Objective To develop a deep learning-based denoising model for accelerating Monte Carlo(MC)simulation of electronic portal imaging device(EPID)transit dose images.Methods A total of 500 EPID fields were collected from 100 lung cancer patients undergoing 5-field intensity-modulated radiotherapy,with 400 fields randomly selected as training set,50 fields as validation set,and 50 fields as test set.EPID transit dose image datasets with low particle counts(1×107)and high particle counts(1×109)were simulated using the GPU-accelerated MC dose calculation engine ARCHER.A denoising network model named SUNet was constructed based on Swin Transformer and U-Net,and trained using low-particle-count images as input and high-particle-count images as output.Following training,SUNet model was used to denoise low-particle-count EPID images in the test set.Denoising performance was evaluated using structural similarity index(SSIM),peak signal-to-noise ratio(PSNR),and Gamma passing rates(3%/2 mm),and the computational efficiency of MC simulation combined with SUNet model was analyzed.Results Compared with the original low-particle-count images,the SUNet-denoised images showed significantly improved quality,reduced noise points,and smoother dose distribution.When benchmarked against high-particle-count images,the SUNet-denoised images achieved an average SSIM greater than 0.9,an average PSNR higher than 32 dB,and an average gamma passing rate exceeding 90%.The MC simulation combined with SUNet model required only 1.88 s to simulate a single EPID transit dose image,representing an approximate 40-fold improvement in computational efficiency as compared with high-particle-count MC simulation.Conclusion The deep learning-based denoising model substantially accelerates MC simulation of EPID transit dose images while preserving both image quality and dose accuracy,which provides possibilities for EPID-basedin vivodose verification.

Objective The development status,hot spots and trends of traditional Chinese medicine in the treatment of multiple sclerosis(MS)were analyzed by bibliometric and visual analysis.Methods Literatures related to the treatment of MS by traditional Chinese medicine were searched from CNKI,Wanfang Data and VIP from January 2000 to July 2024.CiteSpace software was used to visually analyze the number of publications,authors,institutions and key words in relevant literatures.Results A total of 438 literatures were included,and the number of published literatures showed an overall increasing trend.Fan Yongping pubilshed the most papers.The research institutions were mainly Dongzhimen Hospital of Beijing University of Chinese Medicine and Beijing Tiantan Hospital Affiliated to Capital Medical University.The current high-frequency key words in this field included acupuncture,treatment based on syndrome differentiation,traditional Chinese medicine,etc.A total of 9 clusters were formed."Acupuncture"was the most prominent.Conclusion Scholars have carried out active exploration and research in the field of traditional Chinese medicine in the treatment of MS,and the overall development trend is good.The research hot spots include acupuncture,treatment based on syndrome differentiation,traditional Chinese medicine,etc.,and the etiology and pathogenesis may be the future research trend.

Objective The development status,hot spots and trends of traditional Chinese medicine in the treatment of multiple sclerosis(MS)were analyzed by bibliometric and visual analysis.Methods Literatures related to the treatment of MS by traditional Chinese medicine were searched from CNKI,Wanfang Data and VIP from January 2000 to July 2024.CiteSpace software was used to visually analyze the number of publications,authors,institutions and key words in relevant literatures.Results A total of 438 literatures were included,and the number of published literatures showed an overall increasing trend.Fan Yongping pubilshed the most papers.The research institutions were mainly Dongzhimen Hospital of Beijing University of Chinese Medicine and Beijing Tiantan Hospital Affiliated to Capital Medical University.The current high-frequency key words in this field included acupuncture,treatment based on syndrome differentiation,traditional Chinese medicine,etc.A total of 9 clusters were formed."Acupuncture"was the most prominent.Conclusion Scholars have carried out active exploration and research in the field of traditional Chinese medicine in the treatment of MS,and the overall development trend is good.The research hot spots include acupuncture,treatment based on syndrome differentiation,traditional Chinese medicine,etc.,and the etiology and pathogenesis may be the future research trend.

