Quantiferon Monitor Testing Sheds Light on Immune System Disparities between Multiple Sclerosis Patients and Healthy Individuals

The aim of this study was to conduct QuantiFERON Monitor (QFM) testing in patients with multiple sclerosis (MS), which is used to monitor the state of the immune system through the non-specific stimulation of leukocytes followed by determining the level of interferon-gamma (IFN-γ) released from activated cells. Additionally, we tested the level of selected cytokines (IFN-α, IFN-γ, IL-1α, IL-1β, IL-1ra, IL-2, IL-3, IL-4, IL-6, IL-7, IL-10, IL-15, IL-33, VEGF) from stimulated blood samples to further understand the immune response. This study builds upon a previously published study, utilizing activated serum samples that were initially used for IFN-γ determination. However, our current focus shifts from IFN-γ to exploring other cytokines that could provide further insights into the immune response. A screening was conducted using Luminex technology, which yielded promising results. These results were then further elaborated upon using ELISA to provide a more detailed understanding of the cytokine profiles involved. This study, conducted from August 2019 to June 2023, included 280 participants: 98 RRMS patients treated with fingolimod (fMS), 96 untreated patients with progressive MS (pMS), and 86 healthy controls (HC). Our results include Violin plots showing elevated IL-1α in pMS and fMS. Statistical analysis indicated significant differences in the interleukin levels between groups, with IL-1ra and age as key predictors in differentiating HC from pMS and IL-1ra, IL-1α, age, and EDSS in distinguishing pMS from fMS. These findings suggest cytokines' potential as biomarkers in MS progression and treatment response.

Intravenous Thrombolysis in Posterior versus Anterior Circulation Stroke: Clinical Outcome Differs Only in Patients with Large Vessel Occlusion

The safety and efficacy of intravenous thrombolysis (IVT) are well established in anterior circulation stroke (ACS) but are much less clear for posterior circulation stroke (PCS). The aim of this study was to evaluate the occurrence of parenchymal hematoma (PH) and 3-month clinical outcomes after IVT in PCS and ACS. In an observational, cohort multicenter study, we analyzed data from ischemic stroke patients treated with IVT prospectively collected in the SITS (Safe Implementation of Treatments in Stroke) registry in the Czech Republic between 2004 and 2018. Out of 10,211 patients, 1166 (11.4%) had PCS, and 9045 (88.6%) ACS. PH was less frequent in PCS versus ACS patients: 3.6 vs. 5.9%, odds ratio (OR) = 0.594 in the whole set, 4.4 vs. 7.8%, OR = 0.543 in those with large vessel occlusion (LVO), and 2.2 vs. 4.7%, OR = 0.463 in those without LVO. At 3 months, PCS patients compared with ACS patients achieved more frequently excellent clinical outcomes (modified Rankin scale [mRS] 0-1: 55.5 vs. 47.6%, OR = 1.371 in the whole set and 49.2 vs. 37.6%, OR = 1.307 in those with LVO), good clinical outcomes (mRS 0-2: 69.9 vs. 62.8%, OR = 1.377 in the whole set and 64.5 vs. 50.5%, OR = 1.279 in those with LVO), and had lower mortality (12.4 vs. 16.6%, OR = 0.716 in the whole set and 18.4 vs. 25.5%, OR = 0.723 in those with LVO) (p < 0.05 in all cases). In PCS versus ACS patients, an extensive analysis showed a lower risk of PH both in patients with and without LVO, more frequent excellent and good clinical outcomes, and lower mortality 3 months after IVT in patients with LVO.

Incremental deep learning for reflectivity data recognition in stomatology

The recognition of stomatological disorders and the classification of dental caries are important areas of biomedicine that can hugely benefit from machine learning tools for the construction of relevant mathematical models. This paper explores the possibility of using reflectivity data to distinguish between healthy tissues and caries by deep learning and multilayer convolutional neural networks. The experimental data set includes more than 700 observations recorded in the stomatology laboratory. For rigor, the results obtained from the deep learning systems are compared with those evaluated for selected sets of features estimated for each observation and classified by a decision tree, support vector machine (SVM), k-nearest neighbor, Bayesian methods, and two-layer neural networks. The classification accuracy obtained for the deep learning systems was 98.1% and 94.4% for data in the signal and spectral domains, respectively, in comparison with an accuracy of 97.2% and 87.2% evaluated by the SVM method. The proposed method conclusively demonstrates how the artificial intelligence and deep learning methodology can contribute to improved diagnosis of dental problem in stomatology.

