Miracle-dz/UniFAR-FTUs huggingface dataset:
Settling Down: The Genome of Serratia symbiotica from the Aphid Cinara tujafilina Zooms in on the Process of Accommodation to a Cooperative Intracellular Life

Particularly interesting cases of mutualistic endosymbioses come from the establishment of co-obligate associations of more than one species of endosymbiotic bacteria. Throughout symbiotic accommodation from a free-living bacterium, passing through a facultative stage and ending as an obligate intracellular one, the symbiont experiences massive genomic losses and phenotypic adjustments. Here, we scrutinized the changes in the coevolution of Serratia symbiotica and Buchnera aphidicola endosymbionts in aphids, paying particular attention to the transformations undergone by S. symbiotica to become an obligate endosymbiont. Although it is already known that S. symbiotica is facultative in Acyrthosiphon pisum, in Cinara cedri it has established a co-obligate endosymbiotic consortium along with B. aphidicola to fulfill the aphid’s nutritional requirements. The state of this association in C. tujafilina, an aphid belonging to the same subfamily (Lachninae) that C. cedri, remained unknown. Here, we report the genome of S. symbiotica strain SCt-VLC from the aphid C. tujafilina. While being phylogenetically and genomically very closely related to the facultative endosymbiont S. symbiotica from the aphid A. pisum, it shows a variety of metabolic, genetic, and architectural features, which point toward this endosymbiont being one step closer to an obligate intracellular one. We also describe in depth the process of genome rearrangements suffered by S. symbiotica and the role mobile elements play in gene inactivations. Finally, we postulate the supply to the host of the essential riboflavin (vitamin B2) as key to the establishment of S. symbiotica as a co-obligate endosymbiont in the aphids belonging to the subfamily Lachninane.
Structure and mechanism of error-free replication past the major benzo[a]pyrene adduct by human DNA polymerase κ

Abstract Benzo[a]pyrene (BP) is a well-known and frequently encountered carcinogen which generates a bulky DNA adduct (+)-trans-10S-BP-N2-dG (BP-dG) in cells. DNA polymerase kappa (polκ) is the only known Y-family polymerase that bypasses BP-dG accurately and thus protects cells from genotoxic BP. Here, we report the structures of human polκ in complex with DNA containing either a normal guanine (G) base or a BP-dG adduct at the active site and a correct deoxycytidine. The structures and supporting biochemical data reveal a unique mechanism for accurate replication by translesion synthesis past the major bulky adduct. The active site of polκ opens at the minor groove side of the DNA substrate to accommodate the bulky BP-dG that is attached there. More importantly, polκ stabilizes the lesion DNA substrate in the same active conformation as for regular B-form DNA substrates and the bulky BPDE ring in a 5′ end pointing conformation. The BP-dG adducted DNA substrate maintains a Watson–Crick (BP-dG:dC) base pair within the active site, governing correct nucleotide insertion opposite the bulky adduct. In addition, polκ's unique N-clasp domain supports the open conformation of the enzyme and the extended conformation of the single-stranded template to allow bypass of the bulky lesion. This work illustrates the first molecular mechanism for how a bulky major adduct is replicated accurately without strand misalignment and mis-insertion.
Verifiable Multi-Secret Sharing Schemes from Homogeneous Linear Recursion

The research on secure and efficient implementation method of secret sharing has been a hotspot in the field of information security and cryptography. Based on homogeneous linear recursion, we construct two new verifiable multi-secret sharing schemes. In our schemes, all participants themselves select their shares, so the calculation amount of dealer is reduced and secure channel between the dealer and any participant is avoided. Compared with other similar schemes, our schemes have more advantage, such as low calculation amount and no secure channel. In addition, security analysis also shows that our schemes can resist ordinary attacks.
Neuroendocrinology of a Male-Specific Pattern for Depression Linked to Alcohol Use Disorder and Suicidal Behavior

