Developing A Chronic Pain Vocabulary: Communication Preferences Among Individuals With Chronic Pain

In order to be acknowledged, chronic pain must be voiced yet disclosing of chronic pain is fraught with social and professional repercussions. Moreover, there is a perceived disinterest in hearing about, and a stigma associated with the experience of chronic pain. This research explores the therapeutic value of communicating about pain. Nineteen individuals with chronic pain participated in a six-week online writing workshop to describe the way chronic pain impacts daily activities. These qualitative responses were analyzed using discourse analysis and four interpretive repertoires emerged which convey the multi-faceted impacts of living with chronic pain. These findings informed the creation of a quantitative survey tool which was widely disseminated using social media to chronic pain dedicated forums and websites. Findings indicate that audience and gender have a large sway on communication preferences. Individuals with chronic pain desire to receive cure-centered information from health care providers and care-centered information, including empathy, from family and friends when they communicate about their pain. Women in particular aspire to receive emotional support for their well-being and empathy upon communicating about their pain. These results help to fill in the void of patient communication preference within the framework of delivering patient centered care. Understanding patients’ communication preferences has high clinical value as providers can tailor their communication practices to increase rapport, improve patient satisfaction and promote treatment adherence. They place a heightened role on family and friends in the treatment plan as they can offer needed emotional support. Implications include educating family and friends to be aware of pain behavior so they can recognize early indicators and provide empathetic responses. Additionally, using computer mediated communication is a recommended platform to engage individuals with chronic pain due to its convenience, low-cost, and anonymity as well as its potential to connect disparate individuals and build community among marginalized group

Quantification of the Adhesion Strength of Candida albicans to Tooth Enamel

Caries is one of the most prevalent diseases worldwide, which is caused by the degradation of the tooth enamel surface. In earlier research the opportunistic pathogen Candida albicans has been associated with the formation of caries in children. Colonization of teeth by C. albicans starts with the initial adhesion of individual yeast cells to the tooth enamel surface. In this study, we visualized the initial colonization of C. albicans yeast cells on pellicle-covered enamel by scanning electron microscopy. To quantitatively unravel the initial adhesion strength, we applied fluidic force microscopy-based single-cell force spectroscopy to examine the key adhesion parameters adhesion force, rupture length and de-adhesion work. We analyzed single saliva-treated or untreated yeast cells on tooth enamel specimens with or without salivary pellicle. Under all tested conditions, adhesion forces in the lower nanonewton range were determined. Furthermore, we have found that all adhesion parameters were enhanced on the pellicle-covered compared to the uncovered enamel. Our data suggest that initial adhesion occurs through a strong interaction between yeast cell wall-associated adhesins and the salivary pellicle. Future SCFS studies may show whether specific management of the salivary pellicle reduces the adhesion of C. albicans on teeth and thus contributes to caries prophylaxis

Estimating uncertainty in density surface models

This work was funded by OPNAV N45 and the SURTASS LFA Settlement Agreement, and being managed by the U.S. Navy’s Living Marine Resources program under Contract No. N39430-17-C-1982.Providing uncertainty estimates for predictions derived from species distribution models is essential for management but there is little guidance on potential sources of uncertainty in predictions and how best to combine these. Here we show where uncertainty can arise in density surface models (a multi-stage spatial modelling approach for distance sampling data), focussing on cetacean density modelling. We propose an extensible, modular, hybrid analytical-simulation approach to encapsulate these sources. We provide example analyses of fin whales Balaenoptera physalus in the California Current Ecosystem.Publisher PDFPeer reviewe

Candida albicans adhesion to central venous catheters: Impact of blood plasma-driven germ tube formation and pathogen-derived adhesins

