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Transient chemical-mediated epigenetic modulation confers unrestricted lineage potential on human primed pluripotent stem cells

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Science China(Life Sciences) 2025年第4期68卷 1084-1101页

作者： Shi Chen Yuanyuan He Lejun Lv Bei Liu Cheng Li Hongkui Deng Jun Xu Department of Cell Biology School of Basic Medical SciencesPeking University Stem Cell Research CenterPeking University Health Science CenterPeking UniversityBeijing100191China Academy of Advanced Interdisciplinary Studies Peking UniversityBeijing100871China BeiCell Therapeutics Beijing100094China School of Life Sciences Center for BioinformaticsCenter for Statistical SciencePeking UniversityBeijing100871China MOE Engineering Research Center of Regenerative Medicine School of Basic Medical SciencesState Key Laboratory of Natural and Biomimetic DrugsPeking University Health Science Center and the MOE Key Laboratory of Cell Proliferation and DifferentiationCollege of Life SciencesPeking-Tsinghua Center for Life SciencesPeking UniversityBeijing100871China

Human primed pluripotent stem cells are capable of generating all the embryonic ***,their extraembryonic trophectoderm potentials are *** remains unclear how to expand their developmental potential to trophectoderm *** we show that transient treatment with a cocktail of small molecule epigenetic modulators imparts trophectoderm lineage potentials to human primed pluripotent stem cells while preserving their embryonic *** chemically treated cells can generate trophectoderm-like cells and downstream trophoblast stem cells,diverging into syncytiotrophoblast and extravillous trophoblast *** and CUT&Tag analyses reveal that these induced cells share transcriptional profiles with in vivo trophectoderm and cytotrophoblast,and exhibit reduced H3K27me3 modification at gene loci specific to trophoblast lineages compared with primed pluripotent *** exploration highlighted the critical roles of epigenetic modulators HDAC2,EZH1/2,and KDM5s in the activation of trophoblast lineage *** findings demonstrate that transient epigenetic resetting activates unrestricted lineage potential in human primed pluripotent stem cells,and offer new mechanistic insights into human trophoblast lineage specification and in vitro models for studying placental development and related disorders.

关键词： trophectoderm lineages human primed pluripotent stem cells epigenetic regulation small molecules

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SpaGRA:Graph augmentation facilitates domain identification for spatially resolved transcriptomics

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Journal of Genetics and Genomics 2025年第1期52卷 93-104页

作者： Xue Sun Wei Zhang Wenrui Li Na Yu Daoliang Zhang Qi Zou Qiongye Dong Xianglin Zhang Zhiping Liu Zhiyuan Yuan Rui Gao Center of Intelligent Medicine School of Control Science and EngineeringShandong UniversityJinanShandong 250061China MOE Key Lab of Bioinformatics and Bioinformatics Division of BNRIST Department of AutomationTsinghua UniversityBeijing 100084China Institute of Precision Medicine Peking University Shenzhen HospitalShenzhenGuangdong 518036China Department of Clinical Laboratory The Second HospitalCheeloo College of MedicineShandong UniversityJinanShandong 250033China Institute of Science and Technology for Brain-Inspired Intelligence Center for Medical Research and InnovationShanghai Pudong HospitalFudan University Pudong Medical CenterFudan UniversityShanghai 200433China

Recent advances in spatially resolved transcriptomics(SRT)have provided new opportunities for characterizing spatial structures of various ***-based geometric deep learning has gained widespread adoption for spatial domain identification ***,most methods define adjacency relation between cells or spots by their spatial distance in SRT data,which overlooks key biological interactions like gene expression similarities,and leads to inaccuracies in spatial domain *** tackle this challenge,we propose a novel method,SpaGRA(https://***/sunxue-yy/SpaGRA),for automatic multi-relationship construction based on graph *** uses spatial distance as prior knowledge and dynamically adjusts edge weights with multi-head graph attention networks(GATs).This helps SpaGRA to uncover diverse node relationships and enhance message passing in geometric contrastive ***,SpaGRA uses these multi-view relationships to construct negative samples,addressing sampling bias posed by random *** results show that SpaGRA presents superior domain identification performance on multiple datasets generated from different *** SpaGRA,we analyze the functional regions in the mouse hypothalamus,identify key genes related to heart development in mouse embryos,and observe cancer-associated fibroblasts enveloping cancer cells in the latest Visium HD ***,SpaGRA can effectively characterize spatial structures across diverse SRT datasets.

