Mathematical relationships between spinal motoneuron properties

  1. Arnault H Caillet
  2. Andrew TM Phillips
  3. Dario Farina
  4. Luca Modenese  Is a corresponding author
  1. Department of Civil and Environmental Engineering, Imperial College London, United Kingdom
  2. Department of Bioengineering, Imperial College London, United Kingdom
  3. Graduate School of Biomedical Engineering, University of New South Wales, Australia
11 figures, 12 tables and 1 additional file

Figures

Detailed example for the process adopted to successively create the two final {R;SMN} and {Ith;SMN} datasets (right-side thick-solid contour rectangular boxes).

These final datasets were obtained from respectively three and three normalized global datasets of experimental data obtained from the literature (dashed-contour grey-filled boxes) {{R;ACV}, {R;AHP}, {R;SMN}} and {{Ith;R}, {Ith;AHP}, {Ith;ACV}}. The {R;ACV}

Experimental (A) and unknown (B) relations between motoneuron (MN) and muscle unit (mU) properties.

(A) Bubble diagram representing the pairs of MN and/or mU properties that could be investigated in this study from the results provided by the 40 studies identified in our web search. MN and mU …

Normalized global datasets.

These were obtained from the 19 studies reporting cat data that measured and investigated the 17 pairs of motoneuron (MN) properties reported in Figure 2A. For each {A;B} pair, the property A is read …

Normalized motoneuron (MN) size-related final datasets.

These were obtained from the 19 studies reporting cat data that concurrently measured at least two of the morphometric and electrophysiological properties listed in Table 1. For each {A;SMN} pair, the …

Normalized size-dependent behaviour of the motoneuron (MN) properties ACV, AHP, R, Ith,C, and τ.

For displaying purposes, the MN properties are plotted in arbitrary units as power functions (intercept k=1) of SMN : A=SMNc according to Table 3. The larger the MN size, the larger ACV, C, and Ith in the …

Fivefold cross-validation of the normalized mathematical relationships.

Here are reported for each dataset the average values across the five permutations of (A) the normalized maximum error (nME), (B) the normalized root mean square error (nRMSE), and (C) coefficient of …

Global datasets for rat and mouse species and predictions of the motoneuron (MN) properties with the cat mathematical relationships (Table 4).

They were obtained from the five studies reporting data on rats and the four studies presenting data on mice reported in Appendix 1—table 5 that measured the {Ith;R}, {τ;R}, and {C;R} pairs of MN …

Appendix 1—figure 1
Density histograms of the data distributions reported in the experimental studies included in the global datasets.

Depending on the typical range over which each property spans, the distributions are divided in steps of 10 or 20%. The frequency distribution is provided in percentage of the total number of …

Appendix 1—figure 2
Assessment of data variability between the experimental studies that constitute the eight global datasets that include at least two experimental studies.

For each experimental study included in the global dataset {A;B}, the range, mean, coefficient of variation (CoV=standard deviationMean), and the ratio MeMd=MeanMedian of the experimental A values measured in this study were computed. …

Appendix 1—figure 3
Distribution of the size of the experimental datasets constituting the global datasets for assessment of the variability in the input data.

The histogram is divided between global datasets (half vertical lines), grouped as final size-dependent datasets (full vertical lines). For each global dataset, the total number of data points is …

Appendix 1—figure 4
Assessment of data variability between the global datasets.

This figure compares the distributions of the SMN, ACV, AHP, R, Ith, and τ properties between the normalized global datasets built in this study. For each property, the range, mean, coefficient of variation (oV=standard deviationMean), and …

Tables

Table 1
The motoneuron (MN) and muscle unit (mU) properties investigated in this study with their notations and SI base units.

SMN is the size of the MN. As reproduced in Table 2, the MN size SMN is adequately described by measures of the MN surface area Sneuron and the soma diameter Dsoma. R and Rm define the MN-specific electrical …

PropertiesNotationUnit
MN propertiesSize:
Neuron surface area
Soma diameter
SMN
Sneuron
Dsoma
[m2]
[m]
ResistanceRΩ
Specific resistance per unit areaRm[Ωm2]
CapacitanceC[F]
Specific capacitance per unit areaCm[Fm2]
Time constantτ[s]
Rheobase (current recruitment threshold)Ith[A]
Voltage thresholdVth[V]
Afterhyperpolarization durationAHP[s]
Axonal conduction velocityACV[ms1]
mU propertiesSize:SmU
Total fibre cross-sectional areaCSAtot[m2]
Mean fibre cross-sectional areaCSAmean[m2]
Innervation ratioIR[]
Tetanic forceFtet[N]
Twitch forceFtw[N]
Table 2
Measurable indices of motoneuron (MN) and muscle unit (mU) sizes in mammals.

