Analysis on efficacy of magnetic resonance lymphangiography using INV-001 in healthy beagle dogs

We aimed to conduct a proof-of-concept study of INV-001 in visualizing lymphatic vessels and nodes without venous contamination and to determine the optimal dose condition of INV-001 for magnetic resonance lymphangiography (MRL) in healthy beagles. MRL was performed using a 3.0-Tesla (T) whole body clinical magnetic resonance imaging (MRI) scanner. A dose-finding study of INV-001 for MRL in beagles (N = 6) was carried out according to an adaptive optimal dose finding design. For the reproducibility study (N = 6), MRL was conducted at selected INV-001 doses (0.056 and 0.112 mg Fe/kg) with a 15 mM concentration. Additionally, an excretion study (N = 3) of INV-001 was conducted by analyzing T1, T2, and T2* maps of the liver and kidney 48 h post-administration. INV-001 administration at doses of 0.056 and 0.112 mg Fe/kg (concentration: 15 mM) consistently demonstrated the visualization of contrast-enhanced lymphatic vessels and nodes without venous contamination in the beagles. The contrast enhancement effect was highest at 30 min after INV-001 administration, then gradually decreasing. No toxicity-related issues were identified during the study. After 48 h, the T1, T2, and T2* values in the liver and both kidneys were found to be comparable to the pre-administration values, indicating thorough INV-001 excretion. The optimal dosing conditions of INV-001 for MRL for contrast-enhanced visualization of lymphatic vessels and nodes exclusively with no venous contamination in beagles was determined to be 0.056 mg Fe/kg with a 15 mM concentration.

Oligohydramnios affects pulmonary functional/structural abnormalities in school-aged children with bronchopulmonary dysplasia

BACKGROUND

The relationship between early life factors and childhood pulmonary function and structure in preterm infants remains unclear.

PURPOSE

This study investigated the impact of bronchopulmonary dysplasia (BPD) and perinatal factors on childhood pulmonary function and structure.

METHODS

This longitudinal cohort study included preterm participants aged ≥5 years born between 2005 and 2015. The children were grouped by BPD severity according to National Institutes of Health criteria. Pulmonary function tests (PFTs) were performed using spirometry. Chest computed tomography (CT) scans were obtained and scored for hyperaeration or parenchymal lesions. PFT results and chest CT scores were analyzed with perinatal factors.

RESULTS

A total 150 children (66 females) aged 7.7 years (6.4-9.9 years) were categorized into non/mild BPD (n=68), moderate BPD (n=39), and severe BPD (n=43) groups. The median z score for forced expiratory volume in 1 second (FEV1), forced vital capacity (FVC), FEV1/FVC ratio, and forced midexpiratory flow (FEF25%-75%) were significantly lower in the severe versus non/mild BPD group (-1.24 vs. -0.18, -0.22 vs. 0.41, -1.80 vs. -1.12, and -1.88 vs. -1.00, respectively; all P<0.05). The median z scores of FEV1, FEV1/ FVC, and FEF25%-75% among asymptomatic patients were also significantly lower in the severe versus non/mild BPD group (-0.82 vs. 0.09, -1.68 vs. -0.87, -1.59 vs. -0.61, respectively; all P<0.05). The severe BPD group had a higher median (range) CT score than the non/mild BPD group (6 [0-12] vs. 1 [0-10], P<0.001). Prenatal oligohydramnios was strongly associated with both low pulmonary function (FEV1/FVC

CONCLUSION

School-aged children with severe BPD showed airflow limitations and structural abnormalities despite no subjective respiratory symptoms. These results suggest that patients with a history of prenatal oligohydramnios or prolonged mechanical ventilation require extended follow-up.

Collapse

Key Words

• Bronchopulmonary dysplasia
• Cohort study
• Oligohydramnios
• Prematurity
• Respiratory function test

Collapse

MESH Headings Collapse

Grants

• 2018R1A5A2025079 National Research Foundation of Korea
• 2022R1F1A1074624 National Research Foundation of Korea
• Ministry of Science and ICT
• C-2020-0014 Severance Hospital Research Fund for Clinical Excellence
• C-2021-0024 Severance Children's Hospital
• Ilsung Research Award of Korean Academy Pediatric Allergy and Respiratory Disease

Collapse

Affiliation(s)

Jeong Eun Shin Department of Pediatrics, Severance Children’s Hospital, Yonsei University College of Medicine, Seoul, Korea
Soon Min Lee Department of Pediatrics, Gangnam Severance Children’s Hospital, Yonsei University College of Medicine, Seoul, Korea
Mi-Jung Lee Department of Radiology, Severance Children’s Hospital, Yonsei University College of Medicine, Seoul, Korea
Jungho Han Department of Pediatrics, Severance Children’s Hospital, Yonsei University College of Medicine, Seoul, Korea
Joohee Lim Department of Pediatrics, Gangnam Severance Children’s Hospital, Yonsei University College of Medicine, Seoul, Korea
Haerin Jang Department of Pediatrics, Severance Children’s Hospital, Yonsei University College of Medicine, Seoul, Korea
Ho Seon Eun Department of Pediatrics, Severance Children’s Hospital, Yonsei University College of Medicine, Seoul, Korea
Min Soo Park Department of Pediatrics, Severance Children’s Hospital, Yonsei University College of Medicine, Seoul, Korea
Soo Yeon Kim Department of Pediatrics, Severance Children’s Hospital, Yonsei University College of Medicine, Seoul, Korea
Myung Hyun Sohn Department of Pediatrics, Severance Children’s Hospital, Yonsei University College of Medicine, Seoul, Korea
Ji Ye Jung Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Severance Hospital, Yonsei University College of Medicine, Seoul, Korea
Kyung Won Kim Department of Pediatrics, Severance Children’s Hospital, Yonsei University College of Medicine, Seoul, Korea Institute for Innovation in Digital Healthcare, Yonsei University, Seoul, Korea

Collapse

Allergic rhinitis phenotypes with distinct transcriptome profiles in children: A birth cohort

BACKGROUND

Allergic rhinitis (AR) phenotypes in childhood are unclear.

OBJECTIVES

This study sought to determine AR phenotypes and investigate their natural course and clinical and transcriptomic characteristics.

METHODS

Latent class trajectory analysis was used for phenotyping AR in 1050 children from birth through 12 years using a birth cohort study. Blood transcriptome analyses were performed to define the underlying mechanisms of each phenotype.

RESULTS

Five AR phenotypes were identified: early onset (n = 88, 8.4%), intermediate transient (n = 110, 10.5%), late onset (n = 209, 19.9%), very late onset (n=187, 17.8%), and never/infrequent (n = 456, 43.4%). Children with early-onset AR were associated with higher AR severity and sensitizations to foods at age 1 year and inhalants at age 3 years and asthma symptoms, but not with bronchial hyperresponsiveness (BHR). Children with late-onset AR phenotype associated with sensitizations to various foods at age 1 year but not from age 3 years, and to inhalants from age 7 years and with asthma with BHR. Children with very late-onset AR phenotype associated with sensitizations to foods throughout preschool age and to inhalants at ages 7 and 9 years and with asthma with BHR. Transcriptome analysis showed that early-onset AR was associated with viral/bacterial infection-related defense response, whereas late-onset AR was associated with T cell-related immune response.

CONCLUSIONS

Early-onset AR phenotype was associated with sensitization to foods and inhalants at an early age and asthma symptoms, but not with BHR, whereas very late- and late-onset AR phenotypes were positively associated with sensitization to inhalants and asthma with BHR. Transcriptomic analyses indicated that early- and late-onset AR phenotypes had distinct underlying mechanisms related to AR as well.

Comparison of the Pharmacokinetics of Gadolinium-Based and Iron Oxide-Based Contrast Agents inside the Lymphatic Structure using Magnetic Resonance Lymphangiography

PURPOSE

Gadolinium (Gd)-based contrast agents are primarily used for contrast-enhanced magnetic resonance lymphangiography (MRL). However, overcoming venous contamination issues remains challenging. This study aims to assess the MRL efficacy of the newly developed iron-based contrast agent (INV-001) that is specially designed to mitigate venous contamination issues. The study further explores the optimal dosage, including both injection volume and concentration, required to achieve successful visualization of the popliteal lymph nodes and surrounding lymphatic vessels.

PROCEDURES

All animals utilized in this study were male Sprague-Dawley (SD) rats weighing between 250 and 300 g. The contrast agents prepared were injected intradermally in the fourth phalanx of both hind limbs using a 30-gauge syringe in SD rats. MRL was performed every 16 min on a coronal 3D time-of-flight sequence with saturation bands using a 9.4-T animal machine.

RESULTS

Contrary to Gd-DOTA, which exhibited venous contamination in most animals irrespective of injection dosages and conditions, INV-001 showed no venous contamination. For Gd-DOTA, the popliteal lymph nodes and lymphatic vessels reached peak enhancement 16 min after injection from the injection site and then rapidly washed out. However, with INV-001, they reached peak enhancement between 16 and 32 min after injection, with prolonged visualization of the popliteal lymph node and lymphatic vessels. INV-001 at 0.45 μmol (15 mM, 30 μL) and 0.75 μmol (15 mM, 50 μL) achieved high scores for qualitative image analysis, providing good visualization of the popliteal lymph nodes and lymphatic vessels without issues of venous contamination, interstitial space enhancement, or lymph node enlargement.

CONCLUSION

In MRL, INV-001, a novel T1 contrast agent based on iron, enables prolonged enhancement of popliteal lymph nodes and lymphatic vessels without venous contamination.

Pulmonary function characteristics in children with suspected asthma: implications for asthma diagnosis

BACKGROUND

In children suspected of asthma, diagnosis is confirmed via variable expiratory airflow limitation. However, there is no single gold standard test for diagnosing asthma.

