Effects of defoliation at fruit set on vine physiology and berry composition in cabernet sauvignon grapevines

Grapevine canopy defoliation is a fundamentally important technique for the productivity and quality of grapes. Leaf removal is a pivotal operation on high-density vines which aims to improve air circulation, light exposure, and leaf gas exchange. The effects of leaf removal (LR) on vine physiology and berry composition in Cabernet Sauvignon grapevines were studied during the 2018–2019 growing season in the Bolgheri area, Tuscany, Italy. The basal leaves were removed at fruit set at two severity levels (removal of four basal leaves of each shoot (LR4) and removal of eight basal leaves (LR8)). The two treatments were compared with the not defoliated control (CTRL). The following physiological parameters of vines were measured: leaf gas exchange, leaf water potential, chlorophyll fluorescence and indirect chlorophyll content. The results showed that defoliation increased single leaf photosynthesis. In addition, qualitative grape parameters (phenolic and technological analyses) and daytime and night-time berry temperature were studied. The results showed that leaf removal had an impact on total soluble solids (°Brix), titratable acidity, and pH. The LR8-treated grapes had higher titratable acidity, while those in the LR4 treatment had higher °Brix and extractable anthocyanin and polyphenol content. Berry weight was not significantly influenced by the timing and severity of basal defoliation. Therefore, this research aims to investigate the effects of defoliation at the fruit set on vines performance

3D Chitosan-Gallic Acid Complexes: Assessment of the Chemical and Biological Properties

Three-dimensional chitosan-gallic acid complexes were proposed and prepared for the first time by a simple adsorption process of gallic acid (GA) on three-dimensional chitosan structures (3D chitosan). Highly porous 3D devices facilitate a high GA load, up to 2015 mmol/kg at pH 4.0. The preservation of the redox state of GA released from 3D chitosan was confirmed by spectroscopic analyses. The antioxidant activity of 3D chitosan-GA complexes was assessed using the DPPH radical scavenging assay and was found to be dramatically higher than that of free chitosan. The mechanical property of 3D chitosan–GA complexes was also evaluated using a compression test. Finally, 3D chitosan–GA complexes showed a significant antimicrobial capacity against E. coli and S. aureus, selected, respectively, as a model strain for Gram-negative and Gram-positive bacteria. Our study demonstrated a new, simple, and eco-friendly approach to prepare functional chitosan-based complexes for nutraceutical, cosmeceutical, and pharmaceutical applications

An autonomous, in situ light-dark bottle device for determining community respiration and net community production

Author Posting. © The Author(s), 2018. This is the author's version of the work. It is posted here under a nonexclusive, irrevocable, paid-up, worldwide license granted to WHOI. It is made available for personal use, not for redistribution. The definitive version was published in Limnology and Oceanography-Methods 16 (2018): 323-338, doi:10.1002/lom3.10247.We describe a new, autonomous, incubation-based instrument that is deployed in situ to determine rates of gross community respiration and net community production in marine and aquatic ecosystems. During deployments at a coastal pier and in the open ocean, the PHORCYS (PHOtosynthesis and Respiration Comparison-Yielding System) captured dissolved oxygen fluxes over hourly timescales that were missed by traditional methods. The instrument uses fluorescence-quenching optodes fitted into separate light and dark chambers; these are opened and closed with piston-like actuators, allowing the instrument to make multiple, independent rate estimates in the course of each deployment. Consistent with other studies in which methods purporting to measure the same metabolic processes have yielded divergent results, respiration rate estimates from the PHORCYS were systematically higher than those calculated for the same waters using a traditional two-point Winkler titration technique. However, PHORCYS estimates of gross respiration agreed generally with separate incubations in bottles fitted with optode sensor spots. An Appendix describes a new method for estimating uncertainties in metabolic rates calculated from continuous dissolved oxygen data. Multiple successful, unattended deployments of the PHORCYS represent a small step toward fully autonomous observations of community metabolism. Yet the persistence of unexplained disagreements among aquatic metabolic rate estimates — such as those we observed between rates calculated with the PHORCYS and two existing, widely-accepted bottle-based methods — suggests that a new community intercalibration effort is warranted to address lingering sources of error in these critical measurements.This research was supported by the U.S. National Science Foundation (awards OCE-1155438 to B.A.S.V.M., J.R.V., and R.G.K., and OCE- 1059884 to B.A.S.V.M.), the Woods Hole Oceanographic Institution through a Cecil and Ida Green Foundation Innovative Technology Award and an Interdisciplinary Science Award, and a U.S. Environmental Protection Agency (EPA) STAR Graduate Fellowship to J.R.C. under Fellowship Assistance Agreement no. FP-91744301-0

