Miracle-dz/UniFAR-FTUs huggingface dataset:
Widespread dissemination of class 1 integron components in soils and related ecosystems as revealed by cultivation-independent analysis

Class 1 integrons contribute to the emerging problem of antibiotic resistance in human medicine by acquisition, exchange, and expression of resistance genes embedded within gene cassettes. Besides the clinical setting they were recently reported from environmental habitats and often located on plasmids and transposons, facilitating their transfer and spread within bacterial communities. In this study we aimed to provide insights into the occurrence of genes typically associated with the class 1 integrons in previously not studied environments with or without human impact and their association with IncP-1 plasmids. Total community DNA was extracted from manure-treated and untreated soils, lettuce and potato rhizosphere, digestates, and an on-farm biopurification system and screened by PCR with subsequent Southern blot hybridization for the presence of the class 1 integrase gene intI1 as well as qacE and qacEΔ 1 resistance genes. The results revealed a widespread dissemination of class 1 integrons in the environments analyzed, mainly related to the presence of qacEΔ 1 genes. All 28 IncP-1ε plasmids carrying class 1 integrons, which were captured exogenously in a recent study from piggery manure and soils treated with manure, carried qacEΔ 1 genes. Based on the strong hybridization signals in the rhizosphere of lettuce compared to the potato rhizosphere, the abundances of intI1, qacE/qacEΔ 1, and sul1 genes were quantified relative to the 16S rRNA gene abundance by real-time PCR in the rhizosphere of lettuce planted in three different soils and in the corresponding bulk soil. A significant enrichment of intI1 and qacE/qacEΔ 1 genes was confirmed in the rhizosphere of lettuce compared to bulk soil. Additionally, the relative abundance of korB genes specific for IncP-1 plasmids was enriched in the rhizosphere and correlated to the intI1 gene abundance indicating that IncP-1 plasmids might have contributed to the spread of class 1 integrons in the analyzed soils.
Revising the Human Development Sequence Theory Using an Agent-Based Approach and Data

Agent-based models and computer simulations are promising tools for studying emergent macro-phenomena. We apply an agent-based approach in combination with data analysis to investigate the human development sequence (HDS) theory developed by Ronald Inglehart and Christian Welzel. Although the HDS theory is supported by correlational evidence, the sequence of economic growth, democracy and emancipation stated by the theory is not entirely consistent with data. We use an agent-based model to make quantitative predictions about several different micro-level mechanisms. Comparison to data allows us to identify important inconsistencies between HDS and the data, and propose revised agent-based models that modify the theory. Our results indicate the importance of elites and economic inequality in explaining the data available on democratisation.
Constant approximation for virtual backbone construction with Guaranteed Routing Cost in wireless sensor networks

In wireless sensor networks, virtual backbone construction based on connected dominating set is a competitive issue for routing efficiency and topology control. Assume that a sensor networks is defined as a connected unit disk graph (UDG). The problem is to find a minimum connected dominating set of given UDG with minimum routing cost for each node pair. We present a constant approximation scheme which produces a connected dominating set D, whose size |D| is within a factor α from that of the minimum connected dominating set and each node pair exists a routing path with all intermediate nodes in D and with length at most 5 · d(u,v), where d(u,v) is the length of shortest path of this node pair. A distributed algorithm is also provided with analogical performance. Extensive simulation shows that our distributed algorithm achieves significantly than the latest solution in research direction.
Ensemble Subsampling for Imbalanced Multivariate Two-Sample Tests

Some existing nonparametric two-sample tests for equality of multivariate distributions perform unsatisfactorily when the two sample sizes are unbalanced. In particular, the power of these tests tends to diminish with increasingly unbalanced sample sizes. In this article, we propose a new testing procedure to solve this problem. The proposed test, based on the nearest neighbor method by Schilling, employs a novel ensemble subsampling scheme to remedy this issue. More specifically, the test statistic is a weighted average of a collection of statistics, each associated with a randomly selected subsample of the data. We derive the asymptotic distribution of the test statistic under the null hypothesis and show that the new test is consistent against all alternatives when the ratio of the sample sizes either goes to a finite limit or tends to infinity. Via simulated data examples we demonstrate that the new test has increasing power with increasing sample size ratio when the size of the smaller sample is fixed. The test is applied to a real-data example in the field of corporate finance. Supplementary materials for this article are available online.
Seasonal distribution of Alternaria, Aspergillus, Cladosporium and Penicillium species isolated in homes of fungal allergic patients.

