Computable Functions Research Articles

Symptoms and probabilistic anatomical mapping of lacunar infarcts

BackgroundThe anatomical distribution of acute lacunar infarcts has mainly been studied for supratentorial lesions. In addition, little is known about the association with distinct stroke symptoms, not summarized as classical lacunar syndromes. We aimed to describe the spatial lesion distribution of acute supra- and infratentorial lacunar infarcts and their association with stroke symptoms in patients eligible for thrombolysis.MethodsAll patients enrolled in the WAKE-UP trial (efficacy and safety of magnetic resonance imaging [MRI]-based thrombolysis in wake-up stroke) were screened for lacunar infarcts on diffusion-weighted imaging (DWI). The relationship between the anatomical distribution of supra- and infratentorial lacunar infarcts, their demographic characteristics and acute stroke symptoms, defined by the National Institutes of Health Stroke Scale (NIHSS) score, were correlated and compared.ResultsMaps of lesion distribution from 224 lacunar infarct patients (76 [33.9%] females, mean age [standard deviation] of 63.4 [11.5] years) were generated using computational image mapping methods. Median infarct volume was 0.73 ml (interquartile range [IQR] 0.37–1.15 ml). Median NIHSS sum score on hospital arrival was 4 (IQR 3–6). 165 (73.7%) patients had lacunar infarcts in the supratentorial deep white or grey matter, while 59 (26.3%) patients had infratentorial lacunar infarcts. Patients with supratentorial lacunar infarcts presented with a significantly lower occurrence of deficits in the NIHSS items gaze (p < 0.001) and dysarthria (p = 0.008), but had more often a paresis of the left arm (p = 0.009) and left leg (p = 0.068) compared to patients with infratentorial infarcts.ConclusionsThe anatomical lesion distribution of lacunar infarcts reveals a distinct pattern and supports an association of localization with different stroke symptoms.Trial registrationNCT01525290.

Management of failed UKA to TKA: conventional versus robotic-assisted conversion technique

BackgroundFailure of unicompartmental knee arthroplasty (UKA) is a distressing and technically challenging complication. Conventional conversion techniques (CCT) with rods and jigs have produced varying results. A robotic-assisted conversion technique (RCT) is an unexplored, though possibly advantageous, alternative. We compare our reconstructive outcomes between conventional and robotic methods in the management of failed UKA.MethodsThirty-four patients with a failed UKA were retrospectively reviewed. Patients underwent conversion total knee arthroplasty (TKA) with either a CCT or RCT. Seventeen patients were included in each group. All procedures were done by a single surgeon at a single institution, with a mean time to follow-up of 3.6 years (range, 1 to 12). The primary outcome measures were the need for augments and polyethylene thickness. Secondary outcome measures were complications, need for revision, estimated blood loss (EBL), length of stay, and operative time.ResultsThe mean polyethylene thickness was 12 mm (range, 9 to 15) in the CCT group and 10 mm (range, 9 to 14) in the RCT groups, with no statistical difference between the two groups (P = 0.07). A statistically significant difference, however, was present in the use of augments. In the CCT group, five out of 17 knees required augments, whereas none of the 17 knees in the RCT group required augments (P = 0.04). Procedurally, robotic-assisted surgery progressed uneventfully, even with metal artifact noted on the preoperative computerized tomography (CT) scans. Computer mapping of the residual bone surface after implant removal was a helpful guide in minimizing resection depth. No further revisions or reoperations were performed in either group.ConclusionsRobotic-assisted conversion TKA is technically feasible and potentially advantageous. In the absence of normal anatomic landmarks to guide conventional methods, the preoperative CT scans were unexpectedly helpful in establishing mechanical alignment and resection depth. In this limited series, RCT does not seem to be inferior to CCT. Further investigation of outcomes is warranted.

Virus-CKB: an integrated bioinformatics platform and analysis resource for COVID-19 research.

