Smokejumper Magazine, July 2001

This issue of the National Smokejumper Association (NSA) Smokejumper Magazine contains the following articles: Kickin’ Cargo/Bum Pilot (Jeff R. Davis), Log of Rookie Smokejumper (Herb Hidu), profiles Phil Stanley, Mike Kreidler, Doug Sutherland and Gregg Phifer, Smokejumper Thwarts Hijacking of Pam-Am Clipper 73 (Chuck Sheley), Anything for a Jump (Chuck Mansfield). Smokejumper Magazine continues Static Line, which was the original title of the NSA quarterly magazine.https://dc.ewu.edu/smokejumper_mag/1031/thumbnail.jp

Smokejumper Magazine, July 2003

This issue of the National Smokejumper Association (NSA) Smokejumper Magazine contains the following articles: Mick Swift (Troop Emonds), Aggressive Fire Control and the Biscuit Fire (Chuck Mansfield), Counterpoint to editorial control (Jim Veitch), Editorial Oversight –readers respond, Hoarding Jumpers (Steve Nemore), Smokejumper Awarded CIA Medals (Fred Donner), Ted Burgon Update. Profiles DeWayne Davis, John Twiss, Ben Musquez, John McIntosh and Jim Rabideau. Smokejumper Magazine continues Static Line, which was the original title of the NSA quarterly magazine.https://dc.ewu.edu/smokejumper_mag/1039/thumbnail.jp

Towards Generalist Biomedical AI

Medicine is inherently multimodal, with rich data modalities spanning text, imaging, genomics, and more. Generalist biomedical artificial intelligence (AI) systems that flexibly encode, integrate, and interpret this data at scale can potentially enable impactful applications ranging from scientific discovery to care delivery. To enable the development of these models, we first curate MultiMedBench, a new multimodal biomedical benchmark. MultiMedBench encompasses 14 diverse tasks such as medical question answering, mammography and dermatology image interpretation, radiology report generation and summarization, and genomic variant calling. We then introduce Med-PaLM Multimodal (Med-PaLM M), our proof of concept for a generalist biomedical AI system. Med-PaLM M is a large multimodal generative model that flexibly encodes and interprets biomedical data including clinical language, imaging, and genomics with the same set of model weights. Med-PaLM M reaches performance competitive with or exceeding the state of the art on all MultiMedBench tasks, often surpassing specialist models by a wide margin. We also report examples of zero-shot generalization to novel medical concepts and tasks, positive transfer learning across tasks, and emergent zero-shot medical reasoning. To further probe the capabilities and limitations of Med-PaLM M, we conduct a radiologist evaluation of model-generated (and human) chest X-ray reports and observe encouraging performance across model scales. In a side-by-side ranking on 246 retrospective chest X-rays, clinicians express a pairwise preference for Med-PaLM M reports over those produced by radiologists in up to 40.50% of cases, suggesting potential clinical utility. While considerable work is needed to validate these models in real-world use cases, our results represent a milestone towards the development of generalist biomedical AI systems

Multidimensional solid-state NMR spectroscopy of plant cell walls

Plant biomass has become an important source of bio-renewable energy in modern society. The molecular structure of plant cell walls is difficult to characterize by most atomic-resolution techniques due to the insoluble and disordered nature of the cell wall. Solid-state NMR (SSNMR) spectroscopy is uniquely suited for studying native hydrated plant cell walls at the molecular level with chemical resolution. Significant progress has been made in the last five years to elucidate the molecular structures and interactions of cellulose and matrix polysaccharides in plant cell walls. These studies have focused on primary cell walls of growing plants in both the dicotyledonous and grass families, as represented by the model plants Arabidopsis thaliana, Brachypodium distachyon, and Zea mays. To date, these SSNMR results have shown that 1) cellulose, hemicellulose, and pectins form a single network in the primary cell wall; 2) in dicot cell walls, the protein expansin targets the hemicellulose-enriched region of the cellulose microfibril for its wall-loosening function; and 3) primary wall cellulose has polymorphic structures that are distinct from the microbial cellulose structures. This article summarizes these key findings, and points out future directions of investigation to advance our fundamental understanding of plant cell wall structure and function