Knee hemangioma - Diagnostic dilemma: A case report

A hemangioma is a benign tumor of the endothelial cells that line the blood vessels. It is characterized by an increased number of normal or abnormal vessels filled with blood. Usually, it presents as a painful or painless swelling in extremities. Surgical excision is the treatment of choice for large excisable tumor. Here, we present the case of a young girl, referred to our department by orthopedician with a complaint of painful swelling below the right knee that was gradually increasing in size for the past 7 years. Initially, it was misdiagnosed as a hematoma. Hence, incision and drainage were tried but unsuccessful. Finally, computed tomography angiography showed that it was a vascular structure like the hemangioma. The aim of presenting this case is to create awareness and acknowledge the possibility of a hemangioma arising from a joint is usually rare, but it should be kept as a differential diagnosis

Metabolomics approach to studying minimally processed peach (Prunus persica) fruit

Fresh-cut fruit products for both retail and food service applications have increasingly appeared in the market place in recent years. Among different fruit types, peaches can be used and are highly appreciated as fresh-cut product although their commercial success is limited due to their short shelf-life and the quick onset of wounding-related physiological reactions. In this work we analyzed the technological and physiological changes induced by fresh-cut preparation in three different types of peach cultivars: 'Fayette' (melting), 'Wilhelmina' (non-melting) and 'Ghiaccio3' (stony hard). We performed a metabolite targeting profiling to focus on the changes in organic acid levels, important components of fruit taste and organoleptic quality of peaches. Interestingly, 'Ghiaccio3' showed an increase of several organic acids after cutting while 'Fayette' and 'Wilhelmina' showed unchanged amounts or a general reduction. Cutting induces a similar pattern of change in important metabolites (i.e., dehydroascorbate, alanine) in all the three peach types while other metabolites (i.e., citric acid) appeared to be differentially regulated in the considered peach cultivars

Hydrocarbon phenotyping of algal species using pyrolysis-gas chromatography mass spectrometry

<p>Abstract</p> <p>Background</p> <p>Biofuels derived from algae biomass and algae lipids might reduce dependence on fossil fuels. Existing analytical techniques need to facilitate rapid characterization of algal species by phenotyping hydrocarbon-related constituents.</p> <p>Results</p> <p>In this study, we compared the hydrocarbon rich algae <it>Botryococcus braunii </it>against the photoautotrophic model algae <it>Chlamydomonas reinhardtii </it>using pyrolysis-gas chromatography quadrupole mass spectrometry (pyGC-MS). Sequences of up to 48 dried samples can be analyzed using pyGC-MS in an automated manner without any sample preparation. Chromatograms of 30-min run times are sufficient to profile pyrolysis products from C8 to C40 carbon chain length. The freely available software tools AMDIS and SpectConnect enables straightforward data processing. In <it>Botryococcus </it>samples, we identified fatty acids, vitamins, sterols and fatty acid esters and several long chain hydrocarbons. The algae species <it>C. reinhardtii, B. braunii </it>race A and <it>B. braunii </it>race B were readily discriminated using their hydrocarbon phenotypes. Substructure annotation and spectral clustering yielded network graphs of similar components for visual overviews of abundant and minor constituents.</p> <p>Conclusion</p> <p>Pyrolysis-GC-MS facilitates large scale screening of hydrocarbon phenotypes for comparisons of strain differences in algae or impact of altered growth and nutrient conditions.</p

Systemic Metabolomic Changes in Blood Samples of Lung Cancer Patients Identified by Gas Chromatography Time-of-Flight Mass Spectrometry.

Lung cancer is a leading cause of cancer deaths worldwide. Metabolic alterations in tumor cells coupled with systemic indicators of the host response to tumor development have the potential to yield blood profiles with clinical utility for diagnosis and monitoring of treatment. We report results from two separate studies using gas chromatography time-of-flight mass spectrometry (GC-TOF MS) to profile metabolites in human blood samples that significantly differ from non-small cell lung cancer (NSCLC) adenocarcinoma and other lung cancer cases. Metabolomic analysis of blood samples from the two studies yielded a total of 437 metabolites, of which 148 were identified as known compounds and 289 identified as unknown compounds. Differential analysis identified 15 known metabolites in one study and 18 in a second study that were statistically different (p-values &lt;0.05). Levels of maltose, palmitic acid, glycerol, ethanolamine, glutamic acid, and lactic acid were increased in cancer samples while amino acids tryptophan, lysine and histidine decreased. Many of the metabolites were found to be significantly different in both studies, suggesting that metabolomics appears to be robust enough to find systemic changes from lung cancer, thus showing the potential of this type of analysis for lung cancer detection

Genotype x Environment interaction and stability analysis in maize around Southern Aravalli Hilly Ranges of Rajasthan

Crop production is the function of genotype, environment and their interaction (GEI) and evaluation of genotypes in multi environments helps in identifying their adaptation and stability. Forty five maize hybrids along with their 18 parents and two checks were evaluated in three environments viz., E1 (Kharif-2019, Instructional Farm, RCA, Udaipur), E2 (Kharif-2019, Agriculture Research Sub-Station, Vallabhnagar, Udaipur) and E3 (Rabi-2019-2020, Instructional Farm, RCA, Udaipur) in randomized block design with three replications at each environment to assess the phenotypic stability of genotypes. The mean squares due to genotypes and environments were found significant for all the traits under study which indicated inherent genetic differences among the genotypes. The mean squares due to G x E (linear) interaction were found significant for most of the traits under study indicating differences among genotypes for linear response to varying environments. The MSS due to pooled deviation were found non-significant for all the traits which indicated major portion of the genotype x environment interaction was formed by predictable component. The majority of the hybrids depicted non-significant deviations from regression (S2di) for grain yield per plant. It indicated their predictable response across the environments. A great majority of genotypes revealed non-significant non-linear estimates (S2di) for different traits which suggested that the prediction of stability was more or less accurate and reliable. The top three hybrids suitable for all environments (bi≈1) were EI-2653 x EI-102, EI-2639 x EI-670 and EI-2505 x EI-102 with non-significant S2di values. The hybrids EI-2176-3 x EI-03, EI-2525-2 x EI-03 and EI-2159 x EI-670 out yielded the best check cultivar CC-1 for grain yield per plant. Thus, these combinations may be exploited commercially after further multi location yield testing

