Objective A Cobb angle prediction model for adolescent idiopathic scoliosis(AIS)based on three-point mechanical data from three-dimensional(3D)-printed orthotics and various machine learning algorithms was developed,so as to provide an innovative,radiation-free method for early clinical screening and monitoring of AIS.Methods Clinical data from AIS patients and mechanical data from 3D-printed orthotics were collected to construct a comprehensive dataset with features such as gender,age,disease type,weight,and Risser score.Six algorithms,namely,random forest,support vector regression,gradient boosting regressor,extreme gradient boosting,lightgbm,and catboost,were used to construct and evaluate the performance of Cobb angle prediction models.Results The gradient boosting regressor model had the best performance on several evaluation metrics,achieving a precision rate of 0.937,recall rate of 0.818,F1-score of 0.949,and an area under curve(AUC)value of 0.843.In the validation set,the model's predictions reached an accuracy rate of 0.942,fitting well with the actual Cobb values.Conclusions The Cobb angle prediction model based on mechanical data and machine learning effectively avoids the radiation risks associated with traditional full-spine X-ray examinations in early clinical screening.It provides a non-invasive assessment for AIS patients,enhancing the safety and efficiency of screening and monitoring,and offering a powerful decision-making tool for clinicians,with a great clinical significance.

Recent studies have shown that the physiological homeostasis of oral mucosal cells is regulated by the circadian clock.Dis-ruption or dysfunction of the circadian clock is closely associated with the development of oral squamous cell carcinoma(OSCC).Research based on the circadian clock offers a novel perspective on the pathogenesis and therapeutic strategies for OSCC.However,there is current-ly limited research on this topic,and people generally have insufficient understanding and recognition of the circadian clock.Given the complexity and challenges of circadian clock which is the fourth dimension of medical research,we organize relevant experts based on summarizing the current research results of circadian clock in the pathogenesis and precision diagnosis and treatment of OSCC,combining the scientific principles of the circadian clock's role and their long-term research experience,then summarizes and recommends the con-sensus opinions for the research of circadian clock in the pathogenesis mechanism and precision diagnosis and treatment of human OSCC,with the hope of providing guidance for the basic research and clinical application of circadian clock or circadian rhythm in the pathogene-sis mechanism and precision diagnosis and treatment of oral and maxillofacial squamous cell carcinoma.

Objective To explore the effect of early weight-bearing functional exercise on the postoperative function and satisfaction of patients with anterior talofibular ligament rupture.Methods Sixty patients with anterior talofibular ligament rupture admitted to Nanchang Hongdu Hospital of Traditional Chinese Medicine from June 2022 to June 2024 were included.According to the random number table method,the patients were divided into conventional group and early weight-bearing group,with 30 cases in each group.The American Orthopedic Foot and Ankle Society ankle-hindfoot scale(AOFAS-AHS)scores,Cumberland ankle instability tool(CAIT)scores,joint position sense active(JPSA)and joint position sense passive(JPSP)of ankle joint before and after the operation,and postoperative satisfaction of two groups of patients were compared.Results Six months after the operation,the AOFAS-AHS scores and CAIT scores of two groups were significantly higher than those before the operation,and the JPSA and JPSP were significantly lower than those before the operation(P＜0.05).The AOFAS-AHS score and CAIT score of patients of early weight-bearing group were significantly higher than those of conventional group,while the JPSA and JPSP were significantly lower than those of conventional group(P＜0.05).The satisfaction rate of patients of early weight-bearing group was significantly higher than that of conventional group(76.6％vs.66.6％,x2=6.205,P＜0.001).Conclusion Early weight-bearing functional exercise can improve the postoperative function of patients with anterior talofibular ligament rupture and enhance their postoperative satisfaction.

