Cardioprotection via mitochondrial transplantation supports fatty acid metabolism in ischemia-reperfusion injured rat heart.

In addition to cellular damage, ischemia-reperfusion (IR) injury induces substantial damage to the mitochondria and endoplasmic reticulum. In this study, we sought to determine whether impaired mitochondrial function owing to IR could be restored by transplanting mitochondria into the heart under ex vivo IR states. Additionally, we aimed to provide preliminary results to inform therapeutic options for ischemic heart disease (IHD). Healthy mitochondria isolated from autologous gluteus maximus muscle were transplanted into the hearts of Sprague-Dawley rats damaged by IR using the Langendorff system, and the heart rate and oxygen consumption capacity of the mitochondria were measured to confirm whether heart function was restored. In addition, relative expression levels were measured to identify the genes related to IR injury. Mitochondrial oxygen consumption capacity was found to be lower in the IR group than in the group that underwent mitochondrial transplantation after IR injury (p < 0.05), and the control group showed a tendency toward increased oxygen consumption capacity compared with the IR group. Among the genes related to fatty acid metabolism, Cpt1b (p < 0.05) and Fads1 (p < 0.01) showed significant expression in the following order: IR group, IR + transplantation group, and control group. These results suggest that mitochondrial transplantation protects the heart from IR damage and may be feasible as a therapeutic option for IHD.

An In Silico Study for Expanding the Utility of Cannabidiol in Alzheimer's Disease Therapeutic Development.

Cannabidiol (CBD), a major non-psychoactive component of the cannabis plant, has shown therapeutic potential in Alzheimer's disease (AD). In this study, we identified potential CBD targets associated with AD using a drug-target binding affinity prediction model and generated CBD analogs using a genetic algorithm combined with a molecular docking system. As a result, we identified six targets associated with AD: Endothelial NOS (ENOS), Myeloperoxidase (MPO), Apolipoprotein E (APOE), Amyloid-beta precursor protein (APP), Disintegrin and metalloproteinase domain-containing protein 10 (ADAM10), and Presenilin-1 (PSEN1). Furthermore, we generated CBD analogs for each target that optimize for all desired drug-likeness properties and physicochemical property filters, resulting in improved pIC50 values and docking scores compared to CBD. Molecular dynamics (MD) simulations were applied to analyze each target's CBD and highest-scoring CBD analogs. The MD simulations revealed that the complexes of ENOS, MPO, and ADAM10 with CBD exhibited high conformational stability, and the APP and PSEN1 complexes with CBD analogs demonstrated even higher conformational stability and lower interaction energy compared to APP and PSEN1 complexes with CBD. These findings demonstrated the capable binding of the six identified targets with CBD and the enhanced binding stability achieved with the developed CBD analogs for each target.

Selected Phytochemicals and Culinary Plant Extracts Inhibit Fructose Uptake in Caco-2 Cells.

This study compared the ability of nine culinary plant extracts containing a wide array of phytochemicals to inhibit fructose uptake and then explored the involvement of intestinal fructose transporters and phytochemicals for selected samples. The chemical signature was characterized by high performance liquid chromatography with mass spectrometry. Inhibition of [(14)C]-fructose uptake was tested by using human intestinal Caco-2 cells. Then, the relative contribution of the two apical-facing intestinal fructose transporters, GLUT2 and GLUT5, and the signature components for fructose uptake inhibition was confirmed in naive, phloretin-treated and forskolin-treated Caco-2 cells. HPLC/MS analysis of the chemical signature revealed that guava leaf contained quercetin and catechin, and turmeric contained curcumin, bisdemethoxycurcumin and dimethoxycurcumin. Similar inhibition of fructose uptake (by ~50%) was observed with guava leaf and turmeric in Caco-2 cells, but with a higher contribution of GLUT2 for turmeric and that of GLUT5 for guava leaf. The data suggested that, in turmeric, demethoxycurcumin specifically contributed to GLUT2-mediated fructose uptake inhibition, and curcumin did the same to GLUT5-mediated fructose uptake inhibition, but GLUT2 inhibition was more potent. By contrast, in guava leaf, catechin specifically contributed to GLUT5-mediated fructose uptake inhibition, and quercetin affected both GLUT5- and GLUT2-mediated fructose uptake inhibition, resulting in the higher contribution of GLUT5. These results suggest that demethoxycurcumin is an important contributor to GLUT2-mediated fructose uptake inhibition for turmeric extract, and catechin is the same to GLUT5-mediated fructose uptake inhibition for guava leaf extract. Quercetin, curcumin and bisdemethoxycurcumin contributed to both GLUT5- and GLUT2-mediated fructose uptake inhibition, but the contribution to GLUT5 inhibition was higher than the contribution to GLUT2 inhibition.

