Miracle-dz/UniFAR-FTUs huggingface dataset:
Fluorescent protein lifetimes report increased local densities and phases of nuclear condensates during embryonic stem cell differentiation

Fluorescent proteins (FP) are frequently used for studying proteins inside cells. In advanced fluorescence microscopy, FPs can report on additional intracellular variables. One variable is the local density near FPs, which can be useful in studying densities within cellular bio-condensates. Here, we show that a reduction in fluorescence lifetimes of common monomeric FPs reports increased levels of local densities. We demonstrate the use of this fluorescence-based variable to report the distribution of local densities within heterochromatin protein 1α (HP1α) in mouse embryonic stem cells (ESCs), before and after early differentiation. We find that local densities within HP1α condensates in pluripotent ESCs are heterogeneous and cannot be explained by a single liquid phase. Early differentiation, however, induces a change towards a more homogeneous distribution of local densities, which can be explained as a liquid-like phase. In conclusion, we provide a fluorescence-based method to report increased local densities and apply it to distinguish between homogeneous and heterogeneous local densities within bio-condensates.
Variational graph encoders: a surprisingly effective generalist algorithm for holistic computer-aided drug design

While there has been significant progress in molecular property prediction in computer-aided drug design, there is a critical need to have fast and accurate models. Many of the currently available methods are mostly specialists in predicting specific properties, leading to the use of many models side-by-side that lead to impossibly high computational overheads for the common researcher. Henceforth, the authors propose a single, generalist unified model exploiting graph convolutional variational encoders that can simultaneously predict multiple properties such as absorption, distribution, metabolism, excretion and toxicity (ADMET), target-specific docking score prediction and drug-drug interactions. Considerably, the use of this method allows for state-of-the-art virtual screening with an acceleration advantage of up to two orders of magnitude. The minimisation of a graph variational encoder’s latent space also allows for accelerated development of specific drugs for targets with Pareto optimality principles considered, and has the added advantage of explainability.
Growth increases but regeneration declines in response to warming and drying at Arctic treeline in white spruce (Picea glauca)

As a temperature-delineated boundary, the Arctic treeline is predicted to shift northward in response to warming. However, the evidence for northward movement is mixed, with some sections of the treeline advancing while others remain stationary or even retreat. To identify the drivers of this variation, we need a landscape-level understanding of the interactions occurring between climate, tree growth, and population regeneration. In this study, we assessed regeneration alongside annual tree growth and climate during the 20th century. We used an ageheight model combined with tree height from aerial lidar to predict the age structure of 38,652 white spruce trees across 250 ha of Arctic treeline in the central Brooks Range, Alaska, USA. We then used age structure analysis to interpret the trends in regeneration and tree-ring analysis to interpret changes in annual tree growth. The climate became significantly warmer and drier circa 1975, coinciding with divergent responses of regeneration and tree growth. After 1975, regeneration of saplings (trees ≤ 2m tall) decreased compared to previous decades whereas annual growth in mature trees (trees >2m tall) increased by 54% (p<0.0001, Wilcoxon test). Tree-ring width was positively correlated with May-August temperature (p<0.01, Pearson coefficient) during the 20th century. However, after circa 1950, the positive correlation between temperature and growth weakened (i.e., temperature divergence) while the positive correlation with July precipitation strengthened (p<0.01, Pearson coefficient), suggesting that continued drying may limit future growth at this section of Arctic treeline. We conclude that while warmer temperatures appear to benefit annual growth in mature trees, the warmer and drier environmental conditions in spring and summer inhibit regeneration and therefore may be inhibiting the northward advance at this Arctic treeline site. Researchers should consider the interactions between temperature, water availability, and tree age when examining the future of treeline and boreal forest in a changing climate.
Habitual exercise evokes fast and persistent adaptation during split-belt walking

