A multiscale framework for evaluating three-dimensional cell mechanics in fibril-reinforced poroelastic tissues with anatomical cell distribution – Analysis of chondrocyte deformation behavior in mechanically loaded articular cartilage

Characterization of the mechanical environment of cells in collagenous biological tissues during different daily activities is crucial for understanding the role of mechanics on cell biosynthesis and tissue health. However, current imaging methods are limited in characterizing very fast deformations of cells. This could be achieved with computational multiscale modeling, but current models accommodating collagen fibril networks and poroelastic ground matrix have included only a single cell. In this study, a workflow was developed for generating a three-dimensional multiscale model with imaging-based anatomical cell distributions and their micro-environment (pericellular and extracellular matrix). Fibril-reinforced poroelastic material models with (FRPES) and without (FRPE) swelling were implemented into the model and simulations were performed for evaluating cell deformations before and after experimental loading conducted for rabbit knee joint cartilage. We observed that the cells experienced considerably different deformation based on their location in all models. Both FRPE and FRPES models were able to predict the trends in the changes in cell deformations, although the average and median magnitudes differed between the model predictions and experiments. However, the FRPES model results were generally closer to the experimental results. Current findings suggest that morphological properties of cells are affected by the variations in the tissue properties between the samples and variations within the sample caused by the measurement geometry, local structure and composition. Thus, it would be important to consider the anatomical distribution and location of multiple cells along with the structure of fibril networks if cell deformation metrics are evaluated in collagenous tissues. (C) 2020 The Author(s). Published by Elsevier Ltd

Women with PCOS have an increased risk for cardiovascular disease regardless of diagnostic criteria - a prospective population-based cohort study

OBJECTIVE: Polycystic ovary syndrome (PCOS) is associated with many cardiovascular disease (CVD) risk factors, such as obesity, type 2 diabetes mellitus and hypertension. However, it remains debatable whether the presence of multiple CVD risk factors translates to increased CVD events. DESIGN: A prospective, population-based Northern Finland Birth Cohort 1966. METHODS: Individuals with an expected date of birth in 1966 in Northern Finland have been followed from birth. Women in the cohort were classified as having PCOS according to either the National Institute of Health (NIH) criteria (n = 144) or the Rotterdam criteria (n = 386) at age 31, and they were compared to women without any PCOS features. The study population was re-examined at age 46, and the incidence of major adverse cardiovascular events (MACE), including myocardial infarction (MI), stroke, heart failure and cardiovascular mortality, was recorded up to age 53. RESULTS: During the 22-year follow-up, both women with NIH-PCOS and women with Rotterdam-PCOS had a significantly higher risk for cardiovascular events than control women. The BMI-adjusted hazard ratio (HR) for MACE in the Rotterdam-PCOS group and the NIH-PCOS group was 2.33 (1.26-4.30) and 2.47 (1.18-5.17), respectively. The cumulative hazard curves in both diagnostic categories began to diverge at age 35. Regarding the individual CVD endpoints, MI was significantly more prevalent in both women with NIH-PCOS (P = .010) and women with Rotterdam-PCOS (P = .019), when compared to control women. CONCLUSIONS: PCOS should be considered a significant risk factor for CVD. Future follow-up will show how the risk of CVD events develops after menopausal age

Health-related quality of life in relation to shark symptomatic and radiographic definitions of knee osteoarthritis: data from Osteoarthritis Initiative (OAI) 4-year follow- up study

