{"title":"Scouring for essential non-coding RNAs","authors":"Pep Pàmies","doi":"10.1038/s41551-024-01328-x","DOIUrl":"https://doi.org/10.1038/s41551-024-01328-x","url":null,"abstract":"RNA-targeting CRISPR screens reveal hundreds of functional long non-coding RNAs that are crucial for cell survival and implicated in cancer progression.","PeriodicalId":19063,"journal":{"name":"Nature Biomedical Engineering","volume":"250 1","pages":""},"PeriodicalIF":28.1,"publicationDate":"2024-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142825062","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A learned writing assistant for radiologists","authors":"Pep Pàmies","doi":"10.1038/s41551-024-01327-y","DOIUrl":"https://doi.org/10.1038/s41551-024-01327-y","url":null,"abstract":"A large vision–language model trained to generate chest X-ray reports shows promise as an assistive tool for radiologists, particularly for typical cases in outpatient settings.","PeriodicalId":19063,"journal":{"name":"Nature Biomedical Engineering","volume":"6 1","pages":""},"PeriodicalIF":28.1,"publicationDate":"2024-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142825215","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Yifei Du, Philipp Konrad Zuber, Huajuan Xiao, Xueyan Li, Yuliya Gordiyenko, V. Ramakrishnan
{"title":"Efficient circular RNA synthesis for potent rolling circle translation","authors":"Yifei Du, Philipp Konrad Zuber, Huajuan Xiao, Xueyan Li, Yuliya Gordiyenko, V. Ramakrishnan","doi":"10.1038/s41551-024-01306-3","DOIUrl":"https://doi.org/10.1038/s41551-024-01306-3","url":null,"abstract":"<p>Circular RNA (circRNA) is a candidate for next-generation messenger RNA therapeutics owing to its remarkable stability. Here we describe <i>trans</i>-splicing-based methods for the synthesis of circRNAs over 8,000 nucleotides. The methods are independent of bacterial sequences, outperform the permuted intron–exon method and allow for the incorporation of RNA modifications. The resulting unmodified circRNAs, which incorporate sequences from human 28S ribosomal RNA, display low immunogenicity and are translated more efficiently than permuted intron–exon-derived circRNAs. Additionally, by using viral internal ribosomal entry sites for rolling circle translation, we show that ribosomes can efficiently read through highly structured internal ribosomal entry sites, enhancing the efficiency of rolling circle translation by over 7,000-fold with respect to previous constructs. The efficient and reliable production of circRNA may facilitate its therapeutic use.</p>","PeriodicalId":19063,"journal":{"name":"Nature Biomedical Engineering","volume":"29 1","pages":""},"PeriodicalIF":28.1,"publicationDate":"2024-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142815724","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Publisher Correction: Targeting overexpressed antigens in glioblastoma via CAR T cells with computationally designed high-affinity protein binders","authors":"Zhen Xia, Qihan Jin, Zhilin Long, Yexuan He, Fuyi Liu, Chengfang Sun, Jinyang Liao, Chun Wang, Chentong Wang, Jian Zheng, Weixi Zhao, Tianxin Zhang, Jeremy N. Rich, Yongdeng Zhang, Longxing Cao, Qi Xie","doi":"10.1038/s41551-024-01338-9","DOIUrl":"https://doi.org/10.1038/s41551-024-01338-9","url":null,"abstract":"<p>Correction to: <i>Nature Biomedical Engineering</i> https://doi.org/10.1038/s41551-024-01258-8, published online 17 October 2024.</p>","PeriodicalId":19063,"journal":{"name":"Nature Biomedical Engineering","volume":"25 1","pages":""},"PeriodicalIF":28.1,"publicationDate":"2024-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142804862","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Aristeidis Papargyriou, Mulham Najajreh, David P. Cook, Carlo H. Maurer, Stefanie Bärthel, Hendrik A. Messal, Sakthi K. Ravichandran, Till Richter, Moritz Knolle, Thomas Metzler, Akul R. Shastri, Rupert Öllinger, Jacob Jasper, Laura Schmidleitner, Surui Wang, Christian Schneeweis, Hellen Ishikawa-Ankerhold, Thomas Engleitner, Laura Mataite, Mariia Semina, Hussein Trabulssi, Sebastian Lange, Aashreya Ravichandra, Maximilian Schuster, Sebastian Mueller, Katja Peschke, Arlett Schäfer, Sophie Dobiasch, Stephanie E. Combs, Roland M. Schmid, Andreas R. Bausch, Rickmer Braren, Irina Heid, Christina H. Scheel, Günter Schneider, Anja Zeigerer, Malte D. Luecken, Katja Steiger, Georgios Kaissis, Jacco van Rheenen, Fabian J. Theis, Dieter Saur, Roland Rad, Maximilian Reichert
