Compressed sensing 3D T2WI radiomics model: improving diagnostic performance in muscle invasion of bladder cancer.

BACKGROUND: Preoperative discrimination between non-muscle-invasive bladder cancer (NMIBC) and the muscle invasive bladder cancer (MIBC) is a determinant of management. The purpose of this research is to employ radiomics to evaluate the diagnostic value in determining muscle invasiveness of compressed sensing (CS) accelerated 3D T2-weighted-SPACE sequence with high resolution and short acquisition time. METHODS: This prospective study involved 108 participants who underwent preoperative 3D-CS-T2-weighted-SPACE, 3D-T2-weighted-SPACE and T2-weighted sequences. The cohort was divided into training and validation cohorts in a 7:3 ratio. In the training cohort, a Rad-score was constructed based on radiomic features selected by intraclass correlation coefficients, pearson correlation coefficient and least absolute shrinkage and selection operator . Multivariate logistic regression was used to develop a nomogram combined radiomics and clinical indices. In the validation cohort, the performances of the models were evaluated by ROC, calibration, and decision curves. RESULTS: In the validation cohort, the area under ROC curve of 3D-CS-T2-weighted-SPACE, 3D-T2-weighted-SPACE and T2-weighted models were 0.87(95% confidence interval (CI):0.73-1.00), 0.79(95%CI:0.63-0.96) and 0.77(95%CI:0.60-0.93), respectively. The differences in signal-to-noise ratio and contrast-to-noise ratio between 3D-CS-T2-weighted-SPACE and 3D-T2-weighted-SPACE sequences were not statistically significant(p > 0.05). While the clinical model composed of three clinical indices was 0.74(95%CI:0.55-0.94) and the radiomics-clinical nomogram model was 0.88(95%CI:0.75-1.00). The calibration curves confirmed high goodness of fit, and the decision curve also showed that the radiomics model and combined nomogram model yielded higher net benefits than the clinical model. CONCLUSION: The radiomics model based on compressed sensing 3D T2WI sequence, which was acquired within a shorter acquisition time, showed superior diagnostic efficacy in muscle invasion of bladder cancer. Additionally, the nomogram model could enhance the diagnostic performance.

Multi-Sequence and Multi-Regional MRI-Based Radiomics Nomogram for the Preoperative Assessment of Muscle Invasion in Bladder Cancer.

BACKGROUND: Whether bladder cancer (BCa) invades muscle is a determinant of management. However, the accuracy of preoperative diagnosis of muscle invasion is not satisfactory. PURPOSE: To investigate the value of multi-sequence and multi-regional magnetic resonance imaging (MRI)-based radiomics nomogram for assessing muscle invasion of BCa. STUDY TYPE: Retrospective. POPULATION: 342 BCa patients, divided into a training set (239 cases), a validation set (68 cases), and a test set (35 cases). FIELD STRENGTH/SEQUENCE: 3.0 T/T2 -weighted image, diffusion-weighted imaging, and dynamic contrast-enhanced imaging. ASSESSMENT: Patients were divided into muscle-invasive (79 cases) and non-muscle-invasive (263 cases). Two radiologists delineated the whole tumor, tumor body, and muscle layer of BCa, respectively, and extracted radiomic features. STATISTICAL TESTS: Recursive feature elimination, Pearson correlation coefficient, logistic regression, least absolute shrinkage and selection operator (Lasso) regression analysis, and 5-fold cross-validation were used to screen features and build a radiomics model. The clinical data were collected to construct a clinical model and a radiomics-clinical nomogram. RESULTS: 23,688 features were extracted. After screening, the radiomics scoring model was constructed using nine radiomics features with area under curve (AUC) values of 0.933, 0.913, and 0.931 in the training, validation, and test sets, respectively. The clinical model was constructed using five clinical independent risk factors; the AUC values in the training, validation, and test set were 0.876, 0.859, and 0.824, respectively. After logistic regression analysis, the AUC values of the radiomics-clinical nomogram were made up of four clinical independent risk factors and radiomics scores were 0.955, 0.922, and 0.935 for the training, validation, and test sets, respectively. The DeLong test between clinical model and radiomics-clinical nomogram shows P < 0.001. CONCLUSION: Multi-sequence and multi-regional MRI-based radiomics models could effectively assess the state of BCa muscular invasion. The radiomics-clinical nomogram is superior to clinical model for assessing BCa muscular invasion. LEVEL OF EVIDENCE: 4 TECHNICAL EFFICACY: Stage 2.

