External validation of predictive models for new vertebral fractures following percutaneous vertebroplasty.

OBJECTIVE: To investigate the external validation and scalability of four predictive models regarding new vertebral fractures following percutaneous vertebroplasty. METHODS: Utilizing retrospective data acquired from two centers, compute the area under the curve (AUC), calibration curve, and Kaplan-Meier plot to assess the model's discrimination and calibration. RESULTS: In the external validation of Zhong et al.'s 2015 predictive model for the probability of new fractures post-vertebroplasty, the AUC for re-fracture at 1, 2, and 3 years postoperatively was 0.570, 0.617, and 0.664, respectively. The AUC for Zhong et al.'s 2016 predictive model for the probability of new fractures in neighboring vertebrae was 0.738. Kaplan-Meier plot results for both models indicated a significantly lower incidence of re-fracture in low-risk patients compared to high-risk patients. Li et al.'s 2021 model had an AUC of 0.518, and its calibration curve suggested an overestimation of the probability of new fractures. Li et al.'s 2022 model had an AUC of 0.556, and its calibration curve suggested an underestimation of the probability of new fractures. CONCLUSION: The external validation of four models demonstrated that the predictive model proposed by Zhong et al. in 2016 exhibited superior external generalization capabilities.

Accurate and robust segmentation of cerebral vasculature on four-dimensional arterial spin labeling magnetic resonance angiography using machine-learning approach.

Segmentation of cerebral vasculature on MR vascular images is of great significance for clinical application and research. However, the existing cerebrovascular segmentation approaches are limited due to insufficient image contrast and complicated algorithms. This study aims to explore the potential of the emerging four-dimensional arterial spin labeling magnetic resonance angiography (4D ASL-MRA) technique for fast and accurate cerebrovascular segmentation with a simple machine-learning approach. Nine temporal features were extracted from the intensity-time signal of each voxel, and eight spatial features from the neighboring voxels. Then, the unsupervised outlier detection algorithm, i.e. Isolation Forest, is used for segmentation of the vascular voxels based on the extracted features. The total length of the centerlines of the intracranial arterial vasculature, the dice similarity coefficient (DSC), and the average Hausdorff Distance (AVGHD) on the cross-sections of small- to large-sized vessels were calculated to evaluate the performance of the segmentation approach on 4D ASL-MRA of 18 subjects. Experiments show that the temporal information on 4D ASL-MRA can largely improve the segmentation performance. In addition, the proposed segmentation approach outperforms the traditional methods that were performed on the 3D image (i.e. the temporal average intensity projection of 4D ASL-MRA) and the previously proposed frame-wise approach. In conclusion, this study demonstrates that accurate and robust segmentation of cerebral vasculature is achievable on 4D ASL-MRA by using a simple machine-learning approach with appropriate features.

MR Diffusion-Weighted Imaging in Evaluating Immediate HIFU Treatment Response of Uterine Fibroids.

BACKGROUND: Nowadays, High Intensity Focused Ultrasound (HIFU) is a common surgery option for the treatment of uterine fibroids in China, the immediate response of which is clinically evaluated using Contrast Enhanced (CE) imaging. However, the injection of gadolinium with its potential adverse effect is of concern in CE and therefore, it deserves efforts to find a better imaging method without the need for contrast agent injection for this task. OBJECTIVE: To assess the role of diffusion-weighted imaging (DWI) in evaluating the immediate therapeutic response of HIFU treatment for uterine fibroids in comparison with CE. METHODS: 68 patients with 74 uterine fibroids receiving HIFU treatment were enrolled, and immediate treatment response was assessed using post-surgical DWI images. Semi-quantitative ordinal ablation quality grading and quantitative nonperfusion volume (NPV) measurement based on DWI and CE imaging were determined by two experienced radiologists. Agreement of ablation quality grading between DWI and CE was assessed using the weighted kappa coefficient, while intraobserver, interobserver and interprotocol agreements of NPV measurements within and between DWI and CE were evaluated using the intraclass correlation (ICC) and Bland-Altman analysis. RESULTS: Grading of immediate HIFU treatment response showed a moderate agreement between DWI and CE (weighted kappa = 0.446, p < 0.001). NPV measured in 65 fibroids with DWI of Grade 3~5 showed very high ICCs for the intraobserver and interobserver agreement within DWI and CE (all ICC > 0.980, p < 0.001) and also for the interprotocol agreement between DWI and CE (ICC = 0.976, p < 0.001). CONCLUSION: DWI could provide satisfactory ablation quality grading, and reliable NPV quantification results to assess immediate therapeutic responses of HIFU treatment for uterine fibroids in most cases, which suggests that non-contrast enhanced DWI might be potentially used as a more costeffective and convenient method in a large proportion of patients for this task replacing CE imaging.

