S100B belongs to a family of calcium-binding proteins implicated in intracellular and extracellular regulatory activities. This study of serum S100B in primary progressive multiple sclerosis (PPMS) is based on data obtained from a randomized, controlled trial of Interferon β-1a in subjects with PPMS. The key questions were whether S100B levels were associated with either disability or MRI findings in primary progressive MS and whether Interferon β-1a has an effect on their S100B levels. Serial serum S100B levels were measured using an ELISA method. The results demonstrated that serum S100B is not related to either disease progression or MRI findings in subjects with primary progressive MS given Interferon β-1a. Furthermore there is no correlation between S100B levels and the primary and secondary outcome measures.

Introduction S100B belongs to a family of calcium-binding proteins implicated in intracellular and extracellular regulatory activities [ 2 ]. Intracellularly, it exhibits regulatory effects on cell growth, differentiation, cell shape and energy metabolism. Extracellularly, S100B stimulates neuronal survival, differentiation, astrocytic proliferation, neuronal death via apoptosis, and stimulates (in some cases) or inhibits (in others) activity of inflammatory cells. Several studies suggest that S100B has a role in the pathogenesis of multiple sclerosis (MS). Phenotypically and functionally similar T cells specific against S100B can be detected in the peripheral blood of MS patients making S100B a putative candidate auto-antigen in MS [ 15 ]. Furthermore, S100B may act as a cytokine [ 2 , 10 , 11 ] and in vitro studies show that, at high levels, S100 can induce the neuronal expression and secretion of pro-inflammatory interleukin-6. In addition, elevated levels of S100B have been detected in the cerebrospinal fluid (CSF) of MS patients during acute phases or exacerbations of the disease [ 10 ] and it has therefore been proposed that elevated S100B may be indicative of active cell injury [ 11 ]. Interferon-β (IFN-β) is effective in reducing relapse rate in relapsing-remitting [ 6 , 14 , 17 ] and secondary progressive MS [ 3 ] but the mechanisms behind the beneficial action of IFNβ are not fully understood. Two potential sites of action are on cytokine production [ 1 , 4 , 12 ] and on the entry of leukocytes into the CNS [ 8 , 9 , 16 , 18 ]. In this clinically negative phase II study [ 7 ], we assessed the effect of IFNβ-1a on serum levels of S100B at 3-month intervals in subjects with primary progressive MS (PPMS). The key questions were whether serum S100B levels correlated with disability or MRI findings in patients with PPMS, and whether IFN-β has an effect on levels of serum S100B.
Introduction
S100B belongs to a family of calcium-binding proteins implicated in intracellular and extracellular regulatory activities [ 2 ]. Intracellularly, it exhibits regulatory effects on cell growth, differentiation, cell shape and energy metabolism. Extracellularly, S100B stimulates neuronal survival, differentiation, astrocytic proliferation, neuronal death via apoptosis, and stimulates (in some cases) or inhibits (in others) activity of inflammatory cells.Several studies suggest that S100B has a role in the pathogenesis of multiple sclerosis (MS). Phenotypically and functionally similar T cells specific against S100B can be detected in the peripheral blood of MS patients making S100B a putative candidate auto-antigen in MS [ 15 ]. Furthermore, S100B may act as a cytokine [ 2 , 10 , 11 ] and in vitro studies show that, at high levels, S100 can induce the neuronal expression and secretion of pro-inflammatory interleukin-6. In addition, elevated levels of S100B have been detected in the cerebrospinal fluid (CSF) of MS patients during acute phases or exacerbations of the disease [ 10 ] and it has therefore been proposed that elevated S100B may be indicative of active cell injury [ 11 ].Interferon-β (IFN-β) is effective in reducing relapse rate in relapsing-remitting [ 6 , 14 , 17 ] and secondary progressive MS [ 3 ] but the mechanisms behind the beneficial action of IFNβ are not fully understood. Two potential sites of action are on cytokine production [ 1 , 4 , 12 ] and on the entry of leukocytes into the CNS [ 8 , 9 , 16 , 18 ].In this clinically negative phase II study [ 7 ], we assessed the effect of IFNβ-1a on serum levels of S100B at 3-month intervals in subjects with primary progressive MS (PPMS). The key questions were whether serum S100B levels correlated with disability or MRI findings in patients with PPMS, and whether IFN-β has an effect on levels of serum S100B.Methods Patients and examination Fifty patients with PPMS were recruited in a phase II trial of IFNβ-1a (Avonex ® , Biogen) and were assessed three monthly over a study period of 2 years. Fifteen of these patients were treated with IFNβ-1a 30μg intramuscularly (im) weekly (IFN30), 15 received IFNβ-1a 60μg im weekly (IFN60) and 20 with placebo. IFNβ-1a was reduced to half dose in 5 subjects receiving 60μg im weekly, and in 2 subjects receiving IFNβ-1a 30μg im weekly. Seven subjects withdrew from treatment [ 7 ] (see Figure  1 ). Figure 1 Fifty subjects with PPMS were randomised in a phase II trial of Interferon β-1a and were assessed 3 monthly over a 2-year study period. n = number of subjects with PPMS Neurological examination was performed at each visit and disability was measured using Kurtzke's expanded disability status scale (EDSS). Progression was defined as a sustained (3 months apart) increase of at least 1.0 on the EDSS scale between 0 to 5 and 0.5 for subjects with EDSS score of 5.5 and above. Fourteen healthy subjects served as controls. All subjects provided informed consent prior to their inclusion in the study. This study was approved by the ethics committee and has therefore been performed with the ethical standards laid down in the 1964 Declaration of Helsinki. MR imaging and analyses MRI was performed at baseline and 6 monthly for 2 years. Only baseline and year 2 data were included in this study. Brain and spinal cord atrophy, ventricular volume, T1 and T2 lesion load were measured as described elsewhere [ 7 ]. Serum S100B levels Serum samples were centrifuged and stored at -20°C. Serum S100B levels were quantified using a modified ELISA method as previously described by Green et al. [ 5 ]. Ninety-six-well plates were coated with 100μl 0.05 M carbonate buffer containing 10μl monoclonal anti-S100B (Affiniti Research Products, Exeter, UK). The plates were washed with 0.67 M barbitone buffer containing 5 mM calcium lactate, 0.1% BSA and 0.05% Tween and then blocked with 2% BSA and washed again. Diluted serum (1:1) in 0.67 M barbitone buffer containing 5 mM calcium lactate was added in duplicate. After incubation and wash 0.1% HRP conjugated polyclonal anti-S100B (Dako, Copenhagen, Denmark) was used as detecting antibody. The OPD colour reaction was stopped with 1 M hydrochloric acid and the absorbance read at 492 and 405 nm. The antigen concentration was calculated against a standard curve ranging from 0.01 to 2.5 ng/ml. Statistical analyses Median, interquartile range and significance of group differences (Mann-Whitney U tests) were evaluated. Changes of serum level over time were examined using variance components regression models of serum response variable on time as predictor, with random subject-specific intercepts and fixed common slopes. Curvature was assessed using a quadratic term in time; modification of curve over time by treatment was assessed using additional terms for treatment and treatment by time interaction in the model. Two sets of treatment terms were used: i) indicators of assigned weekly dose ii) average weekly dose over follow-up (including changes to dose regime) as continuous variable. Modification of the curve over time by MRI variable values were similarly examined using terms for MRI variable and MRI variable by time interaction. Direct associations between serum level and MRI/clinical variables were examined by regression models of 24 month serum on 24 month MRI variable, adjusting for baseline serum and MRI values (this type of model takes into account change from baseline), with additional terms for treatment and treatment by MRI variable interaction, the latter to assess possible modifications of the relationship by treatment. Software used were the SPSS software package (version 11.0 for Windows) and Stata 7.0 (Stata Corporation. Stata Statistical Software: Release 7.0. College Station, Texas, USA).
Methods
Patients and examination Fifty patients with PPMS were recruited in a phase II trial of IFNβ-1a (Avonex ® , Biogen) and were assessed three monthly over a study period of 2 years. Fifteen of these patients were treated with IFNβ-1a 30μg intramuscularly (im) weekly (IFN30), 15 received IFNβ-1a 60μg im weekly (IFN60) and 20 with placebo. IFNβ-1a was reduced to half dose in 5 subjects receiving 60μg im weekly, and in 2 subjects receiving IFNβ-1a 30μg im weekly. Seven subjects withdrew from treatment [ 7 ] (see Figure  1 ). Figure 1 Fifty subjects with PPMS were randomised in a phase II trial of Interferon β-1a and were assessed 3 monthly over a 2-year study period. n = number of subjects with PPMS Neurological examination was performed at each visit and disability was measured using Kurtzke's expanded disability status scale (EDSS). Progression was defined as a sustained (3 months apart) increase of at least 1.0 on the EDSS scale between 0 to 5 and 0.5 for subjects with EDSS score of 5.5 and above. Fourteen healthy subjects served as controls. All subjects provided informed consent prior to their inclusion in the study. This study was approved by the ethics committee and has therefore been performed with the ethical standards laid down in the 1964 Declaration of Helsinki.
