Late-Onset Ataxia-Telangiectasia Presenting With Dystonia and Tremor: The Use of Nanopore Long-Read Sequencing Solving the Variant Phase.

Objectives: This study investigates atypical late-onset ataxia-telangiectasia (AT) cases in a Korean family, diagnosed via Nanopore long-read sequencing, diverging from the typical early childhood onset caused by biallelic pathogenic ATM variants. Methods: A 52-year-old Korean woman exhibiting dystonia and tremor, with a family history of similar symptoms in her older sister, underwent comprehensive tests including routine laboratory tests, neuropsychological assessments, and neuroimaging. Genetic analysis was conducted through targeted sequencing of 29 dystonia-associated genes and Nanopore long-read sequencing to assess the configuration of 2 ATM gene variants. Results: Routine blood tests and brain imaging studies returned normal results, except for elevated α-fetoprotein levels. Neurologic examination revealed dystonia in the face, hand, and trunk, along with cervical dystonia in the proband. Her sister exhibited similar symptoms without evident telangiectasia. Genetic testing revealed 2 heterozygous pathogenic ATM gene variants (p.Glu2014Ter and p.Glu2052Lys). Nanopore long-read sequencing confirmed these variants were in trans configuration, establishing a definite molecular diagnosis in the proband. Discussion: This report expands the known clinical spectrum of AT, highlighting a familial case of atypical AT. Moreover, it underscores the clinical utility of Nanopore long-read sequencing in phasing variant haplotypes, essential for diagnosing autosomal recessive disorders, especially beneficial for cases without parental samples.

Wireless sequential dual light delivery for programmed PDT in vivo.

Using photodynamic therapy (PDT) to treat deep-seated cancers is limited due to inefficient delivery of photosensitizers and low tissue penetration of light. Polymeric nanocarriers are widely used for photosensitizer delivery, while the self-quenching of the encapsulated photosensitizers would impair the PDT efficacy. Furthermore, the generated short-lived reactive oxygen spieces (ROS) can hardly diffuse out of nanocarriers, resulting in low PDT efficacy. Therefore, a smart nanocarrier system which can be degraded by light, followed by photosensitizer activation can potentially overcome these limitations and enhance the PDT efficacy. A light-sensitive polymer nanocarrier encapsulating photosensitizer (RB-M) was synthesized. An implantable wireless dual wavelength microLED device which delivers the two light wavelengths sequentially was developed to programmatically control the release and activation of the loaded photosensitizer. Two transmitter coils with matching resonant frequencies allow activation of the connected LEDs to emit different wavelengths independently. Optimal irradiation time, dose, and RB-M concentration were determined using an agent-based digital simulation method. In vitro and in vivo validation experiments in an orthotopic rat liver hepatocellular carcinoma disease model confirmed that the nanocarrier rupture and sequential low dose light irradiation strategy resulted in successful PDT at reduced photosensitizer and irradiation dose, which is a clinically significant event that enhances treatment safety.

Prevalence and Characterization of NOTCH2NLC GGC Repeat Expansions in Koreans: From a Hospital Cohort Analysis to a Population-Wide Study.

Background and Objectives: GGC repeat expansions in the NOTCH2NLC gene are associated with a broad spectrum of progressive neurologic disorders, notably, neuronal intranuclear inclusion disease (NIID). We aimed to investigate the population-wide prevalence and clinical manifestations of NOTCH2NLC-related disorders in Koreans. Methods: We conducted a study using 2 different cohorts from the Korean population. Patients with available brain MRI scans from Seoul National University Hospital (SNUH) were thoroughly reviewed, and NIID-suspected patients presenting the zigzag edging signs underwent genetic evaluation for NOTCH2NLC repeats by Cas9-mediated nanopore sequencing. In addition, we analyzed whole-genome sequencing data from 3,887 individuals in the Korea Biobank cohort to estimate the distribution of the repeat counts in Koreans and to identify putative patients with expanded alleles and neurologic phenotypes. Results: In the SNUH cohort, among 90 adult-onset leukoencephalopathy patients with unknown etiologies, we found 20 patients with zigzag edging signs. Except for 2 diagnosed with fragile X-associated tremor/ataxia syndrome and 2 with unavailable samples, all 16 patients (17.8%) were diagnosed with NIID (repeat range: 87-217). By analyzing the Korea Biobank cohort, we estimated the distribution of repeat counts and threshold (>64) for Koreans, identifying 6 potential patients with NIID. Furthermore, long-read sequencing enabled the elucidation of transmission and epigenetic patterns of NOTCH2NLC repeats within a family affected by pediatric-onset NIID. Discussion: This study presents the population-wide distribution of NOTCH2NLC repeats and the estimated prevalence of NIID in Koreans, providing valuable insights into the association between repeat counts and disease manifestations in diverse neurologic disorders.