Cost-Effective Engineered Cementitious Composites with Hybrid PVA and Basalt/PP Fiber: A Study on Compressive, Tensile and Impact Performance.

Currently, oil-coated PVA fibers are the most commonly used material in ECC research. However, the high price limits the application of PVA-ECC in practical engineering. In order to reduce the cost, one of the methods is to partially replace the PVA fibers in ECC. In order to demonstrate the feasibility of PVA/BF-ECC and PVA/PP-ECC, polyvinyl alcohol fibers (PVA), basalt fibers (BFs) and polypropylene fibers (PP) were added at 0.5%, 1.0% and 1.5% by volume of PVA in addition to 1% by volume of PVA. Subsequently, tensile, compression and drop-weight impact tests were conducted on single or hybrid fiber concrete. The results showed that the post-peak compression toughness, tensile strength, and initial cracking impact strength of PVA/BF-ECC and PVA/PP-ECC increased significantly with the increase in the volume ratio of BF and PP fibers, while the performance of PVA-ECC materials with the same fiber volume ratio decreased slightly. Therefore, the cost can be reduced by designing hybrid PVA/BF-ECC materials that meet the performance requirements. The experimental evidence presented in this study demonstrates the feasibility and reasonable prospect of the new hybrid PVA/BF-ECC.

Assessing the causal effect of long-term exposure to air pollution on cognitive decline in middle-aged and older adults - Empirical evidence from a nationwide longitudinal cohort.

Air pollution remains a risk factor for the global burden of disease. Middle-aged and older people are more susceptible to air pollution because of their declining physical function and are more likely to develop diseases from long-term air pollution exposure. Studies of the effects of air pollution on cognitive function in middle-aged and older adults have been inconsistent. More representative and definitive evidence is needed. This study analysed data from the Chinese Family Panel Study, an ongoing nationwide prospective cohort study, collected in waves 2014, 2016 and 2018. Rigorously tested instrument was selected for analysis and participants' PM2.5 and instrument exposures were assessed using high-precision satellite data. The causal relationship between long-term exposure to air pollution and poor cognitive function in middle-aged and older adults was investigated using the Correlated Random Effects Control Function (CRE-CF) method within a quasi-experimental framework. This study included a total of 7042 participants aged 45 years or older. A comparison of CRE-CF with other models (OLS model, ordered probit model, and ordered probit-CRE model) demonstrated the necessity of using CRE-CF given the endogeneity of air pollution. The credibility and validity of the instrumental variable were verified. In the CRE-CF model, long-term exposure to PM2.5 was found to accelerate cognitive decline in middle-aged and older adults (coefficients of -0.159, -0.336 and -0.244 for the total cognitive, verbal and mathematical scores, respectively). Taken together, these results suggest that chronic exposure to ambient air pollution is associated with cognitive decline in middle-aged and older adults, which highlights the need for appropriate protective policies.

Deep learning based MRI reconstruction with transformer.

Magnetic resonance imaging (MRI) has become one of the most powerful imaging techniques in medical diagnosis, yet the prolonged scanning time becomes a bottleneck for application. Reconstruction methods based on compress sensing (CS) have made progress in reducing this cost by acquiring fewer points in the k-space. Traditional CS methods impose restrictions from different sparse domains to regularize the optimization that always requires balancing time with accuracy. Neural network techniques enable learning a better prior from sample pairs and generating the results in an analytic way. In this paper, we propose a deep learning based reconstruction method to restore high-quality MRI images from undersampled k-space data in an end-to-end style. Unlike prior literature adopting convolutional neural networks (CNN), advanced Swin Transformer is used as the backbone of our work, which proved to be powerful in extracting deep features of the image. In addition, we combined the k-space consistency in the output and further improved the quality. We compared our models with several reconstruction methods and variants, and the experiment results proved that our model achieves the best results in samples at low sampling rates. The source code of KTMR could be acquired at https://github.com/BITwzl/KTMR.

Long-term exposure of PM2.5 components on the adults' depressive symptoms in China - Evidence from a representative longitudinal nationwide cohort.

