Objective: To investigate the distribution of pupil diameter and its association with myopia in school age children, providing ideas into the mechanisms of the role of pupil diameter in the onset and development of myopia. Methods: Adopting a combination of stratified cluster random sampling and convenience sampling method, 3 839 children from six schools in Shandong Province were included in September 2021. Pupil diameters distribution was analyzed by age, sex, and myopic status. Pearson correlation analysis was used to assess the relationship between pupil diameter and cycloplegic spherical equivalent (SE), as well as axial length (AL) and other variables. Propensity score matching (PSM) was applied to match myopic and non myopic children at a 1∶1 ratio based on age and sex. A generalized linear model (GLM) was constructed with pupil diameter as the dependent variable to identify independent factors influencing pupil size and its association with myopia. Results: The mean pupil diameter of school age children was (5.77±0.80)mm. Pupil diameter exhibited a significant increasing trend with age ( F =49.34， P trend ＜ 0.01). Myopic children had a significantly larger mean pupil diameter [(6.10±0.73)mm] compared to non myopic children [(5.62±0.79)mm] with a statistically significant difference( t=18.10, P <0.01). Multivariable GLM analysis, adjusted for age, amplitude of accommodation, and uncorrected visual acuity, revealed a negative correlation between pupil diameter and cycloplegic SE (before PSM: β =-0.089, after PSM: β =-0.063, both P ＜0.01). Conclusions Myopic school age children exhibite larger pupil diameters than their non myopic counterparts. Pupil diameter may serve as a potential indicator for monitoring myopia development in school age children.

Objective To observe impact factors of average glandular dose(AGD)of full field digital mammography(FFDM)and digital breast tomosynthesis(DBT)under breast Combo mode.Methods Totally 169 subjects who received FFDM and DBT under Combo mode were collected retrospectively.The breast compression thickness,tube voltage,tube current and AGD of FFDM and DBT exposure at cranio-caudal(CC)and mediolateral oblique(MLO)positions of bilateral breast were recorded.FFDM or DBT exposure conditions and AGD among different breast compression thickness and breast types were compared,and their correlations were analyzed.The impacts of breast compression thickness and breast density on AGD of FFDM or DBT were observed.Results There were significant differences in tube voltage,tube current and AGD of FFDM or DBT among different breast compression thicknesses(all P＜0.001).With the increase of breast compression thickness,tube voltage,tube current and AGD of FFDM or DBT all increased(all P＜0.001).There were statistical differences in breast compression thickness,tube voltage,tube current and AGD of FFDM or DBT among different types breast(all P＜0.001).Hierarchical analysis showed that,when breast compression thickness was＜50 mm,50-59 mm and＞59 mm respectively,statistical differences in AGDFFDM and AGDDBT among different breast types at CC or MLO positions were found(all P＜0.001).Under the same breast compression thickness,tube current,AGDFFDM and AGDDBT of FFDM or DBT all increased with the increase of breast density(all P＜0.001),while tube voltage of FFDM or DBT had no obvious change(all P＞0.05).Breast compression thickness and breast density were both independent factors of AGD of FFDM or DBT(all P＜0.001).Conclusion Under breast Combo mode,breast compression thickness and gland density both had impacts on AGD of FFDM or DBT,and the former had more significant impact on AGD.

Objective To develop a toolkit suitable for assisting community health institutions in the early identification and inter-vention of mild cognitive impairment(MCI)among older adults.Methods A literature review was conducted to construct a draft of the identification and intervention toolkit.Tools with an expert approval rate above 70%were included after expert consultation.The final version of the toolkit was developed by integrating these tools with officially recommended tools in China.Results The expert consultation yielded an authority coefficient of 0.84.The finalized toolkit included the assessment tools of Mini-Mental State Examination,Montreal Cognitive Assessment,General Practitioner Assessment of Cognition,Cognitive Abilities Screening Instrument and Clock Drawing Test,and 18 intervention measures in-cluding pharmacological treatment,cognitive training and psychological interventions,etc.Conclusion The MCI Identification-Intervention Toolkit may serve as a reference for guiding the identification and inter-vention of MCI among older adults for community health institutions.

