It has been hypothesized that exposure to heavy metals may impair male reproduction. To measure the effect produced by low doses of heavy metals on semen parameters, it is necessary to clarify in which body fluids those measurements must be performed. Sixty-one men attending infertility clinics participated in our study. Concentrations of lead, cadmium, and mercury were measured in whole blood, blood plasma, and seminal plasma using spectroanalytical and electrochemical methods. Semen analyses were performed according to World Health Organization criteria. For statistical analysis, Spearman's rank correlations, mean comparison tests, and discriminant analysis were calculated. Significant correlations between the measured concentrations of the three heavy metals in the same biological fluids were observed. However, no similar relationship was seen when comparing the concentrations in different body fluids of the same metal. According to our results and previous publications, seminal plasma might be the best body fluid for assessing impairment of human semen parameters. Over time there has been a significant decline of human fertility . Like otThese demographic transformations, as much as they are socially valued and desirable, have important clinical consequences. The fertility decline has resulted in a major delay in the average age of conception. The first pregnancy is postponed to ages at which women fecundity is decreased . That maIn parallel, it has been hypothesized that there is a worldwide decline in male semen quality –8, but iOur research interests are related to the measurement of the exposure to lead (Pb), cadmium (Cd), and mercury (Hg), and its relationship with human semen quality. The main results published on that issue are summarized in μg/dL of lead in blood produced a decline of sperm count (<20 × 106 cells/mL). In addition, they observed lower motility (<50%) and morphology (<14%), with >35 μg/dL in whole blood [μg/dL) [There is considerable agreement that high or even moderate concentrations of lead cause fertility problems in humans. Fatima et al. showed that >40 le blood . Telisma [μg/dL) . High coμg/dL) were associated with impaired semen quality, 44% of motility, 32% of normal morphology, and 11 × 106 cell/mL of sperm concentration [μg/dL) and low motility, but no effect on morphology (>14%) or sperm concentration (>20 × 106 cells/mL) [μg/dL did not affect sperm concentration (96 × 106 cells/mL) [μg/dL measured in whole blood and 2.78 μg/dL in blood plasma had no effect on morphology (>14%), motility (>50%), or sperm concentration (>20 × 106 cells/mL) [6 cells/mL) or motility (55%) with 1.5 μg/dL of lead concentration in whole blood [However, there are conflicting results about the effect on semen quality at low lead exposures. Hernandez-Ochoa and colleagues found that low lead concentrations in seminal fluid (0.2 ntration . In contells/mL) . Similarells/mL) . Moreoveells/mL) . Meeker le blood . μg/dL) had 5.16 × 106 cells/mL of sperm count and 36% of motile sperms [At high concentrations, cadmium could affect semen quality. According to Akinloye et al., men with high concentrations of cadmium in seminal plasma (65 e sperms . μg/dL in whole blood were associated with head pathologic sperms [μg/dL) [μg/dL) were moderately associated with low sperm motility (<50%) but had no effect on morphology (>14%) or sperm concentration (>20 × 106 cells/mL) [μg/dL) and sperm concentration (96 × 106 cells/mL) [μg/dL) [μg/dL) and blood plasma (0.08 μg/dL) did not impaired morphology (>14%), motility (>50%), or sperm concentration (>20 × 106 cells/mL) [μg/dL) on sperm density (42.7 × 106 cells/mL) and motility (55%) [As seen with lead, there is no agreement on the effect of low concentrations of cadmium on semen quality. Telišman et al. found that even low concentrations of cadmium <1 c sperms . Benoff  [μg/dL) . Mendiolells/mL) . Equallyells/mL) . Chia anells/mL) . Moreovety (55%) . 6 cells/mL of sperm concentration [There is clear evidence that very high concentrations of mercury in the body will harm sperm. Choy et al. showed that high concentrations of total mercury (inorganic and organic) measured in whole blood (40.6 mmol/L) resulted in <50% of progressive motility, <14% of normal morphology, and <20 × 10ntration . 6 cells/mL) at low concentrations of total mercury in seminal plasma (1.18 μg/dL). Besides, low concentrations measured in whole blood (1.99 μg/dL) and blood plasma (0.6 μg/dL) were not related to decreased morphology (>14%), motility (>50%), or sperm concentration (>20 × 106 cells/mL) [6 sperm cells/mL) at low concentrations of organic mercury in whole blood (0.225 μg/dL) [μg/dL) did not affect motility (55%) and sperm concentration (42.7 × 106 cells/mL) [However, Mendiola et al. did not find an alteration of motility (>50%), morphology (>14%), or sperm concentration (>20 × 10ells/mL) . Rignell blood 0.5 μg/dL [ells/mL) . There are at least two problems in assessing whether low concentrations of heavy metals have an impact on human semen quality. First of all, there are just a few studies published on that issue so far. A second problem relates to the variables measured; that is the biological samples in which the concentrations of heavy metals are measured, and the parameters used to measure semen quality . To measure the effect produced by low doses of a heavy metal in the reproductive organs, it is necessary to clarify where to perform those measurements. Concentrations of heavy metals may be measured in the whole blood, in blood plasma, and in seminal plasma. However, it is not clear whether measurements in one or another fluid are equivalent, nor to what extent there are correlations between the three measurements of these heavy metals in the different body fluids. The objectives of this study are (1) to examine whether there are correlations between the concentrations of heavy metals  in the three body fluids  and (2) to explore whether any one of the three measures relates better than the others with the semen quality parameters. The study population, hormone, and semen analyses have been previously described elsewhere , 28. SixA total of 181 biological samples were analyzed for Pb, Cd, and Hg, including 61 samples of seminal plasma, 61 of blood plasma, and 59 of whole blood, as two samples were lost during the study. Biological samples were dispensed into aliquots and frozen and stored at −40°C until analysis. Anodic stripping voltammetry (ASV) was used for measuring Pb and Cd concentrations. ASV was carried out using a voltamperometer with VA 663 stand and VA 608 controller . The voltamperometric cell was equipped with a drop of mercury as the working electrode, an Ag/AgCl/KCl 3 M reference electrode, and a platinum auxiliary electrode. Determination of total Hg was carried out by thermal decomposition, amalgamation, and atomic absorption spectrophotometry, using a mercury analyzer with quartz sample boats . μS/cm. The highest grade purity reagents were employed in this procedure including nitric acid 65% and perchloric acid 70% . The ultrapure water was purified with Millipore Simplicity 185  obtaining conductivity values of 0.054 μg/L; cadmium, 0.11 μg/L, and mercury, 0.1 μg/L. To guarantee the accuracy and precision of the applied technique regarding heavy metals, whole blood reference materials  were employed. In order to prepare the working standard solutions, commercially available standard solutions for Pb 1 g/L and Cd 1 g/L  and Hg 1 g/L  were used. The limits of detection (LOD) for the body's fluid metal levels were as follows: lead, 21 μL of perchloric acid and 15 mL of double-distilled water were added, transferring the final volume into a voltamperometric cell. Pb and Cd determinations were performed using 0.2 mL of the biological sample deposited inside of 25 mL borosilicate glass. Acid digestion was carried out by adding 2 mL of nitric acid and 2 mL of perchloric acid and evaporating it to dryness. Once the sample was dry and cooled down, 100 Biological samples were measured by ASV according to the following method . BrieflyThe statistical analysis encompassed descriptive and inferential analyses. Basic, dispersion as well as frequency parameters were calculated for descriptive analyses. Statistical analyses were performed to explore possible patterns in the concentrations of heavy metals measured in blood serum, whole blood, and seminal plasma. Spearman's rank correlations and scatter plots were employed for comparison of variables. In the inferential analysis, the mean comparison tests and discriminant analysis were performed. All tests were two-tailed, and the level of statistical significance was set at 0.05. Statistical analysis was performed using SPSS 17.0 . μg/dL , in whole blood, blood plasma, and seminal plasma. Figures P = 0.67), between cadmium in seminal plasma and whole blood was −0.50 (P = 0.72), and between mercury in seminal plasma and whole blood −0.34 (P = 0.80). Figures P  value < 0.005) and between mercury and lead 0.76 . Spearman's correlation coefficients and scatter plots revealed a high correlation between the concentrations of the three metals in the same biological fluids. To explore whether these correlations were determined by associations with other factors, exploratory scatter plots were generated between the concentrations of the three metals in the three biological fluids and possible confounding variables. Possible confounders were such as “occupation,” “tobacco smoke,” “exposure to toxics at work” or “using metals at work.” No patterns were observed. Hypothesis tests were used to detect significant differences in the mean concentrations of metals and the possible confounding factors used in the scatter plots. Not significant differences were found (data not shown). As a final alternative, metal concentrations were categorized in two, three, and four groups using the mean values, tertiles, and quartiles, respectively. Discriminant analysis was then used to detect whether any of the factors was related to the categories of the metal concentrations. To this end, different discriminant analysis evaluating the overall Wilks' lambda and the owners of each factor were produced, but none of them were satisfactory. Using the Spearman's correlation coefficient and scatter plots revealed a high correlation between the measured concentrations of the 3 heavy metals in the same biological fluids. However, no similar relationship was observed when comparing the concentrations in different body fluids of the same metal. It would be reasonable to expect that subjects with high and low levels of exposure to any metal would show similar positions (low or high concentrations) in the measurements made in any body fluid. However, we found no correlation between the concentrations of any of the metal in the three biological samples analyzed . Other authors, similarly, found no correlation between the concentrations of the same metal in different fluids , 19. BenThere are some possible hypotheses for these phenomena. The three heavy metals are bound and transported by erythrocytes –32. GiveSurprisingly, the concentrations of Pb, Cd, and Hg were correlated in the same biological samples. Howatta et al. also found that the concentrations of cadmium and lead in seminal plasma were correlated . We do nCorrelations of the three heavy metals in the same body biological fluid may be due to an interaction between the different metals in the same compartment, so that the concentration of one metal determines the concentration of the others. We are not aware of lead, cadmium, or mercury modulate each other. However, it has been published that selenium produces the redistribution of Hg from plasma to erythrocytes at higher ratio  and the As to how to measure the effect produced by heavy metal concentrations on semen quality, it would be better to measure those metals in seminal plasma than in blood plasma or whole blood. Heavy metal concentrations in blood samples do not necessarily reflect the seminal plasma ones, since heavy metal concentrations reaching the seminal plasma could be quite different. Heavy metals have a strong capacity to induce oxidative stress in body cells by disintegration of the lipid membrane, and spermatozoa are quite sensible to oxidative stress , 39. ThuFurthermore, as it can be seen in Finally, our findings might be attributed to chance or bias. The sample of individuals included in the study was small and the lack of statistically significant correlations may be a consequence of that. Our findings are, however, consisting with those , 16, 19 Our study suggests that there is no correlation between the concentrations of any of the metals in the three biological samples analyzed  and there is a correlation between the concentrations of Pb, Cd, and Hg in the same biological samples. According to our results and previous publications, seminal plasma might be the best body fluid for assessing impairment of human semen parameters.


