scholarly journals Bioengineered Skin Intended for Skin Disease Modeling

2019 ◽  
Vol 20 (6) ◽  
pp. 1407 ◽  
Author(s):  
Maria Sarkiri ◽  
Stephan Fox ◽  
Lidy Fratila-Apachitei ◽  
Amir Zadpoor
Keyword(s):  
Drug Screening ◽  
Skin Disease ◽  
Large Scale ◽  
Disease Modeling ◽  
Clinical Use ◽  
Ethical Considerations ◽  
Efficient Replication ◽  
Skin Conditions ◽  
Bioengineered Skin ◽  
Native Skin

Clinical use of bioengineered skin in reconstructive surgery has been established for more than 30 years. The limitations and ethical considerations regarding the use of animal models have expanded the application of bioengineered skin in the areas of disease modeling and drug screening. These skin models should represent the anatomical and physiological traits of native skin for the efficient replication of normal and pathological skin conditions. In addition, reliability of such models is essential for the conduction of faithful, rapid, and large-scale studies. Therefore, research efforts are focused on automated fabrication methods to replace the traditional manual approaches. This report presents an overview of the skin models applicable to skin disease modeling along with their fabrication methods, and discusses the potential of the currently available options to conform and satisfy the demands for disease modeling and drug screening.

scholarly journals A novel artificial lung organoid for simulating a patient derived adenocarcinoma of lung for personalized oncology

2021 ◽  
Author(s):  
Sally Esmail ◽  
Wayne R Danter
Keyword(s):  
Drug Screening ◽  
Large Scale ◽  
Disease Modeling ◽  
Standard Of Care ◽  
Cancer Drug ◽  
Genetic Profile ◽  
Precision Oncology ◽  
Mutational Profiling ◽  
Approved Drugs ◽  
The Individual

ABSTRACTOptimizing patient care based on precision oncology will inevitably become the standard of care. If we accept the principle that every persons’ cancer is different then the most effective therapies will have to be designed for the individual patient and for their tumors genetic profile. Access to tumor mutational profiling is now widely available but continues to be limited by cost and actionable information. For example, novel combinations of approved drugs are rarely considered. These considerations lead us to hypothesize that artificially induced Lung Adenocarcinoma (LUAD) derived lung organoids could provide a novel, alternate approach for LUAD disease modeling and large-scale targeted drug screening.In this project, we used data from a commercially available tumor mutation profile to generate and then validate the artificially induced LUAD-derived lung organoid simulations (aiLUNG-LUAD) to model LUAD and identify several drug combinations that effectively reverse the tumors’ genotypic and phenotypic features when compared with placebo. These results complement previous LUAD-derived lung organoids research and provide a novel and widely applicable cancer drug-screening approach for precision/individualized oncology.

scholarly journals Advancing Drug Discovery for Neurological Disorders Using iPSC-Derived Neural Organoids

2021 ◽  
Vol 22 (5) ◽  
pp. 2659
Author(s):  
Gianluca Costamagna ◽  
Giacomo Pietro Comi ◽  
Stefania Corti
Keyword(s):  
Drug Discovery ◽  
Drug Screening ◽  
Neural Development ◽  
Neurological Disorders ◽  
Large Scale ◽  
Three Dimensional ◽  
Induced Pluripotent Stem Cell ◽  
Cellular Level ◽  
Complex Data ◽  
Complex Data Sets

In the last decade, different research groups in the academic setting have developed induced pluripotent stem cell-based protocols to generate three-dimensional, multicellular, neural organoids. Their use to model brain biology, early neural development, and human diseases has provided new insights into the pathophysiology of neuropsychiatric and neurological disorders, including microcephaly, autism, Parkinson’s disease, and Alzheimer’s disease. However, the adoption of organoid technology for large-scale drug screening in the industry has been hampered by challenges with reproducibility, scalability, and translatability to human disease. Potential technical solutions to expand their use in drug discovery pipelines include Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) to create isogenic models, single-cell RNA sequencing to characterize the model at a cellular level, and machine learning to analyze complex data sets. In addition, high-content imaging, automated liquid handling, and standardized assays represent other valuable tools toward this goal. Though several open issues still hamper the full implementation of the organoid technology outside academia, rapid progress in this field will help to prompt its translation toward large-scale drug screening for neurological disorders.

scholarly journals Engineering the Vasculature of Stem-Cell-Derived Liver Organoids

