Abstract
Epilepsy is one of the brightest manifestations of extreme behavior in living systems. Extreme epileptic events are seizures, that arise suddenly and unpredictably. Usually, treatment ...strategies start by analyzing brain activity during the seizures revealing their type and onset mechanisms. This approach requires collecting data for a representative number of events which is only possible during the continuous EEG monitoring over several days. A big part of the further analysis is searching for seizures on these recordings. An experienced medical specialist spends hours checking the data of a single patient and needs assistance from the automative systems for seizure detection. Machine learning methods typically address this issue in a supervised fashion and exhibit a lack of generalization. The extreme value theory allows addressing this issue with the unsupervised machine learning methods of outlier detection. Here, we make the first step toward using this approach for the seizure detection. Based on our recent work, we specified the EEG features showing extreme behavior during seizures and loaded them to the one-class SVM, a popular outlier detection algorithm. Testing the proposed approach on 83 patients, we reported 77% sensitivity and 12% precision. In 60 patients, sensitivity was 100%. In the rest 23 subjects, we observed deviations from the extreme behavior. The one-class SVM used a single subject’s data for training; therefore, it was stable against between-subject variability. Our results demonstrate an effective convergence between the extreme value theory, a physical concept, and the outlier detection algorithms, a machine learning concept, toward solving the meaningful task of medicine.
Automated labelling of epileptic seizures on electroencephalograms is an essential interdisciplinary task of diagnostics. Traditional machine learning approaches operate in a supervised fashion ...requiring complex pre-processing procedures that are usually labour intensive and time-consuming. The biggest issue with the analysis of electroencephalograms is the artefacts caused by head movements, eye blinks, and other non-physiological reasons. Similarly to epileptic seizures, artefacts produce rare high-amplitude spikes on electroencephalograms, complicating their separability. We suggest that artefacts and seizures are rare events; therefore, separating them from the rest data seriously reduces information for further processing. Based on the occasional nature of these events and their distinctive pattern, we propose using anomaly detection algorithms for their detection. These algorithms are unsupervised and require minimal pre-processing. In this work, we test the possibility of an anomaly (or outlier) detection algorithm to detect seizures. We compared the state-of-the-art outlier detection algorithms and showed how their performance varied depending on input data. Our results evidence that outlier detection methods can detect all seizures reaching 100% recall, while their precision barely exceeds 30%. However, the small number of seizures means that the algorithm outputs a set of few events that could be quickly classified by an expert. Thus, we believe that outlier detection algorithms could be used for the rapid analysis of electroencephalograms to save the time and effort of experts.
The paper reports an experimental study on partial discharges (PD) in bubbles, either floating or developed on an electrode in a transformer oil. In a test cell, the PD occurrence was a very rare ...event. The voltage of the appearance of the PD in both cases was approximately the same. Moreover, the waiting time for the PD in the bubble at the electrode was noticeably longer than that for the free bubble. The moisture content of the oil, as well as the addition of surfactants, had no effect on the occurrence of PD. Analysis of the data showed that only two mechanisms stimulated PD: pulsed X-ray radiation or the presence of water microdroplets. The reason for all these features is the formation of an initiating electrons.
