Sulfidation of metallic nanoparticles such as silver nanoparticles (AgNPs) released to the environment may be an important detoxification mechanism. Two types of AgNPs-an engineered polydisperse and ...aggregated AgNP powder, and a laboratory-synthesized, relatively monodisperse AgNP aqueous dispersion-were studied. The particles were sulfidized to varying degrees and characterized to determine the effect of initial AgNP polydispersity and aggregation state on AgNP sulfidation, and then exposed to Escherichia coli to determine if the degree of sulfidation of pristine AgNPs affects growth inhibition of bacteria. The extent of sulfidation was found to depend on the HS(-)/Ag ratio. However, for the same reaction times, the more monodisperse particles were fully transformed to Ag(2)S, and the polydisperse, aggregated particles were not fully sulfidized, thus preserving the toxic potential of Ag(0) in the aggregates. A higher Ag(2)S:Ag(0) ratio in the sulfidized nanoparticles resulted in less growth inhibition of E. coli over 6 h of exposure. These results suggest that the initial properties of AgNPs can affect sulfidation products, which in turn affect microbial growth inhibition, and that these properties should be considered in assessing the environmental impact of AgNPs.
Stocks of soil organic carbon represent a large component of the carbon cycle that may participate in climate change feedbacks, particularly on decadal and centennial timescales. For Earth system ...models (ESMs), the ability to accurately represent the global distribution of existing soil carbon stocks is a prerequisite for accurately predicting future carbon-climate feedbacks. We compared soil carbon simulations from 11 model centers to empirical data from the Harmonized World Soil Database (HWSD) and the Northern Circumpolar Soil Carbon Database (NCSCD). Model estimates of global soil carbon stocks ranged from 510 to 3040 Pg C, compared to an estimate of 1260 Pg C (with a 95% confidence interval of 890-1660 Pg C) from the HWSD. Model simulations for the high northern latitudes fell between 60 and 820 Pg C, compared to 500 Pg C (with a 95% confidence interval of 380-620 Pg C) for the NCSCD and 290 Pg C for the HWSD. Global soil carbon varied 5.9 fold across models in response to a 2.6-fold variation in global net primary productivity (NPP) and a 3.6-fold variation in global soil carbon turnover times. Model-data agreement was moderate at the biome level (R super(2) values ranged from 0.38 to 0.97 with a mean of 0.75); however, the spatial distribution of soil carbon simulated by the ESMs at the 1 degree scale was not well correlated with the HWSD (Pearson correlation coefficients less than 0.4 and root mean square errors from 9.4 to 20.8 kg C m super(-2)). In northern latitudes where the two data sets overlapped, agreement between the HWSD and the NCSCD was poor (Pearson correlation coefficient 0.33), indicating uncertainty in empirical estimates of soil carbon. We found that a reduced complexity model dependent on NPP and soil temperature explained much of the 1 degree spatial variation in soil carbon within most ESMs (R super(2) values between 0.62 and 0.93 for 9 of 11 model centers). However, the same reduced complexity model only explained 10% of the spatial variation in HWSD soil carbon when driven by observations of NPP and temperature, implying that other drivers or processes may be more important in explaining observed soil carbon distributions. The reduced complexity model also showed that differences in simulated soil carbon across ESMs were driven by differences in simulated NPP and the parameterization of soil heterotrophic respiration (inter-model R super(2) = 0.93), not by structural differences between the models. Overall, our results suggest that despite fair global-scale agreement with observational data and moderate agreement at the biome scale, most ESMs cannot reproduce grid-scale variation in soil carbon and may be missing key processes. Future work should focus on improving the simulation of driving variables for soil carbon stocks and modifying model structures to include additional processes.
Summary CNS metastases are the most common cause of malignant brain tumours in adults. Historically, patients with brain metastases have been excluded from most clinical trials, but their inclusion ...is now becoming more common. The medical literature is difficult to interpret because of substantial variation in the response and progression criteria used across clinical trials. The Response Assessment in Neuro-Oncology Brain Metastases (RANO-BM) working group is an international, multidisciplinary effort to develop standard response and progression criteria for use in clinical trials of treatment for brain metastases. Previous efforts have focused on aspects of trial design, such as patient population, variations in existing response and progression criteria, and challenges when incorporating neurological, neuro-cognitive, and quality-of-life endpoints into trials of patients with brain metastases. Here, we present our recommendations for standard response and progression criteria for the assessment of brain metastases in clinical trials. The proposed criteria will hopefully facilitate the development of novel approaches to this difficult problem by providing more uniformity in the assessment of CNS metastases across trials.
