Development of the Multidimensional Readiness and Enablement Index for Health Technology (READHY) Tool to Measure Individuals' Health Technology Readiness:Initial Testing in a Cancer Rehabilitation Setting

BACKGROUND: The increasing digitization of health care services with enhanced access to fast internet connections, along with wide use of smartphones, offers the opportunity to get health advice or treatment remotely. For service providers, it is important to consider how consumers can take full advantage of available services and how this can create an enabling environment. However, it is important to consider the digital context and the attributes of current and future users, such as their readiness (ie, knowledge, skills, and attitudes, including trust and motivation). OBJECTIVE: The objective of this study was to evaluate how the eHealth Literacy Questionnaire (eHLQ) combined with selected dimensions from the Health Education Impact Questionnaire (heiQ) and the Health Literacy Questionnaire (HLQ) can be used together as an instrument to characterize an individual\u27s level of health technology readiness and explore how the generated data can be used to create health technology readiness profiles of potential users of health technologies and digital health services. METHODS: We administered the instrument and sociodemographic questions to a population of 305 patients with a recent cancer diagnosis referred to rehabilitation in a setting that plans to introduce various technologies to assist the individuals. We evaluated properties of the Readiness and Enablement Index for Health Technology (READHY) instrument using confirmatory factor analysis, convergent and discriminant validity analysis, and exploratory factor analysis. To identify different health technology readiness profiles in the population, we further analyzed the data using hierarchical and k-means cluster analysis. RESULTS: The confirmatory factor analysis found a suitable fit for the 13 factors with only 1 cross-loading of 1 item between 2 dimensions. The convergent and discriminant validity analysis revealed many factor correlations, suggesting that, in this population, a more parsimonious model might be achieved. Exploratory factor analysis pointed to 5 to 6 constructs based on aggregates of the existing dimensions. The results were not satisfactory, so we performed an 8-factor confirmatory factor analysis, resulting in a good fit with only 1 item cross-loading between 2 dimensions. Cluster analysis showed that data from the READHY instrument can be clustered to create meaningful health technology readiness profiles of users. CONCLUSIONS: The 13 dimensions from heiQ, HLQ, and eHLQ can be used in combination to describe a user\u27s health technology readiness level and degree of enablement. Further studies in other populations are needed to understand whether the associations between dimensions are consistent and the number of dimensions can be reduced

Comparison of vaccine-induced antibody neutralization against SARS-CoV-2 variants of concern following primary and booster doses of COVID-19 vaccines

The SARS-CoV-2 pandemic has, as of July 2022, infected more than 550 million people and caused over 6 million deaths across the world. COVID-19 vaccines were quickly developed to protect against severe disease, hospitalization and death. In the present study, we performed a direct comparative analysis of four COVID-19 vaccines: BNT162b2 (Pfizer/BioNTech), mRNA-1273 (Moderna), ChAdOx1 (Oxford/AstraZeneca) and Ad26.COV2.S (Johnson & Johnson/Janssen), following primary and booster vaccination. We focused on the vaccine-induced antibody-mediated immune response against multiple SARS-CoV-2 variants: wildtype, B.1.1.7 (Alpha), B.1.351 (Beta), B.1.617.2 (Delta) and B.1.1.529 (Omicron). The analysis included the quantification of total IgG levels against SARS-CoV-2 Spike, as well as the quantification of antibody neutralization titers. Furthermore, the study assessed the high-throughput ACE2 competition assay as a surrogate for the traditional pseudovirus neutralization assay. The results demonstrated marked differences in antibody-mediated immune responses. The lowest Spike-specific IgG levels and antibody neutralization titers were induced by one dose of the Ad26.COV2.S vaccine, intermediate levels by two doses of the BNT162b2 vaccine, and the highest levels by two doses of the mRNA-1273 vaccine or heterologous vaccination of one dose of the ChAdOx1 vaccine and a subsequent mRNA vaccine. The study also demonstrated that accumulation of SARS-CoV-2 Spike protein mutations was accompanied by a marked decline in antibody neutralization capacity, especially for B.1.1.529. Administration of a booster dose was shown to significantly increase Spike-specific IgG levels and antibody neutralization titers, erasing the differences between the vaccine-induced antibody-mediated immune response between the four vaccines. The findings of this study highlight the importance of booster vaccines and the potential inclusion of future heterologous vaccination strategies for broad protection against current and emerging SARS-CoV-2 variants

Solulin reduces infarct volume and regulates gene-expression in transient middle cerebral artery occlusion in rats

<p>Abstract</p> <p>Background</p> <p>Thrombolysis after acute ischemic stroke has only proven to be beneficial in a subset of patients. The soluble recombinant analogue of human thrombomodulin, Solulin, was studied in an <it>in vivo </it>rat model of acute ischemic stroke.</p> <p>Methods</p> <p>Male SD rats were subjected to 2 hrs of transient middle cerebral artery occlusion (tMCAO). Rats treated with Solulin intravenously shortly before reperfusion were compared to rats receiving normal saline i.v. with respect to infarct volumes, neurological deficits and mortality. Gene expression of IL-6, IL-1β, TNF-α, MMP-9, CD11B and GFAP were semiquantitatively analyzed by rtPCR of the penumbra.</p> <p>Results</p> <p>24 hrs after reperfusion, rats were neurologically tested, euthanized and infarct volumes determined. Solulin significantly reduced mean total (p = 0.001), cortical (p = 0.002), and basal ganglia (p = 0.036) infarct volumes. Hippocampal infarct volumes (p = 0.191) were not significantly affected. Solulin significantly downregulated the expression of IL-1β (79%; p < 0.001), TNF-α (59%; p = 0.001), IL-6 (47%; p = 0.04), and CD11B (49%; p = 0.001) in the infarcted cortex compared to controls.</p> <p>Conclusions</p> <p>Solulin reduced mean total, cortical and basal ganglia infarct volumes and regulated a subset of cytokines and proteases after tMCAO suggesting the potency of this compound for therapeutic interventions.</p

