Objective To evaluate the accuracy of multiparametric imaging on the dual-source CT through acceptance and commissioning testing, and to provide a reference for standardized clinical application. Methods Both the adult and pediatric dual-source CT scanning modes were used to scan the electron density phantom, and identical multiparametric image reconstruction tasks were performed, including the conventional CT images, the mixed CT images, the virtual monoenergetic images, the iodine images, the electron density images, and the effective atomic number images. Results In the adult scanning mode, the virtual monoenergetic CT numbers showed the greatest difference for the cortical bone (1722 HU at 40 keV vs. 30 HU at 80 keV), with smaller differences observed for other materials as their atomic numbers decreased. The pediatric scanning mode exhibited a similar trend, with the largest difference occurring at 40 keV (1393 HU). In the adult scanning mode, the deviations between the theoretical and measured iodine concentration values were all within 5%, whereas in the pediatric scanning mode, the largest deviation was 15% for an iodine concentration of 2.0 mg/mL. For the electron density, the largest deviation between the theoretical and measured values occurred in the LN450 lung (9.18% in the adult scanning mode and 8.96% in the pediatric scanning mode); the deviations for the LN300 lung were all below 7.2%, for aluminum below 6.3%, and for other tissues within 3%. For the effective atomic number, the deviations between the theoretical and measured values were all within 5% in both scanning modes. Conclusion To ensure the accuracy and reproducibility of the dual-source CT applications, a comprehensive acceptance testing protocol should be established to guarantee the safety and precision of the CT localization process.

Two novel diketopiperazines (1 and 5), along with ten known compounds (2-4, 6-12) demonstrating significant skin inflammation inhibition, were isolated from a marine-derived fungus identified as Aspergillus sp. FAZW0001. The structural elucidation and configurational reassessments of compounds 1-5 were established through comprehensive spectral analyses, with their absolute configurations determined via single crystal X-ray diffraction using Cu Kα radiation, Marfey's method, and comparison between experimental and calculated electronic circular dichroism (ECD) spectra. Compounds 1, 2, and 8 exhibited significant anti-inflammatory activities in Propionibacterium acnes (P. acnes)-induced human monocyte cell lines. Compound 8 demonstrated the ability to down-regulate interleukin-1β (IL-1β) expression by inhibiting Toll-like receptor 2 (TLR2) expression and modulating the activation of myeloid differentiation factor 88 (MyD88), mitogen-activated protein kinase (MAPK), and nuclear factor κB (NF-κB) signaling pathways, thus reducing the cellular inflammatory response induced by P. acnes. Additionally, compound 8 showed the capacity to suppress mitochondrial reactive oxygen species (ROS) production and nucleotide-binding oligomerization domain-like receptor protein 3 (NLRP3) inflammasome activation, thereby reducing IL-1β maturation and secretion. A three-dimensional quantitative structure-activity relationships (3D-QSAR) model was applied to compounds 5-12 to analyze their anti-inflammatory structure-activity relationships.
Humans ; Aspergillus/chemistry* ; Diketopiperazines/isolation & purification* ; Anti-Inflammatory Agents/isolation & purification* ; Interleukin-1beta/genetics* ; Toll-Like Receptor 2/immunology* ; Propionibacterium acnes/drug effects* ; NF-kappa B/genetics* ; Molecular Structure ; Myeloid Differentiation Factor 88/immunology* ; Monocytes/immunology* ; NLR Family, Pyrin Domain-Containing 3 Protein/genetics* ; Cell Line

Objective To investigate the clinical characteristics and dosimetric parameters associated with acute hematologic toxicity (AHT) resulting from radiation-induced damage to hematopoietic organs in patients undergoing chemoradiotherapy for cervical cancer and to provide a reference for establishing dose constraints in relevant regions of interest (ROIs) and predicting adverse tissue reactions during the development of clinical treatment plans. Methods A retrospective analysis was conducted on 556 patients with cervical cancer who underwent chemoradiotherapy at our hospital. Univariate (χ² and t-test) and multivariate (binary logistic regression analyses) methods were employed to investigate the association of clinical factors and pelvic dose-volume parameters with grade ≥ 3 AHT in patients with cervical cancer. Clinical factors comprised patients’ age, clinical stage, pathologic stage, whether the patient had received chemotherapy in the radiotherapy cycle of interest, and dose-volume dosimetric parameters V_x and D_mean for pelvic bone marrow (BM) and femoral head (FH) structures. Results The incidence of AHT among the included cases was 30.4% (169/556). Chi-square analysis of the clinical factors revealed that whether the patient had received chemotherapy, patient’s age, and pathologic stage had a significant impact on AHT. Univariate analysis showed that the factors associated with AHT were mean dose, V₅, V₁₀, V₁₅, V₂₀, and V₂₅ of BM and FH; dosimetric parameters such as V₃₅ of FH had a significant impact on the development of AHT. Multivariate logistic regression analysis identified V₁₅ of pelvic BM as an independent risk factor for AHT (P=0.041), with a threshold value of 84.29% as determined by a receiver operating characteristic (ROC) curve. Conclusion Whether a patient had received chemotherapy in the radiotherapy cycle of interest, and patient’s age and pathologic stage can serve as predictors of AHT. V₁₅ of BM is an independent risk factor for AHT development. Therefore, when formulating a treatment plan, it is crucial to ensure that pelvic V₁₅ remains below 84.29% to effectively reduce the incidence of grade ≥ 3 acute bone marrow depression.

