Acute death as a result of poisoning tropical (Bos taurus indicus) but not temperate (Bos taurus taurus) cattle after oral dosing with Lupinus leucophyllus (velvet lupine).

Due to climate change and increasing summer temperatures, tropical cattle may graze where temperate cattle have grazed, exposing tropical cattle to toxic plants they may be unfamiliar with. This work compared the toxicity of Lupinus leucophyllus (velvet lupine) in temperate and tropical cattle. Orally dosed velvet lupine in tropical cattle caused death. If producers opt to graze tropical cattle, additional care must be taken on rangelands where toxic lupines like velvet lupine grow.

Reinforcement learning informs optimal treatment strategies to limit antibiotic resistance.

Antimicrobial resistance was estimated to be associated with 4.95 million deaths worldwide in 2019. It is possible to frame the antimicrobial resistance problem as a feedback-control problem. If we could optimize this feedback-control problem and translate our findings to the clinic, we could slow, prevent, or reverse the development of high-level drug resistance. Prior work on this topic has relied on systems where the exact dynamics and parameters were known a priori. In this study, we extend this work using a reinforcement learning (RL) approach capable of learning effective drug cycling policies in a system defined by empirically measured fitness landscapes. Crucially, we show that it is possible to learn effective drug cycling policies despite the problems of noisy, limited, or delayed measurement. Given access to a panel of 15 [Formula: see text]-lactam antibiotics with which to treat the simulated Escherichia coli population, we demonstrate that RL agents outperform two naive treatment paradigms at minimizing the population fitness over time. We also show that RL agents approach the performance of the optimal drug cycling policy. Even when stochastic noise is introduced to the measurements of population fitness, we show that RL agents are capable of maintaining evolving populations at lower growth rates compared to controls. We further tested our approach in arbitrary fitness landscapes of up to 1,024 genotypes. We show that minimization of population fitness using drug cycles is not limited by increasing genome size. Our work represents a proof-of-concept for using AI to control complex evolutionary processes.

Range and Pasture Plants Likely to Poison Horses.

Range and pasture toxic plants can poison horses. Many of these plants are noxious weeds that can dominate plant populations and replace healthy forages. Poisoning is often difficult to diagnose as the resulting plant-induced disease is similar to other infectious, toxic, and nutritional diseases. Identifying potentially problem plants, and observing what plants horses are eating, is essential in determining the risk of poisoning. If the risk is significant, it can drive management to invest in strategies to avoid exposure, animal disease, and suffering.

Plants that Contaminate Feed and Forage and Poison Horses: Equine Ttxicology.

Many toxic plants are unpalatable to horses and are not eaten when alternative forage is available. However, when such plants contaminate prepared or baled feed and forage, herd competition and improved palatability can alter acceptance and thereby cause equine plant poisonings. Dehydropyrrolizidine alkaloid-containing plants; cocklebur; Salvia reflexa; kleingrass, switchgrass, and other saponin-containing grasses; jimson weed, black henbane, and other tropane alkaloid-containing plants; lantana; Cassia spp and other myotoxic plants; castor bean; cyanogenic glycoside-containing plants; thiaminase-containing plants; and hoary alyssum are among those that most commonly poison horses in North America via contaminated feed or forage.

Modelling structural colour from helicoidal multi-layer thin films with natural disorder.

A coupled mode theory based on Takagi-Taupin equations describing electromagnetic scattering from distorted periodic arrays is applied to the problem of light scattering from beetles. We extend the method to include perturbations in the permittivity tensor to helicoidal arrays seen in many species of scarab beetle and optically anisotropic layered materials more generally. This extension permits analysis of typical dislocations arising from the biological assembly process and the presence of other structures in the elytra. We show that by extracting structural information from transmission electron microscopy data, including characteristic disorder parameters, good agreement with spectral specular and non-specular reflectance measurements is obtained.

Clinical Characteristics and Outcomes of Drug-Induced Acute Kidney Injury Cases.