Epidemiological studies show low rates of diagnosed depression in men compared to women. At the same time, high rates of alcohol use disorders (AUDs) and completed suicide are found among men. These data suggest that a male-specific pattern for depression may exist that is linked to AUDs and suicidal behavior. To date, no underlying neuroendocrine model for this specific pattern of male depression has been suggested. In this paper, we integrate findings related to this specific pattern of depression with underlying steroid secretion patterns, polymorphisms, and methylation profiles of key genes in order to detail an original neuroendocrine model of male-specific depression. Low circulating levels of sex steroids seem to increase the vulnerability for male depression, while concomitant high levels of glucocorticoids further intensify this vulnerability. Interactions of hypothalamus–pituitary–gonadal (HPG) and hypothalamus–pituitary–adrenocortical (HPA) axis-related hormones seem to be highly relevant for a male-specific pattern of depression linked to AUDs and suicidal behavior. Moreover, genetic variants and the epigenetic profiles of the androgen receptor gene, well-known depression related genes, and HPA axis-related genes were shown to further interact with men’s steroid secretion and thus may further contribute to the proposed male-specific pattern for depression. This mini-review points out the multilevel interactions between the HPG and HPA axis for a male-specific pattern of depression linked to AUDs and suicidal behavior. An integration of multilevel interactions within the three-hit concept of vulnerability and resilience concludes the review.
Trafficking‐deficient mutant GABRG2 subunit amount may modify epilepsy phenotype

Genetic epilepsies and many other human genetic diseases display phenotypic heterogeneity, often for unknown reasons. Disease severity associated with nonsense mutations is dependent partially on mutation gene location and resulting efficiency of nonsense‐mediated mRNA decay (NMD) to eliminate potentially toxic proteins. Nonsense mutations in the last exon do not activate NMD, thus producing truncated proteins. We compared the protein metabolism and the impact on channel biogenesis, function, and cellular homeostasis of truncated γ2 subunits produced by GABRG2 nonsense mutations associated with epilepsy of different severities and by a nonsense mutation in the last exon unassociated with epilepsy.
Osteopenia, decreased bone formation and impaired osteoblast development in Sox4 heterozygous mice

The transcription factor Sox4 is vital for fetal development, as Sox4–/– homozygotes die in utero. Sox4 mRNA is expressed in the early embryonic growth plate and is regulated by parathyroid hormone, but its function in bone modeling/remodeling is unknown. We report that Sox4+/– mice exhibit significantly lower bone mass (by dual-energy X-ray absorptiometry) from an early age, and fail to obtain the peak bone mass of wild-type (WT) animals. Microcomputed tomography (μCT), histomorphometry and biomechanical testing of Sox4+/– bones show reduced trabecular and cortical thickness, growth plate width, ultimate force and stiffness compared with WT. Bone formation rate (BFR) in 3-month-old Sox4+/– mice is 64% lower than in WT. Primary calvarial osteoblasts from Sox4+/– mice demonstrate markedly inhibited proliferation, differentiation and mineralization. In these cultures, osterix (Osx) and osteocalcin (OCN) mRNA expression was reduced, whereas Runx2 mRNA was unaffected. No functional defects were found in osteoclasts. Silencing of Sox4 by siRNA in WT osteoblasts replicated the defects observed in Sox4+/– cells. We demonstrate inhibited formation and altered microarchitecture of bone in Sox4+/– mice versus WT, without apparent defects in bone resorption. Our results implicate the transcription factor Sox4 in regulation of bone formation, by acting upstream of Osx and independent of Runx2.
Pilot decontamination using combined angular and amplitude based projections in massive MIMO systems

We address the problem of noise and interference corrupted channel estimation in massive MIMO systems. Interference, which originates from pilot reuse (or contamination), can in principle be discriminated from the desired channels upon observing the distributions of path angles and amplitudes. In this paper we propose novel robust channel estimation algorithms exploiting path diversity in both angle and amplitude domains, relying on a suitable combination of a subspace projection and MMSE estimation. The proposed estimator improves on past methods in a wide range of system and topology scenarios.
An LR-inspired generalized lexicalized phrase structure parser

