Dictyostelium cells undergo highly efficient dedifferentiation, completed by most cells within 24 hr. We use this rapid response to investigate the control features of dedifferentiation, combining single cell imaging with high temporal resolution transcriptomics. Gene expression during dedifferentiation was predominantly a simple reversal of developmental changes, with expression changes not following this pattern primarily associated with ribosome biogenesis. Mutation of genes induced early in dedifferentiation did not strongly perturb the reversal of development. This apparent robustness may arise from adaptability of cells: the relative temporal ordering of cell and molecular events was not absolute, suggesting cell programmes reach the same end using different mechanisms. In addition, although cells start from different fates, they rapidly converged on a single expression trajectory. These regulatory features may contribute to dedifferentiation responses during regeneration.Dedifferentiation is a critical response to tissue damage, yet is not well understood, even at a basic phenomenological level. Developing  Dedifferentiation is the transition of a cell to a state characteristic of an earlier stage of development. This reversal of developmental programmes is a widespread response to tissue damage , allowinPrevious studies have identified some candidate molecular players, including c-Jun , mTORC1 These difficulties in understanding are for several reasons. Firstly, many of the characteristic models of dedifferentiation are slow – often taking days to weeks for effective return to the earlier developmental state. Dedifferentiation within a tissue context will be confounded by the mixed signatures from multiple cell types, and more often than not, by a lack of accessibility. Although IPSC generation in culture provides a more accessible model, the process is slow (weeks), a very small proportion of the starting population makes it back to the stem cell state (which means the cells one is interested in can be difficult to identify) and the process usually involves the forced expression of four transcription factors (TFs), two of which are proto-oncogenes .Dictyostelium cells can completely reverse their differentiation in around 24 hr  medium, or bacteria, as a food source. Both types of nutrition caused cells to reverse development along similar gene expression trajectories in the PCA space of the major principal components 1 and 2. For dedifferentiation under both nutritional conditions, most of the transcriptional changes along the PC1 axis had occurred after 6 hr. Although these trajectories had similar start and end points to the corresponding developmental stages, they diverged from the trajectory used by cells undergoing development, primarily with respect to PC2 values. Cells inoculated into nutrient free buffer after disaggregation showed a different path, which separated rapidly from the dedifferentiating trajectory .Although expression trajectories during dedifferentiation and development appear distinct, consistent with earlier microarray data , analysiDictyostelium genome, found a complex mixture of functional enrichments  and the expression in the mound . We then compared these genes to those strongly induced during early dedifferentiation . For dedifferentiation in bacteria, we found a 41% overlap (165/402 genes) between the dedifferentiation and aggregation genes. This overlap was compared to a simulated scenario with 402 genes sampled at random  from the entire genome. In the simulations, the median overlap between the dedifferentiation genes and the randomly sampled genes was found to be only 22%, with the 41% value never observed. This implies a strong enrichment of aggregation markers in the early dedifferentiation gene set. However, this effect was specific to the bacteria-based dedifferentiation, with liquid medium cultures showing an effect in the opposite direction, with only 15% overlap between dedifferentiation and aggregation-induced genes. We conclude that the re-induction phenomenon is not consistently a feature of dedifferentiation trajectories. An alternative explanation is that genes such as csaA and carA are repressed by strong cAMP signalling in the mound  is expressed in undifferentiated cells, but strongly repressed during development  showing rapid induction in their expression during early dedifferentiation – BzpS, MybD, NfyA, DDB_G0272386, DDB_G0269374 and DDB_G0281091. To determine the genes regulated by these TFs, we mutated the coding sequences of their genes, then carried out RNAseq on the mutants during dedifferentiation. To our surprise, none of the mutants showed clear changes in gene expression compared to wild type . This apelopment . We enrintiation . We therhkA gene  did not hkA gene .PCNA induction  mutant, which has a growth defect during both bacterial and liquid culture . To test this reasoning, we measured dedifferentiation-induced gene expression in the  culture . PCNA exG- cells , howeverG- cells . Clonal ld types , perhapsild type . The rasd medium . As withal lawns , implyinforG- and rasS- mutants have defects in macropinocytosis, which impair their growth in liquid medium. Even after 30 hr of dedifferentiation, when cell division is widespread in the culture and gene expression has returned to the undifferentiated state, the wild-type fluid uptake was only half the normal level of undifferentiated Dictyostelium cells. However, a small but reproducible increase in fluid uptake could be detected around 8 hr into dedifferentiation  that dedifferentiate fairly effectively despite an underlying cell health problem.The efficiency and apparent robustness may be related aspects of the dedifferentiation response. Dedifferentiation is induced experimentally by disaggregation of cells, followed by a nutritional stimulus. Disaggregation means a loss of stimuli related to cell contacts and dilution of other signals, such as cAMP. The nutritional stimulus, whether the peptone-based medium or bacteria , is a complex mix of food biomolecules, likely to enter the cellular metabolic network via many pathways. Given the obvious complexity of the overall stimulus to dedifferentiate, it may be unlikely that the cell, regardless of its fate tendency, has any real choice but to efficiently obey this overwhelming sensory input, and that perturbation of any single molecule will be insufficient to substantially arrest the process. Along these lines, although we observed that different events during differentiation (gene expression and mitosis) show a distinct temporal sequence, at the single cell level the temporal ordering can be reversed. This implies that cell programmes can unfold in different ways to the same stimulus, potentially contributing to robustness. This lack of a rigid dependency between temporal phases of dedifferentiation may also explain why mutants may have some impairment in individual aspects of reversing development, whilst leaving the majority of dedifferentiation responses unperturbed . This isA mutant . These cA mutant , a possiDictyostelium, we also identified the re-expression of markers from an early developmental time, in line with the mammalian literature, however the evidence was anecdotal, based on well-known genes, and did not stand up strongly to a more formal analysis. The idea that cells enter a pre-visited attractor state during reversal of development is an appealing idea if one wishes to understand how cells can navigate a path back to a progenitor- or fail to do so because they get trapped. The apparent lack of such a coherent developmental intermediate during dedifferentiation in Dictyostelium may to a certain extent underlie the speed and efficiency of developmental reversal.A recurring feature of the IPSC literature is the detection of developmental intermediates along reprogramming trajectories. These conclusions are usually based upon the expression of a few developmental markers. In Dictyostelium and during IPSC generation appear to be systemic, and it seems unlikely at the present time that we could use knowledge from the former to improve the latter. The efficiency of dedifferentiation in Dictyostelium may ultimately come down to the likelihood that it is a physiological response, whereas the generation of IPSCs is clearly not. In the migratory slug phase of development many cells fall out of the rear of the slug onto the substrate, where they are then able to re-enter the feeding part of the lifecycle, if bacteria are present, and then fully re-differentiate once the supply of bacteria is exhausted . Wild type AX2 cells were used unless otherwise stated. Cell lines were authenticated using PCR and Southern blotting.forG-, rasS- and DDB_G0280067- mutants), both mutant and wild-type cells were grown on Klebsiella on SM agar and harvested prior to clearance of the bacterial lawn, with cells washed free from bacteria before further processing.Cells maintained in HL5 were kept under selection against bacterial contamination. Cultures were not allowed to enter stationary phase and cells were not used beyond 10 days of culture. For experiments with cells defective in growth in HL5 (4 pH 6.0) and developed on Whatman #50 filter paper at a density of 2.6 × 106 cells cm−2 in a humidified chamber. For dedifferentiation, 14 hr developed cells were washed from the filter paper in KK2 + 20 mM EDTA, then disaggregated by repeated passing through a 20G needle. Cells were dedifferentiated either in HL5 suspension culture (at 2 × 106 cells ml−1) or in culture dishes (at 4 × 106 cells cm−2) containing live Klebsiella in KK2 (OD600 = 2). Buffer-only treatments were carried out in KK2 in culture dishes.For development, log-phase cells were washed in KK2 , sequencing and data analysis is described in the Appendix. For interpreting PCA, cell-type specific genes were selected from published population transcriptomic data  with |loSequencing data have been deposited at GEO with accession number GSE144892.act8 expression in relation to cell division, we used Act8-mNeonGreen knock-in cells (4 cells cm−2 on chambered coverglass (Nunc) and imaged on an inverted microscope optimised for fast sensitive imaging . Two independent clones of each mutant were both tested in two separate experiments, with >50000 cells measured for each strain at each timepoint. FlowJo v10 software  was used for data analysis.For assaying other mutants, we used RNAseq (see above) or more widely, Northern blotting of RNA extracted from cells during dedifferentiation in HL5 suspension. For analysis of AMPK and mTORC1 signalling, protein extracted from cell pellets of dedifferentiating cells was blotted using anti-pAMPKα  and anti-p4E-BP1 . For a standard, we blotted parallel-loaded extracts using an antibody against the C-terminus of histone H3 (Abcam #ab1791). Further details regarding blotting can be found in the Appendix.6 cells ml−1. At the indicated times, aliquots were removed and adjusted to 3 × 106 cells ml−1 in 3 ml. In parallel, undifferentiated cells were taken from a mid-log suspension culture and adjusted to the same density. For both culture types, 2 mg ml−1 TRITC-dextran  was added, with a further 3 ml of each culture retained as an unlabelled control. After 1 hr labelling, fluorescence was quenched with Trypan Blue, while the unlabelled control was quenched immediately after addition of dextran. Cells were washed and resuspended at the same density in ice cold KK2. Internalised fluorescence was measured using a Fluoromax+ spectrofluorometer (Horiba). Fluorescence measurements of unlabelled cells were subtracted from measurements of labelled samples, and fluorescence uptake during dedifferentiation expressed as a percentage of uptake measured in undifferentiated cells.Fluid uptake measurements were adapted from a standard protocol . Cells w In the interests of transparency, eLife publishes the most substantive revision requests and the accompanying author responses.Acceptance summary:This is a very nice study expanding on dedifferentiation in Dictyostelium; it will yield key insights into dedifferentiation in other systems.Decision letter after peer review:eLife. Your article has been reviewed by three peer reviewers, one of whom served as a guest Reviewing Editor, and the evaluation has been overseen by Didier Stainier as the Senior Editor. The following individuals involved in review of your submission have agreed to reveal their identity: Derrick Brazill (Reviewer #2); Pauline Schaap (Reviewer #3).Thank you for submitting your article "Cell and molecular transitions during efficient dedifferentiation" for consideration by The reviewers have discussed the reviews with one another and the Reviewing Editor has drafted this decision to help you prepare a revised submission.Summary:The reviewers find this work interesting, but have requested several clarifications. Please address all of the points raised by the three reviewers.Essential revisions:1) Results subsections “Genome scale features of dedifferentiation” and “Staging gene expression during dedifferentiation” – since this seems to largely follow the Katoh paper, you should point out similarities and differences.dhkA mutant strongly affects dedifferentiation, I'm very puzzled.2) Subsection “Genetic robustness of the dedifferentiation programme” – the authors say they cannot find mutants that affect dedifferentiation, but Katoh et al. showed that the Reviewer #1:This report examines gene expression in D. discoideum cells when the cells are starved to induce differentiation, and then transferred to nutrient-rich growth medium to induce dedifferentiation. There are strong similarities but puzzling differences between the first part of this report and a PNAS paper previously published by another lab, and the similarities and differences need to be clarified.1) Results subsections “Genome