Biomedical subjects

Paolo Magni

Publications and source records attributed to Paolo Magni.

At least 19 recordsLinked to original sources

PubMed2007

Role of neuropeptide Y and its receptors in the progression of endocrine-related cancer.

The neuropeptide Y (NPY) family of peptides, in addition to its many physiological actions, has also been involved in the modulation of tumor progression, with specific reference to endocrine-related cancers such as neuroendocrine tumors, breast and prostate cancers. These have been found either to express NPY receptors, or to secrete NPY-related peptides, or both. The study of the role of the NPY family of peptides in the biology of endocrine-related tumors, specifically concerning cell proliferation, angiogenesis, invasion and metastatization, may help to clarify some aspects of tumor pathophysiology, as well as to indicate novel diagnostic markers and therapeutical approaches.

Disease Progression↗

PubMed2006

A hierarchical Naïve Bayes Model for handling sample heterogeneity in classification problems: an application to tissue microarrays.

BACKGROUND: Uncertainty often affects molecular biology experiments and data for different reasons. Heterogeneity of gene or protein expression within the same tumor tissue is an example of biological uncertainty which should be taken into account when molecular markers are used in decision making. Tissue Microarray (TMA) experiments allow for large scale profiling of tissue biopsies, investigating protein patterns characterizing specific disease states. TMA studies deal with multiple sampling of the same patient, and therefore with multiple measurements of same protein target, to account for possible biological heterogeneity. The aim of this paper is to provide and validate a classification model taking into consideration the uncertainty associated with measuring replicate samples. RESULTS: We propose an extension of the well-known Naïve Bayes classifier, which accounts for biological heterogeneity in a probabilistic framework, relying on Bayesian hierarchical models. The model, which can be efficiently learned from the training dataset, exploits a closed-form of classification equation, thus providing no additional computational cost with respect to the standard Naïve Bayes classifier. We validated the approach on several simulated datasets comparing its performances with the Naïve Bayes classifier. Moreover, we demonstrated that explicitly dealing with heterogeneity can improve classification accuracy on a TMA prostate cancer dataset. CONCLUSION: The proposed Hierarchical Naïve Bayes classifier can be conveniently applied in problems where within sample heterogeneity must be taken into account, such as TMA experiments and biological contexts where several measurements (replicates) are available for the same biological sample. The performance of the new approach is better than the standard Naïve Bayes model, in particular when the within sample heterogeneity is different in the different classes.

Algorithms↗

PubMed2006

A stochastic model to assess the variability of blood glucose time series in diabetic patients self-monitoring.

Several studies have shown that patients suffering from Diabetes Mellitus can significantly delay the onset and slow down the progression of diabetes micro- and macro-angiopathic complications through intensive monitoring and treatment. In general, intensive treatments imply a careful blood glucose level (BGL) self-monitoring. The analysis of BGL measurements is one of the most important tasks in order to assess the glucose metabolic control and to revise the therapeutic protocol. Recent clinical studies have shown the correlation between the glucose variability and the long-term diabetes related complications. In this paper, we propose a stochastic model to extract the time course of such variability from the self-monitoring BGL time series. This information can be conveniently combined with other analysis to evaluate the adequacy of the therapeutic protocol and to highlight periods characterized by an increasing glucose instability. The method here proposed has been validated on two simulated data sets and tested with success in the retrospective analysis of three patients' data sets.

Algorithms↗

PubMed2006

Inferring gene expression networks via static and dynamic data integration.

This paper presents a novel approach for the extraction of gene regulatory networks from DNA microarray data. The approach is characterized by the integration of data coming from static and dynamic experiments, exploiting also prior knowledge on the biological process under analysis. A starting network topology is built by analyzing gene expression data measured during knockout experiments. The analysis of time series expression profiles allows to derive the complete network structure and to learn a model of the gene expression dynamics: to this aim a genetic algorithm search coupled with a regression model of the gene interactions is exploited. The method has been applied to the reconstruction of a network of genes involved into the Saccharomyces Cerevisiae cell cycle. The proposed approach was able to reconstruct known relationships among genes and to provide meaningful biological results.

Artificial Intelligence↗

PubMed2006

Plasma nerve growth factor (NGF) and inflammatory cytokines (IL-6 and MCP-1) in young and adult subjects with Down syndrome: an interesting pathway.

