Search

Just as Queensland commemorated the centenary anniversary of the abolition of the state’s Legislative Council, the Labor government under Premier Annastacia Palaszczuk, a ‘strong’ leader during the contemporaneous COVID-19 pandemic, found itself embroiled in the most serious integrity quagmire of its seven-year history. Given Queensland’s long history of ‘strong’ – even autocratic – political leadership and compromised government integrity, this article posits three arguments: that the abolition of the Legislative Council and a century of political excess in Queensland since 1922 are broadly related; that legislation in Queensland remains largely ‘executive-made’ and not ‘parliament-made’ law; and that the presence of a democratically elected Legislative Council after 1922 would have mitigated if not prevented much of Queensland’s political excess over the past one hundred years. The article also offers a model for a reintroduced Legislative Council that, given electoral distaste for ‘more politicians’, is unlikely to be approved at referendum.

Atmospheric turbulence causes the majority of weather-related aircraft accidents. Climate models project large increases in clear-air turbulence as the jet streams become more sheared in response to climate change. However, climate models have coarser resolutions than the numerical weather prediction models that are used to forecast clear-air turbulence operationally, raising questions about their suitability for this purpose. Here we provide the first rigorous demonstration that climate models are capable of successfully diagnosing clear-air turbulence and its response to climate change. We use an ensemble of seven clear-air turbulence diagnostics to compare 38 years of historic turbulence diagnosed from climate model simulations and high-resolution reanalysis data. We find that the differences in turbulence between the climate model and reanalysis data are much smaller than the spread between the diagnostics. When using a climate model to calculate the probabilities (and their temporal trends) of encountering clear-air turbulence of any strength, at any flight cruising level, and in any season, we find that most of the uncertainty stems from the turbulence diagnostics rather than the climate model. These results confirm the suitability of climate models for the task of producing future clear-air turbulence projections. The turbulence increases are generally larger when diagnosed from the reanalysis data than the climate model, suggesting that previous quantifications from climate models of the response of clear-air turbulence to climate change may be underestimates. Our results show that the key to reducing uncertainty in projections of future clear-air turbulence lies in improving the clear-air turbulence diagnostics rather than the climate models.

Clear-air turbulence (CAT) is hazardous to aircraft and is projected to intensify in response to future climate change. However, our understanding of past CAT trends is currently limited, being derived largely from outdated reanalysis data. Here we analyse CAT trends globally during 1979–2020 in a modern reanalysis dataset using 21 diagnostics. We find clear evidence of large increases around the globe at aircraft cruising altitudes. For example, at an average point over the North Atlantic, the total annual duration of light-or-greater CAT increased by 17% from 466.5 hours in 1979 to 546.8 hours in 2020, with even larger relative changes for moderate-or greater CAT (increasing by 37% from 70.0 hours to 96.1 hours) and severe-or-greater CAT (increasing by 55% from 17.7 hours to 27.4 hours). Our study represents the best evidence yet that CAT has increased over the past four decades.

Supplementary Figures S1-2, Tables S1-3. Figure S1. Comparison of the number of high confidence, non-synonymous somatic point mutations/indels and high level copy number alterations (CNAs) by tumor grade. Figure S2. Copy number plots of representative benign and borderline phyllodes tumors. Table S2: Somatic non-synonymous mutations identified in FFPE phyllodes tumors subjected to targeted next generation sequencing. Table S3: Detailed information about identified somatic non-synonymous mutations.

Description of additional methods and procedures used in the study. Also includes Supplementary References.

Supplementary Figures 1-5 from Src and Caveolin-1 Reciprocally Regulate Metastasis via a Common Downstream Signaling Pathway in Bladder Cancer

Penile squamous cell carcinoma (PeSCCA) is a rare malignancy for which there are limited treatment options due to a poor understanding of the molecular alterations underlying disease development and progression. Therefore, we performed comprehensive, targeted next-generation sequencing to identify relevant somatic genomic alterations in a retrospective cohort of 60 fixed tumor samples from 43 PeSCCA cases (including 14 matched primary/metastasis pairs). We identified a median of two relevant somatic mutations and one high-level copy-number alteration per sample (range, 0–5 and 0–6, respectively). Expression of HPV and p16 was detectable in 12% and 28% of patients, respectively. Furthermore, advanced clinical stage, lack of p16 expression, and MYC and CCND1 amplifications were significantly associated with shorter time to progression or PeSCCA-specific survival. Notably, four cases harbored EGFR amplifications and one demonstrated CDK4 amplification, genes for which approved and investigational targeted therapies are available. Importantly, although paired primary tumors and lymph node metastases were largely homogeneous for relevant somatic mutations, we identified heterogeneous EGFR amplification in primary tumor/lymph node metastases in 4 of 14 cases, despite uniform EGFR protein overexpression. Likewise, activating HRAS mutations occurred in 8 of 43 cases. Taken together, we provide the first comprehensive molecular PeSCCA analysis, which offers new insight into potential precision medicine approaches for this disease, including strategies targeting EGFR. Cancer Res; 75(24); 5219–27. ©2015 AACR.

