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Sample records for aib1 predicts resistance

  1. AIB1 Genomic Amplification Predicts Poor Clinical Outcomes in Female Glioma Patients

    PubMed Central

    Chen, Lihong; Wang, Changwei; Zhang, Xinyuan; Gao, Ke; Liu, Rui; Shi, Bingyin; Hou, Peng

    2016-01-01

    Amplified in breast cancer 1 (AIB1) gene, a coactivator for steroid receptor, is frequently amplified in diverse cancers and is considered as an oncogene in tumorigenesis. However, the prognostic significance of AIB1 amplification in gliomas remains totally unclear. In this study, 115 gliomas and 16 benign meningiomas as control subjects were enrolled, and the copy number of AIB1 was analyzed in these samples. In addition, we explored potential correlation of AIB1 amplification with clinicopathological characteristics and clinical outcomes of glioma patients. Our data showed that glioma samples exhibited a significantly higher AIB1 copy number than control subjects as determined by quantitative polymerase chain reaction (qPCR) approach. Moreover, univariate analysis showed that AIB1 amplification (≥3.5 copies) was strongly correlated with cancer-related death (P =0.03). Interestingly, our data revealed a significant association of AIB1 amplification with WHO grade (P =0.03), tumor recurrence (P =0.03) and survival status (P =0.03) in female patients but not in male patients. Multivariate analysis further demonstrated that AIB1 amplification was independent factor for cancer-related death in female patients. Importantly, AIB1 amplification was closely relevant to worse survival in female patients (P =0.001), but not in male patients (P =1.00). In addition, the patients with AIB1 amplification were resistant to radiotherapy. Altogether, our data demonstrate that AIB1 amplification is a common genetic event in glioma tumorigenesis, and suggest that AIB1 amplification is not only a prognostic factor for poor clinical outcomes in glioma patients, but also a predictor of radiotherapy resistance in gliomas. PMID:27877220

  2. AIB1 is required for the acquisition of epithelial growth factor receptor-mediated tamoxifen resistance in breast cancer cells

    SciTech Connect

    Zhao Wenhui; Zhang Qingyuan Kang Xinmei; Jin Shi; Lou Changjie

    2009-03-13

    Acquired resistance to tamoxifen has become a serious obstacle in breast cancer treatment. The underlying mechanism responsible for this condition has not been completely elucidated. In this study, a tamoxifen-resistant (Tam-R) MCF-7 breast cancer cell line was developed to mimic the occurrence of acquired tamoxifen resistance as seen in clinical practice. Increased expression levels of HER1, HER2 and the estrogen receptor (ER)-AIB1 complex were found in tamoxifen-resistant cells. EGF stimulation and gefitinib inhibition experiments further demonstrated that HER1/HER2 signaling and AIB1 were involved in the proliferation of cells that had acquired Tam resistance. However, when AIB1 was silenced with AIB1-siRNA in Tam-R cells, the cell growth stimulated by the HER1/HER2 signaling pathway was significantly reduced, and the cells were again found to be inhibited by tamoxifen. These results suggest that the AIB1 protein could be a limiting factor in the HER1/HER2-mediated hormone-independent growth of Tam-R cells. Thus, AIB1 may be a new therapeutic target, and the removal of AIB1 may decrease the crosstalk between ER and the HER1/HER2 pathway, resulting in the restoration of tamoxifen sensitivity in tamoxifen-resistant cells.

  3. Salinomycin overcomes acquired tamoxifen resistance through AIB1 and inhibits cancer cell invasion in endocrine resistant breast cancer.

    PubMed

    Manmuan, Suwisit; Sakunrangsit, Nithidol; Ketchart, Wannarasmi

    2017-10-01

    Salinomycin is a monocarboxylic polyether ionophore isolated from Streptomyces albus. It has been widely used as an antibiotic in veterinary medicine in poultry. A recent study demonstrated that salinomycin selectively inhibits human breast cancer stem cells; one possible mechanism of tamoxifen resistance. Our results show that salinomycin is effective in inhibiting MCF-7/LCC2 and MCF-7/LCC9 cell lines which are well-established endocrine resistant cells and has a synergistic effect in combination with tamoxifen using MTT proliferation assay. The inhibitory effect of salinomycin on the reduction of critical ER co-activator; amplified breast 1 (AIB1) mRNA and protein expression is overcoming tamoxifen resistance. Moreover, salinomycin significantly inhibits cell invasion in Matrigel invasion assay. The effect was mediated at least in part by the decrease of matrix metalopeptidase 9 (MMP-9) which is one critical enzyme facilitated in the cell invasion process. In conclusion, salinomycin should be developed as a novel agent used alone or in combination for endocrine-resistant breast cancer. © 2017 John Wiley & Sons Australia, Ltd.

  4. Altered AIB1 or AIB1Δ3 Expression Impacts ERα Effects on Mammary Gland Stromal and Epithelial Content

    PubMed Central

    Nakles, Rebecca E.; Shiffert, Maddalena Tilli; Díaz-Cruz, Edgar S.; Cabrera, M. Carla; Alotaiby, Maram; Miermont, Anne M.; Riegel, Anna T.

    2011-01-01

    Amplified in breast cancer 1 (AIB1) (also known as steroid receptor coactivator-3) is a nuclear receptor coactivator enhancing estrogen receptor (ER)α and progesterone receptor (PR)-dependent transcription in breast cancer. The splice variant AIB1Δ3 demonstrates increased ability to promote ERα and PR-dependent transcription. Both are implicated in breast cancer risk and antihormone resistance. Conditional transgenic mice tested the in vivo impact of AIB1Δ3 overexpression compared with AIB1 on histological features of increased breast cancer risk and growth response to estrogen and progesterone in the mammary gland. Combining expression of either AIB1 or AIB1Δ3 with ERα overexpression, we investigated in vivo cooperativity. AIB1 and AIB1Δ3 overexpression equivalently increased the prevalence of hyperplastic alveolar nodules but not ductal hyperplasia or collagen content. When AIB1 or AIB1Δ3 overexpression was combined with ERα, both stromal collagen content and ductal hyperplasia prevalence were significantly increased and adenocarcinomas appeared. Overexpression of AIB1Δ3, especially combined with overexpressed ERα, led to an abnormal response to estrogen and progesterone with significant increases in stromal collagen content and development of a multilayered mammary epithelium. AIB1Δ3 overexpression was associated with a significant increase in PR expression and PR downstream signaling genes. AIB1 overexpression produced less marked growth abnormalities and no significant change in PR expression. In summary, AIB1Δ3 overexpression was more potent than AIB1 overexpression in increasing stromal collagen content, inducing abnormal mammary epithelial growth, altering PR expression levels, and mediating the response to estrogen and progesterone. Combining ERα overexpression with either AIB1 or AIB1Δ3 overexpression augmented abnormal growth responses in both epithelial and stromal compartments. PMID:21292825

  5. Transcriptional repression of the tumor suppressor DRO1 by AIB1.

    PubMed

    Ferragud, Juan; Avivar-Valderas, Alvaro; Pla, Antoni; De Las Rivas, Javier; Font de Mora, Jaime

    2011-10-03

    Using transcriptomic gene expression profiling we found tumor suppressor DRO1 being repressed in AIB1 transgenic mice. In agreement, AIB1 represses DRO1 promoter and its expression levels inversely correlate with DRO1 in several cancer cell lines and in ectopic and silencing assays. Estrogen modulators treatment showed a regulation in an estrogen receptor-dependent fashion. Importantly, DRO1 overexpression resulted in BCLAF1 upregulation, a compelling concept given that BCLAF1 is a death-promoting transcriptional repressor. Additionally, DRO1 shuttles from Golgi to the endoplasmic reticulum upon apoptotic stimuli, where it is predicted to facilitate the apoptosis cascade. Finally, DRO1 repression is an important factor for AIB1-mediated inhibition of apoptosis. Collectively, our results reveal DRO1 as an AIB1-targeted tumor suppressor, providing a novel mechanism for AIB1-dependent inhibition of apoptosis. Copyright © 2011 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.

  6. Targeting of the Nuclear Receptor Coativator Isoform Delta 3aib1 in Breast Cancer. Addendum

    DTIC Science & Technology

    2007-07-01

    using a regulatable AIB1 directed ribozyme , resulted in reduced tumor growth in vivo. Overall, these data indicate a major role for AIB1 and its isoform...regulatable AIB1 directed ribozyme , resulted in reduced tumor growth in vivo. Overall, these data indicate a major role for AIB1 and its isoform ∆3AIB1 in

  7. AIB1 gene amplification and the instability of polyQ encoding sequence in breast cancer cell lines

    PubMed Central

    Wong, Lee-Jun C; Dai, Pu; Lu, Jyh-Feng; Lou, Mary Ann; Clarke, Robert; Nazarov, Viktor

    2006-01-01

    Background The poly Q polymorphism in AIB1 (amplified in breast cancer) gene is usually assessed by fragment length analysis which does not reveal the actual sequence variation. The purpose of this study is to investigate the sequence variation of poly Q encoding region in breast cancer cell lines at single molecule level, and to determine if the sequence variation is related to AIB1 gene amplification. Methods The polymorphic poly Q encoding region of AIB1 gene was investigated at the single molecule level by PCR cloning/sequencing. The amplification of AIB1 gene in various breast cancer cell lines were studied by real-time quantitative PCR. Results Significant amplifications (5–23 folds) of AIB1 gene were found in 2 out of 9 (22%) ER positive cell lines (in BT-474 and MCF-7 but not in BT-20, ZR-75-1, T47D, BT483, MDA-MB-361, MDA-MB-468 and MDA-MB-330). The AIB1 gene was not amplified in any of the ER negative cell lines. Different passages of MCF-7 cell lines and their derivatives maintained the feature of AIB1 amplification. When the cells were selected for hormone independence (LCC1) and resistance to 4-hydroxy tamoxifen (4-OH TAM) (LCC2 and R27), ICI 182,780 (LCC9) or 4-OH TAM, KEO and LY 117018 (LY-2), AIB1 copy number decreased but still remained highly amplified. Sequencing analysis of poly Q encoding region of AIB1 gene did not reveal specific patterns that could be correlated with AIB1 gene amplification. However, about 72% of the breast cancer cell lines had at least one under represented (<20%) extra poly Q encoding sequence patterns that were derived from the original allele, presumably due to somatic instability. Although all MCF-7 cells and their variants had the same predominant poly Q encoding sequence pattern of (CAG)3CAA(CAG)9(CAACAG)3(CAACAGCAG)2CAA of the original cell line, a number of altered poly Q encoding sequences were found in the derivatives of MCF-7 cell lines. Conclusion These data suggest that poly Q encoding region of AIB1 gene is

  8. AIB1 gene amplification and the instability of polyQ encoding sequence in breast cancer cell lines.

    PubMed

    Wong, Lee-Jun C; Dai, Pu; Lu, Jyh-Feng; Lou, Mary Ann; Clarke, Robert; Nazarov, Viktor

    2006-05-02

    The poly Q polymorphism in AIB1 (amplified in breast cancer) gene is usually assessed by fragment length analysis which does not reveal the actual sequence variation. The purpose of this study is to investigate the sequence variation of poly Q encoding region in breast cancer cell lines at single molecule level, and to determine if the sequence variation is related to AIB1 gene amplification. The polymorphic poly Q encoding region of AIB1 gene was investigated at the single molecule level by PCR cloning/sequencing. The amplification of AIB1 gene in various breast cancer cell lines were studied by real-time quantitative PCR. Significant amplifications (5-23 folds) of AIB1 gene were found in 2 out of 9 (22%) ER positive cell lines (in BT-474 and MCF-7 but not in BT-20, ZR-75-1, T47D, BT483, MDA-MB-361, MDA-MB-468 and MDA-MB-330). The AIB1 gene was not amplified in any of the ER negative cell lines. Different passages of MCF-7 cell lines and their derivatives maintained the feature of AIB1 amplification. When the cells were selected for hormone independence (LCC1) and resistance to 4-hydroxy tamoxifen (4-OH TAM) (LCC2 and R27), ICI 182,780 (LCC9) or 4-OH TAM, KEO and LY 117018 (LY-2), AIB1 copy number decreased but still remained highly amplified. Sequencing analysis of poly Q encoding region of AIB1 gene did not reveal specific patterns that could be correlated with AIB1 gene amplification. However, about 72% of the breast cancer cell lines had at least one under represented (<20%) extra poly Q encoding sequence patterns that were derived from the original allele, presumably due to somatic instability. Although all MCF-7 cells and their variants had the same predominant poly Q encoding sequence pattern of (CAG)3CAA(CAG)9(CAACAG)3(CAACAGCAG)2CAA of the original cell line, a number of altered poly Q encoding sequences were found in the derivatives of MCF-7 cell lines. These data suggest that poly Q encoding region of AIB1 gene is somatic unstable in breast cancer cell

  9. Targeting of the Nuclear Receptor Coactivator Isoform DELTA3AIB1 in Breast Cancer

    DTIC Science & Technology

    2007-03-01

    lab showed that the downregulation of overall levels of AIB1 plus ∆3AIB1, using a regulatable AIB1 directed ribozyme , resulted in reduced tumor...overall levels of AIB1 plus ∆3AIB1, using a regulatable AIB1 directed ribozyme , resulted in reduced tumor growth in vivo. Overall, these data indicate a...Reiter R, Powers C, Wellstein A, Riegel AT. Ribozyme targeting shows that the nuclear receptor coactivator AIB1 is a rate-limiting factor for estrogen

  10. Phosphorylation of AIB1 at Mitosis Is Regulated by CDK1/CYCLIN B

    PubMed Central

    Ferrero, Macarena; Ferragud, Juan; Orlando, Leonardo; Valero, Luz; Sánchez del Pino, Manuel; Farràs, Rosa; Font de Mora, Jaime

    2011-01-01

    Background Although the AIB1 oncogene has an important role during the early phase of the cell cycle as a coactivator of E2F1, little is known about its function during mitosis. Methodology/Principal Findings Mitotic cells isolated by nocodazole treatment as well as by shake-off revealed a post-translational modification occurring in AIB1 specifically during mitosis. This modification was sensitive to the treatment with phosphatase, suggesting its modification by phosphorylation. Using specific inhibitors and in vitro kinase assays we demonstrate that AIB1 is phosphorylated on Ser728 and Ser867 by Cdk1/cyclin B at the onset of mitosis and remains phosphorylated until exit from M phase. Differences in the sensitivity to phosphatase inhibitors suggest that PP1 mediates dephosphorylation of AIB1 at the end of mitosis. The phosphorylation of AIB1 during mitosis was not associated with ubiquitylation or degradation, as confirmed by western blotting and flow cytometry analysis. In addition, luciferase reporter assays showed that this phosphorylation did not alter the transcriptional properties of AIB1. Importantly, fluorescence microscopy and sub-cellular fractionation showed that AIB1 phosphorylation correlated with the exclusion from the condensed chromatin, thus preventing access to the promoters of AIB1-dependent genes. Phospho-specific antibodies developed against Ser728 further demonstrated the presence of phosphorylated AIB1 only in mitotic cells where it was localized preferentially in the periphery of the cell. Conclusions Collectively, our results describe a new mechanism for the regulation of AIB1 during mitosis, whereby phosphorylation of AIB1 by Cdk1 correlates with the subcellular redistribution of AIB1 from a chromatin-associated state in interphase to a more peripheral localization during mitosis. At the exit of mitosis, AIB1 is dephosphorylated, presumably by PP1. This exclusion from chromatin during mitosis may represent a mechanism for governing the

  11. Prior Adjuvant Tamoxifen Treatment in Breast Cancer Is Linked to Increased AIB1 and HER2 Expression in Metachronous Contralateral Breast Cancer

    PubMed Central

    Alkner, Sara; Bendahl, Pär-Ola; Ehinger, Anna; Lövgren, Kristina; Rydén, Lisa; Fernö, Mårten

    2016-01-01

    Aim The estrogen receptor coactivator Amplified in Breast Cancer 1 (AIB1) has been associated with an improved response to adjuvant tamoxifen in breast cancer, but also with endocrine treatment resistance. We hereby use metachronous contralateral breast cancer (CBC) developed despite prior adjuvant tamoxifen for the first tumor as an “in vivo”-model for tamoxifen resistance. AIB1-expression in the presumable resistant (CBC after prior tamoxifen) and naïve setting (CBC without prior tamoxifen) is compared and correlated to prognosis after CBC. Methods From a well-defined population-based cohort of CBC-patients we have constructed a unique tissue-microarray including >700 patients. Results CBC developed after adjuvant tamoxifen more often had a HER2-positive/triple negative-subtype and a high AIB1-expression (37% vs. 23%, p = 0.009), than if no prior endocrine treatment had been administered. In patients with an estrogen receptor (ER) positive CBC, a high AIB1-expression correlated to an inferior prognosis. However, these patients seemed to respond to tamoxifen, but only if endocrine therapy had not been administered for BC1. Conclusions Metachronous CBC developed after prior endocrine treatment has a decreased ER-expression and an increased HER2-expression. This is consistent with endocrine treatment escape mechanisms previously suggested, and indicates metachronous CBC to be a putative model for studies of treatment resistance “in vivo”. The increased AIB1-expression in CBC developed after prior tamoxifen suggests a role of AIB1 in endocrine treatment resistance. In addition, we found indications that the response to tamoxifen in CBC with a high AIB1-expression seem to differ depending on previous exposure to this drug. A different function for AIB1 in the tamoxifen treatment naïve vs. resistant setting is suggested, and may explain previously conflicting results where a high AIB1-expression has been correlated to both a good response to adjuvant

  12. Identification and validation of AIB1 and EIF5A2 for noninvasive detection of bladder cancer in urine samples.

    PubMed

    Zhou, Bang-Fen; Wei, Jin-Huan; Chen, Zhen-Hua; Dong, Pei; Lai, Ying-Rong; Fang, Yong; Jiang, Hui-Ming; Lu, Jun; Zhou, Fang-Jian; Xie, Dan; Luo, Jun-Hang; Chen, Wei

    2016-07-05

    We previously demonstrated that amplified in breast cancer 1 (AIB1) and eukaryotic initiation factor 2 (EIF5A2) overexpression was an independent predictor of poor clinical outcomes for patients with bladder cancer (BCa). In this study, we evaluated the usefulness of AIB1 and EIF5A2 alone and in combination with nuclear matrix protein 22 (NMP22) as noninvasive diagnostic tests for BCa. Using urine samples from 135 patients (training set, controls [n = 50] and BCa [n = 85]), we detected the AIB1, EIF5A2, and NMP22 concentrations using enzyme-linked immunosorbent assay. We applied multivariate logistic regression analysis to build a model based on the three biomarkers for BCa diagnosis. The diagnostic accuracy of the three biomarkers and the model were assessed and compared by the area under the curve (AUC) of the receiver operating characteristic. We validated the diagnostic accuracy of these biomarkers and the model in an independent validation cohort of 210 patients. In the training set, urinary concentrations of AIB1, EIF5A2, and NMP22 were significantly elevated in BCa. The AUCs of AIB1, EIF5A2, NMP22, and the model were 0.846, 0.761, 0.794, and 0.919, respectively. The model had the highest diagnostic accuracy when compared with AIB1, EIF5A2, or NMP22 (p < 0.05 for all). The model had 92% sensitivity and 92% specificity. We obtained similar results in the independent validation cohort. AIB1 and EIF5A2 show promise for the noninvasive detection of BCa. The model based on AIB1, EIF5A2, and NMP22 outperformed each of the three individual biomarkers for detecting BCa.

  13. The AIB1 polyglutamine repeat does not modify breast cancer risk in BRCA1 and BRCA2 mutation carriers.

    PubMed

    Spurdle, Amanda B; Antoniou, Antonis C; Kelemen, Livia; Holland, Helene; Peock, Susan; Cook, Margaret R; Smith, Paula L; Greene, Mark H; Simard, Jacques; Plourde, Marie; Southey, Melissa C; Godwin, Andrew K; Beck, Jeanne; Miron, Alexander; Daly, Mary B; Santella, Regina M; Hopper, John L; John, Esther M; Andrulis, Irene L; Durocher, Francine; Struewing, Jeffery P; Easton, Douglas F; Chenevix-Trench, Georgia

    2006-01-01

    This is by far the largest study of its kind to date, and further suggests that AIB1 does not play a substantial role in modifying the phenotype of BRCA1 and BRCA2 carriers. The AIB1 gene encodes the AIB1/SRC-3 steroid hormone receptor coactivator, and amplification of the gene and/or protein occurs in breast and ovarian tumors. A CAG/CAA repeat length polymorphism encodes a stretch of 17 to 29 glutamines in the HR-interacting carboxyl-terminal region of the protein which is somatically unstable in tumor tissues and cell lines. There is conflicting evidence regarding the role of this polymorphism as a modifier of breast cancer risk in BRCA1 and BRCA2 carriers. To further evaluate the evidence for an association between AIB1 glutamine repeat length and breast cancer risk in BRCA1 and BRCA2 mutation carriers, we have genotyped this polymorphism in 1,090 BRCA1 and 661 BRCA2 mutation carriers from Australia, Europe, and North America. There was no evidence for an increased risk associated with AIB1 glutamine repeat length. Given the large sample size, with more than adequate power to detect previously reported effects, we conclude that the AIB1 glutamine repeat does not substantially modify risk of breast cancer in BRCA1 and BRCA2 mutation carriers. (Cancer Epidemiol Biomarkers Prev 2006;15(1):76-9).

  14. Somatic instability of the DNA sequences encoding the polymorphic polyglutamine tract of the AIB1 gene

    PubMed Central

    Dai, P; Wong, L

    2003-01-01

    Background: AIB1 contains a polymorphic polyglutamine tract (poly Q) that is encoded by a trinucleotide CAG repeat. Previously there have been conflicting results regarding the effect of the poly Q tract length on breast cancer. Since poly Q is not encoded by a perfect CAG repeat, the heterozygous polymorphic alleles need to be resolved, to understand the exact DNA sequences encoding poly Q. Methods: Poly Q encoding sequences of AIB1 from 107 DNA samples, including breast cancer cell lines, sporadic primary breast tumours, and blood samples from BRCA1/BRCA2 mutation carriers and the general population, were resolved by PCR/cloning followed by sequencing of each individual clone. Results: 25 distinct poly Q encoding sequence patterns were found. More than two distinct sequence patterns were found in a significantly higher proportion of tumours and cell lines than that of the general population, suggesting somatic instability. A significantly higher proportion of cancer cell lines or primary breast tumours than that of the general population contained rare sequence patterns. The proportion of sporadic breast tumours having at least one allele ⩽27 repeats is significantly higher than that in the blood of BRCA1/BRCA2 mutation carrier breast cancer patients or the general population. Conclusion: The poly Q encoding DNA sequences are somatically unstable in tumour tissues and cell lines. A missense mutation and a very short glutamine repeat in primary tumours suggests that AIB1 activity may be modulated through poly Q, which in turn plays a role in the cotransactivation of gene expressions in breast cancers. PMID:14684685

  15. Identification of SRC3/AIB1 as a Preferred Coactivator for Hormone-activated Androgen Receptor

    SciTech Connect

    Zhou, X. Edward; Suino-Powell, Kelly M.; Li, Jun; He, Yuanzheng; MacKeigan, Jeffrey P.; Melcher, Karsten; Yong, Eu-Leong; Xu, H.Eric

    2010-09-17

    Transcription activation by androgen receptor (AR), which depends on recruitment of coactivators, is required for the initiation and progression of prostate cancer, yet the mechanisms of how hormone-activated AR interacts with coactivators remain unclear. This is because AR, unlike any other nuclear receptor, prefers its own N-terminal FXXLF motif to the canonical LXXLL motifs of coactivators. Through biochemical and crystallographic studies, we identify that steroid receptor coactivator-3 (SRC3) (also named as amplified in breast cancer-1 or AIB1) interacts strongly with AR via synergistic binding of its first and third LXXLL motifs. Mutagenesis and functional studies confirm that SRC3 is a preferred coactivator for hormone-activated AR. Importantly, AR mutations found in prostate cancer patients correlate with their binding potency to SRC3, corroborating with the emerging role of SRC3 as a prostate cancer oncogene. These results provide a molecular mechanism for the selective utilization of SRC3 by hormone-activated AR, and they link the functional relationship between AR and SRC3 to the development and growth of prostate cancer.

  16. Predicting antibiotic resistance.

    PubMed

    Martínez, José L; Baquero, Fernando; Andersson, Dan I

    2007-12-01

    The treatment of bacterial infections is increasingly complicated because microorganisms can develop resistance to antimicrobial agents. This article discusses the information that is required to predict when antibiotic resistance is likely to emerge in a bacterial population. Indeed, the development of the conceptual and methodological tools required for this type of prediction represents an important goal for microbiological research. To this end, we propose the establishment of methodological guidelines that will allow researchers to predict the emergence of resistance to a new antibiotic before its clinical introduction.

  17. Proto-oncogene ACTR/AIB1 promotes cancer cell invasion by up-regulating specific matrix metalloproteinase expression.

    PubMed

    Li, Li B; Louie, Maggie C; Chen, H-W; Zou, June X

    2008-03-08

    Overexpression of ACTR/AIB1 is frequently found in different cancers with distant metastasis. To address its possible involvement in tumor metastasis, we performed invasion assays to examine the effect of ACTR alteration on the invasiveness of breast cancer cells (MDA-MB-231 or T-47D) and found that high levels of ACTR are required for their strong invasiveness. Molecular analysis indicates that ACTR functions as a coactivator of AP-1 to up-regulate the expression of matrix metalloproteinases such as MMP-7 and MMP-10 and reduce cell adhesion to specific extracellular matrix proteins. These novel findings provide a mechanistic link between ACTR and MMPs, and suggest that ACTR may also play an important role in cancer progression by facilitating tumor invasion.

  18. Identification of SRC3/AIB1 as a Preferred Coactivator for Hormone-activated Androgen Receptor*♦

    PubMed Central

    Zhou, X. Edward; Suino-Powell, Kelly M.; Li, Jun; He, Yuanzheng; MacKeigan, Jeffrey P.; Melcher, Karsten; Yong, Eu-Leong; Xu, H. Eric

    2010-01-01

    Transcription activation by androgen receptor (AR), which depends on recruitment of coactivators, is required for the initiation and progression of prostate cancer, yet the mechanisms of how hormone-activated AR interacts with coactivators remain unclear. This is because AR, unlike any other nuclear receptor, prefers its own N-terminal FXXLF motif to the canonical LXXLL motifs of coactivators. Through biochemical and crystallographic studies, we identify that steroid receptor coactivator-3 (SRC3) (also named as amplified in breast cancer-1 or AIB1) interacts strongly with AR via synergistic binding of its first and third LXXLL motifs. Mutagenesis and functional studies confirm that SRC3 is a preferred coactivator for hormone-activated AR. Importantly, AR mutations found in prostate cancer patients correlate with their binding potency to SRC3, corroborating with the emerging role of SRC3 as a prostate cancer oncogene. These results provide a molecular mechanism for the selective utilization of SRC3 by hormone-activated AR, and they link the functional relationship between AR and SRC3 to the development and growth of prostate cancer. PMID:20086010

  19. Overcoming drug resistance through in silico prediction.

    PubMed

    Carbonell, Pablo; Trosset, Jean-Yves

    2014-03-01

    Prediction tools are commonly used in pre-clinical research to assist target selection, to optimize drug potency or to predict the pharmacological profile of drug candidates. In silico prediction and overcoming drug resistance is a new opportunity that creates a high interest in pharmaceutical research. This review presents two main in silico strategies to meet this challenge: a structure-based approach to study the influence of mutations on the drug-target interaction and a system-biology approach to identify resistance pathways for a given drug. In silico screening of synergies between therapeutic and resistant pathways through biological network analysis is an example of technique to escape drug resistance. Structure-based drug design and in silico system biology are complementary approaches to reach few objectives at once: increase efficiency, reduce toxicity and overcoming drug resistance.

  20. Mass spectrometry methods for predicting antibiotic resistance.

    PubMed

    Charretier, Yannick; Schrenzel, Jacques

    2016-10-01

    Developing elaborate techniques for clinical applications can be a complicated process. Whole-cell MALDI-TOF MS revolutionized reliable microorganism identification in clinical microbiology laboratories and is now replacing phenotypic microbial identification. This technique is a generic, accurate, rapid, and cost-effective growth-based method. Antibiotic resistance keeps emerging in environmental and clinical microorganisms, leading to clinical therapeutic challenges, especially for Gram-negative bacteria. Antimicrobial susceptibility testing is used to reliably predict antimicrobial success in treating infection, but it is inherently limited by the need to isolate and grow cultures, delaying the application of appropriate therapies. Antibiotic resistance prediction by growth-independent methods is expected to reduce the turnaround time. Recently, the potential of next-generation sequencing and microarrays in predicting microbial resistance has been demonstrated, and this review evaluates the potential of MS in this field. First, technological advances are described, and the possibility of predicting antibiotic resistance by MS is then illustrated for three prototypical human pathogens: Staphylococcus aureus, Escherichia coli, and Pseudomonas aeruginosa. Clearly, MS methods can identify antimicrobial resistance mediated by horizontal gene transfers or by mutations that affect the quantity of a gene product, whereas antimicrobial resistance mediated by target mutations remains difficult to detect.

  1. Predicting Resistance Mutations Using Protein Design Algorithms

    SciTech Connect

    Frey, K.; Georgiev, I; Donald, B; Anderson, A

    2010-01-01

    Drug resistance resulting from mutations to the target is an unfortunate common phenomenon that limits the lifetime of many of the most successful drugs. In contrast to the investigation of mutations after clinical exposure, it would be powerful to be able to incorporate strategies early in the development process to predict and overcome the effects of possible resistance mutations. Here we present a unique prospective application of an ensemble-based protein design algorithm, K*, to predict potential resistance mutations in dihydrofolate reductase from Staphylococcus aureus using positive design to maintain catalytic function and negative design to interfere with binding of a lead inhibitor. Enzyme inhibition assays show that three of the four highly-ranked predicted mutants are active yet display lower affinity (18-, 9-, and 13-fold) for the inhibitor. A crystal structure of the top-ranked mutant enzyme validates the predicted conformations of the mutated residues and the structural basis of the loss of potency. The use of protein design algorithms to predict resistance mutations could be incorporated in a lead design strategy against any target that is susceptible to mutational resistance.

  2. Antimicrobial resistance prediction in PATRIC and RAST

    DOE PAGES

    Davis, James J.; Boisvert, Sebastien; Brettin, Thomas; ...

    2016-06-14

    The emergence and spread of antimicrobial resistance (AMR) mechanisms in bacterial pathogens, coupled with the dwindling number of effective antibiotics, has created a global health crisis. Being able to identify the genetic mechanisms of AMR and predict the resistance phenotypes of bacterial pathogens prior to culturing could inform clinical decision-making and improve reaction time. At PATRIC (http://patricbrc.org/), we have been collecting bacterial genomes with AMR metadata for several years. In order to advance phenotype prediction and the identification of genomic regions relating to AMR, we have updated the PATRIC FTP server to enable access to genomes that are binned bymore » their AMR phenotypes, as well as metadata including minimum inhibitory concentrations. Using this infrastructure, we custom built AdaBoost (adaptive boosting) machine learning classifiers for identifying carbapenem resistance in Acinetobacter baumannii, methicillin resistance in Staphylococcus aureus, and beta-lactam and co-trimoxazole resistance in Streptococcus pneumoniae with accuracies ranging from 88–99%. We also did this for isoniazid, kanamycin, ofloxacin, rifampicin, and streptomycin resistance in Mycobacterium tuberculosis, achieving accuracies ranging from 71–88%. Lastly, this set of classifiers has been used to provide an initial framework for species-specific AMR phenotype and genomic feature prediction in the RAST and PATRIC annotation services.« less

  3. Antimicrobial Resistance Prediction in PATRIC and RAST.

    PubMed

    Davis, James J; Boisvert, Sébastien; Brettin, Thomas; Kenyon, Ronald W; Mao, Chunhong; Olson, Robert; Overbeek, Ross; Santerre, John; Shukla, Maulik; Wattam, Alice R; Will, Rebecca; Xia, Fangfang; Stevens, Rick

    2016-06-14

    The emergence and spread of antimicrobial resistance (AMR) mechanisms in bacterial pathogens, coupled with the dwindling number of effective antibiotics, has created a global health crisis. Being able to identify the genetic mechanisms of AMR and predict the resistance phenotypes of bacterial pathogens prior to culturing could inform clinical decision-making and improve reaction time. At PATRIC (http://patricbrc.org/), we have been collecting bacterial genomes with AMR metadata for several years. In order to advance phenotype prediction and the identification of genomic regions relating to AMR, we have updated the PATRIC FTP server to enable access to genomes that are binned by their AMR phenotypes, as well as metadata including minimum inhibitory concentrations. Using this infrastructure, we custom built AdaBoost (adaptive boosting) machine learning classifiers for identifying carbapenem resistance in Acinetobacter baumannii, methicillin resistance in Staphylococcus aureus, and beta-lactam and co-trimoxazole resistance in Streptococcus pneumoniae with accuracies ranging from 88-99%. We also did this for isoniazid, kanamycin, ofloxacin, rifampicin, and streptomycin resistance in Mycobacterium tuberculosis, achieving accuracies ranging from 71-88%. This set of classifiers has been used to provide an initial framework for species-specific AMR phenotype and genomic feature prediction in the RAST and PATRIC annotation services.

  4. Antimicrobial resistance prediction in PATRIC and RAST

    SciTech Connect

    Davis, James J.; Boisvert, Sebastien; Brettin, Thomas; Kenyon, Ronald W.; Mao, Chunhong; Olson, Robert; Overbeek, Ross; Santerre, John; Shukla, Maulik; Wattam, Alice R.; Will, Rebecca; Xia, Fangfang; Stevens, Rick

    2016-06-14

    The emergence and spread of antimicrobial resistance (AMR) mechanisms in bacterial pathogens, coupled with the dwindling number of effective antibiotics, has created a global health crisis. Being able to identify the genetic mechanisms of AMR and predict the resistance phenotypes of bacterial pathogens prior to culturing could inform clinical decision-making and improve reaction time. At PATRIC (http://patricbrc.org/), we have been collecting bacterial genomes with AMR metadata for several years. In order to advance phenotype prediction and the identification of genomic regions relating to AMR, we have updated the PATRIC FTP server to enable access to genomes that are binned by their AMR phenotypes, as well as metadata including minimum inhibitory concentrations. Using this infrastructure, we custom built AdaBoost (adaptive boosting) machine learning classifiers for identifying carbapenem resistance in Acinetobacter baumannii, methicillin resistance in Staphylococcus aureus, and beta-lactam and co-trimoxazole resistance in Streptococcus pneumoniae with accuracies ranging from 88–99%. We also did this for isoniazid, kanamycin, ofloxacin, rifampicin, and streptomycin resistance in Mycobacterium tuberculosis, achieving accuracies ranging from 71–88%. Lastly, this set of classifiers has been used to provide an initial framework for species-specific AMR phenotype and genomic feature prediction in the RAST and PATRIC annotation services.

  5. Antimicrobial Resistance Prediction in PATRIC and RAST

    PubMed Central

    Davis, James J.; Boisvert, Sébastien; Brettin, Thomas; Kenyon, Ronald W.; Mao, Chunhong; Olson, Robert; Overbeek, Ross; Santerre, John; Shukla, Maulik; Wattam, Alice R.; Will, Rebecca; Xia, Fangfang; Stevens, Rick

    2016-01-01

    The emergence and spread of antimicrobial resistance (AMR) mechanisms in bacterial pathogens, coupled with the dwindling number of effective antibiotics, has created a global health crisis. Being able to identify the genetic mechanisms of AMR and predict the resistance phenotypes of bacterial pathogens prior to culturing could inform clinical decision-making and improve reaction time. At PATRIC (http://patricbrc.org/), we have been collecting bacterial genomes with AMR metadata for several years. In order to advance phenotype prediction and the identification of genomic regions relating to AMR, we have updated the PATRIC FTP server to enable access to genomes that are binned by their AMR phenotypes, as well as metadata including minimum inhibitory concentrations. Using this infrastructure, we custom built AdaBoost (adaptive boosting) machine learning classifiers for identifying carbapenem resistance in Acinetobacter baumannii, methicillin resistance in Staphylococcus aureus, and beta-lactam and co-trimoxazole resistance in Streptococcus pneumoniae with accuracies ranging from 88–99%. We also did this for isoniazid, kanamycin, ofloxacin, rifampicin, and streptomycin resistance in Mycobacterium tuberculosis, achieving accuracies ranging from 71–88%. This set of classifiers has been used to provide an initial framework for species-specific AMR phenotype and genomic feature prediction in the RAST and PATRIC annotation services. PMID:27297683

  6. Antibiotic resistance - is resistance detected by surveillance relevant to predicting resistance in the clinical setting?

    PubMed

    Karlowsky, James A; Sahm, Daniel F

    2002-10-01

    Local, regional, national and global surveillance initiatives have several important functions, which include identifying shifts in antibiotic resistance, detecting the emergence of new resistance mechanisms and monitoring the impact of changes made to empiric prescribing, infection control and public health guidelines. Although the need for surveillance is indubitable and its use in the treatment of individual patients important, it cannot unequivocally predict outcomes in patients with infections. Treatment regimens for individual patients with suspected or demonstrated infections should be developed following consideration of symptoms, laboratory findings and relevant medical history, and in the context of appropriate local and widespread antibiotic resistance trends.

  7. Prediction of Cancer Drug Resistance and Implications for Personalized Medicine

    PubMed Central

    Volm, Manfred; Efferth, Thomas

    2015-01-01

    Drug resistance still impedes successful cancer chemotherapy. A major goal of early concepts in individualized therapy was to develop in vitro tests to predict tumors’ drug responsiveness. We have developed an in vitro short-term test based on nucleic acid precursor incorporation to determine clinical drug resistance. This test detects inherent and acquired resistance in vitro and transplantable syngeneic and xenografted tumors in vivo. In several clinical trials, clinical resistance was predictable with more than 90% accuracy, while drug sensitivity was detected with less accuracy (~60%). Remarkably, clinical cross-resistance to numerous drugs (multidrug resistance, broad spectrum resistance) was detectable by a single compound, doxorubicin, due to its multifactorial modes of action. The results of this predictive test were in good agreement with predictive assays of other authors. As no predictive test has been established as yet for clinical diagnostics, the identification of sensitive drugs may not reach sufficiently high reliability for clinical routine. A meta-analysis of the literature published during the past four decades considering test results of more than 15,000 tumor patients unambiguously demonstrated that, in the majority of studies, resistance was correctly predicted with an accuracy between 80 and 100%, while drug sensitivity could only be predicted with an accuracy of 50–80%. This synopsis of the published literature impressively illustrates that prediction of drug resistance could be validated. The determination of drug resistance was reliable independent of tumor type, test assay, and drug used in these in vitro tests. By contrast, chemosensitivity could not be predicted with high reliability. Therefore, we propose a rethinking of the “chemosensitivity” concept. Instead, predictive in vitro tests may reliably identify drug-resistant tumors. The clinical consequence imply to subject resistant tumors not to chemotherapy, but to other new

  8. Automated prediction of HIV drug resistance from genotype data.

    PubMed

    Shen, ChenHsiang; Yu, Xiaxia; Harrison, Robert W; Weber, Irene T

    2016-08-31

    HIV/AIDS is a serious threat to public health. The emergence of drug resistance mutations diminishes the effectiveness of drug therapy for HIV/AIDS. Developing a computational prediction of drug resistance phenotype will enable efficient and timely selection of the best treatment regimens. A unified encoding of protein sequence and structure was used as the feature vector for predicting phenotypic resistance from genotype data. Two machine learning algorithms, Random Forest and K-nearest neighbor, were used. The prediction accuracies were examined by five-fold cross-validation on the genotype-phenotype datasets. A supervised machine learning approach for automatic prediction of drug resistance was developed to handle genotype-phenotype datasets of HIV protease (PR) and reverse transcriptase (RT). It predicts the drug resistance phenotype and its relative severity from a query sequence. The accuracy of the classification was higher than 0.973 for eight PR inhibitors and 0.986 for ten RT inhibitors, respectively. The overall cross-validated regression R(2)-values for the severity of drug resistance were 0.772-0.953 for 8 PR inhibitors and 0.773-0.995 for 10 RT inhibitors. Machine learning using a unified encoding of sequence and protein structure as a feature vector provides an accurate prediction of drug resistance from genotype data. A practical webserver for clinicians has been implemented.

  9. Resist develop prediction by Monte Carlo simulation

    NASA Astrophysics Data System (ADS)

    Sohn, Dong-Soo; Jeon, Kyoung-Ah; Sohn, Young-Soo; Oh, Hye-Keun

    2002-07-01

    Various resist develop models have been suggested to express the phenomena from the pioneering work of Dill's model in 1975 to the recent Shipley's enhanced notch model. The statistical Monte Carlo method can be applied to the process such as development and post exposure bake. The motions of developer during development process were traced by using this method. We have considered that the surface edge roughness of the resist depends on the weight percentage of protected and de-protected polymer in the resist. The results are well agreed with other papers. This study can be helpful for the developing of new photoresist and developer that can be used to pattern the device features smaller than 100 nm.

  10. Concepts of Potency and Resistance in Causal Prediction.

    ERIC Educational Resources Information Center

    Zelazo, Philip David; Shultz, Thomas R.

    1989-01-01

    Used physical systems with effects of continuous magnitude to examine development of causal prediction in 30 children of 5 and 9 years and adults. There were clear age differences in the ability to integrate information about potency and resistance into sophisticated causal predictions of the magnitude of an effect. (RJC)

  11. Biophysical principles predict fitness landscapes of drug resistance.

    PubMed

    Rodrigues, João V; Bershtein, Shimon; Li, Anna; Lozovsky, Elena R; Hartl, Daniel L; Shakhnovich, Eugene I

    2016-03-15

    Fitness landscapes of drug resistance constitute powerful tools to elucidate mutational pathways of antibiotic escape. Here, we developed a predictive biophysics-based fitness landscape of trimethoprim (TMP) resistance for Escherichia coli dihydrofolate reductase (DHFR). We investigated the activity, binding, folding stability, and intracellular abundance for a complete set of combinatorial DHFR mutants made out of three key resistance mutations and extended this analysis to DHFR originated from Chlamydia muridarum and Listeria grayi We found that the acquisition of TMP resistance via decreased drug affinity is limited by a trade-off in catalytic efficiency. Protein stability is concurrently affected by the resistant mutants, which precludes a precise description of fitness from a single molecular trait. Application of the kinetic flux theory provided an accurate model to predict resistance phenotypes (IC50) quantitatively from a unique combination of the in vitro protein molecular properties. Further, we found that a controlled modulation of the GroEL/ES chaperonins and Lon protease levels affects the intracellular steady-state concentration of DHFR in a mutation-specific manner, whereas IC50 is changed proportionally, as indeed predicted by the model. This unveils a molecular rationale for the pleiotropic role of the protein quality control machinery on the evolution of antibiotic resistance, which, as we illustrate here, may drastically confound the evolutionary outcome. These results provide a comprehensive quantitative genotype-phenotype map for the essential enzyme that serves as an important target of antibiotic and anticancer therapies.

  12. Biophysical principles predict fitness landscapes of drug resistance

    PubMed Central

    Bershtein, Shimon; Li, Annabel; Lozovsky, Elena R.; Hartl, Daniel L.; Shakhnovich, Eugene I.

    2016-01-01

    Fitness landscapes of drug resistance constitute powerful tools to elucidate mutational pathways of antibiotic escape. Here, we developed a predictive biophysics-based fitness landscape of trimethoprim (TMP) resistance for Escherichia coli dihydrofolate reductase (DHFR). We investigated the activity, binding, folding stability, and intracellular abundance for a complete set of combinatorial DHFR mutants made out of three key resistance mutations and extended this analysis to DHFR originated from Chlamydia muridarum and Listeria grayi. We found that the acquisition of TMP resistance via decreased drug affinity is limited by a trade-off in catalytic efficiency. Protein stability is concurrently affected by the resistant mutants, which precludes a precise description of fitness from a single molecular trait. Application of the kinetic flux theory provided an accurate model to predict resistance phenotypes (IC50) quantitatively from a unique combination of the in vitro protein molecular properties. Further, we found that a controlled modulation of the GroEL/ES chaperonins and Lon protease levels affects the intracellular steady-state concentration of DHFR in a mutation-specific manner, whereas IC50 is changed proportionally, as indeed predicted by the model. This unveils a molecular rationale for the pleiotropic role of the protein quality control machinery on the evolution of antibiotic resistance, which, as we illustrate here, may drastically confound the evolutionary outcome. These results provide a comprehensive quantitative genotype–phenotype map for the essential enzyme that serves as an important target of antibiotic and anticancer therapies. PMID:26929328

  13. Predicting bacterial fitness cost associated with drug resistance.

    PubMed

    Guo, Beining; Abdelraouf, Kamilia; Ledesma, Kimberly R; Nikolaou, Michael; Tam, Vincent H

    2012-04-01

    It has been proposed that antimicrobial resistance could be associated with a fitness cost in bacteria, which is often determined by competition experiments between isogenic strains (wild-type and mutant). However, this conventional approach is time consuming and labour intensive. An alternative method was developed to assess the fitness cost in drug-resistant bacteria. Time-growth studies were performed with approximately 1 × 10(5) cfu/mL of Acinetobacter baumannii or Pseudomonas aeruginosa at baseline. Serial samples were obtained to quantify the bacterial burden over 24 h. The growth rates (K(g)) of isogenic strains (antibiotic susceptible and resistant) were determined individually and used to predict their relative abundance in a co-culture over an extended period of time. The predicted difference between the two strains was subsequently validated by in vitro growth competition experiments. The growth rates of A. baumannii were not significantly different in different strengths of growth medium. The difference in bacterial burden observed in competition studies was in general agreement with the predicted difference based on K(g) values, suggesting good predicting ability of the mathematical model. The proposed mathematical model was found to be reasonable in characterizing bacterial growth and predicting the fitness cost of resistance. This simple method appears robust in the assessment of fitness cost associated with drug resistance and warrants further investigations.

  14. Mathematical modeling and computational prediction of cancer drug resistance.

    PubMed

    Sun, Xiaoqiang; Hu, Bin

    2017-06-23

    Diverse forms of resistance to anticancer drugs can lead to the failure of chemotherapy. Drug resistance is one of the most intractable issues for successfully treating cancer in current clinical practice. Effective clinical approaches that could counter drug resistance by restoring the sensitivity of tumors to the targeted agents are urgently needed. As numerous experimental results on resistance mechanisms have been obtained and a mass of high-throughput data has been accumulated, mathematical modeling and computational predictions using systematic and quantitative approaches have become increasingly important, as they can potentially provide deeper insights into resistance mechanisms, generate novel hypotheses or suggest promising treatment strategies for future testing. In this review, we first briefly summarize the current progress of experimentally revealed resistance mechanisms of targeted therapy, including genetic mechanisms, epigenetic mechanisms, posttranslational mechanisms, cellular mechanisms, microenvironmental mechanisms and pharmacokinetic mechanisms. Subsequently, we list several currently available databases and Web-based tools related to drug sensitivity and resistance. Then, we focus primarily on introducing some state-of-the-art computational methods used in drug resistance studies, including mechanism-based mathematical modeling approaches (e.g. molecular dynamics simulation, kinetic model of molecular networks, ordinary differential equation model of cellular dynamics, stochastic model, partial differential equation model, agent-based model, pharmacokinetic-pharmacodynamic model, etc.) and data-driven prediction methods (e.g. omics data-based conventional screening approach for node biomarkers, static network approach for edge biomarkers and module biomarkers, dynamic network approach for dynamic network biomarkers and dynamic module network biomarkers, etc.). Finally, we discuss several further questions and future directions for the use of

  15. Protein design algorithms predict viable resistance to an experimental antifolate.

    PubMed

    Reeve, Stephanie M; Gainza, Pablo; Frey, Kathleen M; Georgiev, Ivelin; Donald, Bruce R; Anderson, Amy C

    2015-01-20

    Methods to accurately predict potential drug target mutations in response to early-stage leads could drive the design of more resilient first generation drug candidates. In this study, a structure-based protein design algorithm (K* in the OSPREY suite) was used to prospectively identify single-nucleotide polymorphisms that confer resistance to an experimental inhibitor effective against dihydrofolate reductase (DHFR) from Staphylococcus aureus. Four of the top-ranked mutations in DHFR were found to be catalytically competent and resistant to the inhibitor. Selection of resistant bacteria in vitro reveals that two of the predicted mutations arise in the background of a compensatory mutation. Using enzyme kinetics, microbiology, and crystal structures of the complexes, we determined the fitness of the mutant enzymes and strains, the structural basis of resistance, and the compensatory relationship of the mutations. To our knowledge, this work illustrates the first application of protein design algorithms to prospectively predict viable resistance mutations that arise in bacteria under antibiotic pressure.

  16. Cooperative Bacterial Growth Dynamics Predict the Evolution of Antibiotic Resistance

    NASA Astrophysics Data System (ADS)

    Artemova, Tatiana; Gerardin, Ylaine; Hsin-Jung Li, Sophia; Gore, Jeff

    2011-03-01

    Since the discovery of penicillin, antibiotics have been our primary weapon against bacterial infections. Unfortunately, bacteria can gain resistance to penicillin by acquiring the gene that encodes beta-lactamase, which inactivates the antibiotic. However, mutations in this gene are necessary to degrade the modern antibiotic cefotaxime. Understanding the conditions that favor the spread of these mutations is a challenge. Here we show that bacterial growth in beta-lactam antibiotics is cooperative and that the nature of this growth determines the conditions in which resistance evolves. Quantitative analysis of the growth dynamics predicts a peak in selection at very low antibiotic concentrations; competition between strains confirms this prediction. We also find significant selection at higher antibiotic concentrations, close to the minimum inhibitory concentrations of the strains. Our results argue that an understanding of the evolutionary forces that lead to antibiotic resistance requires a quantitative understanding of the evolution of cooperation in bacteria.

  17. Development of a Protocol for Predicting Bacterial Resistance to Microbicides

    PubMed Central

    Knapp, Laura; Amézquita, Alejandro; McClure, Peter; Stewart, Sara

    2015-01-01

    Regulations dealing with microbicides in Europe and the United States are evolving and now require data on the risk of the development of resistance in organisms targeted by microbicidal products. There is no standard protocol to assess the risk of the development of resistance to microbicidal formulations. This study aimed to validate the use of changes in microbicide and antibiotic susceptibility as initial markers for predicting microbicide resistance and cross-resistance to antibiotics. Three industrial isolates (Pseudomonas aeruginosa, Burkholderia cepacia, and Klebsiella pneumoniae) and two Salmonella enterica serovar Typhimurium strains (SL1344 and 14028S) were exposed to a shampoo, a mouthwash, eye makeup remover, and the microbicides contained within these formulations (chlorhexidine digluconate [CHG] and benzalkonium chloride [BZC]) under realistic, in-use conditions. Baseline and postexposure data were compared. No significant increases in the MIC or the minimum bactericidal concentration (MBC) were observed for any strain after exposure to the three formulations. Increases as high as 100-fold in the MICs and MBCs of CHG and BZC for SL1344 and 14028S were observed but were unstable. Changes in antibiotic susceptibility were not clinically significant. The use of MICs and MBCs combined with antibiotic susceptibility profiling and stability testing generated reproducible data that allowed for an initial prediction of the development of resistance to microbicides. These approaches measure characteristics that are directly relevant to the concern over resistance and cross-resistance development following the use of microbicides. These are low-cost, high-throughput techniques, allowing manufacturers to provide to regulatory bodies, promptly and efficiently, data supporting an early assessment of the risk of resistance development. PMID:25636848

  18. Development of a protocol for predicting bacterial resistance to microbicides.

    PubMed

    Knapp, Laura; Amézquita, Alejandro; McClure, Peter; Stewart, Sara; Maillard, Jean-Yves

    2015-04-01

    Regulations dealing with microbicides in Europe and the United States are evolving and now require data on the risk of the development of resistance in organisms targeted by microbicidal products. There is no standard protocol to assess the risk of the development of resistance to microbicidal formulations. This study aimed to validate the use of changes in microbicide and antibiotic susceptibility as initial markers for predicting microbicide resistance and cross-resistance to antibiotics. Three industrial isolates (Pseudomonas aeruginosa, Burkholderia cepacia, and Klebsiella pneumoniae) and two Salmonella enterica serovar Typhimurium strains (SL1344 and 14028S) were exposed to a shampoo, a mouthwash, eye makeup remover, and the microbicides contained within these formulations (chlorhexidine digluconate [CHG] and benzalkonium chloride [BZC]) under realistic, in-use conditions. Baseline and postexposure data were compared. No significant increases in the MIC or the minimum bactericidal concentration (MBC) were observed for any strain after exposure to the three formulations. Increases as high as 100-fold in the MICs and MBCs of CHG and BZC for SL1344 and 14028S were observed but were unstable. Changes in antibiotic susceptibility were not clinically significant. The use of MICs and MBCs combined with antibiotic susceptibility profiling and stability testing generated reproducible data that allowed for an initial prediction of the development of resistance to microbicides. These approaches measure characteristics that are directly relevant to the concern over resistance and cross-resistance development following the use of microbicides. These are low-cost, high-throughput techniques, allowing manufacturers to provide to regulatory bodies, promptly and efficiently, data supporting an early assessment of the risk of resistance development. Copyright © 2015, American Society for Microbiology. All Rights Reserved.

  19. Genomic prediction for tuberculosis resistance in dairy cattle.

    PubMed

    Tsairidou, Smaragda; Woolliams, John A; Allen, Adrian R; Skuce, Robin A; McBride, Stewart H; Wright, David M; Bermingham, Mairead L; Pong-Wong, Ricardo; Matika, Oswald; McDowell, Stanley W J; Glass, Elizabeth J; Bishop, Stephen C

    2014-01-01

    The increasing prevalence of bovine tuberculosis (bTB) in the UK and the limitations of the currently available diagnostic and control methods require the development of complementary approaches to assist in the sustainable control of the disease. One potential approach is the identification of animals that are genetically more resistant to bTB, to enable breeding of animals with enhanced resistance. This paper focuses on prediction of resistance to bTB. We explore estimation of direct genomic estimated breeding values (DGVs) for bTB resistance in UK dairy cattle, using dense SNP chip data, and test these genomic predictions for situations when disease phenotypes are not available on selection candidates. We estimated DGVs using genomic best linear unbiased prediction methodology, and assessed their predictive accuracies with a cross validation procedure and receiver operator characteristic (ROC) curves. Furthermore, these results were compared with theoretical expectations for prediction accuracy and area-under-the-ROC-curve (AUC). The dataset comprised 1151 Holstein-Friesian cows (bTB cases or controls). All individuals (592 cases and 559 controls) were genotyped for 727,252 loci (Illumina Bead Chip). The estimated observed heritability of bTB resistance was 0.23±0.06 (0.34 on the liability scale) and five-fold cross validation, replicated six times, provided a prediction accuracy of 0.33 (95% C.I.: 0.26, 0.40). ROC curves, and the resulting AUC, gave a probability of 0.58, averaged across six replicates, of correctly classifying cows as diseased or as healthy based on SNP chip genotype alone using these data. These results provide a first step in the investigation of the potential feasibility of genomic selection for bTB resistance using SNP data. Specifically, they demonstrate that genomic selection is possible, even in populations with no pedigree data and on animals lacking bTB phenotypes. However, a larger training population will be required to improve

  20. Genomic Prediction for Tuberculosis Resistance in Dairy Cattle

    PubMed Central

    Tsairidou, Smaragda; Woolliams, John A.; Allen, Adrian R.; Skuce, Robin A.; McBride, Stewart H.; Wright, David M.; Bermingham, Mairead L.; Pong-Wong, Ricardo; Matika, Oswald; McDowell, Stanley W. J.; Glass, Elizabeth J.; Bishop, Stephen C.

    2014-01-01

    Background The increasing prevalence of bovine tuberculosis (bTB) in the UK and the limitations of the currently available diagnostic and control methods require the development of complementary approaches to assist in the sustainable control of the disease. One potential approach is the identification of animals that are genetically more resistant to bTB, to enable breeding of animals with enhanced resistance. This paper focuses on prediction of resistance to bTB. We explore estimation of direct genomic estimated breeding values (DGVs) for bTB resistance in UK dairy cattle, using dense SNP chip data, and test these genomic predictions for situations when disease phenotypes are not available on selection candidates. Methodology/Principal Findings We estimated DGVs using genomic best linear unbiased prediction methodology, and assessed their predictive accuracies with a cross validation procedure and receiver operator characteristic (ROC) curves. Furthermore, these results were compared with theoretical expectations for prediction accuracy and area-under-the-ROC-curve (AUC). The dataset comprised 1151 Holstein-Friesian cows (bTB cases or controls). All individuals (592 cases and 559 controls) were genotyped for 727,252 loci (Illumina Bead Chip). The estimated observed heritability of bTB resistance was 0.23±0.06 (0.34 on the liability scale) and five-fold cross validation, replicated six times, provided a prediction accuracy of 0.33 (95% C.I.: 0.26, 0.40). ROC curves, and the resulting AUC, gave a probability of 0.58, averaged across six replicates, of correctly classifying cows as diseased or as healthy based on SNP chip genotype alone using these data. Conclusions/Significance These results provide a first step in the investigation of the potential feasibility of genomic selection for bTB resistance using SNP data. Specifically, they demonstrate that genomic selection is possible, even in populations with no pedigree data and on animals lacking bTB phenotypes

  1. Personalized Cancer Medicine: Molecular Diagnostics, Predictive biomarkers, and Drug Resistance

    PubMed Central

    Gonzalez de Castro, D; Clarke, P A; Al-Lazikani, B; Workman, P

    2013-01-01

    The progressive elucidation of the molecular pathogenesis of cancer has fueled the rational development of targeted drugs for patient populations stratified by genetic characteristics. Here we discuss general challenges relating to molecular diagnostics and describe predictive biomarkers for personalized cancer medicine. We also highlight resistance mechanisms for epidermal growth factor receptor (EGFR) kinase inhibitors in lung cancer. We envisage a future requiring the use of longitudinal genome sequencing and other omics technologies alongside combinatorial treatment to overcome cellular and molecular heterogeneity and prevent resistance caused by clonal evolution. PMID:23361103

  2. Modelling proteins' hidden conformations to predict antibiotic resistance

    NASA Astrophysics Data System (ADS)

    Hart, Kathryn M.; Ho, Chris M. W.; Dutta, Supratik; Gross, Michael L.; Bowman, Gregory R.

    2016-10-01

    TEM β-lactamase confers bacteria with resistance to many antibiotics and rapidly evolves activity against new drugs. However, functional changes are not easily explained by differences in crystal structures. We employ Markov state models to identify hidden conformations and explore their role in determining TEM's specificity. We integrate these models with existing drug-design tools to create a new technique, called Boltzmann docking, which better predicts TEM specificity by accounting for conformational heterogeneity. Using our MSMs, we identify hidden states whose populations correlate with activity against cefotaxime. To experimentally detect our predicted hidden states, we use rapid mass spectrometric footprinting and confirm our models' prediction that increased cefotaxime activity correlates with reduced Ω-loop flexibility. Finally, we design novel variants to stabilize the hidden cefotaximase states, and find their populations predict activity against cefotaxime in vitro and in vivo. Therefore, we expect this framework to have numerous applications in drug and protein design.

  3. Modelling proteins’ hidden conformations to predict antibiotic resistance

    PubMed Central

    Hart, Kathryn M.; Ho, Chris M. W.; Dutta, Supratik; Gross, Michael L.; Bowman, Gregory R.

    2016-01-01

    TEM β-lactamase confers bacteria with resistance to many antibiotics and rapidly evolves activity against new drugs. However, functional changes are not easily explained by differences in crystal structures. We employ Markov state models to identify hidden conformations and explore their role in determining TEM’s specificity. We integrate these models with existing drug-design tools to create a new technique, called Boltzmann docking, which better predicts TEM specificity by accounting for conformational heterogeneity. Using our MSMs, we identify hidden states whose populations correlate with activity against cefotaxime. To experimentally detect our predicted hidden states, we use rapid mass spectrometric footprinting and confirm our models’ prediction that increased cefotaxime activity correlates with reduced Ω-loop flexibility. Finally, we design novel variants to stabilize the hidden cefotaximase states, and find their populations predict activity against cefotaxime in vitro and in vivo. Therefore, we expect this framework to have numerous applications in drug and protein design. PMID:27708258

  4. Predicting Resistance by Mutagenesis: Lessons from 45 Years of MBC Resistance

    PubMed Central

    Hawkins, Nichola J.; Fraaije, Bart A.

    2016-01-01

    When a new fungicide class is introduced, it is useful to anticipate the resistance risk in advance, attempting to predict both risk level and potential mechanisms. One tool for the prediction of resistance risk is laboratory selection for resistance, with the mutational supply increased through UV or chemical mutagenesis. This enables resistance to emerge more rapidly than in the field, but may produce mutations that would not emerge under field conditions. The methyl benzimidazole carbamates (MBCs) were the first systemic single-site agricultural fungicides, and the first fungicides affected by rapid evolution of target-site resistance. MBC resistance has now been reported in over 90 plant pathogens in the field, and laboratory mutants have been studied in nearly 30 species. The most common field mutations, including β-tubulin E198A/K/G, F200Y and L240F, have all been identified in laboratory mutants. However, of 28 mutations identified in laboratory mutants, only nine have been reported in the field. Therefore, the predictive value of mutagenesis studies would be increased by understanding which mutations are likely to emerge in the field. Our review of the literature indicates that mutations with high resistance factors, and those found in multiple species, are more likely to be reported in the field. However, there are many exceptions, possibly due to fitness penalties. Whether a mutation occurred in the same species appears less relevant, perhaps because β-tubulin is highly conserved so functional constraints are similar across all species. Predictability of mutations in other target sites will depend on the level and conservation of constraints. PMID:27895632

  5. Evaluating the Significance of CDK2-PELP1 Axis in Tumorigenesis and Hormone Therapy Resistance

    DTIC Science & Technology

    2010-02-01

    Evaluating the Significance of CDK2 -PELP1 Axis in Tumorigenesis and Hormone Therapy Resistance PRINCIPAL INVESTIGATOR: Binoj Nair...conspicuous of which is the upregulation of Cyclin E and A, along with activation of Cyclin Dependent Kinase 2 ( CDK2 ) ((6-10). Activation of CDK2 in...SRC-1 (17), SRC3 (AIB1) (18-20), NCOR1 (21) and PELP1 (22). The major focus of this proposal will be on PELP1 (Proline, glutamic Acid and Leucine

  6. Combining classifiers for HIV-1 drug resistance prediction.

    PubMed

    Srisawat, Anantaporn; Kijsirikul, Boonserm

    2008-01-01

    This paper applies and studies the behavior of three learning algorithms, i.e. the Support Vector machine (SVM), the Radial Basis Function Network (the RBF network), and k-Nearest Neighbor (k-NN) for predicting HIV-1 drug resistance from genotype data. In addition, a new algorithm for classifier combination is proposed. The results of comparing the predictive performance of three learning algorithms show that, SVM yields the highest average accuracy, the RBF network gives the highest sensitivity, and k-NN yields the best in specificity. Finally, the comparison of the predictive performance of the composite classifier with three learning algorithms demonstrates that the proposed composite classifier provides the highest average accuracy.

  7. Genomic prediction for tick resistance in Braford and Hereford cattle.

    PubMed

    Cardoso, F F; Gomes, C C G; Sollero, B P; Oliveira, M M; Roso, V M; Piccoli, M L; Higa, R H; Yokoo, M J; Caetano, A R; Aguilar, I

    2015-06-01

    One of the main animal health problems in tropical and subtropical cattle production is the bovine tick, which causes decreased performance, hide devaluation, increased production costs with acaricide treatments, and transmission of infectious diseases. This study investigated the utility of genomic prediction as a tool to select Braford (BO) and Hereford (HH) cattle resistant to ticks. The accuracy and bias of different methods for direct and blended genomic prediction was assessed using 10,673 tick counts obtained from 3,435 BO and 928 HH cattle belonging to the Delta G Connection breeding program. A subset of 2,803 BO and 652 HH samples were genotyped and 41,045 markers remained after quality control. Log transformed records were adjusted by a pedigree repeatability model to estimate variance components, genetic parameters, and breeding values (EBV) and subsequently used to obtain deregressed EBV. Estimated heritability and repeatability for tick counts were 0.19 ± 0.03 and 0.29 ± 0.01, respectively. Data were split into 5 subsets using k-means and random clustering for cross-validation of genomic predictions. Depending on the method, direct genomic value (DGV) prediction accuracies ranged from 0.35 with Bayes least absolute shrinkage and selection operator (LASSO) to 0.39 with BayesB for k-means clustering and between 0.42 with BayesLASSO and 0.45 with BayesC for random clustering. All genomic methods were superior to pedigree BLUP (PBLUP) accuracies of 0.26 for k-means and 0.29 for random groups, with highest accuracy gains obtained with BayesB (39%) for k-means and BayesC (55%) for random groups. Blending of historical phenotypic and pedigree information by different methods further increased DGV accuracies by values between 0.03 and 0.05 for direct prediction methods. However, highest accuracy was observed with single-step genomic BLUP with values of 0.48 for -means and 0.56, which represent, respectively, 84 and 93% improvement over PBLUP. Observed random

  8. Widespread convergence in toxin resistance by predictable molecular evolution

    PubMed Central

    Ujvari, Beata; Casewell, Nicholas R.; Sunagar, Kartik; Arbuckle, Kevin; Wüster, Wolfgang; Lo, Nathan; O’Meally, Denis; Beckmann, Christa; King, Glenn F.; Deplazes, Evelyne; Madsen, Thomas

    2015-01-01

    The question about whether evolution is unpredictable and stochastic or intermittently constrained along predictable pathways is the subject of a fundamental debate in biology, in which understanding convergent evolution plays a central role. At the molecular level, documented examples of convergence are rare and limited to occurring within specific taxonomic groups. Here we provide evidence of constrained convergent molecular evolution across the metazoan tree of life. We show that resistance to toxic cardiac glycosides produced by plants and bufonid toads is mediated by similar molecular changes to the sodium-potassium-pump (Na+/K+-ATPase) in insects, amphibians, reptiles, and mammals. In toad-feeding reptiles, resistance is conferred by two point mutations that have evolved convergently on four occasions, whereas evidence of a molecular reversal back to the susceptible state in varanid lizards migrating to toad-free areas suggests that toxin resistance is maladaptive in the absence of selection. Importantly, resistance in all taxa is mediated by replacements of 2 of the 12 amino acids comprising the Na+/K+-ATPase H1–H2 extracellular domain that constitutes a core part of the cardiac glycoside binding site. We provide mechanistic insight into the basis of resistance by showing that these alterations perturb the interaction between the cardiac glycoside bufalin and the Na+/K+-ATPase. Thus, similar selection pressures have resulted in convergent evolution of the same molecular solution across the breadth of the animal kingdom, demonstrating how a scarcity of possible solutions to a selective challenge can lead to highly predictable evolutionary responses. PMID:26372961

  9. Widespread convergence in toxin resistance by predictable molecular evolution.

    PubMed

    Ujvari, Beata; Casewell, Nicholas R; Sunagar, Kartik; Arbuckle, Kevin; Wüster, Wolfgang; Lo, Nathan; O'Meally, Denis; Beckmann, Christa; King, Glenn F; Deplazes, Evelyne; Madsen, Thomas

    2015-09-22

    The question about whether evolution is unpredictable and stochastic or intermittently constrained along predictable pathways is the subject of a fundamental debate in biology, in which understanding convergent evolution plays a central role. At the molecular level, documented examples of convergence are rare and limited to occurring within specific taxonomic groups. Here we provide evidence of constrained convergent molecular evolution across the metazoan tree of life. We show that resistance to toxic cardiac glycosides produced by plants and bufonid toads is mediated by similar molecular changes to the sodium-potassium-pump (Na(+)/K(+)-ATPase) in insects, amphibians, reptiles, and mammals. In toad-feeding reptiles, resistance is conferred by two point mutations that have evolved convergently on four occasions, whereas evidence of a molecular reversal back to the susceptible state in varanid lizards migrating to toad-free areas suggests that toxin resistance is maladaptive in the absence of selection. Importantly, resistance in all taxa is mediated by replacements of 2 of the 12 amino acids comprising the Na(+)/K(+)-ATPase H1-H2 extracellular domain that constitutes a core part of the cardiac glycoside binding site. We provide mechanistic insight into the basis of resistance by showing that these alterations perturb the interaction between the cardiac glycoside bufalin and the Na(+)/K(+)-ATPase. Thus, similar selection pressures have resulted in convergent evolution of the same molecular solution across the breadth of the animal kingdom, demonstrating how a scarcity of possible solutions to a selective challenge can lead to highly predictable evolutionary responses.

  10. Resistance profiles of coagulase-negative staphylococci contaminating blood cultures predict pathogen resistance and patient mortality.

    PubMed

    Obolski, Uri; Alon, Danny; Hadany, Lilach; Stein, Gideon Y

    2014-09-01

    Blood culture isolates are the cornerstone of adequate antibiotic treatment. However, many blood cultures are contaminated with bacteria residing on the skin, the most common contaminants being coagulase-negative staphylococci (CoNS). Such contaminated cultures are mostly disregarded. In this retrospective study, we show that contaminated cultures contain diagnostic information. We tested the association between resistance profiles of CoNS contaminants and those of the actual infecting bacteria isolated subsequently from the same patient, as well as their association with short-term mortality. We identified all patients in Rabin Medical Center, Israel, with positive blood cultures during 2009-12. Data included patient demographics, hospitalization records, comorbidities, blood culture results and date of death. Our cohort consists of 2518 patients with 5290 blood cultures, where 1124 patients had 1664 blood cultures with CoNS contaminants. High overall CoNS resistance predicted high overall resistance of the subsequent bacterial isolates (P<0.004 and P<0.0006, for Gram-positive and -negative bacteria, respectively). Moreover, the resistance of CoNS contaminants to a specific antibiotic predicted the resistance of the subsequent bacterial isolates to that antibiotic (OR=5.55, 95% CI=3.54-8.66, P<10(-15) and OR=2.47, 95% CI=1.61-3.78, P<3 ×10(-5), for Gram-positive and -negative bacteria, respectively). Finally, highly resistant CoNS isolates were associated with higher short-term mortality (hazard ratio=1.71, 95% CI=1.4-2.11, P<10(-6)). Resistance patterns of CoNS contaminants predict specific and overall resistance of subsequent blood culture isolates and short-term mortality. These results may help predict patient mortality and correct empirical antibiotic therapy if blood cultures yield contaminant bacteria and imply that skin commensals may serve as an additional, non-invasive, diagnostic tool. © The Author 2014. Published by Oxford University Press on

  11. Predicting and tracking spatiotemporal moments in electrical resistivity tomography

    NASA Astrophysics Data System (ADS)

    Ward, W. O. C.; Wilkinson, P. B.; Chambers, J.; Bai, L.

    2015-12-01

    Visualisation is an invaluable tool in the study of near sub-surface processes, whether by mathematical modelling or by geophysical imaging. Quantitative analysis can further assist interpretation of the ongoing physical processes, and it is clear that any reliable model should take direct observations into account. Using electrical resistivity tomography (ERT), localised areas can be surveyed to produce 2-D and 3-D time-lapse images. This study investigates combining quantitative results obtained via ERT with spatio-temporal motion models in tracer experiments to interpret and predict fluid flow. As with any indirect imaging technique, ERT suffers specific issues with resolution and smoothness as a result of its inversion process. In addition, artefacts are typical in the resulting volumes. Mathematical models are also a source of uncertainty - and in combining these with ERT images, a trade-off must be made between the theoretical and the observed. Using computational imaging, distinct regions of stable resistivity can be directly extracted from a time-slice of an ERT volume. The automated nature, as well the potential for more than one region-of-interest, means that multiple regions can be detected. Using Kalman filters, it is possible to convert the detections into a process state, taking into account pre-defined models and predicting progression. In consecutive time-steps, newly detected features are assigned, where possible, to existing predictions to create tracks that match the tracer model. Preliminary studies looked at a simple motion model, tracking the centre of mass of a tracer plume with assumed constant velocity and mean resistivity. Extending the model to factor in spatial distribution of the plume, an oriented semi-axis is used to represent the centralised second-order moment, with an increasing factor of magnitude to represent the plume dispersion. Initial results demonstrate the efficacy of the approach, significantly improving reliability as the

  12. Clinical Prediction Rule of Drug Resistant Epilepsy in Children.

    PubMed

    Boonluksiri, Pairoj; Visuthibhan, Anannit; Katanyuwong, Kamornwan

    2015-12-01

    Clinical prediction rules (CPR) are clinical decision-making tools containing variables such as history, physical examination, diagnostic tests by developing scoring model from potential risk factors. This study is to establish clinical prediction scoring of drug-resistant epilepsy (DRE) in children using clinical manifestationa and only basic electroencephalography (EEG). Retrospective cohort study was conducted. A total of 308 children with diagnosed epilepsy were recruited. Primary outcome was the incidence of DRE. Independent determinants were patient characteristics, clinical manifestations and electroencephalography. CPR was performed based on multiple logistic regression. The incidence of DRE was 42%. Risk factors were age onset, prior neurological deficits, and abnormal EEG. CPR can be established and stratified the prediction using scores into 3 levels such as low risk (score<6), moderate risk (score 6-12) and high risk (score>12) with positive likelihood ratio of 0.5, 1.8 and 12.5 respectively. CPR with scoring risks were stratified into 3 levels. The strongest risk is prior global neurological deficits.

  13. Flow resistance and its prediction methods in compound channels

    NASA Astrophysics Data System (ADS)

    Yang, Kejun; Cao, Shuyou; Liu, Xingnian

    2007-02-01

    A series of experiments was carried out in a large symmetric compound channel composed of a rough main channel and rough floodplains to investigate the resistance characteristics of inbank and overbank flows. The effective Manning, Darcy-Weisbach, Chezy coefficients and the relative Nikuradse roughness height were analyzed. Many different representative methods for predicting the composite roughness were systematically summarized. Besides the measured data, a vast number of laboratory data and field data for compound channels were collected and used to check the validity of these methods for different subsection divisions including the vertical, horizontal, diagonal and bisectional divisions. The computation showed that these methods resulted in big errors in assessing the composite roughness in compound channels, and the reasons were analyzed in detail. The error magnitude is related to the subsection divisions.

  14. Prediction of Putative Resistance Islands in a Carbapenem-Resistant Acinetobacter baumannii Global Clone 2 Clinical Isolate

    PubMed Central

    Lee, Yangsoon; D'Souza, Roshan; Lee, Kyungwon

    2016-01-01

    Background We investigated the whole genome sequence (WGS) of a carbapenem-resistant Acinetobacter baumannii isolate belonging to the global clone 2 (GC2) and predicted resistance islands using a software tool. Methods A. baumannii strain YU-R612 was isolated from the sputum of a 61-yr-old man with sepsis. The WGS of the YU-R612 strain was obtained by using the PacBio RS II Sequencing System (Pacific Biosciences Inc., USA). Antimicrobial resistance genes and resistance islands were analyzed by using ResFinder and Genomic Island Prediction software (GIPSy), respectively. Results The YU-R612 genome consisted of a circular chromosome (ca. 4,075 kb) and two plasmids (ca. 74 kb and 5 kb). Its sequence type (ST) under the Oxford scheme was ST191, consistent with assignment to GC2. ResFinder analysis showed that YU-R612 possessed the following resistance genes: four β-lactamase genes blaADC-30, blaOXA-66, blaOXA-23, and blaTEM-1; armA, aadA1, and aacA4 as aminoglycoside resistance-encoding genes; aac(6')Ib-cr for fluoroquinolone resistance; msr(E) for macrolide, lincosamide, and streptogramin B resistance; catB8 for phenicol resistance; and sul1 for sulfonamide resistance. By GIPSy analysis, six putative resistant islands (PRIs) were determined on the YU-R612 chromosome. Among them, PRI1 possessed two copies of Tn2009 carrying blaOXA-23, and PRI5 carried two copies of a class I integron carrying sul1 and armA genes. Conclusions By prediction of resistance islands in the carbapenem-resistant A. baumannii YU-R612 GC2 strain isolated in Korea, PRIs were detected on the chromosome that possessed Tn2009 and class I integrons. The prediction of resistance islands using software tools was useful for analysis of the WGS. PMID:27139604

  15. Antimicrobial drug resistance: "Prediction is very difficult, especially about the future".

    PubMed

    Courvalin, Patrice

    2005-10-01

    Evolution of bacteria towards resistance to antimicrobial drugs, including multidrug resistance, is unavoidable because it represents a particular aspect of the general evolution of bacteria that is unstoppable. Therefore, the only means of dealing with this situation is to delay the emergence and subsequent dissemination of resistant bacteria or resistance genes. Resistance to antimicrobial drugs in bacteria can result from mutations in housekeeping structural or regulatory genes. Alternatively, resistance can result from the horizontal acquisition of foreign genetic information. The 2 phenomena are not mutually exclusive and can be associated in the emergence and more efficient spread of resistance. This review discusses the predictable future of the relationship between antimicrobial drugs and bacteria.

  16. Use of Spatial Information to Predict Multidrug Resistance in Tuberculosis Patients, Peru

    PubMed Central

    Lin, Hsien-Ho; Shin, Sonya S.; Contreras, Carmen; Asencios, Luis; Paciorek, Christopher J.

    2012-01-01

    To determine whether spatiotemporal information could help predict multidrug resistance at the time of tuberculosis diagnosis, we investigated tuberculosis patients who underwent drug susceptibility testing in Lima, Peru, during 2005–2007. We found that crude representation of spatial location at the level of the health center improved prediction of multidrug resistance. PMID:22516236

  17. Anhedonia Predicts Poorer Recovery among Youth with Selective Serotonin Reuptake Inhibitor Treatment-Resistant Depression

    ERIC Educational Resources Information Center

    McMakin, Dana L.; Olino, Thomas M.; Porta, Giovanna; Dietz, Laura J.; Emslie, Graham; Clarke, Gregory; Wagner, Karen Dineen; Asarnow, Joan R.; Ryan, Neal D.; Birmaher, Boris; Shamseddeen, Wael; Mayes, Taryn; Kennard, Betsy; Spirito, Anthony; Keller, Martin; Lynch, Frances L.; Dickerson, John F.; Brent, David A.

