Single-channel seizure detection with clinical confirmation of seizure locations using CHB-MIT dataset.

Introduction: Long-term electroencephalography (EEG) monitoring is advised to patients with refractory epilepsy who have a failure of anti-seizure medication and therapy. However, its real-life application is limited mainly due to the use of multiple EEG channels. We proposed a patient-specific deep learning-based single-channel seizure detection approach using the long-term scalp EEG recordings of the Children's Hospital Boston-Massachusetts Institute of Technology (CHB-MIT) dataset, in conjunction with neurologists' confirmation of spatial seizure characteristics of individual patients. Methods: We constructed 18-, 4-, and single-channel seizure detectors for 13 patients. Neurologists selected a specific channel among four channels, two close to the behind-the-ear and two at the forehead for each patient, after reviewing the patient's distinctive seizure locations with seizure re-annotation. Results: Our multi- and single-channel detectors achieved an average sensitivity of 97.05-100%, false alarm rate of 0.22-0.40/h, and latency of 2.1-3.4 s for identification of seizures in continuous EEG recordings. The results demonstrated that seizure detection performance of our single-channel approach was comparable to that of our multi-channel ones. Discussion: We suggest that our single-channel approach in conjunction with clinical designation of the most prominent seizure locations has a high potential for wearable seizure detection on long-term EEG recordings for patients with refractory epilepsy.

Severe Neurological Manifestation Associated With Coronavirus Disease 2019 in Children During the Omicron Variant-Predominant Period.

BACKGROUND: The Omicron variant of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is known to be more infectious and less severe than the other variants. Despite the increasing number of symptomatic patients, severe neurological complications in children with the Omicron variant have been reported rarely, unlike with wild-type or Delta variants. This study aimed to investigate severe neurological complications in children with Omicron variant infection. METHODS: We conducted a retrospective study of 17 pediatric patients with severe neurological manifestations associated with coronavirus disease 2019 in Korea during the Omicron variant prevalence, from January 1 to April 30, 2022. RESULTS: Among the 17 patients, 11 had pre-existing neurological disabilities and nine met the criteria for multisystem inflammatory syndrome in children (MIS-C). Four of the five vaccine-eligible patients (12 years and older) were unvaccinated. Severe neurological manifestations included acute necrotizing encephalopathy, acute fulminant cerebral edema, acute disseminated encephalomyelitis, basal ganglia encephalitis, unclassified severe encephalopathy/encephalitis, and refractory status dystonicus. Patients with MIS-C and underlying neurological disabilities had longer median hospital and intensive care unit stays compared with those without these conditions. Five patients survived with new neurological deficits at the one-year follow-up, and three died, all of whom had underlying neurological disabilities. CONCLUSIONS: This study shows that severe neurological complications in pediatric patients with the Omicron variant of SARS-CoV-2 occur infrequently but may lead to significant morbidity and mortality, especially among those with pre-existing neurological disabilities and unvaccinated individuals. Continued efforts are necessary to prevent and manage such complications in these vulnerable populations.

Abnormal Electroencephalogram Findings and Its Correlation With Clinical Features From Pediatric Patients in Psychiatric Clinic.

