Objective:To illustrate the clinical modeling and commissioning results of Monte Carlo dose calculation algorithm in RayStation treatment planning system (TPS) for a domestically developed synchrotron-based spot scanning proton therapy system (SAPT-PS-01).Methods:The proton pencil beam model in RayStation required integral depth dose curves, spot profiles and absolute dose as the input beam data. It was not necessary to collect beam parameters with range shifter. The integral depth dose curves of a single spot were measured by an 8 cm parallel ion chamber. A 2-dimensional scintillation detector was used to measure the in-air spot profile at 5 different depths including the isocenter plane. The absolute dose was calibrated by a 0.25 cm parallel ion chamber under the single energy layer irradiation with a field size of 10 cm × 10 cm. After modeling, the results of the beam model and the Monte Carlo dose calculation algorithm were validated from the range, spot profile, point-dose in a spread-out Bragg peak, planar dose in a clinical plan, point dose in an end-to-end test.Results:For the 94 energy layers, the maximum deviation between the calculated and measured range was 0.03 cm. The maximum difference between the calculated and measured in-air spot sigma was 0.015 cm, and the deviation of in-water spot sigma was measured within ±15%. Compared with the measured values, the calculated dose deviation of 138 measured points in the spread-out Bragg peak was within 3%. For the planar dose verification of clinical plans, the TPS-calculated dose distribution of 285 planes agreed well with the measurement with a minimum gamma-passing rate of 90%, and the gamma passing rate of almost 95% of planes were greater than 95%. The point dose measurements for 8 beams in the end-to-end tests under 4 clinical scenarios were within 5%.Conclusions:The acceptable beam model validation results and successful end-to-end test confirm that the Monte Carlo dose calculation algorithm modeling for the synchrotron-based spot scanning proton therapy system is accurate, which is applicable for the design of patient treatment plan.

Objective To explore the feasibility of radiomics nomogram based on magnetic resonance diffusion weighted imaging for predicting the expression of Ki-67 in breast cancer.Methods A retrospective study was conducted on patients with breast cancer confirmed by surgery and pathology in the Second Affiliated Hospital of Guangdong Medical University.All patients were detected by Ki-67 expression staining,and then divided into group A(n=28,low-level expression of Ki-67)and group B(n=73,high-level expression of Ki-67).The apparent diffusion coefficient(ADC)graph was generated from diffusion weighted images,and the two groups were compared for radiomics features of ADC images and clinical data.The expression level of Ki-67 in breast cancer was predicted using the features of LASSO after dimensionality reduction,and a nomogram model was established,whose diagnostic efficiency was analyzed with receiver operating characteristic curve.Results No significant difference was observed in ADC value,age,carbohydrate antigen 199,carbohydrate antigen 153,carbohydrate antigen 125 and carcinoembryonic antigen between two groups(P>0.05).LASSO regression identified two radiomics features as predictors for the expression level of Ki-67 in breast cancer.The best tuning Lambda of LASSO was-0.125 690 135 478 682,and the included radiomics features for nomogram establishment were MinIntensity and Quantile95.The established nomogram had an area under ROC curve of 0.917,achieving a sensitivity of 91.7%and a specificity of 83.3%.Conclusion The expression of Ki-67 in breast cancer can be predicted based on the radiomics features of ADC images,which can provide a noninvasive detection method for evaluating the proliferation degree and treatment prognosis of breast cancer.

Objective To explore the feasibility of radiomics nomogram based on magnetic resonance diffusion weighted imaging for predicting the expression of Ki-67 in breast cancer.Methods A retrospective study was conducted on patients with breast cancer confirmed by surgery and pathology in the Second Affiliated Hospital of Guangdong Medical University.All patients were detected by Ki-67 expression staining,and then divided into group A(n=28,low-level expression of Ki-67)and group B(n=73,high-level expression of Ki-67).The apparent diffusion coefficient(ADC)graph was generated from diffusion weighted images,and the two groups were compared for radiomics features of ADC images and clinical data.The expression level of Ki-67 in breast cancer was predicted using the features of LASSO after dimensionality reduction,and a nomogram model was established,whose diagnostic efficiency was analyzed with receiver operating characteristic curve.Results No significant difference was observed in ADC value,age,carbohydrate antigen 199,carbohydrate antigen 153,carbohydrate antigen 125 and carcinoembryonic antigen between two groups(P>0.05).LASSO regression identified two radiomics features as predictors for the expression level of Ki-67 in breast cancer.The best tuning Lambda of LASSO was-0.125 690 135 478 682,and the included radiomics features for nomogram establishment were MinIntensity and Quantile95.The established nomogram had an area under ROC curve of 0.917,achieving a sensitivity of 91.7%and a specificity of 83.3%.Conclusion The expression of Ki-67 in breast cancer can be predicted based on the radiomics features of ADC images,which can provide a noninvasive detection method for evaluating the proliferation degree and treatment prognosis of breast cancer.

