Phytochemical and Pharmacological Role of Liquiritigenin and Isoliquiritigenin From Radix Glycyrrhizae in Human Health and Disease Models

The increasing lifespan in developed countries results in age-associated chronic diseases. Biological aging is a complex process associated with accumulated cellular damage by environmental or genetic factors with increasing age. Aging results in marked changes in brain structure and function. Age-related neurodegenerative diseases and disorders (NDDs) represent an ever-growing socioeconomic challenge and lead to an overall reduction in quality of life around the world. Alzheimer’s disease (AD) and Parkinson’s disease (PD) are most common degenerative neurological disorders of the central nervous system (CNS) in aging process. The low levels of acetylcholine and dopamine are major neuropathological feature of NDDs in addition to oxidative stress, intracellular calcium ion imbalance, mitochondrial dysfunction, ubiquitin-proteasome system impairment and endoplasmic reticulum stress. Current treatments minimally influence these diseases and are ineffective in curing the multifunctional pathological mechanisms. Synthetic neuroprotective agents sometimes have negative reactions as an adverse effect in humans. Recently, numerous ethnobotanical studies have reported that herbal medicines for the treatment or prevention of NDDs are significantly better than synthetic drug treatment. Medicinal herbs have traditionally been used around the world for centuries. Radix Glycyrrhizae (RG) is the dried roots and rhizomes of Glycyrrhiza uralensis or G. glabra or G. inflata from the Leguminosae/Fabaceae family. It has been used for centuries in traditional medicine as a life enhancer, for the treatment of coughs and influenza, and for detoxification. Diverse chemical constituents from RG have reported including flavanones, chalcones, triterpenoid saponins, coumarines, and other glycosides. Among them, flavanone liquiritigenin (LG) and its precursor and isomer chalcone isoliquiritigenin (ILG) are the main bioactive constituents of RG. In the present review, we summarize evidence in the literature on the structure and phytochemical properties and pharmacological applications of LG and ILG in age-related diseases to establish new therapeutics to improve human health and lifespan

Superconducting transition of a two-dimensional Josephson junction array in weak magnetic fields

The superconducting transition of a two-dimensional (2D) Josephson junction array exposed to weak magnetic fields has been studied experimentally. Resistance measurements reveal a superconducting-resistive phase boundary in serious disagreement with the theoretical and numerical expectations. Critical scaling analyses of the $IV$ characteristics indicate contrary to the expectations that the superconducting-to-resistive transition in weak magnetic fields is associated with a melting transition of magnetic-field-induced vortices directly from a pinned-solid phase to a liquid phase. The expected depinning transition of vortices from a pinned-solid phase to an intermediate floating-solid phase was not observed. We discuss effects of the disorder-induced random pinning potential on phase transitions of vortices in a 2D Josephson junction array.Comment: 9 pages, 7 figures (EPS+JPG format), RevTeX

Modelling and Simulation of a River-Crossing Operation via Discrete Event Simulation with Engineering Details

From a military standpoint, a river is an area that should be avoided in a potential engagement because of lack of cover and the necessity of dividing the unit while crossing. Thus, a key point of a river-crossing operation is speed. Many efforts have been made to enable faster river crossing by improvement of tactics, techniques, and procedures (TTP). However, improvements in TTP are evaluated by modelling and simulation much less frequently than are the toe-to-toe engagements between two opposing forces, and to our knowledge, this is the first simulation model of brigade-level river crossing with engineering details. This study presents a simulation model of the river-crossing operation, applies real world parameters, and evaluates which tactics are preferable in a particular operational environments. This analysis has led to new operational methods of river crossing that have been suggested by experienced subject-matter experts. For instance, the current Republic of Korea Army Field Manual dictates to rotate river-crossing rafts in all situations, but our experiment suggests that no rotation is preferable when the width of river is less than 400 m based on the statistical analyses, which includes the regression-based meta-modelling and the ANOVA, of our simulation model that embodies the engineering details of river-crossing equipment.Defence Science Journal, Vol. 65, No. 2, March 2015, pp.135-143, DOI:http://dx.doi.org/10.14429/dsj.65.814

