The cientificWorldJOURNAL Clinical Study Fasting Blood Glucose and Lipid Profile Alterations following Twelve-Month Androgen Deprivation Therapy in Men with Prostate Cancer

properly cited. Purpose. In this retrospective study, we aimed to investigate the effects of androgen deprivation therapy (ADT) on blood glucose and blood cholesterol levels over a 12-month period. Materials and Methods. Between January 2010 and June 2012, the data of 44 patients with prostate cancer who were receiving ADT were collected from a hospital database. Patients with additional malignancy or diabetes and those who had been prescribed and were currently taking cholesterol-lowering medication were excluded from the study. Data (including fasting blood glucose levels and a cholesterol profile) were collected and analysed statistically. A P value <0.05 was considered statistically significant. Results. Twelve months after the initiation of ADT, fasting blood glucose (FBG), total cholesterol (TC), low-density lipoprotein (LDL) cholesterol, high-density lipoprotein (HDL) cholesterol, and triglyceride (TG) levels changed. FBG, TC, LDL cholesterol, and TG increased significantly (P = 0.009, 0.000, 0.000, and 0.000, resp.), while HDL cholesterol decreased (P = 0.000). Conclusion. ADT may increase FBG, TC, LDL cholesterol, and TG but decrease HDL cholesterol by the end of a year of treatment. Therefore, close followup may be needed as a consequence of one-year ADT regarding metabolic alterations

Therapy of clinical stage IIA and IIB seminoma: a systematic review

\ua9 2021, The Author(s). Purpose: The optimal treatment for clinical stage (CS) IIA/IIB seminomas is still controversial. We evaluated current treatment options. Methods: A systematic review was performed. Only randomized clinical trials and comparative studies published from January 2010 until February 2021 were included. Search items included: seminoma, CS IIA, CS IIB and therapy. Outcome parameters were relapse rate (RR), relapse-free (RFS), overall and cancer-specific survival (OS, CSS). Additionally, acute and long-term side effects including secondary malignancies (SMs) were analyzed. Results: Seven comparative studies (one prospective and six retrospective) were identified with a total of 5049 patients (CS IIA: 2840, CS IIB: 2209). The applied treatment modalities were radiotherapy (RT) (n = 3049; CS IIA: 1888, CSIIB: 1006, unknown: 155) and chemotherapy (CT) or no RT (n = 2000; CS IIA: 797, CS IIB: 1074, unknown: 129). In CS IIA, RRs ranged from 0% to 4.8% for RT and 0% for CT. Concerning CS IIB RRs of 9.5%–21.1% for RT and of 0%–14.2% for CT have been reported. 5-year OS ranged from 90 to 100%. Only two studies reported on treatment-related toxicities. Conclusions: RT and CT are the most commonly applied treatments in CS IIA/B seminoma. In CS IIA seminomas, RRs after RT and CT are similar. However, in CS IIB, CT seems to be more effective. Survival rates of CS IIA/B seminomas are excellent. Consequently, long-term toxicities and SMs are important survivorship issues. Alternative treatment approaches, e.g., retroperitoneal lymph node dissection (RPLND) or dose-reduced sequential CT/RT are currently under prospective investigation

Incorporating rich background knowledge for gene named entity classification and recognition

<p>Abstract</p> <p>Background</p> <p>Gene named entity classification and recognition are crucial preliminary steps of text mining in biomedical literature. Machine learning based methods have been used in this area with great success. In most state-of-the-art systems, elaborately designed lexical features, such as words, n-grams, and morphology patterns, have played a central part. However, this type of feature tends to cause extreme sparseness in feature space. As a result, out-of-vocabulary (OOV) terms in the training data are not modeled well due to lack of information.</p> <p>Results</p> <p>We propose a general framework for gene named entity representation, called feature coupling generalization (FCG). The basic idea is to generate higher level features using term frequency and co-occurrence information of highly indicative features in huge amount of unlabeled data. We examine its performance in a named entity classification task, which is designed to remove non-gene entries in a large dictionary derived from online resources. The results show that new features generated by FCG outperform lexical features by 5.97 F-score and 10.85 for OOV terms. Also in this framework each extension yields significant improvements and the sparse lexical features can be transformed into both a lower dimensional and more informative representation. A forward maximum match method based on the refined dictionary produces an F-score of 86.2 on BioCreative 2 GM test set. Then we combined the dictionary with a conditional random field (CRF) based gene mention tagger, achieving an F-score of 89.05, which improves the performance of the CRF-based tagger by 4.46 with little impact on the efficiency of the recognition system. A demo of the NER system is available at <url>http://202.118.75.18:8080/bioner</url>.</p