BACKGROUND Allergy to airborne fungi can cause rhinitis and severe asthma, hence the exposure to spores inside home is an important factor of sensitization. The aim of this study was to determine the distribution and prevalence of species of Alternaria, Aspergillus, Cladosporium and Penicillium inside and outside of homes of patients allergic to fungi and to evaluate seasonal variations. METHODS Air samples were collected in 22 selected homes of patients with allergy to fungi using a volumetric method of impacting plates with culture media. The isolated species were identified and statistical analysis of the presence of the four fungi was carried out. RESULTS A total of 431 indoor and 150 outdoor exposed plates were cultured, leading to isolation of 11,843 colonies of fungi (range 0- 1 666 colony-forming units per cubic meter (CFUs/m(3)). 85.5% of total colonies belonged to the four genera considered. The highest presence of Aspergillus, Cladosporium and Penicillium in indoor environment was registered in autumn. Alternaria was more frequent in summer. In the outdoor environment, Penicillium was more abundant in winter and Aspergillus in summer (P= .002). The largest numbers of isolations were of Cladosporium and Penicillium during all four seasons, indoors as well as outdoors. Alternaria was present in all the homes studied both in summer and in autumn. The most prevalent species were: Alternaria alternata, Cladosporium herbarum, Cladosporium cladosporioides, Aspergillus niger and Penicillium chrysogenum. CONCLUSIONS The quantitative analysis of the four taxa related with respiratory allergies demonstrated considerable seasonal variability. Statistical differences between the indoor and outdoor prevalence were detected only in Alternaria. In summer and autumn, the greater level of exposure to the four studied taxas occurred inside homes.
Exact FCFS Matching Rates for Two Infinite Multitype Sequences

Motivated by queues with multitype servers and multitype customers, we consider an infinite sequence of items of types C = {c1,. ,cI}, and another infinite sequence of items of types S = {s1,. ,sJ}, and a bipartite graph G of allowable matches between the types. We assume that the types of items in the two sequences are independent and identically distributed (i.i.d.) with given probability vectors α, β. Matching the two sequences on a first-come, first-served basis defines a unique infinite matching between the sequences. For (ci,sj) ∈ G we define the matching rate rci, sj as the long-term fraction of (ci, sj) matches in the infinite matching, if it exists. We describe this system by a multidimensional countable Markov chain, obtain conditions for ergodicity, and derive its stationary distribution, which is, most surprisingly, of product form. We show that if the chain is ergodic, then the matching rates exist almost surely, and we give a closed-form formula to calculate them. We point out the connection of this model to some queueing models.
Donor Milk: Down but Not Out

To the Editor. — As usual for Schanler et al,1 their latest study is extremely well done, with careful outcome definition and randomization, standardized feeding protocols, and sophisticated statistical analysis. The sample size was based on expected differences in necrotizing enterocolitis (NEC) and late-onset sepsis (LOS) from a prior study.2 Fortunately for the infants, but unfortunately for the study, the incidence of NEC was almost 50% less than anticipated. Because the rates of NEC were much less than predicted, the sample sizes were inadequate to detect a significant difference if present; the mother's own milk (MM) and donor milk (DM) groups had a 6% incidence of NEC, whereas the preterm formula (PF) group had an 11% incidence (see Table 2 in ref 1). The article does not specify which patients from their general NICU population eligible for the study were approached or excluded from study because of parents declining, death before day 4, …
Speech Enhancement Based on Nonlinear Models Using Particle Filters

