Therapeutic efficacy of CT-P59 against P.1 variant of SARS-CoV-2

P.1. or gamma variant also known as the Brazil variant, is one of the variants of concern (VOC) which appears to have high transmissibility and mortality. To explore the potency of the CT-P59 monoclonal antibody against P.1 variant, we tried to conduct binding affinity, in vitro neutralization, and in vivo animal tests. In in vitro assays revealed that CT-P59 is able to neutralize P.1 variant in spite of reduction in its binding affinity against a RBD (receptor binding domain) mutant protein including K417T/E484K/N501Y and neutralizing activity against P.1 pseudoviruses and live viruses. In contrast, in vivo hACE2 (human angiotensin-converting enzyme 2)-expressing TG (transgenic) mouse challenge experiment demonstrated that a clinically relevant or lower dosages of CT-P59 is capable of lowering viral loads in the respiratory tract and alleviates symptoms such as body weight losses and survival rates. Therefore, a clinical dosage of CT-P59 could compensate for reduced in vitro antiviral activity in P.1-infected mice, implying that CT-P59 has therapeutic potency for COVID-19 patients infected with P.1 variant. HighlightsO_LICT-P59 could bind to and neutralize P.1 variant, but CT-P59 showed reduced susceptibility in in vitro tests. C_LIO_LIThe clinical dosage of CT-P59 demonstrated in vivo therapeutic potency against P.1 variants in hACE2-expressing mice challenge study. C_LIO_LICT-P59 ameliorates their body weight loss and prevents the lethality in P.1 variant-infected mice. C_LI

Automated discrimination of dementia spectrum disorders using extreme learning machine and structural T1 MRI features.

The classification of neuroimaging data for the diagnosis of Alzheimer's Disease (AD) is one of the main research goals of the neuroscience and clinical fields. In this study, we performed extreme learning machine (ELM) classifier to discriminate the AD, mild cognitive impairment (MCI) from normal control (NC). We compared the performance of ELM with that of a linear kernel support vector machine (SVM) for 718 structural MRI images from Alzheimer's Disease Neuroimaging Initiative (ADNI) database. The data consisted of normal control, MCI converter (MCI-C), MCI non-converter (MCI-NC), and AD. We employed SVM-based recursive feature elimination (RFE-SVM) algorithm to find the optimal subset of features. In this study, we found that the RFE-SVM feature selection approach in combination with ELM shows the superior classification accuracy to that of linear kernel SVM for structural T1 MRI data.

Motor imagery EEG classification with optimal subset of wavelet based common spatial pattern and kernel extreme learning machine.

Performance of motor imagery based brain-computer interfaces (MI BCIs) greatly depends on how to extract the features. Various versions of filter-bank based common spatial pattern have been proposed and used in MI BCIs. Filter-bank based common spatial pattern has more number of features compared with original common spatial pattern. As the number of features increases, the MI BCIs using filter-bank based common spatial pattern can face overfitting problems. In this study, we used eigenvector centrality feature selection method, wavelet packet decomposition common spatial pattern, and kernel extreme learning machine to improve the performance of MI BCIs and avoid overfitting problems. Furthermore, the computational speed was improved by using kernel extreme learning machine.

Changes in heart rate variability of patients with delirium in intensive care unit.

Delirium is an important syndrome in intensive care unit (ICU) patients, however, its characteristics are still unclear. Many evidences showed that this syndrome can be related to the autonomic instability. In this study, we aimed to investigate the possible alterations of autonomic nervous system (ANS) in delirium patients in ICU. Electrocardiography (ECG) of every ICU patient was measured during routine daily ICU care, and the data were gathered to evaluate the heart rate variability (HRV). HRV of total 60 patients were analyzed in time, frequency and non-linear domains. As a result, we found that heart rates of delirium patients were more variable and irregular than non-delirium patients. These findings may facilitate early detection and prevention of delirium in ICU.

A Preliminary Study on the Circadian Rhythm of Autonomic Nervous System in Patients Admitted to Intensive Care Unit, Using the Heart Rate Variability

OBJECTIVES: normal circadian rhythm of autonomic nervous system function stands for the daily change of sympathetic and parasympathetic modulation, which can be measured by heart rate variability (HRV). Generally, patients in the intensive care unit (ICU) are prone to sleep-wake cycle dysregulation, therefore, it may have an influence on the circadian rhythm of autonomic nervous system. This study was designed to interpret possible dysregulation of autonomic nervous system in ICU patients by using HRV. METHODS: HRV was assessed every 3 hours in 21 ICU patients during a 7-minute period. The statistical differences of HRV features between the morning (AM 6 : 00–PM 12 : 00), and the afternoon (PM 12 : 00–PM 18 : 00) periods were evaluated in time domain and frequency domain. RESULTS: Patients showed significantly increased normalized power of low frequencey (nLF), absolute power of low frequencey (LF)/absolute power of high frequencey (HF) in the afternoon period as compared to the morning period. However, normalized power of high frequency (nHF) was significantly decreased in the afternoon period. There was no statistically significant difference between the morning period and the afternoon period in the time domain analysis. CONCLUSIONS: The increased sympathetic tone in the afternoon period supports possible dysregulation in the circadian rhythm of autonomic nervous system in ICU patients. Future studies can help to interpret the association between autonomic dysregulation and negative outcomes of ICU patients.

A case of gonadoblastoma in patient with mixed gonadal dysgenesis / 대한산부인과학회잡지

Gonadoblastoma occurs almost always in association with a Y chromosome cell line, and developes in one third of patients with Mixed gonadal dysgenesis. Removing of gonads of intersex patients with the Y chromosome is very important because of the strong association of the genesis of tumor in dysgenetic gonads with the presence of a Y chromosome. But it is always possible that an XY cell line could be missed, or that a fragment from Y chromosome could have been translocated and not discovered by chromosomal analysis. PCR with Y specific probe or Southern blotting would reveal the presence of a Y or a translocated fragment. We experienced an 18-year-old woman represent with primary amenorrhea who had 45,X/46,X,+mar. Y-specific PCR revealed that the marker chromosome was drived from Y chromosome. After both gonadectomy and clitorial recession, we found the gonadoblastoma in dysgenetic testis. So we report it with brief review of literatures.