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Baseline Interleukin-6 and 8 Predict Response and Survival in Patients with Advanced Hepatocellular Carcinoma Treated with Sorafenib Monotherapy:An Exploratory Post-hoc Analysis of the SORAMIC Trial
No full textPurpose To explore the potential correlation between baseline interleukin (IL) values and overall survival or objective response in patients with hepatocellular carcinoma (HCC) receiving sorafenib. Methods A subset of patients with HCC undergoing sorafenib monotherapy within a prospective multicenter phase II trial (SORAMIC, sorafenib treatment alone vs. combined with Y90 radioembolization) underwent baseline IL-6 and IL-8 assessment before treatment initiation. In this exploratory post-hoc analysis, the best cut-off points for baseline IL-6 and IL-8 values predicting overall survival (OS) were evaluated, as well as correlation with the objective response. Results Forty-seven patients (43 male) with a median OS of 13.8 months were analyzed. Cut-off values of 8.58 and 57.9 pg/mL most effectively predicted overall survival for IL-6 and IL-8, respectively. Patients with high IL-6 (HR, 4.1 [1.9-8.9], p<0.001) and IL-8 (HR, 2.4 [1.2-4.7], p=0.009) had significantly shorter overall survival than patients with low IL values. Multivariate analysis confirmed IL-6 (HR, 2.99 [1.22-7.3], p=0.017) and IL-8 (HR, 2.19 [1.02-4.7], p=0.044) as independent predictors of OS. Baseline IL-6 and IL-8 with respective cut-off values predicted objective response rates according to mRECIST in a subset of 42 patients with follow-up imaging available (IL-6, 46.6% vs. 19.2%, p=0.007; IL-8, 50.0% vs. 17.4%, p=0.011). Conclusion IL-6 and IL-8 baseline values predicted outcomes of sorafenib-treated patients in this well-characterized prospective cohort of the SORAMIC-trial. We suggest that the respective cut-off values might serve for validation in larger cohorts, potentially offering guidance for improved patient selection
Exposure to ambient air pollution during childhood and subsequent risk of self-harm: a national cohort study
No full textA growing body of evidence indicates that exposure to air pollution not only impacts on physical health but is also linked with a deterioration in mental health. We conducted the first study to investigate exposure to ambient particulate matter with an aerodynamic diameter of less than 2.5 μm (PM2.5) and nitrogen dioxide (NO2) during childhood and subsequent self-harm risk. The study cohort included persons born in Denmark between January 1, 1979 and December 31, 2006 (N = 1,424,670), with information on daily exposures to PM2.5 and NO2 at residence from birth to 10th birthday. Follow-up began from 10th birthday until first hospital-presenting self-harm episode, death, or December 31, 2016, whichever came first. Incidence rate ratios estimated by Poisson regression models revealed a dose relationship between increasing PM2.5 exposure and rising self-harm risk. Exposure to 17-19 μg/m3 of PM2.5 on average per day from birth to 10th birthday was associated with a 1.45 fold (95% CI 1.37-1.53) subsequently elevated self-harm risk compared with a mean daily exposure of <13 μg/m3, whilst those exposed to 19 μg/m3 or above on average per day had a 1.59 times (1.45-1.75) elevated risk. Higher mean daily exposure to NO2 during childhood was also linked with increased self-harm risk, but the dose-response relationship observed was less evident than for PM2.5. Covariate adjustment attenuated the associations, but risk remained independently elevated. Although causality cannot be assumed, these novel findings indicate a potential etiological involvement of ambient air pollution in the development of mental ill health.</p
Exploring the impacts of the inequality of water permit allocation and farmers’ behaviors on the performance of an agricultural water market
No full textWater markets are considered as effective mechanisms to support efficient use of limited water resources and to increase crop production in agricultural systems. This study presents an agent-based modeling (ABM) framework to explore the performance of an agricultural water market under the joint influence of water permit allocation and farmers’ behaviors. The ABM employs a power law function to simulate water permit distribution among farmers for any given level of inequality measured by the Gini coefficient. Farmers’ irrigation behavior (i.e., sensitivity to soil dryness) and bidding behaviors (i.e., degree of rent seeking and learning rate coefficient) are explicitly incorporated into the ABM to represent farmers’ decision-making in a water market based on double auction. Through a set of scenario analyses in a study area in Texas, we find that the water market performance to increase basin-level crop production is constrained by a joint effect of, especially the complex and non-linear interplay between the inequality of water permit allocation, farmers’ behaviors, and hydrological conditions. The potential market performance is higher when water permits are more unequally distributed. The relative market performance is higher when the inequality of water allocation is at a moderate level. The modeling results can advance our understanding of the key contributing factors in market transactions, and provide policy implications to assess the comparative advantage between institutional development and farmers’ behavioral change for improving market performance. This study also provides model implications for future research to draw more robust conclusions about market benefits in the real world
Improved risk-stratification for ventricular arrhythmias and sudden death in non-ischemic dilated cardiomyopathy
