Miracle-dz/UniFAR-FTUs huggingface dataset:
Greb1 is required for axial elongation and segmentation in vertebrate embryos

ABSTRACT During vertebrate embryonic development, the formation of axial structures is driven by a population of stem-like cells that reside in a region of the tailbud called the chordoneural hinge (CNH). We have compared the mouse CNH transcriptome with those of surrounding tissues and shown that the CNH and tailbud mesoderm are transcriptionally similar, and distinct from the presomitic mesoderm. Amongst CNH-enriched genes are several that are required for axial elongation, including Wnt3a, Cdx2, Brachyury/T and Fgf8, and androgen/oestrogen receptor nuclear signalling components such as Greb1. We show that the pattern and duration of tailbud Greb1 expression is conserved in mouse, zebrafish and chicken embryos, and that Greb1 is required for axial elongation and somitogenesis in zebrafish embryos. The axial truncation phenotype of Greb1 morphant embryos can be explained by much reduced expression of No tail (Ntl/Brachyury), which is required for axial progenitor maintenance. Posterior segmentation defects in the morphants (including misexpression of genes such as mespb, myoD and papC) appear to result, in part, from lost expression of the segmentation clock gene, her7. Summary: The Greb1 transcriptional cofactor is expressed in the vertebrate tailbud and required for axial extension and segmentation of developing vertebrate embryos.
Packet domain monitoring system based on cloud storage

Considering the deficiency of efficiency,expansibility and security of the packet domain monitoring system in the mass data application environment,the new monitoring system based on cloud storage is designed.The new system incorporates the telecom private cloud by using Hadoop cloud storage technology.It not only solves the problem of timely processing and storing mass data but also optimizes the whole system's performance.Through the testing verification,the new system is stable and reliable and is suitable for the need of large telecom capacity monitoring.
Effects of Chronic Use of Tramadol on Uterus and Ovary of Albino Rats

Backgrounds: The researches on endocrinopathy related with oral opioids had focused more on males, while fewer studies had focused on females. Objective: it was to demonstrate the possible chronic tramadol toxic effect (histopathological & biochemical) on ovary and endometrium of adult female albino rats. Materials and methods: Twenty-five female rats (control group), were given normal food and water, while one hundred adult female rats were given 30 mg/kg/day tramadol dissolved in distilled water (which represent 1/10 LD50) on daily basis for each rat for 3 months (An average 0.6ml for each rat). Rats were weighted at the beginning of the study and then 2 times weekly. At end of this period, blood samples were taken for Biochemical analysis. Rats’ ovaries and uterus were examined by light microscope after staining with Haematoxylin and Eosin, and then data were analyzed and statistically studied. Results: Our study showed gradual decrease in female body weight and levels of sex hormones. In tramadol treated group, ovaries showed apparent decrease in the number of growing follicles and an increase in the number of corpora lutea. The medulla showed dilated congested blood vessels. Many of the follicles appeared atretic. In the corpora lutea, there were degenerated cells. While endometrium in tramadol treated group there was apparent atrophic glands and stroma in the surface of the endometrium with appearance of inflammatory cells in the stroma. Conclusion: it has harmful histopathological and functional effects on the reproductive organs of female albino rats.
A complex pattern of post‐divergence expansion, contraction, introgression, and asynchronous responses to Pleistocene climate changes in two Dipelta sister species from western China

The well‐known vicariance and dispersal models dominate in understanding the allopatric pattern for related species and presume the simultaneous occurrence of speciation and biogeographic events. However, the formation of allopatry could postdate the species divergence. We examined this hypothesis using DNA sequence data from three chloroplast fragments and five nuclear loci of Dipelta floribunda Maxim. and D. yunnanensis Franch, two shrub species with the circum Sichuan Basin distribution, combining the climatic niche modeling approach. The best‐fit model supported by the approximate Bayesian computation analysis indicated that D. floribunda and D. yunnanensis diverged during the mid‐Pleistocene period, consistent with the largest glacial period in the Qinghai–Tibet Plateau. The historically interspecific gene flow was identified, but seemed to have ceased after the last interglacial period, when the range of D. floribunda moved northward from the south of the Sichuan Basin. Furthermore, populations of D. floribunda had expanded obviously in the north of the Sichuan Basin after the last glacial maximum (LGM). Relatively, the range of D. yunnanensis expanded before the LGM, and reduced during the post‐LGM especially in the north of the Sichuan Basin, reflecting the asynchronous responses of related species to contemporary climate changes. Our results suggested that complex topography should be considered in understanding distributional patterns, even for closely related species and their demographic responses.
Influence of low-tannin sorghum on performance and bone morphometrics of male Ross 308 broilers aged 1 - 42 days