scale features of dedifferentiation” and “Staging gene expression during dedifferentiation” – since this seems to largely follow the Katoh paper, you should point out similarities and differences.dhkA mutant strongly affects dedifferentiation, I'm very puzzled…2) Subsection “Genetic robustness of the dedifferentiation programme” – the authors say they cannot find mutants that affect dedifferentiation, but Katoh et al. showed that the Reviewer #2:This manuscript addresses an interesting and important question regarding the process of dedifferentiation. Little is known about the process except in very artificial systems, so anything learned about it in a natural system has the potential to be very significant. To address this, the authors use Dictyostelium discoideum, which will halt and reverse its starvation-mediated developmental program if the cells in the mound are dissociated and provided food. With this system, they ask a basic question: Is dedifferentiation simply differentiation in reverse, or something different?While this question has been examined in Dictyostelium, the authors do a much more thorough an in depth examination into the transcriptional changes associated with differentiation and dedifferentiation. It is the power of this approach that makes their finding that in general dedifferentiation correlates with a reversal of developmental gene expression valuable and worthy of publication.Unfortunately, their attempts at identifying the genetic regulators of the process were unsuccessful. The genetic screen using act8-mNeonGreen was inspired, even though it did not work. However, the remainder of the focused didn't seem as logical. While the choice of protein types  made sense, the chosen genes seemed random. There were much more rational choices within these groups. DhkA is a developmentally regulated signaling protein that is known to be involved in dedifferentiation. ChdA, ChdB and ChdC are supposed chromatin remodeling proteins that are master regulators for developmental gene expression. There are multiple G α proteins that are known to be involved in food sensing during growth. Almost all of the mutants of all of these gene are able to reach the mound stage of development, so can be examined in this dedifferentiation system. While I am not suggesting that the authors perform these experiments in order to have this manuscript published, I would like a clearer rationale for the mutants that they did choose and why they are better choices than others.I would also be wary of claiming that the dedifferentiation programme is genetically robust for the same reasons. Even though the multitude of mutants they tested didn't show large effects on dedifferentiation, they left out some fairly obvious ones. It would be safer to say that dedifferentiation is more genetically robust that differentiation, since there are a lot more genes that disrupt differentiation. However, this probably has more to do with the fact that development and differentiation requires a higher degree of temporal coordination than dedifferentiation. For dedifferentiation, it makes sense that it doesn't matter whether regulated cAR1 expression occurs before or after adenylyl cyclase expression or G α 2 expression. However, during development, the relative timing of expression is crucial.The cryS experiments were critical in demonstrating that cell fate was not responsible for the two different populations of dedifferentiated cells identified based on motility and division speed. I would ask that the control be mentioned showing proper CrS-mNeonGreen expression in the mounds before dissociation otherwise we don't know whether the system worked well-enough to identify actual prestalk cells. I'd also request a reanalysis of the data to see whether the high/low CryS-mNeonGreen expressing cells had the same ratios of high speed/low speed cells as the entire population. It may be that there is an enrichment of one type of cell based on CryS-mNeonGreeen expression. The data should already exist. It would just need to be analyzed differently.Reviewer #3:This work focusses on dedifferentiation, an overlooked but important process that is important for wound healing, stem cell replenishment and cancer progression.The authors first use an RNAseq approach to compare forward development and dedifferentiation and find that while occurring at a slower pace, the reverse trajectory is the mirror image of the forward trajectory for most genes, but that this is less so for genes involved in protein degradation and ribosome biogenesis.They investigate the hypothesis that dedifferentiation revisits earlier developmental stages, which is suggested by the behaviour of a relatively small number of developmental markers in both pluripotent stem cell induction and their current study. However, for a larger set of 402 genes involved in the aggregation process that precedes the chosen endpoint of forward development, the extent to which this holds true varies from 41% to 22% of genes, dependent on whether dedifferentiation is induced by exposure to bacterial food or to liquid nutrient medium. This suggest that also for animal cells this hypothesis needs to be revisited.The authors use several approaches to show that the dedifferentiation process is robust and not easily perturbed by single gene deletions, such as those of transcription factors and signaling genes that are up-regulated at the onset of dedifferentiation, or identified from mutants that fail to up-regulate the act8 gene that is only expressed in undifferentiated cells.A single cell RNAseq approach was used to determine the relationship between cell division and expression of cell cycle genes. This showed that cell division lagged 12 h behind and occurred when cells had almost completely dedifferentiated, which supported by additional experimentation indicated that cell division is not required for dedifferentiation.Motility followed expression of motility genes more closely, but surprisingly only a fraction of the cells showed the expected increase in motility during dedifferentiation. This appeared unrelated to the prespore or prestalk cell fate that the cells had acquired. The latter also had no effect on the timing of cell division during dedifferentiation nor on the path taken by the two cell types to reach the dedifferentiated state.These results contrast quite strikingly with forward development where cell fate is correlated with several parameters that vary in early stage cells, such as cell cycle phase and nutritional state.All in all the study demonstrates interesting similarities and differences between forward and reverse differentiation in Dictyostelia, which can be expected to be true for other multicellular organisms as well. The experimentation and data analysis is of a very high standard with important conclusions being supported by complementary approaches. Essential revisions:1) Results subsections “Genome scale features of dedifferentiation” and “Staging gene expression during dedifferentiation” – since this seems to largely follow the Katoh paper, you should point out similarities and differences.We have incorporated several additional references to the Katoh paper in this section, and in the manuscript as a whole, to better contextualize our studies.2) Subsection “Genetic robustness of the dedifferentiation programme” – the authors say they cannot find mutants that affect dedifferentiation, but Katoh et al. showed that the dhkA mutant strongly affects dedifferentiation, I'm very puzzled.dhkA mutant:A closer analysis of the Katoh paper, together with further analysis of our own RNAseq data, provides an improved contextualization of the phenotype of the dhkA mutant showed wild-type behaviour.1) All but one of the dedifferentiation features of the dhkA mutants was a delay in the increase in cell counts during dedifferentiation, although it was not clear from the Katoh data whether this apparent growth defect was specific to dedifferentiation, or a more general growth defect caused by loss of dhkA. In several papers from the Shaulsky/Loomis labs, the dhkA mutant displays a very strong developmental defect (e.g. EMBO J15: 3890-8). One possibility is that the delay in increase in cell number during dedifferentiation is a knock-on effect of the defective cell state during development.2) The one phenotype apparent in the dhkA is strongly induced during development, but strongly and rapidly repressed during dedifferentiation, under all culture conditions. This implies a developmental role rather than a dedifferentiation role for the protein, again supporting the view that the dhkA phenotype during dedifferentiation is non-specific. Overall, we feel the dhkA phenotype fits well with the mutants described in our study (forG and rasS) that dedifferentiate fairly effectively despite an underlying cell health problem.3) Our RNAseq data shows that dhkA expression profiles during development and dedifferentiation are now included as a new Figure 3—figure supplement 1A. We have also added a section in the Introduction to introduce the dhkA mutant.We have incorporated this reasoning into an extended paragraph in the Discussion. The Reviewer #1:This report examines gene expression in D. discoideum cells when the cells are starved to induce differentiation, and then transferred to nutrient-rich growth medium to induce dedifferentiation. There are strong similarities but puzzling differences between the first part of this report and a PNAS paper previously published by another lab, and the similarities and differences need to be clarified.1) Results subsections “Genome scale features of dedifferentiation” and “Staging gene expression during dedifferentiation” – since this seems to largely follow the Katoh paper, you should point out similarities and differences.2) Subsection “Genetic robustness of the dedifferentiation programme” – the authors say they cannot find mutants that affect dedifferentiation, but Katoh et al. showed that the dhkA mutant strongly affects dedifferentiation, I'm very puzzled.See the earlier response to the “Essential revisions” section.Reviewer #2:[…] Unfortunately, their attempts at identifying the genetic regulators of the process were unsuccessful. The genetic screen using act8-mNeonGreen was inspired, even though it did not work. However, the remainder of the focused didn't seem as logical. While the choice of protein types  made sense, the chosen genes seemed random. There were much more rational choices within these groups. DhkA is a developmentally regulated signaling protein that is known to be involved in dedifferentiation. ChdA, ChdB and ChdC are supposed chromatin remodeling proteins that are master regulators for developmental gene expression. There are multiple G α proteins that are known to be involved in food sensing during growth. Almost all of the mutants of all of these gene are able to reach the mound stage of development, so can be examined in this dedifferentiation system. While I am not suggesting that the authors perform these experiments in order to have this manuscript published, I would like a clearer rationale for the mutants that they did choose and why they are better choices than others.chdA, chdB and chdC genes in our RNAseq data and found they are strongly induced during development and rapidly repressed during dedifferentiation. These would not be candidates using our criteria. Of the G-α proteins, most showed no induction during dedifferentiation, although two of the genes did. However, the induction showed by these genes was not sufficient to satisfy our induction criteria, and the genes did not pass cutoff. We have expanded the rationale in the text for the selection of the genes we decided to test functionally.These are interesting suggestions of gene classes. We checked the expression of the I would also be wary of claiming that the dedifferentiation programme is genetically robust for the same reasons. Even though the multitude of mutants they tested didn't show large effects on dedifferentiation, they left out some fairly obvious ones. It would be safer to say that dedifferentiation is more genetically robust that differentiation, since there are a lot more genes that disrupt differentiation. However, this probably has more to do with the fact that development and differentiation requires a higher degree of temporal coordination than dedifferentiation. For dedifferentiation, it makes sense that it doesn't matter whether regulated cAR1 expression occurs before or after adenylyl cyclase expression or G α 2 expression. However, during development, the relative timing of expression is crucial.Exactly our view: we have described this in the Discussion.The cryS experiments were critical in demonstrating that cell fate was not responsible for the two different populations of dedifferentiated cells identified based on motility and division speed. I would ask that the control be mentioned showing proper CrS-mNeonGreen expression in the mounds before dissociation otherwise we don't know whether the system worked well-enough to identify actual prestalk cells. I'd also request a reanalysis of the data to see whether the high/low CryS-mNeonGreen expressing cells had the same ratios of high speed/low speed cells as the entire population. It may be that there is an enrichment of one type of cell based on CryS-mNeonGreeen expression. The data should already exist. It would just need to be analyzed differently.Good questions. CryS is a robust prestalk marker in mounds and slugs- we have shown this using multiple approaches (transcriptomics and live imaging) in an earlier study . We carried out the reanalysis requested by the reviewer and found no difference in the motility distributions of the high and low CryS cells. The KS test p-values of this analysis have been incorporated into the text associated with Figure 6.


