Recent findings from Diabetologia highlight the pivotal role of sialic acid-binding immunoglobulin-type lectin 1(SIGLEC-1) positive monocytes in the early onset of type 1 diabetes. These cells activate immune effector cells primarily via the interferon signaling pathway, diverging from traditional antigen presentation methods, thereby triggering pancreatic inflammation and destruction. This discovery paves the way for novel approaches in early diagnosis and targeted therapies for type 1 diabetes.

Objective To explore the effect of evidence-based thinking oriented micro-course and case-based learning(CBL)on cultivation of clinical thinking ability of nurses who are taking the standardised nursing training in intensive care unit(ICU)so as to provide a new teaching method in the training of nurses.Methods A total of 72 nurses taking standardised nursing training in ICU of our hospital from November 2021 to October 2023 were selected as the research objects.Thirty-six of nurses who took rotation in the ICU from November 2021 to October 2022 were assigned in the control group,and other 36 nurses who took rotation in the ICU from November 2022 to October 2023 were assigned in the trial group.In the control group,CBL teaching method was adopted in the standardised nursing training,while both of evidence-based thinking oriented micro-course and CBL teaching mothed were adopted in the trial group for the standardised nursing training.The two groups were compared in terms of scores of clinical thinking ability,assessment of theory and clinical skills,as well as nurses'satisfaction with the teaching.Results After the training,nurses in the trial group exhibited significant superiority to the control group in total scores of clinical thinking ability and its three dimensions,critical thinking ability,systematic thinking ability and evidence-based thinking ability(P<0.05 for all).Furthermore,nurses in the trial group achieved significantly higher scores in theoretical assessment and assessment of clinical skills in comparison with those in the control group(P<0.05).Moreover,the trial group reported significantly higher satisfaction with both of the teaching method and learning atmosphere than those of the control group(P<0.05 for both).Conclusion Evidence-based thinking oriented micro-course and CBL teaching method can effectively improve the clinical thinking ability,theoretical knowledge and operational skills among the nurses taking standardised nursing training in ICU.

AIM:To investigate the anti-fibrotic effect of Panax notoginseng saponins(PNS)in arecoline(ANE)-induced oral submucous fibrosis,and to analyze the effect of PNS on nuclear factor E2-related factor 2(Nrf2)/glu-tamate-cysteine ligase catalytic subunit(GCLC)signaling pathway.METHODS:CCK-8 assay was used to evaluate the effects of different concentrations of PNS and arecoline on the survival rate of human immortalized keratinocyte cell line Ha-CaT.The results of CCK-8 were used to select 75 mg/L arecoline,and 25,50 and 100 mg/L PNS as subsequent experi-mental concentrations.The cells were set as blank control group,model group,and low,medium and high doses(25,50 and 100 mg/L)of PNS groups.The protein and mRNA expressions of collagen type I(COL-I),E-cadherin,Nrf2,GCLC and glutathione reductase(GR)in each group were detected by Western blot and RT-qPCR.Immunofluorescence method was used to detect the entry of Nrf2 into the nucleus.Biochemical kits were used to detect the content of glutathione(GSH),nicotinamide adenine dinucleotide phosphate(NADPH)and malondialdehyde(MDA),and superoxide dis-mutase(SOD)activity in each group of cells.DCFH-DA fluorescent probe was used to detect the content of intracellular reactive oxygen species(ROS).RESULTS:Compared with the blank control group,the protein and mRNA expression of COL-I in the model group was up-regulated,and the protein and mRNA levels of E-cadherin,Nrf2,GCLC,nuclear Nrf2 and GR were down-regulated.The content of NADPH,MDA and ROS in the cells increased,and the content of GSH and the activity of SOD was significantly reduced.Compared with the model group,the protein and mRNA expression of COL-I was down-regulated,and the protein and mRNA expression of E-cadherin,Nrf2,GCLC,nuclear Nrf2 and GR were up-regulated in PNS 50 and 100 mg/L groups.Compared with the model group,the content of NADPH,MDA and ROS in cells decreased,and the content of GSH and the activity of SOD was significantly enhanced(P<0.05 or P<0.01).CON-CLUSION:Panax notoginseng saponins have anti-fibrosis effects in HaCaT cells,and their mechanism may be related to the activation of Nrf2/GCLC signaling pathway,thereby resisting oxidative stress and improving oral submucosal fibrosis.

