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Article
Multidisciplinary Sciences
Meredith Wadman
Article
Oncology
Christophe Deben et al.
Summary: A high-throughput and automated live-cell image analysis software called OrBITS was developed for kinetic monitoring of organoids. The software combines computer vision with convolutional network machine learning and was validated against standard assays. Using OrBITS, the drug screening of lung and pancreatic cancer treatments provided further insights into the drugs' mechanism of action.
Article
Biotechnology & Applied Microbiology
Chang Qiao et al.
Summary: In this study, a rationalized deep learning (rDL) method was developed for improving optical microscopy imaging by addressing artifacts and noise. By incorporating prior knowledge of illumination patterns, the rDL method effectively denoises raw images and enhances the super-resolution information. Moreover, the method can perform self-supervised training using the continuity of noisy data itself, achieving results comparable to supervised methods.
NATURE BIOTECHNOLOGY
(2023)
Article
Biotechnology & Applied Microbiology
Xinyang Li et al.
Summary: DeepCAD-RT is a real-time denoising method for fluorescence time-lapse images, which uses self-supervised deep learning for noise suppression. Compared to traditional methods, DeepCAD-RT significantly reduces the number of network parameters, memory consumption, and processing time, and achieves high imaging signal-to-noise ratio with one-tenth of the photons. In various photon-limited experiments, DeepCAD-RT demonstrates its utility in morphological and functional interrogation of biological dynamics.
NATURE BIOTECHNOLOGY
(2023)
Article
Biology
Sheldon JJ Kwok et al.
Article
Computer Science, Artificial Intelligence
Jesus Pineda et al.
Summary: Despite recent improvements in microscopy acquisition methods, extracting quantitative information from biological experiments in crowded conditions is a challenging task. Pineda and colleagues propose a geometric deep-learning-based framework for automated trajectory linking and dynamical property estimation that is able to effectively deal with complex biological scenarios.
NATURE MACHINE INTELLIGENCE
(2023)
Review
Oncology
David Entenberg et al.
Summary: This article reviews the recent advances in intravital imaging of mammalian models of cancer and describes how intravital imaging can help to understand the role of the tumour microenvironment in cancer progression and metastasis, and to develop novel treatments and therapies.
NATURE REVIEWS CANCER
(2023)
Article
Oncology
Assia Asrir et al.
Summary: Tumor-associated high endothelial venules (TA-HEVs) are crucial for recruiting lymphocytes into tumors, and their presence is associated with better response and survival in anti-PD-1/anti-CTLA-4 treatment. TA-HECs co-express specific proteins and selectins, which attract lymphocytes to infiltrate tumors. Understanding the mechanism of lymphocyte trafficking in cancer immunity and immunotherapy is important for improving treatment outcomes.
Article
Cell Biology
Zhenqin Wu et al.
Summary: A cell's shape and motion are predictive of its function and pathology. However, automated analysis of cell morphology remains challenging, particularly for primary human cells that cannot be genetically labeled. To address this issue, researchers developed DynaMorph, a computational framework that combines quantitative live cell imaging with self-supervised learning to enable automated and quantitative analysis of cell morphodynamics.
MOLECULAR BIOLOGY OF THE CELL
(2022)
Article
Multidisciplinary Sciences
Georgiana Crainiciuc et al.
Summary: Transcriptional and proteomic profiling of individual cells have provided cellular landscapes of tissues, but fail to capture dynamic scenarios. This study used live imaging to record morpho-kinetic parameters of leukocytes in active inflammation and built behavioural landscapes that identified leukocyte identities and revealed a continuum of neutrophil states. Mutant screening identified the kinase Fgr as a driver of pathogenic inflammation, and interfering with Fgr protected mice from inflammatory injury.
Article
Multidisciplinary Sciences
J. Joseph Melenhorst et al.
Summary: CAR T cells redirected to target CD19 demonstrated long-lasting potential and clonal stability in two patients with chronic lymphocytic leukaemia. Highly activated CD4(+) cells emerged and dominated the CAR T cell population at later time points. These unexpected CAR T cell populations provide novel insights into anti-cancer response and long-term remission in leukaemia.
News Item
Biochemical Research Methods
Rita Strack
Summary: Investigating the spatial organization of DNA and its interacting elements in single cells will enhance our knowledge of cell-type-specific gene regulation.
Article
Biochemical Research Methods
John W. Hickey et al.
Summary: Recent developments in multiplexed protein imaging methods have provided detailed spatial and functional maps of complex tissues, utilizing antibodies against protein biomarkers. Key considerations for training future users, generating molecular tools, validating antibody panels, and harmonizing datasets are essential as these approaches become more widely adopted. This Perspective offers guidance for robust and reproducible antibody-based highly multiplexed tissue imaging.
Article
Multidisciplinary Sciences
Chenfei Hu et al.
