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Ell as between different age groups. However, a significant negative association
Ell as between different age groups. However, a significant negative association was noted between sperm DNA damage and advancing paternal age. Men >40 y showed higher levels of sperm DNA damage (24.4 ?18.5 ) compared to younger men (<30 y; 16.7 ?11.2 ; p <0.05). Conclusions: Infertile men over the age of 40 y have a greater percentage of sperm DNA fragmentation compared to infertile men aged 40 y and below. Advanced paternal age (>40 y) may increase the risk of sperm DNA damage in infertile men. Keywords: Paternal age, Sperm DNA damage, Male infertility, Semen parametersBackground Many couples in developed countries are delaying parenthood for a variety of reasons [1-3]. Most believe that delayed parenthood has many advantages [4]. In England and Wales, 25 of live births in 1993 were to fathers older than 35 y but after 10 years, the percentage increased to 40 [5]. In the USA, birth rates for men older than 35 y have increased 40 since 1980 [2,6]. The effect of maternal ageing on fertilization and reproduction is well known [7]. Several studies have shown that women over 35 y have a higher risk of infertility, pregnancy complications, spontaneous abortion, congenital anomalies, and perinatal complications [2,8-10]. On the other hand, the effect of paternal age on semen* Correspondence: [email protected] 1 Glickman Urological and Kidney Institute, Center for Reproductive Medicine, Cleveland Clinic, Cleveland, OH, USA Full list of author information is available at the end of the articlequality is controversial for a couple of reasons. First, there is no universal definition for advanced paternal ageing. The mean population age for paternal age is 21 y, and 40 y is the most frequently used cutoff to describe advanced paternal ageing [2]. Secondly, the literature is full of studies with conflicting ML240 chemical information results, especially for the most common parameters tested (volume, concentration, motility, total sperm count, morphology) [11-17]. A recent meta-analysis showed a consistent impact of advanced age on semen volume but the effect on the other semen parameters was inconsistent [18]. Advancing paternal age has a negative impact on semen volume [15,19,20], sperm motility [19,20], and normal morphology [19,21,22]. Sperm concentration did not show any correlation with male age [23,24] while another report showed an increase with age [25]. Advancing paternal age also has been associated with increased risk of genetic disease [26,27], schizophrenia?2014 Alshahrani et al.; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original PubMed ID:https://www.ncbi.nlm.nih.gov/pubmed/29072704 work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.Alshahrani et al. Reproductive Biology and Endocrinology 2014, 12:103 http://www.rbej.com/content/12/1/Page 2 of[28], autism [26], and other complex disorders [29]. Several studies show that advanced paternal age increases the risk of spontaneous abortions [30,31], and increased risk of low birth weight [32]. De La Rochebrochard and Thonneau found that men who were older than 40 y were at high risk for infertility [33]. The same group also reported higher risk of infecundity and miscarriages in women 35 y a.

Ate with those gathered for markers of inflammation in BALF samples.

Ate with those gathered for markers of inflammation in BALF samples.strain LPS), PBS, GSH, TAU, TCA, SSA, TEP and TBA were from Sigma-Aldrich, St. Louis, MO; 0.1 N and 6 N HCl were from Mallinckrodt Baker, Inc., Phillipsburg, NJ; and metaphosphoric acid was from Aldrich Chemical Co., Inc., Milwaukee, WI.AnimalsFemale Golden Syrian hamsters (5-6 weeks old, 100?5 g in weight, 6 per group) were purchased from Harlan, Indianapolis, IN, USA. The animals were housed in a temperature-controlled room (21? ) with a 12 hr light-12 hr dark cycle; and had free access to a standard hamster chow and filtered tap water for at least 7 days. The study received the approval of the Institutional Animal Care and Use Committee of St. John’s University, and the animals were cared in accordance with the guidelines established by the United States Department of Agriculture.Treatments with LPS and TAUTo determine the effects of a pretreatment with taurine on LPS-induced lung injury, hamsters were treated with TAU (as a solution in phosphate buffered saline (PBS) pH 7.4, 50 mg/kg/0.5 ml/day) by the intraperitoneal (i. p.) route for 3 days, followed successively by an i.p. dose of purchase PNPP pentobarbital sodium (90 mg/kg/0.4 ml) to induce anesthesia, and an intratracheal (i.t.) PubMed ID:https://www.ncbi.nlm.nih.gov/pubmed/28607003 instillation of LPS (0.2 ml of 0.1 mg/ml in PBS pH 7.4) on day 4. Controls were treated with: (a) i.p. PBS pH 7.4 for 3 days followed by i.t. LPS on day 4 (positive control), and (b) only i.t. PBS pH 7.4 on day 4 (negative control). To determine the effects of a posttreatment with TAU on LPS-induced lung injury, the hamsters received LPS (0.2 ml of 0.1 mg/ml in PBS pH 7.4) by i.t. instillation on day 1, followed by TAU (as a solution in phosphate buffered saline (PBS) pH 7.4, 50 mg/kg/0.5 ml/day) by i.p. route for 3 days. Control