Statistical modeling of global geogenic arsenic contamination in groundwater

Contamination of groundwaters with geogenic arsenic poses a major health risk to millions of people. Although the main geochemical mechanisms of arsenic mobilization are well understood, the worldwide scale of affected regions is still unknown. In this study we used a large database of measured arsenic concentration in groundwaters (around 20,000 data points) from around the world as well as digital maps of physical characteristics such as soil, geology, climate, and elevation to model probability maps of global arsenic contamination. A novel rule-based statistical procedure was used to combine the physical data and expert knowledge to delineate two process regions for arsenic mobilization: "reducing" and "high-pH/ oxidizing". Arsenic concentrations were modeled in each region using regression analysis and adaptive neuro-fuzzy inferencing followed by Latin hypercube sampling for uncertainty propagation to produce probability maps. The derived global arsenic models could benefit from more accurate geologic information and aquifer chemical/physical information. Using some proxy surface information, however, the models explained 77% of arsenic variation in reducing regions and 68% of arsenic variation in high-pH/oxidizing regions. The probability maps based on the above models correspond well with the known contaminated regions around the world and delineate new untested areas that have a high probability of arsenic contamination. Notable among these regions are South East and North West of China in Asia, Central Australia, New Zealand, Northern Afghanistan, and Northern Mali and Zambia in Africa.     

Seasonal and diurnal variation of PM2.5 apparent particle density in urban air in Augsburg, Germany

The apparent particle density of particulate matter with aerodynamic diameter < 2.5 microm (rho2.5) was determined at an urban site in Augsburg, Germany and its correlation with chemical composition and meteorological conditions was investigated. rho2.5 showed strong day-to-day variation from 1.05 to 2.36 g cm(-3) (5 to 95% percentile), and nearly 64% of the daily variability could be explained by a multiple variable regression model. A minimum in the morning and afternoon (about 1.5 g cm(-3)), and a maximum (near 1.8 g cm(-3)) during midday was observed. The minima represent fresh primary aerosol emissions, which were related to traffic soot particles with low density due to their agglomerate structure, especially observed in the early morning hours of weekdays. The maximum is likely due to increased secondary particle production and the presence of more aged particles with the built-up of the convectively mixed boundary layer. rho2.5 has the potential to serve as a crude tracer for chemical composition and atmospheric processing and might play an important role when considering the associations between health effects and ambient particles.     

Phytochemical composition and in vitro antimicrobial and antioxidant activities of essential oils of three endemic Soqotraen Boswellia species

The chemical composition of three essential oils obtained from the barks of three endemic Boswellia species namely, Boswellia dioscorides, Boswellia elongata and Boswellia socotrana which were collected from the Soqotra Island (Yemen), was investigated. In parallel to that evaluation of their antimicrobial and antioxidant activities was also carried out. The investigation led to the identification of 72, 70 and 67 constituents for B.dioscorides, B. elongata, and B. socotrana, respectively. The B. dioscorides oil was found to have a high content of monoterpene hydrocarbons (32.8%) with α-thujene (9.3%) and α-pinene (8.3%) as main components. Whereas, the essential oil of B. elongata was characterised by high diterpene content (31.7%), in which incensol (14.8%) was found to be the major constituent. On the other hand, the oil obtained from the B. socotrana was found to be predominated of monoterpene hydrocarbons (26.4%) and oxygenated monoterpenes (30.7%) with p-cymene (13.0%), 2-hydroxy-5-methoxy-acetophenone (16.3%) and camphor (11.6%). All essential oils possessed antimicrobial activity especially against Gram-positive bacteria with MIC-values between 1.8 and 17.2 mg/ml. Furthermore, the DPPH-radical scavenging assay exhibited only weak antioxidant activities (28%) at 1.0 mg/ml.     

Design,Synthesis, and in vitro Evaluation of P2X7 Antagonists

The P2X7 receptor is a promising target for the treatment of various diseases due to its significant role in inflammation and immune cell signaling. This work describes the design, synthesis, and in vitro evaluation of a series of novel derivatives bearing diverse scaffolds as potent P2X7 antagonists. Our approach was based on structural modifications of reported (adamantan-1-yl)methylbenzamides able to inhibit the receptor activation. The adamantane moieties and the amide bond were replaced, and the replacements were evaluated by a ligand-based pharmacophore model. The antagonistic potency of the synthesized analogues was assessed by two-electrode voltage clamp experiments, using Xenopus laevis oocytes that express the human P2X7 receptor. SAR studies suggested that the replacement of the adamantane ring by an aryl-cyclohexyl moiety afforded the most potent antagonists against the activation of the P2X7 cation channel, with analogue 2-chloro-N-[1-(3-(nitrooxymethyl)phenyl)cyclohexyl)methyl]benzamide ( 56 ) exhibiting the best potency with an IC₅₀ value of 0.39 μM.     

