The significance of time stages in different types of multiple sclerosis course for the formation of prognosis

Background. The purpose was to develop a prognosis assessment system based on clinical and mathematical analysis of indicators at different stages in various types of the course of multiple sclerosis. Materials and methods. Clinical (clinical neurological method and survey using a questionnaire developed at the Department of Autoimmune and Degenerative Pathology of the Nervous System of the State Institution “Institute of Neurology, Psychiatry and Narcology of the National Academy of Medical Sciences of Ukraine”) and mathematical and statistical (permutation test) methods were applied. Using the method of permutation (permutation test) in groups of patients with different types of multiple sclerosis, the differences in the mean values of clinical indicators were evaluated characterizing the type of multiple sclerosis course at different time stages: preclinical stage, the onset, recurrent stage for relapsing-remitting and secondary progressive multiple sclerosis, stage of progression — for secondary and primary progressive multiple sclerosis. On this basis, clinical indicators were identified, which with a high probability (confidence interval of 0.95) at each time stage of multiple sclerosis determine the final prognosis of the disease. Results. We have examined 280 patients: 80 (50 women and 30 men) with a relapsing-remitting course, 140 (80 women and 60 men) with a secondary progressive course and 60 (30 women and 30 men) with a primary progressive course of multiple sclerosis. The nature of prognosis (good and uncertain with a relapsing-remitting course, uncertain and poor with progressive types) was assessed on the basis of clinical and diagnostic criteria developed taking into account the features of the disease course as a whole. The studies have shown that a good prognosis is highly probable with a combination of clinical indicators such as mild onset, complete remission after onset, mild relapses developing rapidly, and long-term remission between relapses at a relapsing-remitting stage; uncertain prognosis — in the presence of moderate onset, stem symptoms at the onset, severe and moderate relapses, and a tendency to aggravate and lengthen relapses at a relapsing-remitting stage. A poor prognosis in a secondary progressive course is reliably associated with the chickenpox at the preclinical stage in a premorbid history, lightning-fast onset development, steady progression proceeding without clinically outlined periods of stabilization; uncertain prognosis — with a fast development of the onset. A poor prognosis in a primary progressive course was closely associated with severe traumatic brain injury at the preclinical stage in a premorbid history, cerebellar symptoms at the onset, formation of the progression stage immediately after the onset, without the stabilization period, steady type of progression at the stage of progression; uncertain prognosis — with herpetic infections at the preclinical stage in a premorbid history, mild onset, the formation of a progression stage after a stabilization period that occurred after the onset, incremental progression at the progression stage proceeding in the form of alternating periods of slow accumulation of neurological deficit, which, as a rule, has a local focus, and stages of stabilization with different duration. Conclusions. Thus, with the help of clinical and mathematical analysis, it was shown that the formation of alternative prognosis variants for different types of multiple sclerosis occurs through a selective involvement in a single pattern of clinical indicators that have diagnostic significance at different time stages of the course of the disease.

