1.
Does the fat-protein meal increase postprandial glucose level in type 1 diabetes patients on insulin pump: the conclusion of a randomized study.
Source
1 Institute of the Mother and Child , Warsaw, Poland .
Abstract
Abstract Background: Our study examines the hypothesis that in addition to sugar starch-type diet, a fat-protein meal elevates postprandial glycemia as well, and it should be included in calculated prandial insulin dose accordingly. The goal was to determine the impact of the inclusion of fat-protein nutrients in the general algorithm for the mealtime insulin dose calculator on 6-h postprandial glycemia. Subjects and Methods: Of 26 screened type 1 diabetes patients using an insulin pump, 24 were randomly assigned to an experimental Group A and to a control Group B. Group A received dual-wave insulin boluses for their pizza dinner, consisting of 45 g/180 kcal of carbohydrates and 400 kcal from fat-protein where the insulin dose was calculated using the following algorithm: n Carbohydrate Units×ICR+n Fat-Protein Units×ICR/6 h (standard+extended insulin boluses), where ICR represents the insulin-to-carbohydrate ratio. For the control Group B, the algorithm used was n Carbohydrate Units×ICR. The glucose, C-peptide, and glucagon concentrations were evaluated before the meal and at 30, 60, 120, 240, and 360 min postprandial. Results: There were no statistically significant differences involving patients' metabolic control, C-peptide, glucagon secretion, or duration of diabetes between Group A and B. In Group A the significant glucose increment occurred at 120-360 min, with its maximum at 240 min: 60.2 versus -3.0 mg/dL (P=0.04), respectively. There were no significant differences in glucagon and C-peptide concentrations postprandial. Conclusions: A mixed meal effectively elevates postprandial glycemia after 4-6 h. Dual-wave insulin bolus, in which insulin is calculated for both the carbohydrates and fat proteins, is effective in controlling postprandial glycemia.
Serum concentrations of insulin-like growth factor (IGF)-1 and IGF binding protein-3 (IGFBP-3), IGF-1/IGFBP-3 ratio, and markers of bone turnover: reference values for French children and adolescents and z-score comparability with other references.
Source
INSERM, CIC-EC CIE5, Paris, France.
Abstract
BACKGROUND:
A reference model for converting serum growth factor and bone metabolism markers into an SD score (SDS) is required for clinical practice. We aimed to establish reference values of serum insulin-like growth factor-1 (IGF-1) and IGF binding protein 3 (IGFBP-3) concentrations and bone metabolism markers in French children, to generate a model for converting values into SDS for age, sex, and pubertal stage.
METHODS:
We carried out a cross-sectional study of 1119 healthy white children ages 6-20 years. We assessed concentrations of serum IGF-1, IGFBP-3, carboxyterminal telopeptide α1 chain of type I collagen (CrossLaps), and bone alkaline phosphatase concentrations and height, weight, and pubertal stage, and used semiparametric regression to develop a model.
RESULTS:
A single regression model to calculate the SDSs with an online calculator was provided. A positive relationship was found between SDS for serum IGF-1 and IGFBP-3, IGF/IGFBP-3 mol/L ratio, and anthropometric parameters (P < 0.0001), with slightly greater effects observed for height than for body mass index (BMI). There was a negative relationship between serum CrossLaps concentration and BMI, and a positive relationship between serum CrossLaps concentration and height. A comparison of serum IGF-1 reference databases for children showed marked variation as a function of age and pubertal group; smooth changes with age and puberty were observed only in our model.
CONCLUSIONS:
This new model for the assessment of SDS reference values specific for age, sex, and pubertal stage may help to increase the diagnostic power of these parameters for the assessment of growth and bone metabolism disorders. This study also provides information about the physiological role of height and BMI for the interpretation of these parameters.
Comparative evaluation of simple indices of graft function after islet transplantation.
Source
Nutrition and Metabolism Unit, Division of Metabolic and Cardiovascular Sciences, San Raffaele Scientific Institute, Milano, Italy.
Abstract
BACKGROUND:
Several simple measures of graft function after islet transplantation have been proposed but a comparative evaluation is lacking. Here, we compared the performance of five indices of β-cell function: β-score, transplant estimated function (TEF), homeostasis model assessment (HOMA) 2-B%, C-peptide/glucose ratio, and Secretory Units of Islets in Transplantation (SUIT).
