Two separate linear mixed models revealed that all factors influenced player performance, with age and experience the strongest in each model, respectively. Post hoc Tukey tests indicated that performance was affected by age at each level up until the age of 21 (effect ranging from 0.98 to 3.70 rating points), and by experience at the levels 1–20 and 21–40 matches in comparison to all higher levels of experience (effect ranging from 1.01 to 3.77 rating points). Two segmented models indicated that a point of marginal gains exists within longitudinal performance progression between the age levels 22 and 23, and the experience levels 41–60 and 61–80 matches. Professional sporting organisations may apply the methods provided here to support decisions regarding player recruitment and development.This study aimed to develop a model to objectively benchmark professional Australian Rules football (AF) player performance based on age, experience, positional role and both draft type and round in the Australian Football League (AFL). The secondary aims were to identify the stage of peak performance and specific breakpoints in AF player performance longitudinally. AFL Player Ratings data were obtained for all players ( Identifying when peak performance typically occurs in athletes is an important consideration within professional team sport organisations. Specifically, at what point in an athletes career are they likely to reach their peak. Such information can be used to inform contracting as well as the make-up of team rosters. The identification of peak performance can be measured longitudinally on various time series including the age of an athlete, amount of years within a professional program and their match’s experience . AdditioDespite this, individualised assessment of match performance in professional team sports is commonplace. This includes both subjective assessments of performance, as made by team coaches, management and within the media, as well as objective assessments made through data-driven techniques . AlthougAustralian Rules football (AF) is a dynamic invasion team sport played between two opposing teams consisting of 22 players each (18 on the field and four interchange). In the elite competition of AF, the Australian Football League (AFL), players can be drafted to a professional club and begin playing as early as the age of 18, with various players managing to continue playing into their middle-to-late thirties. There has been a substantial amount of research developed in AF to identify the physical and technical characteristics of individual players with respect to match performance . HoweverIn the abovementioned studies, both In addition to identifying peak player performance, longitudinal research has also looked to identify whether specific changes in trends occur within a time series. Within sport performance, this research has consisted of identifying longitudinal changes in trends of physical performance , game reThe ability to benchmark player performance longitudinally is inherently valuable to many sports, and could be used to support organisational decisions regarding player contracting, recruitment and development . In the There are various player performance measures which are produced commercially within the AFL. The “AFL Player Rankings” is produced by statistics provider Champion Data Pty Ltd., measures player performance by awarding players a fixed value for specific performance actions. The values for these actions were determined relative to their observed relationship to team winning margin . AlternaThe primary aim of this study was to develop a model to objectively benchmark AFL player performance whilst considering their age, experience, positional role and both draft type and round in which they were selected. The secondary aims were to identify the stage of peak performance and specific breakpoints in player performance longitudinally. To achieve these, this study will consider the player characteristics and model types outlined in the abovementioned literature.The AFL Player Ratings were utilised as the objective measure of player performance in this study due to its validity and its equity-based nature . In thisn = 3317.These AFL Player Ratings were obtained from Champion Data Pty Ltd. for all 1034 matches played throughout the 2013–2017 AFL seasons. This included 22 matches played by each team during the regular season rounds, as well as a total of nine matches played throughout the finals series each season. One match was abandoned prior to play during the 2015 season. The AFL Player Ratings data were expressed as a mean season rating for each player across each of the five seasons. The sample included a mean of 3.15 seasons per player (±1.55 SD) among 1052 unique players, giving a total sample size of Data pertaining to player characteristics were also collected in order to assess their relationship with performance. Age (determined by the players age at 31st December of the previous year), experience , positional role classification , were considered as first round selections within the national draft. Further, those drafted after being overlooked in the prior year’s national draft (n = 3) were considered as first round selections within the rookie draft.Further, as part of the entry concessions given to newly established clubs, the Gold Coast Suns and the Greater Western Sydney Giants, 45 players from the dataset were drafted to AFL clubs prior to the 2011, 2012, and 2013 AFL seasons via non-traditional draft methods. Considering the circumstances of these concessions, all players drafted via methods of zone selection, as an underage recruit, through the AFL mini-draft, as an AFL initiative or were pre-listed by an AFL club (Hmisc package (r = 0.83), whilst all remaining associations were weak (r < 0.15). As a result, separate models were created throughout the further analyses, utilising age and experience as the independent variables in each.Descriptive statistics for age and experience, and how they relate to AFL Player Ratings [mean ± 95% confidence intervals (CI)] were obtained. The number of matches played per season and proportion of players were also collected and plotted across age and experience. Prior to undertaking the main analyses, Spearman’s correlation analyses were employed to determine the extent of collinearity between each of the four player characteristics. This analysis was undertaken using the  package  in the R package . This anlme4 package . β0, β1, β2, and β3 are fixed coefficients, and X, Y, and Z are observed covariates. In model (1), Xps and Yps represent the player’s age and positional role for the corresponding season, respectively, whilst Zp represents the category outlining the player’s draft selection, which stays consistent between seasons. The parameter ∝p is a player random effect, which makes the intercept of the model specific to each player and allows for individualised performance projections. The player random effect is treated as constant across seasons and each effect is a draw from a normal distribution with equal variance for all players. The parameter 𝜀ps denotes the player-season residual error. Model (2) takes the exact same form as model (1), however, Xps instead represents a player’s experience for the corresponding season.where PRp = 0) for age and experience, respectively, where means and 90% prediction intervals (PI) are averaged over the levels of positional role and draft for both. A post hoc Tukey test was performed to adjust for multiple comparisons, and to determine whether performance was different within each level of age and experience, and thus identifying a hypothesised breakpoint in performance. To further assess whether a breakpoint exists in each of the linear mixed models, a segmented model (or “piecewise linear model”) was fit to the data to estimate if a change in the trend of the data occurs. This analysis was undertaken using the segmented package  produced a root mean square error of 1.77 and Chi-square values of 356.9 for age, 98.7 for positional role and 57.1 for draft. Comparatively, model (2) produced a root mean square error of 1.82 rating points and Chi-square values of 523.5 for experience, 100.4 for positional role and 21.7 for draft. The values indicate that age and experience had the largest influence on performance in each of the models, respectively, followed by positional role. 0, β1, β2, and β3) for each factor level of the characteristics in each of the respective models.Results of the linear mixed models revealed that all factors affected levels of performance in both models at y, model  producedpost hoc Tukey test indicated that performance was affected by age at various age levels up until the age of 21 (mean differences ranged from 0.98 to 3.70 player rating points). However, no two levels above the age of 21 were seen to exhibit different levels of performance. For experience, differences were seen at the levels of 1–20 matches and 21–40 matches in comparison to all higher levels of experience (mean differences ranged from 1.01 to 3.77 player rating points), and for various experience levels in comparison to 41–60 matches. No differences were seen between any levels above this for experience.Results of the X-axis intercept lines and regression lines were added to The segmented models identified a breakpoint in performance for both age and experience. The results indicate that a breakpoint in age occurs between the age levels 22 and 23, where performance is seen to increase linearly 0.75 rating points per age level prior to this breakpoint, and decline linearly 0.09 rating points per age level thereafter. The breakpoint identified for experience occurs between the levels 41–60 and 61–80, where performance is seen to increase linearly 1.24 rating points per level of experience prior to this breakpoint, and then continue to increase linearly 0.04 