The objective of this study was to determine the effects of low tannin sorghum as a maize replacement on the performance and bone morphometrics of Ross 308 broiler chickens. A total of 250 one-day-old broiler chickens were allotted to a complete randomized design with five treatments replicated five times. Birds were offered varying sorghum levels as maize replacement at 0% (control), 25%, 50%, 75% and 100%, formulated to be isonutritive and isoenergetic. The condensed tannin and total phenolic contents of the sorghum were analysed. Bodyweight and feed intake were measured weekly to calculate feed conversion ratio (FCR), and mortality was recorded as it occurred. Digestibility measurements were done when the chickens were between 15 and 21 days and between 35 and 42 days old. At ages 21 and 42 days, two chickens per pen were slaughtered to determine bone characteristics. A digital calliper was used to measure the length and diameter of the bones, and an electronic scale was used to determine the weight of the bones. Ash, calcium and phosphorus concentrations of the bones were determined. The Seedor and robusticity indices of the tibia were also calculated. The general linear model procedure of Statistical Analysis Software was used to analyse the data. At 1 - 21 days old bodyweight was higher for birds fed a level of 50% sorghum than those that were offered the control diet. Replacing maize with sorghum improved the metabolizable energy (ME) of broiler chickens aged 42 days. Bodyweight and FCR of birds fed diets with 50%, 75% and 100% sorghum were higher and better, respectively, than those on diets with 25% and 0% sorghum at 22 - 42 days old. Bone morphometries of chickens aged 1 - 21 days and 22 - 42 days were not affected by replacing maize with sorghum. Thus, maize can be replaced by a low tannin white sorghum without causing adverse effects on chickens. Keywords: minerals, tibia bone, Seedor and robusticity indices
An Overview of Data Mining Techniques in Recommender Systems

Nowadays, recommender systems support the online customers in their decision making and buying process. Whereas, the information in the web is increasing through continuous growing of the number of websites, recommender systems have to recommend the items with maximal matching to the users’ preference. Recommender systems are an active research topic in the data mining and machine learning fields. Data mining techniques have played an important role in the design and implementation of recommender systems. In this paper, an overview of the main data mining techniques used in the design and implementation of recommender systems is given. The relevant papers which have used the data mining techniques in the context of recommender systems are reviewed. We hope that this research helps researchers who are interested in developing recommender systems with an insight into its state-of-the-art methods.
Benchmarking predictions of MHC class I restricted T cell epitopes

T cell epitope candidates are commonly identified using computational prediction tools in order to enable applications such as vaccine design, cancer neoantigen identification, development of diagnostics and removal of unwanted immune responses against protein therapeutics. Most T cell epitope prediction tools are based on machine learning algorithms trained on MHC binding or naturally processed MHC ligand elution data. The ability of currently available tools to predict T cell epitopes has not been comprehensively evaluated. In this study, we used a recently published dataset that systematically defined T cell epitopes recognized in vaccinia virus (VACV) infected mice, considering both peptides predicted to bind MHC or experimentally eluted from infected cells, making this the most comprehensive dataset of T cell epitopes mapped in a complex pathogen. We evaluated the performance of all currently publicly available computational T cell epitope prediction tools to identify these major epitopes from all peptides encoded in the VACV proteome. We found that all methods were able to improve epitope identification above random, with the best performance achieved by neural network-based predictions trained on both MHC binding and MHC ligand elution data (NetMHCPan-4.0 and MHCFlurry). Impressively, these methods were able to capture more than half of the major epitopes in the top 0.04% (N = 277) of peptides in the VACV proteome (N = 767,788). These performance metrics provide guidance for immunologists as to which prediction methods to use. In addition, this benchmark was implemented in an open and easy to reproduce format, providing developers with a framework for future comparisons against new tools. Author summary Computational prediction tools are used to screen peptides to identify potential T cell epitope candidates. These tools, developed using machine learning methods, save time and resources in many immunological studies including vaccine discovery and cancer neoantigen identification. In addition to the already existing methods several epitope prediction tools are being developed these days but they lack a comprehensive and uniform evaluation to see which method performs best. In this study we did a comprehensive evaluation of publicly accessible MHC I restricted T cell epitope prediction tools using a recently published dataset of Vaccinia virus epitopes. We found that methods based on artificial neural network architecture and trained on both MHC binding and ligand elution data showed very high performance (NetMHCPan-4.0 and MHCFlurry). This benchmark analysis will help immunologists to choose the right prediction method for their desired work and will also serve as a framework for tool developers to evaluate new prediction methods.
The effects of winter stress on Sphagnum species with contrasting macro- and microdistributions

