Objective To investigate the expression changes of iron autophagy-mitochondrial ferric ion transport protein families(SFXNs)in acute kidney injury(AKI)and chronic kidney disease(CKD)mouse models induced by cisplatin(Cis)and ischemia reperfusion(IR).Methods C57BL/6 mice were randomly divided into control group(control),Cis-AKI group,Cis-CKD group,sham-operated group(sham),IR-AKI group,and IR-CKD group.Serum and kidney tissue samples were collected from mice.Serum creatinine(Cr)and blood urea nitrogen(BUN)levels were detected.Pathological changes in renal tissues were observed by HE staining.Western blot was used to detect the expression of renal SFXNs and kidney injury related proteins.Results Compared with the control or sham group,the levels of BUN and Cr in the serum of the model group were significantly increased(P＜0.05),the renal tissue showed significant pathological damage,with the kidney injury molecule-1(KIM-1),neutrophil gelatinase-associated lipocalin(NGAL),and pro-apoptotic protein Bax significantly upregulated(P＜0.05),while the anti-apoptotic protein Bcl-2 was significantly downregulated(P＜0.05).Compared to the control or sham group,the Cis-AKI group showed a significant downregulation of SFXN4(P＜0.05);The SFXN4 and SFXN5 subtypes were significantly downregulated in the IR-AKI group and Cis-CKD group(P＜0.05);All five subtypes of SFXN in the IR-CKD group were significantly downregulated(P＜0.05).Conclusions Cis or IR in-duces renal tissue damage and tubular mitochondrial injury in mice and affects the expression of SFXN family pro-teins,suggesting their potential role in renal injury of animal models.

Objective:To investigate the application of the conjugate gradient (CG) algorithm to treatment plan optimization for intensity-modulated brachytherapy (IMBT).Methods:The general Monte Carlo software TOPAS was utilized to simulate the 192Ir source of IMBT, and the unit dose contribution matrix was calculated. An objective function was established using the weighted least squares method and was solved using the CG algorithm to achieve optimized IMBT treatment plans. The optimization was validated using five clinical cervical cancer cases under modulation width 60°. The dose distributions of IMBT treatment plans under 45°, 60°, 90°, 120°, and 180° modulation widths were compared using the Wilcoxon test to determine the optimal IMBT treatment plan for cervical cancer treatment. Results:The CG algorithm successfully optimized IMBT treatment plans under modulation width 60° for five cases within 22.2 s on average. On the premise of sufficient target dose coverage, the average D2 cm 3 values of the bladder and rectum in IMBT treatment plans were 3.66 and 1.97 Gy, respectively, representing reductions of 0.54 and 0.69 Gy compared to traditional brachytherapy plans. For the five modulation widths, the D90% values of all IMBT treatment plans reached 6 Gy, without statistically significant differences ( P > 0.05). The average D2 cm 3 values of the bladder in IMBT treatment plans were significantly lower than those in the traditional brachytherapy plans( P<0.05), with modulation width 60° associated with the greatest reduction of 0.61 Gy. In contrast, the average D2 cm 3 values of the rectum under 45°, 60°, and 90° modulation widths decreased by 0.63, 0.54, and 0.45 Gy, respectively, compared to traditional plans, with statistically significant differences( P<0.05). Conclusions:The CG method enables rapid achievement of optimized IMBT treatment plans that meet clinical requirements, and modulation width 60° contributes to valid dosimetric optimization. This study can serve as a guide for the clinical implementation of IMBT.

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 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 investigate the application of the conjugate gradient (CG) algorithm to treatment plan optimization for intensity-modulated brachytherapy (IMBT).Methods:The general Monte Carlo software TOPAS was utilized to simulate the 192Ir source of IMBT, and the unit dose contribution matrix was calculated. An objective function was established using the weighted least squares method and was solved using the CG algorithm to achieve optimized IMBT treatment plans. The optimization was validated using five clinical cervical cancer cases under modulation width 60°. The dose distributions of IMBT treatment plans under 45°, 60°, 90°, 120°, and 180° modulation widths were compared using the Wilcoxon test to determine the optimal IMBT treatment plan for cervical cancer treatment. Results:The CG algorithm successfully optimized IMBT treatment plans under modulation width 60° for five cases within 22.2 s on average. On the premise of sufficient target dose coverage, the average D2 cm 3 values of the bladder and rectum in IMBT treatment plans were 3.66 and 1.97 Gy, respectively, representing reductions of 0.54 and 0.69 Gy compared to traditional brachytherapy plans. For the five modulation widths, the D90% values of all IMBT treatment plans reached 6 Gy, without statistically significant differences ( P > 0.05). The average D2 cm 3 values of the bladder in IMBT treatment plans were significantly lower than those in the traditional brachytherapy plans( P<0.05), with modulation width 60° associated with the greatest reduction of 0.61 Gy. In contrast, the average D2 cm 3 values of the rectum under 45°, 60°, and 90° modulation widths decreased by 0.63, 0.54, and 0.45 Gy, respectively, compared to traditional plans, with statistically significant differences( P<0.05). Conclusions:The CG method enables rapid achievement of optimized IMBT treatment plans that meet clinical requirements, and modulation width 60° contributes to valid dosimetric optimization. This study can serve as a guide for the clinical implementation of IMBT.

