Objective:To explore the factors affecting bone mineral density (BMD) in adult males with low-to-moderate fluoride exposure in Henan Province.Methods:Adult male villagers from low-to-moderate fluoride exposure areas in Tongxu County, Kaifeng City, Henan Province were recruited from April to May 2017 based on cluster random sampling. Questionnaire survey, physical measurements and urinary samples collection were conducted respectively. Urinary fluoride (UF) was determined by fluoride ion-selective electrode. Ultrasound bone densitometer was used to measure BMD (T-score). Partial correlation analysis and multiple linear regression were used to analyze the influence factors of BMD.Results:A total of 439 adult males were included in this study. Age, body mass index (BMI), UF content, and T-score of the participants were (47.99 ± 8.49) years, (25.77 ± 3.23) kg/m 2, (1.34 ± 0.74) mg/L, and-1.79 ± 0.79, respectively. Partial correlation analysis showed a significantly positive correlation between BMI and T-score after age adjustment ( r = 0.194, P < 0.05). Multiple linear regression showed that T-score decreased by 0.015 (95% CI:-0.024 -- 0.005, P < 0.05) for each 1-year increase in age and T-score increased by 0.034 (95% CI: 0.009-0.059, P < 0.05) for each 1.0 kg/m 2 increase in BMI. Interaction analysis showed that T-score was closely related to the interaction between overweight (≥24.0 kg/m 2), non-smoking, tea drinking and UF [ β (95% CI): 0.134 (0.001-0.269), 0.163 (- 0.015-0.337), 0.215 (- 0.006-0.436), P < 0.10]. Conclusions:Our findings reveal a negative correlation between age and BMD, and a positive correlation between BMI and BMD in adult males with low-to-moderate fluoride exposure in Henan Province. In addition, low-to-moderate fluoride exposure is more likely to damage the BMD of smokers.

The linear quadratic (LQ) model and deduced biological equivalent dose (BED) model are widely applied in the radiobiological studies and the mathematic models of radiation oncology in clinical practice. However, the LQ model cannot accurately fit the experimental and clinical data in the high-dose region under the high-dose-per-fraction treatment mode. To resolve this issue, researchers have made modifications to the LQ models since 2008. In the paper, first, the theoretical basis and the application scope of LQ and BED models were introduced and the debate on whether LQ model is applicable to the high-dose-per-fraction radiotherapy was reviewed. Second, five modified models were introduced in two categories and their characteristics were summarized. Finally, current research situation and existing problems of radiotherapy using biological equivalent dose (BED) models were briefly summarized and the development trend of models was predicted.

Objective:To investigate the long-term safety of digoxin in patients with coronary artery disease (CAD) and atrial fibrillation (AF).Methods:This was a prospective study, in which 25 512 AF patients were enrolled from China Atrial Fibrillation Registry Study. After exclusion of patients receiving ablation therapy at the enrollment, 1 810 CAD patients [age: (71.5±9.3)years] with AF were included. The subjects were grouped into the digoxin group and non-digoxin group, and were followed up for a period of 80 months. Long-term outcomes were compared between the groups and an adjusted Cox regression analysis was applied to evaluate the risk of digoxin on the long-term outcomes. The primary endpoint was all-cause mortality.Results:The patients were followed up for a median period of 3.05 years. After multivariable adjustment, the Cox regression analysis showed that digoxin significantly increased the risk of all-cause mortality ( HR=1.28, 95% CI 1.01-1.61, P=0.038), cardiovascular mortality ( HR=1.48,95% CI 1.10-2.00, P=0.010), cardiovascular hospitalization ( HR=1.67,95% CI 1.35-2.07, P=0.008) and the composite endpoints ( HR=2.02,95% CI 1.71-2.38, P<0.001). In the subgroup of patients with heart failure (HF), digoxin was not associated with the risk of all-cause mortality, but was still associated with the increased risk of cardiovascular mortality ( HR=1.44,95% CI 1.05-1.98, P=0.025), cardiovascular hospitalization ( HR=1.44,95% CI 1.09-1.90, P=0.010) and the composite endpoints ( HR=1.37, 95% CI 1.01-1.70, P=0.004). However, in the subgroup of patients without HF, digoxin was only associated with all-cause mortality ( HR=2.56,95% CI 1.44-4.54, P=0.001). Conclusion:Digoxin significantly increased the risk of all-cause mortality in CAD patients with AF, especially in patients without HF.