In Figure 2, measurement point coordinate P and normal vector N are shown in Equations 1 and 2, in regard to coordinate system F. (1) (2) Figure 2 Overall coordinate system in this measurement. F, the coordinate system of the optical system. W, a coordinate system of the sample system. S, the coordinate system of the main body of sample. Because

there is the distance of coordinate system selleck inhibitor F and coordinate system W ‘L−Δy + R y ’ apart on Y 1-axis, in regard to coordinate system W, measurement point coordinate P is expressed by the coordinate transformation that Equation 1 is translated. In regard to coordinate system W, normal vector N becomes the same as coordinate system F. Therefore, Equation 3 translated Equation 1, in regard to coordinate system W. (3) In regard to coordinate system S, when measurement point coordinate P and normal vector N are also translated, they become Equations 1 and 2, respectively. (4) (5) Here, the shape derived by using y and n y has low precision. Therefore, the shape is derived by

assigning P(x, z) and N(n x , n y ) to derivation algorithm. This profiler determines the surface shape from the normal vectors and their coordinates by rotational motion, which is more accurate than linear motion and requires no reference optics. Therefore, there are no limitations on the measured shape, and free-forms can be directly measured [11]. Algorithm for obtaining the surface profile We developed an algorithm for buy STI571 calculating the three-dimensional surface profile from the acquired normal vectors and their coordinates. A normal vector is equivalent to the surface slope or derivative of the surface profile. In this algorithm, to derive a figure from a normal vector and the coordinate, we express the figure by a model function and then fit the differential calculus function (slope function) to data on the normal vector by using the least-squares method. By calculating each coefficient of the series, the surface profile is determined. Selleckchem Docetaxel Equations 6 and 7 represent the surface shape and slope for the two-dimensional case, respectively;

the same approach applies to the three-dimensional case. (6) (7) (8) (f j , normal vector or slope; x j , its coordinates). High-speed nanoprofiler Figures 3 and 4 show a photograph and a schematic view, respectively, of the newly developed nanoprofiler for normal vector tracing. The maximum mass of the main body of this machine is approximately 1,200 kg. The measurement sample can set up a greatest dimension to Φ = 50 mm × 40 mm, with a maximum mass of 1 kg and an optical pass length of 400 mm between the sample and the detector. Additionally, each optical element is set by the alignment that a laser beam changes 10 nm on QPD, when a normal vector changes 0.1 μrad. This machine has two pairs of two-axis rotational stages with resolutions of 0.17 μrad and one linear motion stage with a resolution of 1 nm.

Information on fracture site and radiological

evaluation was, however, not systematically available. Outcome measures The outcome measures of the study were MPR and persistence. MPR was defined as the duration of all filled prescriptions divided by the follow-up selleck chemicals llc period. Persistence was measured by the time from initiation of therapy to discontinuation. As required for persistence analysis, a limit on the number of days allowed between refills, the permissible gap (PG), was prespecified. Patients who stopped their treatment for a duration longer than the PG were considered to have discontinued, even if they subsequently restarted treatment. In many previous studies, the PG applied to weekly bisphosphonates was specified empirically at 30 days [9, 26–28]. Cramer et al. [5] recently proposed a less arbitrary method based on the pharmacological properties of the drug and the treatment situation in which the PG definition should take into account the maximum allowable period for which patients could go untreated without anticipating reduced or suboptimal outcomes. As specified in the product labelling, the recommended acceptable dosing window for monthly ibandronate (21 days) is 15 days longer than that of weekly bisphosphonates (6 days). For this reason, a prespecified PG of 45 days for the monthly regimen and of 30 days for the weekly regimen was considered acceptable,

as previously implemented in a US database analysis [29]. We also performed a sensitivity analysis in order to test the influence AMN-107 supplier of the definition of PG on the persistence results in which an identical PG of 30, 45 or 60 days was allowed for both formulations. Statistical analysis The demographic and clinical characteristics of patients included in the two cohorts were compared using the χ 2 test or Fisher’s exact test for categorical variables and the Kruskal–Wallis test for continuous

variables. Persistence rates were evaluated using Kaplan–Meier survival analysis and compared between the two 4-Aminobutyrate aminotransferase cohorts using the log-rank test in a Cox proportional hazards model. For MPR, the two cohorts were described by mean MPR values and by distribution of patients across MPR classes. This analysis was performed on the entire study population. Since the profiles of patients in the weekly and monthly cohorts were potentially different and confounding factors could thus contribute to the difference in persistence and in MPR between the two cohorts, these were taken into account by constructing a propensity score [30]. This score included all demographic, clinical and treatment variables recorded in the database and was calculated using multivariate logistic regression. Each patient was attributed a propensity score that represented the probability of receiving monthly rather than weekly bisphosphonate treatment with respect to the pattern of potential confounding factors presented.

