Induction of splice correction by cell-penetrating peptide nucleic acids

BACKGROUND: Directing splicing using oligonucleotides constitutes a promising therapeutic tool for a variety of diseases such as beta-thalassemia, cystic fibrosis, and certain cancers. The rationale is to block aberrant splice sites, thus directing the splicing of the pre-mRNA towards the desired protein product. One of the difficulties in this setup is the poor bioavailability of oligonucleotides, as the most frequently used transfection agents are unsuitable for in vivo use. Here we present splice-correcting peptide nucleic acids (PNAs), tethered to a variety of cell-penetrating peptides (CPPs), evaluating their mechanism of uptake and ability to correct aberrant splicing. METHODS: HeLa cells stably expressing luciferase containing an aberrant splice site were used. A previously described PNA sequence, capable of correcting the aberrant splicing, was conjugated to the CPPs, Tat, penetratin and transportan, via a disulfide bridge. The ability of the CPP-PNA conjugates to correct splicing was measured, and membrane disturbance and cell viability were evaluated using LDH leakage and WST-1 assays. Lysosomotropic agents, inhibition of endocytosis at 4 degrees C and confocal microscopy were used to investigate the importance of endocytosis in the uptake of the cell-penetrating PNAs. RESULTS: All the three CPPs were able to promote PNA translocation across the plasma membrane and induce splice correction. Transportan (TP) was the most potent vector and significantly restored splicing in a concentration-dependent manner. Interestingly, TP also rendered a concentration-dependent splice correction in serum, in contrast to Tat and penetratin. Addition of the lysosomotrophic agent chloroquine increases the splice correction efficacy of the CPP-PNA conjugates up to 4-fold, which together with experiments at 4 degrees C and the visual information from confocal microscopy, indicate that the mechanism of uptake responsible for internalization of CPP-PNA conjugates is mainly endocytic. Finally, co-localization studies with dextran further indicate that conjugates, at least in the case of TP, internalize via endocytosis and in particular macropinocytosis. CONCLUSIONS: These data demonstrate that CPPs can be used for the delivery of splice-correcting PNAs, with potential to be used as a therapeutic approach for regulating splicing in a variety of diseases. Transportan presents itself as the overall most suitable vector in this study, generating the most efficient conjugates for splice correction.     

Feasibility of an SUV normalization to 1 hour after the 18F-FDG injection

The aim of this work was to reduce the SUV variability related to the time delay between 18F-FDG injection and the static PET acquisition, by means of a normalization to a 1-h time delay. Two static PET acquisitions separated by approximately 1 h were performed on each of 14 cancer patients, with SUVs on 22 hypermetabolic lesions calculated for both scans. The pairs of SUVs were normalized to each other using the parameterized input function with one free parameter (alpha3). This optimized parameter was found by computing the value which yielded equal normalized SUV pairs, on average, over the whole series. Without normalization, SUVs measured at later scans were found to be significantly greater than the earlier ones: mean (+/- SD) ratio of 0.84 (+/-0.08; range 0.69-0.97). After normalization, with an alpha3 value of 0.0257 min(-1), as expected, the mean (+/- SD) ratio was 1.00 (+/-0.07; range 0.88-1.10).     

Taxon-related pollen source areas for lake basins in the southern Alps: an empirical approach

The pollen/vegetation relationship in broadleaved forests dominated by Castanea sativa was analysed using an empirical approach. The pollen content of surface sediments of three lake basins of different sizes (6.3, 22.2, and 101.2 ha) in Ticino (southern Switzerland) was used for a comparison with the surrounding vegetation. We surveyed the vegetation around the two small lakes, Lago di Origlio and Lago di Muzzano, and estimated the relative crown coverage of tree species. The regional vegetation outside the lake catchment (ca. >1 km) was determined with the data from the first Swiss National Forest Inventory. For the third large lake, basin of Ponte Tresa, we used only this latter approach for comparison with pollen data. We compare uncorrected and corrected pollen percentages with vegetational data that were processed with distance-weighting functions. To assess the degree of correspondence between pollen and vegetation data we define a ratio pollen/vegetation, which allows a comparison at the taxon level. The best fit between total pollen load and vegetation is reached for a distance from the lake shore of ca. 300 m for Lago di Origlio (150×350 m in size) and of ca. 600 m for Lago di Muzzano (300×750 m in size). Beside these general patterns, our analysis reveals taxon-specific pollen dispersal patterns that are in agreement with results from previous studies in northern Europe. Ratios of species with local (proximal) and long-distance (distal) pollen dispersal provide evidence that pollen dispersal mechanisms can influence the size of the taxon-related pollen source area, from small (100–400 m) to large (>5 km) for the same lake. The proportion of distal species increases with increasing lake size, highlighting the predominance of atmospheric pollen transport. We conclude that the large species-related differences in pollen source areas have to be taken into account when the provenance at a site is estimated and discussed.     

