The association between asthma (AS), allergic rhinitis (AR) and oral diseases remains inconclusive in adults. AS and AR often coexist. However, studies that investigate AS, AR together and their association with oral diseases are scarce.Data from 22,898 men and 28,541 women, aged 21 to 25 years, were collected from a national database in Taiwan. Five common oral diseases: dental caries, periodontitis, pulpitis, gingivitis, and stomatitis/aphthae were studied. Differences in the incidence of the five oral diseases in AR vs. non-AR, and AS vs. non-AS groups were compared. The incidence of the five oral diseases in men/ women, urban/country citizen, and high/low income groups was studied. The frequencies of clinical visits and impact of topical steroid use between the groups were also studied. The confounding factors included sex, socioeconomic status, urbanization, dentofacial anomalies, disease of salivary flow, diabetes mellitus, and esophageal reflux.The incidence and the frequencies of clinical visits for all five oral diseases were higher in those with AR than in the non-AR group after adjusting for confounding factors and AS. Similar observation was made for the AS group, without adjusting for AR. However, if AR was included for adjustment, no relationship was found between AS and oral diseases. In the AR group, those with higher incomes, and country residents had a high risk of developing oral disease. Intranasal steroids, rather than inhaled steroids, were also associated with oral diseases.AR, rather than AS, may be associated with oral diseases in young adults. Dental caries, periodontitis, pulpitis, gingivitis, and stomatitis/aphthae are common oral diseases , which hThe association between AS, caries  and periAR and AS often coexist. They are linked by epidemiologic, histologic, physiologic, and immunopathologic characteristics, and also by a common therapeutic approach . AS has Studies on the association of AR with caries and periodontitis are few, and they show conflicting results . The assThe NHIRD was created by the National Health Research Institute (NHRI) in Taiwan . The NHRSubjects born between 1985 and 1988 were selected randomly from the NHIRD. Their claims’ data in the age group of 21 to 25 years were analyzed between 2005 and 2013. The subjects were divided into the groups: AR and non-AR; and AS and non-AS. The criteria for AR and AS included at least two diagnoses of AR (ICD-9-CM diagnostic code 477) or AS (ICD-9-CM diagnostic code 493) in five years between the ages of 21 and 25 years. Those with disease durations of AR and AS <180 days were excluded because AR and AS are chronic diseases. Five major oral diseases were selected for the study: dental caries (code 521.0), periodontitis (codes 523.3 and 523.4), pulpitis (code 522.0), gingivitis (codes 523.0 and 523.1), and stomatitis (code 528.0)/oral aphthae (code 528.2).The subjects were followed up for five years (age 21–25 years old). Incidence of the five oral diseases in the AR versus non-AR groups and AS versus non-AS groups, was compared. More than one diagnosis of each oral disease recorded in the study period was defined as having the individual disease. Incidence of the five oral diseases for AR versus non-AR groups was compared using different demographic characteristics, which included male/female, urban/country resident, and high/low income. The magnitude of the relative risk (RRs) of oral diseases in each character was compared between AR and non-AR subjects.During the five years follow up, the mean clinical visit times for the five oral diseases in various groups were compared. Mean clinical visit times for three dental treatment methods: dental restoration, endodontics, and periodontitis treatment  were also compared to investigate the reason for clinical visit.AR subjects were divided into intranasal steroid group  and non-intranasal steroid group . AS subjects were divided into inhaled steroid group  and non-inhaled steroid group . Clinical visit times and treatments for oral disease were compared between the groups. Anatomical Therapeutic Chemical code R01AD was used for intranasal steroids, and R03AK and R03BA for inhaled steroids.Factors that influence oral health include sex, socioeconomic status, urbanization, dentofacial anomalies (ICD-9-CM code 524), salivary flow diseases (ICD-9-CM codes 527 and 710.2), diabetes mellitus (DM) (ICD-9-CM code 250) and esophageal reflux (ICD-9-CM codes 530.11 and 530.81) . These fSocioeconomic status was defined according to the occupation, wherein, the subjects were grouped into high-income  and low-income  groups. Based on Liu’s report , urbanizp < 0.05. Mantel-Haenszel chi-square tests stratified for different characteristics  were used to examine the potential effect modifiers among oral diseases and AR. A chi-square test was used to compare the frequencies of characteristics between groups. A modified Poisson regression analysis was used to obtain RRs for the incidence of oral diseases between the groups. Negative binominal regression was performed for assessing differences in the frequencies of oral disease and clinical treatment visits between the groups. Crude p values and adjusted p value for confounders  were calculated. Two-sided p values of <0.05 were defined as significant.All analyses were performed using SAS version 9.1 for Windows  and PASW Statistics 18 . For the five oral diseases, we assessed model calibration with the Hosmer–Lemeshow goodness of fit test. The model was regarded as no goodness of fit in case of p values for the five oral diseases were as follows: caries (0.059), periodontitis (0.038), pulpitis (0.565), gingivitis (0.303), and aphthae/stomatitis (0.074). Sex, urbanization and income was the potential effect modifiers among caries, periodontitis and AR. Sex, and income was the potential effect modifiers among gingivitis and AR. Sex was the potential effect modifiers among gingivitis and AR.Demographic data are presented in The results for incidence of oral diseases are presented in To evaluate the magnitude of AR’s influence on oral diseases, the RRs data for each demographic character and each oral disease was compared . RRs . The increased prevalence rate may imply that AR influences development of oral diseases, while increased clinical visit times mean that AR might increase the severity of oral diseases. Restoration and endodontics treatment are used for caries, periodontitis, and pulpitis; and increased treatment visit times in AR subjects make the association more certain. Among the AR subjects, men, country residents and those with high income had higher RRs for oral diseases. This might suggest that men who are country residents with a high income should pay more attention to their oral health if they also have AR.There have been more studies investigating the association between AS and caries, periodontitis and gingivitis, than on the association with AR. Many studies have reported a positive association between AS and caries , and per2-agonists (The results of several studies could explain the association between AS, AR, and oral diseases. At the mechanistic level, a decreased saliva secretion rate has been reported in both AS  and AR  subjectsagonists  could deagonists  and AR (agonists  subjectsagonists , and IgAagonists ; IL-12 magonists .Our study has several strengths. First, other studies have assessed AR or AS from past history, rather than being an existing condition at the time of study. AR and AS subjects in our study were in the active stage of allergic disease with more than two diagnoses within the study period. Studying the association between oral diseases and AR and AS during the active stage of allergic diseases is more pertinent. Second, by knowing the frequencies of clinical visits and treatment times, we could understand the influence of allergic disease on the severity of oral diseases, medical treatment, and medical costs.There are limitations to our study. First, there are no laboratory data such as oral pathogenic bacteria, IgA in oral samples/saliva and mucus. Second, there are no data on smoking habit, sugar consumption, engagement with the healthcare system, personal oral hygiene, and oral drugs. Third, the Hosmer–Lemeshow test was used to evaluate the model’s calibration. Caries, pulpitis, gingivitis and aphthae/stomatitis showed a good fit, but periodontitis did not. Future study for the association between AR and periodontitis is necessary.The present study provides evidence that AR might be associated with caries, periodontitis, pulpitis, gingivitis, and stomatitis/aphthae in young adults. Based on increased clinical visit times for the five diseases, it can be speculated that AR also increases the severity of these five oral diseases. Contrary to findings in other studies, there is no association between AS and the five oral diseases. Any association between AS and oral diseases previously found might be due to AR.Men who live in the countryside and have a high income should pay more attention to oral hygiene if they also have AR because incidence of the oral diseases was found to be higher in these demographic categories. Intranasal steroids used in AR, rather than inhaled steroids used in AS, are associated with the development of oral diseases.In order to prevent and treat oral diseases, simultaneous treatment of AR is important. Considering the effects of AR in the elucidation of the etiology of oral diseases is a new direction of study. However more studies are required to ensure whether AR is the cause of oral diseases. More biological research and more epidemiological data on the relationship between AR, AS and oral diseases are necessary in order to gain clarity.10.7717/peerj.7643/supp-1Data S1Click here for additional data file.


