Miracle-dz/UniFAR-FTUs huggingface dataset:
Functional characterization of a small gene family coding for putrescine hydroxycinnamoyltransferases in tomato

Phenolamides are specialized metabolites widely distributed in the plant kingdom. Their structure is composed by the association of hydroxycinnamic acid derivatives to mono-/poly-amine. This association is catalyzed by N-hydroxycinnamoyltransferases enzymes. Tomato plants are accumulating putrescine-derived phenolamides in their vegetative parts. Recently, we identified two genes coding for putrescine-hydroxycinnamoyltransferase (PHT, Solyc11g071470 and Solyc11g071480), which control the accumulation of caffeoylputrescine in tomato leaf submitted to the infestation of leafminer. In this study, we prospected for additional genes implicated in the accumulation of putrescine-derived phenolamides in the tomato vegetative organs. We identified two genes (Solyc06g074710 and Solyc11g066640) that we functionally characterized as new PHT. The substrate specificity and the expression pattern in planta was determined for the four tomato PHT. Taken together the results give a comprehensive view of the control of the putrescine-derived phenolamide accumulation in tomato plant through the biochemical specificity and the spatial expression of this small family of PHT. Main conclusion We identified and functionally characterized two new putrescine hydroxycinnamoyl transferases (PHT) in tomato. These enzymes complete a set a four PHT which control the distribution of putrescine-derived phenolamides in tomato plants.
Radiation by a probe through a substrate

Radiation by a probe through a grounded substrate layer is considered. The reaction concept is adopted and the coaxial line aperture effects are taken into account. Image theory is invoked to simplify the evaluation of the involved Sommerfeld type integrals. These integrals are computed through a real axis integration which combines numerical and analytical techniques. An interpolation method is introduced which eliminates repetitive calculation of reaction quantities. The properties of the probe such as input, mutual impedance, radiation pattern and radiation efficiency are examined as functions of substrate parameters such as thickness and dielectric constant. The probe length may be chosen to be smaller than, equal to or greater than the substrate thickness. The effect of substrate transverse magnetic (TM) surface wave modes is analyzed and it is found that at each mode cutoff omnidirectional radiation is obtained in the \bar{H} -plane with maximum radiation along the horizon. The effect of small substrate loss on the probe parameters is also considered.
Voxelwise encoding models of body stimuli reveal a representational gradient from low-level visual features to postural features in extrastriate body area

Previous research has focused on the role of the extrastriate body area (EBA) in category-specific body representation, but the specific features that are represented in this area are not well understood. This study used ultra-high field fMRI and banded ridge regression to investigate the coding of body images by comparing the performance of three encoding models in predicting brain activity in ventral visual cortex and specifically the EBA. Our results suggest that EBA represents body stimuli based on a combination of low-level visual features and postural features. Author Summary Historically, research on body representation in the brain has focused on category-specific representation, using fMRI to investigate the most posterior body selective region, the extrastriate body area (EBA). However, the role of this area in body perception is still not well understood. This study aims to clarify the role of EBA, in coding information about body images. Using ultra-high field neuroimaging (fMRI) and advanced encoding techniques we tested different computational hypotheses to understand how body images are represented in EBA. Our results suggest that EBA represents bodies using a combination of low-level properties and postural information extracted from the stimulus.
Codon language embeddings provide strong signals for protein engineering

Protein representations from deep language models have yielded state-of-the-art performance across many tasks in computational protein engineering. In recent years, progress has primarily focused on parameter count, with recent models’ capacities surpassing the size of the very datasets they were trained on. Here, we propose an alternative direction. We show that large language models trained on codons, instead of amino acid sequences, provide high-quality representations that outperform comparable state-of-the-art models across a variety of tasks. In some tasks, like species recognition, prediction of protein and transcript abundance, or melting point estimation, we show that a language model trained on codons outperforms every other published protein language model, including some that contain over 50 times more parameters. These results suggest that, in addition to commonly studied scale and model complexity, the information content of biological data provides an orthogonal direction to improve the power of machine learning in biology.
High field electron transport properties of bulk ZnO

The Monte Carlo method is used to simulate electron transport for electric field strengths up to 350 kV/cm in bulk, wurtzite structure ZnO. The relevant parts of the conduction bands of a first-principles band structure are approximated by spherically symmetric, nonparabolic valleys located at the Γ and Umin symmetry points of the Brillouin zone. It is shown that the analytic expressions represent the band structure and the density of states well over a range of nearly 5 eV from the bottom of the conduction band. The simulated electron steady-state drift velocity versus electric field characteristics are calculated for lattice temperatures of 300, 450, and 600 K. For room temperature, drift velocities higher than 3×107 cm/s are reached at fields near 250 kV/cm. Examination of the electron energy distributions shows that the strong decrease of the differential mobility with increasing electric field in the field range studied is to be associated with the pronounced nonparabolicity of the central valley and.
S0033291721000428jra 3646..3654

