Neutron scattering and polymer dynamics

4 páginas, 4 figuras.-- El pdf del artículo es la versión post-print.Nowadays polymers are ubiquitous in our daily life because they are durable, cheap to produce, easy to process and exhibit very versatile and favorable mechanical properties. For example, depending on temperature or time the same polymer may be viscous, rubber elastic, very tough with high impact strength or even brittle. Polymers are composed of macromolecules which are built up by a large number monomer units linked together by covalent bonds. Due to this connectivity, the relevant processes driving the dynamics in polymers depend on the length scale of observation. While at typical inter- and intra-macromolecular length scales (≈ 10 Å and below) polymer dynamics display the universal features of glass-forming systems, at larger distances the macromolecular character of the polymer chains prevails –there, entropy and topological constraints (‘entanglements’) play the major role. Carbon and Hydrogen are in most cases the main constituents of polymers. Therefore, neutron scattering combined with isotopic substitution (H/D labeling) is an extremely well-suited technique to study the dynamical processes of polymeric materials at a molecular level. Motions of particular molecular groups or given polymer chains, e. g. in a polymer blend, can be selectively investigated by neutron scattering. However, the restricted dynamic window offered by this technique prevents a complete characterization of the complex polymer dynamics, including several multi-scale processes the characteristic times of which span over many orders of magnitude. The combination with other experimental techniques is, in most cases, essential to fully characterize the processes; in addition, the use of complementary MD-simulations has proved to be crucial for the interpretation of the neutron-scattering results.Peer reviewe

Exonization of active mouse L1s: a driver of transcriptome evolution?

<p>Abstract</p> <p>Background</p> <p>Long interspersed nuclear elements (LINE-1s, L1s) have been recently implicated in the regulation of mammalian transcriptomes.</p> <p>Results</p> <p>Here, we show that members of the three active mouse L1 subfamilies (A, G_Fand T_F) contain, in addition to those on their sense strands, conserved functional splice sites on their antisense strands, which trigger multiple exonization events. The latter is particularly intriguing in the light of the strong antisense orientation bias of intronic L1s, implying that the toleration of antisense insertions results in an increased potential for exonization.</p> <p>Conclusion</p> <p>In a genome-wide analysis, we have uncovered evidence suggesting that the mobility of the large number of retrotransposition-competent mouse L1s (~2400 potentially active L1s in NCBIm35) has significant potential to shape the mouse transcriptome by continuously generating insertions into transcriptional units.</p

Prostate Cancer Nodal Staging: Using Deep Learning to Predict 68Ga-PSMA-Positivity from CT Imaging Alone

Lymphatic spread determines treatment decisions in prostate cancer (PCa) patients. 68Ga-PSMA-PET/CT can be performed, although cost remains high and availability is limited. Therefore, computed tomography (CT) continues to be the most used modality for PCa staging. We assessed if convolutional neural networks (CNNs) can be trained to determine 68Ga-PSMA-PET/CT-lymph node status from CT alone. In 549 patients with 68Ga-PSMA PET/CT imaging, 2616 lymph nodes were segmented. Using PET as a reference standard, three CNNs were trained. Training sets balanced for infiltration status, lymph node location and additionally, masked images, were used for training. CNNs were evaluated using a separate test set and performance was compared to radiologists' assessments and random forest classifiers. Heatmaps maps were used to identify the performance determining image regions. The CNNs performed with an Area-Under-the-Curve of 0.95 (status balanced) and 0.86 (location balanced, masked), compared to an AUC of 0.81 of experienced radiologists. Interestingly, CNNs used anatomical surroundings to increase their performance, "learning" the infiltration probabilities of anatomical locations. In conclusion, CNNs have the potential to build a well performing CT-based biomarker for lymph node metastases in PCa, with different types of class balancing strongly affecting CNN performance

Compositional mapping of surfaces in atomic force microscopy

We propose a method for mapping the composition of a surface by using an amplitude modulation atomic force microscope operated without tip-surface mechanical contact. The method consists in exciting the first two modes of the microcantilever. The nonlinear dynamics of the tip motion, the coupling of its first two modes, and the sensitivity of the second mode to long-range attractive forces allows us to use this mode to probe compositional changes while the signal from the first mode is used to image the sample surface. We demonstrate that the second mode has a sensitivity to surface force variations below 10−11 N.The authors acknowledge helpful discussions with A. San Paulo. This work was financially supported by then Dirección General de Investigación Científica y Técnica of Spain (PB98-0471) and the European Commission (MONA-LISA, G5RD-CT-2000-00349).Peer reviewe

Hepatocellular adenomas: is there additional value in using Gd-EOB-enhanced MRI for subtype differentiation?

