Development of an adverse outcome pathway network for nephrotoxicity.

Adverse outcome pathways (AOPs) were introduced in modern toxicology to provide evidence-based representations of the events and processes involved in the progression of toxicological effects across varying levels of the biological organisation to better facilitate the safety assessment of chemicals. AOPs offer an opportunity to address knowledge gaps and help to identify novel therapeutic targets. They also aid in the selection and development of existing and new in vitro and in silico test methods for hazard identification and risk assessment of chemical compounds. However, many toxicological processes are too intricate to be captured in a single, linear AOP. As a result, AOP networks have been developed to aid in the comprehension and placement of associated events underlying the emergence of related forms of toxicity-where complex exposure scenarios and interactions may influence the ultimate adverse outcome. This study utilised established criteria to develop an AOP network that connects thirteen individual AOPs associated with nephrotoxicity (as sourced from the AOP-Wiki) to identify several key events (KEs) linked to various adverse outcomes, including kidney failure and chronic kidney disease. Analysis of the modelled AOP network and its topological features determined mitochondrial dysfunction, oxidative stress, and tubular necrosis to be the most connected and central KEs. These KEs can provide a logical foundation for guiding the selection and creation of in vitro assays and in silico tools to substitute for animal-based in vivo experiments in the prediction and assessment of chemical-induced nephrotoxicity in human health.

Metabolism-based category formation for the prioritisation of genotoxicity hazard assessment for plant protection product residues (Part 4): α-Chloroacetamides.

In dietary risk assessment of plant protection products, residues of active ingredients and their metabolites need to be evaluated for their genotoxic potential. The European Food Safety Authority recommend a tiered approach focussing assessment and testing on classes of similar chemicals. To characterise similarity, in terms of metabolism, a metabolic similarity profiling scheme has been developed from an analysis of 69 α-chloroacetamide herbicides for which either Ames, chromosomal aberration or micronucleus test results are publicly available. A set of structural space alerts were defined, each linked to a key metabolic transformation present in the α-chloroacetamide metabolic space. The structural space alerts were combined with covalent chemistry profiling to develop categories suitable for chemical prioritisation via read-across. The method is a robust and reproducible approach to such read-across predictions, with the potential to reduce unnecessary testing. The key challenge in the approach was identified as being the need for metabolism data individual groups of plant protection products as the basis for the development of the structural space alerts.

IDEA tool: Establishing a prioritisation matrix for oral health improvement interventions.

Initial impetus for action: Oral health is not equitably distributed. More deprived areas experience appreciably worse oral health outcomes. Oral health improvement programmes in Local Authorities (LA) seek to reduce these inequalities but have diminished in recent years following the COVID-19 pandemic. LAs have also endured funding cuts to public health budgets, placing a greater emphasis on the need for establishing a clear prioritisation matrix for oral health improvement interventions. Solution: A prioritisation matrix that considered both the importance and do-ability of oral health improvement interventions was developed. Both are composite measures. The importance comprised evidence of benefit, impact on inequalities, alignment with national/local priorities and cost-effectiveness of the intervention. The do-ability considered the available support from stakeholders, building/equipment requirements, workforce issues and investment funding. A working group was necessary to inform the do-ability aspect of the prioritisation matrix. Scores were assigned to each criterion, the sum of the scores informed whether the intervention was eliminated, aspirational or implemented based on predetermined thresholds. Outcome: The prioritisation matrix ensured a transparent and systematic approach for intervention selection, which reflected local resources and priorities. Moreover, this tool should help ensure the most effective, equitable, practical and sustainable interventions are chosen having the greatest impact on improving oral health outcomes.

Metabolism-based category formation for the prioritisation of genotoxicity hazard assessment for plant protection product residues (part 3): Strobilurins.

In dietary risk assessment of plant protection products, residues of active ingredients and their metabolites need to be evaluated for their genotoxic potential. The European Food Safety Authority recommend a tiered approach focussing assessment and testing on classes of similar chemicals. To characterise similarity, in terms of metabolism, a metabolic similarity profiling scheme has been developed from an analysis of 46 chemicals of strobilurin fungicides and their metabolites for which either Ames, chromosomal aberration or micronucleus test results are publicly available. This profiling scheme consists of a set of ten sub-structures, each linked to a key metabolic transformation present in the strobilurin metabolic space. This metabolic similarity profiling scheme was combined with covalent chemistry profiling and physico-chemistry properties to develop chemical categories suitable for chemical prioritisation via read-across. The method is a robust and reproducible approach to such read-across predictions, with the potential to reduce unnecessary testing. The key challenge in the approach was identified as being the need for metabolism data and individual groups of plant protection products as the basis for the development of such profiling schemes.

