Automated Image Analysis System Research Articles

Population vulnerability due to the exposure to radon and airborne particulate matter (PM 10), in Mexico City

Exposure to indoor radon and suspended particulate matter (SPM) is considered a high risk in lung cancer aetiology. In this paper indoor radon and SPM concentration measurements and their correlations, associated with lung cancer cases are given. Mexico City suffers high concentration of SPM as well as other photochemical pollutants such as ozone. During the last decade in Mexico City, radon and SPM have been monitored. The indoor radon measurements were done using the Nuclear Track Methodology, basically the close-end-cup device with polyallyldiglycol carbonate as detector material, followed of an established chemical etching protocol, and automatic digital image analyzer system for counting. SPM size and concentration were obtained from monitoring stations located along the city. The results show that the central–north part of Mexico City has a large concentration of SPM and the vulnerable population (older than 65 years and younger than 14 years) is located essentially in the same region. In this area, a large number of lung cancer cases were found, even if indoor radon levels were below the recommended limits.

Statistical and Economical Efficiency in Assessment of Liver Regeneration Using Defined Sample Size and Selection in Combination With a Fully Automated Image Analysis System

Quantification of liver regeneration is frequently based on determining the 5-bromo-2-deoxyuridine labeling index (BrdU-LI). The quantitative result is influenced by preanalytical, analytical, and postanalytical variables such as the region of interest (ROI). We aimed to present our newly developed and validated automatic computer-based image analysis system (AnalySIS-Macro), and to standardize the selection and sample size of ROIs. Images from BrdU-labeled and immunohistochemically stained liver sections were analyzed conventionally and with the newly developed AnalySIS-Macro and used for validation of the system. Automatic quantification correlated well with the manual counting result (r=0.9976). Validation of our AnalySIS-Macro revealed its high sensitivity (>90%) and specificity. The BrdU-LI ranged from 11% to 57% within the same liver (32.96 +/- 11.94%), reflecting the highly variable spatial distribution of hepatocyte proliferation. At least 2000 hepatocytes (10 images at 200x magnification) per lobe were required as sample size for achieving a representative BrdU-LI. Furthermore, the number of pericentral areas should be equal to that of periportal areas. The combination of our AnalySIS-Macro with rules for the selection and size of ROIs represents an accurate, sensitive, specific, and efficient diagnostic tool for the determination of the BrdU-LI and the spatial distribution of proliferating hepatocytes.

Encapsulation of Pediococcus acidilactici cells in corn and olive oil microcapsules emulsified by peptides and stabilized with xanthan in oil-in-water emulsions: Studies on cell viability under gastro-intestinal simulating conditions

Three different encapsulation systems were developed in the form of oil-in-water acidic emulsions (pH 3.0) with the oil phase in the form of microdroplets in which Pediococcus acidilactici cells were enclosed. The first emulsion contained corn oil microdroplets (mean diameter 1.5 μm) emulsified with peptides and stabilized with SDS. The other two, were food grade systems with microdroplets of corn or olive oil (m.d. 2.1 and 2.2 μm, respectively) emulsified with peptides and stabilized with xanthan. In all systems, meat peptone, a rich source of peptides and amino acids, was provided in aqueous solution in which the cultures were suspended. Peptone derived peptides acted as emulsifiers and at the same time as nutrient substrates and osmoprotectants for cells. Emulsions were stored for 30 days at 4 °C. During this period, samples were examined for physical stability and viability of the encapsulated and freely suspended microorganisms present in the emulsions. Examinations were made through phase contrast microscopy and subsequent image capture and analysis with an automatic image analysis system. Viable and non-viable cells were discriminated on the basis of color differences produced through staining with trypan blue. The method permitted extraction of a large amount of information and produced large amounts of data through automated measurements on images. Emulsion characteristics and cell viabilities were also examined under conditions simulating the gastro-intestinal environment. Encapsulation proved to be critical since, following successive treatments of samples with simulated gastric juice (pH 2.0) and intestinal juice (pH 7.4), it ensured viability rates of encapsulated cells as high as 85% and delivered as much as 92% of the initially encapsulated cells to the target point. The formulated emulsion systems may have a large number of applications in the food sector provided further studies on engineering properties and improvements of stability over a wide pH range are carried out.

