Immune cell dynamics deconvoluted by single-cell RNA sequencing in normothermic machine perfusion of the liver.

Normothermic machine perfusion (NMP) has emerged as an innovative organ preservation technique. Developing an understanding for the donor organ immune cell composition and its dynamic changes during NMP is essential. We aimed for a comprehensive characterization of immune cell (sub)populations, cell trafficking and cytokine release during liver NMP. Single-cell transcriptome profiling of human donor livers prior to, during NMP and after transplantation shows an abundance of CXC chemokine receptor 1+/2+ (CXCR1+/CXCR2+) neutrophils, which significantly decreased during NMP. This is paralleled by a large efflux of passenger leukocytes with neutrophil predominance in the perfusate. During NMP, neutrophils shift from a pro-inflammatory state towards an aged/chronically activated/exhausted phenotype, while anti-inflammatory/tolerogenic monocytes/macrophages are increased. We herein describe the dynamics of the immune cell repertoire, phenotypic immune cell shifts and a dominance of neutrophils during liver NMP, which potentially contribute to the inflammatory response. Our findings may serve as resource to initiate future immune-interventional studies.

Computational cancer neoantigen prediction: current status and recent advances.

Over the last few decades, immunotherapy has shown significant therapeutic efficacy in a broad range of cancer types. Antitumor immune responses are contingent on the recognition of tumor-specific antigens, which are termed neoantigens. Tumor neoantigens are ideal targets for immunotherapy since they can be recognized as non-self antigens by the host immune system and thus are able to elicit an antitumor T-cell response. There are an increasing number of studies that highlight the importance of tumor neoantigens in immunoediting and in the sensitivity to immune checkpoint blockade. Therefore, one of the most fundamental tasks in the field of immuno-oncology research is the identification of patient-specific neoantigens. To this end, a plethora of computational approaches have been developed in order to predict tumor-specific aberrant peptides and quantify their likelihood of binding to patients' human leukocyte antigen molecules in order to be recognized by T cells. In this review, we systematically summarize and present the most recent advances in computational neoantigen prediction, and discuss the challenges and novel methods that are being developed to resolve them.

The colorectal cancer immune paradox revisited.

Tumor infiltrating lymphocytes (TILs) represent a strong independent predictor of relapse and overall survival in colorectal cancer (CRC). However, it appears that a majority of CRCs, i.e., microsatellite stable (MSS) tumors, are refractory to immune checkpoint blockers. The results of recent comprehensive analyses of genomic data provide possible answers.

3DSpectra: A 3-dimensional quantification algorithm for LC-MS labeled profile data.

Mass spectrometry-based proteomics can generate highly informative datasets, as profile three-dimensional (3D) LC-MS data: LC-MS separates peptides in two dimensions (time, m/z) minimizing their overlap, and profile acquisition enhances quantification. To exploit both data features, we developed 3DSpectra, a 3D approach embedding a statistical method for peptide border recognition. 3DSpectra efficiently accesses profile data by means of mzRTree, and makes use of a priori metadata, provided by search engines, to quantify the identified peptides. An isotopic distribution model, shaped by a bivariate Gaussian Mixture Model (GMM), which includes a noise component, is fitted to the peptide peaks using the expectation-maximization (EM) approach. The EM starting parameters, i.e., the centers and shapes of the Gaussians, are retrieved from the metadata. The borders of the peaks are delimited by the GMM iso-density curves, and noisy or outlying data are discarded from subsequent analysis. The 3DSpectra program was compared to ASAPRatio for a controlled mixture of Isotope-Coded Protein Labels (ICPL) labeled proteins, which were mixed at predefined ratios and acquired in enhanced profile mode, in triplicate. The 3DSpectra software showed significantly higher linearity, quantification accuracy, and precision than did ASAPRatio in this real use case simulation where the true ratios are known, and it also achieved wider peptide coverage and dynamic range. BIOLOGICAL SIGNIFICANCE: Quantitative proteomics is pivotal for many systems biology related fields, such as biomarker discovery. The quantification quality provided by the adopted software is crucial for the success of protein differential expression studies. To determine the reliability of a quantitative computational method, we suggest evaluating performance parameters like accuracy and precision of the quantifications, robustness to outliers and proteome coverage. A quantitative comparison of these parameters is highly desirable since it enables to benchmark software performance. We applied this strategy to 3DSpectra, a 3-dimensional approach to spectra analysis for MS1 peptide quantification. It distinguishes peptide peaks from spurious peaks interfering in the survey scan. 3DSpectra was compared to ASAPRatio in terms of quantification quality performance parameters and showed an overall improvement.

