Additionally, shape (n = 3) and trigonometrically derived variables and ratios (n = 9 variables) were employed to detect any geographically-clustered morphological differences between these populations. Random forest modelling (RFM) and linear discriminant function analysis (LDA) were employed to create classification models in instances where sex was known or unknown. The sample was apportioned into training and test sets with a ratio 70/30. The classification accuracies were evaluated by means of k fold cross-validation procedure. In sex estimation, RFM showed similar performance to LDA. However, RFM outperformed LDA in ancestry estimation. Ancestry estimation was satisfactory in the Indian and Egyptian samples albeit the Greek sample was problematic. The Greek samples presented greater morphological overlap with the Indian sample due to high within-group variation. Test samples were accurately assigned to their ancestral category when sex was known. Generally, higher classification accuracies in the validation sample were obtained in the sex-specific model of females than in males. Using RFM and the linear variables, the overall accuracy reached 83% which is distributed as 95%, 71% and 86% for the Egyptian, Indian and Greek females, respectively; whereas in males, the overall accuracy is 72% and is distributed as 58%, 87% and 50% for the Egyptian, Indian and Greek males, respectively. Classification accuracies were also calculated per group in the test data using the 12 derived variables. For the females, the accuracies using the medians model was comparable to the linear model whereas in males the angles model outperformed the linear model for each group but with similar overall accuracy. The classification rates of male specific ancestry were 82%, 78% and 56% for the Egyptian, Indian and Greek males, respectively. In conclusion, Purkait’s triangle has potential utility in ancestry and sex estimation albeit it is not possible to separate all groups successfully with the same efficiency. Intrapopulation variation may impact the accuracy of assigned group membership in forensic contexts.Identification of unknown remains recovered from marine and terrestrial locations is a significant humanitarian problem. This investigation proposes a simple method applicable to fragmentary femora for a more refined level of ancestry and/or sex estimation. To that end, we re-examined Purkait’s triangle which involves three inter-landmark distances between the traction epiphyses and the articular rim of femoral head. A large sample (Key pointsPurkait’s method is a possible ancestry group indicator applicable to fragmentary femora.Random forest model surpassed linear discriminant function analysis in multi-group ancestry classification.Ancestry is more accurately assessed in females than males.The intertrochanteric distance is the most important feature in discrimination of sex whereas in ancestry it was the head to lesser trochanter distance.Sex differences override ancestry due to the tendency of misclassification into same sex but different group rather than the opposite sex of the same ancestry. Sex and geographic ancestry are fundamental components of the biological profile of decedents that should be established in order to expedite the settlement of justice . AncestrThe impetus for ancestry assessment in research and practice is halted by the variations in global practice of forensic anthropology because of political issues, demographic composition of the country as well as regional medico-legal demands , 6. NeveIn the Middle East and North African (MENA) region, Egyptian labour migration is the principal migration pattern to Arab region and Europe. India has the largest diasporas in the world. The US, UAE and Saudi Arabia host the Indian migrants in addition to other gulf states since the “oil boom” in the 1970s , 14. OveOn the other hand, Greece is the fourth country in the European Union as a destination for refugees and asylum seekers from the Arab region according to the Missing Migrants Project . The humFor possible identification of missing persons from a closed list, investigators must have complete information on the age at death, sex, ancestry, stature and time since death in order to meet the demands of the legal process . AncestrPost-cranial metric methods of estimating ancestry have found the most success with the lower limb bones and pelvic girdle, especially the femur , 29. TheEarly models used in sex and ancestry estimation involved classical multivariate analysis techniques such as linear discriminant function analysis in FORDISC 3.0. , 36 and In 2005, a method of sex estimation was developed by Purkait  that invHitherto, no research has been carried out to determine if the anatomical variation in proximal femur as captured by Purkait’s triangle can be used to reconstruct ancestry of unknown individuals. To that end, the construction of a large identified sample from geographically distant populations in conjunction with an intelligent statistical modelling technique by means of RFM would quantify the morphometric characteristics of the femur in each group and also likely indicate the accuracy of the ancestry estimates. We also compared the classification ability of RFM with models generated through linear discriminant function analysis (LDA). If the overall classification accuracy is demonstrated to remain higher than chance alone, then Purkait’s triangle can be used as a criterion for estimating the ancestry of the remains, thus greatly contributing to forensic studies on identity reconstruction.In order to evaluate the applicability of Purkait’s triangle for sex and/or ancestry estimation, we used matched femoral metric data of identified individuals from three geographically distant populations, namely the Egyptian, Indian and Greek samples. Overall, 584 individuals were analyzed, with a total of 352 males and 232 females representing a sex ratio of 1.5:1. ® Perspective  and based on slice thickness of 1.5 mm slices. Three dimensional (3D) reconstruction of proximal femur was performed using the RadiAnt DICOM Viewer  for Windows [The femoral Digital Imaging and Communications in Medicine (DICOM) datasets were obtained from a 64-slice multi-slice Computerized tomography (CT)scanner manufactured by Siemens Somatom Windows . The dif Windows . The acq Windows  and Gree Windows  samples Measurements were exclusively taken on the left proximal femur with the exception of the Indian sample which were taken from both sides and only one side of each was included . We exclR) [Since the current study is retrospective in nature, a unified strategy in error quantification was not possible. Intra-observer error was evaluated for the measurements obtained from the Egyptian virtually reconstructed femur models using the technical error of measurement (TEM), relative TEM (rTEM) and the coefficient of reliability (R) . Prior tR) . Each vapost hoc tests were used to determine which ancestral groups differed from one another by each variable in terms of the size and patterns of sexual dimorphism. The coefficient of variation (CV) was computed using the formula [ for the two groups  in each population sample. Separate ANOVA were run on male and female individuals of each population due to sex differences in size. Tukey honestly significant difference (HSD) iability , 47.n = 9) including the angles, the angle to measurement ratios and the medians have also been considered. The angles were defined by the linear measurements where Angle A, B and C are opposite to BC, AC and AB. The angles were calculated using the Law of Cosines [The ratio of Angle A divided by the length AB multiplied by 100.The ratio of Angle B divided by the length BC multiplied by 100.The ratio of Angle C divided by the length AC multiplied by 100.The three inter-landmark distances and other variables  method . The shaEach group of the three linear and the newly derived trigonometric variables of Purkait’s triangle were modelled for sex and/or ancestry estimation using the LDA and RFM included in the Scikit-learn  in PythoLDA calculates the multivariate distance between groups using the group-specific means and a pooled within-group variance–covariance matrix (VCM), then classifies the observation discriminant score (expressed as a linear combination of a set