Hypoxia is an essential hallmark of several serious diseases such as cardiovascular and metabolic disorders and cancer. A decline in the tissue oxygen level induces hypoxic responses in cells which strive to adapt to the changed conditions. A failure to adapt to prolonged or severe hypoxia can trigger cell death. While some cell types, such as neurons, are highly vulnerable to hypoxia, cancer cells take advantage of a hypoxic environment to undergo tumour growth, angiogenesis and metastasis. Hypoxia‐induced processes trigger complex intercellular communication and there are now indications that extracellular vesicles (EVs) play a fundamental role in these processes. Recent developments in EV isolation and characterization methodology have increased the awareness of the importance of EV purity in functional and cargo studies. Cell death, a hallmark of severe hypoxia, is a known source of intracellular contaminants in isolated EVs. In this review, methodological aspects of studies investigating hypoxia‐induced EVs are critically evaluated. Key concerns and gaps in the current knowledge are highlighted and future directions for studies are set. To accelerate and advance research, an in‐depth analysis of the functions and cargo of hypoxic EVs, compared to normoxic EVs, is provided with the focus on the altered microRNA contents of the EVs. Cells can secrete chemical signals which act as local mediators (paracrine model), hormones are released into the circulation and neurotransmitters transmit messages between neurons. Recently, extracellular vesicles (EVs) have emerged as an important additional mechanism of cellular communication and route of interchange of bioactive molecules  is used throughout the review to refer to exosomes, microvesicles and other types of EVs  signalling pathway . Knocking out of nSMase2 reduces the release of EVs from neuron‐like cells , density gradients, commercial kits, immunoaffinity‐based protocols, and size‐exclusion chromatography (SEC)  or commercial precipitation (24%) based methods Figure , the for4in vitro, introducing another crucial variable to the study design. The most widely used method in the reports reviewed here has been incubation with variable oxygen levels  from endothelial colony forming cells after 72 h conditioning at 1% OIn summary, most studies report increased release of EVs in response to hypoxia, highlighting the need of stable controls for normalization. Currently, it remains unclear if the effects observed here are caused by an increased number of released EVs in hypoxia, an altered content within the individual EVs, or both.6Functional outcomes of hypo‐EVs were evaluated based on the recipient cell types, i.e. the cell type being exposed to the EVs isolated from hypoxic donor cells. This approach was used because in similar recipient cell types similar outcomes are more frequently being examined and make possible a reasonable comparison between different reports.6.1Hypo‐EVs from distinct cell types such as different cancer cells, MSCs and cardiac cells showed highly consistent functional features when endothelial cells were exposed to these EVs Table . Nine ou6.2We found a total of six papers in which cardiomyocytes had been exposed to hypo‐EVs isolated from either cardiac cell types, endothelial cells or MSCs Table . In thesEguchi et al. (2019) tested different mechanisms of EV uptake into cardiomyocytes and showed that hypoxia induced the uptake of EVs, mainly due to increased clathrin‐dependent endocytosis. This hints at a potential approach to manipulate the composition or environment of EVs to guide therapeutic agents via these structures to only those cells needing the treatment. Indeed, methods to conjugate the EV membrane with specific tags to escort EVs to certain target tissues have been already demonstrated in the case of heart and brain  and it is characterized by certain changes in the gene expression such as increased expression levels of vimentin but decrease in E‐cadherin. All studies evaluating the effect of hypo‐EVs on recipient cell stemness have reported enhanced EMT Table . The evi6.4There are an increasing number of studies reporting that hypo‐EVs are anti‐inflammatory when immune cells are exposed to these structures as compared to normo‐EVs Table . InteresRecently, much effort has been devoted to study more complex signalling pathways of hypo‐EVs between immune cells and other cell types. Guo et al. 2018) demonstrated induced expansion and polarization of myeloid‐derived suppressor cells when they were exposed to hypo‐EVs isolated from glioblastoma cells. These hypo‐EV exposed suppressor cells in turn reduced T cell proliferation, leading to reduced cytotoxicity. Another study from Li et al. (2019) supports this observation that the final anti‐inflammatory effect of hypo‐EVs evident on the T cells could be indirectly mediated by suppressor cells via non‐EV dependent mechanisms. In addition, cancer cells have been shown to promote their own growth and metastasis via hypo‐EV polarized macrophages .Our analysis revealed seven hypo‐EV enriched miRNAs, listed in Figure In vivo, these hypo‐EV associated miRNAs can originate from several distal hypoxic cell types and contribute to the heterogeneous pool of functional EVs. Thus, the analysis of possible outcomes of several hypo‐EV altered miRNAs together, even if individual miRNAs were to originate from only a certain type of cell, can prove useful when extrapolating the findings to a more physiological, dynamic environment. Our analysis demonstrates for the first time this collection of miRNAs as common regulators of pathways crucial to cellular adaptation to hypoxia, a phenomenon that should be utilized in a wider context in the future.Using the validated targets of these hypo‐EV enriched miRNAs, we retrieved 17 biological pathways that were enriched in humans, mice and rats Figure . The bioConsequently, we demonstrate the potential additive effect of increased amounts of several miRNAs in the hypo‐EVs on crucial cellular processes, such as angiogenesis, migration, and immunosuppression, by acting at different levels of the signalling pathways towards common functional outcomes. Furthermore, depending on the cellular context, these outcomes may be detrimental (cancers) or reparative (MI and stroke).Next, we briefly focus on the literature of each of these pinpointed miRNA to evaluate the relevance of the predicted enriched pathways.7.2The expression of miR‐210 is directly induced by HIF‐1α that binds to an HRE located in the miR‐210 promoter  analysed the role of hypo‐EVs in the context of cognitive decline and detected the presence of some of these previously mentioned microRNA. Hypo‐EVs from bone marrow‐derived MSCs were found to contain increased levels of several miRNAs, including miR‐210, miR‐21, miR‐23a, miR‐17 and miR‐146a. The infusion of these hypo‐EVs ameliorated spatial learning and memory impairments in a mouse model of Alzheimer's disease, by alleviating Aβ accumulation, increasing synaptic protein expression, inhibiting the activation of astrocytes and microglia, as well as by decreasing the levels of pro‐inflammatory compounds while increasing those with anti‐inflammatory effects.8Data on other molecules than miRNAs in hypo‐EVs are more limited. However, an increase in the enzymatic activity in hypo‐EVs compared to normo‐EVs has been reported (Jong et al., 9Regardless of the major differences in study designs and technical aspects, the literature on the effects of hypoxia on EV release appears to be highly consistent regarding the functions of hypoxic EVs in the recipient cells. These functions involve increased invasiveness and migration, proliferation, angiogenesis and immunomodulation. Some opposing effects have also been reported which may be due to different cell types, type of stimuli and other experimental parameters. Due to the relatively small number of closely identical studies, definite conclusions cannot be made, but the current information serves as a promising platform from which to design future studies to replicate the findings with more state‐of‐art methods to achieve a better characterization of the EVs. Importantly, we would encourage studies also outside the MSC, cancer or cardiovascular fields as current knowledge in these contexts is very limited.A growing number of studies have highlighted the potential contribution of EVs to human disorders involving pathogenic hypoxia. The analysis of the hypo‐EV cargo is essential if one wishes to elucidate the functions of these EVs in the context of complex disorders and to better understand the multifaceted communication among different cell types in response to hypoxia. MiRNAs can directly affect the behaviour of cells by targeting specific transcripts involved in a variety of cellular processes. Interestingly, our bioinformatic analysis of several hypo‐EV associated miRNAs across species revealed how they may regulate many important pathways involved in cellular adaptation to hypoxia, strongly supported by the existing studies on individual miRNAs.Since hypo‐EVs can affect target cells in different ways as compared to normo‐EVs, their inclusion in the studies of novel therapeutic options should be taken into account, for example, in the context of cardiac disorders, where there is convincing evidence pointing to their cardioprotective function. On the other hand, modifications of EV membrane could be exploited to target drug loaded EVs to specific target tissues or cells which could reduce the risk of side effects or increase the potency of drugs. In addition, the characteristics of EVs suggest that they may be a tempting target for biomarker development as EVs originating from a certain cell type could be identified and quantified, i.e. providing biomarkers with improved disease specificity.Future studies will benefit greatly from the expected technological developments in reference materials, measurement of single EVs and improved purity of EVs, as well as in the detection of different EV subpopulations. By taking advantage of these advances, hypo‐EV studies should focus on defining in more detail the effect of cell death on the release of EVs and on the co‐purifying of non‐EV contaminants under hypoxic conditions. Furthermore, the clarification of the many miRNAs in the EVs’ cargos, as well as the effects of the EV‐derived miRNAs in the recipient cells need further evaluation. The use of databases such as EV‐TRACK (Van Deun et al., The authors report no conflict of interest.Kuopio, Finland.Supplementary informationClick here for additional data file.


WHO declared the global outbreak of SARS‐CoV‐2 a pandemic on March 11, 2020, and “call(ed) on all countries to exchange country experiences and practices in a transparent and timely way” . To date, many medical societies have announced their intention to collect and analyze data from COVID‐19 patients and some large‐scale prospective data collections are already running, such as the LEOSS registry (Lean European Open Survey on SARS‐CoV‐2 Infected Patients) or the CAPACITYCOVID registry (registry of patients with COVID‐19 including cardiovascular risk and complications). The necessity to mobilize and harmonize basic and applied research worldwide is of utmost importance .The  This commentary describes the first nation‐wide registry of COVID‐19 autopsies. Autopsies are an essential tool for the understanding of infectious diseases, and the initiative presented here will help harmonizing and accelerating research on COVID‐19.