Summary: The study introduces a method for assessing cell viability without the need for labeling, utilizing deep learning techniques combined with quantitative phase imaging to accurately determine cell survival status without causing damage to the cells.
NATURE COMMUNICATIONS
(2022)
Article
Biology
Ko Sugawara et al.
Summary: ELEPHANT is an interactive 3D cell tracking platform that addresses challenges in deep learning by incrementally enriching training data and improving tracking performance. The platform seamlessly integrates cell track annotation, deep learning, prediction, and proofreading, resulting in accurate and fully-validated cell lineages with modest time and effort investment.
Article
Cell & Tissue Engineering
Shengli Ding et al.
Summary: Patient-derived micro-organospheres (MOSs) generated using microfluidics technology can serve as an ideal model for clinical precision oncology. It enables rapid assessment of tumor drug response and provides a clinical assay for testing immuno-oncology therapies.
Review
Biochemistry & Molecular Biology
Pablo Delgado-Rodriguez et al.
Summary: Light Sheet Fluorescence Microscopy (LSFM) has enabled high-resolution 3D fluorescence imaging of ex vivo samples, opening up new possibilities for studying biological structures, disease diagnostics, and drug efficacy research.
PROGRESS IN BIOPHYSICS & MOLECULAR BIOLOGY
(2022)
Article
Multidisciplinary Sciences
Rebecca C. Larson et al.
Summary: CAR T cell therapy has shown limited efficacy against solid tumours, and this study identifies the loss of genes in the interferon-gamma receptor signalling pathway as a potential resistance mechanism in glioblastoma and other solid tumours. The study reveals that the interferon-gamma receptor signalling pathway is critical for the adhesion and cytotoxicity of CAR T cells in solid tumours, highlighting the importance of enhancing binding interactions between T cells and tumour cells for improved responses in solid tumours.
Article
Biotechnology & Applied Microbiology
Jina Ko et al.
Summary: SAFE is a method for comprehensive longitudinal imaging of living cells using immunofluorescence, allowing multiparameter temporal and spatial imaging. It is non-toxic and functional in various living samples.
NATURE BIOTECHNOLOGY
(2022)
Article
Biochemical Research Methods
Dmitry Ershov et al.
Summary: TrackMate is an automated tracking software that is used for analyzing bioimages. The new version, TrackMate 7, addresses modern research challenges by integrating advanced segmentation algorithms into tracking pipelines. This new version demonstrates its effectiveness across a wide range of bio-imaging experiments, combining machine and deep learning-based image segmentation with accurate object tracking for improved 2D and 3D tracking in biological research.
Article
Multidisciplinary Sciences
Tom Kaufman et al.
Summary: In this study, the authors developed a fluorescence imaging-based visual barcode for livecell clonal-multiplexing, which allows the identification of signalling pathways clusters in response to different chemotherapy compounds. They also demonstrated the use of visual barcodes to generate 'Signalome' cell-lines, enabling the simultaneous monitoring of the activity in 12 branches of signaling at clonal resolution.
NATURE COMMUNICATIONS
(2022)
Article
Multidisciplinary Sciences
Luca Sita et al.
Summary: This paper presents CITE-On, a convolutional neural network-based tool for processing two-photon calcium imaging data. CITE-On enables online automatic cell identification, segmentation, identity tracking, and trace extraction, which is significant for large field-of-view imaging.
NATURE COMMUNICATIONS
(2022)
Article
Multidisciplinary Sciences
Gustave Ronteix et al.
Summary: The cytotoxic T cell responses to cancer vary greatly among individuals. By studying the stochastic modeling of high-throughput T cell behavior and matched tumor spheroid fate data generated by a microfluidics system, the authors show that tumor killing is dependent on T cell cooperativity, which may contribute to the heterogeneity of T cell responses.
NATURE COMMUNICATIONS
(2022)
Article
Biochemistry & Molecular Biology
Takamasa Kudo et al.
Summary: By integrating live-cell imaging with pooled library-based screening, we developed a method that enables intracellular multiplexing and allows for long-term observation and analysis of phenotypes of interest, directly connecting behavior to the cellular genotype.
Review
Genetics & Heredity
Nasim Vahabi et al.
Summary: Studying complex biological processes and disease mechanisms requires the integration of data from different Omics modalities and utilizing external knowledge from biological databases. This review provides an overview of multi-Omics data integration methods, with a focus on unsupervised learning tasks.
FRONTIERS IN GENETICS
(2022)
Article
Engineering, Biomedical
Li You et al.
Summary: By using a custom-built optical microscope with an ultrawide field of view, fast automated image analysis and a dye activatable by visible light, selective photolabelling of cells of interest in large heterogeneous cell populations based on specific functional cellular dynamics is made possible. This approach allows for the identification and understanding of molecular mechanisms underlying functional phenotypes.
