Article
Biochemical Research Methods
Qibing Jiang, Praneeth Sudalagunta, Maria C. Silva, Rafael R. Canevarolo, Xiaohong Zhao, Khandakar Tanvir Ahmed, Raghunandan Reddy Alugubelli, Gabriel DeAvila, Alexandre Tungesvik, Lia Perez, Robert Gatenby, Robert Gillies, Rachid Baz, Mark B. Meads, Kenneth H. Shain, Ariosto S. Silva, Wei Zhang
Summary: Time-lapse microscopy is a powerful technique in precision oncology for quantifying the response of cancer cells to different therapies. This study presents a novel framework called CancerCellTracker that tracks and quantifies cancer cell behavior and viability in a high-throughput manner. Experimental results demonstrate the efficiency and effectiveness of CancerCellTracker.
Article
Biochemical Research Methods
Tao Hu, Shixiong Xu, Lei Wei, Xuegong Zhang, Xiaowo Wang
Summary: Recent advances in long-term time-lapse microscopy have enabled researchers to quantify cell behavior and molecular dynamics with ease. However, the lack of user-friendly software tools optimized for customized research remains a major challenge. CellTracker is a highly integrated graphical user interface software that automates cell segmentation and tracking in time-lapse microscopy images, offering features such as project management, image pre-processing, and statistical analysis.
Article
Computer Science, Artificial Intelligence
Yan Gao, Haojun Xu, Yu Zheng, Jie Li, Xinbo Gao
Summary: The paper focuses on exploring the relationship between segmenter and tracker in the context of multi-object tracking and segmentation. The proposed Object Point set Inductive Tracker (OPITrack) utilizes attention layer and embedding generalization training strategy to improve network robustness and learning capabilities, achieving promising results on MOTS benchmark datasets.
IEEE TRANSACTIONS ON IMAGE PROCESSING
(2022)
Article
Biochemical Research Methods
Yanming Zhu, Erik Meijering
Summary: This study proposed a novel NAS-based solution for deep learning-based live cell segmentation in time-lapse microscopy images. By jointly searching non-repeatable micro architectures to construct the macro network and defining a specific search space suitable for the task, as well as exploring temporal information in cell sequences, the method demonstrated more competitive performance, showing more consistent top performance across all datasets in the experiments.
Article
Multidisciplinary Sciences
Hideya Aragaki, Katsunori Ogoh, Yohei Kondo, Kazuhiro Aoki
Summary: Cell tracking is a critical tool for observing cell behavior and lineages over time, but current software lacks user-friendliness and features like manual correction and data analysis tools. This paper introduces LIM Tracker, a cell tracking software that integrates various tracking functions and offers interactive data visualization. It also includes deep learning recognition capabilities and can be used for a wide range of targets. The software is implemented as a plugin for ImageJ/Fiji.
SCIENTIFIC REPORTS
(2022)
Article
Computer Science, Artificial Intelligence
Lang Yu, Baojun Qiao, Huanlong Zhang, Junyang Yu, Xin He
Summary: Recent progress has been made in combining visual object tracking (VOT) with video object segmentation (VOS). However, the current segmentation methods are still limited by the target model created in the first frame, leading to a lack of long-term adaptability. To overcome this limitation, a novel long-term segmentation tracker (LTST) is proposed in this study, which leverages a memory attention network to achieve online learning without additional training. Experimental results show that the proposed tracker achieves comparable performance to the state-of-the-art long-term tracking algorithms in several benchmark tests.
IMAGE AND VISION COMPUTING
(2022)
Article
Biology
Seol Ah Park, Tamara Sipka, Zuzana Kriva, Georges Lutfalla, Mai Nguyen-Chi, Karol Mikula
Summary: This paper proposes a new algorithm for automatic cell tracking in time-lapse microscopy macrophage data. The algorithm includes a segmentation method and a trajectory extraction method. The proposed tracking achieved high accuracy for macrophage data under challenging situations. The automatically extracted trajectories of macrophages can provide evidence of how macrophages migrate in different situations.
COMPUTERS IN BIOLOGY AND MEDICINE
(2023)
Article
Biochemical Research Methods
Benoit Daviet, Christian Fournier, Llorenc Cabrera-Bosquet, Thierry Simonneau, Maxence Cafier, Charles Romieu
Summary: This study developed a fully automated open-source method to detect, segment, and track overlapping berries in time-series images of grapevine bunches acquired under laboratory conditions. This allows for quantification of fine aspects of individual berry development and characterization of the asynchrony within the bunch.
