BACTEC MGIT 960 TM system for screening of Mycobacterium tuberculosis complex among cattle

Bovine tuberculosis remains a disease of economic and public health importance in developing countries. The largest number of new cases of tuberculosis usually occurs in South-East Asia region and Africa. This study was aimed to evaluate the recent technique (BACTEC MGIT 960 TM system) for screening of Mycobacterium tuberculosis complex among cattle in Egypt. From the 1180 cattle examined in three different Governorates (El-Sharkia, El-Gharbia and El-Monefeia) by single intradermal tuberculin test, 29 animals (2.46%) were positive reactors. The post mortem examination of the positive reactors showed that 22 animals (75.9%) had visible lesions [respiratory form (31.0%), digestive form (13.8%), mixed form (20.7%) and generalized form (10.3%)], while seven (24.1%) did not show visible lesions. The results of isolation and identification using conventional culture method (Lowenstein- Jensen medium) were 22 mycobacterial isolates (75.9%), 20 (68.97%) Mycobacterium bovis and 2 (6.9%) unidentified slow growth. The BACTEC MGIT 960 TM system was used for recovery of Mycobacteria and compared with conventional culture method (Lowenstein-Jensen medium). The recovery rate of BACTEC MGIT 960 TM system was 82.8%, while that of Lowenstein-Jensen medium was 75.9%. The mean time for detection of Mycobacteria was 17.8 ± 0.9 days and 46.5 ± 0.4 days for BACTEC MGIT 960 TM system and Lowenstein-Jensen medium, respectively while the contamination rate with BACTEC MGIT 960 TM system was 6.9% and 10.3% in Lowenstein-Jensen medium.Key words: Bovine tuberculosis, tuberculin test, Lowenstein-Jensen medium, BACTEC system

Intelligent Health Monitoring of Machine Bearings Based on Feature Extraction

This document is the Accepted Manuscript of the following article: Mohammed Chalouli, Nasr-eddine Berrached, and Mouloud Denai, ‘Intelligent Health Monitoring of Machine Bearings Based on Feature Extraction’, Journal of Failure Analysis and Prevention, Vol. 17 (5): 1053-1066, October 2017. Under embargo. Embargo end date: 31 August 2018. The final publication is available at Springer via DOI: https://doi.org/10.1007/s11668-017-0343-y.Finding reliable condition monitoring solutions for large-scale complex systems is currently a major challenge in industrial research. Since fault diagnosis is directly related to the features of a system, there have been many research studies aimed to develop methods for the selection of the relevant features. Moreover, there are no universal features for a particular application domain such as machine diagnosis. For example, in machine bearing fault diagnosis, these features are often selected by an expert or based on previous experience. Thus, for each bearing machine type, the relevant features must be selected. This paper attempts to solve the problem of relevant features identification by building an automatic fault diagnosis process based on relevant feature selection using a data-driven approach. The proposed approach starts with the extraction of the time-domain features from the input signals. Then, a feature reduction algorithm based on cross-correlation filter is applied to reduce the time and cost of the processing. Unsupervised learning mechanism using K-means++ selects the relevant fault features based on the squared Euclidian distance between different health states. Finally, the selected features are used as inputs to a self-organizing map producing our health indicator. The proposed method is tested on roller bearing benchmark datasets.Peer reviewe

Clinicopathologic predictors of renal outcomes in light chain cast nephropathy: a multicenter retrospective study

Light chain cast nephropathy (LCCN) in multiple myeloma often leads to severe and poorly reversible acute kidney injury. Severe renal impairment influences the allocation of chemotherapy and its tolerability; it also affects patient survival. Whether renal biopsy findings add to the clinical assessment in predicting renal and patient outcomes in LCCN is uncertain. We retrospectively reviewed clinical presentation, chemotherapy regimens, hematologic response, and renal and patient outcomes in 178 patients with biopsy-proven LCCN from 10 centers in Europe and North America. A detailed pathology review, including assessment of the extent of cast formation, was performed to study correlations with initial presentation and outcomes. Patients presented with a mean estimated glomerular filtration rate (eGFR) of 13 ± 11 mL/min/1.73 m2, and 82% had stage 3 acute kidney injury. The mean number of casts was 3.2/mm2 in the cortex. Tubulointerstitial lesions were frequent: acute tubular injury (94%), tubulitis (82%), tubular rupture (62%), giant cell reaction (60%), and cortical and medullary inflammation (95% and 75%, respectively). Medullary inflammation, giant cell reaction, and the extent of cast formation correlated with eGFR value at LCCN diagnosis. During a median follow-up of 22 months, mean eGFR increased to 43 ± 30 mL/min/1.73 m2. Age, β2-microglobulin, best hematologic response, number of cortical casts per square millimeter, and degree of interstitial fibrosis/tubular atrophy (IFTA) were independently associated with a higher eGFR during follow-up. This eGFR value correlated with overall survival, independently of the hematologic response. This study shows that extent of cast formation and IFTA in LCCN predicts the quality of renal response, which, in turn, is associated with overall survival.info:eu-repo/semantics/publishedVersio

Neural Correlate of Filtering of Irrelevant Information from Visual Working Memory

