AIM: To investigate the associations of aqueous humor miR-21 and miR-29b levels with the severity of optic nerve damage and GMPE in patients with primary open angle glaucoma(POAG).METHODS:POAG patients who presented to the hospital from May 2023 to May 2025 were prospectively enrolled as the disease group, and patients with cataract treated during the same period were included as the control group. Baseline characteristics and aqueous humor levels of miR-21 and miR-29b were compared between the two groups. POAG patients were categorized into mild and moderate-to-severe groups according to the mean deviation(MD)of visual field. Clinical characteristics and the expression levels of miR-21 and miR-29b in aqueous humor were compared between the two groups. Correlations and nonlinear associations between miR-21/miR-29b levels and RNFL thickness, visual field MD, and BMO-MRW were evaluated. Furthermore, factors influencing the progression of optic nerve damage were analyzed. Based on prognostic outcomes, patients were divided into good prognosis and poor prognosis groups, and the aqueous humor levels of miR-21 and miR-29b were compared. ROC curve analysis was performed to assess the predictive value of combined GMPE with miR-21 and miR-29b for prognosis in POAG patients.Internal validation and decision curve analysis(DCA)were also conducted.RESULTS:This study included 151 patients in the disease group(age 56.07±7.59 y, 84 males and 67 females)and 138 patients in the control group(age 56.84±8.25 y, 68 males and 70 females). There were 45 cases in the mild group(age 54.63±7.34 y, 27 males and 18 females)and 106 cases in the moderate-severe group(age 56.68±8.39 y, 57 males and 49 females). There were 118 cases in the good prognosis group(age 55.83±8.07 y, 67 males and 51 females)and 33 cases in the poor prognosis group(age 56.94±8.23 y, 17 males and 16 females). Compared with the control group, the disease group exhibited significantly higher miR-21 levels and lower miR-29b levels(all P<0.001). Compared with the mild group, intraocular pressure and miR-21 levels were significantly higher in the moderate-to-severe group, while RNFL thickness, visual field MD, BMO-MRW, and miR-29b levels were significantly lower(all P<0.01). The miR-21/miR-29b ratio was negatively correlated with RNFL thickness, visual field MD, and BMO-MRW(all P<0.05). Elevated intraocular pressure and miR-21 levels, reduced RNFL thickness, lower visual field MD, and decreased BMO-MRW and miR-29b levels were identified as risk factors for aggravated optic nerve damage in POAG patients(all P<0.05). Compared with the good prognosis group, the poor prognosis group showed significantly higher miR-21 levels and lower miR-29b, RNFL, and BMO-MRW levels(all P<0.001). The combined prediction model incorporating aqueous humor miR-21, miR-29b, RNFL, and BMO-MRW yielded significantly higher AUC and specificity for predicting POAG prognosis than individual parameters alone(both P<0.05). The ROC prediction model demonstrated good consistency, and the combined prediction model exhibited high clinical utility.CONCLUSION: Aqueous humor levels of miR-21 are significantly elevated while miR-29b levels are significantly decreased in POAG patients, and these alterations are closely correlated with the severity of optic nerve damage and GMPE parameters.

BACKGROUND:Computer-assisted implant surgery can improve implantation accuracy,but the use of implant template in the posterior tooth area is limited for patients with small opening and small interocclusal distance.Therefore,the digital guide has been improved. OBJECTIVE:To study the effect of modified implant template on the accuracy of assisted implantation in missing second molars. METHODS:From July 2020 to July 2023,40 patients who received digital guide plate implantation or free hand implantation to repair missing second molars were selected from First Affiliated Hospital of Guangzhou Medical University.According to the coin toss method,patients were randomly divided into a trial group(n=22;modified digital guide assisted implantation)and a control group(n=18;free hand implantation).The data of neck deviation,tip deviation,depth deviation,and angle deviation were compared between groups for preoperative and postoperative cone beam CT overlap analysis.One week after the operation,the patients'satisfaction with the operation was assessed by visual analog scale score. RESULTS AND CONCLUSION:(1)The trial group included 25 implants(12 in the upper jaw and 13 in the lower jaw);the control group included 23 implants(8 in the upper jaw and 15 in the lower jaw).The neck deviation,tip deviation,depth deviation,and angle deviation of the trial group were all smaller than those of the control group(P<0.05,P<0.001).There was no significant difference in accuracy between the maxillary and mandibular implant site in the trial group(P>0.05).(2)There was no significant difference in satisfaction with the operation between the two groups(P>0.05).(3)The results showed that improving the digital guide plate for assisted implantation for missing second molar can improve surgical accuracy and is suitable for patients with small opening and small interocclusal distance in the posterior tooth area.

