2012 Briganti nomogram predict prostate cancer progression in EAU intermediate risk with unfavorable tumor grade: A single center experience.

BACKGROUND: To investigate the potential prognostic impact of Briganti's 2012 nomogram in EAU intermediate-risk patients presenting with an unfavorable tumor grade and treated with robot-assisted radical prostatectomy, eventually associated with extended pelvic lymph node dissection. MATERIALS AND METHODS: From January 2013 to December 2021, the study included 179 EAU intermediate-risk patients presenting with an unfavorable tumor grade (ISUP 3), eventually associated with a PSA of 10-20 ng/ml and/or cT-2b. Briganti's 2012 nomogram was assessed as both a continuous and dichotomous variable, categorized according to the median (risk score ⩾7% vs <7%). Disease progression, defined as biochemical recurrence and/or metastatic progression, was evaluated using Cox proportional hazards in both univariate and multivariate analyses. RESULTS: Disease progression occurred in 43 (24%) patients after a median (95% CI) follow-up of 78 (65.7-88.4) months. The nomogram risk score predicted disease progression, evaluated both as a continuous variable (hazard ratio, HR = 1.064; 95% CI: 1.035-1.093; p < 0.0001) and as a categorical variable (HR = 3.399; 95% CI: 1.740-6.638; p < 0.0001). This association was confirmed in multivariate analysis, where hazard ratios remained consistent even after adjusting for clinical and pathological factors. CONCLUSIONS: In EAU intermediate-risk PCa cases presenting with an unfavorable tumor grade and treated surgically, Briganti's 2012 nomogram was associated with disease progression after surgery. Consequently, as the nomogram risk score increased, patients were more likely to experience PCa progression, facilitating the stratification of the patient population into distinct prognostic subgroups.

Intraoperative Performance of DaVinci Versus Hugo RAS During Radical Prostatectomy: Focus on Timing, Malfunctioning, Complications, and User Satisfaction in 100 Consecutive Cases (the COMPAR-P Trial).

Background and objective: The Hugo RAS and DaVinci Xi systems are used for performing robot-assisted radical prostatectomy (RARP). This study aims to compare these two platforms providing granular and comprehensive data on their intraoperative performance. Methods: The Comparison of Outcomes of Multiple Platforms for Assisted Robotic surgery-Prostate (COMPAR-P) trial is a prospective post-market study (clinicaltrials.org NCT05766163). Enrollment began in March 2023, allocating patients to DaVinci or Hugo RAS for RARP, without selection criteria, for up to 50 consecutive cases. Two experienced console surgeons performed the procedures, following the same technique. Evaluation focused on timing, learning curves, malfunctioning events, complications, and users' satisfaction, using standard statistical methods, including the cumulative summation analysis (CUSUM) for the learning curve assessment. Key findings and limitations: Fifty patients each were enrolled for DaVinci (DV-RARP) and Hugo RAS (H-RARP) RARP. Baseline features were balanced. DV-RARP showed significantly shorter "setup" and "console" phase durations than H-RARP (37 vs 55 min and 97 vs 126 min, respectively, p < 0.001). A longitudinal timing analysis revealed DV-RARP's flat line, while H-RARP showed a modest decline with breakpoints at 22 and 17 procedures by CUSUM for the setup and console phases. The numbers of malfunctioning events were 4 (DV-RARP) and 20 (H-RARP). DV-RARP had high user satisfaction, while the user satisfaction of H-RARP varied. The comparison was between the first 50 H-RARP and the last 50 DV-RARP cases performed at our institution. This likely accounts for the observed differences in setup and console times between the cohorts. The specialized expertise of the surgeons involved could limit the generalizability of our findings. Conclusions and clinical implications: This prospective study compared unselected patients who underwent DV-RARP and H-RARP. More malfunctioning events occurred in case of Hugo RAS, but surgical outcomes were similar. Longer operative times for Hugo RAS were attributed to meticulous care with the novel platform. Improvement potential was evident within a few procedures, providing valuable insights for adopting this new platform. Patient summary: This study compared two advanced robotic systems, DaVinci and Hugo RAS, used to remove the prostate in patients diagnosed with prostate cancer. While both systems showed similar surgical outcomes, the newer Hugo RAS system required more meticulous movements, leading to slightly longer operation times. The findings suggest that, with further experience, both systems can provide effective treatment options for patients undergoing prostate surgery.

