A Spatial Model of Mosquito Host-Seeking Behavior

Mosquito host-seeking behavior and heterogeneity in host distribution are important factors in predicting the transmission dynamics of mosquito-borne infections such as dengue fever, malaria, chikungunya, and West Nile virus. We develop and analyze a new mathematical model to describe the effect of spatial heterogeneity on the contact rate between mosquito vectors and hosts. The model includes odor plumes generated by spatially distributed hosts, wind velocity, and mosquito behavior based on both the prevailing wind and the odor plume. On a spatial scale of meters and a time scale of minutes, we compare the effectiveness of different plume-finding and plume-tracking strategies that mosquitoes could use to locate a host. The results show that two different models of chemotaxis are capable of producing comparable results given appropriate parameter choices and that host finding is optimized by a strategy of flying across the wind until the odor plume is intercepted. We also assess the impact of changing the level of host aggregation on mosquito host-finding success near the end of the host-seeking flight. When clusters of hosts are more tightly associated on smaller patches, the odor plume is narrower and the biting rate per host is decreased. For two host groups of unequal number but equal spatial density, the biting rate per host is lower in the group with more individuals, indicative of an attack abatement effect of host aggregation. We discuss how this approach could assist parameter choices in compartmental models that do not explicitly model the spatial arrangement of individuals and how the model could address larger spatial scales and other probability models for mosquito behavior, such as Lévy distributions

‘Functional Connectivity’ Is a Sensitive Predictor of Epilepsy Diagnosis after the First Seizure

Background: Although epilepsy affects almost 1 % of the world population, diagnosis of this debilitating disease is still difficult. The EEG is an important tool for epilepsy diagnosis and classification, but the sensitivity of interictal epileptiform discharges (IEDs) on the first EEG is only 30–50%. Here we investigate whether using ‘functional connectivity ’ can improve the diagnostic sensitivity of the first interictal EEG in the diagnosis of epilepsy. Methodology/Principal Findings: Patients were selected from a database with 390 standard EEGs of patients after a first suspected seizure. Patients who were later diagnosed with epilepsy (i.e. $two seizures) were compared to matched nonepilepsy patients (with a minimum follow-up of one year). The synchronization likelihood (SL) was used as an index of functional connectivity of the EEG, and average SL per patient was calculated in seven frequency bands. In total, 114 patients were selected. Fifty-seven patients were diagnosed with epilepsy (20 had IEDs on their EEG) and 57 matched patients had other diagnoses. Epilepsy patients had significantly higher SL in the theta band than non-epilepsy patients. Furthermore, theta band SL proved to be a significant predictor of a diagnosis of epilepsy. When only those epilepsy patients without IEDs were considered (n = 74), theta band SL could predict diagnosis with specificity of 76 % and sensitivity of 62%. Conclusion/Significance: Theta band functional connectivity may be a useful diagnostic tool in diagnosing epilepsy

Interaction between M-Like Protein and Macrophage Thioredoxin Facilitates Antiphagocytosis for Streptococcus equi ssp. zooepidemicus

Streptococcus equi ssp. zooepidemicus (S. zooepidemicus, S.z) is one of the common pathogens that can cause septicemia, meningitis, and mammitis in domesticated species. M-like protein (SzP) is an important virulence factor of S. zooepidemicus and contributes to bacterial infection and antiphagocytosis. The interaction between SzP of S. zooepidemicus and porcine thioredoxin (TRX) was identified by the yeast two-hybrid and further confirmed by co-immunoprecipitation. SzP interacted with both reduced and the oxidized forms of TRX without inhibiting TRX activity. Membrane anchored SzP was able to recruit TRX to the surface, which would facilitate the antiphagocytosis of the bacteria. Further experiments revealed that TRX regulated the alternative complement pathway by inhibiting C3 convertase activity and associating with factor H (FH). TRX alone inhibited C3 cleavage and C3a production, and the inhibitory effect was additive when FH was also present. TRX inhibited C3 deposition on the bacterial surface when it was recruited by SzP. These new findings indicated that S. zooepidemicus used SzP to recruit TRX and regulated the alternative complement pathways to evade the host immune phagocytosis

Disruption of Rolandic Gamma-Band Functional Connectivity by Seizures is Associated with Motor Impairments in Children with Epilepsy

Although children with epilepsy exhibit numerous neurological and cognitive deficits, the mechanisms underlying these impairments remain unclear. Synchronization of oscillatory neural activity in the gamma frequency range (>30 Hz) is purported to be a mechanism mediating functional integration within neuronal networks supporting cognition, perception and action. Here, we tested the hypothesis that seizure-induced alterations in gamma synchronization are associated with functional deficits. By calculating synchrony among electrodes and performing graph theoretical analysis, we assessed functional connectivity and local network structure of the hand motor area of children with focal epilepsy from intracranial electroencephalographic recordings. A local decrease in inter-electrode phase synchrony in the gamma bands during ictal periods, relative to interictal periods, within the motor cortex was strongly associated with clinical motor weakness. Gamma-band ictal desychronization was a stronger predictor of deficits than the presence of the seizure-onset zone or lesion within the motor cortex. There was a positive correlation between the magnitude of ictal desychronization and impairment of motor dexterity in the contralateral, but not ipsilateral hand. There was no association between ictal desynchronization within the hand motor area and non-motor deficits. This study uniquely demonstrates that seizure-induced disturbances in cortical functional connectivity are associated with network-specific neurological deficits

Epilepsy is related to theta band brain connectivity and network topology in brain tumor patients

