Mixed-effects high-dimensional multivariate regression via group-lasso regularization

Linear mixed modeling is a well-established technique widely employed when observations possess a grouping structure. Nonetheless, this standard methodology is no longer applicable when the learning framework encompasses a multivariate response and high-dimensional predictors. To overcome these issues, in the present paper a penalized estimation procedure for multivariate linear mixed-effects models (MLMM) is introduced. In details, we propose to regularize the likelihood via a group-lasso penalty, forcing only a subset of the estimated parameters to be preserved across all components of the multivariate response. The methodology is employed to develop novel surrogate biomarkers for cardiovascular risk factors, such as lipids and blood pressure, from whole-genome DNA methylation data in a multi-center study. The described methodology performs better than current stateof- art alternatives in predicting a multivariate continuous outcome

Low delta-V near-Earth asteroids: A survey of suitable targets for space missions

In the last decades Near-Earth Objects (NEOs) have become very important targets to study, since they can give us clues to the formation, evolution and composition of the Solar System. In addition, they may represent either a threat to humankind, or a repository of extraterrestrial resources for suitable space-borne missions. Within this framework, the choice of next-generation mission targets and the characterisation of a potential threat to our planet deserve special attention. To date, only a small part of the 11,000 discovered NEOs have been physically characterised. From ground and space-based observations one can determine some basic physical properties of these objects using visible and infrared spectroscopy. We present data for 13 objects observed with different telescopes around the world (NASA-IRTF, ESO-NTT, TNG) in the 0.4 - 2.5 um spectral range, within the NEOSURFACE survey (http://www.oa-roma.inaf.it/planet/NEOSurface.html). Objects are chosen from among the more accessible for a rendez-vous mission. All of them are characterised by a delta-V (the change in velocity needed for transferring a spacecraft from low-Earth orbit to rendez-vous with NEOs) lower than 10.5 km/s, well below the Solar System escape velocity (12.3 km/s). We taxonomically classify 9 of these objects for the first time. 11 objects belong to the S-complex taxonomy; the other 2 belong to the C-complex. We constrain the surface composition of these objects by comparing their spectra with meteorites from the RELAB database. We also compute olivine and pyroxene mineralogy for asteroids with a clear evidence of pyroxene bands. Mineralogy confirms the similarity with the already found H, L or LL ordinary chondrite analogues.Comment: 9 pages, 7 figures, to be published in A&A Minor changes by language edito

Imaging-based representation and stratification of intra-tumor heterogeneity via tree-edit distance

Personalized medicine is the future of medical practice. In oncology, tumor heterogeneity assessment represents a pivotal step for effective treatment planning and prognosis prediction. Despite new procedures for DNA sequencing and analysis, non-invasive methods for tumor characterization are needed to impact on daily routine. On purpose, imaging texture analysis is rapidly scaling, holding the promise to surrogate histopathological assessment of tumor lesions. In this work, we propose a tree-based representation strategy for describing intra-tumor heterogeneity of patients affected by metastatic cancer. We leverage radiomics information extracted from PET/CT imaging and we provide an exhaustive and easily readable summary of the disease spreading. We exploit this novel patient representation to perform cancer subtyping according to hierarchical clustering technique. To this purpose, a new heterogeneity-based distance between trees is defined and applied to a case study of prostate cancer. Clusters interpretation is explored in terms of concordance with severity status, tumor burden and biological characteristics. Results are promising, as the proposed method outperforms current literature approaches. Ultimately, the proposed method draws a general analysis framework that would allow to extract knowledge from daily acquired imaging data of patients and provide insights for effective treatment planning

Rotavirus-associated seizures and reversible corpus callosum lesion

Rotavirus is a non-enveloped double-stranded RNA virus that causes severe gastroenteritis in children, but complications are rarely reported. Some reports have shown that rotavirus can induce diverse complications of the central nervous system, such as seizures, encephalopathy with a reversible splenial lesion, encephalitis, cerebral white matter abnormalities, and cerebellitis. Here, we present a 2-year-old patient with seizures, who had an isolated splenial lesion in the corpus callosum on neuroimaging, and the rotavirus antigen detected in faeces. © Lietuvos mokslu akademija, 2019. Other Abstract: ROTAVIRUSO SUKELTI TRAUKULIAI IR LAIKINAS DIDZIOSIOS SMEGENU JUNGTIES PAZEIDIMAS: SantraukaRotavirusas yra dvigrandes RNR virusas be apvalkalo, sukeliantis sunku vaiku gastroenterita, taciau apie komplikacijas pranesama retai. Kai kurie atveju aprasymai rodo, kad rotavirusas gali sukelti ivairias centrines nervu sistemos komplikacijas, tokias kaip traukuliai, encefalopatija su trumpalaikiu didziosios smegenu jungties pazeidimu, encefalitas, smegenu baltosios medziagos anomalijos ir cerebelitas. Cia pristatome dveju metu pacienta su traukuliais, kuriam laikinas didziosios smegenu jungties pazeidimas buvo nustatytas neurovaizdinimo metu, o rotaviruso antigenas aptiktas ismatose.Raktazodziai: rotavirusas, vaiku traukuliai, rotaviruso komplikacijos.publishersversionPeer reviewe

Setting rents in residential real estate: a methodological proposal using multiple criteria decision analysis

The real estate sector has been negatively affected by the recent economic recession, which has forced structural changes that impact property value and price. Recent pressures have also motivated reduced liquidity and access to credit, causing a drop in property sales and, thus, boosting the rental housing market. It is worth noting, however, that the rental housing segment is not with-out difficulties and complexity, namely in terms of legislation and rental value revaluation. In light of this reasoning, this study aims to develop a multiple criteria decision support system for calculation of residential rents. By integrating cognitive maps and the measuring attractiveness by a categorical based evaluation technique (MACBETH), we also aim to introduce simplicity and transparency in the decision making framework. The practical implications, advantages and shortfalls of our proposal are also analyzed

Visualizing active membrane protein complexes by electron cryotomography.

This is the final version of the article. Available from Nature Publishing Group via the DOI in this record.Unravelling the structural organization of membrane protein machines in their active state and native lipid environment is a major challenge in modern cell biology research. Here we develop the STAMP (Specifically TArgeted Membrane nanoParticle) technique as a strategy to localize protein complexes in situ by electron cryotomography (cryo-ET). STAMP selects active membrane protein complexes and marks them with quantum dots. Taking advantage of new electron detector technology that is currently revolutionizing cryotomography in terms of achievable resolution, this approach enables us to visualize the three-dimensional distribution and organization of protein import sites in mitochondria. We show that import sites cluster together in the vicinity of crista membranes, and we reveal unique details of the mitochondrial protein import machinery in action. STAMP can be used as a tool for site-specific labelling of a multitude of membrane proteins by cryo-ET in the future.We thank Drs Ulrike Endesfelder and Mike Heilemann (Institute of Physical and Theoretical Chemistry, University of Frankfurt) for help with confocal microscopy, Deryck Mills (MPI of Biophysics, Frankfurt) for maintenance of the EM facility, and Paolo Lastrico (Graphics Department, MPI of Biophysics, Frankfurt) for assistance with Supplementary Movies and Fig. 1a. We thank Drs Bertram Daum and Karen Davies for helpful discussions on tomography. The plasmids pMAL-c2x-MT2 and pMAL-c2x-MT3 were a gift from Dr Christina Risco (CNB-CSIC, Madrid). This work was supported by the Max Planck Society, Deutsche Forschungsgemeinschaft (Sonderforschungsbereich 746), Excellence Initiative of the German Federal & State Governments (EXC 294 BIOSS) and by an EMBO Long-Term Fellowship to V.A.M.G. (ALTF 1035-2010)

Radiomics-Based Inter-Lesion Relation Network to Describe [18F]FMCH PET/CT Imaging Phenotypes in Prostate Cancer

Advanced image analysis, specifically radiomics, has been recognized as a potential source of biomarkers for cancers. However, there are challenges to its application in the clinic, such as proper description of diseases where multiple lesions coexist. In this study, we aimed to characterize the intra-tumor heterogeneity of metastatic prostate cancer using an innovative approach. This approach consisted of a transformation method to build a radiomic profile of lesions extracted from [18F]FMCH PET/CT images, a qualitative assessment of intra-tumor heterogeneity of patients, and a quantitative representation of the intra-tumor heterogeneity of patients in terms of the relationship between their lesions’ profiles. We found that metastatic prostate cancer patients had lesions with different radiomic profiles that exhibited intra-tumor radiomic heterogeneity and that the presence of many radiomic profiles within the same patient impacted the outcome

A Semiparametric Bayesian Multivariate Model for Survival Probabilities After Acute Myocardial Infarction

In this work, a Bayesian semiparametric multivariate model is fitted to study data related to in-hospital and 60-day survival probabilities of patients admitted to a hospital with ST-elevation myocardial infarction diagnosis. We consider a hierarchical generalized linear model to predict survival probabilities and a process indicator (time of intervention). Poisson-Dirichlet process priors, generalizing the well-known Dirichlet process, are considered for modeling the random-effect distribution of the grouping factor which is the hospital of admission