{"title":"Heterogeneity-driven phenotypic plasticity and treatment response in branched-organoid models of pancreatic ductal adenocarcinoma","authors":"Aristeidis Papargyriou, Mulham Najajreh, David P. Cook, Carlo H. Maurer, Stefanie Bärthel, Hendrik A. Messal, Sakthi K. Ravichandran, Till Richter, Moritz Knolle, Thomas Metzler, Akul R. Shastri, Rupert Öllinger, Jacob Jasper, Laura Schmidleitner, Surui Wang, Christian Schneeweis, Hellen Ishikawa-Ankerhold, Thomas Engleitner, Laura Mataite, Mariia Semina, Hussein Trabulssi, Sebastian Lange, Aashreya Ravichandra, Maximilian Schuster, Sebastian Mueller, Katja Peschke, Arlett Schäfer, Sophie Dobiasch, Stephanie E. Combs, Roland M. Schmid, Andreas R. Bausch, Rickmer Braren, Irina Heid, Christina H. Scheel, Günter Schneider, Anja Zeigerer, Malte D. Luecken, Katja Steiger, Georgios Kaissis, Jacco van Rheenen, Fabian J. Theis, Dieter Saur, Roland Rad, Maximilian Reichert","doi":"10.1038/s41551-024-01273-9","DOIUrl":"https://doi.org/10.1038/s41551-024-01273-9","url":null,"abstract":"<p>In patients with pancreatic ductal adenocarcinoma (PDAC), intratumoural and intertumoural heterogeneity increases chemoresistance and mortality rates. However, such morphological and phenotypic diversities are not typically captured by organoid models of PDAC. Here we show that branched organoids embedded in collagen gels can recapitulate the phenotypic landscape seen in murine and human PDAC, that the pronounced molecular and morphological intratumoural and intertumoural heterogeneity of organoids is governed by defined transcriptional programmes (notably, epithelial-to-mesenchymal plasticity), and that different organoid phenotypes represent distinct tumour-cell states with unique biological features in vivo. We also show that phenotype-specific therapeutic vulnerabilities and modes of treatment-induced phenotype reprogramming can be captured in phenotypic heterogeneity maps. Our methodology and analyses of tumour-cell heterogeneity in PDAC may guide the development of phenotype-targeted treatment strategies.</p>","PeriodicalId":19063,"journal":{"name":"Nature Biomedical Engineering","volume":"19 1","pages":""},"PeriodicalIF":28.1,"publicationDate":"2024-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142797016","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Benyamin Haghi, Tyson Aflalo, Spencer Kellis, Charles Guan, Jorge A. Gamez de Leon, Albert Yan Huang, Nader Pouratian, Richard A. Andersen, Azita Emami
{"title":"Enhanced control of a brain–computer interface by tetraplegic participants via neural-network-mediated feature extraction","authors":"Benyamin Haghi, Tyson Aflalo, Spencer Kellis, Charles Guan, Jorge A. Gamez de Leon, Albert Yan Huang, Nader Pouratian, Richard A. Andersen, Azita Emami","doi":"10.1038/s41551-024-01297-1","DOIUrl":"https://doi.org/10.1038/s41551-024-01297-1","url":null,"abstract":"<p>To infer intent, brain–computer interfaces must extract features that accurately estimate neural activity. However, the degradation of signal quality over time hinders the use of feature-engineering techniques to recover functional information. By using neural data recorded from electrode arrays implanted in the cortices of three human participants, here we show that a convolutional neural network can be used to map electrical signals to neural features by jointly optimizing feature extraction and decoding under the constraint that all the electrodes must use the same neural-network parameters. In all three participants, the neural network led to offline and online performance improvements in a cursor-control task across all metrics, outperforming the rate of threshold crossings and wavelet decomposition of the broadband neural data (among other feature-extraction techniques). We also show that the trained neural network can be used without modification for new datasets, brain areas and participants.