The molecular-level speciation of arsenic has been determined in a soil profile in the Massif Central near Auzon, France that was impacted by As-based pesticides by combining conventional techniques ...(XRD, selective chemical extractions) with X-ray absorption spectroscopy (XAS). The arsenic concentration is very high at the top (>7000 mg kg(-1)) and decreases rapidly downward to a few hundreds of milligrams per kilogram. A thin layer of schultenite (PbHAsO4), a lead arsenate commonly used as an insecticide until the middle of the 20th century, was found at 10 cm depth. Despite the occurrence of this As-bearing mineral, oxalate extraction indicated that more than 65% of the arsenic was released upon dissolution of amorphous iron oxides, suggesting a major association of arsenic with these phases within the soil profile. Since oxalate extraction cannot unambiguously distinguish among the various chemical forms of arsenic, these results were confirmed by a direct in situ determination of arsenic speciation using XAS analysis. XANES data indicate that arsenic occurs mainly as As(V) along the soil profile except for the topsoil sample where a minor amount (7%) of As(III) was detected. EXAFS spectra of soil samples were fit by linear combinations of model compounds spectra and by a shell-by-shell method. These procedures clearly confirmed that As(V) is mainly (at least 80 wt %) associated with amorphous Fe(III) oxides as coprecipitates within the soil profile. If any, the proportion of schultenite, which was evidenced by XRD in a separate thin white layer, does not account for more than 10 wt % of arsenic in soil samples. This study emphasizes the importance of iron oxides in restricting arsenic dispersal within soils following dissolution of primary As-bearing solids manufactured for use as pesticides and released into the soils.
The three-dimensional positions of atoms in protein molecules define their structure and their roles in biological processes. The more precisely atomic coordinates are determined, the more chemical ...information can be derived and the more mechanistic insights into protein function may be inferred. Electron cryo-microscopy (cryo-EM) single-particle analysis has yielded protein structures with increasing levels of detail in recent years
. However, it has proved difficult to obtain cryo-EM reconstructions with sufficient resolution to visualize individual atoms in proteins. Here we use a new electron source, energy filter and camera to obtain a 1.7 Å resolution cryo-EM reconstruction for a human membrane protein, the β3 GABA
receptor homopentamer
. Such maps allow a detailed understanding of small-molecule coordination, visualization of solvent molecules and alternative conformations for multiple amino acids, and unambiguous building of ordered acidic side chains and glycans. Applied to mouse apoferritin, our strategy led to a 1.22 Å resolution reconstruction that offers a genuine atomic-resolution view of a protein molecule using single-particle cryo-EM. Moreover, the scattering potential from many hydrogen atoms can be visualized in difference maps, allowing a direct analysis of hydrogen-bonding networks. Our technological advances, combined with further approaches to accelerate data acquisition and improve sample quality, provide a route towards routine application of cryo-EM in high-throughput screening of small molecule modulators and structure-based drug discovery.
Graphitizing anthracene-based cokes and non-graphitizing saccharose-based chars were processed at temperatures from 450°C to 2900°C at ambient pressure. This offers a whole set of samples that ...greatly differ in structure. Here, their structural evolution was monitored by combining XRD and visible (green) Raman spectroscopy as well as, for the first time, near-infrared Raman and synchrotron-based C-XANES spectroscopies. These different techniques provide complementary information especially regarding the spatial resolution they achieved. However, despite its importance, the quantitative comparison between the structural parameters extracted from these techniques is difficult. Based on a new signal deconvolution procedure to extract quantitative structural information from C-XANES data and the achievement of a new dataset on a complete series of graphitization, the reliability and the precision of the information which can be retrieved from each technique are discussed. C-XANES spectroscopy appears to provide reliable proxies for the extent of aromatic layers of graphitic compounds and an empirical calibration is proposed.