animals were treated with (a) i.t. LPS on day 1 followed by i.p. PBS pH 7.4 on days 2 to 4 (positive control), and (b) only with i.t. PBS pH 7.4 (negative control). All i.t. instillations were carried out using a 1-ml syringe fitted with a 27-gauge needle. Following an i.t. delivery, the incision was closed with metal clips.Collection of lung and BALF samplesMethodsMaterials and chemicalsAll the chemicals, reagents and assay kits used in the study were purchased from commercial sources in the USA. H2O2 (30 w/w), LPS (serotype: O26:B6 obtained from American Type Culture Collection no. 12795; with short chain-length approximating that of mutant roughOn day 5, 24 h after a LPS instillation or a TAU treatment, the animals were sacrificed using a high dose of pentobarbital sodium (240 mg/kg/0.7 ml, i.p.), and BALF Velpatasvir cancer samples were collected by rinsing the bronchoalveolar surface with PBS pH 7.4, and bringing the volume of the pooled washings to 10 ml with additional PBS pH 7.4. Immediately thereafter, the lungs were surgically removed, washed without delay with ice-cold physiologic saline, patted dry with filter paper,Bhavsar et al. Journal of Biomedical Science 2010, 17(Suppl 1):S19 http://www.jbiomedsci.com/content/17/S1/SPage 3 offrozen in liquid nitrogen, and kept at -20 until used in an assay.Preparation of lung homogenatesFollowing their removal, the lung samples were rinsed immediately with physiological saline, patted dry with filter paper, weighed, and perfused with ice-cold physiologic saline. A portion of lung sample was mixed with PBS pH 7.4 in a 1:30 (w/v) ratio and made into a fine homogenate with a hand held tissue homogenizer (Tissue-Tearor? BioSpec Products, Inc.,.Ate with those gathered for markers of inflammation in BALF samples.strain LPS), PBS, GSH, TAU, TCA, SSA, TEP and TBA were from Sigma-Aldrich, St. Louis, MO; 0.1 N and 6 N HCl were from Mallinckrodt Baker, Inc., Phillipsburg, NJ; and metaphosphoric acid was from Aldrich Chemical Co., Inc., Milwaukee, WI.AnimalsFemale Golden Syrian hamsters (5-6 weeks old, 100?5 g in weight, 6 per group) were purchased from Harlan, Indianapolis, IN, USA. The animals were housed in a temperature-controlled room (21? ) with a 12 hr light-12 hr dark cycle; and had free access to a standard hamster chow and filtered tap water for at least 7 days. The study received the approval of the Institutional Animal Care and Use Committee of St. John’s University, and the animals were cared in accordance with the guidelines established by the United States Department of Agriculture.Treatments with LPS and TAUTo determine the effects of a pretreatment with taurine on LPS-induced lung injury, hamsters were treated with TAU (as a solution in phosphate buffered saline (PBS) pH 7.4, 50 mg/kg/0.5 ml/day) by the intraperitoneal (i. p.) route for 3 days, followed successively by an i.p. dose of pentobarbital sodium (90 mg/kg/0.4 ml) to induce anesthesia, and an intratracheal (i.t.) PubMed ID:https://www.ncbi.nlm.nih.gov/pubmed/28607003 instillation of LPS (0.2 ml of 0.1 mg/ml in PBS pH 7.4) on day 4. Controls were treated with: (a) i.p. PBS pH 7.4 for 3 days followed by i.t. LPS on day 4 (positive control), and (b) only i.t. PBS pH 7.4 on day 4 (negative control). To determine the effects of a posttreatment with TAU on LPS-induced lung injury, the hamsters received LPS (0.2 ml of 0.1 mg/ml in PBS pH 7.4) by i.t. instillation on day 1, followed by TAU (as a solution in phosphate buffered saline (PBS) pH 7.4, 50 mg/kg/0.5 ml/day) by i.p. route for 3 days. Control animals were treated with (a) i.t. LPS on day 1 followed by i.p. PBS pH 7.4 on days 2 to 4 (positive control), and (b) only with i.t. PBS pH 7.4 (negative control). All i.t. instillations were carried out using a 1-ml syringe fitted with a 27-gauge needle. Following an i.t. delivery, the incision was closed with metal clips.Collection of lung and BALF samplesMethodsMaterials and chemicalsAll the chemicals, reagents and assay kits used in the study were purchased from commercial sources in the USA. H2O2 (30 w/w), LPS (serotype: O26:B6 obtained from American Type Culture Collection no. 12795; with short chain-length approximating that of mutant roughOn day 5, 24 h after a LPS instillation or a TAU treatment, the animals were sacrificed using a high dose of pentobarbital sodium (240 mg/kg/0.7 ml, i.p.), and BALF samples were collected by rinsing the bronchoalveolar surface with PBS pH 7.4, and bringing the volume of the pooled washings to 10 ml with additional PBS pH 7.4. Immediately thereafter, the lungs were surgically removed, washed without delay with ice-cold physiologic saline, patted dry with filter paper,Bhavsar et al. Journal of Biomedical Science 2010, 17(Suppl 1):S19 http://www.jbiomedsci.com/content/17/S1/SPage 3 offrozen in liquid nitrogen, and kept at -20 until used in an assay.Preparation of lung homogenatesFollowing their removal, the lung samples were rinsed immediately with physiological saline, patted dry with filter paper, weighed, and perfused with ice-cold physiologic saline. A portion of lung sample was mixed with PBS pH 7.4 in a 1:30 (w/v) ratio and made into a fine homogenate with a hand held tissue homogenizer (Tissue-Tearor? BioSpec Products, Inc.,.