Candida albicans-related bloodstream infections are often associated with infected central venous catheters (CVC) triggered by microbial adhesion and biofilm formation. We utilized single-cell force spectroscopy (SCFS) and flow chamber models to investigate the adhesion behavior of C. albicans yeast cells and germinated cells to naïve and human blood plasma (HBP)-coated CVC tubing. Germinated cells demonstrated up to 56.8-fold increased adhesion forces to CVC surfaces when compared to yeast cells. Coating of CVCs with HBP significantly increased the adhesion of 60-min germinated cells but not of yeast cells and 30-min germinated cells. Under flow conditions comparable to those in major human veins, germinated cells displayed a flow directional-orientated adhesion pattern to HBP-coated CVC material, suggesting the germ tip to serve as the major adhesive region. None of the above-reported phenotypes were observed with germinated cells of an als3Δ deletion mutant, which displayed similar adhesion forces to CVC surfaces as the isogenic yeast cells. Germinated cells of the als3Δ mutant also lacked a clear flow directional-orientated adhesion pattern on HBP-coated CVC material, indicating a central role for Als3 in the adhesion of germinated C. albicans cells to blood exposed CVC surfaces. In the common model of C. albicans, biofilm formation is thought to be mediated primarily by yeast cells, followed by surface-triggered the formation of hyphae. We suggest an extension of this model in which C. albicans germ tubes promote the initial adhesion to blood-exposed implanted medical devices via the germ tube-associated adhesion protein Als3

Dynamic habitat models reflect interannual movement of cetaceans within the California current ecosystem

This modeling project was funded by the Navy, Commander, U.S. Pacific Fleet (U.S. Navy), the Bureau of Ocean Energy Management (BOEM), and by the National Oceanic and Atmospheric Administration (NOAA), National Marine Fisheries Service (NMFS), Southwest Fisheries Science Center (SWFSC). The 2018 survey was conducted as part of the Pacific Marine Assessment Program for Protected Species (PacMAPPS), a collaborative effort between NOAA Fisheries, the U.S. Navy, and BOEM to collect data necessary to produce updated abundance estimates for cetaceans in the CCE study area. BOEM funding was provided via Interagency Agreement (IAA) M17PG00025, and Navy funding via IAA N0007018MP4C560, under the Mexican permit SEMARNAT/SGPA/DGVS/013212/18. The methods used to derive uncertainty estimates were developed as part of “DenMod: Working Group for the Advancement of Marine Species Density Surface Modeling” funded by OPNAV N45 and the SURTASS LFA Settlement Agreement, and managed by the U.S. Navy’s Living Marine Resources (LMR) program under Contract No. N39430-17-C-1982. Other permits included INEGI: Oficio núm. 400./331/2018, INEGI.GMA 1.03 SAGARPA de Oficio B00.02.04.1530/2018 NMFS Permit No. 19091.The distribution of wide-ranging cetacean species often cross national or jurisdictional boundaries, which creates challenges for monitoring populations and managing anthropogenic impacts, especially if data are only available for a portion of the species’ range. Many species found off the U.S. West Coast are known to have continuous distributions into Mexican waters, with highly variable abundance within the U.S. portion of their range. This has contributed to annual variability in design-based abundance estimates from systematic shipboard surveys off the U.S. West Coast, particularly for the abundance of warm temperate species such as striped dolphin, Stenella coeruleoalba, which increases off California during warm-water conditions and decreases during cool-water conditions. Species distribution models (SDMs) can accurately describe shifts in cetacean distribution caused by changing environmental conditions, and are increasingly used for marine species management. However, until recently, data from waters off the Baja California peninsula, México, have not been available for modeling species ranges that span from Baja California to the U.S. West Coast. In this study, we combined data from 1992–2018 shipboard surveys to develop SDMs off the Pacific Coast of Baja California for ten taxonomically diverse cetaceans. We used a Generalized Additive Modeling framework to develop SDMs based on line-transect surveys and dynamic habitat variables from the Hybrid Coordinate Ocean Model (HYCOM). Models were developed for ten species: long- and short-beaked common dolphins (Delphinus delphis delphis and D. d. bairdii), Risso’s dolphin (Grampus griseus), Pacific white-sided dolphin (Lagenorhynchus obliquidens), striped dolphin, common bottlenose dolphin (Tursiops truncatus), sperm whale (Physeter macrocephalus), blue whale (Balaenoptera musculus), fin whale (B. physalus), and humpback whale (Megaptera novaeangliae). The SDMs provide the first fine-scale (approximately 9 x 9 km grid) estimates of average species density and abundance, including spatially-explicit measures of uncertainty, for waters off the Baja California peninsula. Results provide novel insights into cetacean ecology in this region as well as quantitative spatial data for the assessment and mitigation of anthropogenic impacts.Publisher PDFPeer reviewe

