Aeromonas hydrophila is an important zoonotic pathogen responsible for septicemia, diarrhea and gastroenteritis, and has attracted considerable attention. The EnvZ/OmpR two-component system (TCS) mediates environmental stress responses in gram-negative bacteria. We investigated the role of the TCS in A. hydrophila by comparing the characteristics of the parental (23-C-23), EnvZ/OmpR knockout (23-C-23:ΔEnvZ/OmpR), and complemented strains (23-C-23:CΔEnvZ/OmpR). Under non-stress conditions, the 23-C-23:ΔEnvZ/OmpR strain showed a significant decrease in growth rate compared to that of 23-C-23. Transcriptome and metabonomic analysis indicated that many metabolic pathways were remarkably affected in the ΔEnvZ/OmpR strain, including the TCA cycle and arginine biosynthesis. In addition, the virulence of the ΔEnvZ/OmpR strain was attenuated in a Kunming mouse model. The ΔEnvZ/OmpR strain exhibited notably reduced tolerance to environmental stresses, including high temperature, different pH conditions, oxidative stress, and high osmotic stress. The downregulated expression of genes related to cell metabolism, motility, and virulence in the ΔEnvZ/OmpR mutant strain was further validated by real-time quantitative PCR. Consequently, our data suggest that the EnvZ/OmpR TCS is required for growth, motility, virulence, and stress response in A. hydrophila, which has significant implications in the development of novel antibacterial and vaccine therapies targeting EnvZ/OmpR against A. hydrophila. Aeromonas hydrophila, an opportunistic aquatic pathogen that causes various diseases in both aquatic and terrestrial species, has attracted considerable attention owing to its high pathogenicity. It causes serious diseases in animals  is a defense mechanism that bacteria have evolved in response to various environmental stresses. A TCS consists of a sensor kinase and response regulator for sensing environmental stress, transducing signals, and mediating gene expression, which allow bacteria to exhibit high survivability and proliferation under different environmental stresses as a key to their pathogenicity . In receassembly , and theassembly . In Edwapression . Moreovepression , antibiopression , reactivpression , and mulpression .Escherichia coli, silencing of the EnvZ/OmpR TCS affects the expression of more than 100 genes, leading to changes in a variety of bacterial physiological properties, such as chemotaxis, adhesion, biofilm formation, stress tolerance, and even pathogenicity  and complemented mutant (23-C-23:CΔEnvZ/OmpR) were constructed in our previously published study  at 28°C. The OD600 of each culture was real time monitored every 1 h for 16 h to detect the growth.The overnight culture was adjusted with TSB liquid medium to an OD600  = 0.6 ± 0.05) at 28°C, and then the cells were harvested and washed twice by sterilized PBS. Total RNA was extracted using Qiagen RNeasy Mini kits , and quantified using a NanoDrop 2000 spectrophotometer . rRNA was depleted, and cDNA libraries were prepared as previously described (2 fold change > 1 (upregulation) or < −1 (downregulation), and a p-value < 0.05 were defined significantly differential expressed genes (DEGs). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment pathway analysis of DEGs was performed using the R package.In brief, the strains were cultured to log-phase ODescribed . The cDN600 = 0.6 ± 0.05) using a bacterial RNA kit , and reverse transcribed using the Prime-Script® RT reagent kit . cDNA was amplified using a SYBR Premix Ex Taq II kit  in a qTOWER Real-Time System . All experiments were carried in triplicates. All data were normalized to 16S rRNA  levels and analyzed using the 2−ΔΔCT method. The transcript-specific primers used for quantitative real-time PCR (qRT-PCR) are listed in Total RNA was extracted from bacteria in log-phase (OD600 = 0.6 ± 0.05) at 28°C, washed twice with precooled PBS buffer, and centrifuged at 10,000× g for 10 min at 4°C. After the supernatant was discarded, precooled methanol/acetonitrile/water  was added and sonicated in an ice bath for 1 h. The mixture was incubated at −20°C for 1 h, centrifuged at 14,000× g at 4°C for 20 min, and then collected samples. The samples collected were analyzed using a UPLC-ESI-Q-Orbitrap-MS system  coupled with Q Exactive Plus . Additionally, quality control samples were prepared and analyzed in the same way. The details of the method can be found in the t-test  on the normalized raw data at univariate analysis level. Metabolites with VIP values > 1.0 and p-value < 0.05 were considered to be significantly differential metabolites. KEGG enrichment analyses were carried out with the Fisher’s exact test, and FDR correction for multiple testing was performed. Enriched KEGG pathways were nominally statistically significant at the p < 0.05 level.The strains were cultured to log-phase (OD600  = 0.6 ± 0.05) at 28°C, and adjusted to an appropriate concentration. The mice were randomly divided into four groups of 10 individuals and injected intraperitoneally with 0.1 ml of each respective strain  at doses of 1 × 107 CFU. The other group injected 0.1 mL of sterile saline only. Mice were observed at 2 h intervals post-challenge, and clinical symptoms and mortality were recorded.Forty healthy Kunming mice (KM) weighing 20 ± 1 g (licensed: SCXK2019-0002), were bought from Hunan SJA Laboratory Animal Co. LTD . The strains were cultured to log-phase (OD600 = 0.6 ± 0.05) at 28°C, and adjusted to an OD600 of 0.1, and 200 μl of culture (1:100 dilution) was dispensed into 96-well plates and incubated at 28°C. A 200 μl aliquot of fresh TSB was added to the plates as a blank control. After 24 h incubation, the medium was discarded, and the plates were washed three times with sterile PBS. The biofilm was fixed with 200 μl of methanol for 15 min and incubated with 200 μl of 1% crystal violet for 15 min. After several washes with ddH2O and air-dried, the dried biofilm was solubilized in 200 μL 95% ethanol for 10 min. The absorbance was measured at 595 nm.The strains were cultured to log-phase (OD600 = 0.6 ± 0.05) at 28°C. One microliter of bacterial suspension was spotted onto a 0.3% TSA plate, and incubated at 28°C for 24 h. The motility diameters of bacteria were measured.The strains were cultured to log-phase (OD600 = 0.6 ± 0.05) at 28°C. A capillary tube was closed at one end and filled with mucus, and the other end was dipped into the bacterial suspension. After 1 h, the liquid in the capillary was removed and double-diluted for counting. The number of bacteria in the capillary tube was measured.The strains were cultured to log-phase (OD600 = 0.6 ± 0.05) at 28°C. The culture was adjusted with TSB liquid medium to an OD600 of 0.1, then the bacterial suspension incubation at 28 (as a control), 37, and 42°C for 24 h. Then, the cultures were double-diluted with sterile PBS and coated onto TSA plates for counting. The ratio of colony-forming units (CFUs) in treatment group to control group was calculated to assess the percent survival.The viability of strains was examined at 37 and 42°C to assess high-temperature tolerance of each strain. The strains were cultured to log-phase (OD600 = 0.6 ± 0.05) at 28°C. Bacterial suspension was collected, washed twice with sterile PBS, and treated in TSB at pH 5.0, pH 6.0, pH 7.0 (as a control), pH 8.0 or pH 9.0, at 28°C for 30 min. Next, viable cells were plated on TSA plates for counting after dilution. The ratio of CFUs in treatment group to that control group was calculated to assess the percent survival.The strains were cultured to log-phase (OD600 = 0.6 ± 0.05) at 28°C. Bacterial suspension was collected, washed twice with sterile PBS, and then suspended in PBS with 0.1 M H2O2, and without H2O2 as a control. After 20 min of incubation, viable cells were counted on TSA agar plates. The ratio of CFUs in treatment group to control group was calculated to assess the percent survival.The strains were cultured to log-phase (OD600 = 0.6 ± 0.05) at 28°C. The cells were collected, and resuspended in fresh TSB with 0.5 M NaCl, and adjusted to an OD600 of 0.1. 200 μl of each bacterial suspension was dispensed into 96-well plates, and then the plates were incubated in an automatic microplate reader at 28°C. The OD600 of each culture was real time monitored every 1 h for 16 h to detect the growth.The strains were cultured to log-phase  of GraphPad Prism 8 software were used to process and analyze routine data. p < 0.05 represents statistically significant.All the experiments were tested at least three times. All data were expressed as the mean ± SD. Student’s 23-C-23. The results from the growth curves showed that the deletion of EnvZ/OmpR in 23-C-23 caused a significant decrease in the growth rate, but complementation with EnvZ/OmpR restored this rate  were identified of which 607 were upregulated and 289 were downregulated  can be found at: The animal study was reviewed and approved by the Animal Ethics Committee of Hunan Agricultural University.ZS, GX, JuL, and XZ designed the study. GX performed the main experiments and wrote the manuscript. YY, JiL, JY, and NX helped to collect, analyze, and interpret the data. YY, JY, and NX helped to revise the manuscript. All authors contributed to the article and approved the submitted version.This research was supported by the Hunan Provincial Natural Science Foundation of China (2021JJ40234).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.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


