Miracle-dz/UniFAR-FTUs huggingface dataset:
Identification of Cholecystokinin by Genome-Wide Profiling as Potential Mediator of Serotonin-Dependent Behavioral Effects of Maternal Separation in the Amygdala

Converging evidence suggests a role of serotonin (5-hydroxytryptamine, 5-HT) and tryptophan hydroxylase 2 (TPH2), the rate-limiting enzyme of 5-HT synthesis in the brain, in modulating long-term, neurobiological effects of early-life adversity. Here, we aimed at further elucidating the molecular mechanisms underlying this interaction, and its consequences for socio-emotional behaviors, with a focus on anxiety and social interaction. In this study, adult, male Tph2 null mutant (Tph2-/-) and heterozygous (Tph2+/-) mice, and their wildtype littermates (Tph2+/+) were exposed to neonatal, maternal separation (MS) and screened for behavioral changes, followed by genome-wide RNA expression and DNA methylation profiling. In Tph2-/- mice, brain 5-HT deficiency profoundly affected socio-emotional behaviors, i.e., decreased avoidance of the aversive open arms in the elevated plus-maze (EPM) as well as decreased prosocial and increased rule breaking behavior in the resident-intruder test when compared to their wildtype littermates. Tph2+/- mice showed an ambiguous profile with context-dependent, behavioral responses. In the EPM they showed similar avoidance of the open arm but decreased prosocial and increased rule breaking behavior in the resident-intruder test when compared to their wildtype littermates. Notably, MS effects on behavior were subtle and depended on the Tph2 genotype, in particular increasing the observed avoidance of EPM open arms in wildtype and Tph2+/- mice when compared to their Tph2-/- littermates. On the genomic level, the interaction of Tph2 genotype with MS differentially affected the expression of numerous genes, of which a subset showed an overlap with DNA methylation profiles at corresponding loci. Remarkably, changes in methylation nearby and expression of the gene encoding cholecystokinin, which were inversely correlated to each other, were associated with variations in anxiety-related phenotypes. In conclusion, next to various behavioral alterations, we identified gene expression and DNA methylation profiles to be associated with TPH2 inactivation and its interaction with MS, suggesting a gene-by-environment interaction-dependent, modulatory function of brain 5-HT availability.
In vivo wear determination of novel CAD/CAM ceramic crowns by using 3D alignment

PURPOSE To determine wear amount of single molar crowns, made from four different restoratives, and opposing natural teeth through computerized fabrication techniques using 3D image alignment. MATERIALS AND METHODS A total of 24 single crowns (N = 24 patients, age range: 18 – 50) were made from lithium disilicate (IPS E-max CAD), lithium silicate and zirconia based (Vita Suprinity CAD), resin matrix ceramic material (Cerasmart, GC), and dual matrix (Vita Enamic CAD) blocks. After digital impressions (Cerec 3D Bluecam, DentsplySirona), the crowns were designed and manufactured (Cerec 3, DentsplySirona). A dual-curing resin cement was used for cementation (Variolink Esthetic DC, Ivoclar). Then, measurement and recording of crowns and the opposing enamel surfaces with the intraoral scanner were made as well as at the third and sixth month follow-ups. All measurements were superimposed with a software (David-Laserscanner, V3.10.4). Volume loss due to wear was calculated from baseline to follow-up periods with Siemens Unigraphics NX 10 software. Statistical analysis was accomplished by Repeated Measures for ANOVA (SPSS 21) at = . 05 significance level. RESULTS After 6 months, insignificant differences of the glass matrix and resin matrix materials for restoration/enamel wear were observed (P>.05). While there were no significant differences between the glass matrix groups (P>.05), significant differences between the resin matrix group materials (P<.05) were obtained. Although Cerasmart and Enamic were both resin matrix based, they exhibited different wear characteristics. CONCLUSION Glass matrix materials showed less wear both on their own and opposing enamel surfaces than resin matrix ceramic materials.
Enhanced Face Recognition by Fusion of Global and Local Features under Varying Illumination