Polysaccharides of Brassica rapa L. attenuate tumor growth via shifting macrophages to M1-like phenotype.

Macrophages are the major tumor-infiltrating leukocytes, and tumor-associated macrophages (TAM) play a critical role in cancer-related inflammation since they show alternative polarization to M1 (tumor-inhibited macrophages) or M2 (tumor-promoted macrophages) phenotype. Brassica rapa L. (B. rapa) has been clinically proven to have anti-tumor and immunity-enhancing activity, and the polysaccharides of B. rapa (BRP) have been reported to have an immunoregulatory effect on macrophages. In this study, we focus on macrophage polarization to investigate the mechanism of anti-tumor response of BRP in vivo and in vitro. We found that BRP improved the expression of M1 markers, including iNOS, COX-2, HLA-DR, CD11b and M1-related cytokines. The expression of M2 markers Arg-1, CD206 and CD163 induced by IL-4 were inhibited by BRP treatment, resulting in the inhibition of tumor growth both in vivo and in co-culture experiments in vitro. The activation of STAT signaling pathway were significantly regulated by BRP, which are important signals in TAM polarization. Overall, the results indicated that BRP has anti-tumor effect through mediating macrophage polarization.

Unmixing the coupling influence from driving factors on vegetation changes considering spatio-temporal heterogeneity in mining areas: a case study in Xilinhot, Inner Mongolia, China.

Considering the spatio-temporal heterogeneity, this study resolved the coupling influence of a variety of driving factors on vegetation changes in mining areas and discovered the influencing characteristics of the respective driving factors, especially mining activities. First, the spatio-temporal characteristics of FVC (fractional vegetation cover) variation were analyzed in the Sheng-Li mining area. Second, the quantitative relationships among the natural factors (temperature, precipitation, and elevation), artificial factors (mining activities, urban activities), and FVC were constructed by GTWR (geographically and temporally weighted regression) to quantify the contribution of each factor to the change in FVC. Third, the influencing characteristics of the respective driving factors, especially mining activities, were analyzed and summarized. The results show that (1) the FVC change was mainly influenced by natural factors in the areas far from mines and towns and artificial factors in the areas close to mines and towns. (2) The contribution of mining activities to vegetation change (C-Mine) was spatially characterized by two features: (a) distance attenuation characteristics: C-Mine showed logarithmic decrement with distance; (b) directional heterogeneity: C-Mine varied significantly in different directions. In particular, there was a high C-Mine area located near multiple mining areas, and the range of this area shifted to include the mine with more production over time. Overall, unmixing the coupling influence from driving factors with spatio-temporal heterogeneity and achieving a quantitative description of the influencing characteristics in mining areas were the main contributions of this study. The quantification methods and results in this paper provide important support for decision-making on ecological protection and restoration in mining areas.

Response of transpiration to rain pulses for two tree species in a semiarid plantation.

Responses of transpiration (Ec) to rain pulses are presented for two semiarid tree species in a stand of Pinus tabulaeformis and Robinia pseudoacacia. Our objectives are to investigate (1) the environmental control over the stand transpiration after rainfall by analyzing the effect of vapor pressure deficit (VPD), soil water condition, and rainfall on the post-rainfall Ec development and recovery rate, and (2) the species responses to rain pulses and implications on vegetation coverage under a changing rainfall regime. Results showed that the sensitivity of canopy conductance (Gc) to VPD varied under different incident radiation and soil water conditions, and the two species exhibited the same hydraulic control (-dG c/dlnVPD to Gcref ratio) over transpiration. Strengthened physiological control and low sapwood area of the stand contributed to low Ec. VPD after rainfall significantly influenced the magnitude and time series of post-rainfall stand Ec. The fluctuation of post-rainfall VPD in comparison with the pre-rainfall influenced the Ec recovery. Further, the stand Ec was significantly related to monthly rainfall, but the recovery was independent of the rainfall event size. Ec enhanced with cumulative soil moisture change (ΔVWC) within each dry-wet cycle, yet still was limited in large rainfall months. The two species had different response patterns of post-rainfall Ec recovery. Ec recovery of P. tabulaeformis was influenced by the pre- and post-rainfall VPD differences and the duration of rainless interval. R. pseudoacacia showed a larger immediate post-rainfall Ec increase than P. tabulaeformis did. We, therefore, concluded that concentrated rainfall events do not trigger significant increase of transpiration unless large events penetrate the deep soil and the species differences of Ec in response to pulses of rain may shape the composition of semiarid woodlands under future rainfall regimes.

