Main Group Redox Catalysis: Reversible P^III/P^V Redox Cycling at a Phosphorus Platform

A planar, trivalent phosphorus compound is shown to undergo reversible two-electron redox cycling (PIII/PV) enabling its use as catalyst for a transfer hydrogenation reaction. The trivalent phosphorus compound activates ammonia-borane to furnish a 10-P-5 dihydridophosphorane, which in turn is shown to transfer hydrogen cleanly to azobenzene, yielding diphenylhydrazine and regenerating the initial trivalent phosphorus species. This result constitutes a rare example of two-electron redox catalysis at a main group compound and suggests broader potential for this nonmetal platform to support bond-modifying redox catalysis of the type dominated by transition metal catalysts

Main Group Redox Catalysis: Reversible P^III/P^V Redox Cycling at a Phosphorus Platform

A planar, trivalent phosphorus compound is shown to undergo reversible two-electron redox cycling (P^III/P^V) enabling its use as catalyst for a transfer hydrogenation reaction. The trivalent phosphorus compound activates ammonia-borane to furnish a 10-P-5 dihydridophosphorane, which in turn is shown to transfer hydrogen cleanly to azobenzene, yielding diphenylhydrazine and regenerating the initial trivalent phosphorus species. This result constitutes a rare example of two-electron redox catalysis at a main group compound and suggests broader potential for this nonmetal platform to support bond-modifying redox catalysis of the type dominated by transition metal catalysts

Polysorbate- and DNA-Mediated Synthesis and Strong, Stable, and Tunable Near-Infrared Photoluminescence of Plasmonic Long-Body Nanosnowmen

Direct photoluminescence (PL) from metal nanoparticles (NPs) without chemical dyes is promising for sensing and imaging applications since this offers a highly tunable platform for controlling and enhancing the signals in various conditions and does not suffer from photobleaching or photoblinking. It is, however, difficult to synthesize metal NPs with a high quantum yield (QY), particularly in the near-infrared (NIR) region where deep penetration and reduced light scattering are advantageous for bioimaging. Herein, we designed and synthesized Au–Ag long-body nanosnowman structures (LNSs), facilitated by polysorbate 20 (Tween 20). The DNA-engineered conductive junction between the head and body parts results in a charge transfer plasmon (CTP) mode in the NIR region. The junction morphology can be controlled by the DNA sequence on the Au core, and polythymine and polyadenine induced thick and thin junctions, respectively. We found that the LNSs with a thicker conductive junction generates the stronger CTP peak and PL signal than the LNSs with a thinner junction. The Au–Ag LNSs showed much higher intensities in both PL and QY than widely studied Au nanorods with similar localized surface plasmon resonance wavelengths, and notably, the LNSs displayed high photostability and robust, sustainable PL signals under continuous laser exposure for >15 h. Moreover, the PL emission from Au–Ag LNSs could be imaged in a deeper scattering medium than fluorescent silica NPs. Finally, highly robust PL-based cell images can be obtained using Au–Ag LNSs without significant signal change while repetitively imaging cells. The results offer the insights in plasmonic NIR probe design, and show that chemical dye-free LNSs can be a very promising candidate with a high QY and a robust, reliable NIR PL signal for NIR sensing and imaging applications

Additional file 1 of Evaluation of the meibomian glands using the tear interferometer wearing orthokeratology lenses

Additional file 1: Table S1. The median and range values for parameters measured by the LipiView® II Ocular Surface Interferometer without (Control group) and with (Ortho-K group) orthokeratologytreatment in Korean children

Immunogenic Extracellular Vesicles Derived from Endoplasmic Reticulum-Stressed Tumor Cells: Implications as the Therapeutic Cancer Vaccine

Tumor-derived extracellular vesicles (TDEs) have potential for therapeutic cancer vaccine applications since they innately possess tumor-associated antigens, mediate antigen presentation, and can incorporate immune adjuvants for enhanced vaccine efficacy. However, the original TDEs also contain immune-suppressive proteins. To address this, we proposed a simple yet powerful preconditioning method to improve the overall immunogenicity of the TDEs. This approach involved inducing endoplasmic reticulum (ER) stress on parental tumor cells via N-glycosylation inhibition with tunicamycin. The generated immunogenic TDEs (iTDEs) contained down-regulated immunosuppressive proteins and up-regulated immune adjuvants, effectively activating dendritic cells (DCs) in vitro. Furthermore, in vivo evidence from a tumor-bearing mouse model showed that iTDEs activated DCs, enabling cytotoxic T lymphocytes (CTLs) to target tumors, and eventually established a systemic antitumor immune response. Additionally, iTDEs significantly delayed tumor recurrence in a postsurgery model compared with control groups. These findings highlight the immense potential of our strategy for utilizing TDEs to develop effective cancer vaccines

Bridging Big Data: Procedures for Combining Non-equivalent Cognitive Measures from the ENIGMA Consortium

AbstractInvestigators in the cognitive neurosciences have turned to Big Data to address persistent replication and reliability issues by increasing sample sizes, statistical power, and representativeness of data. While there is tremendous potential to advance science through open data sharing, these efforts unveil a host of new questions about how to integrate data arising from distinct sources and instruments. We focus on the most frequently assessed area of cognition - memory testing - and demonstrate a process for reliable data harmonization across three common measures. We aggregated raw data from 53 studies from around the world which measured at least one of three distinct verbal learning tasks, totaling N = 10,505 healthy and brain-injured individuals. A mega analysis was conducted using empirical bayes harmonization to isolate and remove site effects, followed by linear models which adjusted for common covariates. After corrections, a continuous item response theory (IRT) model estimated each individual subject’s latent verbal learning ability while accounting for item difficulties. Harmonization significantly reduced inter-site variance by 37% while preserving covariate effects. The effects of age, sex, and education on scores were found to be highly consistent across memory tests. IRT methods for equating scores across AVLTs agreed with held-out data of dually-administered tests, and these tools are made available for free online. This work demonstrates that large-scale data sharing and harmonization initiatives can offer opportunities to address reproducibility and integration challenges across the behavioral sciences.Significance StatementData sharing can increase the quality and rigor of scientific claims, but with large scale data sharing comes an increased need to combine non-equivalent measurements across studies. Auditory verbal learning tasks (AVLTs) are one of the most common research and clinical tools to evaluate memory constructs, but numerous distinct AVLTs are in common use, which creates challenges for data aggregation. We report methods to convert raw scores across common verbal learning instruments, constructed using harmonizing data from 53 studies from around the world. This approach can be replicated in other domains to address long standing data compatibility issues for researchers and clinicians