DMFSGD: A Decentralized Matrix Factorization Algorithm for Network Distance Prediction

The knowledge of end-to-end network distances is essential to many Internet applications. As active probing of all pairwise distances is infeasible in large-scale networks, a natural idea is to measure a few pairs and to predict the other ones without actually measuring them. This paper formulates the distance prediction problem as matrix completion where unknown entries of an incomplete matrix of pairwise distances are to be predicted. The problem is solvable because strong correlations among network distances exist and cause the constructed distance matrix to be low rank. The new formulation circumvents the well-known drawbacks of existing approaches based on Euclidean embedding. A new algorithm, so-called Decentralized Matrix Factorization by Stochastic Gradient Descent (DMFSGD), is proposed to solve the network distance prediction problem. By letting network nodes exchange messages with each other, the algorithm is fully decentralized and only requires each node to collect and to process local measurements, with neither explicit matrix constructions nor special nodes such as landmarks and central servers. In addition, we compared comprehensively matrix factorization and Euclidean embedding to demonstrate the suitability of the former on network distance prediction. We further studied the incorporation of a robust loss function and of non-negativity constraints. Extensive experiments on various publicly-available datasets of network delays show not only the scalability and the accuracy of our approach but also its usability in real Internet applications.Comment: submitted to IEEE/ACM Transactions on Networking on Nov. 201

Decentralized Prediction of End-to-End Network Performance Classes

In large-scale networks, full-mesh active probing of end-to-end performance metrics is infeasible. Measuring a small set of pairs and predicting the others is more scalable. Under this framework, we formulate the prediction problem as matrix completion, whereby unknown entries of an incomplete matrix of pairwise measurements are to be predicted. This problem can be solved by matrix factorization because performance matrices have a low rank, thanks to the correlations among measurements. Moreover, its resolution can be fully decentralized without actually building matrices nor relying on special landmarks or central servers. In this paper we demonstrate that this approach is also applicable when the performance values are not measured exactly, but are only known to belong to one among some predefined performance classes, such as "good" and "bad". Such classification-based formulation not only fulfills the requirements of many Internet applications but also reduces the measurement cost and enables a unified treatment of various performance metrics. We propose a decentralized approach based on Stochastic Gradient Descent to solve this class-based matrix completion problem. Experiments on various datasets, relative to two kinds of metrics, show the accuracy of the approach, its robustness against erroneous measurements and its usability on peer selection.Peer reviewe

Meta-analysis of preclinical studies of mesenchymal stromal cells to treat rheumatoid arthritis.

BackgroundThis study aims to evaluate the quality of preclinical data, determine the effect sizes, and identify experimental measures that inform efficacy using mesenchymal stromal (or stem) cells (MSC) therapy in animal models of rheumatoid arthritis (RA).MethodsLiterature searches were performed on MSC preclinical studies to treat RA. MSC treatment effect sizes were determined by the most commonly used outcome measures, including paw thickness, clinical score, and histological score.FindingsA total of 48 studies and 94 treatment arms were included, among which 42 studies and 79 treatment arms reported that MSC improved outcomes. The effect sizes of RA treatments using MSC, when compared to the controls, were: paw thickness was ameliorated by 53.6% (95% confidence interval (CI): 26.7% -80.4%), histological score was decreased by 44.9% (95% CI: 33.3% -56.6%), and clinical score was decreased by 29.9% (95% CI: 16.7% -43.0%). Specifically, our results indicated that human umbilical cord derived MSC led to large improvements of the clinical score (-42.1%) and histological score (-51.4%).InterpretationTo the best of our knowledge, this meta-analysis is to quantitatively answer whether MSC represent a robust RA treatment in animal models. It suggests that in preclinical studies, MSC have consistently exhibited therapeutic benefits. The findings demonstrate a need for considering variations in different animal models and treatment protocols in future studies using MSC to treat RA in humans to maximise the therapeutic gains in the era of precision medicine.FundsNIH [1DP2CA195763], Baylx Inc.: BI-206512, NINDS/NIH Training Grant [Award# NS082174]

Hepatoprotective mechanism of Silybum marianum on nonalcoholic fatty liver disease based on network pharmacology and experimental verification

The study aimed to identify the key active components in Silybum marianum (S. marianum) and determine how they protect against nonalcoholic fatty liver disease (NAFLD). TCMSP, DisGeNET, UniProt databases, and Venny 2.1 software were used to identify 11 primary active components, 92 candidate gene targets, and 30 core hepatoprotective gene targets in this investigation, respectively. The PPI network was built using a string database and Cytoscape 3.7.2. The KEGG pathway and GO biological process enrichment, biological annotation, as well as the identified hepatoprotective core gene targets were analyzed using the Metascape database. The effect of silymarin on NAFLD was determined using H&E on pathological alterations in liver tissues. The levels of liver function were assessed using biochemical tests. Western blot experiments were used to observe the proteins that were expressed in the associated signaling pathways on the hepatoprotective effect, which the previous network pharmacology predicted. According to the KEGG enrichment study, there are 35 hepatoprotective signaling pathways. GO enrichment analysis revealed that 61 biological processes related to the hepatoprotective effect of S. marianum were identified, which mainly involved in response to regulation of biological process and immune system process. Silymarin was the major ingredient derived from S. marianum, which exhibited the hepatoprotective effect by reducing the levels of ALT, AST, TC, TG, HDL-C, LDL-C, decreasing protein expressions of IL-6, MAPK1, Caspase 3, p53, VEGFA, increasing protein expression of AKT1. The present study provided new sights and a possible explanation for the molecular mechanisms of S. marianum against NAFLD