NATURE BIOMEDICAL ENGINEERING
(2022)
Article
Engineering, Biomedical
Kripa B. Patel et al.
Summary: The study introduces the feasibility of using microscopes based on swept confocally aligned planar excitation technology for real-time volumetric histological imaging of intact living tissue. These microscopes enable rapid image acquisition without the need for tissue excision or staining, allowing for dynamic assessment of tissue perfusion and function, potentially facilitating point-of-care detection of cellular-level biomarkers.
NATURE BIOMEDICAL ENGINEERING
(2022)
Article
Cell Biology
Gerhard A. Burger et al.
Summary: The ability of cancer cells to invade neighboring tissue from primary tumors is a crucial factor in determining metastatic behavior. This study investigates how local tumor cell density affects cell migration characteristics and cluster formation using a combined experimental and computational modeling approach. The results suggest that pseudopod dynamics and interaction may play a role in the aggressive nature of cancers by mediating dispersal.
FRONTIERS IN CELL AND DEVELOPMENTAL BIOLOGY
(2022)
Article
Biochemical Research Methods
Christa Haase et al.
Summary: Image-seq is a technology that allows single-cell transcriptional data to be obtained from cells isolated from specific spatial locations under image guidance, preserving the spatial information of the cells. It can be used with in situ and in vivo imaging to document the temporal and dynamic history of the cells being analyzed. This technology combines spatial information with highly sensitive RNA sequencing, providing valuable insights into cellular organization and function.
Article
Multidisciplinary Sciences
Zheng Ao et al.
Summary: Researchers have developed an automated high-throughput microfluidic platform to track T cell infiltration and cytotoxicity and evaluate treatment efficacy. By screening a drug library, they identified an epigenetic drug that enhances tumor infiltration and treatment effectiveness.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
(2022)
Review
Multidisciplinary Sciences
Darrell J. Irvine et al.
Summary: Immune cell therapy is a promising approach to treating diseases, especially cancer, by engineering immune cells to recognize and respond to specific conditions. This therapy has already been approved for clinical use and continues to be developed and tested in various applications.
Article
Biochemical Research Methods
Jonathan M. Matthews et al.
Summary: Organoids are promising ex vivo disease models for drug discovery, but analyzing their morphology, number, and size is challenging. This study presents OrganoID, an image analysis platform that automatically recognizes, labels, and tracks single organoids pixel-by-pixel. OrganoID enables straightforward and accurate image analysis to accelerate the use of organoids in biomedical applications.
PLOS COMPUTATIONAL BIOLOGY
(2022)
Article
Multidisciplinary Sciences
Wanze Chen et al.
Summary: Live-seq is a novel single-cell transcriptomic profiling approach that preserves cell viability during RNA extraction, allowing for the correlation analysis between a cell's ground-state transcriptome and its downstream molecular or phenotypic behavior. It accurately stratifies diverse cell types and states without major cellular perturbations, and can be used to map a cell's trajectory and evaluate gene effects on cell phenotypes.
Article
Multidisciplinary Sciences
Yuki Ohta et al.
Summary: This study develops an experimental platform for tracking cancer stem cells in colorectal cancer and identifies dormant LGR5(+) cancer stem cells. Transcriptome analysis reveals an upregulation of cell-adhesion molecule COL17A1 in dormant cancer stem cells, and chemotherapy disrupts this dormancy through FAK-YAP activation. Inhibition of YAP signaling prevents chemoresistant cells from exiting dormancy and delays tumor regrowth.
Article
Biotechnology & Applied Microbiology
Johanna F. Dekkers et al.
Summary: This study utilizes a system called BEHAV3D to investigate the dynamic interactions between immune cells and patient cancer organoids. By live-tracking a large number of engineered T cells cultured with patient-derived solid-tumor organoids, a cluster of "super engager" T cells with potent serial killing capacity is identified. The study also examines cancer metabolome-sensing engineered T cells (TEGs) and identifies behavior-specific gene signatures in these cells. Additionally, it demonstrates the ability of type I interferon to prime resistant organoids for TEG-mediated killing.
NATURE BIOTECHNOLOGY
(2022)
Article
Multidisciplinary Sciences
Bernhard A. Kramer et al.
Summary: Individual cells can make decisions based on their internal state and surroundings, but it is still unclear how they can do this reliably. To investigate the information processing capacity of human cells, the researchers conducted a study on signaling responses and cellular state markers. The results showed that signaling nodes in the network displayed adaptive information processing, leading to heterogeneous growth factor responses and enabling cells to capture partially nonredundant information about their state. This demonstrates that individual cells have a large information processing capacity to accurately interpret growth factor concentration in the context of their cellular state and make decisions accordingly. The heterogeneity and complexity in signaling networks may have coevolved to facilitate specific and context-aware decision-making in multicellular settings.
Article
Biology
Bianca C. T. Flores et al.
