Degradation of difenoconazole in water and soil: Kinetics, degradation pathways, transformation products identification and ecotoxicity assessment

Difenoconazole is a widely used triazole fungicide that has been frequently detected in the environment, but comprehensive study about its environmental fate and toxicity of potential transformation products (TPs) is still lacking. Here, laboratory experiments were conducted to investigate the degradation kinetics, pathways, and toxicity of transformation products of difenoconazole. 12, 4 and 4 TPs generated by photolysis, hydrolysis and soil degradation were identified via UHPLC-QTOF/MS and the UNIFI software. Four intermediates TP295, TP295A, TP354A and TP387A reported for the first time were confirmed by purchase or synthesis of their standards, and they were further quantified using UHPLC-MS/MS in all tested samples. The main transformation reactions observed for difenoconazole were oxidation, dechlorination and hydroxylation in the environment. ECOSAR prediction and laboratory tests showed that the acute toxicities of four novel TPs on Brachydanio rerio, Daphnia magna and Selenastrum capricornutum are substantially lower than that of difenoconazole, while all the TPs except for TP277C were predicted chronically very toxic to fish, which may pose a potential threat to aquatic ecosystems. The results are important for elucidating the environmental fate of difenoconazole and assessing the environmental risks, and further provide guidance for scientific and reasonable use.acceptedVersio

Cathode–Electrolyte Interface Modification by Binder Engineering for High-Performance Aqueous Zinc-Ion Batteries

A stable cathode-electrolyte interface (CEI) is crucial for aqueous zinc-ion batteries (AZIBs), but it is less investigated. Commercial binder poly(vinylidene fluoride) (PVDF) is widely used without scrutinizing its suitability and cathode-electrolyte interface (CEI) in AZIBs. A water-soluble binder is developed that facilitated the in situ formation of a CEI protecting layer tuning the interfacial morphology. By combining a polysaccharide sodium alginate (SA) with a hydrophobic polytetrafluoroethylene (PTFE), the surface morphology, and charge storage kinetics can be confined from diffusion-dominated to capacitance-controlled processes. The underpinning mechanism investigates experimentally in both kinetic and thermodynamic perspectives demonstrate that the COO- from SA acts as an anionic polyelectrolyte facilitating the adsorption of Zn2+ ; meanwhile fluoride atoms on PTFE backbone provide hydrophobicity to break desolvation penalty. The hybrid binder is beneficial in providing a higher areal flux of Zn2+ at the CEI, where the Zn-Birnessite MnO2 battery with the hybrid binder exhibits an average specific capacity 45.6% higher than that with conventional PVDF binders; moreover, a reduced interface activation energy attained fosters a superior rate capability and a capacity retention of 99.1% in 1000 cycles. The hybrid binder also reduces the cost compared to the PVDF/NMP, which is a universal strategy to modify interface morphology

Area Deprivation index and Segregation On the Risk of Hiv: a Us Veteran Case-Control Study

BACKGROUND: Preventing HIV infection remains a critically important tool in the continuing fight against HIV/AIDS. The primary aim is to evaluate the effect and interactions between a composite area-level social determinants of health measure and an area-level measure of residential segregation on the risk of HIV/AIDS in U.S. Veterans. METHODS: Using the individual-level patient data from the U.S. Department of Veterans Affairs, we constructed a case-control study of veterans living with HIV/AIDS (VLWH) and age-, sex assigned at birth- and index date-matched controls. We geocoded patient\u27s residential address to ascertain their neighborhood and linked their information to two measures of neighborhood-level disadvantage: area deprivation index (ADI) and isolation index (ISOL). We used logistic regression to estimate the odds ratio (OR) and 95% confidence interval (CI) for comparing VLWH with matched controls. We performed analyses for the entire U.S. and separately for each U.S. Census division. FINDINGS: Overall, living in minority-segregated neighborhoods was associated with a higher risk of HIV (OR: 1.88 (95% CI: 1.79-1.97) while living in higher ADI neighborhoods was associated with a lower risk of HIV (OR: 0.88; 95% CI: 0.84-0.92). The association between living in a higher ADI neighborhood and HIV was inconsistent across divisions, while living in minority-segregated neighborhoods was consistently associated with increased risk across all divisions. In the interaction model, individuals from low ADI and high ISOL neighborhoods had a higher risk of HIV in three divisions: East South Central; West South Central, and Pacific. INTERPRETATION: Our results suggest that residential segregation may prevent people in disadvantaged neighborhoods from protecting themselves from HIV independent from access to health care. There is the need to advance knowledge about the neighborhood-level social-structural factors that influence HIV vulnerability toward developing interventions needed to achieve the goal of ending the HIV epidemic. FUNDING: US National Cancer Institute

