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Triple-negative breast cancer (TNBC) is the most aggressive breast cancer subtype and has the highest rate of recurrence1. The predominant standard of care for advanced TNBC is systemic chemotherapy with or without immunotherapy; however, responses are typically short lived1,2. Thus, there is an urgent need to develop more effective treatments. Components of the PI3K pathway represent plausible therapeutic targets; more than 70% of TNBCs have alterations in PIK3CA, AKT1 or PTEN3–6. However, in contrast to hormone-receptor-positive tumours, it is still unclear whether or how triple-negative disease will respond to PI3K pathway inhibitors7. Here we describe a promising AKT-inhibitor-based therapeutic combination for TNBC. Specifically, we show that AKT inhibitors synergize with agents that suppress the histone methyltransferase EZH2 and promote robust tumour regression in multiple TNBC models in vivo. AKT and EZH2 inhibitors exert these effects by first cooperatively driving basal-like TNBC cells into a more differentiated, luminal-like state, which cannot be effectively induced by either agent alone. Once TNBCs are differentiated, these agents kill them by hijacking signals that normally drive mammary gland involution. Using a machine learning approach, we developed a classifier that can be used to predict sensitivity. Together, these findings identify a promising therapeutic strategy for this highly aggressive tumour type and illustrate how deregulated epigenetic enzymes can insulate tumours from oncogenic vulnerabilities. These studies also reveal how developmental tissue-specific cell death pathways may be co-opted for therapeutic benefit.AKT inhibitors synergize with agents that suppress the histone methyltransferase EZH2 and promote robust tumour regression in multiple triple-negative breast cancer models in vivo by triggering an involution-like process. [ABSTRACT FROM AUTHOR]

Objectives: When assessing for lower gastrointestinal bleed (LGIB) using CTA, many advocate for acquiring non-contrast and delayed phases in addition to an arterial phase to improve diagnostic performance though the potential benefit of this approach has not been fully characterized. We evaluate diagnostic accuracy among radiologists when using single-phase, biphasic, and triphasic CTA in active LGIB detection. Method and materials: A random experimental block design was used where 3 blinded radiologists specialty trained in interventional radiology retrospectively interpreted 96 CTA examinations completed between Oct 2012 and Oct 2017 using (1) arterial only, (2) arterial/non-contrast, and (3) arterial/non-contrast/delayed phase configurations. Confirmed positive and negative LGIB studies were matched, balanced, and randomly ordered. Sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, positive and negative predictive values, and time to identify the presence/absence of active bleeding were examined using generalized estimating equations (GEE) with sandwich estimation assuming a binary distribution to estimate relative benefit of diagnostic performance between phase configurations. Results: Specificity increased with additional contrast phases (arterial 72.2; arterial/non-contrast 86.1; arterial/non-contrast/delayed 95.1; p < 0.001) without changes in sensitivity (arterial 77.1; arterial/non-contrast 70.2; arterial/non-contrast/delayed 73.1; p = 0.11) or mean time required to identify bleeding per study (s, arterial 34.8; arterial/non-contrast 33.1; arterial/non-contrast/delayed 36.0; p = 0.99). Overall agreement among readers (Kappa) similarly increased (arterial 0.47; arterial/non-contrast 0.65; arterial/non-contrast/delayed 0.79). Conclusion: The addition of non-contrast and delayed phases to arterial phase CTA increased specificity and inter-reader agreement for the detection of lower gastrointestinal bleeding without increasing reading times. Key Points: • A triphasic CTA including non-contrast, arterial, and delayed phase has higher specificity for the detection of lower gastrointestinal bleeding than arterial-phase-only protocols. • Inter-reader agreement increases with additional contrast phases relative to single-phase CTA. • Increasing the number of contrast phases did not increase reading times. [ABSTRACT FROM AUTHOR]