Summary: In this study, we report a microfluidic system that combines the capture, co-incubation, time-lapse imaging, and gene expression profiling of doublets to measure the distances between cells and the associated transcriptional profiles due to cell-cell interactions. Our findings demonstrate the time-bound activities of regulatory modules and suggest the existence of transcriptional memory. This approach provides a proof of concept for studying live-cell interactions at doublet resolution.
COMMUNICATIONS BIOLOGY
(2022)
Review
Genetics & Heredity
Tien-Hung Lan et al.
Summary: Optogenetics merges genetics and biophotonics to control biological processes noninvasively with high spatiotemporal precision. Various non-opsin photosensory modules have been utilized to modulate gene transcription, DNA or RNA modifications, DNA recombination, and genome engineering, showing great potential in a wide range of applications.
TRENDS IN GENETICS
(2022)
Article
Multidisciplinary Sciences
Yu Shi et al.
Summary: Light sheet microscopes reduce phototoxicity and background while improving imaging speed. The authors quantify the differences between Gaussian and lattice light sheets using simulations and experimental data, and introduce an approach to spectrally fuse sequential acquisitions of different lattice light sheet patterns.
NATURE COMMUNICATIONS
(2022)
Article
Multidisciplinary Sciences
Johannes Betge et al.
Summary: Patient-derived organoids can be used to model human diseases and tumors, and understanding their morphology can provide insights into treatment response. This study uses high-throughput imaging analysis to quantify the phenotypes of colorectal cancer organoids after treatment with small molecules, and identifies the underlying biological mechanisms and drug interventions that can influence their morphology.
NATURE COMMUNICATIONS
(2022)
Article
Multidisciplinary Sciences
Dmytro Havrylyuk et al.
Summary: This study describes the creation of light-triggered CYP1B1 inhibitors as prodrugs, which achieve a significant improvement in potency upon activation with low-energy light. These inhibitors show high selectivity in live cells and have potential for providing similar selectivity and control.
NATURE COMMUNICATIONS
(2022)
Article
Chemistry, Multidisciplinary
Jina Ko et al.
Summary: The ability to observe cells in live organisms is crucial for understanding their function in complex in vivo milieus. However, current methods have limited multiplexing capacity. In this study, a click chemistry-based strategy called scission-accelerated fluorophore exchange (SAFE) was developed for higher multiplexed in vivo imaging in mouse models. The method allows specific cell staining, complete un-staining, and non-toxic in vivo click chemistries at lower concentrations. It also enables cyclic imaging and has demonstrated potential utility in imaging immune cells with 12 colors.
Article
Multidisciplinary Sciences
Sandra Ottl et al.
Summary: In this study, machine learning methods are used to automatically assess the quality of human semen samples from the Visem dataset in terms of sperm motility. Regression models are trained to predict the percentage of progressive, non-progressive, and immotile spermatozoa. By adopting unsupervised tracking and two different feature extraction methods, the best results are achieved.
Editorial Material
Multidisciplinary Sciences
Sandeep Ravindran
Article
Biochemical Research Methods
Andreas P. Cuny et al.
Summary: TracX improves the accuracy of single-cell tracking using a fingerprinting approach to measure cell similarity across consecutive images. It is applicable across different cell types and image modalities, aiding in accurate cell observation and biological discovery in single-cell biology.
Article
Biochemical Research Methods
Jonatan Alvelid et al.
Summary: Event-triggered STED is an automated imaging method that rapidly initiates STED imaging after detecting cellular events, which can enhance live cell imaging capabilities and enable real-time biological observations and discoveries.
Article
Biochemical Research Methods
Dora Mahecic et al.
Summary: Event-driven acquisition is a method that uses neural network recognition of specific biological events to switch between slow and fast super-resolution imaging, improving the spatiotemporal resolution of capturing interesting events. It allows the microscope to respond specifically to complex biological events, acquiring data enriched in relevant content.
Article
Multidisciplinary Sciences
Yixin Wu et al.
Summary: The authors present a wireless real-time programmable optofluidic platform for precise control of light and drug delivery in optogenetic and photopharmacology experiments. This platform expands the scope of wireless techniques to study neural processing in animal models.
NATURE COMMUNICATIONS
(2022)
Article
Multidisciplinary Sciences
Eva C. Freckmann et al.
Summary: Currently, there is a lack of tools to detect heterogeneity in 3D cultures. This study introduces Traject3d as a framework to identify and understand heterogeneous states in 3D culture and their impact on distinct phenotypes. The findings provide valuable insights into the temporal landscape of morphological states and drug combinations that inhibit heterogeneity.
NATURE COMMUNICATIONS
(2022)
Article
Multidisciplinary Sciences
Gustavo de Medeiros et al.
