Comparison of Accu Chek Inform II point-of-care test blood glucose meter with Hexokinase Plasma method for a diabetes mellitus population during surgery under general anesthesia

Purpose Blood glucose (BG) concentrations of patients with diabetes mellitus (DM) are monitored during surgery to prevent hypo- and hyperglycemia. Access to point-of-care test (POCT) glucose meters at an operating room will usually provide monitoring at shorter intervals and may improve glycemic control. However, these meters are not validated for patients under general anesthesia. Methods This cross-sectional study included 75 arterial BG measurements from 75 patients (71 with DM, mostly insulin dependent) who underwent elective non-cardiac surgery under general anesthesia. Arterial blood samples were taken at least 60 minutes after induction. One drop of blood was used for Accu Chek Inform II (ACI II) POCT BG meter and the residual blood was sent to the clinical laboratory for a Hexokinase Plasma reference method. A Bland-Altman plot was used to visualize the differences between both methods, and correlation was assessed using the intra-class correlation coefficient (ICC). Results The results showed an estimated mean difference of 0.8 mmol/L between ACI II and the reference method, with limits of agreement equal to -0.6 and 2.2 mmol/L. In general, the reference method produced higher values than ACI II. ICC was 0.955 (95% CI 0.634-0.986), P &lt; 0.001, and concordance correlation coefficient (CCC) was 0.955 (95% CI 0.933-0.970). Conclusion Arterial BG measurements during surgery in patients with DM under general anesthesia using POCT BG meter are in general lower than laboratory measurements, but the ICC and CCC show a clinically acceptable correlation. We conclude that POCT measurements conducted on arterial specimens using the ACI II provide sufficiently accurate results for glucose measurement during surgery under general anesthesia.</p

A dynamic Bayesian network for identifying protein-binding footprints from single molecule-based sequencing data

Motivation: A global map of transcription factor binding sites (TFBSs) is critical to understanding gene regulation and genome function. DNaseI digestion of chromatin coupled with massively parallel sequencing (digital genomic footprinting) enables the identification of protein-binding footprints with high resolution on a genome-wide scale. However, accurately inferring the locations of these footprints remains a challenging computational problem

cAMP/PKA signaling balances respiratory activity with mitochondria dependent apoptosis via transcriptional regulation

Background Appropriate control of mitochondrial function, morphology and biogenesis are crucial determinants of the general health of eukaryotic cells. It is therefore imperative that we understand the mechanisms that co-ordinate mitochondrial function with environmental signaling systems. The regulation of yeast mitochondrial function in response to nutritional change can be modulated by PKA activity. Unregulated PKA activity can lead to the production of mitochondria that are prone to the production of ROS, and an apoptotic form of cell death. Results We present evidence that mitochondria are sensitive to the level of cAMP/PKA signaling and can respond by modulating levels of respiratory activity or committing to self execution. The inappropriate activation of one of the yeast PKA catalytic subunits, Tpk3p, is sufficient to commit cells to an apoptotic death through transcriptional changes that promote the production of dysfunctional, ROS producing mitochondria. Our data implies that cAMP/PKA regulation of mitochondrial function that promotes apoptosis engages the function of multiple transcription factors, including HAP4, SOK2 and SCO1. Conclusions We propose that in yeast, as is the case in mammalian cells, mitochondrial function and biogenesis are controlled in response to environmental change by the concerted regulation of multiple transcription factors. The visualization of cAMP/TPK3 induced cell death within yeast colonies supports a model that PKA regulation plays a physiological role in coordinating respiratory function and cell death with nutritional status in budding yeast

Dissecting complex transcriptional responses using pathway-level scores based on prior information

