A novel enzyme-linked immunostaining technique based on silk membrane for the prenatal detection of fetomaternal haemorrhage

Objective: Developing a simple, rapid, reliable, sensitive, and cost-effective method for prenatal detection of fetomaternal haemorrhage by combining multi-aperture silk membrane with enzyme-linked immunosorbent assay (ELISA), which does not require any complicated instruments and can be visually colored, so as to provide a new method for clinical detection of fetomaternal haemorrhage.Methods: As a carrier, a chemically treated silk membrane was used to immobilize anti-A/anti-B antibody reagent. PBS washed slowly after vertically dropping red blood cells. After adding biotin-labeled anti-A/anti-B antibody reagent, PBS is slowly washed, enzyme-labeled avidin is added, and TMB is used for color development after washing.Results: When there were both anti-A and anti-B fetal erythrocytes in pregnant women’s peripheral blood, the final color was dark brown. When there are no anti-A and anti-B fetal red blood cells in pregnant women’s peripheral blood, the final color development results do not change, which corresponds to the color of chemically treated silk membrane.Conclusion: The new enzyme-linked immunosorbent assay (ELISA) based on a silk membrane can distinguish fetal red blood cells from maternal red blood cells prenatally and can be used for prenatal detection of fetomaternal haemorrhage

Diptoindonesin G is a middle domain HSP90 modulator for cancer treatment

HSP90 inhibitors can target many oncoproteins simultaneously, but none have made it through clinical trials due to dose-limiting toxicity and induction of heat shock response, leading to clinical resistance. We identified diptoindonesin G (dip G) as an HSP90 modulator that can promote degradation of HSP90 clients by binding to the middle domain of HSP90 (

Prediction of risk factors for linezolid-induced thrombocytopenia based on neural network model

Background: Based on real-world medical data, the artificial neural network model was used to predict the risk factors of linezolid-induced thrombocytopenia to provide a reference for better clinical use of this drug and achieve the timely prevention of adverse reactions.Methods: The artificial neural network algorithm was used to construct the prediction model of the risk factors of linezolid-induced thrombocytopenia and further evaluate the effectiveness of the artificial neural network model compared with the traditional Logistic regression model.Results: A total of 1,837 patients receiving linezolid treatment in a hospital in Xi ‘an, Shaanxi Province from 1 January 2011 to 1 January 2021 were recruited. According to the exclusion criteria, 1,273 cases that did not meet the requirements of the study were excluded. A total of 564 valid cases were included in the study, with 89 (15.78%) having thrombocytopenia. The prediction accuracy of the artificial neural network model was 96.32%, and the AUROC was 0.944, which was significantly higher than that of the Logistic regression model, which was 86.14%, and the AUROC was 0.796. In the artificial neural network model, urea, platelet baseline value and serum albumin were among the top three important risk factors.Conclusion: The predictive performance of the artificial neural network model is better than that of the traditional Logistic regression model, and it can well predict the risk factors of linezolid-induced thrombocytopenia

Grocery store access and childhood obesity: A systematic review and meta-analysis

Grocery store is usually considered to be a healthy food outlet as it provides access to a variety of healthy food, such as fruits and vegetables, which may potentially improve overall dietary quality and protect against obesity. However, findings of the association between grocery store and childhood obesity are controversial. This study aimed to systematically review the evidence on the association between access to grocery stores and childhood obesity. A literature search was conducted in the PubMed, Embase, and Web of Science for articles published before January 1, 2019, using the combinations of three groups of keywords separately for grocery store, children and adolescents, and weight-related behaviours and outcomes. A total of 27 cross-sectional and eight longitudinal studies were identified. Controversial results existed among 24 studies, which examined the association between the access to grocery stores and weight-related outcomes. A null association was observed in almost all meta-analyses conducted by different measures of grocery stores and weight status, except the analysis between presence of grocery stores and overweight, which reached borderline significance. For weight-related behaviours, mixed findings were reported between grocery stores and dietary behaviours, and no significant associations were found for physical activity. This systematic review and meta-analysis suggested that access to grocery stores may have a rather small influence on child weight

Fast‐food restaurant, unhealthy eating, and childhood obesity:: A systematic review and meta‐analysis