关键词： Spatial domain identification Spatially resolved transcriptomics Multi-head graph attention networks Graph augmentation Geometric contrastive learning

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Identifying candidate biomarkers for detecting bronchogenic carcinoma stages using metaheuristic algorithms based on information fusion theory

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Discover Oncology 2025年第1期16卷 1-27页

作者： Khalvati, Bagher Kavousi, Kaveh Keyhanipour, Amir Hosein Arabfard, Masoud Department of Bioinformatics Kish International Campus University of Tehran Kish Iran Laboratory of Complex Biological Systems and Bioinformatics (CBB) Department of Bioinformatics Institute of Biochemistry and Biophysics (IBB) University of Tehran Tehran Iran Computer Engineering Department Faculty of Engineering College of Farabi University of Tehran Tehran Iran Chemical Injuries Research Center Systems Biology and Poisonings Institute Baqiyatallah University of Medical Sciences Tehran Iran

Objective: Invasive lung cancer staging poses significant challenges, often requiring painful and costly biopsy procedures. This study aims to identify non-invasive biomarkers for detecting bronchogenic carcinoma and its various stages by analyzing gene expression data using bioinformatics and machine learning techniques. By leveraging these advanced computational methods, we seek to eliminate the need for surgical intervention in the diagnostic process. Methods: We utilized the TCGA-LUAD dataset, including gene expression data from healthy and cancerous samples. To identify robust biomarkers, we applied eight metaheuristic algorithms for feature selection, combined with four classification methods and two data fusion techniques to optimize performance. Results: Our approach achieved 100% accuracy in distinguishing healthy samples from cancerous ones, outperforming existing methods that reported 97% accuracy. Notably, while prior methods have struggled to separate bronchogenic carcinoma stages effectively, our research achieved an approximate accuracy of 77% in stage classification. Furthermore, using gene enrichment methods, we identified 5, 7, and 16 diagnostic biomarker candidates for stages I, II, III, and IV, respectively. Conclusion: This study demonstrates that integrating bioinformatics, gene set enrichment, and biological pathway analysis can enable non-invasive diagnostics for bronchogenic carcinoma stages. These findings hold promise for developing alternatives to traditional, invasive staging systems, potentially improving patient outcomes and reducing healthcare costs. © The Author(s) 2025.

关键词： Biomarker Bronchogenic carcinoma Feature selection algorithms Information fusion Machine learning

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CRISPR/Cas9 editing of p-COUMAROYL-CoA:MONOLIGNOL TRANSFERASE 1 in maize alters phenolic metabolism, lignin structure, and lignin-first biomass processing

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Trends in Biotechnology 2025年第5期43卷 1166-1195页

作者： Oliveira, Dyoni M. Saleme, Marina de L.S. Smith, Rebecca A. Vangeel, Thijs Lima, Marcelo de F. Chanoca, Alexandra A. Mota, Thatiane R. Vanhevel, Yasmine Coussens, Griet Van Aelst, Korneel Geerts, Jordi Cornet, Iris Vaneechoutte, Dries Vandepoele, Klaas Pauwels, Laurens Goeminne, Geert Morreel, Kris Sels, Bert F. Ralph, John Vanholme, Ruben Boerjan, Wout Department of Plant Biotechnology and Bioinformatics Ghent University Ghent Belgium VIB Center for Plant Systems Biology Ghent Belgium Great Lakes Bioenergy Research Center and the Wisconsin Energy Institute University of Wisconsin-Madison MadisonWI United States Department of Microbial and Molecular Systems Center for Sustainable Catalysis and Engineering KU Leuven–University of Leuven Leuven Belgium Biochemical Wastewater Valorization and Engineering Group University of Antwerp Antwerp Belgium VIB Metabolomics Core Ghent Belgium Department of Biochemistry University of Wisconsin MadisonWI United States

Valorization of lignocellulosic biomass for sustainable production of high-value chemicals is challenged by the complexity of lignin, a phenolic biopolymer. Beyond the classical lignin monomers derived from p-coumaryl, coniferyl, and sinapyl alcohol, grass lignins incorporate substantial amounts of monolignol p-coumarates that are produced by p-COUMAROYL-CoA:MONOLIGNOL TRANSFERASE (PMT). Here, the CRISPR/Cas9-mediated mutation of ZmPMT1 in maize enabled the design of biomass depleted in p-coumaroylated lignin and enriched in guaiacyl lignin. Lignin-first biorefining of stem biomass from zmpmt1 mutants by reductive catalytic fractionation (RCF) generated a lignin oil depleted in carboxylates and enriched in guaiacyl-derived alcohols, which are desirable substrates for bio-based polyurethane synthesis. The reported lignin engineering in maize is a promising strategy for designing a dual-purpose crop, providing both food and feed, along with a renewable feedstock for the production of plant-based chemicals. © 2025 Elsevier Ltd

