A Molecular Mechanism to Explain the Nickel-Induced Changes in Protamine-like Proteins and Their DNA Binding Affecting Sperm Chromatin in Mytilus galloprovincialis: An In Vitro Study

: Nickel is associated with reproductive toxicity, but little is known about the molecular mechanisms of nickel-induced effects on sperm chromatin and protamine-like proteins (PLs). In the present work, we analyzed PLs from Mytilus galloprovincialis by urea-acetic acid polyacrylamide gel electrophoresis (AU-PAGE) and SDS-PAGE and assessed their binding to DNA by Electrophoretic Mobility Shift Assay (EMSA) after exposing mussels to 5, 15, and 35 µM NiCl2 for 24 h. In addition, a time course of digestion with MNase and release of PLs from sperm nuclei by the NaCl gradient was performed. For all exposure doses, in AU-PAGE, there was an additional migrating band between PL-III and PL-IV, corresponding to a fraction of PLs in the form of peptides detected by SDS-PAGE. Alterations in DNA binding of PLs were observed by EMSA after exposure to 5 and 15 µM NiCl2, while, at all NiCl2 doses, increased accessibility of MNase to sperm chromatin was found. The latter was particularly relevant at 15 µM NiCl2, a dose at which increased release of PLII and PLIII from sperm nuclei and the highest value of nickel accumulated in the gonads were also found. Finally, at all exposure doses, there was also an increase in PARP expression, but especially at 5 µM NiCl2. A possible molecular mechanism for the toxic reproductive effects of nickel in Mytilus galloprovincialis is discussed

On-line learning from clustered input examples

We analyse on-line learning of a linearly separable rule with a simple perceptron. Example inputs are taken from two overlapping clusters of data and the rule is defined through a teacher vector which is in general not aligned with the connection line of the cluster centers. We find that the Hebb algorithm cannot learn the rule perfectly in general. Moreover the dependence of the generalization error on the number of examples is nonmonotonic for certain choices of the model parameters. Perceptron and AdaTron training, however, approach perfect generalization with increasing size of the training set, and the asymptotic behavior is the same as for unstructured input data

Off-line learning from clustered input examples

We analyze the generalization ability of a simple perceptron acting on a structured input distribution for the simple case of two clusters of input data and a linearly separable rule. The generalization ability computed for three learning scenarios: maximal stability, Gibbs, and optimal learning, is found to improve with the separation between the clusters, and is bounded from below by the result for the unstructured case, recovered as the separation between clusters vanishes. The asymptotic behavior for large training sets is the same for structured and unstructured input distributions. For small training sets, the generalization error of the maximally stable perceptron exhibits a nonmonotonic dependence on the number of examples for certain values of the model parameters

Impact of Heavy Metal Exposure on <i>Mytilus galloprovincialis</i> Spermatozoa: A Metabolomic Investigation

Metabolomics is a method that provides an overview of the physiological and cellular state of a specific organism or tissue. This method is particularly useful for studying the influence the environment can have on organisms, especially those used as bio-indicators, e.g., Mytilus galloprovincialis. Nevertheless, a scarcity of data on the complete metabolic baseline of mussel tissues still exists, but more importantly, the effect of mussel exposure to certain heavy metals on spermatozoa is unknown, also considering that, in recent years, the reproductive system has proved to be very sensitive to the effects of environmental pollutants. In order to fill this knowledge gap, the similarities and differences in the metabolic profile of spermatozoa of mussels exposed to metallic chlorides of copper, nickel, and cadmium, and to the mixture to these metals, were studied using a metabolomics approach based on GC–MS analysis, and their physiological role was discussed. A total of 237 endogenous metabolites were identified in the spermatozoa of these mussel. The data underwent preprocessing steps and were analyzed using statistical methods such as PLS-DA. The results showed effective class separation and identified key metabolites through the VIP scores. Heatmaps and cluster analysis further evaluated the metabolites. The metabolite-set enrichment analysis revealed complex interactions within metabolic pathways and metabolites, especially involving glucose and central carbon metabolism and oxidative stress metabolism. Overall, the results of this study are useful to better understand how some pollutants can affect the specific physiological functions of the spermatozoa of this mussel, as well as for further GC–MS-based metabolomic health and safety studies of marine bivalves

Molecular Alterations and Severe Abnormalities in Spermatozoa of Young Men Living in the &ldquo;Valley of Sacco River&rdquo; (Latium, Italy): A Preliminary Study

The Valley of Sacco River (VSR) (Latium, Italy) is an area with large-scale industrial chemical production that has led over time to significant contamination of soil and groundwater with various industrial pollutants, such as organic pesticides, dioxins, organic solvents, heavy metals, and particularly, volatile organic compounds (VOCs). In the present study, we investigated the potential impact of VOCs on the spermatozoa of healthy young males living in the VSR, given the prevalent presence of several VOCs in the semen of these individuals. To accomplish this, spermiograms were conducted followed by molecular analyses to assess the content of sperm nuclear basic proteins (SNBPs) in addition to the protamine-histone ratio and DNA binding of these proteins. We found drastic alterations in the spermatozoa of these young males living in the VSR. Alterations were seen in sperm morphology, sperm motility, sperm count, and protamine/histone ratios, and included significant reductions in SNBP&ndash;DNA binding capacity. Our results provide preliminary indications of a possible correlation between the observed alterations and the presence of specific VOCs

Characterization of endocannabinoids and related acylethanolamides in the synovial fluid of dogs with osteoarthritis: a pilot study

