Integrative pathway analysis of gynecological tumors characterized by different chromosomal instability patterns

openGynecological tumors include four tumor types from TCGA: ovarian cancer (OV), cervical cancer (CESC), endometrial cancer (UCEC) and the rare uterine carcinosarcoma (UCS). Breast cancer (BRCA) can also be included among gynecological tumors, since it shares the same embryonic origin and the influence of female hormones. In order to shed light on the common molecular features characterizing the five tumors, molecular profiles from patients with different patterns of chromosomal instability (CIN), underlying different mechanisms of dysregulation (signatures), were compared at both expression and methylation level. A pathway analysis was performed using SourceSet software, whose topological approach allows to discriminate genes that are the primary source of dysregulation from those that are indirectly affected. Two signatures were investigated: CX1 and CX3. CX1 is characterized by defective mitotic spindle checkpoint, resulting in incorrect chromosome segregation, while CX3 shows replication stress, leading to double strand breaks that are not properly corrected by homologous recombination and result in structural aberrations. Results revealed that OV, UCEC and BRCA tend to have similar expression and methylation profiles, while UCS and CESC are the most divergent tumors. Primary genes are more uniformly detected across tumor types compared to secondary genes, reflecting the common origin of perturbation generating the observed pattern of CIN and the different molecular profiles characterizing different tissues, respectively.Gynecological tumors include four tumor types from TCGA: ovarian cancer (OV), cervical cancer (CESC), endometrial cancer (UCEC) and the rare uterine carcinosarcoma (UCS). Breast cancer (BRCA) can also be included among gynecological tumors, since it shares the same embryonic origin and the influence of female hormones. In order to shed light on the common molecular features characterizing the five tumors, molecular profiles from patients with different patterns of chromosomal instability (CIN), underlying different mechanisms of dysregulation (signatures), were compared at both expression and methylation level. A pathway analysis was performed using SourceSet software, whose topological approach allows to discriminate genes that are the primary source of dysregulation from those that are indirectly affected. Two signatures were investigated: CX1 and CX3. CX1 is characterized by defective mitotic spindle checkpoint, resulting in incorrect chromosome segregation, while CX3 shows replication stress, leading to double strand breaks that are not properly corrected by homologous recombination and result in structural aberrations. Results revealed that OV, UCEC and BRCA tend to have similar expression and methylation profiles, while UCS and CESC are the most divergent tumors. Primary genes are more uniformly detected across tumor types compared to secondary genes, reflecting the common origin of perturbation generating the observed pattern of CIN and the different molecular profiles characterizing different tissues, respectively

What drugs modify the risk of iatrogenic impulse-control disorders in Parkinson’s disease? A preliminary pharmacoepidemiologic study

Introduction Parkinson’s disease (PD) patients treated with pramipexole (PPX) and ropinirole (ROP) exhibit a higher risk of developing impulse control disorders (ICDs), including gambling disorder, compulsive shopping, and hypersexuality. The management of ICDs in PD is challenging, due to the limited availability of effective therapeutic alternatives or counteractive strategies. Here, we used a pharmacoepidemiological approach to verify whether the risk for PPX/ROP-associated ICDs in PD patients was reduced by drugs that have been posited to exert therapeutic effects on idiopathic ICDs–including atypical antipsychotics (AAs), selective serotonin reuptake inhibitors (SSRIs), and glutamatergic modulators (GMs). Methods To quantify the strength of the associations between PPX/ROP and other medications with respect to ICD risk, odds ratios (ORs) were calculated by multivariable logistic regression, adjusting for age, gender, marital status race, psychiatric comorbidities, and use of cabergoline and levodopa. Results A total of 935 patients were included in the analysis. Use of GMs, SSRIs, and AAs was not associated with a decreased ICD risk in PD patients treated with PPX/ROP; conversely, ICD risk was significantly increased in patients treated with either GMs (Adjusted Odds Ratio, ORa: 14.00 [3.58–54.44]) or SSRIs (ORa: 3.67 [1.07–12.59]). Results were inconclusive for AAs, as available data were insufficient to compute a reliable ORa. Conclusions These results suggest that some of the key pharmacological strategies used to treat idiopathic ICD may not be effective for ICDs associated with PPX and ROP in PD patients. Future studies with larger cohorts are needed to confirm, validate, and extend these findings

Animal Models of Virus-Induced Neurobehavioral Sequelae: Recent Advances, Methodological Issues, and Future Prospects

