Insights into the role of nucleotide methylation in metabolic-associated fatty liver disease

Metabolic-associated fatty liver disease (MAFLD) is a chronic liver disease characterized by fatty infiltration of the liver. In recent years, the MAFLD incidence rate has risen and emerged as a serious public health concern. MAFLD typically progresses from the initial hepatocyte steatosis to steatohepatitis and then gradually advances to liver fibrosis, which may ultimately lead to cirrhosis and carcinogenesis. However, the potential evolutionary mechanisms still need to be clarified. Recent studies have shown that nucleotide methylation, which was directly associated with MAFLD’s inflammatory grading, lipid synthesis, and oxidative stress, plays a crucial role in the occurrence and progression of MAFLD. In this review, we highlight the regulatory function and associated mechanisms of nucleotide methylation modification in the progress of MAFLD, with a particular emphasis on its regulatory role in the inflammation of MAFLD, including the regulation of inflammation-related immune and metabolic microenvironment. Additionally, we summarize the potential value of nucleotide methylation in the diagnosis and treatment of MAFLD, intending to provide references for the future investigation of MAFLD

Complex 3D microfluidic architectures formed by mechanically guided compressive buckling.

Microfluidic technologies have wide-ranging applications in chemical analysis systems, drug delivery platforms, and artificial vascular networks. This latter area is particularly relevant to 3D cell cultures, engineered tissues, and artificial organs, where volumetric capabilities in fluid distribution are essential. Existing schemes for fabricating 3D microfluidic structures are constrained in realizing desired layout designs, producing physiologically relevant microvascular structures, and/or integrating active electronic/optoelectronic/microelectromechanical components for sensing and actuation. This paper presents a guided assembly approach that bypasses these limitations to yield complex 3D microvascular structures from 2D precursors that exploit the full sophistication of 2D fabrication methods. The capabilities extend to feature sizes <5 μm, in extended arrays and with various embedded sensors and actuators, across wide ranges of overall dimensions, in a parallel, high-throughput process. Examples include 3D microvascular networks with sophisticated layouts, deterministically designed and constructed to expand the geometries and operating features of artificial vascular networks

Activation of conductive pathways via deformation-induced instabilities

Thesis: S.M., Massachusetts Institute of Technology, Department of Mechanical Engineering, 2014."June 2014." Cataloged from PDF version of thesis.Includes bibliographical references.Inspired by the pattern transformation of periodic elastomeric cellular structures, the purpose of this work is to exploit this unique ability to activate conductive via deformation-induced instabilities. Two microstructural features, the contact nub and the conductive pathway, are introduced to make connections within the void and between the voids upon pattern transformation. Finite element-based micromechanical models are employed to investigate the effects of the contact nub geometries, conductive pathway patterns and elastic properties of the coating and substrate materials on the buckling responses of the structure. Finally, a flexible circuit that can be switched on and off by an applied uniaxial load is fabricated based on the finite element analysis and demonstrated the ability to activate conductive pathways in response to an external triggering stimulus.by Xinchen Ni.S.M

Nanoengineered hierarchical advanced composites with nanofiber interlaminar reinforcement for enhanced laminate-level mechanical performance