Ascertaining injury risk issues through big data analysis: text-mining based analysis of national emergency response data.

Objectives: Injury prevention can be achieved through various interventions, but it faces challenges due to its comprehensive nature and susceptibility to external environmental factors, making it difficult to detect risk signals. Moreover, the reliance on standardized systems leads to the construction and statistical analysis of numerous injury surveillance data, resulting in significant temporal delays before being utilized in policy formulation. This study was conducted to quickly identify substantive injury risk problems by employing text mining analysis on national emergency response data, which have been underutilized so far. Methods: With emerging issue and topic analyses, commonly used in science and technology, we detected problematic situations and signs by deriving injury keywords and analyzing time-series changes. Results: In total, 65 injury keywords were identified, categorized into hazardous, noteworthy, and diffusion accidents. Semantic network analysis on hazardous accident terms refined the injury risk issues. Conclusion: An increased risk of winter epidemic fractures due to extreme weather, self-harm due to depression (especially drug overdose and self-mutilation), and falls was observed in older adults. Thus, establishing effective injury prevention strategies through inter-ministerial and interagency cooperation is necessary.

ALiGN: Attention based Line Guided Network for Vertebral Comprssion Fracture Detection.

Vertebral Compression Fracture (VCF) is one of the common fractures, especially for elderlies. As it affects postural deformation that may cause secondary disorders in the respiratory or digestive system if not treated in time, diagnosis of VCF is crucial. Using deep learning model based detection technology in diagnosis can reduce the workload of healthcare workers and misdiagnosis. Hence in this work, we propose ALiGN, a compression fracture detection model in the lumbar vertebra based on a deep convolutional neural network (CNN). Specifically, we take the location of each vertebral body into account via a feature pyramid network with an attention mechanism. Our proposed model outperforms the earlier works with a sensitivity 0.9729, specificity 0.9914, and mAP 0.7882.

Cu-Catalyzed Synthesis of 2-Silyl-1,3-butadienes from Allenols and Applications to One-Pot Synthesis of Tetrasubstituted Arylsilanes.

A copper-catalyzed chemo- and stereoselective method for the synthesis of (E)-2-silyl-1,3-butadienes from a broad range of allenols using mild Si-B reagents is reported in this study. Our protocol required a short reaction time at ambient temperature to produce the desired dienes in high yields. Synthetic applications are highlighted by the one-pot synthesis of tetrasubstituted arylsilanes from allenols as well as the further functionalization of C-Si bonds.

Neuroprotective effects of fermented tea in MPTP-induced Parkinson's disease mouse model via MAPK signaling-mediated regulation of inflammation and antioxidant activity.

Parkinson's disease (PD) is a neurodegenerative disorder that is characterized by dopaminergic neuronal damage. In this study, three tea extracts from Hadong, Korea, were evaluated in a 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP)-induced neurotoxicity damage model (C57BL/6 mice) for their therapeutic effects against PD: green tea (GT), semi-fermented tea (SFT), and fermented tea (FT). Theaflavin content in the teas increased but catechin content decreased with the degree of fermentation. In addition, SFT showed the highest theanine and γ-aminobutyric acid contents. SFT at a concentration of 25 µg/mL showed the highest activity in the 2,2-diphenyl-1-picrylhydrazyl radical scavenging assay among all samples. Furthermore, the 2,2'-azino-bis 3-ethylbenzothiazoline-6-sulfonic acid radical scavenging activity of 25 µg/mL SFT was higher than that of l-ascorbic acid. Fermented tea suppressed the expression of inflammatory cytokines, such as interleukin-6, tumor necrosis factor-alpha, inducible nitric oxide synthase, cyclooxygenase-2, and macrophage-1, as well as inhibited overexpression of apoptotic signals, including p-53, cleaved caspase-3, and poly (ADP-ribose) polymerase-1. Moreover, GT, SFT, and FT regulated the MPTP-induced oxidative stress-related factors, including superoxide dismutase, glutathione-S-transferase, and nicotinamide adenine dinucleotide phosphate oxidase 4. Fermented tea also alleviated MPTP-induced behavioral impairment and dopaminergic neuronal damage and reduced α-synuclein levels. These results indicate that fermented tea is effective for the treatment of neuro-inflammatory, neuro-apoptotic, and neuro-oxidative disorders.

