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1 Risk e Learning Metals – Bioavailability April 9, 2003 2:00 – 4:00 pm EDT

Risk e Learning Metals – Bioavailability April 9, 2003 2:00 – 4:00 pm EDT

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Risk e Learning Metals – Bioavailability April 9, 2003 2:00 – 4:00 pm EDT. Assessing the Oral Bioavailability of Lead in Soil in Humans. J.H. Graziano 1 , N.J. LoIacono 1 , M. Maddaloni 2 , S. Chillrud 3 , C.B. Blum 4 - PowerPoint PPT Presentation

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Page 1: Risk e Learning Metals – Bioavailability April 9, 2003 2:00 – 4:00 pm EDT

1

Risk e Learning

Metals – BioavailabilityApril 9, 2003

2:00 – 4:00 pm EDT

Page 2: Risk e Learning Metals – Bioavailability April 9, 2003 2:00 – 4:00 pm EDT

2

Assessing the Oral Bioavailability of Lead in Soil in Humans

J.H. Graziano1, N.J. LoIacono1,

M. Maddaloni2, S. Chillrud3, C.B. Blum4

1Environmental Health Sciences, Mailman School of Public Health, Columbia University; 2US Environmental Protection Agency, Region 2;

3Lamont-Doherty Earth Observatory, Columbia University, 4College of Physicians & Surgeons, Columbia University

Page 3: Risk e Learning Metals – Bioavailability April 9, 2003 2:00 – 4:00 pm EDT

3

Assessing the Oral Bioavailability of Lead in Soil in Humans

• Stable isotope dilution

• Previous work on Bunker Hill, ID, soil

• Results from ongoing studies of amended soils (Joplin, MO)

Page 4: Risk e Learning Metals – Bioavailability April 9, 2003 2:00 – 4:00 pm EDT

4

Page 5: Risk e Learning Metals – Bioavailability April 9, 2003 2:00 – 4:00 pm EDT

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Lead Isotope Ratio Midpoint

Lead Isotope Ratio Midpoint

- Australian subjectsN

umbe

r of

Sub

ject

sN

umbe

r of

Sub

ject

s

- US subjects

1.095 1.105 1.115 1.125 1.135 1.145 1.155 1.165 1.175 1.185 1.195 1.205 1.2150

2

4

6

8

10

12

14

16

18

20

A

Lead Isotope Ratio Midpoint

Num

ber of

Sub

ject

s

1.095 1.105 1.115 1.125 1.135 1.145 1.155 1.165 1.175 1.185 1.195 1.205 1.2150

1

2

3

4

5

6

7

8

9

10

B

1.095 1.105 1.115 1.125 1.135 1.145 1.155 1.165 1.175 1.185 1.195 1.205 1.2150

1

2

3

4

5

6

7

8

9

10

C

- Scottish subjects

Page 6: Risk e Learning Metals – Bioavailability April 9, 2003 2:00 – 4:00 pm EDT

6

Lead Isotope Ratios of Select Sites

Location Superfund Site 206Pb/207Pb

Kellogg, ID Bunker Hill 1.057

Butte, MT Silver Bow Creek 1.148

Leadville, CO California Gulch 1.170

Buffalo, NY Bern Metal 1.205

Triumph, ID Triumph Mine 1.253

Tar Creek, OK Tar Creek 1.350

Joplin, MO Oronogo-DuenwegMining Belt

1.378

Page 7: Risk e Learning Metals – Bioavailability April 9, 2003 2:00 – 4:00 pm EDT

7

Clinical Protocol

• Screening and physical exam

• Obtain informed consent

• Three day admission

• Subject dosed at 250 µg Pb/70 kg body wt

• Collect blood and urine samples

• Standardized meals

Page 8: Risk e Learning Metals – Bioavailability April 9, 2003 2:00 – 4:00 pm EDT

88

Page 9: Risk e Learning Metals – Bioavailability April 9, 2003 2:00 – 4:00 pm EDT

9

Time (hrs)

Subject # 5

0 5 10 15 20 25 30 35

Lea

d 2

06

/20

7

1.190

1.191

1.192

1.193

1.194

1.195

1.196

Page 10: Risk e Learning Metals – Bioavailability April 9, 2003 2:00 – 4:00 pm EDT

10

Results of Previous Studies from Bunker Hill Soil

Group(n=6)

