Obesity and type 2 diabetes are strongly associated with abnormal lipid metabolism and accumulation of intramyocellular triacylglycerol, but the underlying cause of these perturbations are yet unknown. Herein, we show that the lipogenic gene, stearoyl-CoA desaturase 1 (SCD1), is robustly up-regulated in skeletal muscle from extremely obese humans. High expression and activity of SCD1, an enzyme that catalyzes the synthesis of monounsaturated fatty acids, corresponded with low rates of fatty acid oxidation, increased triacylglycerol synthesis and increased monounsaturation of muscle lipids. Elevated SCD1 expression and abnormal lipid partitioning were retained in primary skeletal myocytes derived from obese compared to lean donors, implying that these traits might be driven by epigenetic and/or heritable mechanisms. Overexpression of human SCD1 in myotubes from lean subjects was sufficient to mimic the obese phenotype. These results suggest that elevated expression of SCD1 in skeletal muscle contributes to abnormal lipid metabolism and progression of obesity.
To characterize metabolites across the range of maternal glucose by comparing metabolomic profiles of mothers with high and low fasting plasma glucose (FPG).
RESEARCH DESIGN AND METHODS
We compared fasting serum from an oral glucose tolerance test at ∼28 weeks’ gestation from 67 Northern European ancestry mothers from the Hyperglycemia and Adverse Pregnancy Outcome (HAPO) Study with high (>90th percentile) FPG with 50 mothers with low (<10th percentile) FPG but comparable BMI. Metabolic data from biochemical analyses of conventional clinical metabolites, targeted mass spectrometry (MS)-based measurement of amino acids, and nontargeted gas chromatography/MS were subjected to per-metabolite analyses and collective pathway analyses using Unipathway annotation.
High-FPG mothers had a metabolic profile consistent with insulin resistance including higher triglycerides, 3-hydroxybutyrate, and amino acids including alanine, proline, and branched-chain amino acids (false discovery rate [FDR]-adjusted P < 0.05). Lower 1,5-anhydroglucitol in high-FPG mothers suggested recent hyperglycemic excursions (FDR-adjusted P < 0.05). Pathway analyses indicated differences in amino acid degradation pathways for the two groups (FDR-adjusted P < 0.05), consistent with population-based findings in nonpregnant populations. Exploratory analyses with newborn outcomes indicated positive associations for maternal triglycerides with neonatal sum of skinfolds and cord C-peptide and a negative association between maternal glycine and cord C-peptide (P < 0.05).
Metabolomics reveals perturbations in metabolism of major macronutrients and amino acid degradation pathways in high- versus low-FPG mothers.
Reversible posttranslational modifications are emerging as critical regulators of mitochondrial proteins and metabolism. Here, we use a label-free quantitative proteomic approach to characterize the lysine succinylome in liver mitochondria and its regulation by the desuccinylase SIRT5. A total of 1190 unique sites were identified as succinylated, and 386 sites across 140 proteins representing several metabolic pathways including β-oxidation and ketogenesis were significantly hypersuccinylated in Sirt5−/− animals. Loss of SIRT5 leads to accumulation of medium- and long-chain acylcarnitines and decreased β-hydroxybutyrate production in vivo. In addition, we demonstrate that SIRT5 regulates succinylation of the rate-limiting ketogenic enzyme 3-hydroxy-3-methylglutaryl-CoA synthase 2 (HMGCS2) both in vivo and in vitro. Finally, mutation of hypersuccinylated residues K83 and K310 on HMGCS2 to glutamic acid strongly inhibits enzymatic activity. Taken together, these findings establish SIRT5 as a global regulator of lysine succinylation in mitochondria and present a mechanism for inhibition of ketogenesis through HMGCS2.
