In conservation biology there have been varying answers to the question of “How much land to protect?” Simulation models using decision-support software such as Marxan show that the answer is sensitive to target type and amount, and issues of scale. We used a novel model system for landscape ecology to test empirically whether the minimum conservation requirements to represent all species at least once are consistent across replicate landscapes, and if not, whether these minimum conservation requirements are linked to biodiversity patterns. Our model system of replicated microcosms could be scaled to larger systems once patterns and mechanisms are better understood. We found that the minimum representation requirements for lichen species along the microlandscapes of tree trunks were remarkably consistent (4–6 planning units) across 24 balsam fir trees in a single stand, as well as for 21 more widely dispersed fir and yellow birch trees. Variation in minimum number of planning units required correlated positively with gamma diversity. Our results demonstrate that model landscapes are useful to determine whether minimum representation requirements are consistent across different landscapes, as well as what factors  affect variation in these conservation requirements. This system holds promise for further investigation into factors that should be considered when developing conservation designs, thus yielding scientifically-defensible requirements that can be applied more broadly. Research questions related to systematic conservation planning (SCP) have focused on evaluations of how different target types (such as percentage of land area or proportion of populations)3 and amounts 6, effects of scale8, planning unit size9 and data characteristics11 affect conservation planning outcomes. For example, researchers have examined how the scale at which planning takes place affects the number and location of protected areas needed to capture a representative proportion of biodiversity9. A critical question for conservation planners is whether there are guidelines for a fixed percentage of land area that should be set aside for conservation that can ensure that all species are adequately represented2. Such “percentage targets” are appealing for governments and conservation organizations in that they are simple to understand and measure, and provide a tool to evaluate how well agencies are moving towards set goals. However, whether published targets of 12%12 or 50%13 are sufficient to adequately represent and protect biodiversity is not known. The vast number of research papers that have addressed this question (see reviews at refs. 15 for details) have failed to come up with a consistent answer to the question of “how much to protect?”; consensus in the form of multi-authored position papers13 appear to be based more on normative claims than empirical evidence.“How much to protect” has been a pressing question for conservation biologists in both the academic and practitioner literature16. These prima facie differences across studies may explain much of the observed lack of consistency in recommended percentage targets for effective conservation, but these differences also overlook the one limitation that all SCP studies hold in common; the difficulty to rigorously test questions about different aspects of conservation design decisions through experimentation. While SCP exercises are not generally considered “experimental”, SCP is viewed as a tool to make decision making scientific rigorous and transparent17. The strength of SCP as a decision-support tool1 is through the use of models of one type or another . Models are simply expressions of hypotheses given rise, in the case of SCP, from questions generally along the lines of “is a design criterion of X sufficient to conserve biological features Y in area Z?” Within SCP, the design criteria can include issues about the size of individual planning units (candidate protected areas), the type of target  and the target amount .This lack of consistent estimates for the percentage of land necessary to meet particular conservation requirements  may be attributable to differences in the respective ecological systems. Minimum representation requirements will be different in a highly biodiverse tropical rainforest than a less diverse high latitude system. Differences in spatial heterogeneity, both of abiotic and biotic patterns will also have an effect on conservation targetsThe hallmarks of experimentation  are controls, randomization, and replication. Considering conservation planning examples as experiments that can help to develop general guidelines for conservation targets thus faces a challenge. The experimental units for SCP are usually biologically- or politically-bounded regions that are hundreds to thousands of kilometers in extent. These cannot feasibly be replicated. Adjacent bioregions or provinces/states are not suitable replicate experimental units because, due to large spatial scales of landscapes, they are too different to be able to attribute differences in outcomes to the “treatment”  vs. underlying differences in the study areas themselves.in silico analyses. Conservation planning software (the most commonly applied of which is Marxan18) allows researchers to conduct thousands to tens of thousands of “runs” of conservation scenarios to examine how different inputs/constraints affect the conservation output (for an example see ref. 1) and as a form of sensitivity analysis. Other software algorithms  use slightly different approaches; however all in silico analyses are constrained within the same region and on the same data, and hence they are not replicates. Despite that experimentation with replicates at landscape is impossible, it does behoove conservation biologists to consider whether there are alternative ways to increase the empirical rigour of SCP. Increased rigour would help conservation biologists to determine whether conservation targets are situation-specific and not the kind for which generalizations can be made. We propose the use of a novel model system to determine whether consistent “rules” for minimum conservation requirements can be developed.Researchers have tried to get around the problem of replication through Rattus norvegicus, Drosophola melanogaster). Model systems in biomedical research are necessary to address the ethical and logistical challenges of doing medical experiments on humans. Fruit flies and small animals such as mice, rats and zebrafish are easy to maintain in laboratory environments and respond quickly to experimental treatments. This enables manipulative experiments with statistically relevant sample sizes. The genetics and physiology of lab organisms are considered similar enough to that of humans that we can extrapolate findings from these organisms to decisions about how to treat complex diseases in humans, such as cancer20 and Parkinson’s21.Model systems have been widely used in biomedical science  possible  within a single stand, we found that 3–6 planning units per tree were needed to represent all lichen species on each tree at least once Fig. . When ap2 = 0.4898, p = 2.78e-11) of trees with higher lichen diversity requiring more sites to represent all species  scenario identified that five planning units  were required to represent all 37 lichen species in the stand at least once Table . At the Although a protected area strategy, even for small, non-mobile species such as lichens, would not be advisable at the extent of centimetres or metres, this analysis has value in that it allows for tests of consistency in conservation designs within a system of statistically similar micro-landscapes. When we had true experimental replicates, the number of planning units required to represent all species fell consistently between 2–6 for the lichen communities living on the balsam fir and between 1–5 for the lichen communities on yellow birch.What factors influence this observed variation in the number of sites necessary to represent lichen biodiversity is unknown. It would be important to understand drivers of conservation requirements in this model system to extrapolate these findings and develop scientifically defensible conservation targets at kilometres-extent landscapes. Species diversity (gamma diversity) can be an important driver – with areas that have higher diversity predicted to require higher percentages of land set aside for conservation. In this model system, gamma diversity explains 49% of the variation in the number of sites required to represent all species Fig. . Thus, w29, ecosystem productivity30, population dynamics31 and species-area relationships11. The advantage of the model system here is that the spatial extent of study areas  along with abiotic drivers  are held relatively constant, while species diversity on each tree varies. The value of using a model system lies in the ability to have experimental replicates to test hypotheses about conservation requirements in a way that is not possible in larger systems. Because ecological systems are hierarchical32 we believe that patterns from the model systems  is a globally recognized lichen biodiversity hotspot34 with a climate characterized by cool, moist summers and mild winters. Land cover is mainly forests dominated by balsam fir , which occur along the slopes and tops of ribbed moraines — glacial features of rolling hills35 — interspersed with sphagnum-dominated bogs36. Along with the balsam fir trees, black spruce (Picea mariana) can be found in wet areas and yellow birch  occur sporadically throughout the forest, mostly on upland areas.The study area is the Central Avalon Forest Ecoregion, on the island of Newfoundland, Canada. The area  each of which contain 15–22 species (conservation targets). Within each replicate landscape, there are 20 potential planning units , from which we selected the minimum set that represents all species via the Marxan algorithm (described below). The number of planning units per tree is constrained by logistics and sampling protocols described in ref. 27.We replicate our test for whether SCP have a consistent outcome in terms of the minimum number of sites required to represent all species at least once using a model system with two different sampling schema. In the first sampling scheme, we sampled 24 balsam fir trees within a single transect (100 m × 5 m). Trees were of a similar age and we sampled them for macro-lichen diversity by placing a 1 m × 0.1 m “microtransect” vertically along the north- and south-facing sides of the tree bole (starting 0.9 m from the ground), and counting the species richness and number of thalli within 10 cm sample blocks along the transect. Trees contained between 15–22 lichen species each, and overall (gamma) diversity of lichens in the stand was 37. The individual 10 cm × 10 cm blocks contained between 3–12 species and are the analog to “planning units” in the SCP framework. Details on the larger ecoregion characteristics and the lichen sampling and identification protocol can be found in ref. 28.In the second sampling scheme, we sampled 21 sites dispersed across the ecoregion. At each site, we inventoried the diversity of lichens on one balsam fir and one yellow birch . We used a similar microtransect composed of 10 cm × 10 cm sample blocks to sample lichen diversity on both the north and south sides of each tree, but this transect was only 0.5 m long and started at 1.1 m from the ground and sampled for both macro- and micro-lichens. Thus, in the second sampling scheme there were half as many planning units as in the first, but a larger suite of potential species sampled in each, and there were 21 replicate “landscapes” each for balsam fir and yellow birch. Balsam fir trees contained between 6–16 lichen species  and yellow birch trees contained between 5–17 lichen species . The individual 10 cm × 10 cm blocks contained between 1–12 species on balsam fir and between 0–11 species on yellow birch. Details on the lichen sampling and identification protocol can be found in ref. We used lichen data from both sampling schema to carry out a systematic conservation planning (SCP) exercise at two spatial extents. At the first extent, we treated trees as model systems for landscapes. Within each tree, we used the 10 cm × 10 cm sampling blocks as the planning units and asked how many of these would need to be set aside to represent all species of lichens on that tree at least once. In this case, we had 24 experimental replicates in the first sampling scheme and 21 experimental replicates each of two tree species in the second sampling scheme. At the larger extent (stand and ecoregion), we set each individual tree as the planning unit and asked how many trees needed to be set aside to represent each lichen species in the stand or ecoregion at least once.18 using the Simulated Annealing with Gradual Improvement option and 1000 iterations. Cost of planning units was set to 1 (default) in all cases, making planning unit costs invariant. For the tree-level planning scenario, we examined the relationship between the number of 10 cm × 10 cm blocks required to represent all species on a tree and species richness, across all 66 trees using a GLM  in the statistical software R37.In all cases, we applied Marxan


