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Evaluation of the therapeutic effects of the topical and systemic forms of Honokiol in 5-fluorouracil-induced oral mucositis model in rats
Reticular Structural Diversification of Zirconium Metal–Organic Frameworks Through Angular Ligand Configuration Control
Comparative phytochemical and biological evaluation of Egyptian Swinglea glutinosa stems and leaves
Abstract The hydroalcoholic extracts of both stems and leaves of Egyptian Swinglea glutinosa have been evaluated for their biological activities and phytochemical profiling. LC–MS/MS assists in identifying 80 phytoconstituent compounds that alternate between the stem and leaves, the majority of which are new to the genus. Biological investigation results revealed the superiority of stem extract in inhibiting α-amylase and α-glucosidase enzymes scoring IC50 (15.32 ± 0.76) and (0.656 ± 0.03) over the leaves extract, which gives IC50 (112.1 ± 5.55) and (2.721 ± 0.13) respectively at (P < 0.05) and when compared to the antidiabetic standard acarbose it shows better result than it in inhibiting α-amylase and to close to it in inhibiting α-glucosidase enzymes which later score IC50 (27.2 ± 1.35)and (0.375 ± 0.02) at (P < 0.05). Stem extract also shows good inhibitory activity on acetylcholinesterase enzymes compared to standard donepezil, and that was supported by results of intermolecular docking for six compounds (2-Deoxy-2,3-dehydro-N-acetyl-neuraminic acid (DANA), ascorbic acid, glucuronic acid, protocatechuic acid, galacturonic acid, gallic acid) which only identified in stem extract. All of them show high fitting scores and strong binding interactions. Moreover, among tested compounds, DANA, ascorbic acid, and glucuronic acid have the highest-ranking scores against all target enzymes. Highly fitting and binding scores by DANA were remarkably noticed, and the molecular dynamic simulation study proved the effect of DANA against the α-amylase enzyme via decreasing the fluctuations of the enzyme’s amino acid residues due to the stabilization of enzyme-ligand complex.
3-Selective Pyridine Fluorination via Zincke Imine Intermediates
Early hemodynamic differences between generalized and focal epilepsy measured by photoplethysmography
Concentration Energy Ion Channels with Molecular-Structure Dual Recognition for Sustainable Environmental Monitoring
A ZnO-TiO2-Amygdalin nanocomposite for bone regeneration and antimicrobial activity
2D versus 3D tumor-on-chip models to study the impact of tumor organization on metabolic patterns in vitro
Abstract Despite the limitations of in vitro models to investigate cancer cell metabolism, their study can provide new insights essential for understanding tumorigenesis and effectively aiding in the development of novel therapies. The innovative tumor-on-chip models offer a more physiologically relevant platform than the traditional 2D cultures. These 3D cultures incorporate cell–cell and cell–matrix interactions, as well as diffusion dynamics through both the matrix and tumor spheroid, modeling in vivo diffusion within the tumor. Therefore, this work focuses on a quantitative comparison between 2D and 3D cultures through a microfluidic chip that allows daily monitoring of cancer cell key metabolites such as glucose, glutamine and lactate, unveiling critical differences. Our analysis reveals reduced proliferation rates in 3D models, likely due to limited diffusion of nutrients and oxygen. Additionally, 3D cultures showed distinct metabolic profiles, including elevated glutamine consumption under glucose restriction and higher lactate production, indicating an enhanced Warburg effect. The microfluidic chip enabled continuous monitoring, revealing increased per-cell glucose consumption in 3D models, highlighting fewer but more metabolically active cells than in 2D cultures. These findings underscore the importance of using microfluidic-based 3D models to provide a more accurate representation of tumor metabolism and progression compared to traditional 2D cultures.
Carbon Nanotubes for Rechargeable Na/Cl<sub>2</sub> Batteries
Automated interpretation of cardiotocography using deep learning in a nationwide multicenter study
Abstract Timely detection of abnormal cardiotocography (CTG) during labor plays a crucial role in enhancing fetal prognosis. Recent research has explored the use of deep learning for CTG interpretation, most studies rely on small, localized datasets or focus on outcomes less relevant to clinical practice. To address these limitations, we developed a clinically applicable model using a large-scale, nationwide CTG dataset with reliable annotations provided by a board-certified obstetrician. Our study utilized 22,522 deliveries from 14 hospitals, each including cardiotocography (CTG) recordings of up to 75 min in length. The CTG signals were segmented into 5-minute intervals, resulting in a total of 519,800 person-minutes of analyzed data. We trained and validated a deep learning model based on CTG segments for classifying normal and abnormal CTGs. In the independent test dataset, the model achieved an AUC (area under the receiver operating characteristic curve) of 0.880 and PRC (area under the precision-recall curve) of 0.625 in internal tests. External tests across three datasets achieved AUCs of 0.862, 0.895, and 0.862 and PRCs of 0.553, 0.615, and 0.601. Our study results show the potential of the deep learning for automated CTG interpretation. We will evaluate this model in future prospective studies to assess the model’s clinical applicability.
Harnessing Dynamic Supramolecular Interactions for Lanthanide Detection via Computational Pattern Recognition of Magnetic Resonance Fingerprints
Uncertainty analysis of initial orbit determination in the minimum radar admissible region
Genome Mining of Isoindolinone-Containing Peptide Natural Products
Crosstalk of injured podocytes with parietal epithelial cells through Wnt4/β-Catenin signaling
Abstract Focal segmental glomerular sclerosis (FSGS) is considered an irreversible lesion in kidney disease. Here, we investigated the role of the wnt4/β-Catenin signaling pathway in FSGS lesion formation and the crosstalk between PECs and podocytes in a transgenic FSGS rat model and human primary FSGS to explore potential sex-specific differences and therapeutic options. After model induction in rats, we observed strong podocytes loss on day 7, which was significantly higher in male than in female rats. Starting at d14, both glomerular mRNA and protein expression of Wnt4 were increased, but more pronounced in males. Wnt4 was localized to podocytes and β-Catenin to Pax8-positive lesions. The Wnt4 target gene CD44 was strongly upregulated on d7 and increased until the end of the experiment (d42). In cell culture, we confirmed that injured podocytes expressed and secreted Wnt4, which stimulated the expression of the Wnt target gene Axin2 in PECs but not in podocytes. Wnt4/β-Catenin pathway activation was confirmed in human biopsies with podocytopathic FSGS. In conclusion, the canonical Wnt/β-Catenin axis plays a critical role in the crosstalk between PECs and injured podocytes. Furthermore, sex-specific differences in podocyte injury and regeneration appear to be, at least in part, Wnt4-mediated.