Implementation of Bayesian networks and Bayesian inference using a Cu0.1Te0.9/HfO2/Pt threshold switching memristor.

Bayesian networks and Bayesian inference, which forecast uncertain causal relationships within a stochastic framework, are used in various artificial intelligence applications. However, implementing hardware circuits for the Bayesian inference has shortcomings regarding device performance and circuit complexity. This work proposed a Bayesian network and inference circuit using a Cu0.1Te0.9/HfO2/Pt volatile memristor, a probabilistic bit neuron that can control the probability of being 'true' or 'false.' Nodal probabilities within the network are feasibly sampled with low errors, even with the device's cycle-to-cycle variations. Furthermore, Bayesian inference of all conditional probabilities within the network is implemented with low power (<186 nW) and energy consumption (441.4 fJ), and a normalized mean squared error of ∼7.5 × 10-4 through division feedback logic with a variational learning rate to suppress the inherent variation of the memristor. The suggested memristor-based Bayesian network shows the potential to replace the conventional complementary metal oxide semiconductor-based Bayesian estimation method with power efficiency using a stochastic computing method.

Symmetric and Profound Monoaminergic Degeneration in Parkinson's Disease with Premotor REM Sleep Behavior Disorder.

Background: Rapid eye movement sleep behavior disorder (RBD) may precede or follow motor symptoms in Parkinson's disease (PD). While over 70% of idiopathic RBD cases phenoconvert within a decade, a small subset develops PD after a more extended period or remains nonconverted. These heterogeneous manifestations of RBD in PD prompt subtype investigations. Premotor RBD may signify "body-first" PD with bottom-up, symmetric synucleinopathy propagation. Objective: Explore brainstem and nigrostriatal monoaminergic degeneration pattern differences based on premotor RBD presence and duration in de novo PD patients. Methods: In a cross-sectional analysis of de novo PD patients (n = 150) undergoing FP-CIT PET and RBD Single-Question Screen, the cohort was categorized into groups with and without premotor RBD (PDRBD +/-), with further classification of PDRBD + based on a 10-year duration of premotor RBD. Analysis of FP-CIT binding in the striatum and pons, striatal asymmetry, and striatum-to-pons ratios compared patterns of nigrostriatal and brainstem monoaminergic degeneration. Results: PDRBD + exhibited more severe and symmetrical striatal dopaminergic denervation compared to PDRBD-, with the difference in severity accentuated in the least-affected hemisphere. The PDRBD +<10Y subgroup displayed the most prominent striatal symmetry, supporting a more homogeneous "body-first" subtype. Pontine uptakes remained lower in PDRBD + even after adjusting for striatal uptake, suggesting early degeneration of pontine monoaminergic nuclei. Conclusions: Premotor RBD in PD is associated with severe, symmetrical nigrostriatal and brainstem monoaminergic degeneration, especially in cases with PD onset within 10 years of RBD. This supports the concept of a "widespread, bottom-up" pathophysiological mechanism associated with premotor RBD in PD.

The prevalence of non-troublesome dyskinesia in Parkinson's disease.

