4,408 research outputs found
Social Reproduction and Covid-19
As Covid-19 rips across the world we are collectively asked to examine the structures of society to see what is working and what we can change. What can we learn from the roughly 6.9 million deaths (and counting) worldwide? How can we prevent something like this from happening again? This paper follows the course of Covid-19 from its birth in Wuhan, China, to the present day of mid-April 2023. By looking at the ways in which we have reacted to the pandemic, we are able to look forward and imagine new ways of tackling future pandemics and other pressing problems like climate change. Using social reproduction as a basis, we can think about how to center care and culture, rather than money and profit, to make our society more resilient to future emergencies
Predicting attitude towards performance enhancing substance use: A comprehensive test of the Sport Drug Control Model with elite Australian athletes
Objectives: This study presents a comprehensive examination of the Sport Drug Control Model via survey data of elite Australian athletes. Design: A cross-sectional nationwide mail survey. Methods: A mail survey of 1237 elite Australian athletes was conducted. Structural equation modelling was employed to test the model. Results: Morality (personal moral stance on performance-enhancing substances use), reference group opinion (perceived moral stance of reference group on performance-enhancing substances use) and legitimacy (perceptions of the drug testing and appeals processes) evidenced significant relationships with attitude towards performance-enhancing substances use, which in turn was positively associated with doping behaviour. The model accounted for 81% and 13% of the variance in attitude towards performance-enhancing substances use and doping behaviour, respectively. Conclusions: These findings validate the usefulness of the Sport Drug Control Model for understanding influences on performance-enhancing substances use. Nevertheless, there is a need to survey athletes representing a broader range of competition levels and cross-cultural research to test the model’s applicability to other populations of athletes
Learning mixed graphical models with separate sparsity parameters and stability-based model selection
Background: Mixed graphical models (MGMs) are graphical models learned over a combination of continuous and discrete variables. Mixed variable types are common in biomedical datasets. MGMs consist of a parameterized joint probability density, which implies a network structure over these heterogeneous variables. The network structure reveals direct associations between the variables and the joint probability density allows one to ask arbitrary probabilistic questions on the data. This information can be used for feature selection, classification and other important tasks. Results: We studied the properties of MGM learning and applications of MGMs to high-dimensional data (biological and simulated). Our results show that MGMs reliably uncover the underlying graph structure, and when used for classification, their performance is comparable to popular discriminative methods (lasso regression and support vector machines). We also show that imposing separate sparsity penalties for edges connecting different types of variables significantly improves edge recovery performance. To choose these sparsity parameters, we propose a new efficient model selection method, named Stable Edge-specific Penalty Selection (StEPS). StEPS is an expansion of an earlier method, StARS, to mixed variable types. In terms of edge recovery, StEPS selected MGMs outperform those models selected using standard techniques, including AIC, BIC and cross-validation. In addition, we use a heuristic search that is linear in size of the sparsity value search space as opposed to the cubic grid search required by other model selection methods. We applied our method to clinical and mRNA expression data from the Lung Genomics Research Consortium (LGRC) and the learned MGM correctly recovered connections between the diagnosis of obstructive or interstitial lung disease, two diagnostic breathing tests, and cigarette smoking history. Our model also suggested biologically relevant mRNA markers that are linked to these three clinical variables. Conclusions: MGMs are able to accurately recover dependencies between sets of continuous and discrete variables in both simulated and biomedical datasets. Separation of sparsity penalties by edge type is essential for accurate network edge recovery. Furthermore, our stability based method for model selection determines sparsity parameters faster and more accurately (in terms of edge recovery) than other model selection methods. With the ongoing availability of comprehensive clinical and biomedical datasets, MGMs are expected to become a valuable tool for investigating disease mechanisms and answering an array of critical healthcare questions
Hypoalbuminaemia predicts outcome in adult patients with congenital heart disease