Objective To evaluate the inhibitory effect of Lactobacillus plantarum mouthwash on the progression of caries in isolated teeth.Methods Human isolated teeth were infected with Streptococcus mutans solution,and treated with saline,commercial mouth-wash,and Lactobacillus plantarum mouthwash,respectively,for 28 days.Tooth changes were recorded to assess their inhibitory effect on caries progression by light microscopy and scanning electron microscopy.Results Lactobacillus plantarum had an inhibitory effect on caries progression,with significant effects on deep dentinal caries in pit and fissure,and similar efficacy to commercial mouthwash on smooth surface caries.Calcium loss in dentin tubules was observed under an electron microscope,with Lactobacillus plantarum group less than commercial group and saline group.Conclusion Lactobacillus plantarum mouthwash can inhibit the growth of Streptococcus mutans and effectively prevent caries,particularly in controlling the progression of deep pit and fissure caries.

Objective To identify risk factors for colorectal adenomatous polyps using logistic regression analysis,construct a prediction model based on these identified factors,and subsequently evaluate the performance of the model.Methods Encompassed 1,023 patients who underwent large intestine polyp resection at the First Hospital of Handan between January 2017 and January 2022.Among these patients,676 had adenomatous polyps(adenomatous polyp group)and 347 had non-adenomatous polyps(non-adenomatous polyp group).We collected data on basic information,medical history,colonoscopy results,and polyp pathology.By comparing the two groups,we identified significant differences in various indicators,which were selected as candidate factors for model construction.Patients were randomly divided into a training set and a validation set at an 8∶2 ratio.Using the training set data,we constructed a risk prediction model and developed a nomogram using R Studio software to visually present the model.Finally,we internally validated the model using the validation set.The model's discrimination ability was evaluated using the ROC curve,its accuracy was assessed via the calibration curve,and its clinical utility was evaluated through decision curve analysis(DCA).Results Significant differences were observed between the two groups in terms of age,drinking habits,family history of colorectal cancer,hyperlipid-emia,history of cholecystectomy,HP infection,and history of appendectomy(P<0.05).These variables were included in the model construction.A total of 818 participants were randomly assigned to the training set,while 205 were allocated to the validation set.Multivariate logistic regression analysis on the training set confirmed that age(OR=1.021,95%CI:1.006～1.036,P=0.006),alcohol consumption(OR=3.440,95%CI:2.251～5.257,P<0.001),first-degree relatives with colorectal cancer(OR=3.775,95%CI:1.881～7.577,P<0.001),hyperlipidemia(OR=3.428,95%CI:2.443～4.808,P<0.001),history of cholecystectomy(OR=3.916,95%CI:1.756～8.735,P<0.001),Helicobacter pylori(HP)infection(OR=3.292,95%CI:2.309～4.693,P<0.001),and history of appendectomy(OR=3.819,95%CI:2.002～7.286,P<0.001)were independent risk factors for adenomatous polyps.Consequently,a prediction model for large intestine adenomatous polyps was developed using the formula P=1/(1+e-Y),where Y=0.020×age+1.328×first-degree relatives with colorectal cancer+1.235×alcohol consumption+1.232×hyperlipidemia+1.365×cholecystectomy+1.192×HP infection+1.340×appendectomy-1.995.The model demonstrated good performance with AUC values of 0.763(95%CI:0.729～0.797)for the training set and 0.769(95%CI:0.644～0.787)for the validation set.The calibration curve indicated a good fit,and decision curve analysis showed that the model could achieve positive net benefit across a wide range of threshold probabilities,confirming its clinical utility.Conclusions Age,alcohol consumption,a family history of colorectal cancer in first-degree relatives,hyperlipidemia,cholecystectomy,HP infection,and appendectomy were identified as independent risk factors for adenomatous polyps.A prediction model incorporating these risk factors holds significant practical value for predicting the occurrence of colorectal adenomatous polyps.

