Miracle-dz/UniFAR-FTUs huggingface dataset:
Systematic Evaluation of Whole Genome Sequence-Based Predictions of Salmonella Serotype and Antimicrobial Resistance

Whole-genome sequencing (WGS) is used increasingly in public-health laboratories for typing and characterizing foodborne pathogens. To evaluate the performance of existing bioinformatic tools for in silico prediction of antimicrobial resistance (AMR) and serotypes of Salmonella enterica, WGS-based genotype predictions were compared with the results of traditional phenotyping assays. A total of 111 S. enterica isolates recovered from a Canadian baseline study on broiler chicken conducted in 2012-2013 were selected based on phenotypic resistance to 15 different antibiotics and isolates were subjected to WGS. Both SeqSero2 and SISTR accurately determined S. enterica serotypes, with full matches to laboratory results for 87.4 and 89.2% of isolates, respectively, and partial matches for the remaining isolates. Antimicrobial resistance genes (ARGs) were identified using several bioinformatics tools including the Comprehensive Antibiotic Resistance Database – Resistance Gene Identifier (CARD-RGI), Center for Genomic Epidemiology (CGE) ResFinder web tool, Short Read Sequence Typing for Bacterial Pathogens (SRST2 v 0.2.0), and k-mer alignment method (KMA v 1.17). All ARG identification tools had ≥ 99% accuracy for predicting resistance to all antibiotics tested except streptomycin (accuracy 94.6%). Evaluation of ARG detection in assembled versus raw-read WGS data found minimal observable differences that were gene- and coverage- dependent. Where initial phenotypic results indicated isolates were sensitive, yet ARGs were detected, repeat AMR testing corrected discrepancies. All tools failed to find resistance-determining genes for one gentamicin- and two streptomycin-resistant isolates. Further investigation found a single nucleotide polymorphism (SNP) in the nuoF coding region of one of the isolates which may be responsible for the observed streptomycin-resistant phenotype. Overall, WGS-based predictions of AMR and serotype were highly concordant with phenotype determination regardless of computational approach used.
Noncanonical, Dopamine-Dependent Long-Term Potentiation at Hippocampal Output Synapses in a Rodent Model of First-Episode Psychosis

Cognitive deficits and positive symptoms in schizophrenia have both been linked to hippocampal dysfunction. Recently, subregion-specific aberrant and maladaptive hippocampal synaptic plasticity has been suggested as one of the mechanistic underpinnings. The subiculum is the final output hub of the hippocampus and orchestrates hippocampal information transfer to other brain regions. While most CA1 pyramidal neurons show regular-spiking behavior, subicular output neurons comprise bursting and regular-firing pyramidal cells. These two cell types target different brain regions and express unique forms of synaptic plasticity. Here, we used a single systemic application of the noncompetitive glutamatergic N-methyl-D-aspartate receptor (NMDAR) antagonist MK-801 to model first-episode psychosis in rats and studied long-term potentiation (LTP) in subicular regular-firing cells in acute hippocampal slices. Previously, we have reported a facilitation of a presynaptic, late-onset LTP in subicular bursting pyramidal cells after systemic NMDAR antagonism. Here, we show that single systemic NMDAR antagonist application also facilitates the induction of a noncanonical, but postsynaptic NMDAR-independent LTP in ventral subicular but not in CA1 regular-firing pyramidal cells. This form of LTP was dependent on D1/D5 dopamine receptor activation. Activation of D1/D5 dopamine receptors by a specific agonist mimicked and occluded LTP induced by electrical high-frequency stimulation (HFS). Furthermore, our results indicate that this form of LTP relies on postsynaptic Ca2+ signaling and requires the activation of protein kinase A. Considering the pivotal role of the subiculum as information gatekeeper between the hippocampus and other brain regions, this aberrant LTP in ventral subicular regular-firing neurons is expected to interfere with physiological hippocampal output processing and might thereby contribute to hippocampal dysfunction in psychotic events.
Peak Width of Skeletonized Water Diffusion MRI in the Neonatal Brain

