Herpes simplex encephalitis initially presenting without fever or cerebrospinal fluid pleocytosis and with typical neuroimaging findings: a case report

Herpes simplex encephalitis (HSE) is a common viral encephalitis that can be fatal if not adequately treated. Fever, cerebrospinal fluid (CSF) pleocytosis, and typical neuroimaging findings are commonly observed in HSE cases. We encountered a patient with HSE who did not exhibit these classic clinical features. A 63-year-old male presented with his first-ever seizure. Fever did not develop until the fourth day of admission, and neither neuroimaging nor CSF analysis revealed abnormalities. Under suspicion of autoimmune encephalitis, methylprednisolone was administered. Subsequently, when the patient developed fever, a follow-up neuroimaging study was performed and revealed abnormalities consistent with HSE. The patient was promptly treated with acyclovir, which led to a full recovery. Diagnosing HSE in patients who present without fever or CSF pleocytosis and with typical neuroimaging findings poses a challenge. Therefore, prior to initiating immunosuppressive treatment, it is crucial to closely observe patients and to conduct follow-up tests, including neuroimaging and CSF analysis.

Therapeutic Outcomes and Electrophysiological Biomarkers in Anti-Myelin-Associated Glycoprotein Neuropathy: A Multicenter Cohort Study in South Korea

BACKGROUND AND PURPOSE

Unlike other immune-mediated neuropathies, anti-myelin-associated glycoprotein (MAG) neuropathy is often refractory to immunotherapy. It is necessary to compare the relative efficacies of various immunotherapies and develop objective biomarkers in order to optimize its clinical management.

METHODS

This study recruited 91 patients with high anti-MAG antibody titers from 7 tertiary hospitals in South Korea. We analyzed the baseline characteristics, therapeutic outcomes, and nerve conduction study (NCS) findings of 68 patients and excluded 23 false positive cases.

RESULTS

The rate of positive responses to treatment was highest using zanubrutinib (50%) and rituximab (36.4%), followed by corticosteroids (16.7%), immunosuppressants (9.5%), intravenous immunoglobulin (5%), and plasma exchange (0%). Disability and weakness were significantly associated with multiple NCS parameters at the time of diagnosis, especially distal compound muscle action potential (CMAP) amplitudes. Moreover, the longitudinal trajectory of the average CMAP amplitudes paralleled the clinical courses, with a 16.2 percentile decrease as an optimal cutoff for predicting a clinical exacerbation (area under the receiver operating characteristic curve=0.792).

CONCLUSIONS

Our study supports the use of NCS as an objective marker for estimating disease burden and tracking clinical changes in patients with anti-MAG neuropathy. We have described the beneficial effects of rituximab and a new drug, zanubrutinib, compared with conventional immunotherapies.

Aphasic Status Epilepticus Associated with Alzheimer's Disease: Clinical and Electrographic Characteristics

In aphasic status epilepticus (ASE), aphasia is the sole manifestation of seizure in patients with this disorder. Alzheimer's disease (AD) is one of neurological disorders causing ASE. Herein, we report two cases of ASE associated with AD, and discuss their clinical characteristics. Patient 1 presented Broca's aphasia, and patient 2 presented global aphasia during the ictal period. Both patients exhibited atypical ictal electroencephalographic (EEG) patterns, which improved after antiepileptic drug administration. ASE was the presenting symptom of AD in patient 1. ASE can develop at any stage of AD. Alterations in clinical symptoms and EEG patterns after treatment with antiepileptic drug are the key to diagnosis. Prompt diagnosis and treatment are critical for preventing further consciousness dysfunction.

Patient with Epilepsy Showing Psychiatric Symptoms after Remission of Seizures and Normalization of Electroencephalography: The Phenomenon of Forced Normalization?

Psychiatric disorders are commonly observed in patients with epilepsy. Among them, the phenomenon known as forced normalization is scarce. Herein, we report the case of a 41-year-old patient who showed long-term first-onset psychiatric symptoms after seizure remission and normalization of electroencephalography. After changing the antiepileptic drug regimen and psychiatric treatment, the patient's symptoms regressed. However, the exact pathological mechanisms remain to be elucidated. Changing the regimen of antiepileptic drugs and long-term psychiatric treatment may help control this phenomenon.

Anti-N-Methyl-D-Aspartate Receptor Encephalitis after BNT162b2 COVID-19 Vaccination

After the coronavirus disease 2019 (COVID-19) pandemic emerged, the development of vaccines was accelerated. Neurologic complications of COVID-19 vaccination had been reported, which included encephalitis. In this study, we report a very rare case of a female with anti-N-methyl-D-aspartate receptor encephalitis associated with ovarian teratoma that would be triggered by BNT162b2 m-RNA COVID-19 vaccination.