Co-designed mini-games for children with visual impairment: a pilot study on their usability.

Digital games aimed at improving cognitive and/or motor-sensory skills need to be carefully designed to take into account the characteristics and needs of particular categories of users. Several novel mini-games explicitly aimed at children with visual impairment (VI) were co-designed by a multidisciplinary team which involved computer engineers and a therapy team from the Robert Hollman Foundation (Padova, Italy). These games are played by children moving within a large-scale interactive environment - i.e., a floor portion placed under a motion capture system capable of tracking one or more people - with the game linking the players movements to the audio and visual output to produce meaningful interactions. We report on a pilot study of the usability of the system involving 11 children with VI. The results allowed us to improve the system and to define a set of guidelines useful for designers and developers of similar systems. Supplementary Information: The online version contains supplementary material available at 10.1007/s11042-022-13665-7.

Sequence-Specific Features of Short Double-Strand, Blunt-End RNAs Have RIG-I- and Type 1 Interferon-Dependent or -Independent Anti-Viral Effects.

Pathogen-associated molecular patterns, including cytoplasmic DNA and double-strand (ds)RNA trigger the induction of interferon (IFN) and antiviral states protecting cells and organisms from pathogens. Here we discovered that the transfection of human airway cell lines or non-transformed fibroblasts with 24mer dsRNA mimicking the cellular micro-RNA (miR)29b-1* gives strong anti-viral effects against human adenovirus type 5 (AdV-C5), influenza A virus X31 (H3N2), and SARS-CoV-2. These anti-viral effects required blunt-end complementary RNA strands and were not elicited by corresponding single-strand RNAs. dsRNA miR-29b-1* but not randomized miR-29b-1* mimics induced IFN-stimulated gene expression, and downregulated cell adhesion and cell cycle genes, as indicated by transcriptomics and IFN-I responsive Mx1-promoter activity assays. The inhibition of AdV-C5 infection with miR-29b-1* mimic depended on the IFN-alpha receptor 2 (IFNAR2) and the RNA-helicase retinoic acid-inducible gene I (RIG-I) but not cytoplasmic RNA sensors MDA5 and ZNFX1 or MyD88/TRIF adaptors. The antiviral effects of miR29b-1* were independent of a central AUAU-motif inducing dsRNA bending, as mimics with disrupted AUAU-motif were anti-viral in normal but not RIG-I knock-out (KO) or IFNAR2-KO cells. The screening of a library of scrambled short dsRNA sequences identified also anti-viral mimics functioning independently of RIG-I and IFNAR2, thus exemplifying the diverse anti-viral mechanisms of short blunt-end dsRNAs.

SVD-phy: improved prediction of protein functional associations through singular value decomposition of phylogenetic profiles.

UNLABELLED: A successful approach for predicting functional associations between non-homologous genes is to compare their phylogenetic distributions. We have devised a phylogenetic profiling algorithm, SVD-Phy, which uses truncated singular value decomposition to address the problem of uninformative profiles giving rise to false positive predictions. Benchmarking the algorithm against the KEGG pathway database, we found that it has substantially improved performance over existing phylogenetic profiling methods. AVAILABILITY AND IMPLEMENTATION: The software is available under the open-source BSD license at https://bitbucket.org/andrea/svd-phy CONTACT: lars.juhl.jensen@cpr.ku.dk SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

STRING v10: protein-protein interaction networks, integrated over the tree of life.