Changing movement patterns in response to environmental perturbations is a critical aspect of gait and is related to reducing the energetic cost of the movement. Exercise improves energetic capacity for submaximal exercise and may affect how people adapt movement to reach an energetic minimum. The purpose of this study was to determine whether self-reported exercise behavior influences gait adaptation in young adults. Young adults who met the optimal volume of exercise according to the Physical Activity Guidelines for Americans (MOVE; n=19) and young adults who did not meet the optimal volume of exercise (notMOVE; n=13) walked on a split-belt treadmill with one belt moving twice the speed of the other belt for 10 minutes. Step length asymmetry (SLA) and mechanical work done by each leg were measured. Nonlinear mixed effects models compared the time course of adaptation between MOVE and notMOVE, and t-tests compared net work at the end of adaptation between MOVE and notMOVE. Compared to notMOVE, MOVE had a faster initial response to the split belt treadmill, and continued to adapt over the duration of split-belt treadmill walking. Young adults who engage in sufficient amounts of exercise responded more quickly to the onset of a perturbation, and throughout the perturbation they continued to explore movement strategies, which might be related to reduction of energetic cost. Our findings provide insights into the multisystem positive effects of exercise, including walking adaptation.
MammoTab: A Giant and Comprehensive Dataset for Semantic Table Interpretation

In this paper, we present MammoTab , a dataset composed of 1M Wikipedia tables extracted from over 20M Wikipedia pages and annotated through Wikidata. The lack of this kind of datasets in the state-of-the-art makes MammoTab a good resource for testing and training Semantic Table Interpretation approaches. The dataset has been designed to cover several key challenges, such as disambiguation, homonymy, and NIL-mentions. The dataset has been evaluated using MTab, one of the best approaches of the SemTab challenge.
LEAST-SQUARES NEURAL NETWORK (LSNN) METHOD FOR LINEAR ADVECTION-REACTION EQUATION: GENERAL DISCONTINUOUS INTERFACE

We studied the least-squares ReLU neural network method (LSNN) for solving linear advection-reaction equation with discontinuous solution in [Cai, Zhiqiang, Jingshuang Chen, and Min Liu. ”Least-squares ReLU neural network (LSNN) method for linear advection-reaction equation. ” Journal of Computational Physics 443 (2021): 110514]. The method is based on the least-squares formulation and employs a new class of approximating functions: multilayer perceptrons with the rectiﬁed linear unit (ReLU) activation function, i.e., ReLU deep neural networks (DNNs). In this paper, we ﬁrst show that ReLU DNN with depth (cid:100) log 2 ( d + 1) (cid:101) + 1 can approximate any d -dimensional step function on arbitrary discontinuous interfaces with any prescribed accuracy. By decomposing the solution into continuous and discontinuous parts, we prove theoretically that discretization error of the LSNN method using DNN with depth (cid:100) log 2 ( d + 1) (cid:101) + 1 is mainly determined by the continuous part of the solution provided that the solution jump is constant. Numerical results for both two and three dimensional problems with various discontinuous interfaces show that the LSNN method with enough layers is accurate and does not exhibit the common Gibbs phenomena along interfaces.
From Heuristics to Language Models: A Journey Through the Universe of Semantic Table Interpretation with DAGOBAH

This paper presents DAGOBAH SL 2022, a semantic table interpretation system that has been continuously improved over the last four years when participating in the SemTab challenge. This year, we have improved the lookup coverage using external resources and we have integrated language models for better understanding the table headers. We have also implemented various system optimizations that lead to a reduction in execution time of about 30%. In this paper, we also show the relevance of using deep learning-based approaches for resolving certain ambiguities and we discuss the limitations of existing corpora and systems for maturing further this research field
s-elBat: A Semantic Interpretation Approach for Messy taBle-s

This paper describes s-elBat , a Semantic Table Interpretation approach. The approach inherits and improves the part of the techniques belonging to the MantisTable , an approach used and tested in previous editions of the SemTab challenge. s-elBat adds an innovative and optimised lookup approach for generating candidate entities for the annotation.
Towards an Approach Based on Knowledge Graph Refinement for Tabular Data to Knowledge Graph Matching

This paper presents our contribution to the Accuracy Track of Semantic Web Challenge on Tabular Data to Knowledge Graph Matching (SemTab). This contribution consists of the proposition of an approach based on knowledge graph refinement for tabular data annotation. Internal methods were used to predict the links between cells in the table and external methods were used to predict missing entities and relations. This approach was applied to the annotation of HardTables and ToughTables using DBpedia and Wikidata; and GitTables and BiodivTab using DBpedia and Schema.org. During Round 3 of the competition, we were ranked third and second position respectively for the annotation of GitTables and BiodivTab.
Flagged Schur Polynomial Duality via a Lattice Path Bijection