Excessive access to fast-food restaurants (FFRs) in the neighbourhood is thought to be a risk factor for childhood obesity by discouraging healthful dietary behaviours while encouraging the exposure to unhealthful food venues and hence the compensatory intake of unhealthy food option. A literature search was conducted in the PubMed, Web of Science, and Embase for articles published until 1 January 2019 that analysed the association between access to FFRs and weight-related behaviours and outcomes among children aged younger than 18. Sixteen cohort studies and 71 cross-sectional studies conducted in 14 countries were identified. While higher FFR access was not associated with weight-related behaviours (eg, dietary quality score and frequency of food consumption) in most studies, it was commonly associated with more fast-food consumption. Despite that, insignificant results were observed for all meta-analyses conducted by different measures of FFR access in the neighbourhood and weight-related outcomes, although 17 of 39 studies reported positive associations when using overweight/obesity as the outcome. This systematic review and meta-analysis revealed a rather mixed relationship between FFR access and weight-related behaviours/outcomes among children and adolescents

Boost-DiLeu: Enhanced Isobaric N,N-Dimethyl Leucine Tagging Strategy for a Comprehensive Quantitative Glycoproteomic Analysis

Intact glycopeptide analysis has been of great interest because it can elucidate glycosylation site information and glycan structural composition at the same time. However, mass spectrometry (MS)-based glycoproteomic analysis is hindered by the low abundance and poor ionization efficiency of glycopeptides. Relatively large amounts of starting materials are needed for the enrichment, which makes the identification and quantification of intact glycopeptides from samples with limited quantity more challenging. To overcome these limitations, we developed an improved isobaric labeling strategy with an additional boosting channel to enhance N,N-dimethyl leucine (DiLeu) tagging-based quantitative glycoproteomic analysis, termed as Boost-DiLeu. With the integration of a one-tube sample processing workflow and high-pH fractionation, 3514 quantifiable N-glycopeptides were identified from 30 μg HeLa cell tryptic digests with reliable quantification performance. Furthermore, this strategy was applied to human cerebrospinal fluid (CSF) samples to differentiate N-glycosylation profiles between Alzheimer's disease (AD) patients and non-AD donors. The results revealed processes and pathways affected by dysregulated N-glycosylation in AD, including platelet degranulation, cell adhesion, and extracellular matrix, which highlighted the involvement of N-glycosylation aberrations in AD pathogenesis. Moreover, weighted gene coexpression network analysis (WGCNA) showed nine modules of glycopeptides, two of which were associated with the AD phenotype. Our results demonstrated the feasibility of using this strategy for in-depth glycoproteomic analysis of size-limited clinical samples. Taken together, we developed and optimized a strategy for the enhanced comprehensive quantitative intact glycopeptide analysis with DiLeu labeling, showing significant promise for identifying novel therapeutic targets or biomarkers in biological systems with a limited sample quantity

DiLeu Isobaric Labeling Coupled with Limited Proteolysis Mass Spectrometry for High-Throughput Profiling of Protein Structural Changes in Alzheimer's Disease

High-throughput quantitative analysis of protein conformational changes has a profound impact on our understanding of the pathological mechanisms of Alzheimer’s disease (AD). To establish an effective workflow enabling quantitative analysis of changes in protein conformation within multiple samples simultaneously, here we report the combination of N,N-dimethyl leucine (DiLeu) isobaric tag labeling with limited proteolysis mass spectrometry (DiLeu-LiP-MS) for high-throughput structural protein quantitation in serum samples collected from AD patients and control donors. Twenty-three proteins were discovered to undergo structural changes, mapping to 35 unique conformotypic peptides with significant changes between the AD group and the control group. Seven out of 23 proteins, including CO3, CO9, C4BPA, APOA1, APOA4, C1R, and APOA, exhibited a potential correlation with AD. Moreover, we found that complement proteins (e.g., CO3, CO9, and C4BPA) related to AD exhibited elevated levels in the AD group compared to those in the control group. These results provide evidence that the established DiLeu-LiP-MS method can be used for high-throughput structural protein quantitation, which also showed great potential in achieving large-scale and in-depth quantitative analysis of protein conformational changes in other biological systems

Urban sprawl and childhood obesity

202010 bcmaVersion of RecordPublishe