Miracle-dz/UniFAR-FTUs huggingface dataset:
Cigarette smoking increases coffee consumption: findings from a Mendelian randomisation analysis

Background Smokers tend to consume more coffee than non-smokers and there is evidence for a positive relationship between cigarette and coffee consumption in smokers. Cigarette smoke increases the metabolism of caffeine, so this association may represent a causal effect of smoking on caffeine intake. Methods We performed a Mendelian randomisation analysis in 114,029 individuals from the UK Biobank, 56,664 from the Norwegian HUNT study and 78,650 from the Copenhagen General Population Study. We used a genetic variant in the CHRNA5 nicotinic receptor (rs16969968) as a proxy for smoking heaviness. Coffee and tea consumption were self-reported. Analyses were conducted using linear regression and meta-analysed across studies. Results Each additional cigarette per day consumed by current smokers was associated with higher coffee consumption (0.10 cups per day, 95% CI:0.03,0.17). There was weak evidence for an increase in tea consumption per additional cigarette smoked per day (0.04 cups per day, 95% CI:-0.002,0.07). There was strong evidence that each additional copy of the minor allele of rs16969968 (which increases daily cigarette consumption) in current smokers was associated with higher coffee consumption (0.15 cups per day, 95% CI:0.11,0.20), but only weak evidence for an association with tea consumption (0.04 cups per day, 95% CI:- 0.01,0.09). There was no clear evidence that rs16969968 was associated with coffee or tea consumption in never or former smokers. Conclusion These findings suggest that higher cigarette consumption causally increases coffee intake. This is consistent with faster metabolism of caffeine by smokers, but may also reflect behavioural links between smoking and coffee.
Arabidopsis thaliana Metabolites Secreted by Roots during Plant Growth in Phosphorus-Limiting Conditions

Phosphorus is one of the most important nutrients required for plant growth and development. While substantial amounts of total phosphorus are present in many soil types, plants are unable to utilize some organic phosphorus sources. The main goal of this study was to characterize the spectrum of secreted plant proteins, organic acids and other metabolites that can potentially contribute to utilization of various phosphorus compounds. Our data indicate that the composition of extracellular proteins secreted by plant roots varies depending on the specific source of P in the growth medium. Furthermore, some root-secreted metabolites, such as citrate, appear to be specific to a subset of ecotypes, while tartrate, succinate and oxalate are secreted by a number of A. thaliana ecotypes. We observed secretion of phenolic compounds, such as tannins, and deoxycytidine derivatives. Taken together, while no single secreted polypeptide, organic acid or secondary metabolite can be pinpointed as specific to plant growth in particular phosphorus conditions, our data indicate that A. thaliana ecotypes differ in their physiological responses to the source of phosphorus in the growth medium. Overall, these results suggest that physiological changes in plant responses to nutrient limitation are modulated by interactions between soil phosphorus source and the specific genotype of Arabidopsis plants.
Protocols for the Analysis of microRNA Expression, Biogenesis, and Function in Immune Cells

MicroRNAs (miRNAs) are short (19‐ to 25‐nucleotide) noncoding RNA molecules that target mRNAs to repress gene expression and that play important roles in regulating many fundamental biological functions including cell differentiation, development, growth, and metabolism. They are well conserved in eukaryotic cells and are considered essential ancient elements of gene regulation. miRNA genes are transcribed by RNA polymerase II to generate primary miRNAs (pri‐miRNAs), which are cleaved by microprocessor complex in the nucleus to generate stem‐loop structures known as pre‐miRNAs. Pre‐miRNAs are translocated to the cytoplasm and cleaved by Dicer to form the mature miRNAs, which mediate mRNA degradation through their loading to the RNA‐induced silencing complex (RISC) and binding to complementary sequences within target mRNAs to repress their translation by mRNA degradation and/or translation inhibition. Because ∼1900 miRNA genes are reported in the human genome, many associated with disease, appropriate methods to study miRNA expression and regulation under physiological and pathological conditions have become increasingly important to the study of many aspects of human biology, including immune regulation. As with small interfering RNA (siRNA), the mechanism of miRNA‐mediated targeting has been used to develop miRNA‐based therapeutics. For a complete and systematic analysis, it is critical to utilize a variety of different tools to analyze the expression of pri‐mRNAs, pre‐miRNAs, and mature miRNAs and characterize their targets both in vitro and in vivo. Such studies will facilitate future novel drug design and development. This unit provides six basic protocols for miRNA analysis, covering next‐generation sequencing, quantitative real‐time PCR (qRT‐PCR), and digoxigenin‐based expression analysis of pri‐mRNAs, pre‐miRNAs, and mature miRNAs; mapping of pri‐miRNA and their cleavage sites by rapid amplification of cDNA ends (RACE); electrophoretic mobility shift assays (EMSAs) or biotin‐based nonradioactive detection of miRNA‐protein complexes (miRNPs); and functional analysis of miRNAs using miRNA mimics and inhibitors. © 2019 by John Wiley & Sons, Inc.
Carrier Recovery Systems for Arbitrarily Mapped APK Signals

This paper introduces new carrier recovery techniques for general amplitude-phase keying (APK) modulation signals. The APK's include not only normal QAM but also arbitrarily mapped APK's, including an unsymmetrical APK. Difficulty in phase error detection due to signal mapping complexity, undesirable stable-lock point existence, and the contradiction between a fast acquisition and an accurate steady state performance can be overcome. For that purpose, an acquisition mode and a steady-state mode are used. Furthermore, read-only memories (ROM) are used for recognizing various system states. Random sampling controlled PLL noise performance and acquisition mode carrier recovery circuit pull-in performance with hysteresis property was obtained.
Network modelling unravels mechanisms of crosstalk between ethylene and salicylate signalling in potato

To provide means for novel crop breeding strategies, it is crucial to understand the mechanisms underlying the interaction between plants and their pathogens. Network modelling represents a powerful tool that can unravel properties of complex biological systems. Here, we build on a reliable Arabidopsis (Arabidopsis thaliana L.) immune signalling model, extending it with the information from diverse publically available resources. The resulting prior knowledge network (20,012 nodes, 70,091 connections) was then translated to potato (Solanum tuberosum L.) and superimposed with an ensemble network inferred from potato time-resolved transcriptomics data. We used different network modelling approaches to generate specific hypotheses of potato immune signalling mechanisms. An interesting finding was the identification of a string of molecular events, illuminating the ethylene pathway modulation of the salicylic acid pathway through NPR1 gene expression. Functional validations confirmed this modulation, thus confirming the potential of our integrative network modelling approach for unravelling molecular mechanisms in complex systems. One-sentence summary Analysis of integrated prior knowledge and ensemble networks highlights a novel connection between ethylene and salicylic acid signalling modules in potato.
Surface ozone measurements in mountain forested areas using diffusive samplers

The surface ozone levels were measured in the forested mountain areas of the Czech Republic in vegetation periods of 2004 and 2005 using the diffusive samplers. Commercially available Ogawa samplers, using filters coated with a nitrite-based solution, were applied. The ambient ozone oxidises the nitrite to nitrate, which after the exposure, is analysed by ion chromatography. The object of this study was to characterize a spatial and temporal distribution of ozone aiming to indicate within the mountain forested regions the risk areas as to the potential surface ozone impacts. Three research areas were established in forested regions adjacent to the country border. All of these areas are very important with regard to territorial landscape protection and tourism. They are forested, unpolluted with few minor emission sources located on their territory, mostly influenced by the long-range transport of pollutants (either of surface ozone or its precursors). The study has not yet been completed, and some preliminary results are presented here. The precision of replicate samples in both years was very good. The 2-week average concentrations for the Orlicke hory Mts. in 2004 were relatively high with the maximum of 70 ppb between July and August. The difference in the ambient ozone concentrations, calculated using the theoretical or empirical uptake rate, ranges between 2.3–3.9. This results in substantial underestimation of ambient ozone level if using the theoretical uptake rate, ca by a factor of 2–4. The diffusive samplers proved to be a very good tool for environmental studies in rural areas with complex terrain.
Robust Summarization and Inference in Proteome-wide Label-free Quantification

Differential analysis (DA) on a label-free mass-spectrometry benchmark study shows that leading summarization strategies often fail compared with the peptide-based tool MSqRob, and, we provide deep insights in performance gaps of the former methods. MSqRob, however, is computationally expensive and does not provide protein-summaries for downstream analysis and visualization. Therefore, we propose MSqRobSum, which fits MSqRob's model in a two-stage approach, providing a fast modular framework for robust protein summarization and inference that outperforms leading summarization-based methods for DA. Graphical Abstract Highlights In depth performance assessment of leading tools for differential protein abundance. Novel fast modular framework MSqRobSum for robust protein summarization and inference. MsqRobSum outperforms leading protein summarization-based tools. MSqRobSum is on par with top-performing peptide based tool MSqRob. Label-Free Quantitative mass spectrometry based workflows for differential expression (DE) analysis of proteins impose important challenges on the data analysis because of peptide-specific effects and context dependent missingness of peptide intensities. Peptide-based workflows, like MSqRob, test for DE directly from peptide intensities and outperform summarization methods which first aggregate MS1 peptide intensities to protein intensities before DE analysis. However, these methods are computationally expensive, often hard to understand for the non-specialized end-user, and do not provide protein summaries, which are important for visualization or downstream processing. In this work, we therefore evaluate state-of-the-art summarization strategies using a benchmark spike-in dataset and discuss why and when these fail compared with the state-of-the-art peptide based model, MSqRob. Based on this evaluation, we propose a novel summarization strategy, MSqRobSum, which estimates MSqRob's model parameters in a two-stage procedure circumventing the drawbacks of peptide-based workflows. MSqRobSum maintains MSqRob's superior performance, while providing useful protein expression summaries for plotting and downstream analysis. Summarizing peptide to protein intensities considerably reduces the computational complexity, the memory footprint and the model complexity, and makes it easier to disseminate DE inferred on protein summaries. Moreover, MSqRobSum provides a highly modular analysis framework, which provides researchers with full flexibility to develop data analysis workflows tailored toward their specific applications.
Aging-Associated Decrease in the Histone Acetyltransferase KAT6B Causes Myeloid-Biased Hematopoietic Stem Cell Differentiation

Aged hematopoietic stem cells (HSCs) undergo biased lineage priming and differentiation toward production of myeloid cells. A comprehensive understanding of gene regulatory mechanisms causing HSC aging is needed to devise new strategies to sustainably improve immune function in aged individuals. Here, a focused shRNA screen of epigenetic factors reveals that the histone acetyltransferase Kat6b regulates myeloid cell production from hematopoietic progenitor cells. Within the stem and progenitor cell compartment, Kat6b is most highly expressed in long-term (LT)-HSCs and is significantly decreased with aging at the transcript and protein levels. Knockdown of Kat6b in young LT-HSCs causes skewed production of myeloid cells both in vitro and in vivo. Transcriptome analysis identifies enrichment of aging and macrophage-associated gene signatures alongside reduced expression of self-renewal and multilineage priming signatures. Together, our work identifies KAT6B as an epigenetic regulator of LT-HSC aging and a novel target to improve aged immune function.
Temporal processing of facial expressions of mental states

Faces provide not only cues to an individual’s identity, age, gender and ethnicity, but also insight into their mental states. The ability to identify the mental states of others is known as Theory of Mind. Here we present results from a study aimed at extending our understanding of differences in the temporal dynamics of the recognition of expressions beyond the basic emotions at short presentation times ranging from 12.5 to 100 ms. We measured the effect of variations in presentation time on identification accuracy for 36 different facial expressions of mental states based on the Reading the Mind in the Eyes test (Baron-Cohen et al., 2001) and compared these results to those for corresponding stimuli from the McGill Face database, a new set of images depicting mental states portrayed by professional actors. Our results show that subjects are able to identify facial expressions of complex mental states at very brief presentation times. The kind of cognition involved in the correct identification of facial expressions of complex mental states at very short presentation times suggests a fast, automatic Type-1 cognition.
EFFECTS OF ALGAE PRODUCTS ON NUTRIENT UPTAKE AND FRUIT QUALITY OF APPLE

Nowadays the main task of scientists and farmers is to find natural ways to avoid negative effects of climatic anomalies and improve plant productivity lead to environmental friendly agriculture. Biostimulants have a great potential to achieve these aims but unfortunately there is little information about its application in apple growing mostly in East Hungary. For this reason, foliar nutrition experiment was made in the region of Nyírség (East Hungary) to investigate the effect of different biostimulants (algae products) on yield, leaf nutrient concentration and quality parameters of cv. ‘Gala Must’ apple (Malus domestica Borkh.) variety. The study was conducted in 2012 at Nyírbátor in East Hungary in a 14 years old apple plantation. Treatments (application time and doses) were adjusted to the phenological phases of apple and the control was used an untreated check. Effect of treatments was monitored by leaf diagnosis and apple quality measurements. The results demonstrate that the treatments increased the external fruit parameters (diameter, weight, shape index) but not affected consequently the leaf macronutrient status compared to the control. We suppose that, stable treatment effect on leaf nutrient status can be observed in long-lasting experiment only. The applied products significantly increased the amount of flavonoid and phenolic compounds and water soluble antioxidant capacity value compared to the control. Our fruit analysis results supported that the applied biostimulators had no effect on fruit acid and ash content. Moreover, the applied products resulted higher sugar, vitamin C and dry matter content despite the unfavourable, very dry climatic conditions. In sum, results showed that foliar application of biostimulants had a positive effect on yield and resulted bigger and healthier therefore more marketable fruits.
Uniquely excitable neurons enable precise and persistent information transmission through the retrosplenial cortex

The retrosplenial cortex (RSC) is essential for both memory and navigation, but the neural codes underlying these functions remain largely unknown. Here, we show that the most prominent cell type in layers 2/3 (L2/3) of the granular RSC is a uniquely excitable, small pyramidal cell. These cells have a low rheobase (LR), high input resistance, lack of spike-frequency adaptation, and spike widths intermediate to those of neighboring fast-spiking (FS) inhibitory neurons and regular-spiking (RS) excitatory neurons. LR cells are excitatory but rarely synapse onto neighboring neurons. Instead, L2/3 of RSC is an inhibition-dominated network with dense connectivity between FS cells and from FS to LR neurons. Biophysical models of LR but not RS cells precisely and continuously encode sustained input from afferent postsubicular head-direction cells. Thus, the unique intrinsic properties of LR neurons can support both the precision and persistence necessary to encode information over multiple timescales in the RSC.
Integrated data and speech transmission using packet reservation multiple access

The authors propose an integrated packet reservation multiple access (IPRMA) protocol for transmitting both speech and data information. While speech users are allowed to contend for reservation slots on a frame-by-frame basis, data users may reserve multiple slots across a frame to increase throughput. The protocol includes a priority mechanism which ensures that speech users have greater access to idle slots since speech packets have a more demanding delay constraint. The proposed scheme is shown to provide equitable access to channel resources for both types of users, yielding improvements in overall system performance while significantly increasing data throughput compared to a system without data packet reservation. <<ETX>>
The Parallel Asynchronous Differential Evolution Method as a Tool to Analyze Synchrotron Scattering Experimental Data from Vesicular Systems

