Clear cell renal cell carcinoma (ccRCC) is a malignant tumor, originating from the renal epithelium, and accounts for ~85% of RCC cases. The present study aimed to validate the efficacy of an MRI deep learning (DL) model to preoperatively predict the pathological grading of ccRCC. Therefore, a DL algorithm was constructed and trained using diffusion weighted imaging (DWI) and diffusion kurtosis imaging (DKI) sequence images. Subsequently, the apparent diffusion coefficient maps from DWI, as well as axial kurtosis (Ka), fractional anisotropy, radial kurtosis (Kr), mean kurtosis (MK) and mean diffusivity maps from DKI were calculated. The VGG-16 model was selected as the backbone architecture to validate the DL model. Based on the inclusion and exclusion criteria, a total of 79 patients with ccRCC, including 40 low- and 39 high-grade cases, were prospectively evaluated. Among the different image parameters, mean MK achieved the highest accuracy, with a precision of 81.48%, F1-score of 76.04%, recall of 74.08% and accuracy of 76.04%, followed by Kr, with values of 75.51, 75.36, 75.42 and 75.36%, respectively. Ka had precision, recall, F1-score and accuracy values of 81.39, 71.81, 68.31 and 71.81%, respectively. Overall, the results of the current study revealed that the established DL model, as a non-invasive algorithm based on MRI sequences, could accurately predict the pathological grading of ccRCC. Therefore, these findings highlighted the potential of this method to guide individualized treatment decisions for patients with ccRCC.

Patent foramen ovale (PFO) patients may experience states of hypoxia and hypoperfusion, which may increase the burden of enlarged perivascular spaces (EPVS). However, to our knowledge, no data are available regarding EPVS in PFO patients. This study sought to investigate if patients with PFO exhibit a heightened burden of EPVS and to identify the mediating factors between PFO and EPVS. A total of 108 consecutive PFO patients (PFO group) and 110 healthy controls (HC group) from January 2022 to February 2024 were enrolled. The differences in centrum semiovale EPVS (CSO-EPVS) and basal ganglia EPVS (BG-EPVS) scores between PFO and HC groups were compared. The correlations among PFO diameters, laboratory indexes, and EPVS burdens were analyzed. The relationships among them were obtained using mediation analysis. Mean age of PFO and HC group was 47.68 ± 14.47 and 48.14 ± 12.84 years. The CSO-EPVS and BG-EPVS scores were higher in PFO group than HC group (P < 0.001). The CSO-EPVS and BG-EPVS scores for PFO group were concentrated in the ranges 1–3 and 1–2 points, while for HC group were concentrated in the range 0–1 points. A positive correlation among PFO diameters and CSO-EPVS score (r = 0.62, P < 0.001), BG-EPVS score (r = 0.63, P < 0.001), and homocysteine (HCY)(r = 0.21, P = 0.03) was observed. Mediation analysis indicated that higher HCY significantly mediated the relationship between PFO diameter and BG-EPVS burden in PFO patients (P < 0.05). These findings revealed the presence of glymphatic dysfunction in patients with PFO. HCY may mediate the impact of PFO diameter on glymphatic function.

