Search

Cancer, caused by abnormal and excessive cellular proliferation, can invade and destroy surrounding tissues and organs through the spreading of cancer cells. A general strategy for developing anticancer agents is to identify biomarkers that, if targeted, can produce a robust cytotoxic effect with minimal side effects. Cell-cycle regulators, checkpoint regulatory genes, and apoptosis-related genes are well-known biomarkers that inhibit cancer cell proliferation. Several compounds that target such biomarkers have been patented and more are being developed as novel therapies. Recent additions to this list include anticancer drugs that target signaling pathway proteins, such as 5′ adenosine monophosphate-activated protein kinase (AMPK), which plays a vital role in cancer and normal cell metabolism. Herein, we have reviewed recent patents related to AMPK-targeting anticancer drugs and discussed the mechanisms of action of these drugs. We conclude that these recently published patents include several attractive compounds and methods for targeting AMPK. Further research and clinical trials are required to elucidate the comprehensive role of AMPK in cancer cell metabolism, identify its associated signal transduction systems, and develop novel activators that may find applications in cancer therapy. Clinical Trial Registration number: NCT01904123. [ABSTRACT FROM AUTHOR]

After fecal microbiota transplantation (FMT) to treat Clostridioides difficile infection (CDI), cognitive improvement is noticeable, suggesting an essential association between the gut microbiome and neural function. Although it is known that the gut microbiome is linked with cognitive function, whether FMT may lead to cognitive improvement in patients with neurodegenerative disorders remains to be elucidated. We present the case of a 90-year-old woman with Alzheimer's dementia and severe CDI who underwent FMT. Cognitive function testing (Mini-Mental State Examination, Montreal Cognitive Assessment, and Clinical Dementia Rating assessment) was performed one month before FMT and one week and one month after FMT. We collected the patients' fecal samples before FMT and 3 weeks after FMT to compare the microbiota composition. The 16S rRNA gene amplicons were analyzed using the QIIME2 platform (version 2020.2) and the Phyloseq R package. The linear discriminant analysis effect size was performed to determine the taxonomic difference between pre- and post-FMT. Functional biomarker analysis using the Kruskal–Wallis H test was performed between the pre- and post-FMT. The cognitive function tests after FMT showed an improvement compared to the tests before the procedure. FMT changed the microbiota composition in recipient feces. We found that the genera were reported to be associated with cognitive function. In addition, short-chain fatty acids were found to be significantly different between before and after FMT. This finding suggests the presence of an association between the gut microbiome and cognitive function. Further, it emphasizes the need for clinical awareness regarding the effect of FMT on the brain-gut-microbiome axis and its potential as a therapy for patients with dementia. [ABSTRACT FROM AUTHOR]

In addition, it is difficult to manage the behavior of acute stroke patients with COVID-19 after stroke symptoms occur. We need to note that COVID-19 can appear as a local neurological defect, and the diagnosis and treatment methods for stroke patients caused by COVID-19 need to be re-evaluated. Although the occurrence of stroke due to microvascular thrombosis is becoming more evident, recent studies have shown that a significant number of COVID-19 patients develop large vascular occlusions with severe stroke symptoms [[3]]. [Extracted from the article]

(1) Background: Respiratory virus infections, including Coronavirus disease 2019 (COVID-19), seasonal influenza (FLU), and respiratory syncytial virus (RSV) as prominent examples, can severely affect both children and adults. This study aimed to investigate the clinical characteristics of respiratory viral infections in pediatric and adult populations and to identify determinants influencing patient hospitalization. (2) Methods: This retrospective study analyzed the electronic medical records of patients admitted to a regional hospital's emergency department from 1 January 2015 to 31 December 2022, to investigate the clinical characteristics and hospitalization risk factors associated with these three viruses. (3) Results: Infants aged 1 to 11 months were most affected by COVID-19 and RSV, whereas FLU more commonly infected children aged 3 to 5 years. Key factors influencing hospitalization included age and abnormal chest X-ray findings, with higher risks observed in younger children and adults over 65. Notably, the presence of abnormal chest x-ray findings significantly increased the hospitalization risk by 1.9 times [1.5–2.4] in children and 21.4 times [2.4–189.0] in adults. (4) Conclusions: This analysis underscores the impact of COVID-19, FLU, and RSV on hospitalization risk, offering insights for managing these respiratory viral infections (RVIs). Age-related risk differences highlight the necessity for tailored strategies, improving understanding of and treatment development for RVIs. [ABSTRACT FROM AUTHOR]