Human blood plasma factors affect the adhesion kinetics of Staphylococcus aureus to central venous catheters

Staphylococcus aureus is a common cause of catheter-related blood stream infections (CRBSI). The bacterium has the ability to form multilayered biofilms on implanted material, which usually requires the removal of the implanted medical device. A first major step of this biofilm formation is the initial adhesion of the bacterium to the artificial surface. Here, we used single-cell force spectroscopy (SCFS) to study the initial adhesion of S. aureus to central venous catheters (CVCs). SCFS performed with S. aureus on the surfaces of naïve CVCs produced comparable maximum adhesion forces on three types of CVCs in the low nN range (~ 2-7 nN). These values were drastically reduced, when CVC surfaces were preincubated with human blood plasma or human serum albumin, and similar reductions were observed when S. aureus cells were probed with freshly explanted CVCs withdrawn from patients without CRBSI. These findings indicate that the initial adhesion capacity of S. aureus to CVC tubing is markedly reduced, once the CVC is inserted into the vein, and that the risk of contamination of the CVC tubing by S. aureus during the insertion process might be reduced by a preconditioning of the CVC surface with blood plasma or serum albumin

Performance evaluation of cetacean species distribution models developed using generalized additive models and boosted regression trees

Species distribution models (SDMs) are important management tools for highly mobile marine species because they provide spatially and temporally explicit information on animal distribution. Two prevalent modeling frameworks used to develop SDMs for marine species are generalized additive models (GAMs) and boosted regression trees (BRTs), but comparative studies have rarely been conducted; most rely on presence-only data; and few have explored how features such as species distribution characteristics affect model performance. Since the majority of marine species BRTs have been used to predict habitat suitability, we first compared BRTs to GAMs that used presence/absence as the response variable. We then compared results from these habitat suitability models to GAMs that predict species density (animals per km2) because density models built with a subset of the data used here have previously received extensive validation. We compared both the explanatory power (i.e., model goodness of fit) and predictive power (i.e., performance on a novel dataset) of the GAMs and BRTs for a taxonomically diverse suite of cetacean species using a robust set of systematic survey data (1991–2014) within the California Current Ecosystem. Both BRTs and GAMs were successful at describing overall distribution patterns throughout the study area for the majority of species considered, but when predicting on novel data, the density GAMs exhibited substantially greater predictive power than both the presence/absence GAMs and BRTs, likely due to both the different response variables and fitting algorithms. Our results provide an improved understanding of some of the strengths and limitations of models developed using these two methods. These results can be used by modelers developing SDMs and resource managers tasked with the spatial management of marine species to determine the best modeling technique for their question of interest

Performance Evaluation of Cetacean Species Distribution Models Developed Using Generalized Additive Models and Boosted Regression Trees

Species distribution models (SDMs) are important management tools for highly mobile marine species because they provide spatially and temporally explicit information on animal distribution. Two prevalent modeling frameworks used to develop SDMs for marine species are generalized additive models (GAMs) and boosted regression trees (BRTs), but comparative studies have rarely been conducted; most rely on presence-only data; and few have explored how features such as species distribution characteristics affect model performance. Since the majority of marine species BRTs have been used to predict habitat suitability, we first compared BRTs to GAMs that used presence/absence as the response variable. We then compared results from these habitat suitability models to GAMs that predict species density (animals per km2) because density models built with a subset of the data used here have previously received extensive validation. We compared both the explanatory power (i.e., model goodness of fit) and predictive power (i.e., performance on a novel dataset) of the GAMs and BRTs for a taxonomically diverse suite of cetacean species using a robust set of systematic survey data (1991–2014) within the California Current Ecosystem. Both BRTs and GAMs were successful at describing overall distribution patterns throughout the study area for the majority of species considered, but when predicting on novel data, the density GAMs exhibited substantially greater predictive power than both the presence/absence GAMs and BRTs, likely due to both the different response variables and fitting algorithms. Our results provide an improved understanding of some of the strengths and limitations of models developed using these two methods. These results can be used by modelers developing SDMs and resource managers tasked with the spatial management of marine species to determine the best modeling technique for their question of interest