Active learning-based multistage sequential decision-making model with application on common bile duct stone evaluation.

Multistage sequential decision-making occurs in many real-world applications such as healthcare diagnosis and treatment. One concrete example is when the doctors need to decide to collect which kind of information from subjects so as to make the good medical decision cost-effectively. In this paper, an active learning-based method is developed to model the doctors' decision-making process that actively collects necessary information from each subject in a sequential manner. The effectiveness of the proposed model, especially its two-stage version, is validated on both simulation studies and a case study of common bile duct stone evaluation for pediatric patients.

Ensemble dependence of the critical behavior of a system with long-range interaction and quenched randomness.

We propose a hybrid model governed by the Blume-Emery-Griffiths (BEG) Hamiltonian with a mean-field-like interaction, where the spins are randomly quenched such that some of them are "pure" Ising and the others admit the BEG set of states. It is found, by varying the concentration of the Ising spins, that the model displays different phase portraits in concentration-temperature parameter space, within the canonical and the microcanonical ensembles. Phenomenological indications that these portraits are rich and rather unusual are provided.

Distribution equality as an optimal epidemic mitigation strategy.

Upon the development of a therapeutic, a successful response to a global pandemic relies on efficient worldwide distribution, a process constrained by our global shipping network. Most existing strategies seek to maximize the outflow of the therapeutics, hence optimizing for rapid dissemination. Here we find that this intuitive approach is, in fact, counterproductive. The reason is that by focusing strictly on the quantity of disseminated therapeutics, these strategies disregard the way in which this quantity distributes across destinations. Most crucially-they overlook the interplay of the therapeutic spreading patterns with those of the pathogens. This results in a discrepancy between supply and demand, that prohibits efficient mitigation even under optimal conditions of superfluous flow. To solve this, we design a dissemination strategy that naturally follows the predicted spreading patterns of the pathogens, optimizing not just for supply volume, but also for its congruency with the anticipated demand. Specifically, we show that epidemics spread relatively uniformly across all destinations, prompting us to introduce an equality constraint into our dissemination that prioritizes supply homogeneity. This strategy may, at times, slow down the supply rate in certain locations, however, thanks to its egalitarian nature, which mimics the flow of the pathogens, it provides a dramatic leap in overall mitigation efficiency, potentially saving more lives with orders of magnitude less resources.

Topological synchronization of chaotic systems.

A chaotic dynamics is typically characterized by the emergence of strange attractors with their fractal or multifractal structure. On the other hand, chaotic synchronization is a unique emergent self-organization phenomenon in nature. Classically, synchronization was characterized in terms of macroscopic parameters, such as the spectrum of Lyapunov exponents. Recently, however, we attempted a microscopic description of synchronization, called topological synchronization, and showed that chaotic synchronization is, in fact, a continuous process that starts in low-density areas of the attractor. Here we analyze the relation between the two emergent phenomena by shifting the descriptive level of topological synchronization to account for the multifractal nature of the visited attractors. Namely, we measure the generalized dimension of the system and monitor how it changes while increasing the coupling strength. We show that during the gradual process of topological adjustment in phase space, the multifractal structures of each strange attractor of the two coupled oscillators continuously converge, taking a similar form, until complete topological synchronization ensues. According to our results, chaotic synchronization has a specific trait in various systems, from continuous systems and discrete maps to high dimensional systems: synchronization initiates from the sparse areas of the attractor, and it creates what we termed as the 'zipper effect', a distinctive pattern in the multifractal structure of the system that reveals the microscopic buildup of the synchronization process. Topological synchronization offers, therefore, a more detailed microscopic description of chaotic synchronization and reveals new information about the process even in cases of high mismatch parameters.

Pancreatitis in Children.

Pediatric pancreatitis describes a spectrum covering acute pancreatitis, acute recurrent pancreatitis, and chronic pancreatitis, each with varying clinical manifestations and risk factors requiring a tailored diagnostic approach. We emphasize management strategies based on age, risk factors, recurrence, and complications. A discussion of the role of therapeutic endoscopy is reviewed and highlights the growing role of endoscopic ultrasound and endoscopic retrograde cholangiopancreatography in children with pancreatitis. Particular diagnostic challenges in autoimmune pancreatitis are reviewed with an emphasis on differentiating this entity from alternate pancreaticobiliary pathologies. Finally, we explore a multidisciplinary approach to acute recurrent and chronic pancreatitis.