Diverse cases regarding the impact, with its related factors, of the COVID-19 pandemic on mental health have been reported in previous studies. In this study, multivariable datasets were collected from 751 college students who could be easily affected by pandemics based on the complex relationships between various mental health factors. We utilized quantum annealing (QA)-based feature selection algorithms that were executed by commercial D-Wave quantum computers to determine the changes in the relative importance of the associated factors before and after the pandemic. Multivariable linear regression (MLR) and XGBoost models were also applied to validate the QA-based algorithms. Based on the experimental results, we confirm that QA-based algorithms have comparable capabilities in factor analysis research to the MLR models that have been widely used in previous studies. Furthermore, the performance of the QA-based algorithms was validated through the important factor results from the algorithms. Pandemic-related factors (e.g., confidence in the social system) and psychological factors (e.g. decision-making in uncertain situations) were more important in post-pandemic conditions. Although the results should be validated using other mental health variables or national datasets, this study will serve as a reference for researchers regarding the use of the quantum annealing approach in factor analysis with validation through real-world survey dataset analysis. [ABSTRACT FROM AUTHOR]

Diverse cases regarding the impact, with its related factors, of the COVID-19 pandemic on mental health have been reported in previous studies. In this study, multivariable datasets were collected from 751 college students who could be easily affected by pandemics based on the complex relationships between various mental health factors. We utilized quantum annealing (QA)-based feature selection algorithms that were executed by commercial D-Wave quantum computers to determine the changes in the relative importance of the associated factors before and after the pandemic. Multivariable linear regression (MLR) and XGBoost models were also applied to validate the QA-based algorithms. Based on the experimental results, we confirm that QA-based algorithms have comparable capabilities in factor analysis research to the MLR models that have been widely used in previous studies. Furthermore, the performance of the QA-based algorithms was validated through the important factor results from the algorithms. Pandemic-related factors (e.g., confidence in the social system) and psychological factors (e.g. decision-making in uncertain situations) were more important in post-pandemic conditions. Although the results should be validated using other mental health variables or national datasets, this study will serve as a reference for researchers regarding the use of the quantum annealing approach in factor analysis with validation through real-world survey dataset analysis. [ABSTRACT FROM AUTHOR]

Doxorubicin (DOX), an anthracycline-based chemotherapeutic agent, is widely used to treat various types of cancer; however, prolonged treatment induces cardiomyotoxicity. Although studies have been performed to overcome DOX-induced cardiotoxicity (DICT), no effective method is currently available. This study investigated the effects and potential mechanisms of Poncirus trifoliata aqueous extract (PTA) in DICT. Changes in cell survival were assessed in H9c2 rat cardiomyocytes and MDA-MB-231 human breast cancer cells. The C57BL/6 mice were treated with DOX to induce DICT in vivo, and alterations in electrophysiological characteristics, serum biomarkers, and histological features were examined. The PTA treatment inhibited DOX-induced decrease in H9c2 cell viability but did not affect the MDA-MB-231 cell viability. Additionally, the PTA restored the abnormal heart rate, R-R interval, QT interval, and ST segment and inhibited the decrease in serum cardiac and hepatic toxicity indicators in the DICT model. Moreover, the PTA administration protected against myocardial fibrosis and apoptosis in the heart tissue of mice with DICT. PTA treatment restored DOX-induced decrease in the expression of NAD(P)H dehydrogenase quinone acceptor oxidoreductase 1 in a PTA concentration-dependent manner. In conclusion, the PTA inhibitory effect on DICT is attributable to its antioxidant properties, suggesting the potential of PTA as a phytotherapeutic agent for DICT. [ABSTRACT FROM AUTHOR]

Onions are rich in bioactive compounds and have been found to prevent various chronic diseases, including obesity. We performed a systematic review and meta‐analysis to investigate the antiobesity effect of onions. Studies were identified in PubMed/MEDLINE, Embase, Web of Science, and CENTRAL focusing on clinical trials evaluating the antiobesity effects of onion in obese subjects. The risk of bias in the studies was evaluated using Cochrane's Risk of Bias tool. The effect of onions was analyzed using data from the selected studies, and the results were indicated by weighted mean difference with 95% CI. The I2 static test was used to examine heterogeneity between the studies. A total of 38 studies were reviewed, of which five clinical trials meeting the criteria were selected. As investigational products, onion peels were used in four studies and onions were used in one study. Following systematic review, it was determined that the risk of bias was generally low, and body weight, BMI, waist circumference, and triglyceride levels were significantly reduced in the onion groups compared to the placebo. In conclusion, onion intake had an antiobesity effect by reducing body weight and body fat, and this effect was particularly pronounced with onion peel. [ABSTRACT FROM AUTHOR]

