| 1. |
- Lima, Emilly M., et al.
(författare)
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Deep neural network-estimated electrocardiographic age as a mortality predictor
- 2021
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Ingår i: Nature Communications. - : Springer Nature. - 2041-1723. ; 12:1
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Tidskriftsartikel (refereegranskat)abstract
- The electrocardiogram (ECG) is the most commonly used exam for the screening and evaluation of cardiovascular diseases. Here, the authors propose that the age predicted by artificial intelligence from the raw ECG tracing can be a measure of cardiovascular health and provide prognostic information. The electrocardiogram (ECG) is the most commonly used exam for the evaluation of cardiovascular diseases. Here we propose that the age predicted by artificial intelligence (AI) from the raw ECG (ECG-age) can be a measure of cardiovascular health. A deep neural network is trained to predict a patient's age from the 12-lead ECG in the CODE study cohort (n = 1,558,415 patients). On a 15% hold-out split, patients with ECG-age more than 8 years greater than the chronological age have a higher mortality rate (hazard ratio (HR) 1.79, p < 0.001), whereas those with ECG-age more than 8 years smaller, have a lower mortality rate (HR 0.78, p < 0.001). Similar results are obtained in the external cohorts ELSA-Brasil (n = 14,236) and SaMi-Trop (n = 1,631). Moreover, even for apparent normal ECGs, the predicted ECG-age gap from the chronological age remains a statistically significant risk predictor. These results show that the AI-enabled analysis of the ECG can add prognostic information.
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| 2. |
- Henriques, M. S. C., et al.
(författare)
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Columnar Formation in Sodium Triphenylacetate
- 2014
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Ingår i: Journal of Chemical Crystallography. - : Springer Science and Business Media LLC. - 1074-1542 .- 1572-8854. ; 44:11-12, s. 543-547
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Tidskriftsartikel (refereegranskat)abstract
- A new sodium salt, sodium triphenylacetate has been synthesized and characterized by single-crystal X-ray diffraction: triclinic, P-1 with a = 8.3846(2) angstrom, b = 13.5992(3) angstrom, c = 15.5288(3) angstrom, a = 76.7270(11)degrees, b = 74.4500(11)degrees, c = 84.7410(13)degrees, M-W = 656.65, V = 1659.42(6) angstrom(3), Z = 2. The triphenylacetic molecules bridge the metallic ions forming an infinite columnar structure. Calorimetric data does not support the existence of a mesophase induced by temperature.
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| 3. |
- Paixão, Gabriela M. M., et al.
(författare)
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Electrocardiographic Predictors of Mortality: Data from a Primary Care Tele-Electrocardiography Cohort of Brazilian Patients
- 2021
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Ingår i: Hearts. - : MDPI AG. - 2673-3846. ; 2:4, s. 449-458
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Tidskriftsartikel (refereegranskat)abstract
- Computerized electrocardiography (ECG) has been widely used and allows linkage to electronic medical records. The present study describes the development and clinical applications of an electronic cohort derived from a digital ECG database obtained by the Telehealth Network of Minas Gerais, Brazil, for the period 2010–2017, linked to the mortality data from the national information system, the Clinical Outcomes in Digital Electrocardiography (CODE) dataset. From 2,470,424 ECGs, 1,773,689 patients were identified. A total of 1,666,778 (94%) underwent a valid ECG recording for the period 2010 to 2017, with 1,558,421 patients over 16 years old; 40.2% were men, with a mean age of 51.7 [SD 17.6] years. During a mean follow-up of 3.7 years, the mortality rate was 3.3%. ECG abnormalities assessed were: atrial fibrillation (AF), right bundle branch block (RBBB), left bundle branch block (LBBB), atrioventricular block (AVB), and ventricular pre-excitation. Most ECG abnormalities (AF: Hazard ratio [HR] 2.10; 95% CI 2.03–2.17; RBBB: HR 1.32; 95%CI 1.27–1.36; LBBB: HR 1.69; 95% CI 1.62–1.76; first degree AVB: Relative survival [RS]: 0.76; 95% CI0.71–0.81; 2:1 AVB: RS 0.21 95% CI0.09–0.52; and RS 0.36; third degree AVB: 95% CI 0.26–0.49) were predictors of overall mortality, except for ventricular pre-excitation (HR 1.41; 95% CI 0.56–3.57) and Mobitz I AVB (RS 0.65; 95% CI 0.34–1.24). In conclusion, a large ECG database established by a telehealth network can be a useful tool for facilitating new advances in the fields of digital electrocardiography, clinical cardiology and cardiovascular epidemiology.
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| 4. |
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| 5. |
- Dima, B., et al.
