Three Arabidopsis UMP kinases have different roles in pyrimidine nucleotide biosynthesis and (deoxy)CMP salvage.

Pyrimidine nucleotide monophosphate biosynthesis ends in the cytosol with uridine monophosphate (UMP). UMP phosphorylation to uridine diphosphate (UDP) by UMP KINASEs (UMKs) is required for the generation of all pyrimidine (deoxy)nucleoside triphosphates as building blocks for nucleic acids and central metabolites like UDP-glucose. The Arabidopsis (Arabidopsis thaliana) genome encodes five UMKs and three belong to the AMP KINASE (AMK)-like UMKs, which were characterized to elucidate their contribution to pyrimidine metabolism. Mitochondrial UMK2 and cytosolic UMK3 are evolutionarily conserved, whereas cytosolic UMK1 is specific to the Brassicaceae. In vitro, all UMKs can phosphorylate UMP, cytidine monophosphate (CMP) and deoxycytidine monophosphate (dCMP), but with different efficiencies. Clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated nuclease 9 (Cas9)-induced null mutants were generated for UMK1 and UMK2, but not for UMK3, since frameshift alleles were lethal for germline cells. However, a mutant with diminished UMK3 activity showing reduced growth was obtained. Metabolome analyses of germinating seeds and adult plants of single- and higher-order mutants revealed that UMK3 plays an indispensable role in the biosynthesis of all pyrimidine (deoxy)nucleotides and UDP-sugars, while UMK2 is important for dCMP recycling that contributes to mitochondrial DNA stability. UMK1 is primarily involved in CMP recycling. We discuss the specific roles of these UMKs referring also to the regulation of pyrimidine nucleoside triphosphate synthesis.

Pyrimidine catabolism is required to prevent the accumulation of 5-methyluridine in RNA.

5-Methylated cytosine is a frequent modification in eukaryotic RNA and DNA influencing mRNA stability and gene expression. Here we show that free 5-methylcytidine (5mC) and 5-methyl-2'-deoxycytidine are generated from nucleic acid turnover in Arabidopsis thaliana, and elucidate how these cytidines are degraded, which is unclear in eukaryotes. First CYTIDINE DEAMINASE produces 5-methyluridine (5mU) and thymidine which are subsequently hydrolyzed by NUCLEOSIDE HYDROLASE 1 (NSH1) to thymine and ribose or deoxyribose. Interestingly, far more thymine is generated from RNA than from DNA turnover, and most 5mU is directly released from RNA without a 5mC intermediate, since 5-methylated uridine (m5U) is an abundant RNA modification (m5U/U ∼1%) in Arabidopsis. We show that m5U is introduced mainly by tRNA-SPECIFIC METHYLTRANSFERASE 2A and 2B. Genetic disruption of 5mU degradation in the NSH1 mutant causes m5U to occur in mRNA and results in reduced seedling growth, which is aggravated by external 5mU supplementation, also leading to more m5U in all RNA species. Given the similarities between pyrimidine catabolism in plants, mammals and other eukaryotes, we hypothesize that the removal of 5mU is an important function of pyrimidine degradation in many organisms, which in plants serves to protect RNA from stochastic m5U modification.

Simultaneous Inference Using Multiple Marginal Models.

This tutorial describes single-step low-dimensional simultaneous inference with a focus on the availability of adjusted p values and compatible confidence intervals for more than just the usual mean value comparisons. The basic idea is, first, to use the influence of correlation on the quantile of the multivariate t-distribution: the higher the less conservative. In addition, second, the estimability of the correlation matrix using the multiple marginal models approach (mmm) using multiple models in the class of linear up to generalized linear mixed models. The underlying maxT-test using mmm is discussed by means of several real data scenarios using selected R packages. Surprisingly, different features are highlighted, among them: (i) analyzing different-scaled, correlated, multiple endpoints, (ii) analyzing multiple correlated binary endpoints, (iii) modeling dose as qualitative factor and/or quantitative covariate, (iv) joint consideration of several tuning parameters within the poly-k trend test, (v) joint testing of dose and time, (vi) considering several effect sizes, (vii) joint testing of subgroups and overall population in multiarm randomized clinical trials with correlated primary endpoints, (viii) multiple linear mixed effect models, (ix) generalized estimating equations, and (x) nonlinear regression models.