INTRODUCTION: Levodopa-induced dyskinesia is a common complication of long-term treatment of Parkinson's disease (PD), but its impact on daily activities is somewhat controversial. This study investigated the prevalence and severity of dyskinesia, particularly non-troublesome dyskinesia, to provide insights into its significance for long-term PD management. METHODS: We reviewed electronic medical records of 2571 PD patients, who had been followed up at Seoul National University Hospital and were seen between January 2016 and June 2017. Dyskinesia severity had been assessed during follow-up and was recorded with the highest score by considering its impact on functioning (0 = no dyskinesia, 1 = minimal with patient unaware, 2 = mild disability, 3 = moderate disability, 4 = severe disability). RESULTS: The prevalence of dyskinesia increased progressively with longer PD duration; 8.2% in the group with disease duration of 0-5 years, 40.7% for 6-10 years, 66.0% for 11-15 years, 74.6% for 16-20 years, and 83.2% for 21 years or more. The prevalence of dyskinesia scores ≥2 also increased with disease duration, with rates of 6.3% for 0-5 years, 31.9% for 6-10 years, 54.8% for 11-15 years, 62.9% for 16-20 years and 73.7% for 21 or more years. CONCLUSION: Despite the increasing prevalence and severity of dyskinesia with longer PD duration, the study found that less than non-troublesome dyskinesia remained at approximately 26.3% even after more than 21 years of disease duration. These findings suggest that dyskinesia may not be troublesome for many PD patients even in long-term.

Evaluating the validity and reliability of the Korean version of Scales for Outcomes in Parkinson's Disease-Cognition.

Objective: The Scales for Outcomes in Parkinson's Disease-Cognition (SCOPA-Cog) was developed to screen for cognition in PD. In this study, we aimed to evaluate the validity and reliability of the Korean version of the SCOPA-cog. Methods: We recruited 129 PD patients from 31 clinics with movement disorders in South Korea. The original version of the SCOPA-cognition was translated into Korean using the translation-retranslation method. The test-rest method with an intraclass correlation coefficient (ICC) and Cronbach's alpha coefficient were used to assess reliability. The Spearman's Rank correlation analysis with Montreal Cognitive Assessment-Korean version (MOCA-K) and Korean Mini-Mental State Examination (K-MMSE) were used to assess concurrent validity. Results: The Cronbach's alpha coefficient was 0.797, and the ICC was 0.887. Spearman's rank correlation analysis showed a significant correlation with the K-MMSE and MOCA-K scores (r = 0.546 and r = 0.683, respectively). Conclusions: Our results demonstrate that K-SCOPA-Cog exhibits good reliability and validity.

Electroencephalographic spectro-spatial covariance patterns related to phenoconversion in isolated rapid eye movement sleep behavior disorder and their longitudinal trajectories in α-synucleinopathies.

STUDY OBJECTIVES: This study aimed to identify electroencephalographic (EEG) spectro-spatial covariance patterns associated with phenoconversion in isolated rapid eye movement sleep behavior disorder (iRBD) patients and explore their longitudinal trajectories within α-synucleinopathies. METHODS: We assessed 47 participants, including 35 patients with iRBD and 12 healthy controls (HC), through baseline eye-closed resting EEGs. Patients with iRBD underwent follow-up EEG assessments and 18 patients with iRBD converted (12 to Parkinson's disease (PD), 6 to dementia with Lewy bodies [DLB]) during follow-up. We derived EEG spectro-spatial covariance patterns for PD-RBD and DLB-RBD from converters and HC. Correlations with motor and cognitive function, baseline distinctions among iRBD converters and nonconverters, and longitudinal trajectories were examined. RESULTS: At baseline, converters exhibited higher PD-RBD and DLB-RBD beta2 pattern scores compared to nonconverters (each area under curve [AUC] = 0.7751). The delta and alpha spatial patterns effectively distinguished both PD and DLB converters from HC, with the alpha pattern showing high discriminative power (AUC = 0.9097 for PD-RBD, 0.9306 for DLB-RBD). Movement Disorder Society-Sponsored Revision of the Unified Parkinson's Disease Rating Scale part III scores correlated positively with PD-RBD and DLB-RBD delta patterns (Spearman's rho = 0.688, p = 0.00014; rho = 0.539, p = 0.0055, respectively), with age and sex as cofactors. Distinct trajectories emerged during follow-up among PD converters, DLB converters, and iRBD nonconverters. CONCLUSIONS: Unique EEG spectro-spatial patterns specific to PD-RBD and DLB-RBD offer potential as predictive markers for phenoconversion to α-synucleinopathies in iRBD.

Vertically Stackable Ovonic Threshold Switch Oscillator Using Atomic Layer Deposited Ge0.6Se0.4 Film for High-Density Artificial Neural Networks.

