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Aquaphotomics forweak signals quantification in
water
Roumiana Tsenkova
Kobe University, Japan
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http://nirslab.org/
io MeasurementTechnologyLaboratory
Kobe University
Bio measurement Technology Laboratory, Kobe University, Japan
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Understanding that the smallestamount of a substance affects the
organismA person can enter aroom two days after a cat has left itand still suffer an allergic response.
Yolene Thomas, Larbi Kahhak and Jamal Aissa (2006) The physical nature of the biological signal, a puzzlingphenomenon: the critical contribution of Jacques Benveniste, In Water and the Cell, 325-340, Ed. GeraldPolack, Springer.
Dr. Jacques Benveniste
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electromagnetic transmission of biochemical
information can be stored in the electric dipole
moments of water in close analogy to the
manner in which magnetic moments store
information on a computer disk. A. Widom, Y.N. Srivastava, V. Valenzi The Biophysical Basis of Water Memory , http://jacques-
benveniste.org/bio_conf_widom.pdf
Vibrational Spectroscopy IR, NIR
IRInfrared spectroscopy
NIRNear infrared spectroscopy (overtone IR)IR active transitionelectric dipole moment of molecule
changes
NIR overtone spectroscopycan measure water in-vivo
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NIR rangeovertone region
IR range
fundamentalfrequencies
WATER SPECTRUM
Bio measurement Technology Laboratory, Kobe University, Japan
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AQUA
PHOTOME
Spectral
Data Base
BioAqueousSystemNIR spectrum
W M CSThe LETTERSActivated Water
Absorbance Bandswater
Water Spectral Pattern
THE WORD
Perturbations
AQUAPHOTOMICS:
WATER as aMOLECULAR MIRROR
Bio measurement Technology Laboratory, Kobe University, Japan
WAMACS= Water Matrix Coordinates, i.e. water absorbance bands in VIS-NIR range
AQUAPHOTOMICS: THE CONCEPT
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Prof. Rustum Roy
Water structures should be the LETTERS
and
water functionalities will be described as WORDS
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Medical Science,
Pharmacy.
Engineering
Building
bio-systemHOLISTICMODELSthrough
analyzing
spectral
changes of
W TERMOLECUL R
SYSTEM
Spectral Data Base
Epmes
Database
AQUAPHOTOMEDatabase of water
absorbance bands and
patterns
WAPSDatabase of waterabsorbance patterns
according to change
perturbation
WAMACSActivated Water
Absorbance Bands
Biotechnology
Basic ScienceAnalyzing of aqueous system
Interaction of water with DNA
Interaction of water withorganic and non-organic
molecules
Aqueous systems in cells
Aqueous systems in tissue
Aqueous systems in organs
Aqueous systems in whole
body
GOAL
Days
Applying in various fields
UVVISIR
NIRS
WaterBio
Aqueous
System
Sun
Perturbations
Multivariate Analysis
Bio measurement Technology Laboratory, Kobe University, Japan
AQUAPHOTOMICS
Prof. Rustum Roy
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SPECTRA and AQUGRAMSof WATER AND
VAPOR
-1.5
-1
-0.5
0
0.5
1
1.5
2
2.5
3
3.5
1344nm
(V3)
1364nm
(water shell)
1372nm
(V1+V3)
1382nm
(water shell)
1398nm
(free OH)
1410nm
(S0, free water)
1438nm
(H5O2)
1444nm
(S1)
1464nm
(S2)
1474nm
(S3)
1492nm
(S4)
1518nm
(V1, V2)
moisture
water
1300 1410 1490 1580 1680
Wavelength (nm)
A
bsorbance
1362
1382
1372
1452
VAPOR
WATER
MPA
Bio measurement Technology Laboratory, Kobe University, Japan
A
A'A : Absorbance after EMSC (1300-1600 nm)
Mean of Averaged spectraSD of absorbance each wave length
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Following the idea of
QUANTUM SPECTROSCOPY
wherematter is excited and probed with a
sequence of light pulses at definedfrequencies
IN ORDER TO
control and characterize quantum
dynamics of many-body states1
APPROACHING WATER with MONITORING
1. http://en.wikipedia.org/wiki/Quantum-optical_spectroscopy
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Measurement of NIR Spectra Under
Perturbations
NIR spectra of water and protein solutions measured every minute,for the first 5 minutes and every 15 minutes, for 690 min, at 37oC
