Objective: To explore the bidirectional causal relationship between 731 immune cell phenotypes and recurrent aphthous ulcers (RAU) using Mendelian randomization (MR). Methods: A two-sample bidirectional MR study was conducted using publicly available genome-wide association study (GWAS) summary statistics for 731 immune cell phenotypes and the RAU GWAS summary data from the FinnGen consortium. The inverse-variance weighted (IVW) method was used as the primary analysis tool, with supplementary analyses including the weighted median (WM) method, MR-Egger regression, weighted mode, and simple mode. Sensitivity analyses were conducted using Cochran’s Q test, the mendelian randomization pleiotropy residual sum and outlier (MR-PRESSO) method for detecting pleiotropy and outliers, and leave-one-out cross-validation. Furthermore, differential analysis was performed using a clinical cohort dataset from the Gene Expression Omnibus (GEO) to further validate the MR results. Results: In the forward MR analysis, 731 immune cell phenotypes were considered as exposures and RAU as the outcome. Among them, 52 immune cell phenotypes showed a significant causal effect on RAU (P<0.05). After false discovery rate (FDR) correction, two immune phenotypes remained significantly associated with RAU risk: with increased monocyte-derived myeloid suppressor cells (M-MDSC) (OR = 1.06; 95% CI: 1.03-1.09) and CD33 on granulocytic myeloid-derived suppressor cells (G-MDSC) (OR = 1.06; 95% CI: 1.03-1.09), the risk of RAU also increased. In reverse MR, RAU was found to have a significant causal effect on two immune cell phenotypes (P<0.05), but no significant effects were found after FDR correction. Sensitivity analysis showed no significant heterogeneity between SNPs (P>0.05). Differential analysis of the GEO dataset revealed that the characteristic genes of myeloid-derived suppressor cells (MDSC) (CTBS, IPMK, and UBA3) were significantly upregulated in RAU (P<0.05). Conclusion The MR results of 731 immune cell phenotypes suggest that M-MDSC and CD33 molecules on G-MDSC may be risk factors for RAU development. The clinical GEO dataset further validated that MDSC may play a role in RAU, while RAU did not show a significant causal association with the 731 immune cell phenotypes.

Objective:To establish a sterility test method for epinastine hydrochloride eye drops.Methods:Accord-ing to the Pharmacopoeia ofthe People's Republic ofChina 2020,the sterility test method of this product was estab-lished by membrane filtration method,polysorbate 80 was selected as the neutralizing agent,and the washing amount was screened to establish the sterility test method of this variety.Results:Taking 0.1%sterile peptone aqueous solu-tion containing 1%polysorbate 80 as the flushing solution,the flushing volume is 100 mL each time,and the total flushing volume of each membrane is 500 mL,which can eliminate the antibacterial effect.Conclusion:This method can effectively remove the bacteriostasis of epinastine hydrochloride eye drops,and is suitable for the sterility inspec-tion of this variety.

Objective:To construct a general deep learning dose prediction model applicable to radiotherapy for head and neck tumors, establish design methods for artificial intelligence (AI)-assisted radiotherapy plan and evaluate the accuracy of prediction.Methods:Radiotherapy plans of 818 patients who received radiotherapy for head and neck cancers from January 2018 to June 2021 in Cancer Hospital of Chinese Academy of Medical Sciences were enrolled. Patients involved 17 types of common head and neck cancers, and the prescribed dose covered 5 kinds of dose gradients ranging from 54 Gy to 73.92 Gy. And 1-2 cases per each cancer type (31 cases in total) were randomly selected as the validation set, and the remaining 787 cases were used as the training set to build a deep learning head and neck radiotherapy generalized dose prediction model. Then based on the dose prediction results of this model, a program was written to automatically generate inverse optimization condition scripts, which were sent back to the treatment planning system to achieve AI-assisted radiotherapy plan design. Among the patients who received radiotherapy in our hospital from June 2021 to January 2022, 1 patient for each disease type (17 cases in total) was selected to evaluate the AI-assisted plan design program and evaluate its clinical feasibility using paired t-test. Results:Dose prediction model accuracy evaluation revealed that in the 31-case validation set, there was no statistical difference in the evaluation metrics of clinical concern for organs at risks, except for the D 1 cm3 prediction for spinal cord planning risk volume, which was statistically different compared with the clinical reference plan. The AI-assisted plan design program had higher plan quality metric scores (37.88±6.42) than manual plans (35.00±7.63) in 17 test cases ( t=-1.00, P=0.166). The number of manual adjustments to the inverse optimization conditions was reduced from (5.47±2.97) times to (2.76±1.00) times for the AI-assisted plan compared to the manual-only plan ( t=4.12, P<0.001). And the number of outlined dose shaping structures was reduced from 7.35±3.98 to 3.12±1.18 ( t=5.61, P<0.001). Conclusions:The unified universal model of dose prediction established for different head and neck cancers has high accuracy in dose prediction for all types of head and neck tumor plans. The AI-assisted planning method established in this pattern can reduce the clinical workload of physicists and improve the efficiency of their work.