Data Processing Thresholds for Abundance and Sparsity and Missed Biological Insights in an Untargeted Chemical Analysis of Blood Specimens for Exposomics

Background: An untargeted chemical analysis of bio-fluids provides semi-quantitative data for thousands of chemicals for expanding our understanding about relationships among metabolic pathways, diseases, phenotypes and exposures. During the processing of mass spectral and chromatography data, various signal thresholds are used to control the number of peaks in the final data matrix that is used for statistical analyses. However, commonly used stringent thresholds generate constrained data matrices which may under-represent the detected chemical space, leading to missed biological insights in the exposome research.Methods: We have re-analyzed a liquid chromatography high resolution mass spectrometry data set for a publicly available epidemiology study (n = 499) of human cord blood samples using the MS-DIAL software with minimally possible thresholds during the data processing steps. Peak list for individual files and the data matrix after alignment and gap-filling steps were summarized for different peak height and detection frequency thresholds. Correlations between birth weight and LC/MS peaks in the newly generated data matrix were computed using the spearman correlation coefficient.Results: MS-DIAL software detected on average 23,156 peaks for individual LC/MS file and 63,393 peaks in the aligned peak table. A combination of peak height and detection frequency thresholds that was used in the original publication at the individual file and the peak alignment levels can reject 90% peaks from the untargeted chemical analysis dataset that was generated by MS-DIAL. Correlation analysis for birth weight data suggested that up to 80% of the significantly associated peaks were rejected by the data processing thresholds that were used in the original publication. The re-analysis with minimum possible thresholds recovered metabolic insights about C19 steroids and hydroxy-acyl-carnitines and their relationships with birth weight.Conclusions: Data processing thresholds for peak height and detection frequencies at individual data file and at the alignment level should be used at minimal possible level or completely avoided for mining untargeted chemical analysis data in the exposome research for discovering new biomarkers and mechanisms

Systematic analysis of the polyphenol metabolome using the Phenol-Explorer database

SCOPE: The Phenol-Explorer web database details 383 polyphenol metabolites identified in human and animal biofluids from 221 publications. Here we exploit these data to characterize and visualize the polyphenol metabolome, the set of all metabolites derived from phenolic food components. METHODS AND RESULTS: Qualitative and quantitative data on 383 polyphenol metabolites as described in 424 human and animal intervention studies were systematically analyzed. Of these metabolites, 301 were identified without prior enzymatic hydrolysis of biofluids, and included glucuronide and sulfate esters, glycosides, aglycones, and O-methyl ethers. Around one third of these compounds are also known as food constituents and corresponded to polyphenols absorbed without further metabolism. Many ring-cleavage metabolites formed by gut microbiota were noted, mostly derived from hydroxycinnamates, flavanols and flavonols. Median maximum plasma concentrations (Cmax ) of all human metabolites were 0.09 μM and 0.32 μM when consumed from foods or dietary supplements respectively. Median time to reach maximum plasma concentration in humans (Tmax ) was 2.18 h. CONCLUSION: These data show the complexity of the polyphenol metabolome and the need to take into account biotransformations to understand in vivo bioactivities and the role of dietary polyphenols in health and disease. This article is protected by copyright. All rights reserved

Integration of metabolomics, transcriptomics, and microRNA expression profiling reveals a miR-143-HK2-glucose network underlying zinc-deficiency-associated esophageal neoplasia

Esophageal squamous cell carcinoma (ESCC) in humans is a deadly disease associated with dietary zinc (Zn)-deficiency. In the rat esophagus, Zn-deficiency induces cell proliferation, alters mRNA and microRNA gene expression, and promotes ESCC. We investigated whether Zn-deficiency alters cell metabolism by evaluating metabolomic profiles of esophageal epithelia from Zn-deficient and replenished rats vs sufficient rats, using untargeted gas chromatography time-of-flight mass spectrometry (n = 8/group). The Zn-deficient proliferative esophagus exhibits a distinct metabolic profile with glucose down 153-fold and lactic acid up 1.7-fold (P \u3c 0.0001), indicating aerobic glycolysis (the Warburg effect ), a hallmark of cancer cells. Zn-replenishment rapidly increases glucose content, restores deregulated metabolites to control levels, and reverses the hyperplastic phenotype. Integration of metabolomics and our reported transcriptomic data for this tissue unveils a link between glucose down-regulation and overexpression of HK2, an enzyme that catalyzes the first step of glycolysis and is overexpressed in cancer cells. Searching our published microRNA profile, we find that the tumor-suppressor miR-143, a negative regulator of HK2, is down-regulated in Zn-deficient esophagus. Using in situ hybridization and immunohistochemical analysis, the inverse correlation between miR-143 down-regulation and HK2 overexpression is documented in hyperplastic Zndeficient esophagus, archived ESCC-bearing Zn-deficient esophagus, and human ESCC tissues. Thus, to sustain uncontrolled cell proliferation, Zn-deficiency reprograms glucose metabolism by modulating expression of miR-143 and its target HK2. Our work provides new insight into critical roles of Zn in ESCC development and prevention. © Fong et al