ObjectiveThis study aims to compare the modeling effects of submaxillary gland antigen and salivary gland antigen in the establishment of Sjögren syndrome (SS) mouse models, and to characterize the phenotypic and immunological features of these models in comparison with spontaneous SS-prone non-obese diabetic (NOD)/LtJ mice. MethodsAdult C57BL/6J mice (equal numbers of males and females) were immunized with submaxillary gland antigen or salivary gland antigen, respectively, combined with Freund's adjuvant to induce SS models. Mice immunized with phosphate-buffered saline (PBS) combined with Freund's adjuvant served as the control group. Immunization was induced via multiple subcutaneous injections in the back with antigen combined with Freund's complete adjuvant (FCA) on Days 1 and 7. A booster immunization was administered via multiple subcutaneous injections in the back with antigen combined with Freund's incomplete adjuvant (FIA) on Day 14. Female NOD/LtJ mice were used as the spontaneous SS model group, with ICR mice as the corresponding control strain for comparative analysis. Body weight, water intake, and salivary flow rate of mice were dynamically monitored for 4 weeks. At the end of the experiment, tissue and serum samples were collected, the weights of submaxillary glands, thymus, and spleen were measured, and organ indices (organ-to-body weight ratios) were calculated. Pathological morphological analysis of the submaxillary gland and spleen was performed with hematoxylin and eosin (HE) staining. Serum interleukin-17 (IL-17) level was detected using enzyme-linked immunosorbent assay (ELISA). Real-time quantitative polymerase chain reaction was used to detect the mRNA expression levels of SS type A (SSA) and SS type B (SSB) in submaxillary gland tissues. ResultsFemale mice in the submaxillary gland antigen group exhibited significantly increased water intake (P<0.05) and reduced salivary flow rate (P<0.05) compared with the female control group. No statistically significant differences were observed in the submaxillary gland index, thymus index and spleen index (P>0.05). Focal lymphocytic infiltration was observed in the submaxillary glands, and the splenic marginal zone was enlarged. Serum IL-17 levels were significantly increased (P<0.05). There was no significant difference in submaxillary gland SSA/SSB expression levels (P>0.05). Compared with the female control group, female mice in the salivary gland antigen group showed no statistically significant differences in water intake, salivary flow rate, submaxillary gland index, and spleen index (P>0.05), whereas the thymus index was significantly reduced (P<0.01). Mild inflammatory cell infiltration and glandular atrophy were observed in the submaxillary glands, and the splenic white pulp and marginal zone were slightly enlarged. Serum IL-17 levels and submaxillary gland SSB mRNA expression levels were significantly increased (P<0.01), whereas no significant change was observed in submaxillary gland SSA expression levels (P>0.05). Compared with the male control group, mild submaxillary gland atrophy was observed in male mice in the submaxillary gland antigen group, whereas no obvious changes were found in other modeling-related indicators (P>0.05). Compared with the ICR control group, NOD/LtJ model mice exhibited elevated water intake (P<0.05), significantly reduced salivary flow rate (P<0.01), no significant differences in the submaxillary gland index or spleen index (P>0.05), but a significantly increased thymus index (P<0.05). Marked focal infiltration was observed in the submaxillary glands, the splenic marginal zone was obviously enlarged, and serum IL-17 concentrations as well as submaxillary gland SSA/SSB expression levels were significantly increased (P<0.05). ConclusionSubmaxillary gland antigen and salivary gland antigen can induce SS-related features in female C57BL/6J mice. The SS-related phenotype is more pronounced in the submaxillary gland antigen group than in the salivary gland antigen group, but weaker than that in spontaneously SS-prone female NOD/LtJ mice. Immunization of male C57BL/6J mice with submaxillary or salivary gland antigens fails to induce an obvious SS phenotype.