Background. Definition of disorder subtypes may facilitate precision treatment for posttraumatic stress disorder (PTSD). We aimed to identify PTSD subtypes and evaluate their associations with genetic risk factors, types of stress exposures, comorbidity, and course of PTSD. Methods. Data came from a prospective study of three U.S. Army Brigade Combat Teams that deployed to Afghanistan in 2012. Soldiers with probable PTSD (PTSD Checklist for Diagnostic and Statistical Manual of Mental Disorders-Fifth Edition≥31) at three months postdeployment comprised the sample (N = 423) for latent profile analysis using Gaussian mixture modeling and PTSD symptom ratings as indicators. PTSD profiles were compared on polygenic risk scores (derived from external genomewide association study summary statistics), experiences during deployment, comorbidity at three months postdeployment, and persistence of PTSD at nine months postdeployment. Results. Latent profile analysis revealed profiles characterized by prominent intrusions, avoidance, and hyperarousal (threat-reactivity profile; n = 129), anhedonia and negative affect (dysphoric profile; n = 195), and high levels of all PTSD symptoms (high-symptom profile; n = 99). The threat-reactivity profile had the most combat exposure and the least comorbidity. The dysphoric profile had the highest polygenic risk for major depression, and more personal life stress and co-occurring major depression than the threat-reactivity profile. The highsymptom profile had the highest rates of concurrent mental disorders and persistence of PTSD. Conclusions. Genetic and trauma-related factors likely contribute to PTSD heterogeneity, which can be parsed into subtypes that differ in symptom expression, comorbidity, and course. Future studies should evaluate whether PTSD typology modifies treatment response and should clarify distinctions between the dysphoric profile and depressive disorders.
Fat fractal scaling of drainage networks from a random spatial network model

An alternative quantification of the scaling properties of river channel networks is explored using a spatial network model. Whereas scaling descriptions of drainage networks previously have been presented using a fractal analysis primarily of the channel lengths, we illustrate the scaling of the surface area of the channels defining the network pattern with an exponent which is independent of the fractal dimension but not of the fractal nature of the network. The methodology presented is a fat fractal analysis in which the drainage basin minus the channel area is considered the fat fractal. Random channel networks within a fixed basin area are generated on grids of different scales. The sample channel networks generated by the model have a common outlet of fixed width and a rule of upstream channel narrowing specified by a diameter branching exponent using hydraulic and geomorphologic principles. Scaling exponents are computed for each sample network on a given grid size and are regressed against network magnitude. Results indicate that the size of the exponents are related to magnitude of the networks and generally decrease as network magnitude increases. Cases showing differences in scaling exponents with like magnitudes suggest a direction of future work regarding other topologic basin characteristics as potential explanatory variables.
Advanced Modeling and Simulation of Mechanical Responses of Nanotubes, Graphene Sheets and Carbon-based Heterostructures

The stress-strain response of pristine monolayer graphene under uniaxial loading/unloading over a more extensive size range (100 nm×100 nm) is studied by molecular dynamics simulations, which proves that graphene is perfectly elastic prior to the failure strain. Young’s modulus of graphene is calculated by selecting different strain ranges in the elastic region. It is found that Young’s modulus is strongly dependent on the strain range. When the selected strain ranges are increased from 0.5% to 8%, Young’s modulus of the armchair and zigzag graphene is reduced by approximately 60 GPa and 150 GPa, respectively. Based on the Pearson correlation coefficient method, the linearity of the stress-strain curve during graphene stretching is studied. The elastic region of the tensile curve is divided into the linear elastic region and non-linear elastic region. Simultaneously, the linear elastic limit strains for the armchair and zigzag graphene are defined to be about 2.5% and 1.5%, respectively, and they are independent of the size of graphene.On this basis, the chirality dependence and size effects of Young’smodulus, failure strain, and fracture strength of pristine monolayer graphene are investigated. The results show that Young’s modulus is dependent on the chiral angle but insensitive to size. The failure strain and fracture strength depend on the chiral angle and have obvious size effects.
Radial gradient of the solar rotation rate in the near-surface shear layer of the Sun