Background: An accurate and noninvasive method to determine the preoperative clear-cell renal cell carcinoma (ccRCC) pathological grade is of great significance for surgical program selection and prognosis assessment. Previous studies have shown that diffusion-weighted imaging (DWI) has moderate value in grading ccRCC. But DWI cannot reflect the diffusion of tissue accurately because it is calculated using a monoexponential model. Intravoxel incoherent motion (IVIM) is the biexponential model of DWI. Only a few studies have examined the value of IVIM in grading ccRCC yet with inconsistent results. This study aimed to compare the value of DWI and IVIM in grading ccRCC. Methods: In this study, 96 patients with pathologically confirmed ccRCC were evaluated by DWI and IVIM on a 3-T scanner. According to the World Health Organization/International Society of Urological Pathology (WHO/ISUP) classification system, these patients were divided into two groups: low-grade (grade I and II) and high-grade (grade III and IV) ccRCC. The apparent diffusion coefficient (ADC), true diffusion coefficient (D), pseudodiffusion coefficient (D*), and perfusion fraction of pseudodiffusion (f) values were calculated. The Mann-Whitney test, receiver-operating characteristic (ROC) analysis, and the Delong test were used for statistical evaluations. Results: (I) According to the WHO/ISUP nuclear grading system, 96 patients were divided into low-grade (grade I and II, 45 patients) and high-grade (grade III and IV, 51 patients) groups. (II) Compared with patients of low-grade ccRCC, the ADC and D values of those with high-grade ccRCC decreased while the D* and f values increased (P<0.05). (III) The cutoff value of the ADC, D, D*, and f in distinguishing low-grade from high-grade ccRCC was 1.50x10(-3) mm(2)/s, 1.12x10(-3) mm(2)/s, and 33.19x10(-3) mm(2)/s, 0.31, respectively; the area under the curve (AUC) for the ADC, D, D*, and f values was 0.871, 0.942, 0.621, and 0.894, respectively, with the AUC of the D value being the highest; the sensitivity for the ADC, D, D*, and f values was 94.12%, 92.16%, 47.06%, and 92.16%, respectively; and the specificity for the ADC, D, D*, and f values was 66.67%, 91.11%, 77.78%, and 73.33%, respectively. (IV) Based on the Delong test, AUC(D) was significantly higher than AUC(ADC) (P=0.02) and AUC(D*) (P<0.001), but there was no significant difference between AUC(D) and AUC (f) (P=0.18). Conclusions: Compared with the monoexponential model DWI, the biexponential model IVIM was more accurate in grading ccRCC.

Background: The prognosis of hepatocellular carcinoma (HCC) is difficult to predict and carries high mortality. This study utilized radiomic techniques with clinical examinations to assess recurrence in HCC. Purpose: To develop a Cox nomogram to assess the risk of postoperative recurrence in HCC using radiomic features of three volumes of interest (VOIs) in preoperative dynamic contrast-enhanced MRI (DCE-MRI), along with clinical findings. Study Type: Retrospective. Subjects: 249 patients with pathologically proven HCCs undergoing surgical resection at three institutions were selected. Field Strength/Sequence: Fat saturated T2-weighted, Fat saturated T1-weighted, and DCE-MRI performed at 1.5 T and 3.0 T. Assessment: Three VOIs were generated; the tumor VOI corresponds to the area from the tumor core to the outer perimeter of the tumor, the tumor +10 mm VOI represents the area from the tumor perimeter to 10 mm distal to the tumor in all directions, finally, the background liver parenchyma VOI represents the hepatic tissue outside the tumor. Three models were generated. The total radiomic model combined information from the three listed VOI's above. The clinical-radiological model combines physical examination findings with imaging characteristics such as tumor size, margin features, and metastasis. The combined radiomic model includes features from both models listed above and showed the highest reliability for assessing 24-month survival for HCC. Statistical Tests: The least absolute shrinkage and selection operator (LASSO) Cox regression, univariable, and multivariable Cox regression, Kmeans clustering, and Kaplan-Meier analysis. The discrimination performance of each model was quantified by the C-index. A P value <0.05 was considered statistically significant. Results: The combined radiomic model, which included features from the radiomic VOI's and clinical imaging provided the highest performance (C-index: training cohort = 0.893, test cohort = 0.851, external cohort = 0.797) in assessing the survival of HCC. Conclusion: The combined radiomic model provides superior ability to discern the possibility of recurrence-free survival in HCC over the total radiomic and the clinical-radiological models.