A Variant in the Osteoprotegerin Gene Is Associated with Coronary Atherosclerosis in Patients with Rheumatoid Arthritis: Results from a Candidate Gene Study

Objective: Patients with rheumatoid arthritis (RA) have accelerated atherosclerosis, but there is limited information about the genetic contribution to atherosclerosis in this population. Therefore, we examined the association between selected genetic polymorphisms and coronary atherosclerosis in patients with RA. Methods: Genotypes for single-nucleotide polymorphisms (SNPs) in 152 candidate genes linked with autoimmune or cardiovascular risk were measured in 140 patients with RA. The association between the presence of coronary artery calcium (CAC) and SNP allele frequency was assessed by logistic regression with adjustment for age, sex, and race. To adjust for multiple comparisons, a false discovery rate (FDR) threshold was set at 20%. Results: Patients with RA were 54 ± 11 years old and predominantly Caucasian (89%) and female (69%). CAC was present in 70 patients (50%). A variant in rs2073618 that encodes an Asn3Lys missense substitution in the osteoprotegerin gene (OPG, TNFRSF11B) was significantly associated with the presence of CAC (OR = 4.09, p < 0.00026) and withstands FDR correction. Conclusion: Our results suggest that a polymorphism of the TNFRSF11B gene, which encodes osteoprotegerin, is associated with the presence of coronary atherosclerosis in patients with RA. Replication of this finding in independent validation cohorts will be of interest.     

Thin Film Tl-Based HTS Microwave Devices

Linear microstrip resonators suffer from high peak current density inside the resonators which limit the power handling characteristics. To realise higher power filters for cellular applications it is possible to use two dimensional microstrip resonators (such as disks) to equalise the internal current distribution. We have designed and tested such microstrip resonators, fabricated from TBCCO 2212 thin films deposited by RF sputtering onto 10×10mm and 20×20mm LaAlO₃, substrates. The R_s of such films has been measured at 24 GHz using a sapphire dielectric resonator and shown to be less than 500 scaled to 10 GHz and at 80K. Q values of 3-12 GHz disk resonators have demonstrated considerable improvements when compared to both linear HTS microstrip resonators and comparable copper disk resonators. Additionally, the power handling of such resonators has been shown to be superior to that of conventional linear resonators fabricated from similar material.     

Prioritizing Groundwater Monitoring in Data Sparse Regions using Atanassov Intuitionistic Fuzzy Sets (A-IFS)

Water quality index (WQI) is a single measure that is commonly used to prioritize water wells and manage groundwater resources. WQI is pragmatic as it combines several water quality parameters into a single index. However, the process of aggregation is imprecise and suffers from uncertainties in measurements and subjective specification of weights. The goal of this study is to demonstrate how Atanassov’s Intuitionistic Fuzzy Sets (A-IFS) can be used to aggregate water quality parameters into a composite index to rank and prioritize groundwater wells. The A-IFS weighted geometric mean (A-IFS-WGM) method and the A-IFS based Technique for Order of Preference by Similarity to Ideal Solution (A-IFS-TOPSIS) using Euclidean (A-IFS-TOPSIS-E) and Hamming (A-IFS-TOPSIS-H) are introduced and illustrated to prioritize and rank water supply wells in a fast growing yet poorly studied area in Guntur, Andhra Pradesh, India. The concept of A-IFS entropy is also presented to directly ascertain weights from the data. This objective selection of weights from the data eliminates the subjectivity and difficulties associated with assigning relative importance to different water quality parameters. The results of the study indicate that the weights obtained using the entropy methods are consistent with the geochemical characteristics of the regional aquifer. The A-IFS-WGM method is more sensitive to weights compared to the A-IFS-TOPSIS methods which are influenced to a larger extent by the membership and non-membership values (ratings). Special consideration must be placed on ascribing the hesitation margin of the decision maker and identifying the membership values for non-preference as the methods exhibit greater sensitivity to these factors. The developed methods provide pragmatic data-driven approaches to prioritize and rank groundwater wells within a monitoring network.     

Multimodal Precision Imaging of Pulmonary Nanoparticle Delivery in Mice: Dynamics of Application,Spatial Distribution,and Dosimetry

Targeted delivery of nanomedicine/nanoparticles (NM/NPs) to the site of disease (e.g., the tumor or lung injury) is of vital importance for improved therapeutic efficacy. Multimodal imaging platforms provide powerful tools for monitoring delivery and tissue distribution of drugs and NM/NPs. This study introduces a preclinical imaging platform combining X‐ray (two modes) and fluorescence imaging (three modes) techniques for time‐resolved in vivo and spatially resolved ex vivo visualization of mouse lungs during pulmonary NP delivery. Liquid mixtures of iodine (contrast agent for X‐ray) and/or (nano)particles (X‐ray absorbing and/or fluorescent) are delivered to different regions of the lung via intratracheal instillation, nasal aspiration, and ventilator‐assisted aerosol inhalation. It is demonstrated that in vivo propagation‐based phase‐contrast X‐ray imaging elucidates the dynamic process of pulmonary NP delivery, while ex vivo fluorescence imaging (e.g., tissue‐cleared light sheet fluorescence microscopy) reveals the quantitative 3D drug/particle distribution throughout the entire lung with cellular resolution. The novel and complementary information from this imaging platform unveils the dynamics and mechanisms of pulmonary NM/NP delivery and deposition for each of the delivery routes, which provides guidance on optimizing pulmonary delivery techniques and novel‐designed NM for targeting and efficacy.