Instrument: (NIRSystem 6500, wavelength range from 400 to 2500 nm)
Cuvette cellis inserted in to the instrument holder and kept at 37oC
MODELS DEVELOPED: Y = F [ I ], Y = F [ T ]
1,2,3,4,5 20 35 690
TIME as a perturbation
ILLUMINATIONas a perturbation
[I, times]
[T, min]VISNIR Light
65 7 45
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Room temperature
25.0
25.2
25.4
25.6
25.826.0
26.2
26.4
26.6
0 5 10 15 20 25 30 35 40 45 50 55 60
time(minute)
roomtemperature()
12
3
experiment
Temperature Changes
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Humidity
0.0
10.0
20.0
30.0
40.0
50.0
0 5 10 15 20 25 30 35 40 45 50 55 60time(minute)
hu
idit
y(% 1
2
3
experiment
Humidity Changes
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10.84
10.88
10.92
10.96
11.00
11.04
11.08
1 2 3
experiment
e
ight(g
difference
after
experiment(g) 1st 2nd 3rd
before 10.9324 11.0326 10.9596after 10.9088 10.9981 10.9302difference 0.0236 0.0345 0.0294
LOSS of Water
1stexp0.22%
2ndexp0.31%
3rdexp0.27%
Weight Changes
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PCA SCORE PLOT
experiment
1st2nd3rd
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Water Matrix Coordinates: WAMACSPCA,
EZ WAMACS, LOADINGS
wavelength(nm)
Factor1Factor2
1872
1412
1364 1490
1842
14901368
1530
1474
934
1842
1482
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Wavelengths, nm
Water Spectra
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WATER DYNAMIC SPECTRA
2D and 3D Synchronous Correlation Maps
600- 2500 nm
represent positive correlation
represent negative correlation
T SO C TT S WAP
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WATER ABSORBANCE PATTERNS,WAPs(dynamic study)
Power Spectra at 1530nm
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Loading of the first PC over the 600
850nm region
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0.95
1
1.05
1.1
1.15
001
004
035
080
125
170
215
260
320
Time, min
a.u.
670nm
684nm
694nm724nm
774nm
792nm
806nm
0.95
1
1.05
1.1
1.15
1.2
001
004
035
080
125
170
215
260
320
Time, min
a.u.
626nm
644nm
654nm
722nm
772nm
810nm
Real time monitoring
of
NIR water absorbance
at
various wavelengths
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Spectral Differences in Waters
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9 nm
446nm
97 nm
3456
nm
LogT
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MagneticVivoWater miliQWater
Blue: miliQ; Green:magnetic; Red: Vivo water
MSC, Baseline correction: miliQ second measurement subtracted+ smooth 13nm
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Measurement of Very Low
Concentration of Progesterone
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Samples
PdG (ng/ml)1 100
2 50
3 25
4 12.55 6.25
6 3.13
7 1.56
8 0.781
9 0.391
10 0.195
Each of samples is measured 10 consecutive spectra.
Pregnanediol
glucuronide
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400 700 1100 1880 2500
Wavelength (nm)
Absorbance
Raw spectra
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2262 nm
100ng/ml
50ng/ml
25ng/ml
Wavelength (nm)
Absorbance
2ndderivative spectra
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R = 0.7195
0.935
0.94
0.945
0.95
0.955
0.96
0 20 40 60 80 100
Absorbancea
t2262nm
concentration of PdG (ng/ml)
Correlation absorbance at2262 nmwith concentration of PdG standard
Exclude
10 samples100 spectra
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Correlation absorbance at2262 nmwith concentration of PdG standard
8 samples80 spectra
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PLSRfor PdG (the water region 1300 - 1600 nm)
Actual concentration (PdG ng/ml)
Predicted
concentration(PdGng/m
l)
R=0.999
SEC=1.42
Preprocessing : mean-center
Transformation: smooth
10 samples100 spectra
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EMS from DNA Solutions Measurement
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Data set for analysis
15 sample data sets (EMS from DNA, Imprinted EMS, and Water)
Spectral data of each sample are divided into two groups depending on
amplitudes of electromagnetic signal (EMS).
