Correction: Eid et al. Interference with TGFß1-Mediated Inflammation and Fibrosis Underlies Reno-Protective Effects of the CB1 Receptor Neutral Antagonists AM6545 and AM4113 in a Rat Model of Metabolic Syndrome. Molecules 2021, 26, 866.

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Effects of the CB1 receptor antagonists AM6545 and AM4113 on metabolic syndrome-induced prostatic hyperplasia in rats.

Metabolic syndrome (MetS) is a combination of metabolic disorders that can predispose individuals to benign prostatic hyperplasia (BPH). The inhibition of the cannabinoid 1 (CB1) receptor has been used to treat metabolic disorders in animal models. This study reports the use of a peripherally restricted CB1 antagonist (AM6545) and a neutral CB1 antagonist (AM4113) to improve MetS-related BPH in rats. Animals were divided into three control groups to receive either a normal rodent diet, AM6545, or AM4113. MetS was induced in the fourth, fifth, and sixth groups using a concentrated fructose solution and high-salt diet delivered as food pellets for eight weeks. The fifth and sixth groups were further given AM6545 or AM4113 for additional four weeks. Body and prostate weights were measured and prostate sections were stained with hematoxylin eosin. Cyclin D1, markers of oxidative stress and inflammation, and levels of the endocannabinoids were recorded. BPH in rats with MetS was confirmed through increased prostate weight and index, as well as histopathology. Treatment with either AM6545 or AM4113 significantly decreased prostate weight, improved prostate histology, and reduced cyclin D1 expression compared with the MetS group. Groups treated with CB1 antagonists experienced reduced lipid peroxidation, recovered glutathione depletion, restored catalase activity, and had lower inflammatory markers interleukin 6 (IL-6) and tumor necrosis factor alpha (TNF-α). MetS rats treated with either AM6545 or AM4113 showed reduced concentrations of anandamide (AEA) and 2-arachidonoylglycerol (2-AG) in the prostate compared with the MetS group. In conclusion, the CB1 antagonists AM6545 and AM4113 protect against MetS-induced BPH through their anti-proliferative, antioxidant, and anti-inflammatory effects.

Identification of marker genes in Alzheimer's disease using a machine-learning model.

Alzheimer's Disease (AD) is one of the most common causes of dementia, mostly affecting the elderly population. Currently, there is no proper diagnostic tool or method available for the detection of AD. The present study used two distinct data sets of AD genes, which could be potential biomarkers in the diagnosis. The differentially expressed genes (DEGs) curated from both datasets were used for machine learning classification, tissue expression annotation and co-expression analysis. Further, CNPY3, GPR84, HIST1H2AB, HIST1H2AE, IFNAR1, LMO3, MYO18A, N4BP2L1, PML, SLC4A4, ST8SIA4, TLE1 and N4BP2L1 were identified as highly significant DEGs and exhibited co-expression with other query genes. Moreover, a tissue expression study found that these genes are also expressed in the brain tissue. In addition to the earlier studies for marker gene identification, we have considered a different set of machine learning classifiers to improve the accuracy rate from the analysis. Amongst all the six classification algorithms, J48 emerged as the best classifier, which could be used for differentiating healthy and diseased samples. SMO/SVM and Logit Boost further followed J48 to achieve the classification accuracy.

Interference with TGFß1-Mediated Inflammation and Fibrosis Underlies Reno-Protective Effects of the CB1 Receptor Neutral Antagonists AM6545 and AM4113 in a Rat Model of Metabolic Syndrome.

The role of cannabinoid receptors in nephropathy is gaining much attention. This study investigated the effects of two neutral CB1 receptor antagonists, AM6545 and AM4113, on nephropathy associated with metabolic syndrome (MetS). MetS was induced in rats by high-fructose high-salt feeding for 12 weeks. AM6545, the peripheral silent antagonist and AM4113, the central neutral antagonist were administered in the last 4 weeks. At the end of study, blood and urine samples were collected for biochemical analyses while the kidneys were excised for histopathological investigation and transforming growth factor beta 1 (TGFß1) measurement. MetS was associated with deteriorated kidney function as indicated by the elevated proteinuria and albumin excretion rate. Both compounds equally inhibited the elevated proteinuria and albumin excretion rate while having no effect on creatinine clearance and blood pressure. In addition, AM6545 and AM4113 alleviated the observed swelling and inflammatory cells infiltration in different kidney structures. Moreover, AM6545 and AM4113 alleviated the observed histopathological alterations in kidney structure of MetS rats. MetS was associated with a ten-fold increase in urine uric acid while both compounds blocked this increase. Furthermore, AM6545 and AM4113 completely prevented the collagen deposition and the elevated expression of the TGFß1 seen in MetS animals. In conclusion, AM6545 and AM4113, possess reno-protective effects by interfering with TGFß1-mediated renal inflammation and fibrosis, via peripheral action.