Objective: We aimed to evaluate the occurrence of electroencephalogram (EEG) abnormalities in pediatric patients attending an outpatient psychiatry clinic at a tertiary center. We examined the rates of abnormalities and specific findings based on demographics, specific diagnoses, and clinical severity. Methods: This study included pediatric patients who underwent EEG at the outpatient psychiatry clinic. Patient demographics, psychiatric diagnosis, intellectual disability, intelligent quotient (IQ) score, family history of psychiatric disorders, and Clinical Global Impression-Severity (CGI-S) score were obtained through retrospective electronic health record analysis. The rate of EEG abnormalities was calculated, and specific abnormal findings were reviewed. Relationships between the rate of EEG abnormalities and diagnosis, severity, IQ, and age at EEG examination were analyzed. Results: Of 319 patients who underwent EEG, 21.3% (68 patients) of patients exhibited abnormalities, including background abnormalities (14.7%, 47 patients), interictal epileptiform discharges (IEDs) (10.3%, 33 patients), and a slow posterior dominant rhythm (3.8%, 10 patients). The frontal region was the most commonly affected area. Neurodevelopmental disorders (NDDs) had the most frequent abnormalities (29.8%), followed by anxiety (16.7%), sleep (14.3%), mood (11.7%), psychotic (5%), and conduct disorders (0%). Disease severity did not correlate with the rate of EEG abnormalities. Adjusted for age, sex, severity, and family history, patients with EEG abnormalities exhibited lower IQ scores. Conclusion: EEG abnormalities were common in pediatric patients with psychiatric disorders, with background abnormalities detected as frequently as IEDs. Disease severity was not associated with EEG abnormality, while IQ scores showed a negative correlation.

SYNGAP1-related developmental and epileptic encephalopathy: Genotypic and phenotypic characteristics and longitudinal insights.

The clinical and genetic characteristics of SYNGAP1 mutations in Korean pediatric patients are not well understood. We retrospectively analyzed 13 individuals with SYNGAP1 mutations from a longitudinal aspect. Clinical data, genetic profiles, and electroencephalography (EEG) patterns were examined. Genotypic analyses included gene panels and whole-exome sequencing. All patients exhibited global developmental delay from early infancy, with motor development eventually reaching independent ambulation by 3 years of age. Language developmental delay varied significantly from nonverbal to simple sentences, which plateaued in all patients. Patients with the best language outcomes typically managed 2-3-word sentences, corresponding to a developmental age of 2-3 years. Epilepsy developed in 77% of patients, with onset consistently following developmental delays at a median age of 31 months. Longitudinal EEG data revealed a shift from occipital to frontal epileptiform discharges with age, suggesting a correlation with synaptic maturation. These findings suggest that the critical developmental plateau occurs between the ages of 2 and 5 years and is potentially influenced by epilepsy. By analyzing longitudinal data, our study contributes to a deeper understanding of SYNGAP1-related DEE, provides potential EEG biomarkers, and underlines the importance of early diagnosis and intervention to address this complex disorder.

Epilepsy phenotype and gene ontology analysis of the 129 genes in a large neurodevelopmental disorders cohort.

Objective: Although pediatric epilepsy is an independent disease entity, it is often observed in pediatric neurodevelopmental disorders (NDDs) as a major or minor clinical feature, which might provide diagnostic clues. This study aimed to identify the clinical and genetic characteristics of patients with epilepsy in an NDD cohort and demonstrate the importance of genetic testing. Methods: We retrospectively analyzed the detailed clinical differences of pediatric NDD patients with epilepsy according to their genetic etiology. Among 1,213 patients with NDDs, 477 were genetically diagnosed by exome sequencing, and 168 had epilepsy and causative variants in 129 genes. Causative genes were classified into two groups: (i) the "epilepsy-genes" group resulting in epilepsy as the main phenotype listed in OMIM, Epi25, and ClinGen (67 patients) and (ii) the "NDD-genes" group not included in the "epilepsy-genes" group (101 patients). Results: Patients in the "epilepsy-genes" group started having seizures, often characterized by epilepsy syndrome, at a younger age. However, overall clinical features, including treatment responses and all neurologic manifestations, showed no significant differences between the two groups. Gene ontology analysis revealed the close interactions of epilepsy genes associated with ion channels and neurotransmitters. Conclusion: We demonstrated a similar clinical presentation of different gene groups regarding biological/molecular processes in a large NDDs cohort with epilepsy. Phenotype-driven genetic analysis should cover a broad scope, and further studies are required to elucidate integrated pathomechanisms.

Deep learning-based automated detection and multiclass classification of focal interictal epileptiform discharges in scalp electroencephalograms.

