They consider the interaction between contextual circumstances, theoretical mechanisms of change and the outcomes they produce, to arrive at explanations of conditional causality . This Commentary provides example applications using preliminary findings from a large realist implementation study of system-wide value-based healthcare initiatives in New South Wales, Australia. If applied judiciously, realist implementation studies may represent a sound approach to help optimise delivery of the right care in the right setting and at the right time.Implementation science in healthcare aims to understand how to get evidence into practice. Once this is achieved in one setting, it becomes increasingly difficult to replicate elsewhere. The problem is often attributed to differences in context that influence how and whether implementation strategies work. We argue that realist research paradigms provide a useful framework to express the effect of contextual factors within implementation strategy causal processes. Realist studies are theory-driven evaluations that focus on understanding  Replicating implementation successes from one healthcare setting to another remains an ongoing challenge for implementation science.Existing efforts to understand the process of implementation, and thereby facilitate the generalisation of implementation strategy success, has relied on dividing and studying contextual factors, theoretical mechanisms, and outcomes in isolation from one another.Realist research paradigms offer an analytical tool to articulate the explicit role of context within the causal process, moving beyond a catalogue of preconditions for implementation success.One consistent insight from implementation science in healthcare is that widespread practice change is difficult to achieve . Small sFaced with seemingly insurmountable challenges, it can be tempting to treat the problem as an operationalisation issue that can be solved with a blueprint of steps to follow or prescriptive checklists of successful ingredients. Over-reliance on these cookie-cutter types of approaches potentially conceals the deeply complex social process of implementation .composition of improvement initiatives to their properties. In other words, rather than seeking to understand every contextual element at play during implementation it would be more informative to discern the specific influence of contextual differences on the causal processes triggered by implementation strategies. For example, unpicking how implementation strategies like audit and feedback produce favourable outcomes [why they work in different ways depending on the contextual circumstances at play.We can observe this in the deployment of strategies to support improvement initiatives which do not necessarily match the barriers faced by clinicians at the point of care. In healthcare settings, implementation strategies comprise the specific means or methods for adopting and sustaining evidence-based programs or interventions . It is noutcomes –9, as wehow and why questions together. These questions are inextricably linked; neither operates independently like they do in relation to one another. Get this right and we can craft context-specific packages of implementation strategies, which squarely address variation in implementation outcomes across sites.We argue that the key to producing generalisable knowledge and predicting how large-system change might unfold lies in answering both these how and why different implementation science programs work under varying circumstances [Realist research paradigms  are permmstances . Realistmstances . They asmstances , 15.how and why implementation strategies work by linking three core pillars of evaluation [Realist research can offer a framework to understanding aluation : 1) contaluation . RealistMatching Michigan [Explaining Matching Michigan [Within implementation science, contextual factors, theoretical mechanisms, and implementation outcomes achieved through different implementation strategies are usually divided and studied in isolation . We arguMichigan , a two-yMichigan , one of why these may differ between sites and how they influence the social processes that impact outcomes [depending on the context. These are not competing theories of change; but rather alternative theories that are contingent upon the contextual circumstances. To advance the study of context in implementation science, research must move beyond cataloguing the conditions for implementation success and integrate context within causal processes. A nuanced understanding of context cannot be disconnected from causation [Context is often examined separately as compiled lists of important factors, which are not explicitly linked to outcomes . Understoutcomes , 24. Howausation . TherefoThe design of realist studies is method neutral, meaning multi-methods and mixed methods approaches are used . Their ehow processes drive these improvements; in this case, the successful rollout of a vaccination program and achievement of adequate herd-immunity levels. Yet the picture still seems incomplete without uncovering why herd immunity is achieved in one setting but not another. Herd-immunity might only be achieved in certain circumstances such as societies with prosocial motives which create an imperative for people who are responsible for transmission, but do not suffer from the disease, to get vaccinated.By understanding this grouping of contexts, mechanisms and outcomes, we can help clinicians bring together theory and empirical data in a way that is more representative of the actual realities they face in the health system. This framework for examining improvement initiatives uncovers the mechanistic processes or events through which they operate to enable change , 34. ForNote that context is considered as more than the setting in and of itself. Context encompasses the situation where improvement initiatives are implemented and crucially, the features of those situations that affect the process of improvement . ArticulWithin a realist paradigm, reality is stratified according to layers of ontological depth that make up the complete observable and non-observable world influencing the delivery of healthcare, see Fig. The layering of social phenomena is what differentiates realist implementation mechanisms from other conceptualisations of causal processes. The field of implementation science, like many other disciplines, is increasingly seeking to understand the mechanisms responsible for behavioural change. Lewis et al. have advanced this concept by articulating four step causal pathway models to generate empirical evidence with clear contextual boundaries . This caJolles Perez et al. addresses the challenge posed by complex health interventions by operationalising mechanisms as the “core functions” and “forms” of interventions . Core fuRecasting our focus to the mechanisms of implementation is reshaping how systems change is understood. New models are replacing the “black box” approach to evaluating improvement initiatives in healthcare, which focused on summative outcomes without sufficient explanation for how outcomes were achieved . Having Healthcare systems have reorganised over the past decade to improve health outcomes valued by society . ReducinOur realist study protocol has been published elsewhere and the findings are still under development . We illuClinical champions : Using clinical champions to lead large-system change is often included in implementation blueprints for healthcare improvement initiatives. It is assumed to work, but such assumptions prevent an interrogation of challenges faced and exploration of the full repertoire of potential solutions. We add to the emerging conceptual models for how and why clinical champions might work [ons Fig. : Using cght work . Six proAudit and feedback : Audit and feedback, as mentioned earlier, is another readily applied but often misunderstood approach to implementing clinical practice change. It is thought to work through many different channels  [ack Fig. : Audit ahanisms) . Our preIn our case, we are examining a complex intervention . TherefoThe idea of harmonising implementation strategies, context and interventions has been eloquently articulated by Haines’ et al. to maximize usability and usefulness of implementation endeavours . The keyThese examples bring to light a nuanced understanding of conditional causal chains for implementation. It is reasonable to believe that both clinical champions and audit and feedback strategies can (and do) support the implementation of healthcare improvement initiatives at scale; but realist studies make clear that they will only work in certain circumstances. Realist work shows that positive mechanisms are only triggered if certain contextual features are in place. Applying this lens both at the outset of initiatives, but also retrospectively, provides us with the insight that an enabling and conducive context is as important as the design of interventions. If we wish to replicate healthcare improvements across different sites and settings, we need to understand these subtleties involved in the process of implementation.how and why observed impacts occurred, and 3) the impacts on implementation outcomes, represents a way forward for delivering explanatory models for implementation science. A realist approach seeks to unify these three pillars influencing implementation science. Such contextually dependent implementation models enable tailoring of supportive structures, as well as articulating the expected benefits from these activities. By supporting the contemporaneous adoption and sustainment of evidence-based care, “realistic implementation” can uncover applicable evidence for and help optimise that the right care is delivered in the right setting to the right patient at the right time at the right cost.Exploring configurations of 1) the contextual circumstances conducive to triggering change, 2) theoretical causal mechanisms for


The prevailing patient safety strategies in suicide prevention are suicide risk assessments and retrospective reviews, with emphasis on minimising risk and preventing adverse events. Resilient healthcare focuses on how everyday clinical practice succeeds and emphasises learning from practice, not from adverse events. Yet, little is known about resilient practices for suicidal inpatients. The aim of the study is to draw upon the perspectives of patients and healthcare professionals to inform the conceptual development of resilient practices in inpatient suicide prevention.A narrative synthesis was conducted of findings across patients and healthcare professionals derived from a qualitative case study based on interviews with patients and healthcare professionals in addition to a systematic literature review.Three sub-themes categorise resilient practices for healthcare professionals and for patients hospitalised with suicidal behaviour: 1) interactions capturing non-verbal cues; 2) protection through dignity and watchfulness; and 3) personalised approaches to alleviate emotional pressure. The main theme, the establishment of relationships of trust in resilient practices for patients in suicidal crisis, is the foundation of their communication and caring.Clinical practice for patients hospitalised with suicidal behaviour has characteristics of complex adaptive systems in terms of dynamic interactions, decision-making under uncertainty, tensions between goals solved through trade-offs, and adaptations to patient variability and interpersonal needs. To improve the safety of patients hospitalised with suicidal behaviour, variability in clinical practice should be embraced.https://doi.org/10.1136/bmjopen-2016-012874 Our understanding of patient safety for patients hospitalised during a suicidal crisis is limited . In a syAccording to Hollnagel, the traditional view of safety, referred to here as safety-I is defined by the absence of accidents and incidents . ConsequRetrospective reviews of suicide incidents have focused on deficiencies in the interface between healthcare professionals (HCPs) and patients , 17, 18.A safety-I approach narrows the gap between what HCPs do in practice and their procedures for that practice . PatientThe field of resilient healthcare (RHC) has sought insight into healthcare practices and the ways in which everyday clinical practice succeeds –29. HollMental health services have