Tick-borne encephalitis virus (TBEV) is a neurotropic orthoflavivirus that invades the central nervous system, leading to severe neurological manifestations. In this study, we developed a reporter virus comprising TurboGFP-expressing TBEV (tGFP-TBEV) as a versatile tool for advancing TBEV research. The tGFP-TBEV facilitates quantitative measurement of viral replication, enables precise tracking of individual infected cells, and supports high-throughput screening of potential antiviral compounds and virus-neutralization assays. Furthermore, tGFP-TBEV proved effective as a model for studying TBEV infection in rat organotypic cerebellar slices cultured ex vivo and for visualizing TBEV infection in the mouse brain. Using tissue-clearing protocols and light-sheet fluorescence microscopy, we achieved high-resolution, three-dimensional mapping of the TBEV distribution in the mouse brain. This analysis uncovered distinct patterns of TBEV tropism, with infections concentrated in regions associated with neurogenesis, olfactory processing, and specific neuroanatomical pathways. The ability to visualize infection at both the cellular and whole-organ level provides a new tool for detailed investigations into viral tropism, replication, and interactions with host tissues, paving the way for deeper insights into TBEV biology and the pathogenesis of tick-borne encephalitis.
- Keywords
- TBEV, light-sheet microscopy, neurotropism, organotypic cerebellar slices, reporter viruses, tissue clearing,
- MeSH
- Encephalitis, Tick-Borne * virology MeSH
- Rats MeSH
- Humans MeSH
- Luminescent Proteins genetics metabolism MeSH
- Brain * virology MeSH
- Mice, Inbred C57BL MeSH
- Mice MeSH
- Virus Replication MeSH
- Genes, Reporter MeSH
- Viral Tropism MeSH
- Encephalitis Viruses, Tick-Borne * genetics physiology MeSH
- Imaging, Three-Dimensional MeSH
- Animals MeSH
- Check Tag
- Rats MeSH
- Humans MeSH
- Mice MeSH
- Animals MeSH
- Publication type
- Journal Article MeSH
- Names of Substances
- Luminescent Proteins MeSH
Current standards in vascular reconstruction imply the use of autologous or synthetic material. Despite being standard, autologous grafts are limited by pathologies already affecting the patient and possible complications at the site of explantation, while synthetic grafts carry increased infection risks. Decellularized tissues have gained significant attention due to their potential for improving integration and functionality. The decellularization process removes cellular components while retaining the extracellular matrix, providing a scaffold that supports endothelial cell growth and minimizes immune rejection. Porcine decellularized vena cava is a promising candidate for vascular graft applications due to its structural similarity to human blood vessels and biocompatibility. In this study, we decellularized porcine vena cava with a combination of Triton X-100 and sodium dodecyl sulfate in four hours. We subsequently characterized the wall structure through histological stainings and proteomic analysis. Parameters such as wall thickness, intima-media layers thickness, collagen and elastin area fraction were quantified and compared. Moreover, decellularized veins were repopulated in vitro with human endothelial cells in static and dynamic conditions to verify the adhesion of human cells to the porcine scaffold and fully functionalize the lumen. An in-house-designed bioreactor was developed to seed endothelial cells on the lumen, mimicking the in vivo blood flow.