Detection and spatial distribution analyses of interictal epileptiform discharges (IEDs) are important for diagnosing, classifying, and treating focal epilepsy. This study proposes deep learning-based models to detect focal IEDs in electroencephalography (EEG) recordings of the frontal, temporal, and occipital scalp regions. This study included 38 patients with frontal (n = 15), temporal (n = 13), and occipital (n = 10) IEDs and 232 controls without IEDs from a single tertiary center. All the EEG recordings were segmented into 1.5-s epochs and fed into 1- or 2-dimensional convolutional neural networks to construct binary classification models to detect IEDs in each focal region and multiclass classification models to categorize IEDs into frontal, temporal, and occipital regions. The binary classification models exhibited accuracies of 79.3-86.4%, 93.3-94.2%, and 95.5-97.2% for frontal, temporal, and occipital IEDs, respectively. The three- and four-class models exhibited accuracies of 87.0-88.7% and 74.6-74.9%, respectively, with temporal, occipital, and non-IEDs F1-scores of 89.9-92.3%, 84.9-90.6%, and 84.3-86.0%; and 86.6-86.7%, 86.8-87.2%, and 67.8-69.2% for the three- and four-class (frontal, 50.3-58.2%) models, respectively. The deep learning-based models could help enhance EEG interpretation. Although they performed well, the resolution of region-specific focal IED misinterpretations and further model improvement are needed.

Cord blood transforming growth factor-ß-induced as predictive biomarker of retinopathy of prematurity in preterm infants.

PURPOSE: To determine whether 14 inflammation-, angiogenesis-, and adhesion-related proteins in cord blood (CB), alone or in combination with conventional perinatal factors, could predict retinopathy of prematurity (ROP) in preterm infants. METHODS: Data from 111 preterm infants (born at ≤ 32.0 weeks) were retrospectively reviewed. The levels of endoglin, E-selectin, HSP70, IGFBP-3/4, LBP, lipocaline-2, M-CSFR, MIP-1α, pentraxin 3, P-selectin, TGFBI, TGF-ß1, and TNFR2 were assessed in stored CB samples collected at birth using ELISA kits. The primary endpoints included severe ROP (≥ stage 3) and type 1 ROP requiring treatment. RESULTS: ROP was diagnosed in 29 infants (26.1%), among whom 14 (12.6%) had severe ROP and seven (6.3%) had type 1 ROP. Multivariate logistic regression showed that decreased CB TGFBI levels were significantly associated with severe ROP and type 1 ROP after adjusting for gestational age at birth. Stepwise regression analysis allowed to design prediction models with good accuracy, which comprised low CB TGFBI levels and low birth weight (BW) as predictors for severe ROP (area under the curve [AUC] = 0.888), and low CB endoglin levels and low BW as predictors for type 1 ROP (AUC = 0.950). None of the other CB proteins evaluated were found to be associated with severe ROP or type 1 ROP. CONCLUSIONS: Low CB TGFBI levels are associated with severe ROP and type 1 ROP, independently of gestational age. Moreover, combined predictive models based on CB TGFBI and endoglin levels, along with BW data, may act as good indicators at birth for the neonatal risk of ROP progression.

Broad spectrum of phenotype and genotype in Korean α-dystroglycan related muscular dystrophy presenting to a tertiary pediatric neuromuscular center.

α-Dystroglycanopathies are a clinically and genetically heterogeneous group of muscular dystrophies associated with the defective glycosylation of α-dystroglycan (α-DG). Eighteen genes associated with α-dystroglycanopathies have been identified, and the relative prevalence of genetic subtypes varies with ethnicity. Here, we investigated the clinical and genetic characteristics of α-DG-related muscular dystrophy in the Korean pediatric population. We analyzed the clinical characteristics and variant profiles of 42 patients with α-DG-related muscular dystrophies diagnosed by either reduced glycosylation of α-DG and/or genetic confirmation. Genotype-phenotype correlations were explored by a retrospective medical record review. The muscle-eye-brain disease/Fukuyama congenital muscular dystrophy was the most common phenotype (28/42, 66.7%). Homozygous or compound heterozygous variants were detected in 37 patients belonging to 34 unrelated families (37/42; 88.1%). Pathogenic variants were identified in FKTN (n = 24), POMGNT1 (n = 4), GMPPB (n = 4), FKRP (n = 2), POMT1 (n = 2), and ISPD (n = 1). Compound heterozygous retrotransposal insertions and deep-intronic variants in FKTN were the most common genotypes and were associated with severe phenotypes. This study suggests that α-DG-related muscular dystrophy has a wide range of genotypes and phenotypes according to ethnicity. A stratified genetic test according to ethnicity should be considered to diagnose α-DG-related muscular dystrophy.

