Article
Biochemistry & Molecular Biology
Yuanyuan Huang, Yanfei Wu, Han Hu, Bangzhuo Tong, Jie Wang, Siyu Zhang, Yanyi Wang, Jicong Zhang, Yue Yin, Shengkun Dai, Wenjuan Zhao, Bolin An, Jiahua Pu, Yaomin Wang, Chao Peng, Nan Li, Jiahai Zhou, Yan Tan, Chao Zhong
Summary: This study describes a technological workflow that facilitates the design and development of engineered living materials (ELMs) through the integration of bioinformatics, structural biology, and synthetic biology technologies. By developing a bioinformatics software called Bacteria Biopolymer Sniffer (BBSniffer), the researchers are able to identify bacteria and biopolymers of interest. Using genetic manipulation and structural characterization, a programmable bacterium was identified in the industrial workhorse Corynebacterium glutamicum, enabling the design of ELMs.
NATURE CHEMICAL BIOLOGY
(2023)
Article
Psychology, Multidisciplinary
Denis Chenevert, Tyler L. Brown, Marie-Pascale Pomey, Nadia Benomar, Philippe Colombat, Evelyne Fouquereau, Carmen G. Loiselle
Summary: Multidisciplinary teams, especially cancer care teams, often face challenges that can lead to higher levels of distress and burnout. Resilience is emerging as a critical resource that can optimize team members' psychological health and wellbeing, work efficiency, and organizational agility, while reducing burnout. This study aims to implement and evaluate a participatory interventional approach to foster team resilience and determine whether enhanced resilience improves team mental health status and organizational outcomes.
FRONTIERS IN PSYCHOLOGY
(2022)
Article
Biochemistry & Molecular Biology
Qian Liu, Pingzhao Hu
Summary: In precise medicine, computational frameworks for identifying prognostic biomarkers that capture the multi-genomic and phenotypic heterogeneity of breast cancer (BC) are of great value. However, previous radiogenomic studies have suffered from data incompleteness, feature subjectivity, and low interpretability. This study proposed a novel framework for identifying radiogenomic prognostic biomarkers for BC, addressing the limitations of previous studies. The framework includes an explainable DL model for image feature extraction, a Bayesian tensor factorization for multi-genomic feature extraction, a strategy to leverage unpaired data, and mediation analysis for further interpretation. The biomarkers identified by this framework outperformed traditional baseline radiogenomic biomarkers and had guaranteed interpretability through built-in and follow-up analyses.
COMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL
(2022)
Article
Chemistry, Multidisciplinary
Aayush Arya, Jessica Ray, Siddhant Sharma, Romulo Cruz Simbron, Alejandro Lozano, Harrison B. Smith, Jakob Lykke Andersen, Huan Chen, Markus Meringer, Henderson James Cleaves
Summary: The study focuses on a central question in the origins of life research, investigating the connection between non-entailed chemical processes and highly entailed ones. By developing an open-source chemoinformatic workflow, the researchers aim to model abiological chemistry and discover the entailment. The workflow automates the generation and analysis of chemical reaction networks and can help identify autocatalysis and potential self-organization in complex chemical systems.
Review
Biochemistry & Molecular Biology
Ravian L. van Ineveld, Esmee J. van Vliet, Ellen J. Wehrens, Maria Alieva, Anne C. Rios
Summary: This article introduces the importance and potential applications of 3D imaging in cancer research. 3D imaging provides more accurate information about the cellular composition and structure of cancer, and offers new strategies and methods for cancer treatment and patient diagnosis.
Review
Business
Charles Calderwood, Lieke L. ten Brummelhuis, Amanda S. Patel, Trevor Watkins, Allison S. Gabriel, Christopher C. Rosen
Summary: This review provides a cross-disciplinary synthesis of evidence on the implications of physical activity for job performance and proposes a resource-based framework to guide future research in this area.