OBJECTIVE

This study aimed to evaluate the pulmonary function characteristics in children suspected of asthma without bronchodilator response (BDR) and bronchial hyperresponsiveness (BHR).

METHODS

We utilized two separate real-world retrospective observational cohorts of children who underwent both spirometry and bronchial provocation testing for asthma. Spirometry parameters were collected and compared between definite asthma, probable asthma, and non-asthma groups. The original cohort comprised 1199 children who visited the Severance Hospital (Seoul, Korea) between January 2017 and December 2019. The external cohort included 105 children who visited the Gangnam Severance Hospital between January 2019 and December 2019.

RESULTS

Probable asthma accounted for 16.8% and 32.4% of the original and external cohorts, respectively. This group showed a significantly higher FeNO level and prevalence of allergic sensitization. Baseline forced expiratory volume in 1 second (FEV1), FEV1/forced vital capacity (FVC), forced expiratory flow at 25-75% of FVC (FEF25-75), and FEF75 showed stepwise decrements from non-asthma, probable asthma, to definite asthma patients (P < 0.001). The probable asthma group showed significantly higher odds of abnormal FEV1/FVC (OR, 2.24 [95%CI, 1.43-3.52])and FEF25-75 (2.05 [1.13-3.73]) than the non-asthma group and lower odds of abnormal FEV1(0.05 [0.01-0.19]),FEV1 /FVC (0.27 [0.18-0.41]), FEF25-75 (0.17 [0.11-0.28]), and FEF75 (0.14 [0.08-0.24]) compared to the definite asthma group. The external cohort was consistent with the original cohort.

CONCLUSION

We show evidence of airway dysfunction in children for whom a high clinical suspicion of asthma exists without evidence of BDR and BHR. Repeated pulmonary function tests that closely monitor for subtle lung function impairments and active utilization of additional tests, such as allergic screening and FeNO, should be considered to close the gap in diagnosing asthma.

Activated Leukocyte Cell Adhesion Molecule Regulates the Expression of Interleukin-33 in RSV Induced Airway Inflammation by Regulating MAPK Signaling Pathways

PURPOSE

The respiratory syncytial virus (RSV) is a common respiratory virus that causes acute lower respiratory tract infectious diseases, particularly in young children and older individuals. Activated leukocyte cell adhesion molecule (ALCAM) is a membrane glycoprotein expressed in various cell types, including epithelial cells, and is associated with inflammatory responses and various cancers. However, the precise role of ALCAM in RSV-induced airway inflammation remains unclear, and our study aimed to explore this gap in the literature.

METHODS

C57BL/6 wild-type, ALCAM knockout mice and airway epithelial cells were infected with RSV and the expression of ALCAM and inflammatory cytokines were measured. We also conducted further experiments using Anti-ALCAM antibody and recombinant ALCAM in airway epithelial cells.

RESULTS

The expression levels of ALCAM and inflammatory cytokines increased in both RSV-infected mice and airway epithelial cells. Interestingly, IL-33 expression was significantly reduced in ALCAM-knockdown cells compared to control cells following RSV infection. Anti-ALCAM antibody treatment also reduced IL-33 expression following RSV infection. Furthermore, the phosphorylation of ERK1/2, p38, and JNK was diminished in ALCAM-knockdown cells compared to control cells following RSV infection. Notably, in the control cells, inhibition of these pathways significantly decreased the expression of IL-33. In vivo study also confirmed a reduction in inflammation induced by RSV infection in ALCAM deficient mice compared to wild-type mice.

CONCLUSION

These findings demonstrate that ALCAM contributes to RSV-induced airway inflammation at least partly by influencing IL-33 expression through mitogen-activated protein kinase signaling pathways. These results suggest that targeting ALCAM could be a potential therapeutic strategy for alleviating IL-33-associated lung diseases.

Nanoplastics exacerbate Parkinson's disease symptoms in C. elegans and human cells

The increasing prevalence of nanoplastics in our environment due to the widespread use of plastics poses potential health risks that are not yet fully understood. This study examines the physiological and neurotoxic effects of these minuscule nanoplastic particles on the nematode Caenorhabditis elegans as well as on human cells. Here, we find that 25 nm polystyrene nanoplastic particles can inhibit animal growth and movement at very low concentrations, with varying effects on their surface groups. Furthermore, these nanoplastic particles not only accumulate in the digestive tract but also penetrate further into extraintestinal tissues. Such nanoplastics significantly compromise the integrity of the intestinal barrier, leading to "leaky gut" conditions and cause mitochondrial fragmentation in muscles, which possibly explains the observed movement impairments. A striking discovery was that these nanoplastics exacerbate symptoms similar to those of Parkinson's disease (PD), including dopaminergic neuronal degeneration, locomotor dysfunction, and accumulation of α-Synuclein aggregates. Importantly, our study demonstrates that the detrimental effects of nanoplastics on the aggregation of α-Synuclein extend to both C. elegans and human cell models of PD. In conclusion, our research highlights the potential health hazards linked to the physicochemical properties of nanoplastics, underlining the urgency of understanding their interactions with biological systems. ENVIRONMENTAL IMPLICATION: The escalating prevalence of nanoplastics in the environment due to widespread plastic usage raises potential health risks. Studies conducted on C. elegans indicate that even low concentrations of 25 nm polystyrene nanoplastics can impair growth and movement. These particles accumulate in the digestive system, compromising the intestinal barrier, causing "leaky gut", as well as inducing Parkinson's-like symptoms. Importantly, in both C. elegans and human cell models of Parkinson's disease, such nanoplastics penetrate tissues or cells and increase α-Synuclein aggregates. This underscores the urgent need to understand the interactions of nanoplastics with biological systems and highlights potential environmental and health consequences.

Low- or standard-dose edoxaban versus antiplatelet therapy for leaflet thrombus and cerebral thromboembolism after TAVR: A prespecified analysis of randomized ADAPT-TAVR trial

BACKGROUND

The risks of leaflet thrombosis and the associated cerebral thromboembolism are unknown according to different anticoagulation dosing after transcatheter aortic valve replacement (TAVR). The aim was to evaluate the incidence of leaflet thrombosis and cerebral thromboembolism between low-dose (30 mg) or standard-dose (60 mg) edoxaban and dual antiplatelet therapy (DAPT) after TAVR.

METHODS

In this prespecified subgroup analysis of the ADAPT-TAVR trial, the primary endpoint was the incidence of leaflet thrombosis on 4-dimensional computed tomography at 6-months. Key secondary endpoints were new cerebral lesions on brain magnetic resonance imaging and neurological and neurocognitive dysfunction.

RESULTS

Of 229 patients enrolled in this study, 118 patients were DAPT group and 111 were edoxaban group (43 [39.1%] 60 mg vs 68 [61.3%] 30 mg). There was a significantly lower incidence of leaflet thrombosis in the standard-dose edoxaban group than in the DAPT group (2.4% vs 18.3%; odds ratio [OR] 0.11; 95% confidence interval [CI], 0.01-0.55; P = .03). However, no significant difference was observed between low-dose edoxaban and DAPT (15.0% vs 18.3%; OR 0.79; 95% CI, 0.32-1.81; P = .58). Irrespective of different antithrombotic regiments, the percentages of patients with new cerebral lesions on brain MRI and worsening neurological or neurocognitive function were not significantly different.

CONCLUSIONS

In patients without an indication for anticoagulation after TAVR, the incidence of leaflet thrombosis was significantly lower with standard-dose edoxaban but not with low-dose edoxaban, as compared with DAPT. However, this differential effect of edoxaban on leaflet thrombosis was not associated with a reduction of new cerebral thromboembolism and neurological dysfunction.

Predicting the Outcome of Pediatric Oral Food Challenges for Determining Tolerance Development

PURPOSE

Despite the risk of anaphylaxis, oral food challenges (OFCs) are performed clinically for various indications, particularly to confirm tolerance development. This study aimed to assess OFCs by relevant indications and build an outcome prediction model to help determine when to perform OFCs in children who are likely to have developed immune tolerance.

METHODS

In total, 432 pediatric OFCs were retrospectively analyzed according to indications. Clinical characteristics, serum total immunoglobulin (Ig) E, blood eosinophils, and specific IgE and IgG4 levels for food allergens were noted and compared. Machine learning was utilized to select the most important variables in determining the passage of the OFCs, and prediction models were constructed using the selected variables.

RESULTS

OFCs were most commonly performed to confirm tolerance development (number, %; 267, 61.8%). The most common food allergens tested were egg (191, 44.2%) and milk (135, 31.3%). Children who passed the egg challenges for confirming tolerance acquisition had significantly lower egg white-specific IgE level (P = 0.008). Similarly, those who passed milk challenges had significantly lower cow's milk-specific IgE (P = 0.002) and casein-specific IgE levels (P = 0.005). We developed a nomogram to predict the outcome of OFCs to determine the tolerance acquisition with the selected variables; lower food-specific IgE, higher total IgE, and younger age indicated a higher probability of passage. The area under the curve (95% confidence interval) was 0.623 (0.503-0.743) for egg and 0.734 (0.628-0.840) for milk.

CONCLUSIONS

Serum total IgE and food-specific IgE combined with age showed trends toward passing OFCs for confirming tolerance development. The constructed model may be used by clinicians as a practical guide for minimizing the risks of OFCs and a timely reintroduction for children with food allergies.

