Explore the vast range of titles available.

Understanding the complex dynamics of HIV/AIDS transmission requires models that capture real-world progression and intervention impacts. This study introduces an innovative mathematical framework using fractal-fractional calculus to analyze HIV/AIDS dynamics, emphasizing memory effects and nonlocal interactions critical to disease spread. By dividing populations into four distinct compartments-susceptible individuals, infected individuals, those undergoing treatment, and individuals in advanced AIDS stages-the model reflects key phases of infection and therapeutic interventions. Unlike conventional approaches, the proposed nonlinear transmission function, , accounts for varying infectivity levels across stages (where is the total population and denotes the effective contact rate), offering a nuanced view of how treatment efficacy ( ) and progression to AIDS ( ) shape transmission. The analytical framework combines rigorous mathematical exploration with practical insights. We derive the basic reproduction number to assess outbreak potential and employ Lyapunov theory to establish global stability conditions. Using the Schauder fixed-point theorem, we prove the existence and uniqueness of solutions, while bifurcation analysis via center manifold theory reveals critical thresholds for disease persistence or elimination. We use a computational scheme that combines the Adams-Bashforth method with an interpolation-based correction technique to ensure numerical precision and confirm theoretical results. Sensitivity analysis highlights medication accessibility and delaying the spread of AIDS as a vital control strategy by identifying ( ) and ( ) as critical parameters. The numerical simulations illustrate the predictive ability of the model, which shows how fractal-fractional order affects outbreak trajectories and long-term disease burden. The framework outperforms conventional integer order models and produces more accurate epidemiological predictions by integrating memory-dependent transmission with fractional order flexibility. These findings demonstrate the model’s value in developing targeted public health initiatives, particularly in environments with limited resources where disease monitoring and balancing treatment allocation is essential. In the end, our work provides a tool to better predict and manage the evolving challenges of HIV/AIDS by bridging the gap between theoretical mathematics and actual disease control.

Fractional differential equations offer a natural framework for describing systems in which present states are influenced by the past. This work presents a nonlinear Caputo-type fractional differential equation (FDE) with a nonlocal initial condition and attempts to describe a model of memory-dependent behavioral adaptation. The proposed framework uses a fractional-order derivative η∈(0,1) to discuss the long-term memory effects. The existence and uniqueness of solutions are demonstrated by Banach’s and Krasnoselskii’s fixed-point theorems. Stability is analyzed through Ulam–Hyers and Ulam–Hyers–Rassias benchmarks, supported by sensitivity results on the kernel structure and fractional order. The model is further employed for behavioral despair and learned helplessness, capturing the role of delayed stimulus feedback in shaping cognitive adaptation. Numerical simulations based on the convolution-based fractional linear multistep (FVI–CQ) and Adams–Bashforth–Moulton (ABM) schemes confirm convergence and accuracy. The proposed setup provides a compact computational and mathematical paradigm for analyzing systems characterized by nonlocal feedback and persistent memory.

Two-terminal memory elements, or memelements, capable of co-locating signal processing and memory via history-dependent reconfigurability at the nanoscale are vital for next-generation computing materials striving to match the brain’s efficiency and flexible cognitive capabilities. While memory resistors, or memristors, have been widely reported, other types of memelements remain underexplored or undiscovered. Here we report the first example of a volatile, voltage-controlled memcapacitor in which capacitive memory arises from reversible and hysteretic geometrical changes in a lipid bilayer that mimics the composition and structure of biomembranes. We demonstrate that the nonlinear dynamics and memory are governed by two implicitly-coupled, voltage-dependent state variables—membrane radius and thickness. Further, our system is capable of tuneable signal processing and learning via synapse-like, short-term capacitive plasticity. These findings will accelerate the development of low-energy, biomolecular neuromorphic memelements, which, in turn, could also serve as models to study capacitive memory and signal processing in neuronal membranes. Two-terminal memory elements hold promise to store and process information via history-dependent material configurations at low-energy cost. Here, Najem et al . show a voltage-controlled capacitive memory due to reversible geometrical changes in a lipid bilayer capable of learning via synapse-like plasticity.

