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Vertical lines show the 95% SB-715992 pointwise confidence limits whereas SAR302503 cell line stars indicate that the mean densities differed significantly between the reserve and Koyiaki Large sized herbivores Buffalo and elephant were consistently more abundant in the reserve than in the ranches in both seasons (Fig. 4b, d; Tables S1, S2). Eland had higher densities in the

ranches than in the reserve in the wet season but lower densities in the ranches than in the reserve in the dry season (Fig. 4a). Giraffe did not show significant differences between the reserve and the ranches during the dry season, but were somewhat more abundant in the reserve. However, they were consistently more abundant in the ranches than the reserve in the wet season (Fig. 4c; Tables S1, S2). Fig. 4 Comparative changes in densities

(number/km2) of large pure grazers and mixed grazer/browsers, a eland, b buffalo, c giraffe and d elephant between the Mara Reserve (light bars) and the adjoining Koyiaki pastoral ranch (dark bars) during the dry and wet seasons based on the DRSRS aerial surveys from 1977 to 2010. Vertical lines show the 95% pointwise confidence limits whereas stars indicate that the mean densities differed significantly between the reserve and Koyiaki The ground counts conducted Natural Product Library in vitro in 1999 and 2002 confirmed that both gazelles, impala and giraffe were indeed more abundant in the ranches and that topi, hartebeest, wildebeest, zebra, eland, buffalo and elephant were more abundant in the reserve second than in the ranches in the dry season, as revealed by the aerial survey data. High variance in herd sizes rendered the apparently large differences in wildebeest densities between landscapes statistically insignificant. The ground counts also confirmed the greater abundance of livestock in the ranches than

in the reserve shown by the aerial survey data (Table 2). Table 2 Comparisons of mean herbivore densities between the Mara Reserve (808 km2) and Koyiaki pastoral ranch (649 km2) based on ground mapping censuses conducted in November 1999 and 2002 Species November 1999 November 2002 Ranches Reserve Ranches Reserve Thomson’s gazelle 15.97 16.70 28.13 21.30 Sheep + goats 31.28 2.02 61.96 9.19 Impala 9.24 4.49 12.22 6.08 Warthog 0.50 0.83 0.74 1.38 Grant’s gazelle 1.68 1.52 1.96 2.72 Topi 2.68 4.38 3.79 4.21 Wildebeest 12.75 79.21 25.58 108.35 Hartebeest 0.14 0.38 0.16 0.42 Waterbuck 0.25 0.34 0.35 0.27 Cattle 16.84 4.08 34.30 15.98 Zebra 7.90 11.95 15.80 21.01 Eland 0.20 1.00 0.15 1.37 Buffalo 0.50 1.27 0.08 1.31 Giraffe 0.59 0.24 0.65 0.25 Elephant 0.07 0.56 0.09 0.55 Densities that differ significantly (P < 0.

salmonicida subsp. salmonicida JF2267 were loaded for normalization. DNA bands were stained with ethidium bromide for control and transferred onto a nylon membrane (Roche Diagnostics,

Mannheim, Germany) with a VacuGene apparatus (GE Healthcare Bio-Sciences). The IS630 probe was prepared by PCR using primers Clust_asa1052_S6 (5′- AGGCAGAACTTGGGGTTCTT-3′) and Clust_asa1052_R4 (5′- ACAAAAGCGGGTTGTCACTC-3′) EVP4593 and DNA of A. salmonicida subsp. salmonicida JF2267 as a template. PCR was performed in 30 μL which contained 0.5 μL of Taq DNA polymerase (5 units/μL) (Roche Diagnostics, Mannheim, Germany), 300 nM of each primer, 1.75 mM MgCl2, 200 μM concentrations of each dNTP and 1 μl of the Digoxigenin-11-dUTP (1 nmol/μL) (Roche Diagnostics, Mannheim, Germany). Ruboxistaurin Each reaction involved a denaturing step at 94°C for 5 min followed by 30 cycles of 10 sec at 94°C, 30 sec at 54°C and 60 sec at 72°C and a final extension step of 7 min at 72°C. Bioinformatic analysis The hybridization patterns were scanned and the data were analyzed using the BioNumerics software version 6.6 (Applied Maths, Kortrijk, Belgium). Bands automatically assigned by the computer

