Contrasting effects on deep convective clouds by different types of aerosols

Convective clouds produce a significant proportion of the global precipitation and play an important role in the energy and water cycles. We quantify changes of the convective cloud ice mass-weighted altitude centroid (Z_(IWC)) as a function of aerosol optical thickness (AOT). Analyses are conducted in smoke, dust and polluted continental aerosol environments over South America, Central Africa and Southeast Asia, using the latest measurements from the CloudSat and CALIPSO satellites. We find aerosols can inhibit or invigorate convection, depending on aerosol type and concentration. On average, smoke tends to suppress convection and results in lower Z_(IWC) than clean clouds. Polluted continental aerosol tends to invigorate convection and promote higher Z_(IWC). The dust aerosol effects are regionally dependent and their signs differ from place to place. Moreover, we find that the aerosol inhibition or invigoration effects do not vary monotonically with AOT and the variations depend strongly on aerosol type. Our observational findings indicate that aerosol type is one of the key factors in determining the aerosol effects on convective clouds

Neural network for aerosol retrieval from hyperspectral imagery

We retrieve aerosol optical thickness (AOT) independently for brown carbon, dust and sulfate from hyperspectral image data. The model, a neural network, is trained on atmospheric radiative transfer calculations from MODTRAN 6.0 with varying aerosol concentration and type, surface albedo, water vapor, and viewing geometries. From a set of test radiative transfer calculations, we are able to retrieve AOT with a standard error of better than &plusmn;0.05. No a priori information on the surface albedo or atmospheric state is necessary for our model. We apply the model to AVIRIS-NG imagery from a recent campaign over India and demonstrate its performance under high and low aerosol loadings and different aerosol types. </div

Contrasting effects on deep convective clouds by different types of aerosols

Convective clouds produce a significant proportion of the global precipitation and play an important role in the energy and water cycles. We quantify changes of the convective cloud ice mass-weighted altitude centroid (Z_(IWC)) as a function of aerosol optical thickness (AOT). Analyses are conducted in smoke, dust and polluted continental aerosol environments over South America, Central Africa and Southeast Asia, using the latest measurements from the CloudSat and CALIPSO satellites. We find aerosols can inhibit or invigorate convection, depending on aerosol type and concentration. On average, smoke tends to suppress convection and results in lower Z_(IWC) than clean clouds. Polluted continental aerosol tends to invigorate convection and promote higher Z_(IWC). The dust aerosol effects are regionally dependent and their signs differ from place to place. Moreover, we find that the aerosol inhibition or invigoration effects do not vary monotonically with AOT and the variations depend strongly on aerosol type. Our observational findings indicate that aerosol type is one of the key factors in determining the aerosol effects on convective clouds

Analysis of 3D cloud effects in OCO-2 XCO2 retrievals

The presence of 3D cloud radiative effects in OCO-2 retrievals is demonstrated from an analysis of 2014&ndash;2019 OCO-2 XCO2 raw retrievals, bias-corrected XCO2bc data, ground-based Total Carbon Column Observation Network (TCCON) XCO2, and Moderate Resolution Imaging Spectroradiometer (MODIS) cloud and radiance fields. In approximate terms, 40&thinsp;% (quality flag &ndash; QF&thinsp;=&thinsp;0, land or ocean) and 73&thinsp;% (QF&thinsp;=&thinsp;1, land or ocean) of the observations are within 4&thinsp;km of clouds. 3D radiative transfer calculations indicate that 3D cloud radiative perturbations at this cloud distance, for an isolated low-altitude cloud, are larger in absolute value than those due to a 1&thinsp;ppm increase in CO2. OCO-2 measurements are therefore susceptible to 3D cloud effects. Four 3D cloud metrics, based upon MODIS radiance and cloud fields as well as stand-alone OCO-2 measurements, relate XCO2bc&ndash;TCCON averages to 3D cloud effects. This analysis indicates that the operational bias correction has a nonzero residual 3D cloud bias for both QF&thinsp;=&thinsp;0 and QF&thinsp;=&thinsp;1 data. XCO2bc&ndash;TCCON averages at small cloud distances differ from those at large cloud distances by &minus;0.4 and &minus;2.2&thinsp;ppm for the QF&thinsp;=&thinsp;0 and QF&thinsp;=&thinsp;1 data over the ocean. Mitigation of 3D cloud biases with a table lookup technique, which utilizes the nearest cloud distance (Distkm) and spatial radiance heterogeneity (CSNoiseRatio) 3D metrics, reduces QF&thinsp;=&thinsp;1 ocean and land XCO2bc&ndash;TCCON averages from &minus;1&thinsp;ppm to near &plusmn;0.2&thinsp;ppm. The ocean QF&thinsp;=&thinsp;1 XCO2bc&ndash;TCCON averages can be reduced to the 0.5&thinsp;ppm level if 60&thinsp;% (70&thinsp;%) of the QF&thinsp;=&thinsp;1 data points are utilized by applying Distkm (CSNoiseRatio) metrics in a data screening process. Over land the QF&thinsp;=&thinsp;1 XCO2bc&ndash;TCCON averages are reduced to the 0.5 (0.8)&thinsp;ppm level if 65&thinsp;% (63&thinsp;%) of the data points are utilized by applying Diastkm (CSNoiseRatio) data screening. The addition of more terms to the linear regression equations used in the current bias correction processing without data screening, however, did not introduce an appreciable improvement in the standard deviations of the XCO2bc&ndash;TCCON statistics. </div