Prediction Intervals for Overdispersed Poisson Data and Their Application in Medical and Pre-Clinical Quality Control.

In pre-clinical and medical quality control, it is of interest to assess the stability of the process under monitoring or to validate a current observation using historical control data. Classically, this is done by the application of historical control limits (HCL) graphically displayed in control charts. In many applications, HCL are applied to count data, for example, the number of revertant colonies (Ames assay) or the number of relapses per multiple sclerosis patient. Count data may be overdispersed, can be heavily right-skewed and clusters may differ in cluster size or other baseline quantities (e.g., number of petri dishes per control group or different length of monitoring times per patient). Based on the quasi-Poisson assumption or the negative-binomial distribution, we propose prediction intervals for overdispersed count data to be used as HCL. Variable baseline quantities are accounted for by offsets. Furthermore, we provide a bootstrap calibration algorithm that accounts for the skewed distribution and achieves equal tail probabilities. Comprehensive Monte-Carlo simulations assessing the coverage probabilities of eight different methods for HCL calculation reveal, that the bootstrap calibrated prediction intervals control the type-1-error best. Heuristics traditionally used in control charts (e.g., the limits in Shewhart c- or u-charts or the mean ± 2 SD) fail to control a pre-specified coverage probability. The application of HCL is demonstrated based on data from the Ames assay and for numbers of relapses of multiple sclerosis patients. The proposed prediction intervals and the algorithm for bootstrap calibration are publicly available via the R package predint.

Simultaneous Inference of Multiple Binary Endpoints in Biomedical Research: Small Sample Properties of Multiple Marginal Models and a Resampling Approach.

In biomedical research, the simultaneous inference of multiple binary endpoints may be of interest. In such cases, an appropriate multiplicity adjustment is required that controls the family-wise error rate, which represents the probability of making incorrect test decisions. In this paper, we investigate two approaches that perform single-step p $p$ -value adjustments that also take into account the possible correlation between endpoints. A rather novel and flexible approach known as multiple marginal models is considered, which is based on stacking of the parameter estimates of the marginal models and deriving their joint asymptotic distribution. We also investigate a nonparametric vector-based resampling approach, and we compare both approaches with the Bonferroni method by examining the family-wise error rate and power for different parameter settings, including low proportions and small sample sizes. The results show that the resampling-based approach consistently outperforms the other methods in terms of power, while still controlling the family-wise error rate. The multiple marginal models approach, on the other hand, shows a more conservative behavior. However, it offers more versatility in application, allowing for more complex models or straightforward computation of simultaneous confidence intervals. The practical application of the methods is demonstrated using a toxicological dataset from the National Toxicology Program.

The Tukey trend test: Multiplicity adjustment using multiple marginal models.

In dose-response analysis, it is a challenge to choose appropriate linear or curvilinear shapes when considering multiple, differently scaled endpoints. It has been proposed to fit several marginal regression models that try sets of different transformations of the dose levels as explanatory variables for each endpoint. However, the multiple testing problem underlying this approach, involving correlated parameter estimates for the dose effect between and within endpoints, could only be adjusted heuristically. An asymptotic correction for multiple testing can be derived from the score functions of the marginal regression models. Based on a multivariate t-distribution, the correction provides a one-step adjustment of p-values that accounts for the correlation between estimates from different marginal models. The advantages of the proposed methodology are demonstrated through three example datasets, involving generalized linear models with differently scaled endpoints, differing covariates, and a mixed effect model and through simulation results. The methodology is implemented in an R package.

Simultaneous confidence intervals for contrasts of quantiles.

