Marshall B. Ketchum University

Gadolinium nanoparticles (GdNPs) have gained increasing attention as multifunctional metal-based nanoplatforms that extend far beyond their traditional use as magnetic resonance imaging (MRI) contrast agents. Their specific magnetic properties, tunable physicochemical features, and tunable biocompatibilities with biocompatible coatings give them great potential as drug delivery and theranostic applications. They offer greater stability, lower systemic toxicity, and more surface modification options compared to molecular gadolinium chelates. The functionalized GdNPs not only show excellent properties as drug carriers for their specific indications but also serve as agents in various imaging modalities with superior therapeutic efficacy by means of radio sensitization and magnetically assisted delivery. Note too that GdNP-based formulations have demonstrated synergistic activity when administered with chemotherapeutic agents such as doxorubicin. GdNPs have demonstrated promising preclinical outcomes, and their clinical translation remains restricted due to a number of scale-up constraints, long-term safety challenges, pharmacokinetics, and regulatory problems. This review provides information on the use of GdNPs, their key physicochemical and magnetic properties, ligand engineering for targeted delivery, and biological mechanisms of their theranostic performance.

Abstract This research investigates how reviewers’ self-presentation strategies influence their posting behavior. We find reviewers are less likely to post negative reviews early in their review history due to concerns that doing so would make them appear as lacking warmth. This concern diminishes as the number of reviews associated with their profile increases, resulting in a discernable negative trend in ratings at the reviewer level. We document this trend across two well-known review platforms (Yelp and TripAdvisor). A series of controlled laboratory studies replicate the effect while demonstrating the role played by self-presentation concerns in explaining the downward trend of ratings. Specifically, we find concerns about appearing to lack warmth influence reviewers’ initial reluctance to post negative (but not positive) reviews, while concerns about appearing competent do not. We identify two theoretically consistent managerial interventions that moderate the effect. Allowing reviewers to rate experiences without associating a review with their profile reduces the effect of the number of prior reviews on their likelihood to post, as does prompting them to mention one positive element in their written comments. Our findings underscore the common concern that online review platforms provide positively skewed ratings and offers insight into how to address this.

Background/Objectives: Peptide-based inorganic nanoparticles (PINPs) have emerged as promising candidates for intracellular delivery due to their unique structural and functional attributes. These hybrid nanostructures combine the high surface area and tunable optical/magnetic properties of metal cores (e.g., Au, Ag, Fe3O4) with the biocompatibility, targeting specificity, and responsive behavior of peptides. In particular, peptides with amphipathic or cell-penetrating features could facilitate efficient transport of molecular cargos across cellular membranes while enabling stimulus-responsive drug release in target tissues. Methods: We review key synthesis methods (especially green, peptide-mediated one-pot approaches), functionalization strategies (e.g., thiol-gold bonds, click chemistries), and characterization techniques (TEM, DLS, FTIR, etc.) that underpin PINP design. In addition, we highlight diverse peptide classes (linear, cyclic, amphipathic, self-assembling) and their roles (targeting ligands, capping/stabilizing agents, reducing agents) in constructing multifunctional nanocarriers. Results: The prospects of PINPs are considerable: they enable targeted drug delivery with imaging/theranostic capability, improve drug stability and cellular uptake, and harness peptide programmability for precision nanomedicine. However, challenges such as in vivo stability, immunogenicity, and standardization of evaluation must be addressed. Conclusions: Overall, PINPs represent multifunctional platforms that could significantly advance drug delivery and diagnostic applications in the future.

Protocol: doi.org/10.1002/14651858.CD015820.

Multi-sided platform marketplaces connect at least two groups of customers together, enabling complex value creation and capture systems. Over the last decade, they have dominated entire industries, attracting billions of users and dollars of capital. Interestingly, most of the world’s most successful platforms (based on market capitalization) were founded primarily in North America and secondarily in Asia, with only a few founded in Europe and almost none elsewhere. Moreover, business-to-consumer platforms have grown faster than business-to-business platforms. And platforms have had more success per capita in cities than rural locations. This symposium assembles some of the world’s platform experts to describe their explanations and predictions for the locations, industries, and business models that will fuel the next wave of successful platforms. The session will conclude with a discussion among the panelists and audience for a research agenda to guide future efforts in this evolving field.

Targeting drugs to cancer cells via overexpressed cell-surface receptors has emerged as an effective therapeutic strategy for several cancers. However, identifying cell-surface receptors that allow selective uptake of targeting ligands by cancer cells—while sparing normal cells—remains a challenge, especially for triple-negative breast cancer (TNBC), which lacks a well-defined receptor for targeted delivery. In this study, immunohistochemical (IHC) analysis revealed that human TNBC patient tissues have significantly higher levels of keratin 1 (K1) compared to normal breast tissues. Among TNBC tissues, grade 3 tumors showed significantly higher (threefold) K1 expression compared to grade 2 tumors. We analyzed human TNBC and normal mammary epithelial cells to detect K1 from cell lysates using three methods: mass spectrometry, peptide mass fingerprinting, and Western blot. TNBC cell lysates confirmed the presence and high expression levels of 67 kDa K1. Importantly, intact cells showed that K1 is uniformly present on the surface of TNBC cells, while no or minimal cell-surface K1 was found in normal mammary epithelial cells using immunofluorescence confocal microscopy. Further, we show that cell-surface K1 was utilized by TNBC-selective peptide 18–4 for its uptake via cell-surface receptor (K1)-mediated endocytosis in TNBC cells, and the presence of peptide 18–4 did not affect the assembly of endogenous cytoplasmic K1. Taken together, our results demonstrate that K1 is overexpressed in human TNBC, and cell-surface K1 represents a promising new target for directed delivery in TNBC using targeting ligands such as peptide 18–4.

E-commerce platforms use recommendation algorithms to select products and services for consumers from a vast number of options. However, analyzing the causal impact of recommendation algorithms is challenging due to unobserved selection processes, hidden variables, and endogenous adjustments to the current states of the marketplace. We leverage Amazon’s binding commitment to comply with the U.K. Competition and Markets Authority’s (CMA’s) regulation, which prohibits Amazon from using Prime eligibility as a criterion for recommending the Featured Offer within a product market, to study the causal impacts of the recommendation algorithms on seller niche market entry, price and competition strategies, consumer search and purchase behaviors, and the revenues of sellers and the platform. We first identify that the binding commitment to the CMA causes the platform to shift recommendation weights from Prime eligibility to low offer price. Then, we study the average treatment effects of the recommendation algorithm change on product market outcomes and further analyze driving mechanisms. We find that Amazon’s recommendation algorithm change in response to the CMA’s regulation increases product total clicks while decreasing product ratings and consumer click-through rates. Mechanism analysis shows that the recommendation algorithm change decreases offer prices while decreasing offer qualities (intensive margin) and offer varieties (extensive margin), causing sellers to race to the bottom and decreasing consumer satisfaction. Our causal analysis of the impacts of the platform recommendation algorithm provides insights for third-party sellers responding to the platform algorithm change, for the platform owners to design the recommendation algorithm, and for the regulators to design policies in guiding the recommendation algorithm design to promote competition fairness and enhance consumer welfare.