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Rosa multiflora fructus and its active compound ellagic acid improve depressive-like behaviors in mice via monoamine oxidase inhibition

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Biomedicine and Pharmacotherapy 2025年 188卷 118169-118169页

作者： Kim, Minji Lim, Dong Wook Kim, Min-Sun Nam, Heejin Shin, Sooim Lee, Changho Um, Min Young Food Functionality Research Division Korea Food Research Institute Wanju 55365 South Korea Department of Food Biotechnology University of Science & Technology Daejeon 34113 South Korea Interdisciplinary Program of Bioenergy and Biomaterials Graduate School College of Engineering Chonnam National University Gwangju 61186 South Korea Department of Biotechnology & Bioengineering College of Engineering Chonnam National University Gwangju 61186 South Korea

Depression is a significant global health challenge, imposing severe social and economic burdens. Rosa multiflora fructus possesses a range of biological properties;however, its role in reducing stress hormone-induced depression remains unclear. This study examined the antidepressant effects of Rosa multiflora fructus extract (RMFE) on corticosterone (CORT)-induced depressive-like behaviors in mice and explored the underlying molecular mechanisms. ICR mice were administered CORT (40 mg/kg/day, i.p.) for 8 weeks to induce depressive-like behaviors. They were then treated with RMFE (100 or 300 mg/kg/day, p.o.) or selegiline (10 mg/kg/day, p.o.) as a positive control. RMFE treatment significantly alleviated depressive-like behaviors, as evaluated by the tail suspension and forced swimming tests. Furthermore, RMFE reduced hippocampal astrocyte hypertrophy and lowered the protein and mRNA expression of monoamine oxidase A and B (MAOA and MAOB). Phytochemical analysis using UPLC-MS/MS identified five flavonoids in RMFE, including ellagic acid (EA), hyperoside, isoquercetin, quercetin, and quercetin-3-glucuronide. In silico molecular docking revealed that these phenolic compounds interact with MAOA and MAOB, with EA exhibiting the strongest binding affinity. Consistently, EA administration effectively alleviated depressive-like behaviors and increased monoamine neurotransmitter levels in CORT-treated mice. These results suggest that RMFE exerts antidepressant effects by inhibiting MAO, restoring monoamine levels, and modulating hippocampal astrocytic hypertrophy, with EA identified as the primary bioactive compound driving its efficacy. © 2025

关键词： Corticosterone Depression Ellagic acid Monoamine oxidase Rosa multiflora fructus

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Transdermal nanolipoplex simultaneously inhibits subcutaneous melanoma growth and suppresses systemically metastatic melanoma by activating host immunity

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Nanomedicine: Nanotechnology, Biology, and Medicine 2023年 47卷 102628-102628页

作者： Chen, Chia-Hung Weng, Tzu-Han Chuang, Cheng-Hsun Huang, Kai-Yao Huang, Sih-Cheng Chen, Pin-Rong Huang, Hsiao-Hsuan Huang, Ling-Ya Shen, Pei-Chun Chuang, Po-Ya Huang, Hsiao-Yen Wu, Yi-Syuan Chang, Hao-Chiun Weng, Shun-Long Liao, Kuang-Wen Department of Medical Research Hsinchu MacKay Memorial Hospital Hsinchu City30071 Taiwan Dependent of Medical Education MacKay Memorial Hospital Taipei10449 Taiwan Institute of Molecular Medicine and Bioengineering National Yang Ming Chiao Tung University Hsinchu City30068 Taiwan Department of Biological Science and Technology National Yang Ming Chiao Tung University Hsinchu City30068 Taiwan Industrial Development Graduate Program of College of Biological Science and Technology National Yang Ming Chiao Tung University Hsinchu City30068 Taiwan Institute of Bioinformatics and Systems Biology National Yang Ming Chiao Tung University Hsinchu City30068 Taiwan Department of Medicine MacKay Medical College New Taipei City25245 Taiwan Department of Obstetrics and Gynecology Hsinchu MacKay Memorial Hospital Hsinchu City30071 Taiwan MacKay Junior College of Medicine Nursing and Management Taipei City11260 Taiwan Drug Development and Value Creation Research Center College of Dental Medicine Kaohsiung Medical University School of Dentistry Graduate Institute of Medicine College of Medicine Center for Cancer Research Kaohsiung Medical University Kaohsiung City80708 Taiwan Center for Intelligent Drug Systems and Smart Bio-devices National Yang Ming Chiao Tung University Hsinchu City30068 Taiwan Department of Biotechnology and Bioindustry Sciences National Cheng Kung University Tainan City70101 Taiwan Ph.D. Degree Program of Biomedical Science and Engineering National Yang Ming Chiao Tung University Hsinchu City30068 Taiwan

