Objective:To investigate the clinical value of prognostic nutrition index(PNI)in the overall survival of patients with non-small cell lung cancer(NSCLC)aged 70 years and above treated with radiotherapy, and to construct a nomogram prediction model.Methods:General clinicopathological features and routine blood test in144 patients with pathologically confirmed NSCLC aged 70 years and above were collected, PNI(serum albumin+ 5× lymphocyte count)before radiotherapy were calculated, and prognostic factors affecting the survival were analyzed.Build a nomogram model and verify it.Statistical analysis was performed using R language 4.0.3 software.Results:125 elderly patients with NSCLC met the inclusion criteria, with the median survival time of 18.4 months.The optimal cutoff value of PNI was 42.3.PNI was closely correlated with age, chemotherapy, immunotherapy and radiation pneumonia in elderly NSCLC patients receiving radiotherapy( P<0.05).TNM stage, chemotherapy, immunotherapy and PNI were independent factors affecting the prognosis of NSCLC patients aged 70 years and above who had received radiotherapy( P<0.05).We use these independent risk factors to construct prognostic column charts at 1, 2, and 3 years.We use Bootstrap repeated sampling 1000 times, and validate through ROC curves and calibration curves. Conclusions:For NSCLC patients aged 70 years and above who have received radiotherapy, PNI is a simple prognostic indicator and has practical clinical application value.

Objective:To explore the prognostic influencing factors of patients with pulmonary large cell neuroendocrine carcinoma (LCNEC), to develop a nomogram-based predictive model for the overall survival (OS) of LCNEC patients and to make validation.Methods:The clinical data of 2 947 patients with LCNEC in the Surveillance, Epidemiology, and End Results (SEER) database (the modeling group) and 147 patients with LCNEC in Beijing Chest Hospital Affiliated to Capital Medical University from 2010 to 2023 (the validation group). The data of patients in the both groups were compared. Cox proportional hazards model was used to screen out the factors influencing the OS of patients with LCNEC. A nomogram model was constructed to predict the OS based on the multivariate analysis result. Internal validation of the predictive model's performance was conducted through 500 repeated samplings based on the Bootstrap method. The predictive performance of the nomogram model was evaluated by using the area under the curve (AUC) of the receiver operating characteristic (ROC) curve. The consistency index (CI) was used to analyze the discrimination of the nomogram model in predicting the survival of LCNEC patients; calibration curves were used to analyze the consistency between the survival predicted by the nomogram model and the actual survival outcomes; and the decision curve analysis (DCA) was used to assess the net benefit of the model for actual clinical decision-making.Results:The differences in the proportions of patients with different age, gender, race, tumor staging, N stage, M stage, hepatic metastasis or not, pulmonary metastasis or not, chemotherapy and radiotherapy or not between the modeling group and the validation group were statistically significant (all P < 0.05). The median OS time of LCNEC patients in the modeling group was 14.0 months, with the 1-year OS rate of 53.3% and the 5-year OS rate of 21.2%; the median OS time of LCNEC patients in the validation group was 17.5 months, with the 1-year OS rate of 58.7%; there was no statistically significant difference in OS between the 2 groups ( P = 0.280). In the modeling group, the median OS time of female and male LCNEC patients was 18.0 and 12.0 months, respectively, and the difference in OS between the 2 groups was statistically significant ( P < 0.05); for patients with stage Ⅰ-Ⅱ, Ⅲ, and Ⅳ LCNEC, the median OS time was 48.0, 16.0, and 6.0 months, respectively, and the difference in OS among the 3 groups was statistically significant ( P < 0.05); the median OS time of patients receiving surgery and not receiving surgery was 28.0 and 8.0 months, respectively, and the difference in OS between the 2 groups was statistically significant ( P < 0.05). The differences in OS among female and male, patients in stages Ⅰ-Ⅱ, Ⅲ and Ⅳ, patients who underwent surgery or not were statistically significant (all P < 0.05). The results of multivariate Cox regression analysis in the modeling group showed that patients aged >60 years old (>60 years old vs. ≤60 years old: HR = 1.234, 95% CI: 1.114-1.367, P < 0.01), M 1 stage (M 1 stage