Solvent effect in polymer analysis by MALDI-TOF mass spectrometry

<p>Solvent effect is one of the important factors in sample preparation which may affect matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectra of synthetic polymers. MALDI imaging, a useful imaging tool for discovering biomarkers in tissues, is applied here for better comprehension of solvent effect in polymer analysis by MALDI-TOF mass spectrometry. Nylon-6 was chosen as a model polymer for the study of solvent effect. Its MALDI mass spectra in different solvents were performed. MALDI imaging analysis was performed for studying the incorporation of analytes into matrix crystals in different solvent combinations. Specifically, the colocalization of matrix and analyte was obtained through Pearson’s correlation (PC) coefficient analysis of their MALDI images. The results demonstrated that satisfactory spectra were obtained in higher PC value conditions. PC decreased along with an increase in the ratio of poor solvent, which suggested that we should minimize the poor solvent ratio to obtain better MALDI spectra.</p

A Robust Near-Infrared Calibration Model for the Determination of Chlorophyll Concentration in Tree Leaves with a Calibration Transfer Method

<div><p>A method based on piecewise direct standardization was developed to directly predict leaf chlorophyll concentrations by correction of near-infrared spectra to construct a robust calibration model. Chinar, camphor, and gingko leaves collected from two growth intervals were evaluated. Spectral pretreatment methods and wavelength selection were investigated. The first derivative combined with stability competitive adaptive reweighted sampling before piecewise direct standardization provided the best performance. Under the optimized parameters, the root mean square error of prediction was significantly reduced by using piecewise direct standardization. This study demonstrates that the calibration model may be used to rapidly characterize chlorophyll concentrations across species and growth intervals.</p></div

Meta-Analysis of the Prognostic Value of Smad4 Immunohistochemistry in Various Cancers

<div><p>Background</p><p>Accumulating evidence indicates that Smad4 (DPC4) plays a fundamental role in the development and prognosis of several types of cancer. The objective of this study was to conduct a meta-analysis to evaluate whether the loss of Smad4 staining could serve as a prognostic marker.</p><p>Methods</p><p>A comprehensive meta-analysis was conducted using major useful databases to determine the relationship between the immunohistochemical detection of Smad4 and the survival of patients with various cancers. We used hazard ratios (HRs) with 95% confidence interval (CIs) as the effect estimation to evaluate the association of Smad4 with overall survival (OS), cancer-specific survival (CSS) or recurrence-free survival (RFS). The relationship between the clinical characteristics of patients and Smad4 was also evaluated using the odds ratio (OR).</p><p>Results</p><p>A total of 7570 patients from 26 studies were included in the analysis. The pooled results showed that loss of Smad4 staining was a negative predictor of OS with an HR of 1.97 (95% CI: 1.55–2.51; P_{heterogeneity}<0.001) and CSS/RFS (HR = 1.81; 95% CI: 1.30–2.54; P_{heterogeneity}<0.001). In addition, loss of Smad4 staining was more likely to be found in older (OR = 1.69, 95% CI: 1.09–2.61; P_{heterogeneity} = 0.648) colorectal cancer patients with a late tumor stage (OR = 2.31, 95% CI: 1.71–3.10; P_{heterogeneity} = 0.218) and in gastric cancer patients with lymph node metastasis (OR = 2.11, 95% CI: 1.03–4.34; P_{heterogeneity} = 0.038).</p><p>Conclusion</p><p>Based on these results, our meta-analysis provided evidence that loss of Smad4 staining could act as an unfavorable biomarker in the prognosis of various cancers and should be used as a powerful tool in future clinical trials.</p></div

Effect of individual studies on the pooled hazard ratio (HR) for OS (A) and RFS/CSS (B).

<p>Effect of individual studies on the pooled hazard ratio (HR) for OS (A) and RFS/CSS (B).</p

Begg's funnel plots for all of the included studies reported with OS (A) and RFS/CSS (B).

<p>Begg's funnel plots for all of the included studies reported with OS (A) and RFS/CSS (B).</p

Forest plots of studies evaluating the association between Smad4 and clinical parameters.

<p>In gastric cancer (A): histology (left; differentiated vs. undifferentiated); lymph node (right; absent vs. present). In colorectal cancer (B): age (left; old vs. young); gender (middle; male vs. female); TNM stage (right; advanced vs. early). In pancreatic cancer (C): differentiation (left; well/moderate vs. poor); lymph node (middle; absent vs. present); tumor size (right; small vs. large).</p

Methodological flow diagram of the meta-analysis.

<p>Methodological flow diagram of the meta-analysis.</p

Main characteristics of the studies included in this meta-analysis.

<p>NA: not available.</p><p>Main characteristics of the studies included in this meta-analysis.</p

Meta-analysis results.

<p>OS: overall survival; CSS: cancer-specific survival; RFS: recurrence-free survival; HR: hazard ratio; CI: confidence interval; Small: studies with less than 200 participants; Large: studies with more than 200 participants.</p><p>Meta-analysis results.</p

Prognostic Value of PLR in Various Cancers: A Meta-Analysis

<div><p>Background</p><p>Recently, more and more studies investigated the association of inflammation parameters such as the Platelet Lymphocyte Ratio (PLR) and the prognosis of various cancers. However, the prognostic role of PLR in cancer remains controversial.</p><p>Methods</p><p>We conducted a meta-analysis of published studies to evaluate the prognostic value of PLR in various cancers. In order to investigate the association between PLR and overall survival (OS), the hazard ratio (HR) and its 95% confidence interval (CI) were calculated.</p><p>Results</p><p>A total of 13964 patients from 26 studies were included in the analysis. The summary results showed that elevated PLR was a negative predictor for OS with HR of 1.60 (95%CI: 1.35–1.90; P_{heterogeneity} <0.001). Subgroup analysis revealed that increased PLR was a negative prognostic marker in patients with gastric cancer (HR = 1.35, 95%CI: 0.80–2.25, P_{heterogeneity} = 0.011), colorectal cancer (HR = 1.65, 95%CI: 1.33–2.05, P_{heterogeneity} = 0.995), hepatocellular carcinoma (HR = 3.07, 95% CI: 2.04–4.62, P_{heterogeneity} = 0.133), ovarian cancer (HR = 1.57, 95%CI: 1.07–2.31, P_{heterogeneity} = 0.641) and non-small cell lung cancer (NSCLC) (HR = 1.85, 95% CI: 1.42–2.41, P_{heterogeneity} = 0.451) except for pancreatic cancer (HR = 1.00, 95%CI: 0.92–1.09, P_{heterogeneity} = 0.388).</p><p>Conclusion</p><p>The meta-analysis demonstrated that PLR could act as a significant biomarker in the prognosis of various cancers.</p></div