Background: Under the background that diffusion kurtosis imaging (DKI) has become a research hotspot of central nervous system diseases, there are no studies with large sample size evaluating the value of DKI in diagnosing Parkinson's disease (PD). Moreover, the diagnostic efficacy of DKI in PD is not consistent. Therefore, the main purpose of this study is to use the method of meta-analysis, to summarize and evaluate the diagnostic efficacy of DKI in the identification of PD, and to explore the value of its clinical application. Methods: We use PICOS principles for project design. The included patients were PD patients, and the control group were healthy volunteers. We hope to use DKI to make a differential diagnosis between the two, and this study is a diagnostic test. We performed a literature search of English (PubMed, Embase, Cochrane Library, etc.) and Chinese (China knowledge Network, Wanfang Data Knowledge Service platform, China Science and Technology Journal Database, China Biomedical Literature Service system) databases for related literatures on the efficacy of DKI in the differential diagnosis of PD published before March 29, 2022. We used Revman 5.3 software to assess the quality of the literature, Meta-Disc 1.4 software for summarizing sensitivity (Sen), specificity (Spe), diagnostic odds ratios, and heterogeneity tests, and for subgrouping, and Stata 16.0 software for publication bias analysis. Results: Fourteen articles were included through the literature search. The 14 studies included 535 patients with PD and 486 patients without PD. Most of the included literature had good clinical applicability and relatively low risk. By merging statistics, the results obtained were as follows: Sen =0.78 [95% confidence interval (CI): 0.74-0.81], Spe =0.83 (95% CI: 0.79-0.86), and the area under the summary receiver operating characteristic (SROC) curve was 0.8870. Discussion: The results of the meta- analysis showed that magnetic resonance DKI has comparable diagnostic accuracy in the diagnosis of PD. However, this study also has limitations, and the use of different diagnostic gold standards in the included studies may have some impact on the case selection in the study.

甾体激素是一类强效的内分泌干扰物,早先的研究重点在于最先发现的雌激素,而实际上糖皮质激素(Glucocorticoids,GCs)的使用量远大于雌激素和雄激素,并且GCs对COVID-19确诊病人的治疗效果得到广泛肯定.在新冠疫情全球爆发的大背景下,GCs的使用量还可能持续增加.因此,了解GCs在水环境中的源和汇,掌握其在环境中的赋存归趋和生态毒理效应,对评估和控制GCs的潜在风险具有重要意义.文章对此进行文献调研和总结,为进一步开展GCs的环境行为研究提供参考.GCs主要来源于制药厂、医院、养殖场以及污水处理厂,其在多个河流湖泊中检出率为50％—100％,水相质量浓度最高可接近500 ng·L?1,在沉积物中为1.10—5.85μg·kg?1.GCs的亲水性强于其他甾体激素,其在水环境的迁移性可能更强,因此在地下水中也有检出.在环境赋存和归趋的研究中,未来可重点关注常见GCs的前体物及代谢产物、悬浮颗粒和有机质等对GCs环境行为的影响,以及GCs与其他类污染物在不同环境过程中的相互作用.在毒理研究方面,针对GCs对人体健康以及对鱼类影响的研究较多,但对其他营养级生物以及食物链和食物网影响的研究则有待进一步开展,这样才能为更科学地评价GCs的生态风险提供理论支撑.

Phthalic acid esters (PAEs) are endocrine-disrupting compounds that are ubiquitous in surface water. However, early studies on PAEs only focused on six species on the priority contaminant list, and the seasonal variation in the PAE distribution in Taihu Lake, China is unclear. The present study investigated the occurrence, spatial distribution, and ecological risks of 16 PAEs in Taihu Lake during the dry, normal, and wet seasons. The results showed that dibutyl phthalate, diethylhexyl phthalate (DEHP), and diisobutyl phthalate (DIBP) were the major species detected in the surface water of Taihu Lake. The summed concentration of the six priority PAEs accounted for less than 50% of the total, indicating that the contamination of the other PAE congeners was non-negligible. Significant seasonal effects were observed that the total PAE concentration was higher in the wet season than in the dry season, and there were significant positive correlations between the total PAE concentration and rainfall, the water reserve, and the water level. In the dry season, a relatively high PAE level was detected in the area close to the inflow river estuary and the tourist island in the lake. The concentrations of PAEs in the lakeshore area were higher than those in the lake center in the normal season, and were generally high in the wet season. DEHP posed high risks for fish regardless of the season, while butyl benzyl phthalate, DIBP, dihexyl phthalate, and diphenyl phthalate also showed high risks in the normal and wet seasons. These results suggest that the contamination and risks of congeners other than the priority PAEs are also of necessary concern, and seasonal variation should be considered for a comprehensive understanding of PAE contamination in surface water.