Preterm birth is closely associated with cognitive impairment and generalized dysconnectivity of neural networks inferred from water diffusion MRI (dMRI) metrics. Peak width of skeletonized mean diffusivity (PSMD) is a metric derived from histogram analysis of mean diffusivity across the white matter skeleton, and it is a useful biomarker of generalized dysconnectivity and cognition in adulthood. We calculated PSMD and five other histogram based metrics derived from diffusion tensor imaging (DTI) and neurite orientation and dispersion imaging (NODDI) in the newborn, and evaluated their accuracy as biomarkers of microstructural brain white matter alterations associated with preterm birth. One hundred and thirty five neonates (76 preterm, 59 term) underwent 3T MRI at term equivalent age. There were group differences in peak width of skeletonized mean, axial, and radial diffusivities (PSMD, PSAD, PSRD), orientation dispersion index (PSODI) and neurite dispersion index (PSNDI), all p < 10−4. PSFA did not differ between groups. PSNDI was the best classifier of gestational age at birth with an accuracy of 81±10%, followed by PSMD, which had 77±9% accuracy. Models built on both NODDI metrics, and on all dMRI metrics combined, did not outperform the model based on PSNDI alone. We conclude that histogram based analyses of DTI and NODDI parameters are promising new image markers for investigating diffuse changes in brain connectivity in early life.
Enhancing Teachers' Competence in Building Students' Numeracy in Grades K-3

Supporting growth in problem solving is key to capacity development for both teachers and students. When teachers engage in rich academic conversations that inquire deeply into content and pedagogy, they have an opportunity to cultivate student capacity to engage in rich academic discourse, problem solving and mathematical learning. In this study, we examined an intensive professional development training intervention in which teacher participants learned to use and understand the Teaching Learning Community (TLC) approach, design and connect standards-based lessons, and nurture a mindset of learning and thinking like a problem solver among students and teachers alike. We further examined whether there were any differences in students' MAP test scores over time among students whose teachers participated in the intervention and students whose teachers did not participate. Findings from the Analysis of Variance of students' MAP test scores indicated that students whose teachers participated in the intervention demonstrated more growth in mathematical proficiency, particularly in Grade 3. Thus, implementing an intervention like the one described herein that provides the appropriate resources to teachers, education in the form of high-quality professional development, and an opportunity to collaborate with peers and experts can result in direct improvement to student achievement in math.
Skill Learning by Autonomous Robotic Playing Using Active Learning and Exploratory Behavior Composition

We consider the problem of autonomous acquisition of manipulation skills where problem-solving strategies are initially available only for a narrow range of situations. We propose to extend the range of solvable situations by autonomous play with the object. By applying previously-trained skills and behaviors, the robot learns how to prepare situations for which a successful strategy is already known. The information gathered during autonomous play is additionally used to train an environment model. This model is exploited for active learning and the generation of novel preparatory behaviors compositions. We apply our approach to a wide range of different manipulation tasks, e.g., book grasping, grasping of objects of different sizes by selecting different grasping strategies, placement on shelves, and tower disassembly. We show that the composite behavior generation mechanism enables the robot to solve previously-unsolvable tasks, e.g., tower disassembly. We use success statistics gained during real-world experiments to simulate the convergence behavior of our system. Simulation experiments show that the learning speed can be improved by around 30% by using active learning.
Improving the Catalytic Performance of Pectate Lyase Through Pectate Lyase/Cu3(PO4)2 Hybrid Nanoflowers as an Immobilized Enzyme

