Leveraging artificial intelligence to summarize abstracts in lay language for increasing research accessibility and transparency.

OBJECTIVE: Returning aggregate study results is an important ethical responsibility to promote trust and inform decision making, but the practice of providing results to a lay audience is not widely adopted. Barriers include significant cost and time required to develop lay summaries and scarce infrastructure necessary for returning them to the public. Our study aims to generate, evaluate, and implement ChatGPT 4 lay summaries of scientific abstracts on a national clinical study recruitment platform, ResearchMatch, to facilitate timely and cost-effective return of study results at scale. MATERIALS AND METHODS: We engineered prompts to summarize abstracts at a literacy level accessible to the public, prioritizing succinctness, clarity, and practical relevance. Researchers and volunteers assessed ChatGPT-generated lay summaries across five dimensions: accuracy, relevance, accessibility, transparency, and harmfulness. We used precision analysis and adaptive random sampling to determine the optimal number of summaries for evaluation, ensuring high statistical precision. RESULTS: ChatGPT achieved 95.9% (95% CI, 92.1-97.9) accuracy and 96.2% (92.4-98.1) relevance across 192 summary sentences from 33 abstracts based on researcher review. 85.3% (69.9-93.6) of 34 volunteers perceived ChatGPT-generated summaries as more accessible and 73.5% (56.9-85.4) more transparent than the original abstract. None of the summaries were deemed harmful. We expanded ResearchMatch's technical infrastructure to automatically generate and display lay summaries for over 750 published studies that resulted from the platform's recruitment mechanism. DISCUSSION AND CONCLUSION: Implementing AI-generated lay summaries on ResearchMatch demonstrates the potential of a scalable framework generalizable to broader platforms for enhancing research accessibility and transparency.

Chemical Modifications on the αvß6 Intergrin Targeting A20FMDV2 Peptide: A review.

Integrin proteins have received a significant increase in attention in recent scientific endeavors. The current trend uses the pre-established knowledge that the arginyl-glycyl-aspartic acid (RGD) structural motif present in the A20FMDV2 peptide is highly selective for the integrin class αvß6 which is overexpressed in many cancer types. This review will provide an extensive overview of the existing literature research to date to the best of our knowledge, highlighting significant improvements and drawbacks of structure-activity relationships (SAR) work undertaken, aiding future research to identify established SAR for a rational design of future A20FMDV2 mimetic inhibitors. Herein, the review aims to collate the existing structural chemical modifications present on A20FMDV2 in the literature to highlight key structural analogues that display more potent biological activity.

Scientific and religious beliefs are primarily shaped by testimony.

Understanding why individuals are more confident of the existence of invisible scientific phenomena (e.g., oxygen) than invisible religious phenomena (e.g., God) remains a puzzle. Departing from conventional explanations linking ontological beliefs to direct experience, we introduce a model positing that testimony predominantly shapes beliefs in both scientific and religious domains. Distinguishing direct experience (personal observation) from cultural input (testimony-based evidence), we argue that even apparently direct experiences often stem from others' testimony. Our analysis indicates that variability in direct experience cannot explain belief disparities between science and religion, within each domain, or across cultures. Instead, variability in testimony is the primary driver of ontological beliefs. We present developmental evidence for testimony-based beliefs and elucidate the mechanisms underlying their impact.

Impact of financial compensation on enrollment and participation in a remote, mobile-app based research study.

Background: There is no consensus on how to determine appropriate financial compensation for research recruitment. Selecting incentive amounts that are reasonable and respectful, without undue inducement, remains challenging. Previously, we demonstrated that incentive amount significantly impacts participants' willingness to complete various hypothetical research activities. Here we further explore this relationship in a mock decentralized study. Methods: Adult ResearchMatch volunteers were invited to join a prospective study where interested individuals were given an opportunity to view details for a study along with participation requirements, then offered a randomly generated compensation amount between $0 and $50 to enroll and participate. Individuals agreeing to participate were then asked to complete tasks using a remote mobile application (MyCap), for two weeks. Tasks included a weekly survey, a daily gratitude journal and daily phone tapping task. Results: Willingness to participate was 85% across all incentive levels but not significantly impacted by amount. Task completion appeared to increase as a function of compensation until a plateau at $25. While participants described the study as low burden and reported that compensation was moderately important to their decision to join, only 31% completed all study tasks. Conclusion: While offering compensation in this study did not have a strong effect on enrollment rate, this work provides insight into participant motivation when joining and participating in studies employing mobile applications.