In December 2019,the novel 2019 coronavirus disease （COVID-19） emerged in Wuhan and spread all over the country.The Zibo Central Hospital had set up a febrile clinic and isolation ward for confirmed and suspected patients since January 23,2020.Suspected patients were hospitalized immediately to the isolation ward.Every healthcare staff was authorized to undergo low-dose computed tomography （LDCT） of the chest free of charge before and after their assignment in the isolation ward.

The power system is affected by different levels of transient shock caused by different switching angle when AC filter switching on. The shock causes frequent action and aging of lightning arrester. In this article, the causes of frequent action of lightning arrester in Nuozhadu DC project are analyzed by means of power systems computer aided design simulation. The overvoltage, current, and energy of AC filter switching on are also analyzed. The critical angle of the arrester action of AC filters is discussed. The results show that AC filter switching on can affect this group and other groups. When the closing phase angle reaches 12°, the arrester in this group lightnings. When the closing phase angle reaches 18, the arresters in other groups lightning. Finally, the influence of the three phases and the impact which varies with power are also discussed.

Purpose: To evaluate the role of diffusion kurtosis imaging (DKI1) in the characterization of clear cell renal cell carcinoma (ccRCC(2)) compared with standard diffusion-weighted imaging (DWI3). Methods: 89 patients with histologically proven ccRCC were evaluated by DKI and DWI on a 3-T scanner. All ccRCCs were classified as grade 1-4 according to the Fuhrman classification system. The apparent diffusion coefficient (ADC(4)), fractional anisotropy (FA(5)), mean diffusivity (MD6), mean kurtosis (MK7), axial kurtosis (Ka(8)) and radial kurtosis (Kr-9) values were recorded. The differences in DWI and DKI parameters were evaluated by independent-sample t test and a receiver operating characteristic (ROC10) analysis was performed. The DeLong test was performed to compare the ROCs. Results: Compared to normal renal parenchyma, ADC and MD values of ccRCC decreased and MK, Ka, and Kr values increased (p < 0.05). ADC and MD values of ccRCC decreased with the increase in pathological grade, while MK, Ka, and Kr values were increased (p < 0.05). ADC could discriminate G1 vs G3, G1 vs G4, G2 vs G3, G2 vs G4, and G3 vs G4 (p < 0.05) except for G1 vs G2 (p > 0.05). Ka and Kr could discriminate G1 vs G2, G1 vs G3, G1 vs G4, G2 vs G4, and G3 vs G4 (p < 0.05) except for G2 vs G3 (p > 0.05). MD and MK could discriminate G1 vs G2, G1 vs G3, G1 vs G4, G2 vs G3, G2 vs G4, and G3 vs G4 (p < 0.05). The AUC of MK was the highest. The DeLong test showed that there were significant differences regarding ROCs between ADC/MK, ADC/Ka, ADC/Kr in grading G1/G2, and ADC/MK, MK/Ka in grading G3/G4 (p < 0.05). Conclusion: DKI was superior compared to the mono-exponential mode of DWI in grading ccRCC.