    2012-01-01

    Objective: To identify symptom dimensions of depression that predict recovery among selective serotonin reuptake inhibitor (SSRI) treatment-resistant adolescents undergoing second-step treatment. Method: The Treatment of Resistant Depression in Adolescents (TORDIA) trial included 334 SSRI treatment-resistant youth randomized to a medication…

  18. Anhedonia Predicts Poorer Recovery among Youth with Selective Serotonin Reuptake Inhibitor Treatment-Resistant Depression

    ERIC Educational Resources Information Center

    McMakin, Dana L.; Olino, Thomas M.; Porta, Giovanna; Dietz, Laura J.; Emslie, Graham; Clarke, Gregory; Wagner, Karen Dineen; Asarnow, Joan R.; Ryan, Neal D.; Birmaher, Boris; Shamseddeen, Wael; Mayes, Taryn; Kennard, Betsy; Spirito, Anthony; Keller, Martin; Lynch, Frances L.; Dickerson, John F.; Brent, David A.

    2012-01-01

    Objective: To identify symptom dimensions of depression that predict recovery among selective serotonin reuptake inhibitor (SSRI) treatment-resistant adolescents undergoing second-step treatment. Method: The Treatment of Resistant Depression in Adolescents (TORDIA) trial included 334 SSRI treatment-resistant youth randomized to a medication…

  19. Drug-resistant tuberculosis can be predicted by Mycobacterial interspersed repetitive unit locus

    PubMed Central

    Yu-feng, Wen; Chao, Jiang; Xian-feng, Cheng

    2015-01-01

    It is unknown whether MIRU-VNTR (Mycobacterial Interspersed Repetitive Unit-Variable Number of Tandem Repeat) is associated with drug resistance of Mycobacterium tuberculosis. The purpose of this study was to explore the ability of 24 MIRU loci to predict the drug resistance of Isoniazid (INH), Rifampicin (RFP), Streptomycin (SM), Ethambutol (EMB) and Pyrazinamide (PZA). We collected the drug resistance and MIRU loci information of 109 strains of M. tuberculosis from an open database. The results of multivariate logistic regression showed that the VNTR polymorphism of MTUB04 was related to INH resistance [odds ratio (OR) = 2.82, P = 0.00], RFP resistance (OR = 1.91, P = 0.02), SM resistance (OR = 1.98, P = 0.01) and EMB resistance (OR = 1.95, P = 0.03). MIRU40 was associated with INH resistance (OR = 2.22, P = 0.00). MTUB21 was connected with INH resistance (OR = 1.63, P = 0.02) and SM resistance (OR = 1.69, P = 0.01). MIRU26 was correlated with SM resistance (OR = 1.52, P = 0.04). MIRU39 was associated with EMB resistance (OR = 4.07, P = 0.02). The prediction power of MIRU loci were 0.84, 0.70, 0.85, and 0.74 respectively for INH (predicted by MTUB04, MIRU20, and MTUB21), RFP (predicted by MTUB04), SM (predicted by MTUB21 and MIRU26) and EMB (MTUB04 and MIRU39) through ROC analysis. Our results showed that MIRU loci were related to anti-tuberculosis drug and could predict the drug resistance of tuberculosis. PMID:25759689

  20. WGS accurately predicts antimicrobial resistance in Escherichia coli

    USDA-ARS?s Scientific Manuscript database

    Objectives: To determine the effectiveness of whole-genome sequencing (WGS) in identifying resistance genotypes of multidrug-resistant Escherichia coli (E. coli) and whether these correlate with observed phenotypes. Methods: Seventy-six E. coli strains were isolated from farm cattle and measured f...

  1. Contact resistance prediction and structure optimization of bipolar plates

    NASA Astrophysics Data System (ADS)

    Zhou, P.; Wu, C. W.; Ma, G. J.

    The objective of this work is to investigate the effect of clamping force on the interfacial contact resistance and the porosity of the gas diffusion layer (GDL) in a proton exchange membrane fuel cell (PEMFC). An optimal rib shape for the bipolar plate is developed to analyze the electrical contact resistance. We found that the electrical contact resistance is determined by both the clamping force and the contact pressure distribution. A minimum contact resistance can be obtained in the case of a constant contact pressure distribution. The porosity of the GDLs underneath the rib of the bipolar plate decreases with increasing the clamping force, and the void volume is changed with the deformation of the GDLs. It is found that there exists an optimal rib width of the bipolar plates to obtain a reasonable combination of low interfacial contact resistance and good porosity for the GDL.

  2. Determining the waist circumference in african americans which best predicts insulin resistance.

    PubMed

    Sumner, Anne E; Sen, Sabyasachi; Ricks, Madia; Frempong, Barbara A; Sebring, Nancy G; Kushner, Harvey

    2008-04-01

    Total body size and central fat distribution are important determinants of insulin resistance. The BMI and waist circumference (WC) thresholds in African Americans that best predict insulin resistance are unknown. Our goal was to determine the BMI and WC values in African Americans, which optimally predict insulin resistance. The subjects were African Americans (68 men, 63 women), aged 35 +/- 8 years (mean +/- s.d.), with a BMI of 30.9 +/- 7.5, in the range of 18.5-54.7 kg/m(2), and with a WC of 98 +/- 18, in the range of 69-173 cm. Insulin resistance was defined by the lowest tertile of the insulin sensitivity index (S(I)). The Youden index was calculated to determine the WC and BMI thresholds that predict insulin resistance with an optimal combination of sensitivity and specificity. In men the thresholds that optimally predicted insulin resistance were a BMI > or =30 kg/m(2) or a WC > or =102 cm. For women, insulin resistance was best predicted by a BMI > or =32 kg/m(2) or a WC > or =98 cm. In African Americans, insulin resistance (in men) was best predicted by a WC > or =102 cm, and in women by a WC > or =98 cm, or by a BMI value that fell in the obese category (men: > or =30 kg/m(2), women: > or =32 kg/m(2)).

  3. Metagenomic Analysis of Apple Orchard Soil Reveals Antibiotic Resistance Genes Encoding Predicted Bifunctional Proteins▿

    PubMed Central

    Donato, Justin J.; Moe, Luke A.; Converse, Brandon J.; Smart, Keith D.; Berklein, Flora C.; McManus, Patricia S.; Handelsman, Jo

    2010-01-01

    To gain insight into the diversity and origins of antibiotic resistance genes, we identified resistance genes in the soil in an apple orchard using functional metagenomics, which involves inserting large fragments of foreign DNA into Escherichia coli and assaying the resulting clones for expressed functions. Among 13 antibiotic-resistant clones, we found two genes that encode bifunctional proteins. One predicted bifunctional protein confers resistance to ceftazidime and contains a natural fusion between a predicted transcriptional regulator and a β-lactamase. Sequence analysis of the entire metagenomic clone encoding the predicted bifunctional β-lactamase revealed a gene potentially involved in chloramphenicol resistance as well as a predicted transposase. A second clone that encodes a predicted bifunctional protein confers resistance to kanamycin and contains an aminoglycoside acetyltransferase domain fused to a second acetyltransferase domain that, based on nucleotide sequence, was predicted not to be involved in antibiotic resistance. This is the first report of a transcriptional regulator fused to a β-lactamase and of an aminoglycoside acetyltransferase fused to an acetyltransferase not involved in antibiotic resistance. PMID:20453147

  4. Interaction of AIB1 and BRCA1 in Breast Cancer

    DTIC Science & Technology

    2007-03-01

    BRCA1-wild type MCF-7 cells. (A) HCC1937 and (B) MCF-7 cells were plated in IMEM containing 10% fetal bovine serum. After the cells were attached...the media was changed to serum-free IMEM . The cells were transfected with a -1745 cyclin D1 promoter-luciferase (CD1-Luc) reporter construct. After

  5. Resistance to instructed reversal of the learned predictiveness effect.

    PubMed

    Don, Hilary J; Livesey, Evan J

    2015-01-01

    The learned predictiveness effect is a widely observed bias towards previously predictive cues in novel situations. Although the effect is generally attributed to an automatic attentional shift, it has recently been explained as the product of controlled inferences about the predictive value of cues. This view is supported by the susceptibility of learned predictiveness to instruction manipulation. However, recent research has shown conflicting results. Three experiments investigated the parameters of the instructed reversal effect in a human causal learning task, to determine the relative contribution of automatic and controlled attention processes. Experiment 1 showed that reversal instructions abolished, but did not reverse, the learned predictiveness effect, although length of initial training had no effect on the extent to which predictive cues subsequently captured attention. Experiment 2 explored whether particular causal scenarios lend themselves more readily to instructed reversal, but still failed to establish a significant reversal effect. Experiment 3 demonstrated a significant reversal effect when nonpredictive cues were explicitly and individually identified as the causes of outcomes. However, this effect was considerably weaker than the learned predictiveness effect when predictive cues were identified in the same way. Taken together, the results are inconsistent with a purely controlled account of learned predictiveness and provide support for dual-process theories of learning and attention.

  6. Sparse Representation for Prediction of HIV-1 Protease Drug Resistance.

    PubMed

    Yu, Xiaxia; Weber, Irene T; Harrison, Robert W

    2013-01-01

    HIV rapidly evolves drug resistance in response to antiviral drugs used in AIDS therapy. Estimating the specific resistance of a given strain of HIV to individual drugs from sequence data has important benefits for both the therapy of individual patients and the development of novel drugs. We have developed an accurate classification method based on the sparse representation theory, and demonstrate that this method is highly effective with HIV-1 protease. The protease structure is represented using our newly proposed encoding method based on Delaunay triangulation, and combined with the mutated amino acid sequences of known drug-resistant strains to train a machine-learning algorithm both for classification and regression of drug-resistant mutations. An overall cross-validated classification accuracy of 97% is obtained when trained on a publically available data base of approximately 1.5×10(4) known sequences (Stanford HIV database http://hivdb.stanford.edu/cgi-bin/GenoPhenoDS.cgi). Resistance to four FDA approved drugs is computed and comparisons with other algorithms demonstrate that our method shows significant improvements in classification accuracy.

  7. A computational model to monitor and predict trends in bacterial resistance.

    PubMed

    Alawieh, Ali; Sabra, Zahraa; Bizri, Abdul Rahman; Davies, Christopher; White, Roger; Zaraket, Fadi A

    2015-09-01

    Current concern over the emergence of multidrug-resistant superbugs has renewed interest in approaches that can monitor existing trends in bacterial resistance and make predictions of future trends. Recent advances in bacterial surveillance and the development of online repositories of susceptibility tests across wide geographical areas provide an important new resource, yet there are only limited computational tools for its exploitation. Here we propose a hybrid computational model called BARDmaps for automated analysis of antibacterial susceptibility tests from surveillance records and for performing future predictions. BARDmaps was designed to include a structural computational model that can detect patterns among bacterial resistance changes as well as a behavioural computational model that can use the detected patterns to predict future changes in bacterial resistance. Data from the European Antimicrobial Resistance Surveillance Network (EARS-Net) were used to validate and apply the model. BARDmaps was compared with standard curve-fitting approaches used in epidemiological research. Here we show that BARDmaps can reliably predict future trends in bacterial resistance across Europe. BARDmaps performed better than other curve-fitting approaches for predicting future resistance levels. In addition, BARDmaps was also able to detect abrupt changes in bacterial resistance in response to outbreaks and interventions as well as to compare bacterial behaviour across countries and drugs. In conclusion, BARDmaps is a reliable tool to automatically predict and analyse changes in bacterial resistance across Europe. We anticipate that BARDmaps will become an invaluable tool both for clinical providers and governmental agencies to help combat the threat posed by antibiotic-resistant bacteria.

  8. Monitoring Central Venous Catheter Resistance to Predict Imminent Occlusion: A Prospective Pilot Study.

    PubMed

    Wolf, Joshua; Tang, Li; Rubnitz, Jeffrey E; Brennan, Rachel C; Shook, David R; Stokes, Dennis C; Monagle, Paul; Curtis, Nigel; Worth, Leon J; Allison, Kim; Sun, Yilun; Flynn, Patricia M

    2015-01-01

    Long-term central venous catheters are essential for the management of chronic medical conditions, including childhood cancer. Catheter occlusion is associated with an increased risk of subsequent complications, including bloodstream infection, venous thrombosis, and catheter fracture. Therefore, predicting and pre-emptively treating occlusions should prevent complications, but no method for predicting such occlusions has been developed. We conducted a prospective trial to determine the feasibility, acceptability, and efficacy of catheter-resistance monitoring, a novel approach to predicting central venous catheter occlusion in pediatric patients. Participants who had tunneled catheters and were receiving treatment for cancer or undergoing hematopoietic stem cell transplantation underwent weekly catheter-resistance monitoring for up to 12 weeks. Resistance was assessed by measuring the inline pressure at multiple flow-rates via a syringe pump system fitted with a pressure-sensing transducer. When turbulent flow through the device was evident, resistance was not estimated, and the result was noted as "non-laminar." Ten patients attended 113 catheter-resistance monitoring visits. Elevated catheter resistance (>8.8% increase) was strongly associated with the subsequent development of acute catheter occlusion within 10 days (odds ratio = 6.2; 95% confidence interval, 1.8-21.5; p <0.01; sensitivity, 75%; specificity, 67%). A combined prediction model comprising either change in resistance greater than 8.8% or a non-laminar result predicted subsequent occlusion (odds ratio = 6.8; 95% confidence interval, 2.0-22.8; p = 0.002; sensitivity, 80%; specificity, 63%). Participants rated catheter-resistance monitoring as highly acceptable. In this pediatric hematology and oncology population, catheter-resistance monitoring is feasible, acceptable, and predicts imminent catheter occlusion. Larger studies are required to validate these findings, assess the predictive value for

  9. Monitoring Central Venous Catheter Resistance to Predict Imminent Occlusion: A Prospective Pilot Study

    PubMed Central

    Wolf, Joshua; Tang, Li; Rubnitz, Jeffrey E.; Brennan, Rachel C.; Shook, David R.; Stokes, Dennis C.; Monagle, Paul; Curtis, Nigel; Worth, Leon J.; Allison, Kim; Sun, Yilun; Flynn, Patricia M.

    2015-01-01

    Background Long-term central venous catheters are essential for the management of chronic medical conditions, including childhood cancer. Catheter occlusion is associated with an increased risk of subsequent complications, including bloodstream infection, venous thrombosis, and catheter fracture. Therefore, predicting and pre-emptively treating occlusions should prevent complications, but no method for predicting such occlusions has been developed. Methods We conducted a prospective trial to determine the feasibility, acceptability, and efficacy of catheter-resistance monitoring, a novel approach to predicting central venous catheter occlusion in pediatric patients. Participants who had tunneled catheters and were receiving treatment for cancer or undergoing hematopoietic stem cell transplantation underwent weekly catheter-resistance monitoring for up to 12 weeks. Resistance was assessed by measuring the inline pressure at multiple flow-rates via a syringe pump system fitted with a pressure-sensing transducer. When turbulent flow through the device was evident, resistance was not estimated, and the result was noted as “non-laminar.” Results Ten patients attended 113 catheter-resistance monitoring visits. Elevated catheter resistance (>8.8% increase) was strongly associated with the subsequent development of acute catheter occlusion within 10 days (odds ratio = 6.2; 95% confidence interval, 1.8–21.5; p <0.01; sensitivity, 75%; specificity, 67%). A combined prediction model comprising either change in resistance greater than 8.8% or a non-laminar result predicted subsequent occlusion (odds ratio = 6.8; 95% confidence interval, 2.0–22.8; p = 0.002; sensitivity, 80%; specificity, 63%). Participants rated catheter-resistance monitoring as highly acceptable. Conclusions In this pediatric hematology and oncology population, catheter-resistance monitoring is feasible, acceptable, and predicts imminent catheter occlusion. Larger studies are required to validate

  10. ETS Gene Fusions as Predictive Biomarkers of Resistance to Radiation Therapy for Prostate Cancer

    DTIC Science & Technology

    2015-10-01

    Award Number: W81XWH-10-1-0582 TITLE: ETS Gene Fusions as Predictive Biomarkers of Resistance to Radiation Therapy for Prostate Cancer PRINCIPAL...Predictive Biomarkers of Resistance to Radiation Therapy for Prostate Cancer 5b. GRANT NUMBER W81XWH-10-1-0582 5c. PROGRAM ELEMENT NUMBER 6... therapy , which represents a primary treatment modality for localized prostate cancer. In the fifth year of this grant period, we have accomplished

  11. MGMT Expression Predicts PARP-Mediated Resistance to Temozolomide.

    PubMed

    Erice, Oihane; Smith, Michael P; White, Rachel; Goicoechea, Ibai; Barriuso, Jorge; Jones, Chris; Margison, Geoffrey P; Acosta, Juan C; Wellbrock, Claudia; Arozarena, Imanol

    2015-05-01

    Melanoma and other solid cancers are frequently resistant to chemotherapies based on DNA alkylating agents such as dacarbazine and temozolomide. As a consequence, clinical responses are generally poor. Such resistance is partly due to the ability of cancer cells to use a variety of DNA repair enzymes to maintain cell viability. Particularly, the expression of MGMT has been linked to temozolomide resistance, but cotargeting MGMT has proven difficult due to dose-limiting toxicities. Here, we show that the MGMT-mediated resistance of cancer cells is profoundly dependent on the DNA repair enzyme PARP. Both in vitro and in vivo, we observe that MGMT-positive cancer cells strongly respond to the combination of temozolomide and PARP inhibitors (PARPi), whereas MGMT-deficient cells do not. In melanoma cells, temozolomide induced an antiproliferative senescent response, which was greatly enhanced by PARPi in MGMT-positive cells. In summary, we provide compelling evidence to suggest that the stratification of patients with cancer upon the MGMT status would enhance the success of combination treatments using temozolomide and PARPi.

  12. Phylogenetic prediction of Alternaria leaf blight resistance in wild and cultivated species of carrots (Daucus, Apiaceae)

    USDA-ARS?s Scientific Manuscript database

    Plant scientists make inferences and predictions from phylogenetic trees to solve scientific problems. Crop losses due to disease damage is an important problem that many plant breeders would like to solve, so the ability to predict traits like disease resistance from phylogenetic trees derived from...

  13. Testing Taxonomic Predictivity of Foliar and Tuber Resistance to Phytophthora infestans in Wild Relatives of Potato.

    PubMed

    Khiutti, A; Spooner, D M; Jansky, S H; Halterman, D A

    2015-09-01

    Potato late blight, caused by the oomycete phytopathogen Phytophthora infestans, is a devastating disease found in potato-growing regions worldwide. Long-term management strategies to control late blight include the incorporation of host resistance to predominant strains. However, due to rapid genetic changes within pathogen populations, rapid and recurring identification and integration of novel host resistance traits is necessary. Wild relatives of potato offer a rich source of desirable traits, including late blight resistance, but screening methods can be time intensive. We tested the ability of taxonomy, ploidy, crossing group, breeding system, and geography to predict the presence of foliar and tuber late blight resistance in wild Solanum spp. Significant variation for resistance to both tuber and foliar late blight was found within and among species but there was no discernable predictive power based on taxonomic series, clade, ploidy, breeding system, elevation, or geographic location. We observed a moderate but significant correlation between tuber and foliar resistance within species. Although previously uncharacterized sources of both foliar and tuber resistance were identified, our study does not support an assumption that taxonomic or geographic data can be used to predict sources of late blight resistance in wild Solanum spp.

  14. OSPREY Predicts Resistance Mutations using Positive and Negative Computational Protein Design

    PubMed Central

    Ojewole, Adegoke; Lowegard, Anna; Gainza, Pablo; Reeve, Stephanie M.; Georgiev, Ivelin; Anderson, Amy C.; Donald, Bruce R.

    2016-01-01

    Summary Drug resistance in protein targets is an increasingly common phenomenon that reduces the efficacy of both existing and new antibiotics. However, knowledge of future resistance mutations during pre-clinical phases of drug development would enable the design of novel antibiotics that are robust against not only known resistant mutants, but also against those that have not yet been clinically observed. Computational structure-based protein design (CSPD) is a transformative field that enables the prediction of protein sequences with desired biochemical properties such as binding affinity and specificity to a target. The use of CSPD to predict previously unseen resistance mutations represents one of the frontiers of computational protein design. In a recent study (1), we used our OSPREY (Open Source Protein REdesign for You) suite of CSPD algorithms to prospectively predict resistance mutations that arise in the active site of the dihydrofolate reductase enzyme from methicillin-resistant Staphylococcus aureus (SaDHFR) in response to selective pressure from an experimental competitive inhibitor. We demonstrated that our top predicted candidates are indeed viable resistant mutants. Since that study, we have significantly enhanced the capabilities of OSPREY with not only improved modeling of backbone flexibility, but also efficient multi-state design, fast sparse approximations, partitioned rotamers for more accurate energy bounds, and a computationally efficient representation of molecular-mechanics and quantum-mechanical energy functions. Here, using SaDHFR as an example, we present a protocol for resistance prediction using the latest version of OSPREY. Specifically, we show how to use a combination of positive and negative design to predict active site escape mutations that maintain the enzyme’s catalytic function but selectively ablate binding of an inhibitor. PMID:27914058

  15. Prediction of HIV-1 protease inhibitor resistance using a protein-inhibitor flexible docking approach.

    PubMed

    Jenwitheesuk, Ekachai; Samudrala, Ram

    2005-01-01

    Emergence of drug resistance remains one of the most challenging issues in the treatment of HIV-1 infection. Here we focus on resistance to HIV-1 protease inhibitors (PIs) at a molecular level, which can be analysed genotypically or phenotypically. Genotypic assays are based on the analysis of mutations associated with reduced drug susceptibility, but are problematic because of the numerous mutations and mutational patterns that confer drug resistance. Phenotypic resistance or susceptibility can be experimentally evaluated by measuring the amount of free drug bound to HIV-1 protease molecules, but this procedure is expensive and time-consuming. To overcome these problems, we have developed a docking protocol that takes protein-inhibitor flexibility into account to predict phenotypic drug resistance. For six FDA-approved Pls and a total of 1792 HIV-1 protease sequence mutants, we used a combination of inhibitor flexible docking and molecular dynamics (MD) simulations to calculate protein-inhibitor binding energies. Prediction results were expressed as fold changes of the calculated inhibitory constant (Ki), and the samples predicted to have fold-increase in calculated Ki above the fixed cut-off were defined as drug resistant. Our combined docking and MD protocol achieved accuracies ranging from 72-83% in predicting resistance/susceptibility for five of the six drugs evaluated. Evaluating the method only on samples where our predictions concurred with established knowledge-based methods resulted in increased accuracies of 83-94% for the six drugs. The results suggest that a physics-based approach, which is readily applicable to any novel PI and/or mutant, can be used judiciously with knowledge-based approaches that require experimental training data to devise accurate models of HIV-1 Pl resistance prediction.

  16. OSPREY Predicts Resistance Mutations Using Positive and Negative Computational Protein Design.

    PubMed

    Ojewole, Adegoke; Lowegard, Anna; Gainza, Pablo; Reeve, Stephanie M; Georgiev, Ivelin; Anderson, Amy C; Donald, Bruce R

    2017-01-01

    Drug resistance in protein targets is an increasingly common phenomenon that reduces the efficacy of both existing and new antibiotics. However, knowledge of future resistance mutations during pre-clinical phases of drug development would enable the design of novel antibiotics that are robust against not only known resistant mutants, but also against those that have not yet been clinically observed. Computational structure-based protein design (CSPD) is a transformative field that enables the prediction of protein sequences with desired biochemical properties such as binding affinity and specificity to a target. The use of CSPD to predict previously unseen resistance mutations represents one of the frontiers of computational protein design. In a recent study (Reeve et al. Proc Natl Acad Sci U S A 112(3):749-754, 2015), we used our OSPREY (Open Source Protein REdesign for You) suite of CSPD algorithms to prospectively predict resistance mutations that arise in the active site of the dihydrofolate reductase enzyme from methicillin-resistant Staphylococcus aureus (SaDHFR) in response to selective pressure from an experimental competitive inhibitor. We demonstrated that our top predicted candidates are indeed viable resistant mutants. Since that study, we have significantly enhanced the capabilities of OSPREY with not only improved modeling of backbone flexibility, but also efficient multi-state design, fast sparse approximations, partitioned continuous rotamers for more accurate energy bounds, and a computationally efficient representation of molecular-mechanics and quantum-mechanical energy functions. Here, using SaDHFR as an example, we present a protocol for resistance prediction using the latest version of OSPREY. Specifically, we show how to use a combination of positive and negative design to predict active site escape mutations that maintain the enzyme's catalytic function but selectively ablate binding of an inhibitor.

  17. A test of taxonomic predictivity: resistance to early blight in wild relatives of cultivated potato.

    PubMed

    Jansky, S H; Simon, R; Spooner, D M

    2008-06-01

    Host plant resistance offers an attractive method of control for early blight (caused by the foliar fungus Alternaria solani), a widespread disease that appears annually in potato crops worldwide. We tested the assumed ability of taxonomy to predict the presence of early blight resistance genes in wild Solanum species for which resistance was observed in related species. We also tested associations to ploidy, crossing group, breeding system, and geography. As in a prior study of Sclerotinia sclerotiorum (white mold) resistance, tremendous variation for resistance to early blight was found to occur within and among species. There was no discernable relationship between the distribution of resistant phenotypes and taxonomic series (based on an intuitive interpretation of morphological data), clade (based on a cladistic analysis of plastid DNA data), ploidy, breeding system, geographic distance, or climate parameters. Species and individual accessions with high proportions of early blight resistant plants were identified, but high levels of inter- and intra-accession variability were observed. Consequently, the designation of species or accessions as resistant or susceptible must take this variation into account. This study calls into question the assumption that taxonomic or geographic data can be used to predict sources of early blight resistance in wild Solanum species.

  18. Validation of Resistance Predictions Using Total Ship Drag (TSD)

    DTIC Science & Technology

    2011-12-01

    Predictions Using Total Ship Drag (TSD) by Wesley Wilson, Dane Hendrix, Francis Noblesse, Joe Gorski 7 y- i o • a o a 5 co Approved for Public...Total Ship Drag (TSD) 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) Wesley Wilson, Dane Hendrix, Francis Noblesse...its development in the past. Most notably these include Dr. Francis Noblesse and Bryson Metcalf from the Hydromechanics Department at the Naval

  19. Absence of RIPK3 predicts necroptosis resistance in malignant melanoma

    PubMed Central

    Geserick, P; Wang, J; Schilling, R; Horn, S; Harris, P A; Bertin, J; Gough, P J; Feoktistova, M; Leverkus, M

    2015-01-01

    Acquired or intrinsic resistance to apoptotic and necroptotic stimuli is considered a major hindrance of therapeutic success in malignant melanoma. Inhibitor of apoptosis proteins (IAPs) are important regulators of apoptotic and necroptotic cell death mediated by numerous cell death signalling platforms. In this report we investigated the impact of IAPs for cell death regulation in malignant melanoma. Suppression of IAPs strongly sensitized a panel of melanoma cells to death ligand-induced cell death, which, surprisingly, was largely mediated by apoptosis, as it was completely rescued by addition of caspase inhibitors. Interestingly, the absence of necroptosis signalling correlated with a lack of receptor-interacting protein kinase-3 (RIPK3) mRNA and protein expression in all cell lines, whereas primary melanocytes and cultured nevus cells strongly expressed RIPK3. Reconstitution of RIPK3, but not a RIPK3-kinase dead mutant in a set of melanoma cell lines overcame CD95L/IAP antagonist-induced necroptosis resistance independent of autocrine tumour necrosis factor secretion. Using specific inhibitors, functional studies revealed that RIPK3-mediated mixed-lineage kinase domain-like protein (MLKL) phosphorylation and necroptosis induction critically required receptor-interacting protein kinase-1 signalling. Furthermore, the inhibitor of mutant BRAF Dabrafenib, but not Vemurafenib, inhibited necroptosis in melanoma cells whenever RIPK3 is present. Our data suggest that loss of RIPK3 in melanoma and selective inhibition of the RIPK3/MLKL axis by BRAF inhibitor Dabrafenib, but not Vemurafenib, is critical to protect from necroptosis. Strategies that allow RIPK3 expression may allow unmasking the necroptotic signalling machinery in melanoma and points to reactivation of this pathway as a treatment option for metastatic melanoma. PMID:26355347

  20. Prediction of HIV drug resistance from genotype with encoded three-dimensional protein structure

    PubMed Central

    2014-01-01

    Background Drug resistance has become a severe challenge for treatment of HIV infections. Mutations accumulate in the HIV genome and make certain drugs ineffective. Prediction of resistance from genotype data is a valuable guide in choice of drugs for effective therapy. Results In order to improve the computational prediction of resistance from genotype data we have developed a unified encoding of the protein sequence and three-dimensional protein structure of the drug target for classification and regression analysis. The method was tested on genotype-resistance data for mutants of HIV protease and reverse transcriptase. Our graph based sequence-structure approach gives high accuracy with a new sparse dictionary classification method, as well as support vector machine and artificial neural networks classifiers. Cross-validated regression analysis with the sparse dictionary gave excellent correlation between predicted and observed resistance. Conclusion The approach of encoding the protein structure and sequence as a 210-dimensional vector, based on Delaunay triangulation, has promise as an accurate method for predicting resistance from sequence for drugs inhibiting HIV protease and reverse transcriptase. PMID:25081370

  1. Predictive factors of resistance to intravenous immunoglobulin and coronary artery lesions in Kawasaki disease

    PubMed Central

    Lee, Hye Young

    2016-01-01

    Purpose We conducted a study to determine which factors may be useful as predictive markers in identifying Kawasaki disease (KD) patients with a high risk of resistance to intravenous immunoglobulin (IVIG) and developing coronary artery lesions (CAL). Methods We enrolled 287 patients in acute phase of KD at a single center. The demographic, clinical and laboratory data were collected retrospectively. Results There were 34 patients in the IVIG resistant group. The IVIG resistant group had significantly higher serum N-terminal-pro-brain natriuretic protein (NT-proBNP) levels (P<0.01) and polymorphonuclear neutrophil (PMN) percentage (P<0.01) in comparison to the IVIG responders. The results yielded sensitivity (78.8%, 60.6%), specificity (58.2%, 90%) and cutoff value (628.6 pg/mL, 80.3%) of NT-proBNP and PMN respectively, in predicting IVIG resistance. Despite IVIG administration, 13 of the 287 patients developed CAL. The patients in the CAL group had higher NT-proBNP levels (P<0.01) and higher PMN percentage (P<0.01). In these patients, the results yielded sensitivity (73.3%, 56.7%), specificity (67.9%, 88.9%) and cutoff value (853.4 pg/mL, 80.3%) of NT-proBNP and PMN respectively, for predicting CAL. The area under the curve (AUC) for predicting resistance to IVIG was NT-proBNP 0.712, PMN 0.802. The AUC for predicting CAL was NT-proBNP 0.739, and PMN 0.773. Conclusion Serum NT-proBNP levels and PMN percentage were significantly elevated in patients with KD with IVIG resistance and CAL. Thus, they may be useful predicting markers for IVIG resistance and development of CAL in KD patients. PMID:28194213

  2. Using the functional response of a consumer to predict biotic resistance to invasive prey.

    PubMed

    Twardochleb, Laura A; Novak, Mark; Moore, Jonathan W

    2012-06-01

    Predators sometimes provide biotic resistance against invasions by nonnative prey. Understanding and predicting the strength of biotic resistance remains a key challenge in invasion biology. A predator's functional response to nonnative prey may predict whether a predator can provide biotic resistance against nonnative prey at different prey densities. Surprisingly, functional responses have not been used to make quantitative predictions about biotic resistance. We parameterized the functional response of signal crayfish (Pacifastacus leniusculus) to invasive New Zealand mud snails (Potamopyrgus antipodarum; NZMS) and used this functional response and a simple model of NZMS population growth to predict the probability of biotic resistance at different predator and prey densities. Signal crayfish were effective predators of NZMS, consuming more than 900 NZMS per predator in a 12-h period, and Bayesian model fitting indicated their consumption rate followed a type 3 functional response to NZMS density. Based on this functional response and associated parameter uncertainty, we predict that NZMS will be able to invade new systems at low crayfish densities (< 0.2 crayfish/m2) regardless of NZMS density. At intermediate to high crayfish densities (> 0.2 crayfish/m2), we predict that low densities of NZMS will be able to establish in new communities; however, once NZMS reach a threshold density of -2000 NZMS/m2, predation by crayfish will drive negative NZMS population growth. Further, at very high densities, NZMS overwhelm predation by crayfish and invade. Thus, interacting thresholds of propagule pressure and predator densities define the probability of biotic resistance. Quantifying the shape and uncertainty of predator functional responses to nonnative prey may help predict the outcomes of invasions.

  3. Prediction of Ionizing Radiation Resistance in Bacteria Using a Multiple Instance Learning Model.

    PubMed

    Aridhi, Sabeur; Sghaier, Haïtham; Zoghlami, Manel; Maddouri, Mondher; Nguifo, Engelbert Mephu

    2016-01-01

    Ionizing-radiation-resistant bacteria (IRRB) are important in biotechnology. In this context, in silico methods of phenotypic prediction and genotype-phenotype relationship discovery are limited. In this work, we analyzed basal DNA repair proteins of most known proteome sequences of IRRB and ionizing-radiation-sensitive bacteria (IRSB) in order to learn a classifier that correctly predicts this bacterial phenotype. We formulated the problem of predicting bacterial ionizing radiation resistance (IRR) as a multiple-instance learning (MIL) problem, and we proposed a novel approach for this purpose. We provide a MIL-based prediction system that classifies a bacterium to either IRRB or IRSB. The experimental results of the proposed system are satisfactory with 91.5% of successful predictions.

  4. Mathematical Model for Predicting the Resistivity of an Electroconductive Woven Structure

    NASA Astrophysics Data System (ADS)

    Tokarska, Magdalena

    2017-01-01

    Highly conductive woven fabrics (WF) can be used as electronic components. Resistivity is an intrinsic physical property of the conductive textile materials (CTM). The McLachlan model that describes the resistivity of a two-component macroscopic composite (TCMC) subjected to a constant external electric field was proposed to predict the resistivity of fabrics. The volume fraction of voids in material, the voids dimension, and a single morphology parameter were taken into account. The resistivity of a chosen WF was determined based on the model. Verification of the received results was carried out. In the case of four samples, the verification was confirmed by the high level of prediction being in the range of 83-88%. In the case of one sample, the verification was negative (26%). This allowed one to pay attention to the influence of compactness and irregularity of the woven structure on results received using the model.

  5. Mathematical Model for Predicting the Resistivity of an Electroconductive Woven Structure

    NASA Astrophysics Data System (ADS)

    Tokarska, Magdalena

    2017-03-01

    Highly conductive woven fabrics (WF) can be used as electronic components. Resistivity is an intrinsic physical property of the conductive textile materials (CTM). The McLachlan model that describes the resistivity of a two-component macroscopic composite (TCMC) subjected to a constant external electric field was proposed to predict the resistivity of fabrics. The volume fraction of voids in material, the voids dimension, and a single morphology parameter were taken into account. The resistivity of a chosen WF was determined based on the model. Verification of the received results was carried out. In the case of four samples, the verification was confirmed by the high level of prediction being in the range of 83-88%. In the case of one sample, the verification was negative (26%). This allowed one to pay attention to the influence of compactness and irregularity of the woven structure on results received using the model.

  6. Mycobacterial Interspersed Repetitive Unit Can Predict Drug Resistance of Mycobacterium tuberculosis in China.

    PubMed

    Cheng, Xian-Feng; Jiang, Chao; Zhang, Min; Xia, Dan; Chu, Li-Li; Wen, Yu-Feng; Zhu, Ming; Jiang, Yue-Gen

    2016-01-01

    Recently, Mycobacterial Interspersed Repetitive Unit (MIRU) was supposed to be associated with drug resistance in Mycobacterium tuberculosis (M. tuberculosis), but whether the association exists actually in local strains in China was still unknown. This research was conducted to explore that association and the predictability of MIRU to drug resistance of Tuberculosis (TB). The clinical isolates were collected and the susceptibility test were conducted with Lowenstein-Jensen (LJ) medium for five anti-TB drug. Based on PCR of MIRU-VNTR (Variable Number of Tandem Repeat) genotyping, we tested the number of the repeat unite of MIRU. Then, we used logistic regression to evaluate the association between 15 MIRU and drug resistance. In addition, we explored the most suitable MIRU locus of identified MIRU loci for drug resistance by multivariate logistic regression. Of the 102 strains, one isolate was resistant to rifampicin and one isolate was resistant to streptomycin. Among these fifteen MIRU, there was a association between MIRU loci polymorphism and anti-tuberculosis drug resistance, ETRB (P = 0.03, OR = 0.19, 95% CI 0.05-0.81) and ETRC (P = 0.01, OR = 0.14, 95% CI 0.03-0.64) were negatively related to isoniazid resistance; MIRU20 (P = 0.05, OR = 2.87, 95% CI 1.01-8.12) was positively associated with ethambutol resistance; and QUB11a (P = 0.02, OR = 0.79, 95% CI 0.65-0.96) was a negative association factor of p-aminosalicylic acid resistance. Our research showed that MIRU loci may predict drug resistance of tuberculosis in China. However, the mechanism still needs further exploration.

  7. Mycobacterial Interspersed Repetitive Unit Can Predict Drug Resistance of Mycobacterium tuberculosis in China

    PubMed Central

    Cheng, Xian-feng; Jiang, Chao; Zhang, Min; Xia, Dan; Chu, Li-li; Wen, Yu-feng; Zhu, Ming; Jiang, Yue-gen

    2016-01-01

    Background: Recently, Mycobacterial Interspersed Repetitive Unit (MIRU) was supposed to be associated with drug resistance in Mycobacterium tuberculosis (M. tuberculosis), but whether the association exists actually in local strains in China was still unknown. This research was conducted to explore that association and the predictability of MIRU to drug resistance of Tuberculosis (TB). Methods: The clinical isolates were collected and the susceptibility test were conducted with Lowenstein–Jensen (LJ) medium for five anti-TB drug. Based on PCR of MIRU-VNTR (Variable Number of Tandem Repeat) genotyping, we tested the number of the repeat unite of MIRU. Then, we used logistic regression to evaluate the association between 15 MIRU and drug resistance. In addition, we explored the most suitable MIRU locus of identified MIRU loci for drug resistance by multivariate logistic regression. Results: Of the 102 strains, one isolate was resistant to rifampicin and one isolate was resistant to streptomycin. Among these fifteen MIRU, there was a association between MIRU loci polymorphism and anti-tuberculosis drug resistance, ETRB (P = 0.03, OR = 0.19, 95% CI 0.05–0.81) and ETRC (P = 0.01, OR = 0.14, 95% CI 0.03–0.64) were negatively related to isoniazid resistance; MIRU20 (P = 0.05, OR = 2.87, 95% CI 1.01–8.12) was positively associated with ethambutol resistance; and QUB11a (P = 0.02, OR = 0.79, 95% CI 0.65–0.96) was a negative association factor of p-aminosalicylic acid resistance. Conclusion: Our research showed that MIRU loci may predict drug resistance of tuberculosis in China. However, the mechanism still needs further exploration. PMID:27047485

  8. Biofilm accumulation model that predicts antibiotic resistance of Pseudomonas aeruginosa biofilms.

    PubMed Central

    Stewart, P S

    1994-01-01

    A computer model of biofilm dynamics was adapted to incorporate the activity of an antimicrobial agent on bacterial biofilm. The model was used to evaluate the plausibility of two mechanisms of biofilm antibiotic resistance by qualitative comparison with data from a well-characterized experimental system (H. Anwar, J. L. Strap, and J. W. Costerton, Antimicrob. Agents Chemother. 36:1208-1214, 1992). The two mechanisms involved either depletion of the antibiotic by reaction with biomass or physiological resistance due to reduced bacterial growth rates in the biofilm. Both mechanisms predicted the experimentally observed resistance of 7-day-old Pseudomonas aeruginosa biofilms compared with that of 2-day-old ones. A version of the model that incorporated growth rate-dependent killing predicted reduced susceptibility of thicker biofilms because oxygen was exhausted within these biofilms, leading to very slow growth in part of the biofilm. A version of the model that incorporated a destructive reaction of the antibiotic with biomass likewise accounted for the relative resistance of thicker biofilms. Resistance in this latter case was due to depletion of the antibiotic in the bulk fluid rather than development of a gradient in the antibiotic concentration within the biofilm. The modeling results predicted differences between the two cases, such as in the survival profiles within the biofilm, that could permit these resistance mechanisms to be experimentally distinguished. PMID:8067737

  9. Prediction of resistance development against drug combinations by collateral responses to component drugs

    PubMed Central

    Munck, Christian; Gumpert, Heidi K.; Nilsson Wallin, Annika I.; Wang, Harris H.; Sommer, Morten O. A.

    2015-01-01

    Resistance arises quickly during chemotherapeutic selection and is particularly problematic during long-term treatment regimens such as those for tuberculosis, HIV infections, or cancer. Although drug combination therapy reduces the evolution of drug resistance, drug pairs vary in their ability to do so. Thus, predictive models are needed to rationally design resistance-limiting therapeutic regimens. Using adaptive evolution, we studied the resistance response of the common pathogen Escherichia coli to 5 different single antibiotics and all 10 different antibiotic drug pairs. By analyzing the genomes of all evolved E. coli lineages, we identified the mutational events that drive the differences in drug resistance levels and found that the degree of resistance development against drug combinations can be understood in terms of collateral sensitivity and resistance that occurred during adaptation to the component drugs. Then, using engineered E. coli strains, we confirmed that drug resistance mutations that imposed collateral sensitivity were suppressed in a drug pair growth environment. These results provide a framework for rationally selecting drug combinations that limit resistance evolution. PMID:25391482

  10. Electrical Resistance of Ceramic Matrix Composites for Damage Detection and Life-Prediction

    NASA Technical Reports Server (NTRS)

    Smith, Craig; Morscher, Gregory N.; Xia, Zhenhai

    2008-01-01

    The electric resistance of woven SiC fiber reinforced SiC matrix composites were measured under tensile loading conditions. The results show that the electrical resistance is closely related to damage and that real-time information about the damage state can be obtained through monitoring of the resistance. Such self-sensing capability provides the possibility of on-board/in-situ damage detection or inspection of a component during "down time". The correlation of damage with appropriate failure mechanism can then be applied to accurate life prediction for high-temperature ceramic matrix composites.

  11. Beyond serial passages: new methods for predicting the emergence of resistance to novel antibiotics.

    PubMed

    Martínez, José Luis; Baquero, Fernando; Andersson, Dan I

    2011-10-01

    Market launching of a new antibiotic requires knowing in advance its benefits and possible risks, and among them how rapidly resistance will emerge and spread among bacterial pathogens. This information is not only useful from a public health point of view, but also for pharmaceutical industry, in order to reduce potential waste of resources in the development of a compound that might be discontinued at the short term because of resistance development. Most assays currently used for predicting the emergence of resistance are based on culturing the target bacteria by serial passages in the presence of increasing concentrations of antibiotics. Whereas these assays may be valuable for identifying mutations that might cause resistance, they are not useful to establish how fast resistance might appear, neither to address the risk of spread of resistance genes by horizontal gene transfer. In this article, we review recent information pertinent for a more accurate prediction on the emergence and dispersal of antibiotic resistance. Copyright © 2011 Elsevier Ltd. All rights reserved.

  12. Predicting and preventing antimicrobial resistance utilizing pharmacodynamics: Part I gram positive bacteria.

    PubMed

    Linder, Kristin E; Nicolau, David P; Nailor, Michael D

    2016-01-01

    Antimicrobial resistance is a potentially inevitable consequence of widespread use of antibiotics in the healthcare system. An enhanced understanding of pharmacodynamic (PD) targets that prevent antimicrobial resistance development will improve currently availably therapies and help to guide future drug development strategies. Current in vitro methods to predict bacterial resistance to antimicrobials consist of serial dilution experiments, determination of the mutant prevention concentration (MPC), mutant selection window (MSW), and human simulated pharmacodynamics studies. Clinical trial data and real -world surveillance studies can help validate or disprove in vitro modeling. This review will discuss methods of predicting development of resistance and how the use of pharmacodynamics can reduce or eliminate the emergence of resistance among Staphylococcus aureus, Streptococcus pneumoniae, and Enterococcus species. Pharmacodynamic targets can be used successfully to guide antimicrobial therapy to prevent resistance development. Currently, PD targets do not take into consideration horizontal resistance gene transfer and various factors may lead to different PD targets based on sites of infection. Further research is necessary to guide future drug development strategies and optimize new drug therapies.

  13. Anhedonia Predicts Poorer Recovery among Youth with Selective Serotonin Reuptake Inhibitor-Treatment Resistant Depression

    PubMed Central

    McMakin, Dana L.; Olino, Thomas M.; Porta, Giovanna; Dietz, Laura J.; Emslie, Graham; Clarke, Gregory; Wagner, Karen Dineen; Asarnow, Joan R.; Ryan, Neal D.; Birmaher, Boris; Shamseddeen, Wael; Mayes, Taryn; Kennard, Betsy; Spirito, Anthony; Keller, Martin; Lynch, Frances L.; Dickerson, John F.; Brent, David A.

    2012-01-01

    Objective To identify symptom dimensions of depression that predict recovery among SSRI-treatment resistant adolescents undergoing second-step treatment. Method The Treatment of Resistant Depression in Adolescents (TORDIA) trial included 334 SSRI-treatment resistant youth randomized to a medication switch, or a medication switch plus CBT. This study examined five established symptom dimensions (Child Depression Rating Scale-Revised) at baseline as they predicted recovery over 24 weeks of acute and continuation treatment. The two indices of recovery that were evaluated were time to remission and number of depression-free days. Results Multivariate analyses examining all five depression symptom dimensions simultaneously indicated that Anhedonia was the only dimension to predict a longer time to remission, and also the only dimension to predict fewer depression-free days. In addition, when Anhedonia and CDRS-total score were evaluated simultaneously, Anhedonia continued to uniquely predict longer time to remission and fewer depression-free days. Conclusions Anhedonia may represent an important negative prognostic indicator among treatment resistant depressed adolescents. Further research is needed to elucidate neurobehavioral underpinnings of anhedonia, and to test treatments that target anhedonia in the context of overall treatment of depression. PMID:22449646

  14. Modeling bulk canopy resistance from climatic variables for predicting hourly evapotranspiration of maize and buckwheat

    NASA Astrophysics Data System (ADS)

    Yan, Haofang; Shi, Haibin; Hiroki, Oue; Zhang, Chuan; Xue, Zhu; Cai, Bin; Wang, Guoqing

    2015-06-01

    This study presents models for predicting hourly canopy resistance ( r c) and evapotranspiration (ETc) based on Penman-Monteith approach. The micrometeorological data and ET c were observed during maize and buckwheat growing seasons in 2006 and 2009 in China and Japan, respectively. The proposed models of r c were developed by a climatic resistance ( r *) that depends on climatic variables. Non-linear relationships between r c and r * were applied. The measured ETc using Bowen ratio energy balance method was applied for model validation. The statistical analysis showed that there were no significant differences between predicted ETc by proposed models and measured ETc for both maize and buckwheat crops. The model for predicting ETc at maize field showed better performance than predicting ETc at buckwheat field, the coefficients of determination were 0.92 and 0.84, respectively. The study provided an easy way for the application of Penman-Monteith equation with only general available meteorological database.

  15. Prediction of ship resistance in head waves using RANS based solver

    NASA Astrophysics Data System (ADS)

    Islam, Hafizul; Akimoto, Hiromichi

    2016-07-01

    Maneuverability prediction of ships using CFD has gained high popularity over the years because of its improving accuracy and economics. This paper discusses the estimation of calm water and added resistance properties of a KVLCC2 model using a light and economical RaNS based solver, called SHIP_Motion. The solver solves overset structured mesh using finite volume method. In the calm water test, total drag coefficient, sinkage and trim values were predicted together with mesh dependency analysis and compared with experimental data. For added resistance in head sea, short wave cases were simulated and compared with experimental and other simulation data. Overall the results were well predicted and showed good agreement with comparative data. The paper concludes that it is well possible to predict ship maneuverability characteristics using the present solver, with reasonable accuracy utilizing minimum computational resources and within acceptable time.

  16. Ecology of SO2 resistance : IV. Predicting metabolic responses of fumigated shrubs and trees.

    PubMed

    Winner, W E; Koch, G W; Mooney, H A

    1982-01-01

    10 broadleafed trees and shrubs native to the mediterranean climactic zone in California were surveyed for their photosynthetic and stomatal responses to SO2. These species ranged from drought deciduous to evergreen and had diverse responses to SO2. These results suggest an approach for predicting SO2 resistances of plants.We found that conductance values of plants in SO2-free air can be used to estimate the quantity of SO2 which plants absorb. These estimates are based on conductance values for plants in non-limiting environmental conditions. SO2 absorption quantities are then used to predict relative photosynthesis following the fumigation. Thus, relative photosynthesis of plants following fumigation can be predicted on the basis of conductance in SO2-free air. This approach to predicting SO2 resistances of plants includes analysis of their stomatal responses to fumigation, their characteristics of SO2 adsorption and absorption, and their change in photosynthesis resulting from SO2 stress.

  17. Excess positional mutual information predicts both local and allosteric mutations affecting beta lactamase drug resistance.

    PubMed

    Cortina, George A; Kasson, Peter M

    2016-11-15

    Bacterial resistance to antibiotics, particularly plasmid-encoded resistance to beta lactam drugs, poses an increasing threat to human health. Point mutations to beta-lactamase enzymes can greatly alter the level of resistance conferred, but predicting the effects of such mutations has been challenging due to the large combinatorial space involved and the subtle relationships of distant residues to catalytic function. Therefore we desire an information-theoretic metric to sensitively and robustly detect both local and distant residues that affect substrate conformation and catalytic activity. Here, we report the use of positional mutual information in multiple microsecond-length molecular dynamics (MD) simulations to predict residues linked to catalytic activity of the CTX-M9 beta lactamase. We find that motions of the bound drug are relatively isolated from motions of the protein as a whole, which we interpret in the context of prior theories of catalysis. In order to robustly identify residues that are weakly coupled to drug motions but nonetheless affect catalysis, we utilize an excess mutual information metric. We predict 31 such residues for the cephalosporin antibiotic cefotaxime. Nine of these have previously been tested experimentally, and all decrease both enzyme rate constants and empirical drug resistance. We prospectively validate our method by testing eight high-scoring mutations and eight low-scoring controls in bacteria. Six of eight predicted mutations decrease cefotaxime resistance greater than 2-fold, while only one control shows such an effect. The ability to prospectively predict new variants affecting bacterial drug resistance is of great interest to clinical and epidemiological surveillance. Excess mutual information code is available at https://github.com/kassonlab/positionalmi CONTACT: kasson@virginia.edu. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  18. A model for predicting the dynamic fracture and impact fracture resistance of tough thermoplastics

    SciTech Connect

    Leevers, P.S.; Greenshields, C.J.

    1995-11-01

    Design against rapid crack propagation (RCP) in a pipeline requires data for the dynamic fracture resistance of its material, but most of the data available is for resistance to impact crack initiation. These properties are not simply related, and in touch thermoplastics impact fracture resistance is sensitive to impact speed and specimen geometry as well as to temperature tests. Here, a simple mechanism of crack-tip cohesive zone failure is applied to develop models of both failure modes. Impact and dynamic fracture properties of two pipe grade polyethylenes are correctly predicted from more basic properties; and their use in predicting the critical pressure for RCP failure of notched, water pressurized pipe is compared. The model supports the view that the use of impact fracture test data for quantitative design against RCP is intrinsically unsound.

  19. Prediction of clothing thermal insulation and moisture vapour resistance of the clothed body walking in wind.

    PubMed

    Qian, Xiaoming; Fan, Jintu

    2006-11-01

    Clothing thermal insulation and moisture vapour resistance are the two most important parameters in thermal environmental engineering, functional clothing design and end use of clothing ensembles. In this study, clothing thermal insulation and moisture vapour resistance of various types of clothing ensembles were measured using the walking-able sweating manikin, Walter, under various environmental conditions and walking speeds. Based on an extensive experimental investigation and an improved understanding of the effects of body activities and environmental conditions, a simple but effective direct regression model has been established, for predicting the clothing thermal insulation and moisture vapour resistance under wind and walking motion, from those when the manikin was standing in still air. The model has been validated by using experimental data reported in the previous literature. It has shown that the new models have advantages and provide very accurate prediction.

  20. Experimental results on rock resistivity and its applications in monitoring and predicting natural disasters

    NASA Astrophysics Data System (ADS)

    Zhou, Jianguo; Zhu, Tao; Tang, Baolin

    2017-04-01

    There have been many earthquakes occurring in Chinese Mainland. These earthquakes, especially large earthquakes, often cause immeasurable loss. For instance, the 2008 Wenchuan Ms8.0 earthquake killed 70, 000 people and caused 17, 000 people missing. It is well known that this earthquake was not predicted. Why? Were there no precursors? After analyzing the geo-electrical resistivity recording at Chengdu station which is only about 36 km to the epicenter, we find that resistivity had changed abnormally very significantly along NE direction but no outstanding abnormal changes had been observed along NW direction before the earthquake. Perhaps this non-consistent changes result in that this earthquake was not predicted. However, in another standpoint, can another observation way be found to supplement the current geo-electrical resistivity observation in Chinese Mainland in order to improve the probability of catching the precursor? This motivates us to conduct experiments in lab and field. Apparent resistivity data are acquired along three common-midpoint measuring lines during the fixed-rate uniaxial compression on two sets of dry man-made samples and a Magnetite sample. We construct the relative resistivity change images (RRCIs). Our results indicate that all RRCIs show a trending change with stress: with the increase of stress, the resistivity-decreased region (RDR) in the RRCIs shrinks/expands, while the resistivity-increased region (RIR) expands/shrinks gradually, which is in agreement with the field experimental results of earthquake monitoring (Feng et al., 2001). Our results encourage us to conclude that the trending changes in RRCI with stress could probably become a useful indicator in monitoring and predicting earthquakes, volcanic eruptions and large-scale geologic movements. This work is supported by National Natural Science Foundation of China (NSFC, Grant 41574083).

  1. A prediction method of ice breaking resistance using a multiple regression analysis

    NASA Astrophysics Data System (ADS)

    Cho, Seong-Rak; Lee, Sungsu

    2015-07-01

    The two most important tasks of icebreakers are first to secure a sailing route by breaking the thick sea ice and second to sail efficiently herself for purposes of exploration and transportation in the polar seas. The resistance of icebreakers is a priority factor at the preliminary design stage; not only must their sailing efficiency be satisfied, but the design of the propulsion system will be directly affected. Therefore, the performance of icebreakers must be accurately calculated and evaluated through the use of model tests in an ice tank before construction starts. In this paper, a new procedure is developed, based on model tests, to estimate a ship's ice breaking resistance during continuous ice-breaking in ice. Some of the factors associated with crushing failures are systematically considered in order to correctly estimate her ice-breaking resistance. This study is intended to contribute to the improvement of the techniques for ice resistance prediction with ice breaking ships.

  2. Low MITF/AXL ratio predicts early resistance to multiple targeted drugs in melanoma

    PubMed Central

    Müller, Judith; Krijgsman, Oscar; Tsoi, Jennifer; Robert, Lidia; Hugo, Willy; Song, Chunying; Kong, Xiangju; Possik, Patricia A.; Cornelissen-Steijger, Paulien D.M.; Foppen, Marnix H. Geukes; Kemper, Kristel; Goding, Colin R.; McDermott, Ultan; Blank, Christian; Haanen, John; Graeber, Thomas G.; Ribas, Antoni; Lo, Roger S.; Peeper, Daniel S.

    2015-01-01

    Increased expression of the Microphthalmia-associated transcription factor (MITF) contributes to melanoma progression and resistance to BRAF pathway inhibition. Here we show that the lack of MITF is associated with more severe resistance to a range of inhibitors, while its presence is required for robust drug responses. Both in primary and acquired resistance, MITF levels inversely correlate with the expression of several activated receptor tyrosine kinases, most frequently AXL. The MITF-low/AXL-high/drug-resistance phenotype is common among mutant BRAF and NRAS melanoma cell lines. The dichotomous behaviour of MITF in drug response is corroborated in vemurafenib-resistant biopsies, including MITF-high and -low clones in a relapsed patient. Furthermore, drug cocktails containing AXL inhibitor enhance melanoma cell elimination by BRAF or ERK inhibition. Our results demonstrate that a low MITF/AXL ratio predicts early resistance to multiple targeted drugs, and warrant clinical validation of AXL inhibitors to combat resistance of BRAF and NRAS mutant MITF-low melanomas. PMID:25502142

  3. An Analytical Model for Predicting Stab Resistance of Flexible Woven Composites

    NASA Astrophysics Data System (ADS)

    Hou, Limin; Sun, Baozhong; Gu, Bohong

    2013-08-01

    Flexible woven composites have been widely used in geotextiles and light weight building structures. The stab resistance behavior of the flexible woven composite is an important factor for the application design. This paper reports an analytical model for predicting stab resistance of flexible woven composites under perpendicular stab with a blunt steel penetrator. The analytical model was established based on the microstructure and the deformation shape of the flexible woven composite under normal penetration. During the quasi-static stab penetration, the strain energies of warp and weft yarns and resins have been calculated. The stab resistance was calculated from the strain energies of the flexible woven composite. Furthermore, the contributions of the warp and weft yarns, resins to the stab resistance have been analyzed. It was found the three constituents have near the same contribution to the stab resistance. The higher value of weaving density, strength of yarns and especially the higher strength coating resins will lead the higher stab resistance. With the analytical model, the stab resistance would be expected to be designed in an efficient way with an acceptable precision.

  4. Predicting survival time for metastatic castration resistant prostate cancer: An iterative imputation approach

    PubMed Central

    Deng, Detian; Du, Yu; Ji, Zhicheng; Rao, Karthik; Wu, Zhenke; Zhu, Yuxin; Coley, R. Yates

    2016-01-01

    In this paper, we present our winning method for survival time prediction in the 2015 Prostate Cancer DREAM Challenge, a recent crowdsourced competition focused on risk and survival time predictions for patients with metastatic castration-resistant prostate cancer (mCRPC). We are interested in using a patient's covariates to predict his or her time until death after initiating standard therapy. We propose an iterative algorithm to multiply impute right-censored survival times and use ensemble learning methods to characterize the dependence of these imputed survival times on possibly many covariates. We show that by iterating over imputation and ensemble learning steps, we guide imputation with patient covariates and, subsequently, optimize the accuracy of survival time prediction. This method is generally applicable to time-to-event prediction problems in the presence of right-censoring. We demonstrate the proposed method's performance with training and validation results from the DREAM Challenge and compare its accuracy with existing methods. PMID:28299176

  5. CTMP, a predictive biomarker for trastuzumab resistance in HER2-enriched breast cancer patient

    PubMed Central

    Chen, Yu-Chia; Li, Hao-Yi; Liang, Jui-Lin; Ger, Luo-Ping; Chang, Hong-Tai; Hsiao, Michael; Calkins, Marcus J.; Cheng, Hui-Chuan; Chuang, Jiin-Haur; Lu, Pei-Jung

    2017-01-01

    Trastuzumab is regarded as the primary therapy for patients with HER2-enriched breast cancer, but the pathological complete response for advanced cases is less than 30%. The underlying mechanism of trastuzumab resistance remains unclear and there are currently no conclusive biomarkers for patient response to trastuzumab. Identifying predictive biomarkers for trastuzumab response may allow treatments to be individually tailored and optimized multi-target therapies may be developed. CTMP activates AKT signaling in breast cancer and over-activation of AKT has been reported to contribute to trastuzumab resistance. In this study, we examined samples from 369 patients to investigate the correlation between CTMP expression level and patient outcome. Elevated CTMP expression was correlated with adverse outcomes in HER2-enriched patients including overall and disease-free survival as well as trastuzumab resistance. Ectopic expression of varying levels of CTMP in SkBR3 cells dose-dependently attenuated trastuzumab-mediated growth inhibition through AKT activation. In addition, inhibition of AKT signaling by AKT inhibitor IV and Rapamycin reversed CTMP-mediated trastuzumab resistance. In clinical samples, the high expression of CTMP was showed in trastuzumab non-responders and positively correlated with AKT activity. Taken together, we demonstrated that CTMP promotes AKT activation resulting in trastuzumab resistance in patients with HER2-enriched breast cancer. High CTMP expression not only predicted poor prognosis, but may also predict resistance to trastuzumab in HER2-enriched patients. Therefore, CTMP expression may be considered as a prognostic biomarker in HER2-enriched breast cancer and high expression may indicate a utility for AKT-inhibition in these patients. PMID:27447863

  6. Structure-based methods for predicting target mutation-induced drug resistance and rational drug design to overcome the problem.

    PubMed

    Hao, Ge-Fei; Yang, Guang-Fu; Zhan, Chang-Guo

    2012-10-01

    Drug resistance has become one of the biggest challenges in drug discovery and/or development and has attracted great research interests worldwide. During the past decade, computational strategies have been developed to predict target mutation-induced drug resistance. Meanwhile, various molecular design strategies, including targeting protein backbone, targeting highly conserved residues and dual/multiple targeting, have been used to design novel inhibitors for combating the drug resistance. In this article we review recent advances in development of computational methods for target mutation-induced drug resistance prediction and strategies for rational design of novel inhibitors that could be effective against the possible drug-resistant mutants of the target.

  7. Nucleotide substitution patterns can predict the requirements for drug-resistance of HIV-1 proteins.

    PubMed

    Keulen, W; Boucher, C; Berkhout, B

    1996-06-01

    The enzyme reverse transcriptase (RT) plays a fundamental role in the replication of the human immunodeficiency virus type 1 (HIV-1) and several antiviral agents that target this key enzyme have been developed. Unfortunately, treatment of patients with RT inhibitors results in the appearance of drug-resistant variants with specific mutations in the RT protein. We hypothesized that if "difficult' resistance mutations (e.g. transversions/double-hits) are consistently observed at certain positions, it is likely that "easier' nucleotide substitutions (transitions/single-hits) at that codon do not result in a drug-resistant and/or active RT enzyme. In this study, we examined codon changes involved in RT drug resistance against nucleoside and non-nucleoside inhibitors and listed all easier substitutions, which apparently were not selected, either due to reduced enzyme RT activity or lack of drug resistance. These predictions on the requirements for resistance were confirmed by published mutational data on RT variants. We also propose that differences in mutation type can explain the order of appearance of substitutions in case multiple amino acid changes are required for optimal fitness. Differences in mutation pattern have been reported for drug-resistant HIV-1 variants selected in tissue culture compared with variants found in treated patients. In contrast to the in vivo situation, a relatively small population size is handled in in vitro tissue culture systems and this may limit the chances of creating a resistance mutation. Indeed, inspection of the codon changes indicates that the in vitro culture system is more strongly biased towards the relatively easy nucleotide substitutions. These results suggest that the nucleotide substitution pattern can provide important information on RT drug resistance.

  8. pncA gene expression and prediction factors on pyrazinamide resistance in Mycobacterium tuberculosis

    PubMed Central

    Sheen, Patricia; Lozano, Katherine; Gilman, Robert H.; Valencia, Hugo J.; Loli, Sebastian; Fuentes, Patricia; Grandjean, Louis; Zimic, Mirko

    2013-01-01

    Summary Background Mutations in the pyrazinamidase (PZAse) coding gene, pncA, have been considered as the main cause of pyrazinamide (PZA) resistance in Mycobacterium tuberculosis. However, recent studies suggest there is no single mechanism of resistance to PZA. The pyrazinoic acid (POA) efflux rate is the basis of the PZA susceptibility Wayne test, and its quantitative measurement has been found to be a highly sensitive and specific predictor of PZA resistance. Based on biological considerations, the POA efflux rate is directly determined by the PZAse activity, the level of pncA expression, and the efficiency of the POA efflux pump system. Objective This study analyzes the individual and the adjusted contribution of PZAse activity, pncA expression and POA efflux rate on PZA resistance. Methods Thirty M. tuberculosis strains with known microbiological PZA susceptibility or resistance were analyzed. For each strain, PZAse was recombinantly produced and its enzymatic activity measured. The level of pncA mRNA was estimated by quantitative RT-PCR, and the POA efflux rate was determined. Mutations in the pncA promoter were detected by DNA sequencing. All factors were evaluated by multiple regression analysis to determine their adjusted effects on the level of PZA resistance. Findings Low level of pncA expression associated to mutations in the pncA promoter region was observed in pncA wild type resistant strains. POA efflux rate was the best predictor after adjusting for the other factors, followed by PZAse activity. These results suggest that tests which rely on pncA mutations or PZAse activity are likely to be less predictive of real PZA resistance than tests which measure the rate of POA efflux. This should be further analyzed in light of the development of alternate assays to determine PZA resistance. PMID:23867321

  9. pncA gene expression and prediction factors on pyrazinamide resistance in Mycobacterium tuberculosis.

    PubMed

    Sheen, Patricia; Lozano, Katherine; Gilman, Robert H; Valencia, Hugo J; Loli, Sebastian; Fuentes, Patricia; Grandjean, Louis; Zimic, Mirko

    2013-09-01

    Mutations in the pyrazinamidase (PZAse) coding gene, pncA, have been considered as the main cause of pyrazinamide (PZA) resistance in Mycobacterium tuberculosis. However, recent studies suggest there is no single mechanism of resistance to PZA. The pyrazinoic acid (POA) efflux rate is the basis of the PZA susceptibility Wayne test, and its quantitative measurement has been found to be a highly sensitive and specific predictor of PZA resistance. Based on biological considerations, the POA efflux rate is directly determined by the PZAse activity, the level of pncA expression, and the efficiency of the POA efflux pump system. This study analyzes the individual and the adjusted contribution of PZAse activity, pncA expression and POA efflux rate on PZA resistance. Thirty M. tuberculosis strains with known microbiological PZA susceptibility or resistance were analyzed. For each strain, PZAse was recombinantly produced and its enzymatic activity measured. The level of pncA mRNA was estimated by quantitative RT-PCR, and the POA efflux rate was determined. Mutations in the pncA promoter were detected by DNA sequencing. All factors were evaluated by multiple regression analysis to determine their adjusted effects on the level of PZA resistance. Low level of pncA expression associated to mutations in the pncA promoter region was observed in pncA wild type resistant strains. POA efflux rate was the best predictor after adjusting for the other factors, followed by PZAse activity. These results suggest that tests which rely on pncA mutations or PZAse activity are likely to be less predictive of real PZA resistance than tests which measure the rate of POA efflux. This should be further analyzed in light of the development of alternate assays to determine PZA resistance.

  10. Using drug exposure for predicting drug resistance – A data-driven genotypic interpretation tool

    PubMed Central

    Pironti, Alejandro; Pfeifer, Nico; Walter, Hauke; Jensen, Björn-Erik O.; Zazzi, Maurizio; Gomes, Perpétua; Kaiser, Rolf; Lengauer, Thomas

    2017-01-01

    Antiretroviral treatment history and past HIV-1 genotypes have been shown to be useful predictors for the success of antiretroviral therapy. However, this information may be unavailable or inaccurate, particularly for patients with multiple treatment lines often attending different clinics. We trained statistical models for predicting drug exposure from current HIV-1 genotype. These models were trained on 63,742 HIV-1 nucleotide sequences derived from patients with known therapeutic history, and on 6,836 genotype-phenotype pairs (GPPs). The mean performance regarding prediction of drug exposure on two test sets was 0.78 and 0.76 (ROC-AUC), respectively. The mean correlation to phenotypic resistance in GPPs was 0.51 (PhenoSense) and 0.46 (Antivirogram). Performance on prediction of therapy-success on two test sets based on genetic susceptibility scores was 0.71 and 0.63 (ROC-AUC), respectively. Compared to geno2pheno[resistance], our novel models display a similar or superior performance. Our models are freely available on the internet via www.geno2pheno.org. They can be used for inferring which drug compounds have previously been used by an HIV-1-infected patient, for predicting drug resistance, and for selecting an optimal antiretroviral therapy. Our data-driven models can be periodically retrained without expert intervention as clinical HIV-1 databases are updated and therefore reduce our dependency on hard-to-obtain GPPs. PMID:28394945

  11. Using drug exposure for predicting drug resistance - A data-driven genotypic interpretation tool.

    PubMed

    Pironti, Alejandro; Pfeifer, Nico; Walter, Hauke; Jensen, Björn-Erik O; Zazzi, Maurizio; Gomes, Perpétua; Kaiser, Rolf; Lengauer, Thomas

    2017-01-01

    Antiretroviral treatment history and past HIV-1 genotypes have been shown to be useful predictors for the success of antiretroviral therapy. However, this information may be unavailable or inaccurate, particularly for patients with multiple treatment lines often attending different clinics. We trained statistical models for predicting drug exposure from current HIV-1 genotype. These models were trained on 63,742 HIV-1 nucleotide sequences derived from patients with known therapeutic history, and on 6,836 genotype-phenotype pairs (GPPs). The mean performance regarding prediction of drug exposure on two test sets was 0.78 and 0.76 (ROC-AUC), respectively. The mean correlation to phenotypic resistance in GPPs was 0.51 (PhenoSense) and 0.46 (Antivirogram). Performance on prediction of therapy-success on two test sets based on genetic susceptibility scores was 0.71 and 0.63 (ROC-AUC), respectively. Compared to geno2pheno[resistance], our novel models display a similar or superior performance. Our models are freely available on the internet via www.geno2pheno.org. They can be used for inferring which drug compounds have previously been used by an HIV-1-infected patient, for predicting drug resistance, and for selecting an optimal antiretroviral therapy. Our data-driven models can be periodically retrained without expert intervention as clinical HIV-1 databases are updated and therefore reduce our dependency on hard-to-obtain GPPs.

  12. Predicting functional and regulatory divergence of a drug resistance transporter gene in the human malaria parasite.

    PubMed

    Siwo, Geoffrey H; Tan, Asako; Button-Simons, Katrina A; Samarakoon, Upeka; Checkley, Lisa A; Pinapati, Richard S; Ferdig, Michael T

    2015-02-22

    The paradigm of resistance evolution to chemotherapeutic agents is that a key coding mutation in a specific gene drives resistance to a particular drug. In the case of resistance to the anti-malarial drug chloroquine (CQ), a specific mutation in the transporter pfcrt is associated with resistance. Here, we apply a series of analytical steps to gene expression data from our lab and leverage 3 independent datasets to identify pfcrt-interacting genes. Resulting networks provide insights into pfcrt's biological functions and regulation, as well as the divergent phenotypic effects of its allelic variants in different genetic backgrounds. To identify pfcrt-interacting genes, we analyze pfcrt co-expression networks in 2 phenotypic states - CQ-resistant (CQR) and CQ-sensitive (CQS) recombinant progeny clones - using a computational approach that prioritizes gene interactions into functional and regulatory relationships. For both phenotypic states, pfcrt co-expressed gene sets are associated with hemoglobin metabolism, consistent with CQ's expected mode of action. To predict the drivers of co-expression divergence, we integrate topological relationships in the co-expression networks with available high confidence protein-protein interaction data. This analysis identifies 3 transcriptional regulators from the ApiAP2 family and histone acetylation as potential mediators of these divergences. We validate the predicted divergences in DNA mismatch repair and histone acetylation by measuring the effects of small molecule inhibitors in recombinant progeny clones combined with quantitative trait locus (QTL) mapping. This work demonstrates the utility of differential co-expression viewed in a network framework to uncover functional and regulatory divergence in phenotypically distinct parasites. pfcrt-associated co-expression in the CQ resistant progeny highlights CQR-specific gene relationships and possible targeted intervention strategies. The approaches outlined here can be

  13. Random lopinavir concentrations predict resistance on lopinavir-based antiretroviral therapy

    PubMed Central

    Court, Richard; Gordon, Michelle; Cohen, Karen; Stewart, Annemie; Gosnell, Bernadett; Wiesner, Lubbe; Maartens, Gary

    2016-01-01

    Considering that most patients who experience virological failure (VF) on lopinavir-based antiretroviral therapy (ART) fail due to poor adherence rather than resistance, an objective adherence measure could limit costs by rationalising the use of genotype antiretroviral resistance testing (GART) in countries with access to third-line ART. A cross-sectional study was conducted in a resource-limited setting at two large clinics in Kwazulu-Natal, South Africa, in patients experiencing VF (HIV-RNA > 1000 copies/mL) on lopinavir-based ART who had undergone GART. Associations between major protease inhibitor (PI) resistance mutations and random plasma lopinavir concentrations were explored. A total of 134 patients, including 31 children, were included in the analysis. The prevalence of patients with major PI resistance mutations was 20.9% (n = 28). A random lopinavir concentration above the recommended minimum trough of 1 µg/mL [adjusted odds ratio (aOR) = 5.81, 95% confidence interval (CI) 2.04–16.50; P = 0.001] and male sex (aOR = 3.19, 95% CI 1.22–8.33; P = 0.018) were predictive of the presence of at least one major PI resistance mutation. Random lopinavir concentrations of <1 µg/mL had a negative predictive value of 91% for major PI resistance mutations. Random lopinavir concentrations are strongly associated with the presence of major PI resistance mutations. Access to costly GART in patients experiencing VF on second-line ART could be restricted to patients with lopinavir concentrations above the recommended minimum trough of 1 µg/mL or, in areas where GART is unavailable, be used as a criterion to empirically switch to third-line ART. PMID:27345268

  14. Prediction of Bacillus weihenstephanensis acid resistance: the use of gene expression patterns to select potential biomarkers.

    PubMed

    Desriac, N; Postollec, F; Coroller, L; Sohier, D; Abee, T; den Besten, H M W

    2013-10-01

    Exposure to mild stress conditions can activate stress adaptation mechanisms and provide cross-resistance towards otherwise lethal stresses. In this study, an approach was followed to select molecular biomarkers (quantitative gene expressions) to predict induced acid resistance after exposure to various mild stresses, i.e. exposure to sublethal concentrations of salt, acid and hydrogen peroxide during 5 min to 60 min. Gene expression patterns of unstressed and mildly stressed cells of Bacillus weihenstephanensis were correlated to their acid resistance (3D value) which was estimated after exposure to lethal acid conditions. Among the twenty-nine candidate biomarkers, 12 genes showed expression patterns that were correlated either linearly or non-linearly to acid resistance, while for the 17 other genes the correlation remains to be determined. The selected genes represented two types of biomarkers, (i) four direct biomarker genes (lexA, spxA, narL, bkdR) for which expression patterns upon mild stress treatment were linearly correlated to induced acid resistance; and (ii) nine long-acting biomarker genes (spxA, BcerKBAB4_0325, katA, trxB, codY, lacI, BcerKBAB4_1716, BcerKBAB4_2108, relA) which were transiently up-regulated during mild stress exposure and correlated to increased acid resistance over time. Our results highlight that mild stress induced transcripts can be linearly or non-linearly correlated to induced acid resistance and both approaches can be used to find relevant biomarkers. This quantitative and systematic approach opens avenues to select cellular biomarkers that could be incremented in mathematical models to predict microbial behaviour.

  15. Predicting antiretroviral drug resistance from the latest or the cumulative genotype.

    PubMed

    Garcia, Federico; Alvarez, Marta; Fox, Zoe; Garcia-Diaz, Ana; Guillot, Vicente; Johnson, Margaret; Chueca, Natalia; Phillips, Andrew; Hernández-Quero, José; Geretti, Anna Maria

    2011-01-01

    This study evaluates the added benefit when estimating antiretroviral drug resistance of combining all available resistance test results in a cumulative genotype relative to using the latest genotype alone. The prevalence of resistance and genotypic sensitivity scores (GSS) predicted by the latest and the cumulative genotype, together with virological outcomes after the latest genotype, were measured in treatment-experienced patients who underwent ≥2 resistance tests in 1999-2008. Comparing the latest with the cumulative genotype in 227 patients, 4 (1.7%) versus 0 (0.0%) showed no major resistance mutations, whereas 74 (32.6%) versus 46 (20.3%), 88 (38.8%) versus 76 (33.5%) and 61 (26.9%) versus 105 (46.3%) showed single-class, dual-class and triple-class resistance mutations, respectively. The median (IQR) number of fully or partially active drugs was 6 (5-6) versus 5 (4-6) for the nucleoside/nucleotide reverse transcriptase inhibitors, 3 (1-3) versus 1 (1-3) for the non-nucleoside reverse transcriptase inhibitors and 7 (7-7) versus 7 (7-7) for the protease inhibitors, respectively. Among 163 patients who started a new regimen after the latest genotype, both the latest and the cumulative GSS were predictive of early (≤24 weeks) virological responses. The GSS decreased by median 1 unit (IQR 0.5-1.0) in the cumulative genotype and larger differences relative to the latest genotype corresponded to smaller decreases in viral load. The cumulative genotype offers a more comprehensive evaluation of the burden of resistance. This approach can guide small but appreciable improvements in the selection of antiretroviral regimens for treatment-experienced patients.

  16. Ecological resistance surfaces predict fine-scale genetic differentiation in a terrestrial woodland salamander.

    PubMed

    Peterman, William E; Connette, Grant M; Semlitsch, Raymond D; Eggert, Lori S

    2014-05-01

    Landscape genetics has seen tremendous advances since its introduction, but parameterization and optimization of resistance surfaces still poses significant challenges. Despite increased availability and resolution of spatial data, few studies have integrated empirical data to directly represent ecological processes as genetic resistance surfaces. In our study, we determine the landscape and ecological factors affecting gene flow in the western slimy salamander (Plethodon albagula). We used field data to derive resistance surfaces representing salamander abundance and rate of water loss through combinations of canopy cover, topographic wetness, topographic position, solar exposure and distance from ravine. These ecologically explicit composite surfaces directly represent an ecological process or physiological limitation of our organism. Using generalized linear mixed-effects models, we optimized resistance surfaces using a nonlinear optimization algorithm to minimize model AIC. We found clear support for the resistance surface representing the rate of water loss experienced by adult salamanders in the summer. Resistance was lowest at intermediate levels of water loss and higher when the rate of water loss was predicted to be low or high. This pattern may arise from the compensatory movement behaviour of salamanders through suboptimal habitat, but also reflects the physiological limitations of salamanders and their sensitivity to extreme environmental conditions. Our study demonstrates that composite representations of ecologically explicit processes can provide novel insight and can better explain genetic differentiation than ecologically implicit landscape resistance surfaces. Additionally, our study underscores the fact that spatial estimates of habitat suitability or abundance may not serve as adequate proxies for describing gene flow, as predicted abundance was a poor predictor of genetic differentiation.

  17. Thermal boundary resistance predictions from molecular dynamics simulations and theoretical calculations

    NASA Astrophysics Data System (ADS)

    Landry, E. S.; McGaughey, A. J. H.

