Mina J. Bissell Ph.D. & Vectorspace AI Advance New Space Biosciences Division

As the new space race heats up, more humans will be traveling into space than ever before. Spaceflight causes many changes in human health. Humans cannot be sent into space without understanding how to protect and repair human DNA along with tissue regeneration while in space.

To understand stressors and develop countermeasures that can be used to protect and repair human DNA while in space, Vectorspace AI welcomes Mina J. Bissell, Ph.D., distinguished senior scientist (the highest rank bestowed at Lawrence Berkeley National Laboratory (LBNL)/DOE) in the Biological Systems and Engineering Division, to its Scientific Advisory Board (SAB). Dr. Bissell was previously head of the Biosciences division of LNBL for 14 years along with being the chair of the 200+ page report for the NASA Space Radiation Health Program study related to a mission to Mars.

Dr. Bissell is one of five recipients of the 2020 Canada Gairdner International Award, an annual honor given to scientists who have contributed to transformative human health research. She is Faculty of four Graduate Groups in UC Berkeley: Comparative Biochemistry, Endocrinology, Molecular Toxicology, and Bioengineering (UCSF/UCB joint program). She has challenged several established paradigms, and pioneered the field of tumor microenvironment. Using mammary gland and breast cancer her body of work has provided the foundation for the current recognition of the pivotal role that extracellular matrix (ECM) signaling plays in regulation of gene expression in both normal and malignant cells. Her laboratory pioneered the use of 3D organoids and techniques that allowed her to prove her signature phrase that after conception, "phenotype is dominant over genotype."

Vectorspace AI specializes in detecting hidden relationships in data via advanced networks of data engineering pipelines designed to generate datasets and visualizations applied to space biosciences and is a long time collaborator with the Bissell Lab at LBNL under U.S. government contract No. DE-AC02-05CH11231 along with the U.S. Navy's Space and Naval Warfare (SPAWAR) division.

Specifically, Vectorspace AI applies 'tip of the spear' unsupervised learning methods in AI/ML connected to NLP/NLU (Natural Language Processing/Understanding) biological language modeling to generate datasets used to create relationship networks between genes, proteins, diseases, micronutrients and drug compounds. Data engineering pipelines are one of the most important pillars underpinning accelerated scientific discovery.

Dr. Bissell will be advising on partnerships in space biosciences with companies and space agencies such as Virgin Galactic, SpaceX, Blue Origin, NASA Space Biosciences, ESA, JAXA and others with a focus on research related to 'dynamic reciprocity', the ECM (Extra cellularmatrix), TME (Tumor Microenvironment), exosomes, simulated microgravity, biomarkers, ocular, brain ECM, nutrigenomics, GCR (Galactic Cosmic Rays), HZE (High-energy and high-charge ions), Bragg peak and 'track' correlation analysis related to DNA repair pathways along with high/low LET (Linear Energy Transfer) radiation, telomere elongation/shortening, chromosomal translocations and dysregulated gene expression and additional multiomics research in connection to space biosciences.

Additional research includes analysis of key targets and key effects of particle damage correlated to type of particle and track including:

Targets:

• DNA bases/genes

• Carbohydrates

• Proteins

• Lipids

• Mitochondria

• Blood cells

• Membrane receptors

• Cell adhesion molecules

• ECM

• Immune cells

• Stem cells

• Endothelium

• Exosomes

Effects:

• Clustered DNA damage

• Persistent mutations and chomosome aberrations

• Reduced DNA and cellular repair

• Drastic G M block and altered cell cycle kinetics

• Enhanced cytokine activation

• Tumorigenesis at high dose, high-LET or HZE

• Apoptosis, autophagy, senescence, mitotic catastrophe, necrosis

• Altered gene expression and differentiation

• Changes in cell-cell comms and non-targeted effects

• Changes in cell adhesion and motility

• Changes in angiogensis

Specific applications in space biosciences will benefit all humankind indefinitely while also leading to new discoveries and applications in precision and personalized medicine which can be applied today along with drug repurposing, repositioning, and discovery connected to healthspan and revenue.

Working with groups such as NASA's Human Research Roadmap (HRP), NASA GeneLab and Biospecimen Sharing Program (BSP), Vectorspace AI will apply advanced techniques in bioinformatics, AR/XR (Augmented/Extended Reality) and visualization to enable the generation and acceleration of new hypotheses and discoveries in space biosciences. Resulting practical applications in space biosciences can immediately translate into on-ground solutions in all of Life Sciences including licensing and royalty opportunities in the pharmaceutical industry. Future roadmaps include applications in nanomedicine and advanced materials connected to spaceflight.

Vectorspace AI continues to maintain applications in the financial and cryptocurrency markets that provide hedge funds, asset management companies, and other institutions with datasets that generate alpha through its utility token, VXV. The token provides data lineage, provenance, governance and security for its datasets, which are mission critical for any data engineering operation today. Datasets are accessed through the VXV wallet-enabled API.

About Vectorspace

Vectorspace AI  provides high value correlation matrix datasets to enable researchers with the ability to accelerate their data-driven innovation and discoveries using patent protected NLP/NLU. Clients save time in the research loop by quickly testing hypotheses and running experiments with higher throughput. Vectorspace AI originated in the Life Sciences dept. of Lawrence Berkeley National Laboratory (LBNL) where the founders developed the patents that drive the company's innovation for a variety of academic institutions including CERN.