JOURNAL OF MANAGEMENT
(2021)
Article
Oncology
Richard J. Chen, Ming Y. Lu, Drew F. K. Williamson, Tiffany Y. Chen, Jana Lipkova, Zahra Noor, Muhammad Shaban, Maha Shady, Mane Williams, Bumjin Joo, Faisal Mahmood
Summary: Computational pathology has shown promise in developing prognostic models based on histology images. This study uses multimodal deep learning to integrate pathology images and molecular profile data, and discover prognostic features that correlate with outcomes.
Article
Chemistry, Analytical
Chenxin Zhu, Shuang Yang, Hengchao Li, Yuning Wang, Yueting Xiong, Fenglin Shen, Lei Zhang, Pengyuan Yang, Xiaohui Liu
Summary: The study improved the sample preparation method by introducing MOSF, significantly reducing the time required for sample handling. The RSP-MOSF method demonstrated excellent performance in protein and peptide identification, quantitation, and reproducibility, suggesting potential application on an automated platform for further scaled analysis.
Review
Computer Science, Artificial Intelligence
Heba Askr, Enas Elgeldawi, Heba Aboul Ella, Yaseen A. M. M. Elshaier, Mamdouh M. Gomaa, Aboul Ella Hassanien
Summary: Recently, there has been a lot of attention on using artificial intelligence (AI) in drug discovery due to its ability to significantly reduce the time and cost of developing new drugs. This paper presents a systematic literature review (SLR) that integrates recent advancements in deep learning (DL) technology and its applications in various stages of drug development. The review covers topics such as drug-target interactions (DTIs), drug-drug similarity interactions (DDIs), drug sensitivity and responsiveness, and drug-side effect predictions. The paper also provides an overview of explainable AI (XAI) in supporting drug discovery problems, discusses drug dosing optimization and success stories, and proposes digital twining (DT) and open issues as future research challenges. Challenges to be addressed and future research directions are identified, and an extensive bibliography is included.
ARTIFICIAL INTELLIGENCE REVIEW
(2023)
Article
Engineering, Environmental
Miao Yu, Susan L. Teitelbaum, Georgia Dolios, Lam-Ha T. Dang, Peijun Tu, Mary S. Wolff, Lauren M. Petrick
Summary: This study utilized metabolomics to identify molecular linkages between various exposures and health conditions, and proposed the concept of molecular gatekeepers that connect exposure biomarkers with endogenous metabolites. The findings highlight the importance of these molecular gatekeepers in understanding the relationships between exposures and health outcomes that may be obscured by complex interactions.
ENVIRONMENTAL SCIENCE & TECHNOLOGY
(2022)
Article
Chemistry, Multidisciplinary
Shiyang Lin, Mai Yang, Jiajie Chen, Wei Feng, Yu Chen, Yufang Zhu
Summary: In this study, 2D semiconductor FePS3 nanosheets were synthesized as both sonosensitizer and Fenton catalyst. The FePS3-PEG NSs exhibited enhanced ROS generation and significant glutathione depletion, leading to effective and safe tumor inhibition and prolonged survival in tumor-bearing mice. This work provides a new approach for the application of 2D metal phosphorus trichalcogenides in biomedicine.
Article
Pharmacology & Pharmacy
M. Berretta, A. Morra, R. Taibi, F. Monari, N. Maurea, M. Ippolito, U. Tirelli, F. Fiorica, L. Montella, G. Facchini, V. Quagliariello, M. Montopoli
Summary: This study described the clinical cases of four cancer patients who received integrative medicine treatment, showing that this approach can improve patients' quality of life and extend the overall survival in some cases.
FRONTIERS IN PHARMACOLOGY
(2022)
Article
Biochemistry & Molecular Biology
Xinbin Dai, Zhaohong Zhuang, Clarissa Boschiero, Yibo Dong, Patrick X. Zhao
Summary: Legumes have been contributing to human health and sustainable food production for centuries. The study of model legumes is important for deciphering key genes and pathways. The LegumeIP V3 database provides valuable data and tools for identifying important genes in non-model legume crops.