were checked visually and corrected manually. Cluster analysis of the IS-RFLP patterns was done by the unweighted pair group method with average linkages (UPGMA) using the Dice coefficient and the following GW786034 mw parameters: 0.5% Optimization, 0% Band filtering, 0.5% Tolerance and ignore uncertain bands. Prediction of T3SS effectors was performed with the Modlab® online software (http://​gecco.​org.​chemie.​uni-frankfurt.​de/​T3SS_​prediction/​T3SS_​prediction.​html) [45]. Stability of IS630 in cultured A. salmonicida subsp. salmonicida The stability of IS630 under growth conditions in TSB medium was assessed by daily 100x dilution of a culture of strain JF2267 at 18°C and at 25°C during 4 days to reach 20 generations. Every day DNA was extracted

from 109 bacteria, digested with XhoI and submitted to southern blot hybridization. Acknowledgements This research Mirabegron was funded by the Swiss National Science Foundation grant no. 31003A-135808. Electronic supplementary material Additional file 1: Table S1: Table showing for each A. salmonicida A449 IS630 copy, the size of the XhoI-digested DNA fragment containing the IS, the inter- or intragenic localization, the characteristics of the adjacent genes, and the association to a region of variability or to other IS elements. (DOC 90 KB) Additional file 2: Table S2: Profound analysis and comparison of published Aeromonas genomes used for Figures 3 and 4. Grey: conserved ORFs; light green: ORFs specific of the species; yellow: IS630; pink: other IS elements; red: putative or characterized virulence factors; mauve: ORFs for resistance to antibiotic or heavy metal; dark green: ORFs associated to pili, fimbriae or flagella; blue: ORFs associated to phage; cyan: tRNA and rRNA; orange: ORFs with homology to eukaryotic genes.

0001   P2 21 (6) 1 (0.3) -20 (-95)     P3

277 (75) 167 (46) -110 (-40)     P4 69 (19) 197 (54) +128 (+185)   Number of cases exceeding wait-time targets, n (%)       <0.0001   P2 13 (62) 0 (0) -13 (-100)     P3 92 (33) 41 (25) -51 (-55) RXDX-101     P4 2 (3) 2 (1) 0 (0)   Median wait-times by priority, days (range)       0.94   P2 15 (2–29) 9 (N/A) -6 (-40)     P3 21 (0–90) 15 (0–90) -6 (-29)     P4 33 (6–92) 22 (0–90) -11 (-33)   Type of cancer, n (%)       0.027   Breast 104 (28) 79 (22) -25 (-24)     Colorectal 119 (32) 151 (41) +32 (+27)     Hepatopancreatobiliary 8 (2) 18 (5) +10 (+125)     Gastric 10 (3) 5 (1) -5 (-50)     Endocrine 100 (27) 94 (26) -6 (-6)     Lymph 1 (0) 0 (0) -1 (-100)     Soft-tissue sarcoma 6 (2) 8 (2) +2 (+33)     Skin carcinoma1 4 (1) 2 (1) -2 (-50)     Skin melanoma 15 (4) 7 (2) -8 (-53)   1Includes basal and squamous cell carcinoma. The distribution of general surgery cancer cases by priority level was significantly different (p < 0.0001) between the eras: in the post-ACCESS period, P2 and P3 cases declined by 95% and 40%, respectively, while P4 cases rose by 185%. There was no significant change in wait-times for elective general surgery cancer cases pre- and post-ACCESS, according to priority status. However, the proportion of cases that exceeded

assigned wait-time RG7420 nmr targets in the post-ACCESS A-1210477 cost era declined

by 100% and 55% for P2 and P3 cases, respectively (p < 0.0001), while the proportion of P4 cases that exceeded wait-time targets did not change (Table 2). There was also a significant change in the type of cancer operated by general surgeons post-ACCESS: breast cancer, skin carcinoma, and skin melanoma cases declined by 24%, 50%, and 53%, respectively, whereas colorectal and hepatobiliary cases increased by 27% and 125%, respectively (p = 0.027). There were 3309 cancer surgeries performed by non-general surgeon specialists at VH during the study periods (Table 3). There was a 4% reduction in the total number of cancer surgeries performed in the post-ACCESS era. The distribution of cancer cases by priority level was also significantly different post-ACCESS Florfenicol (p < 0.0001): P2 and P3 cases declined by 49% and 25%, respectively, while P4 cases rose by 62%. Furthermore, the number of cases that exceeded wait-time targets based on their designated priority levels declined by 100% and 55% for P2 and P3 cases, respectively, post-ACCESS (p < 0.0001). There was no significant change in the length of wait-times for elective cancer cases pre- and post-ACCESS. Additionally, the proportions by type of cancer treated at VH was significantly different post-ACCESS (p < 0.