Religious polarization and justification of belief in invisible scientific versus religious entities.

Children and adults express greater confidence in the existence of invisible scientific as compared to invisible religious entities. To further examine this differential confidence, 5- to 11-year-old Turkish children and their parents (N = 174, 122 females) from various regions in Türkiye, a country with an ongoing tension between secularism and religion, were tested in 2021 for their belief in invisible entities. Participants expressed more confidence in the existence of scientific than religious entities. For scientific entities, children justified their belief primarily by elaborating on the properties of the entity, rather than referring to the testimonial source of their judgment. This pattern was reversed for religious entities, arguably, highlighting the role of polarization in shaping the testimony children typically hear.

Identifying erroneous height and weight values from adult electronic health records in the All of Us research program.

INTRODUCTION: Electronic Health Records (EHR) are a useful data source for research, but their usability is hindered by measurement errors. This study investigated an automatic error detection algorithm for adult height and weight measurements in EHR for the All of Us Research Program (All of Us). METHODS: We developed reference charts for adult heights and weights that were stratified on participant sex. Our analysis included 4,076,534 height and 5,207,328 wt measurements from âˆ¼ 150,000 participants. Errors were identified using modified standard deviation scores, differences from their expected values, and significant changes between consecutive measurements. We evaluated our method with chart-reviewed heights (8,092) and weights (9,039) from 250 randomly selected participants and compared it with the current cleaning algorithm in All of Us. RESULTS: The proposed algorithm classified 1.4 % of height and 1.5 % of weight errors in the full cohort. Sensitivity was 90.4 % (95 % CI: 79.0-96.8 %) for heights and 65.9 % (95 % CI: 56.9-74.1 %) for weights. Precision was 73.4 % (95 % CI: 60.9-83.7 %) for heights and 62.9 (95 % CI: 54.0-71.1 %) for weights. In comparison, the current cleaning algorithm has inferior performance in sensitivity (55.8 %) and precision (16.5 %) for height errors while having higher precision (94.0 %) and lower sensitivity (61.9 %) for weight errors. DISCUSSION: Our proposed algorithm outperformed in detecting height errors compared to weights. It can serve as a valuable addition to the current All of Us cleaning algorithm for identifying erroneous height values.

Selecting trial centers using a standardized, automated site assessment survey instrument (SASI).

BACKGROUND: To improve the site selection process for clinical trials, we expanded a site survey to include standardized assessments of site commitment time, team experience, feasibility of tight timelines, and local medical community equipoise as factors that might better predict performance. We also collected contact information about institutional research services ahead of site onboarding. AIM: As a first step, we wanted to confirm that an expanded survey could be feasible and generalizable-that asking site teams for more details upfront was acceptable and that the survey could be completed in a reasonable amount of time, despite the assessment length. METHODS: A standardized, two-part Site Assessment Survey Instrument (SASI), examining qualitative components and with multiple contact list sections, was developed using a publicly accessible dashboard and later transferred to a REDCap platform. After multiple rounds of internal testing, the SASI was deployed 11 times for multicenter trials. Follow-up questionnaires were sent to site teams to confirm that an expanded survey instrument is acceptable to the research community and could be completed during a brief work shift. RESULTS: Respondents thought the SASI collected useful and relevant information about their sites (100%). Sites were "comfortable" (90%) supplying detailed information early in the site selection process and 57% completed the SASI in one to two hours. CONCLUSIONS: Coordinating centers and sites found the SASI tool to be acceptable and helpful when collecting data in consideration of multicenter trial site selection.