NUCLEIC ACIDS RESEARCH
(2021)
Article
Biochemistry & Molecular Biology
Hatairat Yingtaweesittikul, Jiaxi Wu, Aanchal Mongia, Rafael Peres, Karrie Ko, Niranjan Nagarajan, Chayaporn Suphavilai
Summary: The development of CREAMMIST, an integrative database for cancer drug response, allows researchers to capture uncertainty and utilize available data for downstream analyses, providing valuable insights for cancer pharmacogenomics research.
NUCLEIC ACIDS RESEARCH
(2023)
Article
Pharmacology & Pharmacy
Jingtao Chen, Chao Niu, Ning Yang, Chunyan Liu, Shan-shan Zou, Shan Zhu
Summary: Liver cancer is a common malignancy, with high morbidity and mortality. Despite progress in treatment, the overall survival rate of patients has not significantly improved. This review highlights the importance of identifying specific liver cancer biomarkers for early screening, accurate diagnosis, prognosis, and prevention of tumor progression. It also discusses the latest research progress and potential applications in biomarker discovery.
PHARMACOLOGICAL RESEARCH
(2023)
Editorial Material
Biology
Heiko Enderling
PHYSICS OF LIFE REVIEWS
(2022)
Article
Biochemical Research Methods
Narmin Ghaffari Laleh, Chiara Maria Lavinia Loeffler, Julia Grajekid, Katerina Stankova, Alexander T. Pearson, Hannah Sophie Muti, Christian Trautwein, Heiko Enderling, Jan Poleszczuk, Jakob Nikolas Kather
Summary: This study fitted differential equation models to tumor volume measurements of patients undergoing chemotherapy or cancer immunotherapy. The Gompertz model provided the best fit to the data and the general Bertalanffy and Gompertz models performed best in predicting treatment outcome. The study provides a benchmark for classical textbook models and state-of-the-art models of human tumor growth.
PLOS COMPUTATIONAL BIOLOGY
(2022)
Article
Chemistry, Medicinal
Kendall Carrasco, Camille Montersino, Carine Derviaux, Magali Saez-Ayala, Laurent Hoffer, Audrey Restouin, Remy Castellano, Justine Casassa, Philippe Roche, Eddy Pasquier, Sebastien Combes, Xavier Morelli, Yves Collette, Stephane Betzi
Summary: A BDII-selective compound was discovered through screening the Fr-PPIChem chemical library, showing low activity in cell-based assays but the ability to modulate anti-leukemic activity in combination with various drugs in a cell- and context-dependent differential manner.
JOURNAL OF MEDICINAL CHEMISTRY
(2022)
Article
Oncology
Rebecca A. Bekker, Mohammad U. Zahid, Jennifer M. Binning, Bryan Q. Spring, Patrick Hwu, Shari Pilon-Thomas, Heiko Enderling
Summary: Immunotherapies have revolutionized oncology by delivering unprecedented response rates in the treatment of certain cancers. However, the reasons for varying responses among patients remain unclear. Understanding the tumor microenvironment and the tumor-immune ecosystem is crucial in predicting treatment outcomes. This article highlights the potential of integrated mathematical oncology approaches in conceptualizing the impact of immunotherapies on tumor response and introducing combination therapies to improve patient outcomes.
JOURNAL FOR IMMUNOTHERAPY OF CANCER
(2022)
Article
Medicine, General & Internal
Mailys Rossi, Julie Talbot, Patricia Piris, Marion Le Grand, Marie-Pierre Montero, Melanie Matteudi, Emilie Agavnian-Couquiaud, Romain Appay, Celine Keime, Daniel Williamson, Duje Buric, Veronique Bourgarel, Laetitia Padovani, Steven C. Clifford, Olivier Ayrault, Eddy Pasquier, Nicolas Andre, Manon Carre
Summary: This study demonstrates the potential of beta-blockers as enhancers of radiotherapy in medulloblastoma, which may improve the treatment and quality of life of children with high-risk brain tumors.
