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Rapid growth in the market for electric vehicles is imperative, to meet global targets for reducing greenhouse gas emissions, to improve air quality in urban centres and to meet the needs of consumers, with whom electric vehicles are increasingly popular. However, growing numbers of electric vehicles present a serious waste-management challenge for recyclers at end-of-life. Nevertheless, spent batteries may also present an opportunity as manufacturers require access to strategic elements and critical materials for key components in electric-vehicle manufacture: recycled lithium-ion batteries from electric vehicles could provide a valuable secondary source of materials. Here we outline and evaluate the current range of approaches to electric-vehicle lithium-ion battery recycling and re-use, and highlight areas for future progress. Processes for dismantling and recycling lithium-ion battery packs from scrap electric vehicles are outlined., Author(s): Gavin Harper [sup.1] [sup.2] [sup.3] , Roberto Sommerville [sup.1] [sup.2] [sup.4] , Emma Kendrick [sup.1] [sup.2] [sup.3] , Laura Driscoll [sup.1] [sup.2] [sup.5] , Peter Slater [sup.1] [sup.2] [sup.5] [...]

Treatment options for adults with chronic cough (CC) are limited. This study reports on the health status and experiences of patients with recent healthcare evaluation for CC. This prospective, UK, cross-sectional study surveyed adults with a CC evaluation within the previous 12 months. All were never smokers (or ex-smokers for ≥12 months). Subjects completed five validated patient-reported outcome measures: cough visual analogue scale (VAS), EuroQoL 5 dimension, 5 level (EQ-5D-5L), EQ-5D VAS, Leicester Cough Questionnaire (LCQ), and Work Productivity and Activity Impairment (WPAI) questionnaire. A total of 101 participants were recruited: 71% were female, mean age was 54.9 ± 15.2 years. Median (IQR) CC duration was 36 (11, 120) months. Mean self-reported CC severity (Cough-VAS) was 51.3 ± 22.9 over the previous 2 weeks and 62.9 ± 23.7 on the worst day of coughing. EQ-5D values were lower for CC patients than population norms. Subanalyses revealed that EQ-5D and LCQ scores were significantly impacted by CC duration and the number of healthcare providers (HCPs) visited. WPAI analysis showed a 27.6% work time impairment because of participants' CC. The number of HCP attendances ranged from 1 to 10 (3.3 ± 2.8) before diagnosis was confirmed. Treatment was being prescribed to 87% of participants and comprised mainly steroids (nasal [19%] and inhaled [25%]), beta agonists (24%), and proton pump inhibitors (21%); 44% of patients were dissatisfied with treatment efficacy. Real-world data from a nationally representative UK population show significant unmet needs associated with CC, including multiple healthcare visits and limited treatment effectiveness, resulting in inadequate cough control and impaired health status. [ABSTRACT FROM AUTHOR]

Concerns about climate change and energy security are driving a global shift towards renewable energy sources and green technologies such as electric vehicles (EVs), energy storage and wind turbines. This commentary analyses the policy challenges raised by the growing demand for critical metals needed for this green transition to net zero. It is crucial that the UK's strategy looks beyond merely increasing primary supply or new mining, towards strategies to ensure better stewardship of secondary mineral resources already contained in a range of products. Furthermore, creating an enabling regulatory environment for procuring key technology metals will be key to addressing future supply threats for the UK, especially post-Brexit, and that failure to do so will put the UK at significant risk of falling behind in the global race to secure supplies. [ABSTRACT FROM AUTHOR]

An amendment to this paper has been published and can be accessed via a link at the top of the paper., Author(s): Gavin Harper [sup.1] [sup.2] [sup.3] , Roberto Sommerville [sup.1] [sup.2] [sup.4] , Emma Kendrick [sup.1] [sup.2] [sup.3] , Laura Driscoll [sup.1] [sup.2] [sup.5] , Peter Slater [sup.1] [sup.2] [sup.5] [...]