SMN and SmU are conceptual parameters which are adequately described by the measurable and linearly inter-related quantities reported in this table.

MN size (SMN)mU size (SmU)
SneuronFtet
DsomaIR
CSAmean
CSAtot
Table 3
Fitted experimental data of pairs of motoneuron (MN) properties and subsequent normalized final size-related relationships.

For information, the r2, p-value, and the equation A=kaBa are reported for each fitted global dataset. The normalized MN-size dependent relationships A=kcSMNc are mathematically derived from the …

MN propertyA=kaBa(normalized global datasets)A=kcSMNc(final MN-size dependent datasets)
ARelationshipkaar2p-valueReference studieskccr2p-valueN points
ACVACV=kaSMNa4.0
(2.5; 6.4)
0.7
(0.6; 0.8)
0.58< 10-5Cullheim, 1978; Kernell and Zwaagstra, 1981; Burke et al., 19824.0
(2.5; 6.4)
0.7
(0.6; 0.8)
0.58< 10-5109
AHPAHP=kaSMNa6.1 · 103
(1.2 · 103; 3.2 · 104)
−1.2
(−1.6; −0.8)
0.34< 10-5Zwaagstra and Kernell, 19802.5 · 104
(1.2 · 104; 5.0 · 104)
−1.5
(−1.7; −1.3)
0.41< 10-5492
AHP=kaACVa1.5 · 104
(7.4 · 103; 2.9 · 104)
−1.4
(−1.5; −1.2)
0.41< 10-5Eccles et al., 1958a; Zwaagstra and Kernell, 1980; Gustafsson and Pinter, 1984b; Foehring et al., 1987
RR=kaSMNa1.5 · 105
(2.7 · 104; 7.9 · 105)
−2.1
(−2.5; −1.7)
0.61< 10-5Kernell and Zwaagstra, 1981; Burke et al., 19829.6 · 105
(4.1 · 105; 2.3 · 106)
−2.4
(−2.6; −2.2)
0.37< 10-5745
R=kaACVa6.3 · 105
(1.9 · 105; 2.1 · 106)
−2.3
(−2.6; −2.0)
0.38< 10-5Kernell, 1966; Burke, 1968; Barrett and Crill, 1974; Kernell and Zwaagstra, 1981; Fleshman et al., 1981; Gustafsson and Pinter, 1984b; Sasaki, 1991
R=kaAHPa6.2 · 10−1
(4.1 · 10−1; 9.2 · 10−1)
1.1
(0.9; 1.2)
0.65< 10-5Gustafsson, 1979; Gustafsson and Pinter, 1984b; Foehring et al., 1987; Pinter and Vanden Noven, 1989; Sasaki, 1991
IthIth=kaRa1.1 · 103
(0.8 · 103; 1.3 · 103)
−1.0
(−1.1; −0.9)
0.37< 10-5Kernell, 1966; Fleshman et al., 1981; Gustafsson and Pinter, 1984a; Zengel et al., 1985; Munson et al., 1986; Foehring et al., 1987; Krawitz et al., 20019.0 · 10−4
(4.7 · 10−4; 1.7 · 10−3)
2.5
(2.4; 2.7)
0.37< 10-5722
Ith=kaACVa3.2 · 10−6
(1.3 · 10−7; 8.2 · 10−5)
3.7
(3.0; 4.4)
0.37< 10-5Kernell and Monster, 1981; Gustafsson and Pinter, 1984a
Ith=kaAHPa2.5 · 104
(1.3 · 104; 4.8· 104)
−1.7
(−1.9; −1.6)
0.60< 10-5Gustafsson and Pinter, 1984a
CC=kaRa2.4 · 102
(2.0 · 102; 3.9 · 102)
−0.4
(−0.4; −0.3)
0.57< 10-5Gustafsson and Pinter, 1984b1.2
(0.7; 2.0)
1.0
(0.9; 1.2)
0.28< 10-5444
C=kaItha2.9 · 101
(2.4 · 101; 3.5 · 101)
0.3
(0.2; 0.3)
0.51< 10-5Gustafsson and Pinter, 1984a
C=kaAHPa2.8 · 102
(1.8 · 102; 4.4 · 102)
−0.4
(−0.5; −0.3)
0.24< 10-5Gustafsson and Pinter, 1984b
C=kaACVa2.5
(0.7; 8.4)
0.8
(0.5; 1.0)
0.17< 10-5Gustafsson and Pinter, 1984b
ττ=kaRa8.7
(7.2; 10.6)
0.5
(0.4; 0.6)
0.52< 10-5Burke and ten Bruggencate, 1971; Barrett and Crill, 1974; Gustafsson, 1979; Gustafsson and Pinter, 1984b; Zengel et al., 1985; Pinter and Vanden Noven, 1989; Sasaki, 19912.6 · 104
(1.5 · 104; 4.5 · 104)
−1.5
(−1.6; −1.4)
0.46< 10-5649
τ=kaAHPa2.2
(1.3; 3.5)
0.8
(0.7; 1.0)
0.63< 10-5Gustafsson and Pinter, 1984b
τ=kaItha2.3 · 102
(1.9 · 102; 2.7 · 102)
−0.4
(−0.5; −0.3)
0.72< 10-5Gustafsson and Pinter, 1984a
τ=kaACVa1.2 · 104
(2.2 · 103; 6.6 · 104)
−1.3
(−1.7; −0.9)
0.30< 10-5Gustafsson and Pinter, 1984b
Table 4
Mathematical empirical cat relationships between the motoneuron (MN) properties Sneuron, Dsoma, R, Rm, C, τ, Ith,AHP, and ACV.

