Prolonged exposure to movement perturbations leads to creation of motor memories which decay towards previous states when the perturbations are removed. However, it remains unclear whether this decay is due only to a spontaneous and passive recovery of the previous state. It has recently been reported that activation of reinforcement-based learning mechanisms delays the onset of the decay. This raises the question whether other motor learning mechanisms may also contribute to the retention and/or decay of the motor memory. Therefore, we aimed to test whether mechanisms of error-based motor adaptation are active during the decay of the motor memory. Forty-five right-handed participants performed point-to-point reaching movements under an external dynamic perturbation. We measured the expression of the motor memory through error-clamped (EC) trials, in which lateral forces constrained movements to a straight line towards the target. We found greater and faster decay of the motor memory for participants who had access to full online visual feedback during these EC trials (Cursor group), when compared with participants who had no EC feedback regarding movement trajectory (Arc group). Importantly, we did not find between-group differences in adaptation to the external perturbation. In addition, we found greater decay of the motor memory when we artificially increased feedback errors through the manipulation of visual feedback (Augmented-Error group). Our results then support the notion of an active decay of the motor memory, suggesting that adaptive mechanisms are involved in correcting for the mismatch between predicted movement trajectories and actual sensory feedback, which leads to greater and faster decay of the motor memory. Mechanisms underlying human motor learning have been extensively studied by applying external visuomotor or dynamic perturbations during performance of reaching movements  available during EC trials, contributes to the decay of the motor memory. This study evaluated whether the decay of the motor memory can be experimentally modified by manipulating online visual feedback during EC trials. We tested three groups of participants in a force-field (FF) adaptation paradigm. We measured the motor memory following adaptation using EC trials, in which there is no positional deviation of the hand, and compared the rate of decay between participants with online visual feedback of movement distance only vs. a veridical cursor, which showed the movement constrained to a straight line towards the target. We also tested a group of participants who were shown an augmented visual feedback error-signal .We recruited 45 self-reported right-handed participants, who were randomly allocated to one of three experimental groups. We first recruited 30 participants, who were allocated to the Arc  and Cursor  groups, whereas a final group of 15 participants were allocated to the Augmented-Error group . All participants were naive to the experimental paradigm, and the purpose of the experiment. All participants gave written informed consent in accordance with the Declaration of Helsinki, and the study was approved by the ethics committee of the University of Birmingham.Participants were comfortably seated in front of a display system. They were asked to perform point-to-point reaching movements in the sagittal plane (distance 15 cm) with a 2-D robotic manipulandum  under non-perturbed conditions . After the familiarization period, participants performed 617 trials in total, which were divided into 22 blocks . A scheme of the experimental design is represented in Figure x FyF]T equal to b was defined as 15 N/(m/s), thus determining a clockwise curl field. During EC trials the robotic device constrained motion to a straight line towards the target by generating reactive forces  as the time from movement onset to trial end. Trials were considered started when the cursor left the start position . Trials were considered finished when the cursor reached the target . We then defined peak velocity, and calculated movement error as the angle  between two vectors linking the position at movement onset with the target, and the position of peak velocity, respectively. For EC trials and IEC trials we measured the force participants exerted against the virtual wall at peak velocity, and normalized this force value based on peak velocity (Force at Peak Velocity).We tested for between-group differences at Baseline by performing separate univariate analysis of variance (Univariate ANOVA) for the Directional Error, Movement Time and Force at Peak Velocity collected at Baseline (N1)—when participant had not yet experienced perturbations.In order to test for participants’ adaptation to the external dynamic perturbation along time, we performed an analysis of variance for repeated measures (ANOVA-RM) for the average within-block Directional Error, using a mixed model with Block (FF1–FF10) as a within-subject factor, and Group  as a between-subject factor. We further explored for motor adaptation by performing an ANOVA-RM for the average within block value of the Force at Peak Velocity on IEC trials interspersed among FF trials. We used Block (FF1–FF10) as within-subject factor, and Group  as between-subject factor. We further control for the potential interference of peak velocity on our analysis of directional error by performing an analysis of covariance (ANCOVA), with Directional Error as dependent variable, and Peak Velocity as covariate.To test for differences in the expression of motor memory, we performed an ANOVA-RM for the average within-block Force at Peak Velocity, with Block (EC1–EC9) as within-subject factor, and Group  as between-subject factor. In order to evaluate whether manipulation of visual feedback in blocks of EC trials resulted in significant between-group differences for peak velocity, we performed a Univariate-ANOVA with Group  as between-subject factor.When significant between-group differences were found —either for motor adaptation or for the expression of the motor memory—we followed the analysis by calculating the average value for bins of six consecutive trials from the same experimental block. We then performed two separate ANOVA-RM, for the initial and final within block performance, respectively. This allowed us to test whether average between-group differences were driven by performance differences already evident at block onset, or alternatively by differences emerging at block end.Reinforcement learning has been suggested as key mechanism for protection of motor memories , with Bin (1–5) as within-subject factor and Group  as between-subject factor. To evaluate whether participants recall previous states when re-exposed to EC trials, we performed an ANOVA-RM for the average Force at Peak Velocity at the end of blocks EC9–EC10, with Block as within-subject factor and Group  as between-subject factor.post hoc comparisons were performed with Bonferroni corrections when a significant result was found. Greenhouse-Geisser corrections were performed when data violated the assumption of sphericity . A p-value ≤ 0.05 was considered significant for all tests. We performed the statistical analysis with the Statistical Package for the Social Sciences .For all ANOVA-RM, b*x + cy = a*e to the data within each EC block. Because fitting curves to individual participants’ data can be unstable, we performed a sub-sampling bootstrap analysis  and the curve asymptote parameter c were then calculated for each possible pair-wise group comparison. Furthermore, we performed a permutation test on each of the 455 bootstrap iterations, for each of the three pair-wise analyses. We randomly assigned each of the 24 participants selected for each iteration to one of two experimental groups . We then fit the average trial-by-trial data for each new group with a single exponential model, and calculated the difference between groups for the three parameters. We then calculated the proportion of permutation samples larger than the mean difference found for the bootstrap procedure, as a measure of how likely it would be to find our results in a population where the two analyzed groups did not differ.We estimated the rate of decay of the motor memory by fitting a single exponential model of the form F = 1.33; p = 0.27), or Force at Peak Velocity  = 0.39; p = 0.68). We found significant between-group differences for Movement Time  = 35.41; p < 0.001), and post hoc comparisons revealed that participants from the Augmented-Error group performed the reaching task significantly slower at baseline than participants from both the Cursor and Arc groups , we performed three separate Univariate ANOVAs for the Directional Error, Movement Time and Force at Peak Velocity, respectively. We did not find significant between-group differences for Directional Error  = 7.91; p < 0.001; Figure F = 0.55; p = 0.58), or a significant Block × Group interaction  = 0.94; p = 0.46).Trial-by-trial average directional error shown by participants at N and FF blocks is presented in Figure F = 7.69; p < 0.001). However, we did not find significant effect for Group  = 0.47; p = 0.63), or significant Block × Group interaction  = 0.79; p = 0.60). An ANOVA-RM for the performance showed by participants at the end of FF blocks revealed a significant effect for Block  = 4.95; p < 0.001). We did not find significant effect for Group  = 1.14; p = 0.33), or significant Block × Group interaction  = 0.96; p = 0.48). Thus participants showed significant adaptation to the perturbation forces, but in all measures the FF performance of the three groups was similar.We further analyzed motor adaptation by calculating the average value for the initial and final performance shown at each FF block . An ANOVA-RM for the initial performance revealed a significant effect for Block  = 2.64; p = 0.006) and Group  = 4.59; p = 0.011) factors. We did not find a significant Block × Group interaction  = 0.31; p = 0.997). Post hoc comparisons revealed a significantly smaller directional error for the Cursor group, compared both with the Arc (p = 0.018) and Augmented-Error (p = 0.03) groups.We also control for the potential influence of peak velocity on our analysis of directional error by performing an ANCOVA, with Directional Error as dependent variable, and Peak Velocity as covariate. We found a significant effect of Block  = 20.29; p < 0.001; Figure F = 1.91; p = 0.16), or a significant Block × Group interaction  = 0.81; p = 0.59). Thus, all three groups equally adapted their movements on the time dimension when the perturbation was introduced, although they were not fully successful in complying with the time constraints.Since feedback about performance success was determined by movement time , subjects had to adjust to changes in movement time resulting from introduction of the dynamic perturbation. Thus, we performed an ANOVA-RM for movement duration, with Block (FF1–FF10) as within-subject factor, and Group  as between-subject factor. Results showed a significant effect for Block  = 23.04; p < 0.001). However, we did not find significant effect for Group  = 1.16; p = 0.32), or significant Block × Group interaction  = 0.94; p = 0.47). An ANOVA-RM for the performance showed by participants at the end of FF blocks revealed a significant effect for Block  = 3.42; p = 0.002), and a significant Block × Group interaction  = 1.76; p = 0.044). We did not find significant effect of Group  = 0.52; p = 0.6). Pair-wise post hoc comparisons revealed significant difference when movement time from the Arc group at FF8 was compared with FF1 (p = 0.006) and FF2 (p = 0.031), and when time at FF2 was compared with FF7 (p = 0.049). However, the analysis did not reveal any between-group significant differences along each of the 10 blocks of practice (FF1–FF10).We further analyzed movement duration by calculating the average value for the initial and final performance from each FF block . An ANOVA-RM for the initial performance revealed a significant effect for Block  = 4.2, p = 0.002; Figure F = 1.0, p = 0.38), or a Block × Group interaction  = 1.18, p = 0.31).An ANOVA-RM for the anticipatory lateral force exerted by participants at peak velocity in IEC trials  revealed a significant effect for Block  = 8.55; p < 0.001), and a significant effect for Group  = 10.61; p < 0.001). We did not find significant Block × Group interaction  = 0.87; p = 0.52). Post hoc comparisons revealed significant differences between the Augmented-Error (0.3 ± 0.6 N·s·m−1) and Arc (−3.5 ± 0.6 N·s·m−1) groups (p < 0.001), and a trend for significance was found when we compared the Augmented-Error with the Cursor (−1.6 ± 0.6 N·s·m−1) group (p = 0.073), as well as