Nanosuspensions and microneedles roller as a combined approach to enhance diclofenac topical bioavailability

Topical application of the anti-inflammatory drug diclofenac (DCF) reduces the severity of systemic unwanted effects compared to its oral administration. A number of transdermal formulations are available on the market and routinely used in clinical and home-care settings. However, the amount of DCF delivered across the skin remains limited and often insufficient, thus making the oral route still necessary for achieving sufficient drug concentration at the inflamed site. In attempting to improve the transdermal penetration, we explored the combined use of DCF nanosuspensions with a microneedle roller. Firstly, DCF nanosuspensions were prepared by a top-down media milling method and characterized by spectroscopic, thermal and electron microscopy analyses. Secondly, the pore-forming action of microneedle rollers on skin specimens (ex vivo) was described by imaging at different scales. Finally, DCF nanosuspensions were applied on newborn pig skin (in vitro) in combination with microneedles roller treatment, assessing the DCF penetration and distribution in the different skin layers. The relative contribution of microneedle length, nanosuspension stabilizer and application sequence could be identified by systemically varying these parameters

The deficit bias: Candidate gender differences in the relative importance of facial stereotypic qualities for leadership hiring

This is the final version. Available on open access from Wiley via the DOI in this recordData availability: The authors confirm that the data supporting the main findings of this research are available online within the supporting information.Recent findings highlight two facets of the two fundamental stereotype content dimensions of agency (i.e., ‘dominance’ and ‘competence’) and communality (i.e., ‘morality’ and ‘sociability’; e.g., Abele et al., 2016) with implications for understanding gender inequality in the workplace (e.g., Prati et al., 2019). Extending this research and contributing to the facial first impressions literature, we examined how these facets of agency and communality when inferred from White men’s and women’s faces, along with attractiveness, influence their leadership suitability. In three studies in the UK (total N = 424), using student and working samples and two managerial descriptions, we found an unexpected pattern of results, supported by an internal meta-analysis: attractiveness and competence were the most important predictors of hirability for all candidates. For women, dominance was the next most important predictor; for men, morality and sociability were more important than dominance. Moreover, morality and sociability were more important in evaluating men than women, whilst dominance was more important in evaluating women than men. Findings are discussed in terms of a ‘deficit bias’, whereby the qualities women and men are considered to lack – dominance for women, morality and sociability for men – may be given more weight when evaluating their leadership suitability.European CommissionItalian Ministry of Education, Universities and Research (MIUR)European Association of Social Psycholog

Transcutol® p containing slns for improving 8-methoxypsoralen skin delivery

Topical psoralens plus ultraviolet A radiation (PUVA) therapy consists in the topical application of 8-methoxypsoralen (8-MOP) followed by the skin irradiation with ultraviolet A radiation. The employment of classical 8-MOP vehicles in topical PUVA therapy is associated with poor skin deposition and weak skin permeability of psoralens, thus requiring frequent drug administration. The aim of the present work was to formulate solid lipid nanoparticles (SLNs) able to increase the skin permeation of 8-MOP. For this purpose, the penetration enhancer Transcutol® P (TRC) was added to the SLN formulation. SLNs were characterized with respect to size, polydispersity index, zeta potential, entrapment efficiency, morphology, stability, and biocompatibility. Finally, 8-MOP skin diffusion and distribution within the skin layers was investigated using Franz cells and newborn pig skin. Freshly prepared nanoparticles showed spherical shape, mean diameters ranging between 120 and 133 nm, a fairly narrow size distribution, highly negative ζ potential values, and high entrapment efficiency. Empty and loaded formulations were almost stable over 30 days. In vitro penetration and permeation studies demonstrated a greater 8-MOP accumulation in each skin layer after SLN TRC 2% and TRC 4% application than that after SLN TRC 0% application. Finally, the results of experiments on 3T3 fibroblasts showed that the incorporation of TRC into SLNs could enhance the cellular uptake of nanoparticles, but it did not increase their cytotoxicity

Recording provenance of workflow runs with RO-Crate

Recording the provenance of scientific computation results is key to the support of traceability, reproducibility and quality assessment of data products.Several data models have been explored to address this need, providing representations of workflow plans and their executions as well as means of packaging the resulting information for archiving and sharing.However, existing approaches tend to lack interoperable adoption across workflow management systems.In this work we present Workflow Run RO-Crate, an extension of RO-Crate (Research Object Crate) and Schema.org to capture the provenance of the execution of computational workflows at different levels of granularity and bundle together all their associated objects (inputs, outputs, code, etc.).The model is supported by a diverse, open community that runs regular meetings, discussing development, maintenance and adoption aspects.Workflow Run RO-Crate is already implemented by several workflow management systems, allowing interoperable comparisons between workflow runs from heterogeneous systems.We describe the model, its alignment to standards such as W3C PROV, and its implementation in six workflow systems.Finally, we illustrate the application of Workflow Run RO-Crate in two use cases of machine learning in the digital image analysis domain.A corresponding RO-Crate for this article is at https://w3id.org/ro/doi/10.5281/zenodo.1036898