The paper introduces an LR-based algorithm for efficient phrase structure parsing of morphologically rich languages. The algorithm generalizes lexicalized parsing (Collins, 2003) by allowing a structured representation of the lexical items. Together with a discriminative weighting component (Collins, 2002), we show that this representation allows us to achieve state of the art accurracy results on a morphologically rich language such as French while achieving more efficient parsing times than the state of the art parsers on the French data set. A comparison with English, a lexically poor language, is also provided.
Decision Support System for Check-up Tracks in Prevention of Cardiac Diseases

Heart conditions are one of the most dominant health problems in Portugal, and the cause of the highest mortality rate. Check-Up Track is a system which allows patients to have a general overview of their health and suggests daily routine changes that they could make, or the system could advise them to seek medical advice. The system makes use of existing mechanisms, such as gym circuits, footpaths, and urban walking groups, by introducing intuitive and easy-access medical equipment like billboards and self-evaluation signs. In this paper we propose to develop a decision support system architecture that will allow the entire process of data capture, processing and the automatic and efficient output of results. The system will also allow statistical analysis of the data collected to help understand the current health status in any given region. Even though this paper is not bringing any innovation to the field of computer science, it aims to show the benefits that current computer science techniques and algorithms can bring to medicine or, in this case, Self-care medicine.
Arabic Tweets Treebanking and Parsing: A Bootstrapping Approach

In this paper, we propose using a “bootstrapping” method for constructing a dependency treebank of Arabic tweets. This method uses a rule-based parser to create a small treebank of one thousand Arabic tweets and a data-driven parser to create a larger treebank by using the small treebank as a seed training set. We are able to create a dependency treebank from unlabelled tweets without any manual intervention. Experiments results show that this method can improve the speed of training the parser and the accuracy of the resulting parsers.
Towards Hardware Realizations of Intelligent Systems: A Cortical Column Approach

Many researchers seek for alternatives to traditional computing architectures, often placing emphasis on modeling biological systems that possess intelligence and learning capabilities. Cortical columns have emerged as a high-level unsupervised learning model for extracting independent data features in a hierarchical manner. Previous cortical models simply rely on software based techniques and neglect the actual purpose of investigating these architectures: to diverge from the conventional Von Neumann approach to an actual hardware realization of an intelligent system. This work presents the hardware realization of a cortical column system, taking several factors into consideration which were previously disregarded by software models. We introduce a Neural Spike Dual-Rail communication scheme, and a temporal pooling unit capable of detecting data distortions during training and testing. This work concludes with a study on cortical columns and their hierarchical impact on hardware resources.
Fast image super-resolution using Connected Component enhancement

The paper focuses on reconstructing the discontinuity between homogenous color regions in an interpolated image to improve its perceptual quality. A low-resolution input image is firstly interpolated and then decomposed into several patches. Each patch is then segmented into multiple homogenous regions using connected component analysis technique. Then a spatial-filter is applied to enhance the color/intensity transition between neighboring components. The designed spatial-filter combines the advantages of both bilateral-filtering and unsharp masking methods, with high computational efficiency. The proposed method can be used for image/video super-resolution applications. Experimental results are promising.
Robust sensor cloud localization from range measurements

This work provides a feasibility study on estimating the 3-D locations of several thousand miniaturized free-floating sensor platforms. The localization is performed on basis of sparse ultrasound range measurements between sensor platforms and without the use of beacons. We show that this task can be viewed as a specific type of pose graph optimization. The main challenge is robustly estimating an initial pose graph, that models the locations of sensor platforms. For this, we introduce a novel graph growing strategy that uses random sample consensus in alternation with non-linear refinement. The theoretical properties of our sensor cloud localization method are analyzed and its robustness is investigated using simulations. These simulations are based on inlier-outlier measurement models and focus on the application of subterranean 3-D mapping of liquid environments, such as pipe infrastructures and oil wells.
Expression of cytokines and inducible nitric oxide synthase mRNA in the lungs of mice infected with Cryptococcus neoformans: effects of interleukin-12