(författare)
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Fungal Systematics and Evolution: FUSE 7
- 2021
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Ingår i: Sydowia. - 0082-0598. ; 73, s. 271-340
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Tidskriftsartikel (refereegranskat)abstract
- In this 7th contribution to the Fungal Systematics and Evolution series published by Sydowia, the authors formally describe 14 species: Cantharomyces paschalis, Cryptandromyces pinguis, C. tricornis, Laboulbenia amblystomi (Laboulbeniales); Cortinarius squamosus, Entoloma brunneicoeruleum, E. callipygmaeum, E. minutigranulosum, E. perasprellum, E. pulchripes, E. tigrinum, E. timidum, E. violaceoserrulatum (Agaricales); and Suillus quercinus (Boletales). The following new country records are reported: Crepidotus malachioides from Italy, Leucoagaricus mucrocystis from French Guiana, Pluteus multiformis from Turkey (Agaricales); Herpomyces periplanetae from Benin, the D.R. Congo, and Togo (Herpomycetales); Melanustilospora ari from Pakistan (Urocystidales); Neopestalotiopsis clavispora causing fruit rot on Zizyphus mauritiana from India (Amphisphaeriales); and Phytopythium chamaehyphon and Pp. litorale from Brazil (Peronosporales). Finally, a new combination is proposed based on morphology, ecology, and phylogenetic analysis: Rhodocollybia asema (Agaricales).
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| 6. |
- Ribeiro, Antônio H., et al.
(författare)
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Automatic diagnosis of the 12-lead ECG using a deep neural network
- 2020
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Ingår i: Nature Communications. - : NATURE PUBLISHING GROUP. - 2041-1723. ; 11:1
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Tidskriftsartikel (refereegranskat)abstract
- The role of automatic electrocardiogram (ECG) analysis in clinical practice is limited by the accuracy of existing models. Deep Neural Networks (DNNs) are models composed of stacked transformations that learn tasks by examples. This technology has recently achieved striking success in a variety of task and there are great expectations on how it might improve clinical practice. Here we present a DNN model trained in a dataset with more than 2 million labeled exams analyzed by the Telehealth Network of Minas Gerais and collected under the scope of the CODE (Clinical Outcomes in Digital Electrocardiology) study. The DNN outperform cardiology resident medical doctors in recognizing 6 types of abnormalities in 12-lead ECG recordings, with F1 scores above 80% and specificity over 99%. These results indicate ECG analysis based on DNNs, previously studied in a single-lead setup, generalizes well to 12-lead exams, taking the technology closer to the standard clinical practice. The role of automatic electrocardiogram (ECG) analysis in clinical practice is limited by the accuracy of existing models. In that context, the authors present a Deep Neural Network (DNN) that recognizes different abnormalities in ECG recordings which matches or outperform cardiology and emergency resident medical doctors.
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| 7. |
- Rizzo, L. V., et al.
(författare)
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Long term measurements of aerosol optical properties at a primary forest site in Amazonia
- 2013
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Ingår i: Atmospheric Chemistry and Physics. - : Copernicus GmbH. - 1680-7324. ; 13:5, s. 2391-2413
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Tidskriftsartikel (refereegranskat)abstract
- A long term experiment was conducted in a primary forest area in Amazonia, with continuous in-situ measurements of aerosol optical properties between February 2008 and April 2011, comprising, to our knowledge, the longest database ever in the Amazon Basin. Two major classes of aerosol particles, with significantly different optical properties were identified: coarse mode predominant biogenic aerosols in the wet season (January-June), naturally released by the forest metabolism, and fine mode dominated biomass burning aerosols in the dry season (July-December), transported from regional fires. Dry particle median scattering coefficients at the wavelength of 550 nm increased from 6.3 Mm(-1) to 22 Mm(-1), whereas absorption at 637 nm increased from 0.5 Mm(-1) to 2.8 Mm(-1) from wet to dry season. Most of the scattering in the dry season was attributed to the predominance of fine mode (PM2) particles (40-80% of PM10 mass), while the enhanced absorption coefficients are attributed to the presence of light absorbing aerosols from biomass burning. As both scattering and absorption increased in the dry season, the single scattering albedo (SSA) did not show a significant seasonal variability, in average 0.86 +/- 0.08 at 637 nm for dry aerosols. Measured particle optical properties were used to estimate the aerosol forcing efficiency at the top of the atmosphere. Results indicate that in this primary forest site the radiative balance was dominated by the cloud cover, particularly in the wet season. Due to the high cloud fractions, the aerosol forcing efficiency absolute values were below -3.5 Wm(-2) in 70% of the wet season days and in 46% of the dry season days. Besides the seasonal variation, the influence of out-of-Basin aerosol sources was observed occasionally. Periods of influence of the Manaus urban plume were detected, characterized by a consistent increase on particle scattering (factor 2.5) and absorption coefficients (factor 5). Episodes of biomass burning and mineral dust particles advected from Africa were observed between January and April, characterized by enhanced concentrations of crustal elements (Al, Si, Ti, Fe) and potassium in the fine mode. During these episodes, median particle absorption coefficients increased by a factor of 2, whereas median SSA values decreased by 7 %, in comparison to wet season conditions.
