Article
Computer Science, Artificial Intelligence
Gao Huang, Zhuang Liu, Geoff Pleiss, Laurens van der Maaten, Kilian Q. Weinberger
Summary: Recent work has shown that adding shorter connections in convolutional networks can make the network deeper, more accurate, and more efficient in training. This paper introduces Dense Convolutional Network (DenseNet), which connects each layer to every other layer in a feed-forward manner. DenseNets alleviate the vanishing-gradient problem, encourage feature reuse, and improve parameter efficiency, leading to significant improvements in object recognition tasks.
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
(2022)
Article
Plant Sciences
Carola Figueroa-Flores, Pablo San-Martin
Summary: This study evaluates the performance of several Deep Learning models for classifying images of Chilean native flora and highlights their potential in accurately classifying these images. The results contribute to enhancing the understanding of Chilean plant species and fostering awareness among the general public.
FRONTIERS IN PLANT SCIENCE
(2023)
Article
Computer Science, Information Systems
Akarsh Aggarwal, Manoj Kumar
Summary: The study introduces a deep learning-based CNN model for surface texture classification that reduces the number of training samples through customized parameter configuration, achieving high accuracy in texture classification on the Kylberg Texture dataset. The proposed models outperform traditional techniques, reaching accuracies of 92.42% for model-1 and 96.36% for model-2, while maintaining a balance between accuracy and computational cost.
MULTIMEDIA TOOLS AND APPLICATIONS
(2021)
Article
Environmental Sciences
Jiangbo Xi, Okan K. Ersoy, Ming Cong, Chaoying Zhao, Wei Qu, Tianjun Wu
Summary: This paper proposes a wide and deep Fourier network for efficient feature learning in hyperspectral remote sensing image (HSI) classification. The method utilizes pruned features extracted in the frequency domain to extract hierarchical features layer-by-layer. Experimental results show that the proposed method achieves excellent performance in HSI classification, with the ability to be implemented in lightweight embedded computing platforms.
Article
Biochemical Research Methods
Bilin Liang, Haifan Gong, Lu Lu, Jie Xu
Summary: The study proposes a novel model, PathGNN, that constructs a Graph Neural Networks (GNNs) model to capture the topological features of pathways. It achieves promising predictive performance in predicting long-term survival of cancer, and the adoption of an interpretation algorithm enables the identification of plausible pathways associated with survival.
BMC BIOINFORMATICS
(2022)
Article
Computer Science, Artificial Intelligence
Ronghua Shang, Jiaming Wang, Licheng Jiao, Xiaohui Yang, Yangyang Li
Summary: This paper proposes a spatial feature-based convolutional neural network (SF-CNN) for solving PolSAR classification problems. The special structure of SF-CNN can expand the training set by combining different samples and enhance the network's ability to extract discriminative features in low-dimensional feature space. Experimental results show that SF-CNN outperforms standard CNN in PolSAR image classification tasks.
APPLIED SOFT COMPUTING
(2022)
Article
Computer Science, Artificial Intelligence
Jin-Young Kim, Sung-Bae Cho
Summary: An anatomical comparison of GNNs provides insight into devising better solutions. By systematically analyzing and comparing thousands of runs, researchers deduced five guidelines for an appropriate model. The study aims to guide the use of GNN for graph classification and validation of experimental reproducibility and replicability.
EXPERT SYSTEMS WITH APPLICATIONS
(2021)
Article
Environmental Sciences
Jiangbo Xi, Ming Cong, Okan K. Ersoy, Weibao Zou, Chaoying Zhao, Zhenhong Li, Junkai Gu, Tianjun Wu
Summary: The paper proposed a dynamic wide and deep neural network (DWDNN) for HSI classification, including multiple efficient wide sliding window and subsampling (EWSWS) networks that can grow dynamically with problem complexity. Compared to other deep learning methods, the proposed approach achieved the highest test accuracies.
Article
Computer Science, Artificial Intelligence
Alessandro Benfenati, Alessio Marta
Summary: This paper proposes a geometric framework for studying deep neural networks, viewing them as sequences of mappings between manifolds using singular Riemannian geometry. The authors present an application of this framework, specifically focusing on constructing equivalence classes of input points that are mapped to the same output by the network. This approach has practical implications in generating synthetic data and understanding the sensitivity of classifiers to input perturbations.