Objective:To compare the clinical efficacy of ultrasound-guided spinal nerve block (SNB) and paraverteral nerve block (PVB) in treating postherpetic neuralgia.Methods:A total of 52 patients with postherpetic neuralgia who visited the Pain Clinic of the Xiangya Hospital, Central South University from February 2020 to December 2022 were selected and randomly divided into an ultrasound-guided SNB group and a PVB group using a random number table method, with 26 patients in each group. Patients in the SNB group received ultrasound-guided spinal nerve block therapy; The PVB group received ultrasound-guided paraverteral nerve block treatment. Visual Analog Scale (VAS) scores, 36-Item Short Form Survey (SF-36) scores, and total effective rate were observed in two groups of patients before treatment, 2 weeks after treatment, 1 month after treatment, 3 months after treatment, and 6 months after treatment. Complications during treatment were also observed.Results:The total effective rates of SNB group patients at 1, 3, and 6 months after treatment were significantly higher than those of PVB group (all P<0.05). After treatment, the VAS scores of both groups of patients at each time point were significantly reduced compared to before treatment (all P<0.05); The VAS scores of patients in the SNB group were lower than those in the PVB group at 1, 3, and 6 months after treatment, but the difference was not statistically significant (all P>0.05). There was no statistically significant difference in Physical Component Summary (PCS) and Mental Component Summary (MCS) scores between SNB and PVB groups before nerve block treatment (all P>0.05). The MCS and PCS scores of the two groups of patients were significantly higher than before treatment at 2 weeks, 1 month, 3 months, and 6 months after treatment (all P<0.05). The MCS scores of the SNB group were significantly higher than those of the PVB group at 2 weeks, 1 month, 3 months, and 6 months after treatment (all P<0.05), but there was no statistically significant difference in PCS scores between the two groups (all P>0.05). Both groups of patients did not experience any serious complications related to the treatment in this study during the follow-up period. Conclusions:Both ultrasound-guided spinal nerve block and paraverteral nerve block can safely and effectively treat postherpetic neuralgia. The clinical effect of ultrasound-guided spinal nerve block in treating postherpetic neuralgia is better than that of paraverteral nerve block.

Objective:To predict lymph node metastasis in patients preoperatively diagnosed with early-stage cervical cancer based on preoperative inflammatory and immune nutritional indicators,and to construct a nomo-gram prediction model,providing a basis and tool for preoperative diagnosis of lymph node metastasis in cervical cancer.Methods:A retrospective analysis was conducted on the clinical data of 307 patients preoperatively diag-nosed with early-stage cervical cancer who underwent surgical treatment at the Obstetrics and Gynecology De-partment of the Second Affiliated Hospital of Zhengzhou University from January 2018 to July 2023.R software was used to randomize the groups into a training set(n=231)and a validation set(n=76)in a 3∶1 ratio.Uni-variate and multivariate logistic regression analyses were employed to identify factors influencing lymph node me-tastasis in patients preoperatively diagnosed with early-stage cervical cancer.R software was used to establish a nomogram prediction model and draw receiver operating characteristic(ROC)curves and calibration curves for validation.Results:① The results of univariate logistic regression analysis showed that positive lymphovascular invasion,platelet-to-lymphocyte ratio(PLR)≥151.70,neutrophil-to-white blood cell ratio(NWR)≥0.65,plate-let-to-albumin ratio(PAR)≥ 4.94,preoperative systemic immune-inflammation index(SII)≥604.03,and sys-temic inflammatory response index(SIRI)≥ 1.05 were associated with lymph node metastasis(P＜0.05).②Multivariate logistic regression analysis found that positive lymphovascular invasion,NWR≥0.65,and PAR≥4.94 were independent risk factors for lymph node metastasis in patients preoperatively diagnosed with early-stage cervical cancer(OR＞1,P＜0.05).③ A nomogram was constructed to predict lymph node metastasis in patients preoperatively diagnosed with early-stage cervical cancer.The ROC curve shows an area under the train-ing set curve(AUC)of 0.821 and a validation set AUC of 0.858.The calibration curve shows an average abso-lute error of 0.024 for the training set and 0.059 for the validation set.Conclusions:The prediction model for lymph node metastasis in cervical cancer constructed using preoperative inflammatory and immune nutritional indi-cators such as NWR,PAR is helpful for gynecological oncologists to predict lymph node metastasis in cervical cancer patients before surgery.

