Polyphenol-Enriched Composite Bone Regeneration Materials: A Systematic Review of In Vitro Studies

One of the possible alternatives for creating materials for the regeneration of bone tissue supporting comprehensive reconstruction is the incorporation of active substances whose controlled release will improve this process. This systematic review aimed to identify and synthesize in vitro studies that assess the suitability of polyphenolics as additives to polymer-ceramic composite bone regeneration materials. Data on experimental studies in terms of the difference in mechanical, wettability, cytocompatibility, antioxidant and anti-inflammatory properties of materials were synthesized. The obtained numerical data were compiled and analyzed in search of percentage changes of these parameters. The results of the systematic review were based on data from forty-six studies presented in nineteen articles. The addition of polyphenolic compounds to composite materials for bone regeneration improved the cytocompatibility and increased the activity of early markers of osteoblast differentiation, indicating a high osteoinductive potential of the materials. Polyphenolic compounds incorporated into the materials presumably give them high antioxidant properties and reduce the production of reactive oxygen species in macrophage cells, implying anti-inflammatory activity. The evidence was limited by the number of missing data and the heterogeneity of the data.     

Biomarkers for the Diagnosis of Alzheimer’s Disease in Clinical Practice: The Role of CSF Biomarkers during the Evolution of Diagnostic Criteria

Alzheimer’s disease (AD) is a progressive condition and the most common cause of dementia worldwide. The neuropathological changes characteristic of the disorder can be successfully detected before the development of full-blown AD. Early diagnosis of the disease constitutes a formidable challenge for clinicians. CSF biomarkers are the in vivo evidence of neuropathological changes developing in the brain of dementia patients. Therefore, measurement of their concentrations allows for improved accuracy of clinical diagnosis. Moreover, AD biomarkers may provide an indication of disease stage. Importantly, the CSF biomarkers of AD play a pivotal role in the new diagnostic criteria for the disease, and in the recent biological definition of AD by the National Institute on Aging, NIH and Alzheimer’s Association. Due to the necessity of collecting CSF by lumbar puncture, the procedure seems to be an important issue not only from a medical, but also a legal, viewpoint. Furthermore, recent technological advances may contribute to the automation of AD biomarkers measurement and may result in the establishment of unified cut-off values and reference limits. Moreover, a group of international experts in the field of AD biomarkers have developed a consensus and guidelines on the interpretation of CSF biomarkers in the context of AD diagnosis. Thus, technological advancement and expert recommendations may contribute to a more widespread use of these diagnostic tests in clinical practice to support a diagnosis of mild cognitive impairment (MCI) or dementia due to AD. This review article presents up-to-date data regarding the usefulness of CSF biomarkers in routine clinical practice and in biomarkers research.     

Gene Variants Related to Cardiovascular and Pulmonary Diseases May Correlate with Severe Outcome of COVID-19

Background: Severe outcomes of COVID-19 account for up to 15% of all cases. The study aims to check if any gene variants related to cardiovascular (CVD) and pulmonary diseases (PD) are correlated with a severe outcome of COVID-19 in a Polish cohort of COVID-19 patients. Methods: In this study, a subset of 747 samples from unrelated individuals collected across Poland in 2020 and 2021 was used and whole-genome sequencing was performed. Results: The GWAS analysis of SNPs and short indels located in genes related to CVD identified one variant significant in COVID-19 severe outcome in the HADHA gene, while for the PD gene panel, we found two significant variants in the DRC1 gene. In this study, both potentially protective and risk variants were identified, of which variants in the HADHA gene deserve the most attention. Conclusions: This is the first study reporting the association between the HADHA and DRC1 genetic variants and COVID-19 severe outcome based on the cohort WGS analysis. Although all the identified variants are localised in introns, they may be correlated and therefore inherited along with other risk variants, potentially causative to severe outcome of COVID-19 but not discovered yet.     

