Strengths and opportunities in research into extracellular matrix ageing: A consultation with the ECMage research community.

Ageing causes progressive decline in metabolic, behavioural, and physiological functions, leading to a reduced health span. The extracellular matrix (ECM) is the three-dimensional network of macromolecules that provides our tissues with structure and biomechanical resilience. Imbalance between damage and repair/regeneration causes the ECM to undergo structural deterioration with age, contributing to age-associated pathology. The ECM 'Ageing Across the Life Course' interdisciplinary research network (ECMage) was established to bring together researchers in the United Kingdom, and internationally, working on the emerging field of ECM ageing. Here we report on a consultation at a joint meeting of ECMage and the Medical Research Council / Versus Arthritis Centre for Integrated Research into Musculoskeletal Ageing, held in January 2023, in which delegates analysed the key questions and research opportunities in the field of ECM ageing. We examine fundamental biological questions, enabling technologies, systems of study and emerging in vitro and in silico models, alongside consideration of the broader challenges facing the field.

Supramolecular Self-Associating Amphiphiles Inhibit Biofilm Formation by the Critical Pathogens, Pseudomonas aeruginosa and Candida albicans.

In 2019, 4.95 million deaths were directly attributed to antimicrobial-resistant bacterial infections globally. In addition, the mortality associated with fungal infections is estimated at 1.7 million annually, with many of these deaths attributed to species that are no longer susceptible to traditional therapeutic regimes. Herein, we demonstrate the use of a novel class of supramolecular self-associating amphiphilic (SSA) salts as antimicrobial agents against the critical pathogens Pseudomonas aeruginosa and Candida albicans. We also identify preliminary structure-activity relationships for this class of compound that will aid the development of next-generation SSAs demonstrating enhanced antibiofilm activity. To gain insight into the possible mode of action for these agents, a series of microscopy studies were performed, taking advantage of the intrinsic fluorescent nature of benzothiazole-substituted SSAs. Analysis of these data showed that the SSAs interact with the cell surface and that a benzothiazole-containing SSA inhibits hyphal formation by C. albicans.

Correction: Two-test algorithms for infectious disease diagnosis: Implications for COVID-19.

[This corrects the article DOI: 10.1371/journal.pgph.0000293.].

Tools to enable the study and translation of supramolecular amphiphiles.

This tutorial review focuses on providing a summary of the key techniques used for the characterisation of supramolecular amphiphiles and their self-assembled aggregates; from the understanding of low-level molecular interactions, to materials analysis, use of data to support computer-aided molecular design and finally, the translation of this class of compounds for real world application, specifically within the clinical setting. We highlight the common methodologies used for the study of traditional amphiphiles and build to provide specific examples that enable the study of specialist supramolecular systems. This includes the use of nuclear magnetic resonance spectroscopy, mass spectrometry, X-ray scattering techniques (small- and wide-angle X-ray scattering and single crystal X-ray diffraction), critical aggregation (or micelle) concentration determination methodologies, machine learning, and various microscopy techniques. Furthermore, this review provides guidance for working with supramolecular amphiphiles in in vitro and in vivo settings, as well as the use of accessible software programs, to facilitate screening and selection of druggable molecules. Each section provides: a methodology overview - information that may be derived from the use of the methodology described; a case study - examples for the application of these methodologies; and a summary section - providing methodology specific benefits, limitations and future applications.

Ultrasound-guided hepatic portal vein injection is not a reproducible technique for delivery of cell therapies to the liver in mice.

AIMS: Our aim was to determine if ultrasound-guided HPV injection in mice would provide reproducible and reliable results, as is currently obtained via open laparotomy techniques, and offer a surgical refinement to emulate islet transplantation in humans. METHODS: Fluorescent-polymer microparticles (20 µm) were injected (27G-needle) into the HPV via open laparotomy (n = 4) or under ultrasound-guidance (n = 4) using an MX550D-transducer with a Vevo3100-scanner (FUJIFILM VisualSonics, Inc.). Mice were culled 24-h post injection; organs were frozen, step sectioned (10 µm-slices) and 10 sections/mouse (50 µm-spacing) were quantified for microparticles in the liver and other organs by fluorescent microscopy. RESULTS: Murine HPV injection, via open laparotomy-route, resulted in widespread distribution of microparticles in the liver, lungs and spleen; ultrasound-guided injection resulted in reduced microparticle delivery (p < 0.0001) and microparticle clustering in distinct areas of the liver at the site of needle penetration, with very few/no microparticles being seen in lung and spleen tissues, hypothesised to be due to flow into the body cavity: liver median (interquartile range) 4.15 (0.00-4.15) versus 0.00 (0.00-0.00) particle-count mm-2 , respectively. CONCLUSIONS: Ultrasound-guided injection results in microparticle clustering in the liver, with an overall reduction in microparticle number when compared to open laparotomy HPV injection, and high variability in microparticle-counts detected between mice. Ultrasound-guided injection is not currently a technique that can replace open laparotomy HPV of islet transplantation in mice.