1) Higher EShigher or normal EMS, 2) Lower ESlower EMS
Patient HIV+
HIV LTR 104bp
HIV LTR 137bp (1stDay)
HIV LTR 137bp (2ndDay)HIV LTR 194bp
HIV LTR 300bp
E. Coli (1stDay)
E. Coli (2ndDay)
Borrelia
Distilled Water (DW)
MilliQ
Kobe
HIV LTR 104bp
Borrelia
Distilled Water (DW)
DNA Water
Imprinted EMS
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35
Prediction of EMS by PLS(Higher ES Samples)
Higher ES
Lower ES
Mean-center
Smooth[25]
1st, 2nd, and 3rd
Step 3
Measured EMS (dB / Hz)
PredictedEMS(dB/Hz)
Factor: 16R: 0.90
SEV: 53 dB / Hz
Sample ES
DNA-HIV-Patient 2
DNA-HIV-104bp 2DNA-HIV-137bp (1st) 2
DNA-HIV-137bp (2nd) 2
DNA-HIV-194bp 2
DNA-HIV-300bp 1
DNA-E.Coli (1st) 2
DNA-E.Coli (2nd) 2
DNA-Borr 2
Water-DW 1
Water-MilliQ 1
Water-Kobe 1
Wave-HIV-104bp 2
Wave-Borr 1
Wave-DW 1
Cross Check 1
LB 1
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36
Prediction of EMS by PLS (Higher ES Samples)
Mean-center
Smooth[25]
1st, 2nd, and 3rd
Step 3
Regression Vector, WAMACSSample ES
DNA-HIV-Patient 2
DNA-HIV-104bp 2DNA-HIV-137bp (1st) 2
DNA-HIV-137bp (2nd) 2
DNA-HIV-194bp 2
DNA-HIV-300bp 1
DNA-E.Coli (1st) 2
DNA-E.Coli (2nd) 2
DNA-Borr 2
Water-DW 1
Water-MilliQ 1
Water-Kobe 1
Wave-HIV-104bp 2
Wave-Borr 1
Wave-DW 1
Cross Check 1
LB 1
Wavelength (nm)
Regressioncoefficient(10^5)
702
838
1248
1274
1526618
964
636
754
728
776
790
900 1030
998
1560
1114
1814
658
808 930
1392
1364
1376
1858
674
872
1056
1084
1136
11241184
1208
1296
1326
1422
1458
1486
1588
1638
1616
1760
1870
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37
Prediction of EMS by PLS (Lower ES Samples)
Higher ES
Lower ES
Mean-center
Smooth[25]
1st, 2nd, and 3rd
Step 3
Measured EMS (dB / Hz)
PredictedEMS(dB/Hz)
Factor: 9R: 0.89
SEV: 40 dB / Hz
Sample ES
DNA-HIV-Patient 2
DNA-HIV-104bp 2DNA-HIV-137bp (1st) 2
DNA-HIV-137bp (2nd) 2
DNA-HIV-194bp 2
DNA-HIV-300bp 1
DNA-E.Coli (1st) 2
DNA-E.Coli (2nd) 2
DNA-Borr 2
Water-DW 1
Water-MilliQ 1
Water-Kobe 1
Wave-HIV-104bp 2
Wave-Borr 1
Wave-DW 1
Cross Check 1
LB 1
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38
Prediction of EMS by PLS (Lower ES Samples)
Mean-center
Smooth[25]
1st, 2nd, and 3rd
Step 3
Regression VectorSample ES
DNA-HIV-Patient 2
DNA-HIV-104bp 2DNA-HIV-137bp (1st) 2
DNA-HIV-137bp (2nd) 2
DNA-HIV-194bp 2
DNA-HIV-300bp 1
DNA-E.Coli (1st) 2
DNA-E.Coli (2nd) 2
DNA-Borr 2
Water-DW 1
Water-MilliQ 1
Water-Kobe 1
Wave-HIV-104bp 2
Wave-Borr 1
Wave-DW 1
Cross Check 1
LB 1
Wavelength (nm)
Regressionc
oefficient(10^4)
746
900
1872
792
1376
814
1004
1344
1526
1566
17021744 18461148
1408
1442
1482
606
776
944928
884
844
1040
1052
1084
1646
16681788
1884
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E.Coli DNA
2012 Experiment in Kobe
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40
Water for DNA dilution
Filter 1 (450nm)
Filter 2 (100nm)
measurement
measurement
1/101/10 1/101/10 1/101/10 1/101/101/10
Water for DNA dilution
Filter 1 (450nm)
Filter 2 (100nm)
measurementmeasurement
measurementmeasurement
1/101/101/101/10 1/101/101/101/10 1/101/101/101/10 1/101/101/101/101/10
10 stage
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41
NIR Spectroscopy
Sample : E.coliDNA
Spectrometer : NIRSystems 6500
Temperature : room temperature
Consective spectra : 3 times
Date : 2011/06/23 (Exp. 1)
2011/06/25 (Exp. 2)
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42
Results
Exp. 1 Exp. 2D2NF 1042 801
D2F450NM 1042 801
D2F450+100 or 20nm 1060 832
D3 1125 855
D4 1107 829
D5 1004 798
D6 990 768
D7 760 809
D8 765 575
D9 709 635
D10 671 610
D11 1188 584
D12 1170 865D13 1596 801
D14 1589 807
D15 1480 809
Exp. 1
ES : D7D10
Exp. 2
ES : D8D11
ES : Electromagnatic signal
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43
Raw spectra
Wavelength (nm)
Absorbanc
e(-)
Exp. 1 Exp. 2
Wavelength (nm)
Absorbance(-)
EMSignal (ES)
No Signal (NS)
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Raw spectra
Absorbance(-)
Wavelength (nm) Wavelength (nm)
Absorbance(-)
Exp. 1 Exp. 2
Wavelength (nm)
Absorbance
(-)
Wavelength (nm)
Absorbance
(-)
EMSNS
Different spectra (Non Filtered sample)
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45
Different spectra (Non-Filtered sample)
770
736748
910
936
Exp. 1 Exp. 2
13621384
1416
1490
1460
Wavelength (nm)
Absorbanc
e(-)
1362
1382 1406
1410
1488
Wavelength (nm)