Pectate lyases (Pels) can be used in the textile industrial process for cotton scouring and ramie degumming, and its hydrolyzed products oligo galacturonic acid, are high-value added agricultural and health products. In our previous studies, an alkaline pectate lyase PEL168 mutant, PEL3, was obtained with improved specific activity and thermostability. Here, a facile and rapid method for preparing an immobilized PEL3-inorganic hybrid nanoflower was developed, as it could improve its biocatalytic performance. With 0.02 mg/mL (112.2 U/mL) PEL3 in PBS buffer, five different divalent ions, including Mn2+, Ca2+, Co2+, Zn2+, and Cu2+, were used as inorganic component. The results showed that PEL3/Cu3(PO4)2 hybrid nanoflowers presented the highest relative activity with 2.5-fold increase, compared to the free PEL3. X-ray diffraction analysis confirmed that the composition of PEL3/Cu3(PO4)2 hybrid nanoflowers were pectate lyase PEL3 and Cu3(PO4)2⋅5H2O. The optimum temperature and pH of PEL3/Cu3(PO4)2 hybrid nanoflowers were ascertained to be 55°C and pH 9.0, respectively, exhibiting subtle difference from the free PEL3. However, the PEL3/Cu3(PO4)2 hybrid nanoflowers maintained 33% residual activity after 24 h incubation at 55°C, while the free PEL3 completely lost its activity after 18 h incubation at 55°C. Furthermore, over 50% residual activity of the PEL3/Cu3(PO4)2 hybrid nanoflowers was remained, even after four times of repetitive utilization, demonstrating its promising stability for practical application.
New Insights From Imputed Whole-Genome Sequence-Based Genome-Wide Association Analysis and Transcriptome Analysis: The Genetic Mechanisms Underlying Residual Feed Intake in Chickens

Poultry feed constitutes the largest cost in poultry production, estimated to be up to 70% of the total cost. Moreover, there is pressure on the poultry industry to increase production to meet the protein demand of humans and simultaneously reduce emissions to protect the environment. Therefore, improving feed efficiency plays an important role to improve profits and the environmental footprint in broiler production. In this study, using imputed whole-genome sequencing data, genome-wide association analysis (GWAS) was performed to identify single-nucleotide polymorphisms (SNPs) and genes associated with residual feed intake (RFI) and its component traits. Furthermore, a transcriptomic analysis between the high-RFI and the low-RFI groups was performed to validate the candidate genes from GWAS. The results showed that the heritability estimates of average daily gain (ADG), average daily feed intake (ADFI), and RFI were 0.29 (0.004), 0.37 (0.005), and 0.38 (0.004), respectively. Using imputed sequence-based GWAS, we identified seven significant SNPs and five candidate genes [MTSS I-BAR domain containing 1, folliculin, COP9 signalosome subunit 3, 5′,3′-nucleotidase (mitochondrial), and gametocyte-specific factor 1] associated with RFI, 20 significant SNPs and one candidate gene (inositol polyphosphate multikinase) associated with ADG, and one significant SNP and one candidate gene (coatomer protein complex subunit alpha) associated with ADFI. After performing a transcriptomic analysis between the high-RFI and the low-RFI groups, both 38 up-regulated and 26 down-regulated genes were identified in the high-RFI group. Furthermore, integrating regional conditional GWAS and transcriptome analysis, ras-related dexamethasone induced 1 was the only overlapped gene associated with RFI, which also suggested that the region (GGA14: 4767015–4882318) is a new quantitative trait locus associated with RFI. In conclusion, using imputed sequence-based GWAS is an efficient method to identify significant SNPs and candidate genes in chicken. Our results provide valuable insights into the genetic mechanisms of RFI and its component traits, which would further improve the genetic gain of feed efficiency rapidly and cost-effectively in the context of marker-assisted breeding selection.
Non-linear Thermo-Optical Properties of MoS2 Nanoflakes by Means of the Z-Scan Technique

The non-linear thermo-optical response of MoS2 nanoflakes was investigated using the Z-scan technique, employing TM00-mode with a CW-laser diode operating at a wavelength of 532 nm. The systems were found to display a strong non-linear response, dominated by non-linear refraction. The effect of the thickness of the MoS2 layer, deposited on a glass substrate, on the non-linear susceptibility was studied. Furthermore, in this study, the effects of modifying the thickness of the MoS2 nanoflakes on the non-linear optical phenomena, such as self-focusing and self-defocusing was investigated for the first time. In all cases, the non-linear absorption and refraction were determined. The corresponding third-order susceptibilities and second-order hyperpolarizability were calculated to be as large as 10–7 (esu) and 10–32 (esu), under laser excitation, respectively. Showing large third-order optical non-linearity suggests the potential of the MoS2 nanoflakes in photonics applications.
Suppressor of Gamma Response 1 Modulates the DNA Damage Response and Oxidative Stress Response in Leaves of Cadmium-Exposed Arabidopsis thaliana