Deep learning-based prediction of post-pancreaticoduodenectomy pancreatic fistula

Postoperative pancreatic fistula is a life-threatening complication with an unmet need for accurate prediction. This study was aimed to develop preoperative artificial intelligence-based prediction models. Patients who underwent pancreaticoduodenectomy were enrolled and stratified into model development and validation sets by surgery between 2016 and 2017 or in 2018, respectively. Machine learning models based on clinical and body composition data, and deep learning models based on computed tomographic data, were developed, combined by ensemble voting, and final models were selected comparison with earlier model. Among the 1333 participants (training, n = 881; test, n = 452), postoperative pancreatic fistula occurred in 421 (47.8%) and 134 (31.8%) and clinically relevant postoperative pancreatic fistula occurred in 59 (6.7%) and 27 (6.0%) participants in the training and test datasets, respectively. In the test dataset, the area under the receiver operating curve [AUC (95% confidence interval)] of the selected preoperative model for predicting all and clinically relevant postoperative pancreatic fistula was 0.75 (0.71-0.80) and 0.68 (0.58-0.78). The ensemble model showed better predictive performance than the individual ML and DL models.

Prognostic value of CT-based radiomics in grade 1-2 pancreatic neuroendocrine tumors

BACKGROUND

Surgically resected grade 1-2 (G1-2) pancreatic neuroendocrine tumors (PanNETs) exhibit diverse clinical outcomes, highlighting the need for reliable prognostic biomarkers. Our study aimed to develop and validate CT-based radiomics model for predicting postsurgical outcome in patients with G1-2 PanNETs, and to compare its performance with the current clinical staging system.

METHODS

This multicenter retrospective study included patients who underwent dynamic CT and subsequent curative resection for G1-2 PanNETs. A radiomics-based model (R-score) for predicting recurrence-free survival (RFS) was developed from a development set (441 patients from one institution) using least absolute shrinkage and selection operator-Cox regression analysis. A clinical model (C-model) consisting of age and tumor stage according to the 8th American Joint Committee on Cancer staging system was built, and an integrative model combining the C-model and the R-score (CR-model) was developed using multivariable Cox regression analysis. Using an external test set (159 patients from another institution), the models' performance for predicting RFS and overall survival (OS) was evaluated using Harrell's C-index. The incremental value of adding the R-score to the C-model was evaluated using net reclassification improvement (NRI) and integrated discrimination improvement (IDI).

RESULTS

The median follow-up periods were 68.3 and 59.7 months in the development and test sets, respectively. In the development set, 58 patients (13.2%) experienced recurrence and 35 (7.9%) died. In the test set, tumors recurred in 14 patients (8.8%) and 12 (7.5%) died. In the test set, the R-score had a C-index of 0.716 for RFS and 0.674 for OS. Compared with the C-model, the CR-model showed higher C-index (RFS, 0.734 vs. 0.662, p = 0.012; OS, 0.781 vs. 0.675, p = 0.043). CR-model also showed improved classification (NRI, 0.330, p < 0.001) and discrimination (IDI, 0.071, p < 0.001) for prediction of 3-year RFS.

CONCLUSIONS

Our CR-model outperformed the current clinical staging system in prediction of the prognosis for G1-2 PanNETs and added incremental value for predicting postoperative recurrence. The CR-model enables precise identification of high-risk patients, guiding personalized treatment planning to improve outcomes in surgically resected grade 1-2 PanNETs.

Mapping Changes in Glutamate with Glutamate-Weighted MRI in Forced Swim Test Model of Depression in Rats

Chemical exchange saturation transfer with glutamate (GluCEST) imaging is a novel technique for the non-invasive detection and quantification of cerebral Glu levels in neuromolecular processes. Here we used GluCEST imaging and 1H magnetic resonance spectroscopy (1H MRS) to assess in vivo changes in Glu signals within the hippocampus in a rat model of depression induced by a forced swim test. The forced swimming test (FST) group exhibited markedly reduced GluCEST-weighted levels and Glu concentrations when examined using 1H MRS in the hippocampal region compared to the control group (GluCEST-weighted levels: 3.67 ± 0.81% vs. 5.02 ± 0.44%, p < 0.001; and Glu concentrations: 6.560 ± 0.292 μmol/g vs. 7.133 ± 0.397 μmol/g, p = 0.001). Our results indicate that GluCEST imaging is a distinctive approach to detecting and monitoring Glu levels in a rat model of depression. Furthermore, the application of GluCEST imaging may provide a deeper insight into the neurochemical involvement of glutamate in various psychiatric disorders.

Limitations of the Cough Sound-Based COVID-19 Diagnosis Artificial Intelligence Model and its Future Direction: Longitudinal Observation Study

BACKGROUND

The outbreak of SARS-CoV-2 in 2019 has necessitated the rapid and accurate detection of COVID-19 to manage patients effectively and implement public health measures. Artificial intelligence (AI) models analyzing cough sounds have emerged as promising tools for large-scale screening and early identification of potential cases.

OBJECTIVE

This study aimed to investigate the efficacy of using cough sounds as a diagnostic tool for COVID-19, considering the unique acoustic features that differentiate positive and negative cases. We investigated whether an AI model trained on cough sound recordings from specific periods, especially the early stages of the COVID-19 pandemic, were applicable to the ongoing situation with persistent variants.

METHODS

We used cough sound recordings from 3 data sets (Cambridge, Coswara, and Virufy) representing different stages of the pandemic and variants. Our AI model was trained using the Cambridge data set with subsequent evaluation against all data sets. The performance was analyzed based on the area under the receiver operating curve (AUC) across different data measurement periods and COVID-19 variants.

RESULTS

The AI model demonstrated a high AUC when tested with the Cambridge data set, indicative of its initial effectiveness. However, the performance varied significantly with other data sets, particularly in detecting later variants such as Delta and Omicron, with a marked decline in AUC observed for the latter. These results highlight the challenges in maintaining the efficacy of AI models against the backdrop of an evolving virus.

CONCLUSIONS

While AI models analyzing cough sounds offer a promising noninvasive and rapid screening method for COVID-19, their effectiveness is challenged by the emergence of new virus variants. Ongoing research and adaptations in AI methodologies are crucial to address these limitations. The adaptability of AI models to evolve with the virus underscores their potential as a foundational technology for not only the current pandemic but also future outbreaks, contributing to a more agile and resilient global health infrastructure.

Diagnosis of Primary Ciliary Dyskinesia via Whole Exome Sequencing and Histologic Findings

PURPOSE

To assess the diagnostic potential of whole-exome sequencing (WES) and elucidate the clinical and genetic characteristics of primary ciliary dyskinesia (PCD) in the Korean population.

MATERIALS AND METHODS

Forty-seven patients clinically suspected of having PCD were enrolled at a tertiary medical center. WES was performed in all patients, and seven patients received biopsy of cilia and transmission electron microscopy (TEM).

RESULTS

Overall, PCD was diagnosed in 10 (21.3%) patients: eight by WES (8/47, 17%), four by TEM. Among patients diagnosed as PCD based on TEM results, two patients showed consistent results with WES and TEM of PCD (2/4, 50%). In addition, five patients, who were not included in the final PCD diagnosis group, had variants of unknown significance in PCD-related genes (5/47, 10.6%). The most frequent pathogenic (P)/likely pathogenic (LP) variants were detected in DNAH11 (n=4, 21.1%), DRC1 (n=4, 21.1%), and DNAH5 (n=4, 21.1%). Among the detected 17 P/LP variants in PCD-related genes in this study, 8 (47.1%) were identified as novel variants. Regarding the genotype-phenotype correlation in this study, the authors experienced severe PCD cases caused by the LP/P variants in MCIDAS, DRC1, and CCDC39.

CONCLUSION

Through this study, we were able to confirm the value of WES as one of the diagnostic tools for PCD, which increases with TEM, rather than single gene tests. These results will prove useful to hospitals with limited access to PCD diagnostic testing but with relatively efficient in-house or outsourced access to genetic testing at a pre-symptomatic or early disease stage.

Insights from the COCOA birth cohort: The origins of childhood allergic diseases and future perspectives

The ongoing COhort for Childhood Origin of Asthma and allergic diseases (COCOA) study is a prospective birth cohort investigating the origin and natural courses of childhood allergic diseases, including atopic dermatitis, food allergy, allergic rhinitis and asthma, with long-term prognosis. Initiated under the premise that allergic diseases result from a complex interplay of immune development alterations, environmental exposures, and host susceptibility, the COCOA study explores these dynamic interactions during prenatal and postnatal periods, framed within the hygiene and microbial hypotheses alongside the developmental origins of health and disease (DOHaD) hypothesis. The scope of the COCOA study extends to genetic predispositions, indoor and outdoor environmental variables affecting mothers and their offsprings such as outdoor and indoor air pollution, psychological factors, diets, and the microbiomes of skin, gut, and airway. We have embarked on in-depth investigations of diverse risk factors and the pathophysiological underpinnings of allergic diseases. By employing multi-omics approaches-proteomics, transcriptomics, and metabolomics-we gain deeper insights into the distinct pathophysiological processes across various endotypes of childhood allergic diseases, incorporating the exposome using extensive resources within the COCOA study. Integration with large-scale datasets, such as national health insurance records, enhances robustness and mitigates potential limitations inherent to birth cohort studies. As part of global networks focused on childhood allergic diseases, the COCOA study fosters collaborative research across multiple cohorts. The findings from the COCOA study are instrumental in informing precision medicine strategies for childhood allergic diseases, underpinning the establishment of disease trajectories.