rating points per experience level thereafter. By applying the PSRE and the fixed effect estimates from the linear mixed models, various applications can be created to benchmark player performance. For example, Additionally, the PSRE provide a measure of player ranking, which adjusts for the individual fixed effects characteristics. The primary aim of this study was to develop a model to objectively benchmark player performance whilst considering their age, experience, positional role, and both draft type and round in which they were selected. It also aimed to identify the stage of peak performance and specific breakpoints in player performance longitudinally. Separate linear mixed model analyses were implemented to benchmark performance based on the multifactorial fixed effects estimates. Segmented models were fit to these fixed effect estimates to determine if and where a change in the linear trend of performance progression occurs.Visual inspection of the descriptive statistics in Each of the two linear mixed models provide context when looking to benchmark player performance longitudinally in AF. In addition to identifying a universal benchmark trend of performance longitudinally, the models produced in this study allow player specific values to be obtained, by adjusting each of the fixed effects relative to the player’s characteristics in each model. These player specific benchmarks allow for both retrospective assessment of a players past performance against expected performance, as well as to forecast player performance relative to expected characteristics . Applications of these models have the potential to be beneficial in supporting the decision making processes within professional AF organisations. Decisions relating to player recruitment and contracting could be objectively informed by gaining an understanding of the past and future potential performance of players, which the club maybe looking to recruit, resign or remove from their current playing squad. Though the examples provided in this study feature 90% PI, clubs/organisations wanting to be more aggressive with their predictions regarding expected performance could adapt the current models to include lower PI. post hoc Tukey test, both analyses indicate that there is a distinct change in the trend of player performance occurring in each model, occurring at around the age 22, and experience level 41–60, respectively. Specifically, they indicate that this change in the trend represents a point of marginal gains within each of the model, such that once these levels are reached the benchmark level of player performance is expected to somewhat plateau. This indication of marginal performance gains beyond these respective levels could have useful implications for both player development and player recruiting/contracting within professional AF. For example, clubs may look to persist with selection of players who are yet to reach these points of marginal gains (as opposed to older/more experienced players of similar ability), knowing that match opportunities are potentially more detrimental to development of the younger/less experienced players. In regards to player recruiting and contracting, clubs could look to use these breakpoints as an indication of whether the performance of current players and/or potential recruits is likely to continue to improve, or whether their performance has reached a point of marginal gains. Though only one breakpoint was identified for each model in this study, clubs/organisations wanting to further explore the longitudinal performance trends could adapt the current methodology to identify whether multiple breakpoints exist.Though the identified breakpoints found in each model differ marginally to the findings of the Despite minor differences, both the models measured longitudinally on each age and experience might be used for different operational purposes based on the preferences of the organisation. For example, due to the reliance of match opportunity for the model based experience, applications of this model may be more suited to benchmark the performance of players who have experienced long-term injuries or are mature aged recruits. Conversely, for those who have had sufficient match opportunities, the models based on age may be more suitable due to the more progressive nature of age as an independent variable. In addition to providing benchmark levels of performance, the models produced in this study also provide an indication of the point at which peak performance occurs longitudinally. Specifically, the findings imply that on average players reach their peak around the age of 22, or 60 matches experience. In comparison to previous literature, this point at which the average player reaches their peak age is younger than what has been identified in other dynamic team sports such as soccer . Though The PSRE outlined in each of the mixed models could also be used to rank players across the 2013–2017 seasons. Specifically, this type of ranking would be more generalisable than other ranking measures that do not adjust for fixed effects such as those used in our model. Thus it allows comparisons to be made between players across different ages, levels of experience, positional roles and draft selections. Some limitations of this study should also be noted. Though mixed model approaches have been supported in previous literature to account for the fixed and random effects associated with longitudinal player performance; there is also an inherent understanding that the decline in performance after peak is often underestimated as a result of athlete drop out. For example, only the most successful athletes continue to get renewed playing contracts, and are subsequently selected to play at the elite level. Thus meaning that there is likely some level of performance deterioration that goes unnoticed by the model beyond certain ages/levels of experience. Another limitation is that the methodology could include additional metrics, such as time on ground or spatiotemporal data, potentially allowing for further explanation of the results. Future work in dynamic team sports should focus on the continual development of improving objective player performance rating models, as well as decision support applications to assist with operational decision-making in professional sporting organisations. In AF specifically, the development of these objective player performance rating models could look to include further positioning dynamics, similar to that in other team sports .This study produced two types of models benchmarking player performance in the AFL. The first method utilised two separate linear mixed models to identify the effect of individual characteristics on player performance. Each of these models could be used to identify how a player’s performance compares to individualised benchmarks, or to forecast future potential performance. The second method utilised segmented models, finding a point of marginal gains within longitudinal performance of both age and experience. The implementation of these methodologies may provide valuable knowledge for professional AFL organisations. Implications of their use could assist with organisational decisions relating to player recruitment, contracting and development. Future work should focus on the refinement of the models produced in this study as additional seasons of data become available.SM and SR conceived and designed the study. SM compiled the data, conducted the statistical analyses, and wrote the bulk of the manuscript. SR oversaw the data collection and statistical analyses, and contributed substantially to the writing of the manuscript. SK contributed significantly to the methodology, and assisted with writing of the “Materials and Methods” section.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


N-substituted 1,3-thiazolidin-4-one derivatives for the evaluation of their anti-Toxoplasma gondii efficacy. This scaffold was functionalised both at the N1-hydrazine portion with three structurally different moieties and at the lactam nitrogen with substituted benzyl groups selected on the basis of our previous structure-activity relationships studies. Using three different assay methods, the compounds were assessed in vitro to determine both the levels of efficacy against the tachyzoites of T. gondii (IC50 = 5–148 μM), as well as any evidence of cytotoxicity towards human host cells (TD50 = 68 to ≥320 μM). Results revealed that ferrocene-based thiazolidinones can possess potent anti-tachyzoite activity (TI =2–64).We designed and synthesised novel  Tachyzoites are responsible for establishing an acute infection in humans and other animals via ingestion of undercooked meat carrying parasite tissue cysts, by consumption of foods or water contaminated with parasite oocysts disseminated by infected felids, or via transplacental passage in pregnant women7,,Toxoplasma inhibitors have been recently reported, yet complete eradication of bradyzoite cysts remains elusiveT. gondii with minimal host cell cytotoxicity. We report here our continuing efforts towards this objective beginning with a focus on anti-tachyzoite activity. Pursuing our research on the thiazole derivatives endowed with anti-Toxoplasma activity and limited cytotoxicityToxoplasma activity in the micromolar range and a better ability to inhibit the penetration of parasite into the host cell. Starting from these results, we synthesised 33 thiazolidinone derivatives and tested them for in vitro anti-parasitic activity using T. gondii tachyzoites. The newly synthesised compounds, with respect to the previous series, kept the thiazolidinone pharmacophore constant varying the chemical space at the nitrogen atoms. After spectroscopic characterisation to ensure purity, the newly synthesised compounds were evaluated for parasite growth inhibition and cytotoxicity, inhibition of tachyzoite