been conceptualised as a CAS by Ellis, Churruca and Braithwaite , in whicA narrative synthesis was conducted of findings across two embedded units of analysis: the experiences of patients and the experiences of HCPs Table  40]. Th. Th40]. The literature review (sample 1) followed a systematic approach according to the PRISMA guidelines  and a co-moderator (SHB/MA). Sample 3 followed a sequential triangulation, with the first data set (focus groups) informing the nature of the second  . All intn = 2) or acute care (n = 2) while open wards specialised in rehabilitation (n = 3) or short-time stabilisation during a crisis (n = 2). Fifty-three individuals (patients and HCPs) participated in the empirical studies. All patient participants had active suicidal ideation during inpatient care, nine had recently attempted suicide prior to admission to mental healthcare, see Table The setting for the empirical studies  was a university hospital in Norway. We used purposeful sampling to recruit suicidal patients and HCPs working in open or locked wards in specialised mental healthcare facilities for adults. Participants were recruited from nine wards. Locked wards specialised in affective disorders . All participants provided voluntary informed and written consent. Patients were interviewed during hospitalisation and all of them were under the care of specialised HCPs. None of the researchers had a role as a clinician or manager in any of the seven units included in the study or had prior established relationships with the participants. Participants were informed of the rationale for the research: to get insight into safe clinical practices for suicidal patients.A narrative synthesis was conducted across methods and samples to find common themes reflecting both patients’ and HCPs’ perspectives, using the four stages of data synthesis as proposed by Whittemore and Knafl . The narThis narrative synthesis synthesised patients’ experiences and the HCPs’ experiences in the context of inpatient suicide prevention. The main theme, relationships of trust in resilient practices for patients in suicidal crisis, is the foundation of their communication and caring. The main theme was described by three sub-themes which illuminate three sets of relationships: interactions capturing non-verbal cues, protection through dignity and watchfulness, and personalised approaches to alleviate emotional pressure. Table The main theme, relationships of trust in resilient practices for patients in suicidal crisis reflected that resilient practices depended on trust between patients and HCPs, and that HCPs need alliances to establish trusting relationships with the patients. Trust is a precondition for resilient practices to adapt protection, treatment, and care to the needs of suicidal patients.Suicidal patients experienced the relationship to the HCPs as essential for a feeling of safety during inpatient care. They felt safe when they met someone who cared, validated their feelings and respected them as human beings. Trusting and familiar relationships with HCPs gave them predictability in terms of how their suicidal behaviour would be understood and treated. Trust is relevant to findings involving patients in vulnerable situations: being externally controlled, talking about suicide and relieving emotional pressure.HCPs experienced personal uncertainty in working with patients in suicidal crisis. They feared losing a patient to suicide while under their care, and they feared being held responsible by the health authorities and the hospital management. HCPs noted that their colleagues’ trust and support were necessary to manage uncertainty in clinical practice. HCPs formed and adapted their informal networks in response to the lack of formal support systems. Without support that could help HCPs cope with the uncertainty of working with suicidal patients, HCPs resorted to fear-based defensive practices to avoid blame and responsibility, which took time and focus away from the personalised activities with patients. However, social support and clinical supervision helped to counteract the impact of personal uncertainty in the patient contact.As such, resilient practices did not merely depend on strengthening the HCPs’ ability to establish trusting relationships with the patients, but also on ensuring that HCPs had reliable support systems.The resilient practice interactions capturing non-verbal cues described the interaction between the patient and the HCPs in the detection of suicidal crisis. Suicidal crisis was apparent not only in what patients did and did not say, but also in their body language and affect, as exemplified in Table Many of the patients expressed a struggle to communicate suicidal ideations during suicide risk assessment and acute suicidal crisis in the ward. They also experienced being recognised by HCPs who were attentive to their body language and to changes in their mental state. Patients noted that when their HCPs took a genuine personal interest in them, they were less likely to attempt suicide during inpatient care (sample 2).HCPs attended to multiple sources of information to make sense of suicidal behaviour including the non-verbal cues. The more experienced HCPs claimed that the formal procedures for assessing risk were not helpful during risk assessment, as the list did not take the context-sensitive and non-verbal behaviour into account. They improved their understanding by establishing relational contact with the patient and triangulating several sources of information, including the patients’ verbal and non-verbal cues, mental state, diagnosis and their own ‘gut feeling’. Expertise increased the complexity and the number of information sources that were considered to clarify the picture. Furthermore, HCPs improved their situational awareness of the patients’ suicide risk by seeking other perspectives, which involved reflecting with the patient, bringing other HCPs into conversations with the patient and discussing the case with more experienced colleagues and with doctors on call (sample 3).Interactions capturing non-verbal cues were grounded in relationships of trust. Patients described a trusted HCPs as someone who connected with them and understood their verbal and non-verbal cues of suicidal crisis (sample 2). When trusted HCPs were unavailable, patients in suicidal deterioration felt unsafe and vulnerable (sample 2). HCPs used experience and emotionally based competence to anticipate suicidal acts, and they perceived this process was strengthened by developing bonds of trust with the patient (sample 3).The resilient practice protection through dignity and watchfulness described the physical protection of patients with suicidal behaviour as a relational and interacting practice, depending on adaptations to ensure that each patient was physically protected, yet connected, as exemplified in Table Suicidal patients expressed a need for a safe balance among multiple needs for protection. Findings reflected that suicidal patients needed to be physically protected from death during suicidal crisis while feeling connected with the HCPs during observation. Lack of connection during observation made some patients feel unsafe and thereby intensified their suicidal behaviour (sample 1).Furthermore, patients’ need for protection during suicidal crisis changed in the course of hospitalisation and depended on a) their ability to establish relations with their HCPs and verbalise their needs; b) their need to withdraw from and master stressors in the outside world; c) their need for closeness to or distance from the HCPs; and d) their need for external control  or internal control . Thus, resilient practices were experienced when protection of the individual balanced his or her multiple needs (sample 2).HCPs were adjusting protection of the patient through dynamic trade-offs between under- and over-protection. While the formal procedure described observation as either constant or intermittent  intervals of observation, HCPs were constantly adjusting the observation practice towards the patient. Instead of watching the patients from a distance, they engaged with them, treated them with dignity, but kept an eye on them. Furthermore, HCPs were constantly balancing the physical protection of the patient from suicidal impulses with the risk of over-protection while increasing the patient’s sense of independence at the risk of under-protection. Thus, safe levels of protection were trade-offs between short- and long-term goals in care (sample 3).Protection through dignity and watchfulness was rooted in relationships of trust. The link between feeling safe and being safe was vital for suicidal patients; their physical safety could not be guaranteed if they felt vulnerable (sample 1). Lack of support from HCPs when patients were under constant observation made patients feel alienated and objectified, their suicidality worsened, and it supported their perception of worthlessness and the sense that no one cared about them (sample 1). Trust that HCPs were acting in the patients’ best interest was a prerequisite for patients’ feelings of safety when they were under external control (sample 2). Likewise, HCP adapted their approaches to protection to ensure patients understood they were acting in their best interest through explaining why doors were locked, and why they had to give away some personal belongings (sample 2) and treating patients with dignity during observation (sample 3).The resilient practice personalised approaches to alleviate emotional pressure described the adaptation of treatment and safety procedures that are made to meet individual patients’ needs. Patients experienced less emotional pressure and their suicidal impulses diminished as a result Table .Table 7EPatients emphasised that regaining a sense of control through coping with symptoms and difficulties was vital when they were having a suicidal crisis. Perception of control through gaining insight, coping with underlying difficulties and symptoms, and being prepared for discharge were essential for suicidal patients’ feeling of safety during inpatient care (sample 1).Personalised approaches to treatment addressed patients’ underlying mental health issues and stressors. This kind of treatment relieved their emotional pressure, whether it involved medications and physical protection to reduce psychotic symptoms or resolving financial issues to instill hope and a sense of relief from depression. These strategies helped suicidal patients feel safe from suicidal impulses through strengthening their sense of internal control. Talking about suicide also alleviated patients’ individual stressors, symptoms, or emotional pain. When conversations about suicide opened with standard questions and answers about suicide risk, they lost their therapeutic benefit and could evoke feelings of shame and hopelessness. Patients achieved a sense of control in a variety of ways. In the acute phases of their suicidal crisis, some patients wanted external control over their suicidal impulses because physical protection convinced them that they could not harm themselves (sample 2).HCPs targeted underlying issues by creating individual clinical pathways for suicidal patients. HCPs considered individualised approaches to be important in conversations about suicidal ideations; however, they experienced competing goals between documenting risk and understanding patients as individuals in practice (sample 3).Personalised approaches to alleviating emotional pressure are rooted in relationships of trust. Seeking help and talking about suicide place a suicidal patient in a highly vulnerable position. If they could not trust their HCPs, some patients withdrew from talking about suicidal ideations and stopped seeking help (sample 2). Likewise, HCPs perceived trusted relationships as a condition for honest responses in suicide risk assessment and described setting aside checklists and forms to prioritise making a trusting bond, a safe atmosphere and engaging with the patients in a dialogue when talking about suicide (sample 3).We identified three sub-themes categorising resilient practices for patients hospitalised with suicidal behaviour and HCPs: interactions capturing non-verbal cues, protection through dignity and watchfulness, and personalised approaches to alleviate emotional pressure. All three are grounded in relationships of trust in resilient