</p>","PeriodicalId":19063,"journal":{"name":"Nature Biomedical Engineering","volume":"13 1","pages":""},"PeriodicalIF":28.1,"publicationDate":"2024-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142782730","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Simple and effective embedding model for single-cell biology built from ChatGPT","authors":"Yiqun Chen, James Zou","doi":"10.1038/s41551-024-01284-6","DOIUrl":"https://doi.org/10.1038/s41551-024-01284-6","url":null,"abstract":"<p>Large-scale gene-expression data are being leveraged to pretrain models that implicitly learn gene and cellular functions. However, such models require extensive data curation and training. Here we explore a much simpler alternative: leveraging ChatGPT embeddings of genes based on the literature. We used GPT-3.5 to generate gene embeddings from text descriptions of individual genes and to then generate single-cell embeddings by averaging the gene embeddings weighted by each gene’s expression level. We also created a sentence embedding for each cell by using only the gene names ordered by their expression level. On many downstream tasks used to evaluate pretrained single-cell embedding models—particularly, tasks of gene-property and cell-type classifications—our model, which we named GenePT, achieved comparable or better performance than models pretrained from gene-expression profiles of millions of cells. GenePT shows that large-language-model embeddings of the literature provide a simple and effective path to encoding single-cell biological knowledge.</p>","PeriodicalId":19063,"journal":{"name":"Nature Biomedical Engineering","volume":"4 1","pages":""},"PeriodicalIF":28.1,"publicationDate":"2024-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142782732","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Charles M. Greenspon, Giacomo Valle, Natalya D. Shelchkova, Taylor G. Hobbs, Ceci Verbaarschot, Thierri Callier, Ev I. Berger-Wolf, Elizaveta V. Okorokova, Brianna C. Hutchison, Efe Dogruoz, Anton R. Sobinov, Patrick M. Jordan, Jeffrey M. Weiss, Emily E. Fitzgerald, Dillan Prasad, Ashley Van Driesche, Qinpu He, Fang Liu, Robert F. Kirsch, Jonathan P. Miller, Ray C. Lee, David Satzer, Jorge Gonzalez-Martinez, Peter C. Warnke, Abidemi B. Ajiboye, Emily L. Graczyk, Michael L. Boninger, Jennifer L. Collinger, John E. Downey, Lee E. Miller, Nicholas G. Hatsopoulos, Robert A. Gaunt, Sliman J. Bensmaia
{"title":"Evoking stable and precise tactile sensations via multi-electrode intracortical microstimulation of the somatosensory cortex","authors":"Charles M. Greenspon, Giacomo Valle, Natalya D. Shelchkova, Taylor G. Hobbs, Ceci Verbaarschot, Thierri Callier, Ev I. Berger-Wolf, Elizaveta V. Okorokova, Brianna C. Hutchison, Efe Dogruoz, Anton R. Sobinov, Patrick M. Jordan, Jeffrey M. Weiss, Emily E. Fitzgerald, Dillan Prasad, Ashley Van Driesche, Qinpu He, Fang Liu, Robert F. Kirsch, Jonathan P. Miller, Ray C. Lee, David Satzer, Jorge Gonzalez-Martinez, Peter C. Warnke, Abidemi B. Ajiboye, Emily L. Graczyk, Michael L. Boninger, Jennifer L. Collinger, John E. Downey, Lee E. Miller, Nicholas G. Hatsopoulos, Robert A. Gaunt, Sliman J. Bensmaia","doi":"10.1038/s41551-024-01299-z","DOIUrl":"https://doi.org/10.1038/s41551-024-01299-z","url":null,"abstract":"<p>Tactile feedback from brain-controlled bionic hands can be partially restored via intracortical microstimulation (ICMS) of the primary somatosensory cortex. In ICMS, the location of percepts depends on the electrode’s location and the percept intensity depends on the stimulation frequency and amplitude. Sensors on a bionic hand can thus be linked to somatotopically appropriate electrodes, and the contact force of each sensor can be used to determine the amplitude of a stimulus. Here we report a systematic investigation of the localization and intensity of ICMS-evoked percepts in three participants with cervical spinal cord injury. A retrospective analysis of projected fields showed that they were typically composed of a focal hotspot with diffuse borders, arrayed somatotopically in keeping with their underlying receptive fields and stable throughout the duration of the study. When testing the participants’ ability to rapidly localize a single ICMS presentation, individual electrodes typically evoked only weak sensations, making object localization and discrimination difficult. However, overlapping projected fields from multiple electrodes produced more localizable and intense sensations and allowed for a more precise use of a bionic hand.