OBJECTIVES: Down's syndrome (DS) is the most frequent chromosomal aberration in men and it is invariably associated with mental retardation. MATERIAL AND METHODS: Plasma levels of nerve growth factor (NGF), interleukin-6 (IL-6), and monocyte chemoattractant protein-1 (MCP-1) from non demented DS subjects of three different age-cohorts (2-14 years; 20-50 yrs; >60 yrs) and healthy controls were measured. No clinical and sub-clinical inflammation was apparent in DS patients. RESULTS: Plasma levels of NGF were higher in children, adult and old DS subjects than in controls. However, a significant age-related decrease of NGF levels was present in DS subjects. Serum levels of IL-6 and MCP-1 were also increased in DS children and adults, but not in older DS patients. CONCLUSIONS: High levels of circulating NGF might protect DS from clinical complications of atherosclerosis. However, the striking decrement of peripheral NGF levels with advancing age may predispose DS to clinical manifestation of dementia after adulthood.

Adolescent↗

PubMed2005

Activation of the Y1 receptor by neuropeptide Y regulates the growth of prostate cancer cells.

This study deals with the role of neuropeptide Y (NPY) in the regulation of cell proliferation. NPY is expressed in the normal and tumoral prostate, but no data on its possible role in prostate cancer (PCa) progression are available. Therefore, we evaluated the direct effect of NPY on the growth of the human PCa cell lines LNCaP (androgen dependent) and DU145 and PC3 (androgen independent). All PCa cell lines expressed Y1-R gene and protein. NPY treatment reduced the proliferation of LNCaP and DU145 cells and increased that of PC3 cells. The Y1-R antagonist BIBP3226 abolished such effects, suggesting a mandatory role of Y1-R in this process. LNCaP cells showed elevated constitutive levels of phosphorylated ERK1/2, which were not affected by NPY. In DU145 cells, NPY stimulated a long-lasting ERK1/2 activation, whereas, in PC3 cells, this effect was rapid and transient and required activation of protein kinase C. Moreover, in both cell lines, pretreatment with BIBP3226 prevented the NPY-induced ERK1/2 phosphorylation, further supporting Y1-R involvement. NPY treatment reduced forskolin-stimulated cAMP accumulation only in PC3 cells and did not change intracellular calcium concentration in any PCa cell line. These data indicate that NPY may directly regulate PCa cell growth via Y1-R. The direction of this effect appears to be related to the time kinetics of MAPK activation, i.e. long-lasting vs. transient, and to the clone-specific involvement of other intracellular signals. These findings suggest that NPY-related mechanisms might play a relevant role in the progression of PCa, at both androgen dependent and independent stages.

Blotting, Western↗

PubMed2005

Reduced sampling schedule for the glucose minimal model: importance of Bayesian estimation.

The minimal model (MM) of glucose kinetics during an intravenous glucose tolerance test (IVGTT) is widely used in clinical studies to measure metabolic indexes such as glucose effectiveness (S(G)) and insulin sensitivity (S(I)). The standard (frequent) IVGTT sampling schedule (FSS) for MM identification consists of 30 points over 4 h. To facilitate clinical application of the MM, reduced sampling schedules (RSS) of 13-14 samples have also been derived for normal subjects. These RSS are especially appealing in large-scale studies. However, with RSS, the precision of S(G) and S(I) estimates deteriorates and, in certain cases, becomes unacceptably poor. To overcome this difficulty, population approaches such as the iterative two-stage (ITS) approach have been recently proposed, but, besides leaving some theoretical issues open, they appear to be oversized for the problem at hand. Here, we show that a Bayesian methodology operating at the single individual level allows an accurate determination of MM parameter estimates together with a credible measure of their precision. Results of 16 subjects show that, in passing from FSS to RSS, there are no significant changes of point estimates in nearly all of the subjects and that only a limited deterioration of parameter precision occurs. In addition, in contrast with the previously proposed ITS method, credible confidence intervals (e.g., excluding negative values) are obtained. They can be crucial for a subsequent use of the estimated MM parameters, such as in classification, clustering, regression, or risk analysis.

Adult↗

PubMed2005

Aldosterone receptor antagonists: biology and novel therapeutic applications.