Cells (buffy coat), which were stored at -80 until further processing

Cells (buffy coat), which were stored at -80 until further processing [66, 67].DNA extraction and bisulfite treatmentDNA was isolated from the buffy coat using the QIAamp DNA Blood Mini Kit (Qiagen, Zebularine web Hilden, Germany) by following the manufacturer’s instructions. EpiTect Bisulfite Kit (Qiagen) was used for bisulfite conversion and cleanup of DNA, during which unmethylated cytosines were converted to uracils and the methylated cytosines were conserved [20, 68]. DNA quality and quantity were examined with a Synergy H4 Hybrid Multi-Mode Microplate Reader (BioTek Instruments, Winooski, VT, USA) and then stored in aliquots at -20 until further assay.Measurement of mtDNAnThe methylation of D-loop region was determined by methylation-specific PCR as descried previously [20, 68]. Briefly, the D-loop sequence 16024?76 (1,122 bp) of the Homo sapiens mitochondrion genome (gi|251831106: c576-1, c16569-16024) was used to identify the CpG island (426?76) and design primers for PCR analysis. The following two pairs of primers were designed: one pair was specific for bisulfite-modified methylated DNA, and the other pair was specific for bisulfite-modified unmethylated DNA amplifying heavy strand. The primers used in this study were TAGGAATTAAAGATAGAT ATTGCGA (forward, starting position at 434 nt) and 5ACTCTCCA TACATTTAATATTTTCGTC-3 (reverse, starting position at 539 nt) for methylated D-loop; 5GGTAGGAATTAAA PubMed ID:https://www.ncbi.nlm.nih.gov/pubmed/27362935 GATAGATATTGTGA-3 (forward, starting position at 432 nt) and 5-ACTCTCCATACATT TAATATTTTCATC-3 (reverse, starting position at 539 nt) for unmethylated D-loop. The bisulfite-modified DNA was used as a template for methylation-specific PCR (MSP) on a ViiATM 7 Real-Time PCR System, using SYBR?Green PCR Master Mix (Life Technology, Grand Island, NY, USA). Two MSPs were performed simultaneously to detect the methylated (amplicon size; 106 bp) and unmethylated (amplicon size; 108 bp) D-loop for each sample. The percentage of methylated DNA is calculated as described previously [20, 68].StatisticsThe data are expressed as the mean ?SE unless otherwise specified. Logarithm-transformed data were used for the analysis of skewed variables, such as HOMA-IR and mtDNAn. Pearson’s correlation and regression analysis was applied to evaluate the relationships among Actidione solubility mtDNAn and the metabolic indexes. Statistical significance was set at a probability level of p < 0.05.Additional filesMitochondrial DNA copy number (mtDNAn) was measured as previously described [10, 41]. Briefly, 40 ng total DNA was used for real-time PCR with the iQTM SYBR?Green Supermix (Bio-Rad Laboratories, Hercules, CA, USA) on a ViiATM 7 Real-Time PCR System (Life Technology, Grand Island, NY, USA). The primers used inAdditional file 1: Figure S1. Scatter plot of the measurements and demographic characteristics of lean (n = 8) and obese (n = 32) participants in this study. The middle lines indicate the mean values, and the other two shorter lines indicate SE *p < 0.05; **p < 0.001; ***p < 0.0001. Additional file 2: Figure S2. Age-matched analysis of mtDNAn in lean (n = 7) and obese (n = 8) participants. (A) No significant difference existed between the ages of lean (n = 7) and obese (n = 8) participants. (B)Zheng et al. Clinical Epigenetics (2015) 7:Page 8 ofComparison of mtDNAn between lean (n = 7) and obese (n = 8) participants. The data were presented as mean ?SE. *p < 0.05; NS, not significant. Additional file 3: Figure S3. Regression analyses of mtDNAn with metabolic parameters and demographic.Cells (buffy coat), which were stored at -80 until further processing [66, 67].DNA extraction and bisulfite treatmentDNA was isolated from the buffy coat using the QIAamp DNA Blood Mini Kit (Qiagen, Hilden, Germany) by following the manufacturer's instructions. EpiTect Bisulfite Kit (Qiagen) was used for bisulfite conversion and cleanup of DNA, during which unmethylated cytosines were converted to uracils and the methylated cytosines were conserved [20, 68]. DNA quality and quantity were examined with a Synergy H4 Hybrid Multi-Mode Microplate Reader (BioTek Instruments, Winooski, VT, USA) and then stored in aliquots at -20 until further assay.Measurement of mtDNAnThe methylation of D-loop region was determined by methylation-specific PCR as descried previously [20, 68]. Briefly, the D-loop sequence 16024?76 (1,122 bp) of the Homo sapiens mitochondrion genome (gi|251831106: c576-1, c16569-16024) was used to identify the CpG island (426?76) and design primers for PCR analysis. The following two pairs of primers were designed: one pair was specific for bisulfite-modified methylated DNA, and the other pair was specific for bisulfite-modified unmethylated DNA amplifying heavy strand. The primers used in this study were TAGGAATTAAAGATAGAT ATTGCGA (forward, starting position at 434 nt) and 5ACTCTCCA TACATTTAATATTTTCGTC-3 (reverse, starting position at 539 nt) for methylated D-loop; 5GGTAGGAATTAAA PubMed ID:https://www.ncbi.nlm.nih.gov/pubmed/27362935 GATAGATATTGTGA-3 (forward, starting position at 432 nt) and 5-ACTCTCCATACATT TAATATTTTCATC-3 (reverse, starting position at 539 nt) for unmethylated D-loop. The bisulfite-modified DNA was used as a template for methylation-specific PCR (MSP) on a ViiATM 7 Real-Time PCR System, using SYBR?Green PCR Master Mix (Life Technology, Grand Island, NY, USA). Two MSPs were performed simultaneously to detect the methylated (amplicon size; 106 bp) and unmethylated (amplicon size; 108 bp) D-loop for each sample. The percentage of methylated DNA is calculated as described previously [20, 68].StatisticsThe data are expressed as the mean ?SE unless otherwise specified. Logarithm-transformed data were used for the analysis of skewed variables, such as HOMA-IR and mtDNAn. Pearson’s correlation and regression analysis was applied to evaluate the relationships among mtDNAn and the metabolic indexes. Statistical significance was set at a probability level of p < 0.05.Additional filesMitochondrial DNA copy number (mtDNAn) was measured as previously described [10, 41]. Briefly, 40 ng total DNA was used for real-time PCR with the iQTM SYBR?Green Supermix (Bio-Rad Laboratories, Hercules, CA, USA) on a ViiATM 7 Real-Time PCR System (Life Technology, Grand Island, NY, USA). The primers used inAdditional file 1: Figure S1. Scatter plot of the measurements and demographic characteristics of lean (n = 8) and obese (n = 32) participants in this study. The middle lines indicate the mean values, and the other two shorter lines indicate SE *p < 0.05; **p < 0.001; ***p < 0.0001. Additional file 2: Figure S2. Age-matched analysis of mtDNAn in lean (n = 7) and obese (n = 8) participants. (A) No significant difference existed between the ages of lean (n = 7) and obese (n = 8) participants. (B)Zheng et al. Clinical Epigenetics (2015) 7:Page 8 ofComparison of mtDNAn between lean (n = 7) and obese (n = 8) participants. The data were presented as mean ?SE. *p < 0.05; NS, not significant. Additional file 3: Figure S3. Regression analyses of mtDNAn with metabolic parameters and demographic.

