Sleep staging algorithm based on smartwatch sensors for healthy and sleep apnea populations.

OBJECTIVE: Sleep stages can provide valuable insights into an individual's sleep quality. By leveraging movement and heart rate data collected by modern smartwatches, it is possible to enable the sleep staging feature and enhance users' understanding about their sleep and health conditions. METHOD: In this paper, we present and validate a recurrent neural network based model with 23 input features extracted from accelerometer and photoplethysmography sensors data for both healthy and sleep apnea populations. We designed a lightweight and fast solution to enable the prediction of sleep stages for each 30-s epoch. This solution was developed using a large dataset of 1522 night recordings collected from a highly heterogeneous population and different versions of Samsung smartwatch. RESULTS: In the classification of four sleep stages (wake, light, deep, and rapid eye movements sleep), the proposed solution achieved 71.6 % of balanced accuracy and a Cohen's kappa of 0.56 in a test set with 586 recordings. CONCLUSION: The results presented in this paper validate our proposal as a competitive wearable solution for sleep staging. Additionally, the use of a large and diverse data set contributes to the robustness of our solution, and corroborates the validation of algorithm's performance. Some additional analysis performed for healthy and sleep apnea population demonstrated that algorithm's performance has low correlation with demographic variables.

Defective hematopoietic differentiation of immune aplastic anemia patient-derived iPSCs.

In acquired immune aplastic anemia (AA), pathogenic cytotoxic Th1 cells are activated and expanded, driving an immune response against the hematopoietic stem and progenitor cells (HSPCs) that provokes cell depletion and causes bone marrow failure. However, additional HSPC defects may contribute to hematopoietic failure, reflecting on disease outcomes and response to immunosuppression. Here we derived induced pluripotent stem cells (iPSCs) from peripheral blood (PB) erythroblasts obtained from patients diagnosed with immune AA using non-integrating plasmids to model the disease. Erythroblasts were harvested after hematologic response to immunosuppression was achieved. Patients were screened for germline pathogenic variants in bone marrow failure-related genes and no variant was identified. Reprogramming was equally successful for erythroblasts collected from the three immune AA patients and the three healthy subjects. However, the hematopoietic differentiation potential of AA-iPSCs was significantly reduced both quantitatively and qualitatively as compared to healthy-iPSCs, reliably recapitulating disease: differentiation appeared to be more severely affected in cells from the two patients with partial response as compared to the one patient with complete response. Telomere elongation and the telomerase machinery were preserved during reprogramming and differentiation in all AA-iPSCs. Our results indicate that iPSCs are a reliable platform to model immune AA and recapitulate clinical phenotypes. We propose that the immune attack may cause specific epigenetic changes in the HSPCs that limit adequate proliferation and differentiation.

Integrated analytical workflow for chromatographic profiling and metabolite annotation of a cytotoxic Phorbas amaranthus extract.

Phorbas is a widely studied genus of marine sponge and produce structurally rich cytotoxic metabolites. Still, only few studies have assessed metabolites present in Brazilian species. To circumvent redundancy, in this work, we applied and herein report the use of a scouting liquid chromatographic system associate to the design of experiment produced by the DryLab® software to obtain a fast and efficient chromatographic separation of the active hexane fraction, further enabling untargeted high-resolution mass spectrometry (HRMS) data. To this end, a crude hydroalcoholic extract of the sponge Phorbas amaranthus collected in Brazilian coast was prepared and partitioned. The cytotoxicity of the crude extract and the fractions was evaluated using tumor cell culture models. Fragmentation pathways assembled from HRMS data allowed the annotation of 18 known Phorbas metabolites, while 17 metabolites were inferred based on Global Natural Product Social Molecular Networking (GNPS), matching with a further 29 metabolites annotated through molecular subnetwork. The workflow employed demonstrates that chromatographic method development can be accelerated by the use of automated scouting systems and DryLab®, which is useful for profiling natural product libraries, as well as data curation by molecular clusters and should be incorporated to the tools of natural product chemists.

Chemical Composition and In Vitro Cytotoxic and Antimicrobial Activities of the Essential Oil from Leaves of Zanthoxylum monogynum St. Hill (Rutaceae).

Background: The Zanthoxylum monogynum species belongs to the family Rutaceae and is found in Southeast, Midwest, and Northeast Brazil. For this genus several biological activities have been described. Methods: The essential oil (EO) was obtained from the leaves of Zanthoxylum monogynum by hydro-distillation and was analyzed by gas chromatograph and gas chromatograph/mass spectrometry (GC and GC/MS). Also the EO of Z. monogynum was evaluated for in vitro cytotoxic activity against six tumor cell lines and for antimicrobial activity, performing disk diffusion and MIC assays with yeast and bacterial strains. Results: The chemical analysis afforded the identification of 18 components (99.0% of the EO). The major components were found to be citronellol (43.0%) and farnesol (32.0%). The in vitro cytotoxic activity against tumor cell lines, resulted in IC50 values ranging from 11-65 µg/mL against all tested cell lines. Antimicrobial activity of the essential oil was also tested and oil was effective, especially against Cryptococcus sp. yeast. All the tested yeast strains showed at least 90% growth inhibition. Conclusions: the essential oil from leaves of Z. monogynum has a different qualitative and quantitative composition when compared to the composition previously described. Also this EO has significant cytotoxic activity and moderate activity against Cryptococcus sp. and Saccharomyces cereviseae yeasts.

The Brazilian developments on the Regional Atmospheric Modeling System (BRAMS 5.2): an integrated environmental model tuned for tropical areas.

We present a new version of the Brazilian developments on the Regional Atmospheric Modeling System where different previous versions for weather, chemistry and carbon cycle were unified in a single integrated software system. The new version also has a new set of state-of-the-art physical parameterizations and greater computational parallel and memory usage efficiency. Together with the description of the main features are examples of the quality of the transport scheme for scalars, radiative fluxes on surface and model simulation of rainfall systems over South America in different spatial resolutions using a scale-aware convective parameterization. Besides, the simulation of the diurnal cycle of the convection and carbon dioxide concentration over the Amazon Basin, as well as carbon dioxide fluxes from biogenic processes over a large portion of South America are shown. Atmospheric chemistry examples present model performance in simulating near-surface carbon monoxide and ozone in Amazon Basin and Rio de Janeiro megacity. For tracer transport and dispersion, it is demonstrated the model capabilities to simulate the volcanic ash 3-d redistribution associated with the eruption of a Chilean volcano. Then, the gain of computational efficiency is described with some details. BRAMS has been applied for research and operational forecasting mainly in South America. Model results from the operational weather forecast of BRAMS on 5 km grid spacing in the Center for Weather Forecasting and Climate Studies, INPE/Brazil, since 2013 are used to quantify the model skill of near surface variables and rainfall. The scores show the reliability of BRAMS for the tropical and subtropical areas of South America. Requirements for keeping this modeling system competitive regarding on its functionalities and skills are discussed. At last, we highlight the relevant contribution of this work on the building up of a South American community of model developers.