Over the past two decades, team‐based care models have advanced the delivery of primary care.… teamwork requires each member to have role‐specific competence, a shared structure to work within, and “coordinative and adaptive capabilities”Over the last 45 years, the need for interprofessional team‐based training for health professions has been well documented.Much has been learned about primary care teamwork from the patient‐centred medical home (PCMH), a team‐based one‐care model implemented extensively in the USA. This approach honours the tenets of primary care – comprehensive, coordinated, accessible and continuous – as well as emphasising the importance of the personal relationship between a patient and the care team members.A straightforward framework to learn, assess and improve primary care teamwork would be a valuable tool for medical professionals and trainees to learn team‐related competencies. In this article, we describe a conceptual model that integrates principles of primary care team performance with research on what constitutes effective teamwork. We suggest strategies for how learners, faculty members and other stakeholders can use the model to enhance primary care team practice, training and assessment.In 2010, the Veterans Administration  adopted the PCMH care model in 900 primary care clinics. We developed the Conceptual Model of Primary Care Team Performance (CM of PCTP) at a VA demonstration site for PCMH implementation. Our workgroup includes two VA clinician‐educators with team‐based practice expertise in patient‐centred communication and social scientists with experience in teamwork, quality improvement, coaching, and innovation development and assessment.We selected the evidence‐based ‘Integrative Framework of Team Effectiveness’ as our starting point because of its validity and flexibility to include primary care practice characteristics.As shown in Figure Team performance in the central oval represents the essential processes that occur as a team works to coordinate patient care Figure . It inco○Meeting practices – routine meetings are scheduled during non‐clinical time and the team uses processes that promote efficient and meaningful care coordination and improvement Table . Althoug○and understanding those of team members.Task work is the delivery of high‐quality patient‐centred care to a specific patient population Table . Care is○Teamwork describes the communication processes required for collaborative work Table . How teaInputs (left side of the model) are the structural features of a team‐based care model determined by practice leadership. Patient demographics define the types, roles and staffing needed on the team, as well as expected outputs of team performance. Work demands are influenced by a team's panel size, patient complexity, and level of clinical staffing.Outputs (right side of the model) are measurable outcomes that drive team performance and serve as benchmarks to monitor a team's care and improvement efforts. Clinical teams must be aware of and work towards relevant goals and outcomes. Patient experience, population health and cost are widely accepted as important aims of health system performance.A relationship‐centred culture (bottom of the model) describes the optimal work environment to promote team performance. Important contributors to culture are leadership style, performance mandates, work demands, staffing, autonomy and acceptable patterns of communication.A straightforward framework to learn, assess and improve primary care teamworkwould be a valuable tool for medical professionals … to learn team‐related competenciesmeeting practices – team members coordinate their work during effective meetings; task work – team members value patient‐centred care, perform their roles and strive for continuous improvement; and teamwork – team members communicate with honesty and respect, and value relationships with team members. Both new and existing clinical teams can use this simple three‐part framework of team performance to stimulate the quick recall of what constitutes team performance, and as a starting point to assess and improve their own team performance.We propose that the CM of PCTP can be easily recalled and applied in three categories: The Conceptual Model of Primary Care Team Performance combines key constructs ofteamwork with characteristics of a primary care practiceTeaching strategies for teams seeking to initiate or improve team‐based education are described in Tables The CM of PCTP will also assist other primary care stakeholders to learn about primary care team performance. Team members and coaches guiding teams to improve their performance can refer to the model to target areas of success and challenge. The model will provide educators with a framework to plan team training curricula and interventions. Evaluators can use the model as a roadmap to develop assessments of care outcomes, team performance, training interventions, and team member well‐being. Clinical leaders may find this framework helpful to analyse the effects of changes in the structure of a primary care practice  on team performance and care outcomes. Finally, all stakeholders can promote team performance and a relationship‐centred culture by clearly defining roles, communicating honestly and respectfully, and by planning for effective meetings.In summary, the CM of PCTP acknowledges the complexities of primary care team performance, yet suggests a simplified approach to its components, implementation, evaluation and potential as an improvement tool. We intend it to be used in three ways: (1) as a tool for primary care team members and trainees to readily remember, learn and practice key characteristics of team performance; (2) as a framework for the development of coaching and training interventions for primary care teams; and (3) as a guiding structure to assess and improve a primary care team's performance, care outcomes and team member well‐being.… teams must have uninterrupted time and space to build relationships, reflect on howthey work together, and coordinate care


Unbiased morphological profiling of bioactivity, for example, in the cell painting assay (CPA), enables the identification of a small molecule's mode of action based on its similarity to the bioactivity of reference compounds, irrespective of the biological target or chemical similarity. This is particularly important for small molecules with nonprotein targets as these are rather difficult to identify with widely employed target‐identification methods. We employed morphological profiling using the CPA to identify compounds that are biosimilar to the iron chelator deferoxamine. Structurally different compounds with different annotated cellular targets provoked a shared physiological response, thereby defining a cluster based on their morphological fingerprints. This cluster is based on a shared mode of action and not on a shared target, that is, cell‐cycle modulation in the S or G2 phase. Hierarchical clustering of morphological fingerprints revealed subclusters that are based on the mechanism of action and could be used to predict target‐related bioactivity. Route planner: We explored a morphology‐based cluster around the iron chelator deferoxamine by using the cell painting assay and identified annotated compounds with different targets but a similar mode of action. This cluster can be used to predict modes of action for unexplored small molecules, thus highlighting the value of morphological profiling to explore the bioactivity of compound collections. Phenotypic screening for perturbed or restored cellular phenotypes is a powerful approach to identifying small‐molecule bioactivity. However, it is limited to the phenotype of interest in a given assay, and wider coverage of bioactivity space requires the exposure of small molecules to multiple phenotypic assays. This limitation can be overcome by morphological profiling, for example, in the cell painting assay (CPA).Here we describe that morphological profiling using the cell painting assay enables the identification of a common MoA for compounds with similar morphological fingerprints, but which have different annotated protein targets or which might not target proteins at all. CPA revealed high morphological fingerprint similarity (biosimilarity) across structurally very different nonprotein targeting iron chelators  and compounds that induce cell‐cycle arrest in the S or G2 phase. This biosimilarity is due to impairment of cell‐cycle progression as a common denominator of iron chelators and S/G2 phase regulators that do not chelate iron as previously reported.Structurally different compounds with different annotated cellular targets can cause shared physiological responses. These compounds define a cluster based on their mode of action. Comparison of morphological fingerprints to reference compounds allows target/MoA prediction for uncharacterized compounds with unknown activity. We employed morphological profiling to identify compounds that do not target proteins as this activity is rather difficult to identify with commonly applied target/MoA identification methods. Therefore, we focused on the iron chelator deferoxamine and identification of a cluster of similar reference compounds with the desired MoA that would afterwards allow to identify novel compounds with shared MoA based on fingerprint similarity.Streptomyces pilosus that has high affinity to FeIII and is clinically used in the treatment of iron‐overload diseases.[Deferoxamine Figure A is a hediseases.12 To exinduction  as a measure of bioactivity.biosimilarity score  determined at different concentrations, which revealed a concentration‐dependent increase in induction, that is, from 9 % at 2 μM to 36 % at 10 μM, at high biosimilarity , libraries of kinase inhibitors and the Prestwick Chemical Library. Using the morphological fingerprint of DFO as a query profile we identified several metal chelating agents among the reference compounds with the highest biosimilarity (>80 %). The metal ion chelators ciclopiroxThis finding demonstrates that iron chelators form a CPA cluster that, in principle, can be successfully employed for the detection of iron chelators and most likely for the identification of novel iron complexing agents.in silico approach to predict bioactivity for small molecules, whereby the bioactivity information extraction and (re)assignment rest on known ligand‐target interactions and chemical and structural similarity of ligands and target proteins.[iron antagonist) for DFO. This calls for extension of the drug‐target space that is considered by cheminformatic approaches to nonprotein targets to facilitate MoA prediction early on in the target or MoA identification process for nonprotein targeting compounds.Cheminformatic methods offer an orthogonal, proteins.4d, 4eThe fingerprints of more than 20 additional references displayed high similarity to DFO  chelation, trifluridine, roscovitine and topotecan did not influence complex formation , while compound 1 and 2 did not affect Ferrozine‐FeII complex formation . In addition, compounds 1 and 2 were analyzed for modulation of topoisomerase 1 and 2 and selected CDK/cyclin complexes. 30 μM compound 1 and 2 neither inhibited the activity of both topoisomerases nor the activity of several CDK/cyclin complexes in biochemical assays (Tables S11–13). However, the compounds may inhibit these enzymes in cells or target different proteins that are involved in cell‐cycle regulation.To gain further insight into the possible mechanism of action, we explored the DNA‐binding activity of compounds 12 do not chelate FeII but cause the accumulation of cells in S‐phase, which is in line with the observed activity in this cluster. Importantly, most compounds in this cluster did not impact cell growth after 22 h at a concentration, at which they increased the number of cells in S‐phase. Therefore, CPA enables the identification of small molecules that impair the cell cycle without marked decrease in cell growth at that stage and by employing staining for cellular components or compartments rather than using cell‐cycle‐specific markers.Macrocycle We performed hierarchical clustering in order to investigate the ability of the cell painting assay to distinguish between different mechanism of action within the Fe/DNA synthesis cluster.1–3 were assigned to the second subcluster of iron chelators, topoisomerase and CDK inhibitors. However, compound 3 is clearly separated from compounds 1 and 2 and clusters, as expected based on the FeII chelating activity . This demonstrates the advantages of a multiplexed phenotypic profiling like the cell painting assay that not only enables the identification of compounds with a common mode of action but also offers insight into target‐related bioactivity, that is, mechanism of action.The hierarchical clustering divided the cluster into two major groups Figure . One groy Figure B, togethy Figure . This fiIron chelators and compounds that impair the cell cycle in S/G2‐phase by targeting DNA or S/G2 regulating proteins display high biosimilarity in the cell painting assay and define a cluster that can be employed to predict a MoA for novel iron‐targeting agents and cell‐cycle modulators in general based on their morphological fingerprints. We identified three uncharacterized compounds that are biosimilar to this cluster and proved that they induce S‐phase arrest. In addition, we demonstrate that hierarchical clustering allows to distinguish between the different mechanisms of action. Our findings underscore the predictive value of unbiased morphological profiling for mode‐of‐action identification to shorten and render the MoA or target identification and validation process more efficient.The authors declare no conflict of interest.As a service to our authors and readers, this journal provides supporting information supplied by the authors. Such materials are peer reviewed and may be re‐organized for online delivery, but are not copy‐edited or typeset. Technical support issues arising from supporting information (other than missing files) should be addressed to the authors.SupplementaryClick here for additional data file.SupplementaryClick here for additional data file.SupplementaryClick here for additional data file.SupplementaryClick here for additional data file.SupplementaryClick here for additional data file.SupplementaryClick here for additional data file.SupplementaryClick here for additional data file.


