Systematic evaluation of particle loss during handling in the percutaneous transluminal angioplasty for eight different drug-coated balloons

Paclitaxel drug coated balloons (DCBs) should provide optimal drug transfer exclusively to the target tissue. The aim of this study was to evaluate the particle loss by handling during angioplasty. A robotic arm was developed for systematic and reproducible drug abrasion experiments. The contact force on eight different commercially available DCB types was gradually increased, and high-resolution microscopic images of the deflated and inflated balloons were recorded. Three types of DCBs were classified: no abrasion of the drug in both statuses (deflated and inflated), significant abrasion only in the inflated status, and significant abrasion in both statuses. Quantitative measurements via image processing confirmed the qualitative classification and showed changes of the drug area between 2.25 and 45.73% (13.28 ± 14.29%) in the deflated status, and between 1.66 and 40.41% (21.43 ± 16.48%) in the inflated status. The structures and compositions of the DCBs are different, some are significantly more susceptible to drug loss. Particle loss by handling during angioplasty leads to different paclitaxel doses in the target regions for same DCB types. Susceptibility to involuntary drug loss may cause side effects, such as varying effective paclitaxel doses, which may explain variations in studies regarding the therapeutic outcome

Simulation and experiment of gas diffusion in a granular bed

The diffusion of gas through porous material is important to understand the physical processes underlying cometary activity. We study the diffusion of a rarefied gas (Knudsen regime) through a packed bed of monodisperse spheres via experiments and numerical modelling, providing an absolute value of the diffusion coefficient and compare it to published analytical models. The experiments are designed to be directly comparable to numerical simulations, by using precision steel beads, simple geometries, and a trade-off of the sample size between small boundary effects and efficient computation. For direct comparison, the diffusion coefficient is determined in Direct Simulation Monte Carlo (DSMC) simulations, yielding a good match with experiments. This model is further-on used on a microscopic scale, which cannot be studied in experiments, to determine the mean path of gas molecules and its distribution, and compare it against an analytical model. Scaling with sample properties (particle size, porosity) and gas properties (molecular mass, temperature) is consistent with analytical models. As predicted by these, results are very sensitive on sample porosity and we find that a tortuosity $q(\varepsilon)$ depending linearly on the porosity $\varepsilon$ can well reconcile the analytical model with experiments and simulations. Mean paths of molecules are close to those described in the literature, but their distribution deviates from the expectation for small path lengths. The provided diffusion coefficients and scaling laws are directly applicable to thermophysical models of idealised cometary material.Comment: accepted by MNRA

Amount of substance and the mole in the SI

Abstract Following the revision of the International System of Units (SI), that takes effect on 20 May 2019, the unit mole is defined by using a fixed number of elementary entities. This number is the fixed numerical value of the Avogadro constant, which is the defining constant of the unit mole. This definition was made possible because the determination of the Avogadro constant had reached a level of relative uncertainty that allowed its value to be fixed and, at the same time, safeguard continuity of measurement results before and after the definition. The motivation for the revision of the SI and the mole in particular will be explained and the experimental work that allowed it is summarized

Tribological performance and tribochemical processes in a DLC/steel system when lubricated in a fully formulated oil and base oil

Diamond-like carbon (DLC) coatings show extremely good promise for a number of applications in automotive components as they exhibit excellent tribological properties such as low friction and good wear resistance. This can impact on improved fuel economy and durability of the engine components. Much work has been reported on the dry sliding of DLC coatings with less so in lubricated contacts and, as such, there is a need to further understand the tribochemistry of lubricated DLC contacts. Commercially-available oils are normally optimised to work on ferrous surfaces. Previous studies on DLC lubricated contacts have tended to use model oil systems rather than fully formulated lubricants and from this an interesting picture of lubrication mechanisms is emerging. Optimising compatibility between a surface and a set of lubricant additives may lead to excellent durability (wear) as well as increased fuel economy (low friction). In this work, the friction and wear properties of a DLC coating under boundary lubrication conditions have been investigated and the tribological performance compared with that of an uncoated steel system. A pin-on-plate tribotester was used to run the experiments using High speed steel (HSS) M2 grade plates coated with 15 at.% hydrogenated DLC (a-C:15H) sliding against cast iron pins. A Group III mineral base oil, fully synthetic Group IV PAO and four different fully formulated oils were used in this study. Furthermore optical and scanning electron microscopes (SEM) were used to observe the wear scar and to assess the durability of the coatings. Energy-Dispersive X-ray analysis (EDX), X-ray Photoelectron Spectroscopy (XPS) and Raman spectroscopy analyses were performed on the tribofilms to understand the tribochemical interactions between oil additives and the a-C:15H coating. This study show that the durability of the a-C:15H coating strongly depends on the selected additive package in the oils. In addition the effect of detergent, dispersant and antioxidants on the performance of the molybdenum-based friction modifier (Mo-FM) and ZDDP anti-wear additive was investigated and results are reported in this paper