A dysregulation of the aldosterone system has been involved in the pathophysiology of cardiovascular diseases, including myocardial failure and, partially, essential hypertension. In humans and in rat models, aldosterone action induces heart remodeling and interstitial and perivascular myocardial fibrosis. Therefore, a rationale for using aldosterone antagonists (ARAs) of the spironolactone family, which have been available for decades for the treatment of aldosterone excess syndromes, has now emerged. The development of compounds such as eplerenone, with a greater selectivity for mineralocorticoid receptors, is promising also in terms of reduction of endocrine side effects. The use of ARAs for the treatment of myocardial failure and selected cases of hypertension, in combination with the current therapy, has been strongly supported by trials such as the Randomized Aldactone Evaluation Study (RALES) and the Eplerenone Neurohormonal Efficacy and Survival Study (EPHESUS). Thus, the addition of ARAs to the conventional therapy appears beneficial, leading to an improved survival rate and a reduced incidence of cardiac complications.

Aldosterone↗

PubMed2005

Temporal data mining for the quality assessment of hemodialysis services.

OBJECTIVE: This paper describes the temporal data mining aspects of a research project that deals with the definition of methods and tools for the assessment of the clinical performance of hemodialysis (HD) services, on the basis of the time series automatically collected during hemodialysis sessions. METHODS: Intelligent data analysis and temporal data mining techniques are applied to gain insight and to discover knowledge on the causes of unsatisfactory clinical results. In particular, two new methods for association rule discovery and temporal rule discovery are applied to the time series. Such methods exploit several pre-processing techniques, comprising data reduction, multi-scale filtering and temporal abstractions. RESULTS: We have analyzed the data of more than 5800 dialysis sessions coming from 43 different patients monitored for 19 months. The qualitative rules associating the outcome parameters and the measured variables were examined by the domain experts, which were able to distinguish between rules confirming available background knowledge and unexpected but plausible rules. CONCLUSION: The new methods proposed in the paper are suitable tools for knowledge discovery in clinical time series. Their use in the context of an auditing system for dialysis management helped clinicians to improve their understanding of the patients' behavior.

Algorithms↗

PubMed2005

TA-clustering: cluster analysis of gene expression profiles through Temporal Abstractions.

This paper describes a new technique for clustering short time series of gene expression data. The technique is a generalization of the template-based clustering and is based on a qualitative representation of profiles which are labelled using trend Temporal Abstractions (TAs); clusters are then dynamically identified on the basis of this qualitative representation. Clustering is performed in an efficient way at three different levels of aggregation of qualitative labels, each level corresponding to a distinct degree of qualitative representation. The developed TA-clustering algorithm provides an innovative way to cluster gene profiles. We show the developed method to be robust, efficient and to perform better than the standard hierarchical agglomerative clustering approach when dealing with temporal dislocations of time series. Results of the TA-clustering algorithm can be visualized as a three-level hierarchical tree of qualitative representations and as such easy to interpret. We demonstrate the utility of the proposed algorithm on a set of two simulated data sets and on a study of gene expression data from S. cerevisiae.

Algorithms↗

PubMed2005

Free and bound plasma leptin in normal weight and obese men and women: relationship with body composition, resting energy expenditure, insulin-sensitivity, lipid profile and macronutrient preference.

OBJECTIVE: The adipose-borne hormone leptin circulates in free and protein-bound forms but little information is available about their biological significance. Free leptin (FL) levels are related to changes in fat mass, whereas bound leptin (BL) appears to be associated with resting energy expenditure (REE). Our aim was to assess FL and BL levels in normal weight and obese subjects and correlate them with metabolic and nutritional variables. DESIGN AND PATIENTS: The partitioning of plasma leptin between FL and BL was evaluated in a population (n = 44) including both genders and different degrees of adiposity [body mass index (BMI) range 18.6-79.6 kg/m2]. MEASUREMENTS: Total leptin and FL and BL concentrations were measured by fast protein liquid chromatography (FPLC) followed by radioimmunoassay (RIA). Body composition, REE, insulin sensitivity, lipid parameters associated with cardiovascular risk and macronutrient preference were also assessed. RESULTS: The BL/FL ratio was significantly reduced in obese subjects due to a major increase in FL compared with BL. Consequently, the gender difference of the %BL/%FL ratio present in lean subjects (35/65 in women; 65/35 in men) was lost in obese subjects. REE was negatively correlated with total leptin (P < 0.0001) and %FL (P < 0.0001), and positively with %BL (P < 0.001). Total leptin and FL were correlated with the diet carbohydrate content in all subjects. CONCLUSIONS: FL increases with the amount of fat mass; the prevalence of FL in normal weight women in comparison to men suggests that this fraction is particularly linked to the amount of subcutaneous fat. Moreover, the correlation of BL with REE and the relationship of FL with food intake favours the view of different biological activities for the two circulating forms of leptin.

