Bone Microarchitecture Phenotypes Identified in Older Adults Are Associated With Different Levels of Osteoporotic Fracture Risk

Prevalence of osteoporosis is more than 50% in older adults, yet current clinical methods for diagnosis that rely on areal bone mineral density (aBMD) fail to detect most individuals who have a fragility fracture. Bone fragility can manifest in different forms, and a “one-size-fits-all” approach to diagnosis and management of osteoporosis may not be suitable. High-resolution peripheral quantitative computed tomography (HR-pQCT) provides additive information by capturing information about volumetric density and microarchitecture, but interpretation is challenging because of the complex interactions between the numerous properties measured. In this study, we propose that there are common combinations of bone properties, referred to as phenotypes, that are predisposed to different levels of fracture risk. Using HR-pQCT data from a multinational cohort (n = 5873, 71% female) between 40 and 96 years of age, we employed fuzzy c-means clustering, an unsupervised machine-learning method, to identify phenotypes of bone microarchitecture. Three clusters were identified, and using partial correlation analysis of HR-pQCT parameters, we characterized the clusters as low density, low volume, and healthy bone phenotypes. Most males were associated with the healthy bone phenotype, whereas females were more often associated with the low volume or low density bone phenotypes. Each phenotype had a significantly different cumulative hazard of major osteoporotic fracture (MOF) and of any incident osteoporotic fracture (p < 0.05). After adjustment for covariates (cohort, sex, and age), the low density followed by the low volume phenotype had the highest association with MOF (hazard ratio = 2.96 and 2.35, respectively), and significant associations were maintained when additionally adjusted for femoral neck aBMD (hazard ratio = 1.69 and 1.90, respectively). Further, within each phenotype, different imaging biomarkers of fracture were identified. These findings suggest that osteoporotic fracture risk is associated with bone phenotypes that capture key features of bone deterioration that are not distinguishable by aBMD. © 2021 American Society for Bone and Mineral Research (ASBMR).     

A new aspect of in vitro antimicrobial leukocyte- and platelet-rich plasma activity based on flow cytometry assessment

The current literature suggests that the antibacterial effect of leukocyte- and platelet-rich plasma (L-PRP) is directly related to platelet and leukocyte concentrations. The aim of this study was twofold: first, to evaluate the antimicrobial effect of L-PRP against selected bacterial strains in vitro, and second, to correlate this effect with leukocyte and platelet content in the final concentration. Blood was collected from 20 healthy males, and L-PRP, acellular plasma (AP), and autologous thrombin were consecutively prepared. Flow cytometry analysis of the blood, L-PRP, and AP was performed. The L-PRP gel, liquid L-PRP, and thrombin samples were tested in vitro for their antibacterial properties against seven selected bacterial strains using the Kirby–Bauer disk-diffusion method. There was notable antimicrobial activity against selected bacterial strains. No statistically significant correlations between antimicrobial activities and the platelet concentration in L-PRP were observed. Statistically significant positive correlations between selected leukocyte subtypes and antimicrobial activity were noted. A negative correlation was found between elevated monocyte count and antimicrobial activity of L-PRP against one bacterial strain studied. L-PRP possesses antimicrobial activity and can be potentially useful in the fight against certain postoperative infections. The bactericidal effect of L-PRP is caused by leukocytes, and there exists a relationship among selected leukocyte subtypes and L-PRP antimicrobial activity.     

Assessment of toxicity using dehydrogenases activity and mathematical modeling

Dehydrogenase activity is frequently used to assess the general condition of microorganisms in soil and activated sludge. Many studies have investigated the inhibition of dehydrogenase activity by various compounds, including heavy metal ions. However, the time after which the measurements are carried out is often chosen arbitrarily. Thus, it can be difficult to estimate how the toxic effects of compounds vary during the reaction and when the maximum of the effect would be reached. Hence, the aim of this study was to create simple and useful mathematical model describing changes in dehydrogenase activity during exposure to substances that inactivate enzymes. Our model is based on the Lagergrens pseudo-first-order equation, the rate of chemical reactions, enzyme activity, and inactivation and was created to describe short-term changes in dehydrogenase activity. The main assumption of our model is that toxic substances cause irreversible inactivation of enzyme units. The model is able to predict the maximum direct toxic effect (MDTE) and the time to reach this maximum (T_MDTE). In order to validate our model, we present two examples: inactivation of dehydrogenase in microorganisms in soil and activated sludge. The model was applied successfully for cadmium and copper ions. Our results indicate that the predicted MDTE and T_MDTE are more appropriate than EC₅₀ and IC₅₀ for toxicity assessments, except for long exposure times.     

The Neurosteroid Allopregnanolone Is Reduced in Prefrontal Cortex in Alzheimer’s Disease

BACKGROUND: Few data are currently available investigating neurosteroids (NS) in Alzheimer's disease (AD). The NS allopregnanolone may be decreased in serum and plasma in patients with AD, but it is unclear if allopregnanolone is also reduced in brain. Because a number of NS exhibit neuroprotective effects and impact cognitive performance in rodent models, these molecules may be relevant to the pathophysiology of neurodegenerative disorders. We therefore investigated prefrontal cortex (PFC) NS levels in AD. METHODS: Neurosteroid levels (allopregnanolone, pregnenolone, dehydroepiandrosterone [DHEA]) were determined in postmortem PFC in 14 male subjects with AD and 15 cognitively intact male control subjects by gas chromatography/mass spectrometry preceded by high-performance liquid chromatography purification. RESULTS: Subjects with AD exhibit significant reductions in allopregnanolone compared with cognitively intact control subjects (median levels = 2.50 ng/g vs. 5.59 ng/g, respectively; p = .02). Allopregnanolone levels are inversely correlated with neuropathological disease stage (Braak), r = -.49, p = .007. Median DHEA levels are elevated in subjects with AD (p = .01). CONCLUSIONS: Subjects with AD demonstrate significant reductions in PFC allopregnanolone levels, a finding that may be relevant to neuropathological disease stage severity. Neurosteroids may have utility as candidate biomarkers in AD.