关键词： Saccharification

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Dynamic liquid film nanochannels for adjustable ion and molecule transport

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Nano research 2025年第3期18卷 494-501页

作者： Chunxiao Liang Dianyu Wang Zhe Xu Haitao Deng Fan Xia Ye Tian Key Laboratory of Bioinspired Materials and Interfacial Science Technical Institute of Physics and ChemistryChinese Academy of SciencesBeijing 100190China University of Chinese Academy of Sciences Beijing 100049China School of Chemical Engineering Zhengzhou UniversityZhengzhou 450001China State Key Laboratory of Biogeology and Environmental Geology Engineering Research Center of Nano-Geomaterials of Ministry of EducationFaculty of Materials Science and ChemistryChina University of GeosciencesWuhan 430074China Suzhou Institute for Advanced Research University of Science and Technology of ChinaSuzhou 215123China Qingdao Institute of Bioenergy and Bioprocess Technology Chinese Academy of SciencesQingdao 266101China

Gating,a fundamental feature of biological nanochannels,enables the intelligent regulation of ion and molecule transport in response to specific *** by nature,numerous artificial gating systems have been researched through the functionalization of solid-state ***,these gating systems typically allow only two transitions:“open”and“closed”,which makes it challenging to achieve multi-state ***,we construct dynamic liquid film nanochannels(DLFNs)by inserting an oil droplet into a capillary with gradient wettability that is filled with ionic *** liquid film,formed between the oil and the capillary,functions as a nanochannel for ion and molecule transport,with its height dynamically adjusted through the capillary's gradient *** a deeper level,the variations in liquid film thickness are driven by the interfacial water structure,which is mediated by hydrogen bonding ***,unlike traditional solid-state nanochannels,which involve two phases(liquid/solid),the properties of DLFNs are influenced by three phases(oil/water/solid),resulting in distinct performance characteristics,such as reconfigurability,low cost,and ease of *** work provides an avenue for designing dynamic nanofluids and may spark promising applications of DLFNs with multiscale gating properties in drug delivery,microreactors,sieving,biosensing,and other related fields.

关键词： dynamic liquid film nanochannel gating wettability oil-water-solid interface

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Methacrylic acid/Tween 80 engineered amorphous calcium phosphate as an effective bioactive reinforcing nanofillers in dental adhesive

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Dental Materials Journal 2025年第2期44卷 190-200页

作者： Maimansomsuk, Siripatsorn Teangrom, Paremai Teanchai, Chayada Sinthuvanich, Chomdao Ruengket, Pakorn Attarataya, Jakrada Akkarachaneeyakorn, Khrongkhwan Department of Chemistry Faculty of Science Kasetsart University Bangkok10900 Thailand Center of Excellence for Innovation in Chemistry Faculty of Science Kasetsart University Bangkok10900 Thailand Research Center Faculty of Dentistry Mahidol University Bangkok10400 Thailand Department of Biochemistry Faculty of Science Kasetsart University Bangkok Thailand Faculty of Science Kasetsart University Bangkok Thailand Genetic Engineering and Bioinformatics Program Graduate School Kasetsart University Bangkok Thailand Nakhon Ratchasima30000 Thailand

Bioactive fillers in dental adhesives are designed to release beneficial ions, such as calcium and phosphate, to help in remineralization process, and preventing secondary caries. Their incorporation also aims to improve the longevity of dental restorations. Herein, CaP nanoparticles were synthesized through a water-in-oil emulsion method using Tween80 as a surfactant and methacrylic acid (MAA). MAA officiated as a co-surfactant and reduced the size of CaP nanoparticle, including improved compatibility with the components of dental adhesive. The incorporation of 2% T80/CaP/MAA nanofillers into dental adhesive demonstrated increased efficiency, as evidenced by a higher degree of conversion (%DC) and greater micro-tensile bond strength (μTBS). More importantly, T80/CaP/ MAA nanofillers were able to induce remineralization process in the dental structure, which was confirmed by EDX mapping and IR imaging. Finally, a cytotoxicity assessment of the dental adhesive containing T80/CaP/MAA showed no significant adverse effects on human fibroblast cells. © 2025, Japanese Society for Dental Materials and Devices. All rights reserved.