Adipose Tissue↗

PubMed2005

Random walk models for bayesian clustering of gene expression profiles.

The analysis of gene expression temporal profiles is a topic of increasing interest in functional genomics. Model-based clustering methods are particularly interesting because they are able to capture the dynamic nature of these data and to identify the optimal number of clusters. We have defined a new Bayesian method that allows us to cope with some important issues that remain unsolved in the currently available approaches: the presence of time dislocations in gene expression, the non-stationarity of the processes generating the data, and the presence of data collected on an irregular temporal grid. Our method, which is based on random walk models, requires only mild a priori assumptions about the nature of the processes generating the data and explicitly models inter-gene variability within each cluster. It has first been validated on simulated datasets and then employed for the analysis of a dataset relative to serum-stimulated fibroblasts. In all cases, the results have been promising, showing that the method can be helpful in functional genomics research.

Journal Article↗

PubMed2004

Predictive pharmacokinetic-pharmacodynamic modeling of tumor growth kinetics in xenograft models after administration of anticancer agents.

The available mathematical models describing tumor growth and the effect of anticancer treatments on tumors in animals are of limited use within the drug industry. A simple and effective model would allow applying quantitative thinking to the preclinical development of oncology drugs. In this article, a minimal pharmacokinetic-pharmacodynamic model is presented, based on a system of ordinary differential equations that link the dosing regimen of a compound to the tumor growth in animal models. The growth of tumors in nontreated animals is described by an exponential growth followed by a linear growth. In treated animals, the tumor growth rate is decreased by a factor proportional to both drug concentration and number of proliferating tumor cells. A transit compartmental system is used to model the process of cell death, which occurs at later times. The parameters of the pharmacodynamic model are related to the growth characteristics of the tumor, to the drug potency, and to the kinetics of the tumor cell death. Therefore, such parameters can be used for ranking compounds based on their potency and for evaluating potential differences in the tumor cell death process. The model was extensively tested on discovery candidates and known anticancer drugs. It fitted well the experimental data, providing reliable parameter estimates. On the basis of the parameters estimated in a first experiment, the model successfully predicted the response of tumors exposed to drugs given at different dose levels and/or schedules. It is, thus, possible to use the model prospectively, optimizing the design of new experiments.

Antineoplastic Agents↗

PubMed2004

Analysing Italian voluntary abortion data using a Bayesian approach to the time series decomposition.

After the approval of the law on voluntary abortion in Italy, the Italian health care system started to practice voluntary abortion before the third month of pregnancy. Since 1980, the Italian Institute of Statistics (ISTAT) has collected data on the abortion frequency per month and per administrative local areas. Although a preliminary analysis of the data showed that, after an initial increase, the number of abortions progressively lowered over years, there is no insight on the existence of periodicity in the time series and on the local effects related to the regional habits and social environments. The aim of our study is therefore to extract local trends and periodicity from the data collected by ISTAT, by combining a 'structural model' of the time series and Bayesian statistics. This paper describes both the adopted stochastic model and its Bayesian estimation through a Markov chain Monte Carlo approach on the Italian abortion data. Abortion data are analysed both at national level and in each of the 95 Italian local areas. At the national level this analysis allows extraction of a trend component that clearly shows that the voluntary abortion trend has decreased constantly since June-July 1983 until the end of the study. The periodic component shows an astonishing regularity too, suggesting that the Italian people have a seasonal preference for voluntary abortion. In particular, abortions are concentrated in the central part of the year (April-August). Finally, at the local level this analysis allows us to find similarities/differences between different areas in trends and/or in seasonal preferences.

Abortion, Legal↗

PubMed2004

Insulin minimal model indexes and secretion: proper handling of uncertainty by a Bayesian approach.

The identification of the insulin minimal model (MM) for the estimation of insulin secretion rate (ISR) and physiological indexes (e.g. beta-cell sensitivity) requires the knowledge of C-peptide (CP) kinetics. The four parameters of the two-compartment model of CP kinetics in a given individual can be derived either from an additional bolus experiment or, more frequently, from a population model. However, in both situations, the CP kinetics is uncertain and, in MM identification, it should be treated as such. This paper shows how to handle CP kinetics uncertainty by using a Bayesian methodology. In seven subjects, MM indexes and ISR were estimated together with their confidence intervals, using either the bolus data or the population model to assess CP kinetics. The two main results that arise from the application of the new methodology are: (i) the use of the population model in place of the bolus data to determine CP kinetics does not affect, on average, the point estimates of ISR profile and MM parameters but only the confidence intervals which becomes wider (less than 50%); (ii) in both the bolus and population situation neglecting the uncertainty of CP kinetics, as done in MM literature so far, introduces no bias, on average, on point estimates of MM indexes but only an underestimation of confidence intervals.