In an isocratic condition, the mobile phase was delivered at a flow rate of 0.3 ml/minute. A positive electrospray ionization interface with multiple-reaction monitoring mode was used to provide simultaneous quantification of cortisol, cortisone, and internal standard at transitions of 363.11 to 121.00, 361.18 to 163.11, and 367.19 to 121.24, respectively. The method was validated for cortisol and cortisone determination over a concentration range of 0.5–50 ng/mL The detection limits for cortisol and cortisone in human sweat were 0.3 and 0.2 ng/ml, respectively. The interday coefficients of variation of cortisol and cortisone were ≤8.5% and ≤10.01%, whereas bias was in the range from −7.9% to 2.1% and from −4.3% to 3.0%, respectively. The assay was successfully applied to evaluate the cortisol-to-cortisone ratio in sweat samples collected from healthy adult volunteers.A simple and effective ultra-high-performance liquid chromatography assay linked to tandem mass spectrometry (UHPLC-MS/MS) for measuring cortisol and cortisone levels in human sweat has been developed and validated. A noninvasive world standard sweat collecting equipment was utilized to collect samples. The samples were analyzed using an Atlantis dC18 (2.1 × 100 mm, 3  Cortisol, a naturally occurring steroid, has an impact on a variety of body processes, including electrolyte balance, brain function, immune response, cardiovascular function, and metabolic activities , 2. The Cortisol levels have been measured in biological fluids using a variety of methods, including chemiluminescence immunoassays (CLIA) , radioimIn this paper, we present a straightforward, confirmed UHPLC-MS/MS method for simultaneously assessing cortisol and cortisone in sweat. A macroduct sweat collection device, a popular noninvasive technique, is used to collect sweat. As a benchmark, the cortisol-cortisone ratio was computed using samples from healthy adult volunteers.Cortisol (hydrocortisone) and cortisone were purchased from Acros Organics, NJ, USA. Cortisol-d4 was obtained from Sigma-Aldrich, MO, USA. Ammonium acetate, potassium phosphate (monobasic), sodium phosphate (dibasic), potassium chloride, sodium chloride, and acetonitrile (HPLC grade) were all provided by Fisher Scientific, NJ, USA. Milli-Q water was prepared by passing distilled water through the Milli-Q System . We prepared phosphate-buffered saline (PBS) by combining 0.01 M sodium phosphate, 0.0018 M potassium phosphate, 0.137 M sodium chloride, and 0.0027 M potassium chloride . The study was approved by the Research Ethics Committee of King Faisal Specialist Hospital and Research Center, Riyadh, Saudi Arabia, under RAC No. 2191297.μm) steel column, which was shielded by an in-line filter. The mobile phase, which was a 50 : 50 (v/v) mixture of acetonitrile and 2.0 mM ammonium acetate, was filtered through a supor membrane filter before being delivered (0.3 mL/minute) . The electrospray ionization source was used to operate the mass spectrometer instrument in a positive ion mode . While nitrogen (1000 L/hr) was utilized for nebulization and desolvation, argon was employed for collision (3.6 × 10−3 mbar). The optimum collision energy for cortisol, cortisone, and the IS was found to be 20 eV. The ion source and desolvation temperatures were kept at 150°C and 500°C, respectively. Multiple-reaction monitoring (MRM) was used to detect cortisol, cortisone, and IS in positive ion mode at mass-to-charge transitions (m/z) of 363.11 to 121.00, 361.18 to 163.111, and 367.19 to 121.24 for cortisol, cortisone, and IS, respectively.An atmospheric pressure ionization (API) interface, an Acquity UHPLC with integrated solvent and sample management, and a tandem mass spectrometer (MS/MS) Xevo-TQD were all used in the investigation . The analytes were estimated using the Atlantis dC18  were produced in methanol. Three quality control solutions  and nine calibration standards with concentrations ranging from 0.5 to 50 ng/mL were prepared using PBS. We prepared three quality control samples by spiking an appropriate amount of cortisol and cortisone into human sweat (blank) to verify the usage of the calibration curve created in PBS. Cortisol and cortisone levels recorded between blank and spiked perspiration were compared to the anticipated rise level from the amount spiked . An IS working solution (100 ng/mL) in methanol was used in sample preparation. All stock and working solutions were kept at a temperature of −20°C and 4°C, respectively.μL. The macroduct is securely fastened to the frontal skin area of the mid-arm that has been iontophoretically stimulated. Hydraulic pressure forces perspiration from the sweat glands out of the ducts and into the microbore tubing spiral that runs between the skin and the concave underside of the macroduct collector. The total amount of perspiration can be easily measured using a small amount of blue dye. The amount of sweat produced varies greatly from person to person. However, an average of 60 microliters of sweat was collected over 30–40 minutes. The collected samples were transferred into a 200 μL glass insert and kept at −20°C until they were examined.A macroduct sweat collecting system (Model 3700) from France was used in this study. Sweat samples were collected in a unique disposable plastic container with a shallow concave underside, holding between 50 and 80 μL of calibration standard, control, or volunteer sweat samples was placed into 200 μL glass inserts, followed by 20 μL of internal standard (100 ng/mL), and vortexed and centrifuged for five minutes. Then, we injected 10 μL of samples into the UHPLC-MS/MS system for analysis.Sweat samples were taken out of the freezer and placed on a bench for 30 minutes to warm up. Then, 50 μL/minute. The mass spectrometry apparatus was set up using the IntelliStart software from Waters Corporation . We employed liquid chromatography and mass spectrometry to analyze saliva samples in settings similar to those previously described [escribed . Accordiescribed .Peak areas of spiking sweat cortisol, cortisone, and IS at concentrations of 1.5, 25, and 45 ng/mL, respectively, and IS of 100 ng/mL were compared to equivalent peak areas of standards prepared in PBS by direct injection to assess matrix effect. However, no apparent matrix effect was observed. Cortisol and cortisone recovery were assessed by measuring cortisol and cortisone levels  in sweat before and after addition. For cortisol and cortisone, the mean measured recovery was 92–102% and 92–104%, respectively.μg/mL, and 10 μL was introduced into the system. The peaks of the analytes were found to be free of interference.The method's specificity was tested by evaluating six different blank human sweat samples and six structurally related steroids that may be found in blank biological fluids, including testosterone, prednisolone, methylprednisolone, progesterone, 17-hydroxyprogesterone, and prednisone. All solutions were prepared in methanol: water  at a concentration of 1.0 n = 6) equation of y = 0.0543 × −0.0067, r2 = 0.9938, and cortisone had a mean (n = 6) equation of y = 0.0861 × −0.0035, r2 = 0.9900. The detection limits for cortisol and cortisone in human sweat were 0.3 and 0.2 ng/ml, respectively, whereas the quantification limit was 0.5 ng/ml.Standard mixtures containing cortisol and cortisone in PBS at nine different concentrations (0.5–50 ng/ml) were evaluated to determine the assay's linearity. Regression analysis was used to examine the peak area ratios and the corresponding concentrations. Cortisol had a mean (n = 10) and interday (n = 20) coefficients of variation (CV) varied in the range of 7.2% to 9.0%, and its bias varied in the range of -8.1% to 2.1%. Cortisone's intraday (n = 10) and interday (n = 20) CV varied in the range from 7.1% to 10.1%, whereas bias varied in the range from −7.6% to 3.0%, respectively  were examined for both intraday and interday precision and accuracy (bias). Cortisol's intraday (ectively .In this article, a simple validated UHPLC-MS/MS assay for measuring cortisol and cortisone in human sweat has been described. The assay is based on an excellent noninvasive sweat collection standard device that has been successfully used to quantify both biochemical markers in human sweat samples.