L-Theanine alleviates MPTP-induced Parkinson's disease by targeting Wnt/ß-catenin signaling mediated by the MAPK signaling pathway.

We evaluated the neuroprotective effect of L-theanine in Parkinson's disease and the underlying mechanism focusing on WNT/ß-catenin signaling mediated by the MAPK pathway. We treated MPTP-induced SH-SY5Y cells with various concentrations of L-theanine (50, 100, 200, and 500 µg/mL), and we also treated Parkinson's model mice with L-theanine. L-theanine treatment effectively reduced the immunohistochemical hallmarks of Parkinson's disease, particularly Lewy bodies and α-synuclein, and increased the number of tyrosine hydroxylase-positive cells. L-theanine also improved the motor dysfunction in MPTP-induced Parkinson's disease model mice as measured by the rotarod test. The levels of several pro-inflammatory mediators that are overexpressed in Parkinson's disease, namely TNF-α, IL-6, COX-2, and MAC-1, were reduced following L-theanine treatment, and the levels of the pro-apoptotic proteins Bcl-2, caspase-3, p53, and PARP-1 were significantly reduced. L-theanine regulated the oxidative stress-related factors SOD-1, GST, and NOX-4 by targeting several proteins related to WNT/ß-catenin signaling, i.e., ß-catenin, WNT-3a, WNT-5a, TCF1/TCF7, and LEF1, via the MAPK pathway (p-JNK, p-ERK, and p-p38). Our results indicate that L-theanine is neuroprotective and has anti-inflammatory effects that could be beneficial for treating Parkinson's disease.

3D printing of mechanically tough and self-healing hydrogels with carbon nanotube fillers.

Hydrogels have the potential to play a crucial role in bioelectronics, as they share many properties with human tissues. However, to effectively bridge the gap between electronics and biological systems, hydrogels must possess multiple functionalities, including toughness, stretchability, self-healing ability, three-dimensional (3D) printability, and electrical conductivity. Fabricating such tough and self-healing materials has been reported, but it still remains a challenge to fulfill all of those features, and in particular, 3D printing of hydrogel is in the early stage of the research. In this paper, we present a 3D printable, tough, and self-healing multi-functional hydrogel in one platform made from a blend of poly(vinyl alcohol) (PVA), tannic acid (TA), and poly(acrylic acid) (PAA) hydrogel ink (PVA/TA/PAA hydrogel ink). Based on a reversible hydrogen-bond (H-bond)-based double network, the developed 3D printable hydrogel ink showed excellent printability via shear-thinning behavior, allowing high printing resolution (~100 µm) and successful fabrication of 3D-printed structure by layer-by-layer printing. Moreover, the PVA/TA/PAA hydrogel ink exhibited high toughness (tensile loading of up to ~45.6 kPa), stretchability (elongation of approximately 650%), tissue-like Young's modulus (~15 kPa), and self-healing ability within 5 min. Furthermore, carbon nanotube (CNT) fillers were successfully added to enhance the electrical conductivity of the hydrogel. We confirmed the practicality of the hydrogel inks for bioelectronics by demonstrating biocompatibility, tissue adhesiveness, and strain sensing ability through PVA/TA/PAA/CNT hydrogel ink.

Fabrication of nano patterns on various substrates using nanosphere lithography technique.