Skewed distributions and inferences concerning quantiles are common in the health and social science researches. And most standard simultaneous inference procedures require the normality assumption. For example, few methods exist for comparing the medians of independent samples or quantiles of several distributions in general. To our knowledge, there is no easy-to-use method for constructing simultaneous confidence intervals for multiple contrasts of quantiles in a one-way layout. In this paper, we develop an asymptotic method for constructing such intervals both for differences and ratios of quantiles and extend the idea to that of right-censored time-to-event data in survival analysis. Small-sample performance of the proposed method and a bootstrap method were assessed in terms of coverage probabilities and average widths of the simultaneous confidence intervals. Good coverage probabilities were observed for most of the distributions considered in our simulations. The proposed methods have been implemented in an R package and are used to analyze two motivating datasets.

Improving Risk Assessment in Clinical Trials: Toward a Systematic Risk-Based Monitoring Approach.

Regulatory authorities have encouraged the usage of a monitoring (RBM) system in clinical trials before trial initiation for detection of potential risks and inclusion of a mitigation plan in the monitoring strategy. Several RBM tools were developed after the International Council for Harmonization gave sponsors the flexibility to initiate an approach to enhance quality management in a clinical trial. However, various studies have demonstrated the need for improvement of the available RBM tools as each does not provide a comprehensive overview of the characteristics, focus, and application. This research lays out a rationale for a risk methodology assessment (RMA) within the RBM system. The core purpose of RMA is to deliver a scientifically based evaluation and decision of any potential risk in a clinical trial. Thereby, a monitoring plan can be developed to elude prior identified risk outcome. To demonstrate RMA's theoretical approach in practice, a Shiny web application (R Foundation for Statistical Computing) was designed to describe the assessment process of risk analysis and visualization tools that eventually aid in focusing monitoring activities. RMA focuses on the identification of an individual risk and visualizes its weight on the trial. The scoring algorithm of the presented approach computes the assessment of the individual risk in a radar plot and computes the overall score of the trial. Moreover, RMA's novelty lies in its ability to decrease biased decision making during risk assessment by categorizing risk influence and detectability; a characteristic pivotal to serve RBM in assessing risks, and in contributing to a better understanding in the monitoring technique necessary for developing a functional monitoring plan. Future research should focus on validating the power of RMAs to demonstrate its efficiency. This would facilitate the process of characterizing the strengths and weaknesses of RMA in practice.

Prediction intervals for overdispersed binomial data with application to historical controls.

Bioassays are highly standardized trials for assessing the impact of a chemical compound on a model organism. In that context, it is standard to compare several treatment groups with an untreated control. If the same type of bioassay is carried out several times, the amount of information about the historical controls rises with every new study. This information can be applied to predict the outcome of one future control using a prediction interval. Since the observations are counts of success out of a given sample size, like mortality or histopathological findings, the data can be assumed to be binomial but may exhibit overdispersion caused by the variability between historical studies. We describe two approaches that account for overdispersion: asymptotic prediction intervals using the quasi-binomial assumption and prediction intervals based on the quantiles of the beta-binomial distribution. Both interval types were α-calibrated using bootstrap methods. For an assessment of the intervals coverage probabilities, a simulation study based on various numbers of historical studies and sample sizes as well as different binomial proportions and varying levels of overdispersion was run. It could be shown that α-calibration can improve the coverage probabilities of both interval types. The coverage probability of the calibrated intervals, calculated based on at least 10 historical studies, was satisfactory close to the nominal 95%. In a last step, the intervals were computed based on a real data set from the NTP homepage, using historical controls from bioassays with the mice strain B6C3F1.

Temperature response of permafrost soil carbon is attenuated by mineral protection.

