Miracle-dz/UniFAR-FTUs huggingface dataset:
Immunity to Influenza A H9N2 Viruses Induced by Infection and Vaccination

ABSTRACT Avian influenza A H9N2 viruses are widespread among domestic poultry and were recently isolated from humans with respiratory illness in China. Two antigenically and genetically distinct groups of H9N2 viruses (G1 and G9) are prevalent in China. To evaluate a strategy for vaccination, we compared G1 and G9 viruses for their relative immunogenicity and cross-protective efficacy. Infection of BALB/c mice with representative viruses of either group protected against subsequent challenge with the homologous or heterologous H9N2 virus in the absence of detectable cross-reactive serum hemagglutination inhibition antibody. Mice injected intramuscularly with inactivated G1 whole virus vaccine were completely protected from challenge with either H9N2 virus. In contrast, mice administered inactivated G9 vaccine were only partially protected against heterologous challenge with the G1 virus. These results have implications for the development of human vaccines against H9N2 viruses, a priority for pandemic preparedness.
Novelty and Inductive Generalization in Human Reinforcement Learning

In reinforcement learning (RL), a decision maker searching for the most rewarding option is often faced with the question: What is the value of an option that has never been tried before? One way to frame this question is as an inductive problem: How can I generalize my previous experience with one set of options to a novel option? We show how hierarchical Bayesian inference can be used to solve this problem, and we describe an equivalence between the Bayesian model and temporal difference learning algorithms that have been proposed as models of RL in humans and animals. According to our view, the search for the best option is guided by abstract knowledge about the relationships between different options in an environment, resulting in greater search efficiency compared to traditional RL algorithms previously applied to human cognition. In two behavioral experiments, we test several predictions of our model, providing evidence that humans learn and exploit structured inductive knowledge to make predictions about novel options. In light of this model, we suggest a new interpretation of dopaminergic responses to novelty.
Crosstalk Between Microtubule Attachment Complexes Ensures Accurate Chromosome Segregation

Dissecting Chromosome Segregation During cell division, the centromere regions of chromosomes assemble multiprotein organelles called kinetochores that form attachments to spindle microtubules. Working in Caenorhabditis elegans, Cheerambathur et al. (p. 1239, published online 14 November) describe a mechanism controlling the formation of kinetochore-spindle microtubule attachments that is essential for accurate chromosome segregation. The findings suggest the existence of crosstalk between the two major protein complexes involved in forming spindle microtubule attachments: the kinetochore dynein module, which initially captures spindle microtubules, and the Ndc80 complex, which ultimately forms the dynamic end-coupled attachments that segregate chromosomes. Chromosome partitioning involves regulatory crosstalk between two major microtubule-binding complexes at the kinetochore. The microtubule-based mitotic spindle segregates chromosomes during cell division. During chromosome segregation, the centromeric regions of chromosomes build kinetochores that establish end-coupled attachments to spindle microtubules. Here, we used the Caenorhabditis elegans embryo as a model system to examine the crosstalk between two kinetochore protein complexes implicated in temporally distinct stages of attachment formation. The kinetochore dynein module, which mediates initial lateral microtubule capture, inhibited microtubule binding by the Ndc80 complex, which ultimately forms the end-coupled attachments that segregate chromosomes. The kinetochore dynein module directly regulated Ndc80, independently of phosphorylation by Aurora B kinase, and this regulation was required for accurate segregation. Thus, the conversion from initial dynein-mediated, lateral attachments to correctly oriented, Ndc80-mediated end-coupled attachments is actively controlled.
Fatal envenomation by jellyfish causing Irukandji syndrome