Introduction: Drug-induced acute kidney injury (DI-AKI) is a frequent adverse event. The identification of DI-AKI is challenged by competing etiologies, clinical heterogeneity among patients, and a lack of accurate diagnostic tools. Our research aims to describe the clinical characteristics and predictive variables of DI-AKI. Methods: We analyzed data from the Drug-Induced Renal Injury Consortium (DIRECT) study (NCT02159209), an international, multicenter, observational cohort study of enriched clinically adjudicated DI-AKI cases. Cases met the primary inclusion criteria if the patient was exposed to at least 1 nephrotoxic drug for a minimum of 24 hours prior to AKI onset. Cases were clinically adjudicated, and inter-rater reliability (IRR) was measured using Krippendorff's alpha. Variables associated with DI-AKI were identified using L1 regularized multivariable logistic regression. Model performance was assessed using the area under the receiver operating characteristic curve (ROC AUC). Results: A total of 314 AKI cases met the eligibility criteria for this analysis, and 271 (86%) cases were adjudicated as DI-AKI. The majority of the AKI cases were recruited from the United States (68%). The most frequent causal nephrotoxic drugs were vancomycin (48.7%), nonsteroidal antiinflammatory drugs (18.2%), and piperacillin/tazobactam (17.8%). The IRR for DI-AKI adjudication was 0.309. The multivariable model identified age, vascular capacity, hyperglycemia, infections, pyuria, serum creatinine (SCr) trends, and contrast media as significant predictors of DI-AKI with good performance (ROC AUC 0.86). Conclusion: The identification of DI-AKI is challenging even with comprehensive adjudication by experienced nephrologists. Our analysis identified key clinical characteristics and outcomes of DI-AKI compared to other AKI etiologies.

Small molecule targeting of the p38/Mk2 stress signaling pathways to improve cancer treatment.

PURPOSE: Although a long-term goal of cancer therapy always has been the development of agents that selectively destroy cancer cells, more recent trends have been to seek secondary agents that sensitize cancer cells to existing treatment regimens. In this regard, the present study explored the possibility of using small molecule inhibitors of p38MAPK/MK2 stress signaling pathways as potential agents to enhance the sensitivity of cancer cells with abrogated G1 checkpoint to the DNA damaging agent etoposide by specifically targeting the DNA damage-induced G2 cell cycle checkpoint. METHODS: We have applied CCK8 and FACS-based viability assays and cell cycle analysis to investigate the effect of small molecules SB203580 and MK2.III on the sensitivity of small cell lung cancer cells (SCLC) that lack the G1 checkpoint to the DNA damaging agent Etoposide when used in combination. We have also assessed the effectiveness of combination chemotherapy on tumor xenograft suppression with etoposide and MK2.III in immunosuppressed mice. In addition, additional CCK8 cell viability analysis of the MDA-MB-231 breast cancer cell line, and SW620, and SW480 colorectal cancer cell lines was performed. RESULTS: Results suggest that etoposide produces a profound effect on the cell cycle profile of cells in a manner that is consistent with the degree of cell viability that is seen using the viable cell assay. Results of the co-treatment experiments revealed that the p38/MK2 kinase inhibitors SB203580 and MK2.III both enhanced the DNA-damaging effects of etoposide on NCI-H69 cell viability in vitro. Results revealed that in vivo MK2.III was able to act as a chemosensitizer when used in combination with etoposide making NCI-H69 lung cancer cells sensitive to chemotherapeutic drug by 45% compared to single usage of the drug. We also report that MK2.III sensitizes metastatic cell lines SW-620 and MDA-MB-231 to etoposide but does not increase the sensitivity of non-metastasizing SW-480 colorectal cells to DNA damaging agent in vitro. CONCLUSION: Findings reported in this study provide evidence that specific inhibitors of MK2 may indeed improve overall cancer therapy; however, their effectiveness depends on cell types.

Rayless goldenrod (Isocoma pluriflora) poisoning in chicks (Gallus gallusdomesticus).

