HyeongGuk SON

Background: Postoperative follow-up after brain tumor surgery is typically limited to intermittent clinic visits, leaving subtle neurological or general deterioration between visits underrecognized. Digital self-monitoring platforms may help fill this gap, but evidence in neuro-oncology is scarce, particularly regarding how patient-reported symptom trajectories can feed into future data-driven early warning systems. Objective: This study aimed to evaluate the feasibility, use patterns, and preliminary usability of a smartphone or web-based self-monitoring system for patients after brain tumor surgery and to explore simple rule-based digital alerts as a first step toward an advanced digital early warning framework. Methods: We conducted a single-center prospective pilot study including adults discharged after brain tumor surgery who had access to a smartphone and could use a web app. Participants completed brief symptom surveys consisting of 51 binary items across 7 symptom domains, with an automatically calculated daily total score and score history visualization. Feasibility was assessed by enrollment, retention, submission counts, and submission rates. A total of 4 interpretable alert rules based on current score, short-term worsening, new-onset symptom combinations, and persistence across domains were evaluated using each patient’s last 3 submissions as the analytic unit. Clinical deterioration was defined a priori as objective decline in performance status, new neurological deficit, radiologic progression, or clinically significant laboratory changes. Rule performance metrics and bootstrap CIs were computed. Usability and acceptability were evaluated using the System Usability Scale and additional adherence-related items. Results: Of 64 enrolled patients, 30 (47%) with ≥3 submissions formed the analysis cohort (median age 57, IQR 47.2–64.5 years; n=12.9, 43% malignant tumors); 6 (20%) experienced clinical deterioration during follow-up. Patients contributed a median of 8.5 submissions (mean 19.03, SD 30.12) at 1.7 surveys per week on average, indicating sustained but heterogeneous engagement. The best-performing rule, based on net short-term score increase, achieved an area under the receiver operating characteristic of 0.88, with sensitivity 0.83, specificity 0.92, and accuracy 0.90 on the last-window dataset, outperforming rules based solely on current score or multidomain persistence. Among 23 app users who completed the System Usability Scale, the mean score was 84.0, reflecting high perceived usability; higher-frequency users reported stronger perceived usefulness and habit-driven use. Conclusions: This pilot study demonstrates that a smartphone or web-based self-monitoring platform for patients with brain tumor is feasible and well accepted and that simple, transparent rules applied to longitudinal symptom scores show potential to capture early signals of clinical deterioration. However, given the small sample size, these predictive metrics are preliminary and require rigorous validation in larger, independent cohorts. These findings support further development of integrated digital early warning systems that combine patient-reported trajectories with clinical and physiological data to enhance postoperative neurosurgical care.

ObjectivesAllergic rhinitis (AR) is a chronic inflammation of the nasal mucosa triggered by environmental allergens. Although its pathophysiology has been extensively investigated, the influence of environmental aggravating factors—particularly combined pollutant exposure—remains insufficiently characterized. This study aimed to assess the impact of coexposure to PM2.5, formaldehyde, and Zn on allergic inflammation in a murine AR model and to delineate the associated immunological and histopathological responses.MethodsFemale BALB/c mice were sensitized with ovalbumin (OVA) and challenged intranasally to induce AR. On days 21–24, the mice were exposed to PM2.5, formaldehyde, and Zn, either individually or in combination with OVA. Allergic symptoms were evaluated through behavioral observation, while immune responses were assessed by analyzing nasal and bronchoalveolar lavage fluids (NALF and BALF), serum immunoglobulin levels, nasal histopathology, and cytokine profiles.ResultsCombined exposure to PM2.5, formaldehyde, and Zn significantly intensified allergic inflammation compared with single exposures. Coexposure to PM2.5 and Zn led to synergistic increases in total and OVA-specific immunoglobulin E levels, eosinophilic infiltration, nasal rubbing, sneezing, and Th2/Th17 cytokine levels in NALF and BALF. Histological analysis demonstrated epithelial thickening and goblet cell hyperplasia after combined exposure. Other combinations, including PM2.5 with formaldehyde, also produced additive or modestly amplified inflammatory responses.ConclusionsCoexposure to PM2.5, formaldehyde, and Zn aggravated allergic inflammation in an OVA-induced murine model, with PM2.5+Zn yielding the strongest synergistic effects. These findings emphasize the role of pollutant–pollutant interactions in allergic airway diseases and highlight the need for further research to clarify long-term health effects and relevance to human disease.

