Miracle-dz/UniFAR-FTUs huggingface dataset:
metagene Profiles Analyses Reveal Regulatory Element’s Factor-Specific Recruitment Patterns

ChIP-Sequencing (ChIP-Seq) provides a vast amount of information regarding the localization of proteins across the genome. The aggregation of ChIP-Seq enrichment signal in a metagene plot is an approach commonly used to summarize data complexity and to obtain a high level visual representation of the general occupancy pattern of a protein. Here we present the R package metagene, the graphical interface Imetagene and the companion package similaRpeak. Together, they provide a framework to integrate, summarize and compare the ChIP-Seq enrichment signal from complex experimental designs. Those packages identify and quantify similarities or dissimilarities in patterns between large numbers of ChIP-Seq profiles. We used metagene to investigate the differential occupancy of regulatory factors at noncoding regulatory regions (promoters and enhancers) in relation to transcriptional activity in GM12878 B-lymphocytes. The relationships between occupancy patterns and transcriptional activity suggest two different mechanisms of action for transcriptional control: i) a “gradient effect” where the regulatory factor occupancy levels follow transcription and ii) a “threshold effect” where the regulatory factor occupancy levels max out prior to reaching maximal transcription. metagene, Imetagene and similaRpeak are implemented in R under the Artistic license 2.0 and are available on Bioconductor.
Option trading and individual investor performance q , qq

This paper examines the impact of option trading on individual investor performance. The results show that most investors incur substantial losses on their option investments, which are much larger than the losses from equity trading. We attribute the detrimental impact of option trading on investor performance to poor market timing that results from overreaction to past stock market returns. High trading costs further contribute to the poor returns on option investments. Gambling and entertainment appear to be the most important motivations for trading options while hedging motives only play a minor role. We also provide strong evidence of performance persistence among option traders. 2008 Elsevier B.V. All rights reserved.
Nuclear DNA content and karyotype of Rosewood (Aniba rosaeodora)

Rosewood (Aniba rosaeodora Ducke, Lauraceae) is ecologically and economically important to the Amazon region. As a consequence of its economic importance, rosewood populations have been decimated in the Amazon forest. Species of nine genera of the Lauraceae family have characterized karyotypes with n = x = 12 chromosomes in the gametophytic phase but the genus Aniba is one of the least studied Lauraceae genera with a previously undescribed genome. We used cytogenetic techniques to determine that the A. rosaeodora karyotype contained 12 pairs (2n = 24) of relatively small submetacentric chromosomes with lengths ranging from 1.34 to 2.25 mm and a nucleolar organizer region (NOR) in the short arm of chromosome 7. Flow cytometry gave 2C = 2.32 pg of DNA, equivalent to approximately 2.24 x 109 base pairs.
Advances in the pharmacotherapy of chronic heart failure with preserved ejection fraction: an ideal opportunity for precision medicine

ABSTRACT Introduction: Heart failure with preserved ejection fraction (HFpEF), which comprises approximately 50% of all heart failure patients, is a challenging and complex clinical syndrome that is often thought to lack effective treatments. Areas covered: Despite the common mantra that HFpEF has no effective treatments, closer inspection of HFpEF clinical trials reveals that several of the drugs tested are associated with benefits in exercise capacity and quality of life, and reduction in heart failure hospitalization. Here we review major randomized controlled trials in HFpEF, focusing on renin-angiotensin-aldosterone system antagonists, organic nitrates, digoxin, beta-blockers, and phosphodiesterase-5 inhibitors. In addition, we review several classes of drugs currently in development for HFpEF such as neprilysin inhibitors, inorganic nitrates (nitrites), and soluble guanylate cyclase stimulators. Expert opinion: HFpEF should not be viewed as lacking effective treatments. While there have been no breakthrough clinical trials showing a reduction in mortality, several existing medications are likely to benefit specific subgroups of HFpEF patients. HFpEF is now well known to be a heterogeneous syndrome; thus, the clinical management of HFpEF patients and future HFpEF clinical trials will both likely require a nuanced, phenotype-specific approach instead of a one-size-fits-all tactic. Drug development for HFpEF therefore represents an exciting opportunity for personalized medicine.
Chronic EtOH effects on putative measures of compulsive behavior in mice