<p>Abstract</p> <p>Background</p> <p>Both epilepsy patients and brain tumor patients show altered functional connectivity and less optimal brain network topology when compared to healthy controls, particularly in the theta band. Furthermore, the duration and characteristics of epilepsy may also influence functional interactions in brain networks. However, the specific features of connectivity and networks in tumor-related epilepsy have not been investigated yet. We hypothesize that epilepsy characteristics are related to (theta band) connectivity and network architecture in operated glioma patients suffering from epileptic seizures. Included patients participated in a clinical study investigating the effect of levetiracetam monotherapy on seizure frequency in glioma patients, and were assessed at two time points: directly after neurosurgery (t1), and six months later (t2). At these time points, magnetoencephalography (MEG) was recorded and information regarding clinical status and epilepsy history was collected. Functional connectivity was calculated in six frequency bands, as were a number of network measures such as normalized clustering coefficient and path length.</p> <p>Results</p> <p>At the two time points, MEG registrations were performed in respectively 17 and 12 patients. No changes in connectivity or network topology occurred over time. Increased theta band connectivity at t1 and t2 was related to a higher total number of seizures. Furthermore, higher number of seizures was related to a less optimal, more random brain network topology. Other factors were not significantly related to functional connectivity or network topology.</p> <p>Conclusions</p> <p>These results indicate that (pathologically) increased theta band connectivity is related to a higher number of epileptic seizures in brain tumor patients, suggesting that theta band connectivity changes are a hallmark of tumor-related epilepsy. Furthermore, a more random brain network topology is related to greater vulnerability to seizures. Thus, functional connectivity and brain network architecture may prove to be important parameters of tumor-related epilepsy.</p

The Connectome Visualization Utility: Software for Visualization of Human Brain Networks

In analysis of the human connectome, the connectivity of the human brain is collected from multiple imaging modalities and analyzed using graph theoretical techniques. The dimensionality of human connectivity data is high, and making sense of the complex networks in connectomics requires sophisticated visualization and analysis software. The current availability of software packages to analyze the human connectome is limited. The Connectome Visualization Utility (CVU) is a new software package designed for the visualization and network analysis of human brain networks. CVU complements existing software packages by offering expanded interactive analysis and advanced visualization features, including the automated visualization of networks in three different complementary styles and features the special visualization of scalar graph theoretical properties and modular structure. By decoupling the process of network creation from network visualization and analysis, we ensure that CVU can visualize networks from any imaging modality. CVU offers a graphical user interface, interactive scripting, and represents data uses transparent neuroimaging and matrix-based file types rather than opaque application-specific file formats

Hv-CBF2A overexpression in barley accelerates COR gene transcript accumulation and acquisition of freezing tolerance during cold acclimation

Abstract C-Repeat Binding Factors (CBFs) are DNAbinding transcriptional activators of gene pathways imparting freezing tolerance. Poaceae contain three CBF subfamilies, two of which, HvCBF3/CBFIII and HvCBF4/CBFIV, are unique to this taxon. To gain mechanistic insight into HvCBF4/CBFIV CBFs we overexpressed Hv-CBF2A in spring barley (Hordeum vulgare) cultivar ‘Golden Promise’. The Hv-CBF2A overexpressing lines exhibited stunted growth, poor yield, and greater freezing tolerance compared to non-transformed ‘Golden Promise’. Differences in freezing tolerance were apparent only upon cold acclimation. During cold acclimation freezing tolerance of the Hv-CBF2A overexpressing lines increased more rapidly than that of ‘Golden Promise’ and paralleled the freezing tolerance of the winter hardy barley ‘Dicktoo’. Transcript levels of candidate CBF target genes, COR14B and DHN5 were increased in the overexpressor lines at warm temperatures, and at cold temperatures they accumulated to much higher levels in the Hv-CBF2A overexpressors than in ‘Golden Promise’. Hv-CBF2A overexpression also increased transcript levels of other CBF genes at FROST RESISTANCE-H2-H2 (FR-H2) possessing CRT/DRE sites in their upstream regions, the most notable of which was CBF12. CBF12 transcript levels exhibited a relatively constant incremental increase above levels in ‘Golden Promise’ both at warm and cold. These data indicate that Hv-CBF2A activates target genes at warm temperatures and that transcript accumulation for some of these targets is greatly enhanced by cold temperatures

A922 Sequential measurement of 1 hour creatinine clearance (1-CRCL) in critically ill patients at risk of acute kidney injury (AKI)

Meeting abstrac

MEG Network Differences between Low- and High-Grade Glioma Related to Epilepsy and Cognition

OBJECTIVE: To reveal possible differences in whole brain topology of epileptic glioma patients, being low-grade glioma (LGG) and high-grade glioma (HGG) patients. We studied functional networks in these patients and compared them to those in epilepsy patients with non-glial lesions (NGL) and healthy controls. Finally, we related network characteristics to seizure frequency and cognitive performance within patient groups. METHODS: We constructed functional networks from pre-surgical resting-state magnetoencephalography (MEG) recordings of 13 LGG patients, 12 HGG patients, 10 NGL patients, and 36 healthy controls. Normalized clustering coefficient and average shortest path length as well as modular structure and network synchronizability were computed for each group. Cognitive performance was assessed in a subset of 11 LGG and 10 HGG patients. RESULTS: LGG patients showed decreased network synchronizability and decreased global integration compared to healthy controls in the theta frequency range (4-8 Hz), similar to NGL patients. HGG patients' networks did not significantly differ from those in controls. Network characteristics correlated with clinical presentation regarding seizure frequency in LGG patients, and with poorer cognitive performance in both LGG and HGG glioma patients. CONCLUSION: Lesion histology partly determines differences in functional networks in glioma patients suffering from epilepsy. We suggest that differences between LGG and HGG patients' networks are explained by differences in plasticity, guided by the particular lesional growth pattern. Interestingly, decreased synchronizability and decreased global integration in the theta band seem to make LGG and NGL patients more prone to the occurrence of seizures and cognitive decline