Partitioning space for range queries

It is shown that, given a set S of n points in R3, one can always find three planes that form an eight-partition of S, that is, a partition where at most n/8 points of S lie in each of the eight open regions. This theorem is used to define a data structure, called an octant tree, for representing any point set in R3. An octant tree for n points occupies O(n) space and can be constructed in polynomial time. With this data structure and its refinements, efficient solutions to various range query problems in 2 and 3 dimensions can be obtained, including (1) half-space queries: find all points of S that lie to one side of any given plane; (2) polyhedron queries: find all points that lie inside (outside) any given polyhedron; and (3) circular queries in R2: for a planar set S, find all points that lie inside (outside) any given circle. The retrieval time for all these queries is T(n)=O(na + m) where a= 0.8988 (or 0.8471 in case (3)) and m is the size of the output. This performance is the best currently known for linear-space data structures which can be deterministically constructed in polynomial time

Imaging cholinergic function in vivo in the brain with radioiodinated stereoisomers of quinuclidinyl benzilate

This thesis evaluates the ability of (R,S)- and (R,R)-[125I]-QNB, two radioiodinated diastereoisomers of the high affinity muscarinic antagonist quinuclidinyl benzilate (QNB), to image dynamic changes in cholinergic function in the central nervous system using in vivo autoradiography. The regional uptake and retention of (R,S)-[125I]-QNB in the rat brain between 2 and 24 hours after intravenous administration was investigated to assess the utility of this technique to image muscarinic receptors in the central nervous system. Similarly, the uptake and retention of (R,R)-[125I]-QNB was investigated between 30 mins and 6 hours after administration using in vivo autoradiography and was compared to that of (R,S)-[125I]-QNB. Secondly, the sensitivity of (R,S)- and (R,R)-[125I]-QNB to dynamic changes in cholinergic neurotransmission in vivo, was assessed in conscious rats. The uptake and retention of (R,S)- and (R,R)-[125I]-QNB following a cholinergic challenge produced by administration of the long lasting AChE inhibitor heptylphysostigmine, was investigated. Regional brain levels of (R,S)- and (R,R)-[125I]-QNB in heptylphysostigmine treated animals were compared to levels in saline treated animals by in vivo autoradiography. The ability of ACh to displace (R,S)- and (R,R)-[125I]-QNB binding from rat brain sections in vitro in the presence of heptylphysostigmine was also investigated. Finally, the effects of heptylphysostigmine administration on regional cerebral blood flow were investigated using [14C]-IAP autoradiography in conscious rats. Three hypotheses were considered to account for the lack of radioligand displacement observed following heptylphysostigmine administration: 1) Heptylphysostigmine was ineffective in inhibiting AChE and raising synaptic ACh levels at the dosage used in this thesis. 2) A small amount of displacement occurred but was masked by the effects of increased cerebral blood flow. 3) (R,S)- and (R,R)-[125I]-QNB are of too high affinity for mAChRs to be displaced by endogenous neurotransmitter. The third hypothesis is viewed as the most plausible. In conclusion, (R,S)- and (R,R)-[125I]-QNB are unsuitable ligands for the detection of cholinergic function in vivo

LiDAR mapping of tidal marshes for ecogeomorphological modelling in the TIDE project

The European research project TIDE (Tidal Inlets Dynamics and Environment) is developing and validating coupled models describing the morphological, biological and ecological evolution of tidal environments. The interactions between the physical and biological processes occurring in these regions requires that the system be studied as a whole rather than as separate parts. Extensive use of remote sensing including LiDAR is being made to provide validation data for the modelling. This paper describes the different uses of LiDAR within the project and their relevance to the TIDE science objectives. LiDAR data have been acquired from three different environments, the Venice Lagoon in Italy, Morecambe Bay in England, and the Eden estuary in Scotland. LiDAR accuracy at each site has been evaluated using ground reference data acquired with differential GPS. A semi-automatic technique has been developed to extract tidal channel networks from LiDAR data either used alone or fused with aerial photography. While the resulting networks may require some correction, the procedure does allow network extraction over large areas using objective criteria and reduces fieldwork requirements. The networks extracted may subsequently be used in geomorphological analyses, for example to describe the drainage patterns induced by networks and to examine the rate of change of networks. Estimation of the heights of the low and sparse vegetation on marshes is being investigated by analysis of the statistical distribution of the measured LiDAR heights. Species having different mean heights may be separated using the first-order moments of the height distribution

Pathway-based analysis of a genome-wide case-control association study of rheumatoid arthritis

