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Corrigendum to "Effect of cell imprinting on viability and drug susceptibility of breast cancer cells to doxorubicin" [Acta Biomaterialia, 2020, 113, 119-129] (Acta Biomaterialia (2020) 113 (119–129), (S1742706120303287), (10.1016/***.2020.06.007))

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Acta Biomaterialia 2025年 198卷 571-572页

作者： Shahriyari, Fatemeh Janmaleki, Mohsen Sharifi, Shahriar Hesar, Milad Eyvazi Hoshian, Sasha Taghiabadi, Reza Razaghian, Ahmad Ghadiri, Majid Peirovi, Afshin Mahmoudi, Morteza Nezhad, Amir Sanati Khademhosseini, Ali Division of Engineering in Medicine Department of Medicine Brigham and Women's Hospital Harvard Medical School CambridgeMA United States Division of Health Sciences & Technology Harvard-Massachusetts Institute of Technology Massachusetts Institute of Technology CambridgeMA United States Department of Materials Engineering Faculty of Engineering Imam Khomeini International University Qazvin Iran Biomedical Engineering Graduate Program University of Calgary Canada Precision Health Program and Department of Radiology Michigan State University East LansingMI48824 United States RWTH Aachen University Templergraben 55 Aachen52062 Germany Department of Chemistry and Materials Science Aalto University School of Chemical Engineering Espoo Finland Department of Mechanical Engineering Faculty of Engineering Imam Khomeini International University Qazvin Iran Nano-Biotechnology Department Pasteur Institute of Iran Tehran Iran Departments of Bioengineering Chemical and Biomolecular Engineering and Radiological Sciences Center for Minimally Invasive Therapeutics California NanoSystems Institute University of California – Los Angeles Los AngelesCA United States Terasaki Institute for Biomedical Innovation Los AngelesCA United States

The authors regret to report that the images for panels h (Plain PDMS) and I (MCF7-imprinted PDMS) in Fig. 3 were mistakenly taken from the same dataset, resulting in the omission of the correct image in panel h for the Plain PDMS day 7 image. We sincerely apologize for this error. For an accurate representation, please see the corrected Fig. 3 provided here along with its original figure caption. This does not affect the validity of the statistical analyses or the overall conclusions drawn from the study. © 2025

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Randomizing the human genome by engineering recombination between repeat elements

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Science (New York, N.Y.) 2025年第6733期387卷 eado3979页

作者： Koeppel, Jonas Ferreira, Raphael Vanderstichele, Thomas Riedmayr, Lisa Maria Peets, Elin Madli Girling, Gareth Weller, Juliane Murat, Pierre Liberante, Fabio Giuseppe Ellis, Tom Church, George McDonald Parts, Leopold Hinxton United Kingdom Harvard Medical School Department of Genetics Boston MA United States Wyss Institute for Biologically Inspired Engineering Harvard University Boston MA United States Broad Institute of Massachusetts Institute of Technology and Harvard University Cambridge MA United States Department of Bioengineering Imperial College London London United Kingdom Harvard-MIT Program in Health Sciences and Technology Cambridge MA United States Harvard Medical School Boston MA United States

We lack tools to edit DNA sequences at scales necessary to study 99% of the human genome that is noncoding. To address this gap, we applied CRISPR prime editing to insert recombination handles into repetitive sequences, up to 1697 per cell line, which enables generating large-scale deletions, inversions, translocations, and circular DNA. Recombinase induction produced more than 100 stochastic megabase-sized rearrangements in each cell. We tracked these rearrangements over time to measure selection pressures, finding a preference for shorter variants that avoided essential genes. We characterized 29 clones with multiple rearrangements, finding an impact of deletions on expression of genes in the variant but not on nearby genes. This genome-scrambling strategy enables large deletions, sequence relocations, and the insertion of regulatory elements to explore genome dispensability and organization.