Background In patients with acquired heart failure, hypoalbuminaemia is associated with increased risk of death. The prevalence of hypoproteinaemia and hypoalbuminaemia and their relation to outcome in adult patients with congenital heart disease (ACHD) remains, however, unknown. Methods Data on patients with ACHD who underwent blood testing in our centre within the last 14 years were collected. The relation between laboratory, clinical or demographic parameters at baseline and mortality was assessed using Cox proportional hazards regression analysis. Results A total of 2886 patients with ACHD were included. Mean age was 33.3 years (23.6–44.7) and 50.1% patients were men. Median plasma albumin concentration was 41.0 g/L (38.0–44.0), whereas hypoalbuminaemia (<35 g/L) was present in 13.9% of patients. The prevalence of hypoalbuminaemia was significantly higher in patients with great complexity ACHD (18.2%) compared with patients with moderate (11.3%) or simple ACHD lesions (12.1%, p<0.001). During a median follow-up of 5.7 years (3.3–9.6), 327 (11.3%) patients died. On univariable Cox regression analysis, hypoalbuminaemia was a strong predictor of outcome (HR 3.37, 95% CI 2.67 to 4.25, p<0.0001). On multivariable Cox regression, after adjusting for age, sodium and creatinine concentration, liver dysfunction, functional class and disease complexity, hypoalbuminaemia remained a significant predictor of death. Conclusions Hypoalbuminaemia is common in patients with ACHD and is associated with a threefold increased risk of risk of death. Hypoalbuminaemia, therefore, should be included in risk-stratification algorithms as it may assist management decisions and timing of interventions in the growing ACHD population
The impact of a pharmacist on post-take ward round prescribing and medication appropriateness
Background Medication communication and prescribing on the post-take ward round following patient admission to hospital can be suboptimal leading to worse patient outcomes. Objective To evaluate the impact of clinical pharmacist participation on the post-take ward round on the appropriateness of medication prescribing, medication communication, and overall patient health care outcomes. Setting Tertiary referral teaching hospital, Brisbane, Australia. Method A pre-post intervention study was undertaken that compared the addition of a senior clinical pharmacist attending the post-take ward was compared to usual wardbase pharmacist service, with no pharmacist present of the post-take ward round. We assessed the proportion of patients with an improvement in medication appropriateness from admission to discharge, using the START/STOPP checklists. Medication communication was assessed by the mean number of brief and in-depth discussions, with health care outcomes measured by comparing length of stay and 28-day readmission rates. Main outcome measures: Medication appropriateness according to the START/STOPP list, number and type of discussions with team members and length of stay and readmission rate. Results Two hundred and sixty patients were recruited (130 pre- and 130-post-intervention), across 23 and 20 post-take ward rounds, respectively. Post-intervention, there was increase in the proportion of patients who had an improvement medication appropriateness (pre-intervention 25.4%, post-intervention 36.9%; p = 0.004), the number of in-depth discussions about patients’ medication (1.9 ± 1.7 per patient pre-intervention, 2.7 ± 1.7 per patient post-, p < 0.001), and the number relating to high-risk medications (0.71 ± 1.1 per patient pre-intervention, to 1.2 ± 1.2 per patient post-, p < 0.05). Length of stay and 28-day mortality were unchanged. Conclusion Clinical pharmacist participation on the post-take ward round leads to improved medication-related communication and improved medication appropriateness but did not significantly improve health care outcomes
Evaluasi Kinerja Bangunan Berlubang Dengan Metode Direct Displacement-based Design
Banyak penelitian mengenai kinerja Direct Displacement Based Design (DDBD) dan Force Based Design (FBD) telah dilakukan sebelumnya. Penelitian-penelitian sebelumnya menunjukkan bahwa DDBD menghasilkan performa struktur yang lebih mendekati target desain. Namun, penelitian terhadap bangunan berlubang belum pernah dilakukan sebelumnya. Konfigurasi struktur dengan void memiliki kekakuan portal yang bervariasi diaman hal ini mempengaruhi distribusi gaya pada setiap portal. Distribusi gaya pada bagian yang memiliki void akan mengalami perpindahan yang lebih besar daripada bagian yang tidak memiliki void khususnya jika pelat lantai diasumsikan semi rigid. Penelitian ini membandingkan kinerja FBD dan DDBD pada bangunan yang didesain berlubang atau memiliki void dengan asumsi desain bangunan tanpa lubang dan gaya geser dasar didistribusikan secara merata. Penelitian akan dievaluasi terhadap wilayah beresiko gempa tinggi dan rendah di Indonesia. Struktur yang didesain diuji dengan analisis non-linear dinamis time history. Hasil dari penelitian ini menunjukkan bahwa struktur bangunan yang didesain dengan DDBD memberikan kinerja yang lebih baik daripada FBD baik dalam drift ratio ataupun failure mechanism. Selain itu, prosedur DDBD lebih efektif dan efisien karena hasil desain mendekati target desain dan durasi desain sangat singkat. Satu-satunya kelemahan dari DDBD adalah biaya yang lebih mahal karena hasil desain yang menggunakan lebih banyak materia
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Structurally-related (−)-epicatechin metabolites in humans: assessment using de novo chemically synthesized authentic standards
