Detection of live and antibiotic-killed bacteria by quantitative real-time PCR of specific fragments of ribosomal RNA

RÉSUMÉ Le but d'un traitement antimicrobien est d'éradiquer une infection bactérienne. Cependant, il est souvent difficile d'en évaluer rapidement l'efficacité en utilisant les techniques standard. L'estimation de la viabilité bactérienne par marqueurs moléculaires permettrait d'accélérer le processus. Ce travail étudie donc la possibilité d'utiliser le RNA ribosomal (rRNA) à cet effet. Des cultures de Streptococcus gordonii sensibles (parent Wt) et tolérants (mutant Tol 1) à l'action bactéricide de la pénicilline ont été exposées à différents antibiotiques. La survie bactérienne au cours du temps a été déterminée en comparant deux méthodes. La méthode de référence par compte viable a été comparée à une méthode moléculaire consistant à amplifier par PCR quantitative en temps réel une partie du génome bactérien. La cible choisie devait refléter la viabilité cellulaire et par conséquent être synthétisée de manière constitutive lors de la vie de la bactérie et être détruite rapidement lors de la mort cellulaire. Le choix s'est porté sur un fragment du gène 16S-rRNA. Ce travail a permis de valider ce choix en corrélant ce marqueur moléculaire à la viabilité bactérienne au cours d'un traitement antibiotique bactéricide. De manière attendue, les S. gordonii sensibles à la pénicilline ont perdu ≥ 4 log10 CFU/ml après 48 heures de traitement par pénicilline alors que le mutant tolérant Tol1 en a perdu ≥ 1 log10 CFU/ml. De manière intéressant, la quantité de marqueur a augmenté proportionnellement au compte viable durant la phase de croissance bactérienne. Après administration du traitement antibiotique, l'évolution du marqueur dépendait de la capacité de la bactérie à survivre à l'action de l'antibiotique. Stable lors du traitement des souches tolérantes, la quantité de marqueur détectée diminuait de manière proportionnelle au compte viable lors du traitement des souches sensibles. Cette corrélation s'est confirmée lors de l'utilisation d'autres antibiotiques bactéricides. En conclusion, l'amplification par PCR du RNA ribosomal 16S permet d'évaluer rapidement la viabilité bactérienne au cours d'un traitement antibiotique en évitant le recours à la mise en culture dont les résultats ne sont obtenus qu'après plus de 24 heures. Cette méthode offre donc au clinicien une évaluation rapide de l'efficacité du traitement, particulièrement dans les situations, comme le choc septique, où l'initiation sans délai d'un traitement efficace est une des conditions essentielles du succès thérapeutique. ABSTRACT Assessing bacterial viability by molecular markers might help accelerate the measurement of antibiotic-induced killing. This study investigated whether ribosomal RNA (rRNA) could be suitable for this purpose. Cultures of penicillin-susceptible and penicillin-tolerant (Tol1 mutant) Streptococcus gordonii were exposed to mechanistically different penicillin and levofloxacin. Bacterial survival was assessed by viable counts, and compared to quantitative real-time PCR amplification of either the 16S-rRNA genes (rDNA) or the 16S rRNA, following reverse transcription. Penicillin-susceptible S. gordonii lost ≥ 4 log10 CFU/ml of viability over 48 h of penicillin treatment. In comparison, the Toll mutant lost ≤ 1 log10 CFU/ml. Amplification of a 427-base fragment of 16S rDNA yielded amplicons that increased proportionally to viable counts during bacterial growth, but did not decrease during drug-induced killing. In contrast, the same 427-base fragment amplified from 16S rDNA paralleled both bacterial growth and drug-induced killing. It also differentiated between penicillin-induced killing of the parent and the Toll mutant (≥4 log10 CFU/ml and ≤1 lo10 CFU/ml, respectively), and detected killing by mechanistically unrelated levofloxacin. Since large fragments of polynucleotides might be degraded faster than smaller fragments the experiments were repeated by amplifying a 119-base region internal to the origina1 427-base fragment. The amount of 119-base amplicons increased proportionally to viability during growth, but remained stable during drug treatment. Thus, 16S rRNA was a marker of antibiotic-induced killing, but the size of the amplified fragment was critical to differentiate between live and dead bacteria.

