Miracle-dz/UniFAR-FTUs huggingface dataset:
Megasphaera elsdenii Lactate Degradation Pattern Shifts in Rumen Acidosis Models

Background: Megasphaera elsdenii is an ecologically important rumen bacterium that metabolizes lactate and relieves rumen acidosis (RA) induced by a high-grain-diet. Understanding the regulatory mechanisms of the lactate metabolism of this species in RA conditions might contribute to developing dietary strategies to alleviate RA. Methods: Megasphaera elsdenii was co-cultured with four lactate producers (Streptococcus bovis, Lactobacilli fermentum, Butyrivibrio fibrisolvens, and Selenomonas ruminantium) and a series of substrate starch doses (1, 3, and 9 g/L) were used to induce one normal and two RA models (subacute rumen acidosis, SARA and acute rumen acidosis, ARA) under batch conditions. The associations between bacterial competition and the shift of organic acids’ (OA) accumulation patterns in both statics and dynamics manners were investigated in RA models. Furthermore, we examined the effects of substrate lactate concentration and pH on Megasphaera elsdenii’s lactate degradation pattern and genes related to the lactate utilizing pathways in the continuous culture. Results and Conclusion: The positive growth of M. elsdenii and B. fibrisolvens caused OA accumulation in the SARA model to shift from lactate to butyrate and resulted in pH recovery. Furthermore, both the quantities of substrate lactate and pH had remarkable effects on M. elsdenii lactate utilization due to the transcriptional regulation of metabolic genes, and the lactate utilization in M. elsdenii was more sensitive to pH changes than to the substrate lactate level. In addition, compared with associations based on statics data, associations discovered from dynamics data showed greater significance and gave additional explanations regarding the relationships between bacterial competition and OA accumulation.
Intrinsically Disordered Proteins and Their “Mysterious” (Meta)Physics

Recognition of the natural abundance and functional importance of intrinsically disordered proteins (IDPs) and hybrid proteins containing ordered and intrinsically disordered protein regions (IDPRs) is changing protein science. IDPs and IDPRs; i.e., functional proteins and protein regions without unique structures, are commonly found in all organisms, where they have crucial roles in various biological processes. Disorder-based functionality complements functions of ordered proteins and domains. However, by virtue of their existence, IDPs/IDPRs, which are characterized by the remarkable conformational flexibility and structural plasticity, break multiple rules elaborated over the years to explain structure, folding, and functionality of well-folded proteins with unique structures. Despite the general believe, which dominated in protein science for more than a century, that unique biological functions of proteins require unique 3D-structures, structure-less IDPs/IDPRs are functional, being able to perform impossible tricks and to be engaged in biological activities, which are improbable for ordered proteins. With their exceptional spatio-temporal heterogeneity and high conformational flexibility, IDPs/IDPRs represent complex systems that act at the edge of chaos and are specifically tunable by various means. In this article, some of the wanders of intrinsic disorder are discussed as illustrations of their ‘mysterious’ (meta)physics.
Neonatal Morbidities of Fetal Growth Restriction: Pathophysiology and Impact

Being born small lays the foundation for short-term and long-term implications for life. Intrauterine or fetal growth restriction describes the pregnancy complication of pathological reduced fetal growth, leading to significant perinatal mortality and morbidity, and subsequent long-term deficits. Placental insufficiency is the principal cause of FGR, which in turn underlies a chronic undersupply of oxygen and nutrients to the fetus. The neonatal morbidities associated with FGR depend on the timing of onset of placental dysfunction and growth restriction, its severity, and the gestation at birth of the infant. In this review, we explore the pathophysiological mechanisms involved in the development of major neonatal morbidities in FGR, and their impact on the health of the infant. Fetal cardiovascular adaptation and altered organ development during gestation are principal contributors to postnatal consequences of FGR. Clinical presentation, diagnostic tools and management strategies of neonatal morbidities are presented. We also present information on the current status of targeted therapies. A better understanding of neonatal morbidities associated with FGR will enable early neonatal detection, monitoring and management of potential adverse outcomes in the newborn period and beyond.
Prostaglandins and Other Eicosanoids in Insects: Biosynthesis and Biological Actions

