Insulin-stimulated phosphorylation of protein phosphatase 1 regulatory subunit 12B revealed by HPLC-ESI-MS/MS

BACKGROUND: Protein phosphatase 1 (PP1) is one of the major phosphatases responsible for protein dephosphorylation in eukaryotes. Protein phosphatase 1 regulatory subunit 12B (PPP1R12B), one of the regulatory subunits of PP1, can bind to PP1cδ, one of the catalytic subunits of PP1, and modulate the specificity and activity of PP1cδ against its substrates. Phosphorylation of PPP1R12B on threonine 646 by Rho kinase inhibits the activity of the PP1c-PPP1R12B complex. However, it is not currently known whether PPP1R12B phosphorylation at threonine 646 and other sites is regulated by insulin. We set out to identify phosphorylation sites in PPP1R12B and to quantify the effect of insulin on PPP1R12B phosphorylation by using high-performance liquid chromatography-electrospray ionization-tandem mass spectrometry. RESULTS: 14 PPP1R12B phosphorylation sites were identified, 7 of which were previously unreported. Potential kinases were predicted for these sites. Furthermore, relative quantification of PPP1R12B phosphorylation sites for basal and insulin-treated samples was obtained by using peak area-based label-free mass spectrometry of fragment ions. The results indicate that insulin stimulates the phosphorylation of PPP1R12B significantly at serine 29 (3.02 ± 0.94 fold), serine 504 (11.67 ± 3.33 fold), and serine 645/threonine 646 (2.34 ± 0.58 fold). CONCLUSION: PPP1R12B was identified as a phosphatase subunit that undergoes insulin-stimulated phosphorylation, suggesting that PPP1R12B might play a role in insulin signaling. This study also identified novel targets for future investigation of the regulation of PPP1R12B not only in insulin signaling in cell models, animal models, and in humans, but also in other signaling pathways

SEC24A deficiency lowers plasma cholesterol through reduced PCSK9 secretion.

The secretory pathway of eukaryotic cells packages cargo proteins into COPII-coated vesicles for transport from the endoplasmic reticulum (ER) to the Golgi. We now report that complete genetic deficiency for the COPII component SEC24A is compatible with normal survival and development in the mouse, despite the fundamental role of SEC24 in COPII vesicle formation and cargo recruitment. However, these animals exhibit markedly reduced plasma cholesterol, with mutations in Apoe and Ldlr epistatic to Sec24a, suggesting a receptor-mediated lipoprotein clearance mechanism. Consistent with these data, hepatic LDLR levels are up-regulated in SEC24A-deficient cells as a consequence of specific dependence of PCSK9, a negative regulator of LDLR, on SEC24A for efficient exit from the ER. Our findings also identify partial overlap in cargo selectivity between SEC24A and SEC24B, suggesting a previously unappreciated heterogeneity in the recruitment of secretory proteins to the COPII vesicles that extends to soluble as well as trans-membrane cargoes. DOI:http://dx.doi.org/10.7554/eLife.00444.001

Metamorphic Testing Integer Overflow Faults of Mission Critical Program: A Case Study

For mission critical programs, integer overflow is one of the most dangerous faults. Different testing methods provide several effective ways to detect the defect. However, it is hard to validate the testing outputs, because the oracle of testing is not always available or too expensive to get, unless the program throws an exception obviously. In the present study, the authors conduct a case study, where the authors apply a metamorphic testing (MT) method to detect the integer overflow defect and alleviate the oracle problem in testing critical program of Traffic Collision Avoidance System (TCAS). Experimental results show that, in revealing typical integer mutations, compared with traditional safety property testing method, MT with a novel symbolic metamorphic relation is more effective than the traditional method in some cases.</jats:p