Summary: This study presents an experimental and image processing framework to convert long-term light-sheet imaging of intestinal organoids into digital organoids, allowing for the visualization and understanding of multivariate and multiscale data. The researchers also identified cytokinesis failure of regenerative cells and discovered that these cells never reside in the intestinal crypt, suggesting tissue scale control on cellular fidelity.
NATURE COMMUNICATIONS
(2022)
Article
Cell & Tissue Engineering
Zhaohui Wang et al.
Summary: Micro-organospheres (MOSs) formed using emulsion microfluidics are promising miniature three-dimensional tissue models that can be rapidly established and retain key biological features and responses to therapy. They have various applications and can be used for assessment of nutrient dependence, anti-viral drug screening, and therapeutic profiling.
Article
Biology
Michael C. Robitaille et al.
Summary: This paper introduces a self-supervised learning approach that uses cellular motion between consecutive images to self-train a machine learning classifier for cell segmentation. The method does not require adjustable parameters or curated imagery, and can self-train on end-user data, eliminating end-user variability and bias.
COMMUNICATIONS BIOLOGY
(2022)
Article
Biochemical Research Methods
Pin-Rui Su et al.
Summary: Single-cell proteomics has the potential to decode tumor heterogeneity, but current methods lack the ability to link individual cell proteomes with phenotypes of interest. Therefore, we developed a microscopy-based technology called FUNpro that allows real-time screening, identification, and isolation of specific single cells, even if the phenotypes are dynamic or the cells of interest are rare. We applied FUNpro to analyze a small subpopulation of U2OS osteosarcoma cells with abnormal, prolonged DNA damage response after ionizing radiation (IR) and identified the PDS5A protein as a contributor to the abnormal DDR dynamics and cell survival after IR.
CELL REPORTS METHODS
(2022)
Proceedings Paper
Computer Science, Artificial Intelligence
Jiqing Zhang et al.
Summary: Event-based cameras have the unique ability to track objects in challenging real-world conditions due to their high temporal resolution and dynamic range. In this study, a spiking transformer network (STNet) is proposed for single object tracking, which dynamically extracts and fuses temporal and spatial information. The experimental results demonstrate that STNet outperforms existing methods in tracking accuracy and speed.
2022 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR)
(2022)
Article
Medicine, Research & Experimental
Gabrielle Romain et al.
Summary: We used high-throughput single-cell technologies to analyze CD19-specific CAR T cells and discovered that directional migration and multifunctionality are correlated. We found that CD2 on T cells is associated with directional migration and that the interaction between CD2 and CD58 on lymphoma cells accelerates killing. Increased CD58 expression on pretreatment tumor samples in patients with relapsed or refractory large B cell lymphomas treated with CD19-specific CAR T cell therapy was associated with complete clinical response and survival. These findings highlight the importance of studying dynamic T cell-tumor cell interactions in identifying optimal antitumor responses.
JOURNAL OF CLINICAL INVESTIGATION
(2022)
Article
Computer Science, Artificial Intelligence
Christopher J. Soelistyo et al.
Summary: Researchers have developed a machine learning approach that can learn the mechanisms behind cell fate and competition from large microscopy datasets. They have created a model that predicts cell fate and discovered that cell density is the most important factor in determining cell fate. Additionally, they have developed a discriminator network that can identify abnormal behavior, paving the way for mechanism-aware drug screening.
NATURE MACHINE INTELLIGENCE
(2022)
Article
Medicine, Research & Experimental
Zheng Ao et al.
Summary: In this study, a microfluidics-based mini-tumor chip approach was developed to predict tumor responses to cancer immunotherapy. By generating mini-tumors on-chip and incorporating time-lapse live-cell imaging, the dynamic immune-tumor interactions and their responses to immunotherapy could be investigated within 36 hours.
Article
Biochemistry & Molecular Biology
Jr-Ming Yang et al.
Summary: Researchers have developed a set of barcoding proteins capable of generating over 100 barcodes, overcoming the limited multiplexing capacity of genetically encoded fluorescent biosensors in live cells. Simultaneous tracking of multiple biosensors reveals highly coordinated activities and complex interactions within the signaling network.
Editorial Material
Biochemical Research Methods
Vivien Marx
Summary: Nature Methods has named spatially resolved transcriptomics as Method of the Year 2020.
Article
Cell Biology
James Longden et al.
Summary: This study utilized deep neural networks to analyze the relationship between drug resistance in cancer cells and cell morphology, revealing that complex cell morphologies can encode states of signaling networks and unravel cellular mechanisms hidden to conventional approaches. By analyzing over 500 billion data points, a continuous 27-dimension space describing cell morphologies was identified, enabling accurate prediction of drug resistance and mechanisms with a validation in lung and head/neck cancer models.
Article
Biochemical Research Methods
Estibaliz Gomez-de-Mariscal et al.
Summary: DeepImageJ is a user-friendly solution that allows trained deep learning models to be run in ImageJ for biomedical image analysis. It provides guiding tools for reliable analyses and opens up access to a repository of pre-trained models. Additionally, it enables nonexperts to easily perform various image processing tasks in life science research using deep learning-based tools.
