Estimation of phase signal change in neuronal current MRI for evoke response of tactile detection with realistic somatosensory laminar network model

Magnetic field generated by neuronal activity could alter magnetic resonance imaging (MRI) signals but detection of such signal is under debate. Previous researches proposed that magnitude signal change is below current detectable level, but phase signal change (PSC) may be measurable with current MRI systems. Optimal imaging parameters like echo time, voxel size and external field direction, could increase the probability of detection of this small signal change. We simulate a voxel of cortical column to determine effect of such parameters on PSC signal. We extended a laminar network model for somatosensory cortex to find neuronal current in each segment of pyramidal neurons (PN). 60,000 PNs of simulated network were positioned randomly in a voxel. Biot–savart law applied to calculate neuronal magnetic field and additional phase. The procedure repeated for eleven neuronal arrangements in the voxel. PSC signal variation with the echo time and voxel size was assessed. The simulated results show that PSC signal increases with echo time, especially 100/80 ms after stimulus for gradient echo/spin echo sequence. It can be up to 0.1 mrad for echo time = 175 ms and voxel size = 1.48 × 1.48 × 2.18 mm³. With echo time less than 25 ms after stimulus, it was just acquired effects of physiological noise on PSC signal. The absolute value of the signal increased with decrease of voxel size, but its components had complex variation. External field orthogonal to local surface of cortex maximizes the signal. Expected PSC signal for tactile detection in the somatosensory cortex increase with echo time and have no oscillation.     

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).     

Successful treatment of hemorrhagic bullous Henoch‐Schonlein purpura with intravenous immunoglobulins

Henoch‐Schonlein purpura (HSP) is the most common systemic vasculitis in childhood. There is no consensus about the management for isolated cutaneous manifestations in HSP. We describe a case of HSP presenting with severe skin lesions that did not respond to standard therapy with corticosteroids. The 11‐year‐old child was treated with intravenous immunoglobulins, which induced rapid and persistent resolution of symptomatology.     

Molecular simplification of lipid A structure: TLR4-modulating cationic and anionic amphiphiles

A growing body of data suggests that therapies based on Toll-like receptors (TLR) targeting, in particular TLR4, holds promise in curing autoimmune and inflammatory pathologies still lacking specific treatment, included several rare diseases. While TLR4 activators (agonists) have already found successful clinical application as vaccine adjuvants, the use of TLR4 blockers (antagonists) as antisepsis agents or as agents against inflammatory diseases (including arthritis, multiple sclerosis, neuroinflammations) and cancer is still at a preclinical phase of development. This minireview focuses on recent achievements on the development of TLR4 modulators based on lipid A structure simplification, in particular on compounds having disaccharide or monosaccharide structures. As the TLR4 activity of natural TLR4 ligands (lipopolysaccharide, LPS and its biologically active part, the lipid A) depends on both the structure of endotoxin aggregates in solution and on single-molecule interaction with MD-2 and CD14 receptors, the rational design of TLR4 modulators should in principle take into account both these factors. In the light of the most recent advances in the field, in this minireview we discuss the structure–activity relationship in simplified lipid A analogs, with cationic or anionic amphiphilic structures.     

Binding mode of conformations and structure-based pharmacophore development for farnesyltransferase inhibitors

Farnesyltransferase (FTase) is one of the prenyltransferase family enzymes that catalyse the transfer of 15-membered isoprenoid (farnesyl) moiety to the cysteine of CAAX motif-containing proteins including Rho and Ras family of G proteins. Inhibitors of FTase act as drugs for cancer, malaria, progeria and other diseases. In the present investigation, we have developed two structure-based pharmacophore models from protein–ligand complex (3E33 and 3E37) obtained from the protein data bank. Molecular dynamics (MD) simulations were performed on the complexes, and different conformers of the same complex were generated. These conformers were undergone protein–ligand interaction fingerprint (PLIF) analysis, and the fingerprint bits have been used for structure-based pharmacophore model development. The PLIF results showed that Lys164, Tyr166, TrpB106 and TyrB361 are the major interacting residues in both the complexes. The RMSD and RMSF analyses on the MD-simulated systems showed that the absence of FPP in the complex 3E37 has significant effect in the conformational changes of the ligands. During this conformational change, some interactions between the protein and the ligands are lost, but regained after some simulations (after 2 ns). The structure-based pharmacophore models showed that the hydrophobic and acceptor contours are predominantly present in the models. The pharmacophore models were validated using reference compounds, which significantly identified as HITs with smaller RMSD values. The developed structure-based pharmacophore models are significant, and the methodology used in this study is novel from the existing methods (the original X-ray crystallographic coordination of the ligands is used for the model building). In our study, along with the original coordination of the ligand, different conformers of the same complex (protein–ligand) are used. It concluded that the developed methodology is significant for the virtual screening of novel molecules on different targets.     

Dying is the Most Grown-Up Thing We Ever Do: But Do Health Care Professionals Prevent Us from Taking It Seriously?

This paper takes a somewhat slant perspective on flourishing and care in the context of suffering, death and dying, arguing that care in this context consists principally of ‘acts of work and courage that enable flourishing’. Starting with the perception that individuals, society and health care professionals have become dulled to death and the process of dying in Western advanced health systems, it suggests that for flourishing to occur, both of these aspects of life need to be faced more directly. The last days of life need to be ‘undulled’. Reflections upon the experiences of the author as carer and daughter in the face of her mother’s experience of death are used as basis for making suggestions about how care systems and professionals might better assist people in dealing with ‘the most grown up thing’ humans ever do, which is to die.