of three variables from Purkait’s triangle or the pooled variables) within one of the several groups under experiment depending on whether the score is higher or lower than the threshold. LDA requires fulfilment of three statistical assumptions: (i) the explanatory variables within each class should have a multivariate normal distribution; (ii) equal VCMs of the groups; (iii) low correlation between explanatory variables .RFM is trained using bootstrap aggregation (Bagging) which is the process of repeatedly testing randomly drawn samples from the original training data (bootstraps), repeating the process and refining the model over several trees and then aggregating the models learned on each bootstrap. A subset of the variables is selected randomly and whichever variable gives the best split is used to split the node iteratively. After creating all the decision trees in the forest, out-of-bag (OOB) error is the average prediction error for each training sample calculated using predictions from trees that do not contain this particular sample in their respective bootstrap sample. This allows the model to be fit and validated while being trained. OOB error is an estimate of generalization (prediction) error of unseen data. Bagging technique has methods for balancing errors in training datasets where classes are imbalanced. Further, it overcomes variance (overfitting) by training multiple decision trees on different subspace of the feature space at the cost of slightly increased bias (i.e. underfitting due to systematic under or over prediction of the target groups) .Two variable importance measures (VIMs) or rankings are calculated during the analysis: mean decrease in accuracy (MDA) and mean decrease in impurity (MDI) . In bothThe sklearn.random_projection module was implemented as a computationally simple and efficient way to reduce the dimensionality of the data in order to visualize them in a 2D plot. The dimensions and distribution of random projections matrices are controlled so as to preserve the pairwise distances between any two data points in the dataset in the original space. Thus random projection is a conventional approximation technique for biological distance based studies .The present study builds methodologically upon Liebenberg et al. , which rR) equal to 0.95. The lowest error was achieved in the BC measurement where the calculated rTEM, TEM and R were 1.37%, 0.81 mm and 0.97, respectively. These results are within the recommended range of human error [an error , 58.Post hoc comparisons showed that significant differences consistently exist in AC diameter among all three population groups in both males and females.The descriptive statistics of each variable by geographic origin and in the pooled sample are summarized in Moreover, the Indian males have a significantly longer AB and shorter AC distances than those of the Greeks. Thus, the superior point on the greater trochanter was high relative to the head. Further, Greek males have the highest within-sex variation, especially in the AB diameter whereas Indian males scored the lowest CV in all measurements . Indian versus 65% of the training samples to the appropriate ancestral group whereas in the test sample, comparable overall accuracy was obtained being 67% versus 66% of the test samples. Looking at each group separately in the test sample, the Egyptians were accurately classified 87% (LDA) and 77% (RFM) of the time, while the Indian were accurately classified 79% of the time by both classifiers. Only 39% of the Greeks were correctly classified by LDA but RFM improved the accuracy to 46%. The models including the newly computed variables, however, resulted in 81%–87% correct group membership versus 77%–87% for the Egyptians using LDA and RFM, respectively and for the Indians 75%–80% versus 82%–85% using LDA and RFM, respectively. For the Greek sample, 38%–39% versus 49%–54% were correctly classified using LDA and RFM, respectively. Surprisingly, the pooled variables model showed 15% higher accuracy for the Greek sample using RFM which outperformed the LDA pooled variables for the same sample. Generally, the pooled variables models improved the classification accuracies over the linear models using LDA and RFM  technology while overcoming the cultural and legal constraints, mitigating the time-consuming nature and tediousness of skeletal maceration or the need for physical storage space . One notIn the sex classification task, RFM achieved better sex-specific and overall accuracy than the application of the population specific function on each population . GeneralBrown and colleagues  found thWhile the BC dimension reflects upper body weight transmission and muscular development as insertion regions of muscles, the AC diameter reflects the femur neck length and position of the lesser trochanter relative to the femur head . ArguablIn the ancestry classification tasks, several trends can be observed. First, the Indian group demonstrated better resolution from the Egyptian and Greek groups using Sex Pooled and Sex Unknown attempts. Surprisingly, 54% of femora from the Greek sample were classified into the Indian group using the Sex Unknown and 50% for the Greek males and less than 14% for the Greek females using the Sex Known information . A standard size variable quantifies the overall size of the bone and scales linearly in relation to the raw measurements . Thus, iSecond, the calculation of separate estimates of the ancestral groups for males and females in this study had a positive impact on the classification accuracies. This observation is in concert with the recommendation by Komar , p. 163 versus 87% of male training samples. Liebenberg et al. [Third, the ancestry of females is more accurately assessed than males using our method. The accuracy of group classification in females was more balanced in each population and higher than in their male counterparts with the exception of the Indian males . This observation is consistent with ancestry estimation in several settings using postcranial bones , 29. Usig et al.  reportedThe model accuracy using LDA was comparable to RFM in the binary classification of sex. Male and female groups are nearly linearly separable using a combination of the three explanatory variables . NotwithThe results also showed that none of the new variables was found to be significant for sex assessment. This is in agreement with a previous Spanish study where the accuracy of sex estimation did not increase using the angles, areas and ratios between these variables . The modWhile there are no studies exploring the utility of populations differences in Purkait’s triangle in the proximal femur for ancestry estimation, a handful of previous studies have explored the shape and size differences in raw measurements and ratios of femur for ancestry estimation , 76. In The results of ancestry estimates in the previous studies vary with the type and number of variables employed, available skeletal elements, as well as the population studied. For example, the utilization of the femur neck axis length (FNAL) alone achieved 46.2% in a six-way analysis of sex and ancestry in American European, African, and Native individuals with complete failure in allocation of American African females. A male sex-specific three- and two-way analysis provided overall accurate classification of 57.1% and 53.2%, respectively . These cversus Hispanic male individuals using seven variables namely femur maximum length, femur epicondylar breadth, femur maximum diameter of head, femur anterior–posterior subtrochanteric diameter, femur transverse subtrochanteric diameter, femur anterior–posterior diameter at midshaft, femur circumference at midshaft.Furthermore, the findings herein indicate comparable or even better results to the overall accuracy (60%) reported by Lienberberg  in a thrUsing multiple postcranial bones in the LDA, better overall results were obtained being 79% and 85% accurate classification in the North American  and SoutWhilst the findings of these aforementioned studies cannot be directly compared with the results of this study, it is clear that sex and ancestry differences in the morphology of posterior aspect of femur can be discerned. Given the previously reported populations differences in proximal femur morphology, it should come as no surprise that the reported classification rates to the appropriate population group are more than chance but are based solidly on the intelligent classifier (i.e. RFM) employed in the current investigation. This patterning is — in part — thought to be the result of genetic drift as well as natural selection and adaptation to highly varied microenvironments in worldwide populations , 63, 77.Purkait’s triangle method combats several issues encountered in ancestry estimation, for example, the measurements are typically reproducible, and relatively simple, with few number of variables can be collected. Purkait’s triangle captures an approximation of femur neck length and angle simultaneously. There is a paucity of research on the femoral NSA due to problems and uncertainties regarding the best method for determining the NSA. Moreover, the complex anatomical aspects of the proximal femur make measurement difficult, including the lack of reliable landmarks and the irregularities of the neck contours, which makes the definition of the neck axis ambiguous , 78. TheA great utility pertinent to its applicability in forensic case scenarios where partial remains are recovered with intact proximal portion of femur. On land, post-cranial bones may be less affected by animal scavenging and other post-mortem factors , 79. TheSupplementary Information is needed. Even better, the use of multiple elements approach offers the potential for combined probabilities and likelihood that should enhance the identification effort in order to achieve the required levels of reliability for forensic applications. Thus, the proposed method might be considered for use in forensic cases involving these three populations while practicing some caution with Greek males. The difficulty in Greek (European) male allocation supports the need for a more refined level of ancestry estimation to fully account for human variation at the population-level [The comprehensive morphological information presented in this paper may be useful in the event that the cranium is unavailable for examination or in instances in which on-level . It mustOne should also note that Greek individuals are accurately separated from the Egyptians which may refer to the applicability in tracking deaths of migrants through the Mediterranean routes. Further, migration in the Arab region is multi-faceted and varies in the scope between countries. Conflicts in the region have led to over 16 million refugees, mainly in Iraq, Libya, Somalia, the Sudan, the Syrian Arab Republic and Yemen. Syrian refugees represented one-third of them since 2011 . Large nFinally, to what extent the overall body mass/size could underpin the intrapopulation variation of the shape of the proximal femur as opposed to inter-population differences remains to be established. Therefore, evaluation of populations from different backgrounds such as Arab migrants and other nationalities needs more attention in future studies to be able to assess the general usability of the method for more accurate and precise ancestry estimates.The use of standardized procedures for investigations of the dead by forensic scientists and investigative agencies involved in the management of dead migrants is paramount to ensure a dignified management of the tragedic incidents. The results presented here are the first, comprehensive analysis of variation in the morphology of the proximal femur as captured by Purkait’s measurements. The core elements to the proposed methodology include analysis of geographically distant groups for insightful study of the diversification of modern humans, applying robust modelling techniques to reveal the subtle differences among the pooled sample, and the demonstration of the differences between the most important variables selected for each classification task. However, the distinctions among geographically distant populations may be blurred as a result of significant intra-population variation which may adversely impact the correct allocation into appropriate ancestry groups. Undetected and/or undocumented intra- and inter-group variations beyond the historical three-group model have significant bearing on forensic anthropological casework.MennattAllah Hassan Attia conceived of the study, and participated in its design and coordination and drafted the manuscript. Yasmin Tarek Farghaly carried out the Egyptian data collection and DICOM file processing, participated in the study design and helped to draft the manuscript; Mohamed Hassan Attia and Bassam Ahmed El-Sayed Abulnoor participated in the study design and performed the statistical analysis in Python and R programming languages, respectively. Sotiris K. Manolis and Ruma Purkait carried out Greek and Indian data collection, respectively. They provided resources and supervised writing the first draft of the manuscript. They participated in reviewing and editing of the manuscript. Douglas H. Ubelaker provided resources and supervised writing the first draft of the manuscript. He participated in reviewing and editing of the manuscript; All authors contributed to the final text and approved it.This research study was conducted retrospectively from radiological database obtained for clinical purposes with institutional approvals. The study protocol has been approved by the Research Ethics Committee of faculty of medicine, Alexandria University, Egypt. .


The knowledge aboutthe integration of letter motor programs during learning to write support the idea of an interdependence of visual and kinesthetic controls to direct the strokes.The objective of our study is to analyze the effect of the vision suppression both on the postural-gestural organization and on the spatial/temporal/kinematic parameters in a prescriptural task.35 school aged children with handwriting disorders (HD group) aged 6-11 years and 35 matched typical children were included in the study. They performed a prescriptural task of copying a cycloid line of loops, carried out under two conditions, with open eyes versus closed eyes. Postural-gestural measures were recorded with two video cameras allowing 2D reconstruction of the gesture. Spatial/temporal/kinematic measures were recorded with a digital pen.The HD group showed a significantly poorer postural control and an improvement in the spatial/temporal/kinematic parameters of the loops when they closed their eyes compared to eyes open. In typical group, the postural-gestural organization became significantly more mature but with no significant influence on the spatial/temporal/kinematic parameters of the loops.HDs could be partly explained by a deficit in the processing of proprioceptive/kinesthetic feedback and a disruptive effect of the visual control on the quality of the prescriptural drawings. The ability to direct the strokes would remain dependent on sensory feedbacks, themselves insufficiently efficient, which would lead to difficulties in reaching a proactive control of handwriting. These results should be able to enhance clinical practices and to contribute to clinical decision making processes for handwriting disorders remediation.No significant relationships.


With the complexity and refinement of industrial systems, fast fault diagnosis is crucial to ensuring the stable operation of industrial equipment. The main limitation of the current fault diagnosis methods is the lack of real-time performance in resource-constrained industrial embedded systems. Rapid online detection can help deal with equipment failures in time to prevent equipment damage. Inspired by the ideas of compressed sensing (CS) and deep extreme learning machines (DELM), a data-driven general method is proposed for fast fault diagnosis. The method contains two modules: data sampling and fast fault diagnosis. The data sampling module non-linearly projects the intensive raw monitoring data into low-dimensional sampling space, which effectively reduces the pressure of transmission, storage and calculation. The fast fault diagnosis module introduces the kernel function into DELM to accommodate sparse signals and then digs into the inner connection between the compressed sampled signal and the fault types to achieve fast fault diagnosis. This work takes full advantage of the sparsity of the signal to enable fast fault diagnosis online. It is a general method in industrial embedded systems under data-driven conditions. The results on the CWRU dataset and real platforms show that our method not only has a significant speed advantage but also maintains a high accuracy, which verifies the practical application value in industrial embedded systems. With the development of modern industrial systems and the pursuit of extreme efficiency, complex industrial systems are gradually automated, sophisticated and integrated . MechaniThe existing research on fast fault diagnosis of the rotating components has achieved valuable results. Such as a data-driven bearing prognostic scheme that was designed based on novel health indicators and gated recurrent unit network . The wor1.The original sampling signals contain a lot of redundant information, which will greatly increase the pressure for subsequent data transmission, storage and calculation.2.Features extracted from the original sampling signals have problems such as high computational complexity, long time consumption and incomplete reflection of fault features.3.Existing fault diagnosis methods cannot effectively balance efficiency and accuracy in resource-constrained environments and cannot effectively classify sparse signals.Starting from the above three aspects, this work further explores the three limitations:Recently, industrial embedded systems  have draCompressing the data from the data sampling source will significantly reduce the subsequent computational complexity. Compressed sensing (CS) theory, which integrates data sampling and compression, may give us some inspiration . CS adopSome studies have introduced the concept of CS ,23,24, aDeep Extreme Learning Machine (DELM)  is a mul1.A data-driven general method for fast fault diagnosis is proposed. This method only needs a small amount of compressed sampling data to achieve fast and high-accuracy fault diagnosis, which dramatically reduces diagnosis time in industrial embedded systems.2.A new adaptive feature extraction method for high-frequency monitoring signals is proposed. Our research found that not all IIoT monitoring signals are strictly sparse, a sparse basis should be added before compressed sampling, and then the transformed high-dimensional signal should be compressed by the observation matrix. This can be seen as a feature representation.3.An improved DKELM fault diagnosis module is constructed. The module can better adapt to sparse signals and provides a new idea for fast fault diagnosis in industrial embedded systems.Combining the advantages of CS and DKELM, this paper proposes a general diagnosis method to realize the functional integration of signal compressed sampling, feature adaptive extraction and fast fault diagnosis. Meanwhile, the Particle Swarm Optimization (PSO) Algorithm  is used The remainder of this paper is organized as follows. Aiming at the limitations of current fault diagnosis methods, such as low computational efficiency, difficulty in feature extraction, the poor balance between efficiency and accuracy and insensitivity to sparse signals, a general method for data sampling and fast fault diagnosis based on CS and DKELM was proposed. This method has two main advantages: one is that it is essentially a classic machine learning algorithm, so its model and computational complexity are lighter than deep learning algorithms, which is more suitable for deployment in industrial embedded systems; the second is that it is especially improved for the sparse signal after compressed sampling, which not only shortens the diagnosis time but also maintains high accuracy. It includes a CS-based data sampling module, which achieves substantial compression on the premise of retaining fault information, greatly reducing the computational complexity of subsequent feature extraction and fault classification. It also contains a DKELM-based fast fault diagnosis module. Through multi-layer nonlinear learning of low-dimensional sampled values, adaptive extraction of fault features and fast diagnosis of sparse signals are realized. The method in this paper is a general method for fast fault diagnosis, which is suitable for high-frequency monitoring signals in industrial systems. The vibration signal of rotating machinery is used here as a demonstration. The procedure of the proposed CS-DKELM method is shown in D, the dimension of which is 1000 × 4800. We randomly selected 70% of the data as training data and the remaining 30% as test data. Then, the preprocessed data set D was compressed, sampled and normalized. The measurement matrix was a Gaussian random matrix, and the compressed rate was The experimental data were provided by the public bearing data set of Case Western Reserve University Bearing Data Center . This daM is the total number of samples. The data sample set can be randomly selected and divided into a training set The mechanical vibration signal is a high-frequency periodic signal. Calculating the monitoring signals directly will exceed the maximum length preset by the computer array in the industrial embedded system, resulting in memory overflow. Therefore, the data must be preprocessed into data samples. This method uses the sliding window for the monitoring signal and integrates the time series data into a data set In view of the large scale of the monitoring signals in industrial embedded systems, it is inconvenient to transmit, store and calculate. Donoho  proposedIn the process of CS, the Compressed Rate (CR) reflects the degree of compression of the original signal, which is defined as followsThere are two prerequisites for the realization of CS. One is that the original signal must meet the sparseness in a certain transform domain , and theOur research found that the high-frequency periodic monitoring signals are not strictly sparse in the transform domain, so they cannot be directly compressed via sampling. This module adds a Fourier transform matrix before compressed sampling to transform the time-domain signal into the frequency-domain (as shown in An Extreme Learning Machine (ELM)  is propoN training samplesGiving L is the hidden layer nodes. C is introduced in . The number of hidden layer nodes of the CS-DKELM was manually set to , and the optimization interval of the number of hidden layer nodes of CS-DKELM(PSO) was set to [10:1000]. The results of diagnostic accuracy and diagnosis time are shown in According to the analysis of To verify the effectiveness of the method in this paper, two classic methods , electric engraver and broken teeth, were man-made faults. Including the normal state, a total of 10 different health conditions were prefabricated on the above-mentioned platform, as shown in We used the CS-DKELM method to perform a fast fault diagnosis on the sampled data, and the average value of 20 trials is shown in In this work, we propose an integrated method for data sampling and fast fault diagnosis based on CS and DKELM. By compressed sampling the original monitoring signal, CS-DKELM can achieve substantial compression of monitoring data while preserving fault information. This sampling method for mechanical vibration signals greatly improves the efficiency of subsequent fault diagnosis. In the fault diagnosis stage, through the multi-layer nonlinear learning of the low-dimensional sampling values of the original signal, the adaptive extraction of fault features and the fast diagnosis of fault types are realized. We verified the accuracy and efficiency of the CS-DKELM method, and its influencing factors were studied and compared with existing methods. The analysis shows that the intelligent diagnosis method proposed in this paper has higher real-time performance and diagnostic accuracy in the resource-constrained industrial embedded systems, which are superior to the existing methods. Moreover, only a small amount of monitoring data needed to be sampled in our scheme, which greatly reduces the pressure of transmission, storage and calculation in the process of fault diagnosis. Finally, we applied this method to the actual hardware platform and achieved ideal experimental results, which verified the practical application value of the method proposed in this paper. In the future work, we will combine edge intelligence technology to study anomaly detection technology for multi-source time series data in industrial embedded platforms.


These are fast emerging research fields, providing new perspectives on innovative biomarkers. This Frontiers Research Topic focused on the application of imaging techniques and markers of connectivity, synaptic density and plasticity in animal models of neurological diseases.Changes in connectivity, synaptic density or plasticity occur early in the pathology of neurological diseases. Until recently, only a limited number of imaging tools, mostly in the Magnetic Resonance Imaging (MRI) field, could measure changes in connectivity in the living brain. Diffusion-based imaging and tractography have been used to study short and long-range brain anatomical connections while functional imaging of the resting brain has been used to characterize functional connectivity changes. Recently, novel positron emission tomography (PET) imaging ligands based on the structure of levetiracetam have become available which bind specifically to a molecule expressed in presynaptic synapses, synaptic vesicle glycoprotein 2A (SV2A), providing a non-invasive measure of synaptic density for Rossi et al. provided an extensive review of the currently accepted features and functions of the SV2A molecule and an overview of preclinical and clinical studies, shedding light on important questions which remain unanswered such as the true biological roles of SV2A, the entry mechanisms of levetiracetam and SV2A tracers as well as their binding sites, and the varying SV2A expression patterns in different brain structures and disease contexts. Future studies addressing these issues are necessary to determine whether increased tracer binding indicates more SV2A copies, more vesicles or more synapses. A better understanding of the tracer properties and the measurement of synaptic density calls for in depth validation using gold standard molecular biology approaches, reviewed by Serrano et al. Their review provides a critical assessment of challenges and limitations of employing synaptic density biomarkers in the study of brain disorders, and discusses the best implementation of available tools, including measurements in postmortem tissue by electron microscopy, histology, immunohistochemistry and autoradiography and in vivo using PET and MRI methods including magnetic resonance spectroscopy and chemical exchange saturation transfer. An important point was the translatability of most of these methods, also used in clinical research. Toyonaga et al. highlight the opportunities of SV2A PET in small animal imaging with a focus on challenges to be overcome with the goal of helping the reader to design and analyse SV2A PET imaging studies in small animals. They present main issues associated with small animal imaging including limited spatial resolution of PET scanners and challenges of kinetic modeling. They compared different injection routes and brain imaging characteristics of currently available SV2A tracers. These complementary articles focus on important aspects of SV2A PET aiming to improve the understanding, the quality of the data, the choice of methods to confirm in vivo findings and the best use of small animal models in hopes of raising the impact of this non-invasive tool in neuroscience research and drug development.A subset of the articles reviewed aspects of the use of novel PET ligands of synaptic SV2A density. Raval et al. imaged 6-hydroxydopamine (6-OHDA) lesioned rodents with unilateral dopamine depletion, with 11C-UCB-J and 18F-FDG, in one of the first studies to directly compare synaptic SV2A density with glucose metabolism. As expected, there was a correlation between the two tracers, both showing decreases in the ipsilateral striatum of 6-OHDA injected rats. However, their exploratory studies in extrastriatal regions implied a discordance in the direction of change in binding between the two tracers, and this interesting finding should be explored in further studies.A major question among PET researchers is the nature of the relationship between the novel SV2A ligands and FDG, the most commonly used PET ligand, which measures glucose metabolism. Droguerre et al. used this technique in a hypertensive rat model and revealed altered local and long-range functional connectivity consistent with clinical findings. This study illustrates the potential for functional ultrasound as a translational tool in Attention Deficit Hyperactivity Disorder research.A variety of techniques other than the classical diffusion and functional MRI methods are being developed to study brain connectivity and are the topic of much ongoing research, some of which are presented in this Topic. Functional ultrasound can be used to assess cerebral brain volume changes associated with resting-state functional connectivity modulations in animal models of neurological disorders. Arceves-Serrano et al. reviewed how PET and MRI can play a role in a better understanding of the physiology, morphology, and neuropharmacology effects of rTMS, including the effects on neurotransmission, brain activity, resting-state connectivity and microstructure. They highlight that these are complex and multifactorial, and depend on technical settings, but also on clinical states and patient populations. This knowledge should help clinicians select optimal protocols to stratify patient populations.Repetitive Transcranial Magnetic Stimulation (rTMS) has been used to treat symptoms of neurological and psychiatric disorders, but its underlying mechanisms are poorly known. Badea et al. proposed a novel metric, the absolute winding number, to characterize early changes in AD mouse models carrying different APOE gene mutations. The authors evaluated spatial search strategies through the shape of the swim path of the animals. This approach has the potential to identify altered circuits associated with cognitive changes in prodromal stages of AD.Measures of altered cognition of complex tasks such as navigation and orientation occur early in Alzheimer's disease (AD). Steinmuller et al. contributes new insight into the neuroanatomical features and connectivity of the minipig basal ganglia, demonstrating the existence of a hyperdirect pathway from cortical areas to the subthalamic nucleus and outlining cortico-striatal motor connections. The minipig is being increasingly used as a non-primate translational large animal model in neuroscience studies, and these findings are of particular relevance to studies of Parkinson's disease and deep brain stimulation.Neuronal tracing is a classic and well-established method to study neuronal connectivity. A study by Overall, the search for new imaging techniques and biomarkers of structural and functional connectivity changes in neurological disorders, and the use of novel PET ligands to assess synaptic SV2A density, should help to improve our understanding of pathophysiological states and provide new translational tools for clinical use.All authors listed have made a substantial, direct, and intellectual contribution to the work and approved it for publication.The authors declare that the work 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.


Prevention and treatment of aggression in psychiatric hospitals is achieved through appropriate medical treatment, professional skills, and optimized physical environment and architecture. Coercive measures are used as a last resort. In 2018 Aarhus University Hospital Psychiatry moved from 19th-century asylum buildings to a newly built modern psychiatric hospital. Advances within psychiatric care have rendered the old psychiatric asylum hospitals inadequate for modern treatment of mental disorders.To examine if relocating from a psychiatric hospital, dating from 19th century to a new, modern psychiatric hospital decreased the use of coercive measures.This is a retrospective longitudinal study, with a follow-up from 2017 to 2019. We use two designs; 1) a pre-post analysis of the use of coercive measures at Aarhus University Hospital Psychiatry before and after the relocation and 2) a case-control analysis of Aarhus University Hospital Psychiatry and the other psychiatric hospitals in the Central Region. Data will be analyzed in STATA using an interrupted time-series analysis or similar method. Additionally case-mix and sensitivity analysis will be performed.Preliminary results show a 45% decrease in the total number of coercive measures and a 52% decrease in the use of mechanical restraint. The reduction that may reasonably be attributed to the relocation is still to be determined and will be presented at the congress.The study may illuminate how future development and planning of psychiatric facilities might improve psychiatric treatment and increase the understanding of how structural changes might contribute the prevention of the use of coercive measures.No significant relationships.


Organ-on-a-chip models, or organ chips, are tiny devices designed to accurately recreate the natural physiology and mechanical forces that cells experience in the human body. Similar to computer microchips, though carrying fluid through channels instead of an electric current, organ-chips are lined with living human cells and their tiny channels can reproduce blood and/or airflow just as in the human body. Their flexibility allows the chips to recreate breathing motions or undergo muscle contractions. This new and rapidly expanding field of research provides a unique opportunity to build models of human organs and to study how cancer cells develop and spread within them. As these chips are simpler and cheaper than animal models of cancer, they could significantly increase the speed of drug discovery and testing in cancer research. This exciting potential has led to the rapid development of this technology in the United Kingdom, with active research on a range of cancer types. This review covers the broad sweep of organ-chip research in the UK, and the network of researchers and companies being developed. Finally, it concludes with a perspective on the future directions in the field as researchers aim to bring about a leap forward in cancer therapies.Organ-on-chip systems are capable of replicating complex tissue structures and physiological phenomena. The fine control of biochemical and biomechanical cues within these microphysiological systems provides opportunities for cancer researchers to build complex models of the tumour microenvironment. Interest in applying organ chips to investigate mechanisms such as metastatsis and to test therapeutics has grown rapidly, and this review draws together the published research using these microfluidic platforms to study cancer. We focus on both in-house systems and commercial platforms being used in the UK for fundamental discovery science and therapeutics testing. We cover the wide variety of cancers being investigated, ranging from common carcinomas to rare sarcomas, as well as secondary cancers. We also cover the broad sweep of different matrix microenvironments, physiological mechanical stimuli and immunological effects being replicated in these models. We examine microfluidic models specifically, rather than organoids or complex tissue or cell co-cultures, which have been reviewed elsewhere. However, there is increasing interest in incorporating organoids, spheroids and other tissue cultures into microfluidic organ chips and this overlap is included. Our review includes a commentary on cancer organ-chip models being developed and used in the UK, including work conducted by members of the UK Organ-on-a-Chip Technologies Network. We conclude with a reflection on the likely future of this rapidly expanding field of oncological research. The transition in cancer research from basic fundamental research to drug discovery most commonly involves the culturing of cancer cells in plastic 2D cell culture dishes alongside follow-up studies conducted on animal models. Indeed, at present, compelling preclinical evidence is a pre-requisite for progression into clinical trials . HoweverMost animal studies involve the treatment of subcutaneously implanted tumours in rodents. However, it is now well established that these studies are poor representations of human biology, notably because they lack key features of the native tissue microenvironments and mix human and non-human cells . It has Collectively, irrespective of the type of animal model used, preclinical studies are broadly accepted to be poor indicators of future therapeutic responses in human clinical trials . This prTraditional in vitro cell culturing involves 2D monolayers of cells grown on tissue-culture-treated glass or hard plastic, and has been used for over 50 years to assess the effects of drugs on tumour cell growth . AlthougA recent development in cancer research is the field of organoid culture, wherein samples of normal or cancerous stem cells are isolated from human epithelium and grown in ECM gels. In these conditions, organotypic microstructures self-form, recreating some elements of the TME. These outcomes have led to significant excitement regarding the propsect of a new in vitro tool for both drug discovery and personalised medicine . HoweverThis review focuses on microfluidic organ-chip devices and the application of novel tools to facilitate oncology research in the United Kingdom. We focus on both in-house systems and commercial platforms being used in the UK for fundamental discovery science and therapeutics testing. We cover the wide variety of cancers being investigated  and the broad sweep of different matrix microenvironments, physiological mechanical stimuli and immunological effects being replicated in these models. The focus is on microfluidic models specifically, rather than organoids or complex tissue or cell co-cultures. However, in cases where these cultures are being deployed innovatively in microfluidic devices, they are discussed here. In this review, we provide a commentary on cancer organ-chip models being developed and used in the UK, including work conducted by members of the UK Organ-on-a-Chip Technologies Network. We conclude with reflection on the likely future of this rapidly expanding field.Organ chips build upon the established field of microfluids, allowing the development of small-scale devices that can be finely-tuned for cell culture conditions. These chips are fabricated from optically clear plastic, glass or flexible polymers, with a common choice being polydimethylsiloxane (PDMS), to contain microchannels which can house selected populations of living cells and culture media. It should be noted that depsite its widespread use, an inherent limitation of PDMS is the tendency for drugs to be absorbed onto its surface. This could reduce the cell uptake of candidate drugs and is therefore a key challenge for the field. These channels and cavities can be arranged to mimic the in vivo physiology and pathophysiology of organs through building tissue- or organ-level structures in vitro . The terThese microfluidic devices have been used to create a range of different models, from “tissue chips”, which comprise a single channel and one cell type, through to complex “organ chips” that incorporate multiple cell types representing numerous tissues. These more complex chips are designed to allow communication and crosstalk across porous membranes or ECM barriers, often coated with a type of ECM hydrogel. Steady perfusion of the culture medium at low flow rates through the channels allows cells to be maintained and observed for long time-periods  . Indeed,A key advantage of many organ-chip platforms is the ability to simultaneously apply and control multiple biochemical and biomechanical cues to direct cell behaviour, allowing the replication of multiple critical aspects of tissue and organ physiology . It has The rapidly developing field of organ-chip research has been enthusiastically embraced by researchers in the UK and their collaborators across the globe see . Both coA standard measure of tumour growth when using traditional cancer-cell monolayer cultures is proliferation across a 2D surface. Similarly, in the more complex 3D environments that can be developed when using organ chips, the proliferation of cancer cells is a key measure of investigation. A collaboration between researchers at the University of Huddersfield and groups in Spain has taken a broad approach to investigating proliferation, building generalised models of the tumour microenvironments of both colon cancer and glioblastoma (an aggressive form of brain cancer) . These cA separate study, resulting from a collaboration between researchers in Germany and the University of Manchester, integrated proliferation measures as part of the assessment of safety and efficacy of an antibody immunotherapy treatment for a type of lung cancer that had potential side-effects on skin tissue. The group built a multi-organ microfluidic model of the human lung cancer microtissues, alongside a compartment containing human full-thickness skin equivalents. Using this model they were able to demonstrate disruption of both lung cancer cell growth rates and the normal proliferation of skin cells following antibody treatment. This demonstrated the potential of these multi-organ, microtumour models regarding the use of patient-derived cells and tissues for drug discovery, alongside the safety profiling of drug candidates .Separately, a multi-tumour chip model arose from a collaboration between researchers at University College London (UCL) and colleagues in China, containing both cervical and lung cancer cells, with a custom chip design guided by numerical modelling. This model was used to demonstrate that tumour cells could be tracked using fluorescent nanoparticles, allowing live cell tracking and the surveillance of cellular proliferation and tumour growth. Notably, these nanoparticles were found to behave similarly in mouse models, suggesting that this platform represents a useful microphysiological system for modelling in vivo tumour growth .Demonstrating the interest of industry in this area, CN Bio Innovations Ltd. and Astrazeneca PLC, both based in the UK, contributed to a project with US research institutes to build chip models of pharangyeal and lung cancers, with the aim of rigorously matching their growth profiles to in vivo data. As well as succeeding in this, the models managed to replicate the expected pharmacokinetic (PK) responses of the cells to different drugs over time, analogously to in vivo responses. This also represented an important step towards standardised, clinically-relevant outputs from chip models of tumour growth .The cascade of events involved in the metastasis of primary tumours to distant sites is poorly understood, but is universally associated with poorer clinical outcomes in cancer patients. Due to these poor prognoses, metastasis is an area of extreme interest in the field of oncology . RegardlThis cascade is composed of a number of complex steps, which have not been well captured in monolayer cell cultures. However, the tunability of organ-chip devices has proven useful for building complex 3D microenvironments that represent cancer cells disseminating into the vasculature, as well as extravasating into the tissue.A research group at the University of Cambridge fabricated a custom-designed PDMS chip to investigate the transendothelial migration of individual breast cancer cells. This platform enabled them to capture the dynamic process of single breast cancer cells exiting the vessel lumen into the surrounding extracellular matrix. Interestingly, the presence of an endothelial lining significantly reduced the cancer cell extravasation events over a 15 h imaging period. A particular strength of the organ-chip approach used here was the ability to map the z-position of individual cancer cells within a 3D vessel representing the lumen, enabling the identification of cancer cell transmigration ‘hot spots’ in real-time, using live-cell imaging. The findings also suggested that variations in the microvessel qualities may result in two distinct types of cancer transmigration behaviour, potentially explaining the success or failure of circulating tumour cells at distant cancer sites .A similar approach was taken in a collaboration between UCL and researchers in Germany, in which custom designed PET-PDMS models of extravasation were built. The team focused on lung and skin cancers, and found that the rapid breakthrough of an epithelial cell layer by cancer cells could be replicated in the chip. Additionally, the researchers were able to manipulate the flow conditions within the vascular channel, discovering that the number of adherent and invading cells depended on both the flow magnitude and flow dynamics . The data not only indicated a role for mechanobiology in the metastatic cascade, but also highlighted how organ-chip models may help to explore these processes .Another type of multi-organ chip, developed at Queen Mary University of London, aimed to determine the interaction between breast or prostate cancer cells and osteocytes, the most abundant bone cell type . The useThese mechanical stimulation techniques may also be applied to spheroid cultures, as performed by researchers at the University of Hull investigating the effect of flow on both glioblastoma and breast cancer cells. By custom-designing a glass microfluidic chip capable of containing singular cancer cell spheroids under continuous flow, they measured the increased release of pro-metastatic factors and inflammatory cytokines when stimulated mechanically. This suggests that the inflammatory response of cancer cells can be modulated by mechanical stimulation, which may have potential implications when considering interactions between cancer cells and immune cells .The impact of mechanical stimulatin on cancer and immun cell interactions has been investigated by researchers in the University of Birmingham, in collaboration with colleagues in Singapore and Boston, using a combined in vitro and computational approach to model macrophage migration under the influence of cancer cells. In a complex 3D organ-chip model, the team observed that macrophage migration was influenced by the combined presence of tumour cells and interstitial fluid flow. Building upon this in vitro work, the researchers built an in silico model to link these observed behaviours to cytokine and mechanosensitive signalling . Most inGlioblastoma cells must develop the ability to control the perivascular niche in order to manipulate its local microenvironment. This niche is particularly difficult to replicate in either animal models or traditional cell cultures; therefore, organotypic chip models may be of particular benefit to exploring this niche. With an organ chip built to a custom design from PDMS and containing endothelial cells from a range of different human origins , researchers in Cambridge, Edinburgh and London collaborated to investigate whether the vascular environment affected the behaviour of glioblastoma cells. Endpoint biological assays, live cell imaging and qPCR showed that glioblastoma cells behaved in a more organotypic fashion when co-cultured within a perivascular niche comprising cells of brain origin. They also found that in these endothelial cells, genes for neovascularisation were upregulated, suggesting cancer cell manipulation of this environment .As well as exploring the broad behavioural phenotypes of cancer cells, organ chips can also be used as fundamental science tools to target specific genes and study the resulting interactions. A team from Imperial College London (ICL) worked with colleagues in China to build a custom-designed PDMS organ chip to investigate p62 expression in triple-negative breast cancer cells . ThroughAnother interesting collaboration exploring immune–vascular interactions using organ chips was established between researchers at the University of Sheffield and US colleagues in California, Seattle and Boston. The groups showed evidence of direct engagement between triple-negative breast cancer cells and monocytes in a 3D vascular niche, finding that this engagement affected the differentiation of monocytes into macrophages. They also found a reciprocal role for the monocyte/macrophages in controlling the degree of migration and intra/extravasation that was possible in the vascular environment. This demonstrated a complex cell-crosstalk at play within this chip microenvironment, which could be further exploited to unpick the molecular mechanisms involved .As well as the wide-ranging possibilities provided by organ chips to measure the direct interactions between cancer cells and tissue-relevant cell types, these tuneable microenvironments grant the possibility to understand fundamental mechanisms in health and development. Understanding these mechanisms is critical for comprehending how their disruption is implicated in malignancy. The behaviour and differentiation of cells in epithelial layers under various types of mechanical stress is a crucial area of study in development, with cell fate known to be connected with forces experienced across an epithelium. This is of importance for cancer research, as the epithelium is the overriding source of malignancy in many major cancers. Furthermore, a major step in the progression of many cancers is the disruption of the epithelial barrier, which is associated with the growth and spread of the disease.Investigating this behaviour, collaborators from Kings College London (KCL), Singapore, Israel and China built an organ chip that replicated the liver epithelium . Using RAnother key event required for tumour progression is angiogenesis, as growing tumours require ever-increasing nutrient supplies, beyond what is available in their initial microenvironment. Additionally, the vasculature is also a common route for metastatic cells to access distant sites, and thus angiogenesis presents a tantalising target for therapeutic intervention to improve patient prognoses. Researchers at the University of Sheffield, alongside colleagues in Italy, Singapore and Boston, built a 3D microvasculature environment in order to assess the effects of various anti-angiogenic agents on the development of new blood vessels in cancer . This chAn interesting cancer-associated behaviour that has been observed clinically in a range of cancer types is increased coagulation or clotting in blood. It is not entirely clear why this occurs, with theories ranging from an increased inflammatory response to actively aiding metastatic spread via attachment to the endothelium. This is extremely difficult to study in vivo, and chips present an ideal testbed to monitor the effect of circulating signalling molecules and microvesicles released by cancer cells into conditioned media. A group at the University of Hull took this exact approach, observing the upregulation of procoagulation activity in human endothelial cell chips when exposed to conditioned media from pancreatic, ovarian and glioblastoma cancer cells ,47.While the use of organ chips to completely replace animals in preclinical testing is a widely-held hope for the field, perhaps the most exciting and more immediate prospect for organ chips lies in their ability to rapidly screen for leading drug candidates. Nowhere is this problem more pressing than in the testing of new cancer drugs, as oncological treatments have the lowest success rate of any therapeutic field, with only 5.1% of cancer drugs that enter Phase I clinical trials ultimately being approved by the FDA . Even wiExamples of this in action in the UK have been mentioned above, with researchers in Huddersfield testing the reaction of colon cancer and glioblastoma cells under doxorubicin treatment . SimilarImmunotherapy testing is of key interest in cancer, and researchers at UCL have worked with international partners to construct a 3D microfluidic microenvironment using SU-8 materials . This brA similar approach taken by researchers at ICL, alongside colleagues in France, led to the development of a “metabolomics chip” , in whicAlongside the liver, the kidney is an organ affected by treatment toxicity, and therefore an important organ to monitor during drug discovery. A team at the University of Cambridge recently built a custom-designed PDMS chip, in collaboration with groups in China, Finland and California, modelling kidney cancer progression to the liver, a common metastatic site for this cancer type. By using a combination of different cells, they were able to predict the treatment efficacy of 5-fluoracil, an anti-cancer drug, on metastatic kidney cells, while also screening for its effects on hepatocytes .Drug testing using organ chips can be augmented to incorporate more complex structures such as spheroids, while still recapitulating some of the mechanical stimulation experienced in vivo. This was the approach taken in a collaboration between the University of Westminster and UCL, in which researchers developed a PDMS in vitro 3D model comprising a central high-density mass of triple-negative breast cancer cells surrounded by collagen type-1 and incorporating fluid flow and pressure . Under tA similar spheroid approach was taken by a Cambridge research group to investigate colorectal cancer. The team used a chip model comprising commercially available Ibidi polystyrene chips, adding Matrigel-encapsulated colorectal cancer spheroids to the microfluidic system. This allowed them to test a number of drugs on their experimental model, measuring the pharmacodynamic (PD) response and finding that it matched in vivo mouse plasma exposure profiles well. This spheroid approach also allowed them to monitor spheroid volume and viability, which were analogous to clinical measurements used in monitoring these tumours .The testing of cancer therapeutics is not limited to drug screening. In a collaboration between the University of Hull, the University of Sheffield and Sheffield Hallam University, researchers investigated the effects of radiation treatment on rare head and neck squamous cell carcinomas (HNSCC) using a microfluidic model. The aim of this study was to develop patient-specific prognoses in response to radiation to help refine treatment options for clinicians. Taking patient biopsies and growing them in a glass organ-chip microenvironment, they were able to faithfully demonstrate the significant inter-patient variability seen in the clinic ,58. In aThe organ-on-a-chip (OOAC) concept emerged about 10 years ago, when scientists combined fluidic systems and analytical methods with both 2D and 3D cell culture protocols into new in vitro models. Since then, the global organ-chip market has expanded exponentially, being recently valued at USD 21 million and projected to reach USD 220 million by 2025 .Historically, an early attempt to gather the key academic and industry stakeholders occurred at the 2014 “t4 transatlantic think tank for toxicology”, which held a workshop focused on the State of the Art in 3D Organ Chip Cultures. This group, which included representation from the UK, released a detailed report outlining the immediate challenges facing the field, including those related to cancer . The recThis activity has also benefited work towards the additional goal of reducing the use of animal models in research and drug testing, with the establishment of centres tasked with sourcing new technologies to improve the efficiency of preclinical testing. This began with the Centre for Alternatives to Animal Testing at Johns Hopkins University, with a satellite location at the University of Konstanz in Germany. The UK followed with the founding of the Animal Replacement Centre of Excellence at Queen Mary University of London, with Canada later launching the Canadian Centre for Alternatives to Animal Methods at the University of Windsor. These dedicated research centres act as nuclei for creating further awareness of the opportunities provided by these technologies.The progress towards this goal of more physiologically relevant models was addressed at a workshop held in the United Kingdom  and included an overview of organ chip technology and its utility. A regulatory view of organ-chip technologies was outlined by David Jones of the UK Medicinces and Healthcare products Regulations Agency (MHRA), noting that in the future organ chips may be applied in human clinical trials to improve safety and efficacy profiles. Furthermore, scientists from the UK were involved in an “Organ on chips: Current gaps and future directions” conference led by GSK and the Biochemical Society (2019). This conference assessed the current challenges involved in the widespread adoption of these model and the design of strategies which may help to surmount these challenges . The UK As an indication of the growing partnership between industry and academia in this field, in 2020, Kirkstall Ltd., one of the leading organ chip commercial manufacturers in the UK, organised a special meeting of the Advances in Cell and Tissue Culture Conference focussed specifically on the topic “Towards More Predictive, Physiological and Animal-free In Vitro Models”. This was attended by all the major academic and industrial players from the UK and Ireland. The major conclusion of this meeting was that in order to gain acceptance for organ-chip technologies, it is necessary to target specific preclinical or clinical tests to replace, and to tailor different models to replace specific tests. This was deemed to increase the likelihood of success over aiming to replicate entire systems faithfully . This teAs a measure of the growing interest in this field, in 2018 the UK Research and Innovation (UKRI) funding agency supported the creation the Organ-on-a-Chip Technologies Network, a Technology Touching Life initiative funded by three research councils. This network ran symposia, public engagement events and training sessions and provided seed grants to draw new researchers into the field. The Network also helped to establish the Queen Mary + Emulate Organs-on-Chips Centre at Queen Mary University of London and provided joint proof-of-concept funding for 18 projects using the Emulate platform. The network has played an active role in shaping policy within the United Kingdom, serving as an expert advisor on animal replacement for key stakeholders, including the Royal Society for the Prevention of Cruelty to Animals (RSPCA), the UK Government Home Office and the UKRI Biotechnology and Biological Sciences Research Council (BBSRC). This engagement with policy-makers is key to further developing standardised regulations, alongside partners in the Regulatory Advisory Board of EUROoCS for the European Medicines Agency (EMA).This Network stimulated a key study from the University of Leeds, which surveyed a broad range of organ-chip developers and end-users . DespiteTaken together with the meetings and reports already mentioned, the survey results demonstrated that there is much overlapping interest and a willingness within the organ-chip community to co-develop existing platforms, ancillary technologies and tools required for the widespread use of organ chips. These active and collaborative research efforts, in both industry and academia, could accelerate the advancement of organ chips to the market and enable the broader adoption and acceptance of the technology, ultimately continuing to support this current exponential growth of the market in the years to come.A further key activity of the Organ-on-a-Chip Technologies Network lies in supporting early-career researchers in the field in order to help the sector flourish as it grows. A particular challenge associated with this is the difficulty inherent in changing a chip model once it has been established in a laboratory, particularly as time spent altering a model to fit field standards or regulatory requirements can feel like a backward step in driving a career. Therefore, the Network has identified that the development of standardised protocols, for example, for the reliable alteration of substrate stiffness inside chips, is urgently required so that methods are widely reproducible and findings are repeatable across the field.As a final note, although the above describes the outlook for organ chips as a whole, perhaps the greatest opportunity for regulatory approval lies in the oncological space. With a projected estimation of one in every two people being diagnosed with cancer in their lifetime, the current timeline for the development of oncology therapeutics is inadequate. The development of cancer treatment remains exorbitantly costly, and it has the lowest success rates in terms of FDA approval. By drawing together the exciting and rapidly developing research in this space in the UK, we hope to spur on these efforts and demonstrate their importance in the development of the both the field and the market.It is clear that organ-on-a-chip research presents a unique opportunity to accelerate both fundamental discovery science and therapeutic testing across the broad range of oncological research. By providing organ-chip models that can better mimic human tissues and the tumour microenvironment, new avenues of scientific enquiry are being explored. Similarly, organ chips provide an additional screening step to determine leading drug candidates early, reducing the need for animal testing and concentrating investments on the most promising targets.This technology has generated significant interest in the United Kingdom, with a growing network of academic and industrial researchers that is now well-established. Strong engagement with regulatory bodies and a focus on standardisation and reproducibility will be key to the future success of this field. Researchers in the UK are focusing on this in the next generation of organ chips, in order to spur the development of new cancer treatments.