Background: Micronutrient (MN) supplementation has a positive impact on clinical outcomes. However, the evidence for the impact of MN supplementation remains controversial. Therefore, our study aims to assess the impact on nutritional outcomes according to exploring the implementation of MN support with multidisciplinary collaboration. Methods: This retrospective cohort study was conducted at a university hospital in Incheon, Korea. All patients referred to a nutrition support team (NST) between July and November 2022 were included. The NST reviews the MN protocol, which includes multivitamins and trace elements, based on international nutrient guidelines. All patients who were on nothing per oral and did not meet ≥70% of their nutritional requirements within 1 week were recommended MN supplements. Compliance with the MN protocol was evaluated, alterations in nutritional status based on the Nutrition Risk Screening 2002 (NRS 2002) scoring system and clinical outcomes were assessed after 7 day and at discharge. Multiple logistic regression analysis was used to identify factors associated with high nutritional risk in discharged patients. In addition, a sub-analysis was performed on changes in the nutritional of patients on the ward and in the ICU. Results: A total of 255 patients were eligible for analysis, with many patients requiring an MN supply of nothing per oral. The rate of implementation of MN supplementation was 50.2%. The findings indicate a significant decrease in the NRS 2002 score in the good compliance group with MN supplementation. No significant differences in protocol compliance were observed in terms of mortality, hospital stay, or length of stay in the intensive care unit. However, bad compliance with MN supplementation was correlated with risk factors for malnutrition at discharge. In subgroup analysis, nutritional status in the ICU and wards improved, with a significant difference between the two groups. Conclusions: The implementation of a MN supplementation protocol by a multidisciplinary NST is a feasible approach for improving the nutritional status of inpatients. Ensuring high compliance with this protocol is crucial, as poor compliance has been identified as a risk factor for malnutrition at discharge. Active intervention by the NST is essential to achieve optimal nutritional outcomes. [ABSTRACT FROM AUTHOR]

Introduction: Diesel particulate matter (DPM) emitted from diesel engines is a major source of air pollutants. DPM is composed of elemental carbon, which adsorbs organic compounds including toxic polycyclic aromatic hydrocarbons (PAHs). The skin, as well as airways, is directly exposed to DPM, and association of atopic dermatitis, psoriasis flares, and premature skin aging with air pollutant levels has been documented. In skin, the permeation of DPM and DPM-adsorbed compounds is primarily blocked by the epidermal permeability barrier deployed in the stratum corneum. Depending upon the integrity of this barrier, certain amounts of DPM and DPM-adsorbed compounds can permeate into the skin. However, this permeation into human skin has not been completely elucidated. Methods: We assessed the permeation of PAHs (adsorbed to DPM) into skin using ex vivo normal (barrier-competent) organ-cultured human skin after application of DPM. Two major PAHs, 2-methylnaphthalene and triphenylene, and a carcinogenic PAH, benzo(a)pyrene, all found in DPM, were measured in the epidermis and dermis using liquid chromatography electrospray ionization tandem mass spectrometry. In addition, we investigated whether a topical formulation can attenuate the permeation of DPM into skin. Results: 2-Methylnaphthalene, triphenylene, and benzo(a)pyrene were recovered from the epidermis. Although these PAHs were also detected in the dermis after DPM application, these PAH levels were significantly lower than those found in the epidermis. We also demonstrated that a topical formulation that has the ability to form more uniform membrane structures can significantly suppress the permeation of PAHs adsorbed to DPM into the skin. Conclusion: Toxic compounds adsorbed by DPM can permeate even barrier-competent skin. Hence, barrier-compromised skin, such as in atopic dermatitis, psoriasis, and xerosis, is even more vulnerable to air pollutants. A properly formulated topical mixture that forms certain membrane structures on the skin surface can effectively prevent permeation of exogenous substances, including DPM, into skin. [ABSTRACT FROM AUTHOR]

