Expression of AS3MT alters transcriptional profiles in human urothelial cells exposed to arsenite

Inorganic arsenic (iAs) is an environmental toxicant and human carcinogen. The enzymatic methylation of iAs that is catalyzed by arsenic (+3 oxidation state)-methyltransferase (AS3MT) generates reactive methylated intermediates that contribute to the toxic and carcinogenic effects of iAs. We have shown that clonal human urothelial cells (UROtsa/F35) that express rat AS3MT and methylate iAs are more susceptible to acute toxicity of arsenite (iAsIII) than parental UROtsa cells that do not express AS3MT and do not methylate iAs. The current work examines transcriptional changes associated with AS3MT expression and identifies specific categories of genes expressed in UROtsa and UROtsa/F35 cells in response to a 24-h exposure to 1 or 50 μM iAsIII. Here, the expression of 21,073 genes was assessed using Agilent Human 1A(V2) arrays. Venn analysis showed marked concentration-dependent differences between gene expression patterns in UROtsa and UROTsa/F35 cells exposed to iAsIII. Among 134 genes altered by exposure to subtoxic 1 μM iAsIII, only 14 were shared by both cell lines. Exposure to cytotoxic 50 μM iAsIII uniquely altered 1389 genes in UROtsa/F35 and 649 genes in UROtsa cells; 5033 altered genes were associated with the chemical alone. In UROtsa, but not UROtsa/F35 cells exposure to 1 μM iAsIII altered expression of genes associated with cell adhesion. In contrast, expression of genes involved in cell cycle regulation was significantly altered in UROtsa/F35 cells at this exposure level. At 50 μM iAsIII, pathways regulating cell cycle, cell death, transcription, and metabolism were affected in both cell lines. However, only Urotsa/F35 cells showed numerous G-protein and kinase pathway alterations as well as alterations in pathways involved in cell growth and differentiation. These data link the AS3MT-catalyzed methylation of iAs to specific genomic responses in human cells exposed to iAsIII. Further analysis of these responses will help to characterize the role of AS3MT-catalyzed methylation in modulation of iAsIII toxicity

Spatial transcriptomic characterization of COVID-19 pneumonitis identifies immune circuits related to tissue injury

Severe lung damage resulting from COVID-19 involves complex interactions between diverse populations of immune and stromal cells. In this study, we used a spatial transcriptomics approach to delineate the cells, pathways, and genes present across the spectrum of histopathological damage in COVID-19–affected lung tissue. We applied correlation network–based approaches to deconvolve gene expression data from 46 areas of interest covering more than 62,000 cells within well-preserved lung samples from 3 patients. Despite substantial interpatient heterogeneity, we discovered evidence for a common immune-cell signaling circuit in areas of severe tissue that involves crosstalk between cytotoxic lymphocytes and pro-inflammatory macrophages. Expression of IFNG by cytotoxic lymphocytes was associated with induction of chemokines, including CXCL9, CXCL10, and CXCL11, which are known to promote the recruitment of CXCR3+ immune cells. The TNF superfamily members BAFF (TNFSF13B) and TRAIL (TNFSF10) were consistently upregulated in the areas with severe tissue damage. We used published spatial and single-cell SARS-CoV-2 data sets to validate our findings in the lung tissue from additional cohorts of patients with COVID-19. The resulting model of severe COVID-19 immune-mediated tissue pathology may inform future therapeutic strategies

Early Mortality and AIDS Progression Despite High Initial Antiretroviral Therapy Adherence and Virologic Suppression in Botswana

