CausalTAB: the PSI-MITAB 2.8 updated format for signalling data representation and dissemination.

MOTIVATION: Combining multiple layers of information underlying biological complexity into a structured framework represent a challenge in systems biology. A key task is the formalization of such information in models describing how biological entities interact to mediate the response to external and internal signals. Several databases with signalling information, focus on capturing, organizing and displaying signalling interactions by representing them as binary, causal relationships between biological entities. The curation efforts that build these individual databases demand a concerted effort to ensure interoperability among resources. RESULTS: Aware of the enormous benefits of standardization efforts in the molecular interaction research field, representatives of the signalling network community agreed to extend the PSI-MI controlled vocabulary to include additional terms representing aspects of causal interactions. Here, we present a common standard for the representation and dissemination of signalling information: the PSI Causal Interaction tabular format (CausalTAB) which is an extension of the existing PSI-MI tab-delimited format, now designated PSI-MITAB 2.8. We define the new term 'causal interaction', and related child terms, which are children of the PSI-MI 'molecular interaction' term. The new vocabulary terms in this extended PSI-MI format will enable systems biologists to model large-scale signalling networks more precisely and with higher coverage than before. AVAILABILITY AND IMPLEMENTATION: PSI-MITAB 2.8 format and the new reference implementation of PSICQUIC are available online (https://psicquic.github.io/ and https://psicquic.github.io/MITAB28Format.html). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

JAMI: a Java library for molecular interactions and data interoperability.

BACKGROUND: A number of different molecular interactions data download formats now exist, designed to allow access to these valuable data by diverse user groups. These formats include the PSI-XML and MITAB standard interchange formats developed by Molecular Interaction workgroup of the HUPO-PSI in addition to other, use-specific downloads produced by other resources. The onus is currently on the user to ensure that a piece of software is capable of read/writing all necessary versions of each format. This problem may increase, as data providers strive to meet ever more sophisticated user demands and data types. RESULTS: A collaboration between EMBL-EBI and the University of Cambridge has produced JAMI, a single library to unify standard molecular interaction data formats such as PSI-MI XML and PSI-MITAB. The JAMI free, open-source library enables the development of molecular interaction computational tools and pipelines without the need to produce different versions of software to read different versions of the data formats. CONCLUSION: Software and tools developed on top of the JAMI framework are able to integrate and support both PSI-MI XML and PSI-MITAB. The use of JAMI avoids the requirement to chain conversions between formats in order to reach a desired output format and prevents code and unit test duplication as the code becomes more modular. JAMI's model interfaces are abstracted from the underlying format, hiding the complexity and requirements of each data format from developers using JAMI as a library.

Encompassing new use cases - level 3.0 of the HUPO-PSI format for molecular interactions.

BACKGROUND: Systems biologists study interaction data to understand the behaviour of whole cell systems, and their environment, at a molecular level. In order to effectively achieve this goal, it is critical that researchers have high quality interaction datasets available to them, in a standard data format, and also a suite of tools with which to analyse such data and form experimentally testable hypotheses from them. The PSI-MI XML standard interchange format was initially published in 2004, and expanded in 2007 to enable the download and interchange of molecular interaction data. PSI-XML2.5 was designed to describe experimental data and to date has fulfilled this basic requirement. However, new use cases have arisen that the format cannot properly accommodate. These include data abstracted from more than one publication such as allosteric/cooperative interactions and protein complexes, dynamic interactions and the need to link kinetic and affinity data to specific mutational changes. RESULTS: The Molecular Interaction workgroup of the HUPO-PSI has extended the existing, well-used XML interchange format for molecular interaction data to meet new use cases and enable the capture of new data types, following extensive community consultation. PSI-MI XML3.0 expands the capabilities of the format beyond simple experimental data, with a concomitant update of the tool suite which serves this format. The format has been implemented by key data producers such as the International Molecular Exchange (IMEx) Consortium of protein interaction databases and the Complex Portal. CONCLUSIONS: PSI-MI XML3.0 has been developed by the data producers, data users, tool developers and database providers who constitute the PSI-MI workgroup. This group now actively supports PSI-MI XML2.5 as the main interchange format for experimental data, PSI-MI XML3.0 which additionally handles more complex data types, and the simpler, tab-delimited MITAB2.5, 2.6 and 2.7 for rapid parsing and download.

