Miracle-dz/UniFAR-FTUs huggingface dataset:
Temporal and environmental factors interact with rootstock genotype to shape leaf elemental composition in grafted grapevines

Plants take up elements through their roots and transport them to their shoot systems for use in numerous biochemical, physiological, and structural functions. Elemental composition of above-ground plant tissues, such as leaves, reflects both above- and below-ground activities of the plant genotype, as well the local environment. Perennial, grafted plants, where the root system of one individual is fused to the shoot system of a genetically distinct individual, offer a powerful experimental system in which to study the role of the root system in the elemental composition of the shoot system. We measured elemental composition of over 7000 leaves in the grapevine cultivar ‘Chambourcin’ growing ungrafted and grafted to three rootstock genotypes. Leaves were collected over multiple years and phenological stages (across the season) and along a developmental time series. Temporal components of this study had the largest effect on leaf elemental composition; and rootstock genotype interacted with year, phenological stage, and leaf age to differentially modulate leaf elemental composition. Further, the local, above-ground environment affected leaf elemental composition, an effect influenced by rootstock genotype. This work highlights the dynamic nature by which root systems interact with shoot systems to respond to temporal and environmental variation.
A tale of two connectivities: intra- and inter-subject functional connectivity jointly enable better prediction of social abilities

Naturalistic functional magnetic resonance imaging (fMRI) paradigms, such as movie viewing, are attracting increased attention, given their ability to mimic the real-world cognitive demands on attention and multimodal sensory integration. Moreover, naturalistic paradigms allow for characterizing brain network responses associated with dynamic social cognition in a model-free manner using inter-subject functional connectivity (ISFC). While intra-subject functional connectivity (FC) characterizes the individual’s brain functional architecture, ISFC characterizes the neural coupling driven by time-locked extrinsic dynamic stimuli across individuals. Here, we hypothesized that ISFC and FC provide distinct and complementary information about individual differences in social cognition. To test this hypothesis, we examined a public movie-viewing fMRI dataset with 32 healthy adults and 90 typically developing children. Building three partial least squares regression (PLS) models to predict social abilities using FC and/or ISFC, we compared predictive performance to determine whether combining two connectivity measures could improve the prediction accuracy of individuals’ social-cognitive abilities measured by a Theory of Mind (ToM) assessment. Our results indicated that the joint model (ISFC+FC) yielded the highest predictive accuracy and significantly predicted individuals’ social cognitive abilities (rho = 0.34, p < 0.001). We also confirmed that the improved accuracy was not due to the increased feature dimensionality. In conclusion, we demonstrated that intra-/inter-subject connectivity encodes unique information about social abilities, and a joint investigation could help us gain a more complete understanding of the complex processes supporting social cognition.
Hrq1/RECQL4 regulation is critical for preventing aberrant recombination during DNA intrastrand crosslink repair and is upregulated in breast cancer

Human RECQL4 is a member of the RecQ family of DNA helicases and functions during DNA replication and repair. RECQL4 mutations are associated with developmental defects and cancer. Although RECQL4 mutations lead to disease, RECQL4 overexpression is also observed in cancer, including breast and prostate. Thus, tight regulation of RECQL4 protein levels is crucial for genome stability. Because mammalian RECQL4 is essential, how cells regulate RECQL4 protein levels is largely unknown. Utilizing budding yeast, we investigated the RECQL4 homolog, HRQ1, during DNA crosslink repair. We find that Hrq1 functions in the error-free template switching pathway to mediate DNA intrastrand crosslink repair. Although Hrq1 repairs cisplatin-induced lesions, it is paradoxically degraded by the proteasome following cisplatin treatment. By identifying the targeted lysine residues, we show that preventing Hrq1 degradation results in increased recombination and mutagenesis. Like yeast, human RECQL4 is similarly degraded upon exposure to crosslinking agents. Furthermore, over-expression of RECQL4 results in increased RAD51 foci, which is dependent on its helicase activity. Using bioinformatic analysis, we observe that RECQL4 overexpression correlates with increased recombination and mutations. Overall, our study uncovers a role for Hrq1/RECQL4 in DNA intrastrand crosslink repair and provides further insight how misregulation of RECQL4 can promote genomic instability, a cancer hallmark.
Nonlinear micro finite element models based on digital volume correlation measurements predict early microdamage in newly formed bone