Age(yrs)

Weight(kg)

Pb Dose(ug)

Soil Dose(mg)

Bioavailability(%)

Fasted 28 59.7 213 72.9 26.2(18.0-35.6)

Fed 28 67.9 242 82.9 2.52(0.2-5.2)

Page 11: Risk e Learning Metals – Bioavailability April 9, 2003 2:00 – 4:00 pm EDT

11

Lead Isotope Ratio Distributions

0123456789

101112

Nu

mb

er

of

Su

bje

cts

1.15

1.18

1.21

1.24

1.27 1.3

1.33

1.36 1.4

Lead Isotope Ratio

Joplin SoilSample

Subjects

Page 12: Risk e Learning Metals – Bioavailability April 9, 2003 2:00 – 4:00 pm EDT

12

Soil Homogeneity

SampleLead(ppm)

Weight(mg) 206Pb/207Pb

Untreated 5,200 75.5 1.3816

“ 69.3 1.3826

“ 62.2 1.3817

Phosphate-Amended*

4,240 66.8 1.3790

“ 65.9 1.3784

“ 66.2 1.3796

* 1% Phosphate, field–treated aged 18 months

Page 13: Risk e Learning Metals – Bioavailability April 9, 2003 2:00 – 4:00 pm EDT

13

Subject Demographics

Subject Soil Type Age Race/Ethnicity Gender Weight Pb Dose Soil Dose(kg) (ug) (mg)

1 Non-amend 30 African Amer F 60 239.2 462 Amended 37 Caucasian F 53.6 195.5 46.13 Non-amend 23 Caucasian M 66 257.4 49.54 Amended 25 Caucasian M 89.5 324.4 76.55 Amended 40 African Amer M 73.5 262.5 61.96 Non-amend 35 Asian F 60.5 215.8 41.57 Amended 41 African Amer F 81 296.4 69.98 Non-amend 34 Middle Eastern M 79 282.4 54.39 Amended 20 Caucasian M 62.7 224.7 5310 Non-amend 23 Caucasian F 59 210.6 40.5

Page 14: Risk e Learning Metals – Bioavailability April 9, 2003 2:00 – 4:00 pm EDT

14

Examples of Pb isotope data : for 2 different soil types .

1.180

1.190

1.200

1.210

1.220

1.230

1.240

1.250

1.260

1.270

0 5 10 15 20 25 30 35

Time from ingestion (hr)

Pb

20

6/P

b2

07

Subj 103 :Untreated Soil

Subj 105 :Treated Soil

Lea

d

206

/207

Page 15: Risk e Learning Metals – Bioavailability April 9, 2003 2:00 – 4:00 pm EDT

15

Subject Change in Blood Lead Subject # Soil Type BPb Start BPb End Change Mean

101 Non-Amended

4.19 5.91 1.72

103 “ 1.30 2.22 0.92

106 “ 1.49 3.32 1.83

108 “ 2.06 2.50 0.44

110 “ 1.11 2.20 1.09 1.20

102 Amended 1.84 2.32 0.48

104 “ 3.62 4.05 0.43

105 “ 4.88 5.78 0.90

107 “ 2.95 3.82 0.87

109 “ 2.27 2.60 0.33 0.60

Page 16: Risk e Learning Metals – Bioavailability April 9, 2003 2:00 – 4:00 pm EDT

16

Preliminary Results

GroupAge(yrs)

Weight(kg)

PbDose(ug)

SoilDose(mg)

Bioavailability(%, Absolute)

Untreated 29.0 64.9 241.1 46.4 35.8(14.6-54.2)

Amended 32.6 72.1 260.7 61.5 15.3(8.0-26.2)

Page 17: Risk e Learning Metals – Bioavailability April 9, 2003 2:00 – 4:00 pm EDT

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Comparative Results: Animal, In vitro & Human

Animal*In vitro**(pH 2.3) Human

% Reduction inBioavailability

38 38 57

* Casteel et. al., ** Ruby et. al.

