Miracle-dz/UniFAR-FTUs huggingface dataset:
PICLN modulates alternative splicing and ensures adaptation to light and temperature changes in plants

Plants undergo transcriptome reprogramming to adapt to daily and seasonal fluctuations in light and temperature conditions. While most efforts have focused on the role of master transcription factors, the importance of splicing factors modulating these processes is now emerging. Efficient pre-mRNA splicing depends on proper spliceosome assembly, which in plants and animals requires the methylosome complex. PICLN is part of the methylosome complex in both humans and Arabidopsis thaliana, and we show here that the human PICLN ortholog rescues phenotypes of A. thaliana picln mutants. Altered photomorphogenic and photoperiodic responses in A. thaliana picln mutants are associated with changes in pre-mRNA splicing, which partially overlap with those in prmt5 mutants. Mammalian PICLN also acts in concert with the Survival Motor Neuron (SMN) complex component GEMIN2 to modulate the late steps of UsnRNP assembly, and many alternative splicing events regulated by PICLN but not PROTEIN-ARGININE METHYL TRANSFERASE 5 (PRMT5), the main protein of the methylosome, are controlled by A. thaliana GEMIN2. As with GEMIN2 and SME1/PCP, low temperature, which increases PICLN expression, aggravates morphological and molecular defects of picln mutants. Taken together, these results establish a key role for PICLN in the regulation of pre-mRNA splicing and in mediating plant adaptation to daily and seasonal fluctuations in environmental conditions.
Isospin-symmetry-breaking corrections to superallowed Fermi β decay: Radial excitations

Based on an exact formalism, we study the effects of isospin-symmetry-breaking interactions on superallowed 0{sup +}{yields}0{sup +} transitions. We calculate the second-order renormalization of the Fermi matrix element due to radial contributions and show that radial excitations neglected in the treatment of Towner and Hardy are significant. These are estimated to decrease the isospin-symmetry-breaking corrections. Our results provide a correction term that can be included in existing approaches.
Ultracold Lithium-6 Atoms in the BEC-BCS Crossover: Experiments and the Construction of a New Apparatus

We use a fermionic gas of Lithium-6 as a model system to study superfluidity. The limiting cases of superfludity are Bose-Einstein condensation (BEC) and superconductivity, described by the theory by Bardeen, Cooper and Schrieffer (BCS). In Lithium-6 gases, we can explore the whole range between the two cases, known as the BEC-BCS crossover, using a Feshbach resonance. We study the change of the momentum distribution of the gas in this crossover and compare to theoretical models. We also investigate the hydrodynamic expansion, characteristic for a superfluid gas. We observe a sudden change of the ellipticity of the gas close to the transition to the superfluid phase. Moreover, we localized heteronuclear Feshbach resonances between Li-6 and Li-7. We are currently constructing a second generation of the experimental setup. An new laser system, based on high power laser diodes, was developed. Changes in the vacuum chamber, including a complete reconstruction of the Zeeman slower, have increased the atomic flux, allowing us to increase the repetition rate of our experiment. Modifications of the geometry of the magnetic traps lead to a higher number of trapped atoms.
Total ozone content changes associated to solar dynamo magnetic field variations.

There are some evidences that support the occurrence of total ozone content changes by high energetic particle flux intensity variations. In turn, these last are strongly linked to sudden commencement storms (SSC ́s). Therefore, an analysis of total ozone content in selected ground stations, radiative input and SSC index yearly means time series, the last defined as the product of the ampli tude by the duration time of each storm, is performed. It is found that long-term ozone variations are mostly related to SSC index long-term variations in all the stations, with different behaviours that depend on geographical location. In particular, the strong decrease of total ozone content during cycle 22 is related to the very high SSC values that occurred during that sunspot cycle and is remarkably strong in Faraday and Halley Bay stations. In all the stations the minimum in total ozone content long term variation is reached around 1993 and is followed by an steady increase, that would continue along the forthcoming years following the descending chaotic transition that solar global magnetic field dynamo system started around 1993.
Neural network and kinetic modelling of human genome replication reveal replication origin locations and strengths