for the comparison between Cursor and Arc groups (p = 0.085). Thus, these results suggest a differential expression of the motor memory for the Augmented-Error group, with the Augmented-Error group shifting their mean responses to oppose the curvature of the cursor’s trajectory  revealed significant effect for Block  = 6.56; p = < 0.001; Figure F = 3.25; p = 0.049) factors. We did not find significant Block × Group interaction  = 0.85; p = 0.56). Post hoc comparisons revealed significant differences between Augmented-Error (−2.02 ± 0.7 N·s·m−1) and Arc (−4.66 ± 0.7 N·s·m−1) groups (p = 0.044). An ANOVA-RM for the performance showed by participants at the end of the EC blocks revealed both a significant effect for Block  = 6.46; p < 0.001) and Group  = 18.54; p < 0.001; Figure F = 0.57; p = 0.83). Post hoc comparisons revealed that participants from the Augmented-Error (1.49 ± 0.5 N·s·m−1) group showed lesser expression of the motor memory, when compared both with the Arc (−2.66 ± 0.5 N·s·m−1) and Cursor (−0.84 ± 0.5 N·s·m−1) groups . Moreover, we found significant differences for the motor memory expressed at the end of EC blocks between the Cursor and Arc groups (p = 0.033).We next analyzed the pattern of change of the motor memory within blocks of EC trials by calculating the average value for the initial and final performance within each block . An ANOVA-RM for the initial performance revealed a significant effect for Block  = 5.40; p < 0.001). However, we did not find significant effect of Group  = 1.23; p = 0.30), or a significant Block × Group interaction  = 0.81; p = 0.61).Since we did not expect to find between-group differences at the onset of blocks of EC trials, we also analyzed the pattern of change of the motor memory within blocks of EC trials by calculating the average value of the initial three consecutive trials within each EC block. An ANOVA-RM revealed a significant effect for Block  = 98.05; p < 0.001) and Block  = 4.17; p < 0.001) factors, but we did not find a significant Block × Group interaction  = 0.82; p = 0.68). Post hoc comparisons revealed significant differences for all pair-wise comparisons for the Group factor . The Arc group (−2.00 ± 0.14 N·s·m−1) showed the most negative value of Force at Peak Velocity, followed by the Cursor (−0.71 ± 0.13 N·s·m−1) and Augmented-Error (0.77 ± 0.14 N·s·m−1) groups. These results then support the notion that between-group differences for the motor memory decay arose mainly during the blocks of EC trials, and that are not just due to potential between-group differences for learning.In order to further test whether between-group differences found across blocks EC1–EC9 resulted from subtle learning differences, we performed an ANCOVA, with Force at Peak Velocity averaged across the last six trials of each block as dependent measure, and Force at Peak Velocity measured at the initial six trials as covariate. We found a significant effect for Group . A summary of the results from the exponential fit is presented in Table b parameter) revealed that the Cursor (−0.26 ± 0.02) and Augmented-Error (−0.25 ± 0.03) groups showed a rate of motor memory decay significantly larger than the Arc group (−0.08 ± 0.02). Results found for the asymptote (c parameter) revealed that the Arc group (−2.27 ± 0.23) showed a plateau value significantly smaller than both the Cursor (−0.90 ± 0.16) and Augmented-Error (1.15 ± 0.27) groups, whereas the Cursor group showed a plateau value significantly smaller than the Augmented-Error group.To test for potential between-group differences for the rate of decay of the motor memory, we calculated the trial-by-trial Force at Peak Velocity, averaged for each participant across nine blocks of EC trials that followed adaptation  = 0.1; p = 0.90). However, an ANOVA-RM for the adaptation phase, Block (FF1–FF10) and Group, revealed a significant effect for Block  = 12.77, p < 0.001), and a trend for an effect of Group factor  = 2.48, p = 0.096; Figure F = 1.10, p = 0.35). An ANOVA-RM for Block (EC1–EC9) and Group revealed no significant effect for Block  = 0.64, p = 0.74) or Group  = 1.11, p = 0.34), and no significant Block × Group interaction  = 0.96, p = 0.50; Figure F = 0.036, p = 0.96).A Univariate ANOVA for the Probability of Success achieved by participants at Baseline did not reveal a significant effect for Group  = 1.41; p = 0.21) or Group  = 0.04; p = 0.96), and no Block × Group interaction was found  = 1.0; p = 0.45). We next performed an ANOVA-RM for the within block average variance of the Force applied at Peak Velocity in EC1–EC9. We found a trend for a significant effect for Block  = 2.07; p = 0.068), and Group  = 3.07; p = 0.057) factors. However, we did not find a significant Block × Group interaction  = 0.76; p = 0.68). Post hoc comparisons revealed only a trend for significant differences between Arc (1.67 ± 0.22 N·s·m−1) and Augmented-Error (2.43 ± 0.22 N·s·m−1) groups (p = 0.06).In order to test for between-group exploratory behavior differences, we analyzed the variance of the directional angle during FF (FF1–FF10) blocks. We did not find significant effect for Block  either within blocks of FF or EC trials.F = 9.59; p < 0.001), and a trend for a significant effect of Time  = 2.24; p = 0.085). However, we did not find significant Time × Group interaction  = 1.35; p = 0.24). Post hoc comparisons revealed that the force exerted at peak velocity by participants from the Augmented-Error group was significantly larger, when compared both with the Arc and Cursor groups  = 11.58; p < 0.001), and a trend for a significant effect of Block  = 3.01; p = 0.09) although we did not find a Block × Group interaction  = 2.42; p = 0.101). Post hoc comparisons revealed that the force exerted by the Arc group was significantly more negative compared with the Cursor and Augmented-Error groups . Altogether, these results suggest that when re-exposed to EC trials, all three groups similarly recalled the motor memory that they had generated during adaptation (FF1–10), and had previously expressed at EC9.An ANOVA-RM for the Force at Peak Velocity measured at EC10, after the washout block N2, with Time  as within-subject factor and Group as between-subject factor, revealed a significant effect for Group  that followed adaptation in the FF blocks Figure , and ourA relationship between reinforcement learning mechanisms and stronger motor memories has previously been proposed  should result in higher rate or magnitude of decay of the motor memory. Crucially, when we increased the error signal by showing participants a trajectory curved to the opposite direction than the expected path (Augmented-Error group), we found significant differences for the rate of decay, compared with the Arc group, and we also found between-group differences for the maximum value of the motor memory at the end of EC blocks, when compared both with the Cursor and Arc groups. Forces applied by participant from the Augmented-Error group aimed towards the opposite direction than the curved visual feedback trajectory . These results confirm our suggestion, that the decay of the motor memory may be driven by active mechanisms of motor adaptation, where movement corrections depend on a mismatch between expected and actual visual feedback.b, Table We hypothesize that the sensory prediction error causes active unlearning. For the Arc group, we deny them access to visual feedback in the EC trials, and as the compensatory forces build up over EC1–9  and the effort  after a washout period (N2), the Force at Peak Velocity was significantly larger for the Augmented-Error group, when compared with both the Arc and Cursor groups. Pekny et al.  reportedIn conclusion, our results extend the notion that active learning occurs during the decay of the motor memory (Vaswani and Shadmehr, AL-R designed the study, performed the data acquisition, analyzed the results, and wrote the article. RCM designed the study, analyzed the results, and wrote the article.This work was supported by the Wellcome Trust, grant WT087554.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


The pathways of thermal instability of amino acids have been unknown. New mass spectrometric data allow unequivocal quantitative identification of the decomposition products.2O, some NH3 and no CO2. Cysteine produces CO2 and little else. The reactions are described by polynomials, AA→a NH3+b H2O+c CO2+d H2S+e residue, with integer or half integer coefficients. The solid monomolecular residues are rich in peptide bonds.Calorimetry, thermogravimetry and mass spectrometry were used to follow the thermal decomposition of the eight amino acids G, C, D, N, E, Q, R and H between 185 °C and 280 °C. Endothermic heats of decomposition between 72 and 151 kJ/mol are needed to form 12 to 70% volatile products. This process is neither melting nor sublimation. With exception of cysteine they emit mainly HEight of the 20 standard amino acids decompose at well-defined, characteristic temperatures, in contrast to commonly accepted knowledge. Products of decomposition are simple. The novel quantitative results emphasize the impact of water and cyclic condensates with peptide bonds and put constraints on hypotheses of the origin, state and stability of amino acids in the range between 200 °C and 300 °C. Previous reports missed the quantitative identification of gaseous products. The broader implication of this general relationship between amino acids and their condensation products is that amino acids might have been synthesized under prebiological conditions on earth or deposited on earth from interstellar space, where they have been found  per sample. All data are summarized in Fig. Although we examined all 20 amino acids, we report results for those eight of them, for which the sum of the volatile gases, NHC2H5NO2, 75 Da, Hf= −528 kJ/molC3H7NO2S, 121 Da, Hf = −534 kJ/molC4H7NO4, 133 Da, Hf = −973 kJ/molC4H8N2O3, 132 Da, Hf = −789 kJ/molC5H9NO4, 147 Da, Hf = −1097 kJ/molC5H10N2O3, 146 Da, Hf = −826kJ/molC6H14N4O2, 174 Da, Hf = −623kJ/molC6H9N3O2, 155 Da, Hf = −467 kJ/molpeak for each amino acid, at the same temperatures they are accompanied by drops in TGA and QMS peaks. The simple fact that the DSC and QMS signals coincide in bell shaped peaks with the TGA drop proves that essentially one simple decomposition process takes place, there is not a spectrum of decomposition temperatures, as there would be for proteins. Qualitatively this proves that the process observed is neither melting nor sublimation . The ob3) = X1. It decomposes upon heating, 2 NaHCO3 → Na2CO3+CO2+H2O. The 3 and 3 lines were quantitatively repeatable over months, in terms of pC/mol CO2 and pC/mol H2O. They served to identify 1 mol CO2/mol Cys and 2O/mol Q beyond any doubt. In the absence of primary NH3 calibration we had to resort to secondary substances, glutamine, aspartic acid and asparagine, which retained stable NH3 and H2O signals over months. The 3/mol Q can only come from the glutamine dimer, which implies that also the H2O signal from glutamine corresponds to 2O/mol Q. For the other two, the correspondence between 1 mol H2O and 1 mol NH3 is convincing. Thus we had four consistent reference points: 2O and 2 from NaHCO3, and 3 from glu- tamine, and 1 mol NH3 from Asparagine. For each amino acid sample, the ion current is measured individually in each mass channel between 1 and 100 Da in 1 Da intervals. Integration over time (and temperature) gives for each mass the ion charge per mol AA, [C/molAA], and with the four calibrations the final values of mol/molAA. In Figs. μC/mol signal for the reference substance X1. Since this definitely cannot contain NH3, a systematic error of 20 μC/mol must be present, though the statistical errors are smaller.The DSC signals have the dimension of specific power [W/g], the QMS ones are ion currents of the order of pA. Integration over time, or, equivalently, temperature, gives the peak areas, which are specific energies [J/g] and ionic charges, of the order of pC. Reduction from specimen weights, typically 10 mg, to mol values is trivial. In absolute terms the ion currents and ionic charges are meaningless, because equipment dependent, calibration is needed. Only one reliable calibration substance was available, sodium bicarbonate , nor sublimation . One concludes that amino acids do not exist in liquid or gaseous form. They decompose endothermally, with heats of decomposition between −72 and −151 kJ/mol, at well defined temperatures between 185 °C and 280 °C.Figures α of the same backbone, NH2−Cα−(C∗OOH), but their decomposition chains are quite different. The pyrolytic process is controlled by three balance laws: In terms of Da the masses must add up, chemically