Objective:To explore the clinical and genetic characteristics of four children with Kabuki syndrome (KS) due to variants of KMT2D gene. Methods:Four children with KS diagnosed at the Children′s Hospital of Shanxi Province between January 2020 and December 2022 were selected as the study subjects. Whole exome sequencing was carried out for the children and their family members. Candidate variants were verified by Sanger sequencing and pathogenicity analysis.Results:The KS phenotype scores for the four children were 7, 8, 6, and 6, respectively. Child 2 also presented with a rare solitary kidney malformation. Genetic testing revealed that all children had harbored novel de novo variants of the KMT2D gene, including c. 16472_16473del, c. 858dup, c. 11899C>T, and c. 12844C>T, respectively. Based on the guidelines from the American College of Medical Genetics and Genomics (ACMG), all of the variants were classified as pathogenic. Conclusion:For children showing phenotypes such as distinctive facial features, intellectual disability, developmental delay, cardiac abnormalities, and urinary system anomalies, KS should be considered. Early diagnosis and intervention can be achieved through genetic testing, especially in the presence of KMT2D gene mutations.

Objective To investigate the identification of octreotide(OCT)modified chitosan(CS)miR-155 molecular beacon nanoparticles(CS-miR-155-MB-OCT)and imaging of lung cancer cells for the early screening of lung cancer.Methods A nude mouse model of lung transplantation tumor was established by injecting A549 lung cancer cells into tail veins to establish lung xenograft models.Cre adenovirus was injected through nasal cavity,and mice were killed at 4,6,8 and 12 weeks after adenovirus injection to establish lung cancer models of atypical hyperplasia,adenoma,carcinoma in situ and adenocarcinoma of lung in LSL K-ras G12D transgenic mice at different pathological stages.Lung tissue samples were taken and observed by HE staining.Immunohistochemistry were used to detect the expression of somatostatin receptor 2(SSTR2).Real-time fluorescence quantitative PCR was used to detect miR-155 expression levels in lung xenograft models and transgenic mice at different stages of lung cancer.Then CS-miR-155-MB and CS-miR-155-MB-OCT were injected via tail vein in lung xenograft models.CS-miR-155-MB-OCT was injected via tail vein in transgenic mice models.The fluorescence signals of lung in nude mice and transgenic mice at different disease stages were imaged by living imaging system.Frozen slices of lung tissue were made.The source of fluorescence signal was detected by laser confocal scanning microscope(CLSM).Results HE staining showed that lung transplantation tumor models and lung cancer models of atypical hyperplasia,adenoma,carcinoma in situ and lung adenocarcinoma at different pathological stages were successfully constructed.Immunohistochemical analysis showed somatostatin receptor 2(SSTR2)was expressed in transplanted lung tumor and tissue at different pathological stages.In transgenic mouse models,the expression of miR-155 was gradually increased as the disease progressed(P＜0.05).In lung xenograft models,the fluorescence signals were significantly higher in the CS-miR-155-MB-OCT group than those of the CS-miR-155-MB group(P＜0.05).In transgenic mouse models,the fluorescence signals gradually increased with the gradual progression of lesions(P＜0.05).After re-imaging the lung tissue,it was found that the fluorescence signal came from lung,and CLSM showed that the fluorescence signal came from cancer cells and some normal alveolar epithelial cells.Conclusion CS-miR-155-MB-OCT can dynamically reflect the occurrence and development of lung cancer according to changes of different fluorescence intensity,thus providing a new technology for the early diagnosis of lung cancer.

Purpose/Significance To construct a specialized database for inflammatory demyelinating disease of the central nervous system(CNS),so as to contribute to clinical research and improve the diagnostic and treatment capabilities of primary healthcare institu-tions.Method/Process Using the internet to collect medical data,after processing and analysis,the CNS inflammatory demyelinating disease database is constructed.Using statistical analysis,natural language processing(NLP),artificial intelligence(AI)image recog-nition and data visualization and other technologies,the database information is integrated and analyzed.Result/Conclusion A standard-ized big database for CNS inflammatory demyelinating diseases is constructed,which enables visualization of clinical research data,pro-vides patient education and specialist training,and facilitates multi-center teleconsultations.The establishment of a specialized database for the CNS inflammatory demyelinating disease can promote the transformation of medical research achievements,provide references for future real-world clinical research,optimize the process of diagnosis and treatment,and improve the clinical capability of primary healthcare institutions.