Trol Mean ?SD (n) 18.5 ?1.3 (6) 19.2 ?1.2 (8) 1.47 ?0.19 (6)** 3.45 ?0.82 (8) * 17.1 ?2.4 (6) 51.4 ?19 (8) * 228 ?14.7 (6) 146.4 ?12.1 (8) * RSD 7.3 6.1 12 23 13 36 6.4 8 Zn + genistein Mean ?SD (n) 17.2 ?2.3 (6) 17.0 ?1.1 (10) 1.74 ?0.45 (6) 2.87 ?0.79 (8) * 16.3 ?2.1 (5) 33.4 ?9.6 (10) * 236.8 ?18.7 (6) 160.8 ?9.3 (10) * RSD

Trol Mean ?SD (n) 18.5 ?1.3 (6) 19.2 ?1.2 (8) 1.47 ?0.19 (6)** 3.45 ?0.82 (8) * 17.1 ?2.4 (6) 51.4 ?19 (8) * 228 ?14.7 (6) 146.4 ?12.1 (8) * RSD 7.3 6.1 12 23 13 36 6.4 8 Zn + genistein Mean ?SD (n) 17.2 ?2.3 (6) 17.0 ?1.1 (10) 1.74 ?0.45 (6) 2.87 ?0.79 (8) * 16.3 ?2.1 (5) 33.4 ?9.6 (10) * 236.8 ?18.7 (6) 160.8 ?9.3 (10) * RSD 13 6.6 26 27 12 28 7.8 5.*differences (p 0.05) between concentrations of metals in DMBA (+) and DMBA (-) groups of each type of diet **differences (p 0.05) between concentrations of metals in each type of diet (DMBA-) relative to standard diet (DMBA-) SD – standard deviation; RSD – relative standard deviation ( ); n- number of samplesBobrowska-Korczak et al. Journal of Biomedical Science 2012, 19:43 http://www.jbiomedsci.com/content/19/1/Page 5 ofTable 4 Altered calcium content in cancerous tissues (DMBA+) vs calcium content in normal tissues (DMBA-) (g/g wet weight)Diet DMBA(-) Mean (confidence interval) (n) 234.8 (73.0 – 754.8) (5) 216.4 (54.8 – 854.2) (6) 83.6 (58.5 – 119.5) (6) 64.7** (60.9 – 68.8) (5) DMBA(+) Mean (confidence interval) (n) 404.4 (178.0 – 916.7) (7) 97.8 (82.4 – 115.9) (8) 510.1* (195.4 – 1334.7) (8) 219.7* (97.9 – 493.6) (10) pStandard< 0.343 < 0.949 < 0.001 < 0.ZnZn + resveratrol Zn + genistein*differences between concentrations PubMed ID:https://www.ncbi.nlm.nih.gov/pubmed/28893839 of calcium in DMBA (+) and DMBA (-) groups of each type of diet **differences between concentrations of calcium in each type of diet (DMBA-) relative to standard diet (DMBA-)resulted in strong copper accumulation in malignant tumors. Thus it seems that a key role in this SIS3 site effective accumulation of copper was played by a combination of Zn and DMBA, and to some extent by polyphenols. Copper plays a significant role in the process of neoplastic angiogenesis. Malignant tumors can develop relatively easily up to the size of 1-2 mm3 . Their further growth requires the formation within the tumor of a network of blood vessels that ensure better cell nourishment, and also allow their expansion in the form of metastases [7]. The process of angiogenesis begins as a result of metabolic oxidative stress in tumor cells. The first stage of this process always involves the activation of endothelial cells. The copper ions have a stimulating effect on the proliferation process, through their ONO-4059 web activating role with respect to various growth factors such as VEGF (vascular endothelial growth factor), TNF (tumor necrosis factor), EGF (epidermal growth factor) or IL-1 (interleukin 1). The factors that have been activated bind with receptors in endothelial cells. As a result, the cell passes from phase G0 to phase G1 and the cell proliferation process is activated. Besides, the presence of copper is required for some proteins to obtain antigenic properties, e.g. for ceruloplasmin, angiogenin or glycyl-L-histydyl-L-lysine tripeptide [7]. The investigations of Brem and Wotoczko-Obadio [13] showed that after decreasing copper concentration by using penicillamin and a special diet poor in copper the proliferating cell can enter phase G0 again, or apoptosis can occur, as a result of which the angiogenic activity of VEGF, TNF, EGF or IL-1 is inhibited [13]. Therefore, because of a very important role of copper in tumor angiogenesis, it seems necessary to search forcompounds that would have a chelating effect or that would reduce its amount in the bloodstream. Zinc is a natural copper antagonist. Zinc-induced metallothioneins in intestinal lumen bind to copper thus inhibiting its absorption into.Trol Mean ?SD (n) 18.5 ?1.3 (6) 19.2 ?1.2 (8) 1.47 ?0.19 (6)** 3.45 ?0.82 (8) * 17.1 ?2.4 (6) 51.4 ?19 (8) * 228 ?14.7 (6) 146.4 ?12.1 (8) * RSD 7.3 6.1 12 23 13 36 6.4 8 Zn + genistein Mean ?SD (n) 17.2 ?2.3 (6) 17.0 ?1.1 (10) 1.74 ?0.45 (6) 2.87 ?0.79 (8) * 16.3 ?2.1 (5) 33.4 ?9.6 (10) * 236.8 ?18.7 (6) 160.8 ?9.3 (10) * RSD 13 6.6 26 27 12 28 7.8 5.*differences (p 0.05) between concentrations of metals in DMBA (+) and DMBA (-) groups of each type of diet **differences (p 0.05) between concentrations of metals in each type of diet (DMBA-) relative to standard diet (DMBA-) SD – standard deviation; RSD – relative standard deviation ( ); n- number of samplesBobrowska-Korczak et al. Journal of Biomedical Science 2012, 19:43 http://www.jbiomedsci.com/content/19/1/Page 5 ofTable 4 Altered calcium content in cancerous tissues (DMBA+) vs calcium content in normal tissues (DMBA-) (g/g wet weight)Diet DMBA(-) Mean (confidence interval) (n) 234.8 (73.0 – 754.8) (5) 216.4 (54.8 – 854.2) (6) 83.6 (58.5 – 119.5) (6) 64.7** (60.9 – 68.8) (5) DMBA(+) Mean (confidence interval) (n) 404.4 (178.0 – 916.7) (7) 97.8 (82.4 – 115.9) (8) 510.1* (195.4 – 1334.7) (8) 219.7* (97.9 – 493.6) (10) pStandard< 0.343 < 0.949 < 0.001 < 0.ZnZn + resveratrol Zn + genistein*differences between concentrations PubMed ID:https://www.ncbi.nlm.nih.gov/pubmed/28893839 of calcium in DMBA (+) and DMBA (-) groups of each type of diet **differences between concentrations of calcium in each type of diet (DMBA-) relative to standard diet (DMBA-)resulted in strong copper accumulation in malignant tumors. Thus it seems that a key role in this effective accumulation of copper was played by a combination of Zn and DMBA, and to some extent by polyphenols. Copper plays a significant role in the process of neoplastic angiogenesis. Malignant tumors can develop relatively easily up to the size of 1-2 mm3 . Their further growth requires the formation within the tumor of a network of blood vessels that ensure better cell nourishment, and also allow their expansion in the form of metastases [7]. The process of angiogenesis begins as a result of metabolic oxidative stress in tumor cells. The first stage of this process always involves the activation of endothelial cells. The copper ions have a stimulating effect on the proliferation process, through their activating role with respect to various growth factors such as VEGF (vascular endothelial growth factor), TNF (tumor necrosis factor), EGF (epidermal growth factor) or IL-1 (interleukin 1). The factors that have been activated bind with receptors in endothelial cells. As a result, the cell passes from phase G0 to phase G1 and the cell proliferation process is activated. Besides, the presence of copper is required for some proteins to obtain antigenic properties, e.g. for ceruloplasmin, angiogenin or glycyl-L-histydyl-L-lysine tripeptide [7]. The investigations of Brem and Wotoczko-Obadio [13] showed that after decreasing copper concentration by using penicillamin and a special diet poor in copper the proliferating cell can enter phase G0 again, or apoptosis can occur, as a result of which the angiogenic activity of VEGF, TNF, EGF or IL-1 is inhibited [13]. Therefore, because of a very important role of copper in tumor angiogenesis, it seems necessary to search forcompounds that would have a chelating effect or that would reduce its amount in the bloodstream. Zinc is a natural copper antagonist. Zinc-induced metallothioneins in intestinal lumen bind to copper thus inhibiting its absorption into.

Colonies was much fewerwhen RNPC1a was over-expressed (Figure. 3C, p
Colonies was much fewerwhen RNPC1a was over-expressed (Figure. 3C, p < 0.05). The ability of MCF-7 or MB-231 cell lines to form colonies was much more when RNPC1a was knockdown (Figure. 3D, p < 0.05).RNPC1a suppressed migratory and invasive potentialAs shown in Figure 4A and C, determined by their migration in the wound gap after 18 h, distance migrated ofXue et al. BMC Cancer 2014, 14:322 http://www.biomedcentral.com/1471-2407/14/Page 8 ofFigure 3 RNPC1a suppressed anchorage dependent growth of breast cancer cells. (A, B) Cell cycle progression was measured using flow cytometry. The progression of MCF-7-RNPC1a and MB-231-RNPC1a cells was arrest in the G1 phase compared with control cells, respectively. Representative photographs (upper) and quantification (lower) are shown. (C) The growth of cells over 15 days was measured using colony formation assays. Clone formation of RNPC1a overexpression arbitrarily set at 100 in control cells (NC). The number and size of MCF-7-RNPC1a or MB-231-RNPC1a was significantly decreased compared to control cells, respectively. Representative photographs (lower) and quantification (upper) are shown. Data were means of three separate experiments mean ?SEM, p < 0.05. (D) Clone formation of RNPC1a knockdown arbitrarily set at 100 in knockdown (shRNPC1a) cells. The number and size of MCF-7-shRNPC1a or MB-231-shRNPC1a was significantly increased compared with control cells, respectively. Representative photographs (lower) and quantification (upper) are shown. Data were means of three separate experiments mean ?SEM, p < 0.05. Colonies > 50 mm PubMed ID:https://www.ncbi.nlm.nih.gov/pubmed/25962748 were RDX5791 web counted. Anchorage ependent growth assays were shown at the bottom. Data were means of three separate experiments mean ?SEM, *p < 0.05.RNPC1a overexpression decreased by 69 m (Figure 4A, p < 0.01), while RNPC1a knockdown increased by 110 m (Figure 4C, p < 0.01) compared to the control cells, respectively. We conducted three-dimensional cell migration assay using transwell chambers and invasion assay with Matrigel-precoated transwell chambers. We found that RNPC1a overexpression exhibited significantly decrease ability of migration and invasion (Figure 4B, both p < 0.01). RNPC1a knockdown exhibited significantly increase ability of migration and invasion (Figure 4D, bothp < 0.05). Besides, we obtained the similar results of MCF7 cells (Additional files 3: Figure S3).RNPC1a down-regulate mutp53 and up-regulate p21 protein expression in breast cancer cellsPrevious study affirmed that translational of wild-type p53 (wtp53) was repressed by RNPC1a [17]. However, our study found wtp53 protein was no significantly altered in RNPC1a over-expressed or silent MCF-7 cells (Figure 5A). Level of p21 protein was increased in RNPC1aXue et al. BMC Cancer 2014, 14:322 http://www.biomedcentral.com/1471-2407/14/Page 9 ofFigure 4 RNPC1a significantly decreased migratory and invasive potential of breast cancer cells. (A, C) Wound healing assay. Images of wound repair were taken at 0, 18 h after wound. The distance of wound closure is shown by area at 18 h. Representative photographs (upper) and quantification (lower) are shown, original magnification, ?00. (B, D) Transwell migration assay and Matrigel invasion assay. Representative photographs (upper) and quantification (lower) are shown. Columns: average of three independent experiments, *p < 0.05, **p < 0.01, original magnification, ?00.over-expressed MCF-7 and MDA-MB-231 cells (Figure 5A and B). Mutp53 protein was decreased in RNPC1a.

Omeres impair tumorigenesis in the INK4aD2/3 cancer-prone mouse. Cell 1999, 97:515?25. 45. Halvorsen
Omeres impair tumorigenesis in the INK4aD2/3 cancer-prone mouse. Cell 1999, 97:515?25. 45. Halvorsen TL, Leibowitz G, Levine F: Telomerase activity is sufficient to allow transformed cells to escape from crisis. Mol Cell Biol 1999, 19:1864?1870. 46. Cheng JQ, Jhanwar SC, Klein WM, Bell DW, Lee WC, Altomare DA, et al: p16 alterations and deletion mapping of 9p21-p22 in malignant mesothelioma. Cancer Res 1994, 54:5547?551. 47. Usami N, Sekido Y, Maeda O, Yamamoto K, Minna JD, Hasegawa Y, Nobori T, Olopade OI, Buckler AJ, Testa JR: Beta-catenin inhibits cell growth of a malignant mesothelioma cell line, NCI-H28, PubMed ID:https://www.ncbi.nlm.nih.gov/pubmed/29045898 with a 3p21.3 homozygous deletion. Oncogene 2003, 22:7923?930. 48. Petroulakis E, Parsyan A, Dowling RJ, LeBacquer O, Martineau Y, Bidinosti M, Larsson O, Alain T, Rong L, Mamane Y, Paquet M, Furic L, Topisirovic I, Shahbazian D, Livingstone M, Costa-Mattioli M, Teodoro JG, Sonenberg N: p53-dependent translational control of senescence and transformation via 4E-BPs. Cancer Cell 2009, 16:439?46. 49. Noda A, Ning Y, Venable SF, Pereira-Smith OM, Smith JR: Cloning of senescent cell-derived inhibitors of DNA synthesis using an expression screen. Exp Cell Res 1994, 211:90?8. 50. Urruticoechea A, Smith IE, Dowsett M: Proliferation marker Ki-67 in early breast cancer. J Clin Oncol 2005, 23:7212?220. 51. Ma C, Rong Y, Radiloff DR, Datto MB, Centeno B, Bao S, Cheng AW, Lin F, Jiang S, Yeatman TJ, Wang XF: Extracellular matrix protein betaig-h3 /TGFBI promotes metastasis of colon cancer by enhancing cell extravasation. Genes Dev 2008, 22:308?21. 52. Ween MP, Lokman NA, Hoffmann P, Rodgers RJ, Ricciardelli C, Oehler MK: Transforming growth factor-beta-induced protein secreted by peritoneal cells increases the metastatic potential of ovarian cancer cells. Intl J Cancer 2011, 128:1570?584. 53. Schneider D, Kleeff J, Berberat, PO, Zhu Z, Korc M, Friess H, and Buchler MW: Induction and expression of BigH3 in pancreatic cancer cells. Biochem. Biophys. ACTA 2002, 1588:1-6. 54. Yamanaka M, Kimura F, Kagata Y, Kondoh N, Asano T, Yamamoto M, and Hayakawa M: BigH3 is overexpressed in clear cell renal cell carcinoma. Oncology Report 2008, 19:865-874. 55. Lin B, Madan A, Yoon JG, Fang X, Yan X, Kim TK, Hwang D, Hood L, Foltz G: Massively parallel signature sequencing and bioinformatics analysis identifies up-regulation of TGFBI and SOX4 in human glioblastoma. PLoS One 2010, 4:e10210.doi:10.1186/1471-2407-12-239 Cite this article as: Li et al.: The role of TGFBI in mesothelioma and breast cancer: association with tumor suppression. BMC Cancer 2012 12:239.Submit your next manuscript to BioMed Central and take full advantage of:?Convenient online submission ?Thorough peer review ?No space constraints or color figure charges ?Immediate publication on acceptance ?Inclusion in PubMed, CAS, Scopus and Google Scholar ?Research which is freely available for redistributionSubmit your manuscript at www.biomedcentral.com/submit
Zhang et al. BMC Cancer 2012, 12:267 http://www.biomedcentral.com/1471-2407/12/RESEARCH ARTICLEOpen AccessTumor suppressor BLU inhibits proliferation of ZM241385 web nasopharyngeal carcinoma cells by regulation of cell cycle, c-Jun N-terminal kinase and the cyclin D1 promoterXiangning Zhang1,2*, Hui Liu1,2, Binbin Li1,2, Peichun Huang1,2, Jianyong Shao3 and Zhiwei He1,2*AbstractBackground: Tumor suppressor genes function to regulate and block tumor cell proliferation. To explore the mechanisms underlying the tumor suppression of BLU/ZMYND10 gene on a frequ.

