Miracle-dz/UniFAR-FTUs huggingface dataset:
Association study of MCP-1 promoter polymorphisms with the susceptibility and progression of sepsis

Previous studies have indicated that the monocyte chemo-attractant protein 1 (MCP-1), also referred to as C-C motif chemokine ligand 2 (CCL2), plays a significant role in the pathogenesis of sepsis, and this study investigated the clinical relevance of two MCP-1 gene polymorphisms on sepsis onset and progression. The Multiplex SNaPshot genotyping method was used to detect MCP-1 gene polymorphisms in the Chinese Han population (403 sepsis patients and 400 controls). MCP-1 mRNA expression levels were measured using real-time quantitative PCR, and enzyme-linked immunosorbent assays were used to analyze MCP-1, tumor necrosis factor-alpha (TNF-α), interleukin 6 (IL-6) and interleukin-1 beta (IL-1β) plasma concentrations. The rs1024611 polymorphism analysis showed lower frequencies of minor homozygous genotype (AA) and allele (A) in sepsis patients compared to the healthy controls (19.4% vs. 31.5%, P = 0.0001 and 45.9% vs. 54.8%, P = 0.0004, respectively). And the frequencies of GG genotype and G allele were lower in sepsis patients compared to the controls (19.6% vs. 31.3%, P = 0.0002 and 46.0% vs. 54.5%, P = 0.0007, respectively). The rs1024611 AG/GG and rs2857656 GC/CC genotypes were both overrepresented in patients with severe sepsis (both P = 0.0005) and septic shock (P = 0.010 and P = 0.015, respectively) compared to the patients with mild sepsis. Moreover, among sepsis patients, the rs1024611 AG/GG and rs2857656 GC/CC carriers exhibited significant increases in expression levels of MCP-1 (P = 0.025), TNF-α (P = 0.034) and IL-6 (P = 0.043) compared with the rs1024611 AA or rs2857656 GG carriers. This study provides valuable clinical evidence that the MCP-1/CCL2 polymorphisms rs1024611 and rs2857656 are associated with sepsis susceptibility and development. We conclude that MCP-1/CCL2 plays a significant role in the pathogenesis of sepsis, which has potentially important therapeutic implications.
Nonlinear analysis of the sleep EEG in children with pervasive developmental disorder.

OBJECTIVES Autism is a severe neurodevelopmental disorder with a high rate of epilepsy and subclinical epileptiform activity. High physical connectivity on a microcolumnar level leading to epileptiform activity and low functional informational connectivity are assumed in autism. The aim of this study was to investigate nonlinear EEG brain dynamics in terms of synchronization in a group of children with autism spectrum disorders compared to a control group. We expected a lower degree of synchronization in autistic subjects. METHODS The autistic group consisted of 27 patients with autism spectrum disorders diagnosed according to ICD-10. The mean age of the sample was 7.1 (SD 3.6) years, 14 of them were mentally retarded. Normal EEG was found in 9 patients, epileptiform EEG in 18 autistic patients. Four patients had a history of epileptic seizures, fully compensated in long term. The control group consisted of 20 children (mean age of 8.4, SD 2.3 years) with normal intelligence, without an epileptic history, investigated within the frame of the research program for cochlear implantation. They had normal neurological examination and suffered from perceptive deafness. Normal EEG was found in 17 of the control subjects, epileptiform EEG was in 3 control subjects. We analyzed night sleep EEG recordings from 10 channels (F3, F4, F7, F8, C3, C4, T3, T4, P3 and P4) with the inclusion of sleep stages NREM 2, 3 and 4 in the subsequent analyses. Coarse-grained entropy information rates between neighbouring electrodes were computed, expressing the synchronization between 11 selected electrode couples. RESULTS Synchronization was significantly lower in the autistic group in all three examined NREM stages even when age and intelligence were taken into account as covariates. CONCLUSIONS The results of the study confirmed the validity of the underconnectivity model in autism.
Efficient Spectral-Galerkin Methods III: Polar and Cylindrical Geometries