[Severe acute pancreatitis secondary to hypertriglyceridemia as the onset of Type 1 Diabetes Mellitus in the pediatric age]. / Pancreatitis aguda grave secundaria a hipertrigliceridemia como debut de Diabetes Mellitus Tipo 1 en edad pediátrica.

Hypertriglyceridemia (HTG)-induced acute pancreatitis (AP) secondary to insulin deficiency following the onset of type 1 diabetes mellitus (T1DM) is a rare but serious complication in children. OBJECTIVE: To describe the diagnosis and treatment of severe HTG and to emphasize the need for timely diagnosis of T1DM. CLINICAL CASE: A 15-year-old female adolescent with a history of overweight presented with a two-weeks history of fever, anorexia, and diffuse abdominal pain. Laboratory tests revealed triglycerides of 17,580 mg/dL, lipase of 723 U/L, and blood glucose of 200 mg/dL. An abdominal CT scan showed an enlarged and edematous pancreas. She was hospitalized with a diagnosis of AP and severe HTG, which progressed to acute necro-hemorrhagic pancreatitis. Treatment included continuous intravenous insulin infusion until triglyceride levels decreased. Upon discontinuation of insulin, fasting hyperglycemia (206 mg/dL) and metabolic acidosis recurred, therefore DM was suspected. Upon targeted questioning, a history of polydipsia, polyuria, and weight loss during the last 3 months stood out. Glycated hemoglobin was markedly elevated (14.7%). Insulin therapy was optimized, achieving stabilization of laboratory parameters after 15 days of treatment and complete anatomical resolution of pancreatic involvement at one year of follow-up. CONCLUSIONS: The presence of severe HTG in pediatrics compels us to consider its secondary causes, such as the onset of T1DM. It is crucial to improve the ability to diagnose T1DM early, as it may present with infrequent and high-risk presentations for the patient.

Classification of Breast Implant Malposition.

BACKGROUND: Implant malposition is a well-recognized complication when using prosthetic implants in the breast for both reconstructive and aesthetic indications. However, to date, no objective classification system has been described. OBJECTIVES: This study presents a prospective trial of an objective and reproducible classification system for implant malposition formulated using retrospective data from a large cohort of patients with implant malposition. METHODS: The authors retrospectively analyzed the degree of medial/lateral and inferior/superior implant malposition relative to their optimal position within the breast footprint in a series of 189 breasts (n = 100 patients). An objective classification system for implant malposition was devised and then applied to a prospective cohort of 53 breasts in 28 patients with implant malposition. RESULTS: The degree of malposition in a single or combination of axes was categorised according to the distance from the ideal breast footprint and measured in centimeters (cms). The classification system incorporated the axis of malposition and distance to generate a treatment decision-making guide. Cases of Grade 1 malposition did not warrant surgical intervention, whilst surgical correction was warranted in all Grade 3 cases.In the combined patient cohort (n = 242 breasts, 128 patients), lateral, inferior, medial and superior displacement ranged between grades 1-3. There was no inter-observer variability in the grades assigned to nine out of ten patients in the prospective group. CONCLUSIONS: We have created a simple and reproducible classification system for implant malposition that allows surgeons to objectively record the extent of malposition, guides surgical decision-making and can be used to document the results of any intervention.

Illuminating the landscape of high-level clinical trial opportunities in the All of Us Research Program.

