Carnosine supplementation and retinal oxidative parameters in a high-calorie diet rat model

BACKGROUND

To assess oxidative effects induced by a high-calorie diet on the retina of Wistar rats and test the antioxidative effects of carnosine supplementation.

METHODS

Wistar rats were randomly divided into the following groups: standard diet (SD), high-calorie diet (HcD), standard diet + carnosine (SD + Car), and high-calorie diet + carnosine (HcD + Car). The body weight, adiposity index, plasma glucose, total lipids, high-density lipoprotein (HDL), low-density lipoprotein (LDL), uric acid, creatinine, and triglycerides of the animals were evaluated. The retinas were analyzed for markers of oxidative stress. Hydrogen peroxide production was assessed by 2',7'-dichlorodihydrofluorescein diacetate (DCF) oxidation. The total glutathione (tGSH), total antioxidant capacity (TAC), protein carbonyl, and sulfhydryl groups of the antioxidant system were analyzed.

RESULTS

TAC levels increased in the retinas of the SD + Car group compared to the SD group (p < 0.05) and in the HcD + Car group compared to the HcD group (p < 0.05). The levels of GSH and the GSSH:GSSG ratio were increased in the HcD + Car group compared to the SD + Car group (p < 0.05). An increase in the retinal carbonyl content was observed in the HcD group compared to the SD group (p < 0.05) and in the HcD + Car group compared to the SD + Car group (p < 0.05). A high-calorie diet (HcD) was also associated with a decrease in retinal sulfhydryl-type levels compared to the SD group (p < 0.05).

CONCLUSION

The results suggest that feeding a high-calorie diet to rats can promote an increase in carbonyl content and a reduction in sulfhydryl groups in their retinas. The administration of carnosine was not effective in attenuating these oxidative markers.

TRIAL REGISTRATION

Animal Ethics Committee of Botucatu Medical School - Certificate number 1292/2019.

Marker Identification and Classification of Cancer Types Using Gene Expression Data and SIMCA

Objectives: High-throughput technologies are radically boosting the understanding of living systems, thus creating enormous opportunities to elucidate the biological processes of cells in different physiological states. In particular, the application of DNA micro-arrays to monitor expression profiles from tumor cells is improving cancer analysis to levels that classical methods have been unable to reach. However, molecular diagnostics based on expression profiling requires addressing computational issues as the overwhelming number of variables and the complex, multi-class nature of tumor samples. Thus, the objective of the present research has been the development of a computational procedure for feature extraction and classification of gene expression data.

Methods: The Soft Independent Modeling of Class Analogy (SIMCA) approach has been implemented in a data mining scheme, which allows the identification of those genes that are most likely to confer robust and accurate classification of samples from multiple tumor types.

Results: The proposed method has been tested on two different microarray data sets, namely Golub’s analysis of acute human leukemia [1] and the small round blue cell tumors study presented by Khan et al. [2]. The identified features represent a rational and dimensionally reduced base for understanding the biology of diseases, defining targets of therapeutic intervention, and developing diagnostic tools for classification of pathological states.

Conclusions: The analysis of the SIMCA model residuals allows the identification of specific phenotype markers. At the same time, the class analogy approach provides the assignment to multiple classes, such as different pathological conditions or tissue samples, for previously unseen instances.

Expression of TNF-α and IL-6 cytokines in the choroid and sclera of hypercholesterolemic rabbits

PURPOSE

This study aimed to evaluate the expression of the inflammatory cytokines TNF-α and IL-6 in the sclera and choroid of hypercholesterolemic rabbits.

METHOD

Twenty-one New Zealand male albino rabbits were divided into two groups: NG and HG. The NG group was fed a standard rabbit diet and the HG group was fed a cholesterol-enriched diet (1%). The serum total cholesterol, triglyceride, HDL cholesterol, and fasting blood glucose levels were determined at the beginning of the experiment and on the day of euthanasia. Euthanasia of animals in the NG and HG groups was performed at the end of the 4th and 8th week, respectively. The eyes were analyzed immunohistochemically using TNF-α and IL-6 antibodies.