Objective To investigate the effect of transcutaneous auricular vagus nerve stimulation(taVNS)on quality of early postoperative recovery in patients undergoing thoracoscopic lung resection.Methods A total of 168 patients scheduled for elective thoracoscopic lung resection(wedge resection,segmentectomy,lobectomy)under general anesthesia were enrolled and randomly assigned to active-taVNS group(group T)or sham-taVNS group(group S)(n=84).Participants received four consecutive 30-minute sessions of active stimulation or sham stimulation at four time points:(1)the afternoon prior to the surgery,(2)the morning of the surgery,(3)following extubation,and(4)the first afternoon post-surgery.The Quality of Recovery-15(QoR-15)scores of the patients,the Numerical Rating Scale(NRS)scores at rest and during cough at 24,48,and 72 hours after surgery were recorded;and the usage of opioids within 48 hours after surgery was recorded;the duration of chest tube indwelling,incidence of severe pulmonary complications,postoperative hospital stay and adverse reactions to the stimulation(such as nausea and vomiting,fever,constipation,dizziness and itching)were observed.Results Compared with group S,group T exhibited significantly higher QoR-15 scores at 24,48,and 72 h postoperatively,lower NRS pain scores during resting and coughing,and reduced opioid consumption within 48 hours postoperatively(P<0.05).There were no significant differences between the two groups in the duration of chest tube indwelling,incidence of severe pulmonary complications,hospital stay,and the incidence of adverse reactions to the stimula-tion(P>0.05).Conclusion TaVNS can significantly improve quality of early postoperative recovery in patients undergoing thoracoscopic lung resection,and provide more effective postoperative analgesia without increasing the risk of postoperative complications.

Objective:To explore the efficacy of letrozole combined with palbociclib in the treatment of hormone receptor +/human epidermal growth factor receptor-2 - (HR +/HER2 -) advanced breast cancer and its influence on serum thymidine kinase 1 (TK1) and proliferating cell nuclear antigen (Ki67) levels. Methods:A total of 82 patients with HR +/HER2 - advanced breast cancer, all admitted from Jan. 2022 to Jan. 2024 from Department of Oncology, Affiliated Hospital of Jining Medical University, were assigned to the control group ( n=41, letrozole) and the study group ( n=41, letrozole + palbociclib) according to the random number table. The therapeutic effect, tumor markers, immune function and serum TK1 and Ki67 levels were compared between the two groups. Results:The study group higher objective response rate and disease control rate than the other group [14.63% (6/41) and 85.37% (35/41) vs. 0.00% (0/41) and 58.54% (24/41) ] (Continuity correction χ2/χ2=4.50, 7.31, P<0.05). After treatment, carbohydrate antigen 153 (CA153), CA125 and carcinoembryonic antigen (CEA) in the study group were lower than the control group [ (12.17±3.19) U/mL, (23.57±3.35) U/mL and (19.51±4.13) ng/mL vs (24.37±5.25) U/mL, (35.16±5.08) U/mL, (34.28±5.72) ng/mL] ( t=12.72, 12.20, 13.41, P<0.05), serum TK1 and Ki67 levels were also lower [ (3.61±0.75) pmol/L and (7.89±1.16) ng/mL vs. (4.76±0.88) pmol/L and (10.85±1.94) ng/mL] ( t=6.37, 8.39, P<0.05). After treatment, CD3 +, CD4 +, CD4 +/CD8 + higher than the control group [ (48.64±5.88) %, (31.34±4.06) %, (1.22±0.27) vs. (43.16±6.09) %, (27.04±3.35) %, (0.87±0.35) ] ( t=4.15, 5.23, 5.07, P<0.05), while CD8 + was lower [ (25.73±4.11) % vs. (30.94±4.47) %] ( t = 5.49, P<0.05) . Conclusions:Letrozole combined with palbociclib is effective in the treatment of HR +/HER2 - advanced breast cancer and can reduce tumor markers and serum TK1 and Ki67 levels in patients.

Objective:To explore the effectiveness of diaphragm exercises in mechanical ventilation patients with severe pneumonia.Methods:Convenience sampling was used to select 166 mechanical ventilation patients with severe pneumonia admitted to the First Affiliated Hospital of Zhengzhou University from May 2021 to August 2023 for the study. Seventy-nine patients admitted from May 2021 to June 2022 were set up as control group and 87 patients admitted from July 2022 to August 2023 were set up as experimental group. Patients in control group received routine nursing, and experimental group carried out diaphragm exercise on the basis of control group. Post-intervention recovery, and the incidence of complications were compared between the two groups.Results:In experimental group, the patients' mechanical ventilation time was shorter than that in control group, the withdrawal success rate was higher than that in control group, and the ventilator-associated pneumonia (VAP) and total complication incidences were lower than those in control group, and the differences were all statistically significant ( P<0.05) . Conclusions:Diaphragm exercise reduces the risk of VAP and promotes recovery in mechanical ventilation patients with severe pneumonia.