In overweight/obese individuals, cardiometabolic risk factors differ by race and sex categories. Small-molecule metabolites and metabolic hormone levels might also differ across these categories and contribute to risk factor heterogeneity. To explore this possibility, we performed a cross-sectional analysis of fasting plasma levels of 69 small-molecule metabolites and 13 metabolic hormones in 500 overweight/obese adults who participated in the Weight Loss Maintenance trial. Principal-components analysis (PCA) was used for reduction of metabolite data. Race and sex-stratified comparisons of metabolite factors and metabolic hormones were performed. African Americans represented 37.4% of the study participants, and females 63.0%. Of thirteen metabolite factors identified, three differed by race and sex: levels of factor 3 (branched-chain amino acids and related metabolites, p<0.0001), factor 6 (long-chain acylcarnitines, p<0.01), and factor 2 (medium-chain dicarboxylated acylcarnitines, p<0.0001) were higher in males vs. females; factor 6 levels were higher in Caucasians vs. African Americans (p<0.0001). Significant differences were also observed in hormones regulating body weight homeostasis. Among overweight/obese adults, there are significant race and sex differences in small-molecule metabolites and metabolic hormones; these differences may contribute to risk factor heterogeneity across race and sex subgroups and should be considered in future investigations with circulating metabolites and metabolic hormones.
Motivation: As a natural consequence of being a computer-based discipline, bioinformatics has a strong focus on database and software development, but the volume and variety of resources are growing at unprecedented rates. An audit of database and software usage patterns could help provide an overview of developments in bioinformatics and community common practice, and comparing the links between resources through time could demonstrate both the persistence of existing software and the emergence of new tools.
Results: We study the connections between bioinformatics resources and construct networks of database and software usage patterns, based on resource co-occurrence, that correspond to snapshots of common practice in the bioinformatics community. We apply our approach to pairings of phylogenetics software reported in the literature and argue that these could provide a stepping stone into the identification of scientific best practice.
Availability and implementation: The extracted resource data, the scripts used for network generation and the resulting networks are available at http://bionerds.sourceforge.net/networks/
There is a growing concern both inside and outside the scientific community over the lack of reproducibility of experiments. The depth and detail of reported methods are critical to the reproducibility of findings, but also for making it possible to compare and integrate data from different studies. In this study, we evaluated in detail the methods reporting in a comprehensive set of trypanosomiasis experiments that should enable valid reproduction, integration and comparison of research findings. We evaluated a subset of other parasitic (Leishmania, Toxoplasma, Plasmodium, Trichuris and Schistosoma) and non-parasitic (Mycobacterium) experimental infections in order to compare the quality of method reporting more generally. A systematic review using PubMed (2000–2012) of all publications describing gene expression in cells and animals infected with Trypanosoma spp was undertaken based on PRISMA guidelines; 23 papers were identified and included. We defined a checklist of essential parameters that should be reported and have scored the number of those parameters that are reported for each publication. Bibliometric parameters (impact factor, citations and h-index) were used to look for association between Journal and Author status and the quality of method reporting. Trichuriasis experiments achieved the highest scores and included the only paper to score 100% in all criteria. The mean of scores achieved by Trypanosoma articles through the checklist was 65.5% (range 32–90%). Bibliometric parameters were not correlated with the quality of method reporting (Spearman's rank correlation coefficient <−0.5; p>0.05). Our results indicate that the quality of methods reporting in experimental parasitology is a cause for concern and it has not improved over time, despite there being evidence that most of the assessed parameters do influence the results. We propose that our set of parameters be used as guidelines to improve the quality of the reporting of experimental infection models as a pre-requisite for integrating and comparing sets of data.
