A Novel Substrate-Inspired Fluorescence-Based Albumin Detection Improves Assessment of Clinical Outcomes in Hemodialysis Patients Receiving a Nursing Nutrition Intervention.

BACKGROUND Albumin level does not precisely reflect nutritional status. We aimed to investigate the impact of a nutrition intervention on hemodialysis patients by use of fluorescence-based plasma albumin (FPA) detection. MATERIAL AND METHODS Eighty patients underwent maintenance hemodialysis for more than half a year and had a mean albumin <3.5 g/dL for over 3 months. The subjects were randomly divided into either a Control Group (CG) or an Intervention Group (IG). The IG received nutritional supplementation, and the CG group received routine nutritional support for 12 months. FPA and plasma albumin (PA) concentrations were measured. The fluorescence probe 1,3-Dichloro-7-hydroxy-9,9-dimethyl-2(9H)-acridone methyl biphenyl benzoate was used in FPA detection. Quality of life was estimated using WHOQOL-BREF (Quality of Life Scale developed through the World Health Organization), the 36-Item Short-Form Survey (SF-36), and the 6-minute walking test (6MWT). RESULTS After a 6-month and a 12-month intervention, PA and FPA concentrations increased, and the increase in FPA concentration was higher than that of PA in the IG group (P<0.05). Comparatively, the parameters of quality of life and 6MWT were improved in the IG group (P<0.05) but there were only minor changes in the CG group (P>0.05). There is an obvious association between the changes in FPA concentration and the parameters of quality of life and 6MWT but not PA. CONCLUSIONS Use of the fluorescence probe improves the detection sensitivity of plasma albumin and provides a potential method to assess clinical outcomes in hemodialysis patients.

Quantitative assessment of the diagnostic role of mucin family members in pancreatic cancer: a meta-analysis.

BACKGROUND: The use of mucins (MUC) as specific biomarkers for various malignancies has recently emerged. MUC1, MUC4, MUC5AC, and MUC16 can be detected at different stages of pancreatic cancer (PC), and can be valuable for indicating the initiation and progression of this disease. However, the diagnostic significance of the mucin family in patients with PC remains disputed. Herein, we assessed the diagnostic accuracy of mucins in PC using a meta-analysis. METHODS: We searched the PubMed, Cochrane Library, Institute for Scientific Information (ISI) Web of Science, Embase, and Chinese databases from their date of inception to June 1, 2020 to identify studies assessing the diagnostic performance of mucins in PC. The estimations of diagnostic indicators in selected studies were extracted for further analysis by Meta-DiSc software. Publication bias was assessed using Deeks' funnel plot asymmetry test. RESULTS: Our meta-analysis included 34 studies. The pooled accuracy indicators of MUC1 in PC including the sensitivity, specificity, diagnostic odds ratio (DOR), positive likelihood ratio (PLR), and negative likelihood ratio (NLR) (with 95% confidence intervals) were 0.84 (0.82-0.86), 0.60 (0.56-0.64), 18.37 (9.18-36.78), 2.62 (1.79-3.86), and 0.22 (0.15-0.33), respectively. The area under the summary receiver operating characteristic (SROC) curve was 0.8875 and the Q index was 0.8181. Quantitative random-effects meta-analysis of MUC4 in PC using the summary (ROC) curve model revealed a pooled sensitivity of 0.86 (95% confidence interval, 0.82-0.89) and specificity of 0.88 (95% confidence interval, 0.85-0.91). In addition, the meta-analysis of MUC5AC in PC diagnosis also showed a high sensitivity and specificity of 0.71 (95% confidence interval, 0.65-0.76) and 0.60 (95% confidence interval, 0.53-0.66), respectively. Regarding MUC16, the area under the summary ROC curve and Q index were 0.9185 and 0.8516, respectively. CONCLUSIONS: In summary, our results suggested a good diagnostic accuracy of several crucial mucins in PC. Mucins may serve as optional indicators in PC examination, and further research is warranted to investigate the role of mucins as potential clinical biomarkers.