The association between protease inhibitors and anal cancer outcomes in veterans living with HIV treated with definitive chemoradiation: a retrospective study

Background: The incidence of anal squamous cell carcinoma has been increasing, particularly in people living with HIV (PLWH). There is concern that radiosensitizing drugs, such as protease inhibitors, commonly used in the management of HIV, may increase toxicities in patients undergoing chemoradiation. This study examines treatment outcomes and toxicities in PLWH managed with and without protease inhibitors who are receiving chemoradiation for anal cancer. Methods: Patient demographic, HIV management, and cancer treatment information were extracted from multiple Veterans Affairs databases. Patients were also manually chart reviewed. Among PLWH undergoing chemoradiation for anal carcinoma, therapy outcomes and toxicities were compared between those treated with and without protease inhibitors at time of cancer treatment. Statistical analysis was performed using chi-square, Cox regression analysis, and logistic regression. Results: A total of 219 PLWH taking anti-retroviral therapy undergoing chemoradiation for anal cancer were identified and included in the final analysis. The use of protease inhibitors was not associated with any survival outcome including colostomy-free survival, progression-free survival, or overall survival (all adjusted hazard ratio p-values\u3e 0.05). Regarding toxicity, protease inhibitor use was not associated with an increased odds of hospitalizations or non-hematologic toxicities; however, protease inhibitor use was associated with increased hospitalizations for hematologic toxicities, including febrile neutropenia (p \u3c 0.01). Conclusion: The use of protease inhibitors during chemoradiation for anal carcinoma was not associated with any clinical outcome or increase in non-hematologic toxicity. Their use was associated with increased hospitalizations for hematologic toxicities. Further prospective research is needed to evaluate the safety and efficacy of protease inhibitors for patients undergoing chemoradiation

Characteristic Metabolic Alterations Identified in Primary Neurons Under High Glucose Exposure

Cognitive dysfunction is a central nervous system (CNS) complication of diabetes mellitus (DM) that is characterized by impaired memory and cognitive ability. An in-depth understanding of metabolic alterations in the brain associated with DM will facilitate our understanding of the pathogenesis of cognitive dysfunction. The present study used an in vitro culture of primary neurons in a high-glucose (HG) environment to investigate characteristic alterations in neuron metabolism using nuclear magnetic resonance (NMR)-based metabonomics. High performance liquid chromatography (HPLC) was also used to measure changes in the adenosine phosphate levels in the hippocampal regions of streptozotocin (STZ)-induced diabetic rats. Our results revealed significant elevations in phosphocholine and ATP production in neurons and decreased formate, nicotinamide adenine dinucleotide (NAD+), tyrosine, methionine, acetate and phenylalanine levels after HG treatment. However, the significant changes in lactate, glutamate, taurine and myo-inositol levels in astrocytes we defined previously in astrocytes, were not found in neurons, suggested cell-specific metabolic alterations. We also confirmed an astrocyte-neuron lactate shuttle between different compartments in the brain under HG conditions, which was accompanied by abnormal acetate transport. These alterations reveal specific information on the metabolite levels and transport processes related to neurons under diabetic conditions. Our findings contribute to the understanding of the metabolic alterations and underlying pathogenesis of cognitive decline in diabetic patients

Uptake kinetics and accumulation of pesticides in wheat (Triticum aestivum L.) : Impact of chemical and plant properties

