Objective To investigate the mechanism of action of circ-0058063 regulating ERK/MAPK signaling pathway on ferroptosis in esophageal cancer cells.Methods EC9706 cells were randomly divided into the Control group,the si-NC group,the si-circ-0058063 group,and the si-circ-0058063+ISO group.qRT-PCR was used to detect the expression of circ-0058063 in esophageal cancer tissues and cells;CCK-8 and clone formation assay were used to detect the cell proliferation ability.The levels of Fe2+,malondialdehyde(MDA),glutathione(GSH),and reactive oxygen species(ROS)in cells were detected.Western blot was used to detect the ERK/MAPK signaling pathway and the expression of ferroptosis-related protein in cells.Results The expression level of circ-0058063 in esophageal cancer tissue was significantly higher than that in adjacent tissues(P<0.05);the expression level of circ-0058063 in human esophageal cancer cell EC9706 was significantly higher than that in human normal esophageal epithelial cell HEEC(P<0.05).Compared with the Control group,the expression level of circ-0058063 in cells,cell survival rate,number of cloned cells,GSH level,ratios of p-ERK1/2/ERK1/2 and p-p38MAPK/p38MAPK,as well as the expression levels of SLC7A11 and GPX4 protein in the si-circ-0058063 group were significantly reduced(P<0.05),while the levels of Fe2+,MDA,and ROS in cells were significantly increased(P<0.05).Compared with the si-circ-0058063 group,the expression level of circ-0058063 in cells,cell survival rate,number of cloned cells,GSH level,ratios of p-ERK1/2/ERK1/2 and p-p38MAPK/p38MAPK,as well as the expression levels of SLC7A11 and GPX4 protein in the si-circ-0058063+ISO group were significantly increased(P<0.05),while the levels of Fe2+,MDA,and ROS in cells were significantly decreased(P<0.05).Conclusion Knockdown of circ-0058063 can inhibit the proliferation of esophageal cancer cells and induce ferroptosis,and its mechanism of action may be related to the inhibition of ERK/MAPK signaling pathway activation.

Objective To analyze the risk factors for increased drainage volume after open transforaminal lumbar interbody fusion(TLIF),and to establish a predictive model and then validate it.Methods The clinical data of 680 patients who underwent open TLIF at the General Hospital of Northern Theater Command from January 2016 to December 2019 were collected and the patients were randomly divided into the training group(n=476)and the validation group(n=204).Taking the predictive factors screened out by LASSO regression analysis as independent variables,a multivariate Logistic regression predictive model was constructed.The model was internally validated through the receiver operating characteristic(ROC)curve,Hosmer-Lemeshow goodness-of-fit test,and calibration curve,and its clinical utility was assessed via decision curve analysis(DCA).Results LASSO regression analysis screened out four predictive variables:age,number of surgical segments,operative duration,and intraoperative blood loss.The multivariate Logistic regression predictive model demonstrated that age≥60 years,number of surgical segments≥4,operative duration≥2 hours,and intraoperative blood loss≥200 mL were independent influencing factors for the increased postoperative drainage volume in patients undergoing TLIF(P<0.05).ROC curve analysis revealed an area under the curve(AUC)of 0.816(95%CI:0.798 to 0.867)in the training group and 0.783(95%CI:0.685 to 0.823)in the validation group,indicating that the predictive model had good discriminatory ability.Additionally,the Hosmer-Lemeshow goodness-of-fit test and calibration curve indicated that the predictive model had a good degree of fit,and the predicted probability was basically consistent with the actual probability,demonstrating a good calibration.The DCA results confirmed that this predictive model could be applied in clinical practice.Conclusion The risk factors for increased drainage volume after open TLIF include age,number of surgical segments,operative duration,and intraoperative blood loss.The predictive model established based on these factors demonstrates good performance,and it can be applied in clinical guidance for the selection of drainage tube removal time after TLIF.