This paper presents a procedure for fabricating large-area, size-tunable, metal arrays with a periodically different shape using Nanosphere Lithography (NSL). This technique has attracted considerable interest because of its important applications as diffraction devices, chemical and optical data recording. Their ordered arrays can be used for anti-reflection surfaces, bio-sensors and nanopatterning masks. Two different types of patterns, honeycomb and hexagonal patterns, could be fabricated on various substrates with different procedures. All steps for making different patterns employed a PS (polystyrene) monolayer by spin coating. Honeycomb patterns were fabricated by spin coating a PS monolayer on a glass substrate and depositing a metal followed by removal of the monolayer, whereas the hexagonal pattern was produced by the transfer of a gold deposited monolayer onto a GaN substrate using the same process. These processes allow simple and excellent control of the size and shape of the patterns. All experimental results on structure characterization and determination of the nanoparticle metrics were accomplished by atomic force microscopy and field emission-scanning electronic microscopy.

Variety of nanopatterns on different substrates using PS-b-PMMA and their applications.

High density arrays of nanostructures over a large area can be formed on a range of substrates, such as glass, GaN, SiO2 deposited silicon wafer, etc. by the self-assembly of PS-b-PMMA block copolymers. The morphology of the polymer surface is strongly dependent on the thickness of the polymer layer. It is necessary to control the size and shape in order to get the desired properties. The deposition of a gold thin film on polymer-patterned glass followed by the removal of the remaining part of the polymer results in patterned gold on glass, which can be used as a transparent conducting electrode, where the conductivity and transparency depends on the thickness of gold and as well as on the connectivity of the gold pattern. Similarly, the polymer pattern can be transferred to an underlying GaN layer in an as grown LED, which increases the photoluminescence intensity making it useful as a photonic crystal.

Multi-View Integrative Attention-Based Deep Representation Learning for Irregular Clinical Time-Series Data.

Electronic health record (EHR) data are sparse and irregular as they are recorded at irregular time intervals, and different clinical variables are measured at each observation point. In this work, to handle irregular multivariate time-series data, we consider the human knowledge of the aspects to be measured and time to measure them in different situations, known as multi-view features, which are indirectly represented in the data. We propose a scheme to realize multi-view features integration learning via a self-attention mechanism. Specifically, we devise a novel multi-integration attention module (MIAM) to extract complex information that is inherent in irregular time-series data. We explicitly learn the relationships among the observed values, missing indicators, and time interval between the consecutive observations in a simultaneous manner. In addition, we build an attention-based decoder as a missing value imputer that helps empower the representation learning of the interrelations among multi-view observations for the prediction task this decoder operates only in the training phase so that the final model is implemented in an imputation-free manner. We validated the effectiveness of our method over the public MIMIC-III and PhysioNet challenge 2012 datasets by comparing with and outperforming the state-of-the-art methods in three downstream tasks i.e., prediction of the in-hospital mortality, prediction of the length of stay, and phenotyping. Moreover, we conduct a layer-wise relevance propagation (LRP) analysis based on case studies to highlight the explainability of the trained model.

Impact of Government Intervention in Response to Coronavirus Disease 2019.

Coronavirus disease 2019 (COVID-19) led to the loss of lives and had serious social and economic effects. Countries implemented various quarantine policies to reduce the effects. The countries were divided into low- and high-risk groups based on the differences in quarantine policies and their levels of infection. Quarantine policies that significantly contributed to risk reduction were determined by analyzing 11 quarantine indicators for reducing the spread of COVID-19. The cross-tabulation and Chi-square tests were used to compare the quarantine policies by the groups. Multivariate logistic regression was used to determine the useful quarantine policies implemented by the low-risk group to verify quarantine policies for minimizing the negative effects. The analysis showed that the low- and medium-risk groups showed significant differences for 9 of the 11 indicators, and 4 of these differentiated the low- from the medium-risk group. Countries with strict quarantine policies related to workplace closure and staying at home were more likely to be included in the low-risk group. These policies had a significant impact in the low-risk countries and could contribute to reducing the spread and effects of COVID-19 in countries included in the high-risk group.

Enhanced CO2 electroconversion of Rhodobacter sphaeroides by cobalt-phosphate complex assisted water oxidation.

