The use of morphological characteristics and texture analysis in the identification of tissue composition in prostatic neoplasia

Quantitative examination of prostate histology offers clues in the diagnostic classification of lesions and in the prediction of response to treatment and prognosis. To facilitate the collection of quantitative data, the development of machine vision systems is necessary. This study explored the use of imaging for identifying tissue abnormalities in prostate histology. Medium-power histological scenes were recorded from whole-mount radical prostatectomy sections at × 40 objective magnification and assessed by a pathologist as exhibiting stroma, normal tissue (nonneoplastic epithelial component), or prostatic carcinoma (PCa). A machine vision system was developed that divided the scenes into subregions of 100 × 100 pixels and subjected each to image-processing techniques. Analysis of morphological characteristics allowed the identification of normal tissue. Analysis of image texture demonstrated that Haralick feature 4 was the most suitable for discriminating stroma from PCa. Using these morphological and texture measurements, it was possible to define a classification scheme for each subregion. The machine vision system is designed to integrate these classification rules and generate digital maps of tissue composition from the classification of subregions; 79.3% of subregions were correctly classified. Established classification rates have demonstrated the validity of the methodology on small scenes; a logical extension was to apply the methodology to whole slide images via scanning technology. The machine vision system is capable of classifying these images. The machine vision system developed in this project facilitates the exploration of morphological and texture characteristics in quantifying tissue composition. It also illustrates the potential of quantitative methods to provide highly discriminatory information in the automated identification of prostatic lesions using computer vision.

Cloning from tissue surrogates: antimicrobial peptide (esculentin) cDNAs from the defensive skin secretions of Chinese ranid frogs

The defensive skin secretions of amphibians are a rich source of bioactive peptides. Here we describe a rapid technique for skin granular gland transcriptome cloning from a surrogate tissue-the secretion itself. cDNA libraries were constructed from lyophilized skin secretion from each of the Chinese frogs (Rana schmackeri, Rana versabilis, and Rana plancyi fukienensis) using magnetic oligo(dT) bead-captured polyadenylated mRNA as templates. Specific esculentin cDNAs were amplified by 3'-RACE using a degenerate primer designed for a consensus nucleotide sequence in the 5' untranslated region of previously characterized ranid frog peptide cDNAs. The cloned cDNAs were found to encode the antimicrobial peptides esculentins 1 and 2 from each of the species examined. The presence of predicted peptide structures in skin secretions was confirmed by MALDI-TOF mass spectrometry and automated Edman degradation. This experimental approach can thus rapidly expedite parallel transcriptome and peptidome analysis of amphibian granular gland secretions without harming or sacrificing donor animals.

Prediction of adipose tissue composition using Raman spectroscopy: average properties and individual fatty acids.

Abstract: Raman spectroscopy has been used for the first time to predict the FA composition of unextracted adipose tissue of pork, beef, lamb, and chicken. It was found that the bulk unsaturation parameters could be predicted successfully [R-2 = 0.97, root mean square error of prediction (RMSEP) = 4.6% of 4 sigma], with cis unsaturation, which accounted for the majority of the unsaturation, giving similar correlations. The combined abundance of all measured PUFA (>= 2 double bonds per chain) was also well predicted with R-2 = 0.97 and RMSEP = 4.0% of 4 sigma. Trans unsaturation was not as well modeled (R-2 = 0.52, RMSEP = 18% of 4 sigma); this reduced prediction ability can be attributed to the low levels of trans FA found in adipose tissue (0.035 times the cis unsaturation level). For the individual FA, the average partial least squares (PLS) regression coefficient of the 18 most abundant FA (relative abundances ranging from 0.1 to 38.6% of the total FA content) was R-2 = 0.73; the average RMSEP = 11.9% of 4 sigma. Regression coefficients and prediction errors for the five most abundant FA were all better than the average value (in some cases as low as RMSEP = 4.7% of 4 sigma). Cross-correlation between the abundances of the minor FA and more abundant acids could be determined by principal component analysis methods, and the resulting groups of correlated compounds were also well-predicted using PLS. The accuracy of the prediction of individual FA was at least as good as other spectroscopic methods, and the extremely straightforward sampling method meant that very rapid analysis of samples at ambient temperature was easily achieved. This work shows that Raman profiling of hundreds of samples per day is easily achievable with an automated sampling system.

Tissue factor expression on monocyte subpopulations during normal pregnancy.

Pregnancy is often referred to as a hypercoaguable state due to changes in the haemostatic system. Tissue factor (TF) is the initiator of blood clotting in vivo. The effect of pregnancy on monocyte TF expression was determined in a longitudinal case control study, (89 pregnant, 39 non-pregnant). Using whole blood flow cytometry and CD14 as a monocyte marker, TF expression was measured on all CD14 positive, CD14Bright and CD14Dim cells. TF expression was significantly lower in pregnant women than in non-pregnant control subjects, on all CD14 positive cells at 20 and 35 weeks, on CD14Bright cells at 12 and 35 weeks and on CD14Dim cells at 20 weeks. Additionally, we report that a higher percentage of CD14Dim than CD14Bright cells express TF. These results suggest that, in order to maintain homeostasis in haemostasis in an otherwise hypercoaguable state, monocyte TF expression is reduced during normal pregnancy.