Demencia prevenció: A korai diagnózistól a személyre szabott intervencióig

Összefoglaló. Az elmúlt évtizedekben a várható élettartam emelkedésével drámai mértékben nőtt a demencia előfordulásának gyakorisága, melynek hátterében leggyakrabban az Alzheimer-kór áll. A rendkívül ígéretes, biomarkereken, agyi képalkotáson és mesterséges intelligencián alapuló megközelítéseknek köszönhetően egyre szélesebb körű információink vannak a betegség kialakulásáról és lefolyásáról, új kapukat nyitva ezzel a demencia korai diagnózisa és a személyre szabott terápia felé. Míg az új kutatási irányzatok előnye vitathatatlan, a nagy mennyiségű kutatási adat kezelése, illetve a betegség korai szakaszban történő azonosítása több biztonsági kérdést felvet. A korai diagnózis mellett egyre nagyobb hangsúly helyeződik az intervencióra, a demenciára hajlamosító tényezőkbe történő beavatkozás által. Summary. As a consequence of increasing life expectancy, the number of those living with dementia is rising. While Alzheimer’s disease (AD) constitutes the most common cause of dementia, the origin of AD is unknown. Furthermore, in the absence of effective treatment, therapy focuses on the cognitive and behavioural symptoms of the disease, and the wellbeing of the patient. AD is characterised by a pronounced impairment experienced in one or more cognitive domains, and the criterion of the diagnosis is the presence of aggregated proteins in the brain leading to neuron death, and eventually to the loss of cognitive abilities. As a result of the latest technological advances, several biological markers (biomarkers) of AD pathology were identified. The biomarkers can be obtained using positron emission tomography or measured from cerebrospinal fluid, and lately from blood serum and plasma as well. Magnetic resonance imaging provides an important measure of brain atrophy, a biomarker of neurodegeneration and neuronal injury. The structure of the brain shows significant alterations as a function of neuronal loss, with cortical thinning and tissue density changes, mainly starting from the medial temporal lobes (also including the hippocampus playing a prominent role in memory functions), and extending to the temporoparietal regions, with observed changes in the activity of the different functional brain networks as well. A major challenge in defeating AD is that in most cases, the disease is recognised subsequent to the appearance of the decline in cognitive abilities, hampering everyday life. Previous studies identified a preclinical stage of AD, where the biomarkers indicative of the disease are present in the absence of detectable cognitive symptoms. This early, preclinical stage – with the use of artificial intelligence-based techniques – has been suggested to be a promising window for the early detection of the disease, and also for the prediction of individual disease trajectories, allowing for the thorough planning of patient management. While the benefit of the early diagnosis is unequivocal, it raises a number of important ethical and safety issues. Besides the tremendous effort of developing effective medical treatments, the importance of intervention stands in the centre of scientific interest. The proposed prevention and intervention methods target the potentially modifiable risk factors of dementia, encouraging engagement in stimulating everyday activities and healthy lifestyle, to preserve longevity.

Features of changes in left ventricular mechanics in patients with epicardial obesity

Currently, there is no single non-invasive marker that can directly assess left ventricular (LV) diastolic function. Untwist of LV contributes to diastolic suction and early filling. Speckle-tracking imaging can be used to diagnose diastolic dysfunction at the preclinical stage. Objective To study the features of changes in the parameters of LV mechanics and their relationship with the levels of serum markers of myocardial fibrosis in patients with epicardial obesity (EO). Materials and methods The study included 125 men with general obesity. All patients underwent transthoracic echocardiography (ECG) to assess the thickness of epicardial adipose tissue (tEAT) as equivalent to visceral obesity, as well as to diagnose diastolic dysfunction (DD) of left ventricle (LV). According to the results of ECG, the patients were divided into 2 groups: EO(+) with epicardial fat thickness (tEAT) ≥7 mm (n=78); EO(−) with (tEAT) <7 mm (n=40). DD LV was detected in 7 patients, who were subsequently excluded from the analysis. Profibrotic markers in blood serum (MMP-3, collagen I, collagen III, TGF-β, VEGFA, PICP) were determined in all patients using enzyme immunoassay. Using speckle-tracking ECG, the mechanics of LV were studied (twist LV, peak twist ratio LV, time to peak twist of LV, peak untwist ratio LV, time to peak untwist of LV). The exclusion criteria were the presence of coronary pathology, arterial hypertension, and type 2 diabetes mellitus. Results In the group of patients with EO(+) statistically significant increase the level of all studied profibrotic markers was revealed. According to the results of speckle-tracking ECG in the EO(+) group an increase peak untwist ratio LV to −125.56 (−141.0; −117.0)deg/s (p=0.003) and an increase time to peak untwist of LV of 469.44 (509.0; 401.0) msec was determined in comparison with the EO(−) group (p=0.03). A weak statistically significant effect of tEAT on the peak untwist ratio LV in EO(+) group was revealed (r=0.28; p=0.03). In addition, there was a significant relationship between peak untwist ratio LV and markers of myocardial fibrosis MMP-3 (r=0.23; p=0.03) and collagen type III (r=0.25; p=0.04). Conclusion Thus, LV unwinding may be a new non-invasive marker of LV DD at the preclinical stage, since this parameter reflects the mechanical aspect of global diastolic function, especially the early phase of diastole. FUNDunding Acknowledgement Type of funding sources: None.