Objective This study aims to develop and validate a dynamic web-based nomogram for predicting kinetophobia in patients following percutaneous coronary intervention(PCI).Methods A prospective design was employed to selectively enroll 330 PCI patients admitted to a hospital in Hangzhou from December 2022 to July 2023.Single-factor analysis and Lasso regression were utilized to identify independent risk factors for kinesophobia post-PCI.Logistic regression was performed using R software,and a nomogram was constructed.The model was assessed through the area under the receiver operating characteristic curve(AUC)and Hosmer-Lemeshow tests.Results There were 206 cases of kinesiophobia in 330 patients after PCI,and the incidence was 62.4％.Logistic regression analysis identified combined heart failure,emergency surgery,NYHA cardiac function grade,ADL level,sedentary behavior,Chinese version of PROMIS Physical Function Summary Table score,and Chinese version of Perceptive Social Support Scale score as independent influencing factors for kinesophobia after PCI(P＜0.05).The AUC value of the model was 0.821,with a sensitivity of 70.4％and specificity of 82.0％.The Hosmer-Lemeshow fit test yielded a non-significant result(x2=9.350,P=0.314).Calibration and decision curves demonstrated the model's favorable calibration and clinical practicability.The C-index of the nomogram prediction model was 0.778,0.774,and 0.800,respectively,by 5-fold cross-validation,10-fold cross-validation,and the Bootstrap method.Conclusion The dynamic nomogram model developed in this study effectively predicts kinesophobia in patients after PCI.It provides valuable references and support for clinical staff in early identification of high-risk patients,enabling the formulation of individualized health education strategies and exercise rehabilitation plans.

This paper summarizes the definition, evaluation tools, influencing factors, and cultivation strategies of moral sensitivity in nursing students, so as to provide reference for moral education of nursing students in China.

Objective:To explore the status quo of self-stigma in diabetic patients and analyze its correlation with self-compassion.Methods:In this cross-sectional study, from December 2020 to January 2021, totally 240 diabetic patients admitted at the Department of Endocrinology in two ClassⅢ Grade A hospitals in Hangzhou, Zhejiang Province were selected by convenient sampling and investigated with the general information questionnaire, Self-Stigma Scale (SSS) , and Self-Compassion Scale (SCS) . Hierarchical regression analysis was used to explore the relationship between self-stigma and self-compassion in diabetic patients. A total of 240 questionnaires were issued, and 225 valid questionnaires were recovered. The effective response rate was 93.75% (225/240) .Results:The total SSS score of the 225 diabetic patients was (56.47±16.72) , and the average score of all items was (2.01±0.60) ; the total SCS score was (86.46±12.79) , and the average score of all items was (3.33±0.49) . Pearson correlation analysis showed that the total SSS score of diabetic patients was negatively correlated with the total SCS score ( P < 0.01) . Hierarchical regression analysis revealed that self-compassion was an influencing factor of self-stigma in diabetic patients ( P< 0.01) , which could independently explain 13.1% of self-stigma (Δ R2=0.131, P<0.001) . Conclusions:Self-stigma of diabetic patients is at a moderate level, and self-compassion is an influencing factor of self-stigma of diabetic patients. Nursing staff can reduce patients ' self-stigma by improving their self-compassion.

Objective:To develope an automatic volumetric modulated arc therapy (VMAT) planning for rectal cancer based on a dose-prediction model for organs at risk(OARs) and an iterative optimization algorithm for objective parameter optimization.Methods:Totally 165 VMAT plans of rectal cancer patients treated in Peking University Cancer Hospital & Institute from June 2018 to January 2021 were selected to establish automatic VMAT planning. Among them, 145 cases were used for training the deep-learning model and 20 for evaluating the feasibility of the model by comparing the automatic planning with manual plans. The deep learning model was used to predict the essential dose-volume histogram (DVH) index as initial objective parameters(IOPs) and the iterative optimization algorithm can automatically modify the objective parameters according to the result of protocol-based automatic iterative optimization(PBAIO). With the predicted IOPs, the automatic planning model based on the iterative optimization algorithm was achieved using a program mable interface.Results:The IOPs of OARs of 20 cases were effectively predicted using the deep learning model, with no significantly statistical difference in the conformity index(CI) for planning target volume(PTV)and planning gross tumor volume(PGTV)between automatic and manual plans( P>0.05). The homogeneity index (HI) of PGTV in automatic and manual plans was 0.06 and 0.05, respectively( t=-6.92, P< 0.05). Compared with manual plans, the automatic plans significantly decreased the V30 for urinary bladder by 2.7% and decreased the V20 for femoral head sand auxiliary structure(avoidance)by 8.37% and 15.95%, respectively ( t=5.65, 11.24, P< 0.05). Meanwhile, the average doses to bladder, femoral heads, and avoidance decreased by 1.91, 4.01, and 3.88 Gy, respectively( t=9.29, 2.80, 10.23, P< 0.05) using the automatic plans. The time of automatic VMAT planning was (71.49±25.48)min in 20 cases. Conclusions:The proposed automatic planning based on dose prediction and an iterative optimization algorithm is feasible and has great potential for sparing OARs and improving the utilization rate of clinical resources.