Sequence-Type Classification of Brain MRI for Acute Stroke Using a Self-Supervised Machine Learning Algorithm

We propose a self-supervised machine learning (ML) algorithm for sequence-type classification of brain MRI using a supervisory signal from DICOM metadata (i.e., a rule-based virtual label). A total of 1787 brain MRI datasets were constructed, including 1531 from hospitals and 256 from multi-center trial datasets. The ground truth (GT) was generated by two experienced image analysts and checked by a radiologist. An ML framework called ImageSort-net was developed using various features related to MRI acquisition parameters and used for training virtual labels and ML algorithms derived from rule-based labeling systems that act as labels for supervised learning. For the performance evaluation of ImageSort-net (MLvirtual), we compare and analyze the performances of models trained with human expert labels (MLhumans), using as a test set blank data that the rule-based labeling system failed to infer from each dataset. The performance of ImageSort-net (MLvirtual) was comparable to that of MLhuman (98.5% and 99%, respectively) in terms of overall accuracy when trained with hospital datasets. When trained with a relatively small multi-center trial dataset, the overall accuracy was relatively lower than that of MLhuman (95.6% and 99.4%, respectively). After integrating the two datasets and re-training them, MLvirtual showed higher accuracy than MLvirtual trained only on multi-center datasets (95.6% and 99.7%, respectively). Additionally, the multi-center dataset inference performances after the re-training of MLvirtual and MLhumans were identical (99.7%). Training of ML algorithms based on rule-based virtual labels achieved high accuracy for sequence-type classification of brain MRI and enabled us to build a sustainable self-learning system.

Identification of acute myocardial infarction and stroke events using the National Health Insurance Service database in Korea

OBJECTIVES

The escalating burden of cardiovascular disease (CVD) is a critical public health issue worldwide. CVD, especially acute myocardial infarction (AMI) and stroke, is the leading contributor to morbidity and mortality in Korea. We aimed to develop algorithms for identifying AMI and stroke events from the National Health Insurance Service (NHIS) database and validate these algorithms through medical record review.

METHODS

We first established a concept and definition of "hospitalization episode," taking into account the unique features of health claims-based NHIS database. We then developed first and recurrent event identification algorithms, separately for AMI and stroke, to determine whether each hospitalization episode represents a true incident case of AMI or stroke. Finally, we assessed our algorithms' accuracy by calculating their positive predictive values (PPVs) based on medical records of algorithm- identified events.

RESULTS

We developed identification algorithms for both AMI and stroke. To validate them, we conducted retrospective review of medical records for 3,140 algorithm-identified events (1,399 AMI and 1,741 stroke events) across 24 hospitals throughout Korea. The overall PPVs for the first and recurrent AMI events were around 92% and 78%, respectively, while those for the first and recurrent stroke events were around 88% and 81%, respectively.

CONCLUSIONS

We successfully developed algorithms for identifying AMI and stroke events. The algorithms demonstrated high accuracy, with PPVs of approximately 90% for first events and 80% for recurrent events. These findings indicate that our algorithms hold promise as an instrumental tool for the consistent and reliable production of national CVD statistics in Korea.

Frequency, Predictors, and Clinical Impact of Valvular and Perivalvular Thrombus After Transcatheter Aortic Valve Replacement

BACKGROUND

Subclinical aortic valve complex (valvular and perivalvular) thrombus is not rare after transcatheter aortic valve replacement (TAVR). The risk factors and clinical implications of these findings remain uncertain.

OBJECTIVES

This study sought to evaluate the frequency, predictors, and clinical outcome of aortic valve complex thrombus after TAVR.

METHODS

In the ADAPT-TAVR (Anticoagulation Versus Dual Antiplatelet Therapy for Prevention of Leaflet Thrombosis and Cerebral Embolization After Transcatheter Aortic Valve Replacement) trial comparing edoxaban vs dual antiplatelet therapy in TAVR patients without an indication for chronic anticoagulation, the frequency of valvular (subclinical leaflet thrombus) and perivalvular (supravalvular, subvalvular, and sinus of Valsalva) thrombus was evaluated by 4-dimensional computed tomography at 6 months. The association of these phenomena with new cerebral thromboembolism on brain magnetic resonance imaging, neurologic and neurocognitive dysfunction, and clinical outcomes was assessed.

RESULTS

Among 211 patients with 6-month computed tomography evaluations, 91 patients (43.1%) had thrombus at any aortic valve complex, 30 (14.2%) patients had leaflet thrombus, and 78 (37.0%) patients had perivalvular thrombus. A small maximum diameter of the stent at the valve level and low body surface area were independent predictors of aortic valve complex and perivalvular thrombus, and decreased renal function was an independent predictor of leaflet thrombus. No significant differences were observed in new cerebral lesions, neurologic or neurocognitive functions, or clinical outcomes among patients with or without valvular or perivalvular thrombus.

CONCLUSIONS

Subclinical aortic valve complex (valvular and perivalvular) thrombus was common in patients who had undergone successful TAVR. However, these imaging phenomena were not associated with new cerebral thromboembolism, neurologic or neurocognitive dysfunction, or adverse clinical outcomes. (Anticoagulation Versus Dual Antiplatelet Therapy for Prevention of Leaflet Thrombosis and Cerebral Embolization After Transcatheter Aortic Valve Replacement [ADAPT-TAVR]; NCT03284827).

Impact of leaflet thrombosis on valve haemodynamic status after transcatheter aortic valve replacement

OBJECTIVES

The effect of subclinical leaflet thrombosis, characterised by hypoattenuated leaflet thickening (HALT), on the valve haemodynamic function and durability of the bioprosthetic valve, is not yet determined. We determined the impact of HALT on valve haemodynamics after transcatheter aortic valve replacement (TAVR) and the predictors of haemodynamic structural valve deterioration (SVD).

METHODS

The Anticoagulation vs Dual Antiplatelet Therapy for Prevention of Leaflet Thrombosis and Cerebral Embolization after Transcatheter Aortic Valve Replacement(ADAPT-TAVR) trial is a multicenter, randomised trial that compared edoxaban and dual antiplatelet therapy in patients who had undergone successful TAVR. The presence of HALT was evaluated by four-dimensional CT at 6 months and serial echocardiography performed at baseline, immediately post-TAVR and after 6 months. SVD was defined as at least one of the following: (1) mean transprosthetic gradient ≥20 mm Hg, (2) change in the mean gradient ≥10 mm Hg from baseline, or (3) new or increase in intraprosthetic aortic regurgitation of at least ≥1 grade, resulting in moderate or greater regurgitation.

RESULTS

At 6 months, HALT was found in 30 of 211 (14.2%) patients. The presence of HALT did not significantly affect aortic valve mean gradients (with vs without HALT; 14.0±4.8 mm Hg vs 13.7±5.5 mm Hg; p=0.74) at 6 months. SVD was reported in 30 of 206 patients (14.6%) at 6-month follow-up echocardiography. Older age (OR: 1.138; 95% CI: 1.019 to 1.293; p=0.033), use of aortic valve size ≤23 mm (OR: 6.254; 95% CI: 2.230 to 20.569; p=0.001) and mean post-TAVR pressure gradient (OR: 1.233; 95% CI: 1.123 to 1.371; p<0.001) were independent predictors of haemodynamic SVD; however, the presence of HALT was not identified as a predictor of SVD.

CONCLUSIONS

In patients who had undergone successful TAVR, aortic valve haemodynamic status was not influenced by the presence of HALT. Although HALT was not a predictor of haemodynamic SVD at 6 months, it warrants further longer-term follow-up to evaluate the effect on long-term valve durability.

TRIAL REGISTRATION NUMBER

NCT03284827 (https://www.

CLINICALTRIALS

gov).

Association of Plant Protein Intake With Risk of Incident CKD: A UK Biobank Study

RATIONALE & OBJECTIVE

Data suggest that various dietary interventions slow kidney disease progression and improve clinical outcomes for those with chronic kidney disease (CKD). However, the association between plant protein intake and incident CKD has been uncertain.

STUDY DESIGN

Prospective cohort study.

SETTING & PARTICIPANTS

117,809 participants who completed at least 1 dietary questionnaire and had an estimated glomerular filtration rate (eGFR) ≥ 60mL/min/1.73m2, a urinary albumin-creatinine ratio (UACR)<30mg/g, and no history of CKD.

EXPOSURE

Daily plant protein intake in g/kg/day.

OUTCOME

Incident CKD based on the International Classification of Diseases, 10th Revision (ICD-10) or the Office of Population Censuses and Surveys Classification of Interventions and Procedures, version 4 (OPCS-4) codes.

ANALYTICAL APPROACH

A cause-specific proportional hazards analysis incorporating competing risks that treated death occurring before incident CKD as a competing event.

RESULTS

During a median follow-up period of 9.9 years, incident CKD occurred in 3,745 participants (3.2%; incidence rate, 3.2 per 1,000 person-years). In a multivariable model, the adjusted hazard ratio (AHR) for the second, third, and highest quartiles of plant protein intake was 0.90 (95% CI, 0.82-0.99), 0.83 (95% CI, 0.75-0.92), and 0.82 (95% CI, 0.73-0.93), respectively, compared with the lowest quartile. Modeled as a continuous variable, the AHR per 0.1g/kg/day plant protein intake increase was 0.96 (95% CI, 0.93-0.99). This beneficial association was also consistent in secondary analyses for which CKD was defined based on codes or 2 consecutive measures of eGFR<60mL/min/1.73m2 or UACR>30mg/g. Various sensitivity analyses demonstrated consistent findings.

LIMITATIONS

Potential incomplete dietary assessments; limited generalizability due to the characteristics of participants in the UK Biobank Study.

CONCLUSIONS

In this large, prospective cohort study, greater dietary plant protein intake was associated with a lower risk of incident CKD. Further interventional studies demonstrating the kidney-protective benefits of plant protein intake are warranted.

PLAIN-LANGUAGE SUMMARY

Plant-based diets confer various health benefits, including lowering the risk of cardiovascular disease and certain cancers. However, the relationship between plant protein intake and the risk of chronic kidney disease (CKD) remains unclear. Our study investigated the association between plant protein intake and the development of CKD. Using the UK Biobank Study data, we found that participants with a higher plant protein intake had a lower risk of developing CKD. Our finding suggests that a higher dietary intake of plant-based protein may be beneficial for kidney health and provides insight into dietary interventions to prevent CKD in primary care settings.