Objective To investigate the association between single nucleotide polymorphisms(SNP)rs57095329 and rs6864584 of miR-146a gene and cervical intraepithelial neoplasia(CIN).Methods A total of 96 patients diagnosed with CIN were randomly collected as the CIN group,and 225 healthy individuals examined during the same period were selected as the control group using SPSS software.Genotyping of the above SNP loci was performed using the TaqMan probe method,and their correlation with CIN was analyzed.Results The allele and genotype distribution of rs57095329 showed a statistically significant differences compared to the control group,with the frequency of the allele A in the CIN group significantly lower than that in the control group(P<0.001;OR=0.48,95%CI:0.32～0.70).In the dominant model,individuals carrying the G allele(A/G-G/G)had a significantly increased risk of CIN(P<0.001;OR=2.67,95%CI:1.64～4.37).In contrast,no correlation was found between the rs6864584 and the risk of CIN.Conclusion The A allele of the miR-146a gene at the rs57095329 locus may be a protective factor for CIN.

Targeting T-cell is a strategy to control allogeneic response disorders, such as acute graft-versus-host disease (GVHD) which is an important cause of therapy-failure after allogeneic hematopoietic cell transplants. Free fatty acid receptor-4 (FFAR4) is a regulator of obesity but its role in T-cell and allogeneic reactions is unknown. Here, we found knockout of Ffar4 in donor T-cells in a mouse allograft model increased acute GVHD whereas the natural FFAR4 ligands and the synthetic FFAR4 agonists decreased it. FFAR4 agonist-mediated anti-acute GVHD effects depended on FFAR4-expression in donor T-cells. The FFAR4 agonist CpdA suppressed donor T-cell-mediated alloreaction by activating an aryl hydrocarbon receptor (AhR) pathway. CpdA recruited β-Arrestin2 to FFAR4 which facilitated nuclear translocation of AhR and upregulation of IL-22. The CpdA-mediated anti-acute GVHD effect was absent in mice receiving Ahr-knockout or Il22-knockout T-cells. Recipient-expressing Ffar4 was also important for the anti-acute GVHD effect of CpdA which inhibited activation of antigen presenting cells. Importantly, CpdA decreased acute GVHD in obese mice, an effect also depended on Ffar4-expression in donor T-cells and recipients. Our study shows the immunoregulatory effect of FFAR4 in T-cell, and targeting FFAR4 might be a relative option for controlling allogeneic reactions in obese patients.

Objective:To illustrate the clinical modeling and commissioning results of Monte Carlo dose calculation algorithm in RayStation treatment planning system (TPS) for a domestically developed synchrotron-based spot scanning proton therapy system (SAPT-PS-01).Methods:The proton pencil beam model in RayStation required integral depth dose curves, spot profiles and absolute dose as the input beam data. It was not necessary to collect beam parameters with range shifter. The integral depth dose curves of a single spot were measured by an 8 cm parallel ion chamber. A 2-dimensional scintillation detector was used to measure the in-air spot profile at 5 different depths including the isocenter plane. The absolute dose was calibrated by a 0.25 cm parallel ion chamber under the single energy layer irradiation with a field size of 10 cm × 10 cm. After modeling, the results of the beam model and the Monte Carlo dose calculation algorithm were validated from the range, spot profile, point-dose in a spread-out Bragg peak, planar dose in a clinical plan, point dose in an end-to-end test.Results:For the 94 energy layers, the maximum deviation between the calculated and measured range was 0.03 cm. The maximum difference between the calculated and measured in-air spot sigma was 0.015 cm, and the deviation of in-water spot sigma was measured within ±15%. Compared with the measured values, the calculated dose deviation of 138 measured points in the spread-out Bragg peak was within 3%. For the planar dose verification of clinical plans, the TPS-calculated dose distribution of 285 planes agreed well with the measurement with a minimum gamma-passing rate of 90%, and the gamma passing rate of almost 95% of planes were greater than 95%. The point dose measurements for 8 beams in the end-to-end tests under 4 clinical scenarios were within 5%.Conclusions:The acceptable beam model validation results and successful end-to-end test confirm that the Monte Carlo dose calculation algorithm modeling for the synchrotron-based spot scanning proton therapy system is accurate, which is applicable for the design of patient treatment plan.

