Miracle-dz/UniFAR-FTUs huggingface dataset:
The Acoustic Dimension of Reading: Does Musical Aptitude Affect Silent Reading Fluency?

Fluent reading in a foreign language includes a complex coordination process of visual and auditory nature as the reading brain transforms written symbols into speaking auditory patterns through subvocalization (inner voice). The auditory information activated for reading involves the projection of speech prosody and allows, beyond letters and words decoding, the recognition of word boundaries and the construction of the melodic contours of the phrase. On the one hand, phonological awareness and auditory working memory have been identified in the literature as relevant factors in the reading process as skilled readers keep the acoustic information in their auditory working memory to predict the construction of larger lexical units. On the other hand, we observed that the inclusion of musical aptitude as an element belonging to the acoustic dimension of the silent reading aptitude of adults learning a foreign language remains understudied. Therefore, this study examines the silent reading fluency of 117 Italian adult students of Spanish as a foreign language. Our main aim was to find a model that could show if linguistic, cognitive and musical skills influence adults’ silent reading fluency. We hypothesized that learners’ contextual word recognition ability in L1 and FL in addition to, phonological awareness, auditory working memory and musical aptitude, elements related to the acoustic dimension of reading, would influence adults’ silent reading fluency. Our structural modeling allows us to describe how these different variables interact to determine the silent reading fluency construct. In fact, the effect of musical aptitude on fluent silent reading in our model reveals to be stronger than phonological awareness or auditory working memory.
Animal and Clinical Studies Evaluating Blood Glucose Control With Palatinose-Based Alternative Sweeteners

Animal and clinical studies were performed to determine whether Palatinose-based alternative sweeteners with increased sweetness contributed to blood glucose elevations. In the animal study, male Sprague-Dawley rats (6 weeks old) received an oral load of 2 g of glucose or Palatinose-based alternative sweeteners per kilogram of body weight. Thirty minutes after the glucose load, the rat blood glucose levels in the Palatinose-based alternative sweetener groups were significantly lower than those in the glucose groups (p < 0.05). Palatinose-based alternative sweeteners significantly improved glucose tolerance in rats. However, significant differences in the blood glucose levels were not observed among the Palatinose-based alternative sweeteners. In the clinical study, 14 healthy volunteers (21.4 ± 1.3 years) consumed glucose or Palatinose-based alternative sweeteners (50 g). At 60 min, when Palatinose-based alternative sweeteners were ingested, blood glucose was significantly lower compared to when glucose was ingested (Palatinose-L, 123.1 mg/dL; Palatinose-IS, 125.9 mg/dL; Palatinose-FOS. 129.1 mg/dL vs. glucose, 154.8 mg/dL, p < 0.05). The glycaemic index of Palatinose-L, Palatinose-IS and Palatinose-FOS was 43.9, 58.1, and 49.2, respectively. Palatinose-based alternative sweeteners could help maintain health as the postprandial blood glucose levels are constantly maintained owing to slow hydrolysis.
Macrophage Subsets in Obesity, Aligning the Liver and Adipose Tissue

The increasing prevalence of obesity is accompanied by a rising incidence in metabolic syndrome and related pathologies such as non-alcoholic fatty liver disease. Macrophages are hypothesized to play central roles in these diseases, through their role as inflammatory mediators and as such are thought to be potential targets for future therapies. Recently, single cell technologies have revealed significant heterogeneity within the macrophage pool in both liver and adipose tissue in obesity. Thus current efforts are focused on dissecting this heterogeneity and understanding the distinct functions of the individual subsets. In this review, we discuss the current knowledge regarding macrophage heterogeneity, ontogeny and functions in the context of obese adipose tissue and fatty liver disease and attempt to align the distinct populations described to date.
The Prognostic Value of Anticholinergic Burden Measures in Relation to Mortality in Older Individuals: A Systematic Review and Meta-Analysis

