Experience-related neural dynamics in infants may be understood from a prediction-based perspective that incorporates bidirectional interactions between perception and expectation, modulated by sleep-wake states. This simulation study addresses two seemingly contradictory sets of fNIRS findings, which exhibit repetition-induced suppression or enhancement of neural response over trials, accompanied by correspondingly opposing surprise-induced responses. The simulation study demonstrates that, by interacting with tasks of varying complexity, a unified implicit, error-driven learning mechanism that engages both bottom-up perception and top-down expectation can simulate experience-related enhancements in perceptual and frontal responses. The distinction between trial-by-trial neural suppression and enhancement is then interpreted based on differing rates of neural attenuation influenced by the involvement of on- and/or off-task resources. In sleep states, a highly familiarized outcome with higher activation is responded to with shorter latency (decreasing on-task involvement), thus suppressing the overall neural response. In wakeful states, however, neural responses may be maintained by sustained attention but can still be subject to neural attenuation through novelty seeking (increasing off-task involvement). The simulation study raises questions about the interplay between the implicit prediction mechanism and (un)conscious states that contribute to experience-related neural dynamics in infants.
Dynamic thermo-mechanical stresses caused by sudden temperature changes and molten steel impact, etc., accelerate the degradation of Al2O3-C refractories during service. To investigate the dynamic degradation behavior, dynamic mechanical tests were conducted using the Split Hopkinson Pressure Bar (SHPB), systematically examining the effects of partial substitution of flake graphite by expanded graphite and thermal degradation. The results show that the Al2O3-C refractories exhibit a significant strain-rate hardening effect, with strength increasing with impact velocity and the failure mode progressively transitioning from crack propagation to pulverization. Cyclic prolonged thermal exposure to 1500 °C contributes to the SiC whiskers formation and densification, and results in the increase strength and brittleness. The phenomenon of specimen after 5 cycles having the optimal impact resistance proves the both the strength and energy dominated failure process. The introduction of expanded graphite effectively suppresses crack propagation and enhances energy dissipation capacity through interlayer sliding and stress buffering related to the myrmekitic texture, which provides a rationale for the development of low-carbon materials.
Radiotherapy’s clinical utility remains fundamentally constrained by the collateral damage to healthy tissues. Ultra-high dose rate (UHDR) irradiation, or FLASH-radiotherapy (FLASH-RT) has emerged as a transformative paradigm to mitigate such toxicity. However, the biological effects of FLASH-RT on the high-efficiency of tumor killing and normal tissue sparing remain poorly understood. In this work, we utilized a petawatt-class laser-plasma acceleration (LPA) platform to deliver discrete 12.9-nanosecond proton pulses at an extreme instantaneous dose rate of 1.94 × 107 Gy/s. This temporal singularity achieved a profound sparing effect in normal bronchial epithelial cells, evidenced by a nine-fold reduction in the lethal α coefficient (from 0.47 to 0.05 Gy−1), while maintaining full tumoricidal potency against lung adenocarcinoma. Mechanistically, we demonstrated that LPA-FLASH could effectively bypass the ATF3-mediated stress response and circumvent the subsequent ferroptotic cascade. This molecular evasion could preserve the mitochondrial cristae integrity and trigger an adaptive bioenergetic ATP surge—a hallmark of metabolic resilience exclusively in healthy tissue cells. Therefore, our findings identify ferroptosis-mediated mitochondrial integrity as a unifying framework for selective normal-tissue protection at the physical limits of radiation delivery, and establish LPA-FLASH-RT as a potent, compact modality for next-generation oncology.
Nerve injury-induced protein 1 (NINJ1) was originally identified in 1996 as a homophilic adhesion molecule upregulated following nerve injury. For over two decades thereafter, research on NINJ1 primarily focused on areas such as nerve regeneration, immune cell migration, and inflammation regulation. In 2021, the discovery by Kayagaki’s group completely transformed the understanding of NINJ1—the protein was demonstrated to be a key executor of plasma membrane rupture (PMR) during lytic cell death, overturning the long-held view that PMR is a passive osmotic event. This finding rapidly sparked intensive research efforts in structural biology, cell death regulation, and therapeutic target development. This review is organized around the central scientific questions in NINJ1 research, systematically tracing the trajectory from molecular discovery, structural elucidation, and activation regulation to disease associations and therapeutic targeting. We critically analyze the logical relationships among different research avenues, discuss the underlying assumptions and limitations of current findings, and highlight the key knowledge gaps that remain in the field.
Intelligent lower-limb prostheses are evolving from single-joint assistance toward coordinated, system-level control that supports cross-task adaptation, multimodal intent estimation, and verifiable safety. This systematic review surveys powered, semi-active, microprocessor-controlled, and related intelligent lower-limb prosthesis literature published between 1 January 2021 and 1 January 2026, spanning electromechanical design, sensing and human-machine interfaces, state/phase estimation, intent/terrain recognition, control and learning, evaluation endpoints, and translational considerations. Following a PRISMA-style workflow, 180 full-text reports were included and synthesized into a modular taxonomy covering clinical needs and endpoints; actuation and transmission; sensing and human-machine interfaces; phase/state estimation; intent/terrain recognition; impedance and trajectory control, including model predictive control; personalization with explicit safety constraints; real-world validation; and safety, reliability, and standardization. Emerging patterns include backdrivable low-impedance hardware, multimodal sensing with uncertainty-aware gating, and continuous phase-variable control, although the level of validation remains heterogeneous. Key gaps remain in endpoint consistency, external validity across users and contexts, and failure-mode reporting. We recommend benchmark protocols and system-level validation frameworks to support more reproducible evaluation and future clinical translation.
