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OBJECTIVE Glioma is the most common form of brain tumor and has high lethality. The authors of this study aimed to elucidate the efficiency of preoperative inflammatory markers, including neutrophil/lymphocyte ratio (NLR), derived NLR (dNLR), platelet/lymphocyte ratio (PLR), lymphocyte/monocyte ratio (LMR), and prognostic nutritional index (PNI), and their paired combinations as tools for the preoperative diagnosis of glioma, with particular interest in its most aggressive form, glioblastoma (GBM). METHODS The medical records of patients newly diagnosed with glioma, acoustic neuroma, meningioma, or nonlesional epilepsy at 3 hospitals between January 2011 and February 2016 were collected and retrospectively analyzed. The values of NLR, dNLR, PLR, LMR, and PNI were compared among patients suffering from glioma, acoustic neuroma, meningioma, and nonlesional epilepsy and healthy controls by using nonparametric tests. Correlations between NLR, dNLR, PLR, LMR, PNI, and tumor grade were analyzed. Receiver operating characteristic (ROC) curve analysis was performed to evaluate the diagnostic significance of NLR, dNLR, PLR, LMR, PNI, and their paired combinations for glioma, particularly GBM. RESULTS A total of 750 patients with glioma (Grade I, 81 patients; Grade II, 208 patients; Grade III, 169 patients; Grade IV [GBM], 292 patients), 44 with acoustic neuroma, 271 with meningioma, 102 with nonlesional epilepsy, and 682 healthy controls were included in this study. Compared with healthy controls and patients with acoustic neuroma, meningioma, or nonlesional epilepsy, the patients with glioma had higher values of preoperative NLR and dNLR as well as lower values of LMR and PNI, whereas PLR was higher in glioma patients than in healthy controls and patients with nonlesional epilepsy. Subgroup analysis revealed a positive correlation between NLR, dNLR, PLR, and tumor grade but a negative correlation between LMR, PNI, and tumor grade in glioma. For glioma diagnosis, the area under the curve (AUC) obtained from the ROC curve was 0.722 (0.697-0.747) for NLR, 0.696 (0.670-0.722) for dNLR, 0.576 (0.549-0.604) for PLR, 0.760 (0.738-0.783) for LMR, and 0.672 (0.646-0.698) for PNI. The best diagnostic performance was obtained with the combination of NLR+LMR and dNLR+LMR, with AUCs of 0.777 and 0.778, respectively. Additionally, NLR (AUC 0.860, 95% CI 0.832-0.887), dNLR (0.840, 0.810-0.869), PLR (0.678, 0.641-0.715), LMR (0.837, 0.811-0.863), and PNI (0.740, 0.706-0.773) had significant predictive value for GBM compared with healthy controls and other disease groups. As compared with the Grade I-III glioma patients, the GBM patients had an AUC of 0.811 (95% CI 0.778-0.844) for NLR, 0.797 (0.763-0.832) for dNLR, 0.662 (0.622-0.702) for PLR, 0.743 (0.707-0.779) for LMR, and 0.661(0.622-0.701) for PNI. For the paired combinations, NLR+LMR demonstrated the highest accuracy. CONCLUSIONS The NLR+LMR combination was revealed as a noninvasive biomarker with relatively high sensitivity and specificity for glioma diagnosis, the differential d...

To gain an insight into the effects of different diets on growth and development of the domesticated silkworm at protein level, we employed comparative proteomic approach to investigate the proteomic differences of midgut, hemolymph, fat body and posterior silk gland of the silkworms reared on fresh mulberry leaves and on artificial diet. Seventy-six differentially expressed proteins were identified by MALDI TOF/TOF MS, and among them, 41 proteins were up-regulated, and 35 proteins were downregulated. Database searches, combined with GO analysis and KEGG pathway analysis revealed that some hemolymph proteins such as Nuecin, Gloverin-like proteins, PGRP, P50 and beta/-N-acetylglucosamidase were related to innate immunity of the silkworm, and some proteins identified in silkworm midgut including Myosin 1 light chain, Tropomyosin 1, Profilin, Serpin-2 and GSH-Px were involved in digestion and nutrition absorption. Moreover, two up-regulated enzymes in fat body of larvae reared on artificial diet were identified as V-ATPase subunit B and Arginine kinase which participate in energy metabolism. Furthermore, 6 down-regulated proteins identified in posterior silk gland of silkworm larvae reared on artificial diet including Ribosomal protein SA, EF-2, EF-1gamma, AspAT, ERp57 and PHB were related to silk synthesis. Our results suggested that the different diets could alter the expression of proteins related to immune system, digestion and absorption of nutrient, energy metabolism and silk synthesis poor nutrition and absorption of nutrition in silkworm. The results also confirmed that the poor nutrient absorption, weakened innate immunity, decreased energy metabolism and reduced silk synthesis are the main reasons for low cocoons yield, inferior filament quality, low survival rate of young larvae and insufficient resistance against specific pathogens in the silkworms fed on artificial diet.