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Longitudinal profiling of low-abundance strains in microbiomes with ChronoStrain

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Nature Microbiology 2025年第5期10卷 1184-1197页

作者： Kim, Younhun Worby, Colin J. Acharya, Sawal van Dijk, Lucas R. Alfonsetti, Daniel Gromko, Zackary Azimzadeh, Philippe N. Dodson, Karen W. Gerber, Georg K. Hultgren, Scott J. Earl, Ashlee M. Berger, Bonnie Gibson, Travis E. Department of Mathematics Massachusetts Institute of Technology Cambridge MA United States Department of Pathology Brigham and Women’s Hospital Boston MA United States Broad Institute of MIT and Harvard Cambridge MA United States Harvard Medical School Boston MA United States Delft Bioinformatics Lab Delft University of Technology Delft Netherlands Computer Science and AI Lab Massachusetts Institute of Technology Cambridge MA United States Department of Molecular Microbiology and Center for Women’s Infectious Disease Research Washington University School of Medicine St Louis MO United States Harvard-MIT Health Sciences and Technology Cambridge MA United States

The ability to detect and quantify microbiota over time from shotgun metagenomic data has a plethora of clinical, basic science and public health applications. Given these applications, and the observation that pathogens and other taxa of interest can reside at low relative abundance, there is a critical need for algorithms that accurately profile low-abundance microbial taxa with strain-level resolution. Here we present ChronoStrain: a sequence quality- and time-aware Bayesian model for profiling strains in longitudinal samples. ChronoStrain explicitly models the presence or absence of each strain and produces a probability distribution over abundance trajectories for each strain. Using synthetic and semi-synthetic data, we demonstrate how ChronoStrain outperforms existing methods in abundance estimation and presence/absence prediction. Applying ChronoStrain to two human microbiome datasets demonstrated its improved interpretability for profiling Escherichia coli strain blooms in longitudinal faecal samples from adult women with recurring urinary tract infections, and its improved accuracy for detecting Enterococcus faecalis strains in infant faecal samples. Compared with state-of-the-art methods, ChronoStrain’s ability to detect low-abundance taxa is particularly stark. © The Author(s), under exclusive licence to Springer Nature Limited 2025.

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Implementation of a Digital Disease Management Platform for Heart Failure: AMAZE

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Journal of Cardiac Failure 2025年第5期31卷 863-867页

作者： PARUCHURI, KAAVYA BERNARDO, RACHEL HAIDERMOTA, S.A.R.A. LANNERY, K.I.M. FINNERAN, PHOEBE WONG, MEGAN SANBORN, TINAMARIE JOICE, MELVIN BOYLE-KELLY, JANET SILACCI, S.A.R.A. HORNSBY, WHITNEY LINGANATHAN, KARTHIK OLUFADE, T.O.P.E. JANUZZI, JAMES L. NATARAJAN, PRADEEP Cardiovascular Research Center Massachusetts General Hospital Boston MA United States Cardiovascular Disease Prevention Center Massachusetts General Hospital Boston MA United States Program in Medical and Population Genetics and Cardiovascular Disease Initiative Broad Institute of Harvard and MIT Cambridge MA United States Department of Medicine Harvard Medical School Boston MA United States The George Washington University School of Medicine and Health Sciences Washington D.C. United States Western University of Health Sciences College of Osteopathic Medicine of the Pacific Pomona CA United States Hospital Medicine Unit Massachusetts General Hospital Boston MA United States Center for Innovation in Digital Health Massachusetts General Hospital Boston MA United States AstraZeneca 1800 Concord Pike Wilmington DE United States Division of Cardiology Department of Medicine Massachusetts General Hospital Boston MA United States Baim Institute for Clinical Research Boston MA United States