Creation of a Pediatric Choledocholithiasis Prediction Model.

BACKGROUND: Definitive non-invasive detection of pediatric choledocholithiasis could allow more efficient identification of those patients who are most likely to benefit from therapeutic endoscopic retrograde cholangiopancreatography (ERCP) for stone extraction. OBJECTIVE: To craft a pediatric choledocholithiasis prediction model using a combination of commonly available serum laboratory values and ultrasound results. METHODS: A retrospective review of laboratory and imaging results from 316 pediatric patients who underwent intraoperative cholangiogram or ERCP due to suspicion of choledocholithiasis were collected and compared to presence of common bile duct stones on cholangiography. Multivariate logistic regression with supervised machine learning was used to create a predictive scoring model. Monte-Carlo cross-validation was used to validate the scoring model and a score threshold that would provide at least 90% specificity for choledocholithiasis was determined in an effort to minimize non-therapeutic ERCP. RESULTS: Alanine aminotransferase (ALT), total bilirubin, alkaline phosphatase, and common bile duct diameter via ultrasound were found to be the key clinical variables to determine the likelihood of choledocholithiasis. The dictated specificity threshold of 90.3% yielded a sensitivity of 40.8% and overall accuracy of 71.5% in detecting choledocholithiasis. Positive predictive value was 71.4% and negative predictive value was 72.1%. CONCLUSION: Our novel pediatric choledocholithiasis predictive model is a highly specific tool to suggest ERCP in the setting of likely choledocholithiasis.

Alternating quarantine for sustainable epidemic mitigation.

Absent pharmaceutical interventions, social distancing, lock-downs and mobility restrictions remain our prime response in the face of epidemic outbreaks. To ease their potentially devastating socioeconomic consequences, we propose here an alternating quarantine strategy: at every instance, half of the population remains under lockdown while the other half continues to be active - maintaining a routine of weekly succession between activity and quarantine. This regime minimizes infectious interactions, as it allows only half of the population to interact for just half of the time. As a result it provides a dramatic reduction in transmission, comparable to that achieved by a population-wide lockdown, despite sustaining socioeconomic continuity at  ~50% capacity. The weekly alternations also help address the specific challenge of COVID-19, as their periodicity synchronizes with the natural SARS-CoV-2 disease time-scales, allowing to effectively isolate the majority of infected individuals precisely at the time of their peak infection.

Distance distribution in extreme modular networks.

Modularity is a key organizing principle in real-world large-scale complex networks. Many real-world networks exhibit modular structures such as transportation infrastructures, communication networks, and social media. Having the knowledge of the shortest paths length distribution between random pairs of nodes in such networks is important for understanding many processes, including diffusion or flow. Here, we provide analytical methods which are in good agreement with simulations on large scale networks with an extreme modular structure. By extreme modular, we mean that two modules or communities may be connected by maximum one link. As a result of the modular structure of the network, we obtain a distribution showing many peaks that represent the number of modules a typical shortest path is passing through. We present theory and results for the case where interlinks are weighted, as well as cases in which the interlinks are spread randomly across nodes in the community or limited to a specific set of nodes.

Retrospective Multicenter Matched Controlled Comparison of Endoscopic Retrograde Cholangiopancreatography in Pediatric Patients: A 10-year Experience.

INTRODUCTION: This study was designed to evaluate outcomes in pediatric patients undergoing endoscopic retrograde cholangiopancreatography (ERCP) as compared with an American Society of Gastrointestinal Endoscopy (ASGE) complexity grade-matched adult cohort. METHOD: In this retrospective case-control study, ERCPs performed in pediatric patients from January 2008 to December 2018 in 2 tertiary referral hospitals were compared with a complexity-matched adult control group with similar procedural indications. Primary outcomes included the clinical success rate, technical success rate, and complication rate. Secondary outcomes included postprocedural admission rates, mode of sedation, procedure time, fluoroscopy time, hospitalization length, and the number of repeat procedures. RESULTS: Two hundred thirty-two ERCPs performed in 110 pediatric patients (average age 13.3) and 318 ERCPs performed in 160 ASGE grade-matched adult controls (average age 47.2 years) were analyzed. All procedures were therapeutic. There was no difference in the technical success rate (P = 0.2), clinical success rate (P = 0.5), complication rates (P = 0.1), and fluoroscopy time (P = 0.4), between the pediatric and adult cohorts. General anesthesia use and length of stay were significantly higher in the pediatric group (P = 0.0001). In subgroup analysis, technical (P = 0.2) and clinical success (P = 0.2) as well as complication rates (P = 0.6) were comparable between patients 10 years or less and patients 11 to 18 years within pediatric cohort. CONCLUSIONS: ERCP in pediatric cohorts appears to be safe and effective with equivalent outcomes relative to an ASGE complexity-matched adult cohort. Pediatric patients are more likely to require general anesthesia and have a longer average length of stay relative to adult controls.

