Robot‐assisted surgery (RAS) has potential panspecialty surgical benefits. High‐quality evidence for widespread implementation is lacking. This systematic review aimed to assess the RAS evidence base for the quality of randomized evidence on safety and effectiveness, specialty ‘clustering’, and outcomes for RAS research.A systematic review was undertaken according to PRISMA guidelines. All pathologies and procedures utilizing RAS were included. Studies were limited to RCTs, the English language and publication within the last decade. The main outcomes selected for the review design were safety and efficacy, and study purpose. Secondary outcomes were study characteristics, funding and governance.Searches identified 7142 titles, from which 183 RCTs were identified for data extraction. The commonest specialty was urology (35·0 per cent). There were just 76 unique study populations, indicating significant overlap of publications; 103 principal studies were assessed further. Only 64·1 per cent of studies reported a primary outcome measure, with 29·1 per cent matching their registration/protocol. Safety was assessed in 68·9 per cent of trials; operative complications were the commonest measure. Forty‐eight per cent of trials reported no significant difference in safety between RAS and comparator, and 11 per cent reported RAS to be superior. Efficacy or effectiveness was assessed in 80·6 per cent of trials; 43 per cent of trials showed no difference between RAS and comparator, and 24 per cent reported that RAS was superior. Funding was declared in 47·6 per cent of trials.The evidence base for RAS is of limited quality and variable transparency in reporting. No patterns of harm to patients were identified. RAS has potential to be beneficial, but requires continued high‐quality evaluation. Robot‐assisted surgery is expanding rapidly, but the evidence base is poor. This article demonstrates the heavy weighting to research in certain specialties, no clear safety or efficacy benefit, inconsistent choice of outcome measures, and poor research governance. These factors significantly increase the risk associated with adopting these potentially revolutionary technologies.Call for better quality evidence. Robot‐assisted surgery (RAS) has undergone rapid development in the past 15 years. It has been approved by regulators worldwide across most surgical specialties for a wide range of surgical indications. For some procedures RAS has become standard of care, for example in prostatectomyCurrently RAS consists of a ‘master–slave’ model in which an ‘active’ system reproduces the surgeon's actions by performing discrete tasks under the control of the surgeonDespite early and anecdotal evidence of potential benefit, the innovation is yet to be fully explored and documented. It is important that safety is maintained during early implementation, and that effectiveness compared with open and traditional MIS techniques is demonstrated to justify investment in platforms and training. Robotic surgical platforms are costly in terms of capital expenditure, infrastructure adaptation, and ongoing use of consumablesRandomized trials are the current foundation of this evidence base. RCTs are an important component of evaluation of innovation as they have the lowest risk of bias. This maps to the IDEAL  model of surgical evaluation in which evidence is collected systematically and documented in an appropriate sequenceThis review aimed to understand the general state of current safety and efficacy evidence across the RAS field. This will directly guide research questions and prioritizationA review of the literature was conducted according to PRISMA guidelinesThis systematic review was registered with PROSPERO (registration number CRD42019046621). There have been no changes to the protocol registered with PROSPERO. The protocol has not been published separately.A search strategy was devised with the assistance of an expert librarian using a PICO framework. Studies of patients of any age with pathology that could be addressed by a RAS procedure were eligible. Studies comparing RAS with open, endoscopic or an alternative RAS procedure were included, as were comparators between RAS with an alternative medical or conservative treatment, or no treatment at all. Outcomes were related to procedural safety measures  and efficacy/effectiveness , length of stay, duration of surgery). Only trials published in the English language were included.S1 (supporting information).A comprehensive search of the Ovid MEDLINE, Ovid Embase, Cochrane CENTRAL, Scopus and Web of Science Core Collection was conducted from 1 January 2008 to 23 August 2019. The search strategy was designed to maximize the numbers of references retrieved about RCTs involving RAS. These were then screened for eligibility against the protocol inclusion criteria. The search strategies used free‐text words and combinations of the relevant thesaurus terms. Further relevant studies were identified from the reference and citation lists of all included articles, from reference lists of systematic reviews, from published protocols for planned or ongoing trials, and from online registries for RCTs. The full search strategies for each database, using equivalent search terms for the database subheading mappings, are included in Table Studies identified by the search strategy were imported into Covidence, the Cochrane Collaboration's online systematic review management platform, which performed automatic deduplication. Each of the remaining titles and abstracts was screened independently and in duplicate by two of five reviewers familiar with the study aims and protocol. Screened studies underwent full‐text review in duplicate, and were selected for inclusion in this systematic review according to the inclusion and exclusion criteria Table 1.From the articles selected for inclusion, data were extracted using an online, standardized, collaborative data extraction platform using Google Sheets™ . Data extraction was piloted on a subset of the search results to optimize the data extraction process.Table The main areas of interest for this review (primary outcome measures in terms of PRISMA design) were the stated purpose of each study and reported safety and efficacy/effectiveness outcomes, including description of the outcome measures used. Secondary areas of interest (secondary PRISMA outcome measures) included study quality characteristics, design, funding and research governance features. PRISMA outcome definitions and how each was coded can be found in Table Risk of bias was not assessed in studies using a formal tool as no meta‐analysis was planned. However, important research governance and study design features were recorded during data extraction Table 2. A higTable In response to the issue of multiple publications from the same study populations, a further analysis was conducted to account for the repeat reporting. Studies were divided according to the ‘nature of the report’ Table 2. ‘PrelFig. The search of Ovid MEDLINE, Ovid Embase, Cochrane CENTRAL, Scopus and the Web of Science Core Collection identified a total of 7142 titles. After deduplication, 7116 unique titles and abstracts were screened by two reviewers independently: 6703 were excluded by both reviewers or after conflicts had been resolved by the lead author. Of 413 titles that were put forward for full‐text review, 183 RCTs were identified for data extraction. Study selection is summarised in Table Table Of the 183 trials identified, the commonest specialty group was urology , followed by obstetrics and gynaecology  and general surgery . No RCTs were identified for breast, plastic, neurosurgery, oral and maxillofacial, otolaryngology or vascular surgery Table 3. The cFig. Review of the study identifiers indicated that, of the 183 trials, patients were drawn from only 76 unique study populations. Two separate RAS trials in urological surgery generated up to 12 publications each from single populations Fig. 2.Table Using only the most recent time point of ‘long‐term follow‐up’ of primary outcomes for a given study population yielded 103 principal studiesTable From these principal trials, the da Vinci® system  was the commonest robotic system where this was specified in the reports  Table 5, folloTables Table A primary outcome was declared formally in nearly two‐thirds of studies , but only 29·1 per cent (30 of 103) matched a reported primary outcome listed in the protocol or a clinical trial registry. Some 43 different primary or main outcome measures were reported; these were highly heterogeneous and often specific to procedures or pathologies. The commonest primary or main reported outcome was duration of surgery , with the majority  being unique to a given study Tables 7. The iFig. Fig. Safety of robotic surgery was assessed in 68·9 per cent of the studies (71 of 103), although not necessarily as the primary or main outcome of interest. Where safety was assessed, the commonest measures were complications , conversion to open surgery/alteration of surgical plan , and the need for secondary or further intervention . Blood loss was reported in 69 per cent of studies (49 of 71), but only 17 per cent (12 of 71) reported transfusion rate, and none reported the rate of transfusion‐related complications. The majority of these studies focused on the short term, with ‘perioperative’ being the commonest follow‐up period reported in studies, without further qualification . Safety follow‐up of 1 year or more was included in only 11 per cent of studies (8 of 71) Fig. 3. StudyFig. Fig. Efficacy or effectiveness of robotic surgery was assessed in 80·6 per cent of the studies (83 of 103). Many studies reported multiple measures of effectiveness; these were often specialty‐ or procedure‐specific and not easily generalizable across procedure types. The commonest effectiveness assessments used a disease‐specific  or general health  PROM, lymph node retrieval  and postoperative pain . The follow‐up period tended to be longer for efficacy/effectiveness assessments than for safety assessments, with median of 12 (range 0–168) months where specified Fig. 5. StudyMore than half of the studies  reported a registration or record number with a recognized trial registry, but only around one‐quarter were registered prospectively . In one publication the reported record number did not match the study performed. Funding declarations were present in 47·6 per cent (49 of 103) of published reports (or the online registration where available) and 54·4 per cent (56 of 103) included a conflict‐of‐interest statement.This review identified a significant degree of duplicate publication from study populations and several publications from different stages of the same trial. Only 76 unique study populations were identified. Over one‐third of trials were not registered, and less than one‐third were registered prospectively. Many reported a different primary outcome to that in the trial protocol, had no declaration of funding, and no formal power calculation. This raises concerns about risk of bias, quality and transparency of research reporting across current randomized research in RAS. Urology and gynaecology were the commonest procedural types evaluated, and Intuitive Surgical's da Vinci® RAS platform was the commonest platform evaluated formally in included studies.Outcomes evaluated in trials of RAS were numerous and varied. As with many clinical innovations, the best outcome measures for specific and extended applications are not always clear at the outset and are likely to evolve along with understanding of the platform. Often it appeared outcomes had been chosen for RAS studies because they were easy to measure rather than pointing to fundamental step‐changes in clinical care, or incremental benefit achieved in targeted and clinically meaningful variablesAssessment of safety was commonly performed, highlighting that this was a key focus of RAS evaluation, with 68·9 per cent of RCTs