Modeling past event feedback through biomarker dynamics in the multi-state event analysis for cardiovascular disease data

In cardiovascular studies, we often observe ordered multiple events along disease progression, which are essentially a series of recurrent events and terminal events with competing risk structure. One of the main interest is to explore the event specific association with the dynamics of longitudinal biomarkers. New Statistical challenge arises when the biomarkers carry information from the past event history, providing feedbacks for the occurrences of future events, and particularly when these biomarkers are only intermittently observed with measurement errors. In this paper, we propose a novel modelling framework where the recurrent events and terminal events are modelled as multi-state process and the longitudinal covariates that account for event feedbacks are described by random effects models. Considering the nature of long-term observation in cardiac studies, flexible models with semiparametric coefficients are adopted. To improve computation efficiency, we develop an one-step estimator of the regression coefficients and derive their asymptotic variances for the computation of the confidence intervals, based on the proposed asymptotically unbiased estimating equation. Simulation studies show that the naive estimators which either ignore the past event feedbacks or the measurement errors are biased. Our method achieves better coverage probability, compared to the naive methods. The model is motivated and applied to a dataset from the Atherosclerosis Risk in Communities Study

Status and Problems in Location Model Research for Guidance Signage in Comprehensive Passenger Transportation Hubs

Internal guidance signs are critical for the normal operation of a comprehensive passenger transportation hub. In the present paper, the procedures, methods and restrictions on the development of guidance sign locations are summarized in terms of the planning and design method of guidance signs and an evaluation of guidance sign service manuals after a sorting and analysis of relevant literature. The results show that the existing location model fails to quantitatively describe the behavior characteristics of massive passenger flows and results in the spatial planning and design of guidance signage being inaccessible for many in mass passenger transit and spatial topological networks resulting from 3D hub architecture make the constraint conditions of location models more complex. Sophisticated guidance signs and location models responding to behavioral characteristics and spatial topological networks will be a trend of interest in the optimal layout of future comprehensive passenger transportation hubs

Competition of zinc ion for the [2Fe-2S] cluster binding site in the diabetes drug target protein mitoNEET

Human mitochondrial protein mitoNEET is a novel target of type II diabetes drug pioglitazone, and contains a redox active [2Fe-2S] cluster that is hosted by a unique ligand arrangement of three cysteine and one histidine residues. Here we report that zinc ion can compete for the [2Fe-2S] cluster binding site in human mitoNEET and potentially modulate the physiological function of mitoNEET. When recombinant mitoNEET is expressed in Escherichia coli cells grown in M9 minimal media, purified mitoNEET contains very little or no iron-sulfur clusters. Addition of exogenous iron or zinc ion in the media produces mitoNEET bound with a [2Fe-2S] cluster or zinc, respectively. Mutations of the amino acid residues that hosting the [2Fe-2S] cluster in mitoNEET diminish the zinc binding activity, indicating that zinc ion and the [2Fe-2S] cluster may share the same binding site in mitoNEET. Finally, excess zinc ion effectively inhibits the [2Fe-2S] cluster assembly in mitoNEET in E. coli cells, suggesting that zinc ion may impede the function of mitoNEET by blocking the [2Fe-2S] cluster assembly in the protein. Copyright © Springer Science+Business Media, LLC. 2012

Pedestrian Guiding Signs Optimization for Airport Terminal

The pedestrian guiding sign (PGS) is used to lead people within the transportation terminal to their directions efficiently and without boundaries. In this paper, we aim to optimize the guiding signs for people in the comprehensive transportation terminal with a mathematical model, which describes the pedestrian's reaction, judgment, and perception of the outline about the guiding signs, as well as pedestrian's moving status through self-organized characteristic behavior. Furthermore, the model also reflects the information intensity of the guiding signs within the pedestrian's visual field which is taken as the influence level score of PGS. In order to solve the model, cellular automation (CA) is employed to simulate the characteristics of the pedestrians such as crowd moving and sign selection

