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Zinc and copper metallic instability: Investigating altered metal functionality in both human and animal studies
(Springer Nature, 2026) Bhardwaj, Nidhi; Bhardwaj, Vandna; Choudhary, Ambika; Choudhary, Monika; Bhardwaj, Indu; Dulta, Kanika; Nagraik, Rupak; Ravi, Karthikeyan; Sharma, Avinash; Aman, Junaid
Homeostasis is the regulatory mechanism for the expression of all genes, the function of all metabolic pathways, the utilization of any essential trace element (TEs), while its disruptions lead to many pathological states. The pathologies include cardiovascular disease, anaemia, diabetes, neurological disorders, and cell death. For this, copper and zinc are two of the major TEs involved in controlling the physiological and pathological processes in both humans and animals. Zinc deficiency, for instance, is linked with decreased body weight, decreased ability to metabolize glucose, and impaired immune function. By contrast, deficiency of copper can lead to several neurological disorders, oxidative stress, mitochondrial dysfunction, and changes in lipid metabolism. On the other hand, there excessive exposure can have adverse effects on health, including the development of epilepsy, neuronal excitability, genotoxic effects, and cellular toxicity. Moreover, dual biological functions of zinc further complicate the understanding of their roles in both health and disease. Such as, zinc has a neuromodulatory function and helps to control excitably in neurons, but sometimes zinc in the synapse, inhibit the functioning of inhibitory neurotransmitter and cause damage to the neurons. Likewise, in metabolic diseases, particularly diabetes mellitus, there is often dysregulation of the levels of zinc and copper, resulting in steel-like interactions; elevated levels of copper and reduced levels of zinc contribute towards the pathogenesis of both the disease and the progression of dementia. Despite this antagonistic relationship, both trace metals act synergistically as necessary derivatives of superoxide dismutase; therefore, both play a vital role in maintaining cellular antioxidant defense systems. Therefore, this review covers published articles from 1992-2025 with regard to zinc and copper in their dietary and nanoparticle forms in animal and human models to demonstrate their differing roles and how they complement one another, or conflict with one another.Graphical AbstractA graphical summary of the percentage of publications (A), as well as the mechanism of neurotransmission by zinc ions (B), and the regulation of Zn2+ and Cu+ ions in both humans and animals, through either positive (regulation) or negative (regulation) pathways (C).
Comparative study on the wear resistance of C&B-type polymer materials for temporary crowns manufactured using 3D DLP printing technology
(MDPI, 2025) Firlej, Marcel; Pieniak, Daniel; Snarski-Adamski, Andrzej; Biedziak, Barbara; Niewczas, Agata; Petrů, Jana; Matijošius, Jonas; Krzysiak, Zbigniew; Zaborowicz, Katarzyna
DLP (Digital Light Processing) 3D printing enables precise fabrication of temporary crowns. Tribological properties of these materials affect clinical durability, wear resistance, and masticatory function. This study compared three C&B-type photopolymers for DLP-printed temporary crowns: Gr-17.1 temporary It, Gr-17 temporary (Pro3dure), and VarseoSmile Temp (BEGO). Samples were printed, post-processed, and polished. Surface topography (Sa, Sz) was measured via white light interferometry, and scratch resistance was evaluated with a Rockwell indenter. Sliding wear tests under wet conditions (37 degrees C, 90% RH) were conducted using an SRV 4 tester at 25 N for 20,000 cycles. VarseoSmile Temp showed the highest scratch and sliding wear resistance, with the lowest mean volumetric wear (0.025 mm(3)) and residual scratch depth, reflecting its higher inorganic filler content (30-50 wt%). Gr-17.1 had the most stable coefficient of friction (similar to 0.3), while Gr-17 experienced the greatest wear (0.235 mm(3)). No direct correlation between friction and wear was observed. These findings indicate that wear resistance depends on microstructure and filler content, supporting tribological testing as a tool to evaluate the durability of 3D-printed temporary crowns.