Very limited studies have evaluated the impact of rainfall on the fate of endocrine-disrupting micropollutants in lacustrine systems. This yearlong study investigated monthly fluctuation of bisphenol A (BPA) and 4-nonylphenol (NP) concentrations in both water and sediment samples from Taihu Lake and evaluated the impact of rainfall on their spatiotemporal distribution and partition trends. Results showed that BPA concentration in water was negatively correlated to rainfall while NP concentrations in both phases were positively related to rainfall. The spatial distribution of NP in the lake water was season specific with the lakeshore area higher than the central area during the wet season and a reversed pattern during the dry season. The spatial distributions of sediment-associated NP and BPA in both phases were not significantly different among seasons. Contrary partition tendencies were observed for BPA and NP that BPA tended to desorb from sediment and NP tended to be adsorbed during the wet season while the trends were reversed during the dry season. This study suggests that rainfall could affect the occurrence, distribution and environmental fate of micropollutants and should be considered in the monitoring program and risk assessment.

Objective: To explore the role of diffusional kurtosis imaging (DKI) in evaluating the efficacy of transcatheter arterial chemoembolization (TACE) in patients with liver cancer. Materials and Methods: A total of 54 patients with primary liver cancer underwent TACE were selected as the study subjects. Magnetic resonance imaging and DKI scans were carried out before and after TACE, and the relevant parameters were analyzed. Results: Compared with those before TACE, the values of radial diffusivity (Dr), axial diffusivity (Da), and mean diffusivity (MD) of tumor tissues in the patients after TACE were significantly increased, whereas the values of axial kurtosis (Ka), fractional anisotropy of kurtosis (FAk), hepatic blood volume (HBV), hepatic blood flow (HBF), and hepatic artery perfusion (HAP) were notably decreased (p < 0.05). There were no significant changes regarding FA, radial kurtosis (Kr), mean kurtosis (MK), hepatic arterial fracture (HAF), permeability-surface area product (PS), mean transit time (MTT), and portal vein perfusion (PVP) (p > 0.05). The differences in apparent diffusion coefficients (ADCs) of different liver cancer tissues in patients under different b values after operation were statistically significant, and the ADC values of liver cancer tissues were evidently higher than those of other tumor tissues (p < 0.05). Conclusion: DKI is characterized with advantages such as fastness, simpleness, high resolution, and impregnability of the density of lipiodol. It can not only directly reflect the changes in blood perfusion at the lesion but also accurately and efficiently evaluate the remnants, necrosis, and recurrence of tumor tissues based on changes in ADC under different b values. It provides certain clinical assistance for the evaluation of the efficacy before and after TACE.

Various classifiers have sprung up in recent years. This paper introduces a new intelligent algorithm for text categorization based on improved random forest algorithm. This improvement greatly increases the performance of the original random forest algorithm. The classifier was tested on the reuters-21578 data set and its classification effect was obtained. The classifier is compared with traditional principle similar classifier CART, REPTree and J48. The experimental results show that the classification accuracy of text classifier based on improved random forest algorithm is higher, and it is faster.

BackgroundThe development of a noninvasive, objective, and accurate method to assess peripheral nerve disorders in Guillain–Barre syndrome (GBS) is of clinical significance. Diffusion tensor imaging (DTI) has been used to evaluate some peripheral nerve disorders.PurposeTo investigate the feasibility of DTI in evaluating the peripheral nerve disorders in patients with GBS.Study TypeCase control.SubjectsTwenty GBS patients and 16 healthy volunteers.Field Strength/Sequence3.0T, T1WI‐SE, T2WI‐SPAIR, DTI; electrophysiology.AssessmentMRI data were analyzed by two radiologists blindly and independently. Fractional anisotropy (FA), apparent diffusion coefficient (ADC), axial diffusion coefficient (AD), and radial diffusion coefficient (RD) values of tibial nerve (TN) and common peroneal nerve (CPN) were recorded. Motor nerve conduction velocity (MCV) and motor nerve conduction amplitude of TN and CPN were recorded.Statistical TestsIntraclass correlation coefficient (ICC), t‐test, receiver‐operating characteristic (ROC), and area under the curve (AUC) analysis, Pearson correlation coefficient.ResultsThe FA and AD values of TN and CPN in the GBS group were significantly lower and the ADC and RD values were higher than those in the controls (P <0.05). The AUC of the FA values (0.970 for TN and 0.927 for CPN) were higher than that of the ADC, AD, and RD values. FA and AD values were positively correlated and ADC, RD values were negatively correlated with MCV and motor nerve conduction amplitude, respectively (P <0.05). The correlations between FA value and electrophysiology parameters were the highest.Data ConclusionDTI quantitative parameters could evaluate the disorders of peripheral nerves in patients with GBS. A moderate correlation was observed between DTI and electrophysiology parameters.Level of Evidence: 3Technical Efficacy: Stage 1J. Magn. Reson. Imaging 2019;49:1356–1364.