MRI radiomics for predicting poor disease-free survival in muscle invasive bladder cancer: the results of the retrospective cohort study.

OBJECTIVES: To develop an MRI radiomic nomogram capable of identifying muscle invasive bladder cancer (MIBC) patients with high-risk molecular characteristics related to poor 2-year disease-free survival (DFS). METHODS: We performed a retrospective analysis of DNA sequencing data, prognostic information, and radiomics features from 91 MIBC patients at stages T2-T4aN0M0 without history of immunotherapy. To identify risk stratification, we employed Cox regression based on TP53 mutation status and tumor mutational burden (TMB) level. Radiomics signatures were selected using the least absolute shrinkage and selection operator (LASSO) to construct a nomogram based on logistic regression for predicting the stratification in the training cohort. The predictive performance of the nomogram was assessed in the testing cohort using receiver operator curve (ROC), Hosmer-Lemeshow (HL) test, clinical impact curve (CIC), and decision curve analysis (DCA). RESULTS: Among 91 participants, the mean TMB value was 3.3 mut/Mb, with 60 participants having TP53 mutations. Patients with TP53 mutations and a below-average TMB value were identified as high risk and had a significantly poor 2-year DFS (hazard ratio = 4.36, 95% CI 1.82-10.44, P < 0.001). LASSO identified five radiomics signatures that correlated with the risk stratification. In the testing cohort, the nomogram achieved an area under the ROC curve of 0.909 (95% CI 0.789-0.991) and an accuracy of 0.889 (95% CI 0.708-0.977). CONCLUSION: The molecular risk stratification based on TP53 mutation status combined with TMB level is strongly associated with DFS in MIBC. Radiomics signatures can effectively predict this stratification and provide valuable information to clinical decision-making.

Non-Gaussian diffusion metrics with whole-tumor histogram analysis for bladder cancer diagnosis: muscle invasion and histological grade.

PURPOSE: To investigate the performance of histogram features of non-Gaussian diffusion metrics for diagnosing muscle invasion and histological grade in bladder cancer (BCa). METHODS: Patients were prospectively allocated to MR scanner1 (training cohort) or MR2 (testing cohort) for conventional diffusion-weighted imaging (DWIconv) and multi-b-value DWI. Metrics of continuous time random walk (CTRW), diffusion kurtosis imaging (DKI), fractional-order calculus (FROC), intravoxel incoherent motion (IVIM), and stretched exponential model (SEM) were simultaneously calculated using multi-b-value DWI. Whole-tumor histogram features were extracted from DWIconv and non-Gaussian diffusion metrics for logistic regression analysis to develop diffusion models diagnosing muscle invasion and histological grade. The models' performances were quantified by area under the receiver operating characteristic curve (AUC). RESULTS: MR1 included 267 pathologically-confirmed BCa patients (median age, 67 years [IQR, 46-82], 222 men) and MR2 included 83 (median age, 65 years [IQR, 31-82], 73 men). For discriminating muscle invasion, CTRW achieved the highest testing AUC of 0.915, higher than DWIconv's 0.805 (p = 0.014), and similar to the combined diffusion model's AUC of 0.885 (p = 0.076). For differentiating histological grade of non-muscle-invasion bladder cancer, IVIM outperformed a testing AUC of 0.897, higher than DWIconv's 0.694 (p = 0.020), and similar to the combined diffusion model's AUC of 0.917 (p = 0.650). In both tasks, DKI, FROC, and SEM failed to show diagnostic superiority over DWIconv (p > 0.05). CONCLUSION: CTRW and IVIM are two potential non-Gaussian diffusion models to improve the MRI application in assessing muscle invasion and histological grade of BCa, respectively. CRITICAL RELEVANCE STATEMENT: Our study validates non-Gaussian diffusion imaging as a reliable, non-invasive technique for early assessment of muscle invasion and histological grade in BCa, enhancing accuracy in diagnosis and improving MRI application in BCa diagnostic procedures. KEY POINTS: Muscular invasion largely determines bladder salvageability in bladder cancer patients. Evaluated non-Gaussian diffusion metrics surpassed DWIconv in BCa muscle invasion and histological grade diagnosis. Non-Gaussian diffusion imaging improved MRI application in preoperative diagnosis of BCa.

