A computational approach involving mathematical modeling and in silico experiments was used to characterize the determinants of extent and duration of platelet cyclooxygenase (COX)-1 inhibition by ...aspirin and design precision dosing in patients with accelerated platelet turnover or reduced drug bioavailability. To this purpose, a recently developed physiologically-based pharmacokinetics (PK) and pharmacodynamics (PD) model of low-dose aspirin in regenerating platelets and megakaryocytes, was used to predict the main features and determinants of platelet COX-1 inhibition. The response to different aspirin regimens in healthy subjects and in pathological conditions associated with alterations in aspirin PK (i.e., severely obese subjects) or PD (i.e., essential thrombocytemya patients), were simulated. A model sensitivity analysis was performed to identify the main processes influencing COX-1 dynamics. In silico experiments and sensitivity analyses indicated a major role for megakaryocytes and platelet turnover in determining the extent and duration of COX-1 inhibition by once-daily, low-dose aspirin. They also showed the superiority of reducing the dosing interval vs increasing the once-daily dose in conditions of increased platelet turnover, while suggested specific dose adjustments in conditions of possible reduction in drug bioavailability. In conclusion, the consistency of our model-based findings with experimental data from studies in healthy subjects and patients with essential thrombocythemia supports the potential of our approach for describing the determinants of platelet inhibition by aspirin and informing precision dosing which may guide personalized antithrombotic therapy in different patient populations, especially in those under-represented in clinical trials or in those associated with poor feasibility.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Protein turnover rate is finely regulated through intracellular mechanisms and signals that are still incompletely understood but that are essential for the correct function of cellular processes. ...Indeed, a dysfunctional proteostasis often impacts the cell's ability to remove unfolded, misfolded, degraded, non-functional, or damaged proteins. Thus, altered cellular mechanisms controlling protein turnover impinge on the pathophysiology of many diseases, making the study of protein synthesis and degradation rates an important step for a more comprehensive understanding of these pathologies. In this manuscript, we describe the application of a dynamic-SILAC approach to study the turnover rate and the abundance of proteins in a cellular model of diabetic nephropathy. We estimated protein half-lives and relative abundance for thousands of proteins, several of which are characterized by either an altered turnover rate or altered abundance between diabetic nephropathic subjects and diabetic controls. Many of these proteins were previously shown to be related to diabetic complications and represent therefore, possible biomarkers or therapeutic targets. Beside the aspects strictly related to the pathological condition, our data also represent a consistent compendium of protein half-lives in human fibroblasts and a rich source of important information related to basic cell biology.
The occurrence of dynamic changes in spontaneous electroencephalogram (EEG) rhythms in the awake state or sleep is highly variable. These rhythms can be externally modulated during transcranial ...magnetic stimulation (TMS) with a perturbation method to trigger oscillatory brain activity. EEG-TMS co-registration was performed during standard wake, during wake after sleep deprivation and in sleep in six healthy subjects. Dynamic changes in the regional neural oscillatory activity of the cortical areas were characterized using time-frequency analysis based on the wavelet method, and the modulation of induced oscillations were related to different vigilance states. A reciprocal synchronizing/desynchronizing effect on slow and fast oscillatory activity was observed in response to focal TMS after sleep deprivation and sleep. We observed a sleep-related slight desynchronization of alpha mainly over the frontal areas, and a widespread increase in theta synchronization. These findings could be interpreted as proof of the interference external brain stimulation can exert on the cortex, and how this could be modulated by the vigilance state. Potential clinical applications may include evaluation of hyperexcitable states such as epilepsy or disturbed states of consciousness such as minimal consciousness.
Fast rhythms excess is a hallmark of Parkinson’s Disease (PD). To implement innovative, non-pharmacological, neurostimulation interventions to restore cortical-cortical interactions, we need to ...understand the neurophysiological mechanisms underlying these phenomena. Here, we investigated effective connectivity on source-level resting-state electroencephalography (EEG) signals in 15 PD participants and 10 healthy controls. First, we fitted multivariate auto-regressive models to the EEG source waveforms. Second, we estimated causal connections using Granger Causality, which provide information on connections’ strength and directionality. Lastly, we sought significant differences connectivity patterns between the two populations characterizing the network graph features—i.e., global efficiency and node strength. Causal brain networks in PD show overall poorer and weaker connections compared to controls quantified as a reduction of global efficiency. Motor areas appear almost isolated, with a strongly impoverished information flow particularly from parietal and occipital cortices. This striking isolation of motor areas may reflect an impaired sensory-motor integration in PD. The identification of defective nodes/edges in PD network may be a biomarker of disease and a potential target for future interventional trials.
Dynamic changes in spontaneous electroencephalogram (EEG) rhythms can be seen to occur with a high rate of variability. An innovative method to study brain function is by triggering oscillatory brain ...activity with transcranial magnetic stimulation (TMS). EEG-TMS coregistration was performed on five healthy subjects during a 1-day experimental session that involved four steps: baseline acquisition, unconditioned single-pulse TMS, intracortical inhibition (ICI, 3 ms) paired-pulse TMS, and transcallosal stimulation over left and right primary motor cortex (M1). A time-frequency analysis based on the wavelet method was used to characterize rapid modifications of oscillatory EEG rhythms induced by TMS. Single, paired, and transcallosal TMS applied on the sensorimotor areas induced rapid desynchronization over the frontal and central-parietal electrodes mainly in the alpha and beta bands, followed by a rebound of synchronization, and rapid synchronization of delta and theta activity. Wavelet analysis after a perturbation approach is a novel way to investigate modulation of oscillatory brain activity. The main findings are consistent with the concept that the human motor system may be based on networklike oscillatory cortical activity and might be modulated by single, paired, and transcallosal magnetic pulses applied to M1, suggesting a phenomenon of fast brain activity resetting and triggering of slow activity.
The experimental protocol of the perfused rat pancreas is commonly used to evaluate β-cell function. In this context, mathematical models become useful tools through the determination of indexes that ...allow the assessment of β-cell function in different experimental groups and the quantification of the effects of antidiabetic drugs, secretagogues, or treatments. However, a minimal model applicable to the isolated perfused rat pancreas has so far been unavailable. In this work, we adapt the C-peptide minimal model applied previously to the intravenous glucose tolerance test to obtain a specific model for the experimental settings of the perfused pancreas. Using the model, it is possible to estimate indexes describing β-cell responsivity for first (ΦD) and second phase (ΦS, T) of insulin secretion. The model was initially applied to untreated pancreata and afterward used for the assessment of pharmacologically relevant agents (the gut hormone GLP-1, the potent GLP-1 receptor agonist lixisenatide, and a GPR40/FFAR1 agonist, SAR1) to quantify and differentiate their effect on insulin secretion. Model fit was satisfactory, and parameters were estimated with good precision for both untreated and treated pancreata. Model application showed that lixisenatide reaches improvement of β-cell function similarly to GLP-1 (11.7- vs. 13.1-fold increase in ΦD and 2.3- vs. 2.8-fold increase in ΦS) and demonstrated that SAR1 leads to an additional improvement of β-cell function in the presence of postprandial GLP-1 levels.
