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Nanotechnology platforms, such as nanoparticles, liposomes, dendrimers, and micelles have been studied extensively for various drug deliveries, to treat or prevent diseases by modulating physiological or pathological processes. The delivery drug molecules range from traditional small molecules to recently developed biologics, such as proteins, peptides, and nucleic acids. Among them, proteins have shown a series of advantages and potential in various therapeutic applications, such as introducing therapeutic proteins due to genetic defects, or used as nanocarriers for anticancer agents to decelerate tumor growth or control metastasis. This review discusses the existing nanoparticle delivery systems, introducing design strategies, advantages of using each system, and possible limitations. Moreover, we will examine the intracellular delivery of different protein therapeutics, such as antibodies, antigens, and gene editing proteins into the host cells to achieve anticancer effects and cancer vaccines. Finally, we explore the current applications of protein delivery in anticancer treatments. 

To realize RNA interference (RNAi) therapeutics, it is necessary to deliver therapeutic RNAs (such as small interfering RNA or siRNA) into cell cytoplasm. A major challenge of RNAi therapeutics is the endosomal entrapment of the delivered siRNA. In this study, we developed a family of delivery vehicles called Janus base nanopieces (NPs). They are rod-shaped nanoparticles formed by bundles of Janus base nanotubes (JBNTs) with RNA cargoes incorporated inside via charge interactions. JBNTs are formed by noncovalent interactions of small molecules consisting of a base component mimicking DNA bases and an amino acid side chain. NPs presented many advantages over conventional delivery materials. NPs efficiently entered cells via macropinocytosis similar to lipid nanoparticles while presenting much better endosomal escape ability than lipid nanoparticles; NPs escaped from endosomes via a “proton sponge” effect similar to cationic polymers while presenting significant lower cytotoxicity compared to polymers and lipids due to their noncovalent structures and DNA-mimicking chemistry. In a proof-of-concept experiment, we have shown that NPs are promising candidates for antiviral delivery applications, which may be used for conditions such as COVID-19 in the future. 

Objectives An Opioid Treatment Desert is an area with limited accessibility to medication-assisted treatment and recovery facilities for Opioid Use Disorder. We explored the concept of Opioid Treatment Deserts including racial differences in potential spatial accessibility and applied it to one Midwestern urban county using high resolution spatiotemporal data. Methods We obtained individual-level data from one Emergency Medical Services (EMS) agency (Columbus Fire Department) in Franklin County, Ohio. Opioid overdose events were based on EMS runs where naloxone was administered from 1/1/2013 to 12/31/2017. Potential spatial accessibility was measured as the time (in minutes) it would take an individual, who may decide to seek treatment after an opioid overdose, to travel from where they had the overdose event, which was a proxy measure of their residential location, to the nearest opioid use disorder (OUD) treatment provider that provided medically-assisted treatment (MAT). We estimated accessibility measures overall, by race and by four types of treatment providers (any type of MAT for OUD, Buprenorphine, Methadone, or Naltrexone). Areas were classified as an Opioid Treatment Desert if the estimate travel time to treatment provider (any type of MAT for OUD) was greater than a given threshold. We performed sensitivity analysis using a range of threshold values based on multiple modes of transportation (car and public transit) and using only EMS runs to home/residential location types. Results A total of 6,929 geocoded opioid overdose events based on data from EMS agencies were used in the final analysis. Most events occurred among 26–35 years old (34%), identified as White adults (56%) and male (62%). Median travel times and interquartile range (IQR) to closest treatment provider by car and public transit was 2 minutes (IQR: 3 minutes) and 17 minutes (IQR: 17 minutes), respectively. Several neighborhoods in the study area had limited accessibility to OUD treatment facilities and were classified as Opioid Treatment Deserts. Travel time by public transit for most treatment provider types and by car for Methadone-based treatment was significantly different between individuals who were identified as Black adults and White adults based on their race. Conclusions Disparities in access to opioid treatment exist at the sub-county level in specific neighborhoods and across racial groups in Columbus, Ohio and can be quantified and visualized using local public safety data (e.g., EMS runs). Identification of Opioid Treatment Deserts can aid multiple stakeholders better plan and allocate resources for more equitable access to MAT for OUD and, therefore, reduce the burden of the opioid epidemic while making better use of real-time public safety data to address a public health epidemic that has turned into a public safety crisis. 

Abstract Decoding sensory stimuli from neural activity can provide insight into how the nervous system might interpret the physical environment, and facilitates the development of brain-machine interfaces. Nevertheless, the neural decoding problem remains a significant open challenge. Here, we present an efficient nonlinear decoding approach for inferring natural scene stimuli from the spiking activities of retinal ganglion cells (RGCs). Our approach uses neural networks to improve on existing decoders in both accuracy and scalability. Trained and validated on real retinal spike data from more than 1000 simultaneously recorded macaque RGC units, the decoder demonstrates the necessity of nonlinear computations for accurate decoding of the fine structures of visual stimuli. Specifically, high-pass spatial features of natural images can only be decoded using nonlinear techniques, while low-pass features can be extracted equally well by linear and nonlinear methods. Together, these results advance the state of the art in decoding natural stimuli from large populations of neurons. 

Abstract RNA delivery into deep tissues with dense extracellular matrix (ECM) has been challenging. For example, cartilage is a major barrier for RNA and drug delivery due to its avascular structure, low cell density and strong negative surface charge. Cartilage ECM is comprised of collagens, proteoglycans, and various other noncollagneous proteins with a spacing of 20nm. Conventional nanoparticles are usually spherical with a diameter larger than 50-60nm (after cargo loading). Therefore, they presented limited success for RNA delivery into cartilage. Here, we developed Janus base nanotubes (JBNTs, self-assembled nanotubes inspired from DNA base pairs) to assemble with small RNAs to form nano-rod delivery vehicles (termed as “Nanopieces”). Nanopieces have a diameter of ∼20nm (smallest delivery vehicles after cargo loading) and a length of ∼100nm. They present a novel breakthrough in ECM penetration due to the reduced size and adjustable characteristics to encourage ECM and intracellular penetration.