Bayesian Approach to Linear Bayesian Networks

This study proposes the first Bayesian approach for learning high-dimensional linear Bayesian networks. The proposed approach iteratively estimates each element of the topological ordering from backward and its parent using the inverse of a partial covariance matrix. The proposed method successfully recovers the underlying structure when Bayesian regularization for the inverse covariance matrix with unequal shrinkage is applied. Specifically, it shows that the number of samples $n = \Omega( d_M^2 \log p)$ and $n = \Omega(d_M^2 p^{2/m})$ are sufficient for the proposed algorithm to learn linear Bayesian networks with sub-Gaussian and 4m-th bounded-moment error distributions, respectively, where $p$ is the number of nodes and $d_M$ is the maximum degree of the moralized graph. The theoretical findings are supported by extensive simulation studies including real data analysis. Furthermore the proposed method is demonstrated to outperform state-of-the-art frequentist approaches, such as the BHLSM, LISTEN, and TD algorithms in synthetic data

Competition between B-Z and B-L transitions in a single DNA molecule: Computational studies

Under negative torsion, DNA adopts left-handed helical forms, such as Z-DNA and L-DNA. Using the random copolymer model developed for a wormlike chain, we represent a single DNA molecule with structural heterogeneity as a helical chain consisting of monomers which can be characterized by different helical senses and pitches. By Monte Carlo simulation, where we take into account bending and twist fluctuations explicitly, we study sequence dependence of B-Z transitions under torsional stress and tension focusing on the interaction with B-L transitions. We consider core sequences, (GC)(n) repeats or (TG)(n) repeats, which can interconvert between the right-handed B form and the left-handed Z form, imbedded in a random sequence, which can convert to left-handed L form with different (tension dependent) helical pitch. We show that Z-DNA formation from the (GC)(n) sequence is always supported by unwinding torsional stress but Z-DNA formation from the (TG)(n) sequence, which are more costly to convert but numerous, can be strongly influenced by the quenched disorder in the surrounding random sequence.National Research Foundation NRF-2012 R1A1A3013044 NRF-2014R1A1A2055681NRF-2012R1A1A2021736IBS-R023-D1NRF-2015R1A2A2A01005916Chemistr

Ars Genotype of Arsenic Oxidizing Bacteria and Detoxification

Objectives The objectives of this study is bioremediation and detoxification of arsenite using arsenic resistance system (ars) genotypes of Arsenic Oxidizing Bacteria (AOB) isolated from highly As-contaminated mine. Methods Bacterial strains that are resistant to arsenic were isolated from the Samkwang mine. The identification of AOB was conducted by analyzing the 16S rRNA gene using universal primers. To determine the genotypes of the arsenic resistance system (ars), specific primers were used for each gene. The extent of arsenic resistance was measured, and the efficiency of arsenite oxidation was assessed through a batch test. Arsenic concentration was measured using ICP-MS. Results and Discussion The arsenic concentrations at site 1 of the Samkwang mine were found to be 1,322 mg/kg. This concentration is 26.4 times higher than the standard for soil pollution concerns (50 mg/kg) and 8.8 times higher than the standard for soil pollution measures (150 mg/kg). The appropriate remediation is studied such as bacterial remediation. The three efficient AOBs were identified as Agrobacterium tumefaciens EBC-SK1 (MF928870), Ochrobactrum anthrophi EBC-SK4 (MF928873), Ochrobactrum anthrophi EBC-SK12 (MF928881), respectively. The arsenic resistance system (ars) genotype were detected, which is the leader genes of the arsenic oxidation system (arsR and arsD), and the membrane gene (arsB). The arsB is involved in the encoding of the efflux/influx pumping system and moves arsenite into the bacterial cells. Arsenite-oxidizing (aox) genes are activated to oxidize arsenite into arsenate. The AOBs biotransform arsenite to arsenate with the regulation of ars genes, which detoxify highly As-contaminated mine. Conclusion The AOBs from Samkwang mine are known for their resistance to highly toxic arsenic environments. They play a crucial role in the bioremediation of abandoned mines by transforming As(III) into As(V) through biotransformation

Human cell-camouflaged nanomagnetic scavengers restore immune homeostasis in a rodent model with bacteremia

Bloodstream infection caused by antimicrobial resistance pathogens is a global concern because it is difficult to treat with conventional therapy. Here, scavenger magnetic nanoparticles enveloped by nanovesicles derived from blood cells (MNVs) are reported, which magnetically eradicate an extreme range of pathogens in an extracorporeal circuit. It is quantitatively revealed that glycophorin A and complement receptor (CR) 1 on red blood cell (RBC)-MNVs predominantly capture human fecal bacteria, carbapenem-resistant (CR) Escherichia coli, and extended-spectrum beta-lactamases-positive (ESBL-positive) E. coli, vancomycin-intermediate Staphylococcus aureus (VISA), endotoxins, and proinflammatory cytokines in human blood. Additionally, CR3 and CR1 on white blood cell-MNVs mainly contribute to depleting the virus envelope proteins of Zika, SARS-CoV-2, and their variants in human blood. Supplementing opsonins into the blood significantly augments the pathogen removal efficiency due to its combinatorial interactions between pathogens and CR1 and CR3 on MNVs. The extracorporeal blood cleansing enables full recovery of lethally infected rodent animals within 7 days by treating them twice in series. It is also validated that parameters reflecting immune homeostasis, such as blood cell counts, cytokine levels, and transcriptomics changes, are restored in blood of the fatally infected rats after treatment

Effect of FIXed-dose combination of ARb and statin on adherence and risk factor control: The randomized FIXAR study

