Derivation and assessment of risk prediction models using case-cohort data

Background Case-cohort studies are increasingly used to quantify the association of novel factors with disease risk. Conventional measures of predictive ability need modification for this design. We show how Harrell’s C-index, Royston’s D, and the category-based and continuous versions of the net reclassification index (NRI) can be adapted. Methods We simulated full cohort and case-cohort data, with sampling fractions ranging from 1% to 90%, using covariates from a cohort study of coronary heart disease, and two incidence rates. We then compared the accuracy and precision of the proposed risk prediction metrics. Results The C-index and D must be weighted in order to obtain unbiased results. The NRI does not need modification, provided that the relevant non-subcohort cases are excluded from the calculation. The empirical standard errors across simulations were consistent with analytical standard errors for the C-index and D but not for the NRI. Good relative efficiency of the prediction metrics was observed in our examples, provided the sampling fraction was above 40% for the C-index, 60% for D, or 30% for the NRI. Stata code is made available. Conclusions Case-cohort designs can be used to provide unbiased estimates of the C-index, D measure and NRI

The need for carbon emissions-driven climate projections in CMIP7

Previous phases of the Coupled Model Intercomparison Project (CMIP) have primarily focused on simulations driven by atmospheric concentrations of greenhouse gases (GHGs), both for idealized model experiments, and for climate projections of different emissions scenarios. We argue that although this approach was pragmatic to allow parallel development of Earth System Model simulations and detailed socioeconomic futures, carbon cycle uncertainty as represented by diverse, process-resolving Earth System Models (ESMs) is not manifested in the scenario outcomes, thus omitting a dominant source of uncertainty in meeting the Paris Agreement. Mitigation policy is defined in terms of human activity (including emissions), with strategies varying in their timing of net-zero emissions, the balance of mitigation effort between short-lived and long-lived climate forcers, their reliance on land use strategy and the extent and timing of carbon removals. To explore the response to these drivers, ESMs need to explicitly represent complete cycles of major GHGs, including natural processes and anthropogenic influences. Carbon removal and sequestration strategies, which rely on proposed human management of natural systems, are currently represented upstream of ESMs in an idealized fashion during scenario development. However, proper accounting of the coupled system impacts of and feedback on such interventions requires explicit process representation in ESMs to build self-consistent physical representations of their potential effectiveness and risks under climate change. We propose that CMIP7 efforts prioritize simulations driven by CO2 emissions from fossil fuel use, projected deployment of carbon dioxide removal technologies, as well as land use and management, using the process resolution allowed by state-of-the-art ESMs to resolve carbon-climate feedbacks. Post-CMIP7 ambitions should aim to incorporate modeling of non-CO2 GHGs (in particular sources and sinks of methane) and process-based representation of carbon removal options. Such experiments would allow resources to be allocated to policy-relevant climate projections and better real-time information related to the detectability and verification of emissions reductions and their relationship to expected near-term climate impacts. Such efforts will provide information on the range of possible future climate states including Earth system processes and feedbacks which are increasingly well-represented in ESMs, thus forming a critical and complementary pillar underpinning proposed km-scale climate modeling activities and calls to better utilize novel machine learning approaches

On social knowledge, ideology and the nuclear power debate

SIGLEAvailable from British Library Lending Division - LD:D57159/85 / BLDSC - British Library Document Supply CentreGBUnited Kingdo

Myofibroblast matrix metalloproteinases activate the neutrophil chemoattractant CXCL7 from intestinal epithelial cells

