skip to main content

Search for: All records

Creators/Authors contains: "Zheng, Jie"

Note: When clicking on a Digital Object Identifier (DOI) number, you will be taken to an external site maintained by the publisher. Some full text articles may not yet be available without a charge during the embargo (administrative interval).
What is a DOI Number?

Some links on this page may take you to non-federal websites. Their policies may differ from this site.

  1. Abstract

    The development and understanding of antifreezing hydrogels are crucial both in principle and practice for the design and delivery of new materials. The current antifreezing mechanisms in hydrogels are almost exclusively derived from their incorporation of antifreezing additives, rather than from the inherent properties of the polymers themselves. Moreover, developing a computational model for the independent yet interconnected double-network (DN) structures in hydrogels has proven to be an exceptionally difficult task. Here, we develop a multiscale simulation platform, integrating ‘random walk reactive polymerization’ (RWRP) with molecular dynamics (MD) simulations, to computationally construct a physically-chemically linked PVA/PHEAA DN hydrogels from monomers that mimic a radical polymerization and to investigate water structures, dynamics, and interactions confined in PVA/PHEAA hydrogels with various water contents and temperatures, aiming to uncover antifreezing mechanism at atomic levels. Collective simulation results indicate that the antifreezing property of PVA/PHEAA hydrogels arises from a combination of intrinsic, strong water-binding networks and crosslinkers and tightly crosslinked and interpenetrating double-network structures, both of which enhance polymer-water interactions for competitively inhibiting ice nucleation and growth. These computational findings provide atomic-level insights into the interplay between polymers and water molecules in hydrogels, which may determine their resistance to freezing.

    more » « less
  2. Abstract

    Quantitative magnetic resonance imaging (qMRI) measures have provided insights into the composition, quality, and structure‐function of musculoskeletal tissues. Low signal‐to‐noise ratio has limited application to tendon. Advances in scanning sequences and sample positioning have improved signal from tendon allowing for evaluation of structure and function. The purpose of this study was to elucidate relationships between tendon qMRI metrics (T1, T2, T1ρ and diffusion tensor imaging [DTI] metrics) with tendon tissue mechanics, collagen concentration and organization. Sixteen human Achilles tendon specimens were collected, imaged with qMRI, and subjected to mechanical testing with quantitative polarized light imaging. T2 values were related to tendon mechanics [peak stress (rsp = 0.51,p = 0.044), equilibrium stress (rsp = 0.54,p = 0.033), percent relaxation (rsp = −0.55,p = 0.027), hysteresis (rsp = −0.64,p = 0.007), linear modulus (rsp = 0.67,p = 0.009)]. T1ρ had a statistically significant relationship with percent relaxation (r = 0.50,p = 0.048). Collagen content was significantly related to DTI measures (range ofr = 0.56–0.62). T2 values from a single slice of the midportion of human Achilles tendons were strongest predictors of tendon tensile mechanical metrics. DTI diffusivity indices (mean diffusivity, axial diffusivity, radial diffusivity) were strongly correlated with collagen content. These findings build on a growing body of literature supporting the feasibility of qMRI to characterize tendon tissue and noninvasively measure tendon structure and function. Statement of Clinical Significance: Quantitative MRI can be applied to characterize tendon tissue and is a noninvasive measure that relates to tendon composition and mechanical behavior.

    more » « less
    Free, publicly-accessible full text available October 1, 2024
  3. Free, publicly-accessible full text available June 1, 2024
  4. Amyloid formation and microbial infection are the two common pathological causes of neurogenerative diseases, including Alzheimer's disease (AD), type II diabetes (T2D), and medullary thyroid carcinoma (MTC). While significant efforts have been made to develop different prevention strategies and preclinical hits for these diseases, conventional design strategies of amyloid inhibitors are mostly limited to either a single prevention mechanism (amyloid cascade vs. microbial infection) or a single amyloid protein (Aβ, hIAPP, or hCT), which has prevented the launch of any successful drug on the market. Here, we propose and demonstrate a new “anti-amyloid and anti-bacteria” strategy to repurpose two intestinal defensins, human α-defensin 6 (HD-6) and human β-defensin 1 (HBD-1), as multiple-target, dual-function, amyloid inhibitors. Both HD-6 and HBD-1 can cross-seed with three amyloid peptides, Aβ (associated with AD), hIAPP (associated with T2D), and hCT (associated with MTC), to prevent their aggregation towards amyloid fibrils from monomers and oligomers, rescue SH-SY5Y and RIN-m5F cells from amyloid-induced cytotoxicity, and retain their original antimicrobial activity against four common bacterial strains at sub-stoichiometric concentrations. Such sequence-independent anti-amyloid and anti-bacterial functions of intestinal defensins mainly stem from their cross-interactions with amyloid proteins through amyloid-like mimicry of β-sheet associations. In a broader view, this work provides a new out-of-the-box thinking to search and repurpose a huge source of antimicrobial peptides as amyloid inhibitors, allowing the blocking of the two interlinked pathological pathways and bidirectional communication between the central nervous system and intestines via the gut–brain axis associated with neurodegenerative diseases. 
    more » « less