Objective:To develop and validate a combined model integrating radiomics, dosiomics, and clinical parameters based on CT simulation and dosimetric images in order to predict the occurrence of radiation pneumonitis (RP) in patients with non-small cell lung cancer (NSCLC).Methods:A retrospective study was conducted on the clinic data of 143 NSCLC patients who received radiotherapy at the Affiliated Hospital of Jining Medical University from January 2016 to December 2022. Patients were randomly stratified into a training group ( n = 100) and an internal validation group ( n = 43) at a 7∶3 ratio. Moreover, clinic data were collected from 34 NSCLC patients who received radiotherapy at the Jining Cancer Hospital between January 2019 and December 2022 as an external validation group. All three groups (the training group, internal validation, and external validation groups) were further categorized into two groups based on the RP severity (i.e., RP ≥ grade 2 and RP < grade 2). Their radiotherapy dose, CT simulation, and 3D dose distribution images were collected. Then, the total lung minus planning target volume (TL-PTV) was defined as the region of interest (ROI) for radiomics and dosiomic feature extraction, followed by feature dimensionality reduction. Consequently, key features associated with RP were determined. Four predictive models were developed using machine learning approaches (especially multilayer perceptron, MLP): a clinical model (CM), a radiomics model (RM), a dosiomics model (DM), and a radiomics and dosiomics nomogram (RDN), with a nomogram subsequently constructed. Ultimately, the performance and clinical feasibility of these models were assessed using receiver operating characteristic (ROC), area under the curve (AUC), and decision curve analysis (DCA). Results:A total of 1 834 radiomic features and 1 834 dosiomic features were extracted. Using the occurrence of RP ≥ grade 2 as the marker variable, 14 radiomic features, 15 dosiomic features, and three clinical features were selected from the training group to construct the prediction models (CM, RM, DM, and RDN). The performance and generalizability of these models were subsequently validated in both the internal validation and external validation groups. Specifically, the RDN exhibited AUCs of 0.915 (95% CI: 0.852-0.978), 0.879 (95% CI: 0.777-0.982), and 0.838 (95% CI: 0.701-0.975) in the three groups, respectively. A nomogram was established for RDN by integrating the radiomics score (R-score), dosiomics score (D-score), mean lung dose (MLD), V20, and V30. This nomogram allowed for individualized risk estimation of RP and facilitated personalized radiotherapy planning. Conclusions:The RDN model that is developed based on CT simulation and 3D dose distribution images and integrates radiomics, dosiomics, and clinical features can effectively predict the RP risk of NSCLC patients. The integration of multidimensional data contributes to the formation of the optimal predictive model, offering guidance for clinicians.

Objective:To assess the safety and efficacy of thiotepa, busulfan, and etoposide (TBE) conditioning followed by autologous hematopoietic stem-cell transplantation (TBE auto-HSCT) in primary central nervous system lymphoma (PCNSL) patients.Methods:Clinical data from 27 PCNSL patients who received TBE auto-HSCT at the Fifth Medical Center of PLA General Hospital between November 1, 2021, and April 30, 2024, were retrospectively analyzed.Results:Twenty-seven patients [16 males, 11 females; median age 57 (23–72) years] were included, with 12 (44.4%, 12/27) over 60. Twenty-five had newly diagnosed PCNSL and 2 were relapsed. Median time from diagnosis to transplantation was 6.9 (5.0–10.0) months. TBE auto-HSCT increased complete remission (CR) rate from 63.0 to 96.3% ( P= 0.005), and 9 of 10 patients in partial remission achieving CR post-transplant. Median follow-up was 24.5 months (range 2.0–36.0). Two-year progress-free and OS rates were (87.2±6.9) % and (88.6±6.2) %, respectively. Common grade 3 nonhematologic adverse events were diarrhea (18.5%, 5/27) and bacterial infections (14.8%, 4/27). One patient (64 years old) died from carbapenem-resistant Enterobacteriaceae infection within 2 months post-transplant, yielding a 100-day treatment-related mortality of 3.7% (1/27) . Conclusion:TBE-conditioned high-dose chemotherapy with auto-HSCT is effective, safe, and well-tolerated in PCNSL patients, including the elderly.

Objective:To assess the safety and efficacy of thiotepa, busulfan, and etoposide (TBE) conditioning followed by autologous hematopoietic stem-cell transplantation (TBE auto-HSCT) in primary central nervous system lymphoma (PCNSL) patients.Methods:Clinical data from 27 PCNSL patients who received TBE auto-HSCT at the Fifth Medical Center of PLA General Hospital between November 1, 2021, and April 30, 2024, were retrospectively analyzed.Results:Twenty-seven patients [16 males, 11 females; median age 57 (23–72) years] were included, with 12 (44.4%, 12/27) over 60. Twenty-five had newly diagnosed PCNSL and 2 were relapsed. Median time from diagnosis to transplantation was 6.9 (5.0–10.0) months. TBE auto-HSCT increased complete remission (CR) rate from 63.0 to 96.3% ( P= 0.005), and 9 of 10 patients in partial remission achieving CR post-transplant. Median follow-up was 24.5 months (range 2.0–36.0). Two-year progress-free and OS rates were (87.2±6.9) % and (88.6±6.2) %, respectively. Common grade 3 nonhematologic adverse events were diarrhea (18.5%, 5/27) and bacterial infections (14.8%, 4/27). One patient (64 years old) died from carbapenem-resistant Enterobacteriaceae infection within 2 months post-transplant, yielding a 100-day treatment-related mortality of 3.7% (1/27) . Conclusion:TBE-conditioned high-dose chemotherapy with auto-HSCT is effective, safe, and well-tolerated in PCNSL patients, including the elderly.