Thesis: Ph. D., Massachusetts Institute of Technology, Department of Mechanical Engineering, 2020Cataloged from PDF of thesis.Includes bibliographical references (pages 157-177).At present, there is a need for novel, scalable, and high-performance structural materials that offer unprecedented combinations of stiffness, strength, and toughness at a low density, which can serve in a variety of applications in the aerospace, transportation, defense, and energy industries. To date, composite materials, specifically advanced carbon fiber reinforced plastics (CFRPs), which are comprised of high specific stiffness and strength continuous carbon microfibers and lightweight, relatively compliant polymers, have been among the most attractive materials and are used extensively in the aerospace sector. However, most CFRPs are fabricated by stacking plies in a layer-by-layer fashion, resulting in a weak polymer-rich region, known as the interlaminar region, at each ply interface that leads to poor properties through the laminate thickness.Although the mechanically superior microfibers are designed to be the primary load carriers, the much weaker polymer matrix causes the laminates to be prone to premature failure with interlaminar delamination, which negatively affects both in-plane and out-of-plane performance. This key shortcoming is known as the Achilles' heel of CFRPs, which hinders their design and wider adoption in critical structural applications. In this dissertation, a novel nanoengineering approach to address the longstanding problem of weak ply interfaces of CFRPs is developed and demonstrated. High densities (>10 billion nanofibers per cm²) of uniformly-distributed vertically aligned carbon nanotubes (A-CNTs) are placed between neighboring plies to bridge the weak polymer-rich interlaminar region in existing prepreg-based laminated composites, creating a hierarchical architecture termed "nanostitch".The effectiveness of nanostitching is evaluated via various mechanical tests including short-beam shear (SBS), Mode I and II fracture, and double edge-notched tension (DENT), in all of which the nanostitched composites have demonstrated enhanced mechanical performance. Furthermore, the multiscale reinforcement mechanisms resulting from the CNTs are elucidated via a variety of ex situ and in situ damage inspection techniques, including optical microscopy, scanning electron microscopy, lab-based micro-computed tomography, and in situ synchrotron radiation computed tomography (SRCT). Specifically, in SBS, despite no increase in static strength, a 115% average increase in fatigue life across all load levels (60 to 90% of static strength), with a larger increase of 249% in high-cycle (at 60% of static strength) fatigue, is observed.In Mode I and Mode II fracture, it is revealed that the interlaminar crack bifurcates into the intralaminar region from the interlaminar precrack, and then propagates within the intralaminar region parallel to the nanostitched interlaminar region as an "intralaminar delamination" in steady state. This unique crack bifurcation phenomenon has never been previously observed and is attributed to the A-CNTs adding interlaminar toughness to a level that causes the interlaminar crack to bifurcate into the less tough intralaminar region. In DENT, an 8% increase in ultimate tensile strength (UTS) is observed and is attributed to the A-CNTs suppressing critical interlaminar delaminations very close to final failure (greater than 90% UTS) via in situ SRCT.In addition to the positive reinforcement results observed for the nanostitched composites, a next-generation higher volume fraction nanostitched composite with additional levels of beneficial hierarchy termed "buckled nanostitch" or "nanostitch 2.0" is created by exploiting the unique buckling behavior displayed by patterned A-CNT forests under compression. This multilevel hierarchical architecture further enhances the composite mechanical performance: SBS strength by 7% and DENT strength by 28%, compared to the baseline composites. The dissertation not only presents a controllable, scalable manufacturing method to produce engineered structural materials that are hierarchically designed down to the nanoscale with enhanced mechanical performance, but it also establishes key new understanding of the complex and coupled strengthening and toughening mechanisms acting at different scales, as well as their effects on macroscopic laminate-level mechanical properties.A particular focus has been the seminal use of in situ SRCT to study the effects of the hierarchical nanoscale reinforcements, and thus the methods established provide an experimental path forward for future work in this area. Together, these advances open up new opportunities for creating next-generation engineered materials with a suite of programmable properties by controlling their structures and constituents across multiple length scales.by Xinchen Ni.Ph. D.Ph.D. Massachusetts Institute of Technology, Department of Mechanical Engineerin

Aerospace-grade Advanced Composites with Buckling-densified Aligned Carbon Nanotubes Interlaminar Reinforcement

© 2020, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved. Aligned carbon nanotube (A-CNT) arrays that were densified via patterning and mechanical instability are placed at the resin-rich ply-ply interface in aerospace-grade advanced composite laminates for z-direction reinforcement. The buckled A-CNT arrays display a wavelike folding shape and maintain such a shape after being transferred between the plies. The buckled A-CNT reinforced laminates were tested under short-beam shear (SBS) and double edge-notched tension (DENT) and are found to have a 7% increase in SBS strength and 25% increase in DENT strength, respectively. Both scanning electron microscope imaging and micro-computed tomography reveal that the buckled A-CNT arrays suppress delamination and force damage into the intralaminar region. Furthermore, they introduce multiscale and mixed mode reinforcement mechanisms. The findings demonstrate good potential for using mechanical instability in nanofiber arrays to densify them and tune their shapes, as well as the promising reinforcement effect from buckling-densified A-CNT arrays. Future work to change the pattern (e.g., patterning feature shape and interspacing between features), as well as synchrotron radiation computed tomography-based in situ testing is planned

Deep Learning Unlocks X‐ray Microtomography Segmentation of Multiclass Microdamage in Heterogeneous Materials

Four-dimensional quantitative characterization of heterogeneous materials using in situ synchrotron radiation computed tomography can reveal 3D sub-micrometer features, particularly damage, evolving under load, leading to improved materials. However, dataset size and complexity increasingly require time-intensive and subjective semi-automatic segmentations. Here, the first deep learning (DL) convolutional neural network (CNN) segmentation of multiclass microscale damage in heterogeneous bulk materials is presented, teaching on advanced aerospace-grade composite damage using ≈65 000 (trained) human-segmented tomograms. The trained CNN machine segments complex and sparse (<<1% of volume) composite damage classes to ≈99.99% agreement, unlocking both objectivity and efficiency, with nearly 100% of the human time eliminated, which traditional rule-based algorithms do not approach. The trained machine is found to perform as well or better than the human due to "machine-discovered" human segmentation error, with machine improvements manifesting primarily as new damage discovery and segmentation augmentation/extension in artifact-rich tomograms. Interrogating a high-level network hyperparametric space on two material configurations, DL is found to be a disruptive approach to quantitative structure-property characterization, enabling high-throughput knowledge creation (accelerated by two orders of magnitude) via generalizable, ultrahigh-resolution feature segmentation