To characterize daily variation of amino acids (AAs) and acylcarnitines (ACs) in response to feeding and activity, we measured serum metabolites at various times and after various activities during the day. Subjects were admitted overnight for serial serum sampling, collected in the evening (6–8pm, n=40), before rising from bed or eating (8AM, n=40), 1 hour after rising but before eating (9 AM, n=20), 1–2 hours after rising and breakfast (9–10 AM, n=40), and at noon (12 PM, n=20). Measurements of 15 AAs and 45 ACs were performed by quantitative tandem mass spectrometry using stable-isotope dilution. Coefficients of variation within and between patients were calculated for individual metabolite values and factors derived from principal components analysis. The change of state between timepoints was evaluated by nearest neighbor non-parametric analysis of values at one timepoint compared to the next subsequent value. Relative to baseline AM recumbent concentrations, AA concentrations rose after activity and feeding while AC concentrations rose after activity and decreased with feeding. Furthermore, for all AAs, ACs, and their factors, biological variation was quantifiably evident and distinct from daily variation. This study confirms the daily variation of AAs and provides the first report of daily variation for a large panel of ACs. Although standardization of sample collection is highly desirable to control for daily variation (within a subject due to activity or feeding), this study demonstrated measurable biological variability (across subjects) suggesting that non-standardized sample collections could potentially provide insights into specific AA and AC metabolic pathways and disease mechanisms.
daily variation; acylcarnitines; amino acids; metabolomics; biomarkers
HIV infection occurs in 30% of children with severe acute malnutrition in sub-Saharan Africa. Effects of HIV on the pathophysiology and recovery from malnutrition are poorly understood.
We conducted a prospective cohort study of 75 severely malnourished Ugandan children. HIV status/CD4 counts were assessed at baseline; auxologic data and blood samples were obtained at admission and after 14 days of inpatient treatment. We utilized metabolomic profiling to characterize effects of HIV infection on metabolic status and subsequent responses to nutritional therapy.
At admission, patients (mean age 16.3 mo) had growth failure (mean W/H z-score −4.27 in non-edematous patients) that improved with formula feeding (mean increase 1.00). 24% (18/75) were HIV-infected. Nine children died within the first 14 days of hospitalization; mortality was higher for HIV-infected patients (33% v. 5%, OR = 8.83). HIV-infected and HIV-negative children presented with elevated NEFA, ketones, and even-numbered acylcarnitines and reductions in albumin and amino acids. Leptin, adiponectin, insulin, and IGF-1 levels were low while growth hormone, cortisol, and ghrelin levels were high. At baseline, HIV-infected patients had higher triglycerides, ketones, and even-chain acylcarnitines and lower leptin and adiponectin levels than HIV-negative patients. Leptin levels rose in all patients following nutritional intervention, but adiponectin levels remained depressed in HIV-infected children. Baseline hypoleptinemia and hypoadiponectinemia were associated with increased mortality.
Our findings suggest a critical interplay between HIV infection and adipose tissue storage and function in the adaptation to malnutrition. Hypoleptinemia and hypoadiponectinemia may contribute to high mortality rates among malnourished, HIV-infected children.
To identify novel biomarkers through metabolomic profiles that distinguish metabolically well (MW) from metabolically unwell (MUW) individuals, independent of body mass index (BMI).
This study was conducted as part of the Measurement to Understand the Reclassification of Disease of Cabarrus/Kannapolis (MURDOCK) project. Individuals from 3 cohorts were classified as lean (BMI<25 kg/m2), overweight (BMI≥25 kg/m2, BMI<30 kg/m2) or obese (BMI≥30 kg/m2). Cardiometabolic abnormalities were defined as: (1) impaired fasting glucose (≥100mg/dL and ≤126mg/dL); (2) hypertension; (3) triglycerides ≥150 mg/dL; (4) HDL-C <40 mg/dL in men, <50 mg/dL in women); and (5) insulin resistance (calculated Homeostatic Model Assessment (HOMA-IR) index of >5.13). MW individuals were defined as having <2 cardiometabolic abnormalities and MUW individuals had ≥two cardiometabolic abnormalities. Targeted profiling of 55 metabolites used mass-spectroscopy-based methods. Principal components analysis (PCA) was used to reduce the large number of correlated metabolites into clusters of fewer uncorrelated factors.
