Antioxidative Hyaluronic Acid-Bilirubin Nanomedicine Targeting Activated Hepatic Stellate Cells for Anti-Hepatic-Fibrosis Therapy.

Liver fibrosis is a life-threatening and irreversible disease. The fibrosis process is largely driven by hepatic stellate cells (HSCs), which undergo transdifferentiation from an inactivated state to an activated one during persistent liver damage. This activated state is responsible for collagen deposition in liver tissue and is accompanied by increased CD44 expression on the surfaces of HSCs and amplified intracellular oxidative stress, which contributes to the fibrosis process. To address this problem, we have developed a strategy that combines CD44-targeting of activated HSCs with an antioxidative approach. We developed hyaluronic acid-bilirubin nanoparticles (HABNs), composed of endogenous bilirubin, an antioxidant and anti-inflammatory bile acid, and hyaluronic acid, an endogenous CD44-targeting glycosaminoglycan biopolymer. Our findings demonstrate that intravenously administered HABNs effectively targeted the liver, particularly activated HSCs, in fibrotic mice with choline-deficient l-amino acid-defined high-fat diet (CD-HFD)-induced nonalcoholic steatohepatitis (NASH). HABNs were able to inhibit HSC activation and proliferation and collagen production. Furthermore, in a murine CD-HFD-induced NASH fibrosis model, intravenously administered HABNs showed potent fibrotic modulation activity. Our study suggests that HABNs have the potential to serve as a targeted anti-hepatic-fibrosis therapy by modulating activated HSCs via CD44-targeting and antioxidant strategies. This strategy could also be applied to various ROS-related diseases in which CD44-overexpressing cells play a pivotal role.

Deep Learning-based Assessment of Facial Asymmetry Using U-Net Deep Convolutional Neural Network Algorithm.

OBJECTIVES: This study aimed to evaluate the diagnostic performance of a deep convolutional neural network (DCNN)-based computer-assisted diagnosis (CAD) system to detect facial asymmetry on posteroanterior (PA) cephalograms and compare the results of the DCNN with those made by the orthodontist. MATERIALS AND METHODS: PA cephalograms of 1020 patients with orthodontics were used to train the DCNN-based CAD systems for autoassessment of facial asymmetry, the degree of menton deviation, and the coordinates of its regarding landmarks. Twenty-five PA cephalograms were used to test the performance of the DCNN in analyzing facial asymmetry. The diagnostic performance of the DCNN-based CAD system was assessed using independent t -tests and Bland-Altman plots. RESULTS: Comparison between the DCNN-based CAD system and conventional analysis confirmed no significant differences. Bland-Altman plots showed good agreement for all the measurements. CONCLUSIONS: The DCNN-based CAD system might offer a clinically acceptable diagnostic evaluation of facial asymmetry on PA cephalograms.

Interrupting specific hydrogen bonds between ELF3 and MED23 as an alternative drug resistance-free strategy for HER2-overexpressing cancers.

INTRODUCTION: HER2 overexpression induces cancer aggression and frequent recurrences in many solid tumors. Because HER2 overproduction is generally followed by gene amplification, inhibition of protein-protein interaction (PPI) between transcriptional factor ELF3 and its coactivator MED23 has been considered an effective but challenging strategy. OBJECTIVES: This study aimed to determine the hotspot of ELF3-MED23 PPI and further specify the essential residues and their key interactions in the hotspot which are controllable by small molecules with significant anticancer activity. METHODS: Intensive biological evaluation methods including SEAP, fluorescence polarization, LC-MS/MS-based quantitative, biosensor, GST-pull down assays, and in silico structural analysis were performed to determine hotspot of ELF3-MED23 PPI and to elicit YK1, a novel small molecule PPI inhibitor. The effects of YK1 on possible PPIs of MED23 and the efficacy of trastuzumab were assessed using cell culture and tumor xenograft mouse models. RESULTS: ELF3-MED23 PPI was found to be specifically dependent on H-bondings between D400, H449 of MED23 and W138, I140 of ELF3 for upregulating HER2 gene transcription. Employing YK1, we confirmed that interruption on these H-bondings significantly attenuated the HER2-mediated oncogenic signaling cascades and exhibited significant in vitro and in vivo anticancer activity against HER2-overexpressing breast and gastric cancers even in their trastuzumab refractory clones. CONCLUSION: Our approach to develop specific ELF3-MED23 PPI inhibitor without interfering other PPIs of MED23 can finally lead to successful development of a drug resistance-free compound to interrogate HER2 biology in diverse conditions of cancers overexpressing HER2.

Morphological and chemical classification of fine particles over the Yellow Sea during spring, 2015-2018.

Airborne fine particles can affect climate change and human health; moreover, they can be transported over significant distances. However, studies on characteristics of individual particles and their morphology, elemental composition, aging processes, and spatial distribution after long-range transport over the Yellow Sea are limited. Therefore, in this study, we conducted shipborne measurements of fine particulate matter of less than 2.5 µm in diameter (PM2.5) over the Yellow Sea and classified the individual particles into seven types based on their morphology and composition. Overall, the percentage of organic-rich particles was the highest, followed by that of sea spray, sulfur-rich, dust, metals, fly ash, soot, and other particles. Near Shandong, China, the percentage of fly ash and sulfur-rich particles increased, while an increased percentage of only sulfur-rich particles was observed near the Korean Peninsula. In the open sea, the PM2.5 concentrations were the lowest, and sea spray particles predominated. During the cruises, three types (Types 1, 2, and 3) of events with substantially increased PM2.5 concentrations occurred, each with different dominant particles. Type 1 events frequently featured air masses from northern China and Mongolia with high wind speeds and increased dust particles. Type 2 events involved air masses from China with high wind speeds; fly ash, soot, organic-rich particles, and the sulfate percentage in PM2.5 increased. Type 3 events displayed stagnant conditions and local transport (from Korea); soot, dust particles, and the secondary sulfate and nitrate percentages in PM2.5 increased. Thus, different types of transport affected concentrations and dominant types of fine particles over the Yellow Sea during spring.