Phyllanthus amarus is known as a healing herb which has traditionally been used in the treatment of various diseases such as hepatitis, diabetes and cancer. The extraction parameters have great effects on the extraction efficiency of bioactive compounds and pharmacological activity of the extracts. This study sought to optimise the microwave-assisted extraction parameters for phenolic compounds-enriched extracts and antioxidant capacity from P. amarus using response surface methodology (RSM). The results showed that the optimal microwave-assisted extraction parameters were an extraction time of 30 min, an irradiation time of 14 s min−1 and a ratio of solvent to sample of 150 mL g−1. The total phenolic content, phenolic extraction efficiency, saponin content, 2,2′-azino-bis(3-ethylbenzthiazoline-6-sulphonic acid) (ABTS) radical scavenging capacity, 2,2-diphenyl-1-picryl-hydrazil (DPPH) radical scavenging capacity and ferric reducing antioxidant power of the P. amarus achieved under these optimal parameters were 87.3 mg of gallic acid equivalents (GAE) per gram of dried sample, 69.7 % , 134.9 mg of escin equivalents (EE) per gram of dried sample, 997.8, 604.7 and 437.3 all in mg of trolox equivalents (TE) per gram of dried sample, respectively, which were not significantly different from the predicted values (86.9 mg of GAE per gram of dried sample, 67.3 % , 123.5 mg of EE per gram of dried sample, 1013.3 mg of TE per gram of dried sample, 530.6 mg of TE per gram of dried sample and 423.5 mg of TE per gram of dried sample, respectively). Accordingly, the optimal microwave-assisted extraction parameters of 30 min, 14 s min−1 and 150 mL g−1 are recommended for the extraction of enriched phenolics from P. amarus for potential application in the nutraceutical and pharmaceutical industries. [ABSTRACT FROM AUTHOR]

Uncertainty analysis is used to make a quantitative evaluation of the reliability of statistically downscaled climate data representing local climate conditions in the northern coastlines of Canada. In this region, most global climate models (GCMs) have inherent weaknesses to adequately simulate the climate regime due to difficulty in resolving strong land/sea discontinuities or heterogeneous land cover. The performance of the multiple regression-based statistical downscaling model in reproducing the observed daily minimum/maximum temperature, and precipitation for a reference period (1961–1990) is evaluated using climate predictors derived from NCEP reanalysis data and those simulated by two coupled GCMs (the Canadian CGCM2 and the British HadCM3). The Wilcoxon Signed Rank test and bootstrap confidence-interval estimation techniques are used to perform uncertainty analysis on the downscaled meteorological variables. The results show that the NCEP-driven downscaling results mostly reproduced the mean and variability of the observed climate very well. Temperatures are satisfactorily downscaled from HadCM3 predictors while some of the temperatures downscaled from CGCM2 predictors are statistically significantly different from the observed. The uncertainty in precipitation downscaled with CGCM2 predictors is comparable to the ones downscaled from HadCM3. In general, all downscaling results reveal that the regression-based statistical downscaling method driven by accurate GCM predictors is able to reproduce the climate regime over these highly heterogeneous coastline areas of northern Canada. The study also shows the applicability of uncertainty analysis techniques in evaluating the reliability of the downscaled data for climate scenarios development. [ABSTRACT FROM AUTHOR]

An amendment to this paper has been published and can be accessed via a link at the top of the paper. [ABSTRACT FROM AUTHOR]

The improvement in adsorption/desorption of hydrofluorocarbons has implications for many heat transformation applications such as cooling, refrigeration, heat pumps, power generation, etc. The lack of chlorine in hydrofluorocarbons minimizes the lasting environmental damage to the ozone, with R134a (1,1,1,2-tetrafluoroethane) being used as the primary industrial alternative to commonly used Freon-12. The efficacy of novel adsorbents used in conjunction with R134a requires a deeper understanding of the host-guest chemical interaction. Metal-organic frameworks (MOFs) represent a newer class of adsorbent materials with significant industrial potential given their high surface area, porosity, stability, and tunability. In this work, we studied two benchmark MOFs, a microporous Ni-MOF-74 and mesoporous Cr-MIL-101. We employed a combined experimental and simulation approach to study the adsorption of R134a to better understand host-guest interactions using equilibrium isotherms, enthalpy of adsorption, Henry's coefficients, and radial distribution functions. The overall uptake was shown to be exceptionally high for Cr-MIL-101, >140 wt% near saturation while >50 wt% at very low partial pressures. For both MOFs, simulation data suggest that metal sites provide preferable adsorption sites for fluorocarbon based on favorable C-F ··· M+ interactions between negatively charged fluorine atoms of R134a and positively charged metal atoms of the MOF framework. [ABSTRACT FROM AUTHOR]