Air Force 711 Human Performance Wing –Application of NAMs · 2018-02-08 · Cleared, 88PA, Case # 2018-0587, 8 Feb 2018 1 Air Force 711th Human Performance Wing –Application

Cleared, 88PA, Case # 2018-0587, 8 Feb 20181

Air Force 711th Human Performance Wing – Application

of NAMsP r e p a r e d b y L a u r a S t o l l e , P h D , L e a d R e s e a r c h To x i c o l o g i s t

P r e s e n t e d b y L i s a S w e e n e y, P h . D . , R i s k A s s e s s m e n t To x i c o l o g i s t a t U E S , I n c .

M a y 2 3 , 2 0 1 9


Total Exposure Health – Big Picture

AFMS CONOPS to enable capture of workplace,

environmental, and lifestyle exposures experienced by an individual to prevent disease

• Emphasis is to leverage and advance:• Exposure Science• Sensor & data technologies• Health informatics• Clinical support systems

• Goals are to:• Obtain holistic health status• ID root causes of disease/injury• Provide innovative, accessible

methods for primary prevention


Systems Biology for Performance VisionElucidate warfighter biologic state and the underlying mechanism of responses such that we can build a computational model/"virtual warfighter" that recapitulates warfighter physiology in diverse operational environments

Enabling individual variable responses to any operational stressor/perturbation (hypoxia, hyperoxia, stress, fatigue, flight line operations, thermal stress, directed energy) to be predicted

From Institute for Systems Biology


In Vitro to In Vivo Extrapolation

Cleared, 88PA, Case # 201x-xxxx, xx Mon 201x.5

In Vitro Data Production


In Vitro – human stem cells

Marchetto and Gage 2010

MAP2 (neuron); GFAP (astrocyte); DAPI (nuclei)

In collaboration with Anne Bang at Sanford Burnham Prebys


Airman-on-a-Chip: Gut-Microbiome-Brain Axis Work-Flow

Operational Stressors

Fatigue Sleep deprivation Oxygen content

Environmental Stressors

Extreme temperatures High elevation Bacteria / viruses

Gut – Microbiome – Brain Axis Organ Systems: Homeostasis, Dysbiosis, Countermeasure Development

3D Extracellular Matrix

Cells: Gut/Endo./iPSC

GUT

Endothelium

GUT Tissue

Jenkins et al. Nutrients 2016, 8(1), 56; https://doi.org/10.3390/nu8010056

Microfluidic Device

Shear Stress + Mechanical Forces

CognitionAwareness

PerformanceMetabolism

Homeostasis

Barrier Integrity

Tyler Nelson

Gut-Organ Axis Discovery/Evaluation


Syn-Bio Chassis and/or Gut Microbiota

Target Cells

Gut Epithelial CellsDirect

Perfusion and

Transport

Secreted Microbiota Signal Molecules

Microbiota & Host Signal Molecules

Bacteria – Host Cell Contact for Signal Transfer

Scan of Bacterial-Host-Target Using Monoculture and Complex Bacterial

Population

Permeable Membrane

Microbiome Surface & Excreted Signal Analyses

Platform Use: SynBio Engineered Chassis Single Bacterial Component (Monoculture) Single Bacterial Component + Mock Community Cecum/Fecal Full Microbiome

Microbiome (MB): Culture & Biofilm (= MAM)16S rRNA Sequencing – Population DynamicsqPCR quantitation of specific speciesMeta transcriptomicsMeta proteomics

MB Output Molecules: Metabolomics – bacterial excreted metabolitesLipidomics – SCFA fatty acid chains

Gut Epithelial (GE) Response: TranscriptomicsTargeted qRT-PCRCytokinesMALDI Imaging for global Omic AnalysisMAFFs

MB/GE Output Molecules: MetabolomicsLipidomicsProteomics - neuropeptides

Target Cell (TC): TranscriptomicsqRT-PCR Key Pathway Genes

TC (Neuronal): Metabolomics, Lipidomics, Proteomics

TC (Skeletal Muscle): Metabolomics, Lipidomics, ProteomicsMarkers of Damage, Energy MetabolismContractionCamilla Mauzy

8


Modeling Performance Enhancement/Protection-tDCS Using Human Mini Brains

Q: What molecular changes are initiated by direct current stimulation?