Which graft material is the optimal graft material for the treatment of aortic graft infections is still a matter of controversy. We used a branched xenopericardial roll graft to replace an infected aortic arch graft as a “rescue” operation. The patient is alive and well 37 months postoperatively without recurrence of the infection and any surgical complication. This procedure may have the possibility to serve as an option for the treatment of aortic arch graft infection. Orthotopic aortic reconstruction with an intraoperatively prepared xenopericardial branched roll graft was successfully performed as a rescue operation to treat a patient with a graft infection.1.1nd left posterolateral branch, 90%. All coronary artery bypass grafts were occluded. The origin of the left subclavian artery was ligated, and a 3rd graft branch was extended by a graft to the axillary artery via the left thoracic cavity. One month postoperatively, open‐chest drainage had been performed to treat left thoracic empyema. Subsequently, an incisional abscess was noted around the site of the left axillary anastomosis, and a graft‐branch‐to‐skin fistula was diagnosed. In 2013, at 64 years of age, the abscess was opened and the graft branch to the axillary artery was partially removed through a subaxillary skin incision. On admission to our hospital, the patient's serum C‐reactive protein level was elevated to 22.5 mg/dL, and a blood culture was positive for methicillin‐sensitive Staphylococcus aureus. The patient gradually became drowsy, and brain magnetic resonance imaging revealed multiple fresh cerebral infarctions and severe right internal carotid artery stenosis  for acute myocardial infarction at 55 years of age, and coronary artery bypass graft surgery x4 using left internal thoracic artery, radial artery, and saphenous vein grafts at 56 years of age. In 2012, at 63 years of age, a triplex 26 mm  had been used to perform a total aortic arch replacement procedure to treat a true aortic arch aneurysm at a nearby hospital. A reversed elephant trunk was inserted to facilitate the distal anastomosis using stepwise distal anastomosis technique. Preoperative coronary angiography showed the following stenosis: proximal left anterior descending artery, 75%; 1st diagonal branch, 75%; 1st left posterolateral branch, 75%; and 21.22 pericardial sheet  was simultaneously prepared intraoperatively from bovine pericardial sheets on a separate, sterile operating table. It takes 30‐40 min. to prepare a branched xenopericardial sheet. The method used to prepare the branched xenopericardial roll graft has been described in detail previouslyA cardiopulmonary bypass through a re‐resternotomy was established by means of two venous cannulas and an inflow cannula into the graft. The left subclavian abscess cavity communicated with the graft. Because of the dense adhesions, the left‐side of the heart was not dissected, and the coronary artery bypass graft was abandoned. Under deep hypothermic circulatory arrest with intermittent pressure‐augmented retrograde cerebral perfusionAs of 37 months postoperatively, the patient has been free of local recurrences of the graft infection, of pseudoaneurysms on the suture lines, and of other graft‐related complications, including of the branches  together with a xenopericardial sheet may be another option to achieve partial reconstruction of the aortic archIn conclusion, accumulation of clinical cases and confirmation of the long‐term durability of branched xenopericardial grafts may demonstrate their advantage as one of the options for the treatment for native aortic and aortic arch graft infection.Additional supporting information may be found online in the Supporting Information section at the end of the article.Supplementary VideoClick here for additional data file.


During the past three decades an expansive literature has emerged that is dedicated to analysing the processes of policy transfer. One neglected pathway involves subnational agents emulating crime control innovations that have emerged in subnational jurisdictions of other nations. This paper presents the case of the London Mayor's Office for Policing and Crime's (MOPAC) Alcohol Abstinence Monitoring Requirement (AAMR) Pilot to examine the multi‐level factors that facilitate and/or constrain international–subnational crime and justice policy transfer.A qualitative case study design reconstructed the (in)formal events that led to components of the South Dakota 24/7 Sobriety Project (USA) being either abandoned or integrated into MOPAC's AAMR Pilot. Evidence is drawn from elite interviews and documentary materials.A series of inter/transnational‐, macro‐domestic‐, meso‐ and micro‐level factors enabled and/or obstructed processes of complete international–subnational policy transfer. Exclusion of domestic violence perpetrators from the London Pilot was fuelled by interest‐group hostility and mobilization. Use of alcohol tags rather than breathalysers to monitor compliance was a result of political–economic constraints, concern surrounding intrusion, technological innovation and policy‐orientated learning. The decision to omit an ‘offender pays’ funding mechanism was a consequence of legal incompatibility and civil service reluctance, while ‘flash incarceration’ for breach was not implemented due to European policy harmonization.The London Alcohol Abstinence Monitoring Requirement Pilot was a policy ‘synthesis’ that combined ideas, goals, vocabulary, principles, technology and practices from the South Dakota model with the existing English and Welsh criminal justice framework. Structural factors and the actions of particular agents limited the extent to which policy transfer occurred. A process in which knowledge about crime and justice institutions, policies or delivery systems in one jurisdiction is used in the development of crime and justice institutions, policies or delivery systems in another jurisdiction in a different country  in 1991 and was later elected Attorney General. In 2003/4 he was appointed to a task‐force charged with reducing the state prison population. Having recognized that substance misuse continued to lie behind much of the work of the criminal justice system, he suggested that an initiative similar to his Bennett County project be piloted. The 24/7 Sobriety Project began in February 2005 in three counties. The pilot initially targeted drink‐driving defendants with at least one prior drink‐driving conviction within the previous 10 years. Software was developed to track the results of each defendant's test data, and participants helped to support the cost of the initiative by paying $1 per test. Judges in the pilot jurisdictions considered 24/7 Sobriety to be a success and, via word of mouth, the project began diffusing to other South Dakota counties Following his attendance at the OPPF, Malthouse instructed his team within the Greater London Authority to undertake desk research into the architecture and outcomes of 24/7 Sobriety. Then, in late 2010, he commenced a London compulsory sobriety pilot campaign. At the heart of his vision were the core components of the South Dakota model: court‐mandated alcohol abstinence; regular monitoring; offender pays; and ‘swift, certain and fair’ punishment for breach. Domestic abusers were highlighted as potential pilot participants, along with drink‐drivers and night‐time economy offenders. Four years later, under the leadership of Malthouse's successor, Stephen Greenhalgh, MOPAC launched an AAMR Pilot in the South London Local Justice Area. As illustrated in Table inter alia, language similarities; institutional and ideological compatibility; economic and technical feasibility; past policies; policy complexity; political leadership; and the influence of networks. Both these models also recognize that policy importation rarely results in photocopying (i.e. the pure replication of a programme). Instead, ‘soft’  or ‘hard’  elements of non‐indigenous schemes are typically fused with existing domestic programmes and practices to create a locally sensitive policy hybrid.Within the mainstream policy transfer literature five main analytical approaches can be detected: process‐centred, comparative, ideational, practice‐based and multi‐level Following a brief description of methods, the remainder of this paper adopts a multi‐level framework to analyse the factors that enabled and/or hindered processes of international–subnational policy transfer from South Dakota to South London, and that resulted in the design of MOPAC's AAMR Pilot morphing over time. Structure and agency are examined across four dimensions: the global and inter/transnational level; the macro‐state level; the meso‐level; and the micro‐level. Discussion is initially focused on factors that aided and/or obstructed broader transfer processes, before moving to the factors that led to domestic abusers being deemed ineligible for inclusion in the pilot and alcohol tags being utilized as the sole monitoring technology. The factors that led to two core elements of 24/7 Sobriety—offender pays and ‘swift, certain, and fair’ punishment—being abandoned will then be presented.Consistent with an exploratory case study design Findings indicate that a series of factors facilitated and/or constrained crime and justice policy transfer with regard to MOPAC's AAMR Pilot. As illustrated in Table Legal Aid, Sentencing and Punishment of Offenders Act 2012. To expand, although some VAWG experts had not expressed strong views or had offered contingent support towards Malthouse's aspiration to import enforced alcohol abstinence, others had been expressing hostility towards emulating 24/7 Sobriety in London for quite some time Evidence suggests that the decision to exclude domestic violence perpetrators from MOPAC's AAMR trial was a product of meso‐level resistance from the UK Violence Against Women and Girls (VAWG) community, and was made after a multi‐agency compulsory sobriety lobbying alliance see  had persWell, I was disappointed […] we came to the view that if you pitch high and come in lower, you come in low enough that you still think that the structure of the scheme will prove its efficacy and that over time people will then start accepting moving towards the full model’—interviewee: Kit Malthouse.Interestingly, Malthouse's prediction was relatively accurate. Following what a government junior minister described as ‘very encouraging’ results, the Cameron Government (2015–16) formally extended MOPAC's AAMR trial for 6 months in July 2015 while discussions took place about the pilot's longer‐term future In siding with the VAWG community and exercising its power to dictate English and Welsh penal policy, the government subsequently announced that MOPAC's pilot could not include domestic violence perpetrators. Disappointment aside, Malthouse was decidedly pragmatic when reflecting on the matter when interviewed in 2015, his attitude being that compromises had to be made to experiment with compulsory sobriety in London, and that positive evaluation results would bolster future attempts to mimic the South Dakota model more closely Several considerations influenced MOPAC's decision to use alcohol tags rather than twice‐daily breathalysing to ensure AAMR compliance. The first centred on macro‐domestic financial and political constraints. MOPAC officers were concerned about the resource implications of breathalyser testing, especially as they were operating within a context of shrinking public services and probation upheaval in the form of Transforming Rehabilitation I gave everything to London, all of my papers, I gave hundreds of files […] I said ‘don't reinvent it; here is how to do [the pilot]’. I spoke to all the policy people down at the Mayor's Office around how they should it. We all succeed together; it is not individual—interviewee: Karyn McCluskey.With regard to international lesson‐drawing, a week‐long fact‐finding visit to the United States by a MOPAC Special Adviser played a role in the abandonment of breathalysers. This adviser accepted an invitation forwarded by the National Association of Drug Court Professionals (NADCP) to attend its Annual Training Conference in Washington, DC Lastly, evidence suggests that MOPAC's preference for alcohol tags was an outcome of international and subnational policy‐orientated learning. MOPAC representatives who were responsible for erecting London's AAMR Pilot tuned‐in to the voices of those who had attained experience of deploying alcohol tags in the United Kingdom and/or the United States. In relation to the subnational–subnational interaction that occurred between UK‐based individuals, MOPAC officials engaged with a district judge who endorsed alcohol tags, having used them efficaciously within child protection cases that were brought to a Family Drug and Alcohol Court in London Findings suggest that the ‘non‐transfer’ habeas corpus the European Court of Human Rights could object to offenders who breach their AAMR being detained without trial Criminal Justice Act 2003Interestingly, US–UK legal discordancy was also cited as a reason as to why the Government would not permit those who breached their AAMR to be ‘flash incarcerated’ as part of MOPAC's pilot. Ministers stated that due to In reaction to this transfer obstruction, MOPAC agents did strive to incorporate the spirit of the ‘swift, certain and fair’ philosophy into their pilot in a manner that was consistent with the English and Welsh criminal justice framework. A bespoke non‐compliance notification process was implemented that entailed staff employed by MOPAC's alcohol tag provider immediately contacting an offender following a suspected breach This is the first paper, to the author's knowledge, to directly examine the multi‐level factors that facilitate and/or constrain international–subnational crime and justice policy transfer. It is also the first to provide a synopsis of the formulation of MOPAC's AAMR Pilot, which itself was the first trial in Europe to combine enforced alcohol abstinence with alcohol tagging Nonetheless, this case study reveals a number of important findings, not least that international–subnational crime control policy transfer is a highly complex and contested form of policy development, even for those operating within a powerful and influential jurisdiction such as Greater London. Years elapsed between Malthouse's attendance at the OPPF and the implementation of a ‘Londonized’ version of 24/7 Sobriety. Although the findings of a single case should not be used to predict future events None.