Non-invasive online fluorescence monitoring in high-throughput microbioreactors is a well-established method to accelerate early-stage bioprocess development. Recently, single-wavelength fluorescence monitoring in microtiter plates was extended to measurements of highly resolved 2D fluorescence spectra, by introducing charge-coupled device (CCD) detectors. Although introductory experiments demonstrated a high potential of the new monitoring technology, an assessment of the capabilities and limits for practical applications is yet to be provided.H. polymorpha strain were conducted. This increased the complexity of the spectral dynamics, which were determined by 2D fluorescence measurements. The metabolic responses upon growth limiting conditions were assessed by monitoring of the oxygen transfer rate and extensive offline sampling. Using only the spectral data, subsequently, partial least-square (PLS) regression models for the key parameters of glycerol, cell dry weight, and pH value were generated. For model calibration, spectral data of only two cultivation conditions were combined with sparse offline sampling data. Applying the models to spectral data of six cultures not used for calibration, resulted in an average relative root-mean-square error (RMSE) of prediction between 6.8 and 6.0%. Thus, while demanding only sparse offline data, the models allowed the estimation of biomass accumulation and glycerol consumption, even in the presence of more or less pronounced secondary substrate limitation.In this study, three experimental sets introducing secondary substrate limitations of magnesium, potassium, and phosphate to cultivations of a GFP-expressing For the secondary substrate limitation experiments of this study, the generation of data-driven models allowed a considerable reduction in sampling efforts while also providing process information for unsampled cultures. Therefore, the practical experiments of this study strongly affirm the previously claimed advantages of 2D fluorescence spectroscopy in microtiter plates.The online version contains supplementary material available at 10.1186/s13036-023-00332-0. Fluorophores are molecules that can undergo absorption and emission of energy upon excitation of light at a compound-specific wavelength. The radiative emission of fluorescent light occurs, when an electron of a singlet excited state returns to the ground state. During this process, energy is partially dissipated by non-radiative vibrational relaxation. Consequently, fluorescence emission is observed at an increased wavelength compared to the excitation wavelength . CoenzymWith the increased amount of available spectral data, also workflows and machine learning methods had to be adapted to the needs of bioprocess engineering. Mowbray et al. classified the available algorithms into the groups of multivariate data analysis (MVDA), support vector machines, ensemble learning, artificial neural networks and Gaussian processes . Of thesEscherichia coli and Hansenula polymorpha [Lactococcus lactis and Kluyveromyces marxianus. Data-driven modeling was used to calculate the coculture composition [. Furthermore, the setup has been used for analysing autofluorescence and absorption of a pigment in Trichoderma reesei RUT- C30 and Streptomyces coelicolor A3 (2) mixed cultures [Online fluorescence monitoring in high-throughput microbioreactors allows cost-efficient, parallel screening experiments. This advantage renders the technology an invaluable tool during early-stage bioprocess development –26. Succlymorpha , 40–42. position . Furthercultures –46.H. polymorpha screening experiments of Kottmeier et al. [2+), potassium (K+), or phosphate (PO43−). 2D fluorescence spectroscopy is used to monitor the dynamics of GFP and biomass accumulation, while further metabolic insights are obtained by the measurement of the oxygen transfer rate (OTR) and by extensive offline sampling. Subsequently, the spectral data of cultures of two cultivation conditions in combination with a subset of the offline data is then used to generate PLS models, before internal and external validation is conducted using data not used for calibration. Based on the results and the comparison to the study by Berg et al. [This study aims to evaluate the capabilities of the new MTP-based monitoring system under more practical-oriented conditions. The methodology for 2D fluorescence-based PLS modeling, presented by Berg et al. , is applr et al. , three sg et al. , the cap2+) supplementation of the modified SYN6-MES medium was varied between 295.8 mg/L and 0 mg/L. In addition to the initial cell dry weight (CDWt0) of 0.03 g/L, for the cultures with 295.8 mg/L magnesium also 0.06 g/L and 0.11 g/L were cultivated. Following the experimental layout described in Additional file t0 of 0.06 g/L (blue upward triangle) and 1.18 mg/L magnesium and a CDWt0 of 0.03 g/L (red downward triangle), taken at a 1.5 h interval, are shown as hollow symbols in Fig. In the first cultivation experiment, the magnesium (Mgt0 of 0.03 g/L (light blue pentagons) showed exponential growth until 22.3 h, with a maximum OTR value of 34.5 mmol/L/h. Afterwards, the OTR dropped below 5 mmol/L/h. Both the scattered light and the GFP signals followed this exponential growth pattern. Shortly before the maximum OTR was reached, a sudden increase was observed for the GFP signal, which is connected to the partial derepression of the FMD promotor due to low glycerol concentrations [t0  described an earlier exponential increase, but were otherwise similar. With decreasing the magnesium supplementation, the maximum OTR was reduced, and the final signal drop was successively replaced by a slight linear decrease. Accordingly, the scattered light signal was observed to transition from an exponential increase to a linear increase upon reaching the OTR maximum. For the GFP signal, a sudden stagnation was observed for the cultures supplemented with a magnesium supplementation of up to 4.14 mg/L (yellow leftward triangles). No considerable metabolic activity was measured for the cultures without magnesium (pink squares) and the wells containing only non-inoculated medium (black hexagons).The OTR signals in Fig. trations , 50. AftThe offline data in Fig. Cal, sparse, accompanied by an increase of the RMSECal, full. According to Berg et al. [Similar to the study by Berg et al. , the PLSg et al. , at thisCal, full of 0.57 g/L was calculated, while for the prediction dataset, an RMSEPred, full of 0.94 g/L resulted. Relative to the measured glycerol range of 11.98 g/L, this accounts for 5.1% for the calibration dataset and 8.5% for the prediction dataset , and an RMSEPred, full of 0.3 g/L (6.5%) were determined . In summary, an RMSECal, full of 0.025 (4.9%) was obtained, while for the RMSEPred, full a value of 0.032 (6.0%) resulted.The PLS model of the pH value is shown in Fig. In conclusion, despite the changes in the scattered light and fluorescence dynamics, the resulting PLS models provide a reasonable overall accuracy. Although for individual cultivation conditions the predictive performance showed shortcomings of the models, with a relative RMSE below 10%, the acceptance criterium for a transferable PLS model described by Yousefi-Darani et al.  is met.+) supplementation to the modified SYN6-MES medium was varied. As for the previous experiment, the calculated RMSE included three very similar cultivation conditions, the variation of the CDWt0 was omitted. Thereby, also the number of cultures grown under limited conditions could be increased. In total, eight cultivation conditions with potassium concentrations between 2017.3 mg/L and 20.2 mg/L were investigated.In the second experiment, the potassium . Following the previously described criteria for the final PLS models of the CDW and the pH value, three LVs were used, while for the glycerol concentration, four LVs were chosen. The resulting trajectories, calculated by the PLS models, are shown in Fig. Similar to the previous experiment, the PLS model was generated based on the spectral online and the sparse offline sampling data of the cultures with the second highest  and the lowest  potassium supplementation. The prediction dataset consisted of duplicates of the remaining online monitored cultivation conditions, shown in Additional file Cal, full is 0.51 g/L (4.7%), while for the prediction dataset, the RMSEPred, full was calculated to 2.05 g/L (18.7%). Excluding the cultures with the highest potassium concentration resulted in a considerably reduced RMSEPred, full, − 100% of 0.57 g/L (5.2%).In Fig. Cal, full of 0.15 g/L (4.0%) was calculated, while the RMSEPred, full was determined to 0.55 g/L (14.6%). The RMSEPred, full, − 100% was reduced to 0.29 g/L (8.4%) as the described fluctuations were omitted.As for the glycerol concentration, also for the PLS model of the CDW, shown in Fig. Cal, full of the PLS model was calculated to 0.034 (4.3%), while the RMSEPred, full was calculated to 0.054 (6.9%). When excluding the cultures with the highest potassium concentration, the RMSEPred, full, − 100% was reduced to 0.032 (6.5%). While this represents only a limited reduction of the percentage value, compared to the RMSEPred, full, the absolute RMSEPred, full, − 100% is nearly reduced by half.The calculated values for the pH value of the calibration dataset in Fig. In conclusion, the potassium experiment showed lower PLS modeling performance than the magnesium variation experiment. This partially resulted from the chosen cultivation conditions and the reduced similarity between the calibration and prediction dataset.43−) was varied between 0 mg/L and 697.9 mg/L. The resulting online and offline values are shown in Additional file In the third experiment, the supplementation of phosphate . With a RMSEPred, full of 0.61 g/L (5.6%) and a RMSEPred, full, − 100%, of 0.59 g/L (5.4%), very comparable values were achieved for the transfer to the prediction dataset.Comparable to the previous experiment, the PLS model for glycerol in Fig. Cal, full was calculated to be 0.12 g/L (3.0%), while the observed deviations of the prediction dataset resulted in an RMSEPred, full of 0.26 g/L (6.6%). Excluding the cultures with the highest phosphate supplementation resulted in a reduced RMSEPred, full, − 100%, of 0.16 g/L (4.3%).Also, for the calculated CDW in Fig. Cal, full was calculated to be 0.038 (3.8%), whereas the described inaccuracies of the prediction dataset resulted in an RMSEPred, full of 0.085 (8.5%) and a considerably reduced RMSEPred, full, − 100% of 0.04 (5.4%).The PLS modeling results for the pH value, shown in Fig. In the phosphate limitation experiment, while the calibration dataset was described accurately, systematic inaccuracies were observed when transferring the PLS models to the prediction dataset. Therefore, overfitting of the calibration data in general and the spectral data in particular can be suggested. One way to investigate this hypothesis is to modify the selection of included spectral