Role of serum alkaline phosphatase as a potential biomarker of severity and prognosis in intracerebral hemorrhage.

OBJECTIVES: Alkaline phosphatase (ALP) catalyzes the hydrolysis of pyrophosphate and facilitates vascular calcification. We aimed at investigating serum ALP levels in intracerebral hemorrhage (ICH) patients and ascertaining its relationship to severity and prognosis. METHODS: Serum ALP levels from 148 patients and 148 healthy controls were detected. Glasgow coma scale (GCS) score and hematoma volume at admission were recorded to evaluate hemorrhagic severity. Modified Rankin Scale (mRS) score > 2 at 90 days after onset was judged as a poor prognosis. RESULTS: Serum ALP levels in patients with ICH were substantially elevated compared with healthy controls, and were significantly related to hematoma volume and GCS score. Serum ALP levels significantly distinguished ICH patients at risk for unfavorable prognosis. Serum ALP levels > 78.5 U/L in ICH patients may indicated a unfavorable prognosis with 69.1 % sensitivity and 83.6 % specificity, and served as an independent predictor for unfavorable prognosis. CONLUSIONS: Elevated serum ALP levels were intimately connected with increased severity and 90-day unfavorable prognosis in patients with ICH. Serum ALP could be a potential biomarker for severity and prognosis of ICH.

Deep Clustering and Visualization for End-to-End High-Dimensional Data Analysis.

High-dimensional data analysis for exploration and discovery includes two fundamental tasks: deep clustering and data visualization. When these two associated tasks are done separately, as is often the case thus far, disagreements can occur among the tasks in terms of geometry preservation. Namely, the clustering process is often accompanied by the corruption of the geometric structure, whereas visualization aims to preserve the data geometry for better interpretation. Therefore, how to achieve deep clustering and data visualization in an end-to-end unified framework is an important but challenging problem. In this article, we propose a novel neural network-based method, called deep clustering and visualization (DCV), to accomplish the two associated tasks end-to-end to resolve their disagreements. The DCV framework consists of two nonlinear dimensionality reduction (NLDR) transformations: 1) one from the input data space to latent feature space for clustering and 2) the other from the latent feature space to the final 2-D space for visualization. Importantly, the first NLDR transformation is mainly optimized by one Clustering Loss, allowing arbitrary corruption of the geometric structure for better clustering, while the second NLDR transformation is optimized by one Geometry-Preserving Loss to recover the corrupted geometry for better visualization. Extensive comparative results show that the DCV framework outperforms other leading clustering-visualization algorithms in terms of both quantitative evaluation metrics and qualitative visualization.

Ferroptosis-Related Gene-Based Prognostic Model and Immune Infiltration in Clear Cell Renal Cell Carcinoma.

Clear cell renal cell carcinoma (ccRCC) is one of the most common tumors in the urinary system. Ferroptosis plays a vital role in ccRCC development and progression. We did an update of ferroptosis-related multigene expression signature for individualized prognosis prediction in patients with ccRCC. Differentially expressed ferroptosis-related genes in ccRCC and normal samples were screened using The Cancer Genome Atlas. Univariate and multivariate Cox regression analyses and machine learning methods were employed to identify optimal prognosis-related genes. CARS1, CD44, FANCD2, HMGCR, NCOA4, SLC7A11, and ACACA were selected to establish a prognostic risk score model. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses revealed that these genes were mainly enriched in immune-related pathways; single-sample Gene Set Enrichment Analysis revealed several immune cells potentially related to ferroptosis. Kaplan-Meier survival analysis demonstrated that patients with high-risk scores had significantly poor overall survival (log-rank P = 7.815 × 10-11). The ferroptosis signature was identified as an independent prognostic factor. Finally, a prognostic nomogram, including the ferroptosis signature, age, histological grade, and stage status, was constructed. Analysis of The Cancer Genome Atlas-based calibration plots, C-index, and decision curve indicated the excellent predictive performance of the nomogram. The ferroptosis-related seven-gene risk score model is useful as a prognostic biomarker and suggests therapeutic targets for ccRCC. The prognostic nomogram may assist in individualized survival prediction and improve treatment strategies.

Identification of a Two-m6A RNA Methylation Regulator Risk Signature as an Independent Prognostic Biomarker in Papillary Renal Cell Carcinoma by Bioinformatic Analysis.

