OBJECTIVES: To study the clinical effect of the L-shape technique combined with concentrated growth factor on the horizontal bone defects of maxillary anterior teeth. METHODS: Twenty-five implants from 25 patients who underwent single maxillary anterior tooth implantation with simultaneous bone grafting were selected as the study subjects. Based on the bone grafting techniques, the patients were divided into a test group (L-shaped technique with guided bone regeneration combined with concentrated growth factor, 11 cases) and a control group (traditional guided bone regeneration combined with concentrated growth factor, 14 cases). The early discomfort and wound healing conditions in the two groups at two weeks after surgery were compared. The horizontal bone thickness, vertical bone thickness, and grayscale values in the augmentation area were measured immediately postsurgery and six months after surgery. Implant stability, hard tissue resorption within six months, and grayscale values were compared between the two groups. RESULTS: Differences in early discomfort, wound healing, implant stability, and grayscale values between the two groups were not statistically significant (P>0.05). Vertical bone thickness in the test group was significantly better than that in the control group at six months after surgery (P<0.05). The variation in horizontal bone thickness in the test group was significantly higher than that in the control group (P<0.05). CONCLUSIONS The application of the L-shape technique with concentrated growth factor for horizontal bone defects in the anterior maxillary area yielded satisfactory short-term results in terms of bone augmentation, early discomfort, wound healing, and implant stability at six months after surgery.
Humans ; Maxilla/diagnostic imaging* ; Intercellular Signaling Peptides and Proteins/therapeutic use* ; Wound Healing ; Bone Transplantation/methods* ; Dental Implantation, Endosseous/methods* ; Bone Regeneration ; Male ; Female ; Adult ; Dental Implants, Single-Tooth ; Middle Aged

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 investigate the expression,synergistic relationship and clinical significance of alcohol de-hydrogenase(ADH1A)and vascular endothelial growth factor-A(VEGFA)in hepatocellular carcinoma(HCC).Methods The expression and correlation of ADH1A and VEGFA in HCC and adjacent normal tissues were ana-lyzed by GEPIA.TCGA and GSEA were used to analyze the pathway of ADH1A in HCC.The clinical and patho-logical data of 84 patients with HCC were collected,and 54 patients with paracancer normal tissue samples were se-lected as controls to analyze the correlation between ADH1A and VEGFA and clinicopathological parameters of HCC.Immunohistochemistry was used to detect the protein expression of ADH1A and VEGFA in cases and con-trols,and the correlation between the expression of ADH1A and VEGFA and the clinical progression and prognosis of patients with HCC was analyzed based on clinical pathological parameters and Kaplan-Meier.Results Bioinfor-matics analysis found that ADH1A was low-expressed in HCC and VEGFA was highly expressed in HCC,and there was a negative correlation between the two(P<0.001);immunohistochemical detection results showed that the expression of ADH1A in HCC tissue was lower than that in normal tissue adjacent to cancer(P<0.01)while the expression rate of VEGFA in HCC tissue was significantly higher than that of normal tissue adjacent to cancer(P<0.01);The recurrence rate of vascular thrombus and HCC patients in HCC group with high expression of ADH1A was lower(P<0.05).The proportion of tumor diameter>5 cm,high TNM stage,microsatellite and G2-G3 dif-ferentiation in HCC tissues in VEGFA high expression group was higher(P<0.05).Kaplan-Meier survival analy-sis showed that patients with high ADH1A expression and low VEGFA expression had a higher five-year survival rate.Conclusion Low expression of ADH1A and high expression of VEGFA in tumor tissues of patients with HCC indicate tumor progression and can be used as one of the prognostic evaluation indicators for patients with HCC.

