Editorial: Eliciting plant defense responses: From basic to applied science for sustainable agriculture

Plants constantly face a diversity of pathogens and insects that affect food production. Synthetic agrochemicals are often use to overcome these challenges. However, current demands for stringent worldwide regulatory policies led to the development of sustainable agriculture strategies, including naturally-derived molecules that elicit plant defense responses (Scariotto et al., 2021). The commercial use of these molecules is still limited, mostly due to poor knowledge on the molecular mechanisms producing their effects on plant metabolism. In recent decades, efforts have been directed toward understanding how individual molecules, such as immune receptors or microbial effectors, enable plants to perceive and respond to pathogens, insects, and other stresses. Furthermore, recent research on plant immunity has revealed high levels of complexity, including regulation mediated by micro-peptides and miRNA. Such knowledge opens the opportunity to link basic and applied science to facilitate using natural elicitors as a sustainable option for crop protection

Comparison of the Predictive Performance and Interpretability of Random Forest and Linear Models on Benchmark Datasets

The ability to interpret the predictions made by quantitative structure activity relationships (QSARs) offers a number of advantages. Whilst QSARs built using non-linear modelling approaches, such as the popular Random Forest algorithm, might sometimes be more predictive than those built using linear modelling approaches, their predictions have been perceived as difficult to interpret. However, a growing number of approaches have been proposed for interpreting non-linear QSAR models in general and Random Forest in particular. In the current work, we compare the performance of Random Forest to two widely used linear modelling approaches: linear Support Vector Machines (SVM), or Support Vector Regression (SVR), and Partial Least Squares (PLS). We compare their performance in terms of their predictivity as well as the chemical interpretability of the predictions, using novel scoring schemes for assessing Heat Map images of substructural contributions. We critically assess different approaches to interpreting Random Forest models as well as for obtaining predictions from the forest. We assess the models on a large number of widely employed, public domain benchmark datasets corresponding to regression and binary classification problems of relevance to hit identification and toxicology. We conclude that Random Forest typically yields comparable or possibly better predictive performance than the linear modelling approaches and that its predictions may also be interpreted in a chemically and biologically meaningful way. In contrast to earlier work looking at interpreting non-linear QSAR models, we directly compare two methodologically distinct approaches for interpreting Random Forest models. The approaches for interpreting Random Forest assessed in our article were implemented using Open Source programs, which we have made available to the community. These programs are the rfFC package [https://r-forge.r-project.org/R/?group_id=1725] for the R Statistical Programming Language, along with a Python program HeatMapWrapper [https://doi.org/10.5281/zenodo.495163] for Heat Map generation

Influence of plasma processing on recovery and analysis of circulating nucleic acids.

Circulating nucleic acids (CNAs) are under investigation as a liquid biopsy in cancer. However there is wide variation in blood processing and methods for isolation of circulating free DNA (cfDNA) and microRNAs (miRNAs). Here we compare the extraction efficiency and reproducibility of 4 commercially available kits for cfDNA and 3 for miRNA using spike-in of reference templates. We also compare the effects of increasing time between venepuncture and centrifugation and differential centrifugation force on recovery of CNAs. cfDNA was quantified by TaqMan qPCR and targeted deep sequencing. miRNA profiles were assessed with TaqMan low-density arrays and assays. The QIAamp(®) DNA Blood Mini and Circulating nucleic acid kits gave the highest recovery of cfDNA and efficient recovery (>90%) of a 564bp spike-in. Moreover, targeted sequencing revealed overlapping cfDNA profiles and variant depth, including detection of HER2 gene amplification, using the Ion AmpliSeq™Cancer Hotspot Panel v2. Highest yields of miRNA and the synthetic Arabidopsis thaliana miR-159a spike-in were obtained using the miRNeasy Serum/Plasma kit, with saturation above 200 µl of plasma. miRNA profiles showed significant variation with increasing time before centrifugation (p 12 years, highlighting the potential for analysis of stored sample biobanks. In the era of the liquid biopsy, standardisation of methods is required to minimise variation, particularly for miRNA

Delayed nephrectomy has comparable long-term overall survival to immediate nephrectomy for cT1a renal cell carcinoma: A population-based analysis

