Atomic Layer Deposition of Zirconia on Titanium Implants Improves Osseointegration in Rabbit Bones.

Purpose: Atomic layer deposition (ALD) is a method that can deposit zirconia uniformly on an atomic basis. The effect of deposited zirconia on titanium implants using ALD was evaluated in vivo. Methods: Machined titanium implants (MTIs) were used as the Control. MTIs treated by sandblasting with large grit and acid etching (SA) and MTIs deposited with zirconia using ALD are referred to as Groups S and Z, respectively. Twelve implants were prepared for each group. Six rabbits were used as experimental animals. To evaluate the osteogenesis and osteocyte aspects around the implants, radiological and histological analyses were performed. The bone-to-implant contact (BIC) ratio was measured and statistically analyzed to evaluate the osseointegration capabilities. Results: In the micro-CT analysis, more radiopaque bone tissues were observed around the implants in Groups S and Z. Histological observation found that Groups S and Z had more and denser mature bone tissues around the implants in the cortical bone area. Many new and mature bone tissues were also observed in the medullary cavity area. For the BIC ratio, Groups S and Z were significantly higher than the Control in the cortical bone area (P < 0.017), but there was no significant difference between Groups S and Z. Conclusion: MTIs deposited with zirconia using ALD (Group Z) radiologically and histologically showed more mature bone formation and activated osteocytes compared with MTIs (Control). Group Z also had a significantly higher BIC ratio than the Control. Within the limitations of this study, depositing zirconia on the surface of MTIs using ALD can improve osseointegration in vivo.

Automated Scoring of Alzheimer's Disease Atrophy Scale with Subtype Classification Using Deep Learning-Based T1-Weighted Magnetic Resonance Image Segmentation.

Background: Application of visual scoring scales for regional atrophy in Alzheimer's disease (AD) in clinical settings is limited by their high time cost and low intra/inter-rater agreement. Objective: To provide automated atrophy scoring using objective volume driven from deep-learning segmentation methods for AD subtype classification using magnetic resonance imaging (MRI). Methods: We enrolled 3,959 participants (1,732 cognitively normal [CN], 1594 with mild cognitive impairment [MCI], and 633 with AD). The occupancy indices for each regional volume were calculated by dividing each volume by the size of the lateral and inferior ventricular volumes. MR images from 355 participants (119 CN, 119 MCI, and 117 AD) from three different centers were used for validation. Two neuroradiologists performed visual assessments of the medial temporal, posterior, and global cortical atrophy scores in the frontal lobe using T1-weighted MR images. Images were also analyzed using the deep learning-based segmentation software, Neurophet AQUA. Cutoff values for the three scores were determined using the data distribution according to age. The scoring results were compared for consistency and reliability. Results: Four volumetric-driven scoring results showed a high correlation with the visual scoring results for AD, MCI, and CN. The overall agreement with human raters was weak-to-moderate for atrophy scoring in CN participants, and good-to-almost perfect in AD and MCI participants. AD subtyping by automated scores also showed usefulness as a research tool. Conclusions: Determining AD subtypes using automated atrophy scoring for late-MCI and AD could be useful in clinical settings or multicenter studies with large datasets.

Femoral osteoporosis prediction model using autosegmentation and machine learning analysis with PyRadiomics on abdomen-pelvic computed tomography (CT).