vs. M 0 stage, HR = 2.646,95% CI: 2.385-2.935, P < 0.001), T 2-4 stage (T 2-4 stage vs. T 1 stage: HR = 1.199, 95% CI: 1.147-1.252, P < 0.001), N 1-3 stage (N 1-3 stage vs. N 0 stage: HR = 1.281, 95% CI: 1.225-1.340, P < 0.001) were independent risk factors of the OS in patients with LCNEC; female (female vs. male: HR = 0.877, 95% CI: 0.805-0.956, P = 0.003), surgery (yes vs. no: HR = 0.612, 95% CI: 0.554-0.676, P < 0.001), chemotherapy (yes vs. no: HR = 0.520, 95% CI: 0.470-0.575, P < 0.001) were independent protective factors of the OS in patients with LCNEC. A nomogram model for predicting 1, 3, and 5-year OS rates of LCNEC patients was constructed based on age, gender, T stage, N stage, M stage, surgery and chemotherapy. The result of ROC curve analysis indicated that the AUC of the nomogram model for predicting 1, 3, and 5-year OS rates in the modeling group was 0.822, 0.821 and 0.821, respectively, while the AUC of 1-year OS rate predicted by the validation group was 0.660. The CI of the modeling group and the validation group was 0.756 and 0.660, respectively. The calibration curve showed that 1, 3, and 5-year OS rates predicted by the modeling group were highly consistent with the actual OS rates. The DCA showed that the nomogram model for predicting OS in the modeling group and the validation group both had good clinical net benefits. Conclusions:The constructed nomogram model for predicting the prognosis of LCNEC patients is proved to be reliable and has good clinical values.

Background High-sensitivity C-reactive protein (hs-CRP) is a sensitive biomarker for cardiovascular disease (CVD) and can independently predict the risk of cardiovascular events. Although the association between per- and polyfluoroalkyl substances (PFAS) exposure and CVD risk has been widely reported, studies on the association between hs-CRP and PFAS remain limited. Objective To investigate the association between PFAS and hs-CRP levels, to provide a scientific basis for early identification and prevention of environment-related cardiovascular events. Methods This study utilized data from the National Health and Nutrition Examination Survey (NHANES) database (2015–2018). Based on predefined inclusion and exclusion criteria, a total of 3219 participants were included for subsequent analysis. Five PFAS with detection rates exceeding 90% were selected as exposure factors and log-transformed (lnPFAS) for subsequent analysis, including perfluorohexane sulfonic acid (PFHxS), perfluorononanoic acid (PFNA), perfluorooctanoic acid (PFOA), perfluorooctane sulfonic acid (PFOS), and perfluorodecanoic acid (PFDA). After selecting potential confounders through a change-in-estimate approach, logistic regression was employed to examine the effects of individual PFAS on serum hs-CRP level. Additionally, quantile g-computation and Bayesian kernel machine regression (BKMR) were applied to assess the combined effects of PFAS mixtures on hs-CRP. Results The study included 3219 participants with a mean age of (50.4±17.6) years, of whom 1554 (48.28%) were male. The median concentrations of the five PFAS compounds were: 1.20 ng·mL⁻¹ (PFHxS), 0.50 ng·mL⁻¹ (PFNA), 1.50 ng·mL⁻¹ (PFOA), 5.20 ng·mL⁻¹ (PFOS), and 0.20 ng·mL⁻¹ (PFDA). The Wilcoxon rank-sum tests revealed statistically significant differences between the elevated serum hs-CRP (≥2 mg·L⁻¹) and normal (<2 mg·L⁻¹) groups for all five PFAS compounds (PFHxS: P=0.005; PFNA: P=0.009; PFOA: P<0.001; PFOS: P<0.001; PFDA: P<0.001). After adjusting for potential confounders, the analysis of individual PFAS exposure demonstrated significant negative associations between serum hs-CRP levels and both ln-PFOS (OR: 0.87; 95%CI: 0.79, 0.96; P=0.0036) and lnPFDA (OR: 0.78; 95%CI: 0.71, 0.86; P < 0.001). The joint effect analysis using quantile g-computation revealed an overall inverse association between PFAS mixtures and hs-CRP, with lnPFDA emerging as a primary contributor; an similar association was observed in males, but not significant in females. Further evaluation through BKMR showed that when PFAS mixture concentrations reached or exceeded P₇₀, their combined effect on hs-CRP became significantly lower than when all PFAS concentrations were at P₅₀, establishing a clear negative dose-response relationship. Conclusion The mixed exposure to PFAS showed a significant negative joint effect on serum hs-CRP levels, with PFDA being the key component contributing to this combined effect. Future prospective cohort studies are warranted to further validate these findings and elucidate the underlying mechanisms involved.