Beliefs, self-efficacy, subjective norms, and eating behaviors according to the breakfast frequency among female university students in South Korea

BACKGROUND/OBJECTIVES

Skipping breakfast is prevalent in young adult women. This study examined the psychosocial factors and eating behaviors according to the breakfast frequency among female university students.

SUBJECTS/METHODS

The subjects were female university students in Seoul, South Korea. A survey was done, and the data from 291 students were analyzed. The subjects were categorized into a high breakfast group (HBG) and low breakfast group (LBG). Analysis of covariance and multiple linear regression were mainly used in data analysis.

RESULTS

The subjects had breakfast 3.6 days/week on average. The HBG (47.4%) and the LBG (52.6%) differed significantly in breakfast status, including place, people eating together, breakfast menu, and breakfast preparers (P < 0.001). The HBG agreed more strongly with the advantages of breakfast than the LBG (P < 0.001). The disadvantages/barriers of breakfast were stronger in the LBG (P < 0.001). The HBG felt more confidence in having breakfast (P < 0.001) and confidence in general eating behaviors (P < 0.05). The two groups also differed in the subjective norms from parents/professionals (P < 0.001) and siblings/friends (P < 0.01). The HBG showed desirable eating behaviors more frequently (P < 0.001) and undesirable eating behaviors less frequently (P < 0.001). Multiple regression showed that the following were significantly related to the breakfast frequency, explaining 57.3% of the variance: self-efficacy regarding having breakfast (P < 0.001), perceived barriers of breakfast (no appetite/habit/indigestion, P < 0.001), desirable and undesirable eating behaviors (P < 0.01), subjective norms from parents/professionals (P < 0.05), and perceived barriers due to lack of time/preparation difficulties (P < 0.05).

CONCLUSIONS

Psychosocial factors and eating behaviors were significantly related to the breakfast frequency. Nutrition education might include strategies to increase self-efficacy for breakfast, modify the beliefs, particularly the disadvantages/barriers of breakfast, adopt desirable eating behaviors, and elicit support from significant others.

Large Duct Pancreatic Ductal Adenocarcinoma: A Morphological Variant of Pancreatic Ductal Adenocarcinoma With Distinct CT and MRI Characteristics

OBJECTIVE

To investigate the imaging characteristics of large duct pancreatic ductal adenocarcinoma (LD-PDAC) on computed tomography (CT) and magnetic resonance imaging (MRI).

MATERIALS AND METHODS

Thirty-five patients with LD-PDAC (63.2 ± 9.7 years) were retrospectively evaluated. Tumor morphology on CT and MRI (predominantly solid mass vs. solid mass with prominent cysts vs. predominantly cystic mass) was evaluated. Additionally, the visibility, quantity, shape (oval vs. branching vs. irregular), and MRI signal intensity of neoplastic cysts within the LD-PDAC were investigated. The radiological diagnoses rendered for LD-PDAC in radiology reports were reviewed.

RESULTS

LD-PDAC was more commonly observed as a solid mass with prominent cysts (45.7% [16/35] on CT and 37.1% [13/35] on MRI) or a predominantly cystic mass (20.0% [7/35] on CT and 40.0% [14/35] on MRI) and less commonly as a predominantly solid mass on CT (34.3% [12/35]) and MRI (22.9% [8/35]). The tumor morphology on imaging was significantly associated with the size of the cancer gland on histopathological examination (P = 0.020 [CT] and 0.013 [MRI]). Neoplastic cysts were visible in 88.6% (31/35) and 91.4% (32/35) of the LD-PDAC cases on CT and MRI, respectively. The cysts appeared as branching (51.6% [16/35] on CT and 59.4% [19/35] on MRI) or oval shapes (45.2% [14/35] on CT and 31.2% [10/35] on MRI) with fluid-like MRI signal intensity. In the radiology reports, 10 LD-PDAC cases (28.6%) were misinterpreted as diseases other than typical PDAC, particularly intraductal papillary mucinous neoplasms.

CONCLUSION

LD-PDAC frequently appears as a solid mass with prominent cysts or as a predominantly cystic mass on CT and MRI. Radiologists should be familiar with the imaging features of LD-PDAC to avoid misdiagnosis.

Prognostic significance of 25-hydroxyvitamin D levels in patients with peripheral T-cell lymphoma

Vitamin D insufficiency has been linked to unfavourable outcomes in diverse malignancies. However, the prognostic significance of vitamin D levels in peripheral T-cell lymphoma (PTCL) remains unclear. In this study, we thus aimed to assess the prognostic relevance of 25-hydroxyvitamin D [25(OH)D] levels in patients newly diagnosed with PTCL. The analysis included 144 patients with PTCL treated from March 2015 to May 2020. The median 25(OH)D level was 12.2 (1.7-48.8) ng/mL, and 59 (41%) patients had vitamin D deficiency. Patients with vitamin D deficiency demonstrated significantly worse event-free survival (EFS) and overall survival (OS). In the multivariate analysis, vitamin D was independently associated with OS, with a hazard ratio of 1.66 (95% confidence interval, 1.05-2.63, p = 0.030). These findings suggest that vitamin D deficiency significantly correlates with poor survival outcomes in patients with PTCL.

Search for Boosted Dark Matter in COSINE-100

We search for energetic electron recoil signals induced by boosted dark matter (BDM) from the galactic center using the COSINE-100 array of NaI(Tl) crystal detectors at the Yangyang Underground Laboratory. The signal would be an excess of events with energies above 4 MeV over the well-understood background. Because no excess of events are observed in a 97.7  kg·yr exposure, we set limits on BDM interactions under a variety of hypotheses. Notably, we explored the dark photon parameter space, leading to competitive limits compared to direct dark photon search experiments, particularly for dark photon masses below 4 MeV and considering the invisible decay mode. Furthermore, by comparing our results with a previous BDM search conducted by the Super-Kamionkande experiment, we found that the COSINE-100 detector has advantages in searching for low-mass dark matter. This analysis demonstrates the potential of the COSINE-100 detector to search for MeV electron recoil signals produced by the dark sector particle interactions.

[Guidelines for Evaluating Treatment Response Based on Bone Scan for Metastatic Castration-Resistant Prostate Cancer: Prostate Cancer Clinical Trial Working Group 3 Recommendations]

In prostate cancer, the bone is the most common site of metastasis, and it is essential to evaluate metastatic bone lesions to assess the tumor burden and treatment response. Castration-resistant prostate cancer refers to the state wherein the cancer continues to progress despite a significant reduction of the sex hormone level and is associated with frequent distant metastasis. The Prostate Cancer Working Group 3 (PCWG3) released guidelines that aimed to standardize the assessment of treatment effects in castration-resistant prostate cancer using bone scintigraphy. However, these guidelines can be challenging to comprehend and implement in practical settings. The purpose of this review was to provide an overview of a specific image acquisition method and treatment response assessment for bone scintigraphy-based evaluation of bone lesions in metastatic castration-resistant prostate cancer, in accordance with the PCWG3 guidelines.

CCR8 as a Therapeutic Novel Target: Omics-Integrated Comprehensive Analysis for Systematically Prioritizing Indications

Target identification is a crucial process in drug development, aiming to identify key proteins, genes, and signal pathways involved in disease progression and their relevance in potential therapeutic interventions. While C-C chemokine receptor 8 (CCR8) has been investigated as a candidate anti-cancer target, comprehensive multi-omics analyzes across various indications are limited. In this study, we conducted an extensive bioinformatics analysis integrating genomics, proteomics, and transcriptomics data to establish CCR8 as a promising anti-cancer drug target. Our approach encompassed data collection from diverse knowledge resources, gene function analysis, differential gene expression profiling, immune cell infiltration assessment, and strategic prioritization of target indications. Our findings revealed strong correlations between CCR8 and specific cancers, notably Breast Invasive Carcinoma (BRCA), Colon Adenocarcinoma (COAD), Head and Neck Squamous Cell Carcinoma (HNSC), Rectum adenocarcinoma (READ), Stomach adenocarcinoma (STAD), and Thyroid carcinoma (THCA). This research advances our understanding of CCR8 as a potential target for anti-cancer drug development, bridging the gap between molecular insights and creating opportunities for personalized treatment of solid tumors.

Detection rate of brain MR and MR angiography for neuroimaging abnormality in patients with newly diagnosed left-sided infective endocarditis

We aimed to investigate the detection rate of brain MR and MR angiography for neuroimaging abnormality in newly diagnosed left-sided infective endocarditis patients with/without neurological symptoms. This retrospective study included consecutive patients with definite or possible left-sided infective endocarditis according to the modified Duke criteria who underwent brain MRI and MR angiography between March 2015 and October 2020. The detection rate for neuroimaging abnormality on MRI was defined as the number of patients with positive brain MRI findings divided by the number of patients with left-sided infective endocarditis. Positive imaging findings included acute ischemic lesions, cerebral microbleeds, hemorrhagic lesions, and infectious aneurysms. In addition, aneurysm rupture rate and median period to aneurysm rupture were evaluated on follow-up studies. A total 115 patients (mean age: 55 years ± 19; 65 men) were included. The detection rate for neuroimaging abnormality was 77% (89/115). The detection rate in patients without neurological symptoms was 70% (56/80). Acute ischemic lesions, cerebral microbleeds, and hemorrhagic lesions including superficial siderosis and intracranial hemorrhage were detected on MRI in 56% (64/115), 57% (66/115), and 20% (23/115) of patients, respectively. In particular, infectious aneurysms were detected on MR angiography in 3% of patients (4/115), but MR angiography in 5 patients (4.3%) was insignificant for infectious aneurysm, which were detected using CT angiography (n = 3) and digital subtraction angiography (n = 2) during follow-up. Among the 9 infectious aneurysm patients, aneurysm rupture occurred in 4 (44%), with a median period of aneurysm rupture of 5 days. The detection rate of brain MRI for neuroimaging abnormality in newly diagnosed left-sided infective endocarditis patients was high (77%), even without neurological symptoms (70%).

