Objectives: We aimed to validate the vasoactive-ventilation-renal (VVR) score and to compare it with other indices as a predictor of outcome in neonates recovering from surgery for critical congenital heart disease. We also sought to determine the optimal time at which the VVR score should be measured.Methods: We retrospectively reviewed neonates recovering from cardiac surgery between July 2017 and June 2020. The VVR score was calculated at admission, 24, 48, and 72 hours postoperatively. Max values, defined as the highest of the four scores, were also recorded. The main end result of interest was a composite outcome which included prolonged intensive care unit stay and mortality. Receiver operating characteristic curves were generated, and areas under the curve with 95% confidence intervals were calculated for all time points. Multivariable logistic regression modeling was also performed.Results: We reviewed 73 neonates and 21 of them showed composite outcomes. The area under the curve value for VVR score as a predictor of composite outcome was greatest at postoperative 72-hour max . On multivariable regression analysis, the VVR max 72 hours remained a strong independent predictor of prolonged ICU stay and mortality .Conclusions: We validated the utility of the VVR score in neonatal cardiac surgery for critical congenital heart disease. The VVR follow-up in postoperative 72 hours is superior to other indices and especially the maximum VVR value is a potentially powerful clinical tool to predict ICU stay and mortality. Newborns operated for critical congenital heart disease (CHD) have a high risk of postoperative mortality and morbidity -4. TheseFor this purpose, it has been shown that the vasoactive inotrope score (VIS) and serum lactate levels, which are used recently in clinical practice, are correlated with prognosis -9. VIS iHowever, newborns undergoing cardiac surgery often have multiorgan dysfunction and especially pulmonary and renal systems are affected ,11. NeitIn order to overcome this limitation of serum lactate and VIS, Miletic et al. introduced the vasoactive-ventilation-renal (VVR) score in 2015 and used markers of the cardiovascular, pulmonary, and renal systems, which are the most frequently affected systems in CHD surgery . In the In the most recent multicenter retrospective study involving only newborns, it was found that the postoperative twelfth-hour VVR score was more effective in predicting the prolonged mechanical ventilation (MV) duration compared to other indices, Society of Thoracic Surgeons - European Association for Cardio-Thoracic Surgery Congenital Heart Surgery (STAT) Mortality Categories and cardiopulmonary bypass (CPB) duration .However, in the vulnerable neonatal populations, the possibility to have temporary cardiovascular, pulmonary, and renal dysfunction in the early postoperative period is higher. Therefore, it would be rational to follow up these patients with VVR scores for a longer period not to miss out on the sustained dysfunction which is more likely to influence the outcome.The aim of our study is to evaluate the potential of predicting prolonged intensive care unit (ICU) stay and/or mortality by calculating the VVR score for 72 hours postoperatively, and to compare it with other indices and, if possible, to find an appropriate cut-off value and to provide an idea for future studies.https://authorea.com/users/371116/articles/489571-validation-of-the-vasoactive-ventilation-renal-score-as-a-predictor-of-prolonged-intensive-care-unit-stay-and-mortality-after-critical-congenital-heart-surgery-in-neonates).This article was previously posted to the Authorea preprint server on October 29, 2020 . Informed written consent were obtained from the parents of all participants for surgical and intensive care procedures.Study populationAll neonates, defined as less than or equal to 28-days-old, who underwent pediatric cardiac surgery (with or without CPB) were reviewed.Exclusion criteria were as follows: (i) premature babies who underwent ligation of patent ductus arteriosus (PDA); (ii) cases that placed on extracorporeal membrane oxygenation (ECMO) support in the operating room or those requiring ECMO support within the first 72 hours postoperatively were excluded from the study.Data collectionData were collected via medical record review. Demographic and preoperative data collection included sex, birth weight, gestational week, being premature , being low birth weight (<2500 g), antenatal diagnosis status, postnatal admission day, underlying cardiovascular diagnoses, presence of noncardiac anomalies, need for MV and inotropic support at admission, need for MV and inotropic support at operation day, preoperative sepsis and need of dialysis, and postnatal day of surgery were recorded.Perioperative data collection included surgical procedure performed, STAT Mortality Category , use andPostoperative data collection included the need for ECMO, need for inhaled nitric oxide therapy, presence of postoperative open sternotomy, the occurrence of arrhythmias, postoperative MV and inotropic duration, duration of ICU stay, and mortality were recorded. We recorded MV variables, arterial blood gas and lactate measurements, and doses of inotropic and vasopressor medications at four postoperative time points: ICU admission, 24 hours, 48 hours, and 72 hours after ICU arrival. We also recorded preoperative serum creatinine and daily serum creatinine measurements obtained within the first 72 postoperative hours.Derivation of the VVRVVR scores were calculated as follows: VI (Ventilation Index) + VIS + ΔCr.VIS = dopamine dose [μg/kg/min] + dobutamine dose [μg/kg/min] + 100 × epinephrine dose [μg/kg/min] + 10 × milrinone dose [μg/kg/min] + 10,000 × vasopressin dose [U/kg/min] + 100 × norepinephrine dose [μg/kg/min]).2))/1,000).VI =  and median (25th-75th percentile) for quantitative data. It is presented as frequency (percentage) for categorical data. The significance level was taken as p<0.05.All statistical analyses were performed using IBM SPSS version 23 . Shapiro-Wilk tests were used to determine normal distribution. The main outcome of interest was the composite outcome . The study group was dichotomized as upper 25th percentile of ICU stay and/or mortality (defined as having composite outcome) versus lower 75th percentile for ICU stay. Bivariate comparisons were performed for demographic and perioperative characteristics of patients with and without composite outcome using Chi-square or Fisher exact test for categorical variables. In the comparison of quantitative variables according to paired groups, an independent two-sample t-test was used for normally distributed data and the Mann-Whitney U test was used for non-normally distributed data. Repeated analysis of variance was used to compare normally distributed data over three or more times, and the Friedman test was used to compare non-normally distributed data. Variables that attained a bivariate significance of 0.2 or less were considered for inclusion in a multivariable logistic regression model. Receiver operating curve (ROC) analysis was used to determine cut-off values for VIS, VI, VVR, VVRThe medical files of 95 newborns who were operated on in the first 28 days of life during the study period were examined. Sixteen of these patients were preterm babies who had bedside PDA ligation. Six patients were excluded from the study because they were placed on ECMO support in the operation room. As a result, the study group consisted of 73 patients. The anatomical diagnoses of the patients included in the study and the surgical procedures performed are summarized in Table The mean gestational week and birth weight of the study group was 38.6 ± 1.6 weeks and 3179 ± 528 g, respectively. Over 72.6% of the cases were male, 12.3% were premature, and 13.7% had an additional non-cardiac anomaly. The antenatal diagnosis rate was 28.8%. 38.4% of the cases had single ventricle anatomy and 82.2% were STAT category 4 or 5. None of the cohorts needed ECMO support in the first 72 hours postoperatively.The postoperative prolonged ICU stay of the cohort was defined as 29 days or longer. Eight cases died in the postoperative period. Two of these cases died before 29 days (15th and 20th days). Thus, 21 cases met the composite outcome criterion, which is the main outcome of our study. The study population was divided into two according to the composite outcome, and bivariate analysis of demographic, anthropometric, and perioperative features of cases with and without composite outcome are presented in Table ROC analysis of serum lactate, VIS, VI, and VVR scores was performed, and area under curve (AUC) values, cutoff values, sensitivity, and specificity data at all measurement points are presented in Table 72max score, the odds of a composite outcome increased by 45% . The remaining variables that were significant on bivariate analysis were not significant on multivariable analysis and did not appreciably affect the model. The best multivariable model for composite outcome including VVR 72 hour max, lactate 72-hour max, and single ventricle physiology is presented in Table All variables in Tables 72max, we dichotomized the variable into high and low. A VVR72max cutoff value of 46.5 was chosen to maximize total accuracy and minimize weighted error ratios, and correctly classified 90% of cases. On multivariable logistic regression analysis, a high VVR72max remained strongly associated with the composite outcome .To simplify the interpretation and use of the VVRWe have validated the VVR score as a multiorgan system severity of illness index for neonates recovering from surgery for critical congenital heart