IMPORTANCE: Patients with cerebral venous thrombosis (CVT) are at risk of recurrent venous thrombotic events (VTEs). Non–vitamin K oral anticoagulants have not been evaluated in randomized controlled ...trials in CVT. OBJECTIVE: To compare the efficacy and safety of dabigatran etexilate with those of dose-adjusted warfarin in preventing recurrent VTEs in patients who have experienced a CVT. DESIGN, SETTING, AND PARTICIPANTS: RE-SPECT CVT is an exploratory, prospective, randomized (1:1), parallel-group, open-label, multicenter clinical trial with blinded end-point adjudication (PROBE design). It was performed from December 21, 2016, to June 22, 2018, with a follow-up of 25 weeks, at 51 tertiary sites in 9 countries (France, Germany, India, Italy, the Netherlands, Poland, Portugal, Russia, and Spain). Adult consecutive patients with acute CVT, who were stable after 5 to 15 days of treatment with parenteral heparin, were screened for eligibility. Patients with CVT associated with central nervous system infection or major trauma were excluded, but those with intracranial hemorrhage from index CVT were allowed to participate. After exclusions, 120 patients were randomized. Data were analyzed following the intention-to-treat approach. INTERVENTIONS: Dabigatran, 150 mg twice daily, or dose-adjusted warfarin for a treatment period of 24 weeks. MAIN OUTCOMES AND MEASURES: Primary outcome was a composite of patients with a new VTE (recurrent CVT, deep vein thrombosis of any limb, pulmonary embolism, and splanchnic vein thrombosis) or major bleeding during the study period. Secondary outcomes were cerebral venous recanalization and clinically relevant non–major bleeding events. RESULTS: In total, 120 patients with CVT were randomized to the 2 treatment groups (60 to dabigatran and 60 to dose-adjusted warfarin). Of the randomized patients, the mean (SD) age was 45.2 (13.8) years, and 66 (55.0%) were women. The mean (SD) duration of exposure was 22.3 (6.16) weeks for the dabigatran group and 23.0 (5.20) weeks for the warfarin group. No recurrent VTEs were observed. One (1.7%; 95% CI, 0.0-8.9) major bleeding event (intestinal) was recorded in the dabigatran group, and 2 (3.3%; 95% CI, 0.4-11.5) (intracranial) in the warfarin group. One additional patient (1.7; 95% CI, 0.0-8.9) in the warfarin group experienced a clinically relevant non–major bleeding event. Recanalization occurred in 33 patients in the dabigatran group (60.0%; 95% CI, 45.9-73.0) and in 35 patients in the warfarin group (67.3%; 95% CI, 52.9-79.7). CONCLUSIONS AND RELEVANCE: This trial found that patients who had CVT anticoagulated with either dabigatran or warfarin had low risk of recurrent VTEs, and the risk of bleeding was similar with both medications, suggesting that both dabigatran and warfarin may be safe and effective for preventing recurrent VTEs in patients with CVT. TRIAL REGISTRATION: ClinicalTrials.gov identifier: NCT02913326
The analysis of experimental data on the initiation of streamers in a liquid di- electric from the surface of a free-floating up gas bubble after partial discharge is performed. Calculations of ...electric fields in a dielectric after partial discharge in bubbles corresponding to experimental conditions, with different degrees of deformation of the bubbles and their dif- ferent position relative to flat electrodes, have been carried out. The effect of image charges on the value of the maximum electric field on the surface of a spherical bubble is estimated. The probability of initiation of branching streamers from the bubble surface into the liquid is analyzed.
Many approaches to automated epileptic seizure detection share a common challenge - the trade-off between recall and precision. This study aims to develop a novel approach for reducing false positive ...predictions in seizure detection tasks applied to real-world EEG recordings. We propose a multi-stage modeling framework, for which the novelty lies in combination of traditional machine learning outlier detection with state-of-the-art convolutional neural networks. Our dataset includes raw epileptic EEG data directly from the hospital. Continuous wavelet analysis is employed for EEG preprocessing and feature extraction. We evaluated the performance of the proposed two-stage algorithm, and it demonstrated a slight decrease in recall but a significant improvement in precision in comparison to machine-learning-only or neural-network-only algorithms. We hypothesize that this finding aligns well with our previous research and relates to the fundamental properties of epileptic EEG, including the extreme behavior of seizures. Finally, we propose a potential practical application of the developed approach within a clinical decision support system.
Background: Toxic desomorphine encephalopathy (TDE) is a pathological condition that develops as a result of the intravenous use of a drug called Krokodil containing desomorphine, made in the ...artisanal conditions using codeine-containing drugs, organic solvents (gasoline), iodine and red phosphorus. This disease is more often observed in the CIS countries. In addition to the acute and chronic pathological conditions with the damage to various organs, the use of Krokodil is characterized by pronounced extrapyramidal manifestations in the form of dystonia, parkinsonism, postural disorders, as well as the occurrence of cognitive and affective disorders.
Aims: To find the clinical and neuroimaging features of toxic desomorphine encephalopathy, as well as possible methods of its treatment.
Methods: A clinical analysis of the medical documentation of 21 TDE patients (11 women and 10 men) with a history of the use of Krokodil was carried out, the patients had been under observation from 2014 to 2021. All the patients underwent a clinical physical and neurological examination, 14 of them underwent neuroimaging (brain MRI and/or MSCT). The observation of these patients revealed a number of characteristic clinical and neuroimaging features inherent in the majority of drug addicts.
Results: The clinical picture of patients with TDE was dominated by movement disorders. All the patients had pronounced postural disorders and gait disturbance. Parkinsonism was observed in 20 of 21 patients. The hyperkinetic syndrome was presented in 17 patients (80.9%) and was manifested by dystonia of various localization with polymorphic manifestations. The brain MRI data taken from the Krokodil users for 3 years were characterized by symmetrical focal changes in the basal ganglia, brainstem, cerebellum and internal capsule of the thalamus in the form of an increase in the intensity of the MR signal in the T1 mode and attenuation in the T2-weighted images mode (7 of 11 cases), with the subsequent regression of these characteristics based on the results of the subsequent MRI studies.
Conclusion: The study results have revealed the clinical manifestations characteristic of TDE polymorphic extrapyramidal disorders, as well as neuroimaging changes reflecting these data.
Recently developed ion mobility mass spectrometer is described. The instrument is based on a drift tube ion mobility spectrometer and an orthogonal acceleration electrostatic sector time-of-flight ...mass analyzer. Data collection is performed using a specially developed fast ADC-based recorder that allows real-time data integration in an interval between 3 and 100 s. Primary tests were done with positive ion electrospray. The tests have shown obtaining 100 ion mobility resolving power and 2000 mass resolving power. Obtained for 2,6-di-tert-butylpyridine in electrosprayed liquid samples during 100 s analysis and full IMS/MS data collection mode were 4 nM relative limits of detection and a 1 pg absolute limit of detection (S/N=3). Characteristic ion mobility/mass distributions were recorded for selected antibiotics, including amoxicillin, ampicillin, lomefloxacin, and ofloxacin. At studied conditions, lomefloxacin forms only a protonated molecule-producing reduced ion mobility peak at 1.082 cm2/(V s). Both amoxicillin and ampicillin produce M + H+, M + CH3OH + H+, and M + CH3CN + H+. Amoxicillin shows two peaks at 0.909 cm2/(V s) and 0.905 cm2/(V s). Ampicillin shows one peak at 0.945 cm2/(V s). Intensity of protonated methanol containing cluster for both ampicillin and amoxicillin has a clear tendency to rise with sample keeping time. Ofloxacin produces two peaks in the ion mobility distribution. A lower ion mobility peak at 1.051 cm2/(V s) is shown to be formed by M + H+ ions. A higher ion mobility peak appearing for samples kept more than 48 h is shown to be formed by both M + H+ ion and a component identified as the M + 2H + M+2 cluster. The cluster probably partly dissociates in the interface producing the M + H+ ion.
. This revision of the classification of unicellular eukaryotes updates that of Levine et al. (1980) for the protozoa and expands it to include other protists. Whereas the previous revision was ...primarily to incorporate the results of ultrastructural studies, this revision incorporates results from both ultrastructural research since 1980 and molecular phylogenetic studies. We propose a scheme that is based on nameless ranked systematics. The vocabulary of the taxonomy is updated, particularly to clarify the naming of groups that have been repositioned. We recognize six clusters of eukaryotes that may represent the basic groupings similar to traditional “kingdoms.” The multicellular lineages emerged from within monophyletic protist lineages: animals and fungi from Opisthokonta, plants from Archaeplastida, and brown algae from Stramenopiles.
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