Second best toll and capacity optimisation in network: solution algorithm and policy implications

This paper looks at the first and second-best jointly optimal toll and road capacity investment problems from both policy and technical oriented perspectives. On the technical side, the paper investigates the applicability of the constraint cutting algorithm for solving the second-best problem under elastic demand which is formulated as a bilevel programming problem. The approach is shown to perform well despite several problems encountered by our previous work in Shepherd and Sumalee (2004). The paper then applies the algorithm to a small sized network to investigate the policy implications of the first and second-best cases. This policy analysis demonstrates that the joint first best structure is to invest in the most direct routes while reducing capacities elsewhere. Whilst unrealistic this acts as a useful benchmark. The results also show that certain second best policies can achieve a high proportion of the first best benefits while in general generating a revenue surplus. We also show that unless costs of capacity are known to be low then second best tolls will be affected and so should be analysed in conjunction with investments in the network

Brain white matter damage and its association with neuronal synchrony during sleep

The restorative function of sleep partly relies on its ability to deeply synchronize cerebral networks to create large slow oscillations observable with EEG. However, whether a brain can properly synchronize and produce a restorative sleep when it undergoes massive and widespread white matter damage is unknown. Here, we answer this question by testing 23 patients with various levels of white matter damage secondary to moderate to severe traumatic brain injuries (ages 18–56; 17 males, six females, 11–39 months post-injury) and compared them to 27 healthy subjects of similar age and sex. We used MRI and diffusion tensor imaging metrics (e.g. fractional anisotropy as well as mean, axial and radial diffusivities) to characterize voxel-wise white matter damage. We measured the following slow wave characteristics for all slow waves detected in N2 and N3 sleep stages: peak-to-peak amplitude, negative-to-positive slope, negative and positive phase durations, oscillation frequency, and slow wave density. Correlation analyses were performed in traumatic brain injury and control participants separately, with age as a covariate. Contrary to our hypotheses, we found that greater white matter damage mainly over the frontal and temporal brain regions was strongly correlated with a pattern of higher neuronal synchrony characterized by slow waves of larger amplitudes and steeper negative-to-positive slopes during non-rapid eye movement sleep. The same pattern of associations with white matter damage was also observed with markers of high homeostatic sleep pressure. More specifically, higher white matter damage was associated with higher slow-wave activity power, as well as with more severe complaints of cognitive fatigue. These associations between white matter damage and sleep were found only in our traumatic brain injured participants, with no such correlation in controls. Our results suggest that, contrary to previous observations in healthy controls, white matter damage does not prevent the expected high cerebral synchrony during sleep. Moreover, our observations challenge the current line of hypotheses that white matter microstructure deterioration reduces cerebral synchrony during sleep. Our results showed that the relationship between white matter and the brain’s ability to synchronize during sleep is neither linear nor simple

Sleep spindles are resilient to extensive white matter deterioration

Sleep spindles are an essential part of non-rapid eye movement sleep, notably involved in sleep consolidation, cognition, learning and memory. These oscillatory waves depend on an interaction loop between the thalamus and the cortex, which relies on a structural backbone of thalamo-cortical white matter tracts. It is still largely unknown if the brain can properly produce sleep spindles when it underwent extensive white matter deterioration in these tracts, and we hypothesized that it would affect sleep spindle generation and morphology. We tested this hypothesis with chronic moderate to severe traumatic brain injury (n ¼ 23; 30.5 6 11.1 years old; 17 m/6f), a unique human model of extensive white matter deterioration, and a healthy control group (n ¼ 27; 30.3 6 13.4 years old; 21m/6f). Sleep spindles were analysed on a full night of polysomnography over the frontal, central and parietal brain regions, and we measured their density, morphology and sigma-band power. White matter deterioration was quantified using diffusion-weighted MRI, with which we performed both whole-brain voxel-wise analysis (Tract-Based Spatial Statistics) and probabilistic tractography (with High Angular Resolution Diffusion Imaging) to target the thalamo-cortical tracts. Group differences were assessed for all variables and correlations were performed separately in each group, corrected for age and multiple comparisons. Surprisingly, although extensive white matter damage across the brain including all thalamo-cortical tracts was evident in the brain-injured group, sleep spindles remained completely undisrupted when compared to a healthy control group. In addition, almost all sleep spindle characteristics were not associated with the degree of white matter deterioration in the braininjured group, except that more white matter deterioration correlated with lower spindle frequency over the frontal regions. This study highlights the resilience of sleep spindles to the deterioration of all white matter tracts critical to their existence, as they conserve normal density during non-rapid eye movement sleep with mostly unaltered morphology. We show that even with such a severe traumatic event, the brain has the ability to adapt or to withstand alterations in order to conserve normal sleep spindles