We propose a new method to enhance performance of face recognition under varying lightings by applying score-level fusion between global and local Fourier-Mellin Transform (FMT) features based SVM. An optimal method based Particle Swarm Optimization (PSO) is used to find optimal weights to fuse the aforementioned information at score-level. The results on Korean face database demonstrate that our proposed method outperforms standard global feature, local feature and other well-known methods. Specifically, the best recognition rate is, respectively, 89% and 85% for indoor and outdoor images.
A predicted sex pheromone receptor of codling moth Cydia pomonella detects the plant volatile pear ester

Plant volatiles mediate host discrimination and host finding in phytophagous insects. Understanding how insects recognize these signals is a current challenge in chemical ecology research. Pear ester, ethyl (E,Z)-2,4-decadienoate, is a powerful, bisexual attractant of codling moth Cydia pomonella (Lepidoptera, Tortricidae) and strongly synergizes the male response to female-produced sex pheromone. We show here that the codling moth odorant receptor (OR) CpomOR3 is dedicated to detecting this plant volatile. Heterologous expression of CpomOR3 in Drosophila T1 trichoid and ab3A basiconic sensilla, followed by a screening with codling moth pheromone compounds and known plant volatile attractants, confirms that CpomOR3 binds to pear ester. Although CpomOR3 does not respond to any of the pheromone components tested, a phylogenetic analysis of lepidopteran chemosensory receptor genes reveals a close relationship of CpomOR3 with pheromone receptors (PRs) in moths. This corroborates the interaction of ecological and social chemosensory cues during premating communication. The finding that a plant volatile compound, pear ester, is a specific ligand for a PR-like lepidopteran receptor adds to our understanding of insect-plant interactions and emphasizes the interaction of natural and sexual selection during the phylogenetic divergence of insect herbivores.
Computation of Layered Reeb Graphs ∗

Reeb graphs represent the topological structure of a manifold based on a scalar-valued, sufficiently smooth function defined on it. The use of more than one function leads to Reeb spaces, which are thus able to capture more features of an object. The structure of the Reeb space of a 3-manifold with boundary with respect to two scalarvalued functions is captured by the layered Reeb graph. We present an efficient algorithm for computing such layered Reeb graphs, using only a boundary representation of the underlying manifold.
Combining keystroke and mouse dynamics for continuous user authentication and identification

In this paper, we analyze the performance of a continuous user authentication and identification system for a PC under various analysis techniques. We applied a novel identification technique called Pairwise User Coupling (PUC) on our own dataset for the analysis. This dataset is a combination of keystroke and mouse usage behaviour data. We obtained an identification accuracy of 62.2% for a closed-set experiment, where the system needs on average of 471 actions to detect an impostor. In case of an open-set experiment the Detection and Identification Rate (DIR) of 58.9% was obtained, where the system needs on average of 333 actions to detect an impostor.
Comparison of Methanol Exposure Routes Reported to Texas Poison Control Centers

Objective Methanol poisoning by ingestion is well represented in current emergency medicine literature. Much less described, however, is poisoning via intentional inhalation of methanol-containing products such as carburetor cleaner. This study intends to explore the exposure routes and treatment patterns of methanol cases reported to Texas Poison Centers. Methods All cases of methanol exposures from January 2003 to May 2005 were collected from the Texas Poison Center Network database “Toxicall. ” Inclusion criteria were 1) methanol as primary exposure, and 2) documented route of exposure. Exclusion criteria were unknown, dermal, and eye exposures. Data was extracted from documented calls to Texas Poison Centers and analyzed using descriptive statistics. Results A total of 203 cases were collected from 6 regional Poison Centers. Eighty seven cases had inhalation as the route of exposure, while 81 were methanol ingestions. Carburetor cleaner was responsible for nearly all the inhalational cases (79/87) while ingestions involved mostly windshield washer fluid (39/81) and carburetor cleaner (20/81). Seventy-eight percent of the inhalational exposures were intentional while most of the ingestions were accidental (49/75) and suicidal (18/75). An anion gap was documented in 31 of the inhalational cases and in 10 of the ingestions. Dialysis, use of fomepizole, and vision loss were documented for both types of exposure. Fifty-six percent of the inhalational group was admitted compared to 46% of the ingestion group. Conclusion We propose that the results obtained from our review show inhalational exposure involving methanol (e.g., “huffing”) represents a significant source of toxicity in the studied population. This is in contrast to previous literature that proposed inhalational toxicity was rare and aggressive treatment usually not necessary in cases of inhalation of methanol-containing carburetor cleaners.
Accelerating parser combinators with macros

