Specific Conversion Factors Research Articles

Cartridge-based automated BCR-ABL1 mRNA quantification: solving the issues of standardization, at what cost?

Molecular monitoring of chronic myeloid leukemia patients treated with tyrosine kinase inhibitors is essential for therapeutic stratification. Inter-laboratory reproducibility is, therefore, a crucial issue which requires standardization and strict alignment of BCR-ABL1 values to the international scale. An automated cartridge-based assay (Xpert BCR-ABL Monitor(™), Cepheid) had been proposed as a robust alternative to non-automated assays. This study aimed to compare inter-laboratory reproducibility of automated and non-automated quantification, the possibility of converting automated results to the international scale, and the potential economic impact of automation. One hundred and eighteen blood samples from chronic myeloid leukemia patients treated with tyrosine kinase inhibitors were prospectively analyzed in two laboratories using both automated and non-automated assays. The economic evaluation involved a micro-costing study and average costs were assessed as a function of sample throughput. Automated assays achieved similar inter-laboratory reproducibility to highly standardized non-automated assays and a short delay (≤6 h) between sampling and blood lysis had a positive impact on inter-laboratory reproducibility. Reporting automated BCR-ABL1 ratios on the international scale was possible using a specific conversion factor which may vary with batches. Cost assessment showed that automated assays could be relevant for annual activity levels below 300 since average costs were lower than those of the non-automated assays. The Xpert BCR-ABL Monitor(™) assay could be appropriately used in a near-patient setting for routine quantification of e13/e14-a2 transcripts, preferably in partnership with a regional reference laboratory. However, its prognostic impact relative to non-automated quantification remains to be tested prospectively within appropriate clinical trials.

Bioconversion of Carotenoids in Five Fruits and Vegetables to Vitamin A Measured by Retinol Accumulation in Rat Livers

Problem statement: Vitamin A deficiency is one of the most prevalent and major nutritional problems in developing countries, espec ially in young children. In many countries, a substantial proportion of dietary vitamin A is comm only derived from pro-vitamin A carotenoids obtained from colored fruits and orange or green ve getables. However, the bioavailability of retinol derived from carotenoids from these plant sources i s not well known. Approach: The present study analyzed β-Carotene and Total Carotenoids (TC) composition of carrots ( Daucus carota ), parsley (Petroselinum crispum ), Spinach ( Spinacea oleracea ), mangoes ( Mangifera indica ) and papayas (Carica papaya ) and determined the bioconversion of their caroten oids to vitamin A by monitoring the levels of retinol accumulated in liver and plasma o f Wistar rats ( Rattus norvegicus ). Products were freeze-dried, β-Carotene content analyzed by HPLC and TC by Spectrophotometry. Results: Carrots presented the highest content of β-carotene followed by parsley with 32.8 and 19.6 mg 100 g -1 , respectively. Spinach had the highest content of TC followed by parsley with 60.7 and 56.7 mg 100 g -1 , respectively. Four-week-old male Wistar rats receiv ed a standard diet as an adaptation period, a diet free of Carotenoids and Vitamin A (CVA-diet) as depletion period and finally a Fruit or Vegetable (FoV) based diet as repletion period. The highest β-carotene bioconversion was for mango and the lowest for parsley, whereas the highest TC bioconve rsion was for carrots and the lowest for parsley. There were no significant differences in plasma ret inol between treatments. Conclusion/Recommendations: There was no relation between carotenoids content in FoV-based diet and retinol status in plasma. Furthermore, the empl oyment of a general retinol conversion factor is regarded as not appropriate. So, it is recommended to consider specific conversion factors for groups of horticultural crops, for example, a factor for g reen leafy vegetables and other factor for fruits o r roots.

