Atrial fibrillation (AF) is associated with substantial morbidity, especially when it goes undetected. If new-onset AF could be predicted, targeted screening could be used to find it early. We ...hypothesized that a deep neural network could predict new-onset AF from the resting 12-lead ECG and that this prediction may help identify those at risk of AF-related stroke.
We used 1.6 M resting 12-lead digital ECG traces from 430 000 patients collected from 1984 to 2019. Deep neural networks were trained to predict new-onset AF (within 1 year) in patients without a history of AF. Performance was evaluated using areas under the receiver operating characteristic curve and precision-recall curve. We performed an incidence-free survival analysis for a period of 30 years following the ECG stratified by model predictions. To simulate real-world deployment, we trained a separate model using all ECGs before 2010 and evaluated model performance on a test set of ECGs from 2010 through 2014 that were linked to our stroke registry. We identified the patients at risk for AF-related stroke among those predicted to be high risk for AF by the model at different prediction thresholds.
The area under the receiver operating characteristic curve and area under the precision-recall curve were 0.85 and 0.22, respectively, for predicting new-onset AF within 1 year of an ECG. The hazard ratio for the predicted high- versus low-risk groups over a 30-year span was 7.2 (95% CI, 6.9-7.6). In a simulated deployment scenario, the model predicted new-onset AF at 1 year with a sensitivity of 69% and specificity of 81%. The number needed to screen to find 1 new case of AF was 9. This model predicted patients at high risk for new-onset AF in 62% of all patients who experienced an AF-related stroke within 3 years of the index ECG.
Deep learning can predict new-onset AF from the 12-lead ECG in patients with no previous history of AF. This prediction may help identify patients at risk for AF-related strokes.
Nearly two hundred common-variant depression risk loci have been identified by genome-wide association studies (GWAS). However, the impact of rare coding variants on depression remains poorly ...understood. Here, we present whole-exome sequencing analyses of depression with seven different definitions based on survey, questionnaire, and electronic health records in 320,356 UK Biobank participants. We showed that the burden of rare damaging coding variants in loss-of-function intolerant genes is significantly associated with risk of depression with various definitions. We compared the rare and common genetic architecture across depression definitions by genetic correlation and showed different genetic relationships between definitions across common and rare variants. In addition, we demonstrated that the effects of rare damaging coding variant burden and polygenic risk score on depression risk are additive. The gene set burden analyses revealed overlapping rare genetic variant components with developmental disorder, autism, and schizophrenia. Our study provides insights into the contribution of rare coding variants, separately and in conjunction with common variants, on depression with various definitions and their genetic relationships with neurodevelopmental disorders.
Currently, cellulose nanostructures (CNS) are obtained using pretreatments of lignocellulosic residues. In this work, different conditions in the enzymatic isolation process were studied to obtain ...CNS, aiming an alternative eco-friendly method. Two isolation methodologies were used: a) one submitting the residue to an alkaline pretreatment and b) other using the lignocellulosic waste directly without pretreatment. A commercial complex of enzymes (Ctec®) was used, varying the time to which the substrate was exposed to the enzymes at 12, 24 and 48 h, searching for the better condition to CNS obtaining. The application of alkaline pretreatment removed 73% of hemicellulose and 50% of lignin from wood fiber leading to a more exposed cellulose structure and increased the amount of nanocellulose produced. The obtained nanostructures were needle-shaped of approximately 70 nm wide. However, CNS of similar size and shape were received as well without pretreatment application, allowing their obtainment with lower reagent consumption through a more environmentally efficient route, as presented in the life cycle impact assessment (LCIA) where energy consumption and acidification potential were considered.
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•Cellulosic nanostructures were obtained by enzymatic hydrolysis without pretreatment.•Time of reaction affects only the yield, not the mean size of the structures.•Needle-like structures with higher crystallinity were obtained without pretreatment.•Pretreatment surpassing reduced the impacts represented in the LCIA.
Eucalyptus sawdust was used for nano and microfibers preparation by a “green” process (ball milling), followed by surface treatments (alkaline and surfactant) and incorporated in PLA, from 1 to 10 wt ...%, aiming for the preparation of films of biocomposites. The treatments applied exposed the polar groups due to lignin removal or by the surfactant adsorption, respectively. The modification intensified the interaction in the interface region between the fibers and the PLA matrix (SEM), maintaining thermal properties (DSC results). The fibers treatments contributed to the films hydrophobicity concerning the humid environments, as evidenced by the results of moisture absorption and contact angle. However, the decrease in the crystallinity index of the biocomposites (4.2%, obtained by DSC) contributed to the increase of the water molecules diffusion (D, water absorption) caused by the structure disorder, which may favor the post-use biodegradation process. The mechanical properties of the films were promising, presenting values always above the PLA property. In general, the results suggest that the incorporation of eucalyptus fibers, mainly detergent treated, improves not only the mechanical properties of PLA but also favors properties that enhance the biodegradation process of the post-use biocomposites.
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•Eucalyptus nano and microfibers (EMs) obtained by a “green” process, ball milling.•Treatments were used to improve the surface of the EMs.•Evaluation of the EMs incorporated into the PLA matrix, biocomposites.•EMs isolated and their BC films showed excellent performance.
Background: Timely diagnosis of structural heart disease improves patient outcomes, yet many remain underdiagnosed. While population screening with echocardiography is impractical, ECG-based ...prediction models can help target high-risk patients. We developed a novel ECG-based machine learning approach to predict multiple structural heart conditions, hypothesizing that a composite model would yield higher prevalence and positive predictive values to facilitate meaningful recommendations for echocardiography. Methods: Using 2 232 130 ECGs linked to electronic health records and echocardiography reports from 484 765 adults between 1984 to 2021, we trained machine learning models to predict the presence or absence of any of 7 echocardiography-confirmed diseases within 1 year. This composite label included the following: moderate or severe valvular disease (aortic/mitral stenosis or regurgitation, tricuspid regurgitation), reduced ejection fraction <50%, or interventricular septal thickness >15 mm. We tested various combinations of input features (demographics, laboratory values, structured ECG data, ECG traces) and evaluated model performance using 5-fold cross-validation, multisite validation trained on 1 site and tested on 10 independent sites, and simulated retrospective deployment trained on pre-2010 data and deployed in 2010. Results: Our composite rECHOmmend model used age, sex, and ECG traces and had a 0.91 area under the receiver operating characteristic curve and a 42% positive predictive value at 90% sensitivity, with a composite label prevalence of 17.9%. Individual disease models had area under the receiver operating characteristic curves from 0.86 to 0.93 and lower positive predictive values from 1% to 31%. Area under the receiver operating characteristic curves for models using different input features ranged from 0.80 to 0.93, increasing with additional features. Multisite validation showed similar results to cross-validation, with an aggregate area under the receiver operating characteristic curve of 0.91 across our independent test set of 10 clinical sites after training on a separate site. Our simulated retrospective deployment showed that for ECGs acquired in patients without preexisting structural heart disease in the year 2010, 11% were classified as high risk and 41% (4.5% of total patients) developed true echocardiography-confirmed disease within 1 year. Conclusions: An ECG-based machine learning model using a composite end point can identify a high-risk population for having undiagnosed, clinically significant structural heart disease while outperforming single-disease models and improving practical utility with higher positive predictive values. This approach can facilitate targeted screening with echocardiography to improve underdiagnosis of structural heart disease.
New effective compounds for tuberculosis treatment are needed. This study evaluated the effects of a series of quinoxaline-derived chalcones against laboratorial strains and clinical isolates of M. ...tuberculosis. Six molecules, namely N5, N9, N10, N15, N16, and N23 inhibited the growth of the M. tuberculosis H37Rv laboratorial strain. The three compounds (N9, N15 and N23) with the lowest MIC values were further tested against clinical isolates and laboratory strains with mutations in katG or inhA genes. From these data, N9 was selected as the lead compound for further investigation. Importantly, this chalcone displayed a synergistic effect when combined with moxifloxacin. Noteworthy, the anti-tubercular effects of N9 did not rely on inhibition of mycolic acids synthesis, circumventing important mechanisms of resistance. Interactions with cytochrome P450 isoforms and toxic effects were assessed in silico and in vitro. The chalcone N9 was not predicted to elicit any mutagenic, genotoxic, irritant, or reproductive effects, according to in silico analysis. Additionally, N9 did not cause mutagenicity or genotoxicity, as revealed by Salmonella/microsome and alkaline comet assays, respectively. Moreover, N9 did not inhibit the cytochrome P450 isoforms CYP3A4/5, CYP2C9, and CYP2C19. N9 can be considered a potential lead molecule for development of a new anti-tubercular therapeutic agent.
Objective: Treatment-resistant depression (TRD) occurs in roughly one-third of all individuals with major depressive disorder (MDD). Although research has suggested a significant common variant ...genetic component of liability to TRD, with heritability estimated at 8% when compared with non-treatment-resistant MDD, no replicated genetic loci have been identified, and the genetic architecture of TRD remains unclear. A key barrier to this work has been the paucity of adequately powered cohorts for investigation, largely because of the challenge in prospectively investigating this phenotype. The objective of this study was to perform a well-powered genetic study of TRD. Methods: Using receipt of electroconvulsive therapy (ECT) as a surrogate for TRD, the authors applied standard machine learning methods to electronic health record data to derive predicted probabilities of receiving ECT. These probabilities were then applied as a quantitative trait in a genome-wide association study of 154,433 genotyped patients across four large biobanks. Results: Heritability estimates ranged from 2% to 4.2%, and significant genetic overlap was observed with cognition, attention deficit hyperactivity disorder, schizophrenia, alcohol and smoking traits, and body mass index. Two genome-wide significant loci were identified, both previously implicated in metabolic traits, suggesting shared biology and potential pharmacological implications. Conclusions: This work provides support for the utility of estimation of disease probability for genomic investigation and provides insights into the genetic architecture and biology of TRD.
The Amazon endemic quillwort
Isoëtes cangae
is a critically endangered submerged plant found exclusively at the Lake Amendoim, at iron rock fields in Serra dos Carajás, Eastern Brazilian Amazon. Lake ...Amendoim is an oligotrophic lake with high iron content and rocky to organic-clay sediment. Another aquatic ecosystem in the vicinity, Lake Três Irmãs-3, was evaluated for its limnological characteristics and the ecophysiological markers to assess whether this ecosystem is suitable for the translocation and conservation of
I. cangae
. Over the course of 2 years, underwater light spectra and water physicochemical characteristics were determined at both sites during dry and rainy periods. In addition, the chlorophyll a fluorescence of
I. cangae
was measured using Pulse-Amplitude Modulated fluorometry. Our findings reveal that the limnological dynamics of both lakes are very similar, and differences in limnological conditions between time periods were restricted to a few variables associated with climatic regime shifts (such as temperature, turbidity and total solids). We also identified that
I. cangae
can maintain its photosynthetic performance and reproduced in the Lake Três Irmãs-3. Our findings suggest that Lake Três Irmãs-3 is a suitable candidate ecosystem for
I. cangae
conservation due to the high limnological similarity between the studied lakes and the ecophysiological results.
Fire at the dry southern margin of the Amazon rainforest could have major consequences for regional soil carbon (C) storage and ecosystem carbon dioxide (CO2) emissions, but relatively little ...information exists about impacts of fire on soil C cycling within this sensitive ecotone. We measured CO2 effluxes from different soil components (ground surface litter, roots, mycorrhizae, soil organic matter) at a large‐scale burn experiment designed to simulate a severe but realistic potential future scenario for the region (Fire plot) in Mato Grosso, Brazil, over 1 year, and compared these measurements to replicated data from a nearby, unmodified Control plot. After four burns over 5 years, soil CO2 efflux (Rs) was ~5.5 t C ha−1 year−1 lower on the Fire plot compared to the Control. Most of the Fire plot Rs reduction was specifically due to lower ground surface litter and root respiration. Mycorrhizal respiration on both plots was around ~20% of Rs. Soil surface temperature appeared to be more important than moisture as a driver of seasonal patterns in Rs at the site. Regular fire events decreased the seasonality of Rs at the study site, due to apparent differences in environmental sensitivities among biotic and abiotic soil components. These findings may contribute toward improved predictions of the amount and temporal pattern of C emissions across the large areas of tropical forest facing increasing fire disturbances associated with climate change and human activities.
An Experimental fire set at the Tanguro forest site (pictures above) and an example of the soil respiration data collected from the experiment (picture below).
This study evaluated the chemical composition and antioxidant activity of fatty acids from the marine red algae Pterocladiella capillacea (S. G. Gmelin) Santelices & Hommersand 1997 and Osmundaria ...obtusiloba (C. Agardh) R. E. Norris 1991. The gas chromatography mass spectrometry (GC-MS) identified nine fatty acids in the two species. The major fatty acids of P. capillacea and O. obtusiloba were palmitic acid, oleic acid, arachidonic acid and eicosapentaenoic acid. The DPPH radical scavenging capacity of fatty acids was moderate ranging from 25.90% to 29.97%. Fatty acids from P. capillacea (31.18%) had a moderate ferrous ions chelating activity (FIC), while in O. obtusiloba (17.17%), was weak. The ferric reducing antioxidant power (FRAP) of fatty acids from P. capillacea and O. obtusiloba was low. As for β-carotene bleaching (BCB), P. capillacea and O. obtusiloba showed a good activity. This is the first report of the antioxidant activities of fatty acids from the marine red algae P. capillacea and O. obtusiloba.
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