TO THE EDITOR: Interpretation of the report describing the first death attributed to the Irukandji syndrome should be tempered by the fact that significant unstated assumptions have been made in attributing the cause of death to a jellyfish.1 While envenomation by a jellyfish remains the likely diagnostic possibility, no evidence is presented that unequivocally confirms a jellyfish as the lethal agent. Several methods could have been used to support or confirm the diagnosis of jellyfish envenomation, including sampling of nematocysts from the victim’s skin (before or after death), jellyfish capture, or reports of other similar, but less severe, stings from the same beach around the time the victim was stung. In severe jellyfish envenomation, attempts are often made to harvest nematocysts from patients’ skin, most commonly by skin scraping or by sticky tape sampling. Recovered nematocysts may help to identify the species, and confirm the diagnosis.3 Although successful nematocyst recovery is uncommon in Irukandji syndrome, it is disappointing that “no attempt was made to sample nematocysts”1 given the relative simplicity of the procedure and the importance of this case. The authors state that “no sting site was clearly delineated”,1 but then go on to say that there were, in fact, areas of “skin flushing and intermittent diaphoresis”1 over a significant period of time. Sticky tape sampling of these areas may have yielded nematocysts, allowing positive species identification. Postmortem skin sections have also been employed in Chironex fleckeri fatalities, and have shown nematocyst barbs on the victim’s skin.4 Postmortem examination may also have revealed other contributing factors. I am particularly interested in the assertion that almost every Irukandji syndrome patient in the Whitsundays develops a “rise in cardiac troponin levels”. 1 In fact, the cited article makes no mention of troponin, simply stating that CK-MB (creatine kinase isoenzyme) levels “can be abnormal”,5 and that “some severe cases [of Irukandji syndrome] may have a CK-MB [level] well above the normal range”. 5 Many aspects of the diagnosis and treatment of jellyfish envenoming remain controversial. Accurate reporting of unusual cases is thus of the utmost importance.
Gene Set-Based Functionome Analysis of Pathogenesis in Epithelial Ovarian Serous Carcinoma and the Molecular Features in Different FIGO Stages

Serous carcinoma (SC) is the most common subtype of epithelial ovarian carcinoma and is divided into four stages by the Federation of Gynecologists and Obstetrics (FIGO) staging system. Currently, the molecular functions and biological processes of SC at different FIGO stages have not been quantified. Here, we conducted a whole-genome integrative analysis to investigate the functions of SC at different stages. The function, as defined by the GO term or canonical pathway gene set, was quantified by measuring the changes in the gene expressional order between cancerous and normal control states. The quantified function, i.e., the gene set regularity (GSR) index, was utilized to investigate the pathogenesis and functional regulation of SC at different FIGO stages. We showed that the informativeness of the GSR indices was sufficient for accurate pattern recognition and classification for machine learning. The function regularity presented by the GSR indices showed stepwise deterioration during SC progression from FIGO stage I to stage IV. The pathogenesis of SC was centered on cell cycle deregulation and accompanied with multiple functional aberrations as well as their interactions.
Besnoitia besnoiti and Toxoplasma gondii: two apicomplexan strategies to manipulate the host cell centrosome and Golgi apparatus

SUMMARY Besnoitia besnoiti and Toxoplasma gondii are two closely related parasites that interact with the host cell microtubule cytoskeleton during host cell invasion. Here we studied the relationship between the ability of these parasites to invade and to recruit the host cell centrosome and the Golgi apparatus. We observed that T. gondii recruits the host cell centrosome towards the parasitophorous vacuole (PV), whereas B. besnoiti does not. Notably, both parasites recruit the host Golgi apparatus to the PV but its organization is affected in different ways. We also investigated the impact of depleting and over-expressing the host centrosomal protein TBCCD1, involved in centrosome positioning and Golgi apparatus integrity, on the ability of these parasites to invade and replicate. Toxoplasma gondii replication rate decreases in cells over-expressing TBCCD1 but not in TBCCD1-depleted cells; while for B. besnoiti no differences were found. However, B. besnoiti promotes a reorganization of the Golgi ribbon previously fragmented by TBCCD1 depletion. These results suggest that successful establishment of PVs in the host cell requires modulation of the Golgi apparatus which probably involves modifications in microtubule cytoskeleton organization and dynamics. These differences in how T. gondii and B. besnoiti interact with their host cells may indicate different evolutionary paths.
Neural Correlates of Rewarded and Unrewarded Eye Movements in the Primate Caudate Nucleus