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Molecular-driven Foundation Model for Oncologic Pathology

arXiv

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arXiv 2025年

作者： Vaidya, Anurag Zhang, Andrew Jaume, Guillaume Song, Andrew H. Ding, Tong Wagner, Sophia J. Lu, Ming Y. Doucet, Paul Robertson, Harry Almagro-Pérez, Cristina Chen, Richard J. ElHarouni, Dina Ayoub, Georges Bossi, Connor Ligon, Keith L. Gerber, Georg Le, Long Phi Mahmood, Faisal Department of Pathology Brigham and Women’s Hospital Harvard Medical School BostonMA United States Department of Pathology Massachusetts General Hospital Harvard Medical School BostonMA United States Cancer Program Broad Institute of Harvard and MIT CambridgeMA United States Health Sciences and Technology Harvard-MIT CambridgeMA United States Harvard John A. Paulson School of Engineering and Applied Sciences Harvard University CambridgeMA United States Helmholtz Munich – German Research Center for Environment and Health Munich Germany School of Computation Information and Technology TUM Munich Germany CambridgeMA United States Sydney Precision Data Science Center The University of Sydney CamperdownNSW Australia Department of Oncologic Pathology Dana-Farber Cancer Institute BostonMA02215 United States Department of Pathology Boston Children’s Hospital BostonMA02115 United States Harvard Data Science Initiative Harvard University CambridgeMA United States

Foundation models are reshaping computational pathology by enabling transfer learning, where models pre-trained on vast datasets can be adapted for downstream diagnostic, prognostic, and therapeutic response tasks. Despite these advances, foundation models are still limited in their ability to encode the entire gigapixel whole-slide images without additional training and often lack complementary multimodal data. Here, we introduce THREADS, a slide-level foundation model capable of generating universal representations of whole-slide images of any size. THREADS was pretrained using a multimodal learning approach on a diverse cohort of 47,171 hematoxylin and eosin (H&E)-stained tissue sections, paired with corresponding genomic and transcriptomic profiles—the largest such paired dataset to be used for foundation model development to date. This unique training paradigm enables THREADS to capture the tissue’s underlying molecular composition, yielding powerful representations applicable to a wide array of downstream tasks. In extensive benchmarking across 54 oncology tasks, including clinical subtyping, grading, mutation prediction, immunohistochemistry status determination, treatment response prediction and survival prediction THREADS outperformed all baselines while demonstrating remarkable generalizability and label efficiency. It is particularly well-suited for predicting rare events, further emphasizing its clinical utility. We intend to make the model publicly available for the broader community. © 2025, CC BY-NC-ND.

关键词： Transfer learning

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ELECTROPORATION IN CELLS AND TISSUES - A BIOPHYSICAL PHENOMENON DUE TO ELECTROMAGNETIC-FIELDS

引用

RADIO SCIENCE 1995年第1期30卷 205-221页

作者： WEAVER, JC Harvard-MIT Division of Health Sciences and Technology Massachusetts Institute of Technology Cambridge

The effect of ''strong'' electromagnetic fields on cells and tissue can be dramatic but not necessarily harmful. The essentially universal biophysical phenomenon of ''electroporation'' occurs if an applied field causes the cell transmembrane voltage to reach about 0.5-1 V in a time of microseconds to milliseconds. Ordinarily the cell membrane is a formidable barrier to the transport of ions and charged molecules. However, electroporation results in a large increase in transmembrane conductance, which is believed to be caused by ion transport through temporary membrane openings (''pores''). This high-conductance state limits the transmembrane voltage and thereby protects the membrane. A large increase in molecular transport generally occurs for the same conditions and allows polar molecules to be introduced into cells. Similar enhanced molecular transport can be caused in living tissues. Not only cell membranes, but also cell layers or even the stratum corneum of human skin can be temporarily altered by the electrical creation of aqueous pathways. The mechanism of electroporation is partially understood, in that the electrical and mechanical behavior of artificial planar bilayer membranes can be described quantitatively by a theoretical model based on transient aqueous pores. More complex behavior in cell membranes may be due to both the complicated shapes of cell membranes and the additional participation of metastable pores and interactions with cell structures. In the case of tissues the situation is even more complex and has only recently begun to be studied but has the prospect of providing a new approach to transporting polar molecules across tissue barriers.