Hypoxia inducible factors(HIFs)are core molecules that enable the body to adapt to hypoxia environments.By sensing changes in intracellular oxygen pressure,HIFs regulate gene expression related to hypoxia adaptation,thereby enhancing the body's hypoxia tolerance at cellular,tissue and organ levels.On the other hand,HIFs promote the generation of red blood cells,angiogenesis,and regulate the body's energy metabolism,thereby improving its hypoxia tolerance.The enhancement of hypoxia tolerance is of great significance for the prevention and treatment of hypoxia-related diseases,upgrading of athletes'performance,enhancement of workers'efficiency at high-altitudes,and the improvement of individu-als'quality of life.This article reviews the relationships between HIFs and hypoxia tolerance as well as related mechanisms in order to provide strategies for enhancing hypoxia tolerance in the body.

Objective To analyze the difference of diseases between the coal mine workers and the general population inpatients by the disease spectrum in Datong City. Methods A total of 282 639 hospitalized patients in Datong City in 2023 were included as the study subjects. Participants were divided into a general population group and a coal mine workers group based on health insurance types, with 247 897 and 34 742 cases, respectively. The disease spectrum of participants in both groups was coded and analyzed according to the International Statistical Classification of Diseases and Related Health Problems, 10th Revision (ICD-10). The standardized constituent ratios of disease categories were calculated and compared between the two groups. Results Patients aged 60-<70 years had the largest standardized proportion in both cohorts (29.02% in the general population group and 33.08% in coal mine workers group). Circulatory system diseases had the highest standardized proportion in both groups. Within the top six disease categories ranked by standardized composition ratio in the coal mine workers, three demonstrated a higher burden, including neoplasms (C00-D48), symptoms, signs and abnormal clinical/laboratory findings not elsewhere classified (R00-R99), and factors influencing health status/contact with health services (Z00-Z99), compared with the general population (11.82% vs 10.44%, 12.99% vs 8.03%, and 6.17% vs 2.04%, respectively). In both groups, male workers had higher standardized constituent ratios of circulatory, respiratory, and digestive system diseases than females (coal mine workers group, 19.53% vs 14.31%, 13.56% vs 9.10%, 10.61% vs 8.43%; general population group, 26.15% vs 22.42%, 15.45% vs 11.87%, 11.52% vs 10.41%). Conversely, the ratios for conditions classified under symptoms, signs and abnormal clinical/laboratory findings not elsewhere classified (R00-R99). and factors influencing health status/contact with health services (Z00-Z99) were higher in females than males (coal mine workers group, 13.31% vs 12.68%, 7.26% vs 5.13%; general population group, 8.91% vs 7.18%, 2.35% vs 1.74%). Mental and behavioral disorders (F00-F99) were most prevalent in the 22-<50-year age group in the general population (9.92%) and in the 50-<60-year age group in coal mine workers (8.58%). The standardized proportion of respiratory system diseases ranked first in≥80-year age workers in general population group and coal mine workers group (29.54% and 26.46%, respectively). Regarding specific malignancies, unspecified malignant neoplasm of the bronchus or lung was the most common cancer among males in both groups (3.44% and 3.62%). Among females, the standardized proportion of unspecified malignant neoplasm of breast was higher in coal mine workers group than in the general population group (2.60% vs 2.09%). Conclusion Neoplasms, abnormal symptoms, and mental health disorders should be prioritized in disease prevention strategies for coal mine workers. Greater attention should be paid to mental health screening in younger populations, and medical resource allocation should be optimized according to sex-specific high-incidence cancers.