Bone regeneration in critical-sized defects is a clinical challenge, with biomaterials under constant development aiming at enhancing the natural bone healing process. The delivery of bone morphogenetic proteins (BMPs) in appropriate carriers represents a promising strategy for bone defect treatment but optimisation of the spatial-temporal release is still needed for the regeneration of bone with biological, structural, and mechanical properties comparable to the native tissue. Nonlinear micro finite element (μFE) models can address some of these challenges by providing a tool able to predict the biomechanical strength and microdamage onset in newly formed bone when subjected to physiological or supraphysiological loads. Yet, these models need to be validated against experimental data. In this study, experimental local displacements in newly formed bone induced by osteoinductive biomaterials subjected to in situ X-ray computed tomography compression in the apparent elastic regime and measured using digital volume correlation (DVC) were used to validate μFE models. Displacement predictions from homogeneous linear μFE models were highly correlated to DVC-measured local displacements, while tissue heterogeneity capturing mineralisation differences showed negligible effects. Nonlinear μFE models improved the correlation and showed that tissue microdamage occurs at low apparent strains. Microdamage seemed to occur next to large cavities or in biomaterial-induced thin trabeculae, independent of the mineralisation. While localisation of plastic strain accumulation was similar, the amount of damage accumulated in these locations was slightly higher when including material heterogeneity. These results demonstrate the ability of the nonlinear μFE model to capture local microdamage in newly formed bone tissue and can be exploited to improve the current understanding of healing bone and mechanical competence. This will ultimately aid the development of BMPs delivery systems for bone defect treatment able to regenerate bone with optimal biological, mechanical, and structural properties.
Beyond resource selection: emergent spatio-temporal distributions from animal movements and stigmergent interactions

A principal concern of ecological research is to unveil the causes behind observed spatio-temporal distributions of species. A key tactic is to correlate observed locations with environmental features, in the form of resource selection functions or other correlative species distribution models. In reality, however, the distribution of any population both affects and is affected by those surrounding it, creating a complex network of feedbacks causing emergent spatio-temporal features that may not correlate with any particular aspect of the underlying environment. Here, we study the way in which the movements of populations in response to one another can affect the spatio-temporal distributions of ecosystems. We construct a stochastic individual-based modelling (IBM) framework, based on stigmergent interactions (i.e. organisms leave marks which cause others to alter their movements) between and within populations. We show how to gain insight into this IBM via mathematical analysis of a partial differential equation (PDE) system given by a continuum limit. We show how the combination of stochastic simulations of the IBM and mathematical analysis of PDEs can be used to categorise emergent patterns into homogeneous vs. heterogeneous, stationary vs. perpetually-fluctuating, and aggregation vs. segregation. In doing so, we develop techniques for understanding spatial bifurcations in stochastic IBMs, grounded in mathematical analysis. Finally, we demonstrate through a simple example how the interplay between environmental features and between-population stigmergent interactions can give rise to predicted spatial distributions that are quite different to those predicted purely by accounting for environmental covariates.
Assessing temporal and geographic contacts across the Adriatic Sea through the analysis of genome-wide data from Southern Italy