On JNER’s 15th anniversary, this editorial analyzes the state of the field of neuroengineering and rehabilitation. I first discuss some ways that the nature of neurorehabilitation research has evolved in the past 15 years based on my perspective as editor-in-chief of JNER and a researcher in the field. I highlight increasing reliance on advanced technologies, improved rigor and openness of research, and three, related, new paradigms – wearable devices, the Cybathlon competition, and human augmentation studies – indicators that neurorehabilitation is squarely in the age of wearability. Then, I briefly speculate on how the field might make progress going forward, highlighting the need for new models of training and learning driven by big data, better personalization and targeting, and an increase in the quantity and quality of usability and uptake studies to improve translation. With JNER turning 15, and having just finished 5 years as the second Editor-in-Chief of JNER, it seems appropriate to reflect on where the field has been and where it is headed. The purpose of this editorial, therefore, is to briefly analyze the current status and future prospects of the field of neuroengineering and rehabilitation through the lens of the papers published at JNER, as well as my own experiences in the field. In particular, I ask – “How is the nature of neurorehabilitation research evolving?” and “How might the field progress over the next 15 years?”In the last 15 years, an important way that neurorehabilitation research has evolved is that it has become increasingly familiar with and reliant on advanced neuroscience and engineering technologies. The trajectory of JNER is evidence of this integration. JNER was founded in 2004 as a “forum to discuss how neuroscience and biomedical engineering are reshaping physical medicine and rehabilitation” [One also sees this blending of technology and clinical neurorehabilitation science in what are currently the top five accessed papers over the history of the journal Fig. . The mosEven though JNER takes a relatively specialized approach to rehabilitation research by studying how cutting-edge technology might reshape rehabilitation, JNER was the top ranked journal in the rehabilitation category in Scopus for 2017. For 2018 JNER was ranked second in the rehabilitation category in Scopus and fourth in the rehabilitation category in Web of Science. Relatedly, in the U.S., the National Institutes of Health has also seen a rise in the prominence of rehabilitation research that incorporates advanced engineering tools. An analysis done in 2018 by NIH analysts found that “bioengineer or rehabilitation engineer” was the most frequently listed specialty by lead PI in the 1117 funded grant applications in the rehabilitation domain between 2007 and 2018 Fig. .Fig. 3EIn my personal observations, I have been impressed as I circulated at poster sessions at recent neurorehabilitation and neuroscience meetings. Physical and occupational therapist researchers now fluently and routinely use cutting-edge technologies – including robotics, brain monitoring and stimulation, and sophisticated data analysis techniques – to aid their research. Use of cutting-edge technologies for research by therapists was uncommon 30 years ago. In 2015, the Eugene Michels Lecture at the American Physical Therapy Association Combined Sections Meeting was titled “Rehabilitation technology: Friend or Foe?”. Then, in 2019, the American Physical Therapy Association Combined Sections Meeting hosted an educational debate: “Why we love AND hate our robots.” [Figure Better science: New technologies allow better rehabilitation science to be done because they increase the reliability of measurements, quantify things not previously measured (e.g. wearable sensing of daily activity), and allow entirely new techniques to be applied in rehabilitation (e.g. robotic error augmentation).Improved technology development: The emergence of cross-disciplinary research teams that include clinicians, users, and engineers allows crucial multi-directional information flow. Greater familiarity with clinical rehabilitation problems helps engineers better design new technologies, and greater familiarity with technology development and translation processes helps clinicians and users better communicate their vision, needs, and desires.Potentially better practice: Although uptake of new technologies in routine clinical practice is slower than uptake into research, most rehabilitation facilities are now experimenting with new technologies, and, in some cases, are finding ways to enhance their practice.This integration of technology and neurorehabilitation has several benefits spanning scientific discovery, technology development, and clinical practice, including:Of course, there are possible disadvantages to overly focusing on technology in rehabilitation research, including a narrowing of perspective, increasing cost and complexity, and discounting of important human factors. When I was beginning as a post-doctoral fellow at the Rehabilitation Institute of Chicago in 1994, I met with renowned prosthetics and assistive technology researcher Dudley Childress to discuss my goal of building a robotic device for rehabilitation therapy. He asked me, “But what about the human touch?” Understanding how rehabilitation technology can best complement the human touch – and can make all of us more human – remains a key goal. It is significant that “psychologist” (including rehabilitation psychologist and neuropsychologist) was the second most frequently listed specialty by lead PI at NIH for rehabilitation in Fig. Another way the field of rehabilitation has continued to evolve is by improving the rigor of research. A key moment was in 2014 when a consortium of rehabilitation journals began requiring the “complete and transparent reporting of research and methods” using established reporting guideline checklists . NIH hasAccess to research results is also improving. When they founded JNER, Paolo Bonato and Biomed Central were at the vanguard of the open access movement. The NIH Public Access Policy was drafted in 2004, JNER’s first year, and mandated in 2008. NIH and other funding agencies across many countries now require the research they fund to be made available to the public for free within 1 year of publication. Since JNER provides immediate, open access, any interested person around the world can read the latest research. This is particularly important for rehabilitation, because this means that inventors, persons with a disability (who may themselves be inventors as well as consumers), and rehabilitation therapists and caregivers worldwide can all interact with the latest findings. The power of the open access movement should not be underestimated – surely a larger, broader, more diverse readership will ultimately produce more innovation and greater uptake of promising methods of rehabilitation.I also want to highlight an evolution in the types of technical topics being published at JNER. I analyzed the title, abstracts, and key words of the 1231 papers published in JNER over the past 15 years for the percent of papers that use the words robot*, exo*, wear*, virtual, sensor, brain-computer, and model. The fastest growing term over the past 5 years is “exo*”, followed by “wear*” and “robot*” Fig. .Fig. 5AAnalysis of the ten most cited JNER papers published in 2017 supports this idea , a difficult and important goal. Indeed, adding actuation to orthotics has begun to improve everyday mobility. However, wearable robotic device work has also quickly became interested in the therapeutic effects of assistance. Until now, rehabilitation therapy has been something mainly done by going to a facility. With AI-enhanced, wearable devices, some aspects of rehabilitation therapy will become continuously accessible. The transition will be like what has happened with knowledge seeking – instead of going to a facility , one now frequently learns from information provided by mobile devices that we carry with us. In the same way, we will learn to move with assistance  provided by wearable devices. We will essentially be able to take a sort of “avatar” of our rehabilitation therapist with us as we move at home or in the community, thereby improving our access to rehabilitation therapy no matter where we live.The rise of wearables is evident in a second innovation – the Cybathlon competition, which was first held in 2016. As described in an editorial in JNER, Robert Riener conceived of the Cybathlon as a new sort of Olympics, in which a pilot with a disability  collaborates with a technical team to race an assistive technology (such as an FES bicycle or wheelchair) or worn device  . As can I have also been excited to see cutting-edge papers submitted to JNER on new approaches to human augmentation. JNER published the first study that demonstrated a metabolic reduction in walking of non-impaired persons using an autonomous exoskeleton  and contMy impression of movement augmentation studies is that they are putting to the test our current understanding of biomechanics and neural control in new ways. They are also bringing together a community of people with and without disabilities around a common goal – enhancing movement. This is similar to the universal design movement, which focuses on design of the built world to benefit both people with and without a disability. The movement augmentation movement  focuses on design of the worn world to benefit both people with and without a disability. Just as curb cuts spun out of universal design into general use, movement augmentation devices are spinning out of neuroengineering and rehabilitation research for general use Fig. . Look foIn light of this evolution, how might the field make progress going forward? I suggest that we need new models of training and learning driven by big data, better personalization and targeting (i.e. precision medicine), and more usability and uptake studies to improve translation.There are still tremendous opportunities to better inform rehabilitation techniques with neuroscientific findings. For example, JNER recently published a collection of papers on brain stimulation as an adjuvant therapy to increase training-related plasticity . The fieThere needs to be a critical mass of researchers focused on computational modeling of rehabilitation, identifying clinical problems where existing modeling technology can improve care. Expansion of models into new areas will require increased openness and support from key funding agencies. The technology revolution in rehabilitation is the great facilitator here, making the moment opportune: machines are helping to build the larger, finer resolution data sets needed to form and test models.We need greater sophistication in the way a rehabilitation technology is matched to each person’s impairments and goals. I mentioned the Cybathlon and movement augmentation studies above as crucibles for this sort of work. Machine learning is also a powerful tool for selecting control algorithms or treatment approaches that work best for specific individuals. In robot-assisted and other technology-assisted rehabilitation approaches, it will be increasingly important to refine methods to identify who can benefit from what type of training and why . I eTranslation remains a significant barrier limiting the implementation of new technologies in clinical practice. Users and their clinicians must be more intimately involved in teams working toward the development and testing of new technologies. Funding agencies can facilitate this by rewarding partnering of engineering and clinical rehabilitation institutions. The field needs to more rigorously document and understand the rehabilitation technology testing process by designing clinical usability studies that go beyond presenting survey results. Currently only 2.4% of the papers published in JNER use the term “usability” in the title, abstract, or keywords. It is critical to better understand what causes the slow uptake of new technologies, and to identify the best practices for incorporating new technologies into clinical practice . FurtherFifteen years ago I imagined what rehabilitation technology would look like if I had a stroke in 2036 . I won’t


This issue, the JACMP presents a Guest Editorial authored by Ehsan Samei on the planned aspirations of the future of medical physics. I invite everyone to consider the opinion below and the reference publication on which it is based — Michael Mills.use of radiation in medicine, where physicists play key roles in commissioning, inspecting, and optimizing the use of the technology. As the discipline has gradually specialized, its clinical presence has taken narrowly defined territories. This territorial definition, while professionally important, has created a constraint which is out of step with challenging needs that clinical medicine is facing, needs such as precision, personalization, and value‐based care that can be tackled by physics. As the profession is evolving, it is crucial to calibrate this evolution with the broader needs of medicine.Physics has done much in medicine. For one, it has been instrumental in the medical use of radiation, both ionizing and nonionizing. And in doing so, it has shaped the modern practice of diagnostic and therapeutic medicine. Over decades since the discovery of X‐rays, physics and physics principles have been steadily applied for continued advancement of technologies related to radiation medicine. Physics has also been present clinically and professionally in the The realities noted above necessitate a new brand of medical physics with increased focus on the precision and personalization of patient care. The focus should include areas within and beyond radiation medicine. This new horizon calls for new skills for medical physicists to be able to practice with strong competence and confidence toward clinical impact. The AAPM initiated the Medical Physics 3.0 (MP3.0) as an effort to motivate this evolution of the profession. MP3.0 is thus defined as a new inspiration for physics serving every patient. The characteristics of this movement were recently clarified in an article in Medical PhysicsYou may ask, do we really need a new brand? Aren't we already impacting patient care? Why do we need Medical Physics 3.0? To these questions, I just offer a few answers in the limited space of an editorial.Publicity: Many good things that we do already need to be better publicized. For example, a typical patient being benefited by our work should know what a medical physicist does, so do administrators who are resourcing healthcare. That is not the case today. We have an opportunity to improve this through MP3.0.consistently excellent everywhere. But to do so, we need a stronger peer expectation, an explicit regulatory mandate, better tools, and models of effective practice. We have an opportunity to improve upon these needs through MP3.0.Inconsistency: Current practice, while great in many respects, is uneven across physics practices. Many places practice at the lowest common denominator. Case in point, we don't apply the same QC rigor across the clinical practice as we do for clinical trials. Is quality and safety for clinical practice any less important than those for clinical trials? Physicists have the ability and skill to make their contributions more Relevance: We undertake many physics procedures. Some are not as relevant to medical care as others. For many we have a difficult task to relate physics results to clinical performance. In the era of value‐based care, the value of an undertaking that takes effort and expense needs to be justified. We have an opportunity to better delineate the relevance of physics in value‐based care through MP3.0.Opportunity: Medical physics has definitely done much and continue to do so in enabling and advancing radiation medicine. But medical physics is not limited to radiation physics; physics is rather present in all aspects of health, healthcare, and associated technologies. Yet physicists are rarely present outsides of the departments of radiation oncology and radiology. We have an opportunity to improve this through MP3.0.How is Medical Physics 3.0 bringing about what is needed? The ongoing activities of the initiative are orchestrated through Units, each of which is focused on fostering one of the seven “smart” aspirations of MP3.0. The term smart is used to invoke the character of intentionality, intelligence, and effectiveness in targeting the objectives of MP3.0. I encourage you to consider MP3.0 as an opportunity to make medical physics and medical physicists as relevant and as essential as they can be to healthcare. The primary reason to do so is not self‐serving, rather it is serving and advancing human health through intentionally comprehensive, integrated, and smart scholarship and practice.


The degree of lung function is frequently used as referral criterion for pulmonary rehabilitation. The efficacy of pulmonary rehabilitation was assessed in 518 chronic obstructive pulmonary disease (COPD) patients, after clustering based on a comprehensive pre-rehabilitation lung function assessment. Mean improvements in dyspnea, exercise performance, health status, mood status and problematic activities of daily life after pulmonary rehabilitation were mostly comparable between the seven clusters, despite significant differences in the degree of lung function. The current study demonstrates no significant relationship between the seven lung-function-based clusters and response to pulmonary rehabilitation. Therefore, baseline lung function cannot be used to identify those who will respond well to pulmonary rehabilitation, and moreover, cannot be used as a criterion for referral to pulmonary rehabilitation in patients with COPD. Pulmonary rehabilitation, defined as a comprehensive non-pharmacological intervention, is generally very effective in patients with chronic obstructive pulmonary disease (COPD) . Indeed,In daily practice and in clinical trials, the degree of airflow limitation is frequently used as an indicator for referral for pulmonary rehabilitation . HoweverRecently, the heterogeneity of respiratory impairment in patients with COPD has been illustrated by the respiratory physiome, in which patients are clustered on multiple lung function attributes . WhetherThis is an observational, prospective, single-center study about COPD, health status and cardiovascular comorbidities in relation to the outcomes of pulmonary rehabilitation (the CHANCE study) . This stPatients with COPD referred by chest physicians for a comprehensive pulmonary rehabilitation program at CIRO  were included. CIRO is a third line rehabilitation center in Southern Netherlands. It specializes in offering individualized and multidimensional rehabilitation programs to patients with complex respiratory diseases. Only patients with COPD were included, and all patients gave written informed consent.2)) were included. Before and after a 40-session comprehensive multidimensional pulmonary rehabilitation program, patients underwent an assessment of lung function and health status characteristics [2), carbon dioxide (PaCO2) and oxygen saturation (SO2). Seven different clusters of lung function impairment could be identified as described in a previous paper [p < 0.01). Cluster 5 had a significantly lower degree of airflow limitation compared to Clusters 6 and 7 (p < 0.01). Static lung volumes were significantly different between Clusters 5 to 7 . Diffusing capacity of the Lung for Carbon Monoxide (DLCO) was higher in Clusters 1, 4 and 5; lower in Clusters 3, 6, and 7, p < 0.01 and mouth pressures were higher in Clusters 1, 3, 4, and 6; lower in Clusters 2, 5, and 7, p < 0.01. Arterial blood gas values were within normal range in Clusters 1–6 [In total, 518 COPD patients ; 72% stratified into group D of the Global initiative for Chronic Obstructive Lung Disease (GOLD D); mean body mass index (BMI) 26.2  were inters 1–6 .The efficacy of pulmonary rehabilitation  was meas−1) or outpatient . The program starts with a careful characterization of pulmonary and extra-pulmonary treatable traits in patients with COPD. From this, a patient-tailored program consisting of different treatment modules is composed. Each module consists of different interventions; physical exercise training, occupational therapy, nutritional counselling, psychosocial counselling, education and exacerbation management. Each module has a specific goal, which once achieved, contributes to the patients’ overall goal(s) of the treatment [The pulmonary rehabilitation program was provided in accordance with the 2013 American Thoracic Society/European Respiratory Society Statement on pulmonary rehabilitation . The proreatment .All statistical analyses were performed using Viscovery Profiler 7.1 by Viscovery Software GmbH, Vienna, Austria. Information available online . Self-orSimultaneously, the efficacy of the pulmonary rehabilitation program was evaluated for each cluster based on the minimal clinically important difference (MCID). The following MCIDs were used: −1 grade on MRC dyspnoea scale ; +30 m op-value of ≤0.01 was set as the level of significance.SGRQ-T . For comA total of 419 of the 518 patients (80.9%) completed the rehabilitation program. Patients in Cluster 2 showed a significantly higher dropout rate compared to the whole sample . In all This is the first report on the efficacy of pulmonary rehabilitation in patients with COPD after clustering for a comprehensive lung function assessment. The results demonstrate that the degree of baseline lung function poorly predicts individual improvements in breathlessness, exercise performance, problematic activities of daily living, mood status and disease-specific health status following pulmonary rehabilitation. Even in those with the most severe respiratory impairment , clinically relevant improvements were achieved. Nevertheless, one-third of the patients in Cluster 2 did not complete the program. Why patients within this cluster seem more at risk for drop-out is currently unknown and needs further evaluation.Based on 65 randomized clinical trials involving 3822 patients for inclusion in the meta-analysis, McCarthy and colleagues concluded that pulmonary rehabilitation relieves dyspnea and fatigue, improves emotional function and enhances the sense of control that individuals have over their condition. Moreover, pulmonary rehabilitation is beneficial in improving health status and exercise capacity .Since quality of life is determined by the degree of dyspnea, depression, anxiety and exercise performance , these fOur study confirms that a comprehensive pulmonary rehabilitation program results in a heterogeneous and differential pattern of patient-related outcomes. This confirms our previous study, that a multidimensional response needs to be considered to evaluate the efficacy of pulmonary rehabilitation services . FurtherPulmonary rehabilitation requires multidimensional profiling of patients, not restricted to pathophysiological respiratory system involvement. Future identification of essential components of pulmonary rehabilitation should be based on a personomic perspective . ComprehThe current study demonstrates no relationship between the seven lung-function-based clusters and response to pulmonary rehabilitation in patients with COPD. Therefore, baseline lung function cannot be used to identify good responders to pulmonary rehabilitation, and therefore, cannot be used as a criterion for referral to pulmonary rehabilitation in patients with COPD.


Despite highly toxic treatments, head and neck squamous cell carcinoma (HNSCC) have poor outcomes. There is an unmet need for more effective, less toxic therapies. Repurposing of clinically-approved drugs, with known safety profiles, may provide a time- and cost-effective approach to address this need.in vitro assays  and in vivo models (xenograft tumors in NOD/SCID/gamma mice).We have developed the AcceleraTED platform to repurpose drugs for HNSCC treatment; using In vivo, daily treatment with 100 mg/kg oral quinacrine plus cisplatin significantly inhibited tumor outgrowth, extending median time to reach maximum tumor volume from 20 to 32 days (p< 0.0001) versus control, and from 28 to 32 days versus 2 mg/kg cisplatin alone. Importantly, combination therapy enabled the dose of cisplatin to be halved to 1 mg/kg, whilst maintaining the same impairment of tumor growth. Treatment was well tolerated; murine plasma levels reached a steady concentration of 0.5 μg/mL, comparable to levels achievable and tolerated in humans.Screening a library of clinically-approved drugs identified the anti-malarial agent quinacrine as a candidate, which significantly reduced viability in a concentration dependent manner in five HNSCC cell lines (IC50 0.63–1.85 μM) and in six primary HNSCC samples (IC50 ~2 μM). Decreased clonogenic survival, increased apoptosis and accumulation of LC3-II  were also observed. Effects were additional to those resulting from standard treatments (cisplatin +/– irradiation) alone. Consequently, due to its favorable toxicity profile and proven safety, quinacrine may be particularly useful in reducing cisplatin dose, especially in frail and older patients; warranting a clinical trial. Head and neck squamous cell carcinoma (HNSCC) is a debilitating disease comprising 600,000 cases per year worldwide . For advRepurposing existing drugs for cancer therapy can be valuable due to known safety profiles leading to higher success rates and reduced development times, and subsequently lower costs compared with the development of novel therapeutics. The time taken to gain clinical approval for repurposed drugs is usually considerably shorter (3–12 years vs 10–17 years for novel therapeutics) , and sucWe established a multi-stage drug discovery and repurposing platform called AcceleraTED. On initial screening against HNSCC cell lines, quinacrine was identified as a potential hit. Quinacrine, also known as mepacrine, was initially utilized as an antimalarial agent as early as the 1930s and is considered safe, with only minimal side effects, such as headaches and gastrointestinal upset . QuinacrThe mechanisms through which quinacrine exerts its anticancer effects are not fully understood. Quinacrine is a potent late-stage autophagy inhibitor  and has Due to promising results from high throughput screening and the supportive literature, we sought to advance the repurposing potential of quinacrine as an anti-cancer therapy for HNSCC.The Prestwick library of 1280 FDA-approved drugs was initially screened at 10 μM using a high-throughput microplate platform. We identified the potential hits and completed a confirmatory screen in CAL27 and VU147 cells , that re50 values for cell lines tested ranging from 0.63 to 1.21 μM  was exposed to a range of quinacrine concentrations. The resulting concentration-response curves illustrate that quinacrine effectively inhibits cell viability in a concentration dependent manner  with IC5 1.21 μM  and 1D, 50: 2, 3 or 10 μM), compared to quinacrine alone (–4 M) or above resulted in dramatic suppression of viability of all cell lines, such that additional suppression by the addition of quinacrine was not possible. For example, when treated with a cisplatin concentration of 0.3 μM (3 × 10–7 M) alone, SCC040 showed cell viability suppression of 12%, compared to suppression of 17%, 48% and 79% following the addition of 0.4, 1.5 and 3 μM quinacrine to 0.3 μM cisplatin, respectively. In comparison, at a cisplatin concentration of 0.1 mM (10–4M), cell viability was reduced by cisplatin alone by 90%, with only marginal additional suppression by increasing doses of quinacrine.HNSCC cell lines showed additional suppression of cell viability when quinacrine was combined with cisplatin . Dose reduction indexes (DRI) refer to the amount that one drug can be reduced by to maintain the same cell viability reduction, termed the fraction affected (Fa)  . DRI valin vitro exhibited similar responses to quinacrine to those observed for the cell lines, with a mean IC50 of ~2 μM  (When comparing the sensitivity of primary HNSCC cultures to the different cell lines at 1 μM quinacrine (10–6 M) , primaryThe primary cell cultures showed additional suppression of cell viability when 2 μM cisplatin was added to quinacrine . As descClonogenic assays were used to assess whether differences in viability were due to reduced clonogenic survival of HNSCC cells. All four cell lines  tested demonstrated a concentration-dependent reduction in survival fractions when treated with increasing concentrations  of quinacrine  and 3B. p< 0.05) at quinacrine concentrations equal to or lower than 1.2 μM. This is due to the large reductions in clonogenic survival caused by higher doses of quinacrine, such that radiotherapy and cisplatin could not cause significant additional reductions in survival.Further reductions were also evident upon the addition of 0.25 μM cisplatin and 0.5 Gy irradiation (Cis-IR) to 1.2 μM quinacrine . HoweverTo understand the mechanisms of quinacrine-induced cell death in HNSCC cell lines, we first investigated apoptosis using the Annexin V apoptosis assay. The table in CAL27, SCC040, SCC47 and FaDu cells were exposed to cisplatin alone (2 μM and 10 μM), increasing concentrations of quinacrine  alone or a combination of increasing quinacrine concentrations and 2 μM cisplatin for 48 hours prior to Annexin V/PI quantification. CAL27, FaDu and, to a lesser extent, SCC040 cells showed a dose-dependent increase in Annexin V positive and PI positive cells with increasing quinacrine concentrations . FaDu ceThe ability of quinacrine to mediate autophagy has been shown in other cancer types, but not in HNSCC to date. We therefore analyzed LC3 levels to determine whether quinacrine affects autophagic flux within CAL27 and SCC040 cells . LC3-I iCells were exposed to cisplatin alone, quinacrine at 1.2, 1.8 and 2.4 μM alone or 1.8 μM quinacrine plus 2 μM cisplatin for 48 hours. Expression of LC3-I and LC3-II was then determined by Western blotting. Both cell lines displayed a dramatic increase in LC3-II at all concentrations of quinacrine treatment tested –5B, wherWe assessed p53 expression in both SCC040 and CAL27 cell lines following 48 hours exposure to quinacrine  alone and with 1.8 μM quinacrine + 2 μM cisplatin to assess the potential influence of p53 on apoptosis in these cell lines. CAL27 cells possess a mutation in p53, rendering it non-functional . They dep = 0.0001)  via intraperitoneal injection on days 4, 8 and 12. Tumor volumes at day 19, when the first control animal was culled, show reductions in the size of treated tumors, mainly in those treated with quinacrine and 2 mg/kg cisplatin ( 0.0001)  and 6B.3 (p< 0.0001), and was also significantly higher than the time taken to reach maximum tumor volume in the group treated by quinacrine alone, from 22 days to 32 days (p = 0.0002). There was a difference in the time needed to reach maximum tumor volume between the combined quinacrine and 2 mg/kg cisplatin group and the 2 mg/kg cisplatin alone group of 4 days, however this did not reach statistical significance (p = 0.6), possibly due to the small sample size and corrections for multiple comparisons.Quinacrine alone showed early inhibition of tumor growth, and modestly extended the mean time needed to reach maximum volume by 2 days (from 20 to 22 days), compared to untreated control  and 6C. The Kaplan-Meier plot  further in vitro experiments demonstrated that the synergy between quinacrine and cisplatin was highest at lower doses of cisplatin, where quinacrine potentiated the effect of cisplatin most. At higher concentrations of cisplatin tumor kill was so high that there was little possibility for quinacrine to add an effect. We therefore also tested the combination of quinacrine with a lower dose of cisplatin . At that concentration, quinacrine and 1 mg/kg cisplatin resulted in the same growth rate as 2 mg/kg cisplatin alone, indicating that by adding quinacrine, the dose of cisplatin can be halved whilst maintaining the same anti-cancer efficacy, which could have significant benefits to patients by reducing toxicity related side effects.Importantly, the in vivo experiment. The weights of mice remained well within the 20% weight loss cut-off . Analysis carried out by LC-MS  revealed that even 48 hours after the last dose, plasma concentrations of 0.5 mg/mL were still present , equatins tested –1D and is tested .To establish whether quinacrine successfully entered tumors from the blood, sections were taken and quinacrine fluorescence visualized at 488nm. Tumor samples from mice receiving quinacrine treatment showed clear fluorescence throughout their tumors, whereas those receiving only control treatment did not ; thus coin vitro quinacrine  reduces viability of head and neck cancer (HNC) cell lines and primary cultures, decreases clonogenic survival, increases apoptosis and inhibit autophagy. Importantly, effects were in addition to those resulting from standard treatment (cisplatin +/– irradiation), and importantly we have demonstrated synergy of quinacrine with cisplatin.Our data support the use of quinacrine as a potential treatment option for HNSCC. We have shown that Quinacrine’s ability to promote apoptosis of cancer cells has been previously reported and mechanisms for this have been suggested. Firstly, it is thought that quinacrine enhances the binding of the TRAIL ligand to Death Receptor 5 (DR5) via formation of a stable quinacrine-TRAIL-DR5 complex . In addiThe divergent proportions of apoptosis seen between the HNC cell lines in this study may be due to intrinsic differences in the expression of proteins within the apoptotic pathway. For example, the poor prognostic marker and anti-apoptotic protein, MCL1 (Myeloid Cell Leukemia Sequence 1 [BCL2-related]), is a target of quinacrine, as shown in anaplastic thyroid cancer . Low MCLQuinacrine has previously been shown to cause the build-up of dysfunctional autolysosomes as evidenced by accumulated LC3-II . Our stuIn vivo quinacrine treatment was well tolerated and data presented here is the first to show that quinacrine, at clinically achievable concentrations is able to reduce tumor burden in mice, extending median time to reach maximum tumor volume. Analysis of plasma concentrations levels of quinacrine during these studies showed a steady state blood plasma concentration of around 0.5 mg/ml (~ 1.25 μM). This is a concentration at which all cells tested in vitro were responsive to quinacrine, including primary tumor cells from HNSCC patients. Due to its relatively long half-life (5–14 days) quinacrine is maintained at a therapeutic dose 48 hours after dosing, indicating a large treatment window allowing for flexible dosing schedules . Stage two validates the findings of the initial screen using a panel of well-characterized HNSCC cell lines and then assesses concentration responses, clonogenic survival, and the ability of compounds to induce apoptotic cell death and autophagy. Stage three further validates results by assessing concentration-response curves using primary cell cultures grown directly from HNSCC patients. The fourth stage undertakes in vivo testing, whereby initial toxicity is established, followed by evaluation of efficacy against HNSCC xenograft tumors. Following successful completion of these stages, stage five intends to test the safety of compounds in combination with standard treatment in early-phase clinical trials.The platform consists of five main stages, each with go/no go criteria to allow progression of a hit to the next stage: The first stage utilizes a high-throughput alamarBlueMore detail on individual assays is given below. All experiments represent a minimum of at least three independent repeats, as indicated.All drugs and chemicals were sourced from Sigma (now Merck) unless otherwise stated. Concentrations used were based upon clinically-achievable concentrations described previously in the literature based on clinically prescribed doses. Solubility information was taken from documentation accompanying the drug library or PubChem.The human papillomavirus (HPV) negative cell lines CAL27 , SCC040  and FaDu (ATCC HTB-43), and HPV positive cell lines SCC47  and VU147  were used. The cell lines were cultured using Dulbecco’s Modified Eagle’s Medium-HEPES Modification (DMEM) supplemented with 10% fetal bovine serum (FBS), 1% L-glutamine, 1% penicillin/ streptomycin and 1% non-essential amino acids (NEAA) at 37°C. All cell lines were verified mycoplasma negative every six months, along with annual authentication via Short Tandem Repeat (STR) profiling.Tumor biopsies were obtained from HNSCC patients undergoing diagnostic biopsy or tumor resections, and who were consented under the Human Research Authority (HRA) Human Tissue Act 2004 ethics approval number 16/NW/0265. Tissue samples were collected and within 30 minutes washed five times in transport medium . Following washing, the tissue was disaggregated using sterile scalpels, transferred to serum-free media (SFM) (as part of a kit including BPE and EGF), supplemented with 50 μg/mL penicillin/ streptomycin, 50 μg/ml gentamicin, 5 μg/mL amphotericin B and 10 μM ROCK inhibitor (Y-27632)  and grown on rat tail collagen (8 μg/mL) coated plates at 37°C. After 24 hours, media was replaced and cells left for 7 days to assess growth.® (Invitrogen) cell viability assay was utilized to measure the relative viability of cells as a measure of proliferation. AlamarBlue® contains a blue dye called resazurin that changes to a pink, highly fluorescent form in the presence of metabolically active cells, giving a quantitative measure of the relative number of viable cells. Cells were seeded in 96 well plates at pre-optimized densities. After 24 hours, appropriate treatments were added to wells and cells were incubated for a further 68 hours (cell lines) or 92 hours (patient-derived primary cells). These time differences reflect the growth rate of cells and allow for the time required to undergo two cell divisions. Cells were then incubated for 4 hours with 20 μL  alamarBlue® reagent per well. Fluorescence was then measured at 550 nm. All relative fluorescence unit (RFU) values were normalized by deducting values from paired plates containing only media and drug (but no cells) and plotted as a percentage of untreated. All assays were carried out in triplicate and the mean values calculated.The alamarBlue® was used for the initial screen for this study. The library consists of 1280 FDA/EMA approved, off-patent drugs [® cell viability assay on at least 2 HNSCC cell lines for each drug.The Prestwick Chemical Librarynt drugs . For themax (or lower) values in alamarBlue® cell viability assays using CAL27 (HPV-) and VU147 (HPV+) HNSCC cell lines. Again, hits were confirmed as compounds that reduced cell viability by 50% or more compared to untreated controls.Those drugs achieving at least 50% suppression of cell viability in both cell lines were considered promising and subsequently analyzed in a secondary confirmatory screen using C®. In addition, response to increasing cisplatin concentrations in combination with 0, 0.4, 1.5, 3 and 6 μM quinacrine was also assessed. Each experiment was carried out in triplicate and normalized to untreated control wells containing only media and drug.Concentration-response curves were generated for quinacrine for each of five HNSCC cell lines and on patient-derived primary cells, following treatment with both quinacrine alone and in combination with cisplatin using alamarBlue50 values. Cells were exposed to drugs for 72 hours and cell viability was quantified using alamarBlue®. The optimal ratio was found to be a 1 to 4 ratio of quinacrine to cisplatin. Chou-Talalay analysis was then carried out using CompuSyn software . This calculates the fraction affected (Fa), a combination index (CI) and dose-reduction index (DRI). In our experiments, the dose reduction index refers to how many times the dose of one drug can be reduced when in combination with another drug and still elicit the same efficacy. A combination index value less than one is indicative of a synergistic effect; a value of one infers additivity and values above one suggest sub-additive responses.CAL27, SCC040 and SCC47 cells were plated in 96 well plates and exposed to fixed ratios of quinacrine and cisplatin in relation to their ICTo assess the survival of HNSCC cells and their ability to proliferate to produce clonal colonies following 24 hour drug exposure, clonogenic assays were utilized. CAL27, SCC040, FaDu and SCC47 cells were plated at optimized seeding densities in 10 cm plates and treated 24 hours later with a range of quinacrine concentrations +/– 0.25 μM cisplatin and 0.5 Gray irradiation. Culture medium was replaced after a further 24 hours and then the cells were left to establish colonies in the absence of any treatment. After 10–14 days depending on the cell line, colonies were stained using crystal violet (0.5% w/v), containing glutaraldehyde (6% v/v). Colonies were counted using Image J software. Due to the nature of growth of SCC47 growth, with less dense colonies, plates could not be analyzed on Image J and were counted manually. Plating efficiency was calculated by dividing the number of colonies formed by the number of cells seeded, which was then used to determine the survival fraction of each treatment normalized to the untreated control.5 × 105 CAL27; 1 × 105 SCC040; 1.4 × 105 FaDu; 3 × 105 SCC47. Drug treatments were added 24 hours later. After 48 hours incubation, cells were harvested and analyzed using Annexin V-Cy5  and the Dead Cell Apoptosis Kit  as per manufacturer’s instructions. The percentage of apoptotic cells was determined by Annexin V-Cy5 positivity using flow cytometry. From each sample, 30,000–50,000 events were recorded using an LSR II flow cytometer . Quantification as a percentage of the overall live and dead cell populations was carried out using Kaluza Software .The ability of quinacrine to induce apoptosis was investigated using Annexin V/ propidium iodide (PI) assays. The Annexin V antibody binds to phosphatidylserine on the outer surface of cells undergoing apoptosis. PI is added to highlight all dead cells, regardless of mechanism of cell death. CAL27, FaDu, SCC040 and SCC47 cells were seeded in 6 well plates at the following number of cells per well: 16 CAL27 or SCC040 cells per plate. After 24 hours, the appropriate drugs were added to the plates. Forty-eight hours after the addition of drugs, cells were harvested in RIPA buffer (Thermo Scientific) supplemented with protease and phosphatase inhibitors and EDTA (Thermo Scientific). Membranes were exposed to primary antibodies diluted in 5% BSA-TBS-T as follows: LC3 1:500 ; β-actin 1:5000 (Abcam ab15580); p53 1:1000 ; p211:1000 . Following overnight incubation, membranes were exposed to anti-rabbit secondary antibody 1:5000  or anti-mouse secondary antibody 1:1000  as appropriate and imaged using a ChemiDoc Imaging system. Densitometry was carried out using ImageJ software. LC3-II accumulation following treatment was used to indicate the impairment of cells to complete autophagy and therefore accumulate autophagosomal markers.To investigate the effect that quinacrine exerts on autophagy, protein expression of the autophagy marker, Microtubule-associated proteins 1A/1B Light Chain 3B (LC3), was assessed by immunoreactivity Western blotting. All reagents were obtained from BioRad unless otherwise stated. Expression of the tumor suppressor protein, p53, was also visualized. Ten cm plates were seeded with 1.2 × 10in vivo validation stage of the AcceleraTED platform, we examined overt toxicity and the anti-tumor efficacy of quinacrine, alone and in combination with cisplatin. Male NOD/SCID/gamma (NSG) mice (Charles River) were kept in 12 hour light and 12 hour dark cycles in individually ventilated cages. All procedures were carried out in accordance with the UK Home Office Animal (Scientific Procedures) Act 1986 and approved by the local University of Birmingham Ethical Review Committee. Mice were maintained on mouse feed and water, ad libitum, and were at least 6 weeks old at the start of treatment.In the fourth, 6 FaDu HNSCC cells, suspended in serum-free medium, by subcutaneous injection into the right flank. Tumors were given three days to become established, at which point mice were randomly allocated into five treatment groups as follows: (1) control (PBS); (2) 200 mg/kg quinacrine dissolved in PBS via daily oral gavage from day 4 onwards; (3) 2 mg/kg cisplatin dissolved in PBS given via intraperitoneal (IP) injection on days 4, 8 and 12; (4) 1 mg/kg cisplatin with 200 mg/kg quinacrine as in groups two and three; (5) 2 mg/kg cisplatin with 200 mg/kg quinacrine as in groups two and three. Animals were monitored daily for signs of ill health. Tumor measurements were taken using calipers and volumes calculated using the formula L × W2.NSG male mice were implanted with 5 × 103. Tumors were then excised and paraffin-embedded or frozen for subsequent analysis. Each group contained 6–8 animals. When displaying tumor growth over time, to gain an understanding of efficacy over a longer period, data was plotted until at least 5 animals per group remained. When fewer animals remained in a group, no more data were plotted. Data from all animals, however, were included when summarizing tumor volumes at day 19 and displaying time taken to reach maximum tumor volume (MTV).Mice were culled once tumors reached a maximum of 1250 mmTo quantify minimum steady state plasma levels of quinacrine, up to 100 μL blood was taken from the tail vein of each animal 48 hours after the last oral dose at the end of the second week of dosing during toxicity experiments. Samples were spun for 10 minutes at 123 × g to separate the plasma, which was stored at –80ºC until analysis.Blood was taken from mice 48 hours following their ninth dose of quinacrine (day 19 of the toxicity study) via saphenous vein bleed. Blood was then centrifuged at 500 × g to separate plasma from cells. Plasma levels of quinacrine were quantified using ultra-high performance liquid chromatography (HPLC) combined with mass spectroscopy (MS) . For detailed methods, see Supplementary Appendix.To establish whether quinacrine was able to penetrate into tumor tissue, fresh frozen tumors were sectioned using a cryostat  and mounted using anti-fade mountant  containing DAPI . The fluorescence caused by quinacrine was then imaged at 488 nm using an epifluorescence microscope.Data were represented as mean ± standard error of the mean (SEM) unless otherwise described. One-Way ANOVA followed by Dunnett’s or Tukey’s corrections for multiple comparisons was used to analyze all data other than for clonogenic analysis, which utilized Two-Way ANOVA. Each treatment value was compared to that of the appropriate control as indicated in the figures. Relative changes were calculated by dividing the value of the drug-treated sample by that of the untreated sample. Kaplan-Meier analyses were used to show differences in survival between all groups. A Mantel-Haenszel test was carried out to calculate the hazard ratios of death for the different treatments on tumor-bearing mice. All statistical analysis was completed using GraphPad Prism 6.


Player evaluation plays a fundamental role in the decision-making processes of professional sporting organisations. In the Australian Football League, both subjective and objective evaluations of player match performance are commonplace. This study aimed to identify the extent to which performance indicators can explain subjective ratings of player performance. A secondary aim was to compare subjective and objective ratings of player performance. Inside Football Player Ratings (IFPR) and Australian Football League Player Ratings were collected as subjective and objective evaluations of player performance, respectively, for each player during all 1026 matches throughout the 2013–2017 Australian Football League seasons. Nine common player performance indicators, player role classification, player age and match outcomes were also collected. Standardised linear mixed model and recursive partitioning and regression tree models were undertaken across the whole dataset, as well as separately for each of the seven player roles. The mixed model analysis produced a model associating the performance indicators with IFPR at a root mean square error of 0.98. Random effects accounting for differences between seasons and players ranged by 0.09 and 1.73 IFPR each across the five seasons and 1052 players, respectively. The recursive partitioning and regression tree model explained IFPR exactly in 35.8% of instances, and to within 1.0 IFPR point in 81.0% of instances. When analysed separately by player role, exact explanation varied from 25.2% to 41.7%, and within 1.0 IFPR point from 70.3% to 88.6%. Overall, kicks and handballs were most associated with the IFPR. This study highlights that a select few features account for a majority of the variance when explaining subjective ratings of player performance, and that these vary by player role. Australian Football League organisations should utilise both subjective and objective assessments of performance to gain a better understanding of the differences associated with subjective performance assessment. Player evaluation plays a fundamental role in the decision-making processes of professional sporting organisations, including player monitoring, team selection, player contracting and scouting –3. DespiAustralian Rules football (AF) is a dynamic invasion team sport played on a large oval field between two opposing teams consisting of 22 players each (18 on the field and four interchange). Due to the dynamic nature of the sport and the complex interactions which occur in AF, individual performance is difficult to analyse, both subjectively and objectively , 10. Deshttps://supercoach.heraldsun.com.au/). The latter takes an alternate approach to most player performance rating systems, and is based on the principle of field equity. In this system, each action is quantified relative to how much the action increases or decreases their team’s expected value of scoring next [Various objective player performance measures also exist for commercial purposes. Examples include the ‘AFL Player Rankings’ and the ‘AFL Player Ratings’, which are both produced by statistics provider Champion Data . The former takes a similar approach to that of Stewart, Mitchell , howevering next . A playeing next .Subjective analyses of performance are also commonplace within the AFL. Examples include the AFL Coaches Association award and the AFL’s award for the fairest and best player . Votes for each of these awards are cast at the conclusion of each match, based on the players deemed most influential during the match. Votes for the AFL Coaches Association award are cast by the senior coaches from both competing teams, and votes for the fairest and best player are cast by the field umpires. Further, various clubs use subjective coach ratings as a way of determining club based awards , and varA common criticism of player performance evaluation in AF, as well as other team sports , is their bias towards players whose specific role involves being more frequently involved in the play, enabling their actions to have a more tangible effect on performance evaluation , 17. TheDespite frequent studies in the team sport notational analysis literature looking to encourage the use of objective performance rating systems , 19, 20,In AF, the majority of research on evaluating player performance has had a specific focus on assessing performance indicators in order to explain or predict playing performance , 23–26. This study aimed to identify the extent to which performance indicators can explain subjective ratings of player performance in the AFL. A secondary aim was to compare subjective and objective ratings of player performance. The rationale for this study was to identify the relationship between subjective ratings of performance and the most basic comprehendible performance indicators, in order to add to the existing understanding of the extent to which human decisions are related to measurable aspects of a player’s performance. The methodologies are expressed as an exemplar of what could be implemented within professional AF organisations using their own specific subjective rating processes. An understanding of these insights could be beneficial in supporting organisational decisions relating to weekly team selection, player recruitment, as well as player contracting and financial remuneration; each which have ramifications on team outcomes.Two separate measures of player performance were collected for each player during 1026 matches played throughout the 2013–2017 AFL seasons. This included 22 matches played by each team during the regular season, as well as a total of nine matches played throughout the finals series each season. One match was abandoned prior to play during the 2015 season. Further, the eight drawn matches that occurred throughout the 2013–2017 seasons were removed from the analyses.http://www.aflplayerratings.com.au, which is a subjective measure of player performance, rated continuously from zero to ten, based on human interpretation of a player’s performance . The ratings for each match were completed by a single AFL accredited journalist who was covering the game for Inside Football (most of whom had 10+ years in the industry). The journalist covering the game was at the ground in the majority of instances, and ratings were provided immediately post-match. The AFL Player Ratings were acquired from Champion Data , which is an objective measure of player performance, rated on an open-ended continuous scale, and based on the principle of field equity [http://www.afl.com.au/stats, for each player and match included in the dataset. These indicators were selected due to being widely reported and available, as well as being previously reported in the literature [The Inside Football Player Ratings (IFPR) were obtained from d equity . The ratd equity . The vald equity , and thed equity . Nine plterature , 11, 28.Hmisc package [Descriptive statistics (mean and standard deviation) were calculated for each of the two player rating measures, as well as for each respective player role. To determine the variation between the two rating systems, as well as each of the playing roles, the coefficient of variation was calculated for each. To determine the level of association between the two player rating systems and each of the features univariately , correlational analyses were undertaken. This analysis was undertaken using the  package  in the R package , and vislme4 package [A linear mixed model analysis was undertaken to determine the extent to which each of the features explained IFPR. This particular approach was used to control the variability created by the repeated measures on each player. This analysis was undertaken using the  package . All facrpart package, which uses the CART algorithm (classification and regression trees) [A recursive partitioning and regression tree model , 37 was n trees) . A minimA comparison of the IFPR and AFL Player Ratings was created for two specific players as a practical decision support application. Specifically, the deviation of each player’s season mean ratings was compared to the overall sample mean for each rating system. This application allowed for a descriptive analysis and visualisation of the difference in evaluation between the subjective and objective systems.r = 0.60) between the AFL Player Ratings and the IFPR. Further, the IFPR and marks both showed moderate associations (r = 0.64 and r = 0.53) with kicks. All of the remaining associations were r < 0.50 and are outlined in Figs Descriptive statistics of each player role for both the IFPR and the AFL Player Ratings measures are presented in p < 0.001), with kicks and handballs having the highest Beta coefficients of 0.844 and 0.646, respectively. The model produced a root mean square error of 0.98 in association with the IFPR. The random effect accounting for the difference between seasons ranged by 0.09 IFPR across the five seasons, indicating minimal variation. The random effect accounting for differences between players ranged by 1.73 IFPR across the 1052 players, indicating that the mixed model varied substantially in its ability to explain player performance for all players.The results of the linear mixed model are outlined in The full recursive partitioning and regression tree model is presented in This study aimed to identify the extent to which performance indicators can explain subjective ratings of player performance. A secondary aim was to compare subjective and objective evaluations of player performance. To achieve the primary aim, two separate models were fit identifying the relationship between our exemplar subjective rating system, the IFPR, and the selected performance indicators. To achieve the secondary aim, a descriptive analysis and visualisation was conducted to outline the potential discrepancies noted between subjective and objective evaluations of player performance. Together, these methodologies are expressed as an exemplar of what could be implemented within professional AF organisation using their own specific subjective rating processes.Inspection of the coefficient of variation for each playing role, and the descriptive statistics outlined in Both the linear mixed model and recursive partitioning and regression tree models provide an objective view of how subjective analyses of performance are explained. Each of the models reflect the results of the other, and outline that when explaining subjective assessment of performance, a small number of features account for a large majority of the variance. The changes seen in the recursive partitioning and regression tree model once analysed separately by position supports the notion that specific indicators differ between playing roles, indicating that controlling for player role when explaining player performance subjectively is important, to account for the roles specific to each positional group . FurtherThe recursive partitioning and regression tree model provides a visual representation of what performance indicators subjective raters tend to associate with better or worse performances. This is particularly visible by conceptualising the explanations of the highest and lowest IFPR values within each of the trees . Whilst we observe that for the more frequently occurring IFPR outcome variables, performance rating can be explained in various ways, by various combinations of associated performance indicators. However, despite each recursive partitioning and regression tree (full model and player role specific models) incorporating six or more of these features, explanation of performances which are associated with highest or lowest IFPR values are explained by just the features kicks, handballs and one or two other features for all player roles, except rucks which has three other features. This explanation of performance associated with the highest and lowest ratings aligns with previous research, whereby subjective evaluation of performance has been shown to rely on the presence of noticeable features that are specific to a player’s role, and are easily brought to mind , 40. ForApplications of these models have the potential to be beneficial in supporting the decision making processes in professional AF organisations. Figs In an applied setting, these findings advocate for performance evaluators and key decision makers  to utilise both types of evaluations, and to be aware of their differences. Further, it also encourages the need for these key decision makers to be aware of the various reasons which could account for these differences, as well as the tendencies of the subjective performance assessors. As an example, the objective measure may not capture and fully account for certain aspects of the game, such as off-ball defensive acts, which would be important to know when evaluating individual players who have a specific role to negate an opposition player. Alternately, the subjective assessor may be prone to certain biases, such as a personal bias, and may consistently under- or over-rate certain players.Some limitations of this study should also be noted. Though the mixed model approach in this study was able to account for repeated measures in the dataset, the recursive partitioning and regression tree model did not. Despite this limitation, as the results of the linear mixed model indicated minimal effects from the repeated measures variables, the recursive partitioning and regression tree model was subsequently used due to its interpretability as an applied application, and its ability identify non-linear trends. Another limitation is that not all available performance indicators were used to construct the models. Future research could look to include these, as well as other factors such as anthropometric features to further analyse subjective ratings of player performance in AF. Specifically, future research should target the subjective ratings of key decision makers within applied sporting organisations , to further understand the validity and reliability of their organisational decision making processes.The models developed in this study provide an explanation of subjective analyses of performance in AF. Specifically, it demonstrates that subjective perceptions of performance can be somewhat accurately explained whilst considering a small number of performance indicators specific to a player’s role. Further, though there is an ongoing development of objective data and player performance measures in both AF and wider team sport literature, the results of this study support the notion that overall player performance evaluations should consider both subjective and objective assessments in a complementary manner to accurately evaluate player performance.S1 Dataset(XLSX)Click here for additional data file.S1 FigTerminal node variables outline the model-expected Inside Football Player Rating. Decimals indicate the absolute classification rate at the node.(TIF)Click here for additional data file.S2 FigTerminal node variables outline the model-expected Inside Football Player Rating. Decimals indicate the absolute classification rate at the node.(TIF)Click here for additional data file.S3 FigTerminal node variables outline the model-expected Inside Football Player Rating. Decimals indicate the absolute classification rate at the node.(TIF)Click here for additional data file.S4 FigTerminal node variables outline the model-expected Inside Football Player Rating. Decimals indicate the absolute classification rate at the node.(TIF)Click here for additional data file.S5 FigTerminal node variables outline the model-expected Inside Football Player Rating. Decimals indicate the absolute classification rate at the node.(TIF)Click here for additional data file.S6 FigTerminal node variables outline the model-expected Inside Football Player Rating. Decimals indicate the absolute classification rate at the node.(TIF)Click here for additional data file.S7 FigTerminal node variables outline the model-expected Inside Football Player Rating. Decimals indicate the absolute classification rate at the node.(TIF)Click here for additional data file.