Unusual changeover in the transition nature of local-interaction Potts models.

A combinatorial approach is used to study the critical behavior of a q-state Potts model with a round-the-face interaction. Using this approach, it is shown that the model exhibits a first order transition for q>3. A second order transition is numerically detected for q=2. Based on these findings, it is deduced that for some two-dimensional ferromagnetic Potts models with completely local interaction, there is a changeover in the transition order at a critical integer q_{c}≤3. This stands in contrast to the standard two-spin interaction Potts model where the maximal integer value for which the transition is continuous is q_{c}=4. A lower bound on the first order critical temperature is additionally derived.

Digitizable therapeutics for decentralized mitigation of global pandemics.

When confronted with a globally spreading epidemic, we seek efficient strategies for drug dissemination, creating a competition between supply and demand at a global scale. Propagating along similar networks, e.g., air-transportation, the spreading dynamics of the supply vs. the demand are, however, fundamentally different, with the pathogens driven by contagion dynamics, and the drugs by commodity flow. We show that these different dynamics lead to intrinsically distinct spreading patterns: while viruses spread homogeneously across all destinations, creating a concurrent global demand, commodity flow unavoidably leads to a highly uneven spread, in which selected nodes are rapidly supplied, while the majority remains deprived. Consequently, even under ideal conditions of extreme production and shipping capacities, due to the inherent heterogeneity of network-based commodity flow, efficient mitigation becomes practically unattainable, as homogeneous demand is met by highly heterogeneous supply. Therefore, we propose here a decentralized mitigation strategy, based on local production and dissemination of therapeutics, that, in effect, bypasses the existing distribution networks. Such decentralization is enabled thanks to the recent development of digitizable therapeutics, based on, e.g., short DNA sequences or printable chemical compounds, that can be distributed as digital sequence files and synthesized on location via DNA/3D printing technology. We test our decentralized mitigation under extremely challenging conditions, such as suppressed local production rates or low therapeutic efficacy, and find that thanks to its homogeneous nature, it consistently outperforms the centralized alternative, saving many more lives with significantly less resources.

Management of Anti-drug Antibodies to Biologic Medications in Children With Inflammatory Bowel Disease.

BACKGROUND: Treatment of pediatric inflammatory bowel disease (IBD) with monoclonal anti- tumor necrosis factor-alpha (TNFα) can result in immunogenicity and formation of anti-drug antibodies (ADAs). ADAs are associated with loss of clinical response and worsening disease progression. Data examining treatment interventions to overcome ADA in pediatric patients with IBD are lacking. RESULTS: Medical records were reviewed from 234 children and adolescents with IBD treated with infliximab or adalimumab who underwent therapeutic drug monitoring (626 tests). All patients who had detectable antibodies were further analyzed. A total 58 patients (24.8%) developed ADA while being treated with infliximab or adalimumab. The incidence of antibody development was 12.9 per 100 person-years of anti-TNF treatment. Twenty-eight patients underwent dose optimization and 54% had undetectable ADA on follow-up monitoring. The mean duration of antibody suppression was 16.8 ±â€Š10.9 months in those who were successfully suppressed with optimization. Patients who switched to a second anti-TNF medication were not more likely to develop antibodies to the second agent. CONCLUSIONS: With limited therapies for IBD and the chronicity of the disease, we advocate salvage of the current anti-TNF through dose optimization in pediatric patients with antibody level <10 U/mL.

Ferromagnetic Potts models with multisite interaction.

