Miracle-dz/UniFAR-FTUs huggingface dataset:
One hypervirulent clone, sequence type 283, accounts for a large proportion of invasive Streptococcus agalactiae isolated from humans and diseased tilapia in Southeast Asia

Background In 2015, Singapore had the first and only reported foodborne outbreak of invasive disease caused by the group B Streptococcus (GBS; Streptococcus agalactiae). Disease, predominantly septic arthritis and meningitis, was associated with sequence type (ST)283, acquired from eating raw farmed freshwater fish. Although GBS sepsis is well-described in neonates and older adults with co-morbidities, this outbreak affected non-pregnant and younger adults with fewer co-morbidities, suggesting greater virulence. Before 2015 ST283 had only been reported from twenty humans in Hong Kong and two in France, and from one fish in Thailand. We hypothesised that ST283 was causing region-wide infection in Southeast Asia. Methodology/Principal findings We performed a literature review, whole genome sequencing on 145 GBS isolates collected from six Southeast Asian countries, and phylogenetic analysis on 7,468 GBS sequences including 227 variants of ST283 from humans and animals. Although almost absent outside Asia, ST283 was found in all invasive Asian collections analysed, from 1995 to 2017. It accounted for 29/38 (76%) human isolates in Lao PDR, 102/139 (73%) in Thailand, 4/13 (31%) in Vietnam, and 167/739 (23%) in Singapore. ST283 and its variants were found in 62/62 (100%) tilapia from 14 outbreak sites in Malaysia and Vietnam, in seven fish species in Singapore markets, and a diseased frog in China. Conclusions GBS ST283 is widespread in Southeast Asia, where it accounts for a large proportion of bacteraemic GBS, and causes disease and economic loss in aquaculture. If human ST283 is fishborne, as in the Singapore outbreak, then GBS sepsis in Thailand and Lao PDR is predominantly a foodborne disease. However, whether transmission is from aquaculture to humans, or vice versa, or involves an unidentified reservoir remains unknown. Creation of cross-border collaborations in human and animal health are needed to complete the epidemiological picture.
Microbial Eukaryotes in Oil Sands Environments: Heterotrophs in the Spotlight

Hydrocarbon extraction and exploitation is a global, trillion-dollar industry. However, for decades it has also been known that fossil fuel usage is environmentally detrimental; the burning of hydrocarbons results in climate change, and environmental damage during extraction and transport can also occur. Substantial global efforts into mitigating this environmental disruption are underway. The global petroleum industry is moving more and more into exploiting unconventional oil reserves, such as oil sands and shale oil. The Albertan oil sands are one example of unconventional oil reserves; this mixture of sand and heavy bitumen lying under the boreal forest of Northern Alberta represent one of the world’s largest hydrocarbon reserves, but extraction also requires the disturbance of a delicate northern ecosystem. Considerable effort is being made by various stakeholders to mitigate environmental impact and reclaim anthropogenically disturbed environments associated with oil sand extraction. In this review, we discuss the eukaryotic microbial communities associated with the boreal ecosystem and how this is affected by hydrocarbon extraction, with a particular emphasis on the reclamation of tailings ponds, where oil sands extraction waste is stored. Microbial eukaryotes, or protists, are an essential part of every global ecosystem, but our understanding of how they affect reclamation is limited due to our fledgling understanding of these organisms in anthropogenically hydrocarbon-associated environments and the difficulties of studying them. We advocate for an environmental DNA sequencing-based approach to determine the microbial communities of oil sands associated environments, and the importance of studying the heterotrophic components of these environments to gain a full understanding of how these environments operate and thus how they can be integrated with the natural watersheds of the region.
Green pre-concentration techniques during pesticide analysis in food samples