Background Greater anticholinergic burden (ACB) increases the risk of mortality in older individuals, yet the strength of this association varies between studies. One possible explanation for this variance is the use of different approaches to quantify ACB. This systematic review (PROSPERO number CRD42019115918) assessed the prognostic utility of ACB-specific measures on mortality in older individuals. Methods Multiple cross-disciplinary databases were searched from 2006–2018. Observational studies assessing the association between ACB and mortality utilizing ≥1 ACB measure, involving persons aged ≥65 years were included. Screening and data extraction were performed by two independent reviewers, with disagreements resolved by a third independent reviewer. Risk of bias and quality of evidence were assessed using Quality in Prognosis Studies (QUIPS) and Grading of Recommendations, Assessment, Development, and Evaluations (GRADE) criteria. Meta-analysis was conducted where appropriate. Results Of 19,224 titles, 20 articles describing 18 cohort studies involving 498,056 older individuals were eligible. Eight anticholinergic-specific measures were identified; the Anticholinergic Cognitive Burden Scale (ACBS, n=9) and Anticholinergic Risk scale (ARS, n=8) were most frequently reported. The evidence base was of poor quality, with moderate to high risk of bias. Meta-analysis showed increased mortality risk. Conclusions There was a modest association between some ACB measures and mortality, with most evidence derived from the ACBS. Studies comparing different measures within the same population were lacking. Analysis was limited by poor generalizability between studies, specifically regarding heterogeneity in methodology and reporting, as well as high risk of bias for most studies in the evidence base.
Integrated miRNAome and Transcriptome Analysis Reveals Argonaute 2-Mediated Defense Responses Against the Devastating Phytopathogen Sclerotinia sclerotiorum

Argonaute 2 (AGO2)-mediated role in plant defense against fungal pathogens remains largely unknown. In this study, integrated miRNAome and transcriptome analysis employing ago2 mutant was performed to reveal AGO2-associated miRNAs and defense responses against the devastating necrotrophic phytopathogen Sclerotinia sclerotiorum. Both miRNAome and transcriptomes of S. sclerotiorum-inoculated ago2-1 mutant (ago2-Ss) and wild-type (WT-Ss) as well as mock-inoculated ago2-1 mutant (ago2) and wild-type (WT) Arabidopsis plants, were analyzed by sRNA and mRNA deep sequencing. Differentially expressed genes (DEGs) and differentially expressed miRNAs (DEMs) of the comparisons WT-Ss/WT, ago2/WT, ago2-Ss/WT-Ss, and ago2-Ss/ago2 were identified. Furthermore, integration analysis for the DEMs and DEGs identified over 40 potential AGO2-dependent Sclerotinia sclerotiorum-responsive (ATSR) DEM-DEG pairs involving modulation of immune recognition, calcium flux, redox homeostasis, hormone accumulation and signaling, cell wall modification and metal ion homeostasis. Data-mining result indicated that most of the DEMs were bound with AGO2. Moreover, Arabidopsis mutant analysis demonstrated that three ROS and redox homeostatasis related DEGs of identified DEM-DEG pairs, GSTU2, GSTU5, and RBOHF contributed to the AGO2-mediated defense against S. sclerotiorum. This work provides genome-wide prediction of miRNA–target gene pairs that are potentially associated with the AGO2-dependent resistance against S. sclerotiorum.
microRNA Expression in Women With and Without Polycystic Ovarian Syndrome Matched for Body Mass Index

Background: Despite several authors who have hypothesized that alterations of small noncoding RNAs (miR) are implicated in the etiopathogenesis of polycystic ovarian syndrome (PCOS), contrasting findings have been reported so far. Discrepancies in body mass index (BMI) levels may account for these differences; therefore, the aim of the present study was to determine whether miR differed in serum samples collected from age- and BMI-matched control and PCOS women. Methods: In a cross-sectional study, miR were measured using quantitative polymerase chain reaction in 29 women with anovulatory PCOS women and 29 control women who were in the follicular phase of their menstrual cycle, from the local biobank. Results: One hundred seventy-six miR were detected, of which 15 miR passed the false discovery rate (FDR; p < 0.05) that differed between PCOS and control women. There was no association of the top 9 miR (p < 0.02) (miR-486-5p, miR-24-3p, miR-19b-3p, miR-22-3p, miR-19a-3p, miR-339-5p, miR-185-5p, miR-101-3p, miR-let-7i-5p) with BMI, androgen levels, insulin resistance, or antimullerian hormone (AMH) in either PCOS or normal women. Ingenuity pathway assessment showed the pathways were interrelated for abnormalities of the reproductive system. Conclusion: When the confounding influence of weight was accounted for, miR levels differed between anovulatory PCOS women and control women in the follicular phase of the menstrual cycle. Interestingly, the differing miR were associated with the pathways of reproductive abnormalities but did not associate with AMH or metabolic parameters.
Exploring the Application of Pattern Recognition and Machine Learning for Identifying Movement Phenotypes During Deep Squat and Hurdle Step Movements

