110 research outputs found
Caregiver depression in families living with autism spectrum disorder: A meta-analysis based on ecological systems theory
This item is only available electronically.Background: Depressive symptoms in family caregivers of persons with autism spectrum disorder are highly prevalent, however the impact of family and social support systems on caregivers’ mental health outcomes is unclear. Aim: To review and map correlates of caregivers’ depressive symptoms using an ecological systems framework. Methods: Thirty-four studies, comprising a pooled sample of 4,968 caregivers, were identified from the Embase, PsycINFO and PubMed databases. Study reporting quality was assessed using the QualSyst tool. Pearsons r, along with fail-safe Ns and heterogeneity, were calculated using random effects modelling. The moderating effect of informal support (perceived, received, network characteristics) was examined. Results: Studies provided good to excellent methodological detail. Weak-to-moderate associations (rw range = -.199 to -.406) were noted between lowered depressive symptoms with positive family unit functioning, relationship quality (marital and parent-child), and informal support (from partners, family, friends). These results were not moderated by the operationalisation of informal support. Conclusions: Clinicians should assess the social and family networks of caregivers to identify those most vulnerable to developing depression. Intervention effectiveness can be enhanced by involving relevant family members in treatment.Thesis (B.PsychSc(Hons)) -- University of Adelaide, School of Psychology, 201
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SARS-CoV-2 Receptor ACE2 Is an Interferon-Stimulated Gene in Human Airway Epithelial Cells and Is Detected in Specific Cell Subsets across Tissues.
There is pressing urgency to understand the pathogenesis of the severe acute respiratory syndrome coronavirus clade 2 (SARS-CoV-2), which causes the disease COVID-19. SARS-CoV-2 spike (S) protein binds angiotensin-converting enzyme 2 (ACE2), and in concert with host proteases, principally transmembrane serine protease 2 (TMPRSS2), promotes cellular entry. The cell subsets targeted by SARS-CoV-2 in host tissues and the factors that regulate ACE2 expression remain unknown. Here, we leverage human, non-human primate, and mouse single-cell RNA-sequencing (scRNA-seq) datasets across health and disease to uncover putative targets of SARS-CoV-2 among tissue-resident cell subsets. We identify ACE2 and TMPRSS2 co-expressing cells within lung type II pneumocytes, ileal absorptive enterocytes, and nasal goblet secretory cells. Strikingly, we discovered that ACE2 is a human interferon-stimulated gene (ISG) in vitro using airway epithelial cells and extend our findings to in vivo viral infections. Our data suggest that SARS-CoV-2 could exploit species-specific interferon-driven upregulation of ACE2, a tissue-protective mediator during lung injury, to enhance infection
Urinary metabolomic signature of esophageal cancer and Barrett’s esophagus
<p>Abstract</p> <p>Background</p> <p>Esophageal adenocarcinoma (EAC) often presents at a late, incurable stage, and mortality has increased substantially, due to an increase in incidence of EAC arising out of Barrett’s esophagus. When diagnosed early, however, the combination of surgery and adjuvant therapies is associated with high cure rates. Metabolomics provides a means for non- invasive screening of early tumor-associated perturbations in cellular metabolism.</p> <p>Methods</p> <p>Urine samples from patients with esophageal carcinoma (n = 44), Barrett’s esophagus (n = 31), and healthy controls (n = 75) were examined using <sup>1</sup>H-NMR spectroscopy. Targeted profiling of spectra using Chenomx software permitted quantification of 66 distinct metabolites. Unsupervised (principal component analysis) and supervised (orthogonal partial least-squares discriminant analysis OPLS-DA) multivariate pattern recognition techniques were applied to discriminate between samples using SIMCA-P<sup>+</sup> software. Model specificity was also confirmed through comparison with a pancreatic cancer cohort (n = 32).</p> <p>Results</p> <p>Clear distinctions between esophageal cancer, Barrett’s esophagus and healthy controls were noted when OPLS-DA was applied. Model validity was confirmed using two established methods of internal validation, cross-validation and response permutation. Sensitivity and specificity of the multivariate OPLS-DA models were summarized using a receiver operating characteristic curve analysis and revealed excellent predictive power (area under the curve = 0.9810 and 0.9627 for esophageal cancer and Barrett’s esophagus, respectively). The metabolite expression profiles of esophageal cancer and pancreatic cancer were also clearly distinguishable with an area under the receiver operating characteristics curve (AUROC) = 0.8954.</p> <p>Conclusions</p> <p>Urinary metabolomics identified discrete metabolic signatures that clearly distinguished both Barrett’s esophagus and esophageal cancer from controls. The metabolite expression profile of esophageal cancer was also discrete from its precursor lesion, Barrett’s esophagus. The cancer-specific nature of this profile was confirmed through comparison with pancreatic cancer. These preliminary results suggest that urinary metabolomics may have a future potential role in non-invasive screening in these conditions.</p
Establishing a Core Outcome Measure for Fatigue in Patients on Hemodialysis: A Standardized Outcomes in Nephrology–Hemodialysis (SONG-HD) Consensus Workshop Report
Fatigue is one of the most highly prioritized outcomes for patients and clinicians, but remains infrequently and inconsistently reported across trials in hemodialysis. We convened an international Standardized Outcomes in Nephrology–Hemodialysis (SONG-HD) consensus workshop with stakeholders to discuss the development and implementation of a core outcome measure for fatigue. 15 patients/caregivers and 42 health professionals (clinicians, researchers, policy makers, and industry representatives) from 9 countries participated in breakout discussions. Transcripts were analyzed thematically. 4 themes for a core outcome measure emerged. Drawing attention to a distinct and all-encompassing symptom was explicitly recognizing fatigue as a multifaceted symptom unique to hemodialysis. Emphasizing the pervasive impact of fatigue on life participation justified the focus on how fatigue severely impaired the patient’s ability to do usual activities. Ensuring relevance and accuracy in measuring fatigue would facilitate shared decision making about treatment. Minimizing burden of administration meant avoiding the cognitive burden, additional time, and resources required to use the measure. A core outcome measure that is simple, is short, and includes a focus on the severity of the impact of fatigue on life participation may facilitate consistent and meaningful measurement of fatigue in all trials to inform decision making and care of patients receiving hemodialysis
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