Climate change in Arctic ecosystems fosters permafrost thaw and makes massive amounts of ancient soil organic carbon (OC) available to microbial breakdown. However, fractions of the organic matter (OM) may be protected from rapid decomposition by their association with minerals. Little is known about the effects of mineral-organic associations (MOA) on the microbial accessibility of OM in permafrost soils and it is not clear which factors control its temperature sensitivity. In order to investigate if and how permafrost soil OC turnover is affected by mineral controls, the heavy fraction (HF) representing mostly MOA was obtained by density fractionation from 27 permafrost soil profiles of the Siberian Arctic. In parallel laboratory incubations, the unfractionated soils (bulk) and their HF were comparatively incubated for 175 days at 5 and 15°C. The HF was equivalent to 70 ± 9% of the bulk CO2 respiration as compared to a share of 63 ± 1% of bulk OC that was stored in the HF. Significant reduction of OC mineralization was found in all treatments with increasing OC content of the HF (HF-OC), clay-size minerals and Fe or Al oxyhydroxides. Temperature sensitivity (Q10) decreased with increasing soil depth from 2.4 to 1.4 in the bulk soil and from 2.9 to 1.5 in the HF. A concurrent increase in the metal-to-HF-OC ratios with soil depth suggests a stronger bonding of OM to minerals in the subsoil. There, the younger 14 C signature in CO2 than that of the OC indicates a preferential decomposition of the more recent OM and the existence of a MOA fraction with limited access of OM to decomposers. These results indicate strong mineral controls on the decomposability of OM after permafrost thaw and on its temperature sensitivity. Thus, we here provide evidence that OM temperature sensitivity can be attenuated by MOA in permafrost soils.

Adenosine receptors regulate gap junction coupling of the human cerebral microvascular endothelial cells hCMEC/D3 by Ca2+ influx through cyclic nucleotide-gated channels.

KEY POINTS: Gap junction channels are essential for the formation and regulation of physiological units in tissues by allowing the lateral cell-to-cell diffusion of ions, metabolites and second messengers. Stimulation of the adenosine receptor subtype A2B increases the gap junction coupling in the human blood-brain barrier endothelial cell line hCMEC/D3. Although the increased gap junction coupling is cAMP-dependent, neither the protein kinase A nor the exchange protein directly activated by cAMP were involved in this increase. We found that cAMP activates cyclic nucleotide-gated (CNG) channels and thereby induces a Ca2+ influx, which leads to the increase in gap junction coupling. The report identifies CNG channels as a possible physiological link between adenosine receptors and the regulation of gap junction channels in endothelial cells of the blood-brain barrier. ABSTRACT: The human cerebral microvascular endothelial cell line hCMEC/D3 was used to characterize the physiological link between adenosine receptors and the gap junction coupling in endothelial cells of the blood-brain barrier. Expressed adenosine receptor subtypes and connexin (Cx) isoforms were identified by RT-PCR. Scrape loading/dye transfer was used to evaluate the impact of the A2A and A2B adenosine receptor subtype agonist 2-phenylaminoadenosine (2-PAA) on the gap junction coupling. We found that 2-PAA stimulated cAMP synthesis and enhanced gap junction coupling in a concentration-dependent manner. This enhancement was accompanied by an increase in gap junction plaques formed by Cx43. Inhibition of protein kinase A did not affect the 2-PAA-related enhancement of gap junction coupling. In contrast, the cyclic nucleotide-gated (CNG) channel inhibitor l-cis-diltiazem, as well as the chelation of intracellular Ca2+ with BAPTA, or the absence of external Ca2+ , suppressed the 2-PAA-related enhancement of gap junction coupling. Moreover, we observed a 2-PAA-dependent activation of CNG channels by a combination of electrophysiology and pharmacology. In conclusion, the stimulation of adenosine receptors in hCMEC/D3 cells induces a Ca2+ influx by opening CNG channels in a cAMP-dependent manner. Ca2+ in turn induces the formation of new gap junction plaques and a consecutive sustained enhancement of gap junction coupling. The report identifies CNG channels as a physiological link that integrates gap junction coupling into the adenosine receptor-dependent signalling of endothelial cells of the blood-brain barrier.

The cataract related mutation N188T in human connexin46 (hCx46) revealed a critical role for residue N188 in the docking process of gap junction channels.