N = 58) were randomly assigned to the predictable or unpredictable group. Fear was measured via verbal ratings and eyeblink startle responses. Results indicated that cued pain-related fear spreads selectively to novel movements that are proprioceptively more similar to the CS+ than to those similar to the CS− in the predictable group, but not in the unpredictable group. This is the first study to demonstrate a generalization gradient of cued pain-related fear. However, this effect was only present in the startle eyeblink responses, but not in the verbal ratings. Taken together, this paradigm represents a novel tool to scrutinize the largely understudied phenomenon of the spreading of fear and avoidance in patients with chronic musculoskeletal pain and mapping possible pathological differences in generalization gradients and the spreading of pain in patients as compared with healthy controls.Increasing evidence supports the notion that pain-related fear plays a key role in the transition from acute to chronic pain. Recent experimental data show that associative learning processes are involved in the acquisition of pain-related fear. An intriguing yet underinvestigated question entails how spreading of pain-related fear in chronic pain occurs. In a voluntary movement paradigm in which one arm movement (CS+) was followed by a painful stimulus and another was not (CS−) in the predictable group and painful stimuli were delivered during the intertrial interval  in the unpredictable group, we tested generalization of fear to six novel generalization movements (GSs) with varying levels of similarity between the original CS+ movement and CS− movement. Healthy participants ( In comparison, patients with low fear of movement-related pain remain active after an acute pain episode, which in turn leads to functional recovery . Stimulus generalization is a highly adaptive mechanism, because the ability to detect similarities between unique but related stimuli may contribute to avoiding harm in a dynamic environment generalization to novel, albeit similar settings is the central pathogenic marker in certain anxiety disorders injury is acquired through associative learning processes, that is, initially neutral movements/activities  that are associated with (increases in) pain  start to elicit defensive responses such as fear and avoidance . In chronic pain patients, fear and avoidance are often not restricted to movements/activities that were associated with pain during the initial pain episode . Hence, contextual cues entail more unpredictability regarding the exact occurrence of the US relative to discrete cues. In the same vein, two types of pain-related fear can be distinguished depending on the temporal (un)predictability of the US: cued and contextual pain-related fear. Cued pain-related fear is experimentally induced by predictable pain , whereas contextual pain-related fear is induced by unpredictable pain  , volunteered to participate in this study as a partial fulfillment of course requirements or in exchange for a monetary compensation of 12. Participants were recruited using the departmental experiment management system , or by means of advertisements distributed at the University of Leuven. Participants completed a general health checklist to confirm they did not have one or more of the following conditions: cardiovascular disease, neurological disease, musculoskeletal disorder, or other pain-related conditions, psychiatric disorders, cardiac pacemaker, or the presence of any other electronic, medical devices, uncorrected vision/hearing problems, injury on hand/wrist, recent use of analgesic, anxiolytic, or antidepressant medication, being pregnant, being under 18 years old, and being a non-native Dutch/Flemish speaker. All participants provided written informed consent and were told that they could decline their participation at any given moment during the experiment. Eight participants were excluded because they did not meet our inclusion criteria. Of the remaining 62 participants that actually participated in the study, 4 were excluded due to technical difficulties, leaving a total of 58 participants to be included in the statistical data-analysis. Participants were randomly assigned to the predictable pain group (n = 29) or the unpredictable pain group (n = 29). The study protocol was approved by the ethical committee of the Department of Psychology of Leuven University.Seventy healthy female undergraduate psychology students of the University of Leuven (The experiment was run on a Windows XP computer (Dell OptiPlex 755) with 2 GB RAM and an Intel Core2 Duo processor. The visual stimuli were presented on a 19-inch computer screen. The presentation of the stimuli and the data acquisition was controlled with the free software package Affect (version 4.0)  and quadrant 8 (CSp−/CSu2) served as the CSs, and movements in quadrants 2–7 (GSp1–6/GSu1–6), served as the GSs in both groups. For half of the participants in the predictable group the movement in quadrant 1  was followed by the pain (CSp+) and the movement in quadrant 8  was never followed by pain (CSp−), whereas for the other half of the participants this combination was reversed. The pain-US was a 50 ms electrocutaneous stimulus, generated by commercial constant current stimulator . Pain stimuli were administered to the wrist of the dominant hand through two surface SensorMedics electrodes (8 mm diameter), spaced approximately 1 cm apart, and filled with K-Y gel. Prior to the experiment, the experimental pain-US was individually calibrated. Starting off with an intensity of 1 mA, the stimulus intensity was gradually increased in steps of 1–4 mA until participants rated the stimulus to be “significantly painful and demanding some effort to tolerate.” Self-reported pain intensity was rated on an 11-point Likert scale ranging from 0 to 10, with “0” meaning no pain and “10” meaning the worst imaginable pain; a stimulus intensity of 8 on this scale was targeted. The mean self-reported stimulus intensity was 7.69 . The mean physical stimulus intensity was 23.78 mA . We observed no differences between the predictable and the unpredictable groups with respect to the subjective intensity of the pain-US , t(56) = −0.22, p = 0.82, or the stimulus intensity in milliamperes , t(56) = 0.25, p = 0.81.The CSs and the generalization stimuli (GSs) were eight, equally spaced movement quadrants Figure . These pOrbicularis Oculi Electromyographic (EMG) activity was recorded with three re-usable Ag/AgCl SensorMedics electrodes (4 mm diameter) filled with electrolyte gel. Before attaching the electrodes on the left side of the face according to the site specifications proposed by Blumenthal et al. , the skinot fearful at all” to “the worst fear imaginable.”After each block during the acquisition and the generalization phase, participants rated the extent to which they were afraid of performing a certain movement on a computerized VAS with anchor points “As a manipulation check, pain-US expectancy was assessed at the end of the experiment. Participants indicated for both CSs to which extent they expected to receive a painful stimulus on a computerized VAS with anchors “not at all” and “very much.” The VAS was coded from 0 to 100.After the experiment and as a manipulation check, a computerized version of the Self-Assessment Manikin (SAM)  the training phase was aborted and the next phase began. No startle probes or electrocutaneous stimulation was delivered during this phase of the experiment.Detailed oral and written instructions were provided to the participants before the onset of the experiment to make sure that the purpose of the joystick task was clear. Their main task was to move the joystick toward eight equally sized blue targets that were positioned at the borders of eight movement quadrants  to circumvent confounds in the data due to large startle responses to the first few probes. Startle habituation trials were excluded from the statistical analysis.This phase was similar to the practice phase, except that: (1) the boundaries of the eight movement quadrants and the yellow circle marking the borders of these quadrants were no longer visible. (2) The range of movements in this phase was restricted to quadrants 1  and 8 , indicated by a blue bar on either side. (3) The movement areas did not turn green or red anymore when the mouse cursor of the joystick reached a valid (green) or invalid (red) movement area. (4) The error message was no longer displayed on the screen when participants reached an invalid target region. (5) Startle probes and pain-USs were presented during this phase.p+ movement, and one CSp− movement in the predictable group, and one CSu1 movement, and one CSu2 movement in the unpredictable group. Although the duration of the CS movement itself was of variable length depending on the participants’ response latency and movement speed, there was a fixed ITI consisting of a 7 s pre-CS interval and a 7 s post-CS interval. In the predictable group, a CSp+ movement was paired with a painful US in 75% of the trials (12 pain-USs per block), whereas a CSp− movement was never followed by the pain-US. In contrast, pain-USs were explicitly unpaired with both the CSu1 and CSu2 movements in the unpredictable group, and were delivered during the ITI, while keeping the number of pain-USs equal in both groups. In the predictable group, the pain-US was presented immediately after the CSp+ movement. In the unpredictable group, the pain-US was delivered in a time window of 2–4 s after the onset of the pre-CS ITI or 4–6 s after onset of the post-CS ITI. A total of 12 startle probes were presented within each acquisition block; eight startle probes were presented during the CSs (four during CSp+/CSu1 and four during CSp−/CSu2), and four probes were administered during the ITI  .The startle data were treated offline with PSPHA, a modular script based program for analyzing psychophysiological data . The decision to collapse every intermediaries took into account both the concerns that treating each of six GSs as a separate class would require a very long experiment  and that having only three gradients-of-movement would not allow a gradual enough continuum between the CS+ and the CS−. Therefore, we chose to have three classes of intermediaries with two types of movements in each class to evaluate the generalization gradient. That way, each intermediary required only half as many trials  = 16.58, p < 0.001, and stimulus type, F = 16.69, p < 0.001. Interestingly, the stimulus type × group interaction was significant, F = 61.37, p < 0.001, indicating that startle responses to the different movements differed between the predictable and unpredictable group. As expected, planned comparisons revealed higher startle responses to the CS+ than to the CS− in the predictable group by the end of acquisition (ACQ2), F = 10.41, p < 0.01, while there was no such difference in the unpredictable group, F < 1  = 42.64, p < 0.001.Eyeblink startle responses during acquisition were analyzed using a 2 (Group: predictable vs. unpredictable) × 2 (Block: ACQ1 vs. ACQ2) × 3  mixed (RM) ANOVA. This analysis yielded significant main effects for block, F = 6.31, p < 0.05, and block, F = 26.18, p < 0.001. Both the block × condition, F = 6.00, p < 0.05, the stimulus type × block, F = 2.76, p < 0.05, as