The spectral features identified above are then used to identify the different forms of carbon present within the metallic films deposited from reactive organometallic inks. While spectra for metals is obtained in dedicated surface science instrumentation, the complex relations between carbon and metal species is only revealed by secondary electron (SE) spectroscopy and SE hyperspectral imaging obtained in a state‐of‐the‐art scanning electron microscope (SEM). This work reveals the inhomogeneous incorporation of carbon on the nanoscale but also uncovers a link between local orientation of metallic components and carbon form.Carbon and carbon/metal systems with a multitude of functionalities are ubiquitous in new technologies but understanding on the nanoscale remains elusive due to their affinity for interaction with their environment and limitations in available characterization techniques. This paper introduces a spectroscopic technique and demonstrates its capacity to reveal chemical variations of carbon. The effectiveness of this approach is validated experimentally through spatially averaging spectroscopic techniques and using Monte Carlo modeling. Characteristic spectra shapes and peak positions for varying contributions of sp During the fabrication of carbon film based devices, electron irradiation is prevalently used for nanopatterning, nanostructure characterization and surface modification.Films and nanomaterials made of complex carbon systems are key to many next‐generation technologies2 and often used as calibration material for scanning tunnel microscopy due to having large, flat, chemically inert area.−6 AmpereHere, we probe carbon surfaces with a novel spectroscopy technique based on the energy‐selective collection of secondary electrons which has been used for insights into nanoscale mapping of semicrystalline polypropylene,The aim of this paper is to probe the character of different carbon species on HOPG surfaces by SEHI to obtain further understanding of the inherent bond types and their associated SE emission. These insights are then applied to carbon present within printed complex metal carbon systems which are expected to affect the end functionality dependent on the bond type of local carbon inclusions. The experimental results are corroborated by Monte Carlo (MC) simulations.22.1FigureHOPG, a manmade polycrystalline graphite (stacked graphene) is well characterized and, as it is possible to exfoliate the top surface revealing “clean” or “fresh” layers, is often used as calibration material for scanning tunnel microscopy.−2, both produce a non‐uniform nucleation of contaminations on the surface following existing localized features on the HOPG surface. The higher doses of 36.7 and 146 C m−2 produced more uniform boxes of a carbonaceous species. The height of the EBID increases from 0 to ≈100 nm with dose as shown in the atomic force microscope image in Figure The difference between Figure FigureThe Secondary stage of contamination is observed in Figure FigureOur observations also revealed the presence of another type of contamination. 2.2The observation of distinct grey levels for fresh HOPG (brightest emission), aged HOPG (lowest emission) and EBID (midgray level) surface indicates the sensitivity of SE emission to the configuration of the carbon which should also be reflected in differences in their SE spectral shape. The electron transport within these materials is key to their analysisFigure2 and sp3 bond types and confirms the SE emission is different for each allotrope with each dominant peak in a different energy range. Therefore, we assign P1 to be sp2‐like, P3 to be sp3‐like and P2 to be associated with the bond‐type associated with the nature of the primary contamination. Amorphous hydrogenated Carbon (a‐CH) is cited to have a higher SE yield than HOPG, due to its diamond‐like sp3 bonding and hydrogen content and their respective low work functions.2 bonds to more distorted sp3‐like bonds.The SE spectra of fresh, aged and EBID covered surfaces of HOPG reveal substantial differences as can be seen in 3 bond types already observed in dedicated surface science SE instrumentation.2‐like HOPG, a‐CH, and sp3‐like diamond, MC simulations of SE emission of HOPG surfaces were generated with different ratios of these carbon types to match the shape of the SE spectra obtained in our SEM, as in Figure 2‐like, a‐CH, and diamond sp3‐like. For further experimental validation, Raman and XPS of the different HOPG surfaces was performed, shown in Sections S4 and S5 in the Supporting Information. The Raman analysis reveals a change in disorder (a change in the Id/Ig ratio) however, this parameter is restricted when evaluating the amorphous nature of the investigated carbons, as it is only indirectly related to the fraction of sp3 sites.3 content with aging, however once again, this technique is expected to be affected by inhomogeneous depth‐resolved distributions of the different bond‐types.2 and sp3 ratios and has significant potential as another tool for the characterization of carbon surfaces, especially if carbon is present within more complex systems such as those in carbon‐containing metal films.The dominant peak in the SE spectra of aged HOPG appears at a higher energy range closer to the energy range for sp2.3FigureHaving linked the variations in emission from different energy regions to the presence of different carbon bonding states, the inspection of those different carbon bond types in a more complex system is now possible. We now look to a less well studied metal/carbon reactive organometallic (ROM) system. 2 like, a‐CH mixed, and Diamond sp3‐like. As shown in Section S6 in the Supporting Information, energy dispersive x‐ray spectroscopy (EDX) analysis reveals limited information except the atomic percentage of carbon was higher in the porous regions compared to the smooth regions, in agreement with our SE spectra. However, the SE spectra reveal further important differences in the character of the carbon species within the metal films. In the case of the thin films, SE emissions from each carbon bond type are present but contributions from the sp2‐like and a‐CH mixed components are increased in the porous form. The spectra of the thicker films reveal the presence of carbon too, albeit with a different character to that of the thin film. The sp2 peak region in the thin film is higher than in the thick film whereas, the thick film exhibits a strong SE emission in the region ascribed to carbon in its sp3 form. This suggests that different crystal orientations in the metal might interact or be correlated to different bond types of carbon. The carbon bond type will contribute to or be detrimental to the conductivity of the film, for example, graphite (sp2‐like) is conductive whereas diamond (sp3‐like) is insulating. However, these higher energy regions are also likely to be influenced by the presence of Pd (100) and Ag (100) peaks, so further work would require SE spectra to be collected with a higher energy resolution to make this distinction clear. Further work would also be needed to use the above information to maximize the conductivity by reconstructing the localized nucleation and growth processes based on a more detailed SE spectroscopy study in combination with more traditional characterization techniques. Nevertheless, we have demonstrated that the SE spectroscopy in an SEM with a through‐the‐lens detector can provide localized information not accessible by traditional averaging techniques such as Raman, XPS, and EDX.In Figure 3SEHI analysis of HOPG surfaces in LV‐SEM revealed a two stage process in surface modification of HOPG through hydrogenation (primary) and charge induced deposition of amorphous carbon species (Secondary). This insight into carbonaceous film formation on carbon has elucidated on different carbon bond types and is also reflected in the changing shape of SE spectra which are confirmed by MC modeling. Exploring SE spectral features to identify the presence of carbon contamination hidden in films deposited from ROM inks reveals links between carbon incorporation, its orientation, and the crystal orientation of the metallic component. As the link between carbon with different bond types and metal deposition is of interest to other complex systems such as anodes in Li‐ion batteries or in catalysts,The authors declare no conflict of interest.SupplementaryClick here for additional data file.


