During the last decade, biological therapies have an increasing share in the modern therapeutics of various diseases including inflammatory bowel diseases (IBD). Animal models of IBD have often been used to identify the targets of biological therapies, to test their relevance to disease pathogenesis, to assess their therapeutic efficacy in vivo, and to check for drug toxicity. In the field of inflammatory diseases the majority of biologics under development have failed to reach the clinic. This review examines the ability of preclinical data from animal models of IBD to predict success or failure of biologics in human IBD. Specifically, it describes the murine models of IBD, the mechanism of disease induction, the phenotype of the disease, its relevance to human IBD, and the specific immunological features of disease pathogenesis in each model and mainly compares the results of the phase II and III trials of biologics in IBD with preclinical data obtained from studies in animal models. Finally, it examines the possible reasons for low success in translation from bench to bedside and offers some suggestions to improve translation rates.
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http://dx.doi.org/10.1152/ajpgi.00004.2013 | DOI Listing |
J Hematol Oncol
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Department of Gynecology, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, China.
N7-methylguanosine (m7G) is an important RNA modification involved in epigenetic regulation that is commonly observed in both prokaryotic and eukaryotic organisms. Their influence on the synthesis and processing of messenger RNA, ribosomal RNA, and transfer RNA allows m7G modifications to affect diverse cellular, physiological, and pathological processes. m7G modifications are pivotal in human diseases, particularly cancer progression.
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Biotechnology Center (BIOTEC) and Center for Molecular and Cellular Bioengineering, Technische Universität Dresden, Tatzberg 47-49, 01307, Dresden, Germany.
Extracellular membrane vesicles (EVs) offer promising values in various medical fields, e.g., as biomarkers in liquid biopsies or as native (or bioengineered) biological nanocarriers in tissue engineering, regenerative medicine and cancer therapy.
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Department of Pharmacology and Toxicology, College of Pharmacy, King Saud University, 11461, Riyadh, Saudi Arabia.
Quantitative structure-property relationship (QSPR) modeling has emerged as a pivotal tool in the field of medicinal chemistry and drug design, offering a predictive framework for understanding the correlation between chemical structure and physicochemical properties. Topological indices are mathematical descriptors derived from the molecular graphs that capture structural features and connectivity, playing a crucial role in QSPR analysis by quantitatively relating chemical structures to their physicochemical properties and biological activities. Lung cancer is characterized by its aggressive nature and late-stage diagnosis, often limiting treatment options and significantly impacting patient survival rates.
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Department of Machine Learning, Moffitt Cancer Center, Tampa, FL, USA.
AI decision support systems can assist clinicians in planning adaptive treatment strategies that can dynamically react to individuals' cancer progression for effective personalized care. However, AI's imperfections can lead to suboptimal therapeutics if clinicians over or under rely on AI. To investigate such collaborative decision-making process, we conducted a Human-AI interaction study on response-adaptive radiotherapy for non-small cell lung cancer and hepatocellular carcinoma.
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Medical Biotechnology and Immunotherapy Research Unit, Institute of Infectious Disease and Molecular Medicine, Faculty of Health Sciences, University of Cape Town, Cape Town, 7700, South Africa.
The field of gene therapy has witnessed significant advancements in the utilization of Adeno-associated virus (AAV) owing to its inherent biological advantages. Targeted AAV vectors are generated through genetic or chemical modification of the capsid for user-directed purposes. However, this process can result in imbalances in viral protein sequence homogeneity, stoichiometry, and functional transduction vector units, thereby introducing new challenges.
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