A rare case of complete C2–C3 dislocation with mild neurological symptoms

The authors report a rare case of complete C2–C3 dislocation with unexpectedly mild neurological symptoms in a 57 year old man involved in a motor vehicle accident, who had previously undergone posterior laminectomy from C3 through C7. A retrospective chart analysis and a thorough radiographic review were performed. X-rays and CT of the cervical spine demonstrated a complete dislocation at the C2–C3 level. Computed tomographic angiography revealed disruption of both vertebral arteries; however, blood flow was evident in the basilar artery. After radiologically guided placement in cervical traction with tongs that reduced the subluxation by approximately 50% the patient had spontaneous eye opening and was able to follow commands. A two-stage 360(o) stabilization and fusion was performed and the patient was finally discharged 24 days after admission with his neurological status essentially unchanged. In conclusion, our patient presented with surprisingly mild neurological symptoms. The previously performed laminectomy could have both predisposed to injury as well as protected his spinal cord from potentially fatal trauma

Major reduction of malaria morbidity with combined vitamin A and zinc supplementation in young children in Burkina Faso: a randomized double blind trial

BACKGROUND: Vitamin A and zinc are crucial for normal immune function, and may play a synergistic role for reducing the risk of infection including malaria caused by Plasmodium falciparum. METHODS: A randomized, double-blind, placebo-controlled trial of a single dose of 200 000 IU of vitamin A with daily zinc supplementation was done in children of Sourkoudougou village, Burkina Faso. Children aged from 6 to 72 months were randomized to receive a single dose of 200 000 IU of vitamin A plus 10 mg elemental zinc, six days a week (n = 74) or placebo (n = 74) for a period of six months. Cross-sectional surveys were conducted at the beginning and the end of the study, and children were evaluated daily for fever. Microscopic examination of blood smear was done in the case of fever (temperature > or =37.5 degrees C) for malaria parasite detection. RESULTS: At the end of the study we observed a significant decrease in the prevalence malaria in the supplemented group (34%) compared to the placebo group (3.5%) (p < 0.001). Malaria episodes were lower in the supplemented group (p = 0.029), with a 30.2% reduction of malaria cases (p = 0.025). Time to first malaria episode was longer in the supplemented group (p = 0.015). The supplemented group also had 22% fewer fever episodes than the placebo group (p = 0.030). CONCLUSION: These results suggest that combined vitamin A plus zinc supplementation reduces the risk of fever and clinical malaria episodes among children, and thus may play a key role in malaria control strategies for children in Africa

A Genome-Wide Gene Function Prediction Resource for Drosophila melanogaster

Predicting gene functions by integrating large-scale biological data remains a challenge for systems biology. Here we present a resource for Drosophila melanogaster gene function predictions. We trained function-specific classifiers to optimize the influence of different biological datasets for each functional category. Our model predicted GO terms and KEGG pathway memberships for Drosophila melanogaster genes with high accuracy, as affirmed by cross-validation, supporting literature evidence, and large-scale RNAi screens. The resulting resource of prioritized associations between Drosophila genes and their potential functions offers a guide for experimental investigations

Finding the “Dark Matter” in Human and Yeast Protein Network Prediction and Modelling

Accurate modelling of biological systems requires a deeper and more complete knowledge about the molecular components and their functional associations than we currently have. Traditionally, new knowledge on protein associations generated by experiments has played a central role in systems modelling, in contrast to generally less trusted bio-computational predictions. However, we will not achieve realistic modelling of complex molecular systems if the current experimental designs lead to biased screenings of real protein networks and leave large, functionally important areas poorly characterised. To assess the likelihood of this, we have built comprehensive network models of the yeast and human proteomes by using a meta-statistical integration of diverse computationally predicted protein association datasets. We have compared these predicted networks against combined experimental datasets from seven biological resources at different level of statistical significance. These eukaryotic predicted networks resemble all the topological and noise features of the experimentally inferred networks in both species, and we also show that this observation is not due to random behaviour. In addition, the topology of the predicted networks contains information on true protein associations, beyond the constitutive first order binary predictions. We also observe that most of the reliable predicted protein associations are experimentally uncharacterised in our models, constituting the hidden or “dark matter” of networks by analogy to astronomical systems. Some of this dark matter shows enrichment of particular functions and contains key functional elements of protein networks, such as hubs associated with important functional areas like the regulation of Ras protein signal transduction in human cells. Thus, characterising this large and functionally important dark matter, elusive to established experimental designs, may be crucial for modelling biological systems. In any case, these predictions provide a valuable guide to these experimentally elusive regions

Directed Mammalian Gene Regulatory Networks Using Expression and Comparative Genomic Hybridization Microarray Data from Radiation Hybrids

Meiotic mapping of quantitative trait loci regulating expression (eQTLs) has allowed the construction of gene networks. However, the limited mapping resolution of these studies has meant that genotype data are largely ignored, leading to undirected networks that fail to capture regulatory hierarchies. Here we use high resolution mapping of copy number eQTLs (ceQTLs) in a mouse-hamster radiation hybrid (RH) panel to construct directed genetic networks in the mammalian cell. The RH network covering 20,145 mouse genes had significant overlap with, and similar topological structures to, existing biological networks. Upregulated edges in the RH network had significantly more overlap than downregulated. This suggests repressive relationships between genes are missed by existing approaches, perhaps because the corresponding proteins are not present in the cell at the same time and therefore unlikely to interact. Gene essentiality was positively correlated with connectivity and betweenness centrality in the RH network, strengthening the centrality-lethality principle in mammals. Consistent with their regulatory role, transcription factors had significantly more outgoing edges (regulating) than incoming (regulated) in the RH network, a feature hidden by conventional undirected networks. Directed RH genetic networks thus showed concordance with pre-existing networks while also yielding information inaccessible to current undirected approaches

