At two hospitals in Southwest London comprising an international population with an African heterosexual predominance, there was a 5% prevalence of cryptococcal antigenemia in newly diagnosed patients with CD4 count < 100 cells/μL. Almost all of the CRAG positive patients were African, though the statistical power of the comparison of proportion of African patients between the CRAG positive (88%) and negative (54%) groups was limited by the cohort size. This relatively high prevalence of cryptococcal infection, on a par with some African countries, reflects our African HIV patient predominance, and may not

be generalizable to all UK HIV cohorts. Our numbers may also have been augmented by a tertiary centre referral bias of complex HIV patients Quizartinib in vitro with advanced disease and CM for specialist Infectious Diseases inpatient care. Four of the 8 patients had been transferred to St George’s from hospitals in our sector, for whom we did not have a new HIV diagnoses denominator. Excluding those transfers would result in a conservative estimate of prevalence of cryptococcal infection in newly diagnosed HIV patients with CD4 < 100 cells/μL in southwest London of 3% (4/153), and 5% (4/84) in Africans. In our cohort, almost all the CRAG positive patients were only diagnosed with HIV at the time of presentation with CM. Late HIV diagnoses are not exclusive to resource-limited countries: in 2010, 28% of new UK HIV diagnoses

had CD4 counts < 200 cells/μL17 and in North America in 2008, 33% of newly HIV-diagnosed patients developed

AIDS GDC-0941 manufacturer within one year.18 By ethnicity, late presentation is highest amongst Black Africans,17 and the National Institute for Clinical Excellence is promoting increased HIV testing in this group.19 For our African CRAG positive patients with known time between arrival to the UK and new HIV diagnosis, this ranged from 5 to 16 years, suggesting opportunities for earlier HIV diagnosis and ART, which might have prevented dissemination of latent cryptococcal infection occurring at lower CD4 counts. For those diagnosed late, the question remains whether CRAG screening at HIV diagnosis should be routinely recommended. To be effective, screening needs to be done prior to symptomatic presentation within the antigenemic window, which ranges from weeks to months.8 Current BHIVA guidelines20 recommend HSP90 excluding cryptococcal infection in symptomatic patients with CD4 < 200 cells/μL but do not advocate routine screening or fluconazole prophylaxis. CM is not a reportable disease: HPA figures of new CM diagnoses in the UK between 2006 and 2011 range from 5 to 28 cases/year, suggesting significant underreporting [C Chau, Health Protection Agency HIV&STI department, personal communication]. Based on these figures and our relatively high prevalence in a London cohort, it is difficult to extrapolate to recommendations for targeted screening in the UK.

Full details of these measurements have been published previously [2]. Statistical analyses were performed using linear model software in DataDesk 6.1.1 (Data Description Inc, Ithaca, NY). Differences between NPNL and lactating women, at the time of their first measurement, were investigated using Student’s two-tailed t-test. Descriptive statistics are reported as means and standard deviations. Changes over time are reported as means and standard selleck kinase inhibitor errors.

Scheffe’s post hoc method was used to reduce effects of multiple testing. All variables, except age, were transformed into natural logarithms to normalize skewness where necessary and to determine proportional (percentage) changes of discrete variables [30]. Independent determinants of changes selleck compound in HSA variables were explored using multiple regression models. Determinants investigated included mean and changes in weight, and mean and changes in calcium intake using the FFQ data obtained at the different timepoints. In addition, data from individual

food diaries, obtained at a single timepoint were used to group women with calcium intakes above and below the median to investigate group differences using conditional regression analysis. The characteristics of the 48 lactating women at 2 weeks postpartum and 23 NPNL women at baseline are shown in Table 1. There were no significant differences in weight and height between the two groups but the NPNL 3-oxoacyl-(acyl-carrier-protein) reductase women were, on average, younger. BMDa was significantly lower for lactating women at the narrow neck (4.2%) and intertrochanter (5.3%) and these differences remained significant after adjusting for age. There were no significant differences for other hip measurements. There was a wide range in calcium intakes for both NPNL and lactating women but the NPNL women had significantly lower intakes of calcium at baseline

