Importance of dissolved neutral mercury sulfides for methyl mercury production in contaminated sediments

Biotic transformation of inorganic mercury, Hg(II), to mono methyl mercury (MeHg) is proposed to be largely controlled by passive uptake of neutral Hg complexes by sulfate reducing bacteria (SRB). In this study, the chemical speciation of Hg(II) in seven locally contaminated sediments covering environments such as (i) brackish water, (ii) low-productivity freshwater, and, (iii) high-productivity freshwater was related to potential Hg methylation rates, determined by incubation at 23 degrees C for 48 h under N2(g), and to total MeHg concentrations in sediments. Pore water speciation was modeled considering Hg complexes with halides, organic thiols [Hg(SR)2(aq), associated to dissolved organic matter], monosulfides, and bisulfides. The sum of neutral mercury sulfides [Hg(SH)20(aq)] and [HgS0(aq)] was significantly, positively (p < 0.001, n = 20) correlated to the specific methylation rate constant (Km, day(-1)) at depths of 5-100 cm in two brackish water sediments. Total Hg, total mercury sulfides or Hg(SR)2(aq) in pore water gave no significant relationships with Km. In two subsets of freshwater sediments, neutral mercury sulfides were positively correlated to total Hg in pore water, and therefore, total Hg also gave significant relationships with Km. The sum of [Hg(SH)20(aq)] and [HgS0(aq)] was significantly, positively correlated to total sediment MeHg (microg kg-1) in brackish waters (p < 0.001, n = 23), in southern, high-productivity freshwaters (p < 0.001, n = 20), as well as in northern, low-productivity freshwater (p = 0.048, n = 6). The slopes (b, b') of the relationships Km (day-1) = a + b([Hg(SH)20(aq)] + [HgS0(aq)]) and MeHg (microg kg-1) = a' + b'([Hg(SH)20(aq)] + [HgS0(aq)]) showed an inverse relationship with the C/N ratio, supposedly reflecting differences in primary production and energy-rich organic matter availability among sites. We conclude that concentrations of neutral inorganic mercury sulfide species, together with the availability of energy-rich organic matter, largely control Hg methylation rates in contaminated sediments. Furthermore, Hg(SH)20(aq) is suggested to be the dominant species taken up by MeHg producing bacteria in organic-rich sediments without formation of HgS(s).     

In Vitro Validation of the Therapeutic Potential of Dendrimer-Based Nanoformulations against Tumor Stem Cells

Tumor cells with stem cell properties are considered to play major roles in promoting the development and malignant behavior of aggressive cancers. Therapeutic strategies that efficiently eradicate such tumor stem cells are of highest clinical need. Herein, we performed the validation of the polycationic phosphorus dendrimer-based approach for small interfering RNAs delivery in in vitro stem-like cells as models. As a therapeutic target, we chose Lyn, a member of the Src family kinases as an example of a prominent enzyme class widely discussed as a potent anti-cancer intervention point. Our selection is guided by our discovery that Lyn mRNA expression level in glioma, a class of brain tumors, possesses significant negative clinical predictive value, promoting its potential as a therapeutic target for future molecular-targeted treatments. We then showed that anti-Lyn siRNA, delivered into Lyn-expressing glioma cell model reduces the cell viability, a fact that was not observed in a cell model that lacks Lyn-expression. Furthermore, we have found that the dendrimer itself influences various parameters of the cells such as the expression of surface markers PD-L1, TIM-3 and CD47, targets for immune recognition and other biological processes suggested to be regulating glioblastoma cell invasion. Our findings prove the potential of dendrimer-based platforms for therapeutic applications, which might help to eradicate the population of cancer cells with augmented chemotherapy resistance. Moreover, the results further promote our functional stem cell technology as suitable component in early stage drug development.     

High-field electron transport in semiconducting zigzag carbon nanotubes

Electron transport in semiconducting zigzag carbon nanotubes is studied by solving the Boltzmann transport equation using the single-particle Monte Carlo technique. The electronic band structure is based on a standard nearest-neighbour tight-binding parameterization, and the phonon spectrum is calculated using a fourth nearest-neighbour force constant model. The electron-phonon scattering probabilities are calculated within a tight-binding formalism. The steady-state drift velocities for the semiconducting zigzag nanotubes (8, 0), (10, 0), (11, 0), (13, 0), and (25, 0) are computed as functions of electric field strength and temperature, and the results are analysed here. The results show the presence of negative differential resistance at high electric fields for some of the nanotubes. The drift velocity and the low-field mobility reach a maximum value of ? 4.67 × 10? cm s?1 and? 4 × 10? cm2 V?1 s?1, respectively, for a (25, 0) nanotube.     