Accumulating data suggest that diets rich in flavanols and procyanidins are beneficial for human health. In this context, there has been a great interest in elucidating the systemic levels and metabolic profiles at which these compounds occur in humans. While recent progress has been made, there still exist considerable differences and various disagreements with regard to the mammalian metabolites of these compounds, which in turn is largely a consequence of the lack of availability of authentic standards that would allow for the directed development and validation of expedient analytical methodologies. In the present study, we developed a method for the analysis of structurally-related flavanol metabolites using a wide range of authentic standards. Applying this method in the context of a human dietary intervention study using comprehensively characterized and standardized flavanol- and procyanidin-containing cocoa, we were able to identify the structurally-related (−)-epicatechin metabolites (SREM) postprandially extant in the systemic circulation of humans. Our results demonstrate that (−)-epicatechin-3′-β-D-glucuronide, (−)-epicatechin-3′-sulfate, and a 3′-O-methyl(−)-epicatechin-5/7-sulfate are the predominant SREM in humans, and further confirm the relevance of the stereochemical configuration in the context of flavanol metabolism. In addition, we also identified plausible causes for the previously reported discrepancies regarding flavanol metabolism, consisting to a significant extent of inter-laboratory differences in sample preparation (enzymatic treatment and sample conditioning for HPLC analysis) and detection systems. Thus, these findings may also aid in the establishment of consensus on this topic
Glycated hemoglobin measurements at three, 12 and 24 months postpartum after gestational diabetes
Purpose: To determine the associations between glycated hemoglobin (A1C) values at three, 12 and 24 months postpartum taken during the Families Defeating Diabetes trial. Methods: The Families Defeating Diabetes trial was a randomized 12 month lifestyle intervention delivered in the first year postpartum. Women were reviewed at three, 6 12 and 24 months for body habitus, diet and lifestyle choices. Glycated hemoglobin levels were measured at three, 12 and 24 months. Results: There were 170 randomization participants: 89 interventional (INT); and 81 control (CON). Of these 170 participants, 50 INT and 47 CON completed 12-month follow-up and 26 INT and 24 CON completed 24-month follow-up. Study outcomes did not differ between the cohorts. Combined intraclass correlation coefficients for reliability of repeated results showed substantial reliability: 0.74 (95% CI 0.63, 0.83) between three and 12 month A1C; and 0.72 (95% CI 0.51, 0.85) for three and 24 month A1C. Pearson correlations for three month vs 12 month A1C were r=0.745 (p\u3c0.001) and three month vs 24 month A1C were r=0.718 (p=0.001) Conclusions: The A1C values at three, 12 and 24 months after gestational diabetes mellitus showed substantial reliability by intraclass correlation coefficients analysis as well as significant Pearson correlations. These findings add perspective to timing and use of A1C to document postpartum glucose tolerance for women with recent gestational diabetes mellitus. These findings suggest a role for postpartum A1C testing; however, a longitudinal comparison with OGTT results is required to confirm clinical validity
Germline DNA Repair Gene Mutations in Young-onset Prostate Cancer Cases in the UK: Evidence for a More Extensive Genetic Panel
Background
Rare germline mutations in DNA repair genes are associated with prostate cancer (PCa) predisposition and prognosis.
Objective
To quantify the frequency of germline DNA repair gene mutations in UK PCa cases and controls, in order to more comprehensively evaluate the contribution of individual genes to overall PCa risk and likelihood of aggressive disease.
Design, setting, and participants
We sequenced 167 DNA repair and eight PCa candidate genes in a UK-based cohort of 1281 young-onset PCa cases (diagnosed at ≤60 yr) and 1160 selected controls.
Outcome measurements and statistical analysis
Gene-level SKAT-O and gene-set adaptive combination of p values (ADA) analyses were performed separately for cases versus controls, and aggressive (Gleason score ≥8, n = 201) versus nonaggressive (Gleason score ≤7, n = 1048) cases.
Results and limitations
We identified 233 unique protein truncating variants (PTVs) with minor allele frequency <0.5% in controls in 97 genes. The total proportion of PTV carriers was higher in cases than in controls (15% vs 12%, odds ratio [OR] = 1.29, 95% confidence interval [CI] 1.01–1.64, p = 0.036). Gene-level analyses selected NBN (pSKAT-O = 2.4 × 10−4) for overall risk and XPC (pSKAT-O = 1.6 × 10−4) for aggressive disease, both at candidate-level significance (p < 3.1 × 10−4 and p < 3.4 × 10−4, respectively). Gene-set analysis identified a subset of 20 genes associated with increased PCa risk (OR = 3.2, 95% CI 2.1–4.8, pADA = 4.1 × 10−3) and four genes that increased risk of aggressive disease (OR = 11.2, 95% CI 4.6–27.7, pADA = 5.6 × 10−3), three of which overlap the predisposition gene set.
Conclusions
The union of the gene-level and gene-set-level analyses identified 23 unique DNA repair genes associated with PCa predisposition or risk of aggressive disease. These findings will help facilitate the development of a PCa-specific sequencing panel with both predictive and prognostic potential.
Patient summary
This large sequencing study assessed the rate of inherited DNA repair gene mutations between prostate cancer patients and disease-free men. A panel of 23 genes was identified, which may improve risk prediction or treatment pathways in future clinical practice
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