This paper proves an identity between flagged Schur polynomials, giving a duality between row flags and column flags. This identity generalises both the binomial determinant duality theorem due to Gessel and Viennot and the symmetric function duality theorem due to Aitken. As corollaries we obtain the lifts of the binomial determinant duality theorem to \(q\)-binomial coefficients and to symmetric polynomials. Our method is a path counting argument on a novel lattice generalising that used by Gessel and Viennot.
Functional differences in cerebral activation between slow wave-coupled and uncoupled sleep spindles

Spindles are often temporally coupled to slow waves (SW). These SW-spindle complexes have been implicated in memory consolidation that involves transfer of information from the hippocampus to the neocortex. However, spindles and SW, which are characteristic of NREM sleep, can occur as part of this complex, or in isolation. It is not clear whether dissociable parts of the brain are recruited when coupled to SW vs. when spindles or SW occur in isolation. Here, we tested differences in cerebral activation time-locked to uncoupled spindles, uncoupled SW and coupled SW-spindle complexes using simultaneous EEG-fMRI. Consistent with the “active system model,” we hypothesized that brain activations time-locked to coupled SW-spindles would preferentially occur in brain areas known to be critical for sleep-dependent memory consolidation. Our results show that coupled spindles and uncoupled spindles recruit distinct parts of the brain. Specifically, we found that hippocampal activation during sleep is not uniquely related to spindles. Rather, this process is primarily driven by SWs and SW-spindle coupling. In addition, we show that SW-spindle coupling is critical in the activation of the putamen. Importantly, SW-spindle coupling specifically recruited frontal areas in comparison to uncoupled spindles, which may be critical for the hippocampal-neocortical dialogue that preferentially occurs during sleep.
Predictors of everyday functional impairment in older patients with schizophrenia: A cross-sectional study

Objective This study investigates the prevalence of everyday functional impairment among older adults with schizophrenia and builds a predictive model of functional decline. Methods A total of 113 hospitalized older patients enrolled in this study. Functional impairment is defined according to the Functional Activities Questionnaire (FAQ). Patients who scored <9 could function independently daily, while those who scored ≥9 had problems in everyday functional activities. Data collected include sociodemographic characteristics, depressive symptoms, social support, and physical comorbidities, which were classified according to the eight anatomical systems of the human body. Results The sample comprised 75% female participants with a mean age of 63.74 ± 7.42 years old. A total of 33.6% had a functional impairment, while cognitive impairment was present in 63.7%. Independent participants had better urinary system and respiratory system health (P < 0.05). After adjusting for the potential confounders of age, disease course, physical comorbidities, psychiatric symptoms, the ability to independently carry out daily activities, and cognitive function, we found that impaired everyday function is associated with poor cognition, depressive symptoms, first admission, psychiatric symptoms (especially positive symptoms), ADL, and respiratory and urinary system diseases. Conclusion Everyday functional capacity is predicted by disease course, admission time, cognition, depressive symptoms, severity of psychosis, ability to carry out daily activities, and respiratory and urinary system health status. Urinary system diseases contribute significantly to the prediction of impaired function. Future studies should focus on health status, drug use, and everyday functional recovery in older patients with schizophrenia.
Antifungal activity of eco-safe nanoemulsions based on Nigella sativa oil against Penicillium verrucosum infecting maize seeds: Biochemical and physiological traits

