Effectiveness of cognitive rehabilitation for people with multiple sclerosis: a meta-synthesis of patient perspectives

While previous randomised controlled trials and meta-analyses offer only limited evidence for the effectiveness of cognitive rehabilitation, qualitative studies examining patient perspectives report more positive outcomes. This meta-synthesis of qualitative studies examined patient perspectives of cognitive rehabilitation for memory, attention, and executive function problems in people with multiple sclerosis. Using set eligibility criteria, we screened electronic databases, reference lists, and academic networks for relevant papers. Seven papers (195 participants) were selected. Two independent researchers conducted quality appraisals of papers. Data analysis, guided by the thematic synthesis approach, yielded six main themes. These suggested that patients benefitted from the group environment in rehabilitation. Cognitive rehabilitation facilitated the participants’ reflection and awareness of their cognitive deficits, and was associated with increased knowledge and understanding of their illness. Increased strategy use was reported and associated with improvements in cognitive functioning and greater confidence and perseverance. Participants reported emotional and social improvements, and felt more optimistic. Overall, these changes had a positive impact on participants’ quality of life. This synthesis of qualitative studies indicates that people with multiple sclerosis who experience cognitive deficits benefit from cognitive rehabilitation programmes. This finding must, however, be viewed in light of the limitations of this meta-synthesis. The meta-synthesis was registered in the PROSPERO database under CRD42017040148.     

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.     

Neutrophils Play an Important Role in Protective Immunity against Coxiella burnetii Infection

Coxiella burnetii is an obligate intracellular Gram-negative bacterium that causes the zoonotic disease Q fever. Although Q fever is mainly transmitted by aerosol infection, study of the immune responses in the lung following pulmonary C. burnetii infection is lacking. Neutrophils are considered the first immune cell to migrate into the lung and play an important role in host defense against aerosol infection with microbial pathogens. However, the role of neutrophils in the host defense against C. burnetii infection remains unclear. To determine the role of neutrophils in protective immunity against C. burnetii infection, the RB6-8C5 antibody was used to deplete neutrophils in mice before intranasal infection with C. burnetii. The results indicated that neutrophil-depleted mice developed more severe disease than their wild-type counterparts, suggesting that neutrophils play an important role in host defense against C. burnetii pulmonary infection. We also found that neither CXC chemokine receptor 2 (CXCR2) nor interleukin-17 (IL-17) receptor (IL-17R) deficiency changed the severity of disease following intranasal C. burnetii challenge, suggesting that keratinocyte-derived chemokine and IL-17 may not play essential roles in the response to C. burnetii infection. However, significantly higher C. burnetii genome copy numbers were detected in the lungs of IL-1R^−/− mice at 14 days postinfection. This indicates that IL-1 may be important for the clearance of C. burnetii from the lungs following intranasal infection. Our results also suggest that neutrophils are involved in protecting vaccinated mice from C. burnetii challenge-induced disease. This is the first study to demonstrate an important role for neutrophils in protective immunity against C. burnetii infection.     

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).