compared to the lactating women at 2 months postpartum (prospective food diary data expressed as mean [SD, range]: NPNL women 904 [196, 456–1160] mg/day; lactating women 1254 [416, 637–2280] mg/day). During the study, lactating women lost significant weight (2 weeks postpartum to peak-lactation −2.79 ± 0.72%, P < 0.001; 2 weeks postpartum to post-lactation −5.00 ± 0.83%, P < 0.0001). In contrast, NPNL women had no significant decrease in weight (0.51 ± 0.89%). The percentage changes in HSA measurements for lactating women from 2 weeks postpartum to peak-lactation and 2 weeks postpartum to post-lactation, are shown in Table 2. This table also reports the HSA changes observed for the NPNL women during the study. At peak-lactation, significant decreases in BMDa were observed at all three hip sites. Significant decreases in CSA were also observed at the narrow neck and intertrochanteric region. There were no significant changes in bone width at any site. Section modulus decreased significantly only at intertrochanter.

Considering that this paradigm uses small fish tanks and regular consumer grade computers, cameras and monitors, it requires only a small amount of space in the laboratory and it also costs very little. Briefly, one can set up 100 test systems and run them in parallel at the same time easily in a small Vivarium room measuring 4 m × 5 m × 2.5 m (width × length × height).

Thus, one can test 100 fish within 2–2.5 hours, that is, about check details 6500 fish per month considering an 8 hour work day and a 5 day work week, a high enough throughput for mutagenesis or drug screens conducted in a single room. It would be misleading to paint a simplified picture and argue we are ready to identify mutations

specifically affecting complex brain functions and behavior, such as learning and memory, or fear and anxiety using a single behavioral task designed for zebrafish. Those who tried this even with the much better examined mouse often (but not always) failed. One reason is that there is no one-to-one correspondence between a gene and behavior. There is no gene ‘for’ learning and memory, and there is no gene ‘for’ anxiety. Furthermore, it must also be appreciated that most behavioral phenomena, such as learning and anxiety, cannot be measured directly. There is no test ‘of’ learning, and there is no test ‘of’ selleckchem fear. We can measure only the behavioral responses in the learning task but not learning itself. This is not just semantics or esoteric argumentation. The point is that, for example, performance in a learning task is influenced by a large number of factors unrelated to learning itself. Chief among them are motivation, perception and motor function. Mutations (or drugs) that alter any of these performance characteristics will be detected as positives in

a behavioral screen. Coproporphyrinogen III oxidase Thus, a positive hit does not yet guarantee success, at least not in the sense the experimenter expected. Briefly, to characterize the identified mutant or drug effect, one must conduct a thorough follow up analysis, hence the need for a test battery. There are two different strategies for such batteries, the top down and the bottom up approaches [28]. In the bottom up approach all possible factors that may influence performance in the test are first investigated in an increasingly complex manner and only fish showing no alterations in these features are then subjected to the top screen for the target phenotype (e.g. learning tasks). The top down approach starts the opposite way.

None of these companies produces the antidiabetics studied in the paper, and these potential conflicts did not affect the given contributions to this article. L.P. in the previous years has received honoraria for lectures at continuing medical education programs for healthcare professionals not focused on specific products. The authors are indebted to Marisa De Rosa, Anna Covezzoli, and Andrea Roncadori (CINECA, Casalecchio di Reno) for providing some

of the additional analyses presented in the article. The essential contribution of the several thousands of diabetes specialists who uploaded their data in the monitoring database is also hereby acknowledged. “
“Genome-wide association studies (GWAS) have identified multiple loci Selleck Dactolisib at which common variants modestly but reproducibly influence risk of type-2 diabetes (T2D) [1], [2], [3], [4], [5] and [6]. Currently, PCI-32765 cost single nucleotide polymorphisms (SNPs) in ∼40 genetic loci have been associated with T2D [7] and [8], most of which relate to insulin secretion rather than insulin resistance [8] and [9], have been distinct from previously studied candidate genes [10],

and do not seem to offer greater predictive value in determining diabetes risk than do commonly used phenotypic risk factors and family history [11] and [12]. Rung and colleagues [13] identified rs2943641C > T, located 500 kb downstream of the insulin receptor substrate-1 gene (IRS1), as a T2D risk locus, with the major C-allele being associated with 19% increased risk of T2D. Importantly, unlike other reported T2D loci, the rs2943641C allele was associated

