Neuroprotective Effects of IGF-I against TNFα-Induced Neuronal Damage in HIV-Associated Dementia

AbstractHuman immunodeficiency virus type 1 (HIV-1) infection often results in disorders of the central nervous system, including HIV-associated dementia (HAD). It is suspected that tumor necrosis factor-α (TNFα) released by activated and/or infected macrophages/microglia plays a role in the process of neuronal damage seen in AIDS patients. In light of earlier studies showing that the activation of the insulin-like growth factor I receptor (IGF-IR) exerts a strong neuroprotective effect, we investigated the ability of IGF-I to protect neuronal cells from HIV-infected macrophages. Our results demonstrate that the conditioned medium from HIV-1-infected macrophages, HIV/CM, causes loss of neuronal processes in differentiated PC12 and P19 neurons and that these neurodegenerative effects are associated with the presence of TNFα. Furthermore, we demonstrate that IGF-I rescues differentiated neurons from both HIV/CM and TNFα-induced damage and that IGF-I-mediated neuroprotection is strongly enhanced by overexpression of the wt IGF-IR cDNA and attenuated by the antisense IGF-IR cDNA. Finally, IGF-I-mediated antiapoptotic pathways are continuously functional in differentiated neurons exposed to HIV/CM and are likely supported by TNFα-mediated phosphorylation of IκB. All together these results suggest that the balance between TNFα and IGF-IR signaling pathways may control the extent of neuronal injury in this HIV-related experimental setting

In utero ethanol exposure induces mitochondrial DNA damage and inhibits mtDNA repair in developing brain

IntroductionMitochondrial dysfunction is postulated to be a central event in fetal alcohol spectrum disorders (FASD). People with the most severe form of FASD, fetal alcohol syndrome (FAS) are estimated to live only 34 years (95% confidence interval, 31 to 37 years), and adults who were born with any form of FASD often develop early aging. Mitochondrial dysfunction and mitochondrial DNA (mtDNA) damage, hallmarks of aging, are postulated central events in FASD. Ethanol (EtOH) can cause mtDNA damage, consequent increased oxidative stress, and changes in the mtDNA repair protein 8-oxoguanine DNA glycosylase-1 (OGG1). Studies of molecular mechanisms are limited by the absence of suitable human models and non-invasive tools.MethodsWe compared human and rat EtOH-exposed fetal brain tissues and neuronal cultures, and fetal brain-derived exosomes (FB-Es) from maternal blood. Rat FASD was induced by administering a 6.7% alcohol liquid diet to pregnant dams. Human fetal (11–21 weeks) brain tissue was collected and characterized by maternal self-reported EtOH use. mtDNA was amplified by qPCR. OGG1 and Insulin-like growth factor 1 (IGF-1) mRNAs were assayed by qRT-PCR. Exosomal OGG1 was measured by ddPCR.ResultsMaternal EtOH exposure increased mtDNA damage in fetal brain tissue and FB-Es. The damaged mtDNA in FB-Es correlated highly with small eye diameter, an anatomical hallmark of FASD. OGG1-mediated mtDNA repair was inhibited in EtOH-exposed fetal brain tissues. IGF-1 rescued neurons from EtOH-mediated mtDNA damage and OGG1 inhibition.ConclusionThe correlation between mtDNA damage and small eye size suggests that the amount of damaged mtDNA in FB-E may serve as a marker to predict which at risk fetuses will be born with FASD. Moreover, IGF-1 might reduce EtOH-caused mtDNA damage and neuronal apoptosis

DING Proteins from Phylogenetically Different Species Share High Degrees of Sequence and Structure Homology and Block Transcription of HIV-1 LTR Promoter

Independent research groups reported that DING protein homologues isolated from bacterial, plant and human cells demonstrate the anti-HIV-1 activity. This might indicate that diverse organisms utilize a DING-mediated broad-range protective innate immunity response to pathogen invasion, and that this mechanism is effective also against HIV-1. We performed structural analyses and evaluated the anti-HIV-1 activity for four DING protein homologues isolated from different species. Our data show that bacterial PfluDING, plant p38SJ (pDING), human phosphate binding protein (HPBP) and human extracellular DING from CD4 T cells (X-DING-CD4) share high degrees of structure and sequence homology. According to earlier reports on the anti-HIV-1 activity of pDING and X-DING-CD4, other members of this protein family from bacteria and humans were able to block transcription of HIV-1 and replication of virus in cell based assays. The efficacy studies for DING-mediated HIV-1 LTR and HIV-1 replication blocking activity showed that the LTR transcription inhibitory concentration 50 (IC50) values ranged from 0.052–0.449 ng/ml; and the HIV-1 replication IC50 values ranged from 0.075–0.311 ng/ml. Treatment of cells with DING protein alters the interaction between p65-NF-κB and HIV-1 LTR. Our data suggest that DING proteins may be part of an innate immunity defense against pathogen invasion; the conserved structure and activity makes them appealing candidates for development of a novel therapeutics targeting HIV-1 transcription

