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).     

Investigation of Bimetallic Nickel Catalysts in Catalyst‐Transfer Polymerization of π‐Conjugated Polymers

A comparative study involving bimetallic nickel catalysts designed from disubstituted N,N,N′,N′‐tetra(diphenylphosphanylmethyl)benzene diamine bridging ligands is reported. Catalyst behavior is explored in the Kumada catalyst‐transfer polymerization (KCTP) using poly(3‐hexylthiophene) (P3HT) as the model system. The success of a controlled polymerization is monitored by analyzing monomer conversion, degree of polymerization, end‐group identity, and molecular weight distribution. The characterization of P3HT obtained from KCTP initiated with the bimetallic catalysts shows chain‐growth behavior; however, the presence of Br/Br end‐groups and broader molecular weight distribution reveals a reduced controlled polymerization compared to the commonly employed Ni(dppp)Cl₂. The observed increase in intermolecular chain transfer and termination processes in KCTP initiation with the bimetallic catalysts can be attributed to a weaker Ni(0)‐π‐aryl complex interaction, which is caused by increased steric crowding of the coordination sphere.