Objective To analyze and identify the volatile constituents in different parts(flowers,stems and leaves)of Huai chrysanthemumin,and to lay a theoretical foundation for the comprehensive utilization for it.Methods The volatile oil in different parts of Huai chrysanthemumin were extracted by hydrodistillation,respectively.Their constituents were analyzed by gas chromatography-mass spectrometry(GC-MS).The compounds were identified by library search and literature screening.The relative percentage of each compound was obtained by the area normalization method.The differences in their chemical compositions were analyzed by Venn diagram,principal component analysis(PCA)and cluster heat map analysis.Results A total of 62 volatile chemical components were identified from different parts of Huai chrysanthemumin,including monoterpenes,sesquiterpenes,and their derivatives,as well as a small amount of aliphatic compounds.32,42 and 40 volatile components were detected from the flowers,stems and flowers,respectively.Furthermore 17 volatile components were shared by three parts,whereas 5,6 and 16 volatile components were unique to the flowers,stems and leaves,respectively.The results of stoichiometric analysis showed that both PCA and cluster heat map analysis could separate the flowers,stems and leaves,and their volatile components were different.Conclusion The types and contents of the volatile oil in the stems,leaves and flowers of Huai chrysanthemumin have certain variability,which provide a scientific basis for the further medicinal or industrial exploitation of different parts of Huai chrysanthemumin.

Objective:To analyze the effects of different dose calculation grid size of Monaco system on the physical and biological dosimetry of target area and organ at risk (OAR) in T 4 nasopharyngeal carcinoma. Methods:A total of 18 patients with stage T 4 nasopharyngeal carcinoma who received radiotherapy in the Department of Radiotherapy of Yunnan Cancer Hospital from October 2020 to April 2022 were selected to complete the delineation of target areas and OAR in the Monaco 5.11.03 system, and the volumetric intensity modulated arc therapy (VMAT) plan was developed on the 3 mm grid with the optimization mode of target area priority. The 3 mm grid group plan was replicated without changing any other parameters, and the physical plan was re-established on the 1, 2, 4 and 5 mm grids, and then the five plans were normalized to the prescription dose to cover 95% of the target volume. The planning time, D 2%, D 50%, D 98%, conformity index (CI), homogeneity index (HI), gradient index (GI), tumor control probability (TCP), D 2% and D mean of important OAR around the target area were calculated and statistically analyzed. Results:Planning primary tumor gross target volume (PGTVp) : The D 2% of 1, 2, 3, 4 and 5 mm groups were (76.94±0.66), (75.98±0.76), (75.56±0.67), (75.67±0.73) and (75.94±0.85) Gy, respectively, with a statistically significant difference ( F=9.86, P<0.001). The CI of 1, 2, 3, 4 and 5 mm groups were 0.75±0.05, 0.78±0.04, 0.78±0.05, 0.79±0.04 and 0.78±0.04, respectively, with a statistically significant difference ( F=2.61, P=0.041). There were statistically significant differences in D 50%, D 98%, HI, equivalent uniform dose (EUD) and tumor control probability (TCP) among the groups ( H=17.14, P=0.002; F=9.35, P<0.001; H=25.43, P<0.001; F=5.85, P<0.001; H=17.65, P=0.001). There was no statistically significant difference in GI among the groups ( P>0.05). Pairwise comparison showed that D 2% in 2, 3, 4, 5 mm groups compared with 1 mm group, D 50% in 5 mm group compared with 2, 3 mm groups, D 98% in 4 mm group compared with 1, 2 mm groups, D 98% in 5 mm group compared with 1, 2, 3 mm groups, CI in 5 mm group compared with 1 mm group, HI in 2, 3, 4, 5 mm groups compared with 1 mm group, EUD in 3 mm group was compared with 1 mm group, EUD in 5 mm group compared with 2, 3 mm groups, TCP in 3 mm group compared with 1 mm group, and TCP in 5 mm group compared with 3 mm group, there were statistically significant differences (all P<0.05). Planning nodal gross target volume (PGTVn) : The D 2% of 1, 2, 3, 4 and 5 mm groups were (76.36±0.59), (75.36±0.62), (75.04±0.68), (75.25±0.72) and (75.39±0.77) Gy, respectively, with a statistically significant difference ( F=10.32, P<0.001). The HI of 1, 2, 3, 4 and 5 mm groups were 1.08 (1.08, 1.08), 1.07 (1.06, 1.07), 1.06 (1.06, 1.07), 1.06 (1.06, 1.07), 1.06 (1.06, 1.07), 1.06 (1.06, 1.08), respectively, with a statistically significant difference ( H=22.00, P<0.001) ; There were statistically significant differences in D 50%, D 98% and EUD among the groups ( H=11.79, P=0.019; H=20.49, P<0.001; F=12.14, P=0.016). Pairwise comparison showed that there were statistically significant differences in D 2% between 2, 3, 4, 5 mm groups and 1 mm group, D 98% between 4 mm group and 1 mm group, D 98% between 5 mm group and 1, 2 mm groups, HI between 2, 3, 4 mm groups and 1 mm group, and EUD between 3 mm group and 1 mm