The rapid increase of bacterial antibiotic resistance could soon render our most effective method to address infections obsolete. Factors influencing pathogen resistance prevalence in human populations remain poorly described, though temperature is known to contribute to mechanisms of spread.To quantify the role of temperature, spatially and temporally, as a mechanistic modulator of transmission of antibiotic resistant microbes.An ecologic analysis was performed on country-level antibiotic resistance prevalence in three common bacterial pathogens across 28 European countries, collectively representing over 4 million tested isolates. Associations of minimum temperature and other predictors with change in antibiotic resistance rates over 17 years (2000–2016) were evaluated with multivariable models. The effects of predictors on the antibiotic resistance rate change across geographies were quantified.Escherichia coli and Klebsiella pneumoniae, European countries with 10°C warmer ambient minimum temperatures compared to others, experienced more rapid resistance increases across all antibiotic classes. Increases ranged between 0.33%/year (95% CI: 0.2 to 0.5) and 1.2%/year (95% CI: 0.4 to 1.9), even after accounting for recognised resistance drivers including antibiotic consumption and population density. For Staphylococcus aureus a decreasing relationship of −0.4%/year (95% CI:  −0.7 to 0.0) was found for meticillin resistance, reflecting widespread declines in meticillin-resistant S. aureus across Europe over the study period.During 2000–2016, for We found evidence of a long-term effect of ambient minimum temperature on antibiotic resistance rate increases in Europe. Ambient temperature might considerably influence antibiotic resistance growth rates, and explain geographic differences observed in cross-sectional studies. Rising temperatures globally may hasten resistance spread, complicating mitigation efforts. For almost a century, antibiotics have been our most effective way to treat bacterial infections, and antibiotics underpin enormous population health gains. However, soon after their initial introduction, bacterial pathogens demonstrated their propensity to acquire and propagate mechanisms to withstand the effects of these agents. Decades of unfettered use of antibiotics has been recognised as a main driver behind the selection and spread of resistant bacteria globally ,2.Antibiotic resistance poses one of the world’s greatest public health threats today, with the potential to render many existing classes of antibiotics ineffective in the near future ,4. To adTemperature is one of the strongest drivers of bacterial reproduction and can also modulate aspects of horizontal gene transfer through which resistance genes can be exchanged ,10. On aHere we use one of the most comprehensive antibiotic resistance databases in existence  ,16 to idWe performed an ecologic analysis of the evolution of country-level antibiotic resistance prevalence in common bacterial pathogens over time across Europe, and evaluated associations with temperature and other predictors over a 17-year period (2000–2016). We built multivariate linear models of antibiotic resistance prevalence over time, for three common pathogens and up to four different subclasses of antibiotics. The study assessed 28 European countries: Austria, Belgium, Bulgaria, Croatia, Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Italy, Latvia, Lithuania, Luxembourg, the Netherlands, Norway, Poland, Portugal, Romania, Slovakia, Slovenia, Spain, Sweden, and the United Kingdom.Escherichia coli (Gram-negative), Klebsiella pneumoniae (Gram-positive), and Staphylococcus aureus (Gram-negative), representing approximately 3.4 million, 0.54 million, and 0.52 million tested isolates, respectively. These pathogens were chosen because they are the most common Gram-positive and Gram-negative pathogens that cause infections globally and align with a previously-published study that investigated these same three pathogens in the US [Antibiotic resistance data at the country level were collected as part of national surveillance for 28 countries across Europe, for three common bacterial Gram-positive and Gram-negative pathogens: n the US . E. coli), 3rd generation cephalosporins (E. coli and K. pneumoniae), fluoroquinolones (E. coli and K. pneumoniae), aminoglycosides (E. coli and K. pneumoniae), and meticillin (S. aureus). Antibiotic resistance data originate from EARS-Net [Antibiotic resistance was identified as prevalence of resistance (% resistant) among reported isolates for a given year, country, and antibiotic subclass. Antibiotic susceptibility was evaluated, where available, for the following subclasses : aminopeEARS-Net  and reprAntibiotic consumption here refers to either sales data, reimbursement data, or both, depending upon the country. We do not distinguish between these two sources, rather referring to them both as ‘consumption’. To account for country level differences in antibiotic consumption, we used annual country level antibiotic consumption data from the European Surveillance of Antimicrobial Consumption Network (ESAC-Net) [SAC-Net) . Specifiminimum temperature has been identified as important when describing species survival [Our second predictor was ambient temperature. Given that survival ,19 and wsurvival , we focuFirst, we calculated the country-level annual average minimum temperature using modelled and assimilated meteorological data, available at a native geographic resolution of 0.5° × 0.625° from the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) . The MERTable S1. It is important to note that using weather station data removes the theoretical modelling assumptions implicit in reanalysis data such as MERRA-2.The other two approaches to calculate minimum temperatures were conceived to assess the sensitivity of our findings to our choice of climate data source and spatial resolution. For these two subsequent approaches, we used city-level temperature data obtained from (i) MERRA-2 data and (ii) local weather stations. For (i), daily minimum temperature from MERRA-2 were obtained from the single 0.5° × 0.625° grid cell covering the centroid of each capital city, and the annual mean for each country was computed over the calendar year. For (ii), we obtained annual average minimum temperature from the most complete weather station data corresponding to a capital or populous city, as provided by the European Climate Data & Assessment (ECD&A) project of the Royal Netherlands Meteorological Institute (KNMI). A total of 26 of the 28 countries had available weather station data, and the list of cities used for each country can be found in 2) for each country and year using annual population estimates obtained through Eurostat. We computed the population density , and population density (tertile)) to assess for potential confounding and effect modifications. Log scales were used for antibiotic consumption given the large spread of values. To ease visualisation of antibiotic resistance across multiple different antibiotics, we centred the data about the mean and normalised by the standard deviation, by pathogen, antibiotic, and year. To further visualise temporal trends, we computed the slope representing the effect, by year, of minimum temperature on antibiotic resistance as well as the rate of change of antibiotic resistance over the 17-year period. These were done for each pathogen type and subclass of antibiotic.To visualise the distribution of antibiotic resistance and minimum temperature across Europe, we generated choropleth maps of (i) normalised antibiotic resistance across the three pathogens and (ii) annual average minimum temperature, each summarised over the 17-year time series. To produce a summary measure of antibiotic resistance, we first computed the weighted average of antibiotic resistance for each year, normalised by pathogen and antibiotic subclass and weighted by the number of isolates tested for a given pathogen and antibiotic subclass. The simple average of these values across years was then used to visualise the average normalised antibiotic resistance per country between 2000 and 2016. We also mapped the annual average minimum temperature by country as the mean of annual minimum temperature over the 17 years. Maps and figures were generated using the ‘ggplot2’ package in R.2), antibiotic consumption , and the interaction between time and minimum temperature. These models were replicated across each pathogen and antibiotic subclass. They had the structure presented in Equation 1, where Tmin is the minimum temperature in Celsius, time the calendar year, Population Density the population density (persons/km2), Antibiotic Consumption the antibiotic consumption , and jCountry the dummy variable for the jth country, where j = (28 − 1 = 27). 1–27β represent the effect of these variables on antibiotic resistance. The linear model assumes a normal distribution of errors (ε).Multivariate linear models were used to measure the association between minimum temperature (°C) and antibiotic resistance prevalence over time, adjusting for country, year, population density  by the observed changes from year to year in the data. We then calculated the distributions of values for each individual term across countries and years. Given that 2β is constant across years and countries, we performed this step on the four rightmost terms of Equation 2.Equation 2 captures how the rate of change of antibiotic resistance evolves in time for each pathogen and antibiotic subclass. To determine the contribution of each of the terms to rates of change of antibiotic resistance, we estimated their values by approximating the time derivatives .All relevant ethical guidelines were followed to conduct this study; due to the use of publicly available, anonymised and aggregated data, this study did not require an institutional review board (IRB) and/or ethics committee approval.E. coli and K. pneumoniae has increased over time for most countries in Europe , while S. aureus resistance to meticillin has generally decreased over time . In the same time period, however, country-specific temporal trends in two potential predictors of resistance, minimum temperature and antibiotic consumption, show no clear temporal tendencies in Figures S4 and S5. Countries have generally experienced steady increases or decreases in population density .Antibiotic resistance in Figures S7A–C; Figures S8A–C). In