Rayless goldenrod (Isocoma spp.) and white snakeroot (Ageratina altissima) poison livestock, wildlife and humans. The suggested toxin for both plants is tremetone, a mixture of benzofuran ketones. However, plant tremetone concentrations often do not correlate with poisoning, and they have not been identified in contaminated milk that poisons nursing neonates. This suggests there may be unidentified metabolites or toxins. Previous studies using various cell culture and large animal models have been inconsistent with varying animal response that often require large doses. The objective of this work is to document the toxicity of rayless goldenrod in California white leghorn chicks, a susceptible small animal model, that would require relatively small amounts of plant material or purified toxins. Four groups of 15 chicks were gavaged with finely ground I. pluriflora at rates of 0, 1%, 2% or 3% of their bodyweight per day for 7 days. After 7 exposure days the chicks were euthanized, necropsied and tissues were collected, fixed and examined microscopically. Myocyte damage was evaluated using clinical signs, weight gain, serum biochemical changes, and histologic lesions and scores. The 3% group had focally extensive myocyte degeneration and necrosis most severely affecting leg muscles (semitendinosus, iliotibialis, peroneus longus and gastrocnemius). This was supported by serum biochemical changes and reduced weight gains. These findings indicate young chicks are a sensitive model of toxicity that may be useful to better identify the rayless goldenrod and white snakeroot toxins, including those unidentified toxins of transmammary poisoning.

Review: Nutritional regulation of muscle growth in neonatal swine.

Despite advances in the nutritional support of low birth weight and early-weaned piglets, most experience reduced extrauterine growth performance. To further optimize nutritional support and develop targeted intervention strategies, the mechanisms that regulate the anabolic response to nutrition must be fully understood. Knowledge gained in these studies represents a valuable intersection of agriculture and biomedical research, as low birth weight and early-weaned piglets face many of the same morbidities as preterm and low birth weight infants, including extrauterine growth faltering and reduced lean growth. While the reasons for poor growth performance are multifaceted, recent studies have increased our understanding of the role of nutrition in the regulation of skeletal muscle growth in the piglet. The purpose of this review is to summarize the published literature surrounding advances in the current understanding of the anabolic signaling that occurs after a meal and how this response is developmentally regulated in the neonatal pig. It will focus on the regulation of protein synthesis, and especially the upstream and downstream effectors surrounding the master protein kinase, mechanistic target of rapamycin complex 1 (mTORC1) that controls translation initiation. It also will examine the regulatory pathways associated with the postprandial anabolic agents, insulin and specific amino acids, that are upstream of mTORC1 and lead to its activation. Lastly, the integration of upstream signaling cascades by mTORC1 leading to the activation of translation initiation factors that regulate protein synthesis will be discussed. This review concludes that anabolic signaling cascades are stimulated by both insulin and amino acids, especially leucine, through separate pathways upstream of mTORC1, and that these stimulatory pathways result in mTORC1 activation and subsequent activation of downstream effectors that regulate translation initiation Additionally, it is concluded that this anabolic response is unique to the skeletal muscle of the neonate, resulting from increased sensitivity to the rise in both insulin and amino acid after a meal. However, this response is dampened in skeletal muscle of the low birth weight pig, indicative of anabolic resistance. Elucidation of the pathways and regulatory mechanisms surrounding protein synthesis and lean growth allow for the development of potential targeted therapeutics and intervention strategies both in livestock production and neonatal care.

Evolution-Informed Strategies for Combating Drug Resistance in Cancer.

The ever-changing nature of cancer poses the most difficult challenge oncologists face today. Cancer's remarkable adaptability has inspired many to work toward understanding the evolutionary dynamics that underlie this disease in hopes of learning new ways to fight it. Eco-evolutionary dynamics of a tumor are not accounted for in most standard treatment regimens, but exploiting them would help us combat treatment-resistant effectively. Here, we outline several notable efforts to exploit these dynamics and circumvent drug resistance in cancer.

Impact of selenium biofortification on production characteristics of forages grown following standard management practices in Oregon.