METHODS:
Two cohorts of transplanted patients were analyzed. Cohort 1 consisted of 14 recipients with type 1 diabetes of islet transplantation whereas cohort 2 consisted of 21 recipients with type 1 diabetes of cultured islet cell graft. The five surrogate indices were compared against the first- and second-phase insulin response to arginine in cohort 1, and against the C-peptide response to a hyperglycemic clamp in cohort 2.
RESULTS:
We found that the performances of the five surrogate indices were close one to each other in cohort 1. The correlation coefficients ranged 0.62 to 0.67 and 0.62 to 0.68 against the first- and second-phase insulin response to arginine, respectively. In cohort 2, we found that the β-score, TEF, C-peptide/glucose ratio, and SUIT were reasonably well correlated with the clamp response (correlation coefficients were in the range 0.71-0.81), whereas HOMA2-B% showed a modest performance (r=0.54). HOMA2-B% could not be evaluated in one patient whose fasting glucose concentration level was below the lower bound indicated by the HOMA calculator (3 mmol/L). SUIT could not be evaluated in three patients whose fasting glucose concentration was below the glucose threshold of the SUIT formula (3.43 mmol/L).
CONCLUSION:
In summary, no single index outperformed the others. Nevertheless, when the benefit to cost ratio is considered, TEF stands out for its good performance at a very low cost.
Defining intrinsic hydrophobicity of amino acids' side chains in random coil conformation. Reversed-phase liquid chromatography of designed syntheticpeptides vs. random peptide data sets.
Source
Manitoba Centre for Proteomics and Systems Biology, Canada.
Abstract
The two leading RP-HPLC approaches for deriving hydrophobicity values of amino acids utilize either sets of designed synthetic peptides or extended random datasets often extracted from proteomics experiments. We find that the best examples of these two methods provide virtually identical results--with exception of Lys, Arg, and His. The intrinsic hydrophobicity values of the remaining residues as determined by Kovacs et al. (Biopolymers 84 (2006) 283) correlates with an R(2)-value of 0.995+ against amino acid retention coefficients from our Sequence Specific Retention Calculatormodel (Anal. Chem. 78 (2006) 7785). This novel finding lays the foundation for establishing consensus amino acids hydrophobicity scales as determined by RP-HPLC. Simultaneously, we find the assignment of hydrophobicity values for charged residues (Lys, Arg and His at pH 2) is ambiguous; their retention contribution is strongly affected by the overallpeptide hydrophobicity. The unique behavior of the basic residues is related to the dualistic character of the RP peptideretention mechanism, where both hydrophobic and ion-pairing interactions are involved. We envision the introduction of "sliding" hydrophobicity scales for charged residues as a new element in peptide retention prediction models. We also show that when using a simple additive retention prediction model, the "correct" coefficient value optimization (0.98+ correlation against values determined by synthetic peptide approach) requires a training set of at least 100 randomly selected peptides.
Copyright © 2011 Elsevier B.V. All rights reserved.
Implementation of a dose calculator for vancomycin to achieve target trough levels of 15-20 microg/mL in persons undergoing hemodialysis.
Source
Department Nephrology and Infectious Diseases, AZ Sint-Jan Brugge-Oostende AV, Bruges, Belgium.
Abstract
(See the article by Brown et al, on pages 164-166.)
BACKGROUND:
Vancomycin is a key antibiotic for the treatment of Gram-positive bacterial infections in patients undergoing dialysis. Vancomycin has a narrow therapeutic range. Overdosing imposes a risk of nephro- and ototoxicity, wherease underdosing predisposes to treatment failure and the emergence of drug resistance. Trough levels of 15-20 μg/mL have been identified as the optimal target trough levels.
METHODS:
A multivariate model called the vancomycin dose calculator (VDC) was prospectively developed and validated to permit accurate vancomycin dosing in persons undergoing hemodialysis.
RESULTS:
The model identified 3 simple parameters that were responsible for 94.6% of the variance observed: predialysis vancomycin trough level, dry body weight, and period to the next dialysis session. Maintenance dosing was accurate in 77.9% of patients, whereas major over- and underdosing were avoided in the remaining patients. The mean measured trough level of 16.5 μg/mL was 5.6% lower than the mean predicted trough level of 17.5 μg/mL. With regard to loading doses, a fixed loading dose of 20 mg/kg led to subtherapeutic trough levels in one-half of patients.