The Synergistic Effect of Topographic Factors and Vegetation Indices on the Underground Coal Mine Utilizing Unmanned Aerial Vehicle Remote Sensing.

Understanding the synergistic effect between topography and vegetation in the underground coal mine is of great significance for the ecological restoration and sustainable development of mining areas. This paper took advantage of unmanned aerial vehicle (UAV) remote sensing to obtain high-precision topographic factors (i.e., digital elevation model (DEM), slope, and aspect) in the Shangwan Coal Mine. Then, a normalized difference vegetation index (NDVI) was calculated utilizing Landsat images from 2017 to 2021, and the NDVI with the same spatial resolution as the slope and aspect was acquired by down-sampling. Finally, the synergistic effect of topography and vegetation in the underground mining area was revealed by dividing the topography obtained using high-precision data into 21 types. The results show that: (1) the vegetation cover was dominated by "slightly low-VC", "medium-VC", and "slightly high-VC" in the study area, and there was a positive correlation between the slope and NDVI when the slope was more than 5°. (2) When the slope was slight, the aspect had less influence on the vegetation growth. When the slope was larger, the influence of the aspect increased in the study area. (3) "Rapidly steep-semi-sunny slope" was the most suitable combination for the vegetation growth in the study area. This paper revealed the relationship between the topography and vegetation. In addition, it provided a scientific and effective foundation for decision-making of ecological restoration in the underground coal mine.

Three-dimensional spatial interpolation for chlorophyll-a and its application in the Bohai Sea.

Assessing the health of coastal ecosystems is crucial for maintaining ecological balance. One significant indicator of water eutrophication is the distribution of chlorophyll-a (Chl-a), which makes obtaining a complete three-dimensional spatial distribution of Chl-a essential for assessment. This study utilized the linear radial basis function (RBF-Linear) method to obtain a comprehensive and reasonable spatial distribution of Chl-a. The method was applied to obtain the three-dimensional spatial field of Chl-a concentration in the Bohai Sea in March, May, August, and October from 2016 to 2018. The distribution pattern of Chl-a concentration in the Bohai Sea displayed characteristic spatial and temporal variations. Spatially, high Chl-a concentration was most concentrated in coastal waters, particularly in estuaries and mariculture areas. Temporally, there were two peaks in March and August. The total Chl-a and areas with high Chl-a concentration in four sub-regions of the Bohai Sea were also calculated to enable a comprehensive assessment of the marine ecological environment. By analyzing the temporal and spatial variation of Chl-a in the Bohai Sea and evaluating the marine ecological environment, we confirmed the feasibility and rationality of RBF-Linear. Our findings have the potential to contribute to improve the accuracy of ecological models and assessment of the satellite products.

Modeling impacts of mining activity-induced landscape change on local climate.

As a major energy source, coal has been mined on an increasingly larger scale as the social economy has continuously developed, resulting in drastic land type changes. These changes in turn cause changes in the local climate and affect the local ecological environment. Therefore, for coal cities, mining activities are an important factor influencing the local climate, and clarifying the impact of mining activities on the ecological environment is important for guiding regional development. In this paper, the impact of land use/cover changes (LUCCs) on local temperature in the spring and summer seasons from 1980 to 2018 was simulated using the Weather Research and Forecasting (WRF) model with Xilinhot city as the study area, and the regional distribution of local surface energy was analyzed in conjunction with the ground-air energy transfer process. The results show that the grassland area in Xilinhot remained above 85% from 1980 to 2018, so mining activities had a small impact on the average temperature of the whole region. However, in the mining area, the warming effect caused by mining activities was more obvious, with an average temperature increase of 0.822 K. Among other land transformation types, the conversion to water bodies had a very obvious cooling effect, lowering the temperature by an average of 2.405 K. By comparing the latent heat flux (LH), sensible heat flux (SH), and ground heat flux (GRD) under different land use types, it was found that in 2018, the LH decreased by 0.487 W/m2, the SH decreased by 0.616 W/m2, and the GRD decreased by 0.753 W/m2. The conversion to built-up urban land caused a significant decrease in the LH in the corresponding area, allowing more energy to be used to increase SH values, which resulted in significantly higher urban temperatures than in other areas.

