Multifunctional mesoporous silica nanospheres for biosensor, stimuli-responsive controlled-release drug delivery carriers and gene transfection vectors

Structurally well-defined mesoporous silica materials with tunable pore size and narrow pore-size distribution have attracted much attention for their potential applications in sensing, drug delivery and gene transfer. A series of mesoporous silica nanosphere-based (MSN) nano-devices were synthesized and utilized for the aforementioned applications.;For sensing application, we provide a first example in utilization of a multi-functionalized mesoporous silica material to selectively detect dopamine. A second application, rooted in this work, is the selective detection of amino-containing neurotransmitters under physiological condition.;The drug delivery applications have been built around a controlled release drug delivery device. In the original conception, the system is using surface-derivatized cadmium sulfide (CdS) nanocrystals as chemically removable caps to encapsulate several drug molecules and neurotransmitters inside the organically functionalized MSN mesoporous framework. To study the cap-dependence release profile, adenosine 5-triphosphate (ATP) molecules were encapsulated in the MSNs followed by capping of the mesopores with chemically removable caps, such as CdS nanoparticles and poly(amido amine) dendrimers (PAMAM). A luciferase chemiluminescence imaging method was employed to investigate the kinetics and mechanism of the ATP release with various disulfide-reducing agents as uncapping triggers in real time. By varying the chemical nature of the cap and trigger molecules in our MSN system, we observed that the release profiles could be regulated.;Further, the PAMAM dendrimers of low generations were utilized as MSN caps for drug delivery. The biocompatibility and delivery efficiency of the later MSN system in interaction with HeLa cervical cancer cells were demonstrated. The system renders the possibility to serve as a universal transmembrane carrier for intracellular drug delivery and imaging applications. This is the first uptake study of MCM-41 type mesoporous silicas into eukaryotic cells.;The last application presented in the current dissertation is gene delivery. A MSN based gene transfection system was developed, where second generation (G2) PAMAMs were covalently attached to the surface of MSN. The G2-PAMAM-capped MSN material (G2-MSN) was able to complex with a plasmid DNA (pEGFP-C1). The gene transfection efficacy, uptake mechanism, and biocompatibility of the G2-MSN system with various cell types were investigated

Facilitated Release of Doxorubicin from Biodegradable Mesoporous Silica Nanoparticles

Cervical cancer is one of the most common causes of cancer death for women in the United States. The current treatment with chemotherapy drugs has significant side effects and may cause harm to healthy cells rather than cancer cells. In order to combat the potential side effects, nanoparticles composed of mesoporous silica were created to house the chemotherapy drug doxorubicin (DOX). The silica network contains the drug, and a pH study was conducted to determine the conditions for the nanoparticle to disperse the drug. The introduction of disulfide bonds within the nanoparticle created a framework to efficiently release 97% of DOX in acidic environments and 40% release in neutral environments. The denotation of acidic versus neutral environments was important as cancer cells are typically acidic. The chemistry was proved with the incubation of the loaded nanoparticle into HeLa cells for a cytotoxicity report and confocal imaging. The use of the framework for the anticancer drug was shown to be effective for the killing of cancerous cells

Spatiotemporal patterns and predictability of cyberattacks

A relatively unexplored issue in cybersecurity science and engineering is whether there exist intrinsic patterns of cyberattacks. Conventional wisdom favors absence of such patterns due to the overwhelming complexity of the modern cyberspace. Surprisingly, through a detailed analysis of an extensive data set that records the time-dependent frequencies of attacks over a relatively wide range of consecutive IP addresses, we successfully uncover intrinsic spatiotemporal patterns underlying cyberattacks, where the term "spatio" refers to the IP address space. In particular, we focus on analyzing {\em macroscopic} properties of the attack traffic flows and identify two main patterns with distinct spatiotemporal characteristics: deterministic and stochastic. Strikingly, there are very few sets of major attackers committing almost all the attacks, since their attack "fingerprints" and target selection scheme can be unequivocally identified according to the very limited number of unique spatiotemporal characteristics, each of which only exists on a consecutive IP region and differs significantly from the others. We utilize a number of quantitative measures, including the flux-fluctuation law, the Markov state transition probability matrix, and predictability measures, to characterize the attack patterns in a comprehensive manner. A general finding is that the attack patterns possess high degrees of predictability, potentially paving the way to anticipating and, consequently, mitigating or even preventing large-scale cyberattacks using macroscopic approaches

The strip entropy approximation of Markov shifts on trees

The strip entropy is studied in this article. We prove that the strip entropy approximation is valid for every ray of a golden-mean tree. This result extends the previous result of [Petersen-Salama, Discrete \& Continuous Dynamical Systems, 2020] on the conventional 2-tree. Lastly, we prove that the strip entropy approximation is valid for eventually periodic rays of a class of Markov-Cayley trees

The fundamental benefits of multiplexity in ecological networks

Acknowledgements and Funding Statement YM was supported Max Planck Society, and was partially supported by the University of Aberdeen Elphinstone Fellowship at earlier stages of this work. The work at Arizona State University was supported by Office of Naval Research under Grant No. N00014-21-1-2323.Peer reviewedPostprin