Objective:To discuss the effect of sialic acid-binding immunoglobulin-like lectin-15(Siglec15)derived from M2 tumor-associated macrophages(M2-TAMs)on promoting the malignant biological behavior of the esophageal squamous cell carcinoma(ESCC)through bioinformatics analysis,and to validate the findings through cell experiment.Methods:The Tumor Immune Estimation Resource(TIMER)online Database was used to analyze the expression differences and immune infiltration of Siglec15 in pan-cancer and adjacent normal tissues.Real-time fluorescence quantitative PCR(RT-qPCR)method was used to detect the expression levels of Siglec15 mRNA in M2-TAMs and ESCC EC109 and KYSE150 cells.Based on the non-contact co-culture of M2-TAMs and ESCC cells,the following groups were set up,such as EC109/KYSE150 group,EC109/KYSE150+si-NC group(transfected with si-NC sequence),and EC109/KYSE150+si-Siglec15 group(transfected with si-Siglec15#1 and si-Siglec15#2 sequences).CCK-8 method was used to detect the proliferation activities of the cells in various groups;wound healing assay was used to detect the wound healing rates of the cells in various groups;Transwell chamber assay was used to detect the numbers of migration and invasion cells in various groups;flow cytometry was used to detect the apoptotic rates of the cells in various groups.Results:The bioinformatics analysis results showed that compared with adjacent normal tissue,the expression levels of Siglec15 mRNA in pan-cancer tissues such as esophageal cancer,colon cancer,and head and neck squamous cell carcinoma tissues were increased(P＜0.05 or P＜0.01),and the expression level of Siglec15 mRNA in esophageal cancer tissue was significantly positively correlated with the infiltration of the macrophages(P＜0.05).Compared with the EC109 cells and KYSE150 cells,the expression level of Siglec15 mRNA in M2-TAMs was significantly increased(P＜0.01).There was no significant difference in the proliferation rate of the cells among EC109/KYSE150 group,EC109/KYSE150+si-NC group,and EC109/KYSE150+si-Siglec15 group(P＞0.05).Compared with EC109/KYSE150 group,after treated for 24 and 48 h,the wound healing rate of the cells in EC109/KYSE150+si-NC group was increased(P＜0.01),the numbers of migration and invasion cells were increased(P＜0.05),and the apoptotic rate was decreased(P＜0.01).Compared with EC109/KYSE150+si-NC group,the wound healing rates of the cells in EC109/KYSE150+si-Siglec15#1 group and EC109/KYSE150+si-Siglec15#2 group were decreased(P＜0.05),the numbers of migration and invasion cells were decreased(P＜0.05),and the apoptotic rates of the cells had no significant difference(P＞0.05).Conclusion:Siglec15 derived from M2-TAMs may be a key factor in promoting the migration and invasion of the ESCC cells.

Objective This study aimed to evaluate the clinical outcomes of immediate implantation of single maxil-lary central incisor and explore factors affecting post-implant bone volume.Methods Clinical data and imaging records from pre-surgery,the day of surgery,and 6 months post-surgery of 100 patients(100 implants)with non-salvageable maxillary central incisors who underwent immediate implantation were collected.Bone thickness at the cervical,middle,and apical regions of the implant's labial and palatal sides were measured immediately post-surgery and at 6 months,and bone volume changes were observed.A regression analysis model was used to assess predictive factors for labial and pal-atal bone plate thickness.Results At 6 months post-surgery,the labial bone thicknesses at the cervical,middle,and api-cal regions were 2.35,2.29,and 3.28 mm,respectively,and those of the palatal side were 0.00,2.40,and 6.05 mm,re-spectively.The cervical region had the highest alveolar crest collapse rates,with 32.87%on the labial side and 62.20%on the palatal side.The regression model indicated that factors influencing the thickness of bone at the cervical labial side of the implant included initial bone thickness,the implant center to adjacent tooth center angle,implant diameter,and the type of implant closure(P<0.05).The initial bone thickness on the palatal side was the sole predictor for bone thickness on the palatal side(P<0.05).Conclusion Immediate implantation of single maxillary central incisors yields effective clinical results.The thickness of new bone around the implant is influenced by multiple factors.A comprehensive consideration of these factors in the plan-ning of immediate implantation is necessary to achieve optimal therapeutic outcomes.

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.