AI-driven Small Molecule Binder Discovery Targeting Cancer
Background and significance:
Cancer is a significant health issue, projected to result in 2 million new cases and 600,000 deaths in
the United States in 2023. Although the development of targeted therapies has transformed the
treatment and clinical responses of various tumor types, many cancers, still lack effective targeted
treatment options. In part, this is due to expensive and time-consuming wet-laboratory experiments,
poor initial hit compounds and the complex and lengthy nature of drug discovery. A significant drug
discovery challenge is identifying small molecules that can bind to disease-associated targets from the
immense chemical space. Virtual screening has the potential to address this challenge; however,
current paradigms remain inefficient, routinely sampling only a tiny fraction of the vast drug-like
chemical space. Therefore, with the recent expansion of chemical libraries beyond the billion-molecule
scale, new computational strategies are essential to efficiently navigate this diverse chemical space,
facilitating the discovery of promising drug candidates for therapeutic development.
The objective of this project is to create an innovative AI-driven virtual screening platform capable of
effectively and efficiently exploring ultra-large compound libraries. The platform is intended for
widespread application in developing high-affinity small molecules for various disease-associated
protein targets. Here, it is applied to identify novel small molecule binders for Arginyl-tRNA–protein
transferase 1, a key target in developing a targeted protein degradation approach for a wide range of
cancers, but for which no known binders currently exist.
Hypothesis and rationale:
The central hypothesis is that a synergistic strategy combining advanced AI techniques with molecular
docking program can significantly enhance the efficiency of the virtual screening process while
achieving high prediction accuracy. This approach is expected to reduce the false positive rate and
improve the quality of hit compounds, yielding molecules with higher binding affinity.
Specific aims:
Develop an ultra-large virtual screening system that integrates deep learning, molecular docking and
protein-ligand binding affinity prediction to systematically explore available chemical libraries for the
discovery of ATE1 binders.
Methods:
With the exponential expansion of virtual libraries, e.g., Enamine REAL (>6.75 billion compounds),
novel approaches for rapid compound screening are imperative. We propose extending DeepDocking,
a robust search strategy, with advanced AI methods and our protein-ligand binding and affinity
prediction methods. Unlike the exhaustive search approach that mandates docking and scoring for
each molecule, our ultra-large virtual screening strategy aims to swiftly pinpoint the highest-scoring
compounds by docking only the library’s small yet most promising fractions. We employ an iterative
search method comprising seven stages: diversity measurement, ligand sampling, molecular docking,
binder identification, binder rescoring, model training, and inference.
Initially, we will select a subset of molecules for ATE-1 target molecular docking using AutoDock Vina,
followed by the prediction of binding likelihoods and affinities using DyScore and DeepAtom
respectively. High-confidence predictions will be used to train a deep neural network to fit the binder
likelihood and affinity, using only small molecule strings as inputs. Once trained, the model will infer the
hit-likeness of small molecules from diverse sets, circumventing the need for time-consuming docking
procedures. Our strategy significantly enhances the efficiency of ultra-large virtual screening by
discarding unfavorable molecules earlier in the process.
A Taste of Culture: Program implementation and training for community health educators delivering culinary-based cooking classes with a focus on whole foods, herbs and spices and kitchen skills.
Faculty Information
Name:
Dr. Melissa Vilaro
Email
mgraveley@ufl.edu
Phone
(617) 448-9302
Faculty Department/Division
UF Health Cancer Center
This project is primarily:
Translational
Research Project Description:
Background and significance:
Chronic diseases like cancer, diabetes, and cardiovascular disease are closely tied to dietary patterns. The “Taste of Culture” curriculum integrates cultural exploration, culinary skills, and evidence-based health benefits of cooking with spices and herbs. This program is one or several community-based classes offered within the UF/IFAS Extension system. County-based Extension faculty conceptualized the 4-lesson program, which covers African, Caribbean, East Asian, and South Asian cuisines. The curriculum was systematically reviewed and updated on several important factors associated with high quality health education: cultural sensitivity, health literacy, engagement, visual design, learning objectives, and use of evidence on the health benefits of the culinary use of spices and herbs. The next steps are to create/deliver/evaluate a structured training (using a train-the-trainer model) and implement the lessons in community settings and obtain pilot data via pre/post-questionnaires and health biomarkers (e.g., blood pressure and veggie meter scores) to evaluate the impact on knowledge, behavior, and health outcomes.
