Project description:Objective: To evaluate if the inflammatory proteomics of uterine fluid could define the endometrial receptivity phase. Methods: Inflammatory proteomics of uterine fluid were measured using the OLINK Target-96 Inflammation panel. Endometrial receptivity testing (ERT) combined with endometrial dating was a gold standard for defining the endometrial receptivity phase. A predictive model based on proteomics of uterine fluid was established to predict the endometrial receptivity phase. Results: The inflammatory factors in uterine fluid were differentially expressed between window of implantation (WOI) and displaced WOI groups, and the displaced WOI group was characterized by the increased expression of a variety of inflammatory factors. The predictive model established based on the top 5 differential proteins could accurately classify the endometrial receptive phase. Transcriptomic data from endometrial tissues showed that the differential gene sets between different receptive phases were mostly enriched in immune-related processes, and the expression of immune-related genes in the WOI group was significantly lower than that in the displaced WOI group. Conclusions: Detection of inflammatory proteins from the uterine fluid using the OLINK inflammation panel could be a novel non-invasive method to define the endometrial receptive phase. The inflammatory immune response during the embryo implantation window was inhibited to adapt to the implantation of the semi-alloimmune embryos.
Project description:Molecular networking has become a key method to visualize and annotate the chemical space in non-targeted mass spectrometry data. We present feature-based molecular networking (FBMN) as an analysis method in the Global Natural Products Social Molecular Networking (GNPS) infrastructure that builds on chromatographic feature detection and alignment tools. FBMN enables quantitative analysis and resolution of isomers, including from ion mobility spectrometry.
Project description:Raw mass spectrometry data from cerebrospinal fluid (CSF) proteomics analysis of central nervous system lymphoma (CNSL) patients undergoing multi-agent intraventricular chemotherapy (MAIVC). The study aimed to identify CSF-based proteomic biomarkers for treatment response and outcome prediction in CNSL, analyzing 117 CSF samples from 59 patients.
Project description:The intermediate filament protein Nestin serves as a biomarker for stem cells and has been used to identify subsets of cancer stem-like cells. However, the mechanistic contributions of Nestin to cancer pathogenesis are not understood. Here we report that Nestin binds the hedgehog pathway transcription factor Gli3 to mediate the development of medulloblastomas of the hedgehog subtype. In a mouse model system, Nestin levels increased progressively during medulloblastoma formation resulting in enhanced tumor growth. Conversely, loss of Nestin dramatically inhibited proliferation and promoted differentiation. Mechanistic investigations revealed that the tumor-promoting effects of Nestin were mediated by binding to Gli3, a zinc finger transcription factor that negatively regulates hedgehog signaling. Nestin binding to Gli3 blocked Gli3 phosphorylation and its subsequent proteolytic processing, thereby abrogating its ability to negatively regulate the hedgehog pathway. Our findings show how Nestin drives hedgehog pathway-driven cancers and uncover in Gli3 a therapeutic target to treat these malignancies.
Project description:Delirium is a common postoperative complication among older patients with many adverse outcomes. Due to lack of validated biomarkers, prediction and monitoring of delirium by biological testing is not currently feasible. Circulating proteins in cerebrospinal fluid (CSF) may reflect biological processes causing delirium. Our goal was to discover and investigate candidate protein biomarkers in preoperative CSF that were associated with development of postoperative delirium in older surgical patients. We employed a nested case–control study design coupled with high multiplex affinity proteomics analysis to measure 1305 proteins in preoperative CSF. Twenty-four matched delirium cases and non-delirium controls were selected from the Healthier Postoperative Recovery (HiPOR) cohort and the associations between preoperative protein levels and postoperative delirium were assessed using t-test statistics with further analysis by systems biology to elucidate delirium pathophysiology. Proteomics analysis identified 32 proteins in preoperative CSF that significantly associate with delirium (t-test p<0.05). Due to the limited sample size these proteins did not remain significant by multiple hypothesis testing using the Benjamini-Hochberg correction and q-value method. Three algorithms were applied to separate delirium cases from non-delirium controls. Hierarchical clustering classified 40/48 case-control samples correctly, principal components analysis separated 43/48. The receiver operating characteristic curve yielded an area under the curve [95% confidence interval] of 0.91 [0.80-0.97]. Systems biology analysis identified several key pathways associated with risk of delirium: inflammation, immune cell migration, apoptosis, angiogenesis, synaptic depression and neuronal cell death. Proteomics analysis of preoperative CSF identifies 32 proteins that might discriminate individuals who subsequently develop postoperative delirium from matched control samples. These proteins are potential candidate biomarkers for delirium and may play a role in its pathophysiology.
Project description:This paper investigates the utilization of commercial masterbatches of graphene nanoplatelets to improve the properties of neat polymer and wood fiber composites manufactured by conventional processing methods. The effect of aspect ratio of the graphene platelets (represented by the different number of layers in the nanoplatelet) on the properties of high-density polyethylene (HDPE) is discussed. The composites were characterized for their mechanical properties (tensile, flexural, impact) and physical characteristics (morphology, crystallization, and thermal stability). The effect of the addition of nanoplatelets on the thermal conductivity and diffusivity of the reinforced polymer with different contents of reinforcement was also investigated. In general, the mechanical performance of the polymer was enhanced at the presence of either of the reinforcements (graphene or wood fiber). The improvement in mechanical properties of the nanocomposite was notable considering that no compatibilizer was used in the manufacturing. The use of a masterbatch can promote utilization of nano-modified polymer composites on an industrial scale without modification of the currently employed processing methods and facilities.