OBJECTIVE: With its size and diversity, the All of Us Research Program has the potential to power and improve representation in clinical trials through ancillary studies like Nutrition for Precision Health. We sought to characterize high-level trial opportunities for the diverse participants and sponsors of future trial investment. MATERIALS AND METHODS: We matched All of Us participants with available trials on ClinicalTrials.gov based on medical conditions, age, sex, and geographic location. Based on the number of matched trials, we (1) developed the Trial Opportunities Compass (TOC) to help sponsors assess trial investment portfolios, (2) characterized the landscape of trial opportunities in a phenome-wide association study (PheWAS), and (3) assessed the relationship between trial opportunities and social determinants of health (SDoH) to identify potential barriers to trial participation. RESULTS: Our study included 181 529 All of Us participants and 18 634 trials. The TOC identified opportunities for portfolio investment and gaps in currently available trials across federal, industrial, and academic sponsors. PheWAS results revealed an emphasis on mental disorder-related trials, with anxiety disorder having the highest adjusted increase in the number of matched trials (59% [95% CI, 57-62]; P < 1e-300). Participants from certain communities underrepresented in biomedical research, including self-reported racial and ethnic minorities, had more matched trials after adjusting for other factors. Living in a nonmetropolitan area was associated with up to 13.1 times fewer matched trials. DISCUSSION AND CONCLUSION: All of Us data are a valuable resource for identifying trial opportunities to inform trial portfolio planning. Characterizing these opportunities with consideration for SDoH can provide guidance on prioritizing the most pressing barriers to trial participation.

Identifying and Extracting Rare Diseases and Their Phenotypes with Large Language Models.

Purpose: Phenotyping is critical for informing rare disease diagnosis and treatment, but disease phenotypes are often embedded in unstructured text. While natural language processing (NLP) can automate extraction, a major bottleneck is developing annotated corpora. Recently, prompt learning with large language models (LLMs) has been shown to lead to generalizable results without any (zero-shot) or few annotated samples (few-shot), but none have explored this for rare diseases. Our work is the first to study prompt learning for identifying and extracting rare disease phenotypes in the zero- and few-shot settings. Methods: We compared the performance of prompt learning with ChatGPT and fine-tuning with BioClinicalBERT. We engineered novel prompts for ChatGPT to identify and extract rare diseases and their phenotypes (e.g., diseases, symptoms, and signs), established a benchmark for evaluating its performance, and conducted an in-depth error analysis. Results: Overall, fine-tuning BioClinicalBERT resulted in higher performance (F1 of 0.689) than ChatGPT (F1 of 0.472 and 0.610 in the zero- and few-shot settings, respectively). However, ChatGPT achieved higher accuracy for rare diseases and signs in the one-shot setting (F1 of 0.778 and 0.725). Conversational, sentence-based prompts generally achieved higher accuracy than structured lists. Conclusion: Prompt learning using ChatGPT has the potential to match or outperform fine-tuning BioClinicalBERT at extracting rare diseases and signs with just one annotated sample. Given its accessibility, ChatGPT could be leveraged to extract these entities without relying on a large, annotated corpus. While LLMs can support rare disease phenotyping, researchers should critically evaluate model outputs to ensure phenotyping accuracy.

Patient-perceived factors influencing physical activity sensor use in stroke prevention and rehabilitation: A thematic synthesis protocol.

INTRODUCTION: While the putative benefits of "fitness trackers" continue to fuel a booming consumer market, results of device-based clinical interventions remain remarkably mixed. This study will explore factors influencing wearable physical activity (PA) sensor use in the context of stroke prevention and rehabilitation for older adults. The findings of this thematic synthesis will provide insights into factors influencing the use of PA sensors in stroke which may inform more effective device-based interventions. METHODS AND ANALYSIS: Thematic synthesis as a formal method described by Thomas and Arden can be used within a systematic review to synthesize primary qualitative research. Accordingly, the proposed study will systematically search bibliographic databases for relevant peer-reviewed papers and synthesize coded thematic data within included papers. The quality of papers will be assessed using the JBI Critical Appraisal Checklist for Qualitative Research. Patterns in the text will be coded, preliminary data visualised, and higher-level analytical themes discerned to explain factors influencing the use of PA sensors in older stroke patients. DISCUSSION: This study does not require ethics approval. Results are expected to be available by June 2024. Data from the thematic synthesis will provide insights into barriers and facilitators influencing the use of wearable PA sensors in stroke and older adults at risk, and implications these factors have for the design of effective device-based interventions. TRIAL REGISTRATION: Systematic review registration: PROSPERO registration number: CRD42020211472. https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42020211472.