</p>","PeriodicalId":19063,"journal":{"name":"Nature Biomedical Engineering","volume":"27 1","pages":""},"PeriodicalIF":28.1,"publicationDate":"2024-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142782735","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A foundation model for enhancing magnetic resonance images and downstream segmentation, registration and diagnostic tasks","authors":"Yue Sun, Limei Wang, Gang Li, Weili Lin, Li Wang","doi":"10.1038/s41551-024-01283-7","DOIUrl":"https://doi.org/10.1038/s41551-024-01283-7","url":null,"abstract":"<p>In structural magnetic resonance (MR) imaging, motion artefacts, low resolution, imaging noise and variability in acquisition protocols frequently degrade image quality and confound downstream analyses. Here we report a foundation model for the motion correction, resolution enhancement, denoising and harmonization of MR images. Specifically, we trained a tissue-classification neural network to predict tissue labels, which are then leveraged by a ‘tissue-aware’ enhancement network to generate high-quality MR images. We validated the model’s effectiveness on a large and diverse dataset comprising 2,448 deliberately corrupted images and 10,963 images spanning a wide age range (from foetuses to elderly individuals) acquired using a variety of clinical scanners across 19 public datasets. The model consistently outperformed state-of-the-art algorithms in improving the quality of MR images, handling pathological brains with multiple sclerosis or gliomas, generating 7-T-like images from 3 T scans and harmonizing images acquired from different scanners. The high-quality, high-resolution and harmonized images generated by the model can be used to enhance the performance of models for tissue segmentation, registration, diagnosis and other downstream tasks.</p>","PeriodicalId":19063,"journal":{"name":"Nature Biomedical Engineering","volume":"53 1","pages":""},"PeriodicalIF":28.1,"publicationDate":"2024-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142776905","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Andi Pan, Charles C. Bailey, Tianling Ou, Jinge Xu, Tonia Aristotelous, Xin Liu, Baodan Hu, Gogce Crynen, Nickolas Skamangas, Naomi Bronkema, Mai H. Tran, Huihui Mou, Xia Zhang, Michael D. Alpert, Yiming Yin, Michael Farzan, Wenhui He
{"title":"In vivo affinity maturation of the CD4 domains of an HIV-1-entry inhibitor","authors":"Andi Pan, Charles C. Bailey, Tianling Ou, Jinge Xu, Tonia Aristotelous, Xin Liu, Baodan Hu, Gogce Crynen, Nickolas Skamangas, Naomi Bronkema, Mai H. Tran, Huihui Mou, Xia Zhang, Michael D. Alpert, Yiming Yin, Michael Farzan, Wenhui He","doi":"10.1038/s41551-024-01289-1","DOIUrl":"https://doi.org/10.1038/s41551-024-01289-1","url":null,"abstract":"<p>Human proteins repurposed as biologics for clinical use have been engineered through in vitro techniques that improve the affinity of the biologics for their ligands. However, the techniques do not select against properties, such as protease sensitivity or self-reactivity, that impair the biologics’ clinical efficacy. Here we show that the B-cell receptors of primary murine B cells can be engineered to affinity mature in vivo the human CD4 domains of the HIV-1-entry inhibitor CD4 immunoadhesin (CD4-Ig). Specifically, we introduced genes encoding the CD4 domains 1 and 2 (D1D2) of a half-life-enhanced form of CD4-Ig (CD4-Ig-v0) into the heavy-chain loci of murine B cells and adoptively transferred these cells into wild-type mice. After immunization, the B cells proliferated, class switched, affinity matured and produced D1D2-presenting antibodies. Somatic hypermutations in the D1D2-encoding region of the engrafted cells improved the binding affinity of CD4-Ig-v0 for the HIV-1 envelope glycoprotein and the inhibitor’s ability to neutralize a panel of HIV-1 isolates without impairing its pharmacokinetic properties. In vivo affinity maturation of non-antibody protein biologics may guide the development of more effective therapeutics.</p>","PeriodicalId":19063,"journal":{"name":"Nature Biomedical Engineering","volume":"47 1","pages":""},"PeriodicalIF":28.1,"publicationDate":"2024-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142776906","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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