The significance and utility of innovative imaging techniques in arterial clot analysis, which enable far more detailed and automated analysis compared to standard methods, are presented. The examination of two types of human thrombi is shown, representing the main ischemic stroke etiologies: fibrin–predominant clot of large vessel origin and red blood cells–rich clot of cardioembolic origin. The synergy effect of Fourier–transform infrared spectroscopy (FTIR), Raman spectroscopy (RS) and atomic force microscopy (AFM) techniques supported by chemometrics in comparison with reference histological staining was presented. The main advantage of such approach refers to free–label and non–destructive quantitative imaging of clinically valid, biochemical parameters in whole sample (FTIR–low resolution) and selected regions (RS–ultra–high resolution). We may include here analysis of lipid content, its distribution and total degree of unsaturation as well as analysis of protein content (mainly fibrin and hemoproteins). The AFM studies enhanced the vibrational data, showed clearly shape and thickness of clot features as well as visualized the fibrin framework. The extraordinary sensitivity of FTIR and RS imaging toward detection and discrimination of clinically valid parameters in clot confirms its applicability in assessment of thrombi origin. Ischemic stroke (IS), caused by vessel occlusion represents 87% of all stroke cases. Thrombectomy, with mechanical clot retriever, is one of the recanalization treatment options for IS. This technique also enables collecting and analyzing of the fresh thrombus samples. It has been recognized that the molecular analysis of the clot composition and its physical properties may provide information on selection of recanalization strategy and establishing of stroke etiology that are crucial for clinical outcome and secondary stroke prevention3. Thus ongoing studies on extracted thrombotic clots have focused on the analysis of their histology composition and have identified the presence of accumulated platelets, fibrin, red blood cells (RBCs) and white blood cells (WBCs)4. Computed tomography (CT) and magnetic resonance imaging (MRI) studies have been correlated previously with the clot histological composition to assess thrombolytic recanalization outcome and IS etiology. A lower clot density  was correlated with a higher resistance to the pharmacological lysis and mechanical thrombectomy2. In turn a high WBCs content in thrombi was associated with the cardioembolic etiology, extended mechanical recanalization time and less favorable recanalization and clinical outcome5. The RBCs–rich clots had higher density than platelet–rich thrombi2 and were more susceptible to intravenous and intra–arterial thrombolysis6. On contrary a number of studies have reported that CT and MRI give poor prognostic information on clinical outcome and have a limited clinical diagnostic value8. It is a heterogeneous disease with numerous underlying causes. Although the numbers of etiopathological classifications have been introduced, stroke etiology for significant number of patients cannot be defined. Published data indicated that an embolic source of stroke remains unidentified in 25–38% of patients while its origin is crucial for patient’s classification in clinical trials, epidemiological or genetic studies and most of all for therapeutic decision–making in everyday practice9.Stroke is the fifth cause of death globally accounting 6.5 millions of deaths worldwide13. In the present work, we show that the applied techniques enable the detection, visualization and differentiation of various features based on their biochemical (VS) and physical properties (AFM).Herein, we propose the combination of two vibrational spectroscopies (VS): Fourier–transform infrared spectroscopy (FTIR) and Raman spectroscopy (RS) supported with atomic force microscopy (AFM) and histological staining as a potential set of tools for the determination of acutely retrieved clot composition. We have previously described and reported the usefulness of such a set of techniques for the characterization of atherosclerotic plaque and other tissue alterations14. Further on, the free–label RS imaging technique was applied for the chosen regions of interest (ROI) to detect biochemical markers with the spatial resolution of around 0.4 µm12. At the end topographies of chosen ROIs were obtained with the use of AFM. Hematoxylin and eosin (H&E) staining was used as a reference. We investigated thrombi from different etiology of the acute ischemic stroke: a fibrin–predominant clot of a large vessel origin and RBCs–rich clot of a cardioembolic origin. The main goal of this work was to present the benefits of the combination of FTIR, RS and AFM techniques for the thrombi analysis and to highlight the potential of such assessment to identify brain clot origin – crucial for future stroke prevention. In addition, our report has a retrospective nature for the future development of the new and label–free VS imaging based method for the clot identification. Obviously, further VS investigations, combined with extensive histological examination on a statistically significant number of thrombi, are required to confirm presented applicability. To the best of our knowledge this is the first study to utilize label–free and chemically sensitive imaging of acute IS retrieved clot.As presented in Fig. The results section is divided into two parts which presents the analysis of thrombi which were representative for a different etiology of the acute ischemic stroke: one sample was derived from a patient suffered from large vessel stroke due to artery dissection while two other samples were collected from two patients with cardioembolic stroke.Figure −1 region, which is especially intense for bands of the methylene and olefinic groups  and asymmetric (asym.) stretching vibrations(ν) of CH2 groups [ν(CH2) modes] observed at 2849 and 2919 cm−1, respectively, and attributed mainly to the high content of lipids or biomolecules containing long acyl chains21. The detailed analysis of the lipid fraction is based on the comparison of the FTIR spectra with the standard compounds and is discussed in Sub–section 3.1.3. Fibrin– and heme–rich classes are characterized in FTIR spectroscopy by domination of intensive amide I at 1652 cm−1 and amide II at 1540 cm−1 bands22. More intense amide bands correspond to the protein–rich class containing fibrin. As we mentioned, RBCs are localized nearby lipids, hence contributions of band at 1461 cm−1 as well as intense bands located at 2849 and 2919 cm−1 in the heme class are expected18.FTIR image of the organic matter distribution was constructed by integration of the 2800–3100 cmups Fig. 15–17. Th23 (for a specific laser wavelength) and it is manifested as an increased background signal24. For example this phenomena was successfully applied for visualization of elastic lamina or fibrous caps in atherosclerotic plaques13. On the other hand, the increase of auto-fluorescence can be assigned to RBCs, where the closely packed heme groups of hemoglobin absorb a considerable amount of Vis photons. This process causes an additional generation of photothermal effects leading to raised background in Raman spectra of RBCs27. This enabled us to assume that auto–fluorescence image displayed in Fig. 13. Raman integration image in the region of 2830–2860 cm−1 revealed the localization of the lipid–rich grease class. K–means CA distinguished three classes which correspond to the areas of the clot rich in fibrin, heme and lipids  modes, respectively28. Moreover, RS technique can easily provide the information about the general lipid unsaturation level. The total degree of unsaturation of the grease lipid–rich class of the clot can be calculated on the base of the RS intensity ratio of the bands at around 1266/1300 cm−1 or at 1655/1444 cm–1 28. In the case of the presented average RS spectrum of the lipid–rich class of clot, the bands at around 1266 and 1655 cm−1, connected with the bending vibration of =CH group and ν(C=C) modes, respectively, are almost invisible, what clearly indicates the absence of unsaturated lipids. Moreover, presented previously Raman database of lipids28, suggests presence of lipids mixture, which detailed analysis is presented in chapter 3.1.3.Figure ids Fig. . The ave10. Here, the chosen ROIs were analyzed from the point of its shape and topography profiles in order to differentiate various clot structures. The fixed and frozen clot sample, was cut into 10 µm slices but due to structural differences between clot components they dried in different manner. Therefore, studying the topography variation of dried samples delivers information about different features, as presented previously10. The topography of the red and green ROIs clearly showed that some areas of the clot stick out from the plane what corresponds to the clot scaffolding. Such areas were assigned to the fibrin skeleton of the clot as H&E staining indicated. The edge is the highest and the stiffest in the entire body of the clot  modes of the lipid–rich grease is similar to the ratio observed in the RS spectra of palmitic and stearic acids whereas the position of the sym.ν(CH2) mode in the RS spectrum of lipid–rich class corresponds rather to the band of octadecane than fatty acids. Bands observed at 1445 and 1463 cm−1 are assigned to the γ(CH2) and δ(CH2) modes, respectively29. While bands at ca. 1300 cm−1 and in the region of 1200–1060 cm−1 originate from the twisting CH2 and ν(C–C) vibrations, respectively28. The spectral profile of all those modes is similar to the spectrum of stearic acid. However, the absence of the ν(C=O) vibrations at approximately 1640 cm−1, suggests carbohydrate component such as long–chain octadecane. Similarly, to RS, the FTIR spectrum of the lipid–rich clot class was compared to the FTIR spectra of the same set of long acyl chain compounds  vibrations, respectively. FTIR spectrum extracted from lipid–rich class is characterised by the presence of the band at 1378 cm−1, 1462 cm−1 and 1472 cm−1 assigned to sym. δ(CH3), asym. δ(CH2) and γ(CH2) modes, respectively. The amide I (1653 cm−1) and amide II (1543 cm−1) bands observed in the lipid–rich spectrum originate rather from other tissue components in this class (proteins). The absence of ν(C=O) modes approximately at 1710–1690 cm−1, suggests that the lipid–rich class of the clot contribute from the long–chain alkane. However, the ratio of bands at 1462 and 1472 cm−1 and the visible only in the second derivative spectrum, very weak vibrations from C=O groups, suggest also the presence of the carboxylic acids.RS and FTIR spectra, extracted for the lipid–rich grease, are as were compared with the spectra of the standard compounds published so far of various carboxylic acids, triglycerides and alkanes with the different number of carbon atomsnds Fig. . Spectra30. Additionally, the high resolution (hi-res) RS spectroscopic imaging indicated the presence of cholesterol in a form of few–micrometric crystals present in the clot structure (−1 and are assigned to the sequence to the cholesterol backbone vibrations such as the γ(CH2) and ν(C=C) modes of the cholesterol ring28. In the high–wave number region, a very typical doublet at 2868 and 2932 cm−1 originated from CH2 modes is observed28.Both, FTIR and RS spectroscopies suggests that the lipid–rich grease areas in the clot is a mixture of different chemical with the majority fraction consisting of long chain