Linear-time haplotype inference on pedigrees without recombinations and mating loops

In this paper, an optimal linear-time algorithm is presented to solve the haplotype inference problem for pedigree data when there are no recombinations and the pedigree has no mating loops. The approach is based on the use of graphs to capture SNP, Mendelian, and parity constraints of the given pedigree. This representation allows us to capture the constraints as the edges in a graph, rather than as a system of linear equations as in previous approaches. Graph traversals are then used to resolve the parity of these edges, resulting in an optimal running time. © 2009 Society for Industrial and Applied Mathematics.published_or_final_versio

Optimal simulation of full binary trees on faulty hypercubes

The problem of operating full binary tree based algorithms on a hypercube with faulty nodes was investigated. Developing a method for embedding a full binary tree into the faulty hypercube is the solution to this problem. Two outcomes for embedding an (n-1)-tree into an n-cube with unit dilation and load, that were based on a new embedding technique, were presented. For the problem where the root can be mapped to any nonfaulty hypercube node, the optimum toleration of faults was shown. Moreover, it was demonstrated that the algorithm for the variable root embedding problem is maximal within a class algorithms called recursive embedding algorithms as far as the number of tolerable faults is concerned. Lastly, it was demonstrated that when an O(1/√n) fraction of nodes in the hypercube are faulty, a O(1)-load variable root embedding is not always possible regardless of the significance of the dilation.published_or_final_versio

Novel cyclic di-GMP effectors of the YajQ protein family control bacterial virulence

Bis-(3 ',5 ') cyclic di-guanylate (cyclic di-GMP) is a key bacterial second messenger that is implicated in the regulation of many critical processes that include motility, biofilm formation and virulence. Cyclic di-GMP influences diverse functions through interaction with a range of effectors. Our knowledge of these effectors and their different regulatory actions is far from complete, however. Here we have used an affinity pull-down assay using cyclic di-GMP-coupled magnetic beads to identify cyclic di-GMP binding proteins in the plant pathogen Xanthomonas campestris pv. campestris (Xcc). This analysis identified XC_3703, a protein of the YajQ family, as a potential cyclic di-GMP receptor. Isothermal titration calorimetry showed that the purified XC_3703 protein bound cyclic di-GMP with a high affinity (K-d similar to 2 mu M). Mutation of XC_3703 led to reduced virulence of Xcc to plants and alteration in biofilm formation. Yeast two-hybrid and far-western analyses showed that XC_3703 was able to interact with XC_2801, a transcription factor of the LysR family. Mutation of XC_2801 and XC_3703 had partially overlapping effects on the transcriptome of Xcc, and both affected virulence. Electromobility shift assays showed that XC_3703 positively affected the binding of XC_2801 to the promoters of target virulence genes, an effect that was reversed by cyclic di-GMP. Genetic and functional analysis of YajQ family members from the human pathogens Pseudomonas aeruginosa and Stenotrophomonas maltophilia showed that they also specifically bound cyclic di-GMP and contributed to virulence in model systems. The findings thus identify a new class of cyclic di-GMP effector that regulates bacterial virulence

Robustness of Physics-Informed Neural Networks to Noise in Sensor Data

Physics-Informed Neural Networks (PINNs) have been shown to be an effective way of incorporating physics-based domain knowledge into neural network models for many important real-world systems. They have been particularly effective as a means of inferring system information based on data, even in cases where data is scarce. Most of the current work however assumes the availability of high-quality data. In this work, we further conduct a preliminary investigation of the robustness of physics-informed neural networks to the magnitude of noise in the data. Interestingly, our experiments reveal that the inclusion of physics in the neural network is sufficient to negate the impact of noise in data originating from hypothetical low quality sensors with high signal-to-noise ratios of up to 1. The resultant predictions for this test case are seen to still match the predictive value obtained for equivalent data obtained from high-quality sensors with potentially 10x less noise. This further implies the utility of physics-informed neural network modeling for making sense of data from sensor networks in the future, especially with the advent of Industry 4.0 and the increasing trend towards ubiquitous deployment of low-cost sensors which are typically noisier

Retarded PDI diffusion and a reductive shift in poise of the calcium depleted endoplasmic reticulum

Background: Endoplasmic reticulum (ER) lumenal protein thiol redox balance resists dramatic variation in unfolded protein load imposed by diverse physiological challenges including compromise in the key upstream oxidases. Lumenal calcium depletion, incurred during normal cell signaling, stands out as a notable exception to this resilience, promoting a rapid and reversible shift towards a more reducing poise. Calcium depletion induced ER redox alterations are relevant to physiological conditions associated with calcium signaling, such as the response of pancreatic cells to secretagogues and neuronal activity. The core components of the ER redox machinery are well characterized; however, the molecular basis for the calcium-depletion induced shift in redox balance is presently obscure. Results: In vitro, the core machinery for generating disulfides, consisting of ERO1 and the oxidizing protein disulfide isomerase, PDI1A, was indifferent to variation in calcium concentration within the physiological range. However, ER calcium depletion in vivo led to a selective 2.5-fold decline in PDI1A mobility, whereas the mobility of the reducing PDI family member, ERdj5 was unaffected. In vivo, fluorescence resonance energy transfer measurements revealed that declining PDI1A mobility correlated with formation of a complex with the abundant ER chaperone calreticulin, whose mobility was also inhibited by calcium depletion and the calcium depletion-mediated reductive shift was attenuated in cells lacking calreticulin. Measurements with purified proteins confirmed that the PDI1A-calreticulin complex dissociated as Ca2+ concentrations approached those normally found in the ER lumen ([Ca2+] K-0.5max = 190 mu M). Conclusions: Our findings suggest that selective sequestration of PDI1A in a calcium depletion-mediated complex with the abundant chaperone calreticulin attenuates the effective concentration of this major lumenal thiol oxidant, providing a plausible and simple mechanism for the observed shift in ER lumenal redox poise upon physiological calcium depletion.Wellcome Trust [Wellcome 084812/Z/08/Z]; European Commission (EU FP7 Beta-Bat) [277713]; Fundacao para a Ciencia e Tecnologia, Portugal [PTDC/QUI-BIQ/119677/2010]info:eu-repo/semantics/publishedVersio