Coagulation and Fragmentation in molecular clouds. II. The opacity of the dust aggregate size distribution

The dust size distribution in molecular clouds can be strongly affected by ice-mantle formation and (subsequent) grain coagulation. Following previous work where the dust size distribution has been calculated from a state-of-the art collision model for dust aggregates that involves both coagulation and fragmentation (Paper I), the corresponding opacities are presented in this study. The opacities are calculated by applying the effective medium theory assuming that the dust aggregates are a mix of 0.1{\mu}m silicate and graphite grains and vacuum. In particular, we explore how the coagulation affects the near-IR opacities and the opacity in the 9.7{\mu}m silicate feature. We find that as dust aggregates grow to {\mu}m-sizes both the near-IR color excess and the opacity in the 9.7 {\mu}m feature increases. Despite their coagulation, porous aggregates help to prolong the presence of the 9.7{\mu}m feature. We find that the ratio between the opacity in the silicate feature and the near-IR color excess becomes lower with respect to the ISM, in accordance with many observations of dark clouds. However, this trend is primarily a result of ice mantle formation and the mixed material composition of the aggregates, rather than being driven by coagulation. With stronger growth, when most of the dust mass resides in particles of size 10{\mu}m or larger, both the near-IR color excess and the 9.7{\mu}m silicate feature significantly diminish. Observations at additional wavelengths, in particular in the sub-mm range, are essential to provide quantitative constraints on the dust size distribution within dense cores. Our results indicate that the sub-mm index {\beta} will increase appreciably, if aggregates grow to ~100{\mu}m in size.Comment: 10 pages, accepted for publication in A&

Using mixed objects in the training of object-based image classifications

Image classification for thematic mapping is a very common application in remote sensing, which is sometimes realized through object-based image analysis. In these analyses, it is common for some of the objects to be mixed in their class composition and thus violate the commonly made assumption of object purity that is implicit in a conventional object-based image analysis. Mixed objects can be a problem throughout a classification analysis, but are particularly challenging in the training stage as they can result in degraded training statistics and act to reduce mapping accuracy. In this paper the potential of using mixed objects in training object-based image classifications is evaluated. Remotely sensed data were submitted to a series of segmentation analyses from which a range of under- to over-segmented outputs were intentionally produced. Training objects were then selected from the segmentation outputs, resulting in training data sets that varied in terms of size (i.e. number of objects) and proportion of mixed objects. These training data sets were then used with an artificial neural network and a generalized linear model, which can accommodate objects of mixed composition, to produce a series of land cover maps. The use of training statistics estimated based on both pure and mixed objects often increased classification accuracy by around 25% when compared with accuracies obtained from the use of only pure objects in training. So rather than the mixed objects being a problem, they can be an asset in classification and facilitate land cover mapping from remote sensing. It is, therefore, desirable to recognize the nature of the objects and possibly accommodate mixed objects directly in training. The results obtained here may also have implications for the common practice of seeking an optimal segmentation output, and also act to challenge the widespread view that object-based classification is superior to pixel-based classification

Interpretable surface-based detection of focal cortical dysplasias:a Multi-centre Epilepsy Lesion Detection study