Article
Computer Science, Artificial Intelligence
Lorenzo Vaquero, Victor M. Brea, Manuel Mucientes
Summary: This paper proposes a method called SiamMOTION, which tracks multiple arbitrary objects in real-time videos by introducing an attention mechanism and a feature pyramid network, and achieves leading performance in several public benchmarks.
PATTERN RECOGNITION
(2023)
Article
Biochemical Research Methods
Oliver J. Meacock, William M. Durham
Summary: Most bacteria live in densely-packed communities on surfaces. Tracking individual cells in these communities is challenging, but the new software tool FAST combines machine learning and information theory to optimize cell tracking. By using various cell characteristics and minimizing tracking errors, FAST provides a quantitative platform to study bacterial behavior in groups.
PLOS COMPUTATIONAL BIOLOGY
(2023)
Article
Physics, Multidisciplinary
Riccardo Scheda, Silvia Vitali, Enrico Giampieri, Gianni Pagnini, Isabella Zironi
Summary: Cellular contacts influence the way cells migrate in a cohesive group compared to a single free cell. A novel pipeline is proposed for analyzing phase contrast images of wound healing scratch assays, with the goal of extracting single particle trajectories describing wound closure dynamics. The method involves using the cell membrane at the wound edge as a unicum for stochastic motion analysis.
Article
Biochemical Research Methods
Saoirse Amarteifio, Todd Fallesen, Gunnar Pruessner, Giovanni Sena
Summary: This study introduces an algorithm to optimize 3D object tracking by combining registration and tracking tasks into one algorithm, using random sampling to solve the identity management problem. The algorithm is designed and applied in the field of plant biology, and is open-source. It fills a gap in existing tracking techniques by tracking mitotic events in challenging datasets using transient fluorescent markers in unregistered images.
Article
Acoustics
Iman Taghavi, Sofie Bech Andersen, Carlos Armando Villagomez Hoyos, Mikkel Schou, Fredrik Gran, Kristoffer Lindskov Hansen, Michael Bachmann Nielsen, Charlotte Mehlin Sorensen, Matthias Bo Stuart, Jorgen Arendt Jensen
Summary: This study presents a new hierarchical Kalman (HK) tracker that can achieve better performance in scenarios with high concentrations of microbubbles and high localization uncertainty. The results show that the HK tracker is most similar to the ground truth in most scenarios and has the lowest root-mean-square error compared to the nearest-neighbor (NN) and Kalman (K) trackers. The HK tracker also provides more accurate vessel diameter reconstruction and better estimation of microbubble velocities. The tracking performance of the HK tracker is observed to be improved in in vivo experiments as well.
Article
Biology
Chentao Wen, Koutarou D. Kimura
Summary: A deep learning-based software pipeline called 3DeeCellTracker has been developed to accurately track cells with large movements in 3D + T images. This protocol provides instructions on setting up the computational environment, required data, and the steps for cell segmentation and tracking, aiding scientists in analyzing cell activities in challenging 3D + T image datasets.
Article
Soil Science
Andrey Guber, Evgenia Blagodatskaya, Archana Juyal, Bahar S. Razavi, Yakov Kuzyakov, Alexandra Kravchenko
Summary: Membrane zymography is a common method used in rhizosphere ecology to map enzyme activities, but the traditional assumptions are unlikely to hold in experimental settings. The new technique of time-lapse zymography eliminates the need for these assumptions and provides more accurate estimates of enzymatic activities. The results of laboratory experiments showed that the time-lapse zymography considerably improved accuracy compared to the traditional method.
