Search

Background: Echocardiography (echo) based machine learning (ML) models may be useful in identifying patients at high-risk of all-cause mortality., Methods: We developed ML models (ResNet deep learning using echo videos and CatBoost gradient boosting using echo measurements) to predict 1-year, 3-year, and 5-year mortality. Models were trained on the Mackay dataset, Taiwan (6083 echos, 3626 patients) and validated in the Alberta HEART dataset, Canada (997 echos, 595 patients). We examined the performance of the models overall, and in subgroups (healthy controls, at risk of heart failure (HF), HF with reduced ejection fraction (HFrEF) and HF with preserved ejection fraction (HFpEF)). We compared the models' performance to the MAGGIC risk score, and examined the correlation between the models' predicted probability of death and baseline quality of life as measured by the Kansas City Cardiomyopathy Questionnaire (KCCQ)., Findings: Mortality rates at 1-, 3- and 5-years were 14.9%, 28.6%, and 42.5% in the Mackay cohort, and 3.0%, 10.3%, and 18.7%, in the Alberta HEART cohort. The ResNet and CatBoost models achieved area under the receiver-operating curve (AUROC) between 85% and 92% in internal validation. In external validation, the AUROCs for the ResNet (82%, 82%, and 78%) were significantly better than CatBoost (78%, 73%, and 75%), for 1-, 3- and 5-year mortality prediction respectively, with better or comparable performance to the MAGGIC score. ResNet models predicted higher probability of death in the HFpEF and HFrEF (30%-50%) subgroups than in controls and at risk patients (5%-20%). The predicted probabilities of death correlated with KCCQ scores (all p < 0.05)., Interpretation: Echo-based ML models to predict mortality had good internal and external validity, were generalizable, correlated with patients' quality of life, and are comparable to an established HF risk score. These models can be leveraged for automated risk stratification at point-of-care., Funding: Funding for Alberta HEART was provided by an Alberta Innovates - Health Solutions Interdisciplinary Team Grant no. AHFMRITG 200801018. P.K. holds a Canadian Institutes of Health Research (CIHR) Sex and Gender Science Chair and a Heart & Stroke Foundation Chair in Cardiovascular Research. A.V. and V.S. received funding from the Mitacs Globalink Research Internship., Competing Interests: Declaration of interests J.T. reports consulting or speaker fees from Daiichi-Sankyo, Boehringer Ingelheim, Roche Diagnostics and Us2.ai, owns patent US-10702247-B2 unrelated to the present work. M.F., M.O. and C.E. report owning stock or stock options from Us2.ai. J.E. reports research grants from Bayer, Merck & Co, Novo Nordisk, Cytokinetics, Applied Therapeutics, American Regent, US2.ai, Canadian Institutes of Health Research, Heart and Stroke Foundation, Weston Foundation; consulting fees from AstraZeneca, Boehringer Ingelheim, Novo Nordisk, Otsuka, Bayer, Novartis; participation on a Data Safety Monitoring Board or Advisory Board for Cardiac Sarcoidosis Randomized Trial (CHASM-CS-RCT); leadership or fiduciary role in the Canadian Heart Failure Society. C-L.H. reports honoraria for lectures or presentations as a speaker with AstraZeneca, Boehringer Ingelheim, Sanofi and Bayer Pharma; participation in Advisory Board activity in AstraZeneca, Boehringer Ingelheim, Sanofi and Bayer Pharma. All other authors report no conflicts of interest., (Copyright © 2023 The Author(s). Published by Elsevier B.V. All rights reserved.)

Trypanosoma brucei and related parasites contain an unusual catenated mitochondrial genome known as kinetoplast DNA (kDNA) composed of maxicircles and minicircles. The kDNA structure and replication mechanism are divergent and essential for parasite survival. POLIB is one of three Family A DNA polymerases independently essential to maintain the kDNA network. However, the division of labor among the paralogs, particularly which might be a replicative, proofreading enzyme, remains enigmatic. De novo modeling of POLIB suggested a structure that is divergent from all other Family A polymerases, in which the thumb subdomain contains a 369 amino acid insertion with homology to DEDDh DnaQ family 3'-5' exonucleases. Here we demonstrate recombinant POLIB 3'-5' exonuclease prefers DNA vs RNA substrates and degrades single- and double-stranded DNA nonprocessively. Exonuclease activity prevails over polymerase activity on DNA substrates at pH 8.0, while DNA primer extension is favored at pH 6.0. Mutations that ablate POLIB polymerase activity slow the exonuclease rate suggesting crosstalk between the domains. We show that POLIB extends an RNA primer more efficiently than a DNA primer in the presence of dNTPs but does not incorporate rNTPs efficiently using either primer. Immunoprecipitation of Pol I-like paralogs from T. brucei corroborates the pH selectivity and RNA primer preferences of POLIB and revealed that the other paralogs efficiently extend a DNA primer. The enzymatic properties of POLIB suggest this paralog is not a replicative kDNA polymerase, and the noncanonical polymerase domain provides another example of exquisite diversity among DNA polymerases for specialized function.