Inter-observer reproducibility of HER2 immunohistochemical assessment and concordance with fluorescent in situhybridization (FISH): pathologist assessment compared to quantitative image analysis

BackgroundIn breast cancer patients, HER2 overexpression is routinely assessed by immunohistochemistry (IHC) and equivocal cases are subject to fluorescent in situ hybridization (FISH). Our study compares HER2 scoring by histopathologists with automated quantitation of staining, and determines the concordance of IHC scores with FISH results.MethodsA tissue microarray was constructed from 1,212 invasive breast carcinoma cases with linked treatment and outcome information. IHC slides were semi-quantitatively scored by two independent pathologists on a range of 0 to 3+, and also analyzed with an Ariol automated system by two operators. 616 cases were scorable by both IHC and FISH.ResultsUsing data from unequivocal positive (3+) or negative (0, 1+) results, both visual and automated scores were highly consistent: there was excellent concordance between two pathologists (kappa = 1.000, 95% CI: 1-1), between two machines (kappa = 1.000, 95% CI: 1-1), and between both visual and both machine scores (kappa = 0.898, 95% CI: 0.775–0.979). Two pathologists successfully distinguished negative, positive and equivocal cases (kappa = 0.929, 95% CI: 0.909–0.946), with excellent agreement with machine 1 scores (kappa = 0.835, 95% CI: 0.806–0.862; kappa = 0.837, 95% CI: 0.81–0.862), and good agreement with machine 2 scores (kappa = 0.698, 95% CI: 0.6723–0.723; kappa = 0.709, 95% CI: 0.684–0.732), whereas the two machines showed good agreement (kappa = 0.806, 95% CI: 0.785–0.826). When comparing categorized IHC scores and FISH results, the agreement was excellent for visual 1 (kappa = 0.814, 95% CI: 0.768–0.856), good for visual 2 (kappa = 0.763, 95% CI: 0.712–0.81) and machine 1 (kappa = 0.665, 95% CI: 0.609–0.718), and moderate for machine 2 (kappa = 0.535, 95% CI: 0.485–0.584).ConclusionA fully automated image analysis system run by an experienced operator can provide results consistent with visual HER2 scoring. Further development of such systems will likely improve the accuracy of detection and categorization of membranous staining, making this technique suitable for use in quality assurance programs and eventually in clinical practice.

Effect of pattern of lymphocyte infiltration in NSCLC on outcome

11079 Background: The role played by the immune system in determining survival in non-small-cell lung cancer (NSCLC) is unclear. The aim of this study was to investigate the prognostic significance of T-lymphocyte infiltration in NSCLC focusing on CD3+, cytotoxic CD8+ and FOXP3+ T regulatory (Treg) cells. Methods: Immunohistochemistry was used to detect CD3+, CD8+ and FOXP3+ lymphocytes in the tumor islets and tumor stroma in 186 patients with surgically resected NSCLC with a minimum follow-up of 3 years. Quantification of immune infiltration was performed using the Aperio automated image analysis system incorporating the Genie software tool. The median of tumor:stroma CD3+, CD8+ and FOXP3+ infiltration ratios were used as thresholds to dichotomise patients to either high or low infiltration rates. Prognostic variables were identified using univariate and Cox multivariate analysis. Kaplan-Meier analysis and the log-rank test were used to illustrate differences in overall survival. Results: Patients with a higher intratumoral CD3+ and CD8+ lymphocyte infiltration ratio had significantly better survival compared to those with a low tumour/stroma infiltration ratio (p=0.023 & <0.001 respectively). Conversely high intratumoral T-regulatory FOXP3+ positive lymphocyte infiltration rates were associated with a particularly poor prognosis independent of surgical stage (p<0.001). Conclusions: Microlocalization of infiltrating T-lymphocytes, in particular Treg cells, is a powerful predictor of outcome for surgically resected NSCLC and compares favourably with recently published prognostic genomic approaches. Assessment of inflammatory cell infiltrates may help determine which patients should receive adjuvant chemotherapy and, in the future, in predicting benefit from novel adjuvant vaccine/immunotherapies. No significant financial relationships to disclose.

