Quality of life among caregivers of people with end-stage kidney disease managed with dialysis or comprehensive conservative care

BACKGROUND: To measure health-related and care-related quality of life among informal caregivers of older people with end-stage kidney disease (ESKD), and to determine the association between caregiver quality of life and care recipient's treatment type. METHODS: A prospective cross-sectional study was conducted. Three renal units in the UK and Australia were included. Informal caregivers of people aged ≥75 years with ESKD managed with dialysis or comprehensive conservative non-dialytic care (estimated glomerular filtration (eGFR) ≤10 mL/min/1.73m2) participated. Health-related quality of life (HRQoL) was assessed using Short-Form six dimensions (SF-6D, 0-1 scale) and care-related quality of life was assessed using the Carer Experience Scale (CES, 0-100 scale). Linear regression assessed associations between care-recipient treatment type, caregiver characteristics and the SF-6D utility index and CES scores. RESULTS: Of 63 caregivers, 49 (78%) were from Australia, 26 (41%) cared for an older person managed with dialysis, and 37 (59%) cared for an older person managed with comprehensive conservative care. Overall, 73% were females, and the median age of the entire cohort was 76 years [IQR 68-81]. When adjusted for caregiver sociodemographic characteristics, caregivers reported significantly worse carer experience (CES score 15.73, 95% CI 5.78 to 25.68) for those managing an older person on dialysis compared with conservative care. However, no significant difference observed for carer HRQoL (SF-6D utility index - 0.08, 95% CI - 0.18 to 0.01) for those managing an older person on dialysis compared with conservative care. CONCLUSIONS: Our data suggest informal caregivers of older people on dialysis have significantly worse care-related quality of life (and therefore greater need for support) than those managed with comprehensive conservative care. It is important to consider the impact on caregivers' quality of life when considering treatment choices for their care recipients

Linking chondrocyte and synovial transcriptional profile to clinical phenotype in osteoarthritis.

OBJECTIVES: To determine how gene expression profiles in osteoarthritis joint tissues relate to patient phenotypes and whether molecular subtypes can be reproducibly captured by a molecular classification algorithm. METHODS: We analysed RNA sequencing data from cartilage and synovium in 113 osteoarthritis patients, applying unsupervised clustering and Multi-Omics Factor Analysis to characterise transcriptional profiles. We tested the association of the molecularly defined patient subgroups with clinical characteristics from electronic health records. RESULTS: We detected two patient subgroups in low-grade cartilage (showing no/minimal degeneration, cartilage normal/softening only), with differences associated with inflammation, extracellular matrix-related and cell adhesion pathways. The high-inflammation subgroup was associated with female sex (OR 4.12, p=0.0024) and prescription of proton pump inhibitors (OR 4.21, p=0.0040). We identified two independent patient subgroupings in osteoarthritis synovium: one related to inflammation and the other to extracellular matrix and cell adhesion processes. A seven-gene classifier including MMP13, APOD, MMP2, MMP1, CYTL1, IL6 and C15orf48 recapitulated the main axis of molecular heterogeneity in low-grade knee osteoarthritis cartilage (correlation ρ=-0.88, p<10-10) and was reproducible in an independent patient cohort (ρ=-0.85, p<10-10). CONCLUSIONS: These data support the reproducible stratification of osteoarthritis patients by molecular subtype and the exploration of new avenues for tailored treatments

High Altitude Student Platform

Our project focuses on the testing of critical components of the next phase of a high altitude robotic puppet that will be used on Near Space balloon missions to engage younger students (K-6). The prototype robotic puppet has been under the development at the University of Bridgeport (UB) supported by a Connecticut Space Grant College Consortium (CSGCC)

High Altitude Thermal Control

On September 1, 2016, a high altitude student platform (HASP) was launched from NASA’s Columbia Scientific Balloon Facility in Fort Sumner, New Mexico with 12 student payloads. The University of Bridgeport sent a robotic arm with three servo-motors and servo-motor testbed to the fringes of space. The objective was to test the motors at very low temperatures and in vacuum conditions. The payload has heaters and temperature sensors fitted on all its walls that can automatically respond to the thermal conditions to assure that the motors operate

Development of Non-Natural Flavanones as Antimicrobial Agents

With growing concerns over multidrug resistance microorganisms, particularly strains of bacteria and fungi, evolving to become resistant to the antimicrobial agents used against them, the identification of new molecular targets becomes paramount for novel treatment options. Recently, the use of new treatments containing multiple active ingredients has been shown to increase the effectiveness of existing molecules for some infections, often with these added compounds enabling the transport of a toxic molecule into the infecting species. Flavonoids are among the most abundant plant secondary metabolites and have been shown to have natural abilities as microbial deterrents and anti-infection agents in plants. Combining these ideas we first sought to investigate the potency of natural flavonoids in the presence of efflux pump inhibitors to limit Escherichia coli growth. Then we used the natural flavonoid scaffold to synthesize non-natural flavanone molecules and further evaluate their antimicrobial efficacy on Escherichia coli, Bacillus subtilis and the fungal pathogens Cryptococcus neoformans and Aspergillus fumigatus. Of those screened, we identified the synthetic molecule 4-chloro-flavanone as the most potent antimicrobial compound with a MIC value of 70 µg/mL in E. coli when combined with the inhibitor Phe-Arg-ß-naphthylamide, and MICs of 30 µg/mL in S. cerevesiae and 30 µg/mL in C. neoformans when used alone. Through this study we have demonstrated that combinatorial synthesis of non-natural flavonones can identify novel antimicrobial agents with activity against bacteria and fungi but with minimal toxicity to human cells