Objective:To predict lymph node metastasis in patients preoperatively diagnosed with early-stage cervical cancer based on preoperative inflammatory and immune nutritional indicators,and to construct a nomo-gram prediction model,providing a basis and tool for preoperative diagnosis of lymph node metastasis in cervical cancer.Methods:A retrospective analysis was conducted on the clinical data of 307 patients preoperatively diag-nosed with early-stage cervical cancer who underwent surgical treatment at the Obstetrics and Gynecology De-partment of the Second Affiliated Hospital of Zhengzhou University from January 2018 to July 2023.R software was used to randomize the groups into a training set(n=231)and a validation set(n=76)in a 3∶1 ratio.Uni-variate and multivariate logistic regression analyses were employed to identify factors influencing lymph node me-tastasis in patients preoperatively diagnosed with early-stage cervical cancer.R software was used to establish a nomogram prediction model and draw receiver operating characteristic(ROC)curves and calibration curves for validation.Results:① The results of univariate logistic regression analysis showed that positive lymphovascular invasion,platelet-to-lymphocyte ratio(PLR)≥151.70,neutrophil-to-white blood cell ratio(NWR)≥0.65,plate-let-to-albumin ratio(PAR)≥ 4.94,preoperative systemic immune-inflammation index(SII)≥604.03,and sys-temic inflammatory response index(SIRI)≥ 1.05 were associated with lymph node metastasis(P＜0.05).②Multivariate logistic regression analysis found that positive lymphovascular invasion,NWR≥0.65,and PAR≥4.94 were independent risk factors for lymph node metastasis in patients preoperatively diagnosed with early-stage cervical cancer(OR＞1,P＜0.05).③ A nomogram was constructed to predict lymph node metastasis in patients preoperatively diagnosed with early-stage cervical cancer.The ROC curve shows an area under the train-ing set curve(AUC)of 0.821 and a validation set AUC of 0.858.The calibration curve shows an average abso-lute error of 0.024 for the training set and 0.059 for the validation set.Conclusions:The prediction model for lymph node metastasis in cervical cancer constructed using preoperative inflammatory and immune nutritional indi-cators such as NWR,PAR is helpful for gynecological oncologists to predict lymph node metastasis in cervical cancer patients before surgery.