Absorbance(-)
778
770750832 916
934
1046
1068
Ab
sorbance(-)
EMSNS
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46
Signal calibration with PLSExp. 1 Exp. 2
Factor = 7
R2= 0.68
SEV = 175.7
Factor = 5
R2= 0.53
SEV = 66.2Shortrange
Middler
ange
Transform : Smooth (9)
averaged spectra (1st3rd)
Factor = 8
R2= 0.67
SEV = 59.4
Factor = 8
R2= 0.61
SEV = 198.2
Signal prediction with PLS: WAMACS
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47
Signal prediction with PLS: WAMACS
Model : Exp. 1
Test : Exp. 2
Factor = 5
R2= 0.69SEV = 188.4
R2= 0.61
SEP = 250.31200 1300 1400 1500 1600 1700 1800
-60000
-40000
-20000
0
20000
40000
60000
1382
1452
156016221360
1410
15521652
regr
ession
vector(-)
wavelength (nm)
1404
1436
Model : averaged spectra (1st3rd)
Test : averaged spectra (1st3rd)
Transform : Smooth (9)
E Coli All Signal DATA Assignment
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E.Coli All Signal DATA Assignment
(2012)Exp. 1 Exp. 2
D2NF 1042 801
D2F450NM 1042 801D2F450+100 or 20nm 1060 832
D3 1125 855
D4 1107 829
D5 1004 798
D6 990 768
D7 760 809
D8 765 575
D9 709 635
D10 671 610D11 1188 584
D12 1170 865
D13 1596 801
D14 1589 807
D15 1480 809
1336nm(aqueous proton [H+(H2O)6] - H2O
asymmetric stretch, 1st overt.), 1358nm (H17O8+free OH stech, 1st overt.), 1374-78nm(aqueous
proton [H+(H2O)3] - H3O+ symmetric stretch, ),
1398nm 1421-28nm, 1460nm, 1482nm, 1678nm,
1742nm(1st overtone Superoxide Tetrahydrate O2-
.(H2O)2 ), 1792nm (1st overtone Superoxide
Tetrahydrate O2-.(H2O)3)
E C li All Si l DATA A i
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E.Coli All Signal DATA Assignment
(2013)
l
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50
E.Coli EMS Aquagram Exp. 1
A=A-
A : Absorbance after MSC (1110 nm1800 nm)
: Mean of all the spectra (with NF, F1)
: SD of absorbance each wavelength
Exp. 1
D2NF 1042
D2F450 nm 1042
D2F450+100 or 20 nm 1060
D3 1125
D4 1107
D5 1004
D6 990
D7 760
D8 765
D9 709
D10 671
D11 1188
D12 1170
D13 1596
D14 1589
D15 1480
-2.5
-1.5
-0.5
0.5
1.5
2.5
1344
1364
1372
1382
1398
1410
1438
1444
1464
1474
1492
1518
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51
Lowest Signal
-2.5
-1.5
-0.5
0.5
1.5
2.5
1344
1364
1372
1382
1398
1410
1438
1444
1464
1474
1492
1518
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-2.5
-1.5
-0.5
0.5
1.5
2.5
1344
1364
1372
1382
1398
1410
1438
1444
1464
1474
1492
1518
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53
-2.5
-1.5
-0.5
0.5
1.5
2.5
1344
1364
1372
1382
1398
1410
1438
1444
1464
1474
1492
1518
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54
Highest Signal
-2.5
-1.5
-0.5
0.5
1.5
2.5
1344
1364
1372
1382
1398
1410
1438
1444
1464
1474
1492
1518
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2013 Experiment in Paris
Sample : E.coliDNA
Spectrometer : XDS Methrom
Temperature : room temperature
Consective spectra : 3 times
Date : 2013/06
E C li All Si l DATA A i t
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E.Coli All Signal DATA Assignment
(2013)
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Less hydrogen
bonded
structures
activated with
high EMS
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S l P i 2
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Sample Preparation - 2
In: A_IL_OA_IOut: A_IL_OA_O
In: A_IA_OA_IOut: A_IA_OA_O
In: A_IL_OL_IOut: A_IL_OL_O
Open-top
In: C_IL_OA_I
Out: C_IL_OA_O
In: C_IA_OA_I
Out: C_IA_OA_O
In: C_IL_OL_I
Out: C_IL_OL_O
Closed
LB
LB+A
Control
Cont_LBACont_LB
SampleName
Sample
Name
M f N i f d
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Measurement of Near-infrared spectrum
Near-infrared spectrum of each sample was measured using
NIRSystems 6500Spectroscopy: NIRSystems 6500 (FOSS NIRSystems)
Wavelength: 400-2500 nm
Methods: Transmittance
Path length: 1 mm
Temperature: Room temperature
Consecutive measurement times: 3 times per a sample
NIRSystems 6500
1) Moving a sample into a cuvette cell 2) Measuring a spectrum
Green: with lid
Red: no lid
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LB
LB + A
LB + A and LB in LB+A
Red: no lid
LB: inside
and
outside
LB: insideLBA: outside
LB: measured
LB: inside LBA:
outsideLB: measured
LB: inside
and
outside
LB: inside
LBA: outsideLBA: measured
LBA influence is stronger
Diff i WAMACS