Sub-structure-based category formation for the prioritisation of genotoxicity hazard assessment for pesticide residues (part 2): Triazoles.

In dietary risk assessment, residues of pesticidal ingredients or their metabolites need to be evaluated for their genotoxic potential. The European Food Safety Authority recommend a tiered approach focussing assessment and testing on classes of similar chemicals. To characterise similarity and to identify structural alerts associated with genotoxic concern, a set of chemical sub-structures was derived for an example dataset of 66 triazole agrochemicals for which either Ames, chromosomal aberration or micronucleus test results are publicly available. This analysis resulted in a set of ten structural alerts that define the chemical space, in terms of the common parent and metabolic scaffolds, associated with the triazole chemical class. An analysis of the available profiling schemes for DNA and protein reactivity shows the importance of investigating the predictivity of such schemes within a well-defined area of structural space. Structural space alerts, covalent chemistry profiling and physico-chemistry properties were combined to develop chemical categories suitable for chemical prioritisation. The method is a robust and reproducible approach to such read-across predictions, with the potential to reduce unnecessary testing. The key challenge in the approach was identified as being the need for pesticide-class specific metabolism data as the basis for structural space alert development.

Sub-structure-based category formation for the prioritisation of genotoxicity hazard assessment for pesticide residues: Sulphonyl ureas.

In dietary risk assessment, residues of pesticidal ingredients or their metabolites need to be evaluated for their genotoxic potential. The European Food Safety Authority recommend a tiered approach focussing assessment and testing on classes of similar chemicals. To characterise similarity and to identify structural alerts associated with genotoxic concern, a set of chemical sub-structures was derived for an example dataset of 74 sulphonyl urea agrochemicals for which either Ames, chromosomal aberration or micronucleus test results are publicly available. This analysis resulted in a set of seven structural alerts that define the chemical space, in terms of the common parent and metabolic scaffolds, associated with the sulphonyl urea chemical class. An analysis of the available profiling schemes for DNA and protein reactivity shows the importance of investigating the predictivity of such schemes within a well-defined area of structural space. Structural space alerts, covalent chemistry profiling and physico-chemistry properties were combined to develop chemical categories suitable for chemical prioritisation. The method is a robust and reproducible approach to such read-across predictions, with the potential to reduce unnecessary testing. The key challenge in the approach was identified as being the need for pesticide-class specific metabolism data as the basis for structural space alert development.

Molecular fingerprint-derived similarity measures for toxicological read-across: Recommendations for optimal use.

Computational approaches are increasingly used to predict toxicity due, in part, to pressures to find alternatives to animal testing. Read-across is the "new paradigm" which aims to predict toxicity by identifying similar, data rich, source compounds. This assumes that similar molecules tend to exhibit similar activities i.e. molecular similarity is integral to read-across. Various of molecular fingerprints and similarity measures may be used to calculate molecular similarity. This study investigated the value and concordance of the Tanimoto similarity values calculated using six widely used fingerprints within six toxicological datasets. There was considerable variability in the similarity values calculated from the various molecular fingerprints for diverse compounds, although they were reasonably concordant for homologous series acting via a common mechanism. The results suggest generic fingerprint-derived similarities are likely to be optimally predictive for local datasets, i.e. following sub-categorisation. Thus, for read-across, generic fingerprint-derived similarities are likely to be most predictive after chemicals are placed into categories (or groups), then similarity is calculated within those categories, rather than for a whole chemically diverse dataset.

Intrapatient viral diversity and treatment outcome in patients with genotype 3a hepatitis C virus infection on sofosbuvir-containing regimens.

Treatment with the direct-acting antiviral agent (DAA) sofosbuvir (SOF), an NS5B inhibitor, and velpatasvir (VEL), an NS5A inhibitor, demonstrates viral cure rates of ≥95% in hepatitis C virus (HCV) genotypes (GT) 1-6. Here, we investigated intrapatient HCV diversity in NS5A and NS5B using Shannon entropy to examine the relationship between viral diversity and treatment outcome. At baseline, HCV diversity was lowest in patients infected with HCV GT3 as compared to the other GTs, and viral diversity was greater in NS5A than NS5B (P < .0001). Treatment outcome with SOF/VEL or the comparator regimen of SOF with ribavirin (RBV) was not correlated with baseline diversity. However, among persons treated with SOF/VEL, a decrease in diversity from baseline was observed at relapse in the majority virologic failures, consistent with a viral bottleneck event at relapse. In contrast, an increase in diversity was observed in 27% of SOF+RBV virologic failures. We investigated whether the increase in diversity was due to an increase in the transition rate, one mode of potential RBV-mediated mutagenesis; however, we found no evidence of this mechanism. Overall, we did not observe that viral diversity at baseline influenced treatment outcome, but the diversity changes observed at relapse can improve our understanding of RBV viral suppression in vivo.

