Analyzing spatial patterns linked to the ecology of herbivores and their natural enemies in the soil

Modern agricultural systems can benefit from the application of concepts and models from applied ecology. When understood, multitrophic interactions among plants, pests, diseases and their natural enemies can be exploited to increase crop production and reduce undesirable environmental impacts. Although the understanding of subterranean ecology is rudimentary compared to the perspective aboveground, technologies today vastly reduce traditional obstacles to studying cryptic communities. Here we emphasize advantages to integrating as much as possible the use of these methods in order to leverage the information gained from studying communities of soil organisms. PCR-based approaches to identify and quantify species (real time qPCR and next generation sequencing) greatly expand the ability to investigate food web interactions because there is less need for wide taxonomic expertise within research programs. Improved methods to capture and measure volatiles in the soil atmosphere in situ make it possible to detect and study chemical cues that are critical to communication across trophic levels. The application of SADIE to directly assess rather than infer spatial patterns in belowground agroecosystems has improved the ability to characterize relationships between organisms in space and time. We review selected methodology and use of these tools and describe some of the ways they were integrated to study soil food webs in Florida citrus orchards with the goal of developing new biocontrol approaches.info:eu-repo/semantics/publishedVersio

Induced Release of a Plant-Defense Volatile ‘Deceptively’ Attracts Insect Vectors to Plants Infected with a Bacterial Pathogen

Transmission of plant pathogens by insect vectors is a complex biological process involving interactions between the plant, insect, and pathogen. Pathogen-induced plant responses can include changes in volatile and nonvolatile secondary metabolites as well as major plant nutrients. Experiments were conducted to understand how a plant pathogenic bacterium, Candidatus Liberibacter asiaticus (Las), affects host preference behavior of its psyllid (Diaphorina citri Kuwayama) vector. D. citri were attracted to volatiles from pathogen-infected plants more than to those from non-infected counterparts. Las-infected plants were more attractive to D. citri adults than non-infected plants initially; however after feeding, psyllids subsequently dispersed to non-infected rather than infected plants as their preferred settling point. Experiments with Las-infected and non-infected plants under complete darkness yielded similar results to those recorded under light. The behavior of psyllids in response to infected versus non-infected plants was not influenced by whether or not they were carriers of the pathogen. Quantification of volatile release from non-infected and infected plants supported the hypothesis that odorants mediate psyllid preference. Significantly more methyl salicylate, yet less methyl anthranilate and D-limonene, was released by infected than non-infected plants. Methyl salicylate was attractive to psyllids, while methyl anthranilate did not affect their behavior. Feeding on citrus by D. citri adults also induced release of methyl salicylate, suggesting that it may be a cue revealing location of conspecifics on host plants. Infected plants were characterized by lower levels of nitrogen, phosphorus, sulfur, zinc, and iron, as well as, higher levels of potassium and boron than non-infected plants. Collectively, our results suggest that host selection behavior of D. citri may be modified by bacterial infection of plants, which alters release of specific headspace volatiles and plant nutritional contents. Furthermore, we show in a laboratory setting that this apparent pathogen-mediated manipulation of vector behavior may facilitate pathogen spread

Dynamic amyloid and metabolic signatures of delayed recall performance within the clinical spectrum of Alzheimer’s disease

Associations between pathophysiological events and cognitive measures provide insights regarding brain networks affected during the clinical progression of Alzheimer’s disease (AD). In this study, we assessed patients’ scores in two delayed episodic memory tests, and investigated their associations with regional amyloid deposition and brain metabolism across the clinical spectrum of AD. We assessed the clinical, neuropsychological, structural, and positron emission tomography (PET) baseline measures of participants from the Alzheimer’s Disease Neuroimaging Initiative. Subjects were classified as cognitively normal (CN), or with early (EMCI) or late (LMCI) mild cognitive impairment, or AD dementia. The memory outcome measures of interest were logical memory 30 min delayed recall (LM30) and Rey Auditory Verbal Learning Test 30 min delayed recall (RAVLT30). Voxel-based [18F]florbetapir and [18F]FDG uptake-ratio maps were constructed and correlations between PET images and cognitive scores were calculated. We found that EMCI individuals had LM30 scores negatively correlated with [18F]florbetapir uptake on the right parieto-occipital region. LMCI individuals had LM30 scores positively associated with left lateral temporal lobe [18F]FDG uptake, and RAVLT30 scores positively associated with [18F]FDG uptake in the left parietal lobe and in the right enthorhinal cortex. Additionally, LMCI individuals had LM30 scores negatively correlated with [18F]florbetapir uptake in the right frontal lobe. For the AD group, [18F]FDG uptake was positively correlated with LM30 in the left temporal lobe and with RAVLT30 in the right frontal lobe, and [18F]florbetapir uptake was negatively correlated with LM30 scores in the right parietal and left frontal lobes. The results show that the association between regional brain metabolism and the severity of episodic memory deficits is dependent on the clinical disease stage, suggesting a dynamic relationship between verbal episodic memory deficits, AD pathophysiology, and clinical disease stages