关键词： Weaving Cells (biology) Electric fields Transient analysis Biomembranes Ions Fluctuations

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Cutting edge acoustics

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IEEE Potentials 1999年第5期17卷 17-20页

作者： Daum, Douglas R. Hynynen, Kullervo MIT/Harvard Div of Health Sciences and Technology

Researchers have been investigating the use of ultrasound imaging to guide, monitor and control ultrasound therapy. This could greatly reduce the cost of treatment guidance and make it more accessible to patients. Ultrasound is a proven method to noninvasively image deep-seated tissue to align a therapeutic transducer and a target tissue. Ultrasonic imaging measurements of low temperature elevations have also been demonstrated in various materials.

关键词： Ultrasonic imaging

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BPS2025 - Time-resolved high-pressure freezing for dynamic, nanoscale imaging

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Biophysical Journal 2025年第3期124卷 312a-312a页

作者： Ami U. Thakrar Daphne-Eleni Archonta Maxim B. Prigozhin Harvard-MIT Program in Health Sciences and Technology Massachusetts Institute of Technology Cambridge MA USA Department of Molecular and Cellular Biology Harvard University Cambridge MA USA Bioengineering Program Harvard University Cambridge MA USA Applied Physics Program Harvard University Cambridge MA USA

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BPS2025 - VIS-À-VIS: Visualization and vitrification of sub-second cellular dynamics

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Biophysical Journal 2025年第3期124卷 172a-172a页

作者： Daphne-Eleni Archonta Ami U. Thakrar Maxim B. Prigozhin Harvard John A. Paulson School Of Engineering and Applied Sciences Harvard University Cambridge MA USA Harvard-MIT Program in Health Sciences and Technology Massachusetts Institute of Technology Cambridge MA USA Department of Molecular and Cellular Biology Harvard University Cambridge MA USA

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Targeted degradation of CDK9 potently disrupts the MYC-regulated network

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Cell Chemical Biology 2025年第4期32卷 542-555.e10页

作者： Toure, Mohammed A. Motoyama, Keisuke Xiang, Yichen Urgiles, Julie Kabinger, Florian Koglin, Ann-Sophie Iyer, Ramya S. Gagnon, Kaitlyn Kumar, Amruth Ojeda, Samuel Harrison, Drew A. Rees, Matthew G. Roth, Jennifer A. Ott, Christopher J. Schiavoni, Richard Whittaker, Charles A. Levine, Stuart S. White, Forest M. Calo, Eliezer Richters, Andre Koehler, Angela N. Koch Institute for Integrative Cancer Research Massachusetts Institute of Technology 500 Main Street Cambridge 02139 MA United States Department of Biological Engineering Massachusetts Institute of Technology Cambridge 02139 MA United States MIT Center for Precision Cancer Medicine Massachusetts Institute of Technology Cambridge 02139 MA United States Broad Institute of MIT and Harvard Cambridge 04142 MA United States Harvard-MIT Health Sciences and Technology Boston 02115 MA United States Massachusetts General Hospital Cancer Center Charlestown 02129 MA United States Department of Medicine Harvard Medical School Boston 02115 MA United States MIT BioMicro Center Department of Biology Massachusetts Institute of Technology Cambridge 02139 MA United States Department of Biology Massachusetts Institute of Technology Cambridge 02139 MA United States

CDK9 coordinates signaling events that regulate transcription and is implicated in oncogenic pathways, making it an actionable target for drug development. While numerous CDK9 inhibitors have been developed, success in the clinic has been limited. Targeted degradation offers a promising alternative. A comprehensive evaluation of degradation versus inhibition is needed to assess when degradation might offer superior therapeutic outcomes. We report a selective and potent CDK9 degrader with rapid kinetics, comparing its downstream effects to those of a conventional inhibitor. We validated that CDK9 inhibition triggers a compensatory feedback mechanism that dampens its anticipated effect on MYC expression and found that this was absent when degraded. Importantly, degradation is more effective at disrupting MYC transcriptional regulation and subsequently destabilizing nucleolar homeostasis, likely by abrogation of both enzymatic and scaffolding functions of CDK9. These findings suggest that CDK9 degradation offers a more robust strategy to overcome limitations associated with its inhibition. © 2025 The Authors

关键词： cancer therapy CDK9 degradation vs. inhibition MYC PROTAC targeted degradation transcription

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