Miracle-dz/UniFAR-FTUs huggingface dataset:
Fecal filtrate transfer protects against necrotizing enterocolitis in preterm pigs

Background and aims Necrotizing enterocolitis (NEC) is an acute and life-threatening gastrointestinal disorder afflicting preterm infants, which is currently unpreventable. Fecal microbiota transplantation (FMT) is a promising preventative therapy, but potential side effects raise concern. Removal of bacteria from donor fecal water may reduce side effects while maintaining wanted effects. We aimed to assess preclinical efficacy and safety of bacteria-free fecal filtrate transfer (FFT). Methods Using fecal material from healthy suckling piglets, we administered rectal FMT or cognate FFT by either rectal or oro-gastric administration to formula-fed preterm, cesarean piglets, and compared gut pathology and related safety parameters with saline controls. We then analyzed mucosa and luminal bacterial and viral composition using 16S rRNA gene amplicon and metavirome sequencing, respectively. Finally, we used isolated ileal mucosa, coupled with RNA-Seq, to gauge the host response to the different treatments. Results Oro-gastric FFT eliminated NEC, which was confirmed by microscopy, whereas FMT did not perform better than control. Moreover, FFT but not FMT reduced intestinal permeability, whereas FMT animals had reduced body weight increase and intestinal growth. Oro-gastric FFT increased viral diversity and reduced Proteobacteria abundance in ileal mucosa relative to control. Global gene expression of host mucosa responded to FMT but not FFT with increased and decreased bacterial and viral defense mechanisms, respectively. Conclusions As preterm infants are extremely vulnerable, rational therapies need incontestable safety profiles. Here we show in a clinically relevant animal model that FFT, as opposed to FMT, efficiently prevents NEC without any recognizable side effects. If translatable to preterm infants, this could lead to a change of practice and in turn a reduction in NEC burden.
Learning to play the piano with the Supernumerary Robotic 3rd Thumb

We wanted to study the ability of our brains and bodies to be augmented by supernumerary robot limbs, here extra fingers. We developed a mechanically highly functional supernumerary robotic 3rd thumb actuator, the SR3T, and interfaced it with human users enabling them to play the piano with 11 fingers. We devised a set of measurement protocols and behavioural “biomarkers”, the Human Augmentation Motor Coordination Assessment (HAMCA), which allowed us a priori to predict how well each individual human user could, after training, play the piano with a two-thumbs-hand. To evaluate augmented music playing ability we devised a simple musical score, as well as metrics for assessing the accuracy of playing the score. We evaluated the SR3T (supernumerary robotic 3rd thumb) on 12 human subjects including 6 naïve and 6 experienced piano players. We demonstrated that humans can learn to play the piano with a 6-fingered hand within one hour of training. For each subject we could predict individually, based solely on their HAMCA performance before training, how well they were able to perform with the extra robotic thumb, after training (training end-point performance). Our work demonstrates the feasibility of robotic human augmentation with supernumerary robotic limbs within short time scales. We show how linking the neuroscience of motor learning with dexterous robotics and human-robot interfacing can be used to inform a priori how far individual motor impaired patients or healthy manual workers could benefit from robotic augmentation solutions.
Somatostatin Neurons of the Bed Nucleus of Stria Terminalis Enhance Associative Fear Memory Consolidation in Mice

Excessive fear learning and generalized, extinction-resistant fear memories are core symptoms of anxiety and trauma-related disorders. Despite significant evidence from clinical studies reporting hyperactivity of the bed nucleus of stria terminalis (BNST) under these conditions, the role of BNST in fear learning and expression is still not clarified. Here, we tested how BNST modulates fear learning in male mice using a chemogenetic approach. Activation of GABAergic neurons of BNST during fear conditioning or memory consolidation resulted in enhanced cue-related fear recall. Importantly, BNST activation had no acute impact on fear expression during conditioning or recalls, but it enhanced cue-related fear recall subsequently, potentially via altered activity of downstream regions. Enhanced fear memory consolidation could be replicated by selectively activating somatostatin (SOM), but not corticotropin-releasing factor (CRF), neurons of the BNST, which was accompanied by increased fear generalization. Our findings suggest the significant modulation of fear memory strength by specific circuits of the BNST. SIGNIFICANCE STATEMENT The bed nucleus of stria terminalis (BNST) mediates different defensive behaviors, and its connections implicate its integrative modulatory role in fear memory formation; however, the involvement of BNST in fear learning has yet to be elucidated in detail. Our data highlight that BNST stimulation enhances fear memory formation without direct effects on fear expression. Our study identified somatostatin (SOM) cells within the extended amygdala as specific neurons promoting fear memory formation. These data underline the importance of anxiety circuits in maladaptive fear memory formation, indicating elevated BNST activity as a potential vulnerability factor to anxiety and trauma-related disorders.
Seed number as a function of growth. A comparative study in soybean, sunflower, and maize

