ミヤタ マサフミ

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: To develop and validate a prediction model for severe bronchopulmonary dysplasia (BPD) that integrates the respiratory severity (RS) score with early postnatal risk factors. METHODS: This retrospective cohort study included preterm infants born at less than 32 weeks gestation or with a birth weight of less than 1500 g, from Aichi Prefecture (training dataset) and Saitama Medical University (validation dataset) from April 1, 2016, to March 31, 2020. The primary outcome was severe BPD, defined as the use of home oxygen therapy or death due to BPD. We used classification and regression tree (CART) analysis to explore the relationship between outcomes and BPD risk factors in the training dataset. RESULTS: The incidence of severe BPD was 149 out of 2026 (7.3%) in the training dataset and 35 out of 387 (8.9%) in the validation dataset. CART analysis identified gestational age and the RS score as significant predictors of outcome in the day 7 and day 14 models, with C-statistics of 0.789 and 0.779, respectively. When applied to the validation dataset, these models achieved C-statistics of 0.753 and 0.827, respectively. CONCLUSION: Our prediction models demonstrated the ability to predict severe BPD, with the RS score being a crucial predictor. IMPACT: Many existing prediction models for bronchopulmonary dysplasia (BPD) use multiple predictors, and do not provide specific cutoff values, which complicates their clinical application. To address this issue, we developed a prediction model for severe BPD based on a score derived from mean airway pressure and inhaled oxygen concentration at 1-2 weeks of age. This user-friendly model can be easily integrated into clinical practice, facilitating treatment decisions based on predicted probabilities.

UBA1 is an E1 ubiquitin-activating enzyme that initiates the ubiquitylation of target proteins and is thus a key component of the ubiquitin signaling pathway. Three disorders are associated with pathogenic variants of the UBA1 gene: vacuoles, E1 enzyme, X-linked, autoinflammatory, somatic (VEXAS) syndrome, lung cancer in never smokers (LCINS), and X-linked spinal muscular atrophy (XL-SMA, SMAX2). We here report a case of infantile respiratory distress syndrome followed by continuing neuromuscular symptoms. We identified a de novo hemizygous mutation, c.1660 C > T (p.Pro554Ser), in exon 15 of the UBA1 gene in this baby. This missense mutation was located with the AAD (active adenylation domain) of the protein, a known hotspot of SMAX2 mutations. This case lends support to the genotype-phenotype correlation regarding the UBA1 mutation and its related diseases.

OBJECTIVES: Intestinal rotavirus (RV) vaccine replication and host immune response are suggested to be affected by several factors, including maternal antibodies, breastfeeding history, and gut microbiome, which are thought to be similar in pairs of twins. The aim of this study was to determine whether viral shedding from the fecal RV vaccine strain Rotarix® (RV1) and IgG and IgA responses to RV show similarity in pairs of twins. METHODS: Quantitative reverse transcription polymerase chain reaction specific to RV vaccine strain RV1 was used to monitor fecal RV1 viral shedding. RV IgG and IgA titers were measured using an in-house enzyme-linked immunosorbent assay. Fecal RV1 viral shedding and immune responses were compared between twins and singletons with mixed effects and fixed effects models. RESULTS: A total of 347 stool and 54 blood samples were collected from four pairs of twins and twelve singletons during the observation period. Although the kinetics of fecal RV1 viral shedding and immune responses differed among vaccinated individuals, they appeared to be similar within twin pairs. RV shedding after the first dose (P=0.049) and RV IgG titers during the entire observation period (P=0.015) had a significantly better fit in the fixed effect model that assumed that twins have the same response versus the model that assumed that twins have a different response. CONCLUSIONS: The similarity of RV vaccine viral replication in intestine and host immune responses in twin pairs was demonstrated using statistical analysis.

BACKGROUND: In Japan, the first human milk bank (HMB) was established in 2017, which changed the practice of enteral feeding in neonatal care. This study investigated the practice of enteral feeding of preterm infants after the establishment of the HMB in Japan and examined related future issues. METHODS: A survey on enteral feeding and the use of the HMB was conducted in 251 neonatal intensive care units (NICUs) from December 2020 to February 2021. RESULTS: The response rate was 61%. The ideal times to start enteral feeding for extremely-low-birthweight infants (ELBWI) and very-low-birthweight infants (VLBWI) were within 24 h after birth in approximately 59% and 62% of NICUs, however, only 30% and 46% could do so, respectively. Artificial nutrition was used to initiate enteral feeding for ELBWIs and VLBWIs in in 24% and 56% of NICUs, respectively. Of the NICUs, 92% considered the HMB "necessary" or "rather necessary". Fifty-five percent wanted to use the HMB but could not. The major reasons for this were (1) difficulty in paying the annual membership fee, (2) difficulty obtaining approval from the NICU, and (3) complexity in using the facility. The indications for using and discontinuation of use of donor milk varied among the NICUs. Only in 17%, milk expression was within 1h after delivery. CONCLUSIONS: Compared with before the establishment of the HMB, NICUs are currently more willing to start enteral feeding for preterm infants earlier. However, the implementation of enteral feeding appears to be challenging. Issues related to the HMB highlighted by the responses need to be addressed. Additionally, guidelines for using donor milk should be established.