Transcriptomic analysis of cutaneous squamous cell carcinoma reveals a multi-gene prognostic signature associated with metastasis

Background: Metastasis of cutaneous squamous cell carcinoma (cSCC) is uncommon. Current staging methods are reported to have sub-optimal performances in metastasis prediction. Accurate identification of patients with tumours at high risk of metastasis would have a significant impact on management.Objective: To develop a robust and validated gene expression profile (GEP) signature for predicting primary cSCC metastatic risk using an unbiased whole transcriptome discovery-driven approach.Methods: Archival formalin-fixed paraffin-embedded primary cSCC with perilesional normal tissue from 237 immunocompetent patients (151 non-metastasising and 86 metastasising) were collected retrospectively from four centres. TempO-seq was used to probe the whole transcriptome and machine learning algorithms were applied to derive predictive signatures, with a 3:1 split for training and testing datasets.Results: A 20-gene prognostic model was developed and validated, with an accuracy of 86.0%, sensitivity of 85.7%, specificity of 86.1%, and positive predictive value of 78.3% in the testing set, providing more stable, accurate prediction than pathological staging systems. A linear predictor was also developed, significantly correlating with metastatic risk.Limitations: This was a retrospective 4-centre study and larger prospective multicentre studies are now required.Conclusion: The 20-gene signature prediction is accurate, with the potential to be incorporated into clinical workflows for cSCC

Roadmap on Li-ion battery manufacturing research

Growth in the Li-ion battery market continues to accelerate, driven primarily by the increasing need for economic energy storage for electric vehicles. Electrode manufacture by slurry casting is the first main step in cell production but much of the manufacturing optimisation is based on trial and error, know-how and individual expertise. Advancing manufacturing science that underpins Li-ion battery electrode production is critical to adding to the electrode manufacturing value chain. Overcoming the current barriers in electrode manufacturing requires advances in materials, manufacturing technology, in-line process metrology and data analytics, and can enable improvements in cell performance, quality, safety and process sustainability. In this roadmap we explore the research opportunities to improve each stage of the electrode manufacturing process, from materials synthesis through to electrode calendering. We highlight the role of new process technology, such as dry processing, and advanced electrode design supported through electrode level, physics-based modelling. Progress in data driven models of electrode manufacturing processes is also considered. We conclude there is a growing need for innovations in process metrology to aid fundamental understanding and to enable feedback control, an opportunity for electrode design to reduce trial and error, and an urgent imperative to improve the sustainability of manufacture

Improved general regression network for protein domain boundary prediction

Background: Protein domains present some of the most useful information that can be used to understand protein structure and functions. Recent research on protein domain boundary prediction has been mainly based on widely known machine learning techniques, such as Artificial Neural Networks and Support Vector Machines. In this study, we propose a new machine learning model (IGRN) that can achieve accurate and reliable classification, with significantly reduced computations. The IGRN was trained using a PSSM (Position Specific Scoring Matrix), secondary structure, solvent accessibility information and inter-domain linker index to detect possible domain boundaries for a target sequence. Results: The proposed model achieved average prediction accuracy of 67% on the Benchmark_2 dataset for domain boundary identification in multi-domains proteins and showed superior predictive performance and generalisation ability among the most widely used neural network models. With the CASP7 benchmark dataset, it also demonstrated comparable performance to existing domain boundary predictors such as DOMpro, DomPred, DomSSEA, DomCut and DomainDiscovery with 70.10% prediction accuracy. Conclusion: The performance of proposed model has been compared favourably to the performance of other existing machine learning based methods as well as widely known domain boundary predictors on two benchmark datasets and excels in the identification of domain boundaries in terms of model bias, generalisation and computational requirements. © 2008 Yoo et al; licensee BioMed Central Ltd

InterPro, progress and status in 2005

InterPro, an integrated documentation resource of protein families, domains and functional sites, was created to integrate the major protein signature databases. Currently, it includes PROSITE, Pfam, PRINTS, ProDom, SMART, TIGRFAMs, PIRSF and SUPERFAMILY. Signatures are manually integrated into InterPro entries that are curated to provide biological and functional information. Annotation is provided in an abstract, Gene Ontology mapping and links to specialized databases. New features of InterPro include extended protein match views, taxonomic range information and protein 3D structure data. One of the new match views is the InterPro Domain Architecture view, which shows the domain composition of protein matches. Two new entry types were introduced to better describe InterPro entries: these are active site and binding site. PIRSF and the structure-based SUPERFAMILY are the latest member databases to join InterPro, and CATH and PANTHER are soon to be integrated. InterPro release 8.0 contains 11 007 entries, representing 2573 domains, 8166 families, 201 repeats, 26 active sites, 21 binding sites and 20 post-translational modification sites. InterPro covers over 78% of all proteins in the Swiss-Prot and TrEMBL components of UniProt. The database is available for text- and sequence-based searches via a webserver (http://www.ebi.ac.uk/interpro), and for download by anonymous FTP (ftp://ftp.ebi.ac.uk/pub/databases/interpro)