Effect of Edoxaban Versus Antiplatelet Therapy on Leaflet Thrombosis and Cerebral Thromboembolism After TAVI According to Major Clinical and Anatomic Factors in Prespecified Subgroup Analysis from the ADAPT-TAVR Trial

It is unknown whether edoxaban versus dual antiplatelet therapy (DAPT) has differential treatment effects on leaflet thrombosis, cerebral thromboembolism, and neurologic or neurocognitive dysfunction according to clinical and anatomic factors after transcatheter aortic valve implantation. To investigate the relative effects of edoxaban and DAPT on leaflet and cerebral thromboembolism in patients with major risk factors. The primary end point of this study was the incidence of leaflet thrombosis on computed tomography at 6 months. The secondary end points were new cerebral lesions on brain magnetic resonance imaging and neurologic and neurocognitive dysfunction between baseline and 6-month follow-up. Cox regression models assessed the consistency of the treatment effects in the prespecified subgroups. The favorable effect of edoxaban versus DAPT on the leaflet thrombosis was consistent across multiple clinical or anatomic subgroups, without significant interaction between the drug effect and each subgroup (p for interaction for age = 0.597, gender = 0.557, body mass index = 0.866, Society of Thoracic Surgeons score = 0.307, valve type = 0.702, edoxaban reduction criteria = 0.604, and valve morphology = 0.688). However, the incidence of new cerebral lesions on brain magnetic resonance imaging and worsening of neurologic and neurocognitive function were not significantly different between the groups among the various key subgroups. The relative effects of edoxaban and DAPT on the risk of leaflet thrombosis, cerebral thromboembolism, and neurologic dysfunction were consistent across a diverse spectrum of clinical or anatomical factors. Further studies are required to define tailored antithrombotic therapy for high-risk groups with specific clinical or anatomic characteristics.

Clinicoradiological Factors Predicting Lymph Node Metastasis in Patients with Nonfunctioning Pancreatic Neuroendocrine Neoplasms: A Systematic Review and Meta-Analysis

INTRODUCTION

Lymph node metastasis of nonfunctioning pancreatic neuroendocrine neoplasms (pNENs) potentially leads to poor survival. Given the contradictory results in the literature regarding factors associated with lymph node metastasis of nonfunctioning pNENs, we conducted a systematic review and meta-analysis to determine the preoperative predictors of lymph node metastasis.

METHODS

Original studies reporting factors associated with lymph node metastasis in patients with nonfunctioning pNENs were identified in PubMed, EMBASE, and Cochrane Library databases, and data from eligible studies were analyzed using random-effects meta-analysis to obtain pooled estimates of odds ratios (ORs) and their 95% confidence intervals (CIs).

RESULTS

Eleven studies were included. Tumor size (>2 cm or >2.5 cm; OR, 5.80 [95% CI, 4.07-8.25]) and pancreatic head location (OR, 1.75 [95% CI, 1.05-2.94]) were significant preoperative predictors of lymph node metastasis. Old age (OR, 1.07 [95% CI, 0.68-1.68]) and male sex (OR, 1.12 [95% CI, 0.74-1.70]) were not significantly associated with lymph node metastasis.

CONCLUSIONS

A large tumor size and pancreatic head location can be useful for planning optimal treatment in patients with nonfunctioning pNENs.

Comprehensive Analysis for Anti-Cancer Target-Indication Prioritization of Placental Growth Factor Inhibitor (PGF) by Use of Omics and Patient Survival Data

The expression of the placental growth factor (PGF) in cancer cells and the tumor microenvironment can contribute to the induction of angiogenesis, supporting cancer cell metabolism by ensuring an adequate blood supply. Angiogenesis is a key component of cancer metabolism as it facilitates the delivery of nutrients and oxygen to rapidly growing tumor cells. PGF is recognized as a novel target for anti-cancer treatment due to its ability to overcome resistance to existing angiogenesis inhibitors and its impact on the tumor microenvironment. We aimed to integrate bioinformatics evidence using various data sources and analytic tools for target-indication identification of the PGF target and prioritize the indication across various cancer types as an initial step of drug development. The data analysis included PGF gene function, molecular pathway, protein interaction, gene expression and mutation across cancer type, survival prognosis and tumor immune infiltration association with PGF. The overall evaluation was conducted given the totality of evidence, to target the PGF gene to treat the cancer where the PGF level was highly expressed in a certain tumor type with poor survival prognosis as well as possibly associated with poor tumor infiltration level. PGF showed a significant impact on overall survival in several cancers through univariate or multivariate survival analysis. The cancers considered as target diseases for PGF inhibitors, due to their potential effects on PGF, are adrenocortical carcinoma, kidney cancers, liver hepatocellular carcinoma, stomach adenocarcinoma, and uveal melanoma.

Blood eosinophil related to maternal allergic rhinitis is associated with the incidence of allergic rhinitis in offspring: COCOA study

OBJECTIVE

The identification of allergic rhinitis (AR) in early life is important for the target of intervention. AR is caused by various environmental factors, including house dust mites. We investigated the relationship between the Dermatophagoides farinae (Der f)-IgE and eosinophil in mothers with AR at delivery and the eosinophil levels and AR incidence in children.

METHODS

The study participants were 983 mother-child pairs from the COhort for Childhood Origin of Asthma and Allergic Diseases. AR was diagnosed by a doctor at delivery in mother and at 3 years of age in offspring. The association between eosinophil level and AR was assessed using logistic regression analysis.

RESULTS

The Der f-IgE level in mother having AR at delivery was associated with the mother's eosinophil level, and the mother's eosinophil level was associated with the child's eosinophil level both at age 1 and 3. The risk of AR at age 3 in children was increased according to increased eosinophil levels in mothers at delivery and in children both aged 1 and 3 years (adjusted odds ratio [aOR] and 95% confidence interval [CI]: 2.57 [1.14-5.78], 2.28 [1.02-5.13], respectively). The risk of childhood AR at the age of 3 is increased when both mothers and children have high eosiniophils (aOR and 95% CI: 2.62 [1.01-6.79], 1.37 [0.98-1.91]).

CONCLUSIONS

Der f-IgE in mothers at delivery was related to eosinophil levels in mothers with AR and higher level of eosinophils in both mother and children was associated with the increased risk of AR incidence at the first 3 years of life of children.

Simulation Method for the Physical Deformation of a Three-Dimensional Soft Body in Augmented Reality-Based External Ventricular Drainage

OBJECTIVES

Intraoperative navigation reduces the risk of major complications and increases the likelihood of optimal surgical outcomes. This paper presents an augmented reality (AR)-based simulation technique for ventriculostomy that visualizes brain deformations caused by the movements of a surgical instrument in a three-dimensional brain model. This is achieved by utilizing a position-based dynamics (PBD) physical deformation method on a preoperative brain image.

METHODS

An infrared camera-based AR surgical environment aligns the real-world space with a virtual space and tracks the surgical instruments. For a realistic representation and reduced simulation computation load, a hybrid geometric model is employed, which combines a high-resolution mesh model and a multiresolution tetrahedron model. Collision handling is executed when a collision between the brain and surgical instrument is detected. Constraints are used to preserve the properties of the soft body and ensure stable deformation.

RESULTS

The experiment was conducted once in a phantom environment and once in an actual surgical environment. The tasks of inserting the surgical instrument into the ventricle using only the navigation information presented through the smart glasses and verifying the drainage of cerebrospinal fluid were evaluated. These tasks were successfully completed, as indicated by the drainage, and the deformation simulation speed averaged 18.78 fps.

CONCLUSIONS

This experiment confirmed that the AR-based method for external ventricular drain surgery was beneficial to clinicians.

Artificial Intelligence in Gastric Cancer Imaging With Emphasis on Diagnostic Imaging and Body Morphometry

Gastric cancer remains a significant global health concern, coercing the need for advancements in imaging techniques for ensuring accurate diagnosis and effective treatment planning. Artificial intelligence (AI) has emerged as a potent tool for gastric-cancer imaging, particularly for diagnostic imaging and body morphometry. This review article offers a comprehensive overview of the recent developments and applications of AI in gastric cancer imaging. We investigated the role of AI imaging in gastric cancer diagnosis and staging, showcasing its potential to enhance the accuracy and efficiency of these crucial aspects of patient management. Additionally, we explored the application of AI body morphometry specifically for assessing the clinical impact of gastrectomy. This aspect of AI utilization holds significant promise for understanding postoperative changes and optimizing patient outcomes. Furthermore, we examine the current state of AI techniques for the prognosis of patients with gastric cancer. These prognostic models leverage AI algorithms to predict long-term survival outcomes and assist clinicians in making informed treatment decisions. However, the implementation of AI techniques for gastric cancer imaging has several limitations. As AI continues to evolve, we hope to witness the translation of cutting-edge technologies into routine clinical practice, ultimately improving patient care and outcomes in the fight against gastric cancer.

Respiratory microbiome profiles are associated with distinct inflammatory phenotype and lung function in children with asthma

BACKGROUND

Respiratory microbiome studies have fostered our understanding of various phenotypes and endotypes of heterogeneous asthma. However, the relationship between the respiratory microbiome and clinical phenotypes in children with asthma remains unclear. We aimed to identify microbiome-driven clusters reflecting the clinical features of asthma and their dominant microbiotas in children with asthma.

METHODS

Induced sputum was collected from children with asthma, and microbiome profiles were generated via sequencing of the V3-V4 region of the 16S rRNA gene. Cluster analysis was performed using the partitioning around medoid clustering method. The dominant microbiota in each cluster was determined using the Linear Discriminant Effect Size analysis. Each cluster was analyzed for association among the dominant microbiota, clinical phenotype, and inflammatory cytokine.