Statistical strategies for avoiding false discoveries in metabolomics and related experiments

Many metabolomics, and other high-content or high-throughput, experiments are set up such that the primary aim is the discovery of biomarker metabolites that can discriminate, with a certain level of certainty, between nominally matched ‘case’ and ‘control’ samples. However, it is unfortunately very easy to find markers that are apparently persuasive but that are in fact entirely spurious, and there are well-known examples in the proteomics literature. The main types of danger are not entirely independent of each other, but include bias, inadequate sample size (especially relative to the number of metabolite variables and to the required statistical power to prove that a biomarker is discriminant), excessive false discovery rate due to multiple hypothesis testing, inappropriate choice of particular numerical methods, and overfitting (generally caused by the failure to perform adequate validation and cross-validation). Many studies fail to take these into account, and thereby fail to discover anything of true significance (despite their claims). We summarise these problems, and provide pointers to a substantial existing literature that should assist in the improved design and evaluation of metabolomics experiments, thereby allowing robust scientific conclusions to be drawn from the available data. We provide a list of some of the simpler checks that might improve one’s confidence that a candidate biomarker is not simply a statistical artefact, and suggest a series of preferred tests and visualisation tools that can assist readers and authors in assessing papers. These tools can be applied to individual metabolites by using multiple univariate tests performed in parallel across all metabolite peaks. They may also be applied to the validation of multivariate models. We stress in particular that classical p-values such as “p < 0.05”, that are often used in biomedicine, are far too optimistic when multiple tests are done simultaneously (as in metabolomics). Ultimately it is desirable that all data and metadata are available electronically, as this allows the entire community to assess conclusions drawn from them. These analyses apply to all high-dimensional ‘omics’ datasets.     

Clonal splitters and integrators in harsh environments of the Trans-Himalaya

Individuals of clonal plants consist of physically and physiologically connected ramets. In splitters, they are integrated for a time shorter than ramet generation time (i.e. the time it takes to produce the first offspring ramet), whereas in integrators connections between ramets persist for a longer time. It has been predicted that integrators should prevail in stressful environments, such as habitats poor in nutrients, whereas splitters are expected to dominate in benign habitats, such as fertile areas with a moderate climate. I tested these predictions in four dry mountain areas of the Trans-Himalaya, in high altitudes subjected to multiple stresses. In accordance with the expectations I found that clonal plants with integrated ramets reach higher mean and maximum altitudes than splitters. Integrators were over-represented in nutrient-poor habitats, such as dry semi-deserts, sandy steppes and in subnival habitats, whereas splitters preferentially colonised mesic habitats, saline sites and wetlands. While there was no difference in the representation of splitters and integrators in habitats with an unstable surface, such as screes, dunes and water bodies, fully integrated clonal plants preferred very stable environments, such as banks of streams covered by closed-canopy vegetation. Most relationships between clonal integration and environmental factors were explainable by the phylogenetic relationship between the species, only the significant preference of splitters for shaded environments persisted in phylogenetically corrected analysis. The results indicate that clonal integration belongs to a set of evolutionarily conservative plant traits, usually shared by related species. Consequently, the adaptive value of clonal integration in individual habitats remains questionable.     

Bias-corrected variance estimation and hypothesis testing for spatial point and marked point processes using subsampling

Summary We introduce novel regression extrapolation based methods to correct the often large bias in subsampling variance estimation as well as hypothesis testing for spatial point and marked point processes. For variance estimation, our proposed estimators are linear combinations of the usual subsampling variance estimator based on subblock sizes in a continuous interval. We show that they can achieve better rates in mean squared error than the usual subsampling variance estimator. In particular, for n×n observation windows, the optimal rate of n^?2 can be achieved if the data have a finite dependence range. For hypothesis testing, we apply the proposed regression extrapolation directly to the test statistics based on different subblock sizes, and therefore avoid the need to conduct bias correction for each element in the covariance matrix used to set up the test statistics. We assess the numerical performance of the proposed methods through simulation, and apply them to analyze a tropical forest data set.     

Estimation and correction of seed recovery bias from moist-soil cores

Scientists estimate seed abundances to calculate seasonal carrying capacities and assess wetland management actions for waterfowl and other wildlife using soil core samples. We evaluated recovery of known quantities of moist-soil seeds from whole and subsampled experimental core samples containing 12 seed taxa representing small, medium, and large size classes. We recovered 86.3% (SE = 1.8) of all seeds added to experimental cores; 8.3% (SE = 1.2) of seeds were destroyed during the sieving process and 5.4% (SE = 1.2) were not recovered by observers. Recovery rates varied by seed size, but not seed quantity or disproportionate ratios of seed-size classes. Overall seed recovery rates were similar between subsampled ( = 81.2%, SE = 3.6) and whole–processed core samples ( = 86.3%, SE = 1.8). We used recovery rates to generate size-specific, taxon-specific, and constant correction factors and applied each to actual core sample data. Size-specific correction factors increased seed mass estimates in the Mississippi Alluvial Valley ( = 10.1%, SE = 0.32), upper Midwest ( = 21.2%, SE = 0.61), and both regions combined ( = 15.7%, SE = 0.51) differently, as seed composition in core samples varied regionally. We suggest scientists consider using size-specific correction factors to account for seed recovery bias in core samples because these factors may be applied to a variety of taxa and produced similar mass estimates as taxon-specific correction factors. However, if data from core samples are unavailable at the resolution of seed size classes, we suggest increasing seed mass estimates by 16% to account for seed recovery bias. © 2011 The Wildlife Society.     