In greenhouses, plant growth is directly influenced by internal environmental conditions, and therefore requires continuous management and proper environmental control. Inadequate environmental conditions make plants vulnerable to pests and diseases, lower yields, and cause impaired growth and development. Previous studies have explored the combination of greenhouse actuator control history with internal and external environmental data to enhance prediction accuracy, using deep learning-based models such as RNNs and LSTMs. In recent years, transformer-based models and RNN-based models have shown good performance in various domains. However, their applications for time-series forecasting in a greenhouse environment remain unexplored. Therefore, the objective of this study was to evaluate the prediction performance of temperature, relative humidity (RH), and CO2 concentration in a greenhouse after 1 and 3 h, using a transformer-based model (Autoformer), variants of two RNN models (LSTM and SegRNN), and a simple linear model (DLinear). The performance of these four models was compared to assess whether the latest state-of-the-art (SOTA) models, Autoformer and SegRNN, are as effective as DLinear and LSTM in predicting greenhouse environments. The analysis was based on four external climate data samples, three internal data samples, and six actuator data samples. Overall, DLinear and SegRNN consistently outperformed Autoformer and LSTM. Both DLinear and SegRNN performed well in general, but were not as strong in predicting CO2 concentration. SegRNN outperformed DLinear in CO2 predictions, while showing similar performance in temperature and RH prediction. The results of this study do not provide a definitive conclusion that transformer-based models, such as Autoformer, are inferior to linear-based models like DLinear or certain RNN-based models like SegRNN in predicting time series for greenhouse environments. [ABSTRACT FROM AUTHOR]

Diabetes is characterized by persistently high blood glucose levels and severe complications and affects millions of people worldwide. In this study, we explored the epigenetic landscape of diabetes using data from the Korean Genome and Epidemiology Study (KoGES), specifically the Ansung–Ansan (AS–AS) cohort. Using epigenome-wide association studies, we investigated DNA methylation patterns in patients with type 2 diabetes mellitus (T2DM) and those with normal glucose regulation. Differential methylation analysis revealed 106 differentially methylated probes (DMPs), with the 10 top DMPs prominently associated with TXNIP, PDK4, NBPF20, ARRDC4, UFM1, PFKFB2, C7orf50, and ABCG1, indicating significant changes in methylation. Correlation analysis highlighted the association between the leading DMPs (e.g., cg19693031 and cg26974062 for TXNIP and cg26823705 for NBPF20) and key glycemic markers (fasting plasma glucose and hemoglobin A1c), confirming their relevance in T2DM. Moreover, we identified 62 significantly differentially methylated regions (DMRs) spanning 61 genes. A DMR associated with PDE1C showed hypermethylation, whereas DMRs associated with DIP2C, FLJ90757, PRSS50, and TDRD9 showed hypomethylation. PDE1C and TDRD9 showed a strong positive correlation between the CpG sites included in each DMR, which have previously been implicated in T2DM-related processes. This study contributes to the understanding of epigenetic modifications in T2DM. These valuable insights can be utilized in identifying potential biomarkers and therapeutic targets for effective management and prevention of diabetes. [ABSTRACT FROM AUTHOR]

Background: Optimal antithrombotic regimens to prevent recurrent stroke in patients with ischemic stroke due to atrial fibrillation (AF) and atherosclerotic large-vessel stenosis remain unknown. Aims: This study aimed to evaluate the effect of multiple antithrombotic therapies on outcomes at 1 year after ischemic stroke due to two or more causes. Methods: We identified 862 patients with ischemic stroke due to AF and large artery atherosclerosis from the linked data. These patients were categorized into three groups according to antithrombotic therapies at discharge: (1) antiplatelets, (2) oral anticoagulants (OAC), and (3) antiplatelets plus OAC. The study outcomes were recurrent ischemic stroke, composite outcomes for cardiovascular events, and major bleeding after 1 year. Inverse probability of treatment weighting (IPTW) was used to balance the three groups using propensity scores. Results: Among 862 patients, 169 (19.6%) were treated with antiplatelets, 405 (47.0%) were treated with OAC, and 288 (33.4%) were treated with antiplatelets and OAC. After applying IPTW, only OAC had a significant beneficial effect on the 1-year composite outcome (hazard ratio (HR): 0.37, 95% confidence interval (CI): 0.23–0.60, p < 0.001) and death (HR: 0.35, 95% CI: (0.19–0.63), p < 0.001). The combination of antiplatelet agents and OAC group had an increased risk of major bleeding complications (HR: 5.27, 95% CI: (1.31–21.16), p = 0.019). However, there was no significant difference in 1-year recurrent stroke events among the three groups. Conclusion: This study demonstrated that OAC monotherapy was associated with lower risks of composite outcome and death in patients at 1 year after ischemic stroke due to AF and atherosclerotic stenosis. In addition, the combination of an antiplatelet and OAC had a high risk of major bleeding. [ABSTRACT FROM AUTHOR]