As one of the major diseases threatening human health,the early accurate diagnosis and localization of tumors are crucial for formulating effective treatment plans.In recent years,molecular probes(MPs)have made significant progress in the field of biological imaging.With advantages such as high sensitivity,high specificity,and non-invasiveness,they have become a research hotspot in the field of tumor diagnosis and treatment.This paper systematically reviews the applications of MPs in tumor diagnosis and treatment,covering their classifications(such as fluorescent,photoacoustic,chemiluminescent,bioluminescent,and multimodal probes),design strategies(including active/pas-sive targeting mechanisms and the synergistic construction of identification units,imaging units,signal conversion units and treatment units),as well as detection principles.It also focuses on elabo-rating the research progress of MPs based on enzymes,receptors,reactive substances,and tumor microenvironment.Meanwhile,this paper emphasizes the advantages of multifunctional integration and multimodal imaging,and analyzes the challenges faced by MPs in clinical translation(such as biocompatibility and optimization of supporting equipment).It aims to provide ideas for the develop-ment of high-performance MPs and promote the advancement of precise and personalized tumor di-agnosis and treatment.

Objective To analyze the influencing factors of the success of clinical pregnancy in secondary infertility patients undergoing in vitro fertilization-embryo transfer(IVF-ET)and construct a nomogram prediction model.Methods A retrospective analysis was conducted on the clinical data of 235 patients with secondary infertility who underwent IVF-ET at Urumqi Maternal and Child Health Hospital from January 2020 to December 2023.They were divided into successful pregnancy group(n=109)and failed pregnancy group(n=1 26)based on whether clinical pregnancy was successful.The general information,ovulation induction data and embryo data of two groups of patients were compared.Multivariate Logistic regression analysis was used to screen out statistically significant indicators,and based on this,a nomogram prediction model was constructed.The receiver operating characteristic curve,calibration curve and decision analysis curve were drawn to verify the discrimination,accuracy and clinical practicability of the model.Results The results of multivariate Logistic regression analysis showed that the female's age,overweight and obesity were all risk factors for clinical pregnancy failure,while anti-Müllerian hormone(AMH)and the total amount of gonadotropins(Gn)were protective factor for clinical pregnancy outcomes.On this basis,a nomogram prediction model was successfully constructed,which has a medium degree of discrimination,good accuracy and clinical practicability.Conclusion For secondary infertility patients undergoing IVF-ET,the female's age,overweight and obesity,AMH,and the total amount of Gn have certain influences on clinical pregnancy.The clinical pregnancy outcome can be predicted through the constructed nomogram prediction model.

As one of the major diseases threatening human health,the early accurate diagnosis and localization of tumors are crucial for formulating effective treatment plans.In recent years,molecular probes(MPs)have made significant progress in the field of biological imaging.With advantages such as high sensitivity,high specificity,and non-invasiveness,they have become a research hotspot in the field of tumor diagnosis and treatment.This paper systematically reviews the applications of MPs in tumor diagnosis and treatment,covering their classifications(such as fluorescent,photoacoustic,chemiluminescent,bioluminescent,and multimodal probes),design strategies(including active/pas-sive targeting mechanisms and the synergistic construction of identification units,imaging units,signal conversion units and treatment units),as well as detection principles.It also focuses on elabo-rating the research progress of MPs based on enzymes,receptors,reactive substances,and tumor microenvironment.Meanwhile,this paper emphasizes the advantages of multifunctional integration and multimodal imaging,and analyzes the challenges faced by MPs in clinical translation(such as biocompatibility and optimization of supporting equipment).It aims to provide ideas for the develop-ment of high-performance MPs and promote the advancement of precise and personalized tumor di-agnosis and treatment.

Endometriosis is an estrogen-dependent chronic inflammatory disease that affects 5%to 10%of women of reproductive age worldwide.Its typical symptoms include dysmenorrhea,infertility,and chronic pelvic pain,which seriously affect quality of life.The tradi-tional diagnostic methods include ultrasonography,magnetic resonance imaging,and laparoscopy.Among these,laparoscopy is considered the gold standard for diagnosis.However,its invasive nature limits its widespread application.Recently,artificial intelligence has rapidly advanced in the diagnosis of endometriosis,significantly improving the accuracy and efficiency of early diagnosis by integrating imaging,clinical data,and biomarkers.This article summarizes the limitations of traditional diagnostic methods for endometriosis and the advance-ments in the application of artificial intelligence in the diagnosis of endometriosis,while exploring the potential of artificial intelligence using practical case studies.

Objective To analyze the influencing factors of the success of clinical pregnancy in secondary infertility patients undergoing in vitro fertilization-embryo transfer(IVF-ET)and construct a nomogram prediction model.Methods A retrospective analysis was conducted on the clinical data of 235 patients with secondary infertility who underwent IVF-ET at Urumqi Maternal and Child Health Hospital from January 2020 to December 2023.They were divided into successful pregnancy group(n=109)and failed pregnancy group(n=1 26)based on whether clinical pregnancy was successful.The general information,ovulation induction data and embryo data of two groups of patients were compared.Multivariate Logistic regression analysis was used to screen out statistically significant indicators,and based on this,a nomogram prediction model was constructed.The receiver operating characteristic curve,calibration curve and decision analysis curve were drawn to verify the discrimination,accuracy and clinical practicability of the model.Results The results of multivariate Logistic regression analysis showed that the female's age,overweight and obesity were all risk factors for clinical pregnancy failure,while anti-Müllerian hormone(AMH)and the total amount of gonadotropins(Gn)were protective factor for clinical pregnancy outcomes.On this basis,a nomogram prediction model was successfully constructed,which has a medium degree of discrimination,good accuracy and clinical practicability.Conclusion For secondary infertility patients undergoing IVF-ET,the female's age,overweight and obesity,AMH,and the total amount of Gn have certain influences on clinical pregnancy.The clinical pregnancy outcome can be predicted through the constructed nomogram prediction model.