Objective:To evaluate the impact of roxadustat on thyroid function and to identify the associated factors in patients undergoing maintenance peritoneal dialysis (PD).Methods:This study was a single-center retrospective study. PD patients who received roxadustat or recombinant human erythropoietin (rHuEPO) treatment at Nanjing Drum Tower Hospital between January 2020 and June 2024 were included. The general and clinical information as well as laboratory indexes were collected. Serum free triiodothyronine (FT3), free thyroxine (FT4) and thyroid-stimulating hormone (TSH) were compared before and after treatment initiation. Hemoglobin (Hb) responses were also observed between the two groups. Logistic regression analysis was performed to explore the factors associated with thyroid function changes.Results:A total of 120 patients were enrolled, with an age of (55.17±16.42) years, including 66 males (55.0%). There were 81 patients received roxadustat (roxadustat group) and 39 patiens received rHuEPO (rHuEPO group). Compared to the rHuEPO group, the roxadustat group had a higher proportion of patients with diabetes ( χ 2= 4.172, P=0.041), a shorter PD vintage ( Z=-3.406, P=0.002), a lower serum level of total cholesterol ( Z=-2.082, P=0.037) and a lower level of fasting blood glucose ( Z=-2.589, P=0.010). Following treatment with roxadustat, the levels of FT4 ( Z=-5.349, P<0.01) and TSH ( Z=-3.720, P<0.01) decreased significantly. In contrast, no significant changes in FT4 or TSH levels were observed in the rHuEPO group (both P>0.05). For both roxadustat and rHuEPO groups, there were no significant changes in FT3 levels after treatment (both P>0.05). Multivariate analysis identified that higher baseline TSH (TSH≥2.27 μIU/ml, OR=1.581, 95% CI 1.196-2.089, P=0.001) and roxadustat exposure ( OR=3.432, 95% CI 1.410-8.355, P=0.007) as independent associated factors of subsequent TSH decline, and identified that higher baseline FT4 (FT4≥14.9 pmol/L, OR=1.390, 95% CI 1.162-1.662, P=0.001) and roxadustat exposure ( OR=5.798, 95% CI 2.225-15.113, P=0.001) as independent associated factors of subsequent FT4 decline. The degrees of hemoglobin changes after roxadustat or rHuEPO treatment did not differ significantly between roxadustat group and rHuEPO group ( t=-1.062, P=0.290). Of the 31 patients who underwent a second thyroid function test during roxadustat treatment, 24 continued with the original regimen, while 7 discontinued roxadustat. Among 24 patients who maintained roxadustat treatment, TSH ( Z=-0.400, P=0.689) and FT4 ( t=0.143, P=0.888) remained stable between the second and third tests. All 7 patients who discontinued roxadustat treatment showed TSH rebound and the changes of TSH levels were more significant than that in continuers ( Z=-2.505, P=0.012). FT4 recovery occurred in only 3 of them, with no significant difference in FT4 change between discontinuers and continuers ( Z=-0.685, P=0.493). Conclusions:Roxadustat commonly suppresses TSH and FT4, but not FT3, in PD patients. Baseline levels of TSH and FT4 are key associated factors of the inhibitory effect of roxadustat on thyroid function. This suppression does not intensify with prolonged exposure and is reversible after discontinuation, with TSH levels normalizing more quickly than FT4. Roxadustat-induced thyroid suppression does not compromise its efficacy in treating renal anemia.