Salmonella genomes where functional prophages are abundant, and where genetic interactions between host and prophages are of particular importance for human health considerations.Thanks to the exponentially increasing number of publicly available bacterial genome sequences, one can now estimate the important contribution of integrated viral sequences to the diversity of bacterial genomes. Indeed, temperate bacteriophages are able to stably integrate the genome of their host through site‐specific recombination and transmit vertically to the host siblings. Lysogenic conversion has been long acknowledged to provide additional functions to the host, and particularly to bacterial pathogen genomes where prophages contribute important virulence factors. This review aims particularly at highlighting the current knowledge and questions about lysogeny in  Salmonella enterica genomes, as most other bacterial species, host multiple prophages whose genes can represent up to 5% of the genome content. In this review, we aim at putting into light the multiple genetic interactions that can be weaved between the host and its prophages and between prophages themselves within the host. Defective: a defective prophage has lost part of its genome and can no longer produce viral particles, but may still be able to excise from the host chromosome.Functional: a prophage is considered functional if it can resume a lytic cycle and re‐infect naive cells.Lysogeny: upon lysogenic infection by a temperate phage its genome is stably maintained as a prophage (most of the time integrated into the chromosome) in the host bacterium and vertically replicates with it. No progeny is produced until a lytic cycle resumes.Lysogenic conversion: describes the phenotypic changes bacteria undergo upon infection by a temperate phage going through lysogeny.Morons (“more on”): genes regulated independently from the rest of the prophage and conferring a fitness advantage under specific environmental conditions.Polylysogeny: the hosting of multiple prophages in a single host genome.Temperate bacteriophage: a phage that can multiply either lytically or through lysogeny.Prophage/provirus: inherited form of a temperate bacteriophage; dormant form of the viral genome which replicates with the bacterial host genome.Pseudolysogeny: a phage–host cell interaction in which the phage genome does not integrate into the host’s and forms an episomal form that can be still transmitted vertically. Pseudolysogeny applies to virulent and temperate phages and does not lead to the usual outcome lysis or lysogeny.Pseudogenization: a gene becomes a pseudogene by accumulating mutations that hinder its correct transcription and/or translation.Virulent or strictly lytic bacteriophage: a phage that multiplies exclusively through a lytic cycle.et al., et al., Bacteriophages are recognized as the most abundant biological entities on earth, participating to numerous biological cycles and constantly reshaping bacterial communities  it is a widespread enterobacteria displaying a broad host range, frequently carried by wild and domestic birds as well as rodents, and an animal and human pathogen, (ii) host‐prophages interactions have been studied for many years and still lead to amazing pieces of work encompassing many topics, such as host‐phage interactions, virulence, ecology and genome evolution.This review aims at highlighting the contribution of prophage genes to the host physiology. To date, a lot of emphasis has been put on the identification and characterization of phage‐encoded virulence factors in various pathogenic bacteria  that was a key model for transduction discovery  , the cleavage of the repressor is not the major outcome of the induction system. Indeed, it was shown for several S. enterica prophages that upon SOS response induction and LexA self‐cleavage, an antirepressor protein (Ant), homologous to the Tum one in phage 186, is being made that inhibits the lytic repressor through protein‐protein interaction  in the absence of induction. Host‐controlled expression of exogenic, and prophage genes in particular, has been described in several bacterial models  .A commonly admitted view is that prophage genes are under control either by the powerful phage repressor or by host factors that tend to limit the negative effects of horizontal gene acquisition. In the first case, thanks to the seminal work of Jacob and Monod “The operon model” Lewis, , the lyset al., et al., et al., et al., Being extremely abundant on earth while presenting a gene content very different from that currently available in the genomic databases, bacteriophage genomes are believed to contribute extensively to the genetic “dark matter”  or endotoxin consisting of a lipid and a polysaccharide composed of O‐antigen, as receptor as opposed to E. coli bacteriophages that often target outer membrane proteins . LPS is a potent activator of immune cells and therefore these temporarily changing surface modifications can shade the bacteria vis‐à‐vis the eukaryotic immune system  and codes for an integral membrane transacylase conferring the specific serotype 05 . This modification restricts super‐infection by ε15 itself and in turn allows infection by phage ε34  and increased cell invasion  that are stored at cold and then reheated exposing bacteria to a chain of stresses, which may in turn induce prophages genes and finally, increase bacterial virulence.Shah et alS. enterica virulence is the secretion of multiple effectors involved in virulence. The effectors are secreted via two different Type Three Secretion Systems (T3SS) encoded by the pathogenicity islands 1 and 2 (SPI1 and 2). SPI1 is activated when S. enterica is in contact with eukaryotic host cells, whereas SPI2 is expressed during the phagocytosis step  , while sseK3 has been previously identified on prophage ST64B  are generally first silenced before being integrated into the host regulatory network. The silencing of genes from foreign origin can, for example, occur S. enterica SL1344  . Indeed, under lysogenic conditions expression of the P22 encoded et al., et al., et al., et al., et al., S. enterica LT2 is similar to the average GC content of the genome .Another factor involved in the silencing of genes acquired by HGT, in addition to core genes, is the DNA binding protein H‐NS . Among the regulators known to control the expression of genes located on the SPI are the InvF transcriptional regulator belonging to the AraC/XylS family for SPI1, itself regulated by the master regulator HilD, and the SsrAB two‐component system for SPI2. Although both regulators were initially thought to be only dedicated to the regulation of genes located on SPI1 and 2, they also regulate expression of prophage‐encoded effectors. Indeed, InvF regulates effectors from prophage origin secreted by SPI1, whereas SsrAB controls effectors that are SPI2‐dependent.In addition to the negative regulation that we have just mentioned, some bacterial regulators also positively regulate genes from prophage origin. Surprisingly, if one looks at the different transcriptomic studies performed in S. enterica SL1344 and secreted by the SPI1 system. Consequently, sopE expression is regulated by InvF, in association with the chaperon protein SicA (Darwin and Miller, sopE regulation (Tucker and Galán, For example, SopE is a virulence factor encoded on the SopEΦ prophage in S. enterica SL1344. Interestingly it has been shown that gogB expression is independent of Gifsy1 prophage factors since it can be transferred by itself in the enteropathogenic E. coli strain E2348/69, expressed from its own promoter and secreted via the T3SS of its new host. This shows that gogB can be integrated easily into the host regulatory network (Coombes et al., gogB shows differences with the GC content of Gifsy1 suggesting that this gene has been recently acquired by the prophage. Moreover, gogB can be found outside of Gifsy1 and is not always prophage‐encoded, which further supports its transcriptional independence from the Gifsy1 prophage (Porwollik et al., Other prophage‐encoded effectors are secreted by SPI2, and as a consequence, their expression depends on the SsrAB two‐component system. Among them, GogB is encoded by the first gene of the Gifsy1 prophage in sseI is a gene located on the Gifsy2 prophage, encoding another T3SS effector. sseI expression is strongly activated by the direct binding of the phosphorylated form of SsrB in its promoter region (Worley et al., et al., sseI expression is also regulated by the phosphorylated form of OmpR but it is not clear whether this regulation is direct or dependent on SsrB (Feng et al., sseI together with the higher expression of pgtE, encoding an outer membrane protein, allows S. enterica ST313 adaptation to cause systemic disease (Carden et al., et al., pgtE transcription is due to a single SNP in its promoter region. Further studies are required to understand how these changes in gene expression modify S. enterica ST313 behavior (Hammarlöf et al., S. enterica fitness within the host (Tomljenovic‐Berube et al., SsrB also regulates genes in the phage remnant SPI12. Among the regulated genes STM2239 encodes a Q antiterminator protein that interacts with the RNA polymerase to facilitate the transcription of late promoters. The absence of STM2239 affects the fitness of the bacteria within the host. STM2239 allows the transcription of phage‐encoded genes but also of bacterial genes involved in metabolic pathways including ribose modification and transport, acetyl coenzyme A synthesis and recycling as well as galactose metabolism. None of these regulations have been characterized further, but it has been speculated that some of them may be important for dgo operon is involved in the uptake and metabolism of D‐galactonate, an important carbon source during intracellular proliferation. In S. enterica LT2 strain, expression of the dgo operon is derepressed in the presence of Pid, a protein encoded on a moron locus in P22 (Cenens et al., Except for virulence, examples of bacterial processes under prophage control are scarce (Fig. pckA gene encoding a phosphoenolpyruvate carboxykinase required for gluconeogenesis. In E. coli, this gene is under the control of the CI repressor of the λ phage (Chen et al., pckA regulatory region is conserved among Enterobacteriaceae and contains sequences homologs to several phage operators, one of them being the binding site for the C2 repressor of P22. This shared regulation between several prophages could be part of an adaptive strategy to increase lysogens fitness by lowering their growth rate under glucose‐limited conditions (Chen et al., Phage‐dependent regulation can be conserved among closely related bacteria. It is the case for the S. enterica DT104 (Balbontín et al., ryeB and corresponds to an internal site in ryeA. Therefore, ΦW104 lysogenization modifies the 5′ portion of ryeA, leading to a decreased transcription of ryeA and an increased transcription of ryeB. This transcriptional regulation has probable physiological consequences on the bacterial host, by modifying the expression of RyeA and RyeB mRNA targets.Prophages often integrate into tRNA encoding genes. One counter example is