well as the stimulus type × condition, F = 2.61, p < 0.05, interactions were significant. The three-way interaction, however did not reach statistical significance, F < 1. Planned comparisons were used to further test our a priori hypotheses. In line with our expectations, there was a significant linear decrease, F = 7.18, p < 0.01, in the startle responses with decreasing GS similarity to the CS+ in the predictable condition, but not in the unpredictable condition, (F < 1). This generalization gradient was present in the first generalization block, but not in the second generalization block (both Fs < 1). During the first generalization block, startle responses were still significantly higher for the CS+ than for the CS− in the predictable group, F = 6.12, p < 0.05, but not in the unpredictable group, (F < 1), and this difference was no longer significant in the second generalization block (F < 1). Contextual pain-related fear appeared to be attenuated during the first generalization block, ITI startle responses tended to be higher in the unpredictable group compared with the unpredictable group but this difference was no longer statistically significant, F = 3.22, p = 0.08. During generalization block 2, however, this difference did reach statistical significance, F = 6.28, p < 0.05. This effect was largely driven by the further decrease in startle responding during the ITI in the predictable group. The generalization gradient was further supported by multiple planned comparisons (see Table We used a 2 (Group: predictable vs. unpredictable) × 2 (Block: G1 vs. G2) × 5 (Stimulus type: CS+ vs. class1 vs. class2 vs. class 3 vs. CS−) mixed (RM)ANOVA. This analysis showed main effects for group, F = 21.27, p < 0.001, and for group, F = 6.58, p < 0.05, the latter effect indicating that participants in the predictable group reported higher fear of movement-related pain compared to the unpredictable group. Of crucial importance, the stimulus type × group effect was significant, F = 60.71, p < 0.001. Planned comparisons at the end of acquisition (ACQ2) confirmed that participants in the predictable group reported significantly more fear of the CS+ compared to the CS−, F = 74.91, p < 0.001, while participants in the unpredictable group did not give differential fear ratings for both movements, F = 10.06, p = 0.07  × 2 (Block: ACQ1 vs. ACQ2) × 2 (Stimulus type: CS+ vs. CS−) F = 3.10, p < 0.05, was significant. There was also a significant main effect of block, F = 4.13, p < 0.05, indicating that the fear of movement-related pain ratings were declining across blocks. The stimulus type × block interaction effect, F = 4.65, p < 0.01, was significant, but the anticipated stimulus type × group interaction, F = 1.18, p = 0.32, and the three-way interaction did not reach statistical significance, F = 1.98, p = 0.10. Trend analysis further revealed a significant linear, F = 8.07, p < 0.01, and quadratic, F = 8.40, p < 0.01, in the predictable condition, but not in the unpredictable condition, . This trend was present in the first generalization block, but not in the second generalization block (both Fs < 1). During the first generalization block, fear of movement-related pain ratings were still significantly higher for the CS+ than for the CS− in the predictable group, F = 8.20, p < 0.01, but not in the unpredictable group, (F < 1), and this difference was no longer significant in the second generalization block (F < 1). These trends in the beginning of the generalization phase were further examined using multiple planned comparisons (see Table We performed a 2 (Group: predictable vs. unpredictable) × 2 (Block: G1 vs. G2) × 5 (Stimulus type: CS+ vs. class1 vs. class2 vs. class 3 vs. CS−) mixed (RM)ANOVA. The main effect of stimulus type, F = 11.52, p < 0.01, and a significant stimulus type × group interaction, F = 62.90, p < 0.001, indicating that US expectancy during the respective CS movements was different in both groups. In line with our expectations, participants in the predictable group expected the pain-US to occur more when they performed the CS+ movement than when performing the CS− movement, F = 64.13, p < 0.001. This difference also turned out to be significant in the unpredictable group, F = 10.29, p < 0.01, but to a much smaller extent.We performed a 2 (Group: predicable vs. unpredictable) × 2 (Stimulus type: CS+ vs. CS−) mixed ANOVA on the retrospective pain-US expectancy ratings  = 6.55, p < 0.05. More importantly, the stimulus type × group interaction, F = 17.55, p < 0.001, was significant. To break down this interaction, planned comparisons were calculated. As expected, participants were less happy when performing the CS+ movement compared to the CS− in the predictable group, F = 22.77, p < 0.001, while there was no such difference in the unpredictable group, F = 1.33, p = 0.25.A 2 (Group: predictable vs. unpredictable) × 2 (Stimulus type: CS+ vs. CS) mixed ANOVA was run on the SAM happiness ratings  with a pain-US relative to a movement that was never paired (CS−) with pain  approaching the original CS− in both measures. However, this trend was more pronounced in the startle measures than in the verbal fear ratings. Moreover, there was an additional quadratic decrease in fear responses for the generalization movements approaching the original CS− in the startle measures. These data seem to suggest that the linear trend in the verbal ratings is rather driven by the CS+ and CS− differences than by the gradual decline in conditioned responding in response to the GS movement classes based on their similarity with the CSs. This interpretation is further supported by the presence of the quadratic trend in the verbal ratings (which was not present in the startle data). These linear trends were only present in the first generalization block but not in the second. There are several explanations for the absence of the gradient in the second generalization block and the absence of a true gradient in the verbal ratings. The generalization test was performed under extinction, hence CSs and GSs were unreinforced during this phase. Under condition of extinction there might be a steady decline in fearful responding that already starts within a few trials. The verbal ratings were assessed retrospectively after each block, that is, after not less than 32 trials, therefore partial extinction probably already took place at the test of the first block. These extinction effects combined with ongoing discrimination learning (differences between the CS+/CS− and the GS movement classes) during the generalization phase might explain the absence of a gradient in the fear ratings. Although the CS+ are still higher than for the CS− and the GS classes during generalization, compared with the end of the acquisition phase, the fear ratings have significantly decreased (mean fear ratings CS+ during ACQ2 = 62.48 vs. mean fear ratings CS+ during G1 = 31.86 vs. mean fear ratings CS+ during G2 = 19.83) which supports our post hoc interpretation of combined extinction and ongoing discrimination learning during the unreinforced generalization phase. This is not the case for the startle measures, because probes are delivered throughout the generalization test providing a more online representation of the fear responses. In line with our post hoc explanation, the difference in fear reported to the CS+ and the CS− declined significantly from the end of acquisition to the first generalization block, F = 23.22, p < 0.001, whereas this decline was not the significant in the startle measures F = 1.33, p = 0.25. Follow-up studies might consider using a partial reinforcement scheme during generalization testing.Third, some procedural aspects deserve some more attention. For instance, another design feature that was different compared with the previous study by Meulders and Vlaeyen  because it is not just an inert cue, the movement is probably more salient which in turn leads to an advance in terms of cue competition predictable situations than men do , that is, more spreading of fear toward novel movements that are proprioceptively related to the original painful movement than to the ones resembling the non-painful movement. There was no such generalization gradient for contextual pain-related fear (unpredictable pain group). Taken together, this paradigm represents a novel tool to scrutinize the largely understudied phenomenon of fear generalization in patients with chronic musculoskeletal pain and mapping possible pathological differences in generalization gradients and the spreading of pain in patients as compared with healthy controls. Future research might focus on the conditions under which these generalization gradients can be broadened or reduced in order to develop new methods to limit the spreading of fear of movement in chronic pain patients. This line of research warrants further investigation, especially given the intriguing but untested idea that based on the close relationship between fear and pain, fear generalization might be associated with subsequent spreading of pain.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.


Bacillus sp.) were applied to aerobic rice. Total bacterial populations, amount of P solubilization, P uptake, soil pH, and root morphology were determined. The results of the study showed significantly high P solubilization in PSB with organic acid treatments. Among the two organic acids, oxalic acid was found more effective compared to malic acid. Application of oxalic acid at 20 mM along with PSB16 significantly increased soluble soil P (28.39 mg kg−1), plant P uptake (0.78 P pot−1), and plant biomass (33.26 mg). Addition of organic acids with PSB and PR had no influence on soil pH during the planting period. A higher bacterial population was found in rhizosphere (8.78 log10 cfu g−1) compared to the nonrhizosphere and endosphere regions. The application of organic acids along with PSB enhanced soluble P in the soil solution, improved root growth, and increased plant biomass of aerobic rice seedlings without affecting soil pH.A study was conducted at Universiti Putra Malaysia to determine the effect of phosphate-solubilizing bacteria (PSB) and organic acids  on phosphate (P) solubilization from phosphate rock (PR) and growth of aerobic rice. Four rates of each organic acid , and PSB strain ( Phosphate-solubilizing bacteria play a vital role in P solubilization by producing organic acids. Additionally, soils contain low molecular weight organic acids with one or more carboxylic groups and some of these acids like citrate, oxalate, acetate, malate, isocitrate, and tartrate. Plant root exudates and microorganisms produce organic acids and degrade complex organic molecules , 2. Orga2PO4−, and Ca2+ [ The PR is an alternative and natural source of P. The dissolution of P from PR is required for the availability of P. Many factors affect the dissolution of PR in soil such as, chemical composition, particle size of the PR, soil characteristics, pH, Hnd Ca2+ . Dissolund Ca2+ :(1)Ca10+) and the concentration of reaction products of Ca2+ and H2PO4. In acidic soils, improvement of P nutrition to plants by direct application of PR as P fertilizer has been considered [The equation specifies that the rate of dissolution is determined by the concentration of protons (Hnsidered . Phosphain vitro condition. PSB16 (Bacillus sp.) isolated