scholarly journals Serum N-Glycomics Stratifies Bacteremic Patients Infected with Different Pathogens

2021 ◽  
Vol 10 (3) ◽  
pp. 516
Author(s):  
Sayantani Chatterjee ◽  
Rebeca Kawahara ◽  
Harry C. Tjondro ◽  
David R. Shaw ◽  
Marni A. Nenke ◽  
...  
Keyword(s):  
Area Under The Curve ◽  
Principal Component ◽  
Bloodstream Infections ◽  
Blood Stream ◽  
Label Free ◽  
Healthy Donors ◽  
Liquid Chromatography Tandem Mass ◽  
Life Threatening ◽  
Patient Groups ◽  
Bacteremic Patient

Bacteremia—i.e., the presence of pathogens in the blood stream—is associated with long-term morbidity and is a potential precursor condition to life-threatening sepsis. Timely detection of bacteremia is therefore critical to reduce patient mortality, but existing methods lack precision, speed, and sensitivity to effectively stratify bacteremic patients. Herein, we tested the potential of quantitative serum N-glycomics performed using porous graphitized carbon liquid chromatography tandem mass spectrometry to stratify bacteremic patients infected with Escherichia coli (n = 11), Staphylococcus aureus (n = 11), Pseudomonas aeruginosa (n = 5), and Streptococcus viridans (n = 5) from healthy donors (n = 39). In total, 62 N-glycan isomers spanning 41 glycan compositions primarily comprising complex-type core fucosylated, bisecting N-acetylglucosamine (GlcNAc), and α2,3-/α2,6-sialylated structures were profiled across all samples using label-free quantitation. Excitingly, unsupervised hierarchical clustering and principal component analysis of the serum N-glycome data accurately separated the patient groups. P. aeruginosa-infected patients displayed prominent N-glycome aberrations involving elevated levels of fucosylation and bisecting GlcNAcylation and reduced sialylation relative to other bacteremic patients. Notably, receiver operating characteristic analyses demonstrated that a single N-glycan isomer could effectively stratify each of the four bacteremic patient groups from the healthy donors (area under the curve 0.93–1.00). Thus, the serum N-glycome represents a new hitherto unexplored class of potential diagnostic markers for bloodstream infections.

scholarly journals Biochemical Changes in Irradiated Oral Mucosa: A FTIR Spectroscopic Study

Biosensors ◽  
2019 ◽  
Vol 9 (1) ◽  
pp. 12 ◽  
Author(s):  
Helena Ukkonen ◽  
Simo Vuokila ◽  
Jopi Mikkonen ◽  
Hannah Dekker ◽  
Engelbert Schulten ◽  
...  
Keyword(s):  
Oral Mucosa ◽  
Infrared Imaging ◽  
Objective Assessment ◽  
Principal Component ◽  
Superficial Layer ◽  
Label Free ◽  
Differential Distribution ◽  
Biochemical Alterations ◽  
Patient Groups ◽  
Therapeutic Irradiation

Radiation exposure during the course of treatment in head and neck cancer (HNC) patients can induce both structural and biochemical anomalies. The present study is focused on utilizing infrared imaging for the identification of the minor biochemical alterations in the oral mucosa. Chemical maps generated using glycoprotein band indicates its differential distribution along the superficial layer. Spectra extracted from this layer suggests changes in overall nucleic acid and protein content in response to the therapeutic irradiation. Discrimination among control and irradiated groups have been achieved using principal component analysis. Findings of this preliminary study further support prospective utilization of Fourier Transform InfraRed (FTIR) imaging as a non-destructive, label-free tool for objective assessment of the oral mucosa in patient groups with or without radiation therapy.

scholarly journals Metabolomic and Proteomic Stratification of Equine Osteoarthritis