Patients and examination
Fifty patients with PPMS were recruited in a phase II trial of IFNβ-1a (Avonex ® , Biogen) and were assessed three monthly over a study period of 2 years. Fifteen of these patients were treated with IFNβ-1a 30μg intramuscularly (im) weekly (IFN30), 15 received IFNβ-1a 60μg im weekly (IFN60) and 20 with placebo. IFNβ-1a was reduced to half dose in 5 subjects receiving 60μg im weekly, and in 2 subjects receiving IFNβ-1a 30μg im weekly. Seven subjects withdrew from treatment [ 7 ] (see Figure  1 ).Neurological examination was performed at each visit and disability was measured using Kurtzke's expanded disability status scale (EDSS). Progression was defined as a sustained (3 months apart) increase of at least 1.0 on the EDSS scale between 0 to 5 and 0.5 for subjects with EDSS score of 5.5 and above.Fourteen healthy subjects served as controls.All subjects provided informed consent prior to their inclusion in the study. This study was approved by the ethics committee and has therefore been performed with the ethical standards laid down in the 1964 Declaration of Helsinki.MR imaging and analyses MRI was performed at baseline and 6 monthly for 2 years. Only baseline and year 2 data were included in this study. Brain and spinal cord atrophy, ventricular volume, T1 and T2 lesion load were measured as described elsewhere [ 7 ].
MR imaging and analyses
MRI was performed at baseline and 6 monthly for 2 years. Only baseline and year 2 data were included in this study. Brain and spinal cord atrophy, ventricular volume, T1 and T2 lesion load were measured as described elsewhere [ 7 ].Serum S100B levels Serum samples were centrifuged and stored at -20°C. Serum S100B levels were quantified using a modified ELISA method as previously described by Green et al. [ 5 ]. Ninety-six-well plates were coated with 100μl 0.05 M carbonate buffer containing 10μl monoclonal anti-S100B (Affiniti Research Products, Exeter, UK). The plates were washed with 0.67 M barbitone buffer containing 5 mM calcium lactate, 0.1% BSA and 0.05% Tween and then blocked with 2% BSA and washed again. Diluted serum (1:1) in 0.67 M barbitone buffer containing 5 mM calcium lactate was added in duplicate. After incubation and wash 0.1% HRP conjugated polyclonal anti-S100B (Dako, Copenhagen, Denmark) was used as detecting antibody. The OPD colour reaction was stopped with 1 M hydrochloric acid and the absorbance read at 492 and 405 nm. The antigen concentration was calculated against a standard curve ranging from 0.01 to 2.5 ng/ml.
Serum S100B levels
Serum samples were centrifuged and stored at -20°C. Serum S100B levels were quantified using a modified ELISA method as previously described by Green et al. [ 5 ]. Ninety-six-well plates were coated with 100μl 0.05 M carbonate buffer containing 10μl monoclonal anti-S100B (Affiniti Research Products, Exeter, UK). The plates were washed with 0.67 M barbitone buffer containing 5 mM calcium lactate, 0.1% BSA and 0.05% Tween and then blocked with 2% BSA and washed again. Diluted serum (1:1) in 0.67 M barbitone buffer containing 5 mM calcium lactate was added in duplicate. After incubation and wash 0.1% HRP conjugated polyclonal anti-S100B (Dako, Copenhagen, Denmark) was used as detecting antibody. The OPD colour reaction was stopped with 1 M hydrochloric acid and the absorbance read at 492 and 405 nm. The antigen concentration was calculated against a standard curve ranging from 0.01 to 2.5 ng/ml.Statistical analyses Median, interquartile range and significance of group differences (Mann-Whitney U tests) were evaluated. Changes of serum level over time were examined using variance components regression models of serum response variable on time as predictor, with random subject-specific intercepts and fixed common slopes. Curvature was assessed using a quadratic term in time; modification of curve over time by treatment was assessed using additional terms for treatment and treatment by time interaction in the model. Two sets of treatment terms were used: i) indicators of assigned weekly dose ii) average weekly dose over follow-up (including changes to dose regime) as continuous variable. Modification of the curve over time by MRI variable values were similarly examined using terms for MRI variable and MRI variable by time interaction. Direct associations between serum level and MRI/clinical variables were examined by regression models of 24 month serum on 24 month MRI variable, adjusting for baseline serum and MRI values (this type of model takes into account change from baseline), with additional terms for treatment and treatment by MRI variable interaction, the latter to assess possible modifications of the relationship by treatment. Software used were the SPSS software package (version 11.0 for Windows) and Stata 7.0 (Stata Corporation. Stata Statistical Software: Release 7.0. College Station, Texas, USA).
Statistical analyses
Median, interquartile range and significance of group differences (Mann-Whitney U tests) were evaluated. Changes of serum level over time were examined using variance components regression models of serum response variable on time as predictor, with random subject-specific intercepts and fixed common slopes. Curvature was assessed using a quadratic term in time; modification of curve over time by treatment was assessed using additional terms for treatment and treatment by time interaction in the model. Two sets of treatment terms were used: i) indicators of assigned weekly dose ii) average weekly dose over follow-up (including changes to dose regime) as continuous variable. Modification of the curve over time by MRI variable values were similarly examined using terms for MRI variable and MRI variable by time interaction.Direct associations between serum level and MRI/clinical variables were examined by regression models of 24 month serum on 24 month MRI variable, adjusting for baseline serum and MRI values (this type of model takes into account change from baseline), with additional terms for treatment and treatment by MRI variable interaction, the latter to assess possible modifications of the relationship by treatment.Software used were the SPSS software package (version 11.0 for Windows) and Stata 7.0 (Stata Corporation. Stata Statistical Software: Release 7.0. College Station, Texas, USA).Results Serum S100B between subjects with PPMS and controls The median and interquartile ranges for all subjects are described in Table  1 . There were no significant differences between any of the groups in relation to age. When comparing S100B levels at baseline of subjects with PPMS and controls, the difference was not statistically significant (p = 0.3). Table 1 Age and serial serum S100B levels expressed as median (interquartile range). n = number of subjects; mo, months; N/A, non-applicable. Control (n = 14) Placebo (n = 20) IFN30 (n = 15) IFN60 (n = 15) Male:Female 6:8 n = 14 15:5 n = 20 10:5 n = 15 7:8 n = 15 Age (years) 32 (29–44) n = 14 43 (36–51) n = 20 51 (39–53) n = 15 52 (43–54) n = 15 S100B-0mo 0.08 (0.08–0.10) n = 14 0.09 (0.02–0.10) n = 20 0.06 (0.04–0.10) n = 12 0.07 (0.04–0.10) n = 14 S100B-3mo N/A 0.08 (0.05–0.10) n = 20 0.06 (0.05–0.10) n = 15 0.07 (0.04–0.10) n = 14 S100B-6mo N/A 0.10 (0.03–0.20) n = 18 0.07 (0.04–0.10) n = 15 0.07 (0.04–0.10) n = 14 S100B-9mo N/A 0.08 (0.03–0.10) n = 18 0.05 (0.02–0.10) n = 15 0.06 (0.04–0.10) n = 14 S100B-12mo N/A 0.07 (0.03–0.10) n = 17 0.08 (0.05–0.10) n = 15 0.08 (0.04–0.10) n = 14 S100B-15mo N/A 0.07 (0.02–0.10) n = 19 0.07 (0.04–0.10) n = 14 0.09 (0.04–0.10) n = 14 S100B-18mo N/A 0.07 (0.04–0.10) n = 18 0.06 (0.02–0.09) n = 13 0.09 (0.03–0.20) n = 14 S100B-21mo N/A 0.06 (0.05–0.10) n = 18 0.08 (0.04–0.10) n = 14 0.08 (0.04–0.20) n = 13 S100B-24mo N/A 0.07 (0.02–0.10) n = 18 0.07 (0.05–0.10) n = 15 0.06 (0.04–0.10) n = 13 Serum S100B change over time There was no change over time in the serum S100B levels. The shape of the serum trajectory did not vary between the treatment regimes, i.e. placebo vs. IFN30 vs. IFN60. Serum S100B versus Clinical and MRI parameters (Table  2 ) There was no evidence that the 24-month serum S100B values were associated with either changes in the T1 or T2 loads, or ventricular or cord volumes at 24 months, after adjusting for the baseline values of each subject. There was no correlation with disease progression on the EDSS. There was also no evidence that these relationships were modified by treatment assignment (intention-to-treat analysis) (Table  2 ) or the overall average dose, which included the changes to treatment regime (non-intention-to-treat analysis) (Table  2 ). Table 2 Serum S100B versus Clinical and MRI variables. Estimated mean change in 24-month serum S100B associated with unit increase in mean value of T1 and T2 lesion load, ventricular and spinal cord volume, adjusted for baseline values of both serum S100B and of MRI parameters. Baseline adjustment ensures that the coefficient assesses the 'effect' of the 24-month MRI parameters value relative to its baseline. * Test of treatment interactions with row variable. Variable Coefficient P-value 95% Confidence Interval (CI) P-value for treatment modification*: Assignment average dose 24 month T1 load -4 × 10 -6 0.35 -1 × 10 -5 , 4 × 10 -6 0.76 0.59 24 month T2 load -3 × 10 -6 0.16 -7 × 10 -6 , 1 × 10 -6 0.57 0.89 24 month ventricular volume 7 × 10 -7 0.75 -3 × 10 -6 , 5 × 10 -6 0.46 0.24 24 month cord volume -2 × 10 -3 0.54 -9 × 10 -3 , 5 × 10 -3 0.58 0.88
Results
Serum S100B between subjects with PPMS and controls The median and interquartile ranges for all subjects are described in Table  1 . There were no significant differences between any of the groups in relation to age. When comparing S100B levels at baseline of subjects with PPMS and controls, the difference was not statistically significant (p = 0.3). Table 1 Age and serial serum S100B levels expressed as median (interquartile range). n = number of subjects; mo, months; N/A, non-applicable. Control (n = 14) Placebo (n = 20) IFN30 (n = 15) IFN60 (n = 15) Male:Female 6:8 n = 14 15:5 n = 20 10:5 n = 15 7:8 n = 15 Age (years) 32 (29–44) n = 14 43 (36–51) n = 20 51 (39–53) n = 15 52 (43–54) n = 15 S100B-0mo 0.08 (0.08–0.10) n = 14 0.09 (0.02–0.10) n = 20 0.06 (0.04–0.10) n = 12 0.07 (0.04–0.10) n = 14 S100B-3mo N/A 0.08 (0.05–0.10) n = 20 0.06 (0.05–0.10) n = 15 0.07 (0.04–0.10) n = 14 S100B-6mo N/A 0.10 (0.03–0.20) n = 18 0.07 (0.04–0.10) n = 15 0.07 (0.04–0.10) n = 14 S100B-9mo N/A 0.08 (0.03–0.10) n = 18 0.05 (0.02–0.10) n = 15 0.06 (0.04–0.10) n = 14 S100B-12mo N/A 0.07 (0.03–0.10) n = 17 0.08 (0.05–0.10) n = 15 0.08 (0.04–0.10) n = 14 S100B-15mo N/A 0.07 (0.02–0.10) n = 19 0.07 (0.04–0.10) n = 14 0.09 (0.04–0.10) n = 14 S100B-18mo N/A 0.07 (0.04–0.10) n = 18 0.06 (0.02–0.09) n = 13 0.09 (0.03–0.20) n = 14 S100B-21mo N/A 0.06 (0.05–0.10) n = 18 0.08 (0.04–0.10) n = 14 0.08 (0.04–0.20) n = 13 S100B-24mo N/A 0.07 (0.02–0.10) n = 18 0.07 (0.05–0.10) n = 15 0.06 (0.04–0.10) n = 13
Serum S100B between subjects with PPMS and controls
The median and interquartile ranges for all subjects are described in Table  1 . There were no significant differences between any of the groups in relation to age. When comparing S100B levels at baseline of subjects with PPMS and controls, the difference was not statistically significant (p = 0.3).Age and serial serum S100B levels expressed as median (interquartile range). n = number of subjects; mo, months; N/A, non-applicable.Control (n = 14)Placebo (n = 20)IFN30 (n = 15)IFN60 (n = 15)Serum S100B change over time There was no change over time in the serum S100B levels. The shape of the serum trajectory did not vary between the treatment regimes, i.e. placebo vs. IFN30 vs. IFN60.
