Understanding molecular characteristics of extracellular vesicles derived from different types of mesenchymal stem cells for therapeutic translation.

Mesenchymal stem cells (MSCs) have been studied for decades as candidates for cellular therapy, and their secretome, including secreted extracellular vesicles (EVs), has been identified to contribute significantly to regenerative and reparative functions. Emerging evidence has suggested that MSC-EVs alone, could be used as therapeutics that emulate the biological function of MSCs. However, just as with MSCs, MSC-EVs have been shown to vary in composition, depending on the tissue source of the MSCs as well as the protocols employed in culturing the MSCs and obtaining the EVs. Therefore, the importance of careful choice of cell sources and culture environments is receiving increasing attention. Many factors contribute to the therapeutic potential of MSC-EVs, including the source tissue, isolation technique, and culturing conditions. This review illustrates the molecular landscape of EVs derived from different types of MSC cells along with culture strategies. A thorough analysis of publicly available omic datasets was performed to advance the precision understanding of MSC-EVs with unique tissue source-dependent molecular characteristics. The tissue-specific protein and miRNA-driven Reactome ontology analysis was used to reveal distinct patterns of top Reactome ontology pathways across adipose, bone marrow, and umbilical MSC-EVs. Moreover, a meta-analysis assisted by an AI technique was used to analyze the published literature, providing insights into the therapeutic translation of MSC-EVs based on their source tissues.

Peptide-based capture-and-release purification of extracellular vesicles and statistical algorithm enabled quality assessment.

Circulating extracellular vesicles (EVs) have gained significant attention for discovering tumor biomarkers. However, isolating EVs with well-defined homogeneous populations from complex biological samples is challenging. Different isolation methods have been found to derive different EV populations carrying different molecular contents, which confounds current investigations and hinders subsequent clinical translation. Therefore, standardizing and building a rigorous assessment of isolated EV quality associated with downstream molecular analysis is essential. To address this need, we introduce a statistical algorithm (ExoQuality Index, EQI) by integrating multiple EV characterizations (size, particle concentration, zeta potential, total protein, and RNA), enabling direct EV quality assessment and comparisons between different isolation methods. We also introduced a novel capture-release isolation approach using a pH-responsive peptide conjugated with NanoPom magnetic beads (ExCy) for simple, fast, and homogeneous EV isolation from various biological fluids. Bioinformatic analysis of next-generation sequencing (NGS) data of EV total RNAs from pancreatic cancer patient plasma samples using our novel EV isolation approach and quality index strategy illuminates how this approach improves the identification of tumor associated molecular markers. Results showed higher human mRNA coverage compared to existing isolation approaches in terms of both pancreatic cancer pathways and EV cellular component pathways using gProfiler pathway analysis. This study provides a valuable resource for researchers, establishing a workflow to prepare and analyze EV samples carefully and contributing to the advancement of reliable and rigorous EV quality assessment and clinical translation.

Towards artificial intelligence-enabled extracellular vesicle precision drug delivery.

Extracellular Vesicles (EVs), particularly exosomes, recently exploded into nanomedicine as an emerging drug delivery approach due to their superior biocompatibility, circulating stability, and bioavailability in vivo. However, EV heterogeneity makes molecular targeting precision a critical challenge. Deciphering key molecular drivers for controlling EV tissue targeting specificity is in great need. Artificial intelligence (AI) brings powerful prediction ability for guiding the rational design of engineered EVs in precision control for drug delivery. This review focuses on cutting-edge nano-delivery via integrating large-scale EV data with AI to develop AI-directed EV therapies and illuminate the clinical translation potential. We briefly review the current status of EVs in drug delivery, including the current frontier, limitations, and considerations to advance the field. Subsequently, we detail the future of AI in drug delivery and its impact on precision EV delivery. Our review discusses the current universal challenge of standardization and critical considerations when using AI combined with EVs for precision drug delivery. Finally, we will conclude this review with a perspective on future clinical translation led by a combined effort of AI and EV research.

CRISPR-Cas9 Engineered Extracellular Vesicles for the Treatment of Dominant Progressive Hearing Loss.

Clinical translation of gene therapy has been challenging, due to limitations in current delivery vehicles such as traditional viral vectors. Herein, we report the use of gRNA:Cas9 ribonucleoprotein (RNP) complexes engineered extracellular vesicles (EVs) for in vivo gene therapy. By leveraging a novel high-throughput microfluidic droplet-based electroporation system (µDES), we achieved 10-fold enhancement of loading efficiency and more than 1000-fold increase in processing throughput on loading RNP complexes into EVs (RNP-EVs), compared with conventional bulk electroporation. The flow-through droplets serve as enormous bioreactors for offering millisecond pulsed, low-voltage electroporation in a continuous-flow and scalable manner, which minimizes the Joule heating influence and surface alteration to retain natural EV stability and integrity. In the Shaker-1 mouse model of dominant progressive hearing loss, we demonstrated the effective delivery of RNP-EVs into inner ear hair cells, with a clear reduction of Myo7ash1 mRNA expression compared to RNP-loaded lipid-like nanoparticles (RNP-LNPs), leading to significant hearing recovery measured by auditory brainstem responses (ABR).

