Accurate screened exchange band structures for transition metal monoxides MnO, FeO, CoO and NiO

We report calculations of the band structures and density of states of the four transition metal monoxides MnO, FeO, CoO and NiO using the hybrid density functional sX-LDA. Late transition metal oxides are prototypical examples of strongly correlated materials, which pose challenges for electronic structure methods. We compare our results with available experimental data and show that our calculations yield accurate predictions for the fundamental band gaps and valence bands of FeO, CoO and NiO. For MnO, the band gaps are underestimated, suggesting additional many-body effects that are not captured by our screened hybrid functional approach.Comment: 9 pages, 3 figures, 3 table

Lattice Dynamics and Specific Heat of α\alpha - GeTe: a theoretical and experimental study

We extend recent \textit{ab initio} calculations of the electronic band structure and the phonon dispersion relations of rhombohedral GeTe to calculations of the density of phonon states and the temperature dependent specific heat. The results are compared with measurements of the specific heat. It is discovered that the specific heat depends on hole concentration, not only in the very low temperature region (Sommerfeld term) but also at the maximum of $C_p/T^3$ (around 16 K). To explain this phenomenon, we have performed \textit{ab initio} lattice dynamical calculations for GeTe rendered metallic through the presence of a heavy hole concentration ($p$ $\sim$ 2$\times$ 10$^{21}$ cm$^{-3}$). They account for the increase observed in the maximum of $C_p/T^3$.Comment: 8 pages, 7 figures, ref. 19 correcte

Self-stabilizing algorithms for Connected Vertex Cover and Clique decomposition problems

In many wireless networks, there is no fixed physical backbone nor centralized network management. The nodes of such a network have to self-organize in order to maintain a virtual backbone used to route messages. Moreover, any node of the network can be a priori at the origin of a malicious attack. Thus, in one hand the backbone must be fault-tolerant and in other hand it can be useful to monitor all network communications to identify an attack as soon as possible. We are interested in the minimum \emph{Connected Vertex Cover} problem, a generalization of the classical minimum Vertex Cover problem, which allows to obtain a connected backbone. Recently, Delbot et al.~\cite{DelbotLP13} proposed a new centralized algorithm with a constant approximation ratio of $2$ for this problem. In this paper, we propose a distributed and self-stabilizing version of their algorithm with the same approximation guarantee. To the best knowledge of the authors, it is the first distributed and fault-tolerant algorithm for this problem. The approach followed to solve the considered problem is based on the construction of a connected minimal clique partition. Therefore, we also design the first distributed self-stabilizing algorithm for this problem, which is of independent interest

Experimental study of negative photoconductivity in n-PbTe(Ga) epitaxial films

We report on low-temperature photoconductivity (PC) in n-PbTe(Ga) epitaxial films prepared by the hot-wall technique on -BaF_2 substrates. Variation of the substrate temperature allowed us to change the resistivity of the films from 10^8 down to 10_{-2} Ohm x cm at 4.2 K. The resistivity reduction is associated with a slight excess of Ga concentration, disturbing the Fermi level pinning within the energy gap of n-PbTe(Ga). PC has been measured under continuous and pulse illumination in the temperature range 4.2-300 K. For films of low resistivity, the photoresponse is composed of negative and positive parts. Recombination processes for both effects are characterized by nonexponential kinetics depending on the illumination pulse duration and intensity. Analysis of the PC transient proves that the negative photoconductivity cannot be explained in terms of nonequilibrium charge carriers spatial separation of due to band modulation. Experimental results are interpreted assuming the mixed valence of Ga in lead telluride and the formation of centers with a negative correlation energy. Specifics of the PC process is determined by the energy levels attributed to donor Ga III, acceptor Ga I, and neutral Ga II states with respect to the crystal surrounding. The energy level corresponding to the metastable state Ga II is supposed to occur above the conduction band bottom, providing fast recombination rates for the negative PC. The superposition of negative and positive PC is considered to be dependent on the ratio of the densities of states corresponding to the donor and acceptor impurity centers.Comment: 7 pages, 4 figure

Detoxifying effect of Nelumbo nucifera and Aegle marmelos on hematological parameters of Common Carp (Cyprinus carpio L.)

The objective of this study was to investigate the efficacy of Nelumbo nucifera and Aegle marmelos on common carp exposed to sub-lethal concentrations of combined heavy metals (5 ppm) under laboratory conditions. The fish were treated with Nelumbo nucifera (500 mg/kg bwt) and Aegle marmelos (500 mg/kgbwt) for 30 days as a dietary supplement. The blood biochemical parameters of the fish were evaluated by analyzing the level of red blood cells (RBC), packed cell volume (PCV), hemoglobin concentration, glucose, cholesterol, iron and copper. The findings of the present investigation showed significant increase in hemoglobin (p<0.001), RBC (p<0.01) and PCV (p<0.01) of herbal drug-treated groups compared with metal-exposed fish. Conversely, glucose and cholesterol level in blood of common carp showed significant reduction compared with heavy-metal-exposed groups. All the values measured in Nelumbo nucifera and Aegle marmelos treated fish were restored comparably to control fish. Our results confirmed that Nelumbo nucifera and Aegle marmelos provide a detoxification mechanism for heavy metals in common carp