The goal of this study was to determine the effects of genetic variation in the organic cation transporter 1, OCT1, on the pharmacokinetics of the antidiabetic drug, metformin. Twenty healthy ...volunteers with known OCT1 genotype agreed to participate in the study. Each subject received two oral doses of metformin followed by collection of blood and urine samples. OCT1 genotypes had a significant (P<0.05) effect on metformin pharmacokinetics, with a higher area under the plasma concentration–time curve (AUC), higher maximal plasma concentration (Cmax), and lower oral volume of distribution (V/F) in the individuals carrying a reduced function OCT1 allele (R61C, G401S, 420del, or G465R). The effect of OCT1 on metformin pharmacokinetics in mice was less than in humans possibly reflecting species differences in hepatic expression level of the transporter. Our studies suggest that OCT1 genotype is a determinant of metformin pharmacokinetics.
Clinical Pharmacology & Therapeutics (2008) doi:10.1038/sj.clpt.6100275
Peripheral artery disease (PAD) is a common cardiovascular disorder that is frequently underdiagnosed, which can lead to poorer outcomes due to lower rates of medical optimization. We aimed to ...develop an automated tool to identify undiagnosed PAD and evaluate physician acceptance of a dashboard representation of risk assessment. Data were derived from electronic health records (EHR). We developed and compared traditional risk score models to novel machine learning models. For usability testing, primary and specialty care physicians were recruited and interviewed until thematic saturation. Data from 3168 patients with PAD and 16,863 controls were utilized. Results showed a deep learning model that utilized time engineered features outperformed random forest and traditional logistic regression models (average AUCs 0.96, 0.91 and 0.81, respectively), P < 0.0001. Of interviewed physicians, 75% were receptive to an EHR-based automated PAD model. Feedback emphasized workflow optimization, including integrating risk assessments directly into the EHR, using dashboard designs that minimize clicks, and providing risk assessments for clinically complex patients. In conclusion, we demonstrate that EHR-based machine learning models can accurately detect risk of PAD and that physicians are receptive to automated risk detection for PAD. Future research aims to prospectively validate model performance and impact on patient outcomes.
The U.S. Food and Drug Administration (FDA) Center for Devices and Radiological Health (CDRH) classifies personal lubricants as Class II medical devices. Because of this status and the nature of body ...contact common to personal lubricants, CDRH reviewers routinely recommend a standard biocompatibility testing battery that includes: an in vivo rabbit vaginal irritation (RVI) test; an in vivo skin sensitization test, such as the guinea pig maximization test (GPMT); and an in vivo acute systemic toxicity test using mice or rabbits. These tests are conducted using live animals, despite the availability of in vitro and other non-animal test methods that may be suitable replacements. The only test included in the biocompatibility battery currently conducted using in vitro assay(s) is cytotoxicity. FDA's recently launched Predictive Toxicology Roadmap calls for the optimization of non-animal methods for the safety evaluation of drugs, consumer products and medical devices. In line with these goals, a Consortium comprising the Institute for In Vitro Sciences, Inc. (IIVS), industry, the Consumer Healthcare Products Association (CHPA), and the PETA International Science Consortium (PETA-ISC) is qualifying the use of an in vitro testing method as replacement for the RVI test. Participating companies include manufacturers of personal lubricants and those interested in the advancement of non-animal approaches working collaboratively with the FDA CDRH to develop an in vitro testing approach that could be used in place of the RVI in pre-market submissions. Personal lubricants and vaginal moisturizers with diverse chemical and physical properties (e.g., formulation, viscosity, pH, and osmolality) in their final undiluted form will be the focus of the program. In vitro vaginal irritation data generated using commercially available human reconstructed vaginal tissue model(s) will be paired with existing in vivo RVI data and analyzed to develop a Prediction Model for the safety assessment of these products. This research plan has been accepted into the FDA CDRH Medical Device Development Tools (MDDT) program as a potential non-clinical assessment model (NAM). The proposed NAM aligns with the goals of the recently launched FDA Roadmap to integrate predictive toxicology methods into safety and risk assessment with the potential to replace or reduce the use of animal testing.
•A Consortium is qualifying the use of an in vitro testing method as replacement for the RVI test.•Personal lubricants and vaginal moisturizers in their final undiluted form will be the focus of the program.•A Prediction Model will be generated based on analysis of paired existing in vivo and new in vitro vaginal irritation data.•This research plan has been accepted into the FDA CDRH MDDT program as a potential NAM.
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