Of 1,872 individuals, 410 were lean, 610 were overweight, and 852 were obese. Of lean individuals, 67% were categorized as MUW, whereas 80% of overweight and 87% of obese individuals were MUW. PCA-derived factors with levels that differed the most between MW and MUW groups were factors 4 (branched chain amino acids [BCAA]) [p<.0001], 8 (various metabolites) [p<.0001], and 9 (C4/Ci4, C3, C5 acylcarnitines) [p<.0001] and 10 (amino acids) [p<.0002]. Further, Factor 4, distinguishes MW from MUW individuals independent of BMI.
BCAA and related metabolites are promising biomarkers that may aid in understanding cardiometabolic health independent of BMI category.
Obesity; Metabolomics; Insulin Resistance; Metabolic Risk
Biomedical ontologists to date have concentrated on ontological descriptions of biomedical entities such as gene products and their attributes, phenotypes and so on. Recently, effort has diversified to descriptions of the laboratory investigations by which these entities were produced. However, much biological insight is gained from the analysis of the data produced from these investigations, and there is a lack of adequate descriptions of the wide range of software that are central to bioinformatics. We need to describe how data are analyzed for discovery, audit trails, provenance and reproducibility.
The Software Ontology (SWO) is a description of software used to store, manage and analyze data. Input to the SWO has come from beyond the life sciences, but its main focus is the life sciences. We used agile techniques to gather input for the SWO and keep engagement with our users. The result is an ontology that meets the needs of a broad range of users by describing software, its information processing tasks, data inputs and outputs, data formats versions and so on. Recently, the SWO has incorporated EDAM, a vocabulary for describing data and related concepts in bioinformatics. The SWO is currently being used to describe software used in multiple biomedical applications.
The SWO is another element of the biomedical ontology landscape that is necessary for the description of biomedical entities and how they were discovered. An ontology of software used to analyze data produced by investigations in the life sciences can be made in such a way that it covers the important features requested and prioritized by its users. The SWO thus fits into the landscape of biomedical ontologies and is produced using techniques designed to keep it in line with user’s needs.
The Software Ontology is available under an Apache 2.0 license at http://theswo.sourceforge.net/; the Software Ontology blog can be read at http://softwareontology.wordpress.com.
Globally, TB notifications have stagnated since 2007, and sputum smear positive notifications have been declining despite policies to improve case detection. We evaluate results of 28 interventions focused on improving TB case detection.
We measured additional sputum smear positive cases treated, defined as the intervention area's increase in case notification during the project compared to the previous year. Projects were encouraged to select control areas and collect historical notification data. We used time series negative binomial regression for over-dispersed cross-sectional data accounting for fixed and random effects to test the individual projects' effects on TB notification while controlling for trend and control populations.
Twenty-eight projects, 19 with control populations, completed at least four quarters of case finding activities, covering a population of 89.2 million. Among all projects sputum smear positive (SS+) TB notifications increased 24.9% and annualized notification rates increased from 69.1 to 86.2/100,000 (p = 0.0209) during interventions. Among the 19 projects with control populations, SS+TB case notifications increased 36.9% increase while in the control populations a 3.6% decrease was observed. Fourteen (74%) of the 19 projects' SS+TB notification rates in intervention areas increased from the baseline to intervention period when controlling for historical trends and notifications in control areas.
Interventions were associated with large increases in TB notifications across many settings, using an array of interventions. Many people with TB are not reached using current approaches. Different methods and interventions tailored to local realities are urgently needed.
The isotope-labeled intravenous glucose tolerance test (IVGTT) combined with computer modeling is widely used to derive parameters related to glucose metabolism in vivo. Most of these methods involve use of either 2H2-labeled or 13C1-labeled D-glucose as a tracer with GC-MS to measure the isotope enrichment. These methods are challenging, both technologically and economically. We have developed a novel approach that is suitable for labeled-IVGTT studies involving a large cohort of individuals.