    2009-10-01

    The accuracies of two theoretical expressions for thermal boundary resistance are assessed by comparing their predictions to independent predictions from molecular dynamics (MD) simulations. In one expression (RE) , the phonon distributions are assumed to follow the equilibrium, Bose-Einstein distribution, while in the other expression (RNE) , the phonons are assumed to have nonequilibrium, but bulk-like distributions. The phonon properties are obtained using lattice dynamics-based methods, which assume that the phonon interface scattering is specular and elastic. We consider (i) a symmetrically strained Si/Ge interface, and (ii) a series of interfaces between Si and “heavy-Si,” which differs from Si only in mass. All of the interfaces are perfect, justifying the assumption of specular scattering. The MD-predicted Si/Ge thermal boundary resistance is temperature independent and equal to 3.1×10-9m2-K/W below a temperature of ˜500K , indicating that the phonon scattering is elastic, as required for the validity of the theoretical calculations. At higher-temperatures, the MD-predicted Si/Ge thermal boundary resistance decreases with increasing temperature, a trend we attribute to inelastic scattering. For the Si/Ge interface and the Si/heavy-Si interfaces with mass ratios greater than two, RE is in good agreement with the corresponding MD-predicted values at temperatures where the interface scattering is elastic. When applied to a system containing no interface, RE is erroneously nonzero due to the assumption of equilibrium phonon distributions on either side of the interface. While RNE is zero for a system containing no interface, it is 40%-60% less than the corresponding MD-predicted values for the Si/Ge interface and the Si/heavy-Si interfaces at temperatures where the interface scattering is elastic. This inaccuracy is attributed to the assumption of bulk-like phonon distributions on either side of the interface.

  18. A mathematical model for predicting the development of bacterial resistance based on the relationship between the level of antimicrobial resistance and the volume of antibiotic consumption.

    PubMed

    Arepyeva, M A; Kolbin, A S; Sidorenko, S V; Lawson, R; Kurylev, A A; Balykina, Yu E; Mukhina, N V; Spiridonova, A A

    2017-03-01

    Infections that are inadequately treated owing to acquired bacterial resistance are a leading cause of mortality. Rates of multidrug-resistant bacteria are rising, resulting in increased antibiotic failures and worsening patient outcomes. Mathematical modelling makes it possible to predict the future spread of bacterial antimicrobial resistance. The aim of this study was to construct a mathematical model that can describe the dependency between the level of antimicrobial resistance and the amount of antibiotic usage. After reviewing existing mathematical models, a cross-sectional, retrospective study was carried out to collect clinical and microbiological data across 3000 patients for the construction of the mathematical model. Based on these data, a model was developed and tested to determine the dependency between antibiotic usage and resistance. Consumption of inhibitor/cephalosporins and fluoroquinolones increases inhibitor/penicillin resistance. Consumption of inhibitor/penicillins increases cephalosporin resistance. Consumption of inhibitor/penicillins increases inhibitor/cephalosporin resistance. It was demonstrated that in some antibiotic-micro-organism pairs, the level of antibiotic usage significantly influences the level of resistance. The model makes it possible to predict the change in resistance and also shows the quantitative effect of antibiotic consumption on the level of bacterial resistance. Copyright © 2017 International Society for Chemotherapy of Infection and Cancer. Published by Elsevier Ltd. All rights reserved.

  19. On the TRAIL to successful cancer therapy? Predicting and counteracting resistance against TRAIL-based therapeutics

    PubMed Central

    Dimberg, Lina Y.; Anderson, Charles K.; Camidge, Ross; Behbakht, Kian; Thorburn, Andrew; Ford, Heide L.

    2015-01-01

    TRAIL and agonistic antibodies against TRAIL death receptors kill tumor cells while causing virtually no damage to normal cells. Several novel drugs targeting TRAIL receptors are currently in clinical trials. However, TRAIL resistance is a common obstacle in TRAIL based therapy and limits the efficiency of these drugs. In this review article we discuss different mechanisms of TRAIL resistance and how they can be predicted and therapeutically circumvented. In addition, we provide a brief overview of all TRAIL based clinical trials conducted so far. It is apparent that although the effects of TRAIL therapy are disappointingly modest overall, a small subset of patients responds very well to TRAIL. We argue that the true potential of targeting TRAIL death receptors in cancer can only be reached when we find efficient ways to select for those patients that are most likely to benefit from the treatment. To achieve this, it is crucial to identify biomarkers that can help us predict TRAIL sensitivity. PMID:22580613

  20. Prediction of the Chloride Resistance of Concrete Modified with High Calcium Fly Ash Using Machine Learning

    PubMed Central

    Marks, Michał; Glinicki, Michał A.; Gibas, Karolina

    2015-01-01

    The aim of the study was to generate rules for the prediction of the chloride resistance of concrete modified with high calcium fly ash using machine learning methods. The rapid chloride permeability test, according to the Nordtest Method Build 492, was used for determining the chloride ions’ penetration in concrete containing high calcium fly ash (HCFA) for partial replacement of Portland cement. The results of the performed tests were used as the training set to generate rules describing the relation between material composition and the chloride resistance. Multiple methods for rule generation were applied and compared. The rules generated by algorithm J48 from the Weka workbench provided the means for adequate classification of plain concretes and concretes modified with high calcium fly ash as materials of good, acceptable or unacceptable resistance to chloride penetration. PMID:28793740

  1. Prediction of the Chloride Resistance of Concrete Modified with High Calcium Fly Ash Using Machine Learning.

    PubMed

    Marks, Michał; Glinicki, Michał A; Gibas, Karolina

    2015-12-11

    The aim of the study was to generate rules for the prediction of the chloride resistance of concrete modified with high calcium fly ash using machine learning methods. The rapid chloride permeability test, according to the Nordtest Method Build 492, was used for determining the chloride ions' penetration in concrete containing high calcium fly ash (HCFA) for partial replacement of Portland cement. The results of the performed tests were used as the training set to generate rules describing the relation between material composition and the chloride resistance. Multiple methods for rule generation were applied and compared. The rules generated by algorithm J48 from the Weka workbench provided the means for adequate classification of plain concretes and concretes modified with high calcium fly ash as materials of good, acceptable or unacceptable resistance to chloride penetration.

  2. Prediction of Corrosion Resistance of Some Dental Metallic Materials with an Adaptive Regression Model

    NASA Astrophysics Data System (ADS)

    Chelariu, Romeu; Suditu, Gabriel Dan; Mareci, Daniel; Bolat, Georgiana; Cimpoesu, Nicanor; Leon, Florin; Curteanu, Silvia

    2015-04-01

    The aim of this study is to investigate the electrochemical behavior of some dental metallic materials in artificial saliva for different pH (5.6 and 3.4), NaF content (500 ppm, 1000 ppm, and 2000 ppm), and with albumin protein addition (0.6 wt.%) for pH 3.4. The corrosion resistance of the alloys was quantitatively evaluated by polarization resistance, estimated by electrochemical impedance spectroscopy method. An adaptive k-nearest-neighbor regression method was applied for evaluating the corrosion resistance of the alloys by simulation, depending on the operation conditions. The predictions provided by the model are useful for experimental practice, as they can replace or, at least, help to plan the experiments. The accurate results obtained prove that the developed model is reliable and efficient.

  3. Concentrations of antibiotics predicted to select for resistant bacteria: Proposed limits for environmental regulation.

    PubMed

    Bengtsson-Palme, Johan; Larsson, D G Joakim

    2016-01-01

    There are concerns that selection pressure from antibiotics in the environment may accelerate the evolution and dissemination of antibiotic-resistant pathogens. Nevertheless, there is currently no regulatory system that takes such risks into account. In part, this is due to limited knowledge of environmental concentrations that might exert selection for resistant bacteria. To experimentally determine minimal selective concentrations in complex microbial ecosystems for all antibiotics would involve considerable effort. In this work, our aim was to estimate upper boundaries for selective concentrations for all common antibiotics, based on the assumption that selective concentrations a priori need to be lower than those completely inhibiting growth. Data on Minimal Inhibitory Concentrations (MICs) were obtained for 111 antibiotics from the public EUCAST database. The 1% lowest observed MICs were identified, and to compensate for limited species coverage, predicted lowest MICs adjusted for the number of tested species were extrapolated through modeling. Predicted No Effect Concentrations (PNECs) for resistance selection were then assessed using an assessment factor of 10 to account for differences between MICs and minimal selective concentrations. The resulting PNECs ranged from 8 ng/L to 64 μg/L. Furthermore, the link between taxonomic similarity between species and lowest MIC was weak. This work provides estimated upper boundaries for selective concentrations (lowest MICs) and PNECs for resistance selection for all common antibiotics. In most cases, PNECs for selection of resistance were below available PNECs for ecotoxicological effects. The generated PNECs can guide implementation of compound-specific emission limits that take into account risks for resistance promotion. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

  4. Prediction of membrane fouling in MBR systems using empirically estimated specific cake resistance.

    PubMed

    Khan, S Jamal; Visvanathan, C; Jegatheesan, V

    2009-12-01

    The focus of this study was to empirically estimate the specific cake resistance (SCR) by the variation in shear intensity (G) in four laboratory-scale MBRs. The control reactor (MBR(0)) was operated with aeration only while other MBRs (MBR(150), MBR(300) and MBR(450)) were operated with aeration and mechanical mixing intensities of 150, 300 and 450 rpm, respectively. It was found that the SCR was strongly correlated (R(2)=0.99) with the fouling rates in the MBRs. Moreover, the contribution of cake resistance (R(c)) to the total hydraulic resistance (R(t)) was predominant compared to the irreversible fouling resistance (R(f)). On this basis, the cake filtration model was selected as a predictive tool for membrane fouling. This model was modified by replacing the SCR with its empirical shear intensity relationship. The modified model can predict the fouling rate for a given shear intensity (G) within 80 and 250 s(-1) in a MBR system.

  5. Personalized prediction of EGFR mutation-induced drug resistance in lung cancer.

    PubMed

    Wang, Debby D; Zhou, Weiqiang; Yan, Hong; Wong, Maria; Lee, Victor

    2013-10-04

    EGFR mutation-induced drug resistance has significantly impaired the potency of small molecule tyrosine kinase inhibitors in lung cancer treatment. Computational approaches can provide powerful and efficient techniques in the investigation of drug resistance. In our work, the EGFR mutation feature is characterized by the energy components of binding free energy (concerning the mutant-inhibitor complex), and we combine it with specific personal features for 168 clinical subjects to construct a personalized drug resistance prediction model. The 3D structure of an EGFR mutant is computationally predicted from its protein sequence, after which the dynamics of the bound mutant-inhibitor complex is simulated via AMBER and the binding free energy of the complex is calculated based on the dynamics. The utilization of extreme learning machines and leave-one-out cross-validation promises a successful identification of resistant subjects with high accuracy. Overall, our study demonstrates advantages in the development of personalized medicine/therapy design and innovative drug discovery.

  6. Personalized prediction of EGFR mutation-induced drug resistance in lung cancer

    PubMed Central

    Wang, Debby D.; Zhou, Weiqiang; Yan, Hong; Wong, Maria; Lee, Victor

    2013-01-01

    EGFR mutation-induced drug resistance has significantly impaired the potency of small molecule tyrosine kinase inhibitors in lung cancer treatment. Computational approaches can provide powerful and efficient techniques in the investigation of drug resistance. In our work, the EGFR mutation feature is characterized by the energy components of binding free energy (concerning the mutant-inhibitor complex), and we combine it with specific personal features for 168 clinical subjects to construct a personalized drug resistance prediction model. The 3D structure of an EGFR mutant is computationally predicted from its protein sequence, after which the dynamics of the bound mutant-inhibitor complex is simulated via AMBER and the binding free energy of the complex is calculated based on the dynamics. The utilization of extreme learning machines and leave-one-out cross-validation promises a successful identification of resistant subjects with high accuracy. Overall, our study demonstrates advantages in the development of personalized medicine/therapy design and innovative drug discovery. PMID:24092472

  7. DRPPP: A machine learning based tool for prediction of disease resistance proteins in plants.

    PubMed

    Pal, Tarun; Jaiswal, Varun; Chauhan, Rajinder S

    2016-11-01

    Plant disease outbreak is increasing rapidly around the globe and is a major cause for crop loss worldwide. Plants, in turn, have developed diverse defense mechanisms to identify and evade different pathogenic microorganisms. Early identification of plant disease resistance genes (R genes) can be exploited for crop improvement programs. The present prediction methods are either based on sequence similarity/domain-based methods or electronically annotated sequences, which might miss existing unrecognized proteins or low similarity proteins. Therefore, there is an urgent need to devise a novel machine learning technique to address this problem. In the current study, a SVM-based tool was developed for prediction of disease resistance proteins in plants. All known disease resistance (R) proteins (112) were taken as a positive set, whereas manually curated negative dataset consisted of 119 non-R proteins. Feature extraction generated 10,270 features using 16 different methods. The ten-fold cross validation was performed to optimize SVM parameters using radial basis function. The model was derived using libSVM and achieved an overall accuracy of 91.11% on the test dataset. The tool was found to be robust and can be used for high-throughput datasets. The current study provides instant identification of R proteins using machine learning approach, in addition to the similarity or domain prediction methods. Copyright © 2016 Elsevier Ltd. All rights reserved.

  8. Prediction of Staphylococcus aureus Antimicrobial Resistance by Whole-Genome Sequencing

    PubMed Central

    Price, J. R.; Cole, K.; Everitt, R.; Morgan, M.; Finney, J.; Kearns, A. M.; Pichon, B.; Young, B.; Wilson, D. J.; Llewelyn, M. J.; Paul, J.; Peto, T. E. A.; Crook, D. W.; Walker, A. S.; Golubchik, T.

    2014-01-01

    Whole-genome sequencing (WGS) could potentially provide a single platform for extracting all the information required to predict an organism's phenotype. However, its ability to provide accurate predictions has not yet been demonstrated in large independent studies of specific organisms. In this study, we aimed to develop a genotypic prediction method for antimicrobial susceptibilities. The whole genomes of 501 unrelated Staphylococcus aureus isolates were sequenced, and the assembled genomes were interrogated using BLASTn for a panel of known resistance determinants (chromosomal mutations and genes carried on plasmids). Results were compared with phenotypic susceptibility testing for 12 commonly used antimicrobial agents (penicillin, methicillin, erythromycin, clindamycin, tetracycline, ciprofloxacin, vancomycin, trimethoprim, gentamicin, fusidic acid, rifampin, and mupirocin) performed by the routine clinical laboratory. We investigated discrepancies by repeat susceptibility testing and manual inspection of the sequences and used this information to optimize the resistance determinant panel and BLASTn algorithm. We then tested performance of the optimized tool in an independent validation set of 491 unrelated isolates, with phenotypic results obtained in duplicate by automated broth dilution (BD Phoenix) and disc diffusion. In the validation set, the overall sensitivity and specificity of the genomic prediction method were 0.97 (95% confidence interval [95% CI], 0.95 to 0.98) and 0.99 (95% CI, 0.99 to 1), respectively, compared to standard susceptibility testing methods. The very major error rate was 0.5%, and the major error rate was 0.7%. WGS was as sensitive and specific as routine antimicrobial susceptibility testing methods. WGS is a promising alternative to culture methods for resistance prediction in S. aureus and ultimately other major bacterial pathogens. PMID:24501024

  9. Prediction of Staphylococcus aureus antimicrobial resistance by whole-genome sequencing.

    PubMed

    Gordon, N C; Price, J R; Cole, K; Everitt, R; Morgan, M; Finney, J; Kearns, A M; Pichon, B; Young, B; Wilson, D J; Llewelyn, M J; Paul, J; Peto, T E A; Crook, D W; Walker, A S; Golubchik, T

    2014-04-01

    Whole-genome sequencing (WGS) could potentially provide a single platform for extracting all the information required to predict an organism's phenotype. However, its ability to provide accurate predictions has not yet been demonstrated in large independent studies of specific organisms. In this study, we aimed to develop a genotypic prediction method for antimicrobial susceptibilities. The whole genomes of 501 unrelated Staphylococcus aureus isolates were sequenced, and the assembled genomes were interrogated using BLASTn for a panel of known resistance determinants (chromosomal mutations and genes carried on plasmids). Results were compared with phenotypic susceptibility testing for 12 commonly used antimicrobial agents (penicillin, methicillin, erythromycin, clindamycin, tetracycline, ciprofloxacin, vancomycin, trimethoprim, gentamicin, fusidic acid, rifampin, and mupirocin) performed by the routine clinical laboratory. We investigated discrepancies by repeat susceptibility testing and manual inspection of the sequences and used this information to optimize the resistance determinant panel and BLASTn algorithm. We then tested performance of the optimized tool in an independent validation set of 491 unrelated isolates, with phenotypic results obtained in duplicate by automated broth dilution (BD Phoenix) and disc diffusion. In the validation set, the overall sensitivity and specificity of the genomic prediction method were 0.97 (95% confidence interval [95% CI], 0.95 to 0.98) and 0.99 (95% CI, 0.99 to 1), respectively, compared to standard susceptibility testing methods. The very major error rate was 0.5%, and the major error rate was 0.7%. WGS was as sensitive and specific as routine antimicrobial susceptibility testing methods. WGS is a promising alternative to culture methods for resistance prediction in S. aureus and ultimately other major bacterial pathogens.

  10. Rapid antibiotic-resistance predictions from genome sequence data for Staphylococcus aureus and Mycobacterium tuberculosis.

    PubMed

    Bradley, Phelim; Gordon, N Claire; Walker, Timothy M; Dunn, Laura; Heys, Simon; Huang, Bill; Earle, Sarah; Pankhurst, Louise J; Anson, Luke; de Cesare, Mariateresa; Piazza, Paolo; Votintseva, Antonina A; Golubchik, Tanya; Wilson, Daniel J; Wyllie, David H; Diel, Roland; Niemann, Stefan; Feuerriegel, Silke; Kohl, Thomas A; Ismail, Nazir; Omar, Shaheed V; Smith, E Grace; Buck, David; McVean, Gil; Walker, A Sarah; Peto, Tim E A; Crook, Derrick W; Iqbal, Zamin

    2015-12-21

    The rise of antibiotic-resistant bacteria has led to an urgent need for rapid detection of drug resistance in clinical samples, and improvements in global surveillance. Here we show how de Bruijn graph representation of bacterial diversity can be used to identify species and resistance profiles of clinical isolates. We implement this method for Staphylococcus aureus and Mycobacterium tuberculosis in a software package ('Mykrobe predictor') that takes raw sequence data as input, and generates a clinician-friendly report within 3 minutes on a laptop. For S. aureus, the error rates of our method are comparable to gold-standard phenotypic methods, with sensitivity/specificity of 99.1%/99.6% across 12 antibiotics (using an independent validation set, n=470). For M. tuberculosis, our method predicts resistance with sensitivity/specificity of 82.6%/98.5% (independent validation set, n=1,609); sensitivity is lower here, probably because of limited understanding of the underlying genetic mechanisms. We give evidence that minor alleles improve detection of extremely drug-resistant strains, and demonstrate feasibility of the use of emerging single-molecule nanopore sequencing techniques for these purposes.

  11. Rapid antibiotic-resistance predictions from genome sequence data for Staphylococcus aureus and Mycobacterium tuberculosis

    PubMed Central

    Bradley, Phelim; Gordon, N. Claire; Walker, Timothy M.; Dunn, Laura; Heys, Simon; Huang, Bill; Earle, Sarah; Pankhurst, Louise J.; Anson, Luke; de Cesare, Mariateresa; Piazza, Paolo; Votintseva, Antonina A.; Golubchik, Tanya; Wilson, Daniel J.; Wyllie, David H.; Diel, Roland; Niemann, Stefan; Feuerriegel, Silke; Kohl, Thomas A.; Ismail, Nazir; Omar, Shaheed V.; Smith, E. Grace; Buck, David; McVean, Gil; Walker, A. Sarah; Peto, Tim E. A.; Crook, Derrick W.; Iqbal, Zamin

    2015-01-01

    The rise of antibiotic-resistant bacteria has led to an urgent need for rapid detection of drug resistance in clinical samples, and improvements in global surveillance. Here we show how de Bruijn graph representation of bacterial diversity can be used to identify species and resistance profiles of clinical isolates. We implement this method for Staphylococcus aureus and Mycobacterium tuberculosis in a software package (‘Mykrobe predictor') that takes raw sequence data as input, and generates a clinician-friendly report within 3 minutes on a laptop. For S. aureus, the error rates of our method are comparable to gold-standard phenotypic methods, with sensitivity/specificity of 99.1%/99.6% across 12 antibiotics (using an independent validation set, n=470). For M. tuberculosis, our method predicts resistance with sensitivity/specificity of 82.6%/98.5% (independent validation set, n=1,609); sensitivity is lower here, probably because of limited understanding of the underlying genetic mechanisms. We give evidence that minor alleles improve detection of extremely drug-resistant strains, and demonstrate feasibility of the use of emerging single-molecule nanopore sequencing techniques for these purposes. PMID:26686880

  12. Expression of xeroderma pigmentosum complementation group C protein predicts cisplatin resistance in lung adenocarcinoma patients.

    PubMed

    Lai, Tan-Chen; Chow, Kuan-Chih; Fang, Hsin-Yuan; Cho, Hsin-Ching; Chen, Chih-Yi; Lin, Tze-Yi; Chiang, I-Ping; Ho, Shu-Peng

    2011-05-01

    DNA repair has been suggested to be a major cause of spontaneous drug resistance in patients with lung adenocarcinomas (LADC). Among the DNA repair-related proteins, excision repair cross-complementation group 1 (ERCC1) has been shown to be essential for repairing cisplatin-induced interstrand cross-linkage. However, the role of other DNA repair-related proteins in drug resistance has not been clearly elucidated. In this study, we used suppression subtractive hybridization and microarray analysis to identify the DNA repair-related genes associated with cisplatin resistance. We focused on the association of XPC protein expression, which plays a pivotal role in the earliest response to global genomic repair, with the survival of LADC patients. Using suppression subtractive hybridization and a microarray analysis to identify drug resistance-associated DNA repair-related genes, we found that the mRNA levels of ERCC1, MSH-3, MSH-6 and XPC were significantly increased in LADC patients. Since the results of ERCC1 mRNA expression corresponded well with those in previous reports, in this study we focused on the clinical correlation between XPC expression and patient survival. The level of XPC protein was determined by immunohistochemical and immunoblotting analyses. We detected the XPC protein in 46 (43%) of 107 pathological LADC samples. XPC protein expression correlated with tumor stage, cigarette smoking and poor survival. In the in vitro experiments with LADC cell lines, increased XPC expression was associated with elevated drug resistance, and silencing of XPC expression reduced cisplatin resistance. Our results suggest that XPC expression predicts drug resistance in LADC.

  13. Prediction of drought-resistant genes in Arabidopsis thaliana using SVM-RFE.

    PubMed

    Liang, Yanchun; Zhang, Fan; Wang, Juexin; Joshi, Trupti; Wang, Yan; Xu, Dong

    2011-01-01

    Identifying genes with essential roles in resisting environmental stress rates high in agronomic importance. Although massive DNA microarray gene expression data have been generated for plants, current computational approaches underutilize these data for studying genotype-trait relationships. Some advanced gene identification methods have been explored for human diseases, but typically these methods have not been converted into publicly available software tools and cannot be applied to plants for identifying genes with agronomic traits. In this study, we used 22 sets of Arabidopsis thaliana gene expression data from GEO to predict the key genes involved in water tolerance. We applied an SVM-RFE (Support Vector Machine-Recursive Feature Elimination) feature selection method for the prediction. To address small sample sizes, we developed a modified approach for SVM-RFE by using bootstrapping and leave-one-out cross-validation. We also expanded our study to predict genes involved in water susceptibility. We analyzed the top 10 genes predicted to be involved in water tolerance. Seven of them are connected to known biological processes in drought resistance. We also analyzed the top 100 genes in terms of their biological functions. Our study shows that the SVM-RFE method is a highly promising method in analyzing plant microarray data for studying genotype-phenotype relationships. The software is freely available with source code at http://ccst.jlu.edu.cn/JCSB/RFET/.

  14. Plasma Renin Activity Predicts the Improvement in Resistant Hypertension after Percutaneous Transluminal Renal Artery Angioplasty

    PubMed Central

    Daidoji, Hyuma; Tamada, Yoshiaki; Suzuki, Saya; Watanabe, Ken; Shikama, Taku; Kikuchi, Yoku; Kato, Shigehiko; Takahashi, Katsuaki; Fukui, Akio; Matsui, Motoyuki; Yahagi, Tomoyasu; Goto, Toshikazu

    2016-01-01

    Objective Percutaneous transluminal renal artery angioplasty (PTRA) has been recommended for the treatment of renovascular resistant hypertension. However, large randomized trials have reported that PTRA did not improve the outcomes compared with optimal medical therapy in patients with renal artery stenosis (RAS). It is important to identify patients with renovascular hypertension who are likely to respond to PTRA. We herein examined whether or not the plasma renin activity (PRA) could predict the improvement in resistant hypertension after PTRA for RAS. Methods and Results A total of 40 patients (mean age: 63±15 years) with unilateral RAS who received PTRA for resistant hypertension were enrolled in this study. Twenty-two (55%) patients experienced a significant reduction in their blood pressure while using few antihypertensive agents at the 3-month follow up. The median PRA was significantly higher in patients using few antihypertensive agents than in those using more [4.2 ng/mL/hr, interquartile range (IQR) 2.6-8.0 vs. 0.8 ng/mL/hr, IQR 0.4-1.7, p<0.001]. To predict the improvement in hypertension after PTRA, a receiver operating characteristic analysis determined the optimal cut-off value of PRA to be 2.4 ng/mL/hr. A multivariate logistic regression analysis showed that higher PRA (>2.4 ng/mL/hr) was an independent predictor of the improvement in hypertension after PTRA (odds ratio: 22.3, 95% confidence interval: 2.17 to 65.6, p<0.01). Conclusion These findings suggest that the evaluation of preoperative PRA may be a useful tool for predicting the improvement in resistant hypertension after PTRA for patients with RAS. PMID:27904103

  15. A quasi-physical model for predicting the thermal insulation and moisture vapour resistance of clothing.

    PubMed

    Qian, Xiaoming; Fan, Jintu

    2009-07-01

    Based on the improved understanding of the effects of wind and walking motion on the thermal insulation and moisture vapour resistance of clothing induced by air ventilation in the clothing system, a new model has been derived based on fundamental mechanisms of heat and mass transfer, which include conduction, diffusion, radiation and natural convection, wind penetration and air ventilation. The model predicts thermal insulation of clothing under body movement and windy conditions from the thermal insulation of clothing measured when the person is standing in the still air. The effects of clothing characteristics such as fabric air permeability, garment style, garment fitting and construction have been considered in the model through the key prediction parameters. With the new model, an improved prediction accuracy is achieved with a percentage of fit being as high as 0.96.

  16. Thermal Modeling of Resistance Spot Welding and Prediction of Weld Microstructure

    NASA Astrophysics Data System (ADS)

    Sheikhi, M.; Valaee Tale, M.; Usefifar, GH. R.; Fattah-Alhosseini, Arash

    2017-09-01

    The microstructure of nuggets in resistance spot welding can be influenced by the many variables involved. This study aimed at examining such a relationship and, consequently, put forward an analytical model to predict the thermal history and microstructure of the nugget zone. Accordingly, a number of numerical simulations and experiments were conducted and the accuracy of the model was assessed. The results of this assessment revealed that the proposed analytical model could accurately predict the cooling rate in the nugget and heat-affected zones. Moreover, both analytical and numerical models confirmed that sheet thickness and electrode-sheet interface temperature were the most important factors influencing the cooling rate at temperatures lower than about T l/2. Decomposition of austenite is one of the most important transformations in steels occurring over this temperature range. Therefore, an easy-to-use map was designed against these parameters to predict the weld microstructure.

  17. Biomarkers of evasive resistance predict disease progression in cancer patients treated with antiangiogenic therapies

    PubMed Central

    Pircher, Andreas; Jöhrer, Karin; Kocher, Florian; Steiner, Normann; Graziadei, Ivo; Heidegger, Isabel; Pichler, Renate; Leonhartsberger, Nicolai; Kremser, Christian; Kern, Johann; Untergasser, Gerold; Gunsilius, Eberhard; Hilbe, Wolfgang

    2016-01-01

    Numerous antiangiogenic agents are approved for the treatment of oncological diseases. However, almost all patients develop evasive resistance mechanisms against antiangiogenic therapies. Currently no predictive biomarker for therapy resistance or response has been established. Therefore, the aim of our study was to identify biomarkers predicting the development of therapy resistance in patients with hepatocellular cancer (n = 11), renal cell cancer (n = 7) and non-small cell lung cancer (n = 2). Thereby we measured levels of angiogenic growth factors, tumor perfusion, circulating endothelial cells (CEC), circulating endothelial progenitor cells (CEP) and tumor endothelial markers (TEM) in patients during the course of therapy with antiangiogenic agents, and correlated them with the time to antiangiogenic progression (aTTP). Importantly, at disease progression, we observed an increase of proangiogenic factors, upregulation of CEC/CEP levels and downregulation of TEMs, such as Robo4 and endothelial cell-specific chemotaxis regulator (ECSCR), reflecting the formation of torturous tumor vessels. Increased TEM expression levels tended to correlate with prolonged aTTP (ECSCR high = 275 days vs. ECSCR low = 92.5 days; p = 0.07 and for Robo4 high = 387 days vs. Robo4 low = 90.0 days; p = 0.08). This indicates that loss of vascular stabilization factors aggravates the development of antiangiogenic resistance. Thus, our observations confirm that CEP/CEC populations, proangiogenic cytokines and TEMs contribute to evasive resistance in antiangiogenic treated patients. Higher TEM expression during disease progression may have clinical and pathophysiological implications, however, validation of our results is warranted for further biomarker development. PMID:26956051

  18. Biomarkers of evasive resistance predict disease progression in cancer patients treated with antiangiogenic therapies.

    PubMed

    Pircher, Andreas; Jöhrer, Karin; Kocher, Florian; Steiner, Normann; Graziadei, Ivo; Heidegger, Isabel; Pichler, Renate; Leonhartsberger, Nicolai; Kremser, Christian; Kern, Johann; Untergasser, Gerold; Gunsilius, Eberhard; Hilbe, Wolfgang

    2016-04-12

    Numerous antiangiogenic agents are approved for the treatment of oncological diseases. However, almost all patients develop evasive resistance mechanisms against antiangiogenic therapies. Currently no predictive biomarker for therapy resistance or response has been established. Therefore, the aim of our study was to identify biomarkers predicting the development of therapy resistance in patients with hepatocellular cancer (n = 11), renal cell cancer (n = 7) and non-small cell lung cancer (n = 2). Thereby we measured levels of angiogenic growth factors, tumor perfusion, circulating endothelial cells (CEC), circulating endothelial progenitor cells (CEP) and tumor endothelial markers (TEM) in patients during the course of therapy with antiangiogenic agents, and correlated them with the time to antiangiogenic progression (aTTP). Importantly, at disease progression, we observed an increase of proangiogenic factors, upregulation of CEC/CEP levels and downregulation of TEMs, such as Robo4 and endothelial cell-specific chemotaxis regulator (ECSCR), reflecting the formation of torturous tumor vessels. Increased TEM expression levels tended to correlate with prolonged aTTP (ECSCR high = 275 days vs. ECSCR low = 92.5 days; p = 0.07 and for Robo4 high = 387 days vs. Robo4 low = 90.0 days; p = 0.08). This indicates that loss of vascular stabilization factors aggravates the development of antiangiogenic resistance. Thus, our observations confirm that CEP/CEC populations, proangiogenic cytokines and TEMs contribute to evasive resistance in antiangiogenic treated patients. Higher TEM expression during disease progression may have clinical and pathophysiological implications, however, validation of our results is warranted for further biomarker development.

  19. Multistrain models predict sequential multidrug treatment strategies to result in less antimicrobial resistance than combination treatment.

    PubMed

    Ahmad, Amais; Zachariasen, Camilla; Christiansen, Lasse Engbo; Græsbøll, Kaare; Toft, Nils; Matthews, Louise; Olsen, John Elmerdahl; Nielsen, Søren Saxmose

    2016-06-23

    Combination treatment is increasingly used to fight infections caused by bacteria resistant to two or more antimicrobials. While multiple studies have evaluated treatment strategies to minimize the emergence of resistant strains for single antimicrobial treatment, fewer studies have considered combination treatments. The current study modeled bacterial growth in the intestine of pigs after intramuscular combination treatment (i.e. using two antibiotics simultaneously) and sequential treatments (i.e. alternating between two antibiotics) in order to identify the factors that favor the sensitive fraction of the commensal flora. Growth parameters for competing bacterial strains were estimated from the combined in vitro pharmacodynamic effect of two antimicrobials using the relationship between concentration and net bacterial growth rate. Predictions of in vivo bacterial growth were generated by a mathematical model of the competitive growth of multiple strains of Escherichia coli. Simulation studies showed that sequential use of tetracycline and ampicillin reduced the level of double resistance, when compared to the combination treatment. The effect of the cycling frequency (how frequently antibiotics are alternated in a sequential treatment) of the two drugs was dependent upon the order in which the two drugs were used. Sequential treatment was more effective in preventing the growth of resistant strains when compared to the combination treatment. The cycling frequency did not play a role in suppressing the growth of resistant strains, but the specific order of the two antimicrobials did. Predictions made from the study could be used to redesign multidrug treatment strategies not only for intramuscular treatment in pigs, but also for other dosing routes.

  20. Predicting bacterial resistance using the time inside the mutant selection window: possibilities and limitations.

    PubMed

    Firsov, Alexander A; Portnoy, Yury A; Strukova, Elena N; Shlykova, Darya S; Zinner, Stephen H

    2014-10-01

    The time inside the mutant selection window (TMSW) has been shown to be less predictive of selection of fluoroquinolone-resistant bacteria than the ratio of the area under the concentration-time curve to minimum inhibitory concentration (AUC/MIC). To explore the different predictive powers of TMSW and AUC/MIC, enrichment of ciprofloxacin-resistant mutants of four Escherichia coli strains was studied in an in vitro dynamic model at widely ranging TMSW values. Each organism was exposed to twice-daily ciprofloxacin for 3 days. Peak antibiotic concentrations were simulated to be close to the MIC, between the MIC and the mutant prevention concentration (MPC), and above the MPC, with TMSW varying from 0% to 100% of the dosing interval. Amplification of resistant mutants was monitored by plating on medium with 8× MIC of the antibiotic. For each organism, TMSW plots of the area under the bacterial mutant concentration-time curve (AUBCM) exhibited a hysteresis loop: at a given TMSW that corresponds to the points on the ascending portion of the bell-shaped AUBCM-AUC/MIC curve [when the time above the MPC (T>MPC) was zero], the AUBCM was greater than at the same TMSW related to the descending portion (T>MPC>0). A sigmoid function fits these separate data sets well for combined data with the four organisms (r(2)=0.81 and 0.92, respectively), in contrast to fitting the whole data pool while ignoring the AUC/MIC-resistance relationship (r(2)=0.61). These data allow the appropriate use of TMSW as a predictor of bacterial resistance.

  1. Using whole genome sequencing to identify resistance determinants and predict antimicrobial resistance phenotypes for year 2015 invasive pneumococcal disease isolates recovered in the United States.

    PubMed

    Metcalf, B J; Chochua, S; Gertz, R E; Li, Z; Walker, H; Tran, T; Hawkins, P A; Glennen, A; Lynfield, R; Li, Y; McGee, L; Beall, B

    2016-12-01

    Our whole genome sequence (WGS) pipeline was assessed for accurate prediction of antimicrobial phenotypes. For 2316 invasive pneumococcal isolates recovered during 2015 we compared WGS pipeline data to broth dilution testing (BDT) for 18 antimicrobials. For 11 antimicrobials categorical discrepancies were assigned when WGS-predicted MICs and BDT MICs predicted different categorizations for susceptibility, intermediate resistance or resistance, ranging from 0.9% (tetracycline) to 2.9% (amoxicillin). For β-lactam antibiotics, the occurrence of at least four-fold differences in MIC ranged from 0.2% (meropenem) to 1.0% (penicillin), although phenotypic retesting resolved 25%-78% of these discrepancies. Non-susceptibility to penicillin, predicted by penicillin-binding protein types, was 2.7% (non-meningitis criteria) and 23.8% (meningitis criteria). Other common resistance determinants included mef (475 isolates), ermB (191 isolates), ermB + mef (48 isolates), tetM (261 isolates) and cat (51 isolates). Additional accessory resistance genes (tetS, tet32, aphA-3, sat4) were rarely detected (one to three isolates). Rare core genome mutations conferring erythromycin-resistance included a two-codon rplD insertion (rplD69-KG-70) and the 23S rRNA A2061G substitution (six isolates). Intermediate cotrimoxazole-resistance was associated with one or two codon insertions within folP (238 isolates) or the folA I100L substitution (38 isolates), whereas full cotrimoxazole-resistance was attributed to alterations in both genes (172 isolates). The two levofloxacin-resistant isolates contained parC and/or gyrA mutations. Of 11 remaining isolates with moderately elevated MICs to both ciprofloxacin and levofloxacin, seven contained parC or gyrA mutations. The two rifampin-resistant isolates contained rpoB mutations. WGS-based antimicrobial phenotype prediction was an informative alternative to BDT for invasive pneumococci.

  2. Finite-size effects on molecular dynamics interfacial thermal-resistance predictions

    NASA Astrophysics Data System (ADS)

    Liang, Zhi; Keblinski, Pawel

    2014-08-01

    Using molecular dynamics simulations, we study the role of finite size effects on the determination of interfacial thermal resistance between two solids characterized by high phonon mean free paths. In particular, we will show that a direct, heat source-sink method leads to strong size effect, associated with ballistic phonon transport to and from, and specular reflections at the simulation domain boundary. Lack of proper account for these effects can lead to incorrect predictions about the role of interfacial bonding and structure on interfacial thermal resistance. We also show that the finite size effect can be dramatically reduced by introduction of rough external boundaries leading to diffuse phonon scattering, as explicitly demonstrated by phonon wave-packet simulations. Finally, we demonstrate that when careful considerations are given to the effects associated with the finite heat capacity of the simulation domains and phonon scattering from the external surfaces, a size-independent interfacial resistance can be properly extracted from the time integral of the correlation function of heat power across the interface. Our work demonstrates that reliable and consistent values of the interfacial thermal resistance can be obtained by equilibrium and nonequilibrium methods with a relatively small computational cost.

  3. TAK1-regulated expression of BIRC3 predicts resistance to preoperative chemoradiotherapy in oesophageal adenocarcinoma patients

    PubMed Central

    Piro, G; Giacopuzzi, S; Bencivenga, M; Carbone, C; Verlato, G; Frizziero, M; Zanotto, M; Mina, M M; Merz, V; Santoro, R; Zanoni, A; De Manzoni, G; Tortora, G; Melisi, D

    2015-01-01

    Background: About 20% of resectable oesophageal carcinoma is resistant to preoperative chemoradiotherapy. Here we hypothesised that the expression of the antiapoptotic gene Baculoviral inhibitor of apoptosis repeat containing (BIRC)3 induced by the transforming growth factor β activated kinase 1 (TAK1) might be responsible for the resistance to the proapoptotic effect of chemoradiotherapy in oesophageal carcinoma. Methods: TAK1 kinase activity was inhibited in FLO-1 and KYAE-1 oesophageal adenocarcinoma cells using (5Z)-7-oxozeaenol. The BIRC3 mRNA expression was measured by qRT–PCR in 65 pretreatment frozen biopsies from patients receiving preoperatively docetaxel, cisplatin, 5-fluorouracil, and concurrent radiotherapy. Receiver operator characteristic (ROC) analyses were performed to determine the performance of BIRC3 expression levels in distinguishing patients with sensitive or resistant carcinoma. Results: In vitro, (5Z)-7-oxozeaenol significantly reduced BIRC3 expression in FLO-1 and KYAE-1 cells. Exposure to chemotherapeutic agents or radiotherapy plus (5Z)-7-oxozeaenol resulted in a strong synergistic antiapoptotic effect. In patients, median expression of BIRC3 was significantly (P<0.0001) higher in adenocarcinoma than in the more sensitive squamous cell carcinoma subtype. The BIRC3 expression significantly discriminated patients with sensitive or resistant adenocarcinoma (AUC-ROC=0.7773 and 0.8074 by size-based pathological response or Mandard's tumour regression grade classifications, respectively). Conclusions: The BIRC3 expression might be a valid biomarker for predicting patients with oesophageal adenocarcinoma that could most likely benefit from preoperative chemoradiotherapy. PMID:26291056

  4. Towards predictive resistance models for agrochemicals by combining chemical and protein similarity via proteochemometric modelling.

    PubMed

    van Westen, Gerard J P; Bender, Andreas; Overington, John P

    2014-10-01

    Resistance to pesticides is an increasing problem in agriculture. Despite practices such as phased use and cycling of 'orthogonally resistant' agents, resistance remains a major risk to national and global food security. To combat this problem, there is a need for both new approaches for pesticide design, as well as for novel chemical entities themselves. As summarized in this opinion article, a technique termed 'proteochemometric modelling' (PCM), from the field of chemoinformatics, could aid in the quantification and prediction of resistance that acts via point mutations in the target proteins of an agent. The technique combines information from both the chemical and biological domain to generate bioactivity models across large numbers of ligands as well as protein targets. PCM has previously been validated in prospective, experimental work in the medicinal chemistry area, and it draws on the growing amount of bioactivity information available in the public domain. Here, two potential applications of proteochemometric modelling to agrochemical data are described, based on previously published examples from the medicinal chemistry literature.

  5. Prediction of future risk of insulin resistance and metabolic syndrome based on Korean boy's metabolite profiling.

    PubMed

    Lee, AeJin; Jang, Han Byul; Ra, Moonjin; Choi, Youngshim; Lee, Hye-Ja; Park, Ju Yeon; Kang, Jae Heon; Park, Kyung-Hee; Park, Sang Ick; Song, Jihyun

    2015-01-01

    Childhood obesity is strongly related to future insulin resistance and metabolic syndrome. Thus, identifying early biomarkers of obesity-related diseases based on metabolic profiling is useful to control future metabolic disorders. We compared metabolic profiles between obese and normal-weight children and investigated specific biomarkers of future insulin resistance and metabolic syndrome. In all, 186 plasma metabolites were analysed at baseline and after 2 years in 109 Korean boys (age 10.5±0.4 years) from the Korean Child Obesity Cohort Study using the AbsoluteIDQ™ p180 Kit. We observed that levels of 41 metabolites at baseline and 40 metabolites at follow-up were significantly altered in obese children (p<0.05). Obese children showed significantly higher levels of branched-chain amino acids (BCAAs) and several acylcarnitines and lower levels of acyl-alkyl phosphatidylcholines. Also, baseline BCAAs were significantly positively correlated with both homeostasis model assessment for insulin resistance (HOMA-IR) and continuous metabolic risk score at the 2-year follow-up. In logistic regression analyses with adjustments for degree of obesity at baseline, baseline BCAA concentration, greater than the median value, was identified as a predictor of future risk of insulin resistance and metabolic syndrome. High BCAA concentration could be "early" biomarkers for predicting future metabolic diseases. Copyright © 2014 Asian Oceanian Association for the Study of Obesity. Published by Elsevier Ltd. All rights reserved.

  6. Carotenoid-based plumage coloration predicts resistance to a novel parasite in the house finch

    NASA Astrophysics Data System (ADS)

    Hill, Geoffrey E.; Farmer, Kristy L.

    2005-01-01

    The Hamilton-Zuk hypothesis proposes that the bright colours displayed by many species of birds serve as signals of individual resistance to parasites. Despite the popularity of this hypothesis, only one previous study has tested whether plumage coloration predicts how individuals respond to a disease challenge. We inoculated 24 male house finches (Carpodacus mexicanus) of variable plumage hue with a novel bacterial pathogen, Mycoplasma gallicepticum (MG). We found no relationship between plumage hue and time to first symptoms following inoculation, but we found a significant negative relationship between plumage hue and clearance of disease: males with redder plumage cleared MG infection significantly better than did males with yellower plumage. The hue of carotenoid-based plumage coloration has been shown to be a primary criterion in female mate choice in the house finch. These observations suggest that one benefit to females for choosing redder males is obtaining mates with better resistance to parasites.

  7. Development and Life Prediction of Erosion Resistant Turbine Low Conductivity Thermal Barrier Coatings

    NASA Technical Reports Server (NTRS)

    Zhu, Dongming; Miller, Robert A.; Kuczmarski, Maria A.

    2010-01-01

    Future rotorcraft propulsion systems are required to operate under highly-loaded conditions and in harsh sand erosion environments, thereby imposing significant material design and durability issues. The incorporation of advanced thermal barrier coatings (TBC) in high pressure turbine systems enables engine designs with higher inlet temperatures, thus improving the engine efficiency, power density and reliability. The impact and erosion resistance of turbine thermal barrier coating systems are crucial to the turbine coating technology application, because a robust turbine blade TBC system is a prerequisite for fully utilizing the potential coating technology benefit in the rotorcraft propulsion. This paper describes the turbine blade TBC development in addressing the coating impact and erosion resistance. Advanced thermal barrier coating systems with improved performance have also been validated in laboratory simulated engine erosion and/or thermal gradient environments. A preliminary life prediction modeling approach to emphasize the turbine blade coating erosion is also presented.

  8. Prediction of steel corrosion resistance based on EBSD-data analysis

    NASA Astrophysics Data System (ADS)

    Chezganov, D. S.; Borovykh, M. A.; Chikova, O. A.

    2017-04-01

    We experimentally compared the samples of chromium-manganese steel prepared with various heat-treatment modes to predict the corrosion resistance of the steel relative to hydrocarbon influence. The study was done using scanning electron microscopy, X-ray energy dispersive spectroscopy and electron backscattered diffraction. The surface visualization and elemental analysis allowed to reveal the existence of inclusions and discontinuities and their elemental composition. The peculiarities of crystal structure, grain sizes and orientations were revealed by the analysis of misorientation distribution histograms, and orientation, band contrast and Schmidt factor maps. The analysis allowed to conclude which of the heat-treatment modes provides the increase of corrosion resistance relative to the hydrocarbons influence.

  9. Genomic Prediction of Northern Corn Leaf Blight Resistance in Maize with Combined or Separated Training Sets for Heterotic Groups

    PubMed Central

    Technow, Frank; Bürger, Anna; Melchinger, Albrecht E.

    2013-01-01

    Northern corn leaf blight (NCLB), a severe fungal disease causing yield losses worldwide, is most effectively controlled by resistant varieties. Genomic prediction could greatly aid resistance breeding efforts. However, the development of accurate prediction models requires large training sets of genotyped and phenotyped individuals. Maize hybrid breeding is based on distinct heterotic groups that maximize heterosis (the dent and flint groups in Central Europe). The resulting allocation of resources to parallel breeding programs challenges the establishment of sufficiently sized training sets within groups. Therefore, using training sets combining both heterotic groups might be a possibility of increasing training set sizes and thereby prediction accuracies. The objectives of our study were to assess the prospect of genomic prediction of NCLB resistance in maize and the benefit of a training set that combines two heterotic groups. Our data comprised 100 dent and 97 flint lines, phenotyped for NCLB resistance per se and genotyped with high-density single-nucleotide polymorphism marker data. A genomic BLUP model was used to predict genotypic values. Prediction accuracies reached a maximum of 0.706 (dent) and 0.690 (flint), and there was a strong positive response to increases in training set size. The use of combined training sets led to significantly greater prediction accuracies for both heterotic groups. Our results encourage the application of genomic prediction in NCLB-resistance breeding programs and the use of combined training sets. PMID:23390596

  10. Prediction of Drug Transfer into Milk Considering Breast Cancer Resistance Protein (BCRP)-Mediated Transport.

    PubMed

    Ito, Naoki; Ito, Kousei; Ikebuchi, Yuki; Toyoda, Yu; Takada, Tappei; Hisaka, Akihiro; Oka, Akira; Suzuki, Hiroshi

    2015-08-01

    Drug transfer into milk is of concern due to the unnecessary exposure of infants to drugs. Proposed prediction methods for such transfer assume only passive drug diffusion across the mammary epithelium. This study reorganized data from the literature to assess the contribution of carrier-mediated transport to drug transfer into milk, and to improve the predictability thereof. Milk-to-plasma drug concentration ratios (M/Ps) in humans were exhaustively collected from the literature and converted into observed unbound concentration ratios (M/Punbound,obs). The ratios were also predicted based on passive diffusion across the mammary epithelium (M/Punbound,pred). An in vitro transport assay was performed for selected drugs in breast cancer resistance protein (BCRP)-expressing cell monolayers. M/Punbound,obs and M/Punbound,pred values were compared for 166 drugs. M/Punbound,obs values were 1.5 times or more higher than M/Punbound,pred values for as many as 13 out of 16 known BCRP substrates, reconfirming BCRP as the predominant transporter contributing to secretory transfer of drugs into milk. Predictability of M/P values for selected BCRP substrates and non-substrates was improved by considering in vitro-evaluated BCRP-mediated transport relative to passive diffusion alone. The current analysis improved the predictability of drug transfer into milk, particularly for BCRP substrates, based on an exhaustive data overhaul followed by focused in vitro transport experimentation.

  11. ABCB1 gene polymorphism associated with clinical factors can predict drug-resistant tuberculosis.

    PubMed

    Pontual, Yasmin; Pacheco, Vanessa S S; Monteiro, Sérgio P; Quintana, Marcel S B; Costa, Marli J M; Rolla, Valeria C; de Castro, Liane

    2017-08-01

    Polymorphism in the ABCB1 gene encoding P-glycoprotein, a transmembrane drug efflux pump, contributes to drug resistance and has been widely studied. However, their association with rifampicin and ethambutol resistance in tuberculosis (TB) patients is still unclear. Genotype/allele/haplotype frequencies in c.1236C > T (rs1128503), c.2677G > T/A (rs2032582), and c.3435C > T (rs1045642) were obtained from 218 patients. Of these, 80 patients with rifampicin and/or ethambutol resistance were selected as the case group and 138 patients were selected for the control group through the results of their culture and drug-sensitive tests. Patients aged <18 years and HIV-positive serologic tests were excluded. ABCB1 polymorphisms were determined using a PCR direct-sequencing approach, and restriction fragment length polymorphism (RFLP). A nomogram was constructed to simulate a combined prediction of the probability of anti-TB drug resistance, with factors including genotype c.1236C > T (rs1128503) (P=0.02), clinical form (P=0.03), previous treatment (P=0.01), and skin color (P=0.03), contributing up to 90% chance of developing anti-TB drug resistance. Considering genotype analyses, CT (rs1128503) demonstrated an increased chance of anti-TB drug resistance (odds ratio (OR): 2.34, P=0.02), while the analyses for ethambutol resistance revealed an association with a rare A allele (rs2032582) (OR: 12.91, P=0.01), the haplotype TTC (OR: 5.83, P=0.05), and any haplotype containing the rare A allele (OR: 7.17, P=0.04). ABCB1 gene polymorphisms in association with others risk factors contribute to anti-TB drug resistance, mainly ethambutol. The use of the nomogram described in the present study could contribute to clinical decision-making prior to starting TB treatment. © 2017 The Author(s). Published by Portland Press Limited on behalf of the Biochemical Society.

  12. Amikacin Concentrations Predictive of Ototoxicity in Multidrug-Resistant Tuberculosis Patients

    PubMed Central

    Modongo, Chawangwa; Pasipanodya, Jotam G.; Zetola, Nicola M.; Williams, Scott M.; Sirugo, Giorgio

    2015-01-01

    Aminoglycosides, such as amikacin, are used to treat multidrug-resistant tuberculosis. However, ototoxicity is a common problem and is monitored using peak and trough amikacin concentrations based on World Health Organization recommendations. Our objective was to identify clinical factors predictive of ototoxicity using an agnostic machine learning method. We used classification and regression tree (CART) analyses to identify clinical factors, including amikacin concentration thresholds that predicted audiometry-confirmed ototoxicity among 28 multidrug-resistant pulmonary tuberculosis patients in Botswana. Amikacin concentrations were measured for all patients. The quantitative relationship between predictive factors and the probability of ototoxicity were then identified using probit analyses. The primary predictors of ototoxicity on CART analyses were cumulative days of therapy, followed by cumulative area under the concentration-time curve (AUC), which improved on the primary predictor by 87%. The area under the receiver operating curve was 0.97 on the test set. Peak and trough were not predictors in any tree. When algorithms were forced to pick peak and trough as primary predictors, the area under the receiver operating curve fell to 0.46. Probit analysis revealed that the probability of ototoxicity increased sharply starting after 6 months of therapy to near maximum at 9 months. A 10% probability of ototoxicity occurred with a threshold cumulative AUC of 87,232 days · mg · h/liter, while that of 20% occurred at 120,000 days · mg · h/liter. Thus, cumulative amikacin AUC and duration of therapy, and not peak and trough concentrations, should be used as the primary decision-making parameters to minimize the likelihood of ototoxicity in multidrug-resistant tuberculosis. PMID:26248372

  13. Predicting path from undulations for C. elegans using linear and nonlinear resistive force theory

    NASA Astrophysics Data System (ADS)

    Keaveny, Eric E.; Brown, André E. X.

    2017-04-01

    A basic issue in the physics of behaviour is the mechanical relationship between an animal and its surroundings. The model nematode C. elegans provides an excellent platform to explore this relationship due to its anatomical simplicity. Nonetheless, the physics of nematode crawling, in which the worm undulates its body to move on a wet surface, is not completely understood and the mathematical models often used to describe this phenomenon are empirical. We confirm that linear resistive force theory, one such empirical model, is effective at predicting a worm’s path from its sequence of body postures for forward crawling, reversing, and turning and for a broad range of different behavioural phenotypes observed in mutant worms. Worms recently isolated from the wild have a higher effective drag anisotropy than the laboratory-adapted strain N2 and most mutant strains. This means the wild isolates crawl with less surface slip, perhaps reflecting more efficient gaits. The drag anisotropies required to fit the observed locomotion data (70  ±  28 for the wild isolates) are significantly larger than the values measured by directly dragging worms along agar surfaces (3-10 in Rabets et al (2014 Biophys. J. 107 1980-7)). A proposed nonlinear extension of the resistive force theory model also provides accurate predictions, but does not resolve the discrepancy between the parameters required to achieve good path prediction and the experimentally measured parameters. We confirm that linear resistive force theory provides a good effective model of worm crawling that can be used in applications such as whole-animal simulations and advanced tracking algorithms, but that the nature of the physical interaction between worms and their most commonly studied laboratory substrate remains unresolved.

  14. Amikacin Concentrations Predictive of Ototoxicity in Multidrug-Resistant Tuberculosis Patients.

    PubMed

    Modongo, Chawangwa; Pasipanodya, Jotam G; Zetola, Nicola M; Williams, Scott M; Sirugo, Giorgio; Gumbo, Tawanda

    2015-10-01

    Aminoglycosides, such as amikacin, are used to treat multidrug-resistant tuberculosis. However, ototoxicity is a common problem and is monitored using peak and trough amikacin concentrations based on World Health Organization recommendations. Our objective was to identify clinical factors predictive of ototoxicity using an agnostic machine learning method. We used classification and regression tree (CART) analyses to identify clinical factors, including amikacin concentration thresholds that predicted audiometry-confirmed ototoxicity among 28 multidrug-resistant pulmonary tuberculosis patients in Botswana. Amikacin concentrations were measured for all patients. The quantitative relationship between predictive factors and the probability of ototoxicity were then identified using probit analyses. The primary predictors of ototoxicity on CART analyses were cumulative days of therapy, followed by cumulative area under the concentration-time curve (AUC), which improved on the primary predictor by 87%. The area under the receiver operating curve was 0.97 on the test set. Peak and trough were not predictors in any tree. When algorithms were forced to pick peak and trough as primary predictors, the area under the receiver operating curve fell to 0.46. Probit analysis revealed that the probability of ototoxicity increased sharply starting after 6 months of therapy to near maximum at 9 months. A 10% probability of ototoxicity occurred with a threshold cumulative AUC of 87,232 days · mg · h/liter, while that of 20% occurred at 120,000 days · mg · h/liter. Thus, cumulative amikacin AUC and duration of therapy, and not peak and trough concentrations, should be used as the primary decision-making parameters to minimize the likelihood of ototoxicity in multidrug-resistant tuberculosis. Copyright © 2015, Modongo et al.

  15. MEASUREMENT AND PREDICTION OF THE RESISTIVITY OF ASH/SORBENT MIXTURES PRODUCED BY SULFUR OXIDE CONTROL PROCESSES

    EPA Science Inventory

    The report describes the development of (1) a modified procedure for obtaining consistent and reproducible laboratory resistivity values for mixtures of coal fly ash and partially spent sorbent, and (2) an approach for predicting resistivity based on the chemical composition of t...

  16. MEASUREMENT AND PREDICTION OF THE RESISTIVITY OF ASH/SORBENT MIXTURES PRODUCED BY SULFUR OXIDE CONTROL PROCESSES

    EPA Science Inventory

    The report describes the development of (1) a modified procedure for obtaining consistent and reproducible laboratory resistivity values for mixtures of coal fly ash and partially spent sorbent, and (2) an approach for predicting resistivity based on the chemical composition of t...

  17. Free Testosterone During Androgen Deprivation Therapy Predicts Castration-Resistant Progression Better Than Total Testosterone.

    PubMed

    Regis, Lucas; Planas, Jacques; Carles, Joan; Maldonado, Xavier; Comas, Inma; Ferrer, Roser; Morote, Juan

    2017-01-01

    The optimal degree of testosterone suppression in patients with prostate cancer undergoing androgen deprivation therapy remains in question. Furthermore, serum free testosterone, which is the active form of testosterone, seems to correlate with intraprostatic testosterone. Here we compared free and total serum testosterone as predictors of survival free of castration resistance. Total testosterone (chemiluminescent assay, lower sensitivity 10 ng/dl) and free testosterone (analogue-ligand radioimmunoassay, lower sensitivity 0.05 pg/ml) were determined at 6 months of LHRH agonist treatment in a prospective cohort of 126 patients with prostate cancer. During a mean follow-up of 67 months (9-120), 75 (59.5%) events of castration-resistant progression were identified. Multivariate analysis and survival analysis according to total testosterone cutoffs of 50, 32, and 20 ng/dl, and free testosterone cutoffs of 1.7, 1.1, and 0.7 pg/ml were performed. Metastatic spread was the most powerful predictor of castration resistance, HR: 2.09 (95%CI: 1.18-3.72), P = 0.012. Gleason score, baseline PSA and PSA at 6 months were also independents predictors, but not free and total testosterone. Stratified analysis was conducted on the basis of the status of metastatic diseases and free testosterone was found to be an independent predictor of survival free of castration resistance in the subgroup of patients without metastasis, HR: 2.12 (95%CI: 1.16-3.85), P = 0.014. The lowest threshold of free testosterone which showed significant differences was 1.7 pg/ml, P = 0.003. Free testosterone at 6 months of LHRH agonist treatment seems to be a better surrogate than total testosterone to predict castration resistance in no metastatic prostate cancer patients. Prostate 77:114-120, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

  18. Micromechanical predictions of crack initiation, propagation and crack growth resistance in boron/aluminum composites

    NASA Technical Reports Server (NTRS)

    Mahishi, J. M.; Adams, D. F.

    1982-01-01

    An elastoplastic, axisymmetric finite element model has been used to predict the initiation and propagation of a crack in a composite model consisting of a single broken boron fiber embedded in an annular sheath of aluminum matrix. The accuracy of the axisymmetric finite element model for crack problems has been established by solving the classical problem of a penny-shaped crack in a thick cylindrical rod under axial tension. Also, the stress intensity factors predicted by the present numerical model are compared with continuum results. A constant displacement boundary condition applied during an increment of crack growth permits a substantial amount of stable crack growth in the matrix material. The concept of Crack Growth Resistance Curves (KR-curves) has been used to determine the point of crack instability

  19. Genome-wide gene expression profiling to predict resistance to anthracyclines in breast cancer patients

    PubMed Central

    Haibe-Kains, B.; Desmedt, C.; Di Leo, A.; Azambuja, E.; Larsimont, D.; Selleslags, J.; Delaloge, S.; Duhem, C.; Kains, J.P.; Carly, B.; Maerevoet, M.; Vindevoghel, A.; Rouas, G.; Lallemand, F.; Durbecq, V.; Cardoso, F.; Salgado, R.; Rovere, R.; Bontempi, G.; Michiels, S.; Buyse, M.; Nogaret, J.M.; Qi, Y.; Symmans, F.; Pusztai, L.; D'Hondt, V.; Piccart-Gebhart, M.; Sotiriou, C.

    2013-01-01

    Validated biomarkers predictive of response/resistance to anthracyclines in breast cancer are currently lacking. The neoadjuvant Trial of Principle (TOP) study, in which patients with estrogen receptor (ER)–negative tumors were treated with anthracycline (epirubicin) monotherapy, was specifically designed to evaluate the predictive value of topoisomerase II-alpha (TOP2A) and develop a gene expression signature to identify those patients who do not benefit from anthracyclines. Here we describe in details the contents and quality controls for the gene expression and clinical data associated with the study published by Desmedt and colleagues in the Journal of Clinical Oncology in 2011 (Desmedt et al., 2011). We also provide R code to easily access the data and perform the quality controls and basic analyses relevant to this dataset. PMID:26484051

  20. Implementation of model predictive control for resistive wall mode stabilization on EXTRAP T2R

    NASA Astrophysics Data System (ADS)

    Setiadi, A. C.; Brunsell, P. R.; Frassinetti, L.

    2015-10-01

    A model predictive control (MPC) method for stabilization of the resistive wall mode (RWM) in the EXTRAP T2R reversed-field pinch is presented. The system identification technique is used to obtain a linearized empirical model of EXTRAP T2R. MPC employs the model for prediction and computes optimal control inputs that satisfy performance criterion. The use of a linearized form of the model allows for compact formulation of MPC, implemented on a millisecond timescale, that can be used for real-time control. The design allows the user to arbitrarily suppress any selected Fourier mode. The experimental results from EXTRAP T2R show that the designed and implemented MPC successfully stabilizes the RWM.

  1. In Silico Prediction of Inhibition of Promiscuous Breast Cancer Resistance Protein (BCRP/ABCG2)

    PubMed Central

    Ding, Yi-Lung; Shih, Yu-Hsuan; Tsai, Fu-Yuan; Leong, Max K.

    2014-01-01

    Background Breast cancer resistant protein has an essential role in active transport of endogenous substances and xenobiotics across extracellular and intracellular membranes along with P-glycoprotein. It also plays a major role in multiple drug resistance and permeation of blood-brain barrier. Therefore, it is of great importance to derive theoretical models to predict the inhibition of both transporters in the process of drug discovery and development. Hitherto, very limited BCRP inhibition predictive models have been proposed as compared with its P-gp counterpart. Methodology/Principal Findings An in silico BCRP inhibition model was developed in this study using the pharmacophore ensemble/support vector machine scheme to take into account the promiscuous nature of BCRP. The predictions by the PhE/SVM model were found to be in good agreement with the observed values for those molecules in the training set (n = 22, r2 = 0.82,  = 0.73, RMSE  =  0.40, s = 0.24), test set (n = 97, q2 = 0.75–0.89, RMSE  = 0.31, s = 0.21), and outlier set (n = 16, q2 = 0.72–0.91, RMSE  =  0.29, s = 0.17). When subjected to a variety of statistical validations, the developed PhE/SVM model consistently met the most stringent criteria. A mock test by HIV protease inhibitors also asserted its predictivity. Conclusions/Significance It was found that this accurate, fast, and robust PhE/SVM model can be employed to predict the BCRP inhibition of structurally diverse molecules that otherwise cannot be carried out by any other methods in a high-throughput fashion to design therapeutic agents with insignificant drug toxicity and unfavorable drug–drug interactions mediated by BCRP to enhance clinical efficacy and/or circumvent drug resistance. PMID:24614353

  2. An experimental and computational investigation of electrical resistivity imaging for prediction ahead of tunnel boring machines

    NASA Astrophysics Data System (ADS)

    Schaeffer, Kevin P.

    Tunnel boring machines (TBMs) are routinely used for the excavation of tunnels across a range of ground conditions, from hard rock to soft ground. In complex ground conditions and in urban environments, the TBM susceptible to damage due to uncertainty of what lies ahead of the tunnel face. The research presented here explores the application of electrical resistivity theory for use in the TBM tunneling environment to detect changing conditions ahead of the machine. Electrical resistivity offers a real-time and continuous imaging solution to increase the resolution of information along the tunnel alignment and may even unveil previously unknown geologic or man-made features ahead of the TBM. The studies presented herein, break down the tunneling environment and the electrical system to understand how its fundamental parameters can be isolated and tested, identifying how they influence the ability to predict changes ahead of the tunnel face. A proof-of-concept, scaled experimental model was constructed in order assess the ability of the model to predict a metal pipe (or rod) ahead of face as the TBM excavates through a saturated sand. The model shows that a prediction of up to three tunnel diameters could be achieved, but the unique presence of the pipe (or rod) could not be concluded with certainty. Full scale finite element models were developed in order evaluate the various influences on the ability to detect changing conditions ahead of the face. Results show that TBM/tunnel geometry, TBM type, and electrode geometry can drastically influence prediction ahead of the face by tens of meters. In certain conditions (i.e., small TBM diameter, low cover depth, large material contrasts), changes can be detected over 100 meters in front of the TBM. Various electrode arrays were considered and show that in order to better detect more finite differences (e.g., boulder, lens, pipe), the use of individual cutting tools as electrodes is highly advantageous to increase spatial

  3. Can serum vaspin levels predict clomiphene resistance in infertile women with PCOS?

    PubMed

    Dogan, Keziban; Ekin, Murat; Helvacioğlu, Çağlar; Yaşar, Levent

    2017-10-01

    To determine whether serum vaspin levels can predict the success of ovulation induction and clomiphene resistance in anovulatory women with PCOS. We designed a prospective case control study. The study population (n=49) was composed of infertile women with PCOS who underwent ovulation induction with clomiphene citrate. Patients were divided into two groups based on their treatment response. Group I consisted of patients with failed ovulation induction, and group II consisted of patients with successful ovulation induction. The study group characteristics, including age, BMI, waist-to-hip ratio, parity, hormone profiles, fasting insulin and glucose levels, HOMA-IR, triglycerides, and cholesterol and serum vaspin levels, were compared between the study groups. There were 29 patients in Group I with failed ovulation induction (59.2%), and Group II consisted of 20 patients with successful ovulation induction (40.8%). No differences in characteristics were found. However, serum vaspin levels were significantly lower in responders achieving ovulation (p=0.001; p<0.01). At a vaspin level of 3.74, the sensitivity, specificity, positive predictive and negative predictive values were 90%, 72.4%, 69.2% and 91.3%, respectively. The odds ratio was determined to be 14.87 (95% CI: 3.41-64.88) as the cut-off point. No significant correlation was found in serum vaspin measurements between pregnant and non-pregnant patients who had achieved successful ovulation induction (p=0.5). Serum vaspin level may be a useful marker for the prediction of ovulation induction success in treatment with clomiphene citrate, and increased vaspin levels (≥3.74ng/mL) are correlated with clomiphene resistance in patients with PCOS according to our study results. Copyright © 2017 Elsevier B.V. All rights reserved.

  4. Prevalence dependent calibration of a predictive model for nasal carriage of methicillin-resistant Staphylococcus aureus

    PubMed Central

    2013-01-01

    Background Published models predicting nasal colonization with Methicillin-resistant Staphylococcus aureus among hospital admissions predominantly focus on separation of carriers from non-carriers and are frequently evaluated using measures of discrimination. In contrast, accurate estimation of carriage probability, which may inform decisions regarding treatment and infection control, is rarely assessed. Furthermore, no published models adjust for MRSA prevalence. Methods Using logistic regression, a scoring system (values from 0 to 200) predicting nasal carriage of MRSA was created using a derivation cohort of 3091 individuals admitted to a European tertiary referral center between July 2007 and March 2008. The expected positive predictive value of a rapid diagnostic test (GeneOhm, Becton & Dickinson Co.) was modeled using non-linear regression according to score. Models were validated on a second cohort from the same hospital consisting of 2043 patients admitted between August 2008 and January 2012. Our suggested correction score for prevalence was proportional to the log-transformed odds ratio between cohorts. Calibration before and after correction, i.e. accurate classification into arbitrary strata, was assessed with the Hosmer-Lemeshow-Test. Results Treating culture as reference, the rapid diagnostic test had positive predictive values of 64.8% and 54.0% in derivation and internal validation corhorts with prevalences of 2.3% and 1.7%, respectively. In addition to low prevalence, low positive predictive values were due to high proportion (> 66%) of mecA-negative Staphylococcus aureus among false positive results. Age, nursing home residence, admission through the medical emergency department, and ICD-10-GM admission diagnoses starting with “A” or “J” were associated with MRSA carriage and were thus included in the scoring system, which showed good calibration in predicting probability of carriage and the rapid diagnostic test’s expected positive

  5. A model for predicting nosocomial carbapenem-resistant Klebsiella pneumoniae infection

    PubMed Central

    Yang, Duo; Xie, Zeqiang; Xin, Xuli; Xue, Wenying; Zhang, Man

    2016-01-01

    Mortality associated with infections due to carbapenem-resistant Klebsiella pneumoniae (CR-KP) is high and the infections need to be predicted early. The risk factors for CR-KP infection are heterogeneous. The aim of the present study was to construct a model allowing for the early prediction of CR-KP infection. Nosocomial infections due to K. pneumoniae were evaluated retrospectively over a 2-year period. The case cohort consisted of 370 inpatients with CR-KP infection. For each case enrolled, two matched controls with no CR-KP infection during their hospitalization were randomly selected. Matching involved month of admission, ward, as well as interval days. The Vitek 2 system was used for identification of isolates and antimicrobial susceptibility testing. General linear model with logistic regression was used to identify possible risk factors. The predicted power of the model was expressed as the area under the receiver-operating characteristic curve. Age, male gender, with cardiovascular disease, hospital stay, recent admission to intensive care unit, indwelling urinary catheter, mechanical ventilation, recent β-lactam-β-lactamase inhibitors, fourth-generation cephalosporins and/or carbapenems therapy were independent risk factors for CR-KP infection. Models predicting CR-KP infection developed by cumulative risk factors exhibited good power, with areas under the receiver-operating characteristic curves of 0.902 [95% confidence interval (CI), 0.883–0.920; P<0.001] and 0.899 (95% CI, 0.877–0.921; P<0.001) after filtering by age (≥70 years). The Yonden index was at the maximum when the cumulative risk factors were ≥3 in the two prediction models. The results show that the prediction model developed in the present study might be useful for controlling infections caused by CR-KP strains. PMID:27699021

  6. Circulating Cytokines Predict the Development of Insulin Resistance in a Prospective Finnish Population Cohort.

    PubMed

    Santalahti, Kristiina; Maksimow, Mikael; Airola, Antti; Pahikkala, Tapio; Hutri-Kähönen, Nina; Jalkanen, Sirpa; Raitakari, Olli T; Salmi, Marko

    2016-09-01

    Metabolic inflammation contributes to the development of insulin resistance (IR), but the roles of different inflammatory and other cytokines in this process remain unclear. We aimed at analyzing the value of different cytokines in predicting future IR. We measured the serum concentrations of 48 cytokines from a nationwide cohort of 2200 Finns (the Cardiovascular Risk in Young Finns Study), and analyzed their role as independent risk factors for predicting the development of IR 4 years later. We used cross-sectional regression analysis adjusted for known IR risk factors (high age, body mass index, systolic blood pressure, triglycerides, smoking, physical inactivity, and low high-density lipoprotein cholesterol), C-reactive protein and 37 cytokines to find the determinants of continuous baseline IR (defined by homeostatic model assessment). A logistic regression model adjusted for the known risk factors, baseline IR, and 37 cytokines was used to predict the future IR. Several cytokines, often in a sex-dependent manner, remained as independent determinants of current IR. In men, none of the cytokines was an independent predictive risk marker of future IR. In women, in contrast, IL-17 (odds ratio, 1.42 for 1-SD change in ln-transformed IL-17) and IL-18 (odds ratio, 1.37) were independently associated with the future IR. IL-17 levels also independently predicted the development of incident future IR (odds ratio, 1.48). The systemic levels of the T helper 1 cell cytokine IL-18 and the T helper 17 cell cytokine IL-17 thus may have value in predicting future insulin sensitivity in women independently of classical IR risk factors.

  7. Prediction of Corrosion Resistance of Concrete Containing Natural Pozzolan from Compressive Strength

    NASA Astrophysics Data System (ADS)

    al-Swaidani, A. M.; Ismat, R.; Diyab, M. E.; Aliyan, S. D.

    2015-11-01

    A lot of Reinforced Concrete (RC) structures in Syria have suffered from reinforcement corrosion which shortened significantly their service lives. Probably, one of the most effective approaches to make concrete structures more durable and concrete industry on the whole - more sustainable is to substitute pozzolan for a portion of Portland cement (PC). Syria is relatively rich in natural pozzolan. In the study, in order to predict the corrosion resistance from compressive strength, concrete specimens were produced with seven cement types: one plain Portland cement (control) and six natural pozzolan-based cements with replacement levels ranging from 10 to 35%. The development of the compressive strengths of concrete cube specimens with curing time has been investigated. Chloride penetrability has also been evaluated for all concrete mixes after three curing times of 7, 28 and 90 days. The effect on resistance of concrete against damage caused by corrosion of the embedded reinforcing steel has been investigated using an accelerated corrosion test by impressing a constant anodic potential for 7, 28 and 90 days curing. Test results have been statistically analysed and correlation equations relating compressive strength and corrosion performance have been developed. Significant correlations have been noted between the compressive strength and both rapid chloride penetrability and corrosion initiation times. So, this prediction could be reliable in concrete mix design when using natural pozzolan as cement replacement.

  8. On the TRAIL to successful cancer therapy? Predicting and counteracting resistance against TRAIL-based therapeutics.

    PubMed

    Dimberg, L Y; Anderson, C K; Camidge, R; Behbakht, K; Thorburn, A; Ford, H L

    2013-03-14

    Tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) and agonistic antibodies against TRAIL death receptors (DR) kill tumor cells while causing virtually no damage to normal cells. Several novel drugs targeting TRAIL receptors are currently in clinical trials. However, TRAIL resistance is a common obstacle in TRAIL-based therapy and limits the efficiency of these drugs. In this review article we discuss different mechanisms of TRAIL resistance, and how they can be predicted and therapeutically circumvented. In addition, we provide a brief overview of all TRAIL-based clinical trials conducted so far. It is apparent that although the effects of TRAIL therapy are disappointingly modest overall, a small subset of patients responds very well to TRAIL. We argue that the true potential of targeting TRAIL DRs in cancer can only be reached when we find efficient ways to select for those patients that are most likely to benefit from the treatment. To achieve this, it is crucial to identify biomarkers that can help us predict TRAIL sensitivity.

  9. Lipid profiling identifies a triacylglycerol signature of insulin resistance and improves diabetes prediction in humans

    PubMed Central

    Rhee, Eugene P.; Cheng, Susan; Larson, Martin G.; Walford, Geoffrey A.; Lewis, Gregory D.; McCabe, Elizabeth; Yang, Elaine; Farrell, Laurie; Fox, Caroline S.; O’Donnell, Christopher J.; Carr, Steven A.; Vasan, Ramachandran S.; Florez, Jose C.; Clish, Clary B.; Wang, Thomas J.; Gerszten, Robert E.

    2011-01-01

    Dyslipidemia is an independent risk factor for type 2 diabetes, although exactly which of the many plasma lipids contribute to this remains unclear. We therefore investigated whether lipid profiling can inform diabetes prediction by performing liquid chromatography/mass spectrometry–based lipid profiling in 189 individuals who developed type 2 diabetes and 189 matched disease-free individuals, with over 12 years of follow up in the Framingham Heart Study. We found that lipids of lower carbon number and double bond content were associated with an increased risk of diabetes, whereas lipids of higher carbon number and double bond content were associated with decreased risk. This pattern was strongest for triacylglycerols (TAGs) and persisted after multivariable adjustment for age, sex, BMI, fasting glucose, fasting insulin, total triglycerides, and HDL cholesterol. A combination of 2 TAGs further improved diabetes prediction. To explore potential mechanisms that modulate the distribution of plasma lipids, we performed lipid profiling during oral glucose tolerance testing, pharmacologic interventions, and acute exercise testing. Levels of TAGs associated with increased risk for diabetes decreased in response to insulin action and were elevated in the setting of insulin resistance. Conversely, levels of TAGs associated with decreased diabetes risk rose in response to insulin and were poorly correlated with insulin resistance. These studies identify a relationship between lipid acyl chain content and diabetes risk and demonstrate how lipid profiling could aid in clinical risk assessment. PMID:21403394

  10. Genetic diversity predicts pathogen resistance and cell-mediated immunocompetence in house finches

    PubMed Central

    Hawley, Dana M; Sydenstricker, Keila V; Kollias, George V; Dhondt, André A

    2005-01-01

    Evidence is accumulating that genetic variation within individual hosts can influence their susceptibility to pathogens. However, there have been few opportunities to experimentally test this relationship, particularly within outbred populations of non-domestic vertebrates. We performed a standardized pathogen challenge in house finches (Carpodacus mexicanus) to test whether multilocus heterozygosity across 12 microsatellite loci predicts resistance to a recently emerged strain of the bacterial pathogen, Mycoplasma gallisepticum (MG). We simultaneously tested whether the relationship between heterozygosity and pathogen susceptibility is mediated by differences in cell-mediated or humoral immunocompetence. We inoculated 40 house finches with MG under identical conditions and assayed both humoral and cell-mediated components of the immune response. Heterozygous house finches developed less severe disease when infected with MG, and they mounted stronger cell-mediated immune responses to phytohaemagglutinin. Differences in cell-mediated immunocompetence may, therefore, partly explain why more heterozygous house finches show greater resistance to MG. Overall, our results underscore the importance of multilocus heterozygosity for individual pathogen resistance and immunity. PMID:17148199

  11. The application of artificial neural networks for phenotypic drug resistance prediction: evaluation and comparison with other interpretation systems.