form aerobic rice rhizosphere [in vitro condition. The isolated strain was identified using 16S rRNA gene sequencing with accession number JX103827. Four rates each of oxalic and malic acids  and PR (Christmas Island Rock Phosphate) at 60 kg P2O5 ha−1 were applied. The aerobic rice (var M9) was grown in the growth chamber for 40 days. Total bacterial populations, P solubilization, soil pH, root morphology, and agronomic parameters were recorded after 40 days of growth. The experiment was conducted under zosphere , which w9 mL−1 of live washed bacterial cells of Bacillus sp. (PSB16) were used as inoculum in each bacterial treatment. The surface sterilized seven days old seedlings were transplanted into pots containing sterilized soil (500 g) with 4 uniform seedlings per pot. Plants were grown for 40 days in a growth chamber with 12 h light/dark cycle at 29 ± 1°C temperature. Approximately 5 × 10The total bacterial population was determined from rhizosphere, nonrhizosphere, and endosphere of aerobic rice plants. After harvest, soil available P was determined using Bray 2  and tota2), and root volume (cm3) were quantified using a scanner  equipped with a 2 cm depth plexiglass tank (20 × 30 cm) filled with UP H2O [The root length (cm), total surface (cmP < 0.05).The experiment was conducted with the three factors in four replicates in a completely randomized design. Data obtained were statistically analyzed using the SAS software program (Version 9.2), and treatment means were compared using Tukey's test  was found in PSB inoculated treatments with 20 mM oxalic acid . −1) was observed with 10 mM of malic acid in PSB inoculated treatments  followed by 30 mM (0.75 P pot−1) concentrations, respectively.  The application of organic acids also affected plant P uptake. Significantly higher plant P uptake was observed in PSB inoculated treatments added with organic acids . Among bP < 0.05) higher populations were found in the rhizosphere (8.78 log10 cfu g−1), while lower populations were found in nonrhizosphere soils (5.40 log10 cfu g−1). The highest rhizosphere population (8.65 log10 cfu g−1) was found in the 30 mM oxalic acid treatment , whereas, in nonrhizosphere soil the highest population was recorded at 10 mM acid without PR (6.54 log10 cfu g−1). However, the endosphere population was not influenced by the addition of organic acids  high values of plant height were observed in the PSB inoculated treatments. Among both acids, the highest plant height (23 cm) was observed in oxalic acid (20 mM) with PR and PSB16, compared to malic acid  higher root length (7.64 cm), root surface area (2.36 cm2) and root volume (0.11 cm3) were found in oxalic acid at 20 mM with PR and PSB16 inoculated treatments  have been proven to solubilize PR with many organic acids [The bacterial population was influenced with the addition of organic acids. The population was varied in both organic acids at different rates in plant rhizosphere and non-rizosphere population. Thus, it might be due direct contact of the acids in soil and could be able to perform prominently for the P solubilization. Moreover, solubilization of P by PSB in the rhizosphere is a continuous process. PSB solubilize insoluble P by several mechanisms such as acidification, chelation, and exchange reactions . It was ic acids . The relic acids . The changes in PSB population occurred mostly in the nonrhizosphere region, and it becomes lower with the addition of oxalic acid treatments. This could happen due to the transfer of bacteria from the nonrhizosphere to the rhizosphere zone, as the rhizospheric zone is a source of organic carbon which is needed for microbial activity. Cannon et al.  pointed The organic acids with PSB16 and PR increased the plant biomass. Besides P solubilization activity, PSB liberates phytohormone (IAA) that might have an influence on root growth. The extensive root system increased nutrient uptake from the surroundings which increased plant biomass . The orgThe application of organic acid, PSB16, and PR slightly affected the soil pH values. This could be due to the soil buffering system, and it did not affect much the change of soil pH. The slight reductions were observed in the rhizosphere, that could be due to the influence of organic acid applications. These results are consistent with the findings of Zeng et al.  who repoThe plant root development in aerobic rice was affected by the application of organic acids, PSB, and PR. External application of organic acids along with PSB enhanced soluble P in the solution and this had a positive impact on root growth. These results are in agreement with the findings of Srivastava et al.  who repoThe application of organic acids and PSB16 showed differences in P solubilization from PR. Among both acids, oxalic acid showed better results when compared to malic acid. The PSB16 population and soil pH were not affected by the application of organic acids. Application of oxalic acid at 20 mM along with PSB16 significantly increased soluble P release from PR. In conclusion, addition of organic acids with PSB increased the solubility of PR and had a significant effect on the growth of aerobic rice. However, at the higher concentration of oxalic acid application may present a health risk, especially for children.


With the Convulsive Status Guidelines due for renewal, we wondered if a phenytoin dose of ‘20 mg/kg’ would be easier to calculate correctly and therefore safer than the current ‘18 mg/kg’. An educational exercise in dose calculation was therefore undertaken to assess ease of calculation.A standard question paper was prepared, comprising five clinical scenarios with children of varying ages and estimated body weights. Medical students, trainee doctors at registrar and senior house officer level, and consultant paediatricians were asked to complete the exercise, in private, by one of two medical students . Calculations were done with and without a calculator, for 18 mg/kg and for 20 mg/kg in randomised order. Speed and errors (greater than 10%) were determined. The data analysis was performed using SPSS version 18.All answered all 20 scenarios, giving a total of 300 answers per doctor/student group, and 300 answers per type of calculation. When comparing the 2 doses, the numbers of errors more than 10% were significantly less in 20 mg/kg dose (0.33%) as compared to the 18 mg/kg dose (9.3%) (p<0.0001). Speed off calculation was significantly decreased in 20 mg/kg dose when compared with 18 mg/kg dose, with (p<0.001) or without (p<0.0001) the calculator. Speed was more than halved and errors were much less frequent by using a calculator, for the 18 mg/kg dose but no difference with or without the calculator for 20 mg/kg dose.We recommend that the future guidelines should suggest iv Phenytoin at 20 mg/kg rather than 18 mg/kg. This will make the calculation easier and reduce the risk of significant errors. With the convulsive status epilepticus in children guideline due for renewal, we wondered if a Phenytoin dose of ‘20 mg/kg’ would be easier to calculate correctly and therefore safer than the previously recommended ‘18 mg/kg’ dose. An educational exercise in dose calculation was therefore undertaken.Convulsive status epilepticus (CSE) is defined as a continuous or recurrent convulsive seizure with loss of consciousness lasting 30 minutes or more, or a cluster of repeated convulsions during which consciousness is not regained, lasting 30 minutes or more . CSE in Data from epidemiological studies suggest that four to eight children per 1000 may be expected to experience an episode of CSE before the age of 15 years , and in iv) infusion over 20 minutes as a third line treatment if other treatments  had failed to control the seizure [The 2000 guideline by the ‘Status Epilepticus Working Party’ for treating and preventing status epilepticus by treating prolonged convulsive seizures (lasting more that 5 or 10 minutes) in children in the UK, advised infusion of 18 mg/kg of Phenytoin by slow intravenous  level, and consultant paediatricians were asked to complete the exercise, confidentially, anonymously, in private, as an educational exercise, by one of two medical students .Calculations were done with and without a calculator, for 18 mg/kg and for 20 mg/kg in randomised order. Speed was recorded with a stop watch, and errors were determined. For our exercise, only calculation errors of greater than 10% different from the correct dose were counted as significant errors.The whole exercise took 5–10 minutes of the student’s or doctor’s time.post hoc analysis using Dunnett C test  was performed for normally distributed data when comparing effect of level of seniority on time taken to calculate. The categorical data was analysed using Fischer’s exact test and p values below 0.05 were taken as significant.The data analysis was performed using SPSS version 18 . Continuous variables were tested for normality using Kolmogrov-Smirnov test and Wilcoxson signed rank test was used for paired data when not normally distributed. One way ANOVA with This was not experimental research, this was an educational exercise, so no ethics committee approval was required and no written consent was obtained,Data was collected from the 20 scenarios as completed by 15 consultant paediatricians, 15 registrars, 15 SHOs, and 15 medical students. All answered all 20 scenarios, giving a total of 300 answers per doctor/student group, and 300 answers per type of calculation  and SHO’s (p = 0.006)  Figure . There wWhen comparing the 2 doses, the numbers of errors more than 10% were significantly less for the 20 mg/kg dose (0.33%) compared to the 18 mg/kg dose (9.3%)  when not using the calculator. The odds ratio for making a significant error is 30.77 with increased risk for the 18 mg/kg calculation. There was no significant difference in the significant error rate when using a calculator.When using the 18 mg/kg dose, using a calculator significantly decreased the significant error rate from 9.3% to 0.66% (p < 0.001). The odds ratio of making an error while calculating the 18 mg/kg dose without a calculator was 15.38 as compared to when using a calculator.vs. 0.3%), in fact, with the 20 mg/kg dose, the significant error rate was less without a calculator.For the 20 mg/kg doses, there was no difference in significant error rate with or without a calculator  or without  a calculator.vs. 18.0 seconds) which is statistically significant , however for the 20 mg/kg dose there was no significant difference in time taken with (median 6 seconds) or without (median 4 seconds) the calculator. In fact the speed was quicker without the calculator for the 20 mg/kg dose.For the 18 mg/kg doses, speed of calculation was better than halved by using a calculator . According to Pfizer the dose of 18 mg/kg quoted was derived from numerous clinical pharmacology studies (dose response studies) along with safety data from their phase 3 clinical programme.We contacted Pfizer pharmaceutical company which now owns Parke-Davis who initially marketed EPANUTINIntravenous Phenytoin infusion can sometimes cause adverse cardiovascular effects, including bradycardia or hypotension ; hence iiv Phenytoin for the management of children with prolonged seizures. To the best of our knowledge there have been no reports suggesting an increased risk of adverse effects with the 20 mg/kg