Introduction: The outermost layer of the skin, the epidermis, is directly exposed to external stress (e.g., irradiation, allergens, and chemicals). Changes in epidermal conditions/environment in response to this stress could also influence conditions of the dermis, located directly beneath the epidermis. Yet, whether/how any epidermal environment changes in response to external stress affect dermal functions has not been completely clarified. Methods: We employed ultraviolet irradiation B (UVB) (which hardly reaches the dermis) as a model of external stress. Human keratinocytes and human dermal fibroblasts were treated with UVB and conditioned medium of keratinocytes exposed to UVB (UVB-keratinocyte-M), respectively. We assessed (1) inflammatory cytokines and lipid mediators in keratinocytes; (2) matrix metalloprotease (MMP) levels and collagen degradation in fibroblasts; (3) ex vivo organ-cultured human skin was treated with UVB. MMP levels and collagen degradation were examined; (4) test whether the mixture of agent (agent cocktail) consisting of dihydroceramide, niacin amide, resveratrol, glucosyl hesperidin, and phytosterol ester that has been shown to improve skin barrier integrity can mitigate influence of UVB in skin; and (5) a pilot one-arm human clinical test to assess efficacy of formulation containing agent cocktail on stratum corneum hydration, skin elasticity, and wrinkle index. Results: Inflammatory-cytokine and -lipid mediator production were increased in cultured keratinocytes treated with UVB, while matrix MMP-1, -3, and -9 production and collagen degradation were increased in fibroblasts incubated with UVB-keratinocyte-M. mRNA expression of COL1A1 (that codes type 1 collagen) levels was decreased in fibroblasts incubated with UVB-keratinocyte-M. The study using ex vivo organ-cultured human skin showed both MMP-1 and MMP-9 expression were increased in both epidermis and dermis and increased dermal collagen degradation following UVB irradiation. Increased MMP production and collagen degradation were attenuated by application of an agent cocktail. Finally, a pilot clinical study demonstrated that the formulation containing our agent cocktail likely has the ability to improve skin hydration, increase skin elasticity, and reduce the appearance of wrinkles. Conclusion: Epidermal changes in epidermal environment and conditions in response to external stress affect dermal conditions, and these negative effects of external stress on various skin layers can be pharmacologically mitigated. [ABSTRACT FROM AUTHOR]

The greenhouse industry achieves stable agricultural production worldwide. Various information and communication technology techniques to model and control the environment have been applied as data from environmental sensors and actuators in greenhouses are monitored in real time. The current study designed data-based, deep learning models for evapotranspiration (ET) and humidity in tomato greenhouses. Using time-series data and applying long short-term memory (LSTM) modeling, an ET prediction model was developed and validated in comparison with the Stanghellini model. Training with 20-day and testing with 3-day data resulted in RMSEs of 0.00317 and 0.00356 kgm−2 s−1, respectively. The standard error of prediction indicated errors of 5.76 and 6.45% in training and testing, respectively. Variables were used to produce a feature map using a two-dimensional convolution layer which was transferred to a subsequent layer and finally connected with the LSTM structure for modeling. The RMSE in humidity prediction using the test dataset was 2.87, indicating a performance better than conventional RNN-LSTM models. Irrigation plans and humidity control may be more accurately conducted in greenhouse cultivation using this model. [ABSTRACT FROM AUTHOR]

Background: On tomato plants, the flowering truss is a group or cluster of smaller stems where flowers and fruit develop, while the growing truss is the most extended part of the stem. Because the state of the growing truss reacts sensitively to the surrounding environment, it is essential to control its growth in the early stages. With the recent development of information and artificial intelligence technology in agriculture, a previous study developed a real-time acquisition and evaluation method for images using robots. Furthermore, we used image processing to locate the growing truss to extract growth information. Among the different vision algorithms, the CycleGAN algorithm was used to generate and transform unpaired images using generated learning images. In this study, we developed a robot-based system for simultaneously acquiring RGB and depth images of the growing truss of the tomato plant. Results: The segmentation performance for approximately 35 samples was compared via false negative (FN) and false positive (FP) indicators. For the depth camera image, we obtained FN and FP values of 17.55 ± 3.01% and 17.76 ± 3.55%, respectively. For the CycleGAN algorithm, we obtained FN and FP values of 19.24 ± 1.45% and 18.24 ± 1.54%, respectively. When segmentation was performed via image processing through depth image and CycleGAN, the mean intersection over union (mIoU) was 63.56 ± 8.44% and 69.25 ± 4.42%, respectively, indicating that the CycleGAN algorithm can identify the desired growing truss of the tomato plant with high precision. Conclusions: The on-site possibility of the image extraction technique using CycleGAN was confirmed when the image scanning robot drove in a straight line through a tomato greenhouse. In the future, the proposed approach is expected to be used in vision technology to scan tomato growth indicators in greenhouses using an unmanned robot platform. [ABSTRACT FROM AUTHOR]

