Nfe2l3 promotes neuroprotection and long-distance axon regeneration after injury in vivo.

Nuclear factor erythroid 2 like (Nfe2l) gene family members 1-3 mediate cellular response to oxidative stress, including in the central nervous system (CNS). However, neuronal functions of Nfe2l3 are unknown. Here, we comparatively evaluated expression of Nfe2l1, Nfe2l2, and Nfe2l3 in singe cell RNA-seq (scRNA-seq)-profiled cortical and retinal ganglion cell (RGC) CNS projection neurons, investigated whether Nfe2l3 regulates neuroprotection and axon regeneration after CNS injury in vivo, and characterized a gene network associated with Nfe2l3 in neurons. We showed that, Nfe2l3 expression transiently peaks in developing immature cortical and RGC projection neurons, but is nearly abolished in adult neurons and is not upregulated after injury. Furthermore, within the retina, Nfe2l3 is enriched in RGCs, primarily neonatally, and not upregulated in injured RGCs, whereas Nfe2l1 and Nfe2l2 are expressed robustly in other retinal cell types as well and are upregulated in injured RGCs. We also found that, expressing Nfe2l3 in injured RGCs through localized intralocular viral vector delivery promotes neuroprotection and long-distance axon regeneration after optic nerve injury in vivo. Moreover, Nfe2l3 provided a similar extent of neuroprotection and axon regeneration as viral vector-targeting of Pten and Klf9, which are prominent regulators of neuroprotection and long-distance axon regeneration. Finally, we bioinformatically characterized a gene network associated with Nfe2l3 in neurons, which predicted the association of Nfe2l3 with established mechanisms of neuroprotection and axon regeneration. Thus, Nfe2l3 is a novel neuroprotection and axon regeneration-promoting factor with a therapeutic potential for treating CNS injury and disease.

External validation of a deep learning algorithm for automated echocardiographic strain measurements.

Aims: Echocardiographic strain imaging reflects myocardial deformation and is a sensitive measure of cardiac function and wall-motion abnormalities. Deep learning (DL) algorithms could automate the interpretation of echocardiographic strain imaging. Methods and results: We developed and trained an automated DL-based algorithm for left ventricular (LV) strain measurements in an internal dataset. Global longitudinal strain (GLS) was validated externally in (i) a real-world Taiwanese cohort of participants with and without heart failure (HF), (ii) a core-lab measured dataset from the multinational prevalence of microvascular dysfunction-HF and preserved ejection fraction (PROMIS-HFpEF) study, and regional strain in (iii) the HMC-QU-MI study of patients with suspected myocardial infarction. Outcomes included measures of agreement [bias, mean absolute difference (MAD), root-mean-squared-error (RMSE), and Pearson's correlation (R)] and area under the curve (AUC) to identify HF and regional wall-motion abnormalities. The DL workflow successfully analysed 3741 (89%) studies in the Taiwanese cohort, 176 (96%) in PROMIS-HFpEF, and 158 (98%) in HMC-QU-MI. Automated GLS showed good agreement with manual measurements (mean ± SD): -18.9 ± 4.5% vs. -18.2 ± 4.4%, respectively, bias 0.68 ± 2.52%, MAD 2.0 ± 1.67, RMSE = 2.61, R = 0.84 in the Taiwanese cohort; and -15.4 ± 4.1% vs. -15.9 ± 3.6%, respectively, bias -0.65 ± 2.71%, MAD 2.19 ± 1.71, RMSE = 2.78, R = 0.76 in PROMIS-HFpEF. In the Taiwanese cohort, automated GLS accurately identified patients with HF (AUC = 0.89 for total HF and AUC = 0.98 for HF with reduced ejection fraction). In HMC-QU-MI, automated regional strain identified regional wall-motion abnormalities with an average AUC = 0.80. Conclusion: DL algorithms can interpret echocardiographic strain images with similar accuracy as conventional measurements. These results highlight the potential of DL algorithms to democratize the use of cardiac strain measurements and reduce time-spent and costs for echo labs globally.

Upregulation of developmentally-downregulated miR-1247-5p promotes neuroprotection and axon regeneration in vivo.