data. To exemplarily demonstrate the impact of the spectral input data, additional PLS models were generated using only the fluorescence of the 2D spectra, as shown in Additional file Pred, full and RMSEPred, full, − 100% of the PLS models for the glycerol concentration and the CDW. Only for the pH value, excluding the scattered light resulted in an additional reduction of the RMSEPred, full, − 100%. The improved PLS modeling performance for three LVs is visualized in Fig. The RMSEs for a variable number of LVs are shown in Additional file Cal, full of 0.04 (4.0%), an RMSEPred, full of 0.106 (10.6%) and an RMSEPred, full, − 100% of 0.034 (4.6%).For the cultures supplemented with 52.3 mg/L phosphate, a more constant trajectory was calculated, whereas for the culture with 244.3 mg/L phosphate, the previously observed second pH increase was no longer exhibited in the new model. For the prediction dataset in Fig. As described before, this noticeable systematic improvement of the prediction resulted from a change in the dominating spectral dynamics due to the exclusion of the scattered light. By applying PCA this change can be visualized, as shown in Fig. The scores of the first principal component PC1) for the dataset including the scattered light accounted for an explained variance of 99.64% and resembled the scattered light intensities shown in Additional file  for the Pred, full (plain columns) and RMSEPred, full, − 100%  is given. Additionally, also for the PLS models including only the fluorescence intensities (Fl), the RMSEPred, full, − 100%  and the respective as RMSEPred, full, − 100% (cross-hatched columns) are shown. An analogous visualisation of the absolute values is shown in Additional file In both, this and the previous study by Berg et al. , PLS regPred, full, with values between 3.5 and 5.3%. In contrast, for all limitation experiments of this study, values above 5% were obtained. The highest relative RMSEPred, full of up to 18.7% was calculated for the glycerol concentration of the potassium limitation experiment (K+). A reduction by more than 10% was obtained when excluding the cultures with the highest potassium supplementation (K+(− 100%)). For the phosphate variation experiment, this exclusion procedure resulted in an RMSEPred, full, − 100% between 5.4 and 4.3%. The additional in-silico exclusion of the scattered light (PO43−(Fl)) further reduced the RMSEPred, full, − 100% for the pH value from 5.4 to 4.6%. However, no considerable change in the RMSE was observed for the CDW, while for the glycerol concentration, the RMSEPred, full, − 100% even increased.The glycerol-variation experiment of the previous study resulted in low relative RMSEPred, full for the PLS models generated from the full 2D spectra ranged between 7.1 and 11.0%. A reduction to values between 6.0 and 6.4% was achieved for the exclusion of the cultures with the highest supplementation. Although these values still represented a considerable increase compared to the glycerol variation experiment of Berg et al. [In conclusion, depending on the offline parameter, the average relative RMSEg et al. , with reg et al. , 54–56. In addition to the comparison with other studies, the PLS model performance can also be compared to the respective conventional determination method of each offline parameter . For the glycerol concentration, the determined relative RMSE of more than 5% is considerably higher than the standard deviation of the implemented HPLC method, which was below 0.2% (data not shown). In contrast, for the CDW measurements, the determined relative RMSE is in good agreement with the reported standard deviations between 0.9 to 7% . Finally2+, K+, PO43−) limitation. For the previous study, both the biomass and the product formation ceased as soon as the glycerol concentration was depleted. This resulted in a constant relation between the two parameters and, thus, in the established PLS model to remain valid. In contrast, under secondary substrate limitation, the carbon source remained available, enabling further metabolic activity with a yet changed metabolism. With the occurring changes in the spectral dynamics and the relation between biomass and product formation, the PLS models reached the performance limits of the regression algorithm. Interestingly, for the experiments of this study, no systematic improved performance for either the limited or unlimited cultivation conditions was observed. For example, for the magnesium limitation experiment, the glycerol concentration  , 47. HowCal,full and a decreasing RMSECal,sparse. In the present study, this trend was only observed for a few models, such as the CDW concentration of the magnesium  strain was used for all experiments. For storage at − 80 °C, cryo cultures were prepared in a modified SYN6-MES medium and supplemented with 150 g/L glycerol.The green fluorescent protein (GFP) expressing 2PO4, 7.66 g/L (NH4)2SO4, 27.3 g/L (140 mM) 2-morpholinoethanesulfonic acid (MES), 3.0 g/L MgSO4·7H2O, 3.3 g/L KCl and 0.3 g/L NaCl. The pH was adjusted to 6.0 using 1 M NaOH. After sterilisation at 121 °C for 20 minutes, a sterile-filtered trace element solution was supplemented to provide final concentrations of 0.65 mg/L NiSO4·6H2O, 0.65 mg/L CoCl2·6H2O, 0.65 mg/L H2BO4, 0.65 mg/L KI and 0.65 mg/L Na2MoO4·2H2O. A sterile microelement solution was added to provide 66.5 mg/L EDTA (Titriplex III), 66.5 mg/L (NH4)2Fe(SO4)2·6H2O, 5.5 mg/L CuSO4·5H2O, 20 mg/L ZnSO4·7H2O and 26.5 mg/L MnSO4·H2O. Additionally, a sterile-filtered stock solution was prepared to supplement 1.0 g/L CaCl2·2H2O. A sterile vitamin solution was added to supply 0.4 mg/L D-biotin and 133.4 mg/L thiamine hydrochloride. For preparing the vitamin stock solution, the D-biotin was first dissolved in a 10 mL mixture (1:1) of 2-propanol and deionised water. The thiamine hydrochloride was dissolved in 90 ml of deionised water and mixed with the D-biotin solution. Next, glycerol was added to the media from a sterile 500 g/L stock solution to achieve the final glycerol concentrations. Finally, sterile water was added to account for differences in volumes.Analogue to a previous study , a modif2+), potassium (K+) and phosphate (PO43−) were prepared according to Kottmeier et al. [Media with reduced secondary substrate concentrations of magnesium , 1.4% (4.14 mg/L), 0.8% (2.37 mg/L), 0.4% (1.18 mg/L) and 0% (0.0 mg/L) of the standard magnesium concentration of the modified SYN6-MES medium .For preparing the medium without magnesium, the supplemented MgSO2PO4 and KCl were replaced by 0.845 g/L (NH4)H2PO4 to avoid phosphate limitation. 2.92 g/L NaCl was added to avoid changes in osmolality. The final potassium concentrations held for 5% (100.9 mg/L), 4% (80.7 mg/L), 3% (60.5 m/L), 2.5% (50.4 mg/L), 1.75% (35.3 mg/L), 1.25% (25.2 mg/L), 1% (20.2 mg/L) and 0% (0.0 mg/L) of the standard potassium concentration of the SYN6-MES medium .For the medium without potassium, KH2PO4 was replaced by 0.547 g/L KCl to avoid a potassium limitation. The final phosphate concentrations held for 35% (244.3 mg/L), 20% (139.6 mg/L), 15% (104.7 mg/L), 12.5% (87.2 mg/L), 10% (69.8 mg/L), 7.5% (52.3 mg/L) and 0% (0.0 mg/L) of the fully supplemented modified SYN6-MES medium .For the medium without phosphate, KHL) of 10 mL modified SYN6-MES medium supplemented with 10 g/L glycerol. The shaking frequency (n) was chosen to be 350 rpm at a shaking diameter (d0) of 50 mm. The temperature (T) was set to 30 °C. The medium was inoculated from the cryo cultures at an initial optical density measured at a wavelength of 600 nm (OD600) of 0.1. The precultures were harvested after the OTR indicated no further growth . Identical inoculation conditions were ensured by preparing one inoculated stock solution per initial cultivation condition, as indicated by different colours in Additional file 0) of 3 mm and a filling volume (VL) of 0.8 mL. The cultivation temperature was set to 30 °C.The method for the cultivation of the main cultures was identical to Berg et al. . The culex) were scanned from 280 to 700 nm with an increment of 10 nm. For each excitation wavelength, an emission spectrum, ranging from 275 to 725 nm at a resolution of 0.44 nm, was recorded, using an integration time of 30 ms. After completing the recording of a 2D spectrum for all monitored wells, an intermediate 10 min measurement break was included, to reduce the mechanical wearing of the device. During the measurement breaks, cultivation conditions were maintained. Although not all wells of the 48-well MTPs were exploited in this study, still, 2D-spectra were recorded. As a result, 2D spectra were measured every 30 min for each well of the 48-well MTP.Multi-wavelength 2D fluorescence online monitoring was conducted in the MTP cultivation platform described by Ladner et al.  (Additio2) of the gas phase in the headspace of every individual well was measured by oxygen-sensitive fluorescence spots, using the Stern-Volmer equation for quenching. Subsequently, the OTR was calculated according to Flitsch et al. [For determining the OTRs of the individual cultivation conditions, the Respiration Activity MOnitoring System  was used , 128 (K+) and 122 (PO43−) samples were taken from the three experiments, respectively. At each sampling time, the culture broth was manually withdrawn from one well per sampled condition using a micro pipette. Due to the small shaking diameter, the orbital shaking was maintained during the sampling. Thereby, oxygen limitation was avoided [600 of the samples was determined using a photometer  and micro cuvettes . Measurements between 0.1 and 0.3 a.u. were ensured by sample dilution with a 0.9% (w/v) NaCl solution. The cell dry weight (CDW) was calculated using a linear correlation with the OD600  used for sampling  between − 10 nm and + 270 nm relative to the excitation wavelength. A moving average filter with a window size of 25 pixels  was applied for noise reduction. The spectral data was further reduced to a resolution of 2 nm to reduce the processing time. No significant deteriorating effect on the modeling results was observed by this procedure (data not shown). For excluding the scattered light in silico, the intensities between − 10 nm and + 13 nm relative to the excitation wavelength were discarded. Finally, for each well, the spectral data of each measurement cycle was referenced to the respective first 2D spectrum by subtraction per wavelength combination (I-I0).The spectral data processing and MVDA were identical to the method described by Berg et al. , using Mmdatools . The rawThe temporal alignment of the online spectral data  were used for online  and offline  monitoring of the cultures of eight different initial cultivation conditions (I–VIII). Grey hatched wells show wells filled with non-inoculated, fully supplemented medium for control. Struck-through wells were not used in the experiment. (A) For the limitation studies of magnesium and phosphate, a μRAMOS cultivation system as described by Flitsch et al. [B) Online 