156 research outputs found
Heating of magnetic fluid systems driven by circularly polarized magnetic field
Cataloged from PDF version of article.A theory is presented to calculate the heat dissipation of a magnetic suspension, a ferrofluid, driven by7 circularly polarized magnetic field. Theory is tested by in vitro experiments and it is shown that, regardless of the character of the relaxation process, linearly and circularly polarized magnetic field excitations, having the same root-mean-square magnitude, are equivalent in terms of heating efficiency. (C) 2010 Elsevier B.V. All rights reserved
Circulating endothelial cells as biomarker for cardiovascular diseases.
Background: Endothelial dysfunction is involved in several cardiovascular diseases. Elevated levels of circulating endothelial cells (CECs) and low levels of endothelial progenitor cells (EPCs) have been described in different cardiovascular conditions, suggesting their potential use as diagnostic biomarkers for endothelial dysfunction. Compared to typical peripheral blood leukocyte subsets, CECs and EPCs occur at very low frequency. The reliable identification and characterization of CECs and EPCs is a prerequisite for their clinical use, however, a validated method to this purpose is still missing but a key for rare cell events. Objectives: To establish a validated flow cytometric procedure in order to quantify CECs and EPCs in human whole blood. Methods: In the establishment phase, the assay sensitivity, robustness, and the sample storage conditions were optimized as prerequisite for clinical use. In a second phase, CECs and EPCs were analyzed in heart failure with preserved (HFpEF) and reduced (HFrEF) ejection fraction, in arterial hypertension (aHT), and in diabetic nephropathy (DN) in comparison to age-matched healthy controls. Results: The quantification procedure for CECs and EPCs showed high sensitivity and reproducibility. CEC values resulted significantly increased in patients with DN and HFpEF in comparison to healthy controls. CEC quantification showed a diagnostic sensitivity of 90% and a sensitivity of 68.0%, 70.4%, and 66.7% for DN, HFpEF, and aHT, respectively. Conclusion: A robust and precise assay to quantify CECs and EPCs in pre-clinical and clinical studies has been established. CEC counts resulted to be a good diagnostic biomarker for DN and HFpEF
Encapsulation of a zinc phthalocyanine derivative in self-assembled peptide nanofibers
Cataloged from PDF version of article.In this article, we demonstrate encapsulation of octakis(hexylthio) zinc phthalocyanine molecules by non-covalent supramolecular organization within self-assembled peptide nanofibers. Peptide nanofibers containing octakis(hexylthio) zinc phthalocyanine molecules were obtained via a straight-forward one-step self-assembly process under aqueous conditions. Nanofiber formation results in the encapsulation and organization of the phthalocyanine molecules, promoting ultrafast intermolecular energy transfer. The morphological, mechanical, spectroscopic and non-linear optical properties of phthalocyanine containing peptide nanofibers were characterized by TEM, SEM, oscillatory rheology, UV-Vis, fluorescence, ultrafast pump-probe and circular dichroism spectroscopy techniques. The ultrafast pump-probe experiments of octakis(hexylthio) zinc phthalocyanine molecules indicated pH controlled non-linear optical characteristics of the encapsulated molecules within self-assembled peptide nanofibers. This method can provide a versatile approach for bottom-up fabrication of supramolecular organic electronic devices. © 2012 The Royal Society of Chemistry
Sequence diversity within the HA-1 gene as detected by melting temperature assay without oligonucleotide probes
BACKGROUND: The minor histocompatibility antigens (mHags) are self-peptides derived from common cellular proteins and presented by MHC class I and II molecules. Disparities in mHags are a potential risk for the development of graft-versus-host disease (GvHD) in the recipients of bone marrow from HLA-identical donors. Two alleles have been identified in the mHag HA-1. The correlation between mismatches of the mHag HA-1 and GvHD has been suggested and methods to facilitate large-scale testing were afterwards developed. METHODS: We used sequence specific primer (SSP) PCR and direct sequencing to detect HA-1 gene polymorphisms in a sample of 131 unrelated Italian subjects. We then set up a novel melting temperature (Tm) assay that may help identification of HA-1 