This paper introduces a real-world cohort research model for community-acquired pneumonia （CAP） based on the Jiangsu Traditional Chinese Medicine （TCM） Dominant Diseases Diagnosis and Treatment Data Platform. Firstly， data cleaning is performed by standardizing diagnosis， symptoms， treatment and imaging， intelligently extracting unstructured information， and cleaning and constructing a standardized database. Secondly， for cohort establishment， CAP patients across the province are screened in accordance with CAP diagnostic criteria to build a high-quality disease-specific cohort. Lastly， in terms of protocol design， the characteristics of TCM research and the CAP disease profile are considered to determine appropriate inclusion and exclusion criteria， estimate sample size， define interventions， outcomes and economic evaluations， providing a reference for real-world TCM research on CAP.

This paper introduces a real-world cohort research model for community-acquired pneumonia （CAP） based on the Jiangsu Traditional Chinese Medicine （TCM） Dominant Diseases Diagnosis and Treatment Data Platform. Firstly， data cleaning is performed by standardizing diagnosis， symptoms， treatment and imaging， intelligently extracting unstructured information， and cleaning and constructing a standardized database. Secondly， for cohort establishment， CAP patients across the province are screened in accordance with CAP diagnostic criteria to build a high-quality disease-specific cohort. Lastly， in terms of protocol design， the characteristics of TCM research and the CAP disease profile are considered to determine appropriate inclusion and exclusion criteria， estimate sample size， define interventions， outcomes and economic evaluations， providing a reference for real-world TCM research on CAP.

Objective: To explore the influencing factors of anxiety symptoms and to construct a predictive model based on machine learning algorithms, so as to provide support for the prevention and management of anxiety symptoms among junior high school students. Methods: From April to May 2023, a stratified random cluster sampling method was adopted to select 8 176 junior high school students from Zhengzhou and Shangqiu citys. All participants completed the Adolescent Self rating Life Events Checklist, the 10item Connor-Davidson Resilience Scale, the School Connectedness Scale, the Parent-Child Cohesion Questionnaire, and the 7 item Generalized Anxiety Disorder Scale. Logistic regression analysis identified the associated factors of anxiety symptoms among junior high school students. Predictive models were constructed using Logistic regression, Random Forest, and eXtreme Gradient Boosting (XGBoost) algorithms, with SHapley Additive exPlanations analysis explaining the optimal model. Results: The detection rate of anxiety symptoms among junior high school students was 16.3%. Logistic regression analysis showed that junior high school students who were female ( OR =1.22), in the ninth grade ( OR =1.27), living in urban areas ( OR =1.37), having a father with a college education or above ( OR =1.26), having a mother with a senior high school education ( OR =1.26), and experiencing higher levels of negative life events ( OR =1.05) reported a higher risk of anxiety symptoms(all P <0.05). In contrast, those with moderate family economic status ( OR =0.71), moderate academic burden ( OR =0.59), low academic burden ( OR =0.54), moderate sleep quality ( OR =0.46), good sleep quality ( OR =0.26), excellent sleep quality ( OR =0.15), higher levels of psychological resilience ( OR =0.96), higher levels of school connectedness ( OR =0.96), and higher levels of parent-child cohesion ( OR =0.98) reported a lower risk of anxiety symptoms (all P <0.05). Three machine learning models demonstrated good predictive performance for anxiety symptoms among junior high school students (all AUC>0.8), with the XGBoost model achieving the best predictive performance. SHAP analysis revealed that negative life events, sleep quality, school connectedness, psychological resilience and parent-child cohesion were the top five relevant factors for predicting anxiety symptoms. Conclusions The detection rate of anxiety symptoms among junior high school students is relatively high. The XGBoost model is the optimal predictive model for anxiety symptoms in the population. Negative life events, sleep quality, school connectedness, psychological resilience, and parent-child cohesion are significant correlates of anxiety symptoms among junior high school students.

Objective To investigate the setup error in patients with spinal bone metastasis who underwent radiotherapy under the guidance of kilovoltage cone-beam CT (KV-CBCT). Methods A total of 118 patients with spinal metastasis who underwent radiotherapy, including 17 cases of cervical spine, 62 cases of thoracic spine, and 39 cases of lumbar spine, were collected. KV-CBCT scans were performed using the linear accelerators from Elekta and Varian’s EDGE system. CBCT images were registered with reference CT images in the bone window mode. A total of 973 data were collected, and 3D linear errors were recorded. Results The patients with spinal bone metastasis were grouped by site, height, weight, and BMI. The P value of the patients grouped only by site was P<0.05, which was statistically significant. Conclusion When grouped by site in the 3D direction, the positioning effect of cervical spine is better than that of thoracic and lumbar spine. The positioning effect of the thoracic spine is better in the head and foot direction but worse in the left and right direction compared with that of the lumbar spine. Instead of extending or narrowing the margin according to the BMI of patients with spinal metastasis, the margin must be changed according to the site of spinal bone metastasis.