Background Movement screens are increasingly used in sport and rehabilitation to evaluate movement competency. However, common screens are often evaluated using subjective visual detection of a priori prescribed discrete movement features (e.g., spine angle at maximum squat depth) and may not account for whole-body movement coordination, or associations between different discrete features. Objective To apply pattern recognition and machine learning techniques to identify whole-body movement pattern phenotypes during the performance of exemplar functional movement screening tasks; the deep squat and hurdle step. Additionally, we also aimed to compare how discrete kinematic measures, commonly used to score movement competency, differed between emergent groups identified via pattern recognition and machine learning. Methods Principal component analysis (PCA) was applied to 3-dimensional (3D) trajectory data from participant’s deep squat (DS) and hurdle step performance, identifying emerging features that describe orthogonal modes of inter-trial variance in the data. A gaussian mixture model (GMM) was fit and used to cluster the principal component scores as an unsupervised machine learning approach to identify emergent movement phenotypes. Between group features were analyzed using a one-way ANOVA to determine if the objective classifications were significantly different from one another. Results Three clusters (i.e., phenotypes) emerged for the DS and right hurdle step (RHS) and 4 phenotypes emerged for the left hurdle step (LHS). Selected discrete points commonly used to score DS and hurdle step movements were different between emergent groups. In regard to the select discrete kinematic measures, 4 out of 5, 7 out of 7 and 4 out of 7, demonstrated a main effect (p < 0.05) between phenotypes for the DS, RHS, and LHS respectively. Conclusion Findings support that whole-body movement analysis, pattern recognition and machine learning techniques can objectively identify movement behavior phenotypes without the need to a priori prescribe movement features. However, we also highlight important considerations that can influence outcomes when using machine learning for this purpose.
Renal Effects of Fetal Reprogramming With Pentaerythritol Tetranitrate in Spontaneously Hypertensive Rats

Aims Current antihypertensive therapies cannot cure hypertension and a life-long medication is necessary. Maternal treatment may represent a promising strategy for hypertension treatment. We have previously shown that maternal treatment of spontaneously hypertensive rats (SHR) with pentaerythritol tetranitrate (PETN) leads to a persistent blood pressure reduction in the female offspring. The underlying mechanisms include improved endothelial function resulting from long-lasting epigenetic changes. In the present study, we address the renal effects of maternal PETN treatment. Methods and Results F0 parental SHR were fed with either normal chow or PETN-containing (1 g/kg) chow ad libitum from the time point of mating to the end of lactation period. The F1 offspring received normal chow without PETN from the time point of weaning (at the age of 3 weeks). At the age of 16 weeks, female PETN offspring showed lower blood pressure than the control. No difference was observed in male offspring. All following experiments were performed with kidneys from 16-week-old female offspring. Maternal PETN treatment reduced the mRNA and protein expression of angiotensin-converting enzyme (ACE) and basic fibroblast growth factor (FGF2), resulting from epigenetic modifications found at the proximal promoter regions. The expression levels of mineralocorticoid receptor (MR) and factors in the MR signalling pathway (Rac1 and Sgk1) were also reduced by PETN. Major profibrotic cytokines, including Wnt4, TNF-alpha, TGF-beta, and MMP9, were downregulated by PETN, which was associated with reduced collagen deposition and glomerulus sclerosis in the kidney of PETN offspring. In addition, PETN treatment also decreased the markers of inflammation and immune cell infiltration in the kidneys. Conclusions PETN maternal treatment leads to epigenetic changes in the kidney of female SHR offspring. The reduced renal inflammation, alleviated kidney fibrosis, and decreased MR signalling are potential mechanisms contributing to the observed blood pressure-lowering effect.
Methane Decomposition Over ZrO2-Supported Fe and Fe–Ni Catalysts—Effects of Doping La2O3 and WO3

