Northern leaf blight (NLB) can cause severe yield loss in maize; however, scouting large areas to accurately diagnose the disease is time consuming and difficult. We demonstrate a system capable of ...automatically identifying NLB lesions in field-acquired images of maize plants with high reliability. This approach uses a computational pipeline of convolutional neural networks (CNNs) that addresses the challenges of limited data and the myriad irregularities that appear in images of field-grown plants. Several CNNs were trained to classify small regions of images as containing NLB lesions or not; their predictions were combined into separate heat maps, then fed into a final CNN trained to classify the entire image as containing diseased plants or not. The system achieved 96.7% accuracy on test set images not used in training. We suggest that such systems mounted on aerial- or ground-based vehicles can help in automated high-throughput plant phenotyping, precision breeding for disease resistance, and reduced pesticide use through targeted application across a variety of plant and disease categories.
A vaccine for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is needed to control the coronavirus disease 2019 (COVID-19) global pandemic. Structural studies have led to the development ...of mutations that stabilize Betacoronavirus spike proteins in the prefusion state, improving their expression and increasing immunogenicity
. This principle has been applied to design mRNA-1273, an mRNA vaccine that encodes a SARS-CoV-2 spike protein that is stabilized in the prefusion conformation. Here we show that mRNA-1273 induces potent neutralizing antibody responses to both wild-type (D614) and D614G mutant
SARS-CoV-2 as well as CD8
T cell responses, and protects against SARS-CoV-2 infection in the lungs and noses of mice without evidence of immunopathology. mRNA-1273 is currently in a phase III trial to evaluate its efficacy.
Computer vision models that can recognize plant diseases in the field would be valuable tools for disease management and resistance breeding. Generating enough data to train these models is ...difficult, however, since only trained experts can accurately identify symptoms. In this study, we describe and implement a two-step method for generating a large amount of high-quality training data with minimal expert input. First, experts located symptoms of northern leaf blight (NLB) in field images taken by unmanned aerial vehicles (UAVs), annotating them quickly at low resolution. Second, non-experts were asked to draw polygons around the identified diseased areas, producing high-resolution ground truths that were automatically screened based on agreement between multiple workers. We then used these crowdsourced data to train a convolutional neural network (CNN), feeding the output into a conditional random field (CRF) to segment images into lesion and non-lesion regions with accuracy of 0.9979 and F1 score of 0.7153. The CNN trained on crowdsourced data showed greatly improved spatial resolution compared to one trained on expert-generated data, despite using only one fifth as many expert annotations. The final model was able to accurately delineate lesions down to the millimeter level from UAV-collected images, the finest scale of aerial plant disease detection achieved to date. The two-step approach to generating training data is a promising method to streamline deep learning approaches for plant disease detection, and for complex plant phenotyping tasks in general.
Automated detection and quantification of plant diseases would enable more rapid gains in plant breeding and faster scouting of farmers' fields. However, it is difficult for a simple algorithm to ...distinguish between the target disease and other sources of dead plant tissue in a typical field, especially given the many variations in lighting and orientation. Training a machine learning algorithm to accurately detect a given disease from images taken in the field requires a massive amount of human-generated training data.
This data set contains images of maize (Zea mays L.) leaves taken in three ways: by a hand-held camera, with a camera mounted on a boom, and with a camera mounted on a small unmanned aircraft system (sUAS, commonly known as a drone). Lesions of northern leaf blight (NLB), a common foliar disease of maize, were annotated in each image by one of two human experts. The three data sets together contain 18,222 images annotated with 105,705 NLB lesions, making this the largest publicly available image set annotated for a single plant disease.
Plant disease poses a serious threat to global food security. Accurate, high-throughput methods of quantifying disease are needed by breeders to better develop resistant plant varieties and by ...researchers to better understand the mechanisms of plant resistance and pathogen virulence. Northern leaf blight (NLB) is a serious disease affecting maize and is responsible for significant yield losses. A Mask R-CNN model was trained to segment NLB disease lesions in unmanned aerial vehicle (UAV) images. The trained model was able to accurately detect and segment individual lesions in a hold-out test set. The mean intersect over union (IOU) between the ground truth and predicted lesions was 0.73, with an average precision of 0.96 at an IOU threshold of 0.50. Over a range of IOU thresholds (0.50 to 0.95), the average precision was 0.61. This work demonstrates the potential for combining UAV technology with a deep learning-based approach for instance segmentation to provide accurate, high-throughput quantitative measures of plant disease.
The phylum Apicomplexa comprises a group of obligate intracellular parasites that alternate between intracellular replicating stages and actively motile extracellular forms that move through tissue. ...Parasite cytosolic Ca2+ signalling activates motility, but how this is switched off after invasion is complete to allow for replication to begin is not understood. Here, we show that the cyclic adenosine monophosphate (cAMP)-dependent protein kinase A catalytic subunit 1 (PKAc1) of Toxoplasma is responsible for suppression of Ca2+ signalling upon host cell invasion. We demonstrate that PKAc1 is sequestered to the parasite periphery by dual acylation of PKA regulatory subunit 1 (PKAr1). Upon genetic depletion of PKAc1 we show that newly invaded parasites exit host cells shortly thereafter, in a perforin-like protein 1 (PLP-1)-dependent fashion. Furthermore, we demonstrate that loss of PKAc1 prevents rapid down-regulation of cytosolic Ca2+ levels shortly after invasion. We also provide evidence that loss of PKAc1 sensitises parasites to cyclic GMP (cGMP)-induced Ca2+ signalling, thus demonstrating a functional link between cAMP and these other signalling modalities. Together, this work provides a new paradigm in understanding how Toxoplasma and related apicomplexan parasites regulate infectivity.
