A Comparative Study of Hollow Copper Sulfide Nanoparticles and Hollow Gold Nanospheres on Degradability and Toxicity

Gold and copper nanoparticles have been widely investigated for photothermal therapy of cancer. However, degradability and toxicity of these nanoparticles remain concerns. Here, we compare hollow CuS nanoparticles (HCuSNPs) with hollow gold nanospheres (HAuNS) in similar particle sizes and morphology following intravenous administration to mice. The injected pegylated HCuSNPs (PEG-HCuSNPs) are eliminated through both hepatobiliary (67 percentage of injected dose, %ID) and renal (23 %ID) excretion within one month postinjection. By contrast, 3.98 %ID of Au is excreted from liver and kidney within one month after iv injection of pegylated HAuNS (PEG-HAuNS). Comparatively, PEG-HAuNS are almost nonmetabolizable, while PEG-HCuSNPs are considered biodegradable nanoparticles. PEG-HCuSNPs do not show significant toxicity by histological or blood chemistry analysis. Principal component analysis and 2-D peak distribution plots of data from matrix-assisted laser desorption ionization-time-of-flight imaging mass spectrometry (MALDI-TOF IMS) of liver tissues demonstrated a reversible change in the proteomic profile in mice receiving PEG-HCuSNPs. This is attributed to slow dissociation of Cu ion from CuS nanoparticles along with effective Cu elimination for maintaining homeostasis. Nonetheless, an irreversible change in the proteomic profile is observed in the liver from mice receiving PEG-HAuNS by analysis of MALDI-TOF IMS data, probably due to the nonmetabolizability of Au. This finding correlates with the elevated serum lactate dehydrogenase at 3 months after PEG-HAuNS injection, indicating potential long-term toxicity. The comparative results between the two types of nanoparticles will advance the development of HCuSNPs as a new class of biodegradable inorganic nanomaterials for photothermal therapy

Thermodynamics and dynamics of the formation of spherical lipidic vesicles

We propose a free energy expression accounting for the formation of spherical vesicles from planar lipidic membranes and derive a Fokker-Planck equation for the probability distribution describing the dynamics of vesicle formation. We found that formation may occur as an activated process for small membranes and as a transport process for sufficiently large membranes. We give explicit expressions for the transition rates and the characteristic time of vesicle formation in terms of the relevant physical parameters.Comment: 14pgs, 6 figures, sendo to Jour. Phys. Bio

A microscale protein NMR sample screening pipeline

As part of efforts to develop improved methods for NMR protein sample preparation and structure determination, the Northeast Structural Genomics Consortium (NESG) has implemented an NMR screening pipeline for protein target selection, construct optimization, and buffer optimization, incorporating efficient microscale NMR screening of proteins using a micro-cryoprobe. The process is feasible because the newest generation probe requires only small amounts of protein, typically 30–200 μg in 8–35 μl volume. Extensive automation has been made possible by the combination of database tools, mechanization of key process steps, and the use of a micro-cryoprobe that gives excellent data while requiring little optimization and manual setup. In this perspective, we describe the overall process used by the NESG for screening NMR samples as part of a sample optimization process, assessing optimal construct design and solution conditions, as well as for determining protein rotational correlation times in order to assess protein oligomerization states. Database infrastructure has been developed to allow for flexible implementation of new screening protocols and harvesting of the resulting output. The NESG micro NMR screening pipeline has also been used for detergent screening of membrane proteins. Descriptions of the individual steps in the NESG NMR sample design, production, and screening pipeline are presented in the format of a standard operating procedure

Decoding Unattended Fearful Faces with Whole-Brain Correlations: An Approach to Identify Condition-Dependent Large-Scale Functional Connectivity

Processing of unattended threat-related stimuli, such as fearful faces, has been previously examined using group functional magnetic resonance (fMRI) approaches. However, the identification of features of brain activity containing sufficient information to decode, or “brain-read”, unattended (implicit) fear perception remains an active research goal. Here we test the hypothesis that patterns of large-scale functional connectivity (FC) decode the emotional expression of implicitly perceived faces within single individuals using training data from separate subjects. fMRI and a blocked design were used to acquire BOLD signals during implicit (task-unrelated) presentation of fearful and neutral faces. A pattern classifier (linear kernel Support Vector Machine, or SVM) with linear filter feature selection used pair-wise FC as features to predict the emotional expression of implicitly presented faces. We plotted classification accuracy vs. number of top N selected features and observed that significantly higher than chance accuracies (between 90–100%) were achieved with 15–40 features. During fearful face presentation, the most informative and positively modulated FC was between angular gyrus and hippocampus, while the greatest overall contributing region was the thalamus, with positively modulated connections to bilateral middle temporal gyrus and insula. Other FCs that predicted fear included superior-occipital and parietal regions, cerebellum and prefrontal cortex. By comparison, patterns of spatial activity (as opposed to interactivity) were relatively uninformative in decoding implicit fear. These findings indicate that whole-brain patterns of interactivity are a sensitive and informative signature of unattended fearful emotion processing. At the same time, we demonstrate and propose a sensitive and exploratory approach for the identification of large-scale, condition-dependent FC. In contrast to model-based, group approaches, the current approach does not discount the multivariate, joint responses of multiple functional connections and is not hampered by signal loss and the need for multiple comparisons correction

ENIGMA-anxiety working group : Rationale for and organization of large-scale neuroimaging studies of anxiety disorders