dose compared with 18 mg/kg dose.It is well known that many hospitals’ local guidelines advocate 20 mg/kg for For this educational exercise, only calculation errors greater than 10% different from the correct dose were counted as significant errors.The significant error rate was considerably lower and the speed much quicker for calculating 20 mg/kg dose when compared with the current recommended dose 18 mg/kg dose, without a calculator .The exercise demonstrated that doctors and medical students will make errors in simple dose calculations in at best 0.3-1% of calculations even with a calculator. These errors may be higher in the real life scenarios as managing status epilepticus is a medical emergency which can be stressful, making us more prone for errors. This underlines the importance of checking all dose calculations. The longer time taken to calculate 18 mg/kg than 20 mg/kg reflects the increased difficulty of the calculation without an electronic calculator, and while many doctors and nurses in emergency health care settings have their personal calculators to hand, when a calculator is not immediately to hand, trying to find one will add to delays and stress. Furthermore, it is good practice when using a calculator to mentally check the result to see if it is “ball-park” correct, in case of a typing error, such as a misplaced decimal point that could lead to a ten-fold dosing error.iv Phenytoin dose calculation difficulties and minimise the risk of errors and therefore recommend 20 mg/kg.We propose that new status epilepticus guidelines should make an attempt to minimise iv Phenytoin, replacing the previously recommended dose of 18 mg/kg [In the latest edition of ‘Advanced Paediatric Life Support’, the status epilepticus algorithm now advises 20 mg/kg 18 mg/kg .iv Phenytoin at 20 mg/kg rather than 18 mg/kg. This will make the calculation easier and reduce the risk of significant errors. Ease of dose calculation without an electronic calculator should be taken into account when making recommendations for drug doses in children, especially those to be used in emergency situations. All dose calculations should be checked.Medication errors are common and children are at particular risk. We recommend All the authors declare that they have no financial and no non-financial competing interests.WPW and VS conceived and planned the excersise, PS and SD undertook the dose calculation educational exercises with the volunteers, collected the data and made preliminary analyses. VS, WPW, PS, SD completed the analyses and MP, SD and WPW undertook the literature review. All the authors contributed to drafting the paper. All authors read and approved the final manuscript.The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1471-2431/13/60/prepub


Objective. To evaluate bacterial growth inhibition, mechanical properties, and compound release rate and stability of copolymers incorporated with anthocyanin . Methods. Resin samples were prepared (Bis-GMA/TEGDMA at 70/30 mol%) and incorporated with 2 w/w% of either ACY or chlorhexidine (CHX), except for the control group. Samples were individually immersed in a bacterial culture (Streptococcus mutans) for 24 h. Cell viability (n = 3) was assessed by counting the number of colony forming units on replica agar plates. Flexural strength (FS) and elastic modulus (E) were tested on a universal testing machine (n = 8). Compound release and chemical stability were evaluated by UV spectrophotometry and 1H NMR (n = 3). Data were analyzed by one-way ANOVA and Tukey's test (α = 0.05). Results. Both compounds inhibited S. mutans growth, with CHX being most effective (P < 0.05). Control resin had the lowest FS and E values, followed by ACY and CHX, with statistical difference between control and CHX groups for both mechanical properties (P < 0.05). The 24 h compound release rates were ACY: 1.33 μg/mL and CHX: 1.92 μg/mL. 1H NMR spectra suggests that both compounds remained stable after being released in water. Conclusion. The present findings indicate that anthocyanins might be used as a natural antibacterial agent in resin based materials. Caries is an endogenous infection that causes lesions in enamel, cementum, and dentin by the action of carbohydrate-rich diet associated with bacteria able to produce, by glycosyltransferase enzyme, insoluble bioadhesive polysaccharides . It mediVaccinium macrocarpon) juice or extracted from cranberry fruit have been established. It has been demonstrated that cranberry polyphenols have the ability to decrease the cell surface hydrophobicity of streptococcal bacteria (S. sobrinus and S. mutans) [S. sobrinus to enamel-like structures coated with saliva [S. mutans in vitro and dental caries development in vivo (Sprague-Dawley rats) has also been reported [Aggregatibacter actinomycetemcomitans, a causative agent involved in periodontal disease. Their results also showed that the cranberry extract inhibited the catalytic activity of both enzymes and elastase. As dentinal proteases are believed to play an important role in the progression of carious lesions, inhibition of MMPs such as MMP-9 might also help preventing caries progression [In recent studies, some benefits related to polyphenols in cranberry ( mutans)  and adhe mutans)  and enam mutans) . Other sh saliva , but alsh saliva . More rereported . Moreovereported  reportedgression .S. mutans), mechanical properties, and compound stability of a dental resin incorporated with an ACY-rich cranberry extract. Resins containing CHX will be also evaluated as a control.Most studies that evaluated the effects of cranberry polyphenols on cariogenic bacteria and MMP activity used a fraction of cranberries called the nondialyzable material (NDM), which is obtained by dialysis of concentrated cranberry juice , 10, 12.S. mutans UA159 strain isolated from a child with active caries was used in this study [S. mutans was cultivated in Brain Heart Infusion (BHI) broth at 37°C in air with 5% CO2. BHI broth agar plates were prepared using 1.5% (w/v) agar. Bis-GMA, TEGDMA, the photosensitizer camphorquinone (CQ), reducing agent 2-(dimethylamino)ethyl methacrylate (DMAEMA), cranberry ACY , and CHX diacetate salt hydrate  were all used as received.n = 3) except flexural properties (n = 10), specimens were fabricated inside an acrylic matrix with internal dimensions of 5 mm diameter × 3 mm height. For flexural properties, specimen dimensions were 2 mm width × 2 mm height × 25 mm length. Unpolymerized material was sandwiched between two polyester strips over a glass-mixing tablet. Polymerization was done on both sides by a visible light curing unit  for 40 s delivering uninterrupted 540 mW/cm2, verified by a radiometer . A UV-Vis Spectrophotometer  was used to evaluate the compound release rates of all groups in triplicate after 24 h water storage (maximum absorption peaks were ACY: 522 nm and CHX diacetate: 257 nm).The experimental resin formulation was prepared combining Bis-GMA at 70 mol% and TEGDMA at 30 mol%. Except for the control group (no compounds added), each formulation was randomly mixed with either ACY or CHX at 2 w/w% comprising a total of 3 groups. Comonomers were activated for visible light polymerization by the addition of CQ and DMAEMA (0.2 w/w% each). For all tests (S. mutans UA159 were diluted (1 : 20) into 1.0 mL of fresh BHI broth followed by addition of one resin sample per test tube. The reaction mixtures were incubated at 37°C for 24 h under constant agitation. The next day, the cells were sonicated and aliquots of 20 μL of each test tube plated on BHI agar for CFU determination. The colonies were counted after 48 h of incubation. The percentage of cell survival corresponded to the number of viable cells after treatment divided by the total number of viable cells in the untreated sample.Overnight cultures of After polymerization, specimens were finished and individually stored in deionized water at 37°C for 24 h prior to testing. The flexural properties were evaluated by a three-point bending test  at a cross-head speed of 0.5 mm/min. Flexural strength was obtained by measuring the load at fracture, and the elastic modulus was calculated from the recorded load-deflection curves .1H NMR spectra were collected for the compounds alone and extracted from resin in deionized water (after 24 h), followed by lyophilization, from the loaded copolymers for analysis of compound stability [2O. In these spectra, signal intensity is plotted versus the chemical shift, measured in ppm.Single-resonance, tability . The speα = 0.05.Data for bacterial viability assay, flexural strength, and elastic modulus were evaluated by one-way ANOVA followed by Tukey's post hoc test at μg/mL for ACY incorporated resin and 1.92 ± 0.4 μg/mL for CHX incorporated resin. The bacteria viability assay for ACY or CHX containing resins is represented in P < 0.05). Mean FS and E values are shown in E values, followed by ACY and by CHX. The values between control and CHX groups were statistically different for both properties (P < 0.05).The 24 h mean drug release rates in deionized water were 1.33 ± 0.0 1H NMR spectra, the signals for ACY and CHX (After the assessment of  and CHX  have beeEscherichia coli bacteria [Helicobacter pylori) [Anthocyanins are plant extracts widely found in many berries, dark grapes, cabbages, and other pigmented plants. Chemically, they belong to a widespread class of phenolic compounds collectively named as flavonoids. The differences between individual anthocyanins are related to the number of hydroxyl groups in the molecular structure as well as the nature and number of sugars and the position of these pendent molecules , 19. Manbacteria , 21 and, pylori)  as well  pylori) .S. mutans, although with far less effectiveness when compared to CHX. Differences in results are likely related to several factors, for instance, the purity of compound, as the ACY used in this study is only 25% pure  as compared to 100% purity of CHX. The amount of drug released is another important aspect to be taken into consideration as higher values were obtained for CHX. Additionally, previous results [μg/mL and 2 μg/mL, resp.; nonpublished data), which may explain the pronounced S. mutans growth inhibition.The present results support previous findings on antibacterial property of cranberry extracts , 10, 11. results  have shoThe incorporation of both compounds had apparently a reinforcing effect on resins leading to higher flexural strength and modulus property. The ACY group values did not, however, statistically differ from any of the remaining groups. A decrease in resin conversion has very likely played a role in the mean values of ACY mechanical properties, as the cranberry polyphenols are naturally pigmented in red color which affects translucency and polymerization light propagation through the resin sample .1H NMR [1H nuclei) in the sample resonate at different frequencies because they are shielded more or less by the electrons that surround them. The NMR spectrum is treated like a fingerprint of the chemical structure of the molecule. The strong line at ∼4.65 ppm (Figures In this study, the stability of released compounds into aqueous media was chosen to be analyzed by 1H NMR . In thes Figures  as compaThe present findings indicate that anthocyanins might be used as a natural antibacterial agent in resin based materials.