invasion of host cells, and inhibition of intracellular tachyzoite replication.Toxoplasmosis is currently treated with compounds that have been associated with severe side effects ranging from intolerance to allergic reactions102.1–33 three different carbonyl compounds  were dissolved/suspended in ethyl alcohol and reacted directly with thiosemicarbazide and catalytic amounts of acetic acid. The resulting intermediate thiosemicarbazones were reacted with ethyl bromoacetate in methanol and sodium acetate in order to obtain the corresponding 1,3-thiazolidin-4-one derivativesN-(chloromethyl)phthalimide in anhydrous acetone and potassium carbonate gave the N-benzyl derivatives (1–33). All the synthesised compounds were washed with petroleum ether and diethyl ether and purified by column chromatography before characterisation by spectroscopic methods (IR and 1 H/13 C NMR) and elemental analysis. Some representative spectra are reported in the Supplementary materials.As outlined in 3.,N-substituted thiazolidinones derivatives were evaluated in vitro for (i) host cell cytotoxicity as well as for the ability to inhibit tachyzoite growth over a period of 5 days  NMR spectra were recorded at 400 (and 101) MHz on a Bruker spectrometer using CDCl3 or DMSO-d6 as solvent. Chemical shifts are expressed as δ units (parts per millions) relative to the solvent peak. Coupling constants J are valued in Hertz (Hz). Elemental analyses for C, H, and N were recorded on a Perkin-Elmer 240 B microanalyzer and the analytical results were within ±0.4% of the theoretical values for all compounds. All reactions were monitored by TLC performed on 0.2 mm thick silica gel plates (60 F254 Merck). In general, the IR spectrum for derivatives 1–33 showed bands at about 3027 cm−1 (Csp2-H stretching), at about 1690 (C = O stretching), at about 1620 (C = N stretching), and at about 1580 and 1440 (C = C stretching). Some representative spectra were reported in the Supplementary materials.The chemicals, solvents for synthesis, and spectral grade solvents were purchased from Aldrich  and used without further purification. Melting points (uncorrected) were determined automatically on an FP62 apparatus . Neat IR spectra were registered on a Perkin Elmer FT-IR Spectrometer Spectrum 1000. 4.1.n-hexane, petroleum ether, or diethyl ether) and dried under vacuum overnight. The intermediate thiosemicarbazone (50 mmol) reacted with ethyl bromoacetate (50 mmol), in methanol (50 ml) and sodium acetate (50 mmol) at room temperature under magnetic stirring for 24 h. The resulting 4-thiazolidinone was poured on ice, filtered or extracted with chloroform (3 × 30 ml) and purified by column chromatography . Then, the resulting thiazolidinone (50 mmol) was dissolved/suspended in 50 ml of anhydrous acetone in the presence of anhydrous potassium carbonate (50 mmol), and reacted with equimolar amounts of 2-,3-,4-nitrobenzyl bromide, 2-,3-,4-chlorobenzyl bromide, 2-,3-,4-fluorobenzyl bromide, 1-(chloromethyl)naphthalene or N-(chloromethyl)phthalimide for 24–48 h. The products were poured on ice, filtered or extracted with chloroform (3 × 50 ml) and purified by column chromatography  in order to obtain the title compounds in high yields as previously reportedThe initial carbonyl compound (50 mmol) was dissolved/suspended in ethanol (50 ml) and magnetically stirred with thiosemicarbazide (50 mmol) and catalytic amounts of acetic acid for 8–24 h at room temperature. The obtained thiosemicarbazone was filtered, washed with appropriate solvent : δ 0.66–0.69 , 0.85–0.88 , 1.26–1.29 , 1.41–1.46 , 2.07–2.09 , 2.18–2.22 , 4.04 , 5.13 , 7.36–7.40 , 7.56–7.58 , 7.68–7.74 , 8.06–8.08 . 13C NMR  δ 10.9 (CH3), 14.3 (CH3), 22.3 (CH2), 28.1 (CH2), 29.7 (CH2), 32.6 (CH2), 35.6 , 42.9 (CH2), 125.2 (Ar), 128.6 (Ar), 129.1 (Ar), 131.4 (Ar), 134.4 (Ar), 148.7 (Ar), 158.3 , 159.6 (C = N), 172.7 (C = O). Anal. Calcd for C17H22N4O3S: C, 56.33; H, 6.12; N, 15.46. Found: C, 56.67; H, 6.31; N, 15.20.White powder, mp 67–69 °C, 95% yield; 4.1.2.1 H NMR : δ 2.26 , 3.90 , 5.44 , 7.05–7.06 , 7.32–7.48 , 7.59–7.61 , 8.07–8.09 . Anal. Calcd for C16H14N4O3S2: C, 51.32; H, 3.77; N, 14.96. Found C, 51.65; H, 3.50; N, 15.11.Pink powder, mp 150–151 °C, 93% yield; 4.1.3.1H NMR : δ 2.02 , 4.05 , 4.15–4.17 , 4.41 , 4.65 , 5.21 , 7.46–7.47 , 7.58–7.59 , 7.73–7.75 , 8.08–8.10 . 13C NMR  δ 15.8 (CH3), 32.7 , 42.9 (CH2), 67.8 , 69.7 , 70.6 , 82.8 , 125.2 (Ar), 129.0 (Ar), 129.2 (Ar) 131.3 (Ar), 134.5 (Ar), 148.8 (Ar), 159.2 , 164.6 (C = N), 172.8 (C = O). Anal. Calcd for C22H20FeN4O3S: C, 55.47; H, 4.23; N, 11.76. Found: C, 55.23; H, 4.45; N, 11.98.Red powder, mp 195–198 °C, 90% yield; 4.1.4.1H NMR : δ 0.64–0.69 , 0.82–0.84 , 1.09–1.11 , 1.26–1.28 , 2.02–2.12 , 3.79 , 4.77 , 7.42–7.47 , 7.54–7.59 , 7.94–7.95 . 13C NMR  δ 11.0 (CH3), 14.0 (CH3), 22.7 (CH2), 28.5 (CH2), 29.6 (CH2), 30.8 (CH2), 32.5 , 45.6 (CH2), 122.9 (Ar), 123.0 (Ar), 130.4 (Ar), 134.7 (Ar), 139.0 (Ar), 148.2 (Ar), 158.9 , 160.4 (C = N), 172.7 (C = O). Anal. Calcd for C17H22N4O3S: C, 56.33; H, 6.12; N, 15.46. Found: C, 56.59; H, 5.94; N, 15.25.Yellow oil, 65% yield; 4.1.5.1H NMR : δ 2.36 , 4.05 , 5.05 , 7.11–7.13 , 7.54–7.55 , 7.61–7.62 , 7.65–7.69 , 7.83–7.85 , 8.17–8.19 , 8.30 . Anal. Calcd for C16H14N4O3S2: C, 51.32; H, 3.77; N, 14.96. Found: C, 51.19; H, 3.95; N, 15.16.Yellow powder, mp 165–170 °C, 82% yield; 4.1.6.1H NMR : δ 2.22 , 4.01 , 4.17 , 4.43 , 4.69 , 5.03 , 7.66–7.70 , 7.84–7.86 , 8.18–8.19 , 8.32 . 13C NMR  δ 16.2 (CH3), 32.5 , 45.6 (CH2), 67.8 , 69.7 , 70.6 , 82.9 , 123.1 (Ar), 123.7 (Ar), 130.5 (Ar), 135.5 (Ar), 138.8 (Ar), 148.2 (Ar), 159.8 , 164.6 (C = N), 172.8 (C = O). Anal. Calcd for C22H20FeN4O3S: C, 55.47; H, 4.23; N, 11.76. Found: C, 55.68; H, 4.11; N, 11.57.Red powder, mp 171–173 °C, 83% yield; 4.1.7.1H NMR : δ 0.86–0.89 , 0.93–1.01 , 1.13–1.18 , 1.22–1.31 , 1.35–1.42 , 1.54–1.62 , 2.31–2.43 , 3.81 , 5.07 , 7.56–7.61 , 8.18–8.20 . 13C NMR  δ 11.0 (CH3), 14.0 (CH3), 22.8 (CH2), 28.6 (CH2), 29.6 (CH2), 30.9 (CH2), 32.5 , 45.7 (CH2), 124.0 (Ar), 128.7 (Ar), 128.8 (Ar), 129.2 (Ar), 144.6 (Ar), 147.2 (Ar), 158.7 , 160.1 (C = N), 172.6 (C = O). Anal. Calcd for C17H22N4O3S: C, 56.33; H, 6.12; N, 15.46. Found: C, 56.19; H, 6.27; N, 15.68.Yellow oil, 63% yield; 4.1.8.1H NMR : δ 2.15 , 4.03 , 4.17 , 4.42 , 4.67 , 5.04 , 7.64–7.66 , 8.23–8.25 . 13C NMR  δ 16.2 (CH3), 32.6 , 45.8 (CH2), 67.8 , 69.7 , 70.6 , 82.9 , 124.0 (Ar), 129.4 (Ar), 144.4 (Ar), 147.4 (Ar), 159.5 , 164.6 (C = N), 172.7 (C = O). Anal. Calcd for C22H20FeN4O3S: C, 55.47; H, 4.23; N, 11.76. Found: C, 55.68; H, 4.11; N, 11.57.Red powder, mp 214–217 °C, 84% yield; 4.1.9.1H NMR : δ 0.75–0.80 , 0.85–0.90 , 1.27–1.32 , 1.42–1.48 , 2.21–2.26 , 4.00 , 4.91 , 7.12–7.35 . 13C NMR  δ 11.0 (CH3), 14.1 (CH3), 22.7 (CH2), 28.5 (CH2), 29.6 (CH2), 30.8 (CH2), 32.4 , 35.6 (CH2), 115.7 (Ar), 123.4 (Ar), 124.8 (Ar), 129.4 (Ar), 129.8 (Ar), 159.2 , 160.1 (C = N), 161.7 , 172.5 (C = O). Anal. Calcd for C17H22FN3OS: C, 60.87; H, 6.61; N, 12.53. Found: C, 60.54; H, 6.39; N, 12.68.Yellow oil, 64% yield; 4.1.10.1H NMR : δ 2.28 , 4.06 , 4.98 , 7.10–7.21 , 7.33–7.36 , 7.51–7.52 , 7.61–7.62 . Anal. Calcd for C16H14FN3OS2: C, 55.31; H, 4.06; N, 12.09. Found: C, 55.60; H, 3.83; N, 12.21.Orange powder, mp 80–85 °C, 91% yield; 4.1.11.1H NMR : δ 2.14 , 4.02 , 4.16 , 4.42 , 4.67 , 4.96 , 7.19–7.24 , 7.33–7.38 . 13C NMR  δ 16.0 (CH3), 32.4 , 67.8 , 69.7 , 70.5 , 82.9 , 115.7 (Ar), 123.4 (Ar), 124.8 (Ar), 129.9 (Ar), 130.1 (Ar), 159.4 , 161.8 , 164.4 (C = N), 172.5 (C = O). Anal. Calcd for C22H20FFeN3OS: C, 58.81; H, 4.49; N, 9.35. Found: C, 58.69; H, 4.22; N, 9.07.Red oil, 65% yield; 4.1.12.1 H NMR : δ 0.55–0.59 , 0.62–0.70 , 0.81–0.85 , 0.92–1.12 , 1.27–1.31 , 2.03–2.12 , 3.79 , 4.66 , 6.88–6.96 , 7.15–7.23 . 13C NMR  δ 11.0 (CH3), 14.3 (CH3), 22.3 (CH2), 28.2 (CH2), 29.6 (CH2), 30.9 (CH2), 32.4 , 45.7 (CH2), 115.2 (Ar), 123.9 (Ar), 124.2 (Ar), 130.8 (Ar), 139.5 (Ar), 160.0 , 160.4 (C = N), 162.5 , 172.6 (C = O). Anal. Calcd for C17H22FN3OS: C, 60.87; H, 6.61; N, 12.53. Found: C, 60.61; H, 6.82; N, 12.36.Yellow powder, mp 30–31 °C, 81% yield; 4.1.13.1 H NMR : δ 2.33 , 4.05 , 4.93 , 7.12–7.22 , 7.38–7.41 , 7.53 , 7.61–7.63 . Anal. Calcd for C16H14FN3OS2: C, 55.31; H, 4.06; N, 12.09. Found: C, 55.56; H, 3.79; N, 11.84.Yellow powder, mp 84–85 °C, 89% yield; 4.1.14.1 H NMR : δ 2.19 , 4.01 , 4.17 , 4.42 , 4.68 , 4.92 , 7.12–7.23 , 7.40–7.42 . 13C NMR  δ 16.2 (CH3), 32.5 , 45.8 (CH2), 67.8 , 69.7 , 70.6 , 82.9 , 114.8 (Ar), 115.2 (Ar), 124.4 (Ar), 130.9 (Ar), 139.4 (Ar), 159.7 , 162.5 , 164.4 (C = N), 172.7 (C = O). Anal. Calcd for C22H20FFeN3OS: C, 58.81; H, 4.49; N, 9.35. Found: C, 58.99; H, 4.65; N, 9.51.Brown oil, 69% yield; 4.1.15.1H NMR : δ 0.78–0.81 , 0.86–0.90 , 1.02–1.05 , 1.12–1.16 , 1.25–1.34 , 1.47–1.51 , 2.24–2.34 , 3.97 , 4.83 , 7.12–7.18 , 7.34–7.38 . 13C NMR  δ 11.0 (CH3), 14.1 (CH3), 22.8 (CH2), 28.6 (CH2), 29.6 (CH2), 31.0 (CH2), 32.4 , 45.5 (CH2), 115.4 (Ar), 115.7 (Ar),130.1 (Ar), 130.2 (Ar) 132.9 (Ar), 160.4 , 160.8 , 163.2 (C = N), 172.6 (C = O). Anal. Calcd for C17H22FN3OS: C, 60.87; H, 6.61; N, 12.53. Found: C, 61.02; H, 6.77; N, 12.70.Yellow oil, 67% yield; 4.1.16.1H NMR : δ 2.47 , 3.81 , 5.00 , 6.93–7.08 , 7.22–7.52 . Anal. Calcd for C16H14FN3OS2: C, 55.31; H, 4.06; N, 12.09. Found: C, 55.06; H, 3.91; N, 11.84.Pink powder, mp 118–123 °C, 80% yield; 4.1.17.1H NMR : δ 2.22 , 3.98 , 4.17 , 4.42 , 4.69 , 4.89 , 7.17–7.21 , 7.43–7.462 . 13C NMR  δ 16.2 (CH3), 32.5 , 45.6 (CH2), 67.8 , 69.7 , 70.6 , 83.0 , 115.5 (Ar), 115.7 (Ar), 130.7 (Ar), 130.8 (Ar), 132.9 (Ar), 159.8 , 162.1 , 164.4 (C = N), 172.6 (C = O). Anal. Calcd for C22H20FFeN3OS: C, 58.81; H, 4.49; N, 9.35. Found: C, 59.04; H, 4.71; N, 9.47.Red powder, mp 122–127 °C, 82% yield; 4.1.18.1H NMR : δ 0.66–0.76 , 0.85–0.90 , 1.00–1.05 , 1.12–1.20 , 1.25–1.32 , 1.43–1.48 , 2.16–2.26 , 4.05 , 4.93 , 7.13–7.20 , 7.27–7.31 , 7.45–7.48 . 