Objective To develop a novel method for measuring the Hounsfield Unit(HU)value of the surface carbon fiber material of the Varian Exact IGRT Couch,and to establish a treatment couch model in the treatment planning system(TPS)for correcting the attenuation of radiation dose caused by the treatment couch.Methods Two different field combinations were used to measure the radiation dose attenuation at the thin end and the middle medium-thickness part of the Varian Exact IGRT Couch.Dose deviations were measured when radiation passed through the treatment couch or not.Multiple sets of different HU values for the couch surface materials were defined in the TPS,and the dose difference between with and without couch was calculated under the same conditions as the measurements.The HU value of the treatment couch material corresponding to the actual measurements was found by data comparison and analysis.Results The attenuation for two interpenetrating fields was-2.49%to-1.69%at the thin end,and-3.43%to-2.23%at the medium-thickness part.The attenuation for multiple oblique incident fields ranged from-3.12%to-2.17%at the thin end,and that was-3.59%to-2.86%at the medium-thickness part.When the HU values of the couch model's surface and internal materials in the TPS were defined as-500 and-960,for two interpenetrating fields,the attenuation was-2.57%to-1.53%at the thin end,and-3.28%to-2.18%at the medium-thickness part;while for multiple oblique incident fields,the attenuation was-3.12%to-2.21%at the thin ends,and-3.42%to-2.43%at the medium-thickness part.These calculated results were consistent with the actual measurement values.For 40 verification plans,the average point dose difference between measurement and calculation in TPS were 0.90%and 0.89%at the thin end and medium-thickness part,respectively.Conclusion This novel measurement method can measure the HU value of the surface carbon fiber material and internal foam material of Exact IGRT Couch.Defining the HU values of these two materials of the couch model in the TPS as-500 and-960 can correct the radiation dose attenuation caused by the treatment couch,thereby improving the dose accuracy of the target volume and organs-at-risk.

Objective:To investigate the clinical value of prognostic nutrition index(PNI)in the overall survival of patients with non-small cell lung cancer(NSCLC)aged 70 years and above treated with radiotherapy, and to construct a nomogram prediction model.Methods:General clinicopathological features and routine blood test in144 patients with pathologically confirmed NSCLC aged 70 years and above were collected, PNI(serum albumin+ 5× lymphocyte count)before radiotherapy were calculated, and prognostic factors affecting the survival were analyzed.Build a nomogram model and verify it.Statistical analysis was performed using R language 4.0.3 software.Results:125 elderly patients with NSCLC met the inclusion criteria, with the median survival time of 18.4 months.The optimal cutoff value of PNI was 42.3.PNI was closely correlated with age, chemotherapy, immunotherapy and radiation pneumonia in elderly NSCLC patients receiving radiotherapy( P<0.05).TNM stage, chemotherapy, immunotherapy and PNI were independent factors affecting the prognosis of NSCLC patients aged 70 years and above who had received radiotherapy( P<0.05).We use these independent risk factors to construct prognostic column charts at 1, 2, and 3 years.We use Bootstrap repeated sampling 1000 times, and validate through ROC curves and calibration curves. Conclusions:For NSCLC patients aged 70 years and above who have received radiotherapy, PNI is a simple prognostic indicator and has practical clinical application value.

Objective To develop a novel method for measuring the Hounsfield Unit(HU)value of the surface carbon fiber material of the Varian Exact IGRT Couch,and to establish a treatment couch model in the treatment planning system(TPS)for correcting the attenuation of radiation dose caused by the treatment couch.Methods Two different field combinations were used to measure the radiation dose attenuation at the thin end and the middle medium-thickness part of the Varian Exact IGRT Couch.Dose deviations were measured when radiation passed through the treatment couch or not.Multiple sets of different HU values for the couch surface materials were defined in the TPS,and the dose difference between with and without couch was calculated under the same conditions as the measurements.The HU value of the treatment couch material corresponding to the actual measurements was found by data comparison and analysis.Results The attenuation for two interpenetrating fields was-2.49%to-1.69%at the thin end,and-3.43%to-2.23%at the medium-thickness part.The attenuation for multiple oblique incident fields ranged from-3.12%to-2.17%at the thin end,and that was-3.59%to-2.86%at the medium-thickness part.When the HU values of the couch model's surface and internal materials in the TPS were defined as-500 and-960,for two interpenetrating fields,the attenuation was-2.57%to-1.53%at the thin end,and-3.28%to-2.18%at the medium-thickness part;while for multiple oblique incident fields,the attenuation was-3.12%to-2.21%at the thin ends,and-3.42%to-2.43%at the medium-thickness part.These calculated results were consistent with the actual measurement values.For 40 verification plans,the average point dose difference between measurement and calculation in TPS were 0.90%and 0.89%at the thin end and medium-thickness part,respectively.Conclusion This novel measurement method can measure the HU value of the surface carbon fiber material and internal foam material of Exact IGRT Couch.Defining the HU values of these two materials of the couch model in the TPS as-500 and-960 can correct the radiation dose attenuation caused by the treatment couch,thereby improving the dose accuracy of the target volume and organs-at-risk.

