Alternative roles for Pseudomonas aeruginosa bacteriocins

Bacteriocins are multi-protein assemblies that bear striking resemblance to bacteriophage (virus) tails. Bacteriocins are an extracellular contractile injection system that kill closely related bacteria by puncturing their cell membrane. Mounting evidence suggests that besides interbacterial competition, bacteriocins also mediate interactions between bacteria and diverse eukaryotic hosts by assembling extracellular hexagonal-bacteriocin arrays composed of numerous bacteriocin particles. Pseudomonas aeruginosa is an opportunistic bacterial pathogen that produces bacteriocins called R2 pyocins which lyse susceptible bacteria. Based on homology to other contractile injection systems, we hypothesize that P. aeruginosa produces bacteriocin arrays that modulate host responses during infection. We have developed a method to quantify R2 pyocins utilizing the lysis of susceptible strains of P. aeruginosa. We are currently applying this quantification method to optimize the production and purification of pyocins to test in host-pathogen models. We have also generated a fluorescently labelled R2 pyocin for the detection of bacteriocin arrays using fluorescence microscopy. These experiments are essential to enable future evaluation of the effect of R2 pyocins on host pathogen interactions

The Mexican Cognitive Aging Ancillary Study (Mex-Cog): Study Design and Methods

Objective: Describe the protocol sample and instruments of the Cognitive Aging Ancillary Study in Mexico (Mex-Cog). The study performs an in-depth cognitive assessment in a subsample of older adults of the ongoing Mexican Health and Aging Study (MHAS). The Mex-Cog is part of the Harmonized Cognitive Assessment Protocol (HCAP) design to facilitate cross-national comparisons of the prevalence and trends of dementia in aging populations around the world, funded by the National Institute on Aging (NIA). Methods: The study protocol consists of a cognitive assessment instrument for the target subject and an informant questionnaire. All cognitive measures were selected and adapted by a team of experts from different ongoing studies following criteria to warrant reliable and comparable cognitive instruments. The informant questionnaire is from the 10/66 Dementia Study in Mexico. Results: A total of 2,265 subjects aged 55-104 years participated, representing a 70% response rate. Validity analyses showed the adequacy of the content validity, proper quality-control procedures that sustained data integrity, high reliability, and internal structure. Conclusions: The Mex-Cog study provides in-depth cognitive data that enhances the study of cognitive aging in two ways. First, linking to MHAS longitudinal data on cognition, health, genetics, biomarkers, economic resources, health care, family arrangements, and psychosocial factors expands the scope of information on cognitive impairment and dementia among Mexican adults. Second, harmonization with other similar studies around the globe promotes cross-national studies on cognition with comparable data. Mex-Cog data is publicly available at no cost to researchers

Adjusted Tornado Probabilities

Tornado occurrence rates computed from the available reports are biased low relative to the unknown true rates. To correct for this low bias, the authors demonstrate a method to estimate the annual probability of being struck by a tornado that uses the average report density estimated as a function of distance from nearest city/town center. The method is demonstrated on Kansas and then applied to 15 other tornado-prone states from Nebraska to Tennessee. States are ranked according to their adjusted tornado rate and comparisons are made with raw rates published elsewhere. The adjusted rates, expressed as return periods, arestates, including Alabama, Mississippi, Arkansas, and Oklahoma. The expected annual number of people exposed to tornadoes is highest for Illinois followed by Alabama and Indiana. For the four states with the highest tornado rates, exposure increases since 1980 are largest for Oklahoma (24%) and Alabama (23%)

Quantifying Co-Oligomer Formation by α-Synuclein.

Small oligomers of the protein α-synuclein (αS) are highly cytotoxic species associated with Parkinson's disease (PD). In addition, αS can form co-aggregates with its mutational variants and with other proteins such as amyloid-β (Aβ) and tau, which are implicated in Alzheimer's disease. The processes of self-oligomerization and co-oligomerization of αS are, however, challenging to study quantitatively. Here, we have utilized single-molecule techniques to measure the equilibrium populations of oligomers formed in vitro by mixtures of wild-type αS with its mutational variants and with Aβ40, Aβ42, and a fragment of tau. Using a statistical mechanical model, we find that co-oligomer formation is generally more favorable than self-oligomer formation at equilibrium. Furthermore, self-oligomers more potently disrupt lipid membranes than do co-oligomers. However, this difference is sometimes outweighed by the greater formation propensity of co-oligomers when multiple proteins coexist. Our results suggest that co-oligomer formation may be important in PD and related neurodegenerative diseases.The authors are grateful for financial support provided by Dr Tayyeb Hussain Scholarship and the ERC (669237) (M. Iljina), the Schiff Foundation (A. Dear), Alzheimer’s Research UK and Marie-Curie Individual Fellowship (S. De), a fellowship from Fondazione Caritro, Trento (BANDO 2017 PER PROGETTI DI RICERCA SVOLTI DA GIOVANI RICERCATORI POST-DOC) (L. Tosatto), the Boehringer Ingelheim Fonds and the Studienstiftung des deutschen Volkes (P. Flagmeier), the Centre for Misfolding Diseases (A. Dear, P. Flagmeier, C. Dobson, T. Knowles), the ERC (669237) and the Royal Society (D. Klenerman). We are grateful to S. Preet for the expression and purification of A90C ɑS. We thank Y. Ye for providing tau k18