Objective To study the effect of wall thickness on the accuracy(trueness and precision)of 3D printed models.Methods The 3D scanning data of the standard gypsum dental arch model was imported into Exocad software.And four sets of models were de-signed,including horseshoe shaped solid model and horseshoe shaped hollow models with different wall thicknesses(2 mm,3 mm,4 mm).On the first and seventh day after printing,the 3D scanning data of resin models were imported into Geomagic software.Deviation analysis were performed on 3D printed models for the root mean square(root mean square,RMS).Results The trueness range of the four groups of printed models on the first day was(34.63±4.17)μm to(45.26±6.50)μm,there was no statistical difference.The pre-cision range was(30.25±10.18)μm to(47.65±14.77)μm,and the precision of the solid group was lower than the other three groups(P＜0.05).The trueness range of the four groups of printing models on the 7th day was(49.00±9.11)μm to(69.25±9.70)μm.The trueness of the 2 mm wall thickness group was lower than that of the solid group and the 4 mum wall thickness group(P＜0.05).Con-clusion The accuracy of printing models with different wall thicknesses was within the clinical acceptance range.There was no statisti-cally significant difference in the trueness values of the four groups of printing models on the first day.The precision value of the solid group was the lowest.On the 7th day,the trueness of the wall thickness of 2 mm group was lower than that of the solid group and the 4 mum wall thickness group.

Objective To identify risk factors for colorectal adenomatous polyps using logistic regression analysis,construct a prediction model based on these identified factors,and subsequently evaluate the performance of the model.Methods Encompassed 1,023 patients who underwent large intestine polyp resection at the First Hospital of Handan between January 2017 and January 2022.Among these patients,676 had adenomatous polyps(adenomatous polyp group)and 347 had non-adenomatous polyps(non-adenomatous polyp group).We collected data on basic information,medical history,colonoscopy results,and polyp pathology.By comparing the two groups,we identified significant differences in various indicators,which were selected as candidate factors for model construction.Patients were randomly divided into a training set and a validation set at an 8∶2 ratio.Using the training set data,we constructed a risk prediction model and developed a nomogram using R Studio software to visually present the model.Finally,we internally validated the model using the validation set.The model's discrimination ability was evaluated using the ROC curve,its accuracy was assessed via the calibration curve,and its clinical utility was evaluated through decision curve analysis(DCA).Results Significant differences were observed between the two groups in terms of age,drinking habits,family history of colorectal cancer,hyperlipid-emia,history of cholecystectomy,HP infection,and history of appendectomy(P<0.05).These variables were included in the model construction.A total of 818 participants were randomly assigned to the training set,while 205 were allocated to the validation set.Multivariate logistic regression analysis on the training set confirmed that age(OR=1.021,95%CI:1.006～1.036,P=0.006),alcohol consumption(OR=3.440,95%CI:2.251～5.257,P<0.001),first-degree relatives with colorectal cancer(OR=3.775,95%CI:1.881～7.577,P<0.001),hyperlipidemia(OR=3.428,95%CI:2.443～4.808,P<0.001),history of cholecystectomy(OR=3.916,95%CI:1.756～8.735,P<0.001),Helicobacter pylori(HP)infection(OR=3.292,95%CI:2.309～4.693,P<0.001),and history of appendectomy(OR=3.819,95%CI:2.002～7.286,P<0.001)were independent risk factors for adenomatous polyps.Consequently,a prediction model for large intestine adenomatous polyps was developed using the formula P=1/(1+e-Y),where Y=0.020×age+1.328×first-degree relatives with colorectal cancer+1.235×alcohol consumption+1.232×hyperlipidemia+1.365×cholecystectomy+1.192×HP infection+1.340×appendectomy-1.995.The model demonstrated good performance with AUC values of 0.763(95%CI:0.729～0.797)for the training set and 0.769(95%CI:0.644～0.787)for the validation set.The calibration curve indicated a good fit,and decision curve analysis showed that the model could achieve positive net benefit across a wide range of threshold probabilities,confirming its clinical utility.Conclusions Age,alcohol consumption,a family history of colorectal cancer in first-degree relatives,hyperlipidemia,cholecystectomy,HP infection,and appendectomy were identified as independent risk factors for adenomatous polyps.A prediction model incorporating these risk factors holds significant practical value for predicting the occurrence of colorectal adenomatous polyps.