the atomic species must balance, and the enthalpy of formation must equal the enthalpies of formation of the products plus the endothermic heat of reaction. The amounts of volatile products are experimental values (TGA and QMS). For the residues only the mass is experimental, their composition is inferred. In this section we analyze possible pathways. Although the choices, restricted by compositional, mass and enthalpy considerations, are convincing, they cannot be unique beyond doubt. Alternatives to our proposals, but indistinguishable by us, are possible. Analyses of the decomposition chains are, therefore, tentative or speculative. Nevertheless, they are less speculative than those of Rodante et al. . The oxygens counterbalance the others with −182 kJ/mol. The obvious way of efficiently transferring enthalpy from the reactants to the products is the formation of water, with Hf (H2O)=−242 kJ/mol.We made use of the enthalpy values listed for standard conditions  without 2 production in Cys is obviously a special case. In principle one expects the N-termini to be stable, making desamination to produce NH3 unlikely. Nitrogen in the side chains is another matter, indeed the NH3 producing Asn and Arg have nitrogen in their side chains. The predominance of H2O production indicates instability of the C-terminus beyond the C ∗ atom, where dehydration can occur by n-oligomerization, which yields (n-1)/n mol H2O/mol AS, from dimerization for n=2, to 1 mol H2O/mol for n →∞ in polymerization. A special case of dimerization is external cyclization in the diketopiperazine reaction, which yields 1 mol H2O/mol AA. These involve joining N- and C- termini in a dehydration reaction. For long side chains also internal cyclization, where the end of the side chain connects to the C-terminus can be envisaged. Integer and half-integer mol values restrict the choice for the residues, but not unequivocally.Detailed analysis for each amino acid is helped by preliminary reference to a few reactions possible in principle. COAll DSC peaks are endothermic, their areas are given negative signs. With this convention endothermic evaporation and exothermic production of water are written as 2H5NO2, 75 Da, Hf =−528 kJ/mol.Glycine, Gly, G, Cpeak =−72.1 kJ/mol.Simple endothermic peak at 250 °C, H2O/mol Gly plus 3/mol Gly is beyond doubt, it is confirmed by the mass loss of 35 Da /mol Gly. This leaves only 10% of the original hydrogen for the residue. The triple and double bonds in carbon rich C4HNO, C3HNO and C2HNO preclude them enthalpy wise and make deposition of carbon likely,The QMS signal of 2H2N2O2, chemspider 11593418, 86 Da,  C4H8N2O3, Hf(s) = − 748 kJ/mol [2-C α-H2 − group on one, and the C α-H2-C ∗OOH group on the other side. The former makes NH3 plus C, the latter makes 2 C plus 2 H2O. This process is specific for the glycine dimer, in which the C α atoms are not protected by proper sidechains, they are just −Cα-H2 − units. This pathway to shear peptide bonds is of interest in the context of possible peptide nucleic acid (PNA) synthesis [4H10N2O2, chemspider 379422, which is deoxidized diglycine, 2Gly→O2+AEG.The simplest pathway seems the formation of linear Glycylglycine, chemspider 10690 Fig. d, m.p. 23H7NO2S: 121 Da, Hf =−534 kJ/mol.Cysteine, Cys, C, Cpeak = 221 °C with a mass loss of 98 Da, Hpeak=−96 kJ/mol.T2 signal leaves no oxygen to form H2O, therefore the spurious 18 Da line must stem from a systematic error. There is also 3/mol Cys. For H2S there is indeed a signal at 34 Da. It corresponds to 1 mol, because the ionization cross sections of H2S and H2O are nearly identical, so that the calibration of Fig. 2 was found. The total reaction isThe clear 1 mol CO4H7N might be ejection of the carboxyl group −C∗OOH and the −SH group from Cys, the remaining chain NH2-C α-C ∗ is too short for internal, but suitable for external cyclization. Two of these form the asymmetric 5-ring , Fig. 142 is cutt off. Indeed the 3 ejected confirms such dimerization. That leaves the molecule C4H7N: 2,5-Dihydro-1H-pyrrole, chemspider 13870958, b.p. 90 °C, 69 Da, Hf(s) =−46.6 kJ/mol . The molecular weight of C4H3NO2 is 97 Da.DSC shows two distinct peaks, at 230 °C and at 250 °C, in each of which 1 mol H4H3NO2) n is polysuccinimide. The two peaks prove that the reaction occurs in two steps, in the first at 230 °C the condensation reaction produces polyaspartic acid, n Asp→H2O+(Asp)n, in the second at 250 °C the poly-Asp degrades to polysuccinimide (PSI) by ejection of another 1 mol H2O/mol Asp. Such a reaction was reported by Schiff [β-poly-Asp, there is an isomer, α-poly-Asp, where the next C in the ring forms a bond to its neighbour. We have no possibility to decide between the two.The compound  was calculated as y=−364 kJ/mol. The two values agree, although because of their histories, the two PSI are not identical. If Asn followed the example of Asp, it would eject 1 mol H2O /mol Asn in the condensation reaction n Asn→H2O+(Asn)n, poly-N, followed by degradation of poly-N to polysuccinimide (PSI) by ejection of 1 mol NH3 /mol Asn. If, however, the H2O of the condensation reaction is not ejected but retained, it can replace the −NH2 in poly-N by −OH. According to Asn−>NH3+ poly-D, this amounts to the formation of polyaspartic acid from asparagine by ejection of NH3. The poly-D then degrades to polysuccinimide (PSI) by ejection of 1 mol H2O/mol Asn. Apparently both alternatives shown in Fig. 3 and H2O.In the broad peak at 232 °C, 1 mol H4H3NO2) n, these two residues need not be identical. For kinetic reasons the oligomerization or polymerization might have proceeded to different lengths in poly-Asp and poly-Asn, therefore the degraded products PSI might have different lengths, with different stabilities and melting points. Moreover, the telomers are different, −OH for PSI from Asp and −NH2 for PSI from Asn. Indeed PSI from Asp remains a white powder up to 289 °C, while PSI from Asn starts melting at 289 °C.Though the formulae for PSI formed from Asp and from Asn, are the same, . The dehydration of Glu has been known for a long time [x=−734 kJ/mol for Hf(C5H7NO3), pyroglutamic acid, chemspider 485, 129 Da, T m=184 °C, b.p. = 433 °C  =−459 kJ/mol and Hf(g) =−375 kJ/mol for C4H5NO2, succinimide, 99 Da, the five ring with O= and =O as wings  =−286 kJ/mol, yellow liquid, can be ruled out, although cutting off the CO2 is sterically tempting.At 200 °C, 1 mol Hk is 12%  Da. The k is 12%  Da. The a et al. , ours isk is 12%  Da. The 5H10N2O3: 146 Da, Hf =−826 kJ/mol.Glutamine, Gln, Q, C2O and NH3 in the peak at Tpeak=185 °C, Hpeak=−77 kJ/mol, indicate that a dimer serves as intermediate step, γ-glutamylglutamine  = +105 kJ/mol, Hf(g) = +179 kJ/mol; for imidazole Hf(s) = +49 kJ/mol, Hf(g) = +132.9 kJ/mol [The MolPort database  quotes t9 kJ/mol . MoreoveSpeak=Hpeak/Tpeak, is 215 J/Kmol, way above the usual entropies of melting , and higher than typical entropies of evaporation . The endothermic heats in the peaks are therefore neither enthalpies of fusion nor enthalpies of sublimation, they are heats of reaction accompanied by phase changes. There is transformation and decomposition, but no reversible melting. Amino acids are stable in solid form, but not as liquids or gases.In the tables of Domalski , Chickos2O is ejected, but neither NH3 nor CO2 are produced in protein formation. Thermal decomposition of amino acids is analogous. In protein formation, the endothermic heat is provided by ATP, in amino acid decomposition it is thermal energy. Figure Five of the eight amino acids have residues containing peptide bonds, −C(=O) −NH−, only Asp and Asn leave polysuccinimide (PSI), Cys leaves cyclic pyrrolines. The preponderance of water in thermal decomposition is not surprising. In natural protein formation, each participating amino acid suffers damage. In the condensation reaction, where the N-terminus of one molecule reacts with the C-terminus of its neighbour, the planar peptide bond −Cα − CO − N − Cα− is formed. The N-atoms on, and the keto-bound O −atoms off the backbones retain their position. HH2O+(X−Y), the difference between the enthalpies of the reactants and the products go into the formation of the peptide bond (PB): Hf(X)+Hf(Y)= −242 kJ+Hf(X−Y)+HPB. With the tabulated value [Hf(X), Hf(Y) and Hf(X-Y) one calculates H PB=−67 kJ in glycylglycine, −70 kJ in alanylglycine, −43 kJ in serylserin, −78 kJ in glycylvaline, −65 kJ in leucylglycine, −91/2 kJ in triglycylglycine, −86/2 kJ in leucylglycylglycine, and −58 kJ in glycylphenylalanine. The average value is −59 ± 13 kJ per peptide bond. The narrow standard deviation indicates that the enthalpy of forming a peptide bond is insensitive to its environment, therefore the endothermic values of oligomerization or polymerization should be close to this. One concludes that the formation of a peptide bond in a linear dimer is endothermic with an enthalpy of 59 ± 13 kJ. It is tempting to compare this with the areas of the DSC peak, the observed endothermic heat of the decomposition reaction. The average of the eight amino acids is −105 ± 27 kJ/mol. One concludes that essentially the endothermic heat of decomposition, the peak area, goes into peptide bond formation.Quantitatively, the parallel between protein formation and pyrolysis is confirmed on the enthalpy level. In the formation of a dipeptide, X+Y →ed value , 15 for 3, contributing up to 3/mol AA. Remarkable is the absence of methane , hydrogen cyanide  and formamide , all in mass channels where we would have seen them. These, suspected in prebiotic synthesis of amino acids, do not appear in their decomposition. Although at most only three molecules are involved, two gases and one monomolecular residue, identification of the structure of the latter is not unequivocal, there remain more or less probable other possibilities than our choices. Clearly, without QMS, data from DSC and TGA could not possibly suffice to identify decomposition chains.In cases where the N-terminus, untouched by the condensation, remains attached to a cyclic product, it could be cut off as NHThe novel quantitative results emphasize the importance of water and cyclic condensates containing peptide bonds. All postulated residues are cyclic compounds, five of the 8 contain peptide bonds. The residues are stable at temperatures >180 °C and beyond the respective peak termperatures. These facts put constraints on hypothetical origin, state and stability of amino acids in the range between 200 °C and 300 °C in the absence and presence of water, but literature is sparse in that respect. The history of diketopiperazine and derivatives is extensively reviewed by Prasad , but Pra3, H2O and CO2. The predominance of the release of H2O during the process of decomposition instead of melting indicates a common principle of condensation and, depending on the individual properties of the respective intermediate products, subsequent decomposition of the condensation products. Comparative data for all 20 standard amino acids, obtained by complementing DSC and TGA with quantitative mass spectrometry (QMS), have never been reported. For the eight with data closure we can say: Amino acids decompose thermally, they do not sublimate, nor do they melt. Only three gases are formed, mostly H2O, less so NH3 and hardly any CO2. Cys forms H2S, but not CS2. In all amino acids investigated, Gly, Cys, Asn, Asp, Gln, Glu, Arg, His, the liquid or solid residues are lactams and heterocyclic compounds with 5- or 6-membered non-  aromatic rings, containing one or two nitrogen atoms , most of them with peptide bonds present.Our comparative analysis allowed us to identify the eight of the twenty standard amino acids, for which the thermochemical equations unequivocally agree with stoichiometric release of NHIn summary, this work addresses an important question of amino acid thermal stability. Several processes may occur upon heating, chemical decomposition or sublimation/evaporation without decomposition. The aim of this work was to accurately determine these processes. For 8 out of the 20 standard amino acid, we demonstrated that these have a well defined temperature of decomposition. The contemporary detection of products of 17 Da, 18 Da, and 44 Da in the gas phase is the proof for decomposition, concise mass and enthalpy balances do not leave any room for speculation. Analysis and interpretation rule out the existence of any byproduct hydrocarbons which could not have been validated. The analysis for glycine, cysteine, aspartic acid, asparagine, glutamic acid, glutamine, arginine and histidine is beyond any doubt. At a heating rate of 5 K/min, neither melting nor sublimation take place. At least 8 of 20 standard amino acids do not exist in liquid form.