CONCLUSIONS:
The VDC permits accurate vancomycin maintenance dosing based on predialysis trough level, dry body weight, and period to the next dialysis session in the majority of patients undergoing hemodialysis. Higher loading doses that accounted for the period to the next dialysis may be more appropriate than fixed loading doses used in this study.
The ribosome binding site calculator.
Source
Department of Chemical Engineering, Pennsylvania State University, University Park, Pennsylvania, USA.
Abstract
The Ribosome Binding Site (RBS) Calculator is a design method for predicting and controlling translation initiation and protein expression in bacteria. The method can predict the rate of translation initiation for every start codon in an mRNA transcript. The method may also optimize a synthetic RBS sequence to achieve a targeted translation initiation rate. Using the RBS Calculator, a protein coding sequence's translation rate may be rationally controlled across a 100,000+ fold range. We begin by providing an overview of the potential biotechnology applications of the RBS Calculator, including the optimization of synthetic metabolic pathways and genetic circuits. We then detail the definitions, methodologies, and algorithms behind the RBS Calculator's thermodynamic model and optimization method. Finally, we outline a protocol for precisely measuring steady-state fluorescent protein expression levels. These methods and protocols provide a clear explanation of the RBS Calculator and its uses.
Copyright © 2011 Elsevier Inc. All rights reserved.
- PMID:
- 21601672
- [PubMed - indexed for MEDLINE]
Cardiac risk scores in high-risk Hispanics and the predictive value of BNP.
Source
University of California Los Angeles School of Nursing, Los Angeles, CA 90095, USA. aoconnel@sonnet.ucla.edu
Abstract
AIMS:
The purpose of this study was to calculate cardiac risk scores in Hispanic subjects and to determine the predictive value of adding B-type natriuretic peptide in identifying those with asymptomatic left ventricular dysfunction as a measure of cardiovascular disease.
BACKGROUND:
Hispanics have higher rates of cardiovascular risk factors leading to coronary heart disease, asymptomatic left ventricular dysfunction and cardiovascular events. Assessing cardiac risk in these groups is important to identify those at high risk for future cardiovascular events. The use of biomarkers such as B-type natriuretic peptidemay increase the accuracy of risk prediction.
DESIGN:
This study used a descriptive, cross-sectional study design to determine the utility of the standard risk assessment tools (Adult Treatment Panel III and the Framingham Risk Scores risk calculator) and the B-type natriureticpeptide biomarker to estimate coronary heart disease risk in low-income, Hispanic participants.
METHODS:
A sample of 71 patients (age 52 SD 11, 69% female) with multiple cardiovascular risk factors seen at an ambulatory clinic at a county facility was enrolled in the study. Sociodemographic and medical history information were obtained. Two widely used risk calculators (Adult Treatment Panel III and Framingham Risk Scores) were used to estimate 10-year coronary heart disease risk in each subject. Baseline B-type natriuretic peptide measurement and echocardiography were performed with each subject to evaluate presence of asymptomatic left ventricular dysfunction. Receiver operating curve analyses were performed to compare predictability, sensitivity and specificity of the traditional risk scores against the B-type natriuretic peptide level to detect asymptomatic left ventricular dysfunction.
RESULTS:
Overall mean risk scores were 5% (SD 5%) (Adult Treatment Panel III) and 10% (SD 7%) (Framingham Risk Scores). Mean B-type natriuretic peptide levels were 108·5 (SD 191·5) pg/ml. Echocardiogram results revealed a high proportion of subjects with asymptomatic left ventricular dysfunction (74·6%). The receiver operating curves showed an area under the curve of 0·67 for B-type natriuretic peptide (p < 0·05), 0·64 (p = NS) for Adult Treatment Panel III and 0·56 (p = NS) for Framingham Risk Scores, evidence that B-type natriuretic peptide does significantly better than Adult Treatment Panel or Framingham Risk Scores in predicting asymptomatic left ventricular dysfunction.
CONCLUSION:
The inclusion of B-type natriuretic peptide with traditional risk scores may be helpful in predicting risk and asymptomatic left ventricular dysfunction in high-risk Hispanics.