Evaluation of the association between single-nucleotide polymorphisms (SNPs) and disease outcomes is widely used to identify genetic risk factors for complex diseases. Although this analysis paradigm has made significant progress in many genetic studies, many challenges remain, such as the requirement of a large sample size to achieve adequate power. Here we use rheumatoid arthritis (RA) as an example and explore a new analysis strategy: pathway-based analysis to search for related genes and SNPs contributing to the disease

Outcome related to impact on daily living: preliminary validation of the ORIDL instrument

<p>Abstract</p> <p>Background</p> <p>The challenge of finding practical, patient-rated outcome measures is a key issue in the evaluation of health care systems and interventions. The ORIDL (Outcome in Relation to Impact on Daily Living) instrument (formerly referred to as the Glasgow Homoeopathic Hospital Outcomes Scale or GHHOS) has been developed to measure patient's views of the outcome of their care by asking about change, and relating this to impact on daily life. The aim of the present paper is to describe the background and potential uses of the ORIDL, and to report on its preliminary validation in a series of three studies in secondary and primary care.</p> <p>Methods</p> <p>In the first study, 105 patients attending the Glasgow Homoeopathic Hospital (GHH) were followed-up at 12 months and changes in health status were measured by the EuroQol (EQOL) and the ORIDL. In the second study, 187 new patients at the GHH were followed-up at 3, 12, and 33 months, using the ORIDL, the Short Form 12 (SF-12), and the Measure Yourself Medical Outcome Profile (MYMOP). In study three, 323 patients in primary care were followed for 1 month post-consultation using the ORIDL and MYMOP. In all 3 studies the Patient Enablement Instrument (PEI) was also used as an outcome measure.</p> <p>Results</p> <p>Study 1 showed substantial improvements in main complaint and well-being over 12 months using the ORIDL, with two-thirds of patients reporting improvements in daily living. These improvements were not significantly correlated with changes in serial measures of the EQOL between baseline and 12 months, but were correlated with the EQOL transitions measure. Study 2 showed step-wise improvements in ORIDL scores between 3 and 33 months, which were only weakly associated with similar changes in SF-12 scores. However, MYMOP change scores correlated well with ORIDL scores at all time points. Study 3 showed similar high correlations between ORIDL scores and MYMOP scores. In all 3 studies, ORIDL scores were also significantly correlated with PEI-outcome scores.</p> <p>Conclusion</p> <p>There is significant agreement between patient outcomes assessed by the ORIDL and the EQOL transition scale, the MYMOP, and the PEI-outcome instrument, suggesting that the ORIDL may be a valid and sensitive tool for measuring change in relation to impact on life.</p

IBD genetic risk profile in healthy first-degree relatives of Crohn's disease patients

BACKGROUND: Family history provides important information on risk of developing inflammatory bowel disease [IBD], and genetic profiling of first-degree relatives [FDR] of Crohn's disease [CD]- affected individuals might provide additional information. We aimed to delineate the genetic contribution to the increased IBD susceptibility observed in FDR. METHODS: N = 976 Caucasian, healthy, non-related FDR; n = 4997 independent CD; and n = 5000 healthy controls [HC]; were studied. Genotyping for 158 IBD-associated single nucleotide polymorphisms [SNPs] was performed using the Illumina Immunochip. Risk allele frequency [RAF] differences between FDR and HC cohorts were correlated with those between CD and HC cohorts. CD and IBD genetic risk scores [GRS] were calculated and compared between HC, FDR, and CD cohorts. RESULTS: IBD-associated SNP RAF differences in FDR and HC cohorts were strongly correlated with those in CD and HC cohorts, correlation coefficient 0.63 (95% confidence interval [CI] 0.53 - 0.72), p = 9.90 x 10(-19). There was a significant increase in CD-GRS [mean] comparing HC, FDR, and CD cohorts: 0.0244, 0.0250, and 0.0257 respectively [p < 1.00 x 10(-7) for each comparison]. There was no significant difference in the IBD-GRS between HC and FDR cohorts [p = 0.81]; however, IBD-GRS was significantly higher in CD compared with FDR and HC cohorts [p < 1.00 x 10(-10) for each comparison]. CONCLUSION: FDR of CD-affected individuals are enriched with IBD risk alleles compared with HC. Cumulative CD-specific genetic risk is increased in FDR compared with HC. Prospective studies are required to determine if genotyping would facilitate better risk stratification of FDR

Jovian Plasmas Torus Interaction with Europa. Plasma Wake Structure and Effect of Inductive Magnetic Field: 3D Hybrid Kinetic Simulation