Objective: To investigate the efficacy of magnesium-strontium co-doped hydroxyapatite mineralized collagen (MSHA/Col) in improving the bone repair microenvironment and enhancing bone regeneration capacity, providing a strategy to address the insufficient biomimetic composition and limited bioactivity of traditional hydroxyapatite mineralized collagen (HA/Col) scaffolds. Methods: A high-molecular-weight polyacrylic acid-stabilized amorphous calcium magnesium strontium phosphate precursor (HPAA/ACMSP) was prepared. Its morphology and elemental distribution were characterized by high-resolution transmission electron microscopy (TEM) and energy-dispersive spectroscopy. Recombinant collagen sponge blocks were immersed in the HPAA/ACMSP mineralization solution. Magnesium-strontium co-doped hydroxyapatite was induced to deposit within collagen fibers (experimental group: MSHA/Col; control group: HA/Col). The morphological characteristics of MSHA/Col were observed using scanning electron microscopy (SEM). Its crystal structure and chemical composition were analyzed by X-ray diffraction and Fourier transform infrared spectroscopy, respectively. The mineral phase content was evaluated by thermogravimetric analysis. The scaffold's porosity, ion release, and in vitro degradation performance were also determined. For cytological experiments, CCK-8 assay, live/dead cell staining, alkaline phosphatase staining, alizarin red S staining, RT-qPCR, and western blotting were used to evaluate the effects of the MSHA/Col scaffold on the proliferation, viability, early osteogenic differentiation activity, late mineralization capacity, and gene and protein expression levels of key osteogenic markers [runt-related transcription factor 2 (Runx2), collagen type Ⅰ (Col-Ⅰ), osteopontin (Opn), and osteocalcin (Ocn)] in mouse embryonic osteoblast precursor cells (MC3T3-E1). Results: HPAA/ACMSP appeared as amorphous spherical nanoparticles under TEM, with energy spectrum analysis showing uniform distribution of carbon, oxygen, calcium, phosphorus, magnesium, and strontium elements. SEM results of MSHA/Col indicated successful complete intrafibrillar mineralization. Elemental analysis showed the mass fractions of magnesium and strontium were 0.72% (matching the magnesium content in natural bone) and 2.89%, respectively. X-ray diffraction revealed characteristic peaks of hydroxyapatite crystals (25.86°, 31°-34°). Infrared spectroscopy results showed characteristic absorption peaks for both collagen and hydroxyapatite. Thermogravimetric analysis indicated a mineral phase content of 78.29% in the material. The scaffold porosity was 91.6% ± 1.1%, close to the level of natural bone tissue. Ion release curves demonstrated sustained release behavior for both magnesium and strontium ions. The in vitro degradation rate matched the ingrowth rate of new bone tissue. Cytological experiments showed that MSHA/Col significantly promoted MC3T3-E1 cell proliferation (130% increase in activity at 72 h, P < 0.001). MSHA/Col exhibited excellent efficacy in promoting osteogenic differentiation, significantly upregulating the expression of osteogenesis-related genes and proteins (Runx2, Col-Ⅰ, Opn, Ocn) (P < 0.01). Conclusion The MSHA/Col scaffold achieves dual biomimicry of natural bone in both composition and structure, and effectively promotes osteogenic differentiation at the genetic and protein levels, breaking through the functional limitations of pure hydroxyapatite mineralized collagen. This provides a new strategy for the development of functional bone repair materials

OBJECTIVE:Postoperative recurrence is a common complication of percutaneous endoscopic lumbar discectomy for lumbar disc herniation,which can significantly increase the risk of reoperation.A well-performing risk prediction model can help identify high-risk groups early and prevent postoperative recurrence.This study systematically evaluated the risk prediction model for postoperative recurrence after percutaneous endoscopic lumbar discectomy to provide a reference for surgical decision-making.METHODS:The PubMed,Embase,Web of Science,CNKI,WanFang Data,VIP,and CBM were electronically searched to collect studies on the recurrence risk prediction models after percutaneous endoscopic lumbar discectomy from inception to July 1,2024.Two reviewers independently screened the literature and extracted data.The models' risk of bias,applicability,and report quality were assessed using prediction model risk of bias assessment tool(PROBAST)and Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis(TRIPOD)tools,respectively.Meta-analysis of postoperative recurrence rate of percutaneous endoscopic lumbar discectomy and related predictors was performed using Revman 5.4 software.RESULTS:(1)A total of 15 studies were included,all of which were retrospective studies,including 24 models for predicting the risk of recurrence after percutaneous endoscopic lumbar discectomy.(2)The PROBAST evaluation results indicated that all 15 studies exhibited a high risk of bias.Regarding applicability,two studies demonstrated a low risk,while 13 presented a high risk.(3)Regarding the TRIPOD reporting quality,the overall quality across the 15 studies was low.The primary reasons for this low compliance included the failure to report blinding,a lack of explanation for the sample size calculation method,lack of detailed description of missing data processing methods,and lack of information such as introduction to the model used.(4)Furthermore,the area under the receiver operating characteristic curve for the model ranged from 0.684 to 0.972,with the number of potential predictor variables varying from 15 to 28.(5)The results of meta-analysis showed that the postoperative recurrence rate of lumbar disc herniation patients treated with percutaneous endoscopic lumbar discectomy was 12％(95％CI=9.0％-15.0％),Modic changes(OR=6.72,95％CI=3.90-11.59),body mass index(OR=1.28,95％CI=1.10-1.49),work intensity(OR=3.22,95％CI=1.85-5.59),age(OR=2.28,95％CI=1.50-3.48),and smoking history(OR=2.65,95％CI=1.75-4.00)were independent influencing factors for postoperative recurrence of percutaneous endoscopic lumbar discectomy(all P＜0.05).CONCLUSION:The overall predictive performance of the recurrence risk prediction models after percutaneous endoscopic lumbar discectomy is satisfactory;however,the model exhibits a high overall risk of bias and applicability,coupled with low reporting quality.Additionally,there is a lack of prospective research and external validation.Future,risk prediction models should consider factors such as Modic changes,body mass index,work intensity,age,and smoking history as potential predictors.