Objective To develop a deep learning-based denoising model for accelerating Monte Carlo(MC)simulation of electronic portal imaging device(EPID)transit dose images.Methods A total of 500 EPID fields were collected from 100 lung cancer patients undergoing 5-field intensity-modulated radiotherapy,with 400 fields randomly selected as training set,50 fields as validation set,and 50 fields as test set.EPID transit dose image datasets with low particle counts(1×107)and high particle counts(1×109)were simulated using the GPU-accelerated MC dose calculation engine ARCHER.A denoising network model named SUNet was constructed based on Swin Transformer and U-Net,and trained using low-particle-count images as input and high-particle-count images as output.Following training,SUNet model was used to denoise low-particle-count EPID images in the test set.Denoising performance was evaluated using structural similarity index(SSIM),peak signal-to-noise ratio(PSNR),and Gamma passing rates(3%/2 mm),and the computational efficiency of MC simulation combined with SUNet model was analyzed.Results Compared with the original low-particle-count images,the SUNet-denoised images showed significantly improved quality,reduced noise points,and smoother dose distribution.When benchmarked against high-particle-count images,the SUNet-denoised images achieved an average SSIM greater than 0.9,an average PSNR higher than 32 dB,and an average gamma passing rate exceeding 90%.The MC simulation combined with SUNet model required only 1.88 s to simulate a single EPID transit dose image,representing an approximate 40-fold improvement in computational efficiency as compared with high-particle-count MC simulation.Conclusion The deep learning-based denoising model substantially accelerates MC simulation of EPID transit dose images while preserving both image quality and dose accuracy,which provides possibilities for EPID-basedin vivodose verification.

Objective:To evaluate the efficacy and safety of nebulized inhalation of recombinant human interferon (IFN) α1b injection in the treatment of respiratory syncytial virus (RSV) associated lower respiratory tract infections (pneumonia and bronchiolitis) in children.Methods:A randomized, double-blind, parallel, placebo-controlled add-on design was used.Children with pneumonia or bronchiolitis aged 2 months to 5 years who tested positive for RSV antigen within 72 hours of onset from 30 clinical trial sites including Beijing Children′s Hospital, Capital Medical University between February 2021 and December 2022 were included in this study and randomly divided into 2 groups at a ratio of 1∶1 based on a stratified-block method.Both groups received basic treatments such as cough control, asthma relieving, expectorant treatment, fever reduction, oxygen therapy, etc.The experimental group received additional nebulized inhalation of IFN α1b injection at a dose of 2.0 μg/(kg·time), twice a day.The control group received nebulized inhalation of placebo twice a day.Clinical efficacy was evaluated based on indicators such as the duration of clinical symptoms and signs, and the Kaplan-Meier method was used to calculate the median and 95% CI of the duration of clinical symptoms and signs.The Log-rank test was used to compared data between groups.Safety was assessed through the incidence of adverse reactions and laboratory tests, and the Chi-square test was used to analyze the difference between groups. Results:There were 123 children in the experimental group and 122 children in the control group.The median durations of all the 5 clinical symptoms and signs [including shortness of breath, wheezing, dyspnea (visible retractions), decreased transcutaneous oxygen saturation, and abnormal mental state] in the experimental group after treatment were slightly shortened than those in the control group [2.7 d(95% CI: 1.9-3.0 d)] vs.[2.9 d(95% CI: 2.6-3.6 d), P=0.027].The improvement in dyspnea (retractions) was especially pronounced in the experimental group, with a relief rate of 50.0% (0, 100%) on the first day of administration[compared with 0 (0, 50.0%) in the control group ( Z=2.002, P=0.025)].The median duration of dyspnea in the experimental group was nearly 1 day shorter than that in the control group [1.0 d(95% CI: 0.7-1.7 d) vs.1.8 d(95% CI: 1.0-2.5 d), P=0.046].There were no significant difference in hospital stay [6.0(5.0, 8.0) d vs.6.5(5.0, 8.0) d, Z=0.675, P=0.500], oxygen therapy duration [32.0(14.0, 96.3) h vs.39.0 (24.0, 83.2) h, Z=0.094, P=0.925], the recovery rate from clinical symptoms during treatment [(105/106, 99.1%) vs.(96/101, 95.0%)], and recurrence rate [(0/106, 0) vs.(2/101, 2.0%)] between the 2 groups (all P>0.05).However, the above-mentioned four indicators in the experimental group showed a trend of clinical benefits.The quantitative virus detection results showed that the RSV viral load in both groups decreased after treatment compared to before treatment.After 2 days of treatment, the decline rate of RSV viral load from the baseline was 0.90 lg copies/(mL·d) in the experimental group and 0.25 lg copies/(mL·d)in the control group, with a statistically significant difference ( P<0.05).Furthermore, there was no statistically significant difference in the incidence of adverse reactions between the 2 groups ( P>0.05).Importantly, no drug-related serious adverse reactions occurred in both groups. Conclusions:The nebulized inhalation therapy of IFN α1b demonstrates efficacy and safety in treating pediatric RSV associated lower respiratory tract infections.It particularly offers outstanding clinical therapeutic value for severe children.

