Takashi Nakano

Abstract Heart rate variability (HRV) is a well-established, noninvasive measure of autonomic nervous system activity and is associated with clinical outcomes. Although real-time monitoring of HRV is valuable in clinical practice, its effectiveness is often compromised by major challenges: high inter-individual variability and frequent data contamination from procedural artifacts. To address these challenges, we developed and validated a computational framework for robust and personalized real-time HRV analysis oriented toward clinical application. The framework performs simultaneous analysis and visualization of both time- and frequency-domain HRV indices and incorporates an adaptive alert algorithm that personalizes alert thresholds using the interquartile range of each patient’s own data. A workflow-integrated mechanism for manually annotating and excluding artifact-prone periods prevents procedural artifacts from skewing the statistical baselines, and a multi-scale visualization module provides a unified view of short-term fluctuations and long-term trends. While existing HRV tools are powerful for research or offline analysis, they often lack the integration of personalized alerting and workflow-oriented artifact management needed for bedside care. The proposed system uniquely combines personalized alerting, care-linked artifact exclusion, and multi-scale bedside visualization within a single real-time software package. The framework was validated using open-access electrocardiogram (ECG) databases and synthetic noise-contaminated signals, confirming robust R-wave detection across pediatric and adult recordings and under low signal-to-noise conditions. In addition, the framework was operationally validated at the bedside using ECG data from 24 newborn patients. By systematically addressing the core challenges of personalization and artifact management in a clinically integrated manner, this work represents a significant step toward translating real-time HRV analysis into routine vital sign management and, ultimately, improved patient outcomes.

BACKGROUND: Noise adversely affects preterm infants in the neonatal intensive care unit (NICU), but past studies focused exclusively on quantifying its acoustic characteristics. PURPOSE: This study aims to examine the relationships between objective noise measurements and nurses' subjective perceptions in the NICU and analyze how these measurements vary by location and time of day during quiet hours. METHODS: In this observational study, noise was measured in 12 bays of an open-bay NICU during set times in the morning, afternoon, and evening. Subjective ratings of perceived noise were solicited from 25 nurses during these periods, converted to numerical scores, and ranked to categorize the bays into 3 measurement areas: loud, intermediate, and quiet. Noise indices were tested for associations with noise score, measurement area, and time by correlation and variance analyses. RESULTS: The equivalent continuous sound level ( Leq ) ranged from 55 to 63 dB over 60-minute measurement periods. The L5 (level exceeded 5% of the 60-minute period) and the L50 (level exceeded 50% of the 60-minute period) were analyzed to capture short-duration high noise levels and typical ambient noise, respectively. Noise ratings showed weak correlations with Leq , L5 , L50 , and minimum sound levels (L min ). IMPLICATIONS FOR PRACTICE AND RESEARCH: Strategies that consider location and time of day, with measures against sudden noise, are needed for NICU care. Future research should address comprehensive assessments of noise sources and their impact evaluation on preterm infants.

When exposed to X-rays, scintillators emit visible luminescence. X-ray-mediated optogenetics employs scintillators for remotely activating light-sensitive proteins in biological tissue through X-ray irradiation. This approach offers advantages over traditional optogenetics, allowing for deeper tissue penetration and wireless control. Here, we assessed the short-term safety and efficacy of candidate scintillator materials for neuronal control. Our analyses revealed that lead-free halide scintillators, such as Cs3Cu2I5, exhibited significant cytotoxicity within 24 h and induced neuroinflammatory effects when injected into the mouse brain. In contrast, cerium-doped gadolinium aluminum gallium garnet (Ce:GAGG) nanoparticles showed no detectable cytotoxicity within the same period, and injection into the mouse brain did not lead to observable neuroinflammation over four weeks. Electrophysiological recordings in the cerebral cortex of awake mice showed that X-ray-induced radioluminescence from Ce:GAGG nanoparticles reliably activated 45% of the neuronal population surrounding the implanted particles, a significantly higher activation rate than europium-doped GAGG (Eu:GAGG) microparticles, which activated only 10% of neurons. Furthermore, we established the cell-type specificity of this technique by using Ce:GAGG nanoparticles to selectively stimulate midbrain dopamine neurons. This technique was applied to freely behaving mice, allowing for wireless modulation of place preference behavior mediated by midbrain dopamine neurons. These findings highlight the unique suitability of Ce:GAGG nanoparticles for X-ray-mediated optogenetics. The deep tissue penetration, short-term safety, wireless neuronal control, and cell-type specificity of this system offer exciting possibilities for diverse neuroscience applications and therapeutic interventions.