Basic Quality Controls Used in Skin Tissue Engineering

Reconstruction of skin defects is often a challenging effort due to the currently limited reconstructive options. In this sense, tissue engineering has emerged as a possible alternative to replace or repair diseased or damaged tissues from the patient’s own cells. A substantial number of tissue-engineered skin substitutes (TESSs) have been conceived and evaluated in vitro and in vivo showing promising results in the preclinical stage. However, only a few constructs have been used in the clinic. The lack of standardization in evaluation methods employed may in part be responsible for this discrepancy. This review covers the most well-known and up-to-date methods for evaluating the optimization of new TESSs and orientative guidelines for the evaluation of TESSs are proposed.

CSF Synaptic Biomarkers in the Preclinical Stage of Alzheimer Disease and Their Association With MRI and PET: A Cross-sectional Study

Objective:To determine whether CSF synaptic biomarkers are altered in the early preclinical stage of the Alzheimer’s continuum and associated with Alzheimer’s disease (AD) risk factors, primary pathology, and neurodegeneration markers.Methods:Cross-sectional study in the ALFA+ cohort, comprising middle-aged cognitively unimpaired participants. CSF neurogranin and GAP-43 were measured using immunoassays and SNAP-25 and synaptotagmin-1 using immunoprecipitation mass spectrometry. AD CSF biomarkers Aβ42/40, p-tau and t-tau, and the neurodegeneration biomarker NfL were also measured. Participants underwent structural MRI, and fluorodeoxyglucose and Aβ PET imaging. General linear modeling was used to test the associations between CSF synaptic biomarkers and risk factors, Aβ pathology, tau pathology, and neurodegeneration markers.Results:All CSF synaptic biomarkers increased with age. CSF neurogranin was higher in females, while CSF SNAP-25 was higher in APOE-ε4 carriers. All CSF synaptic biomarkers increased with higher Aβ load (as measured by CSF Aβ42/40 and Aβ PET Centiloid values) and, importantly, the synaptic biomarkers were increased even in individuals in the earliest stages of Aβ deposition. Higher CSF synaptic biomarkers were also associated with higher CSF p-tau and NfL. Higher CSF neurogranin and GAP-43 were significantly associated with higher brain metabolism, but lower cortical thickness in AD-related brain regions.Conclusion:CSF synaptic biomarkers increase in early preclinical stages of the Alzheimer’s continuum even when a low burden of Aβ pathology is present, and they differ in their association with age, sex, APOE-ε4, and markers of neurodegeneration.

Department of Simulation Education as a Structural Unit of a Multidisciplinary Accreditation and Simulation Center

For the first time, they started talking about virtual simulation technologies in our country in 2002, when at the Institute. Vishnevsky, a virtual simulator "LapSim" was presented at the Congress of Endosurgeons. Since then, there have been great changes in the development of simulators, mannequins and simulators, teaching methods in preclinical training of students. In this regard, there is a real need to give the simulation center the status of a department and to clearly define the tasks that must be solved in the preparation of students and residents at the preclinical stage.

Exploring dynamic functional connectivity alterations in the preclinical stage of Alzheimer’s disease: an exploratory study from SICOLDE