(See Shevela et al. 2012, for a review.) To me, this discovery, in addition to its well-known role in carbon fixation, of the unique role of bicarbonate/CO2 on the electron acceptor side of PS II, by selleck compound Govindjee and coworkers (including Julian Eaton-Rye, author of this Tribute to Govindjee), is a major discovery, and we owe this

to Govindjee’s ingenuity, persistence, and drive unmatched in the history of photosynthesis research. I marvel at this research and I believe that he will go down in the history of photosynthesis research for this unique finding. John C. Munday, Jr. Professor of Natural Science and Mathematics Regent University, Virginia Beach, VA Tribute to Dr. Govindjee Graduate study is a special time of life. The opportunity to be immersed in research on a topic of choice, after years of preparatory schooling, is a time of deep intellectual reward. My choice to study photosynthesis was largely because of its biophysical complexity. The research methods enabled “seeing” events at the molecular level and gaining insights that could explain a process basic to all life on earth. Choosing a major professor was a major decision. On reflection about the options in the Photosynthesis Laboratory at the University of Illinois, I concluded that Dr. Govindjee would be a www.selleckchem.com/products/ew-7197.html wise mentor, a steady hand of guidance, and an

encourager. He had already proven his skill at research and his deep knowledge of the field of photosynthesis. Dr. Govindjee provided a list of problems where he believed that research would bear fruit. This suited my temperament and level at the time. After some investigation I developed a proposal, “owning” the content as my own; but later, looking back, I realized that he had foreseen my proposal exactly as one from his original list. Dr. Govindjee proved to be an exceptionally wise mentor. He was full of patience, manifested fully

a teaching spirit, and with painstaking care instilled a sense of excellence and quality in research. He demonstrated in his own research what he strove to teach. He was ever-present in the laboratory. Always with a cheerful smile, and obviously enjoying research, he made the laboratory a place where students, research associates, and visiting faculty wanted to be. He organized seminars in the lab and at his home. His wife Rajni had the gift of hospitality and we enjoyed her refreshments. Selleck Y27632 (She also made significant contributions of her own in photosynthesis research, and cared for their young family.) Along the way his comments and critique about my research were the stimulus for pushing forward, solving problems, and thinking creatively. I distinctly remember various points he made about how to do quality research. And in a final exam, he defended this student against a visitor’s mistaken claims about unpublished research from abroad, pointing out the core principle that what counts in scientific advance is peer-reviewed publication.

Closer inspection of the intra-species Crc candidates, however, shows that some genes linked to carbohydrate metabolism could also be directly regulated by Crc (Additional file 1). For example, in P. aeruginosa and P. fluorescens species, the gene, zwf, encoding glucose-6-phosphate dehydrogenase has a Crc motif, whereas in P. putida

and P. syringae species, the gene, gap-1, encoding glyceraldehyde-3-phosphate dehydrogenase has a Crc motif. When viewed in an integrated way, it is seen that there are two distinct patterns to the regulation of genes in this class (Figure 2). When present, sugar transporters are generally subject to CRC control, whereas the regulation of selleckchem downstream sugar metabolism is species-specific with respect to genes encoding catabolic enzymes. Interestingly, the same trend is observed for amino acid metabolism where most of the interspecies Crc candidates are involved in transport (Table 1), whereas intraspecies candidates are involved in metabolism (Additional file 1). Figure 2 Predicted Crc regulon of carbohydrate metabolism in Pseudomonas. Selected genes

involved 4SC-202 in carbohydrate transport and metabolism are shown along with their status vis a vis (predicted) Crc regulation. Genes from P. aeruginosa (squares), P. fluorescens (circles), P. putida (triangles) and P. syringae (diamonds) are shown, with filled/unfilled symbols indicating that the target in that species is/is not predicted to be regulated by