Fascial layers influence the spread of injectate during ultrasound-guided infraclavicular brachial plexus block: a cadaver study.

BACKGROUND: Fascial layers of the neurovascular sheath containing the brachial plexus influence distribution of local anaesthetic, hence increasing the risk of block failure when performing infraclavicular brachial plexus block (ICB). METHODS: Ultrasound-guided infraclavicular brachial plexus block was performed on cadavers using a single injection technique with dye (20-30 ml). After injection, we carried out consecutive dissection of the neurovascular bundle to study dye injectate spread and identify the presence of fascial layers. Ultrasound video images (scout scan and injection) and recordings of dissections were evaluated by independent experts (regional anaesthetists and anatomists). RESULTS: Well defined fascial layers were identified at dissection in seven out of 12 infraclavicular spaces studied. These fascial layers impeded the spread of dye injectate substantially in six cases and partially in one case. No fascial layers were identified at dissection in five cases, in each of which the spread of injectate was complete throughout the neurovascular bundle. The sensitivity and specificity of ultrasonography and haptic sensation for detection of fascial layers were poor. CONCLUSIONS: When fascial layers are present in the neurovascular sheath, they impede the spread of injectate during infraclavicular brachial plexus block. Ultrasound detection of these fascial layers is unreliable in cadavers. These findings support the use of greater volumes of injectate or a multiple injection technique when performing this block.

A Retrospective Audit of In-Hospital 30-day Mortality from Acute Myocardial Infarction in Connolly Hospital Blanchardstown.

In 2015, The Department of Health published the first annual report of the "National Healthcare Quality Reporting System." Connolly Hospital was reported to a mortality rate within 30 days post-Acute Myocardial Infarction (AMI) of 9.87 per 100 cases which was statistically significantly higher than the national rate. We carried out a retrospective audit of patients who were HIPE-coded as having died within 30 days of AMI from 2011-2013 and identified 42 patients. On review, only 23 patients (54.8%) were confirmed as having had an AMI. We identified 12 patients who had AMI included on death certificate without any evidence for same. If the 22 patients incorrectly coded were excluded, the mortality rate within 30 days post-AMI in CHB would fall to 4.14 deaths per 100 cases, well below the national average. Inaccuracies of data collection can lead to erroneous conclusions when examining healthcare data.

Proposal of an in silico profiler for categorisation of repeat dose toxicity data of hair dyes.

This study outlines the analysis of 94 chemicals with repeat dose toxicity data taken from Scientific Committee on Consumer Safety opinions for commonly used hair dyes in the European Union. Structural similarity was applied to group these chemicals into categories. Subsequent mechanistic analysis suggested that toxicity to mitochondria is potentially a key driver of repeat dose toxicity for chemicals within each of the categories. The mechanistic hypothesis allowed for an in silico profiler consisting of four mechanism-based structural alerts to be proposed. These structural alerts related to a number of important chemical classes such as quinones, anthraquinones, substituted nitrobenzenes and aromatic azos. This in silico profiler is intended for grouping chemicals into mechanism-based categories within the adverse outcome pathway paradigm.

A strategy for structuring and reporting a read-across prediction of toxicity.

Category formation, grouping and read across methods are broadly applicable in toxicological assessments and may be used to fill data gaps for chemical safety assessment and regulatory decisions. In order to facilitate a transparent and systematic approach to aid regulatory acceptance, a strategy to evaluate chemical category membership, to support the use of read-across predictions that may be used to fill data gaps for regulatory decisions is proposed. There are two major aspects of any read-across exercise, namely assessing similarity and uncertainty. While there can be an over-arching rationale for grouping organic substances based on molecular structure and chemical properties, these similarities alone are generally not sufficient to justify a read-across prediction. Further scientific justification is normally required to justify the chemical grouping, typically including considerations of bioavailability, metabolism and biological/mechanistic plausibility. Sources of uncertainty include a variety of elements which are typically divided into two main issues: the uncertainty associated firstly with the similarity justification and secondly the completeness of the read-across argument. This article focuses on chronic toxicity, whilst acknowledging the approaches are applicable to all endpoints. Templates, developed from work to prepare for the application of new toxicological data to read-across assessment, are presented. These templates act as proposals to assist in assessing similarity in the context of chemistry, toxicokinetics and toxicodynamics as well as to guide the systematic characterisation of uncertainty both in the context of the similarity rationale, the read across data and overall approach and conclusion. Lastly, a workflow for reporting a read-across prediction is suggested.