disease. We demonstrated that the VVR strongly predicts prolonged postoperative ICU stay and/or mortality (composite outcome) more so than VIS, VI, and serum lactate.In a limited number of prior studies, the VVR calculated at 48 hours  and at 12 hours ,15 was f72max) of each case in the first 72 hours with the maximum values of other indices, and unlike other studies, we reached the highest AUC value and highest accuracy in prediction of results. Specifically, if the postoperative VVR72max of a neonate is 46.5 and above, this case was found to be 23 times riskier in terms of prolonged ICU stay and mortality.In order to include all cases in the analysis, we compared the highest measurements  and hospital stay better than VIS and serum lactate level. The cutoff value in this study was found to be 22.5 .In the next prospective study of Miletic et al., the patient population was expanded as under 18 years of age and those entering CPB. The VVR index at postop 48th hour gave better results than all measurements, and the cutoff value was found to be 13 [Scherer et al. included pediatric and adult congenital heart patients in their study, and within 48-hour postoperative measurements; it was stated that the predictivity of the 12th-hour VVR score was the most effective, and the cutoff value was determined as 25 .In a recent multi-center study involving only newborns, like our study, score calculations were made in the postoperative 12-hour period, and the VVR score was found to be superior in determining prolonged MV duration (determined as > 96 hours in this study) compared to VIS, VI, and serum lactate. In this study, the cutoff value was expressed as 35 .As it can be seen, as the study age group descends into complex patient groups such as the neonatal period, the cutoff values increase, but the VVR score maintains its strong predictivity compared to other indices.In our study, 82% of the patient group was in STAT mortality categories 4 and 5 and 80% had undergone CPB. Also, the rate of antenatal diagnosis was as low as 28.8%, so an important part of the study group applied to the hospital with cardiopulmonary decompensation, and 44% required preoperative MV. So our cohort consists of more severe and complex cases according to the literature. We think this is the reason why we found the VVR score cutoff value to be higher.Although VVR is a powerful marker in determining outcomes like postoperative ICU stay and mortality, there are many additional factors that affect outcomes, especially in neonates. For example, even if our study could not be demonstrated due to the limited number of cases, airway anomalies and gastrointestinal anomalies can prolong hospitalization and cause deaths even if the cardiac operation is successful. In addition, cases without antenatal diagnosis or with delays in postnatal diagnosis and treatment admit to the hospital with cardiopulmonary decompensation, and the multiorgan injuries that occur because of this, affect the postoperative process negatively. The next logical step will be increasing the predictivity of the VVR score by adding well-defined preoperative variables and other organ system markers in future studies.Longer scoring time in vulnerable populations like the neonatal period will enable us to predict persistent dysfunction leading to poor prognosis rather than acute dysfunction in the postoperative transition period. As our study shows, 72-hour values have the best predictivity after the maximum value in neonatal cardiac surgery. With multi-center and larger heterogeneous patient cohorts, specific cutoff values should be determined according to anatomical diagnosis, age group, surgical procedure, and postoperative measurement time.Study limitationsOur study has been designed retrospectively and includes only newborn cases. Therefore, multicenter and comprehensive prospective studies are needed regarding the applicability of the VVR score to all congenital heart diseases. We acknowledge that the VVR score cannot reliably be calculated for patients requiring ECMO support and peritoneal dialysis. Studies are needed which focus on this subgroup of patients to identify risk factors for poor outcomes.We validated the utility of the VVR score in neonatal cardiac surgery for critical congenital heart disease. The VVR follow-up in postoperative 72 hours is superior to other indices, and especially, the maximum VVR value is a potentially powerful clinical tool to predict ICU stay and mortality. Neonates with a peak VVR greater than or equal to 46.5 within the first 72 postoperative hours should be considered at increased risk for poor prognosis.


Acacia nilotica pods’ extract and the hydrothermal method to prepare nanoparticles of pure zinc oxide and pure copper oxide and nanocomposites of both oxides in different ratios. Five samples were prepared with different ratios of zinc oxide and copper oxide; 100% ZnO (ZC0), 75% ZnO: 25% CuO (ZC25), 50% ZnO: 50% CuO (ZC50), 25% ZnO: 75% CuO (ZC75), and 100% CuO (ZC100). Several techniques have been applied to characterize the prepared powders as FTIR, XRD, SEM, and TEM. The XRD results confirm the formation of the hexagonal wurtzite phase of zinc oxide and the monoclinic tenorite phase of copper oxide. The microscopy results show the formation of a heterostructure of nanocomposites with an average particle size of 13–27 nm.This work represents a novel combination between  Zinc oxide has been widely applied as photocatalysts ,2,3,4, a3O4-ZnO gas sensor towards triethylamine [2+ = 50 at.% [2O3, which changed the bandgap to 3.17 eV, 3.28 eV and 3.16 eV, respectively [Q. Zeng et al. reported enhanced gas sensing properties of NiO-ZnO nanocomposites, which they attributed to the formation of a p-n heterojunction . The samhylamine . Y. Wang 50 at.% . M. Toe ectively . Copper Various methods are applied to prepare metal oxide nanoparticles and nanocomposites as simple precipitation , electroTagetes spp. petals in the presence of CTAB surfactant [Sambucus nigra L. extract [R. Mohamed et al. prepared CuO-ZnO heterojunction photocatalyst through a simple wet method in the presence of F-127 surfactant . A. Prajrfactant . Moreoverfactant . ZnO-CuO extract .Acacia nilotica, also known as gum arabic tree, belongs to the Fabaceae family. It is popular in Africa and Asia and the tree has roots, pods, stems, and leaves. The extract has many phytochemical components as flavonoids, phenols, and tannins [Acacia nilotica have been used to prepare Ag-TiO2 nanocomposites [ tannins ,39. The  tannins , the lea tannins , the aermposites .Acacia nilotica Pods’ extract and the hydrothermal method. Pristine zinc oxide and copper oxide nanoparticles were synthesized in addition to copper oxide-zinc oxide nanocomposites with different ratios. The functional groups and the formed phases were determined by Fourier Transform Infrared spectroscopy (FTIR) and X-ray diffraction (XRD), respectively. The morphology and particle size were followed by scanning electron microscopy (SEM) and transmission electron microscopy (TEM).The recent work reports for the first time the combination between a green synthesis that employs 2.6H2O), zinc chloride (ZnCl2), potassium hydroxide (KOH) were bought from Sigma-Aldrich. All the primary chemicals used in this work were of analytical grade. All solutions were prepared with double-distilled water. The Acacia nilotica pods were bought from a local store, Al-Ahsa, Saudi Arabia.Copper chloride hexahydrate  (Philips XL30) was used, accelerating voltage of 30 kV and the magnification up to 400,000×. A high-resolution, JEOL JEM-1011 Transmission Electron Microscope was used for TEM imaging.Acacia nilotica pods were rinsed with tap water three times and with distilled water for the last time. To prepare the extract, 10 g of dried pods were boiled with 100 mL of distilled water at 60 °C for 15 min under magnetic stirring. The prepared extract was centrifuged at 8000 rpm for 5 min and then filtered via Whatman No. 1 filter paper, to remove all fine plant debris and stored at 4 °C [The  at 4 °C . The pH 2.6H2O) and a 0.2 M solution of zinc chloride (ZnCl2) were prepared in two different containers. The compositions of samples are mentioned in Acacia nilotica extract is added to a 100 mL of 0.2 M zinc chloride salt solution to prepare sample ZC0. A 1 M KOH was added to the previous mixture while under continuous stirring until the pH reaches 10.A 0.2 M solution of copper chloride hexahydrate  after precipitation, (c) after hydrothermal treatment and drying and (d) after calcination. The FTIR of Acacia nilotica pods’ extract shows a very broad band between 2800–3600 cm−1 which may correspond to the stretching vibration of aromatic and aliphatic OH groups (3200–3500 cm−1) or stretching of aromatic and aliphatic C-H (3000–3100 cm−1). A sharp finger-like peak around 1500–1700 cm−1 stands for carbonyl groups or bending of aromatic C=C. A very broad band below 1000 cm−1 may refer to the bending of aromatic C-H or C-O-C groups. According to the literature, the FTIR results of Acacia nilotica pods’ extract confirm the presence of flavonoids, tannins and terpenoids in the extract [−1 [ extract ,39. The ract [−1 .Samples ZC25, ZC50, and ZC75 show the peaks corresponding to wurtzite hexagonal zinc oxide and tenorite monoclinic copper oxide with different intensities. However, the intensity of peaks corresponding to wurtzite zinc oxide is decreasing gradually in the samples ZC25, ZC50, and ZC75 with decreasing the amount of zinc precursor in the starting materials. The same can be observed in an opposite way for the monoclinic tenorite and the intensity of copper oxide peaks increases gradually in samples