Dataset Information

Uncovering natural variation in root system architecture and growth dynamics using a robotics-assisted phenomics platform.

ABSTRACT: The plant kingdom contains a stunning array of complex morphologies easily observed above-ground, but more challenging to visualize below-ground. Understanding the magnitude of diversity in root distribution within the soil, termed root system architecture (RSA), is fundamental in determining how this trait contributes to species adaptation in local environments. Roots are the interface between the soil environment and the shoot system and therefore play a key role in anchorage, resource uptake, and stress resilience. Previously, we presented the GLO-Roots (Growth and Luminescence Observatory for Roots) system to study the RSA of soil-grown Arabidopsis thaliana plants from germination to maturity (Rellán-Álvarez et al., 2015). In this study, we present the automation of GLO-Roots using robotics and the development of image analysis pipelines in order to examine the temporal dynamic regulation of RSA and the broader natural variation of RSA in Arabidopsis, over time. These datasets describe the developmental dynamics of two independent panels of accessions and reveal highly complex and polygenic RSA traits that show significant correlation with climate variables of the accessions' respective origins.

SUBMITTER: LaRue T

PROVIDER: S-EPMC9499532 | biostudies-literature | 2022 Sep

REPOSITORIES: biostudies-literature

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Uncovering natural variation in root system architecture and growth dynamics using a robotics-assisted phenomics platform.

LaRue Therese T Lindner Heike H Srinivas Ankit A Exposito-Alonso Moises M Lobet Guillaume G Dinneny José R JR

eLife 20220901

The plant kingdom contains a stunning array of complex morphologies easily observed above-ground, but more challenging to visualize below-ground. Understanding the magnitude of diversity in root distribution within the soil, termed root system architecture (RSA), is fundamental in determining how this trait contributes to species adaptation in local environments. Roots are the interface between the soil environment and the shoot system and therefore play a key role in anchorage, resource uptake, ...[more]

PMID: 36047575

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Project description:Nowadays, robotics applications requiring the execution of complex tasks in real-world scenarios are still facing many challenges related to highly unstructured and dynamic environments in domains such as emergency response and search and rescue where robots have to operate for prolonged periods trading off computational performance with increased power autonomy and vice versa. In particular, there is a crucial need for robots capable of adapting to such settings while at the same time providing robustness and extended power autonomy. A possible approach to overcome the conflicting demand of a computational performing system with the need for long power autonomy is represented by cloud robotics, which can boost the computational capabilities of the robot while reducing the energy consumption by exploiting the offload of resources to the cloud. Nevertheless, the communication constraint due to limited bandwidth, latency, and connectivity, typical of field robotics, makes cloud-enabled robotics solutions challenging to deploy in real-world applications. In this context, we designed and realized the XBot2D software architecture, which provides a hybrid cloud manager capable of dynamically and seamlessly allocating robotics skills to perform a distributed computation based on the current network condition and the required latency, and computational/energy resources of the robot in use. The proposed framework leverage on the two dimensions, i.e., 2D (local and cloud), in a transparent way for the user, providing support for Real-Time (RT) skills execution on the local robot, as well as machine learning and A.I. resources on the cloud with the possibility to automatically relocate the above based on the required performances and communication quality. XBot2D implementation and its functionalities are presented and validated in realistic tasks involving the CENTAURO robot and the Amazon Web Service Elastic Computing Cloud (AWS EC2) infrastructure with different network conditions.

Project description:ObjectivesWe demonstrate the feasibility and safety of robotics-assisted left atrial appendage clip exclusion in clinical practice.MethodsAnalysis of a single center robotics-assisted left atrial appendage clip exclusion experience using an epicardial linear clip device in patients with atrial fibrillation with high-risk of thromboembolic stroke and intolerance to oral anticoagulants.ResultsDuring the period from December 2017 to September 2020, we performed 42 robotics-assisted left atrial appendage clip exclusions in response to increased risk of bleeding in patients with atrial fibrillation and intolerance to oral anticoagulants. The average congestive heart failure, hypertension, age, diabetes, stroke, and vascular disease score was 5.2 ± 1.6 and hypertension, abnormal liver or kidney function, stroke, bleeding, labile international normalized ratio, elderly, drugs (aspirin, other antiplatelets, or anticoagulants) score was 4.5 ± 0.9. No patients died intraoperatively or within 30 days, or due to conversion to thoracotomy, intraoperative complications, or failure to apply the clip satisfactorily. The procedure was successfully completed despite pericardial adhesions in 2 patients with prior coronary bypass grafts and 3 with postpericarditis scars. Intraoperative transesophageal echocardiography was performed in 38 out of 42 patients; satisfactory exclusion with left atrial appendage stump <5 mm was confirmed in all. Average length of stay was 3.4 ± 3 days with 12 out of 42 patients discharged within 24 hours. Oral anticoagulants were discontinued in 41 out of 42 patients and no cases of 30-day stroke, myocardial ischemia, or new arrhythmias were observed. One case of hemothorax required thoracoscopy a day later. There was no reported thromboembolic stroke or transient ischemic attack at 12 months. One case of late lacunar stroke was due to in situ small intracranial vessel thrombosis without left atrial appendage thrombus on imaging.ConclusionsRobotics-assisted left atrial appendage clip exclusion is a safe and feasible minimally invasive method for left atrial appendage management in patients with atrial fibrillation with intolerance to oral anticoagulants and increased risk of thromboembolic stroke.

Dataset Information

Uncovering natural variation in root system architecture and growth dynamics using a robotics-assisted phenomics platform.

Publications

Uncovering natural variation in root system architecture and growth dynamics using a robotics-assisted phenomics platform.

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