ABSTRACT Introduction. Sphagnum L. forms much of the ground cover in northern peatlands. Different species show affinities for bioclimatic regions in Europe (oceanic/continental; northern/southern) and species-specific tolerance of winter conditions can be a factor explaining their distribution. Methods. We focussed on low temperature in a series of experiments and tested (1) the innate ability of a selection of Sphagnum species to tolerate low temperature in relation to their micro-topographic (wetness) and geographical (climate) distribution; (2) the rate of cold tolerance acquisition; and (3) the ability of species to survive a range of low temperature once cold hardened. Key results. Our experiments showed that maximal PSII efficiency (Fv/Fm, chlorophyll fluorescence), growth rates and survival were all negatively affected by sub-zero temperatures. Environmental conditions associated with the onset of winter (colder nights and shorter days) triggered the acquisition of cold tolerance in Sphagnum. Conclusions. The results were not unequivocal, but species associated with colder climates were generally more tolerant of sub-zero conditions. Species associated with the wettest and driest ends of the wetness gradient were more consistent in their responses than those in between, with wetter-dwelling species being less sensitive to sub-zero temperature than species found in drier microhabitats. Overall, our results suggest that adaptation to winter conditions contribute to the current distribution patterns of Sphagnum species.
Novel Neuro-dynamic Methods For Solving Robotic Planning And Control Problems

NOVEL NEURO-DYNAMIC METHODS FOR SOLVING ROBOTIC PLANNING AND CONTROL PROBLEMS Ghassan Atmeh, Ph.D. The University of Texas at Arlington, 2015 Supervising Professor: Kamesh Subbarao Robotic systems are growing more complex to cater to the tasks they are required to solve. Irrespective of these tasks the problem of planning and control must be solved for all robotic systems. In this dissertation a general description of that problem is given along with the issues that it faces. This problem concerns planning a trajectory in the operational space of the robot, i.e. the space in which a task is to be executed. Then solving the inverse kinematics problem to compute the joint positions that correspond to that trajectory. And lastly, controlling the robot to track those joint trajectories. One of the issues facing the planning and control problem is singular configurations of a robot; these are joint configurations at which the inverse kinematics problem has multiple solutions. They can also induce large velocities in a robot, and lead to damage in hardware. Another issue to be addressed while solving the planning and control problem is model uncertainties, where the model used to control the robot does not account for all possible parameters that affect its motion. The solution to the planning and control problem presented in this research uses tools from artificial vi intelligence and tackles these issues to provide a robust framework for planning and control that can be implemented on any robotic chain. By using dynamic neural networks with intelligent feedback, adaptive operational space trajectories are generated. Two methods for dealing with singular configurations are presented, one uses artificial potential functions to avoid those configurations while another uses neuro-dynamic solutions to render the system robust to their effects. To control the robot, artificial neural networks with online learning are used in a neuro-adaptive controller. This controller allows for tracking the desired joint values calculated from the inverse kinematics solution. Numerical simulations are used to verify the capabilities of the developed methods for solving the planning and control problem. These methods also tested in a realistic simulation environment of the Atlas humanoid robotic system. In house software is developed to realize an execution of a walking gait using the neuro-dynamic framework. Results show that the developed methods form a singularity robust framework for solving the planning and control problem for a complex robotic system.
Migration Stimulating Factor : new marker for tumour progression?

The aims of my work were: a) to generate reagents (recombinant protein and antibodies) useful to identify MSF as a possible marker for TAMs in human tumours; b) to characterise the biological properties of MSF. MSF is a soluble oncofoetal isoform of human fibronectin 1, identical to the N-terminus portion of fibronectin and characterized by the presence of a unique 10 amino acids long sequence in the C-terminus end. MSF is expressed by epithelial and stromal cells during foetal development and in cancer patients, but not by adult normal cells. Our group found a selective expression of MSF by M2-polarized human macrophages and M2-like tumor-associated macrophages (TAMs). TAMs are major inflammatory cells infiltrating tumors, they support tumour growth and are associated to poor prognosis. These findings suggest that MSF could be a potential marker for tumor progression associated to M2-like polarization of TAM and a promising target for anti-cancer therapy. Human MSF has been expressed in CHO cells and purified by affinity chromatography. Recombinant MSF has a motogenic effect on cancer cell lines, human monocytes and murine peritoneal macrophages. Different levels of MSF expression were observed in human cancer cell lines and correlate with its motogenic effect. In vivo experiments showed that tumors derived from MSF-expressing cells had an higher growth rate compared to tumors derived from control cells. We also developed a monoclonal antibody (MoAb_E10) recognizing human MSF. A initial characterization on human tumour tissues (lung, breast, colon) showed MSF expression in tumor cells as well as stromal cells. In particular MSF expression is associated to M2-like TAM. Given that TAMs are promising target for anticancer therapy, the possibility to identify M2 polarized cells would be of considerable interest and further studies will be necessary to define the importance of MSF in the context of human tumours.
Explicit strategies in force field adaptation

