The ""single-section"" Golgi method adapted for formalin-fixed human brain and light microscopy

The Golgi method has been used for over a century to describe the general morphology of neurons in the nervous system of different species. The ""single-section"" Golgi method of Gabbott and Somogyi (1984) and the modifications made by Izzo et al. (1987) are able to produce consistent results. Here, we describe procedures to show cortical and subcortical neurons of human brains immersed in formalin for months or even years. The tissue was sliced with a vibratome, post-fixed in a combination of paraformaldehyde and picric acid in phosphate buffer, followed by osmium tetroxide and potassium dicromate, ""sandwiched"" between cover slips, and immersed in silver nitrate. The whole procedure takes between 5 and 11 days to achieve good results. The Golgi method has its characteristic pitfalls but, with this procedure, neurons and glia appear well-impregnated, allowing qualitative and quantitative studies under light microscopy. This contribution adds to the basic techniques for the study of human nervous tissue with the same advantages described for the ""single-section"" Golgi method in other species; it is easy and fast, requires minimal equipment, and provides consistent results. (C) 2010 Elsevier B.V. All rights reserved.

PREDICTION OF FAT-FREE MASS BY BIOELECTRICAL IMPEDANCE ANALYSIS IN OLDER ADULTS FROM DEVELOPING COUNTRIES: A CROSS-VALIDATION STUDY USING THE DEUTERIUM DILUTION METHOD

Objective: Several limitations of published bioelectrical impedance analysis (BIA) equations have been reported. The aims were to develop in a multiethnic, elderly population a new prediction equation and cross-validate it along with some published BIA equations for estimating fat-free mass using deuterium oxide dilution as the reference method. Design and setting: Cross-sectional study of elderly from five developing countries. Methods: Total body water (TBW) measured by deuterium dilution was used to determine fat-free mass (FFM) in 383 subjects. Anthropometric and BIA variables were also measured. Only 377 subjects were included for the analysis, randomly divided into development and cross-validation groups after stratified by gender. Stepwise model selection was used to generate the model and Bland Altman analysis was used to test agreement. Results: FFM = 2.95 - 3.89 (Gender) + 0.514 (Ht(2)/Z) + 0.090 (Waist) + 0.156 (Body weight). The model fit parameters were an R(2), total F-Ratio, and the SEE of 0.88, 314.3, and 3.3, respectively. None of the published BIA equations met the criteria for agreement. The new BIA equation underestimated FFM by just 0.3 kg in the cross-validation sample. The mean of the difference between FFM by TBW and the new BIA equation were not significantly different; 95% of the differences were between the limits of agreement of -6.3 to 6.9 kg of FFM. There was no significant association between the mean of the differences and their averages (r = 0.008 and p = 0.2). Conclusions: This new BIA equation offers a valid option compared with some of the current published BIA equations to estimate FFM in elderly subjects from five developing countries.

An association rule-based method to support medical image diagnosis with efficiency

In this paper, we propose a method based on association rule-mining to enhance the diagnosis of medical images (mammograms). It combines low-level features automatically extracted from images and high-level knowledge from specialists to search for patterns. Our method analyzes medical images and automatically generates suggestions of diagnoses employing mining of association rules. The suggestions of diagnosis are used to accelerate the image analysis performed by specialists as well as to provide them an alternative to work on. The proposed method uses two new algorithms, PreSAGe and HiCARe. The PreSAGe algorithm combines, in a single step, feature selection and discretization, and reduces the mining complexity. Experiments performed on PreSAGe show that this algorithm is highly suitable to perform feature selection and discretization in medical images. HiCARe is a new associative classifier. The HiCARe algorithm has an important property that makes it unique: it assigns multiple keywords per image to suggest a diagnosis with high values of accuracy. Our method was applied to real datasets, and the results show high sensitivity (up to 95%) and accuracy (up to 92%), allowing us to claim that the use of association rules is a powerful means to assist in the diagnosing task.

Validation of a manual headspace gas chromatography method for determining volatile compounds in biological fluids

Background: We report the validation of a method for the determination of acetaldehyde, acetone, methanol, and ethanol in biological fluids using manual headspace sample introduction and an acetonitrile internal standard. Method: This method uses a capillary column (I = 30 m, I.D. = 0.25 mm, dF = 0.25 mu m) installed in a gas chromatography-flame ionization detector (GC-FID) apparatus with a run time of 7.5 minutes. Results: Analysis of the retention times and the resolution of the analyte peaks demonstrated excellent separation without widening of the peaks. Precision and accuracy were good (interassay precision < 15% and recovery between 85% and 115%) in both blood and urine. Conclusion: The method was linear (r > 0.09) over the analytical measurement range (AMR) of each analyte.

Validation of ACB in vitro and in vivo as a biomagnetic method for measuring stomach contraction

Background The aim of this study was to validate a biomagnetic method (alternate current biosusceptometry, ACB) for monitoring gastric wall contractions in rats. Methods In vitro data were obtained to establish the relationship between ACB and the strain-gauge (SG) signal amplitude. In vivo experiments were performed in pentobarbital-anesthetized rats with SG and magnetic markers previously implanted under the gastric serosa or after ingestion of magnetic material. Gastric motility was quantified from the tracing amplitudes and frequency profiles obtained by Fast Fourier Transform. Key Results The correlation between in vitro signal amplitudes was strong (R = 0.989). The temporal cross-correlation coefficient between the ACB and SG signal amplitude was higher (P < 0.0001) in the postprandial (88.3 +/- 9.1 V) than in the fasting state (31.0 +/- 16.9 V). Irregular signal profiles, low contraction amplitudes, and smaller signal-to-noise ratios explained the poor correlation between techniques for fasting-state recordings. When a magnetic material was ingested, there was also strong correlation in the frequency and signal amplitude and a small phase-difference between the techniques. The contraction frequencies using ACB were 0.068 +/- 0.007 Hz (postprandial) and 0.058 +/- 0.007 Hz (fasting) (P < 0.002) and those using SG were 0.066 +/- 0.006 Hz (postprandial) and 0.059 +/- 0.008 Hz (fasting) (P < 0.005). Conclusions & Inferences In summary, ACB is reliable for monitoring gastric wall contractions using both implanted and ingested magnetic materials, and may serve as an accurate and sensitive technique for gastrointestinal motility studies.