Article
Computer Science, Artificial Intelligence
Shiye Lei, Fengxiang He, Yancheng Yuan, Dacheng Tao
Summary: This article finds that neural networks with less variability in decision boundaries have better generalizability. The experiments show significant negative correlations between decision boundary variability and generalizability. The article introduces the concepts of algorithm DB variability and (epsilon, eta)-data DB variability to measure variability in decision boundaries.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2023)
Article
Computer Science, Artificial Intelligence
Bo Wang, Shuo Jin, Qingsen Yan, Haibo Xu, Chuan Luo, Lai Wei, Wei Zhao, Xuexue Hou, Wenshuo Ma, Zhengqing Xu, Zhuozhao Zheng, Wenbo Sun, Lan Lan, Wei Zhang, Xiangdong Mu, Chenxi Shi, Zhongxiao Wang, Jihae Lee, Zijian Jin, Minggui Lin, Hongbo Jin, Liang Zhang, Jun Guo, Benqi Zhao, Zhizhong Ren, Shuhao Wang, Wei Xu, Xinghuan Wang, Jianming Wang, Zheng You, Jiahong Dong
Summary: This paper presents the experience of building and deploying an AI system for rapid detection of COVID-19 pneumonia, which can save time for physicians and improve the performance of COVID-19 detection. The authors overcame various challenges in a interdisciplinary team and successfully deployed the system in four weeks.
APPLIED SOFT COMPUTING
(2021)
Article
Geochemistry & Geophysics
Guoqing Zhou, Weiguang Liu, Qiang Zhu, Yanling Lu, Yu Liu
Summary: In recent years, models based on fully convolutional neural networks have been proposed to improve accuracy but ignored computational efficiency. This research presents an innovative deep learning model, ECA-MobileNetV3(large)+SegNet, which simultaneously considers both aspects. By modifying the encoder and decoder structures, the proposed model achieves significant improvement in performance and reduces the number of parameters.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2022)
Article
Chemistry, Multidisciplinary
Jinho Park, Heegwang Kim, Joonki Paik
Summary: The proposed CF-CNN utilizes a disjoint grouping method to learn multilabel classes, improving classification accuracy by up to 3% with a smaller number of parameters.
APPLIED SCIENCES-BASEL
(2021)
Article
Chemistry, Multidisciplinary
Keisuke Manabe, Yusuke Asami, Tomonari Yamada, Hiroyuki Sugimori
Summary: This study evaluated an improved specialized convolutional neural network for medical image classification tasks, achieving high accuracy especially in pancreatic classification. By optimizing the filter size of the convolution layer and max-pooling, accurate results can be quickly obtained.
APPLIED SCIENCES-BASEL
(2021)
Article
Cell Biology
Bolin Chen, Yourui Han, Xuequn Shang, Shenggui Zhang
Summary: Identifying disease related genes is crucial in bioinformatics. Deep learning methods have been successful, but often do not address gene multifunctionality and the scale-free property of biological networks well. A novel network representation method was proposed to tackle these challenges, showing promising results in numerical experiments.