In a dynamic environment stimulus task relevancy could be altered through time and it is not always possible to dissociate relevant and irrelevant objects from the very first moment they come to our sight. In such conditions, subjects need to retain maximum possible information in their WM until it is clear which items should be eliminated from WM to free attention and memory resources. Here, we examined the neural basis of irrelevant information filtering from WM by recording human ERP during a visual change detection task in which the stimulus irrelevancy was revealed in a later stage of the task forcing the subjects to keep all of the information in WM until test object set was presented. Assessing subjects' behaviour we found that subjects' RT was highly correlated with the number of irrelevant objects and not the relevant one, pointing to the notion that filtering, and not selection, process was used to handle the distracting effect of irrelevant objects. In addition we found that frontal N150 and parietal N200 peak latencies increased systematically as the amount of irrelevancy load increased. Interestingly, the peak latency of parietal N200, and not frontal N150, better correlated with subjects' RT. The difference between frontal N150 and parietal N200 peak latencies varied with the amount of irrelevancy load suggesting that functional connectivity between modules underlying fronto-parietal potentials vary concomitant with the irrelevancy load. These findings suggest the existence of two neural modules, responsible for irrelevant objects elimination, whose activity latency and functional connectivity depend on the number of irrelevant object

Design Considerations for Tumor-Targeted Nanoparticles

Inorganic/organic hybrid nanoparticles are potentially useful in biomedicine, but to avoid non-specific background fluorescence and long-term toxicity, they need to be cleared from the body within a reasonable timescale1. Previously, we have shown that rigid spherical nanoparticles such as quantum dots can be cleared by the kidneys if they have a hydrodynamic diameter of approximately 5.5 nm and a zwitterionic surface charge2. Here, we show that quantum dots functionalized with high-affinity small-molecule ligands that target tumours can also be cleared by the kidneys if their hydrodynamic diameter is less than this value, which sets an upper limit of 5–10 ligands per quantum dot for renal clearance. Animal models of prostate cancer and melanoma show receptor-specific imaging and renal clearance within 4 h post-injection. This study suggests a set of design rules for the clinical translation of targeted nanoparticles that can be eliminated through the kidneys.National Science Foundation (U.S.) (NSF-0070319)National Institutes of Health (U.S.) (NIH GM68762)National Institutes of Health (U.S.) (NIH grant no. R33-EB-000673)National Institutes of Health (U.S.) ( NIH grant no. R01-CA-115296)National Institutes of Health (U.S.) (MIT-Harvard NanoMedical Consortium (1U54-CA119349, a Center of Cancer Nanotechnology Excellence))Bank of AmericaMedical Foundation, inc. (Charles A. King Trust Postdoctoral Research Fellowship Program)cance

Exploring perceptions of advertising ethics: an informant-derived approach

Whilst considerable research exists on determining consumer responses to pre-determined statements within numerous ad ethics contexts, our understanding of consumer thoughts regarding ad ethics in general remains lacking. The purpose of our study therefore is to provide a first illustration of an emic and informant-based derivation of perceived ad ethics. The authors use multi-dimensional scaling as an approach enabling the emic, or locally derived deconstruction of perceived ad ethics. Given recent calls to develop our understanding of ad ethics in different cultural contexts, and in particular within the Middle East and North Africa (MENA) region, we use Lebanon—the most ethically charged advertising environment within MENA—as an illustrative context for our study. Results confirm the multi-faceted and pluralistic nature of ad ethics as comprising a number of dimensional themes already salient in the existing literature but in addition, we also find evidence for a bipolar relationship between individual themes. The specific pattern of inductively derived relationships is culturally bound. Implications of the findings are discussed, followed by limitations of the study and recommendations for further research

Regulation of type 1 diabetes development and B-cell activation in nonobese diabetic mice by early life exposure to a diabetogenic environment

Microbes, including viruses, influence type 1 diabetes (T1D) development, but many such influences remain undefined. Previous work on underlying immune mechanisms has focussed on cytokines and T cells. Here, we compared two nonobese diabetic (NOD) mouse colonies, NODlow and NODhigh, differing markedly in their cumulative T1D incidence (22% vs. 90% by 30 weeks in females). NODhigh mice harbored more complex intestinal microbiota, including several pathobionts; both colonies harbored segmented filamentous bacteria (SFB), thought to suppress T1D. Young NODhigh females had increased B-cell activation in their mesenteric lymph nodes. These phenotypes were transmissible. Co-housing of NODlow with NODhigh mice after weaning did not change T1D development, but T1D incidence was increased in female offspring of co-housed NODlow mice, which were exposed to the NODhigh environment both before and after weaning. These offspring also acquired microbiota and B-cell activation approaching those of NODhigh mice. In NODlow females, the low rate of T1D was unaffected by cyclophosphamide but increased by PD-L1 blockade. Thus, environmental exposures that are innocuous later in life may promote T1D progression if acquired early during immune development, possibly by altering B-cell activation and/or PD-L1 function. Moreover, T1D suppression in NOD mice by SFB may depend on the presence of other microbial influences. The complexity of microbial immune regulation revealed in this murine model may also be relevant to the environmental regulation of human T1D