Nelumbo nucifera) are hampered by an inability to account for variation in seed set associated with crosses between different cultivars. We studied seed set in two reciprocal crosses between lotus cultivars (‘Guili’ × ‘Aijiangnan’ and ‘Molingqiuse’ × ‘Qinhuaiyanzhi') to obtain insights into factors that govern fecundity in these experimental hybrids. Pollen viability, stigma receptivity and embryo development were compared for each hybrid and reciprocal cross.Breeding programs for the water lotus  for all cultivars observed from the earliest collected grains (05:00–06:00 a.m.). Stigmatic pollen germination peaked at 4 h after pollination and varied from 4.8 to 60.6 grains per stigma among the crosses. Production of normal embryos ranged from 7.6% to 58.8% at 1 d after pollination and from 0 to 25% by 11 d after pollination. Seed set in crosses (0.2–23.3%) was generally lower than in open-pollinated plants (8.4–26.5%). Similar to the germination results, seed set was substantially reduced in both reciprocal crosses.These results suggested that poor pollen fertility, low stigma receptivity, and embryo abortion were responsible for the failure of the crosses ‘Molingqiuse’ × ‘Qinhuaiyanzhi’, ‘Qinhuaiyanzhi’ × ‘Molingqiuse’, and ‘Aijiangnan’ × ‘Guili’. Nelumbo nucifera Gaertn. and N. lutea (Willd.) Pers. Nelumbo nucifera, also called the Indian or sacred lotus, is found throughout Asia and Australia, whereas N. lutea, also known as the American lotus or water chinquapin, occurs in eastern and southern North America [N. nucifera show that wild populations were distributed previously in eastern Asia including China, India and Japan about 50 million years ago. Wild populations of N. nucifera in China are now mainly distributed in the provinces of Helongjiang, Jilin, and Sandong. Nelumbo nucifera was cultivated in China more than 2000 years ago. The current main cultivation areas in China comprise the provinces of Jiangsu, Zhejiang, Hubei, Anhui, Guangdong, Hunan, Fujian, and Jiangxi. This species is propagated vegetatively by rhizomes in commercial cultivation, and by seeds for breeding purposes [N. nucifera cultivars are classified into three groups: rhizome lotus, seed lotus and water lotus or ornamental lotus according to their use and morphological features [The Nelumbonaceae is a family of perennial, aquatic, herbaceous angiosperms, consisting of the two species  America ,2. Fossipurposes . As an efeatures ,5. Waterfeatures ,7. With features . HybridiChrysanthemum grandiflorumLeymus chinensisPhaseolus vulgaris, and Fragaria ananassa[In general, the characteristics of parental reproductive systems and their interactions are closely related to the breeding efficiency of plant hybridization. Consequently, parental reproductive systems and post-pollination phenomena have been examined in many crops, including  ananassa-13. MostN. nucifera flowers is shaped like a flat-topped cone and contains 20–35 ovules when fully developed. Surrounding the pistil are 200–300 yellow stamens, and both the male and female reproductive organs are protected by 10–35 petals and sepals. Anthesis of individual flowers usually lasts about three days on sunny days. On the first day, the flower begins to open at about 03:00 in the morning and attains its maximum diameter (about 6 cm) at about 05:30. The flower remains at this diameter until about 09:00, after which the flower gradually closes and is completely closed at about 15:00. Substantial fluid is secreted on the stigma surface from 04:00 to 06:00 and the stigma is a bright yellow color, which indicates that the stigma receptivity is high during this period. The anthers do not dehisce on the first day, therefore the pistils mature before the stamens in an individual flower (termed ‘protogyny’). On the second day of anthesis, the process of flower opening is very similar to that on the first day and a maximum diameter of about 10 cm is attained. The anthers dehisce to release quantities of mature pollen from about 04:00 to 05:30. The stigma surface becomes dry and brown, which indicates the loss of stigma receptivity. On the third day of anthesis, the flower begins to open at about 05:00 and is fully open with a maximum diameter of more than 12 cm in diameter at about 10:00. Subsequently, the petals and stamens abscise. The stigma becomes severely dry and brown, and its receptivity is completely lost. An individual flower usually produces about one million pollen grains. Thus the pollen:ovule ratio (P/O) is 30,000-50,000.The cultivars used in the present study were developed about 10 years ago through cross-breeding. Anthesis of lotus flowers is very specific and complex. The pistil of The study site is about 33 hectares in area and contains many pools. Many lotus cultivars, including the four included in the present study, were planted in the pools. Therefore, all of the lotus cultivars growing in at study site were possible sources of pollen for “naturally pollinated flowers” in the present study. Bees, flies and beetles may be effective pollinators at the study location.N. nucifera ‘Guili’ (pollen receptor) ×  N. nucifera ‘Aijiangnan’ (pollen donor) (hereafter referred to as GA), N. nucifera ‘Aijiangnan’ (pollen receptor) ×  N. nucifera ‘Guili’ (pollen donor) (AG), N. nucifera ‘Molingqiuse’ (pollen receptor) ×  N. nucifera ‘Qinhuaiyanzhi’ (pollen donor) (MQ), and N. nucifera ‘Qinhuaiyanzhi’ (pollen receptor) ×  N. nucifera ‘Molingqiuse’ (pollen donor) (QM). About 100 plants of each cultivar were grown in pools in Nanjing Yileen, Zhujiang town, Pukou district, Nanjing, China . The four cultivars are diploid and have a chromosome number of 16 (2 n = 2 x = 16). These specific cultivars were selected for two main reasons. First, the ornamental values of ‘Aijiangnan’ and ‘Guili’ are complementary, for example the flower color of ‘Aijiangnan’ is butter-yellow and that of ‘Guili’ is pink. If these two cultivars can be crossed successfully, it should be possible to obtain genotypes with novel traits. This is also the case for ‘Molingqiuse’ and ‘Qinhuaiyanzhi’. Second, our preliminary studies indicated that seed set differed among these crosses, which motivated us to examine the factors that influence the fecundity of these crosses. In the present study, flowers from multiple plants of each cultivar were used, because one plant was unable to produce a sufficient number of flowers for the present experiment. However, within each cultivar the plants had an identical genetic background, because they were propagated vegetatively from rhizomes. In addition, before we formally carried out the present study, we performed preliminary tests to examine if there was a significant difference in behavior between flowers from the same plant and between flowers those from different plants within a given cultivar. No significant differences were observed.Two reciprocal crosses  were performed using four cultivars of water lotus, i.e. Previous studies have shown that lotus pollen is only viable for a few hours after anther dehiscence and that it is difficult to determine lotus pollen viability . In the Lotus plants are insect-pollinated and the pistil matures one or two days before stamen maturation. In order to prevent insect pollination in the present study, we bagged the flowers of the female parents before the pistil matured. The optimal time for pollination is 05:00 to 08:00 on a sunny day. The pollen grains from 20 bagged male flowers from five plants (four flowers per plant) were collected between 05:00 and 06:00, and used for artificial pollination once the female flowers opened and their stigma surface was coated with bright yellow mucus. We used 150–200 flowers from about 50 plants as the pollen receptor for each cross. The immature stamens of the pollen-receptor flower were first removed, and then the stigmas were pollinated with the freshly collected pollen grains. After artificial pollination, the pollinated flowers were bagged again.-1 NaOH, rinsed in water and mounted on a microscope slide with a drop of 0.1% aniline blue (0.1 mol l-1 K3PO4 supplemented with 18% glycerol), and then observed under a fluorescence microscope (Zeiss Axioskop 40) with a BP 395-440 excitation filter BP 395-440, FT 460 chromatic beam splitter, and LP 470 barrier filter. Digital images were captured with an Axiocam MRC camera [Pollen germination on the stigma in vivo was investigated as described by Sun et al.  with minC camera . In addiC camera .About 80 ovaries (or seeds) were collected from 10 flowers on five plants (two flowers per plant) for each pollination treatment at both 1 and 2 days after pollination and immediately immersed in FAA until use for examination of embryo development. The ovules were dissected from the ovaries and dehydrated through an alcohol series , then infiltrated with xylene, and embedded in paraffin wax . SectionAmong the pollinated flowers, we chose 30 flowers from 10 plants to determine seed set in each cross at 1 month after pollination. Seed set was calculated using the formula: seed set =  × 100% . The crot-test with α = 0.05 (the type I experimentwise error rate). The data are presented as the mean value ± standard deviation.The data were subjected to a one-way analysis of variance using SPSS 16.0 . The means were compared using the Bonferroni The time of pollen grain collection had a significant effect on pollen viability Table . The viaN. nucifera flowers after pollen grains have landed on the stigma. In other words, pollen grains germinate quickly after they are deposited on the stigma. In general, most of the pollen grains germinated and their pollen tubes penetrated the stigmatic surface and grew towards the ovaries within 4 h. After fertilization of the ovules, the stigmas quickly become dry, which will render pollen tubes on the stigma fragile. Pollen tubes on stigmas collected at 8 and 12 h after pollination were increasingly fragile, thus they were more easily washed away during the processes of fixation in FAA, softening in 1 N NaOH, and washing in distilled water. As a consequence, the number of pollen tubes on the stigma decreased after 4 and did not remain constant in the present study.In the four crosses, the number of germinated pollen grains on each stigma increased during the 4 h after pollination; the highest number was attained 4 h after pollination, and thereafter gradually decreased. For example, 60.6, 25.8, 10.0 and 4.8 germinated grains per stigma were recorded 4 h after pollination in GA, AG, MQ and QM, respectively . Seed set of most female parents under open-pollination conditions was higher than that in the corresponding cross. Our observations indicated that bees, flies and beetles may be effective pollinators because they were the most frequent floral visitors. Seed set for G, A, M, and Q under open-pollination conditions was 26.5%, 34.9%, 11.5%, and 8.4%, respectively , and seed set in GA was 2.53–fold higher than that in AG. The reasons for the differences in pistil receptivity in one reciprocal cross remain unclear.In this paper, we carefully studied the factors that govern fecundity in two lotus reciprocal crosses. Three findings in the present study are of note: i) low pollen viability impacts on seed set in water lotus crosses; ii) low stigma receptivity is a vital factor leading to low fecundity of water lotus crosses; and iii) embryo abortion is an additional factor leading to reduced fecundity of lotus crosses. However, the mechanisms involved in low stigma receptivity and embryo abortion remain unknown, and further studies are required to better understand these factors in water lotus, and indeed in other plants as well.NJT, WMF and FDC designed the experiments. NJT, WYL, and CQS performed the experiments and analyzed the data. NJT, YLW, WMF and FDC wrote and revised the manuscript. All authors read and approved the final manuscript.