Herbs and spices are key components of global cuisines, they serve as flavor enhancers and are rich sources of antioxidants (Mackonochie et al., 2023; Yashin et al., 2017). Teaching learners about their bioactive properties during engaging culinary education can empower learners to adopt healthier dietary practices while promoting cultural diversity (D’Adamo et al., 2016). Herbs and spices also offer a healthy way to enhance flavors while reducing the need for salt, sugar, and saturated fats in various dishes, such as marinades, dressings, stir-fries, casseroles, soups, and curries (Isbill et al., 2020; Tapsell et al., 2006).
Broadly the work consists of the following areas:
- Community-based health promotion with a focus on cancer prevention and cancer risk reduction.
- Developing, implementing, and evaluating tailored programs and training for health educators throughout
Florida. - Interdisciplinary collaboration with undergraduate, graduate, and medical students as well as UF/IFAS
Extension faculty (aka Extension Agents). - Interactions with UF/IFAS Extension Culinary Action Team Members and other Extension working
groups/stakeholders.
Hypothesis and rationale:
Cultural tailoring ensures that health education programs align with participants’ values and practices and improves engagement, trust, and the overall impact of interventions (Kreuter et al., 2003). We hypothesize that the stakeholder-created and refined program with have high acceptability and intentions to deliver in their communities among educators and have positive impacts on health outcomes for participants who enroll and complete the 4-lesson program.
Specific Aims:
Aim 1: Evaluate results of the two-county, proof of concept, implementation of the curriculum in terms of learning data (collected pre-post).
Aim 2: Develop, deliver, and evaluate a train-the-trainer workshop to educate county health educators throughout the state, how to implement the 4-lesson program in their counties.
Methods:
Researchers will have access to proof-of-concept implementation data collected in February/March 2025 and will work with the PI and research team to review and compile data for initial insights to inform subsequent community educator training and program delivery. Researchers will prepare and submit an IRB protocol in collaboration with FYCS Master student to assess state-wide training of community educators and subsequent delivery/evaluation of the program. The research team will collaborate with students, Extension culinary action team members and PI to prepare items for the training (in-service-training agenda, slide decks, cooking demos, dates/locations of training, veggie meter and blood pressure data collection). Members of the research team can also participate in delivery and evaluation of the training as available.
Plan for data analysis:
Descriptive statistics including means, standard deviations for continuous data and percentages/frequencies for categorical data will be calculated using SPSS and/or similar data analysis software. Open-ended learner feedback will be analyzed using Sandelowski’s (2000) Qualitative Description (QD) approach – focus on the ‘who, what, and where’ of experiences without deep theorization or recontextualization (Hall & Liebenberg, 2024) .
Role of Medical Student:
The medical student will have the opportunity to participate in several aspects of the project including; paper writing (systematic review, train-the-trainer data, proof of concept pilot), data analysis, collaborative grant writing with FYCS Master student, IRB preparation, training community-based health educators, compiling evidence-based literature on health benefits of culinary levels of herbs and spices and translating to accessible teaching points for community health educators, learning how to use/collect data using veggie meter, creating training protocols for blood pressure/veggie meter collection in community-based settings.
References:
- D’Adamo, C. R., McArdle, P. F., Balick, L., Peisach, E., Ferguson, T., Diehl, A., Bustad, K., Bowden, B., Pierce, B. A., & Berman, B. M. (2016). Spice MyPlate: Nutrition Education Focusing Upon Spices and Herbs Improved Diet Quality and Attitudes Among Urban High School Students. American Journal of Health Promotion: AJHP, 30(5), 346–356. https://doi.org/10.1177/0890117116646333
- Hall, S., & Liebenberg, L. (2024). Qualitative Description as an Introductory Method to Qualitative Research for Master’s-Level Students and Research Trainees. International Journal of Qualitative Methods, 23, 16094069241242264. https://doi.org/10.1177/16094069241242264
- Isbill, J., Kandiah, J., & Kružliaková, N. (2020). Opportunities for Health Promotion: Highlighting Herbs and Spices to Improve Immune Support and Well-being. Integrative Medicine: A Clinician’s Journal, 19(5), 30–42.
