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.

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.

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.

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.

ObjectiveTo investigate the effects of thyme herbal tea （BLX） on the proliferation of human coronavirus OC43 （HCoV-OC43） in vitro and in vivo. MethodThe chemical composition of BLX was analyzed by UPLC-MS. The cytotoxicity of BLX in HRT-18 cells and the effect of BLX treatment on the proliferation of HCoV-OC43 in cells were analyzed. Copies of viral gene were detected by real-time PCR. The effect of BLX treatment on the life cycle of HCoV-OC43 was detected by time-of-addition assay. The maximum tolerated dose of BLX and the influences of BLX on the body weight and survival time of suckling mice infected with HCoV-OC43 were determined. The expression of viral protein in the brain and lung tissue was analyzed by immunohistochemistry. ResultThere were 11 chemical components identified in BLX by UPLC-MS. BLX showed the 50% cytotoxic concentration （CC₅₀） of （13 859.56±319） mg·L^-1， the median inhibitory concentration （IC₅₀） of （1 439.09±200） mg·L^-1， and the selection index of 8.26-11.44 for HCoV-OC43 in HRT-18 cells. Compared with the cells infected with HCoV-OC43， BLX at the concentrations of 1 500， 1 000， 500 mg·L^-1 inhibited the proliferation of this virus （P<0.05， P<0.01）. BLX exhibited antiviral effect in the early stage of virus infection， and the inhibition role in the attachment stage was more significant than that in the entry stage （P<0.05）. In the suckling mice infected with HCoV-OC43， BLX at 1200 and 600 mg·kg^-1·d^-1 alleviated the symptoms， prolonged the survival period， reduced the death rate， and down-regulated the mRNA level of nucleocapsid protein in the mice. Moreover， BLX at 1 200 mg·kg^-1·d^-1 down-regulated the expression of nucleocapsid protein in the brain （P<0.01） and the lung （P<0.01）. ConclusionBLX contained multiple antiviral ingredients. It inhibited the proliferation of HCoV-OC43 both in vitro and in vivo by interference with viral attachment. This study provides theoretical reference for the treatment of acute respiratory tract infection with HCoV-OC43 and for further development and application of BLX.