given by phage ΦW104 that integrates the host chromosome at a locus encoding the RyeA and RyeB sRNA located on the opposite DNA strand in isrK (Hershko‐Shalev et al., isrK, orf45, anrP and isrJ coding sequences. However, there is no translation observed from this mRNA unless IsrK sRNA is present. Indeed, IrsK sRNA binds next to the orf45 ribosome binding site and facilitates the binding of the 30S ribosomal subunit to this site, leading to the translation of downstream sequences and the production of the AnrP protein. AnrP is an anti‐repressor activating the transcription of phage‐encoded genes. Among them, it activates the expression of the antQ gene coding for the AntQ anti‐terminator that interacts and forms a stable complex with RNA polymerase. This leads to an aberrant transcriptional elongation, DNA damage and ultimately cell death (Hershko‐Shalev et al., Finally, another example of host‐gene regulation involves a gene located on the Gifsy1 prophage, S. enterica SL1344 depends on the lysis genes of the ST64B prophage (Nedialkova et al., All the above examples concern regulation of gene expression. However, phages can also influence bacterial physiology by other means. For example, the release of colicin 1b in Salmonella genomes is the diversity of the prophage content as well as the diverse relationships these prophages engage with the host strains. As stated before, we think that contributions to virulence have been more studied and highlighted up to now than regulatory and metabolic interactions between the Salmonella host and its prophages. This bias seems largely due to the prevalent role of Salmonella species in public health threats. In addition, contrary to some previous statements, phage genomes rarely contain antibiotic resistance genes, and if antibioresistance transfer can be sometimes attributed to phages, it is more likely due to generalized transduction rather than lysogeny (Enault et al., What is striking whenever considering and comparing different et al., Apart from actual contributions to virulence, we foresee that many more interactions do exist, and, it seems that microbiologists have only just began to explore the expense of prophage–host interactions and their short and long‐term effects on bacterial metabolism and evolution. More interactions certainly remain to be discovered such as the up‐to‐now neglected carrier state and its implications on the host metabolism (Cenens Salmonella species. The literature becomes quite abundant regarding Salmonella phage quests, but little is known about the consequences of poly‐lysogeny, which can rapidly modify the bacterial surface, and therefore, the resistance to surinfecting phages on the efficacy of phage cocktails, particularly for those developed to treat swine and poultry or in the case of adjuvant in food processing (Wernicki et al., In a context of multidrug resistance spreading and recurrent warnings from WHO and other health authorities, the use of bacteriophages as therapeutic agents is coming back to the scene, not only as potent antimicrobials by themselves but also as synergistic or complementary agents in combination with antibiotics (Kamal and Dennis,


Soils and their microbiomes are now recognized as key components of plant health, but how to steer those microbiomes to obtain their beneficial functions is still unknown. Here, we assess whether plant–soil feedbacks can be applied in a crop system to shape soil microbiomes that suppress herbivorous insects in above‐ground tissues.We used four grass and four forb species to condition living soil. Then we inoculated those soil microbiomes into sterilized soil and grew chrysanthemum as a focal plant. We evaluated the soil microbiome in the inocula and after chrysanthemum growth, as well as plant and herbivore parameters.Frankliniella occidentalis, but not against the mite Tetranychus urticae, when compared with sterilized soil. Additionally, plant species shaped distinct microbiomes that had different effects on thrips, chlorogenic acid concentrations in leaves and plant growth.We show that inocula and inoculated soil in which a focal plant had grown harbor remarkably different microbiomes, with the focal plant exerting a strong negative effect on fungi, especially arbuscular mycorrhizal fungi. Soil inoculation consistently induced resistance against the thrips This study provides a proof‐of‐concept that the plant–soil feedback concept can be applied to steer soil microbiomes with the goal of inducing resistance above ground against herbivorous insects. Chrysanthemum cuttings were provided by the breeding company Deliflor . Chrysanthemum is one of the major cut flower crops worldwide and is commonly cultivated in soil in glasshouses, which is sterilized regularly  to control soil pathogens  with a starting colony provided by the company Hazera Seeds . A culture of the spider mite Tetranychus urticae (line Sandpoort‐2) was established . More details are provided in the Supporting Information Methods The focal plant in our study is et al., Holcus lanatus (HL), Lolium perenne (LP), Alopecurus pratensis (AP), Festuca ovina (FO)) and forbs (Achillea millefolium (AM), Tripleurospermum maritimum (TM), Rumex acetosella (RA), Galium mollugo (GM)).To create different soil inocula, we selected eight wild plant species that are typical of natural grasslands in the Netherlands based on previous work where they exhibited positive plant–soil feedback effects on chrysanthemum growth . Both experiments had two phases (see further details in Methods n = 16 soil/plant replicates). Before inoculation, a soil sample was taken from the inocula (first six soil replicates) for microbiome analysis. Plants were grown in a glasshouse under controlled conditions  and after 3 wk plants were transferred to a semi‐open tunnel glasshouse. This tunnel has a plastic cover and netting on the sides , and no control of temperature, light or humidity. Here, plants were arranged in a randomized complete block design (one soil replicate per block). The plants of the different soil treatments were randomly distributed inside each block. Plants had no physical barriers between them, and were grown for seven more weeks in the tunnel glasshouse. At the end of the experiment we quantified the density of thrips present on each plant and at each plant height, after which above‐ and below‐ground biomass was clipped and dried at 60°C and DW was determined. During the course of the experiment, we did not observe spatial patterns (i.e. differences in interior and outside plants) in thrips colonization or damage patterns (no data available). Bulk soil was sampled from a subset of six replicate pots per treatment and a subsample from each pot was stored in 2 ml Eppendorf tubes at −80°C to assess the microbiomes in the inoculated soils after chrysanthemum had been grown in the soils.The aim of this experiment was to compare the soil microbiomes of the inocula with those after chrysanthemum had grown in the inoculated soils, as well as the effect of soil inoculation on the growth of plants and resistance to naturally occurring herbivores. As the focus of this study is on soils, and the changes therein by plant legacies, rhizosphere soil was not analyzed, owing to the strong differences with surrounding soil and because it was the surrounding soil that was inoculated and not rhizosphere soil. Field soil was collected and each soil replicate (the different pots during the conditioning phase) was kept separate in this experiment . At the end of the experiment, the bulk soil of eight pots per soil type was collected and a subsample from each pot was stored in 2 ml Eppendorf tubes at −80°C for later microbiome analysis.et al., Petri dish plates were prepared with 2 ml of plant agar (1.5%) on one side of the dish. After collecting the leaves, one leaf was placed in each Petri dish, with the petiole inserted into the agar to avoid leaf desiccation, a method shown to be effective to assess resistance to thrips (Maharijaya –1 leaf DW).The third fully opened leaf was collected from each plant, freeze‐dried and finely ground. Ten milligrams of ground leaf material was then used in a methanol extraction . The fungal ITS2 region was amplified using the primers ITS4 and ITS9 . Both library preparation and sequencing were done at McGill University and Genome Quebec, Canada.Soil DNA was extracted from the soil samples using the PowerSoilipits pipeline  and the output of this file was compared (curated) against an in‐house database on fungal functions  and OTUs occurring in less than three samples with relative abundances of < 0.01% were removed. Furthermore, samples with < 1000 or > 50 000 reads were removed from the dataset. Effects of plant species identity and plant functional group on the structure of the bacterial and fungal community were then examined using PERMANOVA based on a Bray–Curtis dissimilarity matrix in R (package vegan) separately for both experiments. Separations among treatments were visualized using nonmetric multidimensional scaling of a Bray–Curtis dissimilarity matrix. The Chao1 Richness index was calculated for each sample and the effects of inoculation, soil inocula and plant functional group on richness were evaluated using linear models in R . The relative abundances were calculated as the number of reads of an OTU, class or phylum divided by the total number of reads in that sample. Pearson correlations were calculated between plant and herbivore parameters, and relative abundances of bacterial phyla and fungal classes using Bonferroni correction for false discovery rate (package corrplot in R).Sequencing data were normalized using the total sum scaling (TSS)  were included as fixed factors. Whether each soil inoculum differed from sterilized soil was tested with post hoc Dunnett tests using the ‘glht’ function of the multcomp package in R. In the third step, we assessed whether there were differences between inocula originating from grasses and forbs. For this last step we excluded the sterilized soil treatment from the analysis. We used a mixed model with functional group as a fixed factor and soil inocula as a random factor. For Expt 2, in two Petri dishes, six thrips were discovered while only five were introduced (one in a replicate from GM and one in a replicate from LP). These data were excluded from analysis. For the mite bioassay, those plates where no eggs were oviposited were removed because of probable misidentification of females or mortality of females. This resulted in four to 10 replicates per treatment for the mite bioassay.The design of the experiment with different inocula and one set of control plants (uninoculated plants) prohibits all questions being answered with one statistical model. Therefore, plant and herbivore data were analyzed in three steps (with different models). In the first step, we assessed the effect of inoculation nlme package. Data on the proportion of thrips reaching the prepupal stage were analyzed using a generalized linear model with binomial distribution using the functions ‘glm’ or ‘glmer’ (when random factors) of the lme4 package. Data on counts of mite eggs or thrips were overdispersed and therefore analyzed with a generalized linear