The genes in cluster C showed a progressive permanent induction in their mean expression behaviour. Each column of the heat map EPZ015938 represents one time point after shift from pH 7.0 to pH 5.75 in the following order: 3, 8, 13, 18, 33, and 63 minutes. The values in the boxes are the M-values of a specific gene represented in a row. The background colour visualises the strength of the induction/lower expression (red/green) by the

colour intensity. (JPEG 275 KB) Additional file 4: Heat map of cluster D of the eight clusters calculated by K-means clustering of the transcriptional Nutlin-3a data obtained by microarray analysis of the S. meliloti 1021 pH shock time course experiment. Cluster D comprises carbon uptake and fatty acid

degradation genes. The containing genes were transiently up-regulated during the first 10 to 30 minutes following the pH shift. Each column of the heat map represents one time point after shift from pH 7.0 to pH 5.75 in the following order: 3, 8, 13, 18, 33, and 63 minutes. The values in the boxes are the M-values of a specific gene represented in a row. The background colour visualises the strength of the induction/lower expression (red/green) by the colour intensity. (JPEG 210 KB) Additional file 5: Heat map of cluster E of the eight clusters Wortmannin calculated by K-means clustering of the transcriptional data obtained by microarray analysis of the S. meliloti 1021 pH shock time course experiment. Cluster E contains genes involved in nitrogen metabolism, ion transport and amino acid biosynthesis. These genes were decreased in their expression value up to 20 minutes after pH shift and then stayed permanently down-regulated. Each column of the heat map represents one time point after shift from pH 7.0 to pH 5.75 in the following order: 3, 8, 13, 18, 33, and 63 minutes. The values in the boxes are the M-values of a specific gene represented in a row. The background colour visualises Ergoloid the strength of the induction/lower expression (red/green) by the colour

intensity. (JPEG 236 KB) Additional file 6: Heat map of cluster F of the eight clusters calculated by K-means clustering of the transcriptional data obtained by microarray analysis of the S. meliloti 1021 pH shock time course experiment. Cluster F is almost exclusively composed of genes playing a role in chemotaxis and motility. Genes in this cluster showed a progressive permanent repression for the duration of the time course. Each column of the heat map represents one time point after shift from pH 7.0 to pH 5.75 in the following order: 3, 8, 13, 18, 33, and 63 minutes. The values in the boxes are the M-values of a specific gene represented in a row. The background colour visualises the strength of the induction/lower expression (red/green) by the colour intensity.

Utility NSC23766 values in the general men population as well as relative reductions due to fractures in the year following the fracture and in subsequent years were derived from a systematic review, which suggested reference values for countries that do not have their own database [37]. The reduction of quality-adjusted life-year (QALY) depends on fracture site but also on the number of prior fractures [18]. In the case of an occurrence

of a second fracture at the same site, the impact of the first fracture event was reduced by 50 % [18]. For example, if a men with a prior hip fracture suffered another fracture, the relative reduction of utility attributable to the first hip fracture was then 0.95. For an individual with both a hip and vertebral clinical fracture, the total impact on QALY was assumed to be equal to find more the sum of the impacts related to each of the fractures. This last assumption is consistent with the study of Tosteson et al. [38], who suggested AP26113 mouse that the impact of the two fractures is even greater than the sum of the impacts related to each of the fractures. The model, however, does not simulate multiple fractures per 6-month cycle.