Objective:To construct a machine learning model based on localization CT-based radiomics, dosiomics and clinical features for predicting radiotherapy response in non-small cell lung cancer (NSCLC) and validate its application value.Methods:A retrospective case series study was conducted. A total of 138 NSCLC patients who received radiotherapy at the Affiliated Hospital of Jining Medical University from January 2016 to December 2022 were selected. The efficacy was evaluated according to the Response Evaluation Criteria in Solid Tumors (RECIST) 1.1, and the patients were stratified according to the objective remission (complete remission+partial remission). Random stratified sampling was used to divide the 138 patients into a training group (96 cases) and an internal validation group (42 cases) at a ratio of 7∶3. Additionally, 33 patients who received radiotherapy at Jining Cancer Hospital from January 2019 to December 2022 were included as the external validation group. Based on the pre-radiotherapy data of the radiotherapy planning system, PyRadiomics software package was used to extract 107 radiomics features and 107 dosiomics features for each patient. Pearson correlation analysis and LASSO regression analysis were used for dimensionality reduction screening; the final selected features were weighted and integrated to generate radiomics-dosiomics scores (RDS), which were then input into logistic regression (LR), support vector machine (SVM), extremely randomized forest (Extra Trees), K-nearest neighbor algorithm (KNN), lightweight gradient boosting machine (Light GBM), and multi-layer perceptron (MLP) machine learning algorithms to construct 6 radiomics-dosiomics models (RDM) for predicting the objective remission. RECIST 1.1 standard was used to evaluate objective remission as the gold standard, receiver operating characteristic (ROC) curve of 6 RDM for predicting objective remission was plotted, and the optimal algorithm for RDM was selected. Univariate and multivariate logistic regression were performed on demographic characteristics, hematological indicators and radiotherapy parameters of the training group to screen independent risk factors for NSCLC patients who received radiotherapy but did not achieve objective remission. These factors were input into the optimal machine learning algorithm to construct a clinical model (CM). Combined with features from RDS and CM, the clinical feature-radiomics-dosiomics combined model (CRDM) was established, and the nomogram of the model for predicting objective remission in NSCLC patients with radiotherapy was drawn. ROC curves were used to evaluate the efficacy of CM, RDM and CRDM in predicting the objective remission in NSCLC patients with radiotherapy in the training group, internal validation group and external validation group.Results:Four radiomics features (including grayscale variance, low grayscale long-range operation emphasis, low grayscale area emphasis, and small area low grayscale area emphasis, all of which were texture features) and 6 dosiomics features [including 1 first-order feature (robust mean absolute deviation), 4 texture features (grayscale non-uniformity, large area emphasis, large area high grayscale emphasis, contrast) and 1 shape feature (shortest axis length)] were selected. ROC curve analysis showed that the area under the curve (AUC) of the RDM constructed using SVM algorithm for judging the objective remission in the training group and the internal validation group was 0.907 (95% CI: 0.836-0.977) and 0.822 (95% CI: 0.685-0.959), which were higher than RDM constructed using other algorithms, and the sensitivity (96.2% and 91.7%), specificity (78.6% and 76.7%) and accuracy (83.3% and 81.0%) at the optimal cut-off values were all higher. Considering the stability and generalization ability of the model, SVM algorithm was ultimately used to construct RDM, CM and CRDM uniformly. Based on training group data, univariate and multivariate logistic regression analysis showed that elevated platelet-to-lymphocyte ratio (PLR) ( OR = 1.001, 95% CI: 1.000-1.003, P = 0.035) and increased target volume of radiotherapy plan ( OR = 1.001, 95% CI: 1.000-1.001, P = 0.008) were independent risk factors for failure to achieve objective remission. ROC curve analysis showed that in the training group and the internal validation group, the AUC of CRDM predicting objective remission were 0.914 (95% CI: 0.856-0.972) and 0.864 (95% CI: 0.754-0.974), respectively, which were better than CM [AUC were 0.735 (95% CI: 0.612-0.857) and 0.697 (95% CI: 0.507-0.888)] and RDM, respectively. In the external validation group, the AUC of CRDM, CM and RDM were 0.778 (95% CI: 0.500-1.000), 0.667 (95% CI: 0.434-0.899) and 0.741 (95% CI: 0.463-1.000), respectively. Conclusions:The CRDM constructed by combining radiomics, dosiomics and clinical features can comprehensively and accurately evaluate the radiotherapy response of NSCLC patients, and may have important clinical application value in achieving precision medicine and optimizing treatment strategies.