13C NMR  δ 10.6 (CH3), 13.8 (CH3), 22.8 (CH2), 28.7 (CH2), 30.0 (CH2), 31.2 (CH2), 32.4 , 44.2 (CH2), 126.8 (Ar), 127.6 (Ar), 128.1 (Ar), 128.5 (Ar), 129.5 (Ar), 132.9 (Ar), 156.9 , 158.7 (C = N), 171.9 (C = O). Anal. Calcd for C17H22ClN3OS: C, 58.02; H, 6.30; N, 11.94. Found: C, 58.14; H, 6.11; N, 11.76.Orange oil, 60% yield; 4.1.19.1H NMR : δ 2.31 , 3.90 , 5.18 , 7.05–7.06 , 7.22 , 7.36–7.41 . Anal. Calcd for C16H14ClN3OS2: C, 52.81; H, 3.88; N, 11.55. Found: C, 52.66; H, 3.63; N, 11.24.Pink powder, mp 100–102 °C, 87% yield; 4.1.20.1H NMR : δ 2.08 , 4.06 , 4.13 , 4.41 , 4.66 , 5.00 , 7.24 , 7.33 , 7.50 . 13C NMR  δ 16.0 (CH3), 32.6 , 44.0 (CH2), 67.8 , 69.7 , 70.5 , 82.9 , 127.7 (Ar), 128.5 (Ar), 129.5 (Ar), 129.8 (Ar), 132.3 (Ar), 133.5 (Ar), 159.4 , 164.4 (C = N), 172.6 (C = O). Anal. Calcd for C22H20ClFeN3OS: C, 56.73; H, 4.33; N, 9.02. Found: C, 56.55; H, 4.15; N, 9.21.Red powder, mp 143–148 °C, 83% yield; 4.1.21.1H NMR : δ 0.77–0.81 , 0.86–0.90 , 1.02–1.06 , 1.21–1.26 , 1.48–1.52 , 2.24–2.35 , 3.98 , 4.85 , 7.28–7.40 . 13C NMR  δ 11.0 (CH3), 14.1 (CH3), 22.8 (CH2), 28.6 (CH2), 29.6 (CH2), 30.9 (CH2), 32.4 , 45.7 (CH2), 126.7 (Ar), 127.9 (Ar), 130.7 (Ar), 133.5 (Ar), 139.1 (Ar), 139.2 (Ar), 158.9 , 160.4 (C = N), 172.7 (C = O). Anal. Calcd for C17H22ClN3OS: C, 58.02; H, 6.30; N, 11.94. Found: C, 58.28; H, 6.08; N, 11.81.Yellow oil, 68% yield; 4.1.22.1H NMR : δ 2.26 , 3.62 , 4.78 , 6.85–6.88 , 7.05–7.08 , 7.17–7.20 , 7.31 . Anal. Calcd for C16H14ClN3OS2: C, 52.81; H, 3.88; N, 11.55. Found: C, 52.99; H, 3.69; N, 11.73.Pink powder, mp 129–131 °C, 89% yield; 4.1.23.1H NMR : δ 2.21 , 4.01 , 4.17 , 4.43 , 4.69 , 4.90 , 7.36–7.40 , 7.47 . 13C NMR  δ 16.2 (CH3), 32.5 , 45.7 (CH2), 67.8 , 69.7 , 70.6 , 82.9 , 127.2 (Ar), 128.0 (Ar), 128.5 (Ar), 130.8 (Ar), 133.4 (Ar), 139.1 (Ar), 159.7 , 164.5 (C = N), 172.7 (C = O). Anal. Calcd for C22H20ClFeN3OS: C, 56.73; H, 4.33; N, 9.02. Found: C, 56.90 H, 4.04; N, 9.18.Red powder, mp 143–144 °C, 87% yield; 4.1.24.1H NMR : δ 0.54–0.57 , 0.62–0.70 , 0.81–0.84 , 0.89–0.93 , 1.08–1.13 , 1.27–1.30 , 2.03–2.11 , 3.78 , 4.63 , 7.11–7.19 . 13C NMR  δ 11.0 (CH3), 14.1 (CH3), 22.8 (CH2), 28.6 (CH2), 29.6 (CH2), 31.0 (CH2), 32.4 , 45.6 (CH2), 128.8 (Ar), 129.8 (Ar), 132.5 (Ar), 135.7 (Ar), 158.8 , 160.2 (C = N), 172.6 (C = O). Anal. Calcd for C17H22ClN3OS: C, 58.02; H, 6.30; N, 11.94. Found: C, 57.81; H, 6.64; N, 12.16.White oil, 60% yield; 4.1.25.1H NMR : δ 2.34 , 4.03 , 4.90 , 7.12 , 7.41 , 7.54 , 7.61–7.62 . Anal. Calcd for C16H14ClN3OS2: C, 52.81; H, 3.88; N, 11.55. Found: C, 53.05; H, 4.02; N, 11.32.White powder, mp 146–151 °C, 81% yield; 4.1.26. H NMR : δ 2.21 , 3.99 , 4.17 , 4.42 , 4.68 , 4.89 , 7.42 . 13C NMR  δ 16.2 (CH3), 32.5 , 45.6 (CH2), 67.8 , 69.7 , 70.6 , 82.9 , 128.8 (Ar), 130.4 (Ar), 132.7 (Ar), 135.7 (Ar), 159.8 , 164.4 (C = N), 172.6 (C = O). Anal. Calcd for C22H20ClFeN3OS: C, 56.73; H, 4.33; N, 9.02. Found: C, 56.95 H, 4.57; N, 8.83.Red powder, mp 167–169 °C, 87% yield; 14.1.27.1H NMR : δ 0.83–0.87 , 0.92–0.96 , 1.23–1.37 , 2.26–2.34 , 3.84 , 5.46 , 7.40–7.58 , 7.80–7.92 , 8.21–8.27 . Anal. Calcd for C21H25N3OS: C, 68.63; H, 6.86; N, 11.43. Found: C, 68.81; H, 6.99; N, 11.60.Orange oil, 65% yield; 4.1.28. H NMR : δ 2.08 , 4.07 , 4.15 , 4.41 , 4.66 , 5.38 , 7.43–7.62 , 7.88–7.90 , 7.98–7.99 , 8.31–8.33 . Anal. Calcd for C26H23FeN3OS: C, 64.87; H, 4.82; N, 8.73. Found: C, 64.59; H, 4.64; N, 8.91.Red oil, 63% yield; 14.1.29. H NMR : δ 0.82–0.93 , 1.08–1.12 , 1.30–1.37 , 1.51–1.55 , 2.24–2.32 , 2.36–2.44 , 3.82 , 5.71 , 7.73–75 , 7.85–7.86 . Anal. Calcd for C19H22N4O3S: C, 59.05; H, 5.74; N, 14.50. Found: C, 59.31; H, 5.99; N, 14.21.Yellow oil, 86% yield; 14.1.30. H NMR : δ 2.08 , 3.98 , 4.08 , 4.39 , 4.62 , 5.59 , 7.88–7.91 . Anal. Calcd for C24H20FeN4O3S: C, 57.61; H, 4.03; N, 11.20. Found: C, 57.34; H, 4.20; N, 11.05.Red powder, mp 235–237 °C, 91% yield; 14.2.in vitro tachyzoite (T. gondii RH-2 F (50839); ATCC, VA) and human foreskin fibroblast  growth for 120 h using a published colorimetric assay,10 dilutions (320–0.032 μM) of each compound were tested. Data from three separate experiments were analysed and the IC50, IC90, and TD50 calculated using Calcusyn software . The therapeutic index (TI), a measure of specific anti-T. gondii activity, was calculated with the formula shown under Compounds were tested for the ability to inhibit RH-2 F 5039; ATCC,4.3.The ferrocene-based derivatives (10 μM) were examined for activity directly on extracellular tachyzoites using an established immunofluorescence-based red/green invasion assay4.4.Toxoplasma gondii tachyzoites only replicate within the PV inside the host cell with one cycle of replication taking 6–8 h. Therefore, PVs containing 1, 2, 4, or 8 tachyzoites indicates that 0, 1, 2, or 3 cycles of replication have been completed. Consequently, a decrease in the number of intravacuolar tachyzoites relative to that of VHL indicates inhibition of replicationThe ferrocene-based derivatives (10 μM) were also tested for inhibitory activity against intracellular tachyzoites that had been allowed to invade host cells and establish an infection for 2 h before the addition of compound using an established immunofluorescence-based protocol5.N-substituted thiazolidin-4-one derivatives in high yield keeping constant three substituents at the N1-hydrazine portion of the scaffold  from the good results obtained in our previous worksin vitro against the tachyzoites of T. gondii. In the five-day growth inhibition assay, compounds were added only once, just before addition of tachyzoites, and thus were present for multiple cycles, up to 20, of parasite replication. Specifically, compounds were tested against, (i) the initial inoculum of tachyzoites as they attempt to invade host cells, (ii) intracellular tachyzoites attempting to replicate within the PV, and (iii) tachyzoites that have egressed from the initial infected cells and are moving out to infect neighbouring cells. Thus, compounds that were highly efficacious in this assay inhibited both host cell invasion and replication. Additionally, such compounds were stable at 37 °C and capable of being transported not only across the cell plasma membrane, but across the PV membrane. In this environment then, the best of the newly synthesised thiazolidinones, in terms of IC50 and TI, were all those deriving from acetylferrocene , showing better values than reference compound sulfadiazine  > 3-F (15) > 2-F (12), 3-Cl (24) ≥ 2-Cl (21) > 4-Cl (27), and 2-NO2 (3) > 3-NO2 (6) > 4-NO2 (9). Only two derivatives  in the 3-heptanone series displayed promising biological activity better than reference drug. In general, phthalimide-based derivatives (at the lactam NH) displayed minimal growth inhibitory activity.We synthesised 33 new adiazine . The onl3 and 27, significantly inhibited invasion. Additionally, compounds 9, 15, and 30 significantly inhibited attachment of tachyzoites to the HFF cells . In this assay, robust inhibition of replication results in PVs containing only one tachyzoite indicating that a treatment did not allow any replication to occur. Likewise, allowance of just one cycle of replication results in a majority of PVs containing just two tachyzoites. However, a predominance of PVs containing eight or more tachyzoites indicates absence of inhibitory activity over a 24 h period . As shown in 27, displayed fairly strong inhibition with the predominant number of PVs containing two tachyzoites and ≤1% containing eight or more. Treatment with derivatives 12 and 18 resulted in modest inhibition with a predominance of PVs containing only two tachyzoites but also 10–18% containing eight tachyzoites (Toxoplasma activity primarily against the tachyzoite itself and are unable to affect intracellular tachyzoites. This could be due to inefficient transport across cell and PV membranes. This aspect will be investigated when designing new chemical modifications within this scaffold.Lastly, the replication assay interrogates a compound’s ability to inhibit an established intracellular hyzoites . In ligh6.N-substituted 1,3-thiazolidin-4-one derivatives to assess their inhibitory activity against Toxoplasma tachyzoites. Approximately one-third of them stood out as promising antiparasitic agents possessing an activity similar or better than that of sulfadiazine against Toxoplasma and a comparable or lower cytotoxicity with respect to the reference drug. Furthermore, we have also documented that among the most active compounds, some derivatives strongly blocked the parasite attachment and invasion of the host cell. From the comparison of these data and the ones reported in our previous paperToxoplasma activity disregarding the type and nature of the substituent at the lactam NH. However, a strong improvement in this biological activity was observed by the introduction of substituted benzyl groups with respect to phthalimide or naphthalene ring at this position. These results demonstrated the promising potential of this thiazolidinone scaffold for the development of new anti-parasitic drugs.We have synthesised a large number of