2D fluorescence data was generated using the online monitoring cultivation system published by Ladner et al. [C) Offline samples were taken in singlets from three additional microtiter plates (MTPs). The total number of offline samples varied depending on the experiment and cultivation condition. Adapted from Berg et al. [Fig. S2. Exemplary 2D spectra recorded at different cultivation times for H. polymorpha RB11 pC9-FMD (PFMD-GFP) cultivated at two different initial cultivation conditions and non-inoculated medium. Spectra recorded for cultures cultivated with a CDWt0 of 0.03 g/L and initial magnesium (Mg2+) concentrations of 295.8 mg/L and 2.37 mg/L are shown in A-D (light blue rectangle) and E-H (orange rectangle), respectively. I-L (black rectangle) shows spectra for non-inoculated medium. Spectra are shown for cultivation times of  0 h,  12 h,  24 h, and  30 h. Spectroscopic measurement settings: excitation wavelength range = 280 nm – 700 nm (step size = 10 nm), emission wavelength range = 278 nm – 720 nm (step size = 0.45 nm), integration time = 30 ms. Cultivation conditions: 48-well microtiter plate with round well geometry, modified SYN6-MES medium, liquid volume = 800 μL, shaking diameter = 3 mm, shaking frequency = 1000 rpm, temperature = 30 °C. Fig. S3. Time-resolved oxygen transfer rate (OTR) signals of individual H. polymorpha RB11 pC9-FMD (PFMD-GFP) cultivations at different initial cell dry weight (CDWt0) and magnesium (Mg2+) concentrations. Solid, dashed, and dotted lines describe the OTR of individual cultures used for calculating the average and standard deviation shown in Fig. Fig. S4. Impact of the number of latent variables on the root-mean-square error (RMSE) for the 2D spectra-based PLS models of (A) glycerol, (B) cell dry weight (CDW) and (C) pH of the magnesium variation experiment. The PLS models are based on the data in Fig. Cal, sparse (black circles) was calculated. The RMSECal, full (red upward triangles) was calculated from the 1.5 h sampling interval  was calculated for the prediction dataset, and the 1.5 h sampling interval was based on the offline values  online monitoring signals and (C-E) offline sample measurements of H. polymorpha RB11 pC9-FMD (PFMD-GFP) cultivations at different potassium (K+) concentrations. (A) Scattered light intensities (λex = λem = 600 nm) and (C) GFP fluorescence intensities  were extracted from 2D spectra of duplicates, shown as solid and dotted lines. Hollow symbols indicate every 10th data point. Values of (C) glycerol, (D) cell dry weight (CDW), and (E) pH value for cultures with an initial potassium concentration of 100.9 mg/L (blue upward triangles) and 20.2 mg/L (pink squares), respectively, are based on singular offline measurements. Hollow symbols show offline measurements for the short sampling interval. Filled, linearly interpolated symbols describe a sparse, more realistic sampling interval of at least 5 h. The vertical dashed line after 43 h describes the last measurement included for PLS modeling. Cultivation conditions: 48-well microtiter plate with round geometry, modified SYN6-MES medium, liquid volume = 800 μL, shaking diameter = 3 mm, shaking frequency = 1000 rpm, temperature = 30 °C. Fig. S6. Impact of the number of latent variables on the root-mean-square error (RMSE) for the 2D spectra-based PLS models of (A) glycerol, (B) cell dry weight (CDW) and (C) pH of the potassium variation experiment. The PLS models are based on the data in Fig. Cal, sparse (black circles) was calculated. The RMSECal, full (red upward triangles) was calculated based on the linear interpolation of all available offline samples . The RMSEPred, full (green downward triangles) was calculated for the prediction dataset and the respective offline values , the cultures with 2017.3 mg/L potassium  were excluded from the calculation. Fig. S7. Time-resolved (A-C) online monitoring signals and (D-F) offline sample measurements of H. polymorpha RB11 pC9-FMD (PFMD-GFP) cultivations at different phosphate (PO43−) concentrations. (A) The mean oxygen transfer rate (OTR) of culture replicates  Scattered light intensities (λex = λem = 600 nm) and (C) GFP fluorescence intensities  were extracted from 2D spectra of duplicates, shown as solid and dotted lines. Hollow symbols indicate every fifth data point. Values of (D) glycerol, (E) cell dry weight (CDW), and (F) pH value for cultures with an initial phosphate concentration of 244.3 mg/L (blue upward triangles) and 52.3 mg/L (red downward triangles), respectively, are based on singular offline measurements. Hollow symbols show offline measurements for the short sampling. Filled, linearly interpolated symbols describe a sparse, sampling interval of at least 5 h. The vertical dashed line after 34.5 h describes the last measurement included for PLS modeling. Cultivation conditions: 48-well microtiter plate with round geometry, modified SYN6-MES medium, liquid volume = 800 μL, shaking diameter = 3 mm, shaking frequency = 1000 rpm, temperature = 30 °C. Fig. S8. Time-resolved oxygen transfer rate (OTR) signals of individual H. polymorpha RB11 pC9-FMD (PFMD-GFP) cultivations at different phosphate (PO43−) concentrations. Solid, dashed, and dotted lines describe the OTR of individual cultures used for calculating the average and standard deviation, shown in Fig. S7A. The number of replicates (n) is shown in the legend. Cultivation conditions: 48-well microtiter plate with round geometry, modified SYN6-MES medium, liquid volume = 800 μL, shaking diameter = 3 mm, shaking frequency = 1000 rpm, temperature = 30 °C. Fig. S9. Impact of the number of latent variables on the root-mean-square error (RMSE) for the 2D spectra-based PLS models of (A) glycerol, (B) cell dry weight (CDW) and (C) pH of the phosphate variation experiment. Resulting errors are shown for PLS models using the spectral dataset (A-C) including the scattered light and fluorescence, and (D-F) including only the fluorescence. All PLS models were calibrated using offline values from the linearly interpolated, sparse sampling interval , from which the RMSECal, sparse (black circles) was calculated. The RMSECal, full (red upward triangles) was calculated based on the linear interpolation of all available offline samples . The RMSEPred, full (green downward triangles) was calculated for the prediction dataset and the respective offline values , the cultures with 697.9 mg/L phosphate  cultures after 24 h of cultivation cultivated at initial phosphate (PO43−) concentrations of  697.9 mg/L and  52.3 mg/L. Spectra  including scattered light and fluorescence, as well as  spectra including fluorescence only are shown. The scattered light exclusion was conducted in silico, as described in the material and methods section. Spectroscopic measurement settings: excitation wavelength range = 280 nm – 700 nm (step size = 10 nm), emission wavelength range = 278 nm – 720 nm (step size = 0.45 nm), integration time = 30 ms. Cultivation conditions: 48-well microtiter plate with round geometry, modified SYN6-MES medium, liquid volume = 800 μL, shaking diameter = 3 mm, shaking frequency = 1000 rpm, temperature = 30 °C. Fig. S11. Comparison of absolute RMSEPred, full for glycerol, CDW and pH value for the PLS models generated in Berg et al. [2: Table S1. Fig. S12. Exemplary Oxygen transfer rate (OTR) measured for the preculture of Hansenula polymorpha RB11 pC9-FMD (PFMD-GFP). Cultivation conditions: modified SYN6-MES medium, 10 g/L glycerol, initial optical density = 0.1, 250 mL shake flask, filling volume = 10 mL, shaking frequency = 350 rpm, shaking diameter = 50 mm, T = 30 °C. Fig. S13. Linear correlation between cell dry weight (CDW) and optical density at 600 nm (OD600). Cultures were grown in a modified SYN6-MES medium according to the preculture protocol. The shake flask cultures were harvested during exponential growth before the dilution series were prepared with fresh medium. For the OD600 measurement of the diluted series, additional dilution was conducted to allow measurements between 0.1 and 0.3. Adapted from Berg et al. [h et al.  was usedr et al. . (C) Offg et al. . Fig. S2g et al.  and thisg et al. . Backwarg et al. .Additional file 2: Table S1. Absolute and relative RMSE of calibration and prediction for PLS models of glycerol, CDW, and pH-value. Results are shown for the experiments of this study and the previous study for glycerol variation [Cal,full, RMSEPred,full). The relative RMSE, shown in brackets, is calculated based on the offline parameter range for the respective experiment.ariation . The RMS


The main purpose of this study was to investigate the relationships between minutes played (MP) with maturity status, fitness, and hormonal levels, and to quantify their influence on minutes played.Twenty-four elite youth soccer players under-16 years participated in this study, over a full-season period. Anthropometric measures, maturity status, hormonal and physical fitness levels were collected. Participants were monitored during the season. After the end-season, players were assessed in 6 different tests over a four-day period.2max) was strongly correlated with MP (r = 0.75), maturity offset (r = 0.52), and countermovement jump (r = 0.53). Multiple linear regression explained 76% of MP  = 6.05, p = 0.001), with an R2 of 0.76. Moreover, Growth hormone (GH) and V̇O2max. were the most influential factors in MP  = 17.92, p ≤ 0.001), with an R2 of 0.63.The maximum oxygen consumption (V̇O2max have a preponderant role in MP by elite youth soccer players, it appears to be more pragmatic to consider other contextual dimensions, as they can impact selection for competition and minutes of participation in a match.High levels of GH and V̇O Most soccer academies worldwide, team categorization and stratification are based on date of birth  , where tIn using such methods, coaches are better able to perform talent identification, selection and development , 12. IndAt the onset of puberty, it is expected that the hormonal system begins to operate without major sex differences in the rate of growth and maturation or in the expression of physical qualities . HoweverTalent identification and selection in soccer is generally based on traditional methods, where it is mistakenly believed that early maturing players are the ideal short- and long-term prospects. The inconvenient truth is that early maturing players are preferred over late maturing players, mainly due to their taller and stronger characteristics, thus excluding their smaller colleagues , 12, 27.Another pertinent issue regarding the differences related to opportunities given to early and later maturers is the time of play and selection for competition. There exists an observable trend towards selection of the stronger and taller players (early maturers) as players are closer, or at, PHV , in an aTime of play and selection for competition may be influenced by the level of maturation, the activity of circulating GH, as well as the level of fitness of young players