Crc. An asterisk (*) after a symbol indicates where an orthologous locus is absent in the relevant species. OM – outer membrane; PP – periplasm; IM – inner membrane; ED – Entner-Doudoroff pathway; EMP – Embden-Meyerhoff pathway; 2-K-3-DG-6-P – 2-keto-3-deoxygluconate-6-phosphate. OprB – carbohydrate porin B; GlpF – glycerol transporter; FruAB – fructose phosphotransferase system; oxyclozanide Mtr – mannitol transporter subunit; GtsA – glucose transporter subunit; GntP – gluconate transporter; KguT – 2-ketogluconate transporter; Mdh – mannitol dehydrogenase; AlgA – mannose-6-P isomerase; Zwf – glucose-6-P dehydrogenase; Edd – gluconate-6-P dehydratase; KguE – xylose isomerase; GapA – glyceraldehyde-3-P dehydrogenase; Eno – phosphopyruvate hydratase. Some steps of the Embden-Meyerhoff pathway are abbreviated with a dashed line for clarity. It is notable that another gene, cstA, with a predicted role in carbon starvation stress alleviation was also implicated as a Crc candidate. The CstA protein is involved in peptide transport that would assist the cell in escaping carbon starvation [47]. In Escherichia coli, induction of the cstA gene depends on cAMP and Crp [48] indicating that this locus is subject to CCR in E. coli.

Table 2 Significant differences between groups   Survivors (n = 10) Nonsurvivors (n = 6) P value ER MAP (mmHg) 76.5 +/- 25.4

45.6 +/- 8.6 0.013* GCS 14 +/- 2.8 8.17 +/- 4.1 0.004* Operative time (min) 189 +/- 65.3 105 +/- 59.8 0.022* ISS 28.7 +/- 3.5 60.3 +/- 22.9 0.0006* OR thoracotomy 20% 83.3% 0.024 + *Oneway ANOVA analysis of variance. + Fischer’s exact test. Six patients (37.5%) were managed with IVC ligation due to difficulty in obtaining adequate exposure and intraoperative hemodynamic instability, and ten patients (62.5%) were managed with simple primary repair. Caval ligation PCI-34051 nmr was significantly associated with increased mortality, with five out of the six patients managed with IVC ligation deceasing (mortality: 83.3%) as opposed to one patient out

of ten managed with primary repair (mortality: Crenolanib mouse 16.67%, p = 0.008) (Table  3). Upon logistic regression analysis, significantly increased odds of mortality were seen with the need to undergo thoracotomy for vascular control (OR = 20, 1.4-282.4, p = 0.027), and the use of caval ligation as operative management (OR = 45, 2.28-885.6, p = 0.012) (Table  4). GCS as a linear scale displayed an inverse relation with the risk of mortality expressed as a binary outcome. Upon linear regression analysis, GCS was a significant inverse predictor of mortality, (p = 0.005) (Table  5). Upon logistic regression, a higher GCS was associated with significantly lower odds of mortality (OR = 0.6, 0.46-0.95, p = 0.026). ROC curves after logistic regression as a measure of model fit were 0.85 for GCS, 0.86 for caval ligation as operative management, and 0.81 for thoracotomy. In our cohort of patients, neither the mechanism of injury, nor the level of the IVC injury were significantly associated with an increase in mortality (Tables  6 and 7). No statistically significant differences existed among non-survivors and survivors for BE on admission

(-19.4 +/- 8.3 vs. -12.7 +/- 6.1, p = 0.08), total number of associated injuries (2.8 Branched chain aminotransferase +/- 1.4 vs. 1.9 +/- 0.9, p = 0.15), transfusional requirements expressed as packed red blood cells (PRBC) (7.09 +/- 2.5 vs. 7.23 +/- 2.7, p = 0.9), or time to surgical treatment (19.5 +/- 6.9 min vs. 32.3 +/- 18.5 min, p = 0.13). Non-survivors mainly died on the operating table due to massive hemorrhage that was impossible to control operatively, with subsequent cardiac arrest. The mean hospital stay of survivors was 24.5 +/- 14.2 days. Table 3 Mortality by operative management (caval ligation versus simple repair) Operative management Number of patients Number of deaths ISS + Mortality rate* IVC ligation 6 (37.5%) 5 59 +/- 10.1 83.3% Simple repair 10 (62.5%) 1 29.5 +/- 1.2 16.6% +P value = 0.002, Student’s T-test. *P value = 0.