Iron metabolism is a critical factor in tumorigenesis and development. Although TP53 mutations are prevalent in glioblastoma (GBM), the mechanisms by which TP53 regulates iron metabolism remain elusive. We reveal an imbalance iron homeostasis in GBM via TCGA database analysis. TP53 mutations disrupted iron homeostasis in GBM, characterized by elevated total iron levels and reduced ferritin (FTH). The gain-of-function effect triggered by TP53 mutations upregulates itchy E3 ubiquitin-protein ligase (ITCH) protein expression in astrocytes, leading to FTH degradation and an increase in free iron levels. TP53-mut astrocytes were more tolerant to the high iron environment induced by exogenous ferric ammonium citrate (FAC), but the increase in intracellular free iron made them more sensitive to Erastin-induced ferroptosis. Interestingly, we found that Erastin combined with FAC treatment significantly increased ferroptosis. These findings provide new insights for drug development and therapeutic modalities for GBM patients with TP53 mutations from iron metabolism perspectives.
Ferroptosis/drug effects* ; Humans ; Iron/metabolism* ; Glioblastoma/metabolism* ; Tumor Suppressor Protein p53/metabolism* ; Homeostasis/physiology* ; Ferritins/metabolism* ; Brain Neoplasms/genetics* ; Mutation ; Astrocytes/drug effects* ; Cell Line, Tumor ; Piperazines/pharmacology* ; Quaternary Ammonium Compounds/pharmacology* ; Ferric Compounds

Objective:To establish a sterility test method for epinastine hydrochloride eye drops.Methods:Accord-ing to the Pharmacopoeia ofthe People's Republic ofChina 2020,the sterility test method of this product was estab-lished by membrane filtration method,polysorbate 80 was selected as the neutralizing agent,and the washing amount was screened to establish the sterility test method of this variety.Results:Taking 0.1%sterile peptone aqueous solu-tion containing 1%polysorbate 80 as the flushing solution,the flushing volume is 100 mL each time,and the total flushing volume of each membrane is 500 mL,which can eliminate the antibacterial effect.Conclusion:This method can effectively remove the bacteriostasis of epinastine hydrochloride eye drops,and is suitable for the sterility inspec-tion of this variety.

OBJECTIVES: The application of photodynamic therapy in solid tumors has attracted increasing attention in recent years, and the efficiency of photosensitizers is a crucial determinant of therapeutic efficacy. This study aims to evaluate the cytotoxic effects of a novel photosensitizer, PEG-MTPABZ-PyC, in photodynamic therapy against gastric cancer cells. METHODS: Gastric cancer MKN45 cells were treated with PEG-MTPABZ-PyC. A high-content live-cell imaging system was used to assess the cellular uptake kinetics and subcellular localization of the photosensitizer. The cytotoxic effects of PEG-MTPABZ-PyC-mediated photodynamic therapy were examined using the cell counting kit-8 (CCK-8) assay and flow cytometry, while the intrinsic cytotoxicity of the photosensitizer alone was verified by the CCK-8 assay. Intracellular reactive oxygen species (ROS) generation after photodynamic therapy was detected using 2'-7'-dichlorodihydrofluorescein diacetate (DCFH-DA). RESULTS: PEG-MTPABZ-PyC alone exhibited no cytotoxicity toward MKN45 cells, indicating excellent cytocompatibility. The compound efficiently entered cells within 6 hours and localized predominantly in lysosomes. Upon light irradiation, PEG-MTPABZ-PyC-mediated photodynamic therapy induced significant cytotoxicity compared with the control group (P<0.05) and generated abundant intracellular ROS. CONCLUSIONS The novel photosensitizer PEG-MTPABZ-PyC demonstrates potent photodynamic cytotoxicity against gastric cancer cells, showing promising potential for further development in gastric cancer photodynamic therapy.
Humans ; Stomach Neoplasms/drug therapy* ; Photochemotherapy/methods* ; Photosensitizing Agents/pharmacology* ; Cell Line, Tumor ; Polyethylene Glycols/chemistry* ; Reactive Oxygen Species/metabolism* ; Mesoporphyrins/pharmacology*