Nanodevice oscillators (nano-oscillators) have received considerable attention to implement in neuromorphic computing as hardware because they can significantly improve the device integration density and energy efficiency compared to complementary metal oxide semiconductor circuit-based oscillators. This work demonstrates vertically stackable nano-oscillators using an ovonic threshold switch (OTS) for high-density neuromorphic hardware. A vertically stackable Ge0.6Se0.4 OTS-oscillator (VOTS-OSC) is fabricated with a vertical crossbar array structure by growing Ge0.6Se0.4 film conformally on a contact hole structure using atomic layer deposition. The VOTS-OSC can be vertically integrated onto peripheral circuits without causing thermal damage because the fabrication temperature is <400 °C. The fabricated device exhibits oscillation characteristics, which can serve as leaky integrate-and-fire neurons in spiking neural networks (SNNs) and coupled oscillators in oscillatory neural networks (ONNs). For practical applications, pattern recognition and vertex coloring are demonstrated with SNNs and ONNs, respectively, using semiempirical simulations. This structure increases the oscillator integration density significantly, enabling complex tasks with a large number of oscillators. Moreover, it can enhance the computational speed of neural networks due to its rapid switching speed.

Optimized treatment parameter by computer simulation for high-intensity focused ultrasound treatment of uterine adenomyosis: Short-term and long-term results.

This study aimed to investigate the efficacy and safety of using optimized parameters obtained by computer simulation for ultrasound-guided high-intensity focused ultrasound (HIFU) treatment of uterine adenomyosis in comparison with conventional parameters. We retrospectively assessed a single-institution, prospective study that was registered at Clinical Research Information Service (CRiS) of Republic of Korea (KCT0003586). Sixty-six female participants (median age: 44 years) with focal uterine adenomyosis were prospectively enrolled. All participants were treated with a HIFU system by using treatment parameters either for treating uterine fibroids (Group A, first 20 participants) or obtained via computer simulation (Group B, later 46 participants). To assess the treatment efficacy of HIFU, qualitative indices, including the clinically effective dysmenorrhea improvement index (DII), were evaluated up to 3 years after treatment, whereas quantitative indices, such as the nonperfused volume ratio and adenomyosis volume shrinkage ratio (AVSR), on MRI were evaluated up to 3 months after treatment. Quantitative/qualitative indices were compared between Groups A and B by using generalized linear mixed effect model. A safety assessment was also performed. Results showed that clinically effective DII was more frequently observed in Group B than in Group A (odds ratio, 3.69; P = 0.025), and AVSR were higher in Group B than in Group A (least-squares means, 21.61; P = 0.001). However, two participants in Group B developed skin burns at the buttock and sciatic nerve pain and required treatment. In conclusion, parameters obtained by computer simulation were more effective than the conventional parameters for treating uterine adenomyosis by using HIFU in terms of clinically effective DII and AVSR. However, care should be taken because of the risk of adverse events.

EEG-based machine learning models for the prediction of phenoconversion time and subtype in isolated rapid eye movement sleep behavior disorder.

STUDY OBJECTIVES: Isolated rapid eye movement sleep behavior disorder (iRBD) is a prodromal stage of α-synucleinopathies and eventually phenoconverts to overt neurodegenerative diseases including Parkinson's disease (PD), dementia with Lewy bodies (DLB), and multiple system atrophy (MSA). Associations of baseline resting-state electroencephalography (EEG) with phenoconversion have been reported. In this study, we aimed to develop machine learning models to predict phenoconversion time and subtype using baseline EEG features in patients with iRBD. METHODS: At baseline, resting-state EEG and neurological assessments were performed on patients with iRBD. Calculated EEG features included spectral power, weighted phase lag index, and Shannon entropy. Three models were used for survival prediction, and four models were used for α-synucleinopathy subtype prediction. The models were externally validated using data from a different institution. RESULTS: A total of 236 iRBD patients were followed up for up to 8 years (mean 3.5 years), and 31 patients converted to α-synucleinopathies (16 PD, 9 DLB, 6 MSA). The best model for survival prediction was the random survival forest model with an integrated Brier score of 0.114 and a concordance index of 0.775. The K-nearest neighbor model was the best model for subtype prediction with an area under the receiver operating characteristic curve of 0.901. Slowing of the EEG was an important feature for both models. CONCLUSIONS: Machine learning models using baseline EEG features can be used to predict phenoconversion time and its subtype in patients with iRBD. Further research including large sample data from many countries is needed to make a more robust model.