We have recently established a murine model of pulmonary and disseminated infection with a highly virulent strain of Cryptococcus neoformans and demonstrated that administration of interleukin-12 (IL-12) protected the animals against infection. In this study, we extended these studies by investigating the host defense mechanisms. In particular, we examined the expression of mRNA for helper T-cell 1 (Th1) cytokines (IL-2, lymphotoxin, and gamma interferon [IFN-gamma]), Th2 cytokines (IL-4, -6, and -10), macrophage-derived cytokines (tumor necrosis factor alpha [TNF-alpha], IL-1beta, transforming growth factor beta [TGF-beta, IL-12p40, and IFN-gamma-inducing factor [IGIF]), and inducible nitric oxide synthase (iNOS) in the lungs on days 1, 3, 7, and 14 after infection and following treatment with IL-12. There was little or no expression of mRNAs for Th1 cytokines, TNF-alpha, IL-12p40, IGIF, and iNOS in the infected mice, but expression increased markedly after treatment with IL-12. In contrast, the mRNAs for Th2 cytokines, IL-1beta, and TGF-beta were detected at considerable levels during the early stages of infection, and, interestingly, expression was not suppressed by IL-12 but rather augmented, particularly during the late stage. Similar results were also obtained for IFN-gamma, IL-4, IL-10, and TNF-alpha measured in the lung homogenates by enzyme-linked immunosorbent assay. These results suggest that the predominance of expression of Th2 cytokines and TGF-beta over Th1 cytokines, TNF-alpha, IL-12p40, IGIF, and iNOS is associated with severe lethal infection in mice and that administration of IL-12 protects infected animals by stimulating Th1 cytokines.
Application of Partial Restarts in a Satisfiability Algorithm

In this paper I describe experiments in the application of dynamic restarts used in heuristic satisfiability algorithms. By modifying a state-of-the-art SAT solver, zchaff, I test three proposed modifications to typical restart policies: exponentially increasing restart thresholds, restricting restarts to occur only at certain critical points, and the addition of transient randomness after a restart. By comparing runtimes on several benchmarks, I evaluate many of the tradeoffs involved in choosing an appropriate restart policy and also attempt to tackle the question of whether or not to use restarts at all. Section 1 introduces Chaff and the basic ideas of restarts, section 2 gives background on research on dynamic restarts, sections 3-5 described our proposed experiment, sections 6-8 describe the procedure, section 9 tabulates the results, and sections 10-11 give my conclusions.
A Knowledge-Evolution Strategy Based on Genetic Programming

Knowledge evolution is an important issue in knowledge management since enterprises face keen competition and need to keep the latest knowledge with time in an organization. In this paper, we proposed a GP-based knowledge-evolution framework to search for a good integrated classification tree with different evolving time points. The proposed approach can learn the evolving knowledge, integrating original and new knowledge, to deal properly with the organizational need for updating the latest knowledge as time goes on in a dynamic environment. In addition, we developed the initial population, consisting of four proportions, to accomplish suitable diversity and thus raise the search range as well as next learning efficiency in the evolutionary process.
Empirical photometric redshifts of luminous red galaxies and clusters in the Sloan Digital Sky Survey