Ultrasound tracking for intra-fractional motion compensation in radiation therapy

Modern techniques as ion beam therapy or 4D imaging require precise target position information. However, target motion particularly in the abdomen due to respiration or patient movement is still a challenge and demands methods that detect and compensate this motion. Ultrasound represents a non-invasive, dose-free and model-independent alternative to fluoroscopy, respiration belt or optical tracking of the patient surface. Thus, ultrasound based motion tracking was integrated into irradiation with actively scanned heavy ions. In a first in vitro experiment, the ultrasound tracking system was used to compensate diverse sinusoidal target motions in two dimensions. A time delay of ∼200 ms between target motion and reported position data was compensated by a prediction algorithm (artificial neural network). The irradiated films proved feasibility of the proposed method. Furthermore, a practicable and reliable calibration workflow was developed to enable the transformation of ultrasound tracking data to the coordinates of the treatment delivery or imaging system – even if the ultrasound probe moves due to respiration. A first proof of principle experiment was performed during time-resolved positron emission tomography (4DPET) to test the calibration workflow and to show the accuracy of an ultrasound based motion tracking in vitro. The results showed that optical ultrasound tracking can reach acceptable accuracies and encourage further research.     

Under-response correction for EBT3 films in the presence of proton spread out Bragg peaks

We present a study of the under-response of the new Gafchromic EBT3 films and a procedure to accurately perform 2D and 3D proton dosimetry measurements for both pristine and spread out Bragg peaks (SOBP) of any energy. These new films differ from the previous EBT2 generation by a slightly different active layer composition, which we show has not effected appreciably their response. The procedure and the beam quality correction factor curve have been benchmarked using 29 MeV modulated proton beams. In order to show the correction to apply when EBT3 films are used as treatment verification tools in anthropomorphic phantoms, two simulation studies involving clinical energies are presented: a SOBP for eye treatments and a SOBP to treat 20 cm deep and 5 cm thick tumours. We find maximum under-responses of 37%, 30% and 7.7% for the modulated 29 MeV beam, eye and deep tumour treatment, respectively, which were attained close to the end of the peak tails, due to a higher proportion of very low energy protons. The maximum deviations between corrected and uncorrected doses were for the three cases, respectively, 20.7%, 8.3% and 2.1% of the average dose across flat region of the SOBP. These values were obtained close to the distal edge of the SOBPs, where the proportion of low energy protons was not as high as on the tail, but there still was a number of protons high enough to deposit a reasonable amount of dose in the films.     

Empirical validation of gradient field models for an accurate ADC measured on clinical 3T MR systems in body oncologic applications

PurposeTo empirically corroborate vendor-provided gradient nonlinearity (GNL) characteristics and demonstrate efficient GNL bias correction for human brain apparent diffusion coefficient (ADC) across 3T MR systems and spatial locations.MethodsSpatial distortion vector fields (DVF) were mapped in 3D using a surface fiducial array phantom for individual gradient channels on three 3T MR platforms from different vendors. Measured DVF were converted into empirical 3D GNL tensors and compared with their theoretical counterparts derived from vendor-provided spherical harmonic (SPH) coefficients. To illustrate spatial impact of GNL on ADC, diffusion weighted imaging using three orthogonal gradient directions was performed on a volunteer brain positioned at isocenter (as a reference) and offset superiorly by 10–17 cm (>10% predicted GNL bias). The SPH tensor-based GNL correction was applied to individual DWI gradient directions, and derived ADC was compared with low-bias reference for human brain white matter (WM) ROIs.ResultsEmpiric and predicted GNL errors were comparable for all three studied 3T MR systems, with <1.0% differences in the median and width of spatial histograms for individual GNL tensor elements. Median (±width) of ADC (10⁻³mm²/s) histograms measured at isocenter in WM reference ROIs from three MR systems were: 0.73 ± 0.11, 0.71 ± 0.14, 0.74 ± 0.17, and at off-isocenters (before versus after GNL correction) were respectively 0.63 ± 0.14 versus 0.72 ± 0.11, 0.53 ± 0.16 versus 0.74 ± 0.18, and 0.65 ± 0.16 versus 0.76 ± 0.18.ConclusionThe phantom-based spatial distortion measurements validated vendor-provided gradient fields, and accurate WM ADC was recovered regardless of spatial locations and clinical MR platforms using system-specific tensor-based GNL correction for routine DWI.