In recent years, there is growing evidence that long-term exposure to fine particulate matter (PM2.5) is associated with depressive symptoms. However, little is known about the individual effects of PM2.5 components, particularly in low-income and middle-income countries. We investigated the association between long-term exposure to major components of PM2.5 and worsening depressive symptoms in Chinese adults based on a large, long-term, nationally representative, population-based prospective cohort. Our data were derived from China Family Panel Study (CFPS) wave 2012, 2016 and 2018 and a long-term (2010-2019) high-resolution PM2.5 components dataset covering the whole China. We assessed respondents' depressive symptoms using standardized scales and applied advanced Fixed-effect ordered logit model (FE-ologit) to capture the ordinal nature of respondents' depressive symptoms and control for individual-specific and time-invariant effects to investigate their associations with PM2.5 components. We included 9503 respondents and the FE-ologit model results indicated that the odds ratio of increase per standard unit was 1.118 (95 % CI: 1.020, 1.225) for black carbon, 1.134 (95 % CI: 1.028, 1.252) for organic matter, 1.127 for ammonium (95 % CI: 1.011, 1.255), 1.107 for nitrate (95 % CI: 0.981, 1.248), and 1.117 for sulfate (95 % CI: 1.020, 1.224). Our study suggests that long-term exposure to PM2.5 components is significantly associated with worsening of depressive symptoms, and that different components may have different toxicity. Reducing PM2.5 emissions, especially the major sources of organic matter and ammonium, may reduce the burden of depressive symptoms in Chinese adults.

Exploring the effect of the primary care health workers number on infectious diarrhea morbidity and where the health resources should go.

We aimed to explore the association between the number of primary healthcare workers and infectious diarrhea morbidity at community levels and to provide evidence-based implications for optimizing primary healthcare manpower resource allocations. We collected annual infectious diarrhea morbidity and relevant data of 4321 communities in Sichuan Province, China, from 2017 to 2019. Global and local Moran's I were calculated to detect the spatial clustering of infectious diarrhea morbidity and to identify areas where increased primary healthcare manpower resources should be allocated. The spatial lag fixed effects panel data model was adopted to explore the association between the number of primary healthcare workers per 1000 residents and infectious diarrhea morbidity. Significantly high-high and low-low clusters of infectious diarrhea cases were found to be mainly distributed in underdeveloped and developed areas during the studied period years, respectively. The infectious diarrhea morbidity was found to be statistically negatively associated with the number of primary healthcare workers per 1000 residents with a coefficient of - 0.172, indicating that a 0.172 reduction of infectious diarrhea morbidity (1/10,000) was associated with doubled amounts of primary healthcare workers per 1000 residents. Our findings highlighted the role of primary healthcare in the process of infectious diarrhea prevention and control, and implied that constant efforts should be addressed to facilitate infectious diarrhea prevention and control, especially in the underdeveloped areas.

Does long-term exposure to air pollution impair physical and mental health in the middle-aged and older adults? - A causal empirical analysis based on a longitudinal nationwide cohort in China.

The world is aging, posing a challenge to public health. Air pollution is increasingly recognized as an important environmental risk factor, with effects on both physical and mental health. Considering the vulnerability of older adults, they tend to have more prevalent comorbidities that may lead to broader consequences. However, evidence to comprehensively assess the causal effects of long-term air pollution exposure on the physical and mental health of older adults remains limited and inconsistent, especially in developing countries. The longitudinal data from the Chinese Family Panel Study (a representative Chinese national cohort study) for 2012, 2014, 2016, and 2018 were included in this study. The Correlated Random Effects Control Function method (CRE-CF) in a counterfactual causal inference framework was employed to explore the causal relationship between long-term exposure to air pollution and physical and mental health and self-rated health status in middle-aged and older adults, considering the ordered categorical nature of health outcomes. The appropriate instrumental variable was selected and validated. This study included 5846 participants aged >45 years in 2012. In the CRE-CF model for activities of daily living (ADLs, positively associated with physical health), subjective memory impairment (SMI, negatively associated with memory health) and self-rated health status in middle-age and older adults, the coefficient of PM2.5 is -0.069, 0.102, and 0.106 respectively, and all statistically significant at 5% level, which suggests that chronic exposure to air pollutants had significant negative effects on ADLs, SMI and self-rated health in middle-aged and older adults. The findings suggest that long-term exposure to air pollutants can impair the health of middle-aged and older adults across the board, including physical and mental health. In the context of an aging society, the findings of this study will provide tremendous implications for the authority to protect them from damage caused by long-term exposure to air pollutants.

Assessing the causal effects of long-term exposure to PM2.5 during pregnancy on cognitive function in the adolescence: Evidence from a nationwide cohort in China.