Determination of Myosin Filament Orientations in Electron Micrographs of Muscle Cross Sections

An automated image analysis system for determining myosin filament azimuthal rotations, or orientations, in electron micrographs of muscle cross sections is described. The micrographs of thin sections intersect the myosin filaments which lie on a triangular lattice. The myosin filament profiles are variable and noisy, and the images exhibit a variable contrast and background. Filament positions are determined by filtering with a point spread function that incorporates the local symmetry of the lattice. Filament orientations are determined by correlation with a template that incorporates the salient filament characteristics, and the orientations are classified using a Gaussian mixture model. The precision of the technique is assessed by application to a variety of micrographs and comparison with manual classification of the orientations. The system provides a convenient, robust, and rapid means of analysing micrographs containing many filaments to study the distribution of filament orientations.

Novel autoantigens immunogenic in COPD patients

BackgroundChronic obstructive pulmonary disease (COPD) is a respiratory inflammatory condition with autoimmune features including IgG autoantibodies. In this study we analyze the complexity of the autoantibody response and reveal the nature of the antigens that are recognized by autoantibodies in COPD patients.MethodsAn array of 1827 gridded immunogenic peptide clones was established and screened with 17 sera of COPD patients and 60 healthy controls. Protein arrays were evaluated both by visual inspection and a recently developed computer aided image analysis technique. By this computer aided image analysis technique we computed the intensity values for each peptide clone and each serum and calculated the area under the receiver operator characteristics curve (AUC) for each clone and the separation COPD sera versus control sera.ResultsBy visual evaluation we detected 381 peptide clones that reacted with autoantibodies of COPD patients including 17 clones that reacted with more than 60% of the COPD sera and seven clones that reacted with more than 90% of the COPD sera. The comparison of COPD sera and controls by the automated image analysis system identified 212 peptide clones with informative AUC values. By in silico sequence analysis we found an enrichment of sequence motives previously associated with immunogenicity.ConclusionThe identification of a rather complex humoral immune response in COPD patients supports the idea of COPD as a disease with strong autoimmune features. The identification of novel immunogenic antigens is a first step towards a better understanding of the autoimmune component of COPD.

Can automated blood film analysis replace the manual differential? An evaluation of the CellaVision DM96 automated image analysis system

Automation of differentials is desirable for economic and time-saving reasons. Over the last 20 years, automated imaging processes have started to be introduced where stained blood films are scanned by a computer-driven microscope and leucocytes classified; however, early methods were slow and had difficulty in classifying abnormal cells. More recently the CellaVision DM96 (CellaVision AB, Lund, Sweden) has been introduced with added features such as continuous loading of slides and a faster throughput than previous instruments. The accuracy of CellaVision DM96 has been evaluated by comparing results to reference manual differentials. Results from different operators using the DM96 were compared with their own manual differential and to a 400-cell reference manual differential. Precision of the instrument was compared to the manual differential. The preclassification accuracy of the DM96 was 89.2%. Precision was similar to that of the 100-cell manual differential. The DM96 was faster than the manual method, even after reclassification by a laboratory scientist of any cells wrongly categorized by the instrument. The DM96 accuracy in morphological classification of leucocytes and red blood cells; depends upon both blood pathology and experience of the laboratory scientist using the instrument. For some cell types and operators, DM96 accuracy was better than the individual's 100 cell manual differential.

Irs2 Inactivation Suppresses Tumor Progression in Pten+/− Mice

Mutations in the phosphatase and tensin homologue (PTEN)/phosphatidylinositol-3 kinase-alpha (PI3K) signaling pathway are frequently found in human cancer. In addition, Pten(+/-) mice develop tumors in multiple organs because of the activation of the PI3K signaling cascade. Because activation of PI3K signaling leads to feedback inhibition of insulin receptor substrate-2 (IRS2) expression, an upstream activator of PI3K, we therefore anticipated that IRS2 expression would be low in tumors that lack PTEN. Surprisingly, however, an elevation of IRS2 was often detected in tumor samples in which PTEN levels were compromised. To determine the potential contribution of Irs2 to tumor progression, Pten(+/-) mice were crossed with Irs2(+/-) mice. Deletion of Irs2 did not affect the initiation of neoplasia found in Pten(+/-) mice but suppressed cancer cell growth, proliferation, and invasion through the basement membrane. Deletion of Irs2 also attenuated the expression of Myc in prostatic intraepithelial neoplasia in Pten(+/-) mice. In addition, the expression levels of IRS2 and MYC were highly correlated in human prostate cancer, and IRS2 could stimulate MYC expression in cultured cells. Our findings provide evidence that the PI3K-activating adaptor Irs2 contributes to tumor progression in Pten(+/-) mice by stimulating both Myc and DNA synthesis.