alleles without oligonucleotide probes. RESULTS: We report the frequencies of HA-1 alleles in the Italian population and the presence of an intronic 5 base-pair deletion associated with the immunogeneic allele HA-1(H). We also detected novel variable sites with respect to the consensus sequence of HA-1 locus. Even though recombination/gene conversion events are documented, there is considerable linkage disequilibrium in the data. The gametic associations between HA-1(R/H )alleles and the intronic 5-bp ins/del polymorphism prompted us to try the Tm analysis with SYBR(® )Green I. We show that the addition of dimethylsulfoxide (DMSO) during the assay yields distinct patterns when amplicons from HA-1(H )homozygotes, HA-1(R )homozygotes, and heterozygotes are analysed. CONCLUSION: The possibility to use SYBR(® )Green I to detect Tm differences between allelic variants is attractive but requires great caution. We succeeded in allele discrimination of the HA-1 locus using a relatively short (101 bp) amplicon, only in the presence of DMSO. We believe that, at least in certain assets, Tm assays may benefit by the addition of DMSO or other agents affecting DNA strand conformation and stability
Calcineurin Interacts with PERK and Dephosphorylates Calnexin to Relieve ER Stress in Mammals and Frogs
Background: The accumulation of misfolded proteins within the endoplasmic reticulum (ER) triggers a cellular process known as the Unfolded Protein Response (UPR). One of the earliest responses is the attenuation of protein translation. Little is known about the role that Ca 2+ mobilization plays in the early UPR. Work from our group has shown that cytosolic phosphorylation of calnexin (CLNX) controls Ca 2+ uptake into the ER via the sarco-endoplasmic reticulum Ca 2+-ATPase (SERCA) 2b. Methodology/Principal Findings: Here, we demonstrate that calcineurin (CN), a Ca 2+ dependent phosphatase, associates with the (PKR)-like ER kinase (PERK), and promotes PERK auto-phosphorylation. This association, in turn, increases the phosphorylation level of eukaryotic initiation factor-2 a (eIF2-a) and attenuates protein translation. Data supporting these conclusions were obtained from co-immunoprecipitations, pull-down assays, in-vitro kinase assays, siRNA treatments and [ 35 S]-methionine incorporation measurements. The interaction of CN with PERK was facilitated at elevated cytosolic Ca 2+ concentrations and involved the cytosolic domain of PERK. CN levels were rapidly increased by ER stressors, which could be blocked by siRNA treatments for CN-Aa in cultured astrocytes. Downregulation of CN blocked subsequent ER-stress-induced increases in phosphorylated elF2-a. CN knockdown in Xenopus oocytes predisposed them to induction of apoptosis. We also found that CLNX was dephosphorylated by CN when Ca 2+ increased. These data were obtained from [c 32 P]-CLN
Evaluation of Combined Artificial Intelligence and Radiologist Assessment to Interpret Screening Mammograms
Importance: Mammography screening currently relies on subjective human interpretation. Artificial intelligence (AI) advances could be used to increase mammography screening accuracy by reducing missed cancers and false positives. Objective: To evaluate whether AI can overcome human mammography interpretation limitations with a rigorous, unbiased evaluation of machine learning algorithms. Design, Setting, and Participants: In this diagnostic accuracy study conducted between September 2016 and November 2017, an international, crowdsourced challenge was hosted to foster AI algorithm development focused on interpreting screening mammography. More than 1100 participants comprising 126 teams from 44 countries participated. Analysis began November 18, 2016. Main Outcomes and Measurements: Algorithms used images alone (challenge 1) or combined images, previous examinations (if available), and clinical and demographic risk factor data (challenge 2) and output a score that translated to cancer yes/no within 12 months. Algorithm accuracy for breast cancer detection was evaluated using area under the curve and algorithm specificity compared with radiologists' specificity with radiologists' sensitivity set at 85.9% (United States) and 83.9% (Sweden). An ensemble method aggregating top-performing AI algorithms and radiologists' recall assessment was developed and evaluated. Results: Overall, 144 231 screening mammograms from 85 580 US women (952 cancer positive ≤12 months from screening) were used for algorithm training and validation. A second