Objective:To rapidly and accurately detect volumetric modulated arc therapy (VMAT) plans with potentially inaccurate radiation doses.Methods:The measurement-based dosimetric verification result of 196 VMAT plans obtained using ArcCHECK phantoms were retrospectively collected. Independent dosimetric calculation and verification were conducted for these plans using the ArcherQA system based on a fast Monte Carlo algorithm. The gamma passing rates of dosimetric verification using ArcCHECK phantom and the ArcherQA system were compared, followed by their correlation analysis and linear regression fitting. The ArcherQA system′s gamma passing rate threshold used to detect positive dosimetric verification result obtained using ArcCHECK phantoms, as well as the specificity of the detection, were calculated. Based on this gamma passing rate threshold, another 50 VMAT plans were selected as a test set to assess the ArcherQA system′s ability to detect positive measurement-based dosimetric verification result.Results:The average gamma passing rates for the dosimetric verification of the VMAT plans using the ArcherQA system and ArcCHECK phantoms were 97.28% and 96.57% (3%/3 mm, TH=10%), respectively. Both rates had a correlation coefficient of 0.71 ( P < 0.01) and a linear fitting coefficient of 0.54 ( R2=0.51). When the gamma passing rate for dosimetric verification using ArcCHECK phantoms was set at 90% (3%/2 mm, TH=10%), the gamma passing rate threshold for dosimetric verification using the ArcherQA system should be adjusted to 94.8% to detect all VMAT plans with positive dosimetric verification result obtained using ArcCHECK phantoms, with a specificity of 67.8%. Using this threshold, the ArcherQA system detected all VMAT plans in the test set for which ArcCHECK phantom-based measurement yielded positive dosimetric verification result. Conclusions:By determining an appropriate gamma passing rate threshold, the ArcherQA system can rapidly and accurately detect VMAT plans with potentially inaccurate doses, thus ensuring treatment accuracy and improving work efficiency.

Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.

Objective:To rapidly and accurately detect volumetric modulated arc therapy (VMAT) plans with potentially inaccurate radiation doses.Methods:The measurement-based dosimetric verification result of 196 VMAT plans obtained using ArcCHECK phantoms were retrospectively collected. Independent dosimetric calculation and verification were conducted for these plans using the ArcherQA system based on a fast Monte Carlo algorithm. The gamma passing rates of dosimetric verification using ArcCHECK phantom and the ArcherQA system were compared, followed by their correlation analysis and linear regression fitting. The ArcherQA system′s gamma passing rate threshold used to detect positive dosimetric verification result obtained using ArcCHECK phantoms, as well as the specificity of the detection, were calculated. Based on this gamma passing rate threshold, another 50 VMAT plans were selected as a test set to assess the ArcherQA system′s ability to detect positive measurement-based dosimetric verification result.Results:The average gamma passing rates for the dosimetric verification of the VMAT plans using the ArcherQA system and ArcCHECK phantoms were 97.28% and 96.57% (3%/3 mm, TH=10%), respectively. Both rates had a correlation coefficient of 0.71 ( P < 0.01) and a linear fitting coefficient of 0.54 ( R2=0.51). When the gamma passing rate for dosimetric verification using ArcCHECK phantoms was set at 90% (3%/2 mm, TH=10%), the gamma passing rate threshold for dosimetric verification using the ArcherQA system should be adjusted to 94.8% to detect all VMAT plans with positive dosimetric verification result obtained using ArcCHECK phantoms, with a specificity of 67.8%. Using this threshold, the ArcherQA system detected all VMAT plans in the test set for which ArcCHECK phantom-based measurement yielded positive dosimetric verification result. Conclusions:By determining an appropriate gamma passing rate threshold, the ArcherQA system can rapidly and accurately detect VMAT plans with potentially inaccurate doses, thus ensuring treatment accuracy and improving work efficiency.