particular, note how the slope for the relationship between temperature and resistance increases with time (e.g. as years increase) in subfigures A (solid lines) and C (dashed lines), indicating that antibiotic resistance increases faster at higher temperatures. We also observed evidence for this relationship differential by antibiotic use, with a stronger relationship (larger slope) between temperature and increases in resistance at higher rates of higher antibiotic use . Such evidence is consistent with previous findings across the US [We found evidence of a positive linear association between minimum ambient temperature and antibiotic resistance across all countries, years, pathogens, and antibiotic subclasses , and obss the US .Figure S9). For aminopenicillin resistance, the effect of minimum temperature was more modest but still larger than that of the other predictors . In Figure S10, we show that the variability in minimum temperature across countries in the data is much larger than the within-country temporal variability in minimum temperature over the 17-year time period, and countries experienced relatively small changes in population density and antibiotic consumption from year-to-year as shown in Figures S5, S6. Thus, for each pathogen and antibiotic subclass, our second result suggests that the most important contributor to differences in rates of change of antibiotic resistance across Europe is local ambient temperature.We developed a model relating temperature to antibiotic resistance accounting for time, antibiotic consumption, population density, and country-specific characteristics, described in the methods. By taking the time derivative of our primary model, Equation 1, we were able to assess how the rate of change of antibiotic resistance evolves in time for each pathogen and antibiotic subclass, as well as the extent to which cross-country variations in temperature and other predictors contributed to the rates of change of antibiotic resistance (Equation 2). Quantifying, for each year and country, the contribution of each predictor to the rate of change of antibiotic resistance, we found that differences in temporal rates of change of antibiotic resistance across geographies were driven mainly by spatial and temporal variations in minimum ambient temperature. In comparison contributions from other predictors that included temporal changes in population density, antibiotic consumption, and minimum temperature were smaller  given by:S7D–G, S8D–G). Over the study time period and controlling for national antibiotic consumption, population density, and constant country-specific confounders, we found that warmer countries, with 10°C larger values in average minimum temperature, experienced an increased rate of change of antibiotic resistance by 0.33%/year (p<0.001), 0.55%/year (p<0.001), and 0.57%/year (p<0.001) for E. coli resistance to aminoglycosides, 3rd-generation cephalosporins, and fluoroquinolones, respectively  and 1.2%/year (p<0.01) for a 10°C increase in temperature across countries, respectively . Interestingly, we observed a decrease in the rate of change of antibiotic resistance across countries by approximately 0.4%/year (p<0.05), with a 10°C increase in minimum temperature, for meticillin resistant S. aureus (MRSA).Consequently, we found that warmer ambient minimum temperatures had a significant effect on the rates of increase (or in one instance decrease) of antibiotic resistance over time, a phenomenon consistent across most pathogens and antibiotic classes . For a few pathogen and antibiotic combinations, lower resistance was associated with more densely populated countries .We also observed that higher values of antibiotic consumption, thought to have important roles in conferring antibiotic resistance, including through population-level selective pressure ,22, were p<0.01, . Across Supplementary tables, S2, S3). Moreover, by removing the within-country temporal variability in minimum temperature, and conducting our analysis using a fixed 17-year average minimum temperature we recovered our original findings (Table S4). The latter result establishes the presence of a long-term effect of minimum temperature on the rate of increase of antibiotic resistance. Our attempts to identify potential short-term climatic influences of our set of predictors on antibiotic resistance, via time-series analysis, did not lead to consistent patterns. For this, we conducted a post-hoc analysis on the direction of the changes (time derivatives), from one year to the next, of minimum temperature, antibiotic consumption, and antibiotic resistance. We calculated the proportion of times for which the direction (increase/decrease) of annual changes of antibiotic resistance and the predictors were the same. This metric, often called ‘hit rate’, captured the congruence in the directional movement of trends in antibiotic resistance, minimum temperature, and antibiotic consumption. Based on these short-term trends analyses, there was no general pattern suggesting that short-term temporal deviations in temperature and antibiotic consumption, either synchronously or lagged , could explain short-term temporal deviations in antibiotic resistance, on average across countries . Note that a hit rate of about 50% suggests that half of the times one of the signals increased, the other one decreased. So a strong signal takes place when the majority of the times both move up or down. Within some countries and for some pathogens and antibiotic subclasses, there may be strong signatures of short-term trends , which future analyses may explore.Our results were almost identical when we conducted our statistical analysis on two different temperature data sources and two distinct spatial resolutions (country- and city-level), confirming that our findings are robust , as well as diseases related to water and sanitation (e.g. cholera) . To datebapenems . Furtherbapenems . FurtherCompared to previous studies, our study offers evidence for the positive relationship between temperature and antibiotic resistance over a large geographic and temporal scale, across three bacterial pathogens and four drug classes and using data that includes the most comprehensive antibiotic resistance and consumption data from national surveillance networks, the gold standard for this kind of data. Other datasets offer the future promise of evaluating the potential impact of climate on antibiotic resistance on a global scale ,27.While we have a limited understanding of the transmission networks that give rise to the spread of antibiotic resistant organisms and mechanisms of resistance, there is a general understanding that this is a complex process, connecting agriculture, animals, humans, and the broader environment . TemperaTable S5). In addition to gaps in data collection, methods and measures to evaluate antibiotic consumption and antibiotic resistance may change over time . Changes in breakpoints are infrequent occurrences for any given class and do not often occur in synchrony with all other classes, which makes them difficult to adjust for in an analysis. However, their impact on our results is unlikely for the following reasons: we do not expect breakpoints to change as a function of temperature (our exposure); our findings are robust to multiple classes of antibiotics; and breakpoint changes based on the introduction of a new drug class are not necessarily reflected in antibiotic consumption immediately after introduction, and this likely varies by country.Limitations to our study include issues inherent to data collection and databases used, such as gaps in national data reporting over time, both systematic (e.g. Lithuania and Latvia not reporting resistance data until 2005−2006) and random . In this study, gaps in data reporting and collection apply in particular to resistance data sourced from EARS-Net and antibiotic consumption data sourced from ESAC-Net. To address the systematically missing data for countries from 2000–2005, we report a separate analysis for 2006–2016 and show that our original findings hold (Table S6) we introduced two time-varying predictors (i) national gross domestic product (GDP) and (ii) total national health expenditure, and this resulted in no notable changes in the study conclusions.Our study dataset was also limited to annual national antibiotic resistance levels, restricting our geographic analysis to the country level and our temporal analysis to the yearly level. As such, evaluating associations on smaller geographic (e.g. state/city) or time  scales was not possible. Evaluating intra-year temperature fluctuations and resistance patterns may lead to additional important insights, and should be pursued with the availability of more granular data. Lastly, the ability to quantify and include potential confounders related to policy  is currently limited, but would improve the ability to test and control for the effects of policy implementation on the rates of antibiotic resistance spread over the years. As a sensitivity analysis (If future studies confirm that the rate at which antibiotic resistance accumulates in human pathogens is influenced by temperature at the global scale, directly or indirectly, then our findings suggest that future increases in global temperature may yield faster increases in antibiotic resistance . This fiEstimating the health and economic burden of antibiotic resistance globally is challenging: one extreme estimate suggests that attributable mortality due to antibiotic resistance could be on the order of ‘millions’ annually by 2050, with annual economic burden in excess of ‘billions’ of US dollars -38. Whil


