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A role for the cortex in sleep–wake regulation
No full textCortical and subcortical circuitry are thought to play distinct roles in the generation of sleep oscillations and global state control, respectively. Here we silenced a subset of neocortical layer 5 pyramidal and archicortical dentate gyrus granule cells in male mice by ablating SNAP25. This markedly increased wakefulness and reduced rebound of electroencephalographic slow-wave activity after sleep deprivation, suggesting a role for the cortex in both vigilance state control and sleep homeostasis
The interplay of stratal and vertical migration pathways in shallow hydrocarbon plumbing systems
No full textHydrocarbon plumbing systems have been extensively documented in the past two decades using high-resolution 3D seismic data, exploiting the ability of seismic imaging techniques to reveal the subsurface geometry of gas charged sediments. In this paper, we present a detailed study of a hydrocarbon plumbing system from the South China Sea, that involves both vertical and lateral (stratal) hydrocarbon migration in Miocene to Recent clastic sediments that comprise multilayer stacking of thinly layered clays, silts and sands. We show that a transtensive fault system that provides lateral seal for fault-dip traps of deep Miocene reservoirs, and offers a vertical pathway for migration to shallower silty units. These silty units in turn form a ‘spillway’ in a regional, northward migration path. This path involves filling each shallow fault-dip trap to spill point towards the fault tips, with stratal migration forced around the outer flanks of the fault-related folds. Successive fill-to-spill leads to a continuous trail of amplitude anomalies that merge into a continuous, larger, gas-charged anomaly pattern. The migrating gas finally accumulates within a zone bounded by a large boundary fault with full juxtaposition seal. The pattern of anomaly distribution suggests that the hydrocarbon migration has been active in the Late Pleistocene and is probably continuing at the present day. Hence this plumbing system may be one of very few examples described to date in which dynamic hydrocarbon migration pathways have been directly imaged by seismic data
Genomic evidence of SARS-CoV-2 reinfection case with the emerging B.1.2 variant in Brazil
No full textMS Greaves 6: Zij-i Jami by Muhammad Shah Khilji
No full textSelections photographed by Dr. Julia Bray for the project "Arabic Books and Astronomy in 17th C Oxford
What intensive care registries can teach us about outcomes
No full textPurpose of review
Critical care registries are synonymous with measurement of outcomes following critical illness. Their ability to provide longitudinal data to enable benchmarking of outcomes for comparison within units over time, and between units, both regionally and nationally is a key part of the evaluation of quality of care and ICU performance as well as a better understanding of case-mix. This review aims to summarize literature on outcome measures currently being reported in registries internationally, describe the current strengths and challenges with interpreting existing outcomes and highlight areas where registries may help improve implementation and interpretation of both existing and new outcome measures.
Recent findings
Outcomes being widely reported through ICU registries include measures of survival, events of interest, patient-reported outcomes and measures of resource utilization (including cost). Despite its increasing adoption, challenges with quality of reporting of outcomes measures remain. Measures of short-term survival are feasible but those requiring longer follow-ups are increasingly difficult to interpret given the evolving nature of critical care in the context of acute and chronic disease management. Furthermore, heterogeneity in patient populations and in healthcare organisations in different settings makes use of outcome measures for international benchmarking at best complex, requiring substantial advances in their definitions and implementation to support those seeking to improve patient care.
Summary
Digital registries could help overcome some of the current challenges with implementing and interpreting ICU outcome data through standardization of reporting and harmonization of data. In addition, ICU registries could be instrumental in enabling data for feedback as part of improvement in both patient-centred outcomes and in service outcomes; notably resource utilization and efficiency
Art, aesthetics and the dynamics of visuality in Ezekiel 23
No full textThis essay explores Ezekiel 23 as a text about art and aesthetics. As an aesthetic response to an artistic endeavour, it argues that the description of Oholibah’s act of viewing must be placed within the context of strategies for verbalizing visual phenomenon in biblical literature. And as a work of art, the carved Chaldean officers must be understood within larger ancient Near Eastern artistic conventions. The convergence of these distinct but related focuses allows us to reassess Oholibah’s act of viewing art and its role in Ezekiel 23
The impact of the COVID-19 lockdown on HIV care in 65 South African primary care clinics: an interrupted time series analysis
No full textBackground
The effect of the COVID-19 pandemic on HIV outcomes in low-income and middle-income countries is poorly described. We aimed to measure the impact of the 2020 national COVID-19 lockdown on HIV testing and treatment in KwaZulu-Natal, South Africa, where 1·7 million people are living with HIV.
Methods
In this interrupted time series analysis, we analysed anonymised programmatic data from 65 primary care clinics in KwaZulu-Natal province, South Africa. We included data from people testing for HIV, initiating antiretroviral therapy (ART), and collecting ART at participating clinics during the study period, with no age restrictions. We used descriptive statistics to summarise demographic and clinical data, and present crude summaries of the main outcomes of numbers of HIV tests per month, ART initiations per week, and ART collection visits per week, before and after the national lockdown that began on March 27, 2020. We used Poisson segmented regression models to estimate the immediate impact of the lockdown on these outcomes, as well as post-lockdown trends.