Seed number, the main yield component of cereals and oil-seed species, strongly depends on the physiological status of the crop during a critical period for seed set. Using a comparative approach including three species with contrasting reproductive strategies, we investigated the relationship between seed number per plant (SNP) and plant growth rate during the critical period for seed set (PGR C ). Indeterminate soybean [Glycine max (L.) Merr. ], sunflower (Helianthus annuus L.), and maize (Zea mays L.) crops were grown under a wide range of plant densities to generate contrasting availability of resources per plant. Growth of individual plants was estimated by a novel, nondestructive method based on relationships between actual shoot dry matter and morphometric variables, including stem diameter, plant height, and dimensions of reproductive structures. Seed number per plant ranged from 0 to 890 in soybean, 0 to 4096 in sunflower, and 0 to 1348 in maize and PGR C (g d -1 ) from 0.01 to 4.3 in soybean, 0.3 to 17.6 in sunflower, and 0.4 to 12.3 in maize. Our study showed that (i) the relationship between SNP and PGR C was linear in soybean, reflecting the reproductive plasticity of this species, and curvilinear in sunflower and maize, reflecting morphogenetic restrictions to generate reproductive sinks under favorable growing conditions; (ii) the PGR C threshold below which no seed was set varied among species, being negligible in soybean, dose to 0.35 g d -1 in sunflower, and 1 g d -1 in maize. Quantitative relationships between seed number and plant growth rate during the critical period of seed set could be useful for crop modeling.
Physical activity shapes the intestinal microbiome and immunity of healthy mice but has no protective effects against colitis in MUC2-/- mice

The interactions among humans, their environment, and the trillions of microbes residing within the human intestinal tract form a tripartite relationship that is fundamental to the overall health of the host. Disruptions in the delicate balance between the intestinal microbiota and their host immunity are implicated in various chronic diseases including inflammatory bowel disease (IBD). There is no known cure for IBD, therefore, novel therapeutics targeting prevention and symptoms management are of great interest. Recently, physical activity in healthy mice was shown to be protective against chemically-induced colitis, however the benefits of physical activity during or following disease onset is not known. In this study, we examine whether voluntary wheel running is protective against primary disease symptoms in a mucin 2 deficient (Muc2-/-) life-long model of murine colitis. We show that 6 weeks of wheel running in healthy C57BL/6 mice leads to distinct changes in fecal bacteriome, increased butyrate production, and modulation in colonic gene expression of various cytokines, suggesting an overall primed anti-inflammatory state. However, these physical activity-derived benefits are not present in Muc2-/- mice harboring a dysfunctional mucosal layer from birth, ultimately showing no improvements in clinical signs. We extrapolate from our findings that while physical activity in healthy individuals may be an important preventative measure against IBD, for those with a compromised intestinal mucosa, a commonality in IBD patients, these benefits are lost.
The Challenge of Building Effective, Enterprise-scale Data Lakes

There has been a rapid rise in the popularity of data lakes as the data infrastructure for modern analytics and data science. The combination of cloud storage and fast, elastic processing provides an inexpensive and scalable solution for building analytical applications. While data lakes make it easy to ingest and store vast amounts of data, the ability to effectively make use of that data is still limited. This data often lacks context, doesn't meet the quality required for applications, and is not easily understandable or discoverable by users. Problems of data consistency and accuracy make it hard to derive value from data lakes and to trust the analytics based on this data. The traditional methods of manually documenting, classifying and assessing the data don't scale to the volume of cloud-based data lakes. New automated, learning-based approaches are required to discover, curate and make the data usable for a wide variety of users. In this talk, we describe the real-world implementation patterns of data lakes and give an overview of the many open challenges in deploying successful, enterprise-scale data lakes.
DeepGraphMol, a multi-objective, computational strategy for generating molecules with desirable properties: a graph convolution and reinforcement learning approach

We address the problem of generating novel molecules with desired interaction properties as a multi-objective optimization problem. Interaction binding models are learned from binding data using graph convolution networks (GCNs). Since the experimentally obtained property scores are recognised as having potentially gross errors, we adopted a robust loss for the model. Combinations of these terms, including drug likeness and synthetic accessibility, are then optimized using reinforcement learning based on a graph convolution policy approach. Some of the molecules generated, while legitimate chemically, can have excellent drug-likeness scores but appear unusual. We provide an example based on the binding potency of small molecules to dopamine transporters. We extend our method successfully to use a multi-objective reward function, in this case for generating novel molecules that bind with dopamine transporters but not with those for norepinephrine. Our method should be generally applicable to the generation in silico of molecules with desirable properties.
MatchMaker: A Deep Learning Framework for Drug Synergy Prediction