2020 ◽  
Author(s):  
James R Anderson ◽  
Marie M Phelan ◽  
Eva Caamaño-Gutiérrez ◽  
Peter D Clegg ◽  
Luis M Rubio-Martinez ◽  
...  
Keyword(s):  
Principal Component ◽  
Apolipoprotein A1 ◽  
Label Free ◽  
Thoroughbred Horses ◽  
Mixed Breed ◽  
Liquid Chromatography Tandem Mass ◽  
Metatarsophalangeal Joints ◽  
Equine Osteoarthritis ◽  
Free Quantification ◽  
Diagnostic Investigations

AbstractOsteoarthritis (OA) is characterised by loss of articular cartilage, synovial membrane dysfunction and subchondral sclerosis. Few studies have used a global approach to stratify equine synovial fluid (SF) molecular profiles according to OA severity. SF was collected from 58 metacarpophalangeal (MCP) and metatarsophalangeal joints of racing Thoroughbred horses (Hong Kong Jockey Club; HKJC) and 83 MCP joints of mixed breed horses from an abattoir and equine hospital (biobank). Joints were histologically and macroscopically assessed for OA severity. For proteomic analysis, native SF and SF loaded onto ProteoMiner™ equalisation columns, to deplete high abundant proteins, were analysed using liquid chromatography-tandem mass spectrometry (LC-MS/MS) and label-free quantification. Validation of selected differentially expressed proteins was undertaken using clinical SF collected during diagnostic investigations. Native SF metabolites were analysed using 1D 1H Nuclear Magnetic Resonance (NMR). 1,834 proteins and 40 metabolites were identified in equine SF. Afamin levels decreased with synovitis severity and four uncharacterised proteins decreased with OA severity. Gelsolin and lipoprotein binding protein decreased with OA severity and apolipoprotein A1 levels increased for mild and moderate OA. Within the biobank, glutamate levels decreased with OA severity and for the HKJC cohort, 2-aminobutyrate, alanine and creatine increased with severity. Proteomic and metabolomic integration was undertaken using linear regression via Lasso penalisation modelling, incorporating 29 variables (R2=0.82) with principal component 2 able to discriminate advanced OA from earlier stages, predominantly driven by H9GZQ9, F6ZR63 and alanine. Combining biobank and HKJC datasets, discriminant analysis of principal components modelling prediction was good for mild OA (90%). This study has stratified equine OA using both metabolomic and proteomic SF profiles and identified a panel of markers of interest which may be applicable to grading OA severity. This is also the first study to undertake computational integration of NMR metabolomic and LC-MS/MS proteomic datasets of any biological system.

scholarly journals Metabolic Profiling of Pitaya (Hylocereus polyrhizus) during Fruit Development and Maturation

Molecules ◽  
2019 ◽  
Vol 24 (6) ◽  
pp. 1114 ◽  
Author(s):  
Yawei Wu ◽  
Juan Xu ◽  
Yizhong He ◽  
Meiyan Shi ◽  
Xiumei Han ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Metabolic Profiling ◽  
Developmental Stages ◽  
Principal Component ◽  
Nutrient Content ◽  
Flight Mass Spectrometry ◽  
Potential Biomarker ◽  
Fruit Samples ◽  
Liquid Chromatography Tandem Mass ◽  
Hylocereus Polyrhizus

Pitaya (Hylocereus polyrhizus) has attracted much interest from consumers as it is a novelty fruit with high nutrient content and a tolerance to drought stress. As a group of attractive pigment- and health-promoting natural compounds, betalains represent a visual feature for pitaya fruit quality. However, little information on the correlation between betalains and relevant metabolites exists so far. Currently, color (Commission International del’Eclairage, CIE) parameters, betalain contents, and untargeted metabolic profiling (gas chromatography-time-of-flight-mass spectrometry, GC–MS and liquid chromatography tandem mass spectrometry, LC–MS) have been examined on ‘Zihonglong’ fruits at nine different developmental stages, and the variation character of the metabolite contents was simultaneously investigated between peel and pulp. Furthermore, principal component analysis (PCA) and partial least-squares discriminant analysis (PLS-DA) were used to explore metabolite profiles from the fruit samples. Our results demonstrated that the decrease of amino acid, accompanied by the increase of sugars and organic acid, might contribute to the formation of betalains. Notably, as one of four potential biomarker metabolites, citramalic acid might be related to betalain formation.