In human and other metazoans, the determinants of replication origin location and strength are still elusive. Origins are licensed in G1 phase and fired in S phase of the cell cycle, respectively. It is debated which of these two temporally separate steps determines origin efficiency. Experiments can independently profile mean replication timing (MRT) and replication fork directionality (RFD) genome-wide. Such profiles contain information on multiple origins’ properties and on fork speed. Due to possible origin inactivation by passive replication, however, observed and intrinsic origin efficiencies can markedly differ. Thus, there is a need for methods to infer intrinsic from observed origin efficiency, which is context-dependent. Here, we show that MRT and RFD data are highly consistent with each other but contain information at different spatial scales. Using neural networks, we infer an origin licensing landscape that, when inserted in an appropriate simulation framework, jointly predicts MRT and RFD data with unprecedented precision and underlies the importance of dispersive origin firing. We furthermore uncover an analytical formula that predicts intrinsic from observed origin efficiency combined with MRT data. Comparison of inferred intrinsic origin efficiencies with experimental profiles of licensed origins (ORC, MCM) and actual initiation events (Bubble-seq, SNS-seq, OK-seq, ORM) show that intrinsic origin efficiency is not solely determined by licensing efficiency. Thus, human replication origin efficiency is set at both the origin licensing and firing steps. Author Summary DNA replication is a vital process that produces two identical replicas of DNA from one DNA molecule, ensuring the faithful transmission of genetic information from mother to daughter cells. The synthesis of new DNA strands initiates at multiple sites, termed replication origins, propagates bidirectionally, and terminates by merging of converging strands. Replication initiation continues in unreplicated DNA but is blocked in replicated DNA. Experiments have only given partial information about origin usage. In this work we reveal the exact propensity of any site to initiate replication along human chromosomes. First, we simulate the DNA replication process using approximate origin information, predict the direction and time of replication at each point of the genome, and train a neural network to precisely recover from the predictions the starting origin information. Second, we apply this network to real replication time and direction data, extracting the replication initiation propensity landscape that exactly predicts them. We compare this landscape to independent origin usage data, benchmarking them, and to landscapes of protein factors that mark potential origins. We find that the local abundance of such factors is insufficient to predict replication initiation and we infer to which extent other chromosomal cues locally influence potential origin usage.
Arnold Diusion of the Discrete Nonlinear Schrodinger Equation

In this article, we prove the existence of Arnold diusion for an in- teresting specic system { discrete nonlinear Schrodinger equation. The proof is for the 5-dimensional case with or without resonance. In higher dimensions, the problem is open. Progresses are made by establishing a complete set of Melnikov-Arnold integrals in higher and innite dimensions. The openness lies at the concrete computation of these Melnikov-Arnold integrals. New ma- chineries introduced here into the topic of Arnold diusion are the Darboux transformation and isospectral theory of integrable systems.
Study of Multiple Rounds of Error Correction in Solid State NMR QIP

Institute for Quantum Computing, University of WaterlooPerimeter Institute for Theoretical Physics, Waterloo, Ontario andDepartment of Physics and Astronomy, University of Waterloo(Dated: March 24, 2011)Methods to control errors will be essential for quantum information processing. It is widelybelieved that fault-tolerant quantum error correction is the leading contender to achieve this goal.Although the theory of fault-tolerant quantum error correction is very well understood, experimentalimplementation has been lagging. We study the feasibility of implementing repeated rounds ofquantum error correction with refreshed ancillas in solid state nuclear magnetic resonance (NMR). In particular we study the procedure proposed for extracting entropy that consists of two stages;an error correcting code optimized to function at nite temperature, and an implementation ofheat-bath algorithmic cooling to refresh the ancilla qubits. Two algorithms are presented whichimplement this method, one for performing tests on 4 qubits, the other for practical implementationon 6 qubits. The e ects of imperfect implementation are examined in both the error correction andrefreshing stages.I. INTRODUCTION
The Effects of Behaviorally‐Based Diet Education and Tai‐Chi on Dietary Intake and Resiliency in Community Dwelling Older Adults