Parser combinators provide an elegant way of writing parsers: parser implementations closely follow the structure of the underlying grammar, while accommodating interleaved host language code for data processing. However, the host language features used for composition introduce substantial overhead, which leads to poor performance. In this paper, we present a technique to systematically eliminate this overhead. We use Scala macros to analyse the grammar specification at compile-time and remove composition, leaving behind an efficient top-down, recursive-descent parser. We compare our macro-based approach to a staging-based approach using the LMS framework, and provide an experience report in which we discuss the advantages and drawbacks of both methods. Our library outperforms Scala's standard parser combinators on a set of benchmarks by an order of magnitude, and is 2x faster than code generated by LMS.
Diagnostic Efficacy MB Isoenzyme of a New Enzyme Immunoassay for Creatine Kinase

A new commercial enzyme immunoassay kit for quantification of creatine kinase-MB (CK-MB) isoenzyme was compared with its electrophoretic determination with respect to efficacy in diagnosis of acute myocardial infarction. Enzygnost’ CK-MB (Behnng Diagnostics) is a solid-phase “sandwich”-type enzyme immunoassay with antibodies to the Bsubunit coated on plastic tubes and peroxidase-conjugated antibodies to the M-subunit added after incubation with sample. This kit is designed to measure only CK-MB and not CK-MM, CK-BB, adenylate kinase, or atypical CK molecules. The linear-regression equation comparing the two methods was: Enzygnost = 0.98 electrophoresis 0.72, with a correlation coefficient of r = 0.967 (n = 143). For 51 patients admitted for diagnosis of possible acute myocardial infarction, the Enzygnost kit achieved 100% sensitivity, specificity, and efficiency in predicting the correct diagnosis. Corresponding values for the electrophoretic assay were: 95.5% sensitivity, 93.1% specificity, and 94.1% efficiency. We condude that this kit method provides an excellent alternative to electrophoresis.
NF-κB oscillations translate into functionally related patterns of gene expression

Several transcription factors (TFs) oscillate, periodically relocating between the cytoplasm and the nucleus. NF-κB, which plays key roles in inflammation and cancer, displays oscillations whose biological advantage remains unclear. Recent work indicated that NF-κB displays sustained oscillations that can be entrained, that is, reach a persistent synchronized state through small periodic perturbations. We show here that for our GFP-p65 knock-in cells NF-κB behaves as a damped oscillator able to synchronize to a variety of periodic external perturbations with no memory. We imposed synchronous dynamics to prove that transcription of NF-κB-controlled genes also oscillates, but mature transcript levels follow three distinct patterns. Two sets of transcripts accumulate fast or slowly, respectively. Another set, comprising chemokine and chemokine receptor mRNAs, oscillates and resets at each new stimulus, with no memory of the past. We propose that TF oscillatory dynamics is a means of segmenting time to provide renewing opportunity windows for decision. DOI: http://dx.doi. org/10.7554/eLife.09100. 001
Randomly select and forward: Erasure probability analysis of a probabilistic relay channel model

This paper proposes a semi-analytical framework for estimating the erasure probability in single-hop multi-relay networks. Specifically, we consider a system, in which relays do not decode the information but simply forward coded packets that have been previously received from the source. This allows for uncoordinated, low-complexity processing at the relays. We present a detailed analysis of the proposed network model, which represents an instance of a new coding scheme that we refer to as distributed fountain coding.
Incremental non-gaussian analysis of microarray gene expression data