saturated fatty acids (SFA) and alkanes with around 16–18 atoms of carbon. Such presence of alkanes next to fatty acids produced due to the oxidative stress is not surprising and plays a crucial role in IS pathogenesistructure . The mos−1 assigned to sym. ν(CH3) mode and high intensities of amide I and amide II bands22. In the region of 1324–1200 cm−1 attributed to the amide III range we identified two bands at around 1311 and 1236 cm−1 corresponding to α–helix and β–sheet secondary structure, respectively31. Based on the comparison of intensities of the bands at 1236 cm−1 and 1311 cm−1 we were able to assign recorded spectra to fibrin and heme, respectively. The grey spectrum with the higher intensity of β–sheet band in comparison to α–helix band was attributed to fibrin class. It is known, that fibrin consists of the mixture of α–helices, β–sheets and other secondary structures and we explain this assignment by the α–helix to β–sheet transition as a result of the formation of clot in dynamic conditions (flowing blood)32. The blue class was relegated to heme structure of RBCs.Figures −1) to 1584 cm−1 mode originating from C–C porphyrin in–plane vibrations. This RS distribution is consistent with the UHCA image constructed from FTIR data.Figure 6This work demonstrates the significance and utility of free–label FTIR, RS and AFM techniques in arterial clot analysis in comparison with reference histological staining. Synergy effect of these free–label imaging techniques, delivering vast amount of sample data, enables far more detailed analysis compared to standard methods. This is demonstrated based on the examination of two types of thrombi, representing main IS etiologies: fibrin–predominant clot of large vessel origin and RBCs–rich clot of cardioembolic origin; where wide spectrum of clinically valid parameters is assessed with FTIR, RS and AFM techniques. Table The main advantages of the VS application, both FTIR and RS, over standard methods of clot composition analyses, refer to label–free and non–destructive quantitative imaging of chosen biochemical compound in whole sample (FTIR–low resolution) and selected region (RS–ultra–high resolution). In addition to the analyses conducted within this study applied techniques enable qualitative and semi–quantitative assessment of type of lipids with their distribution, define the total degree of lipids unsaturation, present the ratio of total lipids to total proteins, differentiate the heme/RBCs from fibrin content. Capabilities of FTIR and RS make it a very flexible research tool for thrombus analysis.The FTIR and RS analyses of the fibrin–predominant thrombus obtained from a person with aortic dissection enable discrimination of three molecular classes: fibrin, heme and different types of lipids. The detailed analysis of RS and FTIR spectra obtained from lipid–rich grease class allowed to assign these clot lipids to the mixture of SFA and alkanes with 16–18 atoms of carbon, which are known to play a crucial role in ischemic stroke. FTIR additionally allowed calculation of lipid–to–clot area ratio concluding that overall 13.19% of lipids fraction is present in the fibrin–predominant clot and revealed non–homogeneous distribution. RS allowed us to calculate the total degree of lipid unsaturation and indicated the saturated lipid dominance. Additionally, the high resolution RS spectroscopic imaging revealed the presence of cholesterol in a form of few–micrometric crystals in clot structure. The morphology of cholesterol crystals and grease lipid–rich class was confirmed by AFM. The H&E staining was far more time–consuming, destructive for sample in terms of lipids rinsing due to requirement of sample dehydration and finally did not allow for lipids visualization. Therefore, this method is not suitable for the lipids detection but is useful as clot morphology reference. The AFM studies enhanced the vibrational data and showed clearly shape and thickness of the clot sample. The AFM results revealed that fibrin framework creates skeleton for the whole thrombus structure. The RS as well as the FTIR integration images of the RBCs–rich clot enabled to distinguish two different protein structures of heme of RBCs and fibrin. The RBCs–rich clot obtained from the patient with the cardioembolic origin was found to not contain lipid fraction.33. Furthermore, SFA are common risk factor for vascular diseases34. Remaining two thrombi, identified as RBC predominant, were both obtained from patients suffering from cardioembolic stroke. As expected, lipids were not detected and their main components were heme from hemoglobin and fibrin.Presented results, based on three cases, indicate potential diagnostic role of VS in identification of thrombi origin. First thrombus of large vessel origin, identified as fibrin–predominant, was obtained from the patient with aortic dissection. It was rich in different types of lipid fractions, including mainly SFA. This finding supports vascular origin of thrombotic material as lipids are commonly present in inflammatory changed vessel wallSample size of this study does not allow drawing clinical conclusions neither on pathomechanisms nor stroke etiology. Presented results aimed to demonstrate added value of IR, RS and AFM techniques to future large scale clinical studies on IS. Such studies have a retrospective nature and will allow for a future development of the new, label–free imaging techniques for clot evaluation with the application of the VS.Application of two vibrational imaging techniques combined with AFM allowed for detection and visualization of various lipid content, RBCs accumulation and fibrin–rich areas in the clots, lipid differentiation and assessment of total degree of lipids unsaturation, semi–qualitative evaluation of total number of lipids as well as physical evaluation of the clot. Such methodology is complementary to the conventional histological staining, but is label–free, operator objective and automated. We proved that the VS can be the potential label–free set of tools for the thrombus composition evaluation. To the best of our knowledge this is the first work where the human brain clots were chemically characterized and visualized on the base of the FTIR and RS measurements, supported by AFM in combination with H&E.The study was approved by the Ethical Committee of the Jagiellonian University and all the experiments were performed in accordance with Ethical Committee of the Jagiellonian University guidelines and regulations. All patients and/or authorized representatives gave full and signed informed consent. A detailed description of materials and methods are presented in the supplemental materials (SM).35. Stroke type was classified to one of five etiologies: large vessel, small vessel disease, cardioembolic or unknown etiology, according to TOAST criteria36. From each fixed and frozen in optimal cutting temperature compound (OCT) clots, minimum three cross sections were cut and transferred onto CaF2 slides and then investigated by FTIR, RS and AFM spectroscopy. Finally samples were stained with hematoxylin and eosin (H&E) what requires dehydration with the use of concentrated alcohol37 and often results in rinsing of the lipids from the sample.Three acute IS patients (N = 3), following informed consent, were included in this study. Each patient underwent mechanical thrombectomy with SOLITAIRE  stent retriever; treatment was performed according to manufacturer protocol. Two patients suffered from cardioembolic stroke, one from large vessel stroke due to artery dissectionSupplementary information


Coastal erosion is one of the major and serious concerns for coastal communities residing in the low lying areas, especially near to estuary delta regions. These regions see lots of anthropogenic activities such as economic development, infrastructure and human settlement especially in rapidly developing countries such as India. Shoreline change is a natural process that occurs in coastal areas. But due to the stresses happening in the coast because of anthropogenic activities, understanding how shorelines change over time is important for sustainable management of coast. A crucial aspect of shoreline change monitoring is to identify the location and change over time which can be achieved by developing monitoring strategies using satellite remote sensing data. Performing shoreline change analysis using long term satellite records will help us to understand how shorelines respond to coastal development over time. In the present study we investigate shoreline erosion and accretion rate using three temporal Landsat scenes acquired over a thirty year period for the years 1988, 2000 and 2017. Digital Shoreline Change Analysis System (DSAS) an extension of ArcGIS software was used to compute rate of change statistics by calculating End Point Rate (EPR) values. We observed that Chilika coast is experiencing both erosion and accretion process with very high erosion rate of −13.6 m/yr and accretion of 13.5 m/yr, at Chilika Lake mouth. The average erosion and accretion rate of −1.13 m/yr and 1.41 m/yr were recorded for the study region. Specifications tableValue of the data•Data are georeferenced and digitized for any future studies.•Data can be used to understand dynamics of lake mouth over a thirty year period by quantifying erosion and accretion process during 1988–2017.•The data produced here will be useful for coastal communities, researchers, policymakers and stakeholders working on coastal ecosystems.1https://earthexplorer.usgs.gov/).The data presented in this study will help us to understand the dynamics of lake mouth as well as the erosion and accretion process happening in the coast for past four decades. 22.1The current study site Chilika, located along the north east coast of Odisha with a coastal stretch of 120 km. Flowchart given in Totally 1861 transects were generated with 25 m spacing and the length of transects was 500 m . Rate of