Southern Italy was characterised by a complex prehistory that started with different Palaeolithic cultures, later followed by the Neolithic transition and the demic dispersal from the Pontic-Caspian Steppe during the Bronze Age. Archaeological and historical evidence points to demic and cultural influences between Southern Italians and the Balkans, starting with the initial Palaeolithic occupation until historical and modern times. To shed light on the dynamics of these contacts, we analysed a genome-wide SNP dataset of more than 700 individuals from the South Mediterranean area (102 from Southern Italy), combined with ancient DNA from neighbouring areas. Our findings revealed high affinities of South-Eastern Italians with modern Eastern Peloponnesians, and a closer affinity of ancient Greek genomes with those from specific regions of South Italy than modern Greek genomes. The higher similarity could be associated with the presence of a Bronze Age component ultimately originating from the Caucasus and characterised by high frequencies of Iranian and Anatolian Neolithic ancestries. Furthermore, to reveal possible signals of natural selection, we looked for extremely differentiated allele frequencies among Northern and Southern Italy, uncovering putatively adapted SNPs in genes involved in alcohol metabolism, nevi features and immunological traits, such as ALDH2, NID1 and CBLB.
Stereochemistry of transient protein-protein interactions in a signaling hub: exploring G3BP1-mediated regulation of CFTR deubiquitination

Intrinsically disordered proteins (IDPs) can coordinate often transient or weak interactions with multiple proteins to mediate complex signals within large, reversible protein networks. Among these, the IDP hub protein G3BP1 forms protein complexes with Caprin1 and USP10, and the resulting control of USP10 activity plays an important role in a pathogenic virulence system that targets CFTR endocytic recycling. However, while the identities of protein interactors are known for many of these IDP hub proteins, the relationship between pairwise affinities and the extent of protein recruitment and activity is not well understood. Here we describe in vitro analysis of the G3BP1 affinities, and show that substitution of G3BP1 residues F15 or F33 to tryptophan reduces affinity for both the USP10 and Caprin1 motif peptides. These same mutations significantly reduce formation of complexes by the full-length proteins. The crystal structure of G3BP1 TripleW (F15W/F33W/F124W) mutant reveals a clear reorientation of the side chain of W33, creating a steric clash with the USP10 and Caprin1 peptides. An amino-acid scan of the USP10 and Caprin1 motif peptides reveals similarities and differences in the ability to substitute residues in the core motifs as well as specific mutations with the potential to create higher affinity peptides. Taken together, these data show that small changes in 1:1 binding affinity can have significant effects on the composition of cellular interaction hubs. These specific protein mutations can be harnessed to manipulate complex protein networks, informing future investigations into roles of these networks in cellular processes.
Rule-based habitat suitability modelling for the reintroduction of the grey wolf (Canis lupus) in Scotland

Though native to Scotland, the grey wolf (Canis lupus) was extirpated c.250 years ago as part of a global eradication drive. The global population has recently expanded, now occupying 67% of its former range. Evidence is growing that apex predators provide a range of ecological benefits, most stemming from the reduction of overgrazing by deer – something from which Scotland suffers. In this study, we build a rule-based habitat suitability model for wolves on the Scottish mainland. From existing literature, we identify the most important variables as land cover, prey density, road density and human density, and establish thresholds of suitability for each. Fuzzy membership functions are used to assign suitability values to each variable, followed by fuzzy overlay to combine all four: a novel approach to habitat suitability modelling for terrestrial mammals. Model sensitivity is tested for land cover and prey density, as these variables constitute a knowledge gap and an incomplete dataset, respectively. The Highlands and Grampian mountains emerge strongly and consistently as the most suitable areas, largely due to high negative covariance between prey density and road/human density. Sensitivity testing reveals the models are fairly robust to changes in prey density, but less robust to changes in the scoring of land cover, with the latter altering the distribution of land mainly through the 70 – 100% suitability range. However, in statistical significance tests, only the least and most generous versions of the model emerge as giving significantly different results. Depending on the version of the model, a contiguous area of between 10,139km2 and 18,857km2 is shown to be 80 to 100% suitable. This could be sufficient to support between 50 and 94 packs of four wolves, if the average pack range size is taken to be 200km2. We conclude that in terms of habitat availability, reintroduction should be feasible.
The periplasmic chaperone Skp prevents misfolding of the secretory lipase A from Pseudomonas aeruginosa