ZC25, ZC50, ZC75 with an increasing copper precursor in the initial compositions  2,26,48,4826,48.Acacia nilotica extract, which seems to be more effective as a capping agent than ethanol as a solvent in decreasing the crystallite size [Calotropis gigantea, and the average crystallite size was about 35 nm [The crystallite size of zinc oxide and copper oxide is estimated using the Debye–Scherrer formula and presented in ite size . C. Kumaut 35 nm . M. Mansut 35 nm . Again, Acacia nilotica phytoexctract acted as capping agents which enhances the growth of CuO bipyramid.Adding 25% copper oxide into zinc oxide resulted in changing the morphology from stacked layers/aggolmerated particles into homogenous elongated particles, as can be depicted in In the present study, ZnO NPs, ZnO-CuO NCs, and CuO NPs have been prepared by an inexpensive and environmentally friendly method; the green-hydrothermal method. The proposed mechanism is presented in the following equations;Acacia nilotica pods’ extract act as capping agents. The capping agents play an important role in decreasing the agglomeration and in controlling the growth during the hydrothermal step.The presence of phytoconstituents, i.e., flavonoids, tannins, and terpenoids; in the Acacia nilotica pods’ extract with the hydrothermal method resulted in the synthesis of ZnO NPs, ZnO-CuO NCs, and CuO NPs. The prepared ZnO NPs have a hexagonal wurtzite phase and the CuO NPs have a monoclinic tenorite phase. Interestingly, ZnO-CuO NCs have a hexagonal phase for ZnO and a monoclinic phase for CuO with no secondary phases. The average crystallite size of NPs and NCs is in the range of 17–30 nm. The morphology of the particles depend on the ratio ZnO-CuO and the prepared particles showed different morphologies as agglomerated particles, nanorods, intermeshed flakes together with irregularly shaped particles.In the recent work, successful combination of


High-shear mixer coatings as well as mechanofusion processes are used in the particle-engineering of dry powder inhalation carrier systems. The aim of coating the carrier particle is usually to decrease carrier–drug adhesion. This study comprises the in-depth comparison of two established dry particle coating options. Both processes were conducted with and without a model additive (magnesium stearate). In doing so, changes in the behaviour of the processed particles can be traced back to either the process or the additive. It can be stated that the coarse model carrier showed no significant changes when processed without additives. By coating the particles with magnesium stearate, the surface energy decreased significantly. This leads to a significant enhancement of the aerodynamic performance of the respective carrier-based blends. Comparing the engineered carriers with each other, the high-shear mixer coating shows significant benefits, namely, lower drug–carrier adhesion and the higher efficiency of the coating process. The increasing prevalence of respiratory diseases has been reported frequently . Due to In this study, an assessment of additive-free and additive-containing processed powders was conducted. This enables the comparison of both approaches on different levels, allowing conclusions on whether changes can be attributed to the additive or the process itself. Since both methods are already established and lead to distinct increases in fine particle fraction (FPF), it is important to investigate the differences. Moreover, this study can help in deciding which particle coating process shall be preferred for adding magnesium stearate or similar additives.® 230  a crystalline, sieved inhalation grade lactose monohydrate was used. Magnesium stearate  served as the model coating material. For the sake of simplicity, the materials are shortened to the following: InhaLac 230 (IH230), magnesium stearate (MgSt), InhaLac 230 processed in the mechanofusion reactor , InhaLac 230 processed in the high-shear mixer . Micronised ipratropium bromide served as the model drug .As the model carrier in the coating processes, InhaLac® using the Picoline® platform . The carrier and coating materials (2% (w/w) MgSt) were premixed in a Turbula® blender  at 42 rpm for 5 min. Pre-blends were then transferred to the AMS. The AMS coating started by increasing the rotor speed up to 4000 rpm within one minute and keeping it constant at 4000 rpm over 10 min.The mechanofusion process was conducted with the Angmill Mechanofusion System (AMS) unit of the Picobond® unit of the Picoline platform. A rotor speed of 500 rpm was kept constant for 15 min.The high-shear mixer (HSM) coating was conducted using the PicomixAll raw materials were sieved before processing (mesh size: 250 µm), as well as the coated samples after processing. To assess the energy input to the powder, the data transfer tool of the Picoline was used. The instrument performance over the whole processes using the same powder mass was averaged and then multiplied with the respective process duration to obtain the total energy input. The procedure was then repeated without powder. The idle running energy was subtracted from the total energy input to calculate the energy input into the powder sample. All coatings were conducted at monitored relative humidity (RH) of 45% ± 15% and room temperature (20 °C to 25 °C).A power compensation DSC  was used for each measurement, and data were evaluated with the PYRIS™ Software (PerkinElmer Inc.). Approximately 5 mg of the respective sample was weighed into an aluminium pan, which was sealed and pierced afterwards to allow gas to escape. A pierced, empty aluminium pan was used as reference. During analysis, the sample was flushed with nitrogen to avoid any oxidation processes. All samples were heated at a rate of 10 °C/min up to 240 °C. Results are plotted as the heat flow (mW) over temperature. Furthermore, the thermogravimetric properties of the sample were analysed , using the same heating rate and heating range as that of the DSC. This provides additional information on what happens at the events observable in the DSC .Dynamic vapour sorption (DVS) was carried out using the DVS Resolution . For these experiments, approximately 70 mg of the respective sample was weighed into the sample pan. Measurements were carried out at 25 °C. The method consisted of two cycles of increasing the partial pressure of bidistilled water (aq. bidest.) from 0–90% in 10% steps and returning to 0%. At the beginning of every measurement, the sample was conditioned for 180 min at 0% RH. Every step of the method was not limited by time but by a change in mass of below 0.005%/min.®, Sympatec GmbH, Clausthal-Zellerfeld, Germany) was equipped with a RODOS® dispersion module and a R4 lens with a measuring range of 0.5 to 350 µm. With compressed air (2 bar), the automatically fed  material was dispersed in an aerosol jet towards the measuring zone.Laser diffraction was applied to determine the particle size distribution (PSD) of the initial and processed material. For this, a Helium Neon Laser Optical System  based on the Fraunhofer enhanced equation.0 0.05–0.35).The assessment of specific surface area (SSA) using the BET method and the surface energy of solids (SE) was carried out using the surface energy analyser . The powder samples were weighed into silanised glass columns (4 mm inner diameter) and fixed with silanised glass wool on both ends. To avoid hollows and cracks in the powder bed, the filled columns were compressed by tapping for 10 min using the SMS column packer accessory. Prior to every measurement, all columns were conditioned at 0% RH and 10 sccm carrier gas flow (nitrogen) for one hour to get rid of any volatile contamination. For SSA measurements, a series of octane injections was performed, providing an adsorption isotherm. The calculation of the SSA was based on the linear section of the adsorption isotherm  for dispersive SE as well as chloroform and toluene for determination of acid-base surface properties. All injected concentrations were based on the respective monolayer capacity, leading to surface coverages from 0.5% up to 10%. For the determination of the dead volume, a double injection of methane was performed at the beginning and at the end of every experiment. All experiments were carried out at 0% RH and 30 °C with a carrier gas flow of 10 sccm.The raw data were analysed using the SEA Analysis Software . Calculations were based on the DellaVolpe scale in combination with the Dorris and Gray approach and the polarisation method ,19. For The imaging of particle morphology was conducted with scanning electron microscopy (SEM) using Phenom XL . To guarantee sample grounding and to minimise charging effects, samples were fixed onto carbon stickers and gold-sputtered with BAL-Tec SCP 050 Sputter Coater . All images were taken at 1000× or 2500× magnitude with an acceleration voltage of 10 kV and with the use of a backscatter detector.