Performance evaluation and relevance of the CellaVisionTM DM96 system in routine analysis and in patients with malignant hematological diseases

The CellaVision™ DM96 is an automated image analysis system dedicated to locating and preclassifying the various types of white blood cells in peripheral blood smears. The system also partially characterizes of the red blood cell morphology and is able to perform platelet counts. We routinely analyzed the blood samples from 440 patients with quantitative and/or qualitative abnormalities detected by the XE-2100 Sysmex™. Only 2.6% of cells are not identified by DM96™. After classification of the unidentified cells very good correlation coefficients are observed between DM96™ and manual microscopy for most hematological parameters and accuracy is judged excellent up to 98%. For most common parameters, false positive and false negative ratios are also very good. Whatever the pathology and the number of blasts on smear, all patients were positive for blast detection on DM96™. The system is a useful tool for assisting in the diagnosis and classification of most acute or chronic leukemia. Automatic cell location and preclassification, along with unique cell views on the computer screen, could reduce the time spent performing differentials and make real-time collaboration between colleagues a natural part of the classification process. The workstation also provides an ergonomically correct and relaxed working environment. We suggest its use in routine analysis; the system could be very helpful for the accurate morphological diagnosis of samples from patients with malignant hematological disease.

The correlation between cellular size and protein expression levels — Normalization for global protein profiling

An automated image analysis system was used for protein quantification of 1862 human proteins in 47 cancer cell lines and 12 clinical cell samples using cell microarrays and immunohistochemistry. The analysis suggests that most proteins are expressed in a cell size dependent manner, and that normalization is required for comparative protein quantification in order to correct for the inherent bias of cell size and systematic ambiguities associated with immunohistochemistry. Two reference standards were evaluated, and normalized protein expression values were found to allow for protein profiling across a panel of morphologically diverse cells, revealing putative patterns of over- and underexpression. Using this approach, proteins with stable expression as well as cell-line specific expression were identified. The results demonstrate the value of large-scale, automated proteome analysis using immunohistochemistry, in revealing functional correlations and establishing methods to interpret and mine proteomic data.

Primary Cutaneous Small/Medium CD4+ T-Cell Lymphomas: A Heterogeneous Group of Tumors With Different Clinicopathologic Features and Outcome

To define the clinical and pathologic characteristics of primary cutaneous small/medium CD4(+) T-cell lymphoma (PCSM-TCL) and identify parameters of prognostic significance. We have investigated 24 patients with primary cutaneous lymphomas composed of small/medium mature T-cells with a betaF1, CD3, CD4(+) and/or noncytotoxic, CD8(-) and CD30(-) phenotype. The proliferation index and CD8(+) infiltrating cells were quantified with an automated image analysis system. Sixteen patients presenting with solitary or localized plaques or small nodules (< 3 cm) had an indolent course. Only three patients experienced repeated cutaneous relapses, and none of them died as a result of the disease after 1 to 168 months (median, 17 months) of follow-up. The tumors had a low proliferation (median Ki-67, 9% +/- 5%) and an intense infiltrate of reactive CD8(+) (median, 20% +/- 11.7%). Five patients presenting with rapidly evolving large tumors or nodules (>/= 5 cm) had an aggressive disease and died with extracutaneous dissemination 18 to 36 months after diagnosis (median, 23 months). These tumors had a significantly higher proliferation (median Ki-67, 22% +/- 11.3%; P < .05) and lower number of infiltrating CD8(+) (median, 1% +/- 3%; P < .05) than the previous group. A third group of three patients had a peculiar clinical presentation with multifocal relapsing lesions without extracutaneous dissemination after a long period of follow-up ranging from 41 to 92 months. Histologically, these cases had an intense infiltrate of eosinophils. PCSM-TCL is a heterogeneous group of tumors with differentiated clinical and pathological characteristics with impact in the outcome of the patients.