Addictions, including alcohol use disorders, are characterized by the loss of control over drug seeking and consumption, but the neural circuits and signaling mechanisms responsible for the transition from controlled use to uncontrolled abuse remain incompletely understood. Prior studies have shown that ‘compulsive‐like’ behaviors in rodents, for example, persistent responding for ethanol (EtOH) despite punishment, are increased after chronic exposure to EtOH. The main goal of the current study was to assess the effects of chronic intermittent EtOH (CIE) exposure on multiple, putative measures of compulsive‐like EtOH seeking in C57BL/6 J mice. Mice were exposed to two or four weekly cycles of CIE and then, post‐withdrawal, tested for progressive ratio responding for EtOH, sustained responding during signaled EtOH unavailability and (footshock) punished suppression of responding for EtOH. Results showed that mice exposed to CIE exhibited attenuated suppression of EtOH seeking during punishment, as compared with air‐exposed controls. By contrast, CIE exposure affected neither punished food reward‐seeking behavior, nor other putative measures of compulsive‐like EtOH seeking. Ex vivo reverse transcription polymerase chain reaction analysis of brain tissue found reduced sensitivity to punished EtOH seeking after CIE exposure was accompanied by a significant increase in gene expression of the GluN1 and GluN2A subunits of the N‐methyl‐d‐aspartate receptor, specifically in the medial orbitofrontal cortex. Moreover, slice electrophysiological analysis revealed increased N‐methyl‐d‐aspartate receptor‐mediated currents in the orbitofrontal cortex after CIE exposure in test‐naïve mice. Collectively, the current findings add to the growing body of evidence demonstrating that chronic exposure to EtOH fosters resistance to punished EtOH seeking in association with adaptations in cortical glutamatergic transmission.
Assessment of three devices used in shear tests of cooked breast meat.

Methods that increase processing efficiency to save energy costs and to improve yield and volume must be evaluated in terms of maintaining or improving final product quality. Shear tests measure the force to cut through fibers of cooked samples. They are the simplest and most common tests used to document cooked meat texture. However, information obtained from shearing devices that perform in a similar way may not be interchangeable. In this study, three shearing devices were assessed. Eight treatments were imposed on broiler breasts processed under commercial conditions to represent ranges of texture characteristics. Treatments included electrical stimulation (S), or no stimulation (NS) of carcasses; postchill deboning at 2 or 6 h; and marination (M), or no marination (NM). Shear force values of cooked breasts were obtained from the benchtop Warner-Bratzler (BT-WB) machine, the Warner-Bratzler blade attachment (TA-WB) and a 45 degrees chisel-end blade attachment (TA-WD). The TA-WB and TA-WD were attached to Model TA.XT2 texture analyzer. For each device, shear value differences were significant (P < 0.05) for deboning time. Marination effects were significant (P < 0.05) for BT-WB and TA-WB. Stimulation by debone interactions were significant (P < 0.05) for BT-WB and TA-WD. The TA-WD values varied the greatest over all treatments (SD = 5.52; SE = 0.65). Variations of BT-WB and TA-WB shear values were similar (SD = 3.25, 2.97, respectively; SE = 0.38, 0.35).
Iron depletion enhances the effect of sorafenib in hepatocarcinoma

