Macroeconomic impact of stranded fossil-fuel assets

Several major economies rely heavily on fossil-fuel production and exports, yet current low-carbon technology diffusion, energy efficiency and climate policy may be substantially reducing global demand for fossil fuels.1-4 This trend is inconsistent with observed investment in new fossil-fuel ventures1,2, which could become stranded as a result. Here we use an integrated global economy environment simulation model to study the macroeconomic impact of stranded fossil-fuel assets (SFFA). Our analysis suggests that part of the SFFA would occur as a result of an already ongoing technological trajectory, irrespective of whether new climate policies are adopted or not; the loss would be amplified if new climate policies to reach the 2°C target are adopted and/or if low-cost producers (some OPEC countries) maintain their level of production (‘sell-out’) despite declining demand; the magnitude of the loss from SFFA may amount to a discounted global wealth loss of $1-4tn; and there are clear distributional impacts, with winners (e.g. net importers such as China or the EU) and losers (e.g. Russia, the US or Canada, which could see their fossil-fuel industries nearly shut down), although the two effects would largely offset each other at the level of aggregate global GDP.The authors acknowledge C-EERNG and Cambridge Econometrics for support, and funding from EPSRC (JFM, fellowship no. EP/ K007254/1); the Newton Fund (JFM, PS, JV, EPSRC grant no EP/N002504/1 and ESRC grant no ES/N013174/1), NERC (NRE, PH, HP, grant no NE/P015093/1), CONICYT (PS), the Philomathia Foundation (JV), the Cambridge Humanities Research Grants Scheme (JV), and Horizon 2020 (HP, JFM; Sim4Nexus project)

Calcium Triggered Lα-H2 Phase Transition Monitored by Combined Rapid Mixing and Time-Resolved Synchrotron SAXS

BACKGROUND: Awad et al. reported on the Ca(2+)-induced transitions of dioleoyl-phosphatidylglycerol (DOPG)/monoolein (MO) vesicles to bicontinuous cubic phases at equilibrium conditions. In the present study, the combination of rapid mixing and time-resolved synchrotron small-angle X-ray scattering (SAXS) was applied for the in-situ investigations of fast structural transitions of diluted DOPG/MO vesicles into well-ordered nanostructures by the addition of low concentrated Ca(2+) solutions. METHODOLOGY/PRINCIPAL FINDINGS: Under static conditions and the in absence of the divalent cations, the DOPG/MO system forms large vesicles composed of weakly correlated bilayers with a d-spacing of approximately 140 A (L(alpha)-phase). The utilization of a stopped-flow apparatus allowed mixing these DOPG/MO vesicles with a solution of Ca(2+) ions within 10 milliseconds (ms). In such a way the dynamics of negatively charged PG to divalent cation interactions, and the kinetics of the induced structural transitions were studied. Ca(2+) ions have a very strong impact on the lipidic nanostructures. Intriguingly, already at low salt concentrations (DOPG/Ca(2+)>2), Ca(2+) ions trigger the transformation from bilayers to monolayer nanotubes (inverted hexagonal phase, H(2)). Our results reveal that a binding ratio of 1 Ca(2+) per 8 DOPG is sufficient for the formation of the H(2) phase. At 50 degrees C a direct transition from the vesicles to the H(2) phase was observed, whereas at ambient temperature (20 degrees C) a short lived intermediate phase (possibly the cubic Pn3m phase) coexisting with the H(2) phase was detected. CONCLUSIONS/SIGNIFICANCE: The strong binding of the divalent cations to the negatively charged DOPG molecules enhances the negative spontaneous curvature of the monolayers and causes a rapid collapsing of the vesicles. The rapid loss of the bilayer stability and the reorganization of the lipid molecules within ms support the argument that the transition mechanism is based on a leaky fusion of the vesicles

Incorporating progesterone receptor expression into the PREDICT breast prognostic model