RELEVANCE TO CLINICAL PRACTICE:
Cardiac risk scores can assist clinicians in identifying patients at high risk for developing coronary heart disease.
© 2011 Blackwell Publishing Ltd.
Using HPLC-mass spectrometry to teach proteomics concepts with problem-based techniques.
Source
Department of Chemistry, Hope College, Holland, Michigan 49423; Department of Biology, Hope College, Holland, Michigan 49423; Montana State University, Bozeman, Montana. short@hope.edu.
Abstract
Practical instruction of proteomics concepts was provided using high-performance liquid chromatography coupled with a mass selective detection system (HPLC-MS) for the analysis of simulated protein digests. The samples were prepared from selected dipeptides in order to facilitate the mass spectral identification. As part of the prelaboratory preparation, students calculated the parent ion patterns of the dipeptides using peptide calculator websites. Following instruction on the use of the HPLC-MS instrument, students analyzed mixtures of the dipeptides and identified the individual dipeptides in the unknowns. In addition, purchased chicken egg white lysozyme alkylated with iodoacetamide and digested with trypsin was analyzed using the same approach. Key tryptic peptides were identified from the HPLC-MS chromatogram with information generated with the FindPept tool. This experiment demonstrates that complex concepts can be taught in the undergraduate biochemistry laboratory using a problem-based approach.
Copyright © 2010 The International Union of Biochemistry and Molecular Biology, Inc.
- PMID:
- 21567835
- [PubMed - in process]
A novel insulin unit calculator for the management of type 1 diabetes.
Source
Department of Endocrinology and Diabetes, University Campus Bio-Medico, Rome, Italy.
Abstract
BACKGROUND:
Intensive insulin therapy is the gold standard therapy for type 1 diabetes (T1D) patients. To achieve optimal glycemic control, adjustments of insulin dose at mealtimes must be made taking into account several parameters: blood glucose levels, insulin/carbohydrate ratio, carbohydrate intake, and physical activity. Calsulin (Thorpe Products Ltd., Cambridge, UK) is a new tool for the administration of insulin dose before each meal. The aim of this study was to evaluate the efficacy of Calsulin on metabolic control in T1D patients undergoing intensive insulin therapy.
SUBJECTS AND METHODS:
Forty consecutive patients affected by T1D, 18-65 years old, with disease duration of >1 year, were randomized to Calsulin or to the control group. Hemoglobin A1c (HbA1c) was evaluated at entry into the study and at 3- and 6-month follow-ups. Paired t test (two tailed) and analysis of variance were used to evaluate differences in HbA1c at 3 and 6 months in the two groups.
RESULTS:
HbA1c at entry was 7.9 ± 1.0% (SD) in the Calsulin-treated group and 7.8 ± 1.6% (SD) in control patients (P not significant). Data showed a slight improvement in HbA1c levels at 3 months in the Calsulin-treated group (-0.61% vs. -0.14% difference, respectively; P not significant). At the 6-month follow-up, a significant reduction in HbA1c levels was observed in the Calsulin-treated group versus the control group (-0.85% vs. -0.07% difference, respectively; P < 0.05).
CONCLUSIONS:
Calsulin is an acceptable and practical tool that makes the process of calculating insulin doses easy to use, and, most importantly, it improves metabolic control as shown by a significant reduction of HbA1c levels.
Guidelines for optimal bolus calculator settings in adults.
Source
Advanced Metabolic Care + Research, Escondido, California 92026, USA. jwalsh@diabetesnet.com
Abstract
Bolus insulin calculators (BCs) became available in insulin pumps in 2002 and are being integrated into glucose meters and portable device applets for use with multiple daily injections. A retrospective analysis of continuous subcutaneous insulin infusion data from the Actual Pump Practices (APP) study is used in this article to generate formulas for more precise BC settings. A well-designed BC determines accurate bolus doses for carbohydrate intake and for correcting elevated glucose levels. It should also provide the logic necessary to track residual bolus insulin and reduce bolus recommendations to minimize insulin stacking. To provide appropriate bolus doses, a BC requires accurate settings for the carbohydrate factor or insulin:carbohydrate ratio, glucose correction factor, duration of insulin action, and correction target. We provide guidelines to select BC settings from the user's current total daily dose (TDD) of insulin and to determine more appropriate BC settings from an improved TDD based on the mean glucose level.
© 2010 Diabetes Technology Society.