The mutation N188T in human connexin46 (hCx46) correlates with a congenital nuclear pulverulent cataract. This mutation is in the second extracellular loop, a domain involved in docking of gap junction hemichannels. To analyze the functional consequences of this mutation, we expressed hCx46N188T and the wild type (hCx46wt) in Xenopus oocytes and HeLa cells. In Xenopus oocytes, hemichannels formed by hCx46wt and hCx46N188T had similar electrical properties. Additionally, a Ca(2+) and La(3+) sensitive current was observed in HeLa cells expressing eGFP-labeled hCx46wt or eGFP-labeled hCx46N188T. These results suggest that the N188T mutation did not alter apparent expression and the membrane targeting of the protein. Cells expressing hCx46wt-eGFP formed gap junction plaques, but plaques formed by hCx46N188T were extremely rare. A reduced plaque formation was also found in cells cotransfected with hCx46N188T-eGFP and mCherry-labeled hCx46wt as well as in cocultured cells expressing hCx46N188T-eGFP and hCx46wt-mCherry. Dye transfer experiments in cells expressing hCx46N188T revealed a lower transfer rate than cells expressing hCx46wt. We postulate that the N188T mutation affects intercellular connexon docking. This hypothesis is supported by molecular modeling of hCx46 using the crystal structure of hCx26 as a template. The model indicated that N188 is important for hemichannel docking through formation of hydrogen bonds with the residues R180, T189 and D191 of the opposing hCx46. The results suggest that the N188T mutation hinders the docking of the connexons to form gap junction channels. Moreover, the finding that a glutamine substitution (hCx46N188Q) could not rescue the docking emphasizes the specific role of N188.

Re-evaluation of a novel approach for quantitative myocardial oedema detection by analysing tissue inhomogeneity in acute myocarditis using T2-mapping.

OBJECTIVES: To re-evaluate a recently suggested approach of quantifying myocardial oedema and increased tissue inhomogeneity in myocarditis by T2-mapping. METHODS: Cardiac magnetic resonance data of 99 patients with myocarditis were retrospectively analysed. Thirthy healthy volunteers served as controls. T2-mapping data were acquired at 1.5 T using a gradient-spin-echo T2-mapping sequence. T2-maps were segmented according to the 16-segments AHA-model. Segmental T2-values, segmental pixel-standard deviation (SD) and the derived parameters maxT2, maxSD and madSD were analysed and compared to the established Lake Louise criteria (LLC). RESULTS: A re-estimation of logistic regression models revealed that all models containing an SD-parameter were superior to any model containing global myocardial T2. Using a combined cut-off of 1.8 ms for madSD + 68 ms for maxT2 resulted in a diagnostic sensitivity of 75% and specificity of 80% and showed a similar diagnostic performance compared to LLC in receiver-operating-curve analyses. Combining madSD, maxT2 and late gadolinium enhancement (LGE) in a model resulted in a superior diagnostic performance compared to LLC (sensitivity 93%, specificity 83%). CONCLUSIONS: The results show that the novel T2-mapping-derived parameters exhibit an additional diagnostic value over LGE with the inherent potential to overcome the current limitations of T2-mapping. KEY POINTS: • A novel quantitative approach to myocardial oedema imaging in myocarditis was re-evaluated. • The T2-mapping-derived parameters maxT2 and madSD were compared to traditional Lake-Louise criteria. • Using maxT2 and madSD with dedicated cut-offs performs similarly to Lake-Louise criteria. • Adding maxT2 and madSD to LGE results in further increased diagnostic performance. • This novel approach has the potential to overcome the limitations of T2-mapping.

A novel multiparametric imaging approach to acute myocarditis using T2-mapping and CMR feature tracking.