Memory loss is a manifestation of type 1 diabetes mellitus (T1DM)-induced brain damage resulting from hyperglycemia. However, the mechanism underlying T1DM-induced memory deficit remains largely unknown. In diabetes, ketogenesis occurs upon insulin deficiency, and β-hydroxybutyrate (β-OHB) is synthesized and plays a dominant role in diabetic ketoacidosis. In the present study, we investigate the effect of β-OHB-mediated lysine β-hydroxybutyrylation (kbhb) of hippocampal calcium/calmodulin-dependent kinase II-α (CaMKII-α) on memory deficits in male T1DM mice. We find that streptozotocin (STZ) induced a significant increase in the concentration of hippocampal β-OHB in T1DM mice. High β-OHB levels promote CaMKII-α kbhb at the K42 and K267 residues and further inhibit CaMKII activity. The suppression of CaMKII-α kbhb in the hippocampus via the inhibition of P300, a kbhb transferase, reverse the decrease in CaMKII activity and alleviate memory deficits in T1DM mice. Molecular dynamics (MD) simulations further reveale that the enhanced flexibility caused by CaMKII-α kbhb on the critical, conserved residue K42, which alters its side chain, in the catalytic ATP-binding site of this enzyme may be one of the factors responsible for the observed reduction enzymatic activity. Collectively, our results show that a high β-OHB concentration dysregulates hippocampal CaMKII-α kbhb, which may contribute to memory deficits in T1DM mice. The level of β-OHB markedly enhances kbhb of hippocampal CaMKII-α at the K42 and K267 residues, which suppresses CaMKII activity, leading to memory impairment in T1DM mice.

The development and assessment of subgrid-scale (SGS) models for large-eddy simulations of the atmospheric boundary layer is an active research area. In this study, we compare the performance of the classical Smagorinsky model, the Lagrangian-averaged scale-dependent (LASD) model, and the anisotropic minimum dissipation (AMD) model. The LASD model has been widely used in the literature for 15 years, while the AMD model was recently developed. Both the AMD and the LASD models allow three-dimensional variation of SGS coefficients and are therefore suitable to model heterogeneous flows over complex terrain or around a wind farm. We perform a one-to-one comparison of these SGS models for neutral, stable, and unstable atmospheric boundary layers. We find that the LASD and the AMD models capture the logarithmic velocity profile and the turbulence energy spectra better than the Smagorinsky model. In stable and unstable boundary-layer simulations, the AMD and LASD model results agree equally well with results from a high-resolution reference simulation. The performance analysis of the models reveals that the computational overhead of the AMD model and the LASD model compared to the Smagorinsky model is approximately 10% and 30% respectively. The LASD model has a higher computational and memory overhead because of the global filtering operations and Lagrangian tracking procedure, which can result in bottlenecks when the model is used in extensive simulations. These bottlenecks are absent in the AMD model, which makes it an attractive SGS model for large-scale simulations of turbulent boundary layers.

Purpose This paper aims to study the energy ratios of plane waves on an interface of nonlocal thermoelastic halfspace (NTS) and nonlocal orthotropic piezothermoelastic half-space (NOPS). Design/methodology/approach The memory-dependent derivatives (MDDs) approach with a hyperbolic two-temperature (HTT), three-phase lag theory is used here to study how the energy ratios change at the interface with the angle of incidence. Findings Plane waves that travel through NTS and hit the interface as a longitudinal wave, a thermal wave, or a transversal wave send four waves into the NOPS medium and three waves back into the NTS medium. The amplitude ratios of the different waves that are reflected and transmitted are used to calculate the energy ratios of the waves. It is observed that these ratios are affected by the HTT, nonlocal and MDD parameters. Research limitations/implications The energy ratios correspond to four distinct models; nonlocal HTT with memory, nonlocal HTT without memory, local HTT with memory and nonlocal classical-two-temperature with memory concerning the angle of incidence from 0 degree to 90 degree. Practical implications This model applies to several fields, including earthquake engineering, soil dynamics, high-energy particle physics, nuclear fusion, aeronautics and other fields where nonlocality, MDD and conductive temperature play an important role. Originality/value The authors produced the submitted document entirely on their initiative, with equal contributions from all of them.

