Thiamine supplementation in hospitalized patients with altered mental status: does it help?

OBJECTIVE: To describe thiamine-prescribing patterns and to study the association of thiamine supplementation with clinical outcomes in hospitalized patients with altered mental status (AMS). METHODS: We conducted a retrospective cohort study of all adult hospitalized patients with AMS with index admission in calendar year 2017. We studied the association of a) supplemental thiamine and b) timing of thiamine relative to glucose, with hospital outcomes - length of stay (LOS), 90-day readmission rates, and mortality rates - using linear, logistic, and extended Cox models, respectively. We also modeled association of supplemental thiamine on time to resolution of AMS using extended Cox models in patients admitted with AMS. RESULTS: Of 985 patients, 178 (18%) received thiamine, including 123 (12.5%) who received thiamine before, with, or without glucose (thiamine first). We identified 365 (37%) patients who received intravenous glucose before or without thiamine (glucose first). We found that patients who received glucose first had longer LOS and higher rate of in-hospital deaths compared to those who did not. Patients who received thiamine supplementation had longer LOS compared to those who did not. There were no significant differences in other hospital outcomes or AMS resolution by discharge compared to their respective reference groups. CONCLUSION: Although thiamine supplementation was not associated with better hospital or cognitive outcomes, we do not have enough evidence to suggest a change in current practice. Thiamine must be administered prior to glucose in hospitalized patients with AMS.

Prospective Randomized Evaluation of Preoperative Angiotensin-Converting Enzyme Inhibition (PREOP-ACEI).

BACKGROUND: Intraoperative hypotension is associated with an increased risk of end organ damage and death. The transient preoperative interruption of angiotensinconverting enzyme inhibitor (ACEI) therapy prior to cardiac and vascular surgeries decreases the occurrence of intraoperative hypotension. OBJECTIVE: We sought to compare the effect of two protocols for preoperative ACEI management on the risk of intraoperative hypotension among patients undergoing noncardiac, nonvascular surgeries. DESIGN: Prospective, randomized study. SETTING: Midwestern urban 489-bed academic medical center. PATIENTS: Patients taking an ACEI for at least six weeks preoperatively were considered for inclusion. INTERVENTIONS: Randomization of the final preoperative ACEI dose to omission (n = 137) or continuation (n = 138). MEASUREMENTS: The primary outcome was intraoperative hypotension, which was defined as any systolic blood pressure (SBP) < 80 mm Hg. Postoperative hypotensive (SBP < 90 mm Hg) and hypertensive (SBP >> 180 mm Hg) episodes were also recorded. Outcomes were compared using Fisher's exact test. RESULTS: Intraoperative hypotension occurred less frequently in the omission group (76 of 137 [55%]) than in the continuation group (95 of 138 [69%]) (RR: 0.81, 95% CI: 0.67 to 0.97, P = .03, NNH 7.5). Postoperative hypotensive events were also less frequent in the ACEI omission group (RR: 0.49, 95% CI: 0.28 to 0.86, P = .02) than in the continuation group. However, postoperative hypertensive events were more frequent in the omission group than in the continuation group (RR: 1.95, 95%: CI: 1.14 to 3.34, P = .01). CONCLUSIONS: The transient preoperative interruption of ACEI therapy is associated with a decreased risk of intraoperative hypotension. REGISTRATION: ClinicalTrials.gov: NCT01669434.

Comparative analysis of protein-protein interactions in cancer-associated genes.

Protein-protein interactions (PPIs) have been widely studied to understand the biological processes or molecular functions associated with different disease systems like cancer. While focused studies on individual cancers have generated valuable information, global and comparative analysis of datasets from different cancer types has not been done. In this work, we carried out bioinformatic analysis of PPIs corresponding to differentially expressed genes from microarrays of various tumor tissues (belonging to bladder, colon, kidney and thyroid cancers) and compared their associated biological processes and molecular functions (based on Gene Ontology terms). We identified a set of processes or functions that are common to all these cancers, as well as those that are specific to only one or partial cancer types. Similarly, protein interaction networks in nucleic acid metabolism were compared to identify the common/specific clusters of proteins across different cancer types. Our results provide a basis for further experimental investigations to study protein interaction networks associated with cancer. The methodology developed in this work can also be applied to study similar disease systems.

A top-down approach to infer and compare domain-domain interactions across eight model organisms.

Knowledge of specific domain-domain interactions (DDIs) is essential to understand the functional significance of protein interaction networks. Despite the availability of an enormous amount of data on protein-protein interactions (PPIs), very little is known about specific DDIs occurring in them. Here, we present a top-down approach to accurately infer functionally relevant DDIs from PPI data. We created a comprehensive, non-redundant dataset of 209,165 experimentally-derived PPIs by combining datasets from five major interaction databases. We introduced an integrated scoring system that uses a novel combination of a set of five orthogonal scoring features covering the probabilistic, evolutionary, evidence-based, spatial and functional properties of interacting domains, which can map the interacting propensity of two domains in many dimensions. This method outperforms similar existing methods both in the accuracy of prediction and in the coverage of domain interaction space. We predicted a set of 52,492 high-confidence DDIs to carry out cross-species comparison of DDI conservation in eight model species including human, mouse, Drosophila, C. elegans, yeast, Plasmodium, E. coli and Arabidopsis. Our results show that only 23% of these DDIs are conserved in at least two species and only 3.8% in at least 4 species, indicating a rather low conservation across species. Pair-wise analysis of DDI conservation revealed a 'sliding conservation' pattern between the evolutionarily neighboring species. Our methodology and the high-confidence DDI predictions generated in this study can help to better understand the functional significance of PPIs at the modular level, thus can significantly impact further experimental investigations in systems biology research.