Self-regulatory behaviour refers to both controlled and automatic processes. When people are distracted, automatic over controlled processes prevail. This was analysed with regard to nutritional behaviour  in situations of low or high distraction.A self-concept Implicit Association Test (IAT) was adapted to assess the implicit associations of self (vs. other) with healthy  food. Explicit preferences for healthy and unhealthy food and the diet’s healthiness were measured by self-report. Both implicit and explicit measures were used as predictors of nutritional behaviour. Among 90 undergraduates, the choice of fruit versus snack in a food choice task (low distraction) and the amount of mineral water and soft drinks consumed in a taste comparison task to cover liquid intake (high distraction) were observed.In the low distraction situation, food choice was predicted solely by explicit measures. Fruits were chosen less, when unhealthy foods were explicitly liked. In the high distraction situation, mineral water intake was predicted solely by the IAT. Participants implicitly associating themselves with healthy foods drank more mineral water than those implicitly associating themselves with unhealthy foods.Nutritional behaviour is influenced by both automatic and controlled processes depending on the available capacity for self-regulation. Explicit, or controlled, and implicit, or automatic processes are seen as basic determinants of human behaviour e.g., , 2). The. The2]).Whereas explicit attitudes and intentions  as determinants of controlled processes can be assessed by direct measures such as self-reports, implicit attitudes and self-concepts as determinants of automatic processes can be assessed indirectly by measures of association strength. A prominent implicit measurement tool is the Implicit Association Test . Mai. Mai19])A number of studies have been conducted to test the predictive power of implicit attitudes (assessed by the IAT) and explicit attitudes (assessed by self-reports) towards specific behavioural food choices e.g., , 21, 22), 2221, 2Based on dual-process models , IAT meIn nutrition research with the IAT, previous research has mostly relied on attitude IATs that combine a  concept classification  with an attribute classification representing positive versus negative valence . An alternative may be self-concept IATs that combine the contrast of self versus other with a nominal contrast . According to Olson and Fazio , the staIn the present study, a self-concept IAT was used as an implicit measure of automatic processes in addition to explicit measures of controlled processes to predict health-related nutritional behaviour in two situations that varied in the degree of attention absorption . A food choice task of fruits versus snacks (low distraction) and a task on comparing the tastes of water and soft drinks (high distraction) were administered. The food chosen in the low distraction task and the amount of mineral water and soft drinks consumed in the high distraction task served as the behavioural measures to be predicted. Thus, as an extension of previous studies, in the present study distraction was an integral part of the task itself to absorb attention and impair controlled processing. Moreover, Friese et al. , p. 405 M = 21.56, SD = 3.83). Their body mass index  ranged between 17.2 and 35.9 kg/m2 . Eleven percent of the sample were underweight (i.e. definition of BMI < 18.5 kg/m2), 76 % were of normal weight (BMI ≥ 18.5 and < 25 kg/m2), 9 % were overweight (BMI ≥ 25 and < 30 kg/m2), and 3 % were obese (BMI ≥ 30 kg/m2).A total of 90 undergraduate students (79 women and 11 men) were recruited on campus during the orientation days of the semester. Their ages ranged between 19 and 38 years . Finally, a behavioural food choice between fruits and snacks was presented to the participants. In this task, participants were shielded from possible distractions (low distraction situation).The study was conducted according to the ethical guidelines of the German Psychological Society and of the Declaration of Helsinki. The project was approved by the Research Ethics Committee of the University of Education Schwäbisch Gmünd. On the monitor, prior to starting the Nutrition IAT, participants were informed that beginning the task would be taken to indicate consent to participate.not at all = 1 to very much = 4. In addition, participants rated their preferences for six unhealthy and six healthy foods . Food items were taken from the Nutrition IAT described below. The internal consistency for the preference for healthy food was α = .69, and that for the preference for unhealthy food was α = .52.The participants indicated the healthiness of their diets with one item  and unhealthy food items .The present study’s Nutrition IAT integrated a self-concept measure using the categories of self versus other (see ) rather man; see ). The str = .86.The Nutrition IAT was administered on a laptop computer with the programme Inquisit 3.0.4 . The IAT procedure consisted of seven blocks . In the Food choice (low distraction situation): At the end of the session, the participants were offered a selection of fruits  and snacks , in each case approximately hand-sized. They were asked to choose something (one piece) as a small reward for their participation. Their choices were coded as 1 = fruit and 0 = snack. The choice of fruit was regarded as healthy behaviour, whereas the choice of a snack was regarded as unhealthy behaviour. Three female participants did not take either fruit or a snack. Thus, all analyses relating to the food choice were calculated without the data of these three participants.not at all to 6 = very much the extent to which you like the drink.”) was used. After the test, the liquid left in each cup was taken to another room and weighed by another experimenter. Thus, for the participants, the taste rating was the task. They were uninformed that the liquid left in each cup was being used to calculate their intake of each beverage.Liquid intake in the taste comparison task (high distraction situation): Four transparent cups, each filled with 155 g of drink , were used for the taste comparison task to cover liquid intake. The participants were instructed to taste each of the four drinks and to rate their tastes to absorb their attention. They were given 9 min. A liquid taste evaluation questionnaire with four adjectives  and an overall taste assessment  increase in R2 change after the last block was entered.The associations between the variables were analysed using zero-order correlations. In addition, we applied regression analyses using hierarchical entry procedures (forced entry) to evaluate the extent to which gender and age (variable Block 1), the three self-report measures healthy diet, preference for healthy food, and preference for unhealthy food (variable Block 2), and the Nutrition IAT (variable Block 3) contributed to the variance in each of the behavioural measures. Final equations were defined by a significant  = 0.70, p = .41, Eta2 = .008. Therefore, healthy and unhealthy IAT stimuli are assumed not to mainly reflect positive  versus negative  stimuli for the participants.Preferences for healthy food and unhealthy food with food items taken from the Nutrition IAT were analysed by a MANOVA with category  as the within-subject factor and gender and age as control factors. No significant effect for category was obtained, Wilks-Lambda = .99, r = .32) and negatively with the preference for unhealthy food (r = −.25). There was no statistically significant relationship between the preferences for healthy and unhealthy food. With the exception of one positive correlation of r = .41 between healthy diet and age, the self-report measures did not have statistically significant associations with gender or age  = 9.85, p < .001. This result indicates that the participants associated themselves more with healthy than with unhealthy food items. The IAT effect did not show significant associations with gender or age  less frequently than snacks (62 %). Our analyses revealed no significant effects for gender or age.r = .64, after controlling for gender: rp = .46, p < .001). With regard to gender and age, the results show that women generally drank less mineral water (r = −.27) and soft drinks (r = −.44) than men. The older participants drank more mineral water than the younger participants (r = .28).Mineral water intake ranged between 0 and 152.9 g, with a mean of 49.8 g, and the intake of each of the soft drinks varied between 0.6 and 152.1 g, with a mean intake of 38.5 g averaged across the three soft drinks. We obtained a general score of preference for mineral water over soft drinks by subtracting the mean soft drink intake from that of mineral water (range from −85.07 to 134.17). The mineral water intake was positively associated with the soft drink intake . In addition, they reported liking healthy food (r = .25) and disliking unhealthy food (r = −.34). Finally, there was no statistically significant relationship between food choice and the Nutrition IAT (r = .11).In the food choice task (low distraction situation), the associations between the three self-report  measures of healthy diet and preferences for healthy and unhealthy food with food choice were statistically significant. Participants who chose fruit instead of a snack reported healthier diets (rs = .30). Participants who drank absolutely or relatively more mineral water in the taste comparison task implicitly associated themselves more with healthy than with unhealthy food items. Furthermore, the self-report  measures of healthy diet (r = .20 and r = .21) and preference for unhealthy food (r = −.24 and r = −.31) were associated with mineral water intake. For soft drink intake, associations with explicit and implicit measures could not be registered.In the taste comparison task (high distraction situation), however, the mineral water intake and the difference between mineral water and soft drink intake were related to the Nutrition IAT  = 3.71, p < .01 (see Table β = −.28). Participants with a preference for unhealthy food tended not to choose fruit instead of a snack.With regard to food choice in the low distraction situation , only step 2, with the self-report  measures, was significant; F  = 4.18, p = .001; soft drink intake: F  = 11.09, p < .001; difference between mineral water intake and soft drink intake: F  = 3.65, p < .01. Specifically, the significant predictors for mineral water intake were gender (β = −.24) and the Nutrition IAT (β = .22). The only predictor for soft drink consumption was gender (β = −.43). In general, women drank less mineral water and soft drinks than men. The statistically significant predictors for the difference between mineral water and soft drink intake were the explicit preference for unhealthy food (β = −.28) and the Nutrition IAT (β = .24). Participants who explicitly preferred unhealthy food consumed relatively less mineral water than soft drinks. Moreover, participants who implicitly associated themselves more with the healthy food items than with unhealthy food items drank more mineral water and preferred mineral water over soft drinks in the taste comparison taskDuring the taste comparison task (high distraction situation), the mineral water intake and the difference between mineral water and soft drink intake were predicted by the Nutrition IAT after the other variables were controlled for , when controlled processing is possible, nutritional behaviour such as the single choice of fruits versus snacks is predicted by an explicit measure such as self-reported preferences for unhealthy food. Conversely, within a situation that absorbs attention , when automatic aspects of processing are crucial, less controlled nutritional behaviour such as consuming mineral water is predicted by an implicit measure such as the Nutrition IAT. For the difference between mineral water and soft drink intake, however, both the implicit and the explicit measures were relevant. For the IAT as a measure of implicit, automatic processes, the results support the predictions made on the basis of dual-process models , 2322, 2Although Perugini  and RichHealthy eating behaviour is influenced by implicit and explicit processes. Studying the interplay between both processes in sight of social-cognitive models of health behaviour Mai et al.  showed tThis study adds to the literature by showing that nutritional behaviour is influenced by both controlled and automatic processes depending on the available capacity for self-regulation: When distraction was low, food choice was predicted solely by explicit measures (reflecting more controlled processes). On the other hand, when distraction was high, the implicit measure (reflecting more automatic processes) predicted mineral water intake. Thereby in contrast to previous studies distraction was an integral part of the tasks itself. This research strengthens the view that interventions to promote health behaviour may benefit from accounting for controlled as well as automatic processes.


To date, these congresses have a 46 year tradition and have taken place in 13 countries:The papers in this special issue of ZooKeys were presented at the 16th International Congress of Myriapodology (16ICM) held in Olomouc, the Czech Republic on July 20–25, 2014. International Congresses of Myriapodology are scientific meetings of scientists, students and enthusiastic amateurs with specific interest in millipedes, centipedes, symphylans and pauropods, as well as velvet worms. Those are organised under the auspices of the Centre International de Myriapodologie (1ICM: 1968 – Paris, France2ICM: 1972 – Manchester, UK3ICM: 1975 – Hamburg, Germany4ICM: 1978 – Gargnano, Italy5ICM: 1981 – Radford, USA6ICM: 1984 – Amsterdam, The Netherlands7ICM: 1987 – Vittorio Veneto, Italy8ICM: 1990 – Innsbruck, Austria9ICM: 1993 – Paris, France10ICM: 1996 – Copenhagen, Denmark11ICM: 1999 – Bialowieza, Poland12ICM: 2002 – Mtunzini, South Africa13ICM: 2005 – Bergen, Norway14ICM: 2008 – Görlitz, Germany15ICM: 2011 – Brisbane, Australia16ICM: 2014 – Olomouc, Czech Republic16ICM was the first myriapodological congress to be held in the Czech Republic. The 84 participants and 18 accompanying persons came from 24 countries on five continents, making the 16th Congress a truly international and global meeting of myriapod specialists (Figs The organisers of the 16ICM are very grateful to the Palacký University, Olomouc, which provided us a pleasant area for all scientific as well as social parts of the Congress. We also thank the Biology Centre CAS and partial support from several unnamed colleagues who allowed the participation of young students at this Congress.Many thanks to Lyubomir Penev and the friendly staff at Pensoft Publishers for making the 16ICM papers freely available to a global online audience.