BACKGROUND: The aim of this study was to evaluate the diagnostic potential of a novel cardiovascular magnetic resonance (CMR) based multiparametric imaging approach in suspected myocarditis and to compare it to traditional Lake Louise criteria (LLC). METHODS: CMR data from 67 patients with suspected acute myocarditis were retrospectively analyzed. Seventeen age- and gender-matched healthy subjects served as control. T2-mapping data were acquired using a Gradient-Spin-Echo T2-mapping sequence in short-axis orientation. T2-maps were segmented according to the 16-segments AHA-model and segmental T2 values and pixel-standard deviation (SD) were recorded. Afterwards, the parameters maxT2 (the highest segmental T2 value) and madSD (the mean absolute deviation (MAD) of the pixel-SDs) were calculated for each subject. Cine sequences in three long axes and a stack of short-axis views covering the left and right ventricle were analyzed using a dedicated feature tracking algorithm. RESULTS: A multiparametric imaging model containing madSD and LV global circumferential strain (GCSLV) resulted in the highest diagnostic performance in receiver operating curve analyses (area under the curve [AUC] 0.84) when compared to any model containing a single imaging parameter or to LLC (AUC 0.79). Adding late gadolinium enhancement (LGE) to the model resulted in a further increased diagnostic performance (AUC 0.93) and yielded the highest diagnostic sensitivity of 97% and specificity of 77%. CONCLUSIONS: A multiparametric CMR imaging model including the novel T2-mapping derived parameter madSD, the feature tracking derived strain parameter GCSLV and LGE yields superior diagnostic sensitivity in suspected acute myocarditis when compared to any imaging parameter alone and to LLC.

Reproducibility of three different cardiac T2 -mapping sequences at 1.5T.

PURPOSE: To elucidate the impact of technical and intraindividual reproducibility on the overall variability of myocardial T2 relaxation times. MATERIALS AND METHODS: Thirty healthy volunteers were examined three times (day 1 morning/evening, evening after 2-3 weeks) at 1.5T. During each examination three different T2 -mapping sequences were acquired twice at three slices in short axis view: multi-echo-spin-echo (MESE), T2 -prepared balanced steady-state free precession (SSFP) (T2 prep), and gradient-spin-echo with and without fat saturation (GraSE/GraSEFS ). Repeated measurements were performed for T2 prep and GraSE. Segmented T2 -maps were generated for each slice according to the American Heart Association (AHA) 16-segment model. RESULTS: The coefficients of variation and intraclass correlation coefficients for intraobserver variability were: 1.3% and 0.89 for T2 prep, 1.5% and 0.93 for GraSE, 3.1% and 0.83 for MESE; and for interobserver variability: 3.3% and 0.66 for T2 prep, 2.0% and 0.83 for GraSE, 3.6% and 0.77 for MESE. No systematic difference of T2 times was observed due to diurnal effects and on long-term analysis using one-way analysis of variance (ANOVA) with Tukey-type multiple comparisons (morning vs. evening scan for T2 prep: 52.5 ± 2.4 vs. 51.7 ± 2.7 msec, P = 0.119; for GraSE: 58.6 ± 4.0 vs. 58.5 ± 3.8 msec, P = 0.984; for GraSEFS 57.1 ± 3.2 vs. 57.2 ± 3.9 msec, P = 0.998, and for MESE: 53.8 ± 2.7 vs. 53.3 ± 3.3 msec, P = 0.541; scans between weeks for T2 prep: 51.7 ± 2.7 vs. 51.4 ± 2.4 msec, P = 0.873; for GraSE: 58.5 ± 3.8 vs. 58.1 ± 3.4 msec, P = 0.736; for GraSEFS : 57.2 ± 3.9 vs. 57.0 ± 4.6 msec, P = 0.964, and for MESE: 53.3 ± 3.3 vs. 53.4 ± 2.4 msec, P = 0.970). ANOVA components, however, demonstrated a greater variance of T2 times over multiple timepoints than for repeated measurements within the same scan (variance components of the model fit for intraday variance vs. repeated measurements: T2 prep 2.22 vs. 1.36, GraSE 3.76 vs. 2.09, GraSEFS 3.96 vs. 1.58, MESE 1.86; and for interweeks variance vs. repeated measurements: T2 prep 2.21 vs. 0.80, GraSE 3.20 vs. 2.10, GraSEFS 8.82 vs. 1.18, and MESE 4.49). CONCLUSION: Technical reproducibility and intra- and interobserver agreement of myocardial T2 relaxation times are excellent and intraindividual variation over time is small. Therefore, we consider subject-related factors to explain most of the interindividual variability of myocardial T2 times reported in previous studies. The acknowledgment of this subject-related, biological variability may be important for the future diagnostic value of T2 -mapping. J. Magn. Reson. Imaging 2016;44:1168-1178.