Cohort profile: the Turin prostate cancer prognostication (TPCP) cohort

Introduction: Prostate cancer (PCa) is the most frequent tumor among men in Europe and has both indolent and aggressive forms. There are several treatment options, the choice of which depends on multiple factors. To further improve current prognostication models, we established the Turin Prostate Cancer Prognostication (TPCP) cohort, an Italian retrospective biopsy cohort of patients with PCa and long-term follow-up. This work presents this new cohort with its main characteristics and the distributions of some of its core variables, along with its potential contributions to PCa research. Methods: The TPCP cohort includes consecutive non-metastatic patients with first positive biopsy for PCa performed between 2008 and 2013 at the main hospital in Turin, Italy. The follow-up ended on December 31st 2021. The primary outcome is the occurrence of metastasis; death from PCa and overall mortality are the secondary outcomes. In addition to numerous clinical variables, the study’s prognostic variables include histopathologic information assigned by a centralized uropathology review using a digital pathology software system specialized for the study of PCa, tumor DNA methylation in candidate genes, and features extracted from digitized slide images via Deep Neural Networks. Results: The cohort includes 891 patients followed-up for a median time of 10 years. During this period, 97 patients had progression to metastatic disease and 301 died; of these, 56 died from PCa. In total, 65.3% of the cohort has a Gleason score less than or equal to 3 + 4, and 44.5% has a clinical stage cT1. Consistent with previous studies, age and clinical stage at diagnosis are important prognostic factors: the crude cumulative incidence of metastatic disease during the 14-years of follow-up increases from 9.1% among patients younger than 64 to 16.2% for patients in the age group of 75-84, and from 6.1% for cT1 stage to 27.9% in cT3 stage. Discussion: This study stands to be an important resource for updating existing prognostic models for PCa on an Italian cohort. In addition, the integrated collection of multi-modal data will allow development and/or validation of new models including new histopathological, digital, and molecular markers, with the goal of better directing clinical decisions to manage patients with PCa

ComPath: comparative enzyme analysis and annotation in pathway/subsystem contexts

<p>Abstract</p> <p>Background</p> <p>Once a new genome is sequenced, one of the important questions is to determine the presence and absence of biological pathways. Analysis of biological pathways in a genome is a complicated task since a number of biological entities are involved in pathways and biological pathways in different organisms are not identical. Computational pathway identification and analysis thus involves a number of computational tools and databases and typically done in comparison with pathways in other organisms. This computational requirement is much beyond the capability of biologists, so information systems for reconstructing, annotating, and analyzing biological pathways are much needed. We introduce a new comparative pathway analysis workbench, ComPath, which integrates various resources and computational tools using an interactive spreadsheet-style web interface for reliable pathway analyses.</p> <p>Results</p> <p>ComPath allows users to compare biological pathways in multiple genomes using a spreadsheet style web interface where various sequence-based analysis can be performed either to compare enzymes (e.g. sequence clustering) and pathways (e.g. pathway hole identification), to search a genome for <it>de novo </it>prediction of enzymes, or to annotate a genome in comparison with reference genomes of choice. To fill in pathway holes or make <it>de novo </it>enzyme predictions, multiple computational methods such as FASTA, Whole-HMM, CSR-HMM (a method of our own introduced in this paper), and PDB-domain search are integrated in ComPath. Our experiments show that FASTA and CSR-HMM search methods generally outperform Whole-HMM and PDB-domain search methods in terms of sensitivity, but FASTA search performs poorly in terms of specificity, detecting more false positive as E-value cutoff increases. Overall, CSR-HMM search method performs best in terms of both sensitivity and specificity. Gene neighborhood and pathway neighborhood (global network) visualization tools can be used to get context information that is complementary to conventional KEGG map representation.</p> <p>Conclusion</p> <p>ComPath is an interactive workbench for pathway reconstruction, annotation, and analysis where experts can perform various sequence, domain, context analysis, using an intuitive and interactive spreadsheet-style interface. </p

Interoperable and scalable data analysis with microservices: applications in metabolomics.