This study compares a deep learning interpretation of 23 echocardiographic parameters-including cardiac volumes, ejection fraction, and Doppler measurements-with three repeated measurements by core lab sonographers. The primary outcome metric, the individual equivalence coefficient (IEC), compares the disagreement between deep learning and human readers relative to the disagreement among human readers. The pre-determined non-inferiority criterion is 0.25 for the upper bound of the 95% confidence interval. Among 602 anonymised echocardiographic studies from 600 people (421 with heart failure, 179 controls, 69% women), the point estimates of IEC are all <0 and the upper bound of the 95% confidence intervals below 0.25, indicating that the disagreement between the deep learning and human measures is lower than the disagreement among three core lab readers. These results highlight the potential of deep learning algorithms to improve efficiency and reduce the costs of echocardiography., (© 2022. The Author(s).)

PIONEER is a high Q-resolution, single-crystal, polarized neutron diffractometer at the Second Target Station (STS), Oak Ridge National Laboratory. It will provide the unprecedented capability of measuring tiny crystals (0.001 mm 3 , i.e., x-ray diffraction size), ultra-thin films (10 nm thickness), and weak structural and magnetic transitions. PIONEER benefits from the increased peak brightness of STS cold-neutron sources and uses advanced Montel mirrors that are able to deliver a focused beam with a high brilliance transfer, a homogeneous profile, and a low background. Monte Carlo simulations suggest that the optimized instrument has a high theoretical peak brilliance of 2.9 × 10 12 n cm -2 sr -1 Å -1 s -1 at 2.5 Å at the sample position, within a 5 × 5 mm 2 region and a ±0.3° divergence range. The moderator-to-sample distance is 60 m, providing a nominal wavelength band of 4.3 Å with a wavelength resolution better than 0.2% in the wavelength range of 1.0-6.0 Å. PIONEER is capable of characterizing large-scale periodic structures up to 200 Å. With a sample-to-detector distance of 0.8 m, PIONEER accommodates various sample environments, including low/high temperature, high pressure, and high magnetic/electric field. A large cylindrical detector array (4.0 sr) with a radial collimator is planned to suppress the background scattering from sample environments. Bottom detector banks provide an additional 0.4 sr coverage or can be removed if needed to accommodate special sample environments. We present virtual experimental results to demonstrate the scientific performance of PIONEER in measuring tiny samples.

To achieve chromium tolerance and high performance, a new series of high-entropy perovskites (HEPs) are investigated as cathode materials for solid oxide fuel cells (SOFCs). Multiple rare-earth, alkaline-earth, and high-order transition metal elements are used for the A-site of this ABO 3 structure. A pure phase is achieved through the designed combination of different elements in seven out of eight candidates. Due to the retaining of alkaline-earth elements Sr and/or Ba, the electrical conductivities of these HEPs are in the order of 100 S/cm at 550-700 °C, a value that can practically eliminate the electronic resistance of the porous cathode. Three out of eight candidates show similar or better performance than the (La 0.6 Sr 0.4 )(Co 0.2 Fe 0.8 )O 3-δ (LSCF) benchmark. It is found that A-site elements can cast a substantial influence on the overall performance even with a change as small as 10% of the total cations. It seems that each element has its individual "phenomenal activity" that can be transferred from one candidate to the other in the general setting of the perovskite structure, leading to the best candidate by using the three most active elements simultaneously at the A-site. Excellent Cr tolerance has been observed on the (La 0.2 Sr 0.2 Pr 0.2 Y 0.2 Ba 0.2 )Co 0.2 Fe 0.8 O 3-δ sample, showing degradation of only 0.25%/kh during a 41 day operation in the presence of Cr, while LSCF increases by 100% within the first day in the same condition. X-ray photoelectron spectroscopy discovers no Sr segregation as LSCF is found in this HEP; rather, the active element Y takes more A-sites on the outermost layer after long-term operation.