Computerized Analysis of Retinal Vessel Width and Tortuosity in Premature Infants

To determine, with novel software, the feasibility of measuring the tortuosity and width of retinal veins and arteries from digital retinal images of infants at risk of retinopathy of prematurity (ROP). The Computer-Aided Image Analysis of the Retina (CAIAR) program was developed to enable semiautomatic detection of retinal vasculature and measurement of vessel tortuosity and width from digital images. CAIAR was tested for accuracy and reproducibility of tortuosity and width measurements by using computer-generated vessel-like lines of known frequency, amplitude, and width. CAIAR was then tested by using clinical digital retinal images for correlation of vessel tortuosity and width readings compared with expert ophthalmologist grading. When applied to 16 computer-generated sinusoidal vessels, the tortuosity measured by CAIAR correlated very well with the known values. Width measures also increased as expected. When the CAIAR readings were compared with five expert ophthalmologists' grading of 75 vessels on 10 retinal images, moderate correlation was found in 10 of the 14 tortuosity output calculations (Spearman rho = 0.618-0.673). Width was less well correlated (rho = 0.415). The measures of tortuosity and width in CAIAR were validated using sequential model vessel analysis. On comparison of CAIAR output with assessments made by expert ophthalmologists, CAIAR correlates moderately with tortuosity grades, but less well with width grades. CAIAR offers the opportunity to develop an automated image analysis system for detecting the vascular changes at the posterior pole, which are becoming increasingly important in diagnosing treatable ROP.

Low-dose ionizing radiation and chromosome translocations: A review of the major considerations for human biological dosimetry

Chromosome translocations are a molecular signature of ionizing radiation exposure. Translocations persist significantly longer after exposure than other types of chromosome exchanges such as dicentrics. This persistence makes translocations the preferred aberration type for performing radiation dosimetry under conditions of protracted exposure or when exposure assessments are temporally delayed. Low doses of radiation are inherently difficult to quantify because the frequency of induced events is low and the background level of translocations among unexposed subjects can show considerable variability. Analyses of translocation frequencies can be confounded by several factors, including age of the subject, lifestyle choices such as cigarette smoking, the presence of clones of abnormal cells, and possibly genotypic variability among subjects. No significant effects of gender or race have been observed, but racial differences have not been completely ruled out. Translocation analyses may be complicated by the presence of different types of exchanges, i.e., reciprocal or non-reciprocal, and because translocations sometimes occur as a component of complex exchanges that include other forms of chromosome rearrangements. Rates of radiation exposure, ranging from acute to chronic, are known to influence the accumulation of translocations and may also affect their persistence. The influences on translocation frequencies of low-dose radiation hypersensitivity as well as the bystander effect and the adaptive response remain poorly characterized. Thus, quantifying the relationship between radiation dose and the frequency of translocations in any given subject requires attention to multiple issues. Part of the solution to understanding the in vivo dose-response relationship is to have accurate estimates of the baseline levels of translocations in healthy unexposed subjects, and some work in this area has been accomplished. Long-term cytogenetic follow-up of exposed subjects is needed to characterize translocation persistence, which is especially relevant for risk analyses. More work also needs to be done in the area of quantifying the role of known confounders. Characterizing the role of genotype will be especially important. Improvements in the ability to use translocation frequencies for low-dose biological dosimetry will require scoring very large numbers of cells per subject, which may be accomplished by developing a rapid automated image analysis system. This work would enhance our comprehension of the effects of low-dose radiation exposure and could lead to significant improvements in understanding the relationship between chromosome damage and human health.