Epidemiological waves - Types, drivers and modulators in the COVID-19 pandemic.

Introduction: A discussion of 'waves' of the COVID-19 epidemic in different countries is a part of the national conversation for many, but there is no hard and fast means of delineating these waves in the available data and their connection to waves in the sense of mathematical epidemiology is only tenuous. Methods: We present an algorithm which processes a general time series to identify substantial, significant and sustained periods of increase in the value of the time series, which could reasonably be described as 'observed waves'. This provides an objective means of describing observed waves in time series. We use this method to synthesize evidence across different countries to study types, drivers and modulators of waves. Results: The output of the algorithm as applied to epidemiological time series related to COVID-19 corresponds to visual intuition and expert opinion. Inspecting the results of individual countries shows how consecutive observed waves can differ greatly with respect to the case fatality ratio. Furthermore, in large countries, a more detailed analysis shows that consecutive observed waves have different geographical ranges. We also show how waves can be modulated by government interventions and find that early implementation of NPIs correlates with a reduced number of observed waves and reduced mortality burden in those waves. Conclusion: It is possible to identify observed waves of disease by algorithmic methods and the results can be fruitfully used to analyse the progression of the epidemic.

Controlling the structure of supramolecular fibre formation for benzothiazole based hydrogels with antimicrobial activity against methicillin resistant Staphylococcus aureus.

Antimicrobial resistance is one of the greatest threats to human health. Gram-positive methicillin resistant Staphylococcus aureus (MRSA), in both its planktonic and biofilm form, is of particular concern. Herein we identify the hydrogelation properties for a series of intrinsically fluorescent, structurally related supramolecular self-associating amphiphiles and determine their efficacy against both planktonic and biofilm forms of MRSA. To further explore the potential translation of this hydrogel technology for real-world applications, the toxicity of the amphiphiles was determined against the eukaryotic multicellular model organism, Caenorhabditis elegans. Due to the intrinsic fluorescent nature of these supramolecular amphiphiles, material characterisation of their molecular self-associating properties included; comparative optical density plate reader assays, rheometry and widefield fluorescence microscopy. This enabled determination of amphiphile structure and hydrogel sol dependence on resultant fibre formation.

Engineered neural tissue made using hydrogels derived from decellularised tissues for the regeneration of peripheral nerves.

Engineered neural tissue (EngNT) promotes in vivo axonal regeneration. Decellularised materials (dECM) are complex biologic scaffolds that can improve the cellular environment and also encourage positive tissue remodelling in vivo. We hypothesised that we could incorporate a hydrogel derived from a decellularised tissue (dECMh) into EngNT, thereby providing an alternative to the currently used purified collagen I hydrogel for the first time. Decellularisation was carried out on bone (B-ECM), liver (LIV-ECM), and small intestinal (SIS-ECM) tissues and the resultant dECM was biochemically and mechanically characterised. dECMh differed in mechanical and biochemical properties that likely had an effect on Schwann cell behaviour observed in metabolic activity and contraction profiles. Cellular alignment was observed in tethered moulds within the B-ECM and SIS-ECM derived hydrogels only. No difference was observed in dorsal root ganglia (DRG) neurite extension between the dECMh groups and collagen I groups when applied as a coverslip coating, however, when DRG were seeded atop EngNT constructs, only the B-ECM derived EngNT performed similarly to collagen I derived EngNT. B-ECM EngNT further exhibited similar axonal regeneration to collagen I EngNT in a 10 mm gap rat sciatic nerve injury model after 4 weeks. Our results have shown that various dECMh can be utilised to produce EngNT that can promote neurite extension in vitro and axonal regeneration in vivo. STATEMENT OF SIGNIFICANCE: Nerve autografts are undesirable due to the sacrifice of a patient's own nerve tissue to repair injuries. Engineered neural tissue (EngNT) is a type of living artificial tissue that has been developed to overcome this. To date, only a collagen hydrogel has been shown to be effective in the production and utilisation of EngNT in animal models. Hydrogels may be made from decellularised extracellular matrix derived from many tissues. In this study we showed that hydrogels from various tissues may be used to create EngNT and one was shown to comparable to the currently used collagen based EngNT in a rat sciatic nerve injry model.