The IMEx coronavirus interactome: an evolving map of Coronaviridae-host molecular interactions.

The current coronavirus disease of 2019 (COVID-19) pandemic, caused by the severe acute respiratory syndrome coronavirus (SARS-CoV)-2, has spurred a wave of research of nearly unprecedented scale. Among the different strategies that are being used to understand the disease and develop effective treatments, the study of physical molecular interactions can provide fine-grained resolution of the mechanisms behind the virus biology and the human organism response. We present a curated dataset of physical molecular interactions focused on proteins from SARS-CoV-2, SARS-CoV-1 and other members of the Coronaviridae family that has been manually extracted by International Molecular Exchange (IMEx) Consortium curators. Currently, the dataset comprises over 4400 binarized interactions extracted from 151 publications. The dataset can be accessed in the standard formats recommended by the Proteomics Standards Initiative (HUPO-PSI) at the IntAct database website (https://www.ebi.ac.uk/intact) and will be continuously updated as research on COVID-19 progresses.

The IMEx Coronavirus interactome: an evolving map of Coronaviridae-Host molecular interactions.

The current Coronavirus Disease 2019 (COVID-19) pandemic, caused by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), has spurred a wave of research of nearly unprecedented scale. Among the different strategies that are being used to understand the disease and develop effective treatments, the study of physical molecular interactions enables studying fine-grained resolution of the mechanisms behind the virus biology and the human organism response. Here we present a curated dataset of physical molecular interactions, manually extracted by IMEx Consortium curators focused on proteins from SARS-CoV-2, SARS-CoV-1 and other members of the Coronaviridae family. Currently, the dataset comprises over 2,200 binarized interactions extracted from 86 publications. The dataset can be accessed in the standard formats recommended by the Proteomics Standards Initiative (HUPO-PSI) at the IntAct database website ( www.ebi.ac.uk/intact ), and will be continuously updated as research on COVID-19 progresses.

Publisher Correction: Capturing variation impact on molecular interactions in the IMEx Consortium mutations data set.

In the original HTML version of this Article, the order of authors within the author list was incorrect. The IMEx Consortium contributing authors were incorrectly listed as the last author and should have been listed as the first author. This error has been corrected in the HTML version of the Article; the PDF version was correct at the time of publication.

Capturing variation impact on molecular interactions in the IMEx Consortium mutations data set.

The current wealth of genomic variation data identified at nucleotide level presents the challenge of understanding by which mechanisms amino acid variation affects cellular processes. These effects may manifest as distinct phenotypic differences between individuals or result in the development of disease. Physical interactions between molecules are the linking steps underlying most, if not all, cellular processes. Understanding the effects that sequence variation has on a molecule's interactions is a key step towards connecting mechanistic characterization of nonsynonymous variation to phenotype. We present an open access resource created over 14 years by IMEx database curators, featuring 28,000 annotations describing the effect of small sequence changes on physical protein interactions. We describe how this resource was built, the formats in which the data is provided and offer a descriptive analysis of the data set. The data set is publicly available through the IntAct website and is enhanced with every monthly release.

[Comparative study of PTFE grafts in forearm vs cuffed permanent catheters]. / Estudio comparativo del uso de protesis vasculares de PTFE a nivel de antebrazo vs cateter permanente.

