ABSTRACT
Maackia amurensis lectins serve as research and botanical agents that bind to sialic residues on proteins. For example, M. amurensis seed lectin (MASL) targets the sialic acid modified podoplanin (PDPN) receptor to suppress arthritic chondrocyte inflammation, and inhibit tumor cell growth and motility. However, M. amurensis lectin nomenclature and composition are not clearly defined. Here, we sought to definitively characterize MASL and its effects on tumor cell behavior. We utilized SDS-PAGE and LC-MS/MS to find that M. amurensis lectins can be divided into two groups. MASL is a member of one group which is composed of subunits that form dimers, evidently mediated by a cysteine residue in the carboxy region of the protein. In contrast to MASL, members of the other group do not dimerize under nonreducing conditions. These data also indicate that MASL is composed of 4 isoforms with an identical amino acid sequence, but unique glycosylation sites. We also produced a novel recombinant soluble human PDPN receptor (shPDPN) with 17 threonine residues glycosylated with sialic acid moieties with potential to act as a ligand trap that inhibits OSCC cell growth and motility. In addition, we report here that MASL targets PDPN with very strong binding kinetics in the nanomolar range. Moreover, we confirm that MASL can inhibit the growth and motility of human oral squamous cell carcinoma (OSCC) cells that express the PDPN receptor. Taken together, these data characterize M. amurensis lectins into two major groups based on their intrinsic properties, clarify the composition of MASL and its subunit isoform sequence and glycosylation sites, define sialic acid modifications on the PDPN receptor and its ability to act as a ligand trap, quantitate MASL binding to PDPN with KD in the nanomolar range, and verify the ability of MASL to serve as a potential anticancer agent.
Subject(s)
Antineoplastic Agents , Carcinoma, Squamous Cell , Head and Neck Neoplasms , Mouth Neoplasms , Humans , Carcinoma, Squamous Cell/pathology , Squamous Cell Carcinoma of Head and Neck , N-Acetylneuraminic Acid/metabolism , Maackia/chemistry , Maackia/metabolism , Mouth Neoplasms/pathology , Chromatography, Liquid , Ligands , Tandem Mass Spectrometry , Lectins/pharmacology , Antineoplastic Agents/pharmacology , Sequence Analysis , Cell MovementABSTRACT
Emergency medicine residency program directors (PDs) in areas hit hardest by the initial U.S. COVID-19 pandemic surge faced novel and rapidly evolving organizational, educational, and resident wellness challenges. Despite variations in residency size, hospital setting, and patient population, PDs from eight residencies in "the epicenter" found uniformity in many of the lessons learned. Here we present those lessons and suggestions for high-yield preparation for running a residency during a surge. Of particular importance were frequent, transparent communication and stepwise staffing plans. Illness of residents and other staff occurred early and were substantially reduced as personal protective equipment protocols tightened. Wellness was compromised by anxiety and illness, with varying timelines. New, rich educational opportunities emerged. All programs declared ACGME pandemic status but remained able to maintain some educational offerings. Planning ahead for future surges can significantly reduce the real-time burden for residency leadership, which is particularly important as clinical demands on leadership may also increase with a surge.
ABSTRACT
Natural language processing (NLP) aims to program machines to interpret human language as humans do. It could quantify aspects of medical education that were previously amenable only to qualitative methods. The application of NLP to medical education has been accelerating over the past several years. This article has three aims. First, we introduce the reader to NLP. Second, we discuss the potential of NLP to help integrate FOAM (Free Open Access Medical Education) resources with more traditional curricular elements. Finally, we present the results of a systematic review. We identified 30 articles indexed by PubMed as relating to medical education and NLP, 14 of which were of sufficient quality to include in this review. We close by discussing potential future work using NLP to advance the field of medical education in emergency medicine.