Serum S100B change over time
There was no change over time in the serum S100B levels. The shape of the serum trajectory did not vary between the treatment regimes, i.e. placebo vs. IFN30 vs. IFN60.Serum S100B versus Clinical and MRI parameters (Table  2 ) There was no evidence that the 24-month serum S100B values were associated with either changes in the T1 or T2 loads, or ventricular or cord volumes at 24 months, after adjusting for the baseline values of each subject. There was no correlation with disease progression on the EDSS. There was also no evidence that these relationships were modified by treatment assignment (intention-to-treat analysis) (Table  2 ) or the overall average dose, which included the changes to treatment regime (non-intention-to-treat analysis) (Table  2 ). Table 2 Serum S100B versus Clinical and MRI variables. Estimated mean change in 24-month serum S100B associated with unit increase in mean value of T1 and T2 lesion load, ventricular and spinal cord volume, adjusted for baseline values of both serum S100B and of MRI parameters. Baseline adjustment ensures that the coefficient assesses the 'effect' of the 24-month MRI parameters value relative to its baseline. * Test of treatment interactions with row variable. Variable Coefficient P-value 95% Confidence Interval (CI) P-value for treatment modification*: Assignment average dose 24 month T1 load -4 × 10 -6 0.35 -1 × 10 -5 , 4 × 10 -6 0.76 0.59 24 month T2 load -3 × 10 -6 0.16 -7 × 10 -6 , 1 × 10 -6 0.57 0.89 24 month ventricular volume 7 × 10 -7 0.75 -3 × 10 -6 , 5 × 10 -6 0.46 0.24 24 month cord volume -2 × 10 -3 0.54 -9 × 10 -3 , 5 × 10 -3 0.58 0.88
Serum S100B versus Clinical and MRI parameters (Table  2 )
There was no evidence that the 24-month serum S100B values were associated with either changes in the T1 or T2 loads, or ventricular or cord volumes at 24 months, after adjusting for the baseline values of each subject. There was no correlation with disease progression on the EDSS. There was also no evidence that these relationships were modified by treatment assignment (intention-to-treat analysis) (Table  2 ) or the overall average dose, which included the changes to treatment regime (non-intention-to-treat analysis) (Table  2 ).Serum S100B versus Clinical and MRI variables. Estimated mean change in 24-month serum S100B associated with unit increase in mean value of T1 and T2 lesion load, ventricular and spinal cord volume, adjusted for baseline values of both serum S100B and of MRI parameters. Baseline adjustment ensures that the coefficient assesses the 'effect' of the 24-month MRI parameters value relative to its baseline. * Test of treatment interactions with row variable.VariableCoefficientP-value95% Confidence Interval (CI)P-value for treatment modification*: Assignment average doseDiscussion These results suggest that serum S100B levels in patients with PPMS were not affected by intramuscular IFNβ-1a and that there was no observable change in S100B over time. Furthermore, we did not observe any correlation between S100B levels and clinical disability or between S100B and quantitative MRI measures. This study therefore suggests Although there is evidence that S100B elevation in MS is related to inflammatory activity [ 10 , 11 , 13 ], this study has shown that S100B was not sensitive to disease progression in PPMS. This supports the view that PPMS is less inflammatory than other forms of MS and that serum S100B would be ineffective as a surrogate marker of disease progression in this subgroup. It would be valuable to identify surrogate markers of clinical progression in PPMS to aid the development of effective therapeutic intervention, since clinical trials with a disability endpoint are very large and resource consuming. It is possible that such markers would need to be less related to acute inflammation and more dependant on other neuropathology such as axonal loss and regeneneration.
Discussion
These results suggest that serum S100B levels in patients with PPMS were not affected by intramuscular IFNβ-1a and that there was no observable change in S100B over time. Furthermore, we did not observe any correlation between S100B levels and clinical disability or between S100B and quantitative MRI measures.This study therefore suggests Although there is evidence that S100B elevation in MS is related to inflammatory activity [ 10 , 11 , 13 ], this study has shown that S100B was not sensitive to disease progression in PPMS. This supports the view that PPMS is less inflammatory than other forms of MS and that serum S100B would be ineffective as a surrogate marker of disease progression in this subgroup.It would be valuable to identify surrogate markers of clinical progression in PPMS to aid the development of effective therapeutic intervention, since clinical trials with a disability endpoint are very large and resource consuming. It is possible that such markers would need to be less related to acute inflammation and more dependant on other neuropathology such as axonal loss and regeneneration.


Background The colour of animals' skin, fur, feathers or cuticula has been estimated in a large number of studies. The methods used to do so are diverse, with some being costly and not available to all researchers. In a study to measure plumage colour in a bird species, a new method of creating a colour chart was developed. While colour-charts have their own limitations, these can be minimised when they have the following properties: 1) being readily available to the majority of biologists, 2) containing a large array of colours to allow accurate recording and differentiation of subtle colour differences, 3) low cost, 4) adhering to a world-wide standard, and 5) being available in both hard-copy and digital formats to allow for various analytical methods. The method described below satisfies all of these requirements.
Background
The colour of animals' skin, fur, feathers or cuticula has been estimated in a large number of studies. The methods used to do so are diverse, with some being costly and not available to all researchers. In a study to measure plumage colour in a bird species, a new method of creating a colour chart was developed. While colour-charts have their own limitations, these can be minimised when they have the following properties: 1) being readily available to the majority of biologists, 2) containing a large array of colours to allow accurate recording and differentiation of subtle colour differences, 3) low cost, 4) adhering to a world-wide standard, and 5) being available in both hard-copy and digital formats to allow for various analytical methods. The method described below satisfies all of these requirements.Results Colour charts estimated to fit the range of the species' plumage colours were created on the computer screen using web software that allowed for HTML-coding (in this case Dreamweaver™). The charts were adjusted using feathers from dead specimens until a satisfying range of darker and lighter colours were found. The resulting chart was printed out and was successfully used in the field to determine the plumage colour of hand-held birds.
Results
Colour charts estimated to fit the range of the species' plumage colours were created on the computer screen using web software that allowed for HTML-coding (in this case Dreamweaver™). The charts were adjusted using feathers from dead specimens until a satisfying range of darker and lighter colours were found. The resulting chart was printed out and was successfully used in the field to determine the plumage colour of hand-held birds.Conclusion Access to a computer and printer, and the software to enable the creation of a chart, is within the reach of the vast majority of biologists. The numbers of colours that can be generated should suit most studies, with the advantage of the method being that the chart can be individually tailored to the species under study. HTML colour coding is a worldwide standard, thus the colours used in studies can be described in the methods section of journal articles using the six-digit alphanumeric code. We believe this method is very useful as a low-tech method for future estimation of individual colour.
Conclusion
Access to a computer and printer, and the software to enable the creation of a chart, is within the reach of the vast majority of biologists. The numbers of colours that can be generated should suit most studies, with the advantage of the method being that the chart can be individually tailored to the species under study. HTML colour coding is a worldwide standard, thus the colours used in studies can be described in the methods section of journal articles using the six-digit alphanumeric code. We believe this method is very useful as a low-tech method for future estimation of individual colour.