Empowering the Participant Voice (EPV): Design and implementation of collaborative infrastructure to collect research participant experience feedback at scale.

Empowering the Participant Voice (EPV) is an NCATS-funded six-CTSA collaboration to develop, demonstrate, and disseminate a low-cost infrastructure for collecting timely feedback from research participants, fostering trust, and providing data for improving clinical translational research. EPV leverages the validated Research Participant Perception Survey (RPPS) and the popular REDCap electronic data-capture platform. This report describes the development of infrastructure designed to overcome identified institutional barriers to routinely collecting participant feedback using RPPS and demonstration use cases. Sites engaged local stakeholders iteratively, incorporating feedback about anticipated value and potential concerns into project design. The team defined common standards and operations, developed software, and produced a detailed planning and implementation Guide. By May 2023, 2,575 participants diverse in age, race, ethnicity, and sex had responded to approximately 13,850 survey invitations (18.6%); 29% of responses included free-text comments. EPV infrastructure enabled sites to routinely access local and multi-site research participant experience data on an interactive analytics dashboard. The EPV learning collaborative continues to test initiatives to improve survey reach and optimize infrastructure and process. Broad uptake of EPV will expand the evidence base, enable hypothesis generation, and drive research-on-research locally and nationally to enhance the clinical research enterprise.

Bioinformatic, Biochemical, and Immunological Mining of MHC Class I Restricted T Cell Epitopes for a Marburg Nucleoprotein Microparticle Vaccine.

The Marburg virus (MARV), the virus responsible for Marburg hemorrhagic fever (MHF), is considered a top-priority pathogen for vaccine development. Recent outbreaks in Equatorial Africa have highlighted the urgency of MARV because of its high fatality rate and historical concerns about potential weaponization. Currently, there are no licensed vaccines for MARV. Existing vaccine candidates rely on attenuated recombinant vesicular stomatitis virus carrying MARV glycoprotein (VSVΔG) or the chimpanzee replication-defective adenovirus 3 vector ChAd3-MARV. Although these platforms provide significant protection in animal models, they face challenges because of their limited thermal stability and the need for cold storage during deployment in resource-poor areas. An alternative approach involves using adjuvanted poly (lactic-co-glycolic acid) (PLGA) microparticles loaded with synthetic peptides representing MHC class I-restricted T cell epitopes. This vaccine platform has demonstrated effectiveness in protecting against SARS-CoV-2 and EBoV disease in animal models and has the advantage of not requiring cold storage and remaining stable at room temperature for over six months. This report outlines the design, manufacturing, and in vivo immunogenicity testing of PLGA microparticle human vaccines designed to prevent Marburg hemorrhagic fever.

Physical Activity and Incident Obesity Across the Spectrum of Genetic Risk for Obesity.

Importance: Despite consistent public health recommendations, obesity rates in the US continue to increase. Physical activity recommendations do not account for individual genetic variability, increasing risk of obesity. Objective: To use activity, clinical, and genetic data from the All of Us Research Program (AoURP) to explore the association of genetic risk of higher body mass index (BMI) with the level of physical activity needed to reduce incident obesity. Design, Setting, and Participants: In this US population-based retrospective cohort study, participants were enrolled in the AoURP between May 1, 2018, and July 1, 2022. Enrollees in the AoURP who were of European ancestry, owned a personal activity tracking device, and did not have obesity up to 6 months into activity tracking were included in the analysis. Exposure: Physical activity expressed as daily step counts and a polygenic risk score (PRS) for BMI, calculated as weight in kilograms divided by height in meters squared. Main Outcome and Measures: Incident obesity (BMI ≥30). Results: A total of 3124 participants met inclusion criteria. Among 3051 participants with available data, 2216 (73%) were women, and the median age was 52.7 (IQR, 36.4-62.8) years. The total cohort of 3124 participants walked a median of 8326 (IQR, 6499-10 389) steps/d over a median of 5.4 (IQR, 3.4-7.0) years of personal activity tracking. The incidence of obesity over the study period increased from 13% (101 of 781) to 43% (335 of 781) in the lowest and highest PRS quartiles, respectively (P = 1.0 × 10-20). The BMI PRS demonstrated an 81% increase in obesity risk (P = 3.57 × 10-20) while mean step count demonstrated a 43% reduction (P = 5.30 × 10-12) when comparing the 75th and 25th percentiles, respectively. Individuals with a PRS in the 75th percentile would need to walk a mean of 2280 (95% CI, 1680-3310) more steps per day (11 020 total) than those at the 50th percentile to have a comparable risk of obesity. To have a comparable risk of obesity to individuals at the 25th percentile of PRS, those at the 75th percentile with a baseline BMI of 22 would need to walk an additional 3460 steps/d; with a baseline BMI of 24, an additional 4430 steps/d; with a baseline BMI of 26, an additional 5380 steps/d; and with a baseline BMI of 28, an additional 6350 steps/d. Conclusions and Relevance: In this cohort study, the association between daily step count and obesity risk across genetic background and baseline BMI were quantified. Population-based recommendations may underestimate physical activity needed to prevent obesity among those at high genetic risk.