OBJECTIVE To provide reference for improving the pre-prescription review system and reducing the occurrence of medication error by analyzing the drug-related problems(DRPs)in the pre-prescription review orders of pediatric outpatient clinics using the Pharmaceutical Care Network Europe(PCNE)classification system.METHODS The data of pre-prescription review orders were retrospectively collected from outpatient department of Shanghai Children's Medical Center,Shanghai Jiao Tong University School of Medicine from July 2022 to June 2023;DRPs in the pre-prescription review orders were classified and summarized by using the PCNE classification system(version 9.1),and then analyzed in terms of types and causes of issues,and the acceptance of interventions.RESULTS A total of 66 017 DRPs orders were included,involving 41 165 patients.The proportion of DRPs orders in children aged ≤5 years old was the highest(58.25％),followed by children aged 6-12 years old(33.52％);the department with the highest proportion of DRPs was internal medicine of pediatrics department(71.41％);the department with the highest incidence of DRPs was thoracic surgery department(9.73％);top three drug categories of DRPs orders were systemic anti-infective drugs(25.26％),Chinese patent medicines(24.74％)and respiratory drugs(22.38％).Referring to PCNE classification system,the types of DRPs mainly focused on treatment safety(64.86％);the reasons of DRPs orders mainly focused on dose selection(82.09％),of which 41.26％were due to excessive drug dosage;92.13％of interventions could be accepted and fully executed by doctors.CONCLUSIONS DRPs orders identified by the pre-prescription review system can be effectively analyzed by using PCNE classification system.Pharmacists should focus on medication use in children aged＜5 years old,update and develop personalized prescription review rules timely,and meet the rational needs of clinical medication for children.

To analyze the disease group structure and its trends in key departments of large public hospitals using diagnosis related group (DRG) data, explore the key points of intervention and optimization of disease groups in departments, and further promote the rational allocation of department resources.

Objective:To evaluate the effect of autologous hematopoietic stem cell transplantation (ASCT) on the treatment of relapsed/refractory multiple myeloma (RRMM) with chimeric antigen receptor T cell (CAR-T) therapy.Methods:A retrospective cohort study. The clinical data of 168 patients with RRMM who underwent CAR-T therapy at the Department of Hematology, Xuzhou Medical University Hospital from 3 January 2020 to 13 September 2022 were analyzed. Patients were classified into a transplantation group (TG; n=47) and non-transplantation group (NTG; n=121) based on whether or not they had undergone ASCT previously. The objective response rate (ORR), progression-free survival (PFS), overall survival (OS) and the levels of CD3, CD4, CD8, CD19, CD56 and natural killer (NK) cells before CAR-T infusion were analyzed by χ2 test, Kaplan-Meier method and independent sample t-test. Results:Among 168 patients with RRMM, 98 (58.3%) were male. The median age of onset was 57 (range 30-70) years. After CAR-T therapy, the ORR of patients was 89.3% (92/103) in the NTG and 72.9% (27/73) in the TG. The ORR of the NTG was better than that of the TG ( χ2=5.71, P=0.017). After 1 year of CAR-T therapy, the ORR of the NTG was 78.1% (75/96), and that of the TG was 59.4% (19/32). The ORR of the NTG was better than that of the TG ( χ2=4.32, P=0.038). The median OS and PFS in the NTG were significantly longer than those in the TG (OS, 30 vs. 20 months; PFS, 26 vs. 12 months; both P<0.05). The CD4 level before CAR-T infusion in the TG was significantly lower than that in the NTG (25.65±13.56 vs. 32.64±17.21; t=-2.15, P=0.034), and there were no significant differences in the counts of CD3, CD8, CD19, CD56, and NK cells between the TG and NTG (all P>0.05). Conclusion:Among patients suffering from RRMM who received CAR-T therapy, patients who did not receive ASCT had significantly better outcomes than those who had received ASCT previously, which may have been related to the CD4 level before receiving CAR-T therapy.

Objective:To explore the correlation between frailty and carotid plaque stability in patients with ischemic stroke.Methods:This study was a cross-sectional study. From May to December 2023, convenience sampling was used to select 360 patients with ischemic stroke in the Department of Neurology of Affiliated Hospital of Jining Medical University and underwent carotid artery color Doppler ultrasound examination as the study subject. Patients were surveyed using the General Information Questionnaire, Barthel Index and the Edmonton Frail Scale. Carotid artery color Doppler ultrasound was used to evaluate the stability of carotid plaques in patients. Multivariate Logistic regression was used to explore the correlation between frailty and carotid plaque stability.Results:A total of 360 questionnaires were distributed, and 352 valid questionnaires were collected, with a valid response rate of 97.78%. The incidence of frailty in 352 ischemic stroke patients was 44.89% (158/352). Multivariate analysis showed that compared to stable plaques, unstable carotid plaques were an independent risk factor for frailty in patients with ischemic stroke ( OR=2.127, 95% confidence interval: 1.247-3.626) . Conclusions:Compared to stable plaques, unstable carotid plaques increase the risk of frailty in patients with ischemic stroke. Strengthening the assessment of carotid plaques in patients with ischemic stroke by nursing staff can early identify high-risk individuals for frailty, and timely carry out personalized interventions, thereby reducing the occurrence of adverse health events in patients.