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73421por Kesseli, Samuel J., Gloria, Jared N., Abraham, Nader, Halpern, Samantha E., Cywinska, Greta N., Zhang, Min, Moris, Dimitrios, Schmitz, Robin, Shaw, Brian I., Fitch, Zachary W., Song, Mingqing, Guy, Cynthia D., Hartwig, Mathew G, Knechtle, Stuart, Barbas, Andrew S.“…Perfusate lactate clearance does not discriminate between viable and nonviable livers during NMP. …”
Publicado 2021
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73422“…The aim of this study was to examine the possibility of 1H-MRS to discriminate malignant from benign breast lesions, using elevated choline (Cho) peak as an imaging biomarker. …”
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73423por Kühn, Jan Philipp, Schmid, Wendelin, Körner, Sandrina, Bochen, Florian, Wemmert, Silke, Rimbach, Hugo, Smola, Sigrun, Radosa, Julia Caroline, Wagner, Mathias, Morris, Luc G.T., Bozzato, Victoria, Bozzato, Alessandro, Schick, Bernhard, Linxweiler, Maximilian“…P16-IHC alone showed the best performance for discriminating between good (high expression) vs poor outcome (low expression; p = 0.0030) in OPSCC patients. …”
Publicado 2021
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73424por Flores-López, María, García-Marchena, Nuria, Pavon, Francisco Javier, Lara, Estrella, Porras-Perales, Oscar, Araos, Pedro, Requena-Ocaña, Nerea, Torres-Galván, Sandra, Mañas-Padilla, M. Carmen, Rubio, Gabriel, Suárez, Juan, Santín, Luis J., Rodríguez de Fonseca, Fernando, Castilla-Ortega, Estela, García-Fernández, María I., Serrano, Antonia“…LPA and ATX were log(10)-transformed to fit the assumptions of parametric testing.The main results were as follows: total LPA and ATX concentrations were dysregulated in the alcohol group, and patients with AUD had significantly lower LPA (F((1,131)) = 10.677, p = 0.001) and higher ATX (F((1,131)) = 8.327, p = 0.005) concentrations than control subjects; patients with AUD and liver disease had significantly higher ATX concentrations (post hoc test, p < 0.05) than patients with AUD but not liver disease; significant correlations between AUD-related variables and concentrations of LPA and ATX were only found in the non-liver disease subgroup (the duration of alcohol abstinence with LPA and ATX (r = +0.33, p < 0.05); and the severity of AUD with ATX (rho = −0.33, p < 0.05)); and a logistic regression model with LPA, ATX, and AUD-related variables showed an excellent discriminative power (area under the curve (AUC) = 0.915, p < 0.001) for distinguishing patients with AUD and comorbid liver disease. …”
Publicado 2021
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73425“…We first used six blood-based biomarkers to construct a composite measure of the Chinese Healthy Aging Index (CHAI, ranging from 0 (healthiest) to 12 (unhealthiest)) and then assessed the psychometric properties of the CHAI score, including acceptability, internal consistency, convergent validity, discriminative validity and precision. In addition, we employed both mean-based Blinder–Oaxaca and unconditional quantile regression decomposition to decompose the change in healthy aging within the 2011–2015 period. …”
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73426por Chang, Li-Chun, Hsu, Yi-Chiung, Chiu, Han-Mo, Ueda, Koji, Wu, Ming-Shiang, Kao, Chiun-How, Shen, Tang-Long“…Moreover, the six identified specific sEV proteins had the potential to discriminate colorectal neoplasia between early-stage and advanced neoplasia. …”
Publicado 2021
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73427por Dai, Guyu, Zhang, Xiangbin, Liu, Wenjie, Li, Zhibin, Wang, Guangyu, Liu, Yaxin, Xiao, Qing, Duan, Lian, Li, Jing, Song, Xinyu, Li, Guangjun, Bai, Sen“…The best ML 3 model was linear discriminant classifier (LDC), which achieved accuracies of 0.903, 0.792, 0.870, 0.931, and 0.671, respectively. …”
Publicado 2021
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73428“…We consider that somatic awareness is an important sensory-discriminative factor to be taken into account in this group of patients. …”
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73429por Fervers, Philipp, Celik, Erkan, Bratke, Grischa, Maintz, David, Baues, Christian, Ruffing, Simon, Pollman-Schweckhorst, Philip, Kottlors, Jonathan, Lennartz, Simon, Große Hokamp, Nils“…Receiver operating characteristic (ROC) analysis was performed to discriminate irradiated vs. non-irradiated and locally progressive vs. stable/responsive LBLs using absolute attenuation post-irradiation and percentage attenuation change for patients with pre-irradiation DECT, if available. …”
Publicado 2021
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73430por Romano, Mariele, Bravin, Alberto, Mittone, Alberto, Eckhardt, Alicia, Barbone, Giacomo E., Sancey, Lucie, Dinkel, Julien, Bartzsch, Stefan, Ricke, Jens, Alunni-Fabbroni, Marianna, Hirner-Eppeneder, Heidrun, Karpov, Dmitry, Giannini, Cinzia, Bunk, Oliver, Bouchet, Audrey, Ruf, Viktoria, Giese, Armin, Coan, Paola“…Brains were analyzed post mortem by multi-scale X-ray Phase Contrast Imaging–Computed Tomography (XPCI-CT), histology, immunohistochemistry, X-ray Fluorescence (XRF), Small- and Wide-Angle X-ray Scattering (SAXS/WAXS). XPCI-CT discriminates with high sensitivity the effects of MRT, MB and BB irradiations on both healthy and GBM-bearing brains producing a first-time 3D visualization and morphological analysis of the radio-induced lesions, MRT and MB induced tissue ablations, the presence of hyperdense deposits within specific areas of the brain and tumor evolution or regression with respect to the evaluation made few days post-irradiation with an in-vivo magnetic resonance imaging session. …”