Physicians are encouraged to counsel overweight and obese patients to lose weight.
It was examined whether discussing weight and use of motivational interviewing techniques (e.g., collaborating, ...reflective listening) while discussing weight predicted weight loss 3 months after the encounter.
Forty primary care physicians and 461 of their overweight or obese patient visits were audio recorded between December 2006 and June 2008. Patient actual weight at the encounter and 3 months after the encounter (n=426); whether weight was discussed; physicians' use of motivational interviewing techniques; and patient, physician, and visit covariates (e.g., race, age, specialty) were assessed. This was an observational study and data were analyzed in April 2009.
No differences in weight loss were found between patients whose physicians discussed weight or did not. Patients whose physicians used motivational interviewing-consistent techniques during weight-related discussions lost weight 3 months post-encounter; those whose physician used motivational interviewing-inconsistent techniques gained or maintained weight. The estimated difference in weight change between patients whose physician had a higher global motivational interviewing-Spirit score (e.g., collaborated with patient) and those whose physician had a lower score was 1.6 kg (95% CI=-2.9, -0.3, p=0.02). The same was true for patients whose physician used reflective statements: 0.9 kg (95% CI=-1.8, -0.1, p=0.03). Similarly, patients whose physicians expressed only motivational interviewing-consistent behaviors had a difference in weight change of 1.1 kg (95% CI=-2.3, 0.1, p=0.07) compared to those whose physician expressed only motivational interviewing-inconsistent behaviors (e.g., judging, confronting).
In this observational study, use of motivational interviewing techniques during weight loss discussions predicted patient weight loss.
Infection by Toxoplasma gondii leads to massive changes to the host cell. Here, we identify a novel host cell effector export pathway that requires the Golgi-resident aspartyl protease 5 (ASP5). We ...demonstrate that ASP5 cleaves a highly constrained amino acid motif that has similarity to the PEXEL-motif of Plasmodium parasites. We show that ASP5 matures substrates at both the N- and C-terminal ends of proteins and also controls trafficking of effectors without this motif. Furthermore, ASP5 controls establishment of the nanotubular network and is required for the efficient recruitment of host mitochondria to the vacuole. Assessment of host gene expression reveals that the ASP5-dependent pathway influences thousands of the transcriptional changes that Toxoplasma imparts on its host cell. All these changes result in attenuation of virulence of Δasp5 tachyzoites in vivo. This work characterizes the first identified machinery required for export of Toxoplasma effectors into the infected host cell.
Background:
Effectiveness of anticoagulation services managed via telepharmacy (TP) has not been clearly demonstrated.
Objective:
This systematic review and meta-analysis compares the effectiveness ...of TP anticoagulation services to face-to-face (FTF) anticoagulation services in the ambulatory care setting.
Methods:
A literature search for studies assessing the effectiveness of TP services was conducted using PubMed, EMBASE, and Cochrane Central databases, from inception through November 18, 2020. Studies that compared TP with FTF anticoagulation services in the ambulatory care setting were included. Outcomes of interest included thromboembolic events, major bleeding, minor bleeding, any bleeding, warfarin international normalized ratio (INR) time in therapeutic range (TTR), frequency of extreme INR, anticoagulation-related emergency department visits, anticoagulation-related hospitalization, any hospitalization, and mortality. Relative risk (RR) and weighted mean difference were calculated using the DerSimonian and Laird random-effects model.
Results:
Overall, 11 studies involving 8395 patients were included in the systematic review, and 9 studies were included in the pooled meta-analysis. Compared with FTF service, TP was associated with a lower risk of any bleeding and any hospitalization, with RRs of 0.65 (95% CI = 0.47 to 0.90; P = 0.01) and 0.59 (95% CI = 0.39 to 0.87; P = 0.01), respectively. There was no statistically significant difference in TTR or the risk of extreme supratherapeutic INR, major bleeding, minor bleeding, or thromboembolic events between the 2 groups.
Conclusions:
TP appears to be at least as effective as FTF anticoagulation services. Findings from this study support the utilization of TP practice models in ambulatory care anticoagulation management.
Licensed vaccines or therapeutics are rarely available for pathogens with epidemic or pandemic potential. Developing interventions for specific pathogens and defining generalizable approaches for ...related pathogens is a global priority and inherent to the UN Sustainable Development Goals. Nipah virus (NiV) poses a significant epidemic threat, and zoonotic transmission from bats-to-humans with high fatality rates occurs almost annually. Human-to-human transmission of NiV has been documented in recent outbreaks leading public health officials and government agencies to declare an urgent need for effective vaccines and therapeutics. Here, we evaluate NiV vaccine antigen design options including the fusion glycoprotein (F) and the major attachment glycoprotein (G). A stabilized prefusion F (pre-F), multimeric G constructs, and chimeric proteins containing both pre-F and G were developed as protein subunit candidate vaccines. The proteins were evaluated for antigenicity and structural integrity using kinetic binding assays, electron microscopy, and other biophysical properties. Immunogenicity of the vaccine antigens was evaluated in mice. The stabilized pre-F trimer and hexameric G immunogens both induced serum neutralizing activity in mice, while the post-F trimer immunogen did not elicit neutralizing activity. The pre-F trimer covalently linked to three G monomers (pre-F/G) induced potent neutralizing antibody activity, elicited responses to the greatest diversity of antigenic sites, and is the lead candidate for clinical development. The specific stabilizing mutations and immunogen designs utilized for NiV were successfully applied to other henipaviruses, supporting the concept of identifying generalizable solutions for prototype pathogens as an approach to pandemic preparedness.
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