Adventitious root (AR) formation in excised plant parts is a bottleneck for survival of isolated plant fragments. AR formation plays an important ecological role and is a critical process in cuttings for the clonal propagation of horticultural and forestry crops. Therefore, understanding the regulation of excision-induced AR formation is essential for sustainable and efficient utilization of plant genetic resources.Recent studies of plant transcriptomes, proteomes and metabolomes, and the use of mutants and transgenic lines have significantly expanded our knowledge concerning excision-induced AR formation. Here, we integrate new findings regarding AR formation in the cuttings of diverse plant species. These findings support a new system-oriented concept that the phytohormone-controlled reprogramming and differentiation of particular responsive cells in the cutting base interacts with a co-ordinated reallocation of plant resources within the whole cutting to initiate and drive excision-induced AR formation. Master control by auxin involves diverse transcription factors and mechanically sensitive microtubules, and is further linked to ethylene, jasmonates, cytokinins and strigolactones. Hormone functions seem to involve epigenetic factors and cross-talk with metabolic signals, reflecting the nutrient status of the cutting. By affecting distinct physiological units in the cutting, environmental factors such as light, nitrogen and iron modify the implementation of the genetically controlled root developmental programme.Despite advanced research in the last decade, important questions remain open for future investigations on excision-induced AR formation. These concern the distinct roles and interactions of certain molecular, hormonal and metabolic factors, as well as the functional equilibrium of the whole cutting in a complex environment. Starting from model plants, cell type- and phase-specific monitoring of controlling processes and modification of gene expression are promising methodologies that, however, need to be integrated into a coherent model of the whole system, before research findings can be translated to other crops. Adventitious root (AR) formation is a fundamental process of root biology by which new roots are formed post-embryonically from cells of non-root tissues. Reflecting the fascinating plasticity of plants, AR formation can be observed in excised plant parts such as shoots or leaves. Excision-induced AR formation is a bottleneck for plant survival, as the development of the new root system of isolated plant fragments restores competence for water and nutrient uptake. AR formation plays an important ecological role. It contributes to the persistence of plant individuals and dynamics of plant populations , and canper se and being linked to the hormonal pathways, we provide a new holistic, system-oriented view on AR formation in cuttings as determined by genetic, epigenetic and environmental factors at stock plant and cutting level. Finally we will discuss the challenges and outlook of future research.AR formation in cuttings is influenced by a large set of exogenous and endogenous factors. In this review, we outline the recent progress in understanding of molecular, hormonal and metabolic control of excision-induced AR formation. Moving forward from a previous conception on the role of plant hormones with a particular focus on auxin , concurrently leading to the accumulation of substances that are usually transported downwards, such as auxin, above the cutting site.In response to excision, a new developmental programme is initiated in particular responsive cells in the stem base near the wound, ultimately leading to the regeneration of a new root system. Depending on the plant and type of explant, diverse cell types, here referred to as AR source cells, may generate ARs . AR formCutting excision from the donor plant greatly modifies plant hormone homeostasis in the isolated shoot. It is widely accepted that auxin is an effective inducer of AR formation (Petunia hybrida) cuttings revealed early IAA accumulation in the stem base as dependent on PAT and essential for subsequent AR formation  by tissue-specific monitoring of molecular factors that control auxin homeostasis and by functional analysis of target genes in mutants. In the hypocotyls of de-rooted seedlings, early auxin maxima were identified via pGH3-2:GUS in pericycle cells as sites of subsequent AR primordium formation, whereas AR formation was reduced by mutations of PIN1, PIN3, PIN7 and ABCB19  genes encoding flavin-containing monoxygenases that convert indole-3-pyruvate to IAA are important controllers of auxin homeostasis in these explants. Using yuc mutants and monitoring local YUC expression, L.Q. YUC2 and YUC6 contribute to the basic auxin level in the leaf, whereas YUC1 and YUC4 are excision induced, first in mesophyll cells above the cutting site and thereafter in the procambium and vascular parenchyma, where AR formation starts (YUC4). Transgenic or chemical inhibition of YUC expression or function, respectively, inhibited AR formation. However, the finding that YUC1 and YUC4 are also induced in attached wounded leaves without rooting emphasizes the dependence of AR formation on the disconnection of the leaf from the vascular continuum of the whole plant and on the site of disconnection in relation to the auxin polarity of the leaf. YUC6 is further highly expressed during early stages of AR primordium formation in entire seedlings and TCLs, localizing in the AR tip (NAM–ATAF1/2–CUC2 (NAC) pathway  proteins recruit TOPLESS (TPL) to exert their repressive function on specific AUXIN RESPONSE FACTORS (ARFs), which are transcriptional regulators of auxin-responsive genes. IAA directly binds to the TRANSPORT INHIBITOR RESPONSE 1/AUXIN-SIGNALLING F-BOX (TIR1/AFB) component of the SKP/CULLIN/F-BOX (SCF)–TIR1/AFB complex and to Aux/IAA repressor proteins. This allows the ubiquitination and subsequent proteasomal degradation of Aux/IAA proteins so that the ARFs are released from repression. Aux/IAA proteins further provide cross-nodes to other plant hormones such as CKs, ET, JA and brassinosteroids , overexpression of the double-stranded RNA-binding protein MdDRB1 led to the downregulation of the auxin-associated miRNAs miR160, miR164 and miR393, which was correlated with increased transcript levels of their target genes MbARF10 and MbARF16, MbNAC1 and MbTIR1, respectively, and with enhanced AR formation in microcuttings  and PLETHORA (PLT) as downstream transcription factor (TF) genes (F) genes .2O2) that have promotive influences on AR formation  proteins in cuttings of several plant species, GRETCHEN HAGEN3 (GH3) genes was monitored in the stem base of cuttings of several plant species  clades that are induced by wounding in leaves, indicating overlap with the ET signalling pathway. GRAS TFs, which mediate auxin control of cell fate in a phase- and cell-type-dependent manner, are assumed to be important factors in the better rooting capacity of juvenile compared with mature cuttings of woody plants . In cuttings of Populus trichocarpa, the expression of the AP2/ERF gene PtAIL1 is enhanced during the differentiation of AR primordia, while the overexpression or downregulation of PtAIL1 increases or decreases the extent of AR formation, respectively  and SHORTROOT (SHR)] and the AINTEGUMENTA-LIKE (AIL) family, belonging to the APETALA 2/ETHYLENE RESPONSE FACTOR (AP2/ERF) domain, exert important control functions during primary root and lateral root (LR) development, linking auxin signalling with cell specification and patterning, in addition to being involved in the feedback regulation of local auxin homeostasis  family  family . AR formormation . ConstitCYCA, B and D-type genes has been reported during the induction phase in cuttings of Pinus contorta, Quercus suber, petunia, carnation and Vigna radiata  and cyclin-dependent kinases (CDKs) are important regulators of the cell cycle and respond to other hormones and to sugars . UpregulPinus contorta, carnation and Eucalyptus grandis, and functional analysis in arabidopsis indicated important roles of MT remodelling and cell wall modification during auxin-induced AR initiation -related transcripts encoding tubulins or MT-associated proteins play essential roles in the control of cell division and elongation, while their action involves modification of the cell wall . Transcrormation , the mecormation . Recent ormation . In a noormation . Thus, pormation . Excisioormation . Similarormation , this maormation . This maPIN1 in the stele cells of primary roots. In root meristematic cells, their transcripts co-localize with the MTs in the mitotic spindle and thereafter with the cell plate. Interestingly, the number of etiolation-induced ARs formed in intact seedlings was strongly enhanced in a triple myosin XI knockout mutant. Even though the data do not provide an explanation of how elimination of myosins contributed to enhanced AR formation  and WOX (in particular WOX11 and WOX5) and indicate an important role for auxin-mediated ERF genes, have been observed in the stem base of cuttings during excision-induced AR formation  or a blocker of ET perception promote or inhibit AR formation, respectively  conjugate that interacts with the COI1 (CORONATINE INSENSITIVE1) F-box protein of the SCFCoI1 complex as receptor (Nicotiana tabacum) or arabidopsis TCLs enhanced AR formation  mutant defective in JA signalling. Monitoring of auxin levels in the TCLs revealed that MeJA raised the IAA level when first AR cell clusters were formed, without affecting the expression of ARF6, ARF8 or ARF17. Application of 0.1 μm MeJA also promoted AR formation in intact seedlings but failed to induce such a response in TCLs which showed an excision-induced early accumulation of endogenous JA. In contrast, MeJA supplied at micromolar concentrations enhanced xylogenesis in both systems, corresponding to enhanced expression of ARF17. Furthermore, the response of AR formation in TCLs to the ET precursor ACC was depressed in mutants defective in JA biosynthesis or signalling, whereas the rooting response to MeJA was depressed in the ET signalling mutant ein3/eil1. Further considering that a combination treatment of TCLs with ACC and MeJA indicated antagonistic effects of ET and JA on AR formation, Continuous supply of JA to the rooting media of intact seedlings of arabidopsis or de-rooted petunia seedlings was found to have no effect at low concentrations but inhibits de-etiolation-induced and excision-induced AR formation, respectively, when applied at higher levels (ASA1 (ANTHTHRANILATE SYNTHASE a1) , carotenoid cleavage dioxygenase (CCD) 7 and CCD8 (encoded by MAX3 and MAX4) and a cytochrome P450 (encoded by MAX1) are involved in SL biosynthesis which mainly occurs in roots, while the