Background: The esophagectomy surgical Apgar score (eSAS) has been found to be a predictor of postoperative complications in esophagectomy. In our previous study, we built a graphic nomogram based on eSAS and demonstrated that it can effectively predict the risk of major morbidity after esophagectomy. In this study, we aimed to assess the benefits of using an eSAS-based nomogram model as a postoperative risk-based triage system for patients undergoing esophagectomy. Methods: We enrolled 119 patients diagnosed with esophageal carcinoma and randomly assigned them to a nomogram group (NG) or control group (CG) from January 2019 to December 2020. Patients in the NG were assigned to a low-risk group and high-risk group based on the nomogram. Patients in the high-risk group were admitted to the intensive care unit (ICU) after esophagectomy. Risk estimation in the CG patients was based on the surgeon's clinical experience. Thirty-day major complications, postoperative hospital stay, hospital costs, and quality of life (QOL) during the follow-up were compared between the two groups. Results: Baseline clinicopathological characteristics were comparable between the NG (n=58) and CG (n=61). All patients underwent esophagectomy. Postoperative complications were significantly higher in the CG (30, 49.2%) than in the NG (14, 24.1%) (P=0.008), with pneumonia being the most common (CG: 23, 37.7%; NG: 12, 20.7%; P=0.042). There was no significant difference in anastomotic leakage (NG: 1, 1.7%; CG: 6, 9.8%; P=0.12). Postoperative median hospital stay was shorter in the NG (14 days) than in the CG (16 days) (P=0.041). Hospital costs (NG: ¥60,045.1; CG: ¥63,961.5; P=0.21) and postoperative QOL did not differ significantly between groups. Conclusions: An eSAS-based nomogram as a triage system can reduce the overall occurrence of postoperative complications and shorten postoperative hospital stay without increasing hospital costs. Trial Registration: Chinese Clinical Trial Registry ChiCTR1900021636.

Observational studies have suggested a link between severe mental illness (SMI) and risk of lung carcinoma (LC); however, causality has not been established. In this study, we conducted a two-sample, two-step Mendelian randomization (MR) investigation to uncover the etiological influence of SMI on LC risk and quantify the mediating effects of known modifiable risk factors. We obtained summary-level datasets for schizophrenia, major depressive disorder (MDD), and bipolar disorder (BD) from the Psychiatric Genomics Consortium (PGC). Data on single nucleotide polymorphisms (SNPs) associated with lung carcinoma (LC) were sourced from a recent large meta-analysis by McKay et al. We employed two-sample MR and two-step MR utilizing the inverse variance weighted method for causal estimation. Sensitivity tests were conducted to validate causal relationships. In two-sample MR, we identified schizophrenia as a risk factor for LC (OR = 1.06, 95% CI 1.02-1.11, P = 3.48E-03), while MDD (OR = 1.18, 95% CI 0.98-1.42, P = .07) and BD (OR = 1.07, 95% CI 0.99-1.15, P = .09) showed no significant association with LC. In the two-step MR, smoking accounted for 24.66% of the schizophrenia-LC risk association, and alcohol consumption explained 7.59% of the effect. Schizophrenia is a risk factor for lung carcinoma, and smoking and alcohol consumption are the mediating factors in this causal relationship. LC screening should be emphasized in individuals with schizophrenia, particularly in those who smoke and consume alcohol regularly.

Background and objective Invasive mucinous adenocarcinoma (IMA) was a rare and specific type of lung adenocarcinoma, which was often characterized by fewer lymphatic metastases. Therefore, it was difficult to evaluate the prognosis of these tumors based on the existing tumor-node-metastasis (TNM) staging. So, this study aimed to develop Nomograms to predict outcomes of patients with pathologic N0 in resected IMA. Methods According to the inclusion criteria and exclusion criteria, IMA patients with pathologic N0 in The Affiliated Lihuili Hospital of Ningbo University (training cohort, n=78) and Ningbo No.2 Hospital (validation cohort, n=66) were reviewed between July 2012 and May 2017. The prognostic value of the clinicopathological features in the training cohort was analyzed and prognostic prediction models were established, and the performances of models were evaluated. Finally, the validation cohort data was put in for external validation. Results Univariate analysis showed that pneumonic type, larger tumor size, mixed mucinous/non-mucinous component, and higher overall stage were significant influence factors of 5-year progression-free survival (PFS) and overall survival (OS). Multivariate analysis further indicated that type of imaging, tumor size, mucinous component were the independent prognostic factors for poor 5-year PFS and OS. Moreover, the 5-year PFS and OS rates were 62.82% and 75.64%, respectively. In subgroups, the survival analysis also showed that the pneumonic type and mixed mucinous/non-mucinous patients had significantly poorer 5-year PFS and OS compared with solitary type and pure mucinous patients, respectively. The C-index of Nomograms with 5-year PFS and OS were 0.815 (95%CI: 0.741-0.889) and 0.767 (95%CI: 0.669-0.865). The calibration curve and decision curve analysis (DCA) of both models showed good predictive performances in both cohorts. Conclusion The Nomograms based on clinicopathological characteristics in a certain extent, can be used as an effective prognostic tool for patients with pathologic N0 after IMA resection.