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| 8. |
- Hens, Bart, et al.
(författare)
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Formulation predictive dissolution (fPD) testing to advance oral drug product development : An introduction to the US FDA funded '21st Century BA/BE' project
- 2018
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Ingår i: International Journal of Pharmaceutics. - : Elsevier. - 0378-5173 .- 1873-3476. ; 548:1, s. 120-127
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Forskningsöversikt (refereegranskat)abstract
- Over the past decade, formulation predictive dissolution (fPD) testing has gained increasing attention. Another mindset is pushed forward where scientists in our field are more confident to explore the in vivo behavior of an oral drug product by performing predictive in vitro dissolution studies. Similarly, there is an increasing interest in the application of modern computational fluid dynamics (CFD) frameworks and high-performance computing platforms to study the local processes underlying absorption within the gastrointestinal (GI) tract. In that way, CFD and computing platforms both can inform future PBPK-based in silico frameworks and determine the GI-motility-driven hydrodynamic impacts that should be incorporated into in vitro dissolution methods for in vivo relevance. Current compendial dissolution methods are not always reliable to predict the in vivo behavior, especially not for biopharmaceutics classification system (BCS) class 2/4 compounds suffering from a low aqueous solubility. Developing a predictive dissolution test will be more reliable, cost-effective and less time-consuming as long as the predictive power of the test is sufficiently strong. There is a need to develop a biorelevant, predictive dissolution method that can be applied by pharmaceutical drug companies to facilitate marketing access for generic and novel drug products. In 2014, Prof. Gordon L. Amidon and his team initiated a far-ranging research program designed to integrate (1) in vivo studies in humans in order to further improve the understanding of the intraluminal processing of oral dosage forms and dissolved drug along the gastrointestinal (GI) tract, (2) advancement of in vitro methodologies that incorporates higher levels of in vivo relevance and (3) computational experiments to study the local processes underlying dissolution, transport and absorption within the intestines performed with a new unique CFD based framework. Of particular importance is revealing the physiological variables determining the variability in in vivo dissolution and GI absorption from person to person in order to address (potential) in vivo BE failures. This paper provides an introduction to this multidisciplinary project, informs the reader about current achievements and outlines future directions.
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| 9. |
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| 10. |
- Osaku, Erica F., et al.
(författare)
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beta-(1 -> 6)-d-glucan secreted during the optimised production of exopolysaccharides by Paecilomyces variotii has immunostimulatory activity
- 2018
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Ingår i: Antonie van Leeuwenhoek. International Journal of General and Molecular Microbiology. - : Springer. - 0003-6072 .- 1572-9699. ; 111:6, s. 981-994
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Tidskriftsartikel (refereegranskat)abstract
- Paecilomyces variotii is a filamentous fungus that occurs worldwide in soil and decaying vegetation. Optimization of the fermentation process for exopolysaccharide (EPS) production from the fungus P. variotii, structure determination and immuno-stimulating activity of EPS were performed. Response surface methodology (RSM) coupled with central composite design (CCD) was used to optimize the physical and chemical factors required to produce EPS in submerged fermentation. Preliminary investigations to choose the three factors for the present work were made using a factorial experimental design. Glucose, ammonium nitrate (NH4NO3) and pH were used as variables for which, with constant temperature of 28 A degrees C and agitation of 90 rpm, the optimal process parameters were determined as glucose values of 0.96%, NH4NO3 0.26% and pH 8.0. The three parameters presented significant effects. In this condition of culture, the main composition of the isolated EPS was a linear beta-(1 -> 6)-linked-D-glucan, as determined by Nuclear Magnetic Resonance (NMR) and methylation analysis. This polysaccharide is a very unusual as an EPS from fungi, especially a filamentous fungus such as P. variotii. Murine peritoneal macrophages cultivated with beta-glucan for 6 and 48 h showed an increase in TNF-alpha, IL-6 and nitric oxide release with increased polysaccharide concentrations. Therefore, we conclude that the beta-(1 -> 6)-linked-D-glucan produced in optimised conditions of P. variotii cultivation has an immune-stimulatory activity on murine macrophages.
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