RESULTS

Eighty-three children diagnosed with asthma were evaluated. Among four clusters reflecting the clinical characteristics of asthma, cluster 1, dominated by Haemophilus and Neisseria, demonstrated lower post-bronchodilator (BD) forced expiratory volume in 1 second (FEV1)/forced vital capacity (FVC) than that in the other clusters and more mixed granulocytic asthma. Neisseria negatively correlated with pre-BD and post-BD FEV1/FVC. Haemophilus and Neisseria positively correlated with programmed death-ligand (PD-L)1.

CONCLUSION

To our knowledge, this study is the first to analyze the relationship between an unbiased microbiome-driven cluster and clinical phenotype in children with asthma. The cluster dominated by Haemophilus and Neisseria showed fixed airflow obstruction and mixed granulocytic asthma, which correlated with PD-L1 levels. Thus, microbiome-driven unbiased clustering can help identify new asthma phenotypes related to endotypes in childhood asthma.

Systolic blood pressure, low-density lipoprotein cholesterol levels, and adverse kidney outcome: results from KNOW-CKD

It is unknown whether intensive control of blood pressure (BP) and lipids can delay the progression of chronic kidney disease (CKD). This study examined the combined association of strict targets of systolic BP (SBP) and low-density lipoprotein cholesterol (LDL-C) levels with adverse kidney outcomes. In total, 2012 patients from the KoreaN Cohort Study for Outcomes in Patients With CKD (KNOW-CKD) were classified into four groups according to SBP of 120 mmHg and LDL-C of 70 mg/dl: group 1, <120 and <70; group 2, <120 and ≥70; group 3, ≥120 and <70; group 4, ≥120 and ≥70. We constructed time-varying models treating two variables as time-varying exposures. The primary outcome was the progression of CKD, defined as a ≥50% decrease in estimated glomerular filtration rate from the baseline or the onset of kidney failure requiring replacement therapy. The primary outcome events occurred in 27.9%, 26.7%, 40.3%, and 39.1% from groups 1 to 4. In the time-varying model, the hazard ratios (95% confidence intervals) for the primary outcome were 0.48 (0.33-0.69), 0.78 (0.63-0.96), and 0.96 (0.74-1.23) for groups 1 to 3, respectively, compared with group 4. When less stringent cut-offs of SBP of 130 mmHg and LDL-C of 100 mg/dl were used, this graded association was lost, while only SBP was associated with adverse kidney outcomes. In this study, the lower targets of SBP of <120 mmHg and LDL-C < 70 mg/dl were synergistically associated with a lower risk of adverse kidney outcomes.

Radiologic Assessment of Lung Edema Score as a Predictor of Clinical Outcome in Children with Acute Respiratory Distress Syndrome

PURPOSE

The radiographic assessment of lung edema (RALE) score enables objective quantification of lung edema and is a valuable prognostic marker of adult acute respiratory distress syndrome (ARDS). We aimed to evaluate the validity of RALE score in children with ARDS.

MATERIALS AND METHODS

The RALE score was measured for its reliability and correlation to other ARDS severity indices. ARDS-specific mortality was defined as death from severe pulmonary dysfunction or the need for extracorporeal membrane oxygenation therapy. The C-index of the RALE score and other ARDS severity indices were compared via survival analyses.

RESULTS

Among 296 children with ARDS, 88 did not survive, and there were 70 ARDS-specific non-survivors. The RALE score showed good reliability with an intraclass correlation coefficient of 0.809 [95% confidence interval (CI), 0.760-0.848]. In univariable analysis, the RALE score had a hazard ratio (HR) of 1.19 (95% CI, 1.18-3.11), and the significance was maintained in multivariable analysis adjusting with age, ARDS etiology, and comorbidity, with an HR of 1.77 (95% CI, 1.05-2.91). The RALE score was a good predictor of ARDS-specific mortality, with a C-index of 0.607 (95% CI, 0.519-0.695).

CONCLUSION

The RALE score is a reliable measure for ARDS severity and a useful prognostic marker of mortality in children, especially for ARDS-specific mortality. This score provides information that clinicians can use to decide the proper time of aggressive therapy targeting severe lung injury and to appropriately manage the fluid balance of children with ARDS.

Cerebral Glutamate Alterations Using Chemical Exchange Saturation Transfer Imaging in a Rat Model of Lipopolysaccharide-Induced Sepsis

Glutamate-weighted chemical exchange saturation transfer (GluCEST) is a useful imaging tool to detect glutamate signal alterations caused by neuroinflammation. This study aimed to visualize and quantitatively evaluate hippocampal glutamate alterations in a rat model of sepsis-induced brain injury using GluCEST and proton magnetic resonance spectroscopy (¹H-MRS). Twenty-one Sprague Dawley rats were divided into three groups (sepsis-induced groups (SEP05, n = 7 and SEP10, n = 7) and controls (n = 7)). Sepsis was induced through a single intraperitoneal injection of lipopolysaccharide (LPS) at a dose of 5 mg/kg (SEP05) or 10 mg/kg (SEP10). GluCEST values and ¹H-MRS concentrations in the hippocampal region were quantified using conventional magnetization transfer ratio asymmetry and a water scaling method, respectively. In addition, we examined immunohistochemical and immunofluorescence staining to observe the immune response and activity in the hippocampal region after LPS exposure. The GluCEST and ¹H-MRS results showed that GluCEST values and glutamate concentrations were significantly higher in sepsis-induced rats than those in controls as the LPS dose increased. GluCEST imaging may be a helpful technique for defining biomarkers to estimate glutamate-related metabolism in sepsis-associated diseases.

The effects of muscle mass and quality on mortality of patients with acute kidney injury requiring continuous renal replacement therapy

This study examined the effects of muscle mass on mortality in patients with acute kidney injury requiring continuous renal replacement therapy. It was conducted in eight medical centers between 2006 and 2021. The data of 2200 patients over the age of 18 years with acute kidney injury who required continuous renal replacement therapy were retrospectively collected. Skeletal muscle areas, categorized into normal and low attenuation muscle areas, were obtained from computed tomography images at the level of the third lumbar vertebra. Cox proportional hazards models were used to investigate the association between mortality within 1, 3, and 30 days and skeletal muscle index. Sixty percent of patients were male, and the 30-day mortality rate was 52%. Increased skeletal muscle areas/body mass index was associated with decreased mortality risk. We also identified a 26% decreased risk of low attenuation muscle area/body mass index on mortality. We established that muscle mass had protective effects on the mortality of patients with acute kidney injury requiring continuous renal replacement therapy. This study showed that muscle mass is a significant determinant of mortality, even if the density is low.

Treatment With Liposomal Irinotecan Plus Fluorouracil and Leucovorin for Patients With Previously Treated Metastatic Biliary Tract Cancer: The Phase 2b NIFTY Randomized Clinical Trial

Importance

The NIFTY trial demonstrated the benefit of treatment with second-line liposomal irinotecan (nal-IRI) plus fluorouracil (FU) and leucovorin (LV) for patients with advanced biliary tract cancer (BTC).

Objective

To report the updated efficacy outcomes from the NIFTY trial with extended follow-up of 1.3 years with reperformed masked independent central review (MICR) with 3 newly invited radiologists.

Design, Setting, and Participants

The NIFTY trial was a randomized, multicenter, open-label, phase 2b clinical trial conducted between September 5, 2018, and December 31, 2021, at 5 tertiary referral centers in South Korea. Patients with advanced BTC whose disease progressed while receiving first-line gemcitabine plus cisplatin with at least 1 measurable lesion per Response Evaluation Criteria in Solid Tumors, version 1.1, were eligible. Data analysis was completed on May 9, 2022.

Interventions

Patients were randomized 1:1 to receive LV, 400 mg/m2, bolus and FU, 2400 mg/m2, for a 46-hour infusion intravenously every 2 weeks with or without nal-IRI, 70 mg/m2, before LV intravenously. Patients were treated until disease progression or unacceptable toxic effects.

Main Outcomes and Measures

Primary end point was progression-free survival (PFS) as assessed by MICR. Secondary end points were PFS as assessed by the investigator, overall survival, and objective response rate.

Results

A total of 178 patients (75 women [42.1%]; median [IQR] age, 64 [38-84] years) were randomly assigned, and 174 patients were included in the full analysis set (88 patients [50.6%] in the nal-IRI plus FU/LV group vs 86 patients [49.4%] in the FU/LV alone group). In this updated analysis, the median MICR-assessed PFS was 4.2 months (95% CI, 2.8-5.3) for the nal-IRI plus FU/LV group and 1.7 months (95% CI, 1.4-2.6) for the FU/LV alone group (hazard ratio, 0.61; 95% CI, 0.44-0.86; P = .004), in contrast to the 7.1 and 1.4 months reported in the previous study, respectively. The discordance rate for tumor progression date between the MICR and investigators was 17.8% (vs 30% in the previous study).

Conclusions and Relevance

The NIFTY randomized clinical trial demonstrated significant improvement in PFS with treatment with nal-IRI plus FU/LV compared with FU/LV alone for patients with advanced BTC after progression to gemcitabine plus cisplatin. The combination of nal-IRI plus FU/LV could be considered as a second-line treatment option for patients with previously treated advanced BTC.

Trial Registration

clinicaltrials.gov Identifier: NCT03524508.