Replying to Wasko et al. Nature Communications https://doi.org/10.1038/s41467-019-13613-4 (2019)1 in our work2. The correspondence from Wasko et al. argued that our finding on the positive scaling rate between storm runoff extremes and temperature can be mainly attributed to snowmelt processes, and claimed that storm runoff extremes should have a negative scaling rate globally. However, we do not agree with their arguments for several reasons.We are thankful for the interest of Wasko et al.3. Many recent studies have reported that sub-daily extremes are usually more sensitive to temperatures than those at a daily scale4, so the strong positive scaling rates of storm runoff extremes detected in our original publication2 may probably further increase at a finer temporal resolution. In addition, inspired by the comment of Wasko et al., we used the high-quality continental US MOPEX dataset and a Chinese basin dataset for detecting and matching the precipitation and streamflow peaks in the same storm events, identifying these two peaks occurring within 7 days, and then conduct scaling analysis with the coincident temperature at the catchment scales. With the matched precipitation and streamflow peaks, we could still observe strong positive scaling rates of storm runoff extremes, and these results are robust when changing the extreme definition or using daily mean temperature (Tmean) 1 day prior to the precipitation peak  and associated different Tpp between precipitation and storm runoff extremes. Wasko et al. misunderstood and assumed that we presupposed that both streamflow and precipitation must increase together with rising temperature. On the contrary, we did not make such an assumption. Instead we quantified and estimated the Tpp for both precipitation and storm runoff extremes, independently. With this method, we did not guarantee that the Tpp of precipitation and storm runoff were the same. Wasko et al. show an example in their Fig. 2 show that the differences of Tpp are usually within 1–2 °C in most areas of the globe except for limited regions in western United States and Southern Europe. Why do we need to detect the Tpp for precipitation and storm runoff extremes individually? Extreme precipitations are mainly governed by atmospheric thermodynamics and partially modulated by atmospheric dynamics, while the runoff generation is also impacted by underlying surface conditions. As the Tpp varies widely from region to region, spanning 0–30 °C5, we detected the Tpp station by station using the LOWESS method for precipitation and storm runoff extremes, and then used this to partition the non-monotonic hook structure into two branches (ascending below and descending above). We also examined the scaling pattern with the high-quality continental US MOPEX dataset and a Chinese basin dataset, and further reconfirmed the positive scaling rates and Tpp variability at the smaller catchment scale  hydrological model incorporated with the snowfall–snowmelt module in Soil and Water Assessment Tool (SWAT); these have been widely employed in capturing snowfall and snowmelt processes in hydrological community. The high Kling-Gupta efficiency (KGE) value and the similar scaling results of simulated storm runoff extremes with those of observations both verified the good simulation performance of these two models (Supplementary Figs. We attempted to examine the impact of snowmelt on storm runoff extremes using a multifaced approach. First, we tested the impact of the snowmelt temperature and omitted the data colder than 1.0 °C, 2.0 °C and 5.0 °C, respectively, and we also extracted data warmer than 0 °C for removing possible snowpack runoff consideration. In all cases, we still observed widespread positive scaling rates between storm runoff extremes and temperatures under different scenarios (Supplementary Figs. 11. The inconsistency between our publication and Wasko et al. is not due to snowmelt consideration but due to their omission of the consideration of a hook temperature structure and separation of base flow. Wasko et al. claimed that a decrease in antecedent soil moisture and snowmelt under a warming climate may somewhat offset flood intensification. However, precipitation intensity is the dominant driver of flood hazards12, and soil moisture is not projected to change dramatically13, except in transitional regions. We also find a significant seasonal variability of soil moisture; although both surface and root-zone soil moistures show a slight decreasing change in winter, they are more likely increasing in summer and autumn over most regions of the globe (Supplementary Figs. 14 and land-use land cover changes such as forest degradation contribute likely more to fast flow extreme intensification. We would like to thank Wasko et al. for this correspondence, which helped clarify several of our findings and we hope that it will generate more investigation of flash flooding generation mechanisms.Finally we would like to conclude by pointing out that, although the scaling-based projection is based on historical changes projected forward, a key conclusion in our publication that the storm runoff extremes may increase under warming in the future is not challenged by Wasko et al. and is supported by prevailing projections about increasing flood risk in the climate communitySupplementary Information


Very few pragmatic and community‐level effectiveness trials integrate the use of qualitative research over all stages of the trial, to inform trial design, implementation optimization, results interpretation and post‐trial policy recommendations. This is despite the growing demand for mixed methods research from funding agencies and awareness of the vital importance of qualitative and mixed methods research for understanding trial successes and challenges.HIV testing and treatment strategies in southern and eastern Africa, and a qualitative study conducted alongside a clinical trial testing the adaptation, acceptability and experience of short‐cycle therapy in children and adolescents living with HIV.We offer examples from work we have been involved in to illustrate how qualitative research conducted within trials can reveal vital contextual factors that influence implementation and outcomes, can enable an informed adaptation of trials as they are being conducted and can lead to the formulation of theory regarding the social and behavioural pathways of intervention, while also enabling community engagement in trial design and implementation. These examples are based on published findings from qualitative studies embedded within two ongoing large‐scale studies demonstrating the population‐level impacts of universal why behind success or failure of interventions in different contexts, but also inform the adaptation of interventions that can facilitate their success, and lead to new alternative strategies and to policy changes that may be vital for achieving public health goals, including the end of AIDS.We advocate for the integration of qualitative with clinical and survey research methods in pragmatic clinical and community‐level trials and implementation studies, and for increasing visibility of qualitative and mixed methods research in medical journals. Qualitative research from trials ideally should be published along with clinical outcome data, either integrated into the “main” trial papers or published concurrently in the same journal issue. Integration of qualitative research within trials can help not only to understand the  We share examples of qualitative research studies embedded within two large community‐based trials testing the population‐level effects of universal HIV testing and treatment (UTT)  to all those person living with HIV) in southern and eastern Africa 22.1Our first example is taken from the Sustainable East African Research in Community Health (SEARCH) NCT# 01864603) study, an ongoing community cluster randomized controlled trial (NCT#01864603) in 32 communities of approximately 10,000 persons each located in three regions in Kenya and Uganda. SEARCH aims to evaluate the health, economic and educational impacts of a community‐based strategy for immediate and streamlined ART for all HIV‐positive persons. A longitudinal qualitative research study embedded within the trial aims to reveal social, behavioural and implementation processes that influence the UTT strategy and its outcomes: why the strategy works or fails in communities, and how it operates in diverse settings. The qualitative findings also have been periodically “fed back” to trial leadership and regional teams to explain how the intervention has evolved, and to inform optimization. The SEARCH trial design is adaptive, and newer methods for inference and estimation of “treatment effect” are used 64603 stuThe SEARCH strategy involved multiple interventions to achieve the UNAIDS 90‐90‐90 targets. To reach the first “90%,” the study conducted multi‐disease testing and services at CHCs combined with home‐based testing for those who did not participate in campaigns These efforts yielded positive results vis‐à‐vis community‐wide participation in testing, and also in qualitative findings showed that they precipitated new opportunities and anxieties related to the disclosure of HIV‐positive status among those either newly diagnosed or confronted anew with a need to disclose as a result of the intervention. An analysis of experiences related to disclosure of HIV status in narratives of people living with HIV (PLHIV) from SEARCH published by Maeri and colleagues 2.2At the same time, qualitative research in SEARCH using data collected in the first two years of the study provided early signs that norms, beliefs and attitudes related to HIV testing, status disclosure and engaging in HIV treatment were changing. Combining these with data collected from another large randomized controlled trial, the Streamlined ART Initiation Strategy (START‐ART) trial in Uganda (NCT#01810289), an analysis published in this journal by Camlin and colleagues 2.3Our next example also illustrates the value of qualitative research for informing trial teams about study communities in the early stages of a trial and for shaping subsequent research. Social science research is integrated into the design of HPTN 017  cluster randomized trial 2.4The last example is from the BREATHER (PENTA 16) clinical trial. Working across 11 countries (including one centre in Uganda), this trial compared virological control of short‐cycle therapy (five days on: two days off) with continuous EFV‐based ART in 199 children and young people (aged 8 to 24) (70 from Uganda) living with HIV with viral load <50 c/mL to examine adaptation, acceptability and experience of short‐cycle therapy to inform intervention development 3a priori, but also generate new avenues of inquiry and opportunities for theory building in response to unexpected empirical findings. Especially in complex trials, interventions are often not implemented as planned, secular trends affect outcomes, and outcomes and their generalizability cannot be interpreted intelligibly without an in‐depth understanding of context. The increasing use of novel adaptive trial designs and hybrid implementation‐effectiveness trial designs is propitious for integration of longitudinal qualitative research, because these designs facilitate use of qualitative findings to inform optimization of interventions as they are being implemented; moreover, these designs value measurement of heterogeneous “implementation” and “contexts,” aiming to elucidate rather than obscure these factors. The integration of qualitative research within trials can help not only to understand the why behind success or failure of interventions in different contexts, but also inform the adaptation of interventions that can facilitate their success, and lead to new alternative strategies and to policy changes that may be vital for achieving public health goals.With increased attention to translating biomedical research advances into clinical practice, policy and population‐level impact , there is a demand for incorporation of qualitative methods in pragmatic clinical and community‐level trials and implementation science studies We advocate specifically for the pairing of qualitative with clinical and survey research methods in trials and implementation studies, and for the publication of qualitative research from trials with clinical outcome data, either fully integrated into the “main” trial papers or published concurrently in the same journal issue. The option of two complementary papers  is probably the most viable, given word limits may preclude adequate coverage of all results in one paper.The findings from qualitative research within trials offer valuable information on the ways people behave and communicate, and the complex social worlds with which research is conducted – information that is essential to the understanding of trials’ results The authors have no competing interests to declare.The authors contributed equally to the conceptualization, writing and editing of this article.