Numerous micro-RNAs (miRNAs) affect neurodevelopment and neuroprotection, but potential roles of many miRNAs in regulating these processes are still unknown. Here, we used the retinal ganglion cell (RGC) central nervous system (CNS) projection neuron and optic nerve crush (ONC) injury model, to optimize a mature miRNA arm-specific quantification method for characterizing the developmental regulation of miR-1247-5p in RGCs, investigated whether injury affects its expression, and tested whether upregulating miR-1247-5p-mimic in RGCs promotes neuroprotection and axon regeneration. We found that, miR-1247-5p is developmentally-downregulated in RGCs, and is further downregulated after ONC. Importantly, RGC-specific upregulation of miR-1247-5p promoted neuroprotection and axon regeneration after injury in vivo. To gain insight into the underlying mechanisms, we analyzed by bulk-mRNA-seq embryonic and adult RGCs, along with adult RGCs transduced by miR-1247-5p-expressing viral vector, and identified developmentally-regulated cilial and mitochondrial biological processes, which were reinstated to their embryonic levels in adult RGCs by upregulation of miR-1247-5p. Since axon growth is also a developmentally-regulated process, in which mitochondrial dynamics play important roles, it is possible that miR-1247-5p promoted neuroprotection and axon regeneration through regulating mitochondrial functions.

To what extent can decommissioning options for marine artificial structures move us toward environmental targets?

Switching from fossil fuels to renewable energy is key to international energy transition efforts and the move toward net zero. For many nations, this requires decommissioning of hundreds of oil and gas infrastructure in the marine environment. Current international, regional and national legislation largely dictates that structures must be completely removed at end-of-life although, increasingly, alternative decommissioning options are being promoted and implemented. Yet, a paucity of real-world case studies describing the impacts of decommissioning on the environment make decision-making with respect to which option(s) might be optimal for meeting international and regional strategic environmental targets challenging. To address this gap, we draw together international expertise and judgment from marine environmental scientists on marine artificial structures as an alternative source of evidence that explores how different decommissioning options might ameliorate pressures that drive environmental status toward (or away) from environmental objectives. Synthesis reveals that for 37 United Nations and Oslo-Paris Commissions (OSPAR) global and regional environmental targets, experts consider repurposing or abandoning individual structures, or abandoning multiple structures across a region, as the options that would most strongly contribute toward targets. This collective view suggests complete removal may not be best for the environment or society. However, different decommissioning options act in different ways and make variable contributions toward environmental targets, such that policy makers and managers would likely need to prioritise some targets over others considering political, social, economic, and ecological contexts. Current policy may not result in optimal outcomes for the environment or society.

Experimental upregulation of developmentally downregulated ribosomal protein large subunits 7 and 7A promotes axon regeneration after injury in vivo.

Ribosomal proteins are involved in neurodevelopment and central nervous system (CNS) disease and injury. However, the roles of specific ribosomal protein subunits in developmental axon growth, and their potential as therapeutic targets for treating CNS injuries, are still poorly understood. Here, we show that ribosomal protein large (Rpl) and small (Rps) subunit genes are substantially (56-fold) enriched amongst the genes, which are downregulated during maturation of retinal ganglion cell (RGC) CNS projection neurons. We also show that Rpl and Rps subunits are highly co-regulated in RGCs, and partially re-upregulated after optic nerve crush (ONC). Because developmental downregulation of ribosomal proteins coincides with developmental decline in neuronal intrinsic axon growth capacity, we hypothesized that Rpl/Rps incomplete re-upregulation after injury may be a part of the cellular response which attempts to reactivate intrinsic axon growth mechanisms. We found that experimentally upregulating Rpl7 and Rpl7A promoted axon regeneration after ONC in vivo. Finally, we characterized gene networks associated with Rpl/Rps, and showed that Rpl7 and Rpl7A belong to the cluster of genes, which are shared between translational and neurodevelopmental biological processes (based on gene-ontology) that are co-downregulated in maturing RGCs during the decline in intrinsic axon growth capacity.

CBD and PSP cell-passaged Tau Seeds Generate Heterogeneous Fibrils with A sub-population Adopting Disease Folds.

The recent discovery by cryo-electron microscopy that the neuropatho-logical hallmarks of different tauopathies, including Alzheimer's disease, corticobasal degeneration (CBD), and progressive supranuclear palsy (PSP), are caused by unique misfolded conformations of the protein tau is among the most profound developments in neurodegenerative disease research. To capitalize on these discoveries for therapeutic development, one must achieve in vitro replication of tau fibrils that adopt the rep-resentative tauopathy disease folds - a grand challenge. To understand whether the commonly used, but imperfect, fragment of the tau pro-tein, K18, is capable of inducing specific protein folds, fibril seeds derived from CBD- and PSP-infected biosensor cells expressing K18, were used to achieve cell-free assembly of naïve, recombinant 4R tau into fibrils without the addition of any cofactors. Using Double Electron Electron Resonance (DEER) spectroscopy, we discovered that cell-passaged patho-logical seeds generate heterogeneous fibrils that are distinct between the CBD and PSP lysate-seeded fibrils, and are also unique from heparin-induced tau fibril populations. Moreover, the lysate-seeded fibrils contain a characteristic sub-population that resembles either the CBD or PSP disease fold, corresponding with the respective starting patient sam-ple. These findings indicate that CBD and PSP patient-derived fibrils retain strain properties after passaging through K18 reporter cells.