TEV/FEV₃ as a coherent metric of small airway dysfunction in childhood asthma

Background: Spirometry is an unrivalled tool for determining asthma and asthma severity. The ratio of forced expiratory volume (FEV) in 1 second (FEV₁) to forced vital capacity (FVC) and the forced expiratory flow between 25% and 75% of FVC (FEF_25-75) are well-known markers of airway obstruction, but they are limited by low reproducibility, particularly in children. In this study, we defined terminal expiration volume (TEV) as FEV in 3 seconds forced expiratory volume in 3 seconds (FEV₃) minus forced expiratory volume in 1 seconds (FEV₁) and investigate whether TEV/FEV₃ can function as a coherent marker to compensate for existing markers. Methods: This retrospective study comprised 980 children ages ≤ 18 years who underwent spirometry and the bronchial provocation testing. TEV/FEV₃ was compared with regard to asthma presence and severity. The findings were verified with an external validation group (n = 105). Results: FEV₃ was obtained in 837 children (85.4%). TEV/FEV₃ was significantly higher in patients with asthma than in patients who did not have asthma (17.1 ± 5.5 versus 12.0 ± 4.4, p < 0.001). External validation with 73 patients showed similar results (18.0 ± 5.9 in asthma versus 10.2 ± 5.1 in non-asthma, p < 0.001). The discriminatory power of TEV/FEV₃ for asthma was comparable with that of FEF_25-75 (p = 0.804). TEV/FEV₃ significantly increased with asthma severity (mild, 16.1 ± 5.4; moderate, 17.7 ± 5.4; severe, 22.0 ± 5.3; p < 0.001). For patients who could not achieve FEV₃, FEF_25-75 demonstrated no significant difference between mild and moderate asthma, and could not discriminate asthma or asthma severity. Conclusion: TEV/FEV₃ is a new metric that may help diagnose and determine asthma severity by using conventional spirometry by assessing small airway dysfunction. TEV/FEV₃ promotes a reassessment of the reliability of other spirometric parameters, particularly in young children. Caution is needed in interpreting the result of spirometry in children who cannot achieve FEV₃.

Is aryl hydrocarbon receptor antagonism after ischemia effective in alleviating acute hepatic ischemia-reperfusion injury in rats?

Aryl hydrocarbon receptors (AhRs) have been reported to be important mediators of ischemic injury in the brain. Furthermore, the pharmacological inhibition of AhR activation after ischemia has been shown to attenuate cerebral ischemia-reperfusion (IR) injury. Here, we investigated whether AhR antagonist administration after ischemia was also effective in ameliorating hepatic IR injury. A 70% partial hepatic IR (45-min ischemia and 24-h reperfusion) injury was induced in rats. We administered 6,2',4'-trimethoxyflavone (TMF, 5 mg/kg) intraperitoneally 10 min after ischemia. Hepatic IR injury was observed using serum, magnetic resonance imaging-based liver function indices, and liver samples. TMF-treated rats showed significantly lower relative enhancement (RE) values and serum alanine aminotransferase (ALT) and aspartate aminotransferase levels than did untreated rats at 3 h after reperfusion. After 24 h of reperfusion, TMF-treated rats had significantly lower RE values, ΔT1 values, serum ALT levels, and necrotic area percentage than did untreated rats. The expression of the apoptosis-related proteins, Bax and cleaved caspase-3, was significantly lower in TMF-treated rats than in untreated rats. This study demonstrated that inhibition of AhR activation after ischemia was effective in ameliorating IR-induced liver injury in rats.

Dithianon exposure induces dopaminergic neurotoxicity in Caenorhabditis elegans

Dithianon is a conventional broad-spectrum protectant fungicide widely used in agriculture, but its potential neurotoxic risk to animals remains largely unknown. In this study, neurotoxic effects of Dithianon and its underlying cellular and molecular mechanisms were investigated using the nematode, Caenorhabditis elegans, as a model system. Upon chronic exposure of C. elegans to Dithianon, dopaminergic neurons were found to be vulnerable, with significant degeneration in terms of structure and function in a concentration-dependent manner. In examining toxicity mechanisms, we observed significant Dithianon-induced increases in oxidative stress and mitochondrial fragmentation, both of which are often associated with cellular stress. The present study suggests that Dithianon exposure causes dopaminergic neurotoxicity in C. elegans, by inducing oxidative stress and mitochondrial dysfunction. These findings contribute to a better understanding of Dithianon's neurotoxic potential.

Associations of prenatal antibiotic exposure and delivery mode on childhood asthma inception

BACKGROUND

Prenatal antibiotic exposure and delivery mode may affect the gut microbiome in early life and influence the development of childhood asthma, but the combined effect of these two factors is unknown.

OBJECTIVE

To identify the individual and combined effects of prenatal antibiotic exposure and delivery mode on the development of asthma in children and the potential mechanisms underlying these associations.

METHODS

A total of 789 children were enrolled from the Cohort for Childhood Origin of Asthma and Allergic Diseases (COCOA) birth cohort study. Asthma was defined as physician-confirmed diagnosis with asthma symptoms in the previous 12 months at age 7. Information on the prenatal antibiotic exposure was obtained by mothers using questionnaire. Logistic regression analysis was used. Gut microbiota analysis using 16S rRNA gene sequencing of fecal specimens obtained at 6 months was undertaken for 207 infants.

RESULTS

Prenatal antibiotic exposure and cesarean section delivery (adjusted odds ratio [aOR], 95% confidence interval [CI], 5.70 [1.25-22.81] and 1.57 [1.36-6.14], respectively) were associated with childhood asthma, especially synergistically when compared to the vaginal delivery-prenatal antibiotic exposure reference group (aOR, 7.35; 95% CI, 3.46-39.61; Interaction P=.033). Prenatal antibiotic exposure was associated with childhood asthma with aORs 21.79 and 27.03 for one and two or more exposures, respectively. Significant small-airway dysfunction (R5-R20 in impulse oscillometry) was observed with prenatal antibiotic exposure and cesarean-section delivery, compared to those with spontaneous delivery without prenatal antibiotic exposure. There was no significant difference in the diversity of gut microbiota among the four groups. However, the relative abundance of Clostridium was significantly increased in infants with prenatal antibiotic exposure and delivered via cesarean section.

CONCLUSION

Prenatal antibiotic exposure and delivery mode might modulate asthma development in children and small-airway dysfunction, potentially through early-life gut microbiota alterations.

Prognostic artificial intelligence model to predict 5 year survival at 1 year after gastric cancer surgery based on nutrition and body morphometry

BACKGROUND

Personalized survival prediction is important in gastric cancer patients after gastrectomy based on large datasets with many variables including time-varying factors in nutrition and body morphometry. One year after gastrectomy might be the optimal timing to predict long-term survival because most patients experience significant nutritional change, muscle loss, and postoperative changes in the first year after gastrectomy. We aimed to develop a personalized prognostic artificial intelligence (AI) model to predict 5 year survival at 1 year after gastrectomy.

METHODS

From a prospectively built gastric surgery registry from a tertiary hospital, 4025 gastric cancer patients (mean age 56.1 ± 10.9, 36.2% females) treated gastrectomy and survived more than a year were selected. Eighty-nine variables including clinical and derived time-varying variables were used as input variables. We proposed a multi-tree extreme gradient boosting (XGBoost) algorithm, an ensemble AI algorithm based on 100 datasets derived from repeated five-fold cross-validation. Internal validation was performed in split datasets (n = 1121) by comparing our proposed model and six other AI algorithms. External validation was performed in 590 patients from other hospitals (mean age 55.9 ± 11.2, 37.3% females). We performed a sensitivity analysis to analyse the effect of the nutritional and fat/muscle indices using a leave-one-out method.

RESULTS

In the internal validation, our proposed model showed AUROC of 0.8237, which outperformed the other AI algorithms (0.7988-0.8165), 80.00% sensitivity, 72.34% specificity, and 76.17% balanced accuracy. In the external validation, our model showed AUROC of 0.8903, 86.96% sensitivity, 74.60% specificity, and 80.78% balanced accuracy. Sensitivity analysis demonstrated that the nutritional and fat/muscle indices influenced the balanced accuracy by 0.31% and 6.29% in the internal and external validation set, respectively. Our developed AI model was published on a website for personalized survival prediction.

CONCLUSIONS

Our proposed AI model provides substantially good performance in predicting 5 year survival at 1 year after gastric cancer surgery. The nutritional and fat/muscle indices contributed to increase the prediction performance of our AI model.

Development and validation of a deep learning model to diagnose COVID-19 using time-series heart rate values before the onset of symptoms

One of the effective ways to minimize the spread of COVID-19 infection is to diagnose it as early as possible before the onset of symptoms. In addition, if the infection can be simply diagnosed using a smartwatch, the effectiveness of preventing the spread will be greatly increased. In this study, we aimed to develop a deep learning model to diagnose COVID-19 before the onset of symptoms using heart rate (HR) data obtained from a smartwatch. In the deep learning model for the diagnosis, we proposed a transformer model that learns HR variability patterns in presymptom by tracking relationships in sequential HR data. In the cross-validation (CV) results from the COVID-19 unvaccinated patients, our proposed deep learning model exhibited high accuracy metrics: sensitivity of 84.38%, specificity of 85.25%, accuracy of 84.85%, balanced accuracy of 84.81%, and area under the receiver operating characteristics (AUROC) of 0.8778. Furthermore, we validated our model using external multiple datasets including healthy subjects, COVID-19 patients, as well as vaccinated patients. In the external healthy subject group, our model also achieved high specificity of 77.80%. In the external COVID-19 unvaccinated patient group, our model also provided similar accuracy metrics to those from the CV: balanced accuracy of 87.23% and AUROC of 0.8897. In the COVID-19 vaccinated patients, the balanced accuracy and AUROC dropped by 66.67% and 0.8072, respectively. The first finding in this study is that our proposed deep learning model can simply and accurately diagnose COVID-19 patients using HRs obtained from a smartwatch before the onset of symptoms. The second finding is that the model trained from unvaccinated patients may provide less accurate diagnosis performance compared with the vaccinated patients. The last finding is that the model trained in a certain period of time may provide degraded diagnosis performances as the virus continues to mutate.