Background: Autonomous medication delivery robots can streamline hospital logistics. However, their feasibility under elevator congestion remains uncertain. Objective: To evaluate the feasibility of medication delivery robots in a tertiary hospital and quantify how the elevator operating rate (EOR, %) affects delivery success, delay, and user experience. Methods: A prospective feasibility study was conducted in a tertiary hospital where a robot is used for delivering medicine. We analyzed 122 non-urgent missions from June 18–29, 2025, spanning weekdays and weekends. Data included the Elevator Operating Rate (EOR), passenger and cargo counts, Elevator Waiting Time, and Elevator Travel Time. The delivery outcomes were recorded, and a Monte Carlo simulation was used to model the failure probabilities under different congestion scenarios. The staff usability and workload were assessed using the System Usability Scale (SUS) and NASA Task Load Index (NASA-TLX). Results: A Higher EOR was strongly associated with more delivery failures. Most failures resulted from physical obstruction by passengers or cargo. The data also confirmed that a high EOR coincided with greater elevator occupancy. Simulations incorporating space occupancy reproduced failure patterns similar to the in situ observations. An increased EOR also prolonged the delivery time. The staff reported relatively high usability, but the NASA-TLX scores indicated that frequent robot users felt greater time-related pressure, likely reflecting delays during congestion. Conclusions: Autonomous medication delivery is feasible. However, its performance is sensitive to elevator congestion. Effective deployment requires consideration of elevator usage rates, and robotic medication delivery should be scheduled when congestion is below critical thresholds to ensure reliability and minimize the staff burden.

BACKGROUND Postoperative follow-up after brain tumor surgery is typically limited to intermittent clinic visits, leaving subtle neurological or general deterioration between visits underrecognized. Digital self-monitoring platforms may help fill this gap, but evidence in neuro-oncology is scarce, particularly regarding how patient-reported symptom trajectories can feed into future data-driven early warning systems. OBJECTIVE This study aimed to evaluate the feasibility, use patterns, and preliminary usability of a smartphone or web-based self-monitoring system for patients after brain tumor surgery and to explore simple rule-based digital alerts as a first step toward an advanced digital early warning framework. METHODS We conducted a single-center prospective pilot study including adults discharged after brain tumor surgery who had access to a smartphone and could use a web app. Participants completed brief symptom surveys consisting of 51 binary items across 7 symptom domains, with an automatically calculated daily total score and score history visualization. Feasibility was assessed by enrollment, retention, submission counts, and submission rates. A total of 4 interpretable alert rules based on current score, short-term worsening, new-onset symptom combinations, and persistence across domains were evaluated using each patient’s last 3 submissions as the analytic unit. Clinical deterioration was defined a priori as objective decline in performance status, new neurological deficit, radiologic progression, or clinically significant laboratory changes. Rule performance metrics and bootstrap CIs were computed. Usability and acceptability were evaluated using the System Usability Scale and additional adherence-related items. RESULTS Of 64 enrolled patients, 30 (47%) with ≥3 submissions formed the analysis cohort (median age 57, IQR 47.2–64.5 years; n=12.9, 43% malignant tumors); 6 (20%) experienced clinical deterioration during follow-up. Patients contributed a median of 8.5 submissions (mean 19.03, SD 30.12) at 1.7 surveys per week on average, indicating sustained but heterogeneous engagement. The best-performing rule, based on net short-term score increase, achieved an area under the receiver operating characteristic of 0.88, with sensitivity 0.83, specificity 0.92, and accuracy 0.90 on the last-window dataset, outperforming rules based solely on current score or multidomain persistence. Among 23 app users who completed the System Usability Scale, the mean score was 84.0, reflecting high perceived usability; higher-frequency users reported stronger perceived usefulness and habit-driven use. CONCLUSIONS This pilot study demonstrates that a smartphone or web-based self-monitoring platform for patients with brain tumor is feasible and well accepted and that simple, transparent rules applied to longitudinal symptom scores show potential to capture early signals of clinical deterioration. However, given the small sample size, these predictive metrics are preliminary and require rigorous validation in larger, independent cohorts. These findings support further development of integrated digital early warning systems that combine patient-reported trajectories with clinical and physiological data to enhance postoperative neurosurgical care.

