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Hyper-uric acid (UA)-induced kidney injury (HAKI) is caused by the deposition of excess blood UA into the kidneys. We confined molecules of uricase (URI), catalase (CAT), and curcumin (Cur) to a single structure (UC/Cur) while retaining their enzymatic activities via a cross-linking complexation reaction between tannic acid and FeCl3 for treating HAKI. Simultaneously, bovine serum albumin (BSA)-UC/Cur nanoparticles were successfully prepared by interlinking the disulfide bonds of BSA with the enzyme complex via Tris(2-carboxyethyl) phosphine(TCEP) to form sulfhydryl groups. BSA-UC/Cur significantly attenuated MSU-induced NLRP3 inflammasome pathway activation and apoptosis in NRK-52e cells by eliminating UA crystals and intracellular reactive oxygen species. More importantly, treatment with BSA-UC/Cur stabilized blood UA concentrations and lowered proximal tubular protein levels, mitochondrial swelling, and fibrotic areas, renducing the expression of matrix metalloproteinase (MMP)2, MMP9, and NLRP3 while, increasing the expression of tight-junction proteins ZO1 and occludin as well as that of TIMP-1, in HAKI model rats. In addition, BSA-UC/Cur nanoparticles reduced the subpopulation ratios of CD8+ T cells and M1 macrophages and increased those of M2 macrophages and Treg cells. Preliminary in-vivo trials showed that long-term intravenous treatment with BSA-UC/Cur is safe. Therefore, BSA-UC/Cur could be a potential nanotherapeutic agent for HAKI.

The development characteristics, scale and control factors of fractures are the core subjects of reservoir sweet spot prediction. The sandstone reservoir of the TX2 gas reservoir in the Zhongjiang Gas Field is a typical low porosity and low permeability tight reservoir with strong heterogeneity, but relatively high-quality reservoirs can be found in different well areas and well segments. In this paper, taking the second Member of the Xujiahe Formation (TX2) as an example, the control factors of fractures were systemically investigated via core observation, thin section, logging data, and fracture logging identifications. The results show that shear fractures are mainly developed in the cores, and they generally have high filling rate and poor effectiveness; microfractures can be found based on the vitrinite and cast thin section results. The intersection diagram (semi-quantitative) and the principal component and BP comprehensive identification (quantitative) methods can effectively identify different types of fractures. The combined application of principal component and BP comprehensive identification methods results in an 83.3 % fracture identification probability. Finally, we found that the development of fractures in TX2 is comprehensively affected by lithology, rock thickness, porosity, and faults.

Objective: To explore the genetic changes in the progression of castration-resistant prostate cancer (CRPC) and neuroendocrine prostate cancer (NEPC) and the reason why these cancers resist existing therapies. Methods: We employed our CRPC cell line microarray and other CRPC or NEPC datasets to screen the target gene NEIL3. Lentiviral transfection and RNA interference were used to construct overexpression and knockdown cell lines. Cell and animal models of radiotherapy were established by using a medical electron linear accelerator. Flow cytometry was used to detect apoptosis or cell cycle progression. Western blot and qPCR were used to detect changes in the protein and RNA levels. Results: TCGA and clinical patient datasets indicated that NEIL3 was downregulated in CRPC and NEPC cell lines, and NEIL3 was correlated with a high Gleason score but a good prognosis. Further functional studies demonstrated that NEIL3 had no effect on the proliferation and migration of PCa cells. However, cell and animal radiotherapy models revealed that NEIL3 could facilitate the radiotherapy sensitivity of PCa cells, while loss of NEIL3 activated radiotherapy resistance. Mechanistically, we found that NEIL3 negatively regulated the expression of ATR, and higher NEIL3 expression repressed the ATR/CHK1 pathway, thus regulating the cell cycle. Conclusions: We demonstrated that NEIL3 may serve as a diagnostic or therapeutic target for therapy-resistant patients.