Objective:To predict lymph node metastasis in patients preoperatively diagnosed with early-stage cervical cancer based on preoperative inflammatory and immune nutritional indicators,and to construct a nomo-gram prediction model,providing a basis and tool for preoperative diagnosis of lymph node metastasis in cervical cancer.Methods:A retrospective analysis was conducted on the clinical data of 307 patients preoperatively diag-nosed with early-stage cervical cancer who underwent surgical treatment at the Obstetrics and Gynecology De-partment of the Second Affiliated Hospital of Zhengzhou University from January 2018 to July 2023.R software was used to randomize the groups into a training set(n=231)and a validation set(n=76)in a 3∶1 ratio.Uni-variate and multivariate logistic regression analyses were employed to identify factors influencing lymph node me-tastasis in patients preoperatively diagnosed with early-stage cervical cancer.R software was used to establish a nomogram prediction model and draw receiver operating characteristic(ROC)curves and calibration curves for validation.Results:① The results of univariate logistic regression analysis showed that positive lymphovascular invasion,platelet-to-lymphocyte ratio(PLR)≥151.70,neutrophil-to-white blood cell ratio(NWR)≥0.65,plate-let-to-albumin ratio(PAR)≥ 4.94,preoperative systemic immune-inflammation index(SII)≥604.03,and sys-temic inflammatory response index(SIRI)≥ 1.05 were associated with lymph node metastasis(P＜0.05).②Multivariate logistic regression analysis found that positive lymphovascular invasion,NWR≥0.65,and PAR≥4.94 were independent risk factors for lymph node metastasis in patients preoperatively diagnosed with early-stage cervical cancer(OR＞1,P＜0.05).③ A nomogram was constructed to predict lymph node metastasis in patients preoperatively diagnosed with early-stage cervical cancer.The ROC curve shows an area under the train-ing set curve(AUC)of 0.821 and a validation set AUC of 0.858.The calibration curve shows an average abso-lute error of 0.024 for the training set and 0.059 for the validation set.Conclusions:The prediction model for lymph node metastasis in cervical cancer constructed using preoperative inflammatory and immune nutritional indi-cators such as NWR,PAR is helpful for gynecological oncologists to predict lymph node metastasis in cervical cancer patients before surgery.

Objective:To predict lymph node metastasis in patients preoperatively diagnosed with early-stage cervical cancer based on preoperative inflammatory and immune nutritional indicators,and to construct a nomo-gram prediction model,providing a basis and tool for preoperative diagnosis of lymph node metastasis in cervical cancer.Methods:A retrospective analysis was conducted on the clinical data of 307 patients preoperatively diag-nosed with early-stage cervical cancer who underwent surgical treatment at the Obstetrics and Gynecology De-partment of the Second Affiliated Hospital of Zhengzhou University from January 2018 to July 2023.R software was used to randomize the groups into a training set(n=231)and a validation set(n=76)in a 3∶1 ratio.Uni-variate and multivariate logistic regression analyses were employed to identify factors influencing lymph node me-tastasis in patients preoperatively diagnosed with early-stage cervical cancer.R software was used to establish a nomogram prediction model and draw receiver operating characteristic(ROC)curves and calibration curves for validation.Results:① The results of univariate logistic regression analysis showed that positive lymphovascular invasion,platelet-to-lymphocyte ratio(PLR)≥151.70,neutrophil-to-white blood cell ratio(NWR)≥0.65,plate-let-to-albumin ratio(PAR)≥ 4.94,preoperative systemic immune-inflammation index(SII)≥604.03,and sys-temic inflammatory response index(SIRI)≥ 1.05 were associated with lymph node metastasis(P＜0.05).②Multivariate logistic regression analysis found that positive lymphovascular invasion,NWR≥0.65,and PAR≥4.94 were independent risk factors for lymph node metastasis in patients preoperatively diagnosed with early-stage cervical cancer(OR＞1,P＜0.05).③ A nomogram was constructed to predict lymph node metastasis in patients preoperatively diagnosed with early-stage cervical cancer.The ROC curve shows an area under the train-ing set curve(AUC)of 0.821 and a validation set AUC of 0.858.The calibration curve shows an average abso-lute error of 0.024 for the training set and 0.059 for the validation set.Conclusions:The prediction model for lymph node metastasis in cervical cancer constructed using preoperative inflammatory and immune nutritional indi-cators such as NWR,PAR is helpful for gynecological oncologists to predict lymph node metastasis in cervical cancer patients before surgery.

