Zero-shot Learning with Minimum Instruction to Extract Social Determinants and Family History from Clinical Notes using GPT Model

Demographics, Social determinants of health, and family history documented in the unstructured text within the electronic health records are increasingly being studied to understand how this information can be utilized with the structured data to improve healthcare outcomes. After the GPT models were released, many studies have applied GPT models to extract this information from the narrative clinical notes. Different from the existing work, our research focuses on investigating the zero-shot learning on extracting this information together by providing minimum information to the GPT model. We utilize de-identified real-world clinical notes annotated for demographics, various social determinants, and family history information. Given that the GPT model might provide text different from the text in the original data, we explore two sets of evaluation metrics, including the traditional NER evaluation metrics and semantic similarity evaluation metrics, to completely understand the performance. Our results show that the GPT-3.5 method achieved an average of 0.975 F1 on demographics extraction, 0.615 F1 on social determinants extraction, and 0.722 F1 on family history extraction. We believe these results can be further improved through model fine-tuning or few-shots learning. Through the case studies, we also identified the limitations of the GPT models, which need to be addressed in future research.Comment: 5 pages, 4 figure

Zeolite membranes - a review and comparison with MOFs

The latest developments in zeolite membranes are reviewed, with an emphasis on the synthesis techniques, including seed assembly and secondary growth methods. This review also discusses the current industrial applications of zeolite membranes, the feasibility of their use in membrane reactors and their hydrothermal stability. Finally, zeolite membranes are compared with metal–organic framework (MOF) membranes and the latest advancements in MOF and mixed matrix membranes are highlighted

HypoRiPPAtlas as an Atlas of hypothetical natural products for mass spectrometry database search

Recent analyses of public microbial genomes have found over a million biosynthetic gene clusters, the natural products of the majority of which remain unknown. Additionally, GNPS harbors billions of mass spectra of natural products without known structures and biosynthetic genes. We bridge the gap between large-scale genome mining and mass spectral datasets for natural product discovery by developing HypoRiPPAtlas, an Atlas of hypothetical natural product structures, which is ready-to-use for in silico database search of tandem mass spectra. HypoRiPPAtlas is constructed by mining genomes using seq2ripp, a machine-learning tool for the prediction of ribosomally synthesized and post-translationally modified peptides (RiPPs). In HypoRiPPAtlas, we identify RiPPs in microbes and plants. HypoRiPPAtlas could be extended to other natural product classes in the future by implementing corresponding biosynthetic logic. This study paves the way for large-scale explorations of biosynthetic pathways and chemical structures of microbial and plant RiPP classes

Evidence‐based review of treatment options for patients with glottic cancer

Evidence‐based medicine integrates the best available data in decision making, with the goal of minimizing physicians' and patients' subjectivity. In 2006, the American Society of Clinical Oncology edited clinical practice guidelines for the use of larynx preservation strategies. The objective of this review was to evaluate the current levels of evidence for glottic squamous cell carcinoma. Current guidelines for early stage glottic cancer are based on low‐level evidence. Conservation surgery (open or transoral) and radiation therapy are all valid options for T1 and selected T2 lesions. For advanced lesions, surgery and combined chemotherapy and radiation are options. High‐level evidence favors combined chemotherapy and radiation therapy or altered fractionation radiation therapy as nonsurgical strategies for organ preservation, compared with radiation therapy alone. The optimal combination of chemotherapy, targeted therapy, and radiation therapy remains to be demonstrated, however, and for high‐volume tumors, total laryngectomy may still be warranted. © 2011 Wiley Periodicals, Inc. Head Neck, 2011Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/87151/1/21528_ftp.pd

Effects of remote mutation on the autolysis of HIV-1 PR: X-ray and NMR investigations

Autolysis rates of the C95M and C95M/C1095A mutants of a HIV-1 protease tethered dimer have been determined by real time NMR and it is observed that the double mutant has approximately two times higher rate. X-ray structure of the C95M/C1095A double mutant has been solved and refined to 2.1 Å resolution. Comparison of the double mutant structure with that of C95M single mutant reveals that there is a shift in the position of the catalytic aspartates and the bound catalytic water. The mutation also causes a loss of hydrophobic packing near the dimerization domain of the protein. These observations demonstrate that subtle changes are adequate to cause significant changes in the rate of autolysis of the double mutant. This provides a rationale for the effects of remote mutations on the activity and drug resistance of the enzyme

The living interface between synthetic biology and biomaterial design

Recent far-reaching advances in synthetic biology have yielded exciting tools for the creation of new materials. Conversely, advances in the fundamental understanding of soft-condensed matter, polymers and biomaterials offer new avenues to extend the reach of synthetic biology. The broad and exciting range of possible applications have substantial implications to address grand challenges in health, biotechnology and sustainability. Despite the potentially transformative impact that lies at the interface of synthetic biology and biomaterials, the two fields have, so far, progressed mostly separately. This Perspective provides a review of recent key advances in these two fields, and a roadmap for collaboration at the interface between the two communities. We highlight the near-term applications of this interface to the development of hierarchically structured biomaterials, from bioinspired building blocks to 'living' materials that sense and respond based on the reciprocal interactions between materials and embedded cells