Review
Immunology
Yinxi Zhou, Jinghua Xia, Shuonan Xu, Tao She, Yanning Zhang, Ying Sun, Miaomiao Wen, Tao Jiang, Yanlu Xiong, Jie Lei
Summary: The development and growth of tumors pose a significant and ongoing threat to human life globally. Despite the remarkable progress achieved by advanced therapeutic strategies such as immune checkpoint therapy and CAR-T in treating solid and hematological malignancies, the malignant initiation and progression of cancer remains controversial and requires further research. Experimental animal models not only have great advantages in simulating tumor occurrence, development, and malignant transformation mechanisms, but also can be used to evaluate the therapeutic effects of diverse clinical interventions, gradually becoming indispensable in cancer research. This paper reviews recent research progress in mouse and rat models, focusing on spontaneous, induced, transgenic, and transplantable tumor models, aiming to provide guidance for future studies on malignant mechanisms and tumor prevention.
FRONTIERS IN IMMUNOLOGY
(2023)
Review
Neurosciences
Naruhiko Sahara, Rin Yanai
Summary: Neurofibrillary tangles composed of hyperphosphorylated tau protein are key features of tauopathy. However, there is a limited number of animal models that display intracellular tau pathology. Recent studies have shown that transgenic mice expressing mutant tau successfully develop neurofibrillary pathology, but there are limitations and pitfalls to be addressed.
FRONTIERS IN NEUROSCIENCE
(2023)
Editorial Material
Multidisciplinary Sciences
Neal D. Amin, Sergiu P. Pasca
Summary: Two research groups have developed self-organizing models of mouse embryos using stem cells in vitro, which can mimic mid-gestation embryos and provide an exceptional opportunity for studying early embryonic development.
Article
Oncology
Angelina T. Regua, Austin Arrigo, Daniel Doheny, Grace L. Wong, Hui-Wen Lo
Summary: Transgenic breast cancer mouse models are essential for preclinical studies, allowing for modeling of abnormal genetic events commonly seen in human breast cancers. By employing tissue-specific genetic manipulation, these models can mimic spontaneous mammary tumorigenesis by expressing oncogenes or deleting tumor suppressors. The variability in characteristics and strain-dependent features of these models can be utilized to study different aspects of mammary tumorigenesis and metastasis.
Article
Biotechnology & Applied Microbiology
Saratram Gopalakrishnan, Chintan J. Joshi, Miguel A. Valderrama-Gomez, Elcin Icten, Pablo Rolandi, William Johnson, Cleo Kontoravdi, Nathan E. Lewis
Summary: Genome-scale metabolic models can be customized to simulate condition-specific physiology by using omics data. The choice of algorithm and the existence of alternate context-specific models can impact the quality of these models. In this study, various extraction methods were evaluated for microbial and mammalian model extraction, and it was found that protecting the metabolic tasks defining an organism's phenotype is crucial. The algorithm choice and the topological properties of the parent genome-scale model greatly influence the scope of alternate models. mCADRE generated the most reproducible context-specific models, while MBA had the most alternate solutions. GIMME performed well in E. coli, while mCADRE was better suited for complex mammalian models.
METABOLIC ENGINEERING
(2023)
Review
Genetics & Heredity
Shan Tang, Birkan Gokbag, Kunjie Fan, Shuai Shao, Yang Huo, Xue Wu, Lijun Cheng, Lang Li
Summary: Synthetic lethality refers to the interaction of two genes that leads to cell or organism death when both are perturbed, but does not affect viability when only one gene is altered. The exploration of experimental technologies and predictive models in studying synthetic lethal gene pairs contribute to our understanding of cancer biology and the development of cancer therapies.
FRONTIERS IN GENETICS
(2022)
Article
Biology
Elizabeth A. Hobson, Matthew J. Silk, Nina H. Fefferman, Daniel B. Larremore, Puck Rombach, Saray Shai, Noa Pinter-Wollman
Summary: Analyzing social networks is challenging and requires non-standard statistical methods. Generating effective reference models involves four approaches, including permutation, resampling, sampling from a distribution, and generative models. Researchers need to be aware of potential pitfalls to avoid.