group (all P<0.05). Planning primary tumor clinical target volume 1 (PCTVp1) : The D 2% of 1, 2, 3, 4 and 5 mm groups were (76.59±0.63), (75.64±0.65), (75.64±0.98), (75.41±0.70) and (75.71±0.84) Gy, respectively, with a statistically significant difference ( F=9.53, P<0.001). The D 50% of 1, 2, 3, 4, 5 mm groups were (72.09±0.34), (71.85±0.39), (71.82±0.45), (72.04±0.56), (72.43±0.66) Gy, respectively, with a statistically significant difference ( F=4.20, P=0.019). There was no statistically significant difference in the other indexes among the groups (all P>0.05). Pairwise comparison showed that there were statistically significant differences in D 2% between 2, 3, 4, 5 mm groups and 1 mm group, and in D 50% between 2, 3 mm groups and 1 mm group (all P<0.05). Planning nodal clinical target volume 1 (PCTVn1) : There were no statistically significant differences in all indexes among the groups (all P>0.05). Planning clinical target volume 2 (PCTV2) : The D 2% of 1, 2, 3, 4 and 5 mm groups were (75.57±0.50), (74.87±0.67), (74.51±0.51), (74.61±0.63) and (75.00±0.74) Gy, respectively, with a statistically significant difference ( F=8.27, P<0.001). Pairwise comparison showed that the D 2% of the 2, 3, 4 mm groups were significantly different from that of the 1 mm group (all P<0.05). The calculation time of physical plan in 1, 2, 4 and 5 mm groups was 987.00 (848.00, 1 091.00), 120.50 (99.75, 134.00), 26.00 (24.00, 34.25) and 21.50 (18.75, 34.75) s, respectively, with a statistically significant difference ( H=61.62, P<0.001). Pairwise comparison showed that there were statistically significant differences in the calculation time between 4 mm group and 1, 2 mm groups, 5 mm group and 1, 2 mm groups (all P<0.05). There was no statistically significant difference in the dosimetric parameters of OAR around the target area among the groups (all P>0.05) . Conclusion:The physical dose and biological dose of the important OAR around the target area and the target area change with the change of dose calculation grid size when formulating the physical plan of radiotherapy for T 4 nasopharyngeal carcinoma. Considering the quality of the physical plan and the calculation time, when the Monaco system formulates the VMAT plan for T 4 nasopharyngeal carcinoma patients, the plan can be optimized on the 3 mm computing grid and copied to the 1 mm computing grid for recalculation.

Objective:This study analyzed the expression of CD24 antigen on bone marrow plasma cells (BMPC) of patients with multiple myeloma (MM) and the predictive value of induction therapy.Methods:This clinical observational study utilized 258 MM patients samples treated at the Hematology Department of Beijing Jishuitan Hospital who met the inclusion criteria in the Department of Hematology, Capital Medical University, from August 12th, 2022 to February 1st, 2024. According to the different stages of the disease, patients were divided into three groups: 78 cases of Newly Diagnosed Multiple Myeloma(NDMM) (42 males and 36 females, aged 62±11), 56 cases of the relapse refractory group (34 males and 22 females, aged 64±9), and 124 cases of the disease remission group (68 males and 56 females, aged 62±10). Multiparameter flow cytometry (MFC) was used to detect the expression level of CD24 antigen on BMPC and the relationship between CD24 and MM disease status. The clinical data and test results of 78 NDMM patients at initial diagnosis were retrospectively analyzed, including gender, age, MFC detection of the positive expression rate of antigens (CD19, CD20, CD24, CD27, CD56), the results of efficacy evaluation after induction therapy, ISS staging, R-ISS staging, blood hemoglobin, β2-microglobulin, human serum albumin, serum creatinine, lactate dehydrogenas, correction of calcium, BMPC ratio, and the results of FISH. The patients were divided into a deep remission group [including complete remission (CR) and very good partial remission (VGPR)] with 43 cases and a non-deep remission group (non CR and VGPR) with 17 cases according to the difference of antigen positive expression rate after induction therapy. The differences of antigen expression on BMPC between the two groups were compared. Binary logistic regression was used to analyze the relationship between the expression of each antigen and the efficacy after induction therapy in patients, and the results showed that CD24 was more correlated with the achievement of deep remission after induction therapy than other antigens. Therefore, taking the positive expression rate of CD24 in NDMM patients at the initial diagnosis and deep remission after induction therapy as the research objects, the predictive value of CD24 for NDMM patients reaching deep remission after induction therapy was analyzed by using receiver operating characteristic curve (ROC), and the optimal cutoff value was obtained. NDMM was divided into two groups according to the cut-off value, and the differences between the two groups in clinical baseline data and prognostic