Yue Fan

BACKGROUND: Hearing loss (HL) is a prevalent issue among the aging population in China, with significant health and social consequences. Understanding the epidemiological situation and contributing factors to HL in post-pandemic China is critical for developing effective prevention and intervention strategies. METHODS: Information on participants' education level, income, noise exposure, tinnitus history, smoking and drinking habits, COVID-19 infection history, and vaccination status was collected through interviews. Additionally, height and weight were measured on-site and fasting blood samples were drawn for blood glucose and serum lipid level testing. RESULTS: The overall prevalence of HL was 74.82%, while the prevalence of high-frequency HL (HF-HL) was 89.10%. Notably, 21.47% of subjects had HF-HL without standard-frequency HL. Multivariable logistic regression identified age, sex, location, education level, noise exposure, tinnitus, ear disease history, smoking, hypertension, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection history, and lipid levels as potential influencing factors for HL. The relationship between lipid metabolism disorders and hearing is complex; triglycerides (TG) exhibited a protective effect on hearing under certain conditions (e.g., when total cholesterol (TC) was < 5.2 mmol/L and TG ≥ 2.3 mmol/L for standard PTA; TC < 5.2 mmol/L and all TG levels for high-frequency PTA). CONCLUSION: The incidence of hearing loss among older individuals has increased in post-pandemic China. Early identification of at-risk populations, expanded community hearing screening, and public education on hearing health could help more aging individuals prevent hearing decline.

Developing structural materials capable of maintaining integrity under extreme irradiation conditions is a cornerstone challenge for advancing sustainable nuclear energy technologies. The complexity and severity of radiation-induced microstructural changes—spanning multiple length and timescales—pose significant hurdles for purely experimental approaches. This review critically evaluates recent advancements in atomistic modeling, emphasizing its transformative potential to decipher fundamental mechanisms driving microstructural evolution in irradiated alloys. Atomistic simulations, such as molecular dynamics (MD), have successfully unveiled initial defect formation processes at picosecond scales. However, the inherent temporal limitations of conventional MD necessitate advanced methodologies capable of exploring slower, thermally activated defect kinetics. We specifically traced the development of powerful potential energy landscape (PEL) exploration algorithms, which enable the simulation of high-barrier, rare events of defect evolution processes that govern long-term material degradation. The review systematically examines point defect behaviors in various crystal structures—BCC, FCC, and HCP metals—and elucidates their characteristic defect dynamics, respectively. Additionally, it highlights the pronounced effects of chemical complexity in concentrated solid-solution alloys and high-entropy alloys, notably their sluggish diffusion and enhanced defect recombination, underpinning their superior radiation tolerance. Further, the interaction of extended defects with mechanical stresses and their mechanistic implications for material properties are discussed, highlighting the critical interplay between thermal activation and strain rate in defect evolution. Special attention is dedicated to the diverse mechanisms of dislocation–obstacle interactions, as well as the behaviors of metastable grain boundaries under far-from-equilibrium environments. The integration of data-driven methods and machine learning with atomistic modeling is also explored, showcasing their roles in developing quantum-accurate potentials, automating defect analysis, and enabling efficient surrogate models for predictive design. This comprehensive review also outlines future research directions and fundamental questions, paving the way toward autonomous materials’ discovery in extreme environments.

Astragaloside IV (AS-IV) is a bioactive compound derived from Radix Astragali, a traditional Chinese herb widely used as a dietary supplement to enhance immune function. Modern pharmacological studies have demonstrated that AS-IV exhibits anti-inflammatory and immunomodulatory properties. In this study, we investigated the effects of AS-IV on motor dysfunction, microglial polarization, and immune regulation mechanisms in a 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP)-induced Parkinson's disease (PD) mouse model. Our results showed that AS-IV (40 mg/kg) significantly improved motor function in PD mice, as evidenced by reduced descent time in the pole test, increased hanging score in the hanging test, increased stride lengths, and reduced paw angle in the gait test. Furthermore, AS-IV administration attenuated the loss of tyrosine hydroxylase (TH)-positive neurons in the substantia nigra pars compacta (SNpc), promoted microglial polarization from the pro-inflammatory M1 phenotype to the anti-inflammatory M2 phenotype, suppressed the levels of pro-inflammatory cytokines including interleukin-1β (IL-1β), interleukin-6 (IL-6), and tumor necrosis factor-α (TNFα), enhanced the levels of anti-inflammatory cytokines including interleukin-4 (IL-4) and interleukin-10 (IL-10) in the SNpc of PD mice. Mechanistically, AS-IV significantly downregulated the expression and phosphorylation levels of TLR4/p38 (JNK)/NF-κB pathway-related proteins, including Toll-like receptor 4 (TLR4), Myeloid differentiation primary response protein 88 (MyD88), Apoptosis signal-regulating kinase 1 (ASK1), Mitogen-activated protein kinase 3/6 (MKK3/6), Phosphorylated-MKK3/6 (p-MKK3/6), Phosphorylated-mitogen-activated protein kinase 4/7 (p-MKK4/7), p38 mitogen-activated protein kinase (p38), Phosphorylated-p38 (p-p38), c-Jun N-terminal kinase (JNK), Phosphorylated-JNK (p-JNK), nuclear factor kappa-B (NF-κB), and Phosphorylated-NF-κB (p-NF-κB). To further validate the targeting effect of AS-IV, 1 mg/kg of LPS-EB Ultrapure was utilized as a specific TLR4 agonistwe to selectively activated the TLR4/NF-κB signaling pathway without triggering other inflammatory pathways, leading to elevated mRNA levels of TLR4, NF-κB, IL-1β, IL-6, TNFα and protein expression of TLR4, p-JNK, p-p38, p-NF-κB, IL-1β, IL-6, TNFα in the SNpc of PD mice. Importantly, AS-IV pretreatment can't counteract these LPS-EB Ultrapure-triggered effects, demonstrating its dependence on the TLR4/NF-κB signaling pathway. In conclusion, our findings indicate that AS-IV modulates microglial polarization and attenuates neuroinflammation by inhibiting the TLR4/NF-κB pathway, thereby ameliorating motor dysfunction and neuronal loss in PD mice.