Monoclonal immunoglobulin deposition disease (MIDD) is characterized by the non-amyloid deposition of monoclonal immunoglobulin fragments in the basement membranes. Heavy chain deposition disease (HCDD) is a type of MIDD. HCDD is an extremely rare disease, and only three cases have been reported in Japan up to the present. The prognosis of HCDD is very poor, and optimal treatment has not been established. Only a few cases of HCDD with favorable long-term renal prognosis have been reported to date.The authors describe a 61-year-old woman who presented with massive proteinuria, progressive kidney impairment, and hypocomplementemia. Kidney biopsy was performed for a precise diagnosis. On light microscopy, glomerules were lobulated and presented with nodular sclerosing glomerulopathy with membranoproliferative glomerulonephritis-like features. Immunofluorescence studies were positive for IgG, C3, and C1q within the mesangial nodules and in a linear distribution along the capillary walls without associated deposition of light chains. Staining for IgG showed the presence of linear deposits along tubular basement membranes. The analysis of the IgG subclass stain demonstrated intense positivity for IgG3 only. Electron microscopy revealed non-organized electron-dense deposits in the expanded mesangial area and inner aspect of the glomerular basement membranes. In accordance with the histological findings, we diagnosed γ3-HCDD. There was no evidence of plasma cell dyscrasia as a result of bone marrow aspiration. Serum and urine monoclonal proteins were not detected by immunoelectrophoresis and immunofixation electrophoresis. The serum free light chain ratio was within normal range. At first, prednisolone was administrated at a dose of 40 mg/day. However, a therapeutic effect was not observed. Urinary protein was not decreased and renal function further deteriorated. Therefore, melphalan plus prednisolone (MP) therapy was initiated. After 4 courses of MP therapy, the clinical parameters, including proteinuria, serum creatinine, albumin, and complement level (C3 and C4) were ameliorated. To date, the patient has been followed for 28 months, and long-term renal survival has been observed.In this case, hematologic disease such as multiple myeloma was not detected; however, MP therapy was effective. Recently, the novel concept of monoclonal gammopathy of renal significance (MGRS) has been reported. MIDD, which includes HCDD, is one category of MGRS. In MGRS, aggressive chemotherapy may induce favorable renal outcomes. Monoclonal immunoglobulin deposition disease (MIDD) has three distinct forms: light chain deposition disease (LCDD), light and heavy chain deposition disease (LHCDD), and heavy chain deposition disease (HCDD). These three subtypes are distinguished depending on the components of the deposits. The deposits are derived from monoclonal light chains only in LCDD, monoclonal light and heavy chains in LHCDD, and monoclonal heavy chains only in HCDD. Renal involvement is frequent in MIDD. The main clinical features are renal dysfunction and proteinuria, often accompanied by nephrotic syndrome (NS). The characteristic pathological findings in MIDD are the presence of linear non-organized monoclonal immunoglobulin deposits along tubular basement membranes (TBM) and glomerular basement membranes (GBM) by immunofluorescence and electron microscopy. Especially in cases of HCDD, light microscopy shows nodular sclerosing glomerulopathy. Among cases of MIDD, HCDD is extremely rare. This rare disease was first described in 1992 . In JapaA 61-year-old woman with a medical history of hypertension and chronic kidney disease (CKD) was admitted to our hospital for proteinuria and progressive deterioration of renal function. She attended the hospital as an outpatient and was administered olmesartan, cilnidipine, and azosemide. Her serum creatinine level was 1.0 mg/dL, and no urinary abnormalities were observed in the local clinic. 2 months before admission, there were subjective symptoms of pedal edema and blood pressure elevation. Her creatinine level increased to 1.52 mg/dL, and heavy proteinuria was observed at a local clinic. Subsequently, she was referred to our hospital for further management.3/μL, hemoglobin level of 12.0 g/dL, and platelet count of 315 × 103/μL. Laboratory investigation revealed a serum creatinine concentration of 1.85 mg/dL, blood urea nitrogen of 37 mg/dL, and estimated glomerular filtration rate of 22.8 mL/min/1.73 m2. The total serum protein level was 5.2 g/dL with a serum albumin level of 3.1 g/dL. The following laboratory data were obtained: total cholesterol: 280 mg/dL, low-density lipoprotein cholesterol: 175 mg/dL, triglycerides: 237 mg/dL, uric acid: 6.3 mg/dL, C-reactive protein: 0.03 mg/dL. Liver dysfunction, diabetes mellitus, and electrolyte imbalance were not observed. Immunological studies showed a serum IgG concentration of 283 mg/dL , IgA of 259 mg/L , and IgM of 183 mg/dL . The serum complement C3 level was 33.2 mg/dL , C4 was 3.3 mg/dL , and total hemolytic activity (CH50) was 9.1 U/mL . Marked hypocomplementemia was recognized. Tests for hepatitis B and C, rheumatoid factor, anti-nuclear antibody, anti-DNA antibody, anti-SS-A/SS-B antibody, anti-neutrophil cytoplasmic antibody, anti-cardiolipin antibody, and cryoglobulin were all negative.At the initial visit, the patient had a blood pressure of 135/88 mmHg, body height of 149.5 cm, and weight of 42.5 kg. Physical examination revealed bilateral edema of the lower extremities. Urinalysis showed proteinuria with protein excretion of 4.15 g/g creatinine and 5–8 red blood cells per high-power field. Hematologic tests indicated a white blood cell count of 6.3 × 10She was admitted to our hospital 2 days after the initial consultation for a careful examination. As a result of the additional examinations, the serum and urine immunoelectrophoresis showed no monoclonal bands. Furthermore, the entity of monoclonal protein was not identified on immunofixation electrophoresis. The serum free κ light chain level was 45.1 mg/L, λ light chain was 57.6 mg/L, and κ/λ ratio was 0.783 . Serum amyloid A protein level was not elevated at 2.7 μg/mL . In the bone marrow examination, the CD 138 positive cells proliferate slightly, but they were not clear tumorous proliferation. Plasma cells are 0.5% in the bone marrow and heteromorphy has not been confirmed. Pathological proliferation of plasma cells was also denied by flow cytometry. Ultrasound examination indicated renal atrophy; therefore, laparoscopic renal biopsy was performed for accurate diagnosis.The kidney specimens were studied by light microscopy, immunofluorescence stain, and electron microscopy using standard techniques. For direct immunofluorescence stain, 3-μm cryostat sections were stained using polyclonal fluorescein isothiocyanate (FITC)-conjugated antibodies to IgG, IgA, IgM , C3, C4, C1q, κ, and λ. Further staining of the IgG subclasses was performed using mouse monoclonal antibodies to human IgG1 , IgG2, IgG3 , and IgG4 , followed by FITC-conjugated goat anti-mouse IgG .The sample contained 13 glomerules, none of which were globally sclerosed. By light microscopy, glomerules showed a diffuse increase in the mesangial matrix and mild mesangial hypercellularity. Most glomeruli were lobulated and exhibited remarkable nodular formation in the mesangial area that narrowed the capillary lumens. Capillary walls were irregularly thickened. Duplication of the GBM accompanied by endothelial cell swelling indicated an endothelium disorder. Endocapillary proliferation and mesangiolysis were observed in several glomeruli. Crescents were not detected in the specimen. Tubular atrophy and interstitial fibrosis was mild with patchy infiltration of mononuclear cells. Vessels showed moderate arteriosclerosis Fig. . ElectroInitially, the patient was treated with oral prednisolone (PSL) at a dose of 40 mg/day. However, the therapeutic response was very poor. The serum creatinine level increased to 3.65 mg/dL and blood urea nitrogen to 122 mg/dL, while the severe hypoalbuminemia (2.4 g/dL) did not improve. Urinary protein excretion did not decrease (4.27 g/g creatinine on admission to a maximum of 12.02 g/g creatinine), and in addition, the ascitic fluid and bilateral edema of the lower extremities became worse. The serum C3, C4, and CH50 titers remained extremely low . Therefore, the patient was treated with chemotherapy consisting of melphalan and PSL at a dose of 40 mg/day for 4 consecutive days. The daily use of PSL was rapidly tapered and stopped after chemotherapy. MP therapy was conducted 4 times in 7 months. The treatment interval was 1 month at short and 3 months at long. The dosage of melphalan was adjusted in accordance with renal function, 4 mg in the first and second courses, 6 mg in the third and 8 mg in the final. After 4 courses of MP therapy, the serum C3 and C4 titers were markedly elevated (C3 84.6 mg/dL and C4 31.3 mg/dL), and the serum creatinine level was decreased to 1.52 mg/dL. After discontinuance of MP therapy, the laboratory data did not deteriorate. To date, the patient has been followed for 28 months. The serum albumin levels have been maintained at over 3 g/dL, and the quantitative analysis of urinary protein was decreased to 2.72 g/g creatinine. NS was not observed and renal function was stable (the serum creatinine level was around 2.0 mg/dL). The patient’s condition improved with no edema, which had been observed initially.We report a case of γ-3HCDD which was diagnosed with clinicopathological features. Written informed consent was obtained from the patient for the administration of melphalan. She provided informed consent for the publication of this case report.Kambham et al. described the disease spectrum of HCDD . The mosIn our case, massive proteinuria and advanced renal failure were observed at the first visit. Organ damage was limited to the kidney. Severe hypocomplementemia was detected in our patient. The existence or nonexistence of hypocomplementemia is related to the IgG subclasses of HCDD. Soma et al. presented a first case report of γ3-HCDD in Japan and mentioned the relevance with hypocomplementemia and IgG subclasses . In the The serum or urine monoclonal protein levels were positive in more than half of the HCDD patients (64–86% in the serum and 50–83% in the urine), but not all . The absTypical pathological findings of HCDD show nodular mesangial sclerosis. The mesangial nodules were generally positive for periodic acid-Schiff, trichrome blue, and silver stain. Crescentic formation is also sometimes observed . Vedder The diagnosis of HCDD requires characteristic pathological findings. The