Properties of healthcare teaming networks as a function of network construction algorithms

This is the final version. Available on open access from Public Library of Science via the DOI in this recordData Availability: The Center for Medicare Services Outpatient Claims DE-SynPUF (DE-SynPUF)\cite{RN120} test set is publicly available from the CMS web site. The full 2013 Medicare Part B Limited Data Set for Medicare claims can be obtained from the Center for Medicare Services. This data is bound by a privacy and limited distribution agreement, as well as HIPAA regulations, and thus cannot be made public with this manuscript. However, the files can be requested from the Center for Medicare Services by individual investigators and used to reproduce our findings. Release of the derived networks is also limited by Medicare requirements to remove nodes and edges where the total number of shared patients 11 shared patients, and these are available on figshare.com as referenced in the Supplemental Data section of the manuscript.Network models of healthcare systems can be used to examine how providers collaborate, communicate, refer patients to each other, and to map how patients traverse the network of providers. Most healthcare service network models have been constructed from patient claims data, using billing claims to link a patient with a specific provider in time. The data sets can be quite large (106±108 individual claims per year), making standard methods for network construction computationally challenging and thus requiring the use of alternate construction algorithms. While these alternate methods have seen increasing use in generating healthcare networks, there is little to no literature comparing the differences in the structural properties of the generated networks, which as we demonstrate, can be dramatically different. To address this issue, we compared the properties of healthcare networks constructed using different algorithms from 2013 Medicare Part B outpatient claims data. Three different algorithms were compared: Binning, sliding frame, and trace-route. Unipartite networks linking either providers or healthcare organizations by shared patients were built using each method. We find that each algorithm produced networks with substantially different topological properties, as reflected by numbers of edges, network density, assortativity, clustering coefficients and other structural measures. Provider networks adhered to a power law, while organization networks were best fit by a power law with exponential cutoff. Censoring networks to exclude edges with less than 11 shared patients, a common de-identification practice for healthcare network data, markedly reduced edge numbers and network density, and greatly altered measures of vertex prominence such as the betweenness centrality. Data analysis identified patterns in the distance patients travel between network providers, and a striking set of teaming relationships between providers in the Northeast United States and Florida, likely due to seasonal residence patterns of Medicare beneficiaries. We conclude that the choice of network construction algorithm is critical for healthcare network analysis, and discuss the implications of our findings for selecting the algorithm best suited to the type of analysis to be performed.National Institute of HealthPhilip Templeton FoundationUniversity of Rochester Center for Health Informatic

The Phyre2 web portal for protein modeling, prediction and analysis

Phyre2 is a suite of tools available on the web to predict and analyze protein structure, function and mutations. The focus of Phyre2 is to provide biologists with a simple and intuitive interface to state-of-the-art protein bioinformatics tools. Phyre2 replaces Phyre, the original version of the server for which we previously published a paper in Nature Protocols. In this updated protocol, we describe Phyre2, which uses advanced remote homology detection methods to build 3D models, predict ligand binding sites and analyze the effect of amino acid variants (e.g., nonsynonymous SNPs (nsSNPs)) for a user's protein sequence. Users are guided through results by a simple interface at a level of detail they determine. This protocol will guide users from submitting a protein sequence to interpreting the secondary and tertiary structure of their models, their domain composition and model quality. A range of additional available tools is described to find a protein structure in a genome, to submit large number of sequences at once and to automatically run weekly searches for proteins that are difficult to model. The server is available at http://www.sbg.bio.ic.ac.uk/phyre2. A typical structure prediction will be returned between 30 min and 2 h after submission

Identification of a Photosystem II Phosphatase Involved in Light Acclimation in Arabidopsis

Reversible protein phosphorylation plays a major role in the acclimation of the photosynthetic apparatus to changes in light. Two paralogous kinases phosphorylate subsets of thylakoid membrane proteins. STN7 phosphorylates LHCII, the light harvesting antenna of photosystem II (PSII), to balance the activity of the two photosystems through state transitions. STN8, which is mainly involved in phosphorylation of PSII core subunits, influences folding of the thylakoid membranes and repair of PSII after photo-damage. The rapid reversibility of these acclimatory responses requires the action of protein phosphatases. In a reverse genetic screen we have identified the chloroplast PP2C phosphatase, PBCP (PHOTOSYSTEM II CORE PHOSPHATASE), which is required for efficient de-phosphorylation of PSII proteins. Its targets, identified by immunoblotting and mass spectrometry, largely coincide with those of the kinase STN8. The recombinant phosphatase is active in vitro on a synthetic substrate or on isolated thylakoids. Thylakoid folding is affected in the absence of PBCP, while its over-expression alters the kinetics of state transitions. PBCP and STN8 form an antagonistic kinase and phosphatase pair whose substrate specificity and physiological functions are distinct from those of STN7 and the counteracting phosphatase PPH1 (TAP38), but their activities may overlap to some degree