In Multiscale Materials Modeling, an enduring vision is to extract the molecular mechanisms governing a certain materials phenomenon of interest in order to predict how the phenomenon will behave at a later time. This goal of predictive simulation has been discussed about a decade ago as a materials research challenge, in the Mesoscale Science Frontier, MSS. To date, it continues to motivate a growing community of computational materials science and technology. Here, we consider several materials phenomena of interest, each well known in their specific areas of application, to note that while molecular dynamics simulation is arguably the most widely used method, MD results have limitations in predicting or explaining the behavior of the phenomenon. For the type of phenomena selected here, we believe that one can raise the issue of whether MD is an appropriate method of molecular simulation in the design and performance testing of complex materials. There exists an alternative to MD, the approach of meta-dynamics simulation based on energy landscape sampling and transition state theory. This approach is notable because it allows predictive molecular simulations over timescales considerably longer than the traditional MD. We are in the process of implementing an enhanced meta-dynamics approach aimed at identifying unknown defect mechanisms, making it particularly well-suited for investigating the deformation processes in engineering alloys at timescales relevant to laboratory measurements of component performance and durability assurance. Our motivation is that such simulation capabilities will find many materials-centric applications. One such application is known as plasma-materials interactions, PMI. In PMI, the phenomenon of nuclear irradiation damage has been a practical challenge, relevant to both nuclear fission and fusion power generation systems. For the present perspective, we will focus on the use of meta-dynamics simulations in collaboration with the research activities at an academic fusion research center.

Contrary to oxide or polymeric glasses, metallic glasses are infamously known for their relatively limited thermal stability, which is often characterized by their narrow supercooled liquid regions. Nonetheless, we successfully fabricated metallic-glass based nanomembranes with an ultrahigh thermal ability by a polymer surface buckling enabled exfoliation technique. These nanomembranes exhibit a distinctive nanostructure with nanosized metallic-glasses encapsulated within an interconnected nanoamorphous-oxide network. Due to a pronounced nanoconfinement effect, crystallization is significantly suppressed. Consequently, these oxidized metallic-glass nanomembranes initiate a glass transition at 324 K at a heating rate of 10 K/min. Remarkably, they also showcase an expansive supercooled liquid region of 448 K, surpassing various metallic and oxide glasses reported. Furthermore, these nanomembranes not only exhibit a low elastic modulus but also achieve superplasticity even at room temperature. This unique blend of thermomechanical properties positions our metallic-glass based nanomembranes as an ideal candidate for nanofabrication processing, such as nanoimprinting, for the creation of next-generation nanodevices.

Both atomistic and mesoscale simulation techniques have been extensively employed to gain fundamental understanding of the structures, deformation mechanisms, and structure-property relationships in bulk metallic glasses (BMGs), each with its unique strengths and limitations. Nevertheless, there is a limited degree of synergistic integration between the two approaches. In this study, we extract key properties of shear transformation zones (STZs) directly from the atomistic simulations, including their size, number of shear modes, eigenstrain, and most importantly, the activation energy barrier spectrum as a function of cooling history and strain rate. We then incorporate these STZ properties into a heterogeneously randomized STZ dynamic model implemented in a kinetic Monte Carlo algorithm to study parametrically the deformation microstructure, shear band formation and stress-strain behavior of BMGs. Two important characteristics of STZ activation that dictate the strength and ductility of a glass are identified. One is the average of the activation energy barrier spectrum (approximated by a Gaussian distribution), determined by the glass composition and processing history such as the cooling rate. The other is the amount of shift of the Gaussian distribution towards smaller activation energy barrier values during deformation, which is determined by the initial structural states and strain rate during deformation, and exhibits a saturation value. These findings have allowed us to gain important fundamental insights into the correlation between the degree of shear-induced softening and the general deformation behavior of BMGs, leading to a better understanding of the correlation between the processing history/loading condition and the mechanical behavior.

An intermittent pattern is observed in the modeling of interfacial cyclic-loading crack growth at high-angle grain boundaries in ternary Fe-Ni-Cr alloys. Different from conventional wisdom of stress-intensity factor, the abrupt crack advances are found driven by extreme value statistics---namely, the aggregation of atoms with most compressive residual stresses. In addition, inherently non-affine atomic stress fluctuations are discovered, and the fluctuations peak at intermediate level of chemical heterogeneity, causing the fastest crack growth. Implications of such nonmonotonic mechanism in regard to the origin of intermediate-temperature embrittlement phenomena are also discussed.