The prospect of immediate reward elicits goal-oriented behavior. However, animals often have to perform actions that do not immediately lead to reward in the pursuit of a long-term goal. Here we identify neural activity in monkey caudate nucleus that specifically correlates with rewarded and unrewarded eye movements. The monkey performed a visually guided saccade task in which only one position was associated with positive reinforcement. To advance in the experimental session, however, the monkey had no choice but to complete a saccade to an unrewarded position as well as to a rewarded position. Some caudate saccadic neurons showed enhanced activity around the time of the saccade in rewarded trials (rewarded-saccade neurons). Another subset of neurons discharged selectively around the execution of the saccade in unrewarded trials (unrewarded-saccade neurons). In both rewarded and unrewarded trials, stronger activity of these neurons was associated with reduced saccade latency. These results suggest that both rewarded and unrewarded saccades are facilitated by caudate saccadic activity. The neuronal activity of unrewarded-saccade neurons might reflect the required execution of unrewarded eye movements on the way to future reward.
Closing the achievement gap between high-poverty schools and low-poverty schools

We examine the achievement gap between low-income minority students in inner city (high-poverty) schools and their white high-income counterparts who attend suburban (lowpoverty) schools. Our data include the 4 and 5 grade math and reading scores for over 15,000 students in a large urban school district. We use a multilevel model to show that school resources do matter. We find that high quality teachers have a significant and positive effect on student test scores and that smaller class size, especially in low performing schools, contributes to higher student achievement. Although school resource variables do matter in our model, they are far less important predictors of student test scores than are the student background variables. Unfortunately, our results lead to the conclusion that schools, alone, cannot close the achievement gap although we do find that better schools raise reading and math scores for the average student in a low performing school by about 12%.
A Census of Metals at High and Low Redshift and the Connection Between Submillimetre Sources and Spheroid Formation

Deep surveys in many wavebands have shown that the rate at which stars were forming was at least a factor of 10 higher at redshifts >1 than today. Heavy elements (‘metals’) are produced by stars, and the star formation history deduced by these surveys implies that a significant fraction of all metals in the Universe today should already exist at z? 2–3. However, only 10 per cent of the total metals expected to exist at this redshift have so far been accounted for (in damped Lyman absorbers and the Lyman forest). In this paper, we use the results of submillimetre surveys of the local and high-redshift Universe to show that there was much more dust in galaxies in the past. We find that a large proportion of the missing metals are traced by this dust, bringing the metals implied from the star formation history and observations into agreement. We also show that the observed distribution of dust masses at high redshift can be reproduced remarkably well by a simple model for the evolution of dust in spheroids, suggesting that the descendants of the dusty galaxies found in deep submillimetre surveys are the relatively dust-free spiral bulges and ellipticals in the Universe today
Antimicrobial Efficacy of Probiotic and Herbal Oral Rinses against Candida albicans in Children: A Randomized Clinical Trial