with increased fasting- and glucose-stimulated hyperinsulinemia and impaired insulin sensitivity. Lower IRS1-associated phosphatidylinositol-3–OH kinase activity in human skeletal muscle biopsies was also shown for the C-allele during insulin infusion, PJ34 HCl and in vitro studies showed that this allele was associated with lower IRS1 protein expression in the basal state, suggesting a direct regulatory link between rs2943641 and IRS1 [13]. The Diabetes Genetics Replication and Meta-analysis Consortium (DIAGRAM) in an earlier meta-analysis did not identify this SNP as a T2D risk variant [4]; however, in a subsequent publication [6] a different IRS1 SNP (rs7578326) adjacent to and in strong linkage disequilibrium (LD) with rs2943641 (r2 = 0.79, in HapMap CEU) was reported to be associated with T2D. The purpose of this study was to validate the rs2943641 association with T2D risk and diabetes-related quantitative traits using data from UK population-based cohorts and T2D patients. In addition, using data from 4752 Caucasians participating in the Whitehall-II study who had been genotyped for 33 IRS1 SNPs using the HumanCVD BeadChip [14] and [15] and with follow-up direct genotyping of IRS1 SNPs in the other study cohorts, we explored the potential association with the risk of T2D of SNPs within and flanking IRS1.

The same information was wrongly written on Table 1, in which the toxin 5-Fluoracil concentration Pancratistatin is mentioned as a component of spider venom, but actually it is from a plant. The authors would like to apologize for any inconvenience caused. “
“A large number of venomous fish are encountered in freshwater and marine environments worldwide. As described for the terrestrial venomous animals, the development of an arsenal of noxious substances by some aquatic animals was an important adaptation that aids these species in their fight for survival in a highly competitive ecosystem (Russell, 1971 and Magalhães et al., 2006). Among the aquatic animals often involved in human accidents, a special attention

is devoted to fish belonging to the Scorpaenidae (lionfish and scorpionfish) and Synanceiidae (stonefish) families due to the severe injuries caused, which include local Protease Inhibitor Library and systemic manifestations. The venom apparatus of these fish comprises 11–17 dorsal, 3 anal and 2 pelvic fin spines with venomous glandular tissue of different morphology located in grooves along opposing sides of each spine (Gwee et al., 1994, Haddad, 2000 and Smith and Wheeler, 2006). All venomous fish use their venom primarily for defensive purposes. This can be deadly for any human unlucky enough to step on them. Therefore, human envenomation occurs when swimmers or fishermen mishandle or step on the spines of the dorsal fin (Halstead, 1951 and Roche and Halstead,

1972). The intensity of the clinical features triggered by fish envenomation is related to the amount of venom injected in the puncture wounds; and patients can be stung by one or several spines present in the dorsal region of the fish

(Gwee et al., 1994). Only a few studies have been dedicated to the venom of specimens of Scorpaena genus scorpionfish. Some works were performed using the venom of Scorpaena guttata, the sculpin or California scorpionfish ( Carlson et al., 1971, Carlson et al., 1973, Schaeffer et al., 1971 and Coats et al., 1980). However Dolutegravir molecular weight there is little information about the venom of Scorpaena plumieri, one of the most abundant scorpionfish found along the Brazilian coast ( Figueiredo and Menezes, 1980 and Carvalho-Filho, 1999). In previous works, we have found that S. plumieri venom is lethal (LD50 in mouse 0.28 mg/kg, i.v.) displaying hemorrhagic, hemolytic and proteolytic activities ( Carrijo et al., 2005). Injections of the venom in the footpad or peritoneal cavity of mice lead to deposition of venom in the lung, endothelial barrier dysfunction and microvascular hyperpermeability ( Boletini-Santos et al., 2008). In addition, the fresh venom was able to induce cardiovascular effects (changes in mean arterial pressure and heart rate) in anaesthetized rats (Carrijo et al., 2005). Recently, we have demonstrated that S. plumieri venom induces coronary vasoconstriction, positive chronotropic, lusitropic and inotropic effects on isolated rat hearts ( Gomes et al., 2010).