Altres ajuts: Anxiety Disorders Research Network European College of Neuropsychopharmacology; Claude Leon Postdoctoral Fellowship; Deutsche Forschungsgemeinschaft (DFG, German Research Foundation, 44541416-TRR58); EU7th Frame Work Marie Curie Actions International Staff Exchange Scheme grant 'European and South African Research Network in Anxiety Disorders' (EUSARNAD); Geestkracht programme of the Netherlands Organization for Health Research and Development (ZonMw, 10-000-1002); Intramural Research Training Award (IRTA) program within the National Institute of Mental Health under the Intramural Research Program (NIMH-IRP, MH002781); National Institute of Mental Health under the Intramural Research Program (NIMH-IRP, ZIA-MH-002782); SA Medical Research Council; U.S. National Institutes of Health grants (P01 AG026572, P01 AG055367, P41 EB015922, R01 AG060610, R56 AG058854, RF1 AG051710, U54 EB020403).Anxiety disorders are highly prevalent and disabling but seem particularly tractable to investigation with translational neuroscience methodologies. Neuroimaging has informed our understanding of the neurobiology of anxiety disorders, but research has been limited by small sample sizes and low statistical power, as well as heterogenous imaging methodology. The ENIGMA-Anxiety Working Group has brought together researchers from around the world, in a harmonized and coordinated effort to address these challenges and generate more robust and reproducible findings. This paper elaborates on the concepts and methods informing the work of the working group to date, and describes the initial approach of the four subgroups studying generalized anxiety disorder, panic disorder, social anxiety disorder, and specific phobia. At present, the ENIGMA-Anxiety database contains information about more than 100 unique samples, from 16 countries and 59 institutes. Future directions include examining additional imaging modalities, integrating imaging and genetic data, and collaborating with other ENIGMA working groups. The ENIGMA consortium creates synergy at the intersection of global mental health and clinical neuroscience, and the ENIGMA-Anxiety Working Group extends the promise of this approach to neuroimaging research on anxiety disorders

The Design and Redesign of an Online SocioConstructivist Course on Engineering Management: The Role of Learning Scenarios and Learning Analytics

This chapter focuses on the design and redesign of an online engineering management course, based on a socio-constructivist approach. At first, the theoretical and contextual premises will be presented with a focus on the suggested teaching and learning methods to acquire domain-related knowledge and crucial skills and on the importance of learning scenario to support an effective learning design. After the background introduction, a user case will be described, focusing on the course online environment and its tools, on the proposed pedagogical strategies and above all, on how instructors can obtain and analyze useful educational data from various sources. Finally, some redesign recommendations will be provided to better use educational data for continuous course improvement

Differentiating tumor heterogeneity in formalin-fixed paraffin-embedded (FFPE) prostate adenocarcinoma tissues using principal component analysis of matrix-assisted laser desorption/ionization imaging mass spectral data

Rationale: Many patients with adenocarcinoma of the prostate present with advanced and metastatic cancer at the time of diagnosis. There is an urgent need to detect biomarkers that will improve the diagnosis and prognosis of this disease. Matrix-assisted laser desorption/ionization imaging mass spectrometry (MALDI-IMS) is playing a key role in cancer research and it can be useful to unravel the molecular profile of prostate cancer biopsies. Methods: MALDI imaging data sets are highly complex and their interpretation requires the use of multivariate statistical methods. In this study, MALDI-IMS technology, sequential principal component analysis (PCA) and two-dimensional (2-D) peak distribution tests were employed to investigate tumor heterogeneity in formalin-fixed paraffin-embedded (FFPE) prostate cancer biopsies. Results: Multivariate statistics revealed a number of mass ion peaks obtained from different tumor regions that were distinguishable from the adjacent normal regions within a given specimen. These ion peaks have been used to generate ion images and visualize the difference between tumor and normal regions. Mass peaks at m/z 3370, 3441, 3447 and 3707 exhibited stronger ion signals in the tumor regions. Conclusions: This study reports statistically significant mass ion peaks unique to tumor regions in adenocarcinoma of the prostate and adds to the clinical utility of MALDI-IMS for analysis of FFPE tissue at a molecular level that supersedes all other standard histopathologic techniques for diagnostic purposes used in the current clinical practice. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd

A comparative study of hollow copper sulfide nanoparticles and hollow gold nanospheres on degradability and toxicity

Gold and copper nanoparticles have been widely investigated for photothermal therapy of cancer. However, degradability and toxicity of these nanoparticles remain concerns. Here, we compare hollow CuS nanoparticles (HCuSNPs) with hollow gold nanospheres (HAuNS) in similar particle sizes and morphology following intravenous administration to mice. The injected pegylated HCuSNPs (PEG-HCuSNPs) are eliminated through both hepatobiliary (67 percentage of injected dose, %ID) and renal (23 %ID) excretion within one month postinjection. By contrast, 3.98 %ID of Au is excreted from liver and kidney within one month after iv injection of pegylated HAuNS (PEG-HAuNS). Comparatively, PEG-HAuNS are almost nonmetabolizable, while PEG-HCuSNPs are considered biodegradable nanoparticles. PEG-HCuSNPs do not show significant toxicity by histological or blood chemistry analysis. Principal component analysis and 2-D peak distribution plots of data from matrix-assisted laser desorption ionization-time-of-flight imaging mass spectrometry (MALDI-TOF IMS) of liver tissues demonstrated a reversible change in the proteomic profile in mice receiving PEG-HCuSNPs. This is attributed to slow dissociation of Cu ion from CuS nanoparticles along with effective Cu elimination for maintaining homeostasis. Nonetheless, an irreversible change in the proteomic profile is observed in the liver from mice receiving PEG-HAuNS by analysis of MALDI-TOF IMS data, probably due to the nonmetabolizability of Au. This finding correlates with the elevated serum lactate dehydrogenase at 3 months after PEG-HAuNS injection, indicating potential long-term toxicity. The comparative results between the two types of nanoparticles will advance the development of HCuSNPs as a new class of biodegradable inorganic nanomaterials for photothermal therapy. © 2013 American Chemical Society