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The paper provides a demonstration of how UV/VIS imaging can be employed to evaluate the crushing strength, friability, disintegration time and dissolution profile of tablets comprised of solely white components. The samples were produced using different levels of compression force and API content of anhydrous caffeine. Images were acquired from both sides of the samples using UV illumination for the API content prediction, while the other parameters were assessed using VIS illumination. Based on the color histograms of the UV images, API content was predicted with 5.6 % relative error. Textural analysis of the VIS images yielded crushing strength predictions under 10 % relative error. Regarding friability, three groups were established according to the weight loss of the samples. Likewise, the evaluation of disintegration time led to the identification of three groups: <10 s, 11-35 s, and over 36 s. Successful classification of the samples was achieved with machine learning algorithms. Finally, immediate release dissolution profiles were accurately predicted under 5 % of RMSE with an artificial neural network. The 50 ms exposition time during image acquisition and the resulting outcomes underscore the practicality of machine vision for real-time quality control in solid dosage forms, regardless of the color of the API., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier B.V. All rights reserved.)

A unique compound (compound 1 ) with structural features including an unprecedented tridentate-bridging coordination mode of permanganate ions and an eight-coordinated (rhombohedral) κ 1 -chlorido and tridentate permanganato ligand in a potassium complex containing coordination polymer (Co III (NH 3 ) 6 ] n [(K(κ 1 -Cl) 2 (μ 2,2',2″ -(κ 3 -O,O',O″-MnO 4 ) 2 ) n ∞ ) with isolated regular octahedral hexamminecobalt(III) cation was synthesized with a yield of >90%. The structure was found to be stabilized by mono and bifurcated N-H∙∙∙Cl and N-H∙∙∙O (bridging and non-bridging) hydrogen bonds. Detailed spectroscopic (IR, far-IR, and Raman) studies and correlation analysis were performed to assign all vibrational modes. The existence of a resonance Raman effect of compound 1 was also observed. The thermal decomposition products at 500 °C were found to be tetragonal nano-CoMn 2 O 4 spinel with 19-25 nm crystallite size and KCl. The decomposition intermediates formed in toluene at 110 °C showed the presence of a potassium- and chloride-containing intermediates combined into KCl during aqueous leaching, together with the formation of cobalt(II) nitrate hexahydrate. This means that the Co III -Co II redox reaction and the complete decomposition of the permanganate ions occurred in the first decomposition step, with a partial oxidation of ammonia into nitrate ions.

Due to the continuously increasing Cost of Goods Sold, the pharmaceutical industry has faced several challenges, and the Right First-Time principle with data-driven decision-making has become more pressing to sustain competitiveness. Thus, in this work, three different types of artificial neural network (ANN) models were developed, compared, and interpreted by analyzing an open-access dataset from a real pharmaceutical tableting production process. First, the multilayer perceptron (MLP) model was used to describe the total waste based on 20 raw material properties and 25 statistical descriptors of the time series data collected throughout the tableting (e.g., tableting speed and compression force). Then using 10 process time series data in addition to the raw material properties, the cumulative waste, during manufacturing was also predicted by long short-term memory (LSTM) and bidirectional LSTM (biLSTM) recurrent neural networks (RNN). The LSTM network was used to forecast the waste production profile to allow preventive actions. The results showed that RNNs were able to predict the waste trajectory, the best model resulting in 1096 and 2174 tablets training and testing root mean squared errors, respectively. For a better understanding of the process, and the models and to help the decision-support systems and control strategies, interpretation methods were implemented for all ANNs, which increased the process understanding by identifying the most influential material attributes and process parameters. The presented methodology is applicable to various critical quality attributes in several fields of pharmaceutics and therefore is a useful tool for realizing the Pharma 4.0 concept., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier B.V. All rights reserved.)

Continuous manufacturing is gaining increasing interest in the pharmaceutical industry, also requiring real-time and non-destructive quality monitoring. Multiple studies have already addressed the possibility of surrogate in vitro dissolution testing, but the utilization has rarely been demonstrated in real-time. Therefore, in this work, the in-line applicability of an artificial intelligence-based dissolution surrogate model is developed the first time. NIR spectroscopy-based partial least squares regression and artificial neural networks were developed and tested in-line and at-line to assess the blend uniformity and dissolution of encapsulated acetylsalicylic acid (ASA) - microcrystalline cellulose (MCC) powder blends in a continuous blending process. The studied blend is related to a previously published end-to-end manufacturing line, where the varying size of the ASA crystals obtained from a continuous crystallization significantly affected the dissolution of the final product. The in-line monitoring was suitable for detecting the variations in the ASA content and dissolution caused by the feeding of ASA with different particle sizes, and the at-line predictions agreed well with the measured validation dissolution curves (f 2  = 80.5). The results were further validated using machine vision-based particle size analysis. Consequently, this work could contribute to the advancement of RTRT in continuous end-to-end processes., (Copyright © 2024 The Author(s). Published by Elsevier B.V. All rights reserved.)

Both biphasic dissolution and simultaneous dissolution-permeation (D-P) systems have great potential to improve the in vitro-in vivo correlation compared to simple dissolution assays, but the assay conditions, and the evaluation methods still need to be refined in order to effectively use these apparatuses in drug development. Therefore, this comprehensive study aimed to compare the predictive accuracy of small-volume (16-20 mL) D-P system and small-volume (40-80 mL) biphasic dissolution apparatus in bioequivalence prediction of five aripiprazole (ARP) containing marketed drug products. Assay conditions, specifically dose dependence were studied to overcome the limitations of both small-scale systems. In case of biphasic dissolution the in vivo maximum plasma concentration (C max ) prediction greatly improved with the dose reduction of ARP, while in case of the D-P setup the use of whole tablet gave just as accurate prediction as the scaled dose. With the dose reduction strategy both equipment was able to reach 100 % accuracy in bioequivalence prediction for C max ratio. In case of the in vivo area under the curve (AUC) prediction the predictive accuracy for the AUC ratio was not dependent on the dose, and both apparatus had a 100 % accuracy predicting bioequivalence based on AUC results. This paper presents for the first time that not only selected parameters of flux assays (like permeability, initial flux, AUC value) were used as an input parameter of a mechanistic model (gastrointestinal unified theory) to predict absorption rate but the whole in vitro flux profile was used. All fraction absorbed values estimated by Predictor Software fell within the ±15 % acceptance range during the comparison with the in vivo data., Competing Interests: Declaration of competing interest The authors declare that they have no conflict of interest., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

This paper presents a novel high-resolution and rapid (50 ms) UV imaging system, which was used for at-line, non-destructive API content determination of tablets. For the experiments, amlodipine and valsartan were selected as two colourless APIs with different UV induced fluorescent properties according to the measured solid fluorescent spectra. Images were captured with a LED-based UV illumination (385-395 nm) of tablets containing amlodipine or valsartan and common tableting excipients. Blue or green colour components from the RGB colour space were extracted from the images and used as an input dataset to execute API content prediction with artificial neural networks. The traditional destructive, solution-based transmission UV measurement was applied as reference method. After the optimization of the number of hidden layer neurons it was found that the relative error of the content prediction was 4.41 % and 3.98 % in the case of amlodipine and valsartan containing tablets respectively. The results open the possibility to use the proposed UV imaging-based system as a rapid, in-line tool for 100 % API content screening in order to greatly improve pharmaceutical quality control and process understanding., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier B.V. All rights reserved.)