The Complex, Unique, and Powerful Imaging Instrument for Dynamics (CUPI2D) at the Spallation Neutron Source (invited).

The Oak Ridge National Laboratory is planning to build the Second Target Station (STS) at the Spallation Neutron Source (SNS). STS will host a suite of novel instruments that complement the First Target Station's beamline capabilities by offering an increased flux for cold neutrons and a broader wavelength bandwidth. A novel neutron imaging beamline, named the Complex, Unique, and Powerful Imaging Instrument for Dynamics (CUPI2D), is among the first eight instruments that will be commissioned at STS as part of the construction project. CUPI2D is designed for a broad range of neutron imaging scientific applications, such as energy storage and conversion (batteries and fuel cells), materials science and engineering (additive manufacturing, superalloys, and archaeometry), nuclear materials (novel cladding materials, nuclear fuel, and moderators), cementitious materials, biology/medical/dental applications (regenerative medicine and cancer), and life sciences (plant-soil interactions and nutrient dynamics). The innovation of this instrument lies in the utilization of a high flux of wavelength-separated cold neutrons to perform real time in situ neutron grating interferometry and Bragg edge imaging-with a wavelength resolution of δλ/λ ≈ 0.3%-simultaneously when required, across a broad range of length and time scales. This manuscript briefly describes the science enabled at CUPI2D based on its unique capabilities. The preliminary beamline performance, a design concept, and future development requirements are also presented.

The theory of change and realistic evaluation applied to the evaluation of a transport intervention: The case of the Nottingham Workplace Parking Levy.

This paper focuses on the application of evaluation based on a Theory of Change Approach, including elements of Realistic Evaluation to a transport intervention; the UK's first Workplace Parking Levy (WPL) introduced in 2012 in the City of Nottingham. A WPL places a charge off-street parking provided by employers. The scheme acts as a transport demand management measure with the revenue hypothecated for funding transport improvements. The WPL and the measures that it funds thus form an integrated package aimed at achieving social, economic and environmental benefits. The approach afforded a robust evaluation of the outcomes and impacts of a WPL package of measures. Based on this case study it is able to conclude that this evaluation approach is an appropriate framework for evaluating public sector interventions in general and transport interventions specifically and recommend as to how the methodology may be refined for future transport evaluations.

Transcriptomic profiling of retinal cells reveals a subpopulation of microglia/macrophages expressing Rbpms marker of retinal ganglion cells (RGCs) that confound identification of RGCs.

Analysis of retinal ganglion cells (RGCs) by scRNA-seq is emerging as a state-of-the-art method for studying RGC biology and subtypes, as well as for studying the mechanisms of neuroprotection and axon regeneration in the central nervous system (CNS). Rbpms has been established as a pan-RGC marker, and Spp1 has been established as an αRGC type and macrophage marker. Here, we analyzed by scRNA-seq retinal microglia and macrophages, and found Rbpms+ subpopulations of retinal microglia/macrophages, which pose a potential pitfall in scRNA-seq studies involving RGCs. We performed comparative analysis of cellular identity of the presumed RGC cells isolated in recent scRNA-seq studies, and found that Rbpms+ microglia/macrophages confounded identification of RGCs. We also showed using immunohistological analysis that, Rbpms protein localizes to stress granules in a subpopulation of retinal microglia after optic nerve injury, which was further supported by bioinformatics analysis identifying stress granule-associated genes enriched in the Rbpms+ microglia/macrophages. Our findings suggest that the identification of Rbpms+ RGCs by immunostaining after optic nerve injury should exclude cells in which Rbpms signal is restricted to a subcellular granule, and include only those cells in which the Rbpms signal is labeling cell soma diffusely. Finally, we provide solutions for circumventing this potential pitfall of Rbpms-expressing microglia/macrophages in scRNA-seq studies, by including in RGC and αRGC selection criteria other pan-RGC and αRGC markers.