19%, 7.99%, and 6.96%, respectively. Assay batch-to-batch variability was assessed by analysing 50 serum samples with varying FLC levels (κ range 3.42–329.88 mg/L; λ range 1.09–130.51 mg/L) Torin 1 solubility dmso and the results are displayed in Fig. 7. All samples were analysed once, on separate assay days, using three consecutive batches of anti-FLC mAbs, calibrators and other appropriate assay reagents. Passing and Bablok regression analysis gave slopes between 0.93–1.01 for κ FLC and 0.86–1.05 for λ FLC. Spearman correlation coefficients for κ FLC were

≥ 0.99 and for λ FLC were ≥ 0.96. Representative assay linearity results are displayed in Fig. 8. Serum samples containing high levels of either κ (581.36, 416.37, and 256.97 mg/L) or λ (485.04, 379.41and 370.56 mg/L) FLC paraproteins were serially diluted in assay buffer. Results indicated that assay linearity was maintained on the monoclonal κ FLC samples between 7.61 mg/L and 568.01 mg/L, 1.94 mg/L and 410.36 mg/L, and, 6.32 mg/L and 260.78 mg/L, respectively. For the λ monoclonal FLC samples, linearity was maintained between 1.38 mg/L and 476.1 mg/L, 1.78 mg/L and 361.72 mg/L, and, 4.45 mg/L and 381.62 mg/L, respectively. For κ FLC, below 10 mg/L no more than 1.45 mg/L non-linearity was found, and above 10 mg/L no more than 16.37% non-linearity was observed. For λ FLC, below 10 mg/L no

more than 2.03 mg/L non-linearity was found, selleck inhibitor and above 10 mg/L no more than 19.0% non-linearity was found. The assay limit of detection PAK5 for each mAb was assessed by measuring each against a κ or λ BJ protein, firstly mixed with normal serum, and then

serially diluted in assay buffer. Limit of detection for BUCIS 01 was 0.63 mg/L, BUCIS 04 was 0.86 mg/L, BUCIS 03 was 0.72 mg/L, and BUCIS 09 was 0.52 mg/L. Assay interference tests showed minimal assay cross-reactivity to alternate κ or λ FLC or intact immunoglobulins, bilirubin, haemoglobin, cholesterol or triglyceride (Fig. 9, in supplementary data). Results demonstrated that no more than a median 2.7 mg/L change was observed for the anti-κ FLC mAbs, and no more than a median 3.7 mg/L change for the anti-λ FLC mAbs. This study describes the development of four mouse anti-human κ:λ FLC mAbs and their initial validation in a multi-plex Luminex® immunoassay. Each of the anti-FLC mAbs exhibited: excellent sensitivity (< 1 mg/L); low batch variation; sustained assay linearity; specificity and minimal cross-reactivity to bound LC, or alternate FLC isotype. Each of the mAbs provided good quantitative concordance with the Freelite™ assay in the measurement of polyclonal FLC in plasma from 249 healthy donors, and FLC levels in serum from 1000 consecutive samples. Specificity and sensitivity were further illustrated in the measurement of FLC in 13,090 urine samples tested for BJ proteins.

Although blast R gene Pi41 was previously reported in cv. 93-11 [47], additional R genes must also be present [26], [31], [49], [50], [51], [52] and [53]. The objectives of the present

study were to evaluate blast resistance in cv. 93-11 using a wide range of Chinese M. oryzae isolates, and to identify and map R genes additional to Pi41. Five rice cultivars, one near-isogenic line (NIL) and ten monogenic lines (MLs) were used in this study (Table 1). Indica cv. 93-11 (resistant, male parent) and japonica cv. Lijiangxintuanheigu (LTH, susceptible, female parent) were evaluated for reaction to M. oryzae isolates, and crossed to develop F2 and F3 populations for genetic analysis and gene mapping. Cultivars CO39, Aichi Asahi and IR64 together with 11 NILs/MLs, each carrying a single R gene ( Table 1), were used as reference lines to differentiate the genes mapped in 93-11 from learn more previously reported R genes. 93-11, LTH, Aichi Asahi, IR64 and F-128-1

are maintained at the Institute of Crop Science, Chinese Academy of Agricultural MK-2206 nmr Sciences (CAAS), Beijing, China. CO39 and the other 10 MLs were kindly provided by Dr. Yoshimichi Fukuta, International Rice Research Institute (IRRI), Los Baños, The Philippines. Seedlings were grown in 60 cm × 30 cm × 5 cm plastic seedling trays in a greenhouse. Pre-soaked seeds of test materials were sown in rows together with the parents. For genetic analysis and gene mapping, 300 seeds of the F2 population and 15 seeds of each parent were sown per tray. For differentiating R genes, 15 seeds of each of the two parents and 11 reference lines ( Table 1) were sown in each tray with two replications. A total of 495 M. oryzae isolates from different rice growing regions were used to evaluate the reaction of cv. 93-11. Among them, five isolates — three