The effects of air pollution on adolescents need further consideration. Although there is evidence that maternal exposure to air pollution may affect the cognitive function of offspring, relevant studies remain limited and inconsistent, with a lack of studies assessing the causal effects and evidence from developing countries. Using data from Chinese Family Panel Studies, a representative Chinese nationwide cohort study, OLS combined with instrumental variable + two-stage least square (IV+2SLS) was used to explore the causal effects of exposure to PM2.5 concentrations during pregnancy on the cognitive function of offspring when they become adolescents. After detailed argumentation and multiple testing, Planetary Boundary Layer Height (PBLH) and Surface Pressure (SP) were selected as the instrumental variables for this study. One thousand five hundred fifty-five adolescents participated in this study, with a mean age of 13.3 years (sd = 2.3). There were 706 females (45.4%), the mean maternal PM2.5 exposure concentration was 64.9 µg/m3, and recorded a mean cognitive function score of 38.1 (sd = 9.4). The OLS results found that maternal exposure to air pollution increased cognitive function in offspring adolescents, corroborating the presence of endogeneity. Multi-domain knowledge, the results of the weak instrumental variable assessments of F-tests (F = 237 > 10) and Stock-yogo tests (minimum eigenvalue statistic = 153.16 > 16.38), and the results of the Hansen J overidentification test (p > 0.05) verified the plausibility and validity of the instrumental variables. The IV+2SLS results, following causal modeling, showed that PM2.5 exposure during pregnancy impairs the cognitive ability of offspring adolescents (ß = -0.040, p < 0.05). Robustness tests also validated the results. This study provides important policy implications for developing countries on protecting their adolescents and reminds parents that the protection of adolescents from air pollution should begin from conception.

Spatial inequality, characteristics of internal migration, and pulmonary tuberculosis in China, 2011-2017: a spatial analysis.

BACKGROUND: Human migration facilitate the spread of tuberculosis (TB). Migrants face an increased risk of TB infection. In this study, we aim to explore the spatial inequity of sputum smear-positive pulmonary TB (SS + PTB) in China; and the spatial heterogeneity between SS + PTB and internal migration. METHODS: Notified SS + PTB cases in 31 provinces in mainland China were obtained from the national web-based PTB surveillance system database. Internal migrant data were extracted from the report on China's migrant population development. Spatial autocorrelations were explored using the global Moran's statistic and local indicators of spatial association. The spatial variation in temporal trends was performed using Kulldorff's scan statistic. Fixed effect and spatial autoregressive models were used to explore the spatial inequity between SS + PTB and internal migration. RESULTS: A total of 2 380 233 SS + PTB cases were reported in China between 2011 and 2017, of which, 1 716 382 (72.11%) were male and 663 851 (27.89%) were female. Over 70% of internal migrants were from rural households and had lower income and less education. The spatial variation in temporal trend results showed that there was an 9.9% average annual decrease in the notification rate of SS + PTB from 2011 to 2017; and spatial clustering of SS + PTB cases was mainly located in western and southern China. The spatial autocorrelation results revealed spatial clustering of internal migration each year (2011-2017), and the clusters were stable within most provinces. Internal emigration, urban-to-rural migration and GDP per capita were significantly associated with SS + PTB, further, internal emigration could explain more variation in SS + PTB in the eastern region in mainland. However, internal immigration and rural-to-urban migration were not significantly associated with SS + PTB across China. CONCLUSIONS: Our study found the spatial inequity between SS + PTB and internal migration. Internal emigration, urban-to-rural migration and GDP per capita were statistically associated with SS + PTB; the negative association was identified between internal emigration, urban-to-rural migration and SS + PTB. Further, we found those migrants with lower income and less education, and most of them were from rural households. These findings can help stakeholders to implement effective PTB control strategies for areas at high risk of PTB and those with high rates of internal migration.

Forecasting PM2.5-induced lung cancer mortality and morbidity at county level in China using satellite-derived PM2.5 data from 1998 to 2016: a modeling study.