In recent years, it has become increasingly clear that a number of learning processes are at play in visuomotor adaptation tasks. In addition to the presumed formation of an internal model of the perturbation, learners can also develop explicit knowledge allowing them to select better actions in responding to a given perturbation. Advances in visuomotor rotation experiments have underscored the important role that such “explicit learning” plays in shaping adaptation to kinematic perturbations. Yet, in adaptation to dynamic perturbations, its contribution has been largely overlooked, potentially because compensation of a viscous force field, for instance, is difficult to assess by commonly-used verbalization-based approaches. We therefore sought to assess the contribution of explicit learning in learners adapting to a dynamic perturbation by two novel modifications of a force field experiment. First, via an elimination approach, we asked learners to abandon any cognitive strategy before selected force channel trials to expose consciously accessible parts of overall learning. Learners indeed reduced compensatory force compared to standard Catch channels. Second, via a manual reporting approach, we instructed a group of learners to mimic their right hand’s adaptation by moving with their naïve left hand. While a control group displayed negligible left-hand force compensation, the Mimic group reported forces that approximated right-hand adaptation but appeared to under-report the velocity component of the force field in favor of a more position-based component. We take these results to clearly demonstrate the contribution of explicit learning to force adaptation, underscoring its relevance to motor learning in general. New & Noteworthy While the role of explicit learning has recently been appreciated in visuomotor adaptation tasks, their contribution to force field adaptation has not been as widely acknowledged. To address this issue, we employed two novel methods to assay explicit learning in force field adaptation tasks and found that learners can voluntarily control aspects of force production and manually report them with their untrained limb. This suggests that an explicit component contributes to force field adaptation and may provide alternative explanations to behavioral phenomena commonly thought to reveal a complex organization of internal models in the brain.
Sensitivity and specificity of a Bayesian single trial analysis for time varying neural signals

We recently reported the existence of fluctuations in neural signals that may permit neurons to code multiple simultaneous stimuli sequentially across time1. This required deploying a novel statistical approach to permit investigation of neural activity at the scale of individual trials. Here we present tests using synthetic data to assess the sensitivity and specificity of this analysis. We fabricated datasets to match each of several potential response patterns derived from single-stimulus response distributions. In particular, we simulated dual stimulus trial spike counts that reflected fluctuating mixtures of the single stimulus spike counts, stable intermediate averages, single stimulus winner-take-all, or response distributions that were outside the range defined by the single stimulus responses (such as summation or suppression). We then assessed how well the analysis recovered the correct response pattern as a function of the number of simulated trials and the difference between the simulated responses to each “stimulus” alone. We found excellent recovery of the mixture, intermediate, and outside categories (>97% correct), and good recovery of the single/winner-take-all category (>90% correct) when the number of trials was >20 and the single-stimulus response rates were 50Hz and 20Hz respectively. Both larger numbers of trials and greater separation between the single stimulus firing rates improved categorization accuracy. These results provide a benchmark, and guidelines for data collection, for use of this method to investigate coding of multiple items at the individual-trial time scale.
Description of two new Caribbean species from the Hypnea musciformis complex (Cystocloniaceae, Rhodophyta)

Hypnea musciformis is a red macroalgal species with economic importance as a source for production of carrageenan. Recent phylogeographic studies revealed a hidden diversity of cryptic species, putting in check its cosmopolitan distribution. The DNA barcode marker COI-5P and plastid rbcL, in addition to morphological studies, were used to investigate the species in this complex and to compare them with specimens from other countries including the type locality in Italy. The divergences between sequences within the H. musciformis complex were significantly high for both markers. Based on these analyses two new species are described, Hypnea caraibica Nauer, Cassano & M.C. Oliveira sp. nov. and Hypnea schneideri Nauer, Cassano & M.C. Oliveira sp. nov. Hypnea caraibica seems to be a common, widespread species in the Gulf of Mexico and the Caribbean and was recently introduced into Hawaii. This species was unnoticed due to lack of phylogeographic studies in the region. Hypnea schneideri seems to be more geographically restricted, but further surveys are needed to understand the distribution of this species. Because the identification of Hypnea species is complicated by their relatively simple and plastic morphology, DNA barcoding surveys and other molecular studies are essential to uncover hidden biodiversity in the genus and to supplement traditional studies based on morphology.
A stateless penalty algorithm for non-TCP friendly flow

Internet has become facing crisis of "congestion collapse"once again because of the appearing of Non- TCP friendly flow. Trash-a stateless penalty algorithm for non-TCP friendly flow is proposed in this paper.By keeping the information on discarded packets, the algorithm can discriminate and punish against the flow which submit more packet than is al1owed by their fair share.Simulation results show that our algorithm has better penalty performance in fairness of bandwidth allocation than that of CHOKe.