Cardiac T2-mapping using a fast gradient echo spin echo sequence - first in vitro and in vivo experience.

BACKGROUND: The aim of this study was the evaluation of a fast Gradient Spin Echo Technique (GraSE) for cardiac T2-mapping, combining a robust estimation of T2 relaxation times with short acquisition times. The sequence was compared against two previously introduced T2-mapping techniques in a phantom and in vivo. METHODS: Phantom experiments were performed at 1.5 T using a commercially available cylindrical gel phantom. Three different T2-mapping techniques were compared: a Multi Echo Spin Echo (MESE; serving as a reference), a T2-prepared balanced Steady State Free Precession (T2prep) and a Gradient Spin Echo sequence. For the subsequent in vivo study, 12 healthy volunteers were examined on a clinical 1.5 T scanner. The three T2-mapping sequences were performed at three short-axis slices. Global myocardial T2 relaxation times were calculated and statistical analysis was performed. For assessment of pixel-by-pixel homogeneity, the number of segments showing an inhomogeneous T2 value distribution, as defined by a pixel SD exceeding 20 % of the corresponding observed T2 time, was counted. RESULTS: Phantom experiments showed a greater difference of measured T2 values between T2prep and MESE than between GraSE and MESE, especially for species with low T1 values. Both, GraSE and T2prep resulted in an overestimation of T2 times compared to MESE. In vivo, significant differences between mean T2 times were observed. In general, T2prep resulted in lowest (52.4 ± 2.8 ms) and GraSE in highest T2 estimates (59.3 ± 4.0 ms). Analysis of pixel-by-pixel homogeneity revealed the least number of segments with inhomogeneous T2 distribution for GraSE-derived T2 maps. CONCLUSIONS: The GraSE sequence is a fast and robust sequence, combining advantages of both MESE and T2prep techniques, which promises to enable improved clinical applicability of T2-mapping in the future. Our study revealed significant differences of derived mean T2 values when applying different sequence designs. Therefore, a systematic comparison of different cardiac T2-mapping sequences and the establishment of dedicated reference values should be the goal of future studies.

Mapping tissue inhomogeneity in acute myocarditis: a novel analytical approach to quantitative myocardial edema imaging by T2-mapping.

BACKGROUND: The purpose of the present study was to investigate the diagnostic value of T2-mapping in acute myocarditis (ACM) and to define cut-off values for edema detection. METHODS: Cardiovascular magnetic resonance (CMR) data of 31 patients with ACM were retrospectively analyzed. 30 healthy volunteers (HV) served as a control. Additionally to the routine CMR protocol, T2-mapping data were acquired at 1.5 T using a breathhold Gradient-Spin-Echo T2-mapping sequence in six short axis slices. T2-maps were segmented according to the 16-segments AHA-model and segmental T2 values as well as the segmental pixel-standard deviation (SD) were analyzed. RESULTS: Mean differences of global myocardial T2 or pixel-SD between HV and ACM patients were only small, lying in the normal range of HV. In contrast, variation of segmental T2 values and pixel-SD was much larger in ACM patients compared to HV. In random forests and multiple logistic regression analyses, the combination of the highest segmental T2 value within each patient (maxT2) and the mean absolute deviation (MAD) of log-transformed pixel-SD (madSD) over all 16 segments within each patient proved to be the best discriminators between HV and ACM patients with an AUC of 0.85 in ROC-analysis. In classification trees, a combined cut-off of 0.22 for madSD and of 68 ms for maxT2 resulted in 83% specificity and 81% sensitivity for detection of ACM. CONCLUSIONS: The proposed cut-off values for maxT2 and madSD in the setting of ACM allow edema detection with high sensitivity and specificity and therefore have the potential to overcome the hurdles of T2-mapping for its integration into clinical routine.

