162 research outputs found
Partitioning predictors in multivariate regression models
A Multivariate Regression Model Based on the Optimal Partition of Predictors (MRBOP) useful in applications in the presence of strongly correlated predictors is presented. Such classes of predictors are synthesized by latent factors, which are obtained through an appropriate linear combination of the original variables and are forced to be weakly correlated. Specifically, the proposed model assumes that the latent factors are determined by subsets of predictors characterizing only one latent factor. MRBOP is formalized in a least squares framework optimizing a penalized quadratic objective function through an alternating least-squares (ALS) algorithm. The performance of the methodology is evaluated on simulated and real data sets. © 2013 Springer Science+Business Media New York
Finite mixture clustering of human tissues with different levels of IGF-1 splice variants mRNA transcripts
BACKGROUND:
This study addresses a recurrent biological problem, that is to define a formal clustering structure for a set of tissues on the basis of the relative abundance of multiple alternatively spliced isoforms mRNAs generated by the same gene. To this aim, we have used a model-based clustering approach, based on a finite mixture of multivariate Gaussian densities. However, given we had more technical replicates from the same tissue for each quantitative measurement, we also employed a finite mixture of linear mixed models, with tissue-specific random effects.
RESULTS:
A panel of human tissues was analysed through quantitative real-time PCR methods, to quantify the relative amount of mRNA encoding different IGF-1 alternative splicing variants. After an appropriate, preliminary, equalization of the quantitative data, we provided an estimate of the distribution of the observed concentrations for the different IGF-1 mRNA splice variants in the cohort of tissues by employing suitable kernel density estimators. We observed that the analysed IGF-1 mRNA splice variants were characterized by multimodal distributions, which could be interpreted as describing the presence of several sub-population, i.e. potential tissue clusters. In this context, a formal clustering approach based on a finite mixture model (FMM) with Gaussian components is proposed. Due to the presence of potential dependence between the technical replicates (originated by repeated quantitative measurements of the same mRNA splice isoform in the same tissue) we have also employed the finite mixture of linear mixed models (FMLMM), which allowed to take into account this kind of within-tissue dependence.
CONCLUSIONS:
The FMM and the FMLMM provided a convenient yet formal setting for a model-based clustering of the human tissues in sub-populations, characterized by homogeneous values of concentrations of the mRNAs for one or multiple IGF-1 alternative splicing isoforms. The proposed approaches can be applied to any cohort of tissues expressing several alternatively spliced mRNAs generated by the same gene, and can overcome the limitations of clustering methods based on simple comparisons between splice isoform expression levels
Development in attention functions and social processing: Evidence from the Attention Network Test
According to the attention network approach, attention is best understood in terms of
three functionally and neuroanatomically distinct networks – alerting, orienting, and
executive attention. Recent findings showed that social information influences the
efficiency of these networks in adults. Using some social and non-social variants of the
Attentional Network Test (ANT), this study was aimed to evaluate the development of
the three attention networks in childhood, also assessing the development of the ability to
manage social or non-social conflicting information. Sixty-six children (three groups of 6,
8, and 10 years of age) performed three variants of the original ANT, using fish, schematic,
or real faces looking to the left or right as target and flanker stimuli. Results showed an
improvement from 6 to 8 and 10 years of age in reaction time (RT) and accuracy, together
with an improvement of executive control and a decrement in alerting. These
developmental changes were not unique to social stimuli, and no differences were
observed between social and no-social variants of the ANT. However, independently
from the age of the children, a real face positively affected the executive control (as
indexed by RTs) as compared to both a schematic face and a fish. Findings of this study
suggest that attentional networks are still developing from 6 to 10 years of age and
underline the importance of face information in modulating the efficiency of executive
control
DYNAMIC MIXTURES OF FACTOR ANALYZERS TO CHARACTERIZE MULTIVARIATE AIR POLLUTANT EXPOSURES
The assessment of pollution exposure is based on the analysis
of multivariate time series that include the concentrations of several
pollutants as well as the measurements of multiple atmospheric variables.
It typically requires methods of dimensionality reduction that
are capable to identify potentially dangerous combinations of pollutants
and, simultaneously, to segment exposure periods according
to air quality conditions. When the data are high-dimensional, however,
efficient methods of dimensionality reduction are challenging
because of the formidable structure of cross-correlations that arise
from the dynamic interaction between weather conditions and natural/anthropogenic
pollution sources. In order to assess pollution exposure
in an urban area while taking the above mentioned difficulties
into account, we develop a class of parsimonious hidden Markov
models. In a multivariate time-series setting, this approach allows to
simultaneously perform temporal segmentation and dimensionality
reduction. We specifically approximate the distribution of multiple
pollutant concentrations by mixtures of factor analysis models, whose
parameters evolve according to a latent Markov chain. Covariates are
included as predictors of the chain transition probabilities. Parameter
constraints on the factorial component of the model are exploited
to tune the flexibility of dimensionality reduction. In order to estimate
the model parameters efficiently, we propose a novel three-step
Alternating Expected Conditional Maximization (AECM) algorithm,
which is also assessed in a simulation study. In the case study, the
proposed methods were capable (1) to describe the exposure to pollution
in terms of a few latent regimes, (2) to associate these regimes
with specific combinations of pollutant concentration levels as well
as distinct correlation structures between concentrations, and (3) to
capture the influence of weather conditions on transitions between
regime
Centrality of Striatal Cholinergic Transmission in Basal Ganglia Function
Work over the past two decades revealed a previously unexpected role for striatal cholinergic interneurons in the context of basal ganglia function. The recognition that these interneurons are essential in synaptic plasticity and motor learning represents a significant step ahead in deciphering how the striatum processes cortical inputs, and why pathological circumstances cause motor dysfunction. Loss of the reciprocal modulation between dopaminergic inputs and the intrinsic cholinergic innervation within the striatum appears to be the trigger for pathophysiological changes occurring in basal ganglia disorders. Accordingly, there is now compelling evidence showing profound changes in cholinergic markers in these disorders, in particular Parkinson's disease and dystonia. Based on converging experimental and clinical evidence, we provide an overview of the role of striatal cholinergic transmission in physiological and pathological conditions, in the context of the pathogenesis of movement disorders
Performance improvement of broadband distributed Raman amplifier using bidirectional pumping with first and dual order forward pumps
In this paper, a new bidirectional pumping scheme with dual order forward pumps is proposed. Performance is compared numerically with conventional bidirectional and backward only pumping schemes for a 70 nm bandwidth, 61.5 km distributed Raman amplifier. We demonstrate that it is possible to design a flat gain spectrum with improved noise figure and OSNR, as well as a low gain ripple (<1 dB)
Lupus mastitis in male mimicking a breast lump
A 43-year-old male, with a 3-month history of a left breast lump underwent clinical evaluation in our Institute. This solid and irregular mass measured 2 2 cm and was located at the upper lateral quadrant with no skin changes. There were no inflammatory signs. However, a lymphadenopathy was presented with a mobile ipsilateral axillary node 1.5 cm in diameter. Computerized tomography demonstrated a hyperplastic lateral cervical lymph nodes reactio
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