The many functional partnerships and interactions that occur between proteins are at the core of cellular processing and their systematic characterization helps to provide context in molecular systems biology. However, known and predicted interactions are scattered over multiple resources, and the available data exhibit notable differences in terms of quality and completeness. The STRING database (http://string-db.org) aims to provide a critical assessment and integration of protein-protein interactions, including direct (physical) as well as indirect (functional) associations. The new version 10.0 of STRING covers more than 2000 organisms, which has necessitated novel, scalable algorithms for transferring interaction information between organisms. For this purpose, we have introduced hierarchical and self-consistent orthology annotations for all interacting proteins, grouping the proteins into families at various levels of phylogenetic resolution. Further improvements in version 10.0 include a completely redesigned prediction pipeline for inferring protein-protein associations from co-expression data, an API interface for the R computing environment and improved statistical analysis for enrichment tests in user-provided networks.

Genome-wide small interfering RNA screens reveal VAMP3 as a novel host factor required for Uukuniemi virus late penetration.

UNLABELLED: The Bunyaviridae constitute a large family of enveloped animal viruses, many of which are important emerging pathogens. How bunyaviruses enter and infect mammalian cells remains largely uncharacterized. We used two genome-wide silencing screens with distinct small interfering RNA (siRNA) libraries to investigate host proteins required during infection of human cells by the bunyavirus Uukuniemi virus (UUKV), a late-penetrating virus. Sequence analysis of the libraries revealed that many siRNAs in the screens inhibited infection by silencing not only the intended targets but additional genes in a microRNA (miRNA)-like manner. That the 7-nucleotide seed regions in the siRNAs can cause a perturbation in infection was confirmed by using synthetic miRNAs (miRs). One of the miRs tested, miR-142-3p, was shown to interfere with the intracellular trafficking of incoming viruses by regulating the v-SNARE VAMP3, a strong hit shared by both siRNA screens. Inactivation of VAMP3 by the tetanus toxin led to a block in infection. Using fluorescence-based techniques in fixed and live cells, we found that the viruses enter VAMP3(+) endosomal vesicles 5 min after internalization and that colocalization was maximal 15 min thereafter. At this time, LAMP1 was associated with the VAMP3(+) virus-containing endosomes. In cells depleted of VAMP3, viruses were mainly trapped in LAMP1-negative compartments. Together, our results indicated that UUKV relies on VAMP3 for penetration, providing an indication of added complexity in the trafficking of viruses through the endocytic network. IMPORTANCE: Bunyaviruses represent a growing threat to humans and livestock globally. Unfortunately, relatively little is known about these emerging pathogens. We report here the first human genome-wide siRNA screens for a bunyavirus. The screens resulted in the identification of 562 host cell factors with a potential role in cell entry and virus replication. To demonstrate the robustness of our approach, we confirmed and analyzed the role of the v-SNARE VAMP3 in Uukuniemi virus entry and infection. The information gained lays the basis for future research into the cell biology of bunyavirus infection and new antiviral strategies. In addition, by shedding light on serious caveats in large-scale siRNA screening, our experimental and bioinformatics procedures will be valuable in the comprehensive analysis of past and future high-content screening data.

Specific inhibition of diverse pathogens in human cells by synthetic microRNA-like oligonucleotides inferred from RNAi screens.

Systematic genetic perturbation screening in human cells remains technically challenging. Typically, large libraries of chemically synthesized siRNA oligonucleotides are used, each designed to degrade a specific cellular mRNA via the RNA interference (RNAi) mechanism. Here, we report on data from three genome-wide siRNA screens, conducted to uncover host factors required for infection of human cells by two bacterial and one viral pathogen. We find that the majority of phenotypic effects of siRNAs are unrelated to the intended "on-target" mechanism, defined by full complementarity of the 21-nt siRNA sequence to a target mRNA. Instead, phenotypes are largely dictated by "off-target" effects resulting from partial complementarity of siRNAs to multiple mRNAs via the "seed" region (i.e., nucleotides 2-8), reminiscent of the way specificity is determined for endogenous microRNAs. Quantitative analysis enabled the prediction of seeds that strongly and specifically block infection, independent of the intended on-target effect. This prediction was confirmed experimentally by designing oligos that do not have any on-target sequence match at all, yet can strongly reproduce the predicted phenotypes. Our results suggest that published RNAi screens have primarily, and unintentionally, screened the sequence space of microRNA seeds instead of the intended on-target space of protein-coding genes. This helps to explain why previously published RNAi screens have exhibited relatively little overlap. Our analysis suggests a possible way of identifying "seed reagents" for controlling phenotypes of interest and establishes a general strategy for extracting valuable untapped information from past and future RNAi screens.