Supplementary Figures 1-2 from Concordant Gene Expression Signatures Predict Clinical Outcomes of Cancer Patients Undergoing Systemic Therapy

Sanger sequencing validation of next generation sequencing (NGS) variant calls ; Alternative view of integrative molecular profiling heatmap ; p16 expression via immunohistochemistry ; Kaplan-Meier analysis of histologic subtypes of PeSCCA ; Comparison of prioritized molecular alterations in penile (PN) squamous cell carcinomas (SCCA) compared to other SCCAs .

Supplementary Methods, Table 1, Figure Legends 1-5 from Src and Caveolin-1 Reciprocally Regulate Metastasis via a Common Downstream Signaling Pathway in Bladder Cancer

Supplementary Figure Legends 1-2, Methods from Concordant Gene Expression Signatures Predict Clinical Outcomes of Cancer Patients Undergoing Systemic Therapy

Clinicopathologic data for all profiled penile squamous cell carcinoma (PeSCCA) samples ; Sequencing data for all profiled penile squamous cell carcinoma (PeSCCA) samples ; Detailed somatic variant information from PeSCCA profiled by next generation sequenicng ; PeSCCA HPV genotyping and p16 immunohistochemistry (IHC) results .

Conventional development of multivariate gene expression models (GEM) predicting therapeutic response of cancer patients is based on analysis of patients treated with specific regimens, which limits generalization to different or novel drug combinations. We overcome this limitation by developing GEMs based on in vitro drug sensitivities and microarray analyses of the NCI-60 cancer cell line panel. These GEMs were evaluated in blind fashion as predictors of tumor response and/or patient survival in seven independent cohorts of patients with breast (n = 275), bladder (n = 59), and ovarian (n= 143) cancer treated with multiagent chemotherapy, of which 233 patients were from prospectively enrolled clinical trials. In all studies, GEMs effectively stratified tumor response and patient survival independent of established clinical and pathologic tumor variables. In bladder cancer patients treated with neoadjuvant methotrexate, vinblastine, Adriamycin (doxorubicin), and cisplatin, the 3-year overall survival for those with favorable GEM scores was 81% versus 33% for those with less favorable scores (P = 0.002). GEMs for breast cancer patients treated with 5-fluorouracil, Adriamycin (doxorubicin), and cyclophosphamide and ovarian cancer patients treated with platinum-containing regimens also stratified patient survival [5-year overall survival 100% versus 74% (P = 0.05) and 3-year overall survival 68% versus 43% (P = 0.008), respectively]. Importantly, clinical prediction using our in vitro GEM was superior to that of conventionally derived GEMs. We show a facile yet effective approach to GEM derivation that identifies patients most likely to benefit from selected multiagent therapy. Use of such in vitro–based GEMs may provide a robust and generalizable approach to personalized cancer therapy. [Cancer Res 2009;69(21):8302–9]

The stabilisation of the leapfrog time-stepping scheme provided by the Robert–Asselin filter has enabled decades of atmospheric and oceanic research and weather and climate predictions. The unfortunate concomitant reduction from second-order accuracy to first-order accuracy inflicted by the filter has recently ushered in a new generation of leapfrog time filters that preserve the second-order accuracy, including the Robert–Asselin–Williams (RAW) filter and its variants. These modern filtered leapfrog schemes have previously been shown to improve numerical simulations made using both simple conceptual models and comprehensive general circulation models. However, their performance in standard benchmark experiments has not previously been assessed. Here we evaluate these filtered leapfrog schemes in four classic benchmark experiments: linear scalar advection; a nonlinear density current in the quasi-compressible equations; a nonlinear rising warm bubble in the fully compressible equations; and the linked behaviour of nonlinear twin tropical cyclones in the rotating shallow-water equations. For a given time-step size, the filtered leapfrog schemes are found to compare favourably with the third-order Runge–Kutta (RK3) scheme. They are also less computationally expensive than RK3, at roughly one-third to one-half the cost per time step. For a given computational expenditure, the filtered leapfrog schemes are found to produce smaller errors with respect to the analytical solution (where available) than RK3. Furthermore, the filtered leapfrog schemes are found to be numerically stable, even when the discretisation method splits the slow advection and diffusion modes from the fast acoustic and gravity-wave modes. Given that implementing filter upgrades requires only minimally invasive changes to an existing computer code, our results provide support for the continued use of filtered leapfrog schemes in atmosphere and ocean models.