Machine vision systems have emerged for quality assessment of solid dosage forms in the pharmaceutical industry. These can offer a versatile tool for continuous manufacturing while supporting the framework of process analytical technology, quality-by-design, and real-time release testing. The aim of this work is to develop a digital UV/VIS imaging-based system for predicting the in vitro dissolution of meloxicam-containing tablets. The alteration of the dissolution profiles of the samples required different levels of the critical process parameters, including compression force, particle size and content of the API. These process parameters were predicted non-destructively by multivariate analysis of UV/VIS images taken from the tablets. The dissolution profile prediction was also executed using solely the image data and applying artificial neural networks. The prediction error (RMSE) of the dissolution profile points was less than 5%. The alteration of the API content directly affected the maximum concentrations observed at the end of the dissolution tests. This parameter was predicted with a relative error of less than 10% by PLS models that are based on the color components of UV and VIS images. In conclusion, this paper presents a modern, non-destructive PAT solution for real-time testing of the dissolution of tablets., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier B.V. All rights reserved.)

Surface powder sticking in pharmaceutical mixing vessels poses a risk to the uniformity and quality of drug formulations. This study explores methods for evaluating the amount of pharmaceutical powder mixtures adhering to the metallic surfaces. Binary powder blends consisting of amlodipine and microcrystalline cellulose (MCC) were used to investigate the effect of the mixing order on the adherence to the vessel wall. Elevated API concentrations were measured on the wall and within the dislodged material from the surface, regardless of the mixing order of the components. UV imaging was used to determine the particle size and the distribution of the API on the metallic surface. The results were compared to chemical maps obtained by Raman chemical imaging. The combination of UV and VIS imaging enabled the rapid acquisition of chemical maps, covering a substantially large area representative of the analysed sample. UV imaging was also applied in tablet inspection to detect tablets that fail to meet the content uniformity criteria. The results present powder adherence as a possible source of poor content uniformity, highlighting the need for 100% inspection of pharmaceutical products to ensure product quality and safety., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

Cell culture media are essential for large-scale recombinant protein production using mammalian cell cultures. The composition and quality of media significantly impact cell growth and product formation. Analyzing media poses challenges due to complex compositions and undisclosed exact compositions. Traditional methods like NMR and chromatography offer sensitivity but require time-consuming sample preparation and lack spatial information. Raman chemical mapping characterizes solids, but its use in cell culture media analysis is limited so far. We present a chemometric evaluation for Raman maps to qualify and quantify media components, evaluate powder homogeneity, and perform lot-to-lot comparisons. Three lots of a marketed cell culture media powder were measured with Raman mapping technique. Chemometrics techniques have outlined a strategy to extract information from complex data. First, a spectral library has been structured. In addition to the 23 spectra for presumed ingredients, we obtained another 9 pure components with Multivariate Curve Resolution-Alternating Least Squares (MCR-ALS). Then the Spectral Angle Mapper-Orthogonal Projection (SAM-OP) algorithm revealed whether references actually occur in the mapped media powders. Finally, a quantification was provided by Classical Least Squares (CLS) modelling. Quantities of 18 significant amino acids mostly correlated with the reference method. The proposed method can be generally applied even for such complicated samples. Leveraging Raman mapping and innovative chemometric methods enhance recombinant protein production by improving the understanding of the spatial distribution and composition of cell culture media in mammalian cell cultivations., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier B.V. All rights reserved.)

Exact p-value (XPV)-based methods for dot product-like score functions-such as the XCorr score implemented in Tide, SEQUEST, Comet or shared peak count-based scoring in MSGF+ and ASPV-provide a fairly good calibration for peptide-spectrum-match (PSM) scoring in database searching-based MS/MS spectrum data identification. Unfortunately, standard XPV methods, in practice, cannot handle high-resolution fragmentation data produced by state-of-the-art mass spectrometers because having smaller bins increases the number of fragment matches that are assigned to incorrect bins and scored improperly. In this article, we present an extension of the XPV method, called the high-resolution exact p-value (HR-XPV) method, which can be used to calibrate PSM scores of high-resolution MS/MS spectra obtained with dot product-like scoring such as the XCorr. The HR-XPV carries remainder masses throughout the fragmentation, allowing them to greatly increase the number of fragments that are properly assigned to the correct bin and, thus, taking advantage of high-resolution data. Using four mass spectrometry data sets, our experimental results demonstrate that HR-XPV produces well-calibrated scores, which in turn results in more trusted spectrum annotations at any false discovery rate level., (© 2023 Wiley-VCH GmbH.)

Sustainable battery concepts are of great importance for the energy storage demands of the future. Organic batteries based on redox-active polymers are one class of promising storage systems to meet these demands, in particular when combined with environmentally friendly and safe electrolytes. Deep Eutectic Solvents (DESs) represent a class of electrolytes that can be produced from sustainable sources and exhibit in most cases no or only a small environmental impact. Because of their non-flammability, DESs are safe, while providing an electrochemical stability window almost comparable to established battery electrolytes and much broader than typical aqueous electrolytes. Here, we report the first all-organic battery cell based on a DES electrolyte, which in this case is composed of sodium bis(trifluoromethanesulfonyl)imide (NaTFSI) and N-methylacetamide (NMA) alongside the electrode active materials poly(2,2,6,6-tetramethylpiperidin-1-yl-oxyl methacrylate) (PTMA) and crosslinked poly(vinylbenzylviologen) (X-PVBV 2+ ). The resulting cell shows two voltage plateaus at 1.07 V and 1.58 V and achieves Coulombic efficiencies of 98 %. Surprisingly, the X-PVBV/X-PVBV + redox couple turned out to be much more stable in NaTFSI : NMA 1 : 6 than the X-PVBV + /X-PVBV 2+ couple, leading to asymmetric capacity fading during cycling tests., (© 2023 The Authors. ChemSusChem published by Wiley-VCH GmbH.)

Postpartum dysgalactia syndrome (PDS) is a condition affecting periparturient sows, characterized by a reduction in milk and colostrum synthesis shortly after farrowing. Insufficient milk production results in substantial economic losses due to increased piglet morbidity/mortality and premature sow culling. Since PDS develops within a few days following farrowing, the study objectives were to determine if periparturient immune cell profiles and circulating biomarkers differ in sows affected by PDS. We hypothesized differences in immune cells, circulating analytes, and inflammatory markers would exist at farrowing in sows that subsequently developed PDS compared to healthy herd-mates. Thirty-six sows with PDS symptoms were matched by parity and day of lactation with 36 healthy control (CON) sows. Diagnosis of PDS (timepoint 2) occurred on average 9.25 ± 2.67 d after farrowing. Blood samples and litter weights were collected at farrowing (timepoint 1) and at the onset of clinical PDS (timepoint 2). Piglets from PDS sows had lower average daily gain and higher mortality than piglets from CON (P < 0.01). Aspartate aminotransferase was increased (20%; P ≤ 0.06) in PDS sows compared to CON at both timepoints. Additionally, blood urea nitrogen was increased in PDS sows at timepoint 1 and timepoint 2 (13%; P = 0.08 and 16%; P = 0.01, respectively). At timepoint 2, total protein, globulin, magnesium, and cholesterol were increased (P ≤ 0.03) while γ-glutamyl transferase and albumin were decreased (P ≤ 0.02) in PDS sows. Lipopolysaccharide-binding protein, an inflammatory biomarker, was increased (48%; P = 0.07) at timepoint 2 in PDS compared to CON sows. Collectively, these data indicate PDS sows have altered metabolism and appear immune activated compared to healthy herd-mates, and further investigation is needed to determine if PDS can be predicted at farrowing., (© The Author(s) 2024. Published by Oxford University Press on behalf of the American Society of Animal Science.)