BACKGROUND:Early exercise treatment is the main prevention way for traumatic joint contracture and is also a research focus.Swimming may be a potential intervention for joint contracture due to the special physical properties of water. OBJECTIVE:To explore the effects of swimming on the development of joint contracture in a rat model and study its mechanisms. METHODS:Twenty-four Sprague-Dawley rats were randomly divided into a blank control group(n=8)and a joint contracture group(n=16).After the surgical operation of knee joint contracture rat models,the joint contracture group was randomly subdivided into a surgical control group(n=8)and a swimming treatment group(n=8).Swimming started in the swimming treatment group in the second week after surgery and lasted for a total of 5 weeks.At the 6th week after surgery,the body mass,knee joint range of motion,and quadriceps diameter were tested,and the diameter/body mass index was calculated.Hematoxylin-eosin staining was performed to detect the pathological changes in the knee joint capsule and quadriceps muscle,and Masson staining was used to observe fibrotic changes in the knee joint capsule.Furthermore,the protein expression of transforming growth factor β1 and type I collagen in the knee joint capsule was quantified by immunohistochemical assay and western blot was performed to detect the protein expression of MuRF1 in the quadriceps femoris. RESULTS AND CONCLUSION:Compared with the blank control group,the knee range of motion decreased in the surgical control and swimming treatment groups(P<0.01),and knee extension deficit and arthrogenic extension deficit were significantly increased(P<0.01),the diameter of the quadriceps muscle was decreased(P<0.01),the joint capsule showed significant fibrosis,the quadriceps muscle was atrophied,and the diameter/body mass index was decreased(P<0.01).Compared with the surgical control group,the swimming treatment group showed a significant increase in knee joint range of motion and quadriceps diameter(P<0.01),and significant improvement in joint capsule fibrosis and quadriceps atrophy.Compared with the blank control group,collagen fiber content and expression of transforming growth factor β1 and type I collagen were increased in the joint capsule of rats in both the surgical control group and the swimming treatment group(P<0.01).Compared with the surgical control group,collagen fiber content and expression of transforming growth factor β1 and type I collagen protein in the joint capsule were decreased in the swimming treatment group.Compared with the blank control group,the expression of MuRF1 protein in the quadriceps muscle of rats in the surgical control group and the swimming treatment group was increased(P<0.05).Compared with the surgical control group,the expression of MuRF1 protein in the quadriceps muscle of rats in the swimming treatment group was decreased(P<0.05).To conclude,early swimming intervention reduces transforming growth factor β1 and type I collagen expression in the joint capsule of traumatic joint contracture rats,decreases MuRF1 expression in the quadriceps muscle,and increases joint range of motion and quadriceps diameter,thereby inhibiting the development of joint contracture.

This case report describes a 68-year-old male patient diagnosed with primary hepatocellular carcinoma (HCC). After receiving Yttrium-90 microsphere selective internal radiation therapy (⁹⁰Y-SIRT), the tumor significantly reduced in size, and tumor markers alpha fetoprotein (AFP) and abnormal prothrombin (PIVKA-Ⅱ) decreased. Postoperative pathological results showed minimal residual tumor cells, indicating that ⁹⁰Y-SIRT has good efficacy and safety in downstaging and conversion of HCC, thereby facilitating subsequent surgical resection.

A method for determination and targeted screening of diflorasone components in health products using ultra performance liquid chromatography-quadrupole time of flight mass spectrometry(UPLC-Q-TOF/MS)was established.Four representative diflorasone and esters(diflorasone,diflorasone diacetate,diflorasone-17-propionate,and diflorasone-21-propionate)were selected to optimize the pretreatment conditions,and 10 mL of extraction solvent dosage,15 min of extraction time and 5 g of salting-out agent as the optimal conditions were selected by response surface methodology.The results showed that the four analytes exhibited good linearity within the concentration range of 2.0?100 μg/L with the chromatographic peak area,and the correlation coefficients(R2)were all greater than 0.9990,while the results of recovery and relative standard deviation could satisfy the requirements of determination.The common characteristic ions of diflorasone and esters werem/z121 andm/z335,and their specific structures were obtained by analyzing the cleavage pathway based on the optimized determination conditions.A targeted screening method for other esters of diflorasone based on characteristic ions guidance strategy was established.This method had many advantages such as high efficiency,high sensitivity and good reproducibility,and could be used for targeted screening of diflorasone and esters in health products.The developed characteristic ion guided strategy could be employed to construct mass spectral databases for various glucocorticoids,enabling comprehensive targeted screening across a broad range of compounds.

