Objective To explore the efficacy of bilateral facial muscle training combined with visual electromyography biofeedback on facial nerve function recovery in patients with idiopathic facial nerve palsy. Methods Patients with idiopathic facial nerve palsy admitted to Shanghai Fifth People’s Hospital, Fudan University from July 2022 to July 2024 were selected and randomly divided into a control group and an intervention group. The control group received conventional physical factor therapy, while the intervention group received bilateral facial muscle training combined with visual electromyography biofeedback therapy based on the control group’s regimen. After 20 treatment sessions, the total effective rate, the House-Brackmann (H-B) facial nerve grading system, the Sunnybrook Facial Grading System (SFGS) score, and the average value ratio of maximal amplitudes of bilateral frontalis and zygomaticus muscles were compared between the two groups. Results A total of 90 patients were included, 45 in each group. After 20 treatment sessions, the total effective rate was significantly higher in the intervention group than in the control group (84.4% vs 75.6%, P＝0.003). Compared with the control group, the intervention group demonstrated a significantly lower H-B grade (P＝0.003) and a higher SFGS score (P＝0.001). The average value ratios of maximal amplitudes of the affected versus healthy side frontalis (P＝0.013) and zygomatic (P＝0.022) muscles were higher in the intervention group than in the control group. Conclusions Bilateral facial muscle training combined with visual electromyography biofeedback is an effective approach for treating idiopathic facial nerve palsy, effectively promoting the recovery of facial nerve function, and improving facial symmetry and facial muscle function.

Objective:To screen differentially expressed circular RNAs(circRNA)associated with lymph node metastasis in cervical cancer and investigate their molecular mechanism and biological function.Methods:Cancer tissue samples were collected from 40 cervical cancer patients(20 with lymph node metastasis and 20 without lymph node metastasis).Three specimens were randomly selected from each group,and the circRNA expression profile was analyzed using high-throughput sequencing technology,and perform KEGG and GO enrichment analy-sis was performed on the differentially expressed circRNA derived mother genes.Real-time fluorescence quantita-tive PCR(qRT-PCR)technology was used to validate four significantly upregulated circRNAs with high differential multiples,and a ceRNA network was constructed for database prediction.The relationship between circRNA with the most significant differential expression and clinical pathological features was analyzed.Transfect circRNA small interfering RNA(siRNA)into cervical cancer cell lines.Cell lines were divided into circRNA knockdown group and negative control(si-NC)group.The proliferation of SiHa cells and HeLa cells in cervical cancer was detected by Cell Counting Kit-8(CCK-8).Results:①A total of 2039 differentially expressed circRNAs were detec-ted.The differentially expressed circRNA derived mother genes are mainly enriched in ubiquitin mediated protein hydrolysis,MAPK signaling pathway,endocytosis,apoptosis and other signaling pathways.②Four significantly up-regulated circRNAs with high differential multiples in the transfer group were selected,which are hsa_circ_0067492,hsa_circ_0004904,hsa_circ_0085465,and hsa_circ_0007718.qRT-PCR showed that hsa_circ_0004904,hsa_circ_0085465,and hsa_circ_0007718 were all highly expressed in cervical cancer tissues with lymph node metas-tasis(P<0.01).Hsa_circ_0004904 could interact with microRNAs(miRNAs)such as hsa-miR-3916.Hsa_circ_0085465 could interact with miRNAs such as hsa-miR-4659b-3p,and hsa_circ_0007718 could interact with miRNAs such as hsa-miR-127-5p.③The high and low expression groups of hsa_circ_0004904 showed statistically signigi-cant differences in lymph node metastasis and lymphovascular invasion status(P<0.05).Compared with the si-NC group,the proliferation ability of SiHa cells and HeLa cells was significantly reduced after transfection with hsa_circ_0004904 at 24,48,and 72 hours(P<0.05).Conclusions:Differentially expressed circRNAs were identi-fied in cervical cancer patients with lymph node metastasis.Silencing these circRNAs significantly inhibited the proliferation of cervical cancer cells,suggesting their potential involvement in the progression of lymph node me-tastasis.These circRNAs may serve as specific biomarkers for predicting lymph node metastasis.