N6-Methyladenosine (m6A), the most common form of mRNA modification, is dynamically regulated by the m6A RNA methylation regulators, which play an important role in regulating the gene expression and phenotype in both health and disease. However, the role of m6A in papillary renal cell carcinoma (pRCC) is unknown. The purpose of this work is to investigate the prognostic value of m6A RNA methylation regulators in pRCC; thus, we can build a risk score model based on m6A RNA methylation regulators as a risk signature for predicting the prognosis of pRCC. Here, we investigated the expression and corresponding clinical data by bioinformatic analysis based on 289 pRCC tissues and 32 normal kidney tissues obtained from TCGA database. As a result, we identified the landscape of m6A RNA methylation regulators in pRCC. We grouped all pRCC patients into two clusters by consensus clustering to m6A RNA methylation regulators, but we found that the clusters were not correlated to the prognosis and clinicopathological features of pRCC. Therefore, we additionally built a two-m6A RNA methylation regulator risk score model as a risk signature by the univariate Cox regression analysis and least absolute shrinkage and selection operator (LASSO) Cox regression. The risk signature was constructed as follows: 0.031HNRNPC + 0.199KIAA1429. It revealed that the risk score was associated with the clinicopathological features such as pT status and pN status of pRCC. More importantly, the risk score was an independent prognostic marker for pRCC patients. Thus, m6A RNA methylation regulators contributed to the malignant progression of pRCC influencing its prognosis.

Long non-coding RNA LINC01234 regulates proliferation, migration and invasion via HIF-2α pathways in clear cell renal cell carcinoma cells.

Long non-coding RNAs (lncRNAs) have been proved to have an important role in different malignancies including clear cell renal cell carcinoma (ccRCC). However, their role in disease progression is still not clear. The objective of the study was to identify lncRNA-based prognostic biomarkers and further to investigate the role of one lncRNA LINC01234 in progression of ccRCC cells. We found that six adverse prognostic lncRNA biomarkers including LINC01234 were identified in ccRCC patients by bioinformatic analysis using The Cancer Genome Atlas database. LINC01234 knockdown impaired cell proliferation, migration and invasion in vitro as compared to negative control. Furthermore, the epithelial-mesenchymal transition was inhibited after LINC01234 knockdown. Additionally, LINC01234 knockdown impaired hypoxia-inducible factor-2a (HIF-2α) pathways, including a suppression of the expression of HIF-2α, vascular endothelial growth factor A, epidermal growth factor receptor, c-Myc, Cyclin D1 and MET. Together, these datas showed that LINC01234 was likely to regulate the progression of ccRCC by HIF-2α pathways, and LINC01234 was both a promising prognostic biomarker and a potential therapeutic target for ccRCC.

Clinical significance of circulating tumor cells detection in renal cell carcinoma with thrombus: A STROBE-compliant study.

The aim of the study was to evaluate the potential role of circulating tumor cell (CTC) detection in the surgical assessment of renal cell carcinoma (RCC) patients with thrombi.Nine patients diagnosed with renal mass and thrombi were enrolled from June 2018 to January 2019. Blood samples were collected for CTC detection using SE-iFISH assay. CD45, DAPI, programmed death ligand 1, and fluorescence in situ hybridization with the centromere of chromosome 8 (CEP8) were immune-stained for analysis. Patient demographics, clinical features, pathological characteristics, and CTC detection results were extracted for analysis.Seven of 9 patients (77.8%) had 12 detectable CTCs, 5 of which were with CEP8-positive signal ≥5 and the others were CEP8-positive signal = 3. All 3 patients (100%) with IVC invasion had detectable CTCs, whereas CTCs were detected in 4 of 6 patients (66.7%) without IVC invasion. CEP8 analysis revealed that CTCs in IVC invasion patients were all of CEP8-positive signal ≥5 status, whereas only half of the CTCs in patients without IVC invasion were of CEP8-positive signal ≥5 pattern.In conclusion, both CTC subtype and total CTC number may serve as a marker for predicting inferior vena cava invasion in RCC patients.

Long non-coding RNAs as prognostic biomarkers in papillary renal cell carcinoma.

The aim of the present study was to identify long non-coding RNA (lncRNA)-based prognostic biomarkers in papillary renal cell carcinoma (pRCC). lncRNA expression data and corresponding clinical data from patients with pRCC were obtained from The Cancer Genome Atlas. R software and packages were used for data analysis. Univariate Cox regression analysis and least absolute shrinkage and selection operator regression were performed to identify key lncRNAs, which were then used to construct a prognostic model using multivariate Cox regression analysis. Patients were divided into high- and low-risk groups, and Kaplan-Meier (KM) survival curves and time-dependent receiver operating characteristic (ROC) curves were plotted. The C-index was calculated to estimate the model's prognostic power. The hazard ratio (HR), 95% confidence interval (CI), and statistical significance of each key lncRNA were also calculated by multivariate Cox regression. Based on the result of the multivariate Cox regression analysis, KM survival plots were plotted for each significantly associated lncRNA. The subcellular locations of the prognostic biomarkers were predicted using lncRNAMap and lncLocator. A total of 17 lncRNA signatures were identified as key lncRNAs. Overall survival rate was significantly higher in the low-risk group compared with the high-risk group. The areas under the ROC curve were 0.93 (3-year ROC) and 0.902 (5-year ROC), and the C-index was 0.915. A forest plot was used to illustrate the HR and 95% CI of key lncRNAs. KM survival analysis revealed the prognostic significance of two protective biomarkers, AC024022.1 and GAS6-AS1, and three adverse biomarkers, AC087379.2, AL352984.1, and AL499627.1. It was predicted that AC024022.1 and AC087379.2 may be located in the cytoplasm and GAS6-AS1 may be located in the cytosol. The present study may contribute to the management of pRCC and serve as a foundation for further investigations into the underlying mechanism of tumorigenesis and progression of pRCC.