In chemostats run under such conditions, acetate is usually not detected [43–45], however it might be possible that scarce amounts of acetate are excreted and immediately taken up by an acetate cross-feeding selleck chemicals llc subpopulation. It has been argued that the production of acetate is independent of the growth rate and that the growing bacteria can simultaneously produce and utilize acetate [45,

46]. The expression of the pck reporter also indicates that most of the cells possibly engaged in the reactions of gluconeogenesis (Additional file 5: Figure S3). Previous studies provided evidence that transcriptional regulation does indeed have a significant impact on the direction of the metabolic flux through the pyruvate/acetyl-CoA node [36]. Transcriptional control at this branching point allows flux to proceed via overflow metabolism, citric acid cycle and/or PEP-glyoxylate cycle [35]. Results presented in another paper indicate that alterations of fluxes through the glyoxylate shunt and the citric acid cycle were associated with changes in the expression of these genes [47]. Therefore, transcriptional reporters for acetate metabolism (the acs reporter) and PEP-glyoxylate pathway (the pck reporter)

may indeed be indicative of the fluxes through those pathways. Switching to overflow metabolism and bimodal expression of the acs reporter ICG-001 mouse It has been shown that the excretion of acetate (overflow metabolism) occurs in chemostat populations at a dilution rate of about 0.3 h-1[22,

44]. Increasing the concentration of glucose in the chemostat feed results in intensified production of acetate [39]. Our results support the existence of overflow metabolism at D = 0.3 h-1 in chemostats with high concentrations (5.6 mM) of glucose in the feed. Under these conditions, decreased expression of acs and pck reporters indicated that assimilation of acetate was reduced and gluconeogenesis was Fossariinae shut down (Figure  5). However, not all replicate cultures showed consistent patterns in the expression of transcriptional reporters. The expression of the reporters for mglB and acs was not consistent between different experiments, in contrast to the measurements for rpsM, ptsG and pck (Figure  5). This suggests that not all replicate cultures switched to the overflow metabolism, possibly due to the fact that the mini-chemostats were operated at the threshold of the expected switch to overflow metabolism. Figure 5 Overflow metabolism in chemostat cultures at the intermediate growth rate D = 0.3 h -1 . Overflow metabolism occurs in chemostats with high concentration of glucose feed (5.6 mM Glc in the media). The distributions of fluorescence measurements corresponding to PrpsM-gfp, PptsG-gfp, PmglB-gfp, Ppck-gfp and Pacs-gfp are depicted in different colors presenting different replicates. The background fluorescence is plotted in black.

It is interesting to note that the competing NRR process remains active even when the excitation photon energy

(E exc) is tuned to 1.96 eV, which is below the GaNP bandgap. Indeed, Arrenius plots of the PL intensity measured at E det = 1.73 eV under E exc = 2.33 eV (the open circles in Figure  2a) and E exc = 1.96 eV (the dots in Figure  2a), i.e., under above and below bandgap excitation, respectively, yield the same activation energy E 2. In addition, the PL thermal quenching under below bandgap excitation seems to be even more severe than that recorded under above bandgap excitation. At first glance, this is somewhat surprising as the 1.96

eV photons could not directly create free electron–hole pairs and will be absorbed at N-related localized states. However, fast thermal activation of the https://www.selleckchem.com/products/chir-99021-ct99021-hcl.html AZD8931 photo-created carriers from these localized states to band states will again lead to their capture by the NRR centers and therefore quenching of the PL intensity. Moreover, the contribution of the NRR processes is known to decrease at high densities of the photo-created carriers due to partial saturation of the NRR centers which results in a shift of the onset of the PL thermal quenching to higher temperatures. In our case, such regime is likely realized for the above bandgap excitation. This is because of (a) significantly (about 1,000 times) lower excitation power used under below bandgap excitation (restricted by the available excitation source) and (b) a high absorption coefficient for the band-to-band transitions.

The revealed non-radiative recombination processes may occur at surfaces, the GaNP/GaP interface or within bulk regions of GaNP Gemcitabine nmr shell. The former two processes are expected to be enhanced in low-dimensional structures with a high surface-to-volume ratio whereas the last process will likely dominate in bulk (or epilayer) samples. Therefore, to further evaluate the origin of the revealed NRR in the studied NW structures, we also investigated the thermal behavior of the PL emission from a reference GaNP epilayer. It is found that thermal quenching of the PL emission in the epilayer can be modeled, within the experimental accuracy, by the same activation energies as those deduced for the NW structure. This is obvious from Figure  2b where an Arrhenius plot of the PL intensity measured at E det = 2.12 eV under E exc = 2.33 eV from the epilayer is shown. However, the contribution of the second activation process (defined by the pre-factor C 2 in Equation 1) is found to be larger in the case of the GaNP/GaP NWs.

