Digital twins and the future of precision mental health.

Science faces challenges in developing much-needed precision mental health treatments to accurately identify and diagnose mental health problems and the optimal treatment for each individual. Digital twins (DTs) promise to revolutionize the field of mental health, as they are doing in other fields of science, including oncology and cardiology, where they have been successfully deployed. The use of DTs in mental health is yet to be explored. In this Perspective, we lay the conceptual foundations for mental health DTs (MHDT). An MHDT is a virtual representation of an individual's mental states and processes. It is continually updated from data collected over the lifespan of the individual, and guides mental health professionals in diagnosing and treating patients based on mechanistic models and statistical and machine learning tools. The merits of MHDT are demonstrated through the example of the working alliance between the therapist and the patient, which is one of the most consistent mechanisms predicting treatment outcome.

Prediction of liver toxicity and mode of action using metabolomics in vitro in HepG2 cells.

Liver toxicity is a leading systemic toxicity of drugs and chemicals demanding more human-relevant, high throughput, cost effective in vitro solutions. In addition to contributing to animal welfare, in vitro techniques facilitate exploring and understanding the molecular mechanisms underlying toxicity. New 'omics technologies can provide comprehensive information on the toxicological mode of action of compounds, as well as quantitative information about the multi-parametric metabolic response of cellular systems in normal and patho-physiological conditions. Here, we combined mass-spectroscopy metabolomics with an in vitro liver toxicity model. Metabolite profiles of HepG2 cells treated with 35 test substances resulted in 1114 cell supernatants and 3556 intracellular samples analyzed by metabolomics. Control samples showed relative standard deviations of about 10-15%, while the technical replicates were at 5-10%. Importantly, this procedure revealed concentration-response effects and patterns of metabolome changes that are consistent for different liver toxicity mechanisms (liver enzyme induction/inhibition, liver toxicity and peroxisome proliferation). Our findings provide evidence that identifying organ toxicity can be achieved in a robust, reliable, human-relevant system, representing a non-animal alternative for systemic toxicology.

Trauma Network North-West - improving holistic care for trauma patients by means of internet and mobile technologies.

The Trauma Network North-West as an initiative seeks to improve the initial and follow-up care for severely injured patients in need of immediate intensive care. The main goals are intensification and optimization of exchange of information, expertise and knowledge among participating clinics. By (a) foundation of the network itself and (b) establishment of a sophisticated IT infrastructure for web-based and mobile communication, instantaneous and concomitant care for trauma patients shall be significantly improved. The network's workflow incorporates participating clinics within a central platform, including parameters such as level of health care, geographic coordinates, overstrained care units and defective medical devices. Mobile components allow locating nearby clinics based on an emergency physician's coordinates and automatic triggering of disposition via coordination offices. A tight interplay between server components and location-based services shall reduce unnecessary transportation as well as financial expenditure. The central web-based system is currently established and evaluated in an initial test phase.

Securing a web-based teleradiology platform according to German law and "best practices".

The Medical Data and Picture Exchange platform (MDPE), as a teleradiology system, facilitates the exchange of digital medical imaging data among authorized users. It features extensive support of the DICOM standard including networking functions. Since MDPE is designed as a web service, security and confidentiality of data and communication pose an outstanding challenge. To comply with demands of German laws and authorities, a generic data security concept considered as "best practice" in German health telematics was adapted to the specific demands of MDPE. The concept features strict logical and physical separation of diagnostic and identity data and thus an all-encompassing pseudonymization throughout the system. Hence, data may only be merged at authorized clients. MDPE's solution of merging data from separate sources within a web browser avoids technically questionable techniques such as deliberate cross-site scripting. Instead, data is merged dynamically by JavaScriptlets running in the user's browser. These scriptlets are provided by one server, while content and method calls are generated by another server. Additionally, MDPE uses encrypted temporary IDs for communication and merging of data.

Clearinghouse: a teleradiology platform emphasizing security of data and communication.

The Clearinghouse application platform is a web based solution for secure digital exchange of radiological images and other clinical documents among authorized researchers and physicians. It implements a sophisticated security and role model to protect privacy and to minimize the risk of eavesdropping of patient data. The Clearinghouse serves as a centralized platform for distributed, distantly located medical research and health care. It is based on Open-Source software, thus ensuring continued support, maintenance, security and last but not least continuity of the platform. The use of the Clearinghouse minimizes turnaround times by superseding comparably slow and insecure conventional communication methods otherwise used for the exchange of radiological images and clinical documents, such as standard mail and courier services. Furthermore, it alleviates the integration of distantly located expert knowledge into diagnostic routines, culminating in an increased health care quality regardless of location of patients or physicians.

Cloning, genomic organization, and tissue-specific expression of the RASL11B gene.

RASL11B is a member of the small GTPase protein family with a high degree of similarity to RAS proteins. Cloning of RASL11B mRNA and in silico analyses revealed that the human RASL11B gene spans about 4.5 kb and comprises four exons on chromosomal locus 4q12. The proximal 5'-flanking region of the gene lacks a TATA box but is GC-rich and contains a CCAAT box and several Sp1 sites. Consistent with this, the RASL11B gene was found to be expressed in all tissues investigated, with highest levels in placenta and in primary macrophages. The predicted RASL11B protein has no typical prenylation signal, indicating that it is probably not anchored to cellular membranes. RASL11B was induced during maturation of THP-1 monocytic cells into macrophage-like cells and in coronary artery smooth muscle cells after treatment with TGF-beta1. These results indicate that RASL11B may play a role in TGF-beta1-mediated developmental processes and in pathophysiologies such as inflammation, cancer, and arteriosclerosis.

IsoSVM--distinguishing isoforms and paralogs on the protein level.

BACKGROUND: Recent progress in cDNA and EST sequencing is yielding a deluge of sequence data. Like database search results and proteome databases, this data gives rise to inferred protein sequences without ready access to the underlying genomic data. Analysis of this information (e.g. for EST clustering or phylogenetic reconstruction from proteome data) is hampered because it is not known if two protein sequences are isoforms (splice variants) or not (i.e. paralogs/orthologs). However, even without knowing the intron/exon structure, visual analysis of the pattern of similarity across the alignment of the two protein sequences is usually helpful since paralogs and orthologs feature substitutions with respect to each other, as opposed to isoforms, which do not. RESULTS: The IsoSVM tool introduces an automated approach to identifying isoforms on the protein level using a support vector machine (SVM) classifier. Based on three specific features used as input of the SVM classifier, it is possible to automatically identify isoforms with little effort and with an accuracy of more than 97%. We show that the SVM is superior to a radial basis function network and to a linear classifier. As an example application we use IsoSVM to estimate that a set of Xenopus laevis EST clusters consists of approximately 81% cases where sequences are each other's paralogs and 19% cases where sequences are each other's isoforms. The number of isoforms and paralogs in this allotetraploid species is of interest in the study of evolution. CONCLUSION: We developed an SVM classifier that can be used to distinguish isoforms from paralogs with high accuracy and without access to the genomic data. It can be used to analyze, for example, EST data and database search results. Our software is freely available on the Web, under the name IsoSVM.

Correspondence of function and phylogeny of ABC proteins based on an automated analysis of 20 model protein data sets.

Using our BLAST-based procedure RiPE (Retrieval-induced Phylogeny Environment), which automates the evolutionary analysis of a protein family, we assembled a set of 1138 ABC protein components [adenosine triphosphate (ATP)-binding cassette and transmembrane domain] from the protein data sets of 20 model organisms and subjected them to phylogenetic and functional analysis. For maximum speed, we based the alignment directly on a homology search with a profile of all known human ABC proteins and used neighbor-joining tree estimation. All but 11 sequences from Homo sapiens, Arabidopsis thaliana, Drosophila melanogaster, and Saccharomyces cerevisiae were placed into the correct subtree/subfamily, reproducing published classifications of the individual organisms. By following a simple "function transfer rule", our comparative phylogenetic analysis successfully predicted the known function of human ABC proteins in 19 of 22 cases. Three functional predictions did not correspond, and 10 were novel. Predictions based on BLAST alone were inferior in five cases and superior in two. Bacterial sequences were placed close to the root of most subtrees. This placement coincides with domain architecture, suggesting an early diversification of the ABC family before the kingdoms split apart. Our approach can, in principle, be used to annotate any protein family of any organism included in the study.

Cloning, cellular localization, genomic organization, and tissue-specific expression of the TGFbeta1-inducible SMAP-5 gene.

SMAP-5 is a member of the five-pass transmembrane protein family localizing in the Golgi apparatus and the endoplasmic reticulum. These proteins have been implicated in intracellular trafficking, in secretion and in vesicular transport. Phylogenetic analyses revealed that SMAP-5 is a member of a small Rab GTPase interacting factor protein family. The human SMAP-5 gene spans about 12.5 kb and comprises 6 exons on chromosomal locus 5q32. The proximal 5'-flanking region of the gene lacks a TATA box and is highly GC rich. Consistent with this, the SMAP-5 gene is expressed in all tissues. The highest level of expression was found in coronary smooth muscle cells, in which expression of the SMAP-5 gene was induced by transforming growth factor beta1, thus indicating that this protein may play an important role in inflammation.

VisCoSe: visualization and comparison of consensus sequences.

We introduce visualization and comparison of consensus sequences (VisCoSe) as a WWW service and a stand-alone command line Perl script for visualizing and comparing consensus sequences of protein and nucleotide sequences. VisCoSe is the only interface available that simultaneously calculates consensus sequences of multiple data sets and automatically compares these consensus sequences. Furthermore, VisCoSe allows visualization of chemical properties of amino acids.

BLASTing proteomes, yielding phylogenies.

We develop a procedure called RiPE (Retrieval-induced Phylogeny Environment) that automatically performs an evolutionary analysis of a protein (sub)family, (i) by retrieving the relevant sequences via a homology search, (ii) by using the search report to construct the alignment using only homologous subsequences (taking into account their neighborhood with a low chance of homology), (iii) by realigning, and (iv) by generating phylogenetic trees based on the alignment. In a first implementation of our scheme, we start with the available proteome data of model organisms, perform a PSI-BLAST search, use MView to convert hits into a multiple alignment, and perform realignment and tree building. As a test case, we have investigated the human ABC transporters of the subfamily G, starting with the five known human ABCG transporters. Our method retrieved homologous sequences not previously analyzed, generating a tree that is more plausible and better supported than previously published trees. The RiPE 0.1 prototype is available at the RiPE website, http://ifg-izkf.uni-muenster.de/fuellen/RiPE/ripe.html.