Objective To explore the impact of"knowledge-attitude-practice"(KAP)training mode on head nur-ses' core competency in healthcare-associated infection(HAI)prevention and control in a tertiary first-class general hospital.Methods Head nurses of 113 departments in a tertiary first-class general hospital were taken as the re-search objects.Guided by problems and demands,HAI training was conducted using the KAP training mode.The training was divided into two stages:a stage with problems of infection control and investigation of knowledge de-mands,as well as a stage with KAP training mode implementation.It included theoretical lectures,visits and lear-ning,and supervision on rectification.Scores of theory,supervision,and core competency of head nurses before training,1 month and 6 months after training were compared by the analysis of variance.SPSS 26.0 statistical soft-ware was used for analysis.Results The top three infection control problems in this hospital were hand hygiene,prevention and control of infection with multidrug-resistant organisms,as well as HAI prevention and control in the wards.The top three training modules required urgently by the head nurses were occupational exposure and self-protection,principles of medical waste disposal,as well as prevention and control of HAI in the wards.Both scores of theory and supervision after training were higher than those before training,with statistically significant diffe-rences(both P＜0.01).The core competencies of the head nurses were at a high level.After implementing KAP training mode,the scores of dimensions in critical thought and research,clinical nursing,leadership,and profe-ssional development,as well as the overall score of core competencies were all higher than before training.Diffe-rences were all statistically significant(all P＜0.05).The overall scores of dimensions in legal and ethical practice,education and consultation,as well as interpersonal relationship were all higher than before training,but the diffe-rences were not statistically significant(all P＞0.05).Conclusion KAP training mode can significantly improve the scores of theory,supervision,and core competencies of head nurses,and can be further promoted and applied in head nurses' infection control training.

Endometriosis is an estrogen-dependent chronic inflammatory disease that affects 5%to 10%of women of reproductive age worldwide.Its typical symptoms include dysmenorrhea,infertility,and chronic pelvic pain,which seriously affect quality of life.The tradi-tional diagnostic methods include ultrasonography,magnetic resonance imaging,and laparoscopy.Among these,laparoscopy is considered the gold standard for diagnosis.However,its invasive nature limits its widespread application.Recently,artificial intelligence has rapidly advanced in the diagnosis of endometriosis,significantly improving the accuracy and efficiency of early diagnosis by integrating imaging,clinical data,and biomarkers.This article summarizes the limitations of traditional diagnostic methods for endometriosis and the advance-ments in the application of artificial intelligence in the diagnosis of endometriosis,while exploring the potential of artificial intelligence using practical case studies.

Objective To explore the impact of"knowledge-attitude-practice"(KAP)training mode on head nur-ses' core competency in healthcare-associated infection(HAI)prevention and control in a tertiary first-class general hospital.Methods Head nurses of 113 departments in a tertiary first-class general hospital were taken as the re-search objects.Guided by problems and demands,HAI training was conducted using the KAP training mode.The training was divided into two stages:a stage with problems of infection control and investigation of knowledge de-mands,as well as a stage with KAP training mode implementation.It included theoretical lectures,visits and lear-ning,and supervision on rectification.Scores of theory,supervision,and core competency of head nurses before training,1 month and 6 months after training were compared by the analysis of variance.SPSS 26.0 statistical soft-ware was used for analysis.Results The top three infection control problems in this hospital were hand hygiene,prevention and control of infection with multidrug-resistant organisms,as well as HAI prevention and control in the wards.The top three training modules required urgently by the head nurses were occupational exposure and self-protection,principles of medical waste disposal,as well as prevention and control of HAI in the wards.Both scores of theory and supervision after training were higher than those before training,with statistically significant diffe-rences(both P＜0.01).The core competencies of the head nurses were at a high level.After implementing KAP training mode,the scores of dimensions in critical thought and research,clinical nursing,leadership,and profe-ssional development,as well as the overall score of core competencies were all higher than before training.Diffe-rences were all statistically significant(all P＜0.05).The overall scores of dimensions in legal and ethical practice,education and consultation,as well as interpersonal relationship were all higher than before training,but the diffe-rences were not statistically significant(all P＞0.05).Conclusion KAP training mode can significantly improve the scores of theory,supervision,and core competencies of head nurses,and can be further promoted and applied in head nurses' infection control training.