Objective:To explore the prognostic influencing factors of patients with pulmonary large cell neuroendocrine carcinoma (LCNEC), to develop a nomogram-based predictive model for the overall survival (OS) of LCNEC patients and to make validation.Methods:The clinical data of 2 947 patients with LCNEC in the Surveillance, Epidemiology, and End Results (SEER) database (the modeling group) and 147 patients with LCNEC in Beijing Chest Hospital Affiliated to Capital Medical University from 2010 to 2023 (the validation group). The data of patients in the both groups were compared. Cox proportional hazards model was used to screen out the factors influencing the OS of patients with LCNEC. A nomogram model was constructed to predict the OS based on the multivariate analysis result. Internal validation of the predictive model's performance was conducted through 500 repeated samplings based on the Bootstrap method. The predictive performance of the nomogram model was evaluated by using the area under the curve (AUC) of the receiver operating characteristic (ROC) curve. The consistency index (CI) was used to analyze the discrimination of the nomogram model in predicting the survival of LCNEC patients; calibration curves were used to analyze the consistency between the survival predicted by the nomogram model and the actual survival outcomes; and the decision curve analysis (DCA) was used to assess the net benefit of the model for actual clinical decision-making.Results:The differences in the proportions of patients with different age, gender, race, tumor staging, N stage, M stage, hepatic metastasis or not, pulmonary metastasis or not, chemotherapy and radiotherapy or not between the modeling group and the validation group were statistically significant (all P < 0.05). The median OS time of LCNEC patients in the modeling group was 14.0 months, with the 1-year OS rate of 53.3% and the 5-year OS rate of 21.2%; the median OS time of LCNEC patients in the validation group was 17.5 months, with the 1-year OS rate of 58.7%; there was no statistically significant difference in OS between the 2 groups ( P = 0.280). In the modeling group, the median OS time of female and male LCNEC patients was 18.0 and 12.0 months, respectively, and the difference in OS between the 2 groups was statistically significant ( P < 0.05); for patients with stage Ⅰ-Ⅱ, Ⅲ, and Ⅳ LCNEC, the median OS time was 48.0, 16.0, and 6.0 months, respectively, and the difference in OS among the 3 groups was statistically significant ( P < 0.05); the median OS time of patients receiving surgery and not receiving surgery was 28.0 and 8.0 months, respectively, and the difference in OS between the 2 groups was statistically significant ( P < 0.05). The differences in OS among female and male, patients in stages Ⅰ-Ⅱ, Ⅲ and Ⅳ, patients who underwent surgery or not were statistically significant (all P < 0.05). The results of multivariate Cox regression analysis in the modeling group showed that patients aged >60 years old (>60 years old vs. ≤60 years old: HR = 1.234, 95% CI: 1.114-1.367, P < 0.01), M 1 stage (M 1 stage vs. M 0 stage, HR = 2.646,95% CI: 2.385-2.935, P < 0.001), T 2-4 stage (T 2-4 stage vs. T 1 stage: HR = 1.199, 95% CI: 1.147-1.252, P < 0.001), N 1-3 stage (N 1-3 stage vs. N 0 stage: HR = 1.281, 95% CI: 1.225-1.340, P < 0.001) were independent risk factors of the OS in patients with LCNEC; female (female vs. male: HR = 0.877, 95% CI: 0.805-0.956, P = 0.003), surgery (yes vs. no: HR = 0.612, 95% CI: 0.554-0.676, P < 0.001), chemotherapy (yes vs. no: HR = 0.520, 95% CI: 0.470-0.575, P < 0.001) were independent protective factors of the OS in patients with LCNEC. A nomogram model for predicting 1, 3, and 5-year OS rates of LCNEC patients was constructed based on age, gender, T stage, N stage, M stage, surgery and chemotherapy. The result of ROC curve analysis indicated that the AUC of the nomogram model for predicting 1, 3, and 5-year OS rates in the modeling group was 0.822, 0.821 and 0.821, respectively, while the AUC of 1-year OS rate predicted by the validation group was 0.660. The CI of the modeling group and the validation group was 0.756 and 0.660, respectively. The calibration curve showed that 1, 3, and 5-year OS rates predicted by the modeling group were highly consistent with the actual OS rates. The DCA showed that the nomogram model for predicting OS in the modeling group and the validation group both had good clinical net benefits. Conclusions:The constructed nomogram model for predicting the prognosis of LCNEC patients is proved to be reliable and has good clinical values.