The architecture of clonal expansions in morphologically normal tissue from cancerous and non-cancerous prostates

Background: Up to 80% of cases of prostate cancer present with multifocal independent tumour lesions leading to the concept of a field effect present in the normal prostate predisposing to cancer development. In the present study we applied Whole Genome DNA Sequencing (WGS) to a group of morphologically normal tissue (n = 51), including benign prostatic hyperplasia (BPH) and non-BPH samples, from men with and men without prostate cancer. We assess whether the observed genetic changes in morphologically normal tissue are linked to the development of cancer in the prostate. Results: Single nucleotide variants (P = 7.0 × 10–03, Wilcoxon rank sum test) and small insertions and deletions (indels, P = 8.7 × 10–06) were significantly higher in morphologically normal samples, including BPH, from men with prostate cancer compared to those without. The presence of subclonal expansions under selective pressure, supported by a high level of mutations, were significantly associated with samples from men with prostate cancer (P = 0.035, Fisher exact test). The clonal cell fraction of normal clones was always higher than the proportion of the prostate estimated as epithelial (P = 5.94 × 10–05, paired Wilcoxon signed rank test) which, along with analysis of primary fibroblasts prepared from BPH specimens, suggests a stromal origin. Constructed phylogenies revealed lineages associated with benign tissue that were completely distinct from adjacent tumour clones, but a common lineage between BPH and non-BPH morphologically normal tissues was often observed. Compared to tumours, normal samples have significantly less single nucleotide variants (P = 3.72 × 10–09, paired Wilcoxon signed rank test), have very few rearrangements and a complete lack of copy number alterations. Conclusions: Cells within regions of morphologically normal tissue (both BPH and non-BPH) can expand under selective pressure by mechanisms that are distinct from those occurring in adjacent cancer, but that are allied to the presence of cancer. Expansions, which are probably stromal in origin, are characterised by lack of recurrent driver mutations, by almost complete absence of structural variants/copy number alterations, and mutational processes similar to malignant tissue. Our findings have implications for treatment (focal therapy) and early detection approaches

Genomic evolution shapes prostate cancer disease type

H.R.F. was supported by a Cancer Research UK Programme Grant to Simon Tavaré (C14303/A17197), as, partially, was A.G.L. A.G.L. acknowledges the support of the University of St Andrews. A.G.L. and J.H.R.F. also acknowledge the support of the Cambridge Cancer Research Fund.The development of cancer is an evolutionary process involving the sequential acquisition of genetic alterations that disrupt normal biological processes, enabling tumor cells to rapidly proliferate and eventually invade and metastasize to other tissues. We investigated the genomic evolution of prostate cancer through the application of three separate classification methods, each designed to investigate a different aspect of tumor evolution. Integrating the results revealed the existence of two distinct types of prostate cancer that arise from divergent evolutionary trajectories, designated as the Canonical and Aalternative evolutionary disease types. We therefore propose the evotype model for prostate cancer evolution wherein Alternative-evotype tumors diverge from those of the Canonical-evotype through the stochastic accumulation of genetic alterations associated with disruptions to androgen receptor DNA binding. Our model unifies many previous molecular observations, providing a powerful new framework to investigate prostate cancer disease progression.Peer reviewe

Sequencing of prostate cancers identifies new cancer genes, routes of progression and drug targets

Prostate cancer represents a substantial clinical challenge because it is difficult to predict outcome and advanced disease is often fatal. We sequenced the whole genomes of 112 primary and metastatic prostate cancer samples. From joint analysis of these cancers with those from previous studies (930 cancers in total), we found evidence for 22 previously unidentified putative driver genes harboring coding mutations, as well as evidence for NEAT1 and FOXA1 acting as drivers through noncoding mutations. Through the temporal dissection of aberrations, we identified driver mutations specifically associated with steps in the progression of prostate cancer, establishing, for example, loss of CHD1 and BRCA2 as early events in cancer development of ETS fusion-negative cancers. Computational chemogenomic (canSAR) analysis of prostate cancer mutations identified 11 targets of approved drugs, 7 targets of investigational drugs, and 62 targets of compounds that may be active and should be considered candidates for future clinical trials

Analysis of the genetic phylogeny of multifocal prostate cancer identifies multiple independent clonal expansions in neoplastic and morphologically normal prostate tissue.

Genome-wide DNA sequencing was used to decrypt the phylogeny of multiple samples from distinct areas of cancer and morphologically normal tissue taken from the prostates of three men. Mutations were present at high levels in morphologically normal tissue distant from the cancer, reflecting clonal expansions, and the underlying mutational processes at work in morphologically normal tissue were also at work in cancer. Our observations demonstrate the existence of ongoing abnormal mutational processes, consistent with field effects, underlying carcinogenesis. This mechanism gives rise to extensive branching evolution and cancer clone mixing, as exemplified by the coexistence of multiple cancer lineages harboring distinct ERG fusions within a single cancer nodule. Subsets of mutations were shared either by morphologically normal and malignant tissues or between different ERG lineages, indicating earlier or separate clonal cell expansions. Our observations inform on the origin of multifocal disease and have implications for prostate cancer therapy in individual cases