model with quasi‐Poisson distributions using the functions ‘glm’ or ‘glmmadmb’ (when random factors) from the package glmmadmb. Data from Expt 1 were all analyzed with mixed models where block was set as random factor . All analyses were performed in R v.3.3.3  function of the http://www.ebi.ac.uk/ena/data/view/PRJEB35722). Plant, herbivore and soil chemistry data that support the findings of this study are openly available in Datavers at https://hdl.handle.net/10411/OIQCZH.Paired‐end DNA sequencing reads for this project have been deposited in the European Nucleotide Archive under accession number PRJEB35722  and in the soils after chrysanthemum had grown in them  or in the soils . Analyses of microbial richness in inocula and chrysanthemum soils, as well as a description of community composition and richness from the second experiment are shown in Notes Our first aim was to assess how the bacterial and fungal communities in the soil change compared with the inocula, once chrysanthemum grew in that soil. For this we sequenced soils from both inocula and chrysanthemum soil from Expt 1. We detected that the community composition for both bacteria and fungi was most affected by whether they were from inocula or chrysanthemum soil, with stronger differences for bacteria than for fungi  of the conditioning plants. The percentage of thrips reaching the pupal stage was significantly lower on plants growing in soil conditioned by the grasses HL and FO compared with sterilized soil Fig. b. Final r = 0.85, P < 0.001). Most bacterial phyla  were positively correlated with the chlorogenic acid content of the plant while only three bacterial phyla were negatively correlated with the chlorogenic acid content . Recent studies have shown that the genetic background of the test plant can determine the root‐associated microbiome and whether conspecific plant–soil feedback effects on plant growth are negative or neutral   should be directed to the Fig. S1 Richness of bacteria and fungal phylotypes in the inocula (upper panels) and in the soil after chrysanthemum growth (bottom panels).Fig. S2 Correlations between the richness (Chao1 index) of bacteria (left) and fungi (right) in the inocula and in the soils after chrysanthemum growth in Expt 1.Fig. S3 Richness (Chao1) of fungal phylotypes of the subphylum Glomeromycotina.Fig. S4 Effects of soil inoculation on chrysanthemum biomass of plants from Expt 1.Fig. S5 Effects of soil inoculation on thrips survival from Expt 2.Fig. S6 Effects of soil inoculation on Phenolics in leaves from uninfested plants from Expt 2.Fig. S7 The relative abundance of bacterial (a) and fungal (b) groups showing the strongest correlation with thrips performance in Expt 2.Fig. S8 Correlations between parameters of plant performance and resistance and relative abundance of fungal and bacterial taxa in Expt 2.Fig. S9 Correlations at the genus level between parameters of plant performance and resistance and relative abundance of fungal and bacterial taxa in Expt 2.Fig. S10 Bacterial and fungal richness (top panels) and community composition (bottom panels) in the soil after chrysanthemum growth from Expt 2.Fig. S11 The relative abundance of bacterial phyla that were affected by the soil conditioning and inoculation in Expt 2.Fig. S12 The relative abundance of fungal phyla that were affected by the soil conditioning and inoculation in Expt 2.Methods S1 Herbivore rearing.Methods S2 Soil preparation and plant growth.Methods S3 Chemical analysis of phenolics.Notes S1 Soil inoculation effects on microbial richness in inocula and soils.Notes S2 Soil inoculation effects on plant growth and plant defenses.Notes S3 Microbial richness and community composition of the chrysanthemum soils from Expt 2.Click here for additional data file.Table S1 Data used to make Figs 5 and S9 which show correlations between parameters of plant performance and resistance and relative abundance of fungal and bacterial taxa.Click here for additional data file.Table S2 Average relative abundances of bacteria and fungi at the lowest taxonomic level that could be identified in chrysanthemum soil and inocula.Click here for additional data file.Table S3 Effect of different factors on the relative abundances of bacterial and fungal taxonomic groups.Click here for additional data file.


To identify and summarize the challenges of conducting qualitative research exploring end‐of‐life communication between healthcare providers and bereaved family carers in nursing homes.A descriptive qualitative study based on in‐the‐field‐notes and research diaries collected during a primary study involving 32 bereaved family carers and 14 nurses across 13 Italian nursing homes in 2018–2019.Two trained female nurses conducted semi‐structured, in‐depth, open‐ended interviews and recorded “in action” (i.e. reflections reported as in‐the‐field‐notes) and “on action” (i.e. retrospective reflections within the team reported immediately in the research diaries) narratives, with the aim of identifying challenges encountered during the research process. A content analysis process was performed to analyse the narratives collected.We identified three major categories of challenges: (a) obtaining approval from the ethical committee; (b) approaching nursing homes and family carers; and (c) dealing with participant‐related impairments . Family carers were identified by the NH director with the support of HCP(s) and then contacted according to NH preferences: (1) by phone call after preliminary contact by the NH director who provided an explanation of the study aims and requested permission for contact; (2) by phone call and interview directly scheduled by the NH director; or (3) with a personalized letter of condolences with a brief presentation of the study aims and the phone number of researchers to be contacted if interested in the study.The nurse most often involved in the care during the resident's last week of life was also interviewed to explore his/her perceptions regarding end‐of‐life communication with family carers.3.3Two trained female nurses who were not affiliated with the NHs' participants or staff or to the family carers were responsible for data collection. Specifically, they were (a) a doctoral candidate in nursing with postgraduate specialization in bioethics and experienced in qualitative research and (b) a nurse with experience in NH end‐of‐life care, respectively. Semi‐structured, in‐depth, open‐ended interviews with follow‐up questions at the family carer's preferred location were carried out. Nurses mainly involved in the care of the residents were interviewed at their workplace before, at the end or during their shift when possible.Data were collected through the in‐the‐field‐notes and a research diary. In in‐the‐field‐notes, defined as written narratives of observational data emerged by fieldwork including descriptive and interpretive data based on the observational experience of the researcher Jackson, , researc(a) the “in action” or the “here‐and‐now” reflections were collected at the beginning of the research process, such as the ethical committee approval and the request for participant consent; and during the research process, with regard to: (i) the interview plan  Pawluch, ; (ii) thBrief, keyword‐based notes were taken during the interview, while maintaining eye contact with participants. The detailed field notes were dictated immediately after the interview ended, thus ensuring the researcher's memory was fresh, the prevention of recall bias and allowing for a free‐flow of ideas.(b) the “on action” reflections were the in‐depth, retrospective reflections collected after each of four formal meetings organized over the study process in research diaries Berger, . These mSpecifically:Narratives, which emerged whatever challenges in (1) designing or (2) conducting qualitative research exploring end‐of‐life communication in NH, were all included. Practical non‐methodological challenges (i.e. reaching NH or family carers at long distances) were excluded.3.4The Ethics Committee of the University of Turin  approved the primary study (Reference 457626/10.12.2018). In the primary study, all participants gave their written informed consent to participate in the study and to be audio‐recorded after being informed about the study purpose and the process of data collection. Participants were free to participate and could stop the interview at any time and for any reason, without the need to give explanations. Transcriptions were anonymized with regard to both the names of the participants and the NHs. Moreover, the two researchers, who collected the data of the present study, gave their informed consent for the data collection process.3.5units of meaning) were highlighted; (3) condensing: two researchers  independently reduced each meaningful unit to a descriptive label (code(s)); and (4) categorization: all researchers compared the codes and grouped them into sub‐categories according to their similarities; the sub‐categories were finally abstracted in categories. The analytical process is reported in Table Direct content analysis  expert in qualitative research assessed compliance with guidelines for trustworthiness Lincoln, . To ensu4We identified three major categories of challenges while designing and implementing the primary qualitative study on NH bereaved family carers: 1) obtaining the ethical committee's approval; (2) approaching NHs and family carers; and (3) dealing with participant‐related impairments  how NHs would be sampled; (b) when participant recruitment would stop; (c) how audio‐recorded interviews would be managed; and (d) the interview guide to be used.“Participation to the study is not mandatory and NHs will adhere on a voluntary basis.”“Statistical sample estimations for generalization is inappropriate in qualitative research. Data saturation (i.e. redundant signs inform researchers that data collection may cease) and information power (i.e. the number of participants depends on the amount of information the sample holds) better fit the aim of qualitative research.”“Audio recordings will be stored in the data folder of an academic computer that will be accessible only to the research team.”