This work presents a system, where deep learning was used on images captured with a digital camera to simultaneously determine the API concentration and the particle size distribution (PSD) of two components of a powder blend. The blend consisted of acetylsalicylic acid (ASA) and calcium hydrogen phosphate (CHP), and the predicted API concentration was found corresponding with the HPLC measurements. The PSDs determined with the method corresponded with those measured with laser diffraction particle size analysis. This novel method provides fast and simple measurements and could be suitable for detecting segregation in the powder. By examining the powders discharged from a batch blender, the API concentrations at the top and bottom of the container could be measured, yielding information about the adequacy of the blending and improving the quality control of the manufacturing process., Competing Interests: Declaration of competing interest The authors declare that they have no conflicts of interest., (Copyright © 2023 The Authors. Published by Elsevier B.V. All rights reserved.)

Introduction: Patients undergoing thoracic surgery are at increased risk of developing, long-lasting pain. Beyond the non-surgical factors, the type of operation, including the number of incisions, and the anesthetic assessment seemed to be important factors, although some studies are controversial. The aim of our study was to examine the presence of chronic postoperative pain after non-intubated uniportal VATS lobectomy. We examined the difference between the intubated, relaxed and non-intubated spontaneous ventilation surgical approaches in patients who underwent video-assisted thoracoscopic (VATS) uniportal lobectomy., Methods: Demographic and postoperative data were retrospectively collected and analyzed, focusing on the use of pain medications, in 67 patients of the 140 patients selected by propensity score matching who underwent intubated (iVATS) or non-intubated (NITS) uniportal VATS lobectomy. This study focused on the use of analgesic medications 3, 6, and 12 months after surgery., Results: Thirty-five intubated and 32 non-intubated patients were compared. Although the analgesic consumption was nearly 2% higher among the iVATS patients during the follow-up period, there were no statistically significant differences at 3 months (15.6 vs. 17.1%) ( p  = 0.868), at 6 months (9.4 vs. 12.4%) ( p  = 0.785), and at 12 months (3.3 vs. 5.9%) ( p  = 0.633) between the NITS and iVATS groups, respectively. More female than male patients reported chronic pain, but the difference was not statistically significant ( p  = 0.616). Diabetes mellitus was a statistically significant cofactor associated with chronic pain ( p  = 0.03), while cardiac disease ( p  = 0.6), perioperative morbidity ( p  = 0.228), prolonged air leak ( p  = 0.057), and repeat drainage ( p  = 0.626) were not., Conclusion: Our study suggests that after non-intubation VATS lobectomies, the postoperative pain was less at 3, 6, and 12 months in NITS patients compared to iVATS patients. The 2% difference was not significant, so it may not be appropriate to claim the advantages of NITS in terms of postoperative pain., Competing Interests: 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., (© 2023 Farkas, Csókási, Fabó, Szabó, Lantos, Pécsy, Lázár, Rárosi, Kecskés and Furák.)

Background: Non-intubated thoracic surgery has not achieved widespread acceptance despite its potential to improve postoperative outcomes. To ensure airway safety, our institute has developed a technique combining spontaneous ventilation with double-lumen tube intubation (SVI). This study aimed to verify the feasibility and limitations of this SVI technique., Methods: For the SVI method, anesthesia induction involves fentanyl and propofol target-controlled infusion, with mivacurium administration. Bispectral index monitoring was used to ensure the optimal depth of anesthesia. Short-term muscle relaxation facilitated double-lumen tube intubation and early surgical steps. Chest opening preceded local infiltration, followed by a vagal nerve blockade to prevent the cough reflex and a paravertebral blockade for pain relief. Subsequently, the muscle relaxant was ceased. The patient underwent spontaneous breathing without coughing during surgical manipulation., Results: Between 10 March 2020 and 28 October 2022, 141 SVI surgeries were performed. Spontaneous respiration with positive end-expiratory pressure was sufficient in 65.96% (93/141) of cases, whereas 31.21% (44/141) required pressure support ventilation. Only 2.84% (4/141) of cases reversed to conventional anesthetic management, owing to technical or surgical difficulties. Results of the 141 cases: The mean maximal carbon dioxide pressure was 59.01 (34.4-92.9) mmHg, and the mean lowest oxygen saturation was 93.96% (81-100%). The mean one-lung, mechanical and spontaneous one-lung ventilation time was 74.88 (20-140), 17.55 (0-115) and 57.73 (0-130) min, respectively., Conclusions: Spontaneous ventilation with double-lumen tube intubation is safe and feasible for thoracic surgery. The mechanical one-lung ventilation time was reduced by 76.5%, and the rate of anesthetic conversion to relaxation was low (2.8%).

A trace amount of water is typically unavoidable as an impurity in ionic liquids, which is a huge challenge for their application in Mg-ion batteries. Here, we employed molecular sieves of different pore diameters (3, 4, and 5 Å), to effectively remove the trace amounts of water from 1-methyl-1-propylpiperidinium bis(trifluoromethylsulfonyl)imide (MPPip-TFSI) and 1-butyl-1-methylpyrrolidinium bis(trifluoromethylsulfonyl)imide (BMP-TFSI). Notably, after sieving (water content <1 mg ⋅ L -1 ), new anodic peaks arise that are attributed to the formation of different anion-cation structures induced by minimizing the influence of hydrogen bonds. Furthermore, electrochemical impedance spectroscopy (EIS) reveals that the electrolyte resistance decreases by ∼10 % for MPPip-TFSI and by ∼28 % for BMP-TFSI after sieving. The electrochemical Mg deposition/dissolution is investigated in MPPip-TFSI/tetraglyme (1 : 1)+100 mM Mg(TFSI) 2 +10 mM Mg(BH 4 ) 2 using Ag/AgCl and Mg reference electrodes. The presence of a trace amount of water leads to a considerable shift of 0.9 V vs. Mg 2+/ Mg in the overpotential of Mg deposition. In contrast, drying of MPPip-TFSI enhances the reversibility of Mg deposition/dissolution and suppresses the passivation of the Mg electrode., (© 2023 The Authors. ChemSusChem published by Wiley-VCH GmbH.)

Inflammasomes, primarily responsible for the activation of IL-1β, have emerged as critical regulators of the tumor microenvironment. By using in vivo and in vitro brain metastasis models, as well as human samples to study the role of the NLRP3 inflammasome in triple-negative breast cancer (TNBC) brain metastases, we found NLRP3 inflammasome components and IL-1β to be highly and specifically expressed in peritumoral astrocytes. Soluble factors from TNBC cells induced upregulation and activation of NLRP3 and IL-1β in astrocytes, while astrocyte-derived mediators augmented the proliferation of metastatic cells. In addition, inhibition of NLRP3 inflammasome activity using MCC950 or dampening the downstream effect of IL-1β prevented the proliferation increase in cancer cells. In vivo, MCC950 reduced IL-1β expression in peritumoral astrocytes, as well as the levels of inflammasome components and active IL-1β. Most importantly, significantly retarded growth of brain metastatic tumors was observed in mice treated with MCC950. Overall, astrocytes contribute to TNBC progression in the brain through activation of the NLRP3 inflammasome and consequent IL-1β release. We conclude that pharmacological targeting of inflammasomes may become a novel strategy in controlling brain metastatic diseases., (© 2023. BioMed Central Ltd., part of Springer Nature.)

Castleman disease is an uncommon lymphoproliferative disorder, located most commonly in the mediastinal lymph nodes. The intrapulmonary presentation is extremely rare, with 14 published cases in the English literature. The clinical presentation of the disorder is not specific and the diagnosis is often challenging. The main goal is to achieve an R0 surgical resection which gives the potential chance for a recurrence-free survival. We present the case of a symptomless, 15-year-old female patient with left-sided tumor mass. Transthoracal invasive tissue biopsy confirmed Castleman disease. The central mass involved the main structures in the left hilus and therefore left pulmonectomy was necessary to reach the complete, tumor-free resection margins. The patient had no local or distant relapse during the 7-year follow-up. Although Castleman disease treated by complete surgical resection provides excellent results, radical and extended lung resection is sometimes inevitable to reach tumor-free margins. Orv Hetil. 2023; 164(37): 1476-1483.