Background: With the advancement of artificial intelligence technology and radiomics analysis, opportunistic prediction of osteoporosis with computed tomography (CT) is a new paradigm in osteoporosis screening. This study aimed to assess the diagnostic performance of osteoporosis prediction by the combination of autosegmentation of the proximal femur and machine learning analysis with a reference standard of dual-energy X-ray absorptiometry (DXA). Methods: Abdomen-pelvic CT scans were retrospectively analyzed from 1,122 patients who received both DXA and abdomen-pelvic computed tomography (APCT) scan from January 2018 to December 2020. The study cohort consisted of a training cohort and a temporal validation cohort. The left proximal femur was automatically segmented, and a prediction model was built by machine-learning analysis using a random forest (RF) analysis and 854 PyRadiomics features. The technical success rate of autosegmentation, diagnostic test, area under the receiver operator characteristics curve (AUC), and precision recall curve (AUC-PR) analysis were used to analyze the training and validation cohorts. Results: The osteoporosis prevalence of the training and validation cohorts was 24.5%, and 10.3%, respectively. The technical success rate of autosegmentation of the proximal femur was 99.7%. In the diagnostic test, the training and validation cohorts showed 78.4% vs. 63.3% sensitivity, 89.4% vs. 98.1% specificity. The prediction performance to identify osteoporosis within the groups used for training and validation cohort was high and the AUC and AUC-PR to forecast the occurrence of osteoporosis within the training and validation cohorts were 90.8% [95% confidence interval (CI), 88.4-93.2%] vs. 78.0% (95% CI, 76.0-79.9%) and 94.6% (95% CI, 89.3-99.8%) vs. 88.8% (95% CI, 86.2-91.5%), respectively. Conclusions: The osteoporosis prediction model using autosegmentation of proximal femur and machine-learning analysis with PyRadiomics features on APCT showed excellent diagnostic feasibility and technical success.

Development of a prediction model for cognitive impairment of sarcopenia using multimodal neuroimaging in non-demented older adults.

INTRODUCTION: Despite prior research on the association between sarcopenia and cognitive impairment in the elderly, a comprehensive model that integrates various brain pathologies is still lacking. METHODS: We used data from 528 non-demented older adults with or without sarcopenia in the Catholic Aging Brain Imaging (CABI) database, containing magnetic resonance imaging scans, positron emission tomography scans, and clinical data. We also measured three key components of sarcopenia: skeletal muscle index (SMI), hand grip strength (HGS), and the five times sit-to-stand test (5STS). RESULTS: All components of sarcopenia were significantly correlated with global cognitive function, but cortical thickness and amyloid-beta (Aß) retention had distinctive relationships with each measure. In the path model, brain atrophy resulting in cognitive impairment was mediated by Aß retention for SMI and periventricular white matter hyperintensity for HGS, but directly affected by the 5STS. DISCUSSION: Treatments targeting each sub-domain of sarcopenia should be considered to prevent cognitive decline. HIGHLIGHTS: We identified distinct impacts of three sarcopenia measures on brain structure and Aß. Muscle mass is mainly associated with Aß and has an influence on the brain atrophy. Muscle strength linked with periventricular WMH and brain atrophy. Muscle function associated with cortical thinning in specific brain regions. Interventions on sarcopenia may be important to ease cognitive decline in the elderly.

Genome-wide association study comparison analysis based on Hanwoo full-sib family.

Objective: The improvement of carcass traits is essential for the Hanwoo industry because of the Hanwoo grade determination system, and Genome-Wide Association Study (GWAS) analysis is an instrumental tool for identifying the genetic factors that impact these traits. While GWAS analysis utilizing family data offers advantages in minimizing genetic bias, research on family-based GWAS in Hanwoo is currently lacking. Methods: This study classified Group A using both parental and offspring genetic information, and Group B based solely on offspring genetic information, to compare GWAS analysis results of Hanwoo carcass traits. Results: 16 significant SNP markers (carcass weight (CWT) 7, back fat thickness (BFT) 3, marbling score (MS) 6) were identified in Group A, and 7 significant SNP markers (CWT 3, eye muscle area (EMA) 1, BFT 1, MS 2) were identified in Group B. Functional annotation analysis revealed only one common function related to carcass traits between the groups, while Protein-protein interaction (PPI) analysis indicated more gene interactions in Group A. The reliability of estimated values for common SNP markers identified between the groups was higher in Group A. Conclusion: GWAS analysis utilizing parental genetic information holds greater potential for application, owing to its higher reliability of estimated values and the ability to explore numerous candidate genes.

Clinician-Driven Reanalysis of Exome Sequencing Data From Patients With Inherited Retinal Diseases.