EPSD: Early Pruning with Self-Distillation for Efficient Model Compression

Neural network compression techniques, such as knowledge distillation (KD) and network pruning, have received increasing attention. Recent work `Prune, then Distill' reveals that a pruned student-friendly teacher network can benefit the performance of KD. However, the conventional teacher-student pipeline, which entails cumbersome pre-training of the teacher and complicated compression steps, makes pruning with KD less efficient. In addition to compressing models, recent compression techniques also emphasize the aspect of efficiency. Early pruning demands significantly less computational cost in comparison to the conventional pruning methods as it does not require a large pre-trained model. Likewise, a special case of KD, known as self-distillation (SD), is more efficient since it requires no pre-training or student-teacher pair selection. This inspires us to collaborate early pruning with SD for efficient model compression. In this work, we propose the framework named Early Pruning with Self-Distillation (EPSD), which identifies and preserves distillable weights in early pruning for a given SD task. EPSD efficiently combines early pruning and self-distillation in a two-step process, maintaining the pruned network's trainability for compression. Instead of a simple combination of pruning and SD, EPSD enables the pruned network to favor SD by keeping more distillable weights before training to ensure better distillation of the pruned network. We demonstrated that EPSD improves the training of pruned networks, supported by visual and quantitative analyses. Our evaluation covered diverse benchmarks (CIFAR-10/100, Tiny-ImageNet, full ImageNet, CUB-200-2011, and Pascal VOC), with EPSD outperforming advanced pruning and SD techniques.Comment: The first two authors are with equal contributions. Paper accepted by AAAI 202

Efficient Secure Multiparty Computation Protocol for Sequencing Problem over Insecure Channel

As a powerful tool in solving privacy preserving cooperative problems, secure multiparty computation is more and more popular in electronic bidding, anonymous voting, and online auction. Privacy preserving sequencing problem which is an essential link is regarded as the core issue in these applications. However, due to the difficulties of solving multiparty privacy preserving sequencing problem, related secure protocol is extremely rare. In order to break this deadlock, this paper first presents an efficient secure multiparty computation protocol for the general privacy-preserving sequencing problem based on symmetric homomorphic encryption. The result is of value not only in theory, but also in practice

An Efficient Generalizable Framework for Visuomotor Policies via Control-aware Augmentation and Privilege-guided Distillation

Visuomotor policies, which learn control mechanisms directly from high-dimensional visual observations, confront challenges in adapting to new environments with intricate visual variations. Data augmentation emerges as a promising method for bridging these generalization gaps by enriching data variety. However, straightforwardly augmenting the entire observation shall impose excessive burdens on policy learning and may even result in performance degradation. In this paper, we propose to improve the generalization ability of visuomotor policies as well as preserve training stability from two aspects: 1) We learn a control-aware mask through a self-supervised reconstruction task with three auxiliary losses and then apply strong augmentation only to those control-irrelevant regions based on the mask to reduce the generalization gaps. 2) To address training instability issues prevalent in visual reinforcement learning (RL), we distill the knowledge from a pretrained RL expert processing low-level environment states, to the student visuomotor policy. The policy is subsequently deployed to unseen environments without any further finetuning. We conducted comparison and ablation studies across various benchmarks: the DMControl Generalization Benchmark (DMC-GB), the enhanced Robot Manipulation Distraction Benchmark (RMDB), and a specialized long-horizontal drawer-opening robotic task. The extensive experimental results well demonstrate the effectiveness of our method, e.g., showing a 17\% improvement over previous methods in the video-hard setting of DMC-GB

A targeted proteomics screen reveals serum and synovial fluid proteomic signature in patients with gout