• Interlighting affected the transpiration-yield correlation. • Defoliation levels showed conflicting yield–drain variations with seasonal changes. • Results suggest an agronomic background for optimizing the agronomic manipulations. Defoliation and inter-lighting affect yield and evapotranspiration. Practically, these agronomic manipulations are mainly performed on a seasonal basis. Evapotranspiration causes significant changes in the drainage volume and its electrical conductivity (EC) on a finer scale than on a seasonal basis, and these water management variables subsequently affect yield. However, the dynamic interactions between agronomic manipulations and water management variables are not well understood, despite these systematic relationships. In this study, seven tomato gutter lines consisting of three different treatment timeline schemes were designed: (1) continuous application of regular defoliation level during the experimental period, (2) intermediate transition from regular to additional defoliation level, and (3) time-varying (in the order of 12→5→2 h per day) inter-lighing. The time-series responses of evapotranspiration, drainage, drainage EC, and tomato yield were analyzed by normalization and principal component analysis (PCA). Normalized water management variables and yield showed sensitive responses to the application of time-variable inter-lighting and two different defoliations. Increasing yield trends in the regular defoliation lines were reversed after the initiation of additional defoliation gutter lines. The yield-promotion effect of inter-lighting was observed after the final time adjustment (2 h per day). Overall, these yield changes accompanied trend reversal in water management variables. PCA results summarized a perturbation effect on the yield-evapotranspiration correlations with increases in drainage volume-drainage EC covariance from the application of inter-lighting. The results indicate that defoliation and inter-lighting should be accompanied by a more flexible water management scheme. This study suggests an agronomic background for the technical optimization of defoliation and inter-lighting. [ABSTRACT FROM AUTHOR]

Tamarixetin (TX) is an O-methylated flavonoid naturally derived from quercetin. TX has bioactive properties; however, whether it shows antilipogenic activity remains unknown. Therefore, in the present study, we aimed to determine the antilipogenic effects of TX using 3T3-L1 adipocytes. The 3T3-L1 adipocytes were cultured in a differentiation medium with or without TX. Lipid accumulation was diminished and the mRNA expression of lipogenesis-related genes was decreased following TX treatment. We found that TX exhibited antilipogenic effects by inhibiting the expression of p300/CBP-associated factor (pCAF), a histone acetyltransferase, as confirmed by pCAF knockdown. Furthermore, TX inhibited both pCAF expression and its activity, thereby reducing the total acetylation level of nonhistone and histone proteins. Finally, TX decreased the expression of CCAAT/enhancer-binding protein alpha and beta (CEBPα and CEBPβ), and peroxisome proliferator-activated receptor γ along with pCAF expression during adipogenesis of 3T3-L1 cells in a time-dependent manner. Collectively, our findings suggest that TX is a potent antilipogenic agent derived from natural products and may be used as a pCAF inhibitor. [ABSTRACT FROM AUTHOR]