The hybrid kinetic model supports comprehensive simulation of the interaction between different spatial and energetic elements of the Europa moon-magnetosphere system with respect to a variable upstream magnetic field and flux or density distributions of plasma and energetic ions, electrons, and neutral atoms. This capability is critical for improving the interpretation of the existing Europa flyby measurements from the Galileo Orbiter mission, and for planning flyby and orbital measurements (including the surface and atmospheric compositions) for future missions. The simulations are based on recent models of the atmosphere of Europa (Cassidy et al., 2007; Shematovich et al., 2005). In contrast to previous approaches with MHD simulations, the hybrid model allows us to fully take into account the finite gyroradius effect and electron pressure, and to correctly estimate the ion velocity distribution and the fluxes along the magnetic field (assuming an initial Maxwellian velocity distribution for upstream background ions). Photoionization, electron-impact ionization, charge exchange and collisions between the ions and neutrals are also included in our model. We consider the models with O and S background plasma, and various betas for background ions and electrons, and pickup electrons. The majority of O2 atmosphere is thermal with an extended non-thermal population (Cassidy et al., 2007). In this paper, we discuss two tasks: (1) the plasma wake structure dependence on the parameters of the upstream plasma and Europa's atmosphere (model I, cases (a) and (b) with a homogeneous Jovian magnetosphere field, an inductive magnetic dipole and high oceanic shell conductivity); and (2) estimation of the possible effect of an induced magnetic field arising from oceanic shell conductivity. This effect was estimated based on the difference between the observed and modeled magnetic fields (model II, case (c) with an inhomogeneous Jovian magnetosphere field, an inductive magnetic dipole and low oceanic shell conductivity)

Total synthesis and biological evaluation of simplified aplyronine analogues as synthetically tractable anticancer agents.

The aplyronines are a family of highly cytotoxic marine natural products with potential application in targeted cancer chemotherapy. To address the severe supply issue, function-oriented molecular editing of their macrolactone scaffold led to the design of a series of simplified aplyronine analogues. Enabled by a highly convergent aldol-based route, the total synthesis of four analogues was achieved, with a significant improvement in step economy versus previous compounds, and their cancer cell growth inhibition in the HeLa cell line was determined. The modular strategy presented offers a means for significantly shortening their chemical synthesis to facilitate the continued development of this promising class of anticancer agent

Predictive phage therapy for Escherichia coli urinary tract infections: cocktail selection for therapy based on machine learning models

This study supports the development of predictive bacteriophage (phage) therapy: the concept of phage cocktail selection to treat a bacterial infection based on machine learning models (MLM). For this purpose, MLM were trained on thousands of measured interactions between a panel of phage and sequenced bacterial isolates. The concept was applied to Escherichia coli (E. coli) associated with urinary tract infections. This is an important common infection in humans and companion animals from which multi-drug resistant (MDR) bloodstream infections can originate. The global threat of MDR infection has reinvigorated international efforts into alternatives to antibiotics including phage therapy. E. coli exhibit extensive genome-level variation due to horizontal gene transfer via phage and plasmids. Associated with this, phage selection for E. coli is difficult as individual isolates can exhibit considerable variation in phage susceptibility due to differences in factors important to phage infection including phage receptor profiles and resistance mechanisms. The activity of 31 phage were measured on 314 isolates with growth curves in artificial urine. Random Forest models were built for each phage from bacterial genome features and the more generalist phage, acting on over 20% of the bacterial population, exhibited F1 scores of &gt;0.6 and could be used to predict phage cocktails effective against previously untested strains. The study demonstrates the potential of predictive models which integrate bacterial genomics with phage activity datasets allowing their use on data derived from direct sequencing of clinical samples to inform rapid and effective phage therapy.Significance Statement With the growing challenge of antimicrobial resistance there is an urgency for alternative treatments for common bacterial diseases including urinary tract infections (UTIs). Escherichia coli is the main causative agent of UTIs in both humans and companion animals with multidrug resistant strains such as the globally disseminated ST131 becoming more common. Bacteriophage (phage) are natural predators of bacteria and potentially an alternative therapy. However, a major barrier for phage therapy is the specificity of phage on target bacteria and therefore difficulty efficiently selecting the appropriate phage. Here, we demonstrate a genomics driven approach using machine learning prediction models combined with phage activity clustering to select phage cocktails based only on the genome sequence of the infecting bacterial strain

Antibiotic dosing in the 'at risk' critically ill patient: Linking pathophysiology with pharmacokinetics/pharmacodynamics in sepsis and trauma patients

Background: Critical illness, mediated by trauma or sepsis, can lead to physiological changes that alter the pharmacokinetics of antibiotics and may result in sub-therapeutic concentrations at the sites of infection. The first aim of this project is to identify the clinical characteristics of critically ill patients with significant trauma that have been recently admitted to ICU that may predict the dosing requirements for the antibiotic, cefazolin. The second aim of this is to identify the clinical characteristics of critically ill patients with sepsis that may predict the dosing requirements for the combination antibiotic, piperacillin-tazobactam