Importance: Despite advances in next-generation sequencing (NGS), a significant proportion of patients with inherited retinal disease (IRD) remain undiagnosed after initial genetic testing. Exome sequencing (ES) reanalysis in the clinical setting has been suggested as one method for improving diagnosis of IRD. Objective: To investigate the association of clinician-led reanalysis of ES data, which incorporates updated clinical information and comprehensive bioinformatic analysis, with the diagnostic yield in a cohort of patients with IRDs in Korea. Design, Setting, and Participants: This was a multicenter prospective cohort study involving 264 unrelated patients with IRDs, conducted in Korea between March 2018 and February 2020. Comprehensive ophthalmologic examinations and ES analyses were performed, and ES data were reanalyzed by an IRD specialist for single nucleotide variants, copy number variants, mobile element insertions, and mitochondrial variants. Data were analyzed from March to July 2023. Main Outcomes and Measures: Diagnostic rate of conventional bioinformatic analysis and clinician-driven ES reanalysis. Results: A total of 264 participants (151 [57.2%] male; mean [SD] age at genetic testing, 33.6 [18.9] years) were enrolled, including 129 patients (48.9%) with retinitis pigmentosa and 26 patients (9.8%) with Stargardt disease or macular dystrophy. Initial bioinformatic analysis diagnosed 166 patients (62.9%). Clinician-driven reanalysis identified the molecular cause of diseases in an additional 22 patients, corresponding to an 8.3-percentage point increase in diagnostic rate. Key factors associated with new molecular diagnoses included clinical phenotype updates (4 patients) and detection of previously overlooked variation, such as structural variants (9 patients), mitochondrial variants (3 patients), filtered or not captured variants (4 patients), and noncanonical splicing variants (2 patients). Among the 22 patients, variants in 7 patients (31.8%) were observed in the initial analysis but not reported to patients, while those in the remaining 15 patients (68.2%) were newly detected by the ES reanalysis. Conclusions and Relevance: In this cohort study, clinician-centered reanalysis of ES data was associated with improved molecular diagnostic yields in patients with IRD. This approach is important for uncovering missed genetic causes of retinal disease.

Contagious infection-free medical interaction system with machine vision controlled by remote hand gesture during an operation.

Background and objective: Medical image visualization is a requirement in many types of surgery such as orthopaedic, spinal, thoracic procedures or tumour resection to eliminate risk such as "wrong level surgery". However, direct contact with physical devices such as mice or touch screens to control images is a challenge because of the potential risk of infection. To prevent the spread of infection in sterile environments, a contagious infection-free medical interaction system has been developed for manipulating medical images. Methods: We proposed an integrated system with three key modules: hand landmark detection, hand pointing, and hand gesture recognition. A proposed depth enhancement algorithm is combined with a deep learning hand landmark detector to generate hand landmarks. Based on the designed system, a proposed hand-pointing system combined with projection and ray-pointing techniques allows for reducing fatigue during manipulation. A proposed landmark geometry constraint algorithm and deep learning method were applied to detect six gestures including click, open, close, zoom, drag, and rotation. Additionally, a control menu was developed to effectively activate common functions. Results: The proposed hand-pointing system allowed for a large control range of up to 1200 mm in both vertical and horizontal direction. The proposed hand gesture recognition method showed high accuracy of over 97% and real-time response. Conclusion: This paper described the contagious infection-free medical interaction system that enables precise and effective manipulation of medical images within the large control range, while minimizing hand fatigue.

Effects of Serious Games in Older Adults With Mild Cognitive Impairment.