    PubMed

    Pasomsub, Ekawat; Sukasem, Chonlaphat; Sungkanuparph, Somnuek; Kijsirikul, Boonserm; Chantratita, Wasun

    2010-03-01

    Although phenotypic resistance testing provides more direct measurement of antiretroviral drug resistance than genotypic testing, it is costly and time-consuming. However, genotypic resistance testing has the advantages of being simpler and more accessible, and it might be possible to use the data obtained for predicting quantitative drug susceptibility to interpret complex mutation combinations. This study applied the Artificial Neural Network (ANN) system to predict the HIV-1 resistance phenotype from the genotype. A total of 7,598 pairs of HIV-1 sequences, with their corresponding phenotypic fold change values for 14 antiretroviral drugs, were trained, validated, and tested in ANN modeling. The results were compared with the HIV-SEQ and Geno2pheno interpretation systems. The prediction performance of the ANN models was measured by 10-fold cross-validation. The results indicated that by using the ANN, with an associated set of amino acid positions known to influence drug resistance for individual antiretroviral drugs, drug resistance was accurately predicted and generalized for individual HIV-1 subtypes. Therefore, high correlation with the experimental phenotype may help physicians choose optimal therapeutic regimens that might be an option, or supporting system, of FDA-approved genotypic resistance testing in heavily treatment-experienced patients.

  12. Can carbapenem-resistant enterobacteriaceae susceptibility results obtained from surveillance cultures predict the susceptibility of a clinical carbapenem-resistant enterobacteriaceae?

    PubMed

    Perez, Leandro Reus Rodrigues; Rodrigues, Diógenes; Dias, Cícero

    2016-08-01

    We evaluated the susceptibility profile of a colonizing carbapenem-resistant enterobacteriaceae to predict its susceptibility when recovered from a clinical specimen. An overall agreement of 88.7% (517 out of 583; 95% confidence interval, 85.8%-91.0%) was observed for the combinations of 11 antibiotics with 53 pairs of Klebsiella pneumoniae carbapenemase-producing K pneumoniae (the only carbapenem-resistant enterobacteriaceae detected). Very major errors were observed mainly for aminoglycoside agents and colistin, limiting the predictability of the susceptibility profile for these clinical isolates.

  13. Stochastic Integration of Crosshole Resistivity and Tracer Test Data for Improving Hydrological Predictions

    NASA Astrophysics Data System (ADS)

    Irving, J.; Singha, K.; Holliger, K.

    2008-12-01

    Quantifying the local configuration of hydraulic conductivity (K) in heterogeneous environments is essential for accurate predictions of subsurface contaminant transport. Although concentration data from tracer tests can be useful for providing estimates of K in a region, such data have too small a support scale to determine continuous K distributions that are required for reliable future predictions. We address this issue by introducing dynamic geophysical data, collected during tracer testing, into the subsurface characterization problem. Specifically, we investigate the use electrical resistivity tomography (ERT) measurements, collected in time during the course of a saline tracer experiment, to help map permeable pathways and reduce the non-uniqueness associated with estimating K from tracer measurements alone. Rather than invert the resistivity measurements independently from the tracer test data to create a deterministic map of subsurface properties as has been done in previous studies, we examine the use of Markov-chain Monte Carlo (McMC) methods to jointly invert these data within a stochastic framework. The benefits of this methodology are that (i) we skip the intermediate step found in uncoupled inversion strategies of trying to estimate the spatial distribution of geophysical properties in time, and (ii) multiple realizations of K are generated, according to the posterior probability distribution consistent with all measured data, which allows us to explore statistically the potential benefits of including the geophysical measurements. In this work, we consider a relatively simple, heterogeneous, binary distribution of K values in a saturated zone setting as the 'true model'. We simulate groundwater flow and tracer transport through this K field, and also electrical resistivity measurements during the tracer experiment, to produce the 'measured data'. We then set out to determine, using the coupled McMC inversion strategy, distributions of K that are

  14. Prediction of permeability of cement-admixed soft clay using resistivity and time-domain IP measurements

    NASA Astrophysics Data System (ADS)

    Latt, Khin M. M.; Giao, P. H.

    2017-02-01

    Permeability is one of the most important petrophysical parameters, which unfortunately is quite difficult to be tested and estimated, particularly for the fine-grained soils and mixed soils. Prediction of permeability based on geophysical measurements is currently one of the most challenging issues in petrophysics. There have been recently reported some empirical relationships between permeability, resistivity and spectral induced polarization (SIP) parameters for a porous medium. However, the disadvantage of this approach is the very scarcity of SIP data as most of practical measurements are time-domain IP. In this study, a detailed overview of permeability prediction models using resistivity and spectral IP data was made. More than that, an innovative approach using resistivity and time-domain IP measurements to predict permeability of cement-admixed Bangkok clay was proposed and successfully applied for tested samples based on measurements of resistivity and time-domain IP data. A good amount of geotechnical and geophysical tests was conducted to investigate the time-dependent development of strength, porosity, and permeability of cement-mixed Bangkok soft clay samples during a 28-day curing process. The permeability predicted by resistivity and chargeability model matched well with permeability measured by consolidation testing. In addition, a series of correlations between unconfined compressive strength, porosity and permeability as measured by geotechnical testing and resistivity and chargeability as measured by geophysical testing were found.

  15. Nestling erythrocyte resistance to oxidative stress predicts fledging success but not local recruitment in a wild bird.

    PubMed

    Losdat, Sylvain; Helfenstein, Fabrice; Blount, Jonathan D; Marri, Viviana; Maronde, Lea; Richner, Heinz

    2013-02-23

    Stressful conditions experienced by individuals during their early development have long-term consequences on various life-history traits such as survival until first reproduction. Oxidative stress has been shown to affect various fitness-related traits and to influence key evolutionary trade-offs but whether an individual's ability to resist oxidative stress in early life affects its survival has rarely been tested. In the present study, we used four years of data obtained from a free-living great tit population (Parus major; n = 1658 offspring) to test whether pre-fledging resistance to oxidative stress, measured as erythrocyte resistance to oxidative stress and oxidative damage to lipids, predicted fledging success and local recruitment. Fledging success and local recruitment, both major correlates of survival, were primarily influenced by offspring body mass prior to fledging. We found that pre-fledging erythrocyte resistance to oxidative stress predicted fledging success, suggesting that individual resistance to oxidative stress is related to short-term survival. However, local recruitment was not influenced by pre-fledging erythrocyte resistance to oxidative stress or oxidative damage. Our results suggest that an individual ability to resist oxidative stress at the offspring stage predicts short-term survival but does not influence survival later in life.

  16. Genome-wide association and genomic prediction of resistance to maize lethal necrosis disease in tropical maize germplasm.

    PubMed

    Gowda, Manje; Das, Biswanath; Makumbi, Dan; Babu, Raman; Semagn, Kassa; Mahuku, George; Olsen, Michael S; Bright, Jumbo M; Beyene, Yoseph; Prasanna, Boddupalli M

    2015-10-01

    Genome-wide association analysis in tropical and subtropical maize germplasm revealed that MLND resistance is influenced by multiple genomic regions with small to medium effects. The maize lethal necrosis disease (MLND) caused by synergistic interaction of Maize chlorotic mottle virus and Sugarcane mosaic virus, and has emerged as a serious threat to maize production in eastern Africa since 2011. Our objective was to gain insights into the genetic architecture underlying the resistance to MLND by genome-wide association study (GWAS) and genomic selection. We used two association mapping (AM) panels comprising a total of 615 diverse tropical/subtropical maize inbred lines. All the lines were evaluated against MLND under artificial inoculation. Both the panels were genotyped using genotyping-by-sequencing. Phenotypic variation for MLND resistance was significant and heritability was moderately high in both the panels. Few promising lines with high resistance to MLND were identified to be used as potential donors. GWAS revealed 24 SNPs that were significantly associated (P < 3 × 10(-5)) with MLND resistance. These SNPs are located within or adjacent to 20 putative candidate genes that are associated with plant disease resistance. Ridge regression best linear unbiased prediction with five-fold cross-validation revealed higher prediction accuracy for IMAS-AM panel (0.56) over DTMA-AM (0.36) panel. The prediction accuracy for both within and across panels is promising; inclusion of MLND resistance associated SNPs into the prediction model further improved the accuracy. Overall, the study revealed that resistance to MLND is controlled by multiple loci with small to medium effects and the SNPs identified by GWAS can be used as potential candidates in MLND resistance breeding program.

  17. Body Size Predicts Cardiac and Vascular Resistance Effects on Men's and Women's Blood Pressure.

    PubMed

    Evans, Joyce M; Wang, Siqi; Greb, Christopher; Kostas, Vladimir; Knapp, Charles F; Zhang, Qingguang; Roemmele, Eric S; Stenger, Michael B; Randall, David C

    2017-01-01

    Key Points Summary We report how blood pressure, cardiac output and vascular resistance are related to height, weight, body surface area (BSA), and body mass index (BMI) in healthy young adults at supine rest and standing.Much inter-subject variability in young adult's blood pressure, currently attributed to health status, may actually result from inter-individual body size differences.Each cardiovascular variable is linearly related to height, weight and/or BSA (more than to BMI).When supine, cardiac output is positively related, while vascular resistance is negatively related, to body size. Upon standing, the change in vascular resistance is positively related to size.The height/weight relationships of cardiac output and vascular resistance to body size are responsible for blood pressure relationships to body size.These basic components of blood pressure could help distinguish normal from abnormal blood pressures in young adults by providing a more effective scaling mechanism. Introduction: Effects of body size on inter-subject blood pressure (BP) variability are not well established in adults. We hypothesized that relationships linking stroke volume (SV), cardiac output (CO), and total peripheral resistance (TPR) with body size would account for a significant fraction of inter-subject BP variability. Methods: Thirty-four young, healthy adults (19 men, 15 women) participated in 38 stand tests during which brachial artery BP, heart rate, SV, CO, TPR, and indexes of body size were measured/calculated. Results: Steady state diastolic arterial BP was not significantly correlated with any index of body size when subjects were supine. However, upon standing, the more the subject weighed, or the taller s/he was, the greater the increase in diastolic pressure. Systolic pressure strongly correlated with body weight and height both supine and standing. Diastolic and systolic BP were more strongly related to height, weight and body surface area than to body mass index. When

  18. Bifurcation of resistive wall mode dynamics predicted by magnetohydrodynamic-kinetic hybrid theory

    SciTech Connect

    Yang, S. X.; Wang, Z. X.; Wang, S.; Hao, G. Z. Song, X. M.; Wang, A. K.; Liu, Y. Q.

    2015-09-15

    The magnetohydrodynamic-kinetic hybrid theory has been extensively and successfully applied for interpreting experimental observations of macroscopic, low frequency instabilities, such as the resistive wall mode, in fusion plasmas. In this work, it is discovered that an analytic version of the hybrid formulation predicts a bifurcation of the mode dynamics while varying certain physical parameters of the plasma, such as the thermal particle collisionality or the ratio of the thermal ion to electron temperatures. This bifurcation can robustly occur under reasonably large parameter spaces as well as with different assumptions, for instance, on the particle collision model. Qualitatively similar bifurcation features are also observed in full toroidal computations presented in this work, based on a non-perturbative hybrid formulation.

  19. Gene signatures of drug resistance predict patient survival in colorectal cancer

    PubMed Central

    Zheng, Y; Zhou, J; Tong, Y

    2015-01-01

    Different combinations of 5-fluorouracil (5-FU), oxaliplatin, irinotecan and other newly developed agents have been used to treat colorectal cancer. Despite the advent of new treatment regimens, the 5-year survival rate for metastatic colorectal cancer remains low (~10%). Knowing the drug sensitivity of a given tumor for a particular agent could significantly impact decision making and treatment planning. Biomarkers are proven to be successful in characterizing patients into different response groups. Using survival prediction analysis, we have identified three independent gene signatures, which are associated with sensitivity of colorectal cancer cells to 5-FU, oxaliplatin or irinotecan. On the basis of the three gene signatures, three score systems were developed to stratify patients from sensitive to resistance. These score systems exhibited robustness in stratify patients in two independent clinical studies. Patients with high scores in all three drugs exhibited the lowest survival. PMID:25179828

  20. Oxacillin disk diffusion testing for the prediction of penicillin resistance in Streptococcus pneumoniae.

    PubMed

    Horna, Gertrudis; Molero, María L; Benites, Liliana; Roman, Sigri; Carbajal, Luz; Mercado, Erik; Castillo, María E; Zerpa, Rito; Chaparro, Eduardo; Hernandez, Roger; Silva, Wilda; Campos, Francisco; Saenz, Andy; Reyes, Isabel; Villalobos, Alex; Ochoa, Theresa J

    2016-08-01

    Objective To 1) describe the correlation between the zones of inhibition in 1-µg oxacillin disk diffusion (ODD) tests and penicillin and ceftriaxone minimum inhibitory concentrations (MICs) of meningeal and non-meningeal strains of Streptococcus pneumoniae and 2) evaluate the usefulness of the ODD test as a predictor of susceptibility to penicillin in S. pneumoniae and as a quick and cost-effective method easily implemented in a routine clinical laboratory setting. Methods S. pneumoniae isolates from healthy nasopharyngeal carriers less than 2 years old, obtained in a multicentric cross-sectional study conducted in various Peruvian hospitals and health centers from 2007 to 2009, were analyzed. Using Clinical and Laboratory Standards Institute (CLSI) breakpoints, the correlation between the zones of inhibition of the ODD test and the MICs of penicillin and ceftriaxone was determined. Results Of the 571 S. pneumoniae isolates, 314 (55%) showed resistance to penicillin (MIC ≥ 0.12 µg/mL) and 124 (21.7%) showed resistance to ceftriaxone (MIC ≥ 1 µg/mL). Comparison of the ODD test zones of inhibition and the penicillin MICs, using the CLSI meningeal breakpoints, showed good correlation (Cohen's kappa coefficient = 0.8239). Conclusions There was good correlation between ODD zones of inhibition and penicillin meningeal breakpoints but weak correlation between the ODD results and non-meningeal breakpoints for both penicillin and ceftriaxone. Therefore, the ODD test appears to be a useful tool for predicting penicillin resistance in cases of meningeal strains of S. pneumoniae, particularly in low- and middle- income countries, where MIC determination is not routinely available.

  1. Loss of Cytoplasmic CDK1 Predicts Poor Survival in Human Lung Cancer and Confers Chemotherapeutic Resistance

    PubMed Central

    Zhang, Chunyu; Elkahloun, Abdel G.; Robertson, Matthew; Gills, Joell J.; Tsurutani, Junji; Shih, Joanna H.; Fukuoka, Junya; Hollander, M. Christine; Harris, Curtis C.; Travis, William D.; Jen, Jin; Dennis, Phillip A.

    2011-01-01

    The dismal lethality of lung cancer is due to late stage at diagnosis and inherent therapeutic resistance. The incorporation of targeted therapies has modestly improved clinical outcomes, but the identification of new targets could further improve clinical outcomes by guiding stratification of poor-risk early stage patients and individualizing therapeutic choices. We hypothesized that a sequential, combined microarray approach would be valuable to identify and validate new targets in lung cancer. We profiled gene expression signatures during lung epithelial cell immortalization and transformation, and showed that genes involved in mitosis were progressively enhanced in carcinogenesis. 28 genes were validated by immunoblotting and 4 genes were further evaluated in non-small cell lung cancer tissue microarrays. Although CDK1 was highly expressed in tumor tissues, its loss from the cytoplasm unexpectedly predicted poor survival and conferred resistance to chemotherapy in multiple cell lines, especially microtubule-directed agents. An analysis of expression of CDK1 and CDK1-associated genes in the NCI60 cell line database confirmed the broad association of these genes with chemotherapeutic responsiveness. These results have implications for personalizing lung cancer therapy and highlight the potential of combined approaches for biomarker discovery. PMID:21887332

  2. Direct prediction of spatially and temporally varying physical properties from time-lapse electrical resistance data

    NASA Astrophysics Data System (ADS)

    Hermans, Thomas; Oware, Erasmus; Caers, Jef

    2016-09-01

    Time-lapse applications of electrical methods have grown significantly over the last decade. However, the quantitative interpretation of tomograms in terms of physical properties, such as salinity, temperature or saturation, remains difficult. In many applications, geophysical models are transformed into hydrological models, but this transformation suffers from spatially and temporally varying resolution resulting from the regularization used by the deterministic inversion. In this study, we investigate a prediction-focused approach (PFA) to directly estimate subsurface physical properties with electrical resistance data, circumventing the need for classic tomographic inversions. First, we generate a prior set of resistance data and physical property forecast through hydrogeological and geophysical simulations mimicking the field experiment. We reduce the dimension of both the data and the forecast through principal component analysis in order to keep the most informative part of both sets in a reduced dimension space. Then, we apply canonical correlation analysis to explore the relationship between the data and the forecast in their reduced dimension space. If a linear relationship can be established, the posterior distribution of the forecast can be directly sampled using a Gaussian process regression where the field data scores are the conditioning data. In this paper, we demonstrate PFA for various physical property distributions. We also develop a framework to propagate the estimated noise level in the reduced dimension space. We validate the results by a Monte Carlo study on the posterior distribution and demonstrate that PFA yields accurate uncertainty for the cases studied.

  3. Friend leukaemia insertion (Fli)-1 is a prediction marker candidate for radiotherapy resistant oral squamous cell carcinoma.

    PubMed

    Shintani, S; Hamakawa, H; Nakashiro, K; Shirota, T; Hatori, M; Tanaka, M; Kuroshita, Y; Kurokawa, Y

    2010-11-01

    Radiotherapy is commonly used to treat oral squamous cell carcinoma (OSCC), but its therapeutic effects are unpredictable. To determine which genes correlate with radiation resistance in oral cancer, the authors evaluated radiation sensitivity using a standard colony formation assay with a gene microarray system for seven OSCC cell lines. They found significant associations between dozens of gene-expression levels and radiation resistance of OSCC cell lines. Following analysis of the different radiosensitive cancer cell lines, the friend leukaemia insertion (Fli)-1 gene was selected as a prediction marker gene for OSCC radiotherapy resistance. Fli-1 expression was associated with radiation resistance in OSCC patients. These data help to predict the effects radiation therapy has on OSCC, in turn contributing to the development of alternative radiation therapies.

  4. Validation Studies of the Numerical Tool PANSHIP for Predicting the Calm Water Resistance of the Armidale Class Patrol Boat

    DTIC Science & Technology

    2015-01-01

    at calm water line (m) U Ship speed (m/s) V Displaced volume (m3) V Speed (m/sec) Vk Speed (knots) Pd Developed power at propeller/engine (W...UNCLASSIFIED UNCLASSIFIED Validation Studies of the Numerical Tool PANSHIP for Predicting the Calm Water Resistance of the Armidale Class...reported previously that DSTO has undertaken a series of calm water resistance scaled model tests on the Armidale Class Patrol Boat (ACPB). In

  5. Prediction of Fluoroquinolone Resistance in Gram-Negative Bacteria Causing Bloodstream Infections.

    PubMed

    Dan, Seejil; Shah, Ansal; Justo, Julie Ann; Bookstaver, P Brandon; Kohn, Joseph; Albrecht, Helmut; Al-Hasan, Majdi N

    2016-04-01

    Increasing rates of fluoroquinolone resistance (FQ-R) have limited empirical treatment options for Gram-negative infections, particularly in patients with severe beta-lactam allergy. This case-control study aims to develop a clinical risk score to predict the probability of FQ-R in Gram-negative bloodstream isolates. Adult patients with Gram-negative bloodstream infections (BSI) hospitalized at Palmetto Health System in Columbia, South Carolina, from 2010 to 2013 were identified. Multivariate logistic regression was used to identify independent risk factors for FQ-R. Point allocation in the fluoroquinolone resistance score (FQRS) was based on regression coefficients. Model discrimination was assessed by the area under receiver operating characteristic curve (AUC). Among 824 patients with Gram-negative BSI, 143 (17%) had BSI due to fluoroquinolone-nonsusceptible Gram-negative bacilli. Independent risk factors for FQ-R and point allocation in FQRS included male sex (adjusted odds ratio [aOR], 1.97; 95% confidence intervals [CI], 1.36 to 2.98; 1 point), diabetes mellitus (aOR, 1.54; 95% CI, 1.03 to 2.28; 1 point), residence at a skilled nursing facility (aOR, 2.28; 95% CI, 1.42 to 3.63; 2 points), outpatient procedure within 30 days (aOR, 3.68; 95% CI, 1.96 to 6.78; 3 points), prior fluoroquinolone use within 90 days (aOR, 7.87; 95% CI, 4.53 to 13.74; 5 points), or prior fluoroquinolone use within 91 to 180 days of BSI (aOR, 2.77; 95% CI, 1.17 to 6.16; 3 points). The AUC for both final logistic regression and FQRS models was 0.73. Patients with an FQRS of 0, 3, 5, or 8 had predicted probabilities of FQ-R of 6%, 22%, 39%, or 69%, respectively. The estimation of patient-specific risk of antimicrobial resistance using FQRS may improve empirical antimicrobial therapy and fluoroquinolone utilization in Gram-negative BSI. Copyright © 2016, American Society for Microbiology. All Rights Reserved.

  6. Prediction of Fluoroquinolone Resistance in Gram-Negative Bacteria Causing Bloodstream Infections

    PubMed Central

    Dan, Seejil; Shah, Ansal; Justo, Julie Ann; Bookstaver, P. Brandon; Kohn, Joseph; Albrecht, Helmut

    2016-01-01

    Increasing rates of fluoroquinolone resistance (FQ-R) have limited empirical treatment options for Gram-negative infections, particularly in patients with severe beta-lactam allergy. This case-control study aims to develop a clinical risk score to predict the probability of FQ-R in Gram-negative bloodstream isolates. Adult patients with Gram-negative bloodstream infections (BSI) hospitalized at Palmetto Health System in Columbia, South Carolina, from 2010 to 2013 were identified. Multivariate logistic regression was used to identify independent risk factors for FQ-R. Point allocation in the fluoroquinolone resistance score (FQRS) was based on regression coefficients. Model discrimination was assessed by the area under receiver operating characteristic curve (AUC). Among 824 patients with Gram-negative BSI, 143 (17%) had BSI due to fluoroquinolone-nonsusceptible Gram-negative bacilli. Independent risk factors for FQ-R and point allocation in FQRS included male sex (adjusted odds ratio [aOR], 1.97; 95% confidence intervals [CI], 1.36 to 2.98; 1 point), diabetes mellitus (aOR, 1.54; 95% CI, 1.03 to 2.28; 1 point), residence at a skilled nursing facility (aOR, 2.28; 95% CI, 1.42 to 3.63; 2 points), outpatient procedure within 30 days (aOR, 3.68; 95% CI, 1.96 to 6.78; 3 points), prior fluoroquinolone use within 90 days (aOR, 7.87; 95% CI, 4.53 to 13.74; 5 points), or prior fluoroquinolone use within 91 to 180 days of BSI (aOR, 2.77; 95% CI, 1.17 to 6.16; 3 points). The AUC for both final logistic regression and FQRS models was 0.73. Patients with an FQRS of 0, 3, 5, or 8 had predicted probabilities of FQ-R of 6%, 22%, 39%, or 69%, respectively. The estimation of patient-specific risk of antimicrobial resistance using FQRS may improve empirical antimicrobial therapy and fluoroquinolone utilization in Gram-negative BSI. PMID:26833166

  7. Integrating simulations and experiments to predict sheet resistance and optical transmittance in nanowire films for transparent conductors.

    PubMed

    Mutiso, Rose M; Sherrott, Michelle C; Rathmell, Aaron R; Wiley, Benjamin J; Winey, Karen I

    2013-09-24

    Metal nanowire films are among the most promising alternatives for next-generation flexible, solution-processed transparent conductors. Breakthroughs in nanowire synthesis and processing have reported low sheet resistance (Rs ≤ 100 Ω/sq) and high optical transparency (%T > 90%). Comparing the merits of the various nanowires and fabrication methods is inexact, because Rs and %T depend on a variety of independent parameters including nanowire length, nanowire diameter, areal density of the nanowires and contact resistance between nanowires. In an effort to account for these fundamental parameters of nanowire thin films, this paper integrates simulations and experimental results to build a quantitatively predictive model. First, by fitting the results from simulations of quasi-2D rod networks to experimental data from well-defined nanowire films, we obtain an effective average contact resistance, which is indicative of the nanowire chemistry and processing methods. Second, this effective contact resistance is used to simulate how the sheet resistance depends on the aspect ratio (L/D) and areal density of monodisperse rods, as well as the effect of mixtures of short and long nanowires on the sheet resistance. Third, by combining our simulations of sheet resistance and an empirical diameter-dependent expression for the optical transmittance, we produced a fully calculated plot of optical transmittance versus sheet resistance. Our predictions for silver nanowires are validated by experimental results for silver nanowire films, where nanowires of L/D > 400 are required for high performance transparent conductors. In contrast to a widely used approach that employs a single percolative figure of merit, our method integrates simulation and experimental results to enable researchers to independently explore the importance of contact resistance between nanowires, as well as nanowire area fraction and arbitrary distributions in nanowire sizes. To become competitive, metal

  8. A test of taxonomic and biogeographic predictivity: resistance to Potato virus Y in wild relatives of the cultivated potato.

    PubMed

    Cai, X K; Spooner, D M; Jansky, S H

    2011-09-01

    A major justification for taxonomic research is its assumed ability to predict the presence of traits in a group for which the trait has been observed in a representative subset of the group. Similarly, populations in similar environments are expected to be more alike than populations in divergent environments. Consequently, it is logical to assume that taxonomic relationships and biogeographical data have the power to predict the distribution of disease resistance phenotypes among plant species. The objective of this study was to test predictivity in a group of widely distributed wild potato species, based on hypotheses that closely related organisms (taxonomy) or organisms from similar environments (biogeography) share resistance to a simply inherited trait (Potato virus Y [PVY]). We found that wild potato species with an endosperm balance number (EBN) of 1 (a measure of cross compatibility) shared resistances to PVY more than species with different EBN values. However, a large amount of variation was found for resistance to PVY among and within species. We also found that populations from low elevations were more resistant than those from high elevations. Because PVY is vectored by aphids, we speculate that the distribution of aphids may determine the level of selection pressure for PVY resistance.

  9. Prediction of HIV-1 protease inhibitor resistance by Molecular Modeling Protocols (MMPs) using GenMol software.

    PubMed

    Pèpe, G; Courcambeck, J; Perbost, R; Jouanna, P; Halfon, P

    2008-11-01

    This paper investigates the contribution of Molecular Modeling to (i) predict and (ii) understand more fundamentally HIV drug resistance. Based on a new automated GenMol module, these goals are approached by Molecular Modeling Protocols (MMPs), respectively, (i) the Molecular Modeling Phenotype Protocol (MMPP) and (ii) the Molecular Modeling Phenotype-Genotype Protocol (MMGPP). Section 2 recalls clinical practice with a reference case study and Section 3 presents atomistic simulation tools. Section 4 is the heart of the paper. In Section 4.1, MMPP drug resistance prediction is based on correlations between fold resistances versus binding energies on 2959 HIV-1 complexes with 6 protease inhibitors. Based on a drug sensitivity twofold criterion, modeling prediction is able to replace long and costly phenotype tests. In Section 4.2, MMGPP enlightens drug resistance by investigating steric and energetic residues/inhibitor interaction. Section 5 gives a synthesis on modeling contribution to drug resistance prediction. In conclusion, the most promising trend consists of MMP automats that are able to suggest a real time diagnosis taking into account the history of each patient, to enrich databases and to develop therapy strategy and new drugs.

  10. Modeling dynamic interactions between pre-exposure prophylaxis interventions & treatment programs: predicting HIV transmission & resistance

    PubMed Central

    Supervie, Virginie; Barrett, Meagan; Kahn, James S.; Musuka, Godfrey; Moeti, Themba Lebogang; Busang, Lesogo; Blower, Sally

    2011-01-01

    Clinical trials have recently demonstrated the effectiveness of Pre-Exposure Prophylaxis (PrEP) in preventing HIV infection. Consequently, PrEP may soon be used for epidemic control. We model the dynamic interactions that will occur between treatment programs and potential PrEP interventions in resource-constrained countries. We determine the consequences for HIV transmission and drug resistance. We use response hypersurface modeling to predict the effect of PrEP on decreasing transmission as a function of effectiveness, adherence and coverage. We predict PrEP will increase need for second-line therapies (SLT) for treatment-naïve individuals, but could significantly decrease need for SLT for treatment-experienced individuals. If the rollout of PrEP is carefully planned it could increase the sustainability of treatment programs. If not, need for SLT could increase and the sustainability of treatment programs could be compromised. Our results show the optimal strategy for rolling out PrEP in resource-constrained countries is to begin around the “worst” treatment programs. PMID:22355700

  11. Mutations of KRAS/NRAS/BRAF predict cetuximab resistance in metastatic colorectal cancer patients

    PubMed Central

    Hsu, Hung-Chih; Thiam, Tan Kien; Lu, Yen-Jung; Yeh, Chien Yuh; Tsai, Wen-Sy; You, Jeng Fu; Hung, Hsin Yuan; Tsai, Chi-Neu; Hsu, An; Chen, Hua-Chien; Chen, Shu-Jen; Yang, Tsai-Sheng

    2016-01-01

    Approximately 45% of metastatic colorectal cancer (mCRC) patients with wild-type KRAS exon 2 are resistant to cetuximab treatment. We set out to identify additional genetic markers that might predict the response to cetuximab treatment. Fifty-three wild-type KRAS exon 2 mCRC patients were treated with cetuximab/irinotecan-based chemotherapy as a first- or third-line therapy. The mutational statuses of 10 EGFR pathway genes were analyzed in primary tumors using next-generation sequencing. BRAF, PIK3CA, KRAS (exons 3 and 4), NRAS, PTEN, and AKT1 mutations were detected in 6, 6, 5, 4, 1, and 1 patient, respectively. Four of the BRAF mutations were non-V600 variants. Four tumors harbored multiple co-existing (complex) mutations. All patients with BRAF mutations or complex mutation patterns were cetuximab non-responders. All patients but one harboring KRAS, NRAS, or BRAF mutations were non-responders. Mutations in any one of these three genes were associated with a poor response rate (7.1%) and reduced survival (PFS = 8.0 months) compared to wild-type patients (74.4% and 11.6 months). Our data suggest that KRAS, NRAS, and BRAF mutations predict response to cetuximab treatment in mCRC patients. PMID:26989027

  12. Modeling dynamic interactions between pre-exposure prophylaxis interventions & treatment programs: predicting HIV transmission & resistance.

    PubMed

    Supervie, Virginie; Barrett, Meagan; Kahn, James S; Musuka, Godfrey; Moeti, Themba Lebogang; Busang, Lesego; Busang, Lesogo; Blower, Sally

    2011-01-01

    Clinical trials have recently demonstrated the effectiveness of Pre-Exposure Prophylaxis (PrEP) in preventing HIV infection. Consequently, PrEP may soon be used for epidemic control. We model the dynamic interactions that will occur between treatment programs and potential PrEP interventions in resource-constrained countries. We determine the consequences for HIV transmission and drug resistance. We use response hypersurface modeling to predict the effect of PrEP on decreasing transmission as a function of effectiveness, adherence and coverage. We predict PrEP will increase need for second-line therapies (SLT) for treatment-naïve individuals, but could significantly decrease need for SLT for treatment-experienced individuals. If the rollout of PrEP is carefully planned it could increase the sustainability of treatment programs. If not, need for SLT could increase and the sustainability of treatment programs could be compromised. Our results show the optimal strategy for rolling out PrEP in resource-constrained countries is to begin around the "worst" treatment programs.

  13. Staphylococcal Enterotoxin P Predicts Bacteremia in Hospitalized Patients Colonized With Methicillin-Resistant Staphylococcus aureus

    PubMed Central

    Calderwood, Michael S.; Desjardins, Christopher A.; Sakoulas, George; Nicol, Robert; DuBois, Andrea; Delaney, Mary L.; Kleinman, Ken; Cosimi, Lisa A.; Feldgarden, Michael; Onderdonk, Andrew B.; Birren, Bruce W.; Platt, Richard; Huang, Susan S.

    2014-01-01

    Background. Methicillin-resistant Staphylococcus aureus (MRSA) colonization predicts later infection, with both host and pathogen determinants of invasive disease. Methods. This nested case-control study evaluates predictors of MRSA bacteremia in an 8–intensive care unit (ICU) prospective adult cohort from 1 September 2003 through 30 April 2005 with active MRSA surveillance and collection of ICU, post-ICU, and readmission MRSA isolates. We selected MRSA carriers who did (cases) and those who did not (controls) develop MRSA bacteremia. Generating assembled genome sequences, we evaluated 30 MRSA genes potentially associated with virulence and invasion. Using multivariable Cox proportional hazards regression, we assessed the association of these genes with MRSA bacteremia, controlling for host risk factors. Results. We collected 1578 MRSA isolates from 520 patients. We analyzed host and pathogen factors for 33 cases and 121 controls. Predictors of MRSA bacteremia included a diagnosis of cancer, presence of a central venous catheter, hyperglycemia (glucose level, >200 mg/dL), and infection with a MRSA strain carrying the gene for staphylococcal enterotoxin P (sep). Receipt of an anti-MRSA medication had a significant protective effect. Conclusions. In an analysis controlling for host factors, colonization with MRSA carrying sep increased the risk of MRSA bacteremia. Identification of risk-adjusted genetic determinants of virulence may help to improve prediction of invasive disease and suggest new targets for therapeutic intervention. PMID:24041793

  14. Evaluation of susceptibility test breakpoints used to predict mecA-mediated resistance in Staphylococcus pseudintermedius isolated from dogs.

    PubMed

    Bemis, David A; Jones, Rebekah D; Frank, Linda A; Kania, Stephen A

    2009-01-01

    Clinical and Laboratory Standards Institute interpretive breakpoints for in vitro susceptibility tests that predict mecA-mediated oxacillin resistance in Staphylococcus pseudintermedius isolates from animals have been changed twice in the past decade. Moreover, there are no counterpart recommendations for human isolates of S. pseudintermedius. Individual medical and veterinary laboratories variably use interpretive breakpoints identical to those recommended for use with Staphylococcus aureus or identical to those recommended for use with coagulase-negative staphylococci. The purpose of the current study was to examine correlations between oxacillin disk diffusion, oxacillin gradient diffusion, oxacillin microbroth dilution, and cefoxitin disk diffusion tests used to predict mecA-mediated resistance in S. pseudintermedius and to retrospectively estimate, from disk diffusion zone diameter measurements, the prevalence and rate of increase of oxacillin resistance among canine S. pseudintermedius isolates submitted to a veterinary teaching hospital laboratory. Oxacillin disk diffusion zone diameters of or=0.5 microg/ml were highly correlated with detection of mecA in canine S. pseudintermedius isolates by polymerase chain reaction. MecA-mediated resistance among S. pseudintermedius isolates from dogs increased from less than 5% in 2001 to near 30% in 2007. More than 90% of the methicillin-resistant S. pseudintermedius isolates in 2006 and 2007 were also resistant to representatives of >or=4 additional antimicrobial drug classes. Cefoxitin disk diffusion with the resistance breakpoint set at

  15. Citric Acid Metabolism in Resistant Hypertension: Underlying Mechanisms and Metabolic Prediction of Treatment Response.

    PubMed

    Martin-Lorenzo, Marta; Martinez, Paula J; Baldan-Martin, Montserrat; Ruiz-Hurtado, Gema; Prado, Jose Carlos; Segura, Julian; de la Cuesta, Fernando; Barderas, Maria G; Vivanco, Fernando; Ruilope, Luis Miguel; Alvarez-Llamas, Gloria

    2017-11-01

    Resistant hypertension (RH) affects 9% to 12% of hypertensive adults. Prolonged exposure to suboptimal blood pressure control results in end-organ damage and cardiovascular risk. Spironolactone is the most effective drug for treatment, but not all patients respond and side effects are not negligible. Little is known on the mechanisms responsible for RH. We aimed to identify metabolic alterations in urine. In addition, a potential capacity of metabolites to predict response to spironolactone was investigated. Urine was collected from 29 patients with RH and from a group of 13 subjects with pseudo-RH. For patients, samples were collected before and after spironolactone administration and were classified in responders (n=19) and nonresponders (n=10). Nuclear magnetic resonance was applied to identify altered metabolites and pathways. Metabolites were confirmed by liquid chromatography-mass spectrometry. Citric acid cycle was the pathway most significantly altered (P<0.0001). Metabolic concentrations were quantified and ranged from ng/mL malate to μg/mL citrate. Citrate and oxaloacetate increased in RH versus pseudoresistant. Together with α-ketoglutarate and malate, they were able to discriminate between responders and nonresponders, being the 4 metabolites increased in nonresponders. Combined as a prediction panel, they showed receiver operating characteristiccurve with area under the curve of 0.96. We show that citric acid cycle and deregulation of reactive oxygen species homeostasis control continue its activation after hypertension was developed. A metabolic panel showing alteration before spironolactone treatment and predicting future response of patients is shown. These molecular indicators will contribute optimizing the rate of control of RH patients with spironolactone. © 2017 American Heart Association, Inc.

  16. Carotenoid-based coloration predicts resistance to oxidative damage during immune challenge.

    PubMed

    Pérez-Rodríguez, Lorenzo; Mougeot, Francois; Alonso-Alvarez, Carlos

    2010-05-01

    Many animal ornaments may have evolved as signals advertising the quality of the bearer. The honesty of the information content of these signals would rely on the costs associated with their expression, these being relatively greater for low-quality than for high-quality individuals. Given the physiological functions of carotenoids, carotenoid-based ornaments could indicate individual immunocompetence, and possibly the ability to mount an immune response at a lower cost. We evaluated whether the red carotenoid-based coloration of male red-legged partridges (Alectoris rufa) predicts the capacity of the individual to counteract the oxidative stress generated by a cell-mediated immune response. Individuals were subcutaneously injected with phytohaemagglutinin (PHA) or phosphate buffer solution (PBS) as a control. We found that eye ring pigmentation predicted the change in the amount of peroxidized lipids (TBARS) in blood after the PHA-induced inflammatory challenge. The degree of pigmentation of this carotenoid-based ornament was also negatively related to individual changes in gamma-glutamyl transferase (GGT), another biomarker of oxidative stress involved in antioxidant metabolism (i.e. glutathione recycling). However, changes in circulating carotenoids did not significantly explain changes in lipid peroxidation or GGT levels, suggesting that the higher resistance to oxidative stress of those individuals with more pigmented eye rings was not directly mediated by their greater circulating levels of carotenoids. Our results indicate that carotenoid-based coloration can predict not only immune responsiveness (more coloured males mount greater responses) but also an individual's ability to counter the oxidative stress generated during immune challenge (more coloured males experience less oxidative damage when mounting an immune response).

  17. Prediction of infection due to antibiotic-resistant bacteria by select risk factors for health care-associated pneumonia.

    PubMed

    Shorr, Andrew F; Zilberberg, Marya D; Micek, Scott T; Kollef, Marin H

    2008-11-10

    Pathogens such as methicillin-resistant Staphylococcus aureus (MRSA) and Pseudomonas aeruginosa now cause pneumonia in patients presenting to the hospital. The concept of health care-associated pneumonia (HCAP) attempts to capture this, but its predictive value is unclear. We examined patients admitted with pneumonia; infection with a resistant pathogen served as the study end point. Health care-associated pneumonia was present if a patient met one of the following criteria: recent hospitalization, nursing home residence, long-term hemodialysis, or immunosuppression. We compared rates of resistant infection among patients meeting any criteria for HCAP with those who did not have HCAP and explored the individual components of the definition. Among the cohort (n = 639), resistant pathogens were recovered in 289 (45.2%). Although each component of HCAP occurred more frequently in persons with resistant infections, the broad definition had a specificity of only 48.6% and misclassified one-third of the subjects. Logistic regression showed 4 variables associated with resistant pneumonia: recent hospitalization, nursing home residence, hemodialysis, and intensive care unit admission. A scoring system assigning 4, 3, 2, and 1 points, respectively, for each variable had moderate predictive power for segregating those with and without resistant bacteria. Among patients with fewer than 3 points, the prevalence of resistant pathogens was less than 20% compared with 55% and more than 75% in persons with scores ranging from 3 to 5 and more than 5 points, respectively (P < .001). Although resistance is common in HCAP, not all component criteria for HCAP convey similar risk. Simple scoring tools may facilitate more accurate identification of persons with pneumonia caused by resistant pathogens.

  18. Ciprofloxacin-resistant Escherichia coli in hospital wastewater of Bangladesh and prediction of its mechanism of resistance.

    PubMed

    Akter, Farhima; Amin, M Ruhul; Osman, Khan Tanjid; Anwar, M Nural; Karim, M Manjurul; Hossain, M Anwar

    2012-03-01

    Hospital and agriculture wastewater is mostly responsible for causing environmental pollution by spreading un-metabolized antibiotics and resistant bacteria, especially in Bangladesh. Here, we studied the influence of the most frequently prescribed antibiotic, fluoroquinolone (~72%), on the development of antibiotic resistance in Escherichia coli. Out of 300, 24 ciprofloxacin resistant E. coli isolates were selected for the study that showed the MBC(100) higher than expected (600 μg/mL). Here, we profiled plasmid, sequenced gyr genes, screened mutations and analyzed the effect of mutation on drug-protein interaction through molecular docking approach. We found that (1) out of 10, most of them (n = 7) had large plasmid(s); (2) all ciprofloxacin-resistant isolates had gyrA double mutations (S83L and D87Y); (3) no isolate had qnr gene; and (4) docking of ciprofloxacin with DNA gyrase A subunit suggests that acquisition of double mutation leads to alteration of the ciprofloxacin binding pocket.

  19. Predictive Studies Suggest that the Risk for the Selection of Antibiotic Resistance by Biocides Is Likely Low in Stenotrophomonas maltophilia

    PubMed Central

    Sánchez, María Blanca; Decorosi, Francesca; Viti, Carlo; Oggioni, Marco Rinaldo; Martínez, José Luis; Hernández, Alvaro

    2015-01-01

    Biocides are used without restriction for several purposes. As a consequence, large amounts of biocides are released without any control in the environment, a situation that can challenge the microbial population dynamics, including selection of antibiotic resistant bacteria. Previous work has shown that triclosan selects Stenotrophomonas maltophilia antibiotic resistant mutants overexpressing the efflux pump SmeDEF and induces expression of this pump triggering transient low-level resistance. In the present work we analyze if two other common biocides, benzalkonium chloride and hexachlorophene, trigger antibiotic resistance in S. maltophilia. Bioinformatic and biochemical methods showed that benzalkonium chloride and hexachlorophene bind the repressor of smeDEF, SmeT. Only benzalkonium chloride triggers expression of smeD and its effect in transient antibiotic resistance is minor. None of the hexachlorophene-selected mutants was antibiotic resistant. Two benzalkonium chloride resistant mutants presented reduced susceptibility to antibiotics and were impaired in growth. Metabolic profiling showed they were more proficient than their parental strain in the use of some dipeptides. We can then conclude that although bioinformatic predictions and biochemical studies suggest that both hexachlorophene and benzalkonium chloride should induce smeDEF expression leading to transient S. maltophilia resistance to antibiotics, phenotypic assays showed this not to be true. The facts that hexachlorophene resistant mutants are not antibiotic resistant and that the benzalkonium chloride resistant mutants presenting altered susceptibility to antibiotics were impaired in growth suggests that the risk for the selection (and fixation) of S. maltophilia antibiotic resistant mutants by these biocides is likely low, at least in the absence of constant selection pressure. PMID:26201074

  20. Predictive Studies Suggest that the Risk for the Selection of Antibiotic Resistance by Biocides Is Likely Low in Stenotrophomonas maltophilia.

    PubMed

    Sánchez, María Blanca; Decorosi, Francesca; Viti, Carlo; Oggioni, Marco Rinaldo; Martínez, José Luis; Hernández, Alvaro

    2015-01-01

    Biocides are used without restriction for several purposes. As a consequence, large amounts of biocides are released without any control in the environment, a situation that can challenge the microbial population dynamics, including selection of antibiotic resistant bacteria. Previous work has shown that triclosan selects Stenotrophomonas maltophilia antibiotic resistant mutants overexpressing the efflux pump SmeDEF and induces expression of this pump triggering transient low-level resistance. In the present work we analyze if two other common biocides, benzalkonium chloride and hexachlorophene, trigger antibiotic resistance in S. maltophilia. Bioinformatic and biochemical methods showed that benzalkonium chloride and hexachlorophene bind the repressor of smeDEF, SmeT. Only benzalkonium chloride triggers expression of smeD and its effect in transient antibiotic resistance is minor. None of the hexachlorophene-selected mutants was antibiotic resistant. Two benzalkonium chloride resistant mutants presented reduced susceptibility to antibiotics and were impaired in growth. Metabolic profiling showed they were more proficient than their parental strain in the use of some dipeptides. We can then conclude that although bioinformatic predictions and biochemical studies suggest that both hexachlorophene and benzalkonium chloride should induce smeDEF expression leading to transient S. maltophilia resistance to antibiotics, phenotypic assays showed this not to be true. The facts that hexachlorophene resistant mutants are not antibiotic resistant and that the benzalkonium chloride resistant mutants presenting altered susceptibility to antibiotics were impaired in growth suggests that the risk for the selection (and fixation) of S. maltophilia antibiotic resistant mutants by these biocides is likely low, at least in the absence of constant selection pressure.

  1. Insulin resistance predicts early cardiovascular morbidity in men without diabetes mellitus, with effect modification by physical activity.

    PubMed

    Hellgren, Margareta I; Daka, Bledar; Jansson, Per-Anders; Lindblad, Ulf; Larsson, Charlotte A

    2015-07-01

    to assess how well insulin resistance predicts cardiovascular disease (CVD) in non-diabetic men and women and to explore the influence of physical activity. in this prospective study 2563 men and women without diabetes were examined with an oral glucose tolerance test, anthropometric measurements and blood pressure assessment. Questionnaires about lifestyle and physical activity were completed. Insulin resistance was estimated by fasting concentrations of plasma insulin and by HOMA index for insulin resistance. Participants were followed up for cardiovascular morbidity and mortality during an 8-year period, using information from the National Swedish Inpatient and Mortality registers. at follow-up, HOMAir predicted CVD morbidity in males (50 events) and females (28 events) combined (HRage/sex-adj 1.4, 95% CI 1.1-1.7); however, when stratified by gender HOMAir was predictive solely in men (HRage-adj 1.8, 95% CI 1.3-2.4), whereas no association was found in women (HRage-adj 1.1, 95% CI 0.8-1.5). When stratifying the data for high and low physical activity, the predictive value of insulin resistance became stronger in sedentary men (HRage-adj 2.3, 95% CI 1.5-3.4) but was abolished in men performing moderate to vigorous physical activity (HRage-adj 1.0, 95% CI 0.6-1.6). The results remained when step-wise adjusted also for BMI, ApoB/ApoA1 and hypertension, as well as for smoking, alcohol consumption and education. Outcome for fasting plasma insulin was similar to HOMAir. insulin resistance predicts CVD in the general population; however, men may be more vulnerable to increased insulin resistance than women, and physically inactive men seem to be at high risk. © The European Society of Cardiology 2014 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.

  2. Validation of airway resistance models for predicting pressure loss through anatomically realistic conducting airway replicas of adults and children.

    PubMed

    Borojeni, Azadeh A T; Noga, Michelle L; Martin, Andrew R; Finlay, Warren H

    2015-07-16

    This work describes in vitro measurement of the total pressure loss at varying flow rate through anatomically realistic conducting airway replicas of 10 children, 4 to 8 years old, and 5 adults. Experimental results were compared with analytical predictions made using published airway resistance models. For the adult replicas, the model proposed by van Ertbruggen et al. (2005. J. Appl. Physiol. 98, 970-980) most accurately predicted central conducting airway resistance for inspiratory flow rates ranging from 15 to 90 L/min. Models proposed by Pedley et al. (1970. J. Respir. Physiol. 9, 371-386) and by Katz et al. (2011. J. Biomech. 44, 1137-1143) also provided reasonable estimates, but with a tendency to over predict measured pressure loss for both models. For child replicas, the Pedley and Katz models both provided good estimation of measured pressure loss at flow rates representative of resting tidal breathing, but under predicted measured values at high inspiratory flow rate (60 L/min). The van Ertbruggen model, developed based on flow simulations performed in an adult airway model, tended to under predict measured pressure loss through the child replicas across the range of flow rates studied (2 to 60 L/min). These results are intended to provide guidance for selection of analytical pressure loss models for use in predicting airway resistance and ventilation distribution in adults and children.

  3. Genetic variation and host-parasite specificity of Striga resistance and tolerance in rice: the need for predictive breeding.

    PubMed

    Rodenburg, Jonne; Cissoko, Mamadou; Kayongo, Nicholas; Dieng, Ibnou; Bisikwa, Jenipher; Irakiza, Runyambo; Masoka, Isaac; Midega, Charles A O; Scholes, Julie D

    2017-02-13

    The parasitic weeds Striga asiatica and Striga hermonthica cause devastating yield losses to upland rice in Africa. Little is known about genetic variation in host resistance and tolerance across rice genotypes, in relation to virulence differences across Striga species and ecotypes. Diverse rice genotypes were phenotyped for the above traits in S. asiatica- (Tanzania) and S. hermonthica-infested fields (Kenya and Uganda) and under controlled conditions. New rice genotypes with either ecotype-specific or broad-spectrum resistance were identified. Resistance identified in the field was confirmed under controlled conditions, providing evidence that resistance was largely genetically determined. Striga-resistant genotypes contributed to yield security under Striga-infested conditions, although grain yield was also determined by the genotype-specific yield potential and tolerance. Tolerance, the physiological mechanism mitigating Striga effects on host growth and physiology, was unrelated to resistance, implying that any combination of high, medium or low levels of these traits can be found across rice genotypes. Striga virulence varies across species and ecotypes. The extent of Striga-induced host damage results from the interaction between parasite virulence and genetically determined levels of host-plant resistance and tolerance. These novel findings support the need for predictive breeding strategies based on knowledge of host resistance and parasite virulence.

  4. Multidrug resistant bacteriuria before percutaneous nephrolithotomy predicts for postoperative infectious complications.

    PubMed

    Patel, Nishant; Shi, William; Liss, Michael; Raheem, Omer; Wenzler, David; Schallhorn, Craig; Kiyama, Linsday; Lakin, Charles; Ritter, Michele; Sur, Roger L

    2015-05-01

    Multidrug resistant (MDR) uropathogens are increasing in prevalence and may contribute to significant morbidity after percutaneous nephrolithotomy (PCNL). We investigate the presence of MDR bacteriuria and occurrence of postoperative infectious complications in patients who underwent PCNL at our institution. Retrospective review was performed of 81 patients undergoing PCNL by a single surgeon (RLS) between 2009 and 2013. Patient demographics, comorbidities, stone parameters on imaging, and microbial data were compiled. MDR organisms were defined as resistant to three or more of the American Urological Association Best Practice Statement antimicrobial classes for PCNL. Postoperative complications were graded by Clavien score and European Association of Urology infection grade. Univariate comparisons were analyzed between patients with and without a postoperative infectious complication. Multivariate logistic regression was performed to determine significant predictor variables for postoperative infectious complications. Of the 81 patients undergoing PCNL, 41/81 (51%) had positive preoperative urine culture, 24/81 (30%) had positive MDR urine culture, and 16/81 (19%) had a postoperative infectious complication. Multivariate analysis revealed a positive preoperative MDR urine culture significantly increased the risk of postoperative infectious complication (odds ratio [OR]=4.89, 95% confidence interval [CI] 1.134-17.8, P=0.016). The presence of more than one access tract during PCNL also predicted for infectious complications (OR=7.5, 95% CI 2.13-26.4, P=0.003) Of the 16 patients with a postoperative infection 3 (18%) had postoperative urine cultures discordant with the preoperative urine cultures. Our institution demonstrated a relatively high prevalence of MDR bacteriuria in patients undergoing PCNL and that MDR is a significant risk factor for postoperative infectious complications despite appropriate preoperative antibiotics. Further investigations regarding

  5. Adiposity indices in the prediction of insulin resistance in prepubertal Colombian children

    PubMed Central

    Mueller, Noel T; Pereira, Mark A; Buitrago-Lopez, Adriana; Rodríguez, Diana C; Duran, Alvaro E; Ruiz, Alvaro J; Rueda-Clausen, Christian F; Villa-Roel, Cristina

    2012-01-01

    Objective To compare BMI with abdominal skinfold thickness (ASF), waist circumference and waist-to-height ratio in the prediction of insulin resistance (IR) in prepubertal Colombian children. Design We calculated age- and sex-specific Z-scores for BMI, ASF, waist circumference, waist-to-height ratio and three other skinfold-thickness sites. Logistic regression with stepwise selection (P = 0·80 for entry and P = 0·05 for retention) was performed to identify predictors of IR and extreme IR, which were determined by age- and sex-specific Z-scores to identify the ≥ 90th and ≥ 95th percentile of homeostasis model assessment (HOMAIR), respectively. We used receiver operating characteristic curves to compare the area under the curve between models. Setting Bucaramanga, Colombia. Subjects Children (n 1261) aged 6–10 years in Tanner stage 1 from a population-based study. Results A total of 127 children (seventy girls and fifty-seven boys) were classified with IR, including sixty-three children (thirty-three girls and thirty boys) classified with extreme IR. Only ASF and BMI Z-scores were retained as predictors of IR by stepwise selection. Adding ASF Z-score to BMI Z-score improved the area under the curve from 0·794 (95% CI 0·752, 0·837) to 0·811 (95% CI 0·770, 0·851; P for contrast = 0·01). In predicting extreme IR, the addition of ASF Z-score to BMI Z-score improved the area under the curve from 0·837 (95% CI 0·790, 0·884) to 0·864 (95% CI 0·823, 0·905; P for contrast = 0·01). Conclusions ASF Z-score predicted IR independent of BMI Z-score in our population of prepubertal children. ASF and BMI Z-scores together improved IR risk stratification compared with BMI Z-score alone, opening new perspectives in the prediction of cardiometabolic risk in prepubertal children. PMID:22916737

  6. mRNA biomarkers selection based on Partial Least Square algorithm in order to further predict Bacillus weihenstephanensis acid resistance.

    PubMed

    Desriac, Noémie; Coroller, Louis; Jannic, Frederic; Postollec, Florence; Sohier, Danièle

    2015-02-01

    In order to integrate omics data to quantitative microbiological risk assessment in foods, gene expressions may serve as bacterial behaviour biomarkers. In this study an integrative approach encompassing predictive modelling and mRNAs quantifications, was followed to select molecular biomarkers to further predict the acid resistance of Bacillus weihenstephanensis. A multivariate analysis was performed to correlate the acid bacterial resistance and the gene expression of vegetative cells with or without exposure to stressing conditions. This mathematical method provides the advantage to take gene expressions and their interactions into account. The use of the Partial Least Squares algorithm allowed the selection of nine genes as acid resistance biomarkers among thirty targeted genes. According to their involvement in the general acid stress response of Bacillus, these genes were assigned to three different biological modules namely, metabolic rearrangements, general stress response and oxidative stress response. The oxidative stress response appeared as the major activated biological module in B. weihenstephanensis cells submitted to acid stress conditions. Furthermore, as a firstly described model, the developed concept showed promising results to further be used to predict bacterial resistance using gene expression. Thus, this study underlines the possibility to integrate the bacterial physiology state, using omics biomarkers, into bacterial behaviour modelling and provide mechanistic understanding in acid bacterial resistance mechanisms. Copyright © 2014 Elsevier Ltd. All rights reserved.

  7. [Resistant Obsessive Compulsive disorder (ROC): clinical picture, predictive factors and influence of affective temperaments].

    PubMed

    Hantouche, E G; Demonfaucon, C

    2008-12-01

    Despite significant advances in clinical research, Obsessive Compulsive Disorder, OCD represents a difficult to treat condition. The French Association of patients suffering from OCD, "AFTOC" is highly concerned by this issue. A new survey was implemented with the aim of exploring Resistant Obsessive Compulsive disorder "ROC". Patients with OCD and members of the "AFTOC" were included in the survey. A self-rated file was elaborated in order to get the maximum of information on the clinical and therapeutic aspects and conditions of OCD. The full version of "TEMPS-A" was also included for assessment of affective temperaments. Statistical analyses were performed for inter-group comparison between "ROC" (resistant OCD) and good responders. Logistic regression analyses with "ROC" method were used to search for independent predictive factors to "ROC". The new survey of "AFTOC", "TOC & ROC" selected a sample of 360 patients, who are members of the association. The rate of "ROC" was 44.2%, 25.3% of Good Responders (GR), and 30.5% in between. Inter-group comparisons ("ROC" versus GR) showed significant higher rates of psychiatric admissions (49% versus 28%), and suicide attempts (26% versus 13%), greater numbers of doctors consulted (5.5 versus. 3.2), compulsions (4.6 versus 3.4), and psychiatric comorbidity (2.8 disorders versus. 2.0; notably agoraphobia, social anxiety and worry about appearance) in the "ROC" group. Assessment by full "TEMPS-A" scale revealed, significantly higher rates of Cyclothymic Temperament (63% versus 43%; p: 0.0003), Depressive Temperament (72% versus 53%; p: 0.004), and Irritable Temperament (21% versus 9%; p: 0.02) in the ROC group. Moreover, the mean global score on each of these temperaments was significantly higher in the "ROC" group. No difference was obtained in the rate or the mean score on the hyperthymic temperament scale. The most predictive factors of "ROC" were represented by "slow continuous course", "worsening under SRI", "worry

  8. Evolutionary Trajectories of Beta-Lactamase CTX-M-1 Cluster Enzymes: Predicting Antibiotic Resistance

    PubMed Central

    Novais, Ângela; Comas, Iñaki; Baquero, Fernando; Cantón, Rafael; Coque, Teresa M.; Moya, Andrés; González-Candelas, Fernando; Galán, Juan-Carlos

    2010-01-01

    . Antimicrobial agents should not be considered only as selectors for efficient mechanisms of resistance but also as diversifying agents of the evolutionary trajectories. Different trajectories were identified using a combination of phylogenetic reconstructions and directed mutagenesis analyses, indicating that such an approach might be useful to fulfill the desirable goal of predicting evolutionary trajectories in antimicrobial resistance. PMID:20107608

  9. Factors Predicting the Type of Tactics Used to Resist Sexual Assault: A Prospective Study of College Women

    ERIC Educational Resources Information Center

    Turchik, Jessica A.; Probst, Danielle R.; Chau, Minna; Nigoff, Amy; Gidycz, Christine A.

    2007-01-01

    The purpose of the current study was to examine how women's intentions, as well as psychological and situational factors, predicted the actual use of resistance tactics in response to a sexual assault situation over a 2-month follow-up period. Twenty-eight percent of the 378 undergraduate women who participated at the baseline assessment and…

  10. Accuracy of genomic prediction for BCWD resistance in rainbow trout using different genotyping platforms and genomic selection models

    USDA-ARS?s Scientific Manuscript database

    In this study, we aimed to (1) predict genomic estimated breeding value (GEBV) for bacterial cold water disease (BCWD) resistance by genotyping training (n=583) and validation samples (n=53) with two genotyping platforms (24K RAD-SNP and 49K SNP) and using different genomic selection (GS) models (Ba...

  11. Factors Predicting the Type of Tactics Used to Resist Sexual Assault: A Prospective Study of College Women

    ERIC Educational Resources Information Center

    Turchik, Jessica A.; Probst, Danielle R.; Chau, Minna; Nigoff, Amy; Gidycz, Christine A.

    2007-01-01

    The purpose of the current study was to examine how women's intentions, as well as psychological and situational factors, predicted the actual use of resistance tactics in response to a sexual assault situation over a 2-month follow-up period. Twenty-eight percent of the 378 undergraduate women who participated at the baseline assessment and…

  12. Proteomics of Genetically Engineered Mouse Mammary Tumors Identifies Fatty Acid Metabolism Members as Potential Predictive Markers for Cisplatin Resistance*

    PubMed Central

    Warmoes, Marc; Jaspers, Janneke E.; Xu, Guotai; Sampadi, Bharath K.; Pham, Thang V.; Knol, Jaco C.; Piersma, Sander R.; Boven, Epie; Jonkers, Jos; Rottenberg, Sven; Jimenez, Connie R.

    2013-01-01

    In contrast to various signatures that predict the prognosis of breast cancer patients, markers that predict chemotherapy response are still elusive. To detect such predictive biomarkers, we investigated early changes in protein expression using two mouse models for distinct breast cancer subtypes who have a differential knock-out status for the breast cancer 1, early onset (Brca1) gene. The proteome of cisplatin-sensitive BRCA1-deficient mammary tumors was compared with that of cisplatin-resistant mammary tumors resembling pleomorphic invasive lobular carcinoma. The analyses were performed 24 h after administration of the maximum tolerable dose of cisplatin. At this time point, drug-sensitive BRCA1-deficient tumors showed DNA damage, but cells were largely viable. By applying paired statistics and quantitative filtering, we identified highly discriminatory markers for the sensitive and resistant model. Proteins up-regulated in the sensitive model are involved in centrosome organization, chromosome condensation, homology-directed DNA repair, and nucleotide metabolism. Major discriminatory markers that were up-regulated in the resistant model were predominantly involved in fatty acid metabolism, such as fatty-acid synthase. Specific inhibition of fatty-acid synthase sensitized resistant cells to cisplatin. Our data suggest that exploring the functional link between the DNA damage response and cancer metabolism shortly after the initial treatment may be a useful strategy to predict the efficacy of cisplatin. PMID:23397111

  13. Designing Predictive Diagnose Method for Insulation Resistance Degradation of the Electrical Power Cables from Neutral Insulated Power Networks

    NASA Astrophysics Data System (ADS)

    Dobra, R.; Pasculescu, D.; Risteiu, M.; Buica, G.; Jevremović, V.

    2017-06-01

    This paper describe some possibilities to minimize voltages switching-off risks from the mining power networks, in case of insulated resistance faults by using a predictive diagnose method. The cables from the neutral insulated power networks (underground mining) are designed to provide a flexible electrical connection between portable or mobile equipment and a point of supply, including main feeder cable for continuous miners, pump cable, and power supply cable. An electronic protection for insulated resistance of mining power cables can be made using this predictive strategy. The main role of electronic relays for insulation resistance degradation of the electrical power cables, from neutral insulated power networks, is to provide a permanent measurement of the insulated resistance between phases and ground, in order to switch-off voltage when the resistance value is below a standard value. The automat system of protection is able to signalize the failure and the human operator will be early informed about the switch-off power and will have time to take proper measures to fix the failure. This logic for fast and automat switch-off voltage without aprioristic announcement is suitable for the electrical installations, realizing so a protection against fires and explosion. It is presented an algorithm and an anticipative relay for insulated resistance control from three-phase low voltage installations with insulated neutral connection.

  14. Electrical Resistance of SiC/SiC Ceramic Matrix Composites for Damage Detection and Life-Prediction

    NASA Technical Reports Server (NTRS)

    Smith, Craig; Morscher, Gregory; Xia, Zhenhai

    2009-01-01

    Ceramic matrix composites (CMC) are suitable for high temperature structural applications such as turbine airfoils and hypersonic thermal protection systems due to their low density high thermal conductivity. The employment of these materials in such applications is limited by the ability to accurately monitor and predict damage evolution. Current nondestructive methods such as ultrasound, x-ray, and thermal imaging are limited in their ability to quantify small scale, transverse, in-plane, matrix cracks developed over long-time creep and fatigue conditions. CMC is a multifunctional material in which the damage is coupled with the material s electrical resistance, providing the possibility of real-time information about the damage state through monitoring of resistance. Here, resistance measurement of SiC/SiC composites under mechanical load at both room temperature monotonic and high temperature creep conditions, coupled with a modal acoustic emission technique, can relate the effects of temperature, strain, matrix cracks, fiber breaks, and oxidation to the change in electrical resistance. A multiscale model can in turn be developed for life prediction of in-service composites, based on electrical resistance methods. Results of tensile mechanical testing of SiC/SiC composites at room and high temperatures will be discussed. Data relating electrical resistivity to composite constituent content, fiber architecture, temperature, matrix crack formation, and oxidation will be explained, along with progress in modeling such properties.

  15. Value of American Thoracic Society guidelines in predicting infection or colonization with multidrug-resistant organisms in critically ill patients.

    PubMed

    Xie, Jianfeng; Ma, Xudong; Huang, Yingzi; Mo, Min; Guo, Fengmei; Yang, Yi; Qiu, Haibo

    2014-01-01

    The incidence rate of infection by multidrug-resistant organisms (MDROs) can affect the accuracy of etiological diagnosis when using American Thoracic Society (ATS) guidelines. We determined the accuracy of the ATS guidelines in predicting infection or colonization by MDROs over 18 months at a single ICU in eastern China. This prospective observational study examined consecutive patients who were admitted to an intensive care unit (ICU) in Nanjing, China. MDROs were defined as bacteria that were resistant to at least three antimicrobial classes, such as methicillin-resistant Staphylococcus aureus (MRSA), vancomycin-resistant enterococci (VRE), Pseudomonas aeruginosa, Acinetobacter baumannii. Screening for MDROs was performed at ICU admission and discharge. Risk factors for infection or colonization with MDROs were recorded, and the accuracy of the ATS guidelines in predicting infection or colonization with MDROs was documented. There were 610 patients, 225 (37%) of whom were colonized or infected with MDROs at ICU admission, and this increased to 311 (51%) at discharge. At admission, the sensitivity (70.0%), specificity (31.6%), positive predictive value (38.2%), and negative predictive value (63.5%), all based on ATS guidelines for infection or colonization with MDROs were low. The negative predictive value was greater in patients from departments with MDRO infection rates of 31-40% than in patients from departments with MDRO infection rates of 30% or less and from departments with MDRO infection rates more than 40%. ATS criteria were not reliable in predicting infection or colonization with MDROs in our ICU. The negative predictive value was greater in patients from departments with intermediate rates of MDRO infection than in patients from departments with low or high rates of MDRO infection. ClinicalTrials.gov NCT01667991.

  16. Postprandial Hypertriglyceridemia Predicts Development of Insulin Resistance Glucose Intolerance and Type 2 Diabetes

    PubMed Central

    Aslam, Mohammad; Aggarwal, Sarla; Sharma, Krishna Kumar; Galav, Vikas; Madhu, Sri Venkata

    2016-01-01

    Insulin resistance (IR) and type 2 diabetes mellitus (T2DM) have been found to be associated with postprandial hypertriglyceridemia (PPHTg). However, whether PPHTg can cause IR and diabetes is not clear. We therefore investigated the role of PPHTg in development of T2DM in rat model of T2DM. 96 male Wistar rats were randomized into four groups (24 rats each). Control Group A, high sucrose diet (HSD) Group B, HSD+Pioglitazone (10mg/kg/day) Group C and HSD+Atorvastatin (20mg/kg/day) Group D. Fat and glucose tolerance tests were done at regular intervals in all groups besides insulin and body weight measurement. At 26 weeks, low dose streptozotocin (15mg/kg,i.p.) was given to half of the rats. All rats were followed up till 48 weeks. PPHTg developed as early as week 2 in Group B and stabilized by week 14. Group B displayed highest PPHTg compared to other groups. Atorvastatin treatment (Group D) abolished PPHTg which became comparable to controls, pioglitazone treatment partially blunted PPHTg resulting in intermediate PPHTg. Group B with highest PPHTg showed highest subsequent IR, glucose intolerance (GI) and highest incidence of prediabetes at week 26 and diabetes at week 34 and 46 compared to other groups. Group D rats displayed lower IR, GI, low incidence of prediabetes and diabetes at these time points compared to Groups B and C. ROC analysis showed that triglyceride area under the curve of each time point significantly predicts the risk of diabetes. Present study provides the evidence that PPHTg predicts the development of IR, GI and T2DM in rat model of diet induced T2DM. PMID:26808523

  17. Postprandial Hypertriglyceridemia Predicts Development of Insulin Resistance Glucose Intolerance and Type 2 Diabetes.

    PubMed

    Aslam, Mohammad; Aggarwal, Sarla; Sharma, Krishna Kumar; Galav, Vikas; Madhu, Sri Venkata

    2016-01-01

    Insulin resistance (IR) and type 2 diabetes mellitus (T2DM) have been found to be associated with postprandial hypertriglyceridemia (PPHTg). However, whether PPHTg can cause IR and diabetes is not clear. We therefore investigated the role of PPHTg in development of T2DM in rat model of T2DM. 96 male Wistar rats were randomized into four groups (24 rats each). Control Group A, high sucrose diet (HSD) Group B, HSD+Pioglitazone (10 mg/kg/day) Group C and HSD+Atorvastatin (20 mg/kg/day) Group D. Fat and glucose tolerance tests were done at regular intervals in all groups besides insulin and body weight measurement. At 26 weeks, low dose streptozotocin (15 mg/kg, i.p.) was given to half of the rats. All rats were followed up till 48 weeks. PPHTg developed as early as week 2 in Group B and stabilized by week 14. Group B displayed highest PPHTg compared to other groups. Atorvastatin treatment (Group D) abolished PPHTg which became comparable to controls, pioglitazone treatment partially blunted PPHTg resulting in intermediate PPHTg. Group B with highest PPHTg showed highest subsequent IR, glucose intolerance (GI) and highest incidence of prediabetes at week 26 and diabetes at week 34 and 46 compared to other groups. Group D rats displayed lower IR, GI, low incidence of prediabetes and diabetes at these time points compared to Groups B and C. ROC analysis showed that triglyceride area under the curve of each time point significantly predicts the risk of diabetes. Present study provides the evidence that PPHTg predicts the development of IR, GI and T2DM in rat model of diet induced T2DM.

  18. Bacterial Resistance Studies Using In Vitro Dynamic Models: the Predictive Power of the Mutant Prevention and Minimum Inhibitory Antibiotic Concentrations

    PubMed Central

    Strukova, Elena N.; Shlykova, Darya S.; Portnoy, Yury A.; Kozyreva, Varvara K.; Edelstein, Mikhail V.; Dovzhenko, Svetlana A.; Kobrin, Mikhail B.; Zinner, Stephen H.

    2013-01-01

    In light of the concept of the mutant selection window, i.e., the range between the MIC and the mutant prevention concentration (MPC), MPC-related pharmacokinetic indices should be more predictive of bacterial resistance than the respective MIC-related indices. However, experimental evidence of this hypothesis remains limited and contradictory. To examine the predictive power of the ratios of the area under the curve (AUC24) to the MPC and the MIC, the selection of ciprofloxacin-resistant mutants of four Escherichia coli strains with different MPC/MIC ratios was studied. Each organism was exposed to twice-daily ciprofloxacin for 3 days at AUC24/MIC ratios that provide peak antibiotic concentrations close to the MIC, between the MIC and the MPC, and above the MPC. Resistant E. coli was intensively enriched at AUC24/MPCs from 1 to 10 h (AUC24/MIC from 60 to 360 h) but not at the lower or higher AUC24/MPC and AUC24/MIC ratios. AUC24/MPC and AUC24/MIC relationships of the areas under the time courses of ciprofloxacin-resistant E. coli (AUBCM) were bell-shaped. A Gaussian-like function fits the AUBCM-AUC24/MPC and AUBCM-AUC24/MIC data combined for all organisms (r2 = 0.69 and 0.86, respectively). The predicted anti-mutant AUC24/MPC ratio was 58 ± 35 h, and the respective AUC24/MIC ratio was 1,080 ± 416 h. Although AUC24/MPC was less predictive of strain-independent E. coli resistance than AUC24/MIC, the established anti-mutant AUC24/MPC ratio was closer to values reported for Staphylococcus aureus (60 to 69 h) than the respective AUC24/MIC ratio (1,080 versus 200 to 240 h). This implies that AUC24/MPC might be a better interspecies predictor of bacterial resistance than AUC24/MIC. PMID:23896481

  19. Transmission of HIV Drug Resistance and the Predicted Effect on Current First-line Regimens in Europe.

    PubMed

    Hofstra, L Marije; Sauvageot, Nicolas; Albert, Jan; Alexiev, Ivailo; Garcia, Federico; Struck, Daniel; Van de Vijver, David A M C; Åsjö, Birgitta; Beshkov, Danail; Coughlan, Suzie; Descamps, Diane; Griskevicius, Algirdas; Hamouda, Osamah; Horban, Andrzej; Van Kasteren, Marjo; Kolupajeva, Tatjana; Kostrikis, Leondios G; Liitsola, Kirsi; Linka, Marek; Mor, Orna; Nielsen, Claus; Otelea, Dan; Paraskevis, Dimitrios; Paredes, Roger; Poljak, Mario; Puchhammer-Stöckl, Elisabeth; Sönnerborg, Anders; Staneková, Danica; Stanojevic, Maja; Van Laethem, Kristel; Zazzi, Maurizio; Zidovec Lepej, Snjezana; Boucher, Charles A B; Schmit, Jean-Claude; Wensing, Annemarie M J; Puchhammer-Stockl, E; Sarcletti, M; Schmied, B; Geit, M; Balluch, G; Vandamme, A-M; Vercauteren, J; Derdelinckx, I; Sasse, A; Bogaert, M; Ceunen, H; De Roo, A; De Wit, S; Echahidi, F; Fransen, K; Goffard, J-C; Goubau, P; Goudeseune, E; Yombi, J-C; Lacor, P; Liesnard, C; Moutschen, M; Pierard, D; Rens, R; Schrooten, Y; Vaira, D; Vandekerckhove, L P R; Van den Heuvel, A; Van Der Gucht, B; Van Ranst, M; Van Wijngaerden, E; Vandercam, B; Vekemans, M; Verhofstede, C; Clumeck, N; Van Laethem, K; Beshkov, D; Alexiev, I; Lepej, S Zidovec; Begovac, J; Kostrikis, L; Demetriades, I; Kousiappa, I; Demetriou, V; Hezka, J; Linka, M; Maly, M; Machala, L; Nielsen, C; Jørgensen, L B; Gerstoft, J; Mathiesen, L; Pedersen, C; Nielsen, H; Laursen, A; Kvinesdal, B; Liitsola, K; Ristola, M; Suni, J; Sutinen, J; Descamps, D; Assoumou, L; Castor, G; Grude, M; Flandre, P; Storto, A; Hamouda, O; Kücherer, C; Berg, T; Braun, P; Poggensee, G; Däumer, M; Eberle, J; Heiken, H; Kaiser, R; Knechten, H; Korn, K; Müller, H; Neifer, S; Schmidt, B; Walter, H; Gunsenheimer-Bartmeyer, B; Harrer, T; Paraskevis, D; Hatzakis, A; Zavitsanou, A; Vassilakis, A; Lazanas, M; Chini, M; Lioni, A; Sakka, V; Kourkounti, S; Paparizos, V; Antoniadou, A; Papadopoulos, A; Poulakou, G; Katsarolis, I; Protopapas, K; Chryssos, G; Drimis, S; Gargalianos, P; Xylomenos, G; Lourida, G; Psichogiou, M; Daikos, G L; Sipsas, N V; Kontos, A; Gamaletsou, M N; Koratzanis, G; Sambatakou, H; Mariolis, H; Skoutelis, A; Papastamopoulos, V; Georgiou, O; Panagopoulos, P; Maltezos, E; Coughlan, S; De Gascun, C; Byrne, C; Duffy, M; Bergin, C; Reidy, D; Farrell, G; Lambert, J; O'Connor, E; Rochford, A; Low, J; Coakely, P; O'Dea, S; Hall, W; Mor, O; Levi, I; Chemtob, D; Grossman, Z; Zazzi, M; de Luca, A; Balotta, C; Riva, C; Mussini, C; Caramma, I; Capetti, A; Colombo, M C; Rossi, C; Prati, F; Tramuto, F; Vitale, F; Ciccozzi, M; Angarano, G; Rezza, G; Kolupajeva, T; Vasins, O; Griskevicius, A; Lipnickiene, V; Schmit, J C; Struck, D; Sauvageot, N; Hemmer, R; Arendt, V; Michaux, C; Staub, T; Sequin-Devaux, C; Wensing, A M J; Boucher, C A B; van de Vijver, D A M C; van Kessel, A; van Bentum, P H M; Brinkman, K; Connell, B J; van der Ende, M E; Hoepelman, I M; van Kasteren, M; Kuipers, M; Langebeek, N; Richter, C; Santegoets, R M W J; Schrijnders-Gudde, L; Schuurman, R; van de Ven, B J M; Åsjö, B; Kran, A-M Bakken; Ormaasen, V; Aavitsland, P; Horban, A; Stanczak, J J; Stanczak, G P; Firlag-Burkacka, E; Wiercinska-Drapalo, A; Jablonowska, E; Maolepsza, E; Leszczyszyn-Pynka, M; Szata, W; Camacho, R; Palma, C; Borges, F; Paixão, T; Duque, V; Araújo, F; Otelea, D; Paraschiv, S; Tudor, A M; Cernat, R; Chiriac, C; Dumitrescu, F; Prisecariu, L J; Stanojevic, M; Jevtovic, Dj; Salemovic, D; Stanekova, D; Habekova, M; Chabadová, Z; Drobkova, T; Bukovinova, P; Shunnar, A; Truska, P; Poljak, M; Lunar, M; Babic, D; Tomazic, J; Vidmar, L; Vovko, T; Karner, P; Garcia, F; Paredes, R; Monge, S; Moreno, S; Del Amo, J; Asensi, V; Sirvent, J L; de Mendoza, C; Delgado, R; Gutiérrez, F; Berenguer, J; Garcia-Bujalance, S; Stella, N; de Los Santos, I; Blanco, J R; Dalmau, D; Rivero, M; Segura, F; Elías, M J Pérez; Alvarez, M; Chueca, N; Rodríguez-Martín, C; Vidal, C; Palomares, J C; Viciana, I; Viciana, P; Cordoba, J; Aguilera, A; Domingo, P; Galindo, M J; Miralles, C; Del Pozo, M A; Ribera, E; Iribarren, J A; Ruiz, L; de la Torre, J; Vidal, F; Clotet, B; Albert, J; Heidarian, A; Aperia-Peipke, K; Axelsson, M; Mild, M; Karlsson, A; Sönnerborg, A; Thalme, A; Navér, L; Bratt, G; Karlsson, A; Blaxhult, A; Gisslén, M; Svennerholm, B; Bergbrant, I; Björkman, P; Säll, C; Mellgren, Å; Lindholm, A; Kuylenstierna, N; Montelius, R; Azimi, F; Johansson, B; Carlsson, M; Johansson, E; Ljungberg, B; Ekvall, H; Strand, A; Mäkitalo, S; Öberg, S; Holmblad, P; Höfer, M; Holmberg, H; Josefson, P; Ryding, U

    2016-03-01

    Numerous studies have shown that baseline drug resistance patterns may influence the outcome of antiretroviral therapy. Therefore, guidelines recommend drug resistance testing to guide the choice of initial regimen. In addition to optimizing individual patient management, these baseline resistance data enable transmitted drug resistance (TDR) to be surveyed for public health purposes. The SPREAD program systematically collects data to gain insight into TDR occurring in Europe since 2001. Demographic, clinical, and virological data from 4140 antiretroviral-naive human immunodeficiency virus (HIV)-infected individuals from 26 countries who were newly diagnosed between 2008 and 2010 were analyzed. Evidence of TDR was defined using the WHO list for surveillance of drug resistance mutations. Prevalence of TDR was assessed over time by comparing the results to SPREAD data from 2002 to 2007. Baseline susceptibility to antiretroviral drugs was predicted using the Stanford HIVdb program version 7.0. The overall prevalence of TDR did not change significantly over time and was 8.3% (95% confidence interval, 7.2%-9.5%) in 2008-2010. The most frequent indicators of TDR were nucleoside reverse transcriptase inhibitor (NRTI) mutations (4.5%), followed by nonnucleoside reverse transcriptase inhibitor (NNRTI) mutations (2.9%) and protease inhibitor mutations (2.0%). Baseline mutations were most predictive of reduced susceptibility to initial NNRTI-based regimens: 4.5% and 6.5% of patient isolates were predicted to have resistance to regimens containing efavirenz or rilpivirine, respectively, independent of current NRTI backbones. Although TDR was highest for NRTIs, the impact of baseline drug resistance patterns on susceptibility was largest for NNRTIs. The prevalence of TDR assessed by epidemiological surveys does not clearly indicate to what degree susceptibility to different drug classes is affected. © The Author 2015. Published by Oxford University Press for the Infectious

  20. Lamivudine Concentration in Hair and Prediction of Virologic Failure and Drug Resistance among HIV Patients Receiving Free ART in China

    PubMed Central

    Wang, Zhe; Wu, Jianjun; Zhang, Jiafeng; Ruan, Yuhua; Hsi, Jenny; Liao, Lingjie; Shao, Yiming; Xing, Hui

    2016-01-01

    Background The assessment of adherence to antiretroviral therapy (ART) is important in order to predict treatment outcomes. Lamivudine (3TC) is one of the most widely used NRTIs in China, but its concentrations in hair and association with virologic failure and drug resistance have not been studied. Methods We conducted a cross-sectional survey to investigate 3TC concentrations in hair as a predictor of virologic failure and drug resistance among HIV patients receiving free ART. We also compared the capacity of hair 3TC concentrations with self-reported adherence in predicting virologic responses. Hair 3TC concentrations were detected through the LC-MS/MS system. Results In patients without HIV drug resistance (HIVDR), with a threshold hair 3TC concentration of 260 ng/g, the sensitivity and specificity in predicting virologic suppression were 76.9% and 89.9%, respectively. Some factors, including CD4+ cell counts, initial treatment regimens with 3TC, and current regimens with second-line drugs, influenced the association between hair 3TC concentrations and virologic suppression. In patients who experienced virologic failure with HIVDR, with a threshold of 180 ng/g, the sensitivity and specificity were 70.0% and 74.4%, respectively. Hair 3TC concentrations had higher sensitivity and specificity in predicting virologic failure and drug resistance than self-reported adherence. Conclusions The hair 3TC concentration was a stronger indicator than self-reported adherence in predicting virologic failure and drug resistance in HIV patients receiving free ART. PMID:27119346

  1. Field-evolved resistance to Bt maize by western corn rootworm: predictions from the laboratory and effects in the field.