Background: Shexiang Baoxin Pill (SBP) is a classical Chinese medicine that improves endothelial function and antioxidant and inflammatory responses. It may also alleviate doxorubicin (DOX)-induced cardiotoxicity. The aim of this study is to explore the potential influence and molecular mechanisms of SBP in DOX-induced cardiotoxicity using network pharmacology. Methods: We established control, SBP, DOX, and DOX + SBP groups to evaluate cell function using a Cell Counting Kit-8 assay, reactive oxygen species (ROS) measurement, cell cycle analysis, and apoptosis assessment. Network pharmacology was employed to predict potential targets and pathways of SBP in DOX-induced cardiotoxicity; the predictions were validated using protein blotting assays. Results: SBP (2.5 mg/L) significantly mitigated DOX-induced cardiotoxicity. DOX elevated ROS levels, induced phosphorylation of the AKT pathway, and altered the expression of apoptosis-related proteins Bcl-2 and Bax. SBP attenuated the impact of DOX on cardiomyocytes. Network pharmacology identified 10 candidate targets. Conclusion: SBP ameliorates DOX-induced cardiomyocyte apoptosis by activating the ROS-mediated AKT/Bcl-2 signaling pathway.

Background Spread through air spaces (STAS), as a new pattern of invasion, was officially proposed by the World Health Organization (WHO) in 2015, and its importance was reiterated in 2021. Since it was proposed, numerous studies have confirmed that STAS is associated with poor prognosis, but there are relatively few studies related to the prognosis of postoperative patients with lung squamous cell carcinoma. By synthesizing different predictive variables, nomogram can obtain the individual digital probability of clinical events succinctly and intuitively, which can meet our needs for personalized medicine. In this study, our goal is to explore the prognostic value of STAS in lung squamous cell carcinoma and establish a prognostic prediction model. Methods Under six inclusion criteria, 540 postoperative patients were enrolled in the study. STAS was re-evaluated by pathologists at Ningbo Clinicopathological Diagnosis Center. Progression-free survival (PFS) referred to the time from randomization to the first occurrence of disease progression or death of any cause. Recurrences were confirmed by clinical, radiological or pathological assessment. The survival information was collected by telephone and outpatient follow-up. A total of 540 patients were randomly divided into groups in a 6:4 ratio for survival analysis to determine the correlation between STAS and prognosis. Cox regression was used for univariate and multivariate analysis, so as to establish a predictive model. The assessment of the nomogram was carried out by receiver operating characteristic (ROC) curve analysis, calibration curve analysis and decision curve analysis (DCA). Results The overall 5-year survival rate was 70.35% in STAS-negative patients and 42.35% in STAS-positive patients. In all cohorts, STAS-negative patients had longer 5-year PFS than STAS-positive patients (P<0.001). Multivariate analysis showed that stage [stage II P=0.008, hazard ratio (HR) =1.792; stage III P<0.001, HR =3.148], tumor differentiation (well-differentiation P=0.021, HR =0.436), and STAS (P=0.026, HR =1.470) were independent predictors of PFS. The area under the curve (AUC) of model 5 in discovery cohort is 0.720, while the AUC of model 5 in validation cohort is 0.693. Conclusions The nomogram combined with STAS can provide a personalized visual survival probability prediction map for postoperative patients with lung squamous cell carcinoma, so as to aid in the pursuit of personalized medicine to a certain extent.