Introduction: Low selenium (Se) concentrations in soils and plants pose a health risk for ruminants consuming locally-grown forages. Previous studies have shown that Se concentrations in forages can be increased using soil-applied selenate amendments. However, the effects of foliar selenate amendments applied with traditional nitrogen-phosphorus-potassium-sulfur (NPKS) fertilizers on forage yields, and nutrient contents, and agronomic efficiencies are unknown. Methods: Using a split plot design, we determined the effects of springtime sodium selenate foliar amendment rates (0, 45, and 90 g Se ha-1) and NPKS application (none, NPK for grasses/PK for alfalfa, and NPKS/PKS fertilization at amounts adapted to meet local forage and soil requirements) on forage growth and N, S, and Se concentrations, yields, and agronomic efficiencies. This 2-year study was conducted across Oregon on four representative forage fields: orchardgrass (Dactylis glomerata L.) in Terrebonne (central Oregon), grass-clover mixture in Roseburg (southwestern Oregon), and both grass mixture and alfalfa (Medicago sativa L.) fields in Union (eastern Oregon). Results: Grasses grew poorly and were low in N content without NPK fertilization. Fertilization with NPK/PK promoted forage growth, increased forage N concentrations, and had to be co-applied with S when plant available S was low. Without Se amendment, forage Se concentrations were low and further decreased with NPKS/PKS fertilization. Selenate amendment linearly increased forage Se concentration without adversely affecting forage yields, N and S concentrations, or N and S agronomic efficiencies. Discussion: Importantly, S fertilization did not interfere with Se uptake in Se amended plots. In conclusion, co-application of NPKS/PKS fertilizers and foliar sodium selenate in springtime is an effective strategy to increase forage total Se concentrations, while maintaining optimal growth and quality of Oregon forages.

Chronic ethanol induces a pro-inflammatory switch in interleukin-1ß regulation of GABAergic signaling in the medial prefrontal cortex of male mice.

Neuroimmune pathways regulate brain function to influence complex behavior and play a role in several neuropsychiatric diseases, including alcohol use disorder (AUD). In particular, the interleukin-1 (IL-1) system has emerged as a key regulator of the brain's response to ethanol (alcohol). Here we investigated the mechanisms underlying ethanol-induced neuroadaptation of IL-1ß signaling at GABAergic synapses in the prelimbic region of the medial prefrontal cortex (mPFC), an area responsible for integrating contextual information to mediate conflicting motivational drives. We exposed C57BL/6J male mice to the chronic intermittent ethanol vapor-2 bottle choice paradigm (CIE-2BC) to induce ethanol dependence, and conducted ex vivo electrophysiology and molecular analyses. We found that the IL-1 system regulates basal mPFC function through its actions at inhibitory synapses on prelimbic layer 2/3 pyramidal neurons. IL-1ß can selectively recruit either neuroprotective (PI3K/Akt) or pro-inflammatory (MyD88/p38 MAPK) mechanisms to produce opposing synaptic effects. In ethanol naïve conditions, there was a strong PI3K/Akt bias leading to a disinhibition of pyramidal neurons. Ethanol dependence produced opposite IL-1 effects - enhanced local inhibition via a switch in IL-1ß signaling to the canonical pro-inflammatory MyD88 pathway. Ethanol dependence also increased cellular IL-1ß in the mPFC, while decreasing expression of downstream effectors (Akt, p38 MAPK). Thus, IL-1ß may represent a key neural substrate in ethanol-induced cortical dysfunction. As the IL-1 receptor antagonist (kineret) is already FDA-approved for other diseases, this work underscores the high therapeutic potential of IL-1 signaling/neuroimmune-based treatments for AUD.

Biomarkers and their potential for detecting livestock plant poisonings in Western North America.

The United States National Cancer Institute defines a biomarker as: "A biological molecule found in blood, other body fluids, or tissues that is a sign of a normal or abnormal process, or of a condition or disease." In Veterinary Medicine, biomarkers associated with plant poisonings of livestock have great utility. Since grazing livestock poisoned by toxic plants are often found dead, biomarkers of plant poisoning allow for a more rapid postmortem diagnosis and response to prevent further deaths. The presence and concentration of toxins in poisonous plants are biomarkers of risk for livestock poisoning that can be measured by the chemical analysis of plant material. More difficult is, the detection of plant toxins or biomarkers in biological samples from intoxicated or deceased animals. The purpose of this article is to review potential biomarkers of plant poisoning in grazing livestock in the Western North America including recently investigated non-invasive sampling techniques. Plants discussed include larkspur, lupine, water hemlock, swainsonine-containing plants, selenium-containing plants, and pyrrolizidine alkaloid containing plants. Other factors such as animal age and sex that affect plant biomarker concentrations in vivo are also discussed.