ABSTRACT Background: A growing number of dentists are embracing the philosophy that natural agents are better for children’s oral health. Knowledge of probiotics on host immune system has entered a new phase of research, and progression in this field is likely to offer novel means by modulating host immunity for prevention and treatment of a wide variety of oral diseases. Aim: To compare the antimicrobial efficacy of probiotics in reducing salivary Candida albicans counts with commonly used antimicrobial agents like 0.2% chlorhexidine and herbal rinse. Materials and methods: A randomized clinical trial was conducted on 60 subjects aged between 6 and 14 years, for a period of 9 months. The subjects were randomly divided into three groups comprising 20 subjects in each group. Three oral agents were administered twice daily for a maximum period of 1 week. Candida albicans counts were recorded before and after intervention and the results were submitted for statistical analysis using Statistical Package for the Social Sciences (SPSS) version 15.0 software. Results: The change in mean log10 colony-forming unit (CFU)/ ml of C. albicans in groups A to C was 0.43 ± 0.72, 0.68 ± 1.05 and 0.22 ± 0.66 CFU/ml respectively. Conclusion: Data obtained from the study demonstrated that probiotic rinse was equally effective as 0.2% chlorhexidine digluconate rinse in reducing C. albicans counts after 1 week of intervention. Herbal oral rinse was least effective. Probiotic oral rinses have opened new horizons in improvement of oral health by maintaining healthy ecosystem. However, a longitudinal study with larger sample size needs to be undertaken to evaluate the therapeutic effects of probiotics and herbal agents. How to cite this article: Mishra R, Tandon S, Rathore M, Banerjee M. Antimicrobial Efficacy of Probiotic and Herbal Oral Rinses against Candida albicans in Children: A Randomized Clinical Trial. Int J Clin Pediatr Dent 2016;9(1):25-30.
Complex Quadratic Optimization and Semidefinite Programming

In this paper we study the approximation algorithms for a class of discrete quadratic optimization problems in the Hermitian complex form. A special case of the problem that we study corresponds to the max-3-cut model used in a recent paper of Goemans and Williamson J. Comput. System Sci., 68 (2004), pp. 442-470]. We first develop a closed-form formula to compute the probability of a complex-valued normally distributed bivariate random vector to be in a given angular region. This formula allows us to compute the expected value of a randomized (with a specific rounding rule) solution based on the optimal solution of the complex semidefinite programming relaxation problem. In particular, we present an $[m^2(1-\cos\frac{2\pi}{m})/8\pi]$-approximation algorithm, and then study the limit of that model, in which the problem remains NP-hard. We show that if the objective is to maximize a positive semidefinite Hermitian form, then the randomization-rounding procedure guarantees a worst-case performance ratio of $\pi/4 \approx 0.7854$, which is better than the ratio of $2/\pi \approx 0.6366$ for its counterpart in the real case due to Nesterov. Furthermore, if the objective matrix is real-valued positive semidefinite with nonpositive off-diagonal elements, then the performance ratio improves to 0.9349.
Clinical Benefit of Combination Treatment with 1,550 nm Fractional Laser and a New Wavelength at 1,927 nm on Photorejuvenation in Asian Patients

Results A total of 25 patients were evaluated. Patients were followed up for up to 12 months (4.04 ± 2.78 months). The overall clinical improvement was 2.12 (Pigment improvement: 1.92 ± 0.84, wrinkle and skin texture; 1.66 ± 0.54). Melanin index showed a substantial decrease after treatments. One patient experienced post inflammatory hyperpigmentation, which subsided with administration of a topical bleaching agent after six months.
Structural basis for a novel mechanism of DNA bridging and alignment in eukaryotic DSB DNA repair

Eukaryotic DNA polymerase mu of the PolX family can promote the association of the two 3′‐protruding ends of a DNA double‐strand break (DSB) being repaired (DNA synapsis) even in the absence of the core non‐homologous end‐joining (NHEJ) machinery. Here, we show that terminal deoxynucleotidyltransferase (TdT), a closely related PolX involved in V(D)J recombination, has the same property. We solved its crystal structure with an annealed DNA synapsis containing one micro‐homology (MH) base pair and one nascent base pair. This structure reveals how the N‐terminal domain and Loop 1 of Tdt cooperate for bridging the two DNA ends, providing a templating base in trans and limiting the MH search region to only two base pairs. A network of ordered water molecules is proposed to assist the incorporation of any nucleotide independently of the in trans templating base. These data are consistent with a recent model that explains the statistics of sequences synthesized in vivo by Tdt based solely on this dinucleotide step. Site‐directed mutagenesis and functional tests suggest that this structural model is also valid for Pol mu during NHEJ.
Modeling and Estimation for Real-Time Microarrays