HCV infected prisoners: should they be still considered a difficult to treat population?

BACKGROUND: The prevalence of chronic hepatitis C virus (HCV) infection in the Italian correctional population is estimated to be around 38%. In this setting HCV infection treatment is controversial because of several factors such as active drug substance abuse, psychiatric illness, length of treatment, risk of re-infection, poor adherence and low success rate. METHODS: A retrospective data review of 159 inmates, positive for anti-Hepatitis C virus (HCV) antibody, evaluated to National Institute for Infectious Diseases "L. Spallanzani" (INMI) from January 2006 to December 2009, was conducted to evaluate rate of completion (feasibility) and outcome efficacy of chronic Hepatitis C Virus (HCV) infection treatment with Pegylated Interferon and Ribavirin in five correctional facilities in Rome. RESULTS: Of the 159 inmates evaluated in the study period, 50, all male (median age 39 years) were treated. Twenty patients (40%) did not complete treatment: 15 showed no response and therapy was stopped, 5 patients (10%) interrupted treatment because of adverse reactions. The global feasibility was 60%. The overall sustained virologic response (SVR) was 50% (32% for genotype 1 and 68% for genotype other than 1). The main predictors of SVR at the Multivariable Logistic Regression Odds Ratio (MLR-OR) were a better pretreatment histological diagnosis (absence of bridging fibrosis or cirrhosis [MLR-OR 11.85; 95% CI 1.96-71.62) and a HCV genotype other than 1 (MLR-OR 5.87; 95% CI 1.49-23.17). CONCLUSIONS: Chronic HCV infection treatment in correctional facilities is feasible and effective and should be strongly recommended, in combination with preventive measures, in appropriately screened patients because it represents an important opportunity to treat a population with a high prevalence of chronic HCV infection among whom treatment options post incarceration may be limited.

STRING v9.1: protein-protein interaction networks, with increased coverage and integration.

Complete knowledge of all direct and indirect interactions between proteins in a given cell would represent an important milestone towards a comprehensive description of cellular mechanisms and functions. Although this goal is still elusive, considerable progress has been made-particularly for certain model organisms and functional systems. Currently, protein interactions and associations are annotated at various levels of detail in online resources, ranging from raw data repositories to highly formalized pathway databases. For many applications, a global view of all the available interaction data is desirable, including lower-quality data and/or computational predictions. The STRING database (http://string-db.org/) aims to provide such a global perspective for as many organisms as feasible. Known and predicted associations are scored and integrated, resulting in comprehensive protein networks covering >1100 organisms. Here, we describe the update to version 9.1 of STRING, introducing several improvements: (i) we extend the automated mining of scientific texts for interaction information, to now also include full-text articles; (ii) we entirely re-designed the algorithm for transferring interactions from one model organism to the other; and (iii) we provide users with statistical information on any functional enrichment observed in their networks.

STITCH 3: zooming in on protein-chemical interactions.

To facilitate the study of interactions between proteins and chemicals, we have created STITCH, an aggregated database of interactions connecting over 300,000 chemicals and 2.6 million proteins from 1133 organisms. Compared to the previous version, the number of chemicals with interactions and the number of high-confidence interactions both increase 4-fold. The database can be accessed interactively through a web interface, displaying interactions in an integrated network view. It is also available for computational studies through downloadable files and an API. As an extension in the current version, we offer the option to switch between two levels of detail, namely whether stereoisomers of a given compound are shown as a merged entity or as separate entities. Separate display of stereoisomers is necessary, for example, for carbohydrates and chiral drugs. Combining the isomers increases the coverage, as interaction databases and publications found through text mining will often refer to compounds without specifying the stereoisomer. The database is accessible at http://stitch.embl.de/.