F-box protein MAX2 is important for SL signalling  are a recently characterized group of plant hormones that are derived from the carotenoid biosynthetic pathway and regulate shoot and root development. In arabidopsis, a 9-gnalling . In arabeedlings . Thus, cMAX3 and MAX4 is light induced  controls the expression of the different TFs and enzymes discussed above that guide the establishment of the new sink in the rooting zone (further explanation below) and the determination, initiation and further differentiation of ARs, involving a mediation of the cell cycle and remodelling of microtubules and the cell wall as major processes. As apparent from Based on the literature discussed above, a model regarding the molecular regulation of excision-induced AR formation in the cutting base is illustrated in Pelargonium × hortorum), Chrysanthemum indicum, Euphorbia pulcherrima and petunia have shown that the number and length of ARs are positively correlated with the initial total N concentration in the cuttings; in petunia, in particular, this phenomenon is associated with enhanced differentiation of new meristematic cells into fully developed ARs . Although P deficiency can regulate the root system architecture in intact plants by increasing the number of ARs  may indicate functions independent on auxin  during the rooting period  and auxin efflux (PIN1 and PIN2) in cuttings during the induction phase, but further induces the expression of SUS1 and SUC5 putatively encoding a sucrose synthase and sucrose transporter, respectively, during the later stage of AR formation  pathway, trehalose-6-phosphate (T6P), sucrose-non-fermenting-1-related protein kinase-1 (SnRK1) and the target of the rapamycin (TOR) kinase pathway have been identified as important interlinked regulatory components mediating the effects of C nutrient status on plant growth and development .BT2 gene, that has a positive function in auxin response and also depressed the IAA-mediated up- and downregulation of several auxin-responsive genes  and TRYPTOPHAN SYNTHASE ALPHA CHAIN1 (TSA1). SUR2 encodes a cytochrome P450 enzyme involved in indole glucosinolate biosynthesis, whose inactivation in arabidopsis causes auxin overproduction and an abnormally high number of ARs in the hypocotyl  pathways to synthesize IAA  associated with the number of roots per rooted cutting, for example in two E. grandis  should be analysed for selected model plants. As a next step, the identified bottlenecks should be tested for relevance to a broader range of (1) cultivars of model species as well as (2) other plant species.Model plants with relevant agricultural, forestry or ecological backgrounds that are suitable for detailed analyses at molecular, physiological and genome levels should be analysed at the following levels.In vitro rooting systems are ideal for investigations of sugar–hormone cross-talk  technology are available for some plants propagated via cuttings, as recently reported for petunia  of multiparental populations of different cultivars, genes putatively controlling AR formation may be identified by a comparison of the target genetic intervals or SNPs with the genome sequence, and further functionally analysed. Due to the high complexity of regulatory networks, systems genetics has recently emerged as a sub-field of systems biology that uses expression QTL mapping or co-expression network mapping not only to identify candidate genes underlying the expressed phenotype but also to ascertain the mechanistic context of a gene or gene interaction module .t, other N fractions and carbohydrates in cuttings by near infrared spectroscopy (To face the genetic diversity, the obtained knowledge of a certain cultivar or species must be translated to other important crop genotypes. Considering the physiological bottlenecks of AR formation in the model systems, cultivars and other species should be tested and categorized into response groups at the physiological level. Ideally, a plant characteristic that determines the respective bottleneck should be used as a measurable marker for the rapid analysis of a large sample number. An example of such an approach to address the N and carbohydrate source limitation of AR formation is the recently developed non-invasive analysis of Ntroscopy .In this review, we considered new findings regarding the hormonal and molecular control of distinct cellular processes of AR formation, and brought them into context with new insights into the role of nutrient and metabolic homeostasis of the whole cutting. Further including a genetic perspective, involving epigenetic factors and facing the complex environment of cuttings, we provided a system-oriented concept on the control of AR formation.WIND and PLT genes appear to control cell de-differentiation. Specific auxin transporters, ARFs, which are under control of Aux/IAA proteins and miRNAs, as well as GRAS and WOX TFs are highlighted as important factors controlling the determination of root founder cells and the differentiation of ARs. Auxin- and mechanically mediated remodelling of MTs revealed as important process controlling the shift from cell division to cell differentiation, and is further suggested to control the excision-induced anticlinal orientation of cell division in root founder cells.Use of advanced molecular techniques has contributed to further elucidation of processes underlying the important role of auxin in AR formation, as further being linked to ET, JA, CKs and SLs, and interacting with the DNA and chromatin configuration. Wound-responsive At the whole-cutting level, AR formation is subjected to the nitrogen and carbohydrate source as controlled by the fertilization and light condition, which determine the surplus of carbohydrates and amino acids in the cutting. Source utilization for AR formation depends on auxin-controlled local activity of sucrolytic enzymes that determines the sink strength of the rooting zone. There, Fe may have a crucial role in ribosome biogenesis as a bottleneck for cell division and differentiation, while the specific functions of other nutrients as well as the signal function of sugars are far from being understood.SAUR genes, sugar and nutrient sensing and hormone–sugar cross-talk should also be exploited in other model plants, and there integrated into coherent models of the response and function of the whole systems. Translation to important horticultural and forestry crops is necessary to provide new knowledge-based breeding and propagation technologies that meet future ecological and economic demands.Even though substantial progress has been made in the understanding of AR formation, there are still important gaps in our knowledge. To date, most functional studies of genes are restricted to arabidopsis, which does not provide the typical cutting structure used for propagation of many crops. In future, underexplored factors and processes such as


Severe burn injuries result in relevant restrictions of physical capacity as well as psychological and social integrity and require a specialized rehabilitation. There is a common agreement, among national as well as international burn associations, that burn rehabilitation is a complex, dynamic process which needs an interdisciplinary and specialized treatment team. There is wide agreement that more research is needed in this field.primary research question addresses the “Pre-post comparison of the physical and psychological outcome measurements,” secondary question I looks at the “Examination of the non-inferiority of the new treatment concept with the established concept,” and secondary question II is the “Analysis of the rehabilitation process based on the rehabilitation cycle.”The aim of the study is to examine the effectiveness and efficiency of our new ICF -based rehabilitation for thermal injuries. Because of ethical reasons, we have chosen a prospective non-randomized design, which takes place at two different rehabilitation centers. At center A, a newly developed ICF-based rehabilitation program was established; at rehabilitation center B, a well-established rehabilitation program has existed for 20 years and is used as reference. The Only patients of the two burn rehabilitation centers who are insured by workers’ compensation will be asked to participate in this study to avoid outcome bias by insurance status. A physical examination  and a standardized questionnaire battery  measure physical and psychological conditions. Data will be taken on admission, during stay, and on discharge of the rehabilitation program and at follow-up 3 and 12 months after discharge. A minimum of 162 participants will be enrolled in this clinical longitudinal, prospective, observational study.The proof of the effectiveness of the ICF-based rehabilitation program for thermal injuries will give evidence in a comprehensive way for the first time in this field. As result, a standardized rehabilitation concept will be introduced, which can be provided to other rehabilitation institutions treating thermal injuries.DRKS00017702. Registered on 2 September 2019.German Clinical Trials Register,  Progress in the medical and surgical management of major burn injuries has significantly increased the likelihood of survival, even in those seriously injured. Since survival from large burns has become more common, mortality is no longer the only relevant outcome measure —functionThere is strong agreement that rehabilitation of patients after burn injuries requires a multidisciplinary team. An increasing number of publications are addressing the relevance of rehabilitation after burn injuries, but structured clinical studies are still rare. Existing studies mostly assess only one special aspect of the treatment program –10 or onNational and international burn associations provide health care professionals with guidelines for burn rehabilitation . BesidesRehabilitation is a comprehensive process