We study the radial gradient of the solar rotation rate in the near-surface shear layer (NSSL) from about . 950 R ⊙ to the solar surface and its variation during Solar Cycles 23 and 24 with ring-diagram analysis applied to Global Oscillation Network Group (GONG) and Helioseismic and Magnetic Imager (HMI) Dopplergrams. The average radial gradient is ∂ log Ω/∂ log r = − 1.0 ± . 1 at . 990 R ⊙ in agreement with previous studies. The average radial gradient is ∂ log Ω/∂ log r = − . 11 ± . 01 at the base of the NSSL at . 950R ⊙, while it is steeper than −1 closer to the surface between . 990R ⊙ and . 997R ⊙. The average radial gradient is rather flat within ±40° latitude from about . 970 R ⊙ to the solar surface. The radial gradient of the solar rotation rate varies with the solar cycle. At locations of high magnetic activity, the radial gradient is more negative than average from about . 970 R ⊙ to . 990 R ⊙, while in quiet regions the radial gradient is less negative than average at these depths. Close to the surface at . 997 R ⊙, this relationship appears to be reversed. Prominent features of the solar-cycle variation of large-scale flows, such as poleward branches or precursor flows, are not obviously present. The variation of the radial gradient thus more likely indicates the presence or absence of magnetic flux above a certain threshold. The temporal variations derived from the different HMI and GONG data sets agree within one error bar at most depths and latitudes, while their amplitudes might be different.
Trilateral association of autophagy, mTOR and Alzheimer’s disease: Potential pathway in the development for Alzheimer’s disease therapy

The primary and considerable weakening event affecting elderly individuals is age-dependent cognitive decline and dementia. Alzheimer’s disease (AD) is the chief cause of progressive dementia, and it is characterized by irreparable loss of cognitive abilities, forming senile plaques having Amyloid Beta (Aβ) aggregates and neurofibrillary tangles with considerable amounts of tau in affected hippocampus and cortex regions of human brains. AD affects millions of people worldwide, and the count is showing an increasing trend. Therefore, it is crucial to understand the underlying mechanisms at molecular levels to generate novel insights into the pathogenesis of AD and other cognitive deficits. A growing body of evidence elicits the regulatory relationship between the mammalian target of rapamycin (mTOR) signaling pathway and AD. In addition, the role of autophagy, a systematic degradation, and recycling of cellular components like accumulated proteins and damaged organelles in AD, is also pivotal. The present review describes different mechanisms and signaling regulations highlighting the trilateral association of autophagy, the mTOR pathway, and AD with a description of inhibiting drugs/molecules of mTOR, a strategic target in AD. Downregulation of mTOR signaling triggers autophagy activation, degrading the misfolded proteins and preventing the further accumulation of misfolded proteins that inhibit the progression of AD. Other target mechanisms such as autophagosome maturation, and autophagy-lysosomal pathway, may initiate a faulty autophagy process resulting in senile plaques due to defective lysosomal acidification and alteration in lysosomal pH. Hence, the strong link between mTOR and autophagy can be explored further as a potential mechanism for AD therapy. Graphical Abstract
Preservation characteristics and bacterial communities of crimped ensiled barley grains modulated by moisture content and additive application

Information about the relationships between preservation characteristics and main bacterial communities of fermented feeds can guide decision making during feed preservation and silage additive development. The objective was to evaluate fermentation quality, aerobic stability, microbial quality and bacterial profile of crimped barley grains ensiled under three moisture contents (MC): 228 (low MC), 287 (medium MC) and 345 (high MC) g/kg fresh matter; and using four additive treatments: 1. Control (CONT), 2. Formic and propionic acid-based additive (FPA), 3. Inoculation with homofermentative and heterofermentative strains of lactic acid bacteria (LAB), and 4. Salt-based additive (SALT). There was a quadratic effect (p < 0.05) of incremental MC on pH where greater decline happened from low (5.81) to medium (4.83) MC than from medium to high (4.28) MC, while lactic acid concentration and aerobic stability increased in a linear manner (p < 0.05). Ammonia-N and acetic acid concentrations increased quadratically (p < 0.05) with increasing levels of MC. The effects of additives depended on MC so that improvements in preservation characteristics in response to LAB and SALT were observed at medium and high MC, while FPA was effective at all MC levels. A minor shift was observed in bacterial ecology from raw material towards low MC samples, with Erwiniaceae sp. , Enterobacterales spp. and Pseudomonas dominating the fermentation. A major change occurred in medium and high MC materials, where Fructilactobacillus dominated the fermentation in CONT, FPA and SALT silages. LAB-treated silages at medium and high MC resulted in a distinguished pattern with dominance of Lentilactobacillus followed by Lactiplantibacillus. Most abundant communities in the samples, such as Fructilactobacillus, Erwiniaceae sp. , Enterobacterales spp. and Pseudomonas, were correlated with several fermentation characteristics. Our results showed that crimped barley grains could be successfully ensiled under various MC and additive treatments. Low MC feeds had higher risk to be aerobically unstable while high MC resulted in more extensive fermentation, with potentially poor fermentation quality. The suitable additive depends on the raw material characteristics as LAB and SALT require relatively high MC to be effective, while FPA showed consistent improvements over all MC levels used in the current study. Awareness of the MC of grain prior to ensiling allows to identify the risks to preservation quality and provides information for choosing an effective additive.
Burden, satisfaction caregiving, and family relations in informal caregivers of older adults