indica-derived isolates, 001-99-1 (pathotype 241.6, from Jiangsu of China), RB17 (pathotype 423.2, from Hunan of China), and GZ26 (pathotype 541.0, from Guizhou of China), and two japonica-derived isolates, 99-26-2 Succinyl-CoA (pathotype 437.1, from Beijing of China) and P-2b (pathotype 303.0, from Japan) — provided clear resistant or susceptible reactions on the two parents and 11 reference lines ( Table 1) and were chosen for further studies. All isolates are stored at the Institute of Crop Science, CAAS, Beijing, China. Inoculum preparation and seedling inoculation followed the procedure described by Chen et al. [60]. Disease reactions were evaluated 6–7 days after inoculation on a numerical scale ranging from 0–3 (resistant) to 4–5 (susceptible) as described by Mackill and Bonman [4]. Observed reactions were verified in the field following injection-inoculation as described by Lei et al. [61]. Genomic DNA was extracted from seedling leaves using the CTAB method [62]. Two sets of DNA bulks, each containing a resistant pool and a susceptible pool, were prepared following the methods described by Yang et al. [47].

Identification of key events at the transcriptional level can facilitate the identification of processes that are critical for disease initiation and progression, thus allowing information from animal experiments to be queried and used for extrapolation to human scenarios (Edwards and Preston, 2008). Comparison of our data with specific models of lung disease, including bacterial infection, airway hypersensitivity and lung injury revealed that CBNPs induced FRAX597 responses that were more closely related to lung injury and fibrosis than to other models. This finding was further supported

by comparison of the expression profiles of CBNP exposed mice to those of curated studies of animals and humans exhibiting a myriad of pulmonary disease phenotypes. This analysis demonstrates that CBNP exposure perturbs genes that are TGF-beta inhibitor known to be involved in tissue injury and fibrosis in mice. Although it is unclear if CBNP exposure would result in the same gene expression profile

in humans, similar pathways including many involved in fibrotic responses were found in both mice and humans (52% of the top 50 pathways found were common between mouse and human). Despite concordance of pathways, the top ranked genes differed considerably between both species. However, many of the genes found in mice and humans had similar functions, including inflammatory and acute phase responses (e.g., Saa3, Socs3 and Mt2 in mice and CP, VNN2 and CXCL10 in humans), cell cycle progression (Cdkn1a in mice and KLF4 in humans) and bone and tissue modelling

(Mmp14, Timp1, Eln and Ogn in mice and SPP1 in humans). Thus, despite discordance in the gene expression profiles between species, the similar functions CYTH4 of top ranked genes and concordance between pathways supports the likelihood of similar responses in the event of CBNP exposure in humans. In addition, fibrosis has been identified as an outcome of exposure to various particles and NPs in animals ( Bermudez et al., 2004 and Shvedova et al., 2008), including Printex 90 (e.g., 28-day nose only inhalation in Wistar WU rats) ( Bellmann et al., 2009), as well as in humans ( Lkhasuren et al., 2007 and Wang and Christiani, 2003). The process of pulmonary fibrosis is closely related to progression of carcinogenic outcome ( Hubbard et al., 2000). These data demonstrating very similar fibrotic pathways in mice and humans and a significant overlap with CBNP-induced gene expression changes thus support the use of pathway-based approaches in identifying molecular mechanisms of disease onset and progression, and using gene expression profiles to support HHRA. This study confirms several key elements that are necessary for the application of gene expression profiling for HHRA of toxicant exposures in general. First, transcriptional profiles can effectively predict the biological effects of chemical exposures.

The only one ‘tallow amine’ actually showed to be false negative in the EpiSkin™ in vitro study and it was not tested in the EpiDerm™