Given the scale and rapid spread of the coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), there is an urgent need for medicines that can help before vaccines are available. In this study, we present a viral-associated disease-specific chemogenomics knowledgebase (Virus-CKB) and apply our computational systems pharmacology-target mapping to rapidly predict the FDA-approved drugs which can quickly progress into clinical trials to meet the urgent demand of the COVID-19 outbreak. Virus-CKB reuses the underlying platform of our DAKB-GPCRs but adds new features like multiple-compound support, multi-cavity protein support and customizable symbol display. Our one-stop computing platform describes the chemical molecules, genes and proteins involved in viral-associated diseases regulation. To date, Virus-CKB archived 65 antiviral drugs in the market, 107 viral-related targets with 189 available 3D crystal or cryo-EM structures and 2698 chemical agents reported for these target proteins. Moreover, Virus-CKB is implemented with web applications for the prediction of the relevant protein targets and analysis and visualization of the outputs, including HTDocking, TargetHunter, BBB predictor, NGL Viewer, Spider Plot, etc. The Virus-CKB server is accessible at https://www.cbligand.org/g/virus-ckb.

Long-term clinical outcomes and prognostic indicators for focal impulse and rotor modulation guided ablation: A single-center observational study

BackgroundElectrophysiologists have developed a computational mapping approach to localize sources that may perpetuate persistent atrial fibrillation (AF). Focal impulse and rotor modulation (FIRM)-guided ablation of these sources have produced variable results. The current study further assesses single-procedure success rates of FIRM-guided ablation for preventing AF or atrial tachyarrhythmia recurrence and analyzes different baseline characteristics as prognostic indicators for individuals experiencing these undesired outcomes. MethodsSeventy-one consecutive patients (mean age 64.58 ± 9.05 years and 36.6% female) with drug-refractory persistent AF with and without prior history of pulmonary vein antral isolation (PVAI) underwent FIRM-guided ablation. Patients without prior history of PVAI underwent FIRM-guided ablation in addition to de novo PVAI. Patients with prior history of PVAI had the pulmonary veins reassessed at the time of FIRM-guided ablation for reconnection as well as re-isolation, when necessary. These patients were then prospectively followed for AF and atrial tachyarrhythmia recurrence. ResultsFIRM analysis revealed rotors in the right atrium in 66.2% (1.77 ± 1.53 mean rotors per patient) and in the left atrium in 85.9% (2.65 ± 1.52 mean rotors per patient) of patients analyzed in the current study. After a single FIRM-guided ablation procedure, AF and atrial tachyarrhythmia recurrence was demonstrated in 21.1% (15/71) and 33.8% (24/71) of patients, respectively. The entire cohort of patients were followed for a mean duration of 23.20 ± 8.38 months with the mean time to AF recurrence found to be 12.35 ± 10.44 months. Furthermore, valvular heart disease (i.e. moderate mitral or tricuspid regurgitation) was found to be a statistically significant independent predictor for AF recurrence following FIRM-guided ablation (p = .033). ConclusionsFIRM-guided ablation in combination with PVAI is a suitable and effective approach for symptomatic individuals with drug-refractory persistent AF with and without prior history of PVAI. Randomized controlled studies are warranted.

Computationally Guided Intracerebral Drug Delivery via Chronically Implanted Microdevices

Treatments for neurologic diseases are often limited in efficacy due to poor spatial and temporal control over their delivery. Intracerebral delivery partially overcomes this by directly infusing therapeutics to the brain. Brain structures, however, are nonuniform and irregularly shaped, precluding complete target coverage by a single bolus without significant off-target effects and possible toxicity. Nearly complete coverage is crucial for effective modulation of these structures. We present a framework with computational mapping algorithms for neural drug delivery (COMMAND) to guide multi-bolus targeting of brain structures that maximizes coverage and minimizes off-target leakage. Custom-fabricated chronic neural implants leverage rational fluidic design to achieve multi-bolus delivery in rodents through a single infusion of radioactive tracer (Cu-64). The resulting spatial distributions replicate computed spatial coverage with 5% error invivo, as detected by positron emission tomography. COMMAND potentially enables accurate, efficacious targeting of discrete brain regions.