Molecular aspects of adipoepithelial transdifferentiation in mouse mammary gland.

The circular, reversible conversion of the mammary gland during pregnancy and involution is a paradigm of physiological tissue plasticity. The two most prominent cell types in mammary gland, adipocytes and epithelial cells, interact in an orchestrated way to coordinate this process. Previously, we showed that this conversion is at least partly achieved by reciprocal transdifferentiation between mammary adipocytes and lobulo-alveolar epithelial cells. Here, we aim to shed more light on the regulators of mammary transdifferentiation. Using immunohistochemistry with cell type-specific lipid droplet-coating markers (Perilipin1 and 2), we show that cells with an intermediate adipoepithelial phenotype exist during and after pregnancy. Nuclei of cells with similar transitional structural characteristics are highly positive for Elf5, a master regulator of alveologenesis. In cultured adipocytes, we could show that transient and stable ectopic expression of Elf5 induces expression of the milk component whey acidic protein, although the general adipocyte phenotype is not affected suggesting that additional pioneering factors are necessary. Furthermore, the lack of transdifferentiation of adipocytes during pregnancy after clearing of the epithelial compartment indicates that transdifferentiation signals must emanate from the epithelial part. To explore candidate genes potentially involved in the transdifferentiation process, we devised a high-throughput gene expression study to compare cleared mammary fat pads with developing, contralateral controls at several time points during pregnancy. Incorporation of bioinformatic predictions of secretory proteins provides new insights into possible paracrine signaling pathways and downstream transdifferentiation factors. We discuss a potential role for osteopontin (secreted phosphoprotein 1 [Spp1]) signaling through integrins to induce adipoepithelial transdifferentiation.

Glucocorticoid-regulated microRNAs and mirtrons in acute lymphoblastic leukemia.

Glucocorticoids (GCs) induce apoptosis in lymphoid lineage cells and are therefore used in the therapy of acute lymphoblastic leukemia (ALL) and related malignancies. MicroRNAs (miRNAs) and the related mirtrons are ~22 nucleotide RNAs derived from polymerase-II transcripts and implicated in the control of essential biological functions, including apoptosis. Whether GCs regulate miRNA-encoding transcription units is unknown. We investigated miRNA/mirtron expression and GC regulation in 8 leukemia/lymphoma in vitro models and 13 ALL children undergoing systemic GC monotherapy using a combination of expression profiling techniques, real time reverse transcription (RT)-PCR and northern blotting to detect mature miRNAs and/or their precursors. We found that mature miRNA regulations can be inferred from expression data of their host genes. Although a simple miRNA-initiated canonical pathway to GC-induced apoptosis or cell cycle arrest did not emerge, we identified several miRNAs/mirtrons that were regulated by GC in patients and cell lines, including the myeloid-specific miR-223 and the apoptosis and cell cycle arrest-inducing miR15 ~ 16 clusters. In an in vitro model, overexpression of miR15b ~ 16 mimics increased and silencing by miR15b ~ 16 inhibitors decreased GC sensitivity. Thus, the observed complex changes in miRNA/mirtron expression during GC treatment might contribute to the anti-leukemic GC effects in a cell context-dependent manner.

A fully Bayesian model to cluster gene-expression profiles.

MOTIVATION: With cDNA or oligonucleotide chips, gene-expression levels of essentially all genes in a genome can be simultaneously monitored over a time-course or under different experimental conditions. After proper normalization of the data, genes are often classified into co-expressed classes (clusters) to identify subgroups of genes that share common regulatory elements, a common function or a common cellular origin. With most methods, e.g. k-means, the number of clusters needs to be specified in advance; results depend strongly on this choice. Even with likelihood-based methods, estimation of this number is difficult. Furthermore, missing values often cause problems and lead to the loss of data. RESULTS: We propose a fully probabilistic Bayesian model to cluster gene-expression profiles. The number of classes does not need to be specified in advance; instead it is adjusted dynamically using a Reversible Jump Markov Chain Monte Carlo sampler. Imputation of missing values is integrated into the model. With simulations, we determined the speed of convergence of the sampler as well as the accuracy of the inferred variables. Results were compared with the widely used k-means algorithm. With our method, biologically related co-expressed genes could be identified in a yeast transcriptome dataset, even when some values were missing. AVAILABILITY: The code is available at http://genome.tugraz.at/BayesianClustering/

Grape-seed derived procyanidins interfere with adipogenesis of 3T3-L1 cells at the onset of differentiation.