Cadmium (Cd) exposure causes an oxidative challenge and inhibits cell cycle progression, ultimately impacting plant growth. Stress-induced effects on the cell cycle are often a consequence of activation of the DNA damage response (DDR). The main aim of this study was to investigate the role of the transcription factor SUPPRESSOR OF GAMMA RESPONSE 1 (SOG1) and three downstream cyclin-dependent kinase inhibitors of the SIAMESE-RELATED (SMR) family in the Cd-induced DDR and oxidative challenge in leaves of Arabidopsis thaliana. Effects of Cd on plant growth, cell cycle regulation and the expression of DDR genes were highly similar between the wildtype and smr4/5/7 mutant. In contrast, sog1-7 mutant leaves displayed a much lower Cd sensitivity within the experimental time-frame and significantly less pronounced upregulations of DDR-related genes, indicating the involvement of SOG1 in the Cd-induced DDR. Cadmium-induced responses related to the oxidative challenge were disturbed in the sog1-7 mutant, as indicated by delayed Cd-induced increases of hydrogen peroxide and glutathione concentrations and lower upregulations of oxidative stress-related genes. In conclusion, our results attribute a novel role to SOG1 in regulating the oxidative stress response and connect oxidative stress to the DDR in Cd-exposed plants.
Changed Patterns of Genomic Variation Following Recent Domestication: Selection Sweeps in Farmed Atlantic Salmon

The introduction of wild Atlantic salmon into captivity, and their subsequent artificial selection for production traits, has caused phenotypic differences between domesticated fish and their wild counterparts. Identification of regions of the genome underling these changes offers the promise of characterizing the early biological consequences of domestication. In the current study, we sequenced a population of farmed European Atlantic salmon and compared the observed patterns of SNP variation to those found in conspecific wild populations. This identified 139 genomic regions that contained significantly elevated SNP homozygosity in farmed fish when compared to their wild counterparts. The most extreme was adjacent to versican, a gene involved in control of neural crest cell migration. To control for false positive signals, a second and independent dataset of farmed and wild European Atlantic salmon was assessed using the same methodology. A total of 81 outlier regions detected in the first dataset showed significantly reduced homozygosity within the second one, strongly suggesting the genomic regions identified are enriched for true selection sweeps. Examination of the associated genes identified a number previously characterized as targets of selection in other domestic species and that have roles in development, behavior and olfactory system. These include arcvf, sema6, errb4, id2-like, and 6n1-like genes. Finally, we searched for evidence of parallel sweeps using a farmed population of North American origin. This failed to detect a convincing overlap to the putative sweeps present in European populations, suggesting the factors that drive patterns of variation under domestication and early artificial selection were largely independent. This is the first analysis on domestication of aquaculture species exploiting whole-genome sequence data and resulted in the identification of sweeps common to multiple independent populations of farmed European Atlantic salmon.
Impact of Hypoventilation Training on Muscle Oxygenation, Myoelectrical Changes, Systemic [K+], and Repeated-Sprint Ability in Basketball Players

This study investigated the impact of repeated-sprint (RS) training with voluntary hypoventilation at low lung volume (VHL) on RS ability (RSA) and on performance in a 30-15 intermittent fitness test (30-15IFT). Over 4 weeks, 17 basketball players included eight sessions of straight-line running RS and RS with changes of direction into their usual training, performed either with normal breathing (CTL, n = 8) or with VHL (n = 9). Before and after the training, athletes completed a RSA test (12 × 30-m, 25-s rest) and a 30-15IFT. During the RSA test, the fastest sprint (RSAbest), time-based percentage decrement score (RSASdec), total electromyographic intensity (RMS), and spectrum frequency (MPF) of the biceps femoris and gastrocnemius muscles, and biceps femoris NIRS-derived oxygenation were assessed for every sprint. A capillary blood sample was also taken after the last sprint to analyse metabolic and ionic markers. Cohen's effect sizes (ES) were used to compare group differences. Compared with CTL, VHL did not clearly modify RSAbest, but likely lowered RSASdec (VHL: −24.5% vs. CTL: −5.9%, group difference: −19.8%, ES −0.44). VHL also lowered the maximal deoxygenation induced by sprints ([HHb]max; group difference: −2.9%, ES −0.72) and enhanced the reoxygenation during recovery periods ([HHb]min; group difference: −3.6%, ES −1.00). VHL increased RMS (group difference: 18.2%, ES 1.28) and maintained MPF toward higher frequencies (group difference: 9.8 ± 5.0%, ES 1.40). These changes were concomitant with a lower potassium (K+) concentration (group difference: −17.5%, ES −0.67), and the lowering in [K+] was largely correlated with RSASdec post-training in VHL only (r = 0.66, p < 0.05). However, VHL did not clearly alter PO2, hemoglobin, lactate and bicarbonate concentration and base excess. There was no difference between group velocity gains for the 30-15IFT (CTL: 6.9% vs. VHL: 7.5%, ES 0.07). These results indicate that RS training combined with VHL may improve RSA, which could be relevant to basketball player success. This gain may be attributed to greater muscle reoxygenation, enhanced muscle recruitment strategies, and improved K+ regulation to attenuate the development of muscle fatigue, especially in type-II muscle fibers.
Alzheimer's Patient Organizations' Role in Enabling Citizenship Projects: A Comparison of the USA, Germany, and the UK