Nano pom-poms prepared exosomes enable highly specific cancer biomarker detection.

Extracellular vesicles (EVs), particularly nano-sized small EV exosomes, are emerging biomarker sources. However, due to heterogeneous populations secreted from diverse cell types, mapping exosome multi-omic molecular information specifically to their pathogenesis origin for cancer biomarker identification is still extraordinarily challenging. Herein, we introduced a novel 3D-structured nanographene immunomagnetic particles (NanoPoms) with unique flower pom-poms morphology and photo-click chemistry for specific marker-defined capture and release of intact exosome. This specific exosome isolation approach leads to the expanded identification of targetable cancer biomarkers with enhanced specificity and sensitivity, as demonstrated by multi-omic exosome analysis of bladder cancer patient tissue fluids using the next generation sequencing of somatic DNA mutations, miRNAs, and the global proteome (Data are available via ProteomeXchange with identifier PXD034454). The NanoPoms prepared exosomes also exhibit distinctive in vivo biodistribution patterns, highlighting the highly viable and integral quality. The developed method is simple and straightforward, which is applicable to nearly all types of biological fluids and amenable for enrichment, scale up, and high-throughput exosome isolation.

Extracellular Vesicles as an Advanced Delivery Biomaterial for Precision Cancer Immunotherapy.

In recent years, cancer immunotherapy has been observed in numerous preclinical and clinical studies for showing benefits. However, due to the unpredictable outcomes and low response rates, novel targeting delivery approaches and modulators are needed for being effective to more broader patient populations and cancer types. Compared to synthetic biomaterials, extracellular vesicles (EVs) specifically open a new avenue for improving the efficacy of cancer immunotherapy by offering targeted and site-specific immunity modulation. In this review, the molecular understanding of EV cargos and surface receptors, which underpin cell targeting specificity and precisely modulating immunogenicity, are discussed. Unique properties of EVs are reviewed in terms of their surface markers, intravesicular contents, intrinsic immunity modulatory functions, and pharmacodynamic behavior in vivo with tumor tissue models, highlighting key indications of improved precision cancer immunotherapy. Novel molecular engineered strategies for reprogramming and directing cancer immunotherapeutics, and their unique challenges are also discussed to illuminate EV's future potential as a cancer immunotherapeutic biomaterial.

Biologically enhanced starch bio-ink for promoting 3D cell growth.

The excellent rheological property has legitimated the suitability of starch hydrogel for extrusion-based 3D printing. However, the inability to promote cell attachment and migration has precluded the non-modified starch hydrogel from direct applications in the biomedical field. Herein, we develop a novel 3D printable nanocomposite starch hydrogel with highly enhanced biocompatibility for promoting 3D cell growth, by formulating with gelatin nanoparticles and collagen. The rheological evaluation reveals the shear-thinning and thixotropic properties of the starch-based hydrogel, as well as the combinatorial effect of collagen and gelatin nanoparticles on maintaining the printability and 3D shape fidelity. The homogeneous microporous structure with abundant collagen fibers and gelatin nanoparticles interlaced and supplies rich attachment sites for cell growth. Corroborated by the cell metabolic activity study, the multiplied proliferation rate of cells on the 3D printed nanocomposite starch hydrogel scaffold confirms the remarkable enhancement of biological function of developed starch hydrogel. Hence, the developed nanocomposite starch hydrogel serves as a highly desirable bio-ink for advancing 3D tissue engineering.

Development of surface engineered antigenic exosomes as vaccines for respiratory syncytial virus.

Respiratory syncytial virus (RSV) is one of the main pathogens associated with lower respiratory tract infections in infants and young children worldwide. Exosomes secreted by antigen presenting cells (APCs) can elicit immune responses by carrying major histocompatibility complex (MHC) class I molecules complexed with antigenic peptides and other co-stimulating factors. Therefore, we developed novel immunomagnetic nanographene particles to sequentially isolate, surface engineer, and release intact dendritic cell (DC) exosomes for use as a potential vaccine platform against RSV. The H-2Db-restricted, immunodominant peptides from RSV (M187-195 and NS161-75) were introduced to MHC-I on DC-derived exosomes to express peptide/MHC-I (pMHC-I) complexes. A mouse model of RSV infection was used to define the immunogenicity of surface engineered exosomes for activating virus-specific immune responses. Ex vivo assays demonstrated that engineered exosomes carrying RSV-specific peptides can elicit interferon-gamma (IFN-γ) production by virus-specific CD8+ T cells isolated from RSV-infected C57BL/6 mice. In vivo assays demonstrated that subcutaneous administration of both M187-195 and NS161-75 engineered exosomes to mice, with or without additional adjuvant, appeared safe and well tolerated, however, did not prime antigen-specific CD8+ T cell responses. Surface engineered exosomes are immunogenic and promising for further development as a vaccine platform.