<p>Abstract</p> <p>Background</p> <p>The genomewide pattern of changes in mRNA expression measured using DNA microarrays is typically a complex superposition of the response of multiple regulatory pathways to changes in the environment of the cells. The use of prior information, either about the function of the protein encoded by each gene, or about the physical interactions between regulatory factors and the sequences controlling its expression, has emerged as a powerful approach for dissecting complex transcriptional responses.</p> <p>Results</p> <p>We review two different approaches for combining the noisy expression levels of multiple individual genes into robust pathway-level differential expression scores. The first is based on a comparison between the distribution of expression levels of genes within a predefined gene set and those of all other genes in the genome. The second starts from an estimate of the strength of genomewide regulatory network connectivities based on sequence information or direct measurements of protein-DNA interactions, and uses regression analysis to estimate the activity of gene regulatory pathways. The statistical methods used are explained in detail.</p> <p>Conclusion</p> <p>By avoiding the thresholding of individual genes, pathway-level analysis of differential expression based on prior information can be considerably more sensitive to subtle changes in gene expression than gene-level analysis. The methods are technically straightforward and yield results that are easily interpretable, both biologically and statistically.</p

TESTLoc: protein subcellular localization prediction from EST data

Abstract Background The eukaryotic cell has an intricate architecture with compartments and substructures dedicated to particular biological processes. Knowing the subcellular location of proteins not only indicates how bio-processes are organized in different cellular compartments, but also contributes to unravelling the function of individual proteins. Computational localization prediction is possible based on sequence information alone, and has been successfully applied to proteins from virtually all subcellular compartments and all domains of life. However, we realized that current prediction tools do not perform well on partial protein sequences such as those inferred from Expressed Sequence Tag (EST) data, limiting the exploitation of the large and taxonomically most comprehensive body of sequence information from eukaryotes. Results We developed a new predictor, TESTLoc, suited for subcellular localization prediction of proteins based on their partial sequence conceptually translated from ESTs (EST-peptides). Support Vector Machine (SVM) is used as computational method and EST-peptides are represented by different features such as amino acid composition and physicochemical properties. When TESTLoc was applied to the most challenging test case (plant data), it yielded high accuracy (~85%). Conclusions TESTLoc is a localization prediction tool tailored for EST data. It provides a variety of models for the users to choose from, and is available for download at http://megasun.bch.umontreal.ca/~shenyq/TESTLoc/TESTLoc.html</p

The demography of fine roots in response to patches of water and nitrogen

Fine root demography was quantified in response to patches of increased water and nitrogen availability in a natural, second-growth, mixed hardwood forest in northern Michigan, USA. As expected, the addition of water and water plus nitrogen resulted in a significant overall increase in the production of new fine roots. New root production was much greater in response to water plus nitrogen when compared with water alone, and the duration of new root production was related to the length of resource addition in the water plus nitrogen treatments; the average difference in new root length between the 20 vs. 40 d additions of water plus nitrogen amounted to almost 600%. Roots produced in response to the additions of water and water plus nitrogen lived longer than roots in the control treatments. Thus, additions of water and water plus nitrogen influenced both the proliferation of new roots and their longevity, with both proliferation and longevity related to the type and duration of resource supply. Results suggest that root longevity and mortality may be plastic in response to changes in soil resource availability, as is well known for root proliferation.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/65770/1/j.1469-8137.1993.tb03905.x.pd

The 19S proteasome subcomplex promotes the targeting of NuA4 HAT to the promoters of ribosomal protein genes to facilitate the recruitment of TFIID for transcriptional initiation in vivo

Previous studies have implicated SAGA (Spt-Ada-Gcn5-acetyltransferase) and TFIID (Transcription factor-IID)-dependent mechanisms of transcriptional activation in yeast. SAGA-dependent transcriptional activation is further regulated by the 19S proteasome subcomplex. However, the role of the 19S proteasome subcomplex in transcriptional activation of the TFIID-dependent genes has not been elucidated. Therefore, we have performed a series of chromatin immunoprecipitation, mutational and transcriptional analyses at the TFIID-dependent ribosomal protein genes such as RPS5, RPL2B and RPS11B. We find that the 19S proteasome subcomplex is recruited to the promoters of these ribosomal protein genes, and promotes the association of NuA4 (Nucleosome acetyltransferase of histone H4) co-activator, but not activator Rap1p (repressor-activator protein 1). These observations support that the 19S proteasome subcomplex enhances the targeting of co-activator at the TFIID-dependent promoter. Such an enhanced targeting of NuA4 HAT (histone acetyltransferase) promotes the recruitment of the TFIID complex for transcriptional initiation. Collectively, our data demonstrate that the 19S proteasome subcomplex enhances the targeting of NuA4 HAT to activator Rap1p at the promoters of ribosomal protein genes to facilitate the recruitment of TFIID for transcriptional stimulation, hence providing a new role of the 19S proteasome subcomplex in establishing a specific regulatory network at the TFIID-dependent promoter for productive transcriptional initiation in vivo