The main goals of the present investigation were to develop O/W nanoemulsion fungicides based on cold-pressed Nigella sativa (black seed) oil to prevent Penicillium verrucosum infection of maize seeds and to test their antifungal activity against this fungus. Additionally, the effect of these nanoemulsions on plant physiological parameters was also investigated. Two nonionic surfactants namely Tween 20 and Tween 80 were used as emulsifying agents in these formulations. The effect of sonication time and surfactant type on the mean droplet size, polydispersity index (PDI), and zeta potential of the nanoemulsions were determined by dynamic light scattering (DLS). Results indicated that both sonication time and emulsifier type had pronounced effects on the stability of O/W nanoemulsions with a small particle size range (168.6–345.3 nm), acceptable PDI (0.181–0.353), and high zeta potential (−27.24 to –48.82 mV). Tween 20 showed superior stability compared to Tween 80 nanoemulsions. The in vitro results showed that complete inhibition of P. verrucosum-growth was obtained by 10_T80 and 10_T20 nanoemulsions at 100% concentration. All nanoemulsions had increment effects on maize seed germination by 101% in the case of 10_T20 and 10_T80 compared to untreated seeds or the chemical fungicide treatment. Nanoemulsions (10_T20 and 10_T80) were able to stimulate root and shoot length as compared to the fungicide treatment. Seed treatment with 10_T80 nanoemulsion showed the highest AI and protease activity by 75 and 70%, respectively, as compared to the infected control. The produced nanoemulsions might provide an effective protectant coating layer for the stored maize seeds.
The binding pocket properties were fundamental to functional diversification of the GDSL-type esterases/lipases gene family in cotton

Cotton is one of the most important crops in the world. GDSL-type esterases/lipases (GELPs) are widely present in all kingdoms and play an essential role in regulating plant growth, development, and responses to abiotic and biotic stresses. However, the molecular mechanisms underlying this functional diversity remain unclear. Here, based on the identification of the GELP gene family, we applied genetic evolution and molecular simulation techniques to explore molecular mechanisms in cotton species. A total of 1502 GELP genes were identified in 10 cotton species. Segmental duplication and differences in evolutionary rates are the leading causes of the increase in the number and diversity of GELP genes during evolution for ecological adaptation. Structural analysis revealed that the GELP family has high structural diversity. Moreover, molecular simulation studies have demonstrated significant differences in the properties of the binding pockets among cotton GELPs. In the process of adapting to the environment, GELPs not only have segmental duplication but also have different evolutionary rates, resulting in gene diversity. This diversity leads to significant differences in the 3D structure and binding pocket properties and, finally, to functional diversity. These findings provide a reference for further functional analyses of plant GELPs.
Exploring the effects of risk-taking, exploitation, and exploration on divergent thinking under group dynamics

This study examined the effects of risk-taking and exploitation/exploration trade-off on divergent thinking in individuals, dyads, and triads. We adopted a simple Q-learning model to estimate risk attitudes, exploitation, and exploration parameters. The results showed that risk-taking, exploitation, and exploration did not affect divergent thinking in dyads. Instead, loss aversion was negatively related to divergent thinking. In contrast, risk attitudes and the inverse temperature as a ratio between exploitation and exploration were significant but with contrasting effects in individuals and triads. For individuals, risk-taking, exploitation and loss aversion played a critical role in divergent thinking. For triads, risk aversion and exploration were significantly related to divergent thinking. However, the results also indicated that balancing risk with exploitation/exploration and loss aversion is critical in enhancing divergent thinking in individuals and triads when learning coherence emerges. These results could be interpreted consistently with related literature such as the odd-vs. even-numbered group dynamics, knowledge diversity in group creativity, and representational change theory in insight problem-solving.
Identification of PLATZ genes in Malus and expression characteristics of MdPLATZs in response to drought and ABA stresses

Plant AT-rich sequences and zinc-binding proteins (PLATZ) play crucial roles in response to environmental stresses. Nevertheless, PLATZ gene family has not been systemically studied in Rosaceae species, such as in apple, pear, peach, or strawberry. In this study, a total of 134 PLATZ proteins were identified from nine Rosaceae genomes and were classified into seven phylogenetic groups. Subsequently, the chromosomal localization, duplication, and collinearity relationship for apple PLATZ genes were investigated, and segmental duplication is a major driving-force in the expansion of PLATZ in Malus. Expression profiles analysis showed that PLATZs had distinct expression patterns in different tissues, and multiple genes were significantly changed after drought and ABA treatments. Furthermore, the co-expression network combined with RNA-seq data showed that PLATZ might be involved in drought stress by regulating ABA signaling pathway. In summary, this study is the first in-depth and systematic identification of PLATZ gene family in Rosaceae species, especially for apple, and provided specific PLATZ gene resource for further functional research in response to abiotic stress.
Transcriptome and QTL mapping analyses of major QTL genes controlling glucosinolate contents in vegetable- and oilseed-type Brassica rapa plants

