Comprehensive analysis of the membrane phosphoproteome regulated by oligogalacturonides in Arabidopsis thaliana

Early changes in the Arabidopsis thaliana membrane phosphoproteome in response to oligogalacturonides (OGs), a class of plant damage-associated molecular patterns (DAMPs), were analyzed by two complementary proteomic approaches. Differentially phosphorylated sites were determined through phosphopeptide enrichment followed by LC-MS/MS using label-free quantification; differentially phosphorylated proteins were identified by 2D-DIGE combined with phospho-specific fluorescent staining (phospho-DIGE). This large-scale phosphoproteome analysis of early OG-signaling enabled us to determine 100 regulated phosphosites using LC-MS/MS and 46 differential spots corresponding to 34 pdhosphoproteins using phospho-DIGE. Functional classification showed that the OG-responsive phosphoproteins include kinases, phosphatases and receptor-like kinases, heat shock proteins (HSPs), reactive oxygen species (ROS) scavenging enzymes, proteins related to cellular trafficking, transport, defense and signaling as well as novel candidates for a role in immunity, for which elicitor-induced phosphorylation changes have not been shown before. A comparison with previously identified elicitor-regulated phosphosites shows only a very limited overlap, uncovering the immune-related regulation of 70 phosphorylation sites and revealing novel potential players in the regulation of elicitor-dependent immunity

Changes in the microsomal proteome of tomato fruit during ripening

The variations in the membrane proteome of tomato fruit pericarp during ripening have been investigated by mass spectrometry-based label-free proteomics. Mature green (MG30) and red ripe (R45) stages were chosen because they are pivotal in the ripening process: MG30 corresponds to the end of cellular expansion, when fruit growth has stopped and fruit starts ripening, whereas R45 corresponds to the mature fruit. Protein patterns were markedly different: among the 1315 proteins identified with at least two unique peptides, 145 significantly varied in abundance in the process of fruit ripening. The subcellular and biochemical fractionation resulted in GO term enrichment for organelle proteins in our dataset, and allowed the detection of low-abundance proteins that were not detected in previous proteomic studies on tomato fruits. Functional annotation showed that the largest proportion of identified proteins were involved in cell wall metabolism, vesicle-mediated transport, hormone biosynthesis, secondary metabolism, lipid metabolism, protein synthesis and degradation, carbohydrate metabolic processes, signalling and response to stress

Human Perception in Natural Language Generation

We ask subjects whether they perceive as human-produced a bunch of texts, some of which are actually human-written, while others are automatically generated. We use this data to fine-tune a GPT-2 model to push it to generate more human-like texts, and observe that this fine-tuned model produces texts that are indeed perceived more human-like than the original model. Contextually, we show that our automatic evaluation strategy well correlates with human judgements. We also run a linguistic analysis to unveil the characteristics of human- vs machine-perceived language

Invisible to People but not to Machines:Evaluation of Style-aware Headline Generation in Absence of Reliable Human Judgment

We automatically generate headlines that are expected to comply with the specific styles of two different Italian newspapers. Through a data alignment strategy and different training/testing settings, we aim at decoupling content from style and preserve the latter in generation. In order to evaluate the generated headlines’ quality in terms of their specific newspaper-compliance, we devise a fine-grained evaluation strategy based on automatic classification. We observe that our models do indeed learn newspaper-specific style.Importantly, we also observe that humans aren’t reliable judges for this task, since although familiar with the newspapers, they are notable to discern their specific styles even in the original human-written headlines. The utility of automatic evaluation goes therefore beyond saving the costs and hurdles of manual annotation, and deserves particular care in its design