addressing this area. The use of complications (99 per cent of those studies), conversion and secondary surgery may suggest a thinking that RAS can reduce any complication rate, or at least to a level equal to that of the current standard, if other benefits exist for RAS. Most safety outcomes were collected in the perioperative period, representing immediate or early sequelae of the surgical procedure. Blood loss requiring transfusion was measured in only 12 studies, and no studies assessed transfusion‐related complications. This is surprising as blood loss and transfusion is an immediate, easy to measure and consequential outcome. Major complications and mortality data were often proposed as markers of safety, but as these are rare and binary variables they are insensitive to detect differences between small groups of patients as seen in the included studies (median 78 patients).The high rates of reporting effectiveness/efficacy outcomes (80·6 per cent of studies) highlighted the importance of evidence for comparative effectiveness studies in RAS for patients, surgeons, hospitals and industry. There was a far greater heterogeneity of outcomes reported for efficacy assessment than for safety, which made overall assessment of efficacy more complex. There may be a case for a core outcome set for robotic surgery in the future. Heterogeneity may also be a manifestation of the many specific settings and clinical needs of the patient groups. The use of pathology‐specific PROMs indicated that authors of the individual studies aimed to use validated measures that were important to patients, but no studies reported differences in terms of minimally clinically important differences or responsivenessOther metrics seemed to be process or economically driven, such as duration of surgery and time to patient discharge. Duration of surgery offers little for safety or effectiveness/efficacy and can provide a perverse incentive. Half of the included studies looked for improvements in time to discharge, but this can be interpreted usefully only in the context of readmission rates, or whether the time saved improved theatre capacity to allow more procedures to be performed.Given the limited intention to establish whether RAS is intrinsically safe or unsafe, effective or ineffective, it was still interesting to observe no overriding pattern around the safety and efficacy of RAS compared with other approaches. This review has highlighted that the evidence base remains small with poorly designed studies, including the striking overlap of sample populations used for different reported studies. Given this, any strong statements about safety and efficacy are largely unsupported. However, it should be noted, and is somewhat comforting, that the review did not uncover any clear evidence of surgical harms associated with RAS; this must be viewed in the context that the majority of these studies were not designed as non‐inferiority or equivalence trials, and heterogeneous outcomes prevent effective meta‐analysis.Formal risk‐of‐bias assessment was not performed in this scoping review. No attempt was made to carry out meta‐analysis of safety or effectiveness measures. Instead, the review used surrogates for research quality and transparency, such as compliance with reporting guidelinesThis review addressed only RCTs to ensure high‐quality evidence and generate an achievable number of studies for close assessment. It was also limited to the last decade in order to capture contemporary evidence . Although RCTs have a high level of internal reliability and remain the standard for healthcare evaluation, they are difficult and costly to design, and cannot offer a sufficiently rapid evaluation, especially for a fast‐changing technologyThe identification of risks and benefits associated with new surgical technologies from high‐quality evidence is critical. Research quality and the overall evidence base for RAS remains variable, with risk of bias. Outcome measures were many and varied, with scope for improved standardization. Reassuringly, no obvious patterns of threat or harm were identified; studies showed no difference between RAS and open or non‐robotic MIS in most cases, and significant benefit in some. The potential for RAS to be an integral component of the future of surgery remains high, but continued systematic and high‐quality evaluation is required.Appendix S1 Search strategyTable S1 Principal studies used for analysisClick here for additional data file.


As a result, discussion of controversies or changes in practice within radiation oncology must involve input from all three disciplines. For this reason, significant effort has been expended recently to foster collaborative multidisciplinary research in radiation oncology, with substantial demonstrated benefit.2α/β value indicates a steeper relationship. Generally late‐reacting normal tissues exhibit lower α/β and early‐reacting normal tissues exhibit higher α/β. Malignancies can have lower or higher α/β depending on the tumor type. In some malignancies, notably human prostate, clinical data indeed indicate α/β as low as 1.5 and thus in prostate cancers, and likewise in early‐stage breast cancers, hypofractionation, arbitrarily defined as a dose per fraction> 2.2 Gy, has become standard of care. In early‐stage non‐small cell lung cancers a higher α/β is seen, similar to early‐reacting normal tissue, but these isolated malignancies can still be more effectively controlled with radical hypofractionation which suggests the story is more complex than a simple LQ picture can paint. So are we moving, and should we be moving, even if slowly but surely, toward giving all patients receiving radiation therapy as hypofractionation? Let us debate!Better Physics, just within this 21st century, now enables us to deliver radiation to a target volume with accuracy better than 1 mm. Given this accuracy, why fractionate at all? If we can put dose only on the cancer, and extremely little on critical normal tissue, then surely just give a high single dose to that cancer, and job done. Local tumor control is 100% with minimal toxicity. If only. Two linked issues keep Biology (radiobiology) in the clinical game. First, our ability to identify, localize, and immobilize anatomy and pathology does not yet correspond with this submillimeter accuracy of radiotherapy delivery. Second, even if that imaging resolution is reached it could still not detect occult disease. Consequently, unless the cancer is truly isolated, which it sometimes may be, for example, in organ‐confined early‐stage prostate cancer, it is always necessary to “degrade” the treatment plan by defining a CTV and PTV into which the radiation delivery is expanded. This inevitably imposes a risk of normal‐tissue radiotoxicity, therefore we must use fractionation to minimize that risk. Traditionally, that fractionation has been carried out with doses close to 2 Gy per fraction. In fractionation, the Linear‐Quadratic (LQ) model describes the relationship between total dose and dose per fraction, for isoeffect. A lower Arguing for the proposition will be Drs. Michael Green, Samantha Van Nest, and Emilie Soisson. Dr. Green is an Assistant Professor at the University of Michigan in the Department of Radiation Oncology. His group utilizes expertise in quantitative immunophenotyping, peripheral tolerance mechanisms, and tumor cell death to define and harness the determinants of inflammation, which shape antitumoral immunity and influence radiotherapy and immunotherapy efficacy. Dr. Van Nest is a Postdoctoral Associate in the Department of Radiation Oncology at Weill Cornell Medicine in New York. Dr. Van Nest's research focuses on developing techniques for the personalization of radiation therapy including Raman spectroscopy and omics‐based signatures. She is investigating mechanisms of radiation‐induced anticancer immunity with particular focus on patient‐based platforms for optimizing immune activation. Dr Soisson is a medical physicist at the University of Vermont Medical Center. She holds faculty appointments at the University of Vermont and McGill University. She earned a PhD in Medical Physics at the University of Wisconsin where she was heavily involved in the clinical implementation of TomoTherapy.Arguing against the proposition will be Drs. Kathryn Huber, Yixiang Liao, and William McBride. Dr. Huber is a Radiation Oncologist at Tufts Medical Center and Assistant Professor at Tufts University School of Medicine, Boston, MA. She specializes in the treatment of thoracic, breast, and head and neck cancers and is the Director of Radiobiology for the residency training program at Tufts. Dr. Liao is a faculty medical physicist at the Rush University Medical Center, Chicago, IL with research interests in brachytherapy, IGRT, SBRT, and treatment planning. Her publications cover various topics including hypofractionation in prostate cancer treatment, and normal tissue tolerance in treatments delivering high dose per fraction such as high‐dose rate (HDR) brachytherapy and intraoperative radiation. She also currently serves as the associate director of the medical physics residency program at Rush. Dr. Liao was among the students of the first IBPRO33.AHypofractionated radiotherapy is characterized by the delivery of greater than 2.2 gray (Gy) per fraction and a reduced number of fractions as compared to conventional fractionation. At the turn of the century, now classic radiobiologic experiments showed that fractionated radiotherapy increased tumor control while diminishing acute toxicity. These empirical observations led to the development of one of our fields' most dear beliefs: that fractionated radiotherapy delivered in 1.8 to 2.0 Gy per day is the most efficacious and safest way of delivering radiotherapy.Multiple randomized trials have suggested that hypofractionated radiotherapy provides superior outcomes in both the definitive and palliative setting. The CHISEL trial demonstrated that ultrahypofractionated radiotherapy was superior to conventional fractionation for Stage I NSCLC.Hypofractionation has only been made possible by improvements in tumor localization through advances in image‐guided radiation therapy (IGRT). Traditional stereotactic localization, which relied on external targeting frames and specialized equipment, has been replaced by volumetric image guidance  and stereoscopic imaging which have become accessories on standard accelerators and are now generally available in all clinics. In addition, a wide variety of motion management strategies are routinely employed to quantify, measure, and track intrafraction tumor motion. Daily 3D alignment and motion management have provided an opportunity to explore dose escalation through reduced tumor margins and moderate hypofractionation in sites where tumor dose was previously limited by normal tissue tolerances. Intriguingly, margins have not been shrinking as much as they could be based on localization ability alone. Numerous studies have shown improved geometric accuracy is achievable with IGRT which should go hand in hand with reduced margins, but surveys of practice patterns showed no relationship between the frequency of image guidance and PTV margins.