Background Animal studies from diverse fields – such as morphology, physiology, behaviour, population dynamics, genetics, ageing and sexing – often require the estimation or classification of colour in skin, fur, feathers or cuticula. To make meaningful comparisons within and between studies, and effectively communicate these findings, a standardised method of assigning a colouration is required. Colour can be categorised, scored and ranked without recourse of any aid other than the observer's eye, as has been successfully demonstrated in many studies [ 1 - 4 ]. Aids to indexing and labelling colours have traditionally compared animals to published colour-standard cards, charts or books. These were often generated for other purposes, such as paint making or characterising soil types [ 5 - 8 ]. Such charts have been employed since the early 1800's, with Charles Darwin using Werner's colour charts [ 9 ] on the  Beagle  expedition [ 10 ]. Newer electronic measuring tools, using a reflectance spectrophotometer to give a high precision estimate of hue, saturation and brightness of the colour [ 11 - 14 ], have been recommended as a reliable and objective way of acquiring detailed data on different aspects of colour [ 15 ]. Lately, photo-processing software (e.g. Adobe Photoshop ®  – Adobe Systems Inc., San Jose, CA, USA) has been used in estimating colour brightness, saturation and hue from digitised photos [ 11 , 16 ]. The benefit of using highly technical methods is the ability to gain very detailed and precise information on different aspects of colour that may be impossible to detect using the human eye. However, in many studies such a high level of precision is not required, and the equipment may be impractical in the field or beyond the budget of the research group. Thus despite the option of high-tech measurement methods, visual comparisons to standardised colour charts are still practical and valuable for many field biologists. While colour-charts have their own limitations, these are minimised when they have the following properties: 1) availability to the majority of biologists, 2) large array of colours to allow accurate recording and differentiation of subtle colour differences, 3) low cost, 4) adherence to a world-wide standard, and 5) availability in both hard-copy and digital formats to allow for various analytical methods. Below we describe a method that satisfies all of these requirements.
Background
Animal studies from diverse fields – such as morphology, physiology, behaviour, population dynamics, genetics, ageing and sexing – often require the estimation or classification of colour in skin, fur, feathers or cuticula. To make meaningful comparisons within and between studies, and effectively communicate these findings, a standardised method of assigning a colouration is required. Colour can be categorised, scored and ranked without recourse of any aid other than the observer's eye, as has been successfully demonstrated in many studies [ 1 - 4 ]. Aids to indexing and labelling colours have traditionally compared animals to published colour-standard cards, charts or books. These were often generated for other purposes, such as paint making or characterising soil types [ 5 - 8 ]. Such charts have been employed since the early 1800's, with Charles Darwin using Werner's colour charts [ 9 ] on the  Beagle  expedition [ 10 ]. Newer electronic measuring tools, using a reflectance spectrophotometer to give a high precision estimate of hue, saturation and brightness of the colour [ 11 - 14 ], have been recommended as a reliable and objective way of acquiring detailed data on different aspects of colour [ 15 ]. Lately, photo-processing software (e.g. Adobe Photoshop ®  – Adobe Systems Inc., San Jose, CA, USA) has been used in estimating colour brightness, saturation and hue from digitised photos [ 11 , 16 ].BeagleThe benefit of using highly technical methods is the ability to gain very detailed and precise information on different aspects of colour that may be impossible to detect using the human eye. However, in many studies such a high level of precision is not required, and the equipment may be impractical in the field or beyond the budget of the research group. Thus despite the option of high-tech measurement methods, visual comparisons to standardised colour charts are still practical and valuable for many field biologists. While colour-charts have their own limitations, these are minimised when they have the following properties: 1) availability to the majority of biologists, 2) large array of colours to allow accurate recording and differentiation of subtle colour differences, 3) low cost, 4) adherence to a world-wide standard, and 5) availability in both hard-copy and digital formats to allow for various analytical methods. Below we describe a method that satisfies all of these requirements.Results and Discussion A starting point for development of this new method was a study on plumage colour in an endemic New Zealand passerine – North Island robin ( Petroica longipes ) – where there was a need for a reliable, species-specific and cost-efficient method to estimate colour (Fig.  1 ; Å Berggren unpublished data). The birds were to be caught and handled in the field, but could not be moved and no samples from the plumage were to be taken. Hence, it was decided to create a specific colour chart, unique for the colours to be compared in this study, and easy to use under fieldwork conditions. It was decided that a computer-generated colour-chart would ideally suit the purposes of the study. Figure 1 The making of a HTML coded colour chart for estimation of animal colour in the field. First the colours relevant for the study are estimated from samples from the species of interest (in this case the New Zealand robin ( Petroica longipes )) (a). From the sample, a set of colours is coded using HTML coding (b), which has a specific code for every colour. In this case the software Dreamweaver™ was used to create nine different shades ranging from light grey (888888) to black (000000) (c). When the chart is made it is printed out and can be enclosed within a plastic covering for protection. This procedure worked well for colour estimation of the species in focus, with individuals' colours being easy to index under field conditions (d). The light emitted from a computer monitor is composed of a particular combination of red, green, and blue light. The proportion of each of these components in the visual colour spectrum can be expressed as a number unique for each specific colour or hue. These colours are coded for using the HTML (Hypertext Markup Language) computer language. This system of colour coding was developed for the Netscape ®  web-browser (Netscape Communication Corp.) and has since become the industry standard [ 17 ]. Today, colour coding is one of the most important features in web page design when creating informative and graphically appealing sites [ 18 ]. Each HTML colour-code specifies the composite of a colour with a six-digit alphanumeric code where the first two digits represent the amount of red, the middle two the amount of green, and the last two the amount of blue. Each character may be represented in one of 16 ways (0 – 9 and A – F), creating a vast array of potential colours [ 17 ]. The actual number of colours that can be produced for viewing on the screen is limited by the computer, ranging from 256 colours in older computers to 16.7 million in newer models. These colours can be generated in web browser software such as Netscape ® , by using the composer feature, or through web-design programmes (e.g. Dreamweaver™ – Macromedia Inc. or FrontPage ©  – Microsoft Corp.). The colours can be displayed on the computer screen and fine-tuned by adjusting the HTML code. For example, between the colours "0000FF" for blue, "00008B" for dark blue and "00C78C" for turquoise blue, a large number of other blues can be created and viewed. When a suitable set of colours have been decided upon, they can be printed out as they present themselves on the screen and saved for future use. The focus species of the plumage study, the North Island robin, has a brown-grey-black plumage (Fig.  1 ) [ 19 ]. Using HTML coding, a colour chart was developed to match the natural variance in the species' brown to black plumage. To ensure the colour range of the feathers was accurately represented in the chart, feathers from a dead specimen were used and compared to the computer generated colours. From this point, an equal number of brighter and darker colour gradations were created, centring on the colour of the feather specimens. The HTML-coding numbering from 0 to 8 (000000 – 888888) resulted in nine shades from black to light grey (Fig.  1 ). This allowed a progression in equal steps from lighter to darker to be displayed sequentially on a printout. This made it possible to hold the bird next to the chart and move it until a colour match was made (Fig.  1 ). The technique worked well and it was possible to get an accurate colour ranking of the darkness of the plumage for the captured 32 birds (Å Berggren unpublished).
Results and Discussion
A starting point for development of this new method was a study on plumage colour in an endemic New Zealand passerine – North Island robin ( Petroica longipes ) – where there was a need for a reliable, species-specific and cost-efficient method to estimate colour (Fig.  1 ; Å Berggren unpublished data). The birds were to be caught and handled in the field, but could not be moved and no samples from the plumage were to be taken. Hence, it was decided to create a specific colour chart, unique for the colours to be compared in this study, and easy to use under fieldwork conditions. It was decided that a computer-generated colour-chart would ideally suit the purposes of the study.Petroica longipesThe light emitted from a computer monitor is composed of a particular combination of red, green, and blue light. The proportion of each of these components in the visual colour spectrum can be expressed as a number unique for each specific colour or hue. These colours are coded for using the HTML (Hypertext Markup Language) computer language. This system of colour coding was developed for the Netscape ®  web-browser (Netscape Communication Corp.) and has since become the industry standard [ 17 ]. Today, colour coding is one of the most important features in web page design when creating informative and graphically appealing sites [ 18 ]. Each HTML colour-code specifies the composite of a colour with a six-digit alphanumeric code where the first two digits represent the amount of red, the middle two the amount of green, and the last two the amount of blue. Each character may be represented in one of 16 ways (0 – 9 and A – F), creating a vast array of potential colours [ 17 ]. The actual number of colours that can be produced for viewing on the screen is limited by the computer, ranging from 256 colours in older computers to 16.7 million in newer models. These colours can be generated in web browser software such as Netscape ® , by using the composer feature, or through web-design programmes (e.g. Dreamweaver™ – Macromedia Inc. or FrontPage ©  – Microsoft Corp.). The colours can be displayed on the computer screen and fine-tuned by adjusting the HTML code. For example, between the colours "0000FF" for blue, "00008B" for dark blue and "00C78C" for turquoise blue, a large number of other blues can be created and viewed. When a suitable set of colours have been decided upon, they can be printed out as they present themselves on the screen and saved for future use.The focus species of the plumage study, the North Island robin, has a brown-grey-black plumage (Fig.  1 ) [ 19 ]. Using HTML coding, a colour chart was developed to match the natural variance in the species' brown to black plumage. To ensure the colour range of the feathers was accurately represented in the chart, feathers from a dead specimen were used and compared to the computer generated colours. From this point, an equal number of brighter and darker colour gradations were created, centring on the colour of the feather specimens. The HTML-coding numbering from 0 to 8 (000000 – 888888) resulted in nine shades from black to light grey (Fig.  1 ). This allowed a progression in equal steps from lighter to darker to be displayed sequentially on a printout. This made it possible to hold the bird next to the chart and move it until a colour match was made (Fig.  1 ). The technique worked well and it was possible to get an accurate colour ranking of the darkness of the plumage for the captured 32 birds (Å Berggren unpublished).Conclusions The method of colour-chart creation utilising HTML code satisfies the criteria listed above. Access to a computer and printer, and the software to enable the creation of a chart, is within the reach of the vast majority of biologists. The numbers of colours (and patterns) that can be generated should suit most studies, with the advantage of the method being that the chart can be individually tailored to the species under study. HTML colour coding is a worldwide standard, thus the colours used in studies can be described in the methods section of journal articles using the six-digit hexadecimal code. Comparisons are not limited to a printout of a colour chart, digital images can also be compared and their colours scored using this method. Drawbacks may include identifying the right colours for the chart to accurately match the animals as encountered in the field, a problem equivalent to other printed colour charts. It is also possible that when printing, the printed colours differ from the colour range as displayed on the computer screen. With some people still using older computers, which are not able to display colours coded in newer machines, there is a risk that there is a discrepancy between computers in the colour presented on the screen. This may be a problem when the aim is to compare specific colours between different studies, but not an issue within studies. Fortunately, this problem will decrease with more computer system being able to display the full range of 16.7 million colours. When using the colour-charts in the field, the usual care of indexing individuals under the same lighting conditions should be taken [ 15 ]. As the technique is easy to refine and adjust to the requirements needed for the species, we believe it is very useful as a low-tech method for future estimation of individual colour. We encourage other researchers and field workers to try the method in future colour studies.