Strigolactones (SLs) are the most recently discovered phytohormones, and their roles in root architecture and metabolism are not fully understood. Here, we investigated four MORE AXILLARY GROWTH (MAX) SL mutants in Arabidopsis thaliana, max3-9, max4-1, max1-1 and max2-1, as well as the SL receptor mutant d14-1 and karrikin receptor mutant kai2-2. By characterising max2-1 and max4-1, we found that variation in SL biosynthesis modified multiple metabolic pathways in root tissue, including that of xyloglucan, triterpenoids, fatty acids and flavonoids. The transcription of key flavonoid biosynthetic genes, including TRANSPARENT TESTA4 (TT4) and TRANSPARENT TESTA5 (TT5) was downregulated in max2 roots and seedlings, indicating that the proposed MAX2 regulation of flavonoid biosynthesis has a widespread effect. We found an enrichment of BRI1-EMS-SUPPRESSOR 1 (BES1) targets amongst genes specifically altered in the max2 mutant, reflecting that the regulation of flavonoid biosynthesis likely occurs through the MAX2 degradation of BES1, a key brassinosteroid-related transcription factor. Finally, flavonoid accumulation decreased in max2-1 roots, supporting a role for MAX2 in regulating both SL and flavonoid biosynthesis., (© 2022 The Authors. Physiologia Plantarum published by John Wiley & Sons Ltd on behalf of Scandinavian Plant Physiology Society.)

Background: Echocardiography is the diagnostic modality for assessing cardiac systolic and diastolic function to diagnose and manage heart failure. However, manual interpretation of echocardiograms can be time consuming and subject to human error. Therefore, we developed a fully automated deep learning workflow to classify, segment, and annotate two-dimensional (2D) videos and Doppler modalities in echocardiograms., Methods: We developed the workflow using a training dataset of 1145 echocardiograms and an internal test set of 406 echocardiograms from the prospective heart failure research platform (Asian Network for Translational Research and Cardiovascular Trials; ATTRaCT) in Asia, with previous manual tracings by expert sonographers. We validated the workflow against manual measurements in a curated dataset from Canada (Alberta Heart Failure Etiology and Analysis Research Team; HEART; n=1029 echocardiograms), a real-world dataset from Taiwan (n=31 241), the US-based EchoNet-Dynamic dataset (n=10 030), and in an independent prospective assessment of the Asian (ATTRaCT) and Canadian (Alberta HEART) datasets (n=142) with repeated independent measurements by two expert sonographers., Findings: In the ATTRaCT test set, the automated workflow classified 2D videos and Doppler modalities with accuracies (number of correct predictions divided by the total number of predictions) ranging from 0·91 to 0·99. Segmentations of the left ventricle and left atrium were accurate, with a mean Dice similarity coefficient greater than 93% for all. In the external datasets (n=1029 to 10 030 echocardiograms used as input), automated measurements showed good agreement with locally measured values, with a mean absolute error range of 9-25 mL for left ventricular volumes, 6-10% for left ventricular ejection fraction (LVEF), and 1·8-2·2 for the ratio of the mitral inflow E wave to the tissue Doppler e' wave (E/e' ratio); and reliably classified systolic dysfunction (LVEF <40%, area under the receiver operating characteristic curve [AUC] range 0·90-0·92) and diastolic dysfunction (E/e' ratio ≥13, AUC range 0·91-0·91), with narrow 95% CIs for AUC values. Independent prospective evaluation confirmed less variance of automated compared with human expert measurements, with all individual equivalence coefficients being less than 0 for all measurements., Interpretation: Deep learning algorithms can automatically annotate 2D videos and Doppler modalities with similar accuracy to manual measurements by expert sonographers. Use of an automated workflow might accelerate access, improve quality, and reduce costs in diagnosing and managing heart failure globally., Funding: A*STAR Biomedical Research Council and A*STAR Exploit Technologies., Competing Interests: Declaration of interests JT is supported by a National University of Singapore Startup Grant and has received personal grants and speaker fees from Olink Proteomics, Roche Diagnostics, Daiichi Sankyo, and Us2.ai. CSPL is supported by a Clinician Scientist Award from the National Medical Research Council of Singapore; has received research support from Boston Scientific, Bayer, Roche Diagnostics, AstraZeneca, Medtronic, and Vifor Pharma; has served as consultant or on the advisory board, steering committee, or executive committee for Boston Scientific, Bayer, Roche Diagnostics, AstraZeneca, Medtronic, Vifor Pharma, Novartis, Amgen, Merck, Janssen Research & Development, Menarini, Boehringer Ingelheim, Novo Nordisk, Abbott Diagnostics, Corvia, Stealth BioTherapeutics, JanaCare, Biofourmis, Darma, Applied Therapeutics, MyoKardia, Cytokinetics, WebMD Global, Radcliffe Group, and Corpus; and is co-founder and non-executive director of Us2.ai. MBI, MJF, and ZJ are employees of Us2.ai and hold equity in the company. PJS was an employee of Us2.ai and held equity in the company during the study. JT, PJS, WO, and CSPL own a patent entitled “Automatic clinical workflow that recognises and analyses 2D and doppler modality echocardiogram images for automated cardiac measurements and the diagnosis, prediction and prognosis of heart disease” related to the present work. JT, WO, and JAE are scientific advisors of Us2.ai and hold equity in the company. AMR is supported by a Senior Translational Research award from the National Medical Research Council of Singapore; holds the New Zealand Heart Foundation Chair of Cardiovascular Studies; has received research support from Boston Scientific, Bayer, AstraZeneca, Medtronic, Roche Diagnostics, Abbott Laboratories, Thermo Fisher Scientific, and Critical Diagnostics; and has consulted for Bayer, Novartis, Merck, AstraZeneca, and Roche Diagnostics. SDS reports grants from Actelion, Alnylam, Amgen, AstraZeneca, Bellerophon, Bayer, Bristol Myers Squibb, Celladon, Cytokinetics, Eidos, Gilead Sciences, GlaxoSmithKline, Ionis Pharmaceuticals, LoneStar Heart, Mesoblast, MyoKardia, NeuroTronik, NHLBI, Novartis, Novo Nordisk, Respicardia, Sanofi Pasteur, and Theracos; and personal fees from Abbott, Actelion, Akros, Alnylam Pharmaceuticals, Amgen, Arena, AstraZeneca, Bayer, Boehringer Ingelheim, Bristol Myers Squibb, Cardior Pharmaceuticals, Cardurion Pharmaceuticals, Corvia Medical, Cytokinetics, Daiichi Sankyo, Gilead Sciences, GlaxoSmithKline, Ironwood Pharmaceuticals, Eli Lilly, Merck, MyoKardia, Novartis, Roche, Takeda, Theracos, Quantum Genetics, Cardurion Pharmaceuticals, AOBiome, Janssen, Cardiac Dimensions, Sanofi Pasteur, Tenaya, DiNAQOR, Tremeau Pharmaceuticals, CellProthera, and Moderna. All other authors declare no competing interests., (Copyright © 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY-NC-ND 4.0 license. Published by Elsevier Ltd.. All rights reserved.)