OBJECTIVE: Our group's previous results on the effects of a grape seed procyanidin extract (GSPE) on adipose metabolism showed that peroxisome proliferator-activated receptor-gamma (PPARgamma) plays a central role in the lipolytic effects of GSPE on adipocytes. Since PPARgamma2 is a main regulator of the differentiation process of adipocytes, we investigated whether GSPE affects the adipogenesis of 3T3-L1 cells. DESIGN: We performed a time point screening by treating 3T3-L1 cells with GSPE during the differentiation process for 24 h. MEASUREMENTS: Differentiation markers and differential gene expression due to GSPE treatment (using the microarray technique). RESULTS: Twenty four hour-GSPE treatment at the onset of differentiation reduces adipose-specific markers and maintains the expression of preadipocyte marker preadipocyte factor-1 (Pref-1) significantly elevated. These effects were not found in other time points. Microarray analysis of gene expression after GSPE treatment at the early stage of differentiation showed a modified gene expression profile in which cell cycle and growth-related genes were downregulated by GSPE. CONCLUSION: These results suggest that GSPE affects adipogenesis, mainly at the induction of differentiation, and that procyanidins may have a new role in which they impede the formation of adipose cells.

Ovarian cancer identification based on dimensionality reduction for high-throughput mass spectrometry data.

MOTIVATION: High-throughput and high-resolution mass spectrometry instruments are increasingly used for disease classification and therapeutic guidance. However, the analysis of immense amount of data poses considerable challenges. We have therefore developed a novel method for dimensionality reduction and tested on a published ovarian high-resolution SELDI-TOF dataset. RESULTS: We have developed a four-step strategy for data preprocessing based on: (1) binning, (2) Kolmogorov-Smirnov test, (3) restriction of coefficient of variation and (4) wavelet analysis. Subsequently, support vector machines were used for classification. The developed method achieves an average sensitivity of 97.38% (sd = 0.0125) and an average specificity of 93.30% (sd = 0.0174) in 1000 independent k-fold cross-validations, where k = 2, ..., 10. AVAILABILITY: The software is available for academic and non-commercial institutions.

ArrayNorm: comprehensive normalization and analysis of microarray data.

SUMMARY: ArrayNorm is a user-friendly, versatile and platform-independent Java application for the visualization, normalization and analysis of two-color microarray data. A variety of normalization options were implemented to remove the systematic and random errors in the data, taking into account the experimental design and the particularities of every slide. In addition, ArrayNorm provides a module for statistical identification of genes with significant changes in expression. AVAILABILITY: The package is freely available for academic and non-profit institutions from http://genome.tugraz.at

Differential gene expression profile of glucocorticoids, testosterone, and dehydroepiandrosterone in human cells.

Glucocorticoids are the major immunomodulating hormones in the human body. Recently, increasing interest in androgens as immunomodulators has emerged. In particular, Dehydroepiandrosterone (DHEA) has been suggested as beneficial in the treatment of some autoimmune disorders. However, the action and role of testicular and adrenal androgens on human immune cells remains unclear. This is the first study to provide large-scale gene expression data on the action of different steroids (DHEA, glucocorticoids, and testosterone) on human peripheral blood mononuclear cells using the recently developed genomic-scale technology of microarrays. Novel computational tools and techniques such as Principal Component Analysis (PCA) were used for analysis, clustering and visualization. We have demonstrated that each steroid has its distinct gene expression profile, although DHEA and testosterone co-regulated most genes in a similar direction while glucocorticoids frequently regulated the same genes in an opposite direction. Our data suggest an important and a complex regulatory role for androgens on human immune cells that should be considered in androgen replacement or treatment strategies.

Impaired glucose transport as a cause of decreased insulin-stimulated muscle glycogen synthesis in type 2 diabetes.