Young adults should continue to be monitored and advised on healthful dietary choices to encourage the development of healthful dietary habits that may persist into middle and late adulthood. Consent Written informed consent was obtained from the patient for the publication of this report and any accompanying images. Acknowledgements The authors wish to thank PFT�� molecular weight the University athletics department for their cooperation with this project. Additional file Additional file 1: Table S2. Exploratory factor analysis: rotated factor pattern of item loadings and communalities. References 1. Julia C, Vernay M, Salanave B, Deschamps V, Malon A, Oleko A, Hercberg S, Castetbon K: Nutrition patterns

and metabolic syndrome: a need for action in young adults (French Nutrition and Health Survey – ENNS, 2006–2007). Prev Med 2010, 51:488–493.PubMedCrossRef 2. Bovard RS: Risk behaviors in high school and college sport. Curr Sports Med Rep 2008, 7:359–366.PubMedCrossRef 3. Borchers JR, Clem KL, Habash DL, Nagaraja HN, Stokley LM, Best TM: Metabolic syndrome www.selleckchem.com/products/hmpl-504-azd6094-volitinib.html and insulin resistance in Division 1 collegiate football players. Med Sci Sports Exerc 2009, 41:2105–2110.PubMedCrossRef 4. Harvey JS Jr: Nutritional management of the adolescent athlete. Clin Sports Med 1984,

3:671–678.PubMed 5. Greaney ML, Less FD, White AA, Dayton SF, Riebe D, Blissmer B, Shoff S, Walsh JR, Greene Celecoxib GW: College students’ barriers and enablers for healthful weight management: a qualitative study. J Nutr Educ Behav 2009, 41:281–286.PubMedCrossRef 6. Quatromoni PA: Clinical observations from nutrition services in college athletics. J Am Diet Assoc 2008, 108:689–694.PubMedCrossRef 7. Amini M, Esmaillzadeh A, Shafaeizadeh S, Behrooz J, Zare M: Relationship between major dietary patterns and metabolic syndrome among individuals with impaired glucose tolerance. Nutrition 2010, 26:986–992.PubMedCrossRef 8. Kant AK: Dietary patterns and health outcomes. J Am Diet Assoc 2004, 104:615–635.PubMedCrossRef 9. Berg CM, Lappas G, Strandhagen E,

Wolk A, Torén K, Rosengren A, Aires N, Thelle DS, Lissner L: Food patterns and cardiovascular disease risk factors: the Swedish INTERGENE research program. Am J Clin Nutr 2008, 88:289–297.PubMed 10. Kant AK: Dietary patterns: biomarkers and chronic disease risk. Appl Physiol Nutr Metab 2010, 35:199–206.PubMedCrossRef 11. Gans KM, Ross E, Barner CW, Wylie-Rosett J, McMurray J, Eaton C: REAP and WAVE: new tools to rapidly assess/discuss nutrition with patients. J Nutr 2003, 133:556S–562S.PubMed 12. Gans KM, Risica PM, Wylie-Rosett J, Ross EM, Strolla LO, McMurray J, Eaton CB: Development and evaluation of the nutrition component of the Rapid Eating and Activity Assessment for Patients (REAP): a new tool for primary care providers. J Nutr Educ Behav 2006, 38:286–292.PubMedCrossRef 13.

Tumor volumes were similar in nanoscale and conventional Photosan groups 6 days after treatment; however, after this time point, tumor were significantly smaller in the former group compared with the latter (p < 0.05) , as shown in Figure 4A and the digital photograph before treatment (Figure 4B) and 14 days after treatment 4c. Stem Cells inhibitor Table 2 Subcutaneous xenograft tumor volumes (cm 3 ) in nude mice   Group A Group B Group C P(A/B) P(A/C) P(B/C) 1. 15 15 15 – - – 2. 0.525 ± 0.019 0.520 ± 0.013 0.527 ± 0.015 0.588 0.876 0.487 3.

0.867 ± 0.031 0.250 ± 0.010* 0.412 ± 0.013* 0.000 0.000 0.856 4. 1.236 ± 0.039 0.112 ± 0.013* 0.217 ± 0.011* 0.000 0.000 0.770 5. 1.750 ± 0.169 0.035 ± 0.014*# 0.105 ± 0.038* 0.000 0.000 0.020 6. 2.251 ± 0.162 0.114 ± 0.020*# 0.406 ± 0.050* 0.000 0.000 0.001