Using the Noncanonical Metallo-Amino Acid [Cu(II)(2,2'-Bipyridin-5-yl)]-alanine to Study the Structures of Proteins.

Genetic code expansion allows modification of the physical and chemical properties of proteins by the site-directed insertion of noncanonical amino acids. Here we exploit this technology for measuring nanometer-scale distances in proteins. (2,2'-Bipyridin-5-yl)alanine was incorporated into the green fluorescent protein (GFP) and used as an anchoring point for Cu(II) to create a spin-label. The incorporation of (2,2'-bipyridin-5-yl)alanine directly into the protein resulted in a high-affinity binding site for Cu(II) capable of outcompeting other binding positions in the protein. The resulting Cu(II)-spin label is very compact and not larger than a conventional amino acid. By using 94 GHz electron paramagnetic resonance (EPR) pulse dipolar spectroscopy we have been able to determine accurately the distance between two such spin-labels. Our measurements revealed that GFP dimers can adopt different quaternary conformations. The combination of spin-labeling using a paramagnetic nonconventional amino acid with high-frequency EPR techniques resulted in a sensitive method for studying the structures of proteins.

Crosstalkr: An open-source R package to facilitate drug target identification.

In the last few decades, interest in graph-based analysis of biological networks has grown substantially. Protein-protein interaction networks are one of the most common biological networks, and represent the molecular relationships between every known protein and every other known protein. Integration of these interactomic data into bioinformatic pipelines may increase the translational potential of discoveries made through analysis of multi-omic datasets. Crosstalkr provides a unified toolkit for drug target and disease subnetwork identification, two of the most common uses of protein protein interaction networks. First, crosstalkr enables users to download and leverage high-quality protein-protein interaction networks from online repositories. Users can then filter these large networks into manageable subnetworks using a variety of methods. For example, network filtration can be done using random walks with restarts, starting at the user-provided seed proteins. Affinity scores from a given random walk with restarts are compared to a bootstrapped null distribution to assess statistical significance. Random walks are implemented using sparse matrix multiplication to facilitate fast execution. Next, users can perform in-silico repression experiments to assess the relative importance of nodes in their network. At this step, users can supply protein or gene expression data to make node rankings more meaningful. The default behavior evaluates the human interactome. However, users can evaluate more than 1000 non-human protein-protein interaction networks as a result of integration with StringDB. It is a free, open-source R package designed to allow users to integrate functional analysis using the protein-protein interaction network into existing bioinformatic pipelines. A beta version of crosstalkr available on CRAN (https://cran.rstudio.com/web/packages/crosstalkr/index.html).

Associations of Maternal Age, Education, and Marital Status with HPV Vaccine Uptake and Hesitancy among United States Youth: A Cross-Sectional Analysis of the 2020 National Immunization Survey.

