Copper (Cu) has been implicated in the progression of Alzheimer’s disease (AD), and aggregation of Cu and amyloid β peptide (Aβ) are considered key pathological features of AD. Metal chelators are considered to be potential therapeutic agents for AD because of their capacity to reduce metal ion-induced Aβ aggregation through the regulation of metal ion distribution. Here, we used phage display technology to screen, synthesize, and evaluate a novel Cu(II)-binding peptide that specifically blocked Cu-triggered Aβ aggregation. The Cu(II)-binding peptide (S-A-Q-I-A-P-H, PCu) identified from the phage display heptapeptide library was used to explore the mechanism of PCu inhibition of Cu²⁺-mediated Aβ aggregation and Aβ production. In vitro experiments revealed that PCu directly inhibited Cu²⁺-mediated Aβ aggregation and regulated copper levels to reduce biological toxicity. Furthermore, PCu reduced the production of Aβ by inhibiting Cu²⁺-induced BACE1 expression and improving Cu(II)-mediated cell oxidative damage. Cell culture experiments further demonstrated that PCu had relatively low toxicity. This Cu(II)-binding peptide that we have identified using phage display technology provides a potential therapeutic approach to prevent or treat AD.

In order to solve the problem of energy supply for underwater equipment, wireless power transmission technology is becoming a new way of underwater power transmission. It has incomparable technical advantages over traditional power supply method, and can effectively improve the safety, reliability, convenience and concealment of power supply for underwater equipment. The WPT has a natural electrical isolation between the primary and secondary sides to ensure safe charging in an underwater environment. This breakthrough technology greatly facilitates power transmission in the deep sea. However, current transmission power and efficiency levels are not at the level of WPT systems in air. Based on the analysis of the development status of underwater wireless power transmission technology, this paper firstly puts forward the challenges of underwater wireless power transmission, and summarizes the electromagnetic coupler structure, underwater docking mode, compensation topology, control method and eddy current loss. The current research hotspots in the field of underwater wireless power transmission are summarized and analyzed. Finally, according to the development trend of technology, the urgent technical problems in underwater wireless power transmission are expounded.

Parkinson’s disease (PD) is characterized by the presence of Lewy bodies caused by α-synuclein. The imbalance of zinc homeostasis is a major cause of PD, promoting α-synuclein accumulation. ATP13A2, a transporter found in acidic vesicles, plays an important role in Zn²⁺ homeostasis and is highly expressed in Lewy bodies in PD-surviving neurons. ATP13A2 is involved in the transport of zinc ions in lysosomes and exosomes and inhibits the aggregation of α-synuclein. However, the potential mechanism underlying the regulation of zinc homeostasis and α-synuclein accumulation by ATP13A2 remains unexplored. We used α-synuclein-GFP transgenic mice and HEK293 α-synuclein-DsRed cell line as models. The spatial exploration behavior of mice was significantly reduced, and phosphorylation levels of α-synuclein increased upon high Zn²⁺ treatment. High Zn²⁺ also inhibited the autophagy pathway by reducing LAMP2a levels and changing the expression of LC3 and P62, by reducing mitochondrial membrane potential and increasing the expression of cytochrom C, and by activating the ERK/P38 apoptosis signaling pathway, ultimately leading to increased caspase 3 levels. These protein changes were reversed after ATP13A2 overexpression, whereas ATP13A2 knockout exacerbated α-synuclein phosphorylation levels. These results suggest that ATP13A2 may have a protective effect on Zn²⁺-induced abnormal aggregation of α-synuclein, lysosomal dysfunction, and apoptosis.

Battery state of power (SOP) estimation is an important parameter index for electric vehicles to improve battery utilization efficiency and maximize battery safety. Most of the current studies on the SOP estimation of lithium–ion batteries consider only a single constraint and rarely pay attention to the estimation of battery state on different time scales, which can reduce the accuracy of SOP estimation and even cause safety problems. In view of this, this paper proposes a multi-time scale and multi-constraint SOP estimation method for lithium–ion batteries based on H∞ filtering. Firstly, a second-order RC equivalent circuit model is established with a ternary lithium–ion monolithic battery as the research object, and parameter identification is performed by using the recursive least squares method with a forgetting factor. Secondly, the H∞ filtering algorithm is applied to estimate the state of charge (SOC), and then the joint multi-time scale multi-constrained SOC-SOP estimation is performed. Finally, the joint estimation algorithm is validated under UDDS conditions. The mean absolute value relative error (MARE) of SOC estimation is 1.17%, and the MARE of SOP estimation at different time scales is less than 1.6%. The results indicate the high accuracy and strong robustness of the joint estimation method.