Motivated by the reportedly strong performance of particle filters (PFs) for noise reduction on essentially linear speech production models, and the mounting evidence that the introduction of nonlinearities can lead to a refined speech model, this paper presents a study of PF solutions to the problem of speech enhancement in the context of nonlinear, neural-type speech models. Several variations of a global model are presented (single/multiple neurons; bias/no bias), and corresponding PF solutions are derived. Different importance functions are given when beneficial, Rao-Blackwellization is proposed when possible, and dual/nondual versions of each algorithms are presented. The method shown can handle both white and colored noise. Using a variety of speech and noise signals and different objective quality measures, the performance of these algorithms are evaluated against other PF solutions running on linear models, as well as some traditional enhancement algorithms. A certain hierarchy in performance is established between each algorithm in the paper. Depending on the experimental conditions, the best-performing algorithms are a classical Rao-Blackwellized particle filter (RBPF) running on a linear model, and a proposed PF employing a nondual, nonlinear model with multiple neurons and no biases. With consistence, the neural-network-based PF outperforms RBPF at low signal-to-noise ratio (SNR).
Increased lymphomagenicity and restored disease specificity of AML1 site (core) mutant SL3-3 murine leukemia virus by a second-site enhancer variant evolved in vivo

SL3-3 is a highly T-lymphomagenic murine retrovirus. The major genetic determinant of disease is the transcriptional enhancer, which consists of a repeated region with densely packed binding sites for several transcription factors, including AML1 (also known as core binding factor and polyoma enhancer-binding protein 2) and nuclear factor 1 (NF1). Previously, we examined the enhancer structure of proviruses from murine tumors induced by SL3-3 with mutated AML1 (core) sites and found a few cases of second-site alterations. These consisted of deletions involving the NF1 sites and alterations in overall number of repeat elements, and they conferred increased enhancer strength in transient transcription assays. We have now tested the pathogenicity of a virus harboring one such second-site variant enhancer in inbred NMRI mice. It induced lymphomas with a 100% incidence and a significantly shorter latency than the AML1 mutant it evolved from. The enhancer structure thus represents the selection for a more tumorigenic virus variant during the pathogenic process. Sequencing of provirus from the induced tumors showed the new enhancer variant to be genetically stable. Also, Southern blotting showed that the tumors induced by the variant were T-cell lymphomas, as were the wild-type-induced lymphomas. In contrast, tumors induced by the original core/AML1 site I-II mutant appeared to be of non-T-cell origin and several proviral genomes with altered enhancer regions could be found in the tumors. Moreover, reporter constructs with the new tumor-derived variant could not be transactivated by AML1 in cotransfection experiments as could the wild type. These results emphasize the importance of both core/AML1 site I and site II for the pathogenic potential of SL3-3 and at the same time show that second-site alterations can form a viral variant with a substantial pathogenic potential although both AML1 sites I and II are nonfunctional.
Long-term survival benefit after adjuvant treatment of cutaneous melanoma with dacarbazine and low dose natural interferon alpha: A controlled, randomised multicentre trial

In a prospective, controlled, randomised, multicentre study 252 patients with totally resected cutaneous melanoma (248 in stage II–III and 4 in stage IV) were either treated with two doses of dacarbazine (DTIC) followed by a 6-month treatment with 3 MU thrice weekly of highly purified natural interferon-alpha (n = 128; arm A) or received no adjuvant treatment (n = 124; arm B). Treatment was well tolerated. After a median follow-up of 8.5 years ITT analysis showed that the difference in survival was statistically significant with respect to melanoma-related deaths (HR = 0.65, CI = 0.46–0.97, p = 0.022) and close to significance with respect to overall survival (HR 0.71, CI 0.49–1.00, p = 0.052). The risk reduction of melanoma-associated death, calculated by Cox proportional hazards modelling, after adjusting for identified predictive variables, was almost 50% (p = 0.002). The overall efficacy of the treatment appeared to be mainly attributable to effects observed in patients with deep and/or metastasizing tumours (HR 0.60, CI 0.40–0.90, p = 0.013).
Hedgehog-Induced Survival of B-Cell Chronic Lymphocytic Leukemia Cells in a Stromal Cell Microenvironment: A Potential New Therapeutic Target