Novel Four-Way Variant Translocation, t(1;9;22;16)(q21;q34;q11.2;q24), in a Patient with Chronic Myeloid Leukemia.

Chronic myeloid leukemia (CML) is characterized by the Philadelphia (Ph) chromosome resulting from the translocation of t(9;22)(q34;q11), producing the BCR::ABL1 fusion gene. Variant Ph chromosome translocations, involving rearrangements in chromosomes other than 9 and 22, occur in 5-10% of CML cases. Herein, we report a unique case of a 36-year-old male with a four-way variant Ph chromosome. Conventional chromosomal analysis performed on bone marrow aspirate samples showed 46, XY, t(1;9;22;16)(q21;q34;q11.2;q24). Nested RT-PCR of the BCR::ABL1 gene revealed a major BCR::ABL rearrangement. The treatment with nilotinib achieved a complete hematologic, cytogenetic, and molecular response after 12 months.

Bio-Inspired Organic Synaptor with In Situ Ion-Doped Ultrathin Polyelectrolyte Containing Acetylcholine-Like Cation.

An ion-based synaptic transistor (synaptor) is designed to emulate a biological synapse using controlled ion movements. However, developing a solid-state electrolyte that can facilitate ion movement while achieving large-scale integration remains challenging. Here, a bio-inspired organic synaptor (BioSyn) with an in situ ion-doped polyelectrolyte (i-IDOPE) is demonstrated. At the molecular scale, a polyelectrolyte containing the tert-amine cation, inspired by the neurotransmitter acetylcholine is synthesized using initiated chemical vapor deposition (iCVD) with in situ doping, a one-step vapor-phase deposition used to fabricate solid-state electrolytes. This method results in an ultrathin, but highly uniform and conformal solid-state electrolyte layer compatible with large-scale integration, a form that is not previously attainable. At a synapse scale, synapse functionality is replicated, including short-term and long-term synaptic plasticity (STSP and LTSP), along with a transformation from STSP to LTSP regulated by pre-synaptic voltage spikes. On a system scale, a reflex in a peripheral nervous system is mimicked by mounting the BioSyns on various substrates such as rigid glass, flexible polyethylene naphthalate, and stretchable poly(styrene-ethylene-butylene-styrene) for a decentralized processing unit. Finally, a classification accuracy of 90.6% is achieved through semi-empirical simulations of MNIST pattern recognition, incorporating the measured LTSP characteristics from the BioSyns.

Large-Scale Screening: Phenotypic and Mutational Spectrum in Isolated and Combined Dystonia Genes.

BACKGROUND: Pathogenic variants in several genes have been linked to genetic forms of isolated or combined dystonia. The phenotypic and genetic spectrum and the frequency of pathogenic variants in these genes have not yet been fully elucidated, neither in patients with dystonia nor with other, sometimes co-occurring movement disorders such as Parkinson's disease (PD). OBJECTIVES: To screen >2000 patients with dystonia or PD for rare variants in known dystonia-causing genes. METHODS: We screened 1207 dystonia patients from Germany (DysTract consortium), Spain, and South Korea, and 1036 PD patients from Germany for pathogenic variants using a next-generation sequencing gene panel. The impact on DNA methylation of KMT2B variants was evaluated by analyzing the gene's characteristic episignature. RESULTS: We identified 171 carriers (109 with dystonia [9.0%]; 62 with PD [6.0%]) of 131 rare variants (minor allele frequency <0.005). A total of 52 patients (48 dystonia [4.0%]; four PD [0.4%, all with GCH1 variants]) carried 33 different (likely) pathogenic variants, of which 17 were not previously reported. Pathogenic biallelic variants in PRKRA were not found. Episignature analysis of 48 KMT2B variants revealed that only two of these should be considered (likely) pathogenic. CONCLUSION: This study confirms pathogenic variants in GCH1, GNAL, KMT2B, SGCE, THAP1, and TOR1A as relevant causes in dystonia and expands the mutational spectrum. Of note, likely pathogenic variants only in GCH1 were also found among PD patients. For DYT-KMT2B, the recently described episignature served as a reliable readout to determine the functional effect of newly identified variants. © 2024 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Association between early lactate-related variables and 6-month neurological outcome in out-of-hospital cardiac arrest patients.