Resilience is the ability to recover after a physical, emotional, financial, or social challenge. Limited research exists on the impact of dietary and physical activity interventions on resiliency. Fifty‐four obese, older women were recruited at two senior centers for a 16‐week community‐based intervention study that implemented a modified Dietary Approaches to Stop Hypertension (DASH) diet and Tai Chi (TC) exercise. At baseline, participants’ mean age was 68.2±7.7 years, with BMI of 35.4±4.3 kg/m2, and total cholesterol of 200.7±33.1 mg/dL. The mean Dietary Screening Tool (DST) score was 67.3±10.6 and the mean physical resiliency scale score was 12.96 ± 2.09. Significance was set at p<0.05. There was no significant difference at baseline between waitlist control (WC) and intervention (DASH‐TC) participants in any of the reported variables. One‐way repeated measures ANOVA comparing baseline to post‐intervention was significant for total DST score, BMI, waist circumference, systolic and diastolic blood pressure, and glucose; all with a large effect size. There was no significant interaction effect between WC and DASH‐TC groups in terms of physical resiliency; this may be related to a possible Hawthorne effect. The combination of DASH diet plus TC didn't seem to impact resiliency in this population. However, further research is needed to verify these results in larger, more diverse populations.
Internal determinants of university student employability. Construction and validation of scales

One of the challenges faced by European universities today is to ensure that their graduates find employment in line with their attributes. Graduate employability depends, among other factors, on many internal determinants in individuals. However, there is no consensus on how to measure them, and the scales developed to date have not been properly validated. The purpose of this paper is to construct and validate, at confirmatory level, a set of instruments for measuring the internal determinants of graduate employability. The results, based on a sample of 816 students, show the structure of the scales resulting from checking content validity, dimensionality, reliability, and convergent, discriminant and nomological validity.
A new model for intravital microscopy of the murine pulmonary microcirculation

Intravital microscopy (IVM) is the gold standard for in vivo investigations of the microcirculation. The availability of transgenic animals has propelled the development of murine IVM models for various organs, but not yet for the lung. We report a new IVM model for studies of the murine pulmonary microcirculation.
Yogurt intake is associated with favorable nutrient intake and healthy body measures in US women: Results from NHANES 2007–08

This study examined the intake of yogurt in American women and studied the association with nutrient intake and body measures. The study used 1‐day dietary recall from NHANES 2007–08 for women ages 20+ (n=2,672). The study population was classified as either a yogurt eater (n=193, 7%) or a non‐yogurt eater (n=2479, 93%). Women who reported eating yogurt on 1+ occasion during the 1‐day recall were classified as yogurt eaters. Women who ate yogurt had significantly higher intakes of protein, vit. D, calcium, potassium, and magnesium, compared to non‐yogurt eaters (p<0.05). Forty‐two percent of yogurt eaters had Adequate Intake (AI) of calcium compared to only 24% of non‐yogurt eaters (p=0.0009). After adjusting for covariates, among yogurt eaters, BMI was lower by 1.3 kg/m2 (p=0.03), waist circumference was lower by 3.5 cm (p=0.02), body fat was lower by 1.5% (p=0.03) and waist‐to‐height ratio was lower by 2% (p=0.02) than non‐yogurt eaters. These data suggest that consumption of yogurt, as part of an overall healthy diet, may help adult women manage body weight and contribute to improved intakes of essential nutrients.
Simplified numerical methods for gasdynamic systems on triangulated domains