The tracer, D-[13C6]glucose, is a low-cost alternative with the significant advantage that the sixth isotope of natural glucose has virtually zero natural abundance, which facilitates isotopomer analysis with <1% labeled glucose in the infusate. After deproteinization of plasma samples collected at various times, glucose is converted to a stable derivative, purified by solid-phase extraction (SPE), and analyzed by HPLC–electrospray ionization mass spectrometry to accumulate the isotope-abundance data for the A+2, A+3, and A+6 ions of the glucose derivative. A 2-pool modeling program was used to derive standard kinetic parameters.
With labeled-IVGTT data from 10 healthy male individuals, the values for insulin sensitivity, glucose effectiveness, and the plasma clearance rate estimated with the 2-pool minimal model compared well with values obtained via traditional methods.
The relative simplicity and robustness of the new method permit the preparation and analysis of up to 48 samples/day, a throughput equivalent to 2 complete IVGTT experiments, and this method is readily adaptable to existing 96 well–format purification and analytical systems.
Relative to diets enriched in palmitic acid (PA), diets rich in oleic acid (OA) are associated with reduced risk of type 2 diabetes. To gain insight into mechanisms underlying these observations, we applied comprehensive lipidomic profiling to specimens collected from healthy adults enrolled in a randomized, crossover trial comparing a high-PA diet to a low-PA/high-OA (HOA) diet. Effects on insulin sensitivity (SI) and disposition index (DI) were assessed by intravenous glucose tolerance testing. In women, but not men, SI and DI were higher during HOA. The effect of HOA on SI correlated positively with physical fitness upon enrollment. Principal components analysis of either fasted or fed-state metabolites identified one factor affected by diet and heavily weighted by the PA/OA ratio of serum and muscle lipids. In women, this factor correlated inversely with SI in the fasted and fed states. Medium-chain acylcarnitines emerged as strong negative correlates of SI, and the HOA diet was accompanied by lower serum and muscle ceramide concentrations and reductions in molecular biomarkers of inflammatory and oxidative stress. This study provides evidence that the dietary PA/OA ratio impacts diabetes risk in women.
Over the past 15 years, the biomedical research community has increased its efforts to produce ontologies encoding biomedical knowledge, and to provide the corresponding infrastructure to maintain them. As ontologies are becoming a central part of biological and biomedical research, a communication channel to publish frequent updates and latest developments on them would be an advantage.
Here, we introduce the JBMS thematic series on Biomedical Ontologies. The aim of the series is to disseminate the latest developments in research on biomedical ontologies and provide a venue for publishing newly developed ontologies, updates to existing ontologies as well as methodological advances, and selected contributions from conferences and workshops. We aim to give this thematic series a central role in the exploration of ongoing research in biomedical ontologies and intend to work closely together with the research community towards this aim. Researchers and working groups are encouraged to provide feedback on novel developments and special topics to be integrated into the existing publication cycles.
A−β+ ketosis-prone diabetes (KPD) is an emerging syndrome of obesity, unprovoked ketoacidosis, reversible β-cell dysfunction, and near-normoglycemic remission. We combined metabolomics with targeted kinetic measurements to investigate its pathophysiology. Fasting plasma fatty acids, acylcarnitines, and amino acids were quantified in 20 KPD patients compared with 19 nondiabetic control subjects. Unique signatures in KPD—higher glutamate but lower glutamine and citrulline concentrations, increased β-hydroxybutyryl-carnitine, decreased isovaleryl-carnitine (a leucine catabolite), and decreased tricarboxylic acid (TCA) cycle intermediates—generated hypotheses that were tested through stable isotope/mass spectrometry protocols in nine new-onset, stable KPD patients compared with seven nondiabetic control subjects. Free fatty acid flux and acetyl CoA flux and oxidation were similar, but KPD had slower acetyl CoA conversion to β-hydroxybutyrate; higher fasting β-hydroxybutyrate concentration; slower β-hydroxybutyrate oxidation; faster leucine oxidative decarboxylation; accelerated glutamine conversion to glutamate without increase in glutamate carbon oxidation; and slower citrulline flux, with diminished glutamine amide–nitrogen transfer to citrulline. The confluence of metabolomic and kinetic data indicate a distinctive pathogenic sequence: impaired ketone oxidation and fatty acid utilization for energy, leading to accelerated leucine catabolism and transamination of α-ketoglutarate to glutamate, with impaired TCA anaplerosis of glutamate carbon. They highlight a novel process of defective energy production and ketosis in A−β+ KPD.