Structural adhesives are commonly used to join dissimilar materials and are of particular interest in complex technological devices used in automotive, telecommunications, photonic devices, aerospace and sustainable power production and storage. Their strength, ease of application and stability are of significant help in the manufacture and service of the device, however, they can present significant issues at end of life, particularly when technology critical metals need to be recovered. In this paper, we highlight some of the issues, and discuss an alternative approach: the use of adhesives that can be debonded upon application of an external stimulus. The aim of this critical review is to consider the polymer systems which have been investigated and suggest some alternative strategies. It also aims to demonstrate the different stimuli that can be used to debond and comment on the applicability of these with a number of case studies. Finally, the service conditions and process economics are considered together with a discussion of the Green benefits of this type of methodology. [ABSTRACT FROM AUTHOR]

One of the most commonly observed asthma treatment patterns is the underuse of inhaled corticosteroid (ICS) maintenance therapy when patients are not experiencing symptoms, and the predominant use of short-acting β2-agonists (SABAs) when patients are experiencing symptoms. This multinational study investigated the current beliefs and behaviors related to reliance on reliever inhalers among asthma patients, and the reasons why patients may not adhere to their recommended maintenance controller treatment. This was a qualitative research study, in which 80 patients with asthma who were receiving reliever therapy (i.e. SABAs) were interviewed, in-depth, for 60 min. The interview questions focused on the patients' experience of living with asthma and their inhaled treatment regimens. The key insights identified in the interviews were (a) patients had a strong emotional attachment to SABA relievers driven by their efficacy and success in quickly alleviating asthma symptoms, with the reliever also becoming an emotional support; (b) patients typically did not understand that the frequent use of SABAs indicates poor asthma control; (c) patients had a misperception of ICS, which could lead to a delay in escalation and poor adherence; and (d) severe exacerbations improve adherence to ICS, but only temporarily in many cases. This study confirmed the poor level of control patients have over their asthma, and how this affects their lifestyle and daily activities. Our results also confirmed that the patients' perception of both the disease and treatment plays a key role in SABA reliance and ICS underuse. [ABSTRACT FROM AUTHOR]

Recycling is always seen as an end-of-pipe process returning as much material as possible into a circular economy. There is a growing school of thought that suggests product design should be an important step in the recycling process. While this review is aimed specifically at one technological product, it contains facets that are applicable to the recycling of any complex product. Decarbonisation of energy production necessitates a proliferation of efficient electrical storage and a significant proportion of this, particularly in automotive propulsion, will use lithium ion batteries. The scale of the projected electric vehicle market means that a circular economy model needs to be established while the scale of end-of-life product is still manageable to prevent a build-up of hazardous waste. This critical review investigates the issues of lithium ion battery recycling and discusses the aspects of pack, module and cell design that can simplify battery dismantling and recycling. It highlights not only Green aspects of elemental recovery, but also technoeconomic features which may govern the appropriate direction for recycling. It also shows that as cell design changes, the approach to recycling can become more efficient. [ABSTRACT FROM AUTHOR]

Tracing the temporal dynamics of pathogens is crucial for developing strategies to detect and limit disease emergence. Canine parvovirus (CPV-2) is an enteric virus causing morbidity and mortality in dogs around the globe. Previous work in Australia reported that the majority of cases were associated with the CPV-2a subtype, an unexpected finding since CPV-2a was rapidly replaced by another subtype (CPV-2b) in many countries. Using a nine-year dataset of CPV-2 infections from 396 dogs sampled across Australia, we assessed the population dynamics and molecular epidemiology of circulating CPV-2 subtypes. Bayesian phylogenetic Skygrid models and logistic regressions were used to trace the temporal dynamics of CPV-2 infections in dogs sampled from 2007 to 2016. Phylogenetic models indicated that CPV-2a likely emerged in Australia between 1973 and 1988, while CPV-2b likely emerged between 1985 and 1998. Sequences from both subtypes were found in dogs across continental Australia and Tasmania, with no apparent effect of climate variability on subtype occurrence. Both variant subtypes exhibited a classical disease emergence pattern of relatively high rates of evolution during early emergence followed by subsequent decreases in evolutionary rates over time. However, the CPV-2b subtype maintained higher mutation rates than CPV-2a and continued to expand, resulting in an increase in the probability that dogs will carry this subtype over time. Ongoing monitoring programs that provide molecular epidemiology surveillance will be necessary to detect emergence of new variants and make informed recommendations to develop reliable detection and vaccine methods. [ABSTRACT FROM AUTHOR]

Pregnancy confers partner-specific protection against complications in future pregnancy that parallel persistence of fetal microchimeric cells (FMcs) in mothers after parturition. We show that preexisting FMcs become displaced by new FMcs during pregnancy and that FMc tonic stimulation is essential for expansion of protective fetal-specific forkhead box P3 (FOXP3)-positive regulatory T cells (T reg cells). Maternal microchimeric cells and accumulation of T reg cells with noninherited maternal antigen (NIMA) specificity are similarly overturned in daughters after pregnancy, highlighting a fixed microchimeric cell niche. Whereas NIMA-specific tolerance is functionally erased by pregnancy, partner-specific resiliency against pregnancy complications persists in mothers despite paternity changes in intervening pregnancy. Persistent fetal tolerance reflects FOXP3 expression plasticity, which allows mothers to more durably remember their babies, whereas daughters forget their mothers with new pregnancy-imprinted immunological memories.