SoK: Contemporary Issues and Challenges to Enable Cyber Situational Awareness for Network Security

Cyber situational awareness is an essential part of cyber defense that allows the cybersecurity operators to cope with the complexity of today's networks and threat landscape. Perceiving and comprehending the situation allow the operator to project upcoming events and make strategic decisions. In this paper, we recapitulate the fundamentals of cyber situational awareness and highlight its unique characteristics in comparison to generic situational awareness known from other fields. Subsequently, we provide an overview of existing research and trends in publishing on the topic, introduce front research groups, and highlight the impact of cyber situational awareness research. Further, we propose an updated taxonomy and enumeration of the components used for achieving cyber situational awareness. The updated taxonomy conforms to the widely-accepted three-level definition of cyber situational awareness and newly includes the projection level. Finally, we identify and discuss contemporary research and operational challenges, such as the need to cope with rising volume, velocity, and variety of cybersecurity data and the need to provide cybersecurity operators with the right data at the right time and increase their value through visualization

Subterranean, herbivore-induced plant volatile increases biological control activity of multiple beneficial nematode species in distinct habitats

While the role of herbivore-induced volatiles in plant-herbivore-natural enemy interactions is well documented aboveground, new evidence suggests that belowground volatile emissions can protect plants by attracting entomopathogenic nematodes (EPNs). However, due to methodological limitations, no study has previously detected belowground herbivore-induced volatiles in the field or quantified their impact on attraction of diverse EPN species. Here we show how a belowground herbivore-induced volatile can enhance mortality of agriculturally significant root pests. First, in real time, we identified pregeijerene (1,5-dimethylcyclodeca-1,5,7-triene) from citrus roots 9-12 hours after initiation of larval Diaprepes abbreviatus feeding. This compound was also detected in the root zone of mature citrus trees in the field. Application of collected volatiles from weevil-damaged citrus roots attracted native EPNs and increased mortality of beetle larvae (D. abbreviatus) compared to controls in a citrus orchard. In addition, field applications of isolated pregeijerene caused similar results. Quantitative real-time PCR revealed that pregeijerene increased pest mortality by attracting four species of naturally occurring EPNs in the field. Finally, we tested the generality of this root-zone signal by application of pregeijerene in blueberry fields; mortality of larvae (Galleria mellonella and Anomala orientalis) again increased by attracting naturally occurring populations of an EPN. Thus, this specific belowground signal attracts natural enemies of widespread root pests in distinct agricultural systems and may have broad potential in biological control of root pests.info:eu-repo/semantics/publishedVersio

Multi-core fibre-fed integral-field unit (MCIFU):Overview and first-light

The Multi-Core Integral-Field Unit (MCIFU) is a new diffraction-limited near-infrared integral-field unit for exoplanet atmosphere characterization with extreme adaptive optics (xAO) instruments. It has been developed as an experimental pathfinder for spectroscopic upgrades for SPHERE+/VLT and other xAO systems. The wavelength range covers 1.0 um to 1.6um at a resolving power around 5000 for 73 points on-sky. The MCIFU uses novel astrophotonic components to make this very compact and robust spectrograph. We performed the first successful on-sky test with CANARY at the 4.2 meter William Herschel Telescope in July 2019, where observed standard stars and several stellar binaries. An improved version of the MCIFU will be used with MagAO-X, the new extreme adaptive optics system at the 6.5 meter Magellan Clay telescope in Chile. We will show and discuss the first-light performance and operations of the MCIFU at CANARY and discuss the integration of the MCIFU with MagAO-X.</p

Recent Progress and Next Steps for the MATHUSLA LLP Detector

We report on recent progress and next steps in the design of the proposed MATHUSLA Long Lived Particle (LLP) detector for the HL-LHC as part of the Snowmass 2021 process. Our understanding of backgrounds has greatly improved, aided by detailed simulation studies, and significant R&D has been performed on designing the scintillator detectors and understanding their performance. The collaboration is on track to complete a Technical Design Report, and there are many opportunities for interested new members to contribute towards the goal of designing and constructing MATHUSLA in time for HL-LHC collisions, which would increase the sensitivity to a large variety of highly motivated LLP signals by orders of magnitude.Comment: Contribution to Snowmass 2021 (EF09, EF10, IF6, IF9), 18 pages, 12 figures. v2: included additional endorser

An international effort towards developing standards for best practices in analysis, interpretation and reporting of clinical genome sequencing results in the CLARITY Challenge