Identification of new halogen-containing 2,4-diphenyl indenopyridin-5-one derivative as a boosting agent for the anticancer responses of clinically available topoisomerase inhibitors.

Based on previous reports on the significance of halogen moieties and the indenopyridin-5-one skeleton, we designed and synthesized a novel series of halogen (F-, Cl-, Br-, CF3- and OCF3-)-containing 2,4-diphenyl indenopyridin-5-ones and their corresponding -5-ols. Unlike indenopyridin-5-ols, most of the prepared indenopyridin-5-ones with Cl-, Br-, and CF3- groups at the 2-phenyl ring conferred a strong dual topoisomerase I/IIα inhibitory effect. Among the series, para-bromophenyl substituted compound 9 exhibited the most potent topoisomerase inhibition and antiproliferative effects, which showed dependency upon the topoisomerase gene expression level of diverse cancer cells. In particular, as a DNA minor groove-binding non-intercalative topoisomerase I/IIα catalytic inhibitor, compound 9 synergistically promoted the anticancer efficacy of clinically applied topoisomerase I/IIα poisons both in vitro and in vivo, having the great advantage of alleviating poison-related toxicities.

Automated Detection of Rice Bakanae Disease via Drone Imagery.

This paper proposes a system for the forecasting and automated inspection of rice Bakanae disease (RBD) infection rates via drone imagery. The proposed system synthesizes camera calibrations and area calculations in the optimal data domain to detect infected bunches and classify infected rice culm numbers. Optimal heights and angles for identification were examined via linear discriminant analysis and gradient magnitude by targeting the morphological features of RBD in drone imagery. Camera calibration and area calculation enabled distortion correction and simultaneous calculation of image area using a perspective transform matrix. For infection detection, a two-step configuration was used to recognize the infected culms through deep learning classifiers. The YOLOv3 and RestNETV2 101 models were used for detection of infected bunches and classification of the infected culm numbers, respectively. Accordingly, 3 m drone height and 0° angle to the ground were found to be optimal, yielding an infected bunches detection rate with a mean average precision of 90.49. The classification of number of infected culms in the infected bunch matched with an 80.36% accuracy. The RBD detection system that we propose can be used to minimize confusion and inefficiency during rice field inspection.

Reactive microglia and astrocytes in neonatal intraventricular hemorrhage model are blocked by mesenchymal stem cells.

Severe intraventricular hemorrhage (IVH) in premature infants triggers reactive gliosis, causing acute neuronal death and glial scar formation. Transplantation of mesenchymal stem cells (MSCs) has often showed improved CNS recovery in an IVH model, but whether this response is related to reactive glial cells is still unclear. Herein, we suggest that MSCs impede the response of reactive microglia rather than astrocytes, thereby blocking neuronal damage. Astrocytes alone showed mild reactiveness under hemorrhagic conditions mimicked by thrombin treatment, and this was not blocked by MSC-conditioned medium (MSC-CM) in vitro. In contrast, thrombin-induced microglial activation and release of proinflammatory cytokines were inhibited by MSC-CM. Interestingly, astrocytes showed greater reactive response when co-cultured with microglia, and this was abolished in the presence of MSC-CM. Gene expression profiles in microglia revealed that transcript levels of genes for immune response and proinflammatory cytokines were altered by thrombin treatment. This result coincided with the robust phosphorylation of STAT1 and p38 MAPK, which might be responsible for the production and release of proinflammatory cytokines. Furthermore, application of MSC-CM diminished thrombin-mediated phosphorylation of STAT1 and p38 MAPK, supporting the acute anti-inflammatory role of MSCs under hemorrhagic conditions. In line with this, activation of microglia and consequent cytokine release were impaired in Stat1-null mice. However, reactive response in Stat1-deficient astrocytes was maintained. Taken together, our results demonstrate that MSCs mainly block the activation of microglia involving STAT1-mediated cytokine release and subsequent reduction of reactive astrocytes.

Precise Modeling of the Protective Effects of Quercetin against Mycotoxin via System Identification with Neural Networks.

Cell cytotoxicity assays, such as cell viability and lactate dehydrogenase (LDH) activity assays, play an important role in toxicological studies of pharmaceutical compounds. However, precise modeling for cytotoxicity studies is essential for successful drug discovery. The aim of our study was to develop a computational modeling that is capable of performing precise prediction, processing, and data representation of cell cytotoxicity. For this, we investigated protective effect of quercetin against various mycotoxins (MTXs), including citrinin (CTN), patulin (PAT), and zearalenol (ZEAR) in four different human cancer cell lines (HeLa, PC-3, Hep G2, and SK-N-MC) in vitro. In addition, the protective effect of quercetin (QCT) against various MTXs was verified via modeling of their nonlinear protective functions using artificial neural networks. The protective model of QCT is built precisely via learning of sparsely measured experimental data by the artificial neural networks (ANNs). The neuromodel revealed that QCT pretreatment at doses of 7.5 to 20 µg/mL significantly attenuated MTX-induced alteration of the cell viability and the LDH activity on HeLa, PC-3, Hep G2, and SK-N-MC cell lines. It has shown that the neuromodel can be used to predict the protective effect of QCT against MTX-induced cytotoxicity for the measurement of percentage (%) of inhibition, cell viability, and LDH activity of MTXs.