A water-soluble membrane transporter for biologically relevant cations.

Synthetic ionophores are promising therapeutic targets, yet poor water solubility limits their potential for translation into the clinic. Here we report a water-soluble, supramolecular self-associating amphiphile that functions as a cation uniporter in synthetic vesicle systems, deriving mechanistic insight through planar bilayer patch clamp experiments.

Estimating the Effectiveness of Shielding during Pregnancy against SARS-CoV-2 in New York City during the First Year of the COVID-19 Pandemic.

Pregnant patients have increased morbidity and mortality in the setting of SARS-CoV-2 infection. The exposure of pregnant patients in New York City to SARS-CoV-2 is not well understood due to early lack of access to testing and the presence of asymptomatic COVID-19 infections. Before the availability of vaccinations, preventative (shielding) measures, including but not limited to wearing a mask and quarantining at home to limit contact, were recommended for pregnant patients. Using universal testing data from 2196 patients who gave birth from April through December 2020 from one institution in New York City, and in comparison, with infection data of the general population in New York City, we estimated the exposure and real-world effectiveness of shielding in pregnant patients. Our Bayesian model shows that patients already pregnant at the onset of the pandemic had a 50% decrease in exposure compared to those who became pregnant after the onset of the pandemic and to the general population.

Supramolecular self-associating amphiphiles as aqueous pollutant scavengers.

We present a series of supramolecular self-associated amphiphiles, which spontaneously self-assemble into aggregated species. These aggregates are shown to absorb a variety of (polar) micropollutants from aqueous mixtures and as a result we determine the suitability for this technology to be developed further as aqueous environmental clean-up agents.

Establishing the selective phospholipid membrane coordination, permeation and lysis properties for a series of 'druggable' supramolecular self-associating antimicrobial amphiphiles.

The rise of antimicrobial resistance remains one of the greatest global health threats facing humanity. Furthermore, the development of novel antibiotics has all but ground to a halt due to a collision of intersectional pressures. Herein we determine the antimicrobial efficacy for 14 structurally related supramolecular self-associating amphiphiles against clinically relevant Gram-positive methicillin resistant Staphylococcus aureus and Gram-negative Escherichia coli. We establish the ability of these agents to selectively target phospholipid membranes of differing compositions, through a combination of computational host:guest complex formation simulations, synthetic vesicle lysis, adhesion and membrane fluidity experiments, alongside our novel 1H NMR CPMG nanodisc coordination assays, to verify a potential mode of action for this class of compounds and enable the production of evermore effective next-generation antimicrobial agents. Finally, we select a 7-compound subset, showing two lead compounds to exhibit 'druggable' profiles through completion of a variety of in vivo and in vitro DMPK studies.

Printing biohybrid materials for bioelectronic cardio-3D-cellular constructs.

Conductive hydrogels are emerging as promising materials for bioelectronic applications as they minimize the mismatch between biological and electronic systems. We propose a strategy to bioprint biohybrid conductive bioinks based on decellularized extracellular matrix (dECM) and multiwalled carbon nanotubes. These inks contained conductive features and morphology of the dECM fibers. Electrical stimulation (ES) was applied to bioprinted structures containing human pluripotent stem cell-derived cardiomyocytes (hPSC-CMs). It was observed that in the absence of external ES, the conductive properties of the materials can improve the contractile behavior of the hPSC-CMs, and this effect is enhanced under the application of external ES. Genetic markers indicated a trend toward a more mature state of the cells with upregulated calcium handling proteins and downregulation of calcium channels involved in the generation of pacemaking currents. These results demonstrate the potential of our strategy to manufacture conductive hydrogels in complex geometries for actuating purposes.

COVID-19 morbidity in Afghanistan: a nationwide, population-based seroepidemiological study.