Does Vibration Warm-up Enhance Kinetic and Temporal Sprint Parameters?

The aim of this study was to investigate the efficacy of vibration warm-up to enhance sprint performance. 12 males involved in representative team sports performed 4 warm-up conditions in a randomised order performed at least 24 h apart; VbX warm-up (VbX-WU); Neural activation warm-up (Neu-WU); Dynamic warm-up (Dyn-WU) and Control (No VbX). Participants completed 5 m sprint at 30 s, 2:30 min and 5 min post warm-up where sprint time, kinetics, and temporal components were recorded. There was no significant (p>0.05) main effect or interaction effect between the split sprint times of 1 m, 2.5 m, and 5 m. There was a condition effect where vertical mean force was significantly higher (p<0.05) in Dyn-WU and Control compared to Neu-WU. No other significant (p>0.05) main and interaction effects in sprint kinetic and temporal parameters existed. Overall, all 4 warm-up conditions produced comparable results for sprint performance, and there was no detrimental effect on short-duration sprint performance using VbX-WU. Therefore, VbX could be useful for adding variety to the training warm-up or be included into the main warm-up routine as a supplementary modality.

Hepatotoxicity: a scheme for generating chemical categories for read-across, structural alerts and insights into mechanism(s) of action.

The ability of a compound to cause adverse effects to the liver is one of the most common reasons for drug development failures and the withdrawal of drugs from the market. Such adverse effects can vary tremendously in severity, leading to an array of possible drug-induced liver injuries (DILIs). As a result, it is not surprising that drug development has evolved into a complex and multifaceted process including methods aiming to identify potential liver toxicities. Unfortunately, hepatotoxicity remains one of the most complex and poorly understood areas of human toxicity; thus it is a significant challenge to identify potential hepatotoxins. The performance of existing methods to identify hepatotoxicity requires improvement. The current study details a scheme for generating chemical categories and the development of structural alerts able to identify potential hepatotoxins. The study utilized a diverse 951-compound dataset and used structural similarity methods to produce a number of structurally restricted categories. From these categories, 16 structural alerts associated with observed human hepatotoxicity were developed. Furthermore, the mechanism(s) by which these compounds cause hepatotoxicity were investigated and a mechanistic rationale was proposed, where possible, to yield mechanistically supported structural alerts. Alerts of this nature have the potential to be used in the screening of compounds to highlight potential hepatotoxicity, whilst the chemical categories themselves are important in applying read-across approaches. The scheme presented in this study also has the potential to act as a knowledge generator serving as an excellent starting platform from which to conduct additional toxicological studies.

Detailed analysis of in-hospital transmission of SARS-CoV-2 using whole genome sequencing.

BACKGROUND: Hospital transmission of SARS-CoV-2 has proved difficult to control, with healthcare-associated infections troublesome throughout. AIM: To understand factors contributing to hospital transmission of infections, which is necessary for containing spread. METHODS: An outbreak of 56 staff and patient cases of COVID-19 over a 31-day period in a tertiary referral unit is presented, with at least a further 29 cases identified outside of the unit and the hospital by whole genome sequencing (WGS). FINDINGS: Transmission is documented from staff to staff, staff to patients, and patients to staff, showing disruption of a tertiary referral service, despite implementation of nationally recommended control measures, superior ventilation, and use of personal protective equipment. There was extensive spread from the index case, despite this patient spending only 10 h bed bound on the ward in strict cubicle isolation and with an initial single target low level (CT = 32) polymerase chain reaction test. CONCLUSION: This investigation highlights how effectively and rapidly SARS-CoV-2 can spread in certain circumstances. It raises questions about infection control measures in place at the time and calls into question the premise that transmissibility can be reliably detected by using lower sensitivity rapid antigen lateral flow tests. We also highlight the value of early intervention in reducing impact as well as the value of WGS in understanding outbreaks.

Evaluation of QSAR models for predicting mutagenicity: outcome of the Second Ames/QSAR international challenge project.