SOIL BIOLOGY & BIOCHEMISTRY
(2021)
Article
Biochemistry & Molecular Biology
Vera Haskamp, Simone Karrie, Toni Mingers, Stefan Barthels, Francois Alberge, Axel Magalon, Katrin Mueller, Eckhard Bill, Wolfgang Lubitz, Kirstin Kleeberg, Peter Schweyen, Martin Broering, Martina Jahn, Dieter Jahn
JOURNAL OF BIOLOGICAL CHEMISTRY
(2018)
Article
Multidisciplinary Sciences
Simon J. Moore, James T. MacDonald, Sarah Wienecke, Alka Ishwarbhai, Argyro Tsipa, Rochelle Aw, Nicolas Kylilis, David J. Bell, David W. McClymont, Kirsten Jensen, Karen M. Polizzi, Rebekka Biedendieck, Paul S. Freemont
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
(2018)
Article
Biochemistry & Molecular Biology
Elisabeth Haertig, Claudia Fraedrich, Maren Behringer, Anja Hartmann, Meina Neumann-Schaal, Dieter Jahn
MOLECULAR MICROBIOLOGY
(2018)
Article
Biochemistry & Molecular Biology
Maike K. Groenewold, Stefanie Hebecker, Christiane Fritz, Simon Czolkoss, Milan Wiesselmann, Dirk W. Heinz, Dieter Jahn, Franz Narberhaus, Meriyem Aktas, Juergen Moser
MOLECULAR MICROBIOLOGY
(2019)
Article
Biochemical Research Methods
Karin Muench, Richard Muench, Rebekka Biedendieck, Dieter Jahn, Johannes Mueller
PLOS COMPUTATIONAL BIOLOGY
(2019)
Article
Biochemistry & Molecular Biology
Jan Jasper, Jose Ramos, Christian Trncik, Dieter Jahn, Oliver Einsle, Gunhild Layer, Juergen Moser
Article
Multidisciplinary Sciences
Christina Elisabeth Anna Engel, David Vorlaender, Rebekka Biedendieck, Rainer Krull, Katrin Dohnt
Article
Electrochemistry
Fabian Kubannek, Simone Thiel, Boyke Bunk, Katharina Huber, Joerg Overmann, Ulrike Krewer, Rebekka Biedendieck, Dieter Jahn
Article
Microbiology
Ilse M. Boekhoud, Annika-Marisa Michel, Jeroen Carver, Dieter Jahn, Wiep Klaas Smits
Review
Biochemical Research Methods
Wei He, Alexander Heinz, Dieter Jahn, Karsten Hiller
Summary: Macrophages play a crucial role in combating infection and supporting tissue recovery post pathogen clearance, requiring metabolic reprogramming to provide sufficient energy and metabolites. Recent studies have shown that certain metabolic intermediates can directly control macrophage activation and effector functions, with citrate, succinate, and itaconate playing key roles in modulating immune responses.
CURRENT OPINION IN BIOTECHNOLOGY
(2021)
Article
Crystallography
Marta Kubiak, Janine Mayer, Ingo Kampen, Carsten Schilde, Rebekka Biedendieck
Summary: Enzymes can be crystallized and immobilized to form cross-linked enzyme crystals (CLECs), with different PGAs showing varying mechanical stability and activity. Bacillus species FJAT-PGA CLECs exhibited the highest hardness and Young's modulus, while FJAT- and BtPGA CLECs also displayed significantly higher volumetric activities compared to BmPGA CLECs.
Review
Biotechnology & Applied Microbiology
Rebekka Biedendieck, Tobias Knuuti, Simon J. Moore, Dieter Jahn
Summary: Over the past 30 years, the Gram-positive bacterium Priestia megaterium has been developed for various biotechnological applications, including the production of vitamin B12, polymers like PHB, and proteins both in vivo and in vitro. The bacterium's characteristics for recombinant protein production and its versatility as a biological tool kit have been highlighted, along with its potential applications in plant protection.
APPLIED MICROBIOLOGY AND BIOTECHNOLOGY
(2021)
Article
Microbiology
Janine Mayer, Tobias Knuuti, Lisa Baumgarten, Elise Menke, Lena Bischoff, Boyke Bunk, Rebekka Biedendieck
Summary: The secretion of recombinant proteins is crucial for their economic production and purification. A plasmid-based signal peptide (SP) library has been established to facilitate the identification of suitable SPs for specific proteins. The functionality of the library has been demonstrated by increasing the secretion of alpha-amylase by 1.6-fold and significantly enhancing the secretion of another protein, penicillin G acylase.
Article
Chemistry, Multidisciplinary
Jan Wichmann, Janine Mayer, Mattes Hintmann, Peer Lukat, Wulf Blankenfeldt, Rebekka Biedendieck
Summary: In this study, we successfully enhanced the crystallizability of a penicillin G acylase (PGA) from Bacillus sp. FJAT-27231 (FJAT-PGA) using protein engineering techniques. The improvements were achieved through surface entropy reduction and strengthening of hydrophobic interactions at crystal contacts, leading to accelerated crystallization, lower required PGA and precipitant concentrations, increased crystal yield, and improved impurity tolerance. A total of twelve amino acid exchanges and one deletion resulted in the best crystallizability achieved in this study.
CRYSTAL GROWTH & DESIGN
(2023)
Article
Biotechnology & Applied Microbiology
Janine Mayer, Jan Pippel, Gabriele Guenther, Carolin Mueller, Anna Lauermann, Tobias Knuuti, Wulf Blankenfeldt, Dieter Jahn, Rebekka Biedendieck
APPLIED MICROBIOLOGY AND BIOTECHNOLOGY
(2019)