Purpose: To differentiate subtypes of hepatocellular adenoma (HCA) based on enhancement characteristics in gadoxetic acid (Gd-EOB) magnetic resonance imaging (MRI). Materials and methods: Forty-eight patients with 79 histopathologically proven HCAs who underwent Gd-EOB-enhanced MRI were enrolled (standard of reference: surgical resection). Two blinded radiologists performed quantitative measurements (lesion-to-liver enhancement) and evaluated qualitative imaging features. Inter-reader variability was tested. Advanced texture analysis was used to evaluate lesion heterogeneity three-dimensionally. Results: Overall, there were 19 (24%) hepatocyte nuclear factor (HNF)-1a-mutated (HHCAs), 37 (47%) inflammatory (IHCAs), 5 (6.5%) b-catenin-activated (bHCA), and 18 (22.5%) unclassified (UHCAs) adenomas. In the hepatobiliary phase (HBP), 49.5% (39/79) of all adenomas were rated as hypointense and 50.5% (40/79) as significantly enhancing (defined as > 25% intralesional GD-EOB uptake). 82.5% (33/40) of significantly enhancing adenomas were IHCAs, while only 4% (1/40) were in the HHCA subgroup (p < 0.001). When Gd-EOB uptake behavior was considered in conjunction with established MRI features (binary regression model), the area under the curve (AUC) increased from 0.785 to 0.953 for differentiation of IHCA (atoll sign + hyperintensity), from 0.859 to 0.903 for bHCA (scar + hyperintensity), and from 0.899 to 0.957 for HHCA (steatosis + hypointensity). Three-dimensional region of interest (3D ROI) analysis showed significantly increased voxel heterogeneity for IHCAs (p = 0.038). Conclusion: Gd-EOB MRI is of added value for subtype differentiation of HCAs and reliably identifies the typical heterogeneous HBP uptake of IHCAs. Diagnostic accuracy can be improved significantly by the combined analysis of established morphologic MR appearances and intralesional Gd-EOB uptake. Key points: •Gd-EOB-enhanced MRI is of added value for subtype differentiation of HCA. •IHCA and HHCA can be identified reliably based on their typical Gd-EOB uptake patterns, and accuracy increases significantly when additionally taking established MR appearances into account. •The small numbers of bHCAs and UHCAs remain the source of diagnostic uncertainty

Retrotransposition and mutation events yield Rap1 GTPases with differential signalling capacity

<p>Abstract</p> <p>Background</p> <p>Retrotransposition of mRNA transcripts gives occasionally rise to functional retrogenes. Through acquiring tempero-spatial expression patterns distinct from their parental genes and/or functional mutations in their coding sequences, such retrogenes may in principle reshape signalling networks.</p> <p>Results</p> <p>Here we present evidence for such a scenario, involving retrogenes of Rap1 belonging to the Ras family of small GTPases. We identified two murine and one human-specific retrogene of Rap1A and Rap1B, which encode proteins that differ by only a few amino acids from their parental Rap1 proteins. Markedly, human hRap1B-retro and mouse mRap1A-retro1 acquired mutations in the 12^thand 59^thamino acids, respectively, corresponding to residues mutated in constitutively active oncogenic Ras proteins. Statistical and structural analyses support a functional evolution scenario, where Rap1 isoforms of retrogenic origin are functionally distinct from their parental proteins. Indeed, all retrogene-encoded GTPases have an increased GTP/GDP binding ratio <it>in vivo</it>, indicating that their conformations resemble that of active GTP-bound Rap1. We furthermore demonstrate that these three Rap1 isoforms exhibit distinct affinities for the Ras-binding domain of RalGDS. Finally, when tested for their capacity to induce key cellular processes like integrin-mediated cell adhesion or cell spreading, marked differences are seen.</p> <p>Conclusions</p> <p>Together, these data lend strong support for an evolution scenario, where retrotransposition and subsequent mutation events generated species-specific Rap1 isoforms with differential signaling potential. Expression of the constitutively active human Rap1B-retro in cells like those derived from Ramos Burkitt's lymphoma and bone marrow from a patient with myelodysplastic syndrome (MDS) warrants further investigation into its role in disease development.</p

Enhancing the differentiation of pulmonary lymphoma and fungal pneumonia in hematological patients using texture analysis in 3-T MRI

Objectives: To evaluate texture analysis in nonenhanced 3-T MRI for differentiating pulmonary fungal infiltrates and lymphoma manifestations in hematological patients and to compare the diagnostic performance with that of signal intensity quotients ("nonenhanced imaging characterization quotients," NICQs). Methods: MR scans were performed using a speed-optimized imaging protocol without an intravenous contrast medium including axial T2-weighted (T2w) single-shot fast spin-echo and T1-weighted (T1w) gradient-echo sequences. ROIs were drawn within the lesions to extract first-order statistics from original images using HeterogeneityCAD and PyRadiomics. NICQs were calculated using signal intensities of the lesions, muscle, and fat. The standard of reference was histology or clinical diagnosis in follow-up. Statistical testing included ROC analysis, clustered ROC analysis, and DeLong test. Intra- and interrater reliability was tested using intraclass correlation coefficients (ICC). Results: Thirty-three fungal infiltrates in 16 patients and 38 pulmonary lymphoma manifestations in 19 patients were included. Considering the leading lesion in each patient, diagnostic performance was excellent for T1w entropy (AUC 80.2%; p 0.81) for these parameters except for moderate intrarater reliability of T1w energy (ICC = 0.64). Conclusions: T1w entropy, uniformity, and energy and T2w energy showed the best performances for differentiating pulmonary lymphoma and fungal pneumonia and outperformed NICQs. Results of the texture analysis should be checked for their intrinsic consistency to identify possible incongruities of single parameters. Key points: • Texture analysis in nonenhanced pulmonary MRI improves the differentiation of pulmonary lymphoma and fungal pneumonia compared with signal intensity quotients. • T1w entropy, uniformity, and energy along with T2w energy show the best performances for differentiating pulmonary lymphoma from fungal pneumonia. • The results of the texture analysis should be checked for their intrinsic consistency to identify possible incongruities of single parameters