In this work we use an Asynchronous Differential Evolution (ADE) method to estimate parameters of the Separated Form Factor (SFF) model which is used to investigate a structure of drug delivery Phospholipid Transport Nano System (PTNS) unilamellar vesicles by experimental small angle synchrotron X-ray scattering spectra (SAXS). We compare the efficiency of different optimizing procedures (OP) for the search for the SFF-model parameters. It is shown that the probability to find the global solution of this problem by ADE-methods is significantly higher than that by either Nelder-Mead method or a Quasi-Newton method with Davidon-Fletcher-Powell formula. The parallel realization of ADE accelerates the calculations significantly. The speed-up obtained by the parallel realization of ADE and results of the model are presented.
Global analysis of plasma lipids identifies liver-derived acyl-carnitines as a fuel source for brown fat thermogenesis

Cold induced thermogenesis is an energy demanding process that protects endotherms against a reduction in ambient temperature. Using non-targeted LC-MS based lipidomics, we identified plasma acylcarnitines as the most significantly changed lipid class in response to the cold. Here we show that acylcarnitines provide fuel for brown fat thermogenesis. In response to the cold, FFAs released from adipocytes activate the nuclear receptor HNF4α to stimulate the expression of genes involved in acylcarnitine metabolism in the liver. Conditional deletion of HNF4α in hepatocytes blocks the cold-induced changes in hepatic gene expression, lowering circulating long chain acylcarnitine (LCAC) levels, and impairing their ability to adapt to the cold. Finally, a bolus of L-carnitine or palmitoylcarnitine rescues the cold sensitivity seen with aging. Our data highlights an elegant mechanism whereby white adipose tissue provides FFAs for hepatic carnitilation to generate plasma LCAC as a fuel source for BAT thermogenesis. Highlights Blood acylcarnitine levels increase in response to the cold. FFA mobilization in response to the cold activates hepatic HNF4α and stimulates genes involved in acylcarnitine metabolism. Brown adipocytes metabolize palmitoylcarnitine. Carnitine administration improves thermogenic response in aged mice. ETOC Simcox et al identified acylcarnitines as a novel source of energy for thermogenesis. In response to the cold, the liver activates a transcriptional program through the transcription factor HNF4α, leading to increased acylcarnitine levels. They also find that aging mice have reduced acylcarnitine levels and an impaired thermogenic response in the cold. Increasing acylcarnitine levels in old mice increases their ability to adapt to the cold. Their studies discover a physiological role for acylcarnitines in thermogenesis. Graphical Abstract Cold exposure stimulates the sympathetic nervous system to release noradrenaline (NA). Activation of β3-adrenergic receptors stimulates FFA release and activation of the transcription factor HNF4α in the liver. This leads to increased gene expression of enzymes involved in acylcarnitine metabolism. The acylcarnitines are released in the blood to provide fuel for brown fat thermogenesis. These studies highlight the role of the liver in the thermogenic response.
Learning Trajectory for Transforming Teachers’ Knowledge for Teaching Mathematics and Science With Digital Image and Video Technologies in an Online Learning Experience

Abstract This qualitative cross-case study explores the influence of a designed learning trajectory on transforming teachers’ technological pedagogical content knowledge (TPACK) for teaching with digital image and video technologies. The TPACK Learning Trajectory embeds tasks with specific instructional strategies within a social metacognitive constructivist structure to engage K–12 in-service teachers in an online learning course for teaching and learning mathematics and science with these technologies. The resulting trajectory shapes teachers’ TPACK into a more robust, integrated knowledge structure, influencing their thinking and decision making about the content, technology, and pedagogical concerns with these technologies. From their learning experiences, the teachers’ instructional intentions transformed to incorporate the tools and processes for teaching with technologies. The TPACK Learning Trajectory thus influences a transformation in the teachers’ TPACK strategic thinking about when, where, and how to use the technologies, with potential for influencing students’ thinking and learning of the content.