Outcomes of the second withdrawal of anti-seizure medication in patients with pediatric-onset epilepsy.

Withdrawal of anti-seizure medication (ASM) is challenging, especially in patients with recurrent seizures. Only limited evidence exists regarding the success rate and recurrence risk factors after withdrawal of ASM for a second time in patients with pediatric-onset epilepsy. In this observational study, we evaluated 104 patients with recurrent pediatric-onset epilepsy who had ASM withdrawn for a second time. The success rate was 41.3% after the second withdrawal of ASM. The absence of a self-limiting epilepsy syndrome, shorter seizure-free intervals before the second withdrawal of ASM, and relapse during tapering after the initial withdrawal of ASM were negative factors significantly associated with the success of ASM withdrawal for a second time. Even after a second seizure recurrence, all patients eventually became seizure-free after restarting their previous ASM (78.7%) or readjusting the ASM (21.3%). Our findings that 40% of patients with recurrent pediatric-onset epilepsy could achieve long-term seizure freedom and that all patients with a second seizure recurrence remained seizure-free suggest that ASM may be withdrawn for a second time after carefully stratifying clinical risk.

Association of inflammatory and angiogenic biomarkers in maternal plasma with retinopathy of prematurity in preterm infants.

OBJECTIVE: To investigate whether various novel inflammatory and angiogenic biomarkers in maternal plasma, alone or in combination with baseline antenatal factors, could predict retinopathy of prematurity (ROP) in preterm infants. METHODS: A retrospective cohort study was conducted on 140 premature singleton neonates born to women with preterm birth (≤32 weeks) and screened for ROP. Maternal blood obtained at the time of admission was assayed for CRP, endoglin, endostatin, IGFBP-2, IGFBP-3, IL-6, LBP, MMP-8, PlGF, S100A8/A9, TGFBI, and VEGFR-1. The primary outcome measures included severe ROP (stage 3 or higher) and type 1 ROP requiring treatment. RESULTS: ROP was present in 25.7% (36/140) of the study population, including 20 (14.3%) cases of severe ROP and 14 (10%) with type 1 ROP. Multiple logistic regression analyses revealed significant associations between high concentrations of maternal plasma LBP and severe ROP, and between elevated plasma IL-6 and LBP levels and type 1 ROP (all P < 0.05), while adjusting for confounders (i.e., gestational age [GA] at sampling). Prenatal prediction models for severe ROP and type 1 ROP were developed by combining plasma IL-6 or LBP levels with GA at sampling, which showed good discriminatory power (area under the curve = 0.747 and 0.854, respectively). CONCLUSIONS: IL-6 and LBP in maternal plasma were found to be independently associated with severe ROP and type 1 ROP. Prediction models based on these biomarkers along with GA at sampling may serve as good prenatal indicators for the neonatal risk of ROP progression in women at risk of preterm birth.

Deep Learning-Based Detection of Epileptiform Discharges for Self-Limited Epilepsy With Centrotemporal Spikes.

