Pancreatic ductal adenocarcinoma (PDAC) is one of the deadliest of all major cancers. We now know that a ‘one-size-fits-all’ approach when treating PDAC patients does not work, so research has focused on developing personalised treatment strategies based on the biology of each patient’s tumour. However, most of these strategies ignore the presence of the characteristic fibrotic PDAC stroma which can act like a fortress to protect the tumour from chemotherapy and drive its aggressive nature. In this review, we summarise the role of this ‘fortress’ in protecting PDAC from chemotherapy and highlight the need for pre-clinical models that are informing precision medicine to reflect this hallmark feature of PDAC. We also propose the power of ex vivo whole-tissue culture models that mimic the tumour and its surrounding fortress to inform personalised treatment for PDAC.Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal cancers and no significant improvement in patient survival has been seen in the past three decades. Treatment options are limited and selection of chemotherapy in the clinic is usually based on the performance status of a patient rather than the biology of their disease. In recent years, research has attempted to unlock a personalised treatment strategy by identifying actionable molecular targets in tumour cells or using preclinical models to predict the effectiveness of chemotherapy. However, these approaches rely on the biology of PDAC tumour cells only and ignore the importance of the microenvironment and fibrotic stroma. In this review, we highlight the importance of the microenvironment in driving the chemoresistant nature of PDAC and the need for preclinical models to mimic the complex multi-cellular microenvironment of PDAC in the precision medicine pipeline. We discuss the potential for ex vivo whole-tissue culture models to inform precision medicine and their role in developing novel therapeutic strategies that hit both tumour and stromal compartments in PDAC. Thus, we highlight the critical role of the tumour microenvironment that needs to be addressed before a precision medicine program for PDAC can be implemented. Pancreatic cancer is set to become the 2nd leading cause of cancer related deaths by 2025 . AffectiCurrently, patients with resectable PDAC make up approximately 15% of all cases . FollowiIn the past decade, significant progress has been made in understanding the molecular biology of PDAC. In fact, genetic profiling has helped us identify different PDAC subtypes that may respond differently to chemotherapy. In 2011, Collison and colleagues  analysedThese findings have inspired an effort to profile the genetic signatures of PDAC patient tumours and use this information to inform individual patient clinical care. However, rather than understanding the subtype that characterises a particular patient’s tumour, the focus has shifted to identify patients that harbour clinically actionable targets ,17,18,19However, although the concept of treating individual patients based on a particular genetic alteration is exciting, a major limitation is that very few PDAC patients have genetic alterations that are therapeutically targetable. In the Know Your Tumour program, the largest PDAC precision medicine trial reported to date, actionable molecular alterations were identified in 26% of patients who received personalised molecular testing results . ImportaNonetheless, even if this logistical barrier is overcome, a major challenge that remains is the vast majority of PDAC patients that do not harbour an actionable molecular target. For precision medicine to be applicable to all patients with PDAC, research should focus on finding ways to predict the standard-of-care chemotherapy drugs that would benefit each individual patient rather than limiting the patient population to the few that have a targetable molecular alteration. Currently, selection of chemotherapy regimens in the clinical setting is not based on the biology of each patient’s disease but rather based on a patient’s performance status to prevent excessive side effects ,7,8. OneFor a pre-clinical model to guide functional precision medicine for PDAC, a key requirement is that it can provide meaningful and actionable results in a short timeframe. Patient-derived xenografts (PDX) are being used to inform personalised treatment in other cancers , but theTo establish tumour organoids, fresh human or mouse tumour tissue is minced, enzymatically or mechanically digested, embedded in a matrix, and supported by culture medium that contains growth factors that enrich for cells of epithelial origin . The firGiven the ability of tumour organoids to rapidly and efficiently model interpatient heterogeneity, several studies have begun to investigate whether drug sensitivity profiles can predict patient response to chemotherapy and inform personalised treatment. Many of these early studies were performed in colorectal cancer tumour organoids. As part of an elegant study by Vlachogiannis et al. , the invn = 9) where clinical chemotherapy response data was available, the ‘chemoresistant’ tertile correlated to patients who had rapid disease progression during treatment, while the ‘chemosensitive’ tertile correlated to patients who responded to treatment [In PDAC, the potential of tumour organoids to predict patient response to chemotherapy has also been investigated. Tiriac and colleagues  generatereatment . We eagereatment . And altreatment . This raThe majority of a PDAC tumour (up to 90%) is made up of extracellular matrix (ECM) and stromal cells ,38,39. CExcessive extracellular matrix (ECM), or fibrosis, can make up to 90% of PDAC tumour volume  and reprThe ECM can also promote chemoresistance in PDAC independent of its role in compressing blood vessels and hindering drug access. A study by Dangi-Garimella and others  showed tPDAC fibrosis is generated by cancer-associated fibroblasts (CAFs) . In healInterestingly, subpopulations of CAFs were recently identified which exhibit both transcriptional and functional diversity ,68. The In addition to CAFs, the PDAC stroma also houses infiltrating immune cells. The immune landscape of the PDAC microenvironment, especially the involvement of tumour-associated macrophages (TAMs), can directly contribute towards the development of chemoresistance. For example, Mitchem and others  showed tAnother factor that can drive chemoresistance in the PDAC tumour microenvironment is the presence of extracellular vesicles (EVs). Over the last 20 years, EVs have gained significant attention after their important role as mediators of cell-to-cell communication was discovered ,75. ReleEVs are not only released from stromal cells but can also be secreted from PDAC cells to increase chemoresistance. For example, EVs released from gemcitabine treated PDAC cells expressed significantly higher levels of miR-155 which is laterally transferred from EVs to recipient tumour cells . These rOverall, the above evidence demonstrates the critical role of the tumour microenvironment in driving the chemoresistant nature of PDAC. If we are to use patient-derived models to inform personalised treatment and predict patient response to therapy, the models that we use must reflect the features of PDAC that are known to drive chemoresistance and metastatic spread.Despite the many advantages of the tumour organoid model, many of the microenvironmental features discussed above are not recapitulated. Several studies have recently attempted to co-culture organoids with CAFs or immune cells, as reviewed recently ,28, but Several independent studies have now sought to bridge this gap using whole tumour tissue slices or tissue explants ex vivo  86,87,8,90,91.One of the first studies to culture PDAC tissue slices was published in 2009, where surgical PDAC tissue was cut into slices and cultured for 6 days submerged in growth media . Since tde novo cell proliferation and are negative for a cell death marker, TUNEL [ex vivo, raising the potential to silence undruggable genes in a preclinical model on a patient-by-patient basis [Our lab has recently published a similar model where we cultured whole tissue explants (1–2 mm diameter) from surgical PDAC tissue for 12 days on haemostatic gelatin sponges . We sougr, TUNEL . Althougr, TUNEL . As proor, TUNEL . Interesr, TUNEL . In ovarr, TUNEL . Important basis . The prent basis . We recent basis . We demont basis .The ability to culture patient PDAC tumour tissue ex vivo without manipulating its multicellular architecture presents exciting new opportunities for the precision medicine pipeline. Although we are yet to see concrete evidence in large patient cohorts that these whole-tissue models can accurately predict patient response to chemotherapy, we can at least hypothesise that their ability to model the complex microenvironment of human PDAC will enable them to more precisely predict patient chemotherapy response compared to other models that study tumour cells alone. While tumour organoid models often use IC50 or AUC values to classify ‘responders’ or ‘non-responders’, whole-tissue models have the potential to study the histological effects of a drug on tumour and stromal cells and could further classify response to drug as ‘complete response’, ‘partial response’, ‘stable disease’, or ‘progressive disease’. Another advantage of whole-tissue models is the rapid timeframe to generate a clinically meaningful result. Pharmacotyping in PDAC tumour organoids has been recently shown to be achievable after a median of 48 days , whereasFor patients with surgically resectable PDAC, tumour organoids can be established from biopsy material when/if a diagnostic biopsy is performed . OrganoiFor patients with unresectable or metastatic PDAC, future research should attempt to culture explants/slices from biopsy material so that such a pipeline could accommodate the entire PDAC patient population. The challenge here, however, is that biopsy material is usually limited, and most tissue needs to be sent to pathology for diagnostic purposes. Even if biopsy tissue can be set aside to establish tissue explant culture, the small size of the biopsy material would limit the number of tissue explants that can be cultured from each patient, and hence would limit the number of chemotherapeutics to be tested. To overcome this challenge, active collaboration is required between researchers, gastroenterologists, and interventional radiologists to ensure that enough tissue from metastatic PDAC patients can be used for research purposes, without compromising the importance of pathology diagnosis. This may involve consent for more than one biopsy site at the time of the procedure.However, even if biopsy of metastatic PDAC does not yield enough tissue to help select patient treatment, there are other avenues by which the tumour explant model could be used to culture metastatic PDAC. The tumour explant model could be adapted for use with a rapid autopsy program whereby both the primary tumour and multiple metastatic lesions could be cultured in parallel. Although this would not be suitable in an interventional precision medicine setting, it could be used to retrospectively uncover mechanisms of chemoresistance and to better study PDAC tumour biology . This coImportantly, such models could become powerful tools to study the dynamic biology and microenvironment of metastatic PDAC which is rarely studied using traditional in vivo or in vitro models. For example, a recent study elegantly identified distinct tumour promoting and tumour repressing functions of CAF subtypes in mouse PDAC liver metastases . The tumNonetheless, the next step is to determine whether whole-tissue explant cultures can predict patient response to chemotherapy. For this to be determined, a non-interventional trial is first needed to assess the response to standard of care adjuvant chemotherapy drugs in the tissue explant model, and then retrospectively assess how this correlates with subsequent patient response in the clinic. This could then be followed by an interventional clinical trial where the tumour explant model is used to generate drug sensitivity profiles to standard of care drugs which is then used to guide selection of treatment. The initial non-interventional trial would also be useful to determine the most accurate and efficient readout for drug response in the tissue explant model. We showed that terminal deoxynucleotidyl transferase dUTP nick end labeling (TUNEL) staining, as a measure of cell-death, can separate responders and non-responders to abraxane in a small number of patients , but thiThe presence and abundance of human and patient-matched stroma in whole-tissue ex vivo models can become a powerful tool to better understand the biology of the stroma in PDAC and the potential to target the PDAC stroma in a personalised setting. The concept of targeting the stroma in PDAC remains controversial given the debated role of the stroma in promoting or restraining tumour progression. However, many of the initial studies that instigated this controversy drew conclusions from mouse models that genetically ablated either α-smooth muscle actin expressing cells  or sonicTaken together, these landmark studies reinforce the need for preclinical models to accurately reflect the stromal and microenvironmental features of human PDAC to be able to guide stromal targeting strategies and to help select ideal patients. Despite failed clinical trials, research has focussed more on stromal reprogramming rather than stromal ablation . There aFor the first time in more than three decades, our improved understanding of the genetic landscape, the multicellular 3-dimensional architecture, and the hostile microenvironment of PDAC has potential to revolutionise the dismal survival of PDAC patients. But as momentum builds in the field of genetic profiling of PDAC tumours with a view towards precision medicine, we must not forget the critical role of the tumour microenvironment and the fibrotic stroma in driving the aggressive nature of PDAC. The advent of new culture techniques that allow us to grow whole pieces of human PDAC tumours ex vivo can re-unite these two fields by testing drug efficacy on each patient’s tumour in models that accurately mimic the microenvironmental cues and the tumour and stromal organisation in the same 3-dimensional architecture as present in the patient’s disease. This also paves the way for the development of a new class of drugs that therapeutically target both tumour and stromal compartments in PDAC.Such research provides an ideal translational cycle of bench-to-bedside then back-to-the-bench. Using clinically relevant patient-derived models to predict response to chemotherapeutics can inform clinical decision making, and at the same time, testing drugs in models that contain the key features and complexities of human PDAC can provide a unique insight into the mechanisms by which these drugs work and the broader functional biology of tumour and stroma in PDAC. Although the fruits of precision medicine are yet to be truly reaped for PDAC patients, this new era offers great hope to the patient community but at the same time, reinforces the need to consider all aspects of PDAC biology while we launch this trajectory of precision medicine.


The intricate relationship between caregiving and health may to some extent be determined by the burden and restrictions imposed on informal caregivers, and the impact these experiences have on health behaviours. It is assumed that a positive caregiver experience leads to health promoting behaviours in caregivers, whereas a negative experience induces the opposite. The objective of this study is to test these assumptions and to investigate the association between the caregiver experience and health behaviours in the caregiving partners of persons with severe physical impairment, due to spinal cord injury.Cross-sectional survey data from 133 couples of caregiving partners and persons with spinal cord injury living in Switzerland was used. We employed multivariable regression to evaluate the associations of the caregiver experience  with health behaviours .The most robust associations were found between subjective caregiver burden and health behaviours, whereby caregivers reporting a higher burden reported less physical activity , more alcohol consumption , greater smoking intensity , and a higher likelihood of insufficient sleep duration . Caregivers, who reported high objective burden, i.e. invested long hours in caregiving, were more prone to partake in health adverse behaviours, in particular greater alcohol consumption. Results also suggested that caregivers who were satisfied in their role and who received social support in caregiving were more likely to be physically active.Caregivers suffering from high emotional and time burden may benefit from both practical and psychological support. This support may release resources enabling individuals to partake in health promoting behaviours, or to develop coping strategies to better deal with the burden of caregiving. The study is set in the longitudinal pro-WELL study that included informal caregivers and their partners with a physical disability, namely spinal cord injury  with the main objective to investigate the psychosocial determinants of wellbeing in persons with spinal cord injury and their caregiving partners. Given that the present study is mainly focused on the caregiving partners and that the main outcome  has only been measured in the baseline assessment, this analysis utilized cross-sectional baseline data from caregiving partners of persons with spinal cord injury (n=133). The baseline assessment was carried out between May 2015 and January 2016 and data were collected by means of standardized telephone interviews, paper-pencil or online questionnaires . Regulations concerning informed consent and data protection were strictly observed and all participants signed an informed consent form.Physical activity was assessed by information on weekly frequency  and duration of physical activity  , ‘some help provided’ (1) and ‘much help provided’ (2). A sum score ranging from 0–12 for ADL and 0–10 for Instrumental activities of daily living was created  short form, which captures personal feelings of strain resulting from the caregiving role . Utilizing DAGs enables the identification of ‘true’ confounders which can subsequently be tested and validated in bivariate analysis. Age, gender, financial hardship, employment status (having paid work vs. not having paid work) and occurrence of a stressful life event in the last 6 months were identified as relevant confounders and were therefore included into multivariate models. Financial hardship was assessed with an item asking participants how they evaluate the availability of financial resources on a 5-point scale ranging from ‘very scarce’ to ‘lasts very well’.The identification of potential confounders was informed by current evidence and by directed acyclic graphs . Distribution of health behaviour variables in both persons with spinal cord injury and in caregiving partners were evaluated and dyadic concordance in health behaviours was assessed using multi-level models to compute within- and between-dyad variation. Intra-class correlations (ICCs) were evaluated to investigate how similar different variables were within dyads, with values closer to 1 indicating higher correlation within the dyad. Multivariate regression was also used to examine the difference in health behaviours between caregivers and persons with SCI, models were adjusted for age and sex. Descriptive analysis was performed with crude data, excluding all cases with missing values.P values were computed using equal fraction-missing-information (FMI) tests  zero-inflated Poisson models (ZIP) were fitted. For binary outcomes (i.e. smoking status and sleep duration), ordinary logistic regressions were applied, and for the continuous score of average daily portions of fruit and vegetables, linear regression was applied. Two subsequent models were computed: Model 1 was unadjusted; Model 2 was adjusted for age, gender, financial hardship, employment status and occurrence of a stressful life event in the last 6 months. Basic characteristics of the pro-WELL sample are displayed in Several of the indicators for objective burden showed consistent associations with health behaviours. Caregivers who provided more support in activities of daily living and instrumental activities of daily living showed on average lower physical activity  and higher smoking intensity than caregivers who provided less support. Those with social support in caregiving further reported higher levels of physical activity . Individuals who invested over 3 h in caregiving per day reported a higher alcohol consumption than those who invested less time in care, although they were also more likely to participate in more physical activity .Caregivers with a higher subjective burden were less than half as likely to partake in physical activity , consumed nearly 50% more alcohol per day  and were almost five times more likely to sleep for less than seven hours per night  than those with a lower subjective burden.Those caregivers who reported few positive aspects of caregiving, i.e. dissatisfaction with the caregiving role, reported lower levels of physical activity than those who were satisfied  and higher likelihood of smoking , albeit with a lower intensity than those who were satisfied.This study provides evidence for the connection between health behaviours and the caregiving experience. In general, our findings support the hypothesis that a higher objective and subjective burden, and a lower satisfaction with caregiving are associated with less health promoting and more health adverse behaviours. More specifically, caregiving partners with a high subjective burden reported higher levels of alcohol and tobacco consumption, lower levels of physical activity and shorter sleep duration. Moreover, the caregiver experience was generally associated with physical activity; showing either raised or reduced levels of physical activity for respectively positive and negative aspects of caregiving. These findings are novel for the caregiver health literature and may reveal an important pathway linking caregiver burden and lack of satisfaction with the caregiver role to health outcomes.What is particularly novel to the literature is our finding that positive appraisals, such as satisfaction with the caregiver role are generally associated with healthy behaviour. Furthermore, we confirmed previous findings that caregiver burden is linked to more health adverse behaviour; this enforces the notion that a comprehensive assessment of the caregiving experience must include both, positive and negative experiences and go beyond the assumption that caregiving is a burden. For many individuals, caregiving is appraised as a positive, fulfilling and satisfying experience with subsequent health enhancing effects, as documented for example for mental health (Fekete et al., Our findings suggest that caregivers bearing a high subjective burden present an important target population for interventions aimed at altering health behaviours. However, there are special considerations, which need to be made in the design of tailored programmes. For example, caregivers may need different prescriptions for physical activity than other populations, regimes that concentrate on shorter bouts of physical activity rather than long training sessions have been seen to be more successful in caregiving population (Marquez et al., A major strength of this study is the use of a wide-ranging set of variables to describe the caregiver experience, which capture not only the subjective and objective nature of caregiver burden but also positive aspects. In addition, we were able to investigate a large array of different health behaviours, capturing health promoting and health adverse behaviours. All associations were tested using multivariate models, which took relevant confounders into account. Furthermore, the pro-WELL study was nested in a large cohort study, showing good representation of the source population of care-receivers in terms of socio-demographic and lesion characteristics (Fekete et al., This study provides an important contribution to the literature on informal caregiving and health behaviour as it goes further than current evidence by including both positive and negative aspects of the caregiver experience as potential predictors of health behaviour. The reduction of the burden of care or the increase of positive aspects of caregiving is considered as a valuable strategy to indirectly support the promotion of favourable health behaviours in caregivers. Therefore, health policy may develop programmes involving both practical and emotional support, e.g. by caregiving relief through respite care or through psychological therapies. A structured needs assessment could assess the ability of the caregiver to provide care and identify situations, which are especially burdensome or damaging for healthy behaviours.


Evolutionary conservation is an invaluable tool for inferring functional significance in the genome, including regions that are crucial across many species and those that have undergone convergent evolution. Computational methods to test for sequence conservation are dominated by algorithms that examine the ability of one or more nucleotides to align across large evolutionary distances. While these nucleotide alignment-based approaches have proven powerful for protein-coding genes and some non-coding elements, they fail to capture conservation of many enhancers, distal regulatory elements that control spatial and temporal patterns of gene expression. The function of enhancers is governed by a complex, often tissue- and cell type-specific code that links combinations of transcription factor binding sites and other regulation-related sequence patterns to regulatory activity. Thus, function of orthologous enhancer regions can be conserved across large evolutionary distances, even when nucleotide turnover is high.We present a new machine learning-based approach for evaluating enhancer conservation that leverages the combinatorial sequence code of enhancer activity rather than relying on the alignment of individual nucleotides. We first train a convolutional neural network model that can predict tissue-specific open chromatin, a proxy for enhancer activity, across mammals. Next, we apply that model to distinguish instances where the genome sequence would predict conserved function versus a loss of regulatory activity in that tissue. We present criteria for systematically evaluating model performance for this task and use them to demonstrate that our models accurately predict tissue-specific conservation and divergence in open chromatin between primate and rodent species, vastly out-performing leading nucleotide alignment-based approaches. We then apply our models to predict open chromatin at orthologs of brain and liver open chromatin regions across hundreds of mammals and find that brain enhancers associated with neuron activity have a stronger tendency than the general population to have predicted lineage-specific open chromatin.The framework presented here provides a mechanism to annotate tissue-specific regulatory function across hundreds of genomes and to study enhancer evolution using predicted regulatory differences rather than nucleotide-level conservation measurements.The online version contains supplementary material available at 10.1186/s12864-022-08450-7. The study of conservation has had a tremendous impact in multiple areas of mammalian biology. When a new genome is sequenced, conservation is applied to provide high-quality annotations of candidate exons, introns, promoters, and other likely functional genomic regions . RegionsThe methods used to infer conservation across species, including those applied to many of the challenges described above, typically rely on nucleotide-level constraint. They generally begin by aligning the nucleotides of multiple genomes together , 13. Frocis-regulatory elements, many of which are enhancers that control gene expression . In. In99]. In addition to being accurate, our models’ predictions revealed that many OCRs may have lineage-specific patterns of open or closed chromatin and that these patterns may be functional. We developed an approach to deciphering the putative lineage-specificity of candidate enhancers identified in other studies in which we clustered our OCRs using predicted open chromatin as features and identified clusters with more overlap with these candidate enhancers than expected by chance. Applying this approach revealed that mouse candidate enhancers activated during neuron firing  are enriOur approach has the potential to be applied to numerous other groups of species, cell types, and tissues because it does not require experimentally determined OCR data from more than a few species but rather requires only genomes, which are being generated in unprecedented quantities , 9, 10, The lineage and tissue-specificity of many enhancers limits our ability to quantify the conservation of enhancers through nucleotide-level conservation scores. Therefore, rather than focusing on identifying cases where natural selection is acting on individual nucleotides, we used open chromatin data from tissues of interest to train CNNs for predicting open chromatin and showed that our predictions can reveal potential cases where natural selection operates to maintain the TF binding sites that are needed to regulate gene expression. We evaluated the success of our CNNs as well as nucleotide conservation-based and other machine learning-based methods using new criteria that we designed explicitly for evaluating open chromatin conservation prediction. We then used CNNs to predict brain and liver open chromatin conservation across mammals and found that candidate enhancers associated with neuron firing tended to overlap regions of predicted lineage-specific open or closed chromatin. Our approaches to quantifying enhancer conservation and evaluating methods for this task can be applied to any tissue or cell type with enhancer data available from multiple species. As this is, to our knowledge, the first study to predict open chromatin conservation across more than a few species, we anticipate that our work will serve as a foundation for identifying OCRs whose open chromatin conservation is involved in gene expression evolution, providing insights into transcriptional regulatory mechanisms underlying phenotypes that have evolved through gene expression and their associated diseases.Mouse liver open chromatin data generation, curation of all other open chromatin datasets, data processing, and positive set construction details are described in Supplemental Methods. We obtained the non-OCR orthologs of OCRs by obtaining the orthologs of OCRs in each other species for which we had data from the same tissue and filtered the orthologs to include only those that did not overlap open chromatin in the same tissue  on the validation set. Before training, we initialized the weights to be those from a pre-trained neural network with the same hyper-parameters and the negative set randomly down-sampled to be the size of the positive set (or a positive set randomly down-sampled to be the size of the negative set if the positive set was larger) in order to help the model handle the class imbalance, as we did in our previous work . We initIn addition to evaluating models on the test sets corresponding to the training sets, we evaluated models on multiple additional evaluation sets to compute their lineage-specific and tissue-specific OCR accuracies. Illustrations of clade-specific and species-specific OCRs for the lineage-specific OCR accuracy evaluations and tissue-specific OCRs for the tissue-specific OCR accuracy evaluations are in Fig. To obtain OCR orthologs that are open in one species but not in another, we used as positives the sequences and reverse complements of sequences underlying OCRs from one species whose orthologs in the other species have closed chromatin and as negatives the sequences and reverse complements of sequences underlying non-OCRs whose orthologs in at least one other species are OCRs. More specifically, to construct positives for the MouseBr ≠ OtherBr and MouseLv ≠ OtherLv evaluations, we used halLiftover  followedWe defined a clade-specific OCR in a tissue as an OCR whose ortholog is open in that tissue in every species within a clade for which we have data and closed in that tissue in every other species for which we have data, and we defined a species-specific OCR in a tissue as an OCR whose ortholog is open in that tissue in a species for which we have data and is closed in that tissue in the single most closely related species (there were no ties) for which we have data Fig. b. LaurasThe species-specific OCRs and non-OCRs are described in Supplemental Table To evaluate the performance of models trained in one tissue on OCRs from another tissue, we defined our positives to be OCRs that are shared between the two tissues (shows our models were learning more than just the sequences involved in tissues-specific open chromatin), and we defined our negatives to be OCRs in the evaluation tissue that do not overlap OCRs in the training tissue  Fig. b. For thFor comparing models trained with different training sets, we also compared the distributions of test set chromosome predictions for the brain OCRs that do not overlap liver OCRs, the brain OCRs that overlap liver OCRs, the liver OCRs that do not overlap brain OCRs Fig. b, and thTo evaluate the relationship between OCR ortholog open chromatin status and phylogenetic distance, we identified test set mouse OCR orthologs in all the fifty-six Glires species from Zoonomia, predicted the open chromatin statuses of those orthologs, and computed the correlation between those predictions and the species’ phylogenetic divergences from mouse. This provides us with an approximate measure of how predicted OCR ortholog open chromatin statuses change over evolution. Specifically, we identified the mouse test chromosome OCR orthologs and OCR summit orthologs in Glires using halLiftover  with theWe compared the predictions to mean conservation scores by identifying OCR orthologs with conserved and non-conserved open chromatin status between species, computing the mean conservation scores of those OCR orthologs, and comparing those scores to the predicted open chromatin status of those OCR orthologs. We defined an OCR ortholog with conserved open chromatin status between mouse and another species as a mouse OCR whose ortholog in the other species overlaps an OCR in the same tissue. For mouse brain test chromosome OCRs, we identified 441 OCRs with conserved open chromatin status in macaque, 195 OCRs with conserved open chromatin status in human, and 670 OCRs with conserved open chromatin status in rat. For mouse liver test chromosome OCRs, we identified 689 OCRs with conserved open chromatin status in macaque and 580 OCRs with conserved open chromatin status in rat. We defined an OCR ortholog with non-conserved open chromatin status between mouse and another species as a mouse OCR whose ortholog in another species does not overlap any union pooled peaks in that tissue in that species  or 12,000 (liver) to cluster the OCRs into small clusters; we defined cluster centroid values for each species as the mean of all OCR ortholog activity predictions for that species in the cluster. We did this because affinity propagation clustering was not tractable for hundreds of thousands of examples with hundreds of features. We then used affinity propagation clustering , implemeTo identify enhancer sets with more overlap with a cluster than expected by chance, we first obtained the enhancer sets from the supplemental information of the relevant manuscripts. For the mouse neuron firing candidate enhancers, we used the regions in Tables S11—S13 from a recent study of enhancers activated during mouse neuron firing  and usedWe wanted to determine if our enrichment for overlaps with clusters with lineage-specific open chromatin or lack of open chromatin could be partially explained by OCRs overlapping enhancer sets having fewer usable orthologs or lower conservation. To evaluate this, we used bedtools  to identAdditional file 1.


This lack of a difference prompted trainers to consider that the phenomenon was not relevant to performance but also suggested that a specific adaptation to exercise is present in EIH athletes. Even though the causes of EIH have been extensively studied, its consequences have not been fully characterized. With the development of endurance outdoor activities and altitude/hypoxia training, athletes often train and/or compete in this stressful environment with a decrease in the partial pressure of inspired O2 (due to the drop in barometric pressure). Thus, one can reasonably hypothesize that EIH athletes can specifically adapt to hypoxemic episodes during exercise at altitude. Although our knowledge of the interactions between EIH and acute exposure to hypoxia has improved over the last 10 years, many questions have yet to be addressed. Firstly, endurance performance during acute exposure to altitude appears to be more impaired in EIH vs. non-EIH athletes but the corresponding physiological mechanisms are not fully understood. Secondly, we lack information on the consequences of EIH during chronic exposure to altitude. Here, we (i) review research on the consequences of EIH under acute hypoxic conditions, (ii) highlight unresolved questions about EIH and chronic hypoxic exposure, and (iii) suggest perspectives for improving endurance training.Exercise-induced hypoxemia (EIH) is well-described in endurance-trained athletes during both maximal and submaximal exercise intensities. Despite the drop in oxygen (O For many years, cardiovascular responses and muscle metabolism were the only acknowledged limiting factors in exercise performance. However, research has now clearly shown that the respiratory system is far from perfect and does not always have the capacity to meet the demands of intense endurance training Amann, . Dempsey2) and a concomitant drop in arterial oxygen saturation (SaO2) between rest and maximal exercise. This hypoxemia is associated with abnormal gas exchange, as reflected by an increase in the alveolo-arterial oxygen pressure difference [D(A-a)O2] , the oxygen (O2) supply to the muscles and thus aerobic exercise performance at sea level are impacted. In this context, EIH has attracted interest from sports scientists and physiologists.EIH was first described in detail by Dempsey et al. in the 1980s. EIH occurs in some  endurance-trained athletes performing exercise at sea level (i.e. under normoxic conditions)  hypoxemia at rest is defined as a fall of 5 mmHg   at rest and during exercise was considered. The use of pulse oximetry to study EIH was validated  the inherent rightward shift of Barcroft's curve during exercise, and (ii) the accuracy of oximeters, Prefaut et al.  and without (NEIH athletes) with similar training volumes have the same VO2max > 68 ml.min−1.kg−1 displayed EIH during an incremental exercise test on a cycle ergometer  of male athletes with a VO2max > 68 ml.min−1.kg−1 performing a progressive-grade treadmill exercise test to exhaustion  present EIH during a cycle test to exhaustion.Few researchers have focused on the prevalence of EIH and an early study reported that 52% of male athletes with a VOEIH is also present at submaximal exercise intensities in some individuals  by the fact that the EIH athletes had a lower maximal heart rate (HRmax) at altitudes of 2150 m  than athletes with a higher SpO2. This blunted hypercapnic ventilatory response might have consequences on ventilatory acclimatization to altitude. Nevertheless, other studies did not find greater hypoxemia values in EIH athletes (vs. NEIH athletes) during hypoxic exercise  could not be wholly explained by a greater reduction in HRmax and so suggested the involvement of another factor and probably specific adaptation to hypoxia in EIH athletes. More recently, it was reported that EIH athletes displayed exacerbated changes in cerebral deoxygenation and a low limb muscle blood volume at sea level; these results were accentuated by the severity of O2 arterial desaturation, and in contrast to NEIH athletes, were the same in hypoxia and normoxia  altitude training mode was developed in which athletes live at moderate altitude but train at sea level or at low altitude  does not depend solely on hematological parameters. Indeed, peripheral factors like exercise economy and/or buffering capacity  on EIH athletes while others followed the same protocol under normoxic conditions  is usually implemented two or three times a year  aims to divert blood to better-oxygenated lung segments, thereby optimizing ventilation/perfusion matching and systemic OSwenson, . HPV is Swenson, . These hThe roles of EIH following diffusion limitation  evaluate whether EIH could impair or facilitate acclimatization to altitude and thereafter, (iii) investigate the putative role of EIH in the great variability of the response to altitude/hypoxia training whatever the method. In order to collect and analyze the large amounts of data and their interaction, openness to the science complex system is essential. In recent years, mathematics has been increasingly used in physiology  monitor SpOIndividualization of the altitude dose is well-known to be the key of altitude/hypoxic training to ultimately reduce inter-individual variability. In the context, monitor the EIH during training has to be considered as a main factor of this individualization to find the best practice to increase performance.The original conception of the work was conducted and the manuscript was drafted by FD and AR. Both authors read and approved the final manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Clinical epidemiology and patient-oriented health care research that incorporates neighborhood-level data is becoming increasingly common. A key step in conducting this research is converting patient address data to longitude and latitude data, a process known as geocoding. Several commonly used approaches to geocoding  send patient addresses over the internet to web-based third-party geocoding services. Here, we describe how these approaches to geocoding disclose patients’ personally identifiable information (PII) and how the subsequent publication of the research findings discloses the same patients’ protected health information (PHI). We explain how these disclosures can occur and recommend strategies to maintain patient privacy when studying neighborhood effects on patient outcomes. Imagine if a clinical researcher were to disclose a list of patient addresses to a third party that was outside of their hospital or health system without a formal agreement with that third party to secure the data. Imagine they then publicly announced that they disclosed the addresses, that the addresses belonged to patients with a specific disease, and that those patients were being treated at a specific hospital. The researcher’s institutional review board (IRB) and Health Insurance Portability and Accountability Act (HIPAA) compliance office would be outraged at these violations of patient privacy. Yet, this sequence of events can happen inadvertently when studying how neighborhood conditions such as access to medical facilities or surrounding food environments affect clinical outcomes in certain patient populations.Clinical epidemiology and patient-oriented health care research incorporating neighborhood-level data is becoming progressively more common as the National Institutes of Health and professional and patient organizations are increasingly encouraging such research ,2. For iWe describe the steps in the research process when PII and PHI can be disclosed when the study population is defined as patients with a specific disease or diseases, as is common in clinical studies. We then explain why many protocols do not protect patient privacy and conclude by offering suggestions for a workflow that avoids the issues we identify. We use a fictional example throughout this article to avoid compounding potential PII and PHI disclosure issues that have occurred in previously published research. The hypothetical study being referenced examines whether residential neighborhood poverty rates are associated with the risk of death among patients with COVID-19 who were treated at the Columbia University Irving Medical Center. Though fictional, the example draws on published studies and studies that we have peer reviewed for clinical and public health journals. The initial risk of disclosing PII and PHI occurs during a key step called geocoding. Geocoding is the process of converting a street address to longitude and latitude coordinates, which can then be linked to neighborhood-level data such as US census data. In our example of patients with COVID-19 who were treated at the Columbia University Irving Medical Center, the patients’ addresses would be geocoded as the first step in estimating poverty rates in each patient’s residential neighborhood.Several commonly used approaches to geocoding send addresses via the internet to third-party geocoding services. These approaches include manually entering addresses into websites such as Google Maps, uploading spreadsheets of addresses to geocoding websites, and using software packages such as the R  packages tidygeocoder, ggmap, and googleway; the Stata command geocode; and some options included with the SAS procedure GEOCODE. The tidygeocoder R package, for example, sends addresses to geocoding web services hosted by the US Census Bureau or by OpenStreetMap (or both), and ggmap and googleway send addresses to the Google Maps geocoder ,6. The RAn additional layer of disclosure occurs when using web-based geocoding services because these services can link home address data that were submitted to the service to the institution from which the data originated. When researchers send geocoding requests, geocoding services capture the IP address of the computer requesting the service along with the patient home address to be geocoded. As a result, the disclosed addresses are linked to a particular health care or research institution. Furthermore, the unique API keys used for many services create a linked history of all geocoding requests submitted by a researcher. Finally, data stored in the researcher’s web browser cookies and search histories can also identify the researcher or clinician when they use some web-based geocoding services. Depending on which third-party service was used to geocode the residential addresses of the patients with COVID-19 in our example, the geocoding service provider would receive data on the identity of the institution originating the geocoding requests; they could also possibly receive data on the identity of the researcher and even information on the researcher’s recent focus on COVID-19 research. Thus, the combination of patient address data, researcher or clinician identity, and the identity of the health institution allows the third-party geocoding service to make inferences about the submitted addresses.Publishing research results in articles allows third parties to further contextualize the disclosed addresses. Publication itself can therefore reveal PHI that can be linked to PII . PublicaSome researchers recognize the risks associated with this type of study but use strategies that do not protect PII and PHI. One approach we have seen proposed is to submit patient addresses of interest to a geocoding service along with a pool of randomly selected addresses . An issuAnother possibility may be to use a virtual private network (VPN) that obscures the identity of the computer sending the addresses to the third-party geocoding service, thus concealing the fact that the addresses are being sent from a medical system. However, VPNs can be difficult to set up securely and many commercial VPNs do in fact reveal the location of the user’s computer . FurtherFor researchers to be compliant with HIPAA and typical IRB regulations, patient addresses should be geocoded using desktop tools, such as ArcGIS, that store address information on local secured machines. QGIS offers a free open-source alternative to ArcGIS, though default geocode options use OpenStreetMap, so care must be taken to set up desktop options. Alternatively, researchers can use a geocoder designed for server hosting within a virtual machine on their local computer. For example, the open-source PostGIS geocoder can be hosted within a Docker container and accessed using R (see  for an eIn summary, geocoding patient addresses using web-based services creates direct and large-scale disclosures of PII and PHI, and the proliferation of simple-to-use R packages for geocoding increases the risk of these inadvertent disclosures. Web-based geospatial tools are powerful and allow for efficient and rigorous research. However, researchers geocoding patient addresses must be aware of the risk of inadvertent disclosure of patient PII and PHI. Researchers should avoid web-based geocoders and use only secure desktop tools when geocoding patient information. Researchers may wish to disconnect computers from the internet while geocoding to ensure that no data are inadvertently passed to third parties.


Diabetes mellitus type II and obesity are two important causes of death in modern society. They are characterized by low-grade chronic inflammation and metabolic dysfunction (meta-inflammation), which is observed in all tissues involved in energy homeostasis. A substantial body of evidence has established an important role for macrophages in these tissues during the development of diabetes mellitus type II and obesity. Macrophages can activate into specialized subsets by cues from their microenvironment to handle a variety of tasks. Many different subsets have been described and in diabetes/obesity literature two main classifications are widely used that are also defined by differential metabolic reprogramming taking place to fuel their main functions. Classically activated, pro-inflammatory macrophages (often referred to as M1) favor glycolysis, produce lactate instead of metabolizing pyruvate to acetyl-CoA, and have a tricarboxylic acid cycle that is interrupted at two points. Alternatively activated macrophages (often referred to as M2) mainly use beta-oxidation of fatty acids and oxidative phosphorylation to create energy-rich molecules such as ATP and are involved in tissue repair and downregulation of inflammation. Since diabetes type II and obesity are characterized by metabolic alterations at the organism level, these alterations may also induce changes in macrophage metabolism resulting in unique macrophage activation patterns in diabetes and obesity. This review describes the interactions between metabolic reprogramming of macrophages and conditions of metabolic dysfunction like diabetes and obesity. We also focus on different possibilities of measuring a range of metabolites intra-and extracellularly in a precise and comprehensive manner to better identify the subsets of polarized macrophages that are unique to diabetes and obesity. Advantages and disadvantages of the currently most widely used metabolite analysis approaches are highlighted. We further describe how their combined use may serve to provide a comprehensive overview of the metabolic changes that take place intracellularly during macrophage activation in conditions like diabetes and obesity. Diabetes mellitus type II (DMTII) is one of the main causes of death in modern society according to the World Health Organization . It corrSeveral factors can contribute to a higher risk of developing DMTII, but it has been proven that overweight or obesity are the most important ones . DMTII iMacrophages are part of the innate immune system and are present in all tissues of our body, including adipose tissues . They plMany studies have described how macrophages become activated by inflammatory stimuli , 10 and One of the key characteristics of DMTII is the altered insulin response. In healthy individuals, with a body mass index (BMI) in the normal range, pancreatic β cells produce insulin in response to circulating glucose levels. This will bind and activate insulin receptors on the cell membrane of different cell types, including macrophages, to lower blood glucose levels by enhancing its uptake by these cells. The binding of insulin to its receptor drives a cascade of events ultimately leading to uptake of glucose and further downstream effects Figure 1DMTII is caused by the development of insulin resistance, meaning the inability of cells to respond to insulin due to a transmission blockage of the insulin receptor, mainly in muscle and liver cells. Pancreatic β-cells will at first try to compensate for the higher levels of glucose by increasing insulin production. This will eventually lead to lower glucose availability in combination with lower tissue insulin sensitivity resulting in loss of β-cell function. This will result in lower insulin secretion, which will consequently lead to a higher concentration of glucose in blood .Insulin resistance can be caused by many different factors, with obesity being the most important one . ElevateThe inflammation related to obesity was first described in 1993 when Hotamisligil et al. showed that adipose tissue from obese rats expressed more tumor necrosis factor-α (TNF-α)  than adiStudies have shown that during obesity, triglyceride accumulation causes stress on adipocytes due to an increase in cell size and subsequent hypoxia . CapillaMacrophages can respond in many different ways to stimuli from their microenvironment. In the past, this was described as macrophage activation, but since the discovery of the many different types of responses of macrophages, this is also called macrophage polarization . PolarizMacrophage responses are currently mostly described by a combination of expression of extracellular and intracellular markers, including production of specific cytokines. The most widely studied and longest known activation response, i.e. classical activation, is induced by pro-inflammatory stimuli generated by infections with micro-organisms . These cWhen it became clear that macrophages could also become activated in ways not resembling the classical way, studies have been trying to delineate these different types of activation states. Many different types of stimuli induce slightly different alternatives to classical activation that are mostly involved in stimulating tissue repair and downregulating inflammation. These stimuli include IL-4 and IL-13, glucocorticosteroids, prostaglandin E2 (PGE2), immune complexes, transforming growth factor β (TGFβ), and IL-10 . These aIn vivo, adipose tissue macrophages from healthy mice express high levels of CD206, whereas adipose tissue macrophages from obese mice express low levels of CD206  cycle, while the latter are used to produce ATP by OXPHOS. In addition, these macrophages can produce pyruvate from glycolysis, convert this to acetyl-CoA, which is then used by the TCA cycle to give electrons in the form of NADH and FADH2 to the OXPHOS complexes  activity, while alternatively activated macrophages convert arginine in proline and polyamines through arginase-1 . Followiomplexes  and favoomplexes . As a reomplexes . A shortde novo lipogenesis.The first consequence of metabolic reprogramming is a breakpoint of the TCA cycle after citrate, due to lower expression of isocitrate dehydrogenase . This cavia α-ketoglutarate into succinate through glutaminolysis or through an upregulated γ-aminobutyric acid (GABA) shunt. This shunt is a TCA cycle bypass which uses glutamine as a substrate to produce succinate, passing through glutamate, GABA, and succinic semialdehyde  because succinate inhibits prolyl hydroxylase domain proteins, which normally hydroxylate HIF-1α leading to its ubiquitination and proteasomal degradation . The staHIF-1α also promotes expression of lactate dehydrogenase, which metabolizes pyruvate to lactate  and exprIn summary, highly active glycolysis combined with increased glucose uptake results in improved availability of glycolytic intermediates, meeting one of the requirements of an inflammatory response, such as an increased demand for energy .The exact mechanism of how macrophages reprogram their metabolism after activation in DMTII and obesity is still unknown. As discussed in the previous paragraph, macrophages undergo metabolic reprogramming when classically activated, but also availability of energy sources influences their metabolism, implying that abundant availability of energy sources (for instance during hyperglycemia or obesity) can also impact their metabolism. Since it has been shown that the phenotype of metabolically activated macrophages differs from classically activated macrophages , 36, thi+ macrophages  seems probable. Indeed, a link between epigenetic changes and DMTII-related meta- inflammation has been reported in a variety of studies, suggesting that metabolic changes induced by obesity/DMTII can lead to epigenetic changes, which then result in transcription of pro-inflammatory genes , 81.In particular, changes in the levels of lysine deacetylases (KDACs), enzymes responsible for the deacetylation of lysine residues in proteins, have been reported in obese mice and patients , 83. KDAin vitro by studies showing that SIRT1 inhibits recruitment of macrophages by co-culturing them with SIRT1-deficient adipocytes and showing that the absence of SIRT1 induced their recruitment and a pro-inflammatory phenotype  and with impaired glucose uptake . Howeverhenotype . In addihenotype .These findings on KDACs suggest that combining KDAC activators with anti-diabetic drugs could be a more efficient way to treat metabolic syndrome. A wide array of KDAC activators is already available and more specific ones are being developed. Examples of KDAC activators that have been used in the context of metabolic syndrome show beneficial effects by inhibiting expression of pro-inflammatory cytokines in adipocytes and higher insulin sensitivity and glucose uptake after treatment . Importain vitro and in vivo in the context of diabetes and obesity  based metabolomics and flux analysis . These t+ ions will be produced, shifting the pH of the medium.Widely used assays in the field of immunology are extracellular flux analyzers that give a functional readout of glycolytic or mitochondrial metabolic activity by measuring changes in energy metabolism in culture medium of cells . MitochoThese assays have the advantage of being performed in living cells, but they are indirect indicators of changes in metabolic pathways or mitochondrial function, which play a pivotal role in macrophage activation and function as outlined above . HoweverKey metabolites to follow with respect to the different macrophage phenotypes are listed in in vitro studies .Metabolite analyses by MS can be performed in a targeted or untargeted manner. With targeted MS methods it is possible to have accurate and precise quantitative information on known metabolites, such as those that are involved in metabolic reprogramming of macrophages. While many metabolites, that play a key role in macrophage metabolic reprogramming, are known, recent work shows that new metabolites are still being discovered using untargeted MS . One exa13C labeled glucose and 13C- and 15N-labeled glutamine combined with a targeted LC-MS approach (selective reaction monitoring (SRM)). Using this pipeline they showed that glutamine is a major source of nitrogen in alternatively activated macrophages and that these cells have an augmented metabolism of amino sugars and nucleotide sugars like uridine diphosphate N-acetylglucosamine. This metabolite is known to link signaling and metabolism through glycosylation of proteins that are localized at the cell-surface, for example, various growth factor receptors (Knowing the concentration and/or abundance of the metabolites at a given moment in time can help to understand which metabolite levels are altered at the moment of metabolite extraction. However, to understand the dynamics of metabolic reprogramming, it is also relevant to know which metabolic pathways are up- or down-regulated, which can be deduced from measuring production and consumption rates of metabolites by following the incorporation of stable isotopes into metabolites over time. This is accomplished by using stable isotope labelled metabolic tracer molecules to study the flux of stable isotopes through different pathways for a set of key metabolites . An untaeceptors . By usineceptors . The auteceptors , plays aTo summarize, a number of analytical approaches can be used to study metabolic reprogramming in macrophages. Flow cytometry analysis allows to define the different phenotypes of macrophages on which subsequent comparative analyses are based. Extracellular flux analysis provides functional insight into macrophage metabolic reprogramming at the level of metabolic pathways that are altered but does not quantify individual metabolites. Enzymatic assays with luminescent, colorimetric or fluorimetric readouts quantify a number of key metabolites. These assays are relatively easy to perform and data analysis does not require specific expertise as is the case for MS analysis. MS in combination with GC or LC allows to cover a wider range of metabolites both known and unknown. It thus allows to follow known key metabolites as well as to potentially gain insights into new metabolites or metabolite patterns. MS analysis can be extended to comprise metabolic flux analysis in order to follow how metabolites are consumed and produced in cell systems and how this varies in the context of changing conditions, for example during the development of DMTII. It is thus of particular interest to combine multiple analytical approaches to gain a comprehensive overview of mechanisms related to macrophage metabolic reprograming. Moreover, even though there is considerable knowledge about metabolic reprogramming during macrophage polarization in cell culture under defined conditions, there is still a large knowledge gap when it comes to diseases like DMTII. Here metabolic changes are key disease features, which most probably will also reflect in changes in the metabolism of macrophages and their polarization. That is why metabolomics in combination with lipidomics, fluxomics, transcriptomics, and proteomics has the potential to lead to the discovery of further mechanistic links between inflammation and metabolic disturbances .A new branch of immunology, called immunometabolism, has been developing rapidly in the past ten years Figure 5We now have clear evidence that macrophages can change metabolic pathways to respond to challenges they encounter. Macrophage polarization and function are highly dependent on fast changes in intracellular metabolism, which explains why macrophages can be extremely versatile in function. While this field is moving forward fast, our understanding of interactions between metabolic changes at the organism level such as found in DMTII/obesity and intracellular metabolic changes in macrophages still lags behind. Macrophages in adipose tissue from individuals with DMTII or obesity clearly show a different but pro-inflammatory phenotype from those of lean individuals or individuals without DMTII. However, those pro-inflammatory phenotypes appear to be unique to DMTII and obesity and are not found when macrophages are M1-polarized in acute inflammation , suggestA better understanding of interaction between different metabolic pathways could also result in the development of new treatment options. Diabetes treatment now focuses on weight loss, rebalancing insulin resistance, and lowering blood glucose levels by using mostly gluconeogenesis inhibitors like metformin or hypoglycemic drugs that stimulate β-cells to release insulin . While wvia epigenetic regulation of gene expression. Recent studies indicate that chronic inflammation is linked to changes in energy metabolism via lysine acetylation of both histones and non-histone proteins (Another aspect that should be further investigated and could develop into a promising therapeutic approach is the link between metabolism and inflammation proteins . TherefoSR, MK, NG, RB, and BM conceived and designed the set-up of the manuscript. SR drafted the manuscript and prepared figures. SR, MK, NG, RB, and BM edited and revised the manuscript and all approved the final version. All authors contributed to the article and approved the submitted version.This project has received funding from the European Union’s Horizon 2020 research and innovation program under the Marie Skłodowska-Curie grant agreement No 754425.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Hip arthroscopy is a reproducible and efficacious procedure for the treatment of femoroacetabular impingement syndrome (FAIS). Despite this efficacy, clinical failures are observed, clinical entities are challenging to treat, and revision hip arthroscopy may be required. The most common cause of symptom recurrence after a hip arthroscopy that leads to a revision arthroscopy is residual cam morphology as a result of inadequate femoral osteochondroplasty and restoration of head–neck offset, though several other revision etiologies including progressive chondral and labral pathologies also exist. In these cases, it is imperative to perform a comprehensive examination to identify the cause of a failed primary arthroscopy as to assess whether or not a revision hip arthroscopy procedure is indicated. When a secondary procedure is indicated, approaches may consist of revision labral repair, complete labral reconstruction, or labral augmentation depending on labral integrity. Gross instability or imaging-based evidence of microinstability may necessitate capsular augmentation or plication. If residual cam or pincer morphology is present, additional resection of the osseous abnormalities may be warranted. This review article discusses indications, the evaluation of patients with residual symptoms after primary hip arthroscopy, and the evaluation of outcomes following revision hip arthroscopy through an evidence-based discussion. We also present a case example of a revision hip arthroscopy procedure to highlight necessary intraoperative techniques during a revision hip arthroscopy. The prevalence of hip arthroscopy has increased as techniques for identifying and treating femoroacetabular impingement (FAI) continue to improve. This condition describes the abnormal contact of the femoral head–neck junction with the acetabulum and labral complex due to bony morphological abnormalities in the femoral head and/or acetabulum . AlthougThe leading cause of clinical failure in hip arthroscopy is persistent FAI secondary to residual cam morphology, which may be combined with high-grade chondral damage and labral pathology , 4. StudThe decision algorithm for revision hip arthroscopy can be complex and is affected by a wide range of factors. Current indications for revision arthroscopy and associated outcomes remain unclear and are a focus of this research study. The purpose of this study is to synthesize indications for revision hip arthroscopy following a failed primary arthroscopy using evidence to support these indications when available. Next, we describe the preferred surgical technique of the authors for a case of revision hip arthroscopy and then describe the other surgical approaches that exist. Finally, we will use an evidence-based discussion to describe the outcomes of revision hip arthroscopy. This information can facilitate preoperative discussion and planning between patients and their surgeons and can guide the expectations of patients about the procedure.Ricciardi et al.  found thThere is a wide range of etiologies that may necessitate a revision hip arthroscopy that results in persistent symptoms and dysfunction . DespiteEvaluation of the patient must be thorough to properly guide surgical decision-making. Importantly, another mechanism of failure consists of advanced cartilage pathology. Though patients may present with symptoms mimicking that they experienced prior to their index procedure, patient selection is a crucial aspect in this setting as more advanced stages of osteoarthritis should be treated with hip arthroplasty as to avoid a second failure . TherefoAll patients with symptom recurrence warrant a thorough clinical examination in the postoperative setting. A thorough history may help the surgeon narrow the differential diagnosis. Pain is present in almost all patients and, therefore, non-specific; however, it is useful to prompt investigation into the underlying etiology as it may indicate labral re-tear. Infection should always be ruled out in this setting despite low likelihood, and the surgeon should order tests for complete blood count, erythrocyte sedimentation rate, and C-reactive protein. In patients with concomitant musculoskeletal pathologies, it is important to determine whether this pain is referred from the spine or is a result of intra-articular or extra-articular hip pathology. Patients with instability secondary to microinstability or previous capsulotomy without closure may report subluxation events where they believe their hip is “coming out of their socket” or have apprehension with certain movements that stress the iliofemoral ligament. Hip dysplasia, femoral anteversion >40°, connective tissue disorders, and previous traumatic hip injuries predispose individuals to post-arthroscopic hip instability . As mostInspection of the previous portal incisions should be performed to rule out wound complications as this may point the surgeon to surgical site infection as the etiology of hip pain. Palpation of the pubic tubercle, greater trochanter, anterior superior iliac spine, and sacroiliac joints should be performed as these may point toward core muscle injury, bursitis, or other tendinopathies as the pain generator. Range of motion examination should be performed and compared with the opposite limb. A positive impingement sign can be clinically evaluated by performing the anterior impingement test by moving the hip in flexion, adduction, and internal rotation (FADIR) . Though Repeat imaging of the symptomatic hip following a failed primary hip arthroscopic procedure is essential to understand the etiology. Imaging options to be used include anterior–posterior (AP) pelvis, false profile, and frog-leg or Dunn lateral radiographs, CT scans with or without three-dimensional (3D) reconstruction, and MRI. Plain radiographs of standing AP pelvis and Dunn view with 45° hip flexion can be used to identify residual cam and pincer impingement in addition to over-resection , 17. We An intra-articular hip steroid injection can be particularly important to confirm the surgical indication. A positive response to an intra-articular hip steroid injection is important for confirming the intra-articular nature of the problem. In patients with imaging and clinical examinations, pointing toward the need for revision surgery, but with a negative response to an intra-articular injection consideration of extra-articular sources of pain, should be considered. In particular, extra-articular sub-spine impingement, psoas tendinitis, lumbar spine pathology, and pelvic floor pain are often complicating diagnoses in patients with persistent pain after primary hip arthroscopy. The surgeon should have a lower threshold to perform revision hip arthroscopy in an expeditious manner when symptom recurrence in conjunction with positive imaging findings of a treatable etiology is present as to not predispose the patient to additional morbidity and joint degeneration.The surgical preparation and hip arthroscopy setup are largely identical in all cases of revision hip arthroscopy. The major difference in revision hip arthroscopy is the procedures to be performed based on the history and clinical examination of the patient. The proceeding section briefly describes procedures commonly performed in revision hip arthroscopy.Labral repair is indicated during revision hip arthroscopy when a patient presents with pain, and there is MRI evidence of a labral repair with sufficient tissues to repair. Debridement in the revision setting is uncommon as damaged tissues or re-tears are often not amenable to this treatment due to the quality of the tissue. In cases where the labrum is torn but is irreparable secondary to insufficient remaining tissue or tear size, a labral augmentation or complete reconstruction can be performed . Labral Acetabular rim trimming may be implicated for residual pincer morphology, while additional femoral osteochondroplasty may be implicated in the patient with symptom recurrence and evidence of residual cam morphology. It is imperative that preoperative radiographic indices of cam morphological dimensions can be made in order for the hip arthroscopist to appropriately plan the depth and extent of their resection, as over-resection can lead to instability and inferior outcomes as noted. These procedures are performed through the same approach and portals as used in a primary hip arthroscopy procedure. Intraoperative examination of the cartilaginous components of the femoral head and acetabular should be performed regardless of whether there is evidence of chondral lesions or delamination on preoperative imaging. If identified, focal chondral lesions can be addressed with microfracture, matrix-enhanced chondral implantation , or autoThough we recommend complete capsular closure in all primary and revision hip arthroscopy cases, patients in whom the capsule was not closed or who have capsular and generalized ligamentous laxity should undergo complete capsular closure and/or plication. During revision hip arthroscopy, it is beneficial to establish identical portals in order to access the areas in which the capsule was previously violated in order to be able to successfully close them . In patients with iatrogenic hip instability and without evidence of residual osseous abnormalities, it is appropriate to perform revision hip arthroscopy for capsular repair , 31.Snapping hip syndrome is infrequently an indication for revision hip arthroscopy, though patients may present with this pathology in conjunction with those described above. A recent study has described the use of an endoscopic iliotibial band release during hip arthroscopy for FAIS and coxa sultans external type with good short-term outcomes . There iResearch studies on outcomes and efficacy following revision hip arthroscopy are growing but are limited , 34, 35.Despite many studies reporting statistically significant improvement in all clinical outcomes following revision hip arthroscopy surgery, these outcomes tend to be inferior when compared to patient outcomes following primary hip arthroscopy , 35. LarNwachukwu et al.  describeIn some cases, patients may need a repeat revision hip surgery, i.e., a third hip arthroscopy. Despite the available studies demonstrating improvements in PROs and high survivorship after revision hip arthroscopy, there is a body of evidence reporting on second revision hip arthroscopy and conversion to hip arthroplasty , 6. In aThe leading cause of failure after primary hip arthroscopy leading to revision hip arthroscopy is residual cam morphology and symptom recurrence. The currently available studies suggest that patients undergoing revision hip arthroscopy can achieve good outcomes if indicated appropriately. Therefore, a thorough clinical examination and advanced imaging are imperative. Care should be taken to evaluate for chondral pathology and capsular incompetency in this setting. Failure to address these findings may result in inferior outcomes. The surgical technique should be tailored to the underlying cause for revision arthroscopy. Continued improvements in hip arthroscopy techniques and understanding of risk factors for failure will likely diminish the incidence of revision cases. This review article can be used to inform and guide identification, treatment, surgical decision-making, and expected outcomes of patients indicated for revision hip arthroscopy.SS, RO, and BN contributed to conception and design of the study. RO, SS, and KK conducted literature reviews and data analysis. RO wrote the first draft of the manuscript. KK, SS, and BN wrote sections of the manuscript. KK performed all major revisions of the final manuscript and additional literature review necessary for publication. All authors contributed to manuscript revision, read, and approved the submitted version.BN declares ownership interest in BICMD (founder) outside of the scope of the submitted manuscript. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Of all mammals, bat possess the most unique and peculiar adaptations that render them as excellent models to investigate the mechanisms of extended longevity and potentially halted senescence. Indeed, they are the longest-lived mammals relative to their body size, with the oldest bat caught being >41 years old, living approx. 8 times longer than expected. Bats defy the ‘rate-of-living’ theories that propose a positive correlation between body size and longevity as they use twice the energy as other species of considerable size, but live far longer. The mechanisms that bats use to avoid the negative physiological effects of their heightened metabolism and deal with an increased production of deleterious Reactive Oxygen Species (ROS) is not known, however it is suggested that they either prevent or repair ROS damage. Bats also appear to have resistance to many viral diseases such as rabies, SARS and Ebola and are the suspected reservoir species for a huge diversity of newly discovered viruses, including Sars-CoV-2 This suggests that their innate immunity is different to other mammals, perhaps playing a role in their unexpected longevity. Here the potential genomic basis for their rare immunity and exceptional longevity is explored across multiple bat genomes and divergent ageing and immune related markers  studied in wild bat populations. These findings provide a deeper understanding of the causal mechanisms of ageing and tolerant immunity, potentially uncovering the key molecular pathways that could be utilised to benefit society.


Across different cell types and within single cells, mitochondria are heterogeneous in form and function. In skeletal muscle cells, morphologically and functionally distinct subpopulations of mitochondria have been identified, but the mechanisms by which the subcellular specialization of mitochondria contributes to energy homeostasis in working muscles remains unclear. Here, we discuss the current data regarding mitochondrial heterogeneity in skeletal muscle cells and highlight potential new lines of inquiry that have emerged due to advancements in cellular imaging technologies. Skeletal muscle cells function to convert biological fuels to mechanical force and are therefore critical to many physiological functions, including movement and metabolism. During sustained muscle contractions, the process of cellular energy transduction is largely mediated by the energy-converting function of the mitochondria and the force-generating capacity of the myofibrils. Specifically, mitochondria convert biological fuels to the high energy molecule adenosine triphosphate (ATP) through oxidative phosphorylation, and ATP is used by the myofibrillar ATPase to generate force during contraction. Although the vast majority of muscle cell volume is dedicated to the myofibrillar matrix , mammali2+ signaling from the sarcoplasmic reticulum (SR)  form complex, elongated shapes  with bralum (SR) , so IFMslum (SR) . Studieslum (SR) . Althouglum (SR) , but it trans-mitochondrial alignment of cristae  , but mucWhile the primary function of the IFM is somewhat intuitive when considering their intricate spatial relationships with the energy-hungry myofibrils, it is unclear why evolution would favor the separate subgroups of morphologically distinct mitochondria found in clusters near the cell boundary. As noted above, greater mitochondrial volume observed near the cell boundary supports greater energy conversion than the smaller mitochondria residing within the intermyofibrillar spaces, and therefore, some investigators have postulated that PM function to directly support the IFM by generating and distributing energy. As early as the 1960s, Romanul and colleagues found mitochondrial oxidative enzyme activity to be higher in mitochondria located adjacent to capillaries compared to mitochondria within the interior regions of the muscle cell , 1965. UTo explore the subcellular specialization of mitochondrial function within skeletal muscle cells, investigators have established techniques that aim to specifically isolate intermyofibrillar mitochondria from the total mitochondria pool within muscles. These techniques typically incorporate a tiered purification method that separates mitochondria according to their degree of interactivity with contractile proteins. Mitochondria isolated from homogenized muscle tissues before protease treatment are considered to have less interaction with contractile proteins and are therefore classified as SSM, whereas mitochondria isolated after digestion are classified as IFM. Although this approach has been implemented in many studies and models , experimDespite these methodological concerns surrounding isolated preparations of mitochondrial subgroups, experiments in isolated mitochondria have produced interesting results when evaluating the apoptotic and ROS-generating capacity of mitochondria. For example, Hood and collaborators demonstrated that IFM isolated from the quadriceps muscles of mice are more sensitive to the apoptotic stimulus hydrogen peroxide compared to SSM . Althougin vivo mitochondrial energy conversion. Although this work found the energy conversion rate to be consistent across PVM and IFM subpopulations, we found the PVM to be more oxidized than the IFM (2+ signaling, apoptosis, fuel importation, and biosynthesis.More recent imaging studies have brought some clarity to the diversification of mitochondrial function within living cells by using 3D and 4D imaging strategies to directly evaluate mitochondrial respiratory enzymes, mitochondrial redox, and even the rate of mitochondrial energy conversion within an intact network . Certain the IFM . In keepSubpopulations of mitochondria may also be differentially influenced by exercise training and pathologies. For example, over 40 years ago, a series of imaging studies provided evidence that SSM are more responsive to changes in energetic demand than IFM  by showiin vivo functions of many mitochondria-organelle contact sites have not been determined in striated muscle cells, and it is unclear whether or not the molecular architecture of mitochondria-organelle contact sites within skeletal muscle cells is consistent with those observed in cell cultures and other tissues. Future experiments may address these questions by using high-resolution and live-cell imaging strategies to map organelle connectivity across large subcellular volumes and comparing the functional capabilities between subpopulations of mitochondria under different experimental conditions. As discussed, recent advancements in high-resolution 3D imaging and automated image analysis have greatly expanded our capacity to measure the subcellular distribution of mitochondrial morphology and mitochondria-organelle interactivity, but contemporary nanoscale imaging strategies, such as EM, are still limited in their ability to provide molecular and functional information. Therefore, answering the many questions that remain surrounding the subcellular specialization of mitochondrial form and function in skeletal muscle cells will require innovative imaging strategies that evaluate mitochondrial function, composition, and structure at the subcellular level with molecular specificity.Recent advancements in nanoscale imaging technologies have greatly expanded our capacity to investigate subcellular structure, and applications of contemporary techniques have shed new light on mitochondrial biology. Work from Lippincott-Schwartz , NunnariAll authors listed have made a substantial, direct and intellectual contribution to the work, and approved it for publication.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


There continues to be an erroneous belief that allergens  are more resistant to gastrointestinal digestion than non-allergens. Government regulations based on this erroneous belief may result in technology developers altering the amino acid sequences of digestively stable native proteins to create digestively unstable modified versions for expression in genetically engineered crops. However, an investigation where a known stable allergen was modified to make it more digestible eliminated the protein’s ability to tolerize against allergy in a mouse model, which is consistent with the dual allergen exposure hypothesis. Thus, the false belief that digestive stability increases the allergenic risk of novel food proteins  could, in some cases, lead to introduction of digestively unstable modified protein versions with greater sensitization risk. However, it is noteworthy that developers have historically been very effective at preventing allergens from being introduced into crops based on the other components of the weight-of-evidence assessment of allergenic risk such that no newly expressed protein in any commercialized genetically engineered crop has ever been documented to cause allergy in anyone. Similar to antibiotics, alteration of the human microbiome is the likely mechanism by which acid-suppressant medications increase allergy rates  was reduced by modifying its amino acid sequence . In a moin vitro digestion assays. If the protein is found to be stable in these assays, developers are motivated to modify the amino acid sequence to be more digestible while maintaining its beneficial activity (The preceding example highlights the potential risk of government regulation for genetically engineered crops based on the erroneous belief that gastro-intestinal digestibility decreases allergenic risk. Current government regulations for newly expressed proteins in genetically engineered crops universally consider gastro-intestinal stability to be a risk factor for allergenicity . Thus, tactivity . While dactivity .The current scientific evidence does not indicate a positive or negative correlation between gastro-intestinal digestion and the allergenic status of proteins . Governm