scholarly journals Raman Spectral Signatures of Serum-Derived Extracellular Vesicle-Enriched Isolates May Support the Diagnosis of CNS Tumors

Cancers ◽  
2021 ◽  
Vol 13 (6) ◽  
pp. 1407
Author(s):  
Matyas Bukva ◽  
Gabriella Dobra ◽  
Juan Gomez-Perez ◽  
Krisztian Koos ◽  
Maria Harmati ◽  
...  
Keyword(s):  
Lumbar Disc ◽  
Area Under The Curve ◽  
Principal Component ◽  
Extracellular Vesicle ◽  
Classification Performance ◽  
Cns Tumors ◽  
Clinical Samples ◽  
Support Vector ◽  
Serum Samples ◽  
Raman Spectroscopic

Investigating the molecular composition of small extracellular vesicles (sEVs) for tumor diagnostic purposes is becoming increasingly popular, especially for diseases for which diagnosis is challenging, such as central nervous system (CNS) malignancies. Thorough examination of the molecular content of sEVs by Raman spectroscopy is a promising but hitherto barely explored approach for these tumor types. We attempt to reveal the potential role of serum-derived sEVs in diagnosing CNS tumors through Raman spectroscopic analyses using a relevant number of clinical samples. A total of 138 serum samples were obtained from four patient groups (glioblastoma multiforme, non-small-cell lung cancer brain metastasis, meningioma and lumbar disc herniation as control). After isolation, characterization and Raman spectroscopic assessment of sEVs, the Principal Component Analysis–Support Vector Machine (PCA–SVM) algorithm was performed on the Raman spectra for pairwise classifications. Classification accuracy (CA), sensitivity, specificity and the Area Under the Curve (AUC) value derived from Receiver Operating Characteristic (ROC) analyses were used to evaluate the performance of classification. The groups compared were distinguishable with 82.9–92.5% CA, 80–95% sensitivity and 80–90% specificity. AUC scores in the range of 0.82–0.9 suggest excellent and outstanding classification performance. Our results support that Raman spectroscopic analysis of sEV-enriched isolates from serum is a promising method that could be further developed in order to be applicable in the diagnosis of CNS tumors.

scholarly journals Penetration of Isavuconazole in Ascites Fluid of Critically Ill Patients

2021 ◽  
Vol 7 (5) ◽  
pp. 376
Author(s):  
Tobias Lahmer ◽  
Gonzalo Batres Baires ◽  
Roland M. Schmid ◽  
Johannes R. Wiessner ◽  
Jörg Ulrich ◽  
...  
Keyword(s):  
Critically Ill ◽  
Critically Ill Patients ◽  
Ascites Fluid ◽  
Candida Spp ◽  
Fungal Peritonitis ◽  
Penetration Ratio ◽  
Threatening Condition ◽  
Liquid Chromatography Tandem Mass ◽  
Life Threatening ◽  
Fluid Levels

Fungal peritonitis is a life-threatening condition which is not only difficult to diagnose, but also to treat. Following recent guidelines, echinocandins and azoles are the recommended antimycotics for the management of intra-abdominal Candida spp. infections, with a favor for echinocandins in critically ill patients. However, the new extended spectrum triazole isavuconazole also has a broad spectrum against Candida spp. Data on its target-site penetration are sparse. Therefore, we assessed isavuconazole concentrations and penetration ratios in ascites fluid of critically ill patients. Obtaining of Isavuconazole plasma and ascites fluid levels as well penetration ratios using paracentesis in critically ill patients. Isavuconazole concentrations were quantified in human plasma and ascites by a liquid chromatography/tandem mass spectrometry (LC-MS/MS) method. Isavuconazole concentrations in plasma and ascites fluid were measured in sixteen critically ill patients. Isavuconazol levels in ascites fluid (1.06 µg/mL) were lower than plasma levels (3.08 µg/mL). Penetration ratio was 36%. In two out of sixteen patients, Candida spp., in detail C. glabrata and C. tropicalis, could be isolated. Cmax/MIC Ratio in plasma of 560 for C. glabrata and 2166 for C. tropicalis could be observed. Following our results, isavuconazole penetrates into ascites. Successful treatment in Candida spp. peritonitis depends on pathogen susceptibility.

