Mycobacterium tuberculosis Responds to Chloride and pH as Synergistic Cues to the Immune Status of its Host Cell

PubMed ID: 23592993This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited

A novel satellite mission concept for upper air water vapour, aerosol and cloud observations using integrated path differential absorption LiDAR limb sounding

We propose a new satellite mission to deliver high quality measurements of upper air water vapour. The concept centres around a LiDAR in limb sounding by occultation geometry, designed to operate as a very long path system for differential absorption measurements. We present a preliminary performance analysis with a system sized to send 75 mJ pulses at 25 Hz at four wavelengths close to 935 nm, to up to 5 microsatellites in a counter-rotating orbit, carrying retroreflectors characterized by a reflected beam divergence of roughly twice the emitted laser beam divergence of 15 µrad. This provides water vapour profiles with a vertical sampling of 110 m; preliminary calculations suggest that the system could detect concentrations of less than 5 ppm. A secondary payload of a fairly conventional medium resolution multispectral radiometer allows wide-swath cloud and aerosol imaging. The total weight and power of the system are estimated at 3 tons and 2,700 W respectively. This novel concept presents significant challenges, including the performance of the lasers in space, the tracking between the main spacecraft and the retroreflectors, the refractive effects of turbulence, and the design of the telescopes to achieve a high signal-to-noise ratio for the high precision measurements. The mission concept was conceived at the Alpbach Summer School 2010

Multisensor data fusion for joint people tracking and identification with a service robot

Tracking and recognizing people are essential skills modern service robots have to be provided with. The two tasks are generally performed independently, using ad-hoc solutions that first estimate the location of humans and then proceed with their identification. The solution presented in this paper, instead, is a general framework for tracking and recognizing people simultaneously with a mobile robot, where the estimates of the human location and identity are fused using probabilistic techniques. Our approach takes inspiration from recent implementations of joint tracking and classification, where the considered targets are mainly vehicles and aircrafts in military and civilian applications. We illustrate how people can be robustly tracked and recognized with a service robot using an improved histogram-based detection and multisensor data fusion. Some experiments in real challenging scenarios show the good performance of our solution

Synergistic Antifungal Study of PEGylated Graphene Oxides and Copper Nanoparticles against Candida albicans

© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).The coupling reactions of polyethylene glycol (PEG) with two different nano-carbonaceous materials, graphene oxide (GO) and expanded graphene oxide (EGO), were achieved by amide bond formations. These reactions yielded PEGylated graphene oxides, GO-PEG and EGO-PEG. Whilst presence of the newly formed amide links (NH-CO) were confirmed by FTIR stretches observed at 1732 cm−1 and 1712 cm−1, the associated Raman D- and G-bands resonated at 1311/1318 cm−1 and 1584/1595 cm−1 had shown the carbonaceous structures in both PEGylated products remain unchanged. Whilst SEM images revealed the nano-sheet structures in all the GO derivatives (GO/EGO and GO-PEG/EGO-PEG), TEM images clearly showed the nano-structures of both GO-PEG and EGO-PEG had undergone significant morphological changes from their starting materials after the PEGylated processes. The successful PEGylations were also indicated by the change of pH values measured in the starting GO/EGO (pH 2.6–3.3) and the PEGylated GO-PEG/EGO-PEG (pH 6.6–6.9) products. Initial antifungal activities of selective metallic nanomaterials (ZnO and Cu) and the four GO derivatives were screened against Candida albicans using the in vitro cut-well method. Whilst the haemocytometer count indicated GO-PEG and copper nanoparticles (CuNPs) exhibited the best antifungal effects, the corresponding SEM images showed C. albicans had, respectively, undergone extensive shrinkage and porosity deformations. Synergistic antifungal effects all GO derivatives in various ratio of CuNPs combinations were determined by assessing C. albicans viabilities using broth dilution assays. The best synergistic effects were observed when a 30:70 ratio of GO/GO-PEG combined with CuNPs, where MIC50 185–225 μm/mL were recorded. Moreover, the decreased antifungal activities observed in EGO and EGO-PEG may be explained by their poor colloidal stability with increasing nanoparticle concentrations.Peer reviewe

Phenotype-Based Screening of Synthetic Cannabinoids in a Dravet Syndrome Zebrafish Model.