Striga hermonthica has developed both promiscuous and type‐specific SL receptors as part of its host recognition strategy.Strigolactones (SLs) are a diverse class of butenolide‐bearing plant hormones associated with several processes of major agricultural concern. SLs initiate symbiosis between plants and arbuscular mycorrhizal fungi, cause germination of crop‐devastating parasitic plants, and inhibit shoot branching in vascular plants. SLs are perceived by dual receptor‐hydrolase proteins, and capturing the intact ligand inside the receptor remains a key challenge for structural biologists. In addition, many discovered SLs are hard to obtain and too unstable to work with. In a computer‐based approach, we investigated the interaction of 20 different SL molecules with nine crystal structures of SL receptors. Our results suggest an important role of the active site for ligand binding and orientation, and that the parasitic plant  We suggest that a flexible ligand‐binding pocket allows the orientation of SL molecules, driven by the active site, and that the parasitic plant 22.1ε atom in the indole plane, therefore, depending on the orientation of its side chain toward a ligand, tryptophan may be considered hydrophilic. : 20, 20, 30 for AtD14; 30, 20, 20 for OsD14; 20, 26, 20 for PhDAD2; 30, 20, 20 for ShD14; 20, 20, 30 for ShHTL1; 30, 20, 20 for ShHTL4; 20, 20, 30 for ShHTL5; 20, 20, 30 for ShHTL7; 20, 20, 30 for ShHTL8. Centers were : −4.556, 4.65, 55.232 for AtD14; 27.259, 14.911, 18.881 for OsD14; −39.109, −37.336, 11.842 for PhDAD2; 24.297, 22.909, 71.445 for ShD14; 19.419, 4.403, 17.932 for ShHTL1; −9.18, −24.374, 1.424 for ShHTL4; −12.748, 26.29, −8.368 for ShHTL5; −20.458, −16.024, −20.27 for ShHTL7; 18.786, −7.138, 4.705 for ShHTL8. Results were analyzed with Phyton Molecule Viewer and visualized using CCP4mg. Distances between atoms were measured with Coot , converted into PDB files with Chem3D (PerkinElmer), and prepared as PDBQT files using AutoDockTools  MD were performed. MD production simulations were performed for 10 ns.Molecular dynamics (MD) simulations were carried out with GROMACS 2020.1 : 4IH4 (AtD14), 3W04 (OsD14), 4DNP (PhDAD2), 5Z7Z (ShD14), 5Z7W (ShHTL1), 5Z7X (ShHTL4), 5CBK (ShHTL5), 5Z7Y (ShHTL7), 6J2R (ShHTL8).33.1To evaluate the reliability of our molecular docking procedure, we carried out docking experiments with existing ligand‐receptor structures and compared our results to the experimental crystal structures. We used the crystal structures of PhDAD2 in complex with glycerol . All mutants failed to orientate the ligand the way the wild‐type proteins were able to. In the MD simulation, orobanchol in AtD14 S97A, and in AtD14 S97A H247A did rotate inside the binding pocket but stabilized with the D‐ring at a position around the center of the binding pocket Figure . In both3.5A. thaliana and the corresponding amino acids in the other receptors contributed to the docking of all SL molecules herein. We further identified residues F136, V144, and V194 making contacts to at least 80% of all successfully docked SL molecules, and residues F28 and F126 contributing to the interaction of about half of all successfully docked SLs ‐GR24  are part of the binding pocket wall and were involved in making contacts to SL molecules in all of our docking experiments where an SL had successfully entered the binding pocket. The fact that these residues are immediately adjacent to glycines might suggest intrinsic flexibility of the binding pocket, since glycine residues display extraordinary flexibility due to their lacking side chain  assays ‐GR24 into ShHTL1, which is in agreement with the results from the germination experiments in the previously mentioned study (Toh et al., Arabidopsis (Wang & Bouwmeester, S. hermonthica receptors appeared more specific, such as ShHTL8 for avenaol and zealactone and ShHTL4 for zeapyranolactone and lotuslactone.We observed significant variation in ligand binding by different SL receptors from S. hermonthica might have developed both promiscuous SL receptors that perceive almost all SL molecules tested herein, and specific ones that display a narrower recognition toward SLs produced by certain hosts or SLs from a certain type. This might have led to increased fitness of S. hermonthica because it can modulate specific responses toward individual hosts and at the same time express receptors for SL molecules for which no specific receptor has evolved yet. Hopefully, biochemical experiments will be able to relate our results to affinities between SL molecules and different receptors. It remains unclear whether the germination of Striga seeds can be stimulated by SL binding to a single receptor or if integration of several receptor signals is required. It will also be interesting to see how receptor specificities differ from those in Striga asiatica, a parasitic plant that has 17 potential SL receptors (Yoshida et al., Phelipanche, which has recently been demonstrated to possess at least one receptor with enzymatic activity toward SLs (de Saint Germain et al., Our study suggests that The authors declare no conflict of interest associated with the work described in this article.M.B. and J.C. designed the research, M.B. performed the research, and M.B and J.C. wrote the manuscript.Supinfo S1Click here for additional data file.


Pulmonary infection is the most common complication to develop after intracerebral hemorrhage (ICH). Antibiotics have certain limitations when used to treat pulmonary infection, while Tanreqing injection (TRQI) is extensively used to treat pulmonary infection as an adjuvant to antibiotics. The aim of this meta-analysis was to investigate the clinical efficacy of TRQI for the treatment of lung infection secondary to ICH.Randomized controlled trials (RCTs) assessing the combination of TRQI and antibiotics compared to antibiotics alone for pulmonary infection after ICH were comprehensively searched for in 7 electronic databases from their establishment to August 2020. Two independent researchers conducted the literature retrieval, screening, and data extraction. The assessment tool of Cochrane risk of bias and Review Manager 5.3 software were applied to assess the methodological quality and analyze the data, respectively.Seventeen RCTs involving 1122 patients with pulmonary infection after ICH were included. Compared to antibiotics alone, the combination treatment enhanced the clinical effective rate, shortened the hospital stay, reduced the white blood cell, procalcitonin, and C-reactive protein levels, ameliorated the times to the resolution of fever, cough, and lung rales, and increased the oxygenation index. The evidence indicated that TRQI combined with antibiotics caused no adverse reactions.Our study showed that the combination of TRQI and antibiotics was effective for treating pulmonary infection after ICH. However, high-quality multicenter RCTs are needed to further verify the clinical efficacy of TRQI due to the publication bias and the low methodological quality of the included RCTs. The mortality rate within 1 month of ICH is as high as 46.5%. Most surviving ICH patients have significantly limited function regarding daily activities, with only 12% to 39% regaining functional independence. In addition to the brain tissue damage caused by primary and secondary injuries, severe complications can also lead to poor function; the most common and most serious complication is lung infection.Intracerebral hemorrhage (ICH) refers to primary nontraumatic cerebral parenchymal hemorrhage, also known as spontaneous cerebral hemorrhage. ICH is a common subtype of stroke, accounting for 10% to 20% of all strokes, and it is characterized by high disability and mortality rates. age, disturbances of consciousness, swallowing dysfunction, bed rest, vomiting, history of smoking, cardiac insufficiency, underlying lung diseases, and diabetes,–9 The other type of factor relates to the use of preventive measures after hospital admittance, including nasal feeding therapy, ventilator therapy, and drug therapy.–12 Once a patient with ICH develops pulmonary infection, the treatment duration and the hospital stay may be prolonged, the cost may increase, and the patient's life may even be endangered. Therefore, early diagnosis and timely treatment of lung infection after ICH significantly improves the prognosis of patients. However, the extensive use of antibiotics to prevent and treat pulmonary infection can very easily lead to drug resistance, and the treatment effects will decline.,15Many factors influence pulmonary infection after ICH. One type of factor is the patient's general condition and related factors, including the patient's gender,,17 are widely used. Many studies have shown that combining Chinese medicine preparations and western medicines can produce synergistic effects.–20 Tanreqing injection (TRQI) is a famous and effective Chinese medicine preparation. It is composed of Scutellaria baicalensis, cornu saigae tataricae, fel ursi pulvis, flos lonicerae, and fructus forsythia. It has antiviral, antibacterial, and anti-inflammatory effects, and can effectively treat pneumonia, upper respiratory tract infection, and chronic obstructive pulmonary disease.–24 Experimental research has shown that TRQI not only has an antibacterial effect but it also synergistically increases the antibacterial activity of antibiotics when used in combination. Studies have shown that TRQI can effectively treat pulmonary infection that is complicated by other diseases.,27 Although many clinical studies have shown that TRQI can be used to treat pulmonary infection secondary to ICH, its efficacy has not been systematically reviewed in a meta-analysis. Hence, we conducted a meta-analysis to assess the clinical curative effect of TRQI in patients with pulmonary infection secondary to ICH.Traditional Chinese medicine preparations, with clear curative effects and high bioavailability,2 checklist.This meta-analysis was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA)2.1Since this study is a meta-analysis with no patient recruitment and personal information collection, the approval of the ethics committee is not required.2.2Randomized controlled trials (RCTs) that met the following conditions were included:1.Patients were diagnosed with pulmonary infection after ICH (with clear diagnostic criteria).2.All patients received conventional antibiotics, such as ceftriaxone sodium, cefuroxime sodium, levofloxacin lactate, cefoperazone sodium, or sulbactam sodium. The control group was given antibiotics only, while the experimental group was given TRQI combined with antibiotics.3.Outcomes included at least one of the following: the clinical effective rate (the primary outcome), length of hospital stay, procalcitonin (PCT), C-reactive protein (CRP), and white blood cell (WBC) levels, times to the resolution of fever, cough, and lung rales, oxygenation index (OI), and adverse reactions (ADRs). The clinical effective rate was calculated using the following formula: (number of cured patients + number of patients with notable improvement + number of patients with improvement) / total number of patients × 100%.4.The study was an RCT.2.3The exclusion criteria included:1.Non-RCTs.2.The patients had other cerebrovascular diseases