Background Adverse outcomes occurring early after antiretroviral therapy (ART) initiation are common in sub-Saharan Africa, despite reports of high levels of ART adherence in this setting. We sought to determine the relationship between very early ART adherence and early adverse outcomes in HIV-infected adults in Botswana. Methods This prospective cohort study of 402 ART-naïve, HIV-infected adults initiating ART at a public HIV clinic in Gaborone, Botswana evaluated the relationship between suboptimal early ART adherence and HIV treatment outcomes in the initial months after ART initiation. Early adherence during the interval between initial ART dispensation and first ART refill was calculated using pill counts. In the primary analysis patients not returning to refill and those with adherence \u3c0.95 were considered to have suboptimal early adherence. The primary outcome was death or loss to follow-up during the first 6 months of ART; a secondary composite outcome included the primary outcome plus incident opportunistic illness (OIs) and virologic failure. We also calculated the percent of early adverse outcomes theoretically attributable to suboptimal early adherence using the population attributable risk percent (PAR%). Results Suboptimal early adherence was independently associated with loss to follow-up and death (adjusted OR 2.3, 95% CI 1.1–4.8) and with the secondary composite outcome including incident OIs and virologic failure (adjusted OR 2.6, 95% CI 1.4–4.7). However, of those with early adverse outcomes, less than one-third had suboptimal adherence and approximately two-thirds achieved virologic suppression. The PAR% relating suboptimal early adherence and primary and secondary outcomes were 14.7% and 17.7%, respectively. Conclusions Suboptimal early adherence was associated with poor outcomes, but most early adverse outcomes occurred in patients with optimal early adherence. Clinical care and research efforts should focus on understanding early adverse outcomes that occur despite optimal adherence

Comparing individual-based approaches to modelling the self-organization of multicellular tissues.

The coordinated behaviour of populations of cells plays a central role in tissue growth and renewal. Cells react to their microenvironment by modulating processes such as movement, growth and proliferation, and signalling. Alongside experimental studies, computational models offer a useful means by which to investigate these processes. To this end a variety of cell-based modelling approaches have been developed, ranging from lattice-based cellular automata to lattice-free models that treat cells as point-like particles or extended shapes. However, it remains unclear how these approaches compare when applied to the same biological problem, and what differences in behaviour are due to different model assumptions and abstractions. Here, we exploit the availability of an implementation of five popular cell-based modelling approaches within a consistent computational framework, Chaste (http://www.cs.ox.ac.uk/chaste). This framework allows one to easily change constitutive assumptions within these models. In each case we provide full details of all technical aspects of our model implementations. We compare model implementations using four case studies, chosen to reflect the key cellular processes of proliferation, adhesion, and short- and long-range signalling. These case studies demonstrate the applicability of each model and provide a guide for model usage

Comparative genomic analyses identify common molecular pathways modulated upon exposure to low doses of arsenic and cadmium

<p>Abstract</p> <p>Background</p> <p>Exposure to the toxic metals arsenic and cadmium is associated with detrimental health effects including cancers of various organs. While arsenic and cadmium are well known to cause adverse health effects at high doses, the molecular impact resulting from exposure to environmentally relevant doses of these metals remains largely unexplored.</p> <p>Results</p> <p>In this study, we examined the effects of <it>in vitro </it>exposure to either arsenic or cadmium in human TK6 lymphoblastoid cells using genomics and systems level pathway mapping approaches. A total of 167 genes with differential expression were identified following exposure to either metal with surprisingly no overlap between the two. Real-time PCR was used to confirm target gene expression changes. The gene sets were overlaid onto protein-protein interaction maps to identify metal-induced transcriptional networks. Interestingly, both metal-induced networks were significantly enriched for proteins involved in common biological processes such as tumorigenesis, inflammation, and cell signaling. These findings were further supported by gene set enrichment analysis.</p> <p>Conclusions</p> <p>This study is the first to compare the transcriptional responses induced by low dose exposure to cadmium and arsenic in human lymphoblastoid cells. These results highlight that even at low levels of exposure both metals can dramatically influence the expression of important cellular pathways.</p

Virtual Patients and Sensitivity Analysis of the Guyton Model of Blood Pressure Regulation: Towards Individualized Models of Whole-Body Physiology

Mathematical models that integrate multi-scale physiological data can offer insight into physiological and pathophysiological function, and may eventually assist in individualized predictive medicine. We present a methodology for performing systematic analyses of multi-parameter interactions in such complex, multi-scale models. Human physiology models are often based on or inspired by Arthur Guyton's whole-body circulatory regulation model. Despite the significance of this model, it has not been the subject of a systematic and comprehensive sensitivity study. Therefore, we use this model as a case study for our methodology. Our analysis of the Guyton model reveals how the multitude of model parameters combine to affect the model dynamics, and how interesting combinations of parameters may be identified. It also includes a “virtual population” from which “virtual individuals” can be chosen, on the basis of exhibiting conditions similar to those of a real-world patient. This lays the groundwork for using the Guyton model for in silico exploration of pathophysiological states and treatment strategies. The results presented here illustrate several potential uses for the entire dataset of sensitivity results and the “virtual individuals” that we have generated, which are included in the supplementary material. More generally, the presented methodology is applicable to modern, more complex multi-scale physiological models