Findings
Between Jan 1, 2018, and July 31, 2020, we recorded 1 315 439 HIV tests. Between Jan 1, 2018, and June 15, 2020, we recorded 71 142 ART initiations and 2 319 992 ART collection visits. We recorded a median of 41 926 HIV tests per month before lockdown (January, 2018, to March, 2020; IQR 37 838–51 069) and a median of 38 911 HIV tests per month after lockdown (April, 2020, to July, 2020; IQR 32 699–42 756). In the Poisson regression model, taking into account long-term trends, lockdown was associated with an estimated 47·6% decrease in HIV testing in April, 2020 (incidence rate ratio [IRR] 0·524, 95% CI 0·446–0·615). ART initiations decreased from a median of 571 per week before lockdown (IQR 498–678), to 375 per week after lockdown (331–399), with an estimated 46·2% decrease in the Poisson regression model in the first week of lockdown (March 30, 2020, to April 5, 2020; IRR 0·538, 0·459–0·630). There was no marked change in the number of ART collection visits (median 18 519 visits per week before lockdown [IQR 17 074–19 922] vs 17 863 visits per week after lockdown [17 509–18 995]; estimated effect in the first week of lockdown IRR 0·932, 95% CI 0·794–1·093). As restrictions eased, HIV testing and ART initiations gradually improved towards pre-lockdown levels (slope change 1·183/month, 95% CI 1·113–1·256 for HIV testing; 1·156/month, 1·085–1·230 for ART initiations).
Interpretation
ART provision was generally maintained during the 2020 COVID-19 lockdown, but HIV testing and ART initiations were heavily impacted. Strategies to increase testing and treatment initiation should be implemented.
Funding
Wellcome Trust, Africa Oxford Initiative
Multivariate generalized linear mixed-effects models for the analysis of clinical trial–based cost-effectiveness data
No full textEconomic evaluations conducted alongside randomized controlled trials are a popular vehicle for generating high-quality evidence on the incremental cost-effectiveness of competing health care interventions. Typically, in these studies, resource use (and by extension, economic costs) and clinical (or preference-based health) outcomes data are collected prospectively for trial participants to estimate the joint distribution of incremental costs and incremental benefits associated with the intervention. In this article, we extend the generalized linear mixed-model framework to enable simultaneous modeling of multiple outcomes of mixed data types, such as those typically encountered in trial-based economic evaluations, taking into account correlation of outcomes due to repeated measurements on the same individual and other clustering effects. We provide new wrapper functions to estimate the models in Stata and R by maximum and restricted maximum quasi-likelihood and compare the performance of the new routines with alternative implementations across a range of statistical programming packages. Empirical applications using observed and simulated data from clinical trials suggest that the new methods produce broadly similar results as compared with Stata’s merlin and gsem commands and a Bayesian implementation in WinBUGS. We highlight that, although these empirical applications primarily focus on trial-based economic evaluations, the new methods presented can be generalized to other health economic investigations characterized by multivariate hierarchical data structures. </jats:p
A signal capture and proofreading mechanism for the KDEL-receptor explains selectivity and dynamic range in ER retrieval
No full textER proteins of widely differing abundance are retrieved from the Golgi by the KDEL-receptor. Abundant ER proteins tend to have KDEL rather than HDEL signals, whereas ADEL and DDEL are not used in most organisms. Here, we explore the mechanism of selective retrieval signal capture by the KDEL-receptor and how HDEL binds with ten-fold higher affinity than KDEL. Our results show the carboxyl-terminus of the retrieval signal moves along a ladder of arginine residues as it enters the binding pocket of the receptor. Gatekeeper residues D50 and E117 at the entrance of this pocket exclude ADEL and DDEL sequences. D50N/E117Q mutation of human KDEL-receptors changes the selectivity to ADEL and DDEL. However, further analysis of HDEL, KDEL and RDEL-bound receptor structures shows that affinity differences are explained by interactions between the variable -4 H/K/R position of the signal and W120, rather than D50 or E117. Together, these findings explain KDEL-receptor selectivity, and how signal variants increase dynamic range to support efficient ER retrieval of low and high abundance proteins
Discriminant knowledge extraction from electrocardiograms for automated diagnosis of myocardial infarction
No full textVisual inspection of electrocardiograms (ECGs) is a common clinical practice to diagnose heart diseases (HDs), which are still responsible for millions of deaths globally every year. In particular, myocardial infarction (MI) is the leading cause of mortality among HDs. ECGs reflect the electrical activity of the heart and provide a quicker process of diagnosis compared to laboratory blood tests. However, still it requires trained clinicians to interpret ECG waveforms, which poses a challenge in low-resourced healthcare systems, such as poor doctor-to-patient ratios. Previous works in this space have shown the use of data-driven approaches to predict HDs from ECG signals but focused on domain-specific features that are less generalizable across patient and device variations. Moreover, limited work has been conducted on the use of longitudinal information and fusion of multiple ECG leads. In contrast, we propose an end-to-end trainable solution for MI diagnosis, which (1) uses 12 ECG leads; (2) fuses the leads at data-level by stacking their spectrograms; (3) employs transfer learning to encode features rather than learning representations from scratch; and (4) uses a recurrent neural network to encode temporal dependency in long duration ECGs. Our approach is validated using multiple datasets, including tens of thousands of subjects, and encouraging performance is achieved