Fine needles with echo markers: increasing cell dragging during biopsy.
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Biomedical subjects
S Rossi
Publications and source records attributed to S Rossi.
Characterization of rheological and mucoadhesive properties of three grades of chitosan hydrochloride.
In the present study the rheological and mucoadhesive properties of three viscosity grades of a cationic polymer, chitosan, were investigated to assess the suitability of this polymer for gastroadhesive formulations. The influence of the pH, ionic strength and temperature of the hydration medium on the rheological properties was studied. The mucoadhesive performance was assessed in vitro by means of rheological synergism and tensile stress testing. A correlation was found between rheological synergism and tensile parameters (force of detachment and work of adhesion), which proves that both methods can correctly predict the mucoadhesive performance of the polymers examined. It was found that the interaction of chitosan with mucin decreases on increasing molecular weight.
Biopolymers↗
[Neurosheet: an electronic sheet for neurosurgical intensive care].
PURPOSE: A growing number of monitoring and diagnostic instruments has considerably increased the amount of information available in the intensive care unit. A data collection system which can be useful in highlighting and processing the most relevant data for the care of head-injured patients (Neurosheet) has been set up. The purpose of this study is to describe Neurosheet and to analyse the results achieved through its use. ENVIRONMENT: Neurosurgical Intensive Care Unit. METHODS: Neurosheet consists of a data sheet which follows the course of some "key" variables in head-injured patients who undergo ICP monitoring for a period of more than 48 hours. SURVEY: Through a questionnaire distributed to the medical staff, the learning period and the opinion of the staff concerning the clinical usefulness of this instrument has been evaluated. The amount of time needed to compile Neurosheet has been measured and some criteria indicating its completeness identified. RESULTS: It has been found that Neurosheet can be learned quickly and is rather easy to use. Data resulting from the study of the learning curve and from the answers to the questionnaire, suggest that its learning period is quite short (10 to 20 minutes). Among the 28 eligible patients, Neurosheet was used for 24 (86%). The data collected show 1,912 hours of monitoring, with an average of 112.8 (+/- 55) hours per patient. Neurosheet was completed in 83% of the cases. CONCLUSIONS: The aim of Neurosheet is to provide an answer to the overload of information using computerised systems able to simplify and support the daily clinical work.
Critical Care↗