Objective:This study aims to evaluate the performance of digital PCR (dPCR) detecting multiple and single copies genes of the Epstein-Barr virus (EBV) for nucleic acid quantification and explore their applicability in clinical settings.Methods:Compared the sensitivity, specificity, precision, lower limit of detection (LoD), and linearity for multicopy BamHI-W dPCR and single-copy EBNA1 dPCR systems. Linear regression analysis using the least squares method was employed to evaluate the linearity. Additionally, we analyzed plasma samples from 182 patients with suspected EBV-related diseases between January and July 2022 at the Southern Medical University Southern Hospital, using both dPCR and quantitative PCR (qPCR) for EBV DNA quantification. Linear regression analysis using the least squares method was conducted to assess their quantitative correlation.Results:The dPCR systems for both multicopy and single-copy genes showed excellent linearity ( R 2 values of 0.992 and 0.997, respectively, both P<0.001). The LoD were 188 IU/ml for BamHI-W gene and 358 IU/ml for EBNA1 gene dPCR systems. The logarithmic coefficient of variation ( CV) values for high-concentration samples (1 000 000 IU/ml) were 0.34% and 0.21% for the BamHI-W gene and EBNA1 gene dPCR assays, respectively, while for low-concentration samples (5 000 IU/ml) were 0.98% and 0.64%, respectively. In the detection of seven common clinical infectious pathogens and EBV positive samples, only EBV-positive samples yielded positive signals in the dPCR detection system, with no cross-reaction with other pathogens. In 182 samples, the positive detection rates were 47.80% (87/182) for BamHI-W gene and 35.16% (64/182) for EBNA1 gene dPCR, compared to 43.41% (79/182) for qPCR. Linear correlation analysis with qPCR showed R2 values of 0.837 for BamHI-W gene and 0.763 for EBNA1 gene dPCR (both P<0.001). The BamHI-W gene copy number ranged from 3 to 18 copies per clinical sample, with patient-specific variations. There was a high consistency in viral load trends between the multicopy BamHI-W gene and single-copy EBNA1 gene dPCR systems within individual patients. Conclusions:The dPCR methods detecting EBV multiple and single copies genes showed high sensitivity, specificity, precision, and quantitative accuracy, suitable for clinical sample analysis. The multicopy BamHI-W gene dPCR method notably enhances detection sensitivity and can be used as a supplement to current EBV DNA load detection methods, especially in low-concentration samples. For within-patient EBV DNA monitoring, the multicopy gene method proves more effective, while inter-patient comparisons might necessitate single-copy gene methods or normalize them using the same standard.

ObjectiveTo understand the current situation of anxiety level and traditional Chinese medicine （TCM） nursing needs among residents during the COVID-19 epidemic， and to discuss the relationship between them，so as to provide references for maintaining their mental health. MethodsA total of 560 residents were recruited using convenience sampling method， and the selected individuals completed three questionnaires based on online platform， including self-designed general information questionnaire， Generalized Anxiety Disorder Scale （GAD-7）， and TCM nursing needs questionnaire. Then the correlation between anxiety level and TCM nursing needs was analyzed by Spearman correlation test. ResultsA total of 552 valid questionnaires were collected. The results of GAD-7 showed that the total score was （11.04±3.72）， and average score of each item was （1.58±0.53）. There were 328 cases （59.4%） without anxiety symptoms， 180 cases （32.6%） with mild anxiety， 33 cases （6.0%） with moderate anxiety， and 11 cases （2.0%） with severe anxiety. The analysis of TCM nursing needs questionnaire showed that the total score was （21.59±7.92）， and dominated by the needs of medical knowledge （2.90±1.15） and TCM dietary care （2.82±1.13）. The item score and total score of TCM nursing needs questionnaire of residents during the COVID-19 epidemic were positively correlated with GAD-7 total score （r=0.240~0.331， P<0.01）. ConclusionResidents suffer from different levels of anxiety during the COVID-19 epidemic， and TCM nursing needs is on the rise， indicating that the anxiety level of residents is correlated with the needs of TCM nursing.

Objective To investigate whether adjuvant therapy can bring survival benefits to patients with esophageal squamous cell carcinoma (ESCC) who have received neoadjuvant therapy plus esophagectomy. Methods Studies were identified by searching databases including PubMed, EMbase, Web of Science, The Cochrane Library and CNKI from inception to November 2022 to collect studies which conformed to the objective of this study. Clinical outcomes including overall survival (OS) and recurrence-free survival (RFS) were extracted from eligible studies after screening. RevMan 5.4 and Stata 14.0 were used to perform the meta-analysis. Results A total of 9 studies were selected including 1 340 patients. Compared with the neoadjuvant therapy plus surgery (NS) group, the neoadjuvant therapy plus surgery+adjuvant therapy (NS+A) group had no significant benefit in the OS [HR=0.88, 95%CI (0.75, 1.02), P=0.09], but had remarkable benefit in the RFS [HR=0.75, 95%CI (0.58, 0.97), P=0.03]. Subgroup analysis by nodal status showed that adjuvant therapy could improve the RFS of patients with node-positive disease. Prolonged OS was observed in the patients with both positive and negative nodes but not in the patients with only positive nodes. In terms of the subgroup analysis by prescription, it revealed that triple agents exhibited advantages in improving RFS but not OS. However, dual agents did not bring additional survival benefits to the NS+A group compared with the NS group. Subgroup analysis by adjuvant therapy indicated that neither postoperative chemoradiotherapy nor chemotherapy improved OS, whereas postoperative chemoradiation elongated RFS. Conclusion Adjuvant therapy can improve the prognosis of patients with ESCC after neoadjuvant therapy followed by esophagectomy.

With the widespread adoption of low-dose CT screening and the extensive application of high-resolution CT, the detection rate of sub-centimeter lung nodules has significantly increased. How to scientifically manage these nodules while avoiding overtreatment and diagnostic delays has become an important clinical issue. Among them, lung nodules with a consolidation tumor ratio less than 0.25, dominated by ground-glass shadows, are particularly worthy of attention. The therapeutic challenge for this group is how to achieve precise and complete resection of nodules during surgery while maximizing the preservation of the patient's lung function. The "watershed topography map" is a new technology based on big data and artificial intelligence algorithms. This method uses Dicom data from conventional dose CT scans, combined with microscopic (22-24 levels) capillary network anatomical watershed features, to generate high-precision simulated natural segmentation planes of lung sub-segments through specific textures and forms. This technology forms fluorescent watershed boundaries on the lung surface, which highly fit the actual lung anatomical structure. By analyzing the adjacent relationship between the nodule and the watershed boundary, real-time, visually accurate positioning of the nodule can be achieved. This innovative technology provides a new solution for the intraoperative positioning and resection of lung nodules. This consensus was led by four major domestic societies, jointly with expert teams in related fields, oriented to clinical practical needs, referring to domestic and foreign guidelines and consensus, and finally formed after multiple rounds of consultation, discussion, and voting. The main content covers the theoretical basis of the "watershed topography map" technology, indications, operation procedures, surgical planning details, and postoperative evaluation standards, aiming to provide scientific guidance and exploration directions for clinical peers who are currently or plan to carry out lung nodule resection using the fluorescent microscope watershed analysis method.