Each column provides the relationships between one and the eight other MN properties. If one property is known, the complete MN profile can be reconstructed by using the pertinent line in this …

Sneuron[m2]Dsoma[m]R[Ω]Rm[Ωm2]C[F]τ[s]Ith[A]AHP[s]ACV[ms1]
Sneuron[m2]Dsoma=1.8102SneuronR=1.71010Sneuron2.43Rm=1.01010Sneuron1.43C=1.3102Sneuronτ=1.01012Sneuron1.48Ith=3.8108Sneuron2.52AHP=1.01011Sneuron1.51ACV=3.0106Sneuron0.69
Dsoma[m]Sneuron=5.5103DsomaR=5.1105Dsoma2.43Rm=1.7107Dsoma1.43C=7.9105Dsomaτ=2.3109Dsoma1.48Ith=7.8102Dsoma2.52AHP=2.7108Dsoma1.51ACV=8.1104Dsoma0.69
R[Ω]Sneuron=9.5105R0.41Dsoma=1.7102R0.41Rm=5.7105R0.59C=1.5106R0.40τ=9.6107R0.61Ith=2.7102R1.04AHP=1.3105R0.62ACV=4.9103R0.29
Rm[Ωm2]Sneuron=1.5107Rm0.70Dsoma=2.6105Rm0.70R=6.8106Rm1.70C=1.8109Rm0.69τ=1.4102Rm1.04Ith=2.2109Rm1.76AHP=2.2101Rm1.06ACV=5.4101Rm0.48
C[F]Sneuron=1.2102CDsoma=2.1104CR=1.51015C2.48Rm=1.71013C1.46τ=8.61016C1.51Ith=6.51013C2.57AHP=7.71015C1.54ACV=8.2107C0.71
τ[s]Sneuron=8.4109τ0.67Dsoma=1.5106τ0.67R=7.1109τ1.64Rm=3.6101τ0.96C=1.61010τ0.66Ith=1.61012τ1.70AHP=1.7101τ1.02ACV=7.5τ0.47
Ith[A]Sneuron=4.0104Ith0.40Dsoma=7.1102Ith0.40R=3.1102Ith0.96Rm=7.4106Ith0.57C=5.9106Ith0.39τ=1.2107Ith0.59AHP=1.5106Ith0.60ACV=1.3104Ith0.27
AHP[s]Sneuron=5.5108AHP0.66Dsoma=9.8106AHP0.66R=7.5107AHP1.61Rm=2.5AHP0.95C=9.71010AHP0.65τ=6.2102AHP0.98Ith=1.81010AHP1.67ACV=2.7101AHP0.46
ACV[ms1]Sneuron=4.61010ACV1.44Dsoma=8.3108ACV1.44R=8.31012ACV3.50Rm=2.3103ACV2.06C=9.01012ACV1.41τ=7.4101ACV2.14Ith=1.11015ACV3.64AHP=1.4103ACV2.18
Table 5
Fitted experimental data of pairs of one muscle unit (mU) and one motoneuron (MN) property and subsequent SmUSMNc relationships.
SpeciesA=kBc(fitted relationships)(final relationships)
Relationshipcr2p-valueReference studiesc
RatIR=kACVc3.40.456.10-3Kanda and Hashizume, 19922.4
CatFtw=kACVc9.40.43<10-5Knott et al., 19716.6
Ftet=kACVc7.20.37<10-5Mcphedran et al., 1965; Wuerker et al., 1965; Appelberg and Emonet-Dénand, 1967; Proske and Waite, 1974; Bagust, 1974; Jami and Petit, 1975; Stephens and Stuart, 1975; Burke et al., 1982; Emonet-Dénand et al., 19885.0
Ftet=kRc-1.30.276.10-5Dum and Kennedy, 19803.2
Ftet=kSMNc2.00.212.10-2Burke et al., 19822.0
MouseFtw=kRc-2.10.42<10-5Manuel and Heckman, 2011; Martínez-Silva et al., 20185.1
Ftw=kIthc1.30.642.10-4Manuel and Heckman, 20113.3
Ftet=kIthc1.00.806.10-2Manuel and Heckman, 20112.5
Mean ± sd3.8 ± 1.5
Table 5—source data 1