Converging lines of clinical and epidemiological evidence suggest that viral infections in early developmental stages may be a causal factor in neuropsychiatric disorders such as schizophrenia, bipolar disorder, and autism-spectrum disorders. This etiological link, however, remains controversial in view of the lack of consistent and reproducible associations between viruses and mental illness. Animal models of virus-induced neurobehavioral disturbances afford powerful tools to test etiological hypotheses and explore pathophysiological mechanisms. Prenatal or neonatal inoculations of neurotropic agents (such as herpes-, influenza-, and retroviruses) in rodents result in a broad spectrum of long-term alterations reminiscent of psychiatric abnormalities. Nevertheless, the complexity of these sequelae often poses methodological and interpretational challenges and thwarts their characterization. The recent conceptual advancements in psychiatric nosology and behavioral science may help determine new heuristic criteria to enhance the translational value of these models. A particularly critical issue is the identification of intermediate phenotypes, defined as quantifiable factors representing single neurochemical, neuropsychological, or neuroanatomical aspects of a diagnostic category. In this paper, we examine how the employment of these novel concepts may lead to new methodological refinements in the study of virus-induced neurobehavioral sequelae through animal models

Gene-sex interactions in schizophrenia: focus on dopamine neurotransmission

Schizophrenia is a severe mental disorder, with a highly complex and heterogenous clinical presentation. Our current perspectives posit that the pathogenic mechanisms of this illness lie in complex arrays of gene × environment interactions. Furthermore, several findings indicate that males have a higher susceptibility for schizophrenia, with earlier age of onset and overall poorer clinical prognosis. Based on these premises, several authors have recently begun exploring the possibility that the greater schizophrenia vulnerability in males may reflect specific gene × sex (G×S) interactions. Our knowledge on such G×S interactions in schizophrenia is still rudimentary; nevertheless, the bulk of preclinical evidence suggests that the molecular mechanisms for such interactions are likely contributed by the neurobiological effects of sex steroids on dopamine (DA) neurotransmission. Accordingly, several recent studies suggest a gender-specific association of certain DAergic genes with schizophrenia. These G×S interactions have been particularly documented for catechol-O-methyltransferase (COMT) and monoamine oxidase (MAO), the main enzymes catalyzing DA metabolism. In the present review, we will outline the current evidence on the interactions of DA-related genes and sex-related factors, and discuss the potential molecular substrates that may mediate their cooperative actions in schizophrenia pathogenesis

Light Majorana Neutrinos in (Semi)invisible Meson Decays

We reconsider decays of pseudoscalar mesons (P) to neutrino pairs and possibly additional photons in presence of (light) Majorana neutrinos. For this purpose we derive a model-independent general parametrization of neutrino mass matrices with physically interpretable and irreducible set of parameters. The parametrization is valid for any number of neutrinos and interpolates smoothly between the heavy Majorana and the (pseudo)Dirac neutrino limits. We apply the new parametrization to the study of $P \rightarrow \nu \nu$ and $P \rightarrow \nu \nu \gamma$ decays within the SM extended by additional singlet fermions. We update the SM predictions for the branching ratios of $B_{s,d} \rightarrow \nu \nu \gamma$ and discuss the sensitivity of the $B_{s,d} \rightarrow E_{\rm miss} (\gamma)$ decays to neutrino mass and mixing parameters.Comment: 17 pages, 6 figure

Probabilistic Determination of Consumers Response and Consumption Management Strategies in Demand Response Programs

In Demand Response programs, the response of the users to the event request depends on several factors. In this paper, a method that examines the response of the consumers to a load reduction request, defining the context in which the demand response event is carrying on and studying how the consumers react, is proposed. Statistical methods are used. Then are proposed several strategies to optimize the consumers’ participation in the load reduction basing the optimization on the previous characterization.The present work was done and funded in the scope of the following projects: UID/EEA/00760/2013 funded by FEDER Funds through COMPETE and National Funds through FCT; SPEAR project co-funded by Portugal 2020 "Fundo Europeu de Desenvolvimento Regional" (FEDER) through PO CI.info:eu-repo/semantics/publishedVersio

Improving the Composition of Ultra High Energy Cosmic Rays with Ground Detector Data

We show that the maximum shower depth distributions of Ultra-High Energy Cosmic Rays (UHECRs), as measured by fluorescence telescopes, can be augmented by building a mapping to observables collected by surface detectors. The resulting statistical improvement of such augmented dataset depends in a universal way on the strength of the correlation exhibited by the mapping. Building upon the publicly available data on "golden hybrid" events from the Pierre Auger Observatory we project possible improvements in the inferred composition of UHECRs for a range of possible mappings with varying correlation strengths.Comment: 8 pages, 6 figures, method correcte