The microarray is gaining popularity in biomedical research due to its ability to analyze hundreds to thousands of genes simultaneously in one experiment. However, the unique nature of microarray data, with a large number of features but relative small number of samples, poses challenges to process the microarray data effectively. The curse of dimensionality introduces the importance of feature extraction in analyzing microarray data. Therefore, we propose a novel incremental method to discover the non-Gaussian weight from the microarray gene expression data with high efficiency. Our proposed method can discover a small number of compact features from a huge number of genes and can still achieve good predictive performance. It integrates non-gaussianity and an adaptive incremental model in an unsupervised way to extract informative features. It is also plausible to analyze microarray data with the number of features much larger than number of observations with promising results.
Colon Cancer Stem Cells: Bench-to-Bedside—New Therapeutical Approaches in Clinical Oncology for Disease Breakdown

It is widely accepted by the scientific community that cancer, including colon cancer, is a “stem cell disease”. Until a few years ago, common opinion was that all neoplastic cells within a tumor contained tumorigenic growth capacity, but recent evidences hint to the possibility that such a feature is confined to a small subset of cancer-initiating cells, also called cancer stem cells (CSCs). Thus, malignant tumors are organized in a hierarchical fashion in which CSCs give rise to more differentiated tumor cells. CSCs possess high levels of ATP-binding cassette (ABC) transporters and anti-apoptotic molecules, active DNA-repair, slow replication capacities and they produce growth factors that confer refractoriness to antineoplastic treatments. The inefficacy of conventional therapies towards the stem cell population might explain cancer chemoresistance and the high frequency of relapse shown by the majority of tumors. Nowadays, in fact all the therapies available are not sufficient to cure patients with advanced forms of colon cancer since they target differentiated cancer cells which constitute most of the tumor mass and spare CSCs. Since CSCs are the entities responsible for the development of the tumor and represent the only cell population able to sustain tumor growth and progression, these cells represent the elective target for innovative therapies.
Measuring temporal turnover in ecological communities

Range migrations in response to climate change, invasive species and the emergence of novel ecosystems highlight the importance of temporal turnover in community composition as a fundamental part of global change in the Anthropocene. Temporal turnover is usually quantified using a variety of metrics initially developed to capture spatial change. However, temporal turnover is the consequence of unidirectional community dynamics resulting from processes such as population growth, colonisation and local extinction. Here, we develop a framework based on community dynamics and propose a new temporal turnover measure. A simulation study and an analysis of an estuarine fish community both clearly demonstrate that our proposed turnover measure offers additional insights relative to spatial context‐based metrics. Our approach reveals whether community turnover is due to shifts in community composition or in community abundance and identifies the species and/or environmental factors that are responsible for any change.
Biological Crystallography Structural Effects of Radiation Damage and Its Potential for Phasing

A detailed analysis of radiation-damage-induced structural and intensity changes is presented on the model protein thaumatin. Changes in re¯ection intensities induced by irradiation display a parabolic character. The most pronounced structural changes observed were disul®de-bond breakage and associated main-chain and side-chain movements as well as decarboxylation of aspartate and glutamate residues. The structural changes induced on the sulfur atoms were successfully used to obtain high-quality phase estimates via an RIP procedure. Results obtained with ACORN suggest that the contribution originating from the partial structure may play an important role in phasing even at less than atomic resolution.
Zero of the discrete beta function in SU(3) lattice gauge theory with color sextet fermions

We have carried out a Schrodinger functional calculation for the SU(3) lattice gauge theory with two flavors of Wilson fermions in the sextet representation of the gauge group. We find that the discrete beta function, which governs the change in the running coupling under a discrete change of spatial scale, changes sign when the Schrodinger functional renormalized coupling is in the neighborhood of g{sup 2}=2.0. The simplest explanation is that the theory has an infrared-attractive fixed point, but more complicated possibilities are allowed by the data. While we compare rescalings by factors of 2 and 4/3, we work at a single lattice spacing.
Un algorithme décentralisé d'apprentissage par renforcement multi-agents coopératifs : le Q-Learning Hystérétique.

