The topology optimization (TO) process has the objective to structurally optimize products in various industries, such as in biomechanical engineering. Additive manufacturing facilitates this procedure and enables the utility of advanced structures in order to achieve the optimal product design. Currently, orthopedic implants are fabricated from metal or metal alloys with totally solid structure to withstand the applied loads; nevertheless, such a practice reduces the compatibility with human tissues and increases the manufacturing cost as more feedstock material is needed. This article investigates the possibility of applying bioinspired lattice structures  in order to topologically optimize an orthopedic hip implant, made of Inconel 718 superalloy. Lattice structures enable topology optimization of an object by reducing its weight and increasing its porosity without compromising its mechanical behavior. Specifically, three different bioinspired advanced lattice structures were investigated through finite element analysis (FEA) under in vivo loading. Furthermore, the regions with lattice structure were optimized through functional gradation of the cellular material. Results have shown that optimal design of hip implant geometry, in terms of stress behavior, was achieved through functionally graded lattice structures and the hip implant is capable of withstanding up to two times the in vivo loads, suggesting that this design is a suitable and effective replacement for a solid implant. The additive manufacturing (AM) process has enabled the production of complex geometries ,2,3,4 alThe truss-based approach imitates the cell structures from natural tissues, such as bones, corals, foams, and so forth. Thus, this approach is suitable for topology optimization of structures in biomechanical applications, such as implants and tissue scaffolds. Specifically, in this approach, the selected volume fills with lattice structures with specific geometry and dimensions replacing the solid material. Besides the advantage of minimizing the mass of the product for usage in biomechanical applications, this procedure offers the above-mentioned additional advantages, which facilitate the tissue regeneration process and allow diffusion of oxygen and nutrients ,15. TherIn addition, there are several studies that have tried to combine additive manufacturing techniques with orthopedic implants through customization and lattice structures. Mahmoud et al.  have gatThe aim of this research was to extract an innovative design for a bioinspired hip implant utilizing topology optimization tools. Therefore, the current paper proposes a novel hip implant design with advanced lattice structures in order to address the reduction in strength and handle the in vivo loadings. Hip implant design follows a series of international standards in order to fulfill its purpose . A typicDesign parameters are configured from past research and existing literature. According to the studies of Charnley et al.  and McKnIn order to apply topology optimization through lattice structures on an orthopedic hip implant, a new hip implant was designed fulfilling all the above-mentioned standards. Therefore, the designed hip implant has the following geometry and dimensions. More specifically, the intramedullary stem’s length is 128 mm, while the neck’s length is 35 mm. In addition, the diameter of the neck is 18 mm and the diameter of the head is 45 mm. The placement angle of the neck and head in relation to the axis of the implant is 135° degrees and the angular range is almost 120° degrees. Cellular materials are scattered in naturally formed structures, such as foams, corals, bones, and so forth. These natural materials are the result of the evolution of thousands of years, thus both mechanical properties and functional properties have been optimized depending on each application. There is a variety of lattice structures that differ in shape and geometry. Therefore, for the topology optimization of a human body implant, it is logical to investigate lattice structures derived from nature that could serve the function of the implant.1, …, pn are the distinct seeds in 3D space, d  is the Euclidean distance between two seeds (p and pi), and V(pi) represents the 3D Voronoi polygon on seed pi. In the case of hip implant, lattice structures should be able to withstand increased loads relative to the body weight and the human movement. Hence, a potential candidate structure which imitates the inside trabecular structure is the Voronoi truss structure ,34. 3D VOther bioinspired lattice structures that could withstand high stress loads and offer the proper conditions to facilitate tissue regeneration are triply periodic minimal surfaces (TPMSs). TPMSs are characterized by surfaces that have an average curvature value equal to zero. TPMS-like geometries result from applying Fourier transformations on level-set equations and by using a level-set parameter c in Equations (2) and (3) . AccordiFinite element analysis (FEA) simulated each hip implant design with different lattice structures under static in vivo conditions. It is worth mentioning that FEA for each implant focused mainly on the determination of yield point and the calculation of safety factor of the topologically optimized implant design. ANSYS™ software was used for the finite element analysis and in particular, the static structural module was used to simulate the quasi-static loading. Generally, mesh generation for lattice structures could be implemented with two different types of elements: hexahedrals  and tetrFurthermore, in order to complete the FEA model, it is necessary to determine, based on the literature, the conditions for the implant’s support and the maximum loads that the implant receives from the human body under in vivo loading conditions. Hence, according to Ducheyne et al. , the hipBefore the topology optimization process, it was necessary to evaluate the initially designed solid hip implant’s mechanical behavior through finite element analysis. Therefore, the 3D CAD model of the solid hip implant  was examAs shown in The process of topology optimization of the hip implant’s design has been analyzed using three different lattice structures, namely, the Voronoi strut structure and the Gyroid and the Schwarz Diamond sheet structures, which are bioinspired. The objective was to evaluate the mechanical behavior of each structure and to highlight the most advanced structures in order to proceed to the next phase of optimization, which was the adaptive adjustment of the lattice structure through functional gradation. Topology optimization exploits the findings of the FEA of the solid hip implant in order to define certain areas of the design to be optimized. The next step was to select the appropriate relative density of the proposed lattice structures to be applied in these regions. The appropriate value of the relative density should be defined by the right trade-off between the deterioration of the mechanical properties, due to size effect, and the desired advantages . Therefore, some of the drawbacks of the size effect, like reduced modulus or a loss in strength, could be overcompensated by lightweight structures with enhanced porosity. Thus, the relative density was chosen to be 50%, due to the fact that it has a negligible influence from the size effect and it was close enough to the relative density of the femur bone  enhancinThe selection of redesigned regions with lattice structure was a result of FEA in the solid hip implant. Therefore, as illustrated in Ult has been also used and it was calculated as the ultimate factor of safety which depends on the ultimate strength of the material, as shown in Ult was greater than the value of 1 (FOSUlt =1.17 > 1). However, the stress concentration in the Gyroid structure was marginally greater than the fracture point of the material, thus it is expected that with an improved design approach through functional gradation, the strength of the implant could be increased. On the other hand, the Voronoi structures should exhibit a fundamental design modification in order to achieve FOS values greater than 1.Τhe factor of safety was calculated by the maximum stress concentration of each structure, as listed in Finite element analyses of the topologically optimized versions of the hip implant through bioinspired lattice structures showed the mechanical superiority of sheet structures, and especially TPMS, over strut structures, as discussed previously. However, through functional gradation of lattice structures, it is possible to achieve further topology optimization of the part. Thus, knowing the regions where the stresses are concentrated, design could be changed to increase or decrease the local relative density of the selected lattice structures, keeping the total relative density of the object constant but increasing its mechanical performance. This procedure was followed for all above-mentioned structures. In the areas where the highest stresses (compressive region) were concentrated, it was decided to apply a denser pattern of lattice structure to reach a local relative density of 65%, in order to completely eliminate the size effect. On the other hand, in the region with low stresses , a sparser local relative density was decided to be implemented as the stresses in this area were lower, hence the integrity of the object would not be affected by the size effect. Since the aim was to maintain the total relative density constant, these two areas were separated using a try-and-error algorithm, in such a way as to produce redesigned hip implants that have the same mass as the Voronoi, Gyroid, and Schwarz Diamond structures. It is worth mentioning that the topology optimization of the hip implant’s head and the tensile region remained the same as the previous design, as further removal of material may have affected locally the integrity of the object’s mechanical behavior. Furthermore, the topologically optimized hip implant with functional gradation of Gyroid and Schwarz Diamond structures revealed even more lower compressive stresses which resulted in a remarkable improvement of the hip implant’s mechanical performance. As it is shown in In order for the redesigned hip implants to handle the forces that they receive from the human body, it is important to access their mechanical behavior through the factor of safety. Hence, the factor of safety for the design approach containing the lattice structure of functionally graded Voronoi was 1.01 and for the design approach containing the TPMS structures of functionally graded Gyroid and Schwarz Diamond were 1.79 and 2.08, respectively. These results showed that the design approaches of the hip implant which consisted of functionally graded lattice structures could withstand the maximum static loads that the hip joint receives under in vivo conditions. Regarding the functionally graded Voronoi structure hip implant, it could marginally withstand these loads without being plastically deformed, as shown in the values of FOS in In this paper, an orthopedic hip implant was designed according to international standards and then a topology optimization of its geometry was performed. The topology optimization process was implemented via bioinspired lattice structures, namely, Voronoi, Gyroid, and Schwarz Diamond structures, which are derived from nature having superior mechanical performance. Moreover, topology optimization occurred with the implementation of these lattice structures in regions of low stress, in order to achieve the optimal mass distribution within the existing volume. Furthermore, functional gradation of the implemented lattice structures was performed. In particular, it was observed that the hip implant that contained Schwarz Diamond structures revealed the best mechanical behavior, both in simple topology optimized implant and in functionally graded implant. The factor of safety of the functionally graded Voronoi was 1.01 and for the design approach containing the TPMS structures of functionally graded Gyroid and Schwarz Diamond were 1.79 and 2.08, respectively. Topology optimization leads to a reduction of weight of 38% compared to the solid version of the hip implant, therefore less construction material is needed. Moreover, for the intramedullary stem, it has a 50% mean porosity to facilitate the process of tissue regeneration through diffusion of cells, oxygen, and other nutrients. Future work will focus on the fabrication of these implants, utilizing additive manufacturing methods and the evaluation of their mechanical properties will be measured.


