Ionic Liquid Design and Process Simulation for Decarbonization of Shale Gas

Ionic liquids (ILs) have been receiving increasing attention as a potential decarbonization solvent. However, the enormous number of potential ILs that can be synthesized makes it a challenging task to search for the best IL for CO₂ removal from methane. In this work, a method was proposed to screen suitable ILs based on the COSMO-RS (conductor-like screening model for real solvents) model, an absorption mechanism, and experimental data. Besides the Henry’s constant, the viscosity and toxicity of ILs should also be taken into consideration for an industrial decarbonization process. Furthermore, process simulation was performed to evaluate the new IL-based decarbonization technology. Considering CO₂ solubility, CO₂/CH₄ selectivity and toxicity and viscosity of ILs, [bmim]­[NTf₂] has been screened to be the potential solvent among 90 classes of ILs. Based on reliable experimental data, a rigorous thermodynamic model was established. The simulation results have been found to agree well with the available experimental results. Two process flow sheet options, use of two single-stage flash operations or a multistage flash operation following the absorber, have been simulated and assessed. Compared with the well-known MDEA (methyldiethanolamine) process for CO₂ capture, the single-stage and multistage process alternatives would reduce the total energy consumption by 42.8% and 66.04%, respectively

A simplified multi-model statistical approach for predicting the effects of forest management on land surface temperature in Fennoscandia

Forests interact with the local climate through a variety of biophysical mechanisms. Observational and modelling studies have investigated the effects of forested vs. non-forested areas, but the influence of forest management on surface temperature has received far less attention owing to the inherent challenges to adapt climate models to cope with forest dynamics. Further, climate models are complex and highly parameterized, and the time and resource intensity of their use limit applications. The availability of simple yet reliable statistical models based on high resolution maps of forest attributes representative of different development stages can link individual forest management practices to local temperature changes, and ultimately support the design of improved strategies. In this study, we investigate how forest management influences local surface temperature (LSTs) in Fennoscandia through a set of machine learning algorithms. We find that more developed forests are typically associated with higher LST than young or undeveloped forests. The mean multi-model estimates from our statistical system can accurately reproduce the observed LST. Relative to the present state of Fennoscandian forests, fully develop forests are found to induce an annual mean warming of 0.26 °C (0.03/0.69 °C as 5th/95th percentile), and an average cooling effect in the summer daytime from -0.85 to -0.23 °C (depending on the model). On the contrary, a scenario with undeveloped forests induces an annual average cooling of -0.29 °C (-0.61/-0.01 °C), but daytime warming in the summer that can be higher than 1 °C. A weak annual mean cooling of -0.01 °C is attributed to forest harvest from 2015 to 2018, with an increased daytime temperature in summer of about 0.04 °C. Overall, this approach is a flexible option to study effects of forest management on LST that can be applied at various scales and for alternative management scenarios, thereby helping to improve local management strategies with consideration of effects on local climate

Expression and processing of fluorescent fusion proteins of amyloid precursor protein (APP)

AbstractProcessing of β-amyloid precursor protein (APP) by β- and γ-secretases in neurons produces amyloid-β (Aβ), whose excess accumulation leads to Alzheimer's disease (AD). Knowledge on subcellular trafficking pathways of APP and its fragments is important for the understanding of AD pathogenesis. We designed fusion proteins comprising a C-terminal fragment of APP (app) and fluorescent proteins GFP (G) and DsRed (D) to permit the tracking of the fusion proteins and fragments in cells. CAD cells expressing these proteins emitted colocalized green and red fluorescence and produce ectodomains, sGapp and sRapp, and Aβ, whose level was reduced by inhibitors of β- and γ-secretases. The presence of GappR in endosomes was observed via colocalization with Rab5. These observations indicated that the fusion proteins were membrane inserted, transported in vesicles and proteolytically processed by the same mechanism for APP. By attenuating fusion protein synthesis with cycloheximide, individual fluorescent colors from the C-terminus of the fusion proteins appeared in the cytosol which was strongly suppressed by β-secretase inhibitor, suggesting that the ectodomains exit the cell rapidly (t1/2 about 20min) while the C-terminal fragments were retained longer in cells. In live cells, we observed the fluorescence of the ectodomains located between parental fusion proteins and plasma membrane, suggesting that these ectodomain positions are part of their secretion pathway. Our results indicate that the native ectodomain does not play a decisive role for the key features of APP trafficking and processing and the new fusion proteins may lead to novel insights in intracellular activities of APP

Spatially and taxonomically explicit characterisation factors for greenhouse gas emission impacts on biodiversity