Classification of Ataxic Gait

Gait disorders accompany a number of neurological and musculoskeletal disorders that significantly reduce the quality of life. Motion sensors enable high-quality modelling of gait stereotypes. However, they produce large volumes of data, the evaluation of which is a challenge. In this publication, we compare different data reduction methods and classification of reduced data for use in clinical practice. The best accuracy achieved between a group of healthy individuals and patients with ataxic gait extracted from the records of 43 participants (23 ataxic, 20 healthy), forming 418 segments of straight gait pattern, is 98% by random forest classifier preprocessed by t-distributed stochastic neighbour embedding.

Factors influencing therapy choice and clinical outcome in cerebral venous sinus thrombosis

We aimed was to assess the factors influencing therapy choice and clinical outcome after 3-4 months in patients with cerebral venous sinus thrombosis (CVST). In a retrospective, bi-centric study, the set consisted of 82 consecutive CVST patients (61 females; mean age 33.5 ± 15.7 years). Following data were collected: baseline characteristics, presence of gender-specific risk factors (GSRF), location and extent of venous sinus impairment, clinical presentation, type of treatment, recanalization, presence of parenchymal lesions, and clinical outcome after 3-4 months (assessed using the modified Rankin Scale [mRS], with excellent outcome defined as mRS 0-1). Multivariate logistic regression analysis was used for statistical evaluation. After 3-4 months, complete recovery was achieved in 41 (50%) and excellent clinical outcome in 67 (81.7%) patients. Female sex (OR 0.11; p = 0.0189) and presence of focal neurologic deficit (OR 0.16; p = 0.0165) were identified as significant independent negative predictors and, the presence of GSRF (OR 15.63; p = 0.0011) as significant independent positive predictor of excellent clinical outcome. In conclusion, in our CVST patients, the presence of GSRF was associated with excellent clinical outcome, while the female sex itself was associated with poorer clinical outcome.

Simple capacitor-switch model of excitatory and inhibitory neuron with all parts biologically explained allows input fire pattern dependent chaotic oscillations

Due to known information processing capabilities of the brain, neurons are modeled at many different levels. Circuit theory is also often used to describe the function of neurons, especially in complex multi-compartment models, but when used for simple models, there is no subsequent biological justification of used parts. We propose a new single-compartment model of excitatory and inhibitory neuron, the capacitor-switch model of excitatory and inhibitory neuron, as an extension of the existing integrate-and-fire model, preserving the signal properties of more complex multi-compartment models. The correspondence to existing structures in the neuronal cell is then discussed for each part of the model. We demonstrate that a few such inter-connected model units are capable of acting as a chaotic oscillator dependent on fire patterns of the input signal providing a complex deterministic and specific response through the output signal. The well-known necessary conditions for constructing a chaotic oscillator are met for our presented model. The capacitor-switch model provides a biologically-plausible concept of chaotic oscillator based on neuronal cells.

Motion Assessment for Accelerometric and Heart Rate Cycling Data Analysis

Motion analysis is an important topic in the monitoring of physical activities and recognition of neurological disorders. The present paper is devoted to motion assessment using accelerometers inside mobile phones located at selected body positions and the records of changes in the heart rate during cycling, under different body loads. Acquired data include 1293 signal segments recorded by the mobile phone and the Garmin device for uphill and downhill cycling. The proposed method is based upon digital processing of the heart rate and the mean power in different frequency bands of accelerometric data. The classification of the resulting features was performed by the support vector machine, Bayesian methods, k-nearest neighbor method, and neural networks. The proposed criterion is then used to find the best positions for the sensors with the highest discrimination abilities. The results suggest the sensors be positioned on the spine for the classification of uphill and downhill cycling, yielding an accuracy of 96.5% and a cross-validation error of 0.04 evaluated by a two-layer neural network system for features based on the mean power in the frequency bands 〈 3 , 8 〉 and 〈 8 , 15 〉 Hz. This paper shows the possibility of increasing this accuracy to 98.3% by the use of more features and the influence of appropriate sensor positioning for motion monitoring and classification.