BACKGROUND: Insulin resistance, a major factor in the pathogenesis of type 2 diabetes mellitus, is due mostly to decreased stimulation of glycogen synthesis in muscle by insulin. The primary rate-controlling step responsible for the decrease in muscle glycogen synthesis is not known, although hexokinase activity and glucose transport have been implicated. METHODS: We used a novel nuclear magnetic resonance approach with carbon-13 and phosphorus-31 to measure intramuscular glucose, glucose-6-phosphate, and glycogen concentrations under hyperglycemic conditions (plasma glucose concentration, approximately 180 mg per deciliter [10 mmol per liter]) and hyperinsulinemic conditions in six patients with type 2 diabetes and seven normal subjects. In vivo microdialysis of muscle tissue was used to determine the gradient between plasma and interstitial-fluid glucose concentrations, and open-flow microperfusion was used to determine the concentrations of insulin in interstitial fluid. RESULTS: The time course and concentration of insulin in interstitial fluid were similar in the patients with diabetes and the normal subjects. The rates of whole-body glucose metabolism and muscle glycogen synthesis and the glucose-6-phosphate concentrations in muscle were approximately 80 percent lower in the patients with diabetes than in the normal subjects under conditions of matched plasma insulin concentrations. The mean (+/-SD) intracellular glucose concentration was 2.0+/-8.2 mg per deciliter (0.11+/-0.46 mmol per liter) in the normal subjects. In the patients with diabetes, the intracellular glucose concentration was 4.3+/-4.9 mg per deciliter (0.24+/-0.27 mmol per liter), a value that was 1/25 of what it would be if hexokinase were the rate-controlling enzyme in glucose metabolism. CONCLUSIONS: Impaired insulin-stimulated glucose transport is responsible for the reduced rate of insulin-stimulated muscle glycogen synthesis in patients with type 2 diabetes mellitus.

The differential effect of food intake and beta-adrenergic stimulation on adipose-derived hormones and cytokines in man.

We determined whether the physiologic changes that accompany food intake or sympathetic activation by beta-adrenergic stimulation result in alterations in the secretion of leptin, tumor necrosis factor-alpha (TNF alpha), or interleukin-6 (IL-6) by serially sampling sc abdominal adipose interstitial fluid by open-flow microperfusion before and after a standardized meal and in response to isoproterenol (1 micromol/L) delivered locally. Post cibum IL-6 rose up to 5-fold, whereas leptin and TNF alpha secretion did not change; TNF alpha, but not IL-6, correlated positively with indices of lipolysis. Isoproterenol-induced lipolysis was accompanied by a transient 40% reduction in leptin and a parallel 85% elevation of TNF alpha concentration, whereas IL-6 levels did not change; again, TNF alpha correlated positively with lipolysis. These data show that secretion of some, but not all, metabolically relevant polypeptides by adipose tissue is modulated within a short time frame by food or stress stimuli, suggesting a role of these peptides in local autocrine/paracrine or distant endocrine effects on fat metabolism. TNF alpha's close correlation with lipolysis suggests that this cytokine participates in a local positive autocrine feedback loop, potentiating lipolysis and inhibiting insulin's antilipolytic actions. The regulations of adipose leptin, TNF alpha, and IL-6 secretion seem distinct from each other and different in the fed vs. fasting state.

Plasma and interstitial glucose dynamics after intravenous glucose injection: evaluation of the single-compartment glucose distribution assumption in the minimal models.

Recent experimental evidence suggests that estimates of glucose effectiveness (S(G)) from the minimal model of unlabeled glucose disappearance (Cold-MM) are in error. The single-compartment glucose distribution assumption embedded in the model has been indicated as a possible source of error. In this study, to directly examine the single-compartment assumption, we measured plasma and interstitial glucose concentrations after intravenous glucose injection. Additionally, we compared the accuracy of the estimates of glucose effectiveness from the Cold-MM and the single-compartment tracer minimal model (Hot-MM). Paired labeled intravenous glucose tolerance tests (IVGTTs) were performed in each of six C-peptide-negative type 1 diabetic subjects. Two different insulin infusion protocols were used: an infusion at constant basal rates and an infusion at variable rates to mimic a normal insulin response. During the labeled IVGTT with basal insulin infusion, the microperfusion technique was employed to sample adipose tissue interstitial fluid. Marked differences between the plasma and interstitial dynamics of (cold) glucose were observed during the first 22 min after glucose injection. These results suggest that the requirements for a single-compartment representation of glucose kinetics are not satisfied during at least the first 22 min of an IVGTT. Data from the labeled IVGTT with normal insulin response were used to identify the minimal-model parameters. The measure of S(G) derived using the Cold-MM was 3.44-fold higher than the direct measure obtained from the labeled IVGTT with basal insulin infusion (0.0179+/-0.0027 vs. 0.0052+/-0.0010 min(-1), P<0.01). The measure of glucose effectiveness (S(G)*) derived by the Hot-MM was 1.36-fold higher than the direct measure available from the labeled IVGTT with basal insulin infusion (0.0079+/-0.0013 vs. 0.0058+/-0.0004 min(-1), P>0.26). These results suggest that the Hot-MM is more appropriate for the evaluation of glucose effectiveness than the Cold-MM.