Background: The purpose was to quantify the decrement in health utility (referred as disutility) associated with knee osteoarthritis (OA) and different symptomatic and radiographic uni- and bilateral definitions of knee OA in a repeated measures design of persons with knee OA or at increased risk of developing knee OA.Methods: Data were obtained from the Osteoarthritis Initiative database. SF-12 health-related quality of life was converted into SF-6D utilities, and were then handled as the health utility loss by subtracting 1.000 from the utility score, yielding a negative value (disutility). Symptomatic OA was defined by radiographic findings (Kellgren-Lawrence, K-L, grade >= 2) and frequent knee pain in the same knee. Radiographic OA was defined by five different definitions (K-L >= 2 unilaterally / bilaterally, or the highest / mean / combination of K-L grades of both knees). Repeated measures generalized estimating equation (GEE) models were used to investigate disutility in relation to these different definitions.Results: Utility decreased with worsening of symptomatic or radiographic status of knee OA. The participants with bilateral and unilateral symptomatic knee OA had 0.03 (p < 0.001) and 0.02 (p < 0.001) points lower utility scores, respectively, compared with the reference group. The radiographic K-L grade 4 defined as the mean or the highest grade of both knees was related to a decrease of 0.04 (p < 0.001) and 0.03 (p < 0.001) points in utility scores, respectively, compared to the reference group.Conclusions: Knee OA is associated with diminished health-related quality of life. Health utility can be quantified in relation to both symptomatic and radiographic uni- and bilateral definitions of knee OA, and these definitions are associated with differing disutilities. The performance of symptomatic definition was better, indicating that pain experience is an important factor in knee OA related quality of life

Eight-year trajectories of changes in health-related quality of life in knee osteoarthritis: Data from the Osteoarthritis Initiative (OAI).

BACKGROUND:Knee osteoarthritis (OA) worsens health-related quality of life (HRQoL) but the symptom pathway varies from person to person. We aimed to identify groups of people with knee OA or at its increased risk whose HRQoL changed similarly. Our secondary aim was to evaluate if patient-related characteristics, incidence of knee replacement (KR) and prevalence of pain medication use differed between the identified HRQoL trajectory groups.METHODS:Eight-year follow-up data of 3053 persons with mild knee OA or at increased risk were obtained from the public Osteoarthritis Initiative (OAI) database. Group-based trajectory modeling was used to identify patterns of experiencing a decrease of ≥10 points (Minimal Important Change, MIC) in the Quality of Life subscale of the Knee injury and Osteoarthritis Outcome Score compared to baseline. Multinomial logistic regression, Cox regression and generalized estimating equation models were used to study secondary aims.RESULTS:Four HRQoL trajectory groups were identified. Persons in the 'no change' group (62.9%) experienced no worsening in HRQoL. 'Rapidly' (9.5%) and 'slowly' worsening (17.1%) groups displayed an increasing probability of experiencing the MIC in HRQoL. The fourth group (10.4%) had 'improving' HRQoL. Female gender, higher body mass index, smoking, knee pain, and lower income at baseline were associated with belonging to the 'rapidly worsening' group. People in 'rapidly' (hazard ratio (HR) 6.2, 95% confidence interval (CI) 3.6-10.7) and 'slowly' worsening (HR 3.4, 95% CI 2.0-5.9) groups had an increased risk of requiring knee replacement. Pain medication was more rarely used in the 'no change' than in the other groups.CONCLUSIONS:HRQoL worsening was associated with several risk factors; surgical and pharmacological interventions were more common in the poorer HRQoL trajectory groups indicating that HRQoL does reflect the need for OA treatment. These findings may have implications for targeting interventions to specific knee OA patient groups.</h4

Rapid CT-based Estimation of Articular Cartilage Biomechanics in the Knee Joint Without Cartilage Segmentation

Knee osteoarthritis (OA) is a painful joint disease, causing disabilities in daily activities. However, there is no known cure for OA, and the best treatment strategy might be prevention. Finite element (FE) modeling has demonstrated potential for evaluating personalized risks for the progression of OA. Current FE modeling approaches use primarily magnetic resonance imaging (MRI) to construct personalized knee joint models. However, MRI is expensive and has lower resolution than computed tomography (CT). In this study, we extend a previously presented atlas-based FE modeling framework for automatic model generation and simulation of knee joint tissue responses using contrast agent-free CT. In this method, based on certain anatomical dimensions measured from bone surfaces, an optimal template is selected and scaled to generate a personalized FE model. We compared the simulated tissue responses of the CT-based models with those of the MRI-based models. We show that the CT-based models are capable of producing similar tensile stresses, fibril strains, and fluid pressures of knee joint cartilage compared to those of the MRI-based models. This study provides a new methodology for the analysis of knee joint and cartilage mechanics based on measurement of bone dimensions from native CT scans