No full textBackground Risk-stratification for ventricular arrhythmias (VA) and sudden death (SD) in non-ischemic dilated cardiomyopathy (DCM) remains sub-optimal. Objectives To provide an improved risk-stratification algorithm for VA and SD in DCM. Methods Retrospective cohort study of consecutive patients with DCM who underwent cardiac magnetic resonance with late gadolinium enhancement (LGE) at two tertiary referral centers. The combined arrhythmic endpoint included appropriate implantable defibrillator (ICD) therapies, sustained ventricular tachycardia, resuscitated cardiac arrest and SD. Results In 1165 patients with median follow-up of 36 months, LGE was an independent and strong predictor of the arrhythmic endpoint (HR 9.9, p<0.001). This association was consistent across all strata of left ventricular ejection fraction (LVEF). Epicardial LGE, transmural LGE and combined septal and free-wall LGE were all associated with heightened risk. A simple algorithm combining LGE and three LVEF strata (≤20%, 21%-35%, >35%) was significantly superior to LVEF with the 35% cut-off (Harrell’s C 0.8 vs 0.69, AUC 0.82 vs 0.7, p<0.001) and reclassified the arrhythmic risk of 34% of DCM patients: LGE- patients with LVEF 21%-35% had low risk (annual event rate 0.7%) while those with high-risk LGE distributions and LVEF>35% had significantly higher risk (annual event rate 3%, p=0.007). Conclusions In a large cohort of patients with DCM, LGE was found to be a significant, consistent and strong predictor of VA or SD. Specific high-risk LGE distributions were identified. A new clinical algorithm integrating LGE and LVEF significantly improved the risk-stratification for VA and SD, with relevant implications for ICD allocation
Realistic Utility Functions Prove Difficult for State-of-the-Art Interactive Multiobjective Optimization Algorithms
No full textImprovements to the design of interactive Evolutionary Multiobjective Algorithms (iEMOAs) are unlikely without quantitative assessment of their behaviour in realistic settings. Experiments with human decision-makers (DMs) are of limited scope due to the difficulty of isolating individual biases and replicating the experiment with enough subjects, and enough times, to obtain confidence in the results. Simulation studies may help to overcome these issues, but they require the use of realistic simulations of decision-makers. Machine decision-makers (MDMs) provide a way to carry out such simulation studies, however, studies so far have relied on simple utility functions. In this paper, we analyse and compare two state-of-the-art iEMOAs by means of a MDM that uses a sigmoid-shaped utility function. This sigmoid utility function is based on psychologically realistic models from behavioural economics, and replicates several realistic human behaviours. Our findings are that, on a variety of well-known benchmarks with two and three objectives, the two iEMOAs do not consistently recover the most-preferred points. We hope that these findings provide an impetus for more directed design and analysis of future iEMOAs
High Weissenberg number simulations with incompressible Smoothed Particle Hydrodynamics and the log-conformation formulation
No full textViscoelastic flows occur widely, and numerical simulations of them are important for a range of industrial applications. Simulations of viscoelastic flows are more challenging than their Newtonian counterparts due to the presence of exponential gradients in polymeric stress fields, which can lead to catastrophic instabilities if not carefully handled. A key development to overcome this issue is the log-conformation formulation, which has been applied to a range of numerical methods, but not previously applied to Smoothed Particle Hydrodynamics (SPH). Here we present a 2D incompressible SPH algorithm for viscoelastic flows which, for the first time, incorporates a log-conformation formulation with an elasto-viscous stress splitting (EVSS) technique. The resulting scheme enables simulations of flows at high Weissenberg numbers (accurate up to Wi=85 for Poiseuille flow). The method is robust, and able to handle both internal and free-surface flows, and a range of linear and non-linear constitutive models. Several test cases are considerd included flow past a periodic array of cylinders and jet buckling. This presents a significant step change in capabilties compared to previous SPH algorithms for viscoelastic flows, and has the potential to simulate a wide range of new and challenging applications
Electrostatic Perturbations from the Protein Affect C-H Bond Strengths of the Substrate and Enable Negative Catalysis in the TmpA Biosynthesis Enzyme
No full textThe nonheme iron dioxygenase 2-(trimethylammonio)- ethylphosphonate dioxygenase (TmpA) is an enzyme involved in the regio- and chemoselective hydroxylation at the C1-position of the substrate as part of the biosynthesis of glycine betaine in bacteria and carnitine in humans. To understand how the enzyme avoids breaking the weak C2-H bond in favor of C1-hydroxylation, we set up a cluster model of 242 atoms representing the first and secondcoordination sphere of the metal center and substrate binding pocket and investigated possible reaction mechanisms of substrate activation by an iron(IV)-oxo species by density functional theory methods. In agreement with experimental product distributions, the calculations predict a favorable C1-hydroxylation pathway. The calculations show that the selectivity is guided through electrostatic perturbations inside the protein from charged residues, external electric fields and electric dipole moments. In particular, charged residues influence and perturb the homolytic bond strength of the C1-H and C2-H bonds of the substrate, and strongly strengthens the C2-H bond in the substrate-bound orientation
Enrolment of older cancer patients in early phase clinical trials – an observational study on the experience in the north west of England
