Quantum Dot Based Heterostructures for Unassisted Photoelectrochemical Hydrogen Generation

TiO₂ hollow nanowires (HNWs) and nanoparticles (NPs) constitute promising architectures for QDs sensitized photoanodes for H₂ generation. We sensitize these structures with CdS/CdSe quantum dots by two different methods (chemical bath deposition, CBD and succesive ionic layer adsorption and reaction, SILAR) and evaluate the performance of these photoelectrodes. Remarkable photocurrents of 4 mA·cm and 8 mA·cm^?2 and hydrogen generation rates of 40 ml·cm^?2·day^?1 and 80 ml·cm^?2·day^?1 have been obtained in a three electrode configuration with sacrificial hole scavengers (Na₂S and Na₂SO₃), for HNWs and NPs respectively, which is confirmed through gas analysis. More importantly, autonomous generation of H₂ (20 ml·cm^?2·day^?1 corresponding to 2 mA·cm^?2 photocurrent) is obtained in a two electrode configuration at short circuit under 100 mW·cm^?2 illumination, clearly showing that these photoanodes can produce hydrogen without the assistance of any external bias. To the best of the authors' knowledge, this is the highest unbiased solar H₂ generation rate reported for these of QDs based heterostructures. Impedance spectroscopy measurements show similar electron density of trap states below the TiO₂ conduction band while the recombination resistance was higher for HNWs, consistently with the much lower surface area compared to NPs. However, the conductivity of both structures is similar, in spite of the one dimensional character of HNWs, which leaves some room for improvement of these nanowired structures. The effect of the QDs deposition method is also evaluated. Both structures show remarkable stability without any appreciable photocurrent loss after 0.5 hour of operation. The findings of this study constitute a relevant step towards the feasibility of hydrogen generation with wide bandgap semiconductors/quantum dots based heterostructures.     

Glycan-binding profile of DC-like cells

Modification of vaccine carriers by decoration with glycans can enhance binding to and even targeting of dendritic cells (DCs), thus augmenting vaccine efficacy. To find a specific glycan-“vector” it is necessary to know glycan-binding profile of DCs. This task is not trivial; the small number of circulating blood DCs available for isolation hinders screening and therefore advancement of the profiling. It would be more convenient to employ long-term cell cultures or even primary DCs from murine blood. We therefore examined whether THP-1 (human monocyte cell line) and DC2.4 (immature murine DC-like cell line) could serve as a model for human DCs. These cells were probed with a set of glycans previously identified as binding to circulating human CD14low/-CD16+CD83+ DCs. In addition, we tested a subpopulation of murine CD14low/-CD80+СD11c+CD16+ cells reported as relating to the human CD14low/-CD16+CD83+ cells. Manα1–3(Manα1–6)Manβ1–4GlcNAcβ1–4GlcNAcβ bound to both the cell lines and the murine CD14low/-CD80+СD11c+CD16+ cells. Primary cells, but not the cell cultures, were capable of binding GalNAcα1–3Galβ (Adi), the most potent ligand for binding to human circulating DCs. In conclusion, not one of the studied cell lines proved an adequate model for DCs processes involving lectin binding. Although the glycan-binding profile of BYRB-Rb (8.17)1Iem mouse DCs could prove useful for assessing human DCs, important glycan interactions were missing, a situation which was aggravated when employing cells from the BALB/c strain. Accordingly, one must treat results from murine work with caution when seeking vaccine targeting of human DCs, and certainly should avoid cell lines such as THP-1 and DC2.4 cells.     

Investigating the heat shock protein response involved in coral bleaching across scleractinian species in the central Red Sea

Coral Reefs - Coral bleaching represents the most serious threat to contemporary coral reefs. In response, focus is being laid on understanding the cellular processes involved in the response of...     

Sequential adaptive variables and subject selection for GEE methods

Modeling correlated or highly stratified multiple-response data is a common data analysis task in many applications, such as those in large epidemiological studies or multisite cohort studies. The generalized estimating equations method is a popular statistical method used to analyze these kinds of data, because it can manage many types of unmeasured dependence among outcomes. Collecting large amounts of highly stratified or correlated response data is time-consuming; thus, the use of a more aggressive sampling strategy that can accelerate this process—such as the active-learning methods found in the machine-learning literature—will always be beneficial. In this study, we integrate adaptive sampling and variable selection features into a sequential procedure for modeling correlated response data. Besides reporting the statistical properties of the proposed procedure, we also use both synthesized and real data sets to demonstrate the usefulness of our method.     

Mitochondrial targeting of recombinant RNAs modulates the level of a heteroplasmic mutation in human mitochondrial DNA associated with Kearns Sayre Syndrome

Mitochondrial mutations, an important cause of incurable human neuromuscular diseases, are mostly heteroplasmic: mutated mitochondrial DNA is present in cells simultaneously with wild-type genomes, the pathogenic threshold being generally >70% of mutant mtDNA. We studied whether heteroplasmy level could be decreased by specifically designed oligoribonucleotides, targeted into mitochondria by the pathway delivering RNA molecules in vivo. Using mitochondrially imported RNAs as vectors, we demonstrated that oligoribonucleotides complementary to mutant mtDNA region can specifically reduce the proportion of mtDNA bearing a large deletion associated with the Kearns Sayre Syndrome in cultured transmitochondrial cybrid cells. These findings may be relevant to developing of a new tool for therapy of mtDNA associated diseases.     

Calcium and iron as key drivers of brown moss composition through differential effects on phosphorus availability

Brown moss-dominated rich fens are characterized by minerotrophic conditions, in which calcium (Ca) and iron (Fe) concentrations show large variations. We examined the relative importance of Ca and Fe in relation to the occurrence of three typical brown moss species: Scorpidium scorpioides, Scorpidium cossonii, and Hamatocaulis vernicosus. Peat chemistry was examined in 24 stands of brown moss-dominated rich fens: 12 in the Netherlands and 12 in central Sweden. Ca and Fe turned out to be important drivers of brown moss composition. Fens dominated by Scorpidium scorpioides or Scorpidium cossonii were characterized by high pore water Ca-concentrations and total soil Ca-contents, but low P-availability. In these Ca-rich, but Fe-poor fens, foliar N:P ratios of vascular vegetation exceeded 20?g?g^?1, indicating phosphorus (P)-limitation due to Ca-P precipitation or low P-sorption capacity due to low Fe-levels. In contrast, fens dominated by Hamatocaulis vernicosus were characterized by high pore water Fe-concentrations and total soil Fe-contents, but also relatively high P-availability. N:P ratios in these fens were below 13.5?g?g^?1, indicating potential nitrogen (N)-limitation. We conclude that the relative roles of Ca and Fe, as related to the geohydrological conditions present, strongly determine the brown moss composition in rich fens through their differential effects on plant P-availability.