Page 18: Risk e Learning Metals – Bioavailability April 9, 2003 2:00 – 4:00 pm EDT

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Relative Costs:Remedies for Metal-Contaminated Soils

0 0.5 1 1.5 2

$ (Millions)

Phosphate Inactivation

Soil Cap

Asphalt Cap

Phytoextraction

Soil Wash

Excavate & Landfill

* Source: EPA Technical Innovation Office

Net Present Cost for 1 Hectare Site

1.62

0.79

0.25

0.16

0.14

0.06

Page 19: Risk e Learning Metals – Bioavailability April 9, 2003 2:00 – 4:00 pm EDT

19

Manuscripts in Progress

• Graziano, JH, LoIacono, NJ, Chillrud, SN, Ross, J, Blum, C. Oral bioavailability of lead in phosphate-amended and non-amended soils from a Missouri smelter site.

• Chillrud, SN, Hemming, G, Wallace, S and Ross, J. Determination of lead isotopes in blood with separation by iron hydroxide co-precipitation and analysis by multi-collector ICP-MS, In preparation for Journal of Analytical Atomic Spectroscopy

Page 20: Risk e Learning Metals – Bioavailability April 9, 2003 2:00 – 4:00 pm EDT

20

Risk e Learning

Metals – BioavailabilityApril 9, 2003

2:00 – 4:00 pm EDT

Page 21: Risk e Learning Metals – Bioavailability April 9, 2003 2:00 – 4:00 pm EDT

21

Determination of Metal Speciation in Aquatic Ecosystems Using Equilibrium Gel Samplers

Martha Chang Jen Galvin

Sarah Griscom Chris Lewis

Dave Senn Jim Shine

Crista Trapp

Harvard School of Public Health - Dept. Environmental Health

NIEHS Superfund Basic Research Program

Page 22: Risk e Learning Metals – Bioavailability April 9, 2003 2:00 – 4:00 pm EDT

22

Outline:

1. Importance of Metal Speciation

2. Gel Flux Samplers

3. ‘Gellyfish’ Equilibrium Gel Sampler

- As a metal speciation tool

- As a bio-mimic

4. Conclusions

Page 23: Risk e Learning Metals – Bioavailability April 9, 2003 2:00 – 4:00 pm EDT

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Knowledge of the Free Metal Ion Concentration is Important:

- Key determinant describing partitioning amongst different phases:

- DOC bound

- POC bound (settling particles)

- Biological Uptake

-Thus a determinant describing:

- Transport

- Fate

- Effects

Page 24: Risk e Learning Metals – Bioavailability April 9, 2003 2:00 – 4:00 pm EDT

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Cd2+

Cd

Transmembrane Protein

Dissolved

Humic Acid

Complex

Water

Cell

Cd

Biotic Ligand Model:

Page 25: Risk e Learning Metals – Bioavailability April 9, 2003 2:00 – 4:00 pm EDT

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Zn2+

Zn

Cd2+

Cd

Transmembrane Protein

Dissolved

Humic Acid

Complex

Water

Cell

Need to Understand Competitive Interactions:

-Interactions can be antagonistic, protective, or neutral

-Need simultaneous data for multiple metals

Page 26: Risk e Learning Metals – Bioavailability April 9, 2003 2:00 – 4:00 pm EDT

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Current Metal Speciation Techniques:

- Indirect

- titrations to characterize ligands

- labor Intensive

- Methodological Uncertainties

-titration window

- L1 & L2 ligands ??

- One metal per titration

Page 27: Risk e Learning Metals – Bioavailability April 9, 2003 2:00 – 4:00 pm EDT

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Acrylic Plate

Gel + Chelex 100

Gel only

(Diffusive Gel Layer)

[dz

Diffusion Gradient (dC)

Gel Flux Samplers: - Diffusion Gradient Thin-film (DGT) Samplers

- Zhang & Davison. 1995. Anal. Chem. 67:3391-3400

Assuming C=0 at Chelex/Gel interface:

a) Determine a flux rate of metals to the Chelex 100

b) F = -D dC/dz solved for C, the external concentration

Page 28: Risk e Learning Metals – Bioavailability April 9, 2003 2:00 – 4:00 pm EDT

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Strengths and Weaknesses of Flux Samplers:

(-) Measures a flux, not a concentration

(-) Unclear what metal species is measured

(+) Flux of individual metals independent of the underlying complex mixture

(-) Flux of individual metals independent of the underlying complex mixture

- less suitable as a biotic ligand analog?