Regression conformal prediction with random forests

Regression conformal prediction produces prediction intervals that are valid, i.e., the probability of excluding the correct target value is bounded by a predefined confidence level. The most important criterion when comparing conformal regressors is efficiency; the prediction intervals should be as tight (informative) as possible. In this study, the use of random forests as the underlying model for regression conformal prediction is investigated and compared to existing state-of-the-art techniques, which are based on neural networks and k-nearest neighbors. In addition to their robust predictive performance, random forests allow for determining the size of the prediction intervals by using out-of-bag estimates instead of requiring a separate calibration set. An extensive empirical investigation, using 33 publicly available data sets, was undertaken to compare the use of random forests to existing state-of-the-art conformal predictors. The results show that the suggested approach, on almost all confidence levels and using both standard and normalized nonconformity functions, produced significantly more efficient conformal predictors than the existing alternatives.     

Field Test to Restore Original Geochemical Conditions in a Flooded Mine Area-An Essential Milestone for the Complete Remediation of the Königstein Uranium Mine

Mine Water and the Environment - Uranium was extracted in the Königstein uranium mine by in-situ leaching with sulfuric acid until 1990. The originally anoxic conditions in the ore body became...     

Engineering the Ligand Specificity of the Human Galectin-1 by Incorporation of Tryptophan Analogues

Galectin-1 is a β-galactoside-binding lectin with manifold biological functions. A single tryptophan residue (W68) in its carbohydrate binding site plays a major role in ligand binding and is highly conserved among galectins. To fine tune galectin-1 specificity, we introduced several non-canonical tryptophan analogues at this position of human galectin-1 and analyzed the resulting variants using glycan microarrays. Two variants containing 7-azatryptophan and 7-fluorotryptophan showed a reduced affinity for 3’-sulfated oligosaccharides. Their interaction with different ligands was further analyzed by fluorescence polarization competition assay. Using molecular modeling we provide structural clues that the change in affinities comes from modulated interactions and solvation patterns. Thus, we show that the introduction of subtle atomic mutations in the ligand binding site of galectin-1 is an attractive approach for fine-tuning its interactions with different ligands.     

Selective Monovalent Galectin-8 Ligands Based on 3-Lactoylgalactoside

Galectin-8 has gained attention as a potential new pharmacological target for the treatment of various diseases, including cancer, inflammation, and disorders associated with bone mass reduction. To that end, new molecular probes are needed in order to better understand its role and its functions. Herein we aimed to improve the affinity and target selectivity of a recently published galectin-8 ligand, 3-O-[1-carboxyethyl]-β-d -galactopyranoside, by introducing modifications at positions 1 and 3 of the galactose. Affinity data measured by fluorescence polarization show that the most potent compound reached a K_D of 12 μM. Furthermore, reasonable selectivity versus other galectins was achieved, making the highlighted compound a promising lead for the development of new selective and potent ligands for galectin-8 as molecular probes to examine the protein's role in cell-based and in vivo studies.     

Nonlinear All-Optical Coherent Generation and Read-Out of Valleys in Atomically Thin Semiconductors

With conventional electronics reaching performance and size boundaries, all-optical processes have emerged as ideal building blocks for high speed and low power consumption devices. A promising approach in this direction is provided by valleytronics in atomically thin semiconductors, where light-matter interaction allows to write, store, and read binary information into the two energetically degenerate but non-equivalent valleys. Here, nonlinear valleytronics in monolayer WSe₂ is investigated and show that an individual ultrashort pulse with a photon energy tuned to half of the optical band-gap can be used to simultaneously excite (by coherent optical Stark shift) and detect (by a rotation in the polarization of the emitted second harmonic) the valley population.     

Epitopes Displayed in a Cyclic Peptide Scaffold Bind SARS-COV-2 Antibodies

The SARS-CoV-2 virus that causes COVID-19 is a global health issue. The spread of the virus has resulted in seven million deaths to date. The emergence of new viral strains highlights the importance of continuous surveillance of the SARS-CoV-2 virus by using timely and accurate diagnostic tools. Here, we used a stable cyclic peptide scaffolds to present antigenic sequences derived from the spike protein that are reactive to SARS-CoV-2 antibodies. Using peptide sequences from different domains of SARS-CoV-2 spike proteins, we grafted epitopes on the peptide scaffold sunflower trypsin inhibitor 1 (SFTI-1). These scaffold peptides were then used to develop an ELISA to detect SARS-CoV-2 antibodies in serum. We show that displaying epitopes on the scaffold improves reactivity overall. One of the scaffold peptides (S2_1146-1161_c) has reactivity equal to that of commercial assays, and shows diagnostic potential.