Benefit for clinical melanoma treatments, the transdermal neoadjuvant therapy could reduce surgery region and increase immunotherapy efficacy. Using lipoplex (Lipo-PEG-PEI-complex, LPPC) encapsulated doxorubicin (DOX) and carrying CpG oligodeoxynucleotide;the transdermally administered nano-liposomal drug complex (LPPC-DOX-CpG) would have high cytotoxicity and immunostimulatory activity to suppress systemic metastasis of melanoma. LPPC-DOX-CpG dramatically suppressed subcutaneous melanoma growth by inducing tumor cell apoptosis and recruiting immune cells into the tumor area. Animal studies further showed that the colonization and growth of spontaneously metastatic melanoma cells in the liver and lung were suppressed by transdermal LPPC-DOX-CpG. Furthermore, NGS analysis revealed IFN-γ and NF-κB pathways were triggered to recruit and activate the antigen-presenting-cells and effecter cells, which could activate the anti-tumor responses as the major mechanism responsible for the therapeutic effect of LPPC-DOX-CpG. Finally, we have successfully proved transdermal LPPC-DOX-CpG as a promising penetrative carrier to activate systemic anti-tumor immunity against subcutaneous and metastatic tumor. © 2022

关键词： Tumors

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Electrically driven programmable phase-change meta-switch reaching 80% efficiency

arXiv

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arXiv 2021年

作者： Abdollahramezani, Sajjad Hemmatyar, Omid Taghinejad, Mohammad Taghinejad, Hossein Krasnok, Alex Eftekhar, Ali A. Teichrib, Christian Deshmukh, Sanchit El-Sayed, Mostafa Pop, Eric Wuttig, Matthias Alù, Andrea Cai, Wenshan Adibi, Ali School of Electrical and Computer Engineering Georgia Institute of Technology 778 Atlantic Drive NW AtlantaGA30332-0250 United States Photonics Initiative Advanced Science Research Center City University of New York New YorkNY10031 United States Department of Electrical Engineering Precourt Institute for Energy Stanford University StanfordCA94305 United States Laser Dynamics Laboratory School of Chemistry and Biochemistry Georgia Institute of Technology AtlantaGA30332-0400 United States George W. Woodruff School of Mechanical Engineering Georgia Institute of Technology AtlantaGA30332-0405 United States Physikalisches Institut IA RWTH Aachen Sommerfeldstrasse 14 Aachen52074 Germany Physics Program Graduate Center City University of New York New YorkNY10016 United States School of Materials Science and Engineering Georgia Institute of Technology 801 Ferst Drive NW AtlantaGA30332-0295 United States

Despite recent advances in active metaoptics, efficient wide dynamic range combined with highspeed reconfigurable solutions is still elusive. Phase-change materials (PCMs) offer a compelling platform for metasurface optical elements, owing to the large index contrast and fast yet stable phase transition properties. Here, we experimentally demonstrate an in situ electrically driven reprogrammable metasurface by harnessing the unique properties of a phase-change chalcogenide alloy, Ge2Sb2Te5 (GST), in order to realize non-volatile, reversible, multilevel, fast, and pronounced optical modulation in the near-infrared spectral range. Co-optimized through a multiphysics analysis, we integrate an efficient heterostructure resistive microheater that indirectly heats and transforms the embedded GST film without compromising the optical performance of the metasurface even after several reversible phase transitions. A hybrid plasmonic-PCM meta-switch with a record eleven-fold change in the reectance (an absolute reectance contrast reaching 80%), unprecedented quasi-continuous spectral tuning over 250 nm, and operation speed that can potentially reach a few kHz is presented. Our work represents a significant step towards the development of fully integrable dynamic metasurfaces and their potential for beamforming applications. © 2021, CC BY.