indicators were compared.Results:The positive rates of plasma cell CD24 expression in the NDMM group, the relapse refractory group and the disease remission group were 2.18 (95% CI 0.08-81.85)%, 3.81 (95% CI 0.10-64.56)%, 8.74 (95% CI 0.79-95.55)% respectively. Compared with the disease remission group, the NDMM and relapse refractory group was lower ( Z=-7.889, -5.282, respectively, P<0.001). Univariate analysis showed that there was a significant difference in the positive expression rate of CD24 at initial diagnosis between the deep remission group and the non-deep remission group ( Z=-3.265, P<0.001), while there was no significant difference in CD19 ( Z=-0.271, P=0.787), CD20 ( Z=-0.205, P=0.837), CD27 ( Z=-0.582, P=0.560), and CD56 ( Z=-0.328, P=0.743) between the two groups. Binary logistic regression analysis showed that compared with other antigens [CD19 ( OR=1.045, 95% CI 0.975-1.120, P=0.217), CD20 ( OR=1.000, 95% CI 0.971-1.030, P=0.976), CD27 ( OR=0.997, 95% CI 0.977-1.016, P=0.734), CD56 ( OR=1.006, 95% CI 0.990-1.006, P=0.449)], the expression of CD24 ( OR=0.423, 95% CI 0.990-1.006, P=0.449) on BMPC in NDMM patients was most closely related to the achievement of deep remission was achieved after induction therapy. The lower the proportion of CD24 at the initial diagnosis was, the lower the probability of achieving deep remission after induction therapy was. The area under the curve (AUC) of CD24 in predicting deep remission after induction therapy was 0.772 (95% CI 0.655-0.889, P=0.001), with a sensitivity of 60.50%, a specificity of 85.00%, and the optimal critical value was 2.21%. Compared with the group with plasma CD24 positive rate>2.21%, the group with plasma CD24 positive rate<2.21% had a higher proportion of male (39.47%vs 65.00%, χ2=5.092, P=0.024), ISS stagingⅢ (41.67% vs 58.33%, χ2=6.175, P=0.046), β2 microglobulin (3.19 mg/L vs 4.14 mg/L, Z=-2.257, P=0.024), and BMPC [(8.672±1.827)% vs (19.530±3.188)%, t=-2.963, P=0.004] detected by MFC, and the differences were statistically significant. Conclusions:The low positive rate of plasma cell CD24 is closely related to the higher tumor burden and the worse disease status of MM patients. In addition, the positive expression rate of CD24 is at initial diagnosis can predict the efficacy achieved after induction therapy, and the lower positive rate of CD24 is, the worse the efficacy achieved after induction therapy. At the same time, MFC detection of CD24 is convenient and efficient in the evaluation and prediction of MM.

Arrhythmogenic cardiomyopathy (ACM), a fatal heart disease characterized by fibroadipocytic replacement of cardiac myocytes, accounts for 20% of sudden cardiac death and lacks effective treatment. It is often caused by mutations in desmosome proteins, with Desmoglein-2 (DSG2) mutations as a common etiology. However, the mechanism underlying the accumulation of fibrofatty in ACM remains unknown, which impedes the development of curative treatment. Here we investigated the fat accumulation and the underlying mechanism in a mouse model of ACM induced by cardiac-specific knockout of Dsg2 (CS-Dsg2 ^-/-). Heart failure and cardiac lipid accumulation were observed in CS-Dsg2 ^-/- mice. We demonstrated that these phenotypes were caused by decline of fatty acid (FA) β-oxidation resulted from impaired mammalian target of rapamycin (mTOR) signaling. Rapamycin worsened while overexpression of mTOR and 4EBP1 rescued the FA β-oxidation pathway in CS-Dsg2 ^-/- mice. Reactivation of PPARα by fenofibrate or AAV9-Pparα significantly alleviated the lipid accumulation and restored cardiac function. Our results suggest that impaired mTOR-4EBP1-PPARα-dependent FA β-oxidation contributes to myocardial lipid accumulation in ACM and PPARα may be a potential target for curative treatment of ACM.

Objective: To compare the predictive efficacy of the two thrombosis risk assessment scores (Padua and IMPEDE scores) in venous thromboembolism (VTE) within 6 months in patients with newly diagnosed multiple myeloma (NDMM) in China. Methods: This study reviewed the clinical data of 421 patients with NDMM hospitalized in Beijing Jishuitan Hospital from April 2014 to February 2022. The sensitivity, specificity, accuracy, and Youden index of the two scores were calculated to quantify the thrombus risk assessment of VTE by the Padua and IMPEDE scores. The receiver operating characteristics curves of the two evaluation scores were drawn. Results: The incidence of VTE was 14.73%. The sensitivity, specificity, accuracy, and Youden index of the Padua score were 100%, 0%, 14.7%, and 0% and that of the IMPEDE score was 79%, 44%, 49.2%, and 23%, respectively. The areas under the curve of Padua and IMPEDE risk assessment scores were 0.591 and 0.722, respectively. Conclusion: IMPEDE score is suitable for predicting VTE within 6 months in patients with NDMM.
Humans ; Venous Thromboembolism/etiology* ; Multiple Myeloma/diagnosis* ; Risk Assessment ; Risk Factors ; ROC Curve ; Retrospective Studies