Biomolecules ◽  
2021 ◽  
Vol 11 (7) ◽  
pp. 966
Author(s):  
Xv Zhang ◽  
Liling Tang ◽  
Qian Yi
Keyword(s):  
Stem Cells ◽  
Stem Cell ◽  
Drug Screening ◽  
Disease Modeling ◽  
Liver Development ◽  
Embryonic Liver ◽  
Hepatic Cells ◽  
Hepatic Vessels ◽  
Liver Organoids ◽  
Application Prospects

The vasculature of stem-cell-derived liver organoids can be engineered using methods that recapitulate embryonic liver development. Hepatic organoids with a vascular network offer great application prospects for drug screening, disease modeling, and therapeutics. However, the application of stem cell-derived organoids is hindered by insufficient vascularization and maturation. Here, we review different theories about the origin of hepatic cells and the morphogenesis of hepatic vessels to provide potential approaches for organoid generation. We also review the main protocols for generating vascularized liver organoids from stem cells and consider their potential and limitations in the generation of vascularized liver organoids.

scholarly journals Human primary liver cancer–derived organoid cultures for disease modeling and drug screening

2017 ◽  
Vol 23 (12) ◽  
pp. 1424-1435 ◽  
Author(s):  
Laura Broutier ◽  
Gianmarco Mastrogiovanni ◽  
Monique MA Verstegen ◽  
Hayley E Francies ◽  
Lena Morrill Gavarró ◽  
...  
Keyword(s):  
Liver Cancer ◽  
Drug Screening ◽  
Disease Modeling ◽  
Primary Liver Cancer ◽  
Organoid Cultures

scholarly journals Untapped research opportunities in China: promising future avenues and potential concerns for aging companion animals

GeroScience ◽  
2021 ◽  
Author(s):  
Jessica M. Hoffman ◽  
Shanshan Song ◽  
Katharina Brugger ◽  
Teresa G. Valencak
Keyword(s):  
Large Scale ◽  
Companion Animals ◽  
Companion Animal ◽  
The European Union ◽  
Pet Ownership ◽  
Ethical Considerations ◽  
Aging Research ◽  
Agricultural Animal ◽  
The Usa ◽  
Laboratory Models

AbstractCompanion animals have recently been proposed as ideal translational models of human aging due to their shared susceptibility for certain diseases, similar environments, and sophisticated veterinary medicine diagnostics, all of which are not possible in rodent laboratory models. Here, we introduce and propose the study of companion animals in China as a largely untapped resource in academic and veterinary aging research. Pet ownership rates along with economic gains in the pet industry have skyrocketed over the last decade in China. Yet, the majority of research institutions still focus on agricultural animal research, not companion animals. In this perspective, we compare available pet ownership rates between the USA, the European Union, and China before focusing on the potential of companion animal aging research in China. In addition, we highlight some ethical considerations that must be addressed before large-scale companion animal aging research can be completed.

scholarly journals Classification of Skin Disease Using Deep Learning Neural Networks with MobileNet V2 and LSTM

Sensors ◽  
2021 ◽  
Vol 21 (8) ◽  
pp. 2852
Author(s):  
Parvathaneni Naga Srinivasu ◽  
Jalluri Gnana SivaSai ◽  
Muhammad Fazal Ijaz ◽  
Akash Kumar Bhoi ◽  
Wonjoon Kim ◽  
...  
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Deep Learning ◽  
Convolutional Neural Network ◽  
Skin Disease ◽  
Network Architecture ◽  
Large Scale ◽  
Short Term Memory ◽  
Convolutional Networks ◽  
Occurrence Matrix

Deep learning models are efficient in learning the features that assist in understanding complex patterns precisely. This study proposed a computerized process of classifying skin disease through deep learning based MobileNet V2 and Long Short Term Memory (LSTM). The MobileNet V2 model proved to be efficient with a better accuracy that can work on lightweight computational devices. The proposed model is efficient in maintaining stateful information for precise predictions. A grey-level co-occurrence matrix is used for assessing the progress of diseased growth. The performance has been compared against other state-of-the-art models such as Fine-Tuned Neural Networks (FTNN), Convolutional Neural Network (CNN), Very Deep Convolutional Networks for Large-Scale Image Recognition developed by Visual Geometry Group (VGG), and convolutional neural network architecture that expanded with few changes. The HAM10000 dataset is used and the proposed method has outperformed other methods with more than 85% accuracy. Its robustness in recognizing the affected region much faster with almost 2× lesser computations than the conventional MobileNet model results in minimal computational efforts. Furthermore, a mobile application is designed for instant and proper action. It helps the patient and dermatologists identify the type of disease from the affected region’s image at the initial stage of the skin disease. These findings suggest that the proposed system can help general practitioners efficiently and effectively diagnose skin conditions, thereby reducing further complications and morbidity.

