Suchergebnisse

PurposeDue to the unintentional or even the intentional mistakes arising from a survey, the purpose of this paper is to present a data-driven method for detecting students' friendship network based on their daily behaviour data. Based on the detected friendship network, this paper further aims to explore how the considered network effects (i.e. friend numbers (FNs), structural holes (SHs) and friendship homophily) influence students' GPA ranking.Design/methodology/approachThe authors collected the campus smart card data of 8,917 sophomores registered in one Chinese university during one academic year, uncovered the inner relationship between the daily behaviour data with the friendship to infer the friendship network among students, and further adopted the ordered probit regression model to test the relationship between network effects with GPA rankings by controlling several influencing variables.FindingsThe data-driven approach of detecting friendship network is demonstrated to be useful and the empirical analysis illustrates that the relationship between GPA ranking andFNpresents an inverted "U-shape", richness inSHspositively affects GPA ranking, and making more friends within the same department will benefit promoting GPA ranking.Originality/valueThe proposed approach can be regarded as a new information technology for detecting friendship network from the real behaviour data, which is potential to be widely used in many scopes. Moreover, the findings from the designed empirical analysis also shed light on how to improve GPA rankings from the angle of network effect and further guide how many friends should be made in order to achieve the highest GPA level, which contributes to the existing literature.

Abstract
Background Chronic hydrocephalus is a common complication of aneurysmal subarachnoid hemorrhage (aSAH); however, the risk factors and the mechanisms underlying its occurrence have yet to be fully elucidated. The purpose of this study was to identify biomarkers that could be used to predict chronic hydrocephalus after aSAH and to investigate the relationships.
Methods We analyzed cerebrospinal fluid (CSF) samples from 19 patients with chronic hydrocephalus after aSAH and 44 controls without hydrocephalus after aSAH. Enzyme-linked immunosorbent assay was used to determine the levels of leucine-rich alpha-2-glycoprotein (LRG), transforming growth factor-β (TGF-β), Smad1, Smad4, Smad5, Smad8, activin receptor-like kinase 1 (Alk-1), activin receptor-like kinase 5 (Alk-5), P38, and TGF-β type II receptor (TGFßRII) in CSF samples.
Results In the CSF of patients with chronic hydrocephalus after aSAH, the levels of LRG, TGF-β, Alk-1, Smad5, and TGFßRII were significantly increased (p < 0.05) and the levels of Smad1, Smad4, and Smad8 were significantly decreased (p < 0.05). There were no significant differences between the two groups concerning the levels of P38 and Alk-5 (p > 0.05). The analysis also identified significant correlations between specific biomarkers: LRG and Smad1, LRG and Smad5, TGF-β and Alk-1, and Alk-1 and Smad4 (p < 0.05); the Pearson's correlation coefficients for these relationships were −0.341, 0.257, 0.256, and −0.424, respectively.
Conclusion The levels of LRG, TGF-β, Alk-1, TGFßRII, Smad1/5/8, and Smad4 in the CSF are potentially helpful as predictive biomarkers of chronic hydrocephalus after aSAH. Moreover, the LRG-TGF-β-Alk-1/TGFßRII-Smad1/5/8-Smad4 signaling pathway is highly likely to be involved in the pathogenic process of chronic hydrocephalus after aSAH.