OBJECTIVE: The rising prevalence of mild cognitive impairment (MCI) has spurred interest in innovative cognitive rehabilitation approaches, including serious games. This review summarizes randomized clinical trials (RCTs) exploring the impact of serious games on MCI patients. METHODS: We conducted a comprehensive data search using key terms such as "gamification," "digital therapy," "cognition," "mild cognitive impairment," and "Alzheimer's disease." We exclusively considered published RCTs, excluding animal studies and basic research. RESULTS: We identified eight RCTs. Four RCTs examined the effects of serious games using cognitive training for MCI patients. Notably, one study found that non-specific training (Nintendo Wii) significantly enhanced cognitive function and quality of life compared to cognition-specific computer training (CoTras). Among the remaining three RCTs, one specifically demonstrated that personalized serious game-based cognitive training yielded superior cognitive outcomes and reduced depressive symptoms. One RCT focused on serious games incorporating physical exercise, highlighting the effectiveness of kinetic-based exergaming in enhancing overall cognition. Three RCT focused on combined cognitive training and physical exercise. A double-blind RCT revealed that progressive resistance training or standalone physical exercise outperformed the combined approach in improving executive function and global cognition. Two additional RCTs reported positive outcomes, including improvements in cognitive function and electroencephalogram patterns associated with game-based interventions. CONCLUSION: Serious games, whether focusing on cognitive training, physical exercise, or a combination of both, have potential to improve cognitive and functional outcomes in individuals with MCI. Further research and standardization of protocols are needed to better understand the full potential of serious games in MCI.

A multimodal machine learning model for predicting dementia conversion in Alzheimer's disease.

Alzheimer's disease (AD) accounts for 60-70% of the population with dementia. Mild cognitive impairment (MCI) is a diagnostic entity defined as an intermediate stage between subjective cognitive decline and dementia, and about 10-15% of people annually convert to AD. We aimed to investigate the most robust model and modality combination by combining multi-modality image features based on demographic characteristics in six machine learning models. A total of 196 subjects were enrolled from four hospitals and the Alzheimer's Disease Neuroimaging Initiative dataset. During the four-year follow-up period, 47 (24%) patients progressed from MCI to AD. Volumes of the regions of interest, white matter hyperintensity, and regional Standardized Uptake Value Ratio (SUVR) were analyzed using T1, T2-weighted-Fluid-Attenuated Inversion Recovery (T2-FLAIR) MRIs, and amyloid PET (αPET), along with automatically provided hippocampal occupancy scores (HOC) and Fazekas scales. As a result of testing the robustness of the model, the GBM model was the most stable, and in modality combination, model performance was further improved in the absence of T2-FLAIR image features. Our study predicts the probability of AD conversion in MCI patients, which is expected to be useful information for clinician's early diagnosis and treatment plan design.

Soft-tissue volume augmentation using a connective tissue graft and a volume-stable collagen matrix with polydeoxyribonucleotide for immediate implant placement: a pilot study in a dog model.

PURPOSE: The aims of this study were 1) to investigate the effects of a subepithelial connective tissue graft (SCTG) and a volume-stable collagen matrix (VCMX) on soft-tissue volume gain in the immediate implant placement protocol, and 2) to determine whether polydeoxyribonucleotide (PDRN) can enhance the effects of a VCMX. METHODS: Dental implants were placed in 4 mongrel dogs immediately after extracting the distal roots of their third and fourth mandibular premolars. The gap between the implant and the buccal bone plate was filled with synthetic bone substitute particles. The following soft-tissue augmentation modalities were applied buccally: 1) control (no augmentation), 2) SCTG, 3) VCMX, and 4) VCMX/PDRN. After 4 months, histomorphometric analysis was performed. Tissue changes were evaluated using superimposed standard tessellation language (STL) files. RESULTS: Wound dehiscence was found in more than half of the test groups, but secondary wound healing was successfully achieved in all groups. Histomorphometrically, tissue thickness was favored in group SCTG at or above the implant platform level (IP), and group SCTG and the groups with VCMX presented similar tissue thickness below the IP. However, the differences in such thickness among the groups were minor. The keratinized tissue height was greater in group VCMX/PDRN than in groups SCTG and VCMX. Superimposing the STL files revealed a decrease in soft-tissue volume in all groups. CONCLUSIONS: Wound dehiscence after soft-tissue volume augmentation might be detrimental to obtaining the expected outcomes. PDRN appears not to have a positive effect on the soft-tissue volume gain.

Awareness of Proton Pump Inhibitor Adverse Events and Treatment Pattern Change According to Physician Practice: A National Questionnaire Study in Korea.