    PubMed

    Gassmann, Aaron J

    2012-07-01

    Crops engineered to produce insecticidal toxins derived from the bacterium Bacillus thuringiensis (Bt) provide an effective management tool for many key insect pests. However, pest species have repeatedly demonstrated their ability to adapt to management practices. Results from laboratory selection experiments illustrate the capacity of pest species to evolve Bt resistance. Furthermore, resistance has been documented to Bt sprays in the field and greenhouse, and more recently, by some pests to Bt crops in the field. In 2009, fields were discovered in Iowa (USA) with populations of western corn rootworm, Diabrotica virgifera virgifera LeConte, that had evolved resistance to maize that produces the Bt toxin Cry3Bb1. Fields with resistant insects in 2009 had been planted to Cry3Bb1 maize for at least three consecutive years and as many as 6years. Computer simulation models predicted that the western corn rootworm might evolve resistance to Bt maize in as few as 3years. Laboratory and field data for interactions between western corn rootworm and Bt maize indicate that currently commercialized products are not high-dose events, which increases the risk of resistance evolution because non-recessive resistance traits may enhance survival on Bt maize. Furthermore, genetic analysis of laboratory strains of western corn rootworm has found non-recessive inheritance of resistance. Field studies conducted in two fields identified as harboring Cry3Bb1-resistant western corn rootworm found that survival of western corn rootworm did not differ between Cry3Bb1 maize and non-Bt maize and that root injury to Cry3Bb1 maize was higher than injury to other types of Bt maize or to maize roots protected with a soil insecticide. These first cases of field-evolved resistance to Bt maize by western corn rootworm provide an early warning and point to the need to apply better integrated pest management practices when using Bt maize to manage western corn rootworm.

  2. Improved prediction of salvage antiretroviral therapy outcomes using ultrasensitive HIV-1 drug resistance testing.

    PubMed

    Pou, Christian; Noguera-Julian, Marc; Pérez-Álvarez, Susana; García, Federico; Delgado, Rafael; Dalmau, David; Álvarez-Tejado, Miguel; Gonzalez, Dimitri; Sayada, Chalom; Chueca, Natalia; Pulido, Federico; Ibáñez, Laura; Rodríguez, Cristina; Casadellà, Maria; Santos, José R; Ruiz, Lidia; Clotet, Bonaventura; Paredes, Roger

    2014-08-15

    The clinical relevance of ultrasensitive human immunodeficiency virus type 1 (HIV-1) genotypic resistance testing in antiretroviral treatment (ART)-experienced individuals remains unknown. This was a retrospective, multicentre, cohort study in ART-experienced, HIV-1-infected adults who initiated salvage ART including, at least 1 ritonavir-boosted protease inhibitor, raltegravir or etravirine. Presalvage ART Sanger and 454 sequencing of plasma HIV-1 were used to generate separate genotypic sensitivity scores (GSS) using the HIVdb, ANRS, and REGA algorithms. Virological failure (VF) was defined as 2 consecutive HIV-1 RNA levels ≥200 copies/mL at least 12 weeks after salvage ART initiation, whereas subjects remained on the same ART. The ability of Sanger and 454-GSS to predict VF was assessed by receiver operating characteristic (ROC) curves and survival analyses. The study included 132 evaluable subjects; 28 (21%) developed VF. Using HIVdb, 454 predicted VF better than Sanger sequencing in the ROC curve analysis (area under the curve: 0.69 vs 0.60, Delong test P = .029). Time to VF was shorter for subjects with 454-GSS < 3 vs 454-GSS ≥ 3 (Log-rank P = .003) but not significantly different between Sanger-GSS < 3 and ≥3. Factors independently associated with increased risk of VF in multivariate Cox regression were a 454-GSS < 3 (HR = 4.6, 95 CI, [1.5, 14.0], P = .007), and the number of previous antiretrovirals received (HR = 1.2 per additional drug, 95 CI, [1.1, 1.3], P = .001). Equivalent findings were obtained with the ANRS and REGA algorithms. Ultrasensitive HIV-1 genotyping improves GSS-based predictions of virological outcomes of salvage ART relative to Sanger sequencing. This may improve the clinical management of ART-experienced subjects living with HIV-1. NCT01346878. © The Author 2014. Published by Oxford University Press on behalf of the Infectious Diseases Society of America. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  3. Memory Reactivation Predicts Resistance to Retroactive Interference: Evidence from Multivariate Classification and Pattern Similarity Analyses

    PubMed Central

    Rugg, Michael D.

    2016-01-01

    Memory reactivation—the reinstatement of processes and representations engaged when an event is initially experienced—is believed to play an important role in strengthening and updating episodic memory. The present study examines how memory reactivation during a potentially interfering event influences memory for a previously experienced event. Participants underwent fMRI during the encoding phase of an AB/AC interference task in which some words were presented twice in association with two different encoding tasks (AB and AC trials) and other words were presented once (DE trials). The later memory test required retrieval of the encoding tasks associated with each of the study words. Retroactive interference was evident for the AB encoding task and was particularly strong when the AC encoding task was remembered rather than forgotten. We used multivariate classification and pattern similarity analysis (PSA) to measure reactivation of the AB encoding task during AC trials. The results demonstrated that reactivation of generic task information measured with multivariate classification predicted subsequent memory for the AB encoding task regardless of whether interference was strong and weak (trials for which the AC encoding task was remembered or forgotten, respectively). In contrast, reactivation of neural patterns idiosyncratic to a given AB trial measured with PSA only predicted memory when the strength of interference was low. These results suggest that reactivation of features of an initial experience shared across numerous events in the same category, but not features idiosyncratic to a particular event, are important in resisting retroactive interference caused by new learning. SIGNIFICANCE STATEMENT Reactivating a previously encoded memory is believed to provide an opportunity to strengthen the memory, but also to return the memory to a labile state, making it susceptible to interference. However, there is debate as to how memory reactivation elicited by

  4. Evaluation of genomic prediction methods for fusarium head blight resistance in wheat

    USDA-ARS?s Scientific Manuscript database

    Fusarium head blight (FHB) resistance is quantitative and difficult to evaluate. Genomic selection (GS) could accelerate FHB resistance breeding. We used US cooperative FHB wheat nursery data to evaluate GS models for several FHB resistance traits including deoxynivalenol (DON) levels. For all trait...

  5. Elevated AKAP12 in Paclitaxel-Resistant Serous Ovarian Cancer Cells is Prognostic and Predictive of Poor Survival in Patients

    PubMed Central

    Bateman, Nicholas W.; Jaworski, Elizabeth; Ao, Wei; Wang, Guisong; Litzi, Tracy; Dubil, Elizabeth; Marcus, Charlotte; Conrads, Kelly A.; Teng, Pang-ning; Hood, Brian L.; Phippen, Neil T.; Vasicek, Lisa A.; McGuire, William P.; Paz, Keren; Sidransky, David; Hamilton, Chad A.; Maxwell, G. Larry; Darcy, Kathleen M.; Conrads, Thomas P.

    2015-01-01

    A majority of high-grade (HG) serous ovarian cancer (SOC) patients develop resistant disease despite high initial response rates to platinum/paclitaxel-based chemotherapy. We identified shed/secreted proteins in preclinical models of paclitaxel-resistant human HGSOC models and correlated these candidate proteins with patient outcomes using public data from HGSOC patients. Proteomic analyses of a HGSOC cell line secretome was compared to those from a syngeneic paclitaxel-resistant variant and from a line established from an intrinsically chemorefractory HGSOC patient Associations between the identified candidate proteins and patient outcome were assessed in a discovery cohort of 545 patients and two validation cohorts totaling 795 independent SOC patients. Among the 81 differentially abundant proteins identified (q < 0.05) from paclitaxel-sensitive vs -resistant HGSOC cell secretomes, AKAP12 was verified to be elevated in all models of paclitaxel-resistant HGSOC. Furthermore, elevated AKAP12 transcript expression was associated with worse progression-free and overall survival. Associations with outcome were observed in three independent cohorts and remained significant after adjusted multivariate modeling. We further provide evidence to support that differential gene methyktion status is associated with elevated expression of AKAP12 in taxol-resistant ovarian cancer cells and ovarian cancer patient subsets. Elevated expression and shedding/secretion of AKAP12 is characteristic of paclitaxel-resistant HGSOC cells, and elevated AKAP12 transcript expression is a poor prognostic and predictive marker for progression-free and overall survival in SOC patients. PMID:25748058

  6. Role of the Egami score to predict immunoglobulin resistance in Kawasaki disease among a Western Mediterranean population.

    PubMed

    Sánchez-Manubens, Judith; Antón, Jordi; Bou, Rosa; Iglesias, Estíbaliz; Calzada-Hernandez, Joan; Borlan, Sergi; Gimenez-Roca, Clara; Rivera, Josefa

    2016-07-01

    Kawasaki disease is an acute self-limited systemic vasculitis common in childhood. Intravenous immunoglobulin (IVIG) is an effective treatment, and it reduces the incidence of cardiac complications. Egami score has been validated to identify IVIG non-responder patients in Japanese population, and it has shown high sensitivity and specificity to identify these non-responder patients. Although its effectiveness in Japan, Egami score has shown to be ineffective in non-Japanese populations. The aim of this study was to apply the Egami score in a Western Mediterranean population in Catalonia (Spain). Observational population-based study that includes patients from all Pediatric Units in 33 Catalan hospitals, both public and private management, between January 2004 and March 2014. Sensitivity and specificity for the Egami score was calculated, and a logistic regression analysis of predictors of overall response to IVIG was also developed. Predicting IVIG resistance with a cutoff for Egami score ≥3 obtained 26 % sensitivity and 82 % specificity. Negative predictive value was 85 % and positive predictive value 22 %. This low sensitivity implies that three out of four non-responders will not be identified by the Egami score. Besides, logistic regression models did not found significance for the use of the Egami score to predict IVIG resistance in Catalan population although having an area under the ROC curve of 0.618 (IC 95 % 0.538-0.698, p < 0.001). Although regression models found an area under the ROC curve >0.5 to predict IVIG resistance, the low sensitivity excludes the Egami score as a useful tool to predict IVIG resistance in Catalan population.

  7. Predicting date rape perceptions: the effects of gender, gender role attitudes, and victim resistance.

    PubMed

    Black, Katherine A; McCloskey, Kathy A

    2013-08-01

    The effects of participant gender and victim resistance on date rape perceptions have been inconsistent. Participant gender role attitudes may contribute to these inconsistencies. We found women with traditional gender role attitudes were least likely to agree that the perpetrator was guilty of rape. Participants were less convinced of the perpetrator's guilt when the victim resisted verbally than when she resisted verbally and physically, and participants with traditional gender role attitudes were less convinced of the negative impact on the victim when she resisted verbally than when she resisted verbally and physically. Perhaps previous inconsistencies resulted from varying proportions of men and women with traditional versus liberal gender role attitudes in the samples.

  8. Comparing the Predictive Capacity of Observed In-Session Resistance to Self-Reported Motivation in Cognitive Behavioral Therapy

    PubMed Central

    Westra, Henny A.

    2010-01-01

    Self-report measures of motivation for changing anxiety have been weakly and inconsistently related to outcome in cognitive behavioral therapy (CBT). While clients may not be able to accurately report their motivation, ambivalence about change may nonetheless be expressed in actual therapy sessions as opposition to the direction set by the therapist (i.e., resistance). In the context of CBT for generalized anxiety disorder, the present study compared the ability of observed in-session resistance in CBT session 1 and two self-report measures of motivation for changing anxiety (the Change Questionnaire & the Client Motivational for Therapy Scale) to (1) predict client and therapist rated homework compliance (2) predict post-CBT and one-year post-treatment worry reduction, and (3) differentiate those who received motivational interviewing prior to CBT from those who received no pretreatment. Observed in-session resistance performed very well on each index, compared to the performance of self-reported motivation which was inconsistent and weaker relative to observed resistance. These findings strongly support both clinician sensitivity to moments of client resistance in actual therapy sessions as early as session 1, and the inclusion of observational process measures in CBT research. PMID:21159325

  9. Predicting treatment failure, death and drug resistance using a computed risk score among newly diagnosed TB patients in Tamaulipas, Mexico.

    PubMed

    Abdelbary, B E; Garcia-Viveros, M; Ramirez-Oropesa, H; Rahbar, M H; Restrepo, B I

    2017-09-14

    The purpose of this study was to develop a method for identifying newly diagnosed tuberculosis (TB) patients at risk for TB adverse events in Tamaulipas, Mexico. Surveillance data between 2006 and 2013 (8431 subjects) was used to develop risk scores based on predictive modelling. The final models revealed that TB patients failing their treatment regimen were more likely to have at most a primary school education, multi-drug resistance (MDR)-TB, and few to moderate bacilli on acid-fast bacilli smear. TB patients who died were more likely to be older males with MDR-TB, HIV, malnutrition, and reporting excessive alcohol use. Modified risk scores were developed with strong predictability for treatment failure and death (c-statistic 0·65 and 0·70, respectively), and moderate predictability for drug resistance (c-statistic 0·57). Among TB patients with diabetes, risk scores showed moderate predictability for death (c-statistic 0·68). Our findings suggest that in the clinical setting, the use of our risk scores for TB treatment failure or death will help identify these individuals for tailored management to prevent these adverse events. In contrast, the available variables in the TB surveillance dataset are not robust predictors of drug resistance, indicating the need for prompt testing at time of diagnosis.

  10. DRUG INTERVENTION RESPONSE PREDICTIONS WITH PARADIGM (DIRPP) IDENTIFIES DRUG RESISTANT CANCER CELL LINES AND PATHWAY MECHANISMS OF RESISTANCE

    PubMed Central

    DIFEO, ANALISA; CHEN, YANWEN; PEARL, TAYLOR; ZHAI, KAIDE; BEBEK, GURKAN; CHANCE, MARK; BARNHOLTZ-SLOAN, JILL

    2014-01-01

    The revolution in sequencing techniques in the past decade has provided an extensive picture of the molecular mechanisms behind complex diseases such as cancer. The Cancer Cell Line Encyclopedia (CCLE) and The Cancer Genome Project (CGP) have provided an unprecedented opportunity to examine copy number, gene expression, and mutational information for over 1000 cell lines of multiple tumor types alongside IC50 values for over 150 different drugs and drug related compounds. We present a novel pipeline called DIRPP, Drug Intervention Response Predictions with PARADIGM7, which predicts a cell line’s response to a drug intervention from molecular data. PARADIGM (Pathway Recognition Algorithm using Data Integration on Genomic Models) is a probabilistic graphical model used to infer patient specific genetic activity by integrating copy number and gene expression data into a factor graph model of a cellular network. We evaluated the performance of DIRPP on endometrial, ovarian, and breast cancer related cell lines from the CCLE and CGP for nine drugs. The pipeline is sensitive enough to predict the response of a cell line with accuracy and precision across datasets as high as 80 and 88% respectively. We then classify drugs by the specific pathway mechanisms governing drug response. This classification allows us to compare drugs by cellular response mechanisms rather than simply by their specific gene targets. This pipeline represents a novel approach for predicting clinical drug response and generating novel candidates for drug repurposing and repositioning. PMID:24297540

  11. Chronic kidney disease and diabetes mellitus predict resistance to vitamin D replacement therapy.

    PubMed

    Alshayeb, Hala M; Wall, Barry M; Showkat, Arif; Mangold, Therese; Quarles, L Darryl

    2013-04-01

    25-Hydroxyvitamin D [25(OH)D] is a marker of nutritional status; however, chronic kidney disease (CKD) results in alterations in vitamin D metabolism, including the loss of vitamin D-binding proteins and alterations in CYP27B1 and CYP24 enzymes that metabolize 25(OH)D. This study was designed to determine the predictors of responsiveness to correction of vitamin D deficiency with oral vitamin D2 (ergocalciferol) in adults. A retrospective study of 183 veterans with 25(OH)D level <30 ng/mL, who were treated with 50,000 IU per week of vitamin D2, was performed. Logistic regression models were developed to determine the factors predicting the response to treatment, defined as either the change in serum 25(OH)D level/1000 IU of vitamin D2 or the number of vitamin D2 doses (50,000 IU per dose) administered. The mean age of the patients was 63 ± 12 years. About 87% were men and 51% diabetic, and 29% had an estimated glomerular filtration rate of <60 mL/min/1.73 m. The average number of vitamin D2 doses was 10.91 ± 5.95; the average increase in 25(OH)D level was 18 ± 10.80 ng/mL. 25(OH)D levels remained <30 ng/mL in 61 patients after treatment. A low estimated glomerular filtration rate and the presence of diabetes mellitus were significant independent predictors for inadequate response to vitamin D2 treatment in logistic regression models. Patients with CKD required greater amounts of vitamin D2 to achieve similar increases in 25(OH)D levels, versus non-CKD patients. The presence of CKD and diabetes mellitus is associated with resistance to correction of 25(OH)D deficiency with vitamin D2 therapy. The underlying mechanism needs to be evaluated in prospective studies.

  12. Whole-Genome Sequencing Analysis Accurately Predicts Antimicrobial Resistance Phenotypes in Campylobacter spp.

    PubMed

    Zhao, S; Tyson, G H; Chen, Y; Li, C; Mukherjee, S; Young, S; Lam, C; Folster, J P; Whichard, J M; McDermott, P F

    2015-10-30

    The objectives of this study were to identify antimicrobial resistance genotypes for Campylobacter and to evaluate the correlation between resistance phenotypes and genotypes using in vitro antimicrobial susceptibility testing and whole-genome sequencing (WGS). A total of 114 Campylobacter species isolates (82 C. coli and 32 C. jejuni) obtained from 2000 to 2013 from humans, retail meats, and cecal samples from food production animals in the United States as part of the National Antimicrobial Resistance Monitoring System were selected for study. Resistance phenotypes were determined using broth microdilution of nine antimicrobials. Genomic DNA was sequenced using the Illumina MiSeq platform, and resistance genotypes were identified using assembled WGS sequences through blastx analysis. Eighteen resistance genes, including tet(O), blaOXA-61, catA, lnu(C), aph(2″)-Ib, aph(2″)-Ic, aph(2')-If, aph(2″)-Ig, aph(2″)-Ih, aac(6')-Ie-aph(2″)-Ia, aac(6')-Ie-aph(2″)-If, aac(6')-Im, aadE, sat4, ant(6'), aad9, aph(3')-Ic, and aph(3')-IIIa, and mutations in two housekeeping genes (gyrA and 23S rRNA) were identified. There was a high degree of correlation between phenotypic resistance to a given drug and the presence of one or more corresponding resistance genes. Phenotypic and genotypic correlation was 100% for tetracycline, ciprofloxacin/nalidixic acid, and erythromycin, and correlations ranged from 95.4% to 98.7% for gentamicin, azithromycin, clindamycin, and telithromycin. All isolates were susceptible to florfenicol, and no genes associated with florfenicol resistance were detected. There was a strong correlation (99.2%) between resistance genotypes and phenotypes, suggesting that WGS is a reliable indicator of resistance to the nine antimicrobial agents assayed in this study. WGS has the potential to be a powerful tool for antimicrobial resistance surveillance programs.

  13. Predicting Antibiotic Resistance in Urinary Tract Infection Patients with Prior Urine Cultures

    PubMed Central

    Geffen, Yuval; Andreassen, Steen; Leibovici, Leonard; Paul, Mical

    2016-01-01

    To improve antibiotic prescribing, we sought to establish the probability of a resistant organism in urine culture given a previous resistant culture in a setting endemic for multidrug-resistant (MDR) organisms. We performed a retrospective analysis of inpatients with paired positive urine cultures. We focused on ciprofloxacin-resistant (cipror) Gram-negative bacteria, extended-spectrum-beta-lactamase (ESBL)-producing Enterobacteriaceae, carbapenem-resistant Enterobacteriaceae (CRE), and carbapenem-resistant nonfermenters (CRNF). Comparisons were made between the frequency of each resistance phenotype following a previous culture with the same phenotype and the overall frequency of that phenotype, and odds ratios (ORs) were calculated. We performed a regression to assess the effects of other variables on the likelihood of a repeat resistant culture. A total of 4,409 patients (52.5% women; median age, 70 years) with 19,546 paired positive urine cultures were analyzed. The frequencies of cipror bacteria, ESBL-producing Enterobacteriaceae, CRE, and CRNF among all cultures were 47.7%, 30.6%, 1.7%, and 2.6%, respectively. ORs for repeated resistance phenotypes were 1.87, 3.19, 48.25, and 19.02 for cipror bacteria, ESBL-producing Enterobacteriaceae, CRE, and CRNF, respectively (P < 0.001 for all). At 1 month, the frequencies of repeated resistance phenotypes were 77.4%, 66.4%, 57.1%, and 33.3% for cipror bacteria, ESBL-producing Enterobacteriaceae, CRE, and CRNF, respectively. Increasing time between cultures and the presence of an intervening nonresistant culture significantly reduced the chances of a repeat resistant culture. Associations were statistically significant over the duration of follow-up (60 months) for CRE and for up to 6 months for all other pathogens. Knowledge of microbiology results in the six preceding months may assist with antibiotic stewardship and improve the appropriateness of empirical treatment for urinary tract infections (UTIs). PMID:27216064

  14. Prediction of multi-drug resistance transporters using a novel sequence analysis method [version 2; referees: 2 approved

    SciTech Connect

    McDermott, Jason E.; Bruillard, Paul; Overall, Christopher C.; Gosink, Luke; Lindemann, Stephen R.

    2015-03-09

    There are many examples of groups of proteins that have similar function, but the determinants of functional specificity may be hidden by lack of sequencesimilarity, or by large groups of similar sequences with different functions. Transporters are one such protein group in that the general function, transport, can be easily inferred from the sequence, but the substrate specificity can be impossible to predict from sequence with current methods. In this paper we describe a linguistic-based approach to identify functional patterns from groups of unaligned protein sequences and its application to predict multi-drug resistance transporters (MDRs) from bacteria. We first show that our method can recreate known patterns from PROSITE for several motifs from unaligned sequences. We then show that the method, MDRpred, can predict MDRs with greater accuracy and positive predictive value than a collection of currently available family-based models from the Pfam database. Finally, we apply MDRpred to a large collection of protein sequences from an environmental microbiome study to make novel predictions about drug resistance in a potential environmental reservoir.

  15. Prediction of multi-drug resistance transporters using a novel sequence analysis method [version 2; referees: 2 approved

    DOE PAGES

    McDermott, Jason E.; Bruillard, Paul; Overall, Christopher C.; ...

    2015-03-09

    There are many examples of groups of proteins that have similar function, but the determinants of functional specificity may be hidden by lack of sequencesimilarity, or by large groups of similar sequences with different functions. Transporters are one such protein group in that the general function, transport, can be easily inferred from the sequence, but the substrate specificity can be impossible to predict from sequence with current methods. In this paper we describe a linguistic-based approach to identify functional patterns from groups of unaligned protein sequences and its application to predict multi-drug resistance transporters (MDRs) from bacteria. We first showmore » that our method can recreate known patterns from PROSITE for several motifs from unaligned sequences. We then show that the method, MDRpred, can predict MDRs with greater accuracy and positive predictive value than a collection of currently available family-based models from the Pfam database. Finally, we apply MDRpred to a large collection of protein sequences from an environmental microbiome study to make novel predictions about drug resistance in a potential environmental reservoir.« less

  16. A comparison of two types of neural network for weld quality prediction in small scale resistance spot welding

    NASA Astrophysics Data System (ADS)

    Wan, Xiaodong; Wang, Yuanxun; Zhao, Dawei; Huang, YongAn

    2017-09-01

    Our study aims at developing an effective quality monitoring system in small scale resistance spot welding of titanium alloy. The measured electrical signals were interpreted in combination with the nugget development. Features were extracted from the dynamic resistance and electrode voltage curve. A higher welding current generally indicated a lower overall dynamic resistance level. A larger electrode voltage peak and higher change rate of electrode voltage could be detected under a smaller electrode force or higher welding current condition. Variation of the extracted features and weld quality was found more sensitive to the change of welding current than electrode force. Different neural network model were proposed for weld quality prediction. The back propagation neural network was more proper in failure load estimation. The probabilistic neural network model was more appropriate to be applied in quality level classification. A real-time and on-line weld quality monitoring system may be developed by taking advantages of both methods.

  17. Penicillin-Binding Protein Transpeptidase Signatures for Tracking and Predicting β-Lactam Resistance Levels in Streptococcus pneumoniae

    PubMed Central

    Metcalf, Benjamin J.; Chochua, Sopio; Li, Zhongya; Gertz, Robert E.; Walker, Hollis; Hawkins, Paulina A.; Tran, Theresa; Whitney, Cynthia G.; McGee, Lesley; Beall, Bernard W.

    2016-01-01

    ABSTRACT β-Lactam antibiotics are the drugs of choice to treat pneumococcal infections. The spread of β-lactam-resistant pneumococci is a major concern in choosing an effective therapy for patients. Systematically tracking β-lactam resistance could benefit disease surveillance. Here we developed a classification system in which a pneumococcal isolate is assigned to a “PBP type” based on sequence signatures in the transpeptidase domains (TPDs) of the three critical penicillin-binding proteins (PBPs), PBP1a, PBP2b, and PBP2x. We identified 307 unique PBP types from 2,528 invasive pneumococcal isolates, which had known MICs to six β-lactams based on broth microdilution. We found that increased β-lactam MICs strongly correlated with PBP types containing divergent TPD sequences. The PBP type explained 94 to 99% of variation in MICs both before and after accounting for genomic backgrounds defined by multilocus sequence typing, indicating that genomic backgrounds made little independent contribution to β-lactam MICs at the population level. We further developed and evaluated predictive models of MICs based on PBP type. Compared to microdilution MICs, MICs predicted by PBP type showed essential agreement (MICs agree within 1 dilution) of >98%, category agreement (interpretive results agree) of >94%, a major discrepancy (sensitive isolate predicted as resistant) rate of <3%, and a very major discrepancy (resistant isolate predicted as sensitive) rate of <2% for all six β-lactams. Thus, the PBP transpeptidase signatures are robust indicators of MICs to different β-lactam antibiotics in clinical pneumococcal isolates and serve as an accurate alternative to phenotypic susceptibility testing. PMID:27302760

  18. An interferon-related gene signature for DNA damage resistance is a predictive marker for chemotherapy and radiation for breast cancer

    PubMed Central

    Weichselbaum, Ralph R.; Ishwaran, Hemant; Yoon, Taewon; Nuyten, Dimitry S. A.; Baker, Samuel W.; Khodarev, Nikolai; Su, Andy W.; Shaikh, Arif Y.; Roach, Paul; Kreike, Bas; Roizman, Bernard; Bergh, Jonas; Pawitan, Yudi; van de Vijver, Marc J.; Minn, Andy J.

    2008-01-01

    Individualization of cancer management requires prognostic markers and therapy-predictive markers. Prognostic markers assess risk of disease progression independent of therapy, whereas therapy-predictive markers identify patients whose disease is sensitive or resistant to treatment. We show that an experimentally derived IFN-related DNA damage resistance signature (IRDS) is associated with resistance to chemotherapy and/or radiation across different cancer cell lines. The IRDS genes STAT1, ISG15, and IFIT1 all mediate experimental resistance. Clinical analyses reveal that IRDS(+) and IRDS(−) states exist among common human cancers. In breast cancer, a seven–gene-pair classifier predicts for efficacy of adjuvant chemotherapy and for local-regional control after radiation. By providing information on treatment sensitivity or resistance, the IRDS improves outcome prediction when combined with standard markers, risk groups, or other genomic classifiers. PMID:19001271

  19. Flow network QSAR for the prediction of physicochemical properties by mapping an electrical resistance network onto a chemical reaction poset.

    PubMed

    Ivanciuc, Ovidiu; Ivanciuc, Teodora; Klein, Douglas J

    2013-06-01

    Usual quantitative structure-activity relationship (QSAR) models are computed from unstructured input data, by using a vector of molecular descriptors for each chemical in the dataset. Another alternative is to consider the structural relationships between the chemical structures, such as molecular similarity, presence of certain substructures, or chemical transformations between compounds. We defined a class of network-QSAR models based on molecular networks induced by a sequence of substitution reactions on a chemical structure that generates a partially ordered set (or poset) oriented graph that may be used to predict various molecular properties with quantitative superstructure-activity relationships (QSSAR). The network-QSAR interpolation models defined on poset graphs, namely average poset, cluster expansion, and spline poset, were tested with success for the prediction of several physicochemical properties for diverse chemicals. We introduce the flow network QSAR, a new poset regression model in which the dataset of chemicals, represented as a reaction poset, is transformed into an oriented network of electrical resistances in which the current flow results in a potential at each node. The molecular property considered in the QSSAR model is represented as the electrical potential, and the value of this potential at a particular node is determined by the electrical resistances assigned to each edge and by a system of batteries. Each node with a known value for the molecular property is attached to a battery that sets the potential on that node to the value of the respective molecular property, and no external battery is attached to nodes from the prediction set, representing chemicals for which the values of the molecular property are not known or are intended to be predicted. The flow network QSAR algorithm determines the values of the molecular property for the prediction set of molecules by applying Ohm's law and Kirchhoff's current law to the poset

  20. Metabolic markers associated with insulin resistance predict type 2 diabetes in Koreans with normal blood pressure or prehypertension.

    PubMed

    Sung, Ki-Chul; Park, Hyun-Young; Kim, Min-Ju; Reaven, Gerald

    2016-03-22

    Questions remain as to the association between essential hypertension and increased incidence of type 2 diabetes (T2DM). The premise of this analysis is that insulin resistance/compensatory hyperinsulinemia is a major predictor of T2DM, and the greater the prevalence of insulin resistance within any population, normotensive or hypertensive, the more likely T2DM will develop. The hypothesis to be tested is that surrogate estimates of insulin resistance will predict incident T2DM to a significant degree in persons with normal blood pressure or prehypertension. Analysis of data from a population-based survey of 10, 038 inhabitants of rural and urban areas of Korea, ≥40 years-old, initiated in 2001, with measures of demographic and metabolic characteristics at baseline and 8-years later. Participants were classified as having normal blood pressure or prehypertension, and three simple manifestations of insulin resistance related to the pathophysiology of T2DM used to predict incident T2DM: (1) glycemia (plasma glucose concentration 2-hour after 75 g oral glucose challenge = 2-hour PG); (2) hyperinsulinemia (plasma insulin concentration 2-hour after 75 g oral glucose challenge = 2-hour PI); and (3) dyslipidemia (ratio of fasting plasma triglyceride/high/density lipoprotein cholesterol concentration = TG/HDL-C ratio). Fully adjusted hazard ratios (HR, 95 % CI) for incident T2DM were highest (P < 0.001) in the quartile of individuals with the highest 2-hour PG concentrations, ranging from 5.84 (3.37-10.1) in women with prehypertension to 12.2 (7.12-21.00) in men with normal blood pressure. T2DM also developed to a significantly greater degree in subjects within the highest quartile of TG/HDL-C ratios, with HRs varying from 2.91 (1.63-2.58) in women with prehypertension (P < 0.001) to 1.77 (1.12-2.81, P < 0.05) in men with prehypertension. The least predictive index of insulin resistance was the 2-hour PI concentration. Subjects with normal blood pressure in the highest

  1. Predictability of Phenotype in Relation to Common β-Lactam Resistance Mechanisms in Escherichia coli and Klebsiella pneumoniae

    PubMed Central

    Agyekum, Alex; Ai, Xiaoman; Ginn, Andrew N.; Zong, Zhiyong; Guo, Xuejun; Turnidge, John; Partridge, Sally R.

    2016-01-01

    The minimal concentration of antibiotic required to inhibit the growth of different isolates of a given species with no acquired resistance mechanisms has a normal distribution. We have previously shown that the presence or absence of transmissible antibiotic resistance genes has excellent predictive power for phenotype. In this study, we analyzed the distribution of six β-lactam antibiotic susceptibility phenotypes associated with commonly acquired resistance genes in Enterobacteriaceae in Sydney, Australia. Escherichia coli (n = 200) and Klebsiella pneumoniae (n = 178) clinical isolates, with relevant transmissible resistance genes (blaTEM, n = 33; plasmid AmpC, n = 69; extended-spectrum β-lactamase [ESBL], n = 116; and carbapenemase, n = 100), were characterized. A group of 60 isolates with no phenotypic resistance to any antibiotics tested and carrying none of the important β-lactamase genes served as comparators. The MICs for all drug-bacterium combinations had a normal distribution, varying only in the presence of additional genes relevant to the phenotype or, for ertapenem resistance in K. pneumoniae, with a loss or change in the outer membrane porin protein OmpK36. We demonstrated mutations in ompK36 or absence of OmpK36 in all isolates in which reduced susceptibility to ertapenem (MIC, >1 mg/liter) was evident. Ertapenem nonsusceptibility in K. pneumoniae was most common in the context of an OmpK36 variant with an ESBL or AmpC gene. Surveillance strategies to define appropriate antimicrobial therapies should include genotype-phenotype relationships for all major transmissible resistance genes and the characterization of mutations in relevant porins in organisms, like K. pneumoniae. PMID:26912748

  2. Passenger vehicle tire rolling resistance can be predicted from a flat-belt test rig

    SciTech Connect

    Ivens, J.

    1989-01-01

    The rolling resistance of fifteen different types of tire was determined on-road by coastdown tests, using several vehicles variously fitted with 14 and 15 inch wheels. Corrections for tire pressure, and for external temperature, were deduced by data regression. The rolling resistance of the same tires was measured on a flat-belt tire test machine, and correction for tire pressure was determined in a like manner. In this paper, the results, in terms of the characteristic rolling resistance, are compared between rig and road. The various test procedures are discussed.

  3. Predicting active slip systems in β-Sn from ideal shear resistance

    NASA Astrophysics Data System (ADS)

    Kinoshita, Y.; Matsushima, H.; Ohno, N.

    2012-04-01

    We analyse the ideal shear resistances of 15 nonequivalent slip systems in β-Sn using first-principles density functional theory. From the ideal shear resistance and Schmid's law, the orientation dependence of active slip systems in a β-Sn single crystal subjected to uniaxial tension is investigated. We find that (1\\,0\\,1)[\\bar{1}\\,0\\,1] has the lowest ideal shear resistance among the 15 slip systems. Our calculations indicate that, depending on crystal orientation, uniaxial tension activates seven nonequivalent groups of slip systems. The active slip systems for [1 0 0] and [1 1 0] orientations determined in this study agree with the experimental results.

  4. Whole-Genome Sequencing Analysis Accurately Predicts Antimicrobial Resistance Phenotypes in Campylobacter spp.

    PubMed Central

    Tyson, G. H.; Chen, Y.; Li, C.; Mukherjee, S.; Young, S.; Lam, C.; Folster, J. P.; Whichard, J. M.; McDermott, P. F.

    2015-01-01

    The objectives of this study were to identify antimicrobial resistance genotypes for Campylobacter and to evaluate the correlation between resistance phenotypes and genotypes using in vitro antimicrobial susceptibility testing and whole-genome sequencing (WGS). A total of 114 Campylobacter species isolates (82 C. coli and 32 C. jejuni) obtained from 2000 to 2013 from humans, retail meats, and cecal samples from food production animals in the United States as part of the National Antimicrobial Resistance Monitoring System were selected for study. Resistance phenotypes were determined using broth microdilution of nine antimicrobials. Genomic DNA was sequenced using the Illumina MiSeq platform, and resistance genotypes were identified using assembled WGS sequences through blastx analysis. Eighteen resistance genes, including tet(O), blaOXA-61, catA, lnu(C), aph(2″)-Ib, aph(2″)-Ic, aph(2′)-If, aph(2″)-Ig, aph(2″)-Ih, aac(6′)-Ie-aph(2″)-Ia, aac(6′)-Ie-aph(2″)-If, aac(6′)-Im, aadE, sat4, ant(6′), aad9, aph(3′)-Ic, and aph(3′)-IIIa, and mutations in two housekeeping genes (gyrA and 23S rRNA) were identified. There was a high degree of correlation between phenotypic resistance to a given drug and the presence of one or more corresponding resistance genes. Phenotypic and genotypic correlation was 100% for tetracycline, ciprofloxacin/nalidixic acid, and erythromycin, and correlations ranged from 95.4% to 98.7% for gentamicin, azithromycin, clindamycin, and telithromycin. All isolates were susceptible to florfenicol, and no genes associated with florfenicol resistance were detected. There was a strong correlation (99.2%) between resistance genotypes and phenotypes, suggesting that WGS is a reliable indicator of resistance to the nine antimicrobial agents assayed in this study. WGS has the potential to be a powerful tool for antimicrobial resistance surveillance programs. PMID:26519386

  5. Predicting Antibiotic Resistance in Urinary Tract Infection Patients with Prior Urine Cultures.

    PubMed

    Dickstein, Yaakov; Geffen, Yuval; Andreassen, Steen; Leibovici, Leonard; Paul, Mical

    2016-08-01

    To improve antibiotic prescribing, we sought to establish the probability of a resistant organism in urine culture given a previous resistant culture in a setting endemic for multidrug-resistant (MDR) organisms. We performed a retrospective analysis of inpatients with paired positive urine cultures. We focused on ciprofloxacin-resistant (cipro(r)) Gram-negative bacteria, extended-spectrum-beta-lactamase (ESBL)-producing Enterobacteriaceae, carbapenem-resistant Enterobacteriaceae (CRE), and carbapenem-resistant nonfermenters (CRNF). Comparisons were made between the frequency of each resistance phenotype following a previous culture with the same phenotype and the overall frequency of that phenotype, and odds ratios (ORs) were calculated. We performed a regression to assess the effects of other variables on the likelihood of a repeat resistant culture. A total of 4,409 patients (52.5% women; median age, 70 years) with 19,546 paired positive urine cultures were analyzed. The frequencies of cipro(r) bacteria, ESBL-producing Enterobacteriaceae, CRE, and CRNF among all cultures were 47.7%, 30.6%, 1.7%, and 2.6%, respectively. ORs for repeated resistance phenotypes were 1.87, 3.19, 48.25, and 19.02 for cipro(r) bacteria, ESBL-producing Enterobacteriaceae, CRE, and CRNF, respectively (P < 0.001 for all). At 1 month, the frequencies of repeated resistance phenotypes were 77.4%, 66.4%, 57.1%, and 33.3% for cipro(r) bacteria, ESBL-producing Enterobacteriaceae, CRE, and CRNF, respectively. Increasing time between cultures and the presence of an intervening nonresistant culture significantly reduced the chances of a repeat resistant culture. Associations were statistically significant over the duration of follow-up (60 months) for CRE and for up to 6 months for all other pathogens. Knowledge of microbiology results in the six preceding months may assist with antibiotic stewardship and improve the appropriateness of empirical treatment for urinary tract infections (UTIs

  6. Comparison of Clinical Prediction Models for Resistant Bacteria in Community-onset Pneumonia

    PubMed Central

    Self, Wesley H.; Wunderink, Richard G.; Williams, Derek J.; Barrett, Tyler W.; Baughman, Adrienne H.; Grijalva, Carlos G.

    2015-01-01

    Objectives Six recently published algorithms classify pneumonia patients presenting from the community into high- and low-risk groups for resistant bacteria. Our objective was to compare performance of these algorithms for identifying patients infected with bacteria resistant to traditional community-acquired pneumonia antibiotics. Methods This was a retrospective study of consecutive adult patients diagnosed with pneumonia in an emergency department and subsequently hospitalized. Each patient was classified as high- or low-risk for resistant bacteria according to the following algorithms: original health care-associated pneumonia (HCAP) criteria, Summit criteria, Brito and Niederman strategy, Shorr model, Aliberti model, and Shindo model. The reference for comparison was detection of resistant bacteria, defined as methicillin-resistant Staphylococcus aureus or gram-negative bacteria resistant to ceftriaxone or levofloxacin. Results Six hundred fourteen patients were studied, including 36 (5.9%) with resistant bacteria. The HCAP criteria classified 304 (49.5%) patients as high-risk, with an area under the receiver operating characteristic curve (AUC) of 0.63 (95% CI = 0.54 to 0.72), sensitivity of 0.69 (95% CI = 0.52 to 0.83), and specificity of 0.52 (95% CI = 0.48 to 0.56). None of the other algorithms improved both sensitivity and specificity, or significantly improved the AUC. Compared to the HCAP criteria, the Shorr and Aliberti models classified more patients as high-risk, resulting in higher sensitivity and lower specificity. The Shindo model classified fewer patients as high-risk, with lower sensitivity and higher specificity. Conclusions All algorithms for identification of resistant bacteria included in this study had suboptimal performance to guide antibiotic selection. New strategies for selecting empirical antibiotics for community-onset pneumonia are necessary. PMID:25996620

  7. miR-21 Expression in Cancer Cells may Not Predict Resistance to Adjuvant Trastuzumab in Primary Breast Cancer.

    PubMed

    Nielsen, Boye Schnack; Balslev, Eva; Poulsen, Tim Svenstrup; Nielsen, Dorte; Møller, Trine; Mortensen, Christiane Ehlers; Holmstrøm, Kim; Høgdall, Estrid

    2014-01-01

    Trastuzumab is established as standard care for patients with HER2-positive breast cancer both in the adjuvant and metastatic setting. However, 50% of the patients do not respond to the trastuzumab therapy, and therefore new predictive biomarkers are highly warranted. MicroRNAs (miRs) constitute a new group of biomarkers and their cellular expression can be determined in tumor samples by in situ hybridization (ISH) analysis. miR-21 is highly prevalent and up-regulated in breast cancer and has been linked to drug resistance in clinical and in vitro settings. To determine expression patterns of miR-21 in high-grade breast cancers, we examined miR-21 expression in 22 HER2-positive tumors and 15 HER2-negative high-grade tumors by ISH. The histological examination indicated that patient samples could be divided into three major expression patterns: miR-21 predominantly in tumor stroma, predominantly in cancer cells, or in both stromal and cancer cells. There was no obvious difference between the HER2-positive and HER2-negative tumors in terms of the miR-21 expression patterns and intensities. To explore the possibility that miR-21 expression levels and/or cellular localization could predict resistance to adjuvant trastuzumab in HER2-positive breast cancer patients, we analyzed additional 16 HER2-positive tumors from patients who were treated with trastuzumab in the adjuvant setting. Eight of the 16 patients showed clinical recurrence and were considered resistant. Examination of the miR-21 expression patterns and intensities revealed no association between the miR-21 scores in the cancer cell population (p = 0.69) or the stromal cells population (p = 0.13) and recurrent disease after adjuvant trastuzumab. Thus, our findings show that elevated miR-21 expression does not predict resistance to adjuvant trastuzumab.

  8. Use of serologic tests to predict resistance to Canine distemper virus-induced disease in vaccinated dogs.

    PubMed

    Jensen, Wayne A; Totten, Janet S; Lappin, Michael R; Schultz, Ronald D

    2015-09-01

    The objective of the current study was to determine whether detection of Canine distemper virus (CDV)-specific serum antibodies correlates with resistance to challenge with virulent virus. Virus neutralization (VN) assay results were compared with resistance to viral challenge in 2 unvaccinated Beagle puppies, 9 unvaccinated Beagle dogs (4.4-7.2 years of age), and 9 vaccinated Beagle dogs (3.7-4.7 years of age). Eight of 9 (89%) unvaccinated adult dogs exhibited clinical signs after virus challenge, and 1 (13%) dog died. As compared to adult dogs, the 2 unvaccinated puppies developed more severe clinical signs and either died or were euthanized after challenge. In contrast, no clinical signs were detected after challenge of the 9 adult vaccinated dogs with post-vaccination intervals of up to 4.4 years. In vaccinated dogs, the positive and negative predictive values of VN assay results for resistance to challenge were 100% and 0%, respectively. Results indicate that dogs vaccinated with modified live CDV can be protected from challenge for ≤4.4 years postvaccination and that detection of virus-specific antibodies is predictive of whether dogs are resistant to challenge with virulent virus. Results also indicate that CDV infection in unvaccinated dogs results in age-dependent morbidity and mortality. Knowledge of age-dependent morbidity and mortality, duration of vaccine-induced immunity, and the positive and negative predictive values of detection of virus-specific serum antibodies are useful in development of rational booster vaccination intervals for the prevention of CDV-mediated disease in adult dogs.

  9. Improved model predictive control of resistive wall modes by error field estimator in EXTRAP T2R

    NASA Astrophysics Data System (ADS)

    Setiadi, A. C.; Brunsell, P. R.; Frassinetti, L.

    2016-12-01

    Many implementations of a model-based approach for toroidal plasma have shown better control performance compared to the conventional type of feedback controller. One prerequisite of model-based control is the availability of a control oriented model. This model can be obtained empirically through a systematic procedure called system identification. Such a model is used in this work to design a model predictive controller to stabilize multiple resistive wall modes in EXTRAP T2R reversed-field pinch. Model predictive control is an advanced control method that can optimize the future behaviour of a system. Furthermore, this paper will discuss an additional use of the empirical model which is to estimate the error field in EXTRAP T2R. Two potential methods are discussed that can estimate the error field. The error field estimator is then combined with the model predictive control and yields better radial magnetic field suppression.

  10. Improving predictions of the risk of resistance development against new and old antibiotics.

    PubMed

    Andersson, D I

    2015-10-01

    The methods used today by academic researchers and the pharmaceutical industry to assess the risk of emergence of resistance, for example during development of new antibiotics or when assessing an old antibiotic, are sub-optimal. Even though easy to perform, the presently used serial passage procedures, minimal prevention concentration measurements and determination of mutation rates in vitro are generally providing inadequate knowledge for risk assessment and making decisions to continue/discontinue drug development. These methods need to be complemented and replaced with more relevant methods such as determination of whether resistance genes already pre-exist in various metagenomes, and the likelihood that these genes can transfer into the relevant pathogens and be stably maintained. Furthermore, to determine the risk of emergence of mutationally conferred resistance the fitness effect of the resistance mechanism is key, as this parameter will determine the ability of the resistant mutants to be maintained and enriched in the host after they have emerged. This information combined with knowledge of bacterial population sizes and growth and killing dynamics at relevant infection sites should allow for better forecasting of the risk of resistance emerging in clinical settings.

  11. Durable Resistance to Crop Pathogens: An Epidemiological Framework to Predict Risk under Uncertainty

    PubMed Central

    Lo Iacono, Giovanni; van den Bosch, Frank; Gilligan, Chris A.

    2013-01-01

    Increasing the durability of crop resistance to plant pathogens is one of the key goals of virulence management. Despite the recognition of the importance of demographic and environmental stochasticity on the dynamics of an epidemic, their effects on the evolution of the pathogen and durability of resistance has not received attention. We formulated a stochastic epidemiological model, based on the Kramer-Moyal expansion of the Master Equation, to investigate how random fluctuations affect the dynamics of an epidemic and how these effects feed through to the evolution of the pathogen and durability of resistance. We focused on two hypotheses: firstly, a previous deterministic model has suggested that the effect of cropping ratio (the proportion of land area occupied by the resistant crop) on the durability of crop resistance is negligible. Increasing the cropping ratio increases the area of uninfected host, but the resistance is more rapidly broken; these two effects counteract each other. We tested the hypothesis that similar counteracting effects would occur when we take account of demographic stochasticity, but found that the durability does depend on the cropping ratio. Secondly, we tested whether a superimposed external source of stochasticity (for example due to environmental variation or to intermittent fungicide application) interacts with the intrinsic demographic fluctuations and how such interaction affects the durability of resistance. We show that in the pathosystem considered here, in general large stochastic fluctuations in epidemics enhance extinction of the pathogen. This is more likely to occur at large cropping ratios and for particular frequencies of the periodic external perturbation (stochastic resonance). The results suggest possible disease control practises by exploiting the natural sources of stochasticity. PMID:23341765

  12. Multimachine Data–Based Prediction of High-Frequency Sensor Signal Noise for Resistive Wall Mode Control in ITER

    SciTech Connect

    Liu, Yueqiang; Sabbagh, S. A.; Chapman, I. T.; Gerasimov, S.; Gribov, Y.; Hender, T. C.; Igochine, V.; Maraschek, M.; Matsunaga, G.; Okabayashi, M.; Strait, E. J.

    2016-11-01

    The high frequency noise, above the frequency of typical resistive wall modes, from magnetic pickup coils is analysed across a range of present tokamak devices including DIII-D, JET, MAST, ASDEX Upgrade, JT-60U and NSTX. Application of a high-pass filter enables identification of the noise component with Gaussian-like statistics, that shares certain common characteristics in all devices considered. A conservative prediction is made for ITER plasmas based on the multi-machine database, for the high-frequency noise component of the sensor signals, for the purpose of feedback stabilisation of the resistive wall mode. The predicted root-mean-square n=1 (n is the toroidal mode number) noise level is 104 -105Gauss/second for the voltage signal, and 0.1-1Gauss for the perturbed magnetic field signal. The lower cutoff frequency of the Gaussian pickup noise scales linearly with the sampling frequency, with the scaling coefficient of about 0.1. These basic noise characteristics should be useful for the modelling based design of the feedback control system for the resistive wall mode in ITER.

  13. Multimachine Data–Based Prediction of High-Frequency Sensor Signal Noise for Resistive Wall Mode Control in ITER

    DOE PAGES

    Liu, Yueqiang; Sabbagh, S. A.; Chapman, I. T.; ...

    2016-11-01

    The high frequency noise, above the frequency of typical resistive wall modes, from magnetic pickup coils is analysed across a range of present tokamak devices including DIII-D, JET, MAST, ASDEX Upgrade, JT-60U and NSTX. Application of a high-pass filter enables identification of the noise component with Gaussian-like statistics, that shares certain common characteristics in all devices considered. A conservative prediction is made for ITER plasmas based on the multi-machine database, for the high-frequency noise component of the sensor signals, for the purpose of feedback stabilisation of the resistive wall mode. The predicted root-mean-square n=1 (n is the toroidal mode number)more » noise level is 104 -105Gauss/second for the voltage signal, and 0.1-1Gauss for the perturbed magnetic field signal. The lower cutoff frequency of the Gaussian pickup noise scales linearly with the sampling frequency, with the scaling coefficient of about 0.1. These basic noise characteristics should be useful for the modelling based design of the feedback control system for the resistive wall mode in ITER.« less

  14. Multimachine data–based prediction of high-frequency sensor signal noise for resistive wall mode control in ITER

    SciTech Connect

    Liu, Yueqiang; Sabbagh, S. A.; Chapman, I. T.; Gerasimov, S.; Gribov, Y.; Hender, T. C.; Igochine, V.; Maraschek, M.; Matsunaga, G.; Okabayashi, M.; Strait, E. J.

    2016-08-12

    The high-frequency noise measured by magnetic sensors, at levels above the typical frequency of resistive wall modes, is analyzed across a range of present tokamak devices including DIII-D, JET, MAST, ASDEX Upgrade, JT-60U, and NSTX. A high-pass filter enables identification of the noise component with Gaussian-like statistics that shares certain common characteristics in all devices considered. A conservative prediction is made for ITER plasma operation of the high-frequency noise component of the sensor signals, to be used for resistive wall mode feedback stabilization, based on the multimachine database. The predicted root-mean-square n = 1 (n is the toroidal mode number) noise level is 104 to 105 G/s for the voltage signal, and 0.1 to 1 G for the perturbed magnetic field signal. The lower cutoff frequency of the Gaussian pickup noise scales linearly with the sampling frequency, with a scaling coefficient of about 0.1. As a result, these basic noise characteristics should be useful for the modeling-based design of the feedback control system for the resistive wall mode in ITER.

  15. Multimachine data–based prediction of high-frequency sensor signal noise for resistive wall mode control in ITER

    DOE PAGES

    Liu, Yueqiang; Sabbagh, S. A.; Chapman, I. T.; ...

    2016-08-12

    The high-frequency noise measured by magnetic sensors, at levels above the typical frequency of resistive wall modes, is analyzed across a range of present tokamak devices including DIII-D, JET, MAST, ASDEX Upgrade, JT-60U, and NSTX. A high-pass filter enables identification of the noise component with Gaussian-like statistics that shares certain common characteristics in all devices considered. A conservative prediction is made for ITER plasma operation of the high-frequency noise component of the sensor signals, to be used for resistive wall mode feedback stabilization, based on the multimachine database. The predicted root-mean-square n = 1 (n is the toroidal mode number)more » noise level is 104 to 105 G/s for the voltage signal, and 0.1 to 1 G for the perturbed magnetic field signal. The lower cutoff frequency of the Gaussian pickup noise scales linearly with the sampling frequency, with a scaling coefficient of about 0.1. As a result, these basic noise characteristics should be useful for the modeling-based design of the feedback control system for the resistive wall mode in ITER.« less

  16. Predictive Value of Molecular Drug Resistance Testing of Mycobacterium tuberculosis Isolates in Valle del Cauca, Colombia

    PubMed Central

    García, Pamela K.; Nieto, Luisa Maria; van Soolingen, Dick

    2013-01-01

    Previous evaluations of the molecular GenoType tests have promoted their use to detect resistance to first- and second-line antituberculosis drugs in different geographical regions. However, there are known geographic variations in the mutations associated with drug resistance in Mycobacterium tuberculosis, and especially in South America, there is a paucity of information regarding the frequencies and types of mutations associated with resistance to first- and second-line antituberculosis drugs. We therefore evaluated the performance of the GenoType kits in this region by testing 228 M. tuberculosis isolates in Colombia, including 134 resistant and 94 pansusceptible strains. Overall, the sensitivity and specificity of the GenoType MTBDRplus test ranged from 92 to 96% and 97 to 100%, respectively; the agreement index was optimal (Cohen's kappa, >0.8). The sensitivity of the GenoType MTBDRsl test ranged from 84 to 100% and the specificity from 88 to 100%. The most common mutations were katG S315T1, rpoB S531L, embB M306V, gyrA D94G, and rrs A1401G. Our results reflect the utility of the GenoType tests in Colombia; however, as some discordance still exists between the conventional and molecular approaches in resistance testing, we adhere to the recommendation that the GenoType tests serve as early guides for therapy, followed by phenotypic drug susceptibility testing for all cases. PMID:23658272

  17. Resistive index in febrile urinary tract infections: predictive value of renal outcome.

    PubMed

    Ozçelik, Gül; Polat, Tuğçin Bora; Aktaş, Seniha; Cetinkaya, Feyzullah; Fetinkaya, Feyzullah

    2004-02-01

    In the absence of specific symptomatology in children, the early diagnosis of acute pyelonephritis is a challenge, particularly during infancy. In an attempt to differentiate acute pyelonephritis from lower urinary tract infection (UTI), we measured intrarenal resistive index (RI). We evaluated its ability to predict renal involvement as assessed by dimercaptosuccinic acid (DMSA) scintigraphy. In total 157 patients admitted to the pediatric department of the Sişli Etfal Hospital with clinical signs of febrile UTI were included in the study. The children were divided into groups according to their age at the time of ultrasonography (US). RI was measured from the renal arteries with Doppler US in the first 72 h in all 157 children. Renal involvement was assessed by (99m)Tc-DMSA scintigraphy in the first 7 days after admission. The examination was repeated at least 6 months later if the first result was abnormal. All available patients with an abnormal scintigraphy underwent voiding cystourethrography 4-6 weeks after the acute infection. All patients with vesicoureteral reflux and scarred kidneys were excluded from the study. DMSA scintigraphy demonstrated abnormal changes in 114 of 157 children and was normal in the remaining 43 children. Of these 114 children, 104 underwent repeat scintigraphy, of whom 77 showed partially or totally reversible lesion(s). Of these 77 children, 17 children (22%) with vesicoureteral reflux were excluded. Thus, we compared the 43 children with lower UTI with the 60 children with definite acute pyelonephritis at admission. Kidneys with changes of acute pyelonephritis had a mean RI of 0.744+/-0.06 in infants, 0.745+/-0.03 in preschool children, and 0.733+/-0.09 in patients of school age with upper UTI. However, the mean RI was 0.703+/-0.06 in infants, 0.696+/-0.1 in preschool children, and 0.671+/-0.09 in school-aged patients with lower UTI. The mean RI values were significantly higher in patients with upper UTI ( P<0.001). There was a

  18. hGBP-1 Expression Predicts Shorter Progression-Free Survival in Ovarian Cancers, While Contributing to Paclitaxel Resistance

    PubMed Central

    Wadi, Suzan; Tipton, Aaron R.; Trendel, Jill A.; Khuder, Sadik A.; Vestal, Deborah J.

    2017-01-01

    Ovarian cancer is the gynecological cancer with the poorest prognosis. One significant reason is the development of resistance to the chemotherapeutic drugs used in its treatment. The large GTPase, hGBP-1, has been implicated in paclitaxel resistance in ovarian cell lines. Forced expression of hGBP-1 in SKOV3 ovarian cancer cells protects them from paclitaxel-induced cell death. However, prior to this study, nothing was known about whether hGBP-1 was expressed in ovarian tumors and whether its expression correlated with paclitaxel resistance. hGBP-1 is expressed in 17% of ovarian tumors from patients that have not yet received treatment. However, at least 80% of the ovarian tumors that recurred after therapies that included a tax-ane, either paclitaxel or docetaxel, were positive for hGBP-1. In addition, hGBP-1 expression predicts a significantly shorter progression-free survival in ovarian cancers. Based on these studies, hGBP-1 could prove to be a potential biomarker for paclitaxel resistance in ovarian cancer. PMID:28090373

  19. Predicting resist sensitivity to chemical flare effects though use of exposure density gradient method

    NASA Astrophysics Data System (ADS)

    Hyatt, Michael; DeVilliers, Anton; Jain, Kaveri

    2011-04-01

    Chemical flare has been shown to be a process limiter for patterns that are surrounded by areas of unexposed resist for certain chemically amplified resists. Using a pattern known to be susceptible to chemical flare effect a method was developed and tested on several materials. Details of the testing patterns, consisting of placements of small and large pattern density areas set to provide multiple degrees of resist loading; and a second level of loading variation achieved by selective exposure locations of those patterns across the wafer are given. Descriptions of the determination of slopes from linear trend-lines of the critical dimensions responses can be used to provide a gauge for internal evaluations as well as feedback to the vendors for chemical flare sensitivity.

  20. Numerical, micro-mechanical prediction of crack growth resistance in a fibre-reinforced/brittle matrix composite

    NASA Technical Reports Server (NTRS)

    Jenkins, Michael G.; Ghosh, Asish; Salem, Jonathan A.

    1990-01-01

    Micromechanics fracture models are incorporated into three distinct fracture process zones which contribute to the crack growth resistance of fibrous composites. The frontal process zone includes microcracking, fiber debonding, and some fiber failure. The elastic process zone is related only to the linear elastic creation of new matrix and fiber fracture surfaces. The wake process zone includes fiber bridging, fiber pullout, and fiber breakage. The R-curve predictions of the model compare well with empirical results for a unidirectional, continuous fiber C/C composite. Separating the contributions of each process zone reveals the wake region to contain the dominant crack growth resistance mechanisms. Fractography showed the effects of the micromechanisms on the macroscopic fracture behavior.

  1. Numerical, micro-mechanical prediction of crack growth resistance in a fibre-reinforced/brittle matrix composite

    NASA Technical Reports Server (NTRS)

    Jenkins, Michael G.; Ghosh, Asish; Salem, Jonathan A.

    1990-01-01

    Micromechanics fracture models are incorporated into three distinct fracture process zones which contribute to the crack growth resistance of fibrous composites. The frontal process zone includes microcracking, fiber debonding, and some fiber failure. The elastic process zone is related only to the linear elastic creation of new matrix and fiber fracture surfaces. The wake process zone includes fiber bridging, fiber pullout, and fiber breakage. The R-curve predictions of the model compare well with empirical results for a unidirectional, continuous fiber C/C composite. Separating the contributions of each process zone reveals the wake region to contain the dominant crack growth resistance mechanisms. Fractography showed the effects of the micromechanisms on the macroscopic fracture behavior.

  2. Prediction of Women's Utilization of Resistance Strategies in a Sexual Assault Situation: A Prospective Study

    ERIC Educational Resources Information Center

    Gidycz, Christine A.; Van Wynsberghe, Amy; Edwards, Katie M.

    2008-01-01

    The present study prospectively explored the predictors of resistance strategies to a sexual assault situation. Participants were assessed at the beginning of an academic quarter on a number of variables, including past history of sexual victimization, perceived risk of sexual victimization, and intentions to use specific types of resistance…

  3. Predicting Aerobic versus Resistance Exercise Using the Theory of Planned Behavior.

    ERIC Educational Resources Information Center

    Bryan, Angela D.; Rocheleau, Courtney A.

    2002-01-01

    Tested the theory of planned behavior (TPB) in aerobic versus resistance training, investigating relationships between TPB variables, extroversion, and perceived health among college students who completed initial and follow-up measurements and provided reasons for exercise. TPB variables, extroversion, and perceived health collectively accounted…

  4. Testing taxonomic predictivity of foliar and tuber resistance to Phytophthora infestans in wild relatives of potato

    USDA-ARS?s Scientific Manuscript database

    Potato late blight, caused by the oomycete phytopathogen Phytophthora infestans, is a devastating disease found in potato growing regions worldwide. Long-term management strategies to control late blight include the incorporation of host resistance to predominant strains. However, due to rapid genet...

  5. ETS Gene Fusions as Predictive Biomarkers of Resistance to Radiation Therapy for Prostate Cancer

    DTIC Science & Technology

    2014-08-01

    resistance  ERG is diffusely localized through the prostate cancer cell and does not redistribute upon genotoxic stress Reportable Outcomes: The past...JL, Schrecengost RS, Han S, Den RB, Dicker AP, Feng FY, and Knudsen KE. A hormone-DNA repair circuit governs the response to genotoxic insult

  6. New Insights into the In Silico Prediction of HIV Protease Resistance to Nelfinavir

    PubMed Central

    Antunes, Dinler A.; Rigo, Maurício M.; Sinigaglia, Marialva; de Medeiros, Rúbia M.; Junqueira, Dennis M.; Almeida, Sabrina E. M.; Vieira, Gustavo F.

    2014-01-01

    The Human Immunodeficiency Virus type 1 protease enzyme (HIV-1 PR) is one of the most important targets of antiretroviral therapy used in the treatment of AIDS patients. The success of protease-inhibitors (PIs), however, is often limited by the emergence of protease mutations that can confer resistance to a specific drug, or even to multiple PIs. In the present study, we used bioinformatics tools to evaluate the impact of the unusual mutations D30V and V32E over the dynamics of the PR-Nelfinavir complex, considering that codons involved in these mutations were previously related to major drug resistance to Nelfinavir. Both studied mutations presented structural features that indicate resistance to Nelfinavir, each one with a different impact over the interaction with the drug. The D30V mutation triggered a subtle change in the PR structure, which was also observed for the well-known Nelfinavir resistance mutation D30N, while the V32E exchange presented a much more dramatic impact over the PR flap dynamics. Moreover, our in silico approach was also able to describe different binding modes of the drug when bound to different proteases, identifying specific features of HIV-1 subtype B and subtype C proteases. PMID:24498124

  7. Post-Spaceflight Orthostatic Hypotension Occurs Mostly in Women and is Predicted by Low Vascular Resistance

    NASA Technical Reports Server (NTRS)

    Waters, Wendy W.; Ziegler, Michael G.; Meck, Janice V.

    2001-01-01

    About 20% of astronauts suffer post-spaceflight presyncope, but the underlying etiology remains elusive. We studied responses to standing in 36 astronauts before and after spaceflight (5- 16 days). Individuals were separated into presyncopal women, presyncopal men, and non-presyncopal men based on their ability to stand for 10 min postflight. Preflight, presyncopal women and presyncopal men had low vascular resistance, with the women having the lowest. Postflight, women experienced significantly higher rates of presyncope (P<0.01) and significantly greater losses of plasma volume than the men (P<0.05). Both presyncopal women and men had lower standing arterial pressure (P<=0.001) and vascular resistance (P<0.05), smaller increases in norepinephrine (P<=0.058) and greater increases in epinephrine (P<=0.058) than nonpresyncopal men. Both presyncopal groups had a strong dependence (P<=0.05) on plasma volume to maintain standing stroke volume. These findings suggest that postflight presyncope is ascribed to a combination of inherently low resistance responses, a strong dependence on volume status, and spaceflight-induced hypoadrenergic responses. In contrast, high vascular resistance and spaceflight-induced hyperadrenergic responses prevent presyncope.

  8. Postspaceflight orthostatic hypotension occurs mostly in women and is predicted by low vascular resistance

    NASA Technical Reports Server (NTRS)

    Waters, Wendy W.; Ziegler, Michael G.; Meck, Janice V.

    2002-01-01

    About 20% of astronauts suffer postspaceflight presyncope. We studied pre- to postflight (5- to 16-day missions) cardiovascular responses to standing in 35 astronauts to determine differences between 1) men and women and 2) presyncopal and nonpresyncopal groups. The groups were presyncopal women, presyncopal men, and nonpresyncopal men based on their ability to stand for 10 min postflight. Preflight, women and presyncopal men had low vascular resistance, with the women having the lowest. Postflight, women experienced higher rates of presyncope (100 vs. 20%; P = 0.001) and greater losses of plasma volume (20 vs. 7%; P < 0.05) than men. Also, presyncopal subjects had lower standing mean arterial pressure (P < or = 0.001) and vascular resistance (P < 0.05), smaller increases in norepinephrine (P < or = 0.058) and greater increases in epinephrine (P < or = 0.058) than nonpresyncopal subjects. Presyncopal subjects had a strong dependence on plasma volume to maintain standing stroke volume. These findings suggest that postflight presyncope is greatest in women, and this can be ascribed to a combination of inherently low-resistance responses, a strong dependence on volume status, and relative hypoadrenergic responses. Conversely, high vascular resistance and postflight hyperadrenergic responses prevent presyncope.

  9. Postspaceflight orthostatic hypotension occurs mostly in women and is predicted by low vascular resistance

    NASA Technical Reports Server (NTRS)

    Waters, Wendy W.; Ziegler, Michael G.; Meck, Janice V.

    2002-01-01

    About 20% of astronauts suffer postspaceflight presyncope. We studied pre- to postflight (5- to 16-day missions) cardiovascular responses to standing in 35 astronauts to determine differences between 1) men and women and 2) presyncopal and nonpresyncopal groups. The groups were presyncopal women, presyncopal men, and nonpresyncopal men based on their ability to stand for 10 min postflight. Preflight, women and presyncopal men had low vascular resistance, with the women having the lowest. Postflight, women experienced higher rates of presyncope (100 vs. 20%; P = 0.001) and greater losses of plasma volume (20 vs. 7%; P < 0.05) than men. Also, presyncopal subjects had lower standing mean arterial pressure (P < or = 0.001) and vascular resistance (P < 0.05), smaller increases in norepinephrine (P < or = 0.058) and greater increases in epinephrine (P < or = 0.058) than nonpresyncopal subjects. Presyncopal subjects had a strong dependence on plasma volume to maintain standing stroke volume. These findings suggest that postflight presyncope is greatest in women, and this can be ascribed to a combination of inherently low-resistance responses, a strong dependence on volume status, and relative hypoadrenergic responses. Conversely, high vascular resistance and postflight hyperadrenergic responses prevent presyncope.

  10. Predicting Aerobic versus Resistance Exercise Using the Theory of Planned Behavior.

    ERIC Educational Resources Information Center

    Bryan, Angela D.; Rocheleau, Courtney A.

    2002-01-01

    Tested the theory of planned behavior (TPB) in aerobic versus resistance training, investigating relationships between TPB variables, extroversion, and perceived health among college students who completed initial and follow-up measurements and provided reasons for exercise. TPB variables, extroversion, and perceived health collectively accounted…

  11. Quantitative Predictions of Binding Free Energy Changes in Drug-Resistant Influenza Neuraminidase

    DTIC Science & Technology

    2012-08-30

    Energy Changes in Drug-Resistant Influenza Neuraminidase. PLoS Comput Biol 8(8): e1002665. doi:10.1371/journal.pcbi.1002665 Editor: Alex Mackerell ...Calculation of protein-ligand binding affinities. Annu Rev Biophys Biomol Struct 36: 21–42. 17. Guvench O, MacKerell Jr AD (2009) Computational evaluation

  12. Fluoroquinolone resistant rectal colonization predicts risk of infectious complications after transrectal prostate biopsy.

    PubMed

    Liss, Michael A; Taylor, Stephen A; Batura, Deepak; Steensels, Deborah; Chayakulkeeree, Methee; Soenens, Charlotte; Rao, G Gopal; Dash, Atreya; Park, Samuel; Patel, Nishant; Woo, Jason; McDonald, Michelle; Nseyo, Unwanaobong; Banapour, Pooya; Unterberg, Stephen; Ahlering, Thomas E; Van Poppel, Hendrik; Sakamoto, Kyoko; Fierer, Joshua; Black, Peter C

    2014-12-01

    Infection after transrectal prostate biopsy has become an increasing concern due to fluoroquinolone resistant bacteria. We determined whether colonization identified by rectal culture can identify men at high risk for post-transrectal prostate biopsy infection. Six institutions provided retrospective data through a standardized, web based data entry form on patients undergoing transrectal prostate biopsy who had rectal culture performed. The primary outcome was any post-transrectal prostate biopsy infection and the secondary outcome was hospital admission 30 days after transrectal prostate biopsy. We used chi-square and logistic regression statistical analysis. A total of 2,673 men underwent rectal culture before transrectal prostate biopsy from January 1, 2007 to September 12, 2013. The prevalence of fluoroquinolone resistance was 20.5% (549 of 2,673). Fluoroquinolone resistant positive rectal cultures were associated with post-biopsy infection (6.6% vs 1.6%, p <0.001) and hospitalization (4.4% vs 0.9%, p <0.001). Fluoroquinolone resistant positive rectal culture increased the risk of infection (OR 3.98, 95% CI 2.37-6.71, p <0.001) and subsequent hospital admission (OR 4.77, 95% CI 2.50-9.10, p <0.001). If men only received fluoroquinolone prophylaxis, the infection and hospitalization proportion increased to 8.2% (28 of 343) and 6.1% (21 of 343), with OR 4.77 (95% CI 2.50-9.10, p <0.001) and 5.67 (95% CI 3.00-10.90, p <0.001), respectively. The most common fluoroquinolone resistant bacteria isolates were Escherichia coli (83.7%). Limitations include the retrospective study design, nonstandardized culture and interpretation of resistance methods. Colonization of fluoroquinolone resistant organisms in the rectum identifies men at high risk for infection and subsequent hospitalization from prostate biopsy, especially in those with fluoroquinolone prophylaxis only. Copyright © 2014 American Urological Association Education and Research, Inc. Published by Elsevier

  13. Aspirin Resistance Predicts Adverse Cardiovascular Events in Patients with Symptomatic Peripheral Artery Disease.

    PubMed

    Pasala, Tilak; Hoo, Jennifer Soo; Lockhart, Mary Kate; Waheed, Rehan; Sengodan, Prasanna; Alexander, Jeffrey; Gandhi, Sanjay

    2016-12-01

    Antiplatelet therapy reduces the risk of myocardial infarction, stroke, and vascular death in patients who have symptomatic peripheral artery disease. However, a subset of patients who take aspirin continues to have recurrent cardiovascular events. There are few data on cardiovascular outcomes in patients with peripheral artery disease who manifest aspirin resistance. Patients with peripheral artery disease on long-term aspirin therapy (≥4 wk) were tested for aspirin responsiveness by means of the VerifyNow Aspirin Assay. The mean follow-up duration was 22.6 ± 8.3 months. The primary endpoint was a composite of death, myocardial infarction, or ischemic stroke. Secondary endpoints were the incidence of vascular interventions (surgical or percutaneous), or of amputation or gangrene caused by vascular disease. Of the 120 patients enrolled in the study, 31 (25.8%) were aspirin-resistant and 89 (74.2%) were aspirin-responsive. The primary endpoint occurred in 10 (32.3%) patients in the aspirin-resistant group and in 13 (14.6%) patients in the aspirin-responsive group (hazard ratio=2.48; 95% confidence interval, 1.08-5.66; P=0.03). There was no significant difference in the secondary outcome of revascularization or tissue loss. By multivariate analysis, aspirin resistance and history of chronic kidney disease were the only independent predictors of long-term adverse cardiovascular events. Aspirin resistance is highly prevalent in patients with symptomatic peripheral artery disease and is an independent predictor of adverse cardiovascular risk. Whether intervening in these patients with additional antiplatelet therapies would improve outcomes needs to be explored.

  14. Aspirin Resistance Predicts Adverse Cardiovascular Events in Patients with Symptomatic Peripheral Artery Disease

    PubMed Central

    Pasala, Tilak; Hoo, Jennifer Soo; Lockhart, Mary Kate; Waheed, Rehan; Sengodan, Prasanna; Alexander, Jeffrey

    2016-01-01

    Antiplatelet therapy reduces the risk of myocardial infarction, stroke, and vascular death in patients who have symptomatic peripheral artery disease. However, a subset of patients who take aspirin continues to have recurrent cardiovascular events. There are few data on cardiovascular outcomes in patients with peripheral artery disease who manifest aspirin resistance. Patients with peripheral artery disease on long-term aspirin therapy (≥4 wk) were tested for aspirin responsiveness by means of the VerifyNow Aspirin Assay. The mean follow-up duration was 22.6 ± 8.3 months. The primary endpoint was a composite of death, myocardial infarction, or ischemic stroke. Secondary endpoints were the incidence of vascular interventions (surgical or percutaneous), or of amputation or gangrene caused by vascular disease. Of the 120 patients enrolled in the study, 31 (25.8%) were aspirin-resistant and 89 (74.2%) were aspirin-responsive. The primary endpoint occurred in 10 (32.3%) patients in the aspirin-resistant group and in 13 (14.6%) patients in the aspirin-responsive group (hazard ratio=2.48; 95% confidence interval, 1.08–5.66; P=0.03). There was no significant difference in the secondary outcome of revascularization or tissue loss. By multivariate analysis, aspirin resistance and history of chronic kidney disease were the only independent predictors of long-term adverse cardiovascular events. Aspirin resistance is highly prevalent in patients with symptomatic peripheral artery disease and is an independent predictor of adverse cardiovascular risk. Whether intervening in these patients with additional antiplatelet therapies would improve outcomes needs to be explored. PMID:28100965

  15. A chemoresponse assay for prediction of platinum resistance in primary ovarian cancer.

    PubMed

    Krivak, Thomas C; Lele, Shashikant; Richard, Scott; Secord, Angeles Alvarez; Leath, Charles A; Brower, Stacey L; Tian, Chunqiao; Moore, Richard G

    2014-07-01

    Recurrence following primary platinum-based chemotherapy remains a challenge in the treatment of patients with advanced-stage epithelial ovarian cancer. This study examines whether a chemoresponse assay can identify patients who are platinum-resistant prior to treatment. Women (n = 276) with International Federation of Gynecology and Obstetrics stage III-IV ovarian, fallopian, and peritoneal cancer were enrolled in an observational study, and the responsiveness of their tumors was evaluated using a chemoresponse assay. All patients were treated with a platinum/taxane regimen following cytoreductive surgery. Assay responses to carboplatin or paclitaxel were classified as sensitive, intermediate sensitive (IS), or resistant. Association of assay response with progression-free survival (PFS) was analyzed using the Kaplan-Meier method and a Cox regression model. Patients whose tumors were resistant to carboplatin were at increased risk of disease progression compared to those with nonresistant (sensitive + IS) tumors (median PFS: 11.8 vs 16.6 months, respectively, P < .001), and the association was confirmed after adjusting for other clinical factors (hazard ratio, 1.71; 95% confidence interval, 1.12-2.62; P = .013). Association of assay response to paclitaxel with PFS trended in multivariate analysis (hazard ratio, 1.28; 95% confidence interval, 0.84-1.95; P = .245). For tumors resistant to carboplatin, 59% were sensitive or IS to at least 1 other commonly used agent, demonstrating the ability of the assay to inform treatment decisions beyond the standard platinum/taxane regimen. Assay resistance to carboplatin is strongly associated with shortened PFS among advanced-stage epithelial ovarian cancer patients treated with carboplatin + paclitaxel therapy, supporting use of this assay to identify patients likely to experience early recurrence on standard platinum-based therapy. Copyright © 2014 Mosby, Inc. All rights reserved.