This dissertation considers simplified finite element and finite volume discretization techniques for first-order systems of conservation laws equipped with a convex (entropy) extension. Using newly developed techniques in entropy symmetrization theory, simplified forms of the Galerkin least-squares (GLS) and the discontinuous Galerkin (DG) finite element method are developed and analyzed. The use of symmetrization variables yields numerical schemes which inherit global entropy stability properties of the PDE system. Central to the development of the simplified GLS and DG methods is the Eigenvalue Scaling Theorem which characterizes right symmetrizers of an arbitrary first-order hyperbolic system in terms of scaled eigenvectors of the corresponding flux Jacobian matrices. A constructive proof is provided for the Eigenvalue Scaling Theorem with detailed consideration given to the Euler, Navier-Stokes, and magnetohydrodynamic (MHD) equations. Linear and nonlinear energy stability is proven for the simplified GLS and DG methods. Spatial convergence properties of the simplified GLS and DG methods are numerical evaluated via the computation of Ringleb flow on a sequence of successively refined triangulations. Next, simplified upwind finite volume methods are developed for conservation law systems. Specifically considered are generalizations of Godunov's method to high order accuracy and triangulated domains. A number of simplified linear reconstruction operators are discussed based on Green-Gauss formulas as well as least-squares approximation. Several theoretical results using maximum principle analysis are then presented for the upwind finite volume method with data reconstruction. Additional calculations of subsonic, transonic, and supersonic Euler and MHD flow are presented to evaluate the spatial accuracy and feature resolution capability of the simplified DG, GLS, and finite volume discretizations. It is concluded from the dissertation research that substantial simplification of the GLS and DG finite element methods is possible by exploiting properties of the Eigenvalue Scaling Theorem. Numerical evidence shows essentially optimal order spatial convergence rates of these simplified methods without disrupting the pleasing energy properties of symmetric variable formulations. It is also concluded that a substantial simplification of the upwind finite volume method is possible by using simplified linear data reconstruction techniques. A range of numerical calculations confirm the favorable properties of these simplified methods.
Structure‐function studies of ADPGlucose Pyrophosphorylase from Thermodesulfovibrio yellowstonii: Probing the Role of the C‐terminus in Allosteric Regulation

Starch serves as both a critical food source and an important biodegradable and renewable carbon source for biofuel and other industries including adhesives, packaging material, and cosmetics. ADP‐glucose pyrophosphorylase (ADPG PPase, glgC gene product) is the key enzyme that is responsible for the rate‐limiting step of both glycogen and starch biosynthesis in bacteria and plants, catalyzing the conversion of glucose‐1‐phosphate and ATP to ADPG and pyrophosphate. Thermodesulfovibrio yellowstonii (Td. y) is a thermophilic sulfate‐reducing bacterium that was isolated from geothermal vents in Yellowstone National Park. Little is known about this ADPG PPase which displays increased heat stability, salt tolerance, and altered regulation compared to other ADPG PPase family members. The Td.y enzyme is substantially activated by phosphoenolpyruvate (PEP), which differs from many other ADPG PPases, as well as G6P, 3PGA, and sulfate. These properties could contribute to biomass production in different crop environments. Multiple sequence alignments have shown deviations from consensus residues in the N‐terminal allosteric region and C‐terminal region of the Td.y ADPG PPase. Two of the more interesting differences are at positions 365 and 397, which have been shown to be involved in allosteric regulation of other ADPG PPases, as part of a conserved region in the enzyme family and associated with plant enzymes, respectively. The K365G and R397A enzymes were generated by site‐directed mutagenesis as a first step in probing structure‐function relationships. We hypothesize that the positively charged lysine at 365 and arginine at 397 may contribute to PEP binding and activation. The altered proteins were purified to homogeneity by a procedure that included two hydroxyapatite chromatography steps followed by size exclusion chromatography. Initial kinetic studies revealed that the K365G protein displayed a lower Vmax (~25% of wild‐type [WT]) but ~2‐fold higher apparent affinity for ATP in the absence of effectors. In contrast to the WT, which was activated over 3‐fold by PEP, the K365G enzyme only exhibited ~10% activation by PEP and a decrease in apparent affinity for ATP. Conversely, the K365G enzyme was activated 2.6 fold by sulfate, an effector which has a much smaller effect on the Vmax of WT. In the absence of effectors, the R397A displayed a similar apparent affinity for ATP compared to WT but a 24 fold decrease in Vmax. In the presence of PEP, R397A exhibited lower apparent affinity for ATP and a Vmax decreased ~42 fold. The response of this enzyme to G6P was very similar to WT. The results so far support the hypothesis that K365 and R397 are critical for PEP activation while also influencing other allosteric properties. Complete kinetic analyses of the K365G and R397A enzymes as well as crystallization trials are underway.
Simulation of surface flows on a droplet in an oscillating pressure field