B-cell chronic lymphocytic leukemia (B-CLL) is characterized by an accumulation of neoplastic B cells due to their resistance to apoptosis and increased survival. Among various factors, the tumor microenvironment is known to play a role in the regulation of cell proliferation and survival of many cancers. However, it remains unclear how the tumor microenvironment contributes to the increased survival of B-CLL cells. Therefore, we studied the influence of bone marrow stromal cell–induced hedgehog (Hh) signaling on the survival of B-CLL cells. Our results show that a Hh signaling inhibitor, cyclopamine, inhibits bone marrow stromal cell–induced survival of B-CLL cells, suggesting a role for Hh signaling in the survival of B-CLL cells. Furthermore, gene expression profiling of primary B-CLL cells (n = 48) indicates that the expression of Hh signaling molecules, such as GLI1, GLI2, SUFU, and BCL2, is significantly increased and correlates with disease progression of B-CLL patients with clinical outcome. In addition, SUFU and GLI1 transcripts, as determined by real-time PCR, are significantly overexpressed and correlate with adverse indicators of clinical outcome in B-CLL patients, such as cytogenetics or CD38 expression. Furthermore, selective down-regulation of GLI1 by antisense oligodeoxynucleotides (GLI1-ASO) results in decreased BCL2 expression and cell survival, suggesting that GLI1 may regulate BCL2 and, thereby, modulate cell survival in B-CLL. In addition, there was significantly increased apoptosis of B-CLL cells when cultured in the presence of GLI1-ASO and fludarabine. Together, these results reveal that Hh signaling is important in the pathogenesis of B-CLL and, hence, may be a potential therapeutic target. (Mol Cancer Res 2008;6(12):1928–36)
Lattice Boltzmann Method

Lattice Boltzmann method is relatively new method in the field of computational fluid dynamics. It has been derived from lattice gas automata and is still under development. Basic steps of the LBM (collision, streaming, boundary conditions, macroscopic quantities) will be presented. Comparison with the finite difference method that uses Navier-Stokes equation on a lid driven cavity benchmark test will be made.
Invited Article: The Alzheimer disease–frontotemporal lobar degeneration spectrum

Alzheimer disease (AD) and frontotemporal lobar degeneration (FTLD) are two frequent forms of primary neurodegenerative dementias. Despite distinctive clinical diagnostic criteria for both brain disorders, differential diagnosis is often complicated by overlapping symptomatology. As we learn more about brain pathology and genetic makeup underlying these dementia disorders, evidence is accumulating for a clinical, pathologic, and genetic spectrum of neurodegenerative brain diseases in which AD and FTLD occur along one continuum. This has important implications for molecular diagnostic testing and genetic counseling of patients with dementia. In this light, we review the molecular genetics of AD and FTLD assessing how AD genes can be implicated in FTLD and conversely FTLD genes in AD, by modifying disease susceptibility. Herein, we focus on recent exciting findings providing further support for an AD-FTLD spectrum.
Balancing Detection and Eradication for Control of Epidemics: Sudden Oak Death in Mixed-Species Stands