Objectives: Early surgical resection remains the recommended treatment option for most small renal mass (≤4 cm). We examined the long-term overall survival (OS) of patients managed with delayed and immediate nephrectomy of cT1a renal cancer. / Patient and methods: We utilized the National Cancer Database (2005–2010) to identify 14,677 patients (immediate nephrectomy: 14,050 patients vs. late nephrectomy: 627 patients) aged 180 days from diagnosis, respectively. Inverse probability of treatment weighting–adjusted Kaplan-Meier curves and Cox proportional hazards regression analyses were used to compare OS of patients in the 2 treatment arms. Influence of patient age and Charlson Comorbidity Index on treatment effect was tested by interactions. Sensitivity analysis was performed to explore the outcome of delaying nephrectomy for >12 months. / Results: Median patient age was 55 years with a median follow-up of 82.5 months. Inverse probability of treatment weighting-adjusted Kaplan-Meier curves suggest no significant difference between treatment arms (immediate nephrectomy [180 days]) (Hazard ratio 0.96; 95% confidence interval 0.73–1.26; P = 0.77). This outcome was consistent between all patients regardless of age (P = 0.48). Sensitivity analysis reports no difference in OS even if nephrectomy was delayed by >12 months (P = 0.60). / Conclusions: We report that delayed and immediate nephrectomy for cT1a renal cell carcinoma confers comparable long-term OS. These findings suggest that a period of observation of between 6 and 12 months is safe to allow identification of renal masses, which will benefit from surgical resection

Payload capabilities and operational limits of eversion robots

Recent progress in soft robotics has seen new types of actuation mechanisms based on apical extension which allows robots to grow to unprecedented lengths. Eversion robots are a type of robots based on the principle of apical extension offering excellent maneuverability and ease of control allowing users to conduct tasks from a distance. Mechanical modelling of these robotic structures is very important for understanding their operational capabilities. In this paper, we model the eversion robot as a thin-walled cylindrical beam inflated with air pressure, using Timoshenko beam theory considering rotational and shear effects. We examine the various failure modes of the eversion robots such as yielding, buckling instability and lateral collapse, and study the payloads and operational limits of these robots in axial and lateral loading conditions. Surface maps showing the operational boundaries for different combinations of the geometrical parameters are presented. This work provides insights into the design of eversion robots and can pave the way towards eversion robots with high payload capabilities that can act from long distances

Clinical ApoA-IV amyloid is associated with fibrillogenic signal sequence

Apolipoprotein A-IV amyloidosis is an uncommon form of the disease normally resulting in renal and cardiac dysfunction. ApoA-IV amyloidosis was identified in sixteen patients attending the National Amyloidosis Centre and in eight clinical samples received for histology review. Unexpectedly, proteomics identified the presence of ApoA-IV signal sequence residues (p.18–43 to p.20–43) in 16/24 trypsin-digested amyloid deposits, but in only 1/266 non-ApoA-IV amyloid samples examined. These additional signal residues were also detected in the cardiac sample from the Swedish patient in which ApoA-IV amyloid was first described, and in plasma from a single cardiac ApoA-IV amyloidosis patient. The most common signal-containing peptide observed in ApoA-IV amyloid, p.20–43 and to far lesser extent the N-terminal peptide, p.21–43 were fibrillogenic in vitro at physiological pH generating Congo red positive fibrils. The addition of a single signal-derived alanine residue to the N-terminus has resulted in markedly increased fibrillogenesis. If this effect translates to the mature circulating protein in vivo, then the presence of signal may result in preferential deposition as amyloid, perhaps acting as seed for the main circulating native form of the protein; it may also influence other ApoA-IV associated pathologies

Observation of associated near-side and away-side long-range correlations in √sNN=5.02 TeV proton-lead collisions with the ATLAS detector

Two-particle correlations in relative azimuthal angle (Δϕ) and pseudorapidity (Δη) are measured in √sNN=5.02  TeV p+Pb collisions using the ATLAS detector at the LHC. The measurements are performed using approximately 1  μb-1 of data as a function of transverse momentum (pT) and the transverse energy (ΣETPb) summed over 3.1<η<4.9 in the direction of the Pb beam. The correlation function, constructed from charged particles, exhibits a long-range (2<|Δη|<5) “near-side” (Δϕ∼0) correlation that grows rapidly with increasing ΣETPb. A long-range “away-side” (Δϕ∼π) correlation, obtained by subtracting the expected contributions from recoiling dijets and other sources estimated using events with small ΣETPb, is found to match the near-side correlation in magnitude, shape (in Δη and Δϕ) and ΣETPb dependence. The resultant Δϕ correlation is approximately symmetric about π/2, and is consistent with a dominant cos⁡2Δϕ modulation for all ΣETPb ranges and particle pT

Search for R-parity-violating supersymmetry in events with four or more leptons in sqrt(s) =7 TeV pp collisions with the ATLAS detector

A search for new phenomena in final states with four or more leptons (electrons or muons) is presented. The analysis is based on 4.7 fb−1 of $\sqrt{s}=7\;\mathrm{TeV}$ proton-proton collisions delivered by the Large Hadron Collider and recorded with the ATLAS detector. Observations are consistent with Standard Model expectations in two signal regions: one that requires moderate values of missing transverse momentum and another that requires large effective mass. The results are interpreted in a simplified model of R-parity-violating supersymmetry in which a 95% CL exclusion region is set for charged wino masses up to 540 GeV. In an R-parity-violating MSUGRA/CMSSM model, values of m 1/2 up to 820 GeV are excluded for 10 < tan β < 40