Magnetic nanoparticles (NPs) hold great promise for biomedical applications. The core composition and small size of these particles produce superparamagnetic behavior, thus facilitating their use in magnetic resonance imaging and magnetically induced therapeutic hyperthermia. However, the development and control of safe in vivo applications for NPs call for the study of cell-NP interactions and cell viability. Furthermore, as for most biotechnological applications, it is desirable to prevent unspecific cell internalization of these particles. It is also crucial to understand how the surface composition of the NPs affects their internalization capacity. Here, through accurate control over unspecific protein adsorption, size distribution, grafting density, and an extensive physicochemical characterization, we correlated the cytotoxicity and cellular uptake mechanism of 6 nm magnetic NPs coated with several types and various densities of biomolecules, such as glucose, galactose, and poly(ethylene glycol). We found that the density of the grafted molecule was crucial to prevent unspecific uptake of NPs by Vero cells. Surprisingly, the glucose-coated NPs described here showed cellular uptake as a result of lipid raft instead of clathrin-mediated cellular internalization. Moreover, these glucose-functionalized NPs could be one of the first examples of NPs being endocytosed by caveolae that finally end up in the lysosomes. These results reinforce the use of simple carbohydrates as an alternative to PEG molecules for NPs functionalization when cellular uptake is required.
The NW coast of the Iberian Peninsula is dominated by extensive shellfish farming, which places this region as a world leader in mussel production. Harmful algal blooms in the area frequent lead to lengthy harvesting closures threatening food security. This study developed a framework for the detection of Pseudo-nitzschia blooms in the Galician rias from satellite data (MERIS full-resolution images) and identified key variables that affect their abundance and toxicity. Two events of toxin-containing Pseudo-nitzschia were detected (up to 2.5 μg L−1 pDA) in the area. This study suggests that even moderate densities of Pseudo-nitzschia in this area might indicate high toxin content. Empirical models for particulate domoic acid (pDA) were developed based on MERIS FR data. The resulting remote-sensing model, including MERIS bands centered around 510, 560, and 620 nm explain 73% of the pDA variance (R2 = 0.73, p < 0.001). The results show that higher salinity values and lower Si(OH)4/N ratios favour higher Pseudo-nitzschia spp. abundances. High pDA values seem to be associated with relatively high PO43, low NO3− concentrations, and low Si(OH)4/N. While MERIS FR data and regionally specific algorithms can be useful for detecting Pseudo-nitzschia blooms, nutrient relationships are crucial for predicting the toxicity of these blooms.
In our work, we aim to identify new candidate host biomarkers to discriminate between active TB patients (n = 28), latent infection (LTBI; n = 27) and uninfected (NoTBI; n = 42) individuals. For that, active TB patients and their contacts were recruited that donated serum and saliva samples. A multiplex assay was performed to study the concentration of different cytokines, chemokines and growth factors. Proteins with significant differences between groups were selected and logistic regression and the area under the ROC curve (AUC) was used to assess the diagnostic accuracy. The best marker combinations that discriminate active TB from NoTBI contacts were [IP-10 + IL-7] in serum and [Fractalkine + IP-10 + IL-1α + VEGF] in saliva. Best discrimination between active TB and LTBI was achieved using [IP-10 + BCA-1] in serum (AUC = 0.83) and IP-10 in saliva (p = 0.0007; AUC = 0.78). The levels of TNFα (p = 0.003; AUC = 0.73) in serum and the combination of [Fractalkine +IL-12p40] (AUC = 0.83) in saliva, were able to differentiate between NoTBI and LTBI contacts. In conclusion, different individual and combined protein markers could help to discriminate between active TB and both uninfected and latently-infected contacts. The most promising ones include [IP-10 + IL-7], [IP-10 + BCA-1] and TNFα in serum and [Fractalkine + IP-10 + IL-1α + VEGF], IP-10 and [Fractalkine+IL-12p40] in saliva.
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