“It is not possible to provide the definitive interview guide, that can be modified as new insight unfolds with interviews. The concept of “open protocol” is an essential part of qualitative research.”We thus amended the protocol by better specifying, for each point arose above‐mentioned, the following revisions:4.24.2.1A NH director said: ‘Family carers are constantly informed about their relative's care, I do not feel the further need to go through these discussions about death and dying’.Several of the NHs initially approached seemed suspicious of the research project and were not interested in being part of the study. NHs might perceive themselves as being judged for their work on symptom control, treatment strategies and communication with families:Participation was further discouraged by the recently modified European regulation on data protection rules (Regulation (EU) 2016/679, 4.2.2A researcher recorded that some family carers said ‘We witnessed uncontrolled suffering during the last days of life’, or ‘We felt somehow guilty for not having done as much as possible’.In our study, family carers were approached after their relative's death. To guarantee sensitive data protection, to be as non‐intrusive as possible and to limit possible refusals for study participation, the NH director made first contact with the potential participants to inform them about the study, to verify their willingness to participate and to request permission for contact from the researchers. We therefore tailored the contact with families according to NH preferences, introducing a great diversity in the approaches used. Twenty‐two family carers joined the study after the researcher phone call; six interviews were directly scheduled by the NH director and only four family carers answered the personalized letters of condolence. Twenty family carers declined to participate as they were not interested in the project aims or remembering their relative's death was too challenging:Thus, we mainly approached participants who had mainly positive end‐of‐life experiences, while those with particularly distressing and burdensome end‐of‐life experiences who may have benefited from sharing their experience with researchers to receive emotional support, were less approached.4.2.3The death was recent, only two months ago, but the daughter had difficulties in remembering several details of end‐of‐life communication, she had reset to forget the suffering of her mother's last days.We set our time frame as between 45–90 days after the resident's death, to avoid approaching families during the acute bereavement stage. Due to difficulties in accessing participants in this timeframe, we also included carers whose relative had died up to nine months earlier. A stricter time frame may not prevent recall bias: some carers whose relative had died less than 2 months previously had forgotten several details about end‐of‐life communication and others who had lost their beloved long time ago had intact memories:4.2.4The notes emerged during the study process about the decision on how many participants to involve led to embrace an innovative and emerging approach in the primary study named “information power” :The interviewer had to rephrase the question about satisfaction with end‐of‐life care three times as the daughter didn't understand.(a) emotional distress: some participants had very challenging end‐of‐life experiences and felt the need to share many details not always consistent with our research aims. For some of them, the interview was a relief valve allowing them to talk about their experiences in the NH, for others it was a way to remember their dead relatives:The daughter thanked me at the end of the interview since she had the opportunity to talk about her mother after many months.(b) The niece asked to be interviewed together with another cousin who had been highly involved in the aunt's care at the end‐of‐life since those memories were too agonizing.It was sometimes necessary to allow them to go off‐topic or to be interviewed together with another bereaved family member to help them face such an emotionally challenging dialogue. Three interviews were therefore conducted with more than one person at once (two interviews with child and daughter‐in‐law and one interview with two nieces):The location of the interview was decided by the family carer to allow maximum comfort. The interview with the nurse most involved in the resident's care during their last week of life was scheduled before that with the family carer, so as to gain a clinical view of the case and avoid upsetting errors with family carers;physical issues: some participants were of advanced age and were unable to drive or being transported; others chose to be interviewed in the NH facility so as to meet the NH personnel and/or residents with whom they had established a friendly relationship during the NH stay:A 70‐years old son happily adhered to the project but asked to be interviewed at home since he hadn't any car neither could be transported to the NH by anyone.(c) Two participants were interviewed over the telephone since they lived abroad and this had not been provided for in the study protocol;misunderstandings based on language and cultural differences: in talking with the family carers, it was important to share the same dialect and language, giving a sense of closeness; and also, some interviewed nurses were non‐Italian workers with poor language proficiency:A nurse perceived to be subordinate to the physician and tried to avoid answering critical questions by saying ‘Ask the physician, he will answer better than me’.(d) 5Our study was designed to identify challenges in undertaking qualitative research in end‐of‐life NH family carers communication. We identified three major challenges, one in the first stage during project approval and the others during the data collection process. Discussing these challenges is an ethical imperative so as to develop the researchers' ethical sensitivity and improve the rigour of qualitative methods to develop evidence capable of improving clinical practice. If these challenges are not addressed and remain unresolved, research findings may not be fully useful , appropriate (i.e. it does not fit a situation) or meaningful  suggesting the need for tailored strategies. By allowing participants to read the topic guide, they were supported in dividing the entire experience into specific parts regarding relevant experienced situations concerning communication with the HCPs and involvement in decision‐making; moreover, expected questions reduced emotional distress. To avoid complicated language  and emotional distress , while others were expected (i.e. involving NHs and family carers) and suggest some important issues for feasibility and acceptability. Sharing the experience and pitfalls of undertaking qualitative research should be an ethical imperative, given that it is only through an in‐depth reflection of practical work that it is possible to identify difficulties and offer insights on overcoming problems, thus enhancing the methodological rigour of qualitative studies.Ethical committees should be made aware of the importance and relevance of investigating lived experiences and perceptions as factors that may affect patient satisfaction and the course of illness. Changing the culture of individuals and institutions requires time, and however, more often asking ethical committees to arrange specific documentation for qualitative research protocols and providing NHs with opportunities to be involved in research projects can promote this change.End‐of‐life research in NH with elder family carers requires researchers to develop specific skills to promote participation. Together with flexibility in arranging the location and timing of data collection, researchers should have empathetic and technical interview skills, including ethical responses to distress, strategies to avoid emotional involvement and possibly a common linguistic and cultural background, especially when culturally based topics are investigated, such as end‐of‐life communication. In Southern Europe qualitative research, courses are usually offered only at a high degree of education , whereas Northern Europe and North America show a different sensitivity, with most nursing Bachelor's programmes offering courses in qualitative methodologies. The greater competence of researchers from Northern Europe and North America in performing qualitative research is confirmed by the fact that most published qualitative research is being conducted in these countries. Southern Europe should develop a greater sensitivity towards this methodology by offering more educational opportunities to qualitative researchers to ensure rigorous qualitative studies on potentially emotionally challenging topics.We have striven to be transparent in discussing the challenges we encountered while conducting qualitative research in NH about end‐of‐life communication. We hope that sharing the challenges and the strategies adopted to overcome them will be of help to other researchers. This should also be an encouragement to persist in investigating these sensitive issues and amplifying the voice of older individuals admitted to NHs, family carers, nurses and researchers, despite the difficulties that may be encountered.The authors have no conflicts of interest to disclose.SG, PDG and AP contributed to the study concept and design. SG and PDG collected data. All authors analysed the data and interpreted the results. SG and AP drafted the manuscript. All authors critically reviewed and revised the manuscript and approved the final version. All authors take responsibility for the integrity of the data and the accuracy of the data analysis.


Visceral pleural invasion (VPI) in adenocarcinoma of the lung is considered a poor prognostic factor. The purpose of this study was to analyze nucleolin and nucleophosmin expression in pulmonary adenocarcinoma (PA) with VPI and in pleural malignant mesothelioma.The study was conducted on the basis of 19 pathologically‐confirmed cases of adenocarcinoma of the lung and 29 cases of epithelioid malignant mesothelioma. The nucleolin and nucleophosmin expression was assessed immunohistochemically and analyzed with image analysis software.Nucleolin expression was lower while nucleophosmin was higher in pleural invasion of pulmonary adenocarcinoma than in the central part of the tumor. Differences in subpopulations of cells with different expression of proteins studied were also found. Malignant mesothelioma showed lower nucleolin expression than adenocarcinoma of the lung but no differences in nucleophosmin expression were found.The results of our study suggested that lower nucleolin and higher nucleophosmin expression may be related to higher invasiveness of adenocarcinoma of the lung. Differences in nucleolin expression between pulmonary adenocarcinoma and malignant mesothelioma indicate another aspect of biology of these pleura‐invading cancers that requires further study.Differences in nucleolin and nucleophosmin expression in pleura invading pulmonary adenocarcinoma indicate the involvement of these proteins in its locoregional spread while differences in nucleolin expression between pulmonary adenocarcinoma and malignant mesothelioma suggest another aspect of biology of these cancers.This is the first study on nucleolin and nucleophosmin expression in pleural malignant mesothelioma and pleura‐invading pulmonary adenocarcinoma. Our findings may assist in understanding the mechanisms of locoregional spread of adenocarcinoma and differences between these two pleura‐invading cancers. The lower nucleolin expression and higher nucleophosmin expression were related to the pleural  invasion of pulmonary adenocarcinoma. Pleural malignant mesothelioma showed lower nucleolin expression than pleura invading pulmonary adenocarcinoma Lung cancer, especially non‐small cell lung cancer (NSCLC), is one of the most common cancers worldwide and the main cause of cancer death. Among different histologic types of lung cancer adenocarcinoma is the most common and its incidence is increasing. It typically localizes at the periphery of the lung and can spread invading