FUS pathology defines the majority of tau- and TDP-43-negative frontotemporal lobar degeneration

Through an international consortium, we have collected 37 tau- and TAR DNA-binding protein 43 (TDP-43)-negative frontotemporal lobar degeneration (FTLD) cases, and present here the first comprehensive analysis of these cases in terms of neuropathology, genetics, demographics and clinical data. 92% (34/37) had fused in sarcoma (FUS) protein pathology, indicating that FTLD-FUS is an important FTLD subtype. This FTLD-FUS collection specifically focussed on aFTLD-U cases, one of three recently defined subtypes of FTLD-FUS. The aFTLD-U subtype of FTLD-FUS is characterised clinically by behavioural variant frontotemporal dementia (bvFTD) and has a particularly young age of onset with a mean of 41 years. Further, this subtype had a high prevalence of psychotic symptoms (36% of cases) and low prevalence of motor symptoms (3% of cases). We did not find FUS mutations in any aFTLD-U case. To date, the only subtype of cases reported to have ubiquitin-positive but tau-, TDP-43- and FUS-negative pathology, termed FTLD-UPS, is the result of charged multivesicular body protein 2B gene (CHMP2B) mutation. We identified three FTLD-UPS cases, which are negative for CHMP2B mutation, suggesting that the full complement of FTLD pathologies is yet to be elucidated

Epstein-Barr virus peptide presented by HLA-E is predominantly recognized by CD8(bright) cells in multiple sclerosis patients.

Multiple sclerosis (MS) is associated with Epstein-Barr virus (EBV) infection, but impaired immune suppression may be part of the disease pathogenesis. CD8(+) T cells that are restricted by HLA-E exert an important immunoregulatory mechanism. To explore how EBV might interfere with immune regulation, we examined the expression of HLA-E and the frequency of CD8(+) cells recognizing HLA-E, presenting either an EBV peptide from the BZLF1 protein or a signal sequence peptide from HLA-A2, in relapsing remitting (MS-RR), primary progressive (MS-PP) MS patients, and healthy controls (HC). Treatment with IFN-α or EBV increased HLA-E expression on CD4(+) cells. However, only MS-PP had increased expression of HLA-E on resting CD4(+) cells when compared with HC (p<0.005). CD8(+) cells were divided into CD8(bright) and CD8(dim) cells by flow cytometry analyses. MS-RR had significantly fewer CD8(dim) cells than HC (p<0.003). Flow cytometry analyses were performed with HLA-E tetramers folded in the presence of the EBV or HLA-A2 peptide to identify HLA-E-interacting cells. MS-RR had increased frequency of CD8(bright) cells recognizing HLA-E/A2 (p=0.006) and HLA-E/BZLF1 (p=0.016). Conversely, MS-RR had fewer CD8(dim) cells that recognized HLA-E/BZLF1 (p=0.001), but this could be attributed to the overall lower number of CD8(dim) cells in MS-RR. Whereas HLA-E/A2 was predominantly recognized by CD8(dim) cells, HLA-E/BZLF1 was predominantly recognized by CD8(bright) cells in MS-RR and MS-PP, but not in HC. As expected, HLA-E/A2 was also recognized by CD8-negative cells in a CD94-dependent manner, whereas HLA-E/BZLF1 was poorly recognized in all groups by CD8-negative cells. These data demonstrate that MS-RR patients have expanded their CD8(bright) cells recognizing HLA-E/BZLF1. Moreover, HLA-E/BZLF1 appears to be recognized by the immune system in a different manner than HLA-E/A2

The impact of smoking on inhaled insulin.

OBJECTIVE—This study, one of the first to address issues of pulmonary insulin delivery in smokers, compared pharmacokinetics of inhaled insulin delivered via the AERx insulin Diabetes Management System (iDMS) in nondiabetic cigarette smokers and nonsmokers. RESEARCH DESIGN AND METHODS—In this randomized two-period crossover efficacy and safety trial in 27 nondiabetic smokers and 16 nonsmokers (18 men/25 women, mean age 28 years, mean BMI 23.0 kg/m2), subjects received single doses of inhaled insulin (33.8 IU) following overnight fasting on consecutive dosing days. On one dosing day, smokers smoked three cigarettes immediately before insulin administration (“acute smoking”); on the other dosing day, smokers had not smoked since midnight (“nonacute smoking”). After inhalation, 6-h serum insulin and serum glucose profiles were determined. RESULTS—Pharmacokinetic results for evaluable subjects were derived from serum insulin profiles. The amount of insulin absorbed during the first 6 h after dosing (area under the exogenous serum insulin curve from 0 to 6 h [AUC(0–6 h)]) was significantly greater in smokers (63.2 vs. 40.0 mU · l−1 · h−1, P = 0.0017); peak concentration was both higher and earlier in the smokers (maximal serum concentration of insulin [Cmax] 42.0 vs. 13.9 mU/l, P < 0.0001; time to maximal serum concentration of insulin [tmax] 31.5 vs. 53.9 min, P = 0.0003). The estimated intrasubject variability of AUC(0–6 h) was 13.7 and 16.5% for nonsmokers and smokers, respectively. No safety issues arose. CONCLUSIONS—Absorption of inhaled insulin via the AERx iDMS was significantly greater in smokers, with a higher AUC(0–6 h) and Cmax and a shorter tmax. Intrasubject variability of AUC(0–6 h) was low and similar in nonsmokers and smokers. These data prompt more extensive investigation of inhaled insulin in diabetic smokers