Page 29: Risk e Learning Metals – Bioavailability April 9, 2003 2:00 – 4:00 pm EDT

29

9101112

Actual Free Cu2+ (CLE-ACSV, pCu)

7

8

9

10

11

DG

T 'L

ab

ile' C

u (

pC

u)

Twiss and Moffett (2002)

- “Impacted Sites”

Page 30: Risk e Learning Metals – Bioavailability April 9, 2003 2:00 – 4:00 pm EDT

30

Equilibrium Sampler (Gellyfish) : Design Criteria

Polyacrylamide gelToyopearl AF Chelate-650M resin

21 mm

3 mm

Toyopearl Resin (Tosohaas, Inc.):

- Mean bead size: 65 µm

- exchange capacity: 35 µeq/ml

Gel Crosslinker: DGT Crosslinker (DGT Research, Ltd.)

Final Resin Concentration Inside Gel:

- 3 x 10-4 eq/L- Designed for less than 5% depletion of metal from surrounding 2 L solution

Page 31: Risk e Learning Metals – Bioavailability April 9, 2003 2:00 – 4:00 pm EDT

31

Strengths and Weaknesses of Gellyfish Sampler:

(+) Is in equilibrium with a concentration, not a flux

(+) Clearer what metal species is measured (free metal ion)

(-) Accumulation of individual metals related to the underlying complex mixture

- possible correction procedures?

(+) Accumulation of individual metals related to the underlying complex mixture

- more suitable as a biotic ligand analog?

Page 32: Risk e Learning Metals – Bioavailability April 9, 2003 2:00 – 4:00 pm EDT

32

General Differences

Flux Sampler = Empirical

- What you see is what you get

- Is what you get what you want to see?

Gellyfish = Mechanistic

- What you see is the free metal ion concentration

- BUT… you must be able to account for all possible

confounding factors

Page 33: Risk e Learning Metals – Bioavailability April 9, 2003 2:00 – 4:00 pm EDT

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The ‘Gellyfish’:

Page 34: Risk e Learning Metals – Bioavailability April 9, 2003 2:00 – 4:00 pm EDT

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Equilibration, Back Extraction, and Analysis:-Experiments conducted with artificial seawater

- AQUIL salts recipe (no nutrients)

- Metal speciation controlled with EDTA

- Equilibration

- Gellyfish suspended in 2L sample with teflon

string for appropriate equilibration period

- After Equilibration:

- Gellyfish removed from test solution,

rinsed in DI water

- Gellyfish placed in 10 ml 10% HNO3

- After 24 - 48 hrs, back extract analyzed for Cu

- ICP-MS (Perkin Elmer ELAN 6100 DRC)

Page 35: Risk e Learning Metals – Bioavailability April 9, 2003 2:00 – 4:00 pm EDT

35

Equilibration Times:

Range of t90 equilibration times: 15 - 30 hours

Coefficient of Variation for Repeated Measures: ~ 5%

0 10 20 30 40 50 60 70 80

Equilibration Time (hours)

0

1

2

3

Ma

ss

Cu

Co

llec

ted

g)

Page 36: Risk e Learning Metals – Bioavailability April 9, 2003 2:00 – 4:00 pm EDT

36

Calibration with Free Metal Ions:

Salinity = 20 ppt (pH = 7.9 - 8.1)

Total Copper:

1.5 x 10-6 M (nominal pCu = 7, 8, 9, 10)

1.5 x 10-7 M (nominal pCu = 11, 12)

r2 = 0.97

7891011

Sample Free Zn 2+ (pZn2+)

1e-10

1e-09

1e-08

5e-08

Gellyfi

sh

Zn

mass c

ollecte

d (

mo

l)

6789101112

Sample Free Cu2+ Concentration (pCu)

1e-12

1e-11

1e-10

1e-09

1e-08

1e-07

Ge

llyfi

sh

Cu

Ma

ss

Co

llec

ted

(m

ol) Cu:

Salinity = 20 ppt (pH = 7.8 - 8.0)

Total Zinc:

5 x 10-7 M (nominal pCu = 7, 8, 9)

5 x 10-8 M (nominal pCu = 10, 11)

Zn:

r2 = 0.94

Page 37: Risk e Learning Metals – Bioavailability April 9, 2003 2:00 – 4:00 pm EDT

37

Correction Procedure for Complex Mixtures:

-K’Cu-Toso = [CuToso]/[Cu2+]*[Tosofree] independent of other

solution components

-Requirement: Semi-conservative solution component

- Conservative behavior in water (Xtotal = Xfree)