® 100 CN, Merck), using a solvent mixture  adjusted to pH 3.2 as mobile phase. The method was validated in terms of system suitability, specificity, precision, repeatability and linearity. The limit of quantification was calculated based on the corresponding ICH guideline (CPMP/ICH/381/95) as 0.08 µg/mL. The quantification calculations were based on an external standard calibration curve (R2 > 0.99) covering a concentration range from 0.21 µg/mL to 104.8 µg/mL. All values used were within the calibrated range. All solvents used were chromatographic grade and supplied by Honeywell Riedel-de Haën .The quantification of drug content was carried out using high-performance liquid chromatography . The analytical procedure was based on a cyanopropyl-substituted stationary phase (LiChrospherw/w active ingredient) using the Picomix high-shear mixer module with two mixing steps at 500 rpm and one sieving step (mesh size: 250 µm) in between. All mixing steps were conducted at a monitored RH of 45% ± 15% and room temperature (20 °C to 25 °C). Every mixture comprised a batch size of 30 g and was tested for homogeneity by analysing 10 randomly picked samples via high performance liquid chromatography. A blend was considered homogeneous at a relative standard deviation below 5% and a recovery of 90–110%.All adhesive mixtures were prepared  with the fast-screening impactor . The FSI allows rapid determination of fine particle dose < 5 µm (FPD) and fine particle fraction (FPF). All experiments were operated at a flow rate corresponding to a 4 kPa pressure drop over the inhaler (78.3 L/min). All results are shown as an average of five measurements with five doses per measurement. All FSI experiments took place in a climate chamber with constant environmental conditions of 21 °C and 45% RH. High performance liquid chromatography  was used for drug quantification.The aerodynamic assessment was carried out using the Novolizerw/w). All results are displayed as the average of three measurements at a monitored temperature of 20 °C (±5 °C) and 45% (±15%) RH.For the adhesion strength screening, an e200LS air-jet sieve  was used. A specified mesh-sized analytical sieve was inserted (20 µm for adhesion strength screening). For every repetition, 5 g of sample was placed on the sieve, covered with a lid and then dispersed via a rotating pressurised air nozzle. A negative pressure of 4 kPa was created by a pump, sucking particles below 20 µm through the sieve. The process was stopped at 6 s, 30 s, 1 min, 2 min, 5 min and 10 min for sampling. Per sampling time, 10 randomised powder samples were picked from above the sieve. From each of the resulting 60 samples, a specific mass of 7 mg (±0.5 mg) was weighed into an Eppendorf tube, dissolved in 2 mL of solvent (aq. bidest.) and analysed in the high-performance liquid chromatography. The resulting drug content was put in in relation to the nominal drug content of the adhesive mixture . All samples were dissolved using diluted nitric acid in combination with sonication (20 min) and shaking (15 min). After centrifugation , the samples were diluted and measured using a flame atomisation (air–acetylene flame) AAS system . The calculation of the content was based on a six-point calibration curve from zero up to 1 ppm magnesium concentration.All statistical calculations were carried out with Microsoft Excel 2016 .The in-depth investigation of two established dry particle coating processes was conducted with a broad spectrum of physico-chemical analysis tools. Since those particle coating processes are used for formulation optimisation attempts ,11 in thThe energy input in both preparation procedures was determined by recording the performance data of the instrument for both conducted processes using the same sample mass. The energy input into the powder was calculated to be 1234 J for the AMS and 1318 J for the HSM process. This corresponds to approximately 6% higher energy input in the HSM coating attempt. Even though both processes show no major differences in energy input, both methods introduce considerable amounts of mechanical energy into the sample. As a comparison: preparing an interactive blend as described introduces approximately 250 J of mechanical energy. Since the mechanical stress during dry particle coating could already cause fundamental changes in the particle properties, such as amorphisation or fragmentation, both processes were conducted with and without additives. This allows the evaluation of whether changes in powder behaviour can be attributed to processing or to the additive itself.When applying mechanical stress to a powder sample, an expectable change is in particle size distribution. To make sure no particle fragmentation occurs, particle size distributions were measured via laser diffraction. The results are displayed in The results demonstrate that even though considerable mechanical stress was applied during both processes, the particle size distribution is unchanged, which indicates that particles were not fragmented significantly when processed without the additive.Since particle size distributions have a huge impact on the performance as a carrier platform in dry powder inhalation formulations , not decOtherwise, one would observe increasing surface areas after processing due to decreased particle sizes.Another alteration, which could have been introduced even without particle fragmentation, is the formation of crystal defects, leading to partial amorphisation. Since the starting material, InhaLac 230, is a highly crystalline lactose, even small amounts of process-induced amorphous content are detectable. As analytical tools, two different methods were used: differential scanning calorimetry (DSC) in combination with thermogravimetric analysis (TGA) and dynamic vapour sorption (DVS). Both techniques were applied to the additive-free samples. Thus, solely the process-induced changes in solid state properties can be tracked. All DSC graphs  show essDVS was chosen as an orthogonal method to verify the conclusion made based on the DSC experiments. For comparability, only additive-free, processed lactose samples were investigated. A slight difference between processed and non-processed samples can be seen. The processed samples reproducibly gained more mass than the non-processed, which can be explained by little differences in surface appearance or the creation of non-recrystallisable defects, which is substantiated by no identifiable differences between both cycles. This combination of methods showed that in both used dry particle coating methods, no introduction of major changes in the solid state of the particles had occurred. This is important not only for stability issues but also for tracing back new particle properties after the process with the additive—not to the process itself, but to the additive.p-value > 0.05 when comparing d10, d50 and d90 values). Following the investigation of the addition of mechanical stress, the determination of particle specifications, namely PSD  and BET 2/g while the AMS sample only increased to 0.4 m2/g. A general increase in surface can be substantiated by the SEM images (A and B) in This observation was supported with the specific surface area results. Both processed samples showed a difference between the BET-specific surface area depending on if processed with or without the additive. The specific surface area of the HSM sample increased to 0.8 mw/w) MgSt was added in both coating strategies. The measured MgSt content of 1.31% and 1.23% before air-jet sieving indicates a loss of more than 30% due to processing. After air-jet sieving, the additive content of the HSM sample decreased by 18.0%, while the content of the AMS sample decreased by over 60% . Comparing the surface energy distribution of the starting material with the material after processing without the additive, the dispersive part of the surface energy showed no significant changes. The acid-base (polar) part, however, decreased after processing. Considering the standard deviations, there was no significant change . At low surface coverages of the probe gases, the total surface energy decreased by up to 15.3% (HSM). Comparing both coating processes, it can be observed that coating in a high-shear mixer led to lower surface energies at low surface coverages  as well as a significant difference between both processes . Such decreases in surface energy can be linked to the decreased tendency of the surface to interact with surroundings  [Processing with the model additive MgSt caused significant changes in surface area and surface energy  .p-value < 0.001), but the difference between both processed carriers was not . Decreases in interaction strength can therefore lead to significant changes in aerodynamic performance, as attachment and detachment of micronised drug particles will be altered. The impact of processing with the additive on resulting fine particle fractions (FPF) of the respective interactive blends assessed in the FSI is displayed in 2 > 0.95). The mean residual drug concentration (starting concentration defined as 100%) after 10 min of dispersing and removing particles below 20 µm is defined as carrier residue (CR). The slope of the linearised function describes the speed of decrease (SOD) of drug content in the dispersed system. In a real setting, the drug has to be detached in a split second [To gain further insight into the adhesion of drug particles on either non-processed or processed carriers, an adhesion force screening of the blends was carried out. The air-jet sieve (AJS) allows the simulation of a situation that is exemplary of a blend that is intended to be dispersed in the airstream. With a mesh size of 20 µm and a negative pressure of 4 kPa, mainly drug particles are sucked through the sieve and therefore eliminated from the dispersed (using pressurised air) system. Sampling at defined times and quantification of residual API in the blend allow conclusions of adhesion strength; the higher the adhesion strength, the less API will detach from the lactose particles. All prepared interactive blends were assessed with this method. The gathered data  were dest second  during ip-values < 0.001; SOD: p-values < 0.05). This was confirmed by the results of the SEA analysis. Another indication for reduced adhesion between the carrier and drug was the share of drug deposited in the pre-separator of the FSI. It also represents an approximation of the amount