The YARHG Domain: An Extracellular Domain in Search of a Function

We have identified a new bacterial protein domain that we hypothesise binds to peptidoglycan. This domain is called the YARHG domain after the most highly conserved sequence-segment. The domain is found in the extracellular space and is likely to be composed of four alpha-helices. The domain is found associated with protein kinase domains, suggesting it is associated with signalling in some bacteria. The domain is also found associated with three different families of peptidases. The large number of different domains that are found associated with YARHG suggests that it is a useful functional module that nature has recombined multiple times

Exopolysaccharide-associated protein sorting in environmental organisms: the PEP-CTERM/EpsH system. Application of a novel phylogenetic profiling heuristic

BACKGROUND: Protein translocation to the proper cellular destination may be guided by various classes of sorting signals recognizable in the primary sequence. Detection in some genomes, but not others, may reveal sorting system components by comparison of the phylogenetic profile of the class of sorting signal to that of various protein families. RESULTS: We describe a short C-terminal homology domain, sporadically distributed in bacteria, with several key characteristics of protein sorting signals. The domain includes a near-invariant motif Pro-Glu-Pro (PEP). This possible recognition or processing site is followed by a predicted transmembrane helix and a cluster rich in basic amino acids. We designate this domain PEP-CTERM. It tends to occur multiple times in a genome if it occurs at all, with a median count of eight instances; Verrucomicrobium spinosum has sixty-five. PEP-CTERM-containing proteins generally contain an N-terminal signal peptide and exhibit high diversity and little homology to known proteins. All bacteria with PEP-CTERM have both an outer membrane and exopolysaccharide (EPS) production genes. By a simple heuristic for screening phylogenetic profiles in the absence of pre-formed protein families, we discovered that a homolog of the membrane protein EpsH (exopolysaccharide locus protein H) occurs in a species when PEP-CTERM domains are found. The EpsH family contains invariant residues consistent with a transpeptidase function. Most PEP-CTERM proteins are encoded by single-gene operons preceded by large intergenic regions. In the Proteobacteria, most of these upstream regions share a DNA sequence, a probable cis-regulatory site that contains a sigma-54 binding motif. The phylogenetic profile for this DNA sequence exactly matches that of three proteins: a sigma-54-interacting response regulator (PrsR), a transmembrane histidine kinase (PrsK), and a TPR protein (PrsT). CONCLUSION: These findings are consistent with the hypothesis that PEP-CTERM and EpsH form a protein export sorting system, analogous to the LPXTG/sortase system of Gram-positive bacteria, and correlated to EPS expression. It occurs preferentially in bacteria from sediments, soils, and biofilms. The novel method that led to these findings, partial phylogenetic profiling, requires neither global sequence clustering nor arbitrary similarity cutoffs and appears to be a rapid, effective alternative to other profiling methods

An analysis of single amino acid repeats as use case for application specific background models

Background Sequence analysis aims to identify biologically relevant signals against a backdrop of functionally meaningless variation. Increasingly, it is recognized that the quality of the background model directly affects the performance of analyses. State-of-the-art approaches rely on classical sequence models that are adapted to the studied dataset. Although performing well in the analysis of globular protein domains, these models break down in regions of stronger compositional bias or low complexity. While these regions are typically filtered, there is increasing anecdotal evidence of functional roles. This motivates an exploration of more complex sequence models and application-specific approaches for the investigation of biased regions. Results Traditional Markov-chains and application-specific regression models are compared using the example of predicting runs of single amino acids, a particularly simple class of biased regions. Cross-fold validation experiments reveal that the alternative regression models capture the multi-variate trends well, despite their low dimensionality and in contrast even to higher-order Markov-predictors. We show how the significance of unusual observations can be computed for such empirical models. The power of a dedicated model in the detection of biologically interesting signals is then demonstrated in an analysis identifying the unexpected enrichment of contiguous leucine-repeats in signal-peptides. Considering different reference sets, we show how the question examined actually defines what constitutes the 'background'. Results can thus be highly sensitive to the choice of appropriate model training sets. Conversely, the choice of reference data determines the questions that can be investigated in an analysis. Conclusions Using a specific case of studying biased regions as an example, we have demonstrated that the construction of application-specific background models is both necessary and feasible in a challenging sequence analysis situation

Speed, Variability, and Timing of Motor Output in ADHD: Which Measures are Useful for Endophenotypic Research?