Centrotemporal spike-waves (CTSWs) are typical interictal epileptiform discharges (IEDs) observed in centrotemporal regions in self-limited epilepsy with centrotemporal spikes (SLECTS). This study aims to develop a deep learning-based approach for automated detection of CTSWs in scalp electroencephalography (EEG) recordings of patients with SLECTS. To lower the substantial burden of IED annotation on clinicians, we simplified it by limiting IEDs to CTSWs because electroencephalographic patterns of CTSWs are known to be highly consistent. Two neurologists annotated 1672 CTSWs of 20 patients with SLECTS. Thereafter, we performed a two-level CTSW detection procedure: epoch-level and EEG-level. In the epoch-level detection, we constructed convolutional neural network-based classification models for CTSW and non-CTSW binary classification using the recordings of 20 patients and 20 controls. We then set the thresholds of the classification models for 100% specificity. In the EEG-level detection, we applied the threshold-adjusted classification models to the recordings of 50 patients and 50 controls that were not used in the epoch-level detection to distinguish between CTSW-positive (with one or more CTSWs) and CTSW-negative (with no CTSW) recordings based on the detection of CTSW presence. We obtained an average sensitivity, specificity, and accuracy of 99.8%, 98.4%, and 99.1%, respectively, with an average false detection rate of 0.19/hr for the controls. Our approach showed high detectability for CTSWs despite the simplified annotation process. We expect that the proposed CTSW detectors have potential clinical usefulness for efficiently reading EEGs and diagnosing SLECTS, and can significantly reduce the burden of IED annotation on clinicians.

The Korean undiagnosed diseases program phase I: expansion of the nationwide network and the development of long-term infrastructure.

BACKGROUND: Phase I of the Korean Undiagnosed Diseases Program (KUDP), performed for 3 years, has been completed. The Phase I program aimed to solve the problem of undiagnosed patients throughout the country and develop infrastructure, including a data management system and functional core laboratory, for long-term translational research. Herein, we share the clinical experiences of the Phase I program and introduce the activities of the functional core laboratory and data management system. RESULTS: During the program (2018-2020), 458 patients were enrolled and classified into 3 groups according to the following criteria: (I) those with a specific clinical assessment which can be verified by direct testing (32 patients); (II) those with a disease group with genetic and phenotypic heterogeneity (353 patients); and (III) those with atypical presentations or diseases unknown to date (73 patients). All patients underwent individualized diagnostic processes based on the decision of an expert consortium. Confirmative diagnoses were obtained for 242 patients (52.8%). The diagnostic yield was different for each group: 81.3% for Group I, 53.3% for Group II, and 38.4% for Group III. Diagnoses were made by next-generation sequencing for 204 patients (84.3%) and other genetic testing for 35 patients (14.5%). Three patients (1.2%) were diagnosed with nongenetic disorders. The KUDP functional core laboratory, with a group of experts, organized a streamlined research pipeline covering various resources, including animal models, stem cells, structural modeling and metabolic and biochemical approaches. Regular data review was performed to screen for candidate genes among undiagnosed patients, and six different genes were identified for functional research. We also developed a web-based database system that supports clinical cohort management and provides a matchmaker exchange protocol based on a matchbox, likely to reinforce the nationwide clinical network and further international collaboration. CONCLUSIONS: The KUDP evaluated the unmet needs of undiagnosed patients and established infrastructure for a data-sharing system and future functional research. The advancement of the KUDP may lead to sustainable bench-to-bedside research in Korea and contribute to ongoing international collaboration.

Variations of Resting-State EEG-Based Functional Networks in Brain Maturation From Early Childhood to Adolescence.

BACKGROUND AND PURPOSE: Alterations in human brain functional networks with maturation have been explored extensively in numerous electroencephalography (EEG) and functional magnetic resonance imaging studies. It is known that the age-related changes in the functional networks occurring prior to adulthood deviate from ordinary trajectories of network-based brain maturation across the adult lifespan. METHODS: This study investigated the longitudinal evolution of resting-state EEG-based functional networks from early childhood to adolescence among 212 pediatric patients (age 12.2±3.5 years, range 4.4-17.9) in 6 frequency bands using 8 types of functional connectivity measures in the amplitude, frequency, and phase domains. RESULTS: Electrophysiological aspects of network-based pediatric brain maturation were characterized by increases in both functional segregation and integration up to middle adolescence. EEG oscillations in the upper alpha band reflected the age-related increases in mean node strengths and mean clustering coefficients and a decrease in the characteristic path lengths better than did those in the other frequency bands, especially for the phase-domain functional connectivity. The frequency-band-specific age-related changes in the global network metrics were influenced more by volume-conduction effects than by the domain specificity of the functional connectivity measures. CONCLUSIONS: We believe that this is the first study to reveal EEG-based functional network properties during preadult brain maturation based on various functional connectivity measures. The findings potentially have clinical applications in the diagnosis and treatment of age-related brain disorders.