- Mackonochie, M., Rodriguez-Mateos, A., Mills, S., & Rolfe, V. (2023). A Scoping Review of the Clinical Evidence for the Health Benefits of Culinary Doses of Herbs and Spices for the Prevention and Treatment of Metabolic Syndrome. Nutrients, 15(23), 4867. https://doi.org/10.3390/nu15234867
- Sandelowski, M. (2000). Whatever happened to qualitative description? Research in Nursing & Health, 23(4), 334–340. https://doi.org/10.1002/1098-240x(200008)23:4<334::aid-nur9>3.0.co;2-g
- Tapsell, L. C., Hemphill, I., Cobiac, L., Sullivan, D. R., Fenech, M., Patch, C. S., Roodenrys, S., Keogh, J. B., Clifton, P. M., Williams, P. G., Fazio, V. A., & Inge, K. E. (2006). Health benefits of herbs and spices: The past, the present, the future. Medical Journal of Australia, 185(S4). https://doi.org/10.5694/j.1326-5377.2006.tb00548.x
- Yashin, A., Yashin, Y., Xia, X., & Nemzer, B. (2017). Antioxidant Activity of Spices and Their Impact on Human Health: A Review. Antioxidants, 6(3), 70. https://doi.org/10.3390/antiox6030070
Where will the primary research take place:
The research will primarily take place in Gainesville/Alachua County. There may be opportunities to travel to UF/IFAS Extension County offices for site visits and/or training opportunities.
Does this project have an international component or travel?
No
If your project has an international component please give details (where, when, data collection involved, etc.):
N/A
In vitro and mathematical modeling the effects of treatment delays in ovarian cancer
Faculty Information
Name:
Prof. Meghan Ferrall-Fairbank
Email
mferrall.fairbanks@bme.ufl.edu
Phone
(352) 846-2762
Faculty Department/Division
Biomedical Engineering & UF Health Cancer Center
This project is primarily:
Basic
Research Project Description:
Ovarian cancer is the second most common gynecological cancer accounting for 12,740 estimated deaths in the U.S. in 2024. The difficulty in diagnosis is due to its nonspecific symptoms resulting in late stage detection and a 5-year survival rate of 50.9%. The standard of care treatment involves chemotherapy, surgical resection, and in some cases targeted therapies. Traditional therapies are administered at maximum tolerated doses, which assume that the tumor is comprised of sensitive cells to the therapy. However, often there are resistant clones inherently present in the tumor population, which evade the effects the therapy and in ovarian cancer, 80% of patients will have recurrence of their disease after first line therapeutics. Mathematical oncologists have leveraged mathematical models of tumor population dynamics to determine alternative treatment schedules. A treatment modality called adaptive therapy has been explored in clinical trials to treat metastatic prostate cancer. Using eco-evolutionary concepts, adaptive therapy schedules have been successful at personalized treatment schedules that allow for lower treatment doses and treatment holidays to avoid the dominance of resistant clones in prostate cancer. The delayed timeline of diagnosis, absence of good biomarkers and screening tools, and low progression-free survival rates in ovarian cancer highlight the need to explore alternative treatment strategies in these cancer patients.
To study the effectiveness of adaptive therapy in ovarian cancer, in-vitro growth dynamics of these tumors exposed to different chemotherapy dosages and timelines need to be collected. While previous mathematical models have been parametrize using in-vitro continuous treatment data, they fail to include treatment delays experienced by ovarian cancer cell lines. To understand this phenomenon, ovarian cancer cell lines (A2780 and Tyk-nu) including sensitive and platinum-based resistant counterparts will be used in in-vitro experiments. Both sensitive and resistant cells have been labeled with nuclear localized fluorescent lentivirus to aid ease of differentiation when co-cultured. To evaluate the effects of intermittent treatment and study treatment delays in an already established populations, cells will be allowed to in standard media for 11 days changing media every 48 hours. On day 12, the three drug concentrations will be added to different wells for the next 11 days. The effects of treatment withdraw will also be evaluated by culturing cells for 11 under the three different treatment concentrations, changing the media every 48 hours. On day 12, the treated media will be removed and replaced with standard media for the next 11 days. Six representative images of each well will be taken every 48 hours and cell counts will be abstracted using QuPath.