Reducing time to treatment and patient costs with breast cancer: the impact of patient visits.

BACKGROUND: The purpose of this study was to evaluate the impact of processes aimed at reducing time to treatment initiation (TTI) on minimizing the days spent to complete pretreatment visits and the associated costs for patients with nonmetastatic breast cancer. METHODS: System-wide initiatives were implemented in 2014 to minimize TTI, by incorporating multiple strategies (eg, creation of teams, patient liaisons, process mapping) and enhanced communication to increase coordinated visits. Average number of days spent to complete visits, TTI, and associated patient costs including driving expenses, parking, food, childcare, and lost wages were calculated and compared between the years 2015 and 2018. RESULTS: In 2015, the median TTI was 43.5 days and the average number of separate days spent to attend multidisciplinary visits prior to first treatment was 1.86. These were reduced to 29 days and 1.52 visits, respectively, in 2018 (p < 0.0001 for both). When evaluating treatment visits by surgical procedure, the average number of visits was reduced regardless of surgical procedure. The average number of visits was highest for patients undergoing mastectomy with reconstruction (2.34 in 2015, reduced to 1.65 in 2018, p < 0.0001). A single visit to complete treatment planning was associated with patient costs of $249 as compared with multiple trips costing $491 for 2 visits and up to $1,226 for 5 visits. CONCLUSIONS: In breast cancer patients, implementing processes to reduce time to treatment was associated with fewer visits required prior to treatment initiation, resulting in lower patient costs.

The power of one: Evaluating the impact of a single multi-disciplinary treatment visit on time to treatment.

Breast cancer treatment often requires multi-disciplinary evaluation, which can require multiple visits, delaying time to treatment initiation (TTI). The present analysis evaluated the impact of system-wide initiatives to reduce TTI by evaluating TTI for patients completing treatment evaluation in a single visit compared with those having multiple visits. The results demonstrated that patients who completed multi-disciplinary evaluation in a single visit had a reduced median TTI (27 vs 32 days, P = .002), which was seen for patients undergoing initial surgery (28.0 vs 33.5 days, P = .01) as well as for those undergoing neoadjuvant systemic therapy (22.5 vs 29 days, P = .05).

Carbodiimide Conjugation of Latent Transforming Growth Factor ß1 to Superparamagnetic Iron Oxide Nanoparticles for Remote Activation.

Conjugation of latent growth factors to superparamagnetic iron oxide nanoparticles (SPIONs) is potentially useful for magnetically triggered release of bioactive macromolecules. Thus, the goal of this work was to trigger the release of active Transforming Growth-Factor Beta (TGF-ß) via magnetic hyperthermia by binding SPIONs to the latent form of TGF-ß, since heat has been shown to induce release of TGF-ß from the latent complex. Commercially available SPIONS with high specific absorption rates (SAR) were hydrolyzed in 70% ethanol to create surface carboxylic acid conjugation sites for carbodiimide chemistry. Fourier-Transform Infra-Red (FTIR) analysis verified the conversion of maleic anhydride to maleic acid. 1-Ethyl-2-(3-dimethyulaminopropyl) carbodiimide (EDC) and N-hydroxysulfosuccinimide (Sulfo-NHS) were used to bind to the open conjugation sites of the SPION in order to graft latent TGF-ß onto the particles. The resulting conjugated particles were imaged with transmission electron microscopy (TEM), and the complexed particles were characterized by dynamic light scattering (DLS) and superconducting quantum interference device (SQUID) magnetometry. Enzyme-linked immunosorbent assay (ELISA) was used to assess the thermally triggered release of active TGF-ß from the latent complex, demonstrating that conjugation did not interfere with release. Results showed that latent TGF-ß was successfully conjugated to the iron oxide nanoparticles, and magnetically triggered release of active TGF-ß was achieved.

There is no coherent evidence for a bilingual advantage in executive processing.

Three studies compared bilinguals to monolinguals on 15 indicators of executive processing (EP). Most of the indicators compare a neutral or congruent baseline to a condition that should require EP. For each of the measures there was no main effect of group and a highly significant main effect of condition. The critical marker for a bilingual advantage, the Group×Condition interaction, was significant for only one indicator, but in a pattern indicative of a bilingual disadvantage. Tasks include antisaccade (Study 1), Simon (Studies 1-3), flanker (Study 3), and color-shape switching (Studies 1-3). The two groups performed identically on the Raven's Advanced Matrices test (Study 3). Analyses on the combined data selecting subsets that are precisely matched on parent's educational level or that include only highly fluent bilinguals reveal exactly the same pattern of results. A problem reconfirmed by the present study is that effects assumed to be indicators of a specific executive process in one task (e.g., inhibitory control in the flanker task) frequently do not predict individual differences in that same indicator on a related task (e.g., inhibitory control in the Simon task). The absence of consistent cross-task correlations undermines the interpretation that these are valid indicators of domain-general abilities. In a final discussion the underlying rationale for hypothesizing bilingual advantages in executive processing based on the special linguistic demands placed on bilinguals is interrogated.