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In this study, we evaluated the association between the PPAT volume and the prognosis of PCa patients after LRP. We retrospectively analysed data of 189 PCa patients who underwent LRP in Beijing Chaoyang Hospital. Volumes of PPAT and prostate were measured by magnetic resonance imaging (MRI), and normalized PPAT volume was computed (PPAT volume divided by prostate volume). Patients were then stratified into the high-PPAT group (n = 95) and low-PPAT group (n = 94) by the median of normalized PPAT volume (73%). The high-PPAT group had significantly higher Gleason score (total score 8 or more, 39.0% vs. 4.3%, p < 0.001) and pathological stage (stage T3b, 28.4% vs. 13.8%, p = 0.048). No significant correlation between normalized PPAT volume and body mass index (ρ = −0.012, p = 0.872) was observed. Kaplan-Meier curve analysis showed the high-PPAT group had significantly shorter biochemical recurrence (BCR) interval (median progression-free survival time 15.9 months vs. 32.7 months, p = 0.001). Univiarate and multivariate Cox regression analyses showed high normalized PPAT volume (>73%) (hazard ratio 1.787 [1.075–3.156], p = 0.002) were independent risk factors for BCR post-operatively. In conclusion, MRI-measured PPAT volume is of significant prognostic value for PCa patients undergoing LRP. [ABSTRACT FROM AUTHOR]

Firms organize tournaments on online crowdsourcing platforms to outsource complex business problems to external solvers. Participants on these platforms often self-organize into ad-hoc virtual teams to compete in such tournaments. Social dominance-based faultlines, which originate from the alignment of members based on IT-enabled social dominance attributes (e.g., rank and tier), have emerged as a novel type of faultline in crowdsourcing teams. Building on the Categorization-Elaboration Model (CEM), we investigate the contingent effects of team ability and team effort on the relationship between social dominance-based faultlines and team performance in crowdsourcing tournaments. We collected data of 265 virtual teams from Kaggle.com. We discovered that IT-enabled social dominance-based faultlines positively influence the performance of teams with low ability and high effort, whereas the effect becomes negative for teams with high ability and low effort. Our study yields theoretical implications by advancing a novel type of social dominance-based faultline and extending the CEM with two contingent factors (i.e., team effort and team ability) pertinent to team performance on crowdsourcing tournaments. We also offer practical guidelines for team formation in crowdsourcing tournaments and for the design of crowdsourcing platforms. [ABSTRACT FROM AUTHOR]

The study presented here aimed to establish a predictive model for heart failure (HF) and all-cause mortality in peritoneal dialysis (PD) patients with machine learning (ML) algorithm. We retrospectively included 1006 patients who initiated PD from 2010 to 2016. XGBoost, random forest (RF), and AdaBoost were used to train models for assessing risk for 1-year and 5-year HF hospitalization and mortality. The performance was validated using fivefold cross-validation. The optimal ML algorithm was used to construct the models to predictive the risk of the HF and all-cause mortality. The prediction performance of ML methods and Cox regression was compared. Over a median follow-up of 49 months. Two hundred and ninety-eight patients developed HF required hospitalization; 199 patients died during the follow-up. The RF model (AUC = 0.853) was the best performing model for predicting HF, and the XGBoost model (AUC = 0.871) was the best model for predicting mortality. Baseline moderate or severe renal disease, systolic blood pressure (SBP), body mass index (BMI), age, Charlson Comorbidity Index (CCI) score were strongly associated with HF hospitalization, whereas age, CCI score, creatinine, age, high-density lipoprotein cholesterol (HDL-C), total cholesterol, baseline estimated glomerular filtration rate (eGFR) were the most significant predictors of mortality. For all the above endpoints, the ML models demonstrated better discrimination than Cox regression. We developed and validated a novel method to predict the risk factors of HF and all-cause mortality that integrates readily available clinical, laboratory, and electrocardiographic variables to predict the risk of HF among PD patients. [ABSTRACT FROM AUTHOR]

In this study, we retrospectively evaluated the data of 901 men undergoing ultrasonography-guided systematic prostate biopsy between March 2013 and May 2022. Adipose features, including periprostatic adipose tissue (PPAT) thickness and subcutaneous fat thickness, were measured using MRI before biopsy. Prediction models of all PCa and clinically significant PCa (csPCa) (Gleason score higher than 6) were established based on variables selected by multivariate logistic regression and prediction nomograms were constructed. Patients with PCa had higher PPAT thickness (4.64 [3.65–5.86] vs. 3.54 [2.49–4.51] mm, p < 0.001) and subcutaneous fat thickness (29.19 [23.05–35.95] vs. 27.90 [21.43–33.93] mm, p = 0.013) than those without PCa. Patients with csPCa had higher PPAT thickness (4.78 [3.80–5.88] vs. 4.52 [3.80–5.63] mm, p = 0.041) than those with non-csPCa. Adding adipose features to the prediction models significantly increased the area under the receiver operating characteristics curve for the prediction of all PCa (0.850 vs. 0.819, p < 0.001) and csPCa (0.827 vs. 0.798, p < 0.001). Based on MRI-measured adipose features and clinical parameters, we established two nomograms that were simple to use and could improve patient selection for prostate biopsy in Chinese population. [ABSTRACT FROM AUTHOR]

A self-embedding watermarking algorithm based on a reference sharing mechanism that has recovery ability under high tampering rates is proposed in this paper. In existing methods, the image recovery ability is often limited under an increasing tampering rate. The proposed method overcomes this limitation by seeking an approximate solution for each character-bit group tampered with. Moreover, the priority assignment of such groups can enhance the accuracy of tampering recovery. Based on this, by using the method proposed in this paper, recovered images always maintain excellent visual quality even at relatively high tampering rates. The experimental results demonstrate the efficacy of the proposed method. [ABSTRACT FROM AUTHOR]

Image hashing is a technique that represents an image as a short unidirectional sequence. In this study, we propose a robust color image hashing technique based on the quaternionic local ranking binary pattern (QLRBP). First, the values of the RGB color channels are expressed as a pure quaternion, and the texture image is generated using the phase difference of the Clifford translation quaternion as the source for local binary pattern (LBP) comparison data. Next, mean pooling is used to reduce the dimensionality of the image texture. For security, the pixels of the dimension-reduced image are randomly selected, and each pixel is quantized to obtain the final image hash. Experimental results showed that the proposed scheme resists a variety of ordinary image operations and achieves good balance between robustness and discrimination. In comparison with other state-of-the-art methods, the receiver operating characteristic (ROC) curves of our scheme demonstrate its superiority in terms of content identification. [ABSTRACT FROM AUTHOR]

Novel coronavirus pneumonia (COVID-19) has become pandemic. It brings serious threat to hemodialysis (HD) patients. Therefore, we carried out a study on the clinical characteristics of HD patients with COVID-19. We retrospectively analyzed the data of 31 HD patients with COVID-19. The clinical features of patients include epidemiology, clinical symptoms, laboratory and imaging test, treatment and prognosis. 61.3% were severe, and 38.7% were mild. 83.9% had a close contact history with COVID-19 patients. The average age was 62.3 years comprising of 58.1% men and 41.9% women. Ninety percent had chronic diseases except ESRD. Clinical symptoms include cough (85%), fever (43%), and shortness of breath (48.4%), etc. Complications included ARDS (25.8%), AHF (22.6%), and septic shock (16.1%), etc. 64.5% of patients had remission, and 35.5% of patients had no remission with 6.5% deaths. Compared with the baseline before infection, HD patients with COVID-19 had lower lymphocytes, albumin and glucose, and higher D-dimer, albumin, phosphorus, lactate dehydrogenase, and CRP. There was no significant correlation between the neutrophils/lymphocytes ratio and the severity of the disease. Compared with the reported general population, the HD patients are susceptible to COVID-19 infection, especially older men and those with other underlying diseases. Moreover, HD patients have more severe infection and inflammation with less symptoms and worse outcome. COVID-19 infection can cause dialysis patients lower immunity, stronger inflammation, malnutrition, and internal environment disorder. Neutrophils/lymphocytes ratio does not reflect the severity of the HD patients with COVID-19. [ABSTRACT FROM AUTHOR]

The purpose of model calibration is to make the model predictions closer to reality. The classical Kennedy-O’Hagan approach is widely used for model calibration, which can account for the inadequacy of the computer model while simultaneously estimating the unknown calibration parameters. In many applications, the phenomenon of censoring occurs when the exact outcome of the physical experiment is not observed, but is only known to fall within a certain region. In such cases, the Kennedy-O’Hagan approach cannot be used directly, and we propose a method to incorporate the censoring information when performing model calibration. The method is applied to study the compression phenomenon of liquid inside a bottle. The results show significant improvement over the traditional calibration methods, especially when the number of censored observations is large. Supplementary materials for this article are available online. [ABSTRACT FROM AUTHOR]

A proliferation inducing ligand (APRIL) is a member of the TNF superfamily. It shares two receptors with B-cell activating factor (BAFF), B-cell maturation antigen (BCMA), and transmembrane activator and CAML interactor (TACI). Herein, the equine APRIL was identified from equine adipose-derived stem cell (ASC), and the protein expression of APRIL and its related molecules were detected during the adipogenic differentiation of equine ASCin vitro. The equineAPRILgene was located on chromosome 11, spans 1852 base pairs (bp). Its open reading frame covers 753 bp, encoding a 250-amino acid protein with the typical TNF structure domain. During the two weeks’ adipogenic differentiation of equine ASC, although the protein expression of APRIL and TACI had an insignificant change, that of BCMA increased significantly. Moreover, with the addition of recombinant protein His6-sAPRIL, a reduced differentiation of equine ASC toward adipocyte was detected. These results may provide the basis for investigating the role of APRIL in ASC adipogenic differentiation. [ABSTRACT FROM AUTHOR]

Objective: To investigate the effect of interleukin-17A (IL-17A) antibodies on radiation-induced lung injuries in mice. Methods: The thorax of 135 mice were divided into Sham ( n = 30), radiation control (RC, n = 35), treatment ( n = 35, IL-17A-neutralizing antibody, 4 μg/mouse, IV, 4 days per month for 4 months) and placebo group ( n = 35) before a single dose irradiation (15 Gy) to the thorax. Inflammation and collagen contents in the lung tissues were examined, and the concentration of IL-17A, TGF-β1, and IL-6 in bronchoalveolar lavage fluid (BALF) were measured. In another 50 animals, 180-day survival rate following the irradiation and treatment was calculated by Kaplan-Meier method. Results: Sixteen weeks after the irradiation and treatment, there was significant inflammatory cell infiltration and interstitial collagen depositions in the radiation control and placebo groups, whereas these changes were relatively mild in the treatment group. The percentage of grade II and III alveolitis in the treatment group (16%, P < .05) was lower than in the RC (72%) or placebo group (64%). The mean Aschcroft fibrosis scores were 2.8 (treatment group), 5.2 (RC), and 4.8 (placebo group), respectively. The scores of treatment group was lower than that of RC ( P < .001) or placebo group ( P < .001). The IL-17A, TGF-β, and IL-6 concentrations in the treatment group were lower than in the RC and placebo group ( P < .01) following the irradiation. The 180-day mortality rate in the treatment group was lower than in the RC group 16.7% versus 75.0%, P < .05). Conclusion: IL-17A antibody treatment alleviates radiation-induced pneumonitis and subsequent fibrosis, and improvise postirradiation survival. [ABSTRACT FROM AUTHOR]