The activation of the dodecameric Ca2+/calmodulin dependent kinase II (CaMKII) holoenzyme is critical for memory formation. We now report that CaMKII has a remarkable property, which is that activation of the holoenzyme triggers the exchange of subunits between holoenzymes, including unactivated ones, enabling the calcium-independent phosphorylation of new subunits. We show, using a single-molecule TIRF microscopy technique, that the exchange process is triggered by the activation of CaMKII, and that exchange is modulated by phosphorylation of two residues in the calmodulin-binding segment, Thr 305 and Thr 306. Based on these results, and on the analysis of molecular dynamics simulations, we suggest that the phosphorylated regulatory segment of CaMKII interacts with the central hub of the holoenzyme and weakens its integrity, thereby promoting exchange. Our results have implications for an earlier idea that subunit exchange in CaMKII may have relevance for information storage resulting from brief coincident stimuli during neuronal signaling. How do fleeting signals passing through the neurons of our brains become memories that can last for years or even decades? An enzyme called CaMKII is known to have an important role in the formation of memories. CaMKII adds phosphate groups to proteins—a process that is called phosphorylation—and is itself activated when calcium levels increase inside the neurons where the enzyme is found. Individual CaMKII proteins bind together in groups of 12 to form a ‘holoenzyme’. When one of the 12 subunits is activated by calcium, it can phosphorylate the other subunits in the same holoenzyme. Once this happens, the activation of CaMKII can continue after the initial rise in calcium has ceased, and this effect is thought to be involved in the formation of long-term memories. 30 years ago, Francis Crick—famous for his role in the discovery of the double helix—proposed that memory formation might involve ‘memory-storage molecules’ passing an activated state to unactivated molecules, and John Lisman later suggested that CaMKII could fulfil this role by swapping subunits of holoenzymes between activated and unactivated ones. Now, Stratton, Lee et al. have tested whether CaMKII can exchange subunits by using advanced microscopy to track single molecules of CaMKII labelled with fluorescent markers. This revealed that activation can cause CaMKII subunits repeatedly to mix between holoenzymes—and this only happens once a first holoenzyme has been activated. Subunits of CaMKII join together via a central ‘hub’ region, but when a subunit is activated, the phosphorylated segment may interact with the hub. This weakens the connections between the subunits, thereby making it easier for subunits to exchange between holoenzymes. This process provides a mechanism by which a level of activated CaMKII can be maintained, even if some subunits become degraded and long after the disappearance of the initial activation signal.

