Performance of several simple, noninvasive models for assessing significant liver fibrosis in patients with chronic hepatitis B

Aim To compare the performance of several simple, noninvasive models comprising various serum markers in diagnosing significant liver fibrosis in the same sample of patients with chronic hepatitis B (CHB) with the same judgment standard. Methods A total of 308 patients with CHB who had undergone liver biopsy, laboratory tests, and liver stiffness measurement (LSM) at the Southwest Hospital, Chongqing, China between March 2010 and April 2014 were retrospectively studied. Receiver operating characteristic (ROC) curves and area under ROC curves (AUROCs) were used to analyze the results of the models, which incorporated ageplatelet (PLT) index (API model), aspartate transaminase (AST) to alanine aminotransferase (ALT) ratio (AAR model), AST to PLT ratio index (APRI model), γ-glutamyl transpeptidase (GGT) to PLT ratio index (GPRI model), GGT-PLT-albumin index (S index model), age-AST-PLT-ALT index (FIB-4 model), and age-AST-PLT-ALT-international normalized ratio index (Fibro-Q model). Results The AUROCs of the S index, GPRI, FIB-4, APRI, API, Fibro-Q, AAR, and LSM for predicting significant liver fibrosis were 0.726 (P < 0.001), 0.726 (P < 0.001), 0.621 (P = 0.001), 0.619 (P = 0.001), 0.580 (P = 0.033), 0.569 (P = 0.066), 0.495 (P = 0.886), and 0.757 (P < 0.001), respectively. The S index and GPRI had the highest correlation with histopathological scores (r = 0.373, P < 0.001; r = 0.372, P < 0.001, respectively) and LSM values (r = 0.516, P < 0.001; r = 0.513, P < 0.001, respectively). When LSM was combined with S index and GPRI, the AUROCs were 0.753 (P < 0.001) and 0.746 (P < 0.001), respectively. Conclusion S index and GPRI had the best diagnostic performance for significant liver fibrosis and were robust predictors of significant liver fibrosis in patients with CHB for whom transient elastography was unavailable

Prognostic value of the distance between the primary tumor and brainstem in the patients with locally advanced nasopharyngeal carcinoma

BACKGROUND: Brainstem dose limitations influence radiation dose reaching to tumor in the patients with locally-advanced nasopharyngeal cancer (NPC). METHODS: A retrospective analysis of the prognostic value of the distance between the primary tumor and brainstem (Dbs) in 358 patients with locally-advanced NPC after intensity-modulated radiation therapy (IMRT). Receiver operating characteristic (ROC) curves were used to identify the cut-off value to analyze the impact of Dbs on tumor dose coverage and prognosis. RESULTS: The three-year overall survival (OS), local relapse-free survival (LRFS), distant metastasis-free survival (DMFS), and disease-free survival (DFS) were 88.8 vs. 78.4 % (P = 0.007), 96.5 vs. 91.1 % (P = 0.018), 87.8 vs. 79.3 % (P = 0.067), and 84.1 vs. 69.6 % (P = 0.002) for the patients with the Dbs > 4.7 vs. ≤ 4.7 mm, respectively. ROC curves revealed Dbs (4.7 mm) combined with American Joint Committee on Cancer (AJCC) T classification had a significantly better prognostic value for OS (P < 0.05). CONCLUSIONS: Dbs (≤4.7 mm) is an independent negative prognostic factor for OS/LRFS/DFS and enhances the prognostic value of T classification in the patients with locally-advanced NPC

Amino-Acid Network Clique Analysis of Protein Mutation Non-Additive Effects: A Case Study of Lysozme

Optimizing amino-acid mutations in enzyme design has been a very challenging task in modern bio-industrial applications. It is well known that many successful designs often hinge on extensive correlations among mutations at different sites within the enzyme, however, the underpinning mechanism for these correlations is far from clear. Here, we present a topology-based model to quantitively characterize non-additive effects between mutations. The method is based on the molecular dynamic simulations and the amino-acid network clique analysis. It examines if the two mutation sites of a double-site mutation fall into to a 3-clique structure, and associates such topological property of mutational site spatial distribution with mutation additivity features. We analyzed 13 dual mutations of T4 phage lysozyme and found that the clique-based model successfully distinguishes highly correlated or non-additive double-site mutations from those additive ones whose component mutations have less correlation. We also applied the model to protein Eglin c whose structural topology is significantly different from that of T4 phage lysozyme, and found that the model can, to some extension, still identify non-additive mutations from additive ones. Our calculations showed that mutation non-additive effects may heavily depend on a structural topology relationship between mutation sites, which can be quantitatively determined using amino-acid network k-cliques. We also showed that double-site mutation correlations can be significantly altered by exerting a third mutation, indicating that more detailed physicochemical interactions should be considered along with the network clique-based model for better understanding of this elusive mutation-correlation principle

Transcriptomic Analysis of <i>Medicago truncatula</i> under Long-Day Conditions

The objective of this research was to understand the expression characteristics and biological functions of Medicago truncatula genes under long-day conditions. The leaves of “R108” tribulus Medicago truncatula at the branch stage (A), bud stage (B), initial flowering stage (C), and full flowering stage (D) were sequenced using RNA-Seq technology. The genome of Medicago truncatula, a related species of Medicago truncatula, was used as the reference genome for sequence comparison. The transcriptomes of three adjacent periods (A vs. B, B vs. C, and C vs. D) were analyzed for differential gene expression and these genes were screened. A total of 6875 differentially expressed genes were detected. GO functional analysis showed that differentially expressed genes were mainly involved in biological processes, cell components, and molecular functions, among which the most differentially expressed genes were involved in the synthesis of cell components. KEGG enrichment analysis showed that the differentially expressed genes were mainly involved in circadian rhythm, photosynthetic antenna protein, ribosome metabolism, and other pathways. The number of single nucleotide variants detected by cSNP analysis was 312,875, and the frequency of A/G and C/T were the highest. The function of eggNOG was divided into 23 categories, with a total of 26,745 genes having similarities, while 9008 genes were classified as having an unknown function, 2669 genes were classified as part of signal transduction mechanisms, and 2194 genes were classified as being involved in transcription. In different developmental stages (A vs. B, B vs. C, and C vs. D), 3463 up-regulated and 3412 down-regulated differentially expressed genes were found. The difference between up-regulated and down-regulated genes was more noteworthy at the bud stage and the initial flowering stage. In addition, a total of 79 flowering genes were found, of which 51 differential genes were identified as participating in the photoperiodic regulation pathway, consisting of 23 differential genes that were up-regulated, and 28 differential genes that were down-regulated. The ratios of gene-LOC11410562(GI), gene-LOC11435974(CO), gene-LOC11422615(TOC1), and gene-LOC11432385(LHY) were higher than those of gene-LOC25500742(PHYA) and gene-LOC11 431402(ELF3); gene-LOC11434778(Col13), gene-LOC25498015(Col6), and gene-LOC11415514(Col9) were pre-expressed. The above differentially expressed genes were significantly expressed in different developmental stages of Medicago truncatula, which lays a foundation for further study of the molecular mechanism of Medicago truncatula