Perturbing parameters to understand cloud contributions to climate change

The sensitivity of cloud feedbacks to atmospheric model parameters is evaluated using a CAM6 perturbed parameter ensemble (PPE). The CAM6 PPE perturbs 45 parameters across 262 simulations, 206 of which are used here. The spread in total cloud feedback and its six components across the CAM6 PPE are comparable to the spread across the CMIP6 and AMIP ensembles, indicating that parametric uncertainty mirrors structural uncertainty. However, the high-cloud altitude feedback is generally larger in the CAM6 PPE than WCRP assessment, CMIP6, and AMIP values. We evaluate the influence of each of the 45 parameters on the total cloud feedback and each of the six cloud feedback components. We also explore whether the CAM6 PPE can be used to constrain the total cloud feedback, with inconclusive results. Further, we find that despite the large parametric sensitivity of cloud feedbacks in CAM6, a substantial increase in cloud feedbacks from CAM5 to CAM6 is not a result of changes in parameter values. Notably, the CAM6 PPE is run with a more recent version of CAM6 (CAM6.3) than was used for AMIP (CAM6.0), and has a smaller total cloud feedback (0.56 W m$^{-2}$ K$^{-1}$) as compared to CAM6.0 (0.81 W m$^{-2}$ K$^{-1}$) owing primarily to reductions in low clouds over the tropics and middle latitudes. The work highlights the large sensitivity of cloud feedbacks to both parameter values and structural details in CAM6

Identification of novel small molecule inhibitors of adenovirus gene transfer using a high throughput screening approach

Due to many favourable attributes adenoviruses (Ads) are the most extensively used vectors for clinical gene therapy applications. However, following intravascular administration, the safety and efficacy of Ad vectors are hampered by the strong hepatic tropism and induction of a potent immune response. Such effects are determined by a range of complex interactions including those with neutralising antibodies, blood cells and factors, as well as binding to native cellular receptors (coxsackie adenovirus receptor (CAR), integrins). Once in the bloodstream, coagulation factor X (FX) has a pivotal role in determining Ad liver transduction and viral immune recognition. Due to difficulties in generating a vector devoid of multiple receptor binding motifs, we hypothesised that a small molecule inhibitor would be of value. Here, a pharmacological approach was implemented to block adenovirus transduction pathways. We developed a high throughput screening (HTS) platform to identify the small molecule inhibitors of FX-mediated Ad5 gene transfer. Using an in vitro fluorescence and cell-based HTS, we evaluated 10,240 small molecules. Following sequential rounds of screening, three compounds, T5424837, T5550585 and T5660138 were identified that ablated FX-mediated Ad5 transduction with low micromolar potency. The candidate molecules possessed common structural features and formed part of the one pharmacophore model. Focused, mini-libraries were generated with structurally related molecules and in vitro screening revealed novel hits with similar or improved efficacy. The compounds did not interfere with Ad5:FX engagement but acted at a subsequent step by blocking efficient intracellular transport of the virus. In vivo, T5660138 and its closely related analogue T5660136 significantly reduced Ad5 liver transgene expression at 48 h post-intravenous administration of a high viral dose (1 × 10<sup>11</sup> vp/mouse). Therefore, this study identifies novel and potent small molecule inhibitors of the Ad5 transduction which may have applications in the Ad gene therapy setting

On the uncertainty of long-period return values of extreme daily precipitation

Methods for calculating return values of extreme precipitation and their uncertainty are compared using daily precipitation rates over the Western U.S. and Southwestern Canada from a large ensemble of climate model simulations. The roles of return-value estimation procedures and sample size in uncertainty are evaluated for various return periods. We compare two different generalized extreme value (GEV) parameter estimation techniques, namely L-moments and maximum likelihood (MLE), as well as empirical techniques. Even for very large datasets, confidence intervals calculated using GEV techniques are narrower than those calculated using empirical methods. Furthermore, the more efficient L-moments parameter estimation techniques result in narrower confidence intervals than MLE parameter estimation techniques at small sample sizes, but similar best estimates. It should be noted that we do not claim that either parameter fitting technique is better calibrated than the other to estimate long period return values. While a non-stationary MLE methodology is readily available to estimate GEV parameters, it is not for the L-moments method. Comparison of uncertainty quantification methods are found to yield significantly different estimates for small sample sizes but converge to similar results as sample size increases. Finally, practical recommendations about the length and size of climate model ensemble simulations and the choice of statistical methods to robustly estimate long period return values of extreme daily precipitation statistics and quantify their uncertainty

A new method for diagnosing effective radiative forcing from aerosol-cloud interactions in climate models

Aerosol-cloud interactions (ACI) are a leading source of uncertainty in estimates of the historical effective radiative forcing (ERF). One reason for this uncertainty is the difficulty of estimating the ERF from aerosol-cloud interactions (ERFaci) in climate models, which typically requires multiple calls to the radiation code and cannot disentangle the contributions from different process to ERFaci. Here, we develop a new, computationally efficient method for estimating the shortwave (SW) ERFaci from liquid clouds using histograms of monthly-averaged cloud fraction partitioned by cloud droplet effective radius (re) and liquid water path (LWP). Multiplying the histograms with SW cloud radiative kernels gives the total SW ERFaci from liquid clouds, which can be decomposed into contributions from the Twomey effect, LWP adjustments, and cloud-fraction (CF) adjustments. We test the method with data from five CMIP6-era models, using the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite instrument simulator to generate the histograms. Our method gives similar total SW ERFaci estimates to other established methods in regions of prevalent liquid cloud, and indicates that the Twomey effect, LWP adjustments, and CF adjustments have contributed −0.34 ± 0.23, −0.22 ± 0.13, and −0.09 ± 0.11 Wm−2, respectively, to the effective radiative forcing of the climate since 1850 in the ensemble mean (95 % confidence). These results demonstrate that widespread adoption of a MODIS re– LWP joint histogram diagnostic would allow the SW ERFaci and its components to be quickly and accurately diagnosed from climate model outputs, a crucial step for reducing uncertainty in the historical ERF