Latitudinal differences in early growth of largehead hairtail (Trichiurus japonicus) in relation to environmental variables

Largehead hairtail (Trichiurus japonicus) in the China Seas shows an increasing catch trend, despite continued overexploitation, which could be attributed to improved recruitment as a result of strengthened early growth. To understand the early growth variability of largehead hairtail, we examined the linkages between early growth, as revealed by otolith microstructure, and the associated environmental variables over both spatial and temporal scales. Young‐of‐the‐Year largehead hairtail were collected from three regions in the Bohai, Yellow and East China Seas between 29° and 39° N. Daily increment widths of sagittal otoliths were measured and used as a proxy for somatic growth. We found two spawning cohorts, Spring‐ and Summer‐spawned cohorts, that showed latitudinal differences in both mean growth and growth pattern. The transition time from larval to juvenile stage was identified at around 40 days. Daily increment widths of two cohorts showed similar growth pattern in the first 40 days, while location had a marked effect on daily growth over 41–110 days. This suggests physiologically constrained growth pattern in larval stage, but more plastic growth subject to habitat‐specific influences in juvenile stage. The gradient forest analysis identified sea bottom temperature, vertical temperature gradient, and sea surface salinity, as the most important variables in determining early growth. Latitudinal differences in early growth pattern and their response to environmental variables suggest adaptive plasticity of early growth, which has notable implication for the management and sustainable utilization of this important but heavily exploited resource in the China Seas.acceptedVersio

Effect of Hyperglycemia at Presentation on Outcomes in Acute Large Artery Occlusion Patients Treated With Solitaire Stent Thrombectomy

Background: Sporadic data showed hyperglycemia at presentation is associated with poor outcomes in patients with acute ischemic stroke (AIS) under mechanical thrombectomy (MT) treatment.Objective: This study aims to evaluate the relationship of admission hyperglycemia and outcomes in patients treated with solitaire stent thrombectomy.Methods: This multicenter prospective study registered patients with AIS due to anterior circulation large vessel occlusion (LVO) suitable for MT with Solitaire stent retriever. We analyzed the influence of admission hyperglycemia (≥7.8 mmol/L) and serum glucose on functional independence which is defined as modified Rankin Scale score (mRS) of 0–2, symptomatic intracranial hemorrhage (sICH) and several outcomes of interest using univariable and multiple logistic regression analysis.Results: This study involved 17 stroke centers across China and consecutively recruited 149 patients. Patients with hyperglycemia at presentation less frequently exhibited a functional independence at 3 months than patients without hyperglycemia (22.2 vs. 66.4%; odds ratio 0.75, 95% confidence interval 0.61–0.92; P = 0.005). Higher glucose levels were correlated with worse outcome (per 1 mmol/L increase in glucose: odds ratio for mRS score 0–2 at 3 months 0.17, 95% confidence interval 0.06–0.45; P < 0.001) at 3 months and sICH (per 1 mmol/L increase in glucose: odds ratio for sICH was 8.2, 95% confidence interval 1.13–29.57; P < 0.001) after thrombectomy.Conclusions: Higher admission serum glucose and hyperglycemia were independently correlated with lower functional independence at 3 months in patients treated with Solitaire stent thrombectomy of anterior circulation LVO. Higher admission serum glucose was also associated with sICH after thrombectomy

Exploring the Midgut Transcriptome and Brush Border Membrane Vesicle Proteome of the Rice Stem Borer, Chilo suppressalis (Walker)

The rice stem borer, Chilo suppressalis (Walker) (Lepidoptera: Pyralidae), is one of the most detrimental pests affecting rice crops. The use of Bacillus thuringiensis (Bt) toxins has been explored as a means to control this pest, but the potential for C. suppressalis to develop resistance to Bt toxins makes this approach problematic. Few C. suppressalis gene sequences are known, which makes in-depth study of gene function difficult. Herein, we sequenced the midgut transcriptome of the rice stem borer. In total, 37,040 contigs were obtained, with a mean size of 497 bp. As expected, the transcripts of C. suppressalis shared high similarity with arthropod genes. Gene ontology and KEGG analysis were used to classify the gene functions in C. suppressalis. Using the midgut transcriptome data, we conducted a proteome analysis to identify proteins expressed abundantly in the brush border membrane vesicles (BBMV). Of the 100 top abundant proteins that were excised and subjected to mass spectrometry analysis, 74 share high similarity with known proteins. Among these proteins, Western blot analysis showed that Aminopeptidase N and EH domain-containing protein have the binding activities with Bt-toxin Cry1Ac. These data provide invaluable information about the gene sequences of C. suppressalis and the proteins that bind with Cry1Ac

Triangle Inequality Violation Avoidance in Internet Coordinate Systems

FP7 ECOD