Statistical methods and software for validation studies on new in vitro toxicity assays.

When a new in vitro assay method is introduced, it should be validated against the best available knowledge or a reference standard assay. For assays resulting in a simple binary outcome, the data can be displayed as a 2×2 table. Based on the estimated sensitivity and specificity, and the assumed prevalence of true positives in the population of interest, the positive and negative predictive values of the new assay can be calculated. We briefly discuss the experimental design of validation experiments and previously published methods for computing confidence intervals for predictive values. The application of the methods is illustrated for two toxicological examples, by using tools available in the free software, namely, R: confidence intervals for predictive values are computed for a validation study of an in vitro test battery, and sample size calculation is illustrated for an acute toxicity assay. The R code necessary to reproduce the results is given.

A Multifunctional Nanostructured Hydrogel as a Platform for Deciphering Niche Interactions of Hematopoietic Stem and Progenitor Cells.

For over half a century, hematopoietic stem cells (HSCs) have been used for transplantation therapy to treat severe hematologic diseases. Successful outcomes depend on collecting sufficient donor HSCs as well as ensuring efficient engraftment. These processes are influenced by dynamic interactions of HSCs with the bone marrow niche, which can be revealed by artificial niche models. Here, a multifunctional nanostructured hydrogel is presented as a 2D platform to investigate how the interdependencies of cytokine binding and nanopatterned adhesive ligands influence the behavior of human hematopoietic stem and progenitor cells (HSPCs). The results indicate that the degree of HSPC polarization and motility, observed when cultured on gels presenting the chemokine SDF-1α and a nanoscale-defined density of a cellular (IDSP) or extracellular matrix (LDV) α4ß1 integrin binding motif, are differently influenced on hydrogels functionalized with the different ligand types. Further, SDF-1α promotes cell polarization but not motility. Strikingly, the degree of differentiation correlates negatively with the nanoparticle spacing, which determines ligand density, but only for the cellular-derived IDSP motif. This mechanism potentially offers a means of predictably regulating early HSC fate decisions. Consequently, the innovative multifunctional hydrogel holds promise for deciphering dynamic HSPC-niche interactions and refining transplantation therapy protocols.

The role of the C-terminus in functional expression and internalization of rat connexin46 (rCx46).

The C-terminus (CT) of rCx46 consists of 186 residues (H230-I416). Recent studies showed that rCx46(28.2), truncated after H243, altered the formation of functional hemichannels when expressed in Xenopus oocytes, while rCx46(37.7), truncated after A333 formed gap junction hemichannels similarly to rCx46(wt). To analyze the role of the CT up to A333 in functional expression with cell imaging and dye-transfer techniques, different mutants were generated by C-terminal truncation between H243-A333, labeled with EGFP and expressed in HeLa cells. These rCx46 variants were characterized according to their compartmentalization in organelles, their presence in microscopic detectable vesicles and their ability to form gap junction plaques. rCx46 truncated after A311 (rCx46(35.3)) was compartmentalized, was found in vesicles and formed functional gap junction plaques similarly to rCx46(wt). With a truncation after P284 (rCx46(32.6)), the protein was not compartmentalized and the amount of vesicles containing the protein were reduced; however, functional gap junction plaque formation was not affected as compared to rCx46(35.3). rCx46(28.2) did not form functional gap junction plaques; it was not found in vesicles or in cellular compartments. Live-cell imaging and detection of annular junctions for rCx46(32.6) and rCx46(35.3) revealed that the truncation after P284 reduced the frequency of vesicle budding from gap junction plaques and the formation of annular junctions. These results suggest that the C-terminal region of rCx46 up to A311 (rCx46(35.3)) is necessary for its correct compartmentalization and internalization in the form of annular junctions, while the H230-P284 C-terminal region (rCx46(32.6)) is sufficient for the formation of dye coupled gap junction channels.