Conflicts of Interest in the Assessment of Chemicals, Waste, and Pollution

Pollution by chemicals and waste impacts human and ecosystem health on regional, national, and global scales, resulting, together with climate change and biodiversity loss, in a triple planetary crisis. Consequently, in 2022, countries agreed to establish an intergovernmental science–policy panel (SPP) on chemicals, waste, and pollution prevention, complementary to the existing intergovernmental science–policy bodies on climate change and biodiversity. To ensure the SPP’s success, it is imperative to protect it from conflicts of interest (COI). Here, we (i) define and review the implications of COI, and its relevance for the management of chemicals, waste, and pollution; (ii) summarize established tactics to manufacture doubt in favor of vested interests, i.e., to counter scientific evidence and/or to promote misleading narratives favorable to financial interests; and (iii) illustrate these with selected examples. This analysis leads to a review of arguments for and against chemical industry representation in the SPP’s work. We further (iv) rebut an assertion voiced by some that the chemical industry should be directly involved in the panel’s work because it possesses data on chemicals essential for the panel’s activities. Finally, (v) we present steps that should be taken to prevent the detrimental impacts of COI in the work of the SPP. In particular, we propose to include an independent auditor’s role in the SPP to ensure that participation and processes follow clear COI rules. Among others, the auditor should evaluate the content of the assessments produced to ensure unbiased representation of information that underpins the SPP’s activities

Machine learning in marine ecology: an overview of techniques and applications

Machine learning covers a large set of algorithms that can be trained to identify patterns in data. Thanks to the increase in the amount of data and computing power available, it has become pervasive across scientific disciplines. We first highlight why machine learning is needed in marine ecology. Then we provide a quick primer on machine learning techniques and vocabulary. We built a database of ∼1000 publications that implement such techniques to analyse marine ecology data. For various data types (images, optical spectra, acoustics, omics, geolocations, biogeochemical profiles, and satellite imagery), we present a historical perspective on applications that proved influential, can serve as templates for new work, or represent the diversity of approaches. Then, we illustrate how machine learning can be used to better understand ecological systems, by combining various sources of marine data. Through this coverage of the literature, we demonstrate an increase in the proportion of marine ecology studies that use machine learning, the pervasiveness of images as a data source, the dominance of machine learning for classification-type problems, and a shift towards deep learning for all data types. This overview is meant to guide researchers who wish to apply machine learning methods to their marine datasets.Machine learning in marine ecology: an overview of techniques and applicationspublishedVersio

An Integrated Process for Co-Developing and Implementing Written and Computable Clinical Practice Guidelines

The goal of this article is to describe an integrated parallel process for the co-development of written and computable clinical practice guidelines (CPGs) to accelerate adoption and increase the impact of guideline recommendations in clinical practice. From February 2018 through December 2021, interdisciplinary work groups were formed after an initial Kaizen event and using expert consensus and available literature, produced a 12-phase integrated process (IP). The IP includes activities, resources, and iterative feedback loops for developing, implementing, disseminating, communicating, and evaluating CPGs. The IP incorporates guideline standards and informatics practices and clarifies how informaticians, implementers, health communicators, evaluators, and clinicians can help guideline developers throughout the development and implementation cycle to effectively co-develop written and computable guidelines. More efficient processes are essential to create actionable CPGs, disseminate and communicate recommendations to clinical end users, and evaluate CPG performance. Pilot testing is underway to determine how this IP expedites the implementation of CPGs into clinical practice and improves guideline uptake and health outcomes

Proceedings of Patient Reported Outcome Measure’s (PROMs) Conference Oxford 2017: Advances in Patient Reported Outcomes Research

A33-Effects of Out-of-Pocket (OOP) Payments and Financial Distress on Quality of Life (QoL) of People with Parkinson’s (PwP) and their Carer

Another Shipment of Six Short-Period Giant Planets from TESS

We present the discovery and characterization of six short-period, transiting giant planets from NASA's Transiting Exoplanet Survey Satellite (TESS) -- TOI-1811 (TIC 376524552), TOI-2025 (TIC 394050135), TOI-2145 (TIC 88992642), TOI-2152 (TIC 395393265), TOI-2154 (TIC 428787891), & TOI-2497 (TIC 97568467). All six planets orbit bright host stars (8.9 <G< 11.8, 7.7 <K< 10.1). Using a combination of time-series photometric and spectroscopic follow-up observations from the TESS Follow-up Observing Program (TFOP) Working Group, we have determined that the planets are Jovian-sized (R$_{P}$ = 1.00-1.45 R$_{J}$), have masses ranging from 0.92 to 5.35 M$_{J}$, and orbit F, G, and K stars (4753 $<$ T$_{eff}$ $<$ 7360 K). We detect a significant orbital eccentricity for the three longest-period systems in our sample: TOI-2025 b (P = 8.872 days, $e$ = $0.220\pm0.053$), TOI-2145 b (P = 10.261 days, $e$ = $0.182^{+0.039}_{-0.049}$), and TOI-2497 b (P = 10.656 days, $e$ = $0.196^{+0.059}_{-0.053}$). TOI-2145 b and TOI-2497 b both orbit subgiant host stars (3.8 $<$ $\log$ g $<$4.0), but these planets show no sign of inflation despite very high levels of irradiation. The lack of inflation may be explained by the high mass of the planets; $5.35^{+0.32}_{-0.35}$ M$_{\rm J}$ (TOI-2145 b) and $5.21\pm0.52$ M$_{\rm J}$ (TOI-2497 b). These six new discoveries contribute to the larger community effort to use {\it TESS} to create a magnitude-complete, self-consistent sample of giant planets with well-determined parameters for future detailed studies.Comment: 20 Pages, 6 Figures, 8 Tables, Accepted by MNRA