Although adverse events of proton pump inhibitors (PPIs) have been reported, there are few studies on physicians' perceptions. We aimed to investigate physicians' awareness of PPI-related adverse events and changes in treatment patterns according to their practice. We conducted an online survey of physicians using a 15-item questionnaire. The survey queried respondents' demographic information, PPI prescription patterns, perceptions, and concerns on the reported PPI-related adverse events. Concerns regarding the adverse events of PPI were assessed by dividing them into possibilities and medical causality. Of the 450 respondents, 430 were specialists, and 232 were gastroenterologists. A total of 87.8% of the respondents were generally or well aware of the adverse effects of PPI, 29.1% considered side effects when prescribing PPI, and 14.6% explained them to patients. Specialists were more aware of the side effects of PPI than general practitioners (p = 0.005), and gastroenterologists were more aware of the side effects of PPI than non-gastroenterologists (p < 0.001). However, gastroenterologists explained less to patients (p = 0.001) and preferred to reduce the dose of PPI rather than discontinue it. The adverse events that were recognized as having the highest probability of occurrence and strongest association with PPI use were bone diseases, Clostridium difficile infection, gastrointestinal infection, pneumonia, and interactions with anti-thrombotic drugs. Physicians' awareness of PPI-related adverse events and treatment patterns differed significantly according to their positions and practice. Although a number of adverse events of PPIs were reported, physicians seem to accept their significance differently according to their specialty and practice patterns.

Digital therapeutics using virtual reality-based visual perceptual learning for visual field defects in stroke: A double-blind randomized trial.

INTRODUCTION: Visual field defects (VFDs) represent a debilitating poststroke complication, characterized by unseen parts of the visual field. Visual perceptual learning (VPL), involving repetitive visual training in blind visual fields, may effectively restore visual field sensitivity in cortical blindness. This current multicenter, double-blind, randomized, controlled clinical trial investigated the efficacy and safety of VPL-based digital therapeutics (Nunap Vision [NV]) for treating poststroke VFDs. METHODS: Stroke outpatients with VFDs (>6 months after stroke onset) were randomized into NV (defective field training) or Nunap Vision-Control (NV-C, central field training) groups. Both interventions provided visual perceptual training, consisting of orientation, rotation, and depth discrimination, through a virtual reality head-mounted display device 5 days a week for 12 weeks. The two groups received VFD assessments using Humphrey visual field (HVF) tests at baseline and 12-week follow-up. The final analysis included those completed the study (NV, n = 40; NV-C, n = 35). Efficacy measures included improved visual area (sensitivity ≥6 dB) and changes in the HVF scores during the 12-week period. RESULTS: With a high compliance rate, NV and NV-C training improved the visual areas in the defective hemifield (>72 degrees2) and the whole field (>108 degrees2), which are clinically meaningful improvements despite no significant between-group differences. According to within-group analyses, mean total deviation scores in the defective hemifield improved after NV training (p = .03) but not after NV-C training (p = .12). CONCLUSIONS: The current trial suggests that VPL-based digital therapeutics may induce clinically meaningful visual improvements in patients with poststroke VFDs. Yet, between-group differences in therapeutic efficacy were not found as NV-C training exhibited unexpected improvement comparable to NV training, possibly due to learning transfer effects.

Multi-target aptamer assay for endocrine-disrupting phthalic acid ester panel screening in plastic leachates.

