Access to voting is increasingly recognized as a social determinant of health. Health equity could be improved if healthcare workers (HCWs) routinely assessed the voter registration status of patients during clinical encounters and helped direct them towards appropriate resources. However, little consensus exists on how to achieve these tasks efficiently and effectively in healthcare settings. Intuitive and scalable tools that minimize workflow disruptions are needed. The Healthy Democracy Kit (HDK) is a novel voter registration toolkit for healthcare settings, featuring a wearable badge and posters that display quick response (QR) and text codes directing patients to an online hub for voter registration and mail-in ballot requests. The objective of this study was to assess national uptake and impact of the HDK prior to the 2020 United States (US) elections.Between 19 May and 3 November 2020, HCWs and institutions could order and use HDKs to help direct patients to resources, free of cost. A descriptive analysis was conducted to summarize the characteristics of participating HCWs and institutions as well as the resultant total persons helped prepare to vote.During the study period, 13,192 HCWs  from 2,407 affiliated institutions across the US ordered 24,031 individual HDKs. Representatives from 604 institutions  ordered 960 institutional HDKs. Collectively, HCWs and institutions from all 50 US states and the District of Columbia used HDKs to help initiate 27,317 voter registrations and 17,216 mail-in ballot requests.A novel voter registration toolkit had widespread organic uptake and enabled HCWs and institutions to successfully conduct point-of-care civic health advocacy during clinical encounters. This methodology holds promise for future implementation of other types of public health initiatives. Further study is needed to assess downstream voting behaviors from healthcare-based voter registration. Civic participation, which includes voting in elections, is associated with better self-reported physical and mental health. This is described across a growing body of cross-sectional and longitudinal studies, and the mechanism seems to be multifactorial and bidirectional . Many auConversely, when marginalized communities abstain from voting–whether due to alienation, suppressive policies, or excess mortality–it can negatively affect their health –5. The pIn June 2022, the American Medical Association recognized access to voting as a SDOH . HealthcExpanding voter registration access through healthcare settings is not without precedent. Several individual clinics have described successful voter registration initiatives at the local level –12. AddiVot-ER (vot-er.org), a nonpartisan 501(c)(3) nonprofit, was founded with the vision of addressing this need. Furthermore, as the coronavirus disease 2019 (COVID-19) pandemic led to restrictions on in-person visits to traditional voter registration sites like departments of motor vehicles and made in-person voting a public health risk, the organization recognized the importance of identifying new channels for promoting voter registration and voting by mail. To that end, a diverse team including designers, HCWs, students, and volunteers developed and distributed the Healthy Democracy Kit (HDK), a readily scalable toolkit that HCWs and institutions could use to connect patients with voting resources during clinical encounters. The purpose of this study was to describe the design, implementation, uptake, and impact of this initiative ahead of the November 2020 US elections.Vot-ER developed two types of HDKs: individual and institutional Fig. . The indThe HDK was designed to maximize HCW workflow efficiency and simplify the patient experience. The key functional elements of HDKs were quick response (QR) and text codes located on the badges and posters. Once participants scanned the QR code or texted “VOTE HEALTH” to “34444” with their smartphone, they were automatically directed to an online hub Fig.  containiHCWs using individual HDKs were instructed to provide a neutral prompt about voter registration during clinical encounters , at which point they could display their badges for patients to scan at the point-of-care. Institutions that displayed codes on posters in waiting areas, after-visit summaries, or other site-based materials created opportunities for passive prompting of patients. HCWs and institutions did not conduct voter registration directly; by design, patients completed the next steps of inputting their information themselves on their smartphones, allowing HCWs to move forward in their clinical workflows.Impact).We provided institutions with the option of customizing their HDKs with a text code of their choosing  and a unique trackable QR code. Customization allowed for near real-time tallying of voter registration and mail-in ballot requests initiated by each institution  and ideas42 funded the production and shipping of physical HDKs, which were provided to HCWs at no cost. Volunteers assembled the physical HDKs for shipping. Institutions received digital HDKs for free and covered their own costs of producing badges and posters locally.We conducted a descriptive analysis of individual and institutional HDK orders placed between 19 May and 3 November 2020. A subset of this data has been described previously in analyses of pediatric  and mediTo better understand the patient populations served by HCWs and institutions that used HDKs, we linked affiliated institution and institution ZIP codes to publicly available datasets with ZIP code-level socio-demographic characteristics, including the 2013 Urban Influence Codes  . Subsequent data entered into the third-party websites, including completed registrations, were not accessible by the study team or included in this study, but a third-party overview of key demographics and aggregate voter turnout for participants is referenced in the Discussion.For institutions utilizing customized codes, we created an online leaderboard that ranked institutions by the number of people they helped initiate voter registration or mail-in ballots. This tool provided feedback by automatically updating every 15 min and allowed institutions to monitor their own performance and make peer comparisons, such as in our previously described voter registration competition amongst 80 US medical schools .Descriptive statistics were derived using RStudio .We adhered to the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines .Between 19 May and 3 November 2020, 13,192 HCWs ordered 24,031 individual HDKs. The largest increase in individual HDK orders occurred during the month of August 2020, which coincided with the inaugural Civic Health Month , when over 100 civic engagement and healthcare partners promoted the importance of civic health across their institutions . From 1 Most individual HDK users identified as physicians , many of whom reported their experience level   initiated voter registrations and 9,248 (54%) initiated ballot requests. Institutions that successfully implemented custom codes initiated a median of 316  registrations and 167  mail-in ballot requests. The institution with the greatest number of people helped was Penn Medicine, with 1,692 initiated registrations and 2,070 initiated ballot requests.This study describes the largest healthcare-based voter registration initiative to date, with unprecedented reach in terms of numbers and types of participating HCWs and institutions, geographic spread, and people helped. This initiative had several unique strengths that facilitated rapid adoption and utilization nationwide.One major innovation was the technologic approach, which centered around QR and text codes and leveraged increasing rates of smartphone ownership (over 85% of Americans) and online voter registration , 30. ThiSimplicity: The HDK was designed to be intuitive and low-effort for HCWs and institutions to acquire, implement, and scale. It was offered at no cost and designed to minimize workflow disruption. Additionally, once a badge was donned, it naturally became part of a HCW’s uniform and eliminated the need to remember to carry around materials. The single-hub website design and helpline streamlined resource access for patients.Visual saliency: Badges were designed to be more colorful and larger than hospital IDs, with an exposed banner asking, “READY TO VOTE?”. This visual nudge helped capture the attention of patients and HCWs alike, facilitating natural discussions about voter registration with patients and prompting interested colleagues to obtain their own HDKs.Feedback, peer comparisons, and gamification: The online leaderboard provided participants with regular feedback in near real time. Participants may have been motivated by overall state or peer institution comparisons, as demonstrated in the highly effective medical school competition , le, le32], Overall, HDKs offer a novel and effective approach to engaging HCWs in advocacy at the point-of-care. No prior initiative describes a trackable code-based badge worn by HCWs, a tool which could be easily implemented for other types of advocacy campaigns. Compared to prior work, this initiative mobilized an unprecedented number and breadth of HCWs across the country to help as many as 46,712 people prepare to vote in 2020 . FurtherThe degree and rapidity of uptake signals a high level of enthusiasm amongst participating HCWs during 2020. In fact, US physicians, perhaps spurred by issues such as the COVID-19 pandemic and protests of racial inequities, were shown to have a higher voter turnout than the general population in 2020, in contrast to prior elections . We beliThe most exciting impact of this work is its potential to directly improve the SDOH of access to voting, and in turn to affect downstream inequities in civic representation and health outcomes. Promisingly, an initial third-party analysis by TurboVote suggests that our inaugural initiative was indeed effective in starting to address disparities in voter registration and in driving subsequent voter turnout. TurboVote reported that 84% of individuals helped by Vot-ER’s toolkit in 2020 completed voter registration and 85% of these registrants subsequently voted in the general election . Of thesThere are many ways in which future work can be expanded for even greater impact. In light of the upcoming 2024 US elections, we are actively working to expand implementation of HDKs to more rural and community-based settings (including more FQHCs), expand participation of certain professional roles such as nurses, and achieve even greater distribution across states. Given the democratized, low-cost, low-input, and largely digital approach of our initiative, the main logistical hurdles to scaling even further are awareness and institutional buy-in. We hope that in disseminating our work and demonstrating the potential positive impact, particularly as it relates to equity, these particular barriers may be lessened. Future data collection should include additional demographic characteristics of participants, follow-up voting behaviors , and the relative yield of different engagement approaches . Additionally, it would be meaningful to evaluate the perceptions and attitudes of both patients and HCWs about promotion of civic health. Furthermore, the US is not the only country in which marginalized groups experience disparities in both voting access and health outcomes, and our blueprint could be potentially adapted to international settings.Finally, while our initiative’s grassroots toolkit approach amongst HCWs and partner institutions held great value in rapid expansion at the point-of-care, there are other avenues by which access to voting could be expanded on a larger systematic scale. National health agencies  could implement a top-down approach with standardized materials and workflows for healthcare settings. Automatic voter registration could occur alongside the signup process for health insurance , allowing for upwards of 1.2 million yearly voter registrations . Public


Machine learning has achieved remarkable success across a broad range of scientific and engineering disciplines, particularly its use for predicting native protein structures from sequence information alone. However, biomolecules are inherently dynamic, and there is a pressing need for accurate predictions of dynamic structural ensembles across multiple functional levels. These problems range from the relatively well-defined task of predicting conformational dynamics around the native state of a protein, which traditional molecular dynamics (MD) simulations are particularly adept at handling, to generating large-scale conformational transitions connecting distinct functional states of structured proteins or numerous marginally stable states within the dynamic ensembles of intrinsically disordered proteins. Machine learning has been increasingly applied to learn low-dimensional representations of protein conformational spaces, which can then be used to drive additional MD sampling or directly generate novel conformations. These methods promise to greatly reduce the computational cost of generating dynamic protein ensembles, compared to traditional MD simulations. In this review, we examine recent progress in machine learning approaches towards generative modeling of dynamic protein ensembles and emphasize the crucial importance of integrating advances in machine learning, structural data, and physical principles to achieve these ambitious goals. Proteins are the major functional macromolecules in biology, which play critical and diverse roles in virtually all cellular processes and are involved in numerous human diseases, including cancers, neurodegenerative diseases, and diabetes ,2,3. A cNotwithstanding the remarkable successes of single protein structure prediction , the neeIn this short review, we summarize recent progresses in the development and application of deep generative models for biomolecular modeling, particularly those developed for generating dynamic structure ensembles of proteins in various contexts. We note that several outstanding reviews already provide in-depth discussions of how ML can be used to learn the energy landscape and collective variables (CVs), derive coarse-grained models, and generate protein structure ensembles ,57,58,59As illustrated in The second major class of functional dynamics include proteins that undergo large-scale conformational transitions between two or more major states, which can be triggered by a wide range of cellular stimuli, including ligand binding, PTMs, and changes in the solution conditions  ,65,66. FThe third and fourth classes of functional protein dynamics include proteins that can remain partially or fully disordered under physiological conditions ,74,75. TGenerative deep learning models are a class of neural networks that aim to learn the regularities of the training dataset and capture such regularities using appropriate probability distribution functions ,101. TheBriefly, autoencoders (AE) are unsupervised ML algorithms that use neural network (NN) architecture to compress input data into knowledge (latent) representations. As illustrated in A key application for ML in the generation of protein functional ensembles is to aid in the discovery of low-dimensional CVs that can distinguish important functional states, particularly those that could monotonically describe the transition between the states and are suitable for usage in enhanced sampling MD simulations such as umbrella sampling, adaptive sampling, and metadynamics ,59. Even12 and a small protein GB98. The results suggest that DESP can sample much broader conformational space compared to both conventional and accelerated MD within the same amount of simulation time. Importantly, unbiased probability distributions also could be uncovered. DESP is in principle generalizable to other proteins. However, additional work is required to understand how the quality of the latent space learned, as well as the choice of biasing potentials, affect the sampling efficiency. Further analysis is also required to evaluate how accurate and/or physical the additional conformational space sampled by DESP is. The apparent lack of reversible transitions in the DESP trajectories is concerning, which may reflect a critical limitation of using KL divergence directly to drive the sampling of new conformational space. Tao and co-workers [In the so-called deeply enhanced sampling of protein (DESP) method developed by Salawu , a neura-workers  have comTiwary and co-workers recently adapted reweighted auto-encoded variational Bayes for enhanced sampling (RAVE) for efficient sampling of protein loop conformations . RAVE isstakes function to modulate how rewards are attributed to different agents for discovering new states. The benefit of this multiagent formulation comes from two features. Conformations are labeled and utilized by the agent who discovers them, and therefore, each agent computes the rewards from different data points. Additionally, the agents share information within an action space to tell other agents what conformations they have already discovered. It was demonstrated that the multiagent REAP algorithm is more efficient in sampling the loop motion of Src kinase and driving large-scale conformational transitions of the transporter OsSWEET2b. The same multiagent formalism was shown to work well with other adaptive sampling techniques, including “least counts” and AdaptiveBandit. A key limitation of both single-agent and multi-agent REAP algorithms, though, is their dependence on user-defined CVs for prioritizing sampling. As illustrated in the works above, identification of such CVs can be highly nontrivial for protein conformational fluctuations in general. It is also not clear how one can reconstruct unbiased ensembles from REAP trajectories, a capacity which will be important for functional studies. The pros and cons of REAP and related adaptive sampling techniques remain to be thoroughly examined, especially compared to weighted ensemble methods that can recover both kinetic rates and thermodynamic stabilities of long-timescale processes [Reinforced learning (RL)-based algorithms ,117 haverocesses .Learning low-dimensional representations of protein conformational ensembles is of interest for more than driving MD sampling. In principle, if one can learn the latent space representation from a relatively limit set of conformations, , one could then sample in the latent space to directly decode and generate new high-dimensional structures of the same protein. The requirement here is that the latent space representation is smooth and continuous. Such a generative approach can be dramatically faster than MD simulations. Nonetheless, the complexity and sheer size of the conformational space should never be under-appreciated, even for small proteins. Functionally relevant conformational states are vanishingly small in comparison, and importantly, they can be well-separated in the Cartesian space. It is not entirely clear if the desired mapping of high-dimensional protein conformational space to a smooth low-dimensional latent space representation exists, or, if such a mapping can be reliably learned from an incomplete set of pre-generated conformations. Nonetheless, direct sampling of protein conformational space using ML-derived latent representation is a highly attractive strategy and has continued to attract intense interest in recent years ,122,123.13 and the protein calmodulin (CaM), the approach demonstrated modest success and could be most suitable for generating new initial structures for seeding additional MD simulations. Using pre-defined latent space is unusual and likely will be ineffective in general.The ability of using the latent space to generate physically plausible structures has been evaluated using a set of proteins of different sizes, topologies and dynamic properties . The resDegiacomi and co-workers  later deNres (number of residues). It was shown that only ~ the first 10% of the MD trajectories were necessary to regenerate the full ensemble of small IDP Q15, but the amount of training data required increased rapidly for larger IDPs such as ChiZ. The authors also evaluated the effects of latent space dimension and input features . The results showed that larger latent vectors do not improve accuracy and the choice of input coordinates does not significantly impact model performance. Curiously, evaluation of VAE performance has focused on the accuracy of regenerating individual conformers, as measured by root-mean-square-distance (RMSD). It would be more desirable to examine ensemble distributions of key local and global properties, such as overall size, residual structures, long-range contacts, etc. One could also examine the details of conformational substates using clustering and principal component analysis, in comparison to the available ensembles generated by much longer MD trajectories. Furthermore, the three IDP ensembles appear largely random and devoid of nontrivial local structures and transient long-range organizations. Yet, many biologically relevant IDPs, especially those involved in cellular signaling and regulation, are not random coils, and contain important residual structures [Success has also been demonstrated recently using VAE to learn the dynamic conformational space of IDPs using short MD simulations and then generate full disordered ensembles . Here, tructures ,125. As x) using a generative network and reweighting procedures. The generative network maps latent space samples from a simple prior distribution P(z)  to high-probability samples from the target distribution P(x)~ex)−u and internal (sidechains) coordinate sets. It was demonstrated that the eventual generator could sample a key X-O loop conformational transition of protein BPTI that occurs on a millisecond-timescale. Clearly, extension of Boltzmann generators for one-shot generation of dynamic protein conformational ensembles requires much additional work. It has been argued that training solely on the energy is unlikely to be adequate [An ultimate “one-shot” generative ML model would take the sequence of the protein and generate a full ensemble of the most relevant conformations. This is an extremely ambitious goal for proteins with high-dimensional and complex conformation space. Progress towards this goal has thus far been more limited ,127,128.Feig and co-workers recently described a conditional generative model for generating disordered protein conformational ensembles using the sequence alone as input . The modRecent breakthroughs in ML approaches have transformed the studies of protein structure and function. The problem of predicting a native structure of protein has essentially been solved. A key new frontier is expanding these ML approaches to help describe dynamic fluctuations and transitions of proteins that are crucial to its functions. For this, much effort has been dedicated to generative ML models such as VAEs and GANs . A commoIt is generally recognized that it is likely critical to incorporate physics towards generative ML models that may be more generally applicable to nontrivial proteins ,133,134.Deeper and more systematic understanding of if and how the complexity of the high-dimensional conformational space of proteins can be mapped to a smooth and continuous space of sufficiently low dimensionality. This may be investigated using ultra-long trajectories of a large set of folded and unfolded proteins, such as those from Shaw and co-workers, using the latest balanced atomistic protein force field , as wellConsistent and rigorous evaluation of the performance of generative ML models that is widely accepted and adopted by the community. At present, most developments are benchmarked using different custom examples and special test-cases. There is only minimal cross-comparison needed to rigorously establish the strengths and weaknesses of various approaches, such as over-fitting, computational cost, and interpretability. Again, ultra-long MD trajectories or highly-converged conformational ensembles generated from enhanced sampling simulations of proteins of different sizes, topologies and dynamic properties could be used as a standard benchmark set. Similar practices have been instrumental in the development of methods for predicting protein structure , proteinNew ML approaches for integrating information from diverse datasets, such as protein structures, sequence alignment, and MD trajectories, and incorporating physical principles of molecular interactions, such as various empirical protein energy functions. ML has been under accelerated development in recent years, with many exciting ideas emerging, such as large language models (LLMs) , deep trAt present, it is hard to clearly envision how generative ML models of protein conformational ensemble may look or how generally applicable these models will be across the spectrum of protein dynamics relevant to biological function . However


Dear Editoret al. assessing quality of life (QoL) of patients undergoing minimally invasive distal pancreatectomy (MIDP) and open distal pancreatectomy (ODP) in a randomized clinical trial setting1. It is encouraging to observe the increasing interest in patient-specific outcomes to inform clinical decision-making.We read with great interest the article by Johansen 3. Based on the LAPOP trial protocol and the present study, we were unable to determine the prehabilitation programme the participants underwent leading up to surgery. Additionally, it would be interesting to assess whether there were differences in length of prehabilitation and adherence with individual components between the arms, as these are crucial factors affecting postoperative outcomes4.It is well known that multimodal surgical prehabilitation, including exercise, nutrition, smoking/alcohol cessation, and psychological counselling, improves postoperative outcomes as well as long-term QoL5. Hence, it is also important to assess whether the arms differed in terms of their socioeconomic status, and how this might influence the long-term QoL outcomes following distal pancreatectomy.A key result of the present study is demonstrating that patients within the MIDP arm had similar scores in several QoL domains at 2 years, compared with a matched Swedish general population. One of the important confounders in QoL analysis is socioeconomic factors, such as education level, income status etc. A recent Swedish study identified that lower socioeconomical and professional status is associated with poorer postoperative health-related QoLet al. provide seminal data in relation to long-term QoL following MIDP and ODP, which adds to the rationale of the already standard minimally invasive approach for distal pancreatectomy. However, further information on the aforementioned variables may provide a more complete picture of the issue at hand. Lastly, as the majority of patients had benign indications, there remains a need to research the impact of rehabilitation/supportive interventions on QoL following DP for oncological indications, where more extensive support may be required.In conclusion, Johansen The authors declare no conflict of interest.


Machine learning-based gait systems facilitate the real-time control of gait assistive technologies in neurological conditions. Improving such systems needs the identification of kinematic signals from inertial measurement unit wearables (IMUs) that are robust across different walking conditions without extensive data processing. We quantify changes in two kinematic signals, acceleration and angular velocity, from IMUs worn on the frontal plane of bilateral shanks and thighs in 30 adolescents (8–18 years) on a treadmills and outdoor overground walking at three different speeds . Primary curve-based analyses included similarity analyses such as cosine, Euclidean distance, Poincare analysis, and a newly defined bilateral symmetry dissimilarity test (BSDT). Analysis indicated that superior–inferior shank acceleration (SI shank Acc) and medial–lateral shank angular velocity (ML shank AV) demonstrated no differences to the control signal in BSDT, indicating the least variability across the different walking conditions. Both SI shank Acc and ML shank AV were also robust in Poincare analysis. Secondary parameter-based similarity analyses with conventional spatiotemporal gait parameters were also performed. This normative dataset of walking reports raw signal kinematics that demonstrate the least to most variability in switching between treadmill and outdoor walking to help guide future machine learning models to assist gait in pediatric neurological conditions. Instrumented gait analysis of walking, a primary human locomotor action, is beneficial for healthcare ,2,3,4, rGround truth precision for gait data collection and analysis has been lab-based and is well-standardized using instrumented motion capture ,10. EquiWith the appropriate sensor setup, large amounts of data across patient populations, terrains, walking conditions, and gait speeds can be reliably captured; with appropriate analysis and signal processing techniques, the resulting output could be helpful for diagnostic, therapeutic, and assistive gait protocols. Such potential applications include early screening for Parkinson’s , gait trInertial measurement units (IMUs) include motion sensors  and rechargeable batteries that enable untethered use to stream and log gait data in and out of lab environments. Commercial IMUs such as the APDM Opal  and Xsense MVN  are now widely available for research and clinical applications and are capable of mounting on various locations on the body. Additionally, low-cost consumer IMU versions common in smartphones and watches make gait data collection and monitoring possible in many additional environments ,20,21. WDespite the inherent advantages of wearables, such as affordability, accessibility, and ease of use, their application in healthcare was tempered by both a lack of standardization in data collection and data analysis ,23,24. IGait kinematics vary substantially due to many factors, including patient populations, physical environments, and cognitive loads. Leveraging the advantages of IMUs, collecting big data helps address this variability ,16 to deGait assessment with IMUs involves separating the triaxial (anterior–posterior (AP) vs. medial–lateral (ML) vs. superior–inferior (SI)) signals, such as acceleration or angular velocity, into quantitative variables . In gaitRecent progress was seen in the clinical implementation of gait monitoring systems by using machine learning, which enables greater efficiency in processing gait parameters ,15,31,32The effect of varying conditions, such as walking surfaces, age, gait speed, and load, on walking gait was studied to different degrees. For example, ample published evidence demonstrates differences between treadmill walking and indoor overground walking . The gaiGait metrics, such as spatiotemporal parameters ,16,37, wAs IMU-based gait studies and gait similarity evolve, there has yet to be a consensus or standardization of which kinematic signals are most reliable across conditions that can be used to develop robust gait monitoring systems. In our study, we propose analysis methods that can identify the kinematic signals showing robust stability even when walking conditions change, such as variability in gait speed or physical environment, similar to real-world walking. The objectives of this study, therefore, were to provide proof of concept that (1) reliable lower limb kinematic signals derived from IMUs, such as angular velocity and acceleration, can be identified that are independent of treadmill and outdoor overground walking conditions and (2) reliable lower limb kinematic signals can be identified that are independent of walking speed, i.e., self-selected, slow, and fast speeds. Our overarching goal was to identify optimal kinematic signals as the inputs of a reliable gait monitoring system. To quantify the effect of environmental and walking speed conditions for our study group, we compared 3-dimensional patterns of angular velocity and acceleration with IMUs during individual gait cycles. We defined a control metric (baseline) against which similarities across surfaces can be compared to quantify the significance of similarity measures. This procedure uses a Z-score as proposed by GDI to quantify the level of similarity. The ultimate goal of this study is to identify specific candidate raw signals for future real-time deep learning applications.Thirty typically developing adolescents  volunteered as participants in this study see . These pBefore arrival, participants were instructed to wear comfortable, closed-toe walking shoes and attire suitable for light exercise. Before starting data collection, participants were asked to strap the IMUs on the intended locations  with instruction from a researcher, ensuring that the IMUs were in the correct location and did not shift with leg movement. The specific IMU mounting configuration was chosen because it was studied for children with CP , and we Gait data were measured using the Opal IMU system from APDM Wearable Technologies . As per manufacturer recommendations, a standardized IMU orientation was implemented in which the IMUs were placed in the frontal plane where z = AP axis, y = ML axis, and x = SI axis, as shown in TM software using a laptop with an APDM Access Point. The data were captured and managed nearby by a laptop-equipped researcher. Indoors, participants walked on a treadmill , and the same treadmill was used for all trials to minimize variation or calibration issues  to allow for individual participant variability ,45. To dStarting with participants, progressing to the anatomic locations of the IMUs, and culminating with the various walking trials, the data collection process is shown in The order for outdoor walking trials  was also kept consistent and mirrored that of the treadmill trials see . The samOutdoor trials at three different speeds of 3 min each were, on average, 250–300 m (820–984 ft) in length, and no turns or pauses were performed during each trial. Because outdoor walking speed naturally fluctuates and is more difficult to control than during treadmill walking, we measured cadence as a proxy to ensure actual changes in outdoor walking speed were similar to that occurred on the treadmill. The IMUs chosen for data collection in this study have a streaming live data transmission mode, which requires an active, powered wireless access point within the wireless transmission range of the IMUs. Thus, the equipment needed for experimentation  was wired to a portable battery and supported on a custom mount on a researcher’s bicycle B. The reThe three-dimensional (3D) angular velocity (AV) and acceleration (Acc) of each of the four IMUs were used for our analyses. In summary, we analyzed 24 kinematic signals for each individual: four locations (left and right shank and thigh), two sensors (AV and Acc), and three axes per sensor . Data were analyzed using Python algorithms in non-proprietary software. Primary outcome measures of the kinematic signals were distance-based similarity (cosine and Euclidean distance) and Poincare analysis, both of which are curve-based. Distance measures (cosine and Euclidean distance) metrics were used to first rank the kinematic signals across the walking conditions of gait, respectively and then to measure paired comparisons of similarity across walking conditions of gait, respectively. Additionally, five spatiotemporal features (parameter-based outcomes) were used as secondary outcome measures to statistically compare the signals’ pattern between the treadmill and the overground.Each participant’s two treadmill 3 min walking trials at each speed were appended into a single 6 min trial. The use of 2 shorter trials at each speed was employed to mitigate the effects of the treadmill accommodation phenomenon  and, wheRecorded raw data was de-identified, converted into non-proprietary CSV format, and subjected to a Python extraction function for file metadata. The first and last five seconds of data from each file were removed to minimize possible errors from the participant speeding up/slowing down. The conditioning steps were as follows.Upon examining the raw data from the ML Shank AV, a 4th-order low-pass Butterworth filter with a cut-off frequency of 20 Hz was applied to smooth the raw signals. Then, gait cycle initiation was identified as the time point where ML shank AV crossed the zero line from a period of negative value . The primary and secondary outcome measures in this study are listed in Additionally, we statistically compared the level of dissimilarity by paired comparison of the subject-specific bilateral similarity during treadmill walking versus the similarity between treadmill and outdoor walking. Although natural spatiotemporal asymmetry between left and right sides exists , bilaterFinally, the nonlinear Poincare analysis was deployed on all 12 signals to offer a more descriptive way of assessing the similarity between treadmill and outdoor walking by capturing the changes in the variability when moved from treadmill to outdoor walking at different speeds. The Poincare graph of the two most similar and the two most dissimilar signals of the ranked order analysis was depicted to visualize these variabilities. Secondary outcome measures of peak, range, valley, gait cycle duration, and swing/stance ratio were calculated using the same datasets for comparison of treadmill walking to outdoor walking .To measure overall similarity, all data from each participant were aggregated by signal. For these 12 signals, treadmill versus outdoor distance-based similarity measures were calculated (cosine and Euclidean distance). These measures were then ranked for all 12 signals for each of the three walking speeds. Cosine distance is defined as the dot product . We termed this analysis Bilateral Symmetry Dissimilarity Testing (BSDT), where a signal-specific control (similarity between treadmill left and right sides) is compared against a signal-specific intervention , as shown in A novel process is proposed to compare the dissimilarity between the treadmill and outdoor signals statistically using signal-specific kinematics. Healthy participants’ left and right leg kinematics during indoor treadmill walking should be nearly symmetrical and thus will have the highest level of similarity measure realistically possible for that particular individual . TherefoPoincare produces plots of consecutive data points that can be used to quantify measures of short- and long-term variability in a signal .pyHRV library. The standard approach for graphing self-similarity in this recurrence plot was taken by plotting points , , ... An ellipse is then fitted to the resultant scatter plot. The standard deviation along the minor axis of this ellipse (SD1) is a measure of the width of the plot or the short-term variability of the temporal data. SD1 is calculated with the standard deviation of successive differences as follows:SDSD is the standard deviation of successive differences (time domain parameters). The Poincare analysis is performed using a graphically modified version of the long-term variability of the temporal data:SDNN is the standard deviation of the values of the time series. Note that the larger SD1 and SD2, the higher the variability.The standard deviation along the major axis of the ellipse (SD2) is a measure of the variance of the total range of values or the Spatiotemporal parameters (STP) measures were either signal-specific or gait-specific see . This paThe gait-specific parameters, gait cycle duration, and S/S were measured on the ML shank AV, resulting in two values. The three signal-specific parameters, peak height, valley depth, and range, were measured on 12 signals , resulting in 36 signal-specific values.t-test was then used when both datasets being compared were parametrically distributed. In contrast, a Wilcoxon Signed-Ranks test was used if at least one of the compared datasets was nonparametric. The distribution and significance test threshold were defined as less than or equal to 0.05.Each of the 30 treadmills and 30 outdoor trials was analyzed for the mean and standard deviation for each sensor signal. To compare the treadmill and outdoor spatiotemporal parameters, all AP, ML, and SI data streams were first evaluated with parametric testing using the Shapiro–Wilk test. A paired Signal similarity measurements were analyzed using comparative and statistical methods. For comparison, the aggregated data from all subjects were ranked by signal, measuring indoor versus outdoor similarity. For the statistical study, individual data from each subject were analyzed as a paired comparison of a bilateral similarity versus treadmill to outdoor similarity.Similarity measures between indoor treadmill and outdoor walking were statistically compared for all three speeds using paired comparison of each participant’s control group data versus that participant’s intervention group data. The Z-score was also calculated for each signal to provide the level of dissimilarity comparable across all the kinematic signals.Our participants showed an average self-selected walking speed of 1.10 m/s, consistent with previous work that measured self-selected walking speed between 0.75 and 1.67 m/s  12,16,3,316,34. When the aggregate data were ranked by cosine similarity between treadmill and outdoor walking, we observed relative similarity across all 12 combined data streams  . This reFor Euclidean distance similarity, all aggregated signals remained in the same rank as cosine across all speeds—showing a strong correlation between these two similarity measures across all signals and all speeds. As the ideal cosine similarity is 1 and the ideal Euclidean distance similarity is 0, the perfect correlation of the two signals would be a correlation of −1. In such a case, the cosine would be increasing toward 1 while the Euclidean distance would be decreasing to 0. In this study, the correlation between cosine and Euclidean distance was highly correlated, with a very strong correlation of −0.96 for self-selected walking, −0.96 for slow walking, and −0.97 for fast walking speed.In the bilateral symmetry dissimilarity testing, individual participant signal data were analyzed and reported in the same banding as delineated by the aggregate signal data. Signals SI shank Acc and ML shank AV showed high similarity between treadmill and outdoor walking across all speeds in the comparative aggregate rank (by ranking in the High band). In addition, these same two signals of SI shank Acc and ML shank AV showed high similarity across all speeds in the bilateral symmetry dissimilarity testing by showing no significant difference across all speeds, as shown in The ratio of short-term variability (SD1) to long-term variability (SD2) indicators in the ML shank AV  was substantially smaller than the ML shank Acc  in both treadmill and outdoor walking conditions see . A lowerSpatiotemporal parameters that were measured included both signal-specific parameters, peak, range, and valley depth, and gait-specific parameters, gait cycle duration, and swing/stance time ratio across all three speeds . The sigThe statistical testing of the signal-specific parameters showed that all of the signals in the High and the Low band demonstrated a statistically significant difference between treadmill and outdoor walking in at least one of the test speeds (grey boxes). Middle-band signal SI shank AV and Low-band signal SI thigh AV, however, were not significantly different at any of the test speeds across all of the parameters . Slow walking speed showed the lowest level of dissimilarity between parameters compared to the other two walking speeds. The ML thigh AV of the High band was the only signal that showed robustness, measured by non-significant dissimilarity, only at self-selected and slow speeds. Fast walking speed was the most variable, demonstrating significant differences in 10 out of the 12 signals, followed by self-selected speed, eight signals, and slow speed, with only four kinetic signals demonstrating statistically significant differences in any of the parameters. For gait-specific parameters, treadmill and outdoor walking gait cycle durations were significantly different regardless of walking speed. The stance/swing ratio (S/S), however, only showed significant differences between treadmill and outdoor walking for slow walking speed.Defining the optimal kinematic signals, axes, and location(s) for IMU-based gait assessment is challenging. This study aimed to identify these three factors in raw kinematic data signals for use in real-time machine learning. We assessed the differences between treadmill versus outdoor overground walking at three different speeds to identify the optimal kinematic signals for IMU-based gait monitoring systems. A standardized IMU orientation was implemented in which the IMUs were placed in the frontal plane where z = AP axis, y = ML axis, and x = SI axis. Statistically, we identified which raw kinematic signals showed the highest similarity, i.e., reliability when changing walking conditions and speed. Based on our analysis, ML shank AV and SI shank Acc showed the highest similarity banding and the least dissimilarity in paired comparison tests of similarity for treadmill versus outdoor walking across the three walking speeds. Based on these criteria, the above-mentioned kinematic signals were the most robust for gait monitoring applications across the varied walking conditions for our defined sensor placement. When using the aggregated data of all participants, the cosine similarity measure shows distinct high/middle/low banding with ML shank AV and SI Shank Acc, showing amongst the highest similarity scores for treadmill versus outdoor walking. For statistical analysis, a novel test assessing dissimilarity, bilateral symmetry dissimilarity testing (BSDT), showed that the outdoor ML shank AV and SI shank Acc, the aforementioned signals with the highest similarity between treadmill and outdoor walking, were not statistically dissimilar to their overground versions. Among these two signals, SI shank Acc demonstrated the highest level of reliability, being the least variable signal in both BSDT and Poincare analysis while demonstrating robustness in spatiotemporal analysis at self-selected and fast walking speeds.Past work on IMU-based gait monitoring systems included multiple processed kinematic signals from multiple sensors and, thus, came at a high computational cost. In a minimalistic approach, we sought to identify the optimal raw kinematic signals for gait monitoring systems to lower computational costs and increase adoption. To identify these signals, different methods were proposed. Sherifi, Renani, et al. utilized deep learning to predict spatiotemporal gait parameters in patients with osteoarthritis after total knee arthroplasty  and, simOur work shows that the ML shank AV and the SI shank Acc signals have the highest level of robustness when walking speed and walking condition change. Previous research has shown that combined gyroscope and accelerometer data gives higher accuracy in gait evaluation than accelerometer data alone . Shank aThere is currently no universally accepted gait similarity measure. One early technique of continuous gait pattern analysis (which predates machine learning) was the Gait Deviation Index (GDI) introduced by Schwartz and Rozumalski . GDI wasIn our bilateral symmetry dissimilarity testing, our control condition consisted of left-to-right similarity during treadmill walking as this side-to-side similarity has shown less variability in comparison to treadmill versus overground similarity  and can BSDT showed no significant difference between our walking conditions in these two signals; however, some significant differences were observed in the less robust signals. Poincare analysis also showed fewer significant differences in the robust signals within the High band when compared to the less robust signals. The STP analysis, however, was less discerning across the signals and did not show a pattern. The decreased variability demonstrated in our Poincare and BSDT analysis, when compared with our parameter-based spatiotemporal analysis, might indicate the strength of curve-based analysis over the parameter-based analysis. Curve-based similarity testing, such as our proposed method BSDT, consists of continuous gait-pattern testing inclusive of the entire continuum of the biomechanical data in the gait curve as opposed to the parameter-based analysis, which utilizes representative discreet features of the kinematic signals. Thus, curve-based analysis might be more versatile in capturing the real differences in the comparing signals and, therefore, is an evolving field within gait analysis. In prior literature, gait comparisons between various conditions are mostly based upon discrete spatiotemporal parameters; this type of parameter-based analysis demonstrated significant between gaits in various walking conditions ,37, as sSome previous works noted that the treadmill gait was qualitatively and quantitatively similar to overground walking . Other wOur participant sample was composed of 30 healthy adolescents, obtained via convenience sampling, and thus limits the generalizability of our results beyond this population. In contrast to past studies in adolescents, which compare either self-selected walking speed treadmill protocols or outdoor walking, our study sample reflects a relatively large sample size. As with all raw data gait research, inter-participant variability and gait perturbations are significant factors that may limit adequate analysis due to limited usable data ,12. IMUsTraditional lab gait analysis is well standardized and validated at this point, and the resulting data are comparable across labs regardless of the equipment . The resBy leveraging widely accepted side-to-side similarity in typical gait, our proposed dissimilarity testing, BSDT, can simply provide subject and signal-specific control values that indicate the magnitude of similarity in different conditions for any curve-based similarity measure. The subject-specificity holds only if the individual has a typical symmetrical gait. In the case of pathological gait, however, one may choose to use signal-specific bilateral symmetry from a normative dataset of typical individuals to conduct a pairwise statistical comparison. A recent systematic review showed ample published work on young adults comparing treadmill walking to indoor overground walking . HoweverSimilarity measure testing is not new and dates to square error clustering in the 1960s. However, it is now being revisited as a more relevant topic in machine learning, image processing, and pattern recognition. Due to the high dimensional nature of gait, however, more deliberate and considerate applications of similarity are needed to study gait. It is possible that our use of well-defined statistical similarity measures may be shown to incompletely quantify differences between high dimensional data. As mentioned above, other similarity measures were used for gait data, such as the Coefficient of Multiple Determinations, Statistical Parameter Mapping, and the Linear Fit Method ,62, and Together, gait data collection, gait analysis, and machine learning enable gait monitoring systems for diagnostics, therapeutics, and assistive technologies. While many previous works have examined parameter-based analysis such as spatiotemporal comparison to quantify gait similarity, we used curve-based similarity analysis to identify reliable kinematic signals when participants change walking conditions and speed. We identified that IMUs aligned in the frontal plane and positioned on the shank were more ideal than IMUs aligned in the frontal plane but located on the thigh. Medial–lateral angular velocity (ML shank AV) and superior–inferior acceleration (SI shank Acc) were the most robust kinematic signals when participants moved from treadmill to outdoor overground walking and at three different walking speeds. These robust raw IMU signals can guide future machine learning-based models for monitoring gait in the face of varying walking conditions while optimizing the processing burden and, thereby, the adaptability of such systems.


The field of regenerative medicine, encompassing several disciplines including stem cell biology and tissue engineering, continues to advance with the accumulating research on cell manipulation technologies, gene therapy and new materials. Recent progress in preclinical and clinical studies may transcend the boundaries of regenerative medicine from laboratory research towards clinical reality. However, for the ultimate goal to construct bioengineered transplantable organs, a number of issues still need to be addressed. In particular, engineering of elaborate tissues and organs requires a fine combination of different relevant aspects; not only the repopulation of multiple cell phenotypes in an appropriate distribution but also the adjustment of the host environmental factors such as vascularisation, innervation and immunomodulation. The aim of this review article is to provide an overview of the recent discoveries and development in stem cells and tissue engineering, which are inseparably interconnected. The current status of research on tissue stem cells and bioengineering, and the possibilities for application in specific organs relevant to paediatric surgery have been specifically focused and outlined. Regenerative medicine encompasses numerous areas of biology and engineering, including stem cell biology, biomaterial engineering and gene therapy . The ultThis review will first briefly overview technological platforms available for regenerative medicine both after birth and prenatally . Tissue Regenerative medicine aimed to overcome three overarching themes: (1) to facilitate the repair of damaged tissues, (2) to replace damaged cells with healthy functional cells, and (3) to replace the damaged organ system with engineered tissues. There have been many technological advancements to this aim, including tissue engineering, stem cells and organoid biology, and gene editing. These advancements have allowed overcome significant technical hurdles and led to a more profound knowledge of how resident cells communicate with their microenvironment, issues of immunogenicity, and the role of stem or progenitor cells in tissue regeneration.The main components of successful bioengineered tissues include cell sources, scaffolds, and biomolecules Fig. . AlthougRecently, in vitro human organ models with physiological functions similar to native organs have become feasible through engineering research, such as micro-physiological systems represented by organ-on-chip. Among in vitro models, organoid-based platforms have a wide range of applications, from basic research in embryology and regenerative medicine to disease modeling and drug discovery research. Furthermore, the application of organoids to regenerative medicine using organoids for transplantation is also beginning to be explored.Organoids have three-dimensional structural characteristics similar to those of organs in vivo. Since organoids are composed of multiple differentiated cell types, they are expected to have physiological responses similar to native tissues compared to the “classic” cell culture . OrganoiAn ultimate application of organoids in tissue engineering is the regeneration of deficient tissues through organoid transplantation. Improved survival of liver failure models through liver organoid transplantation and regeneration of intestinal epithelium through intestinal organoid transplantation have been reported –23. OrgaAirway systems encounter two main fields of interests with substantial unmet clinical needs: conduit system and parenchymal disease. Severe forms of congenital tracheal stenosis/agenesis, laryngotracheal clefts, trauma and aggressive forms of cancer may require the replacement of main airways . In paedThe human respiratory system is composed of a highly complex and hierarchical structure from proximal conducting region to distal alveolar region with numerous different types of cells along , varyingIn early development the digestive and respiratory systems share a common precursor from the anterior foregut endoderm (marked by the expression of the transcription factor Nkx2.1). These progenitors are later specified by transcription factors Sox2 and Sox9 in the proximal and distal regions respectively. Despite the mesenchymal instructive paracrine signals are crucial to regulate proliferation and maturation of endodermal progenitors, there is a paucity of evidence concerning the airways mesodermal-derived progenitors, which are nevertheless thought to share a common origin with cardiopulmonary mesoderm progenitors .In the mature proximal conducting region of the human lung, TRP63 + KRT5 + basal cells have been identified as a progenitor cell population . HoweverIn the alveolar region, alveolar type 2 (AT2) surfactant-producing cells are widely recognised as the best progenitor candidate –36. In aAs exogenous stem cell sources promising candidates are bone marrow-derived stem cells , ESCs 3–41, humaMost evidence on respiratory stem cell biology had been using 2D cell culture models, clearly too simplistic to reflect the complex in vivo interconnections and microarchitectures. Development of lung organoids has been reported from the different epithelial cell populations, including basal cells, club cells and AT2 cells, in addition to hPSCs . A varieAir–liquid interface (ALI) culture systems provide cultured cells with a more physiological environment and allow better differentiation for induced pluripotent stem cells . Since tThe upper airway has been thought to be relatively amenable to bioengineering due to its simple structure and function, and has already been engineered and translated clinically on a compassionate basis , 56. MosWhole lung engineering was obtained in rodent lungs by repopulating decellularised lung ECM with epithelial and endothelial cells and allowed gas exchange –62. MoreIn paediatrics, many conditions may require the presence of a complete or partial substitute of the oesophagus, including long-gap oesophageal atresia (LGOA), caustic ingestion and traumatic injuries. Despite great advances in clinical care, reconstruction of oesophageal continuity is still associated with substantial morbidity and severe consequences on quality of life .Research on tissue engineering of oesophagus was preceded by advancement of biomaterials, including decellularised, natural derived and synthetic materials. The successful in vivo implantation of these materials, using the small patch implantation model, has demonstrated their biocompatibility . HoweverWhile ventral foregut endoderm expresses transcription factor Nkx2.1 giving rise to the respiratory system, transcription factor Sox2 and Pdx1 are vital signalling pathway molecules for specification towards oesophagus, stomach and pancreas .Epithelial cells: The continuous turnover of the epithelial layer of the oesophagus relies on the so-called basal layer. These cells mature flattening into a stratified squamous epithelium consisting of 20–30 layers [0 layers , 70. Rec0 layers . Current0 layers  and CD340 layers  subpopul0 layers –76. More0 layers –79. Furt0 layers , 81.Muscle cells: The submucosa and muscularis externa comprise mesenchymal elements of oesophageal wall; nerve fibres and ganglion cells are responsible for the generation of coordinated peristalsis [istalsis , 83. Howistalsis , 85. Howistalsis . Alternaistalsis –89.Much interest in tissue engineering of the oesophagus has focused on using acellular scaffolds derived from animal or human tissues and with or without cell-seeding. In particular, difficulty mimicking the complex native structure using synthetic materials whilst satisfying all the crucial features required for transplantable tissue constructs has provoked tissue engineering research to shift towards decellularised scaffolds , 91. BadGastrectomy is commonly performed in adults and children for a variety of conditions, ranging from the need of an oesophageal substitute as in LGOA or caustic ingestion  till gasEpithelial cells: Organogenesis of the stomach originates from a highly coordinated interaction between foregut endoderm and splanchnic mesoderm due to interplay of various factors and signals, such as HHEX, SOX2, retinoic acid, FGF and Wnt pathways and gradients of BMP [s of BMP .The adult stomach is lined with a glandular epithelium in which self-renewal is driven by gastric stem cells. However, their exact location among the glandular functional unit is not clear. Using incorporation of labelled nucleotides in animal models, historical studies suggested that renewal of antral gastric cells was driven by one or a few cells localised in the isthmus . More reWhen combined with Lgr5 labelling, AXIN2 + LGR5 + and AXIN2 + LGR5- subpopulations located at the base and lower isthmus of the gastric glands were identified. Importantly, the two cell types can replenish each other, being alternatively activated and silenced in case of specific depletion . MoreoveFinally, in 2014 McCracken et al. firstly described the de novo generation of gastric mucosa from human iPSCs by temporal manipulation of the abovementioned signalling pathway  and subsSmooth muscle cells: The smooth muscle of the stomach is thicker than that of other digestive organs, but the mechanisms of stomach-specific myogenesis from a pool of progenitors are not fully understood [derstood . Moreovederstood . For exaderstood .Tissue engineering of the stomach for translational medicine has two main aims: regeneration of epithelial lineage itself and physiological reinforcement of gastric wall . In the In addition to the reinforcement of the gastric wall defect, improvements in the functional regeneration of the mucosa have been seen once the scaffold has been loaded with organoids. Vacanti's group seeded organoids of a mesenchymal cores surrounded by epithelia onto a PGA tubular construct and then implanted both small (2-step replacement of native stomach in the murine model ) and larVarious paediatric gastrointestinal diseases, including necrotising enterocolitis, gastroschisis, midgut malrotation and volvulus, intestinal atresia, and inflammatory bowel diseases, may result in short bowel syndrome (SBS), in which limited length of the intestine cannot perform the required functions such as absorption and barrier function, commonly caused . PatientThe intestine is a highly complex organ with several essential functions; nutrient absorption, host immunity, and mucin secretion . The intOrganogenesis and maturation of the intestine were recently reviewed in , emphasiGenerating functional intestinal epithelium is crucial to restoring a patient's enteral autonomy. Barker et al. first identified a widely accepted intestinal stem cell marker, Leucine-rich repeat-containing G-protein coupled receptor 5 (Lgr5), expressed in crypt base columnar cells, and demonstrated that a single Lgr5 + cell has the capacity to regenerate crypt-villus structures , 132. MeThe mesenchymal and smooth muscle components of the intestine represent another challenge for intestinal regeneration, as they have a crucial role in maintaining the epithelial niche. Recently, human iPSC-derived intestinal organoids, in combination with human-PSC-derived neural crest cells, were reported to generate a smooth muscle layer that is positive for the smooth muscle marker desmin and can functionally respond to electrical and pharmacological stimuli .Large-scale vascularisation capable of enabling successful surgical anastomosis into isolated engineered intestinal segments remains a challenge. Kitano et al. successfully repopulated human endothelial cells and human iPSCs-derived intestinal progenitors on a decellularised intestinal scaffold in a rat model. They restored perfusability and patency following in vivo isolated transplantation, as well as in ex vivo perfusion testing .To create a sizable intestinal equivalent that can be successfully anastomosed to the native intestine, tissue engineering of the intestine has attempted to bring some or all cellular components and systems together into one platform. Given the complex structure and highly organised function of the intestine, the creation of synthetic biomaterials which recapitulate intestinal ultrastructure, such as the crypt-villus structure and stem cell niche, is challenging. Decellularised scaffolds of the intestine have attracted attention with advantages over synthetic materials. Our group has established a detergent-based decellularisation protocol that retains essential ECM proteins, angiogenic properties, and mechanical strength . Recent Neurological dysfunction within the enteric nervous system (ENS) is responsible for a wide range of gastrointestinal motility disorders, such as oesophageal atresia , oesophaRecently, substantial progress has been made in ENS research through the identification and isolation of enteric neural stem cells (ENSCs): multipotent cells which can be isolated from human GI tracts. McCann et al. reported the restoration of the ENS and colonic motility following the implantation of ENSCs into a mouse model of human enteric neuropathy , which highlighted the significant possibility of clinical ENSC therapy . PSCs arThe intense interest in understanding human pancreas development is related to the treatment of diabetes, a growing health problem worldwide. Type 2 diabetes, the most prevalent form of this disorder, is typically characterised by a progressive failure of β-cells to meet the body’s demands for insulin; in contrast, β-cells are lost by autoimmune destruction in type 1 diabetes mellitus. Both mechanisms leading to diabetes are related to genome sequence variants in adult β-cells  and duriHuman pancreas formation starts with dorsal bud formation deriving from endoderm, and it continues with the appearance of the ventral bud. After the posterior migration, the ventral bud fuses with the dorsal pancreatic bud, giving rise to most of the pancreas. Although knowledge of events in human pancreas organogenesis is limited, Jennings et al. recently reported that contact between the dorsal pancreatic endoderm and the notochord leads to the exclusion of sonic hedgehog (SHH) expression from this endodermal region . As a rePancreatic progenitor cells arise from a cluster of cells originating from the developing foregut. These clusters have been characterised to show multipotent properties  and the Since the first experiments pursuing pancreatic differentiation , there h® being the current standard practice. Because synthetic materials are related to various long-term complications, recent studies described using naturally derived materials, such as small intestine submucosa (SIS) and acellular dermis, with a failure of regeneration and a resultant re-herniation [Several different approaches have been attempted to repair large defect in congenital diaphragmatic hernia (CDH), including synthetic mesh materials, autologous thoracic or abdominal muscle flap, with PTFE/Gore-texrniation , 172. A Skeletal muscle retains high regenerative capacity upon mechanical damage or diseases. This regenerative ability is mediated by a resident stem cell population for skeletal muscle, named muscle satellite cell (SC), and identified by the transcription factor Pax7 , 174. ThSCs and myoblasts are physiological skeletal muscle precursors, so it is rational that most studies on muscle cell therapy have been performed on these cell populations. Although investigations on SCs have demonstrated their proliferation and multipotent differentiation capabilities, utilising SCs for human cell therapy and bioengineered skeletal muscle has faced severe challenges and limitations . Early-pNotably, in the setting of congenital disorders, SCs and myoblasts are exhausted, hindering efficient cell isolation and expansion in vitro. These drawbacks of SCs and myoblasts have led to the identification of alternative stem cell candidates for skeletal muscle regeneration, including mesangioblasts/pericytes , CD133-pRegarding the microenvironment of stem cell niche, the importance of mechanical rigidity of substrate used during in vitro culture has been noted to preserve satellite cell capacity. Appropriate elasticity or geometric micropatterning of a substrate where cells cultured on enhanced survival, self-renewal, and engraftment abilities of satellite cells in vivo , 186, prIn the setting of congenital muscular defects such as CDH or abdominal wall defects, a purely cell-based (scaffold-free) strategy is not applicable due to the massive skeletal muscle defects seen in many cases, which overwhelms the inherent regenerative potential. A bioengineered construct comprising exogenous myogenic stem/progenitor cells combined with scaffold biomaterials would be an attractive option for reconstructing these large defects. Growing evidence has suggested appropriate biomaterials can enhance the potential of stem/progenitor cells (see comprehensive review in ).Most of these biomaterials are broadly divided into synthetic and naturally derived materials. Among various synthetic biodegradable materials, polycaprolactone (PCL), PGA, and poly-lactide-co-glycolic acid (PLGA) have been the most frequently tested materials in vitro and in vivo animal model, with relatively disappointing outcomes due to a pro-inflammatory response of the host immune system against these materials –192. In Researchers have investigated an acellular approach, where only decellularised scaffold was used without cells. Sicari and Badylak et al. utilised an acellular scaffold derived from a porcine small intestinal submucosa-ECM and urinary bladder matrix for rodent volumetric muscle loss (VML) model and human patients. They showed constructive regeneration of skeletal muscle tissue , 194. PiIn contrast, a cell-based tissue construct combining stem/progenitor cells and acellular ECM could be a better therapeutic solution, especially when the recipient's muscle is severely compromised and a scarcity of muscle progenitor pool , 198. ThIn the last decade, regenerative medicine has expanded dramatically, combining numerous relevant fields and technologies, including stem cell biology, biomaterial engineering, immunology, and genetics, indicating the interdisciplinary nature of this emerging discipline. Many novel therapeutic strategies have been proposed to treat adult and paediatric pathologies and realise finely tuned transplantable "artificial" organs. However, regarding applying this innovative paradigm to the paediatric surgical clinical practice, significant practical and ethical limitations still need to be addressed, including optimisation, scalability, and manufacturing standardisation .Recent breakthroughs in this field might provide various alternative platforms and therapeutic options. Since 2017, researchers have developed an artificial placenta system comprising an extracorporeal circuit, oxygenator, and fluid-filled womb-like environment, and they proved the concept using premature animal models . AnotherThe last decade has witnessed remarkable advance in both the basic knowledge and technologies in stem cell biology and bioengineering, which has made it possible to create a variety of engineered tissues and organs with the clinical translational potential. Due to the complexity of reconstruction in paediatrics, many paediatric surgeons contributed to the development of the field. In 1954 Dr Joe Murray, a paediatric plastic surgeon from Children's Hospital Boston, who subsequently received the Nobel prize in 1990, and his team, performed the first successful kidney transplant where the donor and the recipient were two identical twins . Dr JudaDespite the enormous progress, the field of regenerative medicine is still in its relative infancy phase: however, with present momentum on research progress and interdisciplinary collaboration, it is reasonable to expect that shortly, regenerative medicine will lead to realising unprecedented surgical therapeutic strategies where impaired organs are replaced by novel biological substitutes.


Taenia solium, hence requiring prompt, aggressive intervention to alleviate the increased intracranial pressure to prevent imminent lethal complications. Ventricular neurocysticercosis can involve any brain ventricle but with a paramount preference for the fourth ventricle, causing non-communicating hydrocephalus and symmetric ventriculomegaly. However, in this clinical report, we present an uncommon case of trapped (locked-in) lateral ventricle caused by an isolated cysticercus trapped at the ipsilateral foramen of Monro, which is an atypical location for neurocysticercosis, adding more challenges to diagnosis and during the process of surgical extraction. We additionally provide a comprehensive, evidence-based review of the clinical course and management options relevant to the entity of ventricular neurocysticercosis, besides recent relevant clinical updates.Human neurocysticercosis is one of the most prevalent parasitic infestations of the central nervous system. It is considered the most frequent underlying etiology of acquired epilepsy in endemic areas in Central and South America, East Europe, Africa, and Asia, with over 50 million people affected globally. Ventricular involvement is a severe form of neurocysticercosis commonly manifests as arachnoiditis, raised intracranial pressure, or hydrocephalus, secondary to CSF flow obstruction of the ventricular system by cysts of  •Neurocysticercosis (NCC) is the most prevalent CNS parasitic infestation globally.•Ventricular NCC (vNCC) typically presents as hydrocephalus.•An isolated (locked-in) ventricle is an uncommon presentation of vNCC.•3D CISS MR imaging is the most sensitive and specific modality in detecting vNCC.•Endoscope-assisted extraction is now the most widely preferred method for vNCC. Taenia solium tapeworm (cestode), which develops after ingesting eggs from the feces of a tapeworm carrier  or eating meat from an infected intermediate host As the name suggests, cysticercosis is a parasitic infestation caused by the larval stage of A 42-year-old man presented to the emergency department after waking up with a severe generalized headache and profuse vomiting. He reported a 2-week history of progressive headaches and blurry vision, partially controlled with OTC analgesics. On neurologic examination, he had preserved motor, sensory, and autonomic functions with unremarkable neurologic reflexes throughout. However, his clinical manifestations were suggestive of increased intracranial pressure (ICP); therefore, it was prudent to proceed with head imaging before any laboratory investigations or further clinical examinations. A CT scan of the head demonstrated an expanded lateral ventricle on the right side without any significant mass effect, consistent with an isolated, right-sided non-communicating hydrocephalus. However, no identifiable cause was evident. Therefore, we scheduled the patient for urgent MR imaging, which revealed a well-delineated, thin-walled, non-enhancing cystic lesion with an eccentric mural nodule in the right-sided lateral ventricle, causing outflow obstruction through the ipsilateral interventricular foramen of Monro . AnalysiGiven the data obtained thus far, we made a preliminary diagnosis of neurocysticercosis-induced hydrocephalus. The patient was then taken to the OR, where an endoscopic transventricular approach was performed to extract the cystic lesion. Concurrently, an external ventricular drain (EVD) was placed on the ipsilateral side, which instantly alleviated the high ICP manifestations. The cyst was subsequently transferred to the histopathology department. Upon opening the cyst by cutting its membrane, an elongated whitish structure, in continuity with a certain point on the inner surface of the membrane, was observed, consistent with the scolex  of the tapeworm. Histopathological studies on the excised cysticercus demonstrated a nonviable, almost necrotic, vacuolated scolex with a still-viable cystic membrane . Based oT. solium after ingesting raw or undercooked meat-containing cysticerci from infected pigs, which act as intermediate hosts. However, humans might act as intermediate hosts if the infection has occurred through the ingestion of eggs rather than cysticerci via a fecal-oral route. Within the intermediate host, the egg hatches and transforms into an oncosphere, which is the larval form of T. solium , given its most dependent location, followed by the third ventricle (∼27%). The lateral ventricle and Sylvian aqueduct accounted for only 11% and 9%, respectively Ventricular involvement accounts for approximately 20% of all intracranial neurocysticercosis. Oncospheres, by the general circulation, reach the ventricles via the choroid plexus, where they transform into cysticerci. Apuzzo et al. reported that a combination of elevated lactate, choline, alanine, and succinate levels, on top of suppressed creatine and NAA levels to be characteristic of parenchymal lesions Brain imaging plays a pivotal role in neurocysticercosis diagnosis. Due to the readily availability of CT scans in most healthcare centers, it is widely used as the initial diagnostic modality. CT scans have shown higher sensitivity and specificity for parenchymal neurocysticercosis, compared to ventricular lesions, which are hard to visualize via brain CT because they appear as thin-walled lesions, exhibiting isodense signal changes similar to the CSF T. solium-related antigens in serum and CSF. However, available data demonstrate that standard enzyme-linked immunosorbent assays are neither sensitive nor specific for neurocysticercosis diagnosis et al., the authors demonstrated that the presence of a 15 kDa reactive band on EITB is highly sensitive and specific for the diagnosis of neurocysticercosis, although the presence of a 35 kDa band might be associated with infection by multiple cysticercus lesions Several serological tests are currently available to diagnose neurocysticercosis by detecting antibodies to et al., the authors reported that albendazole at 30 mg/kg/day plus dexamethasone for eight days was both safe and effective in the clearance of intraventricular and subarachnoid cysts Neurocysticercosis can be treated medically with cysticidal agents and corticosteroids or surgically to remove the cyst(s). Praziquantel and albendazole are the commonly used cysticidal drugs that have demonstrated high efficacy against all forms of neurocysticercosis. However, they should be preceded by steroid administration, especially in patients with the ventricular and subarachnoid subtypes, to reduce the resultant inflammation from the parasitic degradation and the subsequent risk of shunt obstruction Neurocysticercosis generally possesses a favorable general prognosis after initiating treatment. However, parenchymal involvement might lead to epilepsy and recurrent seizures, while subarachnoid and ventricular subtypes might lead to permanent hydrocephalus, intracranial nerve entrapment leading to cranial nerves palsy, or cerebrovascular complications such as ischemic infarction, transient ischemic attacks, and brain hemorrhages •Neurocysticercosis is the most prevalent parasitic infestation of the CNS, with approximately 50 million people affected globally.•It develops after ingesting eggs from the feces of a tapeworm carrier  or eating meat from an infected intermediate host.•Seizures are the most commonly observed complication in cases with brain parenchymal involvement.•Hydrocephalus, symmetric ventriculomegaly, and increased ICP are the most common presentation of ventricular neurocysticercosis, while an isolated ventricle is uncommon.•The 3D constructive interference in steady-state MR imaging modality is more sensitive and specific than routine MRI sequences in detecting intraventricular cysticerci.•FLAIR MR imaging modality, preceded by a five-minute 100% oxygen inhalation, provides a feasible, inexpensive method for detecting cisternal and subarachnoid cysticerci; however, further modifications are still required to enable the visualization of the intraventricular cysts.•EITB is considered the current serological test of choice for neurocysticercosis.•A VP shunt is warranted in ventricular neurocysticercosis if associated with increased ICP or if ependymitis is suspected.•Transventricular endoscopic extraction is now the most widely preferred method for ventricular neurocysticercosis.•Cerebrovascular complications of neurocysticercosis are more common than expected and typically associated with the subarachnoid and cisternal subtypes.The ethics committee at Al-Azhar University hospitals officially approved all the performed procedures and the followed guidelines under the reference number of HSZ-22–001446.M.M. was responsible for the conception of the work, data collection, drafting the article, critical revisions, and obtaining approval of the final version of the manuscript. M.T. and Z.A. contributed by drafting the article, and critical revisions. All authors were involved in direct patient care.The patient provided a written consent to publish the case and related data.None declared.None.


People with rheumatic diseases are frequent, long-term attenders of health-care services. Their care experiences are central to improving services. The aim of this study was to explore real-world experiences and priorities of people attending outpatient rheumatology care and those of health-care professionals (HCPs) providing care.n = 16) of two tertiary teaching hospitals and HCPs . Participants explored priorities when attending outpatient services, real experiences and aspirations for improving future care. Transcripts were coded using inductive and deductive thematic analysis.This qualitative study consisted of five semi-structured focus groups. Participants included rheumatology outpatients (Seven key themes were identified: smooth flow of technical processes, care coordination, individualized care, information sharing, clinical excellence, patient empowerment and comprehensive care. The findings were aligned conceptually with quality standards in Australia and worldwide. Different sub-themes and prioritization of concerns emerged from patient and HCP subgroups. Highly prioritized themes for patients pertained to processes and technical aspects of care. HCPs focused on themes relating to non-technical aspects of service provision: information sharing, individualization of care, patient advocacy and empowerment.This study captured valuable insights into the current experience of outpatient rheumatology care from the perspective of patients and HCPs. It informs a collective understanding of differing and shared priorities, positives of current care and areas requiring change. Themes derived from the study data can be conceptualized in terms of the process, content and impact of care. Such domains can be measured longitudinally by routine implementation of validated patient-reported experience measures in rheumatology. Key messagesResearch prioritizing the experiences of patients has an important place, alongside quality care indicator and outcome measure data, and can drive change in how rheumatology care is delivered.Our study suggests that rheumatology patients and health-care professionals place high importance on receiving and providing care that is individualized and patient centred.Logistics and care processes can pose barriers to the provision of high-quality care and have a negative impact on patients.There is great potential to capture experience-related data from patients routinely and use this directly to reduce such barriers and improve patient services.Health-care systems continue to evolve as the end of the first quarter of the 21st century approaches. Medicine and health care are no longer delivered in a traditionally didactic way, in which patients assume a passive, receiving role [Leading bodies, including the World Health Organization (WHO), recognize that people-centred health services can deliver more efficient, cost-effective and equitable care by consciously seeking the perspectives of individuals and communities when designing interventions . GloballA key foundation underpinning partnership in direct care provision is information gathering about care experiences, coupled with interventions to promote shared responsibility . To thisThe aims of this study were as follows: to capture the current experiences of care in outpatient rheumatology services, from both patient and health-care professional (HCP) perspectives; to explore patient views on what is considered ideal patient-centred care; to explore HCP views on what constitutes high quality delivery of patient-centred care; and to explore similarities and differences of opinion between cohorts.This non-interventional study was designed in accordance with published guidance on qualitative methodology , 16, usiOur patient research partner contributed to qualitative analysis and manuscript preparation. Study findings will be disseminated via Arthritis Australia .a priori targets of biological sex, age, cultural background, disease diagnosis and duration. Groups were assembled with representation of demographic factors in each. Eligibility criteria included age >18 years, ability to communicate in English, and attendance at outpatient clinics within 12 months at either recruitment site. Patient focus groups were conducted at both hospital sites, in November and December 2021. Transport vouchers were provided.Individuals attending outpatient rheumatology clinics at two Australian tertiary hospitals  were invited to participate in semi-structured focus groups . PotentiTwo focus groups comprising rheumatology HCPs were conducted, including medical, specialty rheumatology nursing, pharmacy or physiotherapy providers within public or private rheumatology clinics. Invitations to participate were sent by email to rheumatology staffing groups across the recruitment sites and to specialist rheumatologists working in the private sector. HCP focus groups were conducted in December 2021 by virtual format owing to coronavirus disease 2019 restrictions.The study was approved by the Central Adelaide Local Health Network Human Ethics Committee (reference 13846).Written informed consent was obtained, including consent for audio recording and transcription. Patient focus groups were facilitated by an experienced qualitative researcher (R.M.) and observed by an additional investigator (M.J.B.). HCP focus groups were facilitated by two investigators (M.J.B. and C.L.H. or R.J.B.). Participants in all groups were invited to discuss perspectives on their care priorities when attending outpatient services (patient groups) and providing care (HCP groups). This included personal experiences of clinic attendance, opinions on patient-centred care and aspirations for future improvement. Groups followed a semi-structured format, with standardized prompt questions developed by the authors  to promoFocus groups were audio-recorded, transcribed verbatim using a professional transcription service, and imported for coding into NVivo v.12 software .Focus group transcripts were analysed using both inductive and deductive approaches, using six phases of thematic analysis as described in published texts on qualitative methodology , 20. Open = 16 in groups of n = 5, n = 5 and n = 6) and two HCP groups . Focus group sizes followed qualitative research guidance on recommended sample size and dynamics [n = 4; HCP: n = 1) or not interested in study objectives (patient n = 7).Forty-three patients and 15 clinicians were invited to participate. Five semi-structured focus groups were conducted with 30 participants: three patient groups .Patient participant characteristics are summarized in n = 8), rheumatology trainees/registrars (n = 2), physiotherapy (n = 2), specialty nursing (n = 1) and pharmacy (n = 1). Sixty-four per cent of participants were female. The median (interquartile range) time in practice was 9.5 (15) years. Eight participants worked solely in public rheumatology clinics, two participants worked in both public and private clinics, and four worked solely in private clinics. One participant reported English as their second language. The predominant cultural background reported was Australian (n = 12); others included Sri Lankan (n = 1) and Australian Chinese (n = 1).Represented in the sample were specialist rheumatologists , in addition to the desire for continued learning: the ‘expect(ation) to know more (about) my condition’ . This conceptual emphasis was reflected by the HCP cohort describing many ways in which information sharing can be adapted and individualized by using illustrative patient results, pictorial resources and multilingual material. That these themes are familiar at both a macroscopic and direct-care level suggest that they remain as authentically relevant to the individuals in the present sample as they are to systems and governance structures on a much larger scale , 31.Overall, we have identified that patient and HCP cohorts are concerned with the same issues, although prioritization is different between groups. Several disparities were noteworthy; the foremost of which was a discord in appreciation of the impact on logistics on the overall care experience. Issues of waiting time and appointment inflexibility were demonstrated as universal patient concerns, and their negative impact on care was grossly evident in patient cohort data. Patients indicated that logistics and processes can significantly impede provision of high-quality clinical care; clinicians cited awareness of such factors, although less cogniscence of their scale, a mismatch with potential to disconnect the entire patient–clinician interaction. Patients reported sentiments such as ‘waiting is what you do’ , yet one has ‘more important things to do’ , views demonstrating the negative impact of logistics on sentiments such as feeling respected or engaged in partnership. HCPs might well be aware of system-level inefficiencies and logistical frustrations, but these are rarely visible to the individual patient experiencing real-time delays or cancellations. Research in other contexts has demonstrated the importance of proactively informing patients of delays in order to mitigate the negative psychological impact of long outpatient waiting times . To thisAlso notable for the contrast between patient and HCP cohorts within this study was the differing emphasis placed on non-technical aspects of care; in particular, the expression and exploration of themes such as empowerment and comprehensive care. Among the patient cohort, empowerment was largely explored in terms of being involved in decision-making and having sufficient time to have concerns addressed. HCPs described many different manifestations of empowerment, such as the importance of facilitating patient self-advocacy, acknowledging patient ownership of health information and adjusting care to account for individual health literacy. This theme was explored in detail by HCPs and was given high priority in descriptions of high-quality care but was not as strongly evident in patient focus group data. Likewise, the theme of comprehensive care revealed a divide between patient and HCP cohorts. For patients, this theme encompassed preferences for greater access to formal support groups, self-management tools and culturally sensitive resources, including interpreting services. In contrast, HCPs focused on the importance of factors such as involving the allied health and multi-disciplinary team and attention to inter-visit care. HCPs explored in depth the need to provide care that is both patient centred and individualized, including seeing patients as more than a diagnosis, understanding biopsychosocial context and seeking creative ways to engage and partner. All of this commentary demonstrated optimism and aspiration in how patient-centred care can be delivered. Despite this, a disparity between cohorts in the terms and language used to describe these phenomena suggests that patients are not yet sufficiently enabled to seek out such important non-technical elements of care.When describing ‘patient-centred care’, patients cited the way an encounter made them feel: heard, respected or seen, as examples. Meanwhile, HCPs described in more practical, literal terms the elements of routine practice they believed to represent individualization of care: being unhurried, involving support persons and facilitating individual treatment decisions based on tailored information and advice. Clinicians readily cited multiple examples of patient-centred care at junctions within a consultation; yet signposting these to patients in real time might not be one of them, as evident in the finding that patients did not describe this experience. Bridging this divide will require clinicians as a profession to incorporate increased and regular patient feedback on non-technical care domains, review blind spots in care provision and adapt practice accordingly.This study was conducted in a metropolitan setting, thus limiting generalizability of findings to the rural and remote patient experience. Also, although this study did include HCPs from the private setting, patients attending private rheumatology clinics were not represented. Within the dual-sector model of Australian health care, the public system provides free access to hospital health-care services, whereas self-funded private health cover affords choice of provider and location . In thisThis study used purposive sampling, wherein prospective participants are identified as qualified to address the study aims, which is an approach frequently adopted in qualitative methodology to select information-rich cases with experience of the question of interest , albeit Rheumatology patients typically attend outpatient services every 3 or 6 months, with a large cohort requiring more frequent appointments, inter-visit follow-up and investigations. This study has demonstrated the significant overlap between process-based and non-technical domains of care within a rheumatology context, such as the burden of waiting times and inflexible processes, and the downstream impact on domains such as feeling respected, achieving high-quality clinical standards and efficient resource allocation. Collecting and analysing experiential data for this cohort is essential to providing care that better addresses patient needs and priorities. Themes derived from this study can be conceptualized in terms of process, content and impact of care, which are domains that can be captured through routine implementation of PREMs . RoutineThis study has captured valuable insights into the current experience of outpatient rheumatology care from the perspective of patients and HCPs. It informs a collective understanding of differing and shared priorities, positives of current care and areas requiring improvement. Building on knowledge, future work will seek to further the role of purpose-designed and validated PREMs in routine rheumatology care, as an adjunct to other quality and outcome measure instruments.