Sleep Apnea Detection with Polysomnography and Depth Sensors

This paper is devoted to proving two goals, to show that various depth sensors can be used to record breathing rate with the same accuracy as contact sensors used in polysomnography (PSG), in addition to proving that breathing signals from depth sensors have the same sensitivity to breathing changes as in PSG records. The breathing signal from depth sensors can be used for classification of sleep [d=R2]apneaapnoa events with the same success rate as with PSG data. The recent development of computational technologies has led to a big leap in the usability of range imaging sensors. New depth sensors are smaller, have a higher sampling rate, with better resolution, and have bigger precision. They are widely used for computer vision in robotics, but they can be used as non-contact and non-invasive systems for monitoring breathing and its features. The breathing rate can be easily represented as the frequency of a recorded signal. All tested depth sensors (MS Kinect v2, RealSense SR300, R200, D415 and D435) are capable of recording depth data with enough precision in depth sensing and sampling frequency in time (20-35 frames per second (FPS)) to capture breathing rate. The spectral analysis shows a breathing rate between 0.2 Hz and 0.33 Hz, which corresponds to the breathing rate of an adult person during sleep. To test the quality of breathing signal processed by the proposed workflow, a neural network classifier (simple competitive NN) was trained on a set of 57 whole night polysomnographic records with a classification of sleep [d=R2]apneaapnoas by a sleep specialist. The resulting classifier can mark all [d=R2]apneaapnoa events with 100% accuracy when compared to the classification of a sleep specialist, which is useful to estimate the number of events per hour. [d=R2]When compared to the classification of polysomnographic breathing signal segments by a sleep specialistand, which is used for calculating length of the event, the classifier has an [d=R1] F 1 score of 92.2%Accuracy of 96.8% (sensitivity 89.1% and specificity 98.8%). The classifier also proves successful when tested on breathing signals from MS Kinect v2 and RealSense R200 with simulated sleep [d=R2]apneaapnoa events. The whole process can be fully automatic after implementation of automatic chest area segmentation of depth data.

CD4+/CD45RO+: A Potential Biomarker of the Clinical Response to Glatiramer Acetate

Background: Glatiramer acetate (GA) is an effective treatment for the earliest stages of multiple sclerosis (MS)—clinically isolated syndrome (CIS) or clinically definite MS (CDMS). Objective: This study aims to determine the differences in the lymphocyte population (at baseline and the course of five years) between confirmed sustained progression (CSP) and non-CSP groups and to identify potential biomarkers among these parameters that can predict a positive response to the treatment. Methods: Twelve male and 60 female patients were included in the study. Peripheral blood samples were collected before and five years after treatment with GA. The authors compared lymphocyte parameters between the CSP and non-CSP groups by statistical analyses. Univariate and penalized logistic regression models were fitted to identify the best lymphocyte parameters at baseline and their combination for potential biomarkers. Subsequently, the ROC analysis was used to identify cut-offs for selected parameters. Results: The parameter CD4+/CD45RO+ was identified as the best single potential biomarker, demonstrating the ability to identify patients with CSP. Moreover, a combination of four lymphocyte parameters at baseline, relative lymphocyte counts, CD3+/CD69+, CD4+/CD45RO+, and CD4+/CD45RA+ab, was identified as a potential composite biomarker. This combination explains 23% of the variability in CSP, which is better than the best univariate parameter when compared to CD4+/CD45RO+ at baseline. Conclusions: The results suggest that other biomarkers can help monitor the conditions of patients and predict a favourable outcome.

