Label-free detection of tobramycin in serum by transmission-localized surface plasmon resonance.

In order to improve the efficacy and safety of treatments, drug dosage needs to be adjusted to the actual needs of each patient in a truly personalized medicine approach. Key for widespread dosage adjustment is the availability of point-of-care devices able to measure plasma drug concentration in a simple, automated, and cost-effective fashion. In the present work, we introduce and test a portable, palm-sized transmission-localized surface plasmon resonance (T-LSPR) setup, comprised of off-the-shelf components and coupled with DNA-based aptamers specific to the antibiotic tobramycin (467 Da). The core of the T-LSPR setup are aptamer-functionalized gold nanoislands (NIs) deposited on a glass slide covered with fluorine-doped tin oxide (FTO), which acts as a biosensor. The gold NIs exhibit localized plasmon resonance in the visible range matching the sensitivity of the complementary metal oxide semiconductor (CMOS) image sensor employed as a light detector. The combination of gold NIs on the FTO substrate, causing NIs size and pattern irregularity, might reduce the overall sensitivity but confers extremely high stability in high-ionic solutions, allowing it to withstand numerous regeneration cycles without sensing losses. With this rather simple T-LSPR setup, we show real-time label-free detection of tobramycin in buffer, measuring concentrations down to 0.5 μM. We determined an affinity constant of the aptamer-tobramycin pair consistent with the value obtained using a commercial propagating-wave based SPR. Moreover, our label-free system can detect tobramycin in filtered undiluted blood serum, measuring concentrations down to 10 μM with a theoretical detection limit of 3.4 μM. While the association signal of tobramycin onto the aptamer is masked by the serum injection, the quantification of the captured tobramycin is possible during the dissociation phase and leads to a linear calibration curve for the concentrations over the tested range (10-80 μM). The plasmon shift following surface binding is calculated in terms of both plasmon peak location and hue, with the latter allowing faster data elaboration and real-time display of the results. The presented T-LSPR system shows for the first time label-free direct detection and quantification of a small molecule in the complex matrix of filtered undiluted blood serum. Its uncomplicated construction and compact size, together with the remarkable performances, represent a leap forward toward effective point-of-care devices for therapeutic drug concentration monitoring.

An inertial sensor-based system for spatio-temporal analysis in classic cross-country skiing diagonal technique.

The present study proposes a method based on ski fixed inertial sensors to automatically compute spatio-temporal parameters (phase durations, cycle speed and cycle length) for the diagonal stride in classical cross-country skiing. The proposed system was validated against a marker-based motion capture system during indoor treadmill skiing. Skiing movement of 10 junior to world-cup athletes was measured for four different conditions. The accuracy (i.e. median error) and precision (i.e. interquartile range of error) of the system was below 6ms for cycle duration and ski thrust duration and below 35ms for pole push duration. Cycle speed precision (accuracy) was below 0.1m/s (0.005m/s) and cycle length precision (accuracy) was below 0.15m (0.005m). The system was sensitive to changes of conditions and was accurate enough to detect significant differences reported in previous studies. Since capture volume is not limited and setup is simple, the system would be well suited for outdoor measurements on snow.

Sanitary quality of edible bivalve mollusks in Southeastern Brazil using an UV based depuration system

The increase in seafood production, especially in mariculture worldwide, has brought out the need of continued monitoring of shellfish production areas in order to ensure safety to human consumption. The purpose of this research was to evaluate pathogenic protozoa, viruses and bacteria contamination in oysters before and after UV depuration procedure, in brackish waters at all stages of cultivation and treatment steps and to enumerate microbiological indicators of fecal contamination from production site up to depuration site in an oyster cooperative located at the Southeastern estuarine area of Brazil. Oysters and brackish water were collected monthly from September 2009 to November 2010. Four sampling sites were selected for enteropathogens analysis: site 1- oyster growth, site 2- catchment water (before UV depuration procedure), site 3 - filtration stage of water treatment (only for protozoa analysis) and site 4- oyster's depuration tank. Three microbiological indicators ! were examined at sites 1, 2 and 4. The following pathogenic microorganisms were searched: Giardia cysts, Cryptosporidium oocysts, Human Adenovirus (HAdV), Hepatitis A virus (HAV), Human Norovirus (HnoV) (genogroups I and II), JC strain Polyomavirus (JCPyV) and Salmonella sp. Analysis consisted of molecular detection (qPCR) for viruses (oysters and water samples); immunomagnetic separation followed by direct immunofluorescence assay for Cryptosporidium oocysts and Giardia cysts and also molecular detection (PCR) for the latter (oysters and water samples); commercial kit (Reveal-Neogee (R)) for Salmonella analysis (oysters). Giardia was the most prevalent pathogen in all sites where it was detected: 36.3%, 18.1%, 36.3% and 27.2% of water from sites 1, 2, 3 and 4 respectively; 36.3% of oysters from site 1 and 54.5% of depurated oysters were harboring Giardia cysts. The huge majority of contaminated samples were classified as Giardia duodenalis. HAdv was detected in water and o! ysters from growth site and HnoV GI in two batches of oysters ! (site 1) in huge concentrations (2.11 x 10(13), 3.10 x 10(12) gc/g). In depuration tank site, Salmonella sp., HAV (4.84 x 10(3)) and HnoV GII (7.97 x 10(14)) were detected once in different batches of oysters. Cryptosporidium spp. oocysts were present in 9.0% of water samples from site four. These results reflect the contamination of oysters even when UV depuration procedures are employed in this shellfish treatment plant. Moreover, the molecular comprehension of the sources of contamination is necessary to develop an efficient management strategy allied to shellfish treatment improvement to prevent foodborne illnesses. (C) 2011 Elsevier Ltd. All rights reserved.

Change points detection in crime-related time series: an on-line fuzzy approach based on a shape space representation

The extension of traditional data mining methods to time series has been effectively applied to a wide range of domains such as finance, econometrics, biology, security, and medicine. Many existing mining methods deal with the task of change points detection, but very few provide a flexible approach. Querying specific change points with linguistic variables is particularly useful in crime analysis, where intuitive, understandable, and appropriate detection of changes can significantly improve the allocation of resources for timely and concise operations. In this paper, we propose an on-line method for detecting and querying change points in crime-related time series with the use of a meaningful representation and a fuzzy inference system. Change points detection is based on a shape space representation, and linguistic terms describing geometric properties of the change points are used to express queries, offering the advantage of intuitiveness and flexibility. An empirical evaluation is first conducted on a crime data set to confirm the validity of the proposed method and then on a financial data set to test its general applicability. A comparison to a similar change-point detection algorithm and a sensitivity analysis are also conducted. Results show that the method is able to accurately detect change points at very low computational costs. More broadly, the detection of specific change points within time series of virtually any domain is made more intuitive and more understandable, even for experts not related to data mining.