Large-scale validation of methods for cytotoxic T-lymphocyte epitope prediction

<p>Abstract</p> <p>Background</p> <p>Reliable predictions of Cytotoxic T lymphocyte (CTL) epitopes are essential for rational vaccine design. Most importantly, they can minimize the experimental effort needed to identify epitopes. NetCTL is a web-based tool designed for predicting human CTL epitopes in any given protein. It does so by integrating predictions of proteasomal cleavage, TAP transport efficiency, and MHC class I affinity. At least four other methods have been developed recently that likewise attempt to predict CTL epitopes: EpiJen, MAPPP, MHC-pathway, and WAPP. In order to compare the performance of prediction methods, objective benchmarks and standardized performance measures are needed. Here, we develop such large-scale benchmark and corresponding performance measures and report the performance of an updated version 1.2 of NetCTL in comparison with the four other methods.</p> <p>Results</p> <p>We define a number of performance measures that can handle the different types of output data from the five methods. We use two evaluation datasets consisting of known HIV CTL epitopes and their source proteins. The source proteins are split into all possible 9 mers and except for annotated epitopes; all other 9 mers are considered non-epitopes. In the RANK measure, we compare two methods at a time and count how often each of the methods rank the epitope highest. In another measure, we find the specificity of the methods at three predefined sensitivity values. Lastly, for each method, we calculate the percentage of known epitopes that rank within the 5% peptides with the highest predicted score.</p> <p>Conclusion</p> <p>NetCTL-1.2 is demonstrated to have a higher predictive performance than EpiJen, MAPPP, MHC-pathway, and WAPP on all performance measures. The higher performance of NetCTL-1.2 as compared to EpiJen and MHC-pathway is, however, not statistically significant on all measures. In the large-scale benchmark calculation consisting of 216 known HIV epitopes covering all 12 recognized HLA supertypes, the NetCTL-1.2 method was shown to have a sensitivity among the 5% top-scoring peptides above 0.72. On this dataset, the best of the other methods achieved a sensitivity of 0.64. The NetCTL-1.2 method is available at <url>http://www.cbs.dtu.dk/services/NetCTL</url>.</p> <p>All used datasets are available at <url>http://www.cbs.dtu.dk/suppl/immunology/CTL-1.2.php</url>.</p

Inherent Grading Characteristics of Individual Pathologists Contribute to Clinically and Prognostically Relevant Interobserver Discordance Concerning Broders' Grading of Penile Squamous Cell Carcinomas

Introduction: The aim of our study was to evaluate the significance of transurethral resection of the prostate (TURP) to detect prostate cancer (PCa). A comparison was performed of the TURP specimens of patients undergoing high-intensity focused ultrasound (HIFU) with the core biopsies. Materials and Methods: TURP before undergoing HIFU therapy was performed in 106 patients without neoadjuvant treatment. The resected tissue was subjected to histopathological evaluation and compared to the histological results of transrectal prostate biopsy. Results: Cancer was detected in the resected tissue of 69 patients (65%). A positive correlation of the amount of resected tissue and detection of PCa could be demonstrated in a multivariate analysis. Conclusions: With a rate of 65% PCa detected by TURP, our data provide evidence that TURP might be suitable to detect PCa in a small group of selected patients with continuously rising PSA levels and several negative biopsies. On the other hand, these data underline/reinforce the necessity to treat the whole gland using modern treatment modalities such as HIFU and cryotherapy

NetCTLpan: pan-specific MHC class I pathway epitope predictions

Reliable predictions of immunogenic peptides are essential in rational vaccine design and can minimize the experimental effort needed to identify epitopes. In this work, we describe a pan-specific major histocompatibility complex (MHC) class I epitope predictor, NetCTLpan. The method integrates predictions of proteasomal cleavage, transporter associated with antigen processing (TAP) transport efficiency, and MHC class I binding affinity into a MHC class I pathway likelihood score and is an improved and extended version of NetCTL. The NetCTLpan method performs predictions for all MHC class I molecules with known protein sequence and allows predictions for 8-, 9-, 10-, and 11-mer peptides. In order to meet the need for a low false positive rate, the method is optimized to achieve high specificity. The method was trained and validated on large datasets of experimentally identified MHC class I ligands and cytotoxic T lymphocyte (CTL) epitopes. It has been reported that MHC molecules are differentially dependent on TAP transport and proteasomal cleavage. Here, we did not find any consistent signs of such MHC dependencies, and the NetCTLpan method is implemented with fixed weights for proteasomal cleavage and TAP transport for all MHC molecules. The predictive performance of the NetCTLpan method was shown to outperform other state-of-the-art CTL epitope prediction methods. Our results further confirm the importance of using full-type human leukocyte antigen restriction information when identifying MHC class I epitopes. Using the NetCTLpan method, the experimental effort to identify 90% of new epitopes can be reduced by 15% and 40%, respectively, when compared to the NetMHCpan and NetCTL methods. The method and benchmark datasets are available at http://www.cbs.dtu.dk/services/NetCTLpan/

European Association of Urology Guidelines Office Rapid Reaction Group: An Organisation-wide Collaborative Effort to Adapt the European Association of Urology Guidelines Recommendations to the Coronavirus Disease 2019 Era

The coronavirus disease 2019 (COVID-19) pandemic is unlike anything seen before by modern science-based medicine. As a scientific society, the European Association of Urology, via the guidelines, section offices, and the European Urology family of journals, we believe that it is important that we try to support urologists in this difficult situation. We aim to do this by providing tools that can facilitate decision making with the goal to minimise the impact and risks for both patients and health professionals delivering urological care, whenever possible, although it is clear that it is not always possible to mitigate them entirely. We hope that these revised recommendations will fill an important urological practice void and assist urologist surgeons across the globe as they do their very best to deal with the crisis of our generation