Using Ion Mobility-Mass Spectrometry to Understand Amyloid β-Protein Assembly: The Effects of Small Molecule Inhibitors and Familial Mutations

Amyloid β-protein (Aβ) has been correlated with Alzheimer’s disease (AD) which is the most common form of dementia. Aβ proteins assemble into oligomers, large aggregates, protofibrils before growing into fibrils. Recently more and more evidence has shown that the intermediate, oligomeric states of Aβ, rather than the fibrils are correlated with AD pathology. Among them, the 56 kDa dodecamer species was identified as a proximate toxic agent for AD onset. Therefore to understand the early oligomerization of Aβ proteins and to target the early assembly of Aβ are of significance for therapeutic strategy for AD treatment. In this thesis work, we use mass spectrometry coupled with ion mobility spectrometry method (IM-MS) to investigate the early assembly of Aβ proteins. In the first, we sought to search for small molecule inhibitors for Aβ and understand their binding interactions and the mechanism of inhibitory actions. Several classes of small molecules, including Z-Phe-Ala-diazomethylketone (PADK), two derivatives of the Aβ C-terminal fragment Aβ(39-42), molecular tweezers, and ML, have been studied and shown different effects. These studies of small molecule inhibitors show that ion mobility spectrometry method has emerged to be a powerful tool for the screening and understanding of small molecule inhibitors for AD and other amyloid diseases. In the second, we sought to understand the effects of amino acid substitutions on Aβ structure and aggregation. Two recently discovered familial mutations at Ala2 (A2) within Aβ, a protective A2T mutation and a recessive A2V mutation were investigated. Our ion mobility studies reveal different assembly pathways for early oligomer formation for each peptide and provide a basis for understanding how these two mutations lead to, or protect against, AD. Lastly, we also sought to understand the early assembly of amyloid β-protein (Aβ) from different rodent species. We investigate the biophysical and biological properties of Aβ peptides from humans, mice (Mus musculus), and rats (Octodon degus). In conclusion, we have successfully applied ion mobility spectrometry method to understand complicated aggregation systems. This provides a powerful tool to screen small molecule inhibitors for Aβ proteins and sheds light onto their inhibitory mechanisms. The studies of Aβ mutants imply that ion mobility method can be used as new tool in developing an understanding of the effect of familial mutations on Aβ assembly in AD and the assembly of other mutated protein systems

Surface decoration by Spirulina polysaccharide enhances the cellular uptake and anticancer efficacy of selenium nanoparticles

A simple and solution-phase method for functionalization of selenium nanoparticles (SeNPs) with Spirulina polysaccharides (SPS) has been developed in the present study. The cellular uptake and anticancer activity of SPS-SeNPs were also evaluated. Monodisperse and homogeneous spherical SPS-SeNPs with diameters ranging from 20 nm to 50 nm were achieved under optimized conditions, which were stable in the solution phase for at least 3 months. SPS surface decoration significantly enhanced the cellular uptake and cytotoxicity of SeNPs toward several human cancer cell lines. A375 human melanoma cells were found extremely susceptible to SPS-SeNPs with half maximal (50%) inhibitory concentration value of 7.94 μM. Investigation of the underlying mechanisms revealed that SPS-SeNPs inhibited cancer cell growth through induction of apoptosis, as evidenced by an increase in sub-G1 cell population, deoxyribonucleic acid fragmentation, chromatin condensation, and phosphatidylserine translocation. Results suggest that the strategy to use SPS as a surface decorator could be an effective way to enhance the cellular uptake and anticancer efficacy of nanomaterials. SPS-SeNPs may be a potential candidate for further evaluation as a chemopreventive and chemotherapeutic agent against human cancers

Inhibition of Osteoclastogenesis and Bone Resorption in vitro and in vivo by a prenylflavonoid xanthohumol from hops

Excessive RANKL signaling leads to superfluous osteoclast formation and bone resorption, is widespread in the pathologic bone loss and destruction. Therefore, targeting RANKL or its signaling pathway has been a promising and successful strategy for this osteoclast-related diseases. In this study, we examined the effects of xanthohumol (XN), an abundant prenylflavonoid from hops plant, on osteoclastogenesis, osteoclast resorption, and RANKL-induced signaling pathway using both in vitro and in vivo assay systems. In mouse and human, XN inhibited osteoclast differentiation and osteoclast formation at the early stage. Furthermore, XN inhibited osteoclast actin-ring formation and bone resorption in a dose-dependent manner. In ovariectomized-induced bone loss mouse model and RANKL-injection-induced bone resorption model, we found that administration of XN markedly inhibited bone loss and resorption by suppressing osteoclast activity. At the molecular level, XN disrupted the association of RANK and TRAF6, resulted in the inhibition of NF-κB and Ca(2+)/NFATc1 signaling pathway during osteoclastogenesis. As a results, XN suppressed the expression of osteoclastogenesis-related marker genes, including CtsK, Nfatc1, Trap, Ctr. Therefore, our data demonstrated that XN inhibits osteoclastogenesis and bone resorption through RANK/TRAF6 signaling pathways. XN could be a promising drug candidate in the treatment of osteoclast-related diseases such as postmenopausal osteoporosis

Epidemiology and clinical course of COVID-19 in Shanghai, China.

Background: Novel coronavirus pneumonia (COVID-19) is prevalent around the world. We aimed to describe epidemiological features and clinical course in Shanghai. Methods: We retrospectively analysed 325 cases admitted at Shanghai Public Health Clinical Center, between January 20 and February 29, 2020. Results: 47.4% (154/325) had visited Wuhan within 2 weeks of illness onset. 57.2% occurred in 67 clusters; 40% were situated within 53 family clusters. 83.7% developed fever during the disease course. Median times from onset to first medical care, hospitalization and negative detection of nucleic acid by nasopharyngeal swab were 1, 4 and 8 days. Patients with mild disease using glucocorticoid tended to have longer viral shedding in blood and feces. At admission, 69.8% presented with lymphopenia and 38.8% had elevated D-dimers. Pneumonia was identified in 97.5% (314/322) of cases by chest CT scan. Severe-critical patients were 8% with a median time from onset to critical disease of 10.5 days. Half required oxygen therapy and 7.1% high-flow nasal oxygen. The case fatality rate was 0.92% with median time from onset to death of 16 days. Conclusion: COVID-19 cases in Shanghai were imported. Rapid identification, and effective control measures helped to contain the outbreak and prevent community transmission

Shoreline Extraction in SAR Image Based on Advanced Geometric Active Contour Model

Rapid and accurate extraction of shoreline is of great significance for the use and management of sea area. Remote sensing has a strong ability to obtain data and has obvious advantages in shoreline survey. Compared with visible-light remote sensing, synthetic aperture radar (SAR) has the characteristics of all-weather and all-day working. It has been well-applied in shoreline extraction. However, due to the influence of natural conditions there is a problem of weak boundary in extracting shoreline from SAR images. In addition, the complex micro topography near the shoreline makes it difficult for traditional visual interpretation and image edge detection methods based on edge information to obtain a continuous and complete shoreline in SAR images. In order to solve these problems, this paper proposes a method to detect the land–sea boundary based on a geometric active contour model. In this method, a new symbolic pressure function is used to improve the geometric active-contour model, and the global regional smooth information is used as the convergence condition of curve evolution. Then, the influence of different initial contours on the number and time of iterations is studied. The experimental results show that this method has the advantages of fewer iteration times, good stability and high accuracy