This essay reviews the discoveries, synthesis, and biological significance of prostaglandins (PGs) and other eicosanoids in insect biology. It presents the most current – and growing – understanding of the insect mechanism of PG biosynthesis, provides an updated treatment of known insect phospholipase A2 (PLA2), and details contemporary findings on the biological roles of PGs and other eicosanoids in insect physiology, including reproduction, fluid secretion, hormone actions in fat body, immunity and eicosanoid signaling and cross-talk in immunity. It completes the essay with a prospectus meant to illuminate research opportunities for interested readers. In more detail, cellular and secretory types of PLA2, similar to those known on the biomedical background, have been identified in insects and their roles in eicosanoid biosynthesis documented. It highlights recent findings showing that eicosanoid biosynthetic pathway in insects is not identical to the solidly established biomedical picture. The relatively low concentrations of arachidonic acid (AA) present in insect phospholipids (PLs) (< 0.1% in some species) indicate that PLA2 may hydrolyze linoleic acid (LA) as a precursor of eicosanoid biosynthesis. The free LA is desaturated and elongated into AA. Unlike vertebrates, AA is not oxidized by cyclooxygenase, but by a specific peroxidase called peroxinectin to produce PGH2, which is then isomerized into cell-specific PGs. In particular, PGE2 synthase recently identified converts PGH2 into PGE2. In the cross-talks with other immune mediators, eicosanoids act as downstream signals because any inhibition of eicosanoid signaling leads to significant immunosuppression. Because host immunosuppression favors pathogens and parasitoids, some entomopathogens evolved a PLA2 inhibitory strategy activity to express their virulence.
The Impact of Hippocampal Sex Hormones Receptors in Modulation of Depressive-Like Behavior Following Chronic Anabolic Androgenic Steroids and Exercise Protocols in Rats

The aim of this study was to evaluate alterations in depressive-like behaviors in rats following chronic administration of a supraphysiological dose of anabolic androgenic steroids (AASs) as well as exposure to a prolonged exercise protocol. The role of hippocampal sex hormones receptors in the modulation of depressive-like behavior was also assessed. A total of 48 male Wistar albino rats were divided into six groups: control, exercise (1 h/day, five consecutive days), nandrolone-decanoate (ND, 20 mg/kg/week, in a single dose), exercise plus ND, testosterone-enanthate (TE, 20 mg/kg/week, in a single dose), and exercise plus TE. After the 6-week protocols were complete, the rats underwent behavioral testing in the tail suspension test (TST). Rats were sacrificed for the collection of blood samples, to determine sex hormones levels, and isolation of the hippocampus, to determine [androgen receptors (AR) and estrogen receptors α (ERα)] expression. ND and TE treatment induced significant depressive-like behavior, opposing the antidepressant effect of exercise. Chronic TE administration elevated testosterone (T) and dihydrotestosterone (DHT) serum levels, and this was augmented by exercise. In contrast, ND and exercise alone did not alter T or DHT levels. There were no changes in serum estradiol levels in any of the groups. Immunohistochemical analysis showed that exercise reduced AR immunoreactivity in all hippocampal regions and increased the ERα expression in the CA1, dentate gyrus (DG), and total hippocampal sections, but not in the CA2/3 region. AASs administration increased AR expression in all hippocampal regions, although not the total hippocampal section in the TE group and did not significantly decrease ERα. The hippocampal AR/ERα expression index was lowered while parvalbumin (PV)-immunoreactivity was enhanced by exercise. AASs administration increased the AR/ERα index and reduced PV-immunoreactivity in the hippocampus. The number of PV-immunoreactive neurons negatively correlated with the antidepressant effects and the AR/ERα ratio. Our results suggest a potential role of the numerical relationship between two sex hormones receptors (stronger correlation than for each individual receptor) in the regulation of depressive-like behavior via the hippocampal GABAergic system in rats, which allow better understanding of the hippocampal sex hormones receptors role in modulation of depressive-like behavior.
Adrenal Aging and Its Implications on Stress Responsiveness in Humans

Normal aging results in subtle changes both in ACTH and cortisol secretion. Most notable is the general increase in mean daily serum cortisol levels in the elderly, without a noteworthy alteration in the normal circadian rhythm pattern. Glucocorticoid excess seen in the elderly population can have serious consequences in both the structural and functional integrity of various key areas in the brain, including the hippocampus, amygdala, prefrontal cortex, with consequent impairment in normal memory, cognitive function, and sleep cycles. The chronically elevated glucocorticoid levels also impinge on the normal stress response in the elderly, leading to an impaired ability to recover from stressful stimuli. In addition to the effects on the brain, glucocorticoid excess is associated with other age-related changes, including loss of muscle mass, hypertension, osteopenia, visceral obesity, and diabetes, among others. In contrast to the increase in glucocorticoid levels, other adrenocortical hormones, particularly serum aldosterone and DHEA (the precursor to androgens and estrogens) show significant decreases in the elderly. The underlying mechanisms for their decrease remain unclear. While the adrenomedullary hormone, norephinephrine, shows an increase in plasma levels, associated with a decrease in clearance, no notable changes observed in plasma epinephrine levels in the elderly. The multiplicity and complexity of the adrenal hormone changes observed throughout the normal aging process, suggests that age-related alterations in cellular growth, differentiation, and senescence specific to the adrenal gland must also be considered.
Agarwood Induction: Current Developments and Future Perspectives