α/β) value in tumor is higher than that of the surrounding normal tissue, but re‐evaluations have found some tumors actually have an α/β value lower than normal tumors.www.aapm.org/pubs/hytec). Thus, prior theoretical concerns have given way to the rapid study and clinical adoption of hypofractionation.The superiority of conventional fractionation is supported by linear‐quadratic (LQ) modeling of radiation effects. These models assume that the alpha/beta  rests in the potential role of novel radiobiological factors that may become relevant at higher doses per fraction. Hypofractionation challenges the long‐held understanding of how RT controls tumors, redefining its role in immune activation, reoxygenation, and repopulation. Hypofractionation is particularly effective at inducing immunogenic cell death (ICD)+ T cells in several cancer models.Evidence suggests the inflammatory effects of RT are activated only above a threshold dose of around 6‐8 GyThe immunogenic effects of hypofractionation can be further exploited through combination with immune checkpoint blockade (ICB). Hypofractionation has been recommended as the optimal strategy for combination with ICB,In addition to promoting immune infiltration, hypofractionation can modulate tumor vasculature.Hypofractionation also reduces the time to achieve the prescribed dose, possibly countering the role of accelerated tumor repopulation during later stages of RT.As we seek to improve the quality of care we provide, we must remember that hypofractionation offers effective patient‐centered high‐value care. Randomized clinical trials, physics advances, and new radiobiological paradigms point to a new simple truth: all patients should receive hypofractionated radiotherapy.3.Bα/β values representing the tissue‐specific element and with correction for proliferation, if required. These radiobiological principles, encapsulated in the “4Rs” of fractionated radiation therapy,Received wisdom from over a century of radiation treatment of cancer is that dose is best delivered fractionated in a long course over typically 5–7 weeks. Historically, attempts to use hypofractionation to condense treatment time into a more convenient and cost‐effective scale gave generally inferior outcomes. As a result, radiation oncologists came to associate high dose per fraction with more severe side effects. Clinical experience was mirrored by radiobiological experiments showing the importance of tissue growth kinetics in modulating effects of changing size of dose per fraction and overall treatment time.In treatment planning for radiation therapy, margins are usually added to create planning target volume (PTV) from gross tumor volume (GTV) and clinical target volume (CTV). This is to account for the setup uncertainty and various voluntary and involuntary tumor motions so that adequate coverage of the tumor will be achieved with the planned treatment.For some tumor subtypes, such as breast and prostate cancers, that have the characteristic of similar growth kinetics to late responding normal tissue, there has been renewed interest in hypofractionation. Investigation into the risk of late reactions following treatment with modest hypofractionation using modern breast cancer techniques has been encouraging. Even when treatment fields include nodal regions, there does not appear to be an increased risk of brachial plexopathy compared to conventional fractionation.While modest hypofractionation of 2.25 Gy per fraction has been shown to provide favorable results in early‐stage (T1‐2N0) glottic cancer, hypofractionation for more advanced H + N cancer can result in extreme morbidity. The laryngeal cartilage is a sensitive structure whose function can be easily impacted by the late effects of radiation with attempts at more aggressive hypofractionation. Recent phase I study on more moderate hypofractionation of 3.5–5 Gy per fraction for early‐stage glottis cancer was closed prematurely due to dose‐limiting toxicities including arytenoid necrosis requiring supraglottic laryngectomy.Similar to the larynx, the pharyngeal muscles and mandible are exquisitely sensitive to late radiation toxicity. Even mild hypofractionation in the setting of a tumor that either invades or is immediately adjacent to the mandible results in unacceptably high rates of osteonecrosis of the mandible.Received wisdom is, of course, rarely universally correct and “habit is a great deadener,” but another round of attempts at hypofractionation that ignore the need for CTV expansions and/or radiobiological considerations would be misguided, and likely dangerous. It may be possible to choose to use hypofractionation for prostate and breast, providing the dose per fraction is not too intense and is delivered with modern techniques that minimizes PTV expansion and optimizes dose homogeneity. Treatment of small lesions, where volume becomes more critical, may be achievable under certain conditions,44.AWe thank our esteemed colleagues for their thoughtful arguments against the adoption of hypofractionated radiotherapy. Indeed, we also believe that “habit is a great deadener,” and it is time to stop defaulting to conventional fractionation due to a belief that prescribing more than 2.2 Gy per day leads to inferior outcomes.Our colleagues point out that hypofractionation requires tighter margins and suggest there is too great a risk of marginal failure to justify its use. Over the past two decades substantial effort has been made to improve on‐board and in‐room imaging technology in radiation oncology. Advanced imaging systems are now used in most radiation therapy treatments. This drive to implement IMRT and IGRT was motived by the fact that improvements in targeting could result in the delivery of highly conformal dose distributions and reduced PTV (not necessarily CTV) margins. Routine IGRT, that now includes kV imaging, CBCT, MRI, optical tracking, automatic image registration, and a myriad of other tools, was intended to open the door to improve the therapeutic ratio in many disease sites. However, the true clinical benefit of these tools will never be fully realized without challenging our conventional thinking on dose and fractionation. Why invest in all this technology without making an effort to improve tumor control with reduced normal tissue complication?Conventional thinking has in fact been challenged in many disease sites and led to a change in practice to at least moderate hypofractionation for most disease sites. Our opponents cite concern about the adoption of hypofractionation in head and neck cancer, which accounts for 4% of all cancers in the United States. We concur that extreme hypofractionated regimens are challenging to deliver and poorly tolerated in patients with head and neck cancers. Indeed, the risk of toxicity in patients with an exceptionally high cure rate such as HPV+ oropharynx squamous cell carcinoma is difficult to justify. However, our argument is not that extreme or ultrahypofractionation is necessary for all patients, only that doses of more than 2.2 Gy per day are appropriate for all. Moderate hypofractionated approaches have long been a standard of care in the management of head and neck malignancies.Our colleagues also point out that there is limited follow‐up with hypofractionated regimens, and that late toxicity must be assessed before wholesale adoption. We ask which other medical or surgical oncologic treatment required even a decade of follow‐up prior to clinical adoption? The 10‐year follow‐up from the Canadian whole breast hypofractionation trials was published in 2010, and there has been no evidence of late fibrosis.Our colleagues’ call for improved radiobiologic understanding refers to using the conventional LQ model and 4 R's of radiobiology to describe cell kill and tumor kinetics following hypofractionation citing literature published “at the end of the last century.” Referencing more recently published data, we have argued in favor of hypofractionation for all patients based on extensive preclinical and clinical radiobiological evidence. The striking clinical outcomes associated with hypofractionation challenges us to consider therapeutic benefits beyond linear‐quadratic cell kill and to more deeply probe the molecular basis for the 4 R's. Evidence suggests hypofractionation could promote a paradigm shift in RT through induction of antitumor immunity.ex vivo patient‐based models to optimize dosing regimens for radiation‐induced immunogenicity.Finally, there is a concern that treating all patients with hypofractionation does not provide individualized care. However, we counter that protracting treatment with standard fractionation is even less patient centered. The adoption of shortened courses of radiation therapy in the management of breast cancer saves 2 weeks of inconvenience for the average patient. Resources should be directed toward establishing individualized treatments informed by both patient and tumor features. To date, clinical implementation of such platforms is limited, but several laboratories are working on individualized biomarker discovery platforms for optimizing RT schedules. Some of these approaches include genomic or spectroscopic based signatures of radiosensitivity as well as Hypofractionation offers equivalent or improved oncologic outcomes and is well tolerated in terms of both acute and late toxicity. IMRT and IGRT have enabled equivalent or improved tumor control and normal tissue toxicity profile with hypofractionation. Advances in radiation physics and radiation biology support a new standard of clinical care in radiation oncology. The answer is clear: all patients should be treated with hypofractionated radiotherapy.4.BWe agree with Drs. Green, Van Nest, and Soisson that the “transformative improvements” in delivery of radiation therapy through advances in image guidance, target delineation, and motion management have led to “unprecedented potential for safe and effective delivery of high dose radiotherapy.” However, we continue to argue against the universal adoption of hypofractionation for all cancer treatments. This bold movement disregards the diverse radiobiological features of both tumors and the intimate normal tissues that cannot be avoided completely, regardless of the current technological advances. While the arguments presented and the references quoted by our colleagues provide evidence for the advantages of hypofractionation for specific clinical situations, there was no evidence provided to support universal application of hypofractionation to all cancer radiotherapy without causing too much harm.We also agree with our colleagues that “future clinical trials are needed to realize the potential of improved localization.” As they point out, practice patterns display a disconnection between the choice of PTV and frequency of image guidance.α/β than their surrounding normal tissues as demonstrated in the HyTEC papers.α/β values and may allow hypofractionation, if IMRT/IGRT is used, simply confirms the validity of the model. It does not encourage its use for all cancer treatments.The suggestion that we “revise the LQ model” is misguided. The model is not the problem. The model is fine and based on a huge amount of hard clinical and preclinical data that simply do not support the application of hypofractionation to all tumors or normal tissues. This is not a “theoretical concern” but an important practical clinical issue. Our opponent's own reference from Hypofractionation Treatment Effects in the Clinic (HyTEC) has shown that LQ model may still approximate the total cell death caused by SBRT/SRS through indirect cell death in certain clinical cases.de novo tumor immunity or boost pre‐existing immunity sufficiently to affect the outcome. We are still a long way off from understanding and regulating what is now still the observance of an occasional abscopal response.Nor can radiation‐induced immunity be recruited to support the general use of hypofractionation. Albeit, this is an exciting time as we are seeing a growing utility of immune therapy in the treatment of cancer; currently, immune checkpoint inhibitors are effective only in the proportion of patients with pre‐existing CD8+ T‐cell antitumor responses.No matter what additional radiobiological factors are invoked — immunity, reoxygenation, repopulation, etc., the only solid evidence that exists for a radiation protocol that can be safely and effectively applied to all cancers is conventional fractionation, which has been honed over the last century. Certainly there are exceptions where hypofractionation makes sense, but to use it universally is a recipe for disaster and a disservice to our patients.The authors declare no conflict of interest.


Intermolecular interactions play a crucial role in materials chemistry because they govern thin film morphology. The photophysical properties of films of organic dyes are highly sensitive to the local environment, and a considerable effort has therefore been dedicated to engineering the morphology of organic thin films. Solubilizing side chains can successfully spatially separate chromophores, reducing detrimental intermolecular interactions. However, this strategy is also significantly decreasing achievable dye concentration. Here, five BODIPY derivatives containing small alkyl chains in the α‐position were synthesized and photophysically characterized. By blending two or more derivatives, the increase in entropy reduces aggregation and therefore produces films with extreme dye concentration and, at the same time almost solution like absorption properties. Such a film was placed inside an optical cavity and the achieved system was demonstrated to reach the strong exciton‐photon coupling regime by virtue of the achieved dye concentration and sharp absorption features of the film. Entropic mixing of two or more, highly similar dye molecules results in thin films showing almost solution like photophysical properties. Mixed films of new, low molecular weight BODIPY dyes, with short alkyl chains, were fabricated and furthermore used in an optical cavity, where the strong coupling regime was reached. Organic dyes have a high tendency to aggregate due to their flat structure and large polarizability. The close dye–dye proximity give rise to strong interchromophore interactions resulting in new and often unwanted effects such as H‐ and J‐aggregates,Strong light‐matter coupling using organic molecules is a relatively new research field, but has already harvested considerable attention.Being half a porphyrin in size, BODIPY (boron dipyrromethene) dyes have been shown to have a broad spectrum of applications. Their excellent photophysical properties such as high fluorescence quantum yields, large molar absorptivity, narrow absorption and emission bands, small Stokes shifts, tuneable emission, and a high photo‐ and chemical stability make them highly versatile.Entropic mixing uses entropy as a mean to reduce a systems ability to aggregate.In this work, five BODIPY dyes with linear as well as branched alkyl chains in the α‐position were synthesized with the discovery of a previously unknown substitution effect that enabled a fourfold increase in yield of the boron complexation. The photophysical properties of the BODIPY dyes in solution were assessed to be indistinguishable using steady state and time resolved optical spectroscopy. Neat films showed a high tendency to aggregate, considerable light scattering, and the sharp BODIPY absorption features were considerable broadened. Films consisting of mixed derivatives having branched substituents showed reduced light scattering and monomeric like absorption features. However, when derivatives having branched and linear substituents were mixed together, phase separation became evident, highlighting the importance of using very similar substituents in entropic mixing schemes. Finally, to demonstrate on the applicability of the concept, a film consisting of mixed BODIPY derivatives where encapsulated within an optical cavity, and the attained system was determined to reach the strong coupling regime, due to the strong and narrow absorption band of the BODIPY film.n‐butyl (nBu‐BODIPY), iso‐propyl (IP‐BODIPY), sec‐butyl (sBu‐BODIPY) and tert‐butyl (tBu‐BODIPY) substituents was successfully conducted via alkylation of pyrrole, followed by condensation and complexation , n Scheme .N,N‐dimethylalkylamides3 to form the corresponding pyrrylketones, and a following reduction of the carbonyl moiety to the alkane, using either LiAlH4 or NaBH4. The alkylated pyrroles were subsequently submitted to a Vielsmeier‐Haack formylation, using DMF and POCl3, which afforded the 2‐alkyl‐5‐formylpyrroles that were used for the BODIPY‐condensation.3 to undergo condensation to the dipyrromethene‐intermediate, which were directly treated with Et3N and BF3⋅OEt2 to perform the complexation to the desired BODIPY dyes.Alkylation of pyrrole with linear sidechains was achieved by performing a Vielsmeier‐Haack type reaction using secbutyl‐pyrrole yielded 49 % of the desired product. Adding a more bulky sidechain though, like a tert‐butyl group, only gave the product in 15 % yield, which agrees well with earlier reported values.n‐butyl, sec‐butyl or tert‐butyl substituents were synthesised, with the surprising discovery that the right amount of bulkiness on the α‐position significantly increases the yield of the complexation reaction.These last two steps produced yields in the range of 10 to 50 %. The compounds with linear sidechains only gave yields of ∼10 %, whereas adding a small branched sidechain like isopropyl increased the yields substantially. The α‐isopropyl‐pyrrole yielded 44 % and the α‐nBu‐, sBu‐ and IP‐BODIPY show sharp absorption and emission bands as well as very small Stokes shifts, large fluorescence quantum yields, single exponential excited state lifetimes and high molar absorptivities . The BODIPY‐derivatives can therefore be mixed together in order to achieve high entropy blends with monomeric like photophysical properties.Entropic mixing requires the blended molecules to exhibit indistinguishable photophysical properties.nBu shows the largest aggregated domain sizes, and IP more rod like aggregates than the others. When chromophores are tightly packed together, interactions between their transition dipole moments can be so strong that the energetics are perturbed. The best‐known examples of intermolecular strong coupling is H‐ and J‐aggregates.sBu and IP films, indicating at least two distinct type of aggregates. The emission lifetime of these two emissive states differs substantially, where the low‐energy transition always is the long‐lived one . To summarize, pristine films of the BODIPY derivatives have a substantial degree of aggregation causing light scattering and a highly broadened absorption profile.The BODIPY core is flat, providing the possibility for molecular stacking. Furthermore, its low energy high intensity electronic transition indicates a large polarizability, and thus large London dispersive forces, further reinforcing the molecules ability to aggregate. The physical and photophysical properties of pristine films of the BODIPY‐derivatives were first studied, and these were later compared to those of blended systems. All five derivatives produce pristine films having a significant degree of aggregated domains as revealed by polarized microscopy . Bulky‐ and linear substituents all seem to give rise to similar aggregation, although sBu, and tBu that do not show any large aggregation domains, and others that show signs of large aggregates forming . In blends containing linear alkyl chain derivatives, rod like aggregate structures were observed, leading to broad absorption and emission bands. Figure sBu blend, very little scattering is present and the linewidth of the main absorption band is considerable narrower as compared to pristine films. The absorption maximum is at 532 nm, a small redshift as compared to the solution value of 512 nm. The emission shows two distinct bands, one sharp with a small Stokes shift, in shape resembling the emission from dilute solution, and another redshifted and slightly broader. Other combinations containing sBu show similar photophysical properties (as for the sBu‐IP blend). To assess the effect of blending on the emission quantum yield, the quantum efficiency of the sBu‐IP blend as well as the individual components, sBu and IP, were determined to 15, 8, and 2 %, respectively. This can be compared to earlier reports of quantum efficiencies in the range of 7–13 % for BODIPYs doped at 15 w/w% in polymers.Pristine films of the derivatives display a broad absorption profile as well as significant light scattering. These undesirable features are due to aggregated domains, being large enough to scatter light, and providing a close packing that results in strong interactions between the transition dipole moments of the individual chromophores. To see if entropy can be used as a means of disrupt packaging without diluting the concentration compared to pristine films, the derivatives were blended together. The properties of blended films can be classified into two categories, those consisting of binary blends of IP, sBu‐tBu blend film was recorded at the maximum of the two emission bands . The average lifetime of the high energy monomeric like emission band is 1.0 ns, and the average lifetime of the low energy emission band is 3.3 ns. A global analysis of the decays from the two emission bands reveals a build‐up of low energy emission with the same time constant as the high‐energy emission decay. This indicates that these two emissive states do not come from different locations in the film, but rather that throughout the film the low energy state acts as an energy relaxing route from the high energy monomeric excited state. The absence of strong absorption in the wavelength range of the low energy emission indicates that either the aggregational state is present in low concentrations, or it has a low transition dipole moment. Furthermore, absorbance of the low energy transition is not seen in excitation spectra . The relative long lifetime of the low energy state supports excimer formation, whereas the relative narrow bandwidth of the emission advocates J‐aggregates. Previous studies have pointed to the existence of J‐aggregated dimers in BODIPY‐polymer mixes.To examine if the low energy emission band is the result from excimeric or J‐aggregate like states, time resolved emission spectroscopy was performed. The decay of emission from the sBu and IP/tBu is sharp and monomeric like. This indicates that for entropic mixing to be successful, very similar substituents should be used as to reduce possible phase segregation. The blending furthermore reduces light scattering due to a reduced amount of large aggregates.Interestingly, we see emission around 500 nm in various blends and in neat IP films. Considering the large emission quantum yield, and that the feature is present in different blend combinations, we assign this feature to an aggregational state rather than an impurity. Excitation spectroscopy reveals that the state being responsible for the emission only absorbs on the high energy shoulder of the film . In summary, the absorbance features from thin films consisting of blends of sBu‐IP 1:1). The BODIPY film is sandwiched between layers of polyvinyl alcohol , which insulates the film from the Ag mirrors in order to remove possible disturbances from Ag surface plasmons. The molecular transition is clearly replaced by two polaritonic states. As the angle of reflectivity increases, the energy of the lower polariton approaches the energy of the bare molecule transition, but never cross it. The observed avoided crossing is a typical feature of a strongly coupled system. The Rabi splitting  was calculated to 358 meV by fitting the angular resolved reflectivity to a coupled oscillators’ model (see methods section). This value is considerably larger than the full width at half maximum of the molecular absorbance (115 meV) of the film, and the condition for entering the strong coupling regime is therefore met. Thus, the ability to process BODIPY in small films at extreme concentrations  without a significant broadening of the absorption envelope, enables the strong exciton‐photon coupling regime to be reached.To reach the strong light‐matter coupling regime, strongly absorbing dyes need to be processed at high concentrations in an optical cavity. The optical cavity provides a mean to enhance the electromagnetic field strength at the frequency of the molecular electronic transition. This by having a cavity thickness that supports a standing wave with the same energy as the BODIPY absorption. Now energy is interchanged between the cavity and the dye faster than energy dissipation, and the strong coupling regime is reached. When this happens, the molecular transition is replaced by two polaritonic states, the upper and lower polaritons, located at higher and lower energy as compared to the molecular transition, respectively Figure . The pol3.In conclusion, five different BODIPY derivatives, alkylated in the α‐position, were synthesized. The highest achieved yield in the boron complexation step was 49 %, which is considerable higher than previously reported yields for this kind of compounds. This is presumably due to a certain steric bulk of the introduced alkyl sidechains, although support for this assumption cannot be rationalized by the suggested mechanism of BODIPY condensation using POClThe authors declare no conflict of interest.As a service to our authors and readers, this journal provides supporting information supplied by the authors. Such materials are peer reviewed and may be re‐organized for online delivery, but are not copy‐edited or typeset. Technical support issues arising from supporting information (other than missing files) should be addressed to the authors.SupplementaryClick here for additional data file.


The loss of biodiversity is altering the structure of ecological networks; however, we are currently in a poor position to predict how these altered communities will affect the evolution of remaining populations. Theory on fitness landscapes provides a framework for predicting how selection alters the evolutionary trajectory and adaptive potential of populations, but often treats the network of interacting populations as a “black box.” Here, we integrate ecological networks and fitness landscapes to examine how changes in food‐web structure shape phenotypic evolution. We conducted a field experiment that removed a guild of larval parasitoids that imposed direct and indirect selection pressures on an insect herbivore. We then measured herbivore survival as a function of three key phenotypic traits to estimate directional, quadratic, and correlational selection gradients in each treatment. We used these selection gradients to characterize the slope and curvature of the fitness landscape to understand the direct and indirect effects of consumer loss on phenotypic evolution. We found that the number of traits under directional selection increased with the removal of larval parasitoids, indicating evolution was more constrained toward a specific combination of traits. Similarly, we found that the removal of larval parasitoids altered the curvature of the fitness landscape in such a way that tended to decrease the evolvability of the traits we measured in the next generation. Our results suggest that the loss of trophic interactions can impose greater constraints on phenotypic evolution. This indicates that the simplification of ecological communities may constrain the adaptive potential of remaining populations to future environmental change. The loss of biodiversity is rewiring the web of life; however, it is uncertain how this will affect the ability of remaining populations to evolve and adapt to future environments. To gain insight into these effects, we conducted a field experiment that either maintained a natural community of predators or removed all but one of the predators that was able to impose selection on a common prey. We found that the loss of predators acted to constrain prey evolution toward a particular combination of traits. Moreover, we found that the loss of predators could make it more difficult for prey to adapt to uncertain future environments. Taken together, our results suggest that the simplification of the web of life may constrain the adaptive potential of remaining populations.The fitness landscape provides a powerful framework for understanding how natural selection has shaped the evolution of biodiversity—from genes to phenotypes to species Wright . More thΔz¯=Gβ, where Δz¯ is a column vector of the average change in each trait between generations, G is the additive genetic (co)variance matrix for these traits , and β is a column vector of directional selection gradients acting on each trait . Grant and Grant  located at Humboldt Bay National Wildlife Refuge (HBNWR)  near Loleta, California, USA. This common garden consists of 26 different willow genotypes that were collected from a single population of willows growing around Humboldt Bay. Stem cuttings of each genotype (25 replicates per genotype) were planted in a completely randomized design in two hectares of a former cattle pasture at HBNWR. Willows at our study site begin flowering in February and reach their peak growth in early August. During this study, willows had reached 5–9 m in height. Further details on the genotyping and planting of the common garden are available in Barbour et al.  to exclude three parasitoid species that attack during larval development. This treatment did not exclude the egg parasitoid Platygaster sp., which attacks prior to gall initiation  and standardized phenotypic traits (i) of individuals—in each food‐web treatment. Second, we scaled selection surfaces relative to mean fitness (W¯) to calculate standardized selection gradients. Third, we used our estimates of directional selection gradients to characterize the slope of the fitness landscape, which we used to quantify the effects of food‐web structure on the trajectory of evolution. Finally, we estimated the curvature of the fitness landscape and used a simulation to explore its effects on the adaptive potential of the gall midge population in the next generation.Our analysis consisted of four parts. First, we used generalized linear mixed models (GLMM) to quantify selection surfaces—linear and nonlinear relationships between absolute fitness (αi), quadratic (αii), and statistical interactions (αij) between each trait. Note that to obtain valid estimates of linear selection surfaces, we removed nonlinear terms prior to estimating linear relationships . To approximate the selection surface, we modeled larval survival as a function of food‐web treatment as well as linear (βi), quadratic (γii), and correlational (γij) selection gradients. Briefly, this method calculates the average gradient of selection surfaces by multiplying the average of W(z)[1−W(z)] by each regression coefficient . We then divided this average gradient by the mean fitness (W¯) to put it on the scale of relative fitness (w=W/W¯), and thus interpretable as a selection gradient. We estimated selection gradients separately for each food‐web treatment. We also determined whether selection gradients differed between food‐web treatments by calculating the difference in bootstrapped replicates between treatments. Note that we doubled all quadratic terms prior to calculating selection gradients to put them on the same scale as estimates of directional and correlational selection , we can infer the effect of food‐web structure on the trajectory of phenotypic evolution.The effect of selection on the trajectory of evolution is determined by the slope of the fitness landscape, which in our study corresponds toΔG=GCG) are governed by the curvature of the fitness landscape (C=γ−ββT), which in our study corresponds toγii  corresponds to the quadratic selection gradient acting on a trait, and each γij  corresponds to the correlational selection gradient acting on a particular trait combination. Note that we omitted the upper triangle of each matrix for clarity because it is simply the reflection of the lower triangle. Subtracting these two matrices results in the curvature matrix of the fitness landscape:Cii  represents the effect of selection on the additive genetic variance in a trait, and each Cij  represents the effect of selection on the additive genetic covariance between a particular trait combination. We used bootstrapped values of each selection gradient to estimate the curvature of each component of the matrix and its associated 95% CI. We also used this information to determine whether the curvature of each component differed between our food‐web treatments.The indirect effects of selection on the G‐matrix (104 random G‐matrices for the next generation. We restricted the range of additive genetic variance (VG) for each element in these G‐matrices to between 0 and 0.5 to reflect typical ranges in narrow‐sense heritability values . Note that this analysis assumes that the effects of recombination and mutation on the G‐matrix are much smaller than the effects of selection, which appears to be a reasonable assumption over short time scales  in each treatment changed the structure of βs) for each of 104 random G‐matrices, we can then assess how changes in the curvature matrix alter the adaptive potential of the associated traits. We report the distribution of these effect sizes, rather than conduct a statistical test, because the number of replicates in a simulation can be arbitrarily high, thus making any effect size statistically significant . We detected a positive bias in both food‐web treatments , indicating that unadjusted relationships would overestimate the strength of selection on chamber diameter. To account for this bias, we subtracted our mean estimates of bias from our estimates with the full dataset prior to calculating chamber diameter's selection surface and directional selection gradient.Rather than imposing selection, parasitoids may influence the expression of herbivore traits, which could bias measurements of selection. In our system, it was plausible that parasitoids may influence chamber diameter by altering larval feeding behavior or killing larvae before they complete their development. To estimate this potential bias, we subset our data to only include galls where there was variation in larval survival within the same gall . If we assume that larvae within each gall should have similar chamber diameters because they come from the same clutch and experience the same local environment , then the relationship between chamber diameter and larval survival in this data subset represents the effect of parasitism on trait expression . We used a GLMM with the same structure as described previously except that we modeled only a linear relationship between chamber diameter and larval survival  and have been archived on Zenodo (https://doi.org/10.5281/zenodo.3706794).All analyses and visualizations were conducted in R . This conflicting selection is likely due to trait differences between guilds, as larger clutches may be easier targets for egg parasitoids to find, but the more complex gall structure may be more difficult for larval parasitoids to oviposit through.We found that the removal of larval parasitoids increased the number of gall midge traits under directional selection (3 of 3) relative to the original food web 1 of 3) , but was simply a consequence of the (expected) lower survival of gall midges in the original food web . We expect this difference to be transient though, because egg parasitoids would increase in abundance once they are released from intraguild predation, which would make the strength of selection on gall diameter comparable to the original food web . It is worth noting that positive selection on chamber diameter in both treatments was unexpected. For example, the fact that larger galls provide more of a refuge from larval parasitoids makes sense because they attack after the gall is formed; however, egg parasitoids attack prior to gall formation, which suggests that chamber diameter is either directly related to survival or strongly correlated with an unmeasured trait that is under selection .We also observed clear evidence of directional selection for midges to avoid ovipositing on plants with high densities of conspecifics when we removed larval parasitoids Fig. ; howeverTo visualize the multivariate effects of natural selection, we plotted the fitness landscape for each trait combination in each treatment Fig. . The arrγPref:Pref= 0.18 ), but was also magnified by the lower average survival in the original food web. This was likely a result of larval parasitoids imposing greater mortality on egg parasitoids at high gall midge densities (see “Selection on egg parasitoids” section), which would act to increase the relative fitness of gall midges at high densities.The curvature of the fitness landscape indirectly affects adaptive potential and is influenced by directional, quadratic, and correlational selection gradients. There was no clear evidence of correlational selection for any combination of traits in either food‐web treatment Table . Similarβi), quadratic (γii), and correlation selection (γij), we calculated the curvature (C=γ−ββT) of the fitness landscape in each food‐web treatment.Using our estimates of directional , then the removal food web decreases the average evolvability in 78% of the G‐matrix scenarios.Interestingly, when we translate the effect of the curvature matrix onto adaptive potential in the next generation, we see that the removal of consumers had a general tendency to decrease evolvability Fig. . SpecifiγPref:Pref = −0.46 , Table S1), such that the impact of larval parasitoids increased nonlinearly with higher gall midge densities  and the lower mean survival of gall midges. This pattern of selection acts to increase genetic variation in oviposition preference, which in turn enhances the ability of the gall midge population to respond to uncertain selection pressures in the next generation . This pattern of selection also indicates the possibility of evolutionary bistability, where different initial conditions  select for different phenotypes of the same species in similar environments Table S2: Standardized selection gradients imposed by larval parasitoids on gall midges in the original food web.Figure S1: Change in average evolvability for 10,000 random G‐matrices using our best (mean) estimate of the curvature matrix for selection in the absence of egg parasitoids vs. the original food web.Click here for additional data file.


While plasma concentration kinetics has traditionally been the predictor of drug pharmacological effects, it can occasionally fail to represent kinetics at the site of action, particularly for solid tumors. This is especially true in the case of delivery of therapeutic macromolecules , which can experience challenges to effective delivery due to particle size‐dependent diffusion barriers at the target site. As a result, disparity between therapeutic plasma kinetics and kinetics at the site of action may exist, highlighting the importance of target site concentration kinetics in determining the pharmacodynamic effects of macromolecular therapeutic agents. Assessment of concentration kinetics at the target site has been facilitated by non‐invasive in vivo imaging modalities. This allows for visualization and quantification of the whole‐body disposition behavior of therapeutics that is essential for a comprehensive understanding of their pharmacokinetics and pharmacodynamics. Quantitative non‐invasive imaging can also help guide the development and parameterization of mathematical models for descriptive and predictive purposes. Here, we present a review of the application of state‐of‐the‐art imaging modalities for quantitative pharmacological evaluation of therapeutic nanoparticles and monoclonal antibodies, with a focus on their integration with mathematical models, and identify challenges and opportunities.Therapeutic Approaches and Drug Discovery > Nanomedicine for Oncologic DiseaseDiagnostic Tools > in vivo Nanodiagnostics and ImagingNanotechnology Approaches to Biology > Nanoscale Systems in BiologyThis article is categorized under: Pharmacological evaluation of nanoparticles and antibodies performed through quantitative imaging‐guided mathematical models. Plasma kinetics has been used to evaluate the pharmacological exposure‐response relationships under the assumption that plasma concentration is a surrogate for drug concentration at the site of action  discuss the biophysical factors that govern the transport of macromolecules, thereby affecting their pharmacology, ii) present the key imaging modalities that are used in vivo or in the clinic for macromolecule visualization and estimation of model parameters, and iii) review key imaging‐driven mathematical models for pharmacological evaluation of macromolecules intended for therapeutic, diagnostic, or theranostic  applications in cancer.Increased application of non‐invasive quantitative imaging will likely allow for the development of new therapeutics, improve diagnosis, and allow real‐time monitoring of treatment and its optimization. In the following, we will 2Q can be expressed as the ratio of the pressure difference between arterial and venous ends (ΔP), and flow resistance . Of notOnce macromolecules have crossed the capillary wall into the interstitium, they are transported via bulk transport with the interstitial fluid, or through diffusion to reach the target cells, represented as  has expanded significantly in clinical practice. MRI is a non‐ionizing imaging modality that uses a strong magnetic field and radio waves to produce detailed images of anatomical structures. It is based on the phenomenon of nuclear magnetic resonance (NMR), which involves the perturbation of spin‐alignment of nuclei in a strong magnetic field through the application of radio frequency  NP‐based MRI gives dark signals in the ROI that are sometimes difficult to differentiate from artifacts or local field inhomogeneity.3.2Nuclear imaging modalities such as PET and single‐photon emission computed tomography (SPECT) utilize the l Figure . With esl Figure , great il Figure .64Cu)   to its excited state S*. Following non‐radiative relaxation to the radiative excited state Sr*, a photon of energy Eem ~ λem−1 is emitted. Similarly, the working principle of bioluminescence is reported in Figure While their clinical application remains challenging, optical in vivo imaging systems (IVOI) are widely employed in preclinical studies to evaluate the biodistribution of a variety of compounds, including mAbs, cells, NPs, and microparticles  that can penetrate biological matter up to a few cm of tissue  blood‐flow driven vascular transport to the organ of interest, ii) transvascular migration into the interstitium, and iii) and interstitial diffusion. The key parameters that characterize these processes can be quantified through in vivo imaging to parameterize mathematical models for quantitative pharmacological evaluation of macromolecules  of mesoporous silica NPs (MSNs) and their in vivo pharmacokinetics Figure  Dogra e. The stuNotable strides in the development of novel mechanistic mathematical models informed by imaging data have been achieved in recent years  mechanisms, whereby “leakiness” in tumor vasculature due to defects in tumor vascular epithelial cells and epithelial fenestrations, as well as the lack of lymph drainage from tumor vasculature (among other mechanisms), tends to increase macromolecular accumulation in tumors relative to other tissues. van de Ven et al.  implemenFrieboes , allowinR2 > 0.9) for tumor NP accumulation due to EPR effects, however at the cost of neglecting the effects of variations in intratumoral interstitial fluid pressure, which is known to resist NP tumor penetration and lead to heterogeneous intratumoral NP delivery  that do not suffer from systematic errors . The stability of the bond between the imaging agent and the macromolecule it labels is critical for the accurate estimation of disposition kinetics and parameter values, and the breaking of this bond can result in leakage of the label from the macromolecule, confounding observations and providing inaccurate pharmacological assessments. The disposition behavior of macromolecules at early time points following administration is critical to accurately assess the pharmacokinetics of macromolecules, hence imaging modalities with low temporal resolution should be avoided in such circumstances, and are appropriate when only a semi‐quantitative assessment is required. Similarly, limitations of spatial resolution should be considered based on the nature of the assessment.The integration of in vivo imaging with mathematical modeling is a valuable tool that, in addition to the pharmacological evaluation of macromolecules, can provide insights into mechanisms of transport barrier‐induced drug resistance or therapy failure, which can support the development of novel strategies to improve delivery and personalize treatment. Selection of which biological and physical phenomena should be included in such mathematical models, and their quantification, is improved when these are informed based on imaging‐based parameter estimates (rather than best fit estimates), which can support the development of mechanistic models for highly accurate predictive applications. Such models will not only provide greater insights into the complex interplay between pathophysiological states and the underlying transport mechanics, but will also serve as in‐silico tools to guide the design optimization of macromolecules for improved delivery and therapeutic efficacy. Further, the application of PBPK‐like modeling frameworks can provide reliable projections for human applications based on models developed for lower species (Aborig et al., The authors have declared no conflicts of interest for this article.Prashant Dogra: Conceptualization; investigation; writing‐original draft; writing‐review and editing. Joseph Butner: Investigation; writing‐original draft; writing‐review and editing. Sara Nizzero: Writing‐original draft; writing‐review and editing. Javier Ruiz Ramírez: Writing‐original draft; writing‐review and editing. Achraf Noureddine: Writing‐original draft; writing‐review and editing. María Peláez: Writing‐original draft. Dalia Elganainy: Writing‐original draft. Zhen Yang: Writing‐original draft. Anh‐Dung Le: Writing‐original draft. Shreya Goel: Writing‐review and editing. Hon Sing Leong: Writing‐review and editing. Eugene Koay: Writing‐review and editing. C. Jeffrey Brinker: Writing‐review and editing. Vittorio Cristini: Writing‐review and editing. Zhihui Wang: Conceptualization; investigation; supervision; writing‐original draft; writing‐review and editing.Engineering of radiolabeled iron oxide nanoparticles for dual‐modality imaging


Understanding the effects that sterilization methods have on the surface of a biomaterial is a prerequisite for clinical deployment. Sterilization causes alterations in a material's surface chemistry and surface structures that can result in significant changes to its cellular response. Here we compare surfaces resulting from the application of the industry standard autoclave sterilisation to that of surfaces resulting from the use of low‐pressure Argon glow discharge within a novel gas permeable packaging method in order to explore a potential new biomaterial sterilisation method. Material surfaces are assessed by applying secondary electron hyperspectral imaging (SEHI). SEHI is a novel low‐voltage scanning electron microscopy based characterization technique that, in addition to capturing topographical images, also provides nanoscale resolution chemical maps by utilizing the energy distribution of emitted secondary electrons. Here, SEHI maps are exploited to assess the lateral distributions of diverse functional groups that are effected by the sterilization treatments. This information combined with a range of conventional surface analysis techniques and a cellular metabolic activity assay reveals persuasive reasons as to why low‐pressure argon glow discharge should be considered for further optimization as a potential terminal sterilization method for PGS‐M, a functionalized form of poly(glycerol sebacate) (PGS). A novel technique built upon secondary electron spectroscopy (SES) provides a detailed investigation into the effects argon plasma treatment has on a biomaterial's surface structures. This unique approach allows for key insights into a samples emission properties and in turn their chemical functional groups, which results in high resolution chemical imaging. However, commonly deployed sterilization techniques such as autoclaving (AC), irradiation, or chemical treatment have been shown to alter the surface and/or the mechanical structure of polymer‐based biomaterials. In comparison, plasma technology has demonstrated a promising potential for surface treatment of biomaterials. A recent review suggests that argon (Ar) plasma can be employed as a viable alternative sterilization procedure for biomaterials. However, several challenges have to be overcome in order to establish plasma sterilization as a standardized ISO method including the characterization of bioactive species of plasma, understanding of microbiological interactions, and achieving standardization of the plasma sterilization method. In particular, ISO standardization requires separate time consuming analyses of surface properties for each specified sterilization condition. Here, Ar plasma treatment is combined with the deployment of semi gas‐permeable packaging in order to form a model treatment of potential sterilization method for future use with polymer‐based biomaterials. Moreover, secondary electron hyperspectral imaging (SEHI) is applied to reveal any localized changes in key functional groups  on the surface of a biomaterial induced as a result of Ar treatment.Biomaterials are rapidly expanding their contribution to today's medical progress, particularly in the role of a permanent or transient alternative for damaged or diseased tissues. It is essential that all biomaterials are sterilized prior to implantation within the patient. Additionally, the preservation of the mechanical properties and surface chemistry of a biomaterial poststerilization is essential for the correct function of the material within the body.1 Howe Thus, SEHI can be successfully applied to the characterization of polymers, including novel polymeric biomaterials, and has already revealed the changes in molecular weight and CH vibrations that occur as a consequence of Ar plasma treatment. As SEHI is carried out in the SEM, local variation in chemical changes and sample topography can be assessed in one step. To do this, SEHI constructs a series of images of the sample area, where each image is formed from a selected SE energy band. While innovative synchronized structural and chemical characterization of materials by SEHI has many uses, this study focuses on revealing and mapping the spatial variation of functional groups that are affected by Ar plasma treatment through identifying specific energy bands for CH—, OH—, and CO— groups. In order to identify suitable energy bands for mapping such variations, a number of reference materials are used to evaluate the effects that Ar plasma treatment exhibits on local surface chemistry of sterilized biomaterials. This is important as a biomaterial's functional groups are closely coupled to its ability to promote cell growth through the local surface variations that result from the differing polymer side chains. Detrimental surface hydrophobic characteristics of some biomaterials developed from synthetic polymers are manifested as a lack of cell adhesion, resulting in the implanted biomaterial presenting poor tissue infiltration and integration outcomes. Thus a range of material characterization techniques in addition to SEHI are utilized here to further evaluate the effects of Ar plasma treatment of the surface topology of a polymer‐based biomaterial, in this instance PGS‐M.The foundation of SEHI is the collection of secondary electron (SE) emission spectra by means of the scanning electron microscope (SEM). The SE spectra for some hydrocarbon materials were found to be strongly influenced by excitation of intramolecular vibrations.7 Thus The PGS‐M polymer, formed by rendering PGS (an elastomeric degradable and nontoxic tunable polymer) photocurable through the process of methacryation, displays characteristics that are perceived as advantageous for biomaterial applications. It has been observed that PGS‐M is likely to include small quantities of unreacted methacrylate side chains after polymerization by UV, removal of the unreacted methacrylate, and creating OH— groups on the surface has the potential to aid cellular growth and further the materials biocompatibility. Previous studies have indicated that plasma treatment can remove unreacted methacrylate. In this study, low‐pressure argon glow discharge has been applied for surface treatment of PGS‐M samples. Plasma treated samples exhibit different functional group densities than those of nontreated PGS‐M control samples. Changes include CO bonding and an increase of polar hydroxyl groups established through SEHI. These changes explain the varying ability of PGS‐M to support cellular adhesion after AC or Ar plasma treatment as demonstrated by contact angle measurements and cell metabolic activity assays.PGS‐M is a functionalized form of poly(glycerol sebacate) (PGS)16 TheFigure  with a higher order yield intensity in this energy region. Ar 10 clearly exhibits a greater carbon peak (Mw) compared to that of Ar 4 and AC. This can be understood as follows: argon plasma treatment causes a high levels of free radicals to create crosslinking sites post‐treatment, which directly affect the molecular order of the material. Argon plasma treated surfaces also exhibit a greater SE emission in the energy range that is associated with CH vibrations, with all samples expressing CH2 and CH3 peaks . Furthermore, the intensity is increased by prolonged Ar plasma exposure. The peak intensity in this energy region has been previously shown to have a direct relationship with the crosslinking density of PGS‐M. Therefore, the SE spectrum of Ar 10 suggests a highly crosslinked surface layer. Reactions within the surface structure by argon plasma induced radicals form crosslinks, which have the potential to enhance the crosslinking density between the surface molecular chains.The PGS‐M materials were enclosed in a gas semipermeable bag, which was exposed to low‐pressure Ar glow discharge. Use of the semipermeable bag ensures that any sterilization effect will not be compromised between the Ar plasma treatment and cell growth experiments. In order to assess the chemical changes taking place during this Ar plasma treatment, and compare this to the effects of AC sterilization, SE spectra were collected and presented in Figure 6 withFurther, differences in the SE spectra for argon plasma treated and AC samples are observed within the region of 5–5.5 eV, related to C=O bonding . The spectrum shows that post‐argon plasma treatment emissions in the 5–5.5 eV range are greatly diminished. Argon plasma treatment is understood to cleave away C—O—C bonds attached to the methacrylate within PGS‐M . By cleaving away this bond, removal of methacrylate greatly decreases the amount of C=O bonds present within the polymer. It is worth noting that the decrease in C=O bonding is most noticeable in the Ar 10 rather than Ar 4 samples, which indicates that the cleavage of methacrylate units is time and area dependent. As more methacrylate is removed, surface crosslinking recombination increases, resulting in an increase in surface crosslinking of Ar 10. Once methacrylate units are removed, an OH containing hydroxyl group remains, signified by Ar 10 and Ar 4 showing emissions within 4.3–5 eV. where all analyzed materials are used to determine the upper and lowest emission values. It is expected that at the length scale of micro/nanometers, structures will include emission from multiple functional groups. To establish the distribution of functional groups, one should consider the brightness of specific emissions. Figure While the SE spectra provide an insight into the average chemical changes at the surface, which could also be obtained by other surface sensitive methods such as x‐ray photoelectron spectroscopy (XPS) , using the above specific energy ranges to form images in the SEM is only possible with SEHI. In order to obtain images from the corresponding spectral components, a non‐negative matrix factorization (nnmf) was used to isolate various components between 0 and 6 eV . Figure 9 wher SEHI images show micrometer‐sized spherical features are clearly present within AC, with strong SE emission signatures of C=O bonding. The C=O bonding related emissions of these structures indicate that they contain excess methacrylate groups. C=O bonding across the matrix of Ar 10 on the whole is diminished seemingly as a result of the cleaving of methacrylate post‐Ar plasma treatment. SEHI images displayed in Figure Figure It is notable that the topography of Ar 10 plasma treated samples differs greatly from AC samples, an observation consistent with previous reports.4 SEHIFrom SEHI images alone it is obvious from the reduction of area with strong SE emission in the CO— bonding related energy range that excess methacrylate has been removed from the sample as a consequence of the Ar plasma treatment. Furthermore, the increase in OH groups and CH related crosslinking has clearly become more abundant across the surface matrix post‐Ar plasma treatment. As previously stated, the removal of unreacted methacrylate together with the introduction of surface OH groups is recognized to aid cell growth through the enhanced cellular response expected in materials that exhibit greater crosslinking, and it is expected that cells would adhere and proliferate better on Ar plasma treated surfaces.Figure To test the expectations based on SEHI functional group mapping and for the purpose of using argon plasma as a terminal sterilant, it is important to understand how the SEHI results link to those obtained through commonly practiced characterization methodologies. This is achieved by investigating how the argon plasma treatment has affected the mechanical properties of PGS‐M.  Indeed, contact angle results  and SE spectra Figure  both sho22 Inds Figure  showed tHere, we assess the sample materials potential to support cellular growth using a cellular metabolic activity assay (Resazurin assay). Figure  SEHI offers an efficient way to achieve this due to its ability to map functional groups with the required image resolution together with an ability to map at multilength scales. This ability is vital to attaining a comprehensive understanding of cell behavior on Ar plasma treated surfaces. This future work, in combination with the use of gas semipermeable bags as demonstrated in this study, would pave the way for the wider deployment of argon plasma as a terminal biomaterial sterilization process.The observed data confirms that argon plasma treatment shows a positive relationship to cellular growth. However, SEHI data and nanoindentation also identified that Ar plasma treatment significantly increased the stiffness of PGS‐M samples due to crosslinking. SEHI maps of CO bonding suggest that surface structures vary locally and can be changed from ≈500 nm size (4 min Ar) to ≈50 nm size (10 min Ar) depending on Ar treatment time. Therefore, future work is recommended to optimize the Ar plasma intensity and duration in order to produce a sterilized biomaterial while controlling the local variation of mechanical properties to surface patterns that promote cellular growth. Further to this work, a large scale sterilization study is required to determine the efficacy of the model argon plasma treatments with regards to sterilization at various conditions with a view to providing evidence of its capacity to achieve the recommended sterility assurance levels (SALs) to be termed a sterilization method under ISO requirements26 SEHThe authors declare no conflict of interest.Supporting InformationClick here for additional data file.