Quantitative structure-activity relationship (QSAR) models are powerful in silico tools for predicting the mutagenicity of unstable compounds, impurities and metabolites that are difficult to examine using the Ames test. Ideally, Ames/QSAR models for regulatory use should demonstrate high sensitivity, low false-negative rate and wide coverage of chemical space. To promote superior model development, the Division of Genetics and Mutagenesis, National Institute of Health Sciences, Japan (DGM/NIHS), conducted the Second Ames/QSAR International Challenge Project (2020-2022) as a successor to the First Project (2014-2017), with 21 teams from 11 countries participating. The DGM/NIHS provided a curated training dataset of approximately 12,000 chemicals and a trial dataset of approximately 1,600 chemicals, and each participating team predicted the Ames mutagenicity of each trial chemical using various Ames/QSAR models. The DGM/NIHS then provided the Ames test results for trial chemicals to assist in model improvement. Although overall model performance on the Second Project was not superior to that on the First, models from the eight teams participating in both projects achieved higher sensitivity than models from teams participating in only the Second Project. Thus, these evaluations have facilitated the development of QSAR models.

Development of mechanism-based structural alerts for respiratory sensitization hazard identification.

This study outlines how mechanistic organic chemistry related to covalent bond formation can be used to rationalize the ability of low molecular weight chemicals to cause respiratory sensitization. The results of an analysis of 104 chemicals which have been reported to cause respiratory sensitization in humans showed that most of the sensitizing chemicals could be distinguished from 82 control chemicals for which no clinical reports of respiratory sensitization exist. This study resulted in the development of a set of mechanism-based structural alerts for chemicals with the potential to cause respiratory sensitization. Their potential for use in a predictive algorithm for this purpose alongside an externally validated quantitative structure-activity relationship model is discussed.

Development of new structural alerts suitable for chemical category formation for assigning covalent and non-covalent mechanisms relevant to DNA binding.

The need to assess the ability of a chemical to act as a mutagen is one of the primary requirements in regulatory toxicology. Several pieces of legislation have led to an increased interest in the use of in silico methods, specifically the formation of chemical categories and read-across for the assessment of toxicological endpoints. One of the key steps in the development of chemical categories for mutagenicity is defining the mechanistic organic chemistry associated with the formation of a covalent bond between DNA and an exogenous chemical. To this end this study has analysed, by use of a large set of mutagenicity data (Ames test), the mechanistic coverage of a recently published set of in silico structural alerts developed for category formation. The results show that the majority of chemicals with a positive result in the Ames test were assigned at least one covalent binding mechanism related to the formation of a DNA adduct. The remaining chemicals with positive data in the Ames assay were subjected to a detailed mechanistic analysis from which 26 new structural alerts relating to covalent binding mechanisms were developed. In addition, structural alerts for radical and non-covalent intercalation mechanisms were also defined. The structural alerts outlined in this study are not intended to predict mutagenicity but rather to identify mechanisms associated with covalent and non-covalent DNA binding. This mechanistic profiling information can then be used to form chemical categories suitable for filling data gaps via read-across. A strategy for chemical category formation for mutagenicity is also presented.

The effect of increased overjet on the magnitude and reproducibility of smiling in adult females.

The objective of this study was to determine if increased overjet (greater than 6 mm) influences the magnitude and reproducibility of natural smile and maximal smile in Caucasian adult females. Twenty adult females with an increased overjet (6-10 mm) and 20 control adult females (overjet 2-4 mm) with no history of orthodontic treatment volunteered to participate. The mean age in the control group was 30.1 ± 6.4 years and the mean age in the test group was 31.9 ± 10.8 years. Three-dimensional stereophotogrammetric images were captured of each subject for three expressions: at rest, natural smile, and maximal smile. The images were recorded twice on two separate occasions, 6 weeks apart. Images were landmarked and a partial ordinary Procrustes superimposition was used to adjust for the differences in head posture between the same expressions. The magnitude of movement relative to the rest position, averaged over all the landmarks, was calculated and compared between the groups using analysis of variance (linear mixed-effects model); the intra- and inter-session reproducibility of both expressions was assessed. There was greater mean movement, averaged over all the landmarks, in the control group than in the increased overjet group for both natural smile and maximal smile (P = 0.0068). For these expressions, there were no statistically significant differences in reproducibility within sessions (P = 0.5403) or between sessions (P = 0.3665). Increased overjet had a statistically significant effect on the magnitude of smiling but did not influence the reproducibility of natural or maximal smile relative to controls.