Conclusions
The method of colour-chart creation utilising HTML code satisfies the criteria listed above. Access to a computer and printer, and the software to enable the creation of a chart, is within the reach of the vast majority of biologists. The numbers of colours (and patterns) that can be generated should suit most studies, with the advantage of the method being that the chart can be individually tailored to the species under study. HTML colour coding is a worldwide standard, thus the colours used in studies can be described in the methods section of journal articles using the six-digit hexadecimal code. Comparisons are not limited to a printout of a colour chart, digital images can also be compared and their colours scored using this method. Drawbacks may include identifying the right colours for the chart to accurately match the animals as encountered in the field, a problem equivalent to other printed colour charts. It is also possible that when printing, the printed colours differ from the colour range as displayed on the computer screen. With some people still using older computers, which are not able to display colours coded in newer machines, there is a risk that there is a discrepancy between computers in the colour presented on the screen. This may be a problem when the aim is to compare specific colours between different studies, but not an issue within studies. Fortunately, this problem will decrease with more computer system being able to display the full range of 16.7 million colours. When using the colour-charts in the field, the usual care of indexing individuals under the same lighting conditions should be taken [ 15 ]. As the technique is easy to refine and adjust to the requirements needed for the species, we believe it is very useful as a low-tech method for future estimation of individual colour. We encourage other researchers and field workers to try the method in future colour studies.Authors' contributions JM came up with the initial idea of using web designer tools for creating colour charts. ÅB developed the colour charts using HTML coding and used them in the field as a research tool. ÅB and JM wrote the manuscript, with ÅB doing the major part. All authors read and approved the manuscript.
Authors' contributions
JM came up with the initial idea of using web designer tools for creating colour charts. ÅB developed the colour charts using HTML coding and used them in the field as a research tool. ÅB and JM wrote the manuscript, with ÅB doing the major part. All authors read and approved the manuscript.


Background Obesity is the most common health problem in developed countries. Recently, several physicians' organizations have issued recommendations for treating obesity to family physicians, including instructions in nutrition, physical activity and medications. The aim of this study was to examine if effective weight-reducing treatment can be given by a family physician. It compares regular treatment with intensive treatment that include close follow-up and orlistat treatment.
Background
Obesity is the most common health problem in developed countries. Recently, several physicians' organizations have issued recommendations for treating obesity to family physicians, including instructions in nutrition, physical activity and medications. The aim of this study was to examine if effective weight-reducing treatment can be given by a family physician. It compares regular treatment with intensive treatment that include close follow-up and orlistat treatment.Methods The study was conducted in three primary care clinics. 225 patients were divided into three groups according to their choice. Group A received a personal diet with fortnightly meetings with the family physician and dietitian and orlistat treatment. Group B received a general diet, monthly meetings with the family physician only and orlistat treatment. Group C received a personal diet, monthly meetings with the dietitian only and no drug treatment. The primary endpoint was reduction of at least 5% of the initial weight during the study period.
Methods
The study was conducted in three primary care clinics. 225 patients were divided into three groups according to their choice. Group A received a personal diet with fortnightly meetings with the family physician and dietitian and orlistat treatment. Group B received a general diet, monthly meetings with the family physician only and orlistat treatment. Group C received a personal diet, monthly meetings with the dietitian only and no drug treatment. The primary endpoint was reduction of at least 5% of the initial weight during the study period.Results A greater percentage of patients in group A achieved their weight reduction goals than in other groups (51%, 13% and 9% in groups A, B and C, respectively, p < 0.001). There was a significant reduction in triglycerides in all groups, a significant reduction of low density lipids (LDL) in groups A and B and no significant difference in high density lipids (HDL) in any group.
Results
A greater percentage of patients in group A achieved their weight reduction goals than in other groups (51%, 13% and 9% in groups A, B and C, respectively, p < 0.001). There was a significant reduction in triglycerides in all groups, a significant reduction of low density lipids (LDL) in groups A and B and no significant difference in high density lipids (HDL) in any group.Conclusions Significant weight reduction was obtained in a family physician setting. Further research is needed to evaluate if, by providing the family physician with the proper tools, similar success can be achieved in more clinics.
Conclusions
Significant weight reduction was obtained in a family physician setting. Further research is needed to evaluate if, by providing the family physician with the proper tools, similar success can be achieved in more clinics.

Background Obesity is the most common health problem in developed countries [ 1 ]. It is a chronic disease and should be treated as such. Its prevalence is increasing worldwide [ 2 ]. In the United States, it is estimated that 64% of the adult population is either overweight or obese with a body mass index (BMI; kg/m 2 ) above 25 [ 3 ]. The rate of obesity is increasing [ 4 ] and has risen by more than 75% in the USA since 1980 [ 5 ]. In 2001, the prevalence of obesity (BMI ≥ 30) was 20.9% vs 19.8% in 2000, an increase of 5.6% [ 6 ]. In Israel, according to a survey of the Nutrition Department of the Ministry of Health, 55% of adult (ages 25–64) women and 59% of adult men have a BMI above 24.9 [ 7 ]. Obesity is associated with increased prevalence of many serious chronic diseases such as diabetes mellitus, hypertension, dyslipidemia, and coronary heart disease [ 8 , 9 ]. It may be responsible for approximately 300,000 deaths in the USA per year [ 10 ]. In the Nurses Health Study, the 14-year mortality rate for women with a BMI greater than 32 was more than double that of women with a BMI of less than 19 [ 11 ]. Obesity now ranks second only to smoking as a cause of preventable death but, soon, obesity may surpass smoking as the leading cause of preventable death in the USA [ 12 ]. In the USA, 19% of deaths from coronary disease and 62% of deaths from diabetes can be attributed to obesity [ 13 ]. The risk of death from all causes increases in moderately and severely overweight men and women of all age groups [ 14 ]. Diet and exercise have limited effectiveness on long-term maintenance of weight loss [ 15 ]. Within five to seven years, 95% of all patients regain the lost weight or more [ 16 ]. Pharmacotherapy in combination with a reduced energy diet improves long-term efficacy [ 17 ]. Loss of 5–10% of their initial body weight substantially improves the health of obese patients and modifies their cardiovascular risk factors [ 8 , 18 ]. Despite growing information on the pathophysiology of obesity and its high prevalence, obesity and obesity-related diseases are still under-diagnosed and untreated by family physicians [ 19 ]. Most family physicians cite lack of time, resources, reimbursement from insurance companies, or knowledge of effective interventions as significant barriers [ 20 ]. The intervention of primary physicians during a ten minute physician/patient encounter and telephone consultation with a community dietitian resulted in a significant decrease in the weight of patients [ 20 ]. Recently, several physicians' organizations have issued recommendations for treating obesity to family physicians, including instructions in nutrition, physical activity and medications. Such recommendations were based on a number of studies that proved the effectiveness of family physician weight-reduction programs, when based on the readiness of patients to make necessary lifestyle changes and use of appropriate techniques to increase the willingness of the patient to make necessary changes [ 21 - 24 ]. The purpose of this study was to examine if more efficient and effective weight-reducing treatment can be given in the family doctor setting. The study compare a non-pharmacological intervention with drug intervention (orlistat) and compare regular management with more intensive family physician based management..