Display omitted
Interferon-α (IFN-α) comprises a family of 13 cytokines involved in the modulation of antiviral, immune, and anticancer responses by orchestrating a complex transcriptional network. ...The activation of IFN-α signaling pathway in endothelial cells results in decreased proliferation and migration, ultimately leading to suppression of angiogenesis. In this study, we knocked-down the expression of seven established or candidate modulators of IFN-α response in endothelial cells to reconstruct a gene regulatory network and to investigate the antiangiogenic activity of IFN-α. This genetic perturbation approach, along with the analysis of interferon-induced gene expression dynamics, highlighted a complex and highly interconnected network, in which the angiostatic chemokine C-X-C Motif Chemokine Ligand 10 (CXCL10) was a central node targeted by multiple modulators. IFN-α-induced secretion of CXCL10 protein by endothelial cells was blunted by the silencing of Signal Transducer and Activator of Transcription 1 (STAT1) and of Interferon Regulatory Factor 1 (IRF1) and it was exacerbated by the silencing of Ubiquitin Specific Peptidase 18 (USP18). In vitro sprouting assay, which mimics in vivo angiogenesis, confirmed STAT1 as a positive modulator and USP18 as a negative modulator of IFN-α-mediated sprouting suppression. Our data reveal an unprecedented physiological regulation of angiogenesis in endothelial cells through a tonic IFN-α signaling, whose enhancement could represent a viable strategy to suppress tumor neoangiogenesis.
High risk forms of human papillomaviruses (
HPVs
) promote cancerous lesions and are implicated in almost all cervical cancer. Of particular relevance to cancer progression is regulation of the early ...promoter that controls gene expression in the initial phases of infection and can eventually lead to precancer progression. Our goal was to develop a stochastic model to investigate the control mechanisms that regulate gene expression from the
HPV
early promoter. Our model integrates modules that account for transcriptional, post-transcriptional, translational and post-translational regulation of
E1
and
E2
early genes to form a functioning gene regulatory network. Each module consists of a set of biochemical steps whose stochastic evolution is governed by a chemical
Master Equation
and can be simulated using the
Gillespie
algorithm. To investigate the role of noise in gene expression, we compared our stochastic simulations with solutions to ordinary differential equations for the mean behavior of the system that are valid under the conditions of large molecular abundances and
quasi-equilibrium
for fast reactions.
The model produced results consistent with known
HPV
biology. Our simulation results suggest that stochasticity plays a pivotal role in determining the dynamics of
HPV
gene expression. In particular, the combination of positive and negative feedback regulation generates stochastic bursts of gene expression. Analysis of the model reveals that regulation at the promoter affects burst amplitude and frequency, whereas splicing is more specialized to regulate burst frequency. Our results also suggest that splicing enhancers are a significant source of stochasticity in
pre-mRNA
abundance and that the number of viruses infecting the host cell represents a third important source of stochasticity in gene expression.
Functional magnetic resonance imaging (fMRI) during a resting-state condition can reveal the co-activation of specific brain regions in distributed networks, called resting-state networks, which are ...selected by independent component analysis (ICA) of the fMRI data. One of the major difficulties with component analysis is the automatic selection of the ICA features related to brain activity. In this study we describe a method designed to automatically select networks of potential functional relevance, specifically, those regions known to be involved in motor function, visual processing, executive functioning, auditory processing, memory, and the default-mode network. To do this, image analysis was based on probabilistic ICA as implemented in FSL software. After decomposition, the optimal number of components was selected by applying a novel algorithm which takes into account, for each component, Pearson's median coefficient of skewness of the spatial maps generated by FSL, followed by clustering, segmentation, and spectral analysis. To evaluate the performance of the approach, we investigated the resting-state networks in 25 subjects. For each subject, three resting-state scans were obtained with a Siemens Allegra 3 T scanner (NYU data set). Comparison of the visually and the automatically identified neuronal networks showed that the algorithm had high accuracy (first scan: 95%, second scan: 95%, third scan: 93%) and precision (90%, 90%, 84%). The reproducibility of the networks for visual and automatic selection was very close: it was highly consistent in each subject for the default-mode network (≥92%) and the occipital network, which includes the medial visual cortical areas (≥94%), and consistent for the attention network (≥80%), the right and/or left lateralized frontoparietal attention networks, and the temporal-motor network (≥80%). The automatic selection method may be used to detect neural networks and reduce subjectivity in ICA component assessment.