A molecular quantitative trait locus map for osteoarthritis

Funder: Medical Research Council Centre for Integrated Research into Musculoskeletal Ageing grant (148985)Funder: Versus Arthritis; Tissue Engineering and Regenerative Therapies Centre (21156)Abstract: Osteoarthritis causes pain and functional disability for over 500 million people worldwide. To develop disease-stratifying tools and modifying therapies, we need a better understanding of the molecular basis of the disease in relevant tissue and cell types. Here, we study primary cartilage and synovium from 115 patients with osteoarthritis to construct a deep molecular signature map of the disease. By integrating genetics with transcriptomics and proteomics, we discover molecular trait loci in each tissue type and omics level, identify likely effector genes for osteoarthritis-associated genetic signals and highlight high-value targets for drug development and repurposing. These findings provide insights into disease aetiopathology, and offer translational opportunities in response to the global clinical challenge of osteoarthritis

A molecular quantitative trait locus map for osteoarthritis

Funder: Medical Research Council Centre for Integrated Research into Musculoskeletal Ageing grant (148985)Funder: Versus Arthritis; Tissue Engineering and Regenerative Therapies Centre (21156)Abstract: Osteoarthritis causes pain and functional disability for over 500 million people worldwide. To develop disease-stratifying tools and modifying therapies, we need a better understanding of the molecular basis of the disease in relevant tissue and cell types. Here, we study primary cartilage and synovium from 115 patients with osteoarthritis to construct a deep molecular signature map of the disease. By integrating genetics with transcriptomics and proteomics, we discover molecular trait loci in each tissue type and omics level, identify likely effector genes for osteoarthritis-associated genetic signals and highlight high-value targets for drug development and repurposing. These findings provide insights into disease aetiopathology, and offer translational opportunities in response to the global clinical challenge of osteoarthritis

A molecular quantitative trait locus map for osteoarthritis

Funder: Medical Research Council Centre for Integrated Research into Musculoskeletal Ageing grant (148985)Funder: Versus Arthritis; Tissue Engineering and Regenerative Therapies Centre (21156)Abstract: Osteoarthritis causes pain and functional disability for over 500 million people worldwide. To develop disease-stratifying tools and modifying therapies, we need a better understanding of the molecular basis of the disease in relevant tissue and cell types. Here, we study primary cartilage and synovium from 115 patients with osteoarthritis to construct a deep molecular signature map of the disease. By integrating genetics with transcriptomics and proteomics, we discover molecular trait loci in each tissue type and omics level, identify likely effector genes for osteoarthritis-associated genetic signals and highlight high-value targets for drug development and repurposing. These findings provide insights into disease aetiopathology, and offer translational opportunities in response to the global clinical challenge of osteoarthritis

Integration of copy number and transcriptomics provides risk stratification in prostate cancer : a discovery and validation cohort study

Study data are deposited in NCBI GEO (unique identifier number GSE70770).Background : Understanding the heterogeneous genotypes and phenotypes of prostate cancer is fundamental to improving the way we treat this disease. As yet, there are no validated descriptions of prostate cancer subgroups derived from integrated genomics linked with clinical outcome. Methods : In a study of 482 tumour, benign and germline samples from 259 men with primary prostate cancer, we used integrative analysis of copy number alterations (CNA) and array transcriptomics to identify genomic loci that affect expression levels of mRNA in an expression quantitative trait loci (eQTL) approach, to stratify patients into subgroups that we then associated with future clinical behaviour, and compared with either CNA or transcriptomics alone. Findings : We identified five separate patient subgroups with distinct genomic alterations and expression profiles based on 100 discriminating genes in our separate discovery and validation sets of 125 and 103 men. These subgroups were able to consistently predict biochemical relapse (p = 0.0017 and p = 0.016 respectively) and were further validated in a third cohort with long-term follow-up (p = 0.027). We show the relative contributions of gene expression and copy number data on phenotype, and demonstrate the improved power gained from integrative analyses. We confirm alterations in six genes previously associated with prostate cancer ( MAP3K7, MELK, RCBTB2, ELAC2, TPD52, ZBTB4), and also identify 94 genes not previously linked to prostate cancer progression that would not have been detected using either transcript or copy number data alone. We confirm a number of previously published molecular changes associated with high risk disease, including MYC amplification, and NKX3-1, RB1 and PTEN deletions, as well as over-expression of PCA3 and AMACR, and loss of MSMB in tumour tissue. A subset of the 100 genes outperforms established clinical predictors of poor prognosis (PSA, Gleason score), as well as previously published gene signatures (p = 0.0001). We further show how our molecular profiles can be used for the early detection of aggressive cases in a clinical setting, and inform treatment decisions. Interpretation : For the first time in prostate cancer this study demonstrates the importance of integrated genomic analyses incorporating both benign and tumour tissue data in identifying molecular alterations leading to the generation of robust gene sets that are predictive of clinical outcome in independent patient cohorts.Publisher PDFPeer reviewe