This study aimed to directly compare electroencephalography (EEG) whole-brain patterns of neural dynamics with concurrently measured fMRI BOLD data. To achieve this, we aim to derive EEG patterns based on a spatio-spectral decomposition of band-limited EEG power in the source-reconstructed space. In a large dataset of 72 subjects undergoing resting-state hdEEG-fMRI, we demonstrated that the proposed approach is reliable in terms of both the extracted patterns as well as their spatial BOLD signatures. The five most robust EEG spatio-spectral patterns not only include the well-known occipital alpha power dynamics, ensuring consistency with established findings, but also reveal additional patterns, uncovering new insights into brain activity. We report and interpret the most reproducible source-space EEG-fMRI patterns, along with the corresponding EEG electrode-space patterns, which are better known from the literature. The EEG spatio-spectral patterns show weak, yet statistically significant spatial similarity to their functional magnetic resonance imaging (fMRI) blood oxygenation level-dependent (BOLD) signatures, particularly in the patterns that exhibit stronger temporal synchronization with BOLD. However, we did not observe a statistically significant relationship between the EEG spatio-spectral patterns and the classical fMRI BOLD resting-state networks (as identified through independent component analysis), tested as the similarity between their temporal synchronization and spatial overlap. This provides evidence that both EEG (frequency-specific) power and the BOLD signal capture reproducible spatio-temporal patterns of neural dynamics. Instead of being mutually redundant, these only partially overlap, providing largely complementary information regarding the underlying low-frequency dynamics.
- Publication type
- Journal Article MeSH
TiO2 nanoparticles (NPs) are extensively used in various applications, highlighting the importance of ongoing research into their effects. This work belongs among rare whole-body inhalation studies investigating the effects of TiO2 NPs on mice. Unlike previous studies, the concentration of TiO2 NPs in the inhalation chamber (130.8 μg/m3) was significantly lower. This 11-week study on mice confirmed in vivo the presence of TiO2 NPs in lung macrophages and type II pneumocytes including their intracellular localization by using the electron microscopy and the state-of-the-art methods detecting NPs' chemical identity/crystal structure, such as the energy-dispersed X-ray spectroscopy (EDX), cathodoluminescence (CL), and detailed diffraction pattern analysis using powder nanobeam diffraction (PNBD). For the first time in inhalation study in vivo, the alterations in erythrocyte morphology with evidence of echinocytes and stomatocytes, accompanied by iron accumulation in spleen, liver, and kidney, are reported following NP's exposure. Together with the histopathological evidence of hyperaemia in the spleen and kidney, and haemosiderin presence in the spleen, the finding of NPs containing iron might suggest the increased decomposition of damaged erythrocytes. The detection of TiO2 NPs on erythrocytes through CL analysis confirmed their potential systemic availability. On the contrary, TiO2 NPs were not confirmed in other organs (spleen, liver, and kidney); Ti was detected only in the kidney near the detection limit.
- MeSH
- Administration, Inhalation MeSH
- Erythrocytes * drug effects pathology MeSH
- Inhalation Exposure * adverse effects MeSH
- Metal Nanoparticles * toxicity MeSH
- Mice MeSH
- Nanoparticles * toxicity MeSH
- Lung * drug effects metabolism pathology MeSH
- Toxicity Tests, Subchronic MeSH
- Titanium * toxicity pharmacokinetics administration & dosage MeSH
- Tissue Distribution MeSH
- Animals MeSH
- Check Tag
- Male MeSH
- Mice MeSH
- Animals MeSH
- Publication type
- Journal Article MeSH
BACKGROUND: The interaction between joint kinematics and kinetics is usually assessed by linear correlation analysis, which does not imply causality. Understanding the causal links between these variables may help develop landing interventions to improve technique and create joint-specific strengthening programs to reduce reaction forces and injury risk. OBJECTIVE: Therefore, the aim of this study was to analyze the causal interaction between lower limb sagittal kinematics and vertical ground reaction force (VGRF) during single-leg jump landing in children who are jumpers (volleyball and gymnastics) and non-jumpers, using the causal empirical decomposition method. Our hypothesis is that children who participate in jumping sports, compared to those who do not, employ a different joint strategy to regulate ground reaction forces during landing, particularly at the ankle level. METHODS: Two groups were compared: the jumpers group (n = 14) and the non-jumpers (control group, n = 11). The causal interaction between sagittal kinematics and VGRF was assessed using ensemble empirical mode decomposition (EEMD) and time series instantaneous phase dependence in bi-directional causality. The relative causal strength (RCS) between the time series was quantified as the relative ratio of absolute cause strength between kinematics and VGRF. RESULTS: A significant interaction between joint and group was found for RCS (p = 0.035, η2p = 0.14). The post-hoc analysis showed the jumpers group had higher ankle-to-VGRF RCS than the control group (p = 0.017, d = 1.03), while in the control group the hip-to-VGRF RCS was higher than the ankle-to-VGRF RCS (p = 0.004, d = 0.91). CONCLUSION: Based on the causal decomposition approach, our results indicate that practicing jumping sports increases the causal effect of ankle kinematics on ground reaction forces in children. While non-jumper children rely more on the hip to modulate reaction forces, jumper children differ from non-jumpers by their greater use of the ankle joint. These findings could be used to develop specific training programs to improve landing techniques according to practice level, potentially helping to reduce the risk of injury in both athletes and non-athletes.