关键词： Stem cells

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Predicting the physiological effects of multiple drugs using electronic health record

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Computers in Biology and Medicine 2025年 184卷 109485-109485页

作者： Jeon, Junhyeok Hong, Eujin Kim, Jong-Yeup Lee, Suehyun Kim, Hyun Uk Daejeon34141 Korea Republic of Department of Biomedical Informatics College of Medicine Konyang University Daejeon35365 Korea Republic of Healthcare Data Science Center Konyang University Hospital Daejeon35365 Korea Republic of Department of Computer Engineering Gachon University Seongnam13120 Korea Republic of Graduate School of Engineering Biology KAIST Daejeon34141 Korea Republic of BioProcess Engineering Research Center and BioInformatics Research Center KAIST Daejeon34141 Korea Republic of

Various computational models have been developed to understand the physiological effects of drug-drug interactions, which can contribute to more effective drug treatments. However, they mostly focus on interactions of only two drugs, and do not consider the patient information. To address this challenge, we use publicly available electronic health record (EHR), MIMIC-IV, to develop machine learning models that predict the physiological effects of two or more drugs. This study involves extensive preprocessing of laboratory measurement data, prescription data and patient data. The resulting machine learning models predict potential abnormalities across 20 selected measurement items (e.g., concentrations of metabolites and blood cells) in the form of a sentence. Analysis of the model predictions showed that age, specific active pharmaceutical ingredients, and male/female appeared to be the most influential features. The model development process showcased in this study can be extended to other measurement items for a target EHR. © 2024 Elsevier Ltd

关键词： Electronic health record

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An Analytical Paradigm for Exploration of Diabetes Using Machine Learning 19

An Analytical Paradigm for Exploration of Diabetes Using Mac...

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19th International Conference on Ubiquitous Information Management and Communication, IMCOM 2025

作者： Chauhan, Ritu Mishra, Aarushi Mani, Ruchi Jakhmola Yafi, Eiad Zuhairi, Megat F. Artificial Intelligence and IoT Lab Center for Computational Biology and Bioinformatics Amity University UP India Proteomics and Translational Research Lab Center for Medical Biotechnology Amity University UP India Faculty of Engineering and Information Technology University of Technology Sydney Sydney Australia Malaysian Institute of Information Technology University of Kuala Lumpur Kuala Lumpur Malaysia

ISBN: (纸本)9798331507817

Machine Learning is an approach in AI which has swiftly emerged as a transformative and powerful tool in the healthcare industry, changing the methods of diagnosing and predicting diseases. In the present situation, the application of different machine learning methods, including deep learning, ensemble techniques, and natural language processing, across various healthcare activities, such as disease prediction, medical imaging analysis, drug discovery, and tailored treatment suggestions, has offered encouraging prospects for improved diagnostics, treatment, and patient results. By utilizing a diverse range of data sources, including electronic health records, medical imaging, and wearable devices, machine learning algorithms have facilitated early detection, precise prognostication, and customized interventions. The application of machine learning algorithms into health databases is the ongoing area of research concerning future modelling predictions. The current study revolves around the utilization of descriptive analytic methods and machine learning algorithms to predict if an individual is diabetic. The effectiveness of four distinct models of machine learning, specifically Random Forest (RF), Decision Tree (DT), Support Vector Machine (SVM) and K Nearest Neighbor (KNN), is assessed and contrasted. The respective accuracies of these classifiers are noted as 89.83%, 77.16%, 84.84%, 81.16%. © 2025 IEEE.

关键词： Electronic health record

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Genome-wide identification, characterization, and expression analysis of the MADS-box gene family in grass pea (Lathyrus sativus) under salt stress conditions

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BMC Genomics 2025年第1期26卷 1-15页

作者： Abdelsattar, Mohamed Nassar, Ahmed E. Mousa, Khaled H. Hussein, Ahmed El-Baghdady, Manal M. S. Radwan, Khaled H. Ibrahim, Manar S. El Allali, Achraf Hamwieh, Aladdin Alsamman, Alsamman M. Kehel, Zakaria Agricultural Genetic Engineering Research Institute (AGERI) Agricultural Research Center (ARC) Giza Egypt International Center for Agricultural Research in the Dry Areas (ICARDA) Giza Egypt National Biotechnology Network of Expertise ASRT Cairo Egypt Bioinformatics Laboratory College of Computing Mohammed VI Polytechnic University Ben Guerir Morocco Biodiversity and Crop Improvement Program International Center for Agricultural Research in the Dry Areas Rabat Morocco