There is tremendous potential for genome sequencing to improve clinical diagnosis and care once it becomes routinely accessible, but this will require formalizing research methods into clinical best practices in the areas of sequence data generation, analysis, interpretation and reporting. The CLARITY Challenge was designed to spur convergence in methods for diagnosing genetic disease starting from clinical case history and genome sequencing data. DNA samples were obtained from three families with heritable genetic disorders and genomic sequence data were donated by sequencing platform vendors. The challenge was to analyze and interpret these data with the goals of identifying disease-causing variants and reporting the findings in a clinically useful format. Participating contestant groups were solicited broadly, and an independent panel of judges evaluated their performance. RESULTS: A total of 30 international groups were engaged. The entries reveal a general convergence of practices on most elements of the analysis and interpretation process. However, even given this commonality of approach, only two groups identified the consensus candidate variants in all disease cases, demonstrating a need for consistent fine-tuning of the generally accepted methods. There was greater diversity of the final clinical report content and in the patient consenting process, demonstrating that these areas require additional exploration and standardization. CONCLUSIONS: The CLARITY Challenge provides a comprehensive assessment of current practices for using genome sequencing to diagnose and report genetic diseases. There is remarkable convergence in bioinformatic techniques, but medical interpretation and reporting are areas that require further development by many groups

ENIGMA-anxiety working group : Rationale for and organization of large-scale neuroimaging studies of anxiety disorders

Altres ajuts: Anxiety Disorders Research Network European College of Neuropsychopharmacology; Claude Leon Postdoctoral Fellowship; Deutsche Forschungsgemeinschaft (DFG, German Research Foundation, 44541416-TRR58); EU7th Frame Work Marie Curie Actions International Staff Exchange Scheme grant 'European and South African Research Network in Anxiety Disorders' (EUSARNAD); Geestkracht programme of the Netherlands Organization for Health Research and Development (ZonMw, 10-000-1002); Intramural Research Training Award (IRTA) program within the National Institute of Mental Health under the Intramural Research Program (NIMH-IRP, MH002781); National Institute of Mental Health under the Intramural Research Program (NIMH-IRP, ZIA-MH-002782); SA Medical Research Council; U.S. National Institutes of Health grants (P01 AG026572, P01 AG055367, P41 EB015922, R01 AG060610, R56 AG058854, RF1 AG051710, U54 EB020403).Anxiety disorders are highly prevalent and disabling but seem particularly tractable to investigation with translational neuroscience methodologies. Neuroimaging has informed our understanding of the neurobiology of anxiety disorders, but research has been limited by small sample sizes and low statistical power, as well as heterogenous imaging methodology. The ENIGMA-Anxiety Working Group has brought together researchers from around the world, in a harmonized and coordinated effort to address these challenges and generate more robust and reproducible findings. This paper elaborates on the concepts and methods informing the work of the working group to date, and describes the initial approach of the four subgroups studying generalized anxiety disorder, panic disorder, social anxiety disorder, and specific phobia. At present, the ENIGMA-Anxiety database contains information about more than 100 unique samples, from 16 countries and 59 institutes. Future directions include examining additional imaging modalities, integrating imaging and genetic data, and collaborating with other ENIGMA working groups. The ENIGMA consortium creates synergy at the intersection of global mental health and clinical neuroscience, and the ENIGMA-Anxiety Working Group extends the promise of this approach to neuroimaging research on anxiety disorders

Severe Asthma Standard-of-Care Background Medication Reduction With Benralizumab: ANDHI in Practice Substudy

Background: The phase IIIb, randomized, parallel-group, placebo-controlled ANDHI double-blind (DB) study extended understanding of the efficacy of benralizumab for patients with severe eosinophilic asthma. Patients from ANDHI DB could join the 56-week ANDHI in Practice (IP) single-arm, open-label extension substudy. Objective: Assess potential for standard-of-care background medication reductions while maintaining asthma control with benralizumab. Methods: Following ANDHI DB completion, eligible adults were enrolled in ANDHI IP. After an 8-week run-in with benralizumab, there were 5 visits to potentially reduce background asthma medications for patients achieving and maintaining protocol-defined asthma control with benralizumab. Main outcome measures for non-oral corticosteroid (OCS)-dependent patients were the proportions with at least 1 background medication reduction (ie, lower inhaled corticosteroid dose, background medication discontinuation) and the number of adapted Global Initiative for Asthma (GINA) step reductions at end of treatment (EOT). Main outcomes for OCS-dependent patients were reductions in daily OCS dosage and proportion achieving OCS dosage of 5 mg or lower at EOT. Results: For non-OCS-dependent patients, 53.3% (n = 208 of 390) achieved at least 1 background medication reduction, increasing to 72.6% (n = 130 of 179) for patients who maintained protocol-defined asthma control at EOT. A total of 41.9% (n = 163 of 389) achieved at least 1 adapted GINA step reduction, increasing to 61.8% (n = 110 of 178) for patients with protocol-defined EOT asthma control. At ANDHI IP baseline, OCS dosages were 5 mg or lower for 40.4% (n = 40 of 99) of OCS-dependent patients. Of OCS-dependent patients, 50.5% (n = 50 of 99) eliminated OCS and 74.7% (n = 74 of 99) achieved dosages of 5 mg or lower at EOT. Conclusions: These findings demonstrate benralizumab's ability to improve asthma control, thereby allowing background medication reduction