Drug combination therapies have been a viable strategy for the treatment of complex diseases such as cancer due to increased efficacy and reduced side effects. However, experimentally validating all possible combinations for synergistic interaction even with high-throughout screens is intractable due to vast combinatorial search space. Computational techniques can reduce the number of combinations to be evaluated experimentally by prioritizing promising candidates. We present MatchMaker that predicts drug synergy scores using drug chemical structure information and gene expression profiles of cell lines in a deep learning framework. For the first time, our model utilizes the largest known drug combination dataset to date, DrugComb. We compare the performance of MatchMaker with the state-of-the-art models and observe up to ~ 20% correlation and ~ 40% mean squared error (MSE) improvements over the next best method. We investigate the cell types and drug pairs that are relatively harder to predict and present novel candidate pairs. MatchMaker is built and available at https://github.com/tastanlab/matchmaker
Adaptation to increasing severity of phoma stem canker on winter oilseed rape in the UK under climate change

SUMMARY Various adaptation strategies are available that will minimize or negate predicted climate change-related increases in yield loss from phoma stem canker in UK winter oilseed rape (OSR) production. A number of forecasts for OSR yield, national production and subsequent economic values are presented, providing estimates of impacts on both yield and value for different levels of adaptation. Under future climate change scenarios, there will be increasing pressure to maintain yields at current levels. Losses can be minimized in the short term (up to the 2020s) with a ‘low’-adaptation strategy, which essentially requires some farmer-led changes towards best management practices. However, the predicted impacts of climate change can be negated and, in most cases, improved upon, with ‘high’-adaptation strategies. This requires increased funding from both the public and private sectors and more directed efforts at adaptation from the producer. Most literature on adaptation to climate change has had a conceptual focus with little quantification of impacts. It is argued that quantifying the impacts of adaptation is essential to provide clearer information to guide policy and industry approaches to future climate change risk.
Transformação genética de laranja 'Hamlin' via Agrobacterium

The development and optimization of efficient transformation protocols is essential in new citrus breeding programs, not only for rootstock, but also for scion improvement. Transgenic 'Hamlin' sweet orange (Citrus sinensis (L.) Osbeck) plants were obtained by Agrobacterium tumefaciens-mediated transformation of epicotyl segments collected from seedlings germinated in vitro. Factors influencing genetic transformation efficiency were evaluated including seedling incubation conditions, time of inoculation with Agrobacterium and co-culture conditions. Epicotyl segments were adequate explants for transformation, regenerating plants by direct organogenesis. Higher percentage of transformation was obtained with explants collected from seedlings germinated in darkness, transferred to 16 hours photoperiod for 2-3 weeks, and inoculated with Agrobacterium for 15-45 min. The best co-culture condition was the incubation of the explants in darkness, for three days in culture medium supplemented with 100 mM of acetosyringone. Genetic transformation was confirmed by performing b-glucoronidase (GUS) assays and, subsequently, by PCR amplification for the nptII and GUS genes.
Bi-allelic variants in TSPOAP1, encoding the active zone protein RIMBP1, cause autosomal recessive dystonia

Dystonia is a debilitating hyperkinetic movement disorder, frequently transmitted as a monogenic trait. Here, we describe homozygous frameshift, nonsense and missense variants in TSPOAP1, encoding the active zone RIM-binding protein 1 (RIMBP1), as a novel genetic cause of autosomal recessive dystonia in seven subjects from three unrelated families. Subjects carrying loss-of-function variants presented with juvenile- onset progressive generalized dystonia, associated with intellectual disability and cerebellar atrophy. Conversely, subjects carrying a pathogenic missense variant (p.Gly1808Ser) presented with isolated adult-onset focal dystonia. In mice, complete loss of RIMBP1, known to reduce neurotransmission, led to motor abnormalities reminiscent of dystonia, decreased Purkinje cell dendritic arborization, and reduced numbers of cerebellar synapses. In vitro analysis of the p.Gly1808Ser variant showed larger spike-evoked calcium transients and enhanced neurotransmission, suggesting that RIMBP1-linked dystonia can be caused by either reduced or enhanced rates of spike-evoked release in relevant neural networks. Our findings establish a direct link between presynaptic RIMBP1 dysfunction and dystonia and highlight the critical role played by well-balanced neurotransmission in motor control and disease pathogenesis.
An In Vivo and In Vitro Immunohistochemical Study of Integrin Alpha Subunit Localization in the Rat Anterior Pituitary