the visceral pleura. Visceral pleural invasion (VPI) is a form of a locoregional spread of NSCLC and is considered a poor prognostic factor. It is defined as tumor cells invading past the elastic layer (PL1), or to the pleural surface (PL2).The nucleolus is a prominent structure in the interphase nucleus composed mainly of ribosomal RNA and more than 400 proteins of which nucleolin and nucleophosmin are the most abundant.et al. found nucleolar size (inconspicuous vs. prominent) to be associated with lymph node and distant metastases of pulmonary adenocarcinoma.et al. found that small nucleoli or absent nucleoli were associated with better survival in epithelioid pleural malignant mesothelioma.Only a few studies have focused on the nucleolus in pulmonary tumors. Xu VPI of pulmonary adenocarcinoma and pleural infiltration of malignant mesothelioma can be considered examples of locoregional spread of cancer. Recently, we studied the nuclear nucleolin and nucleophosmin expression in prostate cancer and its locoregional spread to seminal vesicles. We found a decreased expression of both proteins studied in seminal vesicles infiltrated by prostate cancer compared to cancer cells confined to the prostate gland.We collected 19 samples from patients with primary pulmonary adenocarcinoma (PA) which had invaded the pleura and 37 samples of pleural malignant mesotheliomas that were pathologically examined in the Independent Laboratory of Pathology “Zdunomed” LLC between 01 January 2009 and 07 July 2017. A total of 9 patients with pulmonary adenocarcinomas underwent lobectomy while 10 were treated with segmentectomy. Out of 37 cases of malignant mesothelioma, we selected 29 cases of epithelial subtype for further study. There were eight cases comprised of six samples of biphasic, one case of desmoplastic and one case of sarcomatoid malignant mesothelioma that were considered not representative enough to include in the study group. In the PA samples, we analyzed the protein expression in the central part of the tumor as well as in pleural invasion. Tissue samples for routine pathologic examination were formalin‐fixed and paraffin embedded. All cases were reviewed by an experienced pulmonary pathologist (PW) and representative slides and paraffin‐embedded tissue blocks were selected for immunohistochemical studies.Paraffin blocks were cut into 3 μm sections, deparrafinized and antigens retrieved for immunohistochemical reactions. Slides were incubated with primary antibodies after blockage of endogenous peroxidase. For the detection of nucleolar proteins, two mouse antihuman antibodies were used – anti‐nucleophosmin  and antinucleolin . Immunohistochemical reactions were visualized with EnVision FLEX/HRP . Slides were counterstained with hematoxylin, dehydrated and sealed with coverslips. Several antigen retrieval procedures were tested and antibodies were titrated for optimal visualization of immunohistochemical reactions. Slides were immediately scanned with ScanScope slide scanner  and the results of immunohistochemical reactions were analyzed with Aperio ImageScope software using a nuclear protocol. Regions of interest were drawn manually around nests of cancer cells to avoid other tumor elements such as stroma, necrosis, desmoplasia and inflammatory infiltrations. In pulmonary adenocarcinoma cases, we separately selected regions of interest around cancer cells invading the pleura and around cancer cells in the central part of the tumor. Fig H‐score was calculated with the formula as follows:The study was approved by the Bioethical Commission of the Pomeranian Medical University in Szczecin, Poland .P‐value less than 0.05 indicated statistical significance. All analyses were performed with Statistica for Windows 13.1 .The data distribution was tested with the Shapiro‐Wilk's test and nonparametrical tests were used for determining the differences between groups. A Mean age of patients with pulmonary adenocarcinoma was 61.8 ± 7.9 year, while patients with malignant mesothelioma was 64.7 ± 8.8. Mean adenocarcinoma tumor size was 38.17 mm ± 16.21 mm (mean ± SD). Lymph node (LN) status of adenocarcinoma cases was four cases of LN+, 10 cases of LN(−), and four LN cases of unknown status. The mean number of cells analyzed for nucleolin expression in the central part of the tumor in pulmonary adenocarcinoma was 6176 ± 1045, in pleural infiltration of pulmonary adenocarcinoma was 6186 ± 1470 and in malignant mesothelioma was 7832 ± 2645 (mean ± SD), while for nucleophosmin expression the number of cells analyzed was 6252 ± 1162, 5574 ± 1005 and 8573 ± 1303, respectively.We analyzed the nuclear nucleolin expression in primary pulmonary adenocarcinoma in the central part of the tumor and in the cancer cells which were invading the pleura. We found a lower nucleolin expression indicated by an H‐score, as well as a lower percentage of all nucleolin‐positive cells and a lower percentage of highly (+3)‐positive cells in cancer cells invading the pleura. We also found a higher percentage of nucleolin‐negative cells invading the pleura than in the central part of tumors Table .The analysis of nucleophosmin expression showed higher nucleophosmin expression (H‐score) in cancer cells invading the pleura than in central parts of tumors. We also found differences in percentages of subpopulations of cells showing different levels of nucleophosmin expression. The percentage of cells with high (+3) nucleophosmin expression was higher in cancer cells invading the pleura while percentages of cells with intermediate +2) and low (+1) expression were higher in the central parts of tumors ‐positive cells and as an H‐score. The percentage of low (+1)‐positive and nucleolin‐negative cells was higher in malignant mesothelioma than in pulmonary adenocarcinoma .To our knowledge, this is the first analysis of nucleolin and nucleophosmin expression in pulmonary adenocarcinoma invading the pleura and in malignant mesothelioma. We also studied the differences in nuclear nucleolin and nucleophosmin expression in the central part of the tumor in pulmonary adenocarcinoma and in the cancer cells invading the pleura.et al. analyzed 30 cases of colon cancer as primary tumor, lymph node metastases and distal (liver) metastases. They found a gradual loss of nuclear nucleolin expression from primary tumor through lymph node to distant metastases.et al. also studied nucleolin expression in 225 cases of NSCLC and reported that nuclear nucleolin was lower in higher T stages; however, there were no differences between nucleolin status (low vs. high) and histological type. Longer overall survival and disease‐free survival were correlated with higher nucleolin expression and better overall survival was observed independently for the adenocarcinoma group.We found a lower nucleolin expression, lower percentage of all nucleolin‐positive cells and lower percentage of highly (+3)‐positive cells, as well as a higher percentage of nucleolin‐negative cells in pulmonary adenocarcinoma cancer cells invading the pleura than in the central part of the tumor. Results of our previous study on prostate cancer showed that locoregional spread of prostate cancer  was related to a decrease in nucleolin expression.Lower nucleolin expression was reported to be correlated with shorter overall survival of patients with stage II pancreatic ductal adenocarcinomaet al. on several NSCLC cell lines has shown that overexpression of nucleophosmin stimulated colony formation while depletion of nucleophosmin reduced cell growth. Nucleophosmin acted as an oncoprotein upregulating proliferation, transformation and invasion in A549 cells. Depletion of nucleophosmin increased G1 suggesting that loss of this protein imposes a block before S‐phase entry, while nucleophosmin overexpression increased cell population in S phase. Depletion of nucleophosmin made A549 cells highly sensitive to DNA damage‐induced apoptosis, while nucleophosmin overexpression decreased irradiation‐induced cell death. Thus nucleophosmin is also considered an antiapoptotic protein.et al. the nucleophosmin expression (low vs. high) correlated with histologic grade, tumor stage and recurrence. The higher percentage of cells with high nucleophosmin expression was found in higher histological grades of cancer, higher tumor stages and recurrent tumors.et al. has shown that high nucleophosmin expression correlates with lymph node metastases of colon cancer. The authors concluded that nucleophosmin plays a role in enhanced invasiveness of cancer. Downregulation of nucleophosmin inhibited cancer cell proliferation and impaired migration and invasiveness of colon cancer cell lines while exogenous nucleophosmin expression enhanced cell migration and invasion.et al. has shown that HMBA‐induced differentiation of liver cancer cells resulted in a decrease in nucleophosmin expression on protein and mRNA levels.The analysis of nucleophosmin expression in pulmonary adenocarcinomas with pleural invasion in the current study showed a higher nucleophosmin expression and higher percentage of cells with high (+3) nucleophosmin expression while lower percentages of cells with intermediate (+2) and low (+1) nucleophosmin expression in cancer cells invading pleura than in the central part of tumors. This may indicate that pulmonary adenocarcinoma cells with higher nucleophosmin expression are more prone to locoregional spread. A study by Kim This is the first study dedicated to the analysis of nucleolin and nucleophosmin expression in pleura‐invading adenocarcinoma of the lung and pleural malignant mesothelioma. Cells of malignant mesothelioma showed lower nucleolin expression compared to adenocarcinoma cells invading the pleura. The percentages of low (+1) nucleolin‐positive and nucleolin‐negative cells were higher in malignant mesothelioma. This suggests that lower nucleolin expression is correlated with the aggressiveness of neoplasms; however, these results should be considered with caution and further studies are required to explain the role of nucleolin in these two neoplasms. The results of our previous study on nucleolin in testicular tumors also showed lower nucleolin expression in more aggressive nonseminomatous tumors than in less aggressive seminomas.et al. analyzed nucleophosmin expression in thyroid tumors and found differences in nucleophosmin expression between benign (follicular adenomas) and malignant tumors ; however, expression in benign follicular adenoma was higher than in highly aggressive undifferentiated carcinoma.et al. on some histologic types of renal cell carcinomas and oncocytoma showed that nucleolar nucleophosmin expression was higher in benign oncocytoma and highly aggressive sarcomatoid carcinoma than in clear cell renal cancer or chromophobe cancer. The authors also found a correlation between nucleolar nucleophosmin staining and tumor grade.The nucleophosmin expression did not show any significant differences between pulmonary adenocarcinoma invading the pleura and malignant mesothelioma. The published results of studies on nucleophosmin expression in different tumor types of one anatomic location seem ambiguous. Pianta The authors declare that they have no conflicts of interest.