involving a multidisciplinary team working in collaboration to optimize patients’ recovery. Main elements of the treatment after burn injuries are rehabilitative nursing for skin and wound care, physical, occupational, and sports therapy, and psychotherapy . AdditioIn rehabilitation center A (BG Trauma Center Ludwigshafen) a new ICF-based specialized burn rehabilitation program was elaborated in 2012 and established in 2014. As a control, the elements of the program and the patients’ outcomes will be compared to those of the well-established burn rehabilitation program of rehabilitation center B. Center B’s program concept was established in 1999 and also includes ICF-based elements. The purpose of the study is to establish standards and evaluate the effectiveness of the programs to meet the requirements of evidence, quality assurance, and cost-effectiveness in the treatment of such complex and costly injury patterns.Body function and structureActivity and participationContextual factors .We have chosen the outcome measures along the ICF concept, since it is a highly useful framework describing and organizing health conditions in a comprehensive way involving a biopsychological model. Furthermore, it provides a standard language and a conceptual basis for the definition and measurement of health and disability. Since the ICF was introduced by the World Health Organization (WHO) in 2001 , it has The aim of the present study is to evaluate the effectiveness of the rehabilitation programs for thermal injuries at two centers in Germany. Changes in health status are measured along the ICF constructs of body function and structure, activities, participation, and contextual factors  in order to address health issues as completely as possible. Patients’ conditions in the different domains will be measured before and after the rehabilitation and at two follow-up points, 3 and 12 months after rehabilitation, to quantify long-term changes and treatment effects. Further, the process of rehabilitation will be looked at very closely regarding goal setting and attainment. Patients‘ and therapists‘ satisfaction with the rehabilitation progress will be requested on a regular weekly basis. From the close observation of the rehabilitation process we expect to get a deeper understanding of the needs of our patients and a basis to improve the treatment concept if necessary.The study is approved by the ethics committee of Rheinland-Pfalz, Mainz, Germany. We ask potential participants for written consent prior to their inclusion in the study.The participants are admitted to the two burn rehabilitation centers in Germany dependent on proximity to their place of residence and availability of a contemporary treatment capacity. Preliminary analyses revealed an overall similarity between the both programs except for small differences: The rehabilitation program in center A contains more occupational therapy; at center B the program contains additional balneotherapy, which involves treatment of the skin by bathing in natural mineral water. Center A is located at the campus of a level 1 trauma center, whereas center B is located in a health resort. The duration of the rehabilitation is planned for 3 weeks in both facilities and can be extended individually.Deutsche Gesetzliche Unfallversicherung) are asked to participate in this study to avoid outcome bias by insurance status. This approach is described in other studies for work-related burn injuries [Only patients of the two burn rehabilitation centers who are insured by workers’ compensation  and by questionnaires and will be entered continuously into an Access database.No interventions besides the standard rehabilitation program in both centers are planned.The aim of the study is to evaluate the newly established rehabilitation concept in terms of pre-post comparison and through analyzing the rehabilitation process in matters of patients’ satisfaction with goal attainment.Do the patients benefit from the rehabilitation program regarding their physical and psychological health conditions? Furthermore, are the changes steady after rehabilitation?Physical and psychological outcome measures are enhanced after burn rehabilitation compared to measures before rehabilitation.Physical and psychological outcome measures are enhanced 3 and 12 months after rehabilitation compared to measures before rehabilitation.The alternative hypothesis (H1) is as follows:Physical and psychological measurements are not improved after the burn rehabilitation compared to measures before rehabilitation.Physical and psychological outcome measures are not enhanced 3 and 12 months after rehabilitation compared to measures before rehabilitation.The null hypothesis (H0) is as follows:Are there any differences regarding the effect of the rehabilitation treatment on the outcome measures between the two centers (non-inferiority of center A to center B)?What are the most common rehabilitation goals of the patients, and to which ICF categories are they primarily linked? How do goals change during the course of rehabilitation? And how satisfied are the patients’ with their goal attainment?This study uses a quasi-experimental prospective longitudinal design, including treating patients at two burn rehabilitation centers in Germany. For ethical reasons, randomization of patients or treatments is not possible; therefore, we added the non-inferiority question (comparison of the two centers). No intervention besides the standard rehabilitation program in both centers is planned. Participants will be screened at admission, at discharge, and at follow-up 3 and 12 months after discharge.The patient demographics measured include age, gender, race/ethnicity, family status, and employment status. Medical characteristics include diagnosis and therapies, total body surface area (TBSA), partial thickness and full thickness burns, Abbreviated Burn Severity Index (ABSI), inhalation trauma, pneumonia or sepsis, other diagnoses, and therapies.The types of outcome measures used to collect participant data are listed in Table General physical capacity is measured by the physical working capacity test 150 (PWC 150). The participant sits on a bicycle ergometer . Heart rate is measured with a heart rate monitor with chest strap  and will be recorded before, during, and after the test. The participant should reach a pedal-revolution rate of 70 rounds per minute (rpm). The exercise test begins with a workload of 25 watts (W), and the software automatically increases the workload by 25 W every 2 min. The target heart rate (beats/min) is calculated as 150 minus the age of the participant. When the individual target heart rate has been exceeded for more than 30 s, the final workload stage is reached and will be recorded. After this stage, a 5-min recovery period at 25 W will follow in which the heart rate recovery is recorded. The applied termination criteria are decreasing heart rate despite increasing exertion (for more than 30 s), chest pain or a feeling of constriction in the chest, shortness of breath, headache, dizziness, subjective exhaustion, leg fatigue, leg cramps, and a pedal-revolution rate below 60 rpm.Grip strength will be measured with a Jamar dynamometer  at level 2. The participant will sit in front of the rater, holding the elbows close to the body and flexed at 90 degrees with the wrists in a neutral position. The participant will be requested to press the dynamometer with maximum force. Three trials with each hand will be carried out .Major muscle function is tested according to Janda . MusclesBurn scars will be assessed at two representative sites using the Vancouver Scar Scale (VSS) and cutometry. Both sites are selected by the examiner as representative and are documented by an anatomical description of the location and by photo documentation to ensure retrieval of exactly the same spot in the follow-up measures.The VSS will be used to clinically evaluate the burn scar formation and characteristics. The VSS assesses four parameters of the scar, including vascularization, pigmentation, pliability, and height/thickness, giving a range of 0–14 in the total score. The appearance of the burn scar will be evaluated by a physician .Properties of the scar will be measured objectively with the Cutometer® Multi Probe Adapter (MPA) 580 . The Cutometer® MPA 580 is a device that measures the firmness and elasticity of skin. A negative pressure is created with a vacuum, the skin is drawn into the aperture of the probe, and after a defined time it is released. Inside the probe, the height of skin that is drawn up is determined by a non-contact optical measuring system. The resistance of the skin to the negative pressure (firmness) and its ability to return to its original position (elasticity) are displayed as curves (penetration depth in millimeters/time), and parameters (R0 and R2) are calculated .The extent of burn contracture of the large joints will be measured by range of motion (ROM) using a standard goniometer.Two questionnaires are used. The Disabilities of the Arm, Shoulder and Hand  questioThe Lower Extremity Functional Scale questionnaire for patients with foot and/or leg injuries (LEFS ) is a 20The BSHS-B measures the most important domains of a patient’s quality of life that are affected after burn injury. The BSHS-B consists of 40 items divided into 9 different subscales: affect, interpersonal relationships, sexuality, simple abilities, hand function, work, heat sensitivity, treatment regimens, and body image. Each item asks about the extent of a specific limitation and can be answered on a 5-point Likert scale that ranges from 0 = “extremely limited” to 5 = “not limited at all.” The higher the score, the lower the perceived impairment.The SF-36 questionnaire is one of the most commonly used assessments to measure an adult person’s perceived physical and mental health-related general quality of