Zea mays L. (Poaceae), also known as purple corn, is an annual herbaceous plant that is grown as food for human consumption in a variety of forms, including cooking oils and sweeteners in processed food and beverage products. The purpose of this study was to determine whether a novel purple corn extract, FB801, might have an anti-atopic dermatitis (AD) effect on AD-like skin lesions induced by 2,4-dinitrochlorobenzene (DNCB) in BALB/c mice. Topical sensitization (1%) and challenge (0.3%) by DNCB were performed on the dorsal skin and right ear of BALB/c mice to induce AD. Following FB801 and dexamethasone administered orally, the severity of skin lesions was examined macroscopically and histologically. Serum levels of immunoglobulin E (IgE) and various cytokines were determined by enzyme-linked immunosorbent assay. Oral administration of FB801 significantly reduced typical symptoms of AD (erythema/bleeding, swelling, molting/erosion and scaling/drying), scratching frequencies, and the recruitment of inflammatory and mast cells. In addition, FB801 suppressed serum levels of IgE and T helper (Th)2 type cytokines such as interleukin (IL)-4 and IL-10 in DNCB-treated BALB/c mice. Furthermore, FB801 reduced the degradation of inhibitor of nuclear factor-κB proteins (NF-κB) in tumor necrosis factor (TNF)-α-stimulated human keratinocyte (HaCaT) cells. These results suggest that FB801 inhibited the development of the AD-like skin symptoms by regulating Th1 and Th2 responses in the skin lesions in mice and suppressing TNF-α induced NF-κB activation in HaCaT cells, suggesting that FB801 has potential application as an effective alternative therapy for the prevention and management of AD. [ABSTRACT FROM AUTHOR]

An amendment to this paper has been published and can be accessed via a link at the top of the paper. [ABSTRACT FROM AUTHOR]

Metformin increased cellular ROS levels in AsPC-1 pancreatic cancer cells, with minimal effect in HDF, human primary dermal fibroblasts. Metformin reduced cellular ATP levels in HDF, but not in AsPC-1 cells. Metformin increased AMPK, p-AMPK (Thr172), FOXO3a, p-FOXO3a (Ser413), and MnSOD levels in HDF, but not in AsPC-1 cells. p-AMPK and p-FOXO3a also translocated from the cytosol to the nucleus by metformin in HDF, but not in AsPC-1 cells. Transfection of si-FOXO3a in HDF increased ROS levels, while wt-FOXO3a-transfected AsPC-1 cells decreased ROS levels. Metformin combined with apigenin increased ROS levels dramatically and decreased cell viability in various cancer cells including AsPC-1 cells, with each drug used singly having a minimal effect. Metformin/apigenin combination synergistically decreased mitochondrial membrane potential in AsPC-1 cells but to a lesser extent in HDF cells. Metformin/apigenin combination in AsPC-1 cells increased DNA damage-, apoptosis-, autophagy- and necroptosis-related factors, but not in HDF cells. Oral administration with metformin/apigenin caused dramatic blocks tumor size in AsPC-1-xenografted nude mice. Our results suggest that metformin in cancer cells differentially regulates cellular ROS levels via AMPK-FOXO3a-MnSOD pathway and combination of metformin/apigenin exerts anticancer activity through DNA damage-induced apoptosis, autophagy and necroptosis by cancer cell-specific ROS amplification. [ABSTRACT FROM AUTHOR]

Cerebral small vessel disease is characterized by white matter hyperintensities (WMH) and acute small vessel occlusion (SVO) stroke. We investigated the effect of prior antiplatelet use (APU) on stroke outcome in 1151 patients with acute SVO stroke patients and moderate to severe WMH. Using a multicenter database, this retrospective study used quantitative WMH volume measurements and propensity score matching (PSM) for comparisons between patients with prior APU and without APU. Primary outcomes were stroke progression and poor functional outcome (modified Rankin Scale>2) at 3 months. Logistic regression analyses assessed associations between prior APU, WMH burden, and stroke outcomes. Stroke progression was lower in the prior APU group in both the total cohort (14.8% vs. 6.9%, p < 0.001) and the PSM cohort (16.3% vs. 6.9%, p < 0.001). The proportion of poor functional outcomes at 3 months was not significantly different in the total cohort, but the PSM cohort showed a lower proportion in the prior APU group (30.8% vs. 20.2%, p = 0.002). Logistic regression analysis confirmed that prior APU was associated with a reduced risk of stroke progression (OR, 0.39; 95% CI, 0.22–0.70; p = 0.001) and poor functional outcome at 3 months (OR, 0.37; 95% CI, 0.23–0.59; p < 0.001). Prior APU is associated with reduced stroke progression and improved functional outcome at 3 months in acute SVO stroke patients with moderate to severe WMH. Early treatment of WMH and acute SVO stroke may have potential benefits in improving stroke outcomes. • Early stroke progression and delayed poor functional status are less common in patients with acute SVO stroke with moderate to severe WMH who had received prior antiplatelet therapy. • Prior antiplatelet use is associated with reduced early stroke progression and poor functional status in acute SVO stroke with moderate to severe WMH. • Our study showed a differential effect of prior antiplatelet use on stroke outcomes in acute SVO stroke patients based on the severity of deep MWH and periventricular WMH. [ABSTRACT FROM AUTHOR]