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Difference in WAMACSLoadings of PC Factors 1-red,2-green,3-blue
Close Top C WAMACS:
Open Top A WAMACS:
1362, 1398, 1410, 1420, 1462, 1490,
1538nm
1410nm, So
1412nm, So
1362nm
solvation
shell
1398nm
solvation
shell 1420nm
hydration
1462nm, S2
1366nm
solvation
shell1368,
1386nm
1428nm
hydration
1486nm
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Investigation of water structural
changes
induced by cellular phone irradiation
63
S l i
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Sample preparation
10 mL at each sample
Distilled water
Milli-Q waterCallReceive
Duration of call0 minute5 minutes10 minutes15 minutes20 minutes
Location of samples
2
12/16/2013 Biomeasurement technology laboratory 64
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Spectral measurement
Spectrometer: NIRSystems6500(Foss NIRSystems)
Mode: Transmittance
Path length: 1mm
Temperature: Room temperature
Consecutive times: 3 times
Materials
Cellular phone (PT002, KDDI, 800MHz)Milli-Q water
Distilled water
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PCA score plot
Wavelength range : 680-1090 nm + 1110-1800 nm
Transform : SNV
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SIMCA
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Interclass distance
CS1@8 CS2@6
CS1 0.000000 6.163845
CS2 6.163845 0.000000
Middle NIR a elength range
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Middle NIR wavelength range1110-1800nm
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1452nm1.2
0
Discrimination of irradiated water
and non irradiated with PCA
Score plots: discrimination
Loading spectra: investigation ofwavelengths which contribute the
discrimination
Absorba
nce(-)
Wavelength (nm)
1110nm 1800nm
PCAScore Plots
Optimal factors: 10
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Optimal factors: 10
Preprocessing: mean center
Transforms: smooth(17)
Validation: cross(1)
: 0 minute: 5 minutes: 10 minutes: 15 minutes: 20 minutes
Factor2(-)
[33.00%]
Factor1(-) [66.60%]
Factor3
(-)[0.37%]
Factor3
(-)[0.37%]
Factor1(-) [66.60%] Factor2(-) [33.00%]
Factor 2 showed the
duration of call.
0 minute
5 minutes
10 minutes
15 minutes
20 minutes
Loading spectra: WAMACS l f
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Loading spectra: WAMACS Optimal factors: 10Preprocessing: mean center
Transforms: smooth(17)
Validation: cross(1)
Loadings(-)
Wavelength (nm)
: Factor1
: Factor2
: Factor3
: Factor4
0.1
0
-0.1
1110nm 1800nm
Number Wavelength
1364nm
1386nm
1412nm
1414nm
1426nm
1430nm
1490nm
1492nm
1508nm
Classification Model: SIMCAPreprocessing: mean center
Transforms: smooth(17)
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Classification Model: SIMCA
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Transforms: smooth(17)
Class Variable: duration
Optimal factors (duration):
5 (0 minute)
4 (5 minutes)5 (10 minutes)
5 (15 minutes)
4 (20 minutes)
Model Pred. 1 Pred. 2 Pred. 3 Pred.4 Pred.5 No match
Actual 1 16 0 0 0 0 0
Actual 2 1 15 0 0 0 0
Actual 3 0 0 16 0 0 0
Actual 4 0 0 0 16 0 0
Actual 5 0 0 0 0 16 0
Test Pred. 1 Pred. 2 Pred. 3 Pred.4 Pred.5 No match
Actual 1 8 0 0 0 0 0
Actual 2 1 7 0 0 0 0
Actual 3 0 0 8 0 0 0
Actual 4 0 0 0 8 0 0
Actual 5 0 0 0 0 8 0
Misclassifications
97.0%
97.5%
98.0%
98.5%
99.0%
Accuracy
Model
Test
98.75%
97.50%
SIMCA
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Preprocessing: mean center
Transforms: smooth(17)
Class Variable: duration
Optimal factors (duration):
5 (0 minute)
4 (5 minutes)
5 (10 minutes)
5 (15 minutes)
4 (20 minutes)
0 minute 5 minutes 10 minutes 15 minutes 20 minutes
0 minute 1.39 4.10 7.52 9.79
5 minutes 2.50 12.06 10.94
10 minutes 7.55 7.24
15 minutes 2.61
20 minutes
SIMCA
Interclass distance
: Over 3.00
SIMCADi i i i WAMACS
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Discriminating power: WAMACS
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Number Wavelength
1136nm
1174nm
1190nm
1200nm
D
iscriminatingpower(-)
Wavelength (nm)
1228nm
1270nm
1366nm
1424nm
1468nm
1482nm
1544nm
1556, 1562, 1568nm
1598nm
1622nm
1642nm
1674nm
1704nm
1732nm
1756nm
1796nm
1110nm 1800nm
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Investigate whether duration of
irradiation or measurement orderinfluenced spectra.