In life-cycle impact assessment, currently available characterisation factors (CF) for climate change impacts on biodiversity are highly simplified and do not consider spatial and taxonomic differentiation of species or local climate variability. We develop the first spatially and taxonomically specific CFs for the impacts of 20 GHGs on biodiversity considering 26,648 species across terrestrial and marine ecosystems. Generally, CFs are higher in the tropics, and marine species are affected more severely than terrestrial ones. When global GHG emissions from 2020 are assessed in a scenario with a global temperature rise of 3 °C by 2100, an average of 0.25%, 0.15% and 0.03% of species are negatively affected in 2100 from CO2, CH4, and N2O emissions, respectively, across the globe. The new CFs can be used at different levels of spatial and taxonomic aggregation to quantify co-benefits for biodiversity of climate change mitigation in tools such as life-cycle assessment, input-output analyses, or integrated assessment models

Therapy by physician–pharmacist combination and economic returns for cancer pain management in China: a cost-effectiveness analysis

Objective: To examine whether joint management of cancer pain by physicians and pharmacists in clinics provides economic advantages from the perspective of the Chinese healthcare system.Methods: From February 2018 to March 2020, 100 patients who visited the joint cancer pain clinic at the Xiangya Hospital of Central South University were included. These patients were randomly assigned to either the control or intervention groups. The control group received regular outpatient services from a physician, while the intervention group received regular outpatient services from a physician and medication education provided by a pharmacist. The study considered various direct costs, including drug expenses, physician-pharmacist outpatient services, adverse event management, consultations, examinations, and readmissions. The outcome indicators considered were the cancer pain control rate and the reduction in pain scores. Decision tree modeling, single-factor sensitivity analysis, and probabilistic sensitivity analysis were performed to evaluate the cost-effectiveness of joint physician-pharmacist outpatient services compared to physician-alone outpatient services.Results: The intervention group showed a significantly higher cancer pain control rate than the control group (0.69 vs. 0.39, p = 0.03). In the decision tree model, the intervention group had a significantly lower pain score than the control group (0.23 vs. 0.14). The cost per person in the intervention group was $165.39, while it was$191.1 per person in the control group. The univariate sensitivity analysis showed that the cost of self-management for patients in the control group was identified as the primary sensitivity factor. Probabilistic sensitivity analysis indicated that the joint clinic group had a favorable incremental cost-effectiveness compared to the physician clinic group. In addition, the probabilistic sensitivity analysis demonstrated an absolute advantage in the incremental cost-effectiveness of the joint clinic group over the outpatient physician group.Conclusion: The participation of pharmacists in joint cancer pain clinic services led to improved pain management for patients, demonstrating a clear advantage in terms of cost-effectiveness

Neurodevelopmental toxicity assessments of alkyl phenanthrene and Dechlorane Plus co-exposure in zebrafish.

Alkyl phenanthrene (A-Phen) and Dechlorane Plus (DP) are ubiquitous environmental pollutants that widely co-exist in the environment. It has been established that both A-Phen and DP elicit neurotoxicity, but the potential interactive toxicity of these contaminants is not well-known. To determine whether a mixture of A-Phen and DP would exhibit interactive effects on neurodevelopment, we co-exposed 3-methylphenanthrene (3-MP), a representative of A-Phen, with DP. Our results illustrated that exposure to 5 or 20 μg/L 3-MP alone or in combination with 60 μg/L DP caused neurobehavioral anomalies in zebrafish. In accordance with the behavioral deficits, 3-MP alone or co-exposed with DP significantly decreased axonal growth of secondary motoneurons, altered intracellular Ca2+ homeostasis and induced cell apoptosis in the muscle of zebrafish. Additionally, 3-MP alone or co-exposed with DP significantly increased reactive oxygen species (ROS) and the mRNA levels of apoptosis-related genes. These findings indicate that 3-MP alone or co-exposed with DP induces neurobehavioral deficits through the combined effects on neuronal connectivity and muscle function. Chemical analysis revealed significant increases in 3-MP and DP bioaccumulation in zebrafish co-exposed with 3-MP and DP. Elevated bioaccumulation resulting from mixture exposure may represent a significant contribution of the synergistic effects observed in combined chemical exposure

Late-life depression: Epidemiology, phenotype, pathogenesis and treatment before and during the COVID-19 pandemic

Late-life depression (LLD) is one of the most common mental disorders among the older adults. Population aging, social stress, and the COVID-19 pandemic have significantly affected the emotional health of older adults, resulting in a worldwide prevalence of LLD. The clinical phenotypes between LLD and adult depression differ in terms of symptoms, comorbid physical diseases, and coexisting cognitive impairments. Many pathological factors such as the imbalance of neurotransmitters, a decrease in neurotrophic factors, an increase in β-amyloid production, dysregulation of the hypothalamic-pituitary-adrenal axis, and changes in the gut microbiota, are allegedly associated with the onset of LLD. However, the exact pathogenic mechanism underlying LLD remains unclear. Traditional selective serotonin reuptake inhibitor therapy results in poor responsiveness and side effects during LLD treatment. Neuromodulation therapies and complementary and integrative therapies have been proven safe and effective for the treatment of LLD. Importantly, during the COVID-19 pandemic, modern digital health intervention technologies, including socially assistive robots and app-based interventions, have proven to be advantageous in providing personal services to patients with LLD