Low body weight in females is a risk factor for increased tenofovir exposure and drug-related adverse events

Treatment with tenofovir sometimes leads to non-reversible kidney and/or bone diseases. Factors associated with these drug-related adverse events are poorly characterized. Our objective was to investigate such factors in patients treated long term with daily tenofovir. One-hundred Caucasian HIV-positive patients with basal creatinine clearance >80 mL/min treated with tenofovir for at least 6 months and with at least one assessment of tenofovir plasma trough concentrations were considered. Tenofovir-associated adverse events were defined as the appearance of pathological proteinuria, worsening of renal function or bone demineralization. By multivariate regression analysis, we found that serum creatinine (p\u200a=\u200a0.003) and body weight (p\u200a=\u200a0.002) were the factors independently associated with plasma tenofovir concentrations. In particular, women with body weight50 Kg (160\ub193 vs.71\ub152 ng/mL, p<0.001). High tenofovir plasma trough concentrations and the age of the patients were independently associated with the development of drug-related kidney and bone toxicity. In this retrospective study we have shown that HIV-infected women with low body weight are at risk to be exposed to high tenofovir plasma trough concentrations, ultimately resulting in a significant hazard to develop long-term tenofovir complications

1H-NMR metabolomics reveals the Glabrescione B exacerbation of glycolytic metabolism beside the cell growth inhibitory effect in glioma

BACKGROUND: Glioma is the most common and primary brain tumors in adults. Despite the available multimodal therapies, glioma patients appear to have a poor prognosis. The Hedgehog (Hh) signaling is involved in tumorigenesis and emerged as a promising target for brain tumors. Glabrescione B (GlaB) has been recently identified as the first direct inhibitor of Gli1, the downstream effector of the pathway. METHODS: We established the overexpression of Gli1 in murine glioma cells (GL261) and GlaB effect on cell viability. We used 1H-nuclear magnetic resonance (NMR) metabolomic approach to obtain informative metabolic snapshots of GL261 cells acquired at different time points during GlaB treatment. The activation of AMP activated protein Kinase (AMPK) induced by GlaB was established by western blot. After the orthotopic GL261 cells injection in the right striatum of C57BL6 mice and the intranasal (IN) GlaB/mPEG5kDa-Cholane treatment, the tumor growth was evaluated. The High Performance Liquid Chromatography (HPLC) combined with Mass Spectrometry (MS) was used to quantify GlaB in brain extracts of treated mice. RESULTS: We found that GlaB affected the growth of murine glioma cells both in vitro and in vivo animal model. Using an untargeted 1H-NMR metabolomic approach, we found that GlaB stimulated the glycolytic metabolism in glioma, increasing lactate production. The high glycolytic rate could in part support the cytotoxic effects of GlaB, since the simultaneous blockade of lactate efflux with \u3b1-cyano-4-hydroxycinnamic acid (ACCA) affected glioma cell growth. According to the metabolomic data, we found that GlaB increased the phosphorylation of AMPK, a cellular energy sensor involved in the anabolic-to-catabolic transition. CONCLUSIONS: Our results indicate that GlaB inhibits glioma cell growth and exacerbates Warburg effect, increasing lactate production. In addition, the simultaneous blockade of Gli1 and lactate efflux amplifies the anti-tumor effect in vivo, providing new potential therapeutic strategy for this brain tumor

ePlant: Visualizing and Exploring Multiple Levels of Data for Hypothesis Generation in Plant Biology

A big challenge in current systems biology research arises when different types of data must be accessed from separate sources and visualized using separate tools. The high cognitive load required to navigate such a workflow is detrimental to hypothesis generation. Accordingly, there is a need for a robust research platform that incorporates all data and provides integrated search, analysis, and visualization features through a single portal. Here, we present ePlant (http://bar.utoronto.ca/eplant), a visual analytic tool for exploring multiple levels of Arabidopsis thaliana data through a zoomable user interface. ePlant connects to several publicly available web services to download genome, proteome, interactome, transcriptome, and 3D molecular structure data for one or more genes or gene products of interest. Data are displayed with a set of visualization tools that are presented using a conceptual hierarchy from big to small, and many of the tools combine information from more than one data type. We describe the development of ePlant in this article and present several examples illustrating its integrative features for hypothesis generation. We also describe the process of deploying ePlant as an “app” on Araport. Building on readily available web services, the code for ePlant is freely available for any other biological species research