that are at the critical stages of adolescence. Whilst the influence of maturation levels on time of play has begun to be investigated , the evi2max), fatigue index in Therefore, the aims of this study were twofold: (i) to analyze the relationship between minutes played (MP) in soccer and the skeletal age, maturity offset, maximal oxygen uptake  who played in the Iranian U16 Premier League participated in this study. Considering the field position, the sample was composed by 2 goalkeepers, 9 defenders, 5 central midfielders, 4 wingers, and 4 attackers. The inclusion criteria were: (1) at least 4 years of experience playing soccer; (2) active and regular participation in all stages of the study; (3) they did not use any supplement that could affect growth and maturation; and, (4) participants were not permitted to perform additional exercise/training regimens. The exclusion criteria were: (1) not participating in 80% of competitions  and exercises of the whole season; (2) did not attend one of the medical or physical tests of the study. This study was approved by the Ethics Committee of University of Isfahan, as well as operating in accordance with Declaration of Helsinki. Before participating in the study, players and their parents/guardians were notified about risks and benefits of this study, and signed informed consent and assent, respectively.Twenty-four elite youth soccer players (Mean ± Standard deviation (SD); age: 15.61 ± 0.27 years; height: 176.50 ± 5.23 cm; body mass: 60.97 ± 8.29 kg; skeletal age: 16.65 ± 0.84 years; maturity offset: 1.97 ± 0.43 years; V̇OBased on a previous study that highlighted large to very large correlations between physiological variables in young soccer players , 33, we 2max, fatigue index in repeated sprint test, CMJ performance, GH, and IGF1 levels, respectively; and (ii) to investigate to what extent the aforementioned variables can explain the variance in playing time. Players took part in a formal or non-formal game every week throughout the season. Participants were monitored during the season, and tests were performed upon completion of the competitive season. The timeline of the study can be found in the Table This research was conducted as a quasi-experimental and cohort study which was performed on a cross-sectional basis, yielding practical results. This study had two purposes: (i) to elucidate the relationship between playing time in soccer and the skeletal age, maturity offset, V̇OThe players were assessed over four days, which commenced following three days of rest from the last training session. On the first day, players underwent anthropometric measurements, blood tests, and EOS imaging. On the second day, the CMJ test was used to assess the lower-limb power. On the third day, anaerobic power was tested using seven repeated sprint tests (7RST), and on the fourth day, the Yo-Yo Intermittent Recovery Test level 1 was performed to estimate the aerobic capacity of the participants. All tests were performed in the same weather conditions (21–23 °C temperature and 50% humidity)  in the mTo measure the standing height, participants were unshod, with the heels, hips, shoulder blades, and back of the head as close as possible to the stadiometer, with feet placed beside each other. For sitting height, participants sat on a 50 cm bench and were instructed to bring their buttocks as close as possible to the stadiometer, holding their upper body straight and placing their hands on their feet, at which point, their height assessed. The distance between the highest point of the head and the bench was calculated as sitting height. For this measurement, SECA Model 213, Germany, was used with an accuracy of 5 mm. For measuring maturity offset and age at PHV, we used the following formula: Maturity offset =  − 9.236 + 0.0002708 (leg length × sitting height)—0.001663 (age × leg length) + 0.007216 (age × sitting height) + 0.02292 (Weight by Height ratio), R = 0.94, R2 = 0.891, and SEE = 0.592) and for leg length = Standing Height (cm)—Sitting height (cm) . ParticiTo assess the skeletal age, posterior-anterior radiographs of the left hand-wrist were taken using the EOS imaging system to obtain a 2D X-ray. The EOS imaging system delivers a radiation dose which is 50 to 85 percent lower , 36, 38 In order to determine the levels of GH and IGF1, after at least 12 h of fasting and 72 h after the last training session, 10 ml of blood was drawn from the antecubital fossa of each participant, at 8 am, in the Al-Zahra Hospital laboratory, where the samples were immediately centrifuged in the laboratory , 43. SubTo assess explosive lower-body power , we usedThe Bangsbo repeated sprint test, also known as the 7RST test, was used for measuring anaerobic power. According to the test protocol, each participant must perform 7 curved speeds, with a 25-s active recovery time between each sprint. Participants warmed up for 15 min, including jogging, dynamic stretch, ABC training, and sub maximal speed, under the supervision of a fitness instructor. For the test, the participant starts running at their maximum speed on the signal of the examiner, to the end of the demarcated path, followed by 25 s of active recovery. After 25 s, the participant runs again at maximum speed, and this procedure is continued until the 7th run. The difference between the slowest record and the fastest record was calculated as fatigue index . In inst2max was calculated based on the following formula: V̇O2max (ml.kg−1.min−1) = IR1 distance (m) × 0.0084 + 36.4 [The Yo-Yo Intermittent Recovery Test level 1 (IR1) was used to test the aerobic capacity of players. In this test, each athlete ran a 20 m’ distance back and forth between points, after standardized warm-up (as reported above), according to standardized protocol . Briefly4 + 36.4 . The ICCStatistical analyses were performed using GraphPad Prism 8.0.1. The significance level was set at P < 0.05, a priori, and data were presented as mean and SD. Shapiro–Wilk was applied to check the normality the data. Pearson correlation analysis was performed between the maturity statues, physical fitness tests, and IGF1 with MP. While Spearman correlations were used for GH and soccer training. The following thresholds were used to define the strength of the correlation coefficients : < 0.1 =Descriptive characteristics of players are presented in Table p = 0.02), CMJ , GH , IGF1 Level , and V̇O2max . In addition, there were significant correlations between V̇O2max and maturity offset , CMJ , and skeletal age  , with an R2 = 0.21; V̇O2max  = 27.95, b = 56.00, p ≤ 0.0001), with an R2 = 0.56; CMJ  = 6.31, b = 28.99; p = 0.02) with an R2 = 0.22; GH  = 2.90, b = 40.10; p = 0.015) with an R2 = 0.1165, and IGF1 levels  = 6.11, b = 1.15; p = 0.02, R2 = 0.22, respectively. MP was increased by 56.00 min for each ml.kg−1.min−1 of VO2max; 28.99 min for each cm of CMJ; 40.10 min for each ng/dl of GH, and increased 1.15 min for each ng/dl of IGF1. Conversely, MP decreased − 273.6 min for each year of maturity offset. For clarity, the residual plots are shown in Fig. Linear regression models are depicted in Fig. p = 0.001), with an R2 of 0.76, and derived as MP (Y) = -Beta0 + Beta1 —Beta2 (Maturity offset)—Beta3 (Soccer training) + Beta4 (V̇O2max) + Beta5 (Fatigue index)—Beta6 (CMJ) + Beta7 (GH) + Beta8 (IGF1). It was found that MP increased 37.91 min for each ng/dl of GH, and increased 42.83 min for each ml.kg−1.min−1 of V̇O2max.Multiple linear regression analysis highlighted that maturation status, fitness status, and hormonal levels could significantly predict MP  = 6.05, 2max were significant predictors of MP (Table p < 0.0001), with an R2 of 0.63. Our findings highlighted that for each ml.kg−1.min−1 of V̇O2 max or each ng/dl of GH, MP increased by 53.95 and 31.46 min, respectively.Both GH and V̇OMP Table . Accordi2max. and MP, and moderate correlations between GH, IGF1, maturity offset, CMJ, and MP. Moreover, large correlations were found between V̇O2max and maturity offset, and CMJ, respectively.In the present study, we sought to investigate the relationship between playing time and maturation, physical performance, and hormonal levels. The relationship between maturity status, hormonal levels and physical performance has been investigated previously, revealing equivocal findings , 51. We 2max are better at power-related performances, thus, representing a determining factor regarding selection for competition and greater minutes of play.Children’s peak general fitness development is often coincident with PHV, which occurs at approximately 14 years of age . Indeed,2max, CMJ, maturity offset, IGF1, and GH could account for 56%, 22%, 21%, 21%, and 11% of the variation in MP, respectively. Despite V̇O2max in the present study seemed to also influence the MP, it must be noted that V̇O2max measure was estimated from the YYIR level 1, which consists in a field test that measures aerobic performance [A linear regression for each of the independent variables was conducted to investigate their influence on MP. Indeed, V̇Oformance , 53.The GH-IGF1 axis is well known to have a great impact on linear and normal growth development . Indeed,In the present study, only a moderate relationship between skeletal age and predicted PHV was observed. In fact, a study conducted on 143 youth soccer players, with the aim to validate the estimation of PHV relative to skeletal age, found only a moderate correlation between skeletal age (assessed via the Fels method) and the PHV estimation method . Similar2max explain 63% of MP, representing the most significant predictors of MP in this study. In a previous study, conducted on 29 elite young soccer players, that sought to predict the factors influencing MP through a multiple linear regression, it was revealed that 16.7% of the variance in the MP in a match was explained by jump performance, which is discordant with our results. Indeed, as previously highlighted, the evidence ascertained in the present study suggests that GH levels and aerobic capacity, together, may have greater importance in the selection for competition and MP than jump performance. However, although these two explanatory variables appear to more strongly influence MP, caution should be taken when interpreting these findings, and should be considered in the context of all the included independent variables.Compared to linear regression models, multiple linear regressions are able to yield more insight into what is influencing the dependent variable (minutes of play), by accounting for multiple factors  . AccordiAlthough the present study represents a novel contribution to the literature, our study has some limitations that should be considered. The sample size was one of the main limitations, because only one team was analyzed. However, as elite youth soccer teams have time and training restrictions as found in professional adult teams, gathering volunteers of other teams is impractical . Moreove2max and GH being the most preponderant factors