Review
Biochemistry & Molecular Biology
Ilio Vitale et al.
Summary: Tumors evolve under various pressures and exhibit considerable heterogeneity in genetic, phenotypic, and behavioral aspects. This intratumoral heterogeneity influences disease progression and treatment sensitivity, necessitating consideration of multiple levels of heterogeneity in future therapeutic approaches.
Article
Multidisciplinary Sciences
Miriam Lisci et al.
Summary: This study revealed that CTLs require mitochondria for target cell-killing, and this requirement is linked to mitochondrial translation. Inhibition of mitochondrial translation impairs CTL killing by triggering attenuated cytosolic translation, leading to a reduced capacity for sustained killing. Mitochondria emerge as a previously unappreciated homeostatic regulator of protein translation required for serial CTL killing.
Article
Biochemical Research Methods
Ilya Belevich et al.
Summary: DeepMIB is a software package for training convolutional neural networks for segmentation of multidimensional microscopy datasets. It is capable of handling 2D and 3D datasets with isotropic and anisotropic voxels, and is distributed as open-source Matlab code and standalone application for different operating systems. It is a user-friendly tool that does not require programming knowledge, suitable for users interested in applying deep learning to image segmentation workflows.
PLOS COMPUTATIONAL BIOLOGY
(2021)
Article
Multidisciplinary Sciences
Christopher Z. Eddy et al.
Summary: The study investigates the morphodynamics of MDA-MB-231 cells in a 3D environment, showing that cell shape is influenced by ECM mechanics and Rho/ROCK signaling. Cell shape can be classified into four distinct morphological phenotypes, each corresponding to a different migration mode. This research demonstrates the complex interplay between ECM properties, cell signaling, and cell motility in 3D cancer cell dynamics.
SCIENTIFIC REPORTS
(2021)
Article
Biochemical Research Methods
Phuc Nguyen et al.
Summary: UPSIDE is a machine learning approach for discovering cell types and states from time-resolved live cell imaging data, capable of distinguishing different blood cell types and identifying clinical disease-related cell states. By utilizing deep learning technology, this method provides a unbiased tool for analyzing cell types and state transitions in biology and medicine.
PLOS COMPUTATIONAL BIOLOGY
(2021)
Review
Cell & Tissue Engineering
Qiang Huang et al.
Summary: Imaging techniques are crucial for visualizing tissue development, homeostasis, and regeneration driven by stem cells. Recent advancements in molecular and tissue modeling technologies have led to new imaging modalities to explore tissue heterogeneity and plasticity. Current state-of-the-art imaging modalities and emerging tissue modeling tools can improve resolution, specificity, and throughput.
Article
Oncology
Chahrazade Kantari-Mimoun et al.
Summary: The study found that CD20 CAR-T cells rapidly formed effective conjugates with target cells, while EGFR CAR-T cells need to migrate to the center of tumor cell regions after initial activation at the periphery of tumor islets. Activated CAR-T cells induce upregulation of ICAM-1 on malignant tumor cells via an IFN gamma-dependent pathway.
CANCER IMMUNOLOGY RESEARCH
(2021)
Article
Biochemistry & Molecular Biology
Roxana Khazen et al.
Summary: The majority of CTL interactions with tumor cells either in vitro or in vivo result in sublethal hits, which are associated with reversible calcium elevation and membrane damage in the target cells. In the therapeutic context of anti-CD19 CAR T cells, most interactions with tumor cells do not lead to lethal hit delivery. Differences in CTL lytic potential and tumor cell resistance to cytotoxic hits are two important barriers for effective anti-tumor responses in vivo.
Article
Biochemical Research Methods
Jacob C. Kimmel et al.
Summary: The research explores the use of neural network models to analyze and predict cell motility behaviors, providing accurate classification of various cell types' movements through learning spatial and temporal dependencies. Additionally, unsupervised learning can automatically extract cell motility features, enhancing the performance of cell motility prediction, showing potential practical value in future cell tracking applications.
IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS
(2021)
Article
Oncology
Erin R. Spiller et al.
Summary: Three-quarters of compounds fail to make it to market in clinical trials, highlighting the need for better screening methods. Patient-derived organoids are seen as a promising 3D preclinical model system with challenges in assessing drug efficacy.
FRONTIERS IN ONCOLOGY
(2021)
Article
Cell Biology
Bas Ponsioen et al.
Summary: The study illustrates how EGFR activity enhances signal transduction efficiency in KRAS or BRAF mutant MAPK pathways, revealing a potential mechanism for using EGFR inhibitors in colorectal cancer with KRAS and BRAF mutations.
NATURE CELL BIOLOGY
(2021)
Article
Multidisciplinary Sciences
Lucas von Chamier et al.