Culling of infected individuals is a widely used measure for the control of several plant and animal pathogens but culling first requires detection of often cryptically-infected hosts. In this paper, we address the problem of how to allocate resources between detection and culling when the budget for disease management is limited. The results are generic but we motivate the problem for the control of a botanical epidemic in a natural ecosystem: sudden oak death in mixed evergreen forests in coastal California, in which species composition is generally dominated by a spreader species (bay laurel) and a second host species (coast live oak) that is an epidemiological dead-end in that it does not transmit infection but which is frequently a target for preservation. Using a combination of an epidemiological model for two host species with a common pathogen together with optimal control theory we address the problem of how to balance the allocation of resources for detection and epidemic control in order to preserve both host species in the ecosystem. Contrary to simple expectations our results show that an intermediate level of detection is optimal. Low levels of detection, characteristic of low effort expended on searching and detection of diseased trees, and high detection levels, exemplified by the deployment of large amounts of resources to identify diseased trees, fail to bring the epidemic under control. Importantly, we show that a slight change in the balance between the resources allocated to detection and those allocated to control may lead to drastic inefficiencies in control strategies. The results hold when quarantine is introduced to reduce the ingress of infected material into the region of interest.
SemEval-2013 Task 13: Word Sense Induction for Graded and Non-Graded Senses

Most work on word sense disambiguation has assumed that word usages are best labeled with a single sense. However, contextual ambiguity or fine-grained senses can potentially enable multiple sense interpretations of a usage. We present a new SemEval task for evaluating Word Sense Induction and Disambiguation systems in a setting where instances may be labeled with multiple senses, weighted by their applicability. Four teams submitted nine systems, which were evaluated in two settings.
A meta-analysis of the relationship among impaired taste and treatment, treatment type, and tumor site in head and neck cancer treatment survivors

PROBLEM IDENTIFICATION To understand how taste impairment caused by head and neck cancer treatment changes over time or varies with treatment site or type. LITERATURE SEARCH Ovid MEDLINE® database was searched for reports of health-related quality of life (HRQOL) in head and neck cancer treatment survivors (HNCTS), which included taste function in a HRQOL instrument from 1946-2013. Eligible studies compared taste scores from baseline to post-treatment, using two treatment types or two cancer sites. DATA EVALUATION 247 reports were identified; 19 were suitable for meta-analysis. DATA ANALYSIS A series of dichotomous meta-analyses were conducted using comprehensive meta-analysis software . PRESENTATION OF FINDINGS: Taste scores were statistically significantly worse after treatment; the summary effect for the standard measure difference between pretreatment and post-treatment taste scores was 0.353 (p < 0.001). Patients treated with radiation therapy (RT) reported statistically significant worse taste function post-treatment than those who received no RT; the summary effect for the standard mean differences in taste scores was 0.77 (p = 0.001). Differences in tumor site were not significant. IMPLICATIONS FOR NURSING Taste dysfunction is a long-term complication for HNCTS, and nurses should screen survivors for this sensory dysfunction.
Longitudinal Assessment of Amyloid Pathology in Transgenic ArcAβ Mice Using Multi-Parametric Magnetic Resonance Imaging

Magnetic resonance imaging (MRI) can be used to monitor pathological changes in Alzheimer's disease (AD). The objective of this longitudinal study was to assess the effects of progressive amyloid-related pathology on multiple MRI parameters in transgenic arcAβ mice, a mouse model of cerebral amyloidosis. Diffusion-weighted imaging (DWI), T1-mapping and quantitative susceptibility mapping (QSM), a novel MRI based technique, were applied to monitor structural alterations and changes in tissue composition imposed by the pathology over time. Vascular function and integrity was studied by assessing blood-brain barrier integrity with dynamic contrast-enhanced MRI and cerebral microbleed (CMB) load with susceptibility weighted imaging and QSM. A linear mixed effects model was built for each MRI parameter to incorporate effects within and between groups (i.e. genotype) and to account for changes unrelated to the disease pathology. Linear mixed effects modelling revealed a strong association of all investigated MRI parameters with age. DWI and QSM in addition revealed differences between arcAβ and wt mice over time. CMBs became apparent in arcAβ mice with 9 month of age; and the CMB load reflected disease stage. This study demonstrates the benefits of linear mixed effects modelling of longitudinal imaging data. Moreover, the diagnostic utility of QSM and assessment of CMB load should be exploited further in studies of AD.