Critically ill patients are frequently at risk of neurological dysfunction as a result of primary neurological conditions or secondary insults. Determining which aspects of brain function are affected and how best to manage the neurological dysfunction can often be difficult and is complicated by the limited information that can be gained from clinical examination in such patients and the effects of therapies, notably sedation, on neurological function. Methods to measure and monitor brain function have evolved considerably in recent years and now play an important role in the evaluation and management of patients with brain injury. Importantly, no single technique is ideal for all patients and different variables will need to be monitored in different patients; in many patients, a combination of monitoring techniques will be needed. Although clinical studies support the physiologic feasibility and biologic plausibility of management based on information from various monitors, data supporting this concept from randomized trials are still required.
Mitochondrial dysfunction has been implicated in the pathogenesis of type 2 diabetes. Identifying novel regulators of mitochondrial bioenergetics will broaden our understanding of regulatory checkpoints that coordinate complex metabolic pathways. We previously showed that Nur77, an orphan nuclear receptor of the NR4A family, regulates the expression of genes linked to glucose utilization. Here we demonstrate that expression of Nur77 in skeletal muscle also enhances mitochondrial function. We generated MCK-Nur77 transgenic mice that express wild-type Nur77 specifically in skeletal muscle. Nur77-overexpressing muscle had increased abundance of oxidative muscle fibers and mitochondrial DNA content. Transgenic muscle also exhibited enhanced oxidative metabolism, suggestive of increased mitochondrial activity. Metabolomic analysis confirmed that Nur77 transgenic muscle favored fatty acid oxidation over glucose oxidation, mimicking the metabolic profile of fasting. Nur77 expression also improved the intrinsic respiratory capacity of isolated mitochondria, likely due to the increased abundance of complex I of the electron transport chain. These changes in mitochondrial metabolism translated to improved muscle contractile function ex vivo and improved cold tolerance in vivo. Our studies outline a novel role for Nur77 in the regulation of oxidative metabolism and mitochondrial activity in skeletal muscle.
Nr4a; nuclear receptor; mitochondria
Sepsis-associated brain dysfunction has been linked to white matter lesions (leukoencephalopathy) and ischemic stroke. Our objective was to assess the prevalence of brain lesions in septic shock patients requiring magnetic resonance imaging (MRI) for an acute neurologic change.
Seventy-one septic shock patients were included in a prospective observational study. Patients underwent daily neurological examination. Brain MRI was obtained in patients who developed focal neurological deficit, seizure, coma, or delirium. Electroencephalogy was performed in case of coma, delirium, or seizure. Leukoencephalopathy was graded and considered present when white matter lesions were either confluent or diffuse. Patient outcome was evaluated at 6 months with the Glasgow Outcome Scale (GOS).
We included 71 patients with median age of 65 years (56 to 76) and SAPS II at admission of 49 (38 to 60). MRI was indicated on focal neurological sign in 13 (18%), seizure in 7 (10%), coma in 33 (46%), and delirium in 35 (49%). MRI was normal in 37 patients (52%) and showed cerebral infarcts in 21 (29%), leukoencephalopathy in 15 (21%), and mixed lesions in 6 (8%). EEG malignant pattern was more frequent in patients with ischemic stroke or leukoencephalopathy. Ischemic stroke was independently associated with disseminated intravascular coagulation (DIC), focal neurologic signs, increased mortality, and worse GOS at 6 months.