The STRING database in 2011: functional interaction networks of proteins, globally integrated and scored.

An essential prerequisite for any systems-level understanding of cellular functions is to correctly uncover and annotate all functional interactions among proteins in the cell. Toward this goal, remarkable progress has been made in recent years, both in terms of experimental measurements and computational prediction techniques. However, public efforts to collect and present protein interaction information have struggled to keep up with the pace of interaction discovery, partly because protein-protein interaction information can be error-prone and require considerable effort to annotate. Here, we present an update on the online database resource Search Tool for the Retrieval of Interacting Genes (STRING); it provides uniquely comprehensive coverage and ease of access to both experimental as well as predicted interaction information. Interactions in STRING are provided with a confidence score, and accessory information such as protein domains and 3D structures is made available, all within a stable and consistent identifier space. New features in STRING include an interactive network viewer that can cluster networks on demand, updated on-screen previews of structural information including homology models, extensive data updates and strongly improved connectivity and integration with third-party resources. Version 9.0 of STRING covers more than 1100 completely sequenced organisms; the resource can be reached at http://string-db.org.

STITCH 2: an interaction network database for small molecules and proteins.

Over the last years, the publicly available knowledge on interactions between small molecules and proteins has been steadily increasing. To create a network of interactions, STITCH aims to integrate the data dispersed over the literature and various databases of biological pathways, drug-target relationships and binding affinities. In STITCH 2, the number of relevant interactions is increased by incorporation of BindingDB, PharmGKB and the Comparative Toxicogenomics Database. The resulting network can be explored interactively or used as the basis for large-scale analyses. To facilitate links to other chemical databases, we adopt InChIKeys that allow identification of chemicals with a short, checksum-like string. STITCH 2.0 connects proteins from 630 organisms to over 74,000 different chemicals, including 2200 drugs. STITCH can be accessed at http://stitch.embl.de/.

Statistical analysis of genomic protein family and domain controlled annotations for functional investigation of classified gene lists.

BACKGROUND: The increasing protein family and domain based annotations constitute important information to understand protein functions and gain insight into relations among their codifying genes. To allow analyzing of gene proteomic annotations, we implemented novel modules within GFINDer, a Web system we previously developed that dynamically aggregates functional and phenotypic annotations of user-uploaded gene lists and allows performing their statistical analysis and mining. RESULTS: Exploiting protein information in Pfam and InterPro databanks, we developed and added in GFINDer original modules specifically devoted to the exploration and analysis of functional signatures of gene protein products. They allow annotating numerous user-classified nucleotide sequence identifiers with controlled information on related protein families, domains and functional sites, classifying them according to such protein annotation categories, and statistically analyzing the obtained classifications. In particular, when uploaded nucleotide sequence identifiers are subdivided in classes, the Statistics Protein Families&Domains module allows estimating relevance of Pfam or InterPro controlled annotations for the uploaded genes by highlighting protein signatures significantly more represented within user-defined classes of genes. In addition, the Logistic Regression module allows identifying protein functional signatures that better explain the considered gene classification. CONCLUSION: Novel GFINDer modules provide genomic protein family and domain analyses supporting better functional interpretation of gene classes, for instance defined through statistical and clustering analyses of gene expression results from microarray experiments. They can hence help understanding fundamental biological processes and complex cellular mechanisms influenced by protein domain composition, and contribute to unveil new biomedical knowledge about the codifying genes.

Genomic functional investigation through statistical analysis of protein families and domains.

Protein families and domains represent a very relevant resource useful to understand protein functions and interactions among their codifying genes. To perform evaluations of gene annotations sparsely available in numerous different databanks accessible via Internet, we previously developed GFINDer, a Web server that performs statistical analysis of functional and phenotypic annotations of gene lists. To exploit protein information present in Pfam and InterPro databanks, in GFINDer we integrated two new modules, that allow to annotate and statistically analyze user-classified nucleotide sequence with controlled information on related protein families, domains and functional sites.