Shell limestone tight reservoirs are developed in the Lower Jurassic Da'anzhai Member of the Sichuan Basin. Fractures are important storage spaces and seepage channels in shell limestone tight oil reservoirs and are key factors for high oil and gas production in wells. In this study, considering the shell limestone reservoir of the Da'anzhai Member on the eastern slope of the Western Sichuan Depression as an example, we used multiple fracture interpretation models based on conventional logging to identify fractures. Our results show that: (1) the reservoirs in the Da'anzhai Member primarily showed low-angle structural fractures, mostly filled with calcite. The effective linear density of fractures in each well varied greatly, which primarily explains the strong heterogeneity of tight reservoirs. (2) The logging response characteristics of the fractured and non-fractured segments differ considerably, and the fractured segment shows the characteristics of high acoustic time difference and low resistivity. (3) The well log recombination method, principal component analysis method, multivariate discriminant method, backpropagation (BP) neural network method, and K-nearest neighbor (KNN) algorithm are used for fracture identification. According to the consistency of the fracture identification results with the core observation results, we established a comprehensive fracture identification standard using the multi-logging method. In this study, we established a fracture identification method based on the coupling of multiple linear and nonlinear multi-logging models through core calibration, which avoids the errors and uncertainties caused by using a single method. Additionally, this study provides a foundation for the control factors and the prediction of fracture distribution.

Abstract Background The purpose of this study was to investigate the value of wavelet-transformed radiomic MRI in predicting the pathological complete response (pCR) to neoadjuvant chemotherapy (NAC) for patients with locally advanced breast cancer (LABC). Methods Fifty-five female patients with LABC who underwent contrast-enhanced MRI (CE-MRI) examination prior to NAC were collected for the retrospective study. According to the pathological assessment after NAC, patient responses to NAC were categorized into pCR and non-pCR. Three groups of radiomic textures were calculated in the segmented lesions, including (1) volumetric textures, (2) peripheral textures, and (3) wavelet-transformed textures. Six models for the prediction of pCR were Model I: group (1), Model II: group (1) + (2), Model III: group (3), Model IV: group (1) + (3), Model V: group (2) + (3), and Model VI: group (1) + (2) + (3). The performance of predicting models was compared using the area under the receiver operating characteristic (ROC) curves (AUC). Results The AUCs of the six models for the prediction of pCR were 0.816 ± 0.033 (Model I), 0.823 ± 0.020 (Model II), 0.888 ± 0.025 (Model III), 0.876 ± 0.015 (Model IV), 0.885 ± 0.030 (Model V), and 0.874 ± 0.019 (Model VI). The performance of four models with wavelet-transformed textures (Models III, IV, V, and VI) was significantly better than those without wavelet-transformed textures (Model I and II). In addition, the inclusion of volumetric textures or peripheral textures or both did not result in any improvements in performance. Conclusions Wavelet-transformed textures outperformed volumetric and/or peripheral textures in the radiomic MRI prediction of pCR to NAC for patients with LABC, which can potentially serve as a surrogate biomarker for the prediction of the response of LABC to NAC.

The accurate, objective, and reproducible evaluation of tumor response to therapy is indispensable in clinical trials. This study aimed at investigating the reliability and reproducibility of a computer-aided contouring (CAC) tool in tumor measurements and its impact on evaluation of tumor response in terms of RECIST 1.1 criteria. A total of 200 cancer patients were retrospectively collected in this study, which were randomly divided into two sets of 100 patients for experiential learning and testing. A total of 744 target lesions were identified by a senior radiologist in distinctive body parts, of which 278 lesions were in data set 1 (learning set) and 466 lesions were in data set 2 (testing set). Five image analysts were respectively instructed to measure lesion diameter using manual and CAC tools in data set 1 and subsequently tested in data set 2. The interobserver variability of tumor measurements was validated by using the coefficient of variance (CV), the Pearson correlation coefficient (PCC), and the interobserver correlation coefficient (ICC). We verified that the mean CV of manual measurement remained constant between the learning and testing data sets (0.33 vs. 0.32, p = 0.490), whereas it decreased for the CAC measurements after learning (0.24 vs. 0.19, p < 0.001). The interobserver measurements with good agreement (CV < 0.20) were 29.9% (manual) vs. 49.0% (CAC) in the learning set (p < 0.001) and 30.9% (manual) vs. 64.4% (CAC) in the testing set (p < 0.001). The mean PCCs were 0.56 ± 0.11 mm (manual) vs. 0.69 ± 0.10 mm (CAC) in the learning set (p = 0.013) and 0.73 ± 0.07 mm (manual) vs. 0.84 ± 0.03 mm (CAC) in the testing set (p < 0.001). ICCs were 0.633 (manual) vs. 0.698 (CAC) in the learning set (p < 0.001) and 0.716 (manual) vs. 0.824 (CAC) in the testing set (p < 0.001). The Fleiss’ kappa analysis revealed that the overall agreement was 58.7% (manual) vs. 58.9% (CAC) in the learning set and 62.9% (manual) vs. 74.5% (CAC) in the testing set. The 80% agreement of tumor response evaluation was 55.0% (manual) vs. 66.0% in the learning set and 60.6% (manual) vs. 79.7% (CAC) in the testing set. In conclusion, CAC can reduce the interobserver variability of radiological tumor measurements and thus improve the agreement of imaging evaluation of tumor response.