We study the q-state Potts model with four-site interaction on a square lattice. Based on the asymptotic behavior of lattice animals, it is argued that when q≤4 the system exhibits a second-order phase transition and when q>4 the transition is first order. The q=4 model is borderline. We find 1/lnq to be an upper bound on T_{c}, the exact critical temperature. Using a low-temperature expansion, we show that 1/(θlnq), where θ>1 is a q-dependent geometrical term, is an improved upper bound on T_{c}. In fact, our findings support T_{c}=1/(θlnq). This expression is used to estimate the finite correlation length in first-order transition systems. These results can be extended to other lattices. Our theoretical predictions are confirmed numerically by an extensive study of the four-site interaction model using the Wang-Landau entropic sampling method for q=3,4,5. In particular, the q=4 model shows an ambiguous finite-size pseudocritical behavior.

Spontaneous repulsion in the A+B→0 reaction on coupled networks.

We study the transient dynamics of an A+B→0 process on a pair of randomly coupled networks, where reactants are initially separated. We find that, for sufficiently small fractions q of cross couplings, the concentration of A (or B) particles decays linearly in a first stage and crosses over to a second linear decrease at a mixing time t_{x}. By numerical and analytical arguments, we show that for symmetric and homogeneous structures t_{x}∝(〈k〉/q)log(〈k〉/q) where 〈k〉 is the mean degree of both networks. Being this behavior is in marked contrast with a purely diffusive process, where the mixing time would go simply like 〈k〉/q, we identify the logarithmic slowing down in t_{x} to be the result of a spontaneous mechanism of repulsion between the reactants A and B due to the interactions taking place at the networks' interface. We show numerically how this spontaneous repulsion effect depends on the topology of the underlying networks.

The Performance of Two Supertree Schemes Compared Using Synthetic and Real Data Quartet Input.

Despite impressive advancements in technological and theoretical tools, construction of phylogenetic (evolutionary) trees is still a challenging task. The availability of enormous quantities of molecular data has made large-scale phylogenetic reconstruction involving thousands of species, a more viable goal. For this goal, separate trees over different, overlapping subsets of species, representing histories of various markers of these species, are collected. These trees, typically with conflicting signals, are subsequently combined into a single tree over the full set, an operation denoted as supertree construction. The amalgamation of such trees into a single tree lies at the heart of many tasks in phylogenetics, yet remains a daunting endeavor, especially in light of conflicting signals. In this work, we study the performance of matrix representation with parsimony (MRP), the most widely used supertree method to date, when confronted with quartet trees. Quartet trees are the most basic informational unit when amalgamation of unrooted trees is attempted, and they remain relevant in more general settings even though standard supertree methods are not necessarily confined to quartets. This study involves both real and simulated data, and the effects of several parameters on the results are evaluated, revealing a number of anomalies associated with MRP. We show that these anomalies are surmountable when using a recently introduced supertree method, weighted quartet MaxCut (wQMC).

Optimal cost for strengthening or destroying a given network.

Strengthening or destroying a network is a very important issue in designing resilient networks or in planning attacks against networks, including planning strategies to immunize a network against diseases, viruses, etc. Here we develop a method for strengthening or destroying a random network with a minimum cost. We assume a correlation between the cost required to strengthen or destroy a node and the degree of the node. Accordingly, we define a cost function c(k), which is the cost of strengthening or destroying a node with degree k. Using the degrees k in a network and the cost function c(k), we develop a method for defining a list of priorities of degrees and for choosing the right group of degrees to be strengthened or destroyed that minimizes the total price of strengthening or destroying the entire network. We find that the list of priorities of degrees is universal and independent of the network's degree distribution, for all kinds of random networks. The list of priorities is the same for both strengthening a network and for destroying a network with minimum cost. However, in spite of this similarity, there is a difference between their p_{c}, the critical fraction of nodes that has to be functional to guarantee the existence of a giant component in the network.

Spatio-temporal propagation of cascading overload failures in spatially embedded networks.

Different from the direct contact in epidemics spread, overload failures propagate through hidden functional dependencies. Many studies focused on the critical conditions and catastrophic consequences of cascading failures. However, to understand the network vulnerability and mitigate the cascading overload failures, the knowledge of how the failures propagate in time and space is essential but still missing. Here we study the spatio-temporal propagation behaviour of cascading overload failures analytically and numerically on spatially embedded networks. The cascading overload failures are found to spread radially from the centre of the initial failure with an approximately constant velocity. The propagation velocity decreases with increasing tolerance, and can be well predicted by our theoretical framework with one single correction for all the tolerance values. This propagation velocity is found similar in various model networks and real network structures. Our findings may help to predict the dynamics of cascading overload failures in realistic systems.