complicated with pulmonary infection.3.Incomplete or incorrect data.4.The outcome data could not be analyzed.2.4Two independent researchers conducted literature searches using the China Science and Technology Journal Database (VIP), Chinese Biomedical Literature Database (CBM), Wanfang Database, China National Knowledge Infrastructure (CNKI), Cochrane Library, PubMed, and Embase from database establishment to August 2020, with no language restrictions. The search terms were as follows: (#1) cerebral hemorrhage OR hematencephalon OR encephalorrhagia OR intracerebral hemorrhage OR brain hemorrhage OR ICH; (#2) pulmonary infection OR pneumonia OR lung infection; (#3) Tanreqing OR Tanreqing injection OR TRQI; (#4) #1 AND #2 AND #3. The references of the included articles were also searched to avoid missing any relevant RCTs.2.5The retrieved articles were screened for potential inclusion by 2 independent researchers (XWS and SW), and if any disagreements were encountered, a third researcher (LDX) resolved them. Regarding the included RCTs, the extracted data were as follows:1.first author and year of publication;2.sample size, gender distribution, and mean age;3.types, dosages, and duration of treatments;4.outcomes and ADRs.2.6 The tool includes 7 items:The Cochrane risk of bias tool was used to assess the methodological quality of the included RCTs.1.generation of random sequence;2.concealment of the allocation plan;3.blinding of subjects and researchers;4.blinding of outcome evaluators;5.completeness of the outcome data;6.selective reporting of the results;7.other sources of bias.Each item is evaluated as unclear, high risk, or low risk. If any disagreements were encountered, a third researcher (LDX) resolved them.2.7I2 statistics were used to evaluate the heterogeneity among the RCTs. If the heterogeneity across studies was low (P ≥ .1 and I2 < 50%), a fixed-effect model was applied for data analysis. If the heterogeneity across studies was high (P < .1 and I2 > 50%), a random-effects model was applied to analyze the data. The sources of heterogeneity were confirmed using subgroup analysis. Publication bias was planned to be assessed using a funnel plot if there were >10 studies.Review Manager 5.3 software was used to analyze the data. Dichotomous variables are presented as odds ratios (ORs) and continuous variables as mean differences (MDs). Additionally, 95% confidence intervals (CIs) were calculated for these statistics. Qualitative and 33.1Based on the search strategy, we retrieved a total of 200 articles after searching 7 databases, comprising 119 from Wangfang, 37 from CBM, 25 from CNKI, and 19 from VIP . After eliminating duplicates and screening the titles and abstracts, 27 documents were obtained for further screening. There were 10 documents that did not meet the inclusion criteria; the details are as follows: not RCTs (1), the patients had other cerebrovascular diseases complicated with pulmonary infection (4), the intervention did not meet the inclusion criteria (3), incomplete or incorrect data (1), and the outcome data could not be analyzed (1). Finally, 17 RCTs were enrolled in the meta-analysis. Figure 3.2A total of 17 RCTs involving 1122 patients were included, all of whom were from mainland China, comprising 565 in the experimental groups and 557 in the control groups. The maximum and minimum sample sizes were 100 and 30, respectively. The dosage of TRQI was 20 ml once per day (10 RCTs) or 30 ml once per day (7 RCTs). The treatment duration ranged from 7 to 16 days. TRQI was administered by intravenous drip in all cases. Table 3.3Two studies (which were considered low risk) clearly illustrated the method of random sequence generation; the remaining 15 studies (which were considered of unclear risk) described the method used to generate random sequences as “random” but did not describe the specific randomization method. All of the studies (which were considered of unclear risk) failed to mention allocation concealment. One study (which was considered low risk) blinded the subjects and researchers; the remaining studies (which were considered of unclear risk) did not mention blinding of the subjects and researchers. All of the studies (which were considered of unclear risk) failed to clarify whether there were other biases. Figures 3.43.4.1–45 involving 1062 patients reported the clinical effective rate of pulmonary infection secondary to ICH. The results of the meta-analysis showed that the clinical effective rate of TRQI combined with antibiotics was superior to that of antibiotics alone  , a random-effects model was applied for analysis. The results displayed that TRQI adjuvant treatment effectively reduced the length of hospital stay  , 10 days , and 14 days . Thus, the results indicate that the heterogeneity may be related to the varying treatment durations    Fig. A.3.4.6,40,42,46 involving 410 patients reported the time to the resolution of cough. Due to the obvious heterogeneity , a random-effects model was used for data analysis. TRQI combined with antibiotics relieved cough more rapidly than antibiotics alone   Fig. B.3.4.7,46 involving 160 patients reported the time to the resolution of lung rales. TRQI combined with antibiotics had obvious an advantage regarding shortening the time to the resolution of lung rales compared to antibiotics alone    RCTs reported on ADRs , so definitive conclusions cannot be drawn. The ADRs listed in the TRQI instructions mainly include dizziness, nausea, vomiting, allergic reactions, and itching or rash, which are mainly related to the age and physique of the patients, solvent used, medications that TRQI is combined with, and intravenous drip speed.The overall methodological quality of the RCTs enrolled in this study was not high. All of the studies were randomized, but no specific randomization method was described for 15 of them. None of the RCTs mentioned allocation concealment and none clarified whether there were other biases. Only 1 RCT reported double-blinding (of subjects and researchers). These issues may weaken the reliability of the evidence in our study.Based on clinical efficacy, we created a funnel plot to assess publication bias and found that it was asymmetric, indicating a small degree of publication bias. Although we conducted a comprehensive literature search, this study lacks the support of other languages, unpublished studies and grey articles, which may lead to selection bias.This meta-analysis objectively assessed the clinical efficacy of TRQI in combination with antibiotics, and it provides medical evidence for the therapeutic use of TRQI for pulmonary infection secondary to ICH. However, there were several limitations. Since TRQI is exclusively used in China, therefore, the recruited patients in the RCTs were all from China, with a lack of patients from other countries. Some of the RCTs had small sample sizes, so it is uncertain whether they had any influence on the assessment of the clinical efficacy of the combined treatment of TRQI and antibiotics. Hence, high-quality multicenter RCTs are needed to provide more solid evidence for the use of TRQI.5This meta-analysis showed that the combination of TRQI and antibiotics may improve clinical efficacy, shorten the hospital stay, reduce inflammation levels, and ameliorate other clinical symptoms and signs, and the evidence indicated that the combination treatment is safe. However, due to the small sample sizes, low methodological quality, and potential publication bias related to the included RCTs in this study, large high-quality multicenter RCTs are needed to further verify the efficacy of TRQI for treating lung infections after ICH.Conceptualization: Dongrui Zhou, Lingqun Zhu.Data curation: Ruijia Liu.Formal analysis: Fengzhi Liu, Shuangshuang Zhang.Funding acquisition: Jingling Chang.Methodology: Xiaowei Shi, Fengzhi Liu, Shuang Wu.Software: Dongrui Zhou.Supervision: Liandi Xie, Lingqun Zhu.Visualization: Liandi Xie.Writing – original draft: Dongrui Zhou.Writing – review & editing: Liandi Xie, Xiaowei Shi, Jingling Chang.


The key objective of this study was to develop marble-based geopolymer concrete and examine the viability of its application as a sustainable structural material for the construction industry. The results of the research demonstrated that marble-based geopolymer concrete can be developed, and its physical/mechanical properties were shown to have a very good performance. According to various experimental tests and a large-scale ready-mixed plant test, it was found that the marble-based geopolymer concrete displayed a good workability and was not easily influenced by temperature changes. The results showed that marble-based geopolymer concrete has an excellent potential for further engineering development in the future. In rece2 into the atmosphere [2 emissions [2 alone is responsible for roughly 65% of global warming, and the cement industry is to blame for about 6% [2 emissions in the world by 2050. Regrettably, at present, no energy efficiency measures are sufficient for mitigation. The greenhouse effect is factor that is largely responsible for global warming. This is a matter of immense concern in terms of preserving pleasant environments, and it is also a warning signal for living communities on Earth [It is reported that producing one ton of ordinary Portland cement (OPC) via the present-day process not only consumes 1.7 tons of essential nonrenewable restricted resources of rocks and minerals ,3 but almosphere , which amissions . CO2 aloon Earth .2 emissions in 2018 reached 266.88 million metric tons [According to the statistics of the Environmental Protection Agency (EPA) of Taiwan, 520.29 kg of carbon dioxide are emitted into the air for every ton of cement clinker produced [ric tons . On the 4 and SiO4 tetrahedral units linked by shared oxygen atoms [Consequently, all of the above challenges have encouraged concrete scientists and researchers to seek alternative construction composites that are durable, sustainable, cost-effective, and user- and eco-friendly with a low carbon footprint and less burning of energy. Recently, geopolymer construction technology has emerged as a possible substitute for conventional construction systems. Geopolymers (GPs) belong to the category of novel inorganic polymers that are cementitious alumino-silicates, demonstrating an amorphous three-dimensional (3D) structure and made up of AlOen atoms . Geopolyen atoms ,12,13, aen atoms ,15,16. Gen atoms ,18 and aen atoms ; little en atoms ,20. All en atoms .Globally, an acceleration in the kinds and quantities of solid waste originating from industries, mining, agricultural and other domestic activities has posed a serious threat to the environment and ecology. In this regard, one of the chief industrial wastes comes from the marble industry and its mining processing stages in the form of sludge, powder or solid wastes. By and large, these wastes are disposed of on open land spaces, creating not only landfill predicaments but also environmental pollution. Furthermore, waste can be generated in the cladding or surrounding rock when the mine is being excavated in the form of a huge quantity of abandoned earth and stones. More often than not, the waste is dumped in any pit or vacant land in the vicinity. This leads to additional risks to the environment in the form of pollution through dust spreads covering a vast area. Particularly in dry conditions, the dust dries up and floats in the atmosphere, and it can deposit on vegetation, plants and crops, creating decaying ecological conditions for flora and fauna. Pure drinking water supply systems or water bodies can get contaminated. There are several ways to reuse marble waste for particular purposes, such as in the brick industry , transpoAccording to a report by the Taiwan Bureau of Mines, marble waste amounts to about 0.62 million tons annually in Taiwan . This re50 was about 24.3 μm. The chemical composition analysis of marble powder is shown in The marble powder was collected from marble mine waste ground by a hammer mill , and its D50 of the GGBFS powder is 12.3 μm. The chemical composition analysis of the powder is shown in 2 and Al2O3, with the CaO content being the highest (about 57.9%). The mineral phase analysis of the GGBFS powder showed an amorphous phase.The ground-granulated blast-furnace slag (GGBFS) powder (S4000) utilized for this study was provided by CHC Resources Co., Ltd. . The D50 was 44 µm. The chemical composition analysis, showing mainly CaO and SiO2, is depicted in The mineral wollastonite was employed to reduce the volume shrinkage powder in this study since it is needle-shaped. The particle size distribution range was 2.6–323.9 µm, and the D2/Na2O and SiO2/Al2O3 molar ratios were prepared by mixing sodium silicate solution , sodium hydroxide and sodium aluminate. The alkali solutions were prepared and ready to use the day before the experiment.Alkali solutions with various SiO2/Na2O (with a controlled NaOH concentration of 4 and 6 M) and 50 SiO2/Al2O3 molar ratios at a 0.55 S/L ratio. After 10 min of thorough mixing, sand and gravel were added and blended for an additional 3 min to prepare geopolymer concrete with various geopolymer/sand/gravel ratios. Geopolymer concrete was then cast in Φ10 cm × 20 cm cylinder molds and left to cure at ambient temperature for three days. After three days, the geopolymer concrete was removed from the molds, and the samples were divided into two sections for indoor and outdoor curing until the testing date. For the indoor curing, the samples were placed in plastic containers, and the humidity was controlled at 90% at room temperature. For the outdoor curing, the samples were exposed to an uncontrolled outdoor environment on the roof of a five-story building in the center of Taipei City, Taiwan. Once cured for testing, the concrete specimens (Φ10 cm × 20 cm) were subjected to physical and mechanical property tests. The results were averaged from at least five samples for each test. The mix proportions of the marble-based geopolymer concrete are listed in Marble-based geopolymer concrete was synthesized by adding marble powder, GGBFS powder and wollastonite powder. After 3 min of pre-mixing, the mixture was then activated with an alkali solution with 1.28 or 1.5 SiO2/Na2O molar ratio on the compressive strength of marble-based geopolymer concrete curing in an uncontrolled outdoor environment, as described elsewhere [The effect of the powder ratio and the SiOlsewhere , is illu2/Na2O molar ratios of 1.28 and 1.5 on the compressive strength when curing in an uncontrolled outdoor environment was also investigated. It was found that under the same powder conditions, the compressive strength of SiO2/Na2O with a molar ratio of 1.28 was better and reached 25–32 MPa over 28 days of curing. For long-term to 365-day curing, the compressive strength reached 40–50 MPa in the same case. The reason might be the SiO2/Na2O molar ratio of 1.5, which has increased sodium silicate. However, sodium silicate will dilute the alkalinity of the alkaline solution, resulting in less dissolution of the precursor gel during geopolymerization. The content is also higher, and it takes a long time to dehydrate. There are large amounts of micropores generated in the structure of the geopolymer that hinder the development of compressive strength, and no such phenomenon is found as the ratio is under the SiO2/Na2O ratio of 1.4 [2/Na2O with a molar ratio of 1.5 was poor in the long term; thus, for the subsequent experiments, we selected SiO2/Na2O with a molar ratio of 1.28.The effect of the SiOA densified mixture design algorithm was used to design the proportion of marble-based geopolymer concrete ingredients ,34. The The initial and final setting times of marble-based geopolymer concrete were measured in accordance with the ASTM C403 standard. The effect of the binder/sand/coarse aggregate ratio on the hardening time of the concrete is displayed in The effect of the binder ratio and curing environment on the compressive strength of marble-based geopolymer concrete under indoor and outdoor curing is shown in The effects of different curing environments on the compressive strength of marble-based geopolymer concrete are depicted in According to the experiment results shown, although the binder amount increase will affect the setting time of geopolymer concrete, the binder will also provide compressive strength to geopolymer concrete. Additionally, geopolymer concrete cannot be soaking in lime water because the Ca ions will react with free Si in the geopolymer, causing a decrease in strength. The above two phenomena are different from OPC concrete.In this test, marble-based geopolymer concrete was prepared by selecting the original designed ratio of the best parameters. Since the compressive strength with curing for 28 days can reach 44.5 MPa, the concentration of the alkali solution is reduced to achieve a low cost.The effect of reducing the NaOH molar concentration to 4 M on the fresh properties of marble-based geopolymer concrete is shown in The effect of reducing the molar concentration on the compressive strength of marble-based geopolymer concrete is shown in The effect of reducing the molar concentration on the shrinkage of marble-based geopolymer concrete is demonstrated in 27Al and 29Si NMR analyses were performed to identify the microstructure of marble-based geopolymer concrete using a Bruker 400 MHz Avance III NMR spectrometer. From the 27Al NMR spectrum, as shown in 29Si NMR spectrum of marble-based geopolymer concrete. A full range of siloxane units was found; as shown, the 29Si signal spans between −75 and −88 ppm in both samples [29Si signals, Peak Fit software, developed by Jandel Scientific, was used to calculate the relative deconvoluted peak areas of each individual 29Si unit. After curve fitting, the fraction area of the 29Si MAS NMR spectra of marble-based geopolymer concrete increased from 51.8% to 52.42% as the alkali solution concentration increased from 4 M to 6 M, as shown in  samples . Due to tructure . TherefoIn this experimental study, marble-based geopolymer was synthesized by selecting the original designed ratio of the best parameters, and the feasibility of applying this concrete (CM5S5-WB) was discussed by utilizing recycled concrete aggregates in place of conventional coarse aggregates. The experimental findings show that the slump was satisfied; statistically, the slump was 280 mm and the slump flow was 690 mm. The effect of using recycled aggregate as a replacement for natural coarse aggregate on the hardening time of marble-based geopolymer concrete is shown in The compressive strength of marble-based geopolymer concrete manufactured with recycled aggregates is shown in The shrinkage rate of the marble-based geopolymer manufactured with recycled aggregate is shown in The test results of the physical properties of the test parameters are represented in The present research study is aimed at stabilizing marble waste by using innovative geopolymer technology as a matrix. Lab-scale experimental findings revealed that the compressive strength of marble-based geopolymer mortar could achieve a compressive strength of 42 MPa after 28 days. Several pilot-scale cubic meter marble-based geopolymer mortar blocks were developed in a ready-mixed plant see . The com(1)Compared to the densified mixture design ratio, the strength of the original-ratio marble-based geopolymer concrete increases with age, whether it is indoors or outdoors. Since compressive strength is derived from the binder, it is proportional to the binder content.(2)2/Na2O with a molar ratio of 1.28, which gives the highest compressive strength of 40–50 MPa for 28-day or long-term 365-day curing.The current best ratio is the original ratio (CM5S5-O), and the alkaline solution is preferably SiO(3)The workability of marble-based geopolymer concrete can meet the requirements of first-stage self-compacting concrete. The slump and slump flow can achieve 520 and 640 mm, respectively.(4)The water absorption rate of recycled aggregate is higher than that of natural aggregate. Therefore, recycled aggregate absorbs more alkali solution than natural aggregate does, which causes the alkali liquid to not react completely with the powder, thus reducing the compressive strength and shortening the setting time.(5)The large-scale test for marble-based geopolymer mortar in a ready-mixed plant was successful. The fresh properties were good for making several cubic meter blocks and Jersey barriers, and the compressive strength reached 43 MPa after 28 days of curing.This study reports the performance of marble-waste-based geopolymer concrete. Based on the results in the previous sections, some conclusions can be made:Although marble-based geopolymer concrete may not be used in reinforced concrete when compared with Portland cement, it still shows good potential for further engineering applications.