Objective To explore the risk factors for noncontiguous spinal fractures(NSFs)in the elderly.Methods The clinical data of 614 elderly patients with spinal fracture from January 2013 to December 2019 were analyzed retrospectively.Patients were divided into the NSFs group and the Non-NSFs group according to whether NSFs occurred or not.Univariate analysis and multivariate Logistic regression analysis were used to screen the risk factors of NSFs.Results Univariate analysis showed that female(P=0.003),high-energy violent injury(P=0.032),osteoporosis(P=0.004),fracture in spring(P=0.020),and previous spinal fracture history(P<0.001)were associated with the occurrence of NSFs.Multivariate Logistic regression analysis showed that fracture in spring(P=0.024),previous spinal fracture history(P<0.001)and high-energy violent injury(P=0.038)were the independent risk factors for the occurrence of NSFs in the elderly.Conclusion High-energy violent injury,fracture in spring and previous spinal fracture history are the independent risk factors for the occurrence of NSFs in the elderly.Therefore,elderly patients with the above risk factors should be examined more carefully and comprehensively to avoid missed diagnosis and delayed diagnosis.In order to reduce the incidence of this disease,corresponding measures should be taken according to the preventable risk factors.

Objective To analyze the risk factors for increased drainage volume after open transforaminal lumbar interbody fusion(TLIF),and to establish a predictive model and then validate it.Methods The clinical data of 680 patients who underwent open TLIF at the General Hospital of Northern Theater Command from January 2016 to December 2019 were collected and the patients were randomly divided into the training group(n=476)and the validation group(n=204).Taking the predictive factors screened out by LASSO regression analysis as independent variables,a multivariate Logistic regression predictive model was constructed.The model was internally validated through the receiver operating characteristic(ROC)curve,Hosmer-Lemeshow goodness-of-fit test,and calibration curve,and its clinical utility was assessed via decision curve analysis(DCA).Results LASSO regression analysis screened out four predictive variables:age,number of surgical segments,operative duration,and intraoperative blood loss.The multivariate Logistic regression predictive model demonstrated that age≥60 years,number of surgical segments≥4,operative duration≥2 hours,and intraoperative blood loss≥200 mL were independent influencing factors for the increased postoperative drainage volume in patients undergoing TLIF(P<0.05).ROC curve analysis revealed an area under the curve(AUC)of 0.816(95%CI:0.798 to 0.867)in the training group and 0.783(95%CI:0.685 to 0.823)in the validation group,indicating that the predictive model had good discriminatory ability.Additionally,the Hosmer-Lemeshow goodness-of-fit test and calibration curve indicated that the predictive model had a good degree of fit,and the predicted probability was basically consistent with the actual probability,demonstrating a good calibration.The DCA results confirmed that this predictive model could be applied in clinical practice.Conclusion The risk factors for increased drainage volume after open TLIF include age,number of surgical segments,operative duration,and intraoperative blood loss.The predictive model established based on these factors demonstrates good performance,and it can be applied in clinical guidance for the selection of drainage tube removal time after TLIF.