No full textIntroduction: Older patients represent the majority of cancer patients but are under-represented in trials, particularly early phase clinical trials (EPCTs). Material and Methods: Observational retrospective study of patients referred for EPCTs (January-December 2018) at a specialist cancer centre in the United Kingdom. The primary aim was to analyse the successful enrolment into EPCTs according to age (<65/65+). The secondary aims were to identify enrolment obstacles and the outcomes of enrolled patients. Patient data was analysed at: referral; in-clinic assessment; and after successful enrolment. Amongst patients assessed in clinic, a sample was defined by randomly matching the older cohort with the younger cohort (1:1) by tumour type. Results: 555 patients were referred for EPCTs with a median age of 60 years, of whom 471 were assessed in new patient clinics (38% were 65+). From those assessed, a randomly tumour-matched sample of 318 patients (159 per age cohort) was selected. Older patients had a significantly higher comorbidity score measured by ACE-27 (p<0.0001), lived closer to the hospital (p=0.045) and were referred at a later point in their cancer management (p=0.002). There was no difference in suitability for EPCTs according to age with overall 84% deemed suitable. For patients successfully enrolled into EPCTs there was no difference between age cohorts (20.1% vs 22.6% for younger and older, respectively; p=0.675) and no significant differences in their safety and efficacy outcomes. Discussion: Older age did not affect the enrolment into EPCTs. However, the selected minority referred for EPCTs suggests a pre-selection upstream by primary oncologists
Pore-Scale Modelling of Fluid-Rock Chemical Interactions in Shale during Hydraulic Fracturing
No full textDuring the hydraulic fracturing process in unconventional shale gas reservoirs, chemical interactions between the hydraulic fracturing fluid (HFF) and the shale rock could result in mineral precipitation and dissolution reactions, potentially influencing the gas transport by dissolving or clogging the fractures. The pore-scale distribution of the minerals, especially the highly reactive ones such as calcite, in the shale matrix can impact the structural evolution of the shale rocks. In the present study, a pore-scale reactive transport model is built to investigate the impact of the pore-scale distribution of calcite on the structural alteration of the shales. The alteration of the shales is caused by the barite precipitation, and the dissolution of calcite and pyrite. The simulation results show that the calcite dissolution leads to a permeability enhancement. The permeability enhancement for the shales with coarser calcite grains is more pronounced than that for the shales with finer grains of calcite. The results also indicate that the extent of the permeability enhancement is even more noticeable if the HFF is injected with a higher velocity. The fluid chemistry analysis indicates that the fluid pH for the shale with the fine grains of calcite is higher than that of the shale with the coarse calcite grains and that the injection of the HFF with a higher flowrate leads to the lower pH values. The calcite dissolution observed in the simulations mainly occurs near the inlet. For the shale with the finer calcite grains, barite precipitation also occurs mostly close to the inlet but for the shale with coarser calcite grains, barite precipitation extends more into the domain. This penetration depth increases when the HFF is injected with a higher velocity. In addition to the effect of the calcite distribution, we also used the pore-scale model to study the effect of the calcite content on the structural evolution of the shales. The results from these simulations showed that a higher calcite content can result in higher pH values, higher permeabilities, and also more barite precipitation in the domain
Novel eco-efficient reactive distillation process for dimethyl carbonate production by indirect alcoholysis of urea
No full textDimethyl carbonate is an eco-friendly essential chemical that can be sustainably produced from CO2, which is available from carbon capture activities or can even be captured from the air. The rapid increase in dimethyl carbonate demand is driven by the fast growth of polycarbonates, solvent, pharmaceutical, and lithium-ion battery industries. Dimethyl carbonate can be produced from CO2 through various chemical pathways, but the most convenient route reported is the indirect alcoholysis of urea. Previous research used techniques such as heat integration and reactive distillation to reduce the energy use and costs, but the use of an excess of methanol in the trans-esterification step led to an energy intensive extractive distillation required to break the dimethyl carbonate – methanol azeotrope. This work shows that the production of dimethyl carbonate by indirect alcoholysis of urea can be improved by using an excess of propylene carbonate (instead of an excess of methanol) – a neat feat that we showed it requires only 2.64 kWh/kg dimethyl carbonate in a reaction-separation-recycle process – and a reactive distillation column that effectively replaces two conventional distillation columns and the reactor for dimethyl carbonate synthesis. Therefore, less equipment is required, the methanol - dimethyl carbonate azeotrope does not need to be recycled, and the overall savings are higher. Moreover, we propose the use of a reactive distillation column in a heat integrated process to obtain high purity dimethyl carbonate (>99.8% wt.). The energy requirement is reduced by heat integration to just 1.25 kWh/kg dimethyl carbonate, which is about 52% lower than the reaction-separation-recycle process. To benefit from the energy savings, the dynamics and control of the process are provided for ±10% changes in the nominal rate of 32 ktpy dimethyl carbonate, and for uncertainties in reaction kinetics