Miracle-dz/UniFAR-FTUs huggingface dataset:
Mechanistic investigations of redox polymer-coated electrodes using probe-beam deflection and cyclic voltammetry

Optical probe-beam deflection signals, together with cyclic voltammograms, have been used to analyse the electron-transfer process at electrodes coated with [Ru(bpy)2ClPVP]Cl, polyaniline and poly(1-hydroxyphenazine). With this technique it is possible to determine if anions or cations are used as the charge-compensating ions in the electron-transfer process. The electron transfer at [Ru(bpy)2ClPVP]Cl was shown to be accompanied by a simple counter-ion diffusion process. The known electron-transfer mechanism of polyaniline was confirmed and a plausible mechanism for the electron transfer of poly(l-hydroxyphenazine) has been proposed. The additional information (direction of concentration gradients) obtained by a simple probe-beam deflection experiment is extremely useful in the analysis of reaction mechanisms at redox polymer-coated electrodes.
Inferring Networks of Diffusion and Influence

Information diffusion and virus propagation are fundamental processes taking place in networks. While it is often possible to directly observe when nodes become infected with a virus or publish the information, observing individual transmissions (who infects whom, or who influences whom) is typically very difficult. Furthermore, in many applications, the underlying network over which the diffusions and propagations spread is actually unobserved. We tackle these challenges by developing a method for tracing paths of diffusion and influence through networks and inferring the networks over which contagions propagate. Given the times when nodes adopt pieces of information or become infected, we identify the optimal network that best explains the observed infection times. Since the optimization problem is NP-hard to solve exactly, we develop an efficient approximation algorithm that scales to large datasets and finds provably near-optimal networks. We demonstrate the effectiveness of our approach by tracing information diffusion in a set of 170 million blogs and news articles over a one year period to infer how information flows through the online media space. We find that the diffusion network of news for the top 1,000 media sites and blogs tends to have a core-periphery structure with a small set of core media sites that diffuse information to the rest of the Web. These sites tend to have stable circles of influence with more general news media sites acting as connectors between them.
Symmetrization

We present a symmetrization algorithm for geometric objects. Our algorithm enhances approximate symmetries of a model while minimally altering its shape. Symmetrizing deformations are formulated as an optimization process that couples the spatial domain with a transformation configuration space, where symmetries can be expressed more naturally and compactly as parametrized point-pair mappings. We derive closed-form solution for the optimal symmetry transformations, given a set of corresponding sample pairs. The resulting optimal displacement vectors are used to drive a constrained deformation model that pulls the shape towards symmetry. We show how our algorithm successfully symmetrizes both the geometry and the discretization of complex 2D and 3D shapes and discuss various applications of such symmetrizing deformations.
Observation of Molten Slag Surface under Gas Impingement by X-ray Computed Tomography

Observation of molten slag at 1 673 K was carried out by X-ray Computed Tomography (X-ray CT) to make clear the shape of slag surface where gas was downward blown. X-ray CT scanning of molten slag heated in an electric furnace was conducted to take an image of its cross section. In order to examine the effects of gas momentum supplied on the surface shape, three kinds of inert gases, Ar, He and N 2 , were employed as the blowing gas under the several conditions of gas flow rate and gas pipe diameter. The obtained X-ray CT images successfully visualized the cross section of molten slag. The boundary line between gas and slag in the image was concave under the gas blowing, indicating a formation of depression on the slag surface by gas impingement. The concave boundary is completely different from the parabolic shape conventionally evaluated. The depression became larger, not only in depth but also in width, with increasing gas flow rate, whereas drastically smaller with increasing gas pipe diameter. In addition, larger depth was brought by impingement of larger molecular (atomic)-weight gas. These results were well explained by the conservation law of momentum between gas and slag. It was also revealed that the increment in the boundary line caused by formation of depression, which corresponds to an increase in the interfacial area, is in proportion to the depression depth in the range of more than 2 mm, and was independent of the pipe diameter and gas species.
Using tables to enhance trustworthiness in qualitative research

In this essay, we discuss how tables can be used to ensure—and reassure about—trustworthiness in qualitative research. We posit that in qualitative research, tables help not only increase transparency about data collection, analysis, and findings, but also—and no less importantly—organize and analyze data effectively. We present some of the tables most frequently used by qualitative researchers, explain their uses, discuss how they enhance trustworthiness, and provide illustrative examples to inspire readers in their use of tables in their own research.
Point-block incomplete LU preconditioning with asynchronous iterations on GPU for multiphysics problems