The MADS-box gene family possesses significant potential to improve crop production under harsh conditions by regulating growth, development, and the expression of floral organs. The grass pea (Lathyrus sativus), a crop grown predominantly in arid and semi-arid regions, could benefit greatly from the functions of MADS-box genes, which are not yet well characterized in this promising plant. In this study, a comprehensive analysis of all MADS-box genes in grass pea was performed at both the genomic and transcriptomic levels. A total of 46 genes were identified and classified based on their MADS-box domains. A comparative phylogenetic analysis with apple, Arabidopsis, and rice categorized the grass pea genes into 31 type I genes (M $$\alpha$$ , M $$\beta$$ , M $$\gamma$$ ) and 15 type II genes (MIKCc, MIKC*). Annotation analysis revealed variations in the intron-exon structures of the genes, with most type I genes being intronless. Ten distinct conserved motifs were identified across the genes. Structural analysis revealed the presence of MEF2-like and SRF-TF domains in the grass pea proteins. Protein-protein interaction analysis revealed extensive interactions among type II MADS-box genes, while enrichment analysis showed their involvement in various aspects of plant life, particularly floral organ development. Examination of the cis-elements in the promoter regions of the genes revealed up to 76 potential cis-elements, which were categorized into four groups based on their putative role in transcriptional regulation. RNA-seq was used to profile gene expression under different conditions to gain insights into their potential functional significance. Quantitative PCR (qPCR) analysis validated the expression levels of eight selected genes (LSMADS_D1, LSMADS_R5, LSMADS_R7, LSMADS_R9, LSMADS_D11, LSMADS_D13, LSMADS_R13, and LSMADS_D29) under salt stress conditions and confirmed their involvement in stress responses. This study represents the first genome-wide exploration

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Complete mitogenome of the critically endangered Asian king vulture (Sarcogyps calvus) (Aves, Accipitriformes, Accipitridae): evolutionary insights and comparative analysis

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ZooKeys 2025年 1234卷 47-65页

作者： Buthasane, Wannapol Tangphatsornruang, Sithichoke Jenjaroenpun, Piroon Wongsurawat, Thidathip Sanannu, Saowaphang Shotelersuk, Vorasuk Suriyaphol, Gunnaporn Biochemistry Unit Department of Physiology Faculty of Veterinary Science Chulalongkorn University Bangkok 10330 Thailand National Omics Center National Center for Genetic Engineering and Biotechnology (BIOTEC) National Science and Technology Development Agency Pathum Thani 12120 Thailand Division of Medical Bioinformatics Research Department Faculty of Medicine Siriraj Hospital Mahidol University Bangkok 10700 Thailand Animal Conservation and Research Institute The Zoological Park Organization of Thailand Bangkok 10300 Thailand Center of Excellence for Medical Genomics Medical Genomics Cluster Department of Pediatrics Faculty of Medicine Chulalongkorn University Bangkok 10330 Thailand Excellence Center for Genomics and Precision Medicine King Chulalongkorn Memorial Hospital The Thai Red Cross Society Bangkok 10330 Thailand

The Asian king vulture (Sarcogyps calvus), also known as the red-headed vulture, is an Old World vulture (Gypini) facing severe population declines. This study aimed to assemble the complete mitogenome of S. calvus, explore its phylogenetic relationships, estimate divergence times, and examine genetic distances and amino acid substitutions. The mitogenome was de novo assembled from genomic DNA extracted from the blood of a female S. calvus. Phylogenetic and pairwise genetic distance analyses were conducted, comparing S. calvus with other members of Gypini, New World vultures (Cathartidae) and various other birds. The assembled mitogenome was 17,750 base pairs in length, comprising 13 protein-coding genes (PCGs), 22 transfer RNA genes, two ribosomal RNA genes and two control regions. Most PCGs used the ATG start codon, except for cytochrome c oxidase subunit 1 (COX1), which employed GTG. Phylogenetic analysis revealed a close genetic relationship between S. calvus and other members of Gypini, with an estimated divergence time of 16.7 million years ago. Genetic distance analysis indicated that S. calvus was more closely related to other Gypini, as well as to Spilornis cheela and Circaetus pectoralis (Circaetini)), than to Cathartidae. Conserved amino acid substitutions between Gypini and Cathartidae were primarily observed in the NADH-ubiquinone oxidoreductase chain 1 (ND1) gene. This study provided the first complete mitogenome of S. calvus, offering new insights into its genomic structure, evolutionary history, and genetic relationships. © Wannapol Buthasane et al.

关键词： Asian king vulture comparative analysis evolution mitogenome Sarcogyps calvus

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