Objective To investigate the expression of the histone deacetylase SIRT7 in glioma cells and its impact on epithelial-mesenchymal transformation(EMT),as well as its effects on proliferative,migratory and invasive capabilities of glioma cells.Methods Bioinformatics analysis was conducted on data from glioma patients in the Cancer Genome Atlas(TCGA)and the Chinese glioma Genome Atlas(CGGA)databases to explore the expression of SIRT7 gene in gliomas and its correlation with tumor grading,molecular characteristics and patient clinical prognosis.Glioma cells were randomly divided into control,SIRT7 knockdown,SIRT7 overexpression,drug treatment(10 μmol/L hydrochlorothiazide)and drug(10 μmol/L hydrochlorothiazide)+SIRT7 overexpression groups.The CCK-8 assay,cell scratch assay and Transwell assay were used to observe the effects of upregulating and downregulating SIRT7 expression on glioma cell proliferation,migration and invasion.RT-qPCR and Western blotting were employed to detect the effects of SIRT7 on the expression of neural cadherin(N-cadherin),Vimentin,E-cadherin,transforming growth factor-β(TGF-β),Ki-67,and Smad3 protein in glioma cells.Nude mouse tumor-bearing experiments were conducted to observe the effect of SIRT7 knockdown on glioma growth.Results Higher expression levels of SIRT7 gene were associated with poorer clinical prognosis(P＜0.0001).SIRT7 expression levels were significantly correlated with tumor grading and 1p19q coding status(P＜0.01).Compared with normal HA cells,glioma cells showed significantly increased SIRT7 expression levels(P＜0.01).CCK-8 assay results indicated that,compared with control group,the proliferation activity of glioma cells in SIRT7 knockout group was significantly decreased(P＜0.01),while SIRT7 overexpression group showed significantly increased proliferation activity(P＜0.01).EdU assay results showed that,compared with control group,the proportion of glioma cells in the proliferative stage was significantly decreased in SIRT7 knockdown group(P＜0.01),and significantly increased in SIRT7 overexpression group(P＜0.01).Western blotting results revealed that,compared with control group,the protein expression levels of TGF-β,Smad3,N-cadherin and Vimentin were significantly decreased in SIRT7 knockdown group(P＜0.01),while the expression level of E-cadherin protein was significantly increased(P＜0.05).SIRT7 overexpression group showed significantly increased protein expression levels of TGF-β,Smad3,N-cadherin and Vimentin(P＜0.05),and a significantly decrease in E-cadherin protein expression level(P＜0.05).Scratch assay results indicated that,compared with control group,the migration ability of cells in SIRT7 knockdown group and drug group was significantly decreased(P＜0.01),and SIRT7 overexpression group showed significantly increased cell migration ability(P＜0.05).Compared with drug group,drug+SIRT7 overexpression group exhibited significantly increased cell migration ability(P＜0.01).Transwell assay results showed that,compared with control group,the migration and invasion abilities of cells in SIRT7 knockdown group and drug group were significantly decreased(P＜0.01),and SIRT7 overexpression group exhibited significantly increased migration and invasion abilities(P＜0.01).Compared with drug group,drug+SIRT7 overexpression group showed significantly increased migration and invasion abilities(P＜0.01).Nude mouse tumor-bearing assay results indicated that the volume and weight of glioma in SIRT7 knockdown group were significantly reduced compared with control group(P＜0.01).Conclusions Glioma patients with high SIRT7 expression have poorer clinical prognosis.SIRT7 can regulate the TGF-β/Smad3 pathway to mediate EMT,promoting the proliferation and migration of glioma cells.SIRT7 knockdown can inhibit the growth of transplanted gliomas in nude mice.

Idiopathic pulmonary fibrosis (IPF), a chronic interstitial lung disease, is characterized by aberrant wound healing, excessive scarring and the formation of myofibroblastic foci. Although the role of alternative splicing (AS) in the pathogenesis of organ fibrosis has garnered increasing attention, its specific contribution to pulmonary fibrosis remains incompletely understood. In this study, we identified an up-regulation of serine/arginine-rich splicing factor 7 (SRSF7) in lung fibroblasts derived from IPF patients and a bleomycin (BLM)-induced mouse model, and further characterized its functional role in both human fetal lung fibroblasts and mice. We demonstrated that enhanced expression of Srsf7 in mice spontaneously induced alveolar collagen accumulation. Mechanistically, we investigated alternative splicing events and revealed that SRSF7 modulates the alternative splicing of pyruvate kinase (PKM), leading to metabolic dysregulation and fibroblast activation. In vivo studies showed that fibroblast-specific knockout of Srsf7 in conditional knockout mice conferred resistance to bleomycin-induced pulmonary fibrosis. Importantly, through drug screening, we identified lomitapide as a novel modulator of SRSF7, which effectively mitigated experimental pulmonary fibrosis. Collectively, our findings elucidate a molecular pathway by which SRSF7 drives fibroblast metabolic dysregulation and propose a potential therapeutic strategy for pulmonary fibrosis.