The serious ambient fine particulate matter (PM2.5) is one of the key risk factors for lung cancer. However, existing studies on the health effects of PM2.5 in China were less considered the regional transport of PM2.5 concentration. In this study, we aim to explore the association between lung cancer and PM2.5 and then forecast the PM2.5-induced lung cancer morbidity and mortality in China. Ridge regression (RR), partial least squares regression (PLSR), model tree-based (MT) regression, regression tree (RT) approach, and the combined forecasting model (CFM) were alternative forecasting models. The result of the Pearson correlation analysis showed that both local and regional scale PM2.5 concentration had a significant association with lung cancer mortality and morbidity and compared with the local lag and regional lag exposure to ambient PM2.5; the regional lag effect (0.172~0.235 for mortality; 0.146~0.249 for morbidity) was not stronger than the local lag PM2.5 exposure (0.249~0.294 for mortality; 0.215~0.301 for morbidity). The overall forecasting lung cancer morbidity and mortality were 47.63, 47.86, 39.38, and 39.76 per 100,000 population. The spatial distributions of lung cancer morbidity and mortality share a similar spatial pattern in 2015 and 2016, with high lung cancer morbidity and mortality areas mainly located in the central to east coast areas in China. The stakeholders would like to implement a cross-regional PM2.5 control strategy for the areas characterized as a high risk of lung cancer.

The association between internal migration and pulmonary tuberculosis in China, 2005-2015: a spatial analysis.

BACKGROUND: Internal migration places individuals at high risk of contracting tuberculosis (TB). However, there is a scarcity of national-level spatial analyses regarding the association between TB and internal migration in China. In our research, we aimed to explore the spatial variation in cases of sputum smear-positive pulmonary TB (SS + PTB) in China; and the associations between SS + PTB, internal migration, socioeconomic factors, and demographic factors in the country between 2005 and 2015. METHODS: Reported cases of SS + PTB were obtained from the national PTB surveillance system database; cases were obtained at the provincial level. Internal migration data were extracted from the national population sampling survey and the census. Spatial autocorrelations were explored using the global Moran's statistic and local indicators of spatial association. The spatial temporal analysis was performed using Kulldorff's scan statistic. Fixed effects regression was used to explore the association between SS + PTB and internal migration. RESULTS: A total of 4 708 563 SS + PTB cases were reported in China between 2005 and 2015, of which 3 376 011 (71.7%) were male and 1 332 552 (28.3%) were female. There was a trend towards decreasing rates of SS + PTB notifications between 2005 and 2015. The result of global spatial autocorrelation indicated that there were significant spatial correlations between SS + PTB rate and internal migration each year (2005-2015). Spatial clustering of SS + PTB cases was mainly located in central and southern China and overlapped with the clusters of emigration. The proportions of emigrants and immigrants were significantly associated with SS + PTB. Per capita GDP and education level were negatively associated with SS + PTB. The internal migration flow maps indicated that migrants preferred neighboring provinces, with most migrating for work or business. CONCLUSIONS: This study found a significant spatial autocorrelation between SS + PTB and internal migration. Both emigration and immigration were statistically associated with SS + PTB, and the association with emigration was stronger than that for immigration. Further, we found that SS + PTB clusters overlapped with emigration clusters, and the internal migration flow maps suggested that migrants from SS + PTB clusters may influence the TB epidemic characteristics of neighboring provinces. These findings can help stakeholders to implement effective PTB control strategies for areas at high risk of PTB and those with high rates of internal migrants.

Anti-CD27 Antibody Potentiates Antitumor Effect of Dendritic Cell-Based Vaccine in Prostate Cancer-Bearing Mice.

In the current study, we investigated whether anti-CD27 monoclonal antibody can enhance the antitumor efficacy of a dendritic cell-based vaccine in prostate cancer-bearing mice. The overall therapeutic effect of a dendritic cell-based vaccine for prostate cancer remains moderate. A prostate cancer model was established by subcutaneous injection of RM-1 tumor cells into male C57BL/6 mice on day 0. After 4 days, tumor-bearing mice were treated with RM-1 tumor lysate-pulsed dendritic cells (i.e., dendritic cell-based vaccine), anti-CD27 monoclonal antibody, or a combination of RM-1 tumor lysate-pulsed dendritic cells with anti-CD27 monoclonal antibody. Mice were killed at 21 days after tumor cell implantation. Tumor size was measured for assessment of antitumor effect. Spleens were collected for analysis of antitumor immune responses. The antitumor immune responses were evaluated by measuring the proliferation and activity of T cells, which have the ability to kill tumor cells. The combination therapy with RM-1 tumor lysate-pulsed dendritic cells and anti-CD27 antibody significantly enhanced T-cell proliferation and activity, and significantly reduced tumor growth, compared with monotherapy with RM-1 tumor lysate-pulsed dendritic cells or anti-CD27 antibody. Our results suggest that combined treatment can strengthen antitumor efficacy by improving T-cell proliferation and activity.