Effects of a graphene oxide-alginate sheet scaffold on rotator cuff tendon healing in a rat model.

BACKGROUND: Natural polymer scaffolds used to promote rotator cuff healing have limitations in terms of their mechanical and biochemical properties. This animal study aimed to investigate the effects of combined graphene oxide (GO) and alginate scaffold and the toxicity of GO on rotator cuff healing in a rat model. METHODS: First, the mechanical properties of a GO/alginate scaffold and a pure alginate scaffold were compared. The in vitro cytotoxicity of and proliferation of human tenocytes with the GO/alginate scaffold were evaluated by CCK-8 assay. For the in vivo experiment, 20 male rats were randomly divided into two groups (n = 10 each), and supraspinatus repair was performed: group 1 underwent supraspinatus repair alone, and group 2 underwent supraspinatus repair with the GO/alginate scaffold. Biomechanical and histological analyses were performed to evaluate the quality of tendon-to-bone healing 8 weeks after rotator cuff repair. RESULTS: The GO/alginate scaffold exhibited an increased maximum load (p = .001) and tensile strength (p = .001). In the cytotoxicity test, the cell survival rate with the GO/alginate scaffold was 102.08%. The proliferation rate of human tenocytes was no significant difference between the GO/alginate and alginate groups for 1, 3, 5, and 7 days. Biomechanically, group 2 exhibited a significantly greater ultimate failure load (p < .001), ultimate stress (p < .001), and stiffness (p < .001) than group 1. The histological analysis revealed that the tendon-to-bone interface in group 2 showed more collagen fibers bridging, tendon-to-bone integration, longitudinally oriented collagen fibers, and fibrocartilage formation than in group 1. CONCLUSION: A small amount of GO added to alginate improved the mechanical properties of the scaffold without evidence of cytotoxicity. At 8 weeks after rotator cuff repair, the GO/alginate scaffold improved tendon-to-bone healing without causing any signs of toxicity in a rat model.

Increased interleukin-6 and TP53 levels in rotator cuff tendon repair patients with hypercholesterolemia.

BACKGROUND: A previous study reported that hyperlipidemia increases the incidence of tears in the rotator cuff tendon and affects healing after repair. The aim of our study was to compare the gene and protein expression of torn rotator cuff tendons in patients both with and without hypercholesterolemia. METHODS: Thirty patients who provided rotator cuff tendon samples were classified into either a non-hypercholesterolemia group (n=19, serum total cholesterol [TC] <200 mg/dL) and hypercholesterolemia group (n=11, serum TC ≥240 mg/dL) based on their concentrations of serum TC. The expression of various genes of interest, including COL1A1, IGF1, IL-6, MMP2, MMP3, MMP9, MMP13, TNMD, and TP53, was analyzed by real-time quantitative reverse transcription polymerase chain reaction (qRT-PCR). In addition, Western blot analysis was performed on the proteins encoded by interleukin (IL)-6 and TP53 that showed significantly different expression levels in real-time qRT-PCR. RESULTS: Except for IGF1, the gene expression levels of IL-6, MMP2, MMP9, and TP53 were significantly higher in the hypercholesterolemic group than in the non-hypercholesterolemia group. Western blot analysis confirmed significantly higher protein levels of IL-6 and TP53 in the hypercholesterolemic group (p<0.05). CONCLUSIONS: We observed an increase in inflammatory cytokine and matrix metalloproteinase (MMP) levels in hypercholesterolemic patients with rotator cuff tears. Increased levels of IL-6 and TP53 were observed at both the mRNA and protein levels. We suggest that the overexpression of IL-6 and TP53 may be a specific feature in rotator cuff disease patients with hypercholesterolemia.