Application of Machine Learning and Artificial Intelligence in Proxy Modeling for Fluid Flow in Porous Media

Reservoir simulation models are the major tools for studying fluid flow behavior in hydrocarbon reservoirs. These models are constructed based on geological models, which are developed by integrating data from geology, geophysics, and petro-physics. As the complexity of a reservoir simulation model increases, so does the computation time. Therefore, to perform any comprehensive study which involves thousands of simulation runs, a very long period of time is required. Several efforts have been made to develop proxy models that can be used as a substitute for complex reservoir simulation models. These proxy models aim at generating the outputs of the numerical fluid flow models in a very short period of time. This research is focused on developing a proxy fluid flow model using artificial intelligence and machine learning techniques. In this work, the proxy model is developed for a real case CO2 sequestration project in which the objective is to evaluate the dynamic reservoir parameters (pressure, saturation, and CO2 mole fraction) under various CO2 injection scenarios. The data-driven model that is developed is able to generate pressure, saturation, and CO2 mole fraction throughout the reservoir with significantly less computational effort and considerably shorter period of time compared to the numerical reservoir simulation model

Developing a Grid-Based Surrogate Reservoir Model Using Artificial Intelligence

Reservoir simulation models are the major tools for studying fluid flow behavior in hydrocarbon reservoirs. They are now being used extensively in performing any kind of studies related to fluid production/injection in hydrocarbon bearing formations. Reservoir simulation models are constructed based on geological models, which are developed by integrating data from geology, geophysics, and petro-physics. This data comes from observation, measurements, and interpretations.;Integration of maximum data from geology, geophysics, and petro-physics, contributes to building geologically complex and more realistic models. As the complexity of a reservoir simulation model increases, so does the computation time. Therefore, to perform any comprehensive study which involves thousands of simulation runs (such as uncertainty analysis), a massive amount of time is needed to complete all the required simulation runs. On many occasions, the sheer number of required simulation runs, makes the accomplishment of a project\u27s objectives impractical.;In order to address this problem, several efforts have been made to develop proxy models which can be used as a substitute for complex reservoir simulation models. These proxy models aim to reproduce the outputs of the reservoir models in a very short amount of time. In this study, a Grid-Based Surrogate Reservoir Model (SRM) is developed to be used as a proxy model for a complex reservoir simulation model. SRM is a customized model based on Artificial Intelligent (AI) and Data Mining (DM) techniques and consists of several neural networks, which are trained, calibrated, and validated before being used online.;In this research, a numerical reservoir simulation model is developed and history matched for a CO2 sequestration project, which was performed in Otway basin, Australia where CO2 is injected into a depleted gas reservoir through one injection well. In order to develop SRM, a handful of appropriate simulation scenarios for different operational constraints and/or geological realizations are designed and run. A comprehensive spatio-temporal data set is generated by integrating data from the conducted simulation runs and it is used to train, calibrate, and verify several neural networks which are further combined to make the surrogate model.;This model is able to generate pressure, saturation, and CO2 mole fraction at each grid block of the reservoir with a significantly less computational effort compared to the numerical reservoir simulation model

Application of Machine Learning and Artificial Intelligence in Proxy Modeling for Fluid Flow in Porous Media

Reservoir simulation models are the major tools for studying fluid flow behavior in hydrocarbon reservoirs. These models are constructed based on geological models, which are developed by integrating data from geology, geophysics, and petro-physics. As the complexity of a reservoir simulation model increases, so does the computation time. Therefore, to perform any comprehensive study which involves thousands of simulation runs, a very long period of time is required. Several efforts have been made to develop proxy models that can be used as a substitute for complex reservoir simulation models. These proxy models aim at generating the outputs of the numerical fluid flow models in a very short period of time. This research is focused on developing a proxy fluid flow model using artificial intelligence and machine learning techniques. In this work, the proxy model is developed for a real case CO2 sequestration project in which the objective is to evaluate the dynamic reservoir parameters (pressure, saturation, and CO2 mole fraction) under various CO2 injection scenarios. The data-driven model that is developed is able to generate pressure, saturation, and CO2 mole fraction throughout the reservoir with significantly less computational effort and considerably shorter period of time compared to the numerical reservoir simulation model