A multi-target aptamer assay was developed as a phthalic acid ester (PAE) panel to screen selected PAEs in plastic leachate samples. The panel comprises 13 PAEs (PAE-13), namely dimethyl phthalate, diethyl phthalate, di-n-butyl phthalate, di-n-hexyl phthalate, diisobutyl phthalate, diisononyl phthalate, diisodecyl phthalate, mono-2-ethylhexyl phthalate, di-2-ethylhexyl phthalate, diphenyl phthalate, butyl benzyl phthalate, dicyclohexyl phthalate, and phthalic acid. Herein, we proposed an aptamer assay using a newly truncated aptamer (20-mer) and the 7-aminoactinomycin D fluorophore, which selectively binds to guanine in single-stranded DNA, resulting in increased fluorescence intensity. The assay is highly selective for PAE-13 clusters. The selectivity of the assay was evaluated using 13 different PAEs and mixtures depending on the side chain structure. The quantitative detection of PAEs was demonstrated by adopting mixed PAE-13 simulants and achieved a limit of detection of ∼1.4 pg/mL. The repeatability and reproducibility of the assay were also evaluated by presenting acceptable coefficients of variation (%CV less than 10% and 15%, respectively). The performance of the assay was demonstrated by analyzing the plastic leachate samples, and the positive correlation (correlation coefficient, r = 0.985) was confirmed by comparing them with the total sum of individual PAE peak areas obtained by gas chromatography mass spectrometry analysis.

Millingtonia hortensis L.f. ethanol extract exerts in vivo and in vitro anti-inflammatory activities through inhibition of Syk kinase in NF-κB pathway.

ETHNOPHARMACOLOGICAL RELEVANCE: Millingtonia hortensis L.f., commonly known as tree jasmine or Indian cork tree, is native to South Asia and Southeast Asia. Traditionally, its stem bark, leaves, and roots are employed for pulmonary, gastrointestinal, and antimicrobial purposes, while the flowers are used in treating asthma and sinusitis. AIM OF THE STUDY: The underlying anti-inflammatory mechanisms of M. hortensis remain relatively unexplored. Therefore, we studied the anti-inflammatory effects of M. hortensis and the molecular mechanisms of its ethanol extracts (Mh-EE) both in vitro and in vivo. MATERIALS AND METHODS: Nitric oxide (NO) production was assessed using Griess reagent, while cell viability of RAW264.7 cell and HEK293T cells were determined via the MTT assay. Constituent analysis of Mh-EE using GC/MS-MS and HPLC, and mRNA expression of inflammatory cytokines was measured through PCR and RT-PCR. Protein levels were analyzed using western blotting. The thermal stability of Mh-EE was evaluated by CESTA. Lastly, a gastritis in vivo model was induced by HCl/EtOH, and protein expression levels were measured using western blotting. RESULTS: Mh-EE significantly reduced NO production in LPS-induced RAW264.7 cells without substantially affecting cell viability. Additionally, Mh-EE decreased the expression of proinflammatory factors, such as iNOS, IL-1ß and COX2. Furthermore, Mh-EE downregulated TLR4 expression, altered MyD88 recruitment, and suppressed phosphorylation of Syk, IKKα, IκBα and AKT. Simultaneously, Mh-EE also attenuated NF-κB signaling in HCl/EtOH-induced mice. CONCLUSIONS: Mh-EE exerts anti-inflammatory effects by suppressing p-Syk in the NF-κB pathway, and it has potential as a novel treatment agent for inflammatory diseases.

Modulation of Bone Mineral Density and Its Response to Menopausal Hormone Therapy according to the Apolipoprotein E Genotype in Postmenopausal Korean Women.

OBJECTIVES: Genetic factors are a major cause of osteoporosis. The present study evaluated the association of the apolipoprotein E (ApoE) genotype with bone mineral density (BMD) and its response to menopausal hormone therapy (MHT) in postmenopausal Korean women. METHODS: This retrospective cohort study included 172 postmenopausal women with no endocrine diseases, medications, or lifestyles that would affect bone metabolism and who were continuously treated with MHT for at least 2 years. BMDs were measured at baseline and periodically. RESULTS: Linear regression analysis demonstrated similar baseline BMDs at the lumbar spine, but significantly lower at the femur neck and total hip in the ApoE ε4 carrier than in the noncarrier group, after controlling for age, body mass index, and history of MHT usage. Overall, the Wilcoxon signed rank test demonstrated that MHT increased the BMD percentage change at all three regions, and the Generalized Estimating Equation (GEE) demonstrated significant time trends at the lumbar spine and femur neck. ApoE ε4 noncarriers exhibited a significant time trend in BMD changes at the femur neck, whereas ε4 carriers exhibited a time trend at the lumbar spine. However, BMD changes at each time point were comparable at all regions between the groups. Notably, GEE adjusted for baseline characteristics and BMD revealed a significant interaction effect of time and ApoE ε4 allele in BMD changes at the femur neck. CONCLUSIONS: Postmenopausal Korean women carrying the ApoE ε4 allele demonstrated a lower hip BMD compared with ε4 noncarriers. Furthermore, the ε4 allele may modulate hip BMD responses to MHT.