OBJECTIVE:Postoperative recurrence is a common complication of percutaneous endoscopic lumbar discectomy for lumbar disc herniation,which can significantly increase the risk of reoperation.A well-performing risk prediction model can help identify high-risk groups early and prevent postoperative recurrence.This study systematically evaluated the risk prediction model for postoperative recurrence after percutaneous endoscopic lumbar discectomy to provide a reference for surgical decision-making.METHODS:The PubMed,Embase,Web of Science,CNKI,WanFang Data,VIP,and CBM were electronically searched to collect studies on the recurrence risk prediction models after percutaneous endoscopic lumbar discectomy from inception to July 1,2024.Two reviewers independently screened the literature and extracted data.The models' risk of bias,applicability,and report quality were assessed using prediction model risk of bias assessment tool(PROBAST)and Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis(TRIPOD)tools,respectively.Meta-analysis of postoperative recurrence rate of percutaneous endoscopic lumbar discectomy and related predictors was performed using Revman 5.4 software.RESULTS:(1)A total of 15 studies were included,all of which were retrospective studies,including 24 models for predicting the risk of recurrence after percutaneous endoscopic lumbar discectomy.(2)The PROBAST evaluation results indicated that all 15 studies exhibited a high risk of bias.Regarding applicability,two studies demonstrated a low risk,while 13 presented a high risk.(3)Regarding the TRIPOD reporting quality,the overall quality across the 15 studies was low.The primary reasons for this low compliance included the failure to report blinding,a lack of explanation for the sample size calculation method,lack of detailed description of missing data processing methods,and lack of information such as introduction to the model used.(4)Furthermore,the area under the receiver operating characteristic curve for the model ranged from 0.684 to 0.972,with the number of potential predictor variables varying from 15 to 28.(5)The results of meta-analysis showed that the postoperative recurrence rate of lumbar disc herniation patients treated with percutaneous endoscopic lumbar discectomy was 12％(95％CI=9.0％-15.0％),Modic changes(OR=6.72,95％CI=3.90-11.59),body mass index(OR=1.28,95％CI=1.10-1.49),work intensity(OR=3.22,95％CI=1.85-5.59),age(OR=2.28,95％CI=1.50-3.48),and smoking history(OR=2.65,95％CI=1.75-4.00)were independent influencing factors for postoperative recurrence of percutaneous endoscopic lumbar discectomy(all P＜0.05).CONCLUSION:The overall predictive performance of the recurrence risk prediction models after percutaneous endoscopic lumbar discectomy is satisfactory;however,the model exhibits a high overall risk of bias and applicability,coupled with low reporting quality.Additionally,there is a lack of prospective research and external validation.Future,risk prediction models should consider factors such as Modic changes,body mass index,work intensity,age,and smoking history as potential predictors.

Objective To investigate the relationship between the comorbidity of dyslipidemia, hypertension and diabetes and lifestyle of adult residents in Hebei Province in 2018, and to provide reference for the development of chronic diseases prevention measures. Methods Using data from the surveillance of chronic diseases and their risk factors among adults in Hebei in 2018, 7 711 permanent residents aged ≥18 years were selected as the research subjects. Multivariate logistic regression analysis was used to analyze the relationship between the comorbidity of dyslipidemia, hypertension, and diabetes and lifestyle in adult residents. Results A total of 7 711 subjects aged ≥18 years were included in 2018. The comorbidity rates of hypertension and dyslipidemia, diabetes and dyslipidemia, and hypertension and diabetes were 16.88%, 7.91%, and 8.13%, respectively. The comorbidity rate of hypertension, diabetes, and dyslipidemia was 22.65%. These comorbidity rates increased with age and BMI. Multivariate logistic regression results showed that male, age, overweight/obesity, physical inactivity, daily sedentary behavior time ≥5 hours, and sleep problems were risk factors for the comorbidity of the "three highs". Conclusion The prevalence of the "three highs" comorbidities is relatively high in Hebei Province, and there are multiple common risk factors. Maintaining a healthy lifestyle and implementing comprehensive prevention and control measures are the key to improving the health level of residents.