Development and Validation of a Risk Score for Chronic Kidney Disease in HIV Infection Using Prospective Cohort Data from the D:A:D Study

Ristola M. on työryhmien DAD Study Grp ; Royal Free Hosp Clin Cohort ; INSIGHT Study Grp ; SMART Study Grp ; ESPRIT Study Grp jäsen.Background Chronic kidney disease (CKD) is a major health issue for HIV-positive individuals, associated with increased morbidity and mortality. Development and implementation of a risk score model for CKD would allow comparison of the risks and benefits of adding potentially nephrotoxic antiretrovirals to a treatment regimen and would identify those at greatest risk of CKD. The aims of this study were to develop a simple, externally validated, and widely applicable long-term risk score model for CKD in HIV-positive individuals that can guide decision making in clinical practice. Methods and Findings A total of 17,954 HIV-positive individuals from the Data Collection on Adverse Events of Anti-HIV Drugs (D:A:D) study with >= 3 estimated glomerular filtration rate (eGFR) values after 1 January 2004 were included. Baseline was defined as the first eGFR > 60 ml/min/1.73 m2 after 1 January 2004; individuals with exposure to tenofovir, atazanavir, atazanavir/ritonavir, lopinavir/ritonavir, other boosted protease inhibitors before baseline were excluded. CKD was defined as confirmed (>3 mo apart) eGFR In the D:A:D study, 641 individuals developed CKD during 103,185 person-years of follow-up (PYFU; incidence 6.2/1,000 PYFU, 95% CI 5.7-6.7; median follow-up 6.1 y, range 0.3-9.1 y). Older age, intravenous drug use, hepatitis C coinfection, lower baseline eGFR, female gender, lower CD4 count nadir, hypertension, diabetes, and cardiovascular disease (CVD) predicted CKD. The adjusted incidence rate ratios of these nine categorical variables were scaled and summed to create the risk score. The median risk score at baseline was -2 (interquartile range -4 to 2). There was a 1: 393 chance of developing CKD in the next 5 y in the low risk group (risk score = 5, 505 events), respectively. Number needed to harm (NNTH) at 5 y when starting unboosted atazanavir or lopinavir/ritonavir among those with a low risk score was 1,702 (95% CI 1,166-3,367); NNTH was 202 (95% CI 159-278) and 21 (95% CI 19-23), respectively, for those with a medium and high risk score. NNTH was 739 (95% CI 506-1462), 88 (95% CI 69-121), and 9 (95% CI 8-10) for those with a low, medium, and high risk score, respectively, starting tenofovir, atazanavir/ritonavir, or another boosted protease inhibitor. The Royal Free Hospital Clinic Cohort included 2,548 individuals, of whom 94 individuals developed CKD (3.7%) during 18,376 PYFU (median follow-up 7.4 y, range 0.3-12.7 y). Of 2,013 individuals included from the SMART/ESPRIT control arms, 32 individuals developed CKD (1.6%) during 8,452 PYFU (median follow-up 4.1 y, range 0.6-8.1 y). External validation showed that the risk score predicted well in these cohorts. Limitations of this study included limited data on race and no information on proteinuria. Conclusions Both traditional and HIV-related risk factors were predictive of CKD. These factors were used to develop a risk score for CKD in HIV infection, externally validated, that has direct clinical relevance for patients and clinicians to weigh the benefits of certain antiretrovirals against the risk of CKD and to identify those at greatest risk of CKD.Peer reviewe