scholarly journals ‘Not just a piece of skin in front of you’—a qualitative exploration of the experiences of adolescents with eczema and psoriasis with healthcare professionals

BMJ Open ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. e041108
Author(s):  
Isabella Joy de Vere Hunt ◽  
Abigail McNiven ◽  
Amanda Roberts ◽  
Himesh Parmar ◽  
Tess McPherson
Keyword(s):  
Young People ◽  
Skin Disease ◽  
Healthcare Professionals ◽  
Healthcare Delivery ◽  
Healthcare Providers ◽  
Secondary Analysis ◽  
Emotional Impact ◽  
Skin Conditions ◽  
The Uk ◽  
Qualitative Exploration

BackgroundThere is little qualitative research in the UK focussing on adolescents’ experience of their healthcare providers, and inflammatory skin conditions are a common heath problem in adolescence.AimTo explore the experiences of adolescents with eczema and psoriasis with healthcare professionals, and to distil the participants’ key messages for their healthcare providers.DesignThis is a secondary thematic analysis of interviews with adolescents with eczema or psoriasis.ParticipantsThere were a total of 41 text transcripts of interviews with young people with eczema or psoriasis who had given permission for secondary analysis; 23 of the participants had eczema, and 18 psoriasis. Participants were living in the UK at time of interview, and aged 15–24 years old.ResultsWe have distilled the following key messages from young people with eczema and psoriasis for healthcare providers: (1) address the emotional impact; (2) give more information, with the subtheme and (3) appreciate patient research. We identified the following eczema-specific themes: (ECZ-4) ‘It’s not taken seriously’; (ECZ-5) offer choice in treatment and (ECZ-6) lack of structure/conflicting advice. Two psoriasis-specific themes were identified: (PSO-4) feeling dehumanised/treat me as a person; and (PSO-5) think about how treatments will affect daily life.ConclusionThis qualitative data analysis highlights the need for greater recognition of the emotional impact of skin disease in adolescence, and for more comprehensive provision of information about the conditions. We call for greater sensitivity and flexibility in our approach to adolescents with skin disease, with important implications for healthcare delivery to this group.

scholarly journals Advances in the automated synthesis of 6-[18F]Fluoro-L-DOPA

2021 ◽  
Vol 6 (1) ◽  
Author(s):  
Ângela C. B. Neves ◽  
Ivanna Hrynchak ◽  
Inês Fonseca ◽  
Vítor H. P. Alves ◽  
Mariette M. Pereira ◽  
...  
Keyword(s):  
Large Scale ◽  
Neuroendocrine Tumours ◽  
Radiochemical Yield ◽  
Clinical Applications ◽  
Clinical Use ◽  
Molar Activity ◽  
Neuropsychiatric Diseases ◽  
Recent Developments ◽  
Key Issues ◽  
Improved Methods

AbstractThe neurotracer 6-[18F] FDOPA has been, for many years, a powerful tool in PET imaging of neuropsychiatric diseases, movement disorders and brain malignancies. More recently, it also demonstrated good results in the diagnosis of other malignancies such as neuroendocrine tumours, pheochromocytoma or pancreatic adenocarcinoma.The multiple clinical applications of this tracer fostered a very strong interest in the development of new and improved methods for its radiosynthesis. The no-carrier-added nucleophilic 18F-fluorination process has gained increasing attention, in recent years, due to the high molar activities obtained, when compared with the other methods although the radiochemical yield remains low (17–30%). This led to the development of several nucleophilic synthetic processes in order to obtain the product with molar activity, radiochemical yield and enantiomeric purity suitable for human PET studies.Automation of the synthetic processes is crucial for routine clinical use and compliance with GMP requirements. Nevertheless, the complexity of the synthesis makes the production challenging, increasing the chance of failure in routine production. Thus, for large-scale clinical application and wider use of this radiopharmaceutical, progress in the automation of this complex radiosynthesis is of critical importance.This review summarizes the most recent developments of 6-[18F]FDOPA radiosynthesis and discusses the key issues regarding its automation for routine clinical use.

Sign in / Sign up

Export Citation Format

Share Document