Efficient Dynamic Approximate Distance Oracles for Vertex-Labeled Planar Graphs

Let $G$ be a graph where each vertex is associated with a label. A Vertex-Labeled Approximate Distance Oracle is a data structure that, given a vertex $v$ and a label $\lambda$, returns a $(1+\varepsilon)$-approximation of the distance from $v$ to the closest vertex with label $\lambda$ in $G$. Such an oracle is dynamic if it also supports label changes. In this paper we present three different dynamic approximate vertex-labeled distance oracles for planar graphs, all with polylogarithmic query and update times, and nearly linear space requirements

Composite repetition-aware data structures

In highly repetitive strings, like collections of genomes from the same species, distinct measures of repetition all grow sublinearly in the length of the text, and indexes targeted to such strings typically depend only on one of these measures. We describe two data structures whose size depends on multiple measures of repetition at once, and that provide competitive tradeoffs between the time for counting and reporting all the exact occurrences of a pattern, and the space taken by the structure. The key component of our constructions is the run-length encoded BWT (RLBWT), which takes space proportional to the number of BWT runs: rather than augmenting RLBWT with suffix array samples, we combine it with data structures from LZ77 indexes, which take space proportional to the number of LZ77 factors, and with the compact directed acyclic word graph (CDAWG), which takes space proportional to the number of extensions of maximal repeats. The combination of CDAWG and RLBWT enables also a new representation of the suffix tree, whose size depends again on the number of extensions of maximal repeats, and that is powerful enough to support matching statistics and constant-space traversal.Comment: (the name of the third co-author was inadvertently omitted from previous version

Distribution of catecholamine fibers in the cochlear nucleus of horseshoe bats and mustache bats

The glyoxylic-acid-induced fluorescence technique was applied to demonstrate patterns of catecholaminergic innervation within the auditory brainstem of echolocating bats and the house mouse. In the cochlear nucleus of the rufous horseshoe bat (Rhinolophus rouxi) and the mustache bat (Pteronotus parnelli), species-specific catecholaminergic innervation patterns are found that contrast with the relatively homogeneous innervation in the rodent. In both bats the subnuclei of the cochlear nucleus receive a differentially dense supply of catecholaminergic fibers, and within the subnuclei, the catecholamine innervation densities can be correlated with the tonotopic frequency representation. The areas devoted to the high-frequency echolocation calls are less densely innervated than those regions which are responsive to lower frequencies. Apart from this common scheme, there are noteworthy distinctions between the two bats which correlate with specialized cytoarchitectural features of the cochlear nucleus. The marginal cell group, located medially to the anteroventral cochlear nucleus of Pteronotus, receives the densest supply of catecholaminergic fibers of all auditory nuclei. This plexus is formed by a morphologically distinct population of catecholaminergic fibers

Decoherent Histories Quantum Mechanics with One 'Real' Fine-Grained History

Decoherent histories quantum theory is reformulated with the assumption that there is one "real" fine-grained history, specified in a preferred complete set of sum-over-histories variables. This real history is described by embedding it in an ensemble of comparable imagined fine-grained histories, not unlike the familiar ensemble of statistical mechanics. These histories are assigned extended probabilities, which can sometimes be negative or greater than one. As we will show, this construction implies that the real history is not completely accessible to experimental or other observational discovery. However, sufficiently and appropriately coarse-grained sets of alternative histories have standard probabilities providing information about the real fine-grained history that can be compared with observation. We recover the probabilities of decoherent histories quantum mechanics for sets of histories that are recorded and therefore decohere. Quantum mechanics can be viewed as a classical stochastic theory of histories with extended probabilities and a well-defined notion of reality common to all decoherent sets of alternative coarse-grained histories.Comment: 11 pages, one figure, expanded discussion and acknowledgment

Perceived impact of an online community care platform for Dutch older adults on local participation, informal caregiving, and feelings of connectedness: pretest-posttest observational study

Background: In a changing ageing society wherein older adults are increasingly expected to take care of themselves instead of relying on health care services, online community care platforms can help older adults to meet these expectations. A considerable number of these online community care platforms have been introduced in several European countries based on their potential. However, their actual impact is unclear. Objective: The aim of this study was to investigate the self-reported use, expectations, and perceived impact of a Dutch online community care platform called Grubbenvorst-Online among Dutch older adults. The following 2 questions were studied: (1) What is the self-reported use of Grubbenvorst-Online among older adults? (2) What are their expectations and perceived impact of Grubbenvorst-Online regarding local participation, their social network, mutual informal caregiving, and feelings of connectedness? Methods: An observational pretest-posttest study was conducted. Participants were recruited via a web-based message on the Grubbenvorst-Online platform and data were collected via postal questionnaires among older users at the start of the study and 4 months later. Data regarding the expectations and the perceived impact of Grubbenvorst-Online were compared and tested. Results: Forty-seven Grubbenvorst-Online users with an average age of 74 years participated in this study. They were healthy, predominantly “internet-skilled,” and they found the internet important for maintaining social contacts. In general, the use of the online community care platform decreased during the 4-month follow-up period. The perceived impact of Grubbenvorst-Online was significantly lower than that expected regarding information provision (P=.003), seeking help from fellow villagers (P<.001), giving help to fellow villagers (P<.001), and consulting care or welfare services (P<.001). Conclusions: The findings of this study indicate that online community care platforms perhaps do not provide enough “added value” in their current form. We suggest a new direction in which online community care platforms primarily support existing offline initiatives aimed at stimulating local participation, informal caregiving, and feelings of connectedness

RNA based approaches to profile oncogenic pathways from low quantity samples to drive precision oncology strategies

Precision treatment of cancer requires knowledge on active tumor driving signal transduction pathways to select the optimal effective targeted treatment. Currently only a subset of patients derive clinical benefit from mutation based targeted treatment, due to intrinsic and acquired drug resistance mechanisms. Phenotypic assays to identify the tumor driving pathway based on protein analysis are difficult to multiplex on routine pathology samples. In contrast, the transcriptome contains information on signaling pathway activity and can complement genomic analyses. Here we present the validation and clinical application of a new knowledge-based mRNA-based diagnostic assay platform (OncoSignal) for measuring activity of relevant signaling pathways simultaneously and quantitatively with high resolution in tissue samples and circulating tumor cells, specifically with very small specimen quantities. The approach uses mRNA levels of a pathway\u27s direct target genes, selected based on literature for multiple proof points, and used as evidence that a pathway is functionally activated. Using these validated target genes, a Bayesian network model has been built and calibrated on mRNA measurements of samples with known pathway status, which is used next to calculate a pathway activity score on individual test samples. Translation to RT-qPCR assays enables broad clinical diagnostic applications, including small analytes. A large number of cancer samples have been analyzed across a variety of cancer histologies and benchmarked across normal controls. Assays have been used to characterize cell types in the cancer cell microenvironment, including immune cells in which activated and immunotolerant states can be distinguished. Results support the expectation that the assays provide information on cancer driving signaling pathways which is difficult to derive from next generation DNA sequencing analysis. Current clinical oncology applications have been complementary to genomic mutation analysis to improve precision medicine: (1) prediction of response and resistance to various therapies, especially targeted therapy and immunotherapy; (2) assessment and monitoring of therapy efficacy; (3) prediction of invasive cancer cell behavior and prognosis; (4) measurement of circulating tumor cells. Preclinical oncology applications lie in a better understanding of cancer behavior across cancer types, and in development of a pathophysiology-based cancer classification for development of novel therapies and precision medicine