practices for patients in suicidal crisis. These resilient practices outline a safety-II perspective in inpatient care of suicidal patients, which is based on culturally situated knowledge which cannot be generalised to all inpatient settings . HoweverThe shared understanding of resilient practices offers insight into clinical practice for patients hospitalised with suicidal behaviour. This clinical practice has the characteristics of a CAS , 63, 64,Interactions capturing non-verbal cues of suicidal inpatients reflect uncertainty in clinical decision-making. The findings correspond with previous studies suggesting that caring for suicidal patients involves uncertainty –67 and eProtection through dignity and watchfulness, and personalised approaches to alleviate emotional pressure emphasise that there is no one-size-fits-all approach to the protection and treatment of suicidal patients. Instead, practice relies on interpersonal and context-sensitive adaptations to ensure protection is safe , 31, 77.Relationships of trust in resilient practices for patients in suicidal crisis reflect that the complexity in clinical practice is characterised by the establishment of psychological and relational safety, which is only created through personalised and trusted relationships. Personalised relationships are the core characteristic of mental healthcare as a complex adaptive systems .In a CAS there will be unpredictable consequences of standardised patient safety interventions due to the need for adaptations in clinical practice to ensure safe outcomes. For those designing patient safety interventions at the blunt end of the system, deviations from the procedure may be perceived as an error to be corrected . HoweverThe CAS perspective of clinical practice in suicide prevention also has implications for learning. To learn from variability, it is necessary to move from simple linear models  to systemic models  focusing on why practices vary, succeed or fail at the clinical level, hospital management level and at the health system macro level , 30, 77.This study describes resilient practices which outline complexity in the clinical work in suicidal inpatient care. Some generic lessons regarding how to approach patient safety and suicide prevention at the micro level of the system are drawn based on the RHC perspective.In a CAS, it is impossible for the HCPs to anticipate all of the consequences of adjustments of procedures and trade-offs , 81. FeeFurthermore, suicidal patients’ experiences should inform the development of patient safety measures. This study finding corresponds with the literature that identifies trust as fundamental for hospitalised patients’ feelings of safety , 86. TheThis study implies that HCPs apply sensemaking strategies to improve their situational awareness of suicidal behavior. These strategies are enacted to gain a fuller meaning of the information they have obtained and a sense of what is going on in complex and ill-defined situations , 76, 91.Following the literature, this study highlights the importance of having experienced HCPs , who areLastly, this study implies that resilient practice should not rely solely on HCPs’ capacity to adapt without formal support systems. Without reliable sources of trust, the system is brittle. HCPs’ adaptive capacities may be overstretched and threaten the adaptive capacity of the system –105. TheThe ability to judge the quality of qualitative research rests on four characteristics: credibility, dependability, confirmability and transferability . TrianguDependability is strengthened in this synthesis by the provision of clear, detailed descriptions of all procedures and methods in the first author’s PhD thesis , the oriConfirmability is the degree of neutrality and researcher bias . ConfirmTransferability is the extent to which the findings can be transferred to other settings, context or groups . QualitaResilient practices for patients hospitalised with suicidal behaviour are experienced by those patients and their HCPs using three practice types: interactions capturing non-verbal cues, protection through dignity and watchfulness, and personalised approaches to alleviate emotional pressure. All of these practice types are grounded in relationships of trust.These practices inform the conceptual development of resilience in inpatient suicide prevention. The prevention of inpatient suicide is characterised by complexity related to changing, interrelated and variable patient needs in clinical practice and to the unpredictability of suicidal threats. Thus, inpatient suicide prevention demands adaptations and high levels of sensitivity towards the patient. To improve patient safety in this context, variability in clinical practice must be embraced. It is important to acknowledge the uncertainty in clinical decision-making regarding suicide risk and to avoid concluding that HCPs have performed an unsuccessful suicide risk assessment as the root cause of patient suicides. It is not possible to eliminate all uncertainty of suicide risk at the individual patient level. Nevertheless, it is possible to reduce emotional demands placed on HCPs by acknowledging the complexity and challenges involved in clinical decision-making regarding suicide.Strategies should strengthen feedback systems that foster communication between HCPs and between HCPs and their patients, and reinforce systems such as clinical supervision that ensure support for HCPs. This synthesis was limited to the suicide inpatient care at the micro level of the healthcare system. Future studies should include the roles of family, carers, and ward management.


Metals are needed by all living organisms to function properly and in plants they are taken up from the soil. In both natural and anthropogenic soils, plants are exposed to a wide range of metal concentrations. Plants have therefore evolved sophisticated mechanisms to cope with fluctuating levels of metal supply from deficiency to toxicity. Metalloproteins comprise almost half of all naturally occurring proteins, which underlines the importance of a balanced and sufficient metal availability. Among the most complex reactions in a plant cell, photosynthesis, respiration, and nitrogen fixation strictly depend on metals as catalysts and cofactors. Plants can regulate the balance of metals in the cell, to ensure sufficient supply of metals to maintain substantial reactions and on the other hand, to protect the cell from damage and toxicity by allocating harmful metals. The nine articles collected for this Research Topic describe different aspects of metal homeostasis, with a special focus on the essential metals copper (Cu), iron (Fe) and zinc (Zn).Wiggenhauser et al. recommendations are given to better exploit the information provided by varying isotope compositions, to further advance the non-traditional isotope process tracing of metals in plants. Isotope fractionation describes the small changes in relative isotope abundances during chemical reactions or physical processes. Several processes drive isotope fractionation in plants and for instance, changes in nutrient supply induced shifts in isotope fractionation patterns for Mg, Cu and Zn, suggesting that isotope process tracing can be used as a tool to provide information on acquisition mechanisms, e.g. active or passive uptake. Using this technique, Blotevogel et al. analyzed stable Cu isotope ratios in Grapevine (Vitis vinifera). It turned out, that there was no direct relationship between Cu contents in soils or soil solutions and Cu contents in roots, indicating a partly homeostatic control of Cu uptake. However, at low Cu supply, the Cu-isotope fractionation between soil solution and roots showed that isotopically light Cu was preferentially taken up whereas heavy Cu isotopes were increasingly taken up at high Cu supply levels, suggesting a shift from active to passive uptake mechanisms. The authors emphasize that Cu isotope analysis is a sensitive tool to monitor differences in Cu uptake and translocation pathways even before differences in tissue contents become obvious.In the review by Mancini and Garcia-Molina describes the consequences of simultaneous Cu and Fe deficiency in Arabidopsis thaliana with a particular investigation of alternative splicing events on the transcriptome of rosette leaves. Functional annotation of transcript changes detected under Fe and Cu deficiency revealed that differently expressed genes belong to general stress responses and the translation machinery, while differently spliced genes belong to metabolic reactions, more specifically amino acid biosynthesis. The authors propose that during systematic reprogramming, alternative splicing could act as an independent mechanism to regulate metabolic reactions, which are not adjusted at the transcript or protein level. In a minireview by Su et al. the aspect of chromatin-based regulation in response to the plant Fe status is highlighted and involves histone modification and DNA methylation. Histone trimethylation cannot only induces chromatin condensation resulting in gene silencing during Fe sufficient conditions, but can also activate corresponding target genes in Fe deficient conditions in Arabidopsis thaliana. In rice plants, DNA hypermethylation, in the promotor region of corresponding downstream genes, leads to enhanced transcription during Fe deficiency, whereas the unmethylated stage confers a basal expression of Fe homeostasis genes.The work by Kandwal et al. which contain high concentrations of Fe and Zn in the rice grain, without affecting growth in a paddy field. This rice line possessed a non-sense mutation of the vacuolar localized Fe transporter OsVIT2 and thus Fe and Zn relocation changed in benefit of the grain. The line used in that study is an EMS-mutagenized rice line and therefore offers many advantages compared to transgenic approaches. It highlights the use of OsVIT2 mutations in marker-assisted breeding programs for future grain biofortification of Fe and Zn. To develop strategies for improving Zn content in legume crops, the mechanisms of response to Zn deficiency in the legume model Medicago truncatula was investigated by Liao et al. In legumes species, an adequate supply of Zn to the nodule-rhizobia infected cells is required to ensure optimal symbiotic nitrogen fixation. Two F-group basic region leucine-zipper (F-bZip) transcription factors were described and functionally characterized in M. truncatula, and MtFbZIP1 was identified as a key regulator of the Zn deficiency response related gene expression. Another approach to overcome crop Zn deficiency is described by Li et al. where the authors studied foliar Zn fertilization in sunflower leaves and subsequent translocation by transcriptome analysis combined with synchrotron-based X-ray fluorescence microscopy (XFM). It was observed that foliar Zn application caused rapid stress to the leaf, but once the stress decreased Zn was moved from the leaf epidermis to the vascular tissues. However, it was proposed that loading of Zn into the phloem, or the limited Zn mobility within the phloem itself, determine the restricted translocation of foliar applied Zn in sunflower leaves.A useful breeding line is described by Yang et al. reports of a novel rice mutant with delayed Casparian strip formation and ectopic suberin depositions in small lateral roots. As a consequence, the mutant showed higher concentrations of Fe, manganese (Mn) and sodium (Na) and a reduced tolerance to salt stress due to altered ion permeability. The affected gene encodes a Casparian strip membrane domain protein, which may form a transmembrane scaffold to recruit lignin biosynthetic enzymes.In terrestrial plants nutrients are mainly taken up through the roots. The Casparian strip represents a physical barrier controlling the inward flow of water and nutrients. via the whole plant of submerged macrophytes is described by Xian et al. by comparing two species with different tolerances to ammonium. Ammonium uptake through the above-ground part was dominant under excess ammonium conditions, and the tolerant species possessed a higher plasticity in ammonium utilization under various concentrations and is a good candidate for applications in phytoremediation of polluted water.In the water ecosystem nutrient uptake All authors listed have made a substantial, direct and intellectual contribution to the work, and approved it for publication.