scholarly journals Label-free proteomic analysis of serum exosomes from paroxysmal atrial fibrillation patients

2021 ◽  
Vol 18 (1) ◽  
Author(s):  
Hanwen Ni ◽  
Wenqi Pan ◽  
Qi Jin ◽  
Yucai Xie ◽  
Ning Zhang ◽  
...  
Keyword(s):  
Atrial Fibrillation ◽  
Protein Folding ◽  
Protein Content ◽  
Complement System ◽  
Proteomic Analysis ◽  
Surface Composition ◽  
Label Free ◽  
Healthy Donors ◽  
Variable Surface ◽  
Serum Exosomes

Abstract Background Atrial fibrillation (AF) is the most common cardiac heterogeneous rhythm disorder. It represents a major cause of mortality and morbidity, mainly related to embolic events and heart failure. Mechanisms of AF are complex and remain incompletely understood. Recent evidence suggests exosomes are membrane-coated objects released by many cell-types. Their presence in body fluids and the variable surface composition and content render them attractive as a mechanism for potential biomarkers. However, the content of serum exosomes of AF patients has not been fully delineated. Methods In this work, the serum exosomes from AF patients and healthy donors were used to compare changes in the exosome protein content. Exosomes were isolated from serum of AF patients and healthy donors and their purity was confirmed by Western blotting assays and transmission electron microscopy (TEM). Label-free LC–MS/MS quantitative proteomic analysis was applied to analyze protein content of serum exosomes. Results A total of 440 exosomal protein groups were identified, differentially expressed proteins were filtrated with fold change ≥ 2.0 (AF/controls protein abundance ratio ≥ 2 or ≤ 0.5) and p value less than 0.05 (p < 0.05), significantly changed in abundance group contains 39 elevated proteins and 18 reduced proteins, while consistent presence/absence expression profile group contains 40 elevated proteins and 75 reduced proteins. Bioinformatic analysis of differential exosomal proteins confirmed the significant enrichment of components involved in the anticoagulation, complement system and protein folding. Parallel-Reaction Monitoring Relative Quantitative Analysis (PRM) further suggested that AF related to complement system and protein folding. Conclusions These results revealed the composition and potential function of AF serum exosomes, thus providing a new perspective on the complement system and protein folding to AF.

scholarly journals Relationship between Plasma Trimethylamine N-Oxide Levels and Renal Dysfunction in Patients with Hypertension

2021 ◽  
pp. 1-12
Author(s):  
Jia Zhou ◽  
Dingkun Wang ◽  
Bingong Li ◽  
Xuelian Li ◽  
Xingjun Lai ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Kidney Disease ◽  
Renal Dysfunction ◽  
High Performance ◽  
Characteristic Curve ◽  
Area Under The Curve ◽  
Hypertensive Patients ◽  
Ckd Stage ◽  
Liquid Chromatography Tandem Mass ◽  
The Relationship