Anti-N-Methyl-D-Aspartate Receptor Encephalitis after BNT162b2 COVID-19 Vaccination

After the coronavirus disease 2019 (COVID-19) pandemic emerged, the development of vaccines was accelerated. Neurologic complications of COVID-19 vaccination had been reported, which included encephalitis. In this study, we report a very rare case of a female with anti-N-methyl-D-aspartate receptor encephalitis associated with ovarian teratoma that would be triggered by BNT162b2 m-RNA COVID-19 vaccination.

Residual one-dimensional convolutional neural network for neuromuscular disorder classification from needle electromyography signals with explainability

BACKGROUND AND OBJECTIVE

Neuromuscular disorders are diseases that damage our ability to control body movements. Needle electromyography (nEMG) is often used to diagnose neuromuscular disorders, which is an electrophysiological test measuring electric signals generated from a muscle using an invasive needle. Characteristics of nEMG signals are manually analyzed by an electromyographer to diagnose the types of neuromuscular disorders, and this process is highly dependent on the subjective experience of the electromyographer. Contemporary computer-aided methods utilized deep learning image classification models to classify nEMG signals which are not optimized for classifying signals. Additionally, model explainability was not addressed which is crucial in medical applications. This study aims to improve prediction accuracy, inference time, and explain model predictions in nEMG neuromuscular disorder classification.

METHODS

This study introduces the nEMGNet, a one-dimensional convolutional neural network with residual connections designed to extract features from raw signals with higher accuracy and faster speed compared to image classification models from previous works. Next, the divide-and-vote (DiVote) algorithm was designed to integrate each subject's heterogeneous nEMG signal data structures and to utilize muscle subtype information for higher accuracy. Finally, feature visualization was used to identify the causality of nEMGNet diagnosis predictions, to ensure that nEMGNet made predictions on valid features, not artifacts.

RESULTS

The proposed method was tested using 376 nEMG signals measured from 57 subjects between June 2015 to July 2020 in Seoul National University Hospital. The results from the three-class classification task demonstrated that nEMGNet's prediction accuracy of nEMG signal segments was 62.35%, and the subject diagnosis prediction accuracy of nEMGNet and the DiVote algorithm was 83.69 %, over 5-fold cross-validation. nEMGNet outperformed all models from previous works on nEMG diagnosis classification, and heuristic analysis of feature visualization results indicate that nEMGNet learned relevant nEMG signal characteristics.

CONCLUSIONS

This study introduced nEMGNet and DiVote algorithm which demonstrated fast and accurate performance in predicting neuromuscular disorders based on nEMG signals. The proposed method may be applied in medicine to support real-time electrophysiologic diagnosis.

Calcium extrusion regulatory molecules: differential expression during pregnancy in the porcine uterus

Calcium ions in the uterine endometrium are essential for the establishment and maintenance of pregnancy, but the cellular and molecular mechanisms of calcium ion regulation in the endometrium are not fully understood. Our previous study in pigs found that calcium regulatory molecules, transient receptor potential, vanilloid type 6 and calbindin-D9K, are expressed in the uterine endometrium during the estrous cycle and pregnancy. However, we did not determine the expression of calcium extrusion regulatory molecules, plasma membrane calcium ATPases (ATP2Bs), sodium/calcium exchangers (SLC8As), or potassium-dependent sodium/calcium exchangers (SLC24As), in the uterine endometrium and conceptuses. Thus, in this study we determine whether ATP2Bs, SCL8As, and SLC24As are expressed in the uterine endometrium during the estrous cycle and pregnancy and in conceptuses during early pregnancy. Real-time RT-PCR analysis showed that ATP2Bs, SLC8As, and SLC24As were expressed in the uterine endometrium in a pregnancy status- and stage-specific manner. Conceptuses during early pregnancy also expressed these molecules. In situ hybridization analysis showed that ATP2B1, SLC8A1, and SLC24A4 were localized mainly to luminal and glandular epithelium and stromal cells in the endometrium during pregnancy. These results indicate that calcium extrusion regulatory molecules are expressed in the uterine endometrium during the estrous cycle and pregnancy and in conceptuses during early pregnancy, indicating that calcium extrusion regulatory molecules may play important roles in the establishment and maintenance of pregnancy by regulating calcium ion concentration in the uterine endometrium in pigs.