Monitoring of Lymphocyte Populations During Treatment with Interferon-β-1b to Predict Multiple Sclerosis Disability Progression

The authors aim to understand how lymphocyte populations could predict the course of multiple sclerosis (MS) in people treated with interferon-β (IFN-β). Twenty-five male patients and 72 female patients were analyzed in the study. Peripheral blood samples were taken before and 5 years after the treatment with IFN-β. Lymphocyte subsets were analyzed by flow cytometry. The authors compared lymphocyte parameters between confirmed sustained progression (CSP) and non-CSP groups by using Welch's one-way analysis of means or a chi-square test of independence. A penalized (lasso) logistic regression model was fitted to identify the combination of lymphocyte parameters for potential biomarkers. The combination of lymphocyte counts, relative CD3+/CD25+ cells, absolute CD8 T cells, absolute CD8+/CD38+ cells, absolute CD38+ cells, and relative CD5+/CD19+ cells was identified as potential biomarker for the IFN-β treatment to monitor MS development in relation to CSP. The results suggest that other biomarkers aid in patient observation, predict a favorable outcome, and assist in the decision-making process for the early therapy escalation.

Lymphocyte populations and their change during five-year glatiramer acetate treatment

BACKGROUND

The goal of this study was to determine the characteristics that are affected in patients treated with glatiramer acetate (GA).

METHODS

A total of 113 patients were included in this study. Patients were treated with glatiramer acetate (subcutaneous injection, 20 mg, each day). Peripheral blood samples were obtained just prior to treatment as well as 5 years after GA treatment. All the calculations were performed with the statistical system R (r-project.org).

RESULTS

After 5 years of treatment, a significant decrease was found in the absolute and relative CD3+/CD69+ counts, the absolute and relative CD69 counts, the relative CD8+/CD38+ count and the relative CD38 count. A significant increase was found in the absolute and relative CD5+/CD45RA+ counts and the absolute CD5+/CD45RO+ count after 5 years of treatment.

CONCLUSION

This study presents some parameters that were affected by long-term GA treatment.

Mechanical recanalization in ischemic anterior circulation stroke within an 8-hour time window: a real-world experience

PURPOSE

We aimed to assess the safety and effectiveness of mechanical recanalization in patients with ischemic stroke in the anterior circulation within 8 h since symptoms onset and with unknown onset time. We compared time intervals <6 h vs. 6-8 h/unknown onset time, as only limited data are available for a time window beyond 6 h.

METHODS

Our cohort included 110 consecutive patients (44 males; mean age, 73.0±11.5 years) with ischemic stroke in the anterior circulation due to the acute occlusion of a large intracranial artery who underwent mechanical recanalization within an 8-hour time window or with unknown onset time. All patients underwent unenhanced computed tomography (CT) of the brain, CT angiography of the cervical and intracranial arteries and digital subtraction angiography. Perfusion CT was performed in patients beyond a 6-hour time window/with unknown onset time. We collected the following data: baseline characteristics, presence of risk factors, neurologic deficit at the time of treatment, time to therapy, recanalization rate, and 3-month clinical outcome. Successful recanalization was defined as Thrombolysis in Cerebral Infarction score of 2b/3 and good clinical outcome as modified Rankin scale value of 0-2 points.

RESULTS

Successful recanalization was achieved in 82 patients (74.5%): in 61 patients treated within 6 h (73.5%), 7 patients treated within 6-8 h (63.6%), and 13 patients with unknown onset time (81.3%). Good 3-month clinical outcome was achieved in 61 patients (55.5%): in 46 patients treated within 6 h (55.4%), 5 patients treated within 6-8 h (45.5%), and 10 patients with unknown onset time (62.5%). Recanalization success or clinical outcome were not significantly different between patients treated at different time windows.

CONCLUSION

Our data confirms the safety and effectiveness of mechanical recanalization performed in carefully selected patients with ischemic stroke in the anterior circulation within 8 h of stroke onset or with unknown onset time in everyday practice.

Fibrin Clot Architecture in Acute Ischemic Stroke Treated With Mechanical Thrombectomy With Stent-Retrievers - Cohort Study

BACKGROUND

The composition of intra-arterial clots might influence the efficacy of mechanical thrombectomy (MT) in ischemic stroke (IS) due to the acute occlusions within large cerebral arteries. The aims were to assess the factors associated with blood clot structure and the impact of thromboembolus structure on MT using stent-retrievers in patients with acute large artery IS in the anterior circulation.Methods and Results:In an observational cohort study, we studied the components of intra-arterial clots retrieved from large cerebral arteries in 80 patients with acute IS treated with MT with or without i.v. thrombolysis (IVT). Histology of the clots was carried out without knowledge of the clinical findings, including the treatment methods. The components of the clots, their age, origin and semi-quantitative graded changes in the architecture of the fibrin components (e.g., "thinning") were compared via neuro-interventional, clinical and laboratory data. The most prominent changes in the architecture of the fibrin components in the thromboemboli were associated with IVT (applied in 44 patients; OR, 3.50; 95% CI: 1.21-10.10, P=0.02) and platelet count (OR, 2.94; 95% CI: 1.06-8.12, P=0.04).