Objective:To screen differentially expressed circular RNAs(circRNA)associated with lymph node metastasis in cervical cancer and investigate their molecular mechanism and biological function.Methods:Cancer tissue samples were collected from 40 cervical cancer patients(20 with lymph node metastasis and 20 without lymph node metastasis).Three specimens were randomly selected from each group,and the circRNA expression profile was analyzed using high-throughput sequencing technology,and perform KEGG and GO enrichment analy-sis was performed on the differentially expressed circRNA derived mother genes.Real-time fluorescence quantita-tive PCR(qRT-PCR)technology was used to validate four significantly upregulated circRNAs with high differential multiples,and a ceRNA network was constructed for database prediction.The relationship between circRNA with the most significant differential expression and clinical pathological features was analyzed.Transfect circRNA small interfering RNA(siRNA)into cervical cancer cell lines.Cell lines were divided into circRNA knockdown group and negative control(si-NC)group.The proliferation of SiHa cells and HeLa cells in cervical cancer was detected by Cell Counting Kit-8(CCK-8).Results:①A total of 2039 differentially expressed circRNAs were detec-ted.The differentially expressed circRNA derived mother genes are mainly enriched in ubiquitin mediated protein hydrolysis,MAPK signaling pathway,endocytosis,apoptosis and other signaling pathways.②Four significantly up-regulated circRNAs with high differential multiples in the transfer group were selected,which are hsa_circ_0067492,hsa_circ_0004904,hsa_circ_0085465,and hsa_circ_0007718.qRT-PCR showed that hsa_circ_0004904,hsa_circ_0085465,and hsa_circ_0007718 were all highly expressed in cervical cancer tissues with lymph node metas-tasis(P<0.01).Hsa_circ_0004904 could interact with microRNAs(miRNAs)such as hsa-miR-3916.Hsa_circ_0085465 could interact with miRNAs such as hsa-miR-4659b-3p,and hsa_circ_0007718 could interact with miRNAs such as hsa-miR-127-5p.③The high and low expression groups of hsa_circ_0004904 showed statistically signigi-cant differences in lymph node metastasis and lymphovascular invasion status(P<0.05).Compared with the si-NC group,the proliferation ability of SiHa cells and HeLa cells was significantly reduced after transfection with hsa_circ_0004904 at 24,48,and 72 hours(P<0.05).Conclusions:Differentially expressed circRNAs were identi-fied in cervical cancer patients with lymph node metastasis.Silencing these circRNAs significantly inhibited the proliferation of cervical cancer cells,suggesting their potential involvement in the progression of lymph node me-tastasis.These circRNAs may serve as specific biomarkers for predicting lymph node metastasis.

Recent clinical studies have shown that mutation of phosphatase and tensin homolog deleted on chromosome 10 (PTEN) gene in cancer cells may be associated with immunosuppressive tumor microenvironment (TME) and poor response to immune checkpoint blockade (ICB) therapy. Therefore, efficiently restoring PTEN gene expression in cancer cells is critical to improving the responding rate to ICB therapy. Here, we screened an adeno-associated virus (AAV) capsid for efficient PTEN gene delivery into B16F10 tumor cells. We demonstrated that intratumorally injected AAV6-PTEN successfully restored the tumor cell PTEN gene expression and effectively inhibited tumor progression by inducing tumor cell immunogenic cell death (ICD) and increasing immune cell infiltration. Moreover, we developed an anti-PD-1 loaded phospholipid-based phase separation gel (PPSG), which formed an in situ depot and sustainably release anti-PD-1 drugs within 42 days in vivo. In order to effectively inhibit the recurrence of melanoma, we further applied a triple therapy based on AAV6-PTEN, PPSG^@anti-PD-1 and CpG, and showed that this triple therapy strategy enhanced the synergistic antitumor immune effect and also induced robust immune memory, which completely rejected tumor recurrence. We anticipate that this triple therapy could be used as a new tumor combination therapy with stronger immune activation capacity and tumor inhibition efficacy.

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.