for selection and MP. Additionally, aerobic capacity, jump performance, and maturity offset demonstrated significant correlations with MP. Thus, the integration of these explanatory variables, collectively, may yield more detailed information about what influences the selection for competition and the MP in elite youth soccer.To the authors knowledge, this was the first study that analyzed the influence of maturity status, hormonal activity, and physical variables, collectively, on the selection for competition and MP. The integration of hormonal activity, fitness levels, and maturation status revealed a meaningful influence on MP, with V̇OAs practical applications, both coaches and practitioners would benefit more to use aerobic capacity, jump performance, and hormonal status of each player to design more individualized training programs with the intent to develop the players with lower values. This can potentially lead coaches to have more players available to be selected and improve within-team competition, and avoiding the selection of always the same players. That is, as more advanced in maturity and in physical performance players seem to be the ones that have more MP, developing the players with less advanced maturity and physical performance will increase competitive fairness within the same team.2max and maturity offset and CMJ, respectively. We found that the interaction of maturity, hormonal, and physical dimensions accounted for 76% of MP, whilst GH and V̇O2max were the strongest determining factors influencing MP. Taken collectively, at later stages of puberty, aerobic performance appears to have an important role MP. However, the integration of maturity, hormonal, and physical dimensions may yield more robust information.In conclusion, large correlation coefficients were evident between MP and aerobic performance, and between V̇O


This is the first work ever conducted on such a subject. Analysis of the literature data clearly led to three important conclusions: leucosceptoside A is much more common in plants than leucosceptoside B; leucosceptoside A exerts more biological activities than leucosceptoside B even if nothing can be generally concluded about which one is actually the most potent; neither of these compounds can be used as a chemophenetic marker. These three aspects and more are discussed in more depth in this work. In this review paper, the occurrence in the plant kingdom, the chemophenetic value and the biological activities associated with two specific phenyl-ethanoid glycosides,  Leucosceptoside A and leucosceptoside B are two natural compounds belonging to the class of phenyl-ethanoid glycosides which have gained increasing attention in recent years due to their important and effective biological activities . Phenyl-ethanoid glycosides are biosynthetically generated merging two different processes, the shikimic acid pathway, which produces the β-hydroxy-tyrosol part of phenyl-ethanoid glycosides, and the cinnamate pathway, which produces its caffeic acid part after a series of intermediate steps .The base compound of phenyl-ethanoid glycosides is called verbascoside, acetoside or acteoside, which is structurally characterized by a central glucose residue linked to one β-hydroxy-tyrosol and one rhamnose residue through ether bonds, and to one caffeic acid through an ester bond. Leucosceptoside A differs from verbascoside for the substitution with a methyl group in the caffeic acid moiety. Indeed, leucosceptoside B differs from verbascoside for the substitution with one methyl group each in the caffeic acid and β-hydroxy-tyrosol moieties as well as for the substitution with one β-D-apiose residue in the position 6 of the glucose moiety  Figure . In the literature, there are some review papers on phenyl-ethanoid glycosides in general, exploring mainly their occurrence, structure and biological activities ,2,4; howIn the following Tables, the occurrences of leucosceptoside A  and leucPhlomis L. genus with 15 reports whereas it is quite rare in Betonica L., Schnabelia Hand.-Mazz. and Volkameria L. genera with only one report of its presence each. Henceforth, further phytochemical studies on species belonging to these genera are necessary in order to verify if this compound is really part of their phytochemical components or if its presence was only accidental. All the other seven families see a moderate occurrence of leucosceptoside A. For what concerns the collection areas of the studied species, no significatively restricted zone for the occurrence of this compound has been observed since its presence has been found in species collected from four continents, i.e., America, Europe, Africa and Asia. Nothing can be stated at the moment about the Oceanian situation since no work on it has been found. As for the studied organs, leucosceptoside A has shown no particular preference for a specific accumulation site having been individuated in leaves, aerial parts, tubers, roots and the whole plant even if it seems this compound prefers aerial organs. A few procedures have been used to extract this compound mainly associated with maceration processes in their different forms. Indeed, several techniques have been used for its isolation and identification, including high performing liquid chromatography relative techniques, liquid chromatography relative techniques, thin-layer chromatography relative techniques, infrared, ultraviolet and nuclear magnetic resonance spectroscopies and mass spectrometry. Leucosceptoside A proved to be quite common in the plant kingdom. In fact, it has been evidenced in eleven families. In particular, its lowest occurrence was observed in Asteraceae, Malvaceae and Oleaceae with one report each. In contrast, the highest occurrence has been noticed in the Lamiaceae family with 69 reports even though these were singular reports in most cases. Nevertheless, it is important to underline that not all the genera in the Lamiaceae family have shown the presence of this compound. Within the Lamiaceae family, this compound has been found particularly in the In the end, it is extremely relevant to highlight that Betonica L., Caryopteris Bunge, Clerodendrum L., Galeopsis L., Lagopsis Bunge, Leonurus L., Salvia L., Scutellaria L., Sideritis L. and Volkameria L. genera. This situation prompts the need to perform more phytochemical analyses on the species for its further research, also because several singular reports have been found in the literature with the same conclusions as drawn before. With respect to leucosceptoside A, leucosceptoside B proved to be less common in the plant kingdom. In fact, it has been evidenced only in six families. Its lowest occurrence was observed in the Bignoniaceae, Orobanchaceae, Plantaginaceae and Verbenaceae families with one report each, whereas the highest occurrence has been noticed in the Lamiaceae family again with seventeen reports. There is a certain parallelism between the results found for leucosceptoside A and those found for leucosceptoside B for what concerns the collection areas of the studied species, the studied organs and the methodologies adopted for their isolation and identification. Indeed, there are some important differences for what concerns the families, genera and species where their presence has been reported. In particular, leucosceptoside B has not been reported in the Acanthaceae, Compositae, Linderniaceae, Malvaceae and Oleaceae families. In addition, for what concerns the Bignoniaceae, Scrophulariaceae and Verbenaceae families, leucosceptoside B has been found in completely different species, if not genera themselves, than leucosceptoside A. For what concerns the Lamiaceae family, the reported genera and species are not generally the same as for leucosceptoside A. In particular, leucosceptoside B has not been found in the Leucosceptoside B cannot also be used as a chemophenetic marker at any level for the same reasons as presented before, even if it presents a lower occurrence than leucosceptoside A. Leucosceptoside A has shown several interesting pharmacological activities. In the following lines, these activities are explored and detailed one-by-one. + confirm this with quite similar efficacy values. In particular, Ersöz et al. [50 value of 76.0 µM, which is lower than ascorbic acid used as a positive control (IC50 = 112 µM). Harput et al. [50 value of 18.43 μg/mL, which is higher than quercetin but comparable (IC50 = 4.3 µg/mL), whereas Ono et al. [50 value of 25.7 µM, which is very similar to that for α-tocopherol (EC50 = 25.9 µM). Huang et al. [50 value of 72.14 μM, which is lower than vitamin C (IC50 = 81.83 µM). Lan et al. [50 value of 11.26 μM, which is slightly better than the positive control, ascorbic acid . Indeed, Calis et al. [50 value of 125.4 µM, which is quite higher than that of dl-α-tocopherol, used as a positive control (IC50 = 75.5 µM). Delazar et al. [50 of 0.0148 mg/mL, which is higher than trolox and quercetin, used as positive controls , instead. Lastly, Shen et al. [50 value of 53.32 µM, which was found to be higher than that of BHT, but no value of this latter was given. Leucosceptoside A proved to be a good antioxidant compound. Several studies against DPPH.z et al.  obtainedo et al.  obtainedg et al.  obtainedn et al.  obtaineds et al.  obtainedr et al.  obtainedn et al.  obtainedOn the other hand, Charami et al.  expresse50 of 0.294 mM, which is higher than all the other phenyl-ethanoid glycosides studied in this work. The best one was verbascoside, which presents an SC50 value of 0.063 mM. In addition, Wang et al. [N-formyl-methionyl-leucyl-phenylalanine in stimulated human polymorphonuclear neutrophils. The results showed that this compound is a weak inhibitor of hydroxyl radicals with a percentage of inhibition of 27.8% at the concentration of 0.55 mM and a modest iron reductor with a percentage of 17.86% at the concentration of 1.57 mM. The former value represents the lowest percentage of inhibition among all the phenyl-ethanoid glycosides considered in this study, whereas the latter value is the second worst. Verbascoside was the most active as an inhibitor of the hydroxyl radical with a percentage of 55.7% at the concentration of 0.55 mM, whereas pedicularioside M was the most active as an iron reductor with a percentage of 23.57% at the concentration of 1.73 mM. Heilmann et al. [N-formyl-methionyl-leucyl-phenylalanine-stimulated human polymorphonuclear neutrophils through a luminol-enhanced chemiluminescence assay. The obtained IC50 value was 0.18 µM, which is higher but not too far from that of quercetin used as a positive control . Nevertheless, most of the other phenyl-ethanoid glycosides studied in this work showed better results than leucosceptoside A and, in particular, echinacoside was the best one with an IC50 value of 0.03 µM. Leucosceptoside A was observed to be a modest radical scavenging compound. In particular, Wang et al.  studied g et al.  also stun et al.  also stu50 value of 9.0 µM in the Raw 264.7 cell