<b><i>Introduction:</i></b> Trimethylamine N-oxide (TMAO) is a metabolite produced by gut bacteria. Although increased TMAO levels have been linked to hypertension (HTN) and chronic kidney disease (CKD) with poor prognosis, no clinical studies have directly addressed the relationship between them. In this study, we investigated the relationship between TMAO and renal dysfunction in hypertensive patients. <b><i>Methods:</i></b> We included healthy controls (<i>n</i> = 50), hypertensive patients (<i>n</i> = 46), and hypertensive patients with renal dysfunction (<i>n</i> = 143). Their blood pressure values were taken as the highest measured blood pressure. Renal function was evaluated using the estimated glomerular filtration rate. Plasma TMAO levels were measured using high-performance liquid chromatography tandem mass spectrometry. <b><i>Results:</i></b> We found significant differences in plasma TMAO levels among the 3 groups (<i>p</i> &#x3c; 0.01). The plasma TMAO of patients with HTN was significantly higher than that of healthy people, and the plasma TMAO of patients with HTN complicated by renal dysfunction was significantly higher than either of the other groups. Patients in the highest TMAO quartile were at a higher risk of developing CKD stage 5 than those in the lowest quartile. In the receiver operating characteristic curve, the area under the curve of TMAO combined with β 2-macroglobulin for predicting renal dysfunction in patients with HTN was 0.85 (95% confidence interval 0.80–0.90). <b><i>Conclusion:</i></b> An elevated TMAO level reflects higher levels of HTN and more severe renal dysfunction. TMAO, combined with β 2-macroglobulin levels, may assist in diagnosing CKD in hypertensive patients. Plasma TMAO has predictive value for early kidney disease in hypertensive patients.

scholarly journals 53. Incidence of Bloodstream Infections and Outcomes in Patients with Severe COVID-19 Pneumonia

2020 ◽  
Vol 7 (Supplement_1) ◽  
pp. S156-S157
Author(s):  
Aikaterini Papamanoli ◽  
Jeanwoo Yoo ◽  
Azad Mojahedi ◽  
Robin Jacob ◽  
Prabhjot Grewal ◽  
...  
Keyword(s):  
Length Of Stay ◽  
Medical Records ◽  
Bloodstream Infections ◽  
Blood Stream ◽  
Blood Cultures ◽  
High Flow ◽  
University Hospital ◽  
Skin Microbiota ◽  
Prolonged Recovery ◽  
The Impact

Abstract Background Coronavirus disease 19 (COVID-19) leading to acute respiratory distress syndrome is associated with need for intensive care (IC), mechanical ventilation (MV), and prolonged recovery. These patients are thus predisposed to blood stream infections which can worsen outcomes. This risk may be aggravated by adjunctive therapies. Methods We reviewed the medical records of all adults admitted to Stony Brook University Hospital, NY, from March 1 to April 15, 2020 with severe COVID-19 pneumonia (requiring high-flow O2). Patients who received MV or died within 24h were excluded. Patients were followed until death or hospital discharge. We reviewed positive blood cultures (PBC) for pathogenic microorganisms, and calculated the incidence of bacteremia, rates of infective endocarditis (IE), and impact on mortality. Microbes isolated only once and belonging to groups defined as commensal skin microbiota were labelled as contaminants. We also examined the impact of adjunctive therapies with immunosuppressive potential (steroids and tocilizumab), on bacteremia. Results A total of 469 patients with severe COVID-19 pneumonia were included (Table 1). Of these, 199 (42.4%) required IC and 172 (36.7%) MV. Median length of stay was 13 days (8–22) and 94 (20.0%) had PBC. Of these, 43 were considered true pathogens (bacteremia), with predominance of E. faecalis and S. epidermidis, and 51 were considered contaminants (Table 2). The incidence of bacteremia (43/469, 9.2%) was 5.1 per 1000 patient-days (95%CI 3.8–6.4). An echocardiogram was performed in 21 patients, 1 had an aortic valve vegetation (IE) by methicillin sensitive S. aureus. Bacteremia rates were nonsignificantly higher with steroids (5.9 vs 3.7 per 1000 patient-days; P=0.057). Use of tocilizumab was not associated with bacteremia (5.8 vs 4.8 per 1000 patient-days; P=0.28). Mortality was nonsignificantly higher in patients with (15/43, 34.9%) vs. without (108/426, 25.4%) bacteremia (P=0.20). Length of stay was the strongest predictor of bacteremia, with risk increasing by 7% (95%CI 6%-9%, P&lt; 0.001) per additional day. Cohort Characteristics of Patients with Severe COVID-19 Pneumonia on High-Flow O2 (N= 469) All Microorganisms Isolated from Blood Cultures Conclusion The incidence of bacteremia was relatively low and IE was uncommon in this study of severe COVID-19 patients. Risk of bacteremia increased with longer hospital stay and with steroids use, but not with tocilizumab. Disclosures All Authors: No reported disclosures

scholarly journals An Electronic Component Recognition Algorithm Based on Deep Learning with a Faster SqueezeNet

