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Aerosols exhaled from the lungs have distinctive patterns that can be linked to the abnormalities of the lungs. Yet, due to their intricate nature, it is highly challenging to analyze and distinguish these aerosol patterns. Small airway diseases pose an even greater challenge, as the disturbance signals tend to be weak. The objective of this study was to evaluate the performance of four convolutional neural network (CNN) models (AlexNet, ResNet-50, MobileNet, and EfficientNet) in detecting and staging airway abnormalities in small airways using exhaled aerosol images. Specifically, the model's capacity to classify images inside and outside the original design space was assessed. In doing so, multi-level testing on images with decreasing similarities was conducted for each model. A total of 2745 images were generated using physiology-based simulations from normal and obstructed lungs of varying stages. Multiple-round training on datasets with increasing images (and new features) was also conducted to evaluate the benefits of continuous learning. Results show reasonably high classification accuracy on inbox images for models but significantly lower accuracy on outbox images (i.e., outside design space). ResNet-50 was the most robust among the four models for both diagnostic (2-class: normal vs. disease) and staging (3-class) purposes, as well as on both inbox and outbox test datasets. Variation in flow rate was observed to play a more important role in classification decisions than particle size and throat variation. Continuous learning/training with appropriate images could substantially enhance classification accuracy, even with a small number (~100) of new images. This study shows that CNN transfer-learning models could detect small airway remodeling (<1 mm) amidst a variety of variants and that ResNet-50 can be a promising model for the future development of obstructive lung diagnostic systems. [ABSTRACT FROM AUTHOR]

Previous studies on detonation of the Dihydroxylammonium 5,5′‐bistetrazole‐1,1′‐diolate (TKX‐50), an attractive energetic ionic salt (EIS), were mainly based on thermodynamic codes or small‐scale tests, the available experimental data are not adequate to fully understand detonation characteristics of this new kind of energetic material. This article gives an experimental investigation on detonation reaction zone (DRZ) and acceleration ability of a TKX‐50 based Polymer Bonded eXplosive (PBX), PBX‐TKX‐50. The detonation properties of two traditional explosives: (i)PBX‐HMX, an HMX‐based PBX, (ii) PBX‐RDX, an RDX‐based PBX, both of which contain the energetic compounds and binder in the same mass ratio as PBX‐TKX‐50, are also measured for a comparative analysis. The results show that PBX‐TKX‐50 has the highest detonation velocity and detonation pressure, nevertheless the slowest reaction rate within detonation reaction zone, the longest reaction time and DRZ length among the three PBX samples. Despite its prominent detonation velocity and detonation pressure, the acceleration ability of PBX‐TKX‐50 is lower than PBX‐RDX. The Jones‐Wilkins‐Lee (JWL) equation of state for detonation products calibrated by the cylinder expansion test has severely overestimated the axial acceleration ability of PBX‐TKX‐50 in the numerical simulation of Disc Acceleration eXperiment (DAX), which may due to the fact that remarkable confinement effect and/or geometry effect exist in detonation of the EIS based sample. The mechanisms behind these detonation behaviors are still under investigation in our ongoing studies. [ABSTRACT FROM AUTHOR]

When patients with chronic kidney disease receive hemodialysis, their protein-binding uremic toxins (PBUTs) accumulation rate in the blood is very high. One of the main representative substances is p-cresol sulfate (PCS). About 80% PCS integrates to the Sudlow site II of blood serum albumin through electrostatic interaction or van der Waals force. How to effectively remove PCS is very challenging. Here, we designed and prepared a kind of nanoremover for the removal of PCS. First, Fe3O4 nanoparticles were coated with a metal–organic framework (MOF) shell with abundant pores by an in situ one-step synthesis. Then, ibuprofen (IBU) was loaded into the pores to obtain a Fe3O4/MOF/IBU nanoremover with a core–shell structure. Finally, the nanoremover was applied to capture and remove PCS from blood; its removal mechanism and removal efficiency based on displacement were verified. Finally, the nanoremover was applied to remove uremic toxins such as PCS from blood, its removal mechanism and removal efficiency based on displacement were verified. The in vitro removal experimental results showed that the removal efficiency of the Fe3O4/MOF/IBU nanoremover was about 26.7% when the initial concentration of PCS in the blood was 100 ppm. In general, the magnetic nanoremover based on displacement technology provides the possibility of clinical application for the removal of PBUTs in blood. [ABSTRACT FROM AUTHOR]

ABSTRACT Poly(chloro- p-xylylene) (PPXC) films with a thickness range encompassing more than three orders of magnitude (from 102 nm to 102 μm) were prepared on Si substrates by the chemical vapor deposition method under the same conditions. The effect of the film thickness ( d) on the morphology, crystal structure, and crystal orientation behavior of the PPXC films was studied. The average roughness of the root mean square (rms) of the films increased with increasing d according to a power law (rms ≈ dβ, where β is an exponent that depends on the film growth process over time and β = 0.240±0.005, as probed by atomic force microscopy), and the monomer diffusion and relaxation of polymer were suggested as the primary factors governing this morphological evolution. The X-ray diffraction results indicate that both the crystallinity and crystal size of PPXC increased with increasing d due to the surface confinement effect between the film and the substrate, which retarded the crystallization process. The X-ray pole figures suggested that the (020) fiber textures with the b axis parallel to the Si substrate normal existed in the PPXC films; these fiber textures, mainly composed of edge-on crystal lamellae, were thermodynamically favored. The Herman's orientation factor of the fiber textures increased gradually as d grew; this indicated that stronger (020) fiber textures with higher concentrations of edge-on lamellae existed in the thicker PPXC films. This thickness dependence of the crystal orientation behavior was interpreted to be caused by the strong adhesion between the polymer chains and the substrate. © 2014 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2015, 132, 41394. [ABSTRACT FROM AUTHOR]

Thrombospondin 1 (TSP1) is a multifunctional matricellular protein. Recent studies demonstrate that TSP1 is highly expressed in adipose tissue (AT) and positively associated with AT inflammation and insulin resistance (IR). In this study, the contribution of different cellular sources of TSP1 to obesity-induced metabolic complications is determined by using mice with either adipocyte or myeloid/macrophage-specific deletion of TSP1 in a diet-induced obese model. The results demonstrated that neither adipocyte nor myeloid/macrophage-specific deletion of TSP1 affected the development of long-term high-fat diet-induced obesity. Adipocyte-specific deletion of TSP1 did not protect mice from obesity-induced inflammation and IR. On the contrary, obese mice with myeloid/macrophage loss of TSP1 had reduced macrophage accumulation in AT, which was accompanied with reduced inflammation and improved glucose tolerance and insulin sensitivity compared with obese control mice. Reduced macrophage-derived-TGF-β1 signaling and adipose tissue fibrosis were also observed in long-term high-fat-fed mice with myeloid/macrophage-specific TSP1 deletion. Moreover, in vitro experiments demonstrated an autocrine effect of TSP1-mediated TGF-β activation in macrophages in obesity. Collectively this study highlights the critical contribution of myeloid/macrophage-derived TSP1 to obesity-associated chronic inflammation and IR, which may serve as a new therapeutic target for metabolic disease.