Methane is the second most important greenhouse gas after carbon dioxide and contributes up to 20% to current global warming. Microbial methane oxidation plays a significant role in mitigating methane emission to the atmosphere and therefore is a crucial process to understand in the battle against climate change, where methane mitigation has highest priority as recently reported by the IPCC. Methanotrophs have long been believed to be exclusively dependent on methane for carbon and energy. However, discoveries in the past two decades have demonstrated a much higher metabolic versatility of these environmentally highly relevant microbes. Methanotrophs have been shown to utilize multi-carbon compounds in addition to methane, presumably deriving a competitive advantage from this metabolic versatility. They also can oxidize ammonia, fix nitrogen, catalyze denitrification, execute parts of sulfur metabolism and glycolysis under environmental stress such as nitrate, volatile sulfur compounds and low oxygen concentrations. Additionally, it has been shown that microbial methane oxidation can be coupled to denitrification, sulfate reduction and metal reduction such as iron and manganese under anoxic conditions. These novel insights into the metabolic versatility of methanotrophs also has implication for the interaction with other organisms in the environment. Methanotrophs have been demonstrated to provide methane-derived carbon to food chains in terrestrial and aquatic ecosystems designated them as “primary producers”.2 fixation, and their interaction with non-methanotrophs in natural habitats. Three studies focused on the characterization of the community structure and metabolic characteristics of methanotrophs in association with archaea under anoxic conditions. The last study reported on the response of microbial communities and methane fluxes to climate change in glacier foreland soils.This Research Topic consists of seven original articles aiming at identifying metabolic pathways and biogeochemical processes involved in environmental microbial methane oxidation. Three of these studies investigated the metabolic capabilities of proteobacterial methanotrophs, including methanethiol oxidation, NSchmitz et al. used Methylacidiphilum fumariolicum SolV as a model organism and found that methanotrophs could oxidize methanethiol and produce H2S, which could be further oxidized. This might be a widespread detoxification mechanism in methanotrophs in a range of environments. Cao et al. reported on methane oxidation-induced N2 fixation that led to methanotrophy-primed mineralization, which accounted for 21.7% of total nitrogen involved in facilitation of root carbon turnover. DNA-based stable isotope probing indicated that gammaproteobacterial methanotrophs  dominated N2 fixation in methane-consuming rice roots. Similarly, Cui et al. observed that N2 fixation was enhanced in the presence of methane, which might be related with Diazotrophic Methylosinus species of the family Methylocystaceae. These findings expand the knowledge on interactions of methane and nitrogen cycling providing input for management strategies to mitigate methane emissions from natural and engineering systems while reducing nitrogen input.Methanotrophs have been shown to be versatile in the metabolization of substrates such as ammonia, multicarbon compounds and nitrate in addition to methane, thereby presumably deriving competitive advantages in their habitats. 3+. Anaerobic methanotrophic archaea (ANME) are the main agents in AOM that can be divided into three groups: ANME-1 (ANME-1a and ANME-1b), ANME-2  and ANME-3. Although ANME are often linked to sulfate reduction, Chen et al. reported the participation of ANME in iron reduction coupled to methane oxidation (Fe-AOM) with ANME-1a representatives as key players in an active cold seep in the mid-Okinawa Trough. Co-occurrence analysis revealed that the methanogen/ANME population and some heterotrophic microbial groups could interact metabolically through an anaerobic food chain. Ouboter et al. demonstrated the capacity of members of the Candidatus genus Methanoperedens to transfer electrons extracellularly forming a bio-electrochemical system. These results hold great promise in coupling methane mitigation to the generation of electricity. Additionally, Su et al. also reported that proteobacterial methanotrophs could grow on methane under both oxic and anoxic conditions, although methane oxidation activities were an order of magnitude higher under oxic conditions. This suggested that bacterial AOM by facultative aerobic methane oxidizers might be of much larger environmental significance in reducing methane emissions than previously thought.Anaerobic oxidation of methane (AOM) plays a crucial role in regulating methane emissions from anaerobic habitats, which has been reported to be make use of electron acceptors such as NOXing et al. reported that due to global warming and subsequent glacier retreat, glacier foreland soils changed from methane sinks to methane sources under influence of glacial meltwater. This suggests that enhanced glacial retreat may have positive feedbacks global warming by the modulation of methane cycling microbial communities in these systems.Human activities and climate change can influence microbial communities and methane fluxes from the environment. Methanogens and methanotrophs are responsible for biological methane cycling in various environments, and their relative activities determine the global methane dynamics. Next to this, methane dynamics in the natural environments is controlled by environmental factors such as nutrient availability, vegetation coverage, terrain micro-topography and temperature. Taken together, the set of papers in this Research Topic broaden our horizon on the traits of methanotrophs. The expanding versatility may have major implication in the control of methane cycling in many relevant habitats. It emphasizes the role of methanotrophs in carbon, nitrogen and sulfur cycling and the interactions with non-methanotrophs, the outcome of which can have major implication for many biogeochemical cycles. Further understanding of this fascinating group of microbes and their metabolic flexibility will be crucial in not only predict future methane fluxes but also the impact on other elemental cycles. Additionally, knowledge on traits of methanotrophs will be key in developing biotechnological applications of methanotrophs for facilitating a sustainable future.RH, PB, ZJ, and PX wrote and edited the manuscript. All authors have contributed substantially to the article and approved the manuscript for publication.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


In 2019–2020, four national recommendations were published in the UnitedKingdom to encourage use of low carbon inhalers. This study aimed toinvestigate whether these were associated with a change in primary caredispensing in England and to explore associations between geographicalvariation and clinical commissioning group (CCG) characteristics.Ecological study using aggregated publicly available data.All CCGs in England (March 2016 to February 2021).not applicablePercentage of low carbon inhalers dispensed.The percentage of low carbon inhalers dispensed was 26.3% in 2020–2021 . This decreased over the study period for short-actingbeta-agonist (SABA), inhaled corticosteroid (ICS) and ICS+long-actingbeta-agonist (LABA) inhalers. The same trend was seen for LABA andICS+LABA+long-acting muscarinic antagonist inhalers from 2019. The SABA andICS classes were less often dispensed as low carbon inhalers (⁓6% versus35–45%). Interrupted time series analyses found slight increases in lowcarbon inhaler percentage in the SABA, LABA and ICS classes after April2019, which were soon erased by the long-term trend. There was alsogeographical variation, with the north-west, Birmingham and Londonconsistently dispensing more low carbon inhalers. The presence of advice onclimate change in CCG formularies/guidelines, the prevalence of asthma andpopulation age profile were associated with significant variation in lowcarbon inhaler percentage for some classes.The percentage of low carbon inhalers dispensed in England remains low andcontinues to decrease. Greater use of low carbon inhalers is achievable, butis more likely with locally implemented initiatives. Importantly, hydrofluoroalkane propellants released from pressurised metereddose inhalers (pMDIs) are powerful greenhouse gases and contribute 3% of the NHS’scarbon footprint. Typical pMDIs release 9–36 kg carbon dioxide equivalent (CO2e) perinhaler, whereas propellant-free dry powder inhalers (DPIs) have an estimated carbonfootprint of <6 kg CO2e per inhaler. Similarly, life cycle analysis has estimated that pMDIs using currentHFC-134a and HFC-227ea propellants have a global warming potential of 263 and697 g CO2e per dose respectively, whereas DPIs have aglobal warming potential of just 9 g CO2e per dose. However, DPIs were assessed as having a larger environmental impact thanpMDIs in 8 of 14 other categories, and potential future use of HFC-152a as a pMDIpropellant would produce just 20 g CO2e per dose. In addition, evidence suggests that there is no difference in the efficacy ofpMDIs and DPIs in asthma and chronic obstructive pulmonary disease (COPD) whenpatients have good inhaler technique. Consequently, the 2019 NHS long-term plan proposed increased use of lowercarbon inhalers in order to reduce use of pMDIs.To face the challenge of climate change, the UK government has committed to achievingnet zero greenhouse gas emissions by 2050. This will require the National HealthService (NHS) in England to reduce its emissions, as they are currently equivalentto 4% of England’s total carbon footprint. Three months later, an update to the British Guideline on the Management ofAsthma included a new section on the environmental impact of pMDIs and recommended‘that inhalers with low global-warming potential should be used when they are likelyto be equally effective’. In February 2020, the Primary Care Respiratory Society’s position statementon this issue recommended a multifaceted approach, including improvements indiagnosis and disease management, increased inhaler recycling and switching frompMDIs to propellant-free inhalers ‘where the change is clinically appropriate, safeand acceptable to patients’. This document also highlighted the importance of individual patients’clinical needs remaining the primary focus for clinicians and did not support massswitching between types of inhalers. Similarly, in March 2020, the British ThoracicSociety published a position statement on the environment and lung health thatrecommended the prioritisation of DPIs, switching from pMDIs to DPIs where patientscan use their new inhaler safely, optimisation of inhaler technique and increasedinhaler recycling. However, other authors have concerns about some of these approaches,including the risk of destabilising disease control when switching between inhalers,the wider environmental impact of DPIs and the advantages of pMDIs for certainpatient groups, such as the very young and old.11In line with this high-level policy, in the 12-month period beginning April 2019,four documents were published by respected professional bodies in the UK with theaim of increasing use of low carbon inhalers such as DPIs. In April 2019, theNational Institute for Health and Care Excellence (NICE) published a patientdecision aid highlighting