Surgical treatment for Xp11.2 translocation renal cell carcinoma with venous thrombus: A STROBE-compliant study.

The aim of the study was to report the experience and outcomes of Xp11.2 translocation renal cell carcinoma (tRCC) patients with tumor thrombus undergoing radical nephrectomy and thrombectomy.Between January 2017 and December 2017, 66 consecutive patients with RCC and venous thrombus involvement received surgical treatment at Peking University Third Hospital. Of which, 5 patients were confirmed of Xp11.2 tRCC, 61 patients were diagnosed of non-tRCC subtypes including 45 ccRCCs, 10 pRCCs, and 6 other subtypes. Demographic, clinical, operation, pathological and follow-up data were extracted for analysis. Prognostic factors were identified by Cox regression analysis.All the patients received radical nephrectomy and thrombectomy successfully. During a median follow-up of 18 months, 5 patients in non-tRCC group and 1 patient in tRCC group died of disease progression. Survival analysis revealed that Xp11.2 tRCC patients experienced shorter DFS than non-tRCC patients, however, there is no significant difference in OS between two groups. Xp11.2 tRCC histological subtype and presence of metastasis at diagnosis were identified as independent negative factors of DFS by multivariate analysis.Radical nephrectomy with thrombectomy provides an acceptable efficacy for tRCC patients with tumor thrombus extending into the venous system. In addition, multimodality treatment should be considered for advanced Xp11.2 RCCs as this subtype was a negative prognostic factor of DFS.

Surgical treatment for pelvic lipomatosis using a bladder-sparing technique: A STROBE-compliant study.

The aim of this study was to report the experience and long-term efficacy of a novel surgical treatment for pelvic lipomatosis (PL) using a combination of pelvic fat mass extirpation and ureteral reimplantation.Data of 8 patients with PL who underwent pelvic fat mass extirpation and ureteral reimplantation at our hospital from September 2010 to March 2018 were retrospectively reviewed. Demographics, serum creatinine level, radiographic changes, perioperative complications, and patient-reported outcomes were evaluated.Surgeries were performed successfully without severe perioperative complications in all 8 patients. Median operating time was 150 minutes with a median estimated blood loss of 75 mL. Patients were discharged after a median of 8.5 postoperative days. Imaging studies at the first follow-up revealed varying extents of alleviation of hydronephrosis and 3 patients' urinary symptoms were gradually relieved after surgery. During a median follow-up of 48.5 months (range, 10-100 months), all patients exhibited excellent surgical outcomes without evidence of disease progression, except 1 patient who underwent radical cystectomy with Bricker ileal conduit surgery due to hydronephrosis recurrence in the 49th postoperative month.Based on these cases, pelvic fat mass extirpation and ureteral reimplantation is a safe and effective surgical treatment for PL.

Efficacy and safety of dapoxetine for premature ejaculation: an updated systematic review and meta-analysis.

We conducted a systematic review and meta-analysis of published randomised controlled trials of dapoxetine for premature ejaculation. We systematically searched Embase, PubMed, Cochrane, Web of Knowledge, FDA.gov and Clinical Trials.gov for studies reporting dapoxetine in men with premature ejaculation. Efficacy endpoints included intravaginal ejaculatory latency times (IELT), personal distress related to ejaculation (PDRE) and treatment-emergent adverse events (TEAEs) was used to evaluate safety. Data were analysed using a random-effects model. Electronic search identified 276 papers. The final analysis included eight papers (n = 8422 subjects). Analysis of the pooled results indicated efficacy in both IELT (weighted mean difference (WMD) = 1.67, 95% confidence interval (CI) 1.45-1.89) and PDRE (relative risk = 1.26, 95% CI 1.18-1.35). Subgroup analysis indicated efficacy (i.e. increase in IELT) for 30- and 60-mg on-demand dapoxetine (WMD 1.38 (95% CI 1.01-1.75) and 1.62 (95% CI 1.40-1.84) respectively), as well as daily use of 60 mg dapoxetine (WMD 2.18, 95% CI 1.71-2.64). The safety profile was acceptable. Based on the different effects of magnitude of the three dosing regimens, we recommend a stepwise approach, starting with 30 mg on demand, then 60 mg on demand and finally 60 mg dapoxetine daily.