Conversion factors in carnivore scat analysis: sources of bias

AbstractScat analyses are commonly applied to study feeding ecology of carnivores. Factors developed in feeding trials are often used to convert dry matter mass of scat remainders to fresh matter mass of killed or scavenged prey. In our study, we aimed at: 1) presenting conversion factors (CFs) of roe deer Capreolus capreolus, European hare Lepus europaeus and house mice Mus musculus digested by wolf Canis lupus, Eurasian lynx Lynx lynx and red fox Vulpes vulpes, 2) comparing CFs derived from fox exposed to different feeding levels (fasted vs non‐fasted before each feeding trial), 3) comparing effects of using different mesh sizes in the lab procedure on CFs, 4) comparing effects of applying CFs derived from wolf, lynx and fox to wolf scats, and 5) quantifying biases caused by inappropriate procedures in scat analyses. Feeding level, use of different mesh sizes, and application of predator‐specific CFs affected the estimated number of killed prey individuals. The greatest deviations were found for the feeding level in regard to roe deer and European hare, and for the application of lynx CFs of roe deer and European hare to wolf scats. The strong relationship between prey use and CFs in our study may be used to estimate prey numbers from scats more precisely: in cases of low prey use, we suggest applying CFs derived from non‐fasted carnivores, and in cases of high prey use CFs from fasted conspecifics are more appropriate. We recommend applying predator‐prey specific CFs and using the same mesh size on which these CFs are based. The presented CFs allow recalculation of prey masses and prey numbers from scat analyses, which had been gained by using inappropriate CFs.

On the determination of the ingestion dose in drinking and mineral water

Abstract In Europe and Germany administrative regulations exist for the surveillance of the Total Indicative Dose of water supplied for human consumption. This parameter, which can not be analysed directly, has to be calculated using nuclide specific activity concentrations, age-specific dose conversion factors and consumption rates. Available calculation methods differ regarding the used radionuclides, consumption rates and whether they use age specific dose conversion factors or not. In Germany, administrative guidelines for the determination of the Total Ingestion Dose are still not available. From a large number of water sample analyses, a graded practical concept for the determination of the ingestion dose is derived, which considers radiological, analytical and hydrochemical aspects as well. Finally, it is suggested to consider mineral water in the same manner as drinking water.

Calculating effective dose on a cone beam computed tomography device: 3D Accuitomo and 3D Accuitomo FPD

This study evaluates two methods for calculating effective dose, CT dose index (CTDI) and dose-area product (DAP) for a cone beam CT (CBCT) device: 3D Accuitomo at field size 30x40 mm and 3D Accuitomo FPD at field sizes 40x40 mm and 60x60 mm. Furthermore, the effective dose of three commonly used examinations in dental radiology was determined. CTDI(100) measurements were performed in a CT head dose phantom with a pencil ionization chamber connected to an electrometer. The rotation centre was placed in the centre of the phantom and also, to simulate a patient examination, in the upper left cuspid region. The DAP value was determined with a plane-parallel transmission ionization chamber connected to an electrometer. A conversion factor of 0.08 mSv per Gy cm(2) was used to determine the effective dose from DAP values. Based on data from 90 patient examinations, DAP and effective dose were determined. CTDI(100) measurements showed an asymmetric dose distribution in the phantom when simulating a patient examination. Hence a correct value of CTDI(w) could not be calculated. The DAP value increased with higher tube current and tube voltage values. The DAP value was also proportional to the field size. The effective dose was found to be 11-77 microSv for the specific examinations. DAP measurement was found to be the best method for determining effective dose for the Accuitomo. Determination of specific conversion factors in dental radiology must, however, be further developed.

Converting Nitrogen into Protein—Beyond 6.25 and Jones' Factors

The protein content in foodstuffs is estimated by multiplying the determined nitrogen content by a nitrogen-to-protein conversion factor. Jones' factors for a series of foodstuffs, including 6.25 as the standard, default conversion factor, have now been used for 75 years. This review provides a brief history of these factors and their underlying paradigm, with an insight into what is meant by “protein.” We also review other compelling data on specific conversion factors which may have been overlooked. On the one hand, when 6.25 is used irrespective of the foodstuff, “protein” is simply nitrogen expressed using a different unit and says little about protein (s.s.). On the other hand, conversion factors specific to foodstuffs, such as those provided by Jones, are scientifically flawed. However, the nitrogen:protein ratio does vary according to the foodstuff considered. Therefore, from a scientific point of view, it would be reasonable not to apply current specific factors any longer, but they have continued to be used because scientists fear opening the Pandora's box. But because conversion factors are critical to enabling the simple conversion of determined nitrogen values into protein values and thus accurately evaluating the quantity and the quality of protein in foodstuffs, we propose a set of specific conversion factors for different foodstuffs, together with a default conversion factor (5.6). This would be far more accurate and scientifically sound, and preferable when specifically expressing nitrogen as protein. These factors are of particular importance when “protein” basically means “amino acids,” this being the principal nutritional viewpoint.

Validation of the International Scale for Measurement of BCR-ABL by RQ-PCR Based on Deriving Laboratory-Specific Conversion Factors.