ABSTACT Human hepatocellular carcinoma (HCC) is known to have a poor prognosis. Sorafenib, a molecular targeted drug, is most commonly used for HCC treatment. However, its effect on HCC is limited in clinical use and therefore new strategies regarding sorafenib treatment are required. Iron overload is known to be associated with progression of chronic hepatitis and increased risk of HCC. We previously reported that iron depletion inhibited cancer cell proliferation and conversely induced angiogenesis. Indeed iron depletion therapy including iron chelator needs to be combined with anti-angiogenic drug for its anti-cancer effect. Since sorafenib has an anti-angiogenic effect by its inhibitory targeting VEGFR, we hypothesized that sorafenib could complement the anti-cancer effect of iron depletion. We retrospectively analyzed the relationship between the efficacy of sorafenib and serum iron-related markers in clinical HCC patients. In clinical cases, overall survival was prolonged in total iron binding capacity (TIBC) high- and ferritin low-patients. This result suggested that the low iron-pooled patients, who could have a potential of more angiogenic properties in/around HCC tumors, could be adequate for sorafenib treatment. We determined the effect of sorafenib (Nexavar®) and/or deferasirox (EXJADE®) on cancer cell viability, and on cell signaling of human hepatocarcinoma HepG2 and HLE cells. Both iron depletion by deferasirox and sorafenib revealed insufficient cytotoxic effect by each monotherapy, however, on the basis of increased angiogenesis by iron depletion, the addition of deferasirox enhanced anti-proliferative effect of sorafenib. Deferasirox was confirmed to increase vascular endothelial growth factor (VEGF) secretion into cellular supernatants by ELISA analysis. In in vivo study sorafenib combined with deferasirox also enhanced sorafenib-induced apoptosis. These results suggested that sorafenib combined with deferasirox could be a novel combination chemotherapy for HCC.
The Strength of Weak Randomization: Efficiently Searchable Encryption with Minimal Leakage

Efficiently searchable and easily deployable encryption schemes enable an untrusted, legacy service such as a relational database engine to perform searches over encrypted data. The ease with which such schemes can be deployed on top of existing services makes them especially appealing in operational environments where encryption is needed but it is not feasible to replace large infrastructure components like databases or document management systems. Unfortunately all previously known approaches for efficiently searchable encryption are vulnerable to inference attacks where an adversary can use knowledge of the distribution of the data to recover the plaintext with high probability. In this paper, we present the first efficiently searchable, easily deployable database encryption scheme that is provably secure against inference attacks even when used with real, low-entropy data. Ours is also the only efficiently searchable construction that provides any provable security for protecting multiple related attributes (columns) in the same database. Using this ESE construction as a building block, we give an efficient construction for performing range queries over encrypted data. We implemented our constructions in Haskell and used them to query encrypted databases of up to 10 million records. In experiments with a local Postgres database and with a Google Cloud Platform database, the response time for our encrypted queries is not excessively slower than for plaintext queries. With the use of parallel query processing, our encrypted queries can achieve similar and in some cases superior performance to queries on the plaintext.
The effect of enzyme supplementation on the apparent metabolizable energy and nutrient digestibilities of wheat, barley, oats, and rye for the young broiler chick.

The influence of enzyme supplementation on the bioavailable energy (AME(n)) and apparent digestibilities of lipid (ALD) and protein (APD) in young broiler chicks was examined for diets containing either wheat, hulled or hulless barley, naked oats, or spring rye. Dietary AME(n), APD, and ALD values were depressed (P less than or equal to .01) for all test grains (except hulled Bedford barley) as the inclusion rate of the grain replacing wheat increased. The antinutritives, beta-glucans (barley and oats) and pentosans (rye), had the most pronounced effect on ALD. The decreases in ALD were 43, 77, and 67% for chicks fed diets containing 70% Scout barley (hulless), Terra oats, and Gazelle rye, respectively, compared with those fed the control wheat diet. Enzyme supplementation increased (P less than or equal to .01) AME(n), APD, and ALD for all test cereals. The corresponding increases in the AME(n), of the enzyme-supplemented diets containing 70% HY320 wheat, Bedford barley, Scout barley, Terra oats, and Gazelle rye diets were 4, 7, 42, 33, and 14%, respectively, compared with their unsupplemented counterparts. Enzyme treatment also improved (P less than or equal to .01) weight gains and feed conversion efficiencies of chicks fed diets containing each of the cereals. Overall, the results demonstrate that the nutritive value of cereal grains such as wheat, barley, oats, and rye can be improved by the addition of crude fungal extracts to the diet of young chicks.
Influence of wood on the pyrolysis of poultry litter