Outcomes analysis of radioactive iodine and total thyroidectomy for pediatric Graves' disease.

BACKGROUND: The majority of pediatric patients with Graves' disease will ultimately require definitive therapy in the form of radioactive iodine (RAI) ablation or thyroidectomy. There are few studies that directly compare the efficacy and complication rates between RAI and thyroidectomy. We compared the relapse rate as well as the acute and long-term complications of RAI and total thyroidectomy among children and adolescents with Graves' disease treated at our center. METHODS: Medical records from 81 children and adolescents with a diagnosis of Graves' disease who received definitive therapy over a 12-year period were reviewed. RESULTS: Fifty one patients received RAI and 30 patients underwent thyroidectomy. The relapse rate was not significantly different between RAI and thyroidectomy (12.1% vs. 0.0%, p=0.28). There were no acute or long-term complications in the RAI group, but there were eight cases of hypoparathyroidism (two transient and six permanent) in the thyroidectomy group. None of the patients developed a recurrent laryngeal nerve injury. CONCLUSIONS: RAI is a safe and effective option for treatment of children and adolescents with Graves' disease. In light of the rate of permanent hypoparathyroidism seen at our center with thyroidectomy and previously published long-term safety of RAI, we recommend RAI as the first line treatment for children and adolescents with Graves' disease. For those centers performing thyroidectomies, we recommend that each center select 1-2 high-volume pediatric surgeons to perform all thyroid procedures, allowing individuals to increases case volume and potentially decrease long-term complications of thyroidectomy.

Efficiency of message transmission using biased random walks in complex networks in the presence of traps.

We study the problem of a particle or message that travels as a biased random walk towards a target node in a network in the presence of traps. The bias is represented as the probability p of the particle to travel along the shortest path to the target node. The efficiency of the transmission process is expressed through the fraction f(g) of particles that succeed to reach the target without being trapped. By relating f(g) with the number S of nodes visited before reaching the target, we first show that, for the unbiased random walk, f(g) is inversely proportional to both the concentration c of traps and the size N of the network. For the case of biased walks, a simple approximation of S provides an analytical solution that describes well the behavior of f(g), especially for p>0.5. Also, it is shown that for a given value of the bias p, when the concentration of traps is less than a threshold value equal to the inverse of the mean first passage time (MFPT) between two randomly chosen nodes of the network, the efficiency of transmission is unaffected by the presence of traps and almost all the particles arrive at the target. As a consequence, for a given concentration of traps, we can estimate the minimum bias that is needed to have unaffected transmission, especially in the case of random regular (RR), Erdos-Rényi (ER) and scale-free (SF) networks, where an exact expression (RR and ER) or an upper bound (SF) of the MFPT is known analytically. We also study analytically and numerically, the fraction f(g) of particles that reach the target on SF networks, where a single trap is placed on the highest degree node. For the unbiased random walk, we find that f(g)∼N(-1/(γ-1)), where γ is the power law exponent of the SF network.

Weighted quartets phylogenetics.

Despite impressive technical and theoretical developments, reconstruction of phylogenetic trees for enormous quantities of molecular data is still a challenging task. A key tool in analyses of large data sets has been the construction of separate trees for subsets (e.g., quartets) of sequences, and subsequent combination of these subtrees into a single tree for the full set (i.e., supertree analysis). Unfortunately, even amalgamating quartets into a supertree remains a computationally daunting task. Assigning weights to quartets to indicate importance or reliability was proposed more than a decade ago, but handling weighted quartets is even more challenging and has scarcely been attempted in the past. In this work, we focus on weighted quartet-based approaches. We propose a scheme to assign weights to quartets coming from weighted trees and devise a tree similarity measure for weighted trees based on weighted quartets. We also extend the quartet MaxCut (QMC algorithm) to handle weighted quartets. We evaluate these tools on simulated and real data. Our simulated data analysis highlights the additional information that is conveyed when using the new weighted tree similarity measure, and shows that extending QMC to a weighted setting improves the quality of tree reconstruction. Our analyses of a cyanobacterial data set with weighted QMC reinforce previous results achieved with other tools.