Objective To investigate the mechanism of action of circ-0058063 regulating ERK/MAPK signaling pathway on ferroptosis in esophageal cancer cells.Methods EC9706 cells were randomly divided into the Control group,the si-NC group,the si-circ-0058063 group,and the si-circ-0058063+ISO group.qRT-PCR was used to detect the expression of circ-0058063 in esophageal cancer tissues and cells;CCK-8 and clone formation assay were used to detect the cell proliferation ability.The levels of Fe2+,malondialdehyde(MDA),glutathione(GSH),and reactive oxygen species(ROS)in cells were detected.Western blot was used to detect the ERK/MAPK signaling pathway and the expression of ferroptosis-related protein in cells.Results The expression level of circ-0058063 in esophageal cancer tissue was significantly higher than that in adjacent tissues(P<0.05);the expression level of circ-0058063 in human esophageal cancer cell EC9706 was significantly higher than that in human normal esophageal epithelial cell HEEC(P<0.05).Compared with the Control group,the expression level of circ-0058063 in cells,cell survival rate,number of cloned cells,GSH level,ratios of p-ERK1/2/ERK1/2 and p-p38MAPK/p38MAPK,as well as the expression levels of SLC7A11 and GPX4 protein in the si-circ-0058063 group were significantly reduced(P<0.05),while the levels of Fe2+,MDA,and ROS in cells were significantly increased(P<0.05).Compared with the si-circ-0058063 group,the expression level of circ-0058063 in cells,cell survival rate,number of cloned cells,GSH level,ratios of p-ERK1/2/ERK1/2 and p-p38MAPK/p38MAPK,as well as the expression levels of SLC7A11 and GPX4 protein in the si-circ-0058063+ISO group were significantly increased(P<0.05),while the levels of Fe2+,MDA,and ROS in cells were significantly decreased(P<0.05).Conclusion Knockdown of circ-0058063 can inhibit the proliferation of esophageal cancer cells and induce ferroptosis,and its mechanism of action may be related to the inhibition of ERK/MAPK signaling pathway activation.

The development of artificial intelligence(AI)technology has provided new avenues for the public to access health information.While both domestic and international research and practical applications of health conversational AI have emerged,there remains a lack of consensus on the key issues surrounding their development.Based on a comprehensive review of domestic and international literature and multiple rounds of expert consultations,the study focuses on six issues:the definition,characteristics,application scenarios,evaluation elements,evaluation methods,as well as prospects and challenges of AI-driven health consultation systems,and develops the practice guideline for health conversational artificial intelligence.The findings aim to provide scientific reference for promoting the innovative application of AI technology in the healthcare field.

Objective:To investigate the impact of fibroblast growth factor(FGF)on recurrence following segmen-tal mastectomy in patients with plasma cell mastitis.Methods:A total of 162 female patients diagnosed with plasma cell mastitis(PCM)were selected from our hospital from October 2021 to May 2023.All patients underwent segmental mastectomy.They were divided into recurrence group(n=28)and non-recurrence group(n=134)according to the follow-up survey on recurrence.Conduct a univariate analysis on the factors influencing recurrence in patients with PCM who undergo segmental mastectomy.After correcting for confounding factors,conduct a multiple linear regression analysis.Using a multivariate logistic regression model to explore the independent risk factors for recurrence in patients undergo-ing segmental mastectomy for PCM.Utilizing logistic regression analysis to explore the independent,multiplicative,or additive interaction between FGF and angiogenic factor in the management of recurrence in PCM patients undergoing segmental mastectomy.The Local Weighted Regression Scatter Method(LOWESS)is used to analyze the two-dimensional curve relationship of continuous variables.Evaluate the predictive efficacy of FGF for PCM recurrence fol-lowing segmental mastectomy using Receiver Operating Characteristic(ROC)curves.Results:The results of univariate analysis showed that the body mass index(BMI),estradiol,prolactin levels,nipple depression,and sinus phase propor-tion of patients in the recurrent group were significantly higher than those in the non recurrent group,and the differ-ences were statistically significant(P＜0.05).Before surgery and 1 and 3 months after surgery,the levels of FGF,vascu-lar endothelial growth factor(VEGF),endostatin(ES),and VEGF/ES in the recurrent group were higher than those in the non recurrent group,with statistically significant differences between the groups(P＜0.05).The intra group comparison results showed that compared with before surgery,all indicators in both groups of patients were significantly reduced at 1 month after surgery(P＜0.05),while in the recurrent group,all indicators were significantly increased at 3 months after surgery(P＜0.001).Logistic regression analysis showed that patients with elevated FGF had a higher risk of recurrence in PCM(P＜0.05).LOWESS analysis found that there is a certain non-linear relationship between PCM recurrence rate and FGF.FGF has good predictive performance for PCM recurrence.After further adjusting for various confounding fac-tors such as BMI,it was found that the angiogenic factor is related to FGF.The interaction results show that there is an additive or multiplicative interaction between FGF and VEGF/ES.Conclusion:FGF elevation increases the risk of re-currence after segmental mastectomy for PCM.FGF and VEGF/ES exhibit additive or multiplicative interactions.FGF has good predictive performance for PCM recurrence.