A Method for Identifying the Spatial Range of Mining Disturbance Based on Contribution Quantification and Significance Test.

Identifying the spatial range of mining disturbance on vegetation is of significant importance for the plan of environmental rehabilitation in mining areas. This paper proposes a method to identify the spatial range of mining disturbance (SRMD). First, a non-linear and quantitative relationship between driving factors and fractional vegetation cover (FVC) was constructed by geographically weighted artificial neural network (GWANN). The driving factors include precipitation, temperature, topography, urban activities, and mining activities. Second, the contribution of mining activities (Wmine) to FVC was quantified using the differential method. Third, the virtual contribution of mining activities (V-Wmine) to FVC during the period without mining activity was calculated, which was taken as the noise in the contribution of mining activities. Finally, the SRMD in 2020 was identified by the significance test based on the Wmine and noise. The results show that: (1) the mean RMSE and MRE for the 11 years of the GWANN in the whole study area are 0.0526 and 0.1029, which illustrates the successful construction of the relationship between driving factors and FVC; (2) the noise in the contribution of mining activities obeys normal distribution, and the critical value is 0.085 for the significance test; (3) most of the SRMD are inside the 3 km buffer with an average disturbance distance of 2.25 km for the whole SRMD, and significant directional heterogeneity is possessed by the SRMD. In conclusion, the usability of the proposed method for identifying SRMD has been demonstrated, with the advantages of elimination of coupling impact, spatial continuity, and threshold stability. This study can serve as an early environmental warning by identifying SRMD and also provide scientific data for developing plans of environmental rehabilitation in mining areas.

Monitoring of Vegetation Disturbance and Restoration at the Dumping Sites of the Baorixile Open-Pit Mine Based on the LandTrendr Algorithm.

Overstocked dumping sites associated with open-pit coal mining occupy original vegetation areas and cause damage to the environment. The monitoring of vegetation disturbance and restoration at dumping sites is important for the accurate planning of ecological restoration in mining areas. This paper aimed to monitor and assess vegetation disturbance and restoration in the dumping sites of the Baorixile open-pit mine using the LandTrendr algorithm and remote sensing images. Firstly, based on the temporal datasets of Landsat from 1990 to 2021, the boundaries of the dumping sites in the Baorixile open-pit mine in Hulunbuir city were extracted. Secondly, the LandTrendr algorithm was used to identify the initial time and duration of vegetation disturbance and restoration, while the Normalized Difference Vegetation Index (NDVI) was used as the input parameter for the LandTrendr algorithm. Thirdly, the vegetation restoration effect at the dumping sites was monitored and analyzed from both temporal and spatial perspectives. The results showed that the dumping sites of the Baorixile open-pit mine were disturbed sharply by the mining activities. The North dumping site, the South dumping site, and the East dumping site (hereinafter referred to as the North site, the South site, and the East site) were established in 1999, 2006, and 2010, respectively. The restored areas were mainly concentrated in the South site, the East site, and the northwest of the North site. The average restoration intensity in the North site, South site, and East site was 0.515, 0.489, and 0.451, respectively, and the average disturbance intensity was 0.371, 0.398, and 0.320, respectively. The average restoration intensity in the three dumping sites was greater than the average disturbance intensity. This study demonstrates that the combination of temporal remote sensing images and the LandTrendr algorithm can follow the vegetation restoration process of an open-pit mine clearly and can be used to monitor the progress and quality of ecological restoration projects such as vegetation restoration in mining areas. It provides important data and support for accurate ecological restoration in mining areas.

Immunomodulatory activity of polysaccharides from Brassica rapa by activating Akt/NF-κB signaling.

Objective: To investigate the immunomodulatory activity of polysaccharides from the roots of Brassica rapa. Methods: The crude polysaccharide from roots of B. rapa (BRP) was extracted and purified to further investigate the active fraction of BRT for inducing macrophage phagocytosis. Results: Effects on RAW264.7 cells demonstrated that BRP behaved better phagocytic capacity and had potent immunomodulatory activity, including increasing production of nitric oxide (NO), tumor necrosis factor α (TNFα) and upregulating mRNA levels of inducible NO synthase (iNOS) and TNFα. Furthermore, modulation of macrophage by BRP was indicated to be mediated via the activation of Akt and nuclear factor-kappa B (NF-κB). Conclusion: The beneficial effects of BRP could be used as an immunotherapeutic adjuvant in treatment of inflammatory diseases.