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Yuanyuan Xu ◽  
Genke Yang ◽  
Jiliang Luo ◽  
Jianan He
Keyword(s):  
Deep Learning ◽  
Characteristic Curve ◽  
Area Under The Curve ◽  
Principal Component ◽  
Recognition Algorithm ◽  
Electronic Component ◽  
Support Vector ◽  
Learning Networks ◽  
Component Recognition ◽  
And Performance

Electronic component recognition plays an important role in industrial production, electronic manufacturing, and testing. In order to address the problem of the low recognition recall and accuracy of traditional image recognition technologies (such as principal component analysis (PCA) and support vector machine (SVM)), this paper selects multiple deep learning networks for testing and optimizes the SqueezeNet network. The paper then presents an electronic component recognition algorithm based on the Faster SqueezeNet network. This structure can reduce the size of network parameters and computational complexity without deteriorating the performance of the network. The results show that the proposed algorithm performs well, where the Receiver Operating Characteristic Curve (ROC) and Area Under the Curve (AUC), capacitor and inductor, reach 1.0. When the FPR is less than or equal 10 − 6   level, the TPR is greater than or equal to 0.99; its reasoning time is about 2.67 ms, achieving the industrial application level in terms of time consumption and performance.

scholarly journals Small Extracellular Vesicles Isolated from Serum May Serve as Signal-Enhancers for the Monitoring of CNS Tumors

2020 ◽  
Vol 21 (15) ◽  
pp. 5359 ◽  
Author(s):  
Gabriella Dobra ◽  
Matyas Bukva ◽  
Zoltan Szabo ◽  
Bella Bruszel ◽  
Maria Harmati ◽  
...  
Keyword(s):  
Extracellular Vesicles ◽  
Serum Proteins ◽  
Lumbar Disc ◽  
Principal Component ◽  
Cns Tumors ◽  
Serum Samples ◽  
Force Microscopy ◽  
Isolation And Characterization ◽  
Atomic Force ◽  
Patient Groups

Liquid biopsy-based methods to test biomarkers (e.g., serum proteins and extracellular vesicles) may help to monitor brain tumors. In this proteomics-based study, we aimed to identify a characteristic protein fingerprint associated with central nervous system (CNS) tumors. Overall, 96 human serum samples were obtained from four patient groups, namely glioblastoma multiforme (GBM), non-small-cell lung cancer brain metastasis (BM), meningioma (M) and lumbar disc hernia patients (CTRL). After the isolation and characterization of small extracellular vesicles (sEVs) by nanoparticle tracking analysis (NTA) and atomic force microscopy (AFM), liquid chromatography -mass spectrometry (LC-MS) was performed on two different sample types (whole serum and serum sEVs). Statistical analyses (ratio, Cohen’s d, receiver operating characteristic; ROC) were carried out to compare patient groups. To recognize differences between the two sample types, pairwise comparisons (Welch’s test) and ingenuity pathway analysis (IPA) were performed. According to our knowledge, this is the first study that compares the proteome of whole serum and serum-derived sEVs. From the 311 proteins identified, 10 whole serum proteins and 17 sEV proteins showed the highest intergroup differences. Sixty-five proteins were significantly enriched in sEV samples, while 129 proteins were significantly depleted compared to whole serum. Based on principal component analysis (PCA) analyses, sEVs are more suitable to discriminate between the patient groups. Our results support that sEVs have greater potential to monitor CNS tumors, than whole serum.

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