FRONTIERS IN CELL AND DEVELOPMENTAL BIOLOGY
(2021)
Article
Biochemical Research Methods
Leijie Li, Dongxue Che, Xiaodan Wang, Peng Zhang, Siddiq Ur Rahman, Jianbang Zhao, Jiantao Yu, Shiheng Tao, Hui Lu, Mingzhi Liao
BMC BIOINFORMATICS
(2019)
Article
Genetics & Heredity
Yiming Hu, Mo Li, Qiongshi Lu, Haoyi Weng, Jiawei Wang, Seyedeh M. Zekavat, Zhaolong Yu, Boyang Li, Jianlei Gu, Sydney Muchnik, Yu Shi, Brian W. Kunkle, Shubhabrata Mukherjee, Pradeep Natarajan, Adam Naj, Amanda Kuzma, Yi Zhao, Paul K. Crane, Hui Lu, Hongyu Zhao, Erin Abner, Perrie M. Adams, Marilyn S. Albert, Roger L. Albin, Liana G. Apostolova, Steven E. Arnold, Sanjay Asthana, Craig S. Atwood, Clinton T. Baldwin, Robert C. Barber, Lisa L. Barnes, Sandra Barral, Thomas G. Beach, James T. Becker, Gary W. Beecham, Duane Beekly, David A. Bennett, Eileen H. Bigio, Thomas D. Bird, Deborah Blacker, Bradley F. Boeve, James D. Bowen, Adam Boxer, James R. Burke, Jeffrey M. Burns, Joseph D. Buxbaum, Nigel J. Cairns, Laura B. Cantwell, Chuanhai Cao, Chris S. Carlson, Cynthia M. Carlsson, Regina M. Carney, Minerva M. Carrasquillo, Helena C. Chui, David H. Cribbs, Elizabeth A. Crocco, Carlos Cruchaga, Philip L. De Jager, Charles DeCarli, Malcolm Dick, Dennis W. Dickson, Rachelle S. Doody, Ranjan Duara, Nilufer Ertekin-Taner, Denis A. Evans, Kelley M. Faber, Thomas J. Fairchild, Kenneth B. Fallon, David W. Fardo, Martin R. Farlow, Lindsay A. Farrer, Steven Ferris, Tatiana M. Foroud, Matthew P. Frosch, Douglas R. Galasko, Marla Gearing, Daniel H. Geschwind, Bernardino Ghetti, John R. Gilbert, Alison M. Goate, Neill R. Graff-Radford, Robert C. Green, John H. Growdon, Jonathan L. Haines, Hakon Hakonarson, Ronald L. Hamilton, Kara L. Hamilton-Nelson, John Hardy, Lindy E. Harrell, Lawrence S. Honig, Ryan M. Huebinger, Matthew J. Huentelman, Christine M. Hulette, Bradley T. Hyman, Gail P. Jarvik, Lee-Way Jin, Gyungah Jun, M. Ilyas Kamboh, Anna Karydas, Mindy J. Katz, John S. K. Kauwe, Jeffrey A. Kaye, C. Dirk Keene, Ronald Kim, Neil W. Kowall, Joel H. Kramer, Walter A. Kukull, Amanda P. Kuzma, Frank M. LaFerla, James J. Lah, Eric B. Larson, James B. Leverenz, Allan Levey, Ge Li, Andrew P. Lieberman, Richard B. Lipton, Oscar L. Lopez, Kathryn L. Lunetta, Constantine G. Lyketsos, John Malamon, Daniel C. Marson, Eden R. Martin, Frank Martiniuk, Deborah C. Mash, Eliezer Masliah, Richard Mayeux, Wayne C. McCormick, Susan M. McCurry, Andrew N. McDavid, Stefan McDonough, Ann C. McKee, Marsel Mesulam, Bruce L. Miller, Carol A. Miller, Joshua W. Miller, Thomas J. Montine, John C. Morris, Amanda J. Myers, Adam C. Naj, Sid O'Bryant, John M. Olichney, Joseph E. Parisi, Henry L. Paulson, Margaret A. Pericak-Vance, Elaine Peskind, Ronald C. Petersen, Aimee Pierce, Wayne W. Poon, Huntington Potter, Liming Qu, Joseph F. Quinn, Ashok Raj, Murray Raskind, Eric M. Reiman, Barry Reisberg, Joan S. Reisch, Christiane Reitz, John M. Ringman, Erik D. Roberson, Ekaterina Rogaeva, Howard J. Rosen, Roger N. Rosenberg, Donald R. Royall, Mark A. Sager, Mary Sano, Andrew J. Saykin, Gerard D. Schellenberg, Julie A. Schneider, Lon S. Schneider, William W. Seeley, Amanda G. Smith, Joshua A. Sonnen, Salvatore Spina, Peter St George-Hyslop, Robert A. Stern, Russell H. Swerdlow, Rudolph E. Tanzi, John Q. Trojanowski, Juan C. Troncoso, Debby W. Tsuang, Otto Valladares, Vivianna M. Van Deerlin, Linda J. Van Eldik, Badri N. Vardarajan, Harry V. Vinters, Jean Paul Vonsattel, Li-San Wang, Sandra Weintraub, Kathleen A. Welsh-Bohmer, Kirk C. Wilhelmsen, Jennifer Williamson, Thomas S. Wingo, Randall L. Woltjer, Clinton B. Wright, Chuang-Kuo Wu, Steven G. Younkin, Chang-En Yu, Lei Yu
Article
Genetics & Heredity
Jianping Jiang, Jinwei Huang, Jianlei Gu, Xiaoshu Cai, Hongyu Zhao, Hui Lu
BMC MEDICAL GENETICS
(2019)
Article
Genetics & Heredity
Xujun Wang, Zhengtao Zhang, Weny Qiu, Shiyi Liu, Cong Liu, Georgi Z. Genchev, Lijian Hui, Hongyu Zhao, Hui Lu
Summary: RePhine is a regression-based pharmacogenomic and ChIP-seq data integration method that infers the impact of transcriptional regulators on drug response. Evaluation on simulation and pharmacogenomic data showed improved performance of RePhine in identifying drug response-related transcriptional regulators.