the carbon footprint of different types of inhaler in asthma. a pMDI with spacer is preferred for young children and some elderly people may be unable to generate sufficient inspiratory flowto use a DPI. Some authors have suggested that marketing strategies and prescriber andpatient preferences also influence choices between pMDIs and DPIs. It has also been suggested that advice on the environmental impact ofinhalers could be expressed more explicitly and so some clinicians may not be awareof this topic, especially if local policies and guidelines have not been updated. Finally, ethical and safe switching of an established pMDI to a DPI requiresa face-to-face consultation to obtain the patient’s informed consent, identify a DPIthat they can use appropriately and provide training. The capacity to provide such consultations may also be a barrier to reducingpMDI use. The key influences on inhaler selection therefore include cost, healthcareprofessional knowledge of devices, the inhalation manoeuvre achieved, the patient’sability to use their device correctly and their personal preferences. It is therefore uncertain whether the recent guidelines and positionstatements are sufficient to change prescribing behaviour, especially as the mostrecently published data on inhaler usage in the UK relate to 2017, so evaluation of the impact of such documents has been recommended.There are many barriers to reducing pMDI use that may not have been addressed by thepublication of such documents. For example, some DPIs have a greater upfront costthan equivalent pMDIs,To quantify temporal and geographical variation in the proportion of lowcarbon inhaler dispensing relative to total inhaler dispensing over thepast five years;To explore the association between geographical variation and variablessuch as asthma and COPD prevalence, population age profile and thecontent of local guidelines.The aim of this study, therefore, was to investigate if recent recommendations areassociated with a change in low carbon inhaler dispensing in primary care inEngland. Specific objectives were: This ecological study used aggregated data from several publicly available datasources in England. Data related to primary care, as this is where most inhalers areprescribed. The monthly number of inhaler items dispensed and their cost (at the‘product format’ level) were extracted for the five pharmacological classes ofinhaler where both pMDIs and low carbon inhalers were available: short-actingbeta-agonist (SABA), long-acting beta-agonist (LABA), inhaled corticosteroid(ICS), ICS plus LABA combination (ICS+LABA) and ICS+LABA plus long-actingmuscarinic antagonist combination (ICS+LABA+LAMA) devices. Within these classes,pMDIs and low carbon inhalers  were identified. Other pharmacological classes were excluded,as they did not include both pMDIs and low carbon inhalers. Items were definedas the number of times an inhaler was dispensed; the number of individualinhalers dispensed was not available.Clinical commissioning group (CCG)-level dispensing data for England from March2016 to February 2021 were obtained from OpenPrescribing.net. . CCG asthma and COPD prevalence (%),emergency hospital admissions , mortality rates and adult smoking prevalence (%) were obtained fromPublic Health England . Local formularies and guidelines onCCG public websites in May 2021 were reviewed to record the presence or absenceof advice on the carbon footprint of inhalers and the number of recommendedpMDIs and low carbon inhalers in each pharmacological class . A small amount of CCG data were unavailable from theirrespective data sources .CCG population age profiles (percentage aged under 15 and over 80 years) for 2019were obtained from the Office for National Statistics To fit the data, Poisson regression models were used for SABA, ICS andICS+LABA inhalers and polynomial models for LABA and ICS+LABA+LAMA inhalers.Data for March 2020 were excluded since they were affected by the initialCOVID-19 outbreak and were therefore outlying .Statistical analyses were performed using RStudio Version 1.4.1717. To controlfor changes in the volume of inhaler dispensing, the key outcome measure used inthis study is the percentage of low carbon inhalers dispensed, defined as thenumber of low carbon inhaler items dispensed relative to the total number ofpMDI and low carbon inhaler items. In addition, the average cost for pMDI andlow carbon inhaler items was defined as the total cost of these items divided bythe total number of items. Interrupted time series (ITS) analysis with segmentedregression was used to investigate the temporal variation in low carbon inhalerpercentage for all the five classes of inhalers.The consistency of CCG low carbon inhaler percentage between the fivepharmacological classes was assessed by calculating Cronbach’s alpha for totaldispensing from March 2020 to February 2021. Multivariable regression was usedto investigate the geographical variation for all five classes of inhalers, eachtotalled over the 12-month period from March 2020 to February 2021. Dependentvariables were low carbon inhaler percentage for LABA and ICS+LABA+LAMA classes,and the natural logarithm of low carbon inhaler percentage for SABA, ICS andICS+LABA classes, for a better fit of the model and reduced multicollinearity.Univariable Pearson’s correlation analyses were used to identify independentvariables for inclusion in multivariable regression models; those with acoefficient of determination >0.1 for at least one class were included forall classes, along with those that were clinically useful. This led to therejection of adult smoking prevalence and the number of recommended pMDIs in CCGformularies as independent variables. Therefore, multivariable regression modelswere constructed with the independent variables being the other CCG populationand guideline characteristics described in Section ‘CCG characteristicsdata’.The monthly number of low carbon inhaler items showed a gradually decreasingtrend for all classes except ICS+LABA+LAMA inhalers, where both pMDI and lowcarbon inhaler items increased quickly after these products came to the marketin 2017–2018 . In the SABA and ICS classes,pMDI items were relatively stable over the five years, whereas ICS+LABA pMDIitems increased. LABA pMDIs and low carbon inhaler items both decreased over thefive years. Dispensed items for all categories of inhalers peaked in March 2020,during the initial outbreak of COVID-19 in the UK. In addition, there were smallpeaks in December and January each year for all types of inhalers. Over the five years, there was a decreasing trend of similar relativemagnitude for the SABA, ICS and ICS+LABA classes. Low carbon inhaler percentageincreased for the LABA class over the five years, but showed a decreasing trendsince 2019. ICS+LABA+LAMA low carbon inhaler percentage increased during theirfirst year on the market (2018), but subsequently started to decrease. The SABAand ICS classes also showed seasonal variation in low carbon inhaler percentage,with peaks in the spring and summer months.Small, non-significant increases in low carbon inhaler percentage were observedin the SABA, LABA and ICS classes after publication of the NICE decision aid inApril 2019; however, this was soon erased by the long-term downward trend.Small, non-significant decreases were seen in the ICS+LABA and ICS+LABA+LAMAclasses. Similar results were obtained with the point of intervention set inOctober 2019 and April 2020 .There were several geographical clusters of CCGs that provided advice on thecarbon footprint of inhalers in their formularies of guidelines, such as in theeast of London and the north west of England .A similar distribution of asthma and COPD prevalence was observed .13 and 2017 in England, when approximately 70% of inhalers sold or dispensed were pMDIs. Even for thepharmacological classes with the highest proportion of low carbon inhalers, overhalf of items dispensed during the study period were pMDIs. This is the first studyto report temporal trends in low carbon inhaler use. Although the overall low carboninhaler percentage increased from 2016 to 2021, this was driven by the introductionof ICS+LABA+LAMA inhalers in 2018. All classes of inhaler showed a trend ofdecreasing low carbon inhaler use since 2019, and for the SABA, ICS and ICS+LABAclasses this trend was seen throughout the five-year study period. This has occurreddespite the publication of national guidelines and policies that promote the use oflow carbon inhalers,69 which were not followed bysignificant changes in the dispensing of low carbon inhalers.The overall use of low carbon inhalers in this study was low (26.3%), which issimilar to studies examining the years 2002–2008 in the UK This might be related to the higher cost of low carbon inhalers in the SABAand ICS classes, whereas costs for low carbon inhalers and pMDIs were similar in the otherthree classes. In addition, national guidelines recommend use of a SABA pMDI withspacer during mild–moderate asthma attacks.There were also large differences in low carbon inhaler dispensing between classes.The lowest proportion was for SABA and ICS inhalers, which were two of the threemost commonly dispensed classes. Previous studies have not considered variationbetween such specific classes of inhaler, but a study based on English dispensingdata in 2017 found similar proportions of pMDI dispensing for both the SABA class(94%) and ‘devices that contained an ICS’ .21 and other countries. The presence of advice on climate change in CCG formularies or guidelines wasassociated with small increases in the proportion of low carbon inhaler dispensingfor the two classes with the lowest overall percentage (SABA and ICS). This suggeststhat local initiatives may be important in achieving this NHS long-term planambition, as has also been found in studies of both respiratory and non-respiratorydiseases.24 A higher proportion of the CCG population aged under 15 yearswas associated with a lower proportion of ICS and ICS+LABA low carbon inhalerdispensing, which may be related to the national guideline recommendation to use apMDI and spacer for young children. However, the same guidelines also found high-quality evidence that for thedelivery of beta-agonists and ICS in stable asthma there is similar safety andefficacy data for both pMDIs and DPIs in people aged over five years, although asthis evidence is 20 years old it is not based on more recent DPI designs.There was considerable geographical variation in low carbon inhaler dispensing foreach class, with evidence of similar prescribing practices in neighbouring CCGs.This has not been previously investigated for low carbon inhalers, but regionalvariation has previously been observed in other aspects of the treatment of asthmaand COPD in the UKThe first strength of this study is its novel exploration of temporal andgeographical variation in the dispensing of lower carbon inhalers in fivespecific pharmacological classes. The second strength is the use of detaileddispensing data covering the whole of England over a five-year period, thusreducing the risk of bias from sampling or reliance on surrogate measures. Animportant limitation is that the available data present the number of dispenseditems instead of the number of inhalers, but there is no evidence to suggestthat the number of inhalers per item varies between pMDIs and low carboninhalers, so this limitation is unlikely to have affected the findings. The useof aggregated rather than