Trusting young children to help causes them to cheat less.

Trust and honesty are essential for human interactions. Philosophers since antiquity have long posited that they are causally linked. Evidence shows that honesty elicits trust from others, but little is known about the reverse: does trust lead to honesty? Here we experimentally investigated whether trusting young children to help can cause them to become more honest (total N = 328 across five studies; 168 boys; mean age, 5.94 years; s.d., 0.28 years). We observed kindergarten children's cheating behaviour after they had been entrusted by an adult to help her with a task. Children who were trusted cheated less than children who were not trusted. Our study provides clear evidence for the causal effect of trust on honesty and contributes to understanding how social factors influence morality. This finding also points to the potential of using adult trust as an effective method to promote honesty in children.

Synthesis, Structure-Activity Relationship Study, Bioactivity, and Nephrotoxicity Evaluation of the Proposed Structure of the Cyclic Lipodepsipeptide Brevicidine B.

The brevicidines represent a novel class of nonribosomal antimicrobial peptides that possess remarkable potency and selectivity toward highly problematic and resistant Gram-negative pathogenic bacteria. A recently discovered member of the brevicidine family, coined brevicidine B (2), comprises a single amino acid substitution (from d-Tyr2 to d-Phe2) in the amino acid sequence of the linear moiety of brevicidine (1) and was reported to exhibit broader antimicrobial activity against both Gram-negative (MIC = 2-4 µgmL-1) and Gram-positive (MIC = 2-8 µgmL-1) pathogens. Encouraged by this, we herein report the first total synthesis of the proposed structure of brevicidine B (2), building on our previously reported synthetic strategy to access brevicidine (1). In agreement with the original isolation paper, pleasingly, synthetic 2 demonstrated antimicrobial activity toward Escherichia coli, Pseudomonas aeruginosa, and Klebsiella pneumoniae (MIC = 4-8 µgmL-1). Interestingly, however, synthetic 2 was inactive toward all of the tested Gram-positive pathogens, including methicillin-resistant Staphylococcus aureus strains. Substitution of d-Phe2 with its enantiomer, and other hydrophobic residues, yields analogues that were either inactive or only exhibited activity toward Gram-negative strains. The striking difference in the biological activity of our synthetic 2 compared to the reported natural compound warrants the re-evaluation of the original natural product for purity or possible differences in relative configuration. Finally, the evaluation of synthetic 1 and 2 in a human kidney organoid model of nephrotoxicity revealed substantial toxicity of both compounds, although 1 was less toxic than 2 and polymyxin B. These results indicate that modification to position 2 may afford a strategy to mitigate the nephrotoxicity of brevicidine.

Poly-γ-glutamylation of biomolecules.