Understanding and reducing variability of response to transcranial direct current stimulation (tDCS) requires measuring what factors predetermine sensitivity to tDCS and tracking individual response to tDCS. Human trials, animal models, and computational models suggest structural traits and functional states of neural systems are the major sources of this variance. There are 118 published tDCS studies  that used fMRI as a proxy measure of neural activation to answer mechanistic, predictive, and localization questions about how brain activity is modulated by tDCS. FMRI can potentially contribute as: a measure of cognitive state‐level variance in baseline brain activation before tDCS; inform the design of stimulation montages that aim to target functional networks during specific tasks; and act as an outcome measure of functional response to tDCS. In this systematic review, we explore methodological parameter space of tDCS integration with fMRI spanning: (a) fMRI timing relative to tDCS ; (b) study design ; (c) control condition ; (d) number of tDCS sessions; (e) number of follow up scans; (f) stimulation dose and combination with task; (g) functional imaging sequence ; and (h) additional behavioral  or quantitative  measurements. Existing tDCS‐fMRI literature shows little replication across these permutations; few studies used comparable study designs. Here, we use a representative sample study with both task and resting state fMRI before and after tDCS in a crossover design to discuss methodological confounds. We further outline how computational models of current flow should be combined with imaging data to understand sources of variability. Through the representative sample study, we demonstrate how modeling and imaging methodology can be integrated for individualized analysis. Finally, we discuss the importance of conducting tDCS‐fMRI with stimulation equipment certified as safe to use inside the MR scanner, and of correcting for image artifacts caused by tDCS. tDCS‐fMRI can address important questions on the functional mechanisms of tDCS action  and has the potential to support enhancement of behavioral interventions, provided studies are designed rationally. The former is capable of providing high spatial resolution in terms of identifying anatomical regions while the latter allows the study of dynamic physiological changes  techniques to study the effects of tDCS—both in healthy controls and in clinical populations. The first paper that utilized fMRI to investigate how tDCS modulates neuronal activity was published in 2001, where imaging was done sequentially before and after stimulation , individual papers are cited applicable to specific arguments. We start with a literature review to analyze the parameter space for trial design in tDCS‐MR imaging studies and discuss how MR imaging could contribute in tDCS montage selection, response prediction and as an outcome measure in terms of neural activation. Through a representative sample study, we then introduce potential confounds in the experimental design of tDCS‐fMRI studies; where typical practices from fMRI trials and tDCS trials (each in isolation) nonetheless produce unexpected interactions in combined tDCS‐fMRI experiments. We further discuss practical considerations regarding MR‐compatible stimulation devices and imaging artifacts. Lastly, we discuss how computational finite element models could be integrated in MR imaging studies to reduce variability in responsiveness. Here again we use a case analysis to demonstrate how modeling and image processing can influence outcomes.2The authors adopted a systematic search strategy in accordance with the most updated preferred reporting items for systematic reviews and meta‐analyses (PRISMA) , studies on combining tDCS with electrophysiological/neuroimaging methods other than fMRI and ASL , and tDCS or fMRI‐only articles Figure .n = 220) against the above inclusion and exclusion criteria, which resulted in further exclusion of 102 articles. This resulted in 118 articles included in the qualitative synthesis  tDCS stimulation inside the scanner. The sequential approach allows evaluation of the functional brain state before stimulation and/or the lasting “after‐effects” of stimulation, while the concurrent approach allows studying the effects of stimulation applied during ongoing neural activity. The two main differences between “sequential‐inside scanner” and “sequential‐outside scanner” approach are tDCS timing and posture during stimulation . Modeling studies suggest that interpostural difference influences cerebrospinal fluid (CSF) distribution and consequently current flow in brain : Stimulation could be paired with specific tasks to investigate the effect of stimulation on ongoing task dependent activity/connectivity  or be done during resting‐state : The usual approach for blinding a study is to use a sham stimulation (no stimulation during the session but inducing sensations at the beginning and/or end of the session via ramp up/ ramp down of current). However, inconsistency in sham‐controlled studies in tDCS literature resulted in debates on whether different sham protocols are equivalent : The majority of tDCS‐fMRI studies are designed either as randomized controlled trials (89%) which consist of “parallel studies” (31%) where participants are randomly assigned to either an active or sham tDCS group, and “cross‐over studies” (58%), where each participant is assigned to both active and sham sessions in a randomized order  or subjective (clinician rated or self‐report) measurements: Studies can use objective and/or subjective measures before, during or after stimulation. The measure should be selected in harmony with other parameters of the study to enhance the probability of detecting an effect and reducing noise.Prior to MR‐compatible tDCS systems, studies were limited to the sequential‐outside scanner approach, which represents the majority of studies in this review (72% of studies). In longitudinal studies, there can be follow‐up imaging session's hours or days after stimulation or several stimulation sessions with imaging over the course of days or weeks  yet resulted in complex interactions. In a double blind, crossover , sham controlled study on methamphetamine abstinent participants  Figure , functioSE, mean score change in sham session = −1 ± 2.63 SE; p = .03). This means subjects in the tDCS arm had less self‐reported craving after stimulation compared to sham condition  whether tDCS reduced drug craving (self‐reported measure) heightened by drug‐cues presented before tDCS/sham, and was this benefit maintained when second set of drug‐cues were presented, (b) does tDCS compared to sham changed brain activation in regions associated with craving. Notwithstanding this sophisticated design for imaging trials, in this case tDCS produced a significant change in self‐reported craving  in the first and second fMRI scans in each session (time effect); and then at the second level the contrast across conditions (tDCS vs. sham). At the third level, these contrasts are then passed up to test for a group effect across participants using a mixed effects analysis.In addition to nonlinear dependence of tDCS effect on brain state, second exposure of a task that involves emotion/motivation  would make nonlinear interaction with tDCS effect more complex.For a tDCS trial focused only on determining the subjective (self‐report) effects of tDCS on baseline craving, this protocol might not be optimal—even disregarding the cost/burden of fMRI. Alternatives for an imaging study would be (a) a straightforward design for acute changes that uses resting‐state imaging before and/or after stimulation, (b) task‐based fMRI only after tDCS/sham, (c) tDCS/sham over multiple sessions followed by assessment of drug craving, as well as other outcome measures significant for addiction medicine such as abstinence. Each of the above options for integrations of task based or rest fMRI with tDCS will have their own pros and cons. The goal of this case analysis is not to question the validity of any given tDCS‐imaging trial, but to say that although there are validated and thorough imaging trial designs and accepted protocols to test behavioral or neurophysiological effects of tDCS, their integration with fMRI is not trivial. Investigators should be cognizant of all the limitations and possible interactions of the design.3.20 inhomogeneity  optimally target the brain area to modulate– broadly called anatomical targeting; (b) understand which brain regions are active in a specific task/person and whether targeting active regions increases stimulation efficacy—broadly called functional targeting  in this review reside in this category. In this group of studies, MR‐based functional imaging methods  are used to investigate underlying neural correlates of tDCS mechanisms in terms of changes in brain activation not only in targeted areas but across functionally activated task‐relevant brain regions and large‐scale neural networks , from the RF filter box to a nonmagnetic, shielded local network cable that enters the MRI scanner room via the RF waveguide tube, carefully oriented to reduce resonant capacitive coupling, and then finally sent through another RF filter box  before connecting to the tDCS electrodes Figure a.Connect the leads from the tDCS power supply (MRI control room) to an RF filter attached to the penetration panel, and then connect the other end of the penetration panel (MRI scanner room) to the electrode leads Figure b.A main hardware precaution to be aware of when bringing any electronic equipment into the MRI scanner is not allowing the wires to become RF transmitters and introduce noise into the MRI data. To prevent this, currently two similar hardware configurations for MRI‐compatible tDCS are used  to detect signal. However, as the number of coils, and therefore sensitivity increases, the empty space inside the head coil typically decreases. MRI compatible headphones and head padding further restrict available space, making some montages especially challenging. Accommodating particular montages may require advanced experimental consideration. In many cases, the simplest solution is to compromise by using a larger, but less sensitive head coil.5.4In addition to these MRI‐specific hardware modifications, it is important to be aware of modifications to the electrode setup. Saline soaked sponges have disadvantages in imaging settings. They tend to dehydrate over the course of the experiment. One solution, developed for a PET study  while using these electrodes. For example, if voltage compliance of a device is 40 V and it needs to provide 2 mA current for stimulation, the resistance should be less than 20 KΩ  otherwise the device could not provide the target 2 mA for intensity. Comprehensive test of stimulation device is required before starting any experiment regardless of device brand or type.5.6The interaction of tDCS and MRI equipment creates other additional potential complications. For example, despite isolating the tDCS wires to filter out potential RF noise, simply passing current through the wires and electrodes induces stray magnetic fields that will increase magnetic field inhomogeneities and potential artifacts Figure . Because5.7In the concurrent tDCS/fMRI approach, electrical current interacts with the magnetic field generated by the scanner, and therefore can potentially result in warping of the images acquired. This artifact must be considered as it can potentially cause false positive changes. The magnitude and nature of any artifacts is likely to depend on the exact experimental setup. When stimulation is performed inside scanner, effect of stimulation should be considered in image quality  . More to the point, brain regions do not operate in isolation, they rather communicate in micro, meso‐ and large‐scale networks . Statistical tests were corrected for multiple comparisons (Bonferroni correction). FP was the area that received maximum EF compared to other regions  tDCS, complicates analysis, especially because of how different brain regions interact functionally. Therefore, more focal stimulation protocols and/or using functional connectivity analyses that incorporate the interaction between brain regions along with induced electric field in each cortical area could be a better method to approach these questions in tDCS‐MR imaging studies. We further discussed the importance of MR compatible devices and potential source of artifact that should be carefully investigated when imaging concurrently with stimulation.CUNY has patents on brain stimulation with M. Bikson as inventor. M. Bikson has equity in Soterix Medical Inc. and serves on the scientific advisory boards of Boston Scientific and GlaxoSmithKline. The other authors have potential conflict of interest to be disclosed.