individual-level dispensing and populationcharacteristics data limited the ability to explore the influence of individualpatient factors on low carbon inhaler use. In addition, the study periodincluded the first year of the COVID-19 pandemic in the UK, which causeddisruption to prescribing patterns and longer-term NHS projects, such as thoseintended to reduce pMDI use. Finally, causal inferences cannot be drawn fromthese data, so findings should be interpreted with caution.There are several significant implications of this study. First, it is clear thatthe national initiatives introduced up until the end of March 2021 wereinsufficient to achieve the ambition of the NHS’s long-term plan to increase useof low carbon inhalers. However, local initiatives by CCGs may have had someinfluence. Although this policy has been contested by some clinicians, furtherinitiatives will be required if it is still the aim of the NHS to achieve thisobjective. This study suggests that such initiatives should include at leastsome elements that are implemented locally and that focusing on the ICS classmight be an initial priority, as it is the third most frequently dispensed classand currently has a very low proportion of low carbon inhalers. While SABAinhalers are the most frequently dispensed and have the lowest proportion of lowcarbon inhalers, national guidelines currently recommend use of SABA pMDIs inacute asthma, so initiatives focused on this class may be less appropriate. Suchapproaches will need to overcome the barrier of the greater financial cost ofSABA and ICS low carbon inhalers. A focus on the use of low carbon inhalers forolder children prescribed ICS and ICS+LABA inhalers may also be beneficial,while still considering that over half of LABA, ICS+LABA and ICS+LABA+LAMAinhalers currently used in England are pMDIs. Further research is required todevelop and validate interventions based on these recommendations. As this initiative will be locally implemented, aimed at non-SABAinhalers and addresses financial barriers, it is partially aligned with thefindings of this research and may prove to be more successful than theapproaches employed so far. However, it should be noted that this scheme wassuspended in December 2021 in order to accelerate delivery of COVID-19 booster vaccinations.From October 2021, NHS England and Improvement’s Impact and Investment Fundincluded a series of financial incentives for primary care networks to encourageincreased use of low carbon inhalers.11 Whenever a new low carbon inhaler is started, whether as anew treatment or as a replacement for a pMDI, patients require a face-to-faceconsultation to provide training and ensure that they can use their new device correctly. As well as focusing on use of low carbon inhalers, further work is alsorequired to ensure that the management of all patients with respiratory diseasesis in line with current best practice,11 as this will benefit bothindividual patients and potentially the environment (through reduced consumptionof resources to treat acute exacerbations). Finally, initiatives are alsorequired to reduce the use of brands of pMDI with the highest carbon footprintand increase recycling of both pMDIs and DPIs, which may help to offset some ofthe other environmental impacts of these devices.11It is essential that all initiatives in this area require individual patients’informed consent and that low carbon inhalers are only used when clinicallyappropriate, safe and acceptable to patients, whose individual needs must remainparamount.Despite the publication of numerous national policies and guidelines, the proportionof low carbon inhalers dispensed in England between 2016 and 2021 decreased for theSABA, ICS and ICS+LABA classes. The same trend was seen for the LABA andICS+LABA+LAMA classes from 2019 onwards. The considerable variation betweenpharmacological classes and CCGs suggests that greater use of low carbon inhalers isachievable, but is more likely to be achieved with locally implemented initiativesfocused on key barriers, classes of inhalers and types of patients.https://doi.org/10.15125/BATH-01142Data are available in a public, open access repository. All data created during thisresearch are openly available from the University of Bath Research Data Archive atClick here for additional data file.Supplemental material, sj-pdf-1-jrs-10.1177_01410768221133566 for Temporal andgeographical variation in low carbon inhaler dispensing in England, 2016 to2021: an ecological study by Jianghan Tian, Anita McGrogan, Matthew D Jones inJournal of the Royal Society of Medicine


Machine learning—the ability of computers to “learn” to perform a task rather than being explicitly programmed for the purpose—has seen significant developments in recent years. Biomedical research is no exception to its far-reaching impact and has seen more than a ten-fold increase in the number of publications related to machine learning in the last decade . In thisMainali et al., machine learning algorithms can have particular utility in alleviating two of the clinical challenges of stroke: the time-sensitive nature of the acute-phase treatment and the difficulty of predicting outcomes, especially in the acute phase. Given these potential benefits, calibrating the algorithms to prevent excessive alerts and supporting physician autonomy through careful assessment of human-computer interaction is key to maximizing adoption  are one of the principal sources of standardized clinical information on a patient and can serve as a valuable starting point for algorithm development. The results of  studies , 5 and cLineback et al. employ Natural Language Processing (NLP) to glean freeform textual data. In contrast, Rajashekar et al. combines MRI and CT imaging data to improve prediction models trained solely on EHR data. Multimodal approaches can require more sophisticated models to extract information from various data types but more closely approximate decision-making by physicians and better integrate multifaceted information collected via clinical investigations and examinations.Complementation of EHR data with additional modalities of clinical investigations holds promise in further improving prediction accuracy. Herein, McLouth et al. validate the performance of a commercially available deep learning software in assessing intracranial hemorrhage and large vessel occlusion using CT images. Implementing analysis software within the imaging workflow can provide venues where machine learning algorithms can seamlessly integrate into clinical decision-making. Furthermore, incorporating features from MRI scans, such as in the study by Xiao et al. predicting hypoperfusion in ischemic stroke patients, could define a clinically relevant threshold that directs decision-making in a facile manner. Integration of images in machine learning algorithms provides several benefits, including higher accuracy of diagnosis and improved objectivity compared to physical examinations. Given that imaging is routinely performed for stroke patients and is uniquely capable of providing functionally relevant anatomical information, image analysis models are promising candidates for clinical deployment in stroke care.Imaging is a rich source of information. Imaging has critical clinical relevance in neurology and a high affinity for sophisticated deep learning models, such as convolutional neural networks. Indeed, many of the recent advances in machine learning in healthcare have centered on image analysis, including the use of retinal images for cardiometabolic disease prediction –9 and anKim et al. to identify acute central dizziness and by Lin et al. to identify mild stroke patients at risk of disability exemplify the possibilities—supporting physicians in making challenging clinical decisions. Both models closely approximate or outperform existing risk scores without requiring extensive neurological examinations, allowing more patients to be screened and thus reducing the chances of a deteriorating patient escaping notice.Machine learning can be an invaluable asset, especially in cases where diagnosis requires extensive examination or training or when the diagnosis is based on subtle features and are thus inherently prone to misdiagnosis. The algorithms described by Rana et al. and Darabi et al. have only used administrative data from EHR with additional clinical variables such as NIHSS. By contrast, mining the free text in the patient chart  pose significant challenges. The free text is written by multiple clinicians, often with successive clinicians copying and pasting the written comments by the previous clinicians (via transfer learning using site-specific data achieved superior results for external cohorts (While machine learning holds promises, several challenges persist in implementing these technologies in healthcare. First, technical limitations can stem from the type and quality of the datasets available. EHR data can often be poorly standardized and sparse, posing problems in model generalizability. Investigators such as inicians  in additinicians . Howeverinicians . Sophistinicians . Attribu cohorts , and con cohorts , 22. It Cui et al. used feature importance metrics to rank specific features mainly associated with predictive capability in each machine learning model. Analyses of feature importance could prove helpful in guiding intervention, especially if a factor is consistently listed as important across multiple models. For image analysis models, localization maps generated by methods such as Grad-CAM (Secondly, more complicated machine learning models can often be challenging to interpret, hindering the translation from prognosis to patient management. High-performing “black box” models lacking interpretability are of limited use in the clinic as they do little to inform physicians of actionable points. In particular, identifying modifiable risk factors is essential in the primary and secondary prevention of cerebrovascular events. To this end, Grad-CAM  could prFinally, ethical considerations must not be ignored. Model predictions can often be influenced by the socioeconomic, racial, and gender composition of the training datasets, the awareness of which is necessary to mitigate potential biases in models. For example, machine learning models were found to consistently underdiagnose patients in disadvantaged populations across three large chest X-ray datasets, especially where a patient was a member of more than one underserved group . The preIn conclusion, recent developments in machine learning present ample opportunities for automated models that guide clinical decision-making and improve patient outcomes. The studies included herein represent selections of advances employing machine learning in various contexts in stroke care in our collective efforts to promote improved patient health through effective prevention, diagnosis, and intervention.All authors listed have made a substantial, direct, and intellectual contribution to the work and approved it for publication.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The handling editor J-CB declared a shared affiliation with the author YK at the time of review.