Subjective Experience on Virtual Reality-Assisted Mental Health Promotion Program.

OBJECTIVE: Mental health promotion programs using virtual reality (VR) technology have been developed in various forms. This study aimed to investigate the subjective experience of a VR-assisted mental health promotion program for the community population, which was provided in the form of VR experience on a bus to increase accessibility. METHODS: Ninety-six people participated in this study. The relationship between the subjective experience and mental health states such as depression, anxiety, perceived stress, and quality of life was explored. The subjective experience on depression and stress before and after VR program treatment was compared using the Wilcoxon signed-rank test. The satisfaction with the VR-assisted mental health promotion program was examined after using the VR program. RESULTS: The VR-assisted mental health promotion program on a bus significantly improved subjective symptoms such as depression (p=0.036) and perceived stress (p=0.010) among all the participants. Among the high-risk group, this VR program significantly relieved subjective depressive feeling score (p=0.033), and subjective stressful feeling score (p=0.035). In contrast, there were no significant changes in subjective depressive feelings (p=0.182) and subjective stressful feelings (p=0.058) among the healthy group. Seventy-two percent of the participants reported a high level of satisfaction, scoring 80 points or more. CONCLUSION: The findings of this study suggest that the VR-assisted mental health promotion program may effectively improve the subjective depressive and stressful feelings. The use of VR programs on buses to increase of accessibility for the community could be a useful approach for promoting mental health among the population.

Prediction of High-Risk Neuroblastoma Among Neuroblastic Tumors Using Radiomics Features Derived from Magnetic Resonance Imaging: A Pilot Study.

PURPOSE: This study aimed to predict high-risk neuroblastoma among neuroblastic tumors using radiomics features extracted from MRI. MATERIALS AND METHODS: Pediatric patients (age≤18 years) diagnosed with neuroblastic tumors who had pre-treatment MR images available were enrolled from institution A from January 2010 to November 2019 (training set) and institution B from January 2016 to January 2022 (test set). Segmentation was performed with regions of interest manually drawn along tumor margins on the slice with the widest tumor area by two radiologists. First-order and texture features were extracted and intraclass correlation coefficients (ICCs) were calculated. Multivariate logistic regression (MLR) and random forest (RF) models from 10-fold cross-validation were built using these features. The trained MLR and RF models were tested in an external test set. RESULTS: Thirty-two patients (M:F=23:9, 26.0±26.7 months) were in the training set and 14 patients (M:F=10:4, 33.4±20.4 months) were in the test set with radiomics features (n=930) being extracted. For 10 of the most relevant features selected, intra- and inter-observer variability was moderate to excellent (ICCs 0.633-0.911, 0.695-0.985, respectively). The area under the receiver operating characteristic curve (AUC) was 0.94 (sensitivity 67%, specificity 91%, and accuracy 84%) for the MLR model and the average AUC was 0.83 (sensitivity 44%, specificity 87%, and accuracy 75%) for the RF model from 10-fold cross-validation. In the test set, AUCs of the MLR and RF models were 0.94 and 0.91, respectively. CONCLUSION: An MRI-based radiomics model can help predict high-risk neuroblastoma among neuroblastic tumors.

Effect of the sodium-glucose cotransporter-2 inhibitor, DWP16001, as an add-on therapy to insulin for diabetic dogs: A pilot study.