7. 2.451 ± 0.397 0.266 ± 0.042*# 0.608 ± 0.076* 0.000 0.000 0.008 8. 2.657 ± 0.411 0.475 ± 0.058*# 1.058 ± 0.170* 0.000 0.000 0.004 9. 3.050 ± 0.438 0.623 ± 0.108*# 1.551 ± 0.180* 0.000 0.000 0.000 1. Number of animals; 2. Before treatment; 3. 2 days after treatment; 4. 4 days after treatment; 5. 6 days after treatment; 6. 8 days after treatment; 7. 10 days after treatment; 8. 12 days after treatment; 9. 14 days after treatment; Blebbistatin mw Group A – blank control; Group B – nanoscale Photosan group; Group C – conventional Photosan group; P(A/B) – P value for comparing group A and group B; P(A/C) – P value for comparing group A and group C; P(B/C) – P value for comparing group B and group C. *Significantly different (P < 0.05) from group A, #Significantly different (P < 0.05) from group C. Figure 4 Tumor volumes after treatments during 14 days (A) and their digital photographs (B). (A) When tumor volumes reached approximately 0.5 cm3, one group of the mice did not receive any treatment (A, Control group) and two groups of the mice received treatment with conventional Photosan (C, Free PS group) and nanoscale photosensitizer (B, PS-load HSNP group), respectively. The tumor sizes were measured in the following

14 days. Significantly different (P < 0.05) from group A, #Significantly different (P < 0.05) from group C. The digital photograph of the tumor volumes of the three groups second before treatment (B) and 14 days after treatment (C). Where, A is the control group; B is PS-load HSNP group and C is the Free PS group. Primary liver cancer (hepatocellular carcinoma) is the most common type of malignant tumor in China. Although surgical excision and liver transplantation therapies can significantly prolong the survival of liver cancer patients, most patients are only diagnosed at later stages and cannot be surgically treated. Therefore, non-surgical approaches play a vital role in the treatment of primary liver cancer; however, non-surgical approaches have generally exhibited extremely limited therapeutic efficacy [17].

5 fold or more, P-value < 0.01) grouped by TIGR functional role categories. A, amino acid biosynthesis; B, biosynthesis

of cofactors, prosthetic groups, and carriers; C, cell envelope; D, cellular processes; E, central intermediary metabolism; F, DNA metabolism; G, disrupted reading frame; H, energy metabolism; I, fatty acid and phospholipid metabolism; J, mobile and extrachromosomal element functions; K, protein fate; L, protein synthesis; M, purines, pyrimidines, nucleosides and nucleotides; N, regulatory functions; O, signal transduction; P, transcription; Q, transport and binding proteins; R, unknown function; and S, hypothetical or conserved hypothetical proteins. The physiology of the biofilm The down-regulation of many genes involved in cell envelope biogenesis, biosynthesis https://www.selleckchem.com/products/ly2835219.html of cofactors, prosthetic groups and carriers and other www.selleckchem.com/products/bay80-6946.html cellular processes was observed in this study (Fig. 2). Similarly, many genes involved in energy production, DNA replication, fatty acid and phospholipid metabolism and central intermediary metabolism were also down-regulated. Taken together, these observations suggest a down-turn in cell replication

and a slowed growth rate in biofilm cells. The primary indication of the slowing of cell replication in the biofilm was the down-regulation of genes encoding proteins involved in chromosome replication such as DnaA (PG0001), the primosomal protein n’ PriA (PG2032), single-stranded binding protein Ssb (PG0271), the DNA polymerase III alpha subunit DnaE (PG0035) and the DNA polymerase III beta subunit DnaN(PG1853). Also down-regulated in biofilm cells were genes encoding homologues of proteins involved in DNA repair and recombination, MutS [37]

(PG0412), radA [38] (PG0227) and recN [39, 40] (PG1849). The biofilm cells also displayed up-regulation of a putative translational regulator, RecX (PG0157) that in E. coli has been shown to inhibit RecA activity which is important in homologous recombination and in the SOS pathway of DNA repair and mutagenesis [41]. The down-regulation of a significant number of genes associated with cell envelope biogenesis (see Additional files 1 and 2) also suggests that the growth rate was reduced Thiamine-diphosphate kinase in biofilm cells. The slower growth rate of cells in a biofilm has been previously attributed to restricted penetration of nutrients and helps explain the relative resistance of biofilms to antibiotics targeting growth [42, 43]. As biofilm cells exhibit a slower growth rate then the need for energy would decrease correspondingly. Indeed, the transcriptomic data showed that expression of seven genes involved in the glutamate catabolism pathway, one of the key sources of energy for P. gingivalis [44], were simultaneously down-regulated in biofilm cells.