Abstract The ever-increasing demand for determining pesticides at low concentration levels in different food matrices requires a preliminary step of pre-concentration which is considered a crucial stage. Recently, the parameter of “greenness” during sample pre-concentration of pesticides in food matrices is as important as selectivity in order to avoid using harmful organic solvents during sample preparation. Developing new green pre-concentration techniques is one of the key subjects. Thus, to reduce the impact on the environment during trace analysis of pesticides in food matrices, new developments in pre-concentration have gone in three separate directions: the search for more environmentally friendly solvents, miniaturization and development of solvent-free pre-concentration techniques. Eco-friendly solvents such as supercritical fluids, ionic liquids and natural deep eutectic solvents have been developed for use as extraction solvents during pre-concentration of pesticides in food matrices. Also, miniaturized pre-concentration techniques such as QuEChERS, dispersive liquid–liquid micro-extraction and hollow-fiber liquid-phase micro-extraction have been used during trace analysis of pesticides in food samples as well as solvent-free techniques such as solid-phase micro-extraction and stir bar sorptive extraction. All these developments which are aimed at ensuring that pesticide pre-concentration in different food matrices is green are critically reviewed in this paper.
Detection of HEV in naturally infected swine from central Argentina by an optimized HEV/MS2 duplex RT‐qPCR

Hepatitis E virus (HEV) is currently considered as a global health concern due to the recognition of its zoonotic transmission to humans, mainly from swine, and its association with the development of severe cases of hepatitis in human risk populations. The lack of updated data on HEV state of infection in swineherds of Argentina, and the necessity of robust technologies for its detection in complex biological samples, positions HEV as an emerging issue in public health. Here, we have optimized a RT‐qPCR with internal control for a more precise and accurate HEV RNA detection in swine stool samples. We implemented this optimized molecular tool to analyse the current epidemiological scenario of HEV infection in swine from the core region of commercial activity of Argentina. A total of 135 stool samples were collected from 16 different farms and tested for HEV presence, resulting in 11 positive cases (8.1%). Phylogenetic analysis demonstrated that all of them correspond to HEV genotype 3 and that different subtypes circulate in the region. Moreover, two of the detected strains presented a high nucleotide similarity with a previously identified isolate from human sewage discharges, suggesting the zoonotic transmission of HEV to humans. Collectively, this work provides a better understanding of HEV epidemiology in Argentina while contributes to the improvement of HEV detection technologies.
Atypical neural variability in carriers of 16p11.2 copy number variants

Copy number variations (CNVs) at the 16p11.2 chromosomal region are associated with myriad clinical features including intellectual disability and autism spectrum disorder. The aim of this study is to determine whether 16p11.2 deletion (DEL) and duplication (DUP) carriers demonstrate a distinct and reciprocal pattern of electroencephalography (EEG) activity as represented by neural variability measures. EEG data were previously collected as part of the Simons Variation in Individuals Project. Variability measures, as estimated by single‐trial ERP and spectral power analyses in the alpha and beta frequency bands, in addition to signal‐to‐noise ratios (SNRs), were analyzed in DEL (n = 20), DUP (n = 8), and typical (n = 11) groups. We also analyzed mean visual evoked potentials and spectral power (alpha and beta power) to facilitate comparisons with other studies of associated disorders and CNVs. From measures of single‐trial variability, we found higher intraparticipant variability in P1 amplitude and timecourse amplitude in DEL compared to controls. Compared to DUP, DEL showed higher variability in absolute alpha and absolute beta power but lower variability in P1 latency. SNRs did not differ between the groups. From measures of amplitude, latency, and spectral power, DUP showed lower relative alpha power compared to controls. Although it is yet unclear whether 16p11.2 CNV dosage impacts neural activity in an opposing manner, findings suggest that 16p11.2 DEL impacts the level of variability of neural responses. Higher neural variability may play a role in a range of cognitive processes in 16p11.2 CNV carriers. Autism Res 2019, 12: 1322–1333. © 2019 International Society for Autism Research, Wiley Periodicals, Inc.
An Algorithm for Automated Separation of Trabecular Bone From Variably Thick Cortices in High-Resolution Computed Tomography Data