Experimental gene expression of developmentally downregulated Crmp1, Crmp4, and Crmp5 promotes axon regeneration and retinal ganglion cell survival after optic nerve injury.

Collapsin response mediator proteins (Crmps) play roles in neuronal development and axon growth. However, neuronal-specific roles of Crmp1, Crmp4, and Crmp5 in regeneration of injured central nervous system (CNS) axons in vivo are unclear. Here, we analyzed developmental and subtype-specific expression of Crmp genes in retinal ganglion cells (RGCs), tested whether overexpressing Crmp1, Crmp4, or Crmp5 in RGCs through localized intralocular AAV2 delivery promotes axon regeneration after optic nerve injury in vivo, and characterized developmental co-regulation of gene-concept networks associated with Crmps. We found that all Crmp genes are developmentally downregulated in RGCs during maturation. However, while Crmp1, Crmp2, and Crmp4 were expressed to a varying degree in most RGC subtypes, Crmp3 and Crmp5 were expressed only in a small subset of RGC subtypes. We then found that after optic nerve injury, Crmp1, Crmp4, and Crmp5 promote RGC axon regeneration to varying extents, with Crmp4 promoting the most axon regeneration and also localizing to axons. We also found that Crmp1 and Crmp4, but not Crmp5, promote RGC survival. Finally, we found that Crmp1, Crmp2, Crmp4, and Crmp5's ability to promote axon regeneration is associated with neurodevelopmental mechanisms, which control RGC's intrinsic axon growth capacity.

Fully Automated Artificial Intelligence Assessment of Aortic Stenosis by Echocardiography.

BACKGROUND: Aortic stenosis (AS) is a common form of valvular heart disease, present in over 12% of the population age 75 years and above. Transthoracic echocardiography (TTE) is the first line of imaging in the adjudication of AS severity but is time-consuming and requires expert sonographic and interpretation capabilities to yield accurate results. Artificial intelligence (AI) technology has emerged as a useful tool to address these limitations but has not yet been applied in a fully hands-off manner to evaluate AS. Here, we correlate artificial neural network measurements of key hemodynamic AS parameters to experienced human reader assessment. METHODS: Two-dimensional and Doppler echocardiographic images from patients with normal aortic valves and all degrees of AS were analyzed by an artificial neural network (Us2.ai) with no human input to measure key variables in AS assessment. Trained echocardiographers blinded to AI data performed manual measurements of these variables, and correlation analyses were performed. RESULTS: Our cohort included 256 patients with an average age of 67.6 ± 9.5 years. Across all AS severities, AI closely matched human measurement of aortic valve peak velocity (r = 0.97, P < .001), mean pressure gradient (r = 0.94, P < .001), aortic valve area by continuity equation (r = 0.88, P < .001), stroke volume index (r = 0.79, P < .001), left ventricular outflow tract velocity-time integral (r = 0.89, P < .001), aortic valve velocity-time integral (r = 0.96, P < .001), and left ventricular outflow tract diameter (r = 0.76, P < .001). CONCLUSIONS: Artificial neural networks have the capacity to closely mimic human measurement of all relevant parameters in the adjudication of AS severity. Application of this AI technology may minimize interscan variability, improve interpretation and diagnosis of AS, and allow for precise and reproducible identification and management of patients with AS.

Development and validation of echocardiography-based machine-learning models to predict mortality.

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.

A formal validation of a deep learning-based automated workflow for the interpretation of the echocardiogram.

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.

Trypanosoma brucei Mitochondrial DNA Polymerase POLIB Contains a Novel Polymerase Domain Insertion That Confers Dominant Exonuclease Activity.

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.

PIONEER, a high-resolution single-crystal polarized neutron diffractometer.

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 mm3, 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 × 1012 n cm-2 sr-1 Å-1 s-1 at 2.5 Å at the sample position, within a 5 × 5 mm2 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.

High-Entropy Perovskite as a High-Performing Chromium-Tolerant Cathode for Solid Oxide Fuel Cells.

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 ABO3 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 (La0.6Sr0.4)(Co0.2Fe0.8)O3-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 (La0.2Sr0.2Pr0.2Y0.2Ba0.2)Co0.2Fe0.8O3-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.

Elucidating connections between the strigolactone biosynthesis pathway, flavonoid production and root system architecture in Arabidopsis thaliana.

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.

Automated interpretation of systolic and diastolic function on the echocardiogram: a multicohort study.

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.

Operando measurement of lattice strain in internal combustion engine components by neutron diffraction.

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.