Leveraging the integrated experimental and mathematical modeling pipelines established by our team, cell count data will be used to parameterize a mechanistic mathematical model using ODEs. Growth rates and carrying capacities for the individual cell lines previously collected in our laboratory will be provided to aim in the modeling process shifting the focus on the evaluation of treatment delays with different modeling architectures and evaluated using Bayesian Information Criterion (BIC). Models with parameters resulting in the lowest BIC will be considered the most parsimonious and will be used to explore different treatment schedules. Both maximum tolerated doses (MTD) and adaptive therapy (AT) schedules will be tested to elucidate the most effective treatment able to control the population size, keep an equivalent sensitive and resistant cell density across the timeline and result in the lowest cumulative drug dose. MTD schedule simulations will consist of modeling the delivery of drug at the maximum tolerated dose (IC90 for this purposes) constantly (every 2 days) for 22 days. AT schedule simulations will be done in two manners: 1) drug at the maximum dose will be initially administered and then withdrawn when the population decreases 50% from the initial population size for 22 days and 2) drug dose will initially begin at the maximum tolerated dose and it would change by 25% if the population size changes by 5% for 22 days. The treatment simulations collected using this model including delay terms, will be compared with simulations resulting from parameterization of a model using only continuous treatment data lacking treatment delays. This project will aid in the identification of fundamental model parameters in ovarian cancer to help create effective treatment schedules.
Does this project have an international component or travel?
No
Investigating proteolysis in pancreatic cancer: computational insights to bench validation
Faculty Information
Name:
Prof. Meghan Ferrall-Fairbanks
Email
mferrall.fairbanks@bme.ufl.edu
Phone
(352) 846-2762
Faculty Department/Division
Biomedical Engineering & UF Health Cancer Center
This project is primarily:
Basic
Research Project Description:
Pancreatic cancer has the highest cancer-related mortality rate and will be the 2nd leading cause of cancer deaths by 2030. With no standard screening tools for detection, it is often caught at late-stages where therapeutic options are limited. Less than 20% of patients have surgically resectable disease and even using neoadjuvant therapies, 80% of patients relapse after surgery. There is a significant need to understand the underlying cellular mechanisms that support pancreatic tumor growth and treatment evasion to identify novel treatment strategies to mitigate this deadly disease. This project uses transformative approaches for determining underlying vulnerabilities in pancreatic tumor ecology to improve patient responses to therapies.
The overall goal of this research is to investigate the role of proteolytic activity on the response of cancer patients and cell lines to chemotherapeutics. Information from this project could help elucidate the use of proteases activity as a biomarker of response and the impact of treatment on that biomarker. Our central hypothesis is that treatment-resistant phenotypes have higher proteolytic activity compared to their sensitive counterparts. In Aim 1, we will investigate proteolysis of patient samples computationally through analysis of single-cell RNA sequencing datasets. The findings from Aim 1 will then be validated in Aim 2 by quantifying the expression of these proteases in vitro using pancreatic cancer cell lines available in the lab.
Aim 1. Investigate proteolysis in pancreatic cancer at single-cell resolution.
Data collection: We will compile publicly available human single-cell RNA sequencing pancreatic cancer datasets publicly available from the following publications: Werba et al Nature Communication (2023), Oh et al Nature Communication (2023), and Kim et al Genome Medicine (2024). Additional datasets will be compiled as needed.
Data analysis: All the datasets will be imported into the R and analyzed with the Seurat package. A computational pipeline developed by our lab will be used to preprocess and identify differentially expressed genes across the datasets. The expression of genes encoding for different proteases such as different cysteine proteases like cathepsins K, L, S and V will be quantified using the AddModuleScore function in R. These scores will then be compared across the datasets and based on patient response, disease status, and other common clinical information about the samples.
Aim 2. Validate single-cell proteolysis by quantify proteolysis experimentally in pancreatic cancer.
Design and assays: Four distinct pancreatic cancer cell lines (PANC-1, MIA PaCa-2, AsPC-1, BxPC-3) will be cultured with and without gemcitabine or FOLFIRINOX and then lysed for further characterization. The lysate will be used detect the presence of different cysteine proteases using Western blot, while multiplex zymography will be used to quantify their proteolytic activity. Proteases such as cathepsins K, L, S and V whose overexpression has been linked with cell immortality and proliferation in cancer, will be labeled with primary antibodies. As a control, actin or recombinant enzyme will also be labeled prior to running the assays. Secondary conjugated antibodies will be used to capture protease presence and expression through an imaging system.
Data analysis: Densitometry of zymograms and Western blots will be processed using ImageJ by extracting background noise and quantifying intensity across sensitive and resistant phenotypes for each cell type. Experiments will be done in at least triplicate and intensity values will be compared across cell likes using nonparametric tests.