In this work, the performance of two fast chemical imaging techniques, Raman and near-infrared (NIR) imaging is compared by utilizing these methods to predict the rate of drug release from sustained-release tablets. Sustained release is provided by adding hydroxypropyl methylcellulose (HPMC), as its concentration and particle size determine the dissolution rate of the drug. The chemical images were processed using classical least squares; afterwards, a convolutional neural network was applied to extract information regarding the particle size of HPMC. The chemical images were reduced to an average HPMC concentration and a predicted particle size value; these were used as inputs in an artificial neural network with a single hidden layer to predict the dissolution profile of the tablets. Both NIR and Raman imaging yielded accurate predictions. As the instrumentation of NIR imaging allows faster measurements than Raman imaging, this technique is a better candidate for implementing a real-time technique. The introduction of chemical imaging in the routine quality control of pharmaceutical products would profoundly change quality assurance in the pharmaceutical industry.

Epithelial ion and fluid secretion determine the physiological functions of a broad range of organs, such as the lung, liver, or pancreas. The molecular mechanism of pancreatic ion secretion is challenging to investigate due to the limited access to functional human ductal epithelia. Patient-derived organoids may overcome these limitations, however direct accessibility of the apical membrane is not solved. In addition, due to the vectorial transport of ions and fluid the intraluminal pressure in the organoids is elevated, which may hinder the study of physiological processes. To overcome these, we developed an advanced culturing method for human pancreatic organoids based on the removal of the extracellular matrix that induced an apical-to-basal polarity switch also leading to reversed localization of proteins with polarized expression. The cells in the apical-out organoids had a cuboidal shape, whereas their resting intracellular Ca 2+ concentration was more consistent compared to the cells in the apical-in organoids. Using this advanced model, we demonstrated the expression and function of two novel ion channels, the Ca 2+ activated Cl - channel Anoctamin 1 (ANO1) and the epithelial Na + channel (ENaC), which were not considered in ductal cells yet. Finally, we showed that the available functional assays, such as forskolin-induced swelling, or intracellular Cl - measurement have improved dynamic range when performed with apical-out organoids. Taken together our data suggest that polarity-switched human pancreatic ductal organoids are suitable models to expand our toolset in basic and translational research., (© 2023. The Author(s).)

This paper presents a case study on the first in-line application of AI-based image analysis for real-time pharmaceutical particle size measurement in a continuous milling process. An AI-based imaging system, which utilises a rigid endoscope, was tested for the real-time particle size measurement of solid NaCl powder used as a model API in the range of 200-1000 µm. After creating a dataset containing annotated images of NaCl particles, it was used to train an AI model for detecting particles and measuring their size. The developed system could analyse overlapping particles without dispersing air, thus broadening its applicability. The performance of the system was evaluated by measuring pre-sifted NaCl samples with the imaging tool, after which it was installed into a continuous mill for in-line particle size measurement of a milling process. By analysing ∼100 particles/s, the system was able to accurately measure the particle size of sifted NaCl samples and detect particle size reduction when applied in the milling process. The Dv50 values and PSDs measured real-time with the AI-based system correlated well with the reference laser diffraction measurements (<6% mean absolute difference over the measured samples). The AI-based imaging system shows great potential for in-line particle size analysis, which, in line with the latest pharmaceutical QC trends, can provide valuable information for process development and control., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Author(s). Published by Elsevier B.V. All rights reserved.)

In this work, the capabilities of a state-of-the-art fast Raman imaging apparatus are exploited to gain information about the concentration and particle size of hydroxypropyl methylcellulose (HPMC) in sustained release tablets. The extracted information is utilized to predict the in vitro dissolution profile of the tablets. For the first time, convolutional neural networks (CNNs) are used for the processing of the chemical images of HPMC distribution and to directly predict the dissolution profile based on the image. This new method is compared to wavelet analysis, which gives a quantification of the texture of HPMC distribution, carrying information regarding both concentration and particle size. A total of 112 training and 32 validation tablets were used, when a CNN was used to characterize the particle size of HPMC, the dissolution profile of the validation tablets was predicted with an average f 2 similarity value of 62.95. Direct prediction based on the image had an f 2 value of 54.2, this demonstrates that the CNN is capable of recognizing the patterns in the data on its own. The presented methods can facilitate a better understanding of the manufacturing processes, as detailed information becomes available with fast measurements., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Author(s). Published by Elsevier B.V. All rights reserved.)

The aim of this study was to develop antisense oligonucleotide tablet formulations using high-speed electrospinning. Hydroxypropyl-beta-cyclodextrin (HPβCD) was used as a stabilizer and as an electrospinning matrix. In order to optimize the morphology of the fibers, electrospinning of various formulations was carried out using water, methanol/water (1:1), and methanol as solvents. The results showed that using methanol could be advantageous due to the lower viscosity threshold for fiber formation enabling higher potential drug loadings by using less excipient. To increase the productivity of electrospinning, high-speed electrospinning technology was utilized and HPβCD fibers containing 9.1% antisense oligonucleotide were prepared at a rate of ~330 g/h. Furthermore, to increase the drug content of the fibers, a formulation with a 50% drug loading was developed. The fibers had excellent grindability but poor flowability. The ground fibrous powder was mixed with excipients to improve its flowability, which enabled the automatic tableting of the mixture by direct compression. The fibrous HPβCD-antisense oligonucleotide formulations showed no sign of physical or chemical degradation over the 1-year stability study, which also shows the suitability of the HPβCD matrix for the formulation of biopharmaceuticals. The obtained results demonstrate possible solutions for the challenges of electrospinning such as scale-up and downstream processing of the fibers.

As the pharmaceutical industry increasingly adopts the Pharma 4.0. concept, there is a growing need to effectively predict the product quality based on manufacturing or in-process data. Although artificial neural networks (ANNs) have emerged as powerful tools in data-rich environments, their implementation in pharmaceutical manufacturing is hindered by their black-box nature. In this work, ANNs were developed and interpreted to demonstrate their applicability to increase process understanding by retrospective analysis of developmental or manufacturing data. The in vitro dissolution and hardness of extended-release, directly compressed tablets were predicted from manufacturing and spectroscopic data of pilot-scale development. The ANNs using material attributes and operational parameters provided better results than using NIR or Raman spectra as predictors. ANNs were interpreted by sensitivity analysis, helping to identify the root cause of the batch-to-batch variability, e.g., the variability in particle size, grade, or substitution of the hydroxypropyl methylcellulose excipient. An ANN-based control strategy was also successfully utilized to mitigate the batch-to-batch variability by flexibly operating the tableting process. The presented methodology can be adapted to arbitrary data-rich manufacturing steps from active substance synthesis to formulation to predict the quality from manufacturing or development data and gain process understanding and consistent product quality., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Authors. Published by Elsevier B.V. All rights reserved.)