Pyrolytic oils produced from poultry litter differ in physico-chemical properties and the chemical composition. The litter is composed of manure and bedding material with traces of spilled feed and feathers. The type and amount of bedding material was varied to investigate its influence on the pyrolysis of layer manure. 400g of each feedstock: manure, wood (pine and oak), and mixtures of manure and wood in proportions (75:25 50:50, and 25:75 w/w %) respectively were subjected to fast pyrolysis at 450C in a fluidized bed reactor. The total pyrolytic oil yield ranged from 43.3% to 64.5 wt%. The highest bio oil yield and the lowest char yield were obtained from oak wood. The manure oil had the highest HHV of 29.7 MJ/kg, the highest pH (5.89), the lowest density (1.14 g/cm) and a relatively low viscosity of 130cSt. The oils had relatively high nitrogen content ranging from 5.88wt% to 1.36 wt%; low ash content (approximately <0.07wt %) and low sulfur content (<0.28wt %). FT-IR, CNMR, and HNMR analysis showed that manure oil was rich in aliphatic hydrocarbon and primary and secondary amides and the addition of wood introduced oxygenated compounds like aliphatic alcohols, phenols, aromatic ethers, and carbonyl/carboxylic groups into the oil. TG/DTG analysis also showed that the thermal decomposition of the oils were different depending on the amount and the type of wood in the manure/wood mixture. The parametric variables used for the mixture of 50% manure and 50% pine wood shavings study were; temperature (400-550°C), nitrogen gas flow rate (12-24 L/min), and feed rate (160-480 g/h). The results showed that the pyrolysis product yields, physical properties and the chemical composition of the oil were influenced by all parameters. Temperature was the most influential factor and its effect on the liquid, char and gas yields were significant. It was evident that depending on the gas flow rate and the feed rate, a maximum oil yield (51.1wt.%) can be achieved between 400-500 C. Also an increase in temperature significantly increased the oil viscosity and decreased the carbonyl/carboxylic and the primary aliphatic alcohol functional groups in the oil. The study on the influence of wood on the stability of the oils when stored at ambient conditions for 8 months in a 30ml glass bottle showed that the viscosity of the oils increases when stored, however the manure oil was relatively more stable and the oil from the 50/50 mixture for both pine and oak was the least stable. It was found that the stability of the oils from the manure and wood mixtures were dependent on the amount and the type of wood (pine or oak) added to the manure. Also the addition of 10% solvent (methanol/ethanol) to the oil from 50% manure and 50% pine reduced the initial viscosity of the oil and was also beneficial in slowing down the increase in viscosity during storage.
CATEGORICITY AND TOPOLOGICAL GRAPHS

Let X be a topological graph; i.e., a union of nitely many points and arcs, with arcs joined only at end points. If Y is any locally connected metrizable compactum that is co-elementarily equivalent to X, then Y is homeomorphic to X. In particular, X and Y are homeomorphic if some lattice base for one is elementarily equivalent to some lattice base for the other.
Sentence Boundary Detection for French with Subword-Level Information Vectors and Convolutional Neural Networks

In this work we tackle the problem of sentence boundary detection applied to French as a binary classification task ("sentence boundary" or "not sentence boundary"). We combine convolutional neural networks with subword-level information vectors, which are word embedding representations learned from Wikipedia that take advantage of the words morphology; so each word is represented as a bag of their character n-grams. We decide to use a big written dataset (French Gigaword) instead of standard size transcriptions to train and evaluate the proposed architectures with the intention of using the trained models in posterior real life ASR transcriptions. Three different architectures are tested showing similar results; general accuracy for all models overpasses 0.96. All three models have good F1 scores reaching values over 0.97 regarding the "not sentence boundary" class. However, the "sentence boundary" class reflects lower scores decreasing the F1 metric to 0.778 for one of the models. Using subword-level information vectors seem to be very effective leading to conclude that the morphology of words encoded in the embeddings representations behave like pixels in an image making feasible the use of convolutional neural network architectures.
RHD Tyr311Stop encoded by a novel nonsense mutation

A complete deletion of the RHD gene (RHD*01N.01) is known as the most frequent molecular background accounting for D negativity among Caucasians. Besides, several RHDCE-D hybrid alleles, splice site changes, and nonsense mutations throughout the RHD gene were associated with a non-functional RhD protein. With the purpose of excluding an aberrant RHD allele that may cause a low-level expression of antigen D, the blood sample of a seemingly D– patient, positive for C, underwent further characterization.
A Neural Multi-sequence Alignment TeCHnique (NeuMATCH)

