Sensitivity Analysis of a Model of Human Papillomavirus Late Promoter Regulation.

A mathematical model of Human Papillomavirus late promoter regulation was recently developed, able to predict the main features of HPV gene expression during cellular differentiation under productive infection. A sensitivity analysis is performed to characterize the influence of transcriptional, post-transcriptional and translational regulations on the viral species related to E1, E2, E4 and Li genes. Sensitivity analysis indicates strong influence of parameters related to transcriptional and translational regulation. It also shows a strong influence on the parameters related to post-transcriptional regulation, showing the importance of modeling splicing regulation to well describe the biology of the late promoter.

Modeling HPV Late Promoter Regulation.

High risk HPV can induce cervical and oropharyngeal Iesions. HPV productive infection is strictly linked by differentiation-dependent control of the late promoter. This latter produces HPV transcripts at different epithelial layers through a complex post-transcriptional control. The aim of this study is to develop a novel mathematical model of the late promoter condensing the biological knowledge present in literature. The model describes the interaction among primary transcript, spliced transcripts and their proteins and includes the major splicing mechanisms. When used as an in silico tool it shows the crucial role of splicing regulation to explain the HPV gene expression. Novel testing hypothesis are then formulated to uncover this still elusive but pivotal promoter.

In Silico Modeling of the Antiplatelet Pharmacodynamics of Low-dose Aspirin in Health and Disease.

The influence of platelet turnover on cyclooxygenase (COX-1) inhibition by low-dose aspirin remains largely uncharacterized due to limited feasibility of studying aspirin pharmacodynamics in bone marrow precursors. We developed an in silico compartmental model describing the aspirin effects on COX-1 activity in a population of megakaryocytes (MK) and in peripheral platelets. Model parameters were inferred from the literature and calibrated using measurements of serum thromboxane B2 (sTXB2 ), as proxy of COX-1 activity in peripheral platelets, in 17 healthy subjects and 24 patients with essential thrombocythemia (ET). The model reproduced well the average time-course of sTXB2 inhibition in healthy (accuracy = 10.4%), the reduced inhibition of sTXB2 observed in ET, and the effect of different dosing regimens. In conclusion, the in silico model accurately describes COX-1 inactivation by low-dose aspirin in MK and platelets in different clinical settings, and might help personalize aspirin regimens in conditions of altered megakaryopoiesis.

3DSpectra: A 3-dimensional quantification algorithm for LC-MS labeled profile data.

Mass spectrometry-based proteomics can generate highly informative datasets, as profile three-dimensional (3D) LC-MS data: LC-MS separates peptides in two dimensions (time, m/z) minimizing their overlap, and profile acquisition enhances quantification. To exploit both data features, we developed 3DSpectra, a 3D approach embedding a statistical method for peptide border recognition. 3DSpectra efficiently accesses profile data by means of mzRTree, and makes use of a priori metadata, provided by search engines, to quantify the identified peptides. An isotopic distribution model, shaped by a bivariate Gaussian Mixture Model (GMM), which includes a noise component, is fitted to the peptide peaks using the expectation-maximization (EM) approach. The EM starting parameters, i.e., the centers and shapes of the Gaussians, are retrieved from the metadata. The borders of the peaks are delimited by the GMM iso-density curves, and noisy or outlying data are discarded from subsequent analysis. The 3DSpectra program was compared to ASAPRatio for a controlled mixture of Isotope-Coded Protein Labels (ICPL) labeled proteins, which were mixed at predefined ratios and acquired in enhanced profile mode, in triplicate. The 3DSpectra software showed significantly higher linearity, quantification accuracy, and precision than did ASAPRatio in this real use case simulation where the true ratios are known, and it also achieved wider peptide coverage and dynamic range. BIOLOGICAL SIGNIFICANCE: Quantitative proteomics is pivotal for many systems biology related fields, such as biomarker discovery. The quantification quality provided by the adopted software is crucial for the success of protein differential expression studies. To determine the reliability of a quantitative computational method, we suggest evaluating performance parameters like accuracy and precision of the quantifications, robustness to outliers and proteome coverage. A quantitative comparison of these parameters is highly desirable since it enables to benchmark software performance. We applied this strategy to 3DSpectra, a 3-dimensional approach to spectra analysis for MS1 peptide quantification. It distinguishes peptide peaks from spurious peaks interfering in the survey scan. 3DSpectra was compared to ASAPRatio in terms of quantification quality performance parameters and showed an overall improvement.

Modeling HPV early promoter regulation.

In high risk forms, human papillomaviruses (HPV) can either induce or promote cancerous lesions, especially cervical cancer which is considered the second most common cancer in the women worldwide. HPV life cycle is tightly linked to the infected cell differentiation program and its evolution is strictly joined to the switch between the early and the late viral polycistronic promoters.The aim of this study is to develop a novel mathematical model which collects and structures the available biologic knowledge on the early promoter regulation for HPV in episomal form. The model includes the main regulation by E2 viral protein as well as a novel discovered co-regulation function mediated by the viral E1 protein. Only by including both E2 and E1 regulatory effect the model is able to correctly predict the temporal behaviour of the early promoter switching off. A possible use of the model as in silico tool to evaluate new antiviral therapies is discussed.