Does this project have an international component or travel?
No
Iron Intake and Blood Levels in Relation to All-Cause and Cause-Specific Mortality
Faculty Information
Name:
Dr. Alex Yoon
Email
yoon.h@ufl.edu
Phone
(352) 294-5845
Faculty Department/Division
UF Health Cancer Center
This project is primarily:
Translational
Research Project Description:
Background and significance: Iron, one of the essential minerals, is a vital trace element required for the proper working of various biological functions. Iron overconsumption and overload in cells as well as high blood levels are expected to boost perturbations in immune function and hormone levels, which in turn increases the risk of developing cancers and/or dying from them. Although recent studies have shown a higher likelihood of diets high in iron and elevated total body iron among men and older Americans, indicating the possible cancer burdens attributable to iron, the overall epidemiological evidence on this issue remains elusive, and no scientific conclusions have been reached.
Hypothesis: This project hypothesizes that excessive consumption of heme-iron leads to elevated iron stores in the body, potentially increasing the risk of cancer development and associated mortality rates.
Specific Aims: Aim 1 is to evaluate cancer risk and mortality in relation to dietary intakes of heme, non-heme iron, and Aim 2 is to investigate the association of iron biomarkers with cancer risk and mortality.
Methods: This project will utilize the National Health and Nutrition Examination Survey (NHANES). NHANES collected iron intake using FFQ and 24-hour recall and measured iron biomarkers, including serum iron, ferritin, and total iron-binding capacity from the non-institutionalized civilian population of the U.S. Cox proportional hazard regression will be utilized to estimate the HRs (95% CIs) for incidence of cancer and mortality.
Plan for data analysis: Following education in statistical analysis, the medical student will do a preliminary statistical analysis for this project. The PI will oversee and validate the outcomes in collaboration with UFHCC-BCB-SR.
Role of Medical Student: The medical student will learn basic statistical analysis skills using SAS for this project, as well as drafting a manuscript. I expect to submit one manuscript during this summer research program.
Place: Primary research will take place at UF Main Campus.
References
- Siegel RL, Giaquinto AN, Jemal A. Cancer statistics, 2024. CA A Cancer J Clinicians. 2024;74(1):12-49.
- Torti, S. V. & Torti, F. M. Iron and Cancer: 2020 Vision. Cancer Res. 80, 5435–5448 (2020).
- Basak, T. & Kanwar, R. K. Iron imbalance in cancer: Intersection of deficiency and overload. Cancer Med. 11, 3837–3853 (2022).
- Diet, nutrition, physical activity and cancer: a global perspective : a summary of the Third expert report. (World Cancer Research Fund International, 2018).
- Salnikow, K. Role of iron in cancer. Semin. Cancer Biol. 76, 189–194 (2021).
- Schwedhelm, C., Boeing, H., Hoffmann, G., Aleksandrova, K. & Schwingshackl, L. Effect of diet on mortality and cancer recurrence among cancer survivors: a systematic review and meta-analysis of cohort studies. Nutr. Rev. 74, 737–748 (2016).
- Fonseca-Nunes, A., Jakszyn, P. & Agudo, A. Iron and Cancer Risk—A Systematic Review and Meta-analysis of the Epidemiological Evidence. Cancer Epidemiol. Biomarkers Prev. 23, 12–31 (2014).
- Ramírez-Carmona, W. et al. Are Serum Ferritin Levels a Reliable Cancer Biomarker? A Systematic Review and Meta-Analysis. Nutr. Cancer 74, 1917–1926 (2022).
Does this project have an international component or travel?
No
If your project has an international component please give details (where, when, data collection involved, etc.):
N/A
Cancer biology and drug development
Faculty Information
Name:
Dr. Daiqing Liao
Email
dliao@ufl.edu
Phone
(352) 273-8188
Faculty Department/Division
UF Health Cancer Center
This project is primarily:
Basic
Research Project Description:
The research in the laboratory of Dr. Daiqing Liao focuses on oncogenic signaling, metabolism, and cancer epigenetics, including the discovery and development of small molecule inhibitors and degraders of histone deacetylases (HDACs) and acetyltransferases as cancer therapeutics.