Dravet syndrome is a catastrophic epilepsy of childhood, characterized by cognitive impairment, severe seizures, and increased risk for sudden unexplained death in epilepsy (SUDEP). Although refractory to conventional antiepileptic drugs, emerging preclinical and clinical evidence suggests that modulation of the endocannabinoid system could be therapeutic in these patients. Preclinical research on this topic is limited as cannabis, delta-9-tetrahydrocannabinol (THC) and cannabidiol (CBD), are designated by United States Drug Enforcement Agency (DEA) as illegal substances. In this study, we used a validated zebrafish model of Dravet syndrome, scn1lab homozygous mutants, to screen for anti-seizure activity in a commercially available library containing 370 synthetic cannabinoid (SC) compounds. SCs are intended for experimental use and not restricted by DEA designations. Primary phenotype-based screening was performed using a locomotion-based assay in 96-well plates, and a secondary local field potential recording assay was then used to confirm suppression of electrographic epileptiform events. Identified SCs with anti-seizure activity, in both assays, included five SCs structurally classified as indole-based cannabinoids JWH 018 N-(5-chloropentyl) analog, JWH 018 N-(2-methylbutyl) isomer, 5-fluoro PB-22 5-hydroxyisoquinoline isomer, 5-fluoro ADBICA, and AB-FUBINACA 3-fluorobenzyl isomer. Our approach demonstrates that two-stage phenotype-based screening in a zebrafish model of Dravet syndrome successfully identifies SCs with anti-seizure activity

Adaptive planning for distributed systems using goal accomplishment tracking

Goal accomplishment tracking is the process of monitoring the progress of a task or series of tasks towards completing a goal. Goal accomplishment tracking is used to monitor goal progress in a variety of domains, including workflow processing, teleoperation and industrial manufacturing. Practically, it involves the constant monitoring of task execution, analysis of this data to determine the task progress and notification of interested parties. This information is usually used in a passive way to observe goal progress. However, responding to this information may prevent goal failures. In addition, responding proactively in an opportunistic way can also lead to goals being completed faster. This paper proposes an architecture to support the adaptive planning of tasks for fault tolerance or opportunistic task execution based on goal accomplishment tracking. It argues that dramatically increased performance can be gained by monitoring task execution and altering plans dynamically

Polar Fusion Technique Analysis for Evaluating the Performances of Image Fusion of Thermal and Visual Images for Human Face Recognition

This paper presents a comparative study of two different methods, which are based on fusion and polar transformation of visual and thermal images. Here, investigation is done to handle the challenges of face recognition, which include pose variations, changes in facial expression, partial occlusions, variations in illumination, rotation through different angles, change in scale etc. To overcome these obstacles we have implemented and thoroughly examined two different fusion techniques through rigorous experimentation. In the first method log-polar transformation is applied to the fused images obtained after fusion of visual and thermal images whereas in second method fusion is applied on log-polar transformed individual visual and thermal images. After this step, which is thus obtained in one form or another, Principal Component Analysis (PCA) is applied to reduce dimension of the fused images. Log-polar transformed images are capable of handling complicacies introduced by scaling and rotation. The main objective of employing fusion is to produce a fused image that provides more detailed and reliable information, which is capable to overcome the drawbacks present in the individual visual and thermal face images. Finally, those reduced fused images are classified using a multilayer perceptron neural network. The database used for the experiments conducted here is Object Tracking and Classification Beyond Visible Spectrum (OTCBVS) database benchmark thermal and visual face images. The second method has shown better performance, which is 95.71% (maximum) and on an average 93.81% as correct recognition rate.Comment: Proceedings of IEEE Workshop on Computational Intelligence in Biometrics and Identity Management (IEEE CIBIM 2011), Paris, France, April 11 - 15, 201