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This study demonstrates a high-value valorization of blast furnace slag in foamed alkali-activated filters for adsorption applications, using methylene blue as a model compound. The filters were prepared by combining alkali activation of blast furnace slag with direct foaming, followed by curing at 60 °C for 4 h. Five different surfactants were compared for the stabilization of foams. Based on an initial screening, the Triton X-405 surfactant was selected for further studies. The dosages of selected surfactant and H₂O₂ were optimized to obtain compressive strength of 2.59 MPa and specific surface area of 83.3 m²/g for powdered material and 78.31 m²/g for foam pieces. Porosity was determined as 64%, 65%, or 50% by using gas pycnometry, Archimedes method, or X-ray microtomography, respectively. The optimized filter mix design was applied for methylene blue removal in continuous column experiments at two influent concentrations (5 and 10 ppm) by using constant empty-bed contact time of ~9 min (flowrate of ~1 L/h). After 6 h, for both influent concentrations, the dye removal was still 74%, with the initial removal of ~100%. The saturated filter could be regenerated by a thermal treatment resulting improved adsorption performance. When the material was employed as powder, the maximum adsorption capacity was 60.35 mg/g according to the Langmuir isotherm (R² = 0.99) and adsorption kinetics followed the pseudo-second order model. The results demonstrate preliminarily that porous filters prepared in this study have potential to be used in industrial wastewater treatment.

The aim of this study was to quantify sub-resolution trabecular bone morphometrics, which are also related to osteoarthritis (OA), from clinical resolution cone beam computed tomography (CBCT). Samples (n = 53) were harvested from human tibiae (N = 4) and femora (N = 7). Grey-level co-occurrence matrix (GLCM) texture and histogram-based parameters were calculated from CBCT imaged trabecular bone data, and compared with the morphometric parameters quantified from micro-computed tomography. As a reference for OA severity, histological sections were subjected to OARSI histopathological grading. GLCM and histogram parameters were correlated to bone morphometrics and OARSI individually. Furthermore, a statistical model of combined GLCM/histogram parameters was generated to estimate the bone morphometrics. Several individual histogram and GLCM parameters had strong associations with various bone morphometrics (|r| > 0.7). The most prominent correlation was observed between the histogram mean and bone volume fraction (r = 0.907). The statistical model combining GLCM and histogram-parameters resulted in even better association with bone volume fraction determined from CBCT data (adjusted R2 change = 0.047). Histopathology showed mainly moderate associations with bone morphometrics (|r| > 0.4). In conclusion, we demonstrated that GLCM- and histogram-based parameters from CBCT imaged trabecular bone (ex vivo) are associated with sub-resolution morphometrics. Our results suggest that sub-resolution morphometrics can be estimated from clinical CBCT images, associations becoming even stronger when combining histogram and GLCM-based parameters.

Articular cartilage undergoes structural and biochemical changes during maturation, but the knowledge on how these changes relate to articular cartilage function at different stages of maturation is lacking. Equine articular cartilage samples of four different maturation levels (newborn, 5-month-old, 11-month-old and adult) were collected (N = 25). Biomechanical tensile testing, Fourier transform infrared microspectroscopy (FTIR-MS) and polarized light microscopy were used to study the tensile, biochemical and structural properties of articular cartilage, respectively. The tensile modulus was highest and the breaking energy lowest in the newborn group. The collagen and the proteoglycan contents increased with age. The collagen orientation developed with age into an arcade-like orientation. The collagen content, proteoglycan content, and collagen orientation were important predictors of the tensile modulus (p < 0.05 in multivariable regression) and correlated significantly also with the breaking energy (p < 0.05 in multivariable regression). Partial least squares regression analysis of FTIR-MS data provided accurate predictions for the tensile modulus (r = 0.79) and the breaking energy (r = 0.65). To conclude, the composition and structure of equine articular cartilage undergoes changes with depth that alter functional properties during maturation, with the typical properties of mature tissue reached at the age of 5–11 months.