Selective Serotonin Reuptake Inhibitor Promotes Bone-Tendon Interface Healing in a Rotator Cuff Tear Rat Model.

BACKGROUND: Selective serotonin reuptake inhibitor (SSRI) is believed to accelerate wound healing, and thus expected to have a positive effect on rotator cuff repair. We hypothesized that SSRI has a positive effect on the healing of the bone-tendon interface (BTI), and improved rotator cuff tear healing would be confirmed by mechanical strength measurements and histological assessment of the restored tendon. METHODS: The study used 40 adult male Sprague-Dawley wild-type rats. The animals were divided into two groups: group-SSRI, the supraspinatus repair with SSRI injection group, and group-C, conventional supraspinatus repair only without SSRI. Biomechanical and histological analyses were performed 8 weeks after index rotator cuff surgery. RESULTS: The ultimate load (N) was significantly higher in group-SSRI than in group-C (54.8 ± 56.9 Vs 25.1 ± 11.1, p = .031). In the histological evaluation, the Bonar score confirmed significant differences in collagen fiber density (group-C: 0.6 ± 0.5, group-SSRI: 1.1 ± 0.6, p = .024), vascularity (group-C: 0.1 ± 0.2, group-SSRI: 0.3 ± 0.4, p = .024) and cellularity (group-C: 1.7 ± 0.4, group-SSRI: 2.0 ± 0.0, p = .023) between the groups. Based on the total score, group-SSRI was significantly better compared with group-C (6.3 ± 2.7 Vs 4.3 ± 1.9, p = .019). CONCLUSION: Our study demonstrated that SSRI could facilitate improved biomechanical and histological outcomes 8 weeks after rotator cuff repair in a rat model. Consequently, SSRI may improve healing after rotator cuff repair.

Comparison of the Characteristics of Rotator Cuff Tissue in a Diabetic Rat Model.

This study evaluated the biomechanical and histologic characteristics of the rotator cuff tendon and muscle tissue with rat models with diabetes mellitus (DM) (group 1) and 30 male rats without DM (group 2). We conducted a time zero study without any additional procedures or external variables at 9 weeks after induction of the diabetic rat model. Thereafter, quantitative evaluation of advanced glycation end products (AGEs) was accomplished via enzyme-linked immunosorbent assay and immunohistochemistry (IHC). Fatty infiltration was investigated with Oil Red O staining, and the peroxisome proliferator activated receptor-gamma (PPAR-gamma) value was studied with IHC. Grossly, the supraspinatus tendons of the group 1 rats were more friable and discolored (yellowish) than those of group 2. In the biomechanical analysis, group 1 rats showed significantly inferior ultimate failure load (P=.001) and ultimate stress (P=.02). Group 1 was significantly inferior to group 2 in terms of total histologic scoring (P<.001). Mean AGE levels were significantly higher in group 1 (P<.001), as determined by IHC. In evaluating fatty infiltration, the degree of Oil Red O staining was significantly higher in group 1 (P<.001), but there was no significant difference in PPAR-gamma value between the 2 groups (P=.14). The intact rotator cuffs of rats with DM were associated with inferior biomechanics in association with AGE accumulation and increased fatty infiltration, as confirmed by histologic examination The hyperglycemic state caused by DM is associated with rotator cuff tendon degeneration. [Orthopedics. 2022;45(3):e154-e161.].

Clinico-radiological characteristics of anti-myelin oligodendrocyte glycoprotein antibody-associated autoimmune encephalitis in children.

