| 1. |
- Thean, Lai Fun, et al.
(författare)
-
Enhancer-derived long non-coding RNAs CCAT1 and CCAT2 at rs6983267 has limited predictability for early stage colorectal carcinoma metastasis
- 2021
-
Ingår i: Scientific Reports. - : Nature Publishing Group. - 2045-2322. ; 11:1
-
Tidskriftsartikel (refereegranskat)abstract
- Up-regulation of long non-coding RNAs (lncRNAs), colon-cancer associated transcript (CCAT) 1 and 2, was associated with worse prognosis in colorectal cancer (CRC). Nevertheless, their role in predicting metastasis in early-stage CRC is unclear. We measured the expression of CCAT1, CCAT2 and their oncotarget, c-Myc, in 150 matched mucosa-tumour samples of early-stage microsatellite-stable Chinese CRC patients with definitive metastasis status by multiplex real-time RT-PCR assay. Expression of CCAT1, CCAT2 and c-Myc were significantly up-regulated in the tumours compared to matched mucosa (p < 0.0001). The expression of c-Myc in the tumours was significantly correlated to time to metastasis [hazard ratio = 1.47 (1.10–1.97)] and the risk genotype (GG) of rs6983267, located within CCAT2. Expression of c-Myc and CCAT2 in the tumour were also significantly up-regulated in metastasis-positive compared to metastasis-negative patients (p = 0.009 and p = 0.04 respectively). Nevertheless, integrating the expression of CCAT1 and CCAT2 by the Random Forest classifier did not improve the predictive values of ColoMet19, the mRNA-based predictor for metastasis previously developed on the same series of tumours. The role of these two lncRNAs is probably mitigated via their oncotarget, c-Myc, which was not ranked high enough previously to be included in ColoMet19.
|
|
| 2. |
- Aberg, Fredrik, et al.
(författare)
-
A Dynamic Aspartate-to-Alanine Aminotransferase Ratio Provides Valid Predictions of Incident Severe Liver Disease
- 2021
-
Ingår i: HEPATOLOGY COMMUNICATIONS. - : John Wiley & Sons. - 2471-254X. ; 5:6, s. 1021-1035
-
Tidskriftsartikel (refereegranskat)abstract
- The aspartate-to-alanine aminotransferase ratio (AAR) is associated with liver fibrosis, but its predictive performance is suboptimal. We hypothesized that the association between AAR and liver disease depends on absolute transaminase levels and developed and validated a model to predict liver-related outcomes in the general population. A Cox regression model based on age, AAR, and alanine aminotransferase (ALT) level (dynamic AAR [dAAR]) using restricted cubic splines was developed in Finnish population-based health-examination surveys (FINRISK, 2002-2012; n = 18,067) with linked registry data for incident liver-related hospitalizations, hepatocellular carcinoma, or liver death. The model was externally validated for liver-related outcomes in a Swedish population cohort (Swedish Apolipoprotein Mortality Risk [AMORIS] subcohort; n = 126,941) and for predicting outcomes and/or prevalent fibrosis/cirrhosis in biopsied patients with nonalcoholic fatty liver disease (NAFLD), chronic hepatitis C, or alcohol-related liver disease (ALD). The dynamic AAR model predicted liver-related outcomes both overall (optimism-corrected C-statistic, 0.81) and in subgroup analyses of the FINRISK cohort and identified persons with >10% risk for liver-related outcomes within 10 years. In independent cohorts, the C-statistic for predicting liver-related outcomes up to a 10-year follow-up was 0.72 in the AMORIS cohort, 0.81 in NAFLD, and 0.75 in ALD. Area-under-the-curve (AUC) for detecting prevalent cirrhosis was 0.80-0.83 in NAFLD, 0.80 in hepatitis C, but only 0.71 in ALD. In ALD, model performance improved when using aspartate aminotransferase instead of ALT in the model (C-statistic, 0.84 for outcome; AUC, 0.82 for prevalent cirrhosis). Conclusion: A dAAR score provides prospective predictions for the risk of incident severe liver outcomes in the general population and helps detect advanced liver fibrosis/cirrhosis. The dAAR score could potentially be used for screening the unselected general population and as a trigger for further liver evaluations.
|
|
| 3. |
- Falster, Daniel, et al.
(författare)
-
AusTraits, a curated plant trait database for the Australian flora
- 2021
-
Ingår i: Scientific Data. - : Nature Portfolio. - 2052-4463. ; 8:1
-
Tidskriftsartikel (refereegranskat)abstract
- We introduce the AusTraits database - a compilation of values of plant traits for taxa in the Australian flora (hereafter AusTraits). AusTraits synthesises data on 448 traits across 28,640 taxa from field campaigns, published literature, taxonomic monographs, and individual taxon descriptions. Traits vary in scope from physiological measures of performance (e.g. photosynthetic gas exchange, water-use efficiency) to morphological attributes (e.g. leaf area, seed mass, plant height) which link to aspects of ecological variation. AusTraits contains curated and harmonised individual- and species-level measurements coupled to, where available, contextual information on site properties and experimental conditions. This article provides information on version 3.0.2 of AusTraits which contains data for 997,808 trait-by-taxon combinations. We envision AusTraits as an ongoing collaborative initiative for easily archiving and sharing trait data, which also provides a template for other national or regional initiatives globally to fill persistent gaps in trait knowledge.
|
|