We present in this paper several extremely efficient and accurate spectral-Galerkin methods for second- and fourth-order equations in polar and cylindrical geometries. These methods are based on appropriate variational formulations which incorporate naturally the pole condition(s). In particular, the computational complexities of the Chebyshev--Galerkin method in a disk and the Chebyshev--Legendre--Galerkin method in a disk or a cylinder are quasi-optimal (optimal up to a logarithmic term). As an indication of efficiency, the CPU time for the Poisson solver on a disk by our Chebyshev--Galerkin method is only about 70% of the corresponding finite-difference code in FISHPACK.
Nearly perfectly matched layer method for seismic wave propagation in poroelastic media

The nearly perfectly matched layer (NPML) method has been successfully applied to electromagnetic and elasto dynamic wave equations including elastic isotropic and anisotropic media types to absorb spurious arrivals reflected from introduced boundaries in a number of numerical solution methods. It has been shown to be extremely satisfactory for this purpose. In this paper, a first-order velocity-stress-pressure system with NPML is obtained from Biot’s equations. A staggered-grid finite-difference method with fourth-order accuracy in space and second-order accuracy in time is developed to simulate seismic wave propagation in a 2 D fluidsaturated poroelastic media. The absorbing perform ance of NPML is investigated by wavefield snapshots, waveform and energy decay measurements in numer ical experiments. The numerical results demonstrate that NPML suppresses the spurious reflections in a highly effective manner.
Frequency Diversity in Mode-Division Multiplexing Systems

In the regime of strong mode coupling, the modal gains and losses and the modal group delays of a multimode fiber are known to have well-defined statistical properties. In mode-division multiplexing, mode-dependent gains and losses are known to cause fluctuations in the channel capacity, so that the capacity at finite outage probability can be substantially lower than the average capacity. Mode-dependent gains and losses, when frequency-dependent, have a coherence bandwidth that is inversely proportional to the modal group delay spread. When mode-division-multiplexed signals occupy a bandwidth far larger than the coherence bandwidth, the mode-dependent gains and losses are averaged over frequency, causing the outage capacity to approach the average capacity. The difference between the average and outage capacities is found to be inversely proportional to the square-root of a diversity order that is given approximately by the ratio of the signal bandwidth to the coherence bandwidth.
ARIA: automatic resource inference and allocation for mapreduce environments

MapReduce and Hadoop represent an economically compelling alternative for efficient large scale data processing and advanced analytics in the enterprise. A key challenge in shared MapReduce clusters is the ability to automatically tailor and control resource allocations to different applications for achieving their performance goals. Currently, there is no job scheduler for MapReduce environments that given a job completion deadline, could allocate the appropriate amount of resources to the job so that it meets the required Service Level Objective (SLO). In this work, we propose a framework, called ARIA, to address this problem. It comprises of three inter-related components. First, for a production job that is routinely executed on a new dataset, we build a job profile that compactly summarizes critical performance characteristics of the underlying application during the map and reduce stages. Second, we design a MapReduce performance model, that for a given job (with a known profile) and its SLO (soft deadline), estimates the amount of resources required for job completion within the deadline. Finally, we implement a novel SLO-based scheduler in Hadoop that determines job ordering and the amount of resources to allocate for meeting the job deadlines. We validate our approach using a set of realistic applications. The new scheduler effectively meets the jobs' SLOs until the job demands exceed the cluster resources. The results of the extensive simulation study are validated through detailed experiments on a 66-node Hadoop cluster.
Problem-solving therapy and supportive therapy in older adults with major depression and executive dysfunction.

OBJECTIVE The purpose of this study was to determine whether problem-solving therapy is an effective treatment in older patients with depression and executive dysfunction, a population likely to be resistant to antidepressant drugs. METHOD Participants were adults age 60 and older with major depression and executive dysfunction. Problem-solving therapy was modified to be accessible to this population. Participants were randomly assigned to 12 weekly sessions of problem-solving therapy or supportive therapy and assessed at weeks 3, 6, 9, and 12. RESULTS Of the 653 individuals referred for this study, 221 met selection criteria and were enrolled in the study. Reduction of depressive symptom severity was comparable for the two treatment groups during the first 6 weeks of treatment, but at weeks 9 and 12 the problem-solving therapy group had a greater reduction in symptom severity, a greater response rate, and a greater remission rate than the supportive therapy group (response rates at week 9: 47.1% and 29.3%; at week 12:56.7% and 34.0%; remission rates at week 9: 37.9% and 21.7%; at week 12: 45.6% and 27.8%). Problem-solving therapy yielded one additional response or remission over supportive therapy for every 4.4-5.6 patients by the end of the trial. CONCLUSIONS These results suggest that problem-solving therapy is effective in reducing depressive symptoms and leading to treatment response and remission in a considerable number of older patients with major depression and executive dysfunction. The clinical value of this finding is that problem-solving therapy may be a treatment alternative in an older patient population likely to be resistant to pharmacotherapy.
Performance Rescaling of Complex Networks