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Gait disturbances are common manifestations of Parkinson’s disease (PD), with unmet therapeutic needs. Inertial measurement units (IMUs) are capable of monitoring gait, but they lack neurophysiological information that may be crucial for studying gait disturbances in these patients. Here, we present a machine learning approach to approximate IMU angular velocity profiles and subsequently gait events using electromyographic (EMG) channels during overground walking in patients with PD. We recorded six parkinsonian patients while they walked for at least three minutes. Patient-agnostic regression models were trained on temporally embedded EMG time series of different combinations of up to five leg muscles bilaterally . Gait events could be detected with high temporal precision (median displacement of <50 ms), low numbers of missed events (<2%), and next to no false-positive event detections (<0.1%). Swing and stance phases could thus be determined with high fidelity (median F1-score of ~0.9). Interestingly, the best performance was obtained using as few as two EMG probes placed on the left and right vastus lateralis. Our results demonstrate the practical utility of the proposed EMG-based system for gait event prediction, which allows the simultaneous acquisition of an electromyographic signal to be performed. This gait analysis approach has the potential to make additional measurement devices such as IMUs and force plates less essential, thereby reducing financial and preparation overheads and discomfort factors in gait studies. Gait and balance disturbances are common and important clinical manifestations of Parkinson’s disease (PD), leading to mobility impairment and falls . CurrentDespite detailed testing, specific factors that are critical to predicting locomotor deterioration in PD remain elusive ,7,8,9. BThe precise assessment of gait dynamics should account for its context dependency. New study setups employing fully immersive virtual reality (VR) or augmented reality allow gait assessment  to be conducted in environments that deliver patient-specific triggers of gait impairment . These An open challenge is the continuous monitoring of gait parameters in laboratory as well as real-world environments. Technically, parameters such as the timings of heel strike and toe-off events, which define swing and stance phases and provide valuable information about cadence patterns, etc., can be assessed with optoelectronic systems and force plates. Both systems, however, are expensive, require qualified personnel, and do not offer monitoring in ecological settings. Video-based analyses of gait have also been proposed , althougHowever, some practical limitations should be considered when applying additional sensors on severely ill patients, especially when performing recordings after suspension of medications. For example, in patients with PD, the overnight suspension of dopaminergic drugs is fundamental to evoke and study PD-related symptoms but greatly reduces the time window available for experimental recordings. Limiting the preparation period by limiting the number of sensors may help considerably in this regard. In addition, an excessive number of sensors may alter the natural behavior of subjects, undermining the advantages of working in ecological environments. Another crucial aspect is the cost of multiple sets of sensors. Considering that probes comprising both IMUs and EMG are generally more expensive than standalone solutions, the need for IMUs and EMG in the fine-grained evaluation of gait may be a limiting factor for many laboratories and applications in clinical routine. The use of multiple devices may also not be practical in clinical routine, as synchronization or different recording software may be needed.Considering this, the development of novel technologies that can extract multiple types of signals from the same set of sensors is highly desirable. While the same kinematics can be produced by different muscular patterns, lower-limb kinematics can be inferred using analysis of EMG . The idePrevious approaches aimed to predict discrete gait events , and little attention has been paid to reconstructing the time course of the relevant kinematic variables. Brantley and colleagues were able to predict knee and ankle kinematics, but with varying accuracy across trials and the subjects included . In addiIn the present study, we explore the possibility of identifying fundamental gait events from surface EMG in parkinsonian patients using a machine learning approach. Compared with previous studies, we did not frame the problem as one of detection  or classification . Instead, we used an innovative regression approach to approximate continuous angular velocity profiles as measured by IMUs. We consider this approach strictly more powerful and flexible than previous approaches, as access to the predicted IMU time series allows us not only to extract predetermined types of gait events but also biomechanical quantities such as joint angular velocity and further parameters on which our model has not been trained. Our study is further set apart from published work in that we focused on a clinical cohort rather than healthy participants. To our knowledge, our study is the first to demonstrate the feasibility of accurate gait parameter estimation using EMG in such a population. Remarkably, our approach accounts for the substantial across-patient variability observed in gait patterns of clinical populations, allowing it to be applied without any patient-specific calibration.We recruited six patients with idiopathic PD according to the UK Brain Bank criteria who did not suffer from any other disease, including cognitive decline , vestibular disorders, and orthopedic impairments, that could interfere with walking. An additional inclusion criterion for this preliminary study was the ability of the patient to walk continuously and without assistance for at least three minutes. Disease severity was evaluated using MDS-Unified Parkinson’s Disease Rating Scale motor part (UPDRS-III), and the stage of the disease was evaluated using the Hoehn and Yahr (H&Y) scale. Using items 3.15–3.17 of UPDRS-III (hands and feet), a sum rest tremor sub-score was created for the right and left sides separately. Similarly, a sum bradykinesia-rigidity score (items 3.3–3.8) was obtained for each side.Demographic and clinical features are listed in Patients were investigated in a practical medication-off state, i.e., on the morning after overnight withdrawal (>12 h) of all dopaminergic drugs (meds-off). Kinematic data were recorded using two IMUs , at a sampling rate of 128 Hz, placed bilaterally on the outer anklebones. Each sensor was placed with its vertical axis aligned with the tibial anatomic axis. Surface leg muscle activity as measured by 10 EMG probes  was recorded bilaterally on tibialis anterior (Ta), soleus (S), gastrocnemius medialis (Gm), gastrocnemius lateralis (Gl), and vastus lateralis (Vl) at a sampling rate of 1000 Hz. Two transistor–transistor logic signals (TTL) were provided at the beginning and end of each trial to both EMG and IMU devices to make data synchronization possible. Patients started walking barefoot after a verbal signal at their self-selected speed along a large ellipsoidal path of about 60 m in length . We recoWe focused on the muscles of the lower leg, which are highly involved during the gait cycle. Ta and S are distal monoarticular muscles with distinct and synergistic contributions to human gait . Accordi5 − 1 = 31 sets containing between one and five pairs of distinct muscles. Note that all considered models included either none or both the left and right EMG signals for each studied muscle. Thus, all models comprised an even number of muscles between two and ten.Models based on different muscle combinations were compared to the model including all five pairs of muscles. We were interested in identifying minimal subsets of EMG probes that would make accurate IMU reconstruction possible. Thus, we further exhaustively tested all possible 2Swing peak velocity (SWP), heel contact (HC), and toe-off (TO) events were extracted from the angular velocity profiles measured with respect to the medio-lateral axis by the IMUs . Gait events  were extracted from the predicted IMU time series as described in Ninety-three minutes of gait activity and 5253 full gait cycles were analyzed across the six patients. The median gait cycle duration ranged from 1045 to 1140 ms, corresponding to cadences between 51 and 59 cycles per minute see . The gaip < 0.05 after Bonferroni correction).Event detection errors were rare and did not occur in most trials. Across all trials, events were missed in 1.4%  and 1.3%  of cases. Numbers were nearly identical for all three event types, as HC and TO events were always determined relative to the two enclosing SWP events see . False eWe have demonstrated the feasibility of accurately determining gait events such as HC and TO, defining the swing and stance phases of the gait cycle, in PD patients using a single pair of EMG probes placed bilaterally on the Vl muscle. Our proposed method may have substantial practical benefits in experimental setups in which EMG derivations are indispensable and where additional equipment for kinematic analysis  is either unavailable or would introduce undesired complexity, especially in severely ill patients. Furthermore, robust acquisition of EMG signals is necessary in experimental and commercial applications to achieve control of myoelectric interfaces for neuroprosthetics , includiRather than framing the prediction problem as one of binary classification , our appContrary to our prediction, the EMG profiles of the S and Ta muscles were insufficient to reliably identify major gait cycle events in parkinsonian patients. We based this hypothesis on the distinctive and synergistic activity of these two monoarticular  muscles during human locomotion. Indeed, normal EMG activity of the plantar flexors has been reported to mainly occur during the stance phase. In this phase, the triceps surae restrains the tibial rotation controlling for disequilibrium torque, which is responsible for propelling the body ,47. The The prediction model did not improve when replacing the S muscle with the Gm or Gl or by adding this muscle to the S-Ta pair (data not shown). This was unexpected because while the S muscle may provide less forward propulsion with physiological aging, the gastrocnemius muscle has been shown to maintain its contribution to initiating swinging limb movement ,53, thusIn our study, EMG recordings of the Vl provided the most accurate prediction of IMU times series and gait events. The action pattern of this muscle during the gait cycle paralleled the activation of the Ta but was more selectively confined to the HC. This muscle controls the knee flexion that occurs after HC and ensures knee extension during terminal swing to prepare for ground contact ,55.In principle, there are an infinite number of different combinations of muscle activation that can be applied to maintain a particular posture or produce a given movement . HoweverOur study is somewhat limited by the fact that IMU data are not considered the “gold standard” for defining ground-truth gait parameters. Force plates would have allowed the precise detection of HC and TO events, and possibly of the individual muscle contribution to ground reaction forces, to be performed ,60. HoweThe proposed approach was not tested on healthy control data. However, we expect our model to effectively predict gait events in healthy controls, as patient data are more heterogeneous and generally more challenging in terms of gait alterations, and inter-subject and inter-trial variability, as well as