The aim of this study is to evaluate the effects of patulin on hepatic lipid metabolism and mitochondrial oxidative function and elucidate the underlying molecular mechanisms. The effects of patulin on hepatic lipid accumulation were evaluated in free fatty acid-treated AML12 or HepG2 cells through oil red O staining, triglyceride assay, real-time polymerase chain reaction, and western blotting. Alteration of mitochondrial oxidative capacity by patulin treatment was determined using Seahorse analysis to measure the oxygen consumption rate. The increased amounts of lipid droplets induced by free fatty acids were significantly reduced by patulin treatment. Patulin markedly activated the CaMKII/AMP-activated protein kinase (AMPK)/proliferator-activated receptor-γ coactivator (PGC)-1α signaling pathway in hepatocytes, reduced the expression of sterol regulatory element binding protein 1c (SREBP-1c) and lipogenic genes, and increased the expression of genes related to mitochondrial fatty acid oxidation. In addition, patulin treatment enhanced the mitochondrial consumption rate and increased the expression of mitochondrial oxidative phosphorylation proteins in HepG2 hepatocytes. The effects of patulin on anti-lipid accumulation; SREBP-1c, PGC-1α, and carnitine palmitoyltransferase 1 expression; and mitochondrial oxidative capacity were significantly prevented by compound C, an AMPK inhibitor. Patulin is a potent inducer of the AMPK pathway, and AMPK-mediated mitochondrial activation is required for the efficacy of patulin to inhibit hepatic lipid accumulation. This study is the first to report that patulin is a promising bioactive compound that prevents the development and worsening of fatty liver diseases, including non-alcoholic fatty liver disease, by improving mitochondrial quality and lipid metabolism. [Display omitted] [ABSTRACT FROM AUTHOR]

• A smart farm robot accurately performs repeatable tasks in real time. • Automatically measure plant growth information with a deep learning-based approach. • Data augmentation based on fused RGB-D images contributes to precise measurement. • Solve problems in real-world high-plant-density environments. Traditionally, vegetable and fruit production has relied on empirical and ambiguous decisions made by human farmers. To overcome this uncertainty in agriculture, smart farm robots have been widely studied in recent years. However, measuring growth information with robots remains a challenge because of the similarity in the appearance of the target plant and those around it. In this study, we propose a smart farm robot that accurately measures the growth information of a target plant based on object detection, image fusion, and data augmentation with fused images. The proposed smart farm robot uses an end-to-end real-time deep learning-based object detector that shows state-of-the-art performances. To distinguish the target plant from other plants with a higher accuracy and improved robustness than those of existing methods, we exploited image fusion using both RGB and depth images. In particular, the data augmentation, based on the fused RGB, and depth information, contributes to the precise measurement of growth information from smart farms, regardless of the high density of vegetables and fruits in these farms. We propose and evaluate a real-time measurement system to obtain precise target-plant growth information in precision agriculture. The code and models are publicly available on Github: https://github.com/kistvision/Plant_growth_measurement. [ABSTRACT FROM AUTHOR]

Owing to the hasty growth of communication technologies in the Underwater Internet of Things (UIoT), many researchers and industries focus on enhancing the existing technologies of UIoT systems for developing numerous applications such as oceanography, diver networks monitoring, deep-sea exploration and early warning systems. In a constrained UIoT environment, communication media such as acoustic, infrared (IR), visible light, radiofrequency (RF) and magnet induction (MI) are generally used to transmit information via digitally linked underwater devices. However, each medium has its technical limitations: for example, the acoustic medium has challenges such as narrow-channel bandwidth, low data rate, high cost, etc., and optical medium has challenges such as high absorption, scattering, long-distance data transmission, etc. Moreover, the malicious node can steal the underwater data by employing blackhole attacks, routing attacks, Sybil attacks, etc. Furthermore, due to heavyweight, the existing privacy and security mechanism of the terrestrial internet of things (IoT) cannot be applied directly to UIoT environment. Hence, this paper aims to provide a systematic review of recent trends, applications, communication technologies, challenges, security threats and privacy issues of UIoT system. Additionally, this paper highlights the methods of preventing the technical challenges and security attacks of the UIoT environment. Finally, this systematic review contributes much to the profit of researchers to analyze and improve the performance of services in UIoT applications. [ABSTRACT FROM AUTHOR]