Brain Age from the Electroencephalogram of Sleep

The human electroencephalogram (EEG) of sleep undergoes profound changes with age. These changes can be conceptualized as "brain age", which can be compared to an age norm to reflect the deviation from normal aging process. Here, we develop an interpretable machine learning model to predict brain age based on two large sleep EEG datasets: the Massachusetts General Hospital sleep lab dataset (MGH, N = 2,621) covering age 18 to 80; and the Sleep Hearth Health Study (SHHS, N = 3,520) covering age 40 to 80. The model obtains a mean absolute deviation of 8.1 years between brain age and chronological age in the healthy participants in the MGH dataset. As validation, we analyze a subset of SHHS containing longitudinal EEGs 5 years apart, which shows a 5.5 years difference in brain age. Participants with neurological and psychiatric diseases, as well as diabetes and hypertension medications show an older brain age compared to chronological age. The findings raise the prospect of using sleep EEG as a biomarker for healthy brain aging

Bayesian Centroid Estimation for Motif Discovery

Biological sequences may contain patterns that are signal important biomolecular functions; a classical example is regulation of gene expression by transcription factors that bind to specific patterns in genomic promoter regions. In motif discovery we are given a set of sequences that share a common motif and aim to identify not only the motif composition, but also the binding sites in each sequence of the set. We present a Bayesian model that is an extended version of the model adopted by the Gibbs motif sampler, and propose a new centroid estimator that arises from a refined and meaningful loss function for binding site inference. We discuss the main advantages of centroid estimation for motif discovery, including computational convenience, and how its principled derivation offers further insights about the posterior distribution of binding site configurations. We also illustrate, using simulated and real datasets, that the centroid estimator can differ from the maximum a posteriori estimator.Comment: 24 pages, 9 figure

Antibacterial, antioxidant and anti-proliferative properties and zinc content of five south Portugal herbs

Context: Crataegus monogyna L. (Rosaceae) (CM), Equisetum telmateia L. (Equisataceae) (ET), Geranium purpureum Vil. (Geraniaceae) (GP), Mentha suaveolens Ehrh. (Lamiaceae) (MS), and Lavandula stoechas L. spp. luisieri (Lamiaceae) (LS) are all medicinal. Objective: To evaluate the antioxidant, antiproliferative and antimicrobial activities of plant extracts and quantify individual phenolics and zinc. Material and methods: Aerial part extracts were prepared with water (W), ethanol (E) and an 80% mixture (80EW). Antioxidant activity was measured with TAA, FRAP and RP methods. Phenolics were quantified with a HPLC. Zinc was quantified using voltammetry. Antibacterial activity (after 48 h) was tested using Enterococcus faecalis, Bacillus cereus, Escherichia coli, Staphylococcus aureus, Pseudomonas aeruginosa and Listeria monocytogenes. Antiproliferative activity (after 24 h) was tested using HEP G2 cells and fibroblasts. Results: Solvents influenced results; the best were E and 80EW. GP had the highest antioxidant activity (TAA and FRAP of 536.90mg AAE/g dw and 783.48mg TE/g dw, respectively). CM had the highest zinc concentration (37.21 mg/kg) and phenolic variety, with neochlorogenic acid as the most abundant (92.91 mg/100 g dw). LS was rich in rosmarinic acid (301.71 mg/100 g dw). GP and LS inhibited the most microorganisms: B. cereus, E. coli and S. aureus. GP also inhibited E. faecalis. CM had the lowest MIC: 5830 mu g/mL. The antibacterial activity is explained by the phenolics present. LS and CM showed the most significant anti-proliferative activity, which is explained by their zinc content. Conclusion: The most promising plants for further studies are CM, LS and GP.FCT, Fundacao para a Ciencia e a Tecnologia of Portugal [SFRH/BSA/139/2014