The health benefits of regular physical exercise are well known. Even so, there is increasing evidence that the exercise regimes of elite athletes can evoke cardiac arrhythmias including ventricular fibrillation and even sudden cardiac death (SCD). The mechanism of exercise-induced arrhythmia and SCD is poorly understood. Here, we show that chronic training in a canine model (12 sedentary and 12 trained dogs) that mimics the regime of elite athletes induces electrophysiological remodeling (measured by ECG, patch-clamp, and immunocytochemical techniques) resulting in increases of both the trigger and the substrate for ventricular arrhythmias. Thus, 4 months sustained training lengthened ventricular repolarization (QTc: 237.1±3.4 ms vs. 213.6±2.8 ms, n=12; APD90: 472.8±29.6 ms vs. 370.1±32.7 ms, n=29 vs. 25), decreased transient outward potassium current (6.4±0.5 pA/pF vs. 8.8±0.9 pA/pF at 50 mV, n=54 vs. 42), and increased the short-term variability of repolarization (29.5±3.8 ms vs. 17.5±4.0 ms, n=27 vs. 18). Left ventricular fibrosis and HCN4 protein expression were also enhanced. These changes were associated with enhanced ectopic activity (number of escape beats from 0/hr to 29.7±20.3/hr) in vivo and arrhythmia susceptibility (elicited ventricular fibrillation: 3 of 10 sedentary dogs vs. 6 of 10 trained dogs). Our findings provide in vivo, cellular electrophysiological and molecular biological evidence for the enhanced susceptibility to ventricular arrhythmia in an experimental large animal model of endurance training., Competing Interests: AP, LT, NZ, NT, JP, ZK, SD, VD, PH, VV, GÁ, ZH, PG, JS, TÁ, MN, AS, NJ, LV, NN, IB, AF, AV No competing interests declared, (© 2023, Polyák, Topal et al.)

The Crux tandem mass spectrometry data analysis toolkit provides a collection of algorithms for analyzing bottom-up proteomics tandem mass spectrometry data. Many publications have described various individual components of Crux, but a comprehensive summary has not been published since 2014. The goal of this work is to summarize the functionality of Crux, focusing on developments since 2014. We begin with empirical results demonstrating our recently implemented speedups to the Tide search engine. Other new features include a new score function in Tide, two new confidence estimation procedures, as well as three new tools: Param-medic for estimating search parameters directly from mass spectrometry data, Kojak for searching cross-linked mass spectra, and DIAmeter for searching data independent acquisition data against a sequence database.

The first step in the analysis of protein tandem mass spectrometry data typically involves searching the observed spectra against a protein database. During database search, the search engine must digest the proteins in the database into peptides, subject to digestion rules that are under user control. The choice of these digestion parameters, as well as selection of post-translational modifications (PTMs), can dramatically affect the size of the search space and hence the statistical power of the search. The Tide search engine separates the creation of the peptide index from the database search step, thereby saving time by allowing a peptide index to be reused in multiple searches. Here we describe an improved implementation of the indexing component of Tide that consumes around four times less resources (CPU and RAM) than the previous version and can generate arbitrarily large peptide databases, limited by only the amount of available disk space. We use this improved implementation to explore the relationship between database size and the parameters controlling digestion and PTMs, as well as database size and statistical power. Our results can help guide practitioners in proper selection of these important parameters.

Decomposition of lignocellulosic plant biomass by four filamentous fungi was carried out to facilitate subsequent anaerobic degradation and biogas formation. Agricultural side products, wheat straw and corn stover and forestry energy plant willow chips were selected as plant biomass sources. The substrates were confronted by pure cultures of Penicillium aurantiogriseum (new isolate from rumen), Trichoderma reesei (DSM768), Gilbertella persicaria (SZMC11086) and Rhizomucor miehei (SZMC11005). In addition to total cellulolytic filter paper degradation activity, the production of endoglucanase, cellobiohydrolase, β-glucosidase enzymes were followed during the pretreatment period, which lasted for 10 days at 37 °C. The products of pretreatments were subsequently tested for mesophilic biogas production in batch reactors. All 4 strains effectively pretreated the lignocellulosic substrates albeit in varying degrees, which was related to the level of the tested hydrolytic enzyme activities. Penicillium aurantiogriseum showed outstanding hydrolytic enzyme production and highest biogas yield from the partially degraded substrates. Corn stover was the best substrate for biomass decomposition and biogas production. Scanning electron microscopy confirmed the deep penetration of fungal hyphae into the lignocellulosic substrate in all cases., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 The Authors. Published by Elsevier B.V. All rights reserved.)

Research on new reaction routes and precursors to prepare catalysts for CO 2 hydrogenation has enormous importance. Here, we report on the preparation of the permanganate salt of the urea-coordinated iron(III), [hexakis(urea- O )iron(III)]permanganate ([Fe(urea-O) 6 ](MnO 4 ) 3 ) via an affordable synthesis route and preliminarily demonstrate the catalytic activity of its (Fe,Mn)O x thermal decomposition products in CO 2 hydrogenation. [Fe(urea-O) 6 ](MnO 4 ) 3 contains O-coordinated urea ligands in octahedral propeller-like arrangement around the Fe 3+ cation. There are extended hydrogen bond interactions between the permanganate ions and the hydrogen atoms of the urea ligands. These hydrogen bonds serve as reaction centers and have unique roles in the solid-phase quasi-intramolecular redox reaction of the urea ligand and the permanganate anion below the temperature of ligand loss of the complex cation. The decomposition mechanism of the urea ligand (ammonia elimination with the formation of isocyanuric acid and biuret) has been clarified. In an inert atmosphere, the final thermal decomposition product was manganese-containing wuestite, (Fe,Mn)O, at 800 °C, whereas in ambient air, two types of bixbyite (Fe,Mn) 2 O 3 as well as jacobsite (Fe,Mn) T-4 (Fe,Mn) OC-6 2 O 4 ), with overall Fe to Mn stoichiometry of 1:3, were formed. These final products were obtained regardless of the different atmospheres applied during thermal treatments up to 350 °C. Disordered bixbyite formed first with inhomogeneous Fe and Mn distribution and double-size supercell and then transformed gradually into common bixbyite with regular structure (and with 1:3 Fe to Mn ratio) upon increasing the temperature and heating time. The (Fe,Mn)O x intermediates formed under various conditions showed catalytic effect in the CO 2 hydrogenation reaction with <57.6% CO 2 conversions and <39.3% hydrocarbon yields. As a mild solid-phase oxidant, hexakis(urea- O )iron(III) permanganate, was found to be selective in the transformation of (un)substituted benzylic alcohols into benzaldehydes and benzonitriles.

In this study, a concentration predicting soft sensor was achieved based on the Residence Time Distribution (RTD) of an integrated, three-step pharmaceutical formulation line. The RTD was investigated with color-based tracer experiments using image analysis. Twin-screw wet granulation (TSWG) was directly coupled with a horizontal fluid bed dryer and an oscillating mill. Based on integrated measurement, we proved that it is also possible to couple the unit operations in silico. Three surrogate tracers were produced with a coloring agent to investigate the separated unit operations and the solid and liquid inputs of the TSWG. The soft sensor's prediction was compared to validating experiments of a 0.05 mg/g (15% of the nominal) concentration change with High-Performance Liquid Chromatography (HPLC) reference measurements of the active ingredient proving the adequacy of the soft sensor (RMSE < 4%)., (Copyright © 2022 The Authors. Published by Elsevier B.V. All rights reserved.)

Creating supersaturating drug delivery systems to overcome the poor aqueous solubility of active ingredients became a frequent choice for formulation scientists. Supersaturation as a solution phenomenon is, however, still challenging to understand, and therefore many recent publications focus on this topic. This work aimed to investigate and better understand the pH dependence of supersaturation of telmisartan (TEL) at a molecular level and find a connection between the physicochemical properties of the active pharmaceutical ingredient (API) and the ability to form supersaturated solutions of the API. Therefore, the main focus of the work was the pH-dependent thermodynamic and kinetic solubility of the model API, TEL. Based on kinetic solubility results, TEL was observed to form a supersaturated solution only in the pH range 3-8. The experimental thermodynamic solubility-pH profile shows a slight deviation from the theoretical Henderson-Hasselbalch curve, which indicates the presence of zwitterionic aggregates in the solution. Based on p K a values and the refined solubility constants and distribution of macrospecies, the pH range where high supersaturation-capacity is observed is the same where the zwitterionic form of TEL is present. The existence of zwitterionic aggregation was confirmed experimentally in the pH range of 3 to 8 by mass spectrometry.