Point-block matrices arise naturally in multiphysics problems when all variables associated with a mesh point are ordered together, and are different from the general block matrices since the sizes of the blocks are so small one can often invert some of the diagonal blocks explicitly. Motivated by the recent works of Chow and Patel and Chow et al., we propose an efficient incomplete LU (ILU) preconditioner for point-block matrices targeting applications on GPU. The construction of the preconditioner involves two critical steps: (1) the initial guessing of values for the lower and upper triangular matrices; and (2) several sweeps of asynchronous updating of the triangular matrices. Three representative problems are studied to show the advantage of the proposed point-block approach over the standard point-wise approach in terms of the number of GMRES iterations and also the total compute time. Moreover, we compare the proposed algorithm with the level-scheduling based parallel algorithm employed in NVIDIA’s cuSPARSE library as well as the serial method implemented in Intel MKL library, and the experiments show that a 2×–5× speedup can be achieved over the block-based ILU(p) factorizations from the cuSPARSE library.
Chemogenetic activation of nigrostriatal dopamine neurons in freely moving common marmosets

To interrogate particular neuronal pathways in non-human primates under natural and stress-free conditions, we applied designer receptors exclusively activated by designer drugs (DREADDs) technology to common marmosets. We injected adeno-associated virus vectors expressing the excitatory DREADD hM3Dq into the unilateral substantia nigra in three marmosets. Using multi-tracer positron emission tomography imaging, we detected DREADD expression in vivo, which was confirmed in nigrostriatal dopamine neurons by immunohisto-chemistry, and assessed activation of the substantia nigra and dopamine release following agonist administration. The marmosets rotated in a contralateral direction relative to the activated side 30–90 min after consuming food containing the highly potent DREADD agonist deschloroclozapine (DCZ), but not on the following days without DCZ. These results indicate that non-invasive and reversible DREADD manipulation will extend the utility of marmoset as a primate model for linking neuronal activity and natural behavior in various contexts.
PATO: Pangenome Analysis Toolkit

Motivation Comparative genomics is a growing field but one that will be eventually overtaken by sample size studies and the increase of available genomes in public databases. We present the Pangenome Analysis Toolkit (PATO) designed to simultaneously analyze thousands of genomes using a desktop computer. The tool performs common tasks of pangenome analysis such as core-genome definition and accessory genome properties and includes new features that help characterize population structure, annotate pathogenic features and create gene sharedness networks. PATO has been developed in R to integrate with the large set of tools available for genetic, phylogenetic and statistical analysis in this environment. Results PATO can perform the most demanding bioinformatic analyses in minutes with an accuracy comparable to state-of-the-art software but 20–30x times faster. PATO also integrates all the necessary functions for the complete analysis of the most common objectives in microbiology studies. Lastly, PATO includes the necessary tools for visualizing the results and can be integrated with other analytical packages available in R. Availability The source code for PATO is freely available at https://github.com/irycisBioinfo/PATO under the GPLv3 license. Contact val.fernandez@salud.madrid. org Supplementary information Supplementary data are available at Bioinformatics online
The ETS transcription factor ERF controls the exit from the naïve pluripotent state in a MAPK-dependent manner

The naïve epiblast undergoes a transition to a pluripotent primed state during embryo implantation. Despite the relevance of the FGF pathway during this period, little is known about the downstream effectors regulating this signaling. Here, we examined the molecular mechanisms coordinating the naïve to primed transition by using inducible ESC to genetically eliminate all RAS proteins. We show that differentiated RASKO ESC remain trapped in an intermediate state of pluripotency with naïve-associated features. Elimination of the transcription factor ERF overcomes the developmental blockage of RAS-deficient cells by naïve enhancer decommissioning. Mechanistically, ERF regulates NANOG expression and ensures naïve pluripotency by strengthening naïve transcription factor binding at ESC enhancers. Moreover, ERF negatively regulates the expression of the de novo methyltransferase DNMT3B, which participates in the extinction of the naïve transcriptional program. Collectively, we demonstrated an essential role for ERF controlling the exit from naïve pluripotency during the progression to primed pluripotency. Teaser ERF is the MAPK-dependent switch controlling the transition between naïve and primed pluripotency during embryonic development.
Pseudogenization of trnT-GGU in chloroplast genomes of the plant family Asteraceae

The chloroplast genome evolves through the course of evolution. Various types of mutational events are found within the chloroplast genome, including insertions-deletions (InDels), substitutions, inversions, gene rearrangement, and pseudogenization of genes. The pseudogenization of the trnT-GGU gene was previously reported in the Cryptomeria japonica (Cupressaceae), Pelargonium x hortorum (Geraniaceae), and in the two species of the tribe Gnaphalieae (Asteroideae, Asteraceae). Here, we performed a broad analysis of the trnT-GGU gene among the species of twelve subfamilies of Asteraceae and found pseudogenization of this gene is not limited to the two species of Gnaphalieae or the tribe Gnaphalieae. We report for the first time that this gene is pseudo in the species of three subfamilies of Asteraceae, including Gymnarrhenoideae, Cichorioideae and Asteroideae. The analyses of the species of 78 genera of Asteroideae revealed that this pseudogenization event is linked to the insertion within the 5′ acceptor stem and not linked to the habit, habitat, and geographical distribution of the plant.
AhNGE: A Database for Arachis hypogaea Nodule Developmental Gene Expression

