ObjectivesTo systematically review the efficacy and safety of anti-inflammatory agents for patients with major depressive disorders.MethodsWe searched the literature to identify potentially relevant randomised controlled trials (RCTs) up to 1 January 2019. The primary outcome was efficacy, measured by mean changes in depression score from baseline to endpoint. Secondary outcomes included response and remission rates and quality of life (QoL). Safety was evaluated by incidence of classified adverse events. Heterogeneity was examined using the I2 and Q statistic. Pooled standard mean differences (SMDs) and risk ratios (RRs) were calculated. Subgroup meta-analyses were conducted based on type of treatment, type of anti-inflammatory agents, sex, sponsor type and quality of studies.ResultsThirty RCTs with 1610 participants were included in the quantitative analysis. The overall analysis pooling from 26 of the RCTs suggested that anti-inflammatory agents reduced depressive symptoms (SMD −0.55, 95% CI −0.75 to −0.35, I2=71%) compared with placebo. Higher response (RR 1.52, 95% CI 1.30 to 1.79, I2=29%) and remission rates (RR 1.79, 95% CI 1.29 to 2.49, I2=41%) were seen in the group receiving anti-inflammatory agents than in those receiving placebo. Subgroup analysis showed a greater reduction in symptom severity in both the monotherapy and adjunctive treatment groups. Subgroup analysis of non-steroidal anti-inflammatory drugs, omega-3 fatty acids, statins and minocyclines, respectively, disclosed significant antidepressant effects for major depressive disorder (MDD). For women-only trials, no difference in changes of depression severity was found between groups. Subanalysis stratified by sponsor type and study quality led to the same outcomes in favour of anti-inflammatory agents in both subgroups. Changes of QoL showed no difference between the groups. Gastrointestinal events were the only significant differences between groups in the treatment periods.ConclusionsResults of this systematic review suggest that anti-inflammatory agents play an antidepressant role in patients with MDD and are reasonably safe.

Background: Migraine is one of the most common neurological disorders that leads to disabilities. However, the conventional drug therapy for migraine might be unsatisfactory at times. Therefore, this meta-analysis aimed to evaluate the efficacy and safety of calcitonin-gene-related peptide binding monoclonal antibody (CGRP mAb) for the preventive treatment of episodic migraine, and provide high-quality clinical evidence for migraine therapy. Methods: A systematic electronic database search was conducted to identify the potentially relevant studies. Two independent authors performed data extraction and quality appraisal. Mean difference (MD) and risk ratio (RR) were pooled for continuous and dichotomous data, respectively. The significance levels, weighted effect sizes and homogeneity of variance were calculated. Results: Eleven high-quality randomized control trials that collectively included 4402 patients were included in this meta-analysis. Compared to placebo group, CGRP mAb therapy resulted in a reduction of monthly migraine days [weighted mean difference (WMD) = − 1.44, 95% CI = (− 1.68,− 1.19)] and acute migraine-specific medication days [WMD = − 1.28, 95% CI = (− 1.66,− 0.90)], with an improvement in 50% responder rate [RR = 1.51, 95% CI = (1.37,1.66)]. In addition, the adverse events (AEs) and treatment withdrawal rates due to AEs were not significantly different between CGRP mAb and placebo groups. Similar efficacy and safety results were obtained for erenumab, fremanezumab, and galcanezumab in subgroup analysis. Conclusions: The current body of evidence reveals that CGRP mAb is an effective and safe preventive treatment for episodic migraine.

Ethylene participates in the regulation of numerous cellular events and biological processes, including water loss, during leaf and flower petal wilting. The diverse ethylene responses may be regulated via dynamic interplays between protein phosphorylation/dephosphorylation and ubiquitin/26S proteasome-mediated protein degradation and protease cleavage. To address how ethylene alters protein phosphorylation through multi-furcated signaling pathways, we performed a (15)N stable isotope labelling-based, differential, and quantitative phosphoproteomics study on air- and ethylene-treated ethylene-insensitive Arabidopsis double loss-of-function mutant ein3-1/eil1-1. Among 535 non-redundant phosphopeptides identified, two and four phosphopeptides were up- and downregulated by ethylene, respectively. Ethylene-regulated phosphorylation of aquaporin PIP2;1 is positively correlated with the water flux rate and water loss in leaf. Genetic studies in combination with quantitative proteomics, immunoblot analysis, protoplast swelling/shrinking experiments, and leaf water loss assays on the transgenic plants expressing both the wild-type and S280A/S283A-mutated PIP2;1 in the both Col-0 and ein3eil1 genetic backgrounds suggest that ethylene increases water transport rate in Arabidopsis cells by enhancing S280/S283 phosphorylation at the C terminus of PIP2;1. Unknown kinase and/or phosphatase activities may participate in the initial up-regulation independent of the cellular functions of EIN3/EIL1. This finding contributes to our understanding of ethylene-regulated leaf wilting that is commonly observed during post-harvest storage of plant organs.