Pseudomonas aeruginosa is a wide-spread opportunistic human pathogen and a high-risk factor for immunodeficient people and patients with cystic fibrosis. The extracellular lipase A belongs to the virulence factors of P. aeruginosa. The lipase undergoes folding and activation in the periplasm prior the secretion. Here, we demonstrate that the ubiquitous periplasmic chaperone Skp of P. aeruginosa, but not SurA, FkpA, PpiD or YfgM, efficiently prevents misfolding of the aggregation-prone lipase A and facilitates its activation by a specific foldase LipH. Small-angle X-ray scattering visualizes the trimeric architecture of P. aeruginosa Skp and identifies two primary conformations of the chaperone, a compact and a widely open. We describe two binding modes of Skp to the lipase, with affinities of 20 nM and 2 μM, which correspond to 1:1 and 1:2 stoichiometry of the lipase:Skp complex. Two Skp trimers are required to stabilize the lipase via the apolar interactions, which are not affected by high salt concentrations typical for the sputum of cystic fibrosis patients. The chaperoning effect of Skp points to its potent role in maturation and secretion of the lipase in Pseudomonas species.
Early Tactile Stimulation Influences the Development of Alzheimer Disease in Gestationally Stressed APP NL-G-F Adult Offspring NL-G-F/NL-G-F mice

Alzheimer Disease (AD) is associated with cerebral plaques and tangles, reduced synapse number, and shrinkage in several brain areas and these morphological effects are associated with the onset of compromised cognitive, motor, and anxiety-like behaviours. The focus of this study was to examine the effect of neonatal tactile stimulation on AD-like behavioural and neurological symptoms on APP NL-G-F/NL-G-F mice, a mouse model of AD. Our findings indicate that neonatal tactile stimulation improves cognition, motor skills, and anxiety-like symptoms in both gestationally stressed and non-stressed adult APP mice and that these alterations are associated with reduced Aβ plaque formation. Thus, tactile stimulation appears to be a promising non-invasive preventative strategy for slowing the onset of dementia in aging animals.
Genome-wide association and genomic prediction of resistance to Flavobacterium columnare in a farmed rainbow trout population

Columnaris disease is an emerging disease affecting farmed rainbow trout (Oncorhynchus mykiss) globally. In aquaculture breeding, genomic selection has been increasingly used to improve traits that are difficult to measure on candidate fish (such as disease resistance traits). Following a natural outbreak of columnaris disease, 3,054 exposed fish and their 81 parents (33 dams and 48 sires) were genotyped with the 57K SNP Axiom™ trout genotyping array. Genetic parameters of host resistance (measured as a binary survival trait) were estimated, a genome wide association study was performed, and the accuracy of pedigree-based and genomic prediction was estimated. After quality controls, 2,874 challenged fish (1,403 dead fish and 1,471 alive fish) and 78 parents genotyped for 27,907 SNPs remained. Pedigree based heritability was estimated to be 0.18 and 0.35 on the observed and underlying scale, respectively. Genomic heritability was estimated to be 0.21 and 0.43 on the observed and underlying scale, respectively. A quantitative trait loci (QTL) was detected on chromosome Omy3, significant at the genome-wide level, along with several suggestive QTLs on two other chromosomes. The additive effect on mortality proportion of the peak SNP from Omy3 was estimated to be 0.11 (0.018; se). Pedigree-based prediction accuracy was 0.59, and the use of genomic evaluation increased the prediction accuracy by at least 13.6%. Using the second iteration of a weighted genomic-based evaluation increased the prediction accuracy by 18.6% compared to the pedigree-based model. These results suggest that resistance is a suitable target trait for genetic improvement by selective breeding, and genomic selection may be a useful approach to speed up this process.
Turning the head while biking makes older people lose cycling direction and balance