Symbiotic nitrogen fixation (SNF) inside root-nodules is a primary and sustainable source of soil nitrogen. Understanding nodule development and metabolism in crop legumes may lead to more effective SNF in agriculture. Peanut (Arachis hypogaea) is an economically important allotetraploid legume with non-canonical nodule developmental features. Recent genome sequencing of peanut has opened the possibility of making peanut a model for studying atypical nodule development. To help the community of nodule biologists, we have developed a database called AhNGE (Arachis hypogaea Nodule Developmental Gene Expression: http://nipgr.ac.in/AhNGE/index.php). AhNGE contains RNAseq data from six data points of nodule development in A. hypogagea cv. Tifrunner. This data represents a dynamic view of gene expression during peanut nodule development. Research in model legumes has generated a huge knowledgebase in the last twenty years. To streamline comparative genomics among legumes, we performed ortholog analysis among four legumes (Cicer, Glycine, Lotus, and Medicago) and one non-legume (Arabidopsis). This will facilitate the integration of existing knowledge in nodule development with the Arachis transcriptome. The available data can be retrieved using a single or batch query or searching using gene ID, from above mentioned five species. The output displays the gene expression pattern in graphical as well as tabular form, along with further options to download the sequence data. The database is linked with PeanutBase, the main genomic resource of peanut. Additionally, the expression level of different splicing variants can be retrieved from the database. In summary, AhNGE serves as an important resource for the scientific community working on nodule development.
Cortical Processing of Arithmetic and Simple Sentences in an Auditory Attention Task

Cortical processing of arithmetic and of language rely on both shared and task-specific neural mechanisms, which should also be dissociable from the particular sensory modality used to probe them. Here, spoken arithmetical and non-mathematical statements were employed to investigate neural processing of arithmetic, compared with general language processing, in an attention-modulated cocktail party paradigm. Magnetoencephalography (MEG) data were recorded from 22 human subjects listening to audio mixtures of spoken sentences and arithmetic equations while selectively attending to one of the two speech streams. Short sentences and simple equations were presented diotically at fixed and distinct word/symbol and sentence/equation rates. Critically, this allowed neural responses to acoustics, words, and symbols to be dissociated from responses to sentences and equations. Indeed, the simultaneous neural processing of the acoustics of words and symbols was observed in auditory cortex for both streams. Neural responses to sentences and equations, however, were predominantly to the attended stream, originating primarily from left temporal, and parietal areas, respectively. Additionally, these neural responses were correlated with behavioral performance in a deviant detection task. Source-localized temporal response functions (TRFs) revealed distinct cortical dynamics of responses to sentences in left temporal areas and equations in bilateral temporal, parietal, and motor areas. Finally, the target of attention could be decoded from MEG responses, especially in left superior parietal areas. In short, the neural responses to arithmetic and language are especially well segregated during the cocktail party paradigm, and the correlation with behavior suggests that they may be linked to successful comprehension or calculation. SIGNIFICANCE STATEMENT Neural processing of arithmetic relies on dedicated, modality independent cortical networks that are distinct from those underlying language processing. Using a simultaneous cocktail party listening paradigm, we found that these separate networks segregate naturally when listeners selectively attend to one type over the other. Neural responses in the left temporal lobe were observed for both spoken sentences and equations, but the latter additionally showed bilateral parietal activity consistent with arithmetic processing. Critically, these responses were modulated by selective attention and correlated with task behavior, consistent with reflecting high-level processing for speech comprehension or correct calculations. The response dynamics show task-related differences that were used to reliably decode the attentional target of sentences or equations.
PACAS: pairwise comparisons of aligned subsequences

Evaluation of conservation levels of alignments is a pivotal step for evolutionary analyses. Commonly used software to analyze alignments produce either site-by-site or overall measures of conservation without the ability of performing comparative analyses among sub-regions of the alignment. We have developed a stand-alone alignment analyzer (Pairwise Comparisons of Aligned Subsequences) that uses user-defined sub-regions to report various measures of conservation among pairs of sequences and between the sub-regions and the rest of the alignment. We then used this method to analyze the repetitive regions (low complexity regions; LCRs) of two genes in Plasmodium: AMA1 and CSP. We found that LCRs are not always associated with high entropy (low conservation) suggesting that some LCRs may be less likely to mutate than others. Availability and Implementation PACAS is publicly available at https://github.com/BlabOaklandU/PACAS Contact Fabia U. Battistuzzi battistu@oakland.edu Supplementary information n/a
Combining chemogenomic and gene-dose assays to investigate drug synergy