Localization Uncertainty Estimation for Anchor-Free Object Detection

Since many safety-critical systems, such as surgical robots and autonomous driving cars, are in unstable environments with sensor noise and incomplete data, it is desirable for object detectors to take into account the confidence of localization prediction. There are three limitations of the prior uncertainty estimation methods for anchor-based object detection. 1) They model the uncertainty based on object properties having different characteristics, such as location (center point) and scale (width, height). 2) they model a box offset and ground-truth as Gaussian distribution and Dirac delta distribution, which leads to the model misspecification problem. Because the Dirac delta distribution is not exactly represented as Gaussian, i.e., for any $\mu$ and $\Sigma$. 3) Since anchor-based methods are sensitive to hyper-parameters of anchor, the localization uncertainty modeling is also sensitive to these parameters. Therefore, we propose a new localization uncertainty estimation method called Gaussian-FCOS for anchor-free object detection. Our method captures the uncertainty based on four directions of box offsets~(left, right, top, bottom) that have similar properties, which enables to capture which direction is uncertain and provide a quantitative value in range~[0, 1]. To this end, we design a new uncertainty loss, negative power log-likelihood loss, to measure uncertainty by weighting IoU to the likelihood loss, which alleviates the model misspecification problem. Experiments on COCO datasets demonstrate that our Gaussian-FCOS reduces false positives and finds more missing-objects by mitigating over-confidence scores with the estimated uncertainty. We hope Gaussian-FCOS serves as a crucial component for the reliability-required task

Model-Free Reconstruction of Capacity Degradation Trajectory of Lithium-Ion Batteries Using Early Cycle Data

Early degradation prediction of lithium-ion batteries is crucial for ensuring safety and preventing unexpected failure in manufacturing and diagnostic processes. Long-term capacity trajectory predictions can fail due to cumulative errors and noise. To address this issue, this study proposes a data-centric method that uses early single-cycle data to predict the capacity degradation trajectory of lithium-ion cells. The method involves predicting a few knots at specific retention levels using a deep learning-based model and interpolating them to reconstruct the trajectory. Two approaches are used to identify the retention levels of two to four knots: uniformly dividing the retention up to the end of life and finding optimal locations using Bayesian optimization. The proposed model is validated with experimental data from 169 cells using five-fold cross-validation. The results show that mean absolute percentage errors in trajectory prediction are less than 1.60% for all cases of knots. By predicting only the cycle numbers of at least two knots based on early single-cycle charge and discharge data, the model can directly estimate the overall capacity degradation trajectory. Further experiments suggest using three-cycle input data to achieve robust and efficient predictions, even in the presence of noise. The method is then applied to predict various shapes of capacity degradation patterns using additional experimental data from 82 cells. The study demonstrates that collecting only the cycle information of a few knots during model training and a few early cycle data points for predictions is sufficient for predicting capacity degradation. This can help establish appropriate warranties or replacement cycles in battery manufacturing and diagnosis processes

The Mechanisms of Nuclear Proteotoxicity in Polyglutamine Spinocerebellar Ataxias

Polyglutamine (polyQ) spinocerebellar ataxias (SCAs) are the most prevalent subset of SCAs and share the aberrant expansion of Q-encoding CAG repeats within the coding sequences of disease-responsible genes as their common genetic cause. These polyQ SCAs (SCA1, SCA2, SCA3, SCA6, SCA7, and SCA17) are inherited neurodegenerative diseases characterized by the progressive atrophy of the cerebellum and connected regions of the nervous system, which leads to loss of fine muscle movement coordination. Upon the expansion of polyQ repeats, the mutated proteins typically accumulate disproportionately in the neuronal nucleus, where they sequester various target molecules, including transcription factors and other nuclear proteins. However, it is not yet clearly understood how CAG repeat expansion takes place or how expanded polyQ proteins accumulate in the nucleus. In this article, we review the current knowledge on the molecular and cellular bases of nuclear proteotoxicity of polyQ proteins in SCAs and present our perspectives on the remaining issues surrounding these diseases. © Copyright © 2020 Lee, Lee, Lee and Lee.1

Markedly enhanced intratumoral spread and antitumor effect of oncolytic adenovirus expressing decorin

With the aim of improving viral distribution and tumor penetration, we have engineered decorin expressing replication-incompetent (dl-LacZ-DCNG) and -competent (Ad-[DELTA]E1B-DCNG) adenoviruses. In both tumor spheroids and established solid tumors in vivo, administration of dl-LacZ-DCNG resulted in greater transduction efficiency and viral spread throughout the tumor mass. Ad-[DELTA]E1B-DCNG also enhanced viral distribution and tumor spread, leading to an increased anti-tumor effect and survival advantage. Upon histological analysis, Ad-[DELTA]E1B-DCNG also elicited greater percentage of apoptotic cells and extensive necrosis compared to those from untreated or control virus-treated tumors. Furthermore, Ad-[DELTA]E1B-DCNG substantially decreased extracellular matrix components within the tumor tissue, while normal tissue adjacent to the tumor was not affected. Finally, intratumoral administration of Ad-[DELTA]E1B-DCNG did not enhance but inhibited the formation of pulmonary metastases of B16BL6 melanoma cells in mice. Taken together, these data demonstrate the utility of decorin as a dispersion agent and suggest its utility and potential in improving the efficacy of replicating adenovirus-mediated cancer gene therapy