OBJECTIVE: The primary objectives were to determine the magnitude of COVID-19 infections in the general population and age-specific cumulative incidence, as determined by seropositivity and clinical symptoms of COVID-19, and to determine the magnitude of asymptomatic or subclinical infections. DESIGN, SETTING AND PARTICIPANTS: We describe a population-based, cross-sectional, age-stratified seroepidemiological study conducted throughout Afghanistan during June/July 2020. Participants were interviewed to complete a questionnaire, and rapid diagnostic tests were used to test for SARS-CoV-2 antibodies. This national study was conducted in eight regions of Afghanistan plus Kabul province, considered a separate region. The total sample size was 9514, and the number of participants required in each region was estimated proportionally to the population size of each region. For each region, 31-44 enumeration areas (EAs) were randomly selected, and a total of 360 clusters and 16 households per EA were selected using random sampling. To adjust the seroprevalence for test sensitivity and specificity, and seroreversion, Bernoulli's model methodology was used to infer the population exposure in Afghanistan. OUTCOME MEASURES: The main outcome was to determine the prevalence of current or past COVID-19 infection. RESULTS: The survey revealed that, to July 2020, around 10 million people in Afghanistan (31.5% of the population) had either current or previous COVID-19 infection. By age group, COVID-19 seroprevalence was reported to be 35.1% and 25.3% among participants aged ≥18 and 5-17 years, respectively. This implies that most of the population remained at risk of infection. However, a large proportion of the population had been infected in some localities, for example, Kabul province, where more than half of the population had been infected with COVID-19. CONCLUSION: As most of the population remained at risk of infection at the time of the study, any lifting of public health and social measures needed to be considered gradually.

Percolation across households in mechanistic models of non-pharmaceutical interventions in SARS-CoV-2 disease dynamics.

Since the emergence of the novel coronavirus disease 2019 (COVID-19), mathematical modelling has become an important tool for planning strategies to combat the pandemic by supporting decision-making and public policies, as well as allowing an assessment of the effect of different intervention scenarios. A proliferation of compartmental models were developed by the mathematical modelling community in order to understand and make predictions about the spread of COVID-19. While compartmental models are suitable for simulating large populations, the underlying assumption of a well-mixed population might be problematic when considering non-pharmaceutical interventions (NPIs) which have a major impact on the connectivity between individuals in a population. Here we propose a modification to an extended age-structured SEIR (susceptible-exposed-infected-recovered) framework, with dynamic transmission modelled using contact matrices for various settings in Brazil. By assuming that the mitigation strategies for COVID-19 affect the connections among different households, network percolation theory predicts that the connectivity among all households decreases drastically above a certain threshold of removed connections. We incorporated this emergent effect at population level by modulating home contact matrices through a percolation correction function, with the few additional parameters fitted to hospitalisation and mortality data from the city of São Paulo. Our model with percolation effects was better supported by the data than the same model without such effects. By allowing a more reliable assessment of the impact of NPIs, our improved model provides a better description of the epidemiological dynamics and, consequently, better policy recommendations.

Mathematical analysis of a two-strain tuberculosis model in Bangladesh.

Tuberculosis (TB) is an airborne infectious disease that causes millions of deaths worldwide each year (1.2 million people died in 2019). Alarmingly, several strains of the causative agent, Mycobacterium tuberculosis (MTB)-including drug-susceptible (DS) and drug-resistant (DR) variants-already circulate throughout most developing and developed countries, particularly in Bangladesh, with totally drug-resistant strains starting to emerge. In this study we develop a two-strain DS and DR TB transmission model and perform an analysis of the system properties and solutions. Both analytical and numerical results show that the prevalence of drug-resistant infection increases with an increasing drug use through amplification. Both analytic results and numerical simulations suggest that if the basic reproduction numbers of both DS ([Formula: see text]) and DR ([Formula: see text]) TB are less than one, i.e. [Formula: see text] the disease-free equilibrium is asymptotically stable, meaning that the disease naturally dies out. Furthermore, if [Formula: see text], then DS TB dies out but DR TB persists in the population, and if [Formula: see text] both DS TB and DR TB persist in the population. Further, sensitivity analysis of the model parameters found that the transmission rate of both strains had the greatest influence on DS and DR TB prevalence. We also investigated the effect of treatment rates and amplification on both DS and DR TB prevalence; results indicate that inadequate or inappropriate treatment makes co-existence more likely and increases the relative abundance of DR TB infections.

Non-pharmaceutical interventions and COVID-19 vaccination strategies in Senegal: a modelling study.

BACKGROUND: When vaccines against the novel COVID-19 were available in Senegal, many questions were raised. How long should non-pharmaceutical interventions (NPIs) be maintained during vaccination roll-out? What are the best vaccination strategies? METHODS: In this study, we used an age-structured dynamic mathematical model. This model uses parameters based on SARS-CoV-2 virus, information on different types of NPIs, epidemiological and demographic data, some parameters relating to hospitalisations and vaccination in Senegal. RESULTS: In all scenarios explored, the model predicts a larger third epidemic wave of COVID-19 in terms of new cases and deaths than the previous waves. In a context of limited vaccine supply, vaccination alone will not be sufficient to control the epidemic, and the continuation of NPIs is necessary to flatten the epidemic curve. Assuming 20% of the population have been vaccinated, the optimal period to relax NPIs would be a few days from the last peak. Regarding the prioritisation of age groups to be vaccinated, the model shows that it is better to vaccinate individuals aged 5-60 years and not just the elderly (over 60 years) and those in high-risk groups. This strategy could be more cost-effective for the government, as it would reduce the high costs associated with hospitalisation. In terms of vaccine distribution, the optimal strategy would be to allocate full dose to the elderly. If vaccine doses are limited, half dose followed by full dose would be sufficient for people under 40 years because whether they receive half or full dose, the reduction in hospitalisations would be similar and their death-to-case ratio is very low. CONCLUSIONS: This study could be presented as a decision support tool to help devise strategies to control the COVID-19 pandemic and help the Ministry of Health to better manage and allocate the available vaccine doses.