life. The questionnaire includes eight scales; four can be summarized into the General Mental Health scale, while the remaining four domains form the General Physical Health scale. All subdomains are assessed using a 5-point Likert scale . The scores are converted to a 0–100 scale. The higher the score, the higher the perceived quality of life.The original Symptom Checklist-90-Revised (SCL-90-R) is a widely used questionnaire developed to determine a number of psychological symptoms. Its shortened version has shown equally high internal consistencies as a suitable screening instrument to assess a wide range of psychopathologic symptoms. The questionnaire contains one-dimensional items which are scored on a 4-point Likert scale ranging from 1  to 4 (“extremely”).The IES-R is a 22-item, self-report questionnaire that assesses post-traumatic stress symptoms in relation to a specific event. It is one of the most commonly used metrics of post-traumatic stress disorder (PTSD) symptomatology. Items are rated on a 5-point scale ranging from 0  to 4 („extremely”).A person’s perceived social support will be measured with the short version of the Freiburg Social Support Questionnaire (F-SozU-14), a 14-item questionnaire comprising emotional and practical support as well as social integration and social burdens. The items are rated on a 5-point Likert scale, ranging from 1 (“does not apply”) to 5 (“exactly applicable”).At discharge and after 3 and 12 months, patients are asked to complete the German version of the CSQ-8. The CSQ-8 is a unidimensional, 8-item questionnaire assessing patient satisfaction with the rehabilitation. The items are rated on a 4-point Likert scale, ranging from 1 to 4. A higher score indicates higher satisfaction with the rehabilitation program.Participants are questioned at the beginning of the rehabilitation about the primary goals they want to reach during the course of rehabilitation. Once a week they as well as the therapists are asked to fill out a questionnaire about their satisfaction with goal achievement. Further, they can express if their goals for the following week have changed. These formulated goals will be linked to the ICF categories.At the end of the rehabilitation program, a semi-structured feedback interview will be held in which the patients will be asked to describe their experiences with the rehabilitation program by a psychologist who was not involved in the rehabilitation process.t tests for pre-post comparisons. Due to the small time intervals between the measurements, a small-to-medium effect size of 0.25 with an α-error probability of 0.05 is expected. An expected correlation of the measured values of at least 0.60 requires a power of 0.80. The power analysis revealed a sample size of 162 patients, N = 81 per center. Assuming a drop-out rate of 20%, as usually expected in a clinical trial, 92 patients per center would need to be enrolled.We calculated the required case number for paired unilateral After 2 years as a first milestone, a preliminary evaluation is planned. Termination of the study is considered in the event that severe side effects of the rehabilitation are shown. This includes both physical and psychological aspects. A significant failure in reaching the planned sample size is also defined as a termination criterion.No randomization is planned because of ethical reasons. The assignment of a patient to center A or B depends solely on the proximity of the patient’s hometown and the capacity of the center.Data will be collected continuously. For the statistical analysis, data will be checked for a normal distribution. Data are expressed by means with standard deviations and medians with interquartile range as appropriate. Categorical variables will be expressed as percentages.t tests. Longitudinal treatment effects will be tested by paired one-sided t tests between T1 and T3 and between T1 and T4.Pre-post comparison (T1–T2) of the outcome measures will be tested by paired one-sided The non-inferiority between the two centers will be proved with a power of 0.80 if differences are smaller than 0.4 standard deviation. Since randomized assignment to the centers is not possible, a potential selection bias between the samples will be matched by age, gender, TBSA, ABSI, and inhalation trauma. In case of an imbalance of the two samples, the analysis will be made along the procedure of propensity score matching.A descriptive analysis of the patients’ rehabilitation goals and their linkage to the ICF categories will be performed. Patients’ and therapists’ assessments of goal achievement will be compared. The mean frequency of changing goals during the course of rehabilitation will be obtained. Furthermore, patients’ satisfaction with rehabilitation will be assessed with a qualitative interview, which will be evaluated by content, and the results of the CSQ-8 will be expressed by means and standard deviations.The statistical evaluation will be carried out in cooperation with the statistician who participated in the design of the study (see Acknowledgements).A total of 4 years is planned for the realization of this study. Measurements are taken on admission, at the end of the rehabilitation program, and on follow-up 3 and 12 months after discharge. Enrollment in the study ends after 3 years.The primary focus of this study is to evaluate the rehabilitation program of two different burn rehabilitation centers. Since there is consensus in the burn literature that outcome is multidimensional for burn survivors, we included a broad spectrum of outcome parameters for the pre-post comparison. We chose the outcome measures along the ICF concepts of body function and structure , personal and environmental factors , and activities and participation  in order to get a holistic view about the impact of burn injuries and the treatment necessities.The instruments we chose are predominantly burn-specific  or frequently used in other burn injury studies  to enable better comparison with other studies. Instruments used for the evaluation of body function and structure are standard assessments such as the PWC, muscle function, and grip strength or commonly used instruments for scar assessment like the VSS und the Cutometer® MPA 580. The assessment will be conducted before and after the rehabilitation program and at two follow-up points (3 and 12 months after rehabilitation). The long follow-up period was chosen to prove the long-term effect of the rehabilitation program on the wellbeing of the patients. In the best case, patients will be enabled to fully participate again in their normal life in all aspects through the rehabilitation treatment. Since the complex multidisciplinary rehabilitation treatment is very strenuous for the patients as well as very cost intensive for the insurance, it is also essential to prove its effectiveness and quality to avoid unnecessary strain on the patients as well as unnecessary costs. After completion of the study, it is further planned to integrate the assessment instruments into clinical routine, if they prove to be relevant, and to provide these standardized documents to other interested rehabilitation facilities for burn injuries in Germany.The quasi-experimental prospective pre-post design was chosen due to ethical reasons, which do not allow a classical randomization. To balance this methodological limitation, we implemented the non-inferiority design between the two centers. The rehabilitation programs of the two centers were established independently from each other, at different points of time, but both are multidisciplinary ICF related and include the treatments recommended by national and international guidelines. Therefore, we do not hypothesize any difference in treatment effectiveness between the two centers.A core element of our study is the assessment of patients’ rehabilitation goals, their possible change over the course of the rehabilitation treatment, and the patients’ satisfaction with goal achievement. The detailed observation of the rehabilitation process is one of the strengths of our study. We expect the ICF goals to change during the rehabilitation process from activities of daily living to more complex activities as well as work-related and social items. Assessment of patients’ rehabilitation goals and their satisfaction with goal achievement will also be an important factor for evaluation of our rehabilitation program. Rehabilitation studies in other domains show that a patient-centered, ICF-related program will have the most positive effect on the patients . FurtherWe only include participants insured by worker’s compensation in order to avoid an outcome bias due to insurance status. This limits the possibility to generalize the results to patients of other rehabilitation centers or those with other types of insurance. However, we do not expect differences between our sample and patients of other burn rehabilitation centers in Germany.The effect of rehabilitation is analyzed by a multidisciplinary team consisting of psychologists, physiotherapists and occupational therapists, burn specialists, and rehabilitation physicians. Altogether the findings will provide a better understanding of the rehabilitation process and its effects after burn injury. The detailed view on the impairments and rehabilitation goals on the basis of the ICF concept will enable us to determine if all affected dimensions are addressed by the treatment and therefore if the rehabilitation program supports patients’ recovery at its best.The authors hereby declare that the final report will follow the CONSORT guideline. The SPRIT checklist is provided as Additional file The trial protocol is version 7.0, dated 08/18/2017.Recruitment started in November 2018 and is expected to be completed in November 2021.Additional file 1. SPIRIT 2013 checklist: recommended items to address in a clinical trial protocol and related documents.