BCR-ABL measurement by real-time quantitative PCR (RQ-PCR) has become an essential component for assessing treatment response for CML. A major molecular response (MMR) has prognostic significance and can be used to guide therapeutic decisions. However, the various methods are not standardized and the value representing MMR varies, which may lead to misinterpretation of molecular response. To align data, an international reporting scale (IS) was proposed where MMR is 0.10%. Conversion to the IS is achieved by applying laboratory (lab) specific conversion factors (CF). We aimed to1.calculate CF for diverse RQ-PCR methods by reference of patient BCR-ABL values to those generated in a reference lab with an established CF;2.validate the CF by subsequent patient sample exchange;3.examine the concordance of BCR-ABL values after IS conversion;4.determine if manufactured reference material is suitable for CF calculation. 34 labs from 13 countries (Australia/New Zealand 11, North/South America 9, Asia 8, Europe 6) sent 615 patient samples to the Adelaide reference lab to determine their specific CF.The RQ-PCR methods varied by the control gene (ABL 17, BCR 12, GUSβ 4, G6PDH 2, β2M 1, GAPDH 1; 3 labs used 2 controls therefore 37 methods), instrument, probe technology and standards. The CF for each method was calculated from the bias of patient BCR-ABL values between the originating lab and the reference lab, providing the bias was consistent across the dynamic range (Bland and Altman, Lancet , 1986; 1:307). CF were determined for 33 methods, 1 failed due to inconsistencies in the bias and 3 labs sent insufficient samples. CF were validated by sending subsequent sets of patient samples to the reference lab. The validation process is complete for 12 methods using 384 samples. The specific CF remained valid for each method. The mean bias between the reference and originating lab values was negligible after conversion. The limits of agreement indicated that 95% of values were within ±4.6-fold of the reference value. In contrast, prior to conversion 95% of values were within ±13-fold. Importantly after conversion the concordance in the range representing MMR was 87% (154/178 samples). In the future, conversion to the IS will be achieved using certified reference material, however this is currently not available. In order to mimic the patient bias CF calculation we prepared prototype reference material using BCR-ABL positive cells diluted to 4 levels using volunteer cells. The material was distributed to 29 labs and analysis completed for 24 methods. For 12 of the 24 the CF calculated using the reference material was consistent with the patient bias CF. This indicates that CF calculation is achievable using manufactured reference material but optimization is required before widespread distribution. In summary, alignment of BCR-ABL data generated from diverse methods is achievable using an international standardisation approach, and differences between laboratories are small enough to allow consistent interpretation of results and clinical decision-making.

Satellite remote sensing derived spatial water utilisation index (wui) for benchmarking of irrigation systems

Water Utilisation Index (WUI) defined as area irrigated per unit volume is a measure of water delivery performance and constitutes one of the important spatial performance indicators of an irrigation system. WUI also forms basis for evaluating the adequacy of seasonal irrigation supplies in an irrigation system (inverse of WUI is delta, i.e. depth of water supplied to a given irrigation unit). In the present study WUI and adequacy indicators were used in benchmarking the performance of Nagarjunasagar Left Canal Command (NSLC) in Andhra Pradesh. Optimised temporal satellite data of rabi season during the years 1990–91 and 1998–99 was used in deriving irrigated crop areas adopting hierarchical classification approach. Paddy is the predominant crop grown and cotton, chillies, sugarcane etc. are the other crops grown in the study area. Equivalent wet area (paddy crop area) was estimated using the operationally used project specific conversion factors. WUI was estimated at disaggregated level viz., distributary, irrigation block, irrigation zone level using the canal discharge data. At project level, WUI estimated to be 65 ha/MCM and 92 ha/MCM during rabi season of 1990–91 and 1998–99 years respectively. A comparison of total irrigated area and discharges corresponding to both the years indicate that irrigation service is extensive and sub optimal during 1998–99 and it is intensive and optimal in 1990–91. It was also observed that WUI is lesser in blocks of with higher Culturable Command Area (CCA) compared to the blocks of lower CCA. All the disaggregated units were ranked into various groups of different levels of water distribution performance. The study demonstrates the utility of WUI as spatial performance indicator and thus useful for benchmarking studies of irrigation command areas. The WUI together with satellite data derived spatial irrigation intensity, crop productivity constitutes important benchmarking indices in irrigation command areas.

First Results from a Collaborative Initiative To Develop an International Scale for the Measurement of BCR-ABL by RQ-PCR Based on Deriving Laboratory-Specific Conversion Factors.