INTRODUCTION: As is universally accepted the best form of permanent vascular access for haemodialysis is the native arteriovenous fistula. A second and third options are the politetrafluoroethylene (PTFE) AV grafts and the cuffed, tunneled, internal catheters. The overall performance and complications of catheters is clearly inferior to AV fistula. There are not many studies that compare permanent catheters to grafts in terms of functionality, survival and complications. METHODS: We analyzed 81 vascular accesses carried out from october 99 to december 03 in 59 patients and during a follow-up period of 35 months. Two groups were considered. Group 1, catheters (n 42) and group 2, grafts (n 39). Clinical aspects, comorbidity index (Wright and Kanh), dialysis dose and complications and survival of the access were registered. RESULTS: Both groups were similar in age, sex, time on haemodialysis, number of previous accesses and hospitalization days. Cardiovascular morbidity and comorbidity index were significantly higher in patients with catheter. While blood flow during dialysis was higher in grafts both groups showed no significant differences in parameters of efficacy of dialysis (Kt/V, TAC BUN and PCRn). Serum albumin was lower in patients with catheter. The number of accesses that failed was higher in the graft group being thrombosis the main complication followed by infection. Kaplan-Meier curves showed better accumulated survival of permanent catheters versus grafts (61,4% vs 9,8% at 35 months). The most frequent complication of catheter was infection while in the case of grafts it was thrombosis followed by infection. CONCLUSIONS: Although they were placed in patients with higher comorbidity, cuffed, tunneled catheters showed less number of complications and better survival than PTFE grafts in our patients in haemodialysis. The main cause of failure of both vascular access was thrombosis followed by infection. The dose of dialysis obtained was no different in both groups. Cuffed, tunneled permanent catheters are a very interesting option in a number of patients in haemodialysis and they can be an option to consider in those patients with vascular difficulties and higher comorbidities.

[Renal hyperparathyroidism's control after subtotal parathyroidectomy]. / Control del hiperparatiroidismo renal tras paratiroidectomía subtotal.

UNLABELLED: Parathyroidectomy, in any of its forms, is considered an effective short-term treatment of renal hyperparathyroidism in patients who are not being controlled with drugs. Nevertheless, the outcome in the medium and long term of the various surgical procedures is still unclear and seems a controversial issue. We conducted a prospective study of 15 patients undergoing subtotal parathyroidectomy who were followed up for a period of 48 months after surgery. All patients were included in hemodialysis programmes. Elevated levels of parathyroid hormone which did not decrease with drug therapy recommended parathyroidectomy. The aim of our study is to determine whether subtotal parathyroidectomy is an effective technique in the medium and long term. As regards the results obtained, the levels of parathyroid hormone and calcemia remarkably decreased during the follow-up period, if compared to pre-surgery levels. The level of alkaline phosphatase also showed a reduction and the "hungry bone effect" was observed. The phosphorus and Ca-P product levels only showed a significant reduction immediately after surgery but showed an increment from the first year after surgery onwards. Hemoglobin levels did not show any alteration after parathyroidectomy. In two patients we observed a relapse of hyperparathyroidism. The anatomopathological examination revealed nodular hyperplasia in most of the cases, including the two relapses. CONCLUSION: Subtotal parathyroidectomy is an effective surgical procedure in the medium-term treatment of renal hyperparathyroidism.

Merging and scoring molecular interactions utilising existing community standards: tools, use-cases and a case study.

The evidence that two molecules interact in a living cell is often inferred from multiple different experiments. Experimental data is captured in multiple repositories, but there is no simple way to assess the evidence of an interaction occurring in a cellular environment. Merging and scoring of data are commonly required operations after querying for the details of specific molecular interactions, to remove redundancy and assess the strength of accompanying experimental evidence. We have developed both a merging algorithm and a scoring system for molecular interactions based on the proteomics standard initiative-molecular interaction standards. In this manuscript, we introduce these two algorithms and provide community access to the tool suite, describe examples of how these tools are useful to selectively present molecular interaction data and demonstrate a case where the algorithms were successfully used to identify a systematic error in an existing dataset.