Comparison of bacteria in different metabolic states by micro-Raman spectroscopy

It was shown that several metabolic states of bacteria with various characteristics such as chemical composition participate in the formation of biofilms. To study the connections and differences among different bacterial metabolic states, five species of bacteria in exponential phase, stationary phase and biofilm have been compared and investigated by micro-Raman spectroscopy. The spectral differences between different metabolic states showed that the chemical composition varied among those metabolic states. Moreover, as can be shown by the spectral differences and principal components (PCs), different species and strains of bacteria behave differently. Furthermore, a principal component analysis (PCA) combined with support vector machines (SVM) was applied to distinguish species of bacteria within the same metabolic states. Our study provides valuable data for the comparison of bacteria between different metabolic states utilizing micro-Raman spectroscopy in combination with chemometrics models

Comparison of Different Label-Free Raman Spectroscopy Approaches for the Discrimination of Clinical MRSA and MSSA Isolates

Methicillin-resistant Staphylococcus aureus (MRSA) is classified as one of the priority pathogens that threaten human health. Resistance detection with conventional microbiological methods takes several days, forcing physicians to administer empirical antimicrobial treatment that is not always appropriate. A need exists for a rapid, accurate, and cost-effective method that allows targeted antimicrobial therapy in limited time. In this pilot study, we investigate the efficacy of three different label-free Raman spectroscopic approaches to differentiate methicillin-resistant and -susceptible clinical isolates of S. aureus (MSSA). Single-cell analysis using 532 nm excitation was shown to be the most suitable approach since it captures information on the overall biochemical composition of the bacteria, predicting 87.5% of the strains correctly. UV resonance Raman microspectroscopy provided a balanced accuracy of 62.5% and was not sensitive enough in discriminating MRSA from MSSA. Excitation of 785 nm directly on the petri dish provided a balanced accuracy of 87.5%. However, the difference between the strains was derived from the dominant staphyloxanthin bands in the MRSA, a cell component not associated with the presence of methicillin resistance. This is the first step toward the development of label-free Raman spectroscopy for the discrimination of MRSA and MSSA using single-cell analysis with 532 nm excitation. IMPORTANCE Label-free Raman spectra capture the high chemical complexity of bacterial cells. Many different Raman approaches have been developed using different excitation wavelength and cell analysis methods. This study highlights the major importance of selecting the most suitable Raman approach, capable of providing spectral features that can be associated with the cell mechanism under investigation. It is shown that the approach of choice for differentiating MRSA from MSSA should be single-cell analysis with 532 nm excitation since it captures the difference in the overall biochemical composition. These results should be taken into consideration in future studies aiming for the development of label-free Raman spectroscopy as a clinical analytical tool for antimicrobial resistance determination

Secure Data Aggregation in Wireless Sensor Networks. Homomorphism versus Watermarking Approach

International audienceWireless sensor networks are now in widespread use to monitor regions, detect events and acquire information. Since the deployed nodes are separated, they need to cooperatively communicate sensed data to the base station. Hence, transmissions are a very energy consuming operation. To reduce the amount of sending data, an aggregation approach can be applied along the path from sensors to the sink. However, usually the carried information contains confidential data. Therefore, an end-to-end secure aggregation approach is required to ensure a healthy data reception. End-to-end encryption schemes that support operations over cypher-text have been proved important for private party sensor network implementations. These schemes offer two main advantages: end-to-end concealment of data and ability to operate on cipher text, then no more decryption is required for aggregation. Unfortunately, nowadays these methods are very complex and not suitable for sensor nodes having limited resources. In this paper, we propose a secure end-to-end encrypted-data aggregation scheme. It is based on elliptic curve cryptography that exploits a smaller key size. Additionally, it allows the use of higher number of operations on cypher-texts and prevents the distinction between two identical texts from their cryptograms. These properties permit to our approach to achieve higher security levels than existing cryptosystems in sensor networks. Our experiments show that our proposed secure aggregation method significantly reduces computation and communication overhead and can be practically implemented in on-the-shelf sensor platforms. By using homomorphic encryption on elliptic curves, we thus have realized an efficient and secure data aggregation in sensor networks. Lastly, to enlarge the aggregation functions that can be used in a secure wireless sensor network, a watermarking-based authentication scheme is finally proposed