National regulatory regimes for supervising ongoing clinical trials are affected by external challenges, both international, such as harmonization of EU legislation, and national, such as critical reviews of incidents. This study examines how supervisory bodies dealing with ongoing trials respond to external challenges of the past two decades and engage in institutional work to maintain, repair, or improve the Dutch regulatory regime.n = 27) were conducted with various actors, including public supervisory bodies, hospital staff, and boards of directors.International and national regulatory documents were analyzed and interviews (In the Netherlands, EU harmonization directed at centralizing and coordinating the regulatory regime for good clinical trial practice in Member States has paradoxically led to further fragmentation. The resulting ambiguity and inefficiency remained largely unresolved until a serious incident in a university hospital became a catalyst to clarify both the interconnected responsibilities and working relationships of various supervisory bodies. New legislation and regulatory methods were implemented, and actors outside the legislative framework became active in the field in order to strengthen supervision of ongoing trials, further multiplying yet also aligning with existing regulatory regimes.Public supervision of ongoing trials is fragmented in the Netherlands because the responsibilities and resources are unevenly distributed. In countries like the Netherlands, public supervisory bodies must do a great deal of institutional work to align with new EU regulations and still safeguard their traditional regulatory mechanisms that protect human safety. However, national regulatory traditions also offer new opportunities to strengthen the quality assurance of clinical trials. Clinical trial practice is highly regulated . While iIn recent years, various attempts have been made to harmonize legislation and regulation of ongoing clinical trials within the European Union (EU). EU harmonization creates a massive ongoing challenge for Member States to align international regulation with national law and supervision practices, with various national attempts taking place over time . The NetThis paper uses an institutional theoretical framework, adopting the framework of Hood, Rothstein, and Baldwin  to exploThe research question guiding this paper is: How do supervisory bodies in the public supervision of ongoing clinical trials in the Netherlands respond to the external challenges of the past two decades and engage in institutional work to maintain, repair, and improve the Dutch regulatory regime?We detail how supervisory bodies faced with external pressures undertake institutional work to both change and preserve their institutions. We look at how alignment between the various supervisory bodies comes about, where frictions occur, how these are handled, and what kind of work is needed. In our case study, these challenges, and subsequently their dynamics and frictions, not only call for repair or maintenance work, but also create new space to stimulate action for improvement.The paper is constructed as follows. The next section focuses on how the risk regulation framework and institutional work theory can help us study change and continuity in the institutional regulation regime of ongoing trials. Section 3 explains the regulatory regime of clinical trials in the Netherlands. Section 4 describes the research methods, while section 5 presents the results. Finally, section 6 presents the discussion, describing the impact of our results on both theory and regulatory practice and ending with conclusions. We believe that the mechanisms the Dutch public supervisory bodies use to deal with external challenges are relevant to other countries and domains, as any national supervisory body has to respond to these challenges within their own traditions.Hood, Rothstein, and Baldwin (2001) define risk regulation regimes as "the complex of institutional geography, rules, practice and animating ideas that are associated with the regulation of a particular risk or hazard" . OverallThe concept of a regulatory regime stresses that "institutions matter" . InstituThe notion of institutional work is of particular interest to our investigation of the public supervision of clinical trials in the Netherlands for three reasons. First, it recognizes public supervisory bodies as embedded agents who are not merely executors of regulation, but whose activities contribute to shaping institutional regulatory regimes. Second, implied in the notion of institutional work is the idea of effort in the face of resistance or challenge. Institutional work is considered true "work," as it involves challenging and negotiating existing rules, practices, and beliefs that may be in opposition . Third, EU harmonization attempts, incidents, and other triggers may reveal a misfit between legal regulation and the daily practice of supervision of ongoing trials. Actors manage, exploit, and adjust their actions to the ambiguity, pluralism, and contradiction in regulatory regimes .In this study, we seek to explore the institutional work of three Dutch public supervisory bodies in the regulatory regime of ongoing trials, tracing the effects of external challenges on their working methods and relationships. Before turning to our findings, we will first explain the institutional regulatory regime of clinical trials in the Netherlands.The Netherlands has a decentralized structure of supervision, introduced in 1999 with the Medical Research Involving Human Subjects Act (WMO) , 16. It The WMO stipulates that a sponsor of a clinical trial with human subjects may not start the trial until an MREC has approved the research protocols. Most MRECs are linked to a university medical center (UMC) or one or more general hospitals, and a few work independently. MRECs are accredited and supervised by the CCMO, which can create new guidelines, for instance with regards to the required expertise of MREC members. Research proposals and their MREC assessments must be registered with the CCMO. The Health and Youth Care Inspectorate (IGJ), in turn, is responsible for verifying compliance with the WMO  and for conducting inspections of clinical trials.In 2004, the EU Clinical Trials Directive 2001/20/EC (EUCTD) was introduced . The EUCThe Dutch government decided to implement the EUCTD by modifying the WMO (2006) . It creaSince 2000, the Dutch regulatory regime for assessing clinical trials has met several challenges. Reviews of national legislation and supervisory practices have exposed several weaknesses in the regulatory regime. The first evaluation of the WMO in 2004, prior to the introduction of the EUCTD, highlighted the unclear division of tasks between the IGJ and CCMO . The thiBesides EU harmonization and critical reviews of regulation, the Dutch regime is affected by incidents that attract public attention and act as catalysts , such asThe subsequent investigation conducted by the IGJ and CCMO, among others, highlighted several serious shortcomings in the design and execution of the research protocol, the information on side effects provided to the patients, and the reporting of SAEs―only two of the 33 deaths were reported immediately –26. FurtTo gain insight into how and why changes in the regulatory regime of ongoing trials do or do not occur due to external challenges and how Dutch public supervisory bodies undertake institutional work to engage with these challenges and preserve their institutions, we conducted an exploratory qualitative study. First, to understand the chronology of changes to the regulation of clinical trials and the responses of public supervisory bodies, we studied documents on the Dutch situation, such as legal documents, annual reports of supervisory bodies, and previous research on the development of regulation regarding clinical trials see . The stan = 9; one inspector three times); employees of the CCMO  and the MRECs (n = 5); as well as the board and staff of hospitals . Interviews focused on working methods and mutual relationships  and the literature on risk regulation regimes and institutional work.During data collection, we met regularly to analyze the data. Using inductive and deductive coding, based on regulatory regime and institutional work frameworks, we looked for relevant themes and the labels (codes) to index them. As forms of institutional work emerged, we debated the themes and codes until we reached a consensus. We identified three overarching themes that represented the supervisory bodies' responses to external challenges since 2000: (1) clarifying the division of roles and responsibilities in the supervision of ongoing trials, (2) dealing with the daily control of safety reports by MRECs, and (3) developing IIT inspections of hospitals as trial sites by the IGJ see .Legal evolvement, critical evaluations, and the Propatria trial highlighted weaknesses in the supervision of ongoing trials. We analyzed how these challenges not only became effective catalysts for transforming processes in supervision, but also induced repair work to maintain the regulatory regime. This section shows how supervisory bodies such as the IGJ and CCMO do long-term institutional work, focusing on how they operate and endeavor to strengthen their own position (§ 5.1), and the position of other actors such as MRECs (§ 5.2) and hospital boards of directors (§ 5.3).The national legislator's division of roles and responsibilities has influenced the relationship between the CCMO and IGJ. As pointed out above, the supervisory roles of both bodies have somewhat overlapped since the launch of the WMO in 1999 . The WMOStrictly, I think we [the IGJ] supervise it all, including the CCMO and the MRECs […]. But yes, no one likes that, so no one would ever admit it. Discussion of each other's jurisdiction flared up in 2003, when the IGJ took the initiative to inspect several MRECs and the CCMO:It's true, in the past we sometimes had differences of opinion with the IGJ: who supervises whom? And eventually, in 2003, the IGJ supervised MRECs, including us. But that didn't feel good, frankly. […] There's a lot open to interpretation: where does it [division of authority] begin and where does it end? Researchers involved in the first evaluation of the WMO in 2004 also observed this tension between the CCMO and IGJ . Now it can't come through the mail. Just compact discs. Yeah, it's really hopeless. You must take care you still pick out the essentials. Every week I get this extremely comprehensive set of SAEs where the researcher says that the SAE won't hinder the progress of the study. I believe them and [just] sign the papers blindly. It's correct, administratively. These quotes demonstrate the painstaking work involved in overseeing ongoing trials, but also reveal a lack of supervision by hospital-based MRECs. Our observations are in line with the second WMO review, which states that over half of MRECs found that supervision of ongoing trials was part of their task, but they usually did not have the workforce or financial means to execute it properly . ConsequOne recommendation in the Propatria report was to report all SAEs in medical research with humans to the specific MREC responsible , which iIn sum, MRECs deal differently with supervising ongoing trials due to funding, with MRECs in the not-for-profit sector having fewer resources available than those in the profit sector . This affects their ability to increase capacity when the workload grows. Over the years, the CCMO's creation work, done to gain a better grasp of SAE practice in ongoing trials, has led to a new legal responsibility for reporting annual numbers of SAEs. Despite all efforts, the division of tasks between