Developing a robust and performant data analysis workflow that integrates all necessary components whilst still being able to scale over multiple compute nodes is a challenging task. We introduce a generic method based on the microservice architecture, where software tools are encapsulated as Docker containers that can be connected into scientific workflows and executed using the Kubernetes container orchestrator. We developed a Virtual Research Environment (VRE) which facilitates rapid integration of new tools and developing scalable and interoperable workflows for performing metabolomics data analysis. The environment can be launched on-demand on cloud resources and desktop computers. IT-expertise requirements on the user side are kept to a minimum, and workflows can be re-used effortlessly by any novice user. We validate our method in the field of metabolomics on two mass spectrometry, one nuclear magnetic resonance spectroscopy and one fluxomics study. We showed that the method scales dynamically with increasing availability of computational resources. We demonstrated that the method facilitates interoperability using integration of the major software suites resulting in a turn-key workflow encompassing all steps for mass-spectrometry-based metabolomics including preprocessing, statistics and identification. Microservices is a generic methodology that can serve any scientific discipline and opens up for new types of large-scale integrative science. The PhenoMeNal consortium maintains a web portal (https://portal.phenomenal-h2020.eu) providing a GUI for launching the Virtual Research Environment. The GitHub repository https://github.com/phnmnl/ hosts the source code of all projects. Supplementary data are available at Bioinformatics online

HSRA: Hadoop-based spliced read aligner for RNA sequencing data

[Abstract] Nowadays, the analysis of transcriptome sequencing (RNA-seq) data has become the standard method for quantifying the levels of gene expression. In RNA-seq experiments, the mapping of short reads to a reference genome or transcriptome is considered a crucial step that remains as one of the most time-consuming. With the steady development of Next Generation Sequencing (NGS) technologies, unprecedented amounts of genomic data introduce significant challenges in terms of storage, processing and downstream analysis. As cost and throughput continue to improve, there is a growing need for new software solutions that minimize the impact of increasing data volume on RNA read alignment. In this work we introduce HSRA, a Big Data tool that takes advantage of the MapReduce programming model to extend the multithreading capabilities of a state-of-the-art spliced read aligner for RNA-seq data (HISAT2) to distributed memory systems such as multi-core clusters or cloud platforms. HSRA has been built upon the Hadoop MapReduce framework and supports both single- and paired-end reads from FASTQ/FASTA datasets, providing output alignments in SAM format. The design of HSRA has been carefully optimized to avoid the main limitations and major causes of inefficiency found in previous Big Data mapping tools, which cannot fully exploit the raw performance of the underlying aligner. On a 16-node multi-core cluster, HSRA is on average 2.3 times faster than previous Hadoop-based tools. Source code in Java as well as a user’s guide are publicly available for download at http://hsra.dec.udc.es.Ministerio de Economía, Industria y Competitividad; TIN2016-75845-PXunta de Galicia; ED431G/0

Guideline Application in Real world: multi-Institutional Based survey of Adjuvant and first-Line pancreatic Ductal adenocarcinoma treatment in Italy. Primary analysis of the GARIBALDI survey

Background: Information about the adherence to scientific societies guidelines in the ‘real-world’ therapeutic management of oncological patients are lacking. This multicenter, prospective survey was aimed to improve the knowledge relative to 2017-2018 recommendations of the Italian Association of Medical Oncology (AIOM). Patients and methods: Treatment-naive adult patients with pancreatic adenocarcinoma were enrolled. Group A received adjuvant therapy, group B received primary chemotherapy, and group C had metastatic disease. The results on patients accrued until 31 October 2019 with a mature follow-up were presented. Results: Since July 2017, 833 eligible patients of 923 (90%) were enrolled in 44 Italian centers. The median age was 69 years (range 36-89 years; 24% &gt;75 years); 48% were female; 93% had Eastern Cooperative Oncology Group (ECOG) performance status (PS) score of 0 or 1; group A: 16%, group B: 30%; group C: 54%; 72% Nord, 13% Center, 15% South. In group A, guidelines adherence was 68% [95% confidence interval (CI) 59% to 76%]; 53% of patients received gemcitabine and 15% gemcitabine + capecitabine; median CA19.9 was 29 (range 0-7300; not reported 15%); median survival was 36.4 months (95% CI 27.5-47.3 months). In group B, guidelines adherence was 96% (95% CI 92% to 98%); 55% of patients received nab-paclitaxel + gemcitabine, 27% FOLFIRINOX, 12% gemcitabine, and 3% clinical trial; median CA19.9 was 337 (range 0-20220; not reported 9%); median survival was 18.1 months (95% CI 15.6-19.9 months). In group C, guidelines adherence was 96% (95% CI 94% to 98%); 71% of patients received nab-paclitaxel + gemcitabine, 16% gemcitabine, 8% FOLFIRINOX, and 4% clinical trial; liver and lung metastases were reported in 76% and 23% of patients, respectively; median CA19.9 value was 760 (range 0-1374500; not reported 9%); median survival was 10.0 months (95% CI 9.1-11.1 months). Conclusions: The GARIBALDI survey shows a very high rate of adherence to guidelines and survival outcome in line with the literature. CA19.9 testing should be enhanced; nutritional and psychological counseling represent an unmet need. Enrollment to assess adherence to updated AIOM guidelines is ongoing