Polycystic ovary syndrome (PCOS) is the most frequent endocrinological anomaly in reproductive women that causes persistent hormonal secretion disruption, leading to the formation of numerous cysts within the ovaries and serious health complications. But the real-world clinical detection technique for PCOS is very critical since the accuracy of interpretations being substantially dependent on the physician's expertise. Thus, an artificially intelligent PCOS prediction model might be a feasible additional technique to the error prone and time-consuming diagnostic technique. In this study, a modified ensemble machine learning (ML) classification approach is proposed utilizing state-of-the-art stacking technique for PCOS identification with patients' symptom data; employing five traditional ML models as base learners and then one bagging or boosting ensemble ML model as the meta-learner of the stacked model. Furthermore, three distinct types of feature selection strategies are applied to pick different sets of features with varied numbers and combinations of attributes. To evaluate and explore the dominant features necessary for predicting PCOS, the proposed technique with five variety of models and other ten types of classifiers is trained, tested and assessed utilizing different feature sets. As outcomes, the proposed stacking ensemble technique significantly enhances the accuracy in comparison to the other existing ML based techniques in case of all varieties of feature sets. However, among various models investigated to categorize PCOS and non-PCOS patients, the stacking ensemble model with ‘Gradient Boosting’ classifier as meta learner outperforms others with 95.7% accuracy while utilizing the top 25 features selected using Principal Component Analysis (PCA) feature selection technique. •Proposed a modified stacking ensemble ML classifier to detect PCOS from patient symptoms.•Applied 3 feature selection methods to extract sets with varying numbers & mixtures of attributes.•Proposed methodology & existing ML approaches are trained & tested with different feature sets.•Examined the essential attributes and efficacy of the suggested ensemble methodology.•The proposed classifier outperforms with top 25 dominant features picked as per PCA technique. One from five different kinds of boosting or bagging ensemble classifier  have been employed and evaluated as the meta learner of the model with an aim to explore the best performing stacked ensemble model in this scenario.•For exploring the dominant features required for predicting PCOS, three different types of feature selection techniques  have been employed here. Each feature selection techniques select the different sets of features with different numbers and combinations of attributes from the dataset employing their own feature prioritization methods which are then applied to the machine learning classifiers to detect PCOS.•To validate the efficacy and potency of the proposed technique, other ten types of classifiers are also employed to attain the same objective which include five types of conventional classifiers , one bagging ensemble classifier (Random Forest) and four types boosting ensemble classifiers . Then a meticulous comparative performance analysis has been conducted between the traditional classifiers, bagging and boosting ensemble classifiers and the proposed stacking ensemble models through different performance parameters utilizing different sets of features obtained from feature selection techniques.Therefore, the purpose of this research is to explore several traditional as well as ensemble types of machine learning classifiers to predict PCOS and also to propose an ensemble machine learning classifier based on stacking approach that employs the minimal and optimal amount of prioritized features for more efficiently detecting PCOS through patients' symptoms and test result dataset. The key contributions which has been done to acquire the objective of this research work are listed hereafter.The remaining sections of the article are structured as follows: Section 2PCOS has been linked to a number of disorders resulting in diverse symptoms in patients' bodies compared to normal ovulatory women, including type-2 diabetes, cardiovascular anomalies, hypertension, dyslipidemia, insulin resistance, increased Endometrium thickness and so on Thus, number of studies have been conducted to investigate computer-assisted PCOS detection techniques, which offer substantial advantages such as rapid identification of the condition in the shortest time frame with the least amount of diagnostic error and human effort. For example, to categorize between PCOS and non-PCOS criteria, Danaei et al. Since PCOS is associated with a wide range of symptoms as features, a few studies have emphasized on employing various feature reduction approaches before using machine learning models to accelerate the training process. For example, Inan et al. Now, a potential state-of-the-art approach for several machine learning challenges is ensemble methodologies, as they can significantly improve the performance of a single model's forecasting by training multiple models and combining those results From the previous related works it is also observable that, most of the studies have picked a specific reduced subset of features from the existing dataset through applying feature reduction techniques and then performed machine learning classification using that reduced feature subset. But, hardly any studies have explored multiple reduced feature subsets with different numbers and combinations of attributes from the complete dataset. Also, rarely they have investigated how the performances of various machine learning classification techniques might alter when different feature subsets with various combinations and numbers of attributes extracted from multiple feature reduction methods are being used. Furthermore, less attention has been made on investigating and validating whether the retrieved decreased features are genuinely important or not in terms of real-life clinical diagnosis of PCOS via a cross-check involving relevant healthcare specialists.Thus, this research focuses on addressing these research gaps in this area with the goal of detecting PCOS more effectively and efficiently utilizing the optimum numbers of features. Therefore, a stacking ensemble classifier has been designed, trained, and evaluated as well as the performances of various forms of ensemble and conventional machine learning approaches have been investigated in this study, employing different sets of attributes acquired from feature selection methods.3An extended ensemble ML classifier has been proposed, trained and tested using patient's most significant set of symptom data to differentiate between PCOS & non-PCOS patients in this study. A framework of the research methodology is presented in 3.1A dataset containing the symptoms along with the PCOS diagnosis findings of patients has been utilized here as the training data for supervised machine learning models, for which a publicly available data collection of PCOS patients from ‘Kaggle’ Again, the relationship between target column with other attributes has been examined using various visualization approaches. For example, the 3.2In this work, the dataset has been critically analyzed and preprocessed before using them into machine learning models to address the flaws and irregularities in the datasets such as missing or contradictory data samples, inconsistencies, noise, and other issues. The following steps have been employed for preprocessing the dataset.Firstly, for data preprocessing the null values have been handled. Features with too many null or missing values have been completely removed from the dataset because they don't give any useful information; for example, the feature ‘Unnamed’ in the dataset contains 539 null values for which it has been eliminated. The features comprising a few null values have been substituted with other relevant values; for example, ‘Marriage Status (Yrs)’ and ‘Fast Food (Y/N)’ contains a few null values which have been replaced with 0.x and Secondly, the data balancing has been done for making the classes equally distributed for training, as the dataset has imbalanced target attribute with 364 records of non-PCOS and 177 records of PCOS patients. Therefore, the dataset has been over-sampled using ‘Synthetic Minority Oversampling Technique (SMOTE)’ method that generates a synthetic sample of a minority class to eliminate the imbalance in the target attribute values The third step has been to Drop Unnecessary Columns. At this step, superfluous or duplicated columns have been removed in order to improve forecasting accuracy. One of two columns giving the same information has been kept, while the other has been deleted from the dataset. For example, ‘I beta-HCG(mIU/mL)’ numerical column and ‘II beta-HCG(mIU/mL)’ categorical attribute provide same information from which ‘II beta-HCG(mIU/mL)’ has been discarded. Also the unnecessary columns ‘Sl. No.’ and ‘Patient File No.’ have been discarded from the dataset as they contain simply the serial numbers, patient's file no which can be ignored for further analysis.x where The next step is data normalization in which the values of the dataset are normalized using the MinMax Scalar approach to reduce the influence of variance in measurement units of different features and eliminate attribute bias with sensitivities Finally, as the last step of data preprocessing, the dataset has been divided into train and test datasets for applying them to classification models of machine learning, with 30% of the instances randomly assigned to the test dataset and the remaining 70% assigned to the train dataset.3.3•Chi-Square Technique: Chi-square feature selection technique is one of the most frequent and helpful feature selection strategies used in machine learning •Principal component analysis (PCA) Technique: The second type of technique that has been used for feature selection in this study is the Principal component analysis (PCA) method, which is an efficient dimension reduction tool for feature prioritization utilizing numerical analysis which is accomplished by assessing the correlation between characteristics in order to determine the most important or principal components •Recursive Feature Elimination (RFE) Technique: Recursive Feature Elimination, or RFE, is an efficient wrapper-type strategy that has been utilized in this study for removing features from a training sample for feature selection which ranks the set of attributes and eliminates them at the bottom that contribute the lowest to the categorization Feature selection is an efficient method for picking the most significant attributes and avoiding unimportant features to improve the prediction capacity and accuracy of machine learning algorithms To explore the highly significant attributes that would yield the best performing accuracy when used in machine learning models, each type of feature selection approach selects the top 35, 30, 25, and 20 features from the PCOS dataset of 40 features. The algorithm followed for extracting the reduced set of features from the dataset in this study is shown in 3.4Classification is a machine learning technique that uses a model learned from training data to forecast the category of samples and therefore maps or classifies data instances into the associated class labels which have been predefined in the provided dataset 3.4.1•Traditional ML Classifiers: Although for conducting predictive analytics, a number of classification strategies with the ability to predict outcomes are employed, certain traditional machine learning classification methods have been widely employed to estimate a variety of clinical anomalies in numerous research. Here, technique 1 employs five kinds of well-known and widely utilized traditional machine learning classification techniques with fundamental algorithmic structure which are appropriate to this target area. The models are Logistic Regression classifier, Support Vector Machine classifier, Decision Tree classifier, K-Nearest Neighbour classifier and Naive Bayes classifier. These machine learning classifiers have been applied extensively in a variety of healthcare-related predictive studies. •Bagging Ensemble ML classifiers:A bagging classifier or bootstrap aggregation classifier is an ensemble method that fits multiple base classification models on randomized subsets of the dataset with the same weights given to each model and then aggregates their individual predictions to generate a final result •Boosting Ensemble ML classifiers:Boosting is an ensemble machine learning approach in which a random sample data is chosen, fitted with a model, and then trained in a sequential manner, combining a set of weak learners into a strong learner with an aim to minimize training errors, with every model attempting to compensate for the shortcomings of the previous model 3.4.2To achieve greater forecasting performance than a single classifier, ensemble learning employs multiple classifiers; where Stacking ensemble learning is the technique that use a meta-classifier to aggregate various weak classifiers. The likelihood of belonging to a class is returned by the first layer's classifiers as a meta-feature; than these meta-features with the dataset are the input for the meta-classifier in the second level. Finally, the classifier's output can be either 1 or 0 The proposed model is a multi-level stacked ensemble model where after preprocessing the raw data sample, it is being divided into train and test data and then initially sent to the base learners of level 0. At this phase, the five types of widely utilized traditional machine learning classifiers have been considered to be the weak learners or base classifiers at level 0 of the stacked model, which are: Logistic Regression (LR), Support Vector Machine (SVM), Decision Tree (DT), K-Nearest Neighbour (KNN) and Gaussian Naive Bayes (NB) classifiers see . These b4In this study, to evaluate and compare the efficacy of the predictive models for PCOS detection, total four types of ML techniques have been performed employing fifteen varieties of ML classifiers including the traditional (five models), bagging (one model), boosting (four models) and proposed (five models) techniques. All the experiments have been simulated using patient symptom dataset for classifying the records into PCOS and non-PCOS criteria. Furthermore, to explore the optimum and most significant attributes from the dataset, three types of feature selection methods  have been employed which picked the top 35, 30, 25 and 20 features out of the 40 features of the dataset. Each ML model's performance has then been evaluated employing these different sets of features acquired from feature selection techniques.The performance of different varieties of machine learning algorithms utilizing different sorts of feature sets is analyzed using four performance measures, which are Accuracy, Precision, Sensitivity , and F1 score, to investigate the efficacy of the prediction analysis The findings of this rigorous evaluation process have been shown in 4.1Analyzing the evaluation results from 4.2The different feature selection methods utilized here have selected different sets of attributes employing their own methodologies. A list has been given in From the comparative evaluation with graphical representation in However, when using the PCA feature selection approach, most of the models' accuracy consistently improves with reduced features and has reached its peak with the top 25 features. Therefore, from the overall performance analysis, it is observable that, the traditional machine learning models, are explored as being weak classifiers in the context of this dataset and produce the weaker performances which eventually gives a bit better result through bagging and boosting type of ensemble classification models. On the other hand, as a result of the proposed stacked ensemble models' robust formulation, which incorporates the predictive analytics of several classifiers, the results show that each version of the suggested stacked ensemble approaches yields superior outcomes. Also, in terms of feature engineering, the selected features through PCA technique provide better results employing the classification models while chi-square technique provides least performances. Thus, the results of performance analysis indicate that, the machine learning model employing the proposed stacking ensemble method with five classifiers  as base models and GradBoost classifier as meta learner; utilizing the top 25 attributes from the dataset selected through PCA feature selection technique has been explored to be the highest performing classification model with 95.7% accuracy, 95.2% precision, 95.2% recall and 95.0% F1-score that outperforms all other models to classify PCOS and non-PCOS criteria.5In this article, three types of ensemble machine learning strategies  with multiple classifiers have been explored, trained and tested along with traditional machine learning techniques to classify PCOS and non-PCOS data. Most of the previous studies in this area were based on traditional ML classifiers. However, recently a few researchers have focused on applying ensemble techniques in PCOS detection, but their exploration techniques are based on typical bagging, boosting or voting type of ensemble models Furthermore, using feature selection strategies, the majority of previous studies randomly picked a specified number of features. For example, Bharti et al. 66.1The methodology presented in this study can be a pioneer in effectively detecting PCOS from patients symptoms and test results through machine learning strategies and thereby can play a potentially beneficial role in improving the reproductive health of thousands of women. The findings of this study can be significantly beneficial towards both patients and healthcare providers in identifying PCOS quickly and efficiently combining the advantages of multiple machine learning classifiers ensembled in one robust model employing minimal number of attributes and thus it is anticipated to be widely used in the real-world clinical practices. The study's outcome can be effectively helpful for the physicians in the arduous task evaluating patients by simplifying the complex diagnostic procedure of PCOS. This computational technique can be deployed in the healthcare facilities of rural areas to detect PCOS autonomously where there is scarcity of expert physicians and resources.6.2Yet, owing to a lack of vast dataset, one of the study's flaws was that it only used machine learning algorithms on a small number of patient data. Real-time data couldn't have been acquired; the dataset was taken from an open source resource. Also, the five traditional ML model categories that have been used as base classifiers in the proposed stacked ensemble model were chosen based on their prominence in this field in earlier studies. The performance might have been different if other types of Ml classifiers had been utilized here. Moreover, the varied number of reduced set of features  explored by the feature selection technique have been chosen randomly for this study. In addition, for intelligent clinical applications, explainable AI plays an important role in providing an explanation alongside sufficient justification of AI system predictions, which has not been included in this study. Therefore, the authors hope to investigate more about PCOS detection using larger datasets as well as more types of feature selection techniques in the future incorporating the techniques of eXplainable AI (XAI) with the current study, as well as implement the proposed methodology in other fields of clinical illness predictions.This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.Sayma Alam Suha - Conceived and designed the experiments; Performed the experiments.Muhammad Nazrul Islam, Sayma Alam Suha - Analyzed and interpreted the data; Contributed reagents, materials, analysis tools or data; Wrote the paper.The authors declare no conflict of interest.