Background:The Tumor Node Metastasis (TNM) stage cannot accurately predict the prognosis of patients in pulmonary squamous cell carcinoma (SQCC). The aim of the present study was to evaluate the prognostic value of immunohistochemical (IHC)-based classifiers in patients with pulmonary SQCC who underwent complete surgery resection.Methods:From January 2010 to December 2014, a total of 556 patients with SQCC who underwent complete radical resection were included. The patients were grouped into a discovery group (n=334) and a validation group (n=222). Using the least absolute shrinkage and selection operator (LASSO) regression model, we extracted IHCs that were associated with progression-free survival (PFS) and then built classifiers. Clinicopathological variables and the IHC-based classifiers were analyzed using univariable and multivariable logistic regression analyses. A nomogram to predict PFS was constructed and validated using bootstrap resampling.Results:Following the LASSO regression model, 4 IHC markers associated with PFS were identified. We used the IHC-based classifiers to stratify patients in both groups into high- and low-risk groups. PFS was better in the low-risk group than in the high-risk group in both the discovery and validation groups. Multivariate analysis demonstrated that the IHC-based classifiers were independently prognostic in predicting the PFS of patients with SQCC. The performance of the nomogram was evaluated and proven to be clinically useful.Conclusions:By combining IHC-based classification and clinicopathology, we were able to have better insight into the prognostic assessment of patients with SQCC after surgery, which can inform postoperative patient management.

Objective The mechanism of circRNA on M2 macrophage polarization, which contributes to esophageal cancer, remains unclear. This study is aimed at clarifying the mechanism of circRNA on esophageal cancer by regulating M2 macrophage polarization. Methods The expression of circRNA TCFL5 and miR-543 was detected by qRT-PCR. Western blot was used to detect the expression of FMNL2 and CD163. CCK-8 and transwell assay was used to detect the proliferation, migration, and invasion of Eca109 and KYSE150, respectively. Flow cytometry was used to detect the CD163 positive cells. The contents of IL-10, TGF-β, TNF-α, IL-6, and IL-1β were detected by ELISA. A dual-luciferase reporter system was used to detect the regulation of miR-543 to circRNA TCFL5 and FMNL2. Results 156 upregulated circRNAs and 91 downregulated circRNAs in esophageal cancer tissues were identified, and the expression of circRNA TCFL5 showed the most significant upregulation. Overexpression of circRNA TCFL5 promotes proliferation, invasion, and migration of Eca109 and KYSE150 and promotes tumor growth in vivo. circRNA TCFL5 served as a sponge of miR-543, and FMNL2 was a downstream target gene of miR-543. circRNA TCFL5 promotes cell proliferation, migration, and invasion of Eca109 and KYSE150 by modulating the miR-543/FMNL2 axis. Macrophage M2 polarization promoted proliferation, invasion, and migration of Eca109 and KYSE150 cells, and circRNA TCFL5 mediated macrophage M2 polarization by regulating the FMNL2/miR-543 axis. Conclusion In the present study, we identified that circRNA TCFL5 was dramatically upregulated in esophageal cancer, and circRNA TCFL5 promotes esophageal cancer progression by modulating M2 macrophage polarization via the miR-543-FMNL2 axis, which provides a potential target for the treatment of esophageal cancer.

BackgroundWe aimed to evaluate the prognostic value of immunohistochemistry (IHC) markers and tumor-node-metastasis (TNM) stages in patients with pulmonary squamous cell carcinoma (SQCC). MethodsFrom January 2010 to December 2014, aA total of 556 patients with SQCC who underwent radical resection were included. The patients were grouped into a discovery group ( n = 334) and a validation group ( n = 222). Using the least absolute shrinkage and selection operator regression model, we extracted IHCs that were associated with progression-free survival (PFS) and then built a classifier. Clinicopathologic variables and the IHC-based classifier were analysed using univariable and multivariable logistic regression analysis. A nomogram to predict PFS was constructed and validated using bootstrap resampling.ResultsFollowingUsing the least absolute shrinkage and selection operator regression model, four IHC markers associated with progression-free survival (PFS) were identified. Furthermore, we developed a nomogram integrating IHC markers to predict 3- and 5-year PFS. We used the IHC-based classifiers to stratify patients in both groups into high- and low-risk groups. PFS was better in the low-risk group than in the high-risk group in both the discovery and validation groups. Multivariate analysis demonstrated that the IHC-based classifiers were independently prognostic in predicting the PFS of patients with SQCC. The performance of the nomogram was evaluated and proven to be clinically useful. ConclusionsWe further developed a nomogram integrating the IHC-based classifiers and clinicopathological risk factors to predict PFS. Through combining the IHC-based classification and clinicopathology, we have a better insight into the prognosis assessment of patients with SQCC after surgery, which informs postoperative patient management.