D with the mRNA targets for 5 of the 11 miRNAs. For 4 of
D with the mRNA targets for 5 of the 11 miRNAs. For 4 of the 5 miRNAs with significant target association to the HD canonical pathway, we confirmed their expression by qPCR in the monkey cortical tissues (miR940 did not have commercially available Taqman primers for qPCR) (Figure 1D). For the qPCR verification, we focused on the monkeys (HD4, HD7, and HD8) that had corresponding pathology. Quantitation by qPCR revealed a significant downregulation of miR-128a in the brains of the HD monkeys (Figure 1D), consistent with our microarray results. Additionally, miR-128a was also downregulated in the brains of pre-symptomatic and post-symptomatic HD patients (Figure 1E) when compared to controls (p < 0.05).miR-128a regulates 3'-UTR activity of genes with known roles in HD canonical pathwayThe HD canonical signaling genes HIP-1, HTT, SP-1, and GRM5 PubMed ID:https://www.ncbi.nlm.nih.gov/pubmed/27741243 are all predicted gene targets of miR-128a. To determine whether miR-128a regulates the 3′-UTRs of these genes, luciferase reporter assays were developed and co-transfection assays were performed to examineKocerha et al. Molecular Brain 2014, 7:46 http://www.molecularbrain.com/content/7/1/Page 4 ofFigure 2 Expression of mHTT in monkey frontal cortex. A) Brain sections of HD monkey (rHD4, rHD7 and rHD8) and GFP monkey (C1 and C3) were immunostained with mEM48. Low magnification (upper panels, 40? and high magnification (lower panels, 100? shows that mHTT forms intranuclear inclusions (arrows) and neuropil aggregates (arrowheads). B) mEM48 immunoblot of frontal cortex showed high-molecular-mass mutant HTT aggregate (arrow) in the stacking gel. – tubulin was used as an internal control. C) BLU-554 web Quantification of the mHTT aggregate in the stacking gel showed the relative level of mHTT aggregates in the frontal cortex. All HD monkeys have significantly higher level of mHTT aggregate compared to the controls. D) The percentage of mEM48 positive cells with or without intranuclear inclusions was calculated and compared among HD monkey frontal cortex immunostained with mEM48. HD7 has significantly more nuclei with intranuclear inclusions than HD4 and HD8. The data was presented as mean ?SE. *P < 0.05.the effect of miR-128a mimic on 3′-UTR activation. Transfection of miR-128a mimic significantly reduced the 3′-UTR activation of the WT constructs for HIP-1, HTT, SP-1, and GRM5 in the luciferase reporter assays (Figure 4). Suppression of HIP-1, HTT, and SP-1 by miR-128a mimic (55 , 36 , and 30 respectively) was highly significant compared to the negative control (NC) (p < 0.0001 by One-way ANOVA followed by Tukey’s post-hoc multiple comparison). GRM5 3′ UTR was suppressed by the miR-128a mimic with a significance of p < 0.001. None of the site-specific mutant (MUT) control reporter constructs for the 4 genes examined were significantly regulated by the miR-128a mimic.Discussion In this study, we examine ncRNA regulation in HD monkeys and identified 11 significant disease-associated miRNAs. This is the first study which analyzes miRNA regulation in a transgenic primate model of a human disease, with a goal of helping to bridge or expand on previous results in HD rodents and human patients. The HD monkeys offer a unique resource to identify pathogenic ncRNA mechanisms that are either conserved from lower vertebrates to humans or are primate specific. For example, miR-451, one of the 11 miRNAs wefound modulated in the HD monkeys, is also upregulated in HD patients [24]. However, miR-451 does not appear to be disrupted.

Phosphorylation of PGC-1alpha. Proc Natl Acad Sci USA. 2007;104(29):12017?2. doi:10.1073/ pnas.