Different types of integrin alpha subunit were investigated immunohistochemically to determine the relationship between the cell adhesion molecule and the local morphology of the rat anterior pituitary using anterior pituitary tissues and primary cultured cells. Alpha 3 subunit was shown to be the main integrin subunit in the anterior pituitary. In vitro, immunoreactions of α3 subunit appeared mainly surrounding cell clusters. The distribution roughly overlapped with immunoreaction of laminin, while it was also observed where expression of laminin was negative. When dispersed cells were primary cultured for 2, 3 or 5 days, immunoreaction of α3 subunit was clearly detected in the vicinity of cell membrane throughout the period; while that of α5 subunit was not observed on day 2, it was observed as dots in cytoplasm on day 3 and more distinctly as lines in the vicinity of the cell membrane on day 5. Alpha 5 subunit was not detectable in vivo. These results indicate the possibility that integrin α3 subunit not only binds the cells to the basement membrane but also to other extracellular matrix or directly to adjacent cells in the anterior pituitary. In addition, integrin α5 subunit may supplement the function of α3 subunit under certain conditions.
Leaf endophytes and Populus genotype affect severity of damage from the necrotrophic leaf pathogen, Drepanopeziza populi.

Fungal leaf endophytes—nonpathogenic microfungi that live within plant leaves—are ubiquitous in land plants. Leaf endophytes and host plant genotypes may interact to determine plant disease severity. In a greenhouse inoculation experiment, we found that leaf endophyte species and Populus angustifolia genotypes both affected disease outcomes in plants inoculated with the necrotrophic leaf pathogen Drepanopeziza populi. Contrary to many studies showing endophytes conferring defense, all plant genotypes inoculated with the endophyte Penicillium sp. prior to inoculation with the pathogen D. populi were characterized by greater pathogen symptom severity than plants inoculated with the pathogen only. We quantified defense gene expression via qRT–PCR, but found no evidence that increased pathogen damage was related to differential expression of the assayed genes. A second endophyte, Truncatella angustata, which was previously found to reduce symptom severity of the biotrophic pathogen Melampsora in Populus trichocarpa, did not affect symptom severity of the necrotrophic pathogen D. populi or defense gene expression. Overall, our study highlights the variable effects of endophytes on pathogen symptom severity, and illustrates that plant genotypic variation can remain important for disease outcomes even in the presence of endophytes altering disease. Additional work is needed to elucidate the mechanism by which fungal leaf endophytes alter disease in their host plants.
Supramodal executive control of attention: Evidence from unimodal and crossmodal dual conflict effects

Although we have demonstrated that the executive control of attention acts supramodally as shown by significant correlation between conflict effects measures in visual and auditory tasks, no direct evidence of the equivalence in the computational mechanisms governing the allocation of executive control resources within and across modalities has been found. Here, in two independent groups of 40 participants, we examined the interaction effects of conflict processing in both unimodal (visual) and crossmodal (visual and auditory) dual-conflict paradigms (flanker conflict processing in Task 1 and then in the following Task 2) with a manipulation of the stimulus onset asynchrony (SOA). In both the unimodal and the crossmodal dual-conflict paradigms, the conflict processing of Task 1 interfered with the conflict processing of Task 2 when the SOA was short, reflecting an additive interference effect of Task 1 on Task 2 under the time constraints. These results suggest that there is a unified entity that oversees conflict processing acting supramodally by implementing comparable mechanisms in unimodal and crossmodal scenarios.
On Reasoning about Access to Knowledge

Controlling access to knowledge plays a crucial role in many multi-agent systems. In-deed, it is related to diﬀerent central aspects in interactions among agents such as privacy, security, and cooperation. In this paper, we propose a framework for dealing with access to knowledge that is based on the inference process in classical propositional logic: an agent has access to every piece of knowledge that can be derived from the available knowledge using the classical inference process. We ﬁrst introduce a basic problem in which an agent has to hide pieces of knowledge, and we show that this problem can be solved through the computation of maximal consistent subsets. In the same way, we also propose a counterpart of the previous problem in which an agent has to share pieces of knowledge, and we show that this problem can be solved through the computation of minimal inconsistent subsets. Then, we propose a generalization of the previous problem where an agent has to share pieces of knowledge and hide at the same time others. In this context, we introduce several concepts that allow capturing interesting aspects. Finally, we propose a weight-based approach by associating integers with the pieces of knowledge that have to be shared or hidden.