RESULTS

At the time of euthanasia, the HG group showed a significant increase in total cholesterol and triglyceride when compared with the NG group (p<0.001). When compared with the NG group, there was a significant increase in the expression of TNF-α (p<0.001) and IL-6 (p=0.002) in the choroid and sclera of animals in the HG group.

CONCLUSION

This study demonstrates that the hypercholesterolemic diet induces expression of TNF-α and IL-6 in the choroid and sclera of rabbits.

Effect of candesartan on the expression of sclera-choroidal intercellular adhesion molecule-1 in hypercholesterolemic models

OBJECTIVE

To evaluate the effect of blocking the angiotensin II AT-1 receptor by the systemic administration of candesartan on the expression of intercellular adhesion molecule-1 in the sclera and choroid of hypercholesterolemic rabbits.

METHODS

New Zealand rabbits were divided into 3 groups, as follows: GI, which was fed a rabbit standard diet; GII, which was fed a hypercholesterolemic diet; and GIII, which received hypercholesterolemic diet plus candesartan. Samples of the rabbits' sclera and choroid were then studied by hematoxylin-eosin staining and histomorphometric and immunohistochemical analyses for intercellular adhesion molecule-1 expression.

RESULTS

Histological analysis of hematoxylin- and eosin-stained sclera and choroid revealed that macrophages were rarely present in GI, and GII had significantly increased macrophage numbers compared to GIII. Moreover, in GII, the sclera and choroid morphometry showed a significant increase in thickness in comparison to GI and GIII. GIII presented a significant increase in thickness in relation to GI. Sclera and choroid immunohistochemical analysis for intercellular adhesion molecule-1 expression revealed a significant increase in immunoreactivity in GII in relation to GI and GIII. GIII showed a significant increase in immunoreactivity in relation to GI.

CONCLUSION

Candesartan reduced the expression of intercellular adhesion molecule-1 and consequently macrophage accumulation in the sclera and choroid of hypercholesterolemic rabbits.

Effect of olmesartan on leukocyte recruitment in choroid-sclera complex in hypercholesterolemia model

PURPOSE

Demonstrate that the blockade of angiotensin II AT-1 receptors, through the systemic administration of olmesartan, can reduce the MCP-1 expression and the resulting macrophage accumulation in the choroid and sclera of hypercholesterolemic rabbits.

METHODS

Thirty-two New Zealand rabbits were divided into 3 groups: group I (GI) was fed a standard rabbit diet; group II (GII) was fed a hypercholesterolemic diet; and group III (GIII) was fed a hypercholesterolemic diet plus olmesartan. Serum levels of total cholesterol, triglyceride, HDL cholesterol, and blood glucose were determined in fasting rabbits at the beginning of the experiment and on the day of euthanasia. The choroid and sclera were submitted to morphometric analysis as well as immunohistochemical analysis with MCP-1 and RAM-11 (macrophage marker) antibodies.

RESULTS

No abnormality was detected in GI. Group II and III had significant increases in choroid-sclera complex thicknesses when compared with group I (P<0.001). GII showed a significant increase in immunoreactivity for MCP-1 in relation to GI (P=0.001) and GIII (P=0.004). GII showed a significant increase in immunoreactivity for RAM-11 of the choroid-sclera complex in relation to GI (P<0.001) and GIII (P=0.034). A significant increase in immunoreactivity for RAM-11 was observed in GIII in relation to GI (P=0.008).

CONCLUSION

Olmesartan reduced the MCP-1 expression and the resultant macrophage accumulation in the choroid-sclera complex of hypercholesterolemic rabbits.