of drug, which did not detach and, hence, impacted the lactose carrier in the pre-separator. The shares are shown in p-value < 0.001). All blends fulfilled the mentioned requirements to be considered homogenous before the testing, so the data point at zero seconds is 100% ± 10% . It can be observed that the HSM blend showed less adhesion forces between carrier and API, leading to higher detachment and drug content decreases in the dispersed system. The resulting CR and SOD values of all investigated blends differ in statistical significance  lead to substantial alterations in particle behaviour. The investigation of coating attempts with and without coating materials allowed conclusions on the origin of the introduced changes. Using additive-free processes, the alterations in particle appearance, aerodynamic performance or adhesive properties were traced back to the additive, not the process. Even if AMS and HSM coatings both led to significant increases in FPF, the HSM coating showed superiority in terms of carrier residues and speed of detachment (of drug content). In addition, the SEM images before and after air-jet sieving showed a more complete coating for the HSM process. This was substantiated by the determination of firmly bound additive content. Even though SE decrease and therefore the decrease in the work of adhesion were superior for the HSM surface, the aerodynamic performance showed no significant difference between both options. This supports the theory of energetic levelling of higher energy binding sites on the DPI carrier surface. Although the AMS coating showed inferior coating efficacy, the high-energy sites on the lactose surface decreased for both coating strategies, which therefore substantiates the positive effect of using dry particle coatings in DPI formulation development. Furthermore, this work supports the hypothesis that adhesion strength between drug and carrier may be crucial but not solely decisive for the aerodynamic performance of the respective interactive blend. In conclusion, the HSM strategy should be preferred in a comparable experimental setup due to its reported benefits combined with less processing time.


Cellulose polymer insulation material is widely used in oil immersed bushing. Moisture is one of the important reasons for the deterioration of cellulose polymer insulation, which seriously threatens the safe and stable operation of bushing. It is significant to study the polarization and depolarization behavior of oil-immersed cellulose polymer insulation with different moisture condition under higher voltage. Based on polarization/depolarization current method and charge difference method, the polarization/depolarization current, interfacial polarization current and electrical conductivity of cellulose polymer under different DC voltages and humidity were obtained. Based on molecular-dynamics simulation, the effect of moisture on cellulose polymer insulation was analyzed. The results show that the polarization and depolarization currents become larger with the increase in DC voltage and moisture. The higher applied voltage will accelerate the charge carrier motion. The ionization of water molecules will produce more charge carriers. Thus, high DC voltage and moisture content will increase the interface polarization current. Increased moisture content results in more charge carriers ionized by water molecules. In addition, the invasion of moisture will reduce the band width of cellulose polymer and enhance its electrostatic potential, so as to improve its overall electrical conductivity. This paper provides a reference for analyzing the polarization characteristics of charge carriers in cellulose polymer insulation. The oil-immersed transformer is the core equipment of power transmission in the power grid, wherein safety and stability are significantly important to energy security and social stability. According to statistics, fault of bushing is one of the main causes for transformer faults, and the cellulose polymer paper, as the main insulation material of bushing, is the main factor contributing to the fault of bushing after moisture invaded ,2,3. To To date, some scholars have studied the effect of moisture on cellulose polymer paper. Wenyu Ye, et al. found that the structure of liquid-solid interface is determined by the interaction between insulating oil and cellulose polymer paper, which is based on the Van der Waals effect, and water molecules will gather at the interface because of the interaction of the liquid-solid interface at certain electric field value . GuanweiIn order not to damage the sealing performance of bushing, nondestructive testing methods based on dielectric relaxation theory have been widely used by scholars, among which polarization and depolarization current (PDC) method and frequency domain spectroscopy (FDS) method are the most popularly used ,8,9. BotAlthough some scholars have studied the correlation between the dielectric characteristic parameters of bushing insulating paper in time domain and moisture, most of the research is based on low excitation voltage, resulting in low signal-to-noise ratio, which is easy to be interfered by environmental noise. Additionally, and yet worse, the cellulose paper in the bushing works at a higher voltage, which means the traditional low-voltage measurement results and rules are not applicable to a higher excitation voltage. In addition, there is little research on analyzing the charge accumulation at the interface of oil-paper insulation in bushing based on PDC measurement results. Therefore, it is necessary to analyze the time-domain relaxation behavior of the bushing insulating paper with various moisture contents at high voltage.This paper studies the time domain relaxation behavior of charge carriers for cellu-lose polymer insulation used in oil immersed bushing under higher voltage. Firstly, the polarization and depolarization currents of cellulose polymer insulation with different moisture conditions are obtained. Then, the influence of moisture and applied voltage on the characteristics of interface polarization behavior is studied; the motion of the interface charge carriers during the process of polarization and depolarization and the relationship between the steady state time of electrical conductivity are analyzed. Finally, based on molecular dynamics simulation, the effect of moisture on the insulation properties of cel-lulose polymers is analyzed.Cellulose is a natural polymer compound, its chemical structure is a linear polymer composed of many β-D-glucopyranosyl groups connected to each other by 1, 4-β glycoside bonds. Cellulose polymer insulation is mainly composed of cellulose macromolecular chains composed of cellulose monomers, as shown in In this paper, an oil immersed bushing with cellulose polymer insulation, where the maximum voltage is 40.5 kV, is tested. The structure diagram of the bushing is shown in PDC tests in different DC voltages are carried out; the schematic diagram and physical diagram of PDC test is shown in By applying and removing DC voltages to the insulating medium, the dielectric response characteristics in time domain from the polarization and depolarization current can be extracted based on a PDC test. The schematic diagram is shown as For the insulating medium, the polarization process mainly includes dipole polarization and interface polarization. Due to the difference of dielectric constant and electrical conductivity of composite insulating mediums, the free charge will accumulate at the interface and will not dissipate easily, resulting in the asymmetry of polarization process and depolarization process. Polarization current consists of dipole relaxation current Electrical conductivity can reflect the degree of moisture content of insulating materials. Charge difference analysis method (CDA) can effectively calculate the electrical conductivity of insulating materials by analyzing the change characteristics of the charge amount difference in charge and discharged process ,16,17,18Thus the charge amount difference at any time is as Equation (5), and the difference between polarization current and depolarization current at any time is as Equation (6):k of charge amount difference function with time is approximately constant, as shown in Equation (7).The charge amount difference is numerically the integral of the conductance current over time. As the conductance current changes little with time, the slope From Equations (6) and (7), rσ of the composite insulating medium can be obtained from the conductance current, as shown in Equation (10).When the time of polarization and depolarization process is equal and long enough, the current difference at the final moment is equal to the conductance current, as shown in Equation (9). The electrical conductivity X-Y model when the electrical conductivity of the whole insulating material is known [The composite insulation structure in the bushing is composed of aluminum foil and oil immersed cellulose polymer wrapped closely, as shown in is known .X model, the electrical conductivity of the composite insulating structure is shown as Equation (11), where X is the thickness ratio.As for simplified X equals to 1, the electrical conductivity of cellulose polymer insulation can be simplified, and the electrical conductivity of the cellulose polymer is as shown in Equation (12).Since the electrical conductivity of aluminum foil is much greater than that of cellulose polymer and the thickness of aluminum foil is negligible compared with that of cellulose polymer insulation, which means In order to study the effect of moisture on the insulation properties of