Clostridium difficile colitis). The lack of data precludes any strong international recommendations regarding perioperative prophylaxis using systemic antibiotics in this setting.The indication for antibiotic prophylaxis in burn patients remains highly controversial, with no consensus having been reached. The objective of antibiotic prophylaxis is to reduce the risk of postoperative local and systemic infections. Burn surgery is associated with a high incidence of bacteremia, postoperative infections, and sepsis. However, antibiotic prophylaxis exposes patients to the risk of selecting drug-resistant pathogens as well as to the adverse effects of antibiotics , prospective, randomized, double-blinded, placebo-controlled study. The trial will involve the recruitment of 506 adult burn patients with a total body surface area (TBSA) burn of between 5 and 40% and requiring at least one excision-graft surgery for deep burn injury. Participants will be randomized to receive antibiotic prophylaxis (antibiotic prophylaxis group) or a placebo (control group) 30 min before the incision of the first two surgeries. The primary outcome will be the occurrence of postoperative infections defined as postoperative sepsis and/or surgical site infection and/or graft lysis requiring a new graft within 7 days after surgery. Secondary outcomes will include mortality at day 90 postrandomization, skin graft lysis requiring a new graft procedure, postoperative bacteremia (within 48 h of surgery), postoperative sepsis, postoperative surgical site infection, number of hospitalizations until complete healing (> 95% TBSA), number of hospitalization days living without antibiotic therapy at day 28 and day 90, and multiresistant bacterial colonization or infection at day 28 and day 90.The trial aims to provide evidence on the efficacy and safety of antibiotic prophylaxis for excision-graft surgery in burn patients.NCT04292054. Registered on 2 March 2020ClinicalTrials.gov The online version contains supplementary material available at 10.1186/s13063-020-04894-y. Clostridium difficile colitis) [The indication for antibiotic prophylaxis in burn patients remains highly controversial, with no consensus having been reached. The objective of antibiotic prophylaxis is to reduce the risk of postoperative local and systemic infections. Burn surgery is associated with a high risk of bacteremia, postoperative infections, and sepsis –6. Furthcolitis) , 9. Due The question of systemic antibiotic prophylaxis is a major unresolved issue in the management of burn patients, with no existing recommendations with strong evidence. Existing data include small studies at unclear or high risk of bias , 11. To The aim of this study  was therefore to determine whether preoperative antibiotic prophylaxis before excision/graft surgeries can reduce the incidence of postoperative infections and/or autograft lysis in burn patients.The results of this study will provide important high-quality data to guide physicians treating burn patients and impact future guidelines.The study protocol was designed in accordance with the SPIRIT guidelines  Fig. 1)1). The APostoperative sepsis. Postoperative sepsis is defined by the Sepsis-3 definition  within 7And/or surgical site infection  requirinAnd/or graft lysis (diagnosed within 7 days after surgery) needing a new graft procedure The primary outcome is a composite outcome of postoperative infection defined as follows:Mortality at day 90Skin graft lysis (diagnosed within 7 days after surgery) requiring a new graft procedureSurgical site infection requiring treatment with at least 5 days of systemic antibiotic therapy (diagnosed within 7 days after surgery)Postoperative bacteremia (within 48 h of surgery)Postoperative sepsis (diagnosed within 7 days after surgery)Number of days of hospitalization until complete healing Number of hospitalization days alive without antibiotic therapy at day 28 and day 90And multidrug-resistant bacterial colonization or infection at day 28 and day 90The secondary outcomes are as follows:Patients over 18 years of age with signed informed consent or inclusion under the emergency provisions of the law Patients with a TBSA between 5 and 40% requiring at least one excision-graft surgery for burn injurySigned informed consent or inclusion under the emergency provisions of the law (article L1122-1-2 of the PHC)All participants will be included and randomized by the clinician in charge of the patient. To be included, patients must meet all the inclusion criteria:Proven severe allergy to cephalosporin or piperacillin-tazobactam or any other antibacterial agent of the penicillin classHistory of severe allergic reaction to any other beta-lactam Patient on antibiotic therapy at the time of inclusionPregnant or breast-feeding patientPatient transferred from another burn unitPatient participants in investigational competitive medicinal product studies on the primary endpointPatients with local or systemic signs of infection requiring immediate systemic antimicrobial therapyPatient under guardianshipPatient under curatorshipPatient not covered by the social securityKnown colonization of the burned area to be excised with tazocillin-resistant germObesityPatients are excluded if any of the following criteria apply:Patients are allocated to treatment with antibiotic prophylaxis or a placebo at a ratio of 1:1. A randomization number will be assigned during randomization. This number will have the following format: R-XXXX . The randomization list will be performed electronically through the CleanWeb application at the clinical research unit “Lariboisière-St Louis” and stratified by center and according to the percentage of burn total body surface area (TBSA 5–20% and 21–40%). The randomization list will be developed by a different biostatistician than the biostatistician who will conduct the final analysis within the CRU “Lariboisière- St Louis.”The randomization will be performed after written consent obtainment and as late as possible before surgery by web software (CleanWeb), which assigns the patient a randomization number.Information about the person who volunteers to a research, the specificity for obtaining consent of the person who is part of the research, and the informed consent document are provided in supplementary material file Pseudomonas aeruginosa will be detected using wound swabs before surgery. If no swabs can be performed before the surgery and colonization is unknown, the patient will be considered not colonized by Pseudomonas aeruginosa.Bacterial colonization of After randomization, a prescription indicating the group corresponding to the arm in which the patient has been assigned will be edited automatically (through CTMS/CleanWeb) and printed out.Pseudomonas aeruginosa or piperacillin-tazobactam (4 g over 30 min infusion) if the burn wound is colonized with Pseudomonas aeruginosa.The antibiotic or placebo will be injected 30 min before starting the surgical procedure. The median number of surgical procedures in these patients is 1 (95% CI 1–2) . In the case of multiple surgical procedures, the same protocol will be applied to the second procedure  but not beyond. These cases are, however, expected to represent only a few cases. In the intervention group, antibiotic prophylaxis will be a cephalosporin (cefazolin 2 g over 30 min infusion) if the colonization is unknown or in the absence of colonization with The administration period will be followed by a clinical follow-up period of 90 days. Patients are closely monitored in the first 7 days after randomization Fig. .No treatment will be prohibited with respect to the research.Data on all patients will be collected by trained study nurses or physicians using a web-based (e-CRF). Data collected and time points are presented in Table Each component of the primary endpoint will be collected at each visit based on the previous definition . The occDetails about quality control, case report form, management of noncompliance, audit and inspection, blinding methods, and serious adverse event notification are specified in supplementary file The primary aim of this trial is to demonstrate superiority in the intent-to-treat analysis of antibiotic prophylaxis infusion versus placebo on postoperative infection. The null hypothesis is that there are no differences in the postoperative infection rate between the two treatment groups.The primary analysis is based on the analysis of the primary criterion in intention to treat.The incidence of postoperative infection, adjusted according to %TBSA, will be compared between study arms using logistic regression with the percentage of burn total body surface area as a covariate. The efficacy of antibiotic prophylaxis will be considered to be proven if the null hypothesis for the primary endpoint is rejected and if the treatment difference is in favor of antibiotic prophylaxis in the sense of a shift to a lower postoperative infection rate under antibiotic prophylaxis.Concerning secondary analysis, all parameters related to an event  will be compared by logistic regression with the percentage of TBSA as a covariate. The time until complete healing will be described with Kaplan-Meier curves and analyzed using the Cox model. The reference time is defined as the randomization time. All patients will be censored at the time of the last observation.The number of hospitalization days living without antibiotic therapy at day 28 and day 90 will be compared between groups by the Mann-Whitney test.Continuous variables will be summarized using the number of observations, mean, standard deviation, minimum, maximum, 25%, 50%, 75% quartiles, and two-sided 95% confidence intervals. Means, medians, minimum, maximum, and standard deviations will be presented to one further decimal place.Categorical variables will be expressed as absolute and relative frequencies (percentages).Missing values will be imputed by a multiple imputation technique.The incidence of the primary endpoint is estimated to be 25% . With an alpha risk of 4.9%  and power = 80%, the number of patients to include to show an absolute reduction of 10% of the primary endpoint, we need to enroll 506 patients (253 in the intervention group and 253 in the control group).N will be allowed for changes in sample size). The O-Brien-Fleming boundaries will be used for nominal alpha values .A steering committee will advise the conduct of the trial . An indeThe sponsor must notify all the investigators any information that could adversely affect the safety of the participants. Assistance Publique Hôpitaux de Paris (AP-HP) is the sponsor of this study and has delegated power to its Clinical Research and Development Department (DRCD) to conduct the study in accordance with Article L.1121–1 of the French Public Health Code. AP-HP reserves the right to terminate the study at any time for medical or administrative reasons. In this case, the investigator will be informed accordingly.In the case of loss to follow-up, the investigator will do his or her best to contact the patient to determine his/her vital status. Mailing address, phone number, and phone number of at least one relative will be collected at inclusion to contact the patient. If a patient leaves the research prematurely, data relating to the participant can be used unless an objection was recorded when the patient signed the consent form. If consent is withdrawn, no data about the participant may be used unless he/she states in writing that he/she does not object. In this case, the participant will be excluded from the research Fig. .Fig. 2CIt should be noted that all amendments will be validated by the institutional review board, and once validated, the content of the amendments will be communicated to all investigators through contact emails and newsletters (on a 3-month basis) and during the investigator meeting.According to Article R.1123-49 of the French PHC, the investigator must notify the sponsor without delay on the day when the investigator becomes aware of any serious adverse event that occurs during a trial as described in Article L.1121-1(1) PHC, except those which are listed in the protocol (see section 10.1.2.2.2) and, if applicable, in the investigator’s brochure as not requiring a notification without delay. These latter should be notified by the investigator to the sponsor in an appropriate delay taking into consideration the specific features of the trial, the serious adverse events, and the modalities specified in the protocol or the investigator’s brochure.Events with fatal outcomeAnaphylactic shockQuincke edemaThe sponsor will especially follow the serious adverse events listed below:The investigator must notify the sponsor without delay on the day when the investigator becomes aware of emerging safety issues, as well as security measures taken.Liver test abnormalities (ALT/AST three times higher than the upper limit)Clostridium difficile colitisAcute kidney injuryThe other events requiring the investigator to notify the sponsor without delay are as follows:All these events will be reported in the trial publication.The indication for antibiotic prophylaxis in burn patients remains highly controversial, with no consensus having been reached. To date, no strategy (antibiotic prophylaxis versus no antibiotic prophylaxis) has shown superiority . The admOur protocol will be the most rigorous and the most likely to address the question of the impact of antibiotic prophylaxis on burn surgery postoperative infections. We expect that the antibiotic prophylaxis strategy will decrease the incidence of postoperative infections . Antibiotic prophylaxis strategy is therefore expected to decrease the need for intensive care/hospital resources, allowing faster BICU/hospital discharge, thereby significantly decreasing costs and ultimately improving patient outcomes. Infection is the main cause of morbidity and mortality in burn patients .We acknowledge that the impact of antibiotic prophylaxis in patients suffering very large burn injuries will need additional studies using an alternative design  due to the very low number of patients suffering very large burn injuries each year.The current protocol is version 1.2, dated 19 December 2019. Recruitment will begin in September 2020. The approximate completion date for recruitment is in September 2024. This trial was prospectively registered before recruitment began. The study protocol was approved by the institutional review board (IRB) of Sud Est IV on 11 December 2019 , and from the agence nationale de sécurité du medicament et des produits de santé (MEDAECNAT-2019-10-00036), it was registered as a clinical trial on 2 March 2020 (NCT03788837) and in EudraCT (No. 2019-002396-34)  of Sud Est IV approvalAdditional file 4. Agence nationale de sécurité du medicament et des produits de santé approval