following criteria were applied in previous cohort studies of MIDD; (A) positive staining for a single class of immunoglobulin  on the GBM and/or TBM, (B) completely negative staining of light chains (κ and λ), and (C) characteristic EDD observed by electron microscopy , 18, 24.The treatment of HCDD has not been established until now. The prognosis of HCDD is very poor historically. Kambham et al. reported 11 cases of HCDD treated with corticosteroids, cyclophosphamide, and melphalan . In the Recently, the utility of bortezomib has been reported. Patel et al. presented 3 patients with severe kidney manifestation of HCDD who achieved clinical remission and improvement of renal function following a bortezomib-based treatment . Cohen eTherapeutic indicators for treating HCDD are urinalysis findings and renal function. Particularly, the serum complement level is important in γ3-HCDD patients. In our case, treatment with steroids alone had no effect at all. However, after the treatment with MP therapy, the serum albumin levels have been maintained at over 3.0 g/dL, and NS was not observed for a long period of time. The serum creatinine value was stable.Hypocomplementemia was notably improved. For these reasons, MP therapy was considered to be beneficial in this case. Interestingly, our patient responded well to the MP therapy, although a bone marrow aspirate did not show findings of plasm cell infiltration, and monoclonal immunoglobin was not identified in the serum or urine by conventional electrophoresis and immunofixation. These results indicate that the monoclonal immunoglobin levels are very small, reflecting a strong affinity for kidney tissues. In fact, in this case, monoclonal immunoglobin was demonstrated only in a renal biopsy by immunofluorescence staining. The initiation of therapeutic intervention at an early stage of disease was indicated as a favorable prognostic factor in previous reports , 18, 24.In recent years, a review of monoclonal gammopathy of renal significance (MGRS) has been reported . MGRS isIn conclusion, we present a case of γ3-HCDD with NS and renal dysfunction who responded to MP therapy and maintained kidney function for a long time. However, further careful observation is necessary to assess the treatment effect. In order to improve the renal outcome of HCDD, an excellent understanding of renal pathology for early diagnosis and suitable treatment methods are required. Penetration of MGRS concept and aggressive chemotherapy may improve the renal prognosis.


We attempted to elucidate the antimicrobial activity and potential mechanisms against Staphylococcus aureus.In our previous study, Ag2 and Ag+ bacteriostatic activity against S. aureus strains by MIC assays and S. aureus growth curves, lesion in the membranes by surface hydrophobicity tests, conductivity tests and measurements of DNA and RNA contents in S. aureus cultures, and investigated the inhibition of soluble protein and nucleic acid synthesis by measurements of soluble protein content, fluorescent intensity and nucleic acid content of living S. aureus.The study tested the TiO2 and Ag+ were 1.6 mg ml−1 and 5.781 µg ml−1. TiO2 and Ag+ could inhibit the growth of S. aureus. After treatment with TiO2 and Ag+, the surface hydrophobicity was significantly reduced, the conductivity of cultures increased, and DNA and RNA content in cultures showed no obvious changes. The expressions of soluble proteins and nucleic acid contents of living S. aureus were reduced after treatment with TiO2 and Ag+.The MIC values of TiO2 and Ag+ could cause slight lesion in the membrane to affect S. aureus membrane permeability, but not decomposition of membrane. Moreover, TiO2 and Ag+ could lead to reduced expression of soluble protein by inhibiting the synthesis of nucleic acids, thereby further inhibiting the growth of S. aureus.TiO Additiobination . To enhaify TiO2 .2 to inactivate bacteria because of its excellent broad-spectrum antibacterial properties, heat resistance, good dispersion and low drug resistance [Among these noble metals, Ag has attracted significant attention for doping TiOsistance .2 and Ag-SiO2 polyethylene endotracheal tubes that had excellent antimicrobial properties against ventilator-associated pneumonia (VAP) [et al. found that Ag+-TiO2 nanobelts exhibited greater photocatalytic degradation activity against methyl orange than TiO2 because of the greater amounts of reactive oxygen species that are generated [+-deposited TiO2 are expected to have improved bactericidal properties under conditions of visible light irradiation [+ was investigated by researchers. Heidenau et al. found that an Ag+ concentration of 3.5 µM was not cytotoxic to mouse L929 fibroblasts [et al. found that an Ag+ concentration between 30 and 70 µM affected both cell viability and morphology [et al. found that, for both Gram-negative Escherichia coli ATCC 15597 and Gram-positive Bacillus subtilis, the antimicrobial effects of Ag+ were greater under light conditions compared with those under dark conditions [et al. found that Ag nanoparticles exhibited efficient microbicidal activity against Staphylococcus aureus, but did not significantly affect the viability of osteoblast cells (MC3T3-E1) [et al. found that, compared with TiO2-SiO2, Ag-TiO2-SiO2 exhibited higher photocatalytic activity and antibacterial efficiency after uniform Ag nanoparticles were loaded onto TiO2 [−1, the antibacterial rates against Escherichia coli and S. aureus were 93.41 and 97.37 %, respectively. Jin et al. proposed that the potential antibacterial mechanisms of Ag+ were as follows: first, Ag+ can be easily adsorbed onto the surface of E. coli and affect the outer membrane permeability and ﬂuidity; second, Ag+(silver nanoparticles with carbon dots doped with sulfur) with a smaller size (7.3±1.0 and 6.1±0.8 nm) can permeate the membrane of E. coli to interact with DNA and components of the respiratory chain; and third, Ag+ release can cause E. coli death [We prepared antimicrobial films that contained Ag-TiOia (VAP) . Zhou etenerated . Becauseadiation . Recentlroblasts . Baldi erphology . Jin et nditions . Tan et C3T3-E1) . Shi et nto TiO2 . In respli death . However2 and Ag+ antibacterial agents have been studied by our research group for many years [2 and Ag+ antibacterial agents and investigate their bactericidal mechanisms. We attempted to elucidate the antimicrobial activity and potential mechanisms of TiO2 and Ag+ as antibacterial agents against S. aureus by determining their antimicrobial activity of the MIC values and S. aureus growth curve, conductivity, and macromolecular substances in culture medium, and by measuring the soluble proteins and nucleic acids of S. aureus after treatment with antibacterial agents.The preparation and theoretical use of TiOny years . In this2 stock solution (aged 60 days) was prepared according to previously published methods [+ stock solution was prepared so that the Ag-TiO2 mesoporous materials were dispersed into the water at a mass concentration of 5 wt% [S. aureus ATCC 25923 was obtained from Hangzhou 100 Biotechnology. The biosafety cabinet and enzyme marker were produced by Thermo. The fluorescence microscope was produced by Olympus. Vertical electrophoresis apparatus was produced by Tanon. The conductivity meter was produced by Shanghai Dapu Instrument Co. The UV spectrophotometer was produced by Shanghai Xinmao Instrument Co. The decolorization table was produced by Shanghai Huxi Instrument Co.2,3,5-triphenyltetrazolium chloride (TTC), hexadecane, 4′,6-diamidino-2-phenylindole (DAPI), hexadecane, protein marker and distilled water were of guaranteed reagent quality. The TiO methods . Ag+ stoof 5 wt% . S. aureBeef extract (3 g), peptone (10 g) and NaCl (5 g). All salts were dissolved in 800 ml distilled water, the pH was adjusted to 7.2–7.4, and then more distilled water was added to achieve a total volume of 1000 ml.2HPO4 (14.6 g), NaH2PO4 (1.48 g) and NaCl (43.83 g). All salts were dissolved in 1 l distilled water, and water was added to achieve a final volume of 5 l. The pH was adjusted to 7.2–7.4 with NaOH and stored at room temperature after autoclave sterilization.PBS buffer contained Na2 groups: 0.1, 0.2, 0.4, 0.8 or 1.6 mg ml−1; (3) Ag+ groups: 0.723, 1.445, 2.891, 5.781 or 11.560 µg ml−1.(1) Control; (2) TiOS. aureus were picked up from agar/slant culture medium and inoculated in broth medium at 37 °C, 120 r.p.m. for 24 h. The final concentration of cells was adjusted to 106–107 c.f.u. ml−1 with broth medium. Then, 1.5 ml of the bacterial culture was inoculated on 12-well plates in which 10 µl serial dilutions of TiO2 or Ag+ were added. Plates were incubated at 37 °C, 120 r.p.m. for 24 h. Subsequently, 150 µl of 0.2 % TTC was added to each well. Changes in colour were observed after incubation at 37 °C, 120 r.p.m. for 4 h in the dark. Each group included triple technical replicates.A few S. aureus cells were incubated to the log-phase of growth. Next, 2 % inoculum was transferred to fresh broth medium with 0.5 MIC TiO2 or Ag+ and incubated at 37 °C, 120 r.p.m. Samples were obtained and the OD value was determined at 580 nm at 4 h intervals. Each group included triple technical replicates. S. aureus growth curves after TiO2 or Ag+ treatment were plotted as OD values on the vertical axis compared with time on the horizontal axis. Each group included triple technical replicates.The S. aureus cells were incubated until they reached the log-phase of growth. Then, 2 % inoculum was transferred to fresh broth medium with 0.5 MIC TiO2 or Ag+ and incubated at 37 °C, 120 r.p.m. Next, 2 ml samples were transferred into 5 ml tubes and, after incubation for 0, 2, 8 or 16 h, they were centrifuged at 5000 r.p.m.  for 10 min. Cell pellets were washed twice with 0.1 M KNO3 (pH 6.2) and resuspended with the same buffer. Cell suspensions were adjusted to absorbance A400=0.4 (i.e. A0=0.4); 10 mM sodium phosphate buffer solution served as a blank control. Additionally, 0.2 ml hexadecane was added into the adjusted cell suspensions. Samples were mixed for 2 min using a vortex after a 10 min static incubation. Aqueous phases were transferred and the A400 (A1) absorbance values were measured until the two phases of the mixture became completely separated. Bacterial surface hydrophobicity was indicated by the absorption rate. Bacterial absorption rate =(1−A1/A0)×100 %. Each group included triple technical replicates.S. aureus cells were incubated until they reached the log-phase of growth. Next, 2 % inoculum was transferred to fresh broth medium with 0.5 MIC TiO2 or Ag+ and then incubated at 37 °C, 120 r.p.m. Thereafter, 5 ml samples were harvested after incubation for 0, 2, 