Phosphorylation of PGC-1alpha. Proc Natl Acad Sci USA. 2007;104(29):12017?2. doi:10.1073/ pnas.0705070104. 69. Canto C, Gerhart-Hines Z, Feige JN, Lagouge M, Noriega L, Milne JC, et al. AMPK regulates energy expenditure by modulating NAD+ metabolism and SIRT1 activity. Nature. 2009;458(7241):1056?0. doi:10.1038/ nature07813.Submit your next manuscript to BioMed Central and we will help you at every step:?We accept pre-submission inquiries ?Our selector tool helps you to find the most relevant journal ?We provide round the clock customer support ?Convenient online submission ?Thorough peer review ?Inclusion in PubMed and all major indexing services ?Maximum visibility for your research Submit your manuscript at www.biomedcentral.com/submit
Yan et al. J Transl Med (2017) 15:26 DOI 10.1186/s12967-017-1122-yJournal of Translational MedicineOpen AccessRESEARCHIndividualized analysis reveals CpG sites with methylation aberrations in almost all lung adenocarcinoma tissuesHaidan Yan1,2, Qingzhou Guan2, Jun He2, Yunqing Lin2, Juan Zhang2, Hongdong Li2, Huaping Liu2, Yunyan Gu1, Zheng Guo1,2* and Fei He3*Abstract Background: Due to the heterogeneity of cancer, identifying differentially methylated (DM) CpG sites between a set of cancer samples and a set of normal samples cannot tell us PubMed ID:https://www.ncbi.nlm.nih.gov/pubmed/28893839 which patients have methylation aberrations in a particular DM CpG site. Methods: We firstly buy Stattic showed that the relative methylation-level orderings (RMOs) of CpG sites within individual normal lung tissues are highly stable but widely disrupted in lung adenocarcinoma tissues. This finding provides the basis of using the RankComp algorithm, previously developed for differential gene expression analysis at the individual level, to identify DM CpG sites in each cancer tissue compared with its own normal state. Briefly, through comparing with the highly stable normal RMOs predetermined in a large collection of samples for normal lung tissues, the algorithm finds those CpG sites whose hyper- or hypo-methylations may lead to the disrupted RMOs of CpG site pairs within a disease sample based on Fisher’s exact test. Results: Evaluated in 59 lung adenocarcinoma tissues with paired adjacent normal tissues, RankComp reached an average precision of 94.26 for individual-level DM CpG sites. Then, after identifying DM CpG sites in each of the 539 lung adenocarcinoma samples from TCGA, we found five and 44 CpG sites hypermethylated and hypomethylated in above 90 of the disease samples, respectively. These findings were validated in 140 publicly available and eight additionally measured paired cancer-normal samples. Gene expression analysis revealed that four of the five genes, HOXA9, TAL1, ATP8A2, ENG and SPARCL1, each harboring one of the five frequently hypermethylated CpG sites within its promoters, were also frequently down-regulated in lung adenocarcinoma. Conclusions: The common DNA methylation aberrations in lung adenocarcinoma tissues may be important for lung adenocarcinoma diagnosis and therapy. Keywords: Lung adenocarcinoma, DNA methylation, Relative methylation level orderings, Differentially methylated CpG sites Background The incidence of lung adenocarcinoma is increasing worldwide. It is widely recognized that lung*Correspondence: [email protected]; [email protected] Haidan Yan and Qingzhou Guan contributed equally as first authors 1 Department of Systems Biology, College of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150086, China 3 Ke.

Entromeric region of chromosome 2. Genomics 1993, 17:490-2. 60. Gosden JR, Mtichell AR, Buckland
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Ombined precision (i.e., the number of true positives in the
Ombined precision (i.e., the number of true positives in the output divided by the number of nodes in the output) and recall (i.e., the number of true positives divided by 13, the size of the true PC set) as(1 – precision) 2 + (1 – recall) 2 , toAussem et al. BMC Bioinformatics 2010, 11:487 http://www.biomedcentral.com/1471-2105/11/Page 4 ofFigure 1 Validation of the learning method on the Insulin benchmark. Empirical experiments on synthetic data sets from the Insulin BN. Each algorithm is run on the node having the largest neighborhood (13 nodes). Four sample sizes were considered: 200, 500, 1000 and 2000. PubMed ID:http://www.ncbi.nlm.nih.gov/pubmed/27107493 The figure shows the distribution over 100 data sets of the Euclidean distance from perfect precision and recall, in the form of boxplots.measure the Euclidean distance from perfect precision and recall, as proposed in [10]. Figure 1 summarizes the variability of the Euclidean distance over 50 data sets in the form of quadruplets of boxplots, one for each algorithm (i. e., MMPC, GetPC, Inter-IAPC and HPC). The advantage of HPC PD325901 site against the other three algorithms is clearly noticeable. HPC outperforms the other algorithms in terms of Euclidean distance from perfect precision and recall.Simulation experiments on the sample of womensamples to maximize accuracy. As may be seen, the directionality of the arrows was partially identifiable: 14 edges out of 34 were directed, indicating the presence of several robust uncoupled head-to-head meetings (T ?Y ?X).Physiological knowledge integration into the modelThe consensus PDAG obtained by running RHPC on the present sample of women is shown in Figure 2. Line thickness corresponds to the relative confidence of the edges. The edges that appeared more than 25 in the networks were included in the aggregate PDAG. The threshold was tuned on the previous Insulin benchmarkSeveral interconnected groups of variables were identified, e.g., beer consumption, wine consumption and spirit consumption; cigarettes per day and low exercise; OM and SC fat cell sizes. In each of these densely connected subgraphs, the variables were highly interdependent and a common cause is likely to explain the observed correlations. Hence, we added some extra nodes and directed some of the links according to physiological knowledge available in the literature. The result is the partially directed acyclic graph (PDAG) thatAussem et al. BMC Bioinformatics 2010, 11:487 http://www.biomedcentral.com/1471-2105/11/Page 5 ofFigure 2 Consensus PDAG of visceral obesity related variables in women returned by RHPC. Consensus PDAG obtained by running RHPC on bootstrapped samples. Labels are self-explanatory. Line thickness corresponds to the relative edge strength.Figure 3 BN of visceral obesity related variables in women after physiological knowledge integration into the graph. PDAG of Figure 2 oriented according to biological knowledge. Dash nodes and arrows are latent variables that were added based on current literature.is shown in Figure 3. Dashed nodes and arrows are the latent variables that were added for sake of clarity and coherence. By definition, these latent variables are not observed, nor recorded in our data set. For example, the variable high alcohol intake was added as a common “cause” to beer consumption, wine consumption and spirit consumption; the variable unhealthy lifestyle was added as a common cause to cigarettes per day, high alcohol intake and low exercise; the latent variables fat storage and prevailing hormonal.