Quantifying Uncertainty in Real Time Performance Measurement for Highway Winter Maintenance Operations – Phase 2, RB03-013, 2014

Winter weather in Iowa is often unpredictable and can have an adverse impact on traffic flow. The Iowa Department of Transportation (Iowa DOT) attempts to lessen the impact of winter weather events on traffic speeds with various proactive maintenance operations. In order to assess the performance of these maintenance operations, it would be beneficial to develop a model for expected speed reduction based on weather variables and normal maintenance schedules. Such a model would allow the Iowa DOT to identify situations in which speed reductions were much greater than or less than would be expected for a given set of storm conditions, and make modifications to improve efficiency and effectiveness. The objective of this work was to predict speed changes relative to baseline speed under normal conditions, based on nominal maintenance schedules and winter weather covariates (snow type, temperature, and wind speed), as measured by roadside weather stations. This allows for an assessment of the impact of winter weather covariates on traffic speed changes, and estimation of the effect of regular maintenance passes. The researchers chose events from Adair County, Iowa and fit a linear model incorporating the covariates mentioned previously. A Bayesian analysis was conducted to estimate the values of the parameters of this model. Specifically, the analysis produces a distribution for the parameter value that represents the impact of maintenance on traffic speeds. The effect of maintenance is not a constant, but rather a value that the researchers have some uncertainty about and this distribution represents what they know about the effects of maintenance. Similarly, examinations of the distributions for the effects of winter weather covariates are possible. Plots of observed and expected traffic speed changes allow a visual assessment of the model fit. Future work involves expanding this model to incorporate many events at multiple locations. This would allow for assessment of the impact of winter weather maintenance across various situations, and eventually identify locations and times in which maintenance could be improved.

Real-time Image-based RGB-D Camera Motion Tracking and Environment Mapping

In this work, image based estimation methods, also known as direct methods, are studied which avoid feature extraction and matching completely. Cost functions use raw pixels as measurements and the goal is to produce precise 3D pose and structure estimates. The cost functions presented minimize the sensor error, because measurements are not transformed or modified. In photometric camera pose estimation, 3D rotation and translation parameters are estimated by minimizing a sequence of image based cost functions, which are non-linear due to perspective projection and lens distortion. In image based structure refinement, on the other hand, 3D structure is refined using a number of additional views and an image based cost metric. Image based estimation methods are particularly useful in conditions where the Lambertian assumption holds, and the 3D points have constant color despite viewing angle. The goal is to improve image based estimation methods, and to produce computationally efficient methods which can be accomodated into real-time applications. The developed image-based 3D pose and structure estimation methods are finally demonstrated in practise in indoor 3D reconstruction use, and in a live augmented reality application.

Learning-Based Approach to Real Time Tracking and Analysis of Faces

This paper describes a trainable system capable of tracking faces and facialsfeatures like eyes and nostrils and estimating basic mouth features such as sdegrees of openness and smile in real time. In developing this system, we have addressed the twin issues of image representation and algorithms for learning. We have used the invariance properties of image representations based on Haar wavelets to robustly capture various facial features. Similarly, unlike previous approaches this system is entirely trained using examples and does not rely on a priori (hand-crafted) models of facial features based on optical flow or facial musculature. The system works in several stages that begin with face detection, followed by localization of facial features and estimation of mouth parameters. Each of these stages is formulated as a problem in supervised learning from examples. We apply the new and robust technique of support vector machines (SVM) for classification in the stage of skin segmentation, face detection and eye detection. Estimation of mouth parameters is modeled as a regression from a sparse subset of coefficients (basis functions) of an overcomplete dictionary of Haar wavelets.

Real-time forecasting of inflation and output growth with autoregressive models in the presence of data revisions

We examine how the accuracy of real-time forecasts from models that include autoregressive terms can be improved by estimating the models on ‘lightly revised’ data instead of using data from the latest-available vintage. The benefits of estimating autoregressive models on lightly revised data are related to the nature of the data revision process and the underlying process for the true values. Empirically, we find improvements in root mean square forecasting error of 2–4% when forecasting output growth and inflation with univariate models, and of 8% with multivariate models. We show that multiple-vintage models, which explicitly model data revisions, require large estimation samples to deliver competitive forecasts. Copyright © 2012 John Wiley & Sons, Ltd.

Real-time factor model forecasting and the effects of instability

Factor forecasting models are shown to deliver real-time gains over autoregressive models for US real activity variables during the recent period, but are less successful for nominal variables. The gains are largely due to the Financial Crisis period, and are primarily at the shortest (one quarter ahead) horizon. Excluding the pre-Great Moderation years from the factor forecasting model estimation period (but not from the data used to extract factors) results in a marked fillip in factor model forecast accuracy, but does the same for the AR model forecasts. The relative performance of the factor models compared to the AR models is largely unaffected by whether the exercise is in real time or is pseudo out-of-sample.

