Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1016/j.neuron.2016.10.009 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Novel research model for in vitro immunotherapy: co-culturing tumor organoids with peripheral blood mononuclear cells.
Cancer Cell Int
December 2024
Division of Cancer Biology, Laboratory Animal Center, The Fourth Military Medical University, Xi'an, 710032, Shaanxi, China.
Tumor organoids have emerged as powerful tools for in vitro cancer research due to their ability to retain the structural and genetic characteristics of tumors. Nevertheless, the absence of a complete tumor microenvironment (TME) limits the broader application of organoid models in immunological studies. Given the critical role of immune cells in tumor initiation and progression, the co-culture model of organoids and peripheral blood mononuclear cells (PBMCs) may provide an effective platform for simulating the interactions between immune and tumor cells in vitro.
View Article and Find Full Text PDFExploring the Role of Exosomal lncRNA in Cancer Immunopathogenesis: Unraveling the Immune Response and EMT Pathways.
Exp Cell Res
December 2024
Medical Laboratory Technique College, The Islamic University, Najaf, Iraq; Medical Laboratory Technique College, The Islamic University of Al Diwaniyah, Al Diwaniyah, Iraq; Medical Laboratory Technique College, The Islamic University of Babylon, Babylon, Iraq. Electronic address:
Exosomes are membrane-bound vesicles secreted by diverse cell types, serving as crucial mediators in intercellular communication and significantly influencing cancer development. Exosomes facilitate complex signaling processes in the tumor microenvironment for immunomodulation, metastasis, angiogenesis, and treatment resistance. Notably, long non-coding RNAs (lncRNAs), a class of non-coding RNAs, engage with mRNA, DNA, proteins, and miRNAs to modulate gene expression through multiple mechanisms, including transcriptional, post-transcriptional, translational, and epigenetic pathways.
View Article and Find Full Text PDFRoot system architecture plasticity with beneficial rhizosphere microbes: Current findings and future perspectives.
Microbiol Res
December 2024
State Key Laboratory of Desert and Oasis Ecology, Key Laboratory of Ecological Safety and Sustainable Development in Arid Lands, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi, Xinjiang 830011, China. Electronic address:
The rhizosphere microbiota, often referred to as the plant's "second genome" plays a critical role in modulating root system architecture (RSA). Despite this, existing methods to analyze root phenotypes in the context of root-microbe interactions remain limited, and the precise mechanisms affecting RSA by microbes are still not fully understood. This review comprehensively evaluates current root phenotyping techniques relevant to plant-microbe interactions, discusses their limitations, and explores future directions for integrating advanced technologies to elucidate microbial roles in altering RSA.
View Article and Find Full Text PDFEvaluation of the Development, Implementation, Maintenance, and Impact of 3 Digital Surveillance Tools Deployed in Malawi During the COVID-19 Pandemic: Protocol for a Modified Delphi Expert Consensus Study.
JMIR Res Protoc
December 2024
Business Information Systems, University College Cork, Cork, Ireland.
Background: The COVID-19 pandemic has highlighted the importance of strengthening national monitoring systems to safeguard a globally connected society, especially those in low- and middle-income countries. Africa's rapid adoption of digital technological interventions created a new frontier of digital advancement during crises or pandemics. The use of digital tools for disease surveillance can assist with rapid outbreak identification and response, handling duties such as diagnosis, testing, contact tracing, and risk communication.
View Article and Find Full Text PDFEnhancing Clinical Decision Making by Predicting Readmission Risk in Patients With Heart Failure Using Machine Learning: Predictive Model Development Study.
JMIR Med Inform
December 2024
School of Automation, Xi'an University of Posts and Telecommunications, No. 563 Chang'an South Road, Yanta District, Xi'an, Shaanxi, 710121, China, 86 17810791125.
Background: Patients with heart failure frequently face the possibility of rehospitalization following an initial hospital stay, placing a significant burden on both patients and health care systems. Accurate predictive tools are crucial for guiding clinical decision-making and optimizing patient care. However, the effectiveness of existing models tailored specifically to the Chinese population is still limited.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!