Current progress on removal of recalcitrance coloured particles from anaerobically treated effluent using coagulation–flocculation

The palm oil industry is the most important agro industries in Malaysia and most of the mills adopt anaerobic digestion as their primary treatment for palm oil mill effluent (POME). Due to the public concern, decolourisation of anaerobically treated POME (AnPOME) is becoming a great concern. Presence of recalcitrant-coloured particles hinders biological processes and coagulation–flocculation may able to remove these coloured particles. Several types of inorganic and polymers-based coagulant/flocculant aids for coagulation–flocculation of AnPOME have been reviewed. Researchers are currently interested in using natural coagulant and flocculant aids. Modification of the properties of natural coagulant and flocculant aids enhanced coagulation–flocculation performance. Modelling and optimization of the coagulation–flocculation process have also been reviewed. Chemical sludge has the potential for plant growth that can be evaluated through pot trials and phytotoxicity test

ERYTHROPOIETIN FOR THE TREATMENT OF SUBARACHNOID HEMORRAGE: A FEASIBLE INGREDIENT FOR A SUCCESS MEDICAL RECIPE

Subaracnhoid hemorrage (SAH) following aneurysm bleeding accounts for 6% to 8% of all cerebrovascular accidents. Althoug an aneurysm can be effectively managed by surgery or endovascular therapy, delayed cerebral ischemia is diagnosed in a high percentage of patients resulting in significant morbility and mortality. Cerebral vasospasm occurs in more than half of all patients after aneurysm rupture and is recognized as the leading cause of delayed cerebral ischemia after SAH. Hemodynamic strategies and endovascular procedures may be considered fo the treatment of cerebral vasospasm. In recent years, the mechanism contributing to the development of vasospasm, abnormal reactivity of cerebral arteries and cerebral ischemia following SAH, have been intensively investigated. A number of pathological processes have been identified in the pathogenesis of vasospasm including endothelial injury, smooth muscle cell contraction from spasmogenic substances produced by the subarachnoid blood clots, changes in vascular responsiveness and inflammatory response of the vascular endothelium. to date, the current therapeutic interventions remain ineffective being limited to the manipulation os systemic blood pressure, variation of blood volume and viscosity, and control of arterial carbon dioxide tension. In this scenario, the hormone erythropoietin (EPO), has been found to exert neuroprotective action during experimental SAH when its recombinant form (rHuEPO) is systematically administered. However, recent translation of experimental data into clinical trials has suggested an unclear role of recombinant human EPO in the setting of SAH. In this context, the aim of the recurrent review is to present current evidence on the potential role of EPO in cerebrovascular dysfunction following aneurysmal subarachnoid hemorrage

Tailoring Generative Adversarial Networks for Smooth Airfoil Design

In the realm of aerospace design, achieving smooth curves is paramount, particularly when crafting objects such as airfoils. Generative Adversarial Network (GAN), a widely employed generative AI technique, has proven instrumental in synthesizing airfoil designs. However, a common limitation of GAN is the inherent lack of smoothness in the generated airfoil surfaces. To address this issue, we present a GAN model featuring a customized loss function built to produce seamlessly contoured airfoil designs. Additionally, our model demonstrates a substantial increase in design diversity compared to a conventional GAN augmented with a post-processing smoothing filter

Trends and predictions of metabolic risk factors for acute myocardial infarction: findings from a multiethnic nationwide cohort

BACKGROUND: Understanding the trajectories of metabolic risk factors for acute myocardial infarction (AMI) is necessary for healthcare policymaking. We estimated future projections of the incidence of metabolic diseases in a multi-ethnic population with AMI. METHODS: The incidence and mortality contributed by metabolic risk factors in the population with AMI (diabetes mellitus [T2DM], hypertension, hyperlipidemia, overweight/obesity, active/previous smokers) were projected up to year 2050, using linear and Poisson regression models based on the Singapore Myocardial Infarction Registry from 2007 to 2018. Forecast analysis was stratified based on age, sex and ethnicity. FINDINGS: From 2025 to 2050, the incidence of AMI is predicted to rise by 194.4% from 482 to 1418 per 100,000 population. The largest percentage increase in metabolic risk factors within the population with AMI is projected to be overweight/obesity (880.0% increase), followed by hypertension (248.7% increase), T2DM (215.7% increase), hyperlipidemia (205.0% increase), and active/previous smoking (164.8% increase). The number of AMI-related deaths is expected to increase by 294.7% in individuals with overweight/obesity, while mortality is predicted to decrease by 11.7% in hyperlipidemia, 29.9% in hypertension, 32.7% in T2DM and 49.6% in active/previous smokers, from 2025 to 2050. Compared with Chinese individuals, Indian and Malay individuals bear a disproportionate burden of overweight/obesity incidence and AMI-related mortality. INTERPRETATION: The incidence of AMI is projected to continue rising in the coming decades. Overweight/obesity will emerge as fastest-growing metabolic risk factor and the leading risk factor for AMI-related mortality. FUNDING: This research was supported by the NUHS Seed Fund (NUHSRO/2022/058/RO5+6/Seed-Mar/03) and National Medical Research Council Research Training Fellowship (MOH-001131). The SMIR is a national, ministry-funded registry run by the National Registry of Diseases Office and funded by the Ministry of Health, Singapore