Microarrays are used for collecting information about a large number of different genomic particles simultaneously. Conventional fluorescent-based microarrays acquire data after the hybridization phase. During this phase, the target analytes (e.g., DNA fragments) bind to the capturing probes on the array and, by the end of it, supposedly reach a steady state. Therefore, conventional microarrays attempt to detect and quantify the targets with a single data point taken in the steady state. On the other hand, a novel technique, the so-called real-time microarray, capable of recording the kinetics of hybridization in fluorescent-based microarrays has recently been proposed. The richness of the information obtained therein promises higher signal-to-noise ratio, smaller estimation error, and broader assay detection dynamic range compared to conventional microarrays. In this paper, we study the signal processing aspects of the real-time microarray system design. In particular, we develop a probabilistic model for real-time microarrays and describe a procedure for the estimation of target amounts therein. Moreover, leveraging on system identification ideas, we propose a novel technique for the elimination of cross hybridization. These are important steps toward developing optimal detection algorithms for real-time microarrays, and to understanding their fundamental limitations.
On deep reinforcement learning for data-driven traffic control

To cope with the ever increasing traﬃc congestion in road networks, there is a need for methods to handle more cars with less time and space. Traﬃc lights and their corresponding scheduling algorithms play a key role in eﬀectively managing traﬃc ﬂows. Scheduling algorithms currently employed throughout world wide road networks are static, while research points out that with the usage of smart road sensors and dynamic machine learning techniques based on reinforcement learning , the average waiting times and throughput of a road network can signiﬁcantly be improved upon. In this research, we advance the current state-of-the-art further in both intelligent transport and reinforcement learning by proposing and analyzing a technique called deep reinforcement learning in data-driven traﬃc light scheduling controllers. We aim to give insight into the traﬃc light scheduling problem itself, how machine learning techniques can be applied within this problem domain, and what the current state-of-the-art is in data-driven traﬃc light scheduling. Using these insights, we present several traﬃc light scheduling algorithms based on deep reinforcement learning and a generalized traﬃc simulation framework, which allows us to realistically model complex traﬃc ﬂows through user-deﬁned road networks, such that we can benchmark diﬀerent types of traﬃc light scheduling algorithms. Ultimately, using the generalized traﬃc simulation framework, we show that the scheduling algorithms based on deep reinforcement learning outperform the current state-of-the-art algorithms signiﬁcantly, cutting vehicle waiting times in highly congestive situations by 58 − 86% (76% on average) when compared to traditional timing-based algorithms widely deployed across the real-world, and by 29 − 77% (59% on average) when compared to researched traditional reinforcement learning algorithms.
The HACMS program: using formal methods to eliminate exploitable bugs

For decades, formal methods have offered the promise of verified software that does not have exploitable bugs. Until recently, however, it has not been possible to verify software of sufficient complexity to be useful. Recently, that situation has changed. SeL4 is an open-source operating system microkernel efficient enough to be used in a wide range of practical applications. Its designers proved it to be fully functionally correct, ensuring the absence of buffer overflows, null pointer exceptions, use-after-free errors, etc., and guaranteeing integrity and confidentiality. The CompCert Verifying C Compiler maps source C programs to provably equivalent assembly language, ensuring the absence of exploitable bugs in the compiler. A number of factors have enabled this revolution, including faster processors, increased automation, more extensive infrastructure, specialized logics and the decision to co-develop code and correctness proofs rather than verify existing artefacts. In this paper, we explore the promise and limitations of current formal-methods techniques. We discuss these issues in the context of DARPA’s HACMS program, which had as its goal the creation of high-assurance software for vehicles, including quadcopters, helicopters and automobiles. This article is part of the themed issue ‘Verified trustworthy software systems’.