Mitoproteome: human heart mitochondrial protein sequence database.

The human mitochondrial proteome database has been developed by deriving data from a combination of public repositories and experimental and computational prediction methods. The experimental data is derived from highly purified mitochondria from human heart tissue, whereas predictions have been performed by MITOPRED, a genome-scale method for the prediction of nucleus-encoded mitochondrial proteins. Mitochondrial protein sequences from different sources have been clustered to generate a nonredundant dataset. Annotations related to the protein function, structure, disease association, pathways, and so on are collected from a number of public databases using commonly used UNIX and Perl scripts. This chapter provides a detailed description of various data sources and methods used to download, curate, parse, and generate meaningful annotations from primary as well as derived databases.

Conserved motifs in voltage-sensing and pore-forming modules of voltage-gated ion channel proteins.

Voltage-gated ion channels (VGCs) mediate selective diffusion of ions across cell membranes to enable many vital cellular processes. Three-dimensional structure data are lacking for VGC proteins; hence, to better understand their function, there is a need to identify the conserved motifs using sequence analysis methods. In this study, we have used a profile-to-profile alignment method to identify several new conserved motifs specific to each transmembrane segment (TMS) of the voltage-sensing and the pore-forming modules of Ca2+, Na+, and K+ channel subfamilies. For Ca2+ and Na+, the functional theme of motif conservation is similar in all segments while they differ with those of the K+ channel proteins. Nevertheless, the conservation is strikingly similar in the S4 segment of the voltage-sensing module across all subfamilies. In each subfamily and for each TMS, we have identified conserved motifs/residues and correlated their functional significance and disease associations in human, using mutational data from the literature.

Reconstruction of pathways associated with amino acid metabolism in human mitochondria.

We have used a bioinformatics approach for the identification and reconstruction of metabolic pathways associated with amino acid metabolism in human mitochondria. Human mitochondrial proteins determined by experimental and computational methods have been superposed on the reference pathways from the KEGG database to identify mitochondrial pathways. Enzymes at the entry and exit points for each reconstructed pathway were identified, and mitochondrial solute carrier proteins were determined where applicable. Intermediate enzymes in the mitochondrial pathways were identified based on the annotations available from public databases, evidence in current literature, or our MITOPRED program, which predicts the mitochondrial localization of proteins. Through integration of the data derived from experimental, bibliographical, and computational sources, we reconstructed the amino acid metabolic pathways in human mitochondria, which could help better understand the mitochondrial metabolism and its role in human health.

MITOPRED: a web server for the prediction of mitochondrial proteins.

MITOPRED web server enables prediction of nucleus-encoded mitochondrial proteins in all eukaryotic species. Predictions are made using a new algorithm based primarily on Pfam domain occurrence patterns in mitochondrial and non-mitochondrial locations. Pre-calculated predictions are instantly accessible for proteomes of Saccharomyces cerevisiae, Caenorhabditis elegans, Drosophila, Homo sapiens, Mus musculus and Arabidopsis species as well as all the eukaryotic sequences in the Swiss-Prot and TrEMBL databases. Queries, at different confidence levels, can be made through four distinct options: (i) entering Swiss-Prot/TrEMBL accession numbers; (ii) uploading a local file with such accession numbers; (iii) entering protein sequences; (iv) uploading a local file containing protein sequences in FASTA format. Automated updates are scheduled for the pre-calculated prediction database so as to provide access to the most current data. The server, its documentation and the data are available from http://mitopred.sdsc.edu.

MitoProteome: mitochondrial protein sequence database and annotation system.

MitoProteome is an object-relational mitochondrial protein sequence database and annotation system. The initial release contains 847 human mitochondrial protein sequences, derived from public sequence databases and mass spectrometric analysis of highly purified human heart mitochondria. Each sequence is manually annotated with primary function, subfunction and subcellular location, and extensively annotated in an automated process with data extracted from external databases, including gene information from LocusLink and Ensembl; disease information from OMIM; protein-protein interaction data from MINT and DIP; functional domain information from Pfam; protein fingerprints from PRINTS; protein family and family-specific signatures from InterPro; structure data from PDB; mutation data from PMD; BLAST homology data from NCBI NR; and proteins found to be related based on LocusLink and SWISS-PROT references and sequence and taxonomy data. By highly automating the processes of maintaining the MitoProteome Protein List and extracting relevant data from external databases, we are able to present a dynamic database, updated frequently to reflect changes in public resources. The MitoProteome database is publicly available at http://www. mitoproteome.org/. Users may browse and search MitoProteome, and access a complete compilation of data relevant to each protein of interest, cross-linked to external databases.