The Expression Level of Ligands for Natural Killer Cell Receptors Predicts Response to Bacillus Calmette-Guerin Therapy: A Pilot Study

Up to 90% of patients with high grade superficial bladder tumors experience tumor recurrence and up to 50% have progression despite bacillus Calmette-Guerin treatment. Natural killer cells have a major role in the mechanism of the response to bacillus Calmette-Guerin but the exact mechanisms are still elusive. The recently discovered natural cytotoxicity receptors are linked to the host response to viral infection and to cancer. We tested the hypothesis that tumor expression of natural cytotoxicity receptor ligands can serve as a predictive factor for the response to intravesical bacillus Calmette-Guerin in patients with nonmuscle invasive, high grade bladder cancer. We developed a histochemical staining method for analysis of the ligands of the 3 known natural cytotoxicity receptors NKp30, NKp44 and NKp46 using genetically engineered fusion proteins and an automated image analysis system. We examined formalin fixed, paraffin embedded sections of specimens of transurethral bladder tumor resection from patients with primary, nonmuscle invasive, high grade bladder cancer who were subsequently treated with bacillus Calmette-Guerin. We compared natural cytotoxicity receptor ligand expression to the response to bacillus Calmette-Guerin immunotherapy. Six of 17 patients (35%) had recurrence despite bacillus Calmette-Guerin treatment. Primary tumors from favorably responding patients expressed higher levels of ligands for all 3 fusion proteins (NKp30, NKp44 and NKp46 p = 0.0026, 0.027 and 0.044, respectively). Bacillus Calmette-Guerin resistant, high grade, nonmuscle invasive bladder tumors express significantly lower levels of ligands of all 3 natural cytotoxicity receptors compared with bacillus Calmette-Guerin responsive tumors. This suggests that down-regulation of these ligands facilitates escape from the bacillus Calmette-Guerin effect. Furthermore, analysis of ligand expression, which can be performed on formalin fixed, paraffin embedded sections, may serve as a new predictive assay for the response to bacillus Calmette-Guerin.

Boosting multiclass learning with repeating codes and weak detectors for protein subcellular localization

Determining locations of protein expression is essential to understand protein function. Advances in green fluorescence protein (GFP) fusion proteins and automated fluorescence microscopy allow for rapid acquisition of large collections of protein localization images. Recognition of these cell images requires an automated image analysis system. Approaches taken by previous work concentrated on designing a set of optimal features and then applying standard machine-learning algorithms. In fact, trends of recent advances in machine learning and computer vision can be applied to improve the performance. One trend is the advances in multiclass learning with error-correcting output codes (ECOC). Another trend is the use of a large number of weak detectors with boosting for detecting objects in images of real-world scenes. We take advantage of these advances to propose a new learning algorithm, AdaBoost.ERC, coupled with weak and strong detectors, to improve the performance of automatic recognition of protein subcellular locations in cell images. We prepared two image data sets of CHO and Vero cells and downloaded a HeLa cell image data set in the public domain to evaluate our new method. We show that AdaBoost.ERC outperforms other AdaBoost extensions. We demonstrate the benefit of weak detectors by showing significant performance improvements over classifiers using only strong detectors. We also empirically test our method's capability of generalizing to heterogeneous image collections. Compared with previous work, our method performs reasonably well for the HeLa cell images. CHO and Vero cell images, their corresponding feature sets (SSLF and WSLF), our new learning algorithm, AdaBoost.ERC, and Supplementary Material are available at http://aiia.iis.sinica.edu.tw/

High content image analysis for human H4 neuroglioma cells exposed to CuO nanoparticles

BackgroundHigh content screening (HCS)-based image analysis is becoming an important and widely used research tool. Capitalizing this technology, ample cellular information can be extracted from the high content cellular images. In this study, an automated, reliable and quantitative cellular image analysis system developed in house has been employed to quantify the toxic responses of human H4 neuroglioma cells exposed to metal oxide nanoparticles. This system has been proved to be an essential tool in our study.ResultsThe cellular images of H4 neuroglioma cells exposed to different concentrations of CuO nanoparticles were sampled using IN Cell Analyzer 1000. A fully automated cellular image analysis system has been developed to perform the image analysis for cell viability. A multiple adaptive thresholding method was used to classify the pixels of the nuclei image into three classes: bright nuclei, dark nuclei, and background. During the development of our image analysis methodology, we have achieved the followings: (1) The Gaussian filtering with proper scale has been applied to the cellular images for generation of a local intensity maximum inside each nucleus; (2) a novel local intensity maxima detection method based on the gradient vector field has been established; and (3) a statistical model based splitting method was proposed to overcome the under segmentation problem. Computational results indicate that 95.9% nuclei can be detected and segmented correctly by the proposed image analysis system.ConclusionThe proposed automated image analysis system can effectively segment the images of human H4 neuroglioma cells exposed to CuO nanoparticles. The computational results confirmed our biological finding that human H4 neuroglioma cells had a dose-dependent toxic response to the insult of CuO nanoparticles.