With the development of modern communication technology and the improvement of the overall cultural level of the society, users' personalized information demands make it difficult to maintain the traditional information delivery mode of university libraries. This paper analyzes the practice and application of personalized service in Chinese universities and colleges, and finds that there are many deficiencies. This paper puts forward the corresponding countermeasure to realize the individualized service of university library. Only continuous improvement of library services can better satisfy the readers' personalized needs and provide readers with better services.

Objective The aim of the study was to investigate the molecular subtypes of breast cancer based on the texture features derived from magnetic resonance images (MRIs). Methods One hundred seven patients with preoperative confirmed breast cancer were recruited. One hundred eight breast lesions were divided into 4 subtypes according to the status of estrogen receptor, progesterone receptor, human epidermal growth factor receptor type 2, and Ki67. Fisher discriminant analysis was performed on the texture features that extracted from the enhanced high-resolution T1-weighted images and diffusion weighted images to establish the classification model of molecular subtypes. Results The differentiation accuracies of Fisher discriminant analysis on the enhanced high-resolution T1-weighted images were 82.8% and 86.4% for 1.5T and 3.0T imaging. Fisher discriminant analysis on diffusion weighted imaging texture features were achieved with a classification ability of 73.4% and 88.6%. The combined discriminant results for 2 kinds magnetic resonance images were 95.0%, 97.7% in 1.5T and 3.0T imaging, respectively. Conclusions The fine results indicated a promising approach to predict the molecular subtypes of breast cancer.

With the rapid development of computer technology, e-books have emerged. Compared with traditional paper books, e-books have the advantages of fast update, short publication cycle and rich content. The library quickly accepted this new thing and developed into the main force of the electronic book consumer market. However, the utilization ratio of electronic books does not match with the money invested in each year, and readers always feel the lack of e-books. This paper discusses the bottleneck and countermeasures of the development and application of electronic books in Chinese university libraries, and hopes to make a contribution to the development of electronic books.

Various ensemble classification methods have been proposed in recent years. These methods have been proven to improve classification accuracy considerably. One of the most widely used ensemble methods is Random Forests, an ensemble of CART, it uses bagging or bootstrap aggregating. In the paper, the use of the Random Forests classifier for text classification is explored. We compare the accuracy of the Random Forest classifier to other pre-existing and freely available methods on Reuters-21578, the standard text test collection. The results showed that the model can be applied to text classification; The text classification model based on random forest had the best effect, compared with the results of a text classification model based on CART, REPTree and J48 and F1-Measure reached 0.777; The text classification model based on random forest is convenient, intuitive and effective, and the evaluation results are reliable. It can provide a new idea for the research of text classification.

以粉煤灰替代活性炭,用废铁屑及具有催化性能的稀土Gd作为微电解材料处理有毒有害苯胺废水,探究Gd对处理苯胺废水的影响.采用单因素法优化与确定了本方法处理苯胺废水的有关影响因素,采用正交实验法考察了影响因素的主次顺序及优化组合条件.结果表明,影响因素的主次顺序为pH＞Gd投加量＞反应时间＞粉煤灰铁屑质量比,优化组合条件:pH为3.5,质量浓度3.0 g/L的Gd溶液的投加量16 mL,反应时间1.5 h,粉煤灰、铁屑质量比为1∶2,在此条件下苯胺降解率为85.7％,Gd使苯胺的降解率提高了16.4个百分点.