IntroductionExploring functional connectivity (FC) alterations is important for the understanding of underlying neuronal network alterations in subjective cognitive decline (SCD). The objective of this study was to discover stable and subtle dynamic functional connectivity (FC) changes in the preclinical stage of Alzheimer’s disease (AD), and to explore the associations between dynamic FCs and amyloid accumulation.MethodsNinety-seven normal control (NC) subjects, 101 subjective cognitive decline (SCD) subjects, and 55 cognitive impairment (CI) subjects with neuropsychological assessments and resting-state functional magnetic resonance images constituted the whole cohort. Of these, 29 NCs and 52 SCDs with amyloid images were selected as the sub-cohort. First, independent components (ICs) identified by group independent component analysis (ICA) were used to define static and dynamic brain networks. Static and sliding-window dynamic FCs were then calculated. Second, the connection between each pair of ICs was compared between groups in the two cohorts. Hubs were obtained and considered as seeds in the subsequent seed-based dynamic FC analysis. One-way analysis of variance (ANOVA) was used to compare the seed-based dynamic FC maps between groups in the whole cohort, while a 2×2 ANOVA model was used to measure the group or amyloid effects in the sub-cohort. Post-hoc analysis was applied, and differences were considered significant if the cluster-level FWE-corrected p-value was less than 0.001. Finally, correlation analysis was conducted between the altered dynamic FCs, neuropsychological assessments, and amyloid burden.ResultsThe results showed that 42 ICs were revealed. Compared with the static FCs, the dynamic FCs were found to be more stable and sensitive between groups. The effective dynamic FCs included those between the salience/ventral attention network, the default mode network, and the visual network. Specifically, the dynamic FC of the thalamus/caudate (IC 25) drove the hub role in the group differences between the NC and SCD groups. In the seed-based dynamic FC analysis, the dynamic FC between the thalamus/caudate and the middle temporal/frontal gyrus was observed to be higher in the SCD and CI groups in the whole cohort. Moreover, a higher dynamic FC between the thalamus/caudate and visual cortex was observed in the amyloid positive group. Finally, the altered dynamic FC was associated with the amyloid global level standardized uptake value ratio.ConclusionOur findings indicate that dynamic FCs can reflect subtle changes in the preclinical stage of AD.

Hormone metabolic pattern in the preclinical stage of preeclampsia

BACKGROUND: The imbalance of vascular endothelial cell metabolism determines the clinical manifestations of preeclampsia; however, the molecular mechanisms underlying the vessel destabilization are not fully understood. In recent years, researchers have focused on clarifying the role of dysmetabolic disorders in patients with obstetric pathology, including preeclampsia. This is due to the fact that pregnancy is accompanied by metabolic restructuring aimed at switching the energy supply of the pregnant womans body from the carbohydrate to the fat component in order to maintain an effective energoplastic supply of the developing fetus. Impairment of this evolutionary adaptation mechanism realized during pregnancy requires additional in-depth study. AIM: This study was aimed to identify and compare pathogenetic patterns that characterize early and late preeclampsia at the preclinical stage, based on dynamic clinical and laboratory examination of high-risk pregnant women. MATERIALS AND METHODS: A prospective clinical and laboratory examination of 180 pregnant women with independent factors of high risk of developing preeclampsia was carried out. Comparison groups were identified retrospectively, depending on the period of preeclampsia manifestation: Group I consisted of 31 pregnant women with early preeclampsia; Group II comprised 58 pregnant women with late preeclampsia; and Group III (control) included 30 healthy pregnant women with uncomplicated gestation. Pregnant women were examined twice at the preclinical stage of preeclampsia (11-14 and 18-21 weeks of gestation) and once at clinical manifestation of the disease (28-36 weeks of gestation). The markers of metabolic, hormonal, hemocirculatory, hemostasiological and placental disorders were evaluated. RESULTS: We found similar pathophysiological changes in pregnant women with both early and late PE, from early gestation periods. Those were characterized by pathological insulin resistance and hyperinsulinemia, as well as associated atherogenic changes in the lipid profile, hyperleptinemia, hyperuricemia, hypersympathicotonia, visceral fat deposition, and contra-insular hormonal deviations. The observed alterations reflected a single hormonal and metabolic pattern of the preclinical stage of preeclampsia. During pregnancy, there was shown an increase in clustering diabetogenic and atherogenic abnormalities and hormonal changes, which were supplemented by associated endothelial and hemostasiological dysfunction and, in early preeclampsia, placental dysfunction, thus accelerating the time of clinical implementation of preeclampsia. CONCLUSIONS: From the pathogenetic point of view, preeclampsia of various periods of manifestation is an indivisible category with a common basic developmental mechanism characterized by a hormone metabolic pattern from the early stages of pregnancy. These stable changes are the result of the pathologically transformed phylogenetic mechanism of energoplastic supply of the fetus. This transformation is realized via physiological insulin resistance and compensatory hyperinsulinemia development due to the contra-insular activity of placental hormones. The added structural and functional disorders of the embryo (feto) placental system potentiate basic mechanisms (pathological insulin resistance and hyperinsulinemia) and determine the period of preeclampsia clinical manifestation in each particular woman.