- Reacts with Tosohaas resin

- Candidate: Sr

- Assumption: Srtotal = free Sr2+

- therefore: K’Sr-Toso = [SrToso]/[Srtotal]*[Tosofree]

- solve above equation for [Tosofree]

- substitute into original equation

- Result: Cu2+ = K* * [Cugel] *{[Srtotal]/[Srgel]}

where K* = K’Cu/K’Sr

Page 38: Risk e Learning Metals – Bioavailability April 9, 2003 2:00 – 4:00 pm EDT

38

Model Test of Sr Correction Procedure:

- 5 free Cu ion levels: pCu range: 10 - 12

- 4 salinity levels : 10, 15, 20, 25 o/oo (= 20 total treatments)

- No Correction: Cugel at fixed pCu varies w/ salinity

- Correction Applied: Data collapse to a single line

1e-13 1e-12 1e-11 1e-10 1e-090.0000

0.0001

0.0002

0.0003

0.0004

0.0005

Gel

lyfi

sh C

u (

mo

l/L)

Before Sr Correction

Free Cu2+ (mol/L)

1e-13 1e-12 1e-11 1e-10 1e-090.0000

0.0001

0.0010

0.0100

[Cu

gel]

*{[S

r tota

l]/[S

r gel]}

After Sr Correction

Free Cu2+ (mol/L)

Page 39: Risk e Learning Metals – Bioavailability April 9, 2003 2:00 – 4:00 pm EDT

39

Me2+

Alternate Use: Bio-mimic:

Phytoplankton

Zooplankton Planktivorous Fish

Piscivorous Fish

Gellyfish

Concordance?

Direct Uptake

Trophic Transfer

Trophic Transfer Trophic

Transfer

Page 40: Risk e Learning Metals – Bioavailability April 9, 2003 2:00 – 4:00 pm EDT

40

The ‘Gellyfish’: Field Deployment Apparatus

Gellyfish placed in a piece of LDPE sheet with a hole punched through it, sandwiched by polycarbonate filters, and held togehter with snap-together slide holders.

Slides mounted in a plastic basket for field deployment

Page 41: Risk e Learning Metals – Bioavailability April 9, 2003 2:00 – 4:00 pm EDT

41

Initial Experiments: Calibrate with Biomonitoring Organisms

A) Water:

B) Sediment:

Gellyfish

Gellyfish

Mytilus edulis

Neries Virens

Field Study

Lab Study

Megel

(mol)

Me

org

an

ism

(m

ol/g

)

m = ??

Page 42: Risk e Learning Metals – Bioavailability April 9, 2003 2:00 – 4:00 pm EDT

42

Theoretical Basis:

- Competetive Metal Interactions governing metal uptake by Gellyfish = interactions governing uptake by biological organisms

PbCd

CuMn

Page 43: Risk e Learning Metals – Bioavailability April 9, 2003 2:00 – 4:00 pm EDT

43

Potential Advantages as Monitoring Tool:

1) Gellyfish Don’t Die (can they be eaten?)

2) Gellyfish don’t undergo gametogenesis

3) Gellyfish are all the same (good or bad?)

4) Equilibration time can be controlled

- Surface area/volume ratio

- Can select a desired integration period

Page 44: Risk e Learning Metals – Bioavailability April 9, 2003 2:00 – 4:00 pm EDT

44

Current/ Near Future Experiments:

- Effect of complex mixtures on Metal uptake

-Proof of Sr correction concept

- Use with other metals (Pb, Cd)

- similar analytical windows for different metals?

-Calibrate with uptake into aquatic organisms

- select desired equilibration time?

Page 45: Risk e Learning Metals – Bioavailability April 9, 2003 2:00 – 4:00 pm EDT

45

Conclusions:

- Gel Flux (DGT) Samplers

- are the strengths weaknesses?

- ‘Gellyfish’ Sampler

- Equilibrium based

- Are the ‘weaknesses’ strengths?

- Proof of concept for Cu, Zn promising

- Potential Biotic Ligand Analog?

- Supporting tool for speciation-based WQ approaches?

- Allow new types of experiments in Metal Speciation Research?

- ligand specificity studies

Page 46: Risk e Learning Metals – Bioavailability April 9, 2003 2:00 – 4:00 pm EDT

46

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