AIM: To investigate the clinical characteristics and prevalence of paediatric anti-myelin oligodendrocyte glycoprotein (MOG) antibody-associated autoimmune encephalitis. METHOD: A total of 94 paediatric patients (46 males, 48 females, median age 9 years 5 months, range: 8 months-17 years 8 months) with autoimmune encephalitis were recruited at Seoul National University Children's Hospital. We evaluated autoantibody status and identified patients with anti-MOG antibody-associated autoimmune encephalitis. Retrospective reviews of medical records were performed to describe clinical presentations, laboratory findings, treatments, and outcomes. RESULTS: Eight patients (five males, three females, median age 11 years 9 months) with anti-MOG antibody-associated encephalitis were identified (8.5% of those with autoimmune encephalitis), one of whom was copositive for anti-N-methyl-d-aspartate receptor (NMDAR) antibodies. Anti-NMDAR antibodies were identified in 23 patients (23 out of 94, 24.5%). Unilateral or bilateral cortical involvement was identified in five patients. Focal contrast enhancement was also identified in three of the five patients with cortical lesions. All patients showed favourable response to immunotherapy with a Modified Rankin Scale ≤2 at the last follow-up. Relapse was found in one patient and clinico-radiological remission was achieved with cyclic intravenous immunoglobulin therapy. INTERPRETATION: Anti-MOG antibody-associated encephalitis accounts for a significant proportion of clinically defined paediatric patients with autoimmune encephalitis. Anti-MOG antibody-associated encephalitis should be included in the clinical spectrum of anti-MOG-associated diseases.

Big data analysis and artificial intelligence in epilepsy - common data model analysis and machine learning-based seizure detection and forecasting.

There has been significant interest in big data analysis and artificial intelligence (AI) in medicine. Ever-increasing medical data and advanced computing power have enabled the number of big data analyses and AI studies to increase rapidly. Here we briefly introduce epilepsy, big data, and AI and review big data analysis using a common data model. Studies in which AI has been actively applied, such as those of electroencephalography epileptiform discharge detection, seizure detection, and forecasting, will be reviewed. We will also provide practical suggestions for pediatricians to understand and interpret big data analysis and AI research and work together with technical expertise.

Effect of a Porous Suture Containing Transforming Growth Factor Beta 1 on Healing After Rotator Cuff Repair in a Rat Model.

BACKGROUND: The healing failure rate after rotator cuff repair is considerably high. PURPOSE: To evaluate the effect of a porous suture containing transforming growth factor beta 1 (TGF-ß1) on the sustained release of TGF-ß1 and rotator cuff healing in a rat model. STUDY DESIGN: Controlled laboratory study. METHODS: A porous suture was developed, and its tensile strength was measured. TGF-ß1 was delivered using the porous suture, and a TGF-ß1 release test and human fibroblast proliferation assay were performed. For the animal experiment, 30 rats were randomly allocated into 3 groups (n = 10 each). A bilateral supraspinatus tendon tear was made in all the rats, and repair was performed. Group 1 received repair only; group 2, repair and a single injection of TGF-ß1; and group 3, repair using the porous suture containing TGF-ß1. Eight weeks after repair, biomechanical and histological analyses were performed. RESULTS: The porous suture was successfully developed with mechanical properties compatible with the conventional suture, and the sustained release of TGF-ß1 from the porous suture was confirmed. In addition, the cell proliferation assay confirmed the biological safety of the porous suture. In the animal experiment, group 3 biomechanically exhibited the largest cross-sectional area and the highest ultimate failure load and ultimate stress (all P < .05). Histological examination revealed that group 3 showed significantly better collagen fiber density and tendon-to-bone maturation than did groups 1 and 2 (all P < .05). CONCLUSION: The porous suture containing TGF-ß1 could sustainedly and safely release TGF-ß1, and its use during rotator cuff repair could improve rotator cuff healing, as assessed on the basis of the biomechanical and histological changes in the rat model in this study. Considering the effectiveness, safety, and convenience of the porous suture without extra effort in surgery, the findings of the present study will have a far-reaching effect on the treatment of rotator cuff tears. CLINICAL RELEVANCE: The porous suture containing TGF-ß1 might improve healing after rotator cuff repair.