Composition of the pericellular matrix modulates the deformation behaviour of chondrocytes in articular cartilage under static loading

The aim was to assess the role of the composition changes in the pericellular matrix (PCM) for the chondrocyte deformation. For that, a three-dimensional finite element model with depth-dependent collagen density, fluid fraction, fixed charge density and collagen architecture, including parallel planes representing the split-lines, was created to model the extracellular matrix (ECM). The PCM was constructed similarly as the ECM, but the collagen fibrils were oriented parallel to the chondrocyte surfaces. The chondrocytes were modelled as poroelastic with swelling properties. Deformation behaviour of the cells was studied under 15% static compression. Due to the depth-dependent structure and composition of cartilage, axial cell strains were highly depth-dependent. An increase in the collagen content and fluid fraction in the PCMs increased the lateral cell strains, while an increase in the fixed charge density induced an inverse behaviour. Axial cell strains were only slightly affected by the changes in PCM composition. We conclude that the PCM composition plays a significant role in the deformation behaviour of chondrocytes, possibly modulating cartilage development, adaptation and degeneration. The development of cartilage repair materials could benefit from this information

ISO 26000 in Corporate Sustainability Practices: A Case Study of the Forest and Energy Companies in Bioeconomy

Peer reviewe

Fourier Transform Infrared Spectroscopic Imaging and Multivariate Regression for Prediction of Proteoglycan Content of Articular Cartilage

Fourier Transform Infrared (FT-IR) spectroscopic imaging has been earlier applied for the spatial estimation of the collagen and the proteoglycan (PG) contents of articular cartilage (AC). However, earlier studies have been limited to the use of univariate analysis techniques. Current analysis methods lack the needed specificity for collagen and PGs. The aim of the present study was to evaluate the suitability of partial least squares regression (PLSR) and principal component regression (PCR) methods for the analysis of the PG content of AC. Multivariate regression models were compared with earlier used univariate methods and tested with a sample material consisting of healthy and enzymatically degraded steer AC. Chondroitinase ABC enzyme was used to increase the variation in PG content levels as compared to intact AC. Digital densitometric measurements of Safranin O –stained sections provided the reference for PG content. The results showed that multivariate regression models predict PG content of AC significantly better than earlier used absorbance spectrum (i.e. the area of carbohydrate region with or without amide I normalization) or second derivative spectrum univariate parameters. Increased molecular specificity favours the use of multivariate regression models, but they require more knowledge of chemometric analysis and extended laboratory resources for gathering reference data for establishing the models. When true molecular specificity is required, the multivariate models should be used

Male gender, Charnley class C, and severity of bone defects predict the risk for aseptic loosening in the cup of ABG I hip arthroplasty

<p>Abstract</p> <p>Background</p> <p>We studied which factor could predict aseptic loosening in ABG I hip prosthesis with hydroxyapatite coating. Aseptic loosening and periprosthetic osteolysis are believed to be caused, at least in part, by increased polyethylene (PE) wear rate via particle disease. Based on it, increased PE wear rate should be associated with aseptic loosening regardless of the type of implant.</p> <p>Methods</p> <p>We analyzed data from 155 revisions of ABG I hip prostheses to examine the influence of patient, implant, surgery, and wear related factors on the rate of aseptic loosening at the site of the cup. This was calculated by stepwise logistic regression analysis. The stability of the implant and severity of bone defects were evaluated intraoperatively.</p> <p>Results</p> <p>We found that men (odds ratio, OR = 5.6; <it>p </it>= 0.004), patients with Charnley class C (OR = 6.71; <it>p </it>= 0.013), those having more severe acetabular bone defects (OR = 4 for each degree of severity; <it>p </it>= 0.002), and longer time to revision surgery (OR = 1.51 for each additional year; <it>p </it>= 0.012) had a greater chance of aseptic loosening of the cup. However, aseptic loosening was not directly predicted by polyethylene wear rate in our patients.</p> <p>Conclusion</p> <p>Severity of bone defects predicts the risk for aseptic loosening in ABG I cup. Factors potentially associated with the quality of bone bed and biomechanics of the hip might influence on the risk of aseptic loosening in this implant.</p