New developments in the InterPro database

InterPro is an integrated resource for protein families, domains and functional sites, which integrates the following protein signature databases: PROSITE, PRINTS, ProDom, Pfam, SMART, TIGRFAMs, PIRSF, SUPERFAMILY, Gene3D and PANTHER. The latter two new member databases have been integrated since the last publication in this journal. There have been several new developments in InterPro, including an additional reading field, new database links, extensions to the web interface and additional match XML files. InterPro has always provided matches to UniProtKB proteins on the website and in the match XML file on the FTP site. Additional matches to proteins in UniParc (UniProt archive) are now available for download in the new match XML files only. The latest InterPro release (13.0) contains more than 13 000 entries, covering over 78% of all proteins in UniProtKB. The database is available for text- and sequence-based searches via a webserver (), and for download by anonymous FTP (). The InterProScan search tool is now also available via a web service at

Energetic Selection of Topology in Ferredoxins

Models of early protein evolution posit the existence of short peptides that bound metals and ions and served as transporters, membranes or catalysts. The Cys-X-X-Cys-X-X-Cys heptapeptide located within bacterial ferredoxins, enclosing an Fe4S4 metal center, is an attractive candidate for such an early peptide. Ferredoxins are ancient proteins and the simple α+β fold is found alone or as a domain in larger proteins throughout all three kingdoms of life. Previous analyses of the heptapeptide conformation in experimentally determined ferredoxin structures revealed a pervasive right-handed topology, despite the fact that the Fe4S4 cluster is achiral. Conformational enumeration of a model CGGCGGC heptapeptide bound to a cubane iron-sulfur cluster indicates both left-handed and right-handed folds could exist and have comparable stabilities. However, only the natural ferredoxin topology provides a significant network of backbone-to-cluster hydrogen bonds that would stabilize the metal-peptide complex. The optimal peptide configuration (alternating αL,αR) is that of an α-sheet, providing an additional mechanism where oligomerization could stabilize the peptide and facilitate iron-sulfur cluster binding

NOX1 loss-of-function genetic variants in patients with inflammatory bowel disease.

Genetic defects that affect intestinal epithelial barrier function can present with very early-onset inflammatory bowel disease (VEOIBD). Using whole-genome sequencing, a novel hemizygous defect in NOX1 encoding NAPDH oxidase 1 was identified in a patient with ulcerative colitis-like VEOIBD. Exome screening of 1,878 pediatric patients identified further seven male inflammatory bowel disease (IBD) patients with rare NOX1 mutations. Loss-of-function was validated in p.N122H and p.T497A, and to a lesser degree in p.Y470H, p.R287Q, p.I67M, p.Q293R as well as the previously described p.P330S, and the common NOX1 SNP p.D360N (rs34688635) variant. The missense mutation p.N122H abrogated reactive oxygen species (ROS) production in cell lines, ex vivo colonic explants, and patient-derived colonic organoid cultures. Within colonic crypts, NOX1 constitutively generates a high level of ROS in the crypt lumen. Analysis of 9,513 controls and 11,140 IBD patients of non-Jewish European ancestry did not reveal an association between p.D360N and IBD. Our data suggest that loss-of-function variants in NOX1 do not cause a Mendelian disorder of high penetrance but are a context-specific modifier. Our results implicate that variants in NOX1 change brush border ROS within colonic crypts at the interface between the epithelium and luminal microbes

Carotenoids Play a Positive Role in the Degradation of Heterocycles by Sphingobium yanoikuyae

BACKGROUND: Microbial oxidative degradation is a potential way of removing pollutants such as heterocycles from the environment. During this process, reactive oxygen species or other oxidants are inevitably produced, and may cause damage to DNA, proteins, and membranes, thereby decreasing the degradation rate. Carotenoids can serve as membrane-integrated antioxidants, protecting cells from oxidative stress. FINDINGS: Several genes involved in the carotenoid biosynthetic pathway were cloned and characterized from a carbazole-degrading bacterium Sphingobium yanoikuyae XLDN2-5. In addition, a yellow-pigmented carotenoid synthesized by strain XLDN2-5 was identified as zeaxanthin that was synthesized from β-carotene through β-cryptoxanthin. The amounts of zeaxanthin and hydrogen peroxide produced were significantly and simultaneously enhanced during the biodegradation of heterocycles (carbazole < carbazole + benzothiophene < carbazole + dibenzothiophene). These higher production levels were consistent with the transcriptional increase of the gene encoding phytoene desaturase, one of the key enzymes for carotenoid biosynthesis. CONCLUSIONS/SIGNIFICANCE: Sphingobium yanoikuyae XLDN2-5 can enhance the synthesis of zeaxanthin, one of the carotenoids, which may modulate membrane fluidity and defense against intracellular oxidative stress. To our knowledge, this is the first report on the positive role of carotenoids in the biodegradation of heterocycles, while elucidating the carotenoid biosynthetic pathway in the Sphingobium genus

Identification of GSK3186899/DDD853651 as a Preclinical Development Candidate for the Treatment of Visceral Leishmaniasis

The leishmaniases are diseases that affect millions of people across the world, in particular visceral leishmaniasis (VL) which is fatal unless treated. Current standard of care for VL suffers from multiple issues and there is a limited pipeline of new candidate drugs. As such, there is a clear unmet medical need to identify new treatments. This paper describes the optimization of a phenotypic hit against Leishmania donovani, the major causative organism of VL. The key challenges were to balance solubility and metabolic stability while maintaining potency. Herein, strategies to address these shortcomings and enhance efficacy are discussed, culminating in the discovery of preclinical development candidate GSK3186899/DDD853651 (<b>1</b>) for VL