RQ-PCR provides an appropriate method to monitor CML. However methods are not standardized leading to differences in reported BCR-ABL values. An International Scale (IS) was proposed to generate comparable values when tested in any laboratory, Blood,2006,108,28. The scale is fixed to a major molecular response (MMR), a value with established prognostic significance. We distributed BCR-ABL reference standards to 12 laboratories (labs) to establish lab specific conversion factors (CF) for the IS. The IS MMR value is 0.1%. The Adelaide reference laboratory (ref lab) has an established MMR value (0.08%) and the CF is 1.25 (0.1/0.08). Multiplying by 1.25 converts the ref lab values to the IS. The ref lab prepared standards with 3 BCR-ABL levels (L1, L2, L3) by diluting K562 cells in cells of normal volunteers. Trizol stabilized cells were sent frozen to labs in Europe (2), USA (3), Asia (5) and Australia (2) that use various methods and controls (ABL 7, BCR 3, GUS 1, ABL and GUS 1). Each lab determined mean BCR-ABL/control% values for each level, which were correlated with those of the ref lab. CF were calculated from regression equations using the formulae: Log y=(slope×(log 0.1))+intercept, CF=0.1/antilog y, where y=lab equivalent MMR value and 0.1=IS MMR. 11 of 12 labs showed a linear relationship across the standards and were included in the analysis. Prior to IS conversion there was a wide range between the lowest and highest values; L1 22-fold (r0.01–0.31); L2 48-fold (r0.06–3.0); L3 10-fold (r10–101). After IS conversion using lab specific CF the agreement was substantially improved; L1 1.8-fold (r0.07–0.13), L2 2.4-fold (r0.33–0.77), L3 3.9-fold (r19–76). CF have been validated for 5 labs by patient sample exchange. The ref lab tested up to 20 samples per lab and values compared before and after conversion. Conversion failed to align data in 1 lab and the reason is not yet established. In the other 4 labs there was a significant difference in the median values before conversion (p=0.01) but not after (p=0.49). 75% were within 2-fold and 98% within 5-fold after conversion, a significant improvement compared to pre conversion (45% p=0.005, 72% p=0.0001). The preliminary data suggest the approach is a reasonable process to achieve standardization, which is anchored to a critical BCR-ABL value. It allows for differences generated by various RQ-PCR methods and controls. The on-going validity of conversion is reliant on maintaining performance of analysis within a lab. We anticipate the project will lead to preparation of certified reference standards available to all labs and that standardized molecular monitoring will facilitate more consistent adherence to treatment guidelines.

MATHEMATICAL CONSTANTS THAT VARY?

Dear Editor-in-Chief: Hinckson and Hopkins (1) used mathematical modeling to predict test–retest error of time trials (TT) from variability in time-to-exhaustion tests (TTE). Sample mean estimates of model parameters were considered mathematical constants and used to convert TTE to TT variability; for example, in the critical power model, the value of the term “a/m” was set at 0.506. This sample mean value was then used as a constant factor for converting the sample mean coefficient of variation (CV) in TTE to that in TT. Hinckson and Hopkins' data suggest that the conversion factors employed are not constants at all, but are themselves prone to both between- and within-subject variability. The between- and within-subject CV for the “a/m” conversion factor were 28 and 16%, respectively. It seems inappropriate to use a constant value to convert changes in TTE to changes in TT, when the relationship between these two variables differs substantially between individuals and over time. An analogous situation would be one in which a researcher calculates the work rate corresponding to a certain %V̇O2max for all individuals in all situations using constant values of slope and intercept for the V̇O2–work rate relationship. We request that TT is predicted from TTE using estimates of model parameters specific to a particular subject at a specific time. Once these predicted TT times have been calculated for all subjects at the six test times using specific conversion factors, a CV can be calculated in the normal way. We predict that this CV for predicted TT is larger than those reported in (1), because the between- and within-subject variability in the conversion factors themselves was originally “averaged out.” Aside from the mathematical modeling issues, the exact contribution of variability in pacing strategy to variability in overall TT time is not known at present. Pacing strategy, being an inherent component of real performance, should not be used to deem that something is wrong with TT protocols. Moreover, TTE tests have their own unique components of error. For example, in a relatively long TTE test performed at a lower %V̇O2max, the athlete may be more likely to stop the test, not because of exhaustion, but because of boredom or the need to fulfil other obligations. Physiological variables are conventionally measured at regular periods during longer TTE tests. These measurements would merely serve to provide the athlete with feedback about time completed. Such sources of error in TTE tests should be investigated before it is claimed that any concerns about time-to-exhaustion tests have been laid to rest. Greg Atkinson Research Institute for Sport and Exercise Sciences Liverpool John Moores University Liverpool, United Kingdom Alan Nevill School of Sport, Performing Arts and Leisure University of Wolverhampton Walsall, United Kingdom

A lumped parameter model for acarine predator–prey population interactions

We hereby describe a modelling strategy, based on the implementation of composite models for the numerical simulation of the predator–prey local dynamics. We define a lumped parameter model for the dynamics of the system, where the abundance of the populations are given in terms of their biomass. The model is characterised by bio-ecological parameters (maximum specific rates and conversion factors) and by two functions: the specific growth rate of the prey in absence of predator, and the specific rate of predation, called trophic function. We consider prey growth rates which take into account either undercrowding and overcrowding effects, or only overcrowding effects. We also consider trophic functions depending either on the prey abundance, or on the ratio of the abundance of prey and predator. The responses of the model to different prey growth rates and trophic functions are investigated. Procedures are given for estimating the lumped parameters by means of demographic models of a single species population with stage structure, and formulated in terms of individual life history data. The methodology is applied to a case study of biological control of an acarine population system. Numerical experiments have been performed to illustrate the behaviours of the model with different prey growth and trophic functions. Results of numerical simulations are compared to the dynamics obtained in field experiments.

Moisture content in Dall's porpoise ( Phocoenoides dalli) tissues: a reference base for conversion factors between dry and wet weight trace element concentrations in cetaceans

Concentration of trace elements measured by dry weight basis has become more commonly used in recent studies on cetaceans than wet weight basis, which was used more in earlier studies. Because few authors present moisture content data in their papers, it is difficult to compare the concentrations of trace elements between various studies. Therefore, we felt that it would be useful if a reference conversion factor (CF) for tissue types could be found to convert between wet weight and dry weight data on trace element concentrations. We determined the moisture contents of 14 tissues of Dall's porpoise ( Phocoenoides dalli), and then, calculated the CF values for those tissues. Because the moisture content of each tissue differs from other tissues, it is necessary to use a specific CF for each tissue rather than a general CF for several tissues. We have also found that CF values for Dall's porpoise tissues are similar to the same tissues in other cetaceans. Therefore CF values from Dall's porpoise can be reliably used to convert between wet and dry weight concentrations for other cetacean tissues as reference data.

Empirically based conversion factors for calculating couple-years of protection.

Couple-years of protection (CYP) is one of several commonly used indicators to assess international family planning efforts. It has been the subject of much debate, relating in part to the specific conversion factors used to translate the quantity of the respective contraceptive methods distributed to a single measure of protection. This article outlines a comprehensive effort to revisit those conversion factors based on the best available empirical evidence. In most instances, the analysis supports previously established standard conversion factors. However, there are two notable departures. Fewer condoms and spermicides are recommended for each CYP (120 vs. 150), primarily because coital frequency among condom users is lower than previously assumed. Furthermore, for sterilization, the authors recommend the use of country or region-specific conversion factors. Every program evaluation indicator has strengths and weaknesses, and the best program evaluation efforts use a variety of indicators. If CYP is used to evaluate programs, however, the authors believe that the conversion factors presented reflect the best available evidence.

Calculation of computed tomography dose index to effective dose conversion factors based on measurement of the dose profile along the fan shaped beam.

The variation in computed tomography dose index (CTDI) to effective dose conversion factors between different types of CT scanner is large (i.e. a factor of about 2 due to differences in beam shaping filters). Consequently, scanner specific conversion factors have to be applied. For some types of scanner, however, detailed information on the construction of beam shaping filters is not provided by the manufacturers. It is of interest to investigate the use of measured dose profiles for the calculation of conversion factors. Based upon measured dose profiles, two appropriate photon spectra selected on the basis of measured half value layers, gender specific adult phantoms Adam and Eva, and the Monte Carlo neutron and photon radiation transport code (MCNP), organ and effective dose conversion factors are calculated. To validate the method, a comparison is made between results for measured and calculated beam profiles for a Philips Tomoscan 350. The results in terms of effective dose per slice per unit of CTDI are compared with published data. Relative difference in conversion factors per slice averaged over all slices used for the calculations is 13 +/- 4% between the two spectra, 10.2 +/- 0.2% between measured and calculated beam profiles and 50 +/- 191% between the phantoms of different gender. The relative difference between the averaged results for the Adam and Eva phantoms and published results for a hermaphrodite phantom is on average equal to or less than 15 +/- 13%, depending on the spectrum and beam profile used, although larger differences can occur for specific slices. It is concluded that CTDI to effective dose conversion factors can be derived on the basis of measured beam profiles.