Background
Obesity is the most common health problem in developed countries [ 1 ]. It is a chronic disease and should be treated as such. Its prevalence is increasing worldwide [ 2 ]. In the United States, it is estimated that 64% of the adult population is either overweight or obese with a body mass index (BMI; kg/m 2 ) above 25 [ 3 ]. The rate of obesity is increasing [ 4 ] and has risen by more than 75% in the USA since 1980 [ 5 ]. In 2001, the prevalence of obesity (BMI ≥ 30) was 20.9% vs 19.8% in 2000, an increase of 5.6% [ 6 ]. In Israel, according to a survey of the Nutrition Department of the Ministry of Health, 55% of adult (ages 25–64) women and 59% of adult men have a BMI above 24.9 [ 7 ].Obesity is associated with increased prevalence of many serious chronic diseases such as diabetes mellitus, hypertension, dyslipidemia, and coronary heart disease [ 8 , 9 ]. It may be responsible for approximately 300,000 deaths in the USA per year [ 10 ]. In the Nurses Health Study, the 14-year mortality rate for women with a BMI greater than 32 was more than double that of women with a BMI of less than 19 [ 11 ]. Obesity now ranks second only to smoking as a cause of preventable death but, soon, obesity may surpass smoking as the leading cause of preventable death in the USA [ 12 ]. In the USA, 19% of deaths from coronary disease and 62% of deaths from diabetes can be attributed to obesity [ 13 ]. The risk of death from all causes increases in moderately and severely overweight men and women of all age groups [ 14 ].Diet and exercise have limited effectiveness on long-term maintenance of weight loss [ 15 ]. Within five to seven years, 95% of all patients regain the lost weight or more [ 16 ]. Pharmacotherapy in combination with a reduced energy diet improves long-term efficacy [ 17 ]. Loss of 5–10% of their initial body weight substantially improves the health of obese patients and modifies their cardiovascular risk factors [ 8 , 18 ]. Despite growing information on the pathophysiology of obesity and its high prevalence, obesity and obesity-related diseases are still under-diagnosed and untreated by family physicians [ 19 ]. Most family physicians cite lack of time, resources, reimbursement from insurance companies, or knowledge of effective interventions as significant barriers [ 20 ].The intervention of primary physicians during a ten minute physician/patient encounter and telephone consultation with a community dietitian resulted in a significant decrease in the weight of patients [ 20 ]. Recently, several physicians' organizations have issued recommendations for treating obesity to family physicians, including instructions in nutrition, physical activity and medications. Such recommendations were based on a number of studies that proved the effectiveness of family physician weight-reduction programs, when based on the readiness of patients to make necessary lifestyle changes and use of appropriate techniques to increase the willingness of the patient to make necessary changes [ 21 - 24 ].The purpose of this study was to examine if more efficient and effective weight-reducing treatment can be given in the family doctor setting. The study compare a non-pharmacological intervention with drug intervention (orlistat) and compare regular management with more intensive family physician based management..Methods Study design The study was conducted in three primary care clinics in an urban area in central Israel. The family physicians who took part in this study participated in 80 hours CME course dealing with obesity treatment in Israel. The patients were divided into three groups according to their choice. Patients in groups A and B were treated with orlistat at 120 mg TID. Orlistat (Xenical  ® ) is a lipase inhibitor for obesity management that acts by inhibiting the absorption of dietary fats. The patients in group A received in addition a personal reduced-energy diet and met with a family practitioner and a clinical dietitian once every two weeks. The personal diet was created according to the daily schedule and preferred foods of the individual, emphasizing low-fat foods. The patients received instructions regarding the importance of physical activity and, at each meeting, realistic intermediate goals for achieving two or three small changes in eating habits and physical activity, based on the patient's desires, were determined. The obstacles to change and ways to overcome them were discussed. Support, based on improvements in the patient's health parameters such as an improvement in a blood test, was given. Some of the patients helped with self-criticism, by keeping food and physical activity diaries and by grading their own goal accomplishments. Patients were taught how to resist temptation and reward themselves for success. We also recruited the support and encouragement of the patient's family. At each meeting, the time of the next meeting was determined and it was emphasized that the most important thing for the patients to do was to attend the meetings, even if their goals were not achieved. Group B patients were treated with 120 mg orlistat t.i.d., a general formulated reduced-energy diet and follow-up by the family physician once every four weeks for weighing and prescription renewal. In groups A and B, patients were asked at each meeting if any side effects of orlistat appeared. Patients in group C were given a personal low-calorie diet, designed according to their preferences, and followed-up by a clinical dietitian once a month. The prescribed daily caloric intake was equal in the three groups and was 1200 calories per day for women and 1500 calories per day for men. Before the intervention, every patient received an explanation of the three treatments, the importance of reducing weight, and how excess weight affects their health. All were instructed about the recommended rate of weight loss and a final weight reduction goal of at least 5% of their initial weight within half a year was established. Patients who achieved the 5% reduction goal before the end of the study could choose either to stop the intervention or to complete the study period. Patients Obese (BMI > 30) patients of either sex or patients with a BMI above 27 plus two or more cardiovascular risk factors, aged 20–75 years, were eligible for the study. Patients were excluded if they were pregnant or lactating or if they had any contraindication against using orlistat (chronic malabsorption syndrome, cholestasis, pancreatic disease). Before the intervention, patients underwent an initial screening that included recording of a complete medical history, measurement of vital signs, body weight and height, and calculation of the BMI. Laboratory analysis included a lipid profile. The readiness of the patient to receive treatment was assessed. At the beginning of the intervention, all participants were in the third stage of readiness ("the preparation stage") according to the Transtheoretical Model of Behavior Change. An adverse event of any dose of orlistat was considered serious if it resulted in death, was life-threatening, required hospitalization, or resulted in significant disability. Efficacy measures The main measure was weight loss. Each patient was weighed during each meeting. The primary endpoint was reduction of at least 5% of the initial weight during the study period (six months). Achievement of this goal was defined as successful treatment. Another measure was improvement in the lipid profile. The second lipid profile was done to half of the patients, only those who had dyslipidemia in the first profile had been offered a second profile. Statistical analysis Data on patients' background and weight-reduction results between groups were compared using the Chi square test. Continuous data of the groups, i.e., measurements at the beginning of the study and continuous background data, were compared using one-way tests (ANOVA). When significant statistical differences were found among the three groups, the Tukey Post Hoc test was used to examine the statistical difference between each group of two. ANCOVA was also used and, if there was a difference amongst the groups, the significance (for the measured parameter) was checked using the Bonferonni technique.
Methods
Study design The study was conducted in three primary care clinics in an urban area in central Israel. The family physicians who took part in this study participated in 80 hours CME course dealing with obesity treatment in Israel. The patients were divided into three groups according to their choice. Patients in groups A and B were treated with orlistat at 120 mg TID. Orlistat (Xenical  ® ) is a lipase inhibitor for obesity management that acts by inhibiting the absorption of dietary fats. The patients in group A received in addition a personal reduced-energy diet and met with a family practitioner and a clinical dietitian once every two weeks. The personal diet was created according to the daily schedule and preferred foods of the individual, emphasizing low-fat foods. The patients received instructions regarding the importance of physical activity and, at each meeting, realistic intermediate goals for achieving two or three small changes in eating habits and physical activity, based on the patient's desires, were determined. The obstacles to change and ways to overcome them were discussed. Support, based on improvements in the patient's health parameters such as an improvement in a blood test, was given. Some of the patients helped with self-criticism, by keeping food and physical activity diaries and by grading their own goal accomplishments. Patients were taught how to resist temptation and reward themselves for success. We also recruited the support and encouragement of the patient's family. At each meeting, the time of the next meeting was determined and it was emphasized that the most important thing for the patients to do was to attend the meetings, even if their goals were not achieved. Group B patients were treated with 120 mg orlistat t.i.d., a general formulated reduced-energy diet and follow-up by the family physician once every four weeks for weighing and prescription renewal. In groups A and B, patients were asked at each meeting if any side effects of orlistat appeared. Patients in group C were given a personal low-calorie diet, designed according to their preferences, and followed-up by a clinical dietitian once a month. The prescribed daily caloric intake was equal in the three groups and was 1200 calories per day for women and 1500 calories per day for men. Before the intervention, every patient received an explanation of the three treatments, the importance of reducing weight, and how excess weight affects their health. All were instructed about the recommended rate of weight loss and a final weight reduction goal of at least 5% of their initial weight within half a year was established. Patients who achieved the 5% reduction goal before the end of the study could choose either to stop the intervention or to complete the study period.