More than 500 compounds chosen to represent kinase inhibitor space have been screened against a panel of over 200 protein kinases. Significant results include the identification of hits against new kinases including PIM1 and MPSK1, and the expansion of the inhibition profiles of several literature compounds. A detailed analysis of the data through the use of affinity fingerprints has produced findings with implications for biological target selection, the choice of tool compounds for target validation, and lead discovery and optimization. In a detailed examination of the tyrosine kinases, interesting relationships have been found between targets and compounds. Taken together, these results show how broad cross-profiling can provide important insights to assist kinase drug discovery.

A new machine learning method is presented for extracting interpretable structure-activity relationships from screening data. The method is based on an evolutionary algorithm and reduced graphs and aims to evolve a reduced graph query (subgraph) that is present within the active compounds and absent from the inactives. The reduced graph representation enables heterogeneous compounds, such as those found in high-throughput screening data, to be captured in a single representation with the resulting query encoding structure-activity information in a form that is readily interpretable by a chemist. The application of the method is illustrated using data sets extracted from the well-known MDDR data set and GSK in-house screening data. Queries are evolved that are consistent with the known SARs, and they are also shown to be robust when applied to independent sets that were not used in training.

A multiobjective evolutionary algorithm (MOEA) is described for evolving multiple structure-activity relationships (SARs). The SARs are encoded in easy-to-interpret reduced graph queries which describe features that are preferentially present in active compounds compared to inactives. The MOEA addresses a limitation associated with many machine learning methods; that is, the inherent tradeoff that exists in recall and precision which is usually handled by combining the two objectives into a single measure with a consequent loss of control. By simultaneously optimizing recall and precision, the MOEA generates a family of SARs that lie on the precision-recall (PR) curve. The user is then able to select a query with an appropriate balance in the two objectives: for example, a low recall-high precision query may be preferred when establishing the SAR, whereas a high recall-low precision query may be more appropriate in a virtual screening context. Each query on the PR curve aims at capturing the structure-activity information into a single representation, and each can be considered as an alternative (equally valid) solution. We then investigate combining individual queries into teams with the aim of capturing multiple SARs that may exist in a data set, for example, as is commonly seen in high-throughput screening data sets. Team formation is carried out iteratively as a postprocessing step following the evolution of the individual queries. The inclusion of uniqueness as a third objective within the MOEA provides an effective way of ensuring the queries are complementary in the active compounds they describe. Substantial improvements in both recall and precision are seen for some data sets. Furthermore, the resulting queries provide more detailed structure-activity information than is present in a single query.

Reduced graph representations of chemical structures have been shown to be effective in similarity searching applications where they offer comparable performance to other 2D descriptors in terms of recall experiments. They have also been shown to complement existing descriptors and to offer potential to scaffold hop from one chemical series to another. Various methods have been developed for quantifying the similarity between reduced graphs including fingerprint approaches, graph matching, and an edit distance method. The edit distance approach quantifies the degree of similarity of two reduced graphs based on the number and type of operations required to convert one graph to the other. An attractive feature of the edit distance method is the ability to assign different weights to different operations. For example, the mutation of an aromatic ring node to an acyclic node may be assigned a higher weight than the mutation of an aromatic ring to an aliphatic ring node. In this paper, we describe a genetic algorithm (GA) for training the weights of the different edit distance operations. The method is applied to specific activity classes extracted from the MDDR database to derive activity-class specific weights. The GA-derived weights give substantially improved results in recall experiments as compared to using weights assigned on intuition. Furthermore, such activity specific weights may provide useful structure--activity information for subsequent design efforts. In a virtual screening setting when few active compounds are known, it may be more useful to have weights that perform well across a variety of different activity classes. Thus, the GA is also trained on multiple activity classes simultaneously to derive a generalized set of weights. These more generally applicable weights also represent a substantial improvement on previous work.

This paper describes the development of a drug rings database and Web-based search tools. The database contains ring structures from both corporate and commercial databases, along with characteristic descriptors including frequency of occurrence as an indicator of synthetic accessibility and calculated property and geometric parameters. Analysis of the rings in several major databases is described, with illustrations of applications of the database in lead discovery programs where bioisosteres and geometric isosteres are sought.