Response perseveration and ventral prefrontal sensitivity to reward and punishment in male problem gamblers and smokers

Pathological gambling (PG) is associated with maladaptive perseverative behavior, but the underlying mechanism and neural circuitry is not completely clear. Here, the hypothesis was tested that PG is characterized by response perseveration and abnormalities in reward and/or punishment sensitivity in the ventral frontostriatal circuit. Executive functioning was assessed to verify if these effects are independent of the dorsal frontostriatal circuit. A group of smokers was also included to examine whether impairments in PG generalize to substance use disorders. Response perseveration and reward/punishment sensitivity were measured with a probabilistic reversal-learning task, in which subjects could win and lose money. Executive functioning was measured with a planning task, the Tower of London. Performance and fMRI data were acquired in 19 problem gamblers, 19 smokers, and 19 healthy controls. Problem gamblers showed severe response perseveration, associated with reduced activation of right ventrolateral prefrontal cortex in response to both monetary gain and loss. Results did not fully generalize to smokers. Planning performance and related activation of the dorsal frontostriatal circuit were intact in both problem gamblers and smokers. PG is related to response perseveration and diminished reward and punishment sensitivity as indicated by hypoactivation of the ventrolateral prefrontal cortex when money is gained and lost. Moreover, intact planning abilities and normal dorsal frontostriatal responsiveness indicate that this deficit is not due to impaired executive functioning. Response perseveration and ventral prefrontal hyporesponsiveness to monetary loss may be markers for maladaptive behavior seen in chemical and nonchemical addictions. © 2009 Nature Publishing Group All rights reserved

Neural Correlates of Visual Motion Prediction

Predicting the trajectories of moving objects in our surroundings is important for many life scenarios, such as driving, walking, reaching, hunting and combat. We determined human subjects’ performance and task-related brain activity in a motion trajectory prediction task. The task required spatial and motion working memory as well as the ability to extrapolate motion information in time to predict future object locations. We showed that the neural circuits associated with motion prediction included frontal, parietal and insular cortex, as well as the thalamus and the visual cortex. Interestingly, deactivation of many of these regions seemed to be more closely related to task performance. The differential activity during motion prediction vs. direct observation was also correlated with task performance. The neural networks involved in our visual motion prediction task are significantly different from those that underlie visual motion memory and imagery. Our results set the stage for the examination of the effects of deficiencies in these networks, such as those caused by aging and mental disorders, on visual motion prediction and its consequences on mobility related daily activities

From Dynamic Expression Patterns to Boundary Formation in the Presomitic Mesoderm

The segmentation of the vertebrate body is laid down during early embryogenesis. The formation of signaling gradients, the periodic expression of genes of the Notch-, Fgf- and Wnt-pathways and their interplay in the unsegmented presomitic mesoderm (PSM) precedes the rhythmic budding of nascent somites at its anterior end, which later develops into epithelialized structures, the somites. Although many in silico models describing partial aspects of somitogenesis already exist, simulations of a complete causal chain from gene expression in the growth zone via the interaction of multiple cells to segmentation are rare. Here, we present an enhanced gene regulatory network (GRN) for mice in a simulation program that models the growing PSM by many virtual cells and integrates WNT3A and FGF8 gradient formation, periodic gene expression and Delta/Notch signaling. Assuming Hes7 as core of the somitogenesis clock and LFNG as modulator, we postulate a negative feedback of HES7 on Dll1 leading to an oscillating Dll1 expression as seen in vivo. Furthermore, we are able to simulate the experimentally observed wave of activated NOTCH (NICD) as a result of the interactions in the GRN. We esteem our model as robust for a wide range of parameter values with the Hes7 mRNA and protein decays exerting a strong influence on the core oscillator. Moreover, our model predicts interference between Hes1 and HES7 oscillators when their intrinsic frequencies differ. In conclusion, we have built a comprehensive model of somitogenesis with HES7 as core oscillator that is able to reproduce many experimentally observed data in mice

Candidiasis, Bacterial Vaginosis, Trichomoniasis and Other Vaginal Conditions Affecting the Vulva

info:eu-repo/semantics/publishedVersio