INTRODUCTION: The role of lactate measurement in out-of-hospital cardiac arrest (OHCA) survivors remains controversial. We assessed the association between early lactate-related variables, OHCA characteristics, and long-term neurological outcome. METHODS: In OHCA patients who received targeted temperature management, lactate levels were measured at 0, 12, and 24 h after the return of spontaneous circulation. We calculated lactate clearance and time-weighted cumulative lactate (TWCL), which represent the area under the time-lactate curve. The area under the receiver operating characteristic curve (AUC) and the adjusted odds ratios (AORs) of lactate-related variables for predicting 6-month poor outcome (Cerebral Performance Category 3-5) were evaluated. Interactions between lactate variables and characteristics of OHCA were evaluated by a multivariable logistic model with interaction terms and subgroup analysis. RESULTS: A total of 347 OHCA patients were included. After adjustment, higher lactate levels at the three time points were associated with a poor outcome (AOR 1.10 [95% CI, 1.03-1.18], AOR 1.15 [95% CI, 1.02-1.29], and AOR 1.36 [95% CI, 1.15-1.60], respectively), while TWCL was the only lactate kinetics variable associated with a poor outcome (AOR 1.29 [95% CI, 1.12-1.49]). We identified several interactions between lactate-related variables and OHCA characteristics. In particular, the AUC of TWCL was excellent in cases of noncardiac etiology (AUC 0.92 [95% CI, 0.86-0.96] but only moderate in cardiac etiology (AUC 0.69 [95% CI, 0.62-0.75]). CONCLUSIONS: Early lactate levels, especially at 24 h, and TWCL were independent predictors of neurologic outcome in these patients, whereas lactate clearance was not. The prognostic ability of lactate-related variables varied depending on the OHCA characteristics.

2Memristor-1Capacitor Integrated Temporal Kernel for High-Dimensional Data Mapping.

Compact but precise feature-extracting ability is core to processing complex computational tasks in neuromorphic hardware. Physical reservoir computing (RC) offers a robust framework to map temporal data into a high-dimensional space using the time dynamics of a material system, such as a volatile memristor. However, conventional physical RC systems have limited dynamics for the given material properties, restricting the methods to increase their dimensionality. This study proposes an integrated temporal kernel composed of a 2-memristor and 1-capacitor (2M1C) using a W/HfO2/TiN memristor and TiN/ZrO2/Al2O3/ZrO2/TiN capacitor to achieve higher dimensionality and tunable dynamics. The kernel elements are carefully designed and fabricated into an integrated array, of which performances are evaluated under diverse conditions. By optimizing the time dynamics of the 2M1C kernel, each memristor simultaneously extracts complementary information from input signals. The MNIST benchmark digit classification task achieves a high accuracy of 94.3% with a (196×10) single-layer network. Analog input mapping ability is tested with a Mackey-Glass time series prediction, and the system records a normalized root mean square error of 0.04 with a 20×1 readout network, the smallest readout network ever used for Mackey-Glass prediction in RC. These performances demonstrate its high potential for efficient temporal data analysis.

A Nanoscale Bistable Resistor for an Oscillatory Neural Network.

Coupled oscillators construct an oscillatory neural network (ONN) by mimicking the interactions among neurons in the human brain. This work demonstrates a fully CMOS-based oscillator consisting of a bistable resistor (biristor), which shares a structure identical with that of a metal-oxide-semiconductor field-effect transistor, except for the use of a gate electrode. The biristor-based oscillator (birillator) generates oscillating voltage signals in the form of spikes due to a single transistor latch phenomenon. When two birillators are connected with a coupling capacitor, they become synchronized with a phase difference of 180°. These coupled oscillation characteristics are experimentally investigated for an ONN. As practical applications of the ONN with coupled birillators, edge detection and vertex coloring are conducted by encoding information into phase differences between them. The proposed fully CMOS-based birillators are advantageous for low power consumption, high CMOS compatibility, and a compact footprint area.