the IGJ and MRECs is still unclear. The third WMO review suggests a new round of institutional work, involving the CCMO and hospital boards, to strengthen the position of the hospital-based MRECs in the regulatory regime .The IGJ supervises the execution of all clinical trials in the Netherlands. To respond to and anticipate the results of the Propatria trial investigation, they began to focus increasingly on IITs.The IGJ selected IITs as a theme to underscore the role and responsibility of hospital boards as sponsors of trials initiated by their organization. We observed major differences in the IGJ's working methods between the first and second round of inspections. In the first round, between 2014 and 2016, they carried out inspections targeting IITs of medical products at seven UMCs and two teaching hospitals. An inspector reflects on why IITs became the new focus:We've been saying for years that in some studies it's not so clear that the sponsor [hospital] feels responsible; they should be, but are they really? And that's why the focus shifted to IITs. A risk model for clinical trials of medical products was developed to make the sponsor's responsibilities transparent and place the hospital's board of directors into the position of sponsor. The legal framework was based on the International Council on Harmonization of Technical Requirements for Registration of Pharmaceuticals for Human Use Good Clinical Practice (ICH GCP) guideline , alongsiSo then you see the [hospital] boards generally do feel responsible, but the extent to which they ensure that a [quality] system gets implemented, well, that fluctuates. The first round of results showed that general teaching hospitals were often involved in multicenter IITs. In 2016, the IGJ started a second round of inspections of IITs in teaching hospitals, anticipating that the level of quality assurance would differ because research is not a core business of teaching hospitals. Hence, the IGJ created a new database ranking hospitals by their number of studies and the table of contents of their quality assurance manuals. Using these criteria, ten teaching hospitals were selected for one-day inspections in 2016. The IGJ's creation work was to develop a new working method to obtain insight into actual safety practices while keeping the workload "doable". This method permitted quick scans of ongoing IITs rather than in-depth analysis of one IIT . Each hoOkay, so we had to find a format to do it in fewer days—but that also means looking in less detail. It can't be otherwise. […] It's new, it's actually the first time that we're not just looking at clinical trials of medicinal products in our proactive supervision […] because […] supervising the WMO implementation doesn't just stop at clinical trials with medicinal products. Because of the ICH GCP, and the tools you have when you look at a study, most of the effort went into clinical trials, but that's different now too. As the IGJ was no longer inspecting only clinical trials of medical products, the international ICH GCP became unusable. The IGJ sought new legislation which kept the focus on the responsibilities of the hospital boards. The Dutch Healthcare Quality, Complaints and Disputes Act of 2016 , developIt is important to note that two of the teaching hospitals involved in the first round of inspections shared their critical findings and experiences with other teaching hospitals through the Association of Top Clinical Teaching Hospitals (STZ), an association of 26 teaching hospitals. This created a sense of urgency among other teaching hospitals, and prompted the STZ to undertake further supportive action. A staff member of one of these teaching hospitals explains:Based on our inspection experience, we drew up a document called "Lessons learned". We first discussed this document internally and then with the STZ. It created a flywheel effect and, for example, led to adjustments to 33 STZ standard operating procedures. I think sharing is one of the strengths of the STZ. The STZ's creation work focused on examining "best practices" in top clinical teaching hospitals to create standard operating procedures, which hospitals can use to supplement their quality assurance manuals. This led to an upgraded level of quality assurance. The IGJ was pleasantly surprised to see this learning curve:So, actually, it's nice because these hospitals had three years to pick it up. And of course it's also because the teaching hospitals were so open with the other teaching hospitals about what they'd gone through [in the first round of inspections after the Propatria case] and what they'd learned from the inspections and to share that with the others. That's where it starts naturally. The IGJ halted their inspections after visiting eight of the planned ten teaching hospitals, because the same results and recommendations were evident in every hospital. This was made possible because, on the basis of the perceived sharing culture in the STZ, regarded as a serious partner in research, the IGJ presumed that the inspected hospitals would share their results with one another.The inspectors shared their methods and the results of the inspections with the STZ at various meetings. This quote reveals the boards of directors' growing awareness, especially in teaching hospitals, of their tasks as sponsors of IITs:It was so nice […], you really saw the penny drop. That someone said: "So, as a member of the board of directors, I'm responsible for monitoring the multicenter research that we do in other hospitals?" […] "Yes, that's right. And how you organize that—you can talk about that. You're responsible for it." This came about through the IGJ's institutional work and by including the STZ in their fieldwork.To sum up, the focus of the IGJ inspections shifted to IITs because of the Propatria trial. This shift involved positioning work by the IGJ, as a form of creation work. Subsequently, they created a context in which "new" actors outside of the public supervisory bodies, the hospital boards, were mobilized to take up their self-regulatory role . The IGJThe purpose of this paper is to examine how supervisory bodies in the public supervision of ongoing trials in the Netherlands respond to external challenges, and engage in institutional work to maintain, repair, and improve the regulatory regime for the safety of clinical trials. The paper shows that changes in (inter)national law and severe incidents in research practice created a window of opportunity for institutional work to both change and protect the regulatory regime. Our findings demonstrate that institutional work is a continuous endeavor at the level of regulatory regimes. Ambiguity sometimes complicated finding the right terms for institutional work. When done by a public supervisory body, institutional work can be considered creation work, changing the regulatory regime, but at the same time it can be regarded as protecting the existing regime. These become interconnected as public supervisory bodies respond to the threats to their status quo and the challenges that create new opportunities. In fact, public supervisory bodies must constantly adapt to external challenges in order to stay the same.Paradoxically, this research shows that the EU policy of harmonization led to even more fragmentation in the Dutch regulatory regime. Implementing the EUCTD left the decentralized supervision structure in place, whereas the EUCTD stipulated a centralized system. In practice, the IGJ, CCMO, and MRECs needed clarity on who was responsible and accountable for what in the public supervision of ongoing trials. The Propatria trial became a catalyst for the IGJ and CCMO to perform institutional work and act more constructively, and it let teaching hospitals present themselves as research institutes. However, it left unclarities in place, such as the division of tasks between the IGJ and MRECs, especially in the supervision of ongoing research. The layered regulatory regime implies that public supervisory bodies also monitor the public tasks of other supervisory bodies: the CCMO supervises MRECs, while the IGJ supervises all the involved parties. However, between the IGJ and CCMO, the role of "supervising supervision" still needs clarification. Nowadays, the IGJ is advised to maintain a position such that it can supervise the CCMO . In termOverall, institutional theory offers conceptual tools for analyzing the work needed to make regulatory regimes productive. In countries like the Netherlands, with a different tradition from the EU regulatory framework, public supervisory bodies must carry out a great deal of institutional work to align with EU regulations. By focusing on the dynamic interplay between three supervisory bodies in the past two decades, this study contributes to the literature on the relational features of institutional work in two ways. First, our findings demonstrate that institutional work is needed at the level of the regulatory regime because the interplay between evolving regulations and external challenges creates certain dynamics and frictions. Public supervisory bodies continuously need to align with these dynamics while safeguarding existing effective regulatory mechanisms. Second, our findings reveal how public supervisory bodies deal with the external challenges presented by EU harmonization attempts and exposed weaknesses in the regulatory regime. The weaknesses highlighted in the supervision of ongoing IITs, reflected by one adverse incident, became an especially effective catalyst for maintaining and repairing the regulatory regime of the public supervision of ongoing trials. Although other forms of institutional work could be referenced, as the literature has discerned many categories and labels, the institutional work referred to in our case study dealt particularly with coordination work leading to improvements in information sharing, and positioning work to repair and maintain existing institutions. Our case study showed the importance of positioning work, meaning the mobilization and positioning of actors to assume specific roles or do new things, such as bringing actors from outside the legislative framework, in this case hospital boards and the STZ, onto the playing field. This creates new opportunities to strengthen the quality assurance of clinical trials in hospitals.One limitation of our study is that it is based on a single case in the Netherlands. However, investigating mechanisms like institutional work requires very detailed data collection to link theory to empirical work . TrianguIn conclusion, external challenges like attempts at EU harmonization can be complicated when Member States have divergent regulatory regimes. Harmonization requires more than "just implementing new rules." It requires institutional work by Member States to align existing regulatory regimes with new rules and balance between institutional change and preservation. Given the rise of increasingly international, multi-sited research, such work remains important to safeguard patient safety and data integrity. Zooming in on the supervision of trials in the Netherlands, we observed how EU harmonization attempts created tension in the Dutch regulatory regime and supervision practices. Institutional work is needed to resolve this tension, but new problems may arise from the solutions.While our longitudinal study focused on the consequences of the EUCTD in the regulatory regime, Member States have prepared to implement the next round of harmonization, the ECTR, which will change the process for starting clinical trials in Europe yet again in 2020  and replS1 Table(DOCX)Click here for additional data file.S2 Table(DOCX)Click here for additional data file.S1 Appendix(DOCX)Click here for additional data file.


Previous hotel performance studies neglected the role of information entropy in feedback processes between input and output management. This paper focuses on this gap by exploring the relationship between hotel performance at the industry level and the capability of learning by doing and adopting best practices using a sample of 153 UK hotels over a 10-year period between 2008–2017. Besides, this research also fills a literature gap by addressing the issues of measuring hotel performance in light of negative outputs. In order to achieve this, we apply a novel Modified slack-based model for the efficiency analysis and Least Absolute Shrinkage and Selection Operator to examine the influence of entropy related variable on efficiency score. The Results indicate that less can be learnt from inputs than from outputs to improve efficiency levels and resource allocation is more balanced than cash flow and liquidity. The findings suggest that market dynamics explains the cash flow generation potential and liquidity. We find that market conditions are increasingly offering the opportunities for learning and improving hotel efficiency. The results report that the distinctive characteristic of superior performance in hotel operations is the capability to match the cash flow generation potential with market opportunities. The tourism and hotel management literature has long praised the benefits of hospitality and leisure issues on customer satisfaction levels  and the Performance in hotel industry is often characterized by concentration of best practices in few large players with high economies of scale and profitability . Big intUnited Kingdom, as one of the European countries with a long history, special heritage and traditional culture, attracts huge amount of tourists every day. This tourist attraction was facilitated by the capital of UK, London, which is one of the most important financial centers in the world. In addition, as the increase in the economic growth and optimization in the production process derived from the advancement of internet technology and information sharing, people across the globe saw an increase in the amount of disposable income. Therefore, people do not only pursue the possession of physical capital, but focuses more towards the wealth of themselves at the spiritual level. In other words, people nowadays tend to spend money on exploring the interesting and different aspects in their life. One area of these would be travelling to different countries to feel different culture, food, people, et cetera. The popularity of travelling undoubtedly boosts the development and prosperity of the hotel industry, which is one of the most important components in the hospitality sector, and further contribute to the country’s economic growth.The importance of the hotel industry in the economy together with the increase in the tourism volume induce more researchers to investigate the performance in the hotel industry. On top of the research studies using relevant accounting ratios to evaluate the profitability in the hotel sector, a growing number of research articles use advanced operational method to assess the efficiency level of hotels which provided more accurate results comparing to the accounting ratios. Besides the traditional non-parametric Data Envelopment Analysis and parametric Stochastic Frontier Analysis, scholars built upon and extend these methods resulting in a number of innovative models including Data Envelopment Analysis metafrontier, Data Envelopment Analysis window analysis, Bayesian Stochastic Frontier Analysis, triangular Data Envelopment Analysis, super efficiency Data Envelopment Analysis and grey entropy, slack-based Data Envelopment Analysis, network Data Envelopment Analysis, stochastic Data Envelopment Analysis, hyperbolic network Data Envelopment Analysis as well as two-layer bootstrapped Data Envelopment Analysis.The objective and contribution of this study is to explore the relationship between hotel performance at the industry level and the capability of learning by doing and adopting best practices. Precisely the study is based on the underlying hypothesis that entropy-related variables could help in increasing cash flow generating potentials by a better use of current productive scale ,12. BesiHotel performance measurement is a key research area surrounded by epistemic uncertainty with respect to the dual formed not only by the geographic and temporal scope of the analysis, but also by the method chosen to measure performance. In a broader sense, epistemic uncertainty reflects the lack of prior knowledge on how hotel performance could be impacted by economic conditions  scattered through time and space. For many practical purposes, epistemic uncertainty is inherent to delimitating the object-method pair under study and manifests itself regardless of the literature gap identified, the scale used to measure variables, the variable (input/output) selection, and the reproducibility conditions that are intrinsic to some extent to the hoteling industry, which may vary within and between countries. For instance, there is no questioning that the proper identification of the literature gap is relevant for advancing the body of knowledge in hotel performance, especially with respect to DEA models where a plethora of different alternatives could be employed to handle specific aspects of hotel industry efficiency in different countries. However, research gaps and input/output measurement scales do not by themselves mitigate epistemic uncertainty in the ambit of hotel performance, but only assure under the aspects of internal validity—in light of the current body of knowledge and scale validity—that the proper analytical models were developed to adequately handle the specific nature of what is being measured.Hence, as regards this paper, epistemic uncertainty can be conceptualized as the scientific uncertainty in the process of modelling hotel performance criteria in distinct geographic locations over the course of time. Despite limited data and knowledge, the joint use of information theory and soft computing offers methodological tools to mitigate epistemic uncertainty while increasing research validity and reproducibility: (i) sensitivity analysis not only by running alternative models, but also by allowing the incorporation of variables with negative values in DEA; and (ii) using information entropy principles for improving decision-making as regards whether or not a given model is contributing to reduce epistemic uncertainty by mapping how improvements in hotel inputs and outputs could be achieved through learning from other variables. The methodology here employed satisfy these two conditions, not only by increasing the valid scale range of inputs and outputs to allow negative values in DEA, but also by the composing the information entropy of efficiency scores, inputs, outputs, and contextual variables into its major constituents, thus offering to academics and practitioners an improvement roadmap in the hotel industry. The results show that information entropy on inputs is much wider than the one of outputs, therefore, less can be learnt from inputs to improve the efficiency level in the UK hotel industry. In addition, we find that the entropy dispersion of the contextual and business-related variables is in between the one of inputs and outputs, thus, something can be learnt from the market dynamics related to tourism inflows and outflows as well as financial conditions of hotels, which is related to the cash flow generation potential. We further notice that the evolvement of inputs and contextual variables related to information entropy goes in opposite directions, in other words, at the time when information entropy for inputs increases, the one for contextual variables decreases, which indicates and conforms that over the examined period, there is a degree of opportunity to learn from market conditions to improve the hotel efficiency level. Finally, the negative impact of input/output joint entropy on super efficiency scores suggest that the UK hotels should be operated under a decreasing return to scale combined with a price discount policy, which would be helpful to improve efficiency level from the perspective of increase the cash flow generation potential. The remainder of this paper is organized in four sections. First, we provide a discussion of the literature concerning estimation of hotel efficiency. Then, we describe the study’s methodology. Next, we offer the results and discussion. Finally, we conclude with implications, limitations and future research opportunities.The efficiency in the hotel industry has been extensively investigated by the empirical literature. The original operational methods used to estimate hotel efficiency can mainly divided by Data Envelopment Analysis ,19,20,21Recently, a number of research articles extended the traditional Data Envelopment Analysis or Stochastic Frontier Analysis by introducing some advanced techniques in estimating the level of efficiency in the hotel industry. This includes the use of (1) Data Envelopment Analysis metafrontier analysis , this meBesides the above, the empirical studies also proposed and present the following methods including (3) Bayesian stochastic frontier analysis ,34, in tIn addition, we also observe that empirical studies have attempted to use the method below including (5) super efficiency Data Envelopment Analysis and grey entropy , as arguThird, a number of research articles have applied the following method in estimating hotel efficiency including (7) Network Data Envelopment Analysis model ,44; the Finally, we also find that the following methods have been applied in the hotel performance evaluating including (9) Hyperbolic network Data Envelopment Analysis model ; as arguRegarding the inputs and outputs selection in the hotel production process, quite a few different inputs have been proposed and used by various studies including accommodation capacity ; TouristIn summary, through reviewing the literature regarding the estimation of efficiency in the hotel industry, we observed that there has been no attempt to examine the relationship between hotel performance at the industry level and capability of learning by doing and adopting best practices, the investigating of this is of particular importance regarding the potential behavior that can be engaged in by the hotels through interacting with other hotels in the industry. We fill in this gap by examining this relationship. The issue of negative output in the efficiency analysis has not been addressed in the estimating of hotel efficiency, we contribute to the empirical literature by proposing a modified slack-based model. Finally, we contribute to the literature in the examination of hotel efficiency by being the first to propose a Least Absolute Shrinkage and Selection Operator to examine the influence of entropy related variable on efficiency scores which is supposed to provide more robustness and accurate results for policy making purposes. This section describes the major methodological cornerstones employed in this research. Readers should recall from the introduction that the hybrid approach (DEA-Information Entropy-LASSO regression) here discussed is designed towards the mitigation of epistemic uncertainty in hotel performance. Being a non-parametric technique, DEA embedds in itself a large degree of uncertainty, as long as no distributional assumptions are required whatsoever with respect to inputs, outputs, and the resulting computed scores. Information entropy allows a distributional assessment of these quantities, helping in understanding not only their degree of reliability, but also in unveinlyng non-linear associations that may exist among them, moving further beyond the traditional correlation coefficient approach. In turn, LASSO allows the identification of the critical explanatory variables, by imposing informational penalties, helping in structuring by means of a linear model how much of impact on efficiency scores is due to a given information entropy subset of variables, i.e., inputs, outputs, and contextual variables.We collect a dataset of 153 UK hotels over a 10-year period between 2008–2017. Regarding the selection of inputs and outputs for the novel modified slack-based model proposed, we choose three inputs to represent the operational scale which are number of employees, depreciation/amortization, as well as cost of goods sold, we consider five outputs to represent the cash flow generation potential including operational revenue, other operating expenses, liquidity ratio, capitalization as well as hotel size. Capitalization is measured by the ratio between shareholders’ funds and total assets, hotel size is measured by the natural logarithm of total assets. The third group of variables besides inputs and outputs are contextual business-related variables such as number of international arrivals, number of international departures, international tourism expenditures, international tourism receipts, total assets as well as shareholders’ fund. https://www.bvdinfo.com/en-gb/our-products/data/international/amadeus), which contains comprehensive information about large public and private companies across Europe, while other contextual and business related variables including tourism arrival, departure, expenditure and receipts in the UK are collected from the world bank database (https://data.worldbank.org/). Cost of goods sold, operating revenue, depreciation/amortization, operating expenses, total assets are in the unit of thousand Euros, hotel size, capitalization and liquidity ratios are in ratios, international tourism receipts and expenditure are in the unit of current US dollars, number of arrivals and number of departures are in the unit of persons. The input and output variables together with total assets, shareholders’ fund are collected from Amadeus database There is at least one positive output.