STUDY OBJECTIVE: Human papillomavirus (HPV) vaccination is proven to reduce the risk of HPV-associated cancers and lesions. Factors associated with HPV vaccine receipt or rejection have been studied, but specific maternal characteristics driving uptake among teens requires further investigation. The aim of this study was to examine maternal characteristics influencing teen vaccine uptake and intent to vaccinate. STUDY DESIGN: Cross-sectional analysis METHODS: We analyzed data on 27,320 teens aged 13-17 using the 2020 National Immunization Survey-Teen. We constructed regression models to determine the associations, via relative risk, between child vaccination status and maternal characteristics. RESULTS: Compared with mothers with less education, those with a college degree were significantly more likely to have their children receive HPV vaccination (RR = 1.18; 95% CI, 1.11-1.26). Compared to mothers under 35 years, those aged 35-44 (RR 1.07; 95% CI 1.01-1.14) and over 45 (RR = 1.13; 95% CI, 1.07-1.21) were more likely to provide HPV vaccination to their child. Among children not previously vaccinated (n = 12,098; N = 5,752,355), educated mothers were significantly less likely to report intent to vaccinate their child in the next year. There was no significant difference in vaccination rates in mothers who were married compared with never married (RR = 0.99; 95% CI, 0.97-1.02). CONCLUSION: Maternal education was the strongest predictor of teens receiving the HPV vaccine. Among mothers with teens not previously vaccinated, intent to obtain the HPV vaccine for their child was higher among mothers with less education compared with college-level educated mothers. Understanding maternal characteristics driving HPV vaccine hesitancy can inform targeted approaches to improve vaccine uptake in children. Additionally, adequate and consistent health messaging on the safety, efficacy, and benefits of HPV vaccination from health providers and public health agencies could increase uptake among adolescents and teens of vaccine-hesitant mothers.

Effects of Amount and Chemical Form of Selenium Amendments on Forage Selenium Concentrations and Species Profiles.

Selenium (Se) agronomic biofortification of plants is effective for alleviating Se deficiencies in human and livestock populations. Less is known about how higher selenate amendment rates, or how foliar compared with granular selenate amendments affect forage Se concentrations. Therefore, we compared the effects of a higher sodium selenate foliar amendment rate (900 vs. 90 g Se ha-1), and two selenate amendment methods (liquid foliar sodium selenate vs. granular slow-release Selcote Ultra® at 0, 45, and 90 g Se ha-1) on Se concentrations and Se species in forages across Oregon. The 10 × amendment rate (900 g Se ha-1) resulted in 6.4 × higher forage Se concentrations in the first cut (49.19 vs. 7.61 mg Se kg-1 plant DM, respectively) compared with the 90 g ha-1 amendment rate, indicating that forages can tolerate higher selenate amendment rates. Most Se was incorporated as SeMet (75%) in the harvested portion of the forage (37 mg Se kg-1 forage DM of the first cut) and only a limited amount was stored in the selenate reserve pool in the leaves (~ 5 mg Se kg-1 forage DM). Higher application rates of selenate amendment increased forage Se concentrations in first and second cuts, but carry over in subsequent years was negligible. Application of foliar selenate vs. granular Selcote Ultra® amendments, between 0 and 90 g Se ha-1, both resulted in a linear, dose-dependent increase in forage Se concentration. Amendments differed in their Se incorporation pattern (Se%), in that, first cut forage Se concentrations were higher with foliar selenate amendment and second, third, and residual (following spring) cut forage Se concentrations were higher with granular Selcote Ultra® amendment. Given the linear relationship between forage Se concentrations and whole-blood Se concentrations in livestock consuming Se-biofortified forage, we conclude that targeted grazing or other forage feeding strategies will allow producers to adapt to either selenate-amendment form.

Reinforcement Learning informs optimal treatment strategies to limit antibiotic resistance.

Antimicrobial resistance was estimated to be associated with 4.95 million deaths worldwide in 2019. It is possible to frame the antimicrobial resistance problem as a feedback-control problem. If we could optimize this feedback-control problem and translate our findings to the clinic, we could slow, prevent or reverse the development of high-level drug resistance. Prior work on this topic has relied on systems where the exact dynamics and parameters were known a priori. In this study, we extend this work using a reinforcement learning (RL) approach capable of learning effective drug cycling policies in a system defined by empirically measured fitness landscapes. Crucially, we show that is possible to learn effective drug cycling policies despite the problems of noisy, limited, or delayed measurement. Given access to a panel of 15 ß-lactam antibiotics with which to treat the simulated E. coli population, we demonstrate that RL agents outperform two naive treatment paradigms at minimizing the population fitness over time. We also show that RL agents approach the performance of the optimal drug cycling policy. Even when stochastic noise is introduced to the measurements of population fitness, we show that RL agents are capable of maintaining evolving populations at lower growth rates compared to controls. We further tested our approach in arbitrary fitness landscapes of up to 1024 genotypes. We show that minimization of population fitness using drug cycles is not limited by increasing genome size. Our work represents a proof-of-concept for using AI to control complex evolutionary processes.