Study design
The study was conducted in three primary care clinics in an urban area in central Israel. The family physicians who took part in this study participated in 80 hours CME course dealing with obesity treatment in Israel.The patients were divided into three groups according to their choice. Patients in groups A and B were treated with orlistat at 120 mg TID. Orlistat (Xenical  ® ) is a lipase inhibitor for obesity management that acts by inhibiting the absorption of dietary fats.The patients in group A received in addition a personal reduced-energy diet and met with a family practitioner and a clinical dietitian once every two weeks. The personal diet was created according to the daily schedule and preferred foods of the individual, emphasizing low-fat foods. The patients received instructions regarding the importance of physical activity and, at each meeting, realistic intermediate goals for achieving two or three small changes in eating habits and physical activity, based on the patient's desires, were determined. The obstacles to change and ways to overcome them were discussed. Support, based on improvements in the patient's health parameters such as an improvement in a blood test, was given.Some of the patients helped with self-criticism, by keeping food and physical activity diaries and by grading their own goal accomplishments. Patients were taught how to resist temptation and reward themselves for success. We also recruited the support and encouragement of the patient's family. At each meeting, the time of the next meeting was determined and it was emphasized that the most important thing for the patients to do was to attend the meetings, even if their goals were not achieved.Group B patients were treated with 120 mg orlistat t.i.d., a general formulated reduced-energy diet and follow-up by the family physician once every four weeks for weighing and prescription renewal.In groups A and B, patients were asked at each meeting if any side effects of orlistat appeared.Patients in group C were given a personal low-calorie diet, designed according to their preferences, and followed-up by a clinical dietitian once a month.The prescribed daily caloric intake was equal in the three groups and was 1200 calories per day for women and 1500 calories per day for men.Before the intervention, every patient received an explanation of the three treatments, the importance of reducing weight, and how excess weight affects their health. All were instructed about the recommended rate of weight loss and a final weight reduction goal of at least 5% of their initial weight within half a year was established. Patients who achieved the 5% reduction goal before the end of the study could choose either to stop the intervention or to complete the study period.Patients Obese (BMI > 30) patients of either sex or patients with a BMI above 27 plus two or more cardiovascular risk factors, aged 20–75 years, were eligible for the study. Patients were excluded if they were pregnant or lactating or if they had any contraindication against using orlistat (chronic malabsorption syndrome, cholestasis, pancreatic disease). Before the intervention, patients underwent an initial screening that included recording of a complete medical history, measurement of vital signs, body weight and height, and calculation of the BMI. Laboratory analysis included a lipid profile. The readiness of the patient to receive treatment was assessed. At the beginning of the intervention, all participants were in the third stage of readiness ("the preparation stage") according to the Transtheoretical Model of Behavior Change. An adverse event of any dose of orlistat was considered serious if it resulted in death, was life-threatening, required hospitalization, or resulted in significant disability.
Patients
Obese (BMI > 30) patients of either sex or patients with a BMI above 27 plus two or more cardiovascular risk factors, aged 20–75 years, were eligible for the study. Patients were excluded if they were pregnant or lactating or if they had any contraindication against using orlistat (chronic malabsorption syndrome, cholestasis, pancreatic disease).Before the intervention, patients underwent an initial screening that included recording of a complete medical history, measurement of vital signs, body weight and height, and calculation of the BMI. Laboratory analysis included a lipid profile. The readiness of the patient to receive treatment was assessed. At the beginning of the intervention, all participants were in the third stage of readiness ("the preparation stage") according to the Transtheoretical Model of Behavior Change.An adverse event of any dose of orlistat was considered serious if it resulted in death, was life-threatening, required hospitalization, or resulted in significant disability.Efficacy measures The main measure was weight loss. Each patient was weighed during each meeting. The primary endpoint was reduction of at least 5% of the initial weight during the study period (six months). Achievement of this goal was defined as successful treatment. Another measure was improvement in the lipid profile. The second lipid profile was done to half of the patients, only those who had dyslipidemia in the first profile had been offered a second profile.
Efficacy measures
The main measure was weight loss. Each patient was weighed during each meeting. The primary endpoint was reduction of at least 5% of the initial weight during the study period (six months). Achievement of this goal was defined as successful treatment. Another measure was improvement in the lipid profile.The second lipid profile was done to half of the patients, only those who had dyslipidemia in the first profile had been offered a second profile.Statistical analysis Data on patients' background and weight-reduction results between groups were compared using the Chi square test. Continuous data of the groups, i.e., measurements at the beginning of the study and continuous background data, were compared using one-way tests (ANOVA). When significant statistical differences were found among the three groups, the Tukey Post Hoc test was used to examine the statistical difference between each group of two. ANCOVA was also used and, if there was a difference amongst the groups, the significance (for the measured parameter) was checked using the Bonferonni technique.
Statistical analysis
Data on patients' background and weight-reduction results between groups were compared using the Chi square test. Continuous data of the groups, i.e., measurements at the beginning of the study and continuous background data, were compared using one-way tests (ANOVA). When significant statistical differences were found among the three groups, the Tukey Post Hoc test was used to examine the statistical difference between each group of two. ANCOVA was also used and, if there was a difference amongst the groups, the significance (for the measured parameter) was checked using the Bonferonni technique.Results Two hundred and twenty-five patients participated in the study. Their demographic characteristics, history of cardiovascular disease, and initial lipid profile are shown in Table  1 . There were no significant differences between groups in average age, initial BMI or gender of the participants. The average length of follow-up and the number of meetings varied among groups. There were no cases of significant side effects that required stopping orlistat treatment of any of the participants. Table 1 Participants' demographic data, initial lipids profile, by treatment group Group A Group B Group C P* value Number of patients 62 112 51 Age (years +/- SD) 47.3 ± 11 46.8 ± 12 51 ± 9.6 NS Gender (% female) 71 74 61 NS Ischemic heart disease (%) 0 4 0 NS Hypertension (%) 44 51 27 P < 0.05 Diabetes mellitus (%) 9 18 20 NS Dyslipidemia (%) 16 38 66 P < 0.001 Initial body weight Initial body mass index (BMI; kg/m 2  +/- SD) 33 ± 3.8 34 ± 4.4 31 ± 3.6 P < 0.01 34 > 31(B > C) Initial triglycerides (mg/dl, +/- SD) 170 ± 53 184 ± 49 255 ± 205 P < 0.01 170 <255> 183 (A < B > C) Initial low density lipoproteins (LDL; mg/dl, +/- SD) 150 ± 30 156 ± 36 152 ± 44 NS Initial high density lipoproteins (HDL; mg/dl, +/- SD) 42 ± 7.0 44 ± 6.7 47 ± 14.9 NS Average length of treatment (weeks, +/- SD) 13 ± 12.0 9 ± 4.7 23 ± 12 P < 0.001 23 > 13 > 9 (C > A > B) Number of meetings with physician/dietitian (+/- SD) 4.3 ± 2.0 3.5 ± 1.5 5.2 ± 2.9 P < 0.001 5.2 > 3.5 (C > B) NS = Not significant. Group A – Orlistat, a personal reduced-energy diet and a meeting with a family practitioner and a clinical dietitian once every two weeks. Group B – Orlistat, a general formulated reduced-energy diet and follow-up by the family physician once every four weeks. Group C – a personal low-calorie diet and follow-up by a clinical dietitian once a month. * When significant statistical differences were found among the three groups, we examined the statistical difference between each group of two. Patient-reported adverse events in the orlistat-treated groups were all related to the gastrointestinal tract. The most commonly reported events were flatulence with discharge (9.2%), fatty or oily stool with increased defecation (9.2%), feeling of fullness in the stomach (4.6%), and constipation (1.7%). There were no statistically significant differences in side effects between groups A and B. In group A, 11 patients (17.7%) stopped the treatment for the following reasons: cost of the medication (47%), lack of time (33%), or dissatisfaction (20%). In comparison, ten patients (8.9%) in group B stopped the treatment, mainly because of the cost of the treatment (65%) or low motivation (23.5%). The reasons for stopping treatment significantly differed between groups A and B ( p  = 0.03). The percentage of patients who attained their weight reduction goals was largest in group A where patients received orlistat and intense follow-up, in addition to a personally-designed diet (Fig.  1 ). Changes in lipid profiles are shown in Table  2 . The treatment resulted in a significant reduction in triglyceride levels in all groups, a significant reduction of low density lipoproteins (LDL) in groups A and B and no significant difference between initial and final high density lipoproteins (HDL) in any group. Figure 1 Weight loss by treatment group* Table 2 Changes in lipid profile during treatment according to treatment group 1 (paired sample  t  test) Group A Group B Group C Number of patients 2 32 55 28 Initial triglycerides (mg/dl, +/- SD) 170 ± 53 184 ± 49 255 ± 205 Final triglycerides (mg/dl, +/- SD) 139 ± 43 153 ± 35 165 ± 60 Delta (+/- SD) -31 ± 21 -31 ± 25 -90 ± 187 P value (pre-post) <0.001 <0.001 0.01 Initial low density lipids (LDL; mg/dl, +/- SD) 150 ± 30 156 ± 36 152 ± 44 Final LDL (mg/dl, +/- SD) 129 ± 28 143 ± 32 147 ± 34 Delta -21 ± 26 -12 ± 16 -5 ± 34 P value (pre-post) <0.001 <0.001 NS Initial high density lipids (HDL; mg/dl, +/- SD) 42 ± 7.0 44 ± 6.7 47 ± 14.9 Final HDL (mg/dl, +/- SD) 43 ± 6.6 45 ± 6.7 48 ± 15.3 Delta (+/- SD) 0.9 ± 2.9 0.8 ± 3.3 1.4 ± 8.8 P value (pre-post) NS NS NS NS = Not significant. 1  See footnotes to Table 1 2  Patients with pre and post lipid profile analyses Patients in Group A reduced 5.12 kg (range of 5–8 Kg.) of their initial body weight, patients in Group B reduced 7.8 kg (range 10–12 Kg.) from their initial body weight and patients in Group C reduced 3.12 kg (range 5–6 Kg.) of their initial body weight.