Escherichia coli, ppGpp redirects protein production during nutrient stress by interacting with RNA polymerase directly and by inhibiting several proteins. Consistently, increased levels of ppGpp lead to increased persistence; but, the mechanism by which elevated ppGpp translates into persistence has not been determined. Hence, we explored persistence in the absence of ppGpp so that the underlying mechanism of persister cell formation could be explored. We found that persister cells still form, although at lower levels, in the absence of ppGpp. Additionally, the toxin/antitoxin systems that we investigated  remain able to increase persistence dramatically in the absence of ppGpp. By overproducing each E. coli protein from the 4287 plasmid vectors of the ASKA library and selecting for increased persistence in the absence of ppGpp (via a relA spoT mutant), we identified five new proteins, YihS, PntA, YqjE, FocA, and Zur, that increase persistence simply by reducing cell growth.Most bacterial cells are stressed, and as a result, some become tolerant to antibiotics by entering a dormant state known as persistence. The key intracellular metabolite that has been linked to this persister state is guanosine tetraphosphate (ppGpp), the alarmone that was first linked to nutrient stress. In  Microbial infections are the leading cause of death worldwide3578910Escherichia coli, ppGpp is produced as a response to nutrient starvation and other stresses  and serves to shift transcription away from loci required for rapid growth and toward those needed for stress survivalE. coli, ppGpp is produced via RelA and SpoT 13S), the stress response sigma factor for the stationary phase, and RpoE (sigmaE), the stress response sigma factor for misfolded proteins in the periplasm13The mechanism of persister cell formation has been elusive in that deletion studies have yielded little insight to datehigh persistence (hip) mutant hipA7 that increases persistence. The hipBA locus encodes a toxin/antitoxin module, in which the HipA toxin phosphorylates the active center of the aminoacyl-tRNA synthetase GltX to inhibit translationmqsR and mqsRA2021tisAB/istRyafQTA systems are found in most bacteria and are primarily used by the cell to reduce metabolismin vitro, Lon is not activated by polyphosphate but instead is deactivated by itlon have no effect on persistence against aminoglycosides or β-lactamsppk, which encodes the enzyme that produces polyphosphate, has little impact on persistence against aminoglycosidesThe mechanism by which ppGpp activates toxins of TA systems has not been determined definitively. It has been proposed that production of polyphosphate, due to elevated ppGpp levels resulting from stochastic events, activates Lon protease and that activated Lon then degrades antitoxins, which would result in activated toxinsE. coliThere are several alternative ways to induce persistence. Treatment with antibiotics that reduce transcription, translation, and energy production (ATP) have been shown to increase persistence drasticallyTo explore further mechanisms of persistence, we chose to simplify the system by studying persister cell formation in the absence of ppGpp. Using a selection method that relies on increased persistence, we screened the 4287 gene expression vectors of the ASKA library and identified five novel proteins that increase persistence dramatically. We found that ppGpp is not essential for forming persister cells, and that proteins which simply reduce growth increase persistence in the absence of ppGpp.E. coli K-12 cultures after three rounds of ciprofloxacin treatment (5 μg/mL for 3 h) and subsequent regrowth of persisters in fresh media. There was no observable increase in ciprofloxacin survival after each round of regrowth and no colonies were detectable on agar plates with 5 μg/mL ciprofloxacin, showing that there were no resistant cellsFor this work, we primarily utilized ciprofloxacin at 100X the minimum inhibitory concentration 31To further explore the mechanisms by which cells become persistent, we initially investigated the role of Lon, Clp, and ppGpp with persistence to ciprofloxacin and ampicillin. The absence of Lon had little impact on the number of persister cells with both antibiotics , and theE. coli ΔrelA ΔspoT mutant previously shown to be devoid of ppGppSince Lon and Clp proteases were not important for persister cell formation, we tested persistence in the absence of ppGpp by using an E. coli, we tested whether the production of various toxins of TA systems still increased persistence in the ppGpp-minus strain. We used ampicillin at 100 μg/mL (10X MIC) for 3 h because ampicillin was used for previous persister studies with toxin expression82022To obtain further evidence that ppGpp is not essential for forming persister cells in For the ribosome-independent toxin MqsR358relA ΔspoT strain if a persistence-inducing protein is produced. Hence, we pooled the ASKA library of E. coli proteins produced in the backbone pCA24N under control of the lac promoter (IPTG-inducible), electroporated them into the ΔrelA ΔspoT strain, and isolated cells that were enriched through multiple rounds of treatment with ciprofloxacin (5 μg/mL); ciprofloxacin kills non-persister cellsTo discern insights into the mechanism by which cells become persistent in the absence of ppGpp, we reasoned that persistence would increase in the ΔyihS+, pntA+, yqjE+, focA+, zur+, mazF+, yhrC+ (pseudogene), and the intergenic region between fepB and entC. yihS+ , pntA+ , focA+ , and mazF+  were nearly evenly distributed, whereas yqjE+  and zur+  and the intergenic region  were present at higher frequencies. The pseudogene yrhC  was present with a lower frequency. For simplicity, pseudogene yrhC+ and the intergenic region were not used for further study. Therefore, using this selection technique, we identified five new proteins  important for increasing persistence dramatically in the absence of ppGpp  screening; the inserts ranged from about 450 bp to 1700 bp compared to about 200 bp for the empty vector pCA24N. Sequencing identified plasmids containing sequences for of ppGpp . We alsoof ppGpp .YihS is an isomerase involved in metabolism of sulfoquinovose, a sulfonic acid derivative of glucoselon, and ∆clpP strains were also determined, and these strains grew slightly slower compared to the wild-type strain  have never been linked previously to persistence. The distinguishing feature of these proteins is that all of these proteins increase persistence simply by reducing cell growth. Given that many labs have searched largely in vain for a coherent cause of persistence using such techniques as transposon-sequencing51−1. Our results are also consistent with the finding that proteins that are unrelated to TA system toxins that are toxic, such as E. coli DnaJ of the DnaJ/DnaK/GrpE chaperon system and PmrC of Salmonella enterica serovar Typhimurium, also increase persistence in the presence of ppGppIn addition to well-characterized toxins of TA systems that increased persistence in the absence of ppGpp, we identified several proteins from our search of all E. coli strains were routinely grown in LBrelA ΔspoT mutation was confirmed via PCR and by DNA sequencing using primers . To ensure the correct genotype, the overnight cultures of ΔrelA ΔspoT cells were always checked for lack of growth on minimal medium plates by washing with normal saline, diluting 1,000 fold , plating on M9 glucose−6 dilution on LB agar plates, and wild-type MG1655 grew well on the M9 glucose (0.4%) agar plates. This indicates that the ΔrelA ΔspoT is a true mutant having a ppGpp-minus phenotype. To confirm the ΔrelA ΔspoT strains producing toxins were correct, cell growth was checked by plating cells containing plasmid pCA24N and derivatives on LB Cm30 + 1 mM IPTG agar plates as well as on M9 glucose (0.4%) agar plates to show that strains with the toxins did not grow on either of these two plates, confirming the toxin toxicity as well as ppGpp-minus phenotype.The bacterial strains and plasmids used are listed in For strains without plasmids, cells were grown to the late-stationary phase  for ciprofloxacin treatments or to the exponential phase (16 h grown culture diluted 1:1000 and regrown to a turbidity of ~0.8 at 600 nm) for ampicillin treatments in 25 mL of LB media. A 1 mL culture was used for a drop assay (10 μL × 3) to check cell viability at 0 h. The remaining stationary phase and exponential phase cultures were treated with ciprofloxacin (5 μg/mL) and ampicillin (100 μg/mL), respectively, shaken at 250 rpm, and the cell viability was tested every hour by taking 1 mL of culture, centrifuging at 10,000 rpm for 3 min, resuspending the cells in 1 mL of normal saline (0.85% NaCl), and performing a drop assay. At least two independent cultures were used. For strains harboring plasmids, cells were diluted to a turbidity of ~0.05 at 600 nm with 25 mL of LB broth and incubated with shaking at 250 rpm until reaching a turbidity of ~0.2. The cultures were then induced with 1 mM IPTG for 2 h at 250 rpm. The cells were harvested by centrifugation at 8,000 rpm for 5 min and resuspended in LB broth to remove IPTG. A 1 mL aliquot was serially diluted for a drop assay to check cell viability. The culture (5 mL) was treated with 100 μg/mL ampicillin and with 5 μg/mL ciprofloxacin for 3 h at 250 rpm. After 3 h, 1 mL of culture was centrifuged at 10,000 rpm for 3 min, the supernatant was discarded, and the cells were resuspended in 1 mL of normal saline. Then, the cell suspension was serially diluted for a drop assay to check cell viability.relA ΔspoT cells were transformed with 40 ng of pooled ASKA plasmid DNA, and cells were allowed to recover by incubating in 1 mL of SOC media for 1 h at 250 rpm. For the first round of selection, 1 mL of culture was inoculated into 25 mL of LB broth and incubated at 250 rpm until reaching a turbidity at 600 nm of ~0.2 followed by induction with 0.2 mM IPTG until reaching a turbidity of ~0.8. The culture was treated with 5 μg/mL of ciprofloxacin for 3 h at 250 rpm and 1 mL was taken for plating. For the second and third rounds of selection, cells from the previous round were washed, diluted 1:100 into 25 mL of fresh LB, and incubated overnight at 250 rpm. Cultures were diluted to a turbidity of ~0.05 at 600 nm in fresh LB and incubated at 250 rpm until reaching a turbidity of ~0.2. Then, as in the first round, cells were induced with IPTG, treated with ciprofloxacin, and 1 mL of culture was used for plating. Thirty colonies were randomly screened by PCR with pCA24N-specific primers to check the insert (Forward: 5′-GCCCTTTCGTCTTCACCTCG-3′ and Reverse: 5′-GAACAAATCCAGATGGAGTTCTGAGGT-3′). pCA24N (empty vector) DNA was used to compare the insert size. Colonies yielding PCR products with different insert sizes (higher than pCA24N) were sequenced and the genes were identified using a BLAST search against the BW25113 genome sequence. At least two colonies with the same insert sizes were sequenced.ΔFor strains with plasmids, overnight cultures were diluted to a turbidity of ~0.05 at 600 nm and incubated with shaking (250 rpm). IPTG (1 mM) was added at a turbidity of ~0.2 (0 h) to induce the gene on the pCA24N plasmid, and the turbidity was monitored. For strains without a plasmid, overnight cultures were 1:1000 diluted and incubated with shaking (250 rpm) followed by monitoring of turbidity. At least two independent cultures were used.How to cite this article: Chowdhury, N. et al. Persistence Increases in the Absence of the Alarmone Guanosine Tetraphosphate by Reducing Cell Growth. Sci. Rep.6, 20519; doi: 10.1038/srep20519 (2016).