PurposeThere is a major shortage of reliable early detection methods for pancreatic cancer in high-risk groups. The focus of this preliminary study was to use Time Intensity-Density Curve (TIDC) and Marley Equation analyses, in conjunction with 3D volumetric and perfusion imaging to demonstrate their potential as imaging biomarkers to assist in the early detection of Pancreatic Ductal Adenocarcinoma (PDAC).Experimental DesignsA quantitative retrospective and prospective study was done by analyzing multi-phase Computed Tomography (CT) images of 28 patients undergoing treatment at different stages of pancreatic adenocarcinoma using advanced 3D imaging software to identify the perfusion and radio density of tumors.ResultsTIDC and the Marley Equation proved useful in quantifying tumor aggressiveness. Perfusion delays in the venous phase can be linked to Vascular Endothelial Growth Factor (VEGF)-related activity which represents the active part of the tumor. 3D volume analysis of the multiphase CT scan of the patient showed clear changes in arterial and venous perfusion indicating the aggressive state of the tumor.ConclusionTIDC and 3D volumetric analysis can play a significant role in defining the response of the tumor to treatment and identifying early-stage aggressiveness.

Background Although immune checkpoint inhibitors (ICIs), especially programmed cell death protein 1 (PD-1)/programmed death ligand 1 (PD-L1) axis blockers, exhibit prominent antitumor effects against numerous malignancies, their benefit for patients with prostate cancer (PCa) has been somewhat marginal. This study aimed to assess the feasibility of B7-H3 or HHLA2 as alternative immunotherapeutic targets in PCa.Methods Immunohistochemistry was performed to evaluate the expression pattern of PD-L1, B7-H3 and HHLA2 and the infiltration of CD8+ and Foxp3+ lymphocytes in 239 PCa tissues from two independent cohorts. The correlations between B7-H3 and HHLA2 and clinicopathological features, including the presence of CD8+ and Foxp3+ tumor-infiltrating lymphocytes (TILs), were explored.Results HHLA2 expression was much higher than PD-L1 expression but lower than B7-H3 expression in PCa tissues. High expression of both B7-H3 and HHLA2 was significantly associated with higher Gleason score and tumor stage, lymph node metastasis and dismal overall survival (OS) and cancer-specific survival (CSS). Moreover, a high B7 score, defined as high B7-H3 expression and/or high HHLA2 expression, was an independent prognostic predictor for PCa. Of note, a high B7 score was negatively correlated with CD8+ TILs. Importantly, a new immune classification, based on the B7 score and CD8+ TILs, successfully stratified OS and CSS in PCa.Conclusions Both B7-H3 and HHLA2 have a critical impact on the immunosuppressive microenvironment, and the B7 score could be used as an independent prognostic factor for PCa. The B7 score combined with CD8+ TILs could be used as a new immune classification to stratify the risk of death, especially cancer-related death, for patients with PCa. These findings may provide insights that could improve response to immune-related comprehensive therapy for PCa in the future.

Abstract Metastasis is the major cause of prostate cancer (PCa)‐related mortality. Epithelial‐mesenchymal transition (EMT) is a vital characteristic feature that empowers cancer cells to adapt and survive at the beginning of metastasis. Therefore, it is essential to identify the regulatory mechanism of EMT in metastatic prostate cancer (mPCa) and to develop a novel therapy to block PCa metastasis. Here, we discovered a novel PCa metastasis oncogene, DEP domain containing 1B (DEPDC1B), which was positively correlated with the metastasis status, high Gleason score, advanced tumor stage, and poor prognosis. Functional assays revealed that DEPDC1B enhanced the migration, invasion, and proliferation of PCa cells in vitro and promoted tumor metastasis and growth in vivo. Mechanistic investigations clarified that DEPDC1B induced EMT and enhanced proliferation by binding to Rac1 and enhancing the Rac1‐PAK1 pathway. This DEPDC1B‐mediated oncogenic effect was reversed by a Rac1‐GTP inhibitor or Rac1 knockdown. In conclusion, we discover that the DEPDC1B‐Rac1‐PAK1 signaling pathway may serve as a multipotent target for clinical intervention in mPCa.

Immune checkpoint inhibitors (ICIs) treatment is becoming a new hope for cancer treatment. However, most prostate cancer (PCa) patients do not benefit from it. In order to achieve the accuracy of ICIs treatment in PCa and reduce unnecessary costs for patients, we have analyzed the data from TCGA database to find a indicator that can assist the choice of treatment. By analyzing the data of PCa patients with TMB analysis and immune infiltration analysis, we found the expression of immune cells in different immune infiltration groups. Commonly used markers of ICIs, expressed on CD8+ T cell, were highly expressed in the high immune group. Then we used the forimmune cytolytic activity (CYT) to determine its relationship with the target of ICIs treatment. Through the analysis of CYT score and the ligands of immune checkpoints, we found that there was a significant correlation between them. With the increase of CYT score, the expression of CD80/86, PD-L1/L2, TNFSF14, and LGALS9 also increased gradually. Similarly, CD8+ T cells were significantly increased in the CYT high group compared with the CYT low group in PRAD. The present research provides novel insights into the immune microenvironment of PRAD and potential immunotherapies. The proposed CYT score is a clinically promising indicator that can serve as a marker to assist anti-PD-L1 or other ICIs treatment. At the same time, it also provides a basis for the selection of other immune checkpoint drugs.

To evaluate the diagnostic value of multidetector CT (MDCT) and its multiplanar reformation (MPR), volume rendering (VR) and virtual bronchoscopy (VB) postprocessing techniques for primary trachea and main bronchus tumors.Detection results of 31 primary trachea and main bronchus tumors with MDCT and its MPR, VR and VB postprocessing techniques, were analyzed retrospectively with regard to tumor locations, tumor morphologies, extramural invasions of tumors, longitudinal involvements of tumors, morphologies and extents of luminal stenoses, distances between main bronchus tumors and trachea carinae, and internal features of tumors. The detection results were compared with that of surgery and pathology.Detection results with MDCT and its MPR, VR and VB were consistent with that of surgery and pathology, included tumor locations (tracheae, n = 19; right main bronchi, n = 6; left main bronchi, n = 6), tumor morphologies (endoluminal nodes with narrow bases, n = 2; endoluminal nodes with wide bases, n = 13; both intraluminal and extraluminal masses, n = 16), extramural invasions of tumors (brokethrough only serous membrane, n = 1; 4.0 mm-56.0 mm, n = 14; no clear border with right atelectasis, n = 1), longitudinal involvements of tumors (3.0 mm, n = 1; 5.0 mm-68.0 mm, n = 29; whole right main bronchus wall and trachea carina, n = 1), morphologies of luminal stenoses (irregular, n = 26; circular, n = 3; eccentric, n = 1; conical, n = 1) and extents (mild, n = 5; moderate, n = 7; severe, n = 19), distances between main bronchus tumors and trachea carinae (16.0 mm, n = 1; invaded trachea carina, n = 1; >20.0 mm, n = 10), and internal features of tumors (fairly homogeneous densities with rather obvious enhancements, n = 26; homogeneous density with obvious enhancement, n = 1; homogeneous density without obvious enhancement, n = 1; not enough homogeneous density with obvious enhancement, n = 1; punctate calcification with obvious enhancement, n = 1; low density without obvious enhancement, n = 1).MDCT and its MPR, VR and VB images have respective advantages and disadvantages. Their combination could complement to each other to accurately detect locations, natures (benignancy, malignancy or low malignancy), and quantities (extramural invasions, longitudinal involvements, extents of luminal stenoses, distances between main bronchus tumors and trachea carinae) of primary trachea and main bronchus tumors with crucial information for surgical treatment, are highly useful diagnostic methods for primary trachea and main bronchus tumors.

To investigate image quality and radiation dose of CT colonography (CTC) with adaptive iterative dose reduction three-dimensional (AIDR3D).Ten segments of porcine colon phantom were collected, and 30 pedunculate polyps with diameters ranging from 1 to 15 mm were simulated on each segment. Image data were acquired with tube voltage of 120 kVp, and current doses of 10 mAs, 20 mAs, 30 mAs, 40 mAs, 50 mAs, respectively. CTC images were reconstructed using filtered back projection (FBP) and AIDR3D. Two radiologists blindly evaluated image quality. Quantitative evaluation of image quality included image noise, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR). Qualitative image quality was evaluated with a five-score scale. Radiation dose was calculated based on dose-length product. Ten volunteers were examined supine 50 mAs with FBP and prone 20 mAs with AIDR3D, and image qualities were assessed. Paired t test was performed for statistical analysis.For 20 mAs with AIDR3D and 50 mAs with FBP, image noise, SNRs and CNRs were (16.4 ± 1.6) HU vs. (16.8 ± 2.6) HU, 1.9 ± 0.2 vs. 1.9 ± 0.4, and 62.3 ± 6.8 vs. 62.0 ± 6.2, respectively; qualitative image quality scores were 4.1 and 4.3, respectively; their differences were all not statistically significant. Compared with 50 mAs with FBP, radiation dose (1.62 mSv) of 20 mAs with AIDR3D was decreased by 60.0%. There was no statistically significant difference in image noise, SNRs, CNRs and qualitative image quality scores between prone 20 mAs with AIDR3D and supine 50 mAs with FBP in 10 volunteers, the former reduced radiation dose by 61.1%.Image quality of CTC using 20 mAs with AIDR3D could be comparable to standard 50 mAs with FBP, radiation dose of the former reduced by about 60.0% and was only 1.62 mSv.

To investigate image quality and radiation dose of CT coronary angiography (CTCA) scanned using automatic tube current modulation (ATCM) and reconstructed by strong adaptive iterative dose reduction three-dimensional (AIDR3D).Eighty-four consecutive CTCA patients were collected for the study. All patients were scanned using ATCM and reconstructed with strong AIDR3D, standard AIDR3D and filtered back-projection (FBP) respectively. Two radiologists who were blinded to the patients' clinical data and reconstruction methods evaluated image quality. Quantitative image quality evaluation included image noise, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR). To evaluate image quality qualitatively, coronary artery is classified into 15 segments based on the modified guidelines of the American Heart Association. Qualitative image quality was evaluated using a 4-point scale. Radiation dose was calculated based on dose-length product.Compared with standard AIDR3D, strong AIDR3D had lower image noise, higher SNR and CNR, their differences were all statistically significant (P

This paper investigates the effect of thermal radiation on unsteady convection flow and heat transfer over a vertical permeable stretching surface in porous medium, where the effects of temperature dependent viscosity and thermal conductivity are also considered. By using a similarity transformation, the governing time-dependent boundary layer equations for momentum and thermal energy are first transformed into coupled, non-linear ordinary differential equations with variable coefficients. Numerical solutions to these equations subject to appropriate boundary conditions are obtained by the numerical shooting technique with fourth-fifth order Runge-Kutta scheme. Numerical results show that as viscosity variation parameter increases both the absolute value of the surface friction coefficient and the absolute value of the surface temperature gradient increase whereas the temperature decreases slightly. With the increase of viscosity variation parameter, the velocity decreases near the sheet surface but increases far away from the surface of the sheet in the boundary layer. The increase in permeability parameter leads to the decrease in both the temperature and the absolute value of the surface friction coefficient, and the increase in both the velocity and the absolute value of the surface temperature gradient.

Patients with neurofibromatosis 1 (NF1), NF2, and schwannomatosis are at risk for multiple nerve sheath tumors and premature mortality. Traditional magnetic resonance imaging (MRI) has limited ability to assess disease burden accurately. The aim of this study was to establish an international cohort of patients with quantified whole-body internal tumor burden and to correlate tumor burden with clinical features of disease.We determined the number, volume, and distribution of internal nerve sheath tumors in patients using whole-body MRI (WBMRI) and three-dimensional computerized volumetry. We quantified the distribution of tumor volume across body regions and used unsupervised cluster analysis to group patients based on tumor distribution. We correlated the presence and volume of internal tumors with disease-related and demographic factors.WBMRI identified 1286 tumors in 145/247 patients (59%). Schwannomatosis patients had the highest prevalence of tumors (P = 0.03), but NF1 patients had the highest median tumor volume (P = 0.02). Tumor volume was unevenly distributed across body regions with overrepresentation of the head/neck and pelvis. Risk factors for internal nerve sheath tumors included decreasing numbers of café-au-lait macules in NF1 patients (P = 0.003) and history of skeletal abnormalities in NF2 patients (P = 0.09). Risk factors for higher tumor volume included female gender (P = 0.05) and increasing subcutaneous neurofibromas (P = 0.03) in NF1 patients, absence of cutaneous schwannomas in NF2 patients (P = 0.06), and increasing age in schwannomatosis patients (p = 0.10).WBMRI provides a comprehensive phenotype of neurofibromatosis patients, identifies distinct anatomic subgroups, and provides the basis for investigating molecular biomarkers that correlate with unique disease manifestations.