A leading method for hydrogen production that is free of carbon oxides is catalytic methane decomposition. In this research, Fe and Fe–Ni supported catalysts prepared by the wet impregnation method were used in methane decomposition. The effects of doping the parent support (ZrO2) with La2O3 and WO3 were studied. It was discovered that the support doped with La2O3 gave the best performance in terms of CH4 conversion, H2 yield, and stability at the test condition, 800°C and 4,000-ml h−1 g−1 cat. space velocity. The addition of Ni significantly improved the performance of all the monometallic catalysts. The catalysts were characterized by X-ray diffraction (XRD), Brunauer–Emmett–Teller (BET), temperature-programmed reduction/oxidation (TPR/TPO), thermogravimetric analyzer (TGA), and microscopy (SEM and Raman) techniques. Phases of the different forms of Fe were identified by XRD. BET showed a drastic decline in the specific surface area of the catalysts with respect to the supports. TPR profiles revealed a progressive change in the valency of Fe in its combined form to the zero valence-free metal. The La2O3-promoted support gave the best performance and maintained good stability during the time on stream.
Exploring a Highly D-Galactose Specific L-Arabinose Isomerase From Bifidobacterium adolescentis for D-Tagatose Production

D-Galactose-specific L-arabinose isomerase (L-AI) would have much potential for the enzymatic conversion of D-Galactose into D-tagatose, while most of the reported L-AIs are L-arabinose specific. This study explored a highly D-Galactose-specific L-AI from Bifidobacterium adolescentis (BAAI) for the production of D-tagatose. In the comparative protein-substrate docking for D-Galactose and L-arabinose, BAAI showed higher numbers of hydrogen bonds in D-Galactose-BAAI bonding site than those found in L-arabinose-BAAI bonding site. The activity of BAAI was 24.47 U/mg, and it showed good stability at temperatures up to 65°C and a pH range 6.0–7.5. The Km, Vmax, and Kcat/Km of BAAI were found to be 22.4 mM, 489 U/mg and 9.3 mM–1 min–1, respectively for D-Galactose, while the respective values for L-arabinose were 40.2 mM, 275.1 U/mg, and 8.6 mM–1 min–1. Enzymatic conversion of D-Galactose into D-tagatose by BAAI showed 56.7% conversion efficiency at 55°C and pH 6.5 after 10 h.
Identification of Immune Cell Landscape and Construction of a Novel Diagnostic Nomogram for Crohn’s Disease

Crohn’s disease (CD) has an increasing incidence and prevalence worldwide. The etiology of CD remains unclear and there is no gold standard for diagnosis. The dysregulated immune response and different infiltration status of immune cells are critical for CD pathogenesis; therefore, it is important to provide an overview of immune-cell alterations in CD and explore a novel method for auxiliary diagnosis. Here we analyzed microarray datasets from Gene Expression Omnibus (GEO), and an extended version of Cell-type Identification By Estimating Relative Subsets Of RNA Transcripts (CIBERSORTx) was utilized to estimate the fraction of 22 types of immune cells. Differentially expressed genes (DEGs) and a protein-protein interaction (PPI) network were identified, and we performed gene set enrichment analysis (GSEA) and gene set variation analysis (GSVA) to identify differentially regulated pathways in CD. Least absolute shrinkage and selection operator (LASSO) regression was conducted to filter features, and a diagnostic nomogram based on logistic regression was built and validated in an independent validation cohort. In the derivation cohort, we found a proportion of 17 immune-cell types to be significantly altered between CD and healthy controls and a total of 150 DEGs were identified, which were mostly related to the immune response. Among the 15 hub genes based on the PPI network, C-X-C chemokine ligand 8 (CXCL8) and interleukin-1B (IL-1B) showed the highest degree of interaction. Additionally, GSEA and GSVA identified five significantly enriched pathways, among which the nucleotide-binding oligomerization domain (NOD)-like receptor signaling pathway was critical in the CD development. Furthermore, six variables comprising of CXCL8, IL-1B, M1 macrophages, regulatory T cells, CD8+ T cells, and plasma cells were identified by LASSO regression and incorporated into a logistic regression model. The nomogram displayed a good prediction, with a 0.915 area under the receiver operating curve (AUC) and a C-index of 0.915 [95% confidence interval (CI): 0.875–0.955]. Similar results were found in the validation cohort, with an AUC of 0.884 and a 0.884 C-index (95% CI: 0.843–0.924). These results provide novel in silico insight into cellular and molecular characteristics of CD and potential biomarkers for diagnosis and targeted therapy.
FoodKG: A Tool to Enrich Knowledge Graphs Using Machine Learning Techniques

While there exist a plethora of datasets on the Internet related to Food, Energy, and Water (FEW), there is a real lack of reliable methods and tools that can consume these resources. This hinders the development of novel decision-making applications utilizing knowledge graphs. In this paper, we introduce a novel software tool, called FoodKG, that enriches FEW knowledge graphs using advanced machine learning techniques. Our overarching goal is to improve decision-making and knowledge discovery as well as to provide improved search results for data scientists in the FEW domains. Given an input knowledge graph (constructed on raw FEW datasets), FoodKG enriches it with semantically related triples, relations, and images based on the original dataset terms and classes. FoodKG employs an existing graph embedding technique trained on a controlled vocabulary called AGROVOC, which is published by the Food and Agriculture Organization of the United Nations. AGROVOC includes terms and classes in the agriculture and food domains. As a result, FoodKG can enhance knowledge graphs with semantic similarity scores and relations between different classes, classify the existing entities, and allow FEW experts and researchers to use scientific terms for describing FEW concepts. The resulting model obtained after training on AGROVOC was evaluated against the state-of-the-art word embedding and knowledge graph embedding models that were trained on the same dataset. We observed that this model outperformed its competitors based on the Spearman Correlation Coefficient score.
Autoxidation of Cholesterol and Behavior of Its Hydroperoxide in Aqueous Medium

A model reaction was studied for the interaction between cholesterol (1) and molecular oxygen in biological matrices. An aqueous colloidal solution (60 ml) of 1 (2.7×10-4 mol) dispersed with sodium stearate (1.8×10-4 mol) was adjusted to pH 8 and energetically stirred at 85° without air-bubbling. Relative amounts of the sterols present in the reaction mixtures were determined every one hour by quantitative TLC and time-course of the oxyfunctionalization of 1 was followed for 9 hours. The major product in the early period was the 7-hydroperoxide (2) as an epimeric mixture of α : β≒1 : 2. The amounts of the 7-ketone (3) and 7-hydroxide (4) increased with decrease in that of 2 which was regarded as the intermediate. After passage of 7 hours the autoxidation system arrived at an apparent final state where consumption of 1 and formation of products were suspended and 2 was no longer detectable. More than 70% of 1 was likely to be consumed and the relative amounts of the oxygenated products (3, 4, and the 5, 6-epoxide) and the unchanged substrate (1) were in an approximate ratio of 45 : 25 : 5 : 25. The induction period was lost when a small amount (1×10-5 mol) of the 7α-hydroperoxide (2a) was initially present in the reaction mixture. From these results, the autoxidation of 1 under the conditions was assumed to have an ordinary pattern of the chain reaction initiated by the decomposition of hydroperoxide.
THE MEANING OF OSTEOPOROSIS IN THE LIVES OF RURAL OLDER WOMEN

Twenty-one older women living in three rural communities participated in focus groups to explore the functional and psychosocial consequences of living with osteoporosis. The increased risk of fracture and daily pain associated with the disease frequently precluded or interfered with the completion of daily activities for these women. Those living on farms faced the additional challenge of avoiding the risk of falls while continuing to do the physical labor necessary to maintain their rural lifestyle. Many of the women turned to their spouses or other family members for assistance with daily tasks, forcing the women to relinquish their own caregiver roles. The disease caused many of the women to reassess their own selfconcept and decrease their participation in valued social activities. Maintaining independence was an ongoing concern.