Background & Aims: The up-regulation of matrix metalloproteinases (MMPs) in the inflamed gut has mainly been associated with mucosal degradation and ulceration. However, their in vitro capacity to specifically cleave inflammatory mediators indicates that MMPs may have a profound immunoregulatory impact. We hypothesized that MMPs proteolytically modify intestinal epithelial chemokine signaling.Methods: Interleukin-1?–stimulated Caco-2 cells were exposed basolaterally to nanomolar concentrations of activated MMP-3 or cocultured with interleukin-1?–stimulated, MMP-producing, colonic myofibroblasts (CCD-18co). The conditioned media were subjected to chemotaxis assays. In addition, epithelial cells from patients with colitis were examined by real-time polymerase chain reaction, immunoblotting, and immunohistochemistry.Results: MMP-3 dose-dependently induced the neutrophil (up to 5-fold) but not monocyte chemoattractant capacity of Caco-2 cells. A similar Caco-2 chemotactic response was obtained in the Caco-2/CCD-18co cocultures. The principal mediator of these protease-related effects was identified as the potent neutrophil chemokine CXCL7 (neutrophil activating peptide 2), a proteolytic cleavage product of chemotactically inert platelet basic protein (PBP), not previously identified in the intestine. Antibodies against CXCL7 inhibited the MMP-induced chemotactic response by 84%, and PBP mRNA and protein were detected in stimulated Caco-2 but not in CCD-18co cells. Furthermore, PBP transcript and protein levels were low in the mucosa and in isolated epithelial cells from patients with Crohn’s disease and from normal intestine but increased up to 13-fold in patients with ulcerative colitis.Conclusions: These findings identify a novel proinflammatory action of MMPs in inflammation and suggest that lamina propria myofibroblasts are required to achieve maximal intestinal epithelial immune activation.Abbreviations used in this paper: ENA-78, CXCL 5; GRO, growth-related oncogene; IL, interleukin; MCP, monocyte chemoattractant protein; MMP, matrix metalloproteinase; NAP-2, neutrophil-activating peptide 2; PBP, platelet basic protei

Breast milk lactoferrin regulates gene expression by binding bacterial DNA CpG motifs but not genomic DNA promoters in model intestinal cells

High-affinity binding of DNA by lactoferrin (LF) is an established phenomenon, but the biologic function of this interaction remains unclear. LF is an abundant breast milk protein (12.5-87.5 mu mol/L) and is resistant to digestion in the infant gut. Regulation of gene expression by LF appears to be a major activity, particularly in modulating immune responses. We hypothesized that LF binding to DNA is a mechanism of gene regulation and aimed to identify the mechanism and physiologic sites of this activity. Our studies focused on two major biologic compartments of DNA: LF binding to proinflammatory bacterial DNA sequences (CpG motifs) in extracellular compartments and LF binding to genomic DNA promoters in the nucleus. LF 0.5 mmol/L inhibited CpG motif-induced nuclear factor-kappa B (NF-kappa B) activation and interleukin (IL)-8 and IL-12 cytokine gene transcription in B cells. Intestinal epithelial cells were unresponsive to CpG motifs. However, significant LF transferred across M cell-like monolayers, specialized epithelial cells that transcytose intact macromolecules to underlying B-cell follicles in the intestine. LF did not activate gene expression by binding to putative response elements in epithelial and lymphoid cells. Nor did LF bind to putative response elements specifically in gel-shift assays. No nuclear localization of LF was detected in green fluorescent protein (GFP) tagging experiments. We conclude that breast milk LF regulates gene expression by binding CpG motifs extracellularly, with follicular B cells in C the infant intestine a likely target

Analysis of deformation bands associated with the Trachyte Mesa intrusion, Henry Mountains, Utah: implications for reservoir connectivity and fluid flow around sill intrusions

Shallow-level igneous intrusions are a common feature of many sedimentary basins, and there is increased recognition of the syn-emplacement deformation structures in the host rock that help to accommodate this magma addition. However, the sub-seismic structure and reservoir-scale implications of igneous intrusions remain poorly understood. The Trachyte Mesa intrusion is a small (∼1.5 km2), NE–SW trending satellite intrusion to the Oligocene-age Mount Hillers intrusive complex in the Henry Mountains, Utah. It is emplaced within the highly porous, aeolian Entrada Sandstone Formation (Jurassic), producing a network of conjugate sets of NE–SW striking deformation bands trending parallel to the intrusion margins. The network was characterized by defining a series of nodes and branches, from which the topology, frequency, intensity, spacing, characteristic length, and dimensionless intensity of the deformation band traces and branches were determined. These quantitative geometric and topological measures were supplemented by petrological, porosity and microstructural analyses. Results show a marked increase in deformation band intensity and significant porosity reduction with increasing proximity to the intrusion. The deformation bands are likely to impede fluid flow, forming barriers and baffles within the Entrada reservoir unit. A corresponding increase in Y- and X-nodes highlights the significant increase in deformation band connectivity, which in turn will significantly reduce the permeability of the sandstone. This study indicates that fluid flow in deformed host rocks around igneous bodies may vary significantly from that in the undeformed host rock. A better understanding of the variability of deformation structures, and their association with intrusion geometry, will have important implications for industries where fluid flow within naturally fractured reservoirs adds value (e.g. hydrocarbon reservoir deliverability, hydrology, geothermal energy and carbon sequestration)