Patient groups Analyses were conducted in the population from the MALEO Trial corresponding to men with mean age of 73 years, and with a bone mineral density (BMD) T-score below the threshold value for osteoporosis (i.e., BMD T-score ≤−2.5) or PVFs at baseline, in order to match the two populations for whom postmenopausal osteoporosis

Rebamipide medications are currently reimbursed in Belgium and in most European countries. The MALEO Trial included in the Full Analysis Set (FAS) 243 men aged 65 to 90 years with osteoporosis as assessed by a mean lumbar spine BMD T-score of −2.7 [15]. The mean BMD at the femoral neck was 0.627 (g/cm2), which corresponds to a T-score of approximately −2.2. The incidence of fracture in the general population has to be adjusted to accurately reflect the fracture risk in these populations. The relative risks of fracture were calculated from the BMD and the prevalence of vertebral fracture in the target patient groups. The relative risk for BMD was calculated using a method previously described [25]. This method estimates the risk of individuals at a threshold value or below a threshold value in comparison with that in the general population. BMD values at the femoral neck were derived from the National Health and Nutrition Examination Survey (NHANES) III [39] database and 1 standard deviation decrease in BMD was associated with an increase in age-adjusted relative risk of 1.8, 1.4 and 1.6 for clinical vertebral, wrist and other fracture, respectively [40]. For hip fracture, the age-adjusted relative risk ranged from 3.68 at 50 years to 1.93 at 85 years [41]. So, for example, the relative risks of fracture, for men aged 73 years with a BMD of 0.627 (g/cm2) at the femoral neck, were estimated at 1.683, 1.529, 1.330 and 1.

Int J Radiat Oncol Biol Phys 2001, 51:261–266.PubMedCrossRef 22. Mundt AJ, Mell LK, Roeske JC: Preliminary analysis of chronic gastrointestinal toxicity inGynecology patients treated with intensity-modulated whole pelvic radiation therapy. Int J Radiat Oncol Biol Phys 2003, 56:1354–1360.PubMedCrossRef 23. Huang EH, Pollack A, Levy L, Starkschall G, Dong L, Rosen SCH727965 mw I, Kuban DA: Late rectal toxicity: dose–volume effects of conformal radioPictilisib in vivo therapy for prostate cancer. Int J Radiat Oncol Biol Phys 2002, 54:1314–1321.PubMedCrossRef 24. Sanguineti G, Agostinelli S, Foppiano F, Franzone P, Garelli S, Marcenaro M, Orsatti

M, Vitale V: Adjuvant androgen deprivation impacts late rectal toxicity after conformal MLN8237 molecular weight radiotherapy of prostate carcinoma. Br J Cancer 2002, 86:1843–1847.PubMedCentralPubMedCrossRef 25. Arcangeli G, Saracino B, Gomellini S, Petrongari MG, Arcangeli S, Sentinelli S, Marzi S, Landoni V, Fowler J, Strigari L: A prospective phase III randomized trial of hypofractionation versus conventional fractionation in patients with high-risk prostate cancer. Int J Radiat Oncol Biol Phys 2010,78(1):11–18.PubMedCrossRef 26. Cancer Therapy

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cancer: recommendations of the RTOG-ASTRO Phoenix Consensus Conference. Int J Radiat Oncol Biol Phys 2006, 65:965–974.PubMedCrossRef 28. Barry MJ, Fowler FJ Jr, O’Leary MP, Bruskewitz RC, Holtgrewe HL, Mebust WK, Cockett AT: The American Urological Association symptom index for benign prostatic hyperplasia. The Measurement Committee of the American Urological Association. J Urol 1992, 148:1549–1557.PubMed 29. Michalski JM, Winter K, Purdy JA, Parliament M, Wong H, Perez CA, Roach M, Bosch W, Cox JD: Toxicity after three-dimensional radiotherapy for prostate cancer on RTOG 9406 dose level V. Int J Radiat Oncol Biol Phys 2005, 62:706–713.PubMedCrossRef 30. Michalski J, Gay H, Jackson A, Tucker S, Deasy J: Radiation dose–volume effects in radiation-induced rectal injury. Int J Radiat Oncol Biol Phys 2010,76(3 Supplement):S123-S129.PubMedCentralPubMedCrossRef 31. Martin JM, Bayley A, Bristow R, Chung P, Gospodarowicz M, Menard C, Milosevic M, Rosewall T, Warde PR, Catton CN: Image guided dose escalated prostate radiotherapy: still room to improve. Radiat Oncol 2009, 4:50.PubMedCentralPubMedCrossRef 32.