Health research is evolving to include patient stakeholders  as active members of research teams. Frameworks describing the conceptual foundations underlying this engagement and strategies detailing best practice activities to facilitate engagement have been published to guide these efforts.The aims of this narrative review are to identify, quantify and summarize (a) the conceptual foundational principles of patient stakeholder engagement in research and (b) best practice activities to support these efforts.We accessed a publicly available repository of systematically identified literature related to patient engagement in research. Two reviewers independently screened articles to identify relevant articles and abstracted data.We identified 990 potentially relevant articles of which 935 (94.4%) were excluded and 55 (5.6%) relevant. The most commonly reported foundational principles were “respect”  and “equitable power between all team members” . Creating “trust between patient stakeholders and researchers” was described in 17 (31%) articles. Twenty‐seven (49%) articles emphasized the importance of providing training and education for both patient stakeholder and researchers. Providing financial compensation for patient stakeholders’ time and expertise was noted in 19 (35%) articles. Twenty articles (36%) emphasized regular, bidirectional dialogue between patient partners and researchers as important for successful engagement.Engaging patient stakeholders in research as partners presents an opportunity to design, implement and disseminate patient‐centred research. This review creates an overarching foundational framework for authentic and sustainable partnerships between patient stakeholders and researchers. We used the Preferred Reporting Items for Systematic Reviews and Meta Analyses (PRISMA) to guide the conduct and reporting of this review.2.1We first accessed a publicly available repository of systematically identified articles created by the Patient Centered Outcomes Research Institute (PCORI) and Academy Health.2.2We selected articles for review if they detailed either (a) a framework describing the conceptual foundations of patient stakeholder engagement in research or (b) guidelines describing best practices for supporting engaging patient stakeholders in research. Articles were excluded if they (a) discussed projects that utilized patient stakeholders as partners in research but did not detail how this was accomplished, (b) discussed general consumer involvement in research or public health but did not specifically provide any guidance or any mechanisms or activities to support involvement, (c) only described patient stakeholder involvement in research prioritization or selection of research topics or outcomes, and (d) used community‐based participatory research methods but did not explicitly describe the conceptual principles or best practices for engaging stakeholders in research in this context.We screened all titles and abstracts of all articles contained within the literature repository and identified in the grey literature. The full texts of potentially relevant articles or reports were then obtained. Two reviewers then independently extracted data on a standard data collection form Appendix  to organ3The article repository contained 976 potentially relevant articles and our search of the grey literature identified 14 additional articles (N = 990), of which 935 (94.4%) were excluded . These councils support patient stakeholders to meet regularly at a health‐care institution and share their experiences of care or collective perspectives on a specific topic.The summary framework derived from our review also describes a range of best practice activities, or actions, that build on the foundational elements of patient stakeholder engagement in research. The most frequently noted activity to support engagement was training for both patient stakeholders and researchers. While training is not intended to create researchers of patient stakeholders, which could mean they lose their unique perspective, orientation to research processes, to research topics and to working within a research team has been shown to enhance their participation and engagement. Equally as necessary is researcher training in how to authentically and effectively engage patient stakeholders—a skill deficiency cited by researchers.Compensation for patient stakeholders for their expertise and time, and reimbursement for out‐of‐pocket expenses was cited as good practice in articles identified in this review. While these practices are encouraged by funding agencies and are dependent on the level of engagement,Another activity noted in our review was to regularly evaluate the engagement process during the life cycle of a research project. This allows for engagement efforts to be recalibrated based on feedback and ensures patient stakeholders remain active and informed partners. While there have been significant efforts to describe the benefits, or value, of engaging patient stakeholders in research such as improved research quality, processes, recruitment and retention rates,Our review has a number of limitations including the potential for selection bias given that only English language bibliographic databases were searched, meaning some relevant articles would have been missed. Other English language articles may also have not been included in this review due to the poorly standardized taxonomy and nomenclature related to patient stakeholder engagement in research. Given this limitation, we strongly recommend that new Medical Subject Headings (MeSH) terms are submitted to the National Library that would capture patient engagement in the peer‐reviewed literature. Terms such as “patient engagement,” “patient involvement,” or “patient‐centered outcomes research,” or “patient partner,” and other relevant terms would be extremely helpful for identifying such literature. Further, we acknowledge that the search terms used to identify articles in this review are US centric and do not include terminology used in some international settings. However, given the broad search terms used to create the repository accessed for this review, the number of articles missed would likely be small. It is also essential to apply some caution to our results in that just because a foundational principle, or best practice, is not frequency reported this does not imply that it is less important or applicable. The science of patient stakeholder engagement in research is new and evolving meaning we do not know yet which principles or practices are most important.In summary, this narrative review has summarized the foundational principles of engagement between researchers and patient stakeholders and describes best practice activities to support this process. This information can be used to facilitate patient‐centred research, thereby ensuring the patient stakeholder voice and perspective remains central.The authors have no conflicts of interest to declare. Click here for additional data file. Click here for additional data file. Click here for additional data file.


Deep learning methods for the prediction of molecular excitation spectra are presented. For the example of the electronic density of states of 132k organic molecules, three different neural network architectures: multilayer perceptron (MLP), convolutional neural network (CNN), and deep tensor neural network (DTNN) are trained and assessed. The inputs for the neural networks are the coordinates and charges of the constituent atoms of each molecule. Already, the MLP is able to learn spectra, but the root mean square error (RMSE) is still as high as 0.3 eV. The learning quality improves significantly for the CNN (RMSE = 0.23 eV) and reaches its best performance for the DTNN (RMSE = 0.19 eV). Both CNN and DTNN capture even small nuances in the spectral shape. In a showcase application of this method, the structures of 10k previously unseen organic molecules are scanned and instant spectra predictions are obtained to identify molecules for potential applications. Spectroscopic materials properties must be known to design novel applications. For example, bandgaps are critical for solar cells, optical spectra for organic electronics, vibrational spectra to discover new thermoelectrics for waste heat recovery, X‐ray spectra for better medical diagnostic materials, or conductivity spectra for light‐weight batteries with high storage capacity.Different spectroscopic techniques reveal different properties, and every material is characterized by a variety of spectra. Current spectroscopic methods, such as absorption, emission, scanning tunneling, Raman or electron‐paramagnetic resonance, are well established. However, experiments are often time‐consuming and sometimes require large, multi‐million‐Euro facilities, such as synchrotrons. Complementary theoretical spectroscopy methods based on quantum‐mechanical first principles are similarly time consuming and require large‐scale, high‐performance computing facilities.Spectroscopy has seen many technical advances in individual spectroscopic methods, but no recent paradigm shift that would overcome the time‐cost conundrum. Here we show that artificial intelligence (AI) has the potential to trigger such a conceptual breakthrough toward data driven spectroscopy. We present the first step toward building an AI‐spectroscopist to harvest the wealth of already available spectroscopic data. The AI‐spectroscopist is based on custom made deep neural networks that learn spectra of organic molecules. Our neural networks predict the peak positions of molecular ionization spectra with an average error as low as 0.19 eV and the spectral weight to within 3%. This accuracy is already sufficient for our example application on photoemission spectra, which typically have an experimental resolution of several tenth of eV and theoretical error bars of 0.1–0.3 eV. Once trained, the AI‐spectroscopist can make predictions of spectra instantly and at no further cost to the end‐user.In this new paradigm, deep learning spectroscopy would complement conventional theoretical and experimental spectroscopy to greatly accelerate the spectroscopic analysis of materials, make predictions for novel and hitherto uncharacterized materials, and discover entirely new molecules or materials. We demonstrate this by using our AI‐spectroscopist to make predictions for a new dataset of organic molecules that was not used in training the deep neural networks. At no further computational cost, we make spectra predictions for the 10 000 molecules of the diastereomers dataset of Ramakrishnan et al.2AI methods, which encompass machine learning methods, are gaining traction in the natural sciences and in materials science.5–106 organic molecules, sizes increasingly available from modern database resources.In this study we compare the performance of three deep neural network architectures to evaluate the effect of model choice on the learning quality. We perform both training and testing on consistently computed  spectral data to exclusively quantify AI performance and eliminate other discrepancies, unlike an early study3In this work we approach molecules from an atomistic perspective, in which the atomic structure, that is coordinates of all the constituent atoms, is known precisely. This atomistic representation is natural to theoretical spectroscopy, as the spectral properties can then directly be calculated from approximations to the Hamiltonian of each molecule. In general, representation (or feature engineering) is an important aspect in machine learning. How to best present molecules and materials to an AI for optimal learning, prediction and inference has been a pressing question in chemistry and materials science for the last few years,Cij=ZiZj‖Ri−Rj‖−1, where Zi is the atomic number (nuclear charge) of atom i and Ri its position. The diagonal elements i = j have been fit to the total energies of atoms (0.5Zi2.4).FigureN‐methyl‐N‐formamide molecule. The Coulomb matrix is appealing due to its simplicity and efficiency. We will show here that it provides sufficient input for learning molecular spectra, if the neural network architecture is sophisticated enough.To represent the molecules to two of our three neural networks, we use the Coulomb matrix s 0.5Zi2..4 A typi4FigureIn this work, we chose neural networks due to their ability to learn complex mappings between input and target spaces (such as the Hamiltonian in quantum mechanics). Neural network models have surged in popularity recently, since they can express complex function mappings using inputs with very little or no feature engineering. Here we explored three neural network architectures illustrated in The MLP was chosen because of its architectural simplicity and also because a similar network was used earlierMaking another conceptual leap, we adopt the DTNN architecture5R2 were evaluated for the test set of molecules that the neural networks had not “seen” before. We take R2 as a quality measure for the learning success of our neural networks, whereas the RMSE quantifies the predictive accuracy for excitation energies. We refer the reader to the Supporting Information for details on the DNN architecture, hyperparameters, and training algorithm.The hyperparameters of each neural network  are determined with Bayesian optimization for each dataset. This is a critical step, since it has been shown6We use the QM7b7H10O2 isomers from the 134k dataset.For the application test, we use the 10k diastereomers dataset of Ramakrishnan et al.7FigureR2 values for the three different neural network architectures and the 6k and 132k datasets. We observe that only the DTNN 132k performs uniformly well across all 16 states. For the other networks the predictions of the deeper levels have the highest R2 values and are therefore learned “best” regardless of the model and the dataset size. However, the predictive accuracy is still relatively low (high RMSE) for some networks. This seemingly contradictory behavior likely arises because lower energy levels (from 11 to 15) for smaller molecules correspond to electronic core states, which have a significantly higher absolute energy than valence states. While the cores states are easily learned, predictions with a low relative error at this end of the spectrum can result in absolute errors of several tens of eV and give rise to high RMSE values.First we discuss the simultaneous prediction of the 16 molecular eigenvalues in our datasets. R2 value decreases) the closer the state is to the highest occupied molecular orbital (state number 0) and then rises again from state 3 to 0. Interestingly, the RMSE exhibits an inverse correlation. It first improves and then rises again for the last 4 states. The best predictions are given by the DTNN 132k and have an RMSE of only 0.16 eV with an average RMSE of 0.186 eV  and the predictive accuracy increase (RMSE reduces). The DTNN is our most sophisticated network and trained for the larger 132k dataset it then exhibits the most uniform performance with high accuracy for every state.Figure Figure Regarding spectra predictions, even the worst predictions of the DTNN might still look good to a spectroscopist, as the overall shape and peak positions of the spectrum are captured well. The main differences between the DTNN prediction and the reference spectrum are slight peak shifts and an overall spectral weight reduction. Slight peak shifts lead to a large intensity difference, but only small difference in the peak energies, which is the more important observable in spectroscopy.Our current spectral metric is very sensitive to peak positions. This is in principle desirable, since it forces the neural networks to prioritize on peak positions (and thus excitation energies). However, for many complex spectra, peaks due to individual excitations merge into a broader spectral structure. In such cases, it might be more suitable to adjust future metrics to better capture spectral shapes. In X‐ray diffraction (XRD) and low energy electron diffraction (LEED) studies the same problem arises, as theoretical spectra computed for model structures are compared to experimental spectra to find the best structural model. We will investigate the cosine or Pearson correlation coefficient and the Jensen–Shannon divergence measureGW or co‐kriging techniquesIn this work we used the Kohn–Sham spectrum for simplicity. While Kohn–Sham eigenvalues do not correctly represent molecular excitation energies, they provide us with a convenient and large approximate dataset for developing and testing the AI‐spectroscopist. In the future, we will extend our study to photoemission spectra computed with the GW method.Our deep learning schemes are fully transferable to better accuracy computational datasets, but also to experimental spectra. We chose a relatively large broadening of computed electronic levels to mimic the resolution of common photoemission experiments, which produce broad and often fairly featureless molecular spectra. Future studies will address the effect of this broadening on the learning success, but our current findings indicate good quality predictions on broad spectral curves.10In summary, we demonstrated that deep neural networks can learn spectra to 97% accuracy and peak positions to within 0.19 eV. Our neural networks infer the spectra directly from the molecular structure and do not require auxiliary input. We also show that, contrary to popular belief, neural networks can indeed work well will smaller datasets, if the network architecture is sufficiently sophisticated. The predictions made by the neural networks are fast (a few milliseconds for a single molecule), which facilitates applications to large databases and high throughput screening. Our proof‐of‐principle work can now be extended to build more versatile AI‐spectroscopists.The authors declare no conflict of interest.SupplementaryClick here for additional data file.


