Objective:To explore the dynamic temporal variability of brain functional networks in individuals with internet gaming disorder(IGD)using dynamic functional connectivity density(dFCD).Methods:From January 2019 to December 2021, resting-state functional magnetic resonance imaging data were recruited from 55 patients with IGD and demographically matched 50 healthy controls.Data analysis was performed by IBM SPSS 21.0 software. The functional connectivity density(FCD) combined with sliding window analysis was employed to calculate the temporal variability of global functional connectivity.FCD in whole brain was further devided into ipsilateral and cotralateral parts.The temporal variability of dFCD was further quantified utilizing the standard deviations of whole brain, intra-, and inter-hemispheric FCD. Finally, Pearson correlation analysis was performed between dFCD variance in differential brain regions and clinical behaviors.Results:The inter-hemispheric dFCD in the left posterior cingulate cortex(-0.16±0.24) and the left precuneus(-0.08±0.23) in patients with IGD were lower that those in healthy controls(0.002±0.260, 0.12±0.36)( t=-3.502, -4.160, both P<0.05).And the intra-hemispheric dFCD in the left calcarine, the left precuneus, and the left posterior cingulate cortex in patients with IGD were lower that those in healthy controls( t=-3.809, -4.360, -3.561, all P<0.05).Moreover, abnormal global dFCD variability of the calcarine and ipsilateral dFCD variability of the PCC negatively correlated with the severity of IGD( r=-0.380, -0.413, both P<0.05). Conclusion:Patients with IGD show intra-and inter-hemispheric dFCD differences in the visual attention network and default mode network, which may respond to the underlying neurobiological basis for the presence of cognitive dysfunction and impaired concentration.

Objective To explore the mechanism and effects of Basonuclin 1(BNC1)on the migration and invasion abilities of lung squamous cell carcinoma.Methods Bioinformatics technology was used to analyze the expression patterns and survival impact of BNC1 in patients with lung squamous cell carcinoma in online databases;Tissue microarrays were stained by immunohistochemistry assay and analyzed for BNC1 protein level.Cell lines for lung squamous cell carcinoma with high and low BNC1 expression were screened in the Cancer Cell Line Encyclopedia(CCLE)database.Wound healing experiment and transwell assay were performed on lung squamous cell carcinoma cell models with knockdown and overexpression of BNC1,and the migration and invasion rates of each cell line were detected;Quantitative reverse transcription PCR(RT-qPCR)was used to validate the migration and invasion of 10 highly related genes derived from literature.Western blotting was used to validate the selected regulatory genes.Results Bioinformatics technology found that BNC1 was highly expressed in lung squamous cell carcinoma tissues and was associated with lower survival rate(P=0.047).The expression of BNC1 in lung squamous cell carcinoma was higher than that in paracancerous tissues(P＜0.05).BNC1 had higher expression in the H226 cells and lower expression in the SK-MES1 cells.BNC1 knockdown inhibited the migration and invasion abilities of lung squamous cell carcinoma cells(P＜0.05),and BNC1 overexpression enhanced the migration and invasion abilities of lung squamous cell carcinoma cells(P＜0.05).Screening of BNC1 downstream regulatory molecules at the mRNA level showed that CDH1 was decreased when BNC1 was overexpressed(P＜0.05),and increased when BNC1 was knocked down(P＜0.05).The results of mRNA level were consistent with the results verified by Western blotting(P＜0.05).Conclusion BNC1 may be a gene predicting poor prognosis for lung squamous cell carcinoma patients,and BNC1 may likely to promote cell migration and invasion of lung squamous cell carcinoma by downregulating CDH1 expression.

As an important means of data visualization, statistical graphics can potentially convey scientific findings and key points. However, authoritative graphic guidelines are lacking currently, and medical researchers still have shortcomings in mastering graphic design principles and drawing skills, which may obscure some key research findings and even misinterpret the research findings. Based on statistical examples, we summarized the essential elements and design principles of statistical graphics to address these challenges and to provide a reference for medical researchers.

Objective:To understand the infection status and characteristics of 2019-nCoV infection in different areas in China after the adjustment of the national prevention and control strategy of 2019-nCoV infection.Methods:The online questionnaire survey was conducted among staff and students of 39 public health schools in 23 provinces (municipalities) in China from 12: 00 on December 20 to 9: 00 on December 23, 2022. The infection rates in staff and students in all the provinces were estimated. The risk factors, demographic and clinical characteristics of 2019-nCoV infections were explored.Results:A total of 28 901 valid questionnaires were obtained (26 355 from students and 2 546 from staff) with a qualified rate of 94.3%. The infection rates varied greatly among provinces and cities; the infection rates in students and staff in Beijing reached 78.55% and 76.40%, respectively. Infection rates in students and staff in Tianjin and Hebei also exceeded 65.00%, and 96.76% of infections occurred on and after December 1, 2022. Students had lower risk for the infection compared with staff ( OR=0.72, 95% CI: 0.60-0.86). Compared with age group ≤20 years, the OR of age groups 21-30, 31-40, 41-50, 51-60 and > 60 years were 1.22 (95% CI: 1.14-1.30), 1.54 (95% CI: 1.30-1.84), 1.25 (95% CI: 0.99-1.58), 1.29 (95% CI: 0.94-1.78) and 1.19 (95% CI: 0.51-2.80), respectively. The longer the period after the last vaccination, the higher the risk for the infection. Compared with those who received the last vaccination in the past 3 months, the OR of those who received the last vaccination in the past 4-6 months, 7-9 months, 10-12 months, 13-15 months and ≥16 months were 1.56 (95% CI: 1.34-1.82), 1.59 (95% CI: 1.36-1.86), 1.67 (95% CI: 1.45-1.93), 1.86 (95% CI:1.58-2.19) and 2.46 (95% CI: 2.09-2.90), respectively. Compared with those living alone, the OR of those living with 1-2, 3-4 and ≥5 roommates were 17.55 (95% CI: 15.91-19.39), 20.22 (95% CI: 18.25-22.43) and 11.78 (95% CI: 10.40-13.36), respectively. Only 5.94% of the staff and 7.19% of the students reported asymptomatic infections. Among those with symptoms, 88.18% of students and 85.65% of staff reported symptom of fever. Conclusions:The transmission dynamics of 2019-nCoV infection varied significantly across the country. The speed of transmission of 2019-nCoV and clinical severity of the infection were far beyond our knowledge. Organized epidemiological survey should be regularly carried out to provide reliable data support for more accurate prediction of the epidemic and medical resource allocation.