Protein-lipid interactions and protein anchoring modulate the modes of association of the globular domain of the Prion protein and Doppel protein to model membrane patches.

The Prion protein is the molecular hallmark of the incurable prion diseases affecting mammals, including humans. The protein-only hypothesis states that the misfolding, accumulation, and deposition of the Prion protein play a critical role in toxicity. The cellular Prion protein (PrPC) anchors to the extracellular leaflet of the plasma membrane and prefers cholesterol- and sphingomyelin-rich membrane domains. Conformational Prion protein conversion into the pathological isoform happens on the cell surface. In vitro and in vivo experiments indicate that Prion protein misfolding, aggregation, and toxicity are sensitive to the lipid composition of plasma membranes and vesicles. A picture of the underlying biophysical driving forces that explain the effect of Prion protein - lipid interactions in physiological conditions is needed to develop a structural model of Prion protein conformational conversion. To this end, we use molecular dynamics simulations that mimic the interactions between the globular domain of PrPC anchored to model membrane patches. In addition, we also simulate the Doppel protein anchored to such membrane patches. The Doppel protein is the closest in the phylogenetic tree to PrPC, localizes in an extracellular milieu similar to that of PrPC, and exhibits a similar topology to PrPC even if the amino acid sequence is only 25% identical. Our simulations show that specific protein-lipid interactions and conformational constraints imposed by GPI anchoring together favor specific binding sites in globular PrPC but not in Doppel. Interestingly, the binding sites we found in PrPC correspond to prion protein loops, which are critical in aggregation and prion disease transmission barrier (ß2-α2 loop) and in initial spontaneous misfolding (α2-α3 loop). We also found that the membrane re-arranges locally to accommodate protein residues inserted in the membrane surface as a response to protein binding.

A proposed methodology for uncertainty extraction and verification in priority setting partnerships with the James Lind Alliance: an example from the Common Conditions Affecting the Hand and Wrist Priority Setting Partnership.

BACKGROUND: To report our recommended methodology for extracting and then confirming research uncertainties - areas where research has failed to answer a research question - derived from previously published literature during a broad scope Priority Setting Partnership (PSP) with the James Lind Alliance (JLA). METHODS: This process was completed in the UK as part of the PSP for "Common Conditions Affecting the Hand and Wrist", comprising of health professionals, patients and carers and reports the data (uncertainty) extraction phase of this. The PSP followed the robust methodology dictated by the JLA and sought to identify knowledge gaps, termed "uncertainties" by the JLA. Published Cochrane Systematic Reviews, Guidelines and Protocols, NICE (National Institute for Health and Care Excellence) Guidelines, and SIGN (Scottish Intercollegiate Guidelines Network) Guidelines were screened for documented "uncertainties". A robust method of screening, internally verifying and then checking uncertainties was adopted. This included independent screening and data extraction by multiple researchers and use of a PRISMA flowchart, alongside steering group consensus processes. Selection of research uncertainties was guided by the scope of the Common Conditions Affecting the Hand and Wrist PSP which focused on "common" hand conditions routinely treated by hand specialists, including hand surgeons and hand therapists limited to identifying questions concerning the results of intervention, and not the basic science or epidemiology behind disease. RESULTS: Of the 2358 records identified (after removal of duplicates) which entered the screening process, 186 records were presented to the PSP steering group for eligibility assessment; 79 were deemed within scope and included for the purpose of research uncertainty extraction (45 full Cochrane Reviews, 18 Cochrane Review protocols, 16 Guidelines). These yielded 89 research uncertainties, which were compared to the stakeholder survey, and added to the longlist where necessary; before derived uncertainties were checked against non-Cochrane published systematic reviews. CONCLUSIONS: In carrying out this work, beyond reporting on output of the Common Conditions Affecting the Hand and Wrist PSP, we detail the methodology and processes we hope can inform and facilitate the work of future PSPs and other evidence reviews, especially those with a broader scope beyond a single disease or condition.