The release of the FDA's guidance on Process Analytical Technology has motivated and supported the pharmaceutical industry to deliver consistent quality medicine by acquiring a deeper understanding of the product performance and process interplay. The technical opportunities to reach this high-level control have considerably evolved since 2004 due to the development of advanced analytical sensors and chemometric tools. However, their transfer to the highly regulated pharmaceutical sector has been limited. To this respect, data fusion strategies have been extensively applied in different sectors, such as food or chemical, to provide a more robust performance of the analytical platforms. This survey evaluates the challenges and opportunities of implementing data fusion within the PAT concept by identifying transfer opportunities from other sectors. Special attention is given to the data types available from pharmaceutical manufacturing and their compatibility with data fusion strategies. Furthermore, the integration into Pharma 4.0 is discussed.

The failures of anti-β-amyloid immunotherapies suggested that the very low fraction of injected antibodies reaching the brain parenchyma due to the filtering effect of the BBB may be a reason for the lack of therapeutic effect. However, there is no treatment, as yet, for the amyotrophic lateral sclerosis (ALS) despite substantial evidence existing of the involvement of TDP-43 protein in the evolution of ALS. To circumvent this filtering effect, we have developed a novel approach to facilitate the penetration of antibody fragments (Fabs) into the brain parenchyma. Leveraging the homing properties of endothelial progenitor cells (EPCs), we transfected, ex vivo, such cells with vectors encoding anti-β-amyloid and anti-TDP43 Fabs turning them into an "antibody fragment factory". When injected these cells integrate into the BBB, where they secrete anti-TDP43 Fabs. The results showed the formation of tight junctions between the injected engineered EPCs and the unlabeled resident endothelial cells. When the EPCs were further modified to express the anti-TDP43 Fab, we could observe integration of these cells into the vasculature and the secretion of Fabs. Results confirm that production and secretion of Fabs at the BBB level leads to their migration to the brain parenchyma where they might exert a therapeutic effect.

Industry 4.0 has started to transform the manufacturing industries by embracing digitalization, automation, and big data, aiming for interconnected systems, autonomous decisions, and smart factories. Machine learning techniques, such as artificial neural networks (ANN), have emerged as potent tools to address the related computational tasks. These advancements have also reached the pharmaceutical industry, where the Process Analytical Technology (PAT) initiative has already paved the way for the real-time analysis of the processes and the science- and risk-based flexible production. This paper aims to assess the potential of ANNs within the PAT concept to aid the modernization of pharmaceutical manufacturing. The current state of ANNs is systematically reviewed for the most common manufacturing steps of solid pharmaceutical products, and possible research gaps and future directions are identified. In this way, this review could aid the further development of machine learning techniques for pharmaceutical production and eventually contribute to the implementation of intelligent manufacturing lines with automated quality assurance., (© 2022. The Author(s).)

The potential of machine vision systems has not currently been exploited for pharmaceutical applications, although expected to provide revolutionary solutions for in-process and final product testing. The presented paper aimed to analyze the particle size of meloxicam, a yellow model active pharmaceutical ingredient, in intact tablets by a digital UV/VIS imaging-based machine vision system. Two image processing algorithms were developed and coupled with pattern recognition neural networks for UV and VIS images for particle size-based classification of the prepared tablets. The developed method can identify tablets containing finer or larger particles than the target with more than 97% accuracy. Two algorithms were developed for UV and VIS images for particle size analysis of the prepared tablets. According to the applied statistical tests, the obtained particle size distributions were similar to the results of the laser diffraction-based reference method. Digital UV/VIS imaging combined with multivariate data analysis can provide a new non-destructive, rapid, in-line tool for particle size analysis in tablets., (Copyright © 2022 The Author(s). Published by Elsevier B.V. All rights reserved.)

An innovative, Raman spectroscopy-based monitoring and control system is introduced in this paper for designing dynamic feeding strategies that allow the maintenance of key cellular nutrients at an ideal level in Chinese hamster ovary cell culture. The Partial Least Squares calibration models built for glucose, lactate and 16 (out of 20) individual amino acids had very good predictive power with low root mean square errors values and high square correlation coefficients. The developed models used for real-time measurement of nutrient and by-product concentrations allowed us to gain better insight into the metabolic behavior and nutritional consumption of cells. To establish a more beneficial nutritional environment for the cells, two types of dynamic feeding strategies were used to control the delivery of two-part multi-component feed media according to the prediction of Raman models (glucose or arginine). As a result, instead of high fluctuations, the nutrients (glucose together with amino acids) were maintained at the desired level providing a more balanced environment for the cells. Moreover, the use of amino acid-based feeding control enabled to prevent the excessive nutrient replenishment and was economically beneficial by significantly reducing the amount of supplied feed medium compared to the glucose-based dynamic fed culture., (© 2022 The Authors. Biotechnology Journal published by Wiley-VCH GmbH.)

Spreading depolarizations (SDs) indicate injury progression and predict worse clinical outcome in acute brain injury. We demonstrate in rodents that acute brain swelling upon cerebral ischemia impairs astroglial glutamate clearance and increases the tissue area invaded by SD. The cytotoxic extracellular glutamate accumulation (>15 µM) predisposes an extensive bulk of tissue (4-5 mm 2 ) for a yet undescribed simultaneous depolarization (SiD). We confirm in rat brain slices exposed to osmotic stress that SiD is the pathological expansion of prior punctual SD foci (0.5-1 mm 2 ), is associated with astrocyte swelling, and triggers oncotic neuron death. The blockade of astrocytic aquaporin-4 channels and Na + /K + /Cl - co-transporters, or volume-regulated anion channels mitigated slice edema, extracellular glutamate accumulation (<10 µM) and SiD occurrence. Reversal of slice swelling by hyperosmotic mannitol counteracted glutamate accumulation and prevented SiD. In contrast, inhibition of glial metabolism or inhibition of astrocyte glutamate transporters reproduced the SiD phenotype. Finally, we show in the rodent water intoxication model of cytotoxic edema that astrocyte swelling and altered astrocyte calcium waves are central in the evolution of SiD. We discuss our results in the light of evidence for SiD in the human cortex. Our results emphasize the need of preventive osmotherapy in acute brain injury.

In this paper, the applicability of Raman chemical imaging for the non-destructive prediction of the in vitro dissolution profile of sustained-release tablets is demonstrated for the first time. Raman chemical maps contain a plethora of information about the spatial distribution and the particle size of the components, compression force and even polymorphism. With proper data analysis techniques, this can be converted into simple numerical information which can be used as input in a machine learning model. In our work, sustained-release tablets using hydroxypropyl methylcellulose (HPMC) as matrix polymer are prepared, the concentration and particle size of this component varied between samples. Chemical maps of HPMC are converted into histograms with two different methods, an approach based on discretizing concentration values and a wavelet analysis technique. These histograms are then subjected to Principal Component Analysis, the score value of the first two principal components was found to represent HPMC content and particle size. These values are used as input in Artificial Neural Networks which are trained to predict the dissolution profile of the tablets. As a result, accurate predictions were obtained for the test tablets (the average f 2 similarity value is higher than 59 with both methods). The presented methodology lays the foundations of the analysis of far more extensive datasets acquired with the emerging fast Raman imaging technology., (Copyright © 2022 The Authors. Published by Elsevier B.V. All rights reserved.)