A micro gas chromatographic column with mesoporous surface micro column array prepared by anodization method was proposed.A porous support layer with a characteristic pore size of about 30 nm inside the chromatographic column was prepared in situ using anodization method,and a uniform alumina stationary phase was deposited on the mesoporous support layer using atom layer deposition(ALD)technique.The existence of a mesoporous support layer increased surface area of the chromatographic column,thereby increasing the total amount of stationary phase loading and enhancing column capacity,which facilitated chromatographic separation.The test results showed that the porous support layer significantly reduced the longitudinal molecular diffusion and mass transfer resistance of the micro gas chromatographic column,and significantly increased the number of theoretical plates(n-nonane increased by 290.2%).Furthermore,column efficiency of the chromatographic column was less affected by flow rate,which was conducive to rapid separation of heavy hydrocarbon mixtures.

Aerosol-assisted plasma amplification laser-induced breakdown spectroscopy(LIBS)was employed for phosphorus detection in water.To address the multivariate coupling effects in LIBS and nebulization sampling system,an orthogonal experiment was employed to systematically optimize the key experimental parameters.Using the orthogonal experimental design,the parametric effects of laser energy(output voltage),signal acquisition delay,liquid velocity,and gas velocity on the signal to background ratio(SBR)of P I 213.618 nm were evaluated,and the optimal conditions were achieved,including laser energy of 86 mJ,delay time of 3 μs,gas velocity of 1.05 mL/min,and liquid velocity of 60 μL/min,which were in agreement with the control-variable optimization results.Moreover,the SBR response trends at P I 213.618 nm with all experimental parameters was strong in consistency with control-variable optimization results,which demonstrated the validity of the orthogonal array experimental design.This study established an efficient and accurate parameter optimization methodology for complex LIBS systems,significantly advancing the application of LIBS in environmental monitoring.

Objective:To optimize the image quality of PET/CT following 90Y-selective internal radiation therapy ( 90Y-SIRT) using block-sequential regularized expectation maximization (BSREM) reconstruction algorithm, and to evaluate its impact of different β values on image quality and quantitative analysis. Methods:A retrospective study was conducted on 8 male patients with hepatic tumors (age: 62(52, 71) years) treated at Beijing Tsinghua Changgung Hospital, School of Clinical Medicine, Tsinghua Medicine Tsinghua University, between June 2024 and January 2025. All patients were treated with 90Y resin microspheres (2.6(0.9, 3.6)GBq) and underwent post-treatment 90Y PET/CT liver imaging. Imaging data were reconstructed using BSREM with different noise penalty weighting factors ( β values: 0, 300, 1000, 1500, 2500, 3500, 4000, 6000, 8000, 10000). Visual assessment was independently performed by two nuclear medicine physicians, using a 4-point scale (1=worst, 4=best). The mean score was considered as the final score. The consistency of the 2 reviewers was calculated and analyzed by Kappa test. Visual scores of different β value groups were compared by Friedman test. The β value demonstrating highest mean score and optimal consistency was selected as the optimal. Quantitative analysis was performed using MIM software to calculate the maximum absorbed dose ( Dmax) and the mean absorbed dose ( Dmean) for tumor, normal liver, and whole liver regions, and the CV was used to evaluate the impact of β values. Results:The visual assessment consistency of reviewers in 3 β value groups (0, 3500, 6000) were the highest (7/8) (all kappa=0.88, all P<0.05). Visual scores of the 10 β value groups were significantly different ( χ2=28.74, P<0.001), and the visual scores of 2 β value groups (3500, 4000) were the highest, both of which were 4.0(4.0, 4.0). Overall, visual assessment identified β=3500 as the optimal. Quantitative analysis revealed that, (1) Dmax in all regions (tumor, normal liver, whole liver) decreased with the increasing β values, stabilizing when β>1000 ( CV 56%-67%); (2) Dmean remained stable across different β values ( CV 0.04%-5.00%). Conclusions:In BSREM reconstruction, β=3500 is the optimal parameter for improving 90Y-PET image quality. β values significantly affect Dmax (stabilizing at β > 1000), but have no significant impact on Dmean, suggesting that reconstruction parameters primarily influence dose distribution morphology rather than average dose assessments.