Adult↗

PubMed2003

Comprehensive two-dimensional gas chromatography using large sample volume injection for the determination of polynuclear aromatic hydrocarbons in complex matrices.

The sensitivity of a gas chromatography (GC) analytical method can be substantially enhanced by injecting large sample volumes. The novel Large Volume Splitless injection technique was used in combination with comprehensive two-dimensional GC (GC x GC), taking advantage of the improved detectability and the very high separation capability. An experimental version of Thermo Electron TRACE GC Ultra using a cryogenic dual jet modulator was utilized with a fast flame ionization detector (FID) for the analysis of low ppbs level of PAHs compounds in very complex matrices. Experimental data (relative standard deviation of 1% evaluated on a standard mixture) demonstrate the reliability of the whole system. A dedicated data system is presented for acquiring and managing GC x GC data: three-dimensional and color plot visualization, peaks integration, identification and quantitation are functions available with the software.

Chromatography, Gas↗

PubMed2003

In vitro cell growth pharmacodynamic studies: a new nonparametric approach to determining the relative importance of drug concentration and treatment time.

PURPOSE: The effect of an anticancer treatment on tumor cell proliferation in vitro can be described as a three-dimensional surface where the inhibitory effect is related to drug concentration and treatment time. The analysis of this kind of response surface could provide critical information: for example, it could indicate whether a prolonged exposure to a low concentration of an anticancer agent will produce a different effect from exposure to higher concentrations for a shorter period of time. The parametric approach available in the literature was not flexible enough to accommodate the behavior of the response surface in some of the data sets collected as part of our research programs. Therefore, a new, general, nonparametric approach was developed. METHODS: The response surface of the inhibition of cell-based tumor growth was described using a radial basis function neural network (RBF-NN). The RBF-NN was trained using regularization theory, which provided the initialization of a constrained quadratic optimization algorithm that imposes monotonicity of the surface with respect to both concentration and exposure time. RESULTS: In the two analyzed cases (doxorubicin and flavopiridol), the proposed method was accurate and reliable in describing the inhibition surface of tumor cell growth as a function of drug concentration and exposure time. Residuals were small and unbiased. The new method improved on the parametric approach when the relative importance of drug concentration and exposure time in determining the overall effect was not constant across the experimental data. CONCLUSIONS: The proposed RBF-NN can be reliably applied for the analysis in cell-based tumor growth inhibition studies. This approach can be used for optimizing the administration regimens to be adopted in vivo. The use of this methodology can be easily extended to any cell-based experiment, in which the outcome can be seen as a function of two experimental variables.

Antineoplastic Agents↗

PubMed2003

Hormonal control of the neuropeptide Y system.

Neuropeptide Y (NPY) and the related receptors represent a widely diffused system that is involved in the regulation of multiple biological functions. NPY, a 36-aminoacid peptide expressed in several areas of the nervous system, is a pleiotropic factor participating to the control of some physiological processes, such as cognitive functions, eating behavior, circadian rhythms, neuroendocrine mechanisms, reproductive and cardiovascular functions. NPY acts through a series of G-protein-associated membrane receptors (NPY-Rs), characterized by different tissue distribution and affinity for the ligand. The expression and secretion of NPY and the expression of NPY-R isoforms are controlled by a very wide range of agents, acting in an endocrine and/or paracrine fashion. NPY and NPY-Rs appear to be strongly involved in the control of eating behavior; their expression is modulated by changes of food intake and energy balance and is disrupted in several animal models of obesity and diabetes. Moreover, the hypothalamic NPY system appears to integrate signals of energy balance in the modulation of the reproductive axis. Agents that stimulate their expression include activators of intracellular signalling pathways (protein kinase A and C), classical neurotransmitters, steroid and peptide hormones and growth factors, while other agents (leptin, insulin and retinoic acid) have been shown to be inhibitory. Interestingly, some agents, like retinoic acid, have been shown to modulate the expression of both NPY and NPY-Rs in the same direction, thus providing a fine mechanism for the tuning of the system. The regulation of NPY/NPY-R expression and function appears to be part of a complex system controlling multiple physiological functions, and its disruption might be relevant in the pathophysiology of disease states such as obesity.

Amino Acid Sequence↗