Numerical data used to derive the relationships presented in Table 5.

https://cdn.elifesciences.org/articles/76489/elife-76489-table5-data1-v2.xlsx
Appendix 1—table 1
r2 values obtained for each experimental dataset {A;B} when performing a linear regression analysis on {A;B} directly (‘Linear’) and on the ln(A)ln(B) (‘Power’) and ln(A)B (‘Exponential’) transformations of {A;B}.

The r2 values returned by the three types of regression cannot be directly compared to estimate the best model. However, the power fit returned r2>0.5 for relatively more experimental datasets than the …

StudiesLinearPowerExponential
{ACV;SMN}Cullheim, 19780.420.450.43
Kernell and Zwaagstra, 19810.620.630.6
Burke et al., 19820.230.260.24
{AHP;SMN}Zwaagstra and Kernell, 19800.330.370.35
{AHP;ACV}Eccles et al., 1958b0.530.540.54
Zwaagstra and Kernell, 19800.420.440.42
Gustafsson and Pinter, 1984a0.710.680.7
Foehring et al., 19870.150.140.14
{R;SMN}Kernell and Zwaagstra, 19810.680.710.7
Burke et al., 19820.410.50.46
{R;ACV}Kernell, 19660.700.650.64
Burke, 19680.280.310.31
Kernell and Zwaagstra, 19810.680.710.71
Fleshman et al., 19810.30.210.2
Gustafsson and Pinter, 1984a0.450.440.42
Sasaki, 19910.680.680.66
{R;AHP}Gustafsson, 19790.430.410.42
Gustafsson and Pinter, 1984a0.710.680.67
Foehring et al., 19870.330.320.33
Pinter and Vanden Noven, 19890.660.530.59
Sasaki, 19910.570.490.52
{Ith;R}Kernell, 19660.520.520.68
Fleshman et al., 19810.280.340.38
Gustafsson and Pinter, 1984b0.630.830.83
Zengel et al., 19850.490.60.62
Munson et al., 19860.340.420.47
Foehring et al., 19870.340.470.47
Krawitz et al., 20010.320.490.44
{Ith;ACV}Kernell and Zwaagstra, 19810.230.240.24
Gustafsson and Pinter, 1984b0.40.520.5
{Ith;AHP}Gustafsson and Pinter, 1984b0.550.720.69
{C;R}Gustafsson and Pinter, 1984a0.550.570.57
{C;Ith}Gustafsson and Pinter, 1984a0.230.340.24
{C;AHP}Gustafsson and Pinter, 1984a0.250.260.26
{C;ACV}Gustafsson and Pinter, 1984a0.170.220.19
{τ;R}Burke and ten Bruggencate, 19710.040.070.03
Gustafsson, 19790.60.630.61
Gustafsson and Pinter, 1984a0.630.690.59
Zengel et al., 19850.390.330.36
Pinter and Vanden Noven, 19890.650.690.62
Sasaki, 19910.680.720.64
{τ;Ith}Gustafsson and Pinter, 1984b0.630.590.57
{τ;ACV}Gustafsson and Pinter, 1984a0.690.760.76
{τ;AHP}Gustafsson and Pinter, 1984a0.340.320.31
Appendix 1—table 2
Mathematical empirical normalized relationships between the motoneuron (MN) properties Dsoma, R, C, τ,Ith,AHP, and ACV.