CO2 can be a next generation feedstock for electricity-driven bioproduction due to its abundance and availability. Microbial electrosynthesis (MES), a promising technique for CO2 electroconversion, provides an attractive route for the production of valuable products from CO2, but issues surrounding efficiency and reasonable productivity should be resolved. Improving the anode performance for water oxidation under neutral pH is one of the most important aspects to advance current MES. Here, we introduce cobalt-phosphate (Co-Pi) assisted water oxidation at the counter electrode (i.e., anode) to upgrade the MES performance at pH 7.0. We show that CO2 can be converted by photochemoautotrophic bacterium, Rhodobacter sphaeroides into organic acids and carotenoids in the MES reactor. Planktonic cells of R. sphareroides in the Co-Pi anode equipped MES reactor was ca. 1.5-fold higher than in the control condition (w/o Co-Pi). The faradaic efficiency of the Co-Pi anode equipped MES reactor was remarkably higher (58.3%) than that of the bare anode (27.8%). While the system can improve the CO2 electroconversion nonetheless there are some further optimizations are necessary.

Immunomodulatory and anti-inflammatory efficacy of hederagenin-coated maghemite (γ-Fe2O3) nanoparticles in an atopic dermatitis model.

We investigated the immunomodulatory and anti-inflammatory efficacy of hederagenin coating on maghemite (γ-Fe2O3) nanoparticles (HM) in atopic dermatitis (AD), as well as the physical and optical properties of maghemite nanoparticles (MP) using SEM, XRD spectroscopy, UV-vis spectra, Raman spectra, and FTIR spectroscopy. Dose-dependent treatment with HM (10, 50, 100, 200 µg/mL) inhibited the expression of Interleukin-2 (IL-2) and Tumor necrosis factor- α (TNF-α) in inflammatory induced HaCaT and Jurkat cells with inflammation caused by TNF/IFN-γ and PMA/A23187. AD model was induced by performing topical application of 2,4-dinitrochlorobenzene (DNCB) and dermatophagoides farinae extract (DFE) for a 31-day period on 8-week-old BALB/c mice. The HM treatments efficiently diminished the AD-like cutaneous lesion induced by DNCB-DFE sensitization in mice. Compared to the AD-only groups, HM treatment considerably attenuated mast cell infiltration and lowered epidermal, and dermal thickness of mice ears skin. In addition, HM treatment prominently alleviated the enlarged size and weight of lymph nodes. Furthermore, HM treatment resulted in a notable reduction in the mRNA expression of Th1 cytokines (TNF-α and IFN-γ), Th2 cytokines (IL-4 and IL-6), Th17 (IL-17), and TSLP. Our data showed that HM provides better AD attenuation compared to MP. Additionally, HM had synergistic effect and act as anti-inflammatory and immunomodulatory agent. Thus, HM shows great potential in AD medication and as a substitution of non-steroid-based medication.

Prognostic Impact of Myosteatosis on Mortality in Hospitalized Patients with COVID-19.

Body composition, including sarcopenia, adipose tissue, and myosteatosis, is associated with unfavorable clinical outcomes in patients with coronavirus disease (COVID-19). However, few studies have identified the impact of body composition, including pre-existing risk factors, on COVID-19 mortality. Therefore, this study aimed to evaluate the effect of body composition, including pre-existing risk factors, on mortality in hospitalized patients with COVID-19. This two-center retrospective study included 127 hospitalized patients with COVID-19 who underwent unenhanced chest computed tomography (CT) between February and April 2020. Using the cross-sectional CT images at the L2 vertebra level, we analyzed the body composition, including skeletal muscle mass, visceral to subcutaneous adipose tissue ratio (VSR), and muscle density using the Hounsfield unit (HU). Of 127 patients with COVID-19, 16 (12.6%) died. Compared with survivors, non-survivors had low muscle density (41.9 vs. 32.2 HU, p < 0.001) and high proportion of myosteatosis (4.5 vs. 62.5%, p < 0.001). Cox regression analyses revealed diabetes (hazard ratio [HR], 3.587), myosteatosis (HR, 3.667), and a high fibrosis-4 index (HR, 1.213) as significant risk factors for mortality in patients with COVID-19. Myosteatosis was associated with mortality in hospitalized patients with COVID-19, independent of pre-existing prognostic factors.