Objective: Structural measurements after separation of cortical from trabecular bone are of interest to a wide variety of communities but are difficult to obtain because of the lack of accurate automated techniques. Methods: We present a structure-based algorithm for separating cortical from trabecular bone in binarized images. Using the thickness of the cortex as a seed value, bone connected to the cortex within a spatially local threshold value is identified and separated from the remaining bone. The algorithm was tested on seven biological data sets from four species imaged using micro-computed tomography (μ-CT) and high-resolution peripheral quantitative computed tomography (HR-pQCT). Area and local thickness measurements were compared to images segmented manually. Results: The algorithm was approximately 11 times faster than manual measurements and the median error in cortical area was −4.47 ± 4.15%. The median error in cortical thickness was approximately 0.5 voxels for μ-CT data and less than 0.05 voxels for HR-pQCT images resulting in an overall difference of −28.1 ± 71.1 μm. Conclusion: A simple and readily implementable methodology has been developed that is repeatable, efficient, and requires few user inputs, providing an unbiased means of separating cortical from trabecular bone. Significance: Automating the segmentation of variably thick cortices will allow for the evaluation of large data sets in a time-efficient manner and allow for full-field analyses that have been previously limited to small regions of interest. The MATLAB code can be downloaded from https://github.com/TBL-UIUC/downloads.git.
Association between Dietary Calcium Intake and Adiposity in Male Adolescents

The aim was to investigate the possible association of dietary calcium intake with adiposity, insulin resistance, and adipocytokine values in adolescent boys. In this cross-sectional study, participants were 123 adolescent boys aged 13–15 years, who were divided into tertiles according to their dietary calcium intake. Dietary calcium intake was assessed using three 24 h dietary recalls. In addition, energy intake, body composition, physical activity (PA), and blood biochemical values were also measured. Mean body fat%, fat mass (FM), trunk FM, trunk fat%, and leptin differed between high and low tertiles of calcium intake after adjustment for age, pubertal stage, and PA. For the entire cohort, mean calcium intake was 786 ± 380 mg/day and was related to body mass index (BMI), FM, and trunk fat% but not to insulin resistance or adipocytokine values after adjusting for possible confounders. In addition, only 15.4% of the participants obtained or exceeded their mean dietary calcium intake requirements. These subjects who met their dietary calcium intake had significantly lower body fat% in comparison with subjects not meeting their dietary calcium intake. Odds ratio of being in the highest tertile of FM, trunk FM, and trunk fat% was 3.2–4.4 (95% confidence interval 1.19–12.47; p < 0.05) times higher for boys in low calcium intake tertile, compared to those boys in high calcium intake tertile. In conclusion, dietary calcium intake is inversely associated with total body and abdominal adiposity values in a specific group of healthy male adolescents with different body mass values.
Transactions Papers Near-Capacity Turbo Trellis Coded Modulation Design Based on EXIT Charts and Union Bounds

Bandwidth efficient parallel-concatenated Turbo Trellis Coded Modulation (TTCM) schemes were designed for communicating over uncorrelated Rayleigh fading channels. A symbol-based union bound was derived for analysing the error floor of the proposed TTCM schemes. A pair of In-phase (I) and Quadrature-phase (Q) interleavers were employed for interleaving the I and Q components of the TTCM coded symbols, in order to attain an increased diversity gain. The decoding convergence of the IQ-TTCM schemes was analysed using symbol-based EXtrinsic Information Transfer (EXIT) charts. The best TTCM component codes were selected with the aid of both the symbolbased union bound and non-binary EXIT charts, for designing capacity-approaching IQ-TTCM schemes in the context of 8PSK, 16QAM, 32QAM and 64QAM modulation schemes.
Prognostic Score and Cytogenetic Risk Classification for Chronic Lymphocytic Leukemia Patients: Center for International Blood and Marrow Transplant Research Report