Poly-γ-glutamate tails are a distinctive feature of archaeal, bacterial, and eukaryotic cofactors, including the folates and F420. Despite decades of research, key mechanistic questions remain as to how enzymes successively add glutamates to poly-γ-glutamate chains while maintaining cofactor specificity. Here, we show how poly-γ-glutamylation of folate and F420 by folylpolyglutamate synthases and γ-glutamyl ligases, non-homologous enzymes, occurs via processive addition of L-glutamate onto growing γ-glutamyl chain termini. We further reveal structural snapshots of the archaeal γ-glutamyl ligase (CofE) in action, crucially including a bulged-chain product that shows how the cofactor is retained while successive glutamates are added to the chain terminus. This bulging substrate model of processive poly-γ-glutamylation by terminal extension is arguably ubiquitous in such biopolymerisation reactions, including addition to folates, and demonstrates convergent evolution in diverse species from archaea to humans.

Single-molecule detection and super-resolution imaging with a portable and adaptable 3D-printed microscopy platform (Brick-MIC).

Over the past decades, single-molecule and super-resolution microscopy have advanced and represent essential tools for life science research. There is,however, a growing gap between the state-of-the-art and what is accessible to biologists, biochemists, medical researchers or labs with financial constraints. To bridge this gap, we introduce Brick-MIC, a versatile and affordable open-source 3D-printed micro-spectroscopy and imaging platform. Brick-MIC enables the integration of various fluorescence imaging techniques with single-molecule resolution within a single platform and exchange between different modalities within minutes. We here present variants of Brick-MIC that facilitate single-molecule fluorescence detection, fluorescence correlation spectroscopy and super-resolution imaging (STORM and PAINT). Detailed descriptions of the hardware and software components, as well as data analysis routines are provided, to allow non-optics specialist to operate their own Brick-MIC with minimal effort and investments. We foresee that our affordable, flexible, and open-source Brick-MIC platform will be a valuable tool for many laboratories worldwide.

Polymyxin B and ethylenediaminetetraacetic acid act synergistically against Pseudomonas aeruginosa and Staphylococcus aureus.

Polymyxin B and ethylenediaminetetraacetic acid are antimicrobials possessing antibiofilm activity. They act by displacement and chelation, respectively, of divalent cations in bacterial membranes and may therefore act synergistically when applied in combination. If so, this combination of agents may be useful for the treatment of diseases like cystic fibrosis (CF), in which biofilms are present on the respiratory epithelium. We used checkerboard assays to investigate the synergy between these agents using reference strains Pseudomonas aeruginosa ATCC 27853 and Staphylococcus aureus ATCC 6538 in planktonic form. We then determined the efficacy of each agent against biofilms of both species grown on 96-pin lids and proceeded to combination testing against the P. aeruginosa reference strain and 10 clinical isolates from patients with CF. Synergism was observed for planktonic forms of both species and for biofilms of P. aeruginosa. The susceptibility of biofilms of P. aeruginosa clinical isolates to these agents was variable compared to the laboratory reference strain. This combination of agents may be useful in the management of biofilm-associated conditions, particularly those amenable to topical therapies. These results provide a basis upon which the antimicrobial and antibiofilm efficacy of preparations containing these agents may be enhanced.IMPORTANCEBacteria living in biofilms produce a protective matrix which makes them difficult to kill. Patients with severe respiratory disease often have biofilms. Polymyxin B is an antibiotic commonly used in topical medications, such as eye drops and nasal sprays. Ethylenediaminetetraacetic acid (EDTA) is used widely as a preservative in medication but also has antimicrobial properties. It has been hypothesized that Polymyxin B and EDTA could have a synergistic relationship: when used in combination their antimicrobial effect is enhanced. Here, we evaluated the levels at which Polymyxin B and EDTA work together to kill common pathogens Pseudomonas aeruginosa and Staphylococcus aureus. We found that Polymyxin B and EDTA were synergistic. This synergy may be useful in the management of planktonic infection with P. aeruginosa and S. aureus, or biofilm infection with P. aeruginosa. This synergy may be beneficial in the treatment of respiratory biofilms, in which P. aeruginosa biofilms are common.