Miracle-dz/UniFAR-FTUs huggingface dataset:
Chibby is a weak regulator of β‐catenin activity in gastric epithelium

The canonical Wnt–β‐catenin pathway is important in normal development. Mutations in β‐catenin or proteins involved with regulating its phosphorylation or localization result in its nuclear accumulation where it activates its target genes and stimulates cell proliferation. This pathway is dysregulated in many different types of cancer, including gastric cancer (GC). Chibby (Cby) is a 14‐kDa protein that inhibits β‐catenin localization to the nucleus and represses β‐catenin‐induced transcriptional activity. In the current study, we examined the expression and function of Cby in normal and cancerous human gastric tissue. Reverse‐transcription polymerase chain reaction and immunohistochemistry revealed that Cby is expressed in human stomach and localized to glandular elements. Immunohistochemical staining intensity of Cby was decreased in GC tissue when compared with normal gastric epithelium. In AGS cells, a human gastric carcinoma cell line, Cby expression was low. Stable AGS cell transfectants overexpressing Cby were prepared. Cby overexpression did not affect proliferation rates or β‐catenin levels. However, confocal microscopy and subcellular fractionation studies revealed that Cby overexpression resulted in a small decrease in nuclear β‐catenin. Moreover, Cby overexpression caused a molecular weight shift in nuclear β‐catenin and resulted in decreased β‐catenin signaling in AGS cells as measured by the TopFlash assay. However, Cby overexpression did not affect c‐Myc protein levels. To conclude, Cby expression was decreased in GC samples and Cby expression altered β‐catenin localization in cultured GC cells. However, Cby did not affect cell proliferation rates or β‐catenin‐induced protein expression. Cby may be involved in the early events in the pathogenesis of GC.
Recursive block Markov superposition transmission of short codes

Extensive studies have demonstrated the effectiveness of constructing capacity-approaching codes by block Markov superposition transmission (BMST). However, to achieve high performance, BMST codes typically require large encoding memories and large decoding window sizes, which result in increased decoding complexity and decoding latency. To address this issue, we introduce the recursive BMST (rBMST), in which block-oriented feedback convolutional code is used instead of the block-oriented feedforward convolutional code. We propose to use a modified extrinsic information transfer (EXIT) chart analysis to study the convergence behavior of rBMST codes. On one hand, rBMST code shares most merits of BMST code, including near-capacity performance, low-complexity encoding, and flexible construction. On the other hand, compared with BMST code, rBMST code requires a smaller encoding memory, hence a lower decoding complexity, to approach the capacity. In particular, analytical results show that, rBMST code ensemble with encoding memory three reveals a lower error-floor than the BMST code ensemble with encoding memory twelve.
Salinity and crop yield.

Thirty crop species provide 90% of our food, most of which display severe yield losses under moderate salinity. Securing and augmenting agricultural yield in times of global warming and population increase is urgent and should, aside from ameliorating saline soils, include attempts to increase crop plant salt tolerance. This short review provides an overview of the processes that limit growth and yield in saline conditions. Yield is reduced if soil salinity surpasses crop-specific thresholds, with cotton, barley and sugar beet being highly tolerant, while sweet potato, wheat and maize display high sensitivity. Apart from Na+ , also Cl- , Mg2+ , SO4 2- or HCO3 - contribute to salt toxicity. The inhibition of biochemical or physiological processes cause imbalance in metabolism and cell signalling and enhance the production of reactive oxygen species interfering with cell redox and energy state. Plant development and root patterning is disturbed, and this response depends on redox and reactive oxygen species signalling, calcium and plant hormones. The interlink of the physiological understanding of tolerance processes from molecular processes as well as the agronomical techniques for stabilizing growth and yield and their interlinks might help improving our crops for future demand and will provide improvement for cultivating crops in saline environment.
A Low-Cost Multi-Modal Sensor Network for the Monitoring of Honeybee Colonies/Hives

Honeybees, which play an essential role as pollinators, have suffered a significant decline in recent years. Different types of sensors, including acoustic, chemical, vision, mass and temperature, can provide important information to assess their well-being. However, a multi-modal sensor system would need to be economical and affordable in order to be used on a large scale, including by less wealthy farmers or beekeepers. We present details of a low-cost sensor network system to allow the continuous monitoring of honeybee hives in a non-invasive manner, discussing its advantages relative to other existing systems for the same purpose, and initial results from the deployment of such a system in four hives.
Contribution of Neurochemical Inputs to the Decrease of Motoneuron Excitability During Non-REM and REM Sleep: A Systematic Review

The sleep-related depression of excitability of upper airway motoneurons is a major neurological cause of obstructive sleep apnea whereas a disruption in the inhibition of spinal motoneurons during rapid eye movement (REM) sleep causes the REM sleep behavioral disorder. The large amount of experimental data has been obtained that deal with neurochemical mechanisms that are responsible for sleep-related depression of various motoneuron groups. However, there is a disagreement regarding the outcome of these studies primarily due to the use of different animal models and approaches, as well as due to differences in quantification and interpretation of obtained results. In this study, we sought to apply the same calculation methodology in order to uniformly quantify and compare the relative contribution of excitatory or inhibitory inputs to the decrease of excitability of different motoneuronal pools during REM and/or non-REM sleep. We analyzed only published quantitative data that were obtained by using receptor antagonists or chemogenetic approach to block receptors or silence neuronal populations. The outcomes of this analysis highlight the differences in the neurotransmitter mechanisms of sleep-related motoneuron depression between different motoneuronal pools and demonstrate the consistency of these mechanisms for hypoglossal motoneurons among various animal models.
LSTMs Can Learn Syntax-Sensitive Dependencies Well, But Modeling Structure Makes Them Better

Language exhibits hierarchical structure, but recent work using a subject-verb agreement diagnostic argued that state-of-the-art language models, LSTMs, fail to learn long-range syntax sensitive dependencies. Using the same diagnostic, we show that, in fact, LSTMs do succeed in learning such dependencies—provided they have enough capacity. We then explore whether models that have access to explicit syntactic information learn agreement more effectively, and how the way in which this structural information is incorporated into the model impacts performance. We find that the mere presence of syntactic information does not improve accuracy, but when model architecture is determined by syntax, number agreement is improved. Further, we find that the choice of how syntactic structure is built affects how well number agreement is learned: top-down construction outperforms left-corner and bottom-up variants in capturing non-local structural dependencies.
oi-VAE: Output Interpretable VAEs for Nonlinear Group Factor Analysis

Deep generative models have recently yielded encouraging results in producing subjectively realistic samples of complex data. Far less attention has been paid to making these generative models interpretable. In many scenarios, ranging from scientific applications to finance, the observed variables have a natural grouping. It is often of interest to understand systems of interaction amongst these groups, and latent factor models (LFMs) are an attractive approach. However, traditional LFMs are limited by assuming a linear correlation structure. We present an output interpretable VAE (oi-VAE) for grouped data that models complex, nonlinear latent-to-observed relationships. We combine a structured VAE comprised of group-specific generators with a sparsity-inducