On the other hand, biomedical application of graphene is a relatively new front with significant potential. Many recent reports have indicated that understanding of graphene-cell  interactions; particularly the cellular uptake mechanisms are still challenging. Therefore, use of graphene or graphene oxide properly embedded in suitable PLA matrices can positively impact and accelerate the growth, differentiation, and proliferation of stem cells, conceivably minimizing concerns over cytotoxicity of graphene. As such, PLA-graphene composites hold great promise in tissue engineering, regenerative medicine, and in other biomedical fields. However, since PLA is classified as a hard bio-polyester prone to hydrolysis, understanding and engineering of thermo-mechanical properties of PLA-graphene composites are very crucial for such cutting-edge applications. Hence, this review aims to present an overview of current advances in the preparation and applications of PLA-graphene composites and their properties with focus on various biomedical uses such as scaffolds, drug delivery, cancer therapy, and biological imaging, together with a brief discussion on the challenges and perspectives for future research in this field.Due to its biodegradable and bioabsorbable characteristics polylactic acid (PLA) has attracted considerable attention for numerous biomedical applications. Moreover, a number of tissue engineering problems for function restoration of impaired tissues have been addressed by using PLA and its copolymers due to their biocompatibility and distinctive mechanical properties. Recent studies on various stereocomplex formation between enantiomeric PLA, poly( The l-isomer is a biological metabolite and constitutes the main fraction of PLA derived from renewable sources since the majority of lactic acid from biological sources exists in this form [l- and d, l-enantiomers, PLA can crystallize in three forms . Thorough understanding of the intrinsic structural, thermal, and physicochemical properties of PLA polymers along with the knowledge of how such properties can be tuned and manipulated with nanomaterials have fueled remarkable biotechnological interest in PLA nanocomposites [Polylactic acid (PLA) polymers are synthesized and obtained from renewable agricultural resources by polymerization of lactide, which is the cyclic di-ester of lactic acid . For allhis form . Dependimposites ,5,6. Themposites  presentsmposites . Althougmposites ,10.co-glycolic acid) (PLGA) occurs by hydrolysis leading to metabolite monomers, lactic acid, and glycolic acid. Because these two monomers are endogenous and easily metabolized by the body via the Krebs cycle, a minimal systemic toxicity is associated with the use of PLGA as biomedical material and drug releasing vehicle [PLA polymers have already been demonstrated as surgical implant materials ,12,13, d vehicle .l-lactic acid interference screws were used for graft fixation during anterior cruciate ligament (ACL) reconstruction, the devices were reported to be mechanically weaker than their metallic counterparts and often fractured during implantation [According to Rasal et al. , PLA polantation . Secondlantation . Howeverantation . Moreoveantation ,27. Thirantation ,29. Noneantation  and blenantation . Stereo-antation .2/g), outstanding mechanical strength  and unparalleled thermal conductivity (~5000 W/m/K). As such, it is a highly popular nanoscale additive for reinforced biopolymers [Graphene, on the other hand, has been at the forefront in biotechnological applications ,34,35,36polymers . Biosafepolymers ,40,41. Ipolymers ,43.Among graphene derivatives, graphene oxide (GO) has been widely explored for in vitro and in vivo drug delivery and imaging, taking advantage of its high solubility and stability in physiological solutions, low cost and scalable production, and facile biological/chemical functionalization ,42,43,44As such, thermo-mechanical properties of PLA polymers are directly related to their biomedical performance when interfaced with biological systems, since these properties can be used to optimize important design criteria such as modulus, strength, morphology, crystallinity, biocompatibility, and, in turn, these properties can affect cell response, tissue regeneration, and in vivo degradation. Moreover, recent research indicates that thermal effects on the crystallinity of not only PLA polymers but also other bio-polyesters is very critical for cell biocompatibility and drug release dynamics . Since, One of the most important performance comparison criteria between biodegradable polymers and conventional oil-based polymers is thermal stability along with moisture retention issues. Although mechanical properties of PLA polymers match those of poly (PET) polyesters, for instance, their thermal stability is not as high as PET polymers . ThermalA comprehensive review by Tan et al.  illustram of homo-chiral crystals (160 °C). They argued that PLLA-rich sb-PLAs can be used as more robust and high-performance resins compared to PLA; minimizing the use of d-lactic acid which is more expensive than l-lactic acid.Hirata and Kimura  conductel-lactide), poly(l/d-lactide) and their blends with poly(d-lactide). The isothermal spherulitic crystal growth rate and its dependence on temperature were measured using tapping mode atomic force microscopy and ex-situ isothermal crystallization. Further, they also investigated the crystallization kinetics of blends of poly(l-lactide) and poly(l/d-lactide) with poly(d-lactide). The typical crystalline structure of PDLA polymer annealed at 100 °C can be seen in the atomic force microscope image in Yuryev et al.  studied l-lactic acid) chain. Thermally annealed specimens retained higher values of tensional and flexural modulus of elasticity, impact strength, and heat resistance. They also showed that while PDLLA and amorphous PLLA presented a heat resistance very near to their glass transition temperature (Tg), annealed PLLA demonstrated a better behavior in the sense that it was more stable at temperatures of 50 °C or higher, due to its crystallinity induced stability.Perego et al.  analyzedIn a highly cited work, Carrasco et al.  processeAs can be seen from this section, crystallization of PLA polymers is a very complex thermal process. Many factors such as post annealing, aging, stereocomplexation, cooling or heating rates, plasticizers not only play a significant role in the crystallization temperature but also in the shape, size, type, and density of the crystals that would nucleate and form, eventually determining the final thermomechanical properties of the polymer.The unique crystalline properties of PLA polymers render them attractive platforms for controlling cellular behavior. In fact, homo-composites of PLA polymers with different crystallinity or engineering PLA polymers with crystallinity gradients have been inspired by the occurrence of natural tissues presenting continuous variations of properties along one direction, such as ligament-to-bone, tendon-to-bone, and dentin-to-enamel interfaces ,58. The Strip-shaped blend films were annealed to allow PLLA to crystallize as shown in 4 cells/mL and kept in culture for periods up to two weeks. They concluded that cell viability was not affected by the different tested conditions. However, cell proliferation was increased in the high molecular weight amorphous samples and cells seemed to have higher adhesion patterns on semi-crystalline samples. They attributed these observations to different rates of integrin interaction with the substrate leading to different patterns of focal adhesion point formation. Sladago et al.  reportedLi et al.  used PLLThey used microscopy and image analysis to ascertain that the MC3T3-E1 cells spread out in a random fashion on the amorphous PLA. At 24 h post-seeding, MC3T3-E1 cells on both types of spherulite surfaces were elongated and aligned along the spherulite radius direction. For the banded spherulite surface with radial stripes and coupling annular grooves, the cell orientation and cell nuclear localization were related to the groove structure. With increasing time, this orientation preference was weaker. They further demonstrated that the patterning of the polymer crystallization structure provides important indicators for guiding cells to exhibit characteristic orientation and morphology especially in the early stages of regeneration.Using a novel high-throughput method for creating gradients in polymer crystallinity, Washburn et al.  demonstrPLA polymer-graphene nanocomposites have been increasingly gaining in popularity due to attractive features offered by both materials ,63. NoraWu et al.  conducteWang et al.  preparedc) was increased in samples due to better dispersion and grafting reaction between GnPs and PLA. Isothermal tests also showed that commencement of the crystallization time was affected by the functionalization and then decreased. They also concluded that the growth mechanism of crystallization did not change significantly.Manafi et al.  preparedc) studied by Zhao [The effects of GO with polar groups and functionalized graphene oxide (fGO) with non-polar groups on the isothermal crystallization of PLLA were studied by Zhao et al. . Functio by Zhao .Sun and He  preparedc of 135 °C. They observed a diffuse scattering ring in the first pattern (t = 0 min) for all the samples, indicating no crystals could have survived in the melt. With increasing crystallization time, the isotropic lattice planes, i.e., (200)/(110) reflection, can be observed and gradually sharpen until the completion of crystallization, correlating with the formation and growth of the PLA crystals. In contrast to neat PLA, the advent of ultrasonically treated rGO shortens the appearance time of the diffraction peak remarkably , demonstrating the superb nucleation ability of rGO.Liang et al.  studied Their main conclusion was that both rGOw and rGOp could serve as heterogeneous nucleation agents for PLA, decreasing the induction period of crystallization and accelerating the overall crystallization rate. Prolonged ultrasound time, however, gradually enhanced the nucleation ability of rGOw but suppressed that of RGOp.Xu et al.  fabricatReview of the literature on PLA-graphene nanocomposites in the form of free standing films produced either by solvent processing or by melt molding/extrusion indicates that there is still a significant lack of established recipe or nanocomposite fabrication protocol that could be used to enhance the elastic modulus or elongation at break values of PLA polymers using graphene-based materials. This is due to the fact that graphene comes as filler in the form of many stacked layers , which is influenced by the synthesis history. Different lateral size and thickness distribution exist in all these “commercially available” graphene products. Separately, graphene oxide or reduced graphene oxide introduces other parameters such as surface reactive sites and polarity effects. However, most recent reports highlight the necessity to functionalize graphene surfaces or use graphene oxide with graft chemistry  in orderCataldi et al.  fabricatIn the case of PLA, however, both large multi- and few-layer GnPs caused up to 35% increase in elastic (Young’s) modulus compared to other model 2D or 3D fillers; see Cao et al.  producedThey reported that even for such a small percentage of GNS the reinforcing effect is rather significant: In other words, 0.2 wt% GNS incorporation leads to a 26% increase in tensile strength and a 18% raise in Young’s modulus. In their work , Young’sMarques et al.  reportedθ of 17° and 19° corresponding to a typical PLLA pseudo-orthorhombic α structure. These peaks are also present in the XRD pattern of the nanocomposites  at 30 °C increased from 2.2 GPa to 4.1 GPa with the addition of 20 wt% GO-g-PDLA (containing 1 wt% GO). The large mechanical enhancement was ascribed to the reinforcement of GO on the PLLA–PDLA stereocomplex networks. Similarly, this effect is more significant at 195 °C, particularly after 10 wt% PDLA inclusion. They argued that existence of GO can be regarded as the landscape of the ordering of SC helices surrounding the PLA/GO interface. At last, the stereocomplex crystallite, SC, could begin to grow from the GO surface with the hydrogen bonding inter-chain interactions between PLLA and PDLA and finally an SC network would form with the link of PLA chains and enhancement of GO as schematically shown in Xu et al.  demonstrIn biomedicine, polymeric muscle or bone scaffolds must have an appropriate porosity range with an interconnected and open porosity, and have a biodegradable rate and mechanical properties that match the injured tissue. PLA polymers have been extensively studied for this purpose . As expeε-caprolactone (PCL) copolymer, designated as PLC. Exceptional wettability of PLC on graphene foam resulted in PLC forming a thin uniform coating over the graphene foam. This effective wettability allowed the PLC to fill voids and defects that had been present in the graphene foam. The healing of defects in conjunction with the formation of PLC bridges caused enhanced strength and ductility in the GrF-PLC scaffold. They conducted nano-indentation and macroscale tensile tests and demonstrated that significant increase in strength in both compression and tension at multiple scales occurred, as shown in Nieto et al.  demonstrChen et al.  producedThermal stability was also shown to be improved, with 90 °C increase in degradation temperature as well as the new formation of better crystalline structures. They also conducted cell culturing experiments and results revealed excellent cell viability e–h of 3DChen et al.  further Staphylococcus aureus and the Gram-negative Escherichia coli. They attributed this to the inherent antibacterial property of GO sheets with high specific surface area  (PLGA) embedded with GO nanosheets by electrospinning, and investigated their physiochemical properties including morphological, surface-chemical, mechanical, and thermomechanical properties. They showed a 2-fold increase in tensile modulus as compared to that of pristine PLGA nanofibers. Storage modulus and glass transition temperatures of the PLGA/GO (2 wt%) nanocomposites were much higher than those of PLGA nanofibers and PLGA/GO (1 wt%) nanocomposite nanofibers, as shown in Yoon et al.  construcInterestingly they claimed that the incorporation of GO nanosheets according to concentration led to effective enhancement of their mechanical and thermomechanical properties compared to those of pristine PLGA nanofibers. This enhancement was attributed to stronger interfacial interactions caused by stronger chemical bonding between the PLGA and GO nanosheets and the axial alignment of the GO nanosheets embedded nanocomposite nanofibers. They also showed that nanocomposite nanofibers were more hydrophilic than PLGA nanofibers. In order to investigate the effects of GO nanosheets on nanocomposite biocompatibility, PC 12 neuronal cells were cultured for two days on various nanofibrous scaffolds, and the proliferation and viability of the cells were measured. Biocompatibility tests c–f showeg-PEG were incorporated in PLA polymer as reinforcing fillers to fabricate nanofibrous scaffolds of PLA, PLA/GO, and PLA/GO-g-PEG, which were prepared by means of electrospinning. They measured decreases in complex viscosity for PLA/GO-g-PEG electrospinning suspensions and attributed these observations to the plasticizing effect of the grafted PEG molecules on the surface of GO.Zhang et al.  surface g-PEG had a greater influence than GO in improving the thermal stability of PLA. Tensile tests showed that the addition of GO and GO-g-PEG in PLA achieved significantly improved tensile stress, as shown in g-PEG was more effective in reinforcing PLA than GO due to the grafted PEG chains, which improved the filler dispersion as well as the adhesion between GO and PLA. Moreover, PLA/GO and PLA/GO-g-PEG composite nanofibrous scaffolds were found to be non-toxic to NIH 3T3 cells and were capable of supporting cell attachment and growth  and Gram negative bacteria Escherichia coli (E. coli) as well. Although promising results were reported by Pal et al. [Pal et al.  formulatl et al. , furtherLuo et al.  fabricat2 as blowing agent. PLA/GO nanocomposite foams with oriented and highly elongated cell structure were prepared for the first time in this study. They prepared the nanocomposites by a solution mixing method at various GO contents. The thermal and rheological properties, and CO2 absorption ability of the composites, were investigated and compared with neat PLA. It was found that the incorporation of GO improved the crystallinity of the PLA matrix. The addition of GO enhanced the storage modulus, loss modulus, and complex viscosity of the PLA matrix as well, and the improvements increased with increase of GO content. The unidirectional microcellular foaming revealed that the PLA/GO nanocomposites had the ability to form highly elongated cell structure. Compared to neat PLA, the relatively high GO content  in PLA/GO nanocomposites showed significantly higher expansion ratio, average foam cell size, and cell diameter ratio in the long axis and minor axis. These behaviors were caused by the enhanced CO2 absorption rate, PLA/GO matrix viscosity, and the unidirectional foaming process. They did not demonstrate biocompatibility or discuss any potential biomedical applications although their cellular architectures were claimed to be very suitable as 3D biomedical scaffolds.Kuang et al.  investigAlthough PLA polymer is regarded as one of the most suitable biopolymers for biomedical applications with many successful in vitro and in vivo demonstrations to date, it is now understood that homo-composites of PLA polymers are not only thermally and mechanically superior to pure PLA but also perform better as drug release platforms . In otheOn the other hand, clearly, graphene has the ability to modulate crystallinity and the final thermomechanical properties of PLA polymers including SCs. However, the effectiveness lies in the proper surface functionalization of graphene of GO, a priori. As such, compatibilization of graphene or graphene derivatives with PLA SCs can yet produce significant improvements in the thermomechnical properties of SCs . To achiAn outstanding biomedical issue that still needs to be addressed is the fact that various chemical pathways and agents used or proposed for surface functionalization or grafting graphene or graphene oxide nanosheets so that they can be inserted into PLA matrices must not yield cytotoxicity. Furthermore, their fate after passing through the cell membranes should be carefully evaluated. This issue is still open; however, encouraging new results are being published ,96. SimiSo far many published works on PLA/graphene composites exclusively focus either on the thermomechanical properties or on cell compatibility and behavior. Hence, none of them can be explicitly singled out as an ideal candidate for clinical applications. In fact, both properties are interrelated as was shown by some recent studies on the effect of PLA crystallinity on cell proliferation. Therefore, it is suggested that future studies on PLA-graphene systems should focus on surface functionalization of graphene and graphene oxide with biomacromolecules and incorporation of these modified graphene nanoflakes into PLA polymers, particularly into PLA stereocomplexes. The characterization should clearly demonstrate changes in crystallinity, thermomechanical properties due to functionalized graphene addition, and how this translates into cell proliferation and cytocompatibility compared to simple PLA polymer/graphene systems.Since PLA polymers can be processed with ease in many different ways such as solution, spinning, extrusion, and injection, they offer unique possibilities to produce graphene–PLA nanocomposites with higher-order 3D architectures such as sponge-like macroporous scaffolds, nanofiber mats or hollow micrometer-sized spheres, which are ideal platforms for surgical reconstruction and drug delivery . AlthougThe future seems to be the combination of PLA stereocomplexes with graphene and GO rather than PLA as PLA stereocomplexes are not only thermomechanically superior but also more flexible in terms of interfacial engineering, opening up many promising additional applications in delivery of drugs, genes, proteins, growth factors, and other biomolecules for cancer and other disease therapies. As seen, advances in PLA/graphene material systems are growing rapidly and this trend, the author believes, will continue and even speed up in the years to come.


IntroductionEmergency departments (EDs) see a surge of intoxicated patients during large public summer events. These patients can be distracting and complicated for ED staff to care for.MethodsWe developed two cases to prepare emergency department staff for an anticipated surge of patients related to a large music festival that occurs proximal to our pediatric hospital. We developed and performed cases of simulated patients with alcohol intoxication and methylenedioxymethamphetamine (MDMA) ingestion to review medical management of these patients, as well as to review many of the social aspects of the cases. We surveyed simulation (sim) session participants to assess the degree to which the sessions were helpful and to glean ideas on how to improve sessions for future use.ResultsOver the course of two years, we have hosted eight simulations, for a total of 57 participants comprising various healthcare roles. We achieved an 85% response rate in the post-simulation surveys. The sessions were overall well-received and left participants feeling better prepared to care for intoxicated patients.DiscussionDespite having a large number of staff from many disciplines working varied schedules, we were able to provide simulation training to many of them in preparation for an expected surge of intoxicated patients. Participants appreciated the training and gave feedback to improve sessions in the future. Emergency departments (EDs) see a surge of intoxicated adolescent patients during summer festivals, concerts, and other large public events. Our hospital, located in downtown Chicago, sees a particularly large increase in patient volume during the weekend coinciding with the annual Lollapalooza music festival. Lollapalooza, which began as a small concert series 25 years ago, has turned into an enormous local attraction. In 2016, there were an estimated 400,000 people in attendance, and approximately 20,000 of them were adolescents. Aggregate data from Chicago’s children’s hospitals indicate that in 2014 over 100 children were seen in pediatric EDs with Lollapalooza-related complaints; this number decreased to 88 in 2015 . In anotThe surge of intoxicated teenagers that presents to the ED from Lollapalooza each summer is disruptive to the usual patient flow in the ED and requires additional staffing, including increased physicians, nurses, social workers, and environmental staff. Although there are several studies examining ED preparations for large events , most of this data focuses on how the event itself will communicate with local hospitals to coordinate care of attendees in need -8. ThereOur target audience was all clinical providers in the ED, at all training levels. We reached medical students, residents, attending physicians, nurses, and paramedics. In our ED, the purpose of these simulation sessions was specifically to prepare for a known influx of complicated intoxicated patients. These same sessions could be used in any other ED, either to prepare for a predicted surge of intoxicated patients or simply to review these interesting and dangerous toxidromes at any time of the year.We developed two cases to simulate patients with alcohol intoxication and methylenedioxymethamphetamine  (MDMA) ingestion. These agents were chosen for two different reasons. Alcohol was chosen because it is the most ubiquitous recreational substance seen in intoxicated patients coming from Lollapalooza. While most providers have experience treating alcohol intoxication, we wanted to highlight some of the unique issues associated with the concert during this case, including that many teenagers carry fake identification cards to the event and can therefore be difficult to identify, as well as the possibility of having other substances “slipped into their drink”, as they are often obtaining alcohol from other concert-goers and not from legal vendors. MDMA was chosen because, although it is seen less commonly, its clinical presentation is somewhat unusual and its clinical consequences tend to be much more severe. In addition, MDMA toxicity can involve hyperthermia, which can be a complication from the usual weather during the August concert, and this allows us to discuss cooling measures due to any cause. The simulation sessions and the subsequent debriefing sessions were tailored over time to address gaps in knowledge as well as preferences and suggestions of participants.The two simulation cases were developed based on the learning objectives outlined above. The cases are outlined in Tables Equipment and environmentSimulation sessions took place in the ED, specifically in the resuscitation bays. This location was chosen because of its proximity to the learners during their typical work day and because it is nearly identical to the rooms that are used for actual patient care. This allowed the sessions to appear very realistic relative to real patient care. The equipment required included monitors, intravenous (IV) insertion equipment, and other items that are commonly found in a resuscitation bay. We did not use a manikin for our simulations, but rather used a standardized patient (SP) who was dressed to appear to be a concert-goer.PersonnelAs mentioned above, we used an SP in lieu of a simulator for these sessions. We felt that this would provide the most realistic experience for the team working through the case. The SP each summer has been an intern with the simulation program and is a high school or college student. The SP dressed as a festival-goer and practiced being intoxicated and agitated with the simulation team prior to the actual sessions. Another person (either a staff member or a second intern) acted as the older sibling for the alcohol ingestion case to provide a more realistic social environment for the simulation. There were two to three facilitators leading the case, including one person designated to run the simulated monitors. Everyone else involved were learners.Sessions were scheduled during the two weeks prior to the festival. We knew it would be challenging to recruit participants at times that worked well for everyone. The nature of the ED shift schedule does not allow for a single time of day that will accommodate everyone. Therefore, we conducted multiple sessions at different times of day (including very early mornings and very late nights) over the course of two weeks in an effort to maximize participation, especially for night-shift nurses. Sessions were targeted toward staff who would be working during the weekend of the festival. Staff  actively working a shift were invited to participate and were notified at the start of their shift that the simulation would be occurring. The leaders in charge of staffing tried to coordinate assignments in order to allow staff who would be present during the festival to attend the simulations, while those who were not working the festival weekend continued with usual patient care in the ED. In addition, physicians who were scheduled to work during the festival weekend were invited via email to attend a session outside of their scheduled shift times. Medical students working in the ED and in the urgent care center were invited to participate as observers. In order to quantify the quality and effect of the simulation sessions, we administered a survey after the simulations sessions to all participants .AssessmentFollowing the simulation sessions, participants were offered the opportunity to evaluate the session using a standardized survey Table . The surDebriefingAt the conclusion of the cases, a debriefing session was held with all of the learners and the two to three leaders of the session. We discussed general topics such as how everyone felt about the session, what questions came up, and how the group seemed to interact in terms of communication and teamwork. We also provided learners with a handout of tips and learning points related to the music festival, ingestions of common substances seen at events like this, and basic management strategies. This handout Table  was alsoIn total over two years, we hosted eight simulation sessions, comprising 16 case scenarios (two cases per session). We had 33 participants in the first year and 24 participants in the second year. The groups comprised approximately two-thirds nurses and paramedics and one-third residents and attendings. There were also several medical students who attended, participating only as observers.We achieved an 85% response rate from participants on the survey . Overall, the sessions seemed to be very well-received, and learners were excited to participate. Of all participants in the simulation sessions, 80% reported that they had at least one year of experience taking care of intoxicated patients from the summer music festival. We asked participants to rank statements on a Likert scale of 1 to 5 . The results from this section of the survey are shown in Table Additionally, we asked participants for specific suggestions for improvements. While many responded that they did not have any ideas for improvements, several suggestions were made, and these were incorporated into the sessions during our second year of this program. Some examples of suggestions are shown in Table The initial design of the simulation sessions was based almost entirely on addressing medical management of patients with acute alcohol intoxication. There was little focus on the social aspects of care or the pathophysiologic mechanisms of possible ingested substances and the reasons for various management strategies. While we felt that our simulation sessions had helped prepare providers for the medical needs of the patients, we knew that there were more dimensions to patient care that could be better addressed in future sessions. Based on the suggestions from the pilot year, we made changes and additions to the second year’s simulations. Representatives from our social work department helped to develop a pathway for how to identify patients who were not carrying any formal form of identification . We also made the “tip sheet” more robust to review more pathophysiology. We spent a longer time during debriefing sessions reviewing the reasoning for various medical interventions and discussing possible complications of intoxications that may not have come up during the scenario itself.The results of our simulation sessions, in the form of subjective assessments by the participants of the perceived benefit of the sessions, was overall quite positive. The sessions addressed the major issues that our ED faces during the Lollapalooza weekend, i.e. an influx of unusually intoxicated patients. While it is impossible to objectively quantify the impact of the simulation sessions on individual patient care experience, we have found that, subjectively, participants seem quite satisfied with their experience. As noted above, participants report that they feel more prepared to take care of intoxicated patients after taking part in the simulation sessions.A benefit of the sessions that we did not initially anticipate but have noticed upon reflection is that the simulation sessions serve as a form of a team-building experience in the days leading up to the festival weekend. We specifically enlist providers who are scheduled to work during the festival to participate in the simulation sessions. This allows learners to focus on material that is relevant to their upcoming shifts in the ED and provides an opportunity for providers to practice being on a team together. Teammates build camaraderie and trust, so that when the patient surge arrives, everyone feels like they are working on a team that can communicate effectively.Challenges/barriersPreparing for a festival weekend using simulation sessions has its fair share of challenges. Running simulation sessions in a busy ED and trying to coordinate the timing of sessions with the providers who need the training the most is difficult. We are fortunate to have many providers who are willing to stay late or arrive early in order to participate in this valuable learning experience. Scheduling time and space will continue to be a barrier and could be a challenge to implement the session in other locations where there isn’t robust support for simulation education. Finalizing and announcing the schedule well in advance of the planned sessions has been helpful in circumventing this challenge.Another challenge common to all simulation education is the realistic quality of the patient and the flow of the session. We have invested a great deal of effort to make our festival preparation simulation sessions as high-fidelity as possible. Using an SP instead of a manikin, as well as a live confederate to act as a friend or family member, is a great step toward making these sessions realistic. We’ve been fortunate to have great enthusiasm from our interns who have played the part of the drunk teenager. Not all hospitals or departments will have the same fortune of having such enthusiastic and available SPs.Future changes/revisionsWe plan to continue running the festival-preparations annually, as they have been very well-received, helpful, and fun. The basic content of these cases  will remain the same, but we will continue to incorporate suggestions from participants in order to tailor the education sessions to the needs of the learners. We plan to re-administer the survey each year with the questions altered slightly and space asking for more specific feedback.In preparation for a known surge of intoxicated teenagers related to a summer music festival, we developed and carried out two simulation sessions for use with a multidisciplinary team within the pediatric ED. Despite having a large number of staff from many disciplines working varied schedules, we were able to provide helpful simulation training to many participants. Participants appreciated the training and gave feedback to improve sessions for the future. These simulation cases could be used in a wide variety of other ED settings, either in preparation for a predicted surge of intoxicated patients or simply to review these interesting and dangerous toxidromes at any time of year.


Cervical cancer elevated the expression of PD-1 and PD-L1 in mRNA level. PD-1 expression in peripheral blood of cervical cancer patients was related with tumor differentiation, lymph node metastasis, and invasiveness. PD-1/PD-L1 pathway inhibited lymphocyte proliferation but enhanced the secretion of IL-10 and TGF-β in vitro. In summary, our findings demonstrate that elevated levels of PD-1/PD-L1, TGF-β, and IL-10 in peripheral blood of cervical cancer patients may negatively regulate immune response against cervical cancer cells and contribute to the progression of cervical cancer. Therefore, PD-1/PD-L1 pathway may become an immunotherapy target in the future.The present study is to measure the expression of programmed death-1 (PD-1) and programmed death ligand-1 (PD-L1), as well as its clinical significance in cervical cancer patients. Our results showed that different T cell subsets in patients with cervical cancer had high expression of PD-1, and DCs had high expression of PD-L1. High expression of PD-1 on Treg cells in cervical cancer patients facilitated the production of TGF- Cervical cancer has the second highest morbidity and mortality rates among all female genital tract malignant tumors . SurgeryProgrammed death-l (PD-1) is a recently discovered costimulatory molecule on the surface of T cells that binds with PD-ligand to conduct inhibitory second signals. Programmed death ligand-1 (PD-L1) is a member of costimulatory signal B7 family and plays an important role in tumor immune responses . PD-L1 iA total of 78 patients  who were first diagnosed with cervical cancer by colposcopy pathological examination at our hospital between January 2010 and October 2014 were included in the present study  . AnotherμL) were mixed with APC-CD4, PECy7-CD25, PE-PD-1, and FITC-CD8 antibodies (20 μL each) and APC-CD4, PECy7-CD25, PE-IgG, and FITC-CD8 antibodies (20 μL each), respectively. Then, the mixtures were shaken before incubation at room temperature for 15 minutes in the dark. Afterwards, the mixtures were washed with phosphate-buffered saline (PBS) twice before adding 400 μL PBS to resuspend the cells. For the detection of PD-L1, one aliquot of PBMCs (20 μL) was mixed with PERCP-CD11c and PE-PD-L1 antibodies (20 μL each), and the other aliquot of PBMCs (20 μL) was mixed with PERCP-CD11c and PE-IgG (20 μL each). After shaking, the mixtures were incubated at room temperature for 15 minutes in the dark before washing with PBS twice. Then, 400 μL PBS was added to resuspend the cells. After the samples were prepared, they were subjected to flow cytometry using FACS Aria II  for the detection of PD-1 expression on CD4+ and CD8+T cell surface and PD-L1 expression on dendritic cell (DC) surface.Peripheral blood mononuclear cells (PBMCs) were separated from 5 mL venous blood using Ficoll-Hypaque density gradient centrifugation. For the detection of PD-1, two aliquots of PBMCs  10, and interferon- (IFN-) γ in serum were determined using ELISA kits  according to the manufacturer's manuals. The optical density at 450 nm was measured using a reader .The contents of transforming growth factor- (TGF-) β-actin (233 bp) were TAGGCGGACTGTTACTGAGC (upstream) and TGCTCCAACCAACTGCTGTC (downstream). The PCR reaction system (20 μL) was made using SYBR-Premix Ex TaqTM II according to the manufacturer's manual . PCR reaction conditions were denaturation at 95°C for 30 s, followed by 40 cycles of 95°C for 5 s and 60°C for 30 s. The data were analyzed using iQ520 Standard Edition Optical System Software V2.0 . β-actin was used as internal control. The 2−ΔΔCt method was used to determine the cycle number Ct value corresponding to a specific fluorescence threshold and to quantify the target genes. Experiments were repeated for at least 3 times. The level of mRNA was expressed as the ratio of target gene against β-actin.Peripheral blood (5 mL) was collected from fasting healthy subjects and patients in the morning and plasma was extracted. Total RNA was extracted from PBMC of three groups using TRIzol . Synthesis of cDNA first strand was performed using Fermentas kit  according to the manufacturer's protocols. The sequences of primers for PD-1 (289 bp) were TGCAGCTTCTCCAACACATC (upstream) and CTGCCCTTCTCTCTGTCACC (downstream). The sequences of primers for PD-L1 (101 bp) were CCTGGAGGTTTCGAGATTCA (upstream) and GGCAAAGCCAAGGTACTCC (downstream). The sequences of primers for 6 cells/mL using RPMI-1640 medium. Then, 100 μL cell suspension was added into 96-well culture plates (1 × 105 cells/well) for cultivation of 72 h. To block PD-1/PD-L1 pathway, anti-PD-L1 antibody  was added before incubation for 72 h. The cells were divided into normal control group, control + anti-PD-L1 antibody group, CIN group, CIN + anti-PD-L1 antibody group, cervical cancer group, and cervical cancer + anti-PD-L1 antibody group. Stimulator ConA was added into the medium , followed by incubation at 37°C in 5% CO2 for 72 h. MTT assay was performed to analyze lymphocyte proliferation. Culture supernatants from each group were subjected to CBA assay for the determination of IL-10 and TGF-β levels.Lymphocytes and DCs separated from cervical tissues were labeled with anti-CD3 antibody  and anti-CD11c antibody . Lymphocytes (CD3+) and DCs (CD11c+) were separated using MACS system . The density of cells was adjusted to 1 × 10t-test. Differences between groups were compared using analysis of variance. Comparison among groups was performed using χ2 test.All results were analyzed using SPSS 16.0 statistical software . The data were expressed as means ± standard deviations. Intergroup comparison of ages was performed using P > 0.05)   . In cervical cancer patients, the levels of TGF-β and IL-10 were significantly enhanced, and the level of IFN-γ was significantly reduced  and was negatively correlated with IFN-γ (r = −0.421)  . These rP < 0.05)  . The res+ on CD8+T cells, we studied clinical characteristics such as age, tumor staging, histological types, tumor differentiation, lymph node metastasis, tumor diameter, invasion depth, and tumor metastasis. The data showed that the expression of PD-1 in CD8+T was related with tumor differentiation, lymph node metastasis, and tumor metastasis (P < 0.05), but not age, tumor staging, histological types, tumor diameter, or invasion depth (P > 0.05)  . The resβ, PD-L1 was blocked using anti-PD-L1 and stimulated by ConA. MTT assay showed that lymphocyte proliferation in cervical cancer group and CIN group was significantly lower than control group (P < 0.05). However, blockade of PD-L1 in cervical cancer group significantly enhanced lymphocyte proliferation (P < 0.05) . After addition of anti-PD-L1 antibody, the levels of IL-10 and TGF-β were significantly reduced (P < 0.05) but still significantly higher than those in control (P < 0.05)  . CBA ass Figures . These rβ and IL-10 are elevated, consistent with the results by Yang et al. Further study shows that PD-1 expression on the surface of CD4+T and CD8+T cells, PD-L1 expression on DC surface, and mRNA expression of PD-1 and PD-L1 are significantly enhanced in cervical cancer patients, being higher than that in CIN group. As the development of cervical lesions, the level of PD-1 is elevated, suggesting that PD-1/PD-L1 expression is closely related with the development of cervical lesions. PD-1/PD-L1 signaling pathway may facilitate the occurrence of cervical cancer by inhibiting the immune functions of T cells.PD-1 is an important negative immune regulatory molecule belonging to CD28/CTLA-4 family. The extracellular IgV-like domain of PD-1 contains four important N-linked glycosylation sites that can bind with its ligands PD-L1 or PD-L2. It plays a regulatory role in immune responses by conducting inhibitory signals via immunoreceptor tyrosine-based inhibition motif . Yang etHamanishi et al. report that PD-1 expression and CD8+T infiltration degree in ovarian cancer are negatively correlated with the prognosis of patients . Shi et +T cells and PD-L1+APCs, leading to the development and metastasis of cervical cancer [We discover that the increase of PD-1+CD8+T is correlated with tumor differentiation, lymph node metastasis, and tumor metastasis. High expression of PD-1 in CD8+T cells may inhibit the scavenging effect of CD8+T cells on tumor cells. Therefore, tumor proliferation is promoted and invasion and metastasis occur. Heeren et al. claim that lymph node metastasis of cervical cancer is correlated with the increase of PD-1l cancer .β and IL-10 can also help antigen-presenting cells express PD-L1 via STAT-3 to exert negative regulation effect [β and IL-10 are elevated while that of IFN-γ is reduced in cervical cancer. Correlation analysis shows that PD-1 expression in Treg cells is positively correlated with TGF-β and IL-10 but negatively correlated with IFN-γ, suggesting that PD-1/PD-L1 participates in the inhibition mechanism of Treg cells via TGF-β and IL-10. It is speculated that PD-1/PD-L1 signaling pathway has potential effect in regulating the immune suppression function of Treg cells in cervical cancer patients, leading to the malignancy of the disease.Our previous studies demonstrate that Treg cells are increased as the aggravation of cervical cancer lesions. We speculate that Treg cells play important roles in immune evasion of tumor cells , 18. Anon effect . After bn effect . The preγ. These facts support the speculation that PD-1/PD-L1 pathway blocking therapy can be used to enhance antitumor immunity [β is reduced after blocking of PD-L1. Yang et al. report that PD-1/PD-L1 pathway inhibits cellular immunity, leading to the occurrence and development of CIN [β and IL-10, and results in the proliferation of differentiation of Tregs in cervical cancer microenvironment, finally leading to the escape of tumor cells from immune system. PD-L1 expression in tumor cells enhances the apoptosis of antigen-specific T cells. Therefore, blocking of PD-L1 reduces T cell apoptosis. Recent studies show that depletion of tumor-infiltrating lymphocytes in tumor microenvironment is correlated with PD-L1 secreted by tumor cells or tumor-derived myeloid cells. Blocking of PD-1/PD-L1 signaling pathway enhances the function of effector CD8+T cells, inhibits the functions of Treg cells and myeloid-derived suppressor cells, and increases the antitumor immunity effect [The study also shows that PD-L1 on DC cells is capable of inhibiting T cell activation and lysing tumor cells or sometimes leads to the apoptosis of tumor-specific T cells. Blocking of PD-L1 enhances the efficacy of immune therapy. A study shows that PD-L1 positive P815 tumor cells resist immune therapy, but blocking of PD-L1 restores the effect of anti-CD137 monoclonal antibody therapy . PD-L1 iimmunity , 28. Usit of CIN . Our resy effect –31. Therβ and IL-10, leading to the occurrence of cervical cancer. The present study provides a new idea that blocking of PD-1/PD-L1 signaling pathways using PD-1 or PD-L1 antibodies may provide a therapeutic method in the immune treatment of cervical cancer.In summary, the present study finds that upregulation of PD-1 on T cells and PD-L1 on DCs in cervical cancer may inhibit T cell proliferation and function in tumor microenvironment, leading to immune suppression that facilitates the growth and metastasis of tumors. The results of relevance between changes of PD-1/PD-L1 and Treg cells demonstrate that PD-1/PD-L1 signaling pathway may exert its immune suppression effect via Treg cells and its factors TGF-


A new concept in the formulation of hybrid nanostructured materials combining high quality graphene 3D supported by Nickel foam and polyporphyrins for visible light photocatalytic application is here reported. Our innovative approach involves the development of a freestanding device able to: i) offer a high surface area to bind the photosensitizers by π-π interactions, and ii) enhance stability and photocatalytic efficiency by using cyclic porphyrin polymers. For these purposes, homo- and co-polymerization reactions by using different porphyrin (free or zinc complexed) monomers were performed. The microscopic structures and morphology of graphene polymer nanocomposites were investigated by using Scanning Electron Microscopy (SEM), X-ray photoelectron spectroscopy (XPS) and Atomic Force Microscopy (AFM). Finally, photocatalytic activity under visible light irradiation of the obtained nanocomposites was tested, by using methylene blue (MB) as organic pollutant. The obtained data suggested that hindered cyclic polymeric structures stacked on graphene surface by non-covalent interactions, restrict the formation of non photoactive aggregates and, as a consequence, induce an enhancement of photocatalytic activity. Remarkably, our systems show a degradation efficiency in the visible-light range much higher than other similar devices containing nanoporphyrin units reported in literature. Indeed, the combination of graphene with photoactive materials aims to strongly improve the photocatalytic performance of the formulated systems by boosting the separation and transfer of photo-generated charges, which constitutes a critical step in photocatalytic reactions. As it turns out, the merging of the excellent visible-light absorption abilities of organic photosensitizers with the charge transfer properties of graphene-based materials  represents the cutting-edge on water treatment technology4. Moreover, the low cost, eco-friendliness, flexibility and versatility of the molecular design of these basic organic molecules constitute appealing features, both environmentally and economically.The design of graphene-based hybrid nanomaterials for photocatalytic applications is one of the most promising routes in the field of water remediation5. As thoroughly reported in the literature, the chemical structures of porphyrins, as well as the sizes and morphologies of their self-assembly aggregates, negatively influence their photocatalytic efficiency8, being limited by the fast recombination of photo-induced electron-hole pairs and the low photo-stability of porphyrins themselves. Indeed, the latters tend to undergo photobleaching. In spite of these limitations, the self-assembly of nano-porphyrins have been recently proven to explicate great potential in visible-light photocatalytic applications, promoting a boost of dye degradation efficiencies5. As reported by Guo et al., differences in molecular packing lead to morphology-dependent catalytic performance. In particular, a distinct photocatalytic performance is observed whenever a fibrous zinc-tetra(4-pyridyl)porphyrin nanostructure is used with respect to the spherical one in the degradation of organic pollutants6. Similar findings have been reported for nanostructured meso tetra(4-carboxyphenyl)-porphyrins (TCPP), suggesting that porphyrins molecules existing in a total J-aggregation facilitate the electron transfer process that prolongs the life-time of the excited state and, therefore, the photocatalytic performance9.Among these, porphyrin molecules have shown great potential in visible-light photocatalytic applications because of their large extinction molar coefficient in the visible-light region and the well-defined organic structures with controllable size and morphology17. Some complications arise from the use of graphene-based materials as co-catalysts. In fact, although these materials generate the benefits discussed above, some tricky features have to be taken into account during the photodegradation processes, such as the “shielding effect” as well as the radical scavenger activity. The first phenomenon is induced by the high weight addition of graphene-based materials as co-catalyst. Due to their opacity, a weakening of the light irradiation depth through the graphene-based composites restricts the efficiency of graphene in promoting the photoactivity18. This intrinsic negative effect imposes a weight addition ratio of graphene derivatives into the composite lower than 5%. However, greater amounts of carbon materials would be necessary to inhibit the recombination of electron-hole pairs photogenerated by the photocatalyst18. In covalently graphene oxide (GO) and reduced graphene oxide (rGO) functionalized composites, an increasing number of photoactive sites are clearly related to an improving of photocatalytic efficiencies. To boost the number of such sites, it is indispensable to increase the weight addition ratio or, alternately, the oxidation points onto the graphene surface. The latter indeed introduces significant structural defects that strongly affect the electron mobility and thus the charge transfer and separation processes. Furthermore, a huge adsorption capacity against organic contaminants in water is displayed from oxidised graphene-based materials. This peculiar property, that in the case of GO versus methylene blue (MB) was quantified at 714 mg/g19, makes difficult to discern between adsorption and photodegradation processes during photocatalytic tests. Finally, another crucial point is related to the antioxidant activity of carbon materials versus organic molecules. Multiple experiments have shown that graphene-based materials are an effective scavenger of OH• radicals, avoiding the desired purification catalyzed by photoactive molecules20.Significant efforts in electron transfer process have been made also by anchoring porphyrins onto graphene based materials via covalent and non-covalent interactions  strategies, which permit to bind molecules to the selected substrateTo obtain an efficient device overcoming the aforementioned disadvantages, a freestanding hybrid nanocomposite by using high quality graphene 3D supported by Nickel foam and photoactive macromolecules was realized. The novelty of our approach consists in exploiting extensive non-covalent interactions between the high surface area of graphene co-catalyst and a coating of cyclic porphyrin polymers. The unusual choice of porphyrin polymers (PPrs) as photoactive sites is based on two assumptions: i) their hindering conformational geometries might significantly avoid formation of agglomerates of single porphyrin units, that act the rapid quenching of excited state; ii) if compared to isolate photo-active molecules, polymers are able to much easily coat and protect the co-catalyst surface. Moreover, our structure shows very high avalaible surface thanks to its foam nature, further improving its photocatalytic performances.This new concept of graphene polymer nanocomposites formulation might avoid the shielding effect as well as the radical scavenger activity, maximising the charge transfer process during photocatalysis. The photocatalytic efficiencies of these nanocomposites were tested and compared to graphene/porphyrin monomers by photodegrading MB dye in water under visible-light irradiation. Our results are below reported and discussed.21. Indeed, this growth mechanism is not self-limiting like on copper.The nickel-graphene foam obtained by CVD growth is shown in Fig. 4. Porphyrin systems can act as photocatalytic media as free molecules, supported molecules, nanostructured assemblies and thin films14. Whatever is the strategy adopted, the formation of porphyrin agglomerates triggers the rapid quenching of excited state preventing photocatalysis. We used a simple polymerization process to concatenate higher number of photoactive sites in more stable cyclic chain structures25. In addition, cyclic polymerization of such porphyrins were chosen to restrain the formation of non-photoactive porphyrin aggregates26. In Fig. 27. The synthetic details of polymerization reactions of homo-PPr and co-PPr are reported in the experimental section. The obtained materials were purified and characterized by MALDI-TOF MS, GPC and UV-Vis spectroscopy. MALDI-TOF analysis, performed after samples purification, indicated that zinc derivate (homo-PPr Zn) contained oligomers lower than 3 repeat units, whereas polymerization of porphyrin Zinc free (homo-PPr), displayed a higher number of porphyrin units along the cyclic chains . The Table The heterogeneous catalysis from porphyrins and metal-porphyrins under visible-light irradiation is well reported in the literaturesee Fig.  ESI†. Th2/g, was used as solid support and embedded with the polymeric photosensitizers. The GF pieces of about 5 mm × 20 mm were characterized by Scanning Electron Microscopy (SEM) and Raman spectroscopy  related to the GF/homo-PPr and GF/co-PPr composites are shown in the left panel of Fig. 29 . As widely reported in the literature, the N1s XPS represents a sensitive probe of the charge distribution in the porphyrin macrocycle, being strongly affected by their periphery and intermolecular interactions as well34. In agreement with the literature data related to the free-base porphyrin, the N1s signal consists of a doublet with the two components centered at 400.2 eV and at 398.2 eV, in both GF/Co-PPr and GF/Homo-PPr spectra. Such binding energy (BE) values are diagnostically attributed to the presence of the pyrrolic (−NH−) and to the iminic (−N = ) species, characteristic of the porphyrin ring36. Nonetheless, as seen by comparing Fig. †). The analyses, in fact, further demonstrate the spectral differences between the two porphyrin-based structures, showing the broadening of the N1s XPS bands in the case of homopolymers, compared with the copolymers. Based on our results, we retain that the organic chains used as linker to join the porphyrinic units can modulate the intermolecular π-π stacking of the aromatic rings and, consequently, the final electronic structures of the macromolecular system.In order to inspect the electronic structure of the porphyrin-based compounds, we investigated the high-resolution region related to the N1s and C1s signalsSEM analysis of GF/homo-PPr and GF/co-PPr were also carried out to observe the morphology of polymeric coating onto the GF surface. In Fig. • radicals.However, their morphology shows clear differences, appearing quite smooth in the co-PPr case Fig. , while i†) evidenced a well distributed and extended coating for homo- and co-PPrs films, if compared to porphyrin monomers. Nonetheless, higher magnification AFM analyses of the three samples demonstrated relevant morphological differences.To finely explore the morphologies and appreciate the roughness parameters of porphyrins and cyclic-porphyrin polymers onto the graphene surface, we performed AFM analysis onto 2D reference nickel/graphene substrates. These samples were prepared following the same procedure used for 3D GF/cyclic porphyrin polymers. Lower magnification topographic AFM images Fig.  ESI† eviIn Fig. et al.37, MB could not be an appropriate probe molecule in photocatalytic test under visible light exposure since in this range it can give a contribution in photoabsorption. Thus, it can induce incorrect measurements of MB concentration during catalytic processes. We faced up this problem by measuring the absorption spectrum of aqueous MB solution (without the graphene/Ni foam) under visible light irradiation  and subtracting these absorption contributions to the absorption profile produces by our systems during the exposure time. We underline that the use of MB is still considered an ISO procedure and hence its use allows to obtain an immediate and easy comparison of our results with those recently reported in literature by using similar procedures13.The photocatalytic activity under visible-light irradiation of the nano-hybrid materials was evaluated and compared by degrading MB dye water solution. As argued by Yan see Fig.  ESI† and0 values  of MB as a function of the photo-exposure time during both the dark and visible-light experiments are reported. To dispel any doubts on the efficiency of the GF device in promoting photocatalysis, homo-PPrs were tested also on pristine Nickel foam surface (without graphene). As shown in Fig. 0 values, indicating a very low photocatalytic activity. Similarly, GF with porphyrin monomers, as well as GF/homo-PPr Zn did not give significant catalytic efficiencies , carried out after the third run, shows a sensible damage of polymer coating on graphene surface. This phenomenon could be attributed to the reactive oxygen species (ROS) which have acted a significant erosion. This evidence suggests that the reduction of photocatalytic action was mainly due to degradation of macromolecules on graphene surface. To test if graphene surface was still able to exploit its co-catalytic properties, we embedded again the GF with the co-PPrs polymers solution, washed with DMF and dried for 12 hours obtaining a restored material for a new recyclability experiment. The same procedure was repeated two times. Figure SEM analysis of GF/homo-PPr and GF/co-PPr Fig.  ESI†, ca• radicals, which drastically reduce the photocatalytic efficiencies. On the other hand, the use of sterically hindered cyclic polyporphyrins increases the number of photoactive sites, limiting the formation of agglomerates that hampered the desired charge transfer process onto the GF surface. The photocatalytic degradation tests carried out by using MB in water solution showed higher efficiencies of homo- and co-polyporphyrins compared to porphyrin monomers coating. Additionally we highlighted that only 400 μg of polymers supported on 6 mg of GF explicated an outstanding photocatalytic efficiencies with a good recyclability capabilities. This evidence can be a game changer in the formulation of polyporphyrins as photoactive compounds for such kind of graphene hybrid materials. The co-monomers nature, the MM values, the sequence length as well as the topology of the co-polymers, could significantly influence the photoactivity behaviour of cyclic polyporphyrins materials, reserving new stimulating finding. At the same time, the polymer deposition methods and parameters could be also taken into account to control aggregate formation. As for Ni/GF, interesting future perspectives put forward the use of nickel free graphene 3D as charge transfer material.The combination of organic photosensitizers with graphene-based materials has become a hot topic in water remediation. We demonstrate a novel innovative approach that consists in combining properties of graphene 3D and porphyrin polymers in a freestanding device. This simple assembly method promotes a direct and extensive contact between the graphene and the photosensitizer polymers through the instauration of non-covalent interactions at the materials interface. At the same time, the polymer coating can confine graphene materials to the direct exposure of light, dyes and OHA Waters 515 HPLC pump, connected to four Ultra-Styragel HR columns joined in series , and a Waters R401 differential refractometer, were used for GPC analysis. Polymer solutions  were injected and eluted at a flow rate of 1 ml/min. Calibration curve was obtained using a set of primary polymethylmethacrylate (PMMA) standards.MALDI /mass spectra were recorded in reflector mode using a 4800 MALDI TOF/TOF™ Analyzer , equipped with a Nd:YAG laser (λ = 355 nm) and working in positive-ion mode. External calibration was performed using an Applied Biosystems calibration mixture consisting of polypeptides with different molecular weight values. Mass accuracy was about 50 ppm. The samples were prepared by mixing approximately 0.1 mmol of the monomer or polymer and 40 mmol of trans-3-indoleacrylic acid  on the sampler target, using THF as a solvent. The m/z nominal values reported in the spectra, are referred to molecular ions constituted by the most abundant isotopes of each element present in the molecule.UV-Visible spectra were recorded on a Shimadzu spectrophotometer at room temperature using toluene as a solvent and quartz cuvettes with a path length of 1 cm. The porphyrin content in co-PPr was evaluated by considering the absorption value at 423 nm (λmax for porphyrin group) using Beer’s law and a molar absorption ε of 378692, determined for porphyrin monomer in toluene. The calculated compositions were reported in Table AFM analyses were performed using a Bruker-Innova microscope operating in high-amplitude mode and ultra-sharpened Si tips were used . The Si tips were substituted as soon as a resolution loose was observed during the AFM images acquisition. The AFM images were analyzed by using the SPMLABANALYSES V7.00 software. In order to give representative parameters, statistics on the AFM images were carried out over different areas of the same sample.−9 Torr. The measurements were carried out at 45° photoelectron take-off angle relative to the sample surface with an acceptance angle of ±3°. The analyzer pass energy was set at 23.5 eV for the high-resolution spectra. The binding energy (BE) scale was calibrated by centering the C1s signal of the aliphatic/aromatic component at 285.0 eV). The analyses were performed on 2 mm diameter surface area of the sample, much greater than the lateral size of any carbon island on the nickel foam surface.XPS were performed by a PHI ESCA/SAM 5600 Multy technique spectrometer with the use of an Mg standard X-ray source. During the analyses, the pressure in the chamber was ~10Micro-Raman Stokes spectra were taken in backscattering geometry with a HORIBA Jobin-Yvon system, equipped with Olympus BX41 microscope. He-Ne laser radiation at a wavelength of 632.8 nm is focused to a spot size of about 1 μm by a 100× objective. The laser power on the sample was about 5 mW, and a 550 mm focal length spectrometer with 1800 lines/mm grating was used.The morphology of hybrid structure were analyzed by scanning electron microscopy  using a Zeiss Supra 25 microscope operating at 2.0 kV, both in the Inlens and secondary lens operation mode.All solvents and basic materials were commercial products appropriately purified before use.23 by reaction of 5,10-di[p-(9-methoxytriethylenenoxy)phenyl]−15,20-di[p-hydroxyphenyl]-porphyrin (see ESI† for synthesis method) with CH2Br2. In a 2 mL vial, equipped with magnetic stirrer and placed in a water bath at 70 °C, 10 mg (0.01 mmol) of 5,10-di[p-(9-methoxytriethylenenoxy)phenyl]−15,20-di[p-hydroxyphenyl]-porphyrin were solubilized in 0.5 mL of N-methylpirrolidinone (NMP) together with 3 mg (a large molar excess) of powdered KOH. After 1 hour, 0.3 mL of CH2Br2 (a large excess) were added and the vial closed. After 24 hours, the solution was poured into 5 mL of 5% HCl under vigorous stirring and the obtained suspension was centrifuged to give a purple polymeric residue. The material was solubilized in 2 mL of THF, precipitated in 5 mL of water, centrifuged and dried in vacuum for 24 hours (yield about 80%). The polymer was characterized by MALDI-TOF mass spectrometry, GPC and UV-Vis spectroscopy. Homo-polymer based on zinc-porphyrin monomer was synthesized in a similar way starting from the specific porphyrin derivative.The homopolyformal −15,20-di[p-hydroxyphenyl]-porphyrin (0.011 mmol) and 8.1 mg of di(bisphenoxy-A)eicosane (0.011 mmol) were solubilised in 3 mL of toluene in a 10 mL closed vial and heated at 70 °C. Then, 4 mg of NaOH , solubilised in 1 mL of water together with 7.1 mg of TBAB (0.022 mmol), were added and the solution was stirred at the same temperature for 1 hour before adding 0.5 mL of CH2Br2. After 24 hours, the organic solution was separated from the aqueous one and poured, under stirring, into a solution of 10 mL of EtOH acidified by 0.5 mL of CH3COOH. After separation by centrifugation, the precipitated material was dissolved in THF and precipitated in EtOH a further two times, washed with H2O, then dried under vacuum. 14 mg of a purple fibrous polymeric material was recovered with a yield of about 75%. The copolymer was characterized by MALDI-TOF mass spectrometry, GPC and UV-Vis spectroscopy.Random copolymer [co-PPr in Fig. 2, porosity 95%, 20 pores/cm, purity 95% and 1.6 mm thickness) were used as 3D scaffold templates for the CVD growth of GF. They were cut into pieces of 5 × 10 mm, then immersed in acetic acid to remove Ni native surface oxide layer and finally placed in the chamber of the AIXTRON’s Black Magic Chemical Vapor Deposition (CVD) system. The chamber was firstly pumped down to 4 × 10–3 mbar and then gradually heated both from the top and bottom side of the chamber up to 900 °C and maintained at this temperature for 20 minutes under Ar and H2 flows  to further clean the surface and eliminate the residual thin surface oxide layer. Then, the temperature was raised up to 1000 °C and the CH4 flow was opened for 40 minutes  and then cooled down at 15 °C/min to grow the graphene layers on the Ni foam surface. The working chamber pressure was maintained 25 mbar both in the cleaning and growth steps.Nickel foams  was dissolved in 1 mL of dimethylformamide (DMF). After, a GF piece of 5 mm × 20 mm was immersed in each polymeric solution. Samples were statically impregnated in the mixture overnight, then removed from vials. The resulting hybrid materials were dried under vacuum overnight at 50 °C.2 and equipped with a cut-off filter (λ > 400 nm) was used as the light source. For each experiment, a MB dye aqueous solution (0.015 mM) was prepared. The samples were immersed in 2 ml of the MB solution and left for 12 h in the dark to reach the adsorption-desorption equilibrium. Afterwards, at given time intervals of 1 h, the variation of the concentration of the MB was spectrophotometrically evaluated using a PerkinElmer Lambda 45 UV–Vis spectrophotometer, observing the absorption peaks at 664 nm. The photodegradation ratio was defined as C/C0 where C is the absorption of the dye at a certain time and C0 represents the absorption value of the MB initial concentration. In particular, these curves were previously subtracted by the contributions of MB photoabsorption, that were measured by irradiating MB aqueous solution (without graphene/Ni).The photocatalytic activities of the nanohybrids were evaluated through the degradation of MB dye under visible light irradiation. A xenon lamp operating at 1.5 mW/cmSupplementary information


Drug-specific risk and characteristics of lupus and vasculitis-like events in patients with rheumatoid arthritis treated with TNFi: results from BSRBR-RA. RMD Open 2017;3:e000314.Jani M, Dixon WG, Kersley-Fleet L, The surname of the third author of this paper was spelt incorrectly. The correct surname is “Kearsley-Fleet”.


We can identify single cells with an accuracy >90% for more than half of the communities consisting out of two bacterial populations. In order to assess to what extent an in silico community is representative for its synthetic counterpart, we created so-called abundance gradients, a combination of synthetic  communities containing two bacterial populations in varying abundances. By showing that we are able to retrieve an abundance gradient using a combination of in silico communities and supervised machine learning techniques, we argue that in silico communities form a viable representation for synthetic bacterial communities, opening up new opportunities for the analysis of synthetic communities and bacterial flow cytometry data in general.Bacterial cells can be characterized in terms of their cell properties using flow cytometry. Flow cytometry is able to deliver multiparametric measurements of up to 50,000 cells per second. However, there has not yet been a thorough survey concerning the identification of the population to which bacterial single cells belong based on flow cytometry data. This paper not only aims to assess the quality of flow cytometry data when measuring bacterial populations, but also suggests an alternative approach for analyzing synthetic microbial communities. We created so-called  Microbial communities are primary contributors in most biogeochemical processes on Earth . As suchTo cope with these bottlenecks, synthetic microbial communities, assembled through the selection of individual microbial populations, and studied under controlled environmental conditions, have recently been suggested as promising intermediary platforms –5. AdvanWith the number of synthetic ecology studies ever increasing, the analysis of low-complexity community compositions, i.e. quantifying the abundance of each constituent taxon, remains the most significant challenge. A study by Saleem et al. used traditional plate counting, which entailed the cultivation of all individual members on agar plates followed by subsequent enumeration of the colony forming units (CFU) . Their cEscherichia coli mutants, the analysis of complex synthetic communities that consist of diverse taxa  faces considerable bias due to taxon-dependent nucleic acid extraction efficiencies, varying amplification efficiency and also primer selectivity. In extremis, this has limited studies with complex synthetic communities to relate their temporal observations only to the initial community composition [Other studies, such as the one by Mee et al., applied quantitative PCR (qPCR) . Yet, whposition . Overallbioinformatics, is growing accordingly [Flow cytometry (FCM) offers a multiparametric description of individual cells, which can be applied to study microbial communities , 14. As ordingly .in silico communities. These are communities created by an aggregation of FCM data coming from axenic cultures which are being measured separately through FCM. The great advantage of using this approach is that we know which cell stems from which bacterial population. This enables us to apply a supervised machine learning approach, which has shown previous success in the recognition of leukemia [The main goal of this paper is to explore in a systematic way the possibilities of using FCM data to identify bacterial single cells, in order to be able to characterize the composition of synthetic bacterial communities. We will do this by introducing the concept of leukemia  or to fileukemia . More spleukemia , 19. Appleukemia  or to anleukemia . HoweverIn the first part of the paper we analyze to what extent data coming from FCM can be used in order to separate microbial populations at the single-cell level. To do so we have cultivated twenty axenic cultures and characterized them by FCM. We performed single-cell predictions using Linear Discriminant Analysis (LDA), an established method for performing multivariate analyses in microbial ecology , and a Rabundance gradients, a combination of in vitro communities which consist out of two populations in varying abundances. We will show that we are able to retrieve these relative abundances, using a classifier trained on an in silico community; this result enables researchers to perform a supervised analysis of synthetic microbial communities.In the second part we show to which degree an in silico community is able to identify a synthetic bacterial community. This is not a foregone conclusion due to the heterogeneous character of bacterial populations, which is reflected in FCM data . In ordemulticlass setting. To do so we created and evaluated in silico communities containing more than two populations. The results show that our approach is valid for communities of lower complexities, furthermore FCM gives rise to data that should be feasible for higher complexities as well. A schematic overview of the proposed method can be found in In the third part of the paper we estimate to what extent bacterial communities can be analyzed for higher population complexities, i.e., in a S = 2, S denoting the number of populations making up a community, i.e., the population richness. This results in 190 in silico communities, where the same amount of cells was sampled for each population, thus creating evenly distributed in silico communities. We calculated the mean for the area under the ROC curve (AUC) and the accuracy (acc), accompanied with their standard deviations and the percentage of communities which reported a score higher than 0.90; results are reported in The performances using LDA and a Random Forest classifier were calculated for all possible pairwise combinations considering twenty populations for We conclude that for a majority of in silico communities we are able to perform single-cell predictions up to high performances, especially when using Random Forests; in this case more than half of our communities report results higher than 0.90 for both AUC and the accuracy. Our highest performances top off at an AUC of 0.999 and an accuracy of 0.996. To further illustrate our findings we have visualized the AUC and the accuracy for all in silico communities, where performances have been ranked in descending order according to the results of applying a Random Forest classifier .On average we see that a Random Forest classifier performs better than LDA. However, it is not always necessary to use a ‘black-box’ non-linear classifier such as a Random Forest. For some of the in silico communities we see that the performance of LDA is similar to the performance of Random Forests; 45% of the in silico communities report an increase in AUC of less than 0.03, 17% report an increase in accuracy less than 0.03. Moreover, note that pairwise combinations of populations give rise to performance accuracies ranging from 99% to near random guessing predictions. Hence, our dataset is highly representative, that is, we were not biased towards highly discriminative populations.An abundance gradient consists out of a set of bacterial communities containing two populations in varying abundances. We constructed these gradients for three combinations of bacterial populations, combinations for which we initially reported a low (Comb. 1), medium (Comb. 2) and high performance (Comb. 3) respectively. We created these gradients in vitro, but, because we measured the bacterial cultures separately beforehand through FCM, we were also able to construct these gradients in silico. In order to explore to what extent in silico communities can be used to identify synthetic bacterial communities, we have predicted the relative abundances of both in silico and in vitro abundance gradients, using LDA and a Random Forest classifier trained on a full evenly distributed in silico community. Ideally, a classifier which is able to achieve a high AUC and accuracy on a held-out test set of this in silico community gives rise to a well-predicted abundance gradient, both in silico and in vitro. The predicted abundance gradients are visualized in S. oneidensis population.As expected, the predicted abundance gradients for Comb. 2 and 3 match the target abundance gradients , whereasSecond, we note that for Comb. 2 the predicted gradients highly overlap; this means that an analysis using LDA and a Random Forest gives rise to very similar results. This is however not the case for Comb. 3, where the use of Random Forests results in a gradient that lies closer to the target gradient, which is reflected for both the in silico and the in vitro analysis. These observations are reflected in the root mean squared error (RMSE), which is calculated between the predicted gradients and the known target abundance gradients . The RMSShannon diversity, noted as D1 [evenness of a community . To quantify our results we calculated the mean accuracy for every S; results are displayed in In order to explore to what extent single-cell predictions can be made when we increase the population richness, we created in silico communities in a S our approach is able to make single-cell predictions significantly better than random guessing. As S increases, both the mean accuracy and the size of the confidence interval decreases. As the richness increases, the degree in overlap between populations in the multiparametric ‘FCM-space’ starts growing accordingly. Therefore it is harder for classifiers to make a distinction between populations, which results in performances that are lower and more centered.For all values of S increases. This means that for communities with a low richness  LDA might provide a sufficient method to make single-cell predictions, but as S increases Random Forest will be a better option for most communities. This also implies that although for low S a linear combination of variables already discriminates populations quite well, predictions can be improved by resorting to classifiers which have the possibility of detecting non-linear relations between variables.The difference in performance between the two classifiers increases as Using the concept of in silico communities, we are able to use supervised machine learning techniques to taxonomically identify bacterial cells up to high accuracies based on FCM data. We note that this approach has not yet been adopted to analyze the composition of synthetic bacterial communities. A possible reason for this is the lack of incorporating these methods in standard FCM software .one-versus-one (OVO) or one-versus-all (OVA) approach [Using a full combination of fluorescence and scatter signals, we demonstrated that using ‘off-the-shelf’ classifiers without further data manipulation already results in acceptable to high performances for low population richness. Compared to previous research, we note that Rajwa et al. were not able to use LDA in order to make proper single-cell predictions . While tapproach .technical variability and biological variability. It has been shown that both sources give rise to heterogeneity in FCM data when studying bacterial axenic cultures [Although it has been briefly mentioned in literature that an in silico community can be representative for its in vitro counterpart , there icultures , althougcultures .S = 2, A & B, we see that for a significant number of combinations the difference in classifier performance is noteworthy, with a mean difference of 2% and a standard deviation of 11%. For clarity, we added the Random Forest performances  for all in silico communities in Technical variability has been suggested to arise from the time-dependent bleaching and leaking of fluorochrome molecules . Its effBiological variability is another and perhaps more important factor to take into account when analyzing microbial communities with FCM. Vives-Rego et al. hypothesize that biological variability in FCM stems from cell size diversity and cell cycle variations . In thisTo do so, a more comprehensive protocol is required to make our in silico approach fully operational, a need which has been pointed out before . This prFor now, in silico communities can already be exploited for various purposes. For environments where limited physiological variation in the axenic populations is expected, or where the in silico populations have been defined for all possible physiological states, our approach can be used to retrieve the community composition for low-complexity microbial communities. Furthermore, by using evaluation tools for classifiers such as the accuracy or the AUC, one can quantify which populations are distinguishable and which are not. One intuitive tool which is extensible to a multiclass setting, is the use of a confusion or misidentification matrix. This allows one to inspect which populations are likely to overlap and which are not; an example is given in Secondly, as we have shown that in silico communities form a viable representation of their in vitro counterparts, we are allowed to extrapolate properties of in silico communities to in vitro microbial communities. This means that in silico communities can be used as a stand-in for in vitro communities, enabling us to use them to develop new data-driven techniques, which will ultimately lead to novel applications for microbial FCM.S) of an in silico community varies from S = 2, …, 20.An in silico community consists out of an aggregation of data coming from axenic cultures, which are being measured separately through FCM. As we have twenty axenic cultures at our disposal, the population richness , in order to keep it computationally feasible. For every increment of S we calculated the mean accuracy, averaging the accuracies for all 150 randomly chosen in silico communities.For abundance gradient to prove that properties of in silico communities can be used for the identification of their in vitro counterparts. An abundance gradient consists out of a set of microbial communities where populations have been mixed in varying abundances. We created an abundance gradient both in silico and in vitro for three combinations of two populations, with abundances ranging from 1% to 99% for the one population and vice versa for the other. This was possible as we measured the axenic cultures separately through FCM beforehand. We chose three different combinations of two populations to create abundance gradients, combinations which initially reported a low, medium and high performance respectively, based on the performance of the Random Forest classifier for S = 2. For every community in an abundance gradient we sampled 10,000 cells (both in silico and in vitro), except for one in vitro community of Comb. 3, for which we were not able to register enough cells (see further on).We used the concept of an Nax = 5,000 cells per bacterial population to create the in silico community upon which we trained our classifier; as the abundance gradient acts as our test set, we trained our classifier on the full in silico community. Note that we have cultivated and measured new axenic cultures in order to create both the in silico and in vitro abundance gradients.We trained a classifier on an evenly sampled in silico community to predict the label of individual cells for all communities in an abundance gradient. We sampled www.bccm.belspo.be), Leibniz Institute DSMZ (www.dsmz.de) and Helmholtz Centre for Environmental Research (www.ufz.de/index.php?en=13354), respectively. For cultivation, all bacteria were grown on rich, solid lysogeny broth medium . A single colony was picked and cultivated for 48h in liquid LB medium. Finally, fresh LB medium was inoculated with 10% (v/v) inoculum and incubated for 24h; all samples were measured in duplicate. A bivariate scatterplot (FL1-H vs. FL3-H) after denoising can be found for every culture . >10,000 cells were registered for each measurement, except for Comb. 3 where we registered 3.084 cells for 1% of S. oneidensis.To create abundance gradients, we chose three combinations (Comb.) of two bacterial populations based on Random Forest performances calculated during the in silico analysis of dataset 1 . We measAs we measured the populations separately beforehand through FCM, we were also able to construct an abundance gradient in silico, by sampling communities according to the same relative abundances as described above.6 cells mL-1 in 0.2 μm filtered buffer solution was reached  and stained with a final concentration of 1% (v/v) nucleic acid stain SYBR® Green I (100x concentrate in 0.2 μm filtered dimethyl sulfoxide). Samples were incubated for 20 minutes in the dark at 37°C. FCM measurements were performed on a C6 Accuri flow cytometer  equipped with four fluorescence detectors , two scatter detectors and a 20mW 488nm laser. This results in a multiparametric description of each cell consisting out of twelve variables .Samples were diluted until an approximate cell density of 10x) transformed FL1-FL3 bivariate space, following the guidelines by Hammes et al. [write.FCS function. The cell densities for each individually measured taxon were calculated by the filter function; both functions are available from the flowCore package (v.1.38.1). As axenic cultures and synthetic communities have been measured in a number of replicates, we pooled these replicates together first, before subsampling cells to create our in silico and in vitro communities we use for analysis.The FCM data were denoised from (in)organic and instrument noise by means of a reproducible digital gating strategy in the arcsinh is a linear classifier which tries to find the optimal linear combination of features in order to separate objects or classes. It assumes the data are distributed according to a Gaussian distribution. It has no hyperparameters to tune and is able to handle problems in the multiclass setting in a natural way. For more information, see  or chaptensemble method, a method in which various classifiers are trained and in which a majority vote is taken to predict the outcome of an unknown sample. In this case the ensemble consists out of decorrelated unpruned trees grown on bootstrap samples. The trees are decorrelated because at every split only a random subset of the total number of K variables is available (K = 12). This results in a decrease in variance for only a slight increase in bias, hence lowering the overall classification error. For more information see [A Random Forest classifier is an example of an tion see  or chapttion see .S = 2, …, 19 using the preset We grew 200 trees when training a Random Forest and chose the gini criterion when making a split. We note that there is no need to tune the number of features that are available to choose from when making a split. We applied the preset nce with . This haaccuracy and the area under the receiving operating characteristic curve (AUC). The in vitro analysis is expressed in terms of the root mean squared error (RMSE).We used various performance metrics in order to evaluate our methodology. We evaluated the in silico analysis in terms of the N denotes the total number of elements to predict, y the true label and 1 the indicator function, which returns the value of 1 when its argument is true and 0 otherwise. It can also be expressed in terms of the true positives (tp), the number of correctly predicted elements belonging to a certain class j, true negatives (tn) the number of correctly predicted elements not belonging to class j, false positives (fp), the number of incorrectly predicted elements belonging to class j and false negatives (fn), the number incorrectly predicted elements not belonging to class j. In this setting, the accuracy can be written as:S denotes the total number of classes.The accuracy can be defined in the following way:receiving operating characteristic (ROC) curve and can be used as a performance measurement for a binary classifier [The AUC measures the area under the assifier , 46. TheCalculating this area results in a number between 0 and 1; the higher this number, the better the performance of a classifier. The AUC can be interpreted as the probability that a classifier will rank a randomly chosen positive higher than a randomly chosen negative. Using the AUC has a number of favorable properties. Most notable are the fact that it gives an indication of how well separated the positive and negative class are and that it is insensitive to prior skewness concerning class distributions.p, opposed to the predicted n being the total number of bacterial communities constituting an abundance gradient. Therefore when the set of predictions are close to the ground truth, the RMSE lies close to zero.Expressing the known relative abundance as A confusion matrix is a tool which helps to describe the performance of a classifier. It reports the tp, tn, fp and fn, and is naturally extendable to a multiclass setting. In this way one can inspect to what extent a classifier ‘confuses’ certain labels of classes. An example for the binary setting is given in Applied to the use of in silico communities, one is able to inspect which populations are easily separated by a classifier and which populations have a similar FCM fingerprint.https://github.com/prubbens/InSilicoFlow.Our code has been made available on github: .fcs format on the FlowRepository database [Our data has been made freely available in database , and canAxenic cultures: FR-FCM-ZZSH.Abundance gradients: FR-FCM-ZZSG.flowCore, a package of computational Tools written in R for the analysis of FCM data [The data has been preprocessed and exported using FCM data .Scikit-learn is an open-source library of various machine learning methods, which can be used in Python [n Python . We usedD1 [pi denotes the relative abundance of population i:Knowing the relative abundance of a population, we can determine the Hill number of order one, i.e., the first alpha diversity metric, denoted as D1 . This inD1 is that we can combine uncertainties for the relative abundances. As it has been established that the instrumental variation ϵI for FCM is less than 5% considering cell counts [p can be calculated from a division of two cell counts, pi (as pi can be determined independently) to determine the variance for D1 in the following way: An additional advantage using a diversity index such as l counts , we can S = 2 (as p2 = 1−p1), this formula can be expressed in terms of the relative abundance of the first population p1 as follows, combining the two formulas above:D1 for every community constituting the abundance gradient, and additionally, we gained a confidence interval within which our in vitro constructed D1 should lie, setting ϵI = 0.05; this information is visualized in For S1 File(XLSX)Click here for additional data file.S1 FigS = 5. Every element of the matrix mij gives the fraction of the population i that is predicted as population j.Example of a confusion matrix calculated on a 30% held-out test set for an in silico community with (TIF)Click here for additional data file.S2 FigFlow cytometric characterization of 20 bacterial taxa. Each point represents one single cell characterized by two fluorescence parameters (FL1-H and FL3-H). The data were denoised from (in)organic noise based on a reproducible digital gating strategy (explained above) and was adjusted for each taxon.(TIF)Click here for additional data file.S3 FigA Comb. 1: P. putida—P. fluorescens; B Comb. 2: A. rhizogenes—Janthinobacterium sp. B3; C Comb. 3: S. oneidensis—M. luteus. Data filtering strategy for the FCM data for each abundance gradient based on a reproducible digital gating strategy (explained above); data points outside the filter represent (in)organic noise. Examples are given for the 40%-60% abundance files.(TIF)Click here for additional data file.S4 FigAB Comb. 1: P. putida—P. fluorescens; CD Comb. 2:A. rhizogenes—Janthinobacterium sp. B3; EF Comb. 3: S. oneidensis—M. luteus. Both predicted and target D1 is plotted against the relative abundance of the first population for every combination, both for the in silico (left panel) and in vitro (right panel) abundance gradients; the 68%-CI and 95%-CI for the in vitro gradients are also visualized, determined as described in Appendix: Alpha diversity analysis.(TIF)Click here for additional data file.