Impacts of energy efficiency retrofitting measures on indoor PM concentrations across different income groups in England: a modelling study

As part of an effort to reduce carbon emissions in the UK, policies encouraging the energy-efficient retrofit of domestic properties are being implemented. Typical retrofits, including installation of insulation and double glazing can cause tightening of the building envelope which may affect indoor air quality (IAQ) impacting occupant health. Using the example of PM (an airborne pollutant with known health impacts), this study considers the influence of energy-efficient retrofits on indoor PM concentrations in domestic properties both above and below the low-income threshold (LIT) for a range of tenancies across England. Simulations using EnergyPlus and its integrated Generic Contaminant model are employed to predict indoor PM exposures from both indoor and outdoor sources in building archetypes representative of (i) the existing housing stock and (ii) a retrofitted English housing stock. The exposures of occupants for buildings occupied by groups above and below the LIT are then estimated under current conditions and following retrofits. One-way ANOVA tests were applied to clarify results and investigate differences between the various income and tenure groups. Results indicate that all tenures below the LIT experience greater indoor PM concentrations than those above, suggesting possible social inequalities driven by housing, leading to consequences for health

A new view into prokaryotic cell biology from electron cryotomography

Electron cryotomography (ECT) enables intact cells to be visualized in 3D in an essentially native state to 'macromolecular' (~4 nm) resolution, revealing the basic architectures of complete nanomachines and their arrangements in situ. Since its inception, ECT has advanced our understanding of many aspects of prokaryotic cell biology, from morphogenesis to subcellular compartmentalization and from metabolism to complex interspecies interactions. In this Review, we highlight how ECT has provided structural and mechanistic insights into the physiology of bacteria and archaea and discuss prospects for the future

Systematic discovery of structural elements governing stability of mammalian messenger RNAs.

Decoding post-transcriptional regulatory programs in RNA is a critical step towards the larger goal of developing predictive dynamical models of cellular behaviour. Despite recent efforts, the vast landscape of RNA regulatory elements remains largely uncharacterized. A long-standing obstacle is the contribution of local RNA secondary structure to the definition of interaction partners in a variety of regulatory contexts, including--but not limited to--transcript stability, alternative splicing and localization. There are many documented instances where the presence of a structural regulatory element dictates alternative splicing patterns (for example, human cardiac troponin T) or affects other aspects of RNA biology. Thus, a full characterization of post-transcriptional regulatory programs requires capturing information provided by both local secondary structures and the underlying sequence. Here we present a computational framework based on context-free grammars and mutual information that systematically explores the immense space of small structural elements and reveals motifs that are significantly informative of genome-wide measurements of RNA behaviour. By applying this framework to genome-wide human mRNA stability data, we reveal eight highly significant elements with substantial structural information, for the strongest of which we show a major role in global mRNA regulation. Through biochemistry, mass spectrometry and in vivo binding studies, we identified human HNRPA2B1 (heterogeneous nuclear ribonucleoprotein A2/B1, also known as HNRNPA2B1) as the key regulator that binds this element and stabilizes a large number of its target genes. We created a global post-transcriptional regulatory map based on the identity of the discovered linear and structural cis-regulatory elements, their regulatory interactions and their target pathways. This approach could also be used to reveal the structural elements that modulate other aspects of RNA behaviour

Correspondence of F(R) gravity singularities in Jordan and Einstein frames

We study the finite time singularity correspondence between the Jordan and Einstein frames for various F(R) gravity theories. Particularly we investigate the ordinary pure F(R) gravity case and the unimodular F(R) gravity cases, in the absence of any matter fluids. In the ordinary F(R) gravity cases, by using specific illustrative examples, we show that it is possible to have various correspondences of finite time singularities, and in some cases it is possible a singular cosmology in one frame might be non-singular in the other frame. In the unimodular F(R) gravity case, the unimodular constraint is affected by the conformal transformation, so this has an effect on the metric we choose. Moreover, we study the Einstein frame counterpart theory of the unimodular F(R) gravity case, and we investigate the correspondences of the singularities in the two theories by considering specific illustrative examples. Finally, a brief dynamical system analysis is performed for the vacuum unimodular F(R) gravity and we demonstrate how the dynamical system behaves near the future Big Rip singularity

Testing extra dimensions with boundaries using Newton's law modifications

Extra dimensions with boundaries are often used in the literature, to provide phenomenological models that mimic the standard model. In this context, we explore possible modifications to Newton's law due to the existence of an extra-dimensional space, at the boundary of which the gravitational field obeys Dirichlet, Neumann or mixed boundary conditions. We focus on two types of extra space, namely, the disk and the interval. As we prove, in order to have a consistent Newton's law modification (i.e., of the Yukawa-type), some of the extra-dimensional spaces that have been used in the literature, must be ruled out.Comment: Published version, title changed, 6 figure

The Caltech Tomography Database and Automatic Processing Pipeline

Here we describe the Caltech Tomography Database and automatic image processing pipeline, designed to process, store, display, and distribute electron tomographic data including tilt-series, sample information, data collection parameters, 3D reconstructions, correlated light microscope images, snapshots, segmentations, movies, and other associated files. Tilt-series are typically uploaded automatically during collection to a user’s “Inbox” and processed automatically, but can also be entered and processed in batches via scripts or file-by-file through an internet interface. As with the video website YouTube, each tilt-series is represented on the browsing page with a link to the full record, a thumbnail image and a video icon that delivers a movie of the tomogram in a pop-out window. Annotation tools allow users to add notes and snapshots. The database is fully searchable, and sets of tilt-series can be selected and re-processed, edited, or downloaded to a personal workstation. The results of further processing and snapshots of key results can be recorded in the database, automatically linked to the appropriate tilt-series. While the database is password-protected for local browsing and searching, datasets can be made public and individual files can be shared with collaborators over the Internet. Together these tools facilitate high-throughput tomography work by both individuals and groups

Histogram-based models on non-thin section chest CT predict invasiveness of primary lung adenocarcinoma subsolid nodules.

109 pathologically proven subsolid nodules (SSN) were segmented by 2 readers on non-thin section chest CT with a lung nodule analysis software followed by extraction of CT attenuation histogram and geometric features. Functional data analysis of histograms provided data driven features (FPC1,2,3) used in further model building. Nodules were classified as pre-invasive (P1, atypical adenomatous hyperplasia and adenocarcinoma in situ), minimally invasive (P2) and invasive adenocarcinomas (P3). P1 and P2 were grouped together (T1) versus P3 (T2). Various combinations of features were compared in predictive models for binary nodule classification (T1/T2), using multiple logistic regression and non-linear classifiers. Area under ROC curve (AUC) was used as diagnostic performance criteria. Inter-reader variability was assessed using Cohen's Kappa and intra-class coefficient (ICC). Three models predicting invasiveness of SSN were selected based on AUC. First model included 87.5 percentile of CT lesion attenuation (Q.875), interquartile range (IQR), volume and maximum/minimum diameter ratio (AUC:0.89, 95%CI:[0.75 1]). Second model included FPC1, volume and diameter ratio (AUC:0.91, 95%CI:[0.77 1]). Third model included FPC1, FPC2 and volume (AUC:0.89, 95%CI:[0.73 1]). Inter-reader variability was excellent (Kappa:0.95, ICC:0.98). Parsimonious models using histogram and geometric features differentiated invasive from minimally invasive/pre-invasive SSN with good predictive performance in non-thin section CT