AEROBIC AND ANAEROBIC SCALING IN FISH

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/75506/1/j.1469-185X.1991.tb01134.x.pd

The Gene Ontology knowledgebase in 2023

The Gene Ontology (GO) knowledgebase (http://geneontology.org) is a comprehensive resource concerning the functions of genes and gene products (proteins and noncoding RNAs). GO annotations cover genes from organisms across the tree of life as well as viruses, though most gene function knowledge currently derives from experiments carried out in a relatively small number of model organisms. Here, we provide an updated overview of the GO knowledgebase, as well as the efforts of the broad, international consortium of scientists that develops, maintains, and updates the GO knowledgebase. The GO knowledgebase consists of three components: (1) the GO-a computational knowledge structure describing the functional characteristics of genes; (2) GO annotations-evidence-supported statements asserting that a specific gene product has a particular functional characteristic; and (3) GO Causal Activity Models (GO-CAMs)-mechanistic models of molecular "pathways" (GO biological processes) created by linking multiple GO annotations using defined relations. Each of these components is continually expanded, revised, and updated in response to newly published discoveries and receives extensive QA checks, reviews, and user feedback. For each of these components, we provide a description of the current contents, recent developments to keep the knowledgebase up to date with new discoveries, and guidance on how users can best make use of the data that we provide. We conclude with future directions for the project

In Vitro Transformation of Primary Human CD34+ Cells by AML Fusion Oncogenes: Early Gene Expression Profiling Reveals Possible Drug Target in AML

Different fusion oncogenes in acute myeloid leukemia (AML) have distinct clinical and laboratory features suggesting different modes of malignant transformation. Here we compare the in vitro effects of representatives of 4 major groups of AML fusion oncogenes on primary human CD34+ cells. As expected from their clinical similarities, MLL-AF9 and NUP98-HOXA9 had very similar effects in vitro. They both caused erythroid hyperplasia and a clear block in erythroid and myeloid maturation. On the other hand, AML1-ETO and PML-RARA had only modest effects on myeloid and erythroid differentiation. All oncogenes except PML-RARA caused a dramatic increase in long-term proliferation and self-renewal. Gene expression profiling revealed two distinct temporal patterns of gene deregulation. Gene deregulation by MLL-AF9 and NUP98-HOXA9 peaked 3 days after transduction. In contrast, the vast majority of gene deregulation by AML1-ETO and PML-RARA occurred within 6 hours, followed by a dramatic drop in the numbers of deregulated genes. Interestingly, the p53 inhibitor MDM2 was upregulated by AML1-ETO at 6 hours. Nutlin-3, an inhibitor of the interaction between MDM2 and p53, specifically inhibited the proliferation and self-renewal of primary human CD34+ cells transduced with AML1-ETO, suggesting that MDM2 upregulation plays a role in cell transformation by AML1-ETO. These data show that differences among AML fusion oncogenes can be recapitulated in vitro using primary human CD34+ cells and that early gene expression profiling in these cells can reveal potential drug targets in AML

Biomedical Discovery Acceleration, with Applications to Craniofacial Development

The profusion of high-throughput instruments and the explosion of new results in the scientific literature, particularly in molecular biomedicine, is both a blessing and a curse to the bench researcher. Even knowledgeable and experienced scientists can benefit from computational tools that help navigate this vast and rapidly evolving terrain. In this paper, we describe a novel computational approach to this challenge, a knowledge-based system that combines reading, reasoning, and reporting methods to facilitate analysis of experimental data. Reading methods extract information from external resources, either by parsing structured data or using biomedical language processing to extract information from unstructured data, and track knowledge provenance. Reasoning methods enrich the knowledge that results from reading by, for example, noting two genes that are annotated to the same ontology term or database entry. Reasoning is also used to combine all sources into a knowledge network that represents the integration of all sorts of relationships between a pair of genes, and to calculate a combined reliability score. Reporting methods combine the knowledge network with a congruent network constructed from experimental data and visualize the combined network in a tool that facilitates the knowledge-based analysis of that data. An implementation of this approach, called the Hanalyzer, is demonstrated on a large-scale gene expression array dataset relevant to craniofacial development. The use of the tool was critical in the creation of hypotheses regarding the roles of four genes never previously characterized as involved in craniofacial development; each of these hypotheses was validated by further experimental work

Gene Ontology annotations and resources.

The Gene Ontology (GO) Consortium (GOC, http://www.geneontology.org) is a community-based bioinformatics resource that classifies gene product function through the use of structured, controlled vocabularies. Over the past year, the GOC has implemented several processes to increase the quantity, quality and specificity of GO annotations. First, the number of manual, literature-based annotations has grown at an increasing rate. Second, as a result of a new 'phylogenetic annotation' process, manually reviewed, homology-based annotations are becoming available for a broad range of species. Third, the quality of GO annotations has been improved through a streamlined process for, and automated quality checks of, GO annotations deposited by different annotation groups. Fourth, the consistency and correctness of the ontology itself has increased by using automated reasoning tools. Finally, the GO has been expanded not only to cover new areas of biology through focused interaction with experts, but also to capture greater specificity in all areas of the ontology using tools for adding new combinatorial terms. The GOC works closely with other ontology developers to support integrated use of terminologies. The GOC supports its user community through the use of e-mail lists, social media and web-based resources