Background Bike safety in older subjects is a major concern in multiple countries given the strong increase in the number of cyclists that are admitted to the hospital due to single-sided bicycle accidents in older populations. The increase in single-sided accident rate in older subjects suggests that older adults have more difficulty controlling balance while bicycling in traffic, which has been related to various age-related changes in the sensorimotor system. Yet, the impact of these age-related sensorimotor deficits on the ability of older people to remain stable on their bike during traffic situations such as turning their upper body to check on potential road users, remains unknown. Methods We instructed a group of 40 young (22.86 ± 1.53 years) and 41 older participants (62.73 ± 1.57 years) to bike in a straight line while performing a shoulder check movement in order to identify the color of an object presented behind them. We recorded the task-errors (lost balance, errors in identifying the color, cycling outside the lane) and computed the steering angle and rotation of the frame, pelvis and torso from IMU recordings. Results We observed that older adults made task-errors (one third of the older participants failed at the task by making errors such as cone-identification errors, loss of balance and cycling outside the lane). In the successful trials, we observed an increase in steering angle and rotation of the pelvis with respect to the frame in the older subjects compared to the young subjects. Significance Older cyclists lose balance while turning their head, which might contribute to the increased number of single sided bike accidents in older subjects. The use of simple devices, such as using a mirror, should be encouraged in older subjects to replace the shoulder check maneuver.
Genomic resolution of cryptic species diversity in chipmunks

Discovery of cryptic species is essential to understanding the process of speciation and assessing the impacts of anthropogenic stressors. Here, we used genomic data to test for cryptic species diversity within an ecologically well-known radiation of North American rodents, western chipmunks (Tamias). We assembled a de novo reference genome for a single species (Tamias minimus) combined with new and published targeted sequence-capture data for 21,551 autosomal and 493 X-linked loci sampled from 121 individuals spanning 22 species. We identified at least two cryptic lineages corresponding with an isolated subspecies of least chipmunk (T. minimus grisescens) and with a restricted subspecies of the yellow-pine chipmunk (T. amoenus cratericus) known only from around the extensive Craters of the Moon lava flow. Additional population-level sequence data revealed that the so-called Crater chipmunk is a distinct species that is abundant throughout the coniferous forests of southern Idaho. This cryptic lineage does not appear to be most closely related to the ecologically and phenotypically similar yellow-pine chipmunk but does show evidence for recurrent hybridization with this and other species.
In Silico Evaluation of Plant Nitrification Suppression Effects on Agroecosystem Nitrogen Loss

Nitrification regulates potential for nitrogen (N) loss from ecosystems because it converts ammonium to nitrate, which is susceptible to leaching and gaseous emissions. Crops can suppress the microbes that perform nitrification by exuding nitrification-inhibiting compounds from their roots and taking up available ammonium, the substrate for nitrification. However, the effect of nitrification suppression on agroecosystem N losses remains poorly characterized, and a lack of temporal synchrony between nitrification, N losses, and nitrification suppression by plants could limit the effect of nitrification suppression. We used the DayCent-CABBI model to evaluate the effectiveness of the suppression of nitrification by sorghum to reduce N2O emissions and nitrate leaching in an energy sorghum/soybean rotation at the Energy Farm in Urbana-Champaign, IL. We simulated nitrification suppression at the measured levels (measNS) and at the maximum measured level applied to the entire growing season (maxNS), and we also explored ways to better utilize nitrification suppression by altering the timing of UAN fertilizer applications. Model experiments showed that most nitrification occurred immediately after fertilizer was applied, whereas nitrification suppression begins to ramp up more than a month after planting. On an annual basis, measNS experiments showed a 1-2% reduction in annual N2O emissions relative to no nitrification suppression (noNS), and maxNS experiments showed a 4-9% reduction in annual N2O emissions relative to noNS. Both nitrification suppression levels showed < 1% reduction in nitrate leaching. Altering the timing of fertilizer applications to better synchronize nitrification suppression with high soil ammonium levels had mixed effects on annual N2O emissions and nitrate leaching and sometimes resulted in increased N losses. The timing of simulated N2O emissions shifted with the timing of fertilization, and N2O emissions from denitrification increased when N2O emissions from nitrification decreased. Increasing N retention during the non-growing season may be more effective and growing-season nitrification suppression for reducing annual N losses in the rainfed Midwest, particularly for NO3- leaching in the early spring. Optimizing the timing of nitrification suppression alongside off-season N retention strategies would best improve the N sustainability of agroecosystems.