  16. Rapid prediction of particulate, humus and resistant fractions of soil organic carbon in reforested lands using infrared spectroscopy.

    PubMed

    Madhavan, Dinesh B; Baldock, Jeff A; Read, Zoe J; Murphy, Simon C; Cunningham, Shaun C; Perring, Michael P; Herrmann, Tim; Lewis, Tom; Cavagnaro, Timothy R; England, Jacqueline R; Paul, Keryn I; Weston, Christopher J; Baker, Thomas G

    2017-05-15

    Reforestation of agricultural lands with mixed-species environmental plantings can effectively sequester C. While accurate and efficient methods for predicting soil organic C content and composition have recently been developed for soils under agricultural land uses, such methods under forested land uses are currently lacking. This study aimed to develop a method using infrared spectroscopy for accurately predicting total organic C (TOC) and its fractions (particulate, POC; humus, HOC; and resistant, ROC organic C) in soils under environmental plantings. Soils were collected from 117 paired agricultural-reforestation sites across Australia. TOC fractions were determined in a subset of 38 reforested soils using physical fractionation by automated wet-sieving and (13)C nuclear magnetic resonance (NMR) spectroscopy. Mid- and near-infrared spectra (MNIRS, 6000-450 cm(-1)) were acquired from finely-ground soils from environmental plantings and agricultural land. Satisfactory prediction models based on MNIRS and partial least squares regression (PLSR) were developed for TOC and its fractions. Leave-one-out cross-validations of MNIRS-PLSR models indicated accurate predictions (R(2) > 0.90, negligible bias, ratio of performance to deviation > 3) and fraction-specific functional group contributions to beta coefficients in the models. TOC and its fractions were predicted using the cross-validated models and soil spectra for 3109 reforested and agricultural soils. The reliability of predictions determined using k-nearest neighbour score distance indicated that >80% of predictions were within the satisfactory inlier limit. The study demonstrated the utility of infrared spectroscopy (MNIRS-PLSR) to rapidly and economically determine TOC and its fractions and thereby accurately describe the effects of land use change such as reforestation on agricultural soils.

  17. Role of Nuclear Receptor Coactivators, AIB-1 and SRC-1, in the Development of Breast Cancer

    DTIC Science & Technology

    2003-04-01

    drive CrePRI expression, 19 or in the Purkinje variant of epidermolysis bullosa simplex (EBS-DM) as cells when the GluR82 gene promoter was used to...Yao Tl’, Evans RM (1996) Ecdysone-inducible gene ex- mouse model for epidermolysis bullosa simplex: implications pression in mammalian cells and

  18. EGF Regulation of Nuclear Co-Activator AIB1 Function in Breast Cancer

    DTIC Science & Technology

    2005-04-01

    AD Award Number: DAMDl7-02-1-0394 TITLE: EGF Regulation of Nuclear Co-Activator AIBI Function in Breast Cancer PRINCIPAL INVESTIGATOR: Annabell S. Oh...Activator AIBI Function in DAMD17-02-1-0394 Breast Cancer 6. AUTHOR(S) Annabell S. Oh 7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) 8. PERFORMING...Factor-i Signaling in Human Breast Cancer. Doctoral dissertation of Annabell S. Oh, B.S. from the Department 14 of Tumor Biology, Georgetown

  19. Interaction of AIB1 and BRCA1 in the Development of Breast Cancer

    DTIC Science & Technology

    2006-03-01

    cells were plated in 5% charcoal-stripped serum in IMEM for 3 days prior to transfection. Cells were transfected with the following plasmids...fetal bovine serum in IMEM . After the cells were attached, the cells were transfected with a -1745 cyclin D1 promoter- luciferase reporter construct...The media was changed to serum-free IMEM for the transfection. After 24 hours of transfection, 100 ng/ml of EGF, 100 ng/ml IGF-1, and 10 nM of

  20. High Speed Displacement Vessels Parametric Studies and Calm Water Resistance Predictions - State of the Art,

    DTIC Science & Technology

    1986-04-01

    Hull Form Parameters for Powering T-7 Predictions -- High Speed Displacement Hull Series - V %-, V 5.0-1 Hull Form Series Applications T-8 iv...1.049 - - - - - - T-6- A ’. .. - ~% ". Jb TABLE 4.0-1 Basic Hull Form Parameters for Powering Predictions -- High Speed Displacement Hull ...8217 developed by the author based on some of the high - speed round bilge

  1. The detection of neural autoantibodies in patients with antiepileptic-drug-resistant epilepsy predicts response to immunotherapy.

    PubMed

    Iorio, R; Assenza, G; Tombini, M; Colicchio, G; Della Marca, G; Benvenga, A; Damato, V; Rossini, P M; Vollono, C; Plantone, D; Marti, A; Batocchi, A P; Evoli, A

    2015-01-01

    The detection of antibodies binding neural antigens in patients with epilepsy has led to the definition of 'autoimmune epilepsy'. Patients with neural antibodies not responding to antiepileptic drugs (AEDs) may benefit from immunotherapy. Aim of this study was to evaluate the frequency of autoantibodies specific to neural antigens in patients with epilepsy and their response to immunotherapy. Eighty-one patients and 75 age- and sex-matched healthy subjects (HS) were enrolled in the study. Two groups of patients were included: 39 patients with epilepsy and other neurological symptoms and/or autoimmune diseases responsive to AEDs (group 1) and 42 patients with AED-resistant epilepsy (group 2). Patients' serum and cerebrospinal fluid were evaluated for the presence of autoantibodies directed to neural antigens by indirect immunofluorescence on frozen sections of mouse brain, cell-based assays and a radioimmunoassay. Patients with AED-resistant epilepsy and neural autoantibodies were treated with immunotherapy and the main outcome measure was the reduction in seizure frequency. Neural autoantibodies were detected in 22% of patients (18/81), mostly from the AED-resistant epilepsy group (P = 0.003), but not in HS. Indirect immunofluorescence on mouse brain revealed antibodies binding to unclassified antigens in 10 patients. Twelve patients received immunotherapy and nine (75%) achieved >50% reduction in seizure frequency. A significant proportion of patients with AED-resistant epilepsy harbor neural-specific autoantibodies. The detection of these antibodies, especially of those binding to synaptic antigens, may predict a favorable response to immunotherapy, thus overcoming AED resistance. © 2014 EAN.

  2. Maternal Neutralization-Resistant Virus Variants Do Not Predict Infant HIV Infection Risk.

    PubMed

    Milligan, Caitlin; Omenda, Maxwel M; Chohan, Vrasha; Odem-Davis, Katherine; Richardson, Barbra A; Nduati, Ruth; Overbaugh, Julie

    2016-02-02

    Mother-to-child transmission (MTCT) of HIV provides a setting for studying immune correlates of protection. Neutralizing antibodies (NAbs) are suggested to contribute to a viral bottleneck during MTCT, but their role in blocking transmission is unclear, as studies comparing the NAb sensitivities of maternal viruses have yielded disparate results. We sought to determine whether transmitting mothers differ from nontransmitting mothers in the ability to neutralize individual autologous virus variants present at transmission. Ten transmitting and 10 nontransmitting HIV-infected mothers at high risk of MTCT were included in this study. Full-length HIV envelope genes (n = 100) were cloned from peripheral blood mononuclear cells obtained near transmission from transmitting mothers and at similar time points from nontransmitting mothers. Envelope clones were tested as pseudoviruses against contemporaneous, autologous maternal plasma in neutralization assays. The association between transmission and the log2 50% inhibitory concentration (IC50) for multiple virus variants per mother was estimated by using logistic regression with clustered standard errors. t tests were used to compare proportions of neutralization-resistant viruses. Overall, transmitting mothers had a median IC50 of 317 (interquartile range [IQR], 202 to 521), and nontransmitting mothers had a median IC50 of 243 (IQR, 95 to 594). Transmission risk was not significantly associated with autologous NAb activity (odds ratio, 1.25; P = 0.3). Compared to nontransmitting mothers, transmitting mothers had similar numbers of or fewer neutralization-resistant virus variants, depending on the IC50 neutralization resistance cutoff. In conclusion, HIV-infected mothers harbor mostly neutralization-sensitive viruses, although resistant variants were detected in both transmitting and nontransmitting mothers. These results suggest that MTCT during the breastfeeding period is not driven solely by the presence of maternal

  3. In Men with Castration-Resistant Prostate Cancer, Visceral Metastases Predict Shorter Overall Survival: What Predicts Visceral Metastases? Results from the SEARCH Database.

    PubMed

    Whitney, Colette A; Howard, Lauren E; Posadas, Edwin M; Amling, Christopher L; Aronson, William J; Cooperberg, Matthew R; Kane, Christopher J; Terris, Martha K; Freedland, Stephen J

    2016-08-29

    Although visceral metastases (VMs) are widely recognized to portend worse prognoses compared with bone and lymph metastases in men with metastatic castration-resistant prostate cancer (mCRPC), little is known about what predicts VMs and the extent to which men with VMs do worse. To determine whether men with VMs at initial mCRPC diagnosis have worse overall survival (OS) and identify predictors of VMs. We analyzed 494 men diagnosed with castration-resistant prostate cancer post-1999 and no known metastases from five Veterans Affairs hospitals of the Shared Equal Access Regional Cancer Hospital (SEARCH) database who later developed metastases. Radiology scans within 30 d of initial metastasis diagnosis were reviewed to collect information on bone, visceral, and lymph node metastases. We analyzed the 236 men who had a computed tomography scan performed. Predictors of VMs and OS were evaluated using logistic regression and Cox models, respectively. Of the 236 mCRPC patients, 38 (16%) had VMs. Regarding VMs, 19 patients (50%), 8 patients (21%), and 16 patients (42%) had metastases in the liver, lungs, and other locations, respectively. VMs were a predictor of OS on crude analysis (hazard ratio [HR]: 1.88; 95% confidence interval [CI], 1.30-2.72; p=0.001) and after risk adjustment (HR: 1.84; 95% CI, 1.24-2.72; p=0.002). Age, year, treatment center, prostate-specific antigen (PSA), and time from CRPC to metastases were significant in predicting OS (all p<0.05). None of the variables tested were associated with having VMs (all p > 0.09). Prospective studies and larger cohorts are needed to validate our findings. Demographic, tumor, and PSA kinetic characteristics were not predictive of having VMs, but VMs predicted worse OS. Because patients with VMs have worse overall survival, further research is needed to develop better biomarkers and thus diagnose those with VMs at earlier stages in their disease course. Copyright © 2016 European Association of Urology. Published by

  4. Reverse Genetics in Candida albicans Predicts ARF Cycling Is Essential for Drug Resistance and Virulence

    PubMed Central

    Epp, Elias; Vanier, Ghyslaine; Harcus, Doreen; Lee, Anna Y.; Jansen, Gregor; Hallett, Michael; Sheppard, Don C.; Thomas, David Y.; Munro, Carol A.; Mullick, Alaka; Whiteway, Malcolm

    2010-01-01

    Candida albicans, the major fungal pathogen of humans, causes life-threatening infections in immunocompromised individuals. Due to limited available therapy options, this can frequently lead to therapy failure and emergence of drug resistance. To improve current treatment strategies, we have combined comprehensive chemical-genomic screening in Saccharomyces cerevisiae and validation in C. albicans with the goal of identifying compounds that can couple with the fungistatic drug fluconazole to make it fungicidal. Among the genes identified in the yeast screen, we found that only AGE3, which codes for an ADP-ribosylation factor GTPase activating effector protein, abrogates fluconazole tolerance in C. albicans. The age3 mutant was more sensitive to other sterols and cell wall inhibitors, including caspofungin. The deletion of AGE3 in drug resistant clinical isolates and in constitutively active calcineurin signaling mutants restored fluconazole sensitivity. We confirmed chemically the AGE3-dependent drug sensitivity by showing a potent fungicidal synergy between fluconazole and brefeldin A (an inhibitor of the guanine nucleotide exchange factor for ADP ribosylation factors) in wild type C. albicans as well as in drug resistant clinical isolates. Addition of calcineurin inhibitors to the fluconazole/brefeldin A combination only initially improved pathogen killing. Brefeldin A synergized with different drugs in non-albicans Candida species as well as Aspergillus fumigatus. Microarray studies showed that core transcriptional responses to two different drug classes are not significantly altered in age3 mutants. The therapeutic potential of inhibiting ARF activities was demonstrated by in vivo studies that showed age3 mutants are avirulent in wild type mice, attenuated in virulence in immunocompromised mice and that fluconazole treatment was significantly more efficacious when ARF signaling was genetically compromised. This work describes a new, widely conserved, broad

  5. Body Mass Index Predicts 24-Hour Urinary Aldosterone Levels in Patients With Resistant Hypertension.

    PubMed

    Dudenbostel, Tanja; Ghazi, Lama; Liu, Mingchun; Li, Peng; Oparil, Suzanne; Calhoun, David A

    2016-10-01

    Prospective studies indicate that hyperaldosteronism is found in 20% of patients with resistant hypertension. A small number of observational studies in normotensive and hypertensive patients suggest a correlation between aldosterone levels and obesity while others could not confirm these findings. The correlation between aldosterone levels and body mass index (BMI) in patients with resistant hypertension has not been previously investigated. Our objective was to determine whether BMI is positively correlated with plasma aldosterone concentration, plasma renin activity, aldosterone:renin ratio, and 24-hour urinary aldosterone in black and white patients. We performed a cross-sectional analysis of a large diverse cohort (n=2170) with resistant hypertension. The relationship between plasma aldosterone concentration, plasma renin activity, aldosterone:renin ratio, 24-hour urinary aldosterone, and BMI was investigated for the entire cohort, by sex and race (65.3% white, 40.3% men). We demonstrate that plasma aldosterone concentration and aldosterone:renin ratio were significantly correlated to BMI (P<0.0001) across the first 3 quartiles, but not from the 3rd to 4th quartile of BMI. Plasma renin activity was not correlated with BMI. Twenty-four-hour urinary aldosterone was positively correlated across all quartiles of BMI for the cohort (P<0.0001) and when analyzed by sex (men P<0.0001; women P=0.0013) and race (P<0.05), and stronger for men compared with women (r=0.19, P<0.001 versus r=0.05, P=0.431, P=0.028) regardless of race. In both black and white patients, aldosterone levels were positively correlated to increasing BMI, with the correlation being more pronounced in black and white men. These findings suggest that obesity, particularly the abdominal obesity typical of men, contributes to excess aldosterone in patients with resistant hypertension. © 2016 American Heart Association, Inc.

  6. Application of PK/PD Modeling in Veterinary Field: Dose Optimization and Drug Resistance Prediction.

    PubMed

    Ahmad, Ijaz; Huang, Lingli; Hao, Haihong; Sanders, Pascal; Yuan, Zonghui

    2016-01-01

    Among veterinary drugs, antibiotics are frequently used. The true mean of antibiotic treatment is to administer dose of drug that will have enough high possibility of attaining the preferred curative effect, with adequately low chance of concentration associated toxicity. Rising of antibacterial resistance and lack of novel antibiotic is a global crisis; therefore there is an urgent need to overcome this problem. Inappropriate antibiotic selection, group treatment, and suboptimal dosing are mostly responsible for the mentioned problem. One approach to minimizing the antibacterial resistance is to optimize the dosage regimen. PK/PD model is important realm to be used for that purpose from several years. PK/PD model describes the relationship between drug potency, microorganism exposed to drug, and the effect observed. Proper use of the most modern PK/PD modeling approaches in veterinary medicine can optimize the dosage for patient, which in turn reduce toxicity and reduce the emergence of resistance. The aim of this review is to look at the existing state and application of PK/PD in veterinary medicine based on in vitro, in vivo, healthy, and disease model.

  7. Application of PK/PD Modeling in Veterinary Field: Dose Optimization and Drug Resistance Prediction

    PubMed Central

    Ahmad, Ijaz; Huang, Lingli; Hao, Haihong; Sanders, Pascal; Yuan, Zonghui

    2016-01-01

    Among veterinary drugs, antibiotics are frequently used. The true mean of antibiotic treatment is to administer dose of drug that will have enough high possibility of attaining the preferred curative effect, with adequately low chance of concentration associated toxicity. Rising of antibacterial resistance and lack of novel antibiotic is a global crisis; therefore there is an urgent need to overcome this problem. Inappropriate antibiotic selection, group treatment, and suboptimal dosing are mostly responsible for the mentioned problem. One approach to minimizing the antibacterial resistance is to optimize the dosage regimen. PK/PD model is important realm to be used for that purpose from several years. PK/PD model describes the relationship between drug potency, microorganism exposed to drug, and the effect observed. Proper use of the most modern PK/PD modeling approaches in veterinary medicine can optimize the dosage for patient, which in turn reduce toxicity and reduce the emergence of resistance. The aim of this review is to look at the existing state and application of PK/PD in veterinary medicine based on in vitro, in vivo, healthy, and disease model. PMID:26989688

  8. Role of the Egami Score in Predicting Intravenous Immunoglobulin Resistance in Kawasaki Disease Among Different Ethnicities.

    PubMed

    Loomba, Rohit S; Raskin, Alexander; Gudausky, Todd M; Kirkpatrick, Edward

    Early treatment with intravenous immunoglobulin (IVIG) is necessary to help reduce the risk of coronary artery abnormalities, such as coronary artery aneurysms and to help alleviate symptoms, in Kawasaki disease. Some patients, however, do not respond to an initial dose of IVIG and require additional doses. Prediction of these IVIG nonresponders may be of assistance in altering initial therapy to make it more effective. The Egami score has been validated in the Japanese population to predict IVIG nonresponders but has shown to be ineffective in US populations. This study evaluates the Egami score in a Midwest US population, subdividing patients by race and the diagnosis of typical or atypical type of Kawasaki disease. Patients were included in the study if they met criteria for Kawasaki disease and received IVIG in the inpatient setting. A total of 182 patients were studied, and in all studied groups, the Egami score had poor sensitivity at predicting IVIG nonresponders. Sensitivity of the score differed between races and differed between typical and atypical Kawasaki disease. The Egami score, as well as other systems, have been validated to predict IVIG nonresponders. These, however, lack sensitivity in the US population. Other scores developed in the United States have also lacked sensitivity, likely due to the absence of race or Kawasaki disease classification as variables. The development of a sensitive scoring system to predict IVIG nonresponders in US populations will require the incorporation of race and Kawasaki disease classification, factors that seem to alter IVIG response.

  9. Early reduction in prefrontal theta QEEG cordance value predicts response to venlafaxine treatment in patients with resistant depressive disorder.

    PubMed

    Bares, Martin; Brunovsky, Martin; Kopecek, Miloslav; Novak, Tomas; Stopkova, Pavla; Kozeny, Jiri; Sos, Peter; Krajca, Vladimir; Höschl, Cyril

    2008-08-01

    Previous studies of patients with unipolar depression have shown that early decrease of prefrontal EEG cordance in theta band can predict clinical response to various antidepressants. We have now examined whether decrease of prefrontal quantitative EEG (QEEG) cordance value after 1 week of venlafaxine treatment predicts clinical response to venlafaxine in resistant patients. We analyzed 25 inpatients who finished 4-week venlafaxine treatment. EEG data were monitored at baseline and after 1 week of treatment. QEEG cordance was computed at three frontal electrodes in theta frequency band. Depressive symptoms and clinical status were assessed using Montgomery-Asberg Depression Rating Scale (MADRS), Beck Depression Inventory-Short Form (BDI-S) and Clinical Global Impression (CGI). Eleven of 12 responders (reduction of MADRS >or=50%) and only 5 of 13 non-responders had decreased prefrontal QEEG cordance value after the first week of treatment (p=0.01). The decrease of prefrontal cordance after week 1 in responders was significant (p=0.03) and there was no significant change in non-responders. Positive and negative predictive values of cordance reduction for response were 0.7 and 0.9, respectively. The reduction of prefrontal theta QEEG cordance value after first week of treatment might be helpful in the prediction of response to venlafaxine.

  10. Recent advances in the development and use of molecular tests to predict antimicrobial resistance in Neisseria gonorrhoeae.

    PubMed

    Donà, Valentina; Low, Nicola; Golparian, Daniel; Unemo, Magnus

    2017-09-01

    The number of genetic tests, mostly real-time PCRs, to detect antimicrobial resistance (AMR) determinants and predict AMR in Neisseria gonorrhoeae is increasing. Several of these assays are promising, but there are important shortcomings and few assays have been adequately validated and quality assured. Areas covered: Recent advances, focusing on publications since 2012, in the development and use of molecular tests to predict gonococcal AMR for surveillance and for clinical use, advantages and disadvantages of these tests and of molecular AMR prediction compared with phenotypic AMR testing, and future perspectives for effective use of molecular AMR tests for different purposes. Expert commentary: Several challenges for direct testing of clinical, especially extra-genital, specimens remain. The choice of molecular assay needs to consider the assay target, quality controls, sample types, limitations intrinsic to molecular technologies, and specific to the chosen methodology, and the intended use of the test. Improved molecular- and particularly genome-sequencing-based methods will supplement AMR testing for surveillance purposes, and translate into point-of-care tests that will lead to personalized treatments, while sparing the last available empiric treatment option (ceftriaxone). However, genetic AMR prediction will never completely replace phenotypic AMR testing, which detects also AMR due to unknown AMR determinants.

  11. Two-step feature selection for predicting survival time of patients with metastatic castrate resistant prostate cancer

    PubMed Central

    Shiga, Motoki

    2016-01-01

    Metastatic castrate resistant prostate cancer (mCRPC) is the major cause of death in prostate cancer patients. Even though some options for treatment of mCRPC have been developed, the most effective therapies remain unclear. Thus finding key patient clinical variables related with mCRPC is an important issue for understanding the disease progression mechanism of mCRPC and clinical decision making for these patients. The Prostate Cancer DREAM Challenge is a crowd-based competition to tackle this essential challenge using new large clinical datasets. This paper proposes an effective procedure for predicting global risks and survival times of these patients, aimed at sub-challenge 1a and 1b of the Prostate Cancer DREAM challenge. The procedure implements a two-step feature selection procedure, which first implements sparse feature selection for numerical clinical variables and statistical hypothesis testing of differences between survival curves caused by categorical clinical variables, and then implements a forward feature selection to narrow the list of informative features. Using Cox’s proportional hazards model with these selected features, this method predicted global risk and survival time of patients using a linear model whose input is a median time computed from the hazard model. The challenge results demonstrated that the proposed procedure outperforms the state of the art model by correctly selecting more informative features on both the global risk prediction and the survival time prediction. PMID:27990267

  12. Host life history and host-parasite syntopy predict behavioural resistance and tolerance of parasites.

    PubMed

    Sears, Brittany F; Snyder, Paul W; Rohr, Jason R

    2015-05-01

    There is growing interest in the role that life-history traits of hosts, such as their 'pace-of-life', play in the evolution of resistance and tolerance to parasites. Theory suggests that, relative to host species that have high syntopy (local spatial and temporal overlap) with parasites, host species with low syntopy should have lower selection pressures for more constitutive (always present) and costly defences, such as tolerance, and greater reliance on more inducible and cheaper defences, such as behaviour. Consequently, we postulated that the degree of host-parasite syntopy, which is negatively correlated with host pace-of-life (an axis reflecting the developmental rate of tadpoles and the inverse of their size at metamorphosis) in our tadpole-parasitic cercarial (trematode) system, would be a negative and positive predictor of behavioural resistance and tolerance, respectively. To test these hypotheses, we exposed seven tadpole species to a range of parasite (cercarial) doses crossed with anaesthesia treatments that controlled for anti-parasite behaviour. We quantified host behaviour, successful and unsuccessful infections, and each species' reaction norm for behavioural resistance and tolerance, defined as the slope between cercarial exposure (or attempted infections) and anti-cercarial behaviours and mass change, respectively. Hence, tolerance is capturing any cost of parasite exposure. As hypothesized, tadpole pace-of-life was a significant positive predictor of behavioural resistance and negative predictor of tolerance, a result that is consistent with a trade-off between behavioural resistance and tolerance across species that warrants further investigation. Moreover, these results were robust to considerations of phylogeny, all possible re-orderings of the three fastest or slowest paced species, and various measurements of tolerance. These results suggest that host pace-of-life and host-parasite syntopy are powerful drivers of both the strength and type

  13. Host life history and host–parasite syntopy predict behavioural resistance and tolerance of parasites

    PubMed Central

    Sears, Brittany F.; Snyder, Paul W.; Rohr, Jason R.

    2016-01-01

    Summary There is growing interest in the role that life-history traits of hosts, such as their ‘pace-of-life’, play in the evolution of resistance and tolerance to parasites.Theory suggests that, relative to host species that have high syntopy (local spatial and temporal overlap) with parasites, host species with low syntopy should have lower selection pressures for more constitutive (always present) and costly defences, such as tolerance, and greater reliance on more inducible and cheaper defences, such as behaviour. Consequently, we postulated that the degree of host–parasite syntopy, which is negatively correlated with host pace-of-life (an axis reflecting the developmental rate of tadpoles and the inverse of their size at metamorphosis) in our tadpole–parasitic cercarial (trematode) system, would be a negative and positive predictor of behavioural resistance and tolerance, respectively.To test these hypotheses, we exposed seven tadpole species to a range of parasite (cercarial) doses crossed with anaesthesia treatments that controlled for anti-parasite behaviour. We quantified host behaviour, successful and unsuccessful infections, and each species’ reaction norm for behavioural resistance and tolerance, defined as the slope between cercarial exposure (or attempted infections) and anti-cercarial behaviours and mass change, respectively. Hence, tolerance is capturing any cost of parasite exposure.As hypothesized, tadpole pace-of-life was a significant positive predictor of behavioural resistance and negative predictor of tolerance, a result that is consistent with a trade-off between behavioural resistance and tolerance across species that warrants further investigation. Moreover, these results were robust to considerations of phylogeny, all possible re-orderings of the three fastest or slowest paced species, and various measurements of tolerance.These results suggest that host pace-of-life and host–parasite syntopy are powerful drivers of both the

  14. A predicted protein interactome identifies conserved global networks and disease resistance subnetworks in maize

    PubMed Central

    Musungu, Bryan; Bhatnagar, Deepak; Brown, Robert L.; Fakhoury, Ahmad M.; Geisler, Matt

    2015-01-01

    Interactomes are genome-wide roadmaps of protein-protein interactions. They have been produced for humans, yeast, the fruit fly, and Arabidopsis thaliana and have become invaluable tools for generating and testing hypotheses. A predicted interactome for Zea mays (PiZeaM) is presented here as an aid to the research community for this valuable crop species. PiZeaM was built using a proven method of interologs (interacting orthologs) that were identified using both one-to-one and many-to-many orthology between genomes of maize and reference species. Where both maize orthologs occurred for an experimentally determined interaction in the reference species, we predicted a likely interaction in maize. A total of 49,026 unique interactions for 6004 maize proteins were predicted. These interactions are enriched for processes that are evolutionarily conserved, but include many otherwise poorly annotated proteins in maize. The predicted maize interactions were further analyzed by comparing annotation of interacting proteins, including different layers of ontology. A map of pairwise gene co-expression was also generated and compared to predicted interactions. Two global subnetworks were constructed for highly conserved interactions. These subnetworks showed clear clustering of proteins by function. Another subnetwork was created for disease response using a bait and prey strategy to capture interacting partners for proteins that respond to other organisms. Closer examination of this subnetwork revealed the connectivity between biotic and abiotic hormone stress pathways. We believe PiZeaM will provide a useful tool for the prediction of protein function and analysis of pathways for Z. mays researchers and is presented in this paper as a reference tool for the exploration of protein interactions in maize. PMID:26089837

  15. Low sex hormone-binding globulin as a predictive marker for insulin resistance in women with hyperandrogenic syndrome.

    PubMed

    Kajaia, Natia; Binder, Helge; Dittrich, Ralf; Oppelt, Patricia G; Flor, Bianca; Cupisti, Susanne; Beckmann, Matthias W; Mueller, Andreas

    2007-10-01

    The aim of the present study is to assess insulin resistance (IR) in women with hyperandrogenic syndrome, which was suggested to replace the term polycystic ovary syndrome by the Androgen Excess Society, and to evaluate whether sex hormone-binding globulin (SHBG) can be used as a predictive marker of IR in hyperandrogenic women. Clinical, metabolic, and endocrine parameters were measured, and an oral glucose tolerance test was carried out. The women were classified as IR group or non-IR group, in accordance with defined cutoff points for the homeostatic model assessment of IR (HOMA-IR) at > or =2.5, the quantitative insulin sensitivity check index at < or = 0.33, and the Matsuda insulin sensitivity index (ISI) at < or = 5. The women classified as having IR had a significantly higher body mass index (BMI) and free androgen index (FAI) and showed significantly lower SHBG and high-density lipoprotein (HDL) levels, regardless of the indices used. However, with the Matsuda ISI, generally more women were diagnosed as having IR, and this group had significantly higher total testosterone and triglyceride values, as well as a higher incidence of hirsutism. Women who were classified as being insulin resistant using insulin sensitivity indices showed significantly higher BMI and FAI values and lower SHBG and HDL levels. However, the Matsuda ISI may be more favorable for identifying IR in hyperandrogenic women. SHBG may serve as a predictive marker of IR in these women, particularly in those who are obese.

  16. Genomic Prediction of Resistance to Pasteurellosis in Gilthead Sea Bream (Sparus aurata) Using 2b-RAD Sequencing

    PubMed Central

    Palaiokostas, Christos; Ferraresso, Serena; Franch, Rafaella; Houston, Ross D.; Bargelloni, Luca

    2016-01-01

    Gilthead sea bream (Sparus aurata) is a species of paramount importance to the Mediterranean aquaculture industry, with an annual production exceeding 140,000 metric tons. Pasteurellosis due to the Gram-negative bacterium Photobacterium damselae subsp. piscicida (Phdp) causes significant mortality, especially during larval and juvenile stages, and poses a serious threat to bream production. Selective breeding for improved resistance to pasteurellosis is a promising avenue for disease control, and the use of genetic markers to predict breeding values can improve the accuracy of selection, and allow accurate calculation of estimated breeding values of nonchallenged animals. In the current study, a population of 825 sea bream juveniles, originating from a factorial cross between 67 broodfish (32 sires, 35 dams), were challenged by 30 min immersion with 1 × 105 CFU virulent Phdp. Mortalities and survivors were recorded and sampled for genotyping by sequencing. The restriction-site associated DNA sequencing approach, 2b-RAD, was used to generate genome-wide single nucleotide polymorphism (SNP) genotypes for all samples. A high-density linkage map containing 12,085 SNPs grouped into 24 linkage groups (consistent with the karyotype) was constructed. The heritability of surviving days (censored data) was 0.22 (95% highest density interval: 0.11–0.36) and 0.28 (95% highest density interval: 0.17–0.4) using the pedigree and the genomic relationship matrix respectively. A genome-wide association study did not reveal individual SNPs significantly associated with resistance at a genome-wide significance level. Genomic prediction approaches were tested to investigate the potential of the SNPs obtained by 2b-RAD for estimating breeding values for resistance. The accuracy of the genomic prediction models (r = 0.38–0.46) outperformed the traditional BLUP approach based on pedigree records (r = 0.30). Overall results suggest that major quantitative trait loci affecting

  17. Tag SNP selection for prediction of tick resistance in Brazilian Braford and Hereford cattle breeds using Bayesian methods.

    PubMed

    Sollero, Bruna P; Junqueira, Vinícius S; Gomes, Cláudia C G; Caetano, Alexandre R; Cardoso, Fernando F

    2017-06-15

    Cattle resistance to ticks is known to be under genetic control with a complex biological mechanism within and among breeds. Our aim was to identify genomic segments and tag single nucleotide polymorphisms (SNPs) associated with tick-resistance in Hereford and Braford cattle. The predictive performance of a very low-density tag SNP panel was estimated and compared with results obtained with a 50 K SNP dataset. BayesB (π = 0.99) was initially applied in a genome-wide association study (GWAS) for this complex trait by using deregressed estimated breeding values for tick counts and 41,045 SNP genotypes from 3455 animals raised in southern Brazil. To estimate the combined effect of a genomic region that is potentially associated with quantitative trait loci (QTL), 2519 non-overlapping 1-Mb windows that varied in SNP number were defined, with the top 48 windows including 914 SNPs and explaining more than 20% of the estimated genetic variance for tick resistance. Subsequently, the most informative SNPs were selected based on Bayesian parameters (model frequency and t-like statistics), linkage disequilibrium and minor allele frequency to propose a very low-density 58-SNP panel. Some of these tag SNPs mapped close to or within genes and pseudogenes that are functionally related to tick resistance. Prediction ability of this SNP panel was investigated by cross-validation using K-means and random clustering and a BayesA model to predict direct genomic values. Accuracies from these cross-validations were 0.27 ± 0.09 and 0.30 ± 0.09 for the K-means and random clustering groups, respectively, compared to respective values of 0.37 ± 0.08 and 0.43 ± 0.08 when using all 41,045 SNPs and BayesB with π = 0.99, or of 0.28 ± 0.07 and 0.40 ± 0.08 with π = 0.999. Bayesian GWAS model parameters can be used to select tag SNPs for a very low-density panel, which will include SNPs that are potentially linked to functional genes. It can be useful for cost

  18. Circulating MicroRNA Are Predictive of Aging and Acute Adaptive Response to Resistance Exercise in Men.

    PubMed

    Margolis, Lee M; Lessard, Sarah J; Ezzyat, Yassine; Fielding, Roger A; Rivas, Donato A

    2016-12-07

    Circulating microRNA (c-miRNA) have the potential to function as novel noninvasive markers of the underlying physiological state of skeletal muscle. This investigation sought to determine the influence of aging on c-miRNA expression at rest and following resistance exercise in male volunteers (Young: n = 9; Older: n = 9). Primary findings were that fasting c-miRNA expression profiles were significantly predictive of aging, with miR-19b-3p, miR-206, and miR-486 distinguishing between age groups. Following resistance exercise, principal component analysis revealed a divergent response in expression of 10 c-miRNA, where expression profiles were upregulated in younger and downregulated in older participants. Using Ingenuity Pathway Analysis to test c-miRNA-to-mRNA interactions in skeletal muscle, it was found that response of c-miRNA to exercise was indicative of an anabolic response in younger but not older participants. These findings were corroborated with a positive association observed with the phosphorylation status of p-Akt(Ser473) and p-S6K1(Thr389) and expression of miR-19a-3p, miR-19b-3p, miR-20a-5p, miR-26b-5p, miR-143-3p, and miR-195-5p. These important findings provide compelling evidence that dysregulation of c-miRNA expression with aging may not only serve as a predictive marker, but also reflect underlying molecular mechanisms resulting in age-associated declines in skeletal muscle mass, increased fat mass, and "anabolic resistance."

  19. Is Mid-trimester Insulin Resistance Predictive of Subsequent Puerperal Infection? A Secondary Analysis of Randomized Trial Data

    PubMed Central

    Hughes, Brenna L.; Clifton, Rebecca G.; Hauth, John C.; Leveno, Kenneth J.; Myatt, Leslie; Reddy, Uma M.; Varner, Michael W.; Wapner, Ronald J.; Mercer, Brian M.; Peaceman, Alan M.; Ramin, Susan M.; Tolosa, Jorge E.; Saade, George; Sorokin, Yoram

    2017-01-01

    Objective The objective of this study was to examine whether there is an association between insulin resistance and subsequent development of puerperal infection by measuring insulin resistance in the mid-trimester using the homeostasis model assessment (HOMA:IR). Methods Secondary analysis of low-risk nulliparas enrolled in a multicenter pre-eclampsia prevention trial. HOMA:IR was measured on fasting plasma glucose and insulin concentrations among low-risk nulliparas between 22 and 26 weeks’ gestation. Median HOMA:IR was compared between women who did and did not develop puerperal infection using Wilcoxon rank sum test. Logistic regression was used to control for potential confounders. Results Of 1,180 women with fasting glucose and insulin available, 121 (10.3%) had a puerperal infection. Median HOMA:IR was higher among those with subsequent puerperal infection (4.3 [interquartile, IQR: 2.2–20.5] vs. 2.6 [IQR: 1.5–6.7], p < 0.0001). After controlling for potentially confounding variables HOMA:IR was only marginally associated with an increased risk of development of puerperal infection, adjusted odds ratio: 1.01 (95% confidence interval: 1.00–1.02; p = 0.04) per unit increase. Elevated HOMA:IR performed poorly as a predictor of puerperal infection, with a positive predictive value of 15% and a negative predictive value of 92%. Conclusion Though associated with an increased risk of puerperal infection, insulin resistance, measured by HOMA:IR, is not a clinically useful predictor of puerperal infection. PMID:27120478

  20. Aurora Kinase A expression predicts platinum-resistance and adverse outcome in high-grade serous ovarian carcinoma patients.

    PubMed

    Mignogna, Chiara; Staropoli, Nicoletta; Botta, Cirino; De Marco, Carmela; Rizzuto, Antonia; Morelli, Michele; Di Cello, Annalisa; Franco, Renato; Camastra, Caterina; Presta, Ivan; Malara, Natalia; Salvino, Angela; Tassone, Pierfrancesco; Tagliaferri, Pierosandro; Barni, Tullio; Donato, Giuseppe; Di Vito, Anna

    2016-05-21

    High-Grade Serous Ovarian Carcinoma (HGSOC) is the predominant histotype of epithelial ovarian cancer (EOC), characterized by advanced stage at diagnosis, frequent TP53 mutation, rapid progression, and high responsiveness to platinum-based-chemotherapy. To date, standard first-line-chemotherapy in advanced EOC includes platinum salts and paclitaxel with or without bevacizumab. The major prognostic factor is the response duration from the end of the platinum-based treatment (platinum-free interval) and about 10-0 % of EOC patients bear a platinum-refractory disease or develop early resistance (platinum-free interval shorter than 6 months). On these bases, a careful selection of patients who could benefit from chemotherapy is recommended to avoid unnecessary side effects and for a better disease outcome. In this retrospective study, an immunohistochemical evaluation of Aurora Kinase A (AURKA) was performed on 41 cases of HGSOC according to platinum-status. Taking into account the number and intensity of AURKA positive cells we built a predictive score able to discriminate with high accuracy platinum-sensitive patients from platinum-resistant patients (p < 0.001). Furthermore, we observed that AURKA overexpression correlates to worse overall survival (p = 0.001; HR 0.14). We here suggest AURKA as new effective tool to predict the biological behavior of HGSOC. Particularly, our results indicate that AURKA has a role both as predictor of platinum-resistance and as prognostic factor, that deserves further investigation in prospective clinical trials. Indeed, in the era of personalized medicine, AURKA could assist the clinicians in selecting the best treatment and represent, at the same time, a promising new therapeutic target in EOC treatment.

  1. Resistance Prediction in AML: Analysis of 4,601 Patients from MRC/NCRI, HOVON/SAKK, SWOG, and MD Anderson Cancer Center

    PubMed Central

    Walter, Roland B.; Othus, Megan; Burnett, Alan K.; Löwenberg, Bob; Kantarjian, Hagop M.; Ossenkoppele, Gert J.; Hills, Robert K.; Ravandi, Farhad; Pabst, Thomas; Evans, Anna; Pierce, Sherry R.; Vekemans, Marie-Christiane; Appelbaum, Frederick R.; Estey, Elihu H.

    2014-01-01

    Therapeutic resistance remains the principal problem in acute myeloid leukemia (AML). We used area under receiver operator characteristic curves (AUC) to quantify our ability to predict therapeutic resistance in individual patients where AUC=1.0 denotes perfect prediction and AUC=0.5 denotes a coin flip, using data from 4,601 patients with newly diagnosed AML given induction therapy with 3+7 or more intense standard regimens in MRC/NCRI, HOVON, SWOG, and MD Anderson Cancer Center studies. Age, performance status, white blood cell count, secondary disease, cytogenetic risk, and FLT3-ITD/NPM1 mutation status were each independently associated with failure to achieve complete remission despite no early death (“primary refractoriness”). However, the AUC of a bootstrap-corrected multivariable model predicting this outcome was only 0.78, indicating only fair predictive ability. Removal of FLT3-ITD and NPM1 information only slightly decreased the AUC (0.76). Prediction of resistance, defined as primary refractoriness or short relapse-free survival (RFS), was even more difficult. Our ability to forecast resistance based on routinely available pre-treatment covariates provides a rationale for continued randomization between standard and new therapies and supports further examination of genetic and post-treatment data to optimize resistance prediction in AML. PMID:25113226

  2. Resistance prediction in AML: analysis of 4601 patients from MRC/NCRI, HOVON/SAKK, SWOG and MD Anderson Cancer Center.

    PubMed

    Walter, R B; Othus, M; Burnett, A K; Löwenberg, B; Kantarjian, H M; Ossenkoppele, G J; Hills, R K; Ravandi, F; Pabst, T; Evans, A; Pierce, S R; Vekemans, M-C; Appelbaum, F R; Estey, E H

    2015-02-01

    Therapeutic resistance remains the principal problem in acute myeloid leukemia (AML). We used area under receiver-operating characteristic curves (AUCs) to quantify our ability to predict therapeutic resistance in individual patients, where AUC=1.0 denotes perfect prediction and AUC=0.5 denotes a coin flip, using data from 4601 patients with newly diagnosed AML given induction therapy with 3+7 or more intense standard regimens in UK Medical Research Council/National Cancer Research Institute, Dutch-Belgian Cooperative Trial Group for Hematology/Oncology/Swiss Group for Clinical Cancer Research, US cooperative group SWOG and MD Anderson Cancer Center studies. Age, performance status, white blood cell count, secondary disease, cytogenetic risk and FLT3-ITD/NPM1 mutation status were each independently associated with failure to achieve complete remission despite no early death ('primary refractoriness'). However, the AUC of a bootstrap-corrected multivariable model predicting this outcome was only 0.78, indicating only fair predictive ability. Removal of FLT3-ITD and NPM1 information only slightly decreased the AUC (0.76). Prediction of resistance, defined as primary refractoriness or short relapse-free survival, was even more difficult. Our limited ability to forecast resistance based on routinely available pretreatment covariates provides a rationale for continued randomization between standard and new therapies and supports further examination of genetic and posttreatment data to optimize resistance prediction in AML.

  3. [Virological response to adefovir dipivoxil predicts the long-term development of resistance in previously untreated patients with HBeAg-negative chronic hepatitis B].

    PubMed

    Suárez, Emilio; Gila, Ana; Figueruela, Blanca; Chueca, Natalia; Muñoz Rueda, Pilar; Puche, Beatriz; Fraga, Enrique; García, Federico; Martín, Juan Manuel; Andrade, Raúl J; Nogales, Carmen; Romero-Gómez, Manuel; Salmerón, Javier

    2011-02-01

    Adefovir dipivoxil monotherapy in lamivudine-resistant patients is associated with more frequent development of resistance than in naïve patients. The virological response during treatment predicts the risk of developing resistance. The aims of this study were to assess the efficacy of adefovir dipivoxil treatment in naïve and lamivudine-resistant patients and to determine whether virological response predicts the development of adefovir resistance. This study included 82 patients with HBeAg-negative chronic hepatitis B (CHB) who received adefovir dipivoxil therapy. During active treatment, HBV-DNA values were determined by polymerase chain reaction; in addition, the presence of adefovir resistance-associated mutations was studied in cases of virological breakthrough. Virological response at 12 and 24 months was 59% and 73% in naive patients compared with 40% and 67% in lamivudine-resistant patients, whereas virological breakthrough at 24 months was 9.5% in naïve patients compared with 20% in lamivudine-resistant patients. A small percentage (4%) of patients with virological response at 12 months showed virological breakthrough between 12 and 40 months versus 29.4% of patients without virological response (P=.03). In lamivudine-resistant patients, virological response at 12 months was not a predictive factor for the development of virological breakthrough. Adefovir dipivoxil monotherapy in lamivudine-resistant patients is associated with an increased tendency to develop virological breakthrough, which cannot be predicted by virological response at 12 months of treatment. In naive patients, an undetectable viral load at 12 months of treatment ensures the absence of virological breakthrough at 40 months of treatment. Copyright © 2010 Elsevier España, S.L. All rights reserved.

  4. Low insulin resistance after surgery predicts poor GH suppression one year after complete resection for acromegaly: a retrospective study.

    PubMed

    Edo, Naoki; Morita, Koji; Suzuki, Hisanori; Takeshita, Akira; Miyakawa, Megumi; Fukuhara, Noriaki; Nishioka, Hiroshi; Yamada, Shozo; Takeuchi, Yasuhiro

    2016-05-31

    Remission of acromegaly is defined as a nadir in GH <1.0 ng/mL during a 75-g oral glucose tolerance test (75gOGTT) and insulin-like growth factor-1 (IGF-1) normalization. Recently, a lower cut-off value for GH nadir (<0.4 ng/mL) has been proposed. We retrospectively evaluated the prevalence and clinical characteristics of postoperative cases with normalized IGF-1 levels and a GH nadir of 0.4-1.0 ng/mL one year after complete resection of GH-secreting pituitary adenoma (GHoma). We included 110 cases of acromegaly with complete adenoma resection, no preoperative treatment, preoperative glycosylated hemoglobin <6.5%, preoperative basal plasma glucose <126 mg/dL, GH nadir <1.0 ng/mL during a 75gOGTT, and normalized IGF-1 at the first postoperative year evaluation, whereupon patients were divided into two groups: control (GH nadir <0.4 ng/mL) and high GH (GH nadir >0.4 ng/mL). Clinical parameters, including measures of insulin secretion and resistance, were compared between groups. The high GH group included 10 patients (9.1%) and had a lesser level of insulin resistance immediately following surgery and at the first postoperative year evaluation. On single regression analysis, insulin resistance immediately following surgery was predictive of and correlated with the GH nadir at the first postoperative year evaluation. The GH nadir at the first postoperative year evaluation may be insufficient in patients with normalized IGF-1 with low insulin resistance immediately following complete resection of GHoma. Careful evaluation is needed to assess remission in such patients.

  5. Nationally representative equations that include resistance and reactance for the prediction of percent body fat in Americans.

    PubMed

    Stevens, J; Truesdale, K P; Cai, J; Ou, F-S; Reynolds, K R; Heymsfield, S B

    2017-07-24

    Resistance and reactance collected by bioelectrical impedance (BIA) can be used in equations to estimate percent body fat at relatively low cost and subject burden. To our knowledge, no such equations have been developed in a nationally representative sample. Dual-energy X-ray absorptiometry assessed percent body fat from the 1999 to 2004 National Health and Nutrition Survey was the criterion method for development of sex-specific percent body fat equations using up to 6467 males or 4888 females 8-49 years of age. Candidate variables were studied in multiple mathematical forms and interactions using the Least Absolute Shrinkage and Selection Operator. Models were fit in 2/3's of the data and validated in 1/3 of the data selected at random. Final coefficients, R(2) values and root mean square error (RMSE) were estimated in the full data set. Models that included age, ethnicity, height, weight, BMI and BIA assessments (resistance, reactance and height(2)/resistance) had R(2) values of 0.831 in men and 0.864 in women in the full data set. RMSE measurements were between 2 and 3 body fat percentage points, and all equations showed low bias across groups formed by age, race/ethnicity or body mass index category. The addition of triceps skinfold and waist circumference increased the R(2) to 0.905 in males and 0.883 in females. Adding other anthropometrics (plus menses in females) had little impact on performance. Reactance and resistance alone (in multiple mathematical forms) performed poorly with R(2)~0.2. Equations that included BIA assessments along with demographic and anthropometric variables provided percent body fat assessments that had high generalizability, strong predictive ability and low bias.International Journal of Obesity advance online publication, 15 August 2017; doi:10.1038/ijo.2017.167.

  6. Predicting resistance to stress: incremental validity of trait emotional intelligence over alexithymia and optimism.

    PubMed

    Mikolajczak, Moïra; Luminet, Olivier; Menil, Clémentine

    2006-01-01

    As trait emotional intelligence [TEI] is claimed to facilitate adaptation, study 1 (N= 80) investigated whether TEI would be associated with adaptative outcomes such as enhanced self-reported mental and physical health. As these assumptions were supported, study 2 (N= 75) tested the hypothesis of a moderating effect of TEI on the relationship between stress and psychological and somatic health. Incremental validity of TEI over alexithymia and optimism was also examined. We chose academic exams as the stressor and took measures at the beginning of the year and during the examination period. Regression analyses predicting changes in mental/somatic health from baseline to follow-up revealed that TEI significantly moderated the relationship between examination stress and self-reported health. The fact that high EI people appraised the examination situation as less threatening partly explained this effect. Moreover, TEI predicted both mental and somatic symptoms amid stress over and above alexithymia and optimism.

  7. The use of model-test data for predicting full-scale ACV resistance

    NASA Astrophysics Data System (ADS)

    Forstell, B. G.; Harry, C. W.

    The paper summarizes the analysis of test data obtained with a 1/12-scale model of the Amphibious Assault Landing Craft (AALC) JEFF(B). The analysis was conducted with the objective of improving the accuracy of drag predictions for a JEFF(B)-type air-cushion vehicle (ACV). Model test results, scaled to full-scale, are compared with full-scale drag obtained in various sea states during JEFF(B) trials. From the results of this comparison, it is found that the Froude-scale model rough-water drag data is consistently greater than full-scale derived drag, and is a function of both wave height and craft forward speed. Results are presented indicating that Froude scaling model data obtained in calm water also causes an over-prediction of calm-water drag at full-scale. An empirical correction that was developed for use on a JEFF(B)-type craft is discussed.

  8. ETS Gene Fusions as Predictive Biomarkers of Resistance to Radiation Therapy for Prostate Cancer

    DTIC Science & Technology

    2013-08-01

    University of Michigan Ann Arbor, MI 48109 REPORT DATE: August 2013 TYPE OF REPORT: Annual ummary PREPARED FOR: U.S. Army Medical...2. REPORT TYPE Annual 3. DATES COVERED 15 July 2012 to 14 July 2013 4. TITLE AND SUBTITLE ETS Gene Fusions as Predictive Biomarkers of...wild- type prostate cancer cells and human prostate cancer samples (data not shown). Unfortunately, this level of homogenous diffuse expression, as well

  9. Usefulness of the renal resistive index to predict an increase in urinary albumin excretion in patients with essential hypertension.

    PubMed

    Miyoshi, K; Okura, T; Tanino, A; Kukida, M; Nagao, T; Higaki, J

    2017-01-01

    Microalbuminuria is a risk factor for cardiovascular events and death in hypertensive patients. Patients who are expected to increase albuminuria need strict blood pressure control. In the present study, we assessed the association between the renal resistive index (RI) and future increases in albuminuria in patients with essential hypertension. Sixty-six patients with essential hypertension were included in the study. Univariate and multivariate logistic regression analyses were used to identify the factors, including renal RI, that were significant independent determinants of increased in urinary albumin excretion (UAE), defined as an increase of >50% in the urinary albumin-to-creatinine ratio over 2 years. Receiver operator characteristics curve analysis was used to select the optimal cut-off point that predicted an increase in UAE. RI was the only significant variable that predicted the increase in UAE, with the optimal cut-off value of renal RI that predicted this increase being 0.71 (sensitivity 52.4% and specificity 84.4%). Renal RI is associated with the future increase in albuminuria in patients with essential hypertension.

  10. Comparison of phenotypic methods in predicting methicillin resistance in coagulase-negative Staphylococcus (CoNS) from animals.

    PubMed

    Zhang, Yifan; Wang, Xiaogang; LeJeune, Jeffrey T; Zervos, Marcus; Bhargava, Kanika

    2011-02-01

    Phenotypic detection of methicillin resistance in coagulase-negative Staphylococcus (CoNS) of animal origin has been challenging due to the heterogeneous expression of mecA. To compare different phenotypic methods in predicting the mecA presence in CoNS, a total of 87 CoNS isolates from agricultural animals were analyzed in this study by agar dilution, disk diffusion, and broth microdilution. mecA was present in 81 CoNS isolates. Broth microdilution demonstrated the highest sensitivity of 100% in predicting the mecA presence, followed by 72.8% by agar dilution and 70.4% by disk diffusion. The results indicate that broth microdilution may be more suitable for predicting the presence of mecA in CoNS from animals than the other two methods, although staphylococcal species may also be a factor affecting the sensitivities of the methods as the top three staphylococcal species in this study were Staphylococcus lentus, Staphylococcus sciuri, and Staphylococcus xylosus (a total of 75 of 87).

  11. Mutation of the rice XA21 predicted nuclear localization sequence does not affect resistance to Xanthomonas oryzae pv. oryzae

    DOE PAGES

    Wei, Tong; Chen, Tsung-Chi; Ho, Yuen Ting; ...

    2016-10-05

    Background: The rice receptor kinase XA21 confers robust resistance to the bacterial pathogenXanthomonas oryzae pv.oryzae(Xoo). We previously reported that XA21 is cleaved in transgenic plants overexpressing XA21 with a GFP tag (Ubi-XA21-GFP) and that the released C-terminal domain is localized to the nucleus. XA21 carries a predicted nuclear localization sequence (NLS) that directs the C-terminal domain to the nucleus in transient assays, whereas alanine substitutions in the NLS disrupt the nuclear localization. Methods: To determine if the predicted NLS is required for XA21-mediated immunityin planta, we generated transgenic plants overexpressing an XA21 variant carrying the NLS with the same alaninemore » substitutions (Ubi-XA21nls-GFP). Results: Ubi- XA21nls-GFP plants displayed slightly longer lesion lengths, higherXoo bacterial populations after inoculation and lower levels of reactive oxygen species production compared with the Ubi- XA21-GFP control plants. However, the Ubi- XA21nls-GFP plants express lower levels of protein than that observed inUbi- XA21-GFP. Discussion: These results demonstrate that the predicted NLS is not required for XA21-mediated immunity.« less

  12. Predictable spatial escapes from herbivory: how do these affect the evolution of herbivore resistance in tropical marine communities?

    PubMed

    Hay, Mark E

    1984-11-01

    Between-habitat differences in macrophyte consumption by herbivorous fishes were examined on three Caribbean and two Indian Ocean coral reefs. Transplanted sections of seagrasses were used as a bioassay to compare removal rates in reef-slope, reef-flat, sand-plain, and lagoon habitats. Herbivore susceptibility of fifty-two species of seaweeds from these habitats was also measured in the field. Seagrass consumption on shallow reef slopes was always significantly greater than on shallow reef flats, deep sand plains, or sandy lagoons. Reef-slope seaweeds were consistently resistant to herbivory while reef-flat seaweeds were consistently very susceptible to herbivory. This pattern supports the hypothesis that defenses against herbivores are costly in terms of fitness and are selected against in habitats with predictably low rates of herbivory.Sand-plain and lagoon seaweeds showed a mixed response when placed in habitats with high herbivore pressure; most fleshy red seaweeds were eaten rapidly, most fleshy green seaweeds were eaten at intermediate rates, and most calcified green seaweeds were avoided or eaten at very low rates. Differences in susceptibility between red and green seaweeds from sand-plain or lagoon habitats may result from differential competitive pressures experienced by these seaweed groups or from the differential probability of being encountered by herbivores. The susceptibility of a species to removal by herbivorous fishes was relatively consistent between reefs. Preferences of the sea urchin Diadema antillarum were also similar to those of the fish guilds.Unique secondary metabolites were characteristic of almost all of the most herbivore resistant seaweeds. However, some of the herbivore susceptible species also contain chemicals that have been proposed as defensive compounds. Genera such as Sargassum, Turbinaria, Thalassia, Halodule, and Thalassodendron, which produce polyphenolics or phenolic acids, were consumed at high to intermediate rates

  13. ETS Gene Fusions as Predictive Biomarkers of Resistance to Radiation Therapy for Prostate Cancer

    DTIC Science & Technology

    2016-05-01

    gene   fusion  product)  and  the   DNA  repair  protein   DNA -­PK,  and  3)  to  determine  if  ETS  gene  fusion  status  is  a  clinical  biomarker...established  this  axis  as  a  potential  therapeutic   target.         15. SUBJECT  TERMS Prostate cancer, ETS gene fusions, ERG, radiation resistance, DNA ...interaction  between  ERG   (the   predominant   ETS   gene   fusion   product)   and   the   DNA   repair   protein   DNA -­PK,   and   3)   to

  14. TERT promoter mutations and long telomere length predict poor survival and radiotherapy resistance in gliomas

    PubMed Central

    Qu, Yiping; Wang, Maode; Cui, Bo; Ji, Meiju; Shi, Bingyin; Hou, Peng

    2016-01-01

    Increasing evidences have implicated somatic gain-of-function mutations at the telomerase reverse transcriptase (TERT) promoter as one of the major mechanisms that promote transcriptional activation of TERT and subsequently maintain telomere length in human cancers including glioma. To investigate the prognostic value of these mutations and telomere length, individually and their coexistence, in gliomas, we analyzed two somatic mutations C228T and C250T in the TERT promoter, relative telomere length (RTL), IDH1 mutation and MGMT methylation in 389 glioma patients, and explored their associations with patient characteristics and clinical outcomes. Our data showed that C228T and C250T mutations were found in 17.0% (66 of 389) and 11.8% (46 of 389) of gliomas, respectively, and these two mutations were mutually exclusive in this cancer. Moreover, they were significantly associated with WHO grade. We also found that the RTL was significant longer in gliomas than in meningiomas and normal brain tissues (Median, 0.89 vs. 0.44 and 0.50; P < 0.001), and demonstrated that the RTL was strongly correlated with tumor recurrence. Importantly, TERT promoter mutations or long RTL caused a significantly poorer survival than TERT wild-type or short RTL. Coexisting TERT promoter mutations and long RTL were more commonly associated with poor patient survival than they were individually. Notably, the patients with TERT promoter mutations particularly C228T or long RTL were resistant to radiotherapy. Collectively, TERT promoter mutations and long RTL are not only prognostic factors for poor clinical outcomes, but also the predictors of radiotherapy resistance in gliomas. PMID:26556853

  15. TERT promoter mutations and long telomere length predict poor survival and radiotherapy resistance in gliomas.

    PubMed

    Gao, Ke; Li, Gang; Qu, Yiping; Wang, Maode; Cui, Bo; Ji, Meiju; Shi, Bingyin; Hou, Peng

    2016-02-23

    Increasing evidences have implicated somatic gain-of-function mutations at the telomerase reverse transcriptase (TERT) promoter as one of the major mechanisms that promote transcriptional activation of TERT and subsequently maintain telomere length in human cancers including glioma. To investigate the prognostic value of these mutations and telomere length, individually and their coexistence, in gliomas, we analyzed two somatic mutations C228T and C250T in the TERT promoter, relative telomere length (RTL), IDH1 mutation and MGMT methylation in 389 glioma patients, and explored their associations with patient characteristics and clinical outcomes. Our data showed that C228T and C250T mutations were found in 17.0% (66 of 389) and 11.8% (46 of 389) of gliomas, respectively, and these two mutations were mutually exclusive in this cancer. Moreover, they were significantly associated with WHO grade. We also found that the RTL was significant longer in gliomas than in meningiomas and normal brain tissues (Median, 0.89 vs. 0.44 and 0.50; P < 0.001), and demonstrated that the RTL was strongly correlated with tumor recurrence. Importantly, TERT promoter mutations or long RTL caused a significantly poorer survival than TERT wild-type or short RTL. Coexisting TERT promoter mutations and long RTL were more commonly associated with poor patient survival than they were individually. Notably, the patients with TERT promoter mutations particularly C228T or long RTL were resistant to radiotherapy. Collectively, TERT promoter mutations and long RTL are not only prognostic factors for poor clinical outcomes, but also the predictors of radiotherapy resistance in gliomas.

  16. ERK phosphorylation is predictive of resistance to IGF-1R inhibition in small cell lung cancer.

    PubMed

    Zinn, Rebekah L; Gardner, Eric E; Marchionni, Luigi; Murphy, Sara C; Dobromilskaya, Irina; Hann, Christine L; Rudin, Charles M

    2013-06-01

    New therapies are critically needed to improve the outcome for patients with small cell lung cancer (SCLC). Insulin-like growth factor 1 receptor (IGF-1R) inhibition is a potential treatment strategy for SCLC: the IGF-1R pathway is commonly upregulated in SCLC and has been associated with inhibition of apoptosis and stimulation of proliferation through downstream signaling pathways, including phosphatidylinositol-3-kinase-Akt and mitogen-activated protein kinase. To evaluate potential determinants of response to IGF-1R inhibition, we assessed the relative sensitivity of 19 SCLC cell lines to OSI-906, a small molecule inhibitor of IGF-1R, and the closely related insulin receptor. Approximately one third of these cell lines were sensitive to OSI-906, with an IC50 < 1 μmol/L. Cell line expression of IGF-1R, IR, IGF-1, IGF-2, IGFBP3, and IGFBP6 did not correlate with sensitivity to OSI-906. Interestingly, OSI-906 sensitive lines expressed significantly lower levels of baseline phospho-ERK relative to resistant lines (P = 0.006). OSI-906 treatment resulted in dose-dependent inhibition of phospho-IGF-1R and phospho-Akt in both sensitive and resistant cell lines, but induced apoptosis and cell-cycle arrest only in sensitive lines. We tested the in vivo efficacy of OSI-906 using an NCI-H187 xenograft model and two SCLC patient xenografts in mice. OSI-906 treatment resulted in 50% tumor growth inhibition in NCI-H187 and 30% inhibition in the primary patient xenograft models compared with mock-treated animals. Taken together our data support IGF-1R inhibition as a viable treatment strategy for a defined subset of SCLC and suggest that low pretreatment levels of phospho-ERK may be indicative of sensitivity to this therapeutic approach.

  17. Whole-genome Sequencing for Surveillance of Invasive Pneumococcal Diseases in Ontario, Canada: Rapid Prediction of Genotype, Antibiotic Resistance and Characterization of Emerging Serotype 22F.

    PubMed

    Deng, Xianding; Memari, Nader; Teatero, Sarah; Athey, Taryn; Isabel, Marc; Mazzulli, Tony; Fittipaldi, Nahuel; Gubbay, Jonathan B

    2016-01-01

    Background: Molecular typing is essential for inferring genetic relatedness between bacterial pathogens. In this study, we applied whole genome sequencing (WGS) for rapid prediction of sequence type and antibiotic resistance for invasive pneumococcal isolates. Methods: 240 isolates from adults (≥50 years old) in Ontario, Canada during 2009 to 2013 were subjected to WGS. Sequence type, antibiotic susceptibility and resistance were predicted directly from short reads. Emerging non-vaccine serotype 22F was further characterized by WGS. Results: Sequence type was successfully determined for 98.3% of isolates. The overall sensitivity and specificity for antibiotic resistance prediction were 95 and 100% respectively, compared to standard susceptibility testing methods. WGS-based phylogeny divided emerging 22F (ST433) strains into two distinct clades: clade A harboring a 23 kb-prophage and anti-phage PhD/Doc system and clade B with virulence-related proteases. Five isolates in clade A developed macrolide resistance via 5.1 kb mega element recombination (encoding mefE and msrD), while one isolate in clade B displayed quinolone resistance via a gyrA mutation. Conclusions: WGS is valuable for routine surveillance of pneumococcal clinical isolates and facilitates prediction of genotype and antibiotic resistance. The emergence of 22F in Ontario in the post-vaccine era and evidence of evolution and divergence of the 22F population warrants heightened pneumococcal molecular surveillance.

  18. Whole-genome Sequencing for Surveillance of Invasive Pneumococcal Diseases in Ontario, Canada: Rapid Prediction of Genotype, Antibiotic Resistance and Characterization of Emerging Serotype 22F

    PubMed Central

    Deng, Xianding; Memari, Nader; Teatero, Sarah; Athey, Taryn; Isabel, Marc; Mazzulli, Tony; Fittipaldi, Nahuel; Gubbay, Jonathan B.

    2016-01-01

    Background: Molecular typing is essential for inferring genetic relatedness between bacterial pathogens. In this study, we applied whole genome sequencing (WGS) for rapid prediction of sequence type and antibiotic resistance for invasive pneumococcal isolates. Methods: 240 isolates from adults (≥50 years old) in Ontario, Canada during 2009 to 2013 were subjected to WGS. Sequence type, antibiotic susceptibility and resistance were predicted directly from short reads. Emerging non-vaccine serotype 22F was further characterized by WGS. Results: Sequence type was successfully determined for 98.3% of isolates. The overall sensitivity and specificity for antibiotic resistance prediction were 95 and 100% respectively, compared to standard susceptibility testing methods. WGS-based phylogeny divided emerging 22F (ST433) strains into two distinct clades: clade A harboring a 23 kb-prophage and anti-phage PhD/Doc system and clade B with virulence-related proteases. Five isolates in clade A developed macrolide resistance via 5.1 kb mega element recombination (encoding mefE and msrD), while one isolate in clade B displayed quinolone resistance via a gyrA mutation. Conclusions: WGS is valuable for routine surveillance of pneumococcal clinical isolates and facilitates prediction of genotype and antibiotic resistance. The emergence of 22F in Ontario in the post-vaccine era and evidence of evolution and divergence of the 22F population warrants heightened pneumococcal molecular surveillance. PMID:28082965

  19. Limited predictive value of the IDF definition of metabolic syndrome for the diagnosis of insulin resistance measured with the oral minimal model.

    PubMed

    Ghanassia, E; Raynaud de Mauverger, E; Brun, J-F; Fedou, C; Mercier, J

    2009-01-01

    To assess the agreement of the NCEP ATP-III and the IDF definitions of metabolic syndrome and to determine their predictive values for the diagnosis of insulin resistance. For this purpose, we recruited 150 subjects (94 women and 56 men) and determined the presence of metabolic syndrome using the NCEP-ATP III and IDF definitions. We evaluated their insulin sensitivity S(I) using Caumo's oral minimal model after a standardized hyperglucidic breakfast test. Subjects whose S(I) was in the lowest quartile were considered as insulin resistant. We then calculated sensitivity, specificity, positive and negative predictive values of both definitions for the diagnosis of insulin resistance. The prevalence of metabolic syndrome was 37.4% (NCEP-ATP III) and 40% (IDF). Agreement between the two definitions was 96%. Using NCEP-ATP III and IDF criteria for the identification of insulin resistant subjects, sensitivity was 55.3% and 63%, specificity was 68.8% and 67.8%, positive predictive value was 37.5% and 40%, negative predictive value was 81.9% and 84.5%, respectively. Positive predictive value increased with the number of criteria for both definitions. Whatever the definition, the scoring of metabolic syndrome is not a reliable tool for the individual diagnosis of insulin resistance, and is more useful for excluding this diagnosis.

  20. Prediction of resultant testosterone concentrations from flywheel-based resistive exercise.

    PubMed

    Caruso, John F; Coday, Michael A; Taylor, Skyler T; Mason, Melissa L; Lutz, Brant M; Ford, Jessica L; Kraemer, William J

    2010-09-01

    Numerous variables impact resultant testosterone concentrations (TC) that foretell the efficacy of workouts. Identifying variables may aid the development of in-flight exercise prescription. To identify variables that predict the variance in TC from flywheel ergometer exercise, 17 subjects did 3 workouts in a randomized order. Comprised of 10-repetition leg press sets, workouts entailed either: 1) 3 sets of both concentric and eccentric muscle actions (CE3), and concentric-only actions done for 2) three (CO3), or 3) six (CO6) sets. Venous plasma TC were collected before and at 1 and 30 min postexercise. The last two collection points served as criterion measures. Body mass, delta blood lactate levels, peak angular velocity, average power, and total work from workouts were used to predict the variance in TC. Predictor variables accounted for significant levels of variance at both 1 and 30 min post-exercise for both the CE3 and the concentric-only (CO3 and CO6 bouts combined) workouts using multivariate regression. Inclusion of eccentric variables (only collected from the CE3 bout; r2 = 0.90) predicted nearly twice the variance than the concentric-only (r2 = 0.54) workouts. Body mass and average power indices were the best predictors of the variance in post-workout TC. Since a flywheel-based device is used to abate in-flight muscle atrophy and strength losses, exercise prescriptions may wish to monitor these indices as they impacted post-workout TC to the greatest extent. Future research should assess why eccentric variables increased the amount of explained variance from flywheel ergometer workouts.

  1. Can geometric indices of heart rate variability predict improvement in autonomic modulation after resistance training in chronic obstructive pulmonary disease?

    PubMed

    Santos, Ana Alice Soares Dos; Ricci-Vitor, Ana Laura; Bragatto, Vanessa Santa Rosa; Santos, Ana Paula Soares Dos; Ramos, Ercy Mara Cipulo; Vanderlei, Luiz Carlos Marques

    2017-03-01

    Chronic obstructive pulmonary disease (COPD) is associated with autonomic dysfunctions that can be evaluated through heart rate variability (HRV). Resistance training promotes improvement in autonomic modulation; however, studies that evaluate this scenario using geometric indices, which include nonlinear evaluation, thus providing more accurate information for physiological interpretation of HRV, are unknown. This study aimed to investigate the influence of resistance training on autonomic modulation, using geometric indices of HRV, and peripheral muscle strength in individuals with COPD. Fourteen volunteers with COPD were submitted to resistance training consisting of 24 sessions lasting 60 min each, with a frequency of three times a week. The intensity was determined as 60% of one maximum repetition and was progressively increased until 80% for the upper and lower limbs. The HRV and dynamometry were performed at two moments, the beginning and the end of the experimental protocol. Significant increases were observed in the RRtri (4·81 ± 1·60 versus 6·55 ± 2·69, P = 0·033), TINN (65·36 ± 35·49 versus 101·07 ± 63·34, P = 0·028), SD1 (7·48 ± 3·17 versus 11·04 ± 6·45, P = 0·038) and SD2 (22·30 ± 8·56 versus 32·92 ± 18·78, P = 0·022) indices after the resistance training. Visual analysis of the Poincare plot demonstrated greater dispersion beat-to-beat and in the long-term interval between consecutive heart beats. Regarding muscle strength, there was a significant increase in the shoulder abduction and knee flexion. In conclusion, geometric indices of HRV can predict improvement in autonomic modulation after resistance training in individuals with COPD; improvement in peripheral muscle strength in patients with COPD was also observed.

  2. The TG/HDL-C ratio does not predict insulin resistance in overweight women of African descent: a study of South African, African American and West African women.

    PubMed

    Knight, Michael G; Goedecke, Julia H; Ricks, Madia; Evans, Juliet; Levitt, Naomi S; Tulloch-Reid, Marshall K; Sumner, Anne E

    2011-01-01

    Women of African descent have a high prevalence of diseases caused by insulin resistance. To positively impact cardiometabolic health in Black women, effective screening tests for insulin resistance must be identified. Recently, the TG/HDL-C ratio has been recommended as a tool to predict insulin resistance in overweight people. While the ratio predicts insulin resistance in White women, it is ineffective in African American women. As there are no data for African women, we tested the ability of the TG/HDL-C ratio to predict insulin resistance in Black women from South Africa, West Africa and the United States. For comparison, the ratio was also tested in White women from South Africa. Participants were 801 women (157 Black South African, 382 African American, 119 West African, 143 White South African, age 36 +/- 9y [mean +/- SD]). Standardized scores were created from log-transformed homeostasis model assessment-insulin resistance values from each population. Participants in the upper third of their population distribution were classified as insulin-resistant. To predict insulin resistance by the TC/HDL-C ratio, area under the receiver operating characteristic (AUC-ROC) curve was used and criteria were: 0.50 for no discrimination and > or = 0.70 for acceptable. Seventy-one percent of the Black women were overweight vs 51% of White women (P<.01). In overweight White women, AUC-ROC curve for prediction of insulin resistance by TG/HDL-C was 0.76 +/- 0.06, but below the 0.70 threshold in each group of overweight Black women (Black South African: 0.64 +/- 0.06, African American: 0.66 +/- 0.03, and West African: 0.63 +/- 0.07). Therefore, TG/HDL-C does not predict insulin resistance in overweight African American women and this investigation extends that finding to overweight Black South African and West African women. Resources to identify effective markers of insulin resistance are needed to improve cardiometabolic health in women of African descent.

  3. Genome-enabled prediction for tick resistance in Hereford and Braford beef cattle via reaction norm models.

    PubMed

    Mota, R R; Lopes, P S; Tempelman, R J; Silva, F F; Aguilar, I; Gomes, C C G; Cardoso, F F

    2016-05-01

    Very few studies have been conducted to infer genotype × environment interaction (G×E) based in genomic prediction models using SNP markers. Therefore, our main objective was to compare a conventional genomic-based single-step model (HBLUP) with its reaction norm model extension (genomic 1-step linear reaction norm model [HLRNM]) to provide EBV for tick resistance as well as to compare predictive performance of these models with counterpart models that ignore SNP marker information, that is, a linear animal model (ABLUP) and its reaction norm extension (1-step linear reaction norm model [ALRNM]). Phenotypes included 10,673 tick counts on 4,363 Hereford and Braford animals, of which 3,591 were genotyped. Using the deviance information criterion for model choice, ABLUP and HBLUP seemed to be poorer fitting in comparison with their respective genomic model extensions. The HLRNM estimated lower average and reaction norm genetic variability compared with the ALRNM, whereas ABLUP and HBLUP seemed to be poorer fitting in comparison with their respective genomic reaction norm model extensions. Heritability and repeatability estimates varied along the environmental gradient (EG) and the genetic correlations were remarkably low between high and low EG, indicating the presence of G×E for tick resistance in these populations. Based on 5-fold -means partitioning, mean cross-validation estimates with their respective SE of predictive accuracy were 0.66 (SE 0.02), 0.67 (SE 0.02), 0.67 (SE 0.02), and 0.66 (SE 0.02) for ABLUP, HBLUP, HLRNM, and ALRNM, respectively. For 5-fold random partitioning, HLRNM (0.71 ± 0.01) was statistically different from ABLUP (0.67 ± 0.01). However, no statistical significance was reported when considering HBLUP (0.70 ± 0.01) and ALRNM (0.70 ± 0.01). Our results suggest that SNP marker information does not lead to higher prediction accuracies in reaction norm models. Furthermore, these accuracies decreased as the tick infestation level increased

  4. STAT1‐associated intratumoural TH1 immunity predicts chemotherapy resistance in high‐grade serous ovarian cancer

    PubMed Central

    Au, Katrina K; Le Page, Cécile; Ren, Runhan; Meunier, Liliane; Clément, Isabelle; Tyrishkin, Kathrin; Peterson, Nichole; Kendall‐Dupont, Jennifer; Childs, Timothy; Francis, Julie‐Ann; Graham, Charles H; Craig, Andrew W; Squire, Jeremy A; Mes‐Masson, Anne‐Marie

    2016-01-01

    Abstract High‐grade serous ovarian carcinoma (HGSC) accounts for 70% of all epithelial ovarian cancers but clinical management is challenged by a lack of accurate prognostic and predictive biomarkers of chemotherapy response. This study evaluated the role of Signal Transducer and Activator of Transcription 1 (STAT1) as an independent prognostic and predictive biomarker and its correlation with intratumoural CD8+ T cells in a second independent biomarker validation study. Tumour STAT1 expression and intratumoural CD8+ T cell infiltration were assessed by immunohistochemistry as a multicentre validation study conducted on 734 chemotherapy‐naïve HGSCs. NanoString‐based profiling was performed to correlate expression of STAT1 target genes CXCL9, CXCL10 and CXCL11 with CD8A transcript expression in 143 primary tumours. Multiplexed cytokine analysis of pre‐treatment plasma from resistant and sensitive patients was performed to assess systemic levels of STAT1‐induced cytokines. STAT1 was validated as a prognostic and predictive biomarker in both univariate and multivariate models and its expression correlated significantly with intra‐epithelial CD8+ T cell infiltration in HGSC. STAT1 levels increased the prognostic and predictive value of intratumoural CD8+ T cells, confirming their synergistic role as biomarkers in HGSC. In addition, expression of STAT1 target genes (CXCL9, CXCL10 and CXCL11) correlated significantly with levels of, and CD8A transcripts from intratumoural CD8+ T cells within the resistant and sensitive tumours. Our findings provide compelling evidence that high levels of STAT1, STAT1‐induced chemokines and CD8+ T cells correlate with improved chemotherapy response in HGSC. These results identify STAT1 and its target genes as novel biomarkers of chemosensitivity in HGSC. These findings provide new translational opportunities for patient stratification for immunotherapies based on emerging biomarkers of inflammation in HGSC. An improved

  5. Bioinformatic prediction of ultraviolet light mutagenesis sensitivity of human genes and a method for genetically engineering UVB resistance.

    PubMed

    Lease, Kevin A; Papageorgio, Chris

    2011-04-18

    Living on earth, we are exposed to ultraviolet (UV) light as part of the solar radiation. UVB spectrum light exposure contributes to the development of skin cancer by interacting with pyrimidine pairs to create lesions called cyclobutane pyrimidine dimers. If these lesions are not removed by nucleotide excision repair, they often give rise to C to T transition mutations. Based on these observations, a bioinformatics approach was used to predict the vulnerability of human protein coding genes to UVB induced loss of function mutations. This data was used to evaluate in depth those genes associated with malignant melanoma. In addition, we demonstrate a method of genetically engineering genes that significantly improves resistance to UVB loss of function mutations.

  6. Maximal strength on different resistance training rowing exercises predicts start phase performance in elite kayakers.

    PubMed

    Ualí, Ismael; Herrero, Azael J; Garatachea, Nuria; Marín, Pedro J; Alvear-Ordenes, Ildefonso; García-López, David

    2012-04-01

    This study aimed to examine the relationship existing between maximum strength values in 2 common resistance training row exercises (bilateral bench pull [BBP] and one-arm cable row [OACR]) and short sprint performance in elite kayakers. Ten junior kayakers (5 women and 5 men) were tested on different days for 1 repetition maximum (1RM) and maximal voluntary isometric contraction in both exercises. Moreover, a 12-m sprint kayak was performed in a dew pond to record split times (2, 5, and 10 m), peak velocity, distance completed considering the first 8 strokes, and mean acceleration induced by right blade and left blade strokes. No differences (p > 0.05) were observed when right and left arms were compared in sprint testing or strength testing variables. Maximal strength values in BBP and OACR were significantly correlated with short sprint performance variables, showing the bilateral exercise with slightly stronger correlation coefficients than the unilateral seated row. Moreover, the relationship between strength testing and sprint testing variables is stronger when maximal force is measured through a dynamic approach (1RM) in comparison with an isometric approach. In conclusion, maximal strength in BBP and OACR is a good predictor of the start phase performance in elite sprint kayakers, mainly the 1RM value in BBP.