Objective To investigate the clinical treatment effect and safety of 3D microscopy technology for adjuvant neuraxial tumor resection on neuraxial tumor diseases.Methods A total of 37 patients with neuraxial tumors treated from January 2019 to July 2023,15 patients treated with 3D microscope tumor resection(3D group),and 22 patients treated with general microscope tumor resection(ordinary group)were analyzed.The perioperative indexes,clinical efficacy indexes and safety indexes were compared between the two groups.Results The operation time was(223.78±46.46)min in the ordinary group and(182.93±39.28)min in the 3D group,which was significantly lower than that in the ordinary group(P<0.05),and there was no significant difference in other perioperative indicators between the two groups(P>0.05).All patients had significantly reduced their postoperative pain symptoms and recovered their neurological function to a certain extent.There were statistically significant differences between the two groups(P<0.01),but there was no statistical difference between the two groups(P>0.05),and the McCormick spinal cord function rating was grade I.at one year after surgery.Conclusion The use of 3D microscopy and general microscopy for neuraxial tumor surgery has good clinical efficacy.However,the operation time can be significantly shortened under 3D microscopy,thereby reducing the risk of surgical complications and has better clinical safety.

Objective To study the effect of wall thickness on the accuracy(trueness and precision)of 3D printed models.Methods The 3D scanning data of the standard gypsum dental arch model was imported into Exocad software.And four sets of models were de-signed,including horseshoe shaped solid model and horseshoe shaped hollow models with different wall thicknesses(2 mm,3 mm,4 mm).On the first and seventh day after printing,the 3D scanning data of resin models were imported into Geomagic software.Deviation analysis were performed on 3D printed models for the root mean square(root mean square,RMS).Results The trueness range of the four groups of printed models on the first day was(34.63±4.17)μm to(45.26±6.50)μm,there was no statistical difference.The pre-cision range was(30.25±10.18)μm to(47.65±14.77)μm,and the precision of the solid group was lower than the other three groups(P＜0.05).The trueness range of the four groups of printing models on the 7th day was(49.00±9.11)μm to(69.25±9.70)μm.The trueness of the 2 mm wall thickness group was lower than that of the solid group and the 4 mum wall thickness group(P＜0.05).Con-clusion The accuracy of printing models with different wall thicknesses was within the clinical acceptance range.There was no statisti-cally significant difference in the trueness values of the four groups of printing models on the first day.The precision value of the solid group was the lowest.On the 7th day,the trueness of the wall thickness of 2 mm group was lower than that of the solid group and the 4 mum wall thickness group.

Objective A Cobb angle prediction model for adolescent idiopathic scoliosis(AIS)based on three-point mechanical data from three-dimensional(3D)-printed orthotics and various machine learning algorithms was developed,so as to provide an innovative,radiation-free method for early clinical screening and monitoring of AIS.Methods Clinical data from AIS patients and mechanical data from 3D-printed orthotics were collected to construct a comprehensive dataset with features such as gender,age,disease type,weight,and Risser score.Six algorithms,namely,random forest,support vector regression,gradient boosting regressor,extreme gradient boosting,lightgbm,and catboost,were used to construct and evaluate the performance of Cobb angle prediction models.Results The gradient boosting regressor model had the best performance on several evaluation metrics,achieving a precision rate of 0.937,recall rate of 0.818,F1-score of 0.949,and an area under curve(AUC)value of 0.843.In the validation set,the model's predictions reached an accuracy rate of 0.942,fitting well with the actual Cobb values.Conclusions The Cobb angle prediction model based on mechanical data and machine learning effectively avoids the radiation risks associated with traditional full-spine X-ray examinations in early clinical screening.It provides a non-invasive assessment for AIS patients,enhancing the safety and efficiency of screening and monitoring,and offering a powerful decision-making tool for clinicians,with a great clinical significance.