4, 6 and 8 h, which were each centrifuged at 4000 r.p.m. for 10 min. Cell conductivity was determined with a conductivity meter after 20-fold dilutions of supernatants. Each group included triple technical replicates.S. aureus cells were incubated until they reached the log-phase of growth. Then, 2 % of the inoculum was transferred into fresh broth medium and was again incubated until the culture reached log-phase at 37 °C, 120 r.p.m. Cells were collected, washed twice with PBS and resuspended at an appropriate concentration to yield a cell suspension. A final concentration of 0.5 MIC TiO2 or Ag+ was added to the prepared suspension. After treatment for 0, 2, 4, 6 or 8 h, 3 ml of the suspension was collected and centrifuged at 4000 r.p.m.  for 10 min. Absorption values of DNA and RNA in the supernatant were measured at 260 nm using an ultraviolet spectrophotometer. Each group included triple technical replicates.S. aureus cells were incubated until they reached the log-phase of growth. Then, 2 % of the inoculum was transferred into fresh broth medium with 0.5 MIC TiO2 or Ag+ and incubated at 37 °C, 120 r.p.m. Suspensions were harvested after incubation for 12 and 16 h, and 0.1 g cells were centrifuged at 4000 r.p.m.  for 10 min. Pellets were collected and resuspended in 40 µl sterile water. The sample buffer was mixed with the sample at a volume ratio of 1 : 4, and the mixture was heated in boiling water for 7 min and then centrifuged at 4000 r.p.m.  for 10 min. Soluble proteins in the supernatant were assessed by SDS-PAGE. Each group included triple technical replicates.S. aureus cells were incubated until they reached the log-phase of growth. Then, 2 % of the inoculum was transferred into the fresh broth medium with 0.5 MIC TiO2 or Ag+ and was incubated at 37 °C, 120 r.p.m. for 24 h. Aliquots of 10 µl per sample were diluted 200-fold. Subsequently, 100 µl diluted suspension was spotted on a microslide and stained with the same volume of DAPI staining solution. Mixtures were incubated without shaking in the dark for 10 min. Fluorescence intensity was measured using a fluorescence microplate reader and imaged. Each group included triple technical replicates.S. aureus cells were incubated until they reached the log-phase of growth. Then, 2 % of the inoculum was transferred into the fresh broth medium with0.5 MIC TiO2 or Ag+ and was incubated at 37 °C, 120 r.p.m. Then, 50 µl aliquots were harvested after incubation for 12, 16, 20 and 24 h, and stained with 150 µl DAPI staining solution. Prepared samples were measured immediately after shaking for 10 min. The fluorescence parameters were 364 nm to measure the DNA content and 400 nm to measure the RNA content. Each group included triple technical replicates.sd. Differences between group means were assessed by ANOVA for multiple comparisons using spss 16.0. Values of P<0.05 were considered significant.All data are presented as mean±2  and 58.6 % (P<0.001), respectively.Treatment with TiO2 and Ag+ on bacterial surface hydrophobicity based on the hydrophobicity of hexadecane and bacterial absorption. As shown in 2 or Ag+. Moreover, the effects of TiO2 on S. aureus surface hydrophobicity were higher than those of Ag+.The bacterial cell surface is composed of both hydrophilic and hydrophobic sites, the latter mainly including lipopolysaccharides, lipids and proteins. Bacterial surface hydrophobicity is primarily dependent upon the ratio of proteins and polysaccharides, along with the types and orientations of carbohydrate and polysaccharides in the outer layer of cell. In this present study, we tested effects of TiO2 or Ag+.Changes in bacterial membrane permeability can result in the leakage of intracellular small molecules, such as potassium ions and sodium, which can further alter extracellular conductivity . When a 2 or Ag+ to test for effects on membrane permeability in S. aureus. As shown in S. aureus showed no obvious changes compared with those observed in the control group.Furthermore, we assessed changes in the levels of DNA and RNA macromolecules when cells were treated with TiO2 or Ag+ contributed to changes in membrane permeability in S. aureus. This caused slight lesion in the membrane, but not decomposition of membrane, and it did not cause extracellular DNA and RNA leakage.Together, these findings suggested that treatment with either TiOS. aureus when cells were treated with TiO2 or Ag+. As shown in 2 or Ag+ to the medium could suppress expression of soluble proteins in S. aureus. Moreover, the expression of proteins was further reduced after prolonged treatment with the effectors.We used SDS-PAGE to determine the soluble protein content in 2 and Ag+ on nucleic acid content in S. aureus by measuring the fluorescence intensity of cells that had been treated with DAPI. As shown in 2 or Ag+ was decreased compared with the control group. Further analysis showed that the fluorescence of both DNA and RNA were significantly decreased in the treated groups (both P<0.001), as shown in DAPI is a fluorescent stain that can strongly bind to DNA and RNA, and it is often used to detect nucleic acids. Its fluorescence intensity is positively correlated with the nucleic acid content. In the present study, we studied the effects of TiOS. aureus, E. coli and Pseudomonas aeruginosa. TiO2 has a strong redox ability and stable chemical properties and bactericidal effect by photocatalysis which can decompose bacteria, viruses and fungi. The sterilizing rate is 99.00 % in no light and 99.99 % in UV light irradiation [+, with contact antibacterial action, is the most powerful antibacterial material in inorganic antibacterial materials. In order to effectively control the VAP caused by infection after tracheal intubation, we prepared Ag+-loaded TiO2 and Ag+-loaded SiO2 coatings, which could effectively inhibit bacterial growth, such as S. aureus, E. coli and P. aeruginosa [2 and Ag+ in medical instruments, the underling mechanisms of TiO2 and Ag+ antibacterial effects were explored in the study.VAP is a common serious complication in patients with tracheal intubation. The bacteria associated with VAP are almost all antibiotic-resistant strains, such as adiation . Ag+, wiruginosa  and had ruginosa . In orde2 and Ag+ could inhibit the growth of S. aureus. Moreover, TTC staining analysis indicated that the MIC of TiO2 was 1.6 mg ml−1, while that of Ag+ was 5.781 µg ml−1. Therefore, with the same dose, Ag+had stronger antibacterial activity than TiO2. We used these 0.5 MIC concentrations as working concentrations to explore the mechanisms of TiO2 and Ag+ against S. aureus. Our findings indicated that TiO2 and Ag+ utilized a similar mechanism against bacterial growth by directly damaging the bacterial surface. The activities of these drugs against negatively charged lipopolysaccharides on the cell surface will result in changes of the surface charge and hydrophobicity, which further affect membrane permeability. However, these changes do not damage intact cells or induce leakage of macromolecules, DNA or RNA. Moreover, treatment with TiO2 and Ag+ could lead to reduced soluble protein expression by suppressing the synthesis of nucleic acids, which further inhibited the growth of S. aureus. The result showed that TiO2 and Ag+ could cause slight lesion in the membrane to effect S. aureus membrane permeability, but not decomposition of membrane, and that TiO2 and Ag+ could inhibit S. aureus nucleic acid synthesis and reduce expression of soluble proteins against bacterial growth. Pleskova et al. studied bactericidal activity of TiO2 film and also found that S. aureus is swollen by TiO2 through damaging the cell membrane [et al. also showed that silver nanoparticles could cause DNA to concentrate, lead DNA to lose replication and degrade, and inhibit soluble protein synthesis. Silver nanoparticles could destroy the genetic material of bacteria, so that bacteria could not grow and reproduce [2 and Ag+ antibacterial action against S. aureus was probably through inhibiting the synthesis of nucleic acid, thereby reducing protein synthesis against bacterial growth.It was found that both TiOmembrane . An et aeproduce . Thus, T2 and Ag+ and the underling mechanisms. Although TiO2 and Ag+ have been shown to exhibit strong bactericidal properties on S. aureus, it is important to emphasize that prior to their practical applications in medical instruments, efforts should be made to fully evaluate the potential carcinogenicity and in vivo toxicity of TiO2 and Ag+ against animal cells and tissues.It should be emphasized that the main aim of this study was to investigate the bactericidal activity of TiO


Actinobacillus pleuropneumoniae and Pasteurella multocida, MICs were determined for three drugs, florfenicol, oxytetracycline and marbofloxacin, in five broths  and in pig serum.The most widely used measure of potency of antimicrobial drugs is Minimum Inhibitory Concentration (MIC). MIC is usually determined under standardised conditions in broths formulated to optimise bacterial growth on a species-by-species basis. This ensures comparability of data between laboratories. However, differences in values of MIC may arise between broths of differing chemical composition and for some drug classes major differences occur between broths and biological fluids such as serum and inflammatory exudate. Such differences must be taken into account, when breakpoint PK/PD indices are derived and used to predict dosages for clinical use. There is therefore interest in comparing MIC values in several broths and, in particular, in comparing broth values with those generated in serum. For the pig pneumonia pathogens, P. multocida) and 0.35:1 (A. pleuropneumoniae), so that potency of this drug was reduced for the former species and increased for the latter species. The chemical composition of pig serum and broths was compared; major matrix differences in 14 constituents did not account for MIC differences. Bacterial growth rates were compared in broths and pig serum in the absence of drugs; it was concluded that broth/serum MIC differences might be due to differing growth rates in some but not all instances.For each drug, similar MIC values were obtained in all broths, with one exception, marbofloxacin having similar MICs for three broths and 4–5-fold higher MICs for two broths. In contrast, for both organisms, quantitative differences between broth and pig serum MICs were obtained after correction of MICs for drug binding to serum protein (fu serum MIC). Potency was greater (fu serum MIC lower) in serum than in broths for marbofloxacin and florfenicol for both organisms. For oxytetracycline fu serum:broth MIC ratios were 6.30:1 (For all organisms