Miracle-dz/UniFAR-FTUs huggingface dataset:
Pre-conditioning Strategies for Mesenchymal Stromal/Stem Cells in Inflammatory Conditions of Livestock Species

Mesenchymal stem/stromal cells (MSCs) therapy has been a cornerstone of regenerative medicine in humans and animals since their identification in 1968. MSCs can interact and modulate the activity of practically all cellular components of the immune response, either through cell-cell contact or paracrine secretion of soluble mediators, which makes them an attractive alternative to conventional therapies for the treatment of chronic inflammatory and immune-mediated diseases. Many of the mechanisms described as necessary for MSCs to modulate the immune/inflammatory response appear to be dependent on the animal species and source. Although there is evidence demonstrating an in vitro immunomodulatory effect of MSCs, there are disparate results between the beneficial effect of MSCs in preclinical models and their actual use in clinical diseases. This discordance might be due to cells' limited survival or impaired function in the inflammatory environment after transplantation. This limited efficacy may be due to several factors, including the small amount of MSCs inoculated, MSC administration late in the course of the disease, low MSC survival rates in vivo, cryopreservation and thawing effects, and impaired MSC potency/biological activity. Multiple physical and chemical pre-conditioning strategies can enhance the survival rate and potency of MSCs; this paper focuses on hypoxic conditions, with inflammatory cytokines, or with different pattern recognition receptor ligands. These different pre-conditioning strategies can modify MSCs metabolism, gene expression, proliferation, and survivability after transplantation.
Weed dynamics and production efficiency of rice-based cropping system

Field experiments were conducted during 2007–08 and 2008–09 to study weed dynamics and production efficiency under diversified and intensified rice based cropping systems in Kymore Plateau and Satpura Hills Zone of Madhya Pradesh. Among the all 12 rice based cropping systems under Kharif, in rice Echinochloa crusgalli was the most dominating weed contributing 32.8% of total weed intensity at most critical period (25 DAT) while Monochoria vaginalis at harvest stage (18.8%). During Rabi, relative density of weeds varied between different crops. In early (30.2 to 43.3%) and at harvest stage (10.1 to 46.8%) Medicago denticulata was found to be more serious weed almost in all Rabi crops grown under different cropping systems but in onion and garlic Portulaca oleracea having higher intensity at harvest stage (45.2%). The Portulaca spp. predominantly infested to all summer crops at early (41.5 to 54.6%) and harvest stage (37.2 to 44.1%). In rice varieties the weed intensity and biomass ranged from 229.0 to 254.2/m2 and 1.0 to 1.15 t/ha under different crop systems respectively. During Rabi, weed intensity was higher in vegetable pea (207.3/m2) and weed biomass was higher berseem (0.71 t/ha). During summer season, the weed intensity was maximum (156.4/m2) in okra which resulted into the highest weed biomass production (0.67 t/ha). Both rice and wheat crops grown under rice–wheat system require large quantity of irrigation water which is favourable to build up a typical weed infestation problem. All diversified and intensified cropping systems significantly led to record higher production efficiency (83.13kg/ha/day to 57.05kg/ha/day) beneficial to minimize the serious challenges posed by the weeds as compared to both existing cropping systems viz., rice-wheat (45.63kg/ha/day) and rice-chickpea (39.49kg/ha/day).
Economic and Conservation Evaluation of Capital Renovation Projects: Cameron County Irrigation District No. 2 (San Benito) – Interconnect Between Canals 39 and 13-A1 and Replacement of Rio Grande Diversion Pumping Plant

xiv Bureau of Reclamation’s Endorsement of RGIDECON . xv Executive Summary . xv
Assessing behavioral sex differences to chemical cues of predation risk while provisioning nestlings in a hole-nesting bird

Birds can assess nest predation risk and adjust their parental activity accordingly. Risk taking behavior should be related to investment in reproduction as well as to confidence in parenthood that often differ between sexes. In those cases, sexual differences in risk taking behavior may be expected. For example, in blue tits, females invest more time and energy than males in nest-building, egg laying and incubation. Furthermore, confidence in parenthood is supposed to be higher for females, as extrapair paternity is common in this species. Therefore, the reproductive value of nestlings may be higher for females than for males and the former may assume greater risks to ensure nestling growth and maximize their reproductive success. We examined potential sexual differences in the risk assumed by parents in relation to perceived risk of predation inside the nest cavity, where predation risk perception may be higher. We increased perceived predation risk by adding predator chemical cues inside blue tit (Cyanistes caeruleus) nest-boxes, and we tested whether female and male parents differed in the risk assumed when taking care of nestlings. Females and males did not differ in the risk assumed in response to perceived predation risk. However, females reduced time devoted to nest sanitation activities when predator chemical cues were detected inside the nest-box, likely as an anti-predatory strategy to minimize their own risk of predation. Therefore, these results add to the evidence that birds can detect chemical cues of predators inside the nest cavity and suggest that the behavioral response to an increase in risk of predation perceived through olfactory cues is not sex-dependent in blue tit.
Decomposing predictability to identify dominant causal drivers in complex ecosystems