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 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.

Background::Understanding willingness to undergo pulmonary function tests (PFTs) and the factors associated with poor uptake of PFTs is crucial for improving early detection and treatment of chronic obstructive pulmonary disease (COPD). This study aimed to understand willingness to undergo PFTs among high-risk populations and identify any barriers that may contribute to low uptake of PFTs.Methods::We collected data from participants in the "Happy Breathing Program" in China. Participants who did not follow physicians’ recommendations to undergo PFTs were invited to complete a survey regarding their willingness to undergo PFTs and their reasons for not undergoing PFTs. We estimated the proportion of participants who were willing to undergo PFTs and examined the various reasons for participants to not undergo PFTs. We conducted univariable and multivariable logistic regressions to analyze the impact of individual-level factors on willingness to undergo PFTs.Results::A total of 8475 participants who had completed the survey on willingness to undergo PFTs were included in this study. Out of these participants, 7660 (90.4%) were willing to undergo PFTs. Among those who were willing to undergo PFTs but actually did not, the main reasons for not doing so were geographical inaccessibility ( n = 3304, 43.1%) and a lack of trust in primary healthcare institutions ( n = 2809, 36.7%). Among the 815 participants who were unwilling to undergo PFTs, over half ( n = 447, 54.8%) believed that they did not have health problems and would only consider PFTs when they felt unwell. In the multivariable regression, individuals who were ≤54 years old, residing in rural townships, with a secondary educational level, with medical reimbursement, still working, with occupational exposure to dust, and aware of the abbreviation "COPD" were more willing to undergo PFTs. Conclusions::Willingness to undergo PFTs was high among high-risk populations. Policymakers may consider implementing strategies such as providing financial incentives, promoting education, and establishing community-based programs to enhance the utilization of PFTs.

Radiotherapy is widely used in the treatment of primary and metastatic malignant tumors. It is traditionally believed that the killing effect of radiotherapy on tumor is based on the direct or indirect damage of ionizing radiation to DNA. In recent years, the anti-tumor role and mechanism of anti-tumor immune response induced by ionizing radiation have captivated widespread attention and achieved significant progress. Among them, Cyclic GMP-AMP synthase (cGAS)-stimulator of interference genes (STING) pathway is considered to be one of the key regulatory hubs. cGAS is a cytoplasmic DNA receptor that can bind to tumor-derived double-stranded DNA and activate the downstream STING, thereby activating anti-tumor immune response of the host. In view of the latest progress in this field, the important role and potential mechanism of cGAS-STING pathway in radiotherapy immune effect were mainly summarized, and the application prospect of targeting cGAS-STING pathway in radiotherapy sensitization was explored.

Objective: To investigate the trends in incidence and mortality of gastric cancer in Ningbo City, Zhejiang Province from 2011 to 2022, so as to provide insights into improving gastric cancer control strategy. Methods: The incidence and mortality of gastric cancer in Ningbo City from 2011 to 2022 were collected through Ningbo Municipal Chronic Disease and Cause of Death Monitoring System. The incidence and mortality of gastric cancer were calculated, and standardized by the data from the Sixth Chinese National Population Census in 2020 (Chinese-standardized rate) and the world standard population first introduced by Segi in 1960 (world-standardized rate). The trends in incidence and mortality of gastric cancer were evaluated using annual percent change (APC) and average annual percent change (AAPC). Results : The crude incidence of gastric cancer was 45.69/105 in Ningbo City from 2011 to 2022, with no significant changing patterns seen during the study period (AAPC=-0.02%, P>0.05), and the Chinese- and world-standardized incidence of gastric cancer was 28.61/105 and 21.87/105, which both appeared a tendency towards a decline (AAPC=-3.19% and -3.05%, both P<0.05). The crude, Chinese-standardized and world-standardized mortality rates of gastric cancer were 28.56/105, 17.07/105 and 12.57/105, respectively, all showing a tendency towards a decline (AAPC=-3.00%, -6.26% and -6.34%, all P<0.05). The Chinese- and world-standardized incidence and mortality of gastric cancer all appeared a tendency towards a decline in urban (AAPC=-2.72%, -2.53%, -5.91% and -5.96%, all P<0.05) and rural areas (AAPC=-3.61%, -3.53%, -6.79% and -6.89%, all P<0.05), and the Chinese- and world-standardized incidence and mortality of gastric cancer were significantly higher among urban residents than among rural residents. The Chinese- and world-standardized incidence and mortality of gastric cancer all appeared a tendency towards a decline among men (AAPC=-3.18%, -3.00%, -5.82% and -5.91%, all P<0.05) and women (AAPC=-2.98%, -2.90%, -7.12% and -7.12%, all P<0.05), and the Chinese- and world-standardized incidence and mortality of gastric cancer was significantly higher among men than among women. In addition, the crude incidence and mortality of gastric cancer both appeared a tendency towards a rise with age among residents in Ningbo City (both P<0.05). Conclusions The incidence and mortality of gastric cancer both appeared a tendency towards a decline in Ningbo City from 2011 to 2022; however, the incidence and mortality remained high. Males and urban residents should be given a high priority for gastric cancer control, and gastric cancer screening should be strengthened among individuals at ages of 40 years and older.