Background: The efficacy of fixed-dose combinations (FDCs) in improving adherence and risk factor control for cardiovascular disease has not been reported consistently. Here, we compared adherence and efficacy between an olmesartan/rosuvastatin FDC and the usual regimen. Methods: In this 6-month, open-label, randomized, active-control study, we screened 154 patients; of these, 150 were randomly assigned to receive either olmesartan/rosuvastatin FDC or the usual regimen with separate angiotensin receptor blockers and statins. In total, 135 patients completed the study (median age: 68 years; male: 68.9%). The primary outcome was patients’ adherence; the secondary outcomes were changes in blood pressure (BP) and lipid parameters. Results: During follow-up, adherence in both groups was high and similar between the groups (98.9% and 98.3% in the FDC and usual regimen groups, respectively, p = 0.328). Changes in systolic (–8 and –5 mmHg, respectively, p = 0.084) and diastolic BP (–5 and –2 mmHg, p = 0.092) did not differ significantly, although they were numerically greater in the FDC group. Changes in low-density lipoprotein cholesterol (LDL-C) were greater in the FDC group (–13 and –4 mg/dL, respectively, p = 0.019), whereas changes in other lipid parameters were similar between the groups. The test drugs were well tolerated, showing no difference in safety between the groups. Conclusions: Patients’ adherence was excellent and similar in the groups, whereas the reduction in the LDL-C level was greater in the FDC group. We provide comprehensive information on the adherence and efficacy of an FDC compared to the usual regimen in Korean patients with high cardiovascular risk

Application of performance portability solutions for GPUs and many-core CPUs to track reconstruction kernels

Next generation High-Energy Physics (HEP) experiments are presented with significant computational challenges, both in terms of data volume and processing power. Using compute accelerators, such as GPUs, is one of the promising ways to provide the necessary computational power to meet the challenge. The current programming models for compute accelerators often involve using architecture-specific programming languages promoted by the hardware vendors and hence limit the set of platforms that the code can run on. Developing software with platform restrictions is especially unfeasible for HEP communities as it takes significant effort to convert typical HEP algorithms into ones that are efficient for compute accelerators. Multiple performance portability solutions have recently emerged and provide an alternative path for using compute accelerators, which allow the code to be executed on hardware from different vendors. We apply several portability solutions, such as Kokkos, SYCL, C++17 std::execution::par, Alpaka, and OpenMP/OpenACC, on two mini-apps extracted from the mkFit project: p2z and p2r. These apps include basic kernels for a Kalman filter track fit, such as propagation and update of track parameters, for detectors at a fixed z or fixed r position, respectively. The two mini-apps explore different memory layout formats. We report on the development experience with different portability solutions, as well as their performance on GPUs and many-core CPUs, measured as the throughput of the kernels from different GPU and CPU vendors such as NVIDIA, AMD and Intel

Representative levels of blood lead, mercury, and urinary cadmium in youth: Korean Environmental Health Survey in Children and Adolescents (KorEHS-C), 2012–2014

AbstractBackgroundThis study examined levels of blood lead and mercury, and urinary cadmium, and associated sociodemographic factors in 3–18 year-old Korean children and adolescents.Materials and methodsWe used the nationally representative Korean Environmental Health Survey in Children and Adolescents data for 2012–2014 and identified 2388 children and adolescents aged 3–18 years. The median and 95th percentile exposure biomarker levels with 95% confidence intervals (CIs) were calculated. Multivariate regression analyses were performed on log transformed exposure biomarker levels adjusted for age, sex, area, household income, and father’s education level. The median exposure biomarker levels were compared with data from Germany, the US, and Canada, as well as the levels of Korean children measured at different times.ResultsThe median levels of blood lead and mercury, as well as urinary cadmium were 1.23μg/dL, 1.80μg/L, and 0.40μg/L (95% CIs, 1.21–1.25, 1.77–1.83, and 0.39–0.41, respectively). The blood lead levels were significantly higher in boys and younger children (p<0.0001) and children with less educated fathers (p=0.004) after adjusting for covariates. Urinary cadmium level increased with age (p<0.0001). The median levels of blood mercury and urinary cadmium were much higher in Korean children and adolescents than those in their peers in Germany, the US, and Canada. Blood lead levels tended to decrease with increasing age and divergence between the sexes, particularly in the early teen years. Median levels of blood lead and urinary cadmium decreased since 2010.ConclusionSociodemographic factors, including age, sex, and father’s education level were associated with environmental exposure to heavy metals in Korean children and adolescents. These biomonitoring data are valuable for ongoing surveillance of environmental exposure in this vulnerable population

Automatically Harnessing Sparse Acceleration

Sparse linear algebra is central to many scientific programs, yet compilers fail to optimize it well. High-performance libraries are available, but adoption costs are significant. Moreover, libraries tie programs into vendor-specific software and hardware ecosystems, creating non-portable code. In this paper, we develop a new approach based on our specification Language for implementers of Linear Algebra Computations (LiLAC). Rather than requiring the application developer to (re)write every program for a given library, the burden is shifted to a one-off description by the library implementer. The LiLAC-enabled compiler uses this to insert appropriate library routines without source code changes. LiLAC provides automatic data marshaling, maintaining state between calls and minimizing data transfers. Appropriate places for library insertion are detected in compiler intermediate representation, independent of source languages. We evaluated on large-scale scientific applications written in FORTRAN; standard C/C++ and FORTRAN benchmarks; and C++ graph analytics kernels. Across heterogeneous platforms, applications and data sets we show speedups of 1.1$\times$ to over 10$\times$ without user intervention.Comment: Accepted to CC 202