Purpose: To develop a prognostic model and cytogenetic risk classification for previously treated patients with chronic lymphocytic leukemia (CLL) undergoing reduced intensity conditioning (RIC) allogeneic hematopoietic cell transplantation (HCT). Experimental Design: We performed a retrospective analysis of outcomes of 606 patients with CLL who underwent RIC allogeneic HCT between 2008 and 2014 reported to the Center for International Blood and Marrow Transplant Research. Results: On the basis of multivariable models, disease status, comorbidity index, lymphocyte count, and white blood cell count at HCT were selected for the development of prognostic model. Using the prognostic score, we stratified patients into low-, intermediate-, high-, and very-high-risk [4-year progression-free survival (PFS) 58%, 42%, 33%, and 25%, respectively, P < 0.0001; 4-year overall survival (OS) 70%, 57%, 54%, and 38%, respectively, P < 0.0001]. We also evaluated karyotypic abnormalities together with del(17p) and found that del(17p) or ≥5 abnormalities showed inferior PFS. Using a multivariable model, we classified cytogenetic risk into low, intermediate, and high (P < 0.0001). When the prognostic score and cytogenetic risk were combined, patients with low prognostic score and low cytogenetic risk had prolonged PFS (61% at 4 years) and OS (75% at 4 years). Conclusions: In this large cohort of patients with previously treated CLL who underwent RIC HCT, we developed a robust prognostic scoring system of HCT outcomes and a novel cytogenetic-based risk stratification system. These prognostic models can be used for counseling patients, comparing data across studies, and providing a benchmark for future interventions. For future study, we will further validate these models for patients receiving targeted therapies prior to HCT.
Lexical Chaining and Word-Sense-Disambiguation

Lexical chains algorithms attempt to find sequences of words in a document that are closely related semantically. Such chains have been argued to provide a good indication of the topics covered by the document without requiring a deeper analysis of the text, and have been proposed for many NLP tasks. Different underlying lexical semantic relations based on WordNet have been used for this task. Since links in WordNet connect synsets rather than words, open word-sense disambiguation becomes a necessary part of any chaining algorithm, even if the intended application is not disambiguation. Previous chaining algorithms have combined the tasks of disambiguation and chaining by choosing those word senses that maximize chain connectivity, a strategy which yields poor disambiguation accuracy in practice. We present a novel probabilistic algorithm for finding lexical chains. Our algorithm explicitly balances the requirements of maximizing chain connectivity with the choice of probable word-senses. The algorithm achieves better disambiguation results than all previous ones, but under its optimal settings shifts this balance totally in favor of probable senses, essentially ignoring the chains. This model points to an inherent conflict between chaining and word-sensedisambiguation. By establishing an upper bound on the disambiguation potential of lexical chains, we show that chaining is theoretically highly unlikely to achieve accurate disambiguation. Moreover, by defining a novel intrinsic evaluation criterion for lexical chains, we show that poor disambiguation accuracy also implies poor chain accuracy. Our results have crucial implications for chaining algorithms. At the very least, they show that disentangling disambiguation from chaining significantly improves chaining accuracy. The hardness of all-words disambiguation, however, implies that finding accurate lexical chains is harder than suggested by the literature.
Molecular recognition of M1-linked ubiquitin chains by native and phosphorylated UBAN domains

Although the Ub-binding domain in ABIN proteins and NEMO (UBAN) is highly conserved, UBAN-containing proteins exhibit different Ub-binding properties, resulting in their diverse biological roles. Post-translational modifications further control UBAN domain specificity for poly-Ub chains. However, precisely, how the UBAN domain structurally confers such functional diversity remains poorly understood. Here we report crystal structures of ABIN-1 alone and in complex with one or two M1-linked di-Ub chains. ABIN-1 UBAN forms a homo-dimer that provides two symmetrical Ub-binding sites on either side of the coiled-coil structure. Moreover, crystal structures of ABIN1 UBAN in complex with di-Ub chains reveal a concentration-dependency of UBAN/di-Ub binding stoichiometry. Analysis of UBAN/M1-linked di-Ub binding characteristics indicates that phosphorylated S473 in OPTN and its corresponding phospho-mimetic residue in ABIN-1 (E484) are essential for high affinity interactions with M1-linked Ub chains. Also, a phospho-mimetic mutation of A303 in NEMO, corresponding to S473 of OPTN, increases binding affinity for M1-linked Ub chains. These findings are in line with the diverse physiological roles of UBAN domains, as phosphorylation of OPTN UBAN is required to enhance its binding to Ub during mitophagy.
High-resolution contrast-enhanced microCT reveals the true three-dimensional morphology of the murine placenta

