Pain is common among adults with heart failure (HF), but pain subtypes and associated biomarkers are understudied. The aims were to: 1) characterize chronic pain severity, neuropathic pain quality, lo Show more
Pain is common among adults with heart failure (HF), but pain subtypes and associated biomarkers are understudied. The aims were to: 1) characterize chronic pain severity, neuropathic pain quality, locations, and subtypes; and 2) compare pain severity and levels of biomarkers among pain subtypes. An exploratory aim was to correlate levels of biomarkers with pain severity. This pilot descriptive study included cross-sectional data from 60 adults with HF and chronic pain. Pain was evaluated using the PainDETECT questionnaire. Blood biomarkers included interleukin (IL)-10, IL-18, IL-1β, IL-33, IL-6, IL-8, tumor necrosis factor (TNF)-α, brain-derived neurotrophic factor, leptin, adiponectin, and C-reactive protein. Descriptive statistics, Chi-square test of homogeneity, one-way analysis of variance, and Spearman correlation were used for analyses. The mean age was 70.45 (SD 7.92) years. The sample consisted of 63.3% women and 65.0% White race. Participants primarily reported nociceptive pain only (73.3%) with fewer reporting neuropathic pain only (6.7%) and mixed pain (20.0%). Current and 4-week mean pain severity scores were highest in the mixed pain subtype (p both <.05). No biomarkers were significantly different across the pain subtypes, but lower lL-10 (p=.049), and IL-33 (p=.014), were associated with higher pain severity. In this study, chronic pain and its association with underlying biomarkers were characterized. Future research with a larger sample is needed to understand the unique contributions of biomarkers with targeted pain phenotypes. Show less
The web-based IceBear software is a versatile tool to monitor the results of crystallization experiments and is designed to facilitate supervisor and student communications. It also records and tracks Show more
The web-based IceBear software is a versatile tool to monitor the results of crystallization experiments and is designed to facilitate supervisor and student communications. It also records and tracks all relevant information from crystallization setup to PDB deposition in protein crystallography projects. Fully automated data collection is now possible at several synchrotrons, which means that the number of samples tested at the synchrotron is currently increasing rapidly. Therefore, the protein crystallography research communities at the University of Oulu, Weizmann Institute of Science and Diamond Light Source have joined forces to automate the uploading of sample metadata to the synchrotron. In IceBear, each crystal selected for data collection is given a unique sample name and a crystal page is generated. Subsequently, the metadata required for data collection are uploaded directly to the ISPyB synchrotron database by a shipment module, and for each sample a link to the relevant ISPyB page is stored. IceBear allows notes to be made for each sample during cryocooling treatment and during data collection, as well as in later steps of the structure determination. Protocols are also available to aid the recycling of pins, pucks and dewars when the dewar returns from the synchrotron. The IceBear database is organized around projects, and project members can easily access the crystallization and diffraction metadata for each sample, as well as any additional information that has been provided via the notes. The crystal page for each sample connects the crystallization, diffraction and structural information by providing links to the IceBear drop-viewer page and to the ISPyB data-collection page, as well as to the structure deposited in the Protein Data Bank. Show less