure, mechanical properties and tissue integrity of growing and aging hamster articular cartilage were investigated. Articular cartilage samples (n = 191) were harvested from the proximal tibiae of hamsters aged 1, 3, 6, 12 and 15 months. The hamsters were divided into runners and controls. The runners had free access to a running wheel between 1 and 3 months (runner groups 3-, 12- and 15-month-old hamsters) or 1 and 6 months (runner group 6-month-old hamsters) of age. Control animals were subjected to a sedentary lifestyle. Mechanical indentation tests and depth-wise compositional and structural analyses were performed for the cartilage samples. Furthermore, the integrity of articular cartilage was assessed using histological osteoarthritis grading. Exercise affected the collagen network organization after a 5-month exercise period, especially in the middle and deep zones. However, no effect on the mechanical properties was detected after exercise. Before the age of 12 months, the runners showed less osteoarthritis than the controls, whereas at 15 months of age the situation was reversed. It is concluded that, in hamsters, physical exercise at a young age enhances cartilage maturation and alters the depth-wise cartilage structure and composition. This may be considered beneficial. However, exercise at a young age demonstrated adverse effects on cartilage at a later age with a significant increase in the incidence of osteoarthritis.

Near Infrared Spectroscopy Enables Differentiation of Mechanically and Enzymatically Induced Cartilage Injuries.

This study evaluates the feasibility of near infrared (NIR) spectroscopy to distinguish between different cartilage injury types associated with post-traumatic osteoarthritis and idiopathic osteoarthritis (OA) induced by mechanical and enzymatic damages. Bovine osteochondral samples (n = 72) were subjected to mechanical (n = 24) and enzymatic (n = 36) damage; NIR spectral measurements were acquired from each sample before and after damage, and from a separate control group (n = 12). Biomechanical measurements were then conducted to determine the functional integrity of the samples. NIR spectral variations resulting from different damage types were investigated and the samples classified using partial least squares discriminant analysis (PLS-DA). Partial least squares regression (PLSR) was then employed to investigate the relationship between the NIR spectra and biomechanical properties of the samples. Results of the study demonstrate that substantial spectral changes occur in the region of 1700-2200 nm due to tissue damages, while differences between enzymatically and mechanically induced damages can be observed mainly in the region of 1780-1810 nm. We conclude that NIR spectroscopy, combined with multivariate analysis, is capable of discriminating between cartilage injuries that mimic idiopathic OA and traumatic injuries based on specific spectral features. This information could be useful in determining the optimal treatment strategy during cartilage repair in arthroscopy.

Raman microspectroscopic analysis of the tissue-specific composition of the human osteochondral junction in osteoarthritis: A pilot study.

This study investigates the influence of osteoarthritis (OA) disease severity on the bio-composition of the osteochondral junction at the human tibial plateau using Raman microspectroscopy. We specifically aim to analyze the spatial composition of mineralized osteochondral tissues, i.e., calcified cartilage (CC) and subchondral bone plate (SBP) from unfixed, hydrated specimens. We hypothesize that the mineralization of CC and SBP decreases in advanced OA. Twenty-eight cylindrical osteochondral samples (d = 4 mm) from tibial plateaus of seven cadaveric donors were harvested and sorted into three groups following histopathological grading: healthy (n = 5), early OA (n = 8), and advanced OA (n = 15). Raman spectra were subjected to multivariate cluster analyses to identify different tissues. Finally, the tissue-specific composition was analyzed, and the impact of OA was statistically evaluated with linear mixed models. Cluster analyses of Raman spectra successfully distinguished CC and SBP as well as a tidemark region and uncalcified cartilage. CC was found to be more mineralized and the mineral was more crystalline compared with SBP. Both tissues exhibited similar compositional changes as a function of histopathological OA severity. In early OA, the mineralization tends to increase, and the mineral contains fewer carbonate substitutions. Compared with early OA, mineral crystals are rich in carbonate while the overall mineralization decreases in advanced OA. This Raman spectroscopic study advances the methodology for investigating the complex osteochondral junction from native tissue. The developed methodology can be used to elucidate detailed tissue-specific changes in the chemical composition with advancing OA. STATEMENT OF SIGNIFICANCE: In this study, Raman microspectroscopy was utilized to investigate the influence of osteoarthritic degeneration on the tissue-specific biochemical composition of the human osteochondral junction. Multivariate cluster analyses allowed us to characterize subtle compositional changes in the calcified cartilage and subchondral bone plate as well as in the tidemark region. The compositional differences found between the calcified cartilage and subchondral bone plate in both organic and mineral phases will serve as critical benchmark parameters when designing biomaterials for osteochondral repair. We found tissue-specific changes in the mineralization and carbonate substitution as a function of histopathological OA severity. Our developed methodology can be used to investigate the metabolic changes in the osteochondral junction associated with osteoarthritis.

Histochemical quantification of collagen content in articular cartilage.

BACKGROUND: Articular cartilage (AC) is mainly composed of water, type II collagen, proteoglycans (PGs) and chondrocytes. The amount of PGs in AC is routinely quantified with digital densitometry (DD) from Safranin O-stained sections, but it is unclear whether similar method could be used for collagens. OBJECTIVE: The aim of this study was to clarify whether collagens can be quantified from histological AC sections using DD. MATERIAL AND METHODS: Sixteen human AC samples were stained with Masson's trichrome or Picrosirius red. Optical densities of histological stains were compared to two commonly used collagen parameters (amide I and collagen CH2 side chain peak at 1338cm-1) measured using Fourier Transform Infrared (FTIR) spectroscopic imaging. RESULTS: Optical density of Modified Masson's trichrome staining, which included enzymatic removal of PGs before staining, correlated significantly with FTIR-derived collagen parameters at almost all depths of cartilage. The other studied staining protocols displayed significant correlations with the reference parameters at only few depth layers. CONCLUSIONS: Based on our findings, modified Masson's trichrome staining protocol is suitable for quantification of AC collagen content. Enzymatic removal of PGs prior to staining is critical as us allows better staining of the collagen. Further optimization of staining protocols may improve the results in the future studies.

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.