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Sample preparation
2
Two locations, 1 & 2.
call receive
Cellular phonePT002, KDDI, 800MHz
(another one is the same one)
A cell phone called the opposite one near some kinds of waters in test tubes.
5 kinds water (Milli-Q water,distilled water, gold water,
silver water, and bronze
water)
4 kinds of duration of call
(5,10,15,20min)
2(Irradiated or no)
2 locations
=80 samples
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Spectra measurement
Spectrometer : MPA
Mode : Taransmittance
Consecutive times : 3 times
Path length : 1mm
Temperature : room temperatrure
Wavelength range : 800-2500nm
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Raw spectra
Wavelength (nm)
Absorban
ce(-)
800 1100 1800 2500
PCA Score plots (irradiation)
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PCA Score plots (irradiation)
factor2
factor3
factor4
factor5
factor1 factor2 factor3 factor4
Consecutive No 1
Consecutive No 2
Consecutive No 3
Factor2 loadings
1412
1489
factor2 shows temperature influenced by consecutive measurement
CA S l
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PCA Score plots: waters
factor
2
factor3
factor4
factor5
factor1 factor2 factor3 factor4
bronze
Milli-Q
distilled
gold
silver
ll d l
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PLS: Milli-Q water Model accuracy
Measured order (-)
Predictedorde
r(-)
SEC=0.00080
R=1.00
Measurement order Duration of irradiation
Measured duration (-)
Predictedduratio
n(-)
SEC=0.013
R=1.00
Preprocessing : Mean-center
Smooth(21)
PLS: Milli-Q water Accuracy of
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PLS: Milli Q water Accuracy of
prediction
Predictedorde
r(-)
Measured order (-)
Measurement order
SEP=0.26
R=0.97
Duration of irradiation
Predictedorder
(-)
Measured order (-)
SEP=5.00
R=0.79
PLS Di ill d M d l
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PLS: Distilled water Model accuracy
Measured order (-)
Predictedorde
r(-)
SEC=0.0010
R=1.00
Measurement order Duration of irradiation
Measured duration (-)
Predictedduratio
n(-)
SEC=0.020
R=1.00
Preprocessing : Mean-center
Smooth(21)
PLS: Distilled water Accuracy of
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PLS: Distilled water Accuracy of
prediction
Predictedorde
r(-)
Measured order (-)
Measurement order
SEP=0.34
R=0.96
Duration of irradiation
Predictedorder
(-)
Measured order (-)
SEP=5.67
R=0.69
PLS b M d l
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PLS: bronze water Model accuracy
Measured order (-)
Predictedorde
r(-)
SEC=0.0013
R=1.00
Measurement order Duration of irradiation
Measured duration (-)
Predictedduratio
n(-)
SEC=0.013
R=1.00
Preprocessing : Mean-center
Smooth(21)
PLS: Bronze water Accuracy of
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P S: ron e water Accuracy of
prediction
Predictedorde
r(-)
Measured order (-)
Measurement order
SEP=0.42
R=0.93
Duration of irradiation
Predictedorder
(-)
Measured order (-)
SEP=7.69
R=0.42
PLS Sil t M d l
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PLS: Silver water Model accuracy
Measured order (-)
Predictedorde
r(-)
SEC=0.0007
R=1.00
Measurement order Duration of irradiation
Measured duration (-)
Predictedduratio
n(-)
SEC=0.10
R=1.00
Preprocessing : Mean-center
Smooth(21)
PLS: Silver water Accuracy of
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y
prediction
Predictedorde
r(-)
Measured order (-)
Measurement order
SEP=0.25
R=0.98
Duration of irradiation
Predictedorder
(-)
Measured order (-)
SEP=6.10
R=0.67
PLS G ld t M d l
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PLS: Gold water Model accuracy
Measured order (-)
Predictedorde
r(-)
SEC=0.0010
R=1.00
Measurement order Duration of irradiation
Measured duration (-)
Predictedduration(-)
SEC=0.015
R=1.00
Preprocessing : Mean-center
Smooth(21)
PLS G ld t A f di ti
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PLS: Gold water Accuracy of prediction
Predictedorde
r(-)
Measured order (-)
Measurement order
SEP=0.40
R=0.95
Duration of irradiation
Predictedorder
(-)
Measured order (-)
SEP=7.56
R=0.61
PLS R i R lt
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PLS Regression Results
All models showed high accuracy
Measurement order tests showed high accuracy, but duration ofirradiation time tests showed very low accuracy.
