Therapies for neonatal encephalopathy: Targeting the latent, secondary and tertiary phases of evolving brain injury

In term and near-term neonates with neonatal encephalopathy, therapeutic hypothermia protocols are well established. The current focus is on how to improve outcomes further and the challenge is to find safe and complementary therapies that confer additional protection, regeneration or repair in addition to cooling. Following hypoxia-ischemia, brain injury evolves over three main phases (latent, secondary and tertiary), each with a different brain energy, perfusion, neurochemical and inflammatory milieu. While therapeutic hypothermia has targeted the latent and secondary phase, we now need therapies that cover the continuum of brain injury that spans hours, days, weeks and months after the initial event. Most agents have several therapeutic actions but can be broadly classified under a predominant action (e.g., free radical scavenging, anti-apoptotic, anti-inflammatory, neuroregeneration, and vascular effects). Promising early/secondary phase therapies include Allopurinol, Azithromycin, Exendin-4, Magnesium, Melatonin, Noble gases and Sildenafil. Tertiary phase agents include Erythropoietin, Stem cells and others. We review a selection of promising therapeutic agents on the translational pipeline and suggest a framework for neuroprotection and neurorestoration that targets the evolving injury

Characterizing Interdisciplinarity of Researchers and Research Topics Using Web Search Engines

Researchers' networks have been subject to active modeling and analysis. Earlier literature mostly focused on citation or co-authorship networks reconstructed from annotated scientific publication databases, which have several limitations. Recently, general-purpose web search engines have also been utilized to collect information about social networks. Here we reconstructed, using web search engines, a network representing the relatedness of researchers to their peers as well as to various research topics. Relatedness between researchers and research topics was characterized by visibility boost-increase of a researcher's visibility by focusing on a particular topic. It was observed that researchers who had high visibility boosts by the same research topic tended to be close to each other in their network. We calculated correlations between visibility boosts by research topics and researchers' interdisciplinarity at individual level (diversity of topics related to the researcher) and at social level (his/her centrality in the researchers' network). We found that visibility boosts by certain research topics were positively correlated with researchers' individual-level interdisciplinarity despite their negative correlations with the general popularity of researchers. It was also found that visibility boosts by network-related topics had positive correlations with researchers' social-level interdisciplinarity. Research topics' correlations with researchers' individual- and social-level interdisciplinarities were found to be nearly independent from each other. These findings suggest that the notion of "interdisciplinarity" of a researcher should be understood as a multi-dimensional concept that should be evaluated using multiple assessment means.Comment: 20 pages, 7 figures. Accepted for publication in PLoS On

A pilot study of the King LT supralaryngeal airway use in a rural Iowa EMS system

Introduction In 2003, the King Laryngeal Tube (LT) received FDA approval for US sales. Prehospital systems in urban setting have begun evaluating and adopting the LT for clinical airway management. However, it is not routinely approved by State EMS Boards for use by all prehospita

Fast network centrality analysis using GPUs

<p>Abstract</p> <p>Background</p> <p>With the exploding volume of data generated by continuously evolving high-throughput technologies, biological network analysis problems are growing larger in scale and craving for more computational power. General Purpose computation on Graphics Processing Units (GPGPU) provides a cost-effective technology for the study of large-scale biological networks. Designing algorithms that maximize data parallelism is the key in leveraging the power of GPUs.</p> <p>Results</p> <p>We proposed an efficient data parallel formulation of the All-Pairs Shortest Path problem, which is the key component for shortest path-based centrality computation. A betweenness centrality algorithm built upon this formulation was developed and benchmarked against the most recent GPU-based algorithm. Speedup between 11 to 19% was observed in various simulated scale-free networks. We further designed three algorithms based on this core component to compute closeness centrality, eccentricity centrality and stress centrality. To make all these algorithms available to the research community, we developed a software package <it>gpu</it>-<it>fan </it>(GPU-based Fast Analysis of Networks) for CUDA enabled GPUs. Speedup of 10-50× compared with CPU implementations was observed for simulated scale-free networks and real world biological networks.</p> <p>Conclusions</p> <p><it>gpu</it>-<it>fan </it>provides a significant performance improvement for centrality computation in large-scale networks. Source code is available under the GNU Public License (GPL) at <url>http://bioinfo.vanderbilt.edu/gpu-fan/</url>.</p