The surface flows on a droplet in an oscillating pressure field are simulated numerically by solving the Navier-Stokes equations using the Arbitrary Lagrangian-Eulerian and level set coupled method. Detailed transient flow fields in and around the droplet are calculated by performing parallel computations, and the flow phenomena in a thin layer around the droplet surface are discussed. The recirculation flow region is found to be formed at the top and bottom stagnation points on the droplet surface. It is also found that the oscillating flow with a phase shift appears in the thin layer along the droplet surface. Keywords—Surface flow, Droplet, Oscillating pressure, Arbitrary Lagrangian-Eulerian method, Level set method.
Equational Theories of Boolean Functions

Several noteworthy classes of Boolean functions are characterized by algebraic identities. For a given DNF-specified class, such characteristic identities exist if and only if the class is closed under the operation of forming Boolean minors by variable identification. A single identity suffices to characterize a class if and only if the number of forbidden identification minors minimal in a specified sense is finite. If general first-order sentences are allowed instead of identities only, then essentially all classes can be described by an appropriate set of sentences.
Learning from invariants predicts upcoming behavioral choice from spiking activity in monkey V1

Animals frequently make decisions based on sensory cues. In such a setting, the overlap in the information on the stimulus and on the choice is crucial for the formation of informed behavioral decisions. Yet, how the information on the stimulus and on the choice interact in the brain is poorly understood. Here, we study the representation of a binary decision variable in the primary visual cortex (V1) while macaque monkeys perform delayed match-to-sample task on naturalistic visual stimuli close to psychophysical threshold. Using population vectors, we demonstrate the overlap in decoding spaces on binary stimulus classes “match/non-match” and binary choices “same /different” of the animal. Leveraging this overlap, we use learning from the invariant information across the two classification problems to predict the choice of the animal as a time-dependent population signal. We show the importance of the across-neuron organization and the temporal structure of spike trains for the decision signal and suggest how noise correlations between neurons with similar decoding selectivity are helpful for the accumulation of the decision signal. Finally, we show that decision signal is primarily carried by bursting neurons in the superficial layers of the cortex. Author summary V1 is necessary for normal visual processing and is known to process features of visual stimuli such as orientation, but whether V1 also encodes behavioral decisions is an unresolved issue, with conflicting evidence. Here, we demonstrate that V1 encodes a mixed variable that contains the information about the stimulus as well as about the choice. We learn the structure of population responses in trials pertaining to the variable “stimulus+choice”, and apply the resulting population vectors to trials that differ only about the choice of the animal, but not about the stimulus class. Moreover, we learn structure of population responses on time-averaged data and then apply it on time-dependent (spiking) data. During the late phase of the trial, this procedure allows to predict the upcoming choice of the animal with a time-dependent population signal. The spiking signal of small neural population is sparse, and we hypothesize that positive correlations between neurons in the same decoding pool help the transmission of the decision-related information downstream. We find that noise correlations in the same decoding pool are significantly stronger than across coding pools, which corroborates our hypothesis on the benefit of noise correlations for the read-out of a time-dependent population signal.