Article
Oncology
Evangeline R. Jackson, Ryan J. Duchatel, Dilana E. Staudt, Mika L. Persson, Abdul Mannan, Sridevi Yadavilli, Sarah Parackal, Shaye Game, Wai Chin Chong, W. Samantha N. Jayasekara, Marion Le Grand, Padraic S. Kearney, Alicia M. Douglas, Izac J. Findlay, Zacary P. Germon, Holly P. McEwen, Tyrone S. Beitaki, Adjanie Patabendige, David A. Skerrett-Byrne, Brett Nixon, Nathan D. Smith, Bryan Day, Neevika Manoharan, Sumanth Nagabushan, Jordan R. Hansford, Dinisha Govender, Geoff B. McCowage, Ron Firestein, Meegan Howlett, Raelene Endersby, Nicholas G. Gottardo, Frank Alvaro, Sebastian M. Waszak, Martin R. Larsen, Yolanda Colino-Sanguino, Fatima Valdes-Mora, Andria Rakotomalala, Samuel Meignan, Eddy Pasquier, Nicolas Andre, Esther Hulleman, David D. Eisenstat, Nicholas A. Vitanza, Javad Nazarian, Carl Koschmann, Sabine Mueller, Jason E. Cain, Matthew D. Dun
Summary: Diffuse midline gliomas are highly lethal childhood cancers. Palliative radiotherapy is the only established treatment with limited survival benefits. ONC201, a combination of a DRD2 antagonist and ClpP agonist, has shown promising preclinical and emerging clinical efficacy in treating diffuse intrinsic pontine gliomas. Further research is needed to understand the mechanisms of response, the impact of recurring genomic features, and the potential combination therapy with a brain penetrant PI3K/Akt inhibitor, paxalisib.
Article
Oncology
Isha Harshe, Heiko Enderling, Renee Brady-Nicholls
Summary: Accurately predicting tumor growth is crucial for effective treatment. This study investigated the number of volume measurements needed to predict breast tumor growth dynamics. By calibrating the model using data from 18 untreated breast cancer patients, it was determined that the number of measurements required depended on the noise level and acceptable error of model parameters. This research provides a metric for clinicians to confidently predict patient-specific tumor growth dynamics and make informed treatment decisions.
Article
Pharmacology & Pharmacy
Aswin Anand Pai, Ezhilpavai Mohanan, John C. Panetta, Uday P. Kulkarni, Raveen Stephen Stallon Illangeswaran, Balaji Balakrishnan, Agila Jayaraman, Eunice S. Edison, Kavitha M. Lakshmi, Anup J. Devasia, Nambiathayil Aboobacker Fouzia, Anu Korula, Aby Abraham, Biju George, Alok Srivastava, Vikram Mathews, Joseph F. Standing, Poonkuzhali Balasubramanian
Summary: A new chemotherapy regimen has significantly improved hematopoietic stem cell transplantation outcomes for patients with high-risk beta-thalassemia major, but complications still exist. A study on the dose-exposure-response relationship of treosulfan reveals that lower exposure increases the risk of graft rejection and early transplant-related mortality. Therapeutic drug monitoring-based dose adjustment may be beneficial.
CLINICAL PHARMACOLOGY & THERAPEUTICS
(2023)
Article
Medicine, General & Internal
Jeremy Ariey-Bonnet, Raphael Berges, Marie-Pierre Montero, Baptiste Mouysset, Patricia Piris, Kevin Muller, Guillaume Pinna, Tim W. Failes, Greg M. Arndt, Philippe Morando, Nathalie Baeza-Kallee, Carole Colin, Olivier Chinot, Diane Braguer, Xavier Morelli, Nicolas Andre, Manon Carre, Emeline Tabouret, Dominique Figarella-Branger, Marion Le Grand, Eddy Pasquier
Summary: This study identified targetable vulnerabilities in glioblastoma using high-throughput screening, target deconvolution, and functional genomics. They validated the role of the top gene hit and discovered pharmacological synergisms through drug combination screens. The efficacy of the AURKA/BET inhibitor combination in glioblastoma was confirmed in pre-clinical models.