No abstract

Ethylene is an important plant hormone that regulates numerous cellular processes and stress responses. The mode of action of ethylene is both dose-and time-dependent. Protein phosphorylation plays a key role in ethylene signaling, which is mediated by the activities of ethylene receptors, constitutive triple response 1 (CTR1) kinase, and phosphatase. To address how ethylene alters the cellular protein phosphorylation profile in a time-dependent manner, differential and quantitative phosphoproteomics based on 15 N stable isotope labeling in Arabidopsis was performed on both one-minute ethylene-treated Arabidopsis ethylene-overly-sensitive loss-of-function mutant rcn1-1, deficient in PP2A phosphatase activity, and a pair of long-term ethylene-treated wild-type and loss-of-function ethylene signaling ctr1-1 mutants, deficient in mitogen-activated kinase kinase kinase activity. In total, 1079 phosphopeptides were identified, among which 44 were novel. Several one-minute ethylene-regulated phosphoproteins were found from the rcn1-1. Bioinformatic analysis of the rcn1-1 phosphoproteome predicted nine phosphoproteins as the putative substrates for PP2A phosphatase. In addition, from CTR1 kinase-enhanced phosphosites, we also found putative CTR1 kinase substrates including plastid transcriptionally active protein and calcium-sensing receptor. These regulatory proteins are phosphorylated in the presence of ethylene. Analysis of ethyleneregulated phosphosites using the group-based prediction system with a protein-protein interaction filter revealed a total of 14 kinase-substrate relationships that may function in both CTR1 kinase-and PP2A phosphatase-mediated phosphor-relay pathways. Ethylene is a volatile plant hormone that regulates versatile molecular and physiological processes in higher plants (1). The perception of this gaseous two-carbon hormone is achieved by a group of membrane-associated dimeric ethylene receptors that resemble bacterial two-component signaling systems and are composed of hybrid histidine (or aspartic acid) kinases, a histidine-containing phosphor-transfer domain, and response regulators (2). These receptors are made of two membrane-bound protein subunits cross-linked at the N-terminal region through two disulfide bonds (3). In Arabidopsis, there are five different ethylene receptor subunits: ethylene response 1, ethylene response 2, ethylene insensitive 4 (EIN4), 1 ethylene response sensor 1, and ethylene re- 1 The abbreviations used are: ACC, aminocyclopropane-1-carboxylic acid; ACN, acetonitrile; CIPK1, CBL-interacting protein kinase 1; CTR1, constitutive triple response 1; eer1-1, enhanced ethylene response 1; EIN, ethylene insensitive; FBH3, flowering bHLH 3 protein; FDR, false discovery rate; GPS, group-based prediction system; HMG, high mobility group; IMAC, immobilized metal-ion-affinity chromatography; iTRAQ, isobaric tag for relative and absolute quantitation; LHCB, light harvetsting chlorophyll A/B binding protein; Research

BackgroundPhosphorylation motifs represent common patterns around the phosphorylation site. The discovery of such kinds of motifs reveals the underlying regulation mechanism and facilitates the prediction of unknown phosphorylation event. To date, people have gathered large amounts of phosphorylation data, making it possible to perform substrate-driven motif discovery using data mining techniques.ResultsWe describe an algorithm called Motif-All that is able to efficiently identify all statistically significant motifs. The proposed method explores a support constraint to reduce search space and avoid generating random artifacts. As the number of phosphorylated peptides are far less than that of unphosphorylated ones, we divide the mining process into two stages: The first step generates candidates from the set of phosphorylated sequences using only support constraint and the second step tests the statistical significance of each candidate using the odds ratio derived from the whole data set. Experimental results on real data show that Motif-All outperforms current algorithms in terms of both effectiveness and efficiency.ConclusionsMotif-All is a useful tool for discovering statistically significant phosphorylation motifs. Source codes and data sets are available at: http://bioinformatics.ust.hk/MotifAll.rar.

Post-translational modification isoforms of a protein are known to play versatile biological functions in diverse cellular processes. To measure the molar amount of each post-translational modification isoform (P isf ) of a target protein present in the total protein extract using mass spectrometry, a quantitative proteomic protocol, absolute quantitation of isoforms of post-translationally modified proteins (AQUIP), was developed. A recombinant ERF110 gene overexpression transgenic Arabidopsis plant was used as the model organism for demonstration of the proof of concept. Both Ser-62-independent 14 N-coded synthetic peptide standards and 15 N-coded ERF110 protein standard isolated from the heavy nitrogen-labeled transgenic plants were employed simultaneously to determine the concentration of all isoforms (T isf ) of ERF110 in the whole plant cell lysate, whereas a pair of Ser-62-dependent synthetic peptide standards were used to quantitate the Ser-62 phosphosite occupancy (R aqu ). The P isf was finally determined by integrating the two empirically measured variables using the following equation: P isf ‫؍‬ T isf ⅐ R aqu . The absolute amount of Ser-62-phosphorylated isoform of ERF110 determined using AQUIP was substantiated with a stable isotope labeling in Arabidopsis-based relative and accurate quantitative proteomic approach. The biological role of the Ser-62-phosphorylated isoform was demonstrated in transgenic plants.

Spatial proteomics has the potential to significantly advance our understanding of biology, physiology and medicine. Matrix-assisted laser desorption/ionisation mass spectrometry imaging (MALDI-MSI) is a powerful tool in the spatial proteomics field, enabling direct detection and registration of protein abundance and distribution across tissues. MALDI-MSI preserves spatial distribution and histology allowing unbiased analysis of complex, heterogeneous tissues. However, MALDI-MSI faces the challenge of simultaneous peptide quantification and identification. To overcome this, we develop and validate HIT-MAP (High-resolution Informatics Toolbox in MALDI-MSI Proteomics), an open-source bioinformatics workflow using peptide mass fingerprint analysis and a dual scoring system to computationally assign peptide and protein annotations to high mass resolution MSI datasets and generate customisable spatial distribution maps. HIT-MAP will be a valuable resource for the spatial proteomics community for analysing newly generated and retrospective datasets, enabling robust peptide and protein annotation and visualisation in a wide array of normal and disease contexts.