BACKGROUND: Sodium-glucose cotransporter-2 (SGLT2) inhibitors are a novel class of anti-hyperglycaemic agents. OBJECTIVE: This study aimed to evaluate the safety and the adjuvant glycaemic control effect of an SGLT2 inhibitor, DWP16001, in diabetic dogs receiving insulin treatment. METHODS: Nineteen diabetic dogs receiving insulin treatment (NPH, porcine lente and glargine insulin) were divided into two groups according to dosing frequency: DWP TOD group (n = 10) and DWP SID group (n = 9). In the DWP TOD group, 0.025 mg/kg of DWP16001 was administered once every 3 days, whereas, in the DWP SID group, 0.025 mg/kg of DWP16001 was administered once a day. Food intake was maintained during the trial period. Hypoglycaemia, ketoacidosis or unexpected life-threatening reactions were assessed as adverse effects before and after DWP16001 administration. We compared insulin requirement reduction and blood glucose level control between two groups. RESULTS: No specific adverse effects were observed during the clinical trial, and haematological parameter remained unchanged. Moreover, the fasting glucose levels and daily insulin dose in the DWP TOD group were lower than the pre-administration values, but not significantly different for 8 weeks. Systolic blood pressure, fructosamine and insulin dose decreased significantly in the DWP SID group compared to the DWP TOD group at 8 weeks (p < 0.05) without affecting food consumption. Among these patients, 10 patients were monitored while receiving DWP16001 for 12 months (DWP TOD group n = 5, DWP SID group n = 5). The fasting glucose and fructosamine levels and daily insulin dose were reduced in both groups at 12 months compared with those before receiving DWP16001. CONCLUSION: When DWP16001, an SGLT2 inhibitor, was supplied to dogs with type 1 diabetes, no adverse effects were observed, and it was confirmed that the administered insulin dose can be reduced in controlling blood glucose.

Evaluating Linkage Quality of Population-Based Administrative Data for Health Service Research.

BACKGROUND: To overcome the limitations of relying on data from a single institution, many researchers have studied data linkage methodologies. Data linkage includes errors owing to legal issues surrounding personal information and technical issues related to data processing. Linkage errors affect selection bias, and external and internal validity. Therefore, quality verification for each connection method with adherence to personal information protection is an important issue. This study evaluated the linkage quality of linked data and analyzed the potential bias resulting from linkage errors. METHODS: This study analyzed claims data submitted to the Health Insurance Review and Assessment Service (HIRA DATA). The linkage errors of the two deterministic linkage methods were evaluated based on the use of the match key. The first deterministic linkage uses a unique identification number, and the second deterministic linkage uses the name, gender, and date of birth as a set of partial identifiers. The linkage error included in this deterministic linkage method was compared with the absolute standardized difference (ASD) of Cohen's according to the baseline characteristics, and the linkage quality was evaluated through the following indicators: linked rate, false match rate, missed match rate, positive predictive value, sensitivity, specificity, and F1-score. RESULTS: For the deterministic linkage method that used the name, gender, and date of birth as a set of partial identifiers, the true match rate was 83.5 and the missed match rate was 16.5. Although there was bias in some characteristics of the data, most of the ASD values were less than 0.1, with no case greater than 0.5. Therefore, it is difficult to determine whether linked data constructed with deterministic linkages have substantial differences. CONCLUSION: This study confirms the possibility of building health and medical data at the national level as the first data linkage quality verification study using big data from the HIRA. Analyzing the quality of linkages is crucial for comprehending linkage errors and generating reliable analytical outcomes. Linkers should increase the reliability of linked data by providing linkage error-related information to researchers. The results of this study will serve as reference data to increase the reliability of multicenter data linkage studies.

Prognosis of subsequent pregnancy in uterine necrosis after uterine artery embolization.

In an 8-year period at two medical center, 138 patients underwent uterine artery embolization, and 11 of them were diagnosed with uterine necrosis. Among them, three were successfully conceived. However, one of them developed an arteriovenous malformation after an artificial abortion, and another experienced complications, including placenta previa and placenta accreta spectrum, which resulted in early preterm delivery and recurrent postpartum hemorrhage, necessitating subtotal hysterectomy. Therefore, it is crucial to prepare for potential adverse pregnancy outcomes in subsequent pregnancies for patients with a history of uterine necrosis.