BackgroundIn the past decades, a good deal of studies has provided the possibility of the circulating microRNAs (miRNAs) as noninvasive biomarkers for cancer diagnosis. The aim of our study was to detect the levels of circulating miRNAs in tissues and plasmas of gastric cancer (GC) patients and evaluate their diagnostic value.MethodsTissue samples were collected from 85 GC patients. Plasma samples were collected from 285 GC patients and 285 matched controls. Differentially expressed miRNAs were filtered with by Agilent Human miRNA Microarray and TaqMan low density array (TLDA) with pooled samples, followed by the quantitative reverse transcription polymerase chain reaction (qRT-PCR) validation. Receiver operating characteristic (ROC) curves were structured to evaluate the diagnostic accuracy of the miRNAs. The plasma level of miR-26a in GC patients of different clinical stages was compared.ResultsFour miRNAs (miR-26a, miR-142-3p, miR-148a, and miR-195) revealed coincidentally decreased levels in tissue and plasma of the GC patients compared with controls, and ROC curves were constructed to demonstrate that miR-26a had a highest area under the ROC curve (AUC) of 0.882. Furthermore, miR-26a was stably detected in the plasma of GC patients with different clinical characteristics.ConclusionPlasma miR-26a may provide a novel and stable marker of gastric cancer.

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Gestational diabetes mellitus (GDM) not only has a bad effect on the development of infants but also causes variations in breastmilk composition. This study aims to investigate the changes in the protein profile of colostrum between mothers with GDM and healthy mothers (H) by sequential windowed acquisition of all theoretical fragment ion proteomics techniques. A total of 1295 proteins were detected, with 192 proteins being significantly different between GDM and H. These significantly different proteins were enriched with the carbohydrate and lipid metabolism pathway as well as immunity. Some proteins had an AOC value of 1, such as apolipoprotein E and lipoprotein lipase. In addition, we identified 42 glycated and 93 glycosylated peptides in colostrum without any enrichment, with glycated peptides being upregulated and glycosylated peptides being downregulated in colostrum with GDM. These results help us to better understand the GDM-induced changes in proteomes and glycated and glycosylated level and provide guidance on infant formula adjustment for infants from mothers with GDM.

Hyperlipidemia is one of the main causes of obesity, type 2 diabetes mellitus (T2DM), and atherosclerosis. The adenosine derivative, 2',3',5'-triacetyl-N-(3-hydroxylaniline) adenosine (IMM-H007) is an effective lipid-lowering compound that has important implications for the development of lipid-lowering drugs. Metabolomic analysis based on H NMR was used to monitor dynamic changes in diverse biological media including serum, liver, urine, and feces in response to high-fat diet (HFD) and IMM-H007 treatments. Ultraperformance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) and gas chromatography (GC) analyses were performed to quantify the bile acids and fatty acids in the liver and feces. Fecal microbiome profiling was performed using Illumina sequencing of the 16S rRNA ( 16S rRNA) gene. IMM-H007 improved the metabolism of carbohydrate, ketone bodies, fatty acids, amino acids, and bile acids in hyperlipidemic hamsters. The correlation between metabolite changes was explored in different biological media. Significant changes in gut microbiota were observed in the HFD and IMM-H007 treatment groups. In the HFD group at the phylum level, we found high levels of the Firmicutes genus and low levels of Bacteroidetes. In contrast, the administration of IMM-H007 reversed the levels of Firmicutes and Bacteroidetes. This reversal suggested that IMM-H007 may have the ability to regulate the composition of the gut flora. We also analyzed the correlation between the gut flora and the metabolites. Our results indicate that IMM-H007 treatment improves the hyperlipidemic metabolism and the structure of the gut microbiota in hyperlipidemic hamsters.

Search engines have been the primary tool for online information search before traveling. Timely detection and the control of peak tourist flows in scenic areas prevent safety hazards and the overconsumption of tourism resources due to excessive tourist clustering. This study focuses on the spatial-temporal interactions between the pre-trip stage and the after-arrival stage to investigate online information search behavior. Big data obtained from mobile roaming and search engines provide precise data on daytime and city scales, which enabled this paper to examine the relationship between daily tourist arrivals and their pre-trip searching from 40 cities within the Yangtze River Delta urban agglomeration. This study had several original results. First, tourists generally search for tourist information 2–8 days before arriving at destinations, while tourist volume and SVI from source cities show distance attenuation. Second, SVI is a precursor to changes in tourist volume. The precursory time rises with the increase of traffic time spatially. Third, we validated a VAR model and improved its accuracy by constructing it based on the spatial-temporal differentiation of search features. These findings would enhance the management and preservation of tourism resources and promote the sustainable development of tourism destinations.

In response to acute brain injury (ABI) threats, neuroimmune cells rapidly transition from a quiescent into an activated state, but the dynamic molecular alterations are partially understood. Here, we integrated the dynamics of multi-omics datasets in four ABI mice models. Transcriptomics revealed diversification of thermogenesis, synaptic, and neuroinflammatory genes for ABI at the early phase (12H). Transcriptomics and proteomics combined analysis singled out 15 co-variation risk genes for ABIs. Besides, lipid metabolite alteration reflected a discrepancy between permanent ischemic brain injuries and transient ischemic brain injuries at the middle phase (24H). Together, our data elucidate a potential therapeutic resource for ABIs.

Human milk oligosaccharides (HMOs) are the second largest carbohydrate component and the third largest nutrient after lactose, and their content and composition are related to the genetic characteristics of the mother, lactation period, geography, and other factors. This study examined the differences in fat content, protein composition, and oligosaccharides content between foremilk and hind milk in human milk. The results showed that the fat content of human milk was significantly higher in the hind milk than in the foremilk. However, no significant differences in the composition and content of protein in the fore and hind milk. With respect to oligosaccharides, the total amount of HMOs (based on seven oligosaccharides, lacto-N-neotetraose (LNnT), lacto-N-tetraose (LNT), 2′-fucosyllactose (2′-FL), 3′-fucosyllactose (3′-FL), 3′-galactosyllactose (3′-GL), 3′-sialyllactose (3′-SL), and 6′-sialyllactose (6′-SL) in the hind milk was always higher than in the foremilk in almost all mothers. Similar trend was found in specific oligosaccharide including LNnT, LNT, 2′-FL, 3′-FL, and 3′-GL. On the other hand, sialylated oligosaccharides, 3′-SL, and 6′-SL were quite consistent in foremilk and hind milk.