3 resultados para Sample Preparation
em Universidad Politécnica de Madrid
Resumo:
The leaf cuticular ultrastructure of some plant species has been examined by transmission electron microscopy (TEM) in only few studies. Attending to the different cuticle layers and inner structure, plant cuticles have been grouped into six general morphological types. With the aim of critically examining the effect of cuticle isolation and preparation for TEM analysis on cuticular ultrastructure, adaxial leaf cuticles of blue-gum eucalypt, grey poplar, and European pear were assessed, following a membrane science approach. The embedding and staining protocols affected the ultrastructure of the cuticles analysed. The solubility parameter, surface tension, and contact angles with water of pure Spurr's and LR-White resins were within a similar range. Differences were however estimated for resin : solvent mixtures, since Spurr’s resin is combined with acetone and LR-White resin is mixed with ethanol. Given the composite hydrophilic and lipophilic nature of plant cuticles, the particular TEM tissue embedding and staining procedures employed may affect sample ultrastructure and the interpretation of the results in physicochemical and biological terms. It is concluded that tissue preparation procedures may be optimised to facilitate the observation of the micro- and nanostructure of cuticular layers and components with different degrees of polarity and hydrophobicity.
Resumo:
The present work aims to assess Laser-Induced Plasma Spectrometry (LIPS) as a tool for the characterization of photovoltaic materials. Despite being a well-established technique with applications to many scientific and industrial fields, so far LIPS is little known to the photovoltaic scientific community. The technique allows the rapid characterization of layered samples without sample preparation, in open atmosphere and in real time. In this paper, we assess LIPS ability for the determination of elements that are difficult to analyze by other broadly used techniques, or for producing analytical information from very low-concentration elements. The results of the LIPS characterization of two different samples are presented: 1) a 90 nm, Al-doped ZnO layer deposited on a Si substrate by RF sputtering and 2) a Te-doped GaInP layer grown on GaAs by Metalorganic Vapor Phase Epitaxy. For both cases, the depth profile of the constituent and dopant elements is reported along with details of the experimental setup and the optimization of key parameters. It is remarkable that the longest time of analysis was ∼10 s, what, in conjunction with the other characteristics mentioned, makes of LIPS an appealing technique for rapid screening or quality control whether at the lab or at the production line.
Resumo:
Background: Analysis of exhaled volatile organic compounds (VOCs) in breath is an emerging approach for cancer diagnosis, but little is known about its potential use as a biomarker for colorectal cancer (CRC). We investigated whether a combination of VOCs could distinct CRC patients from healthy volunteers. Methods: In a pilot study, we prospectively analyzed breath exhalations of 38 CRC patient and 43 healthy controls all scheduled for colonoscopy, older than 50 in the average-risk category. The samples were ionized and analyzed using a Secondary ElectroSpray Ionization (SESI) coupled with a Time-of-Flight Mass Spectrometer (SESI-MS). After a minimum of 2 hours fasting, volunteers deeply exhaled into the system. Each test requires three soft exhalations and takes less than ten minutes. No breath condensate or collection are required and VOCs masses are detected in real time, also allowing for a spirometric profile to be analyzed along with the VOCs. A new sampling system precludes ambient air from entering the system, so background contamination is reduced by an overall factor of ten. Potential confounding variables from the patient or the environment that could interfere with results were analyzed. Results: 255 VOCs, with masses ranging from 30 to 431 Dalton have been identified in the exhaled breath. Using a classification technique based on the ROC curve for each VOC, a set of 9 biomarkers discriminating the presence of CRC from healthy volunteers was obtained, showing an average recognition rate of 81.94%, a sensitivity of 87.04% and specificity of 76.85%. Conclusions: A combination of cualitative and cuantitative analysis of VOCs in the exhaled breath could be a powerful diagnostic tool for average-risk CRC population. These results should be taken with precaution, as many endogenous or exogenous contaminants could interfere as confounding variables. On-line analysis with SESI-MS is less time-consuming and doesn’t need sample preparation. We are recruiting in a new pilot study including breath cleaning procedures and spirometric analysis incorporated into the postprocessing algorithms, to better control for confounding variables.