Glucosinolates (GSLs) are secondary metabolites providing defense against pathogens and herbivores in plants, and anti-carcinogenic activity against human cancer cells. Profiles of GSLs vary greatly among members of genus Brassica. In this study, we found that a reference line of Chinese cabbage (B. rapa ssp. pekinensis), ‘Chiifu’ contains significantly lower amounts of total GSLs than the oilseed-type B. rapa (B. rapa ssp. trilocularis) line ‘LP08’. This study aimed to identify the key regulators of the high accumulation of GSLs in Brassica rapa plants using transcriptomic and linkage mapping approaches. Comparative transcriptome analysis showed that, in total, 8,276 and 9,878 genes were differentially expressed between ‘Chiifu’ and ‘LP08’ under light and dark conditions, respectively. Among 162 B. rapa GSL pathway genes, 79 were related to GSL metabolism under light conditions. We also performed QTL analysis using a single nucleotide polymorphism-based linkage map constructed using 151 F5 individuals derived from a cross between the ‘Chiifu’ and ‘LP08’ inbred lines. Two major QTL peaks were successfully identified on chromosome 3 using high-performance liquid chromatography to obtain GSL profiles from 97 F5 recombinant inbred lines. The MYB-domain transcription factor gene BrMYB28.1 (Bra012961) was found in the highest QTL peak region. The second highest peak was located near the 2-oxoacid-dependent dioxygenase gene BrGSL-OH.1 (Bra022920). This study identified major genes responsible for differing profiles of GSLs between ‘Chiifu’ and ‘LP08’. Thus, our study provides molecular insights into differences in GSL profiles between vegetative- and oilseed-type B. rapa plants.
Silent peripheral neuropathy determined by high-resolution ultrasound among contacts of patients with Hansen's disease

Introduction Hansen's disease (HD) primarily infects peripheral nerves, with patients without HD being free of peripheral nerve damage. Household contacts (HHCs) of patients with HD are at a 5–10 times higher risk of HD than the general population. Neural thickening is one of the three cardinal signs that define a case of HD according to WHO guidelines, exclusively considering palpation examination that is subjective and may not detect the condition in the earliest cases even when performed by well-trained professionals. High-resolution ultrasound (HRUS) can evaluate most peripheral nerves, a validated technique with good reproducibility allowing detailed and accurate examination. Objective This study aimed to use the peripheral nerve HRUS test according to the HD protocol as a diagnostic method for neuropathy comparing HHCs with healthy volunteers (HVs) and patients with HD. Methods In municipalities from 14 different areas of Brazil we selected at random 83 HHC of MB-patients to be submitted to peripheral nerve ultrasound and compared to 49 HVs and 176 HD-patients. Results Household contacts assessed by HRUS showed higher median and mean absolute peripheral nerve cross-sectional area (CSA) values and greater asymmetries (ΔCSA) compared to HVs at the same points. Median and mean absolute peripheral nerve CSA values were higher in patients with HD compared to HCCs at almost all points, while ΔCSA values were equal at all points. Mean ± SD focality (ΔTpT) values for HHCs and patients with HD, respectively, were 2.7 ± 2.2/2.6 ± 2.2 for the median nerve, 2.9 ± 2.7/3.3 ± 2.9 for the common fibular nerve (p > 0.05), and 1.3 ± 1.3/2.2 ± 3.9 for the ulnar nerve (p < 0.0001). Discussion Considering HRUS findings for HHCs, asymmetric multiple mononeuropathy signs (thickening or asymmetry) in at least 20% of the nerves evaluated could already indicates evidence of HD neuropathy. Thus, if more nerve points are assessed in HHCs (14 instead of 10), the contacts become more like patients with HD according to nerve thickening determined by HRUS, which should be a cutting-edge tool for an early diagnosis of leprosy cases.