Summary: ZeroCostDL4Mic is an entry-level platform that simplifies access to deep learning by leveraging the free, cloud-based computational resources of Google Colab. Researchers can train and apply key deep learning networks for various microscopy tasks without coding expertise. The platform provides quantitative tools for model evaluation and optimization.
NATURE COMMUNICATIONS
(2021)
Article
Biology
Chentao Wen et al.
Summary: 3DeeCellTracker is a deep learning-based software pipeline that successfully segments and tracks cells in various dynamic environments, providing a new possibility for revealing cell activities in image datasets that have been difficult to analyze.
Article
Oncology
Irfan N. Bandey et al.
Summary: This study identified molecular mechanisms, such as inducible CD137, that can enhance the killing function of T cells through single-cell analysis. Genetically modifying CAR T cells to co-express CD137L led to significant improvement in anti-tumor efficacy and reduced exhaustion.
JOURNAL FOR IMMUNOTHERAPY OF CANCER
(2021)
Article
Immunology
Morgane Boulch et al.
Summary: Chimeric antigen receptor (CAR) T cell therapy relies on interactions with the tumor microenvironment (TME) for optimal activity, with IFN-gamma playing a crucial role in enhancing host immune response and sustaining CAR T cell cytotoxicity. CAR T cell-derived IFN-gamma facilitates host interleukin-12 production to support host immune and CAR T cell responses, highlighting the importance of cytokine-mediated cross-talk for effective CAR T cell therapy.
SCIENCE IMMUNOLOGY
(2021)
Article
Biochemistry & Molecular Biology
Karin Pelka et al.
Summary: By analyzing the transcriptional profiles of cells in tumors, differences in immune responses between mismatch repair-deficient (MMRd) and mismatch repair-proficient (MMRp) tumors were identified, as well as the logic behind the interaction of malignant and immune cells discovered within tumors.
Article
Immunology
Chuan Yan et al.
Summary: This study utilized optically clear immunocompromised zebrafish models engrafted with fluorescent-labeled human cancers and various T cell immunotherapies to visualize T cell immune responses at single-cell resolution in real time. Differences in kinetics of T cell infiltration, tumor cell engagement, and killing were identified among the immunotherapies, leading to early endpoint analysis for predicting therapy responses. EGFR-targeted immunotherapies were established as a powerful approach to eradicate rhabdomyosarcoma muscle cancers, suggesting the potential of assessing a broader range of T cell immunotherapies in this disease.
JOURNAL OF EXPERIMENTAL MEDICINE
(2021)
Article
Computer Science, Artificial Intelligence
Pasquale Cascarano et al.
Summary: A new deep learning-based algorithm is proposed for TLM Video Super Resolution without requiring any training, showing outstanding performances on synthetic and real videos related to tumor-immune interaction. The method introduces new approaches for initializing network weights and penalizing the DIP loss function.
MEDICAL IMAGE ANALYSIS
(2021)
Article
Biotechnology & Applied Microbiology
Ravian L. van Ineveld et al.
Summary: The study introduces an imaging software for large-scale microscopy data, enabling parallelized, deep learning-based segmentation of single cells in tissues to reveal molecular, spatial, and morphological features. The research found that Wilms tumor exhibits a highly disorganized spatial pattern, with cellular profiles resembling human fetal kidney cells, and also identified previously unreported tumor-specific populations.
NATURE BIOTECHNOLOGY
(2021)
Article
Biochemistry & Molecular Biology
Anne M. van der Leun et al.
Summary: The study introduces a photocage-based technology that allows isolation and in-depth analysis of live cells from complex ex vivo systems, including primary human tissues. By using nanobodies and a highly sensitive 4-nitrophenyl(benzofuran) cage, high-resolution photo-uncaging of different cell types in areas of interest is achieved.
NATURE CHEMICAL BIOLOGY
(2021)
Article
Biochemistry & Molecular Biology
Paula Voabil et al.
Summary: A study using patient-derived tumor fragments as an ex vivo platform showed that the reactivation of tumor-infiltrating immune cells after PD-1 blockade could predict clinical outcomes. Tumor-resident T cells were identified as crucial in the immunological response, and a subgroup of tumors was found to be unresponsive to PD-1 blockade. Additionally, the presence of tertiary lymphoid structures in baseline tumors correlated with the capacity for intratumoral immune cell reactivation.
Article
Biochemical Research Methods
Austin E. Y. T. Lefebvre et al.
Summary: Mitometer is an algorithm for fast, unbiased, and automated segmentation and tracking of mitochondria in live-cell time-lapse images, which can identify mitochondrial motion and morphology, including fusion and fission events. Using Mitometer, it was found that mitochondria in triple-negative breast cancer cells are faster, more directional, and more elongated than those in receptor-positive counterparts. Furthermore, mitochondrial motility and morphology in breast cancer, but not in normal breast epithelia, correlate with metabolic activity.