artifact contamination. We were also only able to recruit a few patients for this study. However, it should be considered that walking for over three minutes in the meds-off state is very challenging for subjects with PD and greatly limited patient recruitment. Another limitation was the relatively homogeneous walking speed across all patients. We preferred not to alter the patients’ natural speed, because we wanted to test our model in an ecological setup. In addition, the meds-off state limited the recording window and the possibility of exploring more than one gait condition. It is thus presently unclear how well our prediction model would perform for different speeds when applied out of the box. However, it is straightforward to adapt the model to different speeds by either temporally adjusting the embedding delays . Our approach may have practical benefits for gait studies in which the application of multiple sensing devices is considered impractical, troublesome, or too expensive. Notably, our model was validated using a leave-one-patient-out strategy. We observed very good performance in held-out patients, demonstrating that the model is able to accommodate the across-patient variability of the studied clinical population. Future work could adapt our approach to varying walking speeds and may further extend it to the prediction of other kinematic data obtained using EMG.We have demonstrated the accurate and robust detection of gait events in six parkinsonian patients using just two EMG probes placed on the left and right vastus lateralis. Unlike solutions presented in previous work, our approach proceeds in two steps: First, IMU time courses are predicted using EMG activity within a surrounding temporal window using multiple linear regressions. Second, gait parameters such as heel strike and toe-off events are extracted from the predicted time series. This approach led to accurate results and has the advantage over previous ones that discrete gait events and continuous time series of relevant kinematic quantities can be predicted. It is further expected that it could be generalized to the extraction of further gait parameters not considered here without any model retraining. Our model and an example dataset, as well as Matlab code for data preprocessing, model training, model evaluation, and plotting, have been made publicly available under


Quantifying emotional aspects of animal behavior  is a major focus of neuroscience research. Because manual scoring of emotion-related behaviors is time-consuming and subjective, classical methods rely on easily quantified measures such as lever pressing or time spent in different zones of an apparatus . Recent advancements have made it easier to extract pose information from videos, and multiple approaches for extracting nuanced information about behavioral states from pose estimation data have been proposed. These include supervised, unsupervised, and self-supervised approaches, employing a variety of different model types. Representations of behavioral states derived from these methods can be correlated with recordings of neural activity to increase the scope of connections that can be drawn between the brain and behavior. In this mini review, we will discuss how deep learning techniques can be used in behavioral experiments and how different model architectures and training paradigms influence the type of representation that can be obtained. Animal behavioral studies have been used to investigate neurobiological aspects of human emotions. In this mini review, we define “emotion” as patterns of behavioral, hormonal, and autonomic responses  elicit approach and reward-seeking behaviors  while aversive cues  elicit avoidance and fear behaviors  reached human-level accuracy visual recognition Serre, . Since tThe output of pose estimation workflows (such as DLC) is frame-by-frame information about the location of the labeled body parts (if detected) within the video frame. For research focused primarily on tracking kinematics or an animal’s location , this may be sufficient for the desired analyses. For example, DLC has been used in EPM, EZM, and open field tests to measure time spent in different areas, distance traveled, location, and velocity  or density-based clustering methods (B-SOiD) do not even require that the user specify the number of behavioral clusters. This property is a double-edged sword, however, as hierarchical and density clustering algorithms do not attempt to ensure that all points included within a cluster are similar to each other, only that there is no clear dividing line. Thus, they are suited to detecting behaviors that occur in sustained bouts with relatively brief transitions between behaviors, but may group very different behaviors together when transitions between behaviors occur very frequently.Self-supervised methods  combine Deep behavior mapping (DBM; Zhang et al., Data with occluded views of experimental subjects present an additional challenge for pose estimation-based methods (Mathis and Mathis, in vivo imaging of neuronal activity in freely behaving animals. Using techniques that record from freely moving animals allows for studying an animal’s neuronal activity in more complex behavioral paradigms (Laing et al., Advances in imaging technology such as 1-photon miniscope calcium imaging allow for in vivo 2-photon calcium imaging in mice (Dolensek et al., Many correlations between neural activity and animal behavior are based on measurements such as timestamps. Integrating neural imaging and machine/deep learning techniques in rodents allows for more nuanced relationships to be identified. Studies have utilized machine/deep learning techniques for head-fixed In vivo electrophysiology can also be combined with video recording in freely moving animals. For example, the firing rate of NAc and dorsolateral striatum neurons changed with operant vertical head movement as drug intake increased (Coffey et al., The advent of machine learning and deep learning enables the simultaneous specialization and standardization of behavior classification processes across neuroscience research. Previous studies have utilized various deep learning techniques to look at behaviors that correlate with pain states (Bohic et al., Deep learning techniques can help parse connections between behavior and the brain in complicated situations. For example, various cell types, circuits, systems, and projections in the brain have roles in multiple emotional behaviors, evidenced by chronic pain and depression comorbidity (Taylor et al., JK wrote the first draft of the manuscript. AD developed DBM. All authors contributed to the article and approved the submitted version.This research was supported by NIH NIDA IRP. JK is supported by the NIDA IRP Scientific Director’s Fellowship for Diversity in Research. NB and YZ is supported by the Post-doctoral Fellowship from the Center on Compulsive Behaviors, National Institutes of Health. YL is supported by National Institutes of Health grants 3P20GM121310-05S1, R61NS115161, and 4UH3NS115608-02.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


The annual cancer risk depends on the degree of dysplasia,such as 0.33% if there is no dysplasia, 0.54% with LGD, and 7% with HGDProton-pump inhibitor (PPI) therapy is recommended to control reflux symptoms inpatients with NDBE. The American College of Gastroenterology (ACG)In BE IND, either the epithelial abnormalities are insufficient for a diagnosisof dysplasia, or the nature of the epithelial abnormalities is uncertain due toinflammation or technical difficulties with specimen processing. The risk of HGDor cancer within 1 year of the diagnosis of IND varies between 1.9% and 15%Most patients with an initial diagnosis of LGD (73%) are downstaged to NDBE or toIND after review by expert gastrointestinal pathologistsAs with LGD, the diagnosis of HGD needs to be confirmed by a second pathologistwith gastrointestinal expertise. In the past, the treatment was esophagectomy,but due to demonstrated lower morbidity and equivalent efficacy ofradiofrequency ablation, the current treatment of choice is endoscopic mucosalresection (EMR) of raised lesions, followed by radiofrequency ablation of theentire affected segment,Because dysplasia in BE carries an increased risk of progression to cancer, thecurrent standard of care in these patients is EMR of visible lesions, followed byablation of the flat mucosa, with the aim of achieving complete eradication ofIMPPIs are today the main component of medical treatment for GERD, because they are themost effective medications to decrease gastric acid production, leading to healingof esophagitis and relief of symptoms,,Successful elimination of reflux symptoms does not guarantee control of acid reflux.Often, BE patients do not experience heartburn due to the reduced sensitivity of thecolumnar mucosa to the acidic and bilious refluxateClostridium difficile infectionAs many as 40% of patients with heartburn have either an incomplete or complete lackof response to once-daily PPIsAntireflux surgery (ARS) aims to repair the antireflux barrier, which is defective inpatients with BEOther indications for ARS in patients with BE include younger patients who do notwish to commit themselves to lifelong PPI therapy. It is particularly important thatthese patients are counseled that the surgery is being considered to control theirGERD and decrease their reliance on PPIs, not to eliminate the requirement forlong-term endoscopic Barrett’s follow-upThe optimum timing of ARS in patients with Barrett’s has not been standardized. Somereports have suggested that performing ARS at the time of ablative therapy candecrease the number and improve the efficiency of endoscopic Barrett’s ablation,,Controversies are still present regarding the progression of Barrett’s following ARS.One study based on a Swedish population showed that ARS failed to prevent thedevelopment of esophageal cancer when compared with the correspondingpopulationIncreasingly, patients with LGD are undergoing successful endoscopic ablationAntireflux surgery can be considered in patients following successful ablation ofHGD. However, many surgeons would advocate an extended period of stable postablationendoscopic follow-up before proceeding with ARS. Some practitioners recommendrepeating objective pH testing following ARS in patients with NDBE as well as thosewith LGD or HGD postablationThe current recommended BE treatment is maximal acid suppression with PPIs andhistamine-2 blockers, while in some cases, fundoplication is required to controlreflux refractory to medical therapy. In our opinion, laparoscopic ARS can be anappropriate alternative and even a preferred option from medical therapy for highlyselected candidates. Minimal morbidity and near zero mortality in high volumecenters along with multiple studies demonstrating long-term success of antirefluxoperations support this approach. However, post-treatment surveillance continues tobe a required component of long-term treatment because the risk of progression todysplasia still exists. Nevertheless, a prospective randomized controlled trial isneeded to confirm the therapeutic effect and long-term outcomes of laparoscopic ARSversus medical therapy plus or minus endoscopic ablation in patients with BE. Inaddition, future comparisons of maximal medical therapy versus other surgicaltechniques (LINX device) and endoscopic antireflux procedures such as TIF  and Stretta are also warranted.