Bootstrap test results for multiple intermediary models.

Bootstrap test results for multiple intermediary models.</p

The conceptual model based on previous research and theory.

The conceptual model based on previous research and theory.</p

Multiple stepwise regression results.

BackgroundSubjective well-being has a significant impact on an individual’s physical and mental health. Socioeconomic status, class identity, and social activity participation play important roles in subjective well-being. Therefore, the aim of this study was to uncover the mechanisms through which these factors influence subjective well-being.MethodsA total of 1926 valid samples were recruited using the Chinese General Social Survey 2021 (CGSS 2021). The Chinese Citizen’s Subjective Well-Being Scale (SWBS-CC) was employed to assess subjective well-being. Socioeconomic status was measured using income and education, and class identity and social activity participation were measured using Likert scales. Pearson correlation analysis and the chain mediation model were conducted to explore the relationship between these factors. Finally, the Bootstrap method was used to examine the path coefficients.ResultsA significant correlation was found between socioeconomic status, class identity, social activity, and subjective well-being (p ConclusionsThe study showed that socioeconomic status, class identity, and social activity had significant effects on subjective well-being. Class identity and social activity partially mediated the effects of socioeconomic status on subjective well-being, and they had a chain mediating effect between socioeconomic status and subjective well-being. Therefore, policymakers have the opportunity to enhance subjective well-being in lower socioeconomic status groups by promoting individual class identity and encouraging greater social activity participation.</div

The results of Pearson correlation analysis.

BackgroundSubjective well-being has a significant impact on an individual’s physical and mental health. Socioeconomic status, class identity, and social activity participation play important roles in subjective well-being. Therefore, the aim of this study was to uncover the mechanisms through which these factors influence subjective well-being.MethodsA total of 1926 valid samples were recruited using the Chinese General Social Survey 2021 (CGSS 2021). The Chinese Citizen’s Subjective Well-Being Scale (SWBS-CC) was employed to assess subjective well-being. Socioeconomic status was measured using income and education, and class identity and social activity participation were measured using Likert scales. Pearson correlation analysis and the chain mediation model were conducted to explore the relationship between these factors. Finally, the Bootstrap method was used to examine the path coefficients.ResultsA significant correlation was found between socioeconomic status, class identity, social activity, and subjective well-being (p ConclusionsThe study showed that socioeconomic status, class identity, and social activity had significant effects on subjective well-being. Class identity and social activity partially mediated the effects of socioeconomic status on subjective well-being, and they had a chain mediating effect between socioeconomic status and subjective well-being. Therefore, policymakers have the opportunity to enhance subjective well-being in lower socioeconomic status groups by promoting individual class identity and encouraging greater social activity participation.</div

Ultrastructural characteristics of the GEE cell line using TEM.

<p>(A and B) Morphology of the cell line was cuboidal and nucleus (N) was large and irregular containing a large prominent nucleolus (Nu). (C and D) Cell surface was covered by abundant microvilli (MV) of irregular shape. Cytoplasm had a significant quantity of secretory vesicles (SV), lipid droplets (LD) and endoplasmic reticulum (ER).</p

Analysis of exogenous genes expression in the GEE cell line by IFA.

<p>The GEE cell line was mock-transfected with pcHA or transfected with either pcHA_GPV-VP3, pcHA_DHAV-VP1 or pcHA_NDV-F. At 48 post transfection, cells were fixed with 2% paraformaldehyde for 15 min and permeabilized with 0.5% Triton X-100 in PBS for 5 min. Monoclonal anti-HA antibody and hyperimmune serum from injected chicken with respective viruses were used as a primary antibody in (panel; A) and (panel; B), respectively. While Alexa Fluor^® 488 (Green staining; Santa Cruz Biotech) and anti-chicken IgY (IgG) (whole molecule)—FITC antibody produced in rabbit were used as secondary antibodies. Nuclei were stained with DAPI (Vector Laboratories).</p

Susceptibility of the GEE cell line to GPV, DHAV and NDV infection.

<p>The CPEs following GPV, DHAV and NDV infection of the GEE cell line in the presence of uninfected cells as a mock were evaluated (A, B, and C; upper panel, respectively). Extensive CPEs associated with a rounding of the cells and destruction of the monolayer was observed at 96, 48, and 72 hpi with GPV, DHAV and NDV, respectively. Kinetics analysis of GPV-, DHAV- and NDV-infected GEE cells (A, B, and C; lower panel, respectively). Supernatant from infected cells with respective viruses was collected at diffident time points and titers of each virus were determined using TCID₅₀ assay. The data are the Mean ± S.E. from three independent experiments.</p

Morphology of the DEE cell line at different stages of the culture process.

<p>(A) Initial culture of the goose embryo tissue. (B) After several treatment of primary culture with collagenase, tightly packed epithelial-like cell colonies were observed. (C) Existence of cells with epithelial-like morphology after serial passages. (D) After freezing and thawing, the DEE cell line displayed a uniform shape of the epithelial cells.</p

Standard curves of the qPCR and replication kinetics of the propagated viruses in the GEE cells.

<p>(A, B, and C; upper panel) For stander curves of the qPCR, the purified recombinant plasmids DNA of pC_VP3, _VP1, and F were used as standard DNA templets. The threshold cycle was plotted against the copy number of the standard DNA templets. Y represents the threshold cycle and R² represents correlation coefficient. Growth kinetics of GPV, DHAV and NDV viruses in the GEE cell line (A, B, and C; lower panel, respectively). The GEE cell line was infected with indicated viruses at a moi of 0.1 and cellular RNA were collected at different time points (12, 24, 36, 48, 72, 96, 108, and 120 hpi) and then reverse transcribed into cDNA. The viral copy numbers were measured by qPCR. All samples were performed in three independent times and errors bars represent standard deviations.</p

Growth properties of the GEE cell line.

<p>(A) Cellular growth curve of the GEE cell line. Cells at passages 20, 45 and 65 were grown at 37°C in a 6-well plate containing 2 ml of the M199 medium supplemented with 10% fetal bovine serum until they reach confluency and then were collected at indicated time points for counting. Errors bars represent standard deviations from three independent experiments. (B) Flow cytometry was used to analyze the cell cycle of the GEE cell line. Cellular DNA was stained with the Propidium Iodide fluorescent dye and fluorescence intensity of cells was measured in the G1, S and G2 phases of the cell cycle.</p