Background: Predict Breast (www.predict.nhs.uk) is an online prognostication and treatment benefit tool for early invasive breast cancer. The aim of this study was to incorporate the prognostic effect of progesterone receptor (PR) status into a new version of PREDICT and to compare its performance to the current version (2.2).Method: The prognostic effect of PR status was based on the analysis of data from 45,088 European patients with breast cancer from 49 studies in the Breast Cancer Association Consortium. Cox proportional hazard models were used to estimate the hazard ratio for PR status. Data from a New Zealand study of 11,365 patients with early invasive breast cancer were used for external validation. Model calibration and discrimination were used to test the model performance.Results: Having a PR-positive tumour was associated with a 23% and 28% lower risk of dying from breast cancer for women with oestrogen receptor (ER)-negative and ER-positive breast cancer, respectively. The area under the ROC curve increased with the addition of PR status from 0.807 to 0.809 for patients with ER-negative tumours (p = 0.023) and from 0.898 to 0. 902 for patients with ER-positive tumours (p = 2.3 x 10(-6)) in the New Zealand cohort. Model calibration was modest with 940 observed deaths compared to 1151 predicted.Conclusion: The inclusion of the prognostic effect of PR status to PREDICT Breast has led to an improvement of model performance and more accurate absolute treatment benefit predic-tions for individual patients. Further studies should determine whether the baseline hazard function requires recalibration. (C) 2022 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).Peer reviewe

Development and Validation of the Gene Expression Predictor of High-grade Serous Ovarian Carcinoma Molecular SubTYPE (PrOTYPE).

PURPOSE: Gene expression-based molecular subtypes of high-grade serous tubo-ovarian cancer (HGSOC), demonstrated across multiple studies, may provide improved stratification for molecularly targeted trials. However, evaluation of clinical utility has been hindered by nonstandardized methods, which are not applicable in a clinical setting. We sought to generate a clinical grade minimal gene set assay for classification of individual tumor specimens into HGSOC subtypes and confirm previously reported subtype-associated features. EXPERIMENTAL DESIGN: Adopting two independent approaches, we derived and internally validated algorithms for subtype prediction using published gene expression data from 1,650 tumors. We applied resulting models to NanoString data on 3,829 HGSOCs from the Ovarian Tumor Tissue Analysis consortium. We further developed, confirmed, and validated a reduced, minimal gene set predictor, with methods suitable for a single-patient setting. RESULTS: Gene expression data were used to derive the predictor of high-grade serous ovarian carcinoma molecular subtype (PrOTYPE) assay. We established a de facto standard as a consensus of two parallel approaches. PrOTYPE subtypes are significantly associated with age, stage, residual disease, tumor-infiltrating lymphocytes, and outcome. The locked-down clinical grade PrOTYPE test includes a model with 55 genes that predicted gene expression subtype with >95% accuracy that was maintained in all analytic and biological validations. CONCLUSIONS: We validated the PrOTYPE assay following the Institute of Medicine guidelines for the development of omics-based tests. This fully defined and locked-down clinical grade assay will enable trial design with molecular subtype stratification and allow for objective assessment of the predictive value of HGSOC molecular subtypes in precision medicine applications.See related commentary by McMullen et al., p. 5271.Core funding for this project was provided by the National Institutes of Health (R01-CA172404, PI: S.J. Ramus; and R01-CA168758, PIs: J.A. Doherty and M.A.Rossing), the Canadian Institutes for Health Research (Proof-of-Principle I program, PIs: D.G.Huntsman and M.S. Anglesio), the United States Department of Defense Ovarian Cancer Research Program (OC110433, PI: D.D. Bowtell). A. Talhouk is funded through a Michael Smith Foundation for Health Research Scholar Award. M.S. Anglesio is funded through a Michael Smith Foundation for Health Research Scholar Award and the Janet D. Cottrelle Foundation Scholars program managed by the BC Cancer Foundation. J. George was partially supported by the NIH/National Cancer Institute award number P30CA034196. C. Wang was a Career Enhancement Awardee of the Mayo Clinic SPORE in Ovarian Cancer (P50 CA136393). D.G. Huntsman receives support from the Dr. Chew Wei Memorial Professorship in Gynecologic Oncology, and the Canada Research Chairs program (Research Chair in Molecular and Genomic Pathology). M. Widschwendter receives funding from the European Union’s Horizon 2020 European Research Council Programme, H2020 BRCA-ERC under Grant Agreement No. 742432 as well as the charity, The Eve Appeal (https://eveappeal.org.uk/), and support of the National Institute for Health Research (NIHR) and the University College London Hospitals (UCLH) Biomedical Research Centre. G.E. Konecny is supported by the Miriam and Sheldon Adelson Medical Research Foundation. B.Y. Karlan is funded by the American Cancer Society Early Detection Professorship (SIOP-06-258-01-COUN) and the National Center for Advancing Translational Sciences (NCATS), Grant UL1TR000124. H.R. Harris is 20 supported by the NIH/National Cancer Institute award number K22 CA193860. OVCARE (including the VAN study) receives support through the BC Cancer Foundation and The VGH+UBC Hospital Foundation (authors AT, BG, DGH, and MSA). The AOV study is supported by the Canadian Institutes of Health Research (MOP86727). The Gynaecological Oncology Biobank at Westmead, a member of the Australasian Biospecimen Network-Oncology group, was funded by the National Health and Medical Research Council Enabling Grants ID 310670 & ID 628903 and the Cancer Institute NSW Grants ID 12/RIG/1-17 & 15/RIG/1-16. The Australian Ovarian Cancer Study Group was supported by the U.S. Army Medical Research and Materiel Command under DAMD17-01-1-0729, The Cancer Council Victoria, Queensland Cancer Fund, The Cancer Council New South Wales, The Cancer Council South Australia, The Cancer Council Tasmania and The Cancer Foundation of Western Australia (Multi-State Applications 191, 211 and 182) and the National Health and Medical Research Council of Australia (NHMRC; ID199600; ID400413 and ID400281). BriTROC-1 was funded by Ovarian Cancer Action (to IAM and JDB, grant number 006) and supported by Cancer Research UK (grant numbers A15973, A15601, A18072, A17197, A19274 and A19694) and the National Institute for Health Research Cambridge and Imperial Biomedical Research Centres. Samples from the Mayo Clinic were collected and provided with support of P50 CA136393 (E.L.G., G.L.K, S.H.K, M.E.S.)