- MeSH
- Biomechanical Phenomena physiology MeSH
- Child MeSH
- Lower Extremity physiology MeSH
- Gymnastics * physiology MeSH
- Ankle Joint physiology MeSH
- Humans MeSH
- Volleyball physiology MeSH
- Check Tag
- Child MeSH
- Humans MeSH
- Male MeSH
- Female MeSH
- Publication type
- Journal Article MeSH
A family of new compounds with sulfonamide and amide functional groups as potential Alzheimer's disease drugs were prepared by multistep synthesis. Thermal stability measurements recorded the initial decomposition in the range of 200-220°C, close above the melting point. The final compounds were tested for their ability to inhibit acetylcholinesterase and butyrylcholinesterase, and the in vitro dissolution behavior of selected compounds was studied through both lipophilic and hydrophilic matrix tablets. All nine tested derivatives were even more active in inhibiting acetylcholinesterase than the clinically used rivastigmine. Regression analysis of the obtained dissolution profiles was performed, and the effects of the pH and the release mechanism were determined. Some substances showed remarkable biological activity and became a subject of interest for further extensive study.
- MeSH
- Acetylcholinesterase metabolism MeSH
- Alzheimer Disease * drug therapy MeSH
- Butyrylcholinesterase * metabolism MeSH
- Cholinesterase Inhibitors * pharmacology chemical synthesis chemistry MeSH
- Hydrogen-Ion Concentration MeSH
- Humans MeSH
- Molecular Structure MeSH
- Rivastigmine pharmacology chemical synthesis chemistry MeSH
- Solubility MeSH
- Sulfonamides * pharmacology chemistry chemical synthesis MeSH
- Structure-Activity Relationship MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
Ixazomib is the only orally active proteasome inhibitor used in clinical practice as an anticancer drug. The novel, rapid UHPLC-UV assay for ixazomib was developed and applied to the forced degradation study followed by HRMS identification of the main degradation products. Oxidative deboronation and hydrolysis of the amid bond were found to be the principal degradation pathways. The chemical standards of the main degradation products were prepared. The method was validated for the simultaneous assay of ixazomib and its degradation products within the concentration ranges of 2.50-100.00 μg/mL (ixazomib); 0.75-60.00 μg/mL (Impurity A and B) and 1.25-60.00 μg/mL (Impurity C). The stability study revealed that ixazomib in solution is: 1) relatively stable in neutral and acidic environments, 2) its decomposition is accelerated at higher pH, 3) it is sensitive to the effects of oxidants and light, and 4) the degradation of ixazomib follows the first-order kinetics under neutral, acidic, alkaline, and UV stress. Contrary, the solid substance of ixazomib citrate was relatively resistant to heat (70 °C), heat/humidity (70 °C/75 % RH), and UV irradiation for 24 h. This study presents the first MS-compatible UHPLC method for the quantification of ixazomib and its degradation products. Furthermore, it provides data about the inherent stability and kinetics of degradation of ixazomib in a solution that may be useful in further investigation of this drug, or the development of novel proteasome inhibitors based on the ixazomib structure.
