Stability of folic acid and 5-methyltetrahydrofolic acid in phosphate buffer (0.2 M; pH 7) toward thermal (above 65 degrees C) and combined high pressure (up to 800 MPa)/thermal (20 up to 65 degrees C) treatments was studied on a kinetic basis. Residual folate concentration after thermal and high pressure/thermal treatments was measured using reverse phase liquid chromatography. The degradation of both folates followed first-order reaction kinetics. At ambient pressure, the estimated Arrhenius activation energy (E(a)) values of folic acid and 5-methyltetrahydrofolic acid thermal degradation were 51.66 and 79.98 kJ mol(-1), respectively. It was noticed that the stability of folic acid toward thermal and combined high pressure thermal treatments was much higher than 5-methyltetrahydrofolic acid. High-pressure treatments at room temperature or higher (up to 60 degrees C) had no or little effect on folic acid. In the whole P/T area studied, the rate constant of 5-methyltetrahydrofolic acid degradation was enhanced by increasing pressure, and a remarkable synergistic effect of pressure and temperature on 5-methyltetrahydrofolic acid degradation occurred at temperatures above 40 degrees C. A model to describe the combined pressure and temperature effect on the 5-methyltetrahydrofolic acid degradation rate constant is presented.

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Colorectal cancer (CRC) is the third leading cause of global cancer mortality. Recent studies have proposed several gene signatures to predict CRC prognosis, but none of those have proven reliable for predicting prognosis in clinical practice yet due to poor reproducibility and molecular heterogeneity. Here, we have established a prognostic signature of 113 probe sets (CRC-113) that include potential biomarkers and reflect the biological and clinical characteristics. Robustness and accuracy were significantly validated in external data sets from 19 centers in five countries. In multivariate analysis, CRC-113 gene signature showed a stronger prognostic value for survival and disease recurrence in CRC patients than current clinicopathological risk factors and molecular alterations. We also demonstrated that the CRC-113 gene signature reflected both genetic and epigenetic molecular heterogeneity in CRC patients. Furthermore, incorporation of the CRC-113 gene signature into a clinical context and molecular markers further refined the selection of the CRC patients who might benefit from postoperative chemotherapy. Conclusively, CRC-113 gene signature provides new possibilities for improving prognostic models and personalized therapeutic strategies.

Identification of a potential gene signature for improved diagnosis in non-small cell lung cancer (NSCLC) patient is necessary. Here, we aim to establish and validate the prognostic efficacy of a gene set that can predict prognosis and benefits of adjuvant chemotherapy (ACT) in NSCLC patients from various ethnicities. An 8-gene signature was calculated from the gene expression of 181 patients using univariate Cox proportional hazard regression analysis. The prognostic value of the signature was robustly validated in 1,477 patients from five microarray independent data sets and one RNA-seq data set. The 8-gene signature was identified as an independent predictor of patient survival in the presence of clinical parameters in univariate and multivariate analyses [hazard ratio (HR): 2.84, 95% confidence interval CI (1.74-4.65), p=3.06e-05, [HR] 2.62, 95% CI (1.51-4.53), p=0.001], respectively. Subset analysis demonstrated that the 8-gene signature could identify high-risk patients in stage II-III with improved survival from ACT [(HR) 1.47, 95% CI (1.01-2.14), p=0.044]. The 8-gene signature also stratified risk groups in EGFR-mutated and wild-type patients. In conclusion, the 8-gene signature is a strong and independent predictor that can significantly stratify patients into low- and high-risk groups. Our gene signature also has the potential to predict patients in stage II-III that are likely to benefit from ACT.

Patient diagnosis and care would be significantly improved by understanding the mechanisms underlying platinum and taxane resistance in ovarian cancer. Here, we aim to establish a gene signature that can identify molecular pathways/transcription factors involved in ovarian cancer progression, poor clinical outcome, and chemotherapy resistance. To validate the robustness of the gene signature, a meta-analysis approach was applied to 1,020 patients from 7 datasets. A 97-gene signature was identified as an independent predictor of patient survival in association with other clinicopathological factors in univariate [hazard ratio (HR): 3.0, 95% Confidence Interval (CI) 1.66–5.44, p = 2.7E-4] and multivariate [HR: 2.88, 95% CI 1.57–5.2, p = 0.001] analyses. Subset analyses demonstrated that the signature could predict patients who would attain complete or partial remission or no-response to first-line chemotherapy. Pathway analyses revealed that the signature was regulated by HIF1α and TP53 and included nine HIF1α-regulated genes, which were highly expressed in non-responders and partial remission patients than in complete remission patients. We present the 97-gene signature as an accurate prognostic predictor of overall survival and chemoresponse. Our signature also provides information on potential candidate target genes for future treatment efforts in ovarian cancer.

Precipitation data of finer timescale and higher spatial density are crucial for continuous hydrological modelling and flood risk assessment. Disaggregation methods are often used to transform the coarser‐timescale precipitation data into finer resolutions. The nonparametric approach based on method of fragments (MOF) has received broad attention in precipitation disaggregation literature, given its superiority in reproducing the at‐site statistical attributes. However, a detailed literature review has shown that the MOF‐based resampling approaches are mainly focused in the single‐site precipitation disaggregation context, which may subject to limitations such as the unavailability of at‐site precipitation records and the incapability to preserve the inter‐site correlation structure. To address these issues, we propose three resampling approaches based on MOF. The first approach is a single‐site interval‐based resampling approach which only draws subdaily fragment vectors from at‐site record. The second one extends the first one to a regionalized version where subdaily fragment vectors are drawn from both the at‐site and neighbouring stations. The third one is a multi‐site approach developed to preserve the observed inter‐site correlation. The performances of the three methods are evaluated with applications to daily‐to‐hourly precipitation disaggregation at six rain gauges in Singapore and eight precipitation stations in Wangkuai reservoir catchment in northern China. An elaborate list of performance measures, including standard validation statistics, spatial correlation, inter‐day connectivity, annual extreme analysis, and intra‐day dry and wet spell characteristics are used to assess the performance. The proposed three methods are shown to be effective in reproducing the at‐site attributes, and no significant deterioration of performance is observed when moving from the single‐site method to the regionalized and multi‐site versions. As expected, the multi‐site approach is the only one method that is able to reconstruct the spatial correlation in the disaggregated precipitation field. The approaches can be applied for daily‐to‐subdaily precipitation disaggregation in different regions.

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Colorectal cancer (CRC) is one of the leading causes of cancer-related deaths worldwide. Chemoresistance is a major problem for effective therapy in CRC. Here, we investigated the mechanism by which peptidylprolyl isomerase B (PPIB; cyclophilin B, CypB) regulates chemoresistance in CRC. We found that CypB is a novel wild-type p53 (p53WT)-inducible gene but a negative regulator of p53WT in response to oxaliplatin treatment. Overexpression of CypB shortens the half-life of p53WT and inhibits oxaliplatin-induced apoptosis in CRC cells, whereas knockdown of CypB lengthens the half-life of p53WT and stimulates p53WT-dependent apoptosis. CypB interacts directly with MDM2, and enhances MDM2-dependent p53WT ubiquitination and degradation. Furthermore, we firmly validated, using bioinformatics analyses, that overexpression of CypB is associated with poor prognosis in CRC progression and chemoresistance. Hence, we suggest a novel mechanism of chemoresistance caused by overexpressed CypB, which may help to develop new anti-cancer drugs. We also propose that CypB may be utilized as a predictive biomarker in CRC patients. Copyright © 2018 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.