Engineering neutron diffraction can nondestructively and noninvasively probe stress, strain, temperature, and phase evolutions deep within bulk materials. In this work, we demonstrate operando lattice strain measurement of internal combustion engine components by neutron diffraction. A modified commercial generator engine was mounted in the VULCAN diffractometer at the Spallation Neutron Source, and the lattice strains in both the cylinder block and head were measured under static nonfiring conditions as well as steady state and cyclic transient operation. The dynamic temporal response of the lattice strain change during transient operation was resolved in two locations by asynchronous stroboscopic neutron diffraction. We demonstrated that operando neutron measurements can allow for understanding of how materials behave throughout operational engineering devices. This study opens a pathway for the industrial and academic communities to better understand the complexities of material behavior during the operation of internal combustion engines and other real-scale devices and systems and to leverage techniques developed here for future investigations of numerous new platforms and alloys., Competing Interests: The authors declare no competing interest., (Copyright © 2020 the Author(s). Published by PNAS.)

Excess production of nitric oxide (NO) is implicated in the development of multiple organ failure, with a putative mechanism involving direct mitochondrial inhibition, predominantly affecting complex I. The persistent effects of NO on complex I may be mediated through S-nitrosylation and/or nitration. The temporal contribution of these chemical modifications to the inhibition of respiration and the influence of concurrent hypoxia have not been previously examined. We therefore addressed these questions using J774 macrophages activated by endotoxin and interferon-gamma over a 24-h period, incubated at 21% and 1% oxygen. Oxygen consumption and complex I activity fell progressively over time in the activated cells. This was largely prevented by coincubation with the nonspecific NO synthase inhibitor L-N5-(1-iminoethyl)-ornithine. Addition of glutathione ethyl ester reversed the inhibition at initial time points, suggesting an early mechanism involving nitrosylation. Thereafter, the inhibition of complex I became more persistent, coinciding with a progressive increase in mitochondrial nitration. Hypoxia accelerated the persistent inhibition of complex I, despite a reduction in the total amount of NO generated. Our results suggest that hypoxia amplified the mitochondrial inhibition induced by NO generated during inflammatory disease states.