Identification of Residues Controlling dUTPase Enzyme Activity from Epstein‐Barr Virus

Epstein Barr‐Virus (EBV) is primarily known for causing infectious mononucleosis, but also increases the incidence of lymphomas and autoimmune disorders. There is currently no vaccine or treatment once infected by EBV. The EBV genome encodes a dUTPase enzyme. This enzyme catalyzes the reaction of dUTP to dUMP which is a precursor of the thymidine nucleotide. The enzyme activity regulates the dUTP/dTTP ratio and decreases misincorporation of uracil into newly synthesized DNA. A dUTPase knockout is lethal in mice, E. coli., and S. cerevisiae. The Murine gammaherpesvirus lacking its viral dUTPase has reduced viral replication. It is hypothesized that inhibition of EBV dUTPase would result in uracil misincorporation, double stranded DNA breaks, and a reduction in replication of the viral genome. Characterization of residues required for enzyme activity in EBV dUTPase was performed using sequence alignments and structural data. Mutagenesis and comparative enzyme kinetics on these residues identified aspartate 76 as being critical for enzyme activity. Analysis of structural data identified a histidine residue hypothesized to regulate substrate specificity. A small molecule binding site was identified using computational mapping of two EBV dUTPase 3D structures. We hypothesis that this allosteric binding site contains a serine that post transcriptionally regulates dUTPase activity. This research will guide the development of inhibitors that bind to critical dUTPase residues offering a potential treatment for EBV.Support or Funding InformationThis work was supported by, UWL College of Science and Health, UWL Research and Creativity, and Toce Deans Distinguished Fellowship

A Comparative Study to Determine Substrate-Binding Pattern in Eicosanoid-Generating Enzymes by Computational Mapping

A Comparative Study to Determine Substrate-Binding Pattern in Eicosanoid-Generating Enzymes by Computational Mapping

Multiresonant Split Ring Resonator with Meandered Strips

A multiresonant split ring resonator (SRR) composed of two circular‐shaped meandered strips is presented. Resonances are first analyzed by means of eigenmodes computation and field mapping. It is shown that a resonance can emerge from a standing wave taking place in each slot produced by a meandered strip. A slot operates as a two‐wire transmission line section short‐circuited at one termination and loaded by an open‐circuit at the other end. Consecutively, a resonance occurs approximately when a quarter‐wavelength matches the length of the slot. A resonance frequency shift is observed, and it is related to a transverse magnetic coupling between a first antisymmetric mode and a second symmetric mode. Finally, multiple resonances in an SRR are experimentally evidenced by spectroscopy of the input impedance of an SRR resonator antenna. Experimental results are favorably compared with simulation.

An introduction to feedback Turing computability

Abstract Feedback computability is computation with an oracle that contains the correct convergence/divergence information for all computations calling that same oracle. Here we study feedback Turing computability, as well as feedback for some smaller classes of computation. We also examine some versions of parallelization of these notions.

Computability of topological entropy: From general systems to transformations on Cantor sets and the interval

The dynamics of symbolic systems, such as multidimensional subshifts of finite type or cellular automata, are known to be closely related to computability theory. In particular, the appropriate tools to describe and classify topological entropy for this kind of systems turned out to be algorithmic. Part of the great importance of these symbolic systems relies on the role they have played in understanding more general systems over non-symbolic spaces. The aim of this article is to investigate topological entropy from a computability point of view in this more general, not necessarily symbolic setting. In analogy to effective subshifts, we consider computable maps over effective compact sets in general metric spaces, and study the computability properties of their topological entropies. We show that even in this general setting, the entropy is always a \begin{document}$ \Sigma_2 $\end{document} -computable number. We then study how various dynamical and analytical constrains affect this upper bound, and prove that it can be lowered in different ways depending on the constraint considered. In particular, we obtain that all \begin{document}$ \Sigma_2 $\end{document} -computable numbers can already be realized within the class of surjective computable maps over \begin{document}$ \{0,1\}^{{\mathbb N}} $\end{document} , but that this bound decreases to \begin{document}$ \Pi_{1} $\end{document} (or upper)-computable numbers when restricted to expansive maps. On the other hand, if we change the geometry of the ambient space from the symbolic \begin{document}$ \{0,1\}^{{\mathbb N}} $\end{document} to the unit interval \begin{document}$ [0,1] $\end{document} , then we find a quite different situation – we show that the possible entropies of computable systems over \begin{document}$ [0,1] $\end{document} are exactly the \begin{document}$ \Sigma_{1} $\end{document} (or lower)-computable numbers and that this characterization switches down to precisely the computable numbers when we restrict the class of system to the quadratic family.