Bacterial Production and Growth Rate Estimation from [ 3 H]Thymidine Incorporation for Attached and Free-Living Bacteria in Aquatic Systems

Production and specific growth rates of attached and free-living bacteria were estimated in an oligotrophic marine system, La Salvaje Beach, Vizcaya, Spain, and in a freshwater system having a higher nutrient concentration, Butron River, Vizcaya, Spain. Production was calculated from [methyl-H]thymidine incorporation by estimating specific conversion factors (cells or micrograms of C produced per mole of thymidine incorporated) for attached and free-living bacteria, respectively, in each system. Conversion factors were not statistically different between attached and free-living bacteria: 6.812 x 10 and 8.678 x 10 mug of C mol for free-living and attached bacteria in the freshwater system, and 1.276 x 10 and 1.354 x 10 mug of C mol for free-living and attached bacteria in the marine system. Therefore, use of a unique conversion factor for the mixed bacterial population is well founded. However, conversion factors were higher in the freshwater system than in the marine system. This could be due to the different trophic conditions of the two systems. Free-living bacteria contributed the most to production in the two systems (85% in the marine system and 67% in the freshwater system) because of their greater contribution to total biomass. Specific growth rates calculated from production data and biomass data were similar for attached and free-living bacteria.

Effect of Dietary Fiber on the Metabolizable Energy of Human Diets

Two diets consisting of natural foods that differed in fiber content were fed to 12 men for 6 wk each in a crossover design. Diet 1 contained 37 g total dietary fiber (TDF) from fruits and vegetables and diet 2 contained 16 g TDF from fruit and vegetable juices in a 2800-kcal menu. Seven-day food, urine and fecal composites were made and analyzed for their gross energy, fat, protein and carbohydrate content during the fourth and fifth weeks of each dietary consumption period. The metabolizable energy (ME) of these diets was determined (gross energy of the diet - gross energy of urine and feces) and calculated by Atwater's general energy conversion factors (4, 9, 4), by specific energy conversion factors used in a U.S. food table and by formulas derived by various researchers. The coefficients of availability of energy and the energy-containing nutrients, fat, protein and carbohydrate, were lower while subjects were consuming the higher fiber diet. The specific energy conversion factors of the U.S. food table gave better estimates of the true ME of the lower fiber diet than the higher fiber diet, overestimating the ME of these diets by only 6% (diet 1) and 4.6% (diet 2).

Conversion of Biovolume Measurements of Soil Organisms, Grown Under Various Moisture Tensions, to Biomass and Their Nutrient Content

Direct microscopic measurements of biomass in soil require conversion factors for calculation of the mass of microorganisms from the measured volumes. These factors were determined for two bacteria, five fungi, and a yeast isolated from soil. Moisture stress conditions occurring in nature were simulated by growth in two media using shake cultures, on agar plates, and on membranes held at 34, 330, and 1,390 kPa of suction. The observed conversion factors, i.e., the ratio between dry weight and wet volume, generally increased with increasing moisture stress. The ratios for fungi ranged from 0.11 to 0.41 g/cm with an average of 0.33 g/cm. Correction of earlier data assuming 80% water and a wet-weight specific gravity of 1.1 would require a conversion factor of 1.44. The dry-weight specific gravity of bacteria and yeasts ranged from 0.38 to 1.4 g/cm with an average of 0.8 g/cm. These high values can only occur at 10% ash if no more than 50% of the cell is water, and a specific conversion factor to correct past data for bacterial biomass has not yet been suggested. The high conversion factors for bacteria and yeast could not be explained by shrinkage of cells due to heat fixing, but shrinkage during preparation could not be completely discounted. Moisture stress affected the C, N, and P content of the various organisms, with the ash contents increasing with increasing moisture stress. Although further work is necessary to obtain accurate conversion factors between biovolume and biomass, especially for bacteria, this study clearly indicates that existing data on the specific gravity and the water and nutrient content of microorganisms grown in shake cultures cannot be applied when quantifying the soil microbial biomass.