The alignment of heterogeneous sequential data (video to text) is an important and challenging problem. Standard techniques for this task, including Dynamic Time Warping (DTW) and Conditional Random Fields (CRFs), suffer from inherent drawbacks. Mainly, the Markov assumption implies that, given the immediate past, future alignment decisions are independent of further history. The separation between similarity computation and alignment decision also prevents end-to-end training. In this paper, we propose an end-to-end neural architecture where alignment actions are implemented as moving data between stacks of Long Short-term Memory (LSTM) blocks. This flexible architecture supports a large variety of alignment tasks, including one-to-one, one-to-many, skipping unmatched elements, and (with extensions) non-monotonic alignment. Extensive experiments on semi-synthetic and real datasets show that our algorithm outperforms state-of-the-art baselines.
Tracking All Members of a Honey Bee Colony Over Their Lifetime Using Learned Models of Correspondence

Computational approaches to the analysis of collective behavior in social insects increasingly rely on motion paths as an intermediate data layer from which one can infer individual behaviors or social interactions. Honey bees are a popular model for learning and memory. Previous experience has been shown to affect and modulate future social interactions. So far, no lifetime history observations have been reported for all bees of a colony. In a previous work we introduced a recording setup customized to track up to 4,000 marked bees over several weeks. Due to detection and decoding errors of the bee markers, linking the correct correspondences through time is non-trivial. In this contribution we present an in-depth description of the underlying multi-step algorithm which produces motion paths, and also improves the marker decoding accuracy significantly. The proposed solution employs two classifiers to predict the correspondence of two consecutive detections in the first step, and two tracklets in the second. We automatically tracked ~2,000 marked honey bees over 10 weeks with inexpensive recording hardware using markers without any error correction bits. We found that the proposed two-step tracking reduced incorrect ID decodings from initially ~13% to around 2% post-tracking. Alongside this paper, we publish the first trajectory dataset for all bees in a colony, extracted from ~3 million images covering 3 days. We invite researchers to join the collective scientific effort to investigate this intriguing animal system. All components of our system are open-source.
The story of protein arginine methylation: characterization, regulation, and function

ABSTRACT Introduction: Arginine methylation is an important post-translational modification (PTM) in cells, which is catalyzed by a group of protein arginine methyltransferases (PRMTs). It plays significant roles in diverse cellular processes and various diseases. Misregulation and aberrant expression of PRMTs can provide potential biomarkers and therapeutic targets for drug discovery. Areas covered: Herein, we review the arginine methylation literature and summarize the methodologies for the characterization of this modification, as well as describe the recent insights into arginine methyltransferases and their biological functions in diseases. Expert commentary: Benefits from the enzyme-based large-scale screening approach, the novel affinity enrichment strategies, arginine methylated protein family is the focus of attention. Although a number of arginine methyltransferases and related substrates are identified, the catalytic mechanism of different types of PRMTs remains unclear and few related demethylases are characterized. Novel functional studies continuously reveal the importance of this modification in the cell cycle and diseases. A deeper understanding of arginine methylated proteins, modification sites, and their mechanisms of regulation is needed to explore their role in life processes, especially their relationship with diseases, thus accelerating the generation of potent, selective, cell-penetrant drug candidates.
Left ventricle segmentation By modelling uncertainty in prediction of deep convolutional neural networks and adaptive thresholding inference

Deep neural networks have shown great achievements in solving complex problems. However, there are fundamental problems that limit their real world applications. Lack of measurable criteria for estimating uncertainty in the network outputs is one of these problems. In this paper, we address this limitation by introducing deformation to the network input and measuring the level of stability in the network's output. We calculate simple random transformations to estimate the prediction uncertainty of deep convolutional neural networks. For a real use-case, we apply this method to left ventricle segmentation in MRI cardiac images. We also propose an adaptive thresholding method to consider the deep neural network uncertainty. Experimental results demonstrate state-of-the-art performance and highlight the capabilities of simple methods in conjunction with deep neural networks.