Cucurbitacin E glucoside from Citrullus colocynthis inhibits testosterone-induced benign prostatic hyperplasia in mice.

Benign prostatic hyperplasia (BPH) is a common disorder in men aged over 60 years and significantly contributes to the distressing lower urinary tract symptoms. Cucurbitacins are triterpene derivatives with diverse medicinal uses including prostate diseases. Cucurbitacin E glucoside was evaluated against testosterone-induced prostatic hyperplasia in mice. Our data indicate that it significantly inhibited the increase in prostate weight and prostate index. The compound ameliorated histopathological changes in prostatic architecture and inhibited the increase in glandular epithelial length induced by testosterone. These results were confirmed by decreased expression of cyclin D1 in prostatic tissues compared to those obtained from the testosterone-alone group. Also, it showed significant antioxidant activity as evidenced by inhibiting lipid peroxides accumulation, glutathione depletion and superoxide exhaustion. Further, it exhibited anti-inflammatory activity as it decreased cyclooxygenase-2 and interleukin-1ß protein expression in prostatic tissues. Masson's trichrome staining of prostate sections indicated obvious antifibrotic activity that was supported by decreased α-smooth muscle actin expression. In conclusion, Cucurbitacin E glucoside inhibits testosterone-induced experimental BPH in mice due to, at least partly, its antiproliferative, antioxidant, anti-inflammatory, and antifibrotic effects.

2-Methoxyestradiol attenuates liver fibrosis in mice: implications for M2 macrophages.

Liver fibrosis is a major health problem worldwide due to its serious complications including cirrhosis and liver cancer. 2-Methoxyestradiol (2-ME) is an end metabolite of estradiol with anti-proliferative, antioxidant, and anti-inflammatory activities. However, the protective role of 2-ME in liver fibrosis has not been fully investigated. The aim of this study was to determine the protective effect of 2-ME in carbon tetrachloride (CCl4)-induced liver fibrosis in mice. Animals were injected intraperitoneally with CCl4 twice weekly for 6 weeks. 2-ME 50 mg/kg or 100 mg/kg was administrated intraperitoneally every day over the same period. Our data showed that 2-ME reduced the extent of liver toxicity and fibrosis due to CCl4 exposure. It restored the elevated serum liver enzymes aspartate aminotransferase (AST), alanine aminotransferase (ALT), and alkaline phosphatase (ALP) levels and ameliorated oxidative status. In addition, 2-ME significantly reduced collagen deposition and alpha-smooth muscle actin (α-SMA) protein expressions. Furthermore, 2-ME markedly lowered macrophage infiltration and macrophage alternative activation marker chitinase-like molecules (CHI3L3/YM1). The results of this study indicate an important protective activity of 2-ME in liver fibrosis and highlight the role of macrophage recruitment and alternative activation as a possible target.

Ginger Ingredients Alleviate Diabetic Prostatic Complications: Effect on Oxidative Stress and Fibrosis.

Prostatic complications are common in patients with diabetes. This study investigated the effect of different ginger ingredients: zingerone, geraniol, and 6-gingerol on the prostate in diabetic rats. Diabetes was induced in Wistar rats by streptozotocin intraperitoneal injection (50 mg/kg), and the rats were left for 10 weeks to develop prostatic complications. In diabetic treated groups, rats received daily oral zingerone, geraniol, and 6-gingerol in doses of 20, 200, and 75 mg/kg, respectively, in the last 8 weeks. Treatment with the compounds caused changes in the ventral prostate of diabetic animals as indicated by the columnar ductal epithelium and dense secretions. There was an amelioration of oxidative stress as evidenced by the lowering of prostate malondialdehyde and elevating prostate oxidized to reduced glutathione (GSH/GSSG) ratios by geraniol and 6-gingerol. None of the three ginger ingredients affected the hyperglycemia, reduction in body weight gain, and testosterone deficiency seen in diabetic animals. Interleukin-1ß and interleukin-6 levels remained unchanged. However, zingerone and geraniol ameliorated the fibrosis in diabetic prostate through suppressing the elevated prostate transforming growth factor beta 1 (TGFß1) and collagen IV. Therefore, ginger ingredients could be beneficial in alleviating diabetic prostatic complications through suppressing oxidative stress and tissue fibrosis.

A comprehensive evaluation of machine learning techniques for cancer class prediction based on microarray data.

Prostate cancer is among the most common cancer in males and its heterogeneity is well known. The genomic level changes can be detected in gene expression data and those changes may serve as standard model for any random cancer data for class prediction. Various techniques were implied on prostate cancer data set in order to accurately predict cancer class including machine learning techniques. Large number of attributes but few numbers of samples in microarray data leads to poor training; therefore, the most challenging part is attribute reduction or non-significant gene reduction. In this work, a combination of interquartile range and t-test is used for attribute reduction. Further, a comprehensive evaluation of ten state-of-the-art machine learning techniques for their accuracy in class prediction of prostate cancer is done. Out of these techniques, Bayes Network outperformed with an accuracy of 94.11% followed by Naïve Bayes with an accuracy of 91.17%.