Supramolecular self-associating amphiphiles: determination of molecular self-association properties and calculation of critical micelle concentration using a high-throughput, optical density based methodology.

Supramolecular self-associating amphiphiles are a class of amphiphilic salt, the anionic component of which is 'frustrated' in nature, meaning multiple hydrogen bonding modes can be accessed simultaneously. Here we derive critical micelle concentration values for four supramolecular self-associating amphiphiles using the standard pendant drop approach and present a new high-throughput, optical density measurement based methodology, to enable the estimation of critical micelle concentrations over multiple temperatures. In addition, we characterise the low-level hydrogen bonded self-association events in the solid state, through single crystal X-ray diffraction, and in polar organic DMSO-d6 solutions using a combination of 1H NMR techniques. Moving into aqueous ethanol solutions (EtOH/H2O or EtOH/D2O (1 : 19 v/v)), we also show these amphiphilic compounds to form higher-order self-associated species through a combination of 1H NMR, dynamic light scattering and zeta potential studies.

Two-test algorithms for infectious disease diagnosis: Implications for COVID-19.

Diagnostic assays for various infectious diseases, including COVID-19, have been challenged for their utility as standalone point-of-care diagnostic tests due to suboptimal accuracy, complexity, high cost or long turnaround times for results. It is therefore critical to optimise their use to meet the needs of users. We used a simulation approach to estimate diagnostic outcomes, number of tests required and average turnaround time of using two-test algorithms compared with singular testing; the two tests were reverse transcription polymerase chain reaction (RT-PCR) and an antigen-based rapid diagnostic test (Ag-RDT). A web-based application of the model was developed to visualise and compare diagnostic outcomes for different disease prevalence and test performance characteristics (sensitivity and specificity). We tested the model using hypothetical prevalence data for COVID-19, representing low- and high-prevalence contexts and performance characteristics of RT-PCR and Ag-RDTs. The two-test algorithm when RT-PCR was applied to samples negative by Ag-RDT predicted gains in sensitivity of 27% and 7%, respectively, compared with Ag-RDT and RT-PCR alone. Similarly, when RT-PCR was applied to samples positive by Ag-RDT, specificity gains of 2.9% and 1.9%, respectively, were predicted. The algorithm using Ag-RDT followed by RT-PCR as a confirmatory test for positive patients limited the requirement of RT-PCR testing resources to 16,400 and 3,034 tests when testing a population of 100,000 with an infection prevalence of 20% and 0.05%, respectively. A two-test algorithm comprising a rapid screening test followed by confirmatory laboratory testing can reduce false positive rate, produce rapid results and conserve laboratory resources, but can lead to large number of missed cases in high prevalence setting. The web application of the model can identify the best testing strategies, tailored to specific use cases and we also present some examples how it was used as part of the Access to Covid-19 Tools (ACT) Accelerator Diagnostics Pillar.

Potential global impacts of alternative dosing regimen and rollout options for the ChAdOx1 nCoV-19 vaccine.

The high efficacy, low cost, and long shelf-life of the ChAdOx1 nCoV-19 vaccine positions it well for use in in diverse socioeconomic settings. Using data from clinical trials, an individual-based model was constructed to predict its 6-month population-level impact. Probabilistic sensitivity analyses evaluated the importance of epidemiological, demographic and logistical factors on vaccine effectiveness. Rollout at various levels of availability and delivery speed, conditional on vaccine efficacy profiles (efficacy of each dose and interval between doses) were explored in representative countries. We highlight how expedient vaccine delivery to high-risk groups is critical in mitigating COVID-19 disease and mortality. In scenarios where the availability of vaccine is insufficient for high-risk groups to receive two doses, administration of a single dose of is optimal, even when vaccine efficacy after one dose is just 75% of the two doses. These findings can help inform allocation strategies particularly in areas constrained by availability.