Submission of Evidence on Online Violence Against Women to the UN Special Rapporteur on Violence Against Women, its Causes and Consequences, Dr Dubravka Šimonović

Figure S1. B3GALNT2 levels determined by W.B. and ROC curve. a–c Relative mRNA expression of B3GALNT2 in HCC tumor tissues and normal liver tissues obtained from GSE76427, GSE36376, and TCGA-LIHC datasets. d Western blot analysis of B3GALNT2 levels in 24 pairs of HCC tissues. T HCC tumor tissue, N adjacent non-tumor tissue. e ROC curve analysis of the sensitivity and specificity for the predictive value of TNM model, B3GALNT2 expression, and the combination model. (TIFF 546 kb

Characteristics and metabolic potential of biliary microbiota in patients with giant common bile duct stones

BackgroundEndoscopic retrograde cholangiopancreatography (ERCP) is an effective minimally invasive operation for the management of choledocholithiasis, while successful extraction is hampered by large diameter of stones. Emerging studies have revealed the close correlation between biliary microbiota and common bile duct stones (CBDS). In this study, we aimed to investigate the community characteristics and metabolic functions of biliary microbiota in patients with giant CBDS.MethodsEligible patients were prospectively enrolled in this study in First Affiliated Hospital of Soochow University from February 2022 to October 2022. Bile samples were collected through ERCP. The microbiota was analyzed using 16S rRNA sequencing. Metabolic functions were predicted by PICRUSTs 2.0 calculation based on MetaCyc database. Bile acids were tested and identified using ultra performance liquid chromatography-tandem mass spectrometry.ResultsA total of 26 patients were successfully included into final analysis, 8 in giant stone (GS) group and 18 in control group. Distinct biliary microbial composition was identified in patients with giant CBDS, with a significantly higher abundance of Firmicutes at phylum level. The unique composition at genus level mainly consisted of Enterococcus, Citrobacter, Lactobacillus, Pyramidobacter, Bifidobacterium and Shewanella. Pyramidobacter was exclusively found in GS group, along with the absence of Robinsoniella and Coprococcus. The contents of free bile acids were significantly higher in GS group, including cholic acid (98.39μmol/mL vs. 26.15μmol/mL, p=0.035), chenodesoxycholic acid (54.69μmol/mL vs. 5.86μmol/mL, p=0.022) and ursodeoxycholic acid (2.70μmol/mL vs. 0.17μmol/mL, p=0.047). Decreasing tendency of conjugated bile acids were also observed. Metabolic pathways concerning cholelithiasis were abundant in GS group, including geranylgeranyl diphosphate biosynthesis, gluconeogenesis, glycolysis and L-methionine biosynthesis.ConclusionsThis study demonstrated the community structure and metabolic potential of biliary microbiota in patients with giant CBDS. The unique biliary microbial composition holds valuable predictive potential for clinical conditions. These findings provide new insights into the etiology of giant CBDS from the perspective of biliary microbiota

Achievable Rates for Full-Duplex Massive MIMO Systems With Low-Resolution ADCs/DACs

This paper investigates the uplink and downlink achievable rates of full-duplex (FD) massive multi-input-multi-output (MIMO) systems in which low-resolution analog-to-digital converters/digital-to-analog converters (ADCs/DACs) are employed and maximum ratio combining/maximum ratio transmission processing are adopted. Then, employing an additive quantization noise model, we derive approximate expressions of the uplink and downlink achievable rates, in which the effect of the quantization error, the loop interference, and the inter-user interference is considered. The theoretical results show that using proper power scaling law and more antennas can eliminate the interference and the noise. Furthermore, under the fixed number of antennas, the uplink and downlink approximate achievable rates will become a constant, as the number of quantization bits tends to infinity. Increasing the resolution of ADCs/DACs will limitedly improve the system performance but cause excessive overhead and power consumption, so adopting low-resolution ADCs/DACs in FD massive MIMO systems is sensible