Comparison of the Effectiveness of Teaching Emotion Management Strategies Based on Emotion-Focused Couple Therapy Approach and Couple Therapy Based on Schema Therapy on Sexual Satisfaction and Family Functioning

Background: The family is the place to satisfy various physical, intellectual, and emotional needs, and having awareness of biological and psychological needs, knowing how to satisfy them, being equipped with techniques, and recognizing biological and psychological tendencies is an undeniable necessity. The present study was conducted with the aim of comparing the effectiveness of teaching emotion management strategies based on emotionally focused therapy (EFT) and schema-based couple therapy on sexual satisfaction and family functioning of couples. Methods: The present study was a semi-experimental study with a pre-test and post-test design and follow-up with a control group. The study population included all couples with marital dissatisfaction who referred to the psychological clinic of Isfahan City, Iran, to solve their problems. The research sample included 45 couples who were selected by purposeful sampling and were randomly divided into three experimental groups: 1 (15 couples), 2 (15 couples), and control (15 couples). For the statistical analysis of the data, mixed analysis of variance (ANOVA) between and within subjects was used with the help of SPSS software. Findings: Training emotion management strategies based on EFT and schema-based couple therapy increased sexual satisfaction and family functioning compared to the control group (P < 0.050). There was a statistically significant difference between the effectiveness of teaching emotion management strategies based on EFT and schema-based couple therapy on sexual satisfaction and family performance of couples in the post-test and follow-up stages (P < 0.050), and teaching emotion management strategies based on EFT approach was more effective than schema-based couple therapy in sexual satisfaction and family functioning of couples. Conclusion: Emotion and self-awareness training is an effective method in increasing sexual satisfaction and family functioning of couples

Deregulation of miR-1245b-5p and miR-92a-3p and their potential target gene, GATA3, in epithelial-mesenchymal transition pathway in breast cancer.

BACKGROUND MicroRNAs (miRNAs) are small molecules that have prominent roles in tumor development and metastasis and can be used for diagnostic and therapeutic purposes. This study evaluated the expression of miR-92a-3p and miR-1245b-5p and their potential target gene, GATA3 in patients with breast cancer (BC). MATERIALS AND METHODS In the search for BC-related microRNAs, miR-124b-5p and miR-92a-3p were selected using Medline through PubMed, miR2disease, miRcancer and miRTarBase. Moreover, target gene GATA3 and their possible interaction in the regulating epithelial-mesenchymal transition (EMT) and invasion was evaluated using in silico tools including miRTarBase, TargetScan, STRING-db, and Cytoscape. The expression level of miR-92a-3p, miR1245b-5p, and GATA3 were assessed on extracted RNAs of tumor and nontumor tissues from 36 patients with BC using qPCR. Additionally, clinical-pathologic characteristics, such as tumor grade, tumor stage, lymph node were taken into consideration and the diagnostic power of these miRNAs and GATA3 was evaluated using the ROC curve analysis. RESULTS In silico evaluation of miR-92a-3p and miR-1245b-5p supports their potential association with EMT and invasion signaling pathways in BC pathogenesis. Comparing tumor tissues to nontumor tissues, we found a significant downregulation of miR-1245b-5p and miR-92a-3p and upregulation of GATA3. Patients with BC who had decreased miR-92a-3p expression also had higher rates of advanced stage/grade and ER expression, whereas decreased miR-1245b-5p expression was only linked to ER expression and was not associated with lymph node metastasis. The AUC of miR-1245b-5p, miR-92a-3p, and GATA3 using ROC curve was determined 0.6449 (p = .0239), 0.5980 (p = .1526), and 0.7415 (p < .0001), respectively, which showed a significant diagnostic accuracy of miR-1245b-5p and GATA3 between the BC patients and healthy individuals. CONCLUSION MiR-1245b-5p, miR-92a-3p, and GATA3 gene contribute to BC pathogenesis and they may be having potential regulatory roles in signaling pathways involved in invasion and EMT pathways in BC pathogenesis, as a result of these findings. More research is needed to determine the regulatory mechanisms that they control