关键词： Phase change materials

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Towards all-around knowledge transferring: Learning from task-irrelevant labels

arXiv

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arXiv 2020年

作者： Li, Yinghui Liu, Ruiyang Zhang, ZiHao Ding, Ning Shen, Ying Tao, Linmi Zheng, Hai-Tao Tsinghua Shenzhen International Graduate School Tsinghua University China Department of Computer Science and Technology Tsinghua University China Institute for Interdisciplinary Information Sciences Tsinghua University China School of Intelligent Systems Engineering Sun Yat-Sen University China

Deep neural models have hitherto achieved significant performances on numerous classification tasks, but meanwhile require sufficient manually annotated data. Since it is extremely time-consuming and expensive to annotate adequate data for each classification task, learning an empirically effective model with generalization on small dataset has received increased attention. Existing efforts mainly focus on transferring task-relevant knowledge from other similar data to tackle the issue. These approaches have yielded remarkable improvements, yet neglecting the fact that the task-irrelevant features could bring out massive negative transfer effects. To date, no large-scale studies have been performed to investigate the impact of task-irrelevant features, let alone the utilization of this kind of features. In this paper, we firstly propose Task-Irrelevant Transfer Learning (TIRTL) to exploit task-irrelevant features, which mainly are extracted from task-irrelevant labels. Particularly, we suppress the expression of task-irrelevant information and facilitate the learning process of classification. We also provide a theoretical explanation of our method. In addition, TIRTL does not conflict with those that have previously exploited task-relevant knowledge and can be well combined to enable the simultaneous utilization of task-relevant and task-irrelevant features for the first time. In order to verify the effectiveness of our theory and method, we conduct extensive experiments on facial expression recognition and digit recognition tasks. Our source code will be also available in the future for reproducibility. © 2020, CC-BY.

关键词： Classification (of information)

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Bioinformatics Pathway Analysis Pipeline for NGS Transcriptome Profile Data on Nasopharyngeal Carcinoma

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IOP Conference Series: Earth and Environmental science 2021年第1期794卷

作者： Digdo Sudigyo Gisti Rahmawati Dicka W. Setiasari Risky H. Poluan Tjeng Wawan Cenggoro Arif Budiarto Alam Ahmad Hidayat Sri R. Indrasari Afiahayati Sofia M. Haryana Bens Pardamean Bioinformatics & Data Science Research Center Bina Nusantara University Jakarta Indonesia 11480 Study Program of Biotechnology Gadjah Mada University Yogyakarta Indonesia 55281 Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia 11480 Faculty of Medicine Public Health and Nursing Gadjah Mada University Yogyakarta Indonesia 55281 Department of Computer Science and Electronics Faculty of Mathematics and Natural Science Gadjah Mada University Yogyakarta Indonesia 55281 Computer Science Department BINUS Graduate Program - Master of Computer Science Program Bina Nusantara University Jakarta Indonesia 11480

Next-Generation Sequencing (NGS)-based genomics data have a huge potential to be used in transcriptomic profiling of Nasopharyngeal Carcinoma (NPC) to study the biosynthesis mechanism behind it. The high dimensionality of NGS data is the main challenge in performing the data analysis to extract useful information. In this workflow pipeline, memory-efficient Linux-based software such as HISAT2 and HTSeq are utilized to process the raw NGS data. Furthermore, Differential Expression Gene (DEG) list can be obtained by performing advanced analysis to the aligned Ribonucleic Acid (RNA) sequence using the edgeR protocol. This DEG list is one of the main inputs of biological pathway analysis that can be done in DAVID and PANTHER web-based software. Both tools generate a different pathway result related to inflammation.

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SynthSeg: Segmentation of brain MRI scans of any contrast and resolution without retraining

arXiv

引用

arXiv 2021年

作者： Billot, Benjamin Greve, Douglas N. Puonti, Oula Thielscher, Axel Van Leemput, Koen Fischl, Bruce Dalca, Adrian V. Iglesias, Juan Eugenio Centre for Medical Image Computing University College London United Kingdom Martinos Center for Biomedical Imaging Department of Radiology Massachusetts General Hospital Harvard Medical School United States Danish Research Centre for Magnetic Resonance Centre for Functional and Diagnostic Imaging and Research Copenhagen University Hospital Denmark Department of Health Technology Technical University of Denmark Denmark Computer Science and Artificial Intelligence Laboratory Massachusetts Institute of Technology United States Program in Health Sciences and Technology Massachusetts Institute of Technology United States

Despite advances in data augmentation and transfer learning, convolutional neural networks (CNNs) difficultly generalise to unseen domains. When segmenting brain scans, CNNs are highly sensitive to changes in resolution and contrast: even within the same MRI modality, performance can decrease across datasets. Here we introduce SynthSeg, the first segmentation CNN robust against changes in contrast and resolution. SynthSeg is trained with synthetic data sampled from a generative model conditioned on segmentations. Crucially, we adopt a domain randomisation strategy where we fully randomise the contrast and resolution of the synthetic training data. Consequently, SynthSeg can segment real scans from a wide range of target domains without retraining or fine-tuning, which enables straightforward analysis of huge amounts of heterogeneous clinical data. Because SynthSeg only requires segmentations to be trained (no images), it can learn from labels obtained by automated methods on diverse populations (e.g., ageing and diseased), thus achieving robustness to a wide range of morphological variability. We demonstrate SynthSeg on 5,000 scans of six modalities (including CT) and ten resolutions, where it exhibits unparalleled generalisation compared with supervised CNNs, state-of-the-art domain adaptation, and Bayesian segmentation. Finally, we demonstrate the generalisability of SynthSeg by applying it to cardiac MRI and CT scans. Copyright © 2021, The Authors. All rights reserved.