Objective:To evaluate the impact of roxadustat on thyroid function and to identify the associated factors in patients undergoing maintenance peritoneal dialysis (PD).Methods:This study was a single-center retrospective study. PD patients who received roxadustat or recombinant human erythropoietin (rHuEPO) treatment at Nanjing Drum Tower Hospital between January 2020 and June 2024 were included. The general and clinical information as well as laboratory indexes were collected. Serum free triiodothyronine (FT3), free thyroxine (FT4) and thyroid-stimulating hormone (TSH) were compared before and after treatment initiation. Hemoglobin (Hb) responses were also observed between the two groups. Logistic regression analysis was performed to explore the factors associated with thyroid function changes.Results:A total of 120 patients were enrolled, with an age of (55.17±16.42) years, including 66 males (55.0%). There were 81 patients received roxadustat (roxadustat group) and 39 patiens received rHuEPO (rHuEPO group). Compared to the rHuEPO group, the roxadustat group had a higher proportion of patients with diabetes ( χ 2= 4.172, P=0.041), a shorter PD vintage ( Z=-3.406, P=0.002), a lower serum level of total cholesterol ( Z=-2.082, P=0.037) and a lower level of fasting blood glucose ( Z=-2.589, P=0.010). Following treatment with roxadustat, the levels of FT4 ( Z=-5.349, P<0.01) and TSH ( Z=-3.720, P<0.01) decreased significantly. In contrast, no significant changes in FT4 or TSH levels were observed in the rHuEPO group (both P>0.05). For both roxadustat and rHuEPO groups, there were no significant changes in FT3 levels after treatment (both P>0.05). Multivariate analysis identified that higher baseline TSH (TSH≥2.27 μIU/ml, OR=1.581, 95% CI 1.196-2.089, P=0.001) and roxadustat exposure ( OR=3.432, 95% CI 1.410-8.355, P=0.007) as independent associated factors of subsequent TSH decline, and identified that higher baseline FT4 (FT4≥14.9 pmol/L, OR=1.390, 95% CI 1.162-1.662, P=0.001) and roxadustat exposure ( OR=5.798, 95% CI 2.225-15.113, P=0.001) as independent associated factors of subsequent FT4 decline. The degrees of hemoglobin changes after roxadustat or rHuEPO treatment did not differ significantly between roxadustat group and rHuEPO group ( t=-1.062, P=0.290). Of the 31 patients who underwent a second thyroid function test during roxadustat treatment, 24 continued with the original regimen, while 7 discontinued roxadustat. Among 24 patients who maintained roxadustat treatment, TSH ( Z=-0.400, P=0.689) and FT4 ( t=0.143, P=0.888) remained stable between the second and third tests. All 7 patients who discontinued roxadustat treatment showed TSH rebound and the changes of TSH levels were more significant than that in continuers ( Z=-2.505, P=0.012). FT4 recovery occurred in only 3 of them, with no significant difference in FT4 change between discontinuers and continuers ( Z=-0.685, P=0.493). Conclusions:Roxadustat commonly suppresses TSH and FT4, but not FT3, in PD patients. Baseline levels of TSH and FT4 are key associated factors of the inhibitory effect of roxadustat on thyroid function. This suppression does not intensify with prolonged exposure and is reversible after discontinuation, with TSH levels normalizing more quickly than FT4. Roxadustat-induced thyroid suppression does not compromise its efficacy in treating renal anemia.