One outstanding challenge for machine learning in diagnostic biomedical imaging is algorithm interpretability. A key application is the identification of subtle epileptogenic focal cortical dysplasias (FCDs) from structural MRI. FCDs are difficult to visualize on structural MRI but are often amenable to surgical resection. We aimed to develop an open-source, interpretable, surface-based machine-learning algorithm to automatically identify FCDs on heterogeneous structural MRI data from epilepsy surgery centres worldwide. The Multi-centre Epilepsy Lesion Detection (MELD) Project collated and harmonized a retrospective MRI cohort of 1015 participants, 618 patients with focal FCD-related epilepsy and 397 controls, from 22 epilepsy centres worldwide. We created a neural network for FCD detection based on 33 surface-based features. The network was trained and cross-validated on 50% of the total cohort and tested on the remaining 50% as well as on 2 independent test sites. Multidimensional feature analysis and integrated gradient saliencies were used to interrogate network performance. Our pipeline outputs individual patient reports, which identify the location of predicted lesions, alongside their imaging features and relative saliency to the classifier. On a restricted 'gold-standard' subcohort of seizure-free patients with FCD type IIB who had T1 and fluid-attenuated inversion recovery MRI data, the MELD FCD surface-based algorithm had a sensitivity of 85%. Across the entire withheld test cohort the sensitivity was 59% and specificity was 54%. After including a border zone around lesions, to account for uncertainty around the borders of manually delineated lesion masks, the sensitivity was 67%. This multicentre, multinational study with open access protocols and code has developed a robust and interpretable machine-learning algorithm for automated detection of focal cortical dysplasias, giving physicians greater confidence in the identification of subtle MRI lesions in individuals with epilepsy

The search campaign to identify and Image the Philae Lander on the surface of comet 67P/Churyumov-Gerasimenko

On the 12th of November 2014, the Rosetta Philae Lander descended to make the first soft touchdown on the surface of a comet – comet 67P/Churyumov- Gerasimenko. That soft touchdown did occur but due to the failure in the firing of its two harpoons, Philae bounced and travelled across the comet making contact with the surface twice more before finally landing in a shaded rocky location somewhere on the southern hemisphere of the comet. The search campaign, led by ESA, involved multiple teams across Europe with a wide range of techniques used in support of it. This search campaign would continue through 2015 where a prime candidate on the surface was identified and on into 2016 to end on the 2nd of September 2016 when a definitive and conclusive image was taken of the lander on the surface of the comet, confirming the prime candidate to indeed be Philae

Reporting in a Payload Data Ground Segment

This paper describes the concept and implementation of the DIMS Reporting Control (RC) for the multi-mission PDGS environment. The tool compiles reports based on data collected from multiple components. It generates ad-hoc and scheduled reports and employs statistical analyses to depict the current system state or its evolution over time. This paper introduces DIMS reporting requirements, followed by a discussion on how these drive design decisions. Then involved interfaces and tools are presented. Next the proposed system is compared to existing solutions. The publication concludes with an evaluation of the DIMS Reporting Control implementation from the perspectives of usability and performance

Placental CX3CL1 is Deregulated by Angiotensin II and Contributes to a Pro-Inflammatory Trophoblast-Monocyte Interaction

CX3CL1, which is a chemokine involved in many aspects of human pregnancy, is a membrane-bound chemokine shed into circulation as a soluble isoform. Placental CX3CL1 is induced by inflammatory cytokines and is upregulated in severe early-onset preeclampsia. In this study, the hypothesis was addressed whether angiotensin II can deregulate placental CX3CL1 expression, and whether CX3CL1 can promote a pro-inflammatory status of monocytes. qPCR analysis of human placenta samples (n = 45) showed stable expression of CX3CL1 and the angiotensin II receptor AGTR1 throughout the first trimester, but did not show a correlation between both or any influence of maternal age, BMI, and gestational age. Angiotensin II incubation of placental explants transiently deregulated CX3CL1 expression, while the angiotensin II receptor antagonist candesartan reversed this effect. Overexpression of recombinant human CX3CL1 in SGHPL-4 trophoblasts increased adhesion of THP-1 monocytes and significantly increased IL8, CCL19, and CCL13 in co-cultures with human primary monocytes. Incubation of primary monocytes with CX3CL1 and subsequent global transcriptome analysis of CD16+ subsets revealed 81 upregulated genes, including clusterin, lipocalin-2, and the leptin receptor. Aldosterone synthase, osteopontin, and cortisone reductase were some of the 66 downregulated genes present. These data suggest that maternal angiotensin II levels influence placental CX3CL1 expression, which, in turn, can affect monocyte to trophoblast adhesion. Release of placental CX3CL1 could promote the pro-inflammatory status of the CD16+ subset of maternal monocytes