Publicado 2021
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73431por Naya-Català, Fernando, do Vale Pereira, Gabriella, Piazzon, M. Carla, Fernandes, Ana Margarida, Calduch-Giner, Josep Alvar, Sitjà-Bobadilla, Ariadna, Conceição, Luis E. C., Pérez-Sánchez, Jaume“…Bacterial richness and alpha diversity were lower in fish fed with the PAP diet, and discriminant analysis displayed 135 OTUs driving the separation between groups with 43 taxa correlating with 27 DE genes. …”
Publicado 2021
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73432“…The inflammatory panel could discriminate between WHO grades, and isocitrate-dehydrogenase-mutant/wildtype and define differential survival between astrocytic isocitrate-dehydrogenase-mutant/wildtype. …”
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73433por Lapp, Zena, Han, Jennifer H., Wiens, Jenna, Goldstein, Ellie J. C., Lautenbach, Ebbing, Snitkin, Evan S.“…We used machine learning to determine whether patient and/or microbial characteristics can discriminate between CRKP extraintestinal colonization and infection across multiple health care facilities and found that both patient and microbial factors were predictive. …”
Publicado 2021
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73434por Grønseth, Stine, Rogne, Tormod, Hannula, Raisa, Åsvold, Bjørn Olav, Afset, Jan Egil, Damås, Jan Kristian“…We assessed the ability of an in-house semiquantitative real-time PCR assay to discriminate Pneumocystis pneumonia (PCP) from colonization and identified risk factors for infection in these patients. …”
Publicado 2021
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73435por Brycki, Joshua D., Chen See, Jeremy R., Letson, Gillian R., Emlet, Cade S., Unverdorben, Lavinia V., Heibeck, Nathan S., Brislawn, Colin J., Buonaccorsi, Vincent P., Chan, Jason P., Lamendella, Regina“…Differential analysis of the E. coli transcriptome yielded 22 Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways and 100 KEGG genes enriched when samples were grouped by time point [LDA, linear discriminant analysis; log(LDA), ≥2; P ≤ 0.05], including several involved in biofilm formation. …”
Publicado 2021
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73436por Wen, Yuqi, Feng, Le, Wang, Haorun, Zhou, Hu, Li, Qianqian, Zhang, Wenyan, Wang, Ming, Li, Yeming, Luan, Xingzhao, Jiang, Zengliang, Chen, Ligang, Zhou, Jie“…We further identified five oral microbial features (Capnocytophaga Porphyromonas, Haemophilus, Leptotrichia, and TM7x) that accurately discriminated HGG from LGG (area under the curve [AUC]: 0.63, 95% confidence interval [CI]: 0.44–0.83) and HCs (AUC: 0.79, 95% CI: 0.68–0.92). …”
Publicado 2021
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73437por Wen, Sihui, Cheng, Shenghao, Xie, Shaobing, Zhang, Hua, Xie, Zhihai, Jiang, Weihong“…Multivariate analysis and receiver operating characteristic (ROC) curve were performed to evaluate the value of serum YKL-40 in discriminating eosinophilic CRSwNP (eCRSwNP) and predicting postoperative recurrence. …”
Publicado 2021
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73438por Nochaiwong, Surapon, Ruengorn, Chidchanok, Awiphan, Ratanaporn, Kanjanarat, Penkarn, Ruanta, Yongyuth, Phosuya, Chabaphai, Boonchieng, Waraporn, Nanta, Sirisak, Chongruksut, Wilaiwan, Thavorn, Kednapa, Wongpakaran, Nahathai, Wongpakaran, Tinakon“…The correlation statistics between the COVID-PSS and the Pain Intensity Scale and Insomnia Severity Index were <0.2, supporting the discriminant validity. The reliability of the COVID-PSS was satisfactory, with good internal consistency (Cronbach’s α of 0.85, 95% CI 0.84 to 0.86) and test–retest reproducibility (intraclass correlation of 0.94, 95% CI 0.86 to 0.96). …”
Publicado 2021
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73439por Yeo, Tianrong, Probert, Fay, Sealey, Megan, Saldana, Luisa, Geraldes, Ruth, Höckner, Sebastian, Schiffer, Eric, Claridge, Timothy D W, Leppert, David, DeLuca, Gabriele, Kuhle, Jens, Palace, Jacqueline, Anthony, Daniel C“…Multivariable receiver operating characteristics analysis of these four metabolites in discriminating R versus LR ≥ 24 M showed an area under the curve of 0.758, while the area under the curve for serum neurofilament-light chain was 0.575. …”
Publicado 2021
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73440por Qiu, Shen-Zhong, Zheng, Guan-Rong, Ma, Cai-Yan, Chen, Bin, Huang, Jian-Jun, Huang, Ge, Hua, Hai“…Serum S100A12 levels were substantially higher in patients with a poor outcome (median, 66.5 versus 37.7 ng/mL; P < 0.001) or early neurological deterioration (median, 76.5 versus 40.1 ng/mL; P < 0.001) than in the other remainders, independently predicted a poor outcome (odds ratio, 1.035; 95% confidence interval, 1.007–1.064; P = 0.015) and early neurologic deterioration (odds ratio,1.032; 95% confidence interval, 1.003–1.060; P = 0.027), and significantly discriminated a poor outcome (area under curve, 0.794; 95% confidence interval, 0.702–0.868) and early neurologic deterioration (area under curve, 0.760; 95% confidence interval, 0.664–0.839) under receiver operating characteristic curve. …”
Publicado 2021
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