  7. DNMT3B gene amplification predicts resistance to DNA demethylating drugs.

    PubMed

    Simó-Riudalbas, Laia; Melo, Sónia A; Esteller, Manel

    2011-07-01

    Disruption of the DNA methylation landscape is one of the most common features of human tumors. However, genetic alterations of DNA methyltransferases (DNMTs) have not been described in carcinogenesis. Herein, we show that pancreatic and breast cancer cells undergo gene amplification of the DNA methyltransferase 3B (DNMT3B). The presence of extra copies of the DNMT3B gene is linked to higher levels of the corresponding mRNA and protein. Most importantly, the elevated gene dosage of DNMT3B is associated with increased resistance to the growth-inhibitory effect mediated by DNA demethylating agents. In particular, cancer cells harboring DNMT3B gene amplification are less sensitive to the decrease in cell viability caused by 5-azacytidine (Vidaza), 5-aza-2-deoxycytidine (Decitabine), and SGI-1027. Overall, the data confirm DNMT3B as a bona fide oncogene in human cancer and support the incorporation of the DNMT3B copy number assay into current clinical trials assessing the efficacy of DNA demethylating drugs in solid tumors.

  8. Prediction of the quality of resistance welds by computer based color image analysis

    NASA Astrophysics Data System (ADS)

    Pechersky, M. J.; Zeoli, K. A.; Kestin, P. A.

    Experiments which were completed to correlate the quality of electric resistance pinch welds with an automated computer analysis of the weld surface are discussed. The pinch welds were performed on small diameter stainless steel tubes after they were annealed in air at several different temperatures to form an oxide layer on the weld surfaces. The images of the tube bore were collected with a borescope, stored in a computer and analyzed. The analysis consisted of computing a parameter which gave a representation of the color integrated over the inspected region. This color parameter was then used to rank the tubes in order of their relative oxidation level. Once this was performed the tubes were welded and low magnification metallography was performed on the welds. It was found that the color analysis gave a perfect correlation with the oxidation levels and that the weld quality was inversely proportional to the amount of oxidation. It was also shown that the color analysis was robust in the sense that the sorting was independent of the borescope illumination level over a large range for both oxidized and unoxidized stems. Thus, the color parameter chosen was an excellent predictor of the weld quality.

  9. Weak Ventral Striatal Responses to Monetary Outcomes Predict an Unwillingness to Resist Cigarette Smoking

    PubMed Central

    Wilson, Stephen J.; Delgado, Mauricio R.; McKee, Sherry A.; Grigson, Patricia S.; MacLean, R. Ross; Nichols, Travis T.; Henry, Shannon L.

    2014-01-01

    As a group, cigarette smokers exhibit blunted subjective, behavioral, and neurobiological responses to nondrug incentives and rewards relative to nonsmokers. Findings from recent studies suggest, however, that there are large individual differences in the devaluation of nondrug rewards among smokers. Moreover, this variability appears to have significant clinical implications, as reduced sensitivity to nondrug rewards is associated with poorer smoking cessation outcomes. Currently, little is known about the neurobiological mechanisms that underlie these individual differences in the responsiveness to nondrug rewards. Here, we tested the hypothesis that individual variability in reward devaluation among smokers is linked to the functioning of the striatum. Specifically, functional magnetic resonance imaging was used to examine variability in the neural response to monetary outcomes in nicotine-deprived smokers anticipating an opportunity to smoke – circumstances found to heighten the devaluation of nondrug rewards by smokers in prior work. We also investigated whether individual differences in reward-related brain activity in those expecting to have access to cigarettes were associated with the degree to which the same individuals subsequently were willing to resist smoking in order to earn additional money. Our key finding was that deprived smokers who exhibited the weakest response to rewards (i.e., monetary gains) in the ventral striatum were least willing to refrain from smoking for monetary reinforcement. These results provide evidence that outcome-related signals in the ventral striatum serve as a marker for clinically meaningful individual differences in reward-motivated behavior among nicotine-deprived smokers. PMID:24777394

  10. Roscovitine confers tumor suppressive effect on therapy-resistant breast tumor cells

    PubMed Central

    2011-01-01

    Introduction Current clinical strategies for treating hormonal breast cancer involve the use of anti-estrogens that block estrogen receptor (ER)α functions and aromatase inhibitors that decrease local and systemic estrogen production. Both of these strategies improve outcomes for ERα-positive breast cancer patients, however, development of therapy resistance remains a major clinical problem. Divergent molecular pathways have been described for this resistant phenotype and interestingly, the majority of downstream events in these resistance pathways converge upon the modulation of cell cycle regulatory proteins including aberrant activation of cyclin dependent kinase 2 (CDK2). In this study, we examined whether the CDK inhibitor roscovitine confers a tumor suppressive effect on therapy-resistant breast epithelial cells. Methods Using various in vitro and in vivo assays, we tested the effect of roscovitine on three hormonal therapy-resistant model cells: (a) MCF-7-TamR (acquired tamoxifen resistance model); (b) MCF-7-LTLTca (acquired letrozole resistance model); and (c) MCF-7-HER2 that exhibit tamoxifen resistance (ER-growth factor signaling cross talk model). Results Hormonal therapy-resistant cells exhibited aberrant activation of the CDK2 pathway. Roscovitine at a dose of 20 μM significantly inhibited the cell proliferation rate and foci formation potential of all three therapy-resistant cells. The drug treatment substantially increased the proportion of cells in G2/M cell cycle phase with decreased CDK2 activity and promoted low cyclin D1 levels. Interestingly, roscovitine also preferentially down regulated the ERα isoform and ER-coregulators including AIB1 and PELP1. Results from xenograft studies further showed that roscovitine can attenuate growth of therapy-resistant tumors in vivo. Conclusions Roscovitine can reduce cell proliferation and survival of hormone therapy-resistant breast cancer cells. Our results support the emerging concept that inhibition

  11. Roscovitine confers tumor suppressive effect on therapy-resistant breast tumor cells.

    PubMed

    Nair, Binoj C; Vallabhaneni, Sreeram; Tekmal, Rajeshwar R; Vadlamudi, Ratna K

    2011-08-11

    Current clinical strategies for treating hormonal breast cancer involve the use of anti-estrogens that block estrogen receptor (ER)α functions and aromatase inhibitors that decrease local and systemic estrogen production. Both of these strategies improve outcomes for ERα-positive breast cancer patients, however, development of therapy resistance remains a major clinical problem. Divergent molecular pathways have been described for this resistant phenotype and interestingly, the majority of downstream events in these resistance pathways converge upon the modulation of cell cycle regulatory proteins including aberrant activation of cyclin dependent kinase 2 (CDK2). In this study, we examined whether the CDK inhibitor roscovitine confers a tumor suppressive effect on therapy-resistant breast epithelial cells. Using various in vitro and in vivo assays, we tested the effect of roscovitine on three hormonal therapy-resistant model cells: (a) MCF-7-TamR (acquired tamoxifen resistance model); (b) MCF-7-LTLTca (acquired letrozole resistance model); and (c) MCF-7-HER2 that exhibit tamoxifen resistance (ER-growth factor signaling cross talk model). Hormonal therapy-resistant cells exhibited aberrant activation of the CDK2 pathway. Roscovitine at a dose of 20 μM significantly inhibited the cell proliferation rate and foci formation potential of all three therapy-resistant cells. The drug treatment substantially increased the proportion of cells in G2/M cell cycle phase with decreased CDK2 activity and promoted low cyclin D1 levels. Interestingly, roscovitine also preferentially down regulated the ERα isoform and ER-coregulators including AIB1 and PELP1. Results from xenograft studies further showed that roscovitine can attenuate growth of therapy-resistant tumors in vivo. Roscovitine can reduce cell proliferation and survival of hormone therapy-resistant breast cancer cells. Our results support the emerging concept that inhibition of CDK2 activity has the potential to

  12. Predicting Antimicrobial Resistance Prevalence and Incidence from Indicators of Antimicrobial Use: What Is the Most Accurate Indicator for Surveillance in Intensive Care Units?

    PubMed

    Fortin, Élise; Platt, Robert W; Fontela, Patricia S; Buckeridge, David L; Quach, Caroline

    2015-01-01

    The optimal way to measure antimicrobial use in hospital populations, as a complement to surveillance of resistance is still unclear. Using respiratory isolates and antimicrobial prescriptions of nine intensive care units (ICUs), this study aimed to identify the indicator of antimicrobial use that predicted prevalence and incidence rates of resistance with the best accuracy. Retrospective cohort study including all patients admitted to three neonatal (NICU), two pediatric (PICU) and four adult ICUs between April 2006 and March 2010. Ten different resistance/antimicrobial use combinations were studied. After adjustment for ICU type, indicators of antimicrobial use were successively tested in regression models, to predict resistance prevalence and incidence rates, per 4-week time period, per ICU. Binomial regression and Poisson regression were used to model prevalence and incidence rates, respectively. Multiplicative and additive models were tested, as well as no time lag and a one 4-week-period time lag. For each model, the mean absolute error (MAE) in prediction of resistance was computed. The most accurate indicator was compared to other indicators using t-tests. Results for all indicators were equivalent, except for 1/20 scenarios studied. In this scenario, where prevalence of carbapenem-resistant Pseudomonas sp. was predicted with carbapenem use, recommended daily doses per 100 admissions were less accurate than courses per 100 patient-days (p = 0.0006). A single best indicator to predict antimicrobial resistance might not exist. Feasibility considerations such as ease of computation or potential external comparisons could be decisive in the choice of an indicator for surveillance of healthcare antimicrobial use.

  13. Clinical factors predict surgical outcomes in pediatric MRI-negative drug-resistant epilepsy.

    PubMed

    Arya, Ravindra; Leach, James L; Horn, Paul S; Greiner, Hansel M; Gelfand, Michael; Byars, Anna W; Arthur, Todd M; Tenney, Jeffrey R; Jain, Sejal V; Rozhkov, Leonid; Fujiwara, Hisako; Rose, Douglas F; Mangano, Francesco T; Holland, Katherine D

    2016-10-01

    Lack of a potentially epileptogenic lesion on brain magnetic resonance imaging (MRI) is a poor prognostic marker for epilepsy surgery. We present a single-center series of childhood-onset MRI-negative drug-resistant epilepsy (DRE) and analyze surgical outcomes and predictors. Children with MRI-negative DRE who had resective surgery from January 2007 to December 2013 were identified using an institutional database. Relevant clinical, neurophysiological, imaging, and surgical data was extracted. The primary outcome measure was seizure freedom. Predictors of seizure freedom were obtained using multivariate logistic regression. Out of 47 children with MRI-negative DRE, 12 (25.5%) were seizure free (International League Against Epilepsy [ILAE] outcome class I), after mean follow-up of 2.75 (±1.72) years. Seizure-free proportion was significantly higher in patients with single seizure semiology and concordant ictal EEG (50.0% vs. 15.2%, p=0.025). Multivariate analysis using only non-invasive pre-surgical data showed that children with daily seizures (OR 0.02, 95% CI<0.001-0.55), and earlier onset of seizures (OR 0.72, 95% CI 0.52-0.99) were less likely to be seizure-free. Also, each additional anti-epileptic drug (AED) tried before surgery decreased the probability of seizure-free outcome (OR 0.16, 95% CI 0.04-0.63). Repeat multivariate analysis after including surgical variables found no additional significant predictors of seizure-freedom. Cortical dysplasia (ILAE type IB) was the commonest histopathology. Surgical outcomes in children with MRI-negative DRE are determined by clinical factors including seizure frequency, age of onset of seizures, and number of failed AEDs. Copyright © 2016 British Epilepsy Association. Published by Elsevier Ltd. All rights reserved.

  14. Predicting spring moth emergence in the pink bollworm (Lepidoptera: Gelechiidae): implications for managing resistance to transgenic cotton.

    PubMed

    Carrière, Y; Ellers-Kirk, C; Pedersen, B; Haller, S; Antilla, L

    2001-10-01

    Cultural control methods have been central in the southwestern United States for reducing pink bollworm, Pectinophora gossypiella (Saunders), damage to cotton. Nevertheless, it is not clear at present how such methods could be integrated within the novel pest management framework allowed by introduction of cotton producing a toxin from Bacillus thuringiensis (Bt) for pink bollworm control. Using statewide pheromone trapping and climatic data in conjunction with deterministic simulation models, we investigated whether manipulation of cotton planting date and use of other cultural control methods could represent valuable tactics for control of the pink bollworm in Arizona. Accumulation of heat units from one January accurately predicted the rate of pink bollworm emergence from diapause in 15 cotton-producing regions. Significant variation in rate of emergence from diapause was present among regions, with earlier emergence at higher altitudes. Most adults emerge from diapause too early to reproduce successfully on cotton, a phenomenon known as suicidal emergence. A method for prediction of the fraction of suicidal emergence resulting from adoption of a given cotton planting date is presented. Results from simulation models suggest that manipulation of planting date and implementation of other control cultural methods reduce the rate of application of insecticides and delay the evolution of resistance to Bt cotton in the pink bollworm.

  15. Predicted highly expressed and putative alien genes of Deinococcus radiodurans and implications for resistance to ionizing radiation damage

    PubMed Central

    Karlin, Samuel; Mrázek, Jan

    2001-01-01

    Predicted highly expressed (PHX) and putative alien genes determined by codon usages are characterized in the genome of Deinococcus radiodurans (strain R1). Deinococcus radiodurans (DEIRA) can survive very high doses of ionizing radiation that are lethal to virtually all other organisms. It has been argued that DEIRA is endowed with enhanced repair systems that provide protection and stability. However, predicted expression levels of DNA repair proteins with the exception of RecA tend to be low and do not distinguish DEIRA from other prokaryotes. In this paper, the capability of DEIRA to resist extreme doses of ionizing and UV radiation is attributed to an unusually high number of PHX chaperone/degradation, protease, and detoxification genes. Explicitly, compared with all current complete prokaryotic genomes, DEIRA contains the greatest number of PHX detoxification and protease proteins. Other sources of environmental protection against severe conditions of UV radiation, desiccation, and thermal effects for DEIRA are the several S-layer (surface structure) PHX proteins. The top PHX gene of DEIRA is the multifunctional tricarboxylic acid (TCA) gene aconitase, which, apart from its role in respiration, also alerts the cell to oxidative damage. PMID:11296249

  16. Scaling and Predicting the Geotechnical Resistance Provided by Alfalfa in Experimental Studies of Alluvial-Channel Morphology and Planform

    NASA Astrophysics Data System (ADS)

    Bankhead, N.; Simon, A.

    2008-12-01

    were then used in conjunction with the Bank Stability and Toe Erosion Model (BSTEM), and a series of laboratory experiments, to evaluate if the factor of safety (FS) of experimental channels lined with different densities of alfalfa could be predicted. Sand banks ranging in height from 1.25 to 3.75 cm were modeled and tested experimentally for cases with different groundwater heights and flow depths in the channel, and with cohesion due to roots being scaled appropriately using a length reduction factor. Model results showed that for alfalfa stem densities ranging from 0 to 10 stems/cm2, bank FS ranged from 0.60 to 1.87 and from 0.60 to 1.12 for 1.25 cm and 3.75 cm-high banks respectively. Preliminary results of the laboratory experiments have successfully shown that if cohesion due to roots calculated from the RipRoot model is scaled appropriately, the stability of experimental channels lined with alfalfa of different densities can be predicted. By quantifying the geotechnical resistance of banks during such studies, more accurate predictions of the conditions necessary to create meandering versus braided channel planforms, and the feedback between channel planform and vegetation density in both experimental and real-world scenarios may now be possible.

  17. Artificial Intelligence and Amikacin Exposures Predictive of Outcomes in Multidrug-Resistant Tuberculosis Patients.

    PubMed

    Modongo, Chawangwa; Pasipanodya, Jotam G; Magazi, Beki T; Srivastava, Shashikant; Zetola, Nicola M; Williams, Scott M; Sirugo, Giorgio; Gumbo, Tawanda

    2016-10-01

    Aminoglycosides such as amikacin continue to be part of the backbone of treatment of multidrug-resistant tuberculosis (MDR-TB). We measured amikacin concentrations in 28 MDR-TB patients in Botswana receiving amikacin therapy together with oral levofloxacin, ethionamide, cycloserine, and pyrazinamide and calculated areas under the concentration-time curves from 0 to 24 h (AUC0-24). The patients were followed monthly for sputum culture conversion based on liquid cultures. The median duration of amikacin therapy was 184 (range, 28 to 866) days, at a median dose of 17.30 (range 11.11 to 19.23) mg/kg. Only 11 (39%) patients had sputum culture conversion during treatment; the rest failed. We utilized classification and regression tree analyses (CART) to examine all potential predictors of failure, including clinical and demographic features, comorbidities, and amikacin peak concentrations (Cmax), AUC0-24, and trough concentrations. The primary node for failure had two competing variables, Cmax of <67 mg/liter and AUC0-24 of <568.30 mg · h/L; weight of >41 kg was a secondary node with a score of 35% relative to the primary node. The area under the receiver operating characteristic curve for the CART model was an R(2) = 0.90 on posttest. In patients weighing >41 kg, sputum conversion was 3/3 (100%) in those with an amikacin Cmax of ≥67 mg/liter versus 3/15 (20%) in those with a Cmax of <67 mg/liter (relative risk [RR] = 5.00; 95% confidence interval [CI], 1.82 to 13.76). In all patients who had both amikacin Cmax and AUC0-24 below the threshold, 7/7 (100%) failed, compared to 7/15 (47%) of those who had these parameters above threshold (RR = 2.14; 95% CI, 1.25 to 43.68). These amikacin dose-schedule patterns and exposures are virtually the same as those identified in the hollow-fiber system model. Copyright © 2016 Modongo et al.

  18. Artificial Intelligence and Amikacin Exposures Predictive of Outcomes in Multidrug-Resistant Tuberculosis Patients

    PubMed Central

    Modongo, Chawangwa; Pasipanodya, Jotam G.; Magazi, Beki T.; Srivastava, Shashikant; Zetola, Nicola M.; Williams, Scott M.; Sirugo, Giorgio

    2016-01-01

    Aminoglycosides such as amikacin continue to be part of the backbone of treatment of multidrug-resistant tuberculosis (MDR-TB). We measured amikacin concentrations in 28 MDR-TB patients in Botswana receiving amikacin therapy together with oral levofloxacin, ethionamide, cycloserine, and pyrazinamide and calculated areas under the concentration-time curves from 0 to 24 h (AUC0–24). The patients were followed monthly for sputum culture conversion based on liquid cultures. The median duration of amikacin therapy was 184 (range, 28 to 866) days, at a median dose of 17.30 (range 11.11 to 19.23) mg/kg. Only 11 (39%) patients had sputum culture conversion during treatment; the rest failed. We utilized classification and regression tree analyses (CART) to examine all potential predictors of failure, including clinical and demographic features, comorbidities, and amikacin peak concentrations (Cmax), AUC0–24, and trough concentrations. The primary node for failure had two competing variables, Cmax of <67 mg/liter and AUC0–24 of <568.30 mg · h/L; weight of >41 kg was a secondary node with a score of 35% relative to the primary node. The area under the receiver operating characteristic curve for the CART model was an R2 = 0.90 on posttest. In patients weighing >41 kg, sputum conversion was 3/3 (100%) in those with an amikacin Cmax of ≥67 mg/liter versus 3/15 (20%) in those with a Cmax of <67 mg/liter (relative risk [RR] = 5.00; 95% confidence interval [CI], 1.82 to 13.76). In all patients who had both amikacin Cmax and AUC0–24 below the threshold, 7/7 (100%) failed, compared to 7/15 (47%) of those who had these parameters above threshold (RR = 2.14; 95% CI, 1.25 to 43.68). These amikacin dose-schedule patterns and exposures are virtually the same as those identified in the hollow-fiber system model. PMID:27458224

  19. High expression of TIMP-1 in human breast cancer tissues is a predictive of resistance to paclitaxel-based chemotherapy.

    PubMed

    Zhu, Dongliang; Zha, Xiaoming; Hu, Meiling; Tao, Aidi; Zhou, Hangbo; Zhou, Xiaojun; Sun, Yujie

    2012-12-01

    For breast cancer patients with lymph node metastasis, paclitaxel is the first-line chemotherapy drug. Clinical studies showed that some patients with breast cancer were insensitive to paclitaxel, which led to chemotherapy failure. Today, no validated markers exist for the prediction of chemotherapy sensitivity in this patient group. Tissue inhibitor of metalloproteinases-1 (TIMP-1) has been shown to protect against apoptosis. Epidemiological studies have also associated elevated tumor tissue TIMP-1 levels with a poor response to cyclophosphamide/methotrexate/5-fluorouracil and anthracycline-based chemotherapy. Additionally, our previous study proved that TIMP-1 significantly decreased the sensitivity of breast cancer cells to paclitaxel-induced apoptosis by enhancing degradation of cyclin B1. These data imply that TIMP-1 may be a useful predictive biomarker for chemotherapy resistance. In this retrospective study, we investigated the association between expression levels of TIMP-1 protein in the primary tumor and objective response to paclitaxel-based chemotherapy in 99 patients with breast cancer. With Kaplan-Meier survival analysis, the patients with high TIMP-1 levels were found to have significantly worse 5-year DFS (71.1 %) than the patients with low levels (88.5 %; P = 0.020). Similarly, the patients with high TIMP-1 levels had significantly worse 5-year OS (78.9 %) than patients with low levels (96.7 %; P = 0.004). In Cox's univariate and multivariate analyses, TIMP-1 was prognostic for both DFS and OS. Our data showed that elevated tumor tissue TIMP-1 levels were significantly associated with a poor response to paclitaxel-based chemotherapy, and TIMP-1 might be a potential biomarker for predicting response of breast cancer patients to paclitaxel-based chemotherapy.

  20. Peri-prostatic Fat Volume Measurement as a Predictive Tool for Castration Resistance in Advanced Prostate Cancer.

    PubMed

    Salji, Mark; Hendry, Jane; Patel, Amit; Ahmad, Imran; Nixon, Colin; Leung, Hing Y

    2017-03-01

    Obesity and aggressive prostate cancer (PC) may be linked, but how local peri-prostatic fat relates to tumour response following androgen deprivation therapy (ADT) is unknown. To test if peri-prostatic fat volume (PPFV) predicts tumour response to ADT. We performed a retrospective study on consecutive patients receiving primary ADT. From staging pelvic magnetic resonance imaging scans, the PPFV was quantified with OsirixX 6.5 imaging software. Statistical (univariate and multivariate) analysis were performed using R Version 3.2.1. Of 224 consecutive patients, 61 with advanced (≥T3 or N1 or M1) disease had (3-mm high resolution axial sections) pelvic magnetic resonance imaging scan before ADT. Median age=75 yr; median PPFV=24.8cm(3) (range, 7.4-139.4cm(3)). PPFV was significantly higher in patients who developed castration resistant prostate cancer (CRPC; n=31), with a median of 37.9cm(3) compared with 16.1cm(3) (p <0.0001, Wilcoxon rank sum test) in patients who showed sustained response to ADT (n=30). Multivariate analysis using Cox proportional hazards models were performed controlling for known predictors of CRPC. PPFV was shown to be independent of all included factors, and the most significant predictor of time to CRPC. Using our multivariate model consisting of all known factors prior to ADT, PPFV significantly improved the area under the curve of the multivariate models receiver operating characteristic analysis. The main study limitation is a relatively small cohort to account for multiple variables, necessitating a future large-scale prospective analysis of PPFV in advanced PC. PPFV quantification in patients with advanced PC predicts tumour response to ADT. The amount of fat around the prostate predicts prostate cancer response to hormone treatment. Copyright © 2017 European Association of Urology. Published by Elsevier B.V. All rights reserved.

  1. Evaluation of Machine Learning and Rules-Based Approaches for Predicting Antimicrobial Resistance Profiles in Gram-negative Bacilli from Whole Genome Sequence Data

    PubMed Central

    Pesesky, Mitchell W.; Hussain, Tahir; Wallace, Meghan; Patel, Sanket; Andleeb, Saadia; Burnham, Carey-Ann D.; Dantas, Gautam

    2016-01-01

    The time-to-result for culture-based microorganism recovery and phenotypic antimicrobial susceptibility testing necessitates initial use of empiric (frequently broad-spectrum) antimicrobial therapy. If the empiric therapy is not optimal, this can lead to adverse patient outcomes and contribute to increasing antibiotic resistance in pathogens. New, more rapid technologies are emerging to meet this need. Many of these are based on identifying resistance genes, rather than directly assaying resistance phenotypes, and thus require interpretation to translate the genotype into treatment recommendations. These interpretations, like other parts of clinical diagnostic workflows, are likely to be increasingly automated in the future. We set out to evaluate the two major approaches that could be amenable to automation pipelines: rules-based methods and machine learning methods. The rules-based algorithm makes predictions based upon current, curated knowledge of Enterobacteriaceae resistance genes. The machine-learning algorithm predicts resistance and susceptibility based on a model built from a training set of variably resistant isolates. As our test set, we used whole genome sequence data from 78 clinical Enterobacteriaceae isolates, previously identified to represent a variety of phenotypes, from fully-susceptible to pan-resistant strains for the antibiotics tested. We tested three antibiotic resistance determinant databases for their utility in identifying the complete resistome for each isolate. The predictions of the rules-based and machine learning algorithms for these isolates were compared to results of phenotype-based diagnostics. The rules based and machine-learning predictions achieved agreement with standard-of-care phenotypic diagnostics of 89.0 and 90.3%, respectively, across twelve antibiotic agents from six major antibiotic classes. Several sources of disagreement between the algorithms were identified. Novel variants of known resistance factors and

  2. Evaluation of Machine Learning and Rules-Based Approaches for Predicting Antimicrobial Resistance Profiles in Gram-negative Bacilli from Whole Genome Sequence Data.

    PubMed

    Pesesky, Mitchell W; Hussain, Tahir; Wallace, Meghan; Patel, Sanket; Andleeb, Saadia; Burnham, Carey-Ann D; Dantas, Gautam

    2016-01-01

    The time-to-result for culture-based microorganism recovery and phenotypic antimicrobial susceptibility testing necessitates initial use of empiric (frequently broad-spectrum) antimicrobial therapy. If the empiric therapy is not optimal, this can lead to adverse patient outcomes and contribute to increasing antibiotic resistance in pathogens. New, more rapid technologies are emerging to meet this need. Many of these are based on identifying resistance genes, rather than directly assaying resistance phenotypes, and thus require interpretation to translate the genotype into treatment recommendations. These interpretations, like other parts of clinical diagnostic workflows, are likely to be increasingly automated in the future. We set out to evaluate the two major approaches that could be amenable to automation pipelines: rules-based methods and machine learning methods. The rules-based algorithm makes predictions based upon current, curated knowledge of Enterobacteriaceae resistance genes. The machine-learning algorithm predicts resistance and susceptibility based on a model built from a training set of variably resistant isolates. As our test set, we used whole genome sequence data from 78 clinical Enterobacteriaceae isolates, previously identified to represent a variety of phenotypes, from fully-susceptible to pan-resistant strains for the antibiotics tested. We tested three antibiotic resistance determinant databases for their utility in identifying the complete resistome for each isolate. The predictions of the rules-based and machine learning algorithms for these isolates were compared to results of phenotype-based diagnostics. The rules based and machine-learning predictions achieved agreement with standard-of-care phenotypic diagnostics of 89.0 and 90.3%, respectively, across twelve antibiotic agents from six major antibiotic classes. Several sources of disagreement between the algorithms were identified. Novel variants of known resistance factors and

  3. Targeted MS Assay Predicting Tamoxifen Resistance in Estrogen-Receptor-Positive Breast Cancer Tissues and Sera.

    PubMed

    De Marchi, Tommaso; Kuhn, Erik; Dekker, Lennard J; Stingl, Christoph; Braakman, Rene B H; Opdam, Mark; Linn, Sabine C; Sweep, Fred C G J; Span, Paul N; Luider, Theo M; Foekens, John A; Martens, John W M; Carr, Steven A; Umar, Arzu

    2016-04-01

    We recently reported on the development of a 4-protein-based classifier (PDCD4, CGN, G3BP2, and OCIAD1) capable of predicting outcome to tamoxifen treatment in recurrent, estrogen-receptor-positive breast cancer based on high-resolution MS data. A precise and high-throughput assay to measure these proteins in a multiplexed, targeted fashion would be favorable to measure large numbers of patient samples to move these findings toward a clinical setting. By coupling immunoprecipitation to multiple reaction monitoring (MRM) MS and stable isotope dilution, we developed a high-precision assay to measure the 4-protein signature in 38 primary breast cancer whole tissue lysates (WTLs). Furthermore, we evaluated the presence and patient stratification capabilities of our signature in an independent set of 24 matched (pre- and post-therapy) sera. We compared the performance of immuno-MRM (iMRM) with direct MRM in the absence of fractionation and shotgun proteomics in combination with label-free quantification (LFQ) on both WTL and laser capture microdissected (LCM) tissues. Measurement of the 4-proteins by iMRM showed not only higher accuracy in measuring proteotypic peptides (Spearman r: 0.74 to 0.93) when compared with MRM (Spearman r: 0.0 to 0.76) but also significantly discriminated patient groups based on treatment outcome (hazard ratio [HR]: 10.96; 95% confidence interval [CI]: 4.33 to 27.76; Log-rank P < 0.001) when compared with LCM (HR: 2.85; 95% CI: 1.24 to 6.54; Log-rank P = 0.013) and WTL (HR: 1.16; 95% CI: 0.57 to 2.33; Log-rank P = 0.680) LFQ-based predictors. Serum sample analysis by iMRM confirmed the detection of the four proteins in these samples. We hereby report that iMRM outperformed regular MRM, confirmed our previous high-resolution MS results in tumor tissues, and has shown that the 4-protein signature is measurable in serum samples.

  4. Utility of Prior Cultures in Predicting Antibiotic Resistance of Bloodstream Infections Due to Gram-negative Pathogens: A Multicenter Observational Cohort Study.

    PubMed

    MacFadden, Derek R; Coburn, Bryan; Shah, Nirav; Robicsek, Ari; Savage, Rachel; Elligsen, Marion; Daneman, Nick

    2017-08-12

    Appropriate empiric antibiotic therapy in patients with bloodstream infections due to Gram-negative pathogens can improve outcomes. We evaluated the utility of prior microbiologic results for guiding empiric treatment in Gram-negative bloodstream infections. We conducted a multi-center observational cohort study, in two large health systems in Canada and the United States, including 1,832 hospitalized patients with Gram-negative bloodstream infection (community, hospital, and ICU acquired) from April 2010 to March 2015. Among 1,832 patients with Gram-negative bloodstream infection, 28% (504/1,832) of patients had a documented prior Gram-negative organism from a non-screening culture within the previous 12 months. A most-recent prior Gram-negative organism resistant to a given antibiotic was strongly predictive of the current organism's resistance to the same antibiotic. The overall specificity was 0.92 (95%CI:0.91-0.93) and positive predictive value was 0.66 (95%CI:0.61-0.70) for predicting antibiotic resistance. Specificities and positive predictive values ranged from (0.77 to 0.98) and (0.43 to 0.78) across different antibiotics, organisms, and patient subgroups. Increasing time between cultures was associated with a decrease in positive predictive value but not specificity. An heuristic based on a prior resistant Gram-negative could have been applied to 1 in 4 patients, and in these patients would have changed therapy in 1 in 5. In patients with a bloodstream infection with a Gram-negative organism, identification of a most-recent prior Gram-negative organism resistant to a drug of interest (within the last 12 months) is highly specific for resistance and should preclude use of that antibiotic. Copyright © 2017. Published by Elsevier Ltd.

  5. Fetal Cerebrovascular Resistance and Neonatal EEG Predict 18-month Neurodevelopmental Outcome in Infants with Congenital Heart Disease

    PubMed Central

    Williams, Ismee A.; Tarullo, Amanda R.; Grieve, Philip G.; Wilpers, Abigail; Vignola, Emilia F.; Myers, Michael M.; Fifer, William P.

    2012-01-01

    Objectives The purpose of this study was to investigate early markers of risk for neurobehavioral compromise in congenital heart disease (CHD) survivors. Methods Fetuses < 24 wks gestational age (GA) were enrolled in this prospective pilot study for serial Doppler assessment of the middle cerebral and umbilical artery. The cerebral-to-placental resistance ratio (CPR) and MCA pulsatility index (PI) z-scores for GA were calculated. After birth, subjects underwent high-density (128-lead) electroencephalogram (EEG) and beta frequency (12–24Hz) band EEG power, a measure of local neural synchrony, was analyzed. Neurodevelopment was assessed at 18-months with the Bayley Scales of Infant Development III (BSID). Results 13 subjects were enrolled: 4 with hypoplastic left heart syndrome (HLHS), 4 with transposition of the great arteries (TGA), and 5 with tetralogy of Fallot (TOF). Compared with subjects with normal CPR, those with CPR<1(N=7) had lower mean BSID cognitive scores (91.4±4.8 vs. 99.2±3.8, p=.008). Fetal MCA PI z-score also correlated with BSID cognitive score (r=.589, p=0.044) as did neonatal EEG left frontal polar (r=.58, p=.037) and left frontal (r=.77,p=.002) beta power. Furthermore, fetal Doppler measures were associated with EEG power: fetuses with CPR<1 had lower left frontal polar (t=2.36, p=.038) and left frontal (t=2.85, p=.016) beta power as newborns compared with fetuses with normal CPR, and fetal MCA PI z-score correlated with neonatal EEG left frontal polar (r=.596, p=.04) and left frontal (r=.598, p=.04) beta power. Conclusions In CHD fetuses with HLHS, TGA, and TOF, abnormal cerebrovascular resistance predicted decreased neonatal EEG left frontal beta power and lower 18-mo cognitive development scores. PMID:22351034

  6. Enlarged subcutaneous abdominal adipocyte size, but not obesity itself, predicts type II diabetes independent of insulin resistance.

    PubMed

    Weyer, C; Foley, J E; Bogardus, C; Tataranni, P A; Pratley, R E

    2000-12-01

    Cross-sectional studies indicate that enlarged subcutaneous abdominal adipocyte size is associated with hyperinsulinaemia, insulin resistance and glucose intolerance. To further explore the pathophysiological significance of these associations, we examined prospectively whether enlarged subcutaneous abdominal adipocyte size predicts Type II (non-insulin-dependent) diabetes mellitus. Body composition (hydrodensitometry), mean subcutaneous abdominal adipocyte size (fat biopsy), insulin sensitivity (hyperinsulinaemic clamp) and the acute insulin secretory response (25-g i.v. GTT) were assessed in 280 Pima Indians with either normal (NGT), impaired (IGT) or diabetic glucose tolerance (75-g OGTT). Subjects with NGT were then followed prospectively. After adjusting for age, sex and per cent body fat, mean subcutaneous abdominal adipocyte size was 19% and 11% higher in subjects with diabetes and IGT, compared with those with NGT (p < 0.001). Insulin sensitivity was inversely correlated with mean subcutaneous abdominal adipocyte size (r = -0.53, p < 0.0001), even after adjusting for per cent body fat (r = -0.31, p < 0.001). In 108 NGT subjects followed over 9.3 +/- 4.1 years (33 of whom developed diabetes), enlarged mean subcutaneous abdominal adipocyte size but not high per cent body fat, was an independent predictor of diabetes, in addition to a low insulin sensitivity and acute insulin secretory response [relative hazard 10th vs 90th centile (95% CI): 5.8 (1.7-19.6), p < 0.005]. In 28 NGT subjects with a 9% weight gain over 2.7 +/- 1.3 years, changes in insulin sensitivity were inversely and independently related to changes in mean subcutaneous abdominal adipocyte size and per cent body fat. Although enlarged mean subcutaneous abdominal adipocyte size is associated with insulin resistance cross-sectionally, prospectively, both abnormalities are independent and additive predictors of Type II diabetes.

  7. The Diagnostic Apathia Scale predicts a dose-remission relationship of T-PEMF in treatment-resistant depression.

    PubMed

    Bech, Per; Lunde, Marianne; Lauritzen, Lise; Straasø, Birgit; Lindberg, Lone; Vinberg, Maj; Undén, Mogens; Hellström, Lone Christina; Dissing, Steen; Larsen, Erik Roj

    2015-02-01

    The aim of this study was to evaluate the predictive validity of the apathy subsyndrome in patients with therapy-resistant depression in the dose-remission study with transcranial pulsating electromagnetic fields (T-PEMF). The apathy subsyndrome consists of the symptoms of fatigue, concentration and memory problems, lack of interests, difficulties in making decisions, and sleep problems. We evaluated 65 patients with therapy-resistant depression. In total, 34 of these patients received placebo T-PEMF in the afternoon and active T-PEMF in the morning, that is, one daily dose. The remaining 31 patients received active T-PEMF twice daily. Duration of treatment was 8 weeks in both groups. The Hamilton Depression Scale (HAM-D17) and the Bech-Rafaelsen Melancholia Scale (MES) were used to measure remission. We also focused on the Diagnostic Apathia Scale, which is based on a mixture of items from the MINI and the HAM-D17/MES. In patients without apathy, the remission rate after T-PEMF was 83.9% versus 58.8% in patients with apathy (p≤0.05). In patients without apathy receiving one active dose daily 94.4% remitted versus 50% for patients with apathy (p≤0.05). In patients without apathy who received two active doses 69.9% remitted versus 66.7% for patients with apathy (p≤0.05). Taking the baseline diagnosis of the apathy syndrome into consideration, we found that in patients without apathy one daily dose of T-PEMF is sufficient, but in patients with apathy two daily doses are necessary. Including the apathy syndrome as predictor in future studies would seem to be clinically relevant.

  8. Could "a body shape index" and "waist to height ratio" predict insulin resistance and metabolic syndrome in polycystic ovary syndrome?

    PubMed

    Behboudi-Gandevani, Samira; Ramezani Tehrani, Fahimeh; Cheraghi, Leila; Azizi, Fereidoun

    2016-10-01

    To investigate whether a body shape index (ABSI) and waist to height ratio (WHtR) could predict insulin resistance (IR) and metabolic syndrome (MetS) in women with polycystic ovary syndrome (PCOS) compared to healthy women. In a population-based study a cohort of 754 reproductive-aged women including 704 eumenorrheic non-hirsute subjects and 50 PCOS women selected according to the national institutes of health's (NIH) criteria. The ability of ABSI and WHtR for the prediction of IR was estimated by the homeostasis model and metabolic syndrome according to the joint interim statement criteria. Age and BMI adjusted prevalence of IR and MetS in PCOS women vs. healthy controls were 34% vs. 26%, P=0.041 and 15% vs. 14%, P=0.917, respectively. Mean (SD) of ABSI in PCOS women and healthy women were 0.76 (0.05) and 0.76 (0.053), respectively (P=0.363). The area under curve (CI 95%) of WHtR for predicting IR and MetS among PCOS women vs. healthy women were 0.751 (0.60-0.89) vs. 0.69 (0.65-0.73) and 0.902 (0.81-0.98) vs. 0.802 (0.76-0.83), respectively. As such, the area under curve (CI 95%) of ABSI for ROC curve analysis for predicting IR and MetS among PCOS women vs. healthy women were 0.482 (0.31-0.64) vs. 0.537 (0.49-0.58) and 0.538 (0.35-0.72) vs. 0.584 (0.60-0.69), respectively. These findings suggested that WHtR but not ABSI were a good predictor of IR and MetS among PCOS and healthy women. WHtR may be proposed as a screening tool for IR and MetS risk assessment among PCOS women as a sensitive, inexpensive, noninvasive, simple to assess and easy to calculate measurement tools. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  9. Mathematical modeling of bacterial kinetics to predict the impact of antibiotic colonic exposure and treatment duration on the amount of resistant enterobacteria excreted.

    PubMed

    Nguyen, Thu Thuy; Guedj, Jeremie; Chachaty, Elisabeth; de Gunzburg, Jean; Andremont, Antoine; Mentré, France

    2014-09-01

    Fecal excretion of antibiotics and resistant bacteria in the environment are major public health threats associated with extensive farming and modern medical care. Innovative strategies that can reduce the intestinal antibiotic concentrations during treatments are in development. However, the effect of lower exposure on the amount of resistant enterobacteria excreted has not been quantified, making it difficult to anticipate the impact of these strategies. Here, we introduce a bacterial kinetic model to capture the complex relationships between drug exposure, loss of susceptible enterobacteria and growth of resistant strains in the feces of piglets receiving placebo, 1.5 or 15 mg/kg/day ciprofloxacin, a fluoroquinolone, for 5 days. The model could well describe the kinetics of drug susceptible and resistant enterobacteria observed during treatment, and up to 22 days after treatment cessation. Next, the model was used to predict the expected amount of resistant enterobacteria excreted over an average piglet's lifetime (150 days) when varying drug exposure and treatment duration. For the clinically relevant dose of 15 mg/kg/day for 5 days, the total amount of resistant enterobacteria excreted was predicted to be reduced by 75% and 98% when reducing treatment duration to 3 and 1 day treatment, respectively. Alternatively, for a fixed 5-days treatment, the level of resistance excreted could be reduced by 18%, 33%, 57.5% and 97% if 3, 5, 10 and 30 times lower levels of colonic drug concentrations were achieved, respectively. This characterization on in vivo data of the dynamics of resistance to antibiotics in the colonic flora could provide new insights into the mechanism of dissemination of resistance and can be used to design strategies aiming to reduce it.

  10. Predicting resistance as indicator for need to switch from first-line antiretroviral therapy among patients with elevated viral loads: development of a risk score algorithm.

    PubMed

    Rutstein, Sarah E; Hosseinipour, Mina C; Weinberger, Morris; Wheeler, Stephanie B; Biddle, Andrea K; Wallis, Carole L; Balakrishnan, Pachamuthu; Mellors, John W; Morgado, Mariza; Saravanan, Shanmugam; Tripathy, Srikanth; Vardhanabhuti, Saran; Eron, Joseph J; Miller, William C

    2016-06-13

    In resource-limited settings, where resistance testing is unavailable, confirmatory testing for patients with high viral loads (VL) delays antiretroviral therapy (ART) switches for persons with resistance. We developed a risk score algorithm to predict need for ART change by identifying resistance among persons with persistently elevated VL. We analyzed data from a Phase IV open-label trial. Using logistic regression, we identified demographic and clinical characteristics predictive of need for ART change among participants with VLs ≥1000 copies/ml, and assigned model-derived scores to predictors. We designed three models, including only variables accessible in resource-limited settings. Among 290 participants with at least one VL ≥1000 copies/ml, 51 % (148/290) resuppressed and did not have resistance testing; among those who did not resuppress and had resistance testing, 47 % (67/142) did not have resistance and 53 % (75/142) had resistance (ART change needed for 25.9 % (75/290)). Need for ART change was directly associated with higher baseline VL and higher VL at time of elevated measure, and inversely associated with treatment duration. Other predictors included body mass index and adherence. Area under receiver operating characteristic curves ranged from 0.794 to 0.817. At a risk score ≥9, sensitivity was 14.7-28.0 % and specificity was 96.7-98.6 %. Our model performed reasonably well and may be a tool to quickly transition persons in need of ART change to more effective regimens when resistance testing is unavailable. Use of this algorithm may result in public health benefits and health system savings through reduced transmissions of resistant virus and costs on laboratory investigations.

  11. Mathematical Modeling of Bacterial Kinetics to Predict the Impact of Antibiotic Colonic Exposure and Treatment Duration on the Amount of Resistant Enterobacteria Excreted

    PubMed Central

    Nguyen, Thu Thuy; Guedj, Jeremie; Chachaty, Elisabeth; de Gunzburg, Jean; Andremont, Antoine; Mentré, France

    2014-01-01

    Fecal excretion of antibiotics and resistant bacteria in the environment are major public health threats associated with extensive farming and modern medical care. Innovative strategies that can reduce the intestinal antibiotic concentrations during treatments are in development. However, the effect of lower exposure on the amount of resistant enterobacteria excreted has not been quantified, making it difficult to anticipate the impact of these strategies. Here, we introduce a bacterial kinetic model to capture the complex relationships between drug exposure, loss of susceptible enterobacteria and growth of resistant strains in the feces of piglets receiving placebo, 1.5 or 15 mg/kg/day ciprofloxacin, a fluoroquinolone, for 5 days. The model could well describe the kinetics of drug susceptible and resistant enterobacteria observed during treatment, and up to 22 days after treatment cessation. Next, the model was used to predict the expected amount of resistant enterobacteria excreted over an average piglet's lifetime (150 days) when varying drug exposure and treatment duration. For the clinically relevant dose of 15 mg/kg/day for 5 days, the total amount of resistant enterobacteria excreted was predicted to be reduced by 75% and 98% when reducing treatment duration to 3 and 1 day treatment, respectively. Alternatively, for a fixed 5-days treatment, the level of resistance excreted could be reduced by 18%, 33%, 57.5% and 97% if 3, 5, 10 and 30 times lower levels of colonic drug concentrations were achieved, respectively. This characterization on in vivo data of the dynamics of resistance to antibiotics in the colonic flora could provide new insights into the mechanism of dissemination of resistance and can be used to design strategies aiming to reduce it. PMID:25210849

  12. Prediction of response to antiretroviral therapy by human experts and by the EuResist data-driven expert system (the EVE study).

    PubMed

    Zazzi, M; Kaiser, R; Sönnerborg, A; Struck, D; Altmann, A; Prosperi, M; Rosen-Zvi, M; Petroczi, A; Peres, Y; Schülter, E; Boucher, C A; Brun-Vezinet, F; Harrigan, P R; Morris, L; Obermeier, M; Perno, C-F; Phanuphak, P; Pillay, D; Shafer, R W; Vandamme, A-M; van Laethem, K; Wensing, A M J; Lengauer, T; Incardona, F

    2011-04-01

    The EuResist expert system is a novel data-driven online system for computing the probability of 8-week success for any given pair of HIV-1 genotype and combination antiretroviral therapy regimen plus optional patient information. The objective of this study was to compare the EuResist system vs. human experts (EVE) for the ability to predict response to treatment. The EuResist system was compared with 10 HIV-1 drug resistance experts for the ability to predict 8-week response to 25 treatment cases derived from the EuResist database validation data set. All current and past patient data were made available to simulate clinical practice. The experts were asked to provide a qualitative and quantitative estimate of the probability of treatment success. There were 15 treatment successes and 10 treatment failures. In the classification task, the number of mislabelled cases was six for EuResist and 6-13 for the human experts [mean±standard deviation (SD) 9.1±1.9]. The accuracy of EuResist was higher than the average for the experts (0.76 vs. 0.64, respectively). The quantitative estimates computed by EuResist were significantly correlated (Pearson r=0.695, P<0.0001) with the mean quantitative estimates provided by the experts. However, the agreement among experts was only moderate (for the classification task, inter-rater κ=0.355; for the quantitative estimation, mean±SD coefficient of variation=55.9±22.4%). With this limited data set, the EuResist engine performed comparably to or better than human experts. The system warrants further investigation as a treatment-decision support tool in clinical practice. © 2010 British HIV Association.

  13. Quality of life predicts overall survival in women with platinum-resistant ovarian cancer: an AURELIA substudy.

    PubMed

    Roncolato, F T; Gibbs, E; Lee, C K; Asher, R; Davies, L C; Gebski, V J; Friedlander, M; Hilpert, F; Wenzel, L; Stockler, M R; King, M; Pujade-Lauraine, E

    2017-08-01

    Women with platinum-resistant ovarian cancer are a heterogeneous group whose median overall survival is 12 months. We hypothesized that their quality of life (QoL) scores would be prognostic. Data from AURELIA (n = 326), a randomized trial of chemotherapy with or without bevacizumab, were used to identify baseline QoL domains [EORTC (European Organisation for Research and Treatment of Cancer) QLQ-C30 and OV28] that were significantly associated with overall survival in multivariable Cox regression analyses. Patients were classified as having good, medium, or poor risk. Cutpoints were validated in an independent dataset, CARTAXHY (n = 136). Multivariable analyses of significant QoL domains on survival were adjusted for clinicopathological prognostic factors. The additional QoL information was assessed using C statistic. In AURELIA, all domains, except cognitive function, predicted overall survival in univariable analyses. Physical function (P < 0.001) and abdominal/gastrointestinal symptom (P < 0.001) scores remained significant in multivariable models. In high (score <67), medium (67-93), and low (>93) risk categories for physical function, median overall survival was 11.0, 14.7, and 19.3 months, respectively (P < 0.001). In CARTAXHY, median overall survival was 7.9, 16.2, and 23.9 months (P < 0.001), respectively. For high- (>44), medium- (13-44), and low- (<13) risk categories for abdominal/gastrointestinal symptoms, median overall survival was 11.9, 14.3, and 19.7 months in AURELIA (P < 0.001) and 10.5, 19.6, and 24.1 months in CARTAXHY (P = 0.02). Physical function (P = 0.02) and abdominal/gastrointestinal symptoms (P = 0.03) remained independent prognostic factors after adjustment for clinicopathological factors. The C statistic of the full model was 0.71. For QoL factors alone, patient factors alone and disease factors alone, the C statistics were 0.61, 0.61, and 0.67 respectively. Physical function and

  14. Evaluation of genome-enabled selection for bacterial cold water disease resistance using progeny performance data in Rainbow Trout: Insights on genotyping methods and genomic prediction models

    USDA-ARS?s Scientific Manuscript database

    Bacterial cold water disease (BCWD) causes significant economic losses in salmonid aquaculture, and traditional family-based breeding programs aimed at improving BCWD resistance have been limited to exploiting only between-family variation. We used genomic selection (GS) models to predict genomic br...

  15. Postoperative day 1 access blood flow and resistive index can predict patency in distal forearm arteriovenous fistula.

    PubMed

    Shintaku, Sadanori; Kawanishi, Hideki; Moriishi, Misaki; Ago, Rika; Banshodani, Masataka; Hashimoto, Shinji; Tsuchiya, Shinichiro

    2017-09-11

    Early access failure is an important complication of autogenous arteriovenous fistulas (AVFs). We prospectively monitored patients who underwent AVF creation using ultrasonography. Color flow imaging was used to assess access blood flow in patients undergoing creation of a new AVF in the distal forearm preoperatively and at 1 day and 1 week postoperatively. We measured the flow volume (FV) and resistive index (RI) of the brachial artery, and the internal diameter of the brachial artery and outflow vein. The primary outcome was the primary patency of the AVF without percutaneous angioplasty (PTA) or surgical revision 40 days after access creation. We recruited 35 patients with newly created AVFs (men, 21; mean age, 73 years). Within one day of operation, the overall FV increased from 62 to 352 mL/min (p<0.0001) while the overall RI decreased from 1.0 to 0.63 (p<0.001). Five patients required PTA or surgical revision (intervention group [IG]), whereas 30 patients did not (non-intervention group [NIG]). The FV increased while the RI decreased from day 1 to week 1 in the NIG, but not in the IG (p<0.0001). The diameter of the brachial artery and outflow vein significantly increased in the NIG at 1 week. The FV of 235 mL/min and RI of 0.63 at 1 day were the thresholds for predicting early fistula failure. Access FV and RI at 1 day after AVF creation can predict primary patency and help plan intervention.

  16. Modeling the carbon cost of plant nitrogen acquisition: Mycorrhizal trade-offs and multipath resistance uptake improve predictions of retranslocation

    NASA Astrophysics Data System (ADS)

    Brzostek, Edward R.; Fisher, Joshua B.; Phillips, Richard P.

    2014-08-01

    Accurate projections of the future land carbon (C) sink by terrestrial biosphere models depend on how nutrient constraints on net primary production are represented. While nutrient limitation is nearly universal, current models do not have a C cost for plant nutrient acquisition. Also missing are symbiotic mycorrhizal fungi, which can consume up to 20% of net primary production and supply up to 50% of a plant's nitrogen (N) uptake. Here we integrate simultaneous uptake and mycorrhizae into a cutting-edge plant N model—Fixation and Uptake of Nitrogen (FUN)—that can be coupled into terrestrial biosphere models. The C cost of N acquisition varies as a function of mycorrhizal type, with plants that support arbuscular mycorrhizae benefiting when N is relatively abundant and plants that support ectomycorrhizae benefiting when N is strongly limiting. Across six temperate forested sites (representing arbuscular mycorrhizal- and ectomycorrhizal-dominated stands and 176 site years), including multipath resistance improved the partitioning of N uptake between aboveground and belowground sources. Integrating mycorrhizae led to further improvements in predictions of N uptake from soil (R2 = 0.69 increased to R2 = 0.96) and from senescing leaves (R2 = 0.29 increased to R2 = 0.73) relative to the original model. On average, 5% and 9% of net primary production in arbuscular mycorrhizal- and ectomycorrhizal-dominated forests, respectively, was needed to support mycorrhizal-mediated acquisition of N. To the extent that resource constraints to net primary production are governed by similar trade-offs across all terrestrial ecosystems, integrating these improvements to FUN into terrestrial biosphere models should enhance predictions of the future land C sink.

  17. Modeling Dynamics of Cell-to-Cell Variability in TRAIL-Induced Apoptosis Explains Fractional Killing and Predicts Reversible Resistance

    PubMed Central

    Bertaux, François; Stoma, Szymon; Drasdo, Dirk; Batt, Gregory

    2014-01-01

    Isogenic cells sensing identical external signals can take markedly different decisions. Such decisions often correlate with pre-existing cell-to-cell differences in protein levels. When not neglected in signal transduction models, these differences are accounted for in a static manner, by assuming randomly distributed initial protein levels. However, this approach ignores the a priori non-trivial interplay between signal transduction and the source of this cell-to-cell variability: temporal fluctuations of protein levels in individual cells, driven by noisy synthesis and degradation. Thus, modeling protein fluctuations, rather than their consequences on the initial population heterogeneity, would set the quantitative analysis of signal transduction on firmer grounds. Adopting this dynamical view on cell-to-cell differences amounts to recast extrinsic variability into intrinsic noise. Here, we propose a generic approach to merge, in a systematic and principled manner, signal transduction models with stochastic protein turnover models. When applied to an established kinetic model of TRAIL-induced apoptosis, our approach markedly increased model prediction capabilities. One obtains a mechanistic explanation of yet-unexplained observations on fractional killing and non-trivial robust predictions of the temporal evolution of cell resistance to TRAIL in HeLa cells. Our results provide an alternative explanation to survival via induction of survival pathways since no TRAIL-induced regulations are needed and suggest that short-lived anti-apoptotic protein Mcl1 exhibit large and rare fluctuations. More generally, our results highlight the importance of accounting for stochastic protein turnover to quantitatively understand signal transduction over extended durations, and imply that fluctuations of short-lived proteins deserve particular attention. PMID:25340343

  18. Significant negative differential resistance predicted in scanning tunneling spectroscopy for a C60 monolayer on a metal surface

    NASA Astrophysics Data System (ADS)

    Shi, X. Q.; Pai, Woei Wu; Xiao, X. D.; Cerdá, J. I.; Zhang, R. Q.; Minot, C.; van Hove, M. A.

    2009-08-01

    We theoretically predict the occurrence of negative differential resistance (NDR) in scanning tunneling spectroscopy for a pure C60 monolayer deposited on a metal surface using metal tips, namely, on a Cu(111) surface and using various W tips. It is proposed that the likely reason why NDR has not been observed under such conditions is that NDR can be reduced if an oxidized or Cu-terminated tip is used. A detailed decomposition of the total tunneling current into its contributions from individual molecular orbitals reveals that only some of the orbitals on the tip and on the C60 can be “matched up” to give a contribution to the current and that the NDR is a consequence of the mismatch between these specific orbitals within particular ranges of bias voltage. Moreover, the NDR characteristics, including the peak positions and the peak-to-valley ratios, are found to depend on the tip material, tip geometry, and tip-to-molecule position.

  19. In non-obese girls waist circumference predicts insulin resistance is comparably to MRI fat measures and superior to BMI

    PubMed Central

    Wolfgram, Peter M.; Connor, Ellen L.; Rehm, Jennifer L.; Eickhoff, Jens C.; Zha, Wei; Reeder, Scott B.; Allen, David B.

    2015-01-01

    Objective To investigate the degree to which waist circumference (WC), BMI, and MRI measured abdominal fat deposition predict insulin resistance (IR) in non-obese girls of diverse racial and ethnic backgrounds. Methods Fifty-seven non-obese girls (12 African-American, 16 Hispanic White and 29 non-Hispanic White girls), aged 11–14 years old were assessed for WC, MRI hepatic proton density fat fraction, visceral and subcutaneous adipose tissue volume, BMI Z-score, fasting insulin, HOMA-IR, adiponectin, leptin, sex hormone binding globulin, HDL cholesterol, and triglycerides. Results Univariate and multivariate analyses adjusted for race and ethnicity indicated that only WC and visceral adipose tissue volume were independent predictors of fasting insulin and HOMA-IR, while dependent predictors were hepatic proton density fat fraction, BMI Z-score, and subcutaneous adipose tissue volume. Hispanic White girls showed significantly higher mean fasting insulin, HOMA-IR, and lower sex hormone binding globulin than non-Hispanic White girls (p-value <0.01). Conclusions In non-obese girls of diverse racial and ethnic backgrounds, WC, particularly when adjusted for race or ethnicity, is an independent predictor of IR comparable to MRI-derived measurements of fat and superior to BMI Z-score. PMID:26352642

  20. Increased Pretransplant Frequency of CD28(+) CD4(+) TEM Predicts Belatacept-Resistant Rejection in Human Renal Transplant Recipients.

    PubMed

    Cortes-Cerisuelo, M; Laurie, S J; Mathews, D V; Winterberg, P D; Larsen, C P; Adams, A B; Ford, M L

    2017-09-01

    While most human T cells express the CD28 costimulatory molecule constitutively, it is well known that age, inflammation, and viral infection can drive the generation of CD28(null) T cells. In vitro studies have demonstrated that CD28(null) cell effector function is not impacted by the presence of the CD28 costimulation blocker belatacept. As such, a prevailing hypothesis suggests that CD28(null) cells may precipitate costimulation blockade-resistant rejection. However, CD28(+) cells possess more proliferative and multifunctional capacity, factors that may increase their ability to successfully mediate rejection. Here, we performed a retrospective immunophenotypic analysis of adult renal transplant recipients who experienced acute rejection on belatacept treatment as compared to those who did not. Intriguingly, our findings suggest that patients possessing higher frequency of CD28(+) CD4(+) TEM prior to transplant were more likely to experience acute rejection following treatment with a belatacept-based immunosuppressive regimen. Mechanistically, CD28(+) CD4(+) TEM contained significantly more IL-2 producers. In contrast, CD28(null) CD4(+) TEM isolated from stable belatacept-treated patients exhibited higher expression of the 2B4 coinhibitory molecule as compared to those isolated from patients who rejected. These data raise the possibility that pretransplant frequencies of CD28(+) CD4(+) TEM could be used as a biomarker to predict risk of rejection following treatment with belatacept. © 2017 The American Society of Transplantation and the American Society of Transplant Surgeons.

  1. Predictive value of microparticle-associated tissue factor activity for permeability glycoprotein-mediated multidrug resistance in cancer

    PubMed Central

    Angelini, Antonio; Miscia, Sebastiano; Centurione, Maria Antonietta; Di Pietro, Roberta; Centurione, Lucia

    2016-01-01

    Multidrug resistance (MDR) protein 1, which is also known as permeability glycoprotein (Pgp), and tissue factor (TF) are recurrently overexpressed on the surface of cancer cells, likely in response to stimuli such as chemotherapy. Microparticles (MPs) released from cancer cells into the bloodstream express tumour markers on their surface that may be useful as predictive biomarkers for evaluating disease progression. The present study measured the level of TF/factor VII (FVII)-dependent coagulation of MPs isolated from the plasma of cancer patients with various tumours, who were undergoing chemotherapy. Furthermore, Pgp expression on the surface of MPs was evaluated by immunohistochemistry. A total of 50 cancer patients, as well as 10 healthy volunteers, were enrolled in the present study. MP-associated TF/FVII-dependent coagulation pathways were evaluated as the effect of an anti-FVII antibody on the time to thrombin generation, as compared with controls treated with saline. The significantly lengthened times of coagulation [obtained in 20/50 samples (36.5 ± 16%) after treatment with anti-FVIIa when compared with controls] suggest the presence of TF activity is associated with circulating MPs. Furthermore, the 20 MP/TF-positive samples were associated with Pgp overexpression on their surface. Conversely, in the remaining samples (n=30), treatment with the anti-FVIIa antibody did not significantly lengthen the time to clotting (<10%), and Pgp overexpression was not detected. In addition, in the control samples from healthy individuals, Pgp expression at the plasma membrane and clotting in the presence of the anti-FVII antibody were not observed, indicating the absence of MPs. The present study demonstrated that MPs in the blood of cancer patients promoted fibrin generation via TF/FVII-dependent pathways, thus suggesting that the evaluation of MP-TF activity may have a predictive value for Pgp-mediated MDR in various cancer types. Although further studies are

  2. Hairpin RNA-mediated silencing of Plum pox virus P1 and HC-Pro genes for efficient and predictable resistance to the virus.

    PubMed

    Di Nicola-Negri, Elisa; Brunetti, Angela; Tavazza, Mario; Ilardi, Vincenza

    2005-12-01

    We report the application of the hairpin-mediated RNA silencing technology for obtaining resistance to Plum pox virus (PPV) infection in Nicotiana benthamiana plants. Four sequences, covering the P1 and silencing suppressor HC-Pro genes of an Italian PPV M isolate, were introduced into N. benthamiana plants as two inverted repeats separated by an intron sequence under the transcriptional control of the Cauliflower Mosaic Virus 35S promoter. In a leaf disk infection assay, 38 out of 40 T0 transgenic plants were resistant to PPV infection. Eight lines, 2 for each construct, randomly selected among the 38 resistant plants were further analysed. Two hundred forty eight out of 253 T1 transgenic plants were resistant to local and systemic PPV infection. All transgenic single locus lines were completely resistant. These data indicate that the RNA silencing of PPV P1/HCPro sequences results in an efficient and predictable PPV resistance, which may be utilized in obtaining stone fruit plants resistant to the devastating Sharka disease.

  3. Neck circumference as a new anthropometric indicator for prediction of insulin resistance and components of metabolic syndrome in adolescents: Brazilian Metabolic Syndrome Study

    PubMed Central

    da Silva, Cleliani de Cassia; Zambon, Mariana Porto; Vasques, Ana Carolina J.; Rodrigues, Ana Maria de B.; Camilo, Daniella Fernandes; Antonio, Maria Ângela R. de G. M.; Cassani, Roberta Soares L.; Geloneze, Bruno

    2014-01-01

    OBJECTIVE: To evaluate the correlation between neck circumference and insulin resistance and components of metabolic syndrome in adolescents with different adiposity levels and pubertal stages, as well as to determine the usefulness of neck circumference to predict insulin resistance in adolescents. METHODS: Cross-sectional study with 388 adolescents of both genders from ten to 19 years old. The adolescents underwent anthropometric and body composition assessment, including neck and waist circumferences, and biochemical evaluation. The pubertal stage was obtained by self-assessment, and the blood pressure, by auscultation. Insulin resistance was evaluated by the Homeostasis Model Assessment-Insulin Resistance. The correlation between two variables was evaluated by partial correlation coefficient adjusted for the percentage of body fat and pubertal stage. The performance of neck circumference to identify insulin resistance was tested by Receiver Operating Characteristic Curve. RESULTS: After the adjustment for percentage body fat and pubertal stage, neck circumference correlated with waist circumference, blood pressure, triglycerides and markers of insulin resistance in both genders. CONCLUSIONS: The results showed that the neck circumference is a useful tool for the detection of insulin resistance and changes in the indicators of metabolic syndrome in adolescents. The easiness of application and low cost of this measure may allow its use in Public Health services. PMID:25119754

  4. Potential and limits to unravel the genetic architecture and predict the variation of Fusarium head blight resistance in European winter wheat (Triticum aestivum L.)

    PubMed Central

    Jiang, Y; Zhao, Y; Rodemann, B; Plieske, J; Kollers, S; Korzun, V; Ebmeyer, E; Argillier, O; Hinze, M; Ling, J; Röder, M S; Ganal, M W; Mette, M F; Reif, J C

    2015-01-01

    Genome-wide mapping approaches in diverse populations are powerful tools to unravel the genetic architecture of complex traits. The main goals of our study were to investigate the potential and limits to unravel the genetic architecture and to identify the factors determining the accuracy of prediction of the genotypic variation of Fusarium head blight (FHB) resistance in wheat (Triticum aestivum L.) based on data collected with a diverse panel of 372 European varieties. The wheat lines were phenotyped in multi-location field trials for FHB resistance and genotyped with 782 simple sequence repeat (SSR) markers, and 9k and 90k single-nucleotide polymorphism (SNP) arrays. We applied genome-wide association mapping in combination with fivefold cross-validations and observed surprisingly high accuracies of prediction for marker-assisted selection based on the detected quantitative trait loci (QTLs). Using a random sample of markers not selected for marker–trait associations revealed only a slight decrease in prediction accuracy compared with marker-based selection exploiting the QTL information. The same picture was confirmed in a simulation study, suggesting that relatedness is a main driver of the accuracy of prediction in marker-assisted selection of FHB resistance. When the accuracy of prediction of three genomic selection models was contrasted for the three marker data sets, no significant differences in accuracies among marker platforms and genomic selection models were observed. Marker density impacted the accuracy of prediction only marginally. Consequently, genomic selection of FHB resistance can be implemented most cost-efficiently based on low- to medium-density SNP arrays. PMID:25388142

  5. Prediction of type 2 diabetes using simple measures of insulin resistance: combined results from the San Antonio Heart Study, the Mexico City Diabetes Study, and the Insulin Resistance Atherosclerosis Study.

    PubMed

    Hanley, Anthony J G; Williams, Ken; Gonzalez, Clicerio; D'Agostino, Ralph B; Wagenknecht, Lynne E; Stern, Michael P; Haffner, Steven M

    2003-02-01

    To determine and formally compare the ability of simple indexes of insulin resistance (IR) to predict type 2 diabetes, we used combined prospective data from the San Antonio Heart Study, the Mexico City Diabetes Study, and the Insulin Resistance Atherosclerosis Study, which include well-characterized cohorts of non-Hispanic white, African-American, Hispanic American, and Mexican subjects with 5-8 years of follow-up. Poisson regression was used to assess the ability of each candidate index to predict incident diabetes at the follow-up examination (343 of 3,574 subjects developed diabetes). The areas under the receiver operator characteristic (AROC) curves for each index were calculated and statistically compared. In pooled analysis, Gutt et al.'s insulin sensitivity index at 0 and 120 min (ISI(0,120)) displayed the largest AROC (78.5%). This index was significantly more predictive (P < 0.0001) than a large group of indexes (including those by Belfiore, Avignon, Katz, and Stumvoll) that had AROC curves between 66 and 74%. These findings were essentially similar both after adjustment for covariates and when analyses were conducted separately by glucose tolerance status and ethnicity/study subgroups. In conclusion, we found substantial differences between published IR indexes in the prediction of diabetes, with ISI(0,120) consistently showing the strongest prediction. This index may reflect other aspects of diabetes pathogenesis in addition to IR, which might explain its strong predictive abilities despite its moderate correlation with direct measures of IR.

  6. Noninvasive Detection of AR-FL/AR V7 as a Predictive Biomarker for Therapeutic Resistance in Men with Metastatic Castration-Resistant Prostate Cancer

    DTIC Science & Technology

    2016-10-01

    Using a laboratory- developed, RNA -based assay modified from a commercially available circulating tumor cell (CTC) detection platform, we have developed...for therapeutic resistance in men with metastatic castration-resistant prostate cancer. Using a laboratory-developed, RNA -based assay modified from...between CTC AR expression with contemporaneously acquired fresh CRPC biopsy expression, and with expression detected in cell-free exosome RNA . Subtask 1

  7. Metastasis initiating cells in primary prostate cancer tissues from transurethral resection of the prostate (TURP) predicts castration-resistant progression and survival of prostate cancer patients.

    PubMed

    Li, Qinlong; Li, Quanlin; Nuccio, Jill; Liu, Chunyan; Duan, Peng; Wang, Ruoxiang; Jones, Lawrence W; Chung, Leland W K; Zhau, Haiyen E

    2015-09-01

    We previously reported that the activation of RANK and c-Met signaling components in both experimental mouse models and human prostate cancer (PC) specimens predicts bone metastatic potential and PC patient survival. This study addresses whether a population of metastasis-initiating cells (MICs) known to express a stronger RANKL, phosphorylated c-Met (p-c-Met), and neuropilin-1 (NRP1) signaling network than bystander or dormant cells (BDCs) can be detected in PC tissues from patients subjected to transurethral resection of the prostate (TURP) for urinary obstruction prior to the diagnosis of PC with or without prior hormonal manipulation, and whether the relative abundance of MICs over BDCs could predict castration-resistant progression and PC patient survival. We employed a multiplexed quantum-dot labeling (mQDL) protocol to detect and quantify MICs and BDCs at the single cell level in TURP tissues obtained from 44 PC patients with documented overall survival and castration resistance status. PC tissues with a higher number of MICs and an activated RANK signaling network, including increased expression of RANKL, p-c-Met, and NRP1 compared to BDCs, were found to correlate with the development of castration resistance and overall survival. The assessment of PC cells with MIC and BDC phenotypes in primary PC tissues from hormone-naïve patients can predict the progression to castration resistance and the overall survival of PC patients. © 2015 Wiley Periodicals, Inc.

  8. Metastasis Initiating Cells in Primary Prostate Cancer Tissues From Transurethral Resection of the Prostate (TURP) Predicts Castration-Resistant Progression and Survival of Prostate Cancer Patients

    PubMed Central

    Li, Qinlong; Li, Quanlin; Nuccio, Jill; Liu, Chunyan; Duan, Peng; Wang, Ruoxiang; Jones, Lawrence W.; Chung, Leland W. K.; Zhau, Haiyen E.

    2016-01-01

    BACKGROUND We previouslyreported that the activation of RANK and c-Met signaling components in both experimental mouse models and human prostate cancer (PC) specimens predicts bone metastatic potential and PC patient survival. This study addresses whether a population of metastasis-initiating cells (MICs) known to express a stronger RANKL, phosphorylated c-Met (p-c-Met), and neuropilin-1 (NRP1) signaling network than bystander or dormant cells (BDCs) can be detected in PC tissues from patients subjected to transurethral resection of the prostate (TURP) for urinary obstruction prior to the diagnosis of PC with or without prior hormonal manipulation, and whether the relative abundance of MICs over BDCs could predict castration-resistant progression and PC patient survival. METHODS We employed a multiplexed quantum-dot labeling (mQDL) protocol to detect and quantify MICs and BDCs at the single cell level in TURP tissues obtained from 44 PC patients with documented overall survival and castration resistance status. RESULTS PC tissues with a higher number of MICs and an activated RANK signaling network, including increased expression of RANKL, p-c-Met, and NRP1 compared to BDCs, were found to correlate with the development of castration resistance and overall survival. CONCLUSIONS The assessment of PC cells with MIC and BDC phenotypes in primary PC tissues from hormone-naïve patients can predict the progression to castration resistance and the overall survival of PC patients. PMID:25990623

  9. Partial least squares regression and fourier transform infrared (FTIR) microspectroscopy for prediction of resistance in hepatocellular carcinoma HepG2 cells.

    PubMed

    Junhom, Cholpajsorn; Weerapreeyakul, Natthida; Tanthanuch, Waraporn; Thumanu, Kanjana

    2017-02-01

    We evaluated the feasibility of FTIR microspectroscopy combined with partial least squares regression (PLS-R) for determination of resistance in HepG2 cells. Cell viability testing was performed using neutral red assay for the concentration of cisplatin resulting in 50% antiproliferation (IC50). The resistance index (RI) is the ratio of the IC50 in resistant HepG2 cells vs. parental HepG2 cells. Principal component and unsupervised hierarchical cluster analyses were applied and a differentiation of samples of cells (parental, 1.8RI, 2.3RI, 3.0RI, and 3.5RI) was demonstrated (3000-2800cm(-1) in the lipid and 1700-1500cm(-1) in the protein regions. The FTIR spectra were preprocessed with several treatments to test the algorithm. PLS-R models were built using the 1170 spectra of the HepG2 cells. Cross-validation was used to evaluate prediction of the RI value using this model. PLS-R models-preprocessed with the second derivative FTIR spectra-yielded the best model (R(2)=0.99, RMSEE=0.095 and RPD=7.98). Most RI values were predicted with high accuracy (91-100%) such that the linear correlation between the actual and predicted RI values was nearly perfect (slope~1). FTIR microspectroscopy combined with chemometric analysis using PLS-R offers quick, accurate, and reliable quantitative analysis of HepG2 cell resistance.

  10. Reprogramming of the ERRα and ERα target gene landscape triggers tamoxifen resistance in breast cancer.

    PubMed

    Thewes, Verena; Simon, Ronald; Schroeter, Petra; Schlotter, Magdalena; Anzeneder, Tobias; Büttner, Reinhard; Benes, Vladimir; Sauter, Guido; Burwinkel, Barbara; Nicholson, Robert I; Sinn, Hans-Peter; Schneeweiss, Andreas; Deuschle, Ulrich; Zapatka, Marc; Heck, Stefanie; Lichter, Peter

    2015-02-15

    Endocrine treatment regimens for breast cancer that target the estrogen receptor-α (ERα) are effective, but acquired resistance remains a limiting drawback. One mechanism of acquired resistance that has been hypothesized is functional substitution of the orphan receptor estrogen-related receptor-α (ERRα) for ERα. To examine this hypothesis, we analyzed ERRα and ERα in recurrent tamoxifen-resistant breast tumors and conducted a genome-wide target gene profiling analysis of MCF-7 breast cancer cell populations that were sensitive or resistant to tamoxifen treatment. This analysis uncovered a global redirection in the target genes controlled by ERα, ERRα, and their coactivator AIB1, defining a novel set of target genes in tamoxifen-resistant cells. Beyond differences in the ERα and ERRα target gene repertoires, both factors were engaged in similar pathobiologic processes relevant to acquired resistance. Functional analyses confirmed a requirement for ERRα in tamoxifen- and fulvestrant-resistant MCF-7 cells, with pharmacologic inhibition of ERRα sufficient to partly restore sensitivity to antiestrogens. In clinical specimens (n = 1041), increased expression of ERRα was associated with enhanced proliferation and aggressive disease parameters, including increased levels of p53 in ERα-positive cases. In addition, increased ERRα expression was linked to reduced overall survival in independent tamoxifen-treated patient cohorts. Taken together, our results suggest that ERα and ERRα cooperate to promote endocrine resistance, and they provide a rationale for the exploration of ERRα as a candidate drug target to treat endocrine-resistant breast cancer. ©2015 American Association for Cancer Research.

  11. Impact of the Triglyceride/High-Density Lipoprotein Cholesterol Ratio and the Hypertriglyceremic-Waist Phenotype to Predict the Metabolic Syndrome and Insulin Resistance.

    PubMed

    von Bibra, Helene; Saha, Sarama; Hapfelmeier, Alexander; Müller, Gabriele; Schwarz, Peter E H

    2017-07-01

    Insulin resistance is the underlying mechanism for the metabolic syndrome and associated dyslipidaemia that theoretically implies a practical tool for identifying individuals at risk for cardiovascular disease and type-2-diabetes. Another screening tool is the hypertriglyceremic-waist phenotype (HTW). There is important impact of the ethnic background but a lack of studied European populations for the association of the triglyceride/high-density lipoprotein cholesterol (HDL-C) ratio and insulin resistance. This observational, retrospective study evaluated lipid ratios and the HTW for predicting the metabolic syndrome/insulin resistance in 1932 non-diabetic individuals from Germany in the fasting state and during a glucose tolerance test. The relations of triglyceride/HDL-C, total-cholesterol/HDL-C, and low-density lipoprotein cholesterol/HDL-C with 5 surrogate estimates of insulin resistance/sensitivity and metabolic syndrome were analysed by linear regression analysis and receiver operating characteristics (ROC) in participants with normal (n=1 333) or impaired fasting glucose (n=599), also for the impact of gender. Within the lipid ratios, triglyceride/HDL-C had the strongest associations with insulin resistance/sensitivity markers. In the prediction of metabolic syndrome, diagnostic accuracy was good for triglyceride/HDL-C (area under the ROC curve 0.817) with optimal cut-off points (in mg/dl units) of 2.8 for men (80% sensitivity, 71% specificity) and 1.9 for women (80% sensitivity, 75% specificity) and fair for HTW and HOMA-IR (area under the curve 0.773 and 0.761). These data suggest the triglyceride/HDL-C ratio as a physiologically relevant and practical index for predicting the concomitant presence of metabolic syndrome, insulin resistance and dyslipidaemia for therapeutic and preventive care in apparently healthy European populations. © Georg Thieme Verlag KG Stuttgart · New York.