SEC R SEP R SEC R SEP R
Milli-Q 0.00080 1.00 0.26 0.97 0.013 1.00 5 0.79
distilled 0.0010 1.00 0.34 0.96 0.02 1.00 5.67 0.69
bronze 0.0013 1.00 0.42 0.93 0.013 1.00 7.69 0.42silver 0.00070 1.00 0.25 0.98 0.1 1.00 6.1 0.67
gold 0.001 1.00 0.4 0.95 0.015 1.00 7.56 0.61
model test
measurement order duration of irrudiation
model test
SIMCA M d l i l ifi ti
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SIMCA : Model misclassification
predicted 5min predicted 10min predicted 15min predicted 20min predicted 0min No match
actual 5min 20 0 0 0 0 0
actual 10min 0 20 0 0 0 0
actual 15min 0 0 20 0 0 0
actual 20min 0 0 0 20 0 0
actual 0min 0 1 3 0 76 0
Duration of irradiation
Measurement order
predicted 1(5mi predicted 2(15mi predicted 3(10minpredicted 4(20mi No match
actual 1(5min) 40 0 0 0 0
actual 2(15min) 0 40 0 0 0actual 3(10min) 0 0 40 0 0
actual 4(20min) 0 0 0 40 0
Preprocessing : Mean-center
SIMCA Test misclassification
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SIMCA : Test misclassification
Duration of irradiation
Measurement order
predicted 5min predicted 10min predicted 15min predicted 20min predicted 0min No match
actual 5min 3 0 0 0 7 0
actual 10min 0 6 0 0 4 0
actual 15min 0 0 4 0 6 0
actual 20min 0 0 0 3 7 0
actual 0min 1 2 0 1 36 0
Unmodeled 0 0 0 0 0 0
PredCS1@5 PredCS2@5 PredCS3@5 PredCS4@6 No match
1(5min) 20 0 0 0 0
2(15min) 0 20 0 0 0
3(10min) 0 0 20 0 0
4(20min) 0 0 0 20 0
Unmodeled 0 0 0 0 0
Classification SIMCA
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Both of two patterns of model sets showedhigh accuracy.
Interclass distance of duration of irradiation
model set showed high values, but theyshowed very low accuracy in prediction.
Measurement order prediction showed 100%accuracy.
The effect of cell phone could be controlled bythe water
Classification: SIMCA
NAFION AND EZ
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NAFION AND EZ
WAMACS:
1378nm, 1388, 1394,
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14041414nm(-),
1438-1440nm(+), 1454nm(+), 1464nm(+),
1480nm(+), 1496nm last sharp max
Blue: Water : consecutive spectra (firstsubtracted)
WAMACS:
1386nm (+) first max
1414nm (-)
1446 -1448nm second max
1464min14741480nm max
Naphion
Water
ONLY Naphion: 3 consecutive measurements,
1st one subtracted
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1stone subtracted
WAMACS:
1324nm (-), 1340nm (+), 1420nm (+),
1444nm (+)?, 1458nm(+), 1498nm (-),
1520nm, 1526nm (+), 15381558nm (+)
These are water molecules in the air
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Effect of magnetic force on
the electrical conductivityand spectra of milliQ water
Materials and methods
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Materials and methods
mQ water used
Electrical conductivity was
measured in a 20 mm cuvette(by a portable conductometer)
Magnets attached at the two
sides of the cuvette during theexperiment
N S N S
Place of
the
magnets
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RESULTS
N NS S
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Red line are 9 consecutive spectra of mQ water
(second consecutive subtracted).S-N blue, N-S dark green, S-S brown, NN light
green1432nm OHR,, ncII) and DDA OH-(H2O)4,
14481458nm, O-HCl, deionized water, 1stover tone of O-H
stretch, DDA symmetric stretch of OH-(H2O)4,5,
1492nm,second overtone of bending and symmetric str vibr., S4.
