Miracle-dz/UniFAR-FTUs huggingface dataset:
Effect of Fermentation on Structural Characteristics and Bioactive Compounds of Bee-Pollen Based Food

Abstract Bee-pollen is a product of the hive which has had a growth in consumption in recent years due to the recognition of its nutritional and bioactive potential. However, several reports have shown that the external structure of the grain limits the absorption of nutrients in the human gastrointestinal tract. A structural modification could be achieved through fermentative processes, favoring the release of compounds found inside this food, in addition to obtaining a product with potential probiotic characteristics. The objective of this work was to evaluate how fermentation through the inclusion of yeasts of the species Saccharomyces cerevisiae, bacteria of species Lactobacillus plantarum or a commercial culture Choozit® affeccted such parameters as Scanning Electron Microscopy (SEM), Differential Scanning Calorimetry (DSC), phenolic compounds, flavonoids and antioxidant activity. The results found that the use of consortia between yeast and lactic acid bacteria significantly increased in such characteristics as total phenolics and antioxidant activity by 31% and 39% respectively. The analysis by DSC showed an increase in the heat flow of the fermented products compared to fresh bee-pollen, which could indicate structural modification caused by the activity of microorganisms, a fact made visible through micrographs obtained by Scanning Electron Microscopy.
The First Publicly Available Annotated Genome for Cannabis plants

Recently we have seen a relaxation of the historic restrictions on the use and subsequent research on the Cannabis plants in North America. We have recently described a pipeline for the creation of annotated protein databases using a combination of genomic and proteomic data and the application of this method toward the analysis of the proteomes of Cannabis plants. In parallel with our work, we approached the National Center for Biotechnology Information (NCBI) to align and annotate publicly deposited genomic files for these plants. In September of 2019, this project was completed. The result, NCBI Cannabis sativa Annotation Release 100 is now live and publicly available. The annotated genome allows, for the first time, the use of classical genetics and proteomics tools for the interrogation of these plants. Furthermore, the presence of an annotated genome within the NCBI Genome browser now permits any researcher with a web browser to manually examine or BLAST genetic sequences, vastly reducing the resources required to create primers to amplify genes from the plants or microbial contaminants that may affect them. We describe this new resource and some points of obvious value to the scientific community as well as the integration into the Cannabis Proteome Draft Map Project. Significance Statement Until recently laws in North America have restricted nearly all research on Cannabis plants. Until recent research from our lab, only a few hundred genes and proteins from the plant had been annotated for putative function. The construction of a publicly available annotated genome for this plant allows, for the first time, the use of traditional genomic and proteomic tools for the investigation of these plants. We evaluate herein the first fully annotated publicly available genome for Cannabis plants and the integration of this resource into www.CannabisDraftmap. org
Obsessed with Time? White Rabbit At CERN

To conduct research in fundamental science, big-science research infrastructures develop some of the most sophisticated technologies in existence. As such, mechanisms that can facilitate the transfer and commercialization of these technologies have vast potential to contribute to economic and social welfare. Scientists and engineers at CERN were confronted with the problem of minute data latency that was corrupting scientific measurements in their geographically distributed computing network. In response, they developed White Rabbit (WR) as open source hardware (OSH). In a context of basic research and a deliberate decision to share the R&D process openly with no IP restrictions, WR is now commercialized in diverse economic sectors including finance, telecommunications, energy, Internet of Things (IoT), and air traffic control. We analyze the emergence, development, and exploitation of WR to a) identify the antecedents in which complex R&D-intensive OSH differs from open source software (OSS), b) capture the mechanisms employed by CERN to stimulate firms’ R&D revelation and WR collaborative development, and c) investigate the business model configurations that companies have adopted in the commercial implementation of WR.
Recommended Best Practices based on MBSE Pilot Projects

Model‐Based Systems Engineering (MBSE) is an emerging paradigm for improving the efficiency and effectiveness of systems engineering through the pervasive use of integrated descriptive representations of the system to capture knowledge about the system for the benefit of all stakeholders. This paper describes some of the key engineering lessons and recommended best practices that have emerged from several MBSE pilot projects over the past few years.
Performance of a state‐space multispecies model: What are the consequences of ignoring predation and process errors in stock assessments?

1. Having a realistic representation of ecosystems in fisheries models is important in the context of ecosystem-based fisheries management (EBFM). While different modeling approaches support EBFM, accounting for trophic interactions and uncertainty in stock dynamics is important for management advice. Multispecies models exist, but are rarely used for assessments. Most stock assessments are single species models and predation is subsumed into natural mortality, which is often an assumed known value. The use of state-space assessment models, which account for stochasticity in unobserved processes (process errors), is increasing. However, many stocks are managed assuming deterministic processes. Little is known of how ignoring predation and process errors in stock assessment can impact the perception of the stocks and therefore fisheries management. 2. We developed an age-structured multispecies operating model that simulated data with errors in observations, recruitment and fish abundance. Four estimation models (EMs) that differed according to whether or not they accounted for predation or process errors were fitted to the simulated data. Relative differences between true and predicted outputs were estimated as a measure of bias. Equilibrium unfished biomass was estimated for each model as a proxy reference point. 3. natural by copyright. All reserved subsequently biased reference points. While it may be difficult to estimate natural mortality when no data exist to inform it, stock managers should remember that, if predation is large, assuming a constant mortality over time and/or age could have large consequences on stock perception and reference point estimates and affect resulting management advice.
Simple Assessment of Height and Length of Flight in Complex Gymnastic Skills: Validity and Reliability of a Two-Dimensional Video Analysis Method

In artistic gymnastics, the possibility of using 2D video analysis to measure the peak height (hpeak) and length of flight (L) during routine training in order to monitor the execution and development of difficult elements is intriguing. However, the validity and reliability of such measurements remain unclear. Therefore, in this study, the hpeak and L of 38 vaults, performed by top-level gymnasts, were assessed by 2D and 3D analysis in order to evaluate criterion validity and both intrarater and interrater reliability of the 2D method. Validity calculations showed higher accuracy for hpeak (±95% LoA: ±3.6% of average peak height) than for L (±95% LoA: ±7.6% of average length). Minor random errors, but no systematic errors, were observed in the examination of intrarater reliability (hpeak: CV% = 0.44%, p = 0.81; L: CV% = 0.87%, p = 0.14) and interrater reliability (hpeak: CV% = 0.51%, p = 0.55; L: CV% = 0.72%, p = 0.44). In conclusion, the validity and reliability of the 2D method are deemed sufficient (particularly for hpeak, but with some limitations for L) to justify its use in routine training of the vault. Due to its simplicity and low cost, this method could be an attractive monitoring tool for gymnastics coaches.
Identifying differences in bile acid pathways for cholesterol clearance in Alzheimer’s disease using metabolic networks of human brain regions

Alzheimer’s disease (AD) is the leading cause of dementia, with metabolic dysfunction seen years before the emergence of clinical symptoms. Increasing evidence suggests a role for primary and secondary bile acids, the end-product of cholesterol metabolism, influencing pathophysiology in AD. In this study, we analyzed transcriptomes from 2114 post-mortem brain samples from three independent cohorts and identified that the genes involved in alternative bile acid synthesis pathway was expressed in brain compared to the classical pathway. These results were supported by targeted metabolomic analysis of primary and secondary bile acids measured from post-mortem brain samples of 111 individuals. We reconstructed brain region-specific metabolic networks using data from three independent cohorts to assess the role of bile acid metabolism in AD pathophysiology. Our metabolic network analysis suggested that taurine transport, bile acid synthesis and cholesterol metabolism differed in AD and cognitively normal individuals. Using the brain transcriptional regulatory network, we identified putative transcription factors regulating these metabolic genes and influencing altered metabolism in AD. Intriguingly, we find bile acids from the brain metabolomics whose synthesis cannot be explained by enzymes we find in the brain, suggesting they may originate from an external source such as the gut microbiome. These findings motivate further research into bile acid metabolism and transport in AD to elucidate their possible connection to cognitive decline.
Corrigendum to “Coherent synthesis of genomic associations with phenotypes and home environments”

We discovered an error in our analyses (Lasky, Forester, & Reimherr, 2018). The specific error was in the analysis of enrichment of (a) SNPs associated with G×E for fitness with (b) SNPs associated with G×E for flowering time under experimental warming (Li, Cheng, Spokas, Palmer, & Borevitz, 2014). The error resulted from a failure to convert SNPs from two different versions of the Arabidopsis reference genome assembly: from TAIR8 (used in Li et al., 2014 supplemental materials, which we reanalyzed in our paper) to TAIR9 (used in our analyses of G×E for fitness, Lasky et al., 2018). We fixed the error, converting the Li et al. (2014) SNPs from TAIR8 to TAIR9 and reanalyzing the enrichments. This reanalysis showed (as in Lasky et al., 2018) that SNPs associated with flowering time response to experimental warming (G×E, Li et al., 2014) were significantly and most strongly enriched in SNPs associated with change in fitness across gradients of growing season minimum temperatures (Table 1 here, which supersedes the relevant row from Table 2 in Lasky et al., 2018). Additionally, reanalysis showed a weaker, but significant enrichment of flowering time G×E SNPs in SNPs associated with change in fitness across gradients of growing season variability in precipitation. As in Lasky et al. (2018), SNPs associated with change in fitness across gradients of annual aridity or winter cold were not enriched in flowering time G×E SNPs. In summary, our conclusion that “variants causing flowering time plasticity drive changes in fitness across growing season temperature gradients” (Lasky et al., 2018) is supported by this reanalysis and corrigendum.
Yield and physiological response of Perilla (Perilla frutescens) under different soil fertility treatments

Medicinal plants are one of the main natural resources of Iran from ancient times. Perilla is one of the most important medicinal plants of the mint family Lamiaceae , since there is no study about adaptability of Perilla in Iran climate conditions and different fertilizer systems, this experiment was conducted in two experimental sites. The experiment was conducted as split-plot factorial based on a randomized complete block design with three replications at two experimental regions. The main factor was three chemical fertilizer levels (control, 50, 100, 200 kg/ha) and subplots were different kinds of organic fertilizer (control, humic acid, and compost application) and inoculation with Piriform osporaindica (inoculation and without). Among levels of chemical treatments, 50 and 100 kg/ha lead to a better result. Also, humic acid allows to achieve the highest amount of measured traits between different treatments of organic fertilizer. The highest plant yield (147.2 g/m2) and rosmarinic acid yield per area (3.432 g/m2) was achieved in 100 kg/ha at chemical fertilizer with humic acid and biological fertilizer application and the lowest plant yield (89.86 g/m2) and rosmarinic acid yield per area (1.253 g/m2) was observed in control. Also, the highest stomatal conductance was obtained with application of compost fertilizer (67.67 mmol H2O m-2s-1). Integrated application of the studied fertilizers showed the more positive effect on yield and quality of Perilla than individual application of those fertilizers.
Dynamic Evolution of De Novo DNA Methyltransferases in Rodent and Primate Genomes

Transcriptional silencing of retrotransposons via DNA methylation is paramount for mammalian fertility and reproductive fitness. During germ cell development, most mammalian species utilize the de novo DNA methyltransferases DNMT3A and DNMT3B to establish DNA methylation patterns. However, many rodent species deploy a third enzyme, DNMT3C, to selectively methylate the promoters of young retrotransposon insertions in their germline. The evolutionary forces that shaped DNMT3C’s unique function are unknown. Using a phylogenomic approach, we confirm here that Dnmt3C arose through a single duplication of Dnmt3B that occurred between 45-71Mya in the last common ancestor of muroid rodents. Most importantly, we reveal that DNMT3C is composed of two independently evolving segments: the latter two-thirds has undergone recurrent gene conversion with Dnmt3B, whereas the N-terminus has not undergone gene conversion and has evolved under strong diversifying selection. We hypothesize that positive selection of Dnmt3C is the result on an ongoing evolutionary arms race with young retrotransposon lineages in muroid genomes. Interestingly, although primates lack DNMT3C, we find that the N-terminus of DNMT3A has also evolved under diversifying selection. Thus, the N-termini of two independent de novo DNMT enzymes have evolved under diversifying selection in rodents and primates. We hypothesize that repression of young retrotransposons might be driving the recurrent innovation of a functional domain in the N-termini on germline DNMTs in mammals.
Learning contract, co-operative and flipped learning as useful tools for studying metabolism

Undergraduate students in Biology identify Metabolic Biochemistry as a particularly difficult subject. This is due to the fact that students need to interconnect properly all the contents of its syllabus throughout their study of the subject in order to get a global insight of the complex regulatory features controlling metabolic pathways within the metabolic network under different physiologic and pathologic conditions, as well as metabolism as a whole. Due to these objective difficulties, a high percentage of our students face the study of this subject as a very hard task beyond their forces and capacities. This perception leads to high rates of premature dropout. In previous years, less than 40% of all the registered students attended the examinations of Metabolic Biochemistry (a subject in the second year of the Degree of Biology at our University). Even worse, less than 25% of our students passed the exams. From the academic year 2015/16 on, we are developing innovative teaching projects (PIE15-163 and PIE17-145, funded by University of Malaga) aimed to increase our student loyalty to the subject (and hence to increase their attendance to exams) and to help them to learn more effectively metabolism and its regulation. These innovative teaching projects are based on the use of several powerful tools: a learning contract and problem-based learning within the framework of group tasks promoting an actual collaborative learning in a flipped classroom. The present communication will show the implementation of the PIE15-163 and PIE17-145 projects and some results obtained from them. [This work was supported by Malaga University funds granted to the educational innovation project PIE17-145. The attendance to the END2018 International Conference on Education and New Developments (June 2018, Budapest, Hungary) has received a grant from "I Plan Propio Integral de Docencia. Universidad de Málaga"].
Inflammation and Reduced Parasympathetic Cardiac Modulation in Aortic-Valve Sclerosis

Aortic-valve sclerosis increases cardiovascular mortality risk and precedes aortic-valve stenosis, but its mechanisms are not well understood. The purpose of this study was to compare the cardiac autonomic modulation and inflammation markers between subjects with aortic-valve normal leaflets and subjects with aortic-valve sclerosis. According to 2-D transthoracic echocardiograms, 61 middle-aged volunteers without chronic or acute illnesses were classified in two groups: with no aortic-valve sclerosis (NAVS, N = 16) and with aortic-valve sclerosis (AVS, N = 45). An electrocardiogram at the supine position and active standing was collected to estimate heart rate variability (HRV) indices. A blood sample was obtained to quantify markers of inflammation. Compared to NAVS, AVS subjects showed higher levels of IL-6 (1619 ± 650 vs. 1169 ± 676 pg/mL, p = 0.044) as well as TNFα (370.8 ± 182.0 vs. 247.3 ± 188.2 pg/mL, p = 0.032), and larger low-frequency (LF) to high-frequency (HF) ratio during supine position (Ln(LF/HF) = 0.85 ± 0.85 vs. 0.11 ± 0.69, p = 0.003). Multiple logistic regression analysis showed that AVS was independently associated with LF/HF, TNFα and left ventricle mass index (p < 0.05). In conclusion, a significant reduction of the parasympathetic-driven cardiac modulation and low-grade inflammation occurs in aortic-valve sclerosis.
Maximizing Dissimilarity in Resting State detects Heterogeneous Subtypes in Healthy population associated with High Substance-Use and Problems in Antisocial Personality

Patterns in resting-state fMRI (rs-fMRI) are widely used to characterize the trait effects of brain function. In this aspect, multiple rs-fMRI scans from single subjects can provide interesting clues about the rs-fMRI patterns, though scan-to-scan variability pose challenges. Therefore, rs-fMRI’s are either concatenated or the functional connectivity is averaged. This leads to loss of information. Here, we use an alternative way to extract the rs-fMRI features that are common across all the scans by applying Common-and-Orthogonal-Basis-Extraction (COBE) technique. To address this, we employed rs-fMRI of 788 subjects from the human connectome project and estimated the common-COBE-component of each subject from the four rs-fMRI runs. Since the common-COBE-component are specific to a subject, the pattern was used to classify the subjects based on the similarity/dissimilarity of the features. The subset of subjects (n=107) with maximal-COBE-Dissimilarity (MCD) was extracted and the remaining subjects (n = 681) formed the COBE-similarity (CS) group. The distribution of weights of the common-COBE-component for the two groups across rs-fMRI networks and subcortical regions was evaluated. We found the weights in the default mode network to be lower in the MCD compared to the CS. We compared the scores of 69 behavioral measures and found 6 behaviors related to the use of marijuana, illicit drugs, alcohol, and tobacco; and including a measure of antisocial personality to differentiate the two groups. Gender differences were also significant. Altogether findings suggested that subtypes exist even in healthy control population and comparison studies (Case vs Control) need to be mindful of it.
Using stage-structured food webs to assess the effects of contaminants and predators on aquatic–terrestrial linkages

Aquatic insects are routinely used to measure the biological responses of streams and lakes to contaminants and predators, but assessments often focus only on benthic larval stages. However, like many organisms on earth, aquatic insects have complex life histories in which ontogenetic stages vary in their ecology, habitat, and susceptibility to stressors like contaminants and predators. Here, I summarize the differential responses of aquatic insect life stages (e.g., larva, pupa, adult) to fish predation and contaminants, 2 common and well-studied sources of mortality for aquatic insects. I then examine how stage-structured mortality may alter the link between larval aquatic insect densities and flux of emerging aquatic insects to terrestrial food webs. The most important finding is that predictions of aquatic insect responses based on stage structured food webs deviate strongly from predictions that do not include life stages, implying that larval responses to predation or contaminants may not be appropriate in predicting adult responses. Larval-based bioassessment continues to be an important tool for stream conservation and management. However, failure to account for variation in stage-specific responses may limit the utility of current bioassessment tools to predict aquatic insect emergence, potentially underestimating the impact of freshwater stressors on linked aquatic–terrestrial ecosystems.
Lost pigs and broken genes: the search for causes of embryonic loss in the pig and the assembly of a more contiguous reference genome

The falling cost of DNA sequencing has made the technology affordable to many research groups, enabling researchers to link genomic variants to observed phenotypes in a range of species. This review focusses on whole exome sequencing and its applications in humans and other species. The exome has traditionally been defined to consist of only the protein coding portion of the genome; a region where mutations are likely to affect protein structure and function. There are several commercial kits available for exome sequencing in a number of species and, owing to the highly conserved nature of exons, many of these can be applied to other closely related species. The data set produced from exome sequencing is many times smaller than that of whole genome sequencing, making it more easily manageable and the analysis less complex. Exome sequencing for disease gene discovery in humans is well established and has been used successfully to identify mutations that are causative of complex and rare diseases. Exome sequencing has also been used in a number of domesticated and companion species. The successful application of exome sequencing to crops has yielded results that may be used in selective breeding to improve production in these species, and there is potential for exome sequencing to provide similar advances in livestock species that have not yet been realised.