This paper examines how Alzheimer's disease (AD) patient support organizations (POs) located in diverse healthcare regimes enable patients to claim and construct their rights as citizens. Since citizenship rights of people with AD are debated widely, it is important to recognize the role of POs in enabling people to construct citizenship identities. This paper thus examines the factors that shape the citizenship projects of the AD POs. Since collective health-related behavior changes in line with national differences, we compare the biggest AD POs in three starkly distinct healthcare regimes: the Alzheimer's Association in the US (ALZ), the Deutsche Alzheimer Gesellschaft (German Alzheimer's Association) in Germany (DAG), and Alzheimer's Society in the UK (AS), to examine how distinct health policy contexts shape their citizenship projects. Based on our website analysis of the three POs and other related secondary documents, we argue that the way each POs work toward enabling its members to claim rights and assume responsibilities depend upon the nature of healthcare funding and resource allocation for AD care. Since AD involves long-term care, the ways in which the three POs enable the people with AD to secure their care expenses set apart the nature of citizenships enactments.
GooDBye: a Good Graph Database Benchmark - an Industry Experience

This paper reports a use-case developed for an international IT company, whose one of multiple branches is located in Poland. In order to deploy a graph database in their IT architecture, the company needed an assessment of some of the most popular graph database management systems to select one that fits their needs. Despite the fact that multiple graph database benchmarks have been proposed so far, they do not cover all use-cases required by industry. This problem was faced by the company. A specific structure of graphs used by the company and specific queries, initiated developing a new graph benchmark, tailored to their needs. With this respect, the benchmark that we developed complements the existing benchmarks with 5 real use-cases. Based on the benchmark, 5 open-source graph database management systems were evaluated experimentally. In this paper we present the benchmark and the experimental results.
Stable EEG Biometrics Using Convolutional Neural Networks and Functional Connectivity

Despite some positive results, research on electroencephalography (EEG) biometrics is still in an exploratory phase. The sensitivity of EEG to physical and mental states leads to considerable intra-individual variations that can have a serious negative impact on biometric performance. One open question is the stability of EEG biometrics in relation to the consistency of performance across diverse human states. This paper investigates the idea of using functional connectivity (FC) and convolutional neural networks (CNN) for stable EEG biometrics. Speciﬁcally, the proposed learning model consists of two modules: an FC module which is designed to capture dynamic coupling relationships between brain regions, providing a bivariate measurement that is more stable than current methods relying on univariate signals or features extracted from single channels; and a CNN module to automatically learn inherent FC representations that exhibit unique patterns to each individual. The fusion of FC and CNN provides eﬀective biometric identiﬁers and strong discriminatory power that relaxes the reliance of current methods on human states or sensory stimulation. Evaluation of the model uses ongoing EEG in diﬀerent human states and both the identiﬁcation and authentication scenarios. Results validate the eﬀectiveness of the model in learning identity-bearing information from EEG in both biometric scenarios. Compared to current methods, the improvement brought by the proposed learning model is clear, especially in handling EEG signals in diverse states.