Ecosystems are complex systems of various physical, biological, and chemical processes. Since ecosystem dynamics are composed of a mixture of different levels of stochasticity and nonlinearity, handling these data is a challenge for existing methods of time-series based causal inferences. Here we show that, by harnessing contemporary machine learning approaches, the concept of Granger causality can be effectively extended to the analysis of complex ecosystem time series and bridge the gap between dynamical and statistical approaches. The central idea is to use an ensemble of fast and highly predictive artificial neural networks to select a minimal set of variables that maximizes the prediction of a given variable. It enables decomposition of the relationship among variables through quantifying the contribution of an individual variable to the overall predictive performance. We show how our approach, EcohNet, can improve interaction network inference for a mesocosm experiment and simulated ecosystems. The application of the method to a long-term lake monitoring dataset yielded new but interpretable results on the drivers causing cyanobacteria blooms, which is a serious threat to ecological integrity and ecosystem services. Since performance of EcohNet is enhanced by its predictive capabilities, it also provides an optimized forecasting of overall components in ecosystems. EcohNet could be used to analyze complex and hybrid multivariate time series in many scientific areas not limited to ecosystems. Significance Statement Effective use of ecosystem monitoring data to resolve global environmental issues is a major challenge of the 21st century ecology. A promising solution to address this challenge is a time-series-based causal analysis which can provide insight on the mechanical links between ecosystem components. In this work, a model-free framework named EcohNet is proposed. EcohNet utilizes ensemble predictions of echo state networks, which are known to be fast, accurate, and highly relevant for a variety of dynamical systems, and can robustly predict causal networks of ecosystem components. It also can provide an optimized forecasting of overall ecosystem components, and could be used to analyze complex and hybrid multivariate time series in many scientific areas, not limited to ecosystems.
Glucagon‐like peptide‐1 receptor differentially controls mossy cell activity across the dentate gyrus longitudinal axis

Understanding the role of dentate gyrus (DG) mossy cells (MCs) in learning and memory has rapidly evolved due to increasingly precise methods for targeting MCs and for in vivo recording and activity manipulation in rodents. These studies have shown MCs are highly active in vivo, strongly remap to contextual manipulation, and that their inhibition or hyperactivation impairs pattern separation and location or context discrimination. Less well understood is how MC activity is modulated by neurohormonal mechanisms, which might differentially control the participation of MCs in cognitive functions during discrete states, such as hunger or satiety. In this study, we demonstrate that glucagon‐like peptide‐1 (GLP‐1), a neuropeptide produced in the gut and the brain that regulates food consumption and hippocampal‐dependent mnemonic function, might regulate MC function through expression of its receptor, GLP‐1R. RNA‐seq demonstrated that most, though not all, Glp1r in hippocampal principal neurons is expressed in MCs, and in situ hybridization revealed strong expression of Glp1r in hilar neurons. Glp1r‐ires‐Cre mice crossed with Ai14D reporter mice followed by co‐labeling for the MC marker GluR2/3 revealed that almost all MCs in the ventral DG expressed Glp1r and that almost all Glp1r‐expressing hilar neurons were MCs. However, only ~60% of dorsal DG MCs expressed Glp1r, and Glp1r was also expressed in small hilar neurons that were not MCs. Consistent with this expression pattern, peripheral administration of the GLP‐1R agonist exendin‐4 (5 μg/kg) increased cFos expression in ventral but not dorsal DG hilar neurons. Finally, whole‐cell patch‐clamp recordings from ventral MCs showed that bath application of exendin‐4 (200 nM) depolarized MCs and increased action potential firing. Taken together, this study adds to known MC activity modulators a neurohormonal mechanism that may preferentially affect ventral DG physiology and may potentially be targetable by several GLP‐1R pharmacotherapies already in clinical use.
A brain-wide analysis maps structural evolution to distinct anatomical module

The vertebrate brain is highly conserved topologically, but less is known about neuroanatomical variation between individual brain regions. Neuroanatomical variation at the regional level is hypothesized to provide functional expansion, building upon ancestral anatomy needed for basic functions. Classically, animal models used to study evolution have lacked tools for detailed anatomical analysis that are widely used in zebrafish and mice, presenting a barrier to studying brain evolution at fine scales. In this study, we sought to investigate the evolution of brain anatomy using a single species of fish consisting of divergent surface and cave morphs, that permits functional genetic testing of regional volume and shape across the entire brain. We generated a high-resolution brain atlas for the blind Mexican cavefish Astyanax mexicanus and coupled the atlas with automated computational tools to directly assess variability in brain region shape and volume across all populations. We measured the volume and shape of every grossly defined neuroanatomical region of the brain and assessed correlations between anatomical regions in surface fish, cavefish, and surface × cave F2 hybrids, whose phenotypes span the range of surface to cave. We find that dorsal regions of the brain are contracted, while ventral regions have expanded, with F2 hybrid data providing support for developmental constraint along the dorsal-ventral axis. Furthermore, these dorsal-ventral relationships in anatomical variation show similar patterns for both volume and shape, suggesting that the anatomical evolution captured by these two parameters could be driven by similar developmental mechanisms. Together, these data demonstrate that A. mexicanus is a powerful system for functionally determining basic principles of brain evolution and will permit testing how genes influence early patterning events to drive brain-wide anatomical evolution.
Place cells are non-randomly clustered by field location in CA1 hippocampus

A challenge in both modern and historic neuroscience has been achieving an understanding of neuron circuits, and determining the computational and organizational principles that underlie these circuits. Deeper understanding of the organization of brain circuits and cell types, including in the hippocampus, is required for advances in behavioral and cognitive neuroscience, as well as for understanding principles governing brain development and evolution. In this manuscript, we pioneer a new method to analyze the spatial clustering of active neurons in the hippocampus. We use calcium imaging and a rewarded navigation task to record from 100s of place cells in the CA1 of freely moving rats. We then use statistical techniques developed for and in widespread use in geographic mapping studies, global Moran’s I and local Moran’s I to demonstrate that cells that code for similar spatial locations tend to form small spatial clusters. We present evidence that this clustering is not the result of artifacts from calcium imaging, and show that these clusters are primarily formed by cells that have place field around previously rewarded locations. We go on to show that, although cells with similar place fields tend to form clusters, there is no obvious topographic mapping of environmental location onto the hippocampus, such as seen in the visual cortex. Insights into hippocampal organization, as in this study, can elucidate mechanisms underlying motivational behaviors, spatial navigation, and memory formation.
First assessment of Iranian pomegranate germplasm using targeted metabolites and morphological traits to develop the core collection and modeling of the current and future spatial distribution under climate change conditions

Pomegranate has been considered a medicinal plant due to its rich nutrients and bioactive compounds. Since environmental conditions affect the amount and composition of metabolites, selecting suitable locations for cultivation would be vital to achieve optimal production. In this study, the diversity of targeted metabolites and morphological traits among 152 Iranian pomegranate genotypes was evaluated to establish a core collection. The multivariate analyses were conducted including principal component analysis (PCA), and cluster analysis. In addition, the current and future geographical distribution of pomegranate in Iran was predicted to identify suitable locations using the MaxEnt model. The results showed high diversity in the studied morphological and metabolic traits. The PCA results indicated that FFS, NFT, JA, and AA are the most important traits in discriminating the studied genotypes. A constructed core collection using maximization strategy consisted of 20 genotypes and accounted for 13.16% of the entire collection. Shannon-Weaver diversity index of a core collection was similar or greater than the entire collection. Evaluation of the core collection using four parameters of MD, VD, CR, and VR also indicated the maintenance of the genetic diversity of the original set. According to the MaxEnt model, altitude, average temperature of coldest quarter, and isothertmality were the key factors for the distribution of pomegranate. The most suitable areas for pomegranate cultivation were also determined which were located in arid and semi-arid regions of Iran. The geographic distribution of pomegranate in the future showed that the main provinces of pomegranate cultivation would be less affected by climatic conditions by the middle of the century. The results of this study provide valuable information for selection of elite genotypes to develop the breeding programs to obtain the cultivars with the highest levels of metabolic compounds for pharmaceutical purposes, as well as identification of the most suitable agro-ecological zones for orchard establishment.
Carbon Dots Boost dsRNA Delivery in Plants and Increase Local and Systemic siRNA Production

Carbon dots (CDs) have been proposed for nucleic acid delivery in many biological applications. In this work we have obtained carbon dots by a hydrothermal synthesis method for developing nanocomposites with dsRNA. These CDs were produced using glucose or saccharose as the nucleation source and passivated with branched polyethyleneimines for conferring positive charges. Hydrodynamic analyses and transmission electron microscopy TEM showed that they sized on average 4 and 5 nm, depending on the sugar. The CDs were fluorescent and showed a peak at 468 nm when excited with UV light. Physicochemical characteristics of their surfaces were revealed by X-ray photoelectron spectroscopy (XPS) and Fourier transform infrared spectroscopy (FT-IR). The ζ potential determined that both types of CDs had positive charges as well as good electrophoretic mobility and conductivity. Coating of the CDs to dsRNA was efficient but did not protect from nucleases. DsRNA naked or coated with the CDs were delivered to leaves of cucumber plants by spraying at 2.5 bar. Quantitation of the dsRNA that entered the leaves showed that when coated with the CDs, 50-fold more dsRNA was detected than when naked dsRNA was applied. Moreover, specific siRNAs derived from the sprayed dsRNAs were 130 times more abundant when the dsRNA was coated with the CDs. Systemic dsRNAs were determined in distal leaves showing a dramatic increase in concentration when delivered as a nanocomposite. Similarly, systemic siRNAs were significantly more abundant in distal leaves when spraying with the CD-dsRNA nanocomposite. Furthermore, FITC-labeled dsRNA was shown to accumulate in the apoplast and increase its entry in the plant when coated with CDs. These results indicate that CDs obtained by hydrothermal synthesis are suitable for dsRNA foliar delivery in RNAi plant applications and provide insight into CD-dsRNA translocations.
Hibernation shows no apparent effect on germline mutation rates in grizzly bears

A male mutation bias is observed across vertebrates, and, where data are available, this bias is accompanied by increased per-generation mutation rates with parental age. While continuing mitotic cell division in the male germline post-puberty has been proposed as the major cellular mechanism underlying both patterns, little direct evidence for this role has been found. Understanding the evolution of the per-generation mutation rate among species requires that we identify the molecular mechanisms that change between species. Here, we study the per-generation mutation rate in an extended pedigree of the brown (grizzly) bear, Ursus arctos horribilis. Brown bears hibernate for one-third of the year, a period during which spermatogenesis slows or stops altogether. The cessation of spermatogenesis is predicted to lessen the male mutation bias and to lower the per-generation mutation rate in this species. However, using whole-genome sequencing, we find that both male bias and per-generation mutation rates are the same as expected for a non-hibernating species. We also carry out a phylogenetic comparison of substitution rates along the lineage leading to brown bear and panda (a non-hibernating species) and find no slowing of the substitution rate in the hibernator. Our results contribute to accumulating evidence that suggests that male germline cell division is not the major determinant of mutation rates and mutation biases. The results also provide a quantitative basis for improved estimates of the timing of carnivore evolution.
An Isogenic Collection of Pluripotent Stem Cell Lines With Elevated α-Synuclein Expression Validated for Neural Induction and Cortical Neuron Differentiation

α-Synuclein (αSyn) is a small, disordered protein that becomes aggregated in Lewy body diseases, such as Parkinson’s disease (PD) and dementia with Lewy bodies (DLB). Human induced pluripotent stem cells (hiPSCs) potentially provide a tractable disease model to monitor early molecular changes associated with PD/DLB. We and others have previously derived hiPSC lines from patients with duplication and triplication of the SNCA gene, encoding for αSyn. It is now recognised that to perform meaningful disease modelling with these hiPSC lines, it is critical to generate isogenic control cell lines that lack the disease causing mutations. In order to complement the existing and emerging hiPSC models for PD/DLB, we have generated an allelic series of αSyn over-expressing hESC lines on the same isogenic background. An unresolved question is whether pluripotent stem cell lines, with elevated levels of αSyn, can undergo efficient differentiation into dopaminergic and cortical neurons to model PD and DLB, respectively. We took advantage of our isogenic collection of hESC lines to determine if increased expression of αSyn affects neural induction and neuronal differentiation. Clonal hESC lines with significantly different levels of αSyn expression proliferated normally and maintained expression of pluripotent markers, such as OCT4. All cell lines efficiently produced PAX6+ neuroectoderm and there was no correlation between αSyn expression and neural induction efficiency. Finally, global transcriptomic analysis of cortical differentiation of hESC lines with low or high levels of αSyn expression demonstrated robust and similar induction of cortical neuronal expression profiles. Gene expression differences observed were unrelated to neural induction and neuronal differentiation. We conclude that elevated expression of αSyn in human pluripotent stem cells does not adversely affect their neuronal differentiation potential and that collections of isogenic cell lines with differing levels of αSyn expression are valid and suitable models to investigate synucleinopathies.
CDKL5 deficiency slows synaptic vesicle endocytosis

Christiana Kontaxia,b,c, Elizabeth C. Davenporta,b,c, Peter C. Kinda,b,c, Michael A. Cousina,b,c,* aCentre for Discovery Brain Sciences, Hugh Robson Building, George Square, University of Edinburgh, Edinburgh EH8 9XD, Scotland, United Kingdom bMuir Maxwell Epilepsy Centre, Hugh Robson Building, George Square, University of Edinburgh, Edinburgh EH8 9XD, Scotland, United Kingdom cSimons Initiative for the Developing Brain, Hugh Robson Building, George Square, University of Edinburgh, Edinburgh EH8 9XD, Scotland, United Kingdom