Looking at Cerebellar Malformations through Text-Mined Interactomes of Mice and Humans

WE HAVE GENERATED AND MADE PUBLICLY AVAILABLE TWO VERY LARGE NETWORKS OF MOLECULAR INTERACTIONS: 49,493 mouse-specific and 52,518 human-specific interactions. These networks were generated through automated analysis of 368,331 full-text research articles and 8,039,972 article abstracts from the PubMed database, using the GeneWays system. Our networks cover a wide spectrum of molecular interactions, such as bind, phosphorylate, glycosylate, and activate; 207 of these interaction types occur more than 1,000 times in our unfiltered, multi-species data set. Because mouse and human genes are linked through an orthological relationship, human and mouse networks are amenable to straightforward, joint computational analysis. Using our newly generated networks and known associations between mouse genes and cerebellar malformation phenotypes, we predicted a number of new associations between genes and five cerebellar phenotypes (small cerebellum, absent cerebellum, cerebellar degeneration, abnormal foliation, and abnormal vermis). Using a battery of statistical tests, we showed that genes that are associated with cerebellar phenotypes tend to form compact network clusters. Further, we observed that cerebellar malformation phenotypes tend to be associated with highly connected genes. This tendency was stronger for developmental phenotypes and weaker for cerebellar degeneration

Proteomic and Phospho-Proteomic Profile of Human Platelets in Basal, Resting State: Insights into Integrin Signaling

During atherogenesis and vascular inflammation quiescent platelets are activated to increase the surface expression and ligand affinity of the integrin αIIbβ3 via inside-out signaling. Diverse signals such as thrombin, ADP and epinephrine transduce signals through their respective GPCRs to activate protein kinases that ultimately lead to the phosphorylation of the cytoplasmic tail of the integrin αIIbβ3 and augment its function. The signaling pathways that transmit signals from the GPCR to the cytosolic domain of the integrin are not well defined. In an effort to better understand these pathways, we employed a combination of proteomic profiling and computational analyses of isolated human platelets. We analyzed ten independent human samples and identified a total of 1507 unique proteins in platelets. This is the most comprehensive platelet proteome assembled to date and includes 190 membrane-associated and 262 phosphorylated proteins, which were identified via independent proteomic and phospho-proteomic profiling. We used this proteomic dataset to create a platelet protein-protein interaction (PPI) network and applied novel contextual information about the phosphorylation step to introduce limited directionality in the PPI graph. This newly developed contextual PPI network computationally recapitulated an integrin signaling pathway. Most importantly, our approach not only provided insights into the mechanism of integrin αIIbβ3 activation in resting platelets but also provides an improved model for analysis and discovery of PPI dynamics and signaling pathways in the future

Кинетика восстановления железа при восстановительной плавке рудоугольных окатышей

Исследовано влияние интенсивности теплообмена на кинетику восстановления железа в процессе плавки рудоугольных окатышей. Показано, что с ростом интенсивности теплообмена повышается скорость восстановительных процессов. Вследствие роста коэффициента теплообмена увеличивается глубина восстановленного слоя окатыша, существенно изменяются его структура и химический состав образующейся металлической фазы.Досліджено вплив інтенсивності теплообміну на кінетику відновлення заліза в процесі плавки рудовугільних окатишів. Показано, що при зростанні інтенсивності теплообміну підвищується швидкість відновлювальних процесів. Внаслідок зростання коефіцієнту теплообміну збільшується глибина відновленого шару окатиша, суттєво змінюються його структура та хімічний склад металевої фази, що утворюється.Influence of intensity of heat exchange is investigational on kinetics reduction of iron in the process of melting ore-coal pellets. It is rotined that speed of reduction processes rises with growth of intensity of heat exchange. Because of growth of coefficient of heat exchange the depth of the recovered layer of pellet is increased, his structure and chemical composition of appearing metallic phase changes substantially

Network Compression as a Quality Measure for Protein Interaction Networks

With the advent of large-scale protein interaction studies, there is much debate about data quality. Can different noise levels in the measurements be assessed by analyzing network structure? Because proteomic regulation is inherently co-operative, modular and redundant, it is inherently compressible when represented as a network. Here we propose that network compression can be used to compare false positive and false negative noise levels in protein interaction networks. We validate this hypothesis by first confirming the detrimental effect of false positives and false negatives. Second, we show that gold standard networks are more compressible. Third, we show that compressibility correlates with co-expression, co-localization, and shared function. Fourth, we also observe correlation with better protein tagging methods, physiological expression in contrast to over-expression of tagged proteins, and smart pooling approaches for yeast two-hybrid screens. Overall, this new measure is a proxy for both sensitivity and specificity and gives complementary information to standard measures such as average degree and clustering coefficients