CCNE1 and survival of patients with tubo-ovarian high-grade serous carcinoma: An Ovarian Tumor Tissue Analysis consortium study

BACKGROUND: Cyclin E1 (CCNE1) is a potential predictive marker and therapeutic target in tubo-ovarian high-grade serous carcinoma (HGSC). Smaller studies have revealed unfavorable associations for CCNE1 amplification and CCNE1 overexpression with survival, but to date no large-scale, histotype-specific validation has been performed. The hypothesis was that high-level amplification of CCNE1 and CCNE1 overexpression, as well as a combination of the two, are linked to shorter overall survival in HGSC. METHODS: Within the Ovarian Tumor Tissue Analysis consortium, amplification status and protein level in 3029 HGSC cases and mRNA expression in 2419 samples were investigated. RESULTS: High-level amplification (>8 copies by chromogenic in situ hybridization) was found in 8.6% of HGSC and overexpression (>60% with at least 5% demonstrating strong intensity by immunohistochemistry) was found in 22.4%. CCNE1 high-level amplification and overexpression both were linked to shorter overall survival in multivariate survival analysis adjusted for age and stage, with hazard stratification by study (hazard ratio [HR], 1.26; 95% CI, 1.08-1.47, p = .034, and HR, 1.18; 95% CI, 1.05-1.32, p = .015, respectively). This was also true for cases with combined high-level amplification/overexpression (HR, 1.26; 95% CI, 1.09-1.47, p = .033). CCNE1 mRNA expression was not associated with overall survival (HR, 1.00 per 1-SD increase; 95% CI, 0.94-1.06; p = .58). CCNE1 high-level amplification is mutually exclusive with the presence of germline BRCA1/2 pathogenic variants and shows an inverse association to RB1 loss. CONCLUSION: This study provides large-scale validation that CCNE1 high-level amplification is associated with shorter survival, supporting its utility as a prognostic biomarker in HGSC

MyD88 and TLR4 Expression in Epithelial Ovarian Cancer.