Nous nous interessons aux techniques d'apprentissage par renforcement dans les systemes multi-agents cooperatifs. Nous presentons un nouvel algorithme pour agents independants qui permet d'apprendre l'action jointe optimale dans des jeux ou la coordination est difficile. Nous motivons notre approche par le caractere decentralise de cet algorithme qui ne necessite aucune communication entre agents et des tables Q de taille independante du nombre d'agents. Des tests concluants sont de plus effectues sur des jeux cooperatifs repetes, ainsi que sur un jeu de poursuite.
Learning deep representation from coarse to fine for face alignment

In this paper, we propose a novel face alignment method that trains deep convolutional network from coarse to fine. It divides given landmarks into principal subset and elaborate subset. We firstly keep a large weight for principal subset to make our network primarily predict their locations while slightly take elaborate subset into account. Next the weight of principal subset is gradually decreased until two subsets have equivalent weights. This process contributes to learn a good initial model and search the optimal model smoothly to avoid missing fairly good intermediate models in subsequent procedures. On the challenging COFW dataset [1], our method achieves 6.33% mean error with a reduction of 21.37% compared with the best previous result [2].
Feminine socialization or codependency

This descriptive research focused on the impact of feminine and masculine socialization and its' relationship to perceptions of "codependency" within the context of direct social work practice. Feminist critical theory provided a framework from which to examine the equating of traditional helping role expectations with behaviors that have been labelled as pathologically codependent. This perception of helping behaviors personalizes the problem, blaming people for assuming roles which were once considered normal, healthy, and functional, instead of locating the problem within society. The research sample consisted of 112 social workers (55 male and 57 females.) They responded to questionnaires containing demographic items and a Relational Responsibility (Codependency) Scale designed by the researchers to measure codependency in a hypothetical client. The data indicated that social workers* assessment support the valuation of "female" behaviors as less desirable or healthy than "male" behaviors. Both male and female social workers labeled helping behaviors as nonpathological.
Clustering-training for Data Stream Mining

Mining data streams has attracted much attention recently. Labeled samples needed by most current stream classification methods are more difficult and expensive to obtain than unlabeled ones. This paper proposed a semi-supervised learning algorithm - clustering-training to utilize the unlabeled samples. It uses clustering to select confidently unlabeled samples, and uses them to re-train the classifier incrementally. Experiments on synthetic and real data set showed the effectiveness of the proposed algorithm
Fast sequential and parallel algorithms for association rule mining: a comparison

The eld of knowledge discovery in databases, or \Data Mining", has received increasing attention during recent years as large organizations have begun to realize the potential value of the information that is stored implicitly in their databases. One speciic data mining task is the mining of Association Rules, particularly from retail data. The task is to determine patterns (or rules) that characterize the shopping behavior of customers from a large database of previous consumer transactions. The rules can then be used to focus marketing eeorts such as product placement and sales promotions. Because early algorithms required an unpredictably large number of IO operations, reducing IO cost has been the primary target of the algorithms presented in the literature. One of the most recent proposed algorithms, called PARTITION, uses a new TID-list data representation and a new partitioning technique. The partitioning technique reduces IO cost to a constant amount by processing one database portion at a time in memory. We implemented an algorithm called SPTID that incorporates both TID-lists and partitioning to study their beneets. For comparison, a non-partitioning algorithm called SEAR, which is based on a new preex-tree data structure, is used. Our experiments with SPTID and SEAR indicate that TID-lists have inherent ineeciencies; furthermore, because all of the algorithms tested tend to be CPU-bound, trading CPU-overhead against I/O operations by partitioning did not lead to better performance. In order to scale mining algorithms to the huge databases (e.g., multiple Terabytes) that large organizations will manage in the near future, we implemented parallel versions of SEAR and SPEAR (its partitioned counterpart). The performance results show that, while both algorithms parallelize easily and obtain good speedup and scale-up results, the parallel SEAR version performs better than parallel SPEAR, despite the fact that it uses more communication.