Intracellular lipid production in cancer cells supplies lipids to synthesize cell membranes and signaling molecules during rapid cell proliferation and tumor growth. Cancer cells also utilize fatty acid oxidation (FAO) to generate ATP to meet their energy demand. Notably, different lipid metabolites can inhibit or trigger ferroptosis due to iron-dependent oxidation of polyunsaturated fatty acids (PUFAs). Therefore, identifying regulators maintaining the intricate balance of lipid biosynthesis required for cell proliferation and survival is critical in cancer biology and therapy. Lipid metabolism is regulated by two oncogenic signaling pathways: the RAS-RAF-MEK-MAPK and the mammalian target of rapamycin (mTOR) pathways. About 30% of all cancers harbor constitutively active mutations in KRAS, HRAS, or NRAS, resulting in hyperactive RAS-RAF-MEK-MAPK signaling to drive tumorigenesis, metastatic progression, immune evasion, and resistance to therapy. KRAS regulates lipid uptake, lipid synthesis, and FAO. mTOR is a serine/threonine kinase acting as a key intracellular signaling hub to regulate nutrient homeostasis, metabolism, protein synthesis, and autophagy. The mTORC1 complex promotes lipogenesis. The RAS and mTOR signaling pathways exhibit both positive and negative cross-regulation.
The coordinated activity of both pathways is critical to sustained tumor growth. Notably, mTORC1 signaling inhibition enhances RAS-RAF-MEK-MAPK signaling to promote cancer cell survival and proliferation. Furthermore, constitutive mTORC1 signaling induces cell death when the supply of unsaturated FAs is limited. However, the molecular link for coordinating the activity of the RAS and mTOR signaling pathways remains poorly defined. Our recent study suggests the RAS and mTOR signaling appear to converge to regulate the epigenetic regulator DAXX, which, in turn, governs gene expression underlying lipid metabolism, cell survival, proliferation, and tumorigenesis. We use in vitro and in vivo breast cancer models to elucidate the molecular mechanisms of this pathway and discover potential therapeutics targeting it.
Protein lysine acetyltransferases (KATs) catalyze the acetyl attachment to lysine side chains of protein substrates such as histones and many other cellular proteins. Deacetylases (HDACs) catalyze the reverse reaction to remove the attached acetyl group. Acetylation of protein substrates impacts their stability and functions in various cellular pathways, such as gene transcription, intracellular trafficking, and metabolisms. KATs and HDACs are implicated in human diseases and represent rational therapeutic targets. We have been interested in understanding the cell-biological functions of these enzymes in epigenetics and cancer biology, as well as in discovering, characterizing, and optimizing novel small-molecule inhibitors of these enzymes for cancer therapy. We have discovered novel KAT and HDAC inhibitors. In collaboration with medicinal chemists, we have developed potent degraders targeting class I HDACs, including proteolysis-targeting chimeras (PROTACs) and molecular glue degraders. We use in vitro biochemical and cell-based assays to validate the activities of our inhibitors and degraders. We use mouse tumor models to determine the in vivo anticancer efficacy of these compounds. Our ultimate goal is to translate the inhibitors and degraders to the clinic to benefit cancer patients.
Does this project have an international component or travel?
No
Molecular Mechanism of Brain Muscle Communication
Faculty Information
Name:
Prof. MEI HE
Email
mhe@cop.ufl.edu
Phone
(352) 273-9847
Faculty Department/Division
UF Health Cancer Center
This project is primarily:
Basic
Research Project Description:
Brain-muscle communication has been recognized as the most vital physiological system in humans, governing various aging-related senescence and neurodegenerative diseases. Several modes of communication between the brain and muscle have been explored in the research field, including the emerging route via circulating extracellular vesicles (EVs). Elucidating an EV-enabled communication network between the brain and skeletal muscle could reveal essential molecular targets and signaling pathways, resulting in more effective therapeutic strategies to prevent brain aging and expand health span. For muscle organoids, the expression of pluripotency markers OCT, NANOG Brachyury (mesoderm marker), TBX6, and MSGN1 (presomitic markers) will be monitored to characterize paraxial mesodermal differentiation. Myogenic progenitor markers, PAX3 and PAX7, will be monitored for the early stage of myogenesis and mature skeletal muscle tissues. The TITIN+ muscle cells and MAP2-positive neurons will be quantified. The SEM and confocal microscope will confirm the 3D organoid architectures. We expect long-term organoid culture (≥ 3 months) with stable and well-defined molecular features using 8 donor cells in our brain muscle MPS chamber arrays.
Does this project have an international component or travel?
No
If your project has an international component please give details (where, when, data collection involved, etc.):
no