This study proposes an approach to the external evaluation of medical education programs' quality based on a combination of indicators, including international rankings, external stakeholders' input, and independent agencies' assessments. We modify the success equation with a detailed consideration of the skill component and its decomposition into internal and external quality assurance elements along with authority. We carried out a bibliometric analysis regarding the problem of medical education quality assessment in the context of achieving sustainable development goals. We described the calculation model of external quality assessment indicators through the algorithms of independent education quality assurance agencies' activity and rating indicators shown in the modified Mauboussin's equation. The model considers the economic component (the consequence of achievement) of skill, which is expressed in raising funds from external sources to implement educational and scientific activities. The proposed algorithm for assessing the educational program quality can be applied to benchmark educational program components, complete educational programs within the subject area, and the educational institution for different areas. We propose a "financial" model for educational program quality based on the analysis results. The model makes it possible to determine the need for additional focused funding of the educational program based on the individual analysis of the external evaluation criteria of the achievement level. This study analyzes the accreditation results of more than 110 educational programs in 2020 and 8 months of 2021 within the direction 22 "Medicine" (according to the national classification of fields of knowledge) (state and private Ukrainian medical universities).
- MeSH
- Education, Medical * MeSH
- Educational Measurement * MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
BACKGROUND: Presentation of visual stimuli can induce changes in EEG signals that are typically detectable by averaging together data from multiple trials for individual participant analysis as well as for groups or conditions analysis of multiple participants. This study proposes a new method based on the discrete wavelet transform with Huffman coding and machine learning for single-trial analysis of evenal (ERPs) and classification of different visual events in the visual object detection task. METHODS: EEG single trials are decomposed with discrete wavelet transform (DWT) up to the [Formula: see text] level of decomposition using a biorthogonal B-spline wavelet. The coefficients of DWT in each trial are thresholded to discard sparse wavelet coefficients, while the quality of the signal is well maintained. The remaining optimum coefficients in each trial are encoded into bitstreams using Huffman coding, and the codewords are represented as a feature of the ERP signal. The performance of this method is tested with real visual ERPs of sixty-eight subjects. RESULTS: The proposed method significantly discards the spontaneous EEG activity, extracts the single-trial visual ERPs, represents the ERP waveform into a compact bitstream as a feature, and achieves promising results in classifying the visual objects with classification performance metrics: accuracies 93.60[Formula: see text], sensitivities 93.55[Formula: see text], specificities 94.85[Formula: see text], precisions 92.50[Formula: see text], and area under the curve (AUC) 0.93[Formula: see text] using SVM and k-NN machine learning classifiers. CONCLUSION: The proposed method suggests that the joint use of discrete wavelet transform (DWT) with Huffman coding has the potential to efficiently extract ERPs from background EEG for studying evoked responses in single-trial ERPs and classifying visual stimuli. The proposed approach has O(N) time complexity and could be implemented in real-time systems, such as the brain-computer interface (BCI), where fast detection of mental events is desired to smoothly operate a machine with minds.
- MeSH
- Algorithms MeSH
- Electroencephalography * methods MeSH
- Evoked Potentials physiology MeSH
- Humans MeSH
- Area Under Curve MeSH
- Signal Processing, Computer-Assisted MeSH
- Machine Learning MeSH
- Wavelet Analysis * MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
The use of unicellular algae to remove xenobiotics (including drugs) from wastewaters is one of the rapidly developing areas of environmental protection. Numerous data indicate that for efficient phycoremediation three processes are important, i.e. biosorption, bioaccumulation, and biotransformation. Although biosorption and bioaccumulation do not raise any serious doubts, biotransformation is more problematic since its products can be potentially more toxic than the parent compounds posing a threat to organisms living in a given environment, including organisms that made this transformation. Thus, two questions need to be answered before the proper algae strain is chosen for phycoremediation, namely what metabolites are produced during biotransformation, and how resistant is the analyzed strain to a mixture of parent compound and metabolites that appear over the course of culture? In this work, we evaluated the remediation potential of the model green alga Chlamydomonas reinhardtii in relation to non-steroidal anti-inflammatory drugs (NSAIDs), as exemplified by diclofenac. To achieve this, we analysed the susceptibility of C. reinhardtii to diclofenac as well as its capability to biosorption, bioaccumulation, and biotransformation of the drug. We have found that even at a relatively high concentration of diclofenac the algae maintained their vitality and were able to remove (37.7%) DCF from the environment. A wide range of phase I and II metabolites of diclofenac (38 transformation products) was discovered, with many of them characteristic rather for animal and bacterial biochemical pathways than for plant metabolism. Due to such a large number of detected products, 18 of which were not previously reported, the proposed scheme of diclofenac transformation by C. reinhardtii not only significantly contributes to broadening the knowledge in this field, but also allows to suggest possible pathways of degradation of xenobiotics with a similar structure. It is worth pointing out that a decrease in the level of diclofenac in the media observed in this study cannot be fully explained by biotransformation (8.4%). The mass balance analysis indicates that other processes (total 22%), such as biosorption, a non-extractable residue formation, or complete decomposition in metabolic cycles can be involved in the diclofenac disappearance, and those findings open the prospects of further research.
