Objective:To examine the interaction between interpersonal issues and eating behavior problems among college freshmen, and to identify core psychological factors and potential pathways that drive eating behavior.Methods:In October 2019, a total of 5 073 college freshmen from a university in Shanghai were recruited as participants. Their general demographic data were collected, and they were evaluated using the eating disorder examination questionnaire 6.0 (EDE-Q 6.0) and inventory of interpersonal problems-32(IIP-32).Descriptive analyses were performed using SPSS 24.0 software.A regularized partial correlation network was constructed using the graphical least absolute shrinkage and selection operator (GLASSO) in R(v4.2.3) software. A Bayesian network analysis (BNA) was conducted to build a directed network, aiming to identify core driving factors and key psychological mechanisms.Results:Regularized partial correlation network identified shape concern as the most central node, with the highest strength centrality(1.32) and expected influence(1.20). It showed the highest bridge strength with dominance/control (0.22, 0.21), linking the interpersonal and eating behavior modules. Directed network analysis indicated that low self-confidence was the upstream node influencing social inhibition and cold/ distant relationships, indirectly affecting eating disorder.Within the eating module, shape concern and weight concern predicted eating preoccupation and dietary restraint, forming a pathway structure from eating cognition to behavior.The network demonstrated good stability (CS-coefficient=0.75).Conclusion:Shape concern is the core mechanism underlying eating problems in college freshmen. Low self-confidence contributes indirectly via interpersonal dysfunction. Dominance/control and shape concern bridge interpersonal and eating domains, providing key targets for early prevention and intervention.

Objective:To examine the interaction between interpersonal issues and eating behavior problems among college freshmen, and to identify core psychological factors and potential pathways that drive eating behavior.Methods:In October 2019, a total of 5 073 college freshmen from a university in Shanghai were recruited as participants. Their general demographic data were collected, and they were evaluated using the eating disorder examination questionnaire 6.0 (EDE-Q 6.0) and inventory of interpersonal problems-32(IIP-32).Descriptive analyses were performed using SPSS 24.0 software.A regularized partial correlation network was constructed using the graphical least absolute shrinkage and selection operator (GLASSO) in R(v4.2.3) software. A Bayesian network analysis (BNA) was conducted to build a directed network, aiming to identify core driving factors and key psychological mechanisms.Results:Regularized partial correlation network identified shape concern as the most central node, with the highest strength centrality(1.32) and expected influence(1.20). It showed the highest bridge strength with dominance/control (0.22, 0.21), linking the interpersonal and eating behavior modules. Directed network analysis indicated that low self-confidence was the upstream node influencing social inhibition and cold/ distant relationships, indirectly affecting eating disorder.Within the eating module, shape concern and weight concern predicted eating preoccupation and dietary restraint, forming a pathway structure from eating cognition to behavior.The network demonstrated good stability (CS-coefficient=0.75).Conclusion:Shape concern is the core mechanism underlying eating problems in college freshmen. Low self-confidence contributes indirectly via interpersonal dysfunction. Dominance/control and shape concern bridge interpersonal and eating domains, providing key targets for early prevention and intervention.

Objective To set up loop-mediated isothermal amplification(RT-LAMP) method for quick detection of Schmallenbergvirus.Methods The S gene sequences of Schmallenbergvirus were downloaded from GenBank database and analyzed using MegAlign tools of software DNAStar.The outer primers and inner primers of LAMP were then designed according to their conservative region using software PrimerExplorer V4,and the reaction conditions were optimized.Results The results showed that the RTLAMP assay had a detection limit of 10 RNA copies.The primers used in this assay showed the specificity for Schmallenberg virus and did not amplify FMDV,BVDV,BTV,AKAV and VSV.Conclusion It is indicated the RT-LAMP method is a simple,rapid,accurate,sensitive and specific method for detecting Schmallenberg virus.This assay offers a new method and idea for detecting Schmallenberg virus.