Soil legacy effects are commonly highlighted as drivers of plant community dynamics and species co‐existence. However, experimental evidence for soil legacy effects of conditioning plant communities on responding plant communities under natural conditions is lacking. We conditioned 192 grassland plots using six different plant communities with different ratios of grasses and forbs and for different durations. Soil microbial legacies were evident for soil fungi, but not for soil bacteria, while soil abiotic parameters did not significantly change in response to conditioning. The soil legacies affected the composition of the succeeding vegetation. Plant communities with different ratios of grasses and forbs left soil legacies that negatively affected succeeding plants of the same functional type. We conclude that fungal‐mediated soil legacy effects play a significant role in vegetation assembly of natural plant communities. Under natural conditions, plant communities with different composition drive microbe‐mediated soil legacy effects on subsequent vegetation. Specifically, the abundance of forbs and grasses in vegetation can result in soil communities that negatively affect plants belonging to the same respective group. This study shows that plant–soil feedbacks occur in the field and are – in part – driven by pathogenic soil fungi. Plants and soil organisms are interdependent and the microbiome in the soil is shaped by the plants that grow in the soil  and forbs (dicots) differ fundamentally in root architecture (Craine We grew six different plant communities in a temperate grassland. Each plant community consisted of a combination of grass and/or non‐leguminous forb species (hereafter: forbs) which were grown in different ratios . The (sub)plots were exposed to different durations of conditioning by starting the treatments in two different years. After the conditioning phase of one or two years, all plant communities were removed from the soil, and the same seed mixture of 33 grassland species was sown in each treatment (sub)plot as a responding plant community. In both phases we recorded the abundance of all plant species, soil abiotic characteristics, and soil fungal and bacterial community composition. In the conditioning phase, we expected that plant communities would influence soil abiotic characteristics and soil biotic composition, and we expected that the soil biota would affect the establishment of future plant communities in the responding phase.We hypothesised that manipulation of the composition of the conditioning plant communities will result in different microbial soil legacies, and specifically in the accumulation of specialised soil pathogens and mutualists such as arbuscular mycorrhizal fungi (AMF). Second, we hypothesised that in the response phase, grasses and forbs would be less abundant in soils that had been dominated by their own functional type in the conditioning phase, due to the accumulation of soil pathogens. Third, we hypothesised that these effects would be stronger in soils with a two‐year legacy than in one‐year legacy soils, due to the gradual development of specific soil microbiomes over time. Lastly, we hypothesised that soil legacy effects would be mediated by microbial changes in the soil, rather than by soil abiotic characteristics.c. 4% organic matter, 5.2 pH, 2.5 mg kg−1 N, 4.0 mg kg−1 P, 16.5 mg kg−1 K) .In 2015, the field experiment was set up in a restored grassland site , ‘De Mossel’ . Soils are holtpodzol, sandy loam , one of the two subplots of each plot was randomly selected. All original vegetation of the subplot was removed using shovels, while the other subplot was left untouched in that year. Removal included the top soil layer of approximately 4 cm, which generally contains the highest density of roots in this grassland system. This was done to remove the most dominant roots of the plants and prevent re‐growth of non‐target plant species. Each stripped subplot was then sown with the seed mixture that was allocated to that plot as described above. In May 2016 (i.e. one‐year legacy treatments), all vegetation was removed (as described above) from the remaining untouched subplot in each of the 96 plots. These subplots were then sown with the seed mixture that was also sown a year earlier in the paired subplot.At the end of the conditioning phase, on 12–16 June 2017, the vegetation was again removed from all subplots using a sod‐cutting machine . All sods were cut to a standard depth of 3 cm. This was done to remove most of the thicker roots and to prevent re‐growth. After cutting, the soil was hand‐shaken from the sods above the subplots, allowing us to keep most of the remaining soil from the sods in the respective (sub)plots. On 20 June 2017, all subplots were sown with the same seed mixture consisting of the all species sown in the conditioning phase plus ten others that occur in the area but not at the site , and again in August 2018 (responding phase), vegetation assessments were performed. In each subplot, the percentage of vegetation cover was estimated visually for each plant species within a 50 × 100 cm frame. In addition, the percentage moss cover and bare ground were recorded. The frame was placed approximately in the middle of the subplot in order to exclude potential edge effects. The cover of the different functional types  was calculated as the cumulative cover of each species belonging to the respective functional type.Soils were sampled twice, once at the end of the conditioning phase, just before the vegetation was removed (June 2017) in order to establish the conditioning effects on the soil microbial community. The second sampling was used to assess whether the legacy effects persisted over time and took place roughly three months after the establishment of the responding plant community (September 2017). During both sampling events, nine soil cores  were taken to characterise abiotic parameters and for molecular analysis from each experimental subplot. These nine cores were then pooled per subplot and homogenised. A 2‐mL tube was filled with a subset of homogenised soil for molecular analysis at the day of sampling and stored at −80 °C. The remaining soil was used for analysis of soil abiotic parameters.Description of the analysis of soil abiotic parameters can be found in the Supplementary Methods.et al. et al. et al. et al. et al. DNA was extracted from 0.75 g of soil using the Power Soil DNA extraction kit  according to the manufacturer’s instructions. The primers ITS4ngs and ITS3mix targeting the ITS2 region of fungal genes .Bacterial sequences and fungal sequences were analysed using the Hydra pipeline (version 1.3.6) and the PIPITS pipeline (version 2.3) respectively (Gweon soil abiotic composition (soil nutrients and including soil pH) with a permutational analysis of variance  using Euclidean distances. Furthermore, the effects of conditioning time, conditioning plant community, and forb:grass ratio and all possible interactions on soil fungal (ITS2), soil bacterial (16S), and plant community composition were assessed  using Bray‐Curtis dissimilarity. Fungal and bacterial data were transformed using Hellinger transformation and plant data was square root‐transformed and standardised using Wisconsin double standardisation prior to calculating Bray–Curtis dissimilarities. Plot number was included in the models as a random effect to indicate that the one‐ and two‐year conditioned subplots belong to the same plot. All multivariate analyses were performed in R (version 3.5.3), using the ‘vegan’ package  redundancy analyses with either forb:grass ratio , or conditioning time  as explanatory variables. These analyses were performed and visualised for each of the six conditioning communities separately. Redundancy analyses and visualisations were performed in Canoco 5.03 .Slopeiomyces cylindrosporus , AMF and saprotrophs; (2) plant cover  with general linear mixed models. Plot number was included in the model as random effect, to indicate that one‐ and two‐year conditioned subplots belonged to the same plot. Normality and homogeneity of the residuals were checked and data were transformed when necessary (indicated in the respective summary tables). All mixed models were performed in R using the ‘nlme’ package  relative abundances of specific groups of soil fungi  for plants, fungi and bacteria with the respective transformations described above, and did the same using Euclidean distance for the abiotic parameters. All calculations were done using the ‘P < 0.01 are shown. All correlation matrices were constructed using the package ‘corrplot’ in R (Wei & Simko To explore relationships between the abundance of plant species during the conditioning phase May 2017) and the abundance of the same and other plant species in the responding phase (August 2018), we constructed correlation plots using Pearson linear correlation coefficients separately for each of the six conditioning plant communities. In these correlation plots, relationships between conditioning and responding plant species are indicative of soil‐mediated effects between the species (i.e. positive or negative plant–soil feedbacks). We included only those species that comprised greater than 0.25% average cover and that were present in at least three subplots. Furthermore, we included grass and forb cover and total plant cover of the responding plant community in the correlation plots, to reveal whether observed vegetation patterns are driven by individual conditioning or responding species. All correlation plots were corrected for multiple comparisons using a Bonferroni correction. For visualisation, only pairwise Pearson correlations with significance of  and the conditioning treatments influenced responding plant communities. The forb:grass ratio of the seed mixture sown in the conditioning phase resulted in grass and forb covers that differed significantly from each other , Clinopodium vulgare L. (in community 5), Taraxacum officinale and Holcus lanatus (both in community 6). Only one negative conspecific relationship was observed, for Anthoxanthum odoratum L. (in community 5). Furthermore, there were heterospecific relationships between conditioning plant species and other responding plant species in each of the experimental communities  and heterospecific (i.e. when the conditioning species differ from the responding species) soil legacy effects were assessed and visualised using correlation plots including s Figure . There ws Figure . Finallyy Figure .S. cylindrosporus, showed an increase in relative abundance with an increase in grass cover . The fact that these two plant communities were separated in time indicates that the effects of the conditioning plant communities on the responding plant communities must be mediated via the soil legacies. We used a path analysis based on Mantel tests on dissimilarity matrices to explore which components of the soil are affected by the conditioning plant communities and which components explain the responding plant communities. The composition of the conditioning plant community significantly explained the community composition of soil fungi and bacteria in the conditioning phase, but did not explain the composition of soil abiotic parameters . Interestingly, the relative abundance of forb‐associated pathogens was very low and there was no relationship with the abundance of forbs in the vegetation. Forbs are a broad phylogenetic group (comprised of many plant families). Forb pathogens that specialise on a specific family or group of forb species are unlikely to accept hosts from all forb families, and as a result the relative abundances of such specific forb pathogens may not drive the abundance of this functional group as a whole. Grasses, on the other hand, are phylogenetically more closely related to each other . Due to this higher relatedness, pathogens specialised in this group are more likely to affect a larger proportion of the functional group as a whole. While some pathogens have a rather broad host range, even specialised pathogens may attack a range of host plants if they are closely related  and hence for these species regrowth may be responsible for these observed relationships. However, it is unlikely that these effects have had a strong effect on the responding plant community as a whole, as the strongest relationships – observed between functional types in the conditioning versus the responding plant communities – were negative and thus cannot be explained by regrowth or seed production. We therefore conclude that soil legacy effects must be the dominant driver of these effects.One potential confounding factor in the results is that plant roots and seeds originating from the conditioning plant community could have been left behind in the soil after the conditioning community was removed and that these roots may have influenced the composition of the responding communities, either directly via regrowth or via affecting the soil. There were some positive conspecific relationships between et al.It is important to note that at the plant species level, we detected very few indicators for conspecific plant–soil feedbacks. This is an interesting finding as the field site used in this study has been used to collect soil from for countless plant–soil feedback studies over the past decades. In the majority of these studies, plant species grown in soils from this site have negative conspecific feedback effects .Data will be made available on Dryad upon publication. Sequence data have been deposited in the European Nucleotide Archive and will be made available upon publication (Supplementary MaterialClick here for additional data file.