Objective:To construct a general deep learning dose prediction model applicable to radiotherapy for head and neck tumors, establish design methods for artificial intelligence (AI)-assisted radiotherapy plan and evaluate the accuracy of prediction.Methods:Radiotherapy plans of 818 patients who received radiotherapy for head and neck cancers from January 2018 to June 2021 in Cancer Hospital of Chinese Academy of Medical Sciences were enrolled. Patients involved 17 types of common head and neck cancers, and the prescribed dose covered 5 kinds of dose gradients ranging from 54 Gy to 73.92 Gy. And 1-2 cases per each cancer type (31 cases in total) were randomly selected as the validation set, and the remaining 787 cases were used as the training set to build a deep learning head and neck radiotherapy generalized dose prediction model. Then based on the dose prediction results of this model, a program was written to automatically generate inverse optimization condition scripts, which were sent back to the treatment planning system to achieve AI-assisted radiotherapy plan design. Among the patients who received radiotherapy in our hospital from June 2021 to January 2022, 1 patient for each disease type (17 cases in total) was selected to evaluate the AI-assisted plan design program and evaluate its clinical feasibility using paired t-test. Results:Dose prediction model accuracy evaluation revealed that in the 31-case validation set, there was no statistical difference in the evaluation metrics of clinical concern for organs at risks, except for the D 1 cm3 prediction for spinal cord planning risk volume, which was statistically different compared with the clinical reference plan. The AI-assisted plan design program had higher plan quality metric scores (37.88±6.42) than manual plans (35.00±7.63) in 17 test cases ( t=-1.00, P=0.166). The number of manual adjustments to the inverse optimization conditions was reduced from (5.47±2.97) times to (2.76±1.00) times for the AI-assisted plan compared to the manual-only plan ( t=4.12, P<0.001). And the number of outlined dose shaping structures was reduced from 7.35±3.98 to 3.12±1.18 ( t=5.61, P<0.001). Conclusions:The unified universal model of dose prediction established for different head and neck cancers has high accuracy in dose prediction for all types of head and neck tumor plans. The AI-assisted planning method established in this pattern can reduce the clinical workload of physicists and improve the efficiency of their work.

ObjectiveTo investigate the mechanism of Baitouweng Tang in inhibiting the growth of esophageal cancer （EC） cells by regulating budding uninhibited by benzimidazoles 1 （BUB1）/signal transducer and activator of transcription 3 （STAT3） signaling pathway. MethodGene chip technology was used to explore the differential gene expression between esophageal cancer tissues and normal tissues and identified differentially expressed genes. The differentially expressed genes were analyzed by bioinformatics methods. EC cells were treated with 25， 50， 100， 200， 400， 800 mg·L^-1 Baitouweng Tang. EC cell viability was detected by Thiazolyl Blue （MTT） colorimetry. Cell cycle and apoptosis were measured by flow cytometry. The expression of BUB1 was measured by real time quantitative polymerase chain reaction （Real-time PCR）. The protein levels of BUB1， STAT3， phosphorylated （p）-STAT3， Cyclin B1 （CCNB1）， cyclin-dependent kinase 1 （CDK1）， B-cell lymphoma-2 （Bcl-2）， cysteinyl aspartate-specific proteinase（Caspase）-3， and Caspase-9 were measured by Western blot. The migration and invasion abilities of the cells were measured by wound-healing and Transwell invasion assays. ResultDifferentially expressed genes were primarily involved in biological processes， signaling pathways， and network construction related to cell mitosis， with BUB1 identified as a key core gene. Compared with the control group， Baitouweng Tang inhibited BUB1 expression （P<0.05，P<0.01）. In vitro experiments showed that compared with the control group， Baitouweng Tang could significantly inhibit the growth （P<0.05，P<0.01）， migration and invasion （P<0.05，P<0.01） of EC cells， induce apoptosis （P<0.05，P<0.01）， and cause G₂/M phase increase （P<0.01）. After treatment with Baitouweng Tang， compared with the results in the control group， the expression of Caspase-3， and Caspase-9 in EC cells increased significantly （P<0.05，P<0.01）， while the expression of Bcl-2， BUB1， CCNB1， and CDK1 decreased significantly （P<0.05，P<0.01）. Moreover， the STAT3 signaling pathway was also found to play an important role in this process. ConclusionBaitouweng Tang may inhibit the growth of EC cells by downregulating BUB1 and mediating the STAT3 signaling pathway.