and all drugs investigated in this study, it is suggested that broth MICs should be adjusted by an appropriate scaling factor when used to determine pharmacokinetic/pharmacodynamic breakpoints for dosage prediction. Dosage regimens of antimicrobial drugs should be optimized first to achieve clinical and bacteriological cure and second to provide minimal opportunities for the selection of resistant organisms. The successful outcome of therapy depends on both the pharmacokinetic (PK) profile, which determines the drug concentration-time course at the site of infection and the pharmacodynamic (PD) profile that is drug effect on the pathogen –4. HenceMinimum Inhibitory Concentration (MIC) is the primary PD parameter used to determine potency; it is the lowest drug concentration that inhibits visible bacterial growth after 16–24 h incubation. Standardised methodologies for MIC determination are described in European Committee on Antimicrobial Susceptibility Testing (EUCAST) and Clinical and Laboratory Standards Institute (CLSI)  guidelinWhilst serum is not identical to extravascular infection site fluids, it is likely to be closer to the biophase than broths in chemical composition and indeed in respect of immunological components also , 10. A cWT) by CLSI. However, modification of the two-fold dilution approach may be appropriate, when MICs are correlated with PK data for establishing PK/PD breakpoints. Based on methods previously described [A second consideration, in relation to dose prediction, is that CLSI and EUCAST guidelines have limitations regarding accuracy for individual isolates, because they require use of two-fold dilutions, giving potential for approaching 100% error. For most purposes, this is wholly acceptable, and indeed is necessary, when large numbers of isolates are examined to establish MIC distributions. When plotted on a histogram, using a log-base 2 distribution, they are log-normal. These histograms facilitate the identification of wild-type distributions. Standardisation of methodology thereby enables determination of epidemiological cut-offs (ECOFF) by EUCAST and wild type cut-offs  determine whether any broth/serum MIC differences were attributable solely to drug binding to serum protein; (3) compare chemical compositions of CLSI recommended broths and pig serum; (4) determine rates of growth A. pleuropneumoniae and P. multocida in broths and pig serum in the absence of drugs. Aims 3 and 4 were included to investigate whether chemical composition differences and/or bacterial growth rate differences between broth and serum might account for matrix MIC differences over and above those attributable binding of the drugs to serum protein.It is the hypothesis of this investigation that MICs determined in pig serum  might differ from MICs determined in broths. The aims were to: (1) compare MICs measured in five broths with MICs determined in pig serum, using five sets of overlapping two-fold dilutions for three drugs, florfenicol, marbofloxacin and oxytetracycline, used in the treatment of pig pneumonia caused by the pathogens, P. multocida and three American Type Culture Collection (ATCC) reference strains to validate MIC tests; A. pleuropneumoniae ATCC 27090, Enterococcus faecalis ATCC 29212 and Escherichia coli ATCC 25922. Eight isolates of A. pleuropneumoniae were supplied by A. Rycroft . All P. multocida and A. pleuropneumoniae isolates were obtained from European Union (EU) field cases of pig pneumonia, specifically the UK and France. The quality control organisms were incorporated in each MIC test. Organisms were stored at -80 °C.Don Whitley Scientific  supplied 20 isolates of From the organisms supplied, three isolates of each species were selected, based on three criteria: (1) exhibiting logarithmic growth in all broths (see below) and pig serum; (2) sensitivity to florfenicol, marbofloxacin and oxytetracycline in disk diffusion assays (data not shown); and (3) the highest and lowest CLSI defined broth MICs and one isolate of intermediate MIC, determined using two-fold dilutions (data not shown).A. pleuropneumoniae Chocolate Mueller Hinton Agar (CMHA) was used to grow the organism on a solid medium. Mueller Hinton Agar (MHA), supplemented with 5% defibrinated sheep blood, was used to grow P. multocida. Columbia broth (CB) supplemented with 2 μg/mL nicotinamide adenine dinucleotide (NAD) was used as the principal liquid broth for A. pleuropneumoniae MIC determination. CLSI guidelines require use of Veterinary Fastidious Medium (VFM) for the liquid culture of A. pleuropneumoniae. However, for isolates used in this study, MIC end-points were more readily and reliably established using CB than with VFM. In the latter broth, there was difficulty defining MIC end-points, because the high density of red blood cells caused them to settle at the base of the well obscuring the result of MIC. The CLSI recommended broth for P. multocida is Cation Adjusted Mueller Hinton broth (CAMHB), and this was the principal liquid broth used in this study for this organism.For Both organisms were incubated in a static incubator at 37 °C for 18–24 h. For comparative purposes, MICs were determined for both organisms in five broths, CB, CAMHB, Mueller Hinton broth (MHB), Brain Heart Infusion broth (BHI), Tryptic soy broth (TSB), and pig serum .Bacterial counts were determined by serial dilution and spot plate counts. Culture dilutions were carried out in phosphate buffered saline. Three 10 μL drops of the appropriate dilutions were dropped onto the agar surface and allowed to dry. After 24 h incubation, the mean colony forming unit (CFU) count for each 10 μL was determined and multiplied by 100 and then multiplied by the dilution factor to give the original CFU/mL count.A. pleuropneumoniae and P. multocida, using CLSI guidelines, except that: (1) five sets of overlapping two-fold serial dilutions were used to reduce inaccuracy for individual isolates to no greater than 20%; (2) determinations were made in five broths, MHB, CAMHB, CB, BHIB, TSB and pig serum; (3) the bacterial culture was grown to 0.5 McFarland Standard and this was diluted ten-fold to obtain the intended starting inoculum of 1–2 × 107 CFU/mL. This starting inoculum count is higher than the CLSI recommendation of 5 × 105 CFU/mL, the higher inoculum count being selected deliberately to be equivalent clinically to a medium to heavy in vivo microbial challenge.MICs of florfenicol, marbofloxacin and oxytetracycline were determined by microdilution in 96-well plates for three isolates each of L. These were sealed and incubated statically at 37 °C for 24 h. Spot plate counts were prepared immediately after plate inoculation. ATCC isolates were used in all assays at the CLSI recommended strength of 5 × 105 CFU/mL. A positive control well contained medium and pathogen only and a negative control well contained medium and drug only. Blank controls contained medium alone.Drug solutions, media and culture were added sequentially to the wells of 96-well plates, with a total volume of 200 μMICs were determined in triplicate for each isolate of each species and each drug. In previous studies in this laboratory, binding to pig serum protein had been determined for each drug over the therapeutic concentration range and shown to be independent of concentration –19. PercFor analysis of 14 chemical constituents, three batches of each broth were prepared in 10 mL quantities, according to manufacturer’s instructions and three batches each of pig and calf serum were obtained commercially . Calf serum was included to compare the composition of pig serum with another farm animal species. Samples were analysed for total protein, albumin, globulin, sodium, potassium, calcium, magnesium, chloride, inorganic phosphorus, urea, creatinine, glucose, iron and Unsaturated Iron Binding Capacity (UIBC) .P. multocida and A. pleuropneumoniae  supplied 20 isolates of both organisms for the purpose of determining growth in media), from clinical cases of pig pneumonia, were used to investigate bacterial growth in the absence of antimicrobial drugs. Growth rates were determined in pig serum and the CLSI recommended broths, VFM for A. pleuropneumoniae and CAMHB for P. multocida.Twenty isolates each of Three mL of serum, CAMHB or VFM were aseptically added to the wells of a 96-well plate. Two control wells containing medium alone ensured the absence of contamination. Six independent colonies were removed from a fresh agar plate aseptically and mixed into the medium within the wells. The well plates were placed in a static incubator at 37 °C for 24 h. At times of 0, 6 and 24 h viable counts were determined. Bacterial growth was monitored in triplicate for each of 20 isolates of each species.Tables P. multocida MICs were similar for three broths, MHB, CAMHB and TSB (range = 0.05–0.07 μg/mL). MICs were 4–5-fold higher for CB and BHIB (0.25–0.27 μg/mL). Serum MIC was 0.09 μg/mL and, corrected for protein binding, fu serum MIC was 0.04 μg/mL. The mean MIC ratio fu serum:CAMHB was 0.63:1.A. pleuropneumoniae broth MICs were similar (range = 0.91 μg/mL for CAMHB to 1.37 μg/mL for TSB). Serum MIC was 0.69 μg/mL and fu serum MIC was 0.35 μg/mL; mean MIC ratio fu serum:CB was 0.35:1.For P. multocida MICs in all broths were similar; range = 0.47 μg/mL for MHB to 0.55 μg/mL for CAMHB. Serum MIC was 0.30 μg/mL and fu serum MIC was 0.10 μg/mL. The mean MIC ratio fu serum:CAMHB was 0.19:1.For A. pleuropneumoniae broth MICs ranged from 0.36 μg/mL for both MHB and CAMHB to 0.45 μg/mL for BHIB. Serum MIC was 0.47 μg/mL and fu serum MIC was 0.16 μg/mL, so that mean MIC ratio fu serum:CB was 0.38:1.For P. multocida broth MICs were similar, ranging from 0.28 μg/mL (MHB) to 0.38 μg/mL (TSB). Serum MIC was 6.20 μg/mL and fu serum MIC was 1.80 μg/mL. The mean MIC ratio fu serum:CAMHB was 6.30:1.For A. pleuropneumoniae ranged from 2.34 μg/mL (CAMHB) to 3.22 μg/mL (TSB). Serum MIC and fu serum MIC were 3.47 and 1.01 μg/mL, respectively, so that the mean MIC ratio fu serum:CB was 0.35:1.Broth MICs for Table For the six broths, total protein concentration was low in MHB and CAMHB  but higher and similar for the four other broths (range 9.07–12.6 g/L). Serum total protein concentrations were higher, 79.3 g/L (pig) and 74.3 g/L . For all broths, the principal protein constituent was globulin (range 3.23 to 12.5 g/L) whilst albumin concentrations were uniformly low, ranging from 0.00 to 0.87 g/L, for MHB and VFM, respectively. Albumin serum concentrations were much higher; 40.2 g/L (pig) and 38.1 g/L . Expressed as serum:broth albumin concentration ratios, these ranged from greater than 400:1 for CAMHB to 46:1 for VFM.There were moderate