BACKGROUND Cannabis-based drugs have been shown to be effective in inflammatory diseases. A number of endocannabinoids including N- arachidonoylethanolamide (anandamide, AEA) and 2-arachidonyl glycerol (2-AG) with activity at the cannabinoid receptors (CBR) CBR1 and CBR2, have been identified. Other structurally related endogenous fatty acid compounds such as oleoylethanolamide (OEA) and palmitoyl ethanolamide (PEA) have been identified in biological tissues. These compounds do not bind to CBR but might be involved in facilitating the actions of directly acting endocannabinoids and thus are commonly termed “entourage” compounds due to their ability to modulate the endocannabinoid system. The aim of this study was to evaluate the presence of endocannabinoids and entourage compounds in the synovial fluid of dogs with osteoarthritis subjected to arthrotomy of the knee joint. Cytokines and cytology were studied as well. RESULTS AEA, 2-AG, OEA and PEA were all present in the synovial fluid of arthritic knees and in the contralateral joints; in addition, a significant increase of OEA and 2AG levels were noted in SF from OA knees when compared to the contralateral joints. CONCLUSION The identification and quantification of endocannabinoids and entourage compounds levels in synovial fluids from dogs with OA of the knee is reported for the first time. Our data are instrumental for future studies involving a greater number of dogs. Cannabinoids represent an emerging and innovative pharmacological tool for the treatment of OA and further studies are warranted to evaluate the effectiveness of cannabinoids in veterinary medicine

Exploring the molecular and toxicological mechanism associated with interactions between heavy metals and the reproductive system of Mytilus galloprovincialis

A large number of heavy metals resulted toxic to the reproductive system, but invertebrate infertility has been poorly explored, and above all, there are limited molecular, cellular and toxicological studies. In the present work, we exposed Mytilus galloprovincialis to three individual metal chlorides (CuCl2 15 μM, CdCl2 1.5 μM, NiCl2 15 μM) and their mixture for 24 h, to evaluate the effects on the protamine-like proteins (PLs), sperm DNA and on their interaction in the formation of sperm chromatin. Under all exposure conditions, but particularly after exposure to the metals mix, relevant changes in the electrophoretic pattern, by AU-PAGE and SDS-PAGE, and in fluorescence spectroscopy measurements of PLs were shown. In addition, alterations in DNA binding of these proteins were observed by Electrophoretic Mobility Shift Assay (EMSA) and through their release from sperm nuclei. Moreover, there was evidence of increased accessibility of micrococcal nuclease to sperm chromatin, which was also confirmed by toluidine blue staining. Furthermore, morphological analyses indicated severe gonadal impairments which was also corroborated by increased PARP expression, by Western blotting, and sperm DNA fragmentation, by comet assay. Finally, we investigated the expression of stress genes, gst, hsp70 and mt10, in gonadal tissue. The latter investigations also showed that exposure to this metals mix was more harmful than exposure to the individual metals tested. The present results suggest that these metals and in particular their mixture could have a negative impact on the reproductive fitness of M. galloprovincialis. Based on these evidences, we propose a molecular mechanism

Aberrant signaling through the HER2-ERK1/2 pathway is predictive of reduced disease-free and overall survival in early stage non-small cell lung cancer (NSCLC) patients

Background: Purpose of this study was to evaluate the contribution of the Extracellular-regulated protein kinase (ERK)-1/2 pathway to oncogenic signaling elicited by the tyrosine kinase receptor HER2 in Non-Small Cell Lung Cancer (NSCLC) and to assess the prognostic value of these oncoproteins in NSCLC patients. Methods: Immunohistochemistry was performed to determine expression and activation of HER2 and ERK1/2 (detected by phosphorylation of Y1248 and T202/Y204, respectively) using Tissue Micro Arrays (TMA) containing matched normal and neoplastic tissues from 132 NSCLC patients. Survival analysis was carried out using the Kaplan-Meier method. Univariate and multivariate analysis were used to evaluate the prognostic value of pERK1/2, pHER2 and a combination thereof with clinical-pathological parameters such as age, lymph node status (N), size (T), stage (TNM) and grade. Results: We found that HER2 was overexpressed in 33/120 (27%) and activated in 41/114 (36%) cases; ERK1/2 was activated in 44/102 (43%) cases. A direct association was found between pERK1/2 and pHER2 (23/41; p=0.038). In addition, patients positive for pERK1/2 and for both pHER2 and pERK1/2 showed significantly worse overall survival (OS) and disease-free survival (DFS) compared with negative patients. Univariate and multivariate analysis of patients' survival revealed that positivity for pHER2-pERK1/2 and for pERK1/2 alone were independent prognostic factors of poor survival in NSCLC patients. In particular, this association was significantly important for DFS in stage I+II patients. Conclusion: This study provides evidence that activated ERK1/2 and/or the combined activation of HER2 and ERK1/2 are good indicators of poor prognosis in NSCLC patients, not only in unselected patients but also in early stage disease

Supplementary_Table_1_Trace_metals.xlsx

Concentration of trace metals in the analyzed samples.</p

Supplementary_Table_2_miRNA_analysis.xlsx

A. Sample data and small RNA-Seq alignment statistics. B. Results from the differential expression analysis. C. List of validated DE miRNA-gene target interactions. D. Number of studies supporting each miRNA-target interaction. E. Number of miRNAs targeting the same gene. F. Results from the miRNA target enrichment analysis.</p