From the earliest days of using natural remedies to modern applications of clinically tested medications, combining therapies for disease treatment has been standard practice. Combination treatments can exhibit synergistic effects, broadly defined as a greater-than-additive effect of two or more therapeutic agents. Indeed, clinicians often use their experience and expertise to tailor such combinations in the hopes of maximizing the therapeutic effect. Alongside these efforts, computational studies into understanding and predicting the biophysical underpinnings of how synergy is achieved have benefitted from high-throughput screening and computational biology. One challenge is how to best design and analyze the results of synergy studies performed at scale, especially because the number of possible combinations to test quickly becomes unmanageable, and the tools to analyze the resulting data are quite new. Nevertheless, the benefits of such studies are clear — by combining multiple drugs in the treatment of infectious disease and cancer, for instance, one can lessen host toxicity and simultaneously reduce the likelihood of resistance to treatment. In this study, we extend the widely validated chemogenomic HIPHOP assay to drug combinations. We identify a class of “combination-specific sensitive strains” that suggest mechanisms for the synergies we observe and further suggest focused follow-up studies.
ESD1 Affects Seed Setting Rate in Rice by Controlling Embryo Sac Development

Seed setting rate is one of the critical factors that determine rice yield. Grain formation is a complex biological process, whose molecular mechanism is yet to be improved. Here we investigated the function of an OVATE family protein, Embryo Sac Development 1 (ESD1), in the regulation of seed setting rate in rice (Oryza sativa) by examining its loss-of-function mutants generated via CRISPR/Cas9 technology. ESD1 was predominantly expressed at stage 6 of panicle development, especially in the ovules. esd1 mutants displayed reduced seed setting rates with normal stamen development and pollen tube growth but abnormal pistil group. Investigation of embryo sacs revealed that during the mitosis of functional megaspores, some egg cells degraded during differentiation in esd1 mutants, thereby hindering subsequent fertilization process and reducing seed setting rate. In addition, the transcriptional level of OsAPC6, a reported embryo sac developing gene, was found to be significantly reduced in esd1 mutants. These results support that ESD1 is an important modulator of embryo sac development and seed setting rate in rice. Together, this finding demonstrates that ESD1 positively regulates the seed setting rate by controlling embryo sac development in rice, and has implications for the improvement of rice yield.
Drosophila Evolution over Space and Time (DEST) - A New Population Genomics Resource

Drosophila melanogaster is a leading model in population genetics and genomics, and a growing number of whole-genome datasets from natural populations of this species have been published over the last 20 years. A major challenge is the integration of these disparate datasets, often generated using different sequencing technologies and bioinformatic pipelines, which hampers our ability to address questions about the evolution and population structure of this species. Here we address these issues by developing a bioinformatics pipeline that maps pooled sequencing (Pool-Seq) reads from D. melanogaster to a hologenome consisting of fly and symbiont genomes and estimates allele frequencies using either a heuristic (PoolSNP) or a probabilistic variant caller (SNAPE-pooled). We use this pipeline to generate the largest data repository of genomic data available for D. melanogaster to date, encompassing 271 population samples from over 100 locations in >20 countries on four continents based on a combination of 121 unpublished and 150 previously published genomic datasets. Several of these locations have been sampled at different seasons across multiple years. This dataset, which we call Drosophila Evolution over Space and Time (DEST), is coupled with sampling and environmental meta-data. A web-based genome browser and web portal provide easy access to the SNP dataset. Our aim is to provide this scalable platform as a community resource which can be easily extended via future efforts for an even more extensive cosmopolitan dataset. Our resource will enable population geneticists to analyze spatio-temporal genetic patterns and evolutionary dynamics of D. melanogaster populations in unprecedented detail.
Selfish migrants: How a meiotic driver is selected to increase dispersal

Meiotic drivers are selfish genetic elements that manipulate meiosis to increase their transmission to the next generation to the detriment of the rest of the genome. One example is the t haplotype in house mice, which is a naturally occurring meiotic driver with deleterious traits—poor fitness in polyandrous matings and homozygote inviability or infertility—that prevent its fixation. Recently, we discovered and validated a novel effect of t in a long-term field study on free-living wild house mice and with experiments: t-carriers are more likely to disperse. Here, we ask what known traits of the t haplotype can select for a difference in dispersal between t-carriers and wildtype mice. To that end, we built individual-based models with dispersal loci on the t and the homologous wildtype chromosomes. We also allow for density-dependent expression of these loci. The t haplotype consistently evolves to increase the dispersal propensity of its carriers, particularly at high densities. By examining variants of the model that modify different costs caused by t, we show that the increase in dispersal is driven by the deleterious traits of t, disadvantage in polyandrous matings and lethal homozygosity or male sterility. Finally, we show that an increase in driver-carrier dispersal can evolve across a range of values in driver strength and disadvantages.