independent validation cohort included 166 578 examinations from 68 008 Swedish women (780 cancer positive). The top-performing algorithm achieved an area under the curve of 0.858 (United States) and 0.903 (Sweden) and 66.2% (United States) and 81.2% (Sweden) specificity at the radiologists' sensitivity, lower than community-practice radiologists' specificity of 90.5% (United States) and 98.5% (Sweden). Combining top-performing algorithms and US radiologist assessments resulted in a higher area under the curve of 0.942 and achieved a significantly improved specificity (92.0%) at the same sensitivity. Conclusions and Relevance: While no single AI algorithm outperformed radiologists, an ensemble of AI algorithms combined with radiologist assessment in a single-reader screening environment improved overall accuracy. This study underscores the potential of using machine learning methods for enhancing mammography screening interpretation
Mitochondria localization induced self-assembly of peptide amphiphiles for cellular dysfunction
Achieving spatiotemporal control of molecular self-assembly associated with actuation of biological functions inside living cells remains a challenge owing to the complexity of the cellular environments and the lack of characterization tools. We present, for the first time, the organelle-localized self-assembly of a peptide amphiphile as a powerful strategy for controlling cellular fate. A phenylalanine dipeptide (FF) with a mitochondria-targeting moiety, triphenyl phosphonium (Mito-FF), preferentially accumulates inside mitochondria and reaches the critical aggregation concentration to form a fibrous nanostructure, which is monitored by confocal laser scanning microscopy and transmission electron microscopy. The Mito-FF fibrils induce mitochondrial dysfunction via membrane disruption to cause apoptosis. The organelle-specific supramolecular system provides a new opportunity for therapeutics and in-depth investigations of cellular functions.clos
A MSFD complementary approach for the assessment of pressures, knowledge and data gaps in Southern European Seas : the PERSEUS experience
PERSEUS project aims to identify the most relevant pressures exerted on the ecosystems of the Southern
European Seas (SES), highlighting knowledge and data gaps that endanger the achievement of SES Good
Environmental Status (GES) as mandated by the Marine Strategy Framework Directive (MSFD). A complementary
approach has been adopted, by a meta-analysis of existing literature on pressure/impact/knowledge
gaps summarized in tables related to the MSFD descriptors, discriminating open waters from coastal
areas. A comparative assessment of the Initial Assessments (IAs) for five SES countries has been also
independently performed. The comparison between meta-analysis results and IAs shows similarities
for coastal areas only. Major knowledge gaps have been detected for the biodiversity, marine food
web, marine litter and underwater noise descriptors. The meta-analysis also allowed the identification
of additional research themes targeting research topics that are requested to the achievement of GES.
2015 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license.peer-reviewe
Managing Learner’s Affective States in Intelligent Tutoring Systems
Abstract. Recent works in Computer Science, Neurosciences, Education, and Psychology have shown that emotions play an important role in learning. Learner’s cognitive ability depends on his emotions. We will point out the role of emotions in learning, distinguishing the different types and models of emotions which have been considered until now. We will address an important issue con-cerning the different means to detect emotions and introduce recent approaches to measure brain activity using Electroencephalograms (EEG). Knowing the influ-ence of emotional events on learning it becomes important to induce specific emo-tions so that the learner can be in a more adequate state for better learning or memorization. To this end, we will introduce the main components of an emotion-ally intelligent tutoring system able to recognize, interpret and influence learner’s emotions. We will talk about specific virtual agents that can influence learner’s emotions to motivate and encourage him and involve a more cooperative work, particularly in narrative learning environments. Pushing further this paradigm, we will present the advantages and perspectives of subliminal learning which inter
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