Results
Two hundred and twenty-five patients participated in the study. Their demographic characteristics, history of cardiovascular disease, and initial lipid profile are shown in Table  1 . There were no significant differences between groups in average age, initial BMI or gender of the participants. The average length of follow-up and the number of meetings varied among groups. There were no cases of significant side effects that required stopping orlistat treatment of any of the participants.Participants' demographic data, initial lipids profile, by treatment groupNS = Not significant.Group A – Orlistat, a personal reduced-energy diet and a meeting with a family practitioner and a clinical dietitian once every two weeks.Group B – Orlistat, a general formulated reduced-energy diet and follow-up by the family physician once every four weeks.Group C – a personal low-calorie diet and follow-up by a clinical dietitian once a month.* When significant statistical differences were found among the three groups, we examined the statistical difference between each group of two.Patient-reported adverse events in the orlistat-treated groups were all related to the gastrointestinal tract. The most commonly reported events were flatulence with discharge (9.2%), fatty or oily stool with increased defecation (9.2%), feeling of fullness in the stomach (4.6%), and constipation (1.7%). There were no statistically significant differences in side effects between groups A and B. In group A, 11 patients (17.7%) stopped the treatment for the following reasons: cost of the medication (47%), lack of time (33%), or dissatisfaction (20%). In comparison, ten patients (8.9%) in group B stopped the treatment, mainly because of the cost of the treatment (65%) or low motivation (23.5%). The reasons for stopping treatment significantly differed between groups A and B ( p  = 0.03).pThe percentage of patients who attained their weight reduction goals was largest in group A where patients received orlistat and intense follow-up, in addition to a personally-designed diet (Fig.  1 ). Changes in lipid profiles are shown in Table  2 . The treatment resulted in a significant reduction in triglyceride levels in all groups, a significant reduction of low density lipoproteins (LDL) in groups A and B and no significant difference between initial and final high density lipoproteins (HDL) in any group.Changes in lipid profile during treatment according to treatment group 1 (paired sample  t  test)tNS = Not significant.1  See footnotes to Table 12  Patients with pre and post lipid profile analysesPatients in Group A reduced 5.12 kg (range of 5–8 Kg.) of their initial body weight, patients in Group B reduced 7.8 kg (range 10–12 Kg.) from their initial body weight and patients in Group C reduced 3.12 kg (range 5–6 Kg.) of their initial body weight.Discussion Obesity is a worldwide problem. Treatment of a patient for obesity involves two processes: evaluation of the severity of the obesity and general health condition of the patient, and management which includes guidance in how to gradually reduce weight and maintain the new weight together with imparting healthy lifestyle habits and keeping track of improvement. In this study, we examined weight-reduction techniques that can be carried out in the setting of a community family practice. Intense treatment, combining frequent counseling by the family physician and a dietitian with medications (group A), resulted in the best weight reduction and lipid profile improvement in the short period of this study, as was reported earlier in special weight reduction clinics [ 25 - 27 ] The effectiveness of interventions in primary care setting are controversial [ 28 - 30 ]. Beermann et al [ 28 ] in a community survey of 792 patients found that Orlistat was not prescribed according to the approved indication in the majority of cases. The dropout rate was high and most patients had minor gain from the treatment. Linne et al [ 29 ] noted that success rate of Orlistat in primary-care practice is limited by failure to follow prescribing recommendations. A simple questionnaire to 70 patients revealed that in many cases the referral physician had not observed basic rules and regulations, nor given appropriate information on Orlistat use. Hauptman et al [ 30 ] in a study conducted in seventeen primary care centers in the United States. The study indicates that orlistat is an effective adjunct to dietary intervention in the treatment of obesity in primary care settings. There are many advantages to a program involving cooperation between the family physician and the dietitian. The family physician is acquainted with the patient for a longer time than a dietitian. The physician is familiar with the patient's health condition, medications taken by the patient, the patient's environment and lifestyle and can recommend a treatment suitable to the patient's personality and lifestyle. The family physician is knowledgeable about weight-reducing drugs and possible side effects. The patient trusts and has confidence in the family doctor. Together with the dietitian, a personal diet appropriate to the drug treatment can be created. Obesity is a chronic disease. The physician and the patient must recognize that obesity treatment is a prolonged process that extends a lifetime. Since family physicians are usually familiar with their patients as well as with the patient's family and environment for many years, family physicians know what changes the patient can achieve. They can recruit family members to support the necessary lifestyle changes. Also, because of their training, family physicians are the most suitable professional to holistically treat obesity and its complications. There were several limitations in our study. One limitation was the non-random division of patients into groups A, B and C. It is possible that the patients who chose drug treatment differed from those who chose a diet only. Perhaps they were more ready for the weight-reduction process and to expend money for the drug (in Israel, there is a patient co-payment for medications). The rate of women amongst the patients seeking treatment was higher than the rate of men, as in other reports [ 26 , 27 ]. Hence, we assume that our study represented the segment of the population more prone to try dieting and weight-reduction programs. Ways to increase the number of men participating in weight-reduction programs must be found. The study periods for groups A and B (which received orlistat) were shorter than for group C, partly because there is significant co-payment for orlistat and partly because the targeted weight had been achieved earlier. The drug was well tolerated with minimal gastrointestinal side effects. The patients were treated by family physicians that were orientated toward and trained in weight reduction. Results might have been less successful with other physicians. Hence, family physicians should be trained in the subject by increasing both their knowledge and their treatment skills. Healthcare funds must recognize the importance of weight reduction so that they will allocate the necessary additional time and resources of their physicians, clinics and multi-field staff. This study evaluated only the weight reduction period. Long-term results and whether or not the patient maintained the lifestyle change for a long period were not examined. Further studies should examine the best program for maintaining the new weight. In conclusion, this study showed that within the setting of the family practice it is possible to carry out an effective program of weight reduction and achieve significant weight loss. The addition of orlistat can further improve results. We believe that by providing family physicians with the proper tools, similar success can be achieved in many more clinics.
Discussion
Obesity is a worldwide problem. Treatment of a patient for obesity involves two processes: evaluation of the severity of the obesity and general health condition of the patient, and management which includes guidance in how to gradually reduce weight and maintain the new weight together with imparting healthy lifestyle habits and keeping track of improvement.In this study, we examined weight-reduction techniques that can be carried out in the setting of a community family practice. Intense treatment, combining frequent counseling by the family physician and a dietitian with medications (group A), resulted in the best weight reduction and lipid profile improvement in the short period of this study, as was reported earlier in special weight reduction clinics [ 25 - 27 ]The effectiveness of interventions in primary care setting are controversial [ 28 - 30 ]. Beermann et al [ 28 ] in a community survey of 792 patients found that Orlistat was not prescribed according to the approved indication in the majority of cases. The dropout rate was high and most patients had minor gain from the treatment. Linne et al [ 29 ] noted that success rate of Orlistat in primary-care practice is limited by failure to follow prescribing recommendations. A simple questionnaire to 70 patients revealed that in many cases the referral physician had not observed basic rules and regulations, nor given appropriate information on Orlistat use.Hauptman et al [ 30 ] in a study conducted in seventeen primary care centers in the United States. The study indicates that orlistat is an effective adjunct to dietary intervention in the treatment of obesity in primary care settings.There are many advantages to a program involving cooperation between the family physician and the dietitian. The family physician is acquainted with the patient for a longer time than a dietitian. The physician is familiar with the patient's health condition, medications taken by the patient, the patient's environment and lifestyle and can recommend a treatment suitable to the patient's personality and lifestyle. The family physician is knowledgeable about weight-reducing drugs and possible side effects. The patient trusts and has confidence in the family doctor. Together with the dietitian, a personal diet appropriate to the drug treatment can be created.Obesity is a chronic disease. The physician and the patient must recognize that obesity treatment is a prolonged process that extends a lifetime. Since family physicians are usually familiar with their patients as well as with the patient's family and environment for many years, family physicians know what changes the patient can achieve. They can recruit family members to support the necessary lifestyle changes. Also, because of their training, family physicians are the most suitable professional to holistically treat obesity and its complications.There were several limitations in our study. One limitation was the non-random division of patients into groups A, B and C. It is possible that the patients who chose drug treatment differed from those who chose a diet only. Perhaps they were more ready for the weight-reduction process and to expend money for the drug (in Israel, there is a patient co-payment for medications). The rate of women amongst the patients seeking treatment was higher than the rate of men, as in other reports [ 26 , 27 ]. Hence, we assume that our study represented the segment of the population more prone to try dieting and weight-reduction programs. Ways to increase the number of men participating in weight-reduction programs must be found.The study periods for groups A and B (which received orlistat) were shorter than for group C, partly because there is significant co-payment for orlistat and partly because the targeted weight had been achieved earlier. The drug was well tolerated with minimal gastrointestinal side effects.The patients were treated by family physicians that were orientated toward and trained in weight reduction. Results might have been less successful with other physicians. Hence, family physicians should be trained in the subject by increasing both their knowledge and their treatment skills. Healthcare funds must recognize the importance of weight reduction so that they will allocate the necessary additional time and resources of their physicians, clinics and multi-field staff.This study evaluated only the weight reduction period. Long-term results and whether or not the patient maintained the lifestyle change for a long period were not examined. Further studies should examine the best program for maintaining the new weight.In conclusion, this study showed that within the setting of the family practice it is possible to carry out an effective program of weight reduction and achieve significant weight loss. The addition of orlistat can further improve results. We believe that by providing family physicians with the proper tools, similar success can be achieved in many more clinics.Competing interests The author(s) declare that they have no competing interests.
Competing interests
The author(s) declare that they have no competing interests.Authors' contributions AF and SP conceived and designed the study, participated in the collection, analysis and interpretation of data and drafted the manuscript. SV Participated in the statistical analysis, interpretation of data and draft of the manuscript. MS and EF participated in the design of the study, data collection and interpretetion. All authors read and approved the final manuscript.
Authors' contributions
AF and SP conceived and designed the study, participated in the collection, analysis and interpretation of data and drafted the manuscript. SV Participated in the statistical analysis, interpretation of data and draft of the manuscript. MS and EF participated in the design of the study, data collection and interpretetion. All authors read and approved the final manuscript.Pre-publication history The pre-publication history for this paper can be accessed here:
Pre-publication history
The pre-publication history for this paper can be accessed here: