Miracle-dz/UniFAR-FTUs huggingface dataset:
Biological, Chemical, and Nutritional Food Risks and Food Safety Issues From Italian Online Information Sources: Web Monitoring, Content Analysis, and Data Visualization

Background With rapid evolution of the internet and web 2.0 apps, online sources have become one of the main channels for most people to seek food risk information. Thus, it would be compelling to analyze the coverage of online information sources related to biological, chemical, and nutritional food risks, and related safety issues, to understand the type of content that online readers are exposed to, possibly influencing their perceptions. Objective The aim of this study was to identify the types of online sources that are predominantly covering this theme, and the topics that have received the most attention in terms of coverage and engagement on social media. Methods We performed an analysis of big data related to food risks by combining web monitoring techniques, content analysis, and data visualization of a large amount of unstructured text. Using a dictionary-based approach, a web monitoring app was instructed to automatically collect web content referring to the food risk and safety field. Data were retrieved from March 2017 to February 2018. The validated corpus (N=12,163) was subject to automatic and manual content analysis. Results were combined with descriptive statistics extracted from Web-Live and processed with Qlik Sense. Results Nutritional risks and news about outbreaks, controls, and alerts were the most widely covered topics. Thematic sources devoted major attention to nutritional topics, whereas national sources covered food risks, especially during food emergencies. Regarding engagement on social media, readers’ interest was higher for nutritional topics and animal welfare. Although traditional sources still publish a great amount of content related to food risks and safety, new mediators have emerged as alternative sources for food risk information. Conclusions This mixed methodological approach was demonstrated to be a useful means for obtaining an accurate characterization of the online discourse on food risks, and can provide insight into how the monitored sources contribute to the process of risk communication.
Medical application of biomimetic 4D printing

Abstract Additive manufacturing has attracted a lot of attention in fabrication of bio medical devices and structures in recent years. 4D printing, a new class of 3D printing where time is considered as a 4th dimension, allows us to build biological structures such as scaffolds, implants, and stents with dynamic performance mimicking the body's natural tissues. In order to properly exploit the capabilities of this fabrication method, understanding and exploiting the shape memory materials is critical. These ‘smart’ materials are responsive to the external stimuli which eliminates the need for utilizing the sensors, and batteries. These stimuli-triggered ‘smart’ materials possess a dynamic behavior unlike the static scaffolds based on conventional manufacturing techniques. In this review, recent advances on application of 4D printing for manufacturing of this type of materials and other high-performance biomaterials for medical applications have been discussed.
Gut Colonization Mechanisms of Lactobacillus and Bifidobacterium: An Argument for Personalized Designs.

Lactobacillus and Bifidobacterium spp. are best understood for their applications as probiotics, which are often transient, but as commensals it is probable that stable colonization in the gut is important for their beneficial roles. Recent research suggests that the establishment and persistence of strains of Lactobacillus and Bifidobacterium in the gut are species- and strain-specific and affected by natural history, genomic adaptability, and metabolic interactions of the bacteria and the microbiome and immune aspects of the host but also regulated by diet. This provides new perspectives on the underlying molecular mechanisms. With an emphasis on host-microbe interaction, this review outlines how the characteristics of individual Lactobacillus and Bifidobacterium bacteria, the host genotype and microbiome structure, diet, and host-microbe coadaptation during bacterial gut transition determine and influence the colonization process. The diet-tuned and personally tailored colonization can be achieved via a machine learning prediction model proposed here. Expected final online publication date for the Annual Review of Food Science and Technology, Volume 12 is March 2021. Please see http://www.annualreviews. org/page/journal/pubdates for revised estimates.
Protocol on a multicentre statistical and economic modelling study of risk-based stratified and personalised screening for diabetes and its complications in India (SMART India)

Introduction The aim of this study is to develop practical and affordable models to (a) diagnose people with diabetes and prediabetes and (b) identify those at risk of diabetes complications so that these models can be applied to the population in low-income and middle-income countries (LMIC) where laboratory tests are unaffordable. Methods and analysis This statistical and economic modelling study will be done on at least 48 000 prospectively recruited participants aged 40 years or above through community screening across 20 predefined regions in India. Each participant will be tested for capillary random blood glucose (RBG) and complete a detailed health-related questionnaire. People with known diabetes and all participants with predefined levels of RBG will undergo further tests, including point-of-care (POC) glycated haemoglobin (HbA1c), POC lipid profile and POC urine test for microalbuminuria, retinal photography using non-mydriatic hand-held retinal camera, visual acuity assessment in both eyes and complete quality of life questionnaires. The primary aim of the study is to develop a model and assess its diagnostic performance to predict HbA1c diagnosed diabetes from simple tests that can be applied in resource-limited settings; secondary outcomes include RBG cut-off for definition of prediabetes, diagnostic accuracy of cost-effective risk stratification models for diabetic retinopathy and models for identifying those at risk of complications of diabetes. Diagnostic accuracy inter-tests agreement, statistical and economic modelling will be performed, accounting for clustering effects. Ethics and dissemination The Indian Council of Medical Research/Health Ministry Screening Committee (HMSC/2018–0494 dated 17 December 2018 and institutional ethics committees of all the participating institutions approved the study. Results will be published in peer-reviewed journals and will be presented at national and international conferences. Trial registration number ISRCTN57962668 V1.0 24/09/2018.
Missing value imputation in proximity extension assay-based targeted proteomics data

Targeted proteomics utilizing antibody-based proximity extension assays provides sensitive and highly specific quantifications of plasma protein levels. Multivariate analysis of this data is hampered by frequent missing values (random or left censored), calling for imputation approaches. While appropriate missing-value imputation methods exist, benchmarks of their performance in targeted proteomics data are lacking. Here, we assessed the performance of two methods for imputation of values missing completely at random, the previously top-benchmarked ‘missForest’ and the recently published ‘GSimp’ method. Evaluation was accomplished by comparing imputed with remeasured relative concentrations of 91 inflammation related circulating proteins in 86 samples from a cohort of 645 patients with venous thromboembolism. The median Pearson correlation between imputed and remeasured protein expression values was 69.0% for missForest and 71.6% for GSimp (p = 5.8e-4). Imputation with missForest resulted in stronger reduction of variance compared to GSimp (median relative variance of 25.3% vs. 68.6%, p = 2.4e-16) and undesired larger bias in downstream analyses. Irrespective of the imputation method used, the 91 imputed proteins revealed large variations in imputation accuracy, driven by differences in signal to noise ratio and information overlap between proteins. In summary, GSimp outperformed missForest, while both methods show good overall imputation accuracy with large variations between proteins.
Selection of Resistant Bacteria in Mallards Exposed to Subinhibitory Concentrations of Ciprofloxacin in Their Water Environment

Emergence and selection of antibiotic resistance following exposure to high antibiotic concentrations have been repeatedly shown in clinical and agricultural settings, whereas the role of the weak selective pressures exerted by antibiotic levels below the MIC (sub-MIC) in aquatic environments due to anthropogenic contamination remains unclear. Here, we studied how exposure to sub-MIC levels of ciprofloxacin enriches for Escherichia coli with reduced susceptibility to ciprofloxacin using a mallard colonization model. ABSTRACT Emergence and selection of antibiotic resistance following exposure to high antibiotic concentrations have been repeatedly shown in clinical and agricultural settings, whereas the role of the weak selective pressures exerted by antibiotic levels below the MIC (sub-MIC) in aquatic environments due to anthropogenic contamination remains unclear. Here, we studied how exposure to sub-MIC levels of ciprofloxacin enriches for Escherichia coli with reduced susceptibility to ciprofloxacin using a mallard colonization model. Mallards were inoculated with two isogenic extended-spectrum-β-lactamase (ESBL)-encoding E. coli strains, differing only by a gyrA mutation that results in increased MICs of ciprofloxacin, and exposed to different levels of ciprofloxacin in their swimming water. Changes in the ratios of mutant to parental strains excreted in feces over time and ESBL plasmid spread within the gut microbiota from individual birds were investigated. Results show that in vivo selection of gyrA mutants occurred in mallards during exposure to ciprofloxacin at concentrations previously found in aquatic environments. During colonization, resistance plasmids were readily transferred between strains in the intestines of the mallards, but conjugation frequencies were not affected by ciprofloxacin exposure. Our results highlight the potential for enrichment of resistant bacteria in wildlife and underline the importance of reducing antibiotic pollution in the environment.
Arf1 and Arf6 Synergistically Maintain Survival of T Cells during Activation

Key Points Arf1 and Arf6 are dispensable for cytokine secretion in T cells. Arf1 and Arf6 redundantly protect activated naive T cells from apoptosis. Loss of Arf1 and Arf6 in T cells alleviates autoimmune diseases. ADP-ribosylation factor (Arf) family consisting of six family members, Arf1–Arf6, belongs to Ras superfamily and orchestrates vesicle trafficking under the control of guanine nucleotide exchange factors (GEFs) and GTPase-activating proteins. It is well established that brefeldin A, a potent inhibitor of ArfGEFs, blocks cytokine secretion from activated T cells, suggesting that the Arf pathway plays important roles in T cell functions. In this study, because Arf1 and Arf6 are the best-characterized members among Arf family, we established T lineage–specific Arf1-deficient, Arf6-deficient, and Arf1/6 double-deficient mice to understand physiological roles of the Arf pathway in the immune system. Contrary to our expectation, Arf deficiency had little or no impact on cytokine secretion from the activated T cells. In contrast, the lack of both Arf1 and Arf6, but neither Arf1 nor Arf6 deficiency alone, rendered naive T cells susceptible to apoptosis upon TCR stimulation because of imbalanced expression of Bcl-2 family members. We further demonstrate that Arf1/6 deficiency in T cells alleviates autoimmune diseases like colitis and experimental autoimmune encephalomyelitis, whereas Ab response under Th2-polarizing conditions is seemingly normal. Our findings reveal an unexpected role for the Arf pathway in the survival of T cells during TCR-induced activation and its potential as a therapeutic target in the autoimmune diseases.
Individual and organizational factors associated with evidence-based practice among physical and occupational therapy recent graduates: A cross-sectional national study.

BACKGROUND Occupational therapy (OT) and physical therapy (PT) programs in Canada have moved to graduate-level entry education to address graduates' readiness for evidence-based practice (EBP). Whether rehabilitation professionals with advanced training in EBP are meeting their responsibilities as evidence-based professionals upon entry into practice and the factors that influence the use of evidence is unclear. The aim of this study was to examine the individual and organizational factors associated with the use of EBP and supporting evidence-based activities among graduates of professional OT and PT master's programs. METHODS A cross-sectional design using a survey of recent graduates of the 29 OT and PT programs in Canada. The survey measured six constructs supportive of EBP (ie, knowledge, attitudes, confidence, organizational resources, actual use of EBP, and evidence-based activities). Analyses consisted of descriptive statistics to characterize the sample and the different variables and ordinal multivariate regression analysis. RESULTS 257 graduates (15%) completed the survey. Attitudes towards EBP was positively associated both with evidence-based activities (odds ratio = 1.36 with a 95% CI: 1.22 to 1.52) and use of EBP (odds ratio = 1.23 with a 95% CI: 1.12 to 1.36); greater confidence was related to greater use of EBP (OR = 1.12, 95% CI: 1.01 to 1.24); and working in a private practice setting was found to be related to performing more evidence-based activities (odds ratio = 3.15, 95% CI: 1.40 to 7.12). CONCLUSIONS Despite a greater focus on EBP knowledge in these curricula across Canada, knowledge was not related to EBP use nor evidence-based activities upon entry into practice. On the other hand, attitudes, confidence and working in private practice were. University programs should consider curricular strategies that increase the use of EBP, provide opportunities to engage in evidence-based activities with an emphasis on promoting the development of positive attitudes towards EBP and increasing learners' confidence in their ability to be evidence-based professionals.
Food consumption in Tunisian university students and its association with sociodemographic characteristics and lifestyle behaviours

Abstract Objective: This study aimed to characterise food consumption among students at the University of Carthage (Tunisia), assessing quality of diet and main dietary patterns, and their association with potential conditioning factors. Design: Cross-sectional study. Participants self-reported food consumption in two 24-h recalls and information about sociodemographic, anthropometric and lifestyle characteristics such as BMI, birthplace, physical activity, eating places or kitchen appliances. Mediterranean Diet Score (MDS) and the Nutrient Rich Foods (NRF) index (NRF9.3) were used to assess diet quality. Exploratory factor analysis was conducted to identify eating patterns. Linear regression models were used to test the association of dietary patterns with the diet quality markers. Setting: Students at the University of Carthage, Tunisia. Participants: 132 students Results: Almost 96 % of participants need shifts towards healthier food. Four main food patterns were identified ‘Traditional food’, ‘Transitional food’, ‘European breakfast’ and ‘Western food’. ‘Traditional food’ was the first dietary model, positively associated with MDS and NRF9.3. Women showed higher adherence to ‘European breakfast’ and higher quality of diet by NRF9.3. Students eating out of home showed higher adherence to ‘Western food’, those who never kept a regular schedule of meals consumed lower amount of vegetables and tubers, and sedentary or low active students had a higher intake of ready-to-eat products. Conclusions: Diet quality of the participating Tunisian students is inadequate, but traditional Mediterranean diet remains the main pattern in spite of the advanced transitional nutrition. Some lifestyle risk behaviours affecting quality of diet were identified in this work, which supports the youth’s particular vulnerability.
Aligned N-Doped Carbon Nanotube Bundles Prepared via CVD Using Zeolite Substrates

We report the synthesis of aligned N-doped carbon nanotube bundles via CVD (over the temperature range 700−800 °C) using ammonium-exchanged zeolite-β as the substrate, ferric nitrate as the catalyst, and acetonitrile as the carbon precursor. Ammonium exchange of the zeolite was found to be necessary for the formation of aligned N-doped carbon nanotubes (CNTs). The optimal temperature for the production of large amounts of aligned N-doped CNTs was found to be 750−800 °C. The N-doped CNTs had nitrogen content of between 6 and 9 wt %. The aligned CNTs grew in bundles along the verges, perpendicular to the surface of the hexagonal zeolite-β particles, and retained their aligned order after removal of the zeolite substrate. The length of the CNTs was in the range 2−10 μm depending on CVD temperature, with inner and outer diameters of ca. 10 and 30 nm, respectively. The CNTs exhibited high levels of graphitic ordering and thermal stability in air and had relatively high surface area (226−886 m2/g) and pore volu.
Whole‐genome sequence data of Hypericum perforatum and functional characterization of melatonin biosynthesis by N‐acetylserotonin O‐methyltransferase

Hypericum perforatum is among the most commonly used herbal remedies and supplements. The aerial plant parts are often used to treat depression. Due to the lack of genomic information of H. perforatum, the gene networks regulating secondary metabolite synthesis remain unclear. Here, we present a high‐quality genome for H. perforatum with a 2.3‐Mb scaffold N50. The draft assembly covers 91.9% of the predicted genome and represents the fourth sequenced genus in the order Malpighiales. Comparing this sequence with model or related species revealed that Populus trichocarpa and Hevea brasiliensis could be grouped into one branch, while H. perforatum and Linum usitatissimum are grouped in another branch. Combined with transcriptome data, 40 key genes related to melatonin, hyperforin, and hypericin synthesis were screened and analyzed. Five N‐acetylserotonin O‐methyltransferases (HpASMT1‐HpASMT5) were cloned and functionally characterized. Purified HpASMT3 protein converted N‐acetylserotonin into melatonin with a Vmax of about 1.35 pkat/mg protein. HpASMT1 and HpASMT3 overexpression in Arabidopsis mutants caused 1.5‐2‐fold higher melatonin content than in mutant and wild‐type plants. The endogenous reactive oxygen species (ROS) in transgenic plants was significantly lower than ROS in mutant and wild‐type plants, suggesting higher drought tolerance. The obtained genomic data offer new resources for further study on the evolution of Hypericaceae family, but also provide a basis for further study of melatonin biosynthetic pathways in other plants.
A Second-Generation Fungerp Analog, SCY-247, Shows Potent In Vitro Activity against Candida auris and Other Clinically Relevant Fungal Isolates

Due to the increase of antifungal drug resistance and difficulties associated with drug administration, new antifungal agents for invasive fungal infections are needed. SCY-247 is a second-generation fungerp antifungal compound that interferes with the synthesis of the fungal cell wall polymer β-(1,3)-d-glucan. ABSTRACT Due to the increase of antifungal drug resistance and difficulties associated with drug administration, new antifungal agents for invasive fungal infections are needed. SCY-247 is a second-generation fungerp antifungal compound that interferes with the synthesis of the fungal cell wall polymer β-(1,3)-d-glucan. We conducted an extensive antifungal screen of SCY-247 against yeast and mold strains compared with the parent compound ibrexafungerp (IBX; formerly SCY-078) to evaluate the in vitro antifungal properties of SCY-247. SCY-247 demonstrated similar activity to IBX against all of the organisms tested. Moreover, SCY-247 showed a higher percentage of fungicidal activity against the panel of yeast and mold isolates than IBX. Notably, SCY-247 showed considerable antifungal properties against numerous strains of Candida auris. Additionally, SCY-247 retained its antifungal activity when evaluated in the presence of synthetic urine, indicating that SCY-247 maintains activity and structural stability under environments with decreased pH levels. Finally, a time-kill study showed SCY-247 has potent anti-Candida, -Aspergillus, and -Scedosporium activity. In summary, SCY-247 has potent antifungal activity against various fungal species, indicating that further studies on this fungerp analog are warranted.
Analysis of Binding Affinities for Celecoxib Analogues with COX-1 and COX-2 from Combined Docking and Monte Carlo Simulations and Insight into the COX-2/COX-1 Selectivity

The origins of binding affinity and COX-2/COX-1 selectivity for analogues of celecoxib have been explored using an approach that combines docking with Monte Carlo (MC) simulations. These inhibitors are COX-2-selective nonsteroidal antiinflammatory drugs (NSAIDs) that are of current interest because the gastrointestinal irritation they cause is reduced compared to that caused by traditional NSAIDs. We report a novel docking method, based on a combined Tabu and Monte Carlo protocol, that determines starting conformations for MC simulations. Using the docking-predicted starting conformations, relative changes in binding free energies were computed for methyl, ethyl, hydroxymethyl, hydroxyl, thiomethyl, methoxy, trifluoromethyl, chloro, fluoro, and unsubstituted derivatives with the MC free energy perturbation (FEP) method. The computed free energies are in good accord with IC50 values, and the structural information from the simulations can be used to explain the experimentally observed binding trends. In ad.
ANOVA-HD: Analysis of variance when both input and output layers are high-dimensional

Modern genomic data sets often involve multiple data-layers (e.g., DNA-sequence, gene expression), each of which itself can be high-dimensional. The biological processes underlying these data-layers can lead to intricate multivariate association patterns. We propose and evaluate two methods to determine the proportion of variance of an output data set that can be explained by an input data set when both data panels are high dimensional. Our approach uses random-effects models to estimate the proportion of variance of vectors in the linear span of the output set that can be explained by regression on the input set. We consider a method based on an orthogonal basis (Eigen-ANOVA) and one that uses random vectors (Monte Carlo ANOVA, MC-ANOVA) in the linear span of the output set. Using simulations, we show that the MC-ANOVA method gave nearly unbiased estimates. Estimates produced by Eigen-ANOVA were also nearly unbiased, except when the shared variance was very high (e.g., >0.9). We demonstrate the potential insight that can be obtained from the use of MC-ANOVA and Eigen-ANOVA by applying these two methods to the study of multi-locus linkage disequilibrium in chicken (Gallus gallus) genomes and to the assessment of inter-dependencies between gene expression, methylation, and copy-number-variants in data from breast cancer tumors from humans (Homo sapiens). Our analyses reveal that in chicken breeding populations ~50,000 evenly-spaced SNPs are enough to fully capture the span of whole-genome-sequencing genomes. In the study of multi-omic breast cancer data, we found that the span of copy-number-variants can be fully explained using either methylation or gene expression data and that roughly 74% of the variance in gene expression can be predicted from methylation data.