Agarwood is a resinous part of the non-timber Aquilaria tree, which is a highly valuable product for medicine and fragrance purposes. To protect the endangered Aquilaria species, mass plantation of Aquilaria trees has become a sustainable way in Asian countries to obtain the highly valuable agarwood. As only physiologically triggered Aquilaria tree can produce agarwood, effective induction methods are long sought in the agarwood industry. In this paper, we attempt to provide an overview for the past efforts toward the understanding of agarwood formation, the evolvement of induction methods and their further development prospects by integrating it with high-throughput omics approaches.
Sex Differences in Nutrition, Growth, and Metabolism in Preterm Infants

Biological differences between the sexes are apparent even from the early part of the pregnancy. The crown-rump length is larger in male fetuses compared to females in the first trimester. Placentae of male and female fetuses have different protein and gene expressions, especially in adverse conditions. Even within the intrauterine milieu, the same extracellular micro RNA may show upregulation in females and downregulation in male fetuses. There appears to be a natural survival advantage for females. Maternal glucocorticoids (GC) play an important role in fetal growth and organ maturation. However, excess glucocorticoids can not only affect growth but the response may be sex-specific and probably mediated through glucocorticoid receptors (GR) in the placenta. Mild pre-eclampsia and asthma are associated with normal growth pattern in males, but in female fetuses, they are associated with a slowing of growth rate without causing IUGR probably as an adaptive response for future adverse events. Thus, female fetuses survive while male fetuses exhibit IUGR, preterm delivery and even death in the face of another adverse event. It is thought that the maternal diet may not influence growth but may influence the programming for adult disease. There is growing evidence that maternal pre-pregnancy overweight or obesity status is directly associated with a higher risk of obesity in a male child, but not in a female child, at 1 year of age. It is observed that exposure to gestational diabetes is a risk factor for childhood overweight in boys but not in girls. It is fascinating that male and female fetuses respond differently to the same intrauterine environment, and this suggests a fundamental biological variation most likely at the cellular and molecular level.
Ferulic Acid and Eugenol Have Different Abilities to Maintain Their Inhibitory Activity Against Listeria monocytogenes in Emulsified Systems

Natural phenolic compounds are found in large quantities in plants and plant extracts and byproducts from agro-industries. They could be used to ensure food quality and safety due to their antimicrobial properties demonstrated in systems such as culture media. The aim of this study was to evaluate the ability of two natural phenolic compounds, ferulic acid and eugenol, to maintain their inhibitory activity against the growth of Listeria monocytogenes in an oil-in-water emulsion, simulating a complex food system. The minimum inhibitory concentration (MIC) of each phenolic compound was first determined in culture medium, consisting of TS broth and an added emulsifier. Whey proteins and Tween 80 increased the MIC of the antimicrobial activity of eugenol. The MIC of ferulic acid was less affected by the addition of Tween 80. The inhibitory activities of both phenolic compounds were then compared at the same concentration in emulsions and their corresponding aqueous phases by following the growth of L. monocytogenes by plate counting. In emulsified systems, eugenol lost the high inhibitory activity observed in the aqueous phase, whereas ferulic acid retained it. The partition coefficient (logPoct/wat) appears to be a key factor. Eugenol (logPoct/wat = 2.61) dispersed in the aqueous phase intercalates into the bacterial membrane and has high antimicrobial activity. In contrast, it likely preferentially partitions into the lipid droplets when dispersed in an emulsion, consequently losing its antimicrobial activity. As ferulic acid is more hydrophilic, a higher proportion probably remains in the aqueous phase of the emulsion, retaining its antimicrobial activity.
Achieving predictable, guaranted and work-conserving performance in datacenter networks

Performance interference has been a well-known problem in datacenter networks (DCNs) and one that remains a constant topic of discussion in the literature. Several measurement studies concluded that throughput achieved by virtual machines (VMs) in current datacenters can vary by a factor of five or more, leading to poor and unpredictable overall application performance. Recent efforts have proposed techniques that present some shortcomings, such as underutilization of resources, significant management overhead or negligence of non-network resources. In this thesis, we introduce three proposals that address performance interference in DCNs: IoNCloud, Predictor and Packer. IoNCloud leverages the key observation that temporal bandwidth demands of cloud applications do not peak at exactly the same time. Therefore, it seeks to provide predictable and guaranteed performance while minimizing network underutilization by (a) grouping applications in virtual networks (VNs) according to their temporal network usage and need of isolation; and (b) allocating these VNs on the cloud substrate. Despite achieving its objective, IoNCloud does not provide work-conserving sharing among VNs, which limits utilization of idle resources. Predictor, an evolution over IoNCloud, dynamically programs the network in Software-Defined Networking (SDN)-based DCNs and uses two novel algorithms to provide network guarantees with work-conserving sharing. Furthermore, Predictor is designed with scalability in mind, taking into consideration the number of entries required in flow tables and flow setup time in DCNs with high turnover and millions of active flows. IoNCloud and Predictor neglect resources other than the network at allocation time. This leads to fragmentation of non-network resources and, consequently, results in less applications being allocated in the infrastructure. Packer, in contrast, aims at providing predictable and guaranteed network performance while minimizing overall multi-resource fragmentation. Extending the observation presented for IoNCloud, the key insight for Packer is that applications have complementary demands across time for multiple resources. To enable multi-resource allocation, we devise (i) a new abstraction for specifying temporal application requirements (called Time-Interleaved Multi-Resource Abstraction – TI-MRA); and (ii) a new allocation strategy. We evaluated IoNCloud, Predictor and Packer, showing their benefits and overheads. In particular, all of them provide predictable and guaranteed network performance; Predictor reduces flow table size in switches and flow setup time; and Packer minimizes multi-resource fragmentation.
Exploiting multiple levels of parallelism and online refinement of unstructured meshes in atmospheric model application