Reactive Oxygen Species Suppress Cardiac NaV1.5 Expression through Foxo1

NaV1.5 is a cardiac voltage-gated Na+ channel αsubunit and is encoded by the SCN5a gene. The activity of this channel determines cardiac depolarization and electrical conduction. Channel defects, including mutations and decrease of channel protein levels, have been linked to the development of cardiac arrhythmias. The molecular mechanisms underlying the regulation of NaV1.5 expression are largely unknown. Forkhead box O (Foxo) proteins are transcriptional factors that bind the consensus DNA sequences in their target gene promoters and regulate the expression of these genes. Comparative analysis revealed conserved DNA sequences, 5′-CAAAACA-3′ (insulin responsive element, IRE), in rat, mouse and human SCN5a promoters with the latter two containing two overlapping Foxo protein binding IREs, 5′-CAAAACAAAACA-3′. This finding led us to hypothesize that Foxo1 regulates NaV1.5 expression by directly binding the SCN5a promoter and affecting its transcriptional activity. In the present study, we determined whether Foxo1 regulates NaV1.5 expression at the transcriptional level and also defined the role of Foxo1 in hydrogen peroxide (H2O2)-mediated NaV1.5 suppression in HL-1 cardiomyocytes using chromatin immunoprecipitation (ChIP), constitutively nuclear Foxo1 expression, and RNAi Foxo1 knockdown as well as whole cell voltage-clamp recordings. ChIP with anti-Foxo1 antibody and follow-up semi-quantitative PCR with primers flanking Foxo1 binding sites in the proximal SCN5a promoter region clearly demonstrated enrichment of DNA, confirming Foxo1 recruitment to this consensus sequence. Foxo1 mutant (T24A/S319A-GFP, Foxo1-AA-GFP) was retained in nuclei, leading to a decrease of NaV1.5 expression and Na+ current, while silencing of Foxo1 expression by RNAi resulted in the augmentation of NaV1.5 expression. H2O2 significantly reduced NaV1.5 expression by promoting Foxo1 nuclear localization and this reduction was prevented by RNAi silencing Foxo1 expression. These studies indicate that Foxo1 negatively regulates NaV1.5 expression in cardiomyocytes and reactive oxygen species suppress NaV1.5 expression through Foxo1

Capillary Proliferation in Systemic-Sclerosis-Related Pulmonary Fibrosis: Association with Pulmonary Hypertension

We sought to determine if any histopathologic component of the pulmonary microcirculation can distinguish systemic sclerosis (SSc)-related pulmonary fibrosis (PF) with and without pulmonary hypertension (PH)

Sensitivity and limitations of structures from X-ray and neutron-based diffraction analyses of transition metal oxide lithium-battery electrodes

© 2017 The Electrochemical Society. Lithium transition metal oxides are an important class of electrode materials for lithium-ion batteries. Binary or ternary (transition) metal doping brings about new opportunities to improve the electrode's performance and often leads tomore complex stoichiometries and atomic structures than the archetypal LiCoO2. Rietveld structural analyses of X-ray and neutron diffraction data is a widely-used approach for structural characterization of crystalline materials. However, different structural models and refinement approaches can lead to differing results, and some parameters can be difficult to quantify due to the inherent limitations of the data. Here, through the example of LiNi0.8Co0.15Al0.05O2(NCA), we demonstrated the sensitivity of various structural parameters in Rietveld structural analysis to different refinement approaches and structural models, and proposed an approach to reduce refinement uncertainties due to the inexact X-ray scattering factors of the constituent atoms within the lattice. This refinement approach was implemented for electrochemically-cycled NCA samples and yielded accurate structural parameters using only X-ray diffraction data. The present work provides the best practices for performing structural refinement of lithium transition metal oxides