OBJECTIVE: To evaluate myeloid differentiation primary response gene 88 (MyD88) and Toll-like receptor 4 (TLR4) expression in relation to clinical features of epithelial ovarian cancer, histologic subtypes, and overall survival. PATIENTS AND METHODS: We conducted centralized immunohistochemical staining, semi-quantitative scoring, and survival analysis in 5263 patients participating in the Ovarian Tumor Tissue Analysis consortium. Patients were diagnosed between January 1, 1978, and December 31, 2014, including 2865 high-grade serous ovarian carcinomas (HGSOCs), with more than 12,000 person-years of follow-up time. Tissue microarrays were stained for MyD88 and TLR4, and staining intensity was classified using a 2-tiered system for each marker (weak vs strong). RESULTS: Expression of MyD88 and TLR4 was similar in all histotypes except clear cell ovarian cancer, which showed reduced expression compared with other histotypes (P<.001 for both). In HGSOC, strong MyD88 expression was modestly associated with shortened overall survival (hazard ratio [HR], 1.13; 95% CI, 1.01-1.26; P=.04) but was also associated with advanced stage (P<.001). The expression of TLR4 was not associated with survival. In low-grade serous ovarian cancer (LGSOC), strong expression of both MyD88 and TLR4 was associated with favorable survival (HR [95% CI], 0.49 [0.29-0.84] and 0.44 [0.21-0.89], respectively; P=.009 and P=.02, respectively). CONCLUSION: Results are consistent with an association between strong MyD88 staining and advanced stage and poorer survival in HGSOC and demonstrate correlation between strong MyD88 and TLR4 staining and improved survival in LGSOC, highlighting the biological differences between the 2 serous histotypes

The older people, omega-3, and cognitive health (EPOCH) trial design and methodology: A randomised, double-blind, controlled trial investigating the effect of long-chain omega-3 fatty acids on cognitive ageing and wellbeing in cognitively healthy older adults

Extent: 18p.Background: Some studies have suggested an association between omega-3 long-chain polyunsaturated fatty acids (n-3 LC PUFAs) and better cognitive outcomes in older adults. To date, only two randomised, controlled trials have assessed the effect of n-3 LC PUFA supplementation on cognitive function in older cognitively healthy populations. Of these trials only one found a benefit, in the subgroup carrying the ApoE-ε4 allele. The benefits of n-3 LC PUFA supplementation on cognitive function in older normal populations thus still remain unclear. The main objective of the current study was to provide a comprehensive assessment of the potential of n-3 LC PUFAs to slow cognitive decline in normal elderly people, and included ApoE-ε4 allele carriage as a potential moderating factor. The detailed methodology of the trial is reported herein. Methods: The study was a parallel, 18-month, randomised, double-blind, placebo-controlled intervention with assessment at baseline and repeated 6-monthly. Participants (N = 391, 53.7% female) aged 65-90 years, English-speaking and with normal cognitive function, were recruited from metropolitan Adelaide, South Australia. Participants in the intervention arm received capsules containing fish-oil at a daily dosage of 1720 mg of docosahexaenoic acid and 600 mg of eicosapentaenoic acid while the placebo arm received the equivalent amount of olive oil in their capsules. The primary outcome is rate of change in cognitive performance, as measured by latent variables for the cognitive constructs (encompassing Reasoning, Working Memory, Short-term Memory, Retrieval Fluency, Inhibition, Simple and Choice-Reaction Time, Perceptual Speed, Odd-man-out Reaction Time, Speed of Memory Scanning, and Psychomotor Speed) and assessed by latent growth curve modeling. Secondary outcomes are change in the Mini-mental State Examination, functional capacity and well-being (including health status, depression, mood, and self-report cognitive functioning), blood pressure, and biomarkers of n-3 LC PUFA status, glucose, lipid metabolism, inflammation, oxidative stress, and DNA damage.Vanessa Danthiir, Nicholas R Burns, Ted Nettelbeck, Carlene Wilson and Gary Witter