This review discusses the technological basis of and recent developments in massively parallel genetics, along with the trends it is uncovering in the genotype–phenotype relationship , their possible mechanistic bases and future directions for advancing towards the goal of predictive genetics.With the molecular revolution in Biology, a mechanistic understanding of the genotype–phenotype relationship became possible. Recently, advances in DNA synthesis and sequencing have enabled the development of deep mutational scanning assays, capable of scoring comprehensive libraries of genotypes for fitness and a variety of phenotypes in massively parallel fashion. The resulting empirical genotype–fitness maps pave the way to predictive models, potentially accelerating our ability to anticipate the behaviour of pathogen and cancerous cell populations from sequencing data. Besides from cellular fitness, phenotypes of direct application in industry ( Direct genotype–phenotype mapping has recently become possible on a large scale thanks primarily to the creative use of next‐generation sequencing (NGS) technologies to develop massively parallel assays capable of measuring a particular phenotype for each genetic variant in a large mixed library.e.g. rational design of high‐performance enzymes) and precision medicine  and the interaction between mutations (epistasis).22.1e.g.>5‐mer), a large number (>103) of sequence variants must be characterized; (c) currently, the only economical way of generating large numbers of sequence variants is in bulk; and (d) to characterize a phenotype of a large number of pooled sequence variants, not only do we need a high‐throughput phenotyping technology, but also a high‐throughput way to trace phenotypes back to their sequence.Empirical snapshots of the local, or occasionally global, genotype–phenotype map for short sequences have recently become possible through combinations of high‐throughput technologies. The technical challenge may be broken down as follows: (a) the number of possible nucleic acid or protein sequence variants grows exponentially with sequence length; (b) to draw statistical conclusions about the genotype–phenotype relationship for even very short sequences  the native protein fold was highly tolerant to mutations in the targeted solvent‐exposed positions (with the exceptions of cysteine and proline), with all positions showing a similar level of robustness; (b) hydrophobic residues were generally more stabilizing than hydrophilic ones, a very surprising result for a solvent‐exposed region; (c) at the majority of positions, mutations existed that resulted in both greater stability and stronger receptor binding than the wild type; (d) binding affinity was less robust to mutation than stability, with robustness being position‐specific; (e) binding affinity robustness did not relate strongly to sequence conservation across species; and (f) physicochemical similarity of residue side chains did not correlate strongly with phenotypic effects  bins which are then each subjected to deep‐sequencing  experiment, a 9‐a.a. region of S. cerevisiae Hsp90  was comprehensively mutagenized to create a library of all possible single point mutants. The fitness impact of all mutations was then directly measured in bulk, by serially propagating the library in conditions where expression of the native hsp90 copy was repressed, and using deep‐sequencing to sample mutant frequencies at several time points over a few days. Because the wild‐type sequence was included in the library and the wild‐type generation time was known, the competitive fitness of each mutant could be estimated relative to the wild type as a selection coefficient, by taking the change in the ratio of mutant to wild‐type reads as a function of wild‐type generation time.One particular phenotype has proven generally amenable to easy and affordable experimental genotype–phenotype coupling, however. It allows precise, quantitative estimates and is of direct evolutionary significance: competitive cellular fitness ‐binding protein, antibiotic resistance enzymes, a small nucleolar RNA, tRNAs, metabolic enzymes and regulatory regions , rather than global stability.Whatever the mechanism(s) responsible for changes in protein activity, however, the precise form of the distribution of mutational effects must also depend on the quantitative relationship between activity and the measured phenotype, and on the activity of the wild type. For example, three orthologous wild‐type indole‐3‐glycerol phosphate synthases were found to have their neutral mode shifted towards beneficial effects, showing they were sub‐optimal for fitness under the chosen experimental conditions , but more complex relationships may well be common  so far examined appears to follow similar rules to proteins: deleterious and nearly neutral modes and a miniscule proportion of beneficial mutations again probably shaped in part by both a thermodynamic stability threshold and common saturating concave activity–fitness functions  , but a slower rate of adaptation resulting from beneficial combinations (positive selection), than would be expected in the absence of epistasis.In addition to prevailing negative epistasis, a trend of “increasing losses” is sometimes detected in proteins (at least for mildly deleterious mutations), further supporting the idea that there exists some source of concavity in the phenotypic landscape . This is explained by the fact that repressor binding sites (operators) and RNA polymerase binding sites overlap in this promoter, and so, promoter mutations will tend to effect binding to both of these—one of which decreases transcription, the other of which increases transcription , often differentially, and the measured phenotype  is then some function of these multiple input phenotypes. In reality, as for proteins and noncoding RNAs, many more molecular phenotypes than those typically considered are potentially impacted by an individual mutation, such as DNA structure . For many systems, the problem is that the length of DNA fragments required to carry two different genes exceeds those amenable to the highest‐throughput sequencing technologies (max. ~1kb with Illumina). Presumably largely for this reason, very few deep mutational scanning studies have assayed more than one gene or even regulatory sequence simultaneously, but unique DNA barcodes that allow a long sequence to be broken up for sequencing and then reassembled in silico provide one workaround  provides a rigorous framework to explore how pathway phenotypes such as flux and metabolite concentrations depend on the activity of several enzymes simultaneously, and thus enables predictions of interenzyme epistasis , sequencing costs and associating mutations at distant loci. The first is improving with advances in genome engineering, particularly from CRISPR‐Cas9‐based methods  often found in nature  of different types of large perturbations in single or multiple (maximum of 3) genes  .An early finding of the genome‐wide perturbation studies was that, in most organisms and in permissive conditions, the majority of genes are inessential . One difference is that, as opposed to the sigmoidal and simple concave functions, the nonmonotonicity of FGM also predicts sign epistasis , originally proposed simply as a convenient metaphor for phenotypic adaptation Fisher, , can cor4.3The nature of epistasis appears to be less general across systems. Genome‐wide deletion analyses (like the single gene and regulatory sequence studies) tend to find a predominance of negative interactions, though still alongside a substantial proportion of positive ones  which have some specific role in the system of study Dean, , precise6e.g. depth per replicate, number of replicates, number of time points/selection cycles), and computational analysis has revealed some general guidelines for maximizing experimental power  , which could enable a direct and complete mechanistic description of the translation of genotype into high‐level traits  can reveal surprisingly diverse types epistasis while allowing mechanistic interpretations of their origin. One promise is to integrate these local views to explain genome‐wide epistasis from biological mechanisms. Smaller‐scale studies may also allow the identification of generic principles which could be extrapolated to larger systems, for example the categories of phenotype to fitness relationships which generate certain types of epistasis or not. From a large‐scale evolutionary perspective, it is not currently clear whether upscaling leads to an increase in the complexity of interactions, or could rather lead to a form of averaging, as suggested theoretically Martin, .pairs of genes across the genome and measuring the fitness effects. Although clearly artificial, and in some cases breaking regulatory links that are ensured by native promoters, such an experiment could provide quantitative two‐gene expression–fitness landscapes for many pairs of genes, which should be an extremely important component of the genotype–fitness relationship, and which for now we are almost completely blind to (see Martin, Finally, the systematic analysis of the effects of genome‐wide combinations of point mutations still appears far out of reach, but a feasible next step might be introducing synthetic promoter libraries like those used in Keren et al.  in frontWith constantly improving technologies for reading and writing genotypes on a massive scale, and the application of experimental creativity, our mechanistic understanding of the genotype–phenotype relationship across different scales can only continue to flourish.