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The PACE 2018 Parameterized Algorithms and Computational Experiments Challenge: The Third Iteration

The Program Committee of the Third Parameterized Algorithms and Computational Experiments challenge (PACE 2018) reports on the third iteration of the PACE challenge. This year, all three tracks were dedicated to solve the Steiner Tree problem, in which, given an edge-weighted graph and a subset of its vertices called terminals, one has to find a minimum-weight subgraph which spans all the terminals. In Track A, the number of terminals was limited. In Track B, a tree-decomposition of the graph was provided in the input, and the treewidth was limited. Finally, Track C welcomed heuristics. Over 80 participants on 40 teams from 16 countries submitted their implementations to the competition.
A Compression-Based Toolkit for Modelling and Processing Natural Language Text

A novel compression-based toolkit for modelling and processing natural language text is described. The design of the toolkit adopts an encoding perspective—applications are considered to be problems in searching for the best encoding of different transformations of the source text into the target text. This paper describes a two phase `noiseless channel model’ architecture that underpins the toolkit which models the text processing as a lossless communication down a noise-free channel. The transformation and encoding that is performed in the first phase must be both lossless and reversible. The role of the verification and decoding second phase is to verify the correctness of the communication of the target text that is produced by the application. This paper argues that this encoding approach has several advantages over the decoding approach of the standard noisy channel model. The concepts abstracted by the toolkit’s design are explained together with details of the library calls. The pseudo-code for a number of algorithms is also described for the applications that the toolkit implements including encoding, decoding, classification, training (model building), parallel sentence alignment, word segmentation and language segmentation. Some experimental results, implementation details, memory usage and execution speeds are also discussed for these applications.
Exploring the Kernelization Borders for Hitting Cycles

A generalization of classical cycle hitting problems, called conflict version of the problem, is defined as follows. An input is undirected graphs G and H on the same vertex set, and a positive integer k, and the objective is to decide whether there exists a vertex subset X ⊆ V (G) such that it intersects all desired “cycles” (all cycles or all odd cycles or all even cycles) and X is an independent set in H. In this paper we study the conflict version of classical Feedback Vertex Set, and Odd Cycle Transversal problems, from the view point of kernelization complexity. In particular, we obtain the following results, when the conflict graph H belongs to the family of d-degenerate graphs. 1. CF-FVS admits a O(kO(d)) kernel. 2. CF-OCT does not admit polynomial kernel (even whenH is 1-degenerate), unless NP ⊆ coNP poly . For our kernelization algorithm we exploit ideas developed for designing polynomial kernels for the classical Feedback Vertex Set problem, as well as, devise new reduction rules that exploit degeneracy crucially. Our main conceptual contribution here is the notion of “k-independence preserver”. Informally, it is a set of “important” vertices for a given subset X ⊆ V (H), that is enough to capture the independent set property in H. We show that for d-degenerate graph independence preserver of size kO(d) exists, and can be used in designing polynomial kernel. 2012 ACM Subject Classification Theory of computation→ Design and analysis of algorithms → Parameterized complexity and exact algorithms
Gamified Software to Support the Design of Business Innovation

Business innovation is a process that requires creativity, and benefits from extensive collaboration. Currently, computational support in creativity processes is low, but modern techniques would allow these processes to be sped up. In this context, we provide such a computational support with software for business innovation design that uses computational creativity techniques. Furthermore, the software enables a gamified process to increase user engagement and collaboration, which mimics evolutionary methods, relying on a voting mechanism. The software includes a business innovation ontology representing the domain knowledge that is used to generate and select a set of diverse preliminary representations of business ideas. Indeed, the most promising for novelty and potential impact are identified to ignite a business innovation game where team members collaborate to elaborate new innovation ideas based on those inputs until convergence to a shortlist of business model proposals. The main features of the approach are illustrated by means of a running example concerning innovative services for smart cities.