Retargeting FX binding-ablated HAdV-5 to vascular cells by inclusion of the RGD-4C peptide in hexon hypervariable region 7 and the HI loop

Recent studies have generated interest in the function of human adenovirus serotype 5 (HAdV-5) hexon:  factor X (FX) binding and subsequent hepatocyte transduction and interaction with the immune system. Here, we retargeted adenovirus serotype 5 vectors, ablated for FX interaction, by replacing amino acids in hexon HVR7 with RGD-4C or inserting the peptide into the fibre HI loop. These genetic modifications in the capsid were compatible with virus assembly, and could efficiently retarget transduction of the vector via the αvβ3/5 integrin-mediated pathway, but did not alter immune recognition by pre-existing human neutralizing anti-HAdV-5 antibodies or by natural antibodies in mouse serum. Thus, FX-binding-ablated HAdV-5 can be retargeted but remain sensitive to immune-mediated attack. These findings further refine HAdV-5-based vectors for human gene therapy and inform future vector development

The androgen receptor CAG repeat polymorphism and modification of breast cancer risk in BRCA1 and BRCA2 mutation carriers.

INTRODUCTION: The androgen receptor (AR) gene exon 1 CAG repeat polymorphism encodes a string of 9-32 glutamines. Women with germline BRCA1 mutations who carry at least one AR allele with 28 or more repeats have been reported to have an earlier age at onset of breast cancer. METHODS: A total of 604 living female Australian and British BRCA1 and/or BRCA2 mutation carriers from 376 families were genotyped for the AR CAG repeat polymorphism. The association between AR genotype and disease risk was assessed using Cox regression. AR genotype was analyzed as a dichotomous covariate using cut-points previously reported to be associated with increased risk among BRCA1 mutation carriers, and as a continuous variable considering smaller allele, larger allele and average allele size. RESULTS: There was no evidence that the AR CAG repeat polymorphism modified disease risk in the 376 BRCA1 or 219 BRCA2 mutation carriers screened successfully. The rate ratio associated with possession of at least one allele with 28 or more CAG repeats was 0.74 (95% confidence interval 0.42-1.29; P = 0.3) for BRCA1 carriers, and 1.12 (95% confidence interval 0.55-2.25; P = 0.8) for BRCA2 carriers. CONCLUSION: The AR exon 1 CAG repeat polymorphism does not appear to have an effect on breast cancer risk in BRCA1 or BRCA2 mutation carriers

The Green's function model intercomparison project (GFMIP) protocol

The atmospheric Green's function method is a technique for modeling the response of the atmosphere to changes in the spatial field of surface temperature. While early studies applied this method to changes in atmospheric circulation, it has also become an important tool to understand changes in radiative feedbacks due to evolving patterns of warming, a phenomenon called the “pattern effect.” To better study this method, this paper presents a protocol for creating atmospheric Green's functions to serve as the basis for a model intercomparison project, GFMIP. The protocol has been developed using a series of sensitivity tests performed with the HadAM3 atmosphere‐only general circulation model, along with existing and new simulations from other models. Our preliminary results have uncovered nonlinearities in the response of the atmosphere to surface temperature changes, including an asymmetrical response to warming versus cooling patch perturbations, and a change in the dependence of the response on the magnitude and size of the patches. These nonlinearities suggest that the pattern effect may depend on the heterogeneity of warming as well as its location. These experiments have also revealed tradeoffs in experimental design between patch size, perturbation strength, and the length of control and patch simulations. The protocol chosen on the basis of these experiments balances scientific utility with the simulation time and setup required by the Green's function approach. Running these simulations will further our understanding of many aspects of atmospheric response, from the pattern effect and radiative feedbacks to changes in circulation, cloudiness, and precipitation

Over-expression of Eph and ephrin genes in advanced ovarian cancer: ephrin gene expression correlates with shortened survival

BACKGROUND: Increased expression of Eph receptor tyrosine kinases and their ephrin ligands has been implicated in tumor progression in a number of malignancies. This report describes aberrant expression of these genes in ovarian cancer, the commonest cause of death amongst gynaecological malignancies. METHODS: Eph and ephrin expression was determined using quantitative real time RT-PCR. Correlation of gene expression was measured using Spearman's rho statistic. Survival was analysed using log-rank analysis and (was visualised by) Kaplan-Meier survival curves. RESULTS: Greater than 10 fold over-expression of EphA1 and a more modest over-expression of EphA2 were observed in partially overlapping subsets of tumors. Over-expression of EphA1 strongly correlated (r = 0.801; p < 0.01) with the high affinity ligand ephrin A1. A similar trend was observed between EphA2 and ephrin A1 (r = 0.387; p = 0.06). A striking correlation of both ephrin A1 and ephrin A5 expression with poor survival (r = -0.470; p = 0.02 and r = -0.562; p < 0.01) was observed. Intriguingly, there was no correlation between survival and other clinical parameters or Eph expression. CONCLUSION: These data imply that increased levels of ephrins A1 and A5 in the presence of high expression of Ephs A1 and A2 lead to a more aggressive tumor phenotype. The known functions of Eph/ephrin signalling in cell de-adhesion and movement may explain the observed correlation of ephrin expression with poor prognosis