Attention-Deficit/Hyperactivity Disorder (ADHD) shares a genetic basis with motor coordination problems and probably motor timing problems. In line with this, comparable problems in motor timing should be observed in first degree relatives and might, therefore, form a suitable endophenotypic candidate. This hypothesis was investigated in 238 ADHD-families (545 children) and 147 control-families (271 children). A motor timing task was administered, in which children had to produce a 1,000 ms interval. In addition to this task, two basic motor tasks were administered to examine speed and variability of motor output, when no timing component was required. Results indicated that variability in motor timing is a useful endophenotypic candidate: It was clearly associated with ADHD, it was also present in non-affected siblings, and it correlated within families. Accuracy (under- versus over-production) in motor timing appeared less useful: Even though accuracy was associated with ADHD (probands and affected siblings had a tendency to under-produce the 1,000 ms interval compared to controls), non-affected siblings did not differ from controls and sibling correlations were only marginally significant. Slow and variable motor output without timing component also appears present in ADHD, but not in non-affected siblings, suggesting these deficits not to be related to a familial vulnerability for ADHD. Deficits in motor timing could not be explained by deficits already present in basic motor output without a timing component. This suggests abnormalities in motor timing were predominantly related to deficient motor timing processes and not to general deficient motor functioning. The finding that deficits in motor timing run in ADHD-families suggests this to be a fruitful domain for further exploration in relation to the genetic underpinnings of ADHD

Annotation Error in Public Databases: Misannotation of Molecular Function in Enzyme Superfamilies

Due to the rapid release of new data from genome sequencing projects, the majority of protein sequences in public databases have not been experimentally characterized; rather, sequences are annotated using computational analysis. The level of misannotation and the types of misannotation in large public databases are currently unknown and have not been analyzed in depth. We have investigated the misannotation levels for molecular function in four public protein sequence databases (UniProtKB/Swiss-Prot, GenBank NR, UniProtKB/TrEMBL, and KEGG) for a model set of 37 enzyme families for which extensive experimental information is available. The manually curated database Swiss-Prot shows the lowest annotation error levels (close to 0% for most families); the two other protein sequence databases (GenBank NR and TrEMBL) and the protein sequences in the KEGG pathways database exhibit similar and surprisingly high levels of misannotation that average 5%–63% across the six superfamilies studied. For 10 of the 37 families examined, the level of misannotation in one or more of these databases is >80%. Examination of the NR database over time shows that misannotation has increased from 1993 to 2005. The types of misannotation that were found fall into several categories, most associated with “overprediction” of molecular function. These results suggest that misannotation in enzyme superfamilies containing multiple families that catalyze different reactions is a larger problem than has been recognized. Strategies are suggested for addressing some of the systematic problems contributing to these high levels of misannotation

Opposing effects of cancer-type-specific SPOP mutants on BET protein degradation and sensitivity to BET inhibitors.

It is generally assumed that recurrent mutations within a given cancer driver gene elicit similar drug responses. Cancer genome studies have identified recurrent but divergent missense mutations affecting the substrate-recognition domain of the ubiquitin ligase adaptor SPOP in endometrial and prostate cancers. The therapeutic implications of these mutations remain incompletely understood. Here we analyzed changes in the ubiquitin landscape induced by endometrial cancer-associated SPOP mutations and identified BRD2, BRD3 and BRD4 proteins (BETs) as SPOP-CUL3 substrates that are preferentially degraded by endometrial cancer-associated SPOP mutants. The resulting reduction of BET protein levels sensitized cancer cells to BET inhibitors. Conversely, prostate cancer-specific SPOP mutations resulted in impaired degradation of BETs, promoting their resistance to pharmacologic inhibition. These results uncover an oncogenomics paradox, whereby mutations mapping to the same domain evoke opposing drug susceptibilities. Specifically, we provide a molecular rationale for the use of BET inhibitors to treat patients with endometrial but not prostate cancer who harbor SPOP mutations

The oral microbiome – an update for oral healthcare professionals

For millions of years, our resident microbes have coevolved and coexisted with us in a mostly harmonious symbiotic relationship. We are not distinct entities from our microbiome, but together we form a 'superorganism' or holobiont, with the microbiome playing a significant role in our physiology and health. The mouth houses the second most diverse microbial community in the body, harbouring over 700 species of bacteria that colonise the hard surfaces of teeth and the soft tissues of the oral mucosa. Through recent advances in technology, we have started to unravel the complexities of the oral microbiome and gained new insights into its role during both health and disease. Perturbations of the oral microbiome through modern-day lifestyles can have detrimental consequences for our general and oral health. In dysbiosis, the finely-tuned equilibrium of the oral ecosystem is disrupted, allowing disease-promoting bacteria to manifest and cause conditions such as caries, gingivitis and periodontitis. For practitioners and patients alike, promoting a balanced microbiome is therefore important to effectively maintain or restore oral health. This article aims to give an update on our current knowledge of the oral microbiome in health and disease and to discuss implications for modern-day oral healthcare