Photoexcited species localize on solvent-accessible fluorophore-rich domains inside carbon dots
(Elsevier, 2026) Langer, Michal; Zdražil, Lukáš; Rogach, Andrey L.; Osella, Silvio; Otyepka, Michal
Understanding the optical properties of luminescent carbon dots (CDs) at the electronic level is essential for engineering their light-responsive behavior. The localization of photoexcited species and the pathways of their de-excitation govern CD performance in sensing, bioimaging, and emerging photocatalytic applications. Yet, the underlying mechanisms remain unresolved. Here, we combine multiscale simulations with experiments on CDs synthesized from citric acid (CA) and ethylenediamine (EDA), precursors capable of forming the molecular fluorophore 5-oxo-1,2,3,5-tetrahydroimidazo[1,2-alpha]pyridine-7-carboxylic acid (IPCA). All-atom molecular dynamics simulations in water reveal that CA-EDA oligomeric condensation products containing IPCA units spontaneously assemble into dynamic similar to 2 nm nanoparticles with amorphous internal structures and stacked domains reminiscent of those observed in transmission electron microscopy images of CDs. Time-dependent density functional theory (TD-DFT) calculations show that photoexcited carriers are generated in these domains and remain spatially distributed, not confined to the CD core. Quenching experiments with Hg2+ confirm their accessibility to the environment. We therefore propose a structural model of fluorophore-rich domains embedded in an amorphous carbonaceous matrix, explaining the quasi-spherical morphology and characteristic blue photoluminescence. This model provides a mechanistic basis for fluorescence sensing and photocatalysis and establishes a framework for rational design of CDs with tailored photophysical and catalytic properties.
Cross-coupling reactions with nickel, visible light, and tert-butylamine as a bifunctional additive
(American Chemical Society, 2024) Düker, Jonas; Philipp, Maximilian; Lentner, Thomas; Cadge, Jamie A.; Lavarda, João E.A.; Gschwind, Ruth M.; Sigman, Matthew S.; Ghosh, Indrajit; König, Burkhard
Transition metal catalysis is crucial for the synthesis of complex molecules, with ligands and bases playing a pivotal role in optimizing cross-coupling reactions. Despite advancements in ligand design and base selection, achieving effective synergy between these components remains challenging. We present here a general approach to nickel-catalyzed photoredox reactions employing tert-butylamine as a cost-effective bifunctional additive, acting as the base and ligand. This method proves effective for C-O and C-N bond-forming reactions with a diverse array of nucleophiles, including phenols, aliphatic alcohols, anilines, sulfonamides, sulfoximines, and imines. Notably, the protocol demonstrates significant applicability in biomolecule derivatization and facilitates sequential one-pot functionalizations. Spectroscopic investigations revealed the robustness of the dynamic catalytic system, while elucidation of structure-reactivity relationships demonstrated how computed molecular properties of both the nucleophile and electrophile correlated to reaction performance, providing a foundation for effective reaction outcome prediction.
Federated-reinforcement learning-assisted IoT consumers system for kidney disease images
(IEEE, 2024) Mohammed, Mazin Abed; Lakhan, Abdullah; Abdulkareem, Karrar Hameed; Deveci, Muhammet; Dutta, Ashit Kumar; Memon, Sajida; Marhoon, Haydar Abdulameer; Martinek, Radek
The number of people with kidney disease rises every day for many reasons. Many existing machine-learning-enabled mechanisms for processing kidney disease suffer from long delays and consume much more resources during processing. In this paper, the study shows how federated and reinforcement learning schemes can be used to develop the best delay scheme. The scheme must optimize both the internal and external states of reinforcement learning and the federated learning fog cloud network. This work presents the Adaptive Federated Reinforcement Learning-Enabled System (AFRLS) for Internet of Things (IoT) consumers' kidney disease image processing. The main relationship between IoT consumers and kidney image is that the data is collected from different IoT consumer sources, such as ultrasound and X-rays in healthcare clinics. In healthcare applications, kidney urinary tasks reduce the time it takes to preprocess federated learning datasets for training and testing and run them on different fog and cloud nodes. AFRLS decides the scheduling on other nodes and improves constraints based on the decision tree. Based on the simulation results, AFRLS is a new strategy that reduces the time tasks need to be delayed compared to other machine learning methods used in fog cloud networks. The AFRLS improved the delay among nodes by 55%, the delay among internal states by 40%, and the training and testing delay by 51%.