Significance During pregnancy, the placenta functions as surrogate fetal lungs, kidneys, and gut. Proper placental functioning is therefore paramount during embryonic development. Indeed, placental defects are highly prevalent in mouse mutants showing embryonic death. Here we validate a contrast agent that allows development of the intact placenta to be visualized using microfocus computed topography. This technique enables an initial 3D inspection of the overall placental structure and provides the possibility to quantify different compartments in the placenta. Moreover, the nondestructive nature of this contrast agent permits further histological processing of the same sample when defects are observed. Genetic engineering of the mouse genome identified many genes that are essential for embryogenesis. Remarkably, the prevalence of concomitant placental defects in embryonic lethal mutants is highly underestimated and indicates the importance of detailed placental analysis when phenotyping new individual gene knockouts. Here we introduce high-resolution contrast-enhanced microfocus computed tomography (CE-CT) as a nondestructive, high-throughput technique to evaluate the 3D placental morphology. Using a contrast agent, zirconium-substituted Keggin polyoxometalate (Zr-POM), the soft tissue of the placenta (i.e., different layers and cell types and its vasculature) was imaged with a resolution of 3.5 µm voxel size. This approach allowed us to visualize and study early and late stages of placental development. Moreover, CE-CT provides a method to precisely quantify placental parameters (i.e., volumes, volume fraction, ratio of different placental layers, and volumes of specific cell populations) that are crucial for statistical comparison studies. The CE-CT assessment of the 3D morphology of the placentas was validated (i) by comparison with standard histological studies; (ii) by evaluating placentas from 2 different mouse strains, 129S6 and C57BL/6J mice; and (iii) by confirming the placental phenotype of mice lacking phosphoinositol 3-kinase (PI3K)-p110α. Finally, the Zr-POM–based CE-CT allowed for inspection of the vasculature structure in the entire placenta, as well as detecting placental defects in pathologies characterized by embryonic resorption and placental fusion. Taken together, Zr-POM–based CE-CT offers a quantitative 3D methodology to investigate placental development or pathologies.
A model-based imputation procedure for multilevel regression models with random coefficients, interaction effects, and nonlinear terms.

Despite the broad appeal of missing data handling approaches that assume a missing at random (MAR) mechanism (e.g., multiple imputation and maximum likelihood estimation), some very common analysis models in the behavioral science literature are known to cause bias-inducing problems for these approaches. Regression models with incomplete interactive or polynomial effects are a particularly important example because they are among the most common analyses in behavioral science research applications. In the context of single-level regression, fully Bayesian (model-based) imputation approaches have shown great promise with these popular analysis models. The purpose of this article is to extend model-based imputation to multilevel models with up to 3 levels, including functionality for mixtures of categorical and continuous variables. Computer simulation results suggest that this new approach can be quite effective when applied to multilevel models with random coefficients and interaction effects. In most scenarios that we examined, imputation-based parameter estimates were quite accurate and tracked closely with those of the complete data. The new procedure is available in the Blimp software application for macOS, Windows, and Linux, and the article includes a data analysis example illustrating its use. (PsycINFO Database Record (c) 2019 APA, all rights reserved).
FXR overexpression alters adipose tissue architecture in mice and limits its storage capacity leading to metabolic derangements[S]

The bile acid-activated nuclear receptor, FXR (NR1H4), has been implicated in the control of lipid and energy metabolism, but its role in fat tissue, where it is moderately expressed, is not understood. In view of the recent development of FXR-targeting therapeutics for treatment of human metabolic diseases, understanding the tissue-specific actions of FXR is essential. Transgenic mice expressing human FXR in adipose tissue (aP2-hFXR mice) at three to five times higher levels than endogenous Fxr, i.e., much lower than its expression in liver and intestine, have markedly enlarged adipocytes and show extensive extracellular matrix remodeling. Ageing and exposure to obesogenic conditions revealed a strongly limited capacity for adipose expansion and development of fibrosis in adipose tissues of aP2-hFXR transgenic mice. This was associated with impaired lipid storage capacity, leading to elevated plasma free fatty acids and ectopic fat deposition in liver and muscle as well as whole-body insulin resistance. These studies establish that adipose FXR is a determinant of adipose tissue architecture and contributes to whole-body lipid homeostasis.