  12. Activities of multiple cancer-related pathways are associated with BRAF mutation and predict the resistance to BRAF/MEK inhibitors in melanoma cells

    PubMed Central

    Liu, Dingxie; Liu, Xuan; Xing, Mingzhao

    2014-01-01

    Drug resistance is a major obstacle in the targeted therapy of melanoma using BRAF/MEK inhibitors. This study was to identify BRAF V600E-associated oncogenic pathways that predict resistance of BRAF-mutated melanoma to BRAF/MEK inhibitors. We took in silico approaches to analyze the activities of 24 cancer-related pathways in melanoma cells and identify those whose activation was associated with BRAF V600E and used the support vector machine (SVM) algorithm to predict the resistance of BRAF-mutated melanoma cells to BRAF/MEK inhibitors. We then experimentally confirmed the in silico findings. In a microarray gene expression dataset of 63 melanoma cell lines, we found that activation of multiple oncogenic pathways preferentially occurred in BRAF-mutated melanoma cells. This finding was reproduced in 5 additional independent melanoma datasets. Further analysis of 46 melanoma cell lines that harbored BRAF mutation showed that 7 pathways, including TNFα, EGFR, IFNα, hypoxia, IFNγ, STAT3, and MYC, were significantly differently expressed in AZD6244-resistant compared with responsive melanoma cells. A SVM classifier built on this 7-pathway activation pattern correctly predicted the response of 10 BRAF-mutated melanoma cell lines to the MEK inhibitor AZD6244 in our experiments. We experimentally showed that TNFα, EGFR, IFNα, and IFNγ pathway activities were also upregulated in melanoma cell A375 compared with its sub-line DRO, while DRO was much more sensitive to AZD6244 than A375. In conclusion, we have identified specific oncogenic pathways preferentially activated in BRAF-mutated melanoma cells and a pathway pattern that predicts resistance of BRAF-mutated melanoma to BRAF/MEK inhibitors, providing novel clinical implications for melanoma therapy. PMID:24200969

  13. Early prediction of treatment resistance in low-risk gestational trophoblastic neoplasia using population kinetic modelling of hCG measurements

    PubMed Central

    You, B; Harvey, R; Henin, E; Mitchell, H; Golfier, F; Savage, P M; Tod, M; Wilbaux, M; Freyer, G; Seckl, M J

    2013-01-01

    Background: In low-risk gestational trophoblastic neoplasia (GTN) patients, a predictive marker for early identification of methotrexate (MTX) resistance would be useful. We previously demonstrated that kinetic modelling of human chorionic gonadotrophin (hCG) measurements could provide such a marker. Here we validate this approach in a large independent patient cohort. Methods: Serum hCG measurements of 800 low-risk GTN patients treated with MTX were analysed. The cohort was divided into Model and Test data sets. hCG kinetics were described from initial treatment day to day 50 using: ‘(hCG(time))=hCG0*exp(–k*time)+hCGres', where hCGres is the modelled residual production, hCG0 is the baseline hCG level, and k is the rate constant. HCGres-predictive value was investigated against previously reported predictors of MTX resistance. Results: Declining hCG measurements were well fitted by the model. The best discriminator of MTX resistance in the Model data set was hCGres, categorised by an optimal cut-off value of >20.44 IU l−1: receiver-operating characteristic (ROC) area under the curve (AUC)=0.87; Se=0.91; Sp=0.83. The predictive value of hCGres was reproducible using the Test data set: ROC AUC=0.87; Se=0.88; Sp=0.86. Multivariate analyses revealed hCGres as a better predictor of MTX resistance (HR=1.01, P<0.0001) and MTX failure-free survival (HR=13.25, P<0.0001) than other reported predictive factors. Conclusion: hCGres, a modelled kinetic parameter calculated after fully dosed three MTX cycles, has a reproducible value for identifying patients with MTX resistance. PMID:23591194

  14. The effectiveness of prefrontal theta cordance and early reduction of depressive symptoms in the prediction of antidepressant treatment outcome in patients with resistant depression: analysis of naturalistic data.

    PubMed

    Bares, Martin; Novak, Tomas; Kopecek, Miloslav; Brunovsky, Martin; Stopkova, Pavla; Höschl, Cyril

    2015-02-01

    Current studies suggest that an early improvement of depressive symptoms and the reduction of prefrontal theta cordance value predict the subsequent response to antidepressants. The aim of our study was (1) to compare the predictive abilities of early clinical improvement defined as ≥ 20 % reduction in Montgomery and Åsberg Depression Rating Scale (MADRS) total score at week 1 and 2, and the decrease of prefrontal theta cordance at week 1 in resistant depressive patients and (2) to assess whether the combination of individual predictors yields more robust predictive power than either predictor alone. Eighty-seven subjects were treated (≥ 4 weeks) with various antidepressants chosen according to the judgment of attending psychiatrists. Areas under curve (AUC) were calculated to compare predictive effect of defined single predictors (≥ 20 % reduction in MADRS total score at week 1 and 2, and the decrease of cordance at week 1) and combined prediction models. AUCs of all three predictors were not statistically different (pair-wise comparison). The model combining all predictors yielded an AUC value 0.91 that was significantly higher than AUCs of each individual predictor. The results indicate that the combined predictor model may be a useful and clinically meaningful tool for the prediction of antidepressant response in patients with resistant depression.

  15. [Predictive factor analysis of time to progression of castration-resistant prostate cancer after androgen deprivation therapy].

    PubMed

    Ji, G J; Huang, C; Song, G; Li, X S; Song, Y; Zhou, L Q

    2017-08-18

    To explore risk factors including prostate-specific antigen (PSA) kinetics for the prediction of castration-resistant prostate cancer (CRPC), and to build a practical model for predicting the progression to CRPC after androgen deprivation therapy (ADT) so as to facilitate clinicians in decision-making for prostate cancer patients receiving ADT. A total of 185 patients with prostate cancer who had received ADT as the primary therapy in Department of Urology of Peking University First Hospital from 2003 to 2014 were enrolled retrospectively. All the patients were diagnosed with prostate cancer via prostate biopsy and followed up every four weeks from the initiation of ADT. All the patients received ADT with luteinizing hormone-releasing hormone agonists (LHRH-A) or surgical castration accompanied with an antiandrogen (bicalutamide or flutamide, combined androgen blockade). The clinical information of the patients were collected including age, clinical TNM stage, Gleason score (GS), risk groups of prostate cancer, PSA at the initiation of ADT, PSA nadir after ADT, PSA decline velocity, and the time to PSA nadir. The end point of this study was the diagnosis of CRPC, which was based on the European Association of Urology (EAU) Guideline 2016. Cox proportional hazards regression models were established to analyze and estimate their effects on the time of progression to CRPC. In this study, 185 patients with prostate cancer who had received ADT as the primary therapy were included. The mean age was (71.02±8.67) years. The median time to progression to CRPC in this cohort was 38 months (ranging from 4 to 158 months). On univariate analysis, we found clinical T stage, N stage, the metastasis state before ADT, risk groups of prostate cancer, PSA decline velocity, and PSA nadir were all related to the time to CRPC progression, P<0.01 for all the above variables. And on multivariate analysis, the presence of distant metastasis before ADT (HR=6.030, 95% CI: 3.229-11.263, P=0

  16. Race does not predict the development of metastases in men with nonmetastatic castration-resistant prostate cancer.

    PubMed

    Whitney, Colette A; Howard, Lauren E; Amling, Christopher L; Aronson, William J; Cooperberg, Matthew R; Kane, Christopher J; Terris, Martha K; Freedland, Stephen J

    2016-12-15

    Although race is associated with prostate cancer progression in early stage disease, once men have advanced disease, it is unclear whether race continues to predict a poor outcome. The authors hypothesized that, in an equal-access setting among patients with castration-resistant prostate cancer (CRPC) and no known metastases (M0/Mx), black men would receive imaging tests at similar rates as nonblack men (ie, there would be an equal opportunity to detect metastases) but would have a higher risk of metastatic disease. In total, 837 men who were diagnosed with M0/Mx CRPC during 2000 through 2014 from 5 Veterans Affairs hospitals in the SEARCH (Shared Equal Access Regional Cancer Hospital) database were analyzed. Data on all imaging tests after CRPC diagnosis were collected, including date, type, and outcome. Multivariable Cox models were used to test associations between race and the time to first metastasis, first bone metastasis, first bone scan, second bone scan among men who had a negative first bone scan, and overall survival. Black men (n = 306) were equally as likely as nonblack men (n = 531) to receive a first and second bone scan after a diagnosis of CRPC. There were no significant differences in the risk of developing any metastases, bone metastases, time to bone scans, or overall survival between black men and nonblack men (all P > .2). The lack of racial differences in the development of metastases and scanning practices observed in this study suggests that, once men have a diagnosis of M0/Mx CRPC, race may not be a prognostic factor. Efforts to understand prostate cancer racial disparities may derive greater benefit by focusing on the risk of developing prostate cancer and on the outcomes of men who have early stage disease. Cancer 2016;122:3848-3855. © 2016 American Cancer Society. © 2016 American Cancer Society.

  17. Two-dimensional assessment of the nasal valve area cannot predict minimum cross-sectional area or airflow resistance.

    PubMed

    Bhatia, Daman D S; Palesy, Tom; Ramli, Raziqah; Barham, Henry P; Christensen, Jenna M; Gunaratne, Dakshika A; Marcells, George N; Harvey, Richard J

    2016-05-01

    Clinicians who manage nasal obstruction often comment on the shape and size of the nasal valve (NV) area. However, correlation of the symptoms of obstruction, nasal airflow dynamics, and the endoscopic appearance of the anatomic cross-sectional area of the NV is poorly understood. Endoscopic imaging and calculation of the NV area is investigated as a tool for either clinical or research use. To describe and evaluate a two-dimensional measurement of the minimum cross-sectional area (MCA) of the NV by using endoscopic imaging. A cross-sectional study of patients with symptoms of nasal obstruction who were undergoing nasal assessment was performed. The NV was measured with digital imaging taken from the endoscopy. Adobe Photoshop was used to calculate the digital MCA of the NV based on pixel count and a reference marker placed in the image field. Airway parameters were assessed by using a nasal obstruction visual analog scale, nasal airway resistance via rhinomanometry, and acoustic rhinometry derived MCA (acoustic MCA). Correlation of the digital MCA and airway parameters was made and interobserver correlation of the MCA measures was calculated. Thirty-three nasal airways were assessed: mean (standard deviation) digital MCA (0.28 ± 0.13 cm(2)) and mean (standard deviation) acoustic MCA (0.51 ± 0.15 cm(2)). Correlation of the digital MCA with visual analog scale was poor (Pearson r = 0.10, p = 0.56). Similar finding between digital and acoustic MCA was poor (Pearson r = 0.50, p = 0.56, respectively) despite a moderately strong interobserver correlation for the digital MCA (Pearson r = 0.79, p < 0.001). Qualitative endoscopic assessment of the NV may help clinicians predict NV dysfunction but simple two-dimensional measures seemed to be of limited value in accurately assessing the three-dimensional NV quantitatively.

  18. MET Gene Amplification and MET Receptor Activation Are Not Sufficient to Predict Efficacy of Combined MET and EGFR Inhibitors in EGFR TKI-Resistant NSCLC Cells

    PubMed Central

    Presutti, Dario; Santini, Simonetta; Cardinali, Beatrice; Papoff, Giuliana; Lalli, Cristiana; Samperna, Simone; Fustaino, Valentina; Giannini, Giuseppe; Ruberti, Giovina

    2015-01-01

    are not sufficient to predict a positive response of NSCLC cells to a cocktail of MET and EGFR inhibitors and highlights the importance of identifying more reliable biomarkers to predict the efficacy of treatments in NSCLC patients resistant to EGFR TKI. PMID:26580964

  19. Emergence and maintenance of resistance to fluoroquinolones and coumarins in Staphylococcus aureus: predictions from in vitro studies.

    PubMed

    Vickers, A A; O'Neill, A J; Chopra, I

    2007-08-01

    Fluoroquinolones and coumarins interfere with the activity of bacterial type II topoisomerase enzymes. We examined the development of resistance to these agents in Staphylococcus aureus and determined the effect of simultaneous topoisomerase IV and DNA gyrase mutations on the biological fitness of the organism. This work aimed to gain insight into how such mutants might arise and survive in the clinical environment. Spontaneous mutants resistant to fluoroquinolones and coumarins were selected in S. aureus. Resistance mutations were identified by DNA sequencing of PCR amplicons corresponding to the genes encoding topoisomerase IV and DNA gyrase. In vitro fitness of resistant mutants was compared with the antibiotic-susceptible progenitor strain using pair-wise competition assays. Mutants simultaneously resistant to both a fluoroquinolone and either of the coumarins, novobiocin or coumermycin A1, could not be recovered following a single-step selection. However, mutants concurrently resistant to both classes of antimicrobial could be generated by step-wise selections. These mutants demonstrated reductions in competitive fitness of up to 36%. Dual-targeting of topoisomerase IV and DNA gyrase enzymes, for example with the combination of a fluoroquinolone and a coumarin agent, could minimize the emergence of resistance to these drugs in S. aureus. However, resistance-associated fitness costs may not be sufficient to limit the survival of mutants with dual resistance, if they arose in the clinical setting.

  20. Mechanisms of reduced susceptibility and genotypic prediction of antibiotic resistance in Prevotella isolated from cystic fibrosis (CF) and non-CF patients

    PubMed Central

    Sherrard, Laura J.; Schaible, Bettina; Graham, Kathryn A.; McGrath, Stef J.; McIlreavey, Leanne; Hatch, Joseph; Wolfgang, Matthew C.; Muhlebach, Marianne S.; Gilpin, Deirdre F.; Schneiders, Thamarai; Elborn, J. Stuart; Tunney, Michael M.

    2014-01-01

    Objectives To investigate mechanisms of reduced susceptibility to commonly used antibiotics in Prevotella cultured from patients with cystic fibrosis (CF), patients with invasive infection and healthy control subjects and to determine whether genotype can be used to predict phenotypic resistance. Methods The susceptibility of 157 Prevotella isolates to seven antibiotics was compared, with detection of resistance genes (cfxA-type gene, ermF and tetQ), mutations within the CfxA-type β-lactamase and expression of efflux pumps. Results Prevotella isolates positive for a cfxA-type gene had higher MICs of amoxicillin and ceftazidime compared with isolates negative for this gene (P < 0.001). A mutation within the CfxA-type β-lactamase (Y239D) was associated with ceftazidime resistance (P = 0.011). The UK CF isolates were 5.3-fold, 2.7-fold and 5.7-fold more likely to harbour ermF compared with the US CF, UK invasive and UK healthy control isolates, respectively. Higher concentrations of azithromycin (P < 0.001) and clindamycin (P < 0.001) were also required to inhibit the growth of the ermF-positive isolates compared with ermF-negative isolates. Furthermore, tetQ-positive Prevotella isolates had higher MICs of tetracycline (P = 0.001) and doxycycline (P < 0.001) compared with tetQ-negative isolates. Prevotella spp. were also shown, for the first time, to express resistance nodulation division (RND)-type efflux pumps. Conclusions This study has demonstrated that Prevotella isolated from various sources harbour a common pool of resistance genes and possess RND-type efflux pumps, which may contribute to tetracycline resistance. The findings indicate that antibiotic resistance is common in Prevotella spp., but the genotypic traits investigated do not reflect phenotypic antibiotic resistance in every instance. PMID:24917582

  1. Predictive urinary biomarkers for steroid-resistant and steroid-sensitive focal segmental glomerulosclerosis using high resolution mass spectrometry and multivariate statistical analysis

    PubMed Central

    2014-01-01

    Background Focal segmental glomerulosclerosis (FSGS) is a glomerular scarring disease diagnosed mostly by kidney biopsy. Since there is currently no diagnostic test that can accurately predict steroid responsiveness in FSGS, prediction of the responsiveness of patients to steroid therapy with noninvasive means has become a critical issue. In the present study urinary proteomics was used as a noninvasive tool to discover potential predictive biomarkers. Methods Urinary proteome of 10 patients (n = 6 steroid-sensitive, n = 4 steroid-resistant) with biopsy proven FSGS was analyzed using nano-LC-MS/MS and supervised multivariate statistical analysis was performed. Results Twenty one proteins were identified as discriminating species among which apolipoprotein A-1 and Matrix-remodeling protein 8 had the most drastic fold changes being over- and underrepresented, respectively, in steroid sensitive compared to steroid resistant urine samples. Gene ontology enrichment analysis revealed acute inflammatory response as the dominant biological process. Conclusion The obtained results suggest a panel of predictive biomarkers for FSGS. Proteins involved in the inflammatory response are shown to be implicated in the responsiveness. As a tool for biomarker discovery, urinary proteomics is especially fruitful in the area of prediction of responsiveness to drugs. Further validation of these biomarkers is however needed. PMID:25182141

  2. A prediction model of substrates and non-substrates of breast cancer resistance protein (BCRP) developed by GA-CG-SVM method.

    PubMed

    Zhong, Lei; Ma, Chang-Ying; Zhang, Hui; Yang, Li-Jun; Wan, Hua-Lin; Xie, Qing-Qing; Li, Lin-Li; Yang, Sheng-Yong

    2011-11-01

    Breast cancer resistance protein (BCRP) is one of the key multi-drug resistance proteins, which significantly influences the therapeutic effects of many drugs, particularly anti-cancer drugs. Thus, distinguishing between substrates and non-substrates of BCRP is important not only for clinical use but also for drug discovery and development. In this study, a prediction model of the substrates and non-substrates of BCRP was developed using a modified support vector machine (SVM) method, namely GA-CG-SVM. The overall prediction accuracy of the established GA-CG-SVM model is 91.3% for the training set and 85.0% for an independent validation set. For comparison, two other machine learning methods, namely, C4.5 DT and k-NN, were also adopted to build prediction models. The results show that the GA-CG-SVM model is significantly superior to C4.5 DT and k-NN models in terms of the prediction accuracy. To sum up, the prediction model of BCRP substrates and non-substrates generated by the GA-CG-SVM method is sufficiently good and could be used as a screening tool for identifying the substrates and non-substrates of BCRP.

  3. Factors that predict preexisting colonization with antibiotic-resistant gram-negative bacilli in patients admitted to a pediatric intensive care unit.

    PubMed

    Toltzis, P; Hoyen, C; Spinner-Block, S; Salvator, A E; Rice, L B

    1999-04-01

    To predict which patients hospitalized in a pediatric intensive care unit (ICU) are colonized with antibiotic-resistant gram-negative rods on admission. Consecutive children admitted to a pediatric ICU over a 6-month period were entered into the study. A questionnaire soliciting information regarding the child's medical history and home environment was completed by the parent or guardian. Nasopharyngeal and rectal cultures were obtained on each of the first 3 days of ICU admission, and organisms resistant to ceftazidime or tobramycin were identified. Only clonally distinct organisms, as confirmed by pulsed field gel electrophoresis, were analyzed. The association between identification of colonization with an antibiotic-resistant gram-negative rod within 3 days of ICU admission and factors included in the questionnaire was tested by chi2 or t test. RESULTS. In 64 (8.8%) of 727 admissions, an antibiotic-resistant gram-negative bacillus was isolated within the first 3 ICU days. More than half were identified on the day of admission. Colonization was associated with two factors related to the patient's medical history, namely, number of past ICU admissions (1.98 vs.87) and administration of intravenous antibiotics within the past 12 months (67.9% vs 28.2%). No association was found between colonization and exposure to oral antibiotics. In addition, factors related to the child's environment were also associated with presumed importation of an antibiotic-resistant gram-negative rod into the ICU. Specifically, residence in a chronic care facility was strongly associated with colonization (28.3% vs 2.6%); exposure to a household contact who had been hospitalized in the past 12 months also predicted colonization (41.7% vs 18.5%). These data suggest that a profile can be established characterizing children colonized with resistant gram-negative bacilli before admission to a pediatric ICU. Infection control measures may help to contain these potentially dangerous bacteria

  4. Fouling resistance prediction using artificial neural network nonlinear auto-regressive with exogenous input model based on operating conditions and fluid properties correlations

    SciTech Connect

    Biyanto, Totok R.

    2016-06-03

    Fouling in a heat exchanger in Crude Preheat Train (CPT) refinery is an unsolved problem that reduces the plant efficiency, increases fuel consumption and CO{sub 2} emission. The fouling resistance behavior is very complex. It is difficult to develop a model using first principle equation to predict the fouling resistance due to different operating conditions and different crude blends. In this paper, Artificial Neural Networks (ANN) MultiLayer Perceptron (MLP) with input structure using Nonlinear Auto-Regressive with eXogenous (NARX) is utilized to build the fouling resistance model in shell and tube heat exchanger (STHX). The input data of the model are flow rates and temperatures of the streams of the heat exchanger, physical properties of product and crude blend data. This model serves as a predicting tool to optimize operating conditions and preventive maintenance of STHX. The results show that the model can capture the complexity of fouling characteristics in heat exchanger due to thermodynamic conditions and variations in crude oil properties (blends). It was found that the Root Mean Square Error (RMSE) are suitable to capture the nonlinearity and complexity of the STHX fouling resistance during phases of training and validation.

  5. Fouling resistance prediction using artificial neural network nonlinear auto-regressive with exogenous input model based on operating conditions and fluid properties correlations

    NASA Astrophysics Data System (ADS)

    Biyanto, Totok R.

    2016-06-01

    Fouling in a heat exchanger in Crude Preheat Train (CPT) refinery is an unsolved problem that reduces the plant efficiency, increases fuel consumption and CO2 emission. The fouling resistance behavior is very complex. It is difficult to develop a model using first principle equation to predict the fouling resistance due to different operating conditions and different crude blends. In this paper, Artificial Neural Networks (ANN) MultiLayer Perceptron (MLP) with input structure using Nonlinear Auto-Regressive with eXogenous (NARX) is utilized to build the fouling resistance model in shell and tube heat exchanger (STHX). The input data of the model are flow rates and temperatures of the streams of the heat exchanger, physical properties of product and crude blend data. This model serves as a predicting tool to optimize operating conditions and preventive maintenance of STHX. The results show that the model can capture the complexity of fouling characteristics in heat exchanger due to thermodynamic conditions and variations in crude oil properties (blends). It was found that the Root Mean Square Error (RMSE) are suitable to capture the nonlinearity and complexity of the STHX fouling resistance during phases of training and validation.

  6. Insulin resistance and systemic inflammation, but not metabolic syndrome phenotype, predict 9 years mortality in older adults

    PubMed Central

    Zuliani, Giovanni; Morieri, Mario Luca; Volpato, Stefano; Maggio, Marcello; Cherubini, Antonio; Francesconi, Daniela; Bandinelli, Stefania; Paolisso, Giuseppe; Guralnik, Jack M.; Ferrucci, Luigi

    2014-01-01

    Background Although metabolic syndrome (MS) is a typical condition of middle-aged/older person, the association between MS and mortality risk has not been confirmed in people over 65 years. We hypothesized that while in the elderly MS phenotype might lose its value in predicting mortality risk, the two core factors of MS, i.e. insulin resistance (IR) and low-grade systemic inflammation (LGSI) would not. Methods 1011 community-dwelling older individuals (InCHIANTI study) were included. MS phenotype was defined by NCEP-ATP-III criteria. IR was calculated by HOMA; high-sensitivity C-reactive protein was measured by ELISA. Subjects were divided into four groups based on presence/absence of IR (HOMA ≥2.27) and LGSI (hs-CRP ≥ 3g/L): Group 1: no IR/LGSI (reference); Group 2: LGSI only; Group 3: IR only; Group 4: IR+LGSI. Hazard Ratios (HR) for 9-years cardiovascular (CVD) and total mortality, according to IR/LGSI groups, were estimated in subjects with (n.311) and without MS by Cox model. Results 31.8% of subjects with MS phenotype had no IR, 45.3% had no LGSI; moreover, 51% of subjects with both IR and LGSI didn’t display the MS phenotype. MS phenotype was not associated with CVD (HR:1.29; 95%C.I.:0.92–1.81) or total (HR:1.07; 95%C.I.:0.86–1.34) mortality risk, whereas the presence of IR plus LGSI was associated with increased CVD (no MS: HR 2.07, 95%CI:1.12–3.72; MS: HR 9.88, 95%CI:2.18–4), and overall (no MS: HR 1.72, 95%CI:1.001–3.17; MS: HR 1.51, 95%CI:1.02–2.28) mortality risk. The presence of IR (HR: 6.90, 95%CI:1.45–32) or LGSI (HR 7.56, 95%CI:1.63–35) was associated with CVD mortality, only among individuals with MS phenotype. Conclusions Among community dwelling older individuals, IR and LGSI, but not MS phenotype, was associated with 9-years overall and CVD mortality risk. Since a reduced “overlap” between MS phenotype and its physiopathological core (IR and LGSI) might be present with aging, we suggest that the definition of MS might

  7. Analysis of pMA67, a predicted rolling-circle replicating, mobilizable, tetracycline-resistance plasmid from the honey bee pathogen, Paenibacillus larvae.

    PubMed

    Murray, K Daniel; Aronstein, Katherine A; de León, Jesse H

    2007-09-01

    This work characterizes a recently discovered natural tetracycline-resistance plasmid called pMA67 from Paenibacillus larvae--a Gram-positive bacterial pathogen of honey bees. We provide evidence that pMA67 replicates by the rolling-circle mechanism, and sequence comparisons place it in the pMV158 family of rolling-circle replicons. The plasmid contains predicted rep, cop, and rnaII genes for control of replication initiating at a predicted double-strand origin. The plasmid has an ssoT single-strand origin, which is efficient enough to allow only very small amounts of the single-stranded DNA intermediate to accumulate. The overall efficiency of replication is sufficient to render the plasmid segregationally stable without selection in P. larvae and in Bacillus megaterium, but not in Escherichia coli. The plasmid is expected to be mobilizable due to the presence of a mob gene and an oriT site. The plasmid contains a tetL gene, whose predicted amino acid sequence implies a relatively ancient divergence from all previously known plasmid-encoded tetL genes. We confirm that the tetL gene alone is sufficient for conferring resistance to tetracyclines. Sequence comparisons, mostly with the well-characterized pMV158, allow us to predict promoters, DNA and RNA secondary structures, DNA and protein motifs, and other elements.

  8. Drug resistance testing through remote genotyping and predicted treatment options in human immunodeficiency virus type 1 infected Tanzanian subjects failing first or second line antiretroviral therapy.

    PubMed

    Svärd, Jenny; Mugusi, Sabina; Mloka, Doreen; Neogi, Ujjwal; Meini, Genny; Mugusi, Ferdinand; Incardona, Francesca; Zazzi, Maurizio; Sönnerborg, Anders

    2017-01-01

    Antiretroviral therapy (ART) has been successfully introduced in low-middle income countries. However an increasing rate of ART failure with resistant virus is reported. We therefore described the pattern of drug resistance mutations at antiretroviral treatment (ART) failure in a real-life Tanzanian setting using the remote genotyping procedure and thereafter predicted future treatment options using rule-based algorithm and the EuResist bioinformatics predictive engine. According to national guidelines, the default first-line regimen is tenofovir + lamivudine + efavirenz, but variations including nevirapine, stavudine or emtricitabine can be considered. If failure on first-line ART occurs, a combination of two nucleoside reverse transcriptase inhibitors (NRTIs) and boosted lopinavir or atazanavir is recommended. Plasma was obtained from subjects with first (n = 174) or second-line (n = 99) treatment failure, as defined by clinical or immunological criteria, as well as from a control group of ART naïve subjects (n = 17) in Dar es Salaam, Tanzania. Amplification of the pol region was performed locally and the amplified DNA fragment was sent to Sweden for sequencing (split genotyping procedure). The therapeutic options after failure were assessed by the genotypic sensitivity score and the EuResist predictive engine. Viral load was quantified in a subset of subjects with second-line failure (n = 52). The HIV-1 pol region was successfully amplified from 55/174 (32%) and 28/99 (28%) subjects with first- or second-line failure, respectively, and 14/17 (82%) ART-naïve individuals. HIV-1 pol sequence was obtained in 82 of these 97 cases (84.5%). Undetectable or very low (<2.6 log10 copies/10-3 L) viral load explained 19 out of 25 (76%) amplification failures in subjects at second-line ART failure. At first and second line failure, extensive accumulation of NRTI (88% and 73%, respectively) and NNRTI (93% and 73%, respectively) DRMs but a limited number of PI DRMs (11% at

  9. Current status of anti-human epidermal growth factor receptor 2 therapies: predicting and overcoming herceptin resistance.

    PubMed

    Chung, Alice; Cui, Xiaojiang; Audeh, William; Giuliano, Armando

    2013-08-01

    Human epidermal growth factor receptor 2-overexpressing (HER2+) breast cancer occurs in 20% to 25% of cases and is associated with poor prognosis. Trastuzumab (Herceptin; Genentech, South San Francisco, CA) is a monoclonal antibody targeting the HER2 extracellular domain that has been shown to significantly reduce relapse rates. However, some patients with HER2+ tumors do not respond to Herceptin, and 60% to 85% of patients with HER2+ metastatic breast cancer acquire resistance within a short time period. In this review, we discuss proposed mechanisms of action of trastuzumab and trastuzumab resistance and various drugs that have been developed to overcome drug resistance. We introduce the basal molecular subtype as a predictor of increased risk in HER2+ breast cancer and a possible alternative cause of drug resistance.

  10. Improving LASSO performance for Grey Leaf Spot disease resistance prediction based on genotypic data by considering all possible two-way SNP interactions.

    PubMed

    Patel, Rinkal; Caraviello, Daniel; Qian, Wei

    2012-05-01

    Disease resistance prediction using genotypic data has been widely pursued in animal as well as plant research, mostly in cases where genotypic data can be readily available for a large number of subjects. With the evolution of SNP marker genotyping technology and the consequent cost reduction for genotyping thousands of SNP markers, significant research effort is being undertaken in the statistics and machine learning community to perform efficient analysis of these multidimensional datasets. For large plant breeding programs, besides identifying biomarkers associated with disease resistance, developing accurate predictive models of the phenotype based on the genotype alone is one of the most relevant scientific goals, as it allows for efficient selection without having to grow and phenotype every individual. While the importance of interactions for understanding diseases has been shown in many studies, the majority of the existing methods are limited by considering each biomarker as an independent variable, completely ignoring complex interactions among biomarkers. In this study, logistic regression p-value, Pearson correlation and mutual information were calculated for all two-way SNP interactions with respect to the Grey Leaf Spot (GLS) disease resistance phenotype. These interactions were subsequently ranked based on these measures and the performance of the LASSO algorithm for GLS disease resistance prediction was then shown to be maximized by adding the top 10 000 two-way interactions from the logistic regression p-value based rank. The logistic regression p-value based rank also led to an error rate of more than 3 percentual points lower than not adding any interaction and more than 3.5 percentual points lower than adding interactions chosen at random.

  11. Validating the prediction accuracies of marker-assisted and genomic selection of Fusarium head blight resistance in wheat using an independent sample.

    PubMed

    Jiang, Yong; Schulthess, Albert Wilhelm; Rodemann, Bernd; Ling, Jie; Plieske, Jörg; Kollers, Sonja; Ebmeyer, Erhard; Korzun, Viktor; Argillier, Odile; Stiewe, Gunther; Ganal, Martin W; Röder, Marion S; Reif, Jochen C

    2017-03-01

    Compared with independent validation, cross-validation simultaneously sampling genotypes and environments provided similar estimates of accuracy for genomic selection, but inflated estimates for marker-assisted selection. Estimates of prediction accuracy of marker-assisted (MAS) and genomic selection (GS) require validations. The main goal of our study was to compare the prediction accuracies of MAS and GS validated in an independent sample with results obtained from fivefold cross-validation using genomic and phenotypic data for Fusarium head blight resistance in wheat. In addition, the applicability of the reliability criterion, a concept originally developed in the context of classic animal breeding and GS, was explored for MAS. We observed that prediction accuracies of MAS were overestimated by 127% using cross-validation sampling genotype and environments in contrast to independent validation. In contrast, prediction accuracies of GS determined in independent samples are similar to those estimated with cross-validation sampling genotype and environments. This can be explained by small population differentiation between the training and validation sets in our study. For European wheat breeding, which is so far characterized by a slow temporal dynamic in allele frequencies, this assumption seems to be realistic. Thus, GS models used to improve European wheat populations are expected to possess a long-lasting validity. Since quantitative trait loci information can be exploited more precisely if the predicted genotype is more related to the training population, the reliability criterion is also a valuable tool to judge the level of prediction accuracy of individual genotypes in MAS.

  12. Prognostic and predictive effects of primary versus secondary platinum resistance for bevacizumab treatment for platinum-resistant ovarian cancer in the AURELIA trial.

    PubMed

    Trillsch, F; Mahner, S; Hilpert, F; Davies, L; García-Martínez, E; Kristensen, G; Savarese, A; Vuylsteke, P; Los, M; Zagouri, F; Gladieff, L; Sehouli, J; Khoon Lee, C; Gebski, V; Pujade-Lauraine, E

    2016-09-01

    Progression-free survival (PFS), objective response rate (ORR), and patient-reported outcomes (PROs) were significantly improved by adding bevacizumab to chemotherapy for platinum-resistant ovarian cancer (PROC) in the phase III AURELIA trial. We explored treatment outcomes according to primary platinum resistance (PPR) versus secondary platinum resistance (SPR). Patients were categorized as PPR (disease progression <6 months after completing first-line platinum therapy) or SPR (progression ≥6 months after first platinum but <6 months after second). The exploratory Cox and logistic regression analyses correlated PFS, ORR, overall survival (OS), and PROs with the time to development of platinum resistance. Baseline characteristics were similar in patients with PPR (n = 262; 73%) and SPR (n = 99; 27%), although ascites were more common in the PPR subgroup. In bevacizumab-treated patients (n = 179), SPR was associated with improved PFS (median 10.2 versus 5.6 months in PPR patients; P < 0.001) and OS (median 22.2 versus 13.7 months, respectively; P < 0.001) but not PROs (22% versus 22% with improved abdominal/gastrointestinal symptoms at week 8/9). In multivariate analyses, SPR remained an independent prognostic factor for better PFS [adjusted hazard ratio (HR) 0.41, 95% confidence interval (CI) 0.25-0.67; P < 0.001] and OS (HR 0.49, 95% CI 0.30-0.80; P = 0.005) in bevacizumab-treated patients, but was not statistically significant for either end point in the chemotherapy-alone subgroup. The magnitude of PFS benefit from bevacizumab appeared greater in SPR than PPR patients (HR 0.30 versus 0.55, respectively; interaction P = 0.07) with a similar direction of effect for OS (interaction P = 0.18). In bevacizumab-treated patients, PFS and OS were more favorable in SPR than PPR patients with equally improved PROs. The PFS and OS benefit from combining bevacizumab with chemotherapy was more pronounced in SPR than PPR PROC. PPR versus SPR should be a stratification factor

  13. Digestion-Resistant Dextrin Derivatives Are Moderately Digested in the Small Intestine and Contribute More to Energy Production Than Predicted from Large-Bowel Fermentation in Rats.

    PubMed

    Kondo, Takashi; Handa, Kei; Genda, Tomomi; Hino, Shingo; Hamaguchi, Norihisa; Morita, Tatsuya

    2017-03-01

    Background: Digestion-resistant dextrin derivatives (DRDDs), including resistant maltodextrin (RM), polydextrose, and resistant glucan (RG), have been developed as low-energy foods. However, data on the resistance of DRDDs to small-intestinal digestion are scarce.Objective: We sought to determine the site and extent of DRDD breakdown in the rat intestine and to predict its energy contributions.Methods: In vitro small-intestinal resistance of DRDDs was evaluated by the AOAC method for dietary fiber measurement and by artificial digestion with the use of pancreatic α-amylase and brush-boarder membrane vesicles. In vivo small-intestinal resistance of DRDDs was determined from the feces of male ileorectostomized Sprague-Dawley rats fed a control diet or a diet containing one of the DRDDs at 50 g/kg for 9 d (period 1) and then for 10 d (period 2), during which they received 1 g neomycin/L in their drinking water. Separately, male Sprague-Dawley rats were fed the same diets for 4 wk, and the whole-gut recoveries of DRDDs were determined from feces at days 8-10.Results: Small-intestinal resistances determined in vitro by artificial digestion (RM: 70%; polydextrose: 67%; RG: 69%) were lower than those measured by the AOAC method (RM: 92%; polydextrose: 80%; RG: 82%). In the ileorectostomized rats, fecal dry-matter excretions were consistently greater in the DRDDs than in the control. The small-intestinal resistances of the DRDDs were 68%, 58%, and 62% in period 1 and 66%, 61%, and 67% during period 2 for RM, polydextrose, and RG, respectively. The resistances did not differ among the DRDDs at either time. In the normal rats, food intakes and body weight gains did not differ among the groups. The whole-gut recovery of RM (13%) was lower than that of polydextrose (33%) and RG (29%), which did not differ.Conclusions: DRDDs were more digestible in the rat small intestine than the AOAC method. The energy contribution from small-intestine digestibility, not just large

  14. Early insulin resistance predicts weight gain and waist circumference increase in first-episode psychosis--A one year follow-up study.

    PubMed

    Keinänen, Jaakko; Mantere, Outi; Kieseppä, Tuula; Mäntylä, Teemu; Torniainen, Minna; Lindgren, Maija; Sundvall, Jouko; Suvisaari, Jaana

    2015-12-01

    First-episode psychosis (FEP) is associated with weight gain during the first year of treatment, and risk of abdominal obesity is particularly increased. To identify early risk markers of weight gain and abdominal obesity, we investigated baseline metabolic differences in 60 FEP patients and 27 controls, and longitudinal changes during the first year of treatment in patients. Compared to controls at baseline, patients had higher low-density lipoprotein, triglyceride and apolipoprotein B levels, and lower levels of high-density lipoprotein and apolipoprotein A-I but no difference in body mass index or waist circumference. At 12-month follow-up, 60.6% of patients were overweight or obese and 58.8% had abdominal obesity. No significant increase during follow-up was seen in markers of glucose and lipid metabolism or blood pressure, but increase in C-reactive protein between baseline and 12-month follow-up was statistically significant. Weight increase was predicted by baseline insulin resistance and olanzapine use, while increase in waist circumference was predicted by baseline insulin resistance only. In conclusion, insulin resistance may be an early marker of increased vulnerability to weight gain and abdominal obesity in young adults with FEP. Olanzapine should be avoided as a first-line treatment in FEP due to the substantial weight increase it causes. In addition, the increase in the prevalence of overweight and abdominal obesity was accompanied by the emergence of low-grade systemic inflammation. Copyright © 2015 Elsevier B.V. All rights reserved.

  15. Principles of a New Protocol for Prediction of Azole Resistance in Candida albicans Infections on the Basis of ERG11 Polymorphisms.

    PubMed

    Caban, Monika; Strapagiel, Dominik; Dziadek, Jarosław; Korycka-Machała, Małgorzata; Grzelak, Agnieszka

    2016-08-01

    In recent years, Candida albicans infections treatment has become a growing problem because, among others, pathogenic strains are capable to develop resistance to the administered drugs. The elaboration of rapid and accurate method of resistance assessment is an important goal of many studies. They aim to avoid inappropriate dosage or drug choice, which may be life threatening in case of severe candidiasis. Here we propose a new protocol to predict C. albicans infections. The resistance prediction is based on high-resolution melt (HRM) analysis of ERG11 gene, especially, at the particularly unstable regions. Two statistically significant nucleotide polymorphisms were detected among twenty-seven strains isolated from saliva, one of which was silent mutation (Glu266Asp, Leu480Leu). We propose also HRM analysis as a convenient, simple and inexpensive method of preliminary selection of C. albicans DNA samples that vary in ERG11 nucleotide sequence within presumed region. Taken together, our study provides firm basis for the development of fast, simple and reliable methodology for diagnosis of C. albicans infections.

  16. A study on the effect of flat plate friction resistance on speed performance prediction of full scale

    NASA Astrophysics Data System (ADS)

    Park, Dong-Woo

    2015-01-01

    Flat plate friction lines hare been used in the process to estimate speed performance of full-scale ships in model tests. The results of the previous studies showed considerable differences in determining form factors depending on changes in plate friction lines and Reynolds numbers. These differences had a great influence on estimation of speed performance of full-scale ships. This study- was conducted in two parts. In the first part, the scale effect of the form factor depending on change in the Reynolds number was studied based on CFD, in connection with three kinds of friction resistance curves: the ITTC-1957, the curve proposed by Grigson (1993; 1996), and the curve developed by Katsui et al (2005). In the second part, change in the form factor by three kinds of friction resistance curves was investigated based on model tests, and then the brake power and the revolution that were finally determined by expansion processes of full-scale ships. When three kinds of friction resistance curves were applied to each kind of ships, these were investigated: differences between resistance and self-propulsion components induced in the expansion processes of full-scale ships, correlation of effects between these components, and tendency of each kind of ships. Finally, what friction resistance curve was well consistent with results of test operation was examined per each kind of ships.

  17. Evaluation of Genome-Enabled Selection for Bacterial Cold Water Disease Resistance Using Progeny Performance Data in Rainbow Trout: Insights on Genotyping Methods and Genomic Prediction Models.

    PubMed

    Vallejo, Roger L; Leeds, Timothy D; Fragomeni, Breno O; Gao, Guangtu; Hernandez, Alvaro G; Misztal, Ignacy; Welch, Timothy J; Wiens, Gregory D; Palti, Yniv

    2016-01-01

    Bacterial cold water disease (BCWD) causes significant economic losses in salmonid aquaculture, and traditional family-based breeding programs aimed at improving BCWD resistance have been limited to exploiting only between-family variation. We used genomic selection (GS) models to predict genomic breeding values (GEBVs) for BCWD resistance in 10 families from the first generation of the NCCCWA BCWD resistance breeding line, compared the predictive ability (PA) of GEBVs to pedigree-based estimated breeding values (EBVs), and compared the impact of two SNP genotyping methods on the accuracy of GEBV predictions. The BCWD phenotypes survival days (DAYS) and survival status (STATUS) had been recorded in training fish (n = 583) subjected to experimental BCWD challenge. Training fish, and their full sibs without phenotypic data that were used as parents of the subsequent generation, were genotyped using two methods: restriction-site associated DNA (RAD) sequencing and the Rainbow Trout Axiom® 57 K SNP array (Chip). Animal-specific GEBVs were estimated using four GS models: BayesB, BayesC, single-step GBLUP (ssGBLUP), and weighted ssGBLUP (wssGBLUP). Family-specific EBVs were estimated using pedigree and phenotype data in the training fish only. The PA of EBVs and GEBVs was assessed by correlating mean progeny phenotype (MPP) with mid-parent EBV (family-specific) or GEBV (animal-specific). The best GEBV predictions were similar to EBV with PA values of 0.49 and 0.46 vs. 0.50 and 0.41 for DAYS and STATUS, respectively. Among the GEBV prediction methods, ssGBLUP consistently had the highest PA. The RAD genotyping platform had GEBVs with similar PA to those of GEBVs from the Chip platform. The PA of ssGBLUP and wssGBLUP methods was higher with the Chip, but for BayesB and BayesC methods it was higher with the RAD platform. The overall GEBV accuracy in this study was low to moderate, likely due to the small training sample used. This study explored the potential of GS for

  18. Evaluation of Genome-Enabled Selection for Bacterial Cold Water Disease Resistance Using Progeny Performance Data in Rainbow Trout: Insights on Genotyping Methods and Genomic Prediction Models

    PubMed Central

    Vallejo, Roger L.; Leeds, Timothy D.; Fragomeni, Breno O.; Gao, Guangtu; Hernandez, Alvaro G.; Misztal, Ignacy; Welch, Timothy J.; Wiens, Gregory D.; Palti, Yniv

    2016-01-01

    Bacterial cold water disease (BCWD) causes significant economic losses in salmonid aquaculture, and traditional family-based breeding programs aimed at improving BCWD resistance have been limited to exploiting only between-family variation. We used genomic selection (GS) models to predict genomic breeding values (GEBVs) for BCWD resistance in 10 families from the first generation of the NCCCWA BCWD resistance breeding line, compared the predictive ability (PA) of GEBVs to pedigree-based estimated breeding values (EBVs), and compared the impact of two SNP genotyping methods on the accuracy of GEBV predictions. The BCWD phenotypes survival days (DAYS) and survival status (STATUS) had been recorded in training fish (n = 583) subjected to experimental BCWD challenge. Training fish, and their full sibs without phenotypic data that were used as parents of the subsequent generation, were genotyped using two methods: restriction-site associated DNA (RAD) sequencing and the Rainbow Trout Axiom® 57 K SNP array (Chip). Animal-specific GEBVs were estimated using four GS models: BayesB, BayesC, single-step GBLUP (ssGBLUP), and weighted ssGBLUP (wssGBLUP). Family-specific EBVs were estimated using pedigree and phenotype data in the training fish only. The PA of EBVs and GEBVs was assessed by correlating mean progeny phenotype (MPP) with mid-parent EBV (family-specific) or GEBV (animal-specific). The best GEBV predictions were similar to EBV with PA values of 0.49 and 0.46 vs. 0.50 and 0.41 for DAYS and STATUS, respectively. Among the GEBV prediction methods, ssGBLUP consistently had the highest PA. The RAD genotyping platform had GEBVs with similar PA to those of GEBVs from the Chip platform. The PA of ssGBLUP and wssGBLUP methods was higher with the Chip, but for BayesB and BayesC methods it was higher with the RAD platform. The overall GEBV accuracy in this study was low to moderate, likely due to the small training sample used. This study explored the potential of GS for

  19. Microbiological features of vancomycin in the 21st century: minimum inhibitory concentration creep, bactericidal/static activity, and applied breakpoints to predict clinical outcomes or detect resistant strains.

    PubMed

    Jones, Ronald N

    2006-01-01

    The results of vancomycin susceptibility tests document that the drug continues to have activity against a wide variety of gram-positive pathogens. The subsequent emergence of vancomycin-resistant enterococci, the persistent failure of vancomycin therapy against strains tested as susceptible, and the more recent discoveries of vancomycin-intermediate or -resistant Staphylococcus aureus strains have compromised the use of vancomycin. Although analyses of surveillance studies fail to demonstrate "minimum inhibitory concentration creep" among populations of wild-type enterococci, streptococci, or staphylococci, enterococci with acquired resistance to vancomycin continue to evolve. The dominantly used automated commercial tests poorly recognize vancomycin-intermediate S. aureus, heteroresistant vancomycin-intermediate S. aureus, and vancomycin-resistant S. aureus isolates, which necessitates the use of expensive supplemental screening tests. Monitoring for appropriate serum levels of vancomycin and determinations of the bactericidal activity of vancomycin appear to best predict clinical outcome, thus creating additional diagnostic burdens for clinical laboratories. Improvements in current test methods with breakpoint criteria and expanded use of the vancomycin bactericidal assays to detect "tolerant" strains will be required to increase the value of vancomycin treatment or to refocus therapy toward the use of newer, alternative agents.

  20. Does Homeostasis Model Assessment of Insulin Resistance have a predictive value for post-coronary artery bypass grafting surgery outcomes?

    PubMed Central

    Aydin, Ebuzer; Ozkokeli, Mehmet

    2014-01-01

    Objective This study aims to investigate whether pre-operative Homeostasis Model Assessment Insulin Resistance (HOMA-IR) value is a predictor in non-diabetic coronary artery bypass grafting patients in combination with hemoglobin A1c, fasting blood glucose and insulin levels. Methods Eighty one patients who were admitted to Cardiovascular Surgery Clinic at our hospital between August 2012 and January 2013 with a coronary artery bypass grafting indication were included. Patients were non-diabetic with <6.3% hemoglobin A1c and were divided into two groups including treatment and control groups according to normal insulin resistance (HOMA-IR<2.5, Group A; n=41) and high insulin resistance (HOMA-IR>2.5, Group B; n=40), respectively. Pre-operative fasting blood glucose and insulin were measured and serum chemistry tests were performed. The Homeostasis Model Assessment Insulin Resistance values were calculated. Statistical analysis was performed. Results There was a statistically significant difference in fasting blood glucose and HOMA-IR values between the groups. Cross-clamping time, and cardiopulmonary bypass time were longer in Group B, compared to Group A (P=0.043 and P=0.031, respectively). Logistic regression analysis revealed that hemoglobin A1c was not a reliable determinant factor alone for pre-operative glucometabolic evaluation of non-diabetic patients. The risk factors of fasting blood glucose and cardiopulmonary bypass time were more associated with high Homeostasis Model Assessment Insulin Resistance levels. Conclusion Our study results suggest that preoperative screening of non-diabetic patients with Homeostasis Model Assessment Insulin Resistance may improve both follow-up visit schedule and short-term outcomes, and may be useful in risk stratification of the high-risk population for impending health problems. PMID:25372910

  1. Predicting time to castration resistance in hormone sensitive prostate cancer by a personalization algorithm based on a mechanistic model integrating patient data.

    PubMed

    Elishmereni, Moran; Kheifetz, Yuri; Shukrun, Ilan; Bevan, Graham H; Nandy, Debashis; McKenzie, Kyle M; Kohli, Manish; Agur, Zvia

    2016-01-01

    Prostate cancer (PCa) is a leading cause of cancer death of men worldwide. In hormone-sensitive prostate cancer (HSPC), androgen deprivation therapy (ADT) is widely used, but an eventual failure on ADT heralds the passage to the castration-resistant prostate cancer (CRPC) stage. Because predicting time to failure on ADT would allow improved planning of personal treatment strategy, we aimed to develop a predictive personalization algorithm for ADT efficacy in HSPC patients. A mathematical mechanistic model for HSPC progression and treatment was developed based on the underlying disease dynamics (represented by prostate-specific antigen; PSA) as affected by ADT. Following fine-tuning by a dataset of ADT-treated HSPC patients, the model was embedded in an algorithm, which predicts the patient's time to biochemical failure (BF) based on clinical metrics obtained before or early in-treatment. The mechanistic model, including a tumor growth law with a dynamic power and an elaborate ADT-resistance mechanism, successfully retrieved individual time-courses of PSA (R(2) = 0.783). Using the personal Gleason score (GS) and PSA at diagnosis, as well as PSA dynamics from 6 months after ADT onset, and given the full ADT regimen, the personalization algorithm accurately predicted the individual time to BF of ADT in 90% of patients in the retrospective cohort (R(2) = 0.98). The algorithm we have developed, predicting biochemical failure based on routine clinical tests, could be especially useful for patients destined for short-lived ADT responses and quick progression to CRPC. Prospective studies must validate the utility of the algorithm for clinical decision-making. © 2015 Wiley Periodicals, Inc.

  2. Individual Differences in the Resistance to Social Change and Acceptance of Inequality Predict System Legitimacy Differently Depending on the Social Structure

    PubMed Central

    Reyna, Christine

    2017-01-01

    Abstract We propose that individual differences in the resistance to social change and the acceptance of inequality can have divergent effects on legitimacy depending on the context. This possibility was tested in a sample of 27 European countries (N = 144 367) and across four experiments (total N = 475). Individual differences in the resistance to social change were related to higher levels of perceived legitimacy no matter the level of inequality of the society. Conversely, individual differences in the acceptance of inequality were related to higher levels of perceived legitimacy in unequal societies, but either a relationship near zero or the opposite relationship was found in more equal societies. These studies highlight the importance of distinguishing between individual differences that make up political ideology, especially when making predictions in diverse settings. © 2017 The Authors. European Journal of Personality published by John Wiley & Sons Ltd on behalf of European Association of Personality Psychology PMID:28706346

  3. Individual Differences in the Resistance to Social Change and Acceptance of Inequality Predict System Legitimacy Differently Depending on the Social Structure.

    PubMed

    Brandt, Mark J; Reyna, Christine

    2017-01-01

    We propose that individual differences in the resistance to social change and the acceptance of inequality can have divergent effects on legitimacy depending on the context. This possibility was tested in a sample of 27 European countries (N = 144 367) and across four experiments (total N = 475). Individual differences in the resistance to social change were related to higher levels of perceived legitimacy no matter the level of inequality of the society. Conversely, individual differences in the acceptance of inequality were related to higher levels of perceived legitimacy in unequal societies, but either a relationship near zero or the opposite relationship was found in more equal societies. These studies highlight the importance of distinguishing between individual differences that make up political ideology, especially when making predictions in diverse settings. © 2017 The Authors. European Journal of Personality published by John Wiley & Sons Ltd on behalf of European Association of Personality Psychology.

  4. Frontal theta cordance predicts 6-month antidepressant response to subcallosal cingulate deep brain stimulation for treatment-resistant depression: a pilot study.

    PubMed

    Broadway, James M; Holtzheimer, Paul E; Hilimire, Matthew R; Parks, Nathan A; Devylder, Jordan E; Mayberg, Helen S; Corballis, Paul M

    2012-06-01

    Deep brain stimulation (DBS) of subcallosal cingulate white matter (SCC) may be an effective approach for treatment-resistant depression (TRD) that otherwise fails to respond to more conventional therapies, but DBS is invasive, costly, and has potential for adverse effects. Therefore, it is important to identify potential biomarkers for predicting antidepressant response before intervention. Resting-state EEG was recorded from 12 TRD patients at pre-treatment baseline, after 4 weeks SCC DBS, and after 24 weeks SCC DBS. Lower frontal theta cordance (FTC) at baseline (and higher FTC after 4 weeks) predicted lower depression severity scores after 24 weeks. Greater FTC increases (baseline-4 weeks) predicted greater decreases in depression severity scores subsequently (4-24 weeks) and over the course of the study (baseline-24 weeks). Predictive relationships were topographically specific to theta cordance for frontal electrodes. Thus, results from this pilot study suggest that baseline FTC and changes early in treatment each have utility as biomarkers for predicting 6-month clinical response to SCC DBS for TRD.

  5. Frontal Theta Cordance Predicts 6-Month Antidepressant Response to Subcallosal Cingulate Deep Brain Stimulation for Treatment-Resistant Depression: A Pilot Study

    PubMed Central

    Broadway, James M; Holtzheimer, Paul E; Hilimire, Matthew R; Parks, Nathan A; DeVylder, Jordan E; Mayberg, Helen S; Corballis, Paul M

    2012-01-01

    Deep brain stimulation (DBS) of subcallosal cingulate white matter (SCC) may be an effective approach for treatment-resistant depression (TRD) that otherwise fails to respond to more conventional therapies, but DBS is invasive, costly, and has potential for adverse effects. Therefore, it is important to identify potential biomarkers for predicting antidepressant response before intervention. Resting-state EEG was recorded from 12 TRD patients at pre-treatment baseline, after 4 weeks SCC DBS, and after 24 weeks SCC DBS. Lower frontal theta cordance (FTC) at baseline (and higher FTC after 4 weeks) predicted lower depression severity scores after 24 weeks. Greater FTC increases (baseline–4 weeks) predicted greater decreases in depression severity scores subsequently (4–24 weeks) and over the course of the study (baseline–24 weeks). Predictive relationships were topographically specific to theta cordance for frontal electrodes. Thus, results from this pilot study suggest that baseline FTC and changes early in treatment each have utility as biomarkers for predicting 6-month clinical response to SCC DBS for TRD. PMID:22414813

  6. Combined measurement of fetal lung volume and pulmonary artery resistance index is more accurate for prediction of neonatal respiratory distress syndrome in preterm fetuses: A Pilot Study.

    PubMed

    Laban, Mohamed; Mansour, Ghada; El-Kotb, Ahmed; Hassanin, Alaa; Laban, Zina; Saleh, Abdelrahman

    2017-10-02

    To estimate optimal cut-off values for mean fetal lung volume (FLV) and pulmonary artery resistance index (PA-RI) as noninvasive measures to predict neonatal respiratory distress syndrome (RDS) in preterm fetuses. A prospective study conducted at Ain Shams University Maternity Hospital, Egypt from May 2015 to July 2017: eighty eligible women diagnosed with preterm labor were recruited at 32-36 weeks' gestation. Before delivery, three-dimensional ultrasound was used to estimate FLV using virtual organ computer-aided analysis (VOCAL), while PA-RI was measured by Doppler ultrasonography. A total of 80 women were examined. 37 (46%) of the newborns developed neonatal RDS. FLV was significantly lower in neonates who developed RDS (p = 0.04), whereas PARI was significantly higher in those who didn't (p = 0.02). Cut-off values of FLV ≤ 27.2 cm(3) and PARI ≥ 0.77 predicted the subsequent development of RDS. Combining both cut-offs generated a more sensitive and specific methodical approach for the prediction of RDS (sensitivity 100%, specificity 88.5%). Measurement of FLV or PA-RI can predict RDS in preterm fetuses. Combined use of both measures bolstered their predictive significance.

  7. Genomic selection models double the accuracy of predicted breeding values for bacterial cold water disease resistance compared to a traditional pedigree-based model in rainbow trout aquaculture.

    PubMed

    Vallejo, Roger L; Leeds, Timothy D; Gao, Guangtu; Parsons, James E; Martin, Kyle E; Evenhuis, Jason P; Fragomeni, Breno O; Wiens, Gregory D; Palti, Yniv

    2017-02-01

    Previously, we have shown that bacterial cold water disease (BCWD) resistance in rainbow trout can be improved using traditional family-based selection, but progress has been limited to exploiting only between-family genetic variation. Genomic selection (GS) is a new alternative that enables exploitation of within-family genetic variation. We compared three GS models [single-step genomic best linear unbiased prediction (ssGBLUP), weighted ssGBLUP (wssGBLUP), and BayesB] to predict genomic-enabled breeding values (GEBV) for BCWD resistance in a commercial rainbow trout population, and compared the accuracy of GEBV to traditional estimates of breeding values (EBV) from a pedigree-based BLUP (P-BLUP) model. We also assessed the impact of sampling design on the accuracy of GEBV predictions. For these comparisons, we used BCWD survival phenotypes recorded on 7893 fish from 102 families, of which 1473 fish from 50 families had genotypes [57 K single nucleotide polymorphism (SNP) array]. Naïve siblings of the training fish (n = 930 testing fish) were genotyped to predict their GEBV and mated to produce 138 progeny testing families. In the following generation, 9968 progeny were phenotyped to empirically assess the accuracy of GEBV predictions made on their non-phenotyped parents. The accuracy of GEBV from all tested GS models were substantially higher than the P-BLUP model EBV. The highest increase in accuracy relative to the P-BLUP model was achieved with BayesB (97.2 to 108.8%), followed by wssGBLUP at iteration 2 (94.4 to 97.1%) and 3 (88.9 to 91.2%) and ssGBLUP (83.3 to 85.3%). Reducing the training sample size to n = ~1000 had no negative impact on the accuracy (0.67 to 0.72), but with n = ~500 the accuracy dropped to 0.53 to 0.61 if the training and testing fish were full-sibs, and even substantially lower, to 0.22 to 0.25, when they were not full-sibs. Using progeny performance data, we showed that the accuracy of genomic predictions is substantially higher

  8. Comparison of regional fat mass measurement by whole body DXA scans and anthropometric measures to predict insulin resistance in women with polycystic ovary syndrome and controls.

    PubMed

    Glintborg, Dorte; Petersen, Maria Houborg; Ravn, Pernille; Hermann, Anne Pernille; Andersen, Marianne

    2016-11-01

    Polycystic ovary syndrome (PCOS) is characterized by obesity and insulin resistance. Measures of regional obesity may be used to predict insulin resistance. In the present study we compared fat distribution in patients with PCOS vs. controls and established the best measure of fat mass to predict insulin resistance in patients with PCOS. The study was cross-sectional in an academic tertiary-care medical center with 167 premenopausal women with PCOS and 110 controls matched for ethnicity, BMI and age. Total and regional fat and lean body mass were assessed by whole body dual-energy X-ray absorptiometry (DXA) scans. Anthropometric measures (BMI, waist) and fasting metabolic analyses [insulin, glucose, lipids, Homeostasis model assessment (HOMA-IR), lipid accumulation product, and visceral adiposity index] were determined. Trial registration numbers: NCT00451568, NCT00145340. Women with PCOS had higher central fat mass (waist, waist-hip ratio, and upper/lower fat ratio) compared with controls. In bivariate associations, the strongest associations were found between HOMA-IR and the fat mass measures trunk fat (r = 0.59), waist (r = 0.57) and BMI (r = 0.56), all p < 0.001. During multiple regression analyses, trunk fat, waist and BMI were the best predictors of HOMA-IR (R(2 ) = 0.48, 0.49, and 0.47, respectively). Women with PCOS were characterized by central obesity. Trunk fat, waist and BMI were the best predictors of HOMA-IR in PCOS, but only limited information regarding insulin resistance was gained by whole body DXA scan. © 2016 Nordic Federation of Societies of Obstetrics and Gynecology.

  9. A Comprehensive Evaluation of Biomarkers Predictive of Response to PI3K Inhibitors and of Resistance Mechanisms in Head and Neck Squamous Cell Carcinoma

    PubMed Central

    Mazumdar, Tuhina; Byers, Lauren A.; Shing Ng, Patrick Kwok; Mills, Gordon B.; Peng, Shaohua; Diao, Lixia; Fan, You-Hong; Stemke-Hale, Katherine; Heymach, John V.; Myers, Jeffrey N.; Glisson, Bonnie S.; Johnson, Faye M.

    2014-01-01

    The PI3K/AKT/mTOR pathway is frequently activated in head and neck squamous cell carcinoma (HNSCC), but pathway inhibition has variable efficacy. Identification of predictive biomarkers and mechanisms of resistance would allow selection of patients most likely to respond and novel therapeutic combinations. The purpose of this study was to extend recent discoveries regarding the PI3K/AKT/mTOR pathway in HNSCC by more broadly examining potential biomarkers of response, by examining pathway inhibitors with a diverse range of targets, and by defining mechanisms of resistance and potential combination therapies. We used reverse-phase protein arrays (RPPA) to simultaneously evaluate expression of 195 proteins; single-nucleotide polymorphism array to estimate gene copy number; and mass array to identify mutations. We examined altered signaling at baseline and after pathway inhibition. Likewise, we examined the activation of the PI3K/AKT/mTOR pathway in HNSCC tumors by RPPA. Cell lines with PIK3CA mutations were sensitive to pathway inhibitors, whereas amplification status did not predict sensitivity. While we identified a set of individual candidate biomarkers of response to pathway inhibitors, proteomic pathway scores did not correlate with amplification or mutation and did not predict response. Several receptor tyrosine kinases, including EGFR and ERK, were activated following PI3K inhibition in resistant cells; dual pathway inhibition of PI3K and EGFR or MEK demonstrated synergy. Combined MEK and PI3K inhibition was markedly synergistic in HRAS-mutant cell lines. Our findings indicate that clinical trials of single-agent PI3K/AKT/mTOR pathway inhibitors in selected populations and of PI3K-EGFR or PI3KMEK inhibitor combinations are warranted; we plan to conduct such trials. PMID:25193510

  10. Prediction of paclitaxel resistance in breast cancer: is CYP1B1*3 a new factor of influence?

    PubMed

    Gehrmann, Mathias; Schmidt, Markus; Brase, Jan C; Roos, Peter; Hengstler, Jan G

    2008-07-01

    This article focuses on the recent findings by Marsh and colleagues, and also discusses recent findings with regards to breast cancer. Taxanes are amongst the most active agents in the treatment of breast cancer. However, many tumors are intrinsically resistant. Therefore, it would be an enormous progress, if factors could be identified that reliably differentiate between taxane-sensitive and -resistant patients. Marsh and colleagues analyzed the CYP1B1*3 (Val432Leu) polymorphism in patients with high-risk stage III and IV breast cancer, who received dose-intense paclitaxel in combination with doxorubicin and cyclophosphamide. They report for the first time that patients with two leucine alleles in codon 432 of CYP1B1 experience a longer progression-free survival compared with patients with the Val/Leu or Val/Val genotypes. If confirmed in independent cohorts CYP1B1*3 may prove to be an important factor that helps to differentiate between paclitaxel-sensitive and resistant breast cancer patients. However, the mechanism behind the association between CYP1B1*3 and prognosis of paclitaxel-treated patients remains unclear. Several studies provide strong evidence that CYP1B1 does not influence tumor progression independently from paclitaxel chemotherapy, and that CYP1B1 itself does not alter paclitaxel resistance. In addition, CYP1B1 mRNA expression does not correlate with paclitaxel sensitivity of primary tumor cells. Although still speculative, a possible explanation is an association between CYP1B1*3 with still unknown factors that, on their part, influence paclitaxel sensitivity. In the future, studies with SNP chips and studies on the transcriptome, proteome and metabolome level should be performed in order to identify signatures differentiating between paclitaxel-sensitive and -resistant patients.

  11. Performance and Verification of a Real-Time PCR Assay Targeting the gyrA Gene for Prediction of Ciprofloxacin Resistance in Neisseria gonorrhoeae

    PubMed Central

    Hemarajata, P.; Yang, S.; Soge, O. O.; Klausner, J. D.

    2016-01-01

    In the United States, 19.2% of Neisseria gonorrhoeae isolates are resistant to ciprofloxacin. We evaluated a real-time PCR assay to predict ciprofloxacin susceptibility using residual DNA from the Roche Cobas 4800 CT/NG assay. The results of the assay were 100% concordant with agar dilution susceptibility test results for 100 clinical isolates. Among 76 clinical urine and swab specimens positive for N. gonorrhoeae by the Cobas assay, 71% could be genotyped. The test took 1.5 h to perform, allowing the physician to receive results in time to make informed clinical decisions. PMID:26739156

  12. Androgen Receptor Variant AR-V9 Is Coexpressed with AR-V7 in Prostate Cancer Metastases and Predicts Abiraterone Resistance.

    PubMed

    Kohli, Manish; Ho, Yeung; Hillman, David W; Van Etten, Jamie L; Henzler, Christine; Yang, Rendong; Sperger, Jamie M; Li, Yingming; Tseng, Elizabeth; Hon, Ting; Clark, Tyson; Tan, Winston; Carlson, Rachel E; Wang, Liguo; Sicotte, Hugues; Thai, Ho; Jimenez, Rafael; Huang, Haojie; Vedell, Peter T; Eckloff, Bruce W; Quevedo, Jorge F; Pitot, Henry C; Costello, Brian A; Jen, Jin; Wieben, Eric D; Silverstein, Kevin A T; Lang, Joshua M; Wang, Liewei; Dehm, Scott M

    2017-08-15

    Purpose: Androgen receptor (AR) variant AR-V7 is a ligand-independent transcription factor that promotes prostate cancer resistance to AR-targeted therapies. Accordingly, efforts are under way to develop strategies for monitoring and inhibiting AR-V7 in castration-resistant prostate cancer (CRPC). The purpose of this study was to understand whether other AR variants may be coexpressed with AR-V7 and promote resistance to AR-targeted therapies.Experimental Design: We utilized complementary short- and long-read sequencing of intact AR mRNA isoforms to characterize AR expression in CRPC models. Coexpression of AR-V7 and AR-V9 mRNA in CRPC metastases and circulating tumor cells was assessed by RNA-seq and RT-PCR, respectively. Expression of AR-V9 protein in CRPC models was evaluated with polyclonal antisera. Multivariate analysis was performed to test whether AR variant mRNA expression in metastatic tissues was associated with a 12-week progression-free survival endpoint in a prospective clinical trial of 78 CRPC-stage patients initiating therapy with the androgen synthesis inhibitor, abiraterone acetate.Results: AR-V9 was frequently coexpressed with AR-V7. Both AR variant species were found to share a common 3' terminal cryptic exon, which rendered AR-V9 susceptible to experimental manipulations that were previously thought to target AR-V7 uniquely. AR-V9 promoted ligand-independent growth of prostate cancer cells. High AR-V9 mRNA expression in CRPC metastases was predictive of primary resistance to abiraterone acetate (HR = 4.0; 95% confidence interval, 1.31-12.2; P = 0.02).Conclusions: AR-V9 may be an important component of therapeutic resistance in CRPC. Clin Cancer Res; 23(16); 4704-15. ©2017 AACR. ©2017 American Association for Cancer Research.

  13. Pre-treatment minority HIV-1 drug resistance mutations and long term virological outcomes: is prediction possible?

    PubMed

    Mzingwane, M L; Tiemessen, C T; Richter, K L; Mayaphi, S H; Hunt, G; Bowyer, S M

    2016-10-12

    Although the use of highly active antiretroviral therapy in HIV positive individuals has proved to be effective in suppressing the virus to below detection limits of commonly used assays, virological failure associated with drug resistance is still a major challenge in some settings. The prevalence and effect of pre-treatment resistance associated variants on virological outcomes may also be underestimated because of reliance on conventional population sequencing data which excludes minority species. We investigated long term virological outcomes and the prevalence and pattern of pre-treatment minority drug resistance mutations in individuals initiating HAART at a local HIV clinic. Patient's records of viral load results and CD4 cell counts from routine treatment monitoring were used and additional pre-treatment blood samples for Sanger sequencing were obtained. A selection of pre-treatment samples from individuals who experienced virological failure were evaluated for minority resistance associated mutations to 1 % prevalence and compared to individuals who achieved viral suppression. At least one viral load result after 6 months or more of treatment was available for 65 out of 78 individuals followed for up to 33 months. Twenty (30.8 %) of the 65 individuals had detectable viremia and eight (12.3 %) of them had virological failure (viral load > 1000 RNA copies/ml) after at least 6 months of HAART. Viral suppression, achieved by month 8 to month 13, was followed by low level viremia in 10.8 % of patients and virological failure in one patient after month 20. There was potentially reduced activity to Emtricitabine or Tenofovir in three out of the eight cases in which minority drug resistance associated variants were investigated but detectable viremia occurred in one of these cases while the activity of Efavirenz was generally reduced in all the eight cases. Early viral suppression was followed by low level viremia for some patients which may be an

  14. Accumulation of ALDH1-positive cells after neoadjuvant chemotherapy predicts treatment resistance and prognosticates poor outcome in ovarian cancer

    PubMed Central

    Debald, Manuel; Rostamzadeh, Babak; Thiesler, Thore; Schröder, Lars; Barchet, Winfried; Abramian, Alina; Kaiser, Christina; Kristiansen, Glen; Kuhn, Walther; Kübler, Kirsten

    2015-01-01

    Although ovarian cancer is a highly chemosensitive disease, it is only infrequently cured. One of the major reasons lies in the presence of drug-resistant cancer stem-like cells, sufficient to fuel recurrence. We phenotyped cancer stem-like cells by flow cytometry and immunohistochemistry in 55 matched samples before and after taxane/platinum-based neoadjuvant chemotherapy. All used markers of stemness (ALDH1, CD24, CD117, CD133) isolated low frequencies of malignant cells. ALDH1 was the most valuable marker for tracking stemness in vivo. The enrichment of ALDH1 expression after treatment was associated with a poor response to chemotherapy, with platinum resistance and independently prognosticated unfavorable outcome. Our results suggest that increased ALDH1 expression after treatment identifies patients with aggressive tumor phenotypes. PMID:25999351

  15. Accumulation of ALDH1-positive cells after neoadjuvant chemotherapy predicts treatment resistance and prognosticates poor outcome in ovarian cancer.

    PubMed

    Ayub, Tiyasha H; Keyver-Paik, Mignon-Denise; Debald, Manuel; Rostamzadeh, Babak; Thiesler, Thore; Schröder, Lars; Barchet, Winfried; Abramian, Alina; Kaiser, Christina; Kristiansen, Glen; Kuhn, Walther; Kübler, Kirsten

    2015-06-30

    Although ovarian cancer is a highly chemosensitive disease, it is only infrequently cured. One of the major reasons lies in the presence of drug-resistant cancer stem-like cells, sufficient to fuel recurrence. We phenotyped cancer stem-like cells by flow cytometry and immunohistochemistry in 55 matched samples before and after taxane/platinum-based neoadjuvant chemotherapy. All used markers of stemness (ALDH1, CD24, CD117, CD133) isolated low frequencies of malignant cells. ALDH1 was the most valuable marker for tracking stemness in vivo. The enrichment of ALDH1 expression after treatment was associated with a poor response to chemotherapy, with platinum resistance and independently prognosticated unfavorable outcome. Our results suggest that increased ALDH1 expression after treatment identifies patients with aggressive tumor phenotypes.

  16. Total body fat and central fat mass independently predict insulin resistance but not hyperandrogenemia in women with polycystic ovary syndrome.

    PubMed

    Tosi, Flavia; Di Sarra, Daniela; Kaufman, Jean-Marc; Bonin, Cecilia; Moretta, Rosa; Bonora, Enzo; Zanolin, Elisabetta; Moghetti, Paolo

    2015-02-01

    Obesity is a common feature of women with polycystic ovary syndrome (PCOS). The aim of this study was to assess the role of body fat on insulin resistance and androgen excess in these subjects. One hundred sixteen consecutive Caucasian women with PCOS, diagnosed by the Rotterdam criteria, underwent accurate assessment of clinical, anthropometric, hormonal, and metabolic features. In particular, total fat mass and fat distribution were assessed by dual-energy x-ray absorptiometry, serum-free T by liquid chromatography mass spectrometry and equilibrium dialysis and insulin sensitivity by the glucose clamp technique. Total fat mass and truncal fat were significantly higher in insulin-resistant than in insulin-sensitive PCOS subjects (+89% and +127%, respectively, both P < .001), and both tended to be higher in hyperandrogenemic than in normoandrogenemic women (+22% and +28%, respectively, P = .087 and P = .090). All parameters of adiposity correlated inversely with insulin sensitivity (P < .001) and directly with serum-free T (P ≤ .001). A statistically significant inverse relationship was observed between insulin sensitivity and serum-free T concentrations (r = -0.527, P < .001). In a multiple regression analysis, either total fat mass or truncal fat, in addition to serum-free T and age, were independent predictors of insulin sensitivity. However, insulin sensitivity, but not total fat mass or truncal fat, was an independent predictor of free T concentrations. These data suggest that body fat contributes to determining insulin resistance in PCOS women. However, the association between body fat and hyperandrogenism seems to be to a large extent explained by insulin resistance.

  17. Mechanics based model for predicting structure-induced rolling resistance (SRR) of the tire-pavement system

    NASA Astrophysics Data System (ADS)

    Shakiba, Maryam; Ozer, Hasan; Ziyadi, Mojtaba; Al-Qadi, Imad L.

    2016-11-01

    The structure-induced rolling resistance of pavements, and its impact on vehicle fuel consumption, is investigated in this study. The structural response of pavement causes additional rolling resistance and fuel consumption of vehicles through deformation of pavement and various dissipation mechanisms associated with inelastic material properties and damping. Accurate and computationally efficient models are required to capture these mechanisms and obtain realistic estimates of changes in vehicle fuel consumption. Two mechanistic-based approaches are currently used to calculate vehicle fuel consumption as related to structural rolling resistance: dissipation-induced and deflection-induced methods. The deflection-induced approach is adopted in this study, and realistic representation of pavement-vehicle interactions (PVIs) is incorporated. In addition to considering viscoelastic behavior of asphalt concrete layers, the realistic representation of PVIs in this study includes non-uniform three-dimensional tire contact stresses and dynamic analysis in pavement simulations. The effects of analysis type, tire contact stresses, pavement viscoelastic properties, pavement damping coefficients, vehicle speed, and pavement temperature are then investigated.

  18. Clinical prediction rule for identifying patients with vancomycin-resistant enterococci (VRE) at the time of admission to the intensive care unit in a low VRE prevalence setting.

    PubMed

    Yoon, Young Kyung; Kim, Hyeon Jeong; Lee, Won Jin; Lee, Sung Eun; Yang, Kyung Sook; Park, Dae Won; Sohn, Jang Wook; Kim, Min Ja

    2012-12-01

    The purpose of this study was to develop and validate a clinical prediction rule to screen patients at risk of vancomycin-resistant enterococci (VRE) carriage at intensive care unit (ICU) admission in a hospital setting with low VRE prevalence. This study was retrospectively conducted in the ICUs of a university-affiliated hospital in Korea, where active surveillance cultures for VRE had been run at ICU admission and weekly thereafter. In the derivation cohort from April 2008 to September 2010, risk factors for VRE carriage at ICU admission were determined and assigned weighted point values using a multivariate logistic regression model. In the validation cohort from October 2010 to March 2011, predictability of the prediction rule was evaluated. Of a total of 4445 cultures taken from patients at ICU admission, 153 (3.4%) patients carried VRE. In the derivation cohort, independent risk factors (assigned points) for VRE carriage at ICU admission were ICU readmission during hospitalization (1 point), chronic obstructive lung disease (2 points), recent antibiotic treatment (3 points) and recent vancomycin use (2 points). In the validation cohort, the sensitivity, specificity, and positive and negative predictive values of the prediction rule, on the basis of risk scores ≥3 points, were 84.2%, 82.5%, 15.2% and 99.3%, respectively. This clinical prediction rule for identifying VRE carriage at the time of ICU admission is expected to markedly reduce the screening volume (by 80.1%) in our healthcare facility. For use in clinical practice, the rule needs to be prospectively validated in other settings.

  19. Longitudinal Use of a Line Probe Assay for Human Immunodeficiency Virus Type 1 Protease Predicts Phenotypic Resistance and Clinical Progression in Patients Failing Highly Active Antiretroviral Therapy

    PubMed Central

    Servais, Jean; Lambert, Christine; Plesséria, Jean-Marc; Fontaine, Elodie; Robert, Isabelle; Arendt, Vic; Staub, Thérèse; Hemmer, Robert; Schneider, François; Schmit, Jean-Claude

    2002-01-01

    An observational study assessed the longitudinal use of a new line probe assay for the detection of protease mutations. Probe assays for detection of reverse transcriptase (Inno-LiPA HIV-1 RT; Innogenetics) and protease (prototype kit Inno-LiPA HIV Protease; Innogenetics) mutations gave results for 177 of 199 sequential samples collected over 2 years from 26 patients failing two nucleoside reverse transcriptase inhibitors and one protease inhibitor (first line: indinavir, n = 6; ritonavir, n = 10; and saquinavir, n = 10). Results were compared to recombinant virus protease inhibitor susceptibility data (n = 87) and to clinical and virological data. Combinations of protease mutations (M46I, G48V, I54V, V82A or -F, I84V, and L90M) predicted phenotypic resistance to the protease inhibitor and to nelfinavir. The sum of protease mutations was associated with virological and clinical outcomes from 6 and 3 months on, respectively. Moreover, a poorer clinical outcome was linked to the sum of reverse transcriptase mutations. In conclusion, despite the limited number of patients studied and the restricted number of codons investigated, probe assay-based genotyping correlates with phenotypic drug resistance and predicts new Centers for Disease Control and Prevention stage B and C clinical events and virological outcome. Line probe assays provide additional prognostic information and should be prospectively investigated for their potential for treatment monitoring. PMID:12019110

  20. Three-dimensional quantitative structure-activity relationship analysis of propafenone-type multidrug resistance modulators: influence of variable selection on test set predictivity.

    PubMed

    Fleischer, Romy; Wiese, Michael

    2003-11-06

    An extended set of multidrug-resistance modulators of the propafenone type were investigated using CoMFA and CoMSIA. A number of 3D-QSAR models were derived from steric, electrostatic, and hydrophobic fields and their combinations. The hydrophobic fields alone and in combination with the steric and both (steric and electrostatic) fields yielded the models with the highest cross-validated predictivity, in agreement with a previous analysis of a smaller data set of propafenone-type multidrug-resistance (MDR) modulators. Inclusion of lipophilicity did not lead to an improvement of the models. The results point to the importance of hydrophobicity as a space-directed molecular property for MDR-modulating activity. The influence of variable selection applying the GOLPE procedure was investigated with an external test set. Variable-selection procedure was repetitively applied, keeping at each stage variables with uncertain contribution to the models. For the CoMFA-based 3D-QSAR models, an increase in external prediction quality was found. In contrast, the CoMSIA-based 3D-QSAR models were not improved by the GOLPE variable-selection procedure.