Search for microwave emission from ultrahigh energy cosmic rays

We present a search for microwave emission from air showers induced by ultrahigh energy cosmic rays with the microwave detection of air showers experiment. No events were found, ruling out a wide range of power flux and coherence of the putative emission, including those suggested by recent laboratory measurements.Comment: 5 pages, 3 figure

Piedra blanca genital. Reporte de tres casos

Se informa de 2 casos de micosis superficiales causados por Trichosporon belgelii observados en personal militar y uno en un homosexual, en Sao Paulo, Brasi

A review on the current Status of Numerical Weather Prediction in Portugal 2021: surface–atmosphere interactions

Earth system modelling is currently playing an increasing role in weather forecasting and understanding climate change, however, the operation, deployment and development of numerical Earth system models are extremely demanding in terms of computational resources and human effort. Merging synergies has become a natural process by which national meteorological services assess and contribute to the development of such systems. With the advent of joining synergies at the national level, the second edition of the workshop on Numerical Weather Prediction in Portugal was promoted by the Portuguese Institute for the Sea and Atmosphere, I.P. (IPMA), in cooperation with several Portuguese Universities. The event was hosted by the University of Évora, during the period of 11–12 of November 2021. It was dedicated to surface–atmosphere interactions and allowed the exchange of experiences between experts, students and newcomers. The workshop provided a refreshed overview of ongoing research and development topics in Portugal on surface–atmosphere interaction modelling and its applications and an opportunity to revisit some of the concepts associated with this area of atmospheric sciences. This article reports on the main aspects discussed and offers guidance on the many technical and scientific modelling platforms currently under study.info:eu-repo/semantics/publishedVersio

Genetically encoded sender-receiver system in 3D mammalian cell culture

Engineering spatial patterning in mammalian cells, employing entirely genetically encoded components, requires solving several problems. These include how to code secreted activator or inhibitor molecules and how to send concentration-dependent signals to neighboring cells, to control gene expression. The Madin-Darby Canine Kidney (MDCK) cell line is a potential engineering scaffold as it forms hollow spheres (cysts) in 3D culture and tubulates in response to extracellular hepatocyte growth factor (HGF). We first aimed to graft a synthetic patterning system onto single developing MDCK cysts. We therefore developed a new localized transfection method to engineer distinct sender and receiver regions. A stable reporter line enabled reversible EGFP activation by HGF and modulation by a secreted repressor (a truncated HGF variant, NK4). By expanding the scale to wide fields of cysts, we generated morphogen diffusion gradients, controlling reporter gene expression. Together, these components provide a toolkit for engineering cell-cell communication networks in 3D cell culture.Centro Regional de Estudios Genómico

Copy number alterations associated with clinical features in an underrepresented population with breast cancer

As the most incident tumor among women worldwide, breast cancer is a heterogeneous disease. Tremendous efforts have been made to understand how tumor characteristics as histological type, molecular subtype, and tumor microenvironment collectively influence disease diagnosis to treatment, which impact outcomes. Differences between populations and environmental and cultural factors have impacts on the origin and evolution of the disease, as well as the therapeutic challenges that arise due to these factors. We, then, compared copy number variations (CNVs) in mucinous and nonmucinous luminal breast tumors from a Brazilian cohort to investigate major CNV imbalances in mucinous tumors versus non‐mucinous luminal tumors, taking into account their clinical and pathological features.48 breast tumor samples and 48 matched control blood samples from Brazilian women were assessed for CNVs by chromosome microarray. Logistic regression and random forest models were used in order to assess CNVs in chromosomal regions from tumors.CNVs that were identified in chromosomes 1, 5, 8, 17, 19, and 21 classify tumors according to their histological type, ethnicity, disease stage, and familial history.Copy number alterations described in this study provide a better understanding of the landscape of genomic aberrations in mucinous breast cancers that are associated with clinical features.77FAPESP – Fundação de Amparo à Pesquisa Do Estado De São Paulo2013/25683-3; 2015/18830-