(b)There is at least one positive input.(c)There is some negative input/output data.Suppose we have a set of The production possibility set is defined as belowThe Modified Slack-based Model is defined as follow :minρ=1−∑In this section we propose our ranking approach. First, we compute the efficiency score of Decision Making Units using the Modified Slack-Based Model. If there is just one efficient Decision Making Unit, then we do not need ranking. On the other hand, suppose that there is more than one efficient unit and let Now, the proposed super-efficiency model is as followsRemark 1.Iforthen we setorrespectively, and as a result,andare positive.The model (2) has the following properties.Proposition 1.Letbe the optimal value of model (2). Then,Proof. The proof is clear and hence omitted. □Proposition 2.The super-efficiency scoreis units invariant, i.e., it is independent of the units in which the inputs and outputs are measured provided these units are the same for every Proof. The proof is clear and hence omitted. □Proposition 3.Model (2) is translation invariant.Proof. The proof is clear and hence omitted. □Model (2) is a fractional programming and can be easily converted to the following linear model:Example 1.This example has been taken from . ConsideInformation Entropy can be conceptualized as a measure of uncertainty, which is a probabilistic concept. Depending on the entropy characteristics, the randomness and dispersion produced by a random variable can be determined by calculating the information entropy for each original variable—for example: input, output—under each group of analysis . The greater the value of the information entropy, the greater the randomness or the dispersion within the ambit of each group and, therefore, the greater the heterogeneity produced in analyzing this unknown phenomenon . In thisJoint Entropy, in turn, represents the joint epistemic uncertainty of two random variables. It helps in understanding how balanced their responses are. Specifically, with respect to input and output Joint Entropy at the hotel level, it is possible to describe whether cash flow generating potentials are elastic or inelastic to variations in operational scale. This is particularly important because hotel operations are capital intensive requiring somewhat higher breaking-even levels. Joint Entropy between outputs and contextual variables related to tourism inflow may reflect also whether or not revenues are elastic with respect to demand. Differently from Information Entropy and Mutual Information, which is discussed next, Joint Entropy bridges the gap between epistemic uncertainty and learning processes by imposing economic constraints or boundaries—such as scale and revenue elasticities—on possible joint fluctuations. While balanced joint fluctuations would denote a neutral or constant response; unbalanced ones would represent decreasing/increasing returns-to-scale and inelastic/elastic revenue responses to demand given a capacity level.Mutual Information represents the mutual information level of two random variables A and B and measures the “amount of information” that can be inferred about one random variable by observing the other . Puttingc as the index for cities, c = {1 … C, C = 55}; t as the index for years = {1 … T, T = 10}; and h as the index for hotels = {1 … H, H = 153}. Let´s also consider that, for each hotel at each year of the sample, i = {1 … I; I = 3}is the index for its inputs (x); o = {1 … O; O = 5} is the index for its outputs (y); and v = {1 … V; V = 6} is the index for its contextual variables (z). At last, let s denote the (super) efficiency scores computed per each hotel h for each year t. Hence, the following information quantities can be defined:The dataset summarized in Information entropy mass for the efficiency scores per hotel per year:For efficiency scores: For super-efficiency scores:Information entropy mass at the hotel level per year per city:For the inputs: For the outputs:For the contextual variables: Conditional information entropy means per year per city:For the inputs:For the outputs:For the contextual variables: Conditional joint entropy per city per year:For the input-output pair: For the input-contextual pair:For the output-contextual pair:Conditional mutual information per city per year:For the input-output pair: For the input-contextual pair:For the output-contextual pair:β0, β1, …, βp. This procedure is more restrictive in estimating the coefficients, and sets a number of them to exactly zero when the tuning parameter λ  is sufficiently large [λ for the Least Absolute Shrinkage and Selection Operator is critical; and cross-validation technique is often used. Equation (18) gives the Least Absolute Shrinkage and Selection Operator model used in this research to select a subset of information entropy related variables capable of explaining UK hotel super-efficiency scores.The Least Absolute Shrinkage and Selection Operator relies upon the linear model but uses an alternative fitting procedure for estimating the coefficients ly large . Hence, Results for the super-efficiency scores computed using the novel Modified Slack-Based Model are depicted in p < 0.05 from traditional Data Envelopment Analysis models to the proposed Modified Slack-Based Model (from 0.114 to 0.130), the dispersion of information entropy distributions was dramatically reduced  presented a positive impact on super-efficiency scores, indicating that the distinctive characteristic of superior performance in UK hotel operations is the capability to match the cash flow generation potential with market opportunities related to touristic in/outflow within the ambit of feedback learning processes. On the other hand, the negative result for input/output joint entropy reveals that input resource dimensioning imposes scale and revenue elasticity constraints in light of output optimization. As long as hotel operations are capital intensive, there is a great likelihood to exploit market opportunities, derived from changes in touristic flows by operating in decreasing returns to scale with continuous price discount policies to sustain liquidity and cash-flow generation of the course of time. This is exactly the case in the UK hotel industry, for instance, the hotels in the big cities such as London and Manchester, in the city center area, there would be a number of different hotels located near each other offering similar level/quality of accommodations/catering to the tourist, therefore we can deduce and imagine that the capacity of hotels to accommodate the tourists is big enough, increase the operational scale will not achieve the effect of cost saving, because of higher level of competition among different hotels, they should consider the measurements or owned policies to sustain their market share, one of the effect way would be reduce the price level through providing discount the customers which is supposed to attract more people. The economic growth across the globe, together with the increase in the volume of Gross Domestic Product per capita make people have more disposable income. Besides the traditional physical products demanded and consumed by the people, there is a general trend of increasing in the consumption in the area of entertainment. In particular, people spent more time and money on exploring new experience  through travelling to different countries, this is mainly derived from the globalization in which countries they do not only engage in trading with each other in tangible goods, but also in the areas of intangible services such as the international tourism. The United Kingdom, together with Germany, Italy and France, make up the four biggest economies in Europe. London, the capital city of the United Kingdom, is the world largest financial center, which does not only attract the influential financial institutions and companies to headquartered in, but also attract many people to look around and pay a visit to this legendary city and country every year. The hotel industry, one of the most important components of the hospitality sector facilitate the development of the country’s international tourism industry by providing accommodations and catering to both the local domestic people as well as the travelers from all over the world. The performance of the hotel industry is very important from the perspective that it will provide an indicator to the potential investors for their decision to invest the money in this sector. For instance, large amount of profit in this sector will attract more potential investors to enter into this industry, on the contrary, lower amount of profits will divert more people to invest the money to other sectors of the economy. For the existing hotel management and hotel practitioners, not only do they consider the profit through their operation, but also, they concern the issue of how to reduce the cost of operation through optimizing the resource allocation in the production process. In addition to this, both the hotel companies and academic researchers have a great interest in the factors which will influence the efficiency in the hotel industry, the latter devote a large amount of effort by proposing different types of advanced methods to investigate the efficiency of hotel companies. Different from the empirical studies in related to the estimation of efficiency in the hotel industry, we use a sample of UK hotels to significantly contribute to the area of efficiency analysis by proposing a modified slack-based model to evaluate the level of super-efficiency in addressing the issue of negative values of cash flow and liquidity variables. We are also the pioneer to propose the Least Absolute Shrinkage and Selection Operator to examine the influence of entropy related variables including both mutual information and joint entropy on efficiency scores. The findings of our study suggest that less can be learnt from the input side to improve the efficiency level in the UK hotel industry, while in comparison the results show that the market dynamics in related to tourism inflow and outflow together with financial strength of hotels in terms of total assets and shareholders’ funds have a higher explanatory power in the efficiency level in the UK hotel industry. We provide important policy implications to the UK hotel industry to improve the efficiency level: (1) the UK hotels should operate in a decreasing return to scale (reduce the size of operations) and also implement the policy of providing discount; (2) more focus should be given in the process of hotel management in terms of how to further increase the level of revenue, therefore, probably a diversification strategy could facilitate the achievement of this; (3) the UK hotels should further increase the liquidity level and also enhance the level of capitalization; (4) the UK hotels should pay attention to reduce the level of overhead costs, some of the areas that the hotels can focus on related to the cost reduction include the administration cost, utilities cost, insurance cost, marketing cost and maintenance cost. The future research could use alternative advanced Data Envelopment Analysis method to evaluate the efficiency in the UK hotel industry or use the advance Stochastic Frontier Analysis to check and compare the robustness of our results, while the robustness can be further checked by using alternative econometric techniques to test the influence of the contextual and business-related variables on the efficiency score. Finally, the sample could be expanded to including other European countries or compare the efficiency in the hotel industry between UK and other Asian countries.


Hydrogen cross-feeding microbes form a functionally important subset of the human colonic microbiota. The three major hydrogenotrophic functional groups of the colon: sulphate-reducing bacteria (SRB), methanogens and reductive acetogens, have been linked to wide ranging impacts on host physiology, health and wellbeing.An existing mathematical model for microbial community growth and metabolism was combined with models for each of the three hydrogenotrophic functional groups. The model was further developed for application to the colonic environment via inclusion of responsive pH, host metabolite absorption and the inclusion of host mucins. Predictions of the model, using two existing metabolic parameter sets, were compared to experimental faecal culture datasets. Model accuracy varied between experiments and measured variables and was most successful in predicting the growth of high relative abundance functional groups, such as the Bacteroides, and short chain fatty acid (SCFA) production. Two versions of the colonic model were developed: one representing the colon with sequential compartments and one utilising a continuous spatial representation. When applied to the colonic environment, the model predicted pH dynamics within the ranges measured in vivo and SCFA ratios comparable to those in the literature. The continuous version of the model simulated relative abundances of microbial functional groups comparable to measured values, but predictions were sensitive to the metabolic parameter values used for each functional group. Sulphate availability was found to strongly influence hydrogenotroph activity in the continuous version of the model, correlating positively with SRB and sulphide concentration and negatively with methanogen concentration, but had no effect in the compartmentalised model version.Although the model predictions compared well to only some experimental measurements, the important features of the colon environment included make it a novel and useful contribution to modelling the colonic microbiota. This last technique, although dependent on experimental data for model validation, has appeal as a fast, cheap and high-throughput method, leading to the creation of several mathematical models predicting colonic microbial dynamics in recent years . Effortrs e.g. , 3). Mos. Mos, anrs . Finally, various substrate availability scenarios were simulated to give predictions for their effect on the microbiota.https://cran.r-project.org/web/packages/microPop/index.html) contains ten colonic MFGs, with a total of 17 metabolic pathways, influencing the concentrations of 20 metabolites. The model utilises Monod kinetics, involving maximum growth rates, half-saturation constants, yield and stoichiometric parameters for each metabolite in each metabolic pathway. The pH and substrate preferences of each MFG are also included, leading to 243 model parameters in total. These parameters were set based on existing knowledge of the MFGs, rather than parameterisation of microPop with faecal culture data. Note that two sets of microbial kinetic parameter values were used in this work: an Alpha set, utilising the original parameter values of Kettle et al. [microPop constructs and solves a system of ordinary differential equations for any number of MFGs and metabolites, as defined by the user. The base version of microPop  concentrations were mostly inaccurate see Fig. : Table 1The model prediction under low peptide conditions , preventing population growth.No explicit data was available for the acetogen or the methanogen MFGs from these experiments; these were simply calculated as a proportion of the total Firmicutes and total bacteria, respectively  gave the best predictions of the four for some aspects of the comparison to literature values in Table The consistent underprediction of SCFAs by each of the models could be remedied by a greater concentration of protein, NSP and resistant starch entering the colon. However, none of the model runs were able to achieve predictions for the NoButyStarchDeg and NoButyFibreDeg MFGs within an order of magnitude of the observed relative abundances, making this the only consistent failing of the model that could not be explained by insufficient substrate availability. Since these MFGs were also underpredicted in the comparisons to experimental data in the "2S) production in the colon. Previous research has shown both positive and neutral results of increased dietary sulphate increasing the colonic SRB population [2S production in the model. The reasoning was that the sulphate released during mucin metabolism would be in excess of what can be metabolised by the small SRB MFG population in the colon, therefore sulphate would not be limiting, and additional sulphate would have no effect. To investigate this, microPop:Colon was run with varied sulphate inflow concentrations and transit times.The microPop:Colon model was developed for use as a tool to quickly provide predictions on the effect of changes in substrate availability on colonic dynamics. As our interest was in the hydrogenotroph dynamics in the colon, it was considered what the role of inflowing sulphate quantity was on the SRB population and SRB hydrogen sulphide , where the sulphate availability was increased by a factor of 10 from the NormS case. To investigate the influence of transit time on the results, colonic transit times of one day (as investigated previously), two days and four days were simulated.The discrete and continuous versions of the microPop:Colon model were run as described in the previous sections, using the Alpha parameter set and with sulphate inflow the only substrate that was varied. Conditions compared were as follows: zero sulphate (NoS), where sulphate may be derived from cross-feeding on the breakdown products of mucin only; low sulphate availability (NormS), for which the results of the previously performed model runs with 0.86 g L–4 g L−1 were observed for all metabolite concentrations, with the exception of sulphate, which increased with increasing influx levels.Using the discrete model, variations in sulphate resulted in a maximum concentration change of less than 0.02% for those MFGs that avoided washout, including the hydrogenotrophs. Steady state differences of less than 102S concentration changes following the SRB trend.The results of the continuous model showed greater differentiation between sulphate and transit time conditions Table . Changes2S concentrations, while removal of sulphate inflow would result in substantial decreases in both these quantities.Thus, the discrete and continuous models were not consistent in their conclusions on the effect of varied sulphate influx on the SRB MFG. The discrete model predicted washout of the SRB MFG under all conditions simulated, whereas the continuous model predicted that increased sulphate would result in incremental increases in SRB and HThe modelling work described here builds on the work of Kettle et al. , developThe number of in vitro data sources used for model validation was limited by the requirement for detailed information on study design and time-course measurements of metabolite and microbial concentrations. However, the three sources and 14 independent experiments used allowed for comparison of the model predictions to microbial data for the majority of MFGs in the model, and against concentration data for five microbial metabolites, namely acetate, butyrate, propionate, lactate and formate.The accuracy of the model predictions varied between parameter sets. Overall, no clearly superior parameter set was established from the validation runs: while the Beta parameter set of Wang et al.  appearedThe viable and optimal pH range of each MFG was altered between the Alpha and Beta parameter sets. As pH varies between 5 and 7.5 in the simulations of the in vitro experiments and for the microPop:Colon runs, this change has a strong effect on growth. Moreover, substantial alterations were made to the maximum growth rate of the Bacteroides MFG on protein, NSP and resistant starch. Due to the dominance of this MFG in many of the simulations detailed here, the differing model predictions between parameter sets were to be expected.The original setting of parameter values in the Alpha set by Kettle et al.  and of tThere are obvious limitations in assuming that a single set of parameter values is representative of an entire functional group: clearly more variation exists between strains in the same MFG than is captured using this assumption. Kettle et al.  addresseThe major addition to the original microPop model described here was the inclusion of the SRB MFG and the alterations to the modelling of the other hydrogenotrophic MFGs. A full comparison of the developed model with the original microPop model has not been presented here, mainly due to a lack of data around hydrogenotroph dynamics: none of the data sources used here measured all three hydrogenotrophic MFGs and their associated metabolites. The novel SRB MFG was washed out in all simulations in the "Another challenge faced by the creators of the original microPop model was in determining the initial abundance of MFGs. Kettle et al.  determinThe development of microPop:Colon required the inclusion of environmental factors and their influence on MFGs. The inclusion of host SCFA absorption allowed the effect of the colonic microbiota on the host to be quantified. The proportion of total SCFAs absorbed was consistently lower than observed in vivo, which could be due to several factors. Firstly, the absorption parameter used in microPop:Colon was calculated using results from perfusion experiments; colonic absorption under normal conditions may take place at a different rate. Secondly, the absorption rate in microPop:Colon was dependent on the volume of the colonic section (for the discrete model) or of the modelled digesta (for the continuous version), with greater volumes resulting in greater SCFA absorption. Estimates of adult colonic volume in the literature vary widely, from the 3.02 L used here , 32 to amicroPop:Colon also considered bicarbonate secretion by the host, and subsequent buffering of the colonic environment. This is one of the strengths of the model, as it allows for a more physiological representation of pH than would be possible if pH were fixed. However, it was challenging to find consistent estimates of colonic bicarbonate secretion in the literature. Bicarbonate ions are exchanged for SCFAs at the colonic epithelium, but also for other ions such as chloride, which were not modelled , 35. TheAlthough the inclusion of pH in the model adds functionality, there is also potential for this to contribute to errors in the model predictions. If the pH value is incorrect, then this will influence the growth and metabolism of the modelled MFGs, resulting in variation in the production of pH influencing metabolites. This feedback mechanism should be considered in interpreting model results and should also be an area for future development and testing of the model.Another aspect of the model that defies consistent estimation is transit time. For microPop:Colon, a mean transit time of 24 h was chosen based on measurements in the literature , 20. HowTransit time has been shown as a determining factor in hydrogenotroph abundance , 39. BotOne important omission of the model was the mucous layer. Previous models for colonic microbiota dynamics, such as that of Muñoz-Tamayo et al. , have inmicroPop:Colon predicted no increase in the SRB MFG concentration in the discrete model and only minimal increases in the continuous model with increased sulphate influx. This, alongside the inverse relationship between the SRB and methanogen MFGs in terms of population size in this investigation, suggests that competition between these MFGs for hydrogen or formate may be present. This relationship was not seen with the acetogen MFG, perhaps due to its additional ability to metabolise carbohydrates. Competition between the hydrogenotrophic MFGs has been postulated previously but no consensus has yet been reached on the extent to which this occurs in the colon , 5.The microbial community in microPop:Colon was shown to vary from the profile seen in vivo Table . HoweverIn the future, it may be possible to use faecal abundance data to give an estimate of the proximal colonic population using microPop:Colon. Inverting the model, so that data such as faecal pH, MFG and metabolite concentrations are the input, could allow a reverse simulation or Markov Chain Monte Carlo estimation to be conducted in which the proximal colonic population could be predicted, to within some degree of accuracy. Such a model would require rigorous validation of the current model against human data, as the prediction quality of the reverse model would be dependent on its accuracy in its current form.There are several existing models for microbial and metabolite dynamics in the colon. Table Adaptations to the original microPop model of Kettle et al.  have beemicroPop:Colon represents a tool for the further interrogation of experimental data or investigation of hypotheses on the behaviour and function of the human colonic microbiota. Once validated against experimental data for a specific in vitro system, the model could be used to analyse the data from a different perspective. With further validation against in vivo data, the model could be used to make predictions about the effects of dietary interventions, probiotic performance, or antibiotic resistance on the microbiome. Some other example uses of the model include: deriving an estimate for the amount of acetate produced via reductive acetogenesis during a faecal fermentation study; estimating the effect of increased dietary resistant starch on the colonic microbiota and SCFA absorption; or, providing a prediction for the best candidate prebiotics to elicit a butyrogenic effect before beginning more expensive in vitro tests.The advantages of microPop:Colon over its in vitro and modelling alternatives are its rapid results, low cost and the ease with which new functionality can be built in. Disadvantages include the limited depth to which microbes and metabolites can currently be interrogated, in comparison to metagenomics and metabolomics approaches, and the degree of abstraction necessary, leaving the quality of model predictions dependent on the validity of its simplifying assumptions. Thus, the model should be viewed as complementary to experimental work. There is clear potential for both microPop and the colonic expansion of the model to be grown, with inclusion of further metabolites and MFGs and further comparison to in vitro and in vivo data. The model has the potential to benefit microbiome research both by guiding experimental research through the provision of experimentally testable hypotheses, and in application to questions that cannot feasibly be addressed experimentally.The microbial community modelling tool microPop  models mBlautia hydrogenotrophica of Smith et al. [Desulfovibrio vulgaris model of Smith et al. [The main alterations to the microPop MFGs performed here involved the representation of hydrogenotrophs. microPop included hydrogenotrophic pathways in a methanogen and an acetogen MFG. Changes to the original methanogen MFG parameter values were made as detailed in Additional file h et al.  was usedh et al. , as wellwww.mathworks.com). SCFA and MFG measurements were converted into microPop units from information provided in the publications  and negatively charged ions . Moreover, it was assumed that the host buffers the colonic lumen via secretion of bicarbonate ions, absorption of SCFAs and secretion and absorption of CO2. Absorption of SCFAs is described in Sect. 2.3.3. Bicarbonate and CO2 was modelled to adhere to the equilibrium equation:pH variation based on the metabolism of the microbiota and host activity was identified as an important inclusion. Thus, the charge balance model structures of Batstone et al.  and the 2, 2, bicarbonate and H+ ions, respectively. Thus, as bicarbonate is secreted into the colonic lumen, it combines with H+ ions to form CO2 and H2O to balance the equilibrium equation. This balancing also occurs during CO2 secretion and absorption. The pH was then calculated from the concentration of H+ ions, where where −1 [The influx of substrates and metabolites into the model was limited to the first compartment, with the exception of mucin and bicarbonate. Rates of substrate inflow from dietary sources were taken as equal to those from experimental estimates in the literature , and the novel SRB MFG. Unless stated as changed specifically for microPop:Colon, all values used were those of the original model. For the initial microbial population sizes, 16S rRNA data from faecal samples were used, converted to microPop MFGs according to Kettle et al.  (Additiowww.mathworks.com) rather than R, the format for the original publication, for ease of code management. The availability of microPop functionality in both MATLAB and R should facilitate wider usage of the model. The mathematical structure and parameter values given in the supporting material of the microPop package were used to transition the tool between software. Upon completion, the MATLAB version was tested to ensure that its predictions were consistent with those of the R version. This testing was carried out for the pH static experiment displayed in Fig. Although microPop was used as the basis for microPop:Colon, the equations for microPop:Colon were implemented in MATLAB .The adaptations of the model to the human colonic environment described above were all carried out in the MATLAB environment. The code is available in the BioModels repository (Additional file 1: Contains supporting text and tables relevant to the Methods.Additional file 2: Contains additional figures and a table of parameters of model fit.Additional file 3: Contains the model data analysed.


Background. Because of their work, emergency workers, such as police officers (POs), are exposed to traumatic events on a daily basis. These experiences can have consequences in terms of physical and emotional stress. Primary attachment relationships affect the development of coping strategies for dealing with stressful events (primarily hyperactivating strategies in entangled adults and hypo-activating strategies in dismissing adults). In this study, we explored how POs describe the experience of traumatic accidents, the effects they reported and their coping strategies related to their attachment style. Methods. We used a quantitative-qualitative method. Thirty-nine POs were administered the Beck Depression Inventory, the Maslach Burnout Inventory and a semi-structured interview about traumatic events and reactions. Interviews were analyzed using Interpretative Phenomenological Analysis. Results. Traumatic events at work predominantly concerned aggressions, witnessing deaths, forced hospitalizations, and domestic violence involving children. POs with a responsible role were more likely than POs to use security-based strategies. Most POs narrated overactivation and deactivation strategies, which were associated with depressive symptoms, emotional exhaustion, and depersonalization. Conclusions. These results can be useful to improve trauma-informed interventions for POs based on their different attachment styles and coping strategies. Emergency workers are exposed to traumatic events that can have consequences in terms of physical and emotional stress. Although these workers may have developed a certain degree of tolerance, due, for example, to experience, this does not mean that they do not experience the consequences of trauma ,2,3. PolThis does not mean that all POs perceive these events as traumatic in the same way: life experiences, especially in early childhood, the presence or absence of support mechanisms, and environmental and genetic aspects are factors that determine the response to events ,17. For Another aspect that is strongly linked to an individual′s vulnerability to traumatic events is the coping strategy adopted. Coping is defined as “cognitive and behavioral efforts to manage specific external and internal demands that are appraised as taxing or exceeding the resources of the person”  (p. 141)Several studies have focused on the link between attachment and emotional well-being in facing critical accidents on military corps and public officers such as soldiers in the Gulf War , ambulanMore specifically, Shaver and Mikulincer  argue thThe objective of this exploratory research was to collect data on how POs describe the experience of traumatic accidents, the emotional consequences and the strategies they used to cope with these events. To better understand their strategies for dealing with the traumatic event, we used a quantitative-qualitative method. The quantitative data made it possible to collect the results of coping in terms of depressive symptoms and burn-out. For the collection of qualitative data, the chosen method was the narrative approach. In the narrative approach, attachment is considered an interpersonal motivational system that leads people to seek closeness and protection in situations of vulnerability. Through its activation the individual also develops the narrative schemes of the self and the ability to share his own stories. The concept of attachment in the strict sense was not used: to better adapt to the organizational context, the strategies for regulating emotions in relation to traumatic experiences were evaluated through interpretative phenomenological analysis.This study was approved by the University of Torino ethics committee (protocol number: 14526). This research conforms to the provisions of the Declaration of Helsinki , and allParticipants were assured of the anonymity of their responses through fulfilment of ethical guidelines for conducting interviews. Participation in the survey was voluntary, and participants did not receive any reward for their participation.-Beck Depression Inventory  is a se-Maslach Burnout Inventory  is a scThe participants were given a questionnaire consisting of the following scales:Following the questionnaire administration, in the same day, we proceeded with the administration of the in-depth interview. No participant dropped out after the questionnaire administration. The interviews were conducted by the first author, CC. The semi-structured interviews, lasting approximately 30 min, investigated the traumatic events connected to the working context with a trace that included both the analysis of potentially traumatic events attributable to routine duties , and the events with a high traumatic impact (example of question: “Do you think about the most traumatic event that has happened to you in the workplace. Do you remember how you reacted at that moment?”). For recording the interviews, consent was obtained from all individual participants, and in case of dissent to the recording, the narrative was collected through annotations faithful to what the participant told the interviewer.-Superficial reading of the transcripts was performed. It is advisable to read the interview several times and possibly, if available, to listen to the recording again. In this phase, the researcher can take notes and note their reflections, bearing in mind that each rereading could reveal new interpretative ideas. The researcher can focus on the content as well as on the use of language, trying to highlight the participant′s distinctive phrases or emotional responses.-Emerging themes were identified starting from the notes taken during the interview phase. Starting from the parts of the interview that have been highlighted, we tried to formulate a sentence (subtheme) that contains the psychological meaning of that particular salient segment of the interview.-Clustering of sub-themes was then performed. Links are sought between subthemes that are grouped under a label (theme) that provides a description of the given grouping. At this stage, all subthemes that do not fit into any of the clusters can be discarded .All recordings were transcribed verbatim and related transcripts were de-identified before analysis. All the portions of the interviews referred to the incidents described above were analyzed. To code the narrative interview, we used the Interpretative Phenomenological Analysis (IPA) method. IPA is a qualitative analysis method developed by Smith in 1990 , with a The analytical process was independently conducted by two members of the research team who are experts in psychopathology (GDF) and in organizational psychology (DAM) (Cohen’s k before reaching an agreement = 0.85 ). PossibStatistical analyses were performed by the first author, CC, using the statistical software SPSS, version 26 9. .Firstly, because of the small sample, we checked all the assumption needed to run the statistical analysis. We verified the assumption of normality through the analysis of the skewness and the kurtosis and through the Shapiro-Wilk test, explicitly recommended with small sample sizes .p < 0.05 was considered to be significantly different). Because of the categorical nature of the data, χ2 tests were used to evaluate the cooccurrence of gender and role with regards to the coping strategies. The effect size (Cramer’s V) was calculated to estimate the practical significance of the differences. As a post hoc test, standardized Pearson residuals (SPR) were determined for each cell to determine which cell differences contributed to the χ2 test results. SPRs with absolute values greater than 1.96 implied that the number of cases in that cell was significantly greater than would be supposed if the null hypotheses were true (in terms of both overrepresentation or underrepresentation), with a significance level of 0.05.Descriptive measures (means ± SD) were calculated for all test variables for all groups of participants. The t-test was performed to evaluate the statistical significance of EE, DP and PA subscales respect to the tool norms . A Tukey post hoc test was used. Estimates of effect size (Eta squared) were calculated to describe the proportion of total variability.The sample was composed of 39 out of 42 municipal police POs of the Municipality of Collegno. One subject was away from work due to illness at the time of administration and two POs refused to participate. The participation was voluntary and participants did not receive any compensation. Collegno has less than 50,000 inhabitants and is located in the metropolitan area of Turin, a city in the north of the country. Socio-demographic characteristics of the sample are shown in p > 0.05). Because there was a small-medium effect size (the η2 range was comprised between 0.08 and 0.37) the required sample size would be n = 159. As such, the outcome of the ANOVA should be interpreted with caution, as the results might be different with a larger sample size. Average scores for depressive symptoms and burnout are shown in t = 5.53, p < 0.01) and lower level of personal accomplishment .The assumption of normality for BDI, EE, DP and PA scores were satisfied for all the coping styles groups, as assessed by Shapiro-Wilk′s test (n = 15), to intervention in the event of death on the street or home (n = 12), to the forced hospitalization of subjects with psychopathologies (n = 5), and to interventions for domestic violence involving children (n = 3). Two subjects indicated excessive exposure to the media as a traumatic event, while one subject described the murder/suicide of a colleague, which occurred in another command, as a traumatic event. Six subjects identified more than one traumatic event.From the analysis of the transcripts, it appears that the traumas indicated by the POs participating in the research refer to the aggression suffered . Regarding age, the t-test did not show statistically significant differences between the average age and the use of trauma coping strategies .Trauma processing strategies were the subject of a subsequent analysis that aimed to highlight any statistically significant differences between the use of the three strategies that emerged from the textual analysis  and the socio-demographic variables gender, age, and role . Additiop < 0.001) and the DP subscale  = 7.05, p = 0.003). The Tukey post hoc test revealed that both hypo- and hyperactivating subjects exhibited greater scores on the EE and DP subscales compared to subjects who primarily used secure strategies. There was no significant difference between groups on the PA subscale. Regarding BDI, a statistically significant difference was found between groups  = 7.80, p = 0.002). The Tukey post hoc test revealed that both hypo- and hyperactivating subjects presented higher levels of depression than subjects who primarily used secure strategies.The ANOVA test highlights differences between groups in experiencing depressive symptoms and burnout . SignifiThe goal of this pilot research was to examine trauma management strategies based on safety and insecurity in POs. A generalization of the results is not warranted, due to the small sample involved. The first interesting result was related to the type of trauma indicated by the participants. In line with what emerged from the research of the authors , in thisThe hyperactivation strategy adopted by the POs involves exaggerating the perception of the severity of the danger and the implementation of a state of perennial vigilance. This strategy may lead the person to perceive minimal signs of disapproval, decreased interest or imminent abandonment. POs who adopt these strategies can have easy access to thoughts and emotions related to threatening situations and have difficulty keeping them under control. Furthermore, it can be easy for them to maintain contradictory cognitions of the past and present negative experiences in their working memory by mixing them together, creating a chaotic mental situation dominated by negative emotions . POs who use deactivation strategies, on an interpersonal level, strategically try to live with detachment to exercise control and leverage themselves . These sIn this work, our ultimate clinical aim was to give a contribution in tailoring efficient interventions for deal with trauma in POs. Before discussing which strategies and intervention plans can be used with this population, it is useful to note that no single strategy has proven most suitable for addressing this complex phenomenon. However, each context must be thoroughly examined to outline a possible intervention that can be conducted effectively. Therefore, each situation requires ad hoc treatment that accounts for all variables involved in the phenomenon.Although this project has an exploratory perspective, our indication is to provide, when possible, a context analysis to understand the emotional climate and the coping strategies of the POs involved in a critical incident. In fact, different stress management strategies emerge from the research and the same intervention can be useful for some subjects and detrimental for others.Scientific and clinical projects are going in that direction. For example, several study show how a debriefing intervention, after each traumatic event, can facilitate the processing of trauma ,60, justThis study opens up many questions on the prevention and management policies of work-related stress in POs, but it obviously has limitations. First, the sample number was small and the study was underpowered: for this reason, results must be interpreted with caution, as the outcomes might be different with an adequate sample size. Subjects who participated in this study worked in the same location, sharing traumatic events. This sharing can lead to a mechanism that allows you not to let go of the memory because the effects of the trauma are visible and occur in every day ,70. AnotThe data obtained herein can be used to better implement the method of selection of POs, the training dedicated to them at the moment of entry and supervision during the course of their work. In light of what has emerged, the hope is that intervention in cases of traumatic events can be done on the basis of the different attachment styles that characterize POs. This will improve the quality of life of the POs and allow adoption of adaptive strategies with positive repercussions in the work environment as well as the home environment.