Key elements for successful intensive insulin pump therapy in individuals with type 1 diabetes.
Source
Endocrinology Institute, Sheba Medical Center, Israel. cukierm@mcmaster.ca
Abstract
OBJECTIVE:
Clinical trials have demonstrated that in individuals with type 1 diabetes the use of CSII pump resulted in better glucose control. Advantages of pumps therapy include many features such as the bolus calculators (wizard). These features are optional and therefore it is important to determine whether their use is associated with better glucose control. Thus, the aim of this analysis was to assess which features and parameters of insulin pump use are associated with better glucose control.
METHODS:
Data regarding consecutive patients with type 1 diabetes treated with an insulin pump and attending a tertiary referral for intensive glucose control was included in this analysis. The relationship between glycemic indices and treatment parameters (number of insulin units, number of glucose readings, bolus calculator use etc.) was assessed.
RESULTS:
A statistically significant relationship was found between glycemic indices and wizard use. Thus, individuals that used the wizard function in 50% of their boluses had an A1C, mean blood glucose values that were 0.6% (p=0.008) and 25mg/dL (p=0.000) lower respectively.
CONCLUSION:
The use of the bolus calculator feature was associated with better glucose control. Larger prospective clinical trials are needed in order to further validate this finding.
Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.
A signal processing-based bioinformatics approach to assessing drug resistance: human immunodeficiency virus as a case study.
Source
Bio-Health Informatics Research Group within the Centre for Computational Intelligence, Department of Informatics, Faculty of Technology, De Montfort University, Leicester, LE1 9BH, The United Kingdom. nnwankwo@dmu.ac.uk
Abstract
Measuring drug resistance is one of the challenging and essential pharmaceutical activities. It is a laborious and costly laboratory-based experimentation. Various clinical and experimental analyses for measuring drug resistance have been carried out. Results have been obtained for different types of therapeutic agents as a consequence of changes in the amino acids compositions in the sequence (mutation) of the organisms involved. In the same manner, the positions of these amino acids alterations and the level of resistance (folds) have also been experimentally identified. For example, G36S and V38M mutation in the Human Immunodeficiency Virus (HIV) Transmembrane glycoprotein (gp41) has been found to cause 100-fold resistance. However, there does not seem to have bioinformatics method developed in which the amino acid information of the proteins involved in the studies were used to computationally assess the degree of drug resistance without involving laboratory-based experimental procedure. The post-genomic era has witnessed the relevance of Bioinformatics approaches in the analysis of huge biomedical data. One such approach is the analysis of protein residues using digital signal processing technique such as informational spectrum method (ISM). Therefore, we propose a new bioinformatics method that is capable of assessing drug resistance without the use of any laboratory-based experiments. This new method incorporates ISM, sequence information of the proteins and other relevant information. By using the ISM and EIIP amino acid scale, the technique was applied in three classes of anti-HIV/AIDS drugs as a case study. It is observed that the protein residues of the susceptible strains attained the maximal peak amplitude at the consensus frequency while the resistant strains maintained lower amplitudes. This result signifies lower contribution from the resistant strains due to the mutation. The findings are consistent with those of the experimental ones and therefore suggest that the approach taken can be used to help assess drug resistance without laboratory-based experimentation. It should also be noted that the method can be applied in other drug resistance studies where sequence information of proteins is available and help design a computer-aided drug resistance calculator.
Guidelines for insulin dosing in continuous subcutaneous insulin infusion using new formulas from a retrospective study of individuals with optimal glucose levels.
Source
Advanced Metabolic Care and Research, Escondido, California 92026, USA. jwalsh@diabetesnet.com
Abstract
BACKGROUND:
Successful insulin pump therapy depends on correct insulin doses based on an optimal total daily dose (TDD) and optimal pump settings for basal infusion, carbohydrate factor (CarbF), and glucose correction factor (CorrF) based on the TDD. There are limited data in the literature to guide providers and patients regarding methods to optimize these critical parameters for glucose control.
METHODS:
Anonymous data downloads from 1020 insulin pumps used throughout the United States and overseen by a variety of clinicians were analyzed retrospectively to find insulin doses that provided the best glucose control. A subset of 396 pumps was chosen for glucose data reliability, with over 85% of their glucose data directly entered from a meter. This subset was divided into tertiles based on glucose levels, and the low glucose tertile was analyzed to derive formulas for optimal insulin pump settings.