differences in sodium concentration between the growth matrices; the lowest concentration was 118 mmol/L (TSB) and the highest was 168 mmol/L (BHI) and serum concentrations were intermediate, 153 and 148 mmol/L, for pig and calf, respectively. Similarly, serum chloride ion concentrations for pig and calf were intermediate  between the lowest, 79 mmol/L for TSB, and highest broth concentration of 123 mmol/L for BHI. MHB had the lowest potassium concentration (2.49 mmol/L) whereas the highest concentration was 39 mmol/L for VFM. Serum potassium concentrations were intermediate, 7.13 and 7.07 mmol/L for pig and calf, respectively.With the exception of CAMHB, the concentration of calcium was much lower in broths, ranging from 0.05 to 0.33 mmol/L, in comparison with serum, 2.59 and 2.55 mmol/L for pig and calf, respectively. For CAMHB the calcium concentration was 5.21 mmol/L. Concentrations of magnesium were lower in three broths  than in serum of pig and calf, 0.98 and 1.00 mmol/L, respectively, whereas concentrations in CAMHB, CB and VFM were higher, 4.20, 1.41 and 1.16, respectively.Broth inorganic phosphorus concentrations ranged from 2.55 mmol/L (MHB) to 14.3 mmol/L (VFM) and serum concentrations were similar to MHB, 2.82 and 3.28 mmol/L for pig and calf, respectively. Broth urea concentrations ranged from 0.93 mmol/L (MHB) to 5.97 mmol/L (BHI) and concentrations in serum were slightly less than the highest broth value, 4.67 and 5.23 mmol/L, pig and calf, respectively. In broths, creatinine concentration was lowest in MHB (61 μmol/L) and highest in BHI (418 μmol/L) and serum concentrations were intermediate . Broth glucose concentrations ranged from 2.56 mmol/L (MHB and CAMHB) to 12.9 mmol/L (CB) whilst serum concentrations were intermediate, 5.47 mmol/L (pig) and 4.43 mmol/L .Iron broth concentrations varied almost 10-fold, from 6.86 μmol/L (TSB) to 63.9 μmol/L (CB) and serum concentrations were intermediate, 19.1 μmol/L (pig) and 22.2 μmol/L . Unsaturated iron binding capacity also varied widely (data not shown).P. multocida and A. pleuropneumoniae, respectively. There were no apparent inter-isolate differences in P. multocida growth rates in CAMHB at 6 and 24 h. For all isolates at 6 h, bacterial counts had increased to 6-7x109CFU/mL in broth and at 24 h counts exceeded 1010 CFU/mL for all isolates. In serum, there was again minimal inter-isolate difference in growth of P. multocida at 6 h but the count, 5-6x107CFU/mL, was lower at this time than in CAMHB by some 2 × 102 CFU/mL. After 24 h, there was further increase in growth but there were some inter-isolate differences in count, which ranged from 8-10 × 1010 CFU/mL, and the serum count was somewhat lower than the 24 h count in CAMHB at this time.Figures A. pleuropneumoniae, bacterial growth was much slower initially (at 6 h) in both media than for P. multocida. At 6 h the mean CFU/mL count for 20 isolates was 5.37 × 105 in broth and in in serum it was significantly lower, 1.36x102CFU/mL. In contrast with P. multocida there was clear inter-isolate variability in growth rate at 6 h. However, by 24 h considerable growth had occurred and counts were of a similar order in both media, approaching or exceeding slightly 10log10 CFU/mL.For Mannheimia haemolytica, a MIC in serum 6 times greater than the broth MIC. In marked contrast, Toutain et al. [smaller in calf serum compared to broth for tulathromycin for M. haemolytica and P. multocida isolates from calves. Similar findings, with quantitatively even lower MICs for Mycoplasma mycoides mycoides in calf serum compared to broth, were reported for the macrolides, tulathromycin and gamithromycin by Mitchell et al. [For some drug classes, MICs measured in broths using internationally standardised procedures  may not differ significantly from potency estimated in biological fluids. The absence of growth matrix differences implies no significant impact on PK/PD breakpoint estimation, as a basis for dose determination, provided that the protein bound serum drug concentration is corrected for , 16, 20.l et al. –24. ThusThese published data suggest: first, that serum MIC values should be considered on both a drug-by-drug and bacterial species-by-species basis to allow for the inactive protein bound fraction; and second, corrected serum values may not be the same as, and therefore might be used in preference to, the broth MIC for PK/PD breakpoint estimation.Only free drug is microbiologically active and therefore protein binding is a major factor, and unfortunately sometimes the only factor, considered in seeking to explain growth medium differences in antimicrobial drug potency , 25–27. P. multocida) and 0.35:1 (A. pleuropneumoniae); florfenicol 0.19:1 (P. multocida) and 0.38:1 (A. pleuropneumoniae); oxytetracycline 6.30:1 (P. multocida) and 0.35:1 (A. pleuropneumoniae). Thus, for marbofloxacin and florfenicol there were small to moderate trends for both pathogens of increased (1.6- to 5.2-fold) potency in serum compared to broth. Likewise, for oxytetracycline and A. pleuropneumoniae the greater potency in serum was 2.8-fold, whereas for P. multocida potency was 6.3-fold lower in serum. Consequently, correction of serum MIC for protein binding is, as stated, necessary but not sufficient for determination of potency differences between the two matrices for these two bacterial species and these three drugs. The consistent finding of differences, which were nevertheless unpredictable in direction (increased or reduced potency) and magnitude indicates the possibility of similar differences for human pathogens also more frequently than is commonly recognised.For both organisms investigated in this study, correcting the serum MIC for protein binding for marbofloxacin, florfenicol and oxytetracycline yielded fu serum MICs differing from broth MICs in most instances. Fu serum:broth MIC ratios were: marbofloxacin 0.63:1 (P. multocida only. However, even for this drug and species, MICs were similar for two broths and different but again similar for other three broths. In contrast, the broth and corrected serum MICs differed, despite the finding that chemical composition of pig serum for every analyte was within the lower and upper ranges for the five broths. Therefore, chemical composition indicated no readily apparent explanation for the broth/serum MIC differences.Possibly the most important difference in chemical composition between all broths and serum was in albumin concentration, which was much higher in serum. Correction for drug binding to serum albumin revealed broth/serum potency differences for all drugs. It is therefore necessary to consider whether other differences, as well as albumin content, in chemical composition might explain the protein binding corrected potency differences. The chemical analyses indicated wide differences in composition of five broths for electrolytes, iron and organic compounds. Possibly surprisingly, these frequently large inter-broth differences resulted in, at most, very minor differences in MICs, with one exception, namely marbofloxacin, and for In addition to the chemical differences between broths and serum, for circulating blood there are other differences e.g. the presence of white and red cells as well as a wide range of immunological components in blood. Future studies should therefore be directed towards evaluating which of these might interact with drugs, and how, to modulate drug potency. One factor, pH, is known to influence the rate and extent of growth of microorganisms , 29. An Staphylococcus aureus and Pseudomonas aeruginosa in MHB and serum. Slower logarithmic growth was obtained for both species in serum compared to broth, and this might be expected to provide more rapid kill in serum, as a consequence of a smaller microbial challenge [M. haemolytica and P. multocida, while Dorey et al. [Zeitlinger et al.  comparedhallenge , 30. Indhallenge , 29 repoy et al. –19 reporP. multocida and A. pleuropneumoniae. This difference persisted for P. multocida at 24 h, whereas for A. pleuropneumoniae logarithmic growth was similar for the two media at this time. Slower growth, resulting potentially in lesser challenge to bacterial kill, therefore might explain, at least in part, the greater potency in serum compared to broth in five of six instances. The one notable exception, however, was the 6-fold reduction in potency of oxytetracycline in serum compared to broth for P. multocida. This finding indicates that some serum factor, presently unknown, operates to reduce potency of this drug for this species, whilst conversely potency was increased in serum for A. pleuropneumoniae.In the present study, bacterial growth was initially greater in broths than serum for both The differences in MIC between serum and broth reported in this study do not provide a rationale for abandoning broths by diagnostic laboratories reporting MIC distributions of wild type organisms. This would be impractical and unnecessary. Rather, the present data suggest that, for marbofloxacin, florfenicol and oxytetracycline and the two bacterial species studied, it will be appropriate and possible to apply a scaling factor, to bridge between MICs in broths and pig serum when calculating PK/PD breakpoints.A. pleuropneumoniae and P. multocida, differences between serum and broth MICs were obtained, after correction was made for binding to serum protein. In contrast, major differences were not obtained when MICs were determined in five broths, marked differences in chemical composition between the broths notwithstanding. In the absence of drugs, the rate of logarithmic growth of A. pleuropneumoniae and P. multocida was slower in pig serum than in broth. It is suggested that, in using MIC data as a pharmacodynamic parameter to determine PK/PD breakpoints, the use of a scaling factor to bridge between broth and biological fluids may be required more commonly than currently recognised.For three commonly used drugs, florfenicol, oxytetracycline and marbofloxacin, and two pathogenic species of bacteria causing pig pneumonia, For florfenicol, oxytetracycline and marbofloxacin and the pig pathogens, A. pleuropneumoniae and P. multocida, there were no major differences in MICs measured in five broths, widely differing in chemical composition.Significant differences between serum and broth MICs were obtained, after correction for binding to serum protein, indicating that such correction is necessary but that it does not alone account for potency differences.With one exception potency was greater in serum than broths.In using MIC data to predict dosages for clinical use, the use of a scaling factor to bridge between broth and biological fluids may be required.