CONCLUSIONS

In patients with large artery IS treated with the MT using stent-retrievers, bridging therapy with IVT preceding MT and higher platelet count were associated with significant changes of the histological structure of blood clots.

Lymphocytes in the treatment with interferon beta-1 b

BACKGROUND

Multiple sclerosis (MS) is a chronic inflammatory demyelinating and neurodegenerative disease affecting the central nervous system. One of the basic medications for the treatment of a clinically isolated syndrome (CIS) or relapsing-remitting MS is interferon beta (INFβ). Although the exact mechanism of its effects is unknown, the medication has an anti-inflammatory and immunomodulatory effect. The goal of this study was to determine the characters which are affected in patients treated with INFβ.

METHODS

A total of 97 patients (25 males and 72 females) were included into the study. Patients were treated by INFβ 1-b (subcutaneous injection, 250µg, each other day). Clinical evaluations were performed by an attending neurologist. Peripheral blood samples were obtained just prior to treatment and 5 years after INFβ 1-b. Statistical analysis and processing of the obtained data were performed by using a comprehensive statistical software package MATLAB®.

RESULTS

A significant decrease of the observed parameters after 5 years' of treatment (significant at the 1% significance level) was found in the absolute and relative CD69 count, absolute cytotoxic/suppressor T lymphocyte count, absolute total leukocyte count, absolute natural killer cells count. A significant decrease of the observed parameters after 5 years' of treatment (significant at the 5% significance level) was found in the absolute lymphocyte count, relative cytotoxic/suppressor T lymphocyte count, relative CD3+CD69+ count and absolute CD8+CD38+ count.

CONCLUSION

The treatment with interferon beta reduces clinical exacerbations in multiple sclerosis (MS) through several known immunomodulatory mechanisms. However, the exact mechanism of effect of this medication is not known. This study presents some parameters that were affected by the long-term INFβ treatment.

Breathing Analysis Using Thermal and Depth Imaging Camera Video Records

The paper is devoted to the study of facial region temperature changes using a simple thermal imaging camera and to the comparison of their time evolution with the pectoral area motion recorded by the MS Kinect depth sensor. The goal of this research is to propose the use of video records as alternative diagnostics of breathing disorders allowing their analysis in the home environment as well. The methods proposed include (i) specific image processing algorithms for detecting facial parts with periodic temperature changes; (ii) computational intelligence tools for analysing the associated videosequences; and (iii) digital filters and spectral estimation tools for processing the depth matrices. Machine learning applied to thermal imaging camera calibration allowed the recognition of its digital information with an accuracy close to 100% for the classification of individual temperature values. The proposed detection of breathing features was used for monitoring of physical activities by the home exercise bike. The results include a decrease of breathing temperature and its frequency after a load, with mean values -0.16 °C/min and -0.72 bpm respectively, for the given set of experiments. The proposed methods verify that thermal and depth cameras can be used as additional tools for multimodal detection of breathing patterns.

Cerebral Venous Sinus Thrombosis

The frequency of patients diagnosed with cerebral venous sinus thrombosis (CVST) has increased due to the expanded use of noninvasive brain imaging methods. The aim of this study was to assess the correlations between the location and extent of venous sinus impairment, clinical presentation during the acute phase, recanalization, the presence of parenchymal lesions, and clinical outcome after 3 to 4 months in patients with CVST. In a retrospective study, clinical and magnetic resonance imaging data from a cohort of 51 consecutive patients with CVST (mean age 33.1 ± 15.4 years) were collected and analyzed. Good clinical outcome after 3 to 4 months, which was assessed using the modified Rankin scale, significantly negatively correlated with a thrombosis location in the left transverse, left sigmoid, or superior sagittal sinus ( P = .022, P = .045, and P = .046, respectively) and positively correlated with recanalization ( P = .048). The clinical outcome was significantly more favorable in the females with gender-specific risk factors than in the males ( P = .029). In conclusion, successful recanalization substantially helps to achieve good clinical outcome in patients with CVST.

Proteomic analysis of cerebrospinal fluid for relapsing-remitting multiple sclerosis and clinically isolated syndrome

Early diagnosis and treatment of multiple sclerosis (MS) in the initial stages of the disease can significantly retard its progression. The aim of the present study was to identify changes in the cerebrospinal fluid proteome in patients with relapsing-remitting MS and clinically isolated MS syndrome who are at high risk of developing MS (case group) compared to healthy population (control) in order to identify potential new markers, which could ultimately aid in early diagnosis of MS. The protein concentrations of each of the 11 case and 15 control samples were determined using a bicinchoninic acid assay. Nanoscale liquid chromatography coupled with tandem mass spectrometry was used for protein identification. Proteomics data were processed using the Perseus software suite and R. The results were filtered using the Benjamini-Hochberg procedure for the false discovery rate (FDR) correction (FDR<0.05). The results showed that, 26 proteins were significantly dysregulated in case samples compared to the controls. Nine proteins were found to be significantly less abundant in case samples, while the abundance of 17 proteins was significantly increased in case samples compared to controls. Three of the proteins were previously linked to RR MS, including immunoglobulin (Ig) γ-1 chain C region, Ig heavy chain V–III region BRO and Ig κ chain C region. Three proteins that were uniquely expressed in patients with RR MS were identified and these proteins may serve as prognostic biomarkers for identifying patients with a high risk of developing RR MS.

Motion tracking and gait feature estimation for recognising Parkinson's disease using MS Kinect

Background

Analysis of gait features provides important information during the treatment of neurological disorders, including Parkinson’s disease. It is also used to observe the effects of medication and rehabilitation. The methodology presented in this paper enables the detection of selected gait attributes by Microsoft (MS) Kinect image and depth sensors to track movements in three-dimensional space.

Methods

The experimental part of the paper is devoted to the study of three sets of individuals: 18 patients with Parkinson’s disease, 18 healthy aged-matched individuals, and 15 students. The methodological part of the paper includes the use of digital signal-processing methods for rejecting gross data-acquisition errors, segmenting video frames, and extracting gait features. The proposed algorithm describes methods for estimating the leg length, normalised average stride length (SL), and gait velocity (GV) of the individuals in the given sets using MS Kinect data.

Results

The main objective of this work involves the recognition of selected gait disorders in both the clinical and everyday settings. The results obtained include an evaluation of leg lengths, with a mean difference of 0.004 m in the complete set of 51 individuals studied, and of the gait features of patients with Parkinson’s disease (SL: 0.38 m, GV: 0.61 m/s) and an age-matched reference set (SL: 0.54 m, GV: 0.81 m/s). Combining both features allowed for the use of neural networks to classify and evaluate the selectivity, specificity, and accuracy. The achieved accuracy was 97.2 %, which suggests the potential use of MS Kinect image and depth sensors for these applications.

Conclusions

Discussion points include the possibility of using the MS Kinect sensors as inexpensive replacements for complex multi-camera systems and treadmill walking in gait-feature detection for the recognition of selected gait disorders.

ASPIRIN RESISTANCE IN NEUROVASCULAR DISEASES

INTRODUCTION

The issue of resistance to antiplatelet therapy has raised many questions in the area of neurovascular diseases. The first objective of this work was to determine the prevalence of aspirin resistance in neurovascular patients with clinical non-responsiveness to aspirin treatment and a high-risk of atherothrombotic complications using two interpretable and independent methods (aggregation and PFA 100). The second objective was to find the correlation between both assays and to evaluate the results in groups at risk for various cerebrovascular diseases.

MATERIAL AND METHODS

Laboratory tests of aspirin resistance were performed in 79 patients with clinical non-responsiveness to aspirin treatment suffering from neurovascular diseases. Patients were divided into the two groups: expected low risk for aspirin resistance due to the first manifestation of a neurovascular disease (n = 34) and expected high risk due to the second clinical manifestation of a neurovascular disease (n = 45).

RESULTS

The prevalence of aspirin resistance in both groups combined as determined by the PFA-100 and CPG techniques were 50.6% and 17.7%, respectively. No correlation was found between the two techniques.

CONCLUSIONS

No significant prevalence of aspirin resistance was demonstrated by either method despite the heterogeneous pathophysiological mechanisms. However, we are presently unable to provide an accurate opinion on the value of laboratory test result or routine monitoring in clinical neurology.

Separation of overlapping dental arch objects using digital records of illuminated plaster casts

Background

Plaster casts of individual patients are important for orthodontic specialists during the treatment process and their analysis is still a standard diagnostical tool. But the growing capabilities of information technology enable their replacement by digital models obtained by complex scanning systems.

Method

This paper presents the possibility of using a digital camera as a simple instrument to obtain the set of digital images for analysis and evaluation of the treatment using appropriate mathematical tools of image processing. The methods studied in this paper include the segmentation of overlapping dental bodies and the use of different illumination sources to increase the reliability of the separation process. The circular Hough transform, region growing with multiple seed points, and the convex hull detection method are applied to the segmentation of orthodontic plaster cast images to identify dental arch objects and their sizes.

Results

The proposed algorithm presents the methodology of improving the accuracy of segmentation of dental arch components using combined illumination sources. Dental arch parameters and distances between the canines and premolars for different segmentation methods were used as a measure to compare the results obtained.

Conclusion

A new method of segmentation of overlapping dental arch components using digital records of illuminated plaster casts provides information with the precision required for orthodontic treatment. The distance between corresponding teeth was evaluated with a mean error of 1.38% and the Dice similarity coefficient of the evaluated dental bodies boundaries reached 0.9436 with a false positive rate \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$FPR=0.0381$$\end{document}FPR=0.0381 and false negative rate \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$FNR=0.0728$$\end{document}FNR=0.0728.

Painful lumbosacral plexopathy: a case report

Patients frequently suffer from lumbosacral plexus disorder. When conducting a neurological examination, it is essential to assess the extent of muscle paresis, sensory disorder distribution, pain occurrence, and blocked spine. An electromyography (EMG) can confirm axonal lesions and their severity and extent, root affliction (including dorsal branches), and disorders of motor and sensory fiber conduction. Imaging examination, particularly gadolinium magnetic resonance imaging (MRI) examination, ensues. Cerebrospinal fluid examination is of diagnostic importance with radiculopathy, neuroinfections, and for evidence of immunoglobulin synthesis. Differential diagnostics of lumbosacral plexopathy (LSP) include metabolic, oncological, inflammatory, ischemic, and autoimmune disorders.In the presented case study, a 64-year-old man developed an acute onset of painful LSP with a specific EMG finding, MRI showing evidence of plexus affliction but not in the proximal part of the roots. Painful plexopathy presented itself with severe muscle paresis in the femoral nerve and the obturator nerve innervation areas, and gradual remission occurred after 3 months. Autoimmune origin of painful LSP is presumed.We describe a rare case of patient with painful lumbar plexopathy, with EMG findings of axonal type, we suppose of autoimmune etiology.

Anti-NMDA receptor antibodies in patients with a first episode of schizophrenia

BACKGROUND

Encephalitis with antibodies against N-methyl-D-aspartate receptor (NMDA-R) is classified as an autoimmune disorder with psychotic symptoms, which are frequently dominant. However, it remains unclear how frequently NMDA-R antibodies lead to a condition that mimics psychosis and first-episode schizophrenia. In our work, we investigated the presence of antibodies against NMDA-R in patients with first-episode psychosis (FEP) in comparison with healthy volunteers.

METHODS

This study included 50 antipsychotic-naïve patients with FEP (including 21 women) and 50 healthy volunteers (including 21 women). The mean age of the patients was 27.4 (±7.4) years and that of the healthy controls was 27.0 (±7.3) years. Antibodies against NMDA-R in the serum were detected by immunofluorescence.

RESULTS

None of the investigated patients with an FEP and none of the healthy controls showed positive antibodies against NMDA-Rs.

CONCLUSION

According to results of studies, a small proportion of patients with an FEP possess antibodies against NMDA-R. However, the extent to which this finding contributes to the etiopathogenesis of the response to antipsychotic medication and whether immunomodulatory therapy is indicated in these cases remains uncertain.

Rare case of a localized radial nerve amyloid neuropathy

We report the case of a 55-year-old woman with a 6-month history of progressive paresis of the right radial nerve. Perioperative imaging detected a spindle-shaped expansion of the radial nerve caused by an isolated local deposit of amyloid (amyloidoma). The deposit was resected in 2 phases and the resulting defect was bridged by a sural nerve autograft. Overall internal and hematological examination did not reveal systemic amyloidosis or lymphoproliferative disorder. The reason for our report is that localized forms of amyloid neuropathy are very rare.

Complex continuous wavelet coherence for EEG microstates detection in insight and calm meditation

Complex continuous wavelet coherence (WTC) can be used for non-stationary signals, such as electroencephalograms. Areas of the WTC with a coherence higher than the calculated optimal threshold were obtained, and the sum of their areas was used as a criterion to differentiate between groups of experienced insight-focused meditators, calm-focused meditators and a control group. This method demonstrated the highest accuracy for the real WTC parts in the frontal region, while for the imaginary parts, the highest accuracy was shown for the frontal occipital pairs of electrodes. In the frontal area, in the broadband frequency, both types of experienced meditators demonstrated an enlargement of the increased coherence areas for the real WTC parts. For the imaginary parts unaffected by the volume conduction and global artefacts, the most significant increase occurred for the frontal occipital pair of electrodes.

Change in the characteristics of EEG color noise in Alzheimer's disease

Neurophysiological experiments support the hypothesis of the presence of critical dynamics of brain activity. This is also manifested by power law of electroencephalography (EEG) power spectra, which can be described by the relation 1/f(alpha). This dependence is a result of internal interactions between parts of the brain and is probably required for optimal processing of information. In Alzheimer's disease, changes in the functional organization of the brain occur, which may be manifested by changes in the alpha coefficient. We compared the average values of alpha for 19 electrodes in the resting EEG record in 110 patients with moderate to severe Alzheimer's disease (Mini-Mental State Examination [MMSE] score = 10-19) with 110 healthy controls. Statistically, the most significant differences are present in the prefrontal areas. In addition to the prefrontal and frontal areas, the largest separation value in the evaluation of receiver operating characteristic (ROC) curves was recorded in the temporal area. The coefficient alpha has few false-positive results in the optimal operating point of the ROC curve, and is thereby highly specific for Alzheimer's disease.

Evaluation of dental morphometrics during the orthodontic treatment

BACKGROUND

Diagnostic orthodontic and prosthetic procedures commence with an initial examination, during which a number of individual findings on occlusion or malocclusion are clarified. Nowadays we try to replace standard plaster casts by scanned objects and digital models.

METHOD

Geometrically calibrated images aid in the comparison of several different steps of the treatment and show the variation of selected features belonging to individual biomedical objects. The methods used are based on geometric morphometrics, making a new approach to the evaluation of the variability of features. The study presents two different methods of measurement and shows their accuracy and reliability.

RESULTS

The experimental part of the present paper is devoted to the analysis of the dental arch objects of 24 patients before and after the treatment using the distances between the canines and premolars as the features important for diagnostic purposes. Our work proved the advantage of measuring digitalized orthodontic models over manual measuring of plaster casts, with statistically significant results and accuracy sufficient for dental practice.

CONCLUSION

A new method of computer imaging and measurements of a dental stone cast provides information with the precision required for orthodontic treatment. The results obtained point to the reduction in the variance of the distances between the premolars and canines during the treatment, with a regression coefficient RC=0.7 and confidence intervals close enough for dental practice. The ratio of these distances pointed to the nearly constant value of this measure close to 0.84 for the given set of 24 individuals.

Common yew intoxication: a case report

Introduction

Taxine alkaloids cause fatal poisoning, in particular due to the compound’s toxic effect on the cardiovascular apparatus.

Case presentation

We describe the case of a 39-year-old Caucasian man with common yew intoxication for whom cardiopulmonary resuscitation using all available methods, although delayed and extended, was successful.

Conclusions

Extended and delayed cardiopulmonary resuscitation can be used successfully to treat common yew intoxication.