Plant uptake is an important process in determining the transfer of pesticides through a food chain. Understanding how crops take up and translocate pesticides is critical in developing powerful models to predict pesticide accumulation in agricultural produce and potential human exposure. Herein, wheat was selected as a model plant species to investigate the uptake and distribution of eleven widely used pesticides in a hydroponic system as a function of time for 144 h. The time-dependent uptake kinetics of these pesticides were fitted with a first-order 1-compartment kinetic model. During 144 h, flusilazole and difenoconazole, with relative high log Kow (3.87 and 4.36, respectively), displayed higher root uptake rate constants (k). To clarify the role of root lipid content (flip) in plant accumulation of pesticides, we conducted a lipid normalization meta-analysis using data from this and previous studies, and found that the flip value was an important factor in predicting the root concentration factor (RCF) of pesticides. An improved correlation was observed between log RCF and log flipKow (R2 = 0.748, N = 26, P 3) during the uptake process. The quasi-equilibrium factor (αpt) was inversely related to log Kow (R2 = 0.773, N = 11, P < 0.001) suggesting a hydrophobicity-regulated uptake equilibrium. Findings from this study could facilitate crop-uptake model optimization. Integrating the pesticide Kow with plant root lipid content (flipKow) is better for predicting the root concentration factors of pesticides than just Kow

Logistic regression models for ordinal response: A study of self-efficacy in colorectal cancer screening

The ordinal logistic regression models are used to analyze the dependant variable with multiple outcomes that can be ranked, but have been underutilized. In this study, we describe four logistic regression models for analyzing the ordinal response variable. In this methodological study, the four regression models are proposed. The first model uses the multinomial logistic model. The second is adjacent-category logit model. The third is the proportional odds model and the fourth model is the continuation-ratio model. We illustrate and compare the fit of these models using data from the survey designed by the University of Texas, School of Public Health research project PCCaSO (Promoting Colon Cancer Screening in people 50 and Over), to study the patient’s confidence in the completion colorectal cancer screening (CRCS). The purpose of this study is two fold: first, to provide a synthesized review of models for analyzing data with ordinal response, and second, to evaluate their usefulness in epidemiological research, with particular emphasis on model formulation, interpretation of model coefficients, and their implications. Four ordinal logistic models that are used in this study include (1) Multinomial logistic model, (2) Adjacent-category logistic model [9], (3) Continuation-ratio logistic model [10], (4) Proportional logistic model [11]. We recommend that the analyst performs (1) goodness-of-fit tests, (2) sensitivity analysis by fitting and comparing different models

A Hybrid Seasonal Mechanism with a Chaotic Cuckoo Search Algorithm with a Support Vector Regression Model for Electric Load Forecasting

Providing accurate electric load forecasting results plays a crucial role in daily energy management of the power supply system. Due to superior forecasting performance, the hybridizing support vector regression (SVR) model with evolutionary algorithms has received attention and deserves to continue being explored widely. The cuckoo search (CS) algorithm has the potential to contribute more satisfactory electric load forecasting results. However, the original CS algorithm suffers from its inherent drawbacks, such as parameters that require accurate setting, loss of population diversity, and easy trapping in local optima (i.e., premature convergence). Therefore, proposing some critical improvement mechanisms and employing an improved CS algorithm to determine suitable parameter combinations for an SVR model is essential. This paper proposes the SVR with chaotic cuckoo search (SVRCCS) model based on using a tent chaotic mapping function to enrich the cuckoo search space and diversify the population to avoid trapping in local optima. In addition, to deal with the cyclic nature of electric loads, a seasonal mechanism is combined with the SVRCCS model, namely giving a seasonal SVR with chaotic cuckoo search (SSVRCCS) model, to produce more accurate forecasting performances. The numerical results, tested by using the datasets from the National Electricity Market (NEM, Queensland, Australia) and the New York Independent System Operator (NYISO, NY, USA), show that the proposed SSVRCCS model outperforms other alternative models