Recent progress in network topology modeling has shown that it is possible to create smaller-scale replicas of large complex networks, like the Internet, while simultaneously preserving several important topological properties. However, the constructed replicas do not include notions of capacities and latencies, and the fundamental question of whether smaller networks can reproduce the performance of larger networks remains unanswered. We address this question in this letter, and show that it is possible to predict the performance of larger networks from smaller replicas, as long as the right link capacities and propagation delays are assigned to the replica's links. Our procedure is inspired by techniques introduced in and combines a time-downscaling argument from . We show that significant computational savings can be achieved when simulating smaller-scale replicas with TCP and UDP traffic, with simulation times being reduced by up to two orders of magnitude.
Allelopathic effects of weeds extracts against seed germination of some plants.

This study investigated the allelopathic effects of various weeds extracts on seed germination of 11 crop species. Most of the weed extracts tested had inhibitory effects on seed germination of common bean, tomato, pepper, squash, onion, barley, wheat, and corn at different application rates as compared with the 10% acetone control. Chickpea seed germination was inhibited by extracts of Solanum nigrum L. , Chenopodium album L. , and Matricaria chamomilla L. (10%, 20% and 22.5%, respectively) at the end of 21 day incubation period. However, Glycyrrhiza glabra L. , Sorghum halepense (L.) Pers. , and Reseda lutea L. extracts stimulated chickpea seed germination at the rates of 95%, 94%, and 93%, respectively, compared to control. It was concluded that some of the weed extracts tested in this study could be used as inhibitor while others could be used as stimulator for the crops.
Towards Unbiased BFS Sampling

Breadth First Search (BFS) is a widely used approach for sampling large graphs. However, it has been empirically observed that BFS sampling is biased toward high-degree nodes, which may strongly affect the measurement results. In this paper, we quantify and correct the degree bias of BFS. First, we consider a random graph RG(pk) with an arbitrary degree distribution pk. For this model, we calculate the node degree distribution expected to be observed by BFS as a function of the fraction f of covered nodes. We also show that, for RG(pk), all commonly used graph traversal techniques (BFS, DFS, Forest Fire, Snowball Sampling, RDS) have exactly the same bias. Next, we propose a practical BFS-bias correction procedure that takes as input a collected BFS sample together with the fraction f. Our correction technique is exact (i.e., leads to unbiased estimation) for RG(pk). Furthermore, it performs well when applied to a broad range of Internet topologies and to two large BFS samples of Facebook and Orkut networks.
Induction of the Chemokines Interleukin-8 and IP-10 by Human Immunodeficiency Virus Type 1 Tat in Astrocytes

ABSTRACT A finding commonly observed in human immunodeficiency virus type 1 (HIV-1)-infected patients is invasion of the brain by activated T cells and infected macrophages, eventually leading to the development of neurological disorders and HIV-1-associated dementia. The recruitment of T cells and macrophages into the brain is likely the result of chemokine expression. Indeed, earlier studies revealed that levels of different chemokines were increased in the cerebrospinal fluid of HIV-1-infected patients whereas possible triggers and cellular sources for chemokine expression in the brain remain widely undefined. As previous studies indicated that HIV-1 Tat, the retroviral transactivator, is capable of inducing a variety of cellular genes, we investigated its capacity to induce production of chemokines in astrocytes. Herein, we demonstrate that HIV-1 Tat72aa is a potent inducer of MCP-1, interleukin-8 (IL-8), and IP-10 expression in astrocytes. Levels of induced IP-10 protein were sufficiently high to induce chemotaxis of peripheral blood lymphocytes. In addition, Tat72aa induced IL-8 expression in astrocytes. IL-8 mRNA induction was seen less then 1 h after Tat72aastimulation, and levels remained elevated for up to 24 h, leading to IL-8 protein production. Tat72aa-mediated MCP-1 and IL-8 mRNA induction was susceptible to inhibition by the MEK1/2 inhibitor UO126 but was only modestly decreased by the inclusion of the p38 mitogen-activated protein kinase (MAPK) inhibitor SB202190. In contrast, Tat-mediated IP-10 mRNA induction was suppressed by SB202190 but not by the MEK1/2 inhibitor UO126. These findings indicate that MAPKs play a major role in Tat72aa-mediated chemokine induction in astrocytes.
Hard X-Ray Emission Associated with White Dwarfs