Brain MRI in septic shock patients who developed acute brain dysfunction can reveal leukoencephalopathy and ischemic stroke, which is associated with DIC and increased mortality.
A peptide designed to induce apoptosis of endothelium in white adipose tissue (WAT) decreases adiposity. The goal of this work is to determine whether targeting of WAT endothelium results in impaired glucose regulation as a result of impaired WAT function. Glucose tolerance tests were performed on days 2 and 3 of treatment with vehicle (HF-V) or proapoptotic peptide (HF-PP) and mice pair-fed to HF-PP (HF-PF) in obese mice on a high-fat diet (HFD). Serum metabolic variables, including lipid profile, adipokines, individual fatty acids, and acylcarnitines, were measured. Microarray analysis was performed in epididymal fat of lean or obese mice treated with vehicle or proapoptotic peptide (PP). PP rapidly and potently improved glucose tolerance of obese mice in a weight- and food intake–independent manner. Serum insulin and triglycerides were decreased in HF-PP relative to HF-V. Levels of fatty acids and acylcarnitines were distinctive in HF-PP compared with HF-V or HF-PF. Microarray analysis in AT revealed that pathways involved in mitochondrial dysfunction, oxidative phosphorylation, and branched-chain amino acid degradation were changed by exposure to HFD and were reversed by PP administration. These studies suggest a novel role of the AT vasculature in glucose homeostasis and lipid metabolism.
Clinical monitoring of cerebral blood flow (CBF) autoregulation in patients undergoing liver transplantation may provide a means for optimizing blood pressure to reduce the risk of brain injury. The purpose of this pilot project is to test the feasibility of autoregulation monitoring with transcranial Doppler (TCD) and near infrared spectroscopy (NIRS) in patients undergoing liver transplantation and to assess changes that may occur perioperatively.
We performed a prospective observational study in 9 consecutive patients undergoing orthotopic liver transplantation. Patients were monitored with TCD and NIRS. A continuous Pearson’s correlation coefficient was calculated between mean arterial pressure (MAP) and CBF velocity and between MAP and NIRS data, rendering the variables mean velocity index (Mx) and cerebral oximetry index (COx), respectively. Both Mx and COx were averaged and compared during the dissection phase, anhepatic phase, first 30 mins of reperfusion, and remaining reperfusion phase. Impaired autoregulation was defined as Mx ≥ 0.4.
Autoregulation was impaired in one patient during all phases of surgery, in two patients during the anhepatic phase, and in one patient during reperfusion. Impaired autoregulation was associated with a MELD score > 15 (p=0.015) and postoperative seizures or stroke (p<0.0001). Analysis of Mx categorized in 5-mmHg bins revealed that MAP at the lower limit of autoregulation (MAP when Mx increased to ≥ 0.4) ranged between 40 and 85 mmHg. Average Mx and average COx were significantly correlated (p=0.0029). The relationship between COx and Mx remained when only patients with bilirubin > 1.2 mg/dL were evaluated (p=0.0419). There was no correlation between COx and baseline bilirubin (p=0.2562) but MELD score and COx were correlated (p=0.0458). Average COx was higher for patients with a MELD score > 15 (p=0.073) and for patients with a neurologic complication than for patients without neurologic complications (p=0.0245).
These results suggest that autoregulation is impaired in patients undergoing liver transplantation, even in the absence of acute, fulminant liver failure. Identification of patients at risk for neurologic complications after surgery may allow for prompt neuroprotective interventions, including directed pressure management.