- MeSH
- Anti-Inflammatory Agents, Non-Steroidal analysis MeSH
- Biotransformation MeSH
- Water Pollutants, Chemical * analysis MeSH
- Chlamydomonas reinhardtii * metabolism MeSH
- Diclofenac toxicity metabolism MeSH
- Water MeSH
- Animals MeSH
- Check Tag
- Animals MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
BACKGROUND: A good health care system and, especially, the provision of efficient hospital care are the goals of national and regional health policies. However, the scope of general hospital care in the 16 federal states in Germany varies considerably from region to region. The objectives of this paper are to evaluate the technical efficiencies of all general hospitals of the 16 federal states for the period from 2015 to 2020, to find out the relation between the exogenous factors and score of efficiency, and also the influence of the COVID-19 pandemic on the results of the technical efficiency of hospital care in the German states. METHODS: A two-step approach was used. First, an input-oriented Data Envelopment Analysis model with constant returns to scale and variable returns to scale was applied for the 6-year period from 2015 to 2020. The calculation of technical efficiency according to the input-oriented DEA model contains the three components-total technical efficiency (TTE), pure technical efficiency (PTE) and scale efficiency (SE). In the second stage, the influence of exogenous variables on the previously determined technical efficiency was evaluated by applying the tobit regression analysis. RESULTS: Although the level of average technical efficiency of about 90% is high, total technical efficiency deteriorated steadily from 2015 to 2020. Its lowest point at around 78%, was in the year 2020. The deterioration of the average technical efficiency is notably influenced by the lower results in the years 2019 and 2020. The decomposition of technical efficiency also revealed that the deterioration of overall average efficiency was influenced by both pure technical efficiency (PTE) and scale efficiency (SE). Based on the tobit regression analysis performed, it was possible to conclude that the change in the efficiency score can be explained by the influence of exogenous factors only from 6.4% for overall efficiency and from 7.1% for scale efficiency. CONCLUSIONS: The results of the analysis of the overall technical efficiency reveal that the aggregated data of all general hospitals of all 16 federal states show a steadily worsening total technical efficiency every year since 2015. Although, especially, the deterioration of the year 2020 with the occurrence of COVID-19 pandemic, contributes to a deteriorated efficiency average, the deterioration of the efficiency values, based on the analysis performed, is also observable between the years 2016 and 2019. Considering the output generated, for inefficient units and the relevant policy authorities in the hospital sector, it can be recommended that the number of beds and in particular the number of physicians, should be reduced as inputs. Based on this study, it is also recommended that decisions to increase the efficiency of general hospitals should be made with consideration of exogenous factors such as the change in the number of general hospitals or the population density in the respective state, as these had explanatory value in connection with the increase in efficiency values. Due to the wide variation in the size of the federal states, the recommendation is more appropriate for federal states with low population density.
- Publication type
- Journal Article MeSH
Fetal phonocardiography is a non-invasive, completely passive and low-cost method based on sensing acoustic signals from the maternal abdomen. However, different types of interference are sensed along with the desired fetal phonocardiography. This study focuses on the comparison of fetal phonocardiography filtering using eight algorithms: Savitzky-Golay filter, finite impulse response filter, adaptive wavelet transform, maximal overlap discrete wavelet transform, variational mode decomposition, empirical mode decomposition, ensemble empirical mode decomposition, and complete ensemble empirical mode decomposition with adaptive noise. The effectiveness of those methods was tested on four types of interference (maternal sounds, movement artifacts, Gaussian noise, and ambient noise) and eleven combinations of these disturbances. The dataset was created using two synthetic records r01 and r02, where the record r02 was loaded with higher levels of interference than the record r01. The evaluation was performed using the objective parameters such as accuracy of the detection of S1 and S2 sounds, signal-to-noise ratio improvement, and mean error of heart interval measurement. According to all parameters, the best results were achieved using the complete ensemble empirical mode decomposition with adaptive noise method with average values of accuracy = 91.53% in the detection of S1 and accuracy = 68.89% in the detection of S2. The average value of signal-to-noise ratio improvement achieved by complete ensemble empirical mode decomposition with adaptive noise method was 9.75 dB and the average value of the mean error of heart interval measurement was 3.27 ms.