Objective:To evaluate the value of ultrasound radiomics combined with machine learning for early diagnosis of seronegative Hashimoto’s thyroiditis (SN-HT) .Methods:This retrospective study included 164 patients from Liaoning Provincial People’s Hospital , Lixin County People’s Hospital, Linghai Dalinghe Hospital, Fengcheng Phoenix Hospital, who underwent thyroidectomy for solitary nodules with normal thyroid function between Nov. 2016 and Jan. 2024. Postoperative pathology confirmed Hashimoto’s thyroiditis (HT) in some cases, who were further categorized into antibody-positive and antibody-negative groups based on serum antibody status. Patients without Hashimoto’s thyroiditis served as the control group. A total of 298 ultrasound images were analyzed. Radiomics features were extracted from hypoechoic non-nodular areas within 0.5 cm surrounding the tumor. Two senior pathologists and two senior ultrasound physicians independently assessed lymphocytic infiltration, eosinophilic changes of follicular epithelium, and the proportion of hypoechoic areas in pathology and ultrasound images, respectively. A machine learning model, CCH-NET, was developed using linear regression and t-distributed stochastic neighbor embedding (t-SNE) techniques. The dataset was divided into a training set (80%) and a validation set (20%) to compare the diagnostic accuracy of CCH-NET with that of senior ultrasound physicians. Results:In internal validation, CCH-NET achieved a diagnostic accuracy of 88.89% for both antibody-positive and antibody-negative groups, significantly higher than the 66.67% accuracy of senior ultrasound physicians ( P<0.01). In external validation, CCH-NET achieved 75.00% and 66.67% accuracy for the two groups, compared to 50.00% by senior ultrasound physicians. For the control group, both methods achieved 93.33% accuracy. The AUC of CCH-NET was 0.848, outperforming senior ultrasound physicians (0.681) ,demonstrating superior diagnostic performance. Conclusion:The radiomics-based CCH-NET model, using non-nodular hypoechoic areas as a specific indicator, can accurately identify early SN-HT in euthyroid patients. It significantly outperforms senior ultrasound physicians, improving diagnostic accuracy and reducing missed diagnoses.

Objective:To evaluate the value of ultrasound radiomics combined with machine learning for early diagnosis of seronegative Hashimoto’s thyroiditis (SN-HT) .Methods:This retrospective study included 164 patients from Liaoning Provincial People’s Hospital , Lixin County People’s Hospital, Linghai Dalinghe Hospital, Fengcheng Phoenix Hospital, who underwent thyroidectomy for solitary nodules with normal thyroid function between Nov. 2016 and Jan. 2024. Postoperative pathology confirmed Hashimoto’s thyroiditis (HT) in some cases, who were further categorized into antibody-positive and antibody-negative groups based on serum antibody status. Patients without Hashimoto’s thyroiditis served as the control group. A total of 298 ultrasound images were analyzed. Radiomics features were extracted from hypoechoic non-nodular areas within 0.5 cm surrounding the tumor. Two senior pathologists and two senior ultrasound physicians independently assessed lymphocytic infiltration, eosinophilic changes of follicular epithelium, and the proportion of hypoechoic areas in pathology and ultrasound images, respectively. A machine learning model, CCH-NET, was developed using linear regression and t-distributed stochastic neighbor embedding (t-SNE) techniques. The dataset was divided into a training set (80%) and a validation set (20%) to compare the diagnostic accuracy of CCH-NET with that of senior ultrasound physicians. Results:In internal validation, CCH-NET achieved a diagnostic accuracy of 88.89% for both antibody-positive and antibody-negative groups, significantly higher than the 66.67% accuracy of senior ultrasound physicians ( P<0.01). In external validation, CCH-NET achieved 75.00% and 66.67% accuracy for the two groups, compared to 50.00% by senior ultrasound physicians. For the control group, both methods achieved 93.33% accuracy. The AUC of CCH-NET was 0.848, outperforming senior ultrasound physicians (0.681) ,demonstrating superior diagnostic performance. Conclusion:The radiomics-based CCH-NET model, using non-nodular hypoechoic areas as a specific indicator, can accurately identify early SN-HT in euthyroid patients. It significantly outperforms senior ultrasound physicians, improving diagnostic accuracy and reducing missed diagnoses.