ObjectiveTo characterize the inflammatory proteome in both serum and synovial fluid (SF) of patients with gout, in comparison to healthy controls and individuals with osteoarthritis (OA), by utilizing a high-quality, high-throughput proteomic analysis technique.MethodsUsing the Olink Target 48 Inflammation panel, we measured serum concentrations of 45 inflammatory proteins in gout, OA, and healthy controls. We analyzed protein levels in SF samples from gout and OA, performed ROC curve analyses to identify diagnostic biomarkers, evaluate efficacy, and set cut-off values. Additionally, A protein-protein interaction (PPI) network was used to study protein relationships and significance.ResultsWe have delineated the proteomic landscape of gout and identified 20 highly differentially expressed proteins (DEPs) in the serum of gout patients in comparison to that of healthy controls, which included VEGF-A, MMP-1, TGF-α, and OSM with corresponding area under the curve (AUC) values of 0.95, 0.95, 0.92, and 0.91 respectively. For the analysis of synovial fluid, 6 proteins were found to be elevated in gout in contrast to osteoarthritis (OA), among which IP-10, VEGF-A, IL-8, and MIP-3β had corresponding AUC values of 0.78, 0.78, 0.76, and 0.75 respectively. The protein-protein interaction (PPI) network analysis identified significantly prominent pathways in gout.ConclusionThis research marks a significant advancement in elucidating the inflammatory profile present in the serum and synovial fluid of individuals suffering from gout. Our discoveries have identified several novel proteins in both serum and synovial fluid that are potential biomarkers for diagnostic purposes and are believed to have critical roles as pathogenic factors in the pathophysiology of gout

Increased Reactive Oxygen Species Production and Lower Abundance of Complex I Subunits and Carnitine Palmitoyltransferase 1B Protein Despite Normal Mitochondrial Respiration in Insulin-Resistant Human Skeletal Muscle

OBJECTIVE The contribution of mitochondrial dysfunction to skeletal muscle insulin resistance remains elusive. Comparative proteomics are being applied to generate new hypotheses in human biology and were applied here to isolated mitochondria to identify novel changes in mitochondrial protein abundance present in insulin-resistant muscle. RESEARCH DESIGN AND METHODS Mitochondria were isolated from vastus lateralis muscle from lean and insulin-sensitive individuals and from obese and insulin-resistant individuals who were otherwise healthy. Respiration and reactive oxygen species (ROS) production rates were measured in vitro. Relative abundances of proteins detected by mass spectrometry were determined using a normalized spectral abundance factor method. RESULTS NADH- and FADH2-linked maximal respiration rates were similar between lean and obese individuals. Rates of pyruvate and palmitoyl-dl-carnitine (both including malate) ROS production were significantly higher in obesity. Mitochondria from obese individuals maintained higher (more negative) extramitochondrial ATP free energy at low metabolic flux, suggesting that stronger mitochondrial thermodynamic driving forces may underlie the higher ROS production. Tandem mass spectrometry identified protein abundance differences per mitochondrial mass in insulin resistance, including lower abundance of complex I subunits and enzymes involved in the oxidation of branched-chain amino acids (BCAA) and fatty acids (e.g., carnitine palmitoyltransferase 1B). CONCLUSIONS We provide data suggesting normal oxidative capacity of mitochondria in insulin-resistant skeletal muscle in parallel with high rates of ROS production. Furthermore, we show specific abundance differences in proteins involved in fat and BCAA oxidation that might contribute to the accumulation of lipid and BCAA frequently associated with the pathogenesis of insulin resistance. </jats:sec

Outlook on ecologically improved composites for aviation interior and secondary structures

Today, mainly man-made materials such as carbon and glass fibres are used to produce composite parts in aviation. Renewable materials such as natural fibres or bio-sourced resin systems have not found their way into aviation, yet. The project ECO-COMPASS aims to evaluate the potential applications of ecologically improved composite materials in the aviation sector in an international collaboration of Chinese and European partners. Natural fibres such as flax and ramie will be used for different types of reinforcements and sandwich cores. Furthermore, the bio-based epoxy resins to substitute bisphenol-A based epoxy resins in secondary structures are under investigation. Adapted material protection technologies to reduce environmental influence and to improve fire resistance are needed to fulfil the demanding safety requirements in aviation. Modelling and simulation of chosen eco-composites aims for an optimized use of materials while a life cycle assessment aims to prove the ecological advantages compared to synthetic state-of-the-art materials. In this paper, the status of selected ecologically improved materials will be presented with an outlook for potential application in interior and secondary structures