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Abstract Emerging and re-emerging viral pathogens present a unique challenge for anti-viral therapeutic development. Anti-viral approaches with high flexibility and rapid production times are essential for combating these high-pandemic risk viruses. CRISPR-Cas technologies have been extensively repurposed to treat a variety of diseases, with recent work expanding into potential applications against viral infections. However, delivery still presents a major challenge for these technologies. Lipid-coated mesoporous silica nanoparticles (LCMSNs) offer an attractive delivery vehicle for a variety of cargos due to their high biocompatibility, tractable synthesis, and amenability to chemical functionalization. Here, we report the use of LCMSNs to deliver CRISPR-Cas9 ribonucleoproteins (RNPs) that target the Niemann–Pick disease type C1 gene, an essential host factor required for entry of the high-pandemic risk pathogen Ebola virus, demonstrating an efficient reduction in viral infection. We further highlight successful in vivo delivery of the RNP-LCMSN platform to the mouse liver via systemic administration.

Introduction: The role of postoperative radiation (PR) in treating mammary ACC is poorly defined. This study evaluated the impact of PR on survival outcomes for mammary ACC and the extent of utilization. Methods: Patients who underwent surgery for mammary ACC from 2005 to 2015 in SEER database were analyzed. KM analyses of OS and DSS were done for PR versus no PR. Cox hazard regression models were used to determine predictors of OS and DSS. Results: Of the 488 patients, 244 underwent PR. The PR group was younger, but other variables were similar between the 2 groups. OS was better for PR (p = 0.029). 10-year DSS was better for PR group by an absolute value of 6 % but did not reach statistical significance (p = 0.537). Age, radiation, nodal metastasis, and grade III/IV were independent predictors of OS while grade III/IV and AJCC stage III/IV independently predicted DSS. Conclusion: PR improves OS for mammary ACC, but this study did not show increased utilization. Radiation should be considered after surgery for mammary ACC, particularly for patients with independent predictors of OS.

Polymersomes are being widely explored as synthetic analogs of lipid vesicles based on their enhanced stability and potential uses in a wide variety of applications in (e.g., drug delivery, cell analogs, etc.). Controlled formation of giant polymersomes for use in membrane studies and cell mimetic systems, however, is currently limited by low-yield production methodologies. Here, we describe for the first time, how the size distribution of giant poly(ethylene glycol)-poly(butadiene) (PEO-PBD) polymersomes formed by gel-assisted rehydration may be controlled based on membrane fluidization. We first show that the average diameter and size distribution of PEO-PBD polymersomes may be readily increased by increasing the temperature of the rehydration solution. Further, we describe a correlative relationship between polymersome size and membrane fluidization through the addition of sucrose during rehydration, enabling the formation of PEO-PBD polymersomes with a range of diameters, including giant-sized vesicles (>100 μm). This correlative relationship suggests that sucrose may function as a small molecule fluidizer during rehydration, enhancing polymer diffusivity during formation and increasing polymersome size. Overall the ability to easily regulate the size of PEO-PBD polymersomes based on membrane fluidity, either through temperature or fluidizers, has broadly applicability in areas including targeted therapeutic delivery and synthetic biology.

Superparamagnetic relaxometry (SPMR) is a highly sensitive technique for the in vivo detection of tumor cells and may improve early stage detection of cancers. SPMR employs superparamagnetic iron oxide nanoparticles (SPION). After a brief magnetizing pulse is used to align the SPION, SPMR measures the time decay of SPION using super-conducting quantum interference device (SQUID) sensors. Substantial research has been carried out in developing the SQUID hardware and in improving the properties of the SPION. However, little research has been done in the pre-processing of sensor signals and post-processing source modeling in SPMR. In the present study, we illustrate new pre-processing tools that were developed to: (1) remove trials contaminated with artifacts, (2) evaluate and ensure that a single decay process associated with bounded SPION exists in the data, (3) automatically detect and correct flux jumps, and (4) accurately fit the sensor signals with different decay models. Furthermore, we developed an automated approach based on multi-start dipole imaging technique to obtain the locations and magnitudes of multiple magnetic sources, without initial guesses from the users. A regularization process was implemented to solve the ambiguity issue related to the SPMR source variables. A procedure based on reduced chi-square cost-function was introduced to objectively obtain the adequate number of dipoles that describe the data. The new pre-processing tools and multi-start source imaging approach have been successfully evaluated using phantom data. In conclusion, these tools and multi-start source modeling approach substantially enhance the accuracy and sensitivity in detecting and localizing sources from the SPMR signals. Furthermore, multi-start approach with regularization provided robust and accurate solutions for a poor SNR condition similar to the SPMR detection sensitivity in the order of 1000 cells. We believe such algorithms will help establishing the industrial standards for SPMR when applying the technique in pre-clinical and clinical settings. [ABSTRACT FROM AUTHOR]