RESULTS:
An inconsistent clustering of pump settings was found for the CarbF and the CorrF. This was less pronounced when CarbFs and CorrFs were determined from the actual bolus doses delivered once adjustments were made to the initial dose calculations by users and, to a larger extent, internally by the bolus calculator itself. Common beliefs that hyperglycemia is related to less carb counting, fewer carb boluses, or delivery of less insulin per day were not substantiated in this data. New or verified insulin dosing formulas presented include basal U/day = TDD × 0.48; CarbF = [2.6 × Wt(lb)]/TDD; and CorrF = 1960/TDD.
CONCLUSIONS:
Insulin pump users cannot reap full benefit from their pump bolus calculator if the settings on which bolus doses are based are less than optimal. Our data show that CarbFs and CorrFs tend to be unevenly distributed, suggesting that these factors are not selected in a systematic manner through use of formulas. Poor glucose outcomes among insulin pump users appear to be related to pump setting errors and being relatively underinsulinized, even though those in poor control use more total insulin per day. We have developed a model with the hypothesis that improved glucose outcomes will result from the use of formulas to derive appropriate pump settings. Prospective validation of these concepts is needed.
© 2010 Diabetes Technology Society.
Genetic evaluation of the TNF-α -238G>A and -308G>A promoter polymorphisms in Croatian patients with type I diabetes.
Source
Ruđer Bošković Institute, Division of Molecular Medicine, Zagreb, Croatia.
Abstract
A case-control study was performed to establish a potential association of two TNF-α gene promoter SNPs (-238G>A and -308G>A) with occurrence of type 1 Diabetes mellitus (T1DM) in Croatian population (174 patients and 193 healthy controls). Genotypes (obtained by polymerase chain reaction-restriction fragment length polymorphism), and the clinical parameters of T1DM patients were statistically evaluated by SPSS 13 and Arlequin software, G*Power 3.0.10 program, and calculator for Hardy-Weinberg equilibrium. The frequency of the risk (A) allele, as well as the distribution of high-expression (GA, AA) genotypes were significantly higher (p < 0.0001) in T1DM patients only at locus -308. The distribution of the -238G/-308A haplotype was also significantly higher in patients compared with controls (27.6% vs 9.6%, p < 0.0001). Gender-dependent analysis revealed that female T1DM -308GA genotype carriers exhibit considerably stronger association with T1DM (odds ratio = 6.37, 95% confidence interval = 3.16-12.85) than male -308GA patients (odds ratio = 2.71, 95% confidence interval = 1.31-5.59). Clinical parameter analysis of T1DM patients revealed significantly decreased level of hemoglobin A(1)c (HbA(1)c) in -238A allele carriers compared with -238G allele carriers (6.55% vs 7.17%, p = 0.022), as well as the tendency of the risk allele carriers at -238 or -308 locus to develop T1DM earlier in life compared with non-risk allele carriers. In conclusion, susceptibility to T1DM in the Croatian population is strongly associated with the TNF-α -308G>A polymorphism, especially in women. In addition, significantly lower HbA(1c) levels found in T1DM -238A allele carriers might indicate better glycemic control in these patients.
Copyright © 2010 American Society for Histocompatibility and Immunogenetics. Published by Elsevier Inc. All rights reserved.
Predicting peptide retention times for proteomics.
Source
Department of Internal Medicine, University of Manitoba, Winnipeg, Canada.
Abstract
The vast majority of modern bottom-up proteomic protocols include chromatographic reversed-phase (RP) fractionation ofpeptides prior to mass-spectrometric analysis. Retention time information can be easily extracted from LC-MS data and it can be used to improve protein identification/characterization procedures. The key to the success of this procedure is the correct retention time prediction based on compositional and structural properties of the separated species. Our Sequence Specific Retention Calculator (SSRCalc) is a Web-based peptide retention prediction that covers the separation selectivity of the most popular RP-HPLC conditions applied in proteomics. Procedures for the application of SSRCalc to proteomic analyses are described in this unit.
Memory-efficient calculation of the isotopic mass states of a molecule.
Source
Department of Chemistry and Volen Center for Complex Systems, Brandeis University, Waltham, MA 02454, USA.
Abstract
Our previous work postulated a transition concept among different isotopic mass states (i.e., isotopic species) of a molecule, and developed a hierarchical algorithm for accurately calculating their masses and abundances. A theoretical mass spectrum can be generated by convoluting a peak shape function to these discrete mass states. This approach suffers from limited memory if a level in the hierarchical structure has too many mass states. Here we present a memory efficient divide-and-recursively-combine algorithm to do the calculation, which also improves the truncation method used in the previous hierarchical algorithm. Instead of treating all of the elements in a molecule as a whole, the new algorithm first 'strips' each element one by one. For the mass states of each element, a hierarchical structure is established and kept in the memory. This process reduces the memory usage by orders of magnitude (e.g., for bovine insulin, memory can be reduced from gigabytes to kilobytes). Next, a recursive algorithm is applied to combine mass states of elements to mass states of the whole molecule. The algorithm described above has been implemented as a computer program called Isotope Calculator, which was written in C++. It is freely available under the GNU Lesser General Public License from http://www.cs.brandeis.edu/~hong/software.html or http://people.brandeis.edu/~agar.
2010 John Wiley & Sons, Ltd.
Bolus guide: a novel insulin bolus dosing decision support tool based on selection of carbohydrate ranges.
Source
Medingo, Haifa, Israel. gali@medingo.com
Abstract
BACKGROUND:
Optimal continuous subcutaneous insulin infusion (CSII) therapy emphasizes the relationship between insulin dose and carbohydrate consumption. One widely used tool (bolus calculator) requires the user to enter discrete carbohydrate values; however, many patients might not estimate carbohydrates accurately. This study assessed carbohydrate estimation accuracy in type 1 diabetes CSII users and compared simulated blood glucose (BG) outcomes using the bolus calculator and the "bolus guide," an alternative system based on ranges of carbohydrate load.
METHODS:
Patients (n = 60) estimated the carbohydrate load of a representative sample of meals of known carbohydrate value. The estimated error distribution [coefficient of variation (CV)] was the basis for a computer simulation (n = 1.6 million observations) of insulin recommendations for the bolus guide and bolus calculator, translated into outcome blood glucose (OBG) ranges (< or =60, 61-200, >201 mg/dl). Patients (n = 30) completed questionnaires assessing satisfaction with the bolus guide.
RESULTS:
The CV of typical meals ranged from 27.9% to 44.5%. The percentage of simulated OBG for the calculatorand the bolus guide in the <60 mg/dl range were 20.8% and 17.2%, respectively, and 13.8% and 15.8%, respectively, in the >200 mg/dl range. The mean and median scores of all bolus guide satisfaction items and ease of learning and use were 4.17 and 4.2, respectively (of 5.0).
CONCLUSION:
The bolus guide recommendation based on carbohydrate range selection is substantially similar to thecalculator based on carbohydrate point estimation and appears to be highly accepted by type 1 diabetes insulin pump users.
2010 Diabetes Technology Society.
Bolus calculator with nutrition database software, a new concept of prandial insulin programming for pump users.
Source
Department of Pediatrics, Medical University of Warsaw, Warsaw, Poland. pankowskae@gmail.com
Abstract
Bolus calculators are effective tools in controlling blood glucose levels in patients treated with insulin. Diabetics is a new software devised for patients to facilitate and improve self-managing for prandial insulin dosing and for better controlling food intake. This device contains two integral parts: a nutrition database and a bolus calculator. The algorithm is based on a formula in which carbohydrate (CHO) and either fat and/or protein (FP) products are engulfed in insulin. The insulin dose setting is programmed individually for CHO in a normal bolus (N-W) and for FP in a square-wave bolus (S-W). The device calculates the dose of insulin for N-W or S-W, suggests the optimal kind of bolus, and indicates the timing in hours for an S-W bolus. In addition, this calculator, which contains a nutrition database and insulin dosing software, helps determine the correct type of necessary boluses for selected foods.
(c) 2010 Diabetes Technology Society.
Glycemic control in critically ill patients before and after institution of an intensive insulin infusion protocol: circadian rhythm and the quality durationcalculator.