PubMedCrossRef 25. Eyers M, Chapelle S, Van Camp G, Goossens H, Wachter RD: Discrimination among thermophilic Campylobacter species by polymerase chain reaction amplification of 23 S rRNA gene fragments. J Clin Microbiol 1994,32(6):1623.PubMed 26. Sambrook J, Fritsch EF, Maniatis T: Molecular cloning: SCH772984 manufacturer a laboratory manual. 2nd edition. Cold Spring Harbor Laboratory Press, Cold Spring Harbor, N.Y; 1989. Competing interests The authors declare that they have no competing interests. Authors’ contribution CJD Performed and Epacadostat concentration planned experiments and wrote large portions of the final manuscript. LEHT Performed and planned experiments

and wrote large portions of the final manuscript. LKS Produced antibody for analysis of Tlp1 and performed experiments utilising this antibody. Also helped in the preparation of the final manuscript. RMK Helped plan and performed animal work and helped prepare the final manuscript. GT Performed and planned many of the experiments

selleck inhibitor involving Tlp11 and helped prepare the final manuscript. SKD Identified, isolated and provided fresh clinical isolates for this publication. EAS Helped perform animal work and preparation and performing of experiments involving GCH isolates and aided in the preparation of the final manuscript. VK Devising of initial experiment, planning of experiments and drafting of the manuscript. All authors read and approved the final manuscript.”
“Background Lignin is, after cellulose, the second most abundant terrestrial biopolymer, accounting for approximately 30% of the organic carbon in the biosphere [1]. The biodegradation of lignin plays a crucial role in the earth’s carbon cycle. Unlike cellulose and hemicellulose, this amorphous and insoluble aromatic material lacks

stereoregularity and is not susceptible to hydrolytic attack. In nature, the white-rot fungus Phanerochaete chrysosporium is among the small group of fungi that can completely degrade lignin to carbon dioxide while leaving the crystalline cellulose untouched [2]. Lignin MycoClean Mycoplasma Removal Kit degradation by P. chrysosporium is initiated by an array of extracellular oxidases and peroxidases, such as the multiple isoenzymes of lignin peroxidase (LiP) and manganese-dependent peroxidase (MnP) [3–6]. Both LiP and MnP require extracellular H2O2 for their catalytic activity. One likely source of H2O2 is the copper radical oxidases, such as glyoxal oxidase [7–9]. In addition to the copper radical oxidases, the FAD-dependent extracellular aryl-alcohol oxidases (Aaop) catalyze the oxidation of aryl-alcohol derivatives into their corresponding aldehydes with the concomitant reduction of O2 to H2O2[6, 10]. The Aaop substrates, like the physiologically-significant secondary metabolite 3,4-Dimethoxybenzyl (Veratryl) alcohol [11], can originate, firstly, through de novo biosynthesis [12] and secondly, through reduction of aromatic aldehydes released during lignin degradation in cyclic redox reactions involving also aryl-alcohol dehydrogenase (Aadp) [13–17].

To identify the selleck inhibitor alternative route for cellular entry of R9/GFP complexes in cyanobacteria, we used

macropinocytic inhibitors 5-(N-ethyl-N-isopropyl)-amiloride (EIPA), wortmannin, and cytochalasin D (CytD) in cells pretreated LY3023414 cell line with NEM to block clathrin- and caveolin-dependent endocytosis. The cells were treated with either R9/GFP as a control or R9/GFP plus macropinocytic inhibitors. Significant reductions in the intensity of cellular green fluorescence were observed in treatments with CytD and wortmannin in the 6803 strain of cells, and with all of the macropinocytic inhibitors in the 7942 strain of cells (Figure 3). Wortmannin was the most effective inhibitor in the 6803 strain, while EIPA was the most effective inhibitor in the 7942 strain (Figure 3). These results indicate that protein transduction of R9 in cyanobacteria involves lipid raft-dependent macropinocytosis. Figure 3 The mechanism of the CPP-mediated GFP delivery in 6803 and 7942 strains of cyanobacteria. Cells were treated with NEM and R9/GFP mixtures in the absence or presence of CytD, EIPA, or wortmannin (Wort), as indicated. Results were observed in the GFP channel using a confocal microscope, and fluorescent intensities

were analyzed by the UN-SCAN-IT software. Data are presented as mean ± SD from three independent experiments. Significant differences of P < 0.05 (*) are indicated. Cytotoxicity To investigate whether treatments with R9 and GFP are toxic BI 2536 in vivo and cause membrane leakage, cytotoxicity was evaluated using cells treated