Robot-assisted surgery with its advantages such as three-dimensional high-definition vision, dexterous robotic arms, and tremor filtration, is increasingly being applied to complex radical gastrectomy. However, the role of the surgical assistant remains crucial during the procedure. The assistant is responsible for tasks outside the console, including adjusting robotic arms, changing instruments, exposing the surgical field, and addressing unexpected situations. The technical proficiency of the assistant and their collaboration efficiency with the primary surgeon directly impact the smoothness of surgery and patients' outcomes. With the expansion of robot-assisted surgical indications, the establishment of a standardized training system and the optimization of team collaboration models have become urgent challenges to address. This article draws on the author's practical experience as an assistant in robot-assisted gastric cancer surgeries, conducting an in-depth analysis of the responsibilities and operational skills of surgical assistants in robot-assisted procedures. The aim is to develop a relatively comprehensive set of operational guidelines for surgical assistants in robot-assisted radical gastrectomy, providing valuable references for enhancing the overall efficiency of surgical teams and improving surgical outcomes.

ObjectiveTo explore the changes in volatile components， total polysaccharides， enzyme activity， and chromaticity value of Myristicae Semen Koji（MSK） during the fermentation process， and conduct correlation analysis. MethodsBased on gas chromatography-mass spectrometry（GC-MS）， the changes of volatile components in MSK at different fermentation times were identified. The phenol sulfuric acid method， dinitrosalicylic acid method（DNS）， and carboxymethyl cellulose sodium salt method（CMC-Na） were used to investigate the total polysaccharide content， amylase activity， and cellulase activity during the fermentation process. Visual analysis technology was used to explore the changes in chromaticity values， revealing the fermentation process of MSK and the dynamic changes of various measurement indicators， partial least squares-discriminant analysis（PLS-DA） was used to explore the differential compounds of MSK at different fermentation degrees， and Pearson correlation analysis was used to explore the correlation between volatile components of MSK and total polysaccharides， enzyme activity， and chromaticity values. ResultsA total of 60 volatile compounds were identified from MSK， the relative contents of components such as （+）-α-pinene， β-phellandrene， β-pinene， （+）-limonene， and p-cymene obviously increased， while the relative contents of components such as safrole， methyl isoeugenol， methyleugenol， myristicin， and elemicin significantly decreased. During the fermentation process， the total polysaccharide content showed an upward trend， while the activities of amylase and cellulase showed an initial increase followed by a decrease， and reached their maximum value at 40 h. the overall brightness（L^*） and total color difference（ΔE^*） gradually increased， while the changes in red-green value（a^*） and yellow-blue value（b^*） were not obvious. PLS-DA results showed that MSK could be clearly distinguished at different fermentation times， and 13 differential biomarkers were screened out. Pearson correlation analysis results showed that the contents of α-terpinene， β-phellandrene， methyleugenol， β-cubebene and myristic acid had an obvious correlation with chromaticity values. ConclusionAfter fermentation， the volatile components， total polysaccharides， amylase activity， and cellulase activity of MSK undergo significant changes， and there is a clear correlation between them and chromaticity values， which reveals the dynamic changes in the fermentation process and related indicators of MSK， laying a foundation for the quality control.

Objective To explore the symptom clusters in renal transplant recipients and con-struct a concurrent symptom network to identify core symptoms.Methods A total of 343 patients with followed up after renal transplantation were selected as the study subjects.A general information questionnaire and the Chinese version of the Modified Transplant Symptom Occurrence and Symptom Distress Scale were employed to analyze the occurrence of symptoms in patients.In this study,only symptoms with an incidence rate greater than 20％and Spearman correlation coefficient greater than 0.40 between symptom severity and total score were retained.Exploratory factor analysis was used to extract symptom clusters with a factor loading of ≥0.45 as the criterion.The R language was utilized to construct symptom network,based on which core symptoms and bridge symptoms were identified.Results A total of 5 symptom clusters were extracted in this study:the neuro-gastrointestinal symp-tom cluster,the mood-related symptom cluster,the hormone-related symptom cluster,the energy de-ficiency symptom cluster and the vision-related symptom cluster.The core symptoms were anxiety(rs=1.75),mood swings(rs=1.50)and muscle weakness(rs=1.27).The top three symptoms in terms of bridge strength were muscle weakness(rb=0.87),lack of vitality(rb=0.66)and fa-tigue(rb=0.65).Conclusion Multiple symptoms are presented in patients after renal transplanta-tion.Based on the results of symptom network analysis,clinicians can strengthen the assessment of core symptoms and bridge symptoms to develop precise intervention strategies and improve the effectiveness of symptom management.