Objective:To predict lymph node metastasis in patients preoperatively diagnosed with early-stage cervical cancer based on preoperative inflammatory and immune nutritional indicators,and to construct a nomo-gram prediction model,providing a basis and tool for preoperative diagnosis of lymph node metastasis in cervical cancer.Methods:A retrospective analysis was conducted on the clinical data of 307 patients preoperatively diag-nosed with early-stage cervical cancer who underwent surgical treatment at the Obstetrics and Gynecology De-partment of the Second Affiliated Hospital of Zhengzhou University from January 2018 to July 2023.R software was used to randomize the groups into a training set(n=231)and a validation set(n=76)in a 3∶1 ratio.Uni-variate and multivariate logistic regression analyses were employed to identify factors influencing lymph node me-tastasis in patients preoperatively diagnosed with early-stage cervical cancer.R software was used to establish a nomogram prediction model and draw receiver operating characteristic(ROC)curves and calibration curves for validation.Results:① The results of univariate logistic regression analysis showed that positive lymphovascular invasion,platelet-to-lymphocyte ratio(PLR)≥151.70,neutrophil-to-white blood cell ratio(NWR)≥0.65,plate-let-to-albumin ratio(PAR)≥ 4.94,preoperative systemic immune-inflammation index(SII)≥604.03,and sys-temic inflammatory response index(SIRI)≥ 1.05 were associated with lymph node metastasis(P＜0.05).②Multivariate logistic regression analysis found that positive lymphovascular invasion,NWR≥0.65,and PAR≥4.94 were independent risk factors for lymph node metastasis in patients preoperatively diagnosed with early-stage cervical cancer(OR＞1,P＜0.05).③ A nomogram was constructed to predict lymph node metastasis in patients preoperatively diagnosed with early-stage cervical cancer.The ROC curve shows an area under the train-ing set curve(AUC)of 0.821 and a validation set AUC of 0.858.The calibration curve shows an average abso-lute error of 0.024 for the training set and 0.059 for the validation set.Conclusions:The prediction model for lymph node metastasis in cervical cancer constructed using preoperative inflammatory and immune nutritional indi-cators such as NWR,PAR is helpful for gynecological oncologists to predict lymph node metastasis in cervical cancer patients before surgery.

Objective:To predict lymph node metastasis in patients preoperatively diagnosed with early-stage cervical cancer based on preoperative inflammatory and immune nutritional indicators,and to construct a nomo-gram prediction model,providing a basis and tool for preoperative diagnosis of lymph node metastasis in cervical cancer.Methods:A retrospective analysis was conducted on the clinical data of 307 patients preoperatively diag-nosed with early-stage cervical cancer who underwent surgical treatment at the Obstetrics and Gynecology De-partment of the Second Affiliated Hospital of Zhengzhou University from January 2018 to July 2023.R software was used to randomize the groups into a training set(n=231)and a validation set(n=76)in a 3∶1 ratio.Uni-variate and multivariate logistic regression analyses were employed to identify factors influencing lymph node me-tastasis in patients preoperatively diagnosed with early-stage cervical cancer.R software was used to establish a nomogram prediction model and draw receiver operating characteristic(ROC)curves and calibration curves for validation.Results:① The results of univariate logistic regression analysis showed that positive lymphovascular invasion,platelet-to-lymphocyte ratio(PLR)≥151.70,neutrophil-to-white blood cell ratio(NWR)≥0.65,plate-let-to-albumin ratio(PAR)≥ 4.94,preoperative systemic immune-inflammation index(SII)≥604.03,and sys-temic inflammatory response index(SIRI)≥ 1.05 were associated with lymph node metastasis(P＜0.05).②Multivariate logistic regression analysis found that positive lymphovascular invasion,NWR≥0.65,and PAR≥4.94 were independent risk factors for lymph node metastasis in patients preoperatively diagnosed with early-stage cervical cancer(OR＞1,P＜0.05).③ A nomogram was constructed to predict lymph node metastasis in patients preoperatively diagnosed with early-stage cervical cancer.The ROC curve shows an area under the train-ing set curve(AUC)of 0.821 and a validation set AUC of 0.858.The calibration curve shows an average abso-lute error of 0.024 for the training set and 0.059 for the validation set.Conclusions:The prediction model for lymph node metastasis in cervical cancer constructed using preoperative inflammatory and immune nutritional indi-cators such as NWR,PAR is helpful for gynecological oncologists to predict lymph node metastasis in cervical cancer patients before surgery.