Determination of EEG activity propagation: pair-wise versus multichannel estimate

Performance of different estimators describing propagation of electroencephalogram (EEG) activity, namely: Granger causality, directed transfer function (DTF), direct DTF (dDTF), short-time DTF (SDTF), bivariate coherence, and partial directed coherence are compared by means of simulations and on the examples of experimental signals. In particular, the differences between pair-wise and multichannel estimates are studied. The results show unequivocally that in most cases, the pair-wise estimates are incorrect and a complete set of signals involved in a given process has to be used to obtain the correct pattern of EEG flows. Different performance of multivariate estimators of propagation depending on their normalization is discussed. Advantages of multivariate autoregressive model are pointed out.     

Energy-efficient Rate Adaptation MAC Protocol for Ad Hoc Wireless Networks

In this paper, two novel energy-efficient rate adaptation schemes are presented. The proposed protocols use the Distributed Power Control (DPC) algorithm to predict the channel state and determine the necessary transmission power which optimizes the energy consumption. The first proposed rate adaptation scheme heuristically alters the modulation rate to balance the energy-efficiency and the required throughput which is estimated with queue fill ratio. Moreover, the back-off scheme is incorporated to mitigate congestion and reduce packet losses due to buffer overflows thus minimizing energy consumption. Consequently, the nodes will conserve energy when the traffic is low, offer higher throughput when needed and save energy during congestion by limiting transmission rates. The second rate adaptation scheme employs dynamic programming (DP) principle to analytically select modulation rate and a burst size to be used during transmission. The proposed quadratic cost-function minimizes the energy consumption while alleviating network congestions and buffer overflows. The proposed DP solution renders a Riccati equation ultimately providing an optimal rate selection. The simulation results indicate that an increase in throughput by 96% and energy-efficiency by 131% is observed when compared to other available protocols, for example Receiver Based AutoRate (RBAR).

Variable Fractional Delay Filter Design Using a Symmetric Window

In this paper a numerically efficient method for designing a nearly optimal variable fractional delay (VFD) filter based on a simple and well-known window method is presented. In the proposed method a single window extracted from the optimal filter with fixed fractional delay (FD) is divided into even and odd part. Subsequently, the odd part is discarded and symmetric even part of the extracted window is used to design a family of nearly optimal filters with varying FD. In addition to window extraction, the proposed approach requires filter gain correction which is dependent on the desired FD. Optimum values of the gain correction factor as well as the extracted window can be computed beforehand, which allows us to design a nearly optimal FD filter with arbitrary FD at low numerical costs during runtime. On the basis of the proposed filter design method, the universal structure of VFD filter allowing for change of filter type and length has been proposed. In the paper, three FD filter optimality criteria are considered, which are maximal flatness, Chebyshev (minimax), and least squares.     

The Dynamic Emission Zone in Sandwich Polymer Light‐Emitting Electrochemical Cells

In light‐emitting electrochemical cells (LECs), the position of the emission zone (EZ) is not predefined via a multilayer architecture design, but governed by a complex motion of electrical and ionic charges. As a result of the evolution of doped charge transport layers that enclose a dynamic intrinsic region until steady state is reached, the EZ is often dynamic during turn‐on. For thick sandwich polymer LECs, a continuous change of the emission color provides a direct visual indication of a moving EZ. Results from an optical and electrical analysis indicate that the intrinsic zone is narrow at early times, but starts to widen during operation, notably well before the electrical device optimum is reached. Results from numerical simulations demonstrate that the only precondition for this event to occur is that the mobilities of anions (μ_a) and cations (μ_c) are not equal, and the direction of the EZ shift dictates μ_c > μ_a. Quantitative ion profiles reveal that the displacement of ions stops when the intrinsic zone stabilizes, confirming the relation between ion movement and EZ shift. Finally, simulations indicate that the experimental current peak for constant‐voltage operation is intrinsic and the subsequent decay does not result from degradation, as commonly stated.