BIOLOGICAL REVIEWS
(2021)
Article
Biology
Nardus Mollentze, Deborah Keen, Uuriintuya Munkhbayar, Roman Biek, Daniel G. Streicker
Summary: The transmission of SARS-CoV-2 from humans to other species poses a threat to wildlife conservation and can lead to the emergence of new sources of viral diversity. Researchers have developed computational heuristics to identify susceptible host species based on the variation in the ACE2 receptor used by the virus. However, the predictive performance of these heuristics remains uncertain. This study shows that while ACE2 variation can accurately predict animal susceptibility to sarbecoviruses, the predictions are primarily based on host phylogeny rather than infection biology.
Review
Zoology
Luara Tourinho, Mariana M. Vale
Summary: Researchers compared different models for estimating species' niche and distribution, finding that mechanistic and correlative models have different strengths and limitations. Hybrid models combining both approaches were considered promising. However, the best approach depends on the specific context and research objectives.
INTEGRATIVE ZOOLOGY
(2023)
Review
Endocrinology & Metabolism
Yu Gu, Tung Bui, William J. Muller
Summary: Breast cancer recurrence and metastasis remain major challenges for disease treatment. Understanding the biology of dormant tumors and cancer cells is crucial for overcoming clinical obstacles. Mouse models, particularly immunocompetent transgenic models, offer versatility and potential for studying the mechanisms of dormancy and developing therapeutic strategies.
Review
Pediatrics
Florian Friedmacher, Udo Rolle, Prem Puri
Summary: This article provides an up-to-date overview of congenital diaphragmatic hernia (CDH), including its implicated transcription factors, molecules regulating cell migration, and components contributing to extracellular matrix formation. The article also discusses the significance of genetic models in studying altered lung development in relation to the human situation.
FRONTIERS IN PEDIATRICS
(2022)
Article
Nanoscience & Nanotechnology
Tanmoy Saha, Jayanta Mondal, Sachin Khiste, Hrvoje Lusic, Zhang-Wei Hu, Ruparoshni Jayabalan, Kevin J. Hodgetts, HaeLin Jang, Shiladitya Sengupta, Somin Eunice Lee, Younggeun Park, Luke P. Lee, Aaron Goldman
Summary: This research presents two innovative delivery strategies combining nanotechnology with cancer medicine to target different drug resistance mechanisms, bypassing resistance barriers through engineering strategies, and inducing cell killing through multimodal mechanisms including nanophotonic mechanisms.
Review
Biochemistry & Molecular Biology
Beatriz Martin-Carro, Javier Donate-Correa, Sara Fernandez-Villabrille, Julia Martin-Virgala, Sara Panizo, Natalia Carrillo-Lopez, Laura Martinez-Arias, Juan F. F. Navarro-Gonzalez, Manuel Naves-Diaz, Jose L. Fernandez-Martin, Cristina Alonso-Montes, Jorge B. Cannata-Andia
Summary: Preclinical biomedical models play a fundamental role in advancing our understanding and management of diseases, particularly diabetes mellitus. This is because the pathophysiological and molecular mechanisms underlying diabetes development are not fully understood, and there is currently no cure for the disease.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2023)
Article
Neurosciences
Brianna Gurdon, Catherine Kaczorowski
Summary: Alzheimer's disease is a complex disease mediated by numerous factors, with research focusing on how imaging modalities can be integrated into systems biology approaches to understand the genotype to phenotype relationship driving disease development. By combining imaging and omics data, AD can be classified into subtypes, paving the way for precision medicine solutions to prevent and treat the disease.
NEUROBIOLOGY OF DISEASE
(2021)
Article
Biotechnology & Applied Microbiology
R. P. van Rosmalen, R. W. Smith, V. A. P. Martins dos Santos, C. Fleck, M. Suarez-Diez
Summary: Constraint-based, genome-scale metabolic models are crucial for guiding metabolic engineering, but lack the time dimension and enzyme dynamics. Model reduction can bridge the gap between these models and kinetic models, allowing integration into the Design Built-Test-Learn cycle. These reduced size models can represent the dynamics of the original model and enable further exploration of dynamic responses in metabolic networks.
METABOLIC ENGINEERING
(2021)