Biosonar spatial resolution along the distance axis: revisiting the clutter interference zone.

Many echolocating bats forage close to vegetation - a chaotic arrangement of prey and foliage where multiple targets are positioned behind one another. Bats excel at determining distance: they measure the delay between the outgoing call and the returning echo. In their auditory cortex, delay-sensitive neurons form a topographic map, suggesting that bats can resolve echoes of multiple targets along the distance axis - a skill crucial for the forage-amongst-foliage scenario. We tested this hypothesis combining an auditory virtual reality with formal psychophysics: we simulated a prey item embedded in two foliage elements, one in front of and one behind the prey. The simulated spacing between 'prey' (target) and 'foliage' (maskers) was defined by the inter-masker delay (IMD). We trained Phyllostomus discolor bats to detect the target in the presence of the maskers, systematically varying both loudness and spacing of the maskers. We show that target detection is impaired when maskers are closely spaced (IMD<1 ms), but remarkably improves when the spacing is increased: the release from masking is approximately 5 dB for intermediate IMDs (1-3 ms) and increases to over 15 dB for large IMDs (≥9 ms). These results are comparable to those from earlier work on the clutter interference zone of bats (Simmons et al., 1988). They suggest that prey would enjoy considerable acoustic protection from closely spaced foliage, but also that the range resolution of bats would let them 'peek into gaps'. Our study puts target ranging into a meaningful context and highlights the limitations of computational topographic maps.

Use of geoinformation systems in environmental monitoring

The purpose of the study, the materials of which are outlined in this article, is to uncover current trends in the development of environmental monitoring and the tracking of anthropogenic environmental impacts. To achieve this goal, it is proposed to use geoinformation systems to perform environmental monitoring and control, using appropriate software. For this purpose ArcGis software was used which allows monitoring the state of the atmosphere, its pollution and other deviations from the norm. The research was conducted exemplified by nine districts of Kharkiv. As a result of computer geospatial analysis, models and maps of urban pollution have been developed. In general, the intellectual analysis of geostatic models of emission distribution in the city allowed identifying and classifying zones of high concentrations of pollution and comparing them with air quality data. Methods of geostatistics transformed the data from a discrete to a continuous form of representation. Further studies in this area may be related to the improvement of geostatistical data analysis and pollution distribution prediction methods. As an example, mathematical formulas were presented to determine the atmospheric pollution index and the true or predicted pollution index, which can be determined on the basis of the data obtained and represented by elements of the ArcGis software package in a discrete and continuous form.

The N-Dimension Computing Machine Postulate

This paper postulates a novel N-dimension computing machine that operates in an unconventional manner. This postulate aims at solving existing problems in higher dimensions, where one must re-think the scope of a given problem domain beyond the one-dimension Turing machine to dictate all subsequent problem representation, problem transformation, and algorithmic derivation. Two over-simplified well-known problems, namely, the Traveling Salesman Problem and the Tower of Hanoi problem are presented to demonstrate the point. Both synthetic problems are effectively adapted to solve a real world project. To realize the postulate in a viable architectural construct, data flow and molecular computers are investigated since they show potential computation power. Unfortunately, they are still confined to working in one-dimension domain. A biological-like architecture for software systems is proposed in three design aspects: structure, function, and behavior. Contributions of this work are to revamp traditional Turing computation paradigm to N-dimension computing machine, yet it is simple, straightforward, and implementable by state-of-the-practice hardware and software technologies. Thus, the burden of solving difficult problems can be lessened.