( ICCVAM, 2002). These fatty nitrile substances are characterized as cationic surfactants. They consist of a large lipophilic alkyl chain, and a nitrogen Nutlin-3 mw that is charged in physiological circumstances. This leads to high adsorptive properties to negatively charged surfaces as cellular membranes. The apolar tails easily dissolve in membranes, whereas the polar head causes disruption and leakage of the membranes leading to cell damage or lysis of the cell content. As a consequence, the whole molecule will not easily pass membrane structures. Ethical considerations have moved the chemical industry, which is doing business in Europe, to routinely incorporate in vitro Ferroptosis inhibitor drugs assays into the testing strategy to correctly classify products. If for these substances the animal data are considered the sentinel data, the in vitro data has under

predicted the results. Additional studies should be undertaken to tease out why there is a difference between in vitro and in vivo studies. Although it is indicated that the reconstructed human epidermis (RhE) closely mimics the histological, morphological, biochemical and physiological properties of the upper parts of the human epidermis (Fig. 1), it should be remarked that RhE does not contain all cell-types that are normally present in the epidermis (Fig. 2). A further indication to this comes from the false positive predictions for these substances in the Local Lymph Node Assay, which are thought to be related to release of Interleukins such as IL-1α or other pro-inflammatory Epothilone B (EPO906, Patupilone) mediators, which may not occur with the in vitro tissue constructs during the duration of the study. Evaluate inflammatory cytokines (ie. IL-8) for which at least 6 h are needed to allow expression and understand the potential inflammatory response. The authors declare that there are no conflicts of interest. Transparency document. “
“Drug-induced liver injury (DILI) is one of

the most common adverse event leading to drug attrition during pharmaceutical development (Kola and Landis, 2004) and to drug withdrawals (Wilke et al., 2007) after market introduction. There are many clinical situations and mechanisms leading to DILI. Intracellular accumulation of lipids (steatosis) or phospholipids (phospholipidosis) and inhibition of biliary clearance (cholestasis and hyperbilirubinemia) are regarded as severe pathological features affecting the liver. Following impairment of multiple mechanisms such as mitochondrial β-oxidation, de novo fatty acid synthesis (lipogenesis) or fatty acid release from adipose tissues (lipolysis), neutral lipids can accumulate in hepatocytes leading to micro- and macro-vesicular steatosis ( Begriche et al., 2011 and Labbe et al., 2008).

pouchetii when most of the P. globosa and P. pouchetii cells occur in colonies, suggesting an efficient strategy of cells of embedded colonies for protection against virus-induced mortality ( Hamm et al., 1999 and Ruardij et al., 2005). This also suggested that viral infection, and thus progeny production, can be avoided U0126 clinical trial even at the initial stages of bloom formation and this, in turn, may explain why no virus could be detected within the embedded cells

of older colonies. Moreover, since cyanobacterial colonies were isolated randomly, presumably at different stages following infection, the stage of bloom development at the time of sampling and the length of incubation during the experiments may also influence the detection of viral lysis. For example, if the latent period exceeds 24 h and phages are visible only in the last phase of infection (~ 10% of the pre-lysis period; Waterbury & Valois 1993), a longer incubation period would

be required in order to detect cell lysis and virus production. Indeed, even learn more if adsorption of the virus to the cell surface of colony-embedded cells were possible, the actual rates of infection at the initial and exponential phases of bloom development would generally be low, increasing significantly only during the bloom termination phase ( Granhall, 1972 and Coulombe and Robinson, 1981). Therefore, assuming that only a small fraction of colonies in the exponential phase (data not shown) was isolated from the natural population, it is possible that the actual infection and lysis rate of colony-embedded cyanobacteria in the Curonian Lagoon is under-represented in the results. Hewson et al. (2004) have demonstrated prophage induction in colonies of Trichodesmium. However, the absence of mitomycin C-inducible prophages in isolated colonies of A. flos-aquae and M. aeruginosa may indicate that lysogeny is not the main strategy

of viral attack in these species. On the other hand, not all prophages are induced by mitomycin C or by other inducing agents such as UV radiation, intense light, heat, chemicals etc. ( Paul & Weinbauer 2010). It has also been shown that colony formation may lead to antibiotic resistance, including resistance to mitomycin C ( Martínez & Rojo 2011 and references therein). Furthermore, some studies indicate that a seasonal pattern of lysogeny may exist that depends on the Adenosine triphosphate prevailing temperature conditions ( Cochran and Paul, 1998 and McDaniel et al., 2002). For example, Cochran & Paul (1998) have shown that prophage induction occurs only when the water temperature exceeds 19 °C, which is greater than the temperature used in the present study. To date, there is but scanty information on the M. aeruginosa prophage ( Yoshida et al. 2008a) and no investigations have yet demonstrated that the A. flos-aquae genome contains known prophage sequences ( Cao et al. 2014). Collectively, these factors all have the potential to frustrate the detection of lysogeny in our samples.