Direct access to interstitial fluid in adipose tissue in humans by use of open-flow microperfusion.

To gain direct access to the interstitial fluid (ISF), a new technique called open-flow microperfusion has been evaluated. This method is based on a double-lumen catheter with macroscopic (0.3-0.5 mm diameter) perforations that is inserted into the subcutaneous adipose tissue and constantly perfused. Thus partial equilibration between the ISF and the perfusion fluid occurs. The glucose concentration of the ISF was determined by established (zero flow rate, no net flux, and recirculation procedures) and new (ionic reference and suction technique) calibration methods by use of open-flow microperfusion. The data show that 1) the glucose concentration in the ISF is significantly lower than the corresponding arterialized venous plasma values during basal steady-state conditions (adipose tissue 3.2 +/- 0.10 mM, plasma 5.27 +/- 0.12 mM) as well as during hyperglycemic clamp experiments (adipose tissue 7.3 +/- 0.13 mM, plasma 9.91 +/- 0.16 mM), and 2) it is possible to determine the recovery continuously by using the ion concentration of the ISF as an internal standard (ionic reference).

Lactate metabolism of subcutaneous adipose tissue studied by open flow microperfusion.

Open flow microperfusion and a novel calibration technique (ionic reference technique) were evaluated for the frequent measurement of the absolute lactate concentration in sc adipose tissue. Furthermore, the influence of the plasma insulin concentration on the lactate concentration of sc adipose tissue was investigated during hyperglycemia. Sixteen lean healthy young men participated in the studies. In the postabsorbtive state the mean sc lactate concentrations were 1.29 and 1.36 mmol/L for the ionic reference technique and the no net flux protocol, respectively (not significant, P > 0.05). The simultaneously measured arterialized plasma lactate concentration was significantly lower at 0.77 mmol/L (P < 0.05). Both the sc lactate concentration (1.8+/-0.33 mmol/L) and the plasma lactate concentration (0.96+/-0.03 mmol/L) were significantly elevated during a hyperinsulinemic euglycemic clamp experiment. During a hyperglycemic clamp experiment the sc lactate concentration reached a significantly elevated plateau (2.15+/-0.27 mmol/L) that was not influenced by the increasing plasma insulin concentration. It is concluded that 1) open flow microperfusion combined with the ionic reference technique enables frequent measurement of the sc lactate concentration; 2) sc adipose tissue is a significant source of lactate release in the postabsorbtive state as well as during hyperinsulinemic clamp conditions; and 3) insulin concentrations greater than 180 pmol/L have no further influence on adipocyte stimulation of sc adipose tissue with respect to lactate release.

Continuous measurement of subcutaneous lactate concentration during exercise by combining open-flow microperfusion and thin-film lactate sensors.

The present study was carried out to investigate in vivo in healthy humans the method of open-flow microperfusion for monitoring of the subcutaneous (s.c.) lactate concentration during rest and cycle ergometer exercise. Using open-flow microperfusion, a perforated double lumen catheter with an inflow and an outflow connection is inserted into the s.c. adipose tissue and perfused with a sterile, isotonic, ionfree fluid. Due to the low flow rate, the fluid partially equilibrates with the surrounding tissue. The equilibrated perfusate passes a sensor flow chamber where the substance of interest and the rate of recovery (i.e. the ratio of sampled concentration to interstitial concentration) are continuously monitored. Within this study, the method was evaluated in four healthy volunteers during cycle ergometer exercise. The relative increase of the lactate concentration was approximately a third in the s.c. tissue compared to the capillary blood and the peak time was delayed on average by 10 min. The correlation coefficient between blood and s.c. tissue lactate concentration ranged from r = 0.41 to r = 0.90 (n = 29) in the individual experiments. The combination of open-flow microperfusion and lactate and conductivity sensors enables on-line monitoring of the s.c. lactate concentration without in vivo calibration during steady-state and cycle ergometer exercise.