Form Follows Brain Function: A Computational Mapping Approach

The strong association between computation and the built environment gives birth to new research approaches to urban design. Although these approaches enable the implementation of urban systems based on various collections of datasets, they usually neglect human experience. To address this problem, our research identifies and quantifies spatial information and patterns of urban organization based on experience, by gathering two parallel types of user data: sensory and recollection. The presented experiment, executed in Copenhagen, Denmark with 23 participants, involves a walking task, and a recollection task. The walking task is 1 km walk from the Copenhagen Court House building to the Royal Danish Theatre through Strøget Street, while wearing eye-tracking spectacles. The recollection task includes the underlining – on a 3D photorealistic digital model – of the elements that the participants can recall from their walk. We monitor the eye movement of the participants to locally characterize the urban path by computing four spatial attributes: a) The fixations on elements (counted through iMotions Software), b) The distance from the viewer (taken by GPS points through FUMapp software), c) The position of the stimuli related to the eye-level (calculated in FUMapp), and d) The degree of spatial transformations on street intersections (through spatial variables in FUMapp). Then we compare the eye-tracking and the recollection data and we evaluate their heat maps. The originality of this research is twofold: First, for the first time a substantial amount of quantifiable optical data related to urban walking is recorded; Second, for the first time this experiment is performed on the public street. The proposed method could offer a quantifiable basis for predicting eye fixation locations, determining human centric guidelines for urban design. Additional modes of body sensors could yield even more all-encompassing body-metrics related to the urban walking experience.

Interaction Energetics and Druggability of the Protein-Protein Interaction between Kelch-like ECH-Associated Protein 1 (KEAP1) and Nuclear Factor Erythroid 2 Like 2 (Nrf2).

Development of small molecule inhibitors of protein-protein interactions (PPIs) is hampered by our poor understanding of the druggability of PPI target sites. Here, we describe the combined application of alanine-scanning mutagenesis, fragment screening, and FTMap computational hot spot mapping to evaluate the energetics and druggability of the highly charged PPI interface between Kelch-like ECH-associated protein 1 (KEAP1) and nuclear factor erythroid 2 like 2 (Nrf2), an important drug target. FTMap identifies four binding energy hot spots at the active site. Only two of these are exploited by Nrf2, which alanine scanning of both proteins shows to bind primarily through E79 and E82 interacting with KEAP1 residues S363, R380, R415, R483, and S508. We identify fragment hits and obtain X-ray complex structures for three fragments via crystal soaking using a new crystal form of KEAP1. Combining these results provides a comprehensive and quantitative picture of the origins of binding energy at the interface. Our findings additionally reveal non-native interactions that might be exploited in the design of uncharged synthetic ligands to occupy the same site on KEAP1 that has evolved to bind the highly charged DEETGE binding loop of Nrf2. These include π-stacking with KEAP1 Y525 and interactions at an FTMap-identified hot spot deep in the binding site. Finally, we discuss how the complementary information provided by alanine-scanning mutagenesis, fragment screening, and computational hot spot mapping can be integrated to more comprehensively evaluate PPI druggability.

Downsampling of Bounded Bandlimited Signals and the Bandlimited Interpolation: Analytic Properties and Computability

Downsampling and the computation of the bandlimited interpolation of discrete-time signals are two important concepts in signal processing. In this paper we analyze the downsampling operation regarding its impact on the existence and computability of the bounded bandlimited interpolation. We assume that the discrete-time signal is obtained by downsampling the samples of a bounded bandlimited signal that vanishes at infinity, and we study two problems. First, we investigate the existence of the bounded bandlimited interpolation for such discrete-time signals from a signal theoretic perspective and show that there exist signals for which the bounded bandlimited interpolation does not exist. Second, we analyze the algorithmic generation of the bounded bandlimited interpolation, using the concept of Turing computability. Turing computability models what is theoretically implementable on a digital computer. Interestingly, it turns out that even if the bounded bandlimited interpolation exists analytically, it is not always computable, which implies that there exists no algorithm on a digital computer that can always compute it. Computability is important in order that the approximation error be controlled. If a signal is not computable, we cannot ascertain whether the computed signal is sufficiently close to the true signal, i.e., we cannot verify every approximation accuracy.