Background Type 2 diabetes mellitus (T2DM) induced diabetes-associated cognitive dysfunction (DACD) that seriously affects the self-management of T2DM patients, is currently one of the most severe T2DM-associated complications, but the mechanistic basis remains unclear. Mitochondria are highly dynamic organelles, whose function refers to a broad spectrum of features such as mitochondrial dynamics, mitophagy and so on. Mitochondrial abnormalities have emerged as key determinants for cognitive function, the relationship between DACD and mitochondria is not well understood. Methods Here, we explored the underlying mechanism of mitochondrial dysfunction of T2DM mice and HT22 cells treated with high glucose/palmitic acid (HG/Pal) focusing on the mitochondrial fission-mitophagy axis with drug injection, western blotting, Immunofluorescence, and electron microscopy. We further explored the potential role of caveolin-1 (cav-1) in T2DM induced mitochondrial dysfunction and synaptic alteration through viral transduction. Results As previously reported, T2DM condition significantly prompted hippocampal mitochondrial fission, whereas mitophagy was blocked rather than increasing, which was accompanied by dysfunctional mitochondria and impaired neuronal function. By contrast, Mdivi-1 (mitochondrial division inhibitor) and urolithin A (mitophagy activator) ameliorated mitochondrial and neuronal function and thereafter lead to cognitive improvement by inhibiting excessive mitochondrial fission and giving rise to mitophagy, respectively. We have previously shown that cav-1 can significantly improve DACD by inhibiting ferroptosis. Here, we further demonstrated that cav-1 could not only inhibit mitochondrial fission via the interaction with GSK3β to modulate Drp1 pathway, but also rescue mitophagy through interacting with AMPK to activate PINK1/Parkin and ULK1-dependent signlings. Conclusions Overall, our data for the first time point to a mitochondrial fission-mitophagy axis as a driver of neuronal dysfunction in a phenotype that was exaggerated by T2DM, and the protective role of cav-1 in DACD. Graphical Abstract Graphic Summary Illustration. In T2DM, excessive mitochondrial fission and impaired mitophagy conspire to an altered mitochondrial morphology and mitochondrial dysfunction, with a consequent neuronal damage, overall suggesting an unbalanced mitochondrial fission-mitophagy axis. Upon cav-1 overexpression, GSK3β and AMPK are phosphorylated respectively to activate Drp1 and mitophagy-related pathways (PINK1 and ULKI), ultimately inhibits mitochondrial fission and enhances mitophagy. In the meantime, the mitochondrial morphology and neuronal function are rescued, indicating the protective role of cav-1 on mitochondrial fission-mitophagy axis. 4fVNd5UMHP9GEmZKs4s8VH Video Abstract

Purpose This paper addresses a significant research gap in the study of Rayleigh surface wave propagation within a piezoelectric medium characterized by piezoelectric properties, thermal effects and voids. Previous research has often overlooked the crucial aspects related to voids. This study aims to provide analytical solutions for Rayleigh waves propagating through a medium consisting of a nonlocal piezo-thermo-elastic material with voids under the Moore–Gibson–Thompson thermo-elasticity theory with memory dependencies. Design/methodology/approach The analytical solutions are derived using a wave-mode method, and roots are computed from the characteristic equation using the Durand–Kerner method. These roots are then filtered based on the decay condition of surface waves. The analysis pertains to a medium subjected to stress-free and isothermal boundary conditions. Findings Computational simulations are performed to determine the attenuation coefficient and phase velocity of Rayleigh waves. This investigation goes beyond mere calculations and examines particle motion to gain deeper insights into Rayleigh wave propagation. Furthermore, this investigates how kernel function and nonlocal parameters influence these wave phenomena. Research limitations/implications The results of this study reveal several unique cases that significantly contribute to the understanding of Rayleigh wave propagation within this intricate material system, particularly in the presence of voids. Practical implications This investigation provides valuable insights into the synergistic dynamics among piezoelectric constituents, void structures and Rayleigh wave propagation, enabling advancements in sensor technology, augmented energy harvesting methodologies and pioneering seismic monitoring approaches. Originality/value This study formulates a novel governing equation for a nonlocal piezo-thermo-elastic medium with voids, highlighting the significance of Rayleigh waves and investigating the impact of memory.

In susceptible individuals, overwhelming traumatic stress often results in severe abnormalities of memory processing, manifested either as the uncontrollable emergence of memories (flashbacks) or as an inability to remember events (dissociative amnesia, DA) that are usually, but not necessarily, related to the stressful experience. These memory abnormalities are often the source of debilitating psychopathologies such as anxiety, depression and social dysfunction. The question of why memory for some traumatic experiences is compromised while other comparably traumatic experiences are remembered perfectly well, both within and across individuals, has puzzled clinicians for decades. In this article, we present clinical, cognitive, and neurobiological perspectives on memory research relevant to DA. In particular, we examine the role of state dependent memory (wherein memories are difficult to recall unless the conditions at encoding and recall are similar), and discuss how advances in the neurobiology of state-dependent memory (SDM) gleaned from animal studies might be translated to humans.