Introduction Family caregivers of older persons devote much of their time and energy to caring for another person. This exposure may burden caregivers and compromise their health and quality of life. Objective To investigate the relationship between burden, sociodemographic, caregiving, and health characteristics of informal caregivers of dependent older adults. Methods Cross-sectional and analytical study carried out in Palmas, Tocantins, Brazil, with 52 informal caregivers of older persons who need full-time help for basic living activities. Caregivers' burden was assessed by Zarit Burden Interview (ZBI). Data were analyzed using a T-test, Pearson's correlation, and Multiple Linear Regression. Results The ZBI mean score of caregivers was 26.3 points (SD = 14.6; min = 0; max = 68). Burden scores were higher among caregivers who did not receive help from other people in care (p = 0.016), reported family dysfunction (p = 0.001), and had depression symptoms (p = 0.007). A correlation was found between the scores of burdens and satisfaction with care (r = 0.76; p < 0.001) and perceived material support (r = −0.30; p = 0.40). Satisfaction with care (β: 0.61; p < 0.001) and family dysfunction (β: 8.07; p = 0.033) were significantly associated with the burden score. Conclusion Caregivers with dysfunctional families and satisfaction with the care presented the highest-burden scores. The findings reveal the need for strategies to facilitate mediation and reduce caregiver burden by strengthening the family network support or providing professional assistance.
Predictive effect of resilience on self-efficacy during the COVID-19 pandemic: The moderating role of creativity

Introduction To appraise the relationship and mechanism between resilience and self-efficacy in the context of the COVID-19 pandemic, we proposed a model to investigate the effect of resilience on self-efficacy and the moderating effect of creativity in this regard. Methods Scales that measured resilience, creative behavior, and self-efficacy were rated by 881 college students in China to establish the moderating model. Results The results showed that resilience and self-efficacy of participating college students were positively correlated, which meant that high resilience could predict a high level of self-efficacy. Moderating analysis using the SPSS PROCESS plug-in showed that creativity was an important element of resilience that positively affected self-efficacy and that this moderating effect was more significant in participants with a high degree of creativity. Discussion These findings can provide a better understanding of the relationship between resilience and self-efficacy in demonstrating the traumatic impact of the COVID-19 pandemic on adolescent mental health and academic performance.
Factors associated with critical care requirements in diabetic patients treated with dexamethasone for COVID-19 infection in the first wave of the pandemia

Introduction Diabetes mellitus (DM) and hyperglycemia are important risk factors for poor outcomes in hospitalized patients with coronavirus disease 2019 (COVID-19). The aim of the present study was to analyze the factors associated with the composite outcome of the necessity of invasive mechanical ventilation (IMV) or admission to the intensive care unit (ICU) in subjects with severe COVID-19 infection treated with dexamethasone comparing patients with DM vs. patients without DM. Research design and methods An observational retrospective cohort study was performed, including hospitalized subjects with a diagnosis of SARS-CoV-2 pneumonia. Inclusion criteria were: age ≥18 years old with severe COVID-19 disease requiring daily intravenous 6 mg dexamethasone treatment for 10 days. Exclusion criteria were: <18 years old, non-severe illness and/or patients in charge of ICU. Variables related to clinical and analytical parameters, glycemic control, acquired-hospital superinfections, mortality, IMV requirement, ICU admission and length of stay were included. Results Two hundred and nine individuals with COVID-19 disease treated with dexamethasone were included. One hundred twenty-five out of these subjects (59.8%) were patients with DM. Overall, from the 209 subjects, 66 (31.6%) required IMV or were admitted to the ICU, with significant differences between patients with DM (n=50) vs. patients without DM (n=16) (76% vs. 24%, p=0.002). Among the group of subjects with DM (n=125), those who required IMV or were admitted to the ICU showed higher serum concentrations of C-reactive protein, interleukin-6, D-dimer, ferritin and pro-calcitonin and significantly lower serum concentrations of albumin compared to those who did not require IMV or were not admitted to the ICU. Besides, between these two groups of patients with DM, we observed no differences in glycemic parameters, including median capillary blood glucose values, glycosylated hemoglobin, coefficient of variability and hypoglycemic episodes. In the multinomial analysis, factors independently associated with the composite outcome of IMV or admission to the ICU in the insulin-treated group were the National Early Warning Score (NEWS) 2 score (OR 1.55 [1.17-2.17], p=0.005) and the presence of hospital-acquired superinfections (OR 35.21 [5.11-386.99], p=0.001). Conclusions In our study, parameters related to glycemic control were not associated with IMV requirement nor admission to the ICU in patients with DM and severe COVID-19 disease receiving daily 6 mg of dexamethasone for 10 days. However, hospital-acquired superinfections and disease severity at admission were independent factors associated with this composite outcome.