Computational pan-genome mapping and pairwise SNP-distance improve detection of Mycobacterium tuberculosis transmission clusters.

Next-generation sequencing based base-by-base distance measures have become an integral complement to epidemiological investigation of infectious disease outbreaks. This study introduces PANPASCO, a computational pan-genome mapping based, pairwise distance method that is highly sensitive to differences between cases, even when located in regions of lineage specific reference genomes. We show that our approach is superior to previously published methods in several datasets and across different Mycobacterium tuberculosis lineages, as its characteristics allow the comparison of a high number of diverse samples in one analysis—a scenario that becomes more and more likely with the increased usage of whole-genome sequencing in transmission surveillance.

P38α Mitogen-Activated Protein Kinase Is a Druggable Target in Pancreatic Adenocarcinoma.

p38 mitogen-activated protein kinases are signaling molecules with major involvement in cancer. A detailed mechanistic understanding of how p38 MAPK family members function is urgently warranted for cancer targeted therapy. The conformational dynamics of the most common member of p38 MAPK family, p38α, are crucial for its function but poorly understood. Here we found that, unlike in other cancer types, p38α is significantly activated in pancreatic adenocarcinoma samples, suggesting its potential for anti-pancreatic cancer therapy. Using a state of the art supercomputer, Anton, long-timescale (39 μs) unbiased molecular dynamics simulations of p38α show that apo p38α has high structural flexibility in six regions, and reveal potential catalysis mechanism involving a “butterfly” motion. Moreover, in vitro studies show the low-selectivity of the current p38α inhibitors in both human and mouse pancreatic cancer cell lines, while computational solvent mapping identified 17 novel pockets for drug design. Taken together, our study reveals the conformational dynamics and potentially druggable pockets of p38α, which may potentiate p38α-targeting drug development and benefit pancreatic cancer patients.

The back-and-forth method and computability without delay

We study the algorithmic content of back-and-forth proofs for graphs and homogeneous structures from the perspective of Turing computations in which unbounded search is forbidden. Quite unexpectedly, we discover subtle differences between the back-and-forth proofs for the random graph, the dense linear order of the rationals, and the universal countable abelian p-group. We also prove the primitive recursive analog of the Cantor–Bernstein theorem for graphs which says that if there is a “back” isomorphism and the “forth” isomorphism, then there is a “back-and-forth” isomorphism. We also show that the fully primitive recursive degrees (to be defined) of the dense linear order of the rationals are downwards dense.

Fixed point quasiconvex subgradient method

Constrained quasiconvex optimization problems appear in many fields, such as economics, engineering, and management science. In particular, fractional programming, which models ratio indicators such as the profit/cost ratio as fractional objective functions, is an important instance. Subgradient methods and their variants are useful ways for solving these problems efficiently. Many complicated constraint sets onto which it is hard to compute the metric projections in a realistic amount of time appear in these applications. This implies that the existing methods cannot be applied to quasiconvex optimization over a complicated set. Meanwhile, thanks to fixed point theory, we can construct a computable nonexpansive mapping whose fixed point set coincides with a complicated constraint set. This paper proposes an algorithm that uses a computable nonexpansive mapping for solving a constrained quasiconvex optimization problem. We provide convergence analyses for constant diminishing step-size rules. Numerical comparisons between the proposed algorithm and an existing algorithm show that the proposed algorithm runs stably and quickly even when the running time of the existing algorithm exceeds the time limit.