An in silico analytical study of lung cancer and smokers datasets from gene expression omnibus (GEO) for prediction of differentially expressed genes.

Smoking is the leading cause of lung cancer development and several genes have been identified as potential biomarker for lungs cancer. Contributing to the present scientific knowledge of biomarkers for lung cancer two different data sets, i.e. GDS3257 and GDS3054 were downloaded from NCBI׳s GEO database and normalized by RMA and GRMA packages (Bioconductor). Diffrentially expressed genes were extracted by using and were R (3.1.2); DAVID online tool was used for gene annotation and GENE MANIA tool was used for construction of gene regulatory network. Nine smoking independent gene were found whereas average expressions of those genes were almost similar in both the datasets. Five genes among them were found to be associated with cancer subtypes. Thirty smoking specific genes were identified; among those genes eight were associated with cancer sub types. GPR110, IL1RN and HSP90AA1 were found directly associated with lung cancer. SEMA6A differentially expresses in only non-smoking lung cancer samples. FLG is differentially expressed smoking specific gene and is related to onset of various cancer subtypes. Functional annotation and network analysis revealed that FLG participates in various epidermal tissue developmental processes and is co-expressed with other genes. Lung tissues are epidermal tissues and thus it suggests that alteration in FLG may cause lung cancer. We conclude that smoking alters expression of several genes and associated biological pathways during development of lung cancers.

Chemical effects in biological systems--data dictionary (CEBS-DD): a compendium of terms for the capture and integration of biological study design description, conventional phenotypes, and 'omics data.

A critical component in the design of the Chemical Effects in Biological Systems (CEBS) Knowledgebase is a strategy to capture toxicogenomics study protocols and the toxicity endpoint data (clinical pathology and histopathology). A Study is generally an experiment carried out during a period of time for the purpose of obtaining data, and the Study Design Description captures the methods, timing, and organization of the Study. The CEBS Data Dictionary (CEBS-DD) has been designed to define and organize terms in an attempt to standardize nomenclature needed to describe a toxicogenomics Study in a structured yet intuitive format and provide a flexible means to describe a Study as conceptualized by the investigator. The CEBS-DD will organize and annotate information from a variety of sources, thereby facilitating the capture and display of toxicogenomics data in biological context in CEBS, i.e., associating molecular events detected in highly-parallel data with the toxicology/pathology phenotype as observed in the individual Study Subjects and linked to the experimental treatments. The CEBS-DD has been developed with a focus on acute toxicity studies, but with a design that will permit it to be extended to other areas of toxicology and biology with the addition of domain-specific terms. To illustrate the utility of the CEBS-DD, we present an example of integrating data from two proteomics and transcriptomics studies of the response to acute acetaminophen toxicity (A. N. Heinloth et al., 2004, Toxicol. Sci. 80, 193-202).

Epithelial cells in the oviduct and vagina and steroid-synthesizing cells in the rabbit ovary express AhR and ARNT.

The aryl hydrocarbon receptor (AhR) is a ligand-activated transcription factor. Beside exogenous ligands, an increasing list of endogenous ligands has recently been described. The AhR and its dimerization partner AhR nuclear translocator (ARNT) were found in embryos, fetuses and in genital tract tissue. Its role in reproduction and fertility is not known. In the current study, AhR and ARNT expression and co-localization were studied immunohistochemicaly during the pre-implantation period in various genital tract organs (ovary, oviduct, vagina) of the rabbit. In the ovary, the AhR was expressed in the steroid-secreting interstitial cells, in follicular and granulosa cells, and in lutein cells. The receptor was localized in the cytoplasm. A cytoplasmic localization was also found in the oviduct epithelium with a diffuse cytoplasmic staining in the ampulla and a localized cytoplasmic localization in the isthmus. In the vagina, AhR localization changed from cytoplasmic in the non-pregnant animal to nuclear staining in the basal layer of the vaginal epithelium on day 6 of pregnancy. The ARNT protein was found in all AhR expressing cells except for oocytes within primordial follicles. Its localization was in the cytoplasm and/or nuclei. Therefore, the full complement for AhR/ARNT transcriptional activity was found in the studied organs. AhR expression showed stage-specific changes in both the uterus (Hasan and Fischer 2001) and the vagina during the pre-implantation period, while the ARNT protein exhibited no change in expression during this period. In summary, these findings indicate a functional AhR/ARNT complex in the rabbit genital tract epithelia. Its precise role and activation mechanism in reproductive tissue is not clear. It is supposed, however, that this complex may be involved in both hormone production and hormone-induced cellular changes during early pregnancy of the rabbit.