(4 different neuronal classes + oligodendrocytes + astrocytes)

Pathways of Interest: Angiogenesis, Neurogenesis, Synaptic PlasticityLaura Stolle

In Vitro – Personalized Risk

Cleared, 88PA, Case # 2018-0

Patrick McLendon

Chemical exposure

Nuclear Envelope Determination

Cytoplasmic Volume

Nuclear Area / Cell Area

Phenotypic IDPhenotypic features that characterize response of cells to chemicals

ID correlation between genetic makeup and differential phenotypic responses

•Toxin sensitivity•Disease susceptibility•Therapeutic response•Therapeutic optimization

predict

correlate

sensitive

resistant

HCA features

Chemical “X”concentration

Commercially availablegenetically defined cells

A B C

ABC

A B C

587, 8 Feb 201810


Assessment of Neuro-Vascular Responses to HyperoxicOscillations in Airman: A Systems Biology Approach

Tyler Nelson


Biological Systems Modeling


Development of a Generalized Inhalation Model for Use with the High-Throughput Toxicokinetics (httk) Package in R

Dr. Matt Linakis- Recent collaborative workwith the USEPA

• 42 chemicals for model building/training

• Input: • Gas inhalation

• Output: • Blood and other tissue

concentrations• Exhaled breath

concentrations

• Under Development:• Aerosol inhalation

Lung TissueLung Blood

Alveolar Space

Gut TissueGut Blood

Gut Lumen

Liver TissueLiver Blood

Body TissueBody Blood

Kidney TissueKidney Blood

Qcardiac

Arterial Blood

Qkidney

Qrest

Qliver

Qgut

Veno

us B

lood

Qalv Qalv

Inhaled Air

kgutabs

Clmetabolism

Qgfr

Exhaled Breath

(MM Elim)

Mucous


The Potential for Genetic Variation to Impact Risk Estimates from Chemical Exposures in a United States Air Force Population

Brain

Alveolar

Fat

Rapid

Slow

urine

Liver

Art

eria

l Blo

od

Veno

us B

lood

inhaleddose

URT Mucus

metabolism

Jeffery Gearhart and Joseph Jarvis


Development of Exposure Limits for Chemicals Encountered During Aircraft Operation

Drs. Lisa Sweeney, Matt Linakis

Aircrew Problem Formulation—In-flight airborne chemicalcontaminants

Population: healthy adults Exposure

• Assume 2 flights (1 h/flight) per day with 2 hseparation on three consecutive days

• Several stressors possible (heat, exertion, altitude,+Gz forces, vibration)

Comparator• Same exposure concentration and schedule, lack

of stressors (modified value) Outcome

• Critical effect(s) for toxicity reference valuederivation

Exposure: 25 ppm 1,2,4-Trimethylbenzene (TMB)

Predicted peak bloodconcentrations of 1,2,4-TMB are ~5-fold higherunder physiologicalstress (heart rate = 120bpm) vs. baseline.

Impact of the flight-related stressors +Gz forces and altitude/barometric pressure on physiologically-based pharmacokinetic model parameters used for risk assessment

• ~170 articles reviewed, data extracted from ~70.

• >20 data synthesis figures have been prepared (see example below)

Fractional change in cerebral blood flow velocity due to increases in +Gz (baseline of +1 Gz). ○: Kawai et al. 1997; ×: Ossard et al. 1994, 1996; �: other sources (Iwasaki et al. 2012, Ogawa et al. 2016, Stevenson and Scott 2014). Trendline: y = 0.0083 x2 –0.1505 x; r2 = 0.805

Current efforts:

Incorporate stressor-related impacts into physiologically based pharmacokinetic models

Literature review/data extraction for vibration


In Vivo Validation


In Vivo Validation

+ =

Low level exposure operational features of flight• G-forces• Oxygenation• Argon (and other air components)• Hypobaric pressure• Isometric workload• Work of breathing

?


Acknowledgements• Dr. Heather Pangburn, RHB, Systems Biology for Performance Core Research Area Lead

• Dr. Darrin Ott – RHM, Aerospace Operational Medicine Core Technical Competency Lead

• Dr. (Mark) Tyler Nelson – RHB, Organ on a Chip Team Lead

• Dr. Jeffery Gearhart – RHM, Biological Modeling Team Lead

• Dr. Patrick McLendon – RHM, In Vitro Modeling Team Lead

• Dr. Anne Bang – Sanford Burnham Prebys

• Dr. Joseph Jarvis – RHB, Bioinformatics Team Lead


Questions?

Air Force 711th Human Performance Wing – Application of NAMsTotal Exposure Health – Big PictureSystems Biology for Performance VisionIn Vitro to In Vivo ExtrapolationIn Vitro Data ProductionIn Vitro – human stem cellsAirman-on-a-Chip: Gut-Microbiome-Brain Axis Work-Flow Gut-Organ Axis Discovery/Evaluation�Modeling Performance Enhancement/Protection-tDCS Using Human Mini BrainsIn Vitro – Personalized RiskAssessment of Neuro-Vascular Responses to Hyperoxic Oscillations in Airman: A Systems Biology ApproachBiological Systems ModelingDevelopment of a Generalized Inhalation Model for Use with the High-Throughput Toxicokinetics (httk) Package in RThe Potential for Genetic Variation to Impact Risk Estimates from Chemical Exposures in a United States Air Force PopulationDevelopment of Exposure Limits for Chemicals �Encountered During Aircraft OperationIn Vivo ValidationIn Vivo ValidationSummaryAcknowledgementsQuestions?

Documents

Air Force 711 Human Performance Wing –Application of NAMs · 2018-02-08 · Cleared, 88PA, Case # 2018-0587, 8 Feb 2018 1 Air Force 711th Human Performance Wing –Application