Nanoparticle technology: addressing the fundamental roadblocks to protein biomarker discovery

Clinically relevant biomarkers exist in blood and body fluids in extremely low concentrations, are masked by high abundance high molecular weight proteins, and often undergo degradation during collection and transport due to endogenous and exogenous proteinases. Nanoparticles composed of a N-isopropylacrylamide hydrogel core shell functionalized with internal affinity baits are a new technology that can address all of these critical analytical challenges for disease biomarker discovery and measurement. Core-shell, bait containing, nanoparticles can perform four functions in one step, in solution, in complex biologic fluids (e.g. blood or urine): a) molecular size sieving, b) complete exclusion of high abundance unwanted proteins, c) target analyte affinity sequestration, and d) complete protection of captured analytes from degradation. Targeted classes of protein analytes sequestered by the particles can be concentrated in small volumes to effectively amplify (up to 100 fold or greater depending on the starting sample volume) the sensitivity of mass spectrometry, western blotting, and immunoassays. The materials utilized for the manufacture of the particles are economical, stable overtime, and remain fully soluble in body fluids to achieve virtually 100 percent capture of all solution phase target proteins within a few minutes.

Marker identification and classification of cancer types using gene expression data and SIMCA

OBJECTIVES

High-throughput technologies are radically boosting the understanding of living systems, thus creating enormous opportunities to elucidate the biological processes of cells in different physiological states. In particular, the application of DNA micro-arrays to monitor expression profiles from tumor cells is improving cancer analysis to levels that classical methods have been unable to reach. However, molecular diagnostics based on expression profiling requires addressing computational issues as the overwhelming number of variables and the complex, multi-class nature of tumor samples. Thus, the objective of the present research has been the development of a computational procedure for feature extraction and classification of gene expression data.

METHODS

The Soft Independent Modeling of Class Analogy (SIMCA) approach has been implemented in a data mining scheme, which allows the identification of those genes that are most likely to confer robust and accurate classification of samples from multiple tumor types.

RESULTS

The proposed method has been tested on two different microarray data sets, namely Golub's analysis of acute human leukemia and the small round blue cell tumors study presented by Khan et al.. The identified features represent a rational and dimensionally reduced base for understanding the biology of diseases, defining targets of therapeutic intervention, and developing diagnostic tools for classification of pathological states.

CONCLUSIONS

The analysis of the SIMCA model residuals allows the identification of specific phenotype markers. At the same time, the class analogy approach provides the assignment to multiple classes, such as different pathological conditions or tissue samples, for previously unseen instances.

PCA disjoint models for multiclass cancer analysis using gene expression data

MOTIVATION

Microarray expression profiling appears particularly promising for a deeper understanding of cancer biology and to identify molecular signatures supporting the histological classification schemes of neoplastic specimens. However, molecular diagnostics based on microarray data presents major challenges due to the overwhelming number of variables and the complex, multiclass nature of tumor samples. Thus, the development of marker selection methods, that allow the identification of those genes that are most likely to confer high classification accuracy of multiple tumor types, and of multiclass classification schemes is of paramount importance.

RESULTS

A computational procedure for marker identification and for classification of multiclass gene expression data through the application of disjoint principal component models is described. The identified features represent a rational and dimensionally reduced base for understanding the basic biology of diseases, defining targets for therapeutic intervention, and developing diagnostic tools for the identification and classification of multiple pathological states. The method has been tested on different microarray data sets obtained from various human tumor samples. The results demonstrate that this procedure allows the identification of specific phenotype markers and can classify previously unseen instances in the presence of multiple classes.

Reliability of tympanometric measures obtained with children

Conductance and susceptance measurements at probe frequencies of 220 and 660 Hz from eleven children's ears at intervals of 1 min, 10 min, 1 day, and 1 week (7 to 10 days) were obtained utilizing the Grason-Stadler Otoadmittance Meter model 1720. All test-retest correlation coefficients were found to be statistically significant (p less than 0.05); therefore, reliability of tympanometric measures using this instrument with children seems to be adequate for clinical use.