Objective:To explore the efficacy of the features of ultrasound imaging omics at the area peripheral thyroid nodule in predicting cervical lymph node metastasis(LNM)of papillary thyroid carcinoma(PTC),and construct a prediction model based on the features of imaging omics and to verify its performance.Methods:A total of 237 PTC patients who admitted to Shaanxi Provincial Hospital of Chinese Medicine from March 2021 to June 2024 and were confirmed by pathology were retrospectively collected.They were divided into the training set(166 cases)and the validation set(71 cases)as a ratio of 7 to 3.According to the postoperatively pathological results,237 patients were divided into the metastasis group(108 cases)and the non-metastasis group(129 cases).The clinical data and conventional ultrasound characteristic information of all patients were collected,and a feature model of imaging omics was constructed through quantitative extracting and screening the features of ultrasound imaging omics within nodules and peripheral nodules,and utilizing machine learning classifier.Then,the feature score(Rad-Score)of image omics was obtained.The Rad-Score values within and peripheral nodules,and the Rad-Score values peripheral nodules of metastasis group and non-metastasis group were compared.In training set,the independent risk factors of affecting neck LNM were analyzed,and a clinical-ultrasonic model was constructed,which was combined with Rad-Score to construct a joint model based on the features of imaging omics peripheral nodules.The receiver operating characteristic(ROC)curve was used to analyze and compare its predictive efficacy.The nomogram of the joint model was constructed,and then,the calibration and fitting degrees of the nomogram were assessed by calibration curve and Hosmer-Lemeshow test.Result:In training set,6 features of imaging omics within nodules and 11 features of imaging omics peripheral nodules were respectively extracted and screened out through the least absolute shrinkage and selection operator(LASSO)algorithm.In the training set and validation set,the Rad-Scores peripheral the nodules in the metastasis group were respectively(7.43±0.45)points and(7.19±0.51)points,which were significantly higher than(3.25±0.28)points and(3.51±0.32)points peripheral the nodules in the non-metastasis group,and the differences were statistically significant(t=72.708,61.222,P<0.05).The results of factor analysis showed that age,capsule invasion,microcalcification,ultrasound-indicated lymph node positivity and Rad-Score around nodules were independent risk factors of affecting cervical LNM of PTC patients(OR=0.592,2.983,3.593,4.424,2.575,P<0.05).The ROC curve showed that the area under curve(AUC)values of the ROC curve of joint model in training set and validation set were respectively 0.861 and 0.872 in predicting LNM,respectively,which were superior to 0.759 and 0.783 of the clinical-ultrasound model.Conclusion:In both the training set and the validation set,the nomogram of joint model has favorable calibration and fitting in predicting cervical LNM of PTC patients.The construction of clinical model based on the features of ultrasound imaging omics peripheral nodules has a favorable efficacy in predicting the status of cervical lymph node of PTC patients before surgery,which is expected to be an effective tool of individual prediction for LNM.

Objective:To explore the efficacy of the features of ultrasound imaging omics at the area peripheral thyroid nodule in predicting cervical lymph node metastasis(LNM)of papillary thyroid carcinoma(PTC),and construct a prediction model based on the features of imaging omics and to verify its performance.Methods:A total of 237 PTC patients who admitted to Shaanxi Provincial Hospital of Chinese Medicine from March 2021 to June 2024 and were confirmed by pathology were retrospectively collected.They were divided into the training set(166 cases)and the validation set(71 cases)as a ratio of 7 to 3.According to the postoperatively pathological results,237 patients were divided into the metastasis group(108 cases)and the non-metastasis group(129 cases).The clinical data and conventional ultrasound characteristic information of all patients were collected,and a feature model of imaging omics was constructed through quantitative extracting and screening the features of ultrasound imaging omics within nodules and peripheral nodules,and utilizing machine learning classifier.Then,the feature score(Rad-Score)of image omics was obtained.The Rad-Score values within and peripheral nodules,and the Rad-Score values peripheral nodules of metastasis group and non-metastasis group were compared.In training set,the independent risk factors of affecting neck LNM were analyzed,and a clinical-ultrasonic model was constructed,which was combined with Rad-Score to construct a joint model based on the features of imaging omics peripheral nodules.The receiver operating characteristic(ROC)curve was used to analyze and compare its predictive efficacy.The nomogram of the joint model was constructed,and then,the calibration and fitting degrees of the nomogram were assessed by calibration curve and Hosmer-Lemeshow test.Result:In training set,6 features of imaging omics within nodules and 11 features of imaging omics peripheral nodules were respectively extracted and screened out through the least absolute shrinkage and selection operator(LASSO)algorithm.In the training set and validation set,the Rad-Scores peripheral the nodules in the metastasis group were respectively(7.43±0.45)points and(7.19±0.51)points,which were significantly higher than(3.25±0.28)points and(3.51±0.32)points peripheral the nodules in the non-metastasis group,and the differences were statistically significant(t=72.708,61.222,P<0.05).The results of factor analysis showed that age,capsule invasion,microcalcification,ultrasound-indicated lymph node positivity and Rad-Score around nodules were independent risk factors of affecting cervical LNM of PTC patients(OR=0.592,2.983,3.593,4.424,2.575,P<0.05).The ROC curve showed that the area under curve(AUC)values of the ROC curve of joint model in training set and validation set were respectively 0.861 and 0.872 in predicting LNM,respectively,which were superior to 0.759 and 0.783 of the clinical-ultrasound model.Conclusion:In both the training set and the validation set,the nomogram of joint model has favorable calibration and fitting in predicting cervical LNM of PTC patients.The construction of clinical model based on the features of ultrasound imaging omics peripheral nodules has a favorable efficacy in predicting the status of cervical lymph node of PTC patients before surgery,which is expected to be an effective tool of individual prediction for LNM.

OBJECTIVE: To explore the clinical application value of mineralized collagen (MC) bone scaffolds in repairing various types of skull defects, and to assess the suitability and repair effectiveness of porous MC (pMC) scaffolds, compact MC (cMC) scaffolds, and biphasic MC composite (bMC) scaffolds. METHODS: A retrospective analysis was conducted on the clinical data of 105 patients who underwent skull defect repair with pMC, cMC, or bMC between October 2014 and April 2022. The cohort included 63 males and 42 females, ranging in age from 3 months to 55 years, with a median age of 22.7 years. Causes of defects included craniectomy after traumatic surgery in 37 cases, craniotomy in 58 cases, tumor recurrence or intracranial hemorrhage surgery in 10 cases. Appropriate MC scaffolds were selected based on the patient's skull defect size and age: 58 patients with defects <3 cm² underwent skull repair with pMC (pMC group), 45 patients with defects ≥3 cm² and aged ≥5 years underwent skull repair with cMC (cMC group), and 2 patients with defects ≥3 cm² and aged <5 years underwent skull repair with bMC (bMC group). Postoperative clinical follow-up and imaging examinations were conducted to evaluate bone regeneration, the biocompatibility of the repair materials, and the occurrence of complications. RESULTS: All 105 patients were followed up 3-24 months, with an average of 13 months. No material-related complication occurred in any patient, including skin and subcutaneous tissue infection, excessive ossification, and rejection. CT scans at 6 months postoperatively showed bone growth in all patients, and CT scans at 12 months postoperatively showed complete or near-complete resolution of bone defects in all patients, with 58 cases repaired in the pMC group. The CT values of the defect site and the contralateral normal skull bone in the pMC group at 12 months postoperatively were (1 123.74±93.64) HU and (1 128.14±92.57) HU, respectively, with no significant difference ( t=0.261, P=0.795). CONCLUSION MC exhibits good biocompatibility and osteogenic induction ability in skull defect repair. pMC is suitable for repairing small defects, cMC is suitable for repairing large defects, and bMC is suitable for repairing pediatric skull defects.
Humans ; Tissue Scaffolds ; Male ; Female ; Collagen ; Retrospective Studies ; Adult ; Child ; Adolescent ; Middle Aged ; Child, Preschool ; Skull/surgery* ; Young Adult ; Infant ; Plastic Surgery Procedures/methods* ; Tissue Engineering/methods* ; Craniotomy/methods* ; Bone Regeneration ; Treatment Outcome ; Porosity ; Biocompatible Materials

Objective To screen out the biomarkers linked to prognosis of breast invasive carcinoma based on the analysis of transcriptome data by random forest(RF),extreme gradient boosting(XGBoost),light gradient boosting machine(LightGBM),and categorical boosting(CatBoost).Methods We obtained the ex-pression data of breast invasive carcinoma from The Cancer Genome Atlas and employed DESeq2,t-test,and Cox univariate analysis to identify the differentially expressed protein-coding genes associated with survival prog-nosis in human breast invasive carcinoma samples.Furthermore,RF,XGBoost,LightGBM,and CatBoost mod-els were established to mine the protein-coding gene markers related to the prognosis of breast invasive cancer and the model performance was compared.The expression data of breast cancer from the Gene Expression Omnibus was used for validation.Results A total of 151 differentially expressed protein-coding genes related to survival prog-nosis were screened out.The machine learning model established with C3orf80,UGP2,and SPC25 demonstrated the best performance.Conclusions Three protein-coding genes(UGP2,C3orf80,and SPC25)were screened out to identify breast invasive carcinoma.This study provides a new direction for the treatment and diagnosis of breast invasive carcinoma.

Temporomandibular joint (TMJ) diseases are common clinical conditions. The number of patients with TMJ diseases is large, and the etiology, epidemiology, disease spectrum, and treatment of the disease remain controversial and unknown. To understand and master the current situation of the occurrence, development and prevention of TMJ diseases, as well as to identify the patterns in etiology, incidence, drug sensitivity, and prognosis is crucial for alleviating patients′suffering.This will facilitate in-depth medical research, effective disease prevention measures, and the formulation of corresponding health policies. Cohort construction and research has an irreplaceable role in precise disease prevention and significant improvement in diagnosis and treatment levels. Large-scale cohort studies are needed to explore the relationship between potential risk factors and outcomes of TMJ diseases, and to observe disease prognoses through long-term follw-ups. The consensus aims to establish a standard conceptual frame work for a cohort study on patients with TMJ disease while providing ideas for cohort data standards to this condition. TMJ disease cohort data consists of both common data standards applicable to all specific disease cohorts as well as disease-specific data standards. Common data were available for each specific disease cohort. By integrating different cohort research resources, standard problems or study variables can be unified. Long-term follow-up can be performed using consistent definitions and criteria across different projects for better core data collection. It is hoped that this consensus will be facilitate the development cohort studies of TMJ diseases.

BACKGROUND:Confirming the reliability and validity of the My jump 2 application for measuring lower limb vertical stiffness may offer the possibility of it as an alternative to the Kistler three-dimensional force platform for measuring lower limb stiffness. OBJECTIVE:To verify the reliability and validity of the My Jump 2 application in measuring lower limb vertical stiffness of college students. METHODS:The drop jump data of the participants were collected through the Kistler three-dimensional force platform and the My Jump 2 application,and the vertical stiffness of the participants'lower limb vertical stiffness was calculated.The intraclass correlation coefficient was used to analyze the data measured by the My Jump 2 application and the Kistler three-dimensional force platform,attempting to verify the reliability of the My Jump 2 application.The bias and average between the two devices were drawn into a Bland-Altman diagram to verify the consistency between the two test methods.Finally,the test-retest reliability of the My Jump 2 applications at 30 cm and 40 cm was analyzed using the Cronbach's alpha(α)and coefficient of variation.Pearson product-moment correlation was used to analyze the correlation of My Jump 2 applications. RESULTS AND CONCLUSION:My Jump 2 application has high reliability and validity when measuring the vertical stiffness of the lower limb.At the same time,due to its advantages of low cost,convenient portability and field testing for large samples,it can be used as an alternative to the Kistler three-dimensional force platform to test the vertical stiffness of the lower limb in college students and similar populations.

Objective To explore the causal relationship between family resilience and mental health in military personnel population.Methods A total of 204 military personnel were recruited from an army unit stationed in Western China with cluster convenience sampling.Family Resilience Scale(FRS)and Symptom Checklist 90(SCL-90)were used to survey them twice,in an interval of 4 months.Amos 26.0 was applied to construct a cross-lag model and analyze the data.Results After controlling mental symptoms from the first survey,family resilience in the first measure significantly predicted mental symptoms in the second measure(β=-0.14,P＜0.05).After controlling for family resilience from the first survey,mental symptoms in the first measure significantly predicted family resilience in the second measure(β=-0.13,P＜0.05).Conclusion The relationship between family resilience and mental health is mutually causal in military personnel,and one predicts the other one.Our findings highlight the key dimensions of the relationship between the two.

Objective To explore the effect of 6-week high-intensity interval training(HIIT)on health physical fitness of naval officers and soldiers.Methods Twenty male naval officers and soldiers were divided into experimental group and control group according to the random numer table,with 10 cases in each group.The experimental group participated in HIIT 3 times a week for 6 consecutive weeks,while the control group received routine physical fitness training.The physical fitness indexes,such as body fat percentage,plank,sit-and-reach,300-yard(1 yard≈0.914 m)shuttle run,grip strength,standing long jump and deep jump,were tested before and after training.Results Compared with before intervention,there were significant differences in body fat percentage(P=0.009),plank(P=0.003),300-yard shuttle run(P=0.014),sit-and-reach(P=0.05)and right hand grip strength(P=0.005)in the experimental group after intervention,and there were significant differences only in the plank(P=0.042)and standing long jump(P=0.041)in the control group.There were significant differences in the body fat percentage(P=0.016),plank(P=0.001),300-yard shuttle run(P=0.021),sit-and-reach(P=0.003),left hand grip strength(P=0.025)and right hand grip strength(P=0.001)between the two groups after intervention.Conclusion Six-week HIIT can enhance the health physical fitness in naval crews.

Humans ; Hospital Mortality ; Pulmonary Embolism ; Comorbidity ; Registries ; Neoplasms/complications*