Detailed Analysis of the Crystal Structures and Magnetic Properties of a Dysprosium(III) Phthalocyaninato Sextuple-Decker Complex: Weak f–f Interactions Suppress Magnetic Relaxation

In the research field of single-molecule magnets (SMMs), lanthanoid–lanthanoid interactions, so-called f–f interactions, are known to affect the SMM properties, although their magnitudes are small. In this article, an SMM with very weak f–f interactions is reported, and the effects of the interactions on the SMM properties are discussed. X-ray structural analysis of the Dy^III-Cd^II-phthalocyaninato sextuple-decker complex (Dy₂Cd₃) reveals that the intramolecular Dy−Dy length in Dy₂Cd₃ is more than 13 Å, which is longer than the intermolecular Dy−Dy length. Even though the two Dy^III ions are far apart, intermolecular ferromagnetic dipole–dipole interactions are observed in Dy₂Cd₃. From detailed analysis of ac magnetic susceptibilities, quantum tunneling of the magnetization (QTM) in Dy₂Cd₃ is partially suppressed owing to the existence of very weak Dy−Dy interactions. Our results show that even very weak Dy−Dy interactions act as a dipolar bias, suppressing QTM.     

Determination of a novel antifibrotic small molecule GDC‐3280 in human plasma and urine by liquid chromatography tandem mass spectrometry to support its first‐in‐human clinical trial

A specific and robust LC–MS/MS method was developed and validated for the quantitative determination of GDC‐3280 in human plasma and urine. The nonspecific binding associated with urine samples was overcome by the addition of CHAPS. The sample volume was 25 μL for either matrix, and supported liquid extraction was employed for analyte extraction. d6‐GDC‐3280 was used as the internal standard. Linear standard curves (R² > 0.9956) were established from 5.00 to 5000 ng/mL in both matrices with quantitation extended to 50,000 ng/mL through dilution. In plasma matrix, the precision (RSD) ranged from 1.5 to 9.9% (intra‐run) and from 2.4 to 7.2% (inter‐run); the accuracy (RE) ranged from 96.1 to 107% (intra‐run) and from 96.7 to 104% (inter‐run). Similarly, in urine the precision was 1.5–6.2% (intra‐run) and 1.9–6.1% (inter‐run); the accuracy was 83.1–99.3% (intra‐run) and 87.1–98.3% (inter‐run). Good recovery (>94%) and negligible matrix effect were achieved in both matrices. Long‐term matrix stability was established for at least 703 days in plasma and 477 days in urine. Bench‐top stability of 25 h and five freeze–thaw cycles were also confirmed in both matrices. The method was successfully implemented in GDC‐3280's first‐in‐human trial for assessing its pharmacokinetic profiles.     

Melham's Conjecture on Odd Power Sums of Fibonacci Numbers

Ozeki and Prodinger showed that the odd power sum of the first several consecutive Fibonacci numbers of even order is equal to a polynomial evaluated at a certain Fibonacci number of odd order. We prove that this polynomial and its derivative both vanish at 1, and will be an integer polynomial after multiplying it by a product of the first consecutive Lucas numbers of odd order. This presents an a?rmative answer to a conjecture of Melham.     

Allostatic load as a complex clinical construct: A case‐based computational modeling approach

Allostatic load (AL) is a complex clinical construct, providing a unique window into the cumulative impact of stress. However, due to its inherent complexity, AL presents two major measurement challenges to conventional statistical modeling (the field's dominant methodology): it is comprised of a complex causal network of bioallostatic systems, represented by an even larger set of dynamic biomarkers; and, it is situated within a web of antecedent socioecological systems, linking AL to differences in health outcomes and disparities. To address these challenges, we employed case‐based computational modeling (CBM), which allowed us to make four advances: (1) we developed a multisystem, 7‐factor (20 biomarker) model of AL's network of allostatic systems; (2) used it to create a catalog of nine different clinical AL profiles (causal pathways); (3) linked each clinical profile to a typology of 23 health outcomes; and (4) explored our results (post hoc) as a function of gender, a key socioecological factor. In terms of highlights, (a) the Healthy clinical profile had few health risks; (b) the pro‐inflammatory profile linked to high blood pressure and diabetes; (c) Low Stress Hormones linked to heart disease, TIA/Stroke, diabetes, and circulation problems; and (d) high stress hormones linked to heart disease and high blood pressure. Post hoc analyses also found that males were overrepresented on the High Blood Pressure (61.2%), Metabolic Syndrome (63.2%), High Stress Hormones (66.4%), and High Blood Sugar (57.1%); while females were overrepresented on the Healthy (81.9%), Low Stress Hormones (66.3%), and Low Stress Antagonists (stress buffers) (95.4%) profiles. © 2015 Wiley Periodicals, Inc. Complexity 21: 291–306, 2016     

Well‐defined polyisoprene‐grafted silica nanoparticles via the RAFT process

The preparation of well‐defined polyisoprene‐grafted silica nanoparticles (PIP‐g‐SiO₂ NPs) was investigated. Surface initiated reversible addition fragmentation chain transfer (SI‐RAFT) polymerization was used to polymerize isoprene from the surface of 15 nm silica NPs. A high temperature stable trithiocarbonate RAFT agent was anchored onto the surface of particles with controllable graft densities. The polymerization of isoprene mediated by silica anchored RAFT with different densities were investigated and compared to the polymerization mediated by free RAFT agents. The effects of different temperatures, initiators, and monomer feed ratios on the kinetics of the SI‐RAFT polymerization were also investigated. Using this technique, block copolymers of polyisoprene and polystyrene on the surface of silica particles were also prepared. The well‐defined synthesized PIP‐g‐SiO₂ NPs were then mixed with a polyisoprene matrix which showed a good level of dispersion throughout the matrix. These tunable grafted particles have potential applications in the field of rubber nanocomposites. © 2017 Wiley Periodicals, Inc. J. Polym. Sci., Part A: Polym. Chem. 2017 , 55, 1493–1501