cellulose polymer, the models of cellulose without moisture and after moisture were constructed by using Materials Studio software .Three cellulose chains with a degree of polymerization of 10 were used as the cellulose polymer insulation model without moisture, while 3.5% water molecules were added into three cellulose chains with a degree of polymerization of 10 as the cellulose polymer insulation model with moisture. The two cellulose polymer insulation models are shown in First, 10,000 steps of geometric optimization were carried out for the two models by using the Steepest descent method. Then, the two models were annealed to make the model reach the most realistic condition; the annealing temperature was 300–500 K. Under Compass force field, constant-pressure and constant-temperature ensemble (NPT ensemble), with a constant number of molecules, pressure, and temperature, was used to balance each model and to make the model more reasonable with 500 ps. Based on the density functional theory (DFT), the calculations for two cellulose models were analyzed by DMol3 Tool in Materials Studio. The geometry optimization, molecule orbitals and electrostatic potential were calculated by employing the PBE function under the generalized gradient approximation (GGA) exchange-correlation term. The double numerical plus polarization (DNP) basis set was applied for setting the parameters of C, H, O atoms in this computational work. The all-electron method was adopted for core electron calculation.The polarization and depolarization current of bushings with different moisture conditions and applied voltages are shown in This phenomenon can be explained by the differing hydrophilic qualities of oil and cellulose polymer. Since the hydrophilic quality of cellulose polymer is much higher than that of insulation oil, when water is present, most water molecules in the insulation oil will migrate to the cellulose polymer with the invasion of moisture. As polar molecules, the more moisture infiltrates into the cellulose polymer insulation, the more polar molecules are involved in the polarization reaction, leading to a larger polarization intensity difference. The moisture content, on one hand, can increase the electrical conductivity of the insulation system, whereas, on the other hand, it can enhance the response speed of the interface polarization, aggravating the dielectric asymmetry of the oil-immersed cellulose polymer insulation system at the same time. Finally, the insulation resistance and capacitance increase, and the polarization process is aggravated ,23,24. TWhen the applied voltage is lower than 1000 V, the current fluctuates significantly with time. This is because the polarization process of oil-immersed cellulose polymer insulation system inside the bushing cannot be fully stimulated by low DC voltage in such a large size. Therefore, the polarization and depolarization currents of the insulation are small and susceptible to the interference of environmental noise, which has an obvious influence on the accuracy of the test results. When the applied DC voltage increases, the corresponding current becomes larger and the fluctuation of that decreases. The development trend of polarization and depolarization current is not affected by applied DC voltage, which means the applied DC voltage has little influence on the general trend of the dielectric polarization process. Thus, a high applied DC voltage test can not only improve the signal-to-noise ratio, but also reflect the polarization process of bushing more clearly, resulting in a more accurate and effective test result.The interface polarization current of the three bushings can be calculated by Equations (1)–(3), as shown in The insulation system of the bushing is composed of aluminum foil and cellulose polymer, and the dielectric constants of both are different. When applying DC voltage in the insulation system, the interface polarization process occurs, and an interface polarization current is generated. When the voltage increases, the electric field becomes larger, accelerating the motion of the charge carriers. When the moisture infiltrates into the insulation medium, the water molecules are ionized to produce more charge carriers under the effect of electric field. This explains the characteristic of interface polarization current under the influence of moisture content and applied DC voltage. The migration process of charge carriers at the cellulose polymer interface is shown in in The charge difference spectrum of normal bushing, dampened oil bushing and dampened cellulose polymer paper bushing under different voltages are shown in The slopes of the polarization/depolarization charge amount difference at 200 V, 1000 V and 4000 V are shown in σ. The geometric capacitance of the insulation in the bushing is 228 pF, thus the real electrical conductivity of normal, bushings with dampened oil and dampened cellulose polymer insulation are 7.9748 × 10−13 S/m, 9.7884 × 10−13 S/m and 1.1672 × 10−12 S/m, respectively. The results indicate that electrical conductivity increases when the moisture content in the insulation material is higher, leading to the deterioration of the insulation performance.The electrical conductivity change behavior of cellulose polymer insulation with different moisture conditions is shown in For normal bushing, electrical conductivity is stabilized the fastest because the interface polarization current dissipates faster with time, resulting in the electrical conductivity current taking less time to stabilize. However, the polarization process can be influenced by the invasion of moisture when the insulation material is dampened, resulting in a longer time that the interface polarization current dissipates and the higher value of the interface polarization current. Additionally, moisture content can also lead to a longer time that the conductance current takes to be stable and can decrease the initial value of polarization and depolarization charge amount difference. The polarization current increases significantly while the depolarization current is less affected under the influence of moisture content, leading to the increase in slope of polarization/depolarization charge amount difference. Because the electrical conductivity is linear with the slope of the polarization/depolarization charge amount difference curve, the electrical conductivity of the bushing with dampened oil and dampened cellulose polymer in the stable state is larger than that of normal bushing. These reasons explain that normal bushing has a larger electrical conductivity than that of bushing with dampened oil and cellulose polymer insulation, and that the electrical conductivity of normal bushing takes less time to stabilize.E) of unmoistened cellulose is 5.657 eV, while the band gap width of moistened cellulose is 5.546 eV. The wider the band width, the weaker the electrical conductivity. The energy band width of cellulose is narrowed after the water content of cellulose is increased, so the moistened cellulose polymer insulation electrical conductivity is stronger.The band structure of unmoistened cellulose and moistened cellulose is shown in The electrostatic potential of unmoistened cellulose and moistened cellulose is shown in Due to the existence of a large number of hydroxyl groups in cellulose, these hydroxyl groups can easily form hydrogen bonds with each other. It is precisely because of the existence of hydrogen bonds that cellulose has strong intermolecular and intramolecular interaction forces, and the ability of cellulose to resist external damage is also closely related to the concentration of hydrogen bonds. The molecular simulation results show that the presence of water destroys the intramolecular and intermolecular hydrogen bonds in the cellulose chain, and forms a new hydrogen bond interaction with the oxygen atom on the cellulose hydroxyl group. Water mainly acts on the hydroxyl and glycoside bonds of cellulose and destroys their stability. Therefore, the motion of charge carriers in the insulating paper cellulose is more intense under the action of the electric field. This is consistent with the conclusion in  that chaIn conclusion, with the invasion of moisture, the electrical conductivity and polarity of cellulose polymer insulation will increase. Under the excitation of DC electric field, the polarization/depolarization process is more intense, which is specifically reflected in the experiment by the polarization/depolarization current being greater. In addition, the electrostatic potential of cellulose polymer is stronger after moisture invasion, indicating that its electrical conductivity characteristics are better under the action of electric field, that is, the electrical conductivity is greater, which verifies the calculated electrical conductivity of cellulose polymer insulation in different oil-immersed bushings above.The polarization/depolarization current of bushings increases when the applied voltage becomes higher. High applied voltage can decrease the influence of noise. Moisture can aggravate the polarization/depolarization process, leading to higher polarization/depolarization current.When applied voltage is higher, the speed of charge carriers increases, leading to the increase of interface polarization current. Water molecules are ionized under the effect of electric field, producing more charge carriers, thus increasing the interface polarization current as well. With the increase of interface current, the relaxation behavior will be further intensified.The charge amount difference of polarization and depolarization current is linearly aligned with the time, and the slope becomes larger with the increase in moisture, which is more obvious under high applied voltage. Water molecules produce more charge carriers after being ionized and provide more paths for charge movement.With the invasion of moisture, the band width of cellulose polymer insulation becomes narrower, and its electrostatic potential increases, which improves the electrical conductivity of cellulose polymer insulation, and the polarization characteristics under DC electric field are more significant.This paper studies the time domain relaxation behavior of charge carriers for cellulose polymer insulation used in oil-immersed bushing, and the characteristics of dielectric response and motion of charge carriers have been analyzed. The conclusions drawn are as follows:


