Changes in mechanical properties of myocardium caused by a infarction can lead to kinematic abnormalities. This phenomenon has inspired us to develop this work for delineation of myocardial infarction area directly from non-contrast agents cardiac MR imaging sequences. The main contribution of this work is to develop a new joint motion feature learning architecture to efficiently establish direct correspondences between motion features and tissue properties. This architecture consists of three seamless connected function layers: the heart localization layers can automatically crop the region of interest (ROI) sequences involving the left ventricle from the cardiac MR imaging sequences; the motion feature extraction layers, using long short-term memory-recurrent neural networks, a) builds patch-based motion features through local intensity changes between fixed-size patch sequences (cropped from image sequences), and b) uses optical flow techniques to build image-based features through global intensity changes between adjacent images to describe the motion of each pixel; the fully connected discriminative layers can combine two types of motion features together in each pixel and then build the correspondences between motion features and tissue identities (that is, infarct or not) in each pixel. We validated the performance of our framework in 165 cine cardiac MR imaging datasets by comparing to the ground truths manually segmented from delayed Gadolinium-enhanced MR cardiac images by two radiologists with more than 10 years of experience. Our experimental results show that our proposed method has a high and stable accuracy (pixel-level: 95.03%) and consistency (Kappa statistic: 0.91; Dice: 89.87%; RMSE: 0.72  mm; Hausdorff distance: 5.91  mm) compared to manual delineation results. Overall, the advantage of our framework is that it can determine the tissue identity in each pixel from its motion pattern captured by normal cine cardiac MR images, which makes it an attractive tool for the clinical diagnosis of infarction.

Cell response to extracellular ligand is affected not only by ligand availability, but also by pre-existing cell-to-cell variability that enables a range of responses within a cell population. We developed a computational model that incorporates cell heterogeneity in order to investigate Jurkat T cell response to time dependent extracellular IL-2 stimulation. Our model predicted preferred timing of IL-2 oscillatory input for maximizing downstream intracellular STAT5 nuclear translocation. The modeled cytokine exposure was replicated experimentally through the use of a microfluidic platform that enabled the parallelized capture of dynamic single cell response to precisely delivered pulses of IL-2 stimulus. The in vitro results demonstrate that single cell response profiles vary with pulsatile IL-2 input at pre-equilibrium levels. These observations confirmed our model predictions that Jurkat cells have a preferred range of extracellular IL-2 fluctuations, in which downstream response is rapidly initiated. Further investigation into this filtering behavior could increase our understanding of how pre-existing cellular states within immune cell populations enable a systems response within a preferred range of ligand fluctuations, and whether the observed cytokine range corresponds to in vivo conditions.

Taraxacum officinale (Asteraceae) is widely distributed weedy plant used as a traditional medicinal herb. The population genetics and historical biogeography of this plant have remained relatively unexplored. This study explores phylogeny, population genetics and ancestral reconstructions adopting multi locus sequence typing (MLST) approach. MLST sequences dataset was generated from genomics and chloroplast DNA sequences obtained from 31 T. officinale haplotypes located in 16 different countries. Phylogenetic analysis distributed these haplotypes in well differentiated geographic clades. The study suggested a close relationship between Europe and adjacent Asian countries. Populations of these regions predominantly formed common haplogroups, showed considerable level of gene flow and evidence for recombination events across European and Asian population. Biogeographical inferences obtained by applying statistical dispersal-vicariance analysis (S-DIVA) and Bayesian binary MCMC (BBM) analysis showed that T. officinale was putatively originated in Europe. Molecular clock analysis based on ITS dataset suggested that the divergence between Europe and East Asian populations can be dated to 1.07 Mya with subsequent dispersal and vicariance events. Among different spatial process long distance seed dispersal mediated by wind had potentially assisted the population expansion of T. officinale.