Concentrations of acetyl–coenzyme A and nicotinamide adenine dinucleotide (NAD+) affect histone acetylation and thereby couple cellular metabolic status and transcriptional regulation. We report that the ketone body d-β-hydroxybutyrate (βOHB) is an endogenous and specific inhibitor of class I histone deacetylases (HDACs). Administration of exogenous βOHB, or fasting or calorie restriction, two conditions associated with increased βOHB abundance, all increased global histone acetylation in mouse tissues. Inhibition of HDAC by βOHB was correlated with global changes in transcription, including that of the genes encoding oxidative stress resistance factors FOXO3A and MT2. Treatment of cells with βOHB increased histone acetylation at the Foxo3a and Mt2 promoters, and both genes were activated by selective depletion of HDAC1 and HDAC2. Consistent with increased FOXO3A and MT2 activity, treatment of mice with βOHB conferred substantial protection against oxidative stress.
Constant technological advances have allowed scientists in biology to migrate from conventional single-omics to multi-omics experimental approaches, challenging bioinformatics to bridge this multi-tiered information. Ongoing research in renal biology is no exception. The results of large-scale and/or high throughput experiments, presenting a wealth of information on kidney disease are scattered across the web. To tackle this problem, we recently presented the KUPKB, a multi-omics data repository for renal diseases.
In this article, we describe KUPNetViz, a biological graph exploration tool allowing the exploration of KUPKB data through the visualization of biomolecule interactions. KUPNetViz enables the integration of multi-layered experimental data over different species, renal locations and renal diseases to protein-protein interaction networks and allows association with biological functions, biochemical pathways and other functional elements such as miRNAs. KUPNetViz focuses on the simplicity of its usage and the clarity of resulting networks by reducing and/or automating advanced functionalities present in other biological network visualization packages. In addition, it allows the extrapolation of biomolecule interactions across different species, leading to the formulations of new plausible hypotheses, adequate experiment design and to the suggestion of novel biological mechanisms. We demonstrate the value of KUPNetViz by two usage examples: the integration of calreticulin as a key player in a larger interaction network in renal graft rejection and the novel observation of the strong association of interleukin-6 with polycystic kidney disease.
The KUPNetViz is an interactive and flexible biological network visualization and exploration tool. It provides renal biologists with biological network snapshots of the complex integrated data of the KUPKB allowing the formulation of new hypotheses in a user friendly manner.
Biology-focused databases and software define bioinformatics and their use is central to computational biology. In such a complex and dynamic field, it is of interest to understand what resources are available, which are used, how much they are used, and for what they are used. While scholarly literature surveys can provide some insights, large-scale computer-based approaches to identify mentions of bioinformatics databases and software from primary literature would automate systematic cataloguing, facilitate the monitoring of usage, and provide the foundations for the recovery of computational methods for analysing biological data, with the long-term aim of identifying best/common practice in different areas of biology.
We have developed bioNerDS, a named entity recogniser for the recovery of bioinformatics databases and software from primary literature. We identify such entities with an F-measure ranging from 63% to 91% at the mention level and 63-78% at the document level, depending on corpus. Not attaining a higher F-measure is mostly due to high ambiguity in resource naming, which is compounded by the on-going introduction of new resources. To demonstrate the software, we applied bioNerDS to full-text articles from BMC Bioinformatics and Genome Biology. General mention patterns reflect the remit of these journals, highlighting BMC Bioinformatics’s emphasis on new tools and Genome Biology’s greater emphasis on data analysis. The data also illustrates some shifts in resource usage: for example, the past decade has seen R and the Gene Ontology join BLAST and GenBank as the main components in bioinformatics processing.
Conclusions We demonstrate the feasibility of automatically identifying resource names on a large-scale from the scientific literature and show that the generated data can be used for exploration of bioinformatics database and software usage. For example, our results help to investigate the rate of change in resource usage and corroborate the suspicion that a vast majority of resources are created, but rarely (if ever) used thereafter. bioNerDS is available at http://bionerds.sourceforge.net/.