line, whereas the positive control aminoguanidine had an IC50 value of 10.7 µM. Vien et al. [50 value of 61.1 µM, which is much higher than the positive control butein (IC50 = 4.5 µM). In contrast, Ochi et al. [Leucosceptoside A shows moderate anti-inflammatory activities with respect to NO production. In particular, Han et al.  obtainedn et al.  obtainedi et al.  obtainedi.e., α-glucosidase, acetylcholinesterase, protein kinase C alpha and tyrosinase. Leucosceptoside A has been also studied for its potential inhibitory effects on some enzymes, 50 value of 0.7 mM, which is much lower than acarbose used as a positive control (IC50 = 14.4 mM). Indeed, Thu et al. [50 value of 273.0 µM, which is a little higher than that of acarbose (IC50 = 204.2 µM). Concerning α-glucosidase, this compound has shown contrasting results. In fact, Liu et al.  obtainedu et al.  obtained50 value of 423.7 µg/mL, which is much higher than Captopril® used as a positive control . In addition, Saidi et al. [50 value of 72.85 µM, which is also much higher than that of the positive control used in this study, i.e., galantamine . Indeed, Li et al. [50 value of 3.86 mM, which is comparable to that of Captopril® used again as a positive control . Leucosceptoside A also possesses between moderate and modest acetylcholinesterase inhibitory effects. In fact, Kang et al.  obtainedi et al.  obtainedi et al. , using t50 value of 19.0 µM. This value is good in number but, in the same study, other phenyl-ethanoid glycosides were found to be more active, such as forsythoside and verbascoside, showing IC50 values of 4.6 and 9.3 µM, respectively [This compound is also a modest protein kinase C alpha inhibitor with an ICectively . In addition, this compound shows only modest tyrosinase inhibitory activities, with a percentage of inhibition of 21.65% at the concentration of 0.051 mM. Kojic acid, used as a positive control, has a percentage of inhibition of 53.87% at the concentration of 0.047 mM . A similLastly, this compound has shown no effect on the hyaluronidase enzyme inhibition test and collagenase enzyme inhibition test at the concentration of 100 µg/mL .4 intoxication, by means of an MTT assay and flow cytometry, with values of cell number and cell viability both above 80%, thus, implying a restoration of cell survival. These values are extremely good in numbers, but no standard compound was tested for comparison. The mechanism of action occurs through the inhibition of NF-kB activation since it was observed that pretreatment with this compound can inhibit CCl4-induced lipid peroxidation in HepG2 cells by 177.73% and attenuate the decrease in SOD by 76.58%; furthermore, pre-incubation of the same cells with this compound can prevent ROS production by 183.56% [At 100 µM, leucosceptoside A exerts strong hepatoprotective properties in pretreatment as obtained by studying the viability of HepG2 cells after CCl 183.56% . +)-induced cell death in mesencephalic neurons of rats. MPP+ is the ion produced after the biotransformation of the neurotoxin 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine by the monoamine oxidase B, and it is well known to cause Parkinson’s disease in rats and non-human primates. By means of an MTT assay, it was observed that leucosceptoside A, at the concentration of 4 µM, reduces cell death by 7%, whereas at the concentration of 16 µM, it increases cell growth by 3.7%. These values are extraordinary, however, in the same study, a more efficient compound was found, i.e., pedicularioside A. In fact, at the concentration of 4 µM, this latter compound shows a reduction value of cell death by 3.4% and, at the concentration of 16 µM, it increases cell growth by 21.4% [Leucosceptoside A, in pretreatment, exerts good neuroprotective effects against the 1-methyl-4-phenylpyridinium ion  [Leucosceptoside A exhibits promising cytoprotective effects against 37.1 µM) . 50 value of 0.23 mM, which is slightly higher than that of the standard compound heparin (CH50 = 0.06 mM) [Leucosceptoside A exerts good anticomplementary effects with a CH0.06 mM) .50 value of 29.4 µM. This value is better than curcumin (IC50 = 54.3 µM) and comparable to L-chicoric acid (IC50 = 21.0 µM) used as positive controls [Leucosceptoside A has shown strong HIV-1 integrase inhibitory effects with an ICcontrols . 50 values of 200, 189.08 and 182.33 µg/mL, respectively. The standard compound doxorubicin presents IC50 values of 0.175, 0.235 and 0.096 µg/mL, respectively, whereas the other standard compound actinomycin D presents IC50 values of 0.013, 0.022 and 0.019µg/mL, respectively. On the contrary, it showed no effect against melanoma. Saidi et al. [50 = 80.87 µM as well as a positive result on the A549  cancer cell line obtaining an IC50 = 99.00 µM. All these values are much higher than the standard compounds used, i.e., doxorubicin for the former cancer cell line (IC50 = 0.36 µM) and ellipticine for the latter cancer cell line (IC50 = 0.31 µM). Abe et al. [50 = 42 µM) and also against the B16F10 (murine melanoma) cell line with a GI50 value equal to 28 µM and against the MK-1 (gastric carcinoma with liver metastasis) cell line with a GI50 value equal to 33 µM. All these values are good in numbers, but some other phenyl-ethanoid glycosides studied in this work present better results in full or in part. In particular, iso-verbascoside was the most potent against B16F10 and MK-1 with GI50 values of 10 and 32 µM, respectively, whereas arenarioside was the most potent against HeLa with a GI50 value of 34 µM. Unlike the previous works, Saracoglu et al. [According to Argyropoulou et al. , leucosci et al.  also tese et al.  obtained50 value of 1.69 µM, which is very promising. Yet, other phenyl-ethanoid glycosides studied in this work showed better results. In particular, iso-verbascoside was the most potent with an IC50 value of 0.38 µM [Leucosceptoside A exhibits good inhibitory effects against ADP + NADPH-induced lipid peroxidation in rat liver microsomes with an IC 0.38 µM . 9 dm3 mol−1 s−1. This value is very good in number, but without a direct comparison with any compound [This compound also exhibits inhibitory effects on the protonation of thymine radical anion induced by pulse radiolysis, which causes severe damages in cells with a reaction rate constant of electronic transfer equal to 1.54 × 10compound . Staphylococcus aureus ATCC29213 and Enterococcus faecalis ATCC29212 with MIC values of 1000 µg/mL [Leucosceptoside A exerts poor antimicrobial effects against 00 µg/mL . These vEscherichia coli ATCC25922 [Mycobacterium tuberculosis H37Rv [Pseudomonas aeruginosa ATCC27853 [Bacillus subtilis NBRC3134 and Klebsiella pneumoniae NBRC3512 [Indeed, it has shown no activity against TCC25922 , Mycobacis H37Rv , PseudomTCC27853 , BacilluNBRC3512 .Candida albicans ATCC90028, Candida krusei ATCC6258 and Candida parapsilosis ATCC22019 [Leucosceptoside A has shown no activity against TCC22019 .Leucosceptoside B has also shown some interesting pharmacological activities, even if less numerous than leucosceptoside A. In the following lines, these activities are explored and detailed one-by-one. Leucosceptoside B proved to be an antioxidant compound. Several studies, according to different assays, confirm this with opposite efficacy values. + assay, this compound exerts between moderate and modest effects. In fact, Niu et al. [50 value of 31.16 µM, which is higher than ascorbic acid used as a positive control (IC50 = 7.81 µM). In addition, Georgiev et al. [50 value of 96 µg/mL, which is high with respect to the other phenyl-ethanoid glycosides studied in this work. In particular, this compound was found to be the weakest, whereas the most potent was forsythoside B with an IC50 value of 21 µg/mL. Indeed, Lan et al. [50 value of 13.05 μM, which is comparable to that of ascorbic acid . Lastly, Calis et al. [50 value of 61.3 µM, which is lower than that of dl-α-tocopherol used as a positive control (IC50 = 75.5 µM); yet there was one phenyl-ethanoid glycosides (myricoside) that is even more potent than this (IC50 = 46.8 µM).According to the DPPH.u et al.  obtainedv et al.  obtainedn et al.  obtaineds et al.  obtained50 value of 0.17 µM, which is higher but not too far from that of quercetin used as a positive control . Through a luminol-enhanced chemiluminescence assay with formyl-methionyl-leucyl-phenylalanine in stimulated human polymorphonuclear neutrophils, Heilmann et al.  reported50 value of approximately 45 µg/mL, which is much higher with respect to the other phenyl-ethanoid glycosides studied in this work, and in particular, of verbascoside, which was the best one (IC50 = 4.2 µg/mL). Indeed, Georgiev et al.  also stuLeucosceptoside B exerts good inhibitory effects on cobra venom factor-induced alternative pathway activation in mouse sera with a percentage of inhibition of 40% and on COX-2 production with a percentage of inhibition near 30%. The positive control, indomethacin, presents a percentage of inhibition near 70%. In addition, it shows moderate inhibitory effects on NO production and IL-10 production as well as good inhibitory effects on COX-1, even if in the study, the values were not clearly expressed. Furthermore, all these values are higher than indomethacin . Georgiev et al.  studied 50 value of 20.1 µg/mL, whereas galanthamine has an IC50 value of 13.2 µg/mL. Indeed, Cespedes et al.  obtainedCespedes et al.  did not +)-induced cell death in mesencephalic neurons at the concentration of 40 µg/mL. The potency was measured as optical density with a value of 1.06. However, buddleoside A, another phenyl-ethanoid glycoside, was found to be much more potent with a value of 1.62 [Leucosceptoside B, in pretreatment, is also able to exert strong neuroprotective effects against the 1-methyl-4-phenylpyridinium ion  [+ radical scavenging assay and showed that leucosceptoside A is slightly better than leucosceptoside B  [+ radical scavenging assay; however, the relative studies led to extremely contrasting results. In fact, the IC50 values found for leucosceptoside A were 76.0 µM [50 values found for leucosceptoside B were 31.16 µM [According to the data as reported in 0.17 µM) . The sec3.05 µM) . One fur 76.0 µM , 18.43 µ 76.0 µM , 125.4 µ 76.0 µM  and 53.331.16 µM , 96.0 µM31.16 µM  and 61.331.16 µM . These dThis review article clearly shows how leucosceptoside A and leucosceptoside B are important compounds with regards to some aspects. In fact, they have been found in different species belonging to several families and, even though they do not possess chemophenetic significance on their own, they are also endowed with several interesting pharmacological activities including antioxidant, anti-inflammatory, enzyme inhibitory and neuroprotective. However, searching for these phytochemical components of plants is still quite limited due to the several factors. This review article also aimed to be a stimulus to amplify studies on both phytochemistry and pharmacology since there is still a lot to be discovered.