Surface electromyography pattern of human swallowing

<p>Abstract</p> <p>Background</p> <p>The physiology of swallowing is characterized by a complex and coordinated activation of many stomatognathic, pharyngeal, and laryngeal muscles. Kinetics and electromyographic studies have widely investigated the pharyngeal and laryngeal pattern of deglutition in order to point out the differences between normal and dysphagic people. In the dental field, muscular activation during swallowing is believed to be the cause of malocclusion.</p> <p>Despite the clinical importance given to spontaneous swallowing, few physiologic works have studied stomatognathic muscular activation and mandibular movement during spontaneous saliva swallowing.</p> <p>The aim of our study was to investigate the activity patterns of the mandibular elevator muscles (masseter and anterior temporalis muscles), the submental muscles, and the neck muscles (sternocleidomastoid muscles) in healthy people during spontaneous swallowing of saliva and to relate the muscular activities to mandibular movement.</p> <p>Methods</p> <p>The spontaneous swallowing of saliva of 111 healthy individuals was analyzed using surface electromyography (SEMG) and a computerized kinesiography of mandibular movement.</p> <p>Results</p> <p>Fifty-seven of 111 patients swallowed without occlusal contact (SNOC) and 54 individuals had occlusal contact (SOC). The sternocleidomastoid muscles showed a slight, but constant activation during swallowing. The SEMG of the submental and sternocleidomastoid muscles showed no differences between the two groups. The SEMG of the anterior temporalis and masseter muscles showed significant differences (p < 0.0001). The duration of swallowing was significantly higher in the SNOC subjects. Gender and age were not related to electromyographic activation. Healthy SOC and SNOC behaved in different ways.</p> <p>Conclusion</p> <p>The data suggest that there is not a single "normal" or "typical" pattern for spontaneous saliva swallowing. The polygraph seemed a valuable, simple, non-invasive and reliable tool to study the physiology of swallowing.</p

Growth in Children with Cerebral Palsy during five years after Selective Dorsal Rhizotomy: a practice-based study

Background: Overweight is reported as a side effect of SDR. The aims were to study the development of weight, height and body mass index (BMI) during five years after SDR. Methods: This prospective, longitudinal and practice-based study included all 56 children with CP spastic diplegia undergoing SDR from the start in March 1993 to April 2003 in our hospital. The preoperative Gross Motor Function Classification System (GMFCS) levels were I-II in 17, III in 15, IV-V in 24 children. Median age at SDR was 4.3 years (range 2.4-7.4 years). Weight and height/recumbent length were measured. Swedish growth charts for typically developing children generated weight, height and BMI z-scores for age and gender. Results: The preoperative median z-scores were for height-1.92 and for body mass index (BMI)-0.22. Five years later, the median BMI z-score was increased by + 0.57 (p + 2 SD) increased (p < 0.05). Baseline BMI and age at the start of follow-up influenced the BMI change during the five years (p < 0.001 and p < 0.05 respectively). The individual growth was highly variable, but a tendency towards increasing stunting with age was seen in severe gross motor dysfunction (GMFCS levels IV-V) and the opposite, a slight catch-up of height in children with walking ability (GMFCS levels I-III). Conclusions: These are the first available subtype-and GMFCS-specific longitudinal growth data for children with CP spastic diplegia. Their growth potential according to these data should be regarded as a minimum, as some children were undernourished. It is unknown whether the spasticity reduction through SDR increased the weight gain velocity, or if the relative weight increase was part of the general "obesity epidemic". For some children the weight increase was highly desirable. In others, it resulted in overweight and obesity with risk of negative health effects. Weight and height should be monitored to enable early prevention of weight aberrations also causing problems with mobility, activity and participation

Midlife muscle strength and human longevity up to age 100 years: a 44-year prospective study among a decedent cohort

We studied prospectively the midlife handgrip strength, living habits, and parents’ longevity as predictors of length of life up to becoming a centenarian. The participants were 2,239 men from the Honolulu Heart Program/Honolulu–Asia Aging Study who were born before the end of June 1909 and who took part in baseline physical assessment in 1965–1968, when they were 56–68 years old. Deaths were followed until the end of June 2009 for 44 years with complete ascertainment. Longevity was categorized as centenarian (≥100 years, n = 47), nonagenarian (90–99 years, n = 545), octogenarian (80–89 years, n = 847), and ≤79 years (n = 801, reference). The average survival after baseline was 20.8 years (SD = 9.62). Compared with people who died at the age of ≤79 years, centenarians belonged 2.5 times (odds ratio (OR) = 2.52, 95% confidence interval (CI) = 1.23–5.10) more often to the highest third of grip strength in midlife, were never smokers (OR = 5.75 95% CI = 3.06–10.80), had participated in physical activity outside work (OR = 1.13 per daily hour, 95% CI = 1.02–1.25), and had a long-lived mother (≥80 vs. ≤60 years, OR = 2.3, 95% CI = 1.06–5.01). Associations for nonagenarians and octogenarians were parallel, but weaker. Multivariate modeling showed that mother’s longevity and offspring’s grip strength operated through the same or overlapping pathway to longevity. High midlife grip strength and long-lived mother may indicate resilience to aging, which, combined with healthy lifestyle, increases the probability of extreme longevity