Very small increase in 1464nm, S2, working horses and1518nm.; 1667nm1682nm O-HR, H13O6+ H-bonded OH
strech, 1st overt.
Decrease in S1, 1441nm!!!Dicrease in H-bonded OH
stretch1477nm; 1479.3nm,
1482nm, IHB/HOH bend (OH-H2O) and H5O2 (terminal water)
at. Decrease of aqueous protons.
Isosbestic point moves from 1438nm to 1420nm.
N - N1st experiment (in every 40s)
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No magnet S - N N - S
S - S
2nd experiment 1st part
(continuous)
conductivity,S/cm(1stmeasurement)
conductivity,S/cm(2ndmeasurement)
number of data
1.
1.
2.
2.
3.
3.
4.
4.
5.
5.
Measurement
order
Legend
S-S pink
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N-N blue
S-N red
N-S green
mQbrown
AQUAPHOTOME DATA BASE
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Systems PerturbationsWavelengths, LETTERS
Spectral Patterns, WORDSFunctiona
lities
Waters: Temperature first overtone stress tolerancemQ, distilled, deionised, mineral, treated etc.
Pressure second overtone disease
Water solutions:
DNA Illumination third overtone probiotics
biomolecules: proteins, sugars, lipids, alcohols etc.
minerals, salts, metals etc. Concentration combination bands dehydration
Bio fluidsMagnetic field solvation shells hydration
blood, urine, serum, rumen juice etc.
Cells Dillution oxidationCHO, bacteria
Tissue: (in vitro and in vivo)
organs: liver, kidney, stomack etc.
mammary gland, mussels, plants tissue, etc.
Water Bands (WAMACS)
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1368.7 1st overtone OH-str (OH-H2O) Science28
1368.7 H15O7+, 1st overt. Wei and Salahub 1997: The Journal of Chemical Physics, 106: 6086.
1369.5 H17O8+, 1st overt. Wei and Salahub 1997: The Journal of Chemical Physics, 106: 6086.
1369.5 H15O7+ free OH stech, 1st overt. Mizuse and Fijii 2012: The Journal of Physical Chemistry, 116: 4868.
1369.5 H17O8+ free OH stech, 1st overt. Mizuse and Fijii 2012: The Journal of Physical Chemistry, 116: 4868.
1369.9 aqueous proton [H+(H2O)6] - H2O symmetric stretch, 1st overt. Headrick et al. (Mark Johnson) 2005: Science, 308: 1765.
1370.5 1st overtone (OH-(H2O)5) Science28
1370.6 H13O6+ free OH stech, 1st overt. Mizuse and Fijii 2012: The Journal of Physical Chemistry, 116: 4868.
1371.0 aqueous proton [H+(H2O)5] - H2O symmetric stretch, 1st overt. Headrick et al. (Mark Johnson) 2005: Science, 308: 1765.
1371 1st overtone Superoxide Tetrahydrate O2-.(H2O)4 Weber, Science 2000
1371.4 H11O5+ free OH stech, 1st overt. Mizuse and Fijii 2012: The Journal of Physical Chemistry, 116: 4868.
1372.1 aqueous proton [H+(H2O)4] - H2O symmetric stretch, 1st overt. Headrick et al. (Mark Johnson) 2005: Science, 308: 1765. 1374.0 aqueous proton [H+(H2O)3] - H2O symmetric stretch, 1st overt. Headrick et al. (Mark Johnson) 2005: Science, 308: 1765.
1375.9 H9O4+ free OH stech, 1st overt. Mizuse and Fijii 2012: The Journal of Physical Chemistry, 116: 4868.
1377.4 aqueous proton [H+(H2O)3] - H3O+ symmetric stretch, 2nd overt. Headrick et al. (Mark Johnson) 2005: Science, 308: 1765.
1379 n1+n3 Tsenkova1379.3 H2O - n1+n3 Ozaki 1982
1380 1st overtone OH-str (OH-H2O) Xantheas, 1995
1380.85 1st overtone (OH-(H2O)5) Science28
1383 1st overtone Superoxide Tetrahydrate O2-.(H2O)4 Weber, Science 2000
1383.15 1st overtone interwater / DD stretch (OH-(H2O)4) Science28
1388.7 H2O - 2*n1 Ozaki 1982
1388.9 H+(H2O)10, 1st overt. Headrick et al. (Mark Johnson) 2005: Science, 308: 1765.
1388.9 H bond 18=
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Water Matrix Coordinates are the Letters or
the Characters related to water structures
Water Spectral Patterns are the words that
speak about functionalities
Huge data base, i.e. Aquaphotome
has to be organized in order to
learn the language of water and
to measure and understand weak signals
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