Background: Eosinophilic chronic rhinosinusitis with nasal polyps (eCRSwNP) is characterized by persistent sinonasal inflammation and marked eosinophilic infiltration. Although the relationship between eosinophils and NP formation has been extensively studied, the mechanisms governing eosinophil transepithelial migration into the nasal mucosa remain poorly understood. Cadherin‐26 (CDH26), an epithelial adhesion molecule that binds to integrins α4 (ITGA4) and αE, has been implicated in eosinophilic inflammation and may play a critical role in eosinophil recruitment and tissue infiltration. Objective: This study aimed to investigate the role and underlying mechanism of CDH26 in facilitating eosinophil transepithelial migration in patients with eCRSwNP. Methods: Single‐cell ribonucleic acid (RNA) sequencing and immunohistochemistry (IHC) were performed on nasal tissues from patients with eCRSwNP, non‐eCRSwNP, chronic rhinosinusitis without nasal polyps (CRSsNP), and healthy controls to evaluate CDH26 expression. Human primary nasal epithelial cells (hPNECs) were stimulated in vitro with interleukin‐4 (IL‐4) or IL‐13, and CDH26 expression was assessed via reverse transcription polymerase chain reaction (RT‐PCR), western blotting, and IHC. The effect of IL‐4 receptor blockade using Dupilumab was evaluated in monolayer cultures. ITGA4 expression in EoL‐1 eosinophil‐like cells was measured by flow cytometry, and their interaction with recombinant CDH26 was evaluated using cell adhesion and Transwell migration assays. Results: CDH26 expression was significantly upregulated in eCRSwNP tissues compared to that in other groups. IL‐4 and IL‐13 stimulation induced CDH26 expression in hPNECs, which was dose‐dependently inhibited by Dupilumab. EoL‐1 cells expressed ITGA4 and adhered to recombinant CDH26 in vitro. Th2 cytokine stimulation enhanced EoL‐1 cell transepithelial migration, which was significantly reduced by CDH26 knockdown or Dupilumab treatment. Conclusion: Th2 cytokine‐induced upregulation of epithelial CDH26 facilitates eosinophil transepithelial migration, potentially via ITGA4 interaction. Thus, CDH26 may represent a novel therapeutic target for managing eCRSwNP.

Degenerative cascades of the intervertebral disc (IVD) are characterized by the presence of immune cells like monocytes, macrophages, and leukocytes, which contribute to inflammation. Previous in vitro studies on monocyte chemotaxis in the presence of chemical or mechanical stimulation were unable to establish the effects of endogenous stimulating factors from resident IVD cells, or fully understand macrophage and monocyte differentiation pathways in IVD degeneration. Our study simulates monocyte extravasation using a fabricated microfluidic chemotaxis IVD organ-on-a-chip (IVD organ chip), which models the geometry of IVD, chemoattractant diffusion, and infiltration of immune cells. Additionally, the fabricated IVD organ chip mimics stepwise monocyte infiltration and differentiation into macrophages in the degenerative nucleus pulposus (NP) induced by IL-1β. We find that naïve NP cells do not recruit THP-1 monocyte-like cells, but degenerative NP cells recruit and accumulate macrophages through chemo-gradient channels. Furthermore, the differentiated and migrated THP-1 cells show phagocytic activity around inflammatory NP cells. Our in vitro model of monocyte chemotaxis with degenerative NP on an IVD organ chip depicts the sequential processes of monocyte migration/infiltration, monocyte-to-macrophage differentiation, and accumulation. Using this platform to gain a deeper understanding of monocyte infiltration and differentiation processes can provide insights into the pathophysiology of the immune response in degenerative IVD.