In this work I discuss the necessary steps for deriving photometric redshifts for luminous red galaxies (LRGs) and galaxy clusters through simple empirical methods. The data used are from the Sloan Digital Sky Survey (SDSS). I show that with three bands only (gri) it is possible to achieve results as accurate as the ones obtained by other techniques, generally based on more filters. In particular, the use of the (g - i) colour helps improving the final redshifts (especially for clusters), as this colour monotonically increases up to z ∼ 0.8. For the LRGs I generate a catalogue of ∼ 1.5 million objects at z < 0.70. The accuracy of this catalogue is a = 0.027 for z ≤ 0.55 and σ = 0.049 for 0.55 < z ≤ 0.70. The photometric redshift technique employed for clusters is independent of a cluster selection algorithm. Thus, it can be applied to systems selected by any method or wavelength, as long as the proper optical photometry is available. When comparing the redshift listed in literature to the photometric estimate, the accuracy achieved for clusters is σ = 0.024 for z ≤ 0.30 and a = 0.037 for 030 < z ≤ 0.55. However, when considering the spectroscopic redshift as the mean value of SDSS galaxies on each cluster region, the accuracy is at the same level as found by other authors: a = 0.011 for z ≤ 0.30 and a = 0.016 for 030 < z ≤ 0.55. The photometric redshift relation derived here is applied to thousands of cluster candidates selected elsewhere. I have also used galaxy photometric redshifts available in SDSS to identify groups in redshift space and then compare the redshift peak of the nearest group to each cluster redshift. This procedure provides an alternative approach for cluster selection, especially at high redshifts, as the cluster red sequence may be poorly defined.
The concert system--compiler and runtime support for efficient, fine-grained concurrent object-oriented programs

The introduction of concurrency complicates the already difficult task of large-scale programming. Concurrent object-oriented languages provide a mechanism, encapsulation, for managing the increased complexity of large-scale concurrent programs, thereby reducing the difficulty of large scale concurrent programming. In particular, fine-grained object-oriented approaches provide modularity through encapsulation while exposing large degrees of concurrency. Though fine-grained concurrent object-oriented languages are attractive from a programming perspective, they have historically suffered from poor efficiency. The goal of the Concert project is to develop portable, efficient implementations of fine-grained concurrent object-oriented languages. Our approach incorporates careful program analysis and information management at every stage from the compiler to the runtime system. In this document, we outline the basic elements of the Concert approach. In particular, we discuss program analyses, program transformations, their potential payoff, and how they will be embodied in the Concert system. Initial performance results and specific plans for demonstrations and system development are also detailed.
Ras and Calcium Signaling Pathways Converge at Raf1 via the Shoc2 Scaffold Protein

Activation of Raf1 at the plasma membrane requires not only Ras activation but also an increase in Ca2+ concentration or inhibition of calmodulin. The Ca2+-dependent activation of Raf1 is abrogated by knockdown of Shoc2. We show that the Shoc2 scaffold protein modulates Ras-dependent Raf1 activation in a Ca2+- and calmodulin-dependent manner.
A method for systematic discovery of adverse drug events from clinical notes

OBJECTIVE Adverse drug events (ADEs) are undesired harmful effects resulting from use of a medication, and occur in 30% of hospitalized patients. The authors have developed a data-mining method for systematic, automated detection of ADEs from electronic medical records. MATERIALS AND METHODS This method uses the text from 9.5 million clinical notes, along with prior knowledge of drug usages and known ADEs, as inputs. These inputs are further processed into statistics used by a discriminative classifier which outputs the probability that a given drug-disorder pair represents a valid ADE association. Putative ADEs identified by the classifier are further filtered for positive support in 2 independent, complementary data sources. The authors evaluate this method by assessing support for the predictions in other curated data sources, including a manually curated, time-indexed reference standard of label change events. RESULTS This method uses a classifier that achieves an area under the curve of 0.94 on a held out test set. The classifier is used on 2,362,950 possible drug-disorder pairs comprised of 1602 unique drugs and 1475 unique disorders for which we had data, resulting in 240 high-confidence, well-supported drug-AE associations. Eighty-seven of them (36%) are supported in at least one of the resources that have information that was not available to the classifier. CONCLUSION This method demonstrates the feasibility of systematic post-marketing surveillance for ADEs using electronic medical records, a key component of the learning healthcare system.