with BG-11 medium and 100% methanol as negative and positive controls, respectively. In the presence of NEM, cells were incubated with R9/GFP complexes mixed with CytD, EIPA, or wortmannin as experimental groups, respectively. The 1-(4,5-dimethylthiazol-2-yl)-3,5-diphenylformazan (MTT) assay was applied. There is a significant correlation (R2 = 0.9949) between cell number and activity of MTT reduction (Additional file 2: Figure S2A). Further, 100% methanol, 100% dimethyl sulfoxide (DMSO), and autoclave treatments were effective in causing cell death (Additional file 2: Figure S2B). We chose 100% methanol treatment as a positive control for cytotoxicity analysis. The 6803 strain treated with R9/GFP complexes mixed with CytD, EIPA, or wortmannin in the presence of NEM was analyzed by the MYO10 MTT assay. No cytotoxicity was detected in experimental groups, but significant reduction in cell viability was observed in the positive control (Figure 4A). To further confirm the effect of endocytic modulators on cell viability, the membrane leakage assay was conducted. No membrane damage was detected in the negative control and experimental groups (Figure 4B). These data indicate that R9/GFP and endocytic modulators were nontoxic to cyanobacteria. Figure 4 Cell viability of the R9/GFP delivery system in the presence of uptake modulators. (A) The MTT assay.

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K, Hiramoto T, Fukuda T, Miyagawa K: A novel human rad54 homologue, Rad54B, associates with Rad51. J Biol Chem 2000, 275:26316–26321.PubMedCrossRef 21. Cote P, Hogues H, Whiteway M: Transcriptional analysis of the Candida albicans cell cycle. Mol Biol Cell 2009, 20:3363–3373.PubMedCrossRef 22. Reuss O, Vik A, Kolter R, Morschhauser J: The SAT1 flipper, an optimized tool for gene disruption in Candida albicans. Gene 2004, 341:119–127.PubMedCrossRef 23. Andaluz E, Ciudad T, Gomez-Raja J, Calderone R, Larriba G: Rad52 depletion

in Candida albicans triggers both the DNA-damage checkpoint and filamentation accompanied VEGFR inhibitor by but independent of expression of hypha-specific genes. Mol CP673451 mouse Microbiol 2006, 59:1452–1472.PubMedCrossRef 24. Garcia-Prieto F, Gomez-Raja J, Andaluz E, Calderone R, Larriba G: Role of the homologous recombination genes RAD51 and RAD59 in the resistance of Candida albicans to UV light, radiomimetic and anti-tumor compounds and oxidizing agents. Fungal Genet Biol 2010, 47:433–445.PubMedCrossRef 25. Weinert TA, Kiser GL, Hartwell LH: Mitotic checkpoint genes in budding yeast and the dependence of mitosis on DNA replication and repair. Genes Dev 1994, 8:652–665.PubMedCrossRef 26. Shi QM, Wang YM, Zheng XD, Lee RT, Wang Y: Critical role of DNA checkpoints in mediating genotoxic-stress-induced

filamentous growth in Candida albicans. Mol Biol Cell 2007, 18:815–826.PubMedCrossRef 27. Chi P, Kwon Y, Seong C, Epshtein A, Lam I, Sung P, Klein HL: Yeast recombination factor Rdh54 functionally interacts with the Rad51 recombinase Ketotifen and catalyzes Rad51 removal from DNA. J Biol Chem 2006, 281:26268–26279.PubMedCrossRef 28. Symington LS: Role of RAD52 epistasis group genes in homologous recombination and double-strand break repair. Microbiol Mol Biol Rev 2002, 66:630–670. table of contentsPubMedCrossRef 29. Ciudad T, Andaluz E, Steinberg-Neifach O, Lue NF, Gow NA, Calderone RA, Larriba G: Homologous recombination in Candida albicans: role of CaRad52p in DNA repair, integration of linear DNA fragments and telomere length. Mol Microbiol 2004, 53:1177–1194.PubMedCrossRef 30. Bezzubova O, Silbergleit A, Yamaguchi-Iwai Y, Takeda S, Buerstedde JM: Reduced X-ray resistance and homologous recombination frequencies in a RAD54-/- mutant of the chicken DT40 cell line. Cell 1997, 89:185–193.PubMedCrossRef 31.