Article
Chemistry, Multidisciplinary
Patricia Piris, Duje Buric, Toshihide Yamasaki, Paul Huchede, Mailys Rossi, Melanie Matteudi, Marie-Pierre Montero, Anne Rodallec, Romain Appay, Christine Roux, Sebastien Combes, Eddy Pasquier, Marie Castets, Nicolas Andre, Paul Bremond, Manon Carre
Summary: Brain tumors, particularly glioblastoma and medulloblastoma, are highly lethal and difficult to treat. This study presents a novel approach using alkoxyamines and a bioconjugate called ALK4-MMPp to inhibit the progression of these tumors. The compounds showed promising results in in vitro and in vivo experiments, suggesting their potential as effective anticancer drug candidates. The study also developed innovative models to monitor treatment response and demonstrated the selective targeting of tumor cells without significant damage to normal brain tissue.
Article
Biology
Nuverah Mohsin, Heiko Enderling, Renee Brady-Nicholls, Mohammad U. Zahid
Summary: Mathematical modeling is crucial in understanding radiobiology and designing treatment approaches in radiotherapy for cancer. This study compares three tumor volume dynamics models and analyzes the implications of model selection. A new metric, the point of maximum reduction of tumor volume (MRV), is introduced to quantify the impact of radiotherapy. The results emphasize the importance of caution in selecting models of response to radiotherapy due to the artifacts imposed by each model.
JOURNAL OF THEORETICAL BIOLOGY
(2024)
Meeting Abstract
Oncology
Andria Rakotomalala, Paul Lewandowski, Quentin Bailleul, Clara Savary, Melanie Arcicasa, Christine Bal, Maud Hamadou, Paul Huchede, Audrey Restouin, Remy Castellano, Yves Collette, Audrey Vincent, Pierre-Olivier Angrand, Eric Adriaenssens, Xuefen Le Bourhis, Pierre Leblond, Marie Castets, Eddy Pasquier, Alessandro Furlan, Samuel Meignan
Meeting Abstract
Oncology
Izac Findlay, Dilana Staudt, Padraic Kearney, Holly McEwen, Ryan Duchatel, Evangeline Jackson, Tyrone Beitaki, Nathan Smith, Nicholas Vitanza, Ron Firestein, Jason Cain, Sabine Mueller, Eddy Pasquier, Carl Koschmann, Esther Hulleman, Javad Nazarian, Mitchell Hansen, Frank Alvaro, Melissa Davis, Sebastian Waszak, Matthew Dun
Meeting Abstract
Oncology
Evangeline Jackson, Ryan Duchatel, Mika Persson, Abdul Mannan, Sridevi Yadavilli, Sarah Parackal, Shaye Game, Wai Chin Chong, Samantha Jayasekara, Marion Le Grand, Padraic Kearney, Alicia Douglas, Izac Findlay, Dilana Staudt, Zacary Germon, David Skerrett-Byrne, Brett Nixon, Nathan Smith, Esther Hulleman, Bryan Day, Geoffrey McCowage, Frank Alvaro, Sebastian Waszak, Martin Larsen, Yolanda Colino-Sanguino, Fatima Valdes-Mora, Andria Rakotomalala, Samuel Meignan, Eddy Pasquier, Nicholas Vitanza, Javad Nazarian, Carl Koschmann, Jason Cain, Sabine Mueller, Matthew Dun
Meeting Abstract
Oncology
Matthew D. Dun, Evangeline R. Jackson, Ryan J. Duchatel, Mika L. Persson, Abdul Mannan, Sridevi Yadavilli, Sarah Parackal, Shaye Game, Wai Chin Chong, Samantha Jayasekara, Marion Le Grand, Padraic S. Kearney, Alicia M. Douglas, Izac J. Findlay, Dilana Staudt, Zacary P. Germon, David A. Skerrett-Byrne, Brett Nixon, Nathan D. Smith, Esther Hulleman, Bryan Day, Geoff B. McCowage, Frank Alvaro, Sebastian M. Waszak, Martin R. Larsen, Yolanda Colino-Sanguino, Fatima Valdes-Mora, Andria Rakotomalala, Samuel Meignan, Eddy Pasquier, Nicholas A. Vitanza, Javad Nazarian, Carl Koschmann, Jason Cain, Sabine Mueller