Each column provides the relationships between one and the six other MN properties. All constants and properties are normalized up to a theoretical 100% maximum value. To scale the normalized …

DsomaRCτIthAHPACV
DsomaR=9.6105Dsoma2.4C=1.2Dsomaτ=2.6104Dsoma1.5Ith=9.0104Dsoma2.5AHP=2.5104Dsoma1.5ACV=4.0Dsoma0.7
RDsoma=2.9102R0.4C=2.7102R0.4τ=5.8R0.6Ith=1.5103RAHP=4.7R0.6ACV=2.0102R0.3
CDsoma=8.6101CR=1.4106C2.5τ=3.3104C1.5Ith=6.2104C2.6AHP=3.1104C1.6ACV=3.6C0.7
τDsoma=9.5102τ0.7R=5.6102τ1.6C=8.5102τ0.7Ith=2.9104τ1.7AHP=7.8101τACV=4.6102τ0.5
IthDsoma=1.6101Ith0.4R=1.1103IthC=1.7101Ith0.4τ=4.2102Ith0.6AHP=3.7102Ith0.6ACV=2.7101Ith0.3
AHPDsoma=8.1102AHP0.7R=8.4102AHP1.6C=7.3102AHP0.6τ=1.3AHPIth=1.9104AHP1.7ACV=4.1102AHP0.5
ACVDsoma=1.4101ACV1.4R=1.2108ACV3.5C=1.7101ACV1.4τ=5.0105ACV2.1Ith=5.9106ACV3.6AHP=5.0105ACV2.2
Appendix 1—table 3
Typical ranges of physiological values for Dsoma and Sneuron in cat rat and mouse species.

SMN is found to vary over an average qSE=2.4-fold range, which sets the amplitude of the theoretical ranges. Absolute {min; max} reports the minimum and maximum values retrieved in the reference studies …

PropertyUnitAbsolute{min;max}Average{min; max}qSEReference studiesTheoretical range
CatDsoma[µm]{25.0;90.0}{36.7;75.5}2.2Kernell, 1966; Cullheim, 1978; Zwaagstra and Kernell, 1980; Kernell and Zwaagstra, 1981; Ulfhake and Kellerth, 1981; Zwaagstra and Kernell, 1981; Burke et al., 1982; Donselaar et al., 1986; Destombes et al., 1992[33; 79]
Sneuron[mm2]{0.08;0.64}{0.17;0.45}2.7Barrett and Crill, 1974; Ulfhake and Kellerth, 1981; Burke et al., 1982; Ulfhake and Kellerth, 1984; Ulfhake and Cullheim, 1988; Moschovakis et al., 1991[0.18; 0.44]
RatDsoma[µm]{17.5;66.0}{23.9;55.7}2.4Swett et al., 1986; Vult von Steyern et al., 1999; Copray and Kernell, 2000; Ishihara et al., 2001; Deardorff et al., 2013; Mierzejewska-Krzyżowska et al., 2014
MouseDsoma[µm]{14.0;35.0}{14.0;35.0}2.5Vult von Steyern et al., 1999
Sneuron[mm2]{0.01;0.08}{0.01;0.06}4.4Amendola and Durand, 2008; Brandenburg et al., 2020
Appendix 1—table 4
Typical ranges of physiological values for the motoneuron (MN) properties R, Rm, C, τ, Ith, AHP, and ACV.