Inspired by the hard X-ray emission from WD 2226-210, the central star of the Helix Nebula, we have made a systematic search for similar sources by correlating the white dwarf catalog of McCook & Sion and the ROSAT Position Senstive Proportional Counter (PSPC) point-source catalog of White, Giommi, & Angelini. We find 76 white dwarfs coincident with X-ray sources at a high level of confidence. Among these sources, 17 show significant hard X-ray emission at energies greater than 0.5 keV. Twelve of these white dwarfs with hard X-ray emission are in known binary systems, in two of which the accretion of the close companion's material onto the white dwarf produces hard X-ray emission, and in the other 10 the late-type companions' coronal activity emits hard X-rays. One apparently single white dwarf is projected near an active galactic nucleus that is responsible for the hard X-ray emission. The remaining four white dwarfs and two additional white dwarfs with hard X-ray emission appear single. The lack of near-IR excess from the apparently single white dwarfs suggests that either X-ray observations are more effective than near-IR photometry in diagnosing faint companions, or a different emission mechanism is needed. It is intriguing that 50% of the six apparently single white dwarfs with hard X-ray emission are among the hottest white dwarfs. We have compared X-ray properties of 11 hot white dwarfs with different spectral types and conclude that stellar pulsation and fast stellar winds are not likely the origin of the hard X-ray emission, but a leakage of the high-energy Wien tail of emission from deep in the stellar atmosphere remains a tantalizing source of hard X-ray emission from hot DO and DQZO white dwarfs. A complete survey using the entire ROSAT PSPC archive is needed to enlarge the sample of white dwarfs with hard X-ray emission. Follow-up near-IR photometric observations are needed to verify the existence of late-type companions, and high-resolution deep X-ray observations are needed to verify the positional coincidence and to study the X-ray spectral properties in order to determine the origin and nature of the hard X-ray emission.
[F]Fluorodeoxyglucose – positron emission tomography/computed tomography improves staging in patients with high-risk muscle-invasive bladder cancer scheduled for radical cystectomy

Objective. The aim of this study was to evaluate the clinical use of [F]fluorodeoxyglucosepositron emission tomography/computed tomography (FDG-PET/CT) in addition to conventional preoperative radiological investigations in a defined group of patients with high-risk muscle-invasive bladder cancer. Materials and methods. In total, 103 patients with high-risk muscle-invasive bladder cancer defined as stage T3/T4 disease or as stage T2 with hydronephrosis or high-risk histological features, who were provisionally scheduled to undergo cystectomy, were prospectively recruited to the study. The patients were referred to FDG-PET/CT in addition to standard preoperative investigation with computed tomography (CT). The final treatment decision was reached at a multidisciplinary conference based on all available information including the FDG-PET/CT findings. Results. Compared to CT alone, FDG-PET/CT provided more supplemental findings suggesting malignant manifestations in 48 (47%) of the 103 patients. The additional FDG-PET/CT findings led to an altered provisional treatment plan in 28 out of 103 patients (27%), detection of disseminated bladder cancer and subsequent cancellation of the initially intended cystectomy in 16 patients, and identification of disseminated disease and treatment with induction chemotherapy before radical cystectomy in 12 patients. Conclusions. Preoperative FDG-PET/CT changed the treatment plan for a considerable proportion (27%) of the present patients. Accordingly, such examination can potentially improve the preoperative staging of cystectomy patients with high-risk features, and may also reduce the number of futile operations in patients with advanced disease who are beyond cure.
Innovative Design for Flux Leakage Reduction in IPM Machines