Modelling hemodynamic response function in epilepsy.

OBJECTIVE: Electroencephalography and functional magnetic resonance imaging (fMRI) can be combined to noninvasively map abnormal brain activation elicited by epileptic processes. A major aim was to investigate the impact of a subject-specific hemodynamic response function (HRF) to describe the differences across patients versus the use of a standard model. METHODS: We developed and applied on simulated and real data a method designed to choose optimum HRF model for identifying fMRI activation maps. In simulation, the ability of five models to reproduce data was assessed: four standard and an individual-based HRF model (ibHRF). In clinical data, drug-resistant epileptic patients underwent fMRI to investigate hemodynamic responses evoked by interictal activity. RESULTS: When data are simulated with models different from the standard ones, the results obtained with ibHRF are superior to those obtained with the standard HRFs. Results on real data indicate an increase in extent and degree of activation with the ibHRF in comparison of the results obtainable using standard HRFs. CONCLUSIONS: The use of the same HRF in all patients is inappropriate and resolves in biased extension of the activation maps. SIGNIFICANCE: The new method could represent an useful diagnostic tool for other clinical studies that may be biased because of misspecification of HRF.

Effect of median-nerve electrical stimulation on BOLD activity in acute ischemic stroke patients.

OBJECTIVE: To investigate blood oxygenation level-dependent (BOLD) activation during somatosensory electrical stimulation of the median nerve in acute stroke patients and to determine its correlation with ischemic damage and clinical recovery over time. METHODS: Fourteen acute stroke patients underwent functional magnetic resonance imaging (fMRI) during contralesional median-nerve electrical stimulation 12-48 h after stroke. Findings were then validated by diffusion tensor imaging (DTI) and motor evoked potential by transcranial magnetic stimulation (TMS). RESULTS: Poor clinical recovery at three months was noted in four patients with no activation in the early days after stroke, whereas good clinical recovery was observed in eight patients with a normal activation pattern in the primary sensory motor area in the acute phase. In two patients BOLD activation correlated weakly with clinical recovery. Findings from TMS and DTI partially correlated with clinical recovery and functional scores. CONCLUSIONS: Clinically relevant insights into the "functional reserve" of stroke patients gained with peripheral nerve stimulation during fMRI may carry prognostic value already in the acute period of a cerebrovascular accident. SIGNIFICANCE: BOLD activation maps could provide insights into the functional organization of the residual systems and could contribute to medical decision making in neurological and rehabilitative treatment.

Relationship between fractional pancreatic beta cell area and fasting plasma glucose concentration in monkeys.

AIMS/HYPOTHESIS: We sought to establish the relationship between fasting plasma glucose concentrations and pancreatic fractional beta cell area in adult cynomolgus monkeys (Macaca fascicularis). METHODS: Fasting plasma glucose and pancreatic fractional beta cell area were measured in 18 control and 17 streptozotocin-treated adult primates (17.0 +/- 1.2 vs 15.4 +/- 1.2 years old). RESULTS: Fasting plasma glucose was increased (12.0 +/- 2.0 vs 3.4 +/- 0.1 mmol/l, p < 0.01) and fractional beta cell area was decreased (0.62 +/- 0.13% vs 2.49 +/- 0.35%, p < 0.01) in streptozotocin-treated monkeys. The relationship between fasting plasma glucose and pancreatic fractional beta cell area was described by a wide range of beta cell areas in controls. In streptozotocin-treated monkeys there was an inflection of fasting blood glucose at approximately 50% of the mean beta cell area in controls with a steep increase in blood glucose for each further decrement in beta cell area. CONCLUSIONS/INTERPRETATION: In adult non-human primates a decrement in fractional beta cell area of approximately 50% or more leads to loss of glycaemic control.

Electroencephalographic analysis for the assessment of hepatic encephalopathy: comparison of non-parametric and parametric spectral estimation techniques.

OBJECTIVE: To compare electroencephalographic spectral analysis obtained by periodogram (calculated by means of Fast Fourier Transform) and autoregressive (AR) modelling for the assessment of hepatic encephalopathy. METHODS: The mean dominant frequency (MDF) and the relative power of delta, theta, alpha, and beta bands were computed by both techniques from the electroencephalograms (EEG) of 201 cirrhotics and were evaluated in the clinical and prognostic assessment of the patients. RESULTS: The values of all the five indexes computed by periodogram and AR modelling matched each other, but the latter provided stable values after the analysis of fewer epochs. Independently of the technique, the relative power of theta and alpha bands fitted the clinical data and had prognostic value. The relative power of beta and delta bands computed by AR modelling fitted more closely with clinical data fitted the clinical data more closely. CONCLUSIONS: The electroencephalographic spectral indexes obtained by periodogram and AR modelling were found to be, on average, undistinguishable, but the latter appeared less sensitive to noise and provided a more reliable assessment of low-power bands.