As described in ‘Methods’, qAE is the average among reference studies of the ratios of minimum and maximum values; the properties experimentally vary over a qAE -fold range. This ratio compares with …

MN propertyUnitAbsolute exp {min;max}Average exp {min; max}qAEReference studiesqATqAEqATTheoretical range
R[MΩ]{0.2;8.1}{0.4;4.0}10.9Kernell, 1966; Burke, 1968; Burke and ten Bruggencate, 1971; Barrett and Crill, 1974; Gustafsson, 1979; Kernell and Zwaagstra, 1981; Fleshman et al., 1981; Burke et al., 1982; Ulfhake and Kellerth, 1984; Gustafsson and Pinter, 1984a; Zengel et al., 1985; Foehring et al., 1986; Munson et al., 1986; Foehring et al., 1987; Sasaki, 1991; Krawitz et al., 20018.41.3[0.5;4.0]
C[nF]{2.2;8.5}{2.2;8.5}3.9Gustafsson and Pinter, 1984a; Gustafsson and Pinter, 19852.31.6[3.2;7.5]
τ[ms]{2.0;14.2}{2.9;10.2}3.5Burke and ten Bruggencate, 1971; Barrett and Crill, 1974; Gustafsson, 1979; Ulfhake and Kellerth, 1984; Gustafsson and Pinter, 1984a; Gustafsson and Pinter, 1985; Sasaki, 19913.70.9[2.8;10.3]
Ith[nA]{1.7;52.7}{2.3;36.6}16.3Fleshman et al., 1981; Kernell and Monster, 1981; Ulfhake and Kellerth, 1984; Gustafsson and Pinter, 1984b; Zengel et al., 1985; Foehring et al., 1986; Munson et al., 1986; Foehring et al., 1987; Krawitz et al., 20019.11.8[3.9;35.0]
AHP[ms]{10.6;266.6}{44.2;158.7}4.1Eccles et al., 1957; Gustafsson, 1979; Dum and Kennedy, 1980; Zwaagstra and Kernell, 1980; Ulfhake and Kellerth, 1984; Gustafsson and Pinter, 1984a; Zengel et al., 1985; Foehring et al., 1987; Sasaki, 19913.81.1[42.6;160.2]
ACV[m·s-1]{51.1;127.2}{65.3;114.8}1.8Eccles et al., 1957; Mcphedran et al., 1965; Kernell, 1966; Appelberg and Emonet-Dénand, 1967; Burke, 1968; Barrett and Crill, 1974; Proske and Waite, 1974; Bagust, 1974; Stephens and Stuart, 1975; Cullheim, 1978; Dum and Kennedy, 1980; Zwaagstra and Kernell, 1980; Kernell and Zwaagstra, 1981; Fleshman et al., 1981; Glenn and Dement, 1981; Burke et al., 1982; Gustafsson and Pinter, 1984a; Zengel et al., 1985; Foehring et al., 1986; Foehring et al., 19872.30.8[63.5;116.6]
Appendix 1—table 5
Validation of the cat relationships (Table 4) against rat and mouse data.

nME, normalized maximum error; nRMSE, normalized root mean square error; rpred2, coefficient of determination between experimental and predicted quantities; rexp2, coefficient of determination of the power …

AnimalDatasetReference studiesnME (%)nRMSE (%)rpred2rexp2
RatIth;RGardiner, 1993; Bakels and Kernell, 1993; Lee and Heckman, 1998; Button et al., 2008; Turkin et al., 2010; Krutki et al., 2015352160.530.54
MouseIth;RDelestrée et al., 2014; Martínez-Silva et al., 2018; Huh et al., 2021385160.460.46
τ;RManuel et al., 200912191680.350.40
C;RManuel et al., 20091915980.380.38
Author response table 1
For one {A; B} global datasetTraining setTest set
Permutation 1p1, p2, p3, p4p5
Permutation 2p2, p3, p4, p5p1
Permutation 3p1, p3, p4, p5p2
Permutation 4p1, p2, p4, p5p3
Permutation 5p1, p2, p3, p5p4
Author response table 2
DatasetsPrevious validationNew validation
nMEnRMSER2nMEnRMSER2
AHP = ka ∙ SMNa70140,4067120,46
AHP = ka ∙ ACVa158200,43147190,43
R = ka ∙ SMNa255200,56312310,51
R = ka ∙ ACVa246230,43205180,46
R = ka ∙ AHPa153210,63143210,66
Ith = ka ∙ Ra410190,37300190,36
Ith = ka ∙ ACVa171260,34155200,42
Ith = ka ∙ AHPa84150,5978170,61
C = ka ∙ Ra61120,5855130,57
C = ka ∙ ITaℎ47170,5352190,49
C = ka ∙ AHPa75160,2662160,22
C = ka ∙ ACVa82210,1674210,20
τ = ka ∙ Ra86130,5473130,51
τ = ka ∙ AHPa88140,6277130,64
τ = ka ∙ ITaℎ83150,6865130,74
τ = ka ∙ ACVa81170,3884160,44

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