A Coevolutionary Residue Network at the Site of a Functionally Important Conformational Change in a Phosphohexomutase Enzyme Family

Coevolution analyses identify residues that co-vary with each other during evolution, revealing sequence relationships unobservable from traditional multiple sequence alignments. Here we describe a coevolutionary analysis of phosphomannomutase/phosphoglucomutase (PMM/PGM), a widespread and diverse enzyme family involved in carbohydrate biosynthesis. Mutual information and graph theory were utilized to identify a network of highly connected residues with high significance. An examination of the most tightly connected regions of the coevolutionary network reveals that most of the involved residues are localized near an interdomain interface of this enzyme, known to be the site of a functionally important conformational change. The roles of four interface residues found in this network were examined via site-directed mutagenesis and kinetic characterization. For three of these residues, mutation to alanine reduces enzyme specificity to ∼10% or less of wild-type, while the other has ∼45% activity of wild-type enzyme. An additional mutant of an interface residue that is not densely connected in the coevolutionary network was also characterized, and shows no change in activity relative to wild-type enzyme. The results of these studies are interpreted in the context of structural and functional data on PMM/PGM. Together, they demonstrate that a network of coevolving residues links the highly conserved active site with the interdomain conformational change necessary for the multi-step catalytic reaction. This work adds to our understanding of the functional roles of coevolving residue networks, and has implications for the definition of catalytically important residues

Network Structure Implied by Initial Axon Outgrowth in Rodent Cortex: Empirical Measurement and Models

The developmental mechanisms by which the network organization of the adult cortex is established are incompletely understood. Here we report on empirical data on the development of connections in hamster isocortex and use these data to parameterize a network model of early cortical connectivity. Using anterograde tracers at a series of postnatal ages, we investigate the growth of connections in the early cortical sheet and systematically map initial axon extension from sites in anterior (motor), middle (somatosensory) and posterior (visual) cortex. As a general rule, developing axons extend from all sites to cover relatively large portions of the cortical field that include multiple cortical areas. From all sites, outgrowth is anisotropic, covering a greater distance along the medial/lateral axis than along the anterior/posterior axis. These observations are summarized as 2-dimensional probability distributions of axon terminal sites over the cortical sheet. Our network model consists of nodes, representing parcels of cortex, embedded in 2-dimensional space. Network nodes are connected via directed edges, representing axons, drawn according to the empirically derived anisotropic probability distribution. The networks generated are described by a number of graph theoretic measurements including graph efficiency, node betweenness centrality and average shortest path length. To determine if connectional anisotropy helps reduce the total volume occupied by axons, we define and measure a simple metric for the extra volume required by axons crossing. We investigate the impact of different levels of anisotropy on network structure and volume. The empirically observed level of anisotropy suggests a good trade-off between volume reduction and maintenance of both network efficiency and robustness. Future work will test the model's predictions for connectivity in larger cortices to gain insight into how the regulation of axonal outgrowth may have evolved to achieve efficient and economical connectivity in larger brains

Assessing the functional coherence of modules found in multiple-evidence networks from Arabidopsis

<p>Abstract</p> <p>Background</p> <p>Combining multiple evidence-types from different information sources has the potential to reveal new relationships in biological systems. The integrated information can be represented as a relationship network, and clustering the network can suggest possible functional modules. The value of such modules for gaining insight into the underlying biological processes depends on their functional coherence. The challenges that we wish to address are to define and quantify the functional coherence of modules in relationship networks, so that they can be used to infer function of as yet unannotated proteins, to discover previously unknown roles of proteins in diseases as well as for better understanding of the regulation and interrelationship between different elements of complex biological systems.</p> <p>Results</p> <p>We have defined the functional coherence of modules with respect to the Gene Ontology (GO) by considering two complementary aspects: (i) the fragmentation of the GO functional categories into the different modules and (ii) the most representative functions of the modules. We have proposed a set of metrics to evaluate these two aspects and demonstrated their utility in <it>Arabidopsis thaliana</it>. We selected 2355 proteins for which experimentally established protein-protein interaction (PPI) data were available. From these we have constructed five relationship networks, four based on single types of data: PPI, co-expression, co-occurrence of protein names in scientific literature abstracts and sequence similarity and a fifth one combining these four evidence types. The ability of these networks to suggest biologically meaningful grouping of proteins was explored by applying Markov clustering and then by measuring the functional coherence of the clusters.</p> <p>Conclusions</p> <p>Relationship networks integrating multiple evidence-types are biologically informative and allow more proteins to be assigned to a putative functional module. Using additional evidence types concentrates the functional annotations in a smaller number of modules without unduly compromising their consistency. These results indicate that integration of more data sources improves the ability to uncover functional association between proteins, both by allowing more proteins to be linked and producing a network where modular structure more closely reflects the hierarchy in the gene ontology.</p