A 41-year-old, New Zealand European male, was seen in the acute eye clinic as an in-patient from the trauma ward with multiple comorbidities including an orbital fracture from injuries sustained in a road traffic accident. It is not uncommon in emergency settings for emergency physicians to review polytrauma patients prior to Ophthalmologists, with Computerized Tomography being the imaging modality of choice. A hyper-dense lesion within the right globe was noted by radiology at the time and concerns were raised about the possibility of a retained intraocular foreign body. Upon Ophthalmic examination, a clinical diagnosis of sclerochoroidal calcification was made. This case highlights a rare case of sclerochoroidal calcification manifesting as a hyperdense lesion on computerized tomography masquerading as an intraocular foreign body. Globally it is estimated that 55 million eye injuries occur annually Radiographic evaluation in the assessment of intraocular foreign bodies is essential, as often patients may present with polytrauma, and history or physical examination can often be limited by the severity of the injuries. Magnetic resonance imaging of any metallic foreign body is contraindicated due to the magnetic field generated causing any metallic material to become dislodged, damaging ocular structures along its trajectory This case highlights sclerochoroidal calcification, an idiopathic and usually benign ocular condition that masqueraded as an intraocular foreign body on CT imaging of a patient presenting with polytrauma.A 41-year-old, New Zealand European male, was seen in the acute eye clinic as an in-patient from the trauma ward with multiple comorbidities sustained from a car vs bicycle collision. the patient ejected off their bicycle and sustained a multitude of injuries relating to multiorgan perforations, lacerations, and fractures. Most notably, a right tripod facial fracture was detected with concerns raised as to the integrity of the globe and its structures.Once the patient was stabilized, follow up examinations for the tripod fracture were arranged by the Maxillofacial department with Ophthalmology input requested to investigate the possibility of a retained IOFB, given the hyperattenuating lesion noted in the right eye on CT imaging .Fig. 1 imaging through the right retinal lesion was obtained  which shA diagnosis of a right unilateral scleral choroidal calcification at the site of the superior oblique insertion was made with no globe injury related to the trauma. At maxillo-facial review, a decision was made not to repair the orbital fracture given the absence of diplopia and enophthalmos. The patient was discharged back to the care of their optometrist for regular review included dilated fundoscopy and EDI-OCT scans of the sclerochoroidal lesion.This case highlights 2 main points: Ocular injuries and to a lesser extent retained intraocular foreign bodies, are extremely common in tripod facial fractures, requiring acute ophthalmology collaboration. Secondly, increasing the recognition of sclerochoroidal calcification as a masquerading condition to retained intraocular foreign body amongst other differential diagnoses.Ocular injuries are common amongst facial fractures, highlighting the need for acute ophthalmology input. Al-Qurainy and colleagues  demonstrCT is the most practical step in assessing trauma cases as it is readily available and can detect not only osseous damage but a wide range of metallic intraocular foreign bodies safely at small limits of detection . Most meThe challenge arises when other conditions, such as sclerochoroidal calcification, masquerade as retained intraocular foreign bodies due to similar hyper dense appearances on CT imaging. Sclerochoroidal calcification is an idiopathic, usually benign, yet uncommon condition characterized by yellow-whitish subretinal lesions classically located in the superior temporal midperiphery of the fundus beyond the vascular arcades . DespiteIn some rare cases, there may be systemic conditions associated with metastatic sclerochoroidal calcification usually involving abnormal calcium phosphorus metabolism or renal tubular hypokalemia metabolic alkalosis syndromes . PatientThis case is a rare example of a singular unilateral lesion found in a uniquely young individual, under exceptional circumstances. Due to the complicated nature of this polytrauma scenario, specifically affecting the periorbital region, an initial diagnosis of intraocular foreign body was made based on CT findings. This case not only highlights this poorly understood entity, but it also demonstrates the significant power of interspecialty collaboration alongside multimodal imaging techniques on masquerading conditions.In summary, sclerochoroidal calcification is a rare and usually benign condition which may masquerade as a retained intraocular foreign body as in the case of this patient. As CT is usually the first imaging modality used in trauma cases, radiologists are among the first to assess scans and as such hyper dense lesions within the globe are more commonly thought to be as a result of retained intraocular foreign bodies, therefore adding complexity in differential diagnoses. Furthermore, this case highlights the benefits of multimodal imaging and likewise demonstrates a typically rare ocular condition of sclerochoroidal calcification.Written informed consent was obtained from the patient for the publication of this case report.


Exposure to childhood victimisation  can detrimentally impact later psychosocial adjustment. However, this is not the case for all victimised children; some do well despite their experiences and are considered to be resilient. Understanding the factors associated with such resilience is important to inform interventions to support better psychosocial outcomes among victimised children. This review provides an overview of the extant research examining resilience factors for psychosocial outcomes during the transition to adulthood following exposure to childhood victimisation. Studies were identified through a systematic literature search of Embase, PsychINFO and Ovid MEDLINE databases. The 26 included studies spanned a range of psychosocial outcomes between ages 18–25, including education and work, housing and independent living, criminal behaviour, victimisation, and social and psychological adjustment. For each outcome, a variety of putative resilience factors had been investigated including those related to the individual, their family and the wider community within which they lived. However, because few studies had comparable resilience factors and psychosocial outcomes, it is difficult to draw conclusions about which factors are consistently associated with resilience to a particular psychosocial outcome. Additionally, this review revealed that the included studies were of variable methodological quality – many were limited by cross-sectional designs with retrospective self-reports of childhood victimisation, and convenience or unrepresentative samples. In this review, we also highlight gaps in knowledge about the co-occurring impact of multiple resilience factors in combination and the need for studies conducted in non-Western and low- and middle-income countries. Childhood victimisation – that is, exposure to abuse, neglect, domestic violence or bullying – affects the lives of millions of children around the world . These eAlthough there has been much focus on the negative impacts of childhood victimisation, not all children with these experiences go on to have such poor psychosocial outcomes; some do well and are therefore considered to be ‘resilient’ . For insThis resilience framework provides a useful means to understand why some children are resistant to the negative effects of their victimisation exposure. Factors may be associated with resilience following childhood victimisation via (i) a direct relationship (main effect) that increases positive outcomes or decreases poor outcomes or (ii) they may buffer the negative effect of the childhood victimisation (interaction effect). The identification of such ‘promotive’ and ‘protective’ factors (collectively referred to here as ‘resilience factors’) is important to illuminate potential mechanisms and targets for interventions to support better psychosocial outcomes among victimised children.Existing systematic reviews of resilience factors have focussed on maltreatment  as the childhood victimisation exposure of interest . MoreoveThe transition to adulthood is especially prominent for individuals exposed to childhood victimisation who live in out-of-home placements  as they are emancipated from – or ‘age out’ of – the care system, usually around the age of 18. Unlike those who live at home, relying on family support while they gradually gain independence is often not an option that is available to those leaving care. Seeking to fill this gap are policies of extended care beyond the age of 18 and programmes to support the leaving care transition in some countries and US states. Nevertheless, navigating the transition to adulthood in the context of leaving care is especially challenging. Understanding factors associated with psychosocial resilience during this transition is therefore critical.To address the identified knowledge gaps and augment existing work, our systematic review focusses on factors associated with resilience to psychosocial outcomes during the transition to adulthood. Consistent with evidence on poly-victimisation, whereby different forms of victimisation are found to frequently co-occur , we do nAn electronic search was conducted of Embase, PsychINFO and Ovid MEDLINE databases for peer-reviewed journal articles written in English and published before December 02, 2019, that examined resilience factors associated with psychosocial outcomes during the transition to adulthood following childhood victimisation See . We searIdentified titles and abstracts were screened by one researcher (RML). Two researchers (RML and JBN) independently screened full texts and any inconsistencies were resolved through discussion with a third researcher (HLF). Data extracted included author names, date of publication and country of study as well as information related to sample size and selection; participant characteristics and retention; study design; childhood victimisation exposure; measurement of victimisation, resilience factor(s), and outcome(s); analytic approach; and key findings. The methodological quality of included quantitative studies was assessed by RML in consultation with HLF using an adapted version of the Newcastle–Ottawa Scale for cohort studies , which iAs shown in N = 1) and quantitative (N = 25) with cross-sectional (N = 13) and longitudinal (N = 13) designs. They were published between 2005 and 2019 with 85% published since 2011. The majority of the studies (58%) were conducted in the United States and, with the exception of one study in China, all were conducted in Western, educated, industrialised, rich and democratic (WEIRD) countries. The assessed methodological quality of the quantitative studies ranged from a score of one to nine out of 11, with a median score of four. The quality assessment score for each quantitative study is shown in Included studies were qualitative  status; income; social assistance dependency), housing and independent living , criminal behaviour , victimisation , social outcomes  and psychological outcomes . The evidence regarding factors associated with resilience in each of these psychosocial areas is summarised below.Education and work. Six studies explored factors related to resilience in education and work following exposure to childhood maltreatment  and independent living skills (n = 1) during the transition to adulthood following exposure to childhood maltreatment . We identified five quantitative studies that examined resilience factors associated with received and/or perpetrated victimisation during the transition to adulthood (dulthood . Three sdulthood  to six (dulthood  out of 1n = 3) examined the potential beneficial effect of a two-parent family structure and positive relationships with family and friends. Having two married parents was found to be associated with lower concurrent levels of received and perpetrated physical aggression in dating relationships for victimised and non-victimised individuals alike , retrospectively measuring abuse and neglect among university students and longitudinal (n = 2), either using a sample of individuals who had been the subject of child maltreatment investigations or comparing females exposed to child sexual abuse with a non-abused comparison group. The assessed quality of the studies ranged from three  were found to be concurrently associated with lower levels of interpersonal distress in a sample of female university students . HoweverThe expression of genuine positive emotion (e.g. genuine smiles and laughter) was examined by the third study . This waPsychological outcomes. We identified six studies that examined resilience factors associated with psychological outcomes including post-traumatic growth   PTG; , feelingce) PTG; , self-esce) PTG; , and posce) PTG; . Studiesce) PTG; , whereasTwo studies examined life satisfaction during the transition to adulthood – one following childhood exposure to intimate partner violence IPV;  and the In two other studies of individuals who experienced childhood abuse and/or neglect, optimism, religious coping , positive reframing, acceptance and emotional support were found to be associated with higher levels of PTG at the transition to adulthood . FurtherLastly, childhood bullying was found to be related to feelings of shame during the transition to adulthood via reduced feeling of self-compassion suggesting that promoting self-compassion following exposure to bullying may protect against subsequent feelings of shame .Multi-domain psychosocial outcomes. Two quantitative studies examined multiple psychosocial outcomes in combination; one was cross-sectional and used a sample of university students’ retrospective reports of maltreatment , the family  and community . Whilst there is evidence for some resilience factors for psychosocial functioning during the transition to adulthood following childhood victimisation, the small number of studies with comparable resilience factors and psychosocial outcomes precludes us from drawing firm conclusions about which are consistently associated with resilience to particular psychosocial outcomes. Further research in this area is therefore needed to bolster the evidence base  during the transition to adulthood following childhood victimisation; but in the context of severe childhood maltreatment and exposure to domestic violence, close family relationships were associated with increased vulnerability for perpetration and experience of victimisation . Though The methodological quality of the reviewed studies was wide-ranging. The use of prospective longitudinal study designs with a clear temporal order of victimisation, resilience factor(s) and psychosocial outcome(s) are vital to help clarify the direction of observed associations. However, we found that a large proportion of studies in our review relied on cross-sectional designs using individuals’ retrospective reports of childhood victimisation. This has the potential to introduce time-related memory biases such as inaccuracy due to delay  and the An additional methodological concern highlighted by our review was the use of convenience and other non-representative samples. Studies that use methods to achieve a sample that is representative of the target population (e.g. random or stratified sampling) allow us to generalise their findings to this population with greater confidence than studies that simply select from the target population people who are available at the time. This convenience approach biases the sample, undermines its representativeness and, thus, reduces the generalisability of the study findings to the target population. For instance, several studies in our review used samples of university students to examine resilience during the transition to adulthood. Whilst this may be relevant and of value for work focussed on educational resilience following childhood victimisation, it captures a very particular demographic that likely represents individuals who are functioning relatively well. This therefore limits the conclusions that can be drawn from this sample regarding resilience to other  psychosocial outcomes.Finally, our review highlighted the preponderance of research in WEIRD countries. Childhood victimisation and its detrimental psychosocial impacts are a global concern ; howeverThese findings should be considered in the context of some important study limitations. We focussed on childhood victimisation defined as exposure to abuse, neglect, domestic violence and bullying, and therefore, we have not included other exposures such as racial victimisation and community violence. Despite our comprehensive search strategy, there may be relevant studies that were not identified or included in the review including unpublished studies and other grey literature. Given the very large number of records identified by our search, we had only one author undertake the initial screening. Our literature search was limited to studies published in English therefore relevant studies that are published in other languages may exist. This latter point is particularly pertinent to our finding of few studies in non-WEIRD samples.Despite the noted limitations, this review provides a comprehensive overview of the current literature regarding factors associated with resilience to psychosocial outcomes in the transition to adulthood following exposure to childhood victimisation. We highlight gaps in current knowledge, methodological limitations of existing evidence and the need for future research that examines multiple resilience factors in combination, utilises longitudinal designs, prospectively reported victimisation and samples from diverse contexts.There is evidence that there are a number of resilience factors for psychosocial outcomes during the transition to adulthood following childhood victimisation, suggesting that interventions that target these may successfully boost resilience.Although some factors reduce the impact of childhood victimisation on psychosocial outcomes, these individuals may remain at higher risk of poor outcomes than their non-victimised peers.Practitioners working with individuals exposed to childhood victimisation should be aware that factors associated with resilience to one psychosocial outcome do not necessarily also promote resilience to a different outcome. It is possible for something (e.g. close parent–child relationships) to be both a resilience factor and a vulnerability factor depending on the victimisation exposure and outcome of interest.Most studies examine only one or a few resilience factors. Future research should examine multiple factors in combination to understand the co-occurring resilient influences on psychosocial functioning during the transition to adulthood for those exposed to childhood victimisation.Research is needed from low- and middle-income countries to illuminate whether resilience factors differ in these contexts.


Supermarkets are the primary source of food for many people yet their full potential as a setting to encourage healthy dietary-related behaviours remains underutilised. Sharing the experiences from research groups who have worked with supermarket chains to evaluate strategies that promote healthy eating could improve the efficiency of building such relationships and enhance the design quality of future research studies.A collective case study approach was used to synthesise experiences of engaging and sustaining research collaborations with national supermarket chains to test the effectiveness of health-focused in-store interventions. The collective narrative covers studies conducted in three high-income countries: Australia, the Netherlands and the United Kingdom.We have distilled our experiences and lessons learned into six recommendations for conducting high quality public health research with commercial supermarket chains. These include: (i) using personal contacts, knowledge of supermarket activities and engaging executive management to establish a partnership and allowing time to build trust; (ii) using scientifically robust study designs with appropriate sample size calculations; (iii) formalising data exchange arrangements and allocating adequate resource for data extraction and re-categorisation; (iv) assessing effects at individual/households level where possible; (v) designing a mixed-methods process evaluation to measure intervention fidelity, dose and unintended consequences; and (vi) ensuring scientific independence through formal contract agreements.Our collective experiences of working in non-financial partnerships with national supermarket chains could be useful for other research groups looking to develop and implement supermarket studies in an efficient manner. Further evidence from real-life supermarket interventions is necessary to identify sustainable strategies that can improve population diet and maintain necessary commercial outcomes. Poor diet constitutes one of the greatest threats to population health, being a significant determinant of overweight, obesity and many noncommunicable diseases , 2. DietSupermarkets play a significant role in peoples’ food environments yet their full potential as a setting to improve dietary behaviours has been underutilised. Commercial supermarket chains which are typically a nationally recognised brand, with hundreds of stores sized > 2,000 square feet, each selling tens of thousands of products, hold particular promise for dietary intervention. Such supermarket chains offer a suitable intervention setting for a number of reasons. Firstly, they dominate grocery sales across high income countries, accounting for approximately 83% of all retail food purchases in the United Kingdom (UK), 75% in the Netherlands and 68% in Australia [Secondly, supermarkets routinely collect sales data at the store level, and often purchasing data at the household level through loyalty cards, providing objective measures of dietary-related behaviour . EffectsThirdly, customers’ food purchasing behaviours can be examined in a real-life setting. Experimental interventions designed to test a hypothesis under optimal scientific conditions are important to assess proof-of-concept and the efficacy of isolated intervention components . VirtualThe aim of this paper is to outline the opportunities, challenges and lessons learned from conducting independent evaluations of interventions with national supermarket chains that test the effectiveness of creating healthier in-store environments. These experiences have been distilled into specific recommendations for conducting high quality research with commercial retail chains. The findings aim to provide novel insights for researchers and policy makers hoping to broker similar relationships and contribute to the evidence base in this field.This study adopted a case study approach to generate an in-depth and multi-faceted understanding of working with national, commercial supermarket chains in high income countries in real-life contexts . CollectThe collective case study approach applied in this study followed the fours key phases of research activity recommended by Crowe et al. :Defining the aim of the study – the specific aim of this study was carefully formulated based on reviews of existing literature Selecting the cases – the selection of research activities included in this collective case study draws from the authors own work which has involved collaborating with major national supermarket chains from market leaders through to smaller nationwide players in three high income countries, namely Australia, the Netherlands and UK. Table Collecting and synthesising the data – the lead authors  initially complied an extensive list of lessons learned across all cases through face-to-face and video-call discussions. All authors contributed to a process of prioritisation and refinement of the extensive list through video-call and email communications. Each author subsequently detailed their research team’s experiences in relation to the refined list, resulting in a cross-case comparison and analysis for each lesson. This synthesis process identified shared experiences as well as unique challenges and opportunities and enabled all experiences to be distilled into six recommendations for how to conduct high quality research with commercial supermarket chains  drafted the initial manuscript to characterise our collective experiences and related them to existing literature. The manuscript was refined with input from all authors.The first challenge to conducting public health research in supermarkets, and a question we are frequently asked, is how did you establish the relationship? From our experiences there is no single or ‘best’ method of developing a connection with a supermarket chain. The time period for engagement and relationship development varied significantly in our studies from several months to many years. Engagement was triggered via (i) a personal connection, where a previous researcher took up a position within the supermarket chain, (ii) the research group leader being approached by the supermarket chain’s health manager and building the relationship over many years, even decades, and (iii) sending a cold-call letter to the Chief Executive Officer of the target supermarket chain. In the case of the personal contact, a route into the company was facilitated by the established trust this individual had with both the research group and the supermarket head-office staff. Having personal connections within the target group or a stakeholder who holds joint academic and health/community service positions is recognised as a key element to success in community-based and translation research because it offers an important conduit for partnership negotiation , 23. TheFor another of our research groups, the approach from the supermarket’s executive was driven by two key factors. Firstly, the reputations of the research team leader and university were viewed as offering independent, expert scientific knowledge, and status in the area of nutrition. A supermarket’s reputation may benefit if they are seen to be partnering with respected scientists whose skills in quantitative and qualitative evaluation can offer new insights for the company, and evaluations performed by academic researchers are generally trusted more by the public and policy makers than those completed by supermarkets themselves. Findings from community-based research demonstrate how historical reputation can help or hinder relationship development . Having While the process of engagement adopted for each study was unique, similar approaches were used to sustain the relationships and followed the core practices of good partnership , 33. TheSynthesising our experiences and evidence from the field of community-based and translation research, to engage and sustain a successful relationship with a commercial supermarket chain we recommend: (i) using personal connections, knowledge of the supermarket chain’s activities and contextual factors to build partnerships and identify objectives that meet the needs of both parties, (ii) engaging the supermarket’s executive management early and (iii) allowing time to build trust and working relationships with various supermarket staff.Systematic reviews of health-focused supermarket interventions demonstrate that most evidence to date come from studies of poor quality design , 37–42. Optimal RCT designs, particularly those with appropriate statistical power, are however, considerably more challenging to implement for interventions at the store level. These types of interventions can involve altering the availability or positioning of products, or using shelf or trolley prompts to inform customers of healthier options and require cluster trial designs. The need for power calculations that take account of clustering at the store level has been mostly overlooked in this field of research . While pWe recommend that future studies use scientifically robust study designs with appropriate sample size calculations wherever possible. We recognise, however, the challenges researchers can face attempting to realise this goal when working with commercial partners and so recommend consideration of more novel trial methods. Stepped-wedge approaches, for example, lend themselves nicely to store-level evaluations because the intervention can be rolled-out sequentially and rely on regular follow-up assessments  . AnotherAccessing big data, such as supermarket sales data, for research can be a challenge due to large time and/or cost requirements . Unlike Managing the complexity of supermarket sales data has been noted previously by health researchers , 56 but Analysing supermarket sales data can also present challenges for which our experiences may help other researchers prepare. The nature of supermarket collaborations often necessitates the protection of commercial sensitivities such as raw sales figures. Using percentage sales figures is one approach  , or applMany supermarket intervention studies have applied difference-in-difference analysis methods , 41, whiLearning collectively from our experiences, we advocate following five steps for efficient acquisition, management and analysis of supermarket sales data: (i) request a dummy sales dataset early to identify products/categories and all data required for outcome and process evaluations, keeping in mind that product-level details can change over short time frames; (ii) outline up-front and in a formal agreement the data exchange arrangements; (iii) discuss with supermarket staff the time needed to extract, prepare and transfer data to the research team, acknowledging that research projects are not core supermarket business; (iv) allow researcher time and resource for re-categorisation of products in vast datasets; and (v) involve a statistician and skilled data processor to facilitate data transformations and analyses to make best use of the available data.As public health researchers we are intrinsically interested in understanding intervention effects at the population level. Store-level sales data enable population evaluation because they are objective and generalizable to all customers of participating stores over the study period . IncreasWhile the decision to recruit participants to assess individual/household level data is scientifically important, there are resource and time implications, and data protection obstacles to consider. Data protection laws can create an extra layer of complexity to recruit participants and access their loyalty card data because customers own, and supermarkets host, these data. In some of our studies, potential participants had to be identified and invited by the supermarkets in order to comply with data protection laws. Interested participants then contacted the research team directly and this approach had varying levels of success , 46. TheAdditional resource and time costs required for individual/household level data can include the provision of incentives to encourage participant recruitment and retention. Our studies included incentives of up to £30/$AUD60/€40 in vouchers, cash or groceries , 46, 51,To build the evidence base in this field, we recommend future research assesses effects at the individual and household level. We recognise data protection laws, time and resource constraints can hinder collection of these data, but our experiences demonstrate that by engaging with organisational legal teams and appropriately costing and resourcing study activities, high quality individual and household level data can be collected to improve understanding of how different customer groups respond to supermarket interventions.Given the complex nature of conducting supermarket research in a real life context it is paramount to complete process evaluation activities alongside outcome evaluations; yet such evaluations have rarely been reported –72. TherAssessing whether an intervention has been carried out as intended and capturing deviations from the protocol is particularly important for supermarket studies that involve alterations to the in-store environment because they are often implemented by numerous supermarket staff. Similarly to previous US research , in-storFor individually targeted interventions, such as price subsidies or healthier swaps, data about intervention dose can be collected from participants. Our SHELf study used both quantitative and qualitative methods to obtain information that could aid interpretation of the outcome results . For exaProcess evaluation activities can also provide information on unintended effects. Few studies have used sales or purchasing data to assess substitution effects yet such analyses can indicate intervention impact on overall shopping patterns. Our economic evaluation for SHELf showed small unexpected substitution effects among participants in the price subsidy arms where purchases of bakery and dairy products increased alongside fruit and vegetables . QualitaWe recommend designing a mixed-method process evaluation alongside the outcome evaluation to measure intervention fidelity, dose and unintended consequences. Contextual factors should also be assessed to ensure understanding of which approaches worked best in certain contexts and what support may be needed to ensure success. The extent of the process and implementation evaluation will depend on available resources, but these activities should be prioritised where possible to provide important information for interpreting outcome findings and translating evidence into policy and practice.There has been much debate in the field of public health nutrition about the real and perceived conflicts of interest that can result from public sector population health researchers working with food industry –85. In aAccepting only in-kind support from the collaborating supermarkets afforded a number of benefits for our research teams, particularly independence in analysis and greater external trust in our studies’ findings. The in-kind support from supermarkets largely took the form of implementing the interventions , plus the collection, extraction and sharing of store sales and loyalty card data. Ensuring independent analysis and reporting of study data was paramount for each research team. Liaison with supermarket staff was required in some instances to ensure accuracy in understanding and re-categorising sales data, and to achieve joint publicity ventures. Independence was further ensured through study steering committee oversight. Committee members were external to the research team and supermarket chain, and included representatives from regional municipalities, health boards, non-government organisations and reputable universities. They regularly reviewed study activities and provided valuable expertise and input regarding balancing private commercial interests against public health benefits.We recommend research groups maintain independence from the supermarket chain by following three key strategies: (i) develop formal contracts involving organisational legal teams and clear summaries of the work and reporting arrangements, (ii) accept only in-kind support to maintain autonomy in analysis and (iii) appoint an external study steering committee to regularly monitor study activities.This paper describes the experiences and lessons learned from a number of different trials our research teams have evaluated with national supermarket chains in Australia, the Netherlands and UK. While our analysis is unique in its application to national, commercial supermarket chains, research teams from the US and UK have previously synthesised their experiences of working with small independent grocery and convenience stores to test healthy eating interventions , 87. TheA key difference between our case study synthesis and previous examples from the convenience store sector relates primarily to our emphasis on robust scientific study designs, alongside comprehensive mixed-methods evaluations. This emphasis in our recommendation is appropriate for partnerships with commercial supermarket chains because of the routine data that are collected at store and households levels, and because of the large number of stores available to achieve adequately powered trials. Working with independent grocery and convenience stores requires greater negotiation and relationship building at the store level which increases the time and challenges of achieving optimal sample size calculations, particularly when cultural and linguistic diversity is considered . AnotherThis study provides unique insight into the challenges and opportunities of conducting research partnerships with commercial supermarket chains who have nationwide reach into the shopping trolleys of millions of families. We adopted a case study approach which covered studies in three high income countries. This approach may reflect experiences unique to these particular research studies and contexts which could be considered to limit generalisation of our findings. The four-stage process for data synthesis used in this study, however, identified six cross-cutting themes that were applicable to each of the real-world supermarket trials, contexts and countries examined. It is possible that alternative challenges and opportunities working with supermarkets to conduct public health nutrition trials could arise in different settings.Supermarkets are an important setting to influence dietary behaviour. Even small changes in food purchasing can shift population level dietary intake in a healthier direction. We believe that the six recommendation and synthesis of lessons we have learned from working with national supermarket chains can help guide the development and implementation of more and scientifically robust supermarket intervention studies. Further evidence from real-life supermarket interventions will help to identify sustainable strategies that can improve population diet and maintain necessary commercial outcomes.


Saccharomyces cerevisiae and Komagataella phaffii (syn. Pichia pastoris). We dissect possible sources of burden in these organisms, from aspects related to genetic engineering to protein translation and export of soluble protein. We also summarize advances as well as challenges for cell factory design to mitigate burden and increase overall heterologous protein production from metabolic engineering, systems biology, and synthetic biology perspectives. Lastly, future profiling and engineering strategies are highlighted that may lead to constructing robust burden-resistant cell factories. This includes incorporation of systems-level data into mathematical models for rational design and engineering dynamical regulation circuits in production strains.Production of heterologous proteins, especially biopharmaceuticals and industrial enzymes, in living cell factories consumes cellular resources. Such resources are reallocated from normal cellular processes toward production of the heterologous protein that is often of no benefit to the host cell. This competition for resources is a burden to host cells, has a negative impact on cell fitness, and may consequently trigger stress responses. Importantly, this often causes a reduction in final protein titers. Engineering strategies to generate more burden resilient production strains offer sustainable opportunities to increase production and profitability for this growing billion-dollar global industry. We review recently reported impacts of burden derived from resource competition in two commonly used protein-producing yeast cell factories:  Biomanufacturing of heterologous proteins from genetically engineered cell factories is a growing industry. The first such biopharmaceutical product was approved by the FDA four decades ago   status allowing for easier approval processes . This allows for a biomass formation phase prior to an induced expression production phase, where the medium carbon source is switched from glycerol, glucose, or sorbitol to methanol , compared to the popular TEF1 promoter  than strains with more than two copies (8.19-12.09UA-1012/cell) . NADPH is required in many anabolic processes, including K. phaffii production strains where acetate did not accumulate despite increased demands for NADPH  and glucose uptake rate (from 4.2 to 2.2 mmol g−1h−1) for BapA production strains compared to the reference strain , which is commonly fused to heterologous proteins to drive their post-translational translocation into the ER, augmented burden during Rhizopus oryzae lipase (ROL) expression. This was observed as a reduction in growth rate, biomass yield, and final protein titer  than the reference strain (34 U−1) in a chemostat with dilution rate near the maximum of the reference strain but still far from maximum for the optimized strain , also requires NADPH . UPR is a quality control system that helps re-establish cellular proteome homeostasis and is therefore activated as a response to burden in the ER . Prolonged overexpressing of this transcription factor improved production in burdened K. phaffii  pathway is another important quality control system in yeast. ERAD targets misfolded proteins for cytosolic degradation and ensures that ER homeostasis is maintained (Hwang and Qi, To summarize, cellular stress is tightly coupled to burden. As heterologous proteins are directed to the secretory pathway, burden is induced by overload and subsequent disruptions in protein folding and redox balance in the ER which trigger the onset of different cellular stress responses. Engineering target 3 in Several process and genetic engineering strategies have been proposed to improve production from burdened host cells (Deparis et al., in silico modeling with -omics techniques and bioinformatic analyses allows for the identification of factors that are critical but might not necessarily stand out when the data is first observed. Thus, modeling represents a useful tool for quantifying the bioproduction limitations of living cells (Mattanovich et al., 13-metabolic flux analysis and additional in silico data into stoichiometric models (Jordà et al., Systems biology offers a promising interdisciplinary approach to discover new targets for metabolic engineering (Hou et al., E. coli production strains and show strengths over the more classic genetic engineering approach of simply deleting or over-/under-expressing candidate genes. As heterologous protein production requires resources from shared pools of metabolites with native cellular processes, static overexpression of specific genes leads to a less robust systems since it does not help minimize the changing levels of burden on production host during cultivation (Boo et al., E. coli using CRISPR technology which dynamically regulated heterologous protein production in response to burden (Ceroni et al., E. coli cells have time to recover and achieve greater production levels over the total course of the cultivation. This study highlights the potential for engineering similar burden-driven negative feedback systems for heterologous protein production in yeast.Indeed, diverse systems-based efforts have been introduced to alleviate burden in production hosts. Notably, such efforts have inspired the construction of dynamic control systems that respond to changing metabolic and energy demands. These have proven highly effective in S. cerevisiae strains engineered to produce valuable compounds such as bioethanol or vanillin-β-glucoside (D'Ambrosio et al., S. cerevisiae, a more robust strain was achieved by placing target genes in the ethanol pathway under control of stress-regulated promoters to ensure dynamic feedback regulation (Qin et al., S. cerevisiae cell factory was developed to produce vanillin-β-glucoside by coupling pathway intermediate production to biosensor-controlled expression of an essential gene (D'Ambrosio et al., Similar and other kinds of regulatory feedback circuits have already proven useful to mitigate or circumvent burden in The above mentioned strategies represent novel and promising approaches which could be applied for burden-driven regulation of heterologous proteins expression. It might also be useful to place secondary “helper genes” under the control of such dynamic regulation, including genes encoding some combination of factors involved in restoring redox balance, controlling UPR and/or ERAD pathways, or ensuring adequate protein folding. Engineering dynamic systems that tailor heterologous protein expression to ever-changing host cell needs over the course of the cultivation represents a novel approach that aims at multiple engineering targets highlighted in S. cerevisiae cell factories, where burdensome production and cultivation caused non-genetic heterogeneity in the population to favor the growth of low-producing cells in the population (Wright et al., Burden derived from resource competition is often encountered in bioproduction processes triggering a phenotype with compromised production during long-term cultivations. Therefore, engineering production strains that are either more tolerant to burden or able to adjust heterologous protein expression to burden is paramount, and efforts have already been made to engineer such yeast strains as listed in Commonly, the impact of burden is measured as a reduction in physiological parameters like specific growth rate, biomass yield, and respiratory capacity (Kazemi Seresht et al., Sources of host cell burden can be more specifically identified from high-throughput, omics-based approaches since they provide a systems-level overview of the burden response. With tools that profile the metabolome, transcriptome, proteome, and/or fluxome of any specific production strain over time, these complex networks can be dissected to understand the burdened phenotype at a molecular level, identify causal factors responsible for pathway bottleneck, and allow rational engineering strategies to alleviate burden and enhance heterologous protein production (Heyland et al., S. cerevisiae, activation of amino acid biosynthesis was suggested to be elicited following the up-regulation of transcription factor Gcn4, which is induced by UPR (Kazemi Seresht et al., K. phaffii (Gu et al., In line with this, the gene regulatory network of underlying metabolic pathways might play an important role in inducing burden and could be an interesting direction for future studies. As reviewed here, cellular stress responses are intertwined with the burden state. Likely, these stress responses and other pathways have additional functions such as facilitating crosstalk with the metabolic pathways affected by burden (Kalender and Çalik, There are still gaps in our understanding of the concept of burden in yeast cell factories. By emphasizing this topic, we hope to draw the attention of future research to elucidate the molecular basis and underlying mechanisms of burden in yeast to mitigate this common production limitation. Despite these challenges, recent advances in bioengineering are already paving the way for improved heterologous protein titers from yeast cell factories by developing strategies that alleviate burden, such as dynamic control system engineering. We expect such approaches to be adopted by the biotech industry and significantly enhance heterologous protein production in the years to come.CW and MJ conceived the topic reviewed in this manuscript. CW, MJ, RA, and LK contributed content and ideas for the manuscript structure. LK wrote the manuscript. CW, MJ, and RA contributed with corrections and revised drafts at all stages. All authors approved the submitted version.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.


The historically known relationship of interspecies companionship between Aboriginal foraging communities in Australia and free-ranging dingoes provides a model for understanding the human-canid relations that gave rise to the first domesticated dogs. Here, we propose that a broadly similar relationship might have developed early in time between wild-living wolves and mobile groups of foragers in Late Pleistocene Eurasia, with hunter-gatherers routinely raiding wild wolf dens for pre-weaned pups, which were socialized to humans and kept in camp as tamed companions (“pets”). We outline a model in which captive wolf pups that reverted to the wild to breed when they were sexually mature established their territories in the vicinity of foraging communities — in a “liminal” ecological zone between humans and truly wild-living wolves. Many (or most) of the wolf pups humans took from the wilderness to rear in camp may have derived from these liminal dens where the breeding pairs had been under indirect human selection for tameness over many generations. This highlights the importance of the large seasonal hunting/aggregation camps associated with mammoth kill-sites in Gravettian/Epigravettian central Europe. Large numbers of foragers gathered regularly at these locations during the wild wolf birthing season. We infer that if a pattern of this kind occurred over long periods of time then there might have been a pronounced effect on genetic variation in free-ranging wolves that denned and whelped in the liminal zones in the vicinity of these human seasonal aggregation sites. The argument is not that wolves were domesticated in central Europe. Rather, it is this pattern of hunter-gatherers who caught and reared wild wolf pups gathering seasonally in large numbers that might have been the catalyst for the early changes leading to the first domesticated dogs — whether in western Eurasia or further afield. Canis familiaris) is widely regarded by scientists as our oldest domesticated animal (C. lupus)   . The firago (ka) . On the ago (ka) . Age estago (ka) , morpholago (ka) , 2015a, ago (ka) .There are two competing hypotheses of wolf domestication: (1) wolves self-domesticated by adapting genetically to anthropogenic environments as commensal scavengers ; and (2)Canis dingo). Australia is host to the only mobile foraging communities whose ubiquitous practice of taking the pups of free-ranging canids from their dens and raising them as companion animals is relatively well attested in the historical record , and stealing pups from dens . The pupNumerous observers recorded that some dingo pups were kept alive specifically with the intention of raising them in human society . These sMost authorities agree that Aboriginal people did not intentionally control the breeding of camp dingoes . SpecifiPups were usually taken from dens at a very young age, when they were pre-weaned, largely immobile, and completely dependent on parental care. As Smith comments:[Aboriginal people] preferred the dingoes as young as possible, usually around two to four weeks old. This suggests an understanding of the critical period of socialisation in canids, where there is only a small window of opportunity to socialise a pup to humans in order for it to be a successful and well-adjusted pet later in life :87.Some evidence suggests that, upon raiding a den, the choice between which individuals within the litter of newborn pups were killed for food, and which would be kept alive to rear as companions in camp, was not necessarily an arbitrary one. For example, Pitjantjatjara people would usually kill most of the pups in the den for food, ‘but some particularly marked and semi-albinic animals may be kept’ :374. SimPre-weaned pups that were taken from dens and selected to live with people as social companions were hand-reared with loving care and affection. Women most commonly undertook this surrogate “mothering” role :347. FavReports describe the strong emotional attachments between camp dingoes and their adoptive parents or carers . Unlike Despite all this, historical accounts and anthropological observations suggest a consistent cultural pattern in which very young pups were intensely nurtured and doted upon, well-fed and so on, but as they grew out of the cute puppyhood phase — and thus presumably became less appealing as objects of human affection — they were largely left to fend for themselves . These dThe early writers are largely silent on this issue of what happened to the young socialized companion dingoes when they were physically mature. To our knowledge, there are few confirmed observations of breeding-age females or adult males consistently being present in Aboriginal camps , 2022. IThe most commonly held notion among present-day scholars — based principally on the testimony of Aboriginal informants — is that when human-raised dingoes reached reproductive age (~12–24 months) they reverted permanently to the wild to breed :92–93. Tvia inhumation in the same manner, and often alongside, Aboriginal people  from the diets of people . Two dinustralia . The genWithin such a landscape where larger, more closely-spaced and longer-resident Aboriginal communities were practicing the annual rearing of dingoes taken from dens, the relative probability of human influence acting inter-generationally upon these dingoes must have been greater. This could be because settlements were, through the availability of resources, more capable of sustaining several generations of tame dingoes reproducing within their confines if so desired. More interestingly, pups born to formerly tame dingoes which had left the camp to reproduce in the wild would also have had a greater chance of being subsequently collected from the den by members of the same community or a neighboring one for taming  — by virThe available insight into the human-dingo relationship in Australia conflicts with two key interrelated aspects of the human-initiated model of wolf domestication. Firstly, rather than keeping hand-reared pups within or close to human society when they reach sexual maturity — in order to acquire the next generation of pups — Aboriginal people typically allowed socialized dingoes of breeding age to revert to the wild, chased them away, or even killed them to prevent them from reproducing within the milieu of human domestic life. This presents a challenge for the scenario outlined by The latter point is noteworthy. As has been previously mentioned, the pup-keeping hypothesis of wolf domestication proposes that Late Pleistocene hunter-gatherers took the very first generations of pre-weaned wolf pups from the natal dens of free-ranging wolves and reared them in camp; the sexually mature wolves then began to breed in human captivity, giving birth to pups within the confines of foraging settlements. There is therefore a tacit assumption that only a few generations after the first pups were brought in from the wild to live in human communities it would no longer have been necessary to raid wild dens to acquire these companion animals. Nevertheless, wolf domestication would have involved a long and anastomosing pattern, and the process should not be equated to a simple path ending with the emergence of the first modern dogs see .With regards to the case in Australia, as C. dingo . This practice endures despite the fact that Indigenous people in these remote settlements have long possessed European domestic canines (“camp dogs”) that reside with them permanently . MoreoveIn sum, the human-dingo model would appear to subvert two of the main assumptions of the pup-keeping hypothesis of wolf domestication. A key question therefore remains: if the human-wolf relationship in Upper Paleolithic western Eurasia was similar to or at least compatible in nature with the human-dingo relationship in Australia, would it still be possible for domestication to occur?The argument for an early and widespread practice of wolf pup adoption in Late Pleistocene Eurasia is broadly consistent with the archeological record — or at least is not directly refuted by it. A detailed study of the age distribution of the large canids found at Upper Paleolithic sites in Europe has not yet been undertaken. However, at the site of Předmostí (28.5 ka) in the Czech Republic , most caUnder the human-initiated pet-keeping model, it can be anticipated that many of the large canids living as companions at any given time in Late Pleistocene hunter-gatherer communities prior to when the first widely accepted domesticated dogs appear (~17 ka) would have been very young pups and juveniles (or adults) of non-breeding age. However, the presence of skeletal remains of adult canids at Upper Paleolithic archeological sites, or the absence or rarity of juveniles, does not refute this prediction. Concerning the latter, the remains of very young wolf pups are less likely to be preserved in the Late Pleistocene archeological record from a taphonomic standpoint — just as the skeletal remains of babies and very small children rarely survived at these sites.We would also expect to find adult wolf remains in human settlements, given the argument that some human-socialized pups would have lived with people as adults. Moreover, excavated archeological findings indicate that Upper Paleolithic people killed adult wolves for food and raw materials  wolves and the camp sites occupied by humans.We agree with It follows that if camp-living and dispersing socialized wolves commonly formed mated pairs with each other, then any offspring they produced are likely to have inherited morphological and behavioral characteristics that had been under human selection in one or both parents. Hence, we surmise that a long-term pattern of hand-reared, socialized wolves breeding in liminal zones near human camps may have influenced the enrichment of genetic variants  in these populations.cf.We would expect this process to have begun to produce recognizable changes in wild wolf populations long before the first widely accepted remains of domestic dogs appear in the archeological record after the Last Glacial Maximum (LGM). Evidence for this is provided by the early appearance of dog-like skeletal remains in western Eurasian contexts . In the The oldest known specimen of a Palaeodog identified thus far is from Goyet Cave in Belgium , by the Gravettian and Epigravettian periods, there may have been a continuous cycle of (1) mobile groups of hunter-gatherers returning regularly to specific congregation sites , accompanied by young socialized canids which they had obtained previously from liminal dens located in the vicinity of these seasonal camps; (2) some of these socialized canids of breeding age dispersing into the wild  from these seasonal camps; and (3) hunter-gatherers congregated at these campsites replenishing their supply of wolf pups by raiding liminal dens, a practice that is likely to have involved revisiting known denning areas they had targeted previously [On Ellesmere Island, Such a pattern, if repeated over a number of generations, could have had a pronounced effect on the population of canids from which humans routinely acquired new pups . First oUnder this scenario, pups born at the camp sites or in liminal dens in these areas could have descended from lineages that had been subjected to many generations of unconscious human selection for particular morphological and behavioral traits, such as characteristics associated with tameness . It therefore seems plausible that many pups taken from these dens could have displayed altered craniodental morphometry and body size reduction, resulting in the distinctive Palaeodog morphotype . Indeed,Palaeodogs that had been hand-reared and socialized may still have been predisposed to disperse from human communities when they matured, forming mated pairs with socialized or unsocialized wolves, or socialized or unsocialized Palaeodogs – and giving birth in camp, in liminal dens, or further away in wild dens. Some of the dispersing socialized canids  may have roamed beyond the liminal zone into areas where they came into direct contact with packs of free-living, unsocialized wolves, forming mated pairs and interbreeding with them. Furthermore, humans gathered at the seasonal camps might have acquired some wolf pups from dens located further out in the non-anthropogenic or “wild” environment , bringing them back to camp to raise alongside pups born in the camps or obtained from the liminal zone .Some Palaeodog lineages, having acquired more behavioral traits associated with domestication, may have been inclined to freely come and go from human camps as adults, or even to reside in them on a permanent or semi-permanent basis. Concerning the latter, it seems likely that the liminal zone was not a completely safe area for socialized canids that had dispersed from human communities. Dangerous predators such as cave hyaenas, cave lions, and brown bears could also have been visiting this zone and may have preyed on them. Some socialized adult canids could have managed in this environment, and hence their liminal dens could have been raided by humans. Others, however, were restrained to campsites or being flexible enough, had the ability to breed in the presence of humans and may have chosen to birth their pups inside the confines of hunter-gatherer campsites, where they were protected and cared for by humans and thus free from inter- and intra-specific competition , 2021a,bdid furnish humans with an adequate supply of new pups, the practice of raiding wild dens for more pups may have continued for non-utilitarian reasons. As the Yolngu example noted above suggests, perhaps den raids were still undertaken because they reinforced a perceived spiritual connection between humans and wild wolves. Whatever the case, we contend that the practice of den raiding and wild pup-raising was a long-term cultural tradition over large parts of Eurasia that was not confined to the earliest phases of dog domestication  their supply of wolf pups by raiding dens in the spring. As with dingoes, socialized adult wolves that remained in camp may have reproduced at a low rate in captivity. However, even if camp-living wolves tication :195, as Such a complex human-canid relationship could have endured in different regions in parallel for a long period of time, slowly modifying the genes of the local wolf populations and leading to the development and retention of traits associated with domestication. However, the influx of wild wolf genes would account for the long road to genetic isolation. During den raids, moreover, it may not have been possible for humans to reliably distinguish between pups from the liminal dens and those from the wild dens. This would have permitted gene flow from the wild, thereby delaying reproductive isolation in socialized camp wolves as there were several possible sources of genetic input.In sum, the onset of springtime aggregation by large groups of Upper Paleolithic hunter-gatherers may have initiated more pronounced genetic changes in the wild-living wolf population from which humans obtained their pups, changes that enabled people to more successfully keep the socialized adults in camp after they matured sexually. However, in-camp reproduction was probably a “work in progress.” Socialized canids would have frequently dispersed when they reached breeding age and the ongoing practice of den raiding in liminal zones meant that there was constant gene flow from the wild into any populations of camp-born canids .per se are directly related to the beginnings of dog domestication. It could be the case, for example, that wolves were domesticated somewhere in Central or East Asia , could have given rise to the ancestors of modern domestic dogs. But this need not imply that dogs were domesticated from wolves in the central or eastern European region, or that the mammoth megasites on the Moravian Gate or Russian Plain ia e.g., . Even ifIn Australia, the special relationship between Aboriginal people and dingoes seems to have existed over a long period of time without resulting in the domestication of these wild-living canids ; althougcf.The close relationship between Aboriginal Australians and wild dingoes, as documented in the ethnohistorical record, has implications for our understanding of the human-canid relations that may ultimately have given rise to domestic dogs in Late Pleistocene Eurasia. Based on the dingo analogy, we contend that regular raiding of wolf dens for pre-weaned pups was a defining trait of the intimate relationship between humans and wolves that long preceded the appearance of the earliest uncontested dog remains in Eurasia (~17 ka). We further infer that: (1) when hand-reared, socialized, human-selected wolf pups reached sexual maturity they often would have reverted to the wild to breed, although some could have mated in captivity; (2) the dispersing socialized wolves commonly formed mated pairs with each other, but sometimes with wild Pleistocene wolves; the former would have most commonly established their territory in a liminal zone situated between human settlement sites , as proposed by The original contributions presented in the study are included in the article; further inquiries can be directed to the corresponding author.All 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.


This work has important implications for understanding how marine sediment microbes function together to provide important ecosystem services like recycling organic matter.Sulfate-reducing microorganisms (SRM) are key players in global sulfur and carbon cycles, especially in anoxic marine sediments. They are critical in anaerobic food webs because they consume fermentation products like volatile fatty acids (VFAs) and/or hydrogen produced from other microbes that degrade organic matter. Apart from this, the interplay between SRM and other coexisting microorganisms is poorly understood. A recent study by Liang et al. provides intriguing new insights about how the activity of SRM influence microbial communities. Using an elegant combination of microcosm experiments, community ecology, genomics, and  This living and breathing marine mud, or the “guts of our oceans,” plays a critical role in global element cycles because large amounts of organic material are deposited there. This organic material is either degraded and recycled by microbes back to CO2 or buried into the deep subsurface and therefore locked away from the carbon cycle (Sulfate-reducing microorganisms (SRM) are a functional guild of microbes that use sulfate as a terminal electron acceptor for anaerobic respiration. They are especially key among the diverse and massive populations of microbial life that inhabit the vast expanses of marine sediments underlying our oceans . This isThe anaerobic degradation of organic material in marine sediments is intriguing because complex microbial communities work together to hydrolyze, ferment, and dispose of fermentation by-products like volatile fatty acids (VFAs) and/or hydrogen . For thimBio study by Liang et al., the authors aimed to shed new light on how SRM interact with and exert control over other key members of a marine sediment microbial community . This group of bacteria was interesting because they were also found to be tightly intertwined within the ecological networks of key SRM in the control incubations, suggesting they interact under normal conditions. This was also intriguing because most of these other non-SRM don’t have enzymes that would be affected by molybdate, indicating something else might be strongly affecting their ecology and niche.in vitro for pH sensitivity. Importantly, they first showed that the strains are not inhibited by molybdate at concentrations used in the microcosm experiments, suggesting they were indeed likely affected by something else. When testing their pH preferences in vitro, it was apparent that this group of organisms had reduced growth at weakly acidic pH levels seen in the sediment microcosms when SRM were inhibited, i.e., around pH 6.4. This coincided with this pH level being very close to the minimal pH tolerance of the strains. Thus, it seems the SRM are critical for maintaining the pH niche of these taxa in marine sediments.To hone in on a reason, the authors suspected the pH effect. To explore this, they isolated a collection of Marinilabiliales strains from the sediments and tested them In a nice follow-up experiment, the authors repeated the microcosm incubations, but added a buffering agent (HEPES) to the SRB-inhibited treatments. This kept the pH up around 7.4 even though VFAs would have accumulated, and thus kept the pH similar to the sediments of the control microcosms where SRB consume the VFAs efficiently. Sequencing of the community then showed that members of the family Marinifilaceae  were less affected when the sediments were buffered, further supporting that pH was specifically affecting their abundances in the communities.Finally, the authors postulated that further metabolic interactions based on metabolite exchanges of key metabolites could also help explain the interaction between SRM and Marinilabiliales. To explore this, the authors performed genomic analyses of various taxa from the sediments, in order to identify genetic potential for biosynthetic capabilities, or lack thereof. While various auxotrophies were identified, several complementing metabolite biosynthetic capabilities were found for SRM and Marinilabiliales, e.g., L-proline, L-ornithine, L-cysteine, and vitamins B7 and B12, suggesting exchange of these could promote their growth and interactions. The authors then also went back to the lab and showed that supplementing these specific metabolites to 10 Marinilabiliales strains indeed facilitated better growth in the minimal media used. This therefore suggested SRM may fill gaps in some of the auxotrophies of Marinilabiliales. Finally, the authors also point out that other factors like the hydrogen sulfide produced by SRM may be another key factor shaping the communities.in vitro and in silico studies. Such approaches will undoubtedly be useful for deciphering microbial community ecology and functioning in other contexts in the future too.Overall, this work provides new and unique perspectives on how interlinked anaerobic microbial communities function and how SRM alter the niche space of accompanying community members. While teasing apart such factors can be difficult in complex environmental samples, the authors did a commendable job of combining experimental microbial community ecology, with complementary