Objectives People with stroke sit for long periods each day, which may compromise blood glucose control and increase risk of recurrent stroke. Studies in other populations have found regular activity breaks have a significant immediate (within-day) positive effect on glucose metabolism. We examined the effects of breaking up uninterrupted sitting with frequent, short bouts of light-intensity physical activity in people with stroke on post-prandial plasma glucose and insulin. Methods Randomized within-participant crossover trial. We included people between 3 months and 10 years post-stroke, ambulant with minimal assistance and not taking diabetic medication other than metformin. The three experimental conditions (completed in random order) were: sitting for 8 h uninterrupted, sitting with 3 min bouts of light-intensity exercise while standing every 30 min, or sitting with 3 min of walking every 30 min. Meals were standardized and bloods were collected half- to one-hourly via an intravenous cannula. Results A total of 19 participants (9 female, mean [SD] age 68.2 [10.2]) completed the trial. The majority ( n = 12, 63%) had mild stroke symptoms (National Institutes of Stroke Scale score 0-13). There was no significant effect of experimental condition on glucose (mean [SD] positive incremental area [+iAUC] mmol·L·h-1 under the curve during sitting 42.3 [29.5], standing 47.4 [23.1], walking 44.6 [26.5], p = 0.563) or insulin (mean + iAUC pmol·L·h-1 sitting 14,161 [7,560], standing 14,043 [8,312], walking 14,008 [8,269], p = 0.987). Conclusion Frequent, short bouts of light-intensity physical activity did not have a significant effect on post-prandial plasma glucose and insulin in this sample of people with stroke. Further studies are needed to identify strategies that improve inactivity-related glucose metabolism after stroke.

AGuIX® are sub-5 nm nanoparticles made of a polysiloxane matrix and gadolinium chelates. This nanoparticle has been recently accepted in clinical trials in association with radiotherapy. This review will summarize the principal preclinical results that have led to first in man administration. No evidence of toxicity has been observed during regulatory toxicity tests on two animal species (rodents and monkeys). Biodistributions on different animal models have shown passive uptake in tumours due to enhanced permeability and retention effect combined with renal elimination of the nanoparticles after intravenous administration. High radiosensitizing effect has been observed with different types of irradiations in vitro and in vivo on a large number of cancer types (brain, lung, melanoma, head and neck…). The review concludes with the second generation of AGuIX nanoparticles and the first preliminary results on human.

In past decades, rapid progress in nanoparticle (NP) synthesis and engineering has provided a broad range of nanoscale agents affording both therapeutic and diagnostic functions. More recently, the emergence of biomimetic NPs as an efficient and promising technology has further expanded this field. The employment of biomemetic NPs offers many distinct advantages, including enhanced stability, the solubilization of hydrophobic payloads, extended blood residence times and the ability to better target a region of interest. In this review, we focus on two main categories of biomimetic NPs, protein/peptide-templated biomimetic NPs and cell membrane-derived biomimetic NPs. The properties, applications and challenges of these biomimetic NPs in tumor diagnosis and treatment are discussed. The pros and cons, and future development, of biomimetic NPs are also considered.

Understanding interactions between functional nanoparticles and lipid bilayers is important to many emerging biomedical and bioanalytical applications. In this paper, we report incorporation of hydrophobic cadmium sulphide quantum dots (CdS QDs) into mixed 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC)/1-palmitoyl-2-oleoyl-sn-glycero-3-phosphoethanolamine (POPE) liposomes, and into their supported bilayers (SLBs). The QDs were found embedded in the hydrophobic regions of the liposomes and the supported bilayers, which retained the QD fluorescent properties. In particular, we studied the effect of the QD size (2.7-5.4 nm in diameter) on the formation kinetics and structure of the supported POPC/POPE bilayers, monitored in situ using quartz crystal microbalance with dissipation monitoring (QCM-D), as the liposomes ruptured onto the substrate. The morphology of the obtained QD-lipid hybrid bilayers was studied using atomic force microscopy (AFM), and their structure by synchrotron X-ray reflectivity (XRR). It was shown that the incorporation of hydrophobic QDs promoted bilayer formation on the PEI cushion, evident from the rupture and fusion of the QD-endowed liposomes at a lower surface coverage compared to the liposomes without QDs. Furthermore, the degree of disruption in the supported bilayer structure caused by the QDs was found to be correlated with the QD size. Our results provide mechanistic insights into the kinetics of the rupturing and formation process of QD-endowed supported lipid bilayers via liposome fusion on polymer cushions.