关键词： computerized tomography

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Assessment of circulating extracellular vesicles from calorie-restricted mice and humans in ischaemic injury models

Journal of Extracellular Biology

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Journal of Extracellular Biology 2023年第5期2卷 e86页

作者： Jaimes, Manuel S. V. Liao, Chia-Te Chen, Max M. Czosseck, Andreas Lee, Tsung-Lin Chou, Yu-Hsiang Chen, Yung-Ming Lin, Shuei-Liong Lai, James J. Lundy, David J. Graduate Institute of Biomedical Materials & Tissue Engineering Taipei Medical University Taipei Taiwan Division of Nephrology Department of Internal Medicine Shuang Ho Hospital Taipei Medical University New Taipei Taiwan Division of Nephrology Department of Internal Medicine School of Medicine College of Medicine Taipei Medical University Taipei Taiwan TMU Research Center of Urology and Kidney (TMU-RCUK) Taipei Medical University Taipei Taiwan Division of Nephrology Department of Internal Medicine National Taiwan University Hospital College of Medicine National Taiwan University Taipei Taiwan Graduate Institute of Physiology College of Medicine National Taiwan University Taipei Taiwan Department of Bioengineering University of Washington Seattle WA United States Department of Materials Science and Engineering National Taiwan University of Science and Technology Taipei Taiwan International PhD Program in Biomedical Engineering Taipei Medical University Taipei Taiwan Center for Cell Therapy Taipei Medical University Hospital Taipei Taiwan

Calorie restriction (CR) and fasting affect lifespan, disease susceptibility and response to acute injury across multiple animal models, including ischaemic injuries such as myocardial infarction or kidney hypoxia. The cargo and function of circulating extracellular vesicles (EV) respond to changes in host physiology, including exercise, injury, and other interventions. Thus, we hypothesised that EVs induced following CR may reflect some of the beneficial properties of CR itself. In a pilot study, EVs were isolated from mice following 21 days of 30 % CR, and from eight human donors after 72 h water-only fasting. EV size, concentration and morphology were profiled by NTA, western blot and cryoEM, and their function was assessed using multiple assays related to ischaemic diseases. We found that EVs from post-fasting samples better protected cardiac cells from hypoxia/reperfusion (H/R) injury compared to pre-fasting EVs. However, there was no difference when used to treat H/R-injured kidney epithelial cells. Post-fasting derived EVs slowed the rate of fibroblast migration and slightly reduced macrophage inflammatory gene expression compared to pre-fasting derived EVs. Lastly, we compared miRNA cargos of pre- and post-fasting human serum EVs and found significant changes in a small number of miRNAs. We conclude that fasting appears to influence EV cargo and function, with varied effects worthy of further exploration. © 2023 The Authors. Journal of Extracellular Biology published by Wiley Periodicals, LLC on behalf of the International Society for Extracellular Vesicles.

关键词： calorie restriction cardiomyocyte diet extracellular vesicle fasting hypoxia ketone macrophage microRNA serum

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Phase transitions in the frustrated Ising ladder with stoquastic and nonstoquastic catalysts

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Physical Review Research 2021年第4期3卷 043013-043013页

作者： Kabuki Takada Shigetoshi Sota Seiji Yunoki Bibek Pokharel Hidetoshi Nishimori Daniel A. Lidar Department of Physics Tokyo Institute of Technology Yokohama Kanagawa 226-8503 Japan Computational Materials Science Research Team RIKEN Center for Computational Science (R-CCS) Kobe Hyogo 650-0047 Japan Computational Condensed Matter Physics Laboratory RIKEN Cluster for Pioneering Research (CPR) Wako Saitama 351-0198 Japan Computational Quantum Matter Research Team RIKEN Center for Emergent Matter Science (CEMS) Wako Saitama 351-0198 Japan Department of Physics University of Southern California Los Angeles California 90089 USA Center for Quantum Information Science & Technology University of Southern California Los Angeles California 90089 USA Institute of Innovative Research Tokyo Institute of Technology Yokohama Kanagawa 226-8503 Japan Graduate School of Information Sciences Tohoku University Sendai Miyagi 980-8579 Japan RIKEN Interdisciplinary Theoretical and Mathematical Sciences Program (iTHEMS) Wako Saitama 351-0198 Japan Department of Electrical & Computer Engineering and Department of Chemistry University of Southern California Los Angeles California 90089 USA

The role of nonstoquasticity in the field of quantum annealing and adiabatic quantum computing is an actively debated topic. We study a strongly-frustrated quasi-one-dimensional quantum Ising model on a two-leg ladder to elucidate how a first-order phase transition with a topological origin is affected by interactions of the ±XX-type. Such interactions are sometimes known as stoquastic (negative sign) and nonstoquastic (positive sign) “catalysts”. Carrying out a symmetry-preserving real-space renormalization group analysis and extensive density-matrix renormalization group computations, we show that the phase diagrams obtained by these two methods are in qualitative agreement with each other and reveal that the first-order quantum phase transition of a topological nature remains stable against the introduction of both XX-type catalysts. This is the first study of the effects of nonstoquasticity on a first-order phase transition between topologically distinct phases. Our results indicate that nonstoquastic catalysts are generally insufficient for removing topological obstacles in quantum annealing and adiabatic quantum computing.

关键词： Adiabatic quantum optimization Phase transitions by order Quantum spin models Density matrix renormalization group Renormalization group

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Response to "Comment on 'A novel two-dimensional boron-carbon-nitride (BCN) monolayer: A first-principles insight [J. Appl. Phys. 2021, 130, 114301]'"

arXiv

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arXiv 2022年

作者： Bafekry, Asadollah Naseri, Mosayeb Fadlallah, Mohamed M. Sarsari, Ismaeil Abdolhosseini Faraji, Mehrdad Khatibani, Abbas bagheri Ghergherehchi, Mitra Gogova, Daniela Department of Radiation Application Shahid Beheshti University Tehran*** Iran Department of Physics Kermanshah Branch Islamic Azad University Kermanshah*** Iran Department of Physics Faculty of Science Benha University Benha13518 Egypt Department of Physics Isfahan University of Technology Isfahan84156-83111 Iran Micro and Nanotechnology Graduate Program TOBB University of Economics and Technology Sogutozu Caddesi No 43 Sogutozu Ankara06560 Turkey Nano Research Lab Lahijan Branch Islamic Azad University Lahijan1616 Iran Department of Electrical and Computer Engineering Sungkyunkwan University Suwon16419 Korea Republic of Department of Physics Chemistry and Biology Linkoping University Linköping581 83 Sweden

Mortazavi et al. comment on the results of our paper "A novel two-dimensional boron-carbon-nitride BCN monolayer: A First-principles insight," in which we have considered different configurations of BCN. For clarification, we applied the fingerprint theory [1-3] to examine the similarity between the distinct structures. The fingerprint function is a crystal structure descriptor, an 1D-function related to the pair correlation function and diffraction patterns. It does not depend on absolute atomic coordinates, but only on interatomic distances. Small deviations in atomic positions will influence the fingerprints only slightly [1-3]. Fingerprint theory allows quantification of the degree of order and complexity of a crystal structure. © 2022, CC BY.

关键词： Monolayers

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Analysis of backpropagation neural neural network algorithm on student ability based cognitive aspects

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IOP Conference Series: Materials science and Engineering 2020年第1期725卷

作者： Fahmi Izhari Muhammad Zarlis Sutarman Graduate Program of Computer Science Faculty of Computer Science and Information Technology Universitas Sumatera Utara Medan Indonesia

Back propagation is one of the supervised learning and multi-layered training program and uses errors during the process of changing the weight value in the backward process as well as the forward propagation. In the method for predicting cognitive abilities backpropagation the first step is to set the input neuron number, the number of neurons that are hidden, and the number of output neurons. The number of neurons used in the program is 6 neurons consisting of cognitive criteria, 6 hidden neuron layers, and 2 neuron outputs. The highest level of accuracy is in the binary sigmoid and bipolar sigmoid activation functions at the 64th epoch with the accuracy of each function of 82.93% +/- 37.63% and 85.37% +/- 35.34%. The smallest root mean squared error value was found in binary sigmoid of 0.266 with a tolerance of +/- 0.258 on the 100th epoch with an accuracy of 80.49% while for the sigmoid bipolar activation function the smallest root mean squared error value was obtained at the epoch 500 of 0.282 with tolerance +/- 0.353.

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