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Background: Immunomagnetic separation is essential for screening pathogenic bacteria to prevent food poisoning. However, free immunomagnetic nanobeads (IMNBs) coexist with IMNB-bacteria conjugates (IBCs) after traditional immunomagnetic separation resulting in the infeasibility for IMNBs on IBCs to further act as signal label in bacterial detection. Although we have demonstrated that magnetophoretic separation at a high flowrate could separate IBCs from IMNBs, partial IMNBs were still found with IBCs due to chaotic flows and resulted in inevitable interferences.

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Floral nectar is a sugar-rich resource which is ubiquitously inhabited by a wide array of microorganisms. Fermentation by nectar-inhabiting microbes can alter several nectar traits, including nectar scent, via changes in the blend of volatile organic compounds (VOCs). Although there is growing evidence on how yeasts and bacteria influence the foraging behavior of flower-visiting insects, the potential role of other microbial taxa that can colonize nectar has been largely neglected.

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Despite extensive investigations into the microbiome and metabolome changes associated with colon polyps and colorectal cancer (CRC), the microbiome and metabolome profiles of individuals with colonic polyposis, including those with (Gene-pos) and without (Gene-neg) a known genetic driver, remain comparatively unexplored. Using colon biopsies, polyps, and stool from patients with Gene-pos adenomatous polyposis ( = 9), Gene-neg adenomatous polyposis ( = 18), and serrated polyposis syndrome (SPS,  = 11), we demonstrated through 16S rRNA sequencing that the mucosa-associated microbiota in individuals with colonic polyposis is representative of the microbiota associated with small polyps, and that both Gene-pos and SPS cohorts exhibit differential microbiota populations relative to Gene-neg polyposis cohorts. Furthermore, we used these differential microbiota taxa to perform linear discriminant analysis to differentiate Gene-neg subjects from Gene-pos and from SPS subjects with an accuracy of 89% and 93% respectively.

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Aims/hypothesis: Components of the insulin processing and secretion pathways remain incompletely understood. Here, we examined a genome-wide association study (GWAS) signal for plasma proinsulin levels. Lead GWAS variant rs150781447-T encodes an Arg279Cys substitution in TBC1 domain family member 30 (TBC1D30), but no role for this protein in insulin processing or secretion has been established previously.

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This study established a H-NMR-based biochemometric approach for the isolation of biologically active compounds from complex extracts. In both pharmacognosy and natural product chemistry, reliably isolating bioactive compounds typically necessitates repeating time-consuming and laborious isolation and purification steps, presenting a bottleneck in many studies. We applied biochemometric methods to accurately estimate active compounds, thus minimizing the number of assays and isolation steps.

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