Neural predictive controller for insulin delivery using the subcutaneous route.

A neural predictive controller for closed-loop control of glucose using subcutaneous (s.c.) tissue glucose measurement and s.c. infusion of monomeric insulin analogs was developed and evaluated in a simulation study. The proposed control strategy is based on off-line system identification using neural networks (NN's) and nonlinear model predictive controller design. The system identification framework combines the concept of nonlinear autoregressive model with exogenous inputs (NARX) system representation, regularization approach for constructing radial basis function NN's, and validation methods for nonlinear systems. Numerical studies on system identification and closed-loop control of glucose were carried out using a comprehensive model of glucose regulation and a pharmacokinetic model for the absorption of monomeric insulin analogs from the s.c. depot. The system identification procedure enabled construction of a parsimonious network from the simulated data, and consequently, design of a controller using multiple-step-ahead predictions of the previously identified model. According to the simulation results, stable control is achievable in the presence of large noise levels, for unknown or variable time delays as well as for slow time variations of the controlled process. However, the control limitations due to the s.c. insulin administration makes additional action from the patient at meal time necessary.

Simulation studies on neural predictive control of glucose using the subcutaneous route.

A novel strategy for closed-loop control of glucose using subcutaneous (s.c.) tissue glucose measurement and s.c. infusion of monomeric insulin analogues was developed and evaluated in a simulation study. The proposed control strategy is an amalgamation of a neural network and nonlinear model predictive control (NPC) technique. A radial basis function neural network was used for off-line system identification of Nonlinear Auto Regressive model with eXogenous inputs (NARX) model of the glucoregulatory system. The explicit NARX model obtained from the off-line identification procedure was then used to predict the effects of future control actions. Numerical studies were carried out using a comprehensive model of glucose regulation. The system identification procedure enabled construction of a parsimonious network from the stimulated data, and consequently, design of a controller using multiple-step-ahead predictions of the previously identified model. According to the simulation results, stable control is achievable in the presence of large noise levels and for unknown or variable physiological or technical time delays. In conclusion, the simulation results suggest that closed-loop control of glucose will be achievable using s.c. glucose measurement and s.c. insulin administration. However, the control limitations due to the s.c. insulin administration makes additional action of the patient at meal time necessary.

Validation of home blood glucose meters with respect to clinical and analytical approaches.

OBJECTIVE: To evaluate the clinical and analytical accuracy of home blood glucose meters. RESEARCH DESIGN AND METHODS: Six blood glucose meters--Reflolux S (Boehringer Mannheim, Mannheim, Germany), One Touch II (LifeScan, Milpitas, CA), Glucocard Memory (Menarini, Florence, Italy), Precision QID (Medisense, Cambridge, U.K.), HaemoCue (HaemoCue, Angelholm, Sweden), and Accutrend alpha (Boehringer Mannheim, Mannheim, Germany)--were compared with a reference method (Beckman Glucose Analyzer II) under controlled conditions (glucose clamp technique). Validation of the blood glucose meters was accomplished by clinically oriented approaches (error grid analysis), statistical approaches (variance components analysis), and by the criteria of the American Diabetes Association (ADA), which recommend a target variability of < 5%. RESULTS: A total of 1,794 blood glucose monitor readings and 299 reference values ranging from 2.2 to 18.2 mmol/l were analyzed (705 readings < 3.89 mmol/l, 839 readings between 3.89 and 9.99 mmol/l, and 250 readings > 9.99 mmol/l). According to error grid analysis, only Reflolux S and Glucocard M had 100% of estimations within the clinically acceptable zones A and B. Assessment of analytical accuracy revealed substantial differences between the glucose meters after separation of the data into defined glycemic ranges. None of the devices met the ADA criteria. CONCLUSIONS: To evaluate accuracy of blood glucose meters, error grid analysis, as well as statistical models, are helpful means and should be performed together. Analytical performance of currently available home blood glucose meters differs substantially within defined glycemic ranges.