Source
Division of Critical Care Medicine, Albert Einstein College of Medicine, Montefiore Medical Center, Bronx, New York 10467, USA. akeene@montefiore.org
Abstract
INTRODUCTION:
A circadian rhythm of blood glucose values has been recently reported in critically ill patients, but there are no reports of how this rhythm is altered by a continuous intensive insulin infusion therapy protocol (IIT). We wished to examine the effect of IIT on this rhythm as well as to describe the use of the quality duration calculator (QDC) for the evaluation of glycemic control before and after IIT.
METHODS:
This was a retrospective multihospital observational study that took place in the medical and surgical intensive care units (ICUs) of 2 tertiary care hospitals. Cohorts of consecutively admitted critically ill patients from 2-year periods before and after institution of an IIT protocol were examined. Laboratory, demographic, and outcome data were extracted from hospital databases.
RESULTS:
We studied 167,645 blood glucose measurements from 8,327 patients. We observed a circadian rhythm of blood glucose control in the pre-IIT cohort that was greatly attenuated in the post-IIT cohort. The difference between the morning and the average daily blood glucose in the pre-IIT cohort was 3.53 mg/dL (P < .001), and the difference between these values in the post-IIT cohort was 1.10 mg/dL (P = .031). In addition, the circadian nature of hyperglycemia incidence observed in the pre-IIT cohort was not seen in the post-IIT cohort. The amount of time spent in goal glycemic range increased from 23.69% (95% CI 23.01-24.38) in the pre-IIT cohort to 29.67% (95% CI 29.04-30.31) in the post-IIT cohort as estimated by the QDC. The amount of time spent in the hyperglycemic decreased from 20.17% (95% CI 19.33-20.99) in the pre-IIT cohort to 14.80% (95% CI 14.15-15.39) in the post-IIT cohort.
CONCLUSIONS:
The circadian rhythm of blood glucose control confirmed in our pre-IIT cohort was lost after institution of IIT. The morning blood glucose value appears to be a reasonable surrogate of overall glycemic control in a critically ill population on IIT, although this may vary based on the degree of control achieved. The QDC method is useful for analyzing glycemic control in patients on IIT.
The IRS2 Gly1057Asp variant is associated with human longevity.
Source
Department of Geriatric Medicine and Metabolic Diseases, Second University of Naples, Piazza Miraglia 2, 80138, Naples, Italy.
Abstract
BACKGROUND:
Reduced insulin and insulin-like growth factor-1 (IGF-1) signaling extends the life span of invertebrate and mammals. Recently, reduced insulin receptor substrate-2 (IRS2) signaling was found associated with increased longevity in mice. The aim of our study was to evaluate whether a common polymorphism (Gly1057Asp) in human IRS2 gene is associated with human longevity.
METHODS:
Six hundred seventy-seven participants (289 males and 388 females) between 16 and 104 years of age, categorized as long lived (LL; >85 years old) or controls (C; <85 years old), were genotyped for Gly1057Asp-IRS2 locus variability (rs1805097). All participants, contacted at home or in their institution or selected from Italian geriatric and internal medicine or geriatric rehabilitation structures, underwent to a clinical, biochemical, and functional characterization, with particular attention to the insulin and IGF-1 signaling. Insulin resistance (Homeostasis Model Assessment [HOMA]-IR), insulin sensitivity (HOMA IS), and ss-cell function (HOMA-B cell) were calculated by the HOMA2 calculator v2.2 (www.dtu.ox.ac.uk/homa).
RESULTS:
In the whole population, homozygous IRS2(Asp/Asp) participants were more represented among LL versus C participants (16.7% vs 12.0%; p = .04). The association between IRS2 gene polymorphism with longevity (being LL) was independent of anthropometric and metabolic covariates (odds ratio: 2.07, 95% confidence interval [CI] = 1.38-3.12; p = .001). Categorizing participants into percentiles by age, IRS2(Asp/Asp) participants were more likely to reach extreme old age (>or=90 percentile, 96-104 years; odds ratio: 2.03, 95% CI = 1.39-2.99; p = .0003).
CONCLUSIONS:
These results support the hypothesis that the IRS2 branch of the insulin and IGF signaling is associated with human longevity. Further studies will be necessary for replicating our finding in an independent larger population group with sufficient power before the association between IRS2 gene polymorphism and longevity can be regarded as proven. Furthermore, studies of genetic and/or environmental background interactions may be useful after basic replication is complete.
- PMID:
- 19887537
- [PubMed - indexed for MEDLINE]
No comments:
Post a Comment