GENOMICS PROTEOMICS & BIOINFORMATICS
(2021)
Article
Health Care Sciences & Services
Mengting Ji, Georgi Z. Genchev, Hengye Huang, Ting Xu, Hui Lu, Guangjun Yu
Summary: This study aimed to develop and validate a measurement instrument and test the interrelationships of evaluation variables for an artificial intelligence-enabled clinical decision support system evaluation framework. The results showed that user acceptance is the central dimension of artificial intelligence-enabled clinical decision support system success, directly influenced by perceived ease of use, information quality, service quality, and perceived benefit, and indirectly influenced through system quality and information quality.
JOURNAL OF MEDICAL INTERNET RESEARCH
(2021)
Article
Oncology
Liangqing Dong, Dayun Lu, Ran Chen, Youpei Lin, Hongwen Zhu, Zhou Zhang, Shangli Cai, Peng Cui, Guohe Song, Dongning Rao, Xinpei Yi, Yingcheng Wu, Nixue Song, Fen Liu, Yunhao Zou, Shu Zhang, Xiaoming Zhang, Xiaoying Wang, Shuangjian Qiu, Jian Zhou, Shisheng Wang, Xu Zhang, Yongyong Shi, Daniel Figeys, Li Ding, Pei Wang, Bing Zhang, Henry Rodriguez, Qiang Gao, Daming Gao, Hu Zhou, Jia Fan
Summary: This study performed proteogenomic characterization of intrahepatic cholangiocarcinoma (iCCA) and revealed important features of iCCA pathogenesis. It identified subgroup-specific biomarkers and provided valuable insights into molecular pathogenesis and therapeutic opportunities in iCCA.
Article
Genetics & Heredity
Jianlei Gu, Jiawei Dai, Hui Lu, Hongyu Zhao
Summary: Comprehensive characterization of spatial and temporal gene expression patterns in humans is critical for understanding human diseases. This study proposed a data-driven framework to derive a list of Ubiquitously Expressed Genes (UEGs) and their global expression patterns, providing a valuable resource for further characterizing the human transcriptome.
GENOMICS PROTEOMICS & BIOINFORMATICS
(2023)
Article
Psychiatry
Yuanyuan Gui, Xiaocheng Zhou, Zixin Wang, Yiliang Zhang, Zhaobin Wang, Geyu Zhou, Yize Zhao, Manhua Liu, Hui Lu, Hongyu Zhao
Summary: This study examined the associations between the predicted polygenic risk scores of six psychiatric disorders and cognitive functions, behavior, and brain imaging traits using publicly available genome-wide association studies and individual-level data from the Adolescent Brain Cognitive Development study and the UK Biobank study. Significant heterogeneity was found in genetic associations between cognitive traits and psychiatric disorders, as well as behavior and brain imaging, between sexes.
TRANSLATIONAL PSYCHIATRY
(2022)
Article
Biology
Yongyong Ren, Yan Kong, Xiaocheng Zhou, Georgi Z. Genchev, Chao Zhou, Hongyu Zhao, Hui Lu
Summary: The quality control of genetic variants from whole-genome sequencing data is important in clinical diagnosis and human genetics research. The current filtering methods have limitations, but FVC, an adaptive method, performs better in filtering out false variants.
COMMUNICATIONS BIOLOGY
(2022)
Article
Psychiatry
Zhaobin Wang, Xiaocheng Zhou, Yuanyuan Gui, Manhua Liu, Hui Lu
Summary: Attention deficit hyperactivity disorder (ADHD) is a common psychiatric disorder in school-aged children. This study proposes an automated ADHD classification framework by combining multiple measures of resting-state functional magnetic resonance imaging (rsfMRI) in the adolescent brain.
TRANSLATIONAL PSYCHIATRY
(2023)
Article
Health Care Sciences & Services
Shuya Cui, Qingmin Lin, Yuanyuan Gui, Yunting Zhang, Hui Lu, Hongyu Zhao, Xiaolei Wang, Xinyue Li, Fan Jiang
Summary: In this study, a new metric called circadian activity rhythm energy (CARE) is introduced to better measure circadian amplitude. CARE is found to be significantly correlated with melatonin amplitude and associated with cognitive functions. The study also identifies a genetic basis for CARE and demonstrates its causal effect on cognitive functions.
NPJ DIGITAL MEDICINE
(2023)
Article
Computer Science, Artificial Intelligence
Shu Wang, Xiaocheng Zhou, Yan Kong, Hui Lu
Summary: Spatially resolved transcriptomics (SRT) is a vital technique for measuring gene expression while preserving spatial information. In this study, researchers propose a deep learning-based method to enhance spot resolution, achieving higher resolution SRT data. The method outperforms traditional superresolution techniques and offers a substantial advancement in SRT by enabling higher-resolution gene expression data generation.
APPLIED INTELLIGENCE
(2023)
Article
Computer Science, Artificial Intelligence
Fan Yang, Wenchuan Wang, Fang Wang, Yuan Fang, Duyu Tang, Junzhou Huang, Hui Lu, Jianhua Yao
Summary: Annotating cell types based on single-cell RNA-seq data is crucial for studying disease progress and tumor microenvironments. Existing annotation methods often face challenges such as a lack of curated marker gene lists, difficulties in handling batch effects, and inability to leverage gene-gene interaction information, leading to limited generalization and robustness. In this study, we developed a pretrained deep neural network model called scBERT, which overcomes these challenges by training on large amounts of unlabeled scRNA-seq data and achieving a comprehensive understanding of gene-gene interactions. scBERT demonstrates superior performance in cell type annotation, novel cell type discovery, robustness to batch effects, and model interpretability.
NATURE MACHINE INTELLIGENCE
(2022)
Article
Mathematical & Computational Biology
Chenfang Zhang, Georgi Z. Genchev, Dennis Bergau, Hui Lu
INTERDISCIPLINARY SCIENCES-COMPUTATIONAL LIFE SCIENCES
(2020)
Article
Computer Science, Theory & Methods
Guang-jun Yu, Jian-lei Gu, Wen-bin Cui, Jian-ping Jiang, Yang Wang, Georgi Z. Genchev, Ting Lu, Hui Lu
JOURNAL OF BIG DATA
(2019)
Review
Biochemistry & Molecular Biology
M. T. Ciubuc-Batcu, N. J. C. Stapelberg, J. P. Headrick, G. M. C. Renshaw
Summary: The nervous system relies on mitochondria, and impaired mitochondrial function is associated with major depressive disorder. Modulating mitochondrial function may be a therapeutic target for treating MDD.
BIOCHIMICA ET BIOPHYSICA ACTA-MOLECULAR BASIS OF DISEASE
(2024)
Correction
Biochemistry & Molecular Biology
Saowaluk Saisomboon, Ryusho Kariya, Piyanard Boonnate, Kanlayanee Sawanyawisuth, Ubon Cha'on, Vor Luvira, Yaovalux Chamgramol, Chawalit Pairojkul, Wunchana Seubwai, Atit Silsirivanit, Sopit Wongkham, Seiji Okada, Sarawut Jitrapakdee, Kulthida Vaeteewoottacharn
BIOCHIMICA ET BIOPHYSICA ACTA-MOLECULAR BASIS OF DISEASE
(2024)
Article
Biochemistry & Molecular Biology
Pavan Thapak, Zhe Ying, Victoria Palafox-Sanchez, Guanglin Zhang, Xia Yang, Fernando Gomez-Pinilla
Summary: Traumatic brain injury (TBI) impairs cellular energy demand, compromising neuronal function and plasticity. This study demonstrates that the mitochondrial activator humanin (HN) can counteract the reduction in mitochondrial bioenergetics caused by TBI, restore memory function and synaptic protein levels, and suppress inflammation and astrocyte proliferation. HN plays an integral role in normalizing fundamental aspects of TBI pathology.
BIOCHIMICA ET BIOPHYSICA ACTA-MOLECULAR BASIS OF DISEASE
(2024)
Article
Biochemistry & Molecular Biology
M. Paul Murphy, Valeria A. Buzinova, Carrie E. Johnson
Summary: Progress has been made in the treatment of Alzheimer's disease through the development of anti-A beta therapeutics, which have shown modest efficacy in slowing the progression of the disease. However, the puzzling issue remains as to why completely removing A beta does not fully stop the disease.
BIOCHIMICA ET BIOPHYSICA ACTA-MOLECULAR BASIS OF DISEASE
(2024)
Review
Biochemistry & Molecular Biology
Yang Zhang, Mengqiu Hao, Xuyang Yang, Su Zhang, Junhong Han, Ziqiang Wang, Hai-Ning Chen
Summary: Colorectal cancer often requires adjuvant therapies to reduce tumor burden, and the efficacy of these therapies is significantly influenced by reactive oxygen species (ROS). ROS-mediated colorectal cancer adjuvant therapies involve multiple mechanisms, and preliminary clinical trials have shown the potential of ROS-manipulating therapy in enhancing treatment outcomes.
BIOCHIMICA ET BIOPHYSICA ACTA-MOLECULAR BASIS OF DISEASE
(2024)
Article
Biochemistry & Molecular Biology
Mengxin Li, Xuanzhong Wang, Xuyang Chen, Jinghui Hong, Ye Du, Dong Song
Summary: Pancreatic adenocarcinoma (PAAD) is a common digestive malignant tumor with limited treatment options. This study demonstrates that TGM2 may serve as a marker for treatment and prognosis in pancreatic cancer patients. Co-treatment of low dose cisplatin (DDP) and the TGM2 inhibitor GK921 effectively inhibits PAAD cell viability and proliferation in vitro and in vivo, by inhibiting epithelial-to-mesenchymal transition (EMT) induced by TGM2 and enhancing cell cycle arrest and apoptosis caused by DDP. These findings suggest that the combination of GK921 and DDP holds promise as a treatment for PAAD patients.
BIOCHIMICA ET BIOPHYSICA ACTA-MOLECULAR BASIS OF DISEASE
(2024)
Article
Biochemistry & Molecular Biology
Liaoran Niu, Qi Wang, Fan Feng, Wanli Yang, Zhenyu Xie, Gaozan Zheng, Wei Zhou, Lili Duan, Kunli Du, Yiding Li, Ye Tian, Junfeng Chen, Qibin Xie, Aqiang Fan, Hanjun Dan, Jinqiang Liu, Daiming Fan, Liu Hong, Jian Zhang, Jianyong Zheng
Summary: This review provides a comprehensive summary of the interaction between cancer cells and macrophages in the tumor microenvironment, and discusses the role of small extracellular vesicles (sEVs) in this process. It also explores the various effects of macrophage-secreted sEVs on tumor malignant transformation, and addresses the therapeutic advancements and challenges associated with these vesicles.
BIOCHIMICA ET BIOPHYSICA ACTA-MOLECULAR BASIS OF DISEASE
(2024)
Article
Biochemistry & Molecular Biology
Neha Sawant, Sudhir Kshirsagar, P. Hemachandra Reddy, Arubala P. Reddy
Summary: Depression is a common neuropsychiatric comorbidity in Alzheimer's disease (AD) and other Tauopathies. Selective serotonin reuptake inhibitor (SSRI) treatment, such as Citalopram, not only has anti-depressive and anxiolytic effects, but also helps improve neurogenesis, reduce amyloid burden & Tau pathologies, and neuroinflammation in AD. In this study, Citalopram was found to reduce pathologically pTau level, increase synaptic gene expression and cytoskeletal structure, as well as improve cell survival, mitochondrial respiration, and mitochondrial morphology in cells expressing mutant APP and Tau. These findings suggest that Citalopram could be a promising therapeutic drug for treating depression and AD.
BIOCHIMICA ET BIOPHYSICA ACTA-MOLECULAR BASIS OF DISEASE
(2024)
Article
Biochemistry & Molecular Biology
Yueqi Chen, Jiulin Tan, Chuan Yang, Zhiguo Ling, Jianzhong Xu, Dong Sun, Fei Luo
Summary: Bone is a self-healing organ that undergoes continuous regeneration through the cooperation of osteoclasts and osteoblasts. This study used ATAC-seq and RNA-Seq techniques to investigate the chromatin accessibility and transcriptomic landscape of osteoblast differentiation and mineralization. The results showed that global chromatin accessibility was extensively improved during osteoblastogenesis. Additionally, several transcription factors including MEF2A, PRRX1, Shox2, and HOXB13 were found to modulate the promoter accessibility of target genes during osteoblast differentiation.
BIOCHIMICA ET BIOPHYSICA ACTA-MOLECULAR BASIS OF DISEASE
(2024)
Article
Biochemistry & Molecular Biology
Zi-Ran Kang, Shanshan Jiang, Ji-Xuan Han, Yaqi Gao, Yile Xie, Jinxian Chen, Qiang Liu, Jun Yu, Xin Zhao, Jie Hong, Haoyan Chen, Ying-Xuan Chen, Huimin Chen, Jing-Yuan Fang
Summary: The study demonstrates that BCAA metabolism is involved in the development of colorectal cancer (CRC). BCAT2 deficiency promotes CRC progression by inhibiting BCAA metabolism and chronically activating the mTORC1 pathway.
BIOCHIMICA ET BIOPHYSICA ACTA-MOLECULAR BASIS OF DISEASE
(2024)
Article
Biochemistry & Molecular Biology
Chao Zheng, Lingling Liu, Caiyun Liu, Fengna Chu, Yue Lang, Shan Liu, Yan Mi, Jie Zhu, Tao Jin
Summary: Inducing tolerogenic dendritic cells (tDCs) with low RelB expression could effectively alleviate symptoms and reduce immune cell infiltration and demyelination in experimental autoimmune encephalomyelitis (EAE) mouse model.
BIOCHIMICA ET BIOPHYSICA ACTA-MOLECULAR BASIS OF DISEASE
(2024)
Article
Biochemistry & Molecular Biology
Hang Lam Li, Simei Go, Jung-Chin Chang, Arthur Verhoeven, Ronald Oude Elferink
Summary: This review highlights the distinct characteristics and crucial role of soluble adenylyl cyclase (sAC) in cellular processes, as well as recent significant advancements in the field of sAC research.
BIOCHIMICA ET BIOPHYSICA ACTA-MOLECULAR BASIS OF DISEASE
(2024)
Article
Biochemistry & Molecular Biology
M. Seco-Cervera, D. Ortiz-Masia, D. C. Macias-Ceja, S. Coll, L. Gisbert-Ferrandiz, J. Cosin-Roger, C. Bauset, M. Ortega, B. Heras-Moran, F. Navarro-Vicente, M. Millan, J. V. Esplugues, S. Calatayud, M. D. Barrachina
Summary: The study revealed the presence of resistance to apoptosis in complicated ileal Crohn's disease, with PDGFB inducing an ETS1-mediated resistance to apoptosis associated with an inflammatory and fibrogenic pattern of expression in intestinal fibroblasts. Potential targets against ileal fibrosis include PDGFRB, IL1R1, or MCL1.
BIOCHIMICA ET BIOPHYSICA ACTA-MOLECULAR BASIS OF DISEASE
(2024)
Review
Biochemistry & Molecular Biology
Yunmeng Wang, Ping Cheng
Summary: Oncolytic viruses (OVs) are emerging as therapeutically relevant anticancer agents, especially when combined with genetically modified bispecific T cell engagers (BiTEs). This combination strategy can overcome the limitations of BiTEs alone and provide targeted cytotoxicity to solid tumors.
BIOCHIMICA ET BIOPHYSICA ACTA-MOLECULAR BASIS OF DISEASE
(2024)
Article
Biochemistry & Molecular Biology
Stephanie Tannous, Hassan Y. Naim
Summary: Congenital sucrase-isomaltase deficiency (CSID) is an autosomal recessive disorder caused by variants in the SI gene. A frameshift mutation called c.273_274delAG (p.Gly92Leufs*8) has been identified in CSID patients in Greenlandic population, which leads to loss of digestive function of SI. Surprisingly, the truncated mutant can still be located on the cell surface and interacts with wild type SI, negatively affecting its enzymatic function. Furthermore, heterozygote carriers of this mutation may also exhibit CSID symptoms.
BIOCHIMICA ET BIOPHYSICA ACTA-MOLECULAR BASIS OF DISEASE
(2024)