Association of Skeletal Muscle and Adipose Tissue Distribution with Histologic Severity of Non-Alcoholic Fatty Liver.

Adipose tissue and skeletal muscle is associated with non-alcoholic fatty liver disease (NAFLD). This study evaluates the association between body composition and histologic severity in patients with NAFLD. Using the cross-sectional CT images at the level of L3 vertebra and the histologic findings of 178 patients with biopsy-proven NAFLD, we analyzed the correlation of the histologic findings to the skeletal muscle index (SMI), subcutaneous adipose tissue index (SATI), and visceral adipose tissue index (VATI), which is defined as the body composition area (cm2) by height squared (m2). The clinical and laboratory features with body composition were analyzed to determine the risk factors for advanced fibrosis. The VATI significantly increased in severe non-alcoholic steatohepatitis (NASH) or advanced fibrosis. In addition, the VATI was correlated with the NAFLD activity score (NAS) and the fibrosis stage. In multivariate analyses, age (odds ratio (OR), 1.09; 95% confidence interval (CI), 1.02-1.19; p = 0.025), severe NASH (OR, 8.66; 95% CI, 2.13-46.40; p = 0.005), and visceral adiposity (OR, 6.77; 95% CI, 1.81-29.90; p = 0.007) were independently associated with advanced fibrosis in patients with NAFLD. Visceral adiposity is correlated with the histologic severity of NAFLD, which is independently associated with advanced fibrosis.

Microvessel occlusions alter amyloid-beta plaque morphology in a mouse model of Alzheimer's disease.

Vascular dysfunction is correlated to the incidence and severity of Alzheimer's disease. In a mouse model of Alzheimer's disease (APP/PS1) using in vivo, time-lapse, multiphoton microscopy, we found that occlusions of the microvasculature alter amyloid-beta (Aß) plaques. We used several models of vascular injury that varied in severity. Femtosecond laser-induced occlusions in single capillaries generated a transient increase in small, cell-sized, Aß deposits visualized with methoxy-X04, a label of fibrillar Aß. After occlusions of penetrating arterioles, some plaques changed morphology, while others disappeared, and some new plaques appeared within a week after the lesion. Antibody labeling of Aß revealed a transient increase in non-fibrillar Aß one day after the occlusion that coincided with the disappearance of methoxy-X04-labeled plaques. Four days after the lesion, anti-Aß labeling decreased and only remained in patches unlabeled by methoxy-X04 near microglia. Histology in two additional models, sparse embolic occlusions from intracarotid injections of beads and infarction from photothrombosis, demonstrated increased labeling intensity in plaques after injury. These results suggest that microvascular lesions can alter the deposition and clearance of Aß and confirm that Aß plaques are dynamic structures, complicating the interpretation of plaque burden as a marker of Alzheimer's disease progression.

Antibacterial efficacy of phages against Pseudomonas aeruginosa infections in mice and Drosophila melanogaster.

Phage therapy against Pseudomonas aeruginosa infections has received renewed attention owing to the increasing prevalence of antibiotic resistance in this bacterium. Here, we isolated and characterized two new potentially lytic bacteriophages (MPK1 and MPK6), which produced large and clear plaques on P. aeruginosa strain PAO1. Based on their morphology, MPK1 belongs to the Myoviridae, while MPK6 belongs to the Podoviridae. The group B polysaccharide of lipopolysaccharide was required for infection, suggesting that their host spectra are associated with the serotypes of P. aeruginosa strains. Intramuscular and intraperitoneal administration of MPK1 and, to a lesser extent, MPK6 significantly protected mice from mortality caused by PAO1-induced peritonitis-sepsis (P < 0.01). Mice treated with either phage also had lower bacterial burdens in their livers, lungs, and spleens. The antibacterial efficacy of MPK1 and MPK6 was also evaluated based on Drosophila melanogaster systemic infection caused by P. aeruginosa, for which phages were administered by feeding. Both phages significantly delayed the PAO1-induced killing of D. melanogaster (P < 0.001), although MPK1 persisted longer than MPK6 in uninfected D. melanogaster tissue samples. These results suggest that a mini-scale experiment using D. melanogaster infection is valid for evaluating the antibacterial efficacy of phage therapy against P. aeruginosa infections.