Bioprinting is increasingly used to create complex tissue constructs for an array of research applications, and there are also increasing efforts to print tissues for transplantation. Bioprinting may also prove valuable in the context of drug screening for personalized medicine for treatment of diseases such as cancer. However, the rapidly expanding bioprinting research field is currently limited by access to bioprinters. To increase the availability of bioprinting technologies we present here an open source extrusion bioprinter based on the E3D motion system and tool changer to enable high-resolution multimaterial bioprinting. As proof of concept, the bioprinter is used to create collagen constructs using freeform reversible embedding of suspended hydrogels (FRESH) methodology, as well as multimaterial constructs composed of distinct sections of laminin and collagen. Data is presented demonstrating that the bioprinted constructs support growth of cells either seeded onto printed constructs or included in the bioink prior to bioprinting. This open source bioprinter is easily adapted for different bioprinting applications, and additional tools can be incorporated to increase the capabilities of the system. Such constructs present opportunities to study cell biology and pathogenic processes in complex, well-defined environments. Bioprinted constructs also hold potential to become widely used model systems and assays for drug screening5, and their viability as transplantable materials for patient care is an area of intense research interest9.Additive manufacturing is an umbrella term for a variety of manufacturing techniques usually based on building three-dimensional (3D) objects in a layer-by-layer fashion. Additive technologies are gaining widespread popularity in a variety of research fields, as well as in industry, as 3D printing enables rapid prototyping and generation of objects with complex geometries from a very wide range and combination of materials. Bioprinting describes the application of additive manufacturing to reproducibly create tissue-like 3D constructs composed of biomolecules and/or biomaterials and cells. As a tissue engineering technology, bioprinting permits cells to be incorporated into printed constructs post-production or during the printing process, and the ultimate goal is often to recapitulate the architecture and function of living tissues and organs10, laser-assisted bioprinting, stereolithography, and inkjet-based bioprinting11. To date extrusion-based bioprinting is one of the most widespread techniques, which has borrowed innovations from the analogous fused filament fabrication (FFF) technology that is extensively used in plastic additive manufacturing. Compared to other bioprinting technologies, extrusion based bioprinting has several advantages such as low cost, a relatively high printing speed, and compatibility with bioinks in a wide range of viscosities. However, extrusion-based bioprinting does suffer from a relatively low spatial resolution, and cell viability can be compromised due to the mechanical stress generated during extrusion of cells through the deposition needle or nozzle12.Developments in the field of bioprinting encompasses many established fields of research such as material science, cell and tissue engineering, regenerative medicine, as well as robotics, automation and biotechnology. This requirement for interdisciplinary collaborations presents a number of challenges to progress in the bioprinting field; however, by increasing the availability of user-friendly solutions, more researchers are likely to adopt the technology and in doing so advance the field as a whole. As with standard additive manufacturing, many different technologies are capable of constructing bioprinted 3D-objects in a layer-by-layer fashion. The most commonly used techniques for the printing of cell-laden bioinks are extrusion-based bioprinting14. However, this strategy employing sacrificial materials typically demands a bioprinting platform with the capacity to perform multimaterial printing. Freeform reversible embedding of suspended hydrogels (FRESH) is an innovative solution that provides a 3D structurally supportive print environment, without the need for multimaterial printer functionality16. During FRESH bioprinting collagen-based bioinks (or other bioinks of interest) are extruded directly into a support bath consisting of gelatin microparticles, and this permits complex 3D constructs to be printed in an essentially suspended state, without the need for printed support structures. The gelatin bath can subsequently be melted away by increasing the temperature, allowing the construct to be retrieved. The FRESH bioprinting strategy has been widely adopted throughout the bioprinting research community17; therefore, designing bioprinting platforms that are compatible with FRESH bioprinting will likely be of great general interest.A challenge that confronts many additive manufacturing techniques, especially those using soft materials such as hydrogels, is the low structural stability of the construct during the printing process, which can negatively impact the geometry and architecture of the intended construct design. Strategies that have been employed to circumvent this limitation include the use of sacrificial support materials. This allows for a construct to be printed in one or more bioinks of choice, while it is simultaneously embedded in a structurally supportive scaffold material printed in parallel. Once the construct is complete and stabilized through post-printing reactions or treatments, the sacrificial material can be removed to release the construct. This technique can also be used to introduce design features such as channels that facilitate the perfusion of printed constructs19, and while they may be limited to the extrusion of a single type of bioink at a time, previous studies demonstrate the benefits of leveraging existing additive manufacturing technologies for bioprinting. In the present study we present an open source extrusion-based bioprinter built around the E3D motion system and tool changer, with the potential to produce constructs using up to four syringe pump tools and bioinks. The bioprinter features a transparent polycarbonate cabinet with an integrated HEPA filter and air intake fan to enable contamination-free bioprinting, and automatic tool offset calibration and bed leveling, making it easy to use multiple syringe pump tools to combine different bioinks in order to create complex bioprinted 3D constructs. Due to the open source nature of the components used, the system is highly adaptable to allow for incorporation of new tools and functionalities. FRESH bioprinting as well as multimaterial printing with collagen and laminin was performed to demonstrate the capacity of the system.Efforts to bring bioprinters to a wider audience have included the repurposing of affordable FFF-printers for bioprinting applications20. E3D provides free access to the systems build files, which facilitated the design process when adapting the existing system for the bioprinting purpose described here21. A polycarbonate box compatible with ethanol-based surface sterilization and fitted with an integrated HEPA filter and air intake fan was constructed to enclose the E3D system to reduce the risk of contamination of bioprinted constructs. The polycarbonate enclosure could easily be adapted to allow for temperature and humidity control should this be required for future bioprinting applications  printing or extrusion through the syringe and 1 week later  into a hydrogel construct, which is removed after printing, can provide perfusion channels, which can increase cell viability and survival in larger constructsink Fig. d. Col-F ink Fig. e. Unexpeink Fig. e.35, the analysis of multi-cell type behaviors36, and is important for future efforts to facilitate and scale up bioprinting of constructs for use in research and drug screening. The open source bioprinter is easily adapted for different bioprinting applications, and the possibility of incorporating additional tools should accelerate the development of novel bioprinting approaches and applications.The open source bioprinter presented here, based on the E3D motion system and tool changer, enables a variety of bioprinting tasks including FRESH bioprinting, multimaterial prints, and the extrusion of cell-laden bioinks. In the presented configuration only two of the four tool positions were used. The remaining tool positions present opportunities for further automation of protocols to reduce user intervention, and to increase reproducibility and throughput. For instance, we are currently developing a grip tool and protocol to manipulate the 3D printed basket in which the FRESH collagen constructs are bioprinted, to allow for automated construct transport from the gelatin support bath to a heated washing station, which