- Keywords
- Bioreactor repopulation, Decellularization, Histological analysis, Porcine vena cava, Proteomics,
- MeSH
- Bioreactors MeSH
- Decellularized Extracellular Matrix * chemistry MeSH
- Human Umbilical Vein Endothelial Cells cytology MeSH
- Endothelial Cells cytology MeSH
- Extracellular Matrix chemistry MeSH
- Cells, Cultured MeSH
- Humans MeSH
- Swine MeSH
- Tissue Engineering methods MeSH
- Tissue Scaffolds * chemistry MeSH
- Venae Cavae * cytology chemistry MeSH
- Animals MeSH
- Check Tag
- Humans MeSH
- Animals MeSH
- Publication type
- Journal Article MeSH
- Names of Substances
- Decellularized Extracellular Matrix * MeSH
Continuous manufacturing (CM) of solid dosage forms in the pharmaceutical industry offers several advantages over batch processing. The most straightforward CM pathway within the pharmaceutical industry is continuous direct compression (CDC), which consists of three main consecutive steps: loss-in-weight feeding, continuous blending and tableting (die-filling and compaction). However, as the majority of the newly developed APIs are cohesive materials with a mean particle size of < 100 μm, a wide particle size distribution (PSD) and a high tendency to agglomerate, they are difficult to handle on CM lines. In this research paper, the impact of a diverse selection of glidants on the continuous blending unit was assessed. Two cohesive APIs (acetaminophen micronized and metoprolol tartrate) and three different glidants (Aerosil\protect \relax \special {t4ht=®} 200, Aerosil\protect \relax \special {t4ht=®} R972 and Syloid\protect \relax \special {t4ht=®} 244 FP) were included. Via multivariate data analysis, quantitative relationships were established between glidant concentration, blending responses (hold-up mass (HM), bulk residence time (BRT), blender fill fraction (BFF %) and relative standard deviation of the blend uniformity (RSDBU)), blend properties and process settings. The dry-coating of APIs with small quantities of glidants efficiently improved the flowability of cohesive powders, thereby optimizing the gravimetric feeding performance. Dry powder coating of the API altered its bulk properties which affected the bulk properties of the final blend as well as the blending responses (HM, BRT, BFF %). This was mainly attributed to the changes in basic flow energy (BFE), conditioned bulk density (CBD), flowability rate index (FRI) and flow function coefficient (ffc), which are all correlated to HM, BRT and BFF %. It was also observed that glidants did not improve RSDBU during continuous blending within the investigated experimental space. Moreover, adding higher concentrations of glidants can even increase RSDBU due to fluidization segregation and less paddle interactions. However, the overal RSDBU values obtained with the continuous blender were relatively low.
- Keywords
- Continuous blending, Continuous direct compression, Flow enhancers, Formulation development, Glidants, Particle engineering,
- MeSH
- Chemistry, Pharmaceutical methods MeSH
- Technology, Pharmaceutical methods MeSH
- Metoprolol * chemistry MeSH
- Bulk Drugs MeSH
- Acetaminophen chemistry MeSH
- Excipients * chemistry MeSH
- Powders MeSH
- Drug Compounding * methods MeSH
- Tablets chemistry MeSH
- Particle Size MeSH
- Publication type
- Journal Article MeSH
- Names of Substances
- Metoprolol * MeSH
- Bulk Drugs MeSH
- Acetaminophen MeSH
- Excipients * MeSH
- Powders MeSH
- Tablets MeSH
Monitoring cognitive load is critical in diverse, demanding environments, yet conventional assessment methods face limitations in real-time applicability. While machine learning approaches using physiological signals show promise, they often require long data segments, exhibit high computational complexity, or neglect underlying causal dynamics. This paper proposes an efficient framework for cognitive load decoding using causal spatiotemporal patterns derived from multimodal peripheral biosignals. We introduce a novel feature engineering pipeline that transforms short signal segments into image-like representations capturing temporal dynamics via Gramian Angular Difference Fields and Motif Difference Fields, alongside causal interdependencies assessed using forward-backward copula Granger causality networks. These fused multimodal features are classified using a lightweight capsule neural network employing a self-attention routing mechanism. To evaluate the proposed solution, we conducted experiments on two widely used benchmark datasets, WESAD and CLAS. Our model achieved up to 94% accuracy using only 5-second signal segments, and maintained robust performance (84% accuracy) even with 1-second windows, a configuration rarely addressed in prior research. The proposed architecture includes only 323K trainable parameters, offering a favorable balance between model complexity and classification performance. The results confirm the framework's potential for computationally efficient, real-time cognitive load assessment suitable for resource-constrained environments and biofeedback applications.