Összefoglaló. Bevezetés: Myocardialis infarktus esetén a panasz kezdetétől az ér megnyitásáig eltelt idő prognosztikus jelentőségű, a legtöbb szívizom megmentésére az első órákban van lehetőség. A Nemzeti Szívinfarktus Regiszter alapján tudjuk, hogy hazánkban a teljes ischaemiás idő kedvezőtlenül hosszú. Célkitűzés: Az ST-elevációval járó myocardialis infarktusos betegek késési idejét befolyásoló tényezők azonosítása. Módszer: Prospektív klinikai vizsgálatot végeztünk, melynek során a Szegedi Tudományegyetemen a II. Belgyógyászati Klinika és Kardiológiai Központ Invazív Kardiológiai Részlegére érkezett STEMI-s betegek adatait gyűjtöttük saját kérdőív alapján. Az adatgyűjtés 2019. 01. 01. és 2019. 12. 20. között zajlott, 121 beteg adatait dolgoztuk fel. Eredmények: A medián bejelentési idő 83 perc, a medián prehospitális idő 252 perc, a medián teljes ischaemiás idő 304 perc volt. Az Országos Mentőszolgálat (OMSZ) értesítésekor minden késési idő szignifikánsan rövidebb volt, a Sürgősségi Betegellátó Osztály (SBO) vagy a háziorvos értesítéséhez viszonyítva (a teljes ischaemiás idő mediánja: OMSZ: 233 perc, SBO: 341 perc, háziorvos: 650 perc). A betegek lakhelye szignifikánsan befolyásolta a késési időket és a választott betegutat: a bejelentési idő mediánja városban 60 perc, faluban 147 perc volt; az OMSZ-t értesítette a városi betegek 50%-a, a falusi betegek 25%-a. A közös segélyhívó szám ismerete szignifikánsan rövidítette a betegúthoz tartozó késési időt (a betegútkésés medián ideje, ha a segélyhívó számot ismerte: 178 perc, ha nem ismerte: 268 perc). Következtetés: A késési idők rendkívül hosszúak voltak. A legszorosabb összefüggést a késési időkkel a választott betegút mutatta. A városi emberek előbb jelezték panaszaikat, és gyakrabban választották a megfelelő betegutat, az OMSZ-t, így késési idejük is rövidebb volt. Eredményeink felhívják a figyelmet a társadalom edukációjának fontosságára, különös tekintettel a kis települések lakóira. Orv Hetil. 2022; 163(11): 438-445., Introduction: The time elapsing from myocardial infarction onset to revascularization is prognostic; the most myocardium can be saved in the first hours. According to the Hungarian Myocardial Infarction Registry, the total ischaemic time is long in Hungary., Objective: We aimed to identify the factors influencing the delay times of patients with ST-elevation myocardial infarction (STEMI)., Method: We performed a prospective clinical study and collected data from 121 patients presenting with STEMI at the Cardiology Center of the University of Szeged in 2019. We filled out a questionnaire by interviewing patients after primary coronary intervention., Results: The medians of the patient delay, prehospital delay time and total ischaemic time were 83, 252 and 304 minutes, respectively. When the Ambulance Service (AS) was notified, every delay time was significantly shorter than those measured when the Emergency Department or the general practitioner was notified. The place of residence of the patients significantly influenced the delay times and the chosen pathway of healthcare: median patient delays were 60 and 147 minutes in cities and villages, respectively; AS was called first by 50% of urban patients vs. 25% of rural patients. Knowing the emergency number was associated with reduced delay times., Conclusion: Delay times were long. The chosen pathway of healthcare had the greatest impact on the delay times. Urban people reported their complaints sooner, were more likely to choose the best healthcare pathway (AS), thus their delay times were shorter. These suggest that it is important to educate the society, especially rural communities. Orv Hetil. 2022; 163(11): 438-445.

Today, graphene oxide (GO) has gained well-deserved recognition, with its applications continuing to increase. Much of the processing of GO-based devices occurs in a dispersed form, which explains the commercialization of GO suspensions. Aging of these suspensions can, however, affect the shelf life and thus their application potential. Aging of GO preparations is often acknowledged, but no longer-term systematic study has been reported on the alteration of GO suspensions. This paper investigates high-concentration (10 mg/mL) aqueous GO suspensions over a 2-year time scale. In addition to steady shear tests, the dynamic behavior of the suspensions was studied in more detail by transient shear and frequency sweep measurements. Both the viscosity and the dynamic moduli increased with age, particularly within the first year. The results of the complementary Raman spectroscopic studies indicate that the change in the rheological behavior with aging results from a slow oxidation process occurring in the highly acidic aqueous medium during the relatively long-term storage. The (over)oxidized layers peel off spontaneously or are removed by high shear stress, resulting in increased viscosity, as it was corroborated by XRD and XPS.

In the present study, the effect of long-term exercise training was investigated on myocardial morphological and functional remodeling and on proarrhythmic sensitivity in a rabbit athlete's heart model. New-Zealand white rabbits were trained during a 12-week long treadmill running protocol and compared with their sedentary controls. At the end of the training protocol, echocardiography, in vivo and in vitro ECG recordings, proarrhythmic sensitivity with dofetilide (nM) were performed in isolated hearts, and action potential duration (APD) measurements at different potassium concentrations (4.5 and 2 mM) were made in the isolated papillary muscles. Expression levels of the slow component of delayed rectifier potassium current and fibrosis synthesis and degradation biomarkers were quantified. Echocardiography showed a significantly dilated left ventricle in the running rabbits. ECG PQ and RR intervals were significantly longer in the exercised group (79 ± 2 vs. 69 ± 2 ms and 325 ± 11 vs. 265 ± 6 ms, p < 0.05, respectively). The in vivo heart rate variability (HRV) (SD of root mean square: 5.2 ± 1.4 ms vs. 1.4 ± 0.2 ms, p < 0.05) and Tpeak-Tend variability were higher in the running rabbits. Bradycardia disappeared in the exercised group in vitro . Dofetilide tended to increase the QTc interval in a greater extent, and significantly increased the number of arrhythmic beats in the trained animals in vitro . APD was longer in the exercised group at a low potassium level. Real-time quantitative PCR (RT-qPCR) showed significantly greater messenger RNA expression of fibrotic biomarkers in the exercised group. Increased repolarization variability and higher arrhythmia incidences, lengthened APD at a low potassium level, increased fibrotic biomarker gene expressions may indicate higher sensitivity of the rabbit "athlete's heart" to life-threatening arrhythmias., Competing Interests: 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., (Copyright © 2022 Kui, Polyák, Morvay, Tiszlavicz, Nagy, Ördög, Takács, Leprán, Farkas, Papp, Jost, Varró, Baczkó and Farkas.)

The present paper reports the powder filling of milled electrospun materials in vials, which contained voriconazole and sulfobutylether-β-cyclodextrin. High-speed electrospinning was used for the production of the fibrous sample, which was divided into 6 parts. Each portion was milled using different milling methods and sizes of sieves to investigate whether the milling influences the powder and filling properties. Bulk and tapped density tests, laser diffraction and angle of repose measurements were applied to characterize the milled powders, while a vibratory feeder was used for the feeding experiments. The correlation between the material property descriptors and the feeding responses was investigated by multivariate data analysis. Based on the results, three samples were chosen for the vial filling, which was accomplished with 3400 mg electrospun material containing 200 mg voriconazole, representative of the commercial product. The feed rate was set to fit the 240 g/h production rate of the electrospinning and the relative standard deviation of three repeated vial filling was determined to see the accuracy of the process. This research shows that by applying a suitable milling method it is possible to process electrospun fibers to a powder, which can be filled into vials and used as reconstitution dosage forms., (Copyright © 2021 The Authors. Published by Elsevier B.V. All rights reserved.)