Identification of a Potential Cardiac Antifibrotic Mechanism of Torasemide in Patients With Chronic Heart Failure

This study sought to investigate whether torasemide inhibits the enzyme involved in the myocardial extracellular generation of collagen type I molecules (i.e., procollagen type I carboxy-terminal proteinase [PCP]). Torasemide has been reported to reduce myocardial fibrosis in patients with chronic heart failure (HF). Chronic HF patients received either 10 to 20 mg/day oral torasemide (n = 11) or 20 to 40 mg/day oral furosemide (n = 11) in addition to their standard HF therapy. At baseline and after 8 months from randomization, right septal endomyocardial biopsies were obtained to analyze the expression of PCP by Western blot and the deposition of collagen fibers (collagen volume fraction [CVF]) with an automated image analysis system. The carboxy-terminal propeptide of procollagen type I (PICP) released as a result of the action of PCP on procollagen type I was measured in serum by radioimmunoassay. The ratio of PCP active form to PCP zymogen, an index of PCP activation, decreased (p < 0.05) in torasemide-treated patients and remained unchanged in furosemide-treated patients. A reduction (p < 0.01) in both CVF and PICP was observed in torasemide-treated but not in furosemide-treated patients. Changes in PCP activation were positively correlated (p < 0.001) with changes in CVF and changes in PICP in patients receiving torasemide. These findings suggest the hypothesis that the ability of torasemide to reduce myocardial fibrosis in chronic HF patients is related to a decreased PCP activation. Further studies are required to ascertain whether PCP may represent a new target for antifibrotic strategies in chronic HF.

Quantitative image analysis in adipose tissue using an automated image analysis system: Differential effects of peroxisome proliferator‐activated receptor‐α and ‐γ agonist on white and brown adipose tissue morphology in AKR obese and db/db diabetic mice

Morphometric analysis of adipocytes is widely used to demonstrate the effects of antiobesity drugs or anti-diabetic drugs on adipose tissues. However, adipocyte morphometry has been quantitatively performed by manual object extraction using conventional image analysis systems. The authors have developed an automated quantitative image analysis method for adipose tissues using an innovative object-based quantitative image analysis system (eCognition). Using this system, it has been shown quantitatively that morphological features of adipose tissues of mice treated with peroxisome proliferator-activated receptor (PPAR) agonists differ dramatically depending on the type of PPAR agonist. Marked alteration of morphological characteristics of brown adipose tissue (BAT) treated with GI259578A, a PPAR-alpha agonist, was observed in AKR/J (AKR) obese mice. Furthermore, there was a 22.8% decrease in the mean size of adipocytes in white adipose tissue (WAT) compared with vehicle. In diabetic db/db mice, the PPAR-gamma agonist GW347845X decreased the mean size of adipocytes in WAT by 15.4% compared with vehicle. In contrast to changes in WAT, GW347845X increased the mean size of adipocytes in BAT greatly by 96.1% compared with vehicle. These findings suggest that GI259578A may activate fatty acid oxidation in BAT and that GW347845X may cause adipocyte differentiation in WAT and enhancement of lipid storage in BAT.

Fragmentation studies of high-energy ions using CR39 nuclear track detectors

We report on the measurements of the total charge changing fragmentation cross-sections in high-energy nucleus–nucleus collisions using Fe, Si and Pb incident ions. Several stacks of CR39 nuclear track detectors with different target combinations were exposed at normal incidence to high-energy accelerator beams to integrated densities of about 2000 ions/cm 2. The nuclear track detector foils were chemically etched, and ion tracks were measured using an automatic image analyzer system. The cross-section determination is based on the charge identification of beam ions and their fragments and on the reconstruction of their path through the stacks.