melts the gelatin support material. The grip tool can subsequently move the construct through additional washing solutions, effectively automating key steps of the post-processing procedure. The benefits of automating biofabrication protocols have been outlined for the formation of tissue spheroids21, and enclosed in a custom-built polycarbonate cabinet with an integrated a HEPA filter with an air intake fan. The syringe pump extrusion tool  program originally developed by Danal Estesess Fig. . This is.factory file format, which is native to Simplify3D. Further information about software configuration and slicing settings can be found in the The toolpath generation software  was used to generate G-code files for bioprinting of the different constructs. Bioprinting was typically performed at a speed of 10 mm/s, as printing at this speed produced reproducible constructs of both the collagen and laminin bioinks. The printing parameters are available in a πr2h), where r is the inner radius of the Hamilton 0.25 ml syringe (1.15 mm). This yielded a value of 0.39 ± 0.02 μl (mean ± S.D.). To assess the practical lower limits of the resolution of the bioprinter we used a nozzle with a 50 μm cross-sectional diameter to extrude strings of collagen using FRESH bioprinting. The strings were imaged by differential interference contrast using a Zeiss LSM710 confocal microscope (Zeiss), and the average cross-sectional width of the finest collagen strings that we could produce and recover was calculated from multiple measurements along the length of the printed string  was mounted beneath the lead screw and adjusted such that its contact point was in contact with the plunger press. The stepper motor was programmed to take 10 mm, 1 mm, or 0.1 mm steps sizes and for each step the measured displacement distance was recorded from the dial indicator. These measurements were repeated 10 times for each step size, and a linear plot was prepared  according to the instructions provided by the supplier ATCC.The MDA-MB-231 breast cancer cell line was obtained from the American Type Culture Collection (ATCC) and cultured in Dulbecco’s Modified Eagle Medium (DMEM) Glutamax , supplemented with 10% Fetal Bovine Serum , referred to hereafter as culture medium, in a humidified incubator  bioink and LaminInk + (Cellink) laminin bioink were first transferred to a 5 ml plastic syringe with male-male LuerLock. To reduce the presence of bubbles in the bioink, the loaded syringe was centrifuged for 4 min at 1200×16, using LifeInk 240 (Advanced Biomatrix). The FRESH LifeSupport powder (Cellink), from which the gelatin microparticle support bath was prepared, was used as per the manufacturer’s instructions. Following print completion, the tool was left at the tool dock and the build plate lowered. All constructs generated using FRESH bioprinting was made in a custom-designed and easily moveable basket. After a completed print, the basket holding the collagen construct was placed at 37 °C for 1 h to melt the gelatin support material and to thereby release the printed construct. Constructs were washed three times in 1× phosphate buffered saline  and stored in PBS at 4 °C until further use. For fluorescent imaging, collagen constructs were stained for 1 h at 37 °C with 10 μM Col-F  prepared in 1× PBS, and then washed twice (5 min each) with 1× PBS at room temperature. Constructs were imaged by confocal microscopy performed on a Zeiss LSM700  instrument and images were captured using Zen imaging software . For cell seeding, FRESH constructs were first typically stored overnight at 4 °C in 1× PBS supplemented with the antibiotics penicillin and streptomycin . Individual constructs were next moved to separate wells in a µ-slide 8-well coverglass-bottomed chamber (Ibidi) and a cell suspension of 30 × 103 MDA-MB-231 cells diluted in 250 µl culture medium supplemented with 1× PenStrep per well was deposited directly onto the collagen construct or into an adjacent, construct-free wells, and cultured for 20 h under standard cell culture conditions. Cell staining and analysis of viability and cell morphology by microscopy are described below.FRESH bioprinting was performed according to the protocol by Lee et al.38. For cell-laden collagen constructs, the z-plane containing the highest number of cells was selected for analysis. Individual cells were identified as regions of interest (ROI) by applying a threshold to the NucBlue signal. The ImageJ particle analysis function was applied to this thresholded image to include particles within a size range of 15–600 μm2. This range excluded non-specific signals from small debris and very large clusters of cells. However, it included smaller cell clusters that could be delineated as individual cells by applying the automatic watershed function to the thresholded image. This ROI mask of individual cells was then overlaid on the PI and Cell event caspase-3/7 channels and the mean fluorescence was recorded in each ROI for each channel. This data was exported to Excel, and mean intensity per ROI and channel was background adjusted using an average from three ROIs measured in cell-free areas of the collagen construct. Data was statistically analyzed using ordinary one-way ANOVA with Tukey’s multiple comparisons in GraphPad Prism (Prism).To assess cell viability in FRESH bioprinted collagen constructs, cell-seeded constructs were incubated with the NucBlue nuclear stain to detect individual cells , propidium iodide (PI) to identify dead cells , and the Cell event caspase-3/7 stain that reports on the activity of caspase 3 and 7 in apoptotic cells . Staining solutions were diluted in OptiMEM , supplemented with 1× PenStrep. To control for the effectivity of the viability stains, cells were treated for 5 h with staurosporine , a potent protein kinase inhibitor known to induce apoptosis. Fluorescent signals for the respective stains were captured by confocal microscopy with an LSM700 instrument and Zen software (Zeiss). Multiple z-planes were captured for cell-laden constructs, while a single in-focus z-plane was captured for cells attached directly to the glass in construct-free wells. These experiments were conducted in duplicate on three independent occasions. Image analysis was conducted in the Fiji version of ImageJTo visualize cells adhering to FRESH bioprinted collagen constructs the cells were labelled overnight with SiR-actin , which permits fluorescence imaging of the actin cytoskeleton. Samples were washed twice in OptiMEM cell culture medium, which was then exchanged for OptiMEM containing the NucBlue nuclear stain. The cells were imaged as described above by confocal microscopy.FRESH bioprinting of constructs for one week culture was performed as described above, however to reduce unnecessary handling, constructs were printed directly on a Labtek 8 well chamber coverslip. Onto each construct 24,000 cells/well were seeded in DMEM . Half the media was exchanged every 1–2 days. Live/dead staining was performed on day 1 after cell seeding, and in separate constructs 1 week after cell seeding. Briefly, cells were stained with fluorescein diacetate (Sigma) 8 µg/ml and PI, diluted 1:1000 in OptiMEM, for 10 min. Then constructs were washed once with OptiMEM. Images were taken using an LSM 700 confocal microscope (Zeiss) and a 10× objective. For each construct two images were taken of a z-plane with high cell density and used for analysis in ImageJ. In ImageJ both channels were thresholded manually and the automatic watershed function applied. Subsequently, the particle analysis tool was used to count the number of live or dead cells. Using Excel, the percentage of viable cells was calculated for each image. To determine statistically significant differences between groups, data were imported to GraphPad Prism and analyzed by Student’s t-test. Experiments were performed in three independent repetitions with two timepoints and four to five constructs per timepoint and repetition.6 cells/ml was mixed with 1 ml Laminink + Bioink (Cellink) by passing back and forth between two 1 ml syringes. For control, the cell-laden bioink was directly deposited into wells from the plastic syringe without extrusion through a thin needle or nozzle. The remaining ink was loaded into a 250 µl Hamilton glass syringe and bioprinting performed with an 18 G needle. For crosslinking of all constructs, including non-printed controls, the recommended Crosslinking Agent (Cellink) was applied for 1 min. Subsequently, the constructs were washed once in warm (37 °C) DMEM Glutamax, supplemented with 10% FBS and 1× PenStrep, and then either cultured for one week in 100 µl of media, with half the media being exchanged daily, in a cell incubator  or directly used for live/dead staining, described above. Experiments were conducted in three independent repetitions with two timepoints and a total number of three to five printed constructs and non-printed control hydrogels for each group and repetition. For each construct two images were taken of a z-plane with high cell density and used for particle analysis in ImageJ, and statistical analysis in GraphPad Prism (Prism), as described above.Cell-laden laminin bioink was prepared as follows; 100 µl of cell suspension containing 11 × 102, to induce gelation of collagen and laminin, respectively.Multimaterial constructs were bioprinted using acidified collagen (Advanced Biomatrix) and Laminink + (Cellink) containing cells as described above. Printing was done directly onto a glass slide, followed by incubation in 50 mM HEPES (pH 7.4) containing 50 mM CaClSupplementary Information 1.Supplementary Information 2.Supplementary Information 3.Supplementary Information 4.