This paper presents a novel rotor design for interior permanent-magnet machines. The advantage of this solution is the near elimination of magnetic flux leakage in the rotor iron bridges, which represents the main disadvantage of this machine topology. Therefore, enhanced magnet utilization results from the new rotor arrangement. This concept is accomplished by utilizing non-magnetic wedges to lock the magnet in a robust rotor structure. This paper is supported by both electromagnetic and mechanical finite-element method analyses. Significant results of this investigation are presented and discussed in this paper. A machine prototype with the implemented innovative rotor design was manufactured and tested for the validation of the finite-element simulations. Several manufacturing methods of the wedge have been investigated in order to evaluate the resultant wedge characteristics and in order to assess the feasibility of mass production. The total cost analysis yields potential machine cost reduction.
Standard and reduced radiation dose liver CT images: adaptive statistical iterative reconstruction versus model-based iterative reconstruction-comparison of findings and image quality.

PURPOSE To investigate whether reduced radiation dose liver computed tomography (CT) images reconstructed with model-based iterative reconstruction ( MBIR model-based iterative reconstruction ) might compromise depiction of clinically relevant findings or might have decreased image quality when compared with clinical standard radiation dose CT images reconstructed with adaptive statistical iterative reconstruction ( ASIR adaptive statistical iterative reconstruction ). MATERIALS AND METHODS With institutional review board approval, informed consent, and HIPAA compliance, 50 patients (39 men, 11 women) were prospectively included who underwent liver CT. After a portal venous pass with ASIR adaptive statistical iterative reconstruction images, a 60% reduced radiation dose pass was added with MBIR model-based iterative reconstruction images. One reviewer scored ASIR adaptive statistical iterative reconstruction image quality and marked findings. Two additional independent reviewers noted whether marked findings were present on MBIR model-based iterative reconstruction images and assigned scores for relative conspicuity, spatial resolution, image noise, and image quality. Liver and aorta Hounsfield units and image noise were measured. Volume CT dose index and size-specific dose estimate ( SSDE size-specific dose estimate ) were recorded. Qualitative reviewer scores were summarized. Formal statistical inference for signal-to-noise ratio ( SNR signal-to-noise ratio ), contrast-to-noise ratio ( CNR contrast-to-noise ratio ), volume CT dose index, and SSDE size-specific dose estimate was made (paired t tests), with Bonferroni adjustment. RESULTS Two independent reviewers identified all 136 ASIR adaptive statistical iterative reconstruction image findings (n = 272) on MBIR model-based iterative reconstruction images, scoring them as equal or better for conspicuity, spatial resolution, and image noise in 94.1% (256 of 272), 96.7% (263 of 272), and 99.3% (270 of 272), respectively. In 50 image sets, two reviewers (n = 100) scored overall image quality as sufficient or good with MBIR model-based iterative reconstruction in 99% (99 of 100). Liver SNR signal-to-noise ratio was significantly greater for MBIR model-based iterative reconstruction (10.8 ± 2.5 [standard deviation] vs 7.7 ± 1.4, P < .001); there was no difference for CNR contrast-to-noise ratio (2.5 ± 1.4 vs 2.4 ± 1.4, P = .45). For ASIR adaptive statistical iterative reconstruction and MBIR model-based iterative reconstruction , respectively, volume CT dose index was 15.2 mGy ± 7.6 versus 6.2 mGy ± 3.6; SSDE size-specific dose estimate was 16.4 mGy ± 6.6 versus 6.7 mGy ± 3.1 (P < .001). CONCLUSION Liver CT images reconstructed with MBIR model-based iterative reconstruction may allow up to 59% radiation dose reduction compared with the dose with ASIR adaptive statistical iterative reconstruction , without compromising depiction of findings or image quality.
Linear regression and two-class classification with gene expression data

MOTIVATION Using gene expression data to classify (or predict) tumor types has received much research attention recently. Due to some special features of gene expression data, several new methods have been proposed, including the weighted voting scheme of Golub et al., the compound covariate method of Hedenfalk et al. (originally proposed by Tukey), and the shrunken centroids method of Tibshirani et al. These methods look different and are more or less ad hoc. RESULTS We point out a close connection of the three methods with a linear regression model. Casting the classification problem in the general framework of linear regression naturally leads to new alternatives, such as partial least squares (PLS) methods and penalized PLS (PPLS) methods. Using two real data sets, we show the competitive performance of our new methods when compared with the other three methods.