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Biochemical Research Methods
Christoffer Edlund et al.
Summary: The LIVECell dataset consists of annotated phase-contrast images of over 1.6 million cells, aiming to improve the training of image segmentation models through deep learning. Its creation and utilization help explore biological phenomena and conduct high-throughput quantitative imaging studies.
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Multidisciplinary Sciences
Alex S. Genshaft et al.
Summary: The authors introduce the development and application of SPACECAT technology for labeling, tracking, and isolating cells to study their spatiotemporal activities, achieving high precision marking and temporal stability of cells. By showcasing various experimental examples, the authors demonstrate the application of SPACECAT in different cell and tissue types, and provide a computational framework for identifying transcriptome patterns and enriched phenotypes.
NATURE COMMUNICATIONS
(2021)
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Multidisciplinary Sciences
Chen Chen et al.
Summary: The research team developed a multi-parameter measurement system that can simultaneously quantify cell surface proteins, endocytosis activities, and metabolic dynamics of single live cells. This technique allows for analysis of 14 parameters under drug perturbations, enabling powerful clustering, correlation, and network analysis.
NATURE COMMUNICATIONS
(2021)
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Multidisciplinary Sciences
Bettina Weigelin et al.
Summary: The study demonstrates that sublethal interactions from multiple CTL can accumulate over time and achieve tumor cell killing by additive cytotoxicity. Statistical modeling reveals that delivering three serial hits within decay intervals below 50 minutes can distinguish between tumor cell death or survival after recovery.
NATURE COMMUNICATIONS
(2021)
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Biochemistry & Molecular Biology
Assaf Zaritsky et al.
Summary: The study utilized a generative neural network and supervised machine learning to classify the metastatic efficiency of melanoma cells, revealing characteristic features of metastatic cells and validating these findings with live cell observations. It demonstrates how artificial intelligence can aid in identifying cell properties predictive of complex phenotypes and integrated cell functions that may be subtle and difficult for human experts to identify in raw imagery.
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Multidisciplinary Sciences
Giuseppe Pettinato et al.
Summary: A new approach using microfabricated cell-repellent microwell arrays for rapid organoid formation from hiPSCs and endothelial cells was introduced, allowing real-time monitoring of differentiation processes with Raman spectroscopy and confocal light scattering spectroscopic microscopy. This approach significantly shortened the time required for protocol fine-tuning, and successfully cultured homogeneous liver organoids with main functional features of the human liver for potential liver therapy in humans.
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Multidisciplinary Sciences
Jingwen Shou et al.
Summary: Observing multiple molecular species simultaneously with high spatiotemporal resolution is crucial for comprehensive understanding of biological systems. The super-multiplex optical imaging technique breaks the color barrier of fluorescence, achieving multiplexing number over six in living systems. Integrated stimulated Raman and fluorescence microscopy enables super-multiplex imaging with high speed and temporal resolution of seconds, providing a powerful tool to elucidate spatiotemporal organization and interactions in biological systems.
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Computer Science, Artificial Intelligence
Arif Ahmed Sekh et al.
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NATURE MACHINE INTELLIGENCE
(2021)
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Medicine, Research & Experimental
Ran You et al.
Summary: Intratumoral T cells in an exhausted state exhibit variable mobility within human tumors, with speed inversely correlated with local tumor density and differing by region and patient. This study reveals dynamic states of T cells in individual human tumors and suggests an active program in exhausted T cells beyond mere incapacitation.
JOURNAL OF CLINICAL INVESTIGATION
(2021)
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Medicine, Research & Experimental
Lei Liu et al.
Summary: The study found that the killing efficiency of CTLs in the liver is restrained compared to the spleen, and this limitation can be reversed by blocking immunosuppressive cytokines. Tumor cells exposed to CTLs in the liver showed prolonged calcium influx before caspase-3 activity.
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Computer Science, Interdisciplinary Applications
Kristina Ulicna et al.
Summary: By combining deep learning and Bayesian methods, we developed a novel cell tracking approach that accurately reconstructs cellular lineage information from time-lapse microscopy data. Our method allows for the extraction of thousands of fully annotated single-cell trajectories and multi-generational lineage trees with minimal manual curation, providing high-fidelity results.
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Matthias Mulazzani et al.
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Salo N. Ooft et al.
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A. J. Davenport et al.
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(2018)
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NATURE COMMUNICATIONS
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Livnat Jerby-Arnon et al.
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Jarno Drost et al.
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(2018)
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EMBO MOLECULAR MEDICINE
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Felix Buggenthin et al.
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C. S. Manning et al.
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Anoop P. Patel et al.
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Dmitriy M. Chudakov et al.
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Rolf T. Borlinghaus
MICROSCOPY RESEARCH AND TECHNIQUE
(2006)
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R Ando et al.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
(2002)