The development of artificial intelligence(AI)technology has provided new avenues for the public to access health information.While both domestic and international research and practical applications of health conversational AI have emerged,there remains a lack of consensus on the key issues surrounding their development.Based on a comprehensive review of domestic and international literature and multiple rounds of expert consultations,the study focuses on six issues:the definition,characteristics,application scenarios,evaluation elements,evaluation methods,as well as prospects and challenges of AI-driven health consultation systems,and develops the practice guideline for health conversational artificial intelligence.The findings aim to provide scientific reference for promoting the innovative application of AI technology in the healthcare field.

Objective:To investigate the impact of fibroblast growth factor(FGF)on recurrence following segmen-tal mastectomy in patients with plasma cell mastitis.Methods:A total of 162 female patients diagnosed with plasma cell mastitis(PCM)were selected from our hospital from October 2021 to May 2023.All patients underwent segmental mastectomy.They were divided into recurrence group(n=28)and non-recurrence group(n=134)according to the follow-up survey on recurrence.Conduct a univariate analysis on the factors influencing recurrence in patients with PCM who undergo segmental mastectomy.After correcting for confounding factors,conduct a multiple linear regression analysis.Using a multivariate logistic regression model to explore the independent risk factors for recurrence in patients undergo-ing segmental mastectomy for PCM.Utilizing logistic regression analysis to explore the independent,multiplicative,or additive interaction between FGF and angiogenic factor in the management of recurrence in PCM patients undergoing segmental mastectomy.The Local Weighted Regression Scatter Method(LOWESS)is used to analyze the two-dimensional curve relationship of continuous variables.Evaluate the predictive efficacy of FGF for PCM recurrence fol-lowing segmental mastectomy using Receiver Operating Characteristic(ROC)curves.Results:The results of univariate analysis showed that the body mass index(BMI),estradiol,prolactin levels,nipple depression,and sinus phase propor-tion of patients in the recurrent group were significantly higher than those in the non recurrent group,and the differ-ences were statistically significant(P＜0.05).Before surgery and 1 and 3 months after surgery,the levels of FGF,vascu-lar endothelial growth factor(VEGF),endostatin(ES),and VEGF/ES in the recurrent group were higher than those in the non recurrent group,with statistically significant differences between the groups(P＜0.05).The intra group comparison results showed that compared with before surgery,all indicators in both groups of patients were significantly reduced at 1 month after surgery(P＜0.05),while in the recurrent group,all indicators were significantly increased at 3 months after surgery(P＜0.001).Logistic regression analysis showed that patients with elevated FGF had a higher risk of recurrence in PCM(P＜0.05).LOWESS analysis found that there is a certain non-linear relationship between PCM recurrence rate and FGF.FGF has good predictive performance for PCM recurrence.After further adjusting for various confounding fac-tors such as BMI,it was found that the angiogenic factor is related to FGF.The interaction results show that there is an additive or multiplicative interaction between FGF and VEGF/ES.Conclusion:FGF elevation increases the risk of re-currence after segmental mastectomy for PCM.FGF and VEGF/ES exhibit additive or multiplicative interactions.FGF has good predictive performance for PCM recurrence.

Surface plasmon resonance （SPR） sensor is an optical detection technique enables real-time and dynamic monitoring of biological samples. SPR-based biosensors have remarkable characteristics such as label-free detection and high sensitivity, making them important tools for studying molecular interactions. The recognition element, which plays a critical role in SPR sensors,which could specifically identify and capture of target analytes, closely influencing the selectivity performance of the sensor. The progress on SPR sensors in pharmaceutical research were reviewed, which focused on the application of recognition elements such as antibodies, aptamers, molecularly imprinted polymers, and metal nanoparticles.