A real-time polymerase chain reaction assay for the identification and quantification of American Leishmania species on the basis of glucose-6-phosphate dehydrogenase

A real-time polymerase chain reaction (PCR) test was developed on the basis of the Leishmania glucose-6-phosphate dehydrogenase locus that enables identification and quantification of parasites. Using two independent pairs of primers in SYBR-Green assays, the test identified etiologic agents of cutaneous leishmaniasis belonging to both subgenera, Leishmania (Viannia) and Leishmania (Leishmania) in the Americas. Furthermore, use of TaqMan probes enables distinction between L. (V.) braziliensis or L. (V.) peruviania from the other L. (Viannia) species. All assays were negative with DNA of related trypanosomatids, humans, and mice. The parasite burden was estimated by normalizing the number of organisms per total amount of DNA in the sample or per host glyceraldehyde-3-phosphate dehydrogenase copies. The real-time PCR assay for L. (Leishmania) subgenus showed a good linear correlation with quantification on the basis of a limiting dilution assay in experimentally infected mice. The test successfully identifies and quantifies Leishmania in human biopsy specimens and represents a new tool to study leishmaniasis.

Simple telemedicine for developing regions: Camera phones and paper-based microfluidic devices for real-time, off-site diagnosis

This article describes a prototype system for quantifying bioassays and for exchanging the results of the assays digitally with physicians located off-site. The system uses paper-based microfluidic devices for running multiple assays simultaneously, camera phones or portable scanners for digitizing the intensity of color associated with each colorimetric assay, and established communications infrastructure for transferring the digital information from the assay site to an off-site laboratory for analysis by a trained medical professional; the diagnosis then can be returned directly to the healthcare provider in the field. The microfluidic devices were fabricated in paper using photolithography and were functionalized with reagents for colorimetric assays. The results of the assays were quantified by comparing the intensities of the color developed in each assay with those of calibration curves. An example of this system quantified clinically relevant concentrations of glucose and protein in artificial urine. The combination of patterned paper, a portable method for obtaining digital images, and a method for exchanging results of the assays with off-site diagnosticians offers new opportunities for inexpensive monitoring of health, especially in situations that require physicians to travel to patients (e.g., in the developing world, in emergency management, and during field operations by the military) to obtain diagnostic information that might be obtained more effectively by less valuable personnel.

Genetic associations between carcass traits measured by real-time ultrasound and scrotal circumference and growth traits in Nelore cattle

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Real-time optical monitoring of the dip coating process

A significant part of film production by the coating industry is based on wet bench processes, where better understanding of their temporal dynamics could facilitate control and optimization. In this work, in situ laser interferometry is applied to study properties of flowing liquids and quantitatively monitor the dip coating batch process. Two oil standards Newtonian, non-volatile, with constant refractive indices and distinct flow properties - were measured under several withdrawing speeds. The dynamics of film physical thickness then depends on time as t(-1/2), and flow characterization becomes possible with high precision (linear slope uncertainty of +/-0.04%). Resulting kinematic viscosities for OP60 and OP400 are 1,17 +/- 0,03. St and 9,9 +/- 0,2 St, respectively. These results agree with nominal values, as provided by the manufacturer. For more complex films (a multi-component sol-gel Zirconyl Chloride aqueous solution) with a varying refractive index, through a direct polarimetric measurement, allowing also determination of the temporal evolution of physical thickness (uncertainty of +/- 0,007 microns) is also determined during dip coating.

Electrogravimetric Real-Time and in Situ Michaelis-Menten Enzimatic Kinetics: Progress Curve of Acetylcholinesterase Hydrolysis

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Real time orbit determination using GPS navigation solution

This work analyses a real time orbit estimator using the raw navigation solution provided by GPS receivers. The estimation algorithm considers a Kalman filter with a rather simple orbit dynamic model and random walk modeling of the receiver clock bias and drift. Using the Topex/Poseidon satellite as test bed, characteristics of model truncation, sampling rates and degradation of the GPS receiver (Selective Availability) were analysed. Copyright © 2007 by ABCM.

Onboard and real-time artificial satellite orbit determination using GPS

An algorithm for real-time and onboard orbit determination applying the Extended Kalman Filter (EKF) method is developed. Aiming at a very simple and still fairly accurate orbit determination, an analysis is performed to ascertain an adequacy of modeling complexity versus accuracy. The minimum set of to-be-estimated states to reach the level of accuracy of tens of meters is found to have at least the position, velocity, and user clock offset components. The dynamical model is assessed through several tests, covering force model, numerical integration scheme and step size, and simplified variational equations. The measurement model includes only relevant effects to the order of meters. The EKF method is chosen to be the simplest real-time estimation algorithm with adequate tuning of its parameters. In the developed procedure, the obtained position and velocity errors along a day vary from 15 to 20 m and from 0.014 to 0.018 m/s, respectively, with standard deviation from 6 to 10 m and from 0.006 to 0.008 m/s, respectively, with the SA either on or off. The results, as well as analysis of the final adopted models used, are presented in this work. © 2013 Ana Paula Marins Chiaradia et al.

Monitoring of hydrogen sulfide via substrate-integrated hollow waveguide mid-infrared sensors in real-time

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)