- Keywords
- Capsule network, Cognitive load, Electrocardiogram, Electrodermal activity, Machine learning, Pattern recognition, Physiology,
- MeSH
- Cognition * physiology MeSH
- Humans MeSH
- Neural Networks, Computer * MeSH
- Signal Processing, Computer-Assisted * MeSH
- Machine Learning MeSH
- Check Tag
- Humans MeSH
- Male MeSH
- Publication type
- Journal Article MeSH
Mass spectrometry-based lipidomics and metabolomics generate extensive data sets that, along with metadata such as clinical parameters, require specific data exploration skills to identify and visualize statistically significant trends and biologically relevant differences. Besides tailored methods developed by individual labs, a solid core of freely accessible tools exists for exploratory data analysis and visualization, which we have compiled here, including preparation of descriptive statistics, annotated box plots, hypothesis testing, volcano plots, lipid maps and fatty acyl chain plots, unsupervised and supervised dimensionality reduction, dendrograms, and heat maps. This review is intended for those who would like to develop their skills in data analysis and visualization using freely available R or Python solutions. Beginners are guided through a selection of R and Python libraries for producing publication-ready graphics without being overwhelmed by the code complexity. This manuscript, along with associated GitBook code repository containing step-by-step instructions, offers readers a comprehensive guide, encouraging the application of R and Python for robust and reproducible chemometric analysis of omics data.
- MeSH
- Mass Spectrometry MeSH
- Humans MeSH
- Lipidomics * methods MeSH
- Metabolomics * methods MeSH
- Programming Languages MeSH
- Software * MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
- Review MeSH
This paper deals with the use of multiple linear regression to predict the viscosity of engine oil at 100 °C based on the analysis of selected parameters obtained by Fourier transform infrared spectroscopy (FTIR). The spectral range (4000-650 cm⁻¹), resolution (4 cm⁻¹), and key pre-processing steps such as baseline correction, normalization, and noise filtering applied prior to modeling. A standardized laboratory method was used to analyze 221 samples of used motor oils. The prediction model was built based on the values of Total Base Number (TBN), fuel content, oxidation, sulphation and Anti-wear Particles (APP). Given the large number of potential predictors, stepwise regression was first used to select relevant variables, followed by Bayesian Model Averaging (BMA) to optimize model selection. Based on these methods, a regression relationship was developed for the prediction of viscosity at 100 °C. The calibration model was subsequently validated, and its accuracy was determined using the Root Mean Squared Error (RMSE) metric, it was 0.287. Finally, the obtained model was used to predict the lifetime of engine oil in diesel engines operating under severe conditions.
- Publication type
- Journal Article MeSH
Herein, we report a nickel-catalyzed tandem cyclization-coupling method for the regioselective synthesis of 1-methyleneindenes and benzofulvenes from 1-(2,2-dibromovinyl)-2-alkynylbenzenes and aryl boronic acids. The transformation proceeds in the presence of a suitable ligand and base, enabling sequential activation of the C─Br bonds and intra-molecular alkyne moiety under relatively mild reaction conditions with yields 72%-85%. This robust protocol offers wide range of functional group tolerance in substrate and boronic acid part. Density functional theory (DFT) calculations, in addition, provide thorough mechanistic insights that point to a tandem process of oxidative addition, migratory insertion, and reductive elimination, with key energetic preferences explaining the observed product selectivity.
- Publication type
- Journal Article MeSH
Proteolysis is a crucial step in both bottom-up and structural proteomics workflows, directly influencing peptide identification and sequence coverage in mass spectrometry-based analyses. While classical proteomics typically relies on highly specific enzymes with well-defined cleavage patterns, structural MS approaches such as hydrogen/deuterium exchange mass spectrometry (HDX-MS) often employ nonspecific or semispecific proteases, producing complex peptide mixtures that require more detailed digestion analysis. To address these needs and streamline the entire process, we developed DigDig, a standalone, Java-based software tool for evaluating and comparing proteolytic digestion across diverse experimental conditions. DigDig processes output files from common search engines and provides customizable visualizations of key digestion metrics, including sequence coverage, reproducibility, peptide redundancy, cleavage site preferences, and peptide length distributions. A distinguishing feature is its ability to detect and report repetitive peptide sequences, which are frequently missed by standard tools. We demonstrate its capabilities using data sets from both specific and nonspecific digestions, highlighting its utility in digestion quality control, protease characterization, and method development, particularly in HDX-MS workflows. DigDig is freely available at https://peterslab.org/DigDig/.
- Publication type
- Journal Article MeSH
Regenerative medicine has gained significant attention due to its diverse strategies for tissue restoration and restructuring. This therapeutic approach combines knowledge from cellular biology, tissue engineering, and translational medicine, providing new hope for treating conditions that previously lacked definitive therapeutic options. Although natural tissue regeneration occurs in some organs, such as the liver, and in superficial epidermal injuries, this process is limited. Tissue regeneration involves replacing damaged cells with cells of the same type, fully restoring tissue structure and function, while healing often results in scar tissue that may not have the same functional properties. Given this limitation, regenerative medicine aims to enhance the body's regenerative capacity. The manipulation of growth factors, such as platelet-derived growth factor and vascular endothelial growth factor, has been shown to increase vascularization and cell proliferation. Autologous fat grafting has emerged as a vital tool in regenerative medicine, demonstrating efficacy in promoting tissue regeneration due to its rich composition of mesenchymal stem cells and growth factors. Case studies illustrate that lipografting can improve wound healing in patients with chronic ulcers and contribute to aesthetic and functional outcomes in breast reconstruction. This study reports a case of a 27-year-old male who sustained severe trauma to his left hand in a car accident, resulting in complex injuries. Despite the potential for amputation, the decision was made to preserve the limb. A series of surgical interventions, including necrotic tissue debridement and lipografting, were conducted over several weeks, resulting in significant tissue regeneration. By the fifth week, the wound bed exhibited adequate granulation tissue, and a skin graft was applied, demonstrating successful integration and functional recovery. This case underscores the potential of regenerative medicine techniques, specifically lipografting, in limb salvage and tissue repair. Further research is needed to enhance understanding and application of these strategies in treating complex wounds and improving patient outcomes.
- Keywords
- Wound healing, fat grafting, limb salvage, regenerative medicine,
- MeSH
- Adult MeSH
- Wound Healing MeSH
- Humans MeSH
- Regenerative Medicine * methods MeSH
- Adipose Tissue * transplantation MeSH
- Limb Salvage * methods MeSH
- Check Tag
- Adult MeSH
- Humans MeSH
- Male MeSH
- Publication type
- Journal Article MeSH
- Case Reports MeSH
Light-responsive proteins are involved in a wide range of essential physiological processes in bacteria, plants, and animals. Engineered light-responsive proteins have also emerged as prospective tools in biotechnology and biomedicine. These proteins are often characterized by short-lived lit states and the need for continuous illumination to reach photostationary states. Therefore, developing methods for studying light-responsive proteins and their interactions under illumination represents an important research goal. Here, we report on a novel front-illuminated surface plasmon resonance (fiSPR) biosensor for monitoring interactions involving light-responsive proteins. The fiSPR biosensor combines the optical platform based on the Kretschmann geometry with advanced transparent microfluidics and an additional light module, enabling in situ illumination of the liquid sample in contact with the SPR chip. We apply the fiSPR biosensor to study the blue light-responsive transcription factor EL222, which recovers to the dark state in a few seconds and plays an important role in the optogenetic control of gene expression. Specifically, we determine the rate and equilibrium constants for EL222 dimerization and DNA binding. The results support the hypothesis that EL222 dimerizes prior to binding DNA. In addition, we provide evidence of the interaction between an interleukin receptor modified with a photocaged tyrosine (IL-20R2-Y70NBY) and its cytokine ligand (IL-24) only upon UV illumination. Overall, this study demonstrates the versatility of the developed fiSPR biosensor for monitoring biomolecular interactions involving both natural and engineered light-responsive proteins, particularly those featuring short lit-state lifetimes.
- Keywords
- Non-canonical amino acids, Photosensory proteins, Protein–DNA interactions, Protein–protein interactions, Surface plasmon resonance,
- Publication type
- Journal Article MeSH