The present paper serves as a demonstration how an in-line PAT tool can be used for rapid and efficient process development in a fully continuous powder to granule line consisting of an interconnected twin-screw wet granulator, vibrational fluid bed dryer, and a regranulating mill. A new method was investigated for the periodic in-line particle size measurement of high mass flow materials to obtain real-time particle size data of the regranulated product. The system utilises a vibratory feeder with periodically altered feeding intensity in order to temporarily reduce the mass flow of the material passing in front of the camera. This results in the drastic reduction of particle overlapping in the images, making image analysis a viable tool for the in-line particle size measurement of high mass-flow materials. To evaluate the performance of the imaging system, the effect of several milling settings and the liquid-to-solid ratio was investigated on the product's particle size in the span of a few hours. The particle sizes measured with the in-line system were in accordance with the expected trends as well as with the results of the off-line reference particle size measurements. Based on the results, the in-line imaging system can serve as a PAT tool to obtain valuable real-time information for rapid process development or quality assurance., (Copyright © 2021 The Authors. Published by Elsevier B.V. All rights reserved.)

Curcuminoids (CUs) of antitumor and various other potential biological activities have extremely low water solubility therefore special formulation was elaborated. New fast dissolving reconstitution dosage forms of four CUs were prepared as fibrous form of 2-hydroxypropyl-β-cyclodextin (HP-β-CD). In the electrospinning process HP-β-CD could act both as solubilizer and fiber-forming agent. The solubilization efficiency of the CU-HP-β-CD systems was determined with phase-solubility measurements. The electrospun CUs were amorphous and uniformly distributed in the fibers according to XRD analysis and Raman mappings. The fibrous final products had fast (<5 min) and complete dissolution. In typical iv. infusion reconstitution volume (20 mL) fibers containing 40-80 mg of CU could be dissolved, which is similar to the currently proposed dose (<120 mg/m 2 ). The in vitro cytostatic effect data showed that the antitumor activity of the CU-HP-β-CD complexes was similar or better compared to the free APIs., (Copyright © 2021 The Authors. Published by Elsevier B.V. All rights reserved.)

The work aimed to develop the Absorption Driven Drug Formulation (ADDF) concept, which is a new approach in formulation development to ensure that the drug product meets the expected absorption rate. The concept is built on the solubility-permeability interplay and the rate of supersaturation as the driving force of absorption. This paper presents the first case study using the ADDF concept where not only dissolution and solubility but also permeation of the drug is considered in every step of the formulation development. For that reason, parallel artificial membrane permeability assay (PAMPA) was used for excipient selection, small volume dissolution-permeation apparatus was used for testing amorphous solid dispersions (ASDs), and large volume dissolution-permeation tests were carried out to characterize the final dosage forms. The API-excipient interaction studies on PAMPA indicated differences when different fillers or surfactants were studied. These differences were then confirmed with small volume dissolution-permeation assays where the addition of Tween 80 to the ASDs decreased the flux dramatically. Also, the early indication of sorbitol's advantage over mannitol by PAMPA has been confirmed in the investigation of the final dosage forms by large-scale dissolution-permeation tests. This difference between the fillers was observed in vivo as well. The presented case study demonstrated that the ADDF concept opens a new perspective in generic formulation development using fast and cost-effective flux-based screening methods in order to meet the bioequivalence criteria. Graphical Abstract., (© 2022. The Author(s).)

Plant pathogenic fungi are responsible for enormous crop losses worldwide. Overcoming this problem is challenging as these fungi can be highly resistant to approved chemical fungicides. There is thus a need to develop and introduce fundamentally new plant and crop protection strategies for sustainable agricultural production. Highly stable extracellular antifungal proteins (AFPs) and their rationally designed peptide derivatives (PDs) constitute feasible options to meet this challenge. In the present study, their potential for topical application to protect plants and crops as combinatorial biofungicides is supported by the investigation of two Neosartorya ( Aspergillus ) fischeri AFPs (NFAP and NFAP2) and their γ-core PDs. Previously, the biofungicidal potential of NFAP, its rationally designed γ-core PD (γ NFAP -opt), and NFAP2 was reported. Susceptibility tests in the present study extended the in vitro antifungal spectrum of NFAP2 and its γ-core PD (γ NFAP2 -opt) to Botrytis , Cladosporium , and Fusarium spp. Besides, in vitro additive or indifferent interactions, and synergism were observed when NFAP or NFAP2 was applied in combination with γ NFAP -opt. Except for γ NFAP2 -opt, the investigated proteins and peptides did not show any toxicity to tomato plant leaves. The application of NFAP in combination with γ NFAP -opt effectively inhibited conidial germination, biofilm formation, and hyphal extension of the necrotrophic mold Botrytis cinerea on tomato plant leaves. However, the same combination only partially impeded the B. cinerea -mediated decay of tomato fruits, but mitigated the symptoms. Our results highlight the feasibility of using the combination of AFP and PD as biofungicide for the fungal infection control in plants and crops., Supplementary Information: The online version contains supplementary material available at 10.1007/s10526-022-10132-y., Competing Interests: Conflict of interestThe authors declare that there are no conflicts of interest associated with this publication., (© The Author(s) 2022.)

In this paper we present a thorough description of the digital twin development for a continuous pharmaceutical powder blending process in accordance with the Process Analytical Technologies (PAT) and Quality by Design (QbD) guidelines. A low-dosage system of caffeine active pharmaceutical ingredient (API) and dextrose excipient was examined via continuous blending experiments. Near infrared (NIR) spectroscopy-based process analytics were applied; quantitative evaluation of spectra was achieved using multivariate data analysis. The blending system was represented with mechanistic residence time distribution (RTD) models and two types of recurrent artificial neural networks (ANN), experimental datasets were used for model training or fitting and validation. Detailed comparison of the two modelling approaches, the optimization of the model-based digital twin, and efficiency of the soft sensor-based process monitoring is presented through several validating simulations. Both RTD models and nonlinear autoregressive neural networks demonstrated excellent predictive power for the low dosage blending process. RTD models can prove to be more advantageous in industrial development as they are less resource-intensive to develop and prediction accuracy on low concentration levels lacks dependency from the precision of chemometric calibration. Reduced material costs and limited development timeframe render the digital twin an efficient tool in technological development., (Copyright © 2021 The Author(s). Published by Elsevier B.V. All rights reserved.)

This study examined the concentrations of Al, Ca, Cd, Cr, Cu, Fe, K, Mg, Mn, Na, Ni, Pb, and Zn in the liver and kidney samples of golden jackals (n = 163) and red foxes (n = 64). Additionally, we studied how sex affected element concentration in both species, and in the case of golden jackals, how concentration levels were affected by age.Liver was the most important storage organ for Cu, Fe, Mn, and Zn, while kidney for Cd and Na in jackals and foxes.We found no sex-related differences in concentration of any of the selected elements in fox samples. In jackals, the mean concentrations of Al, Mn, and Zn were significantly higher in kidneys of males, while Zn and Cu had higher concentrations in female livers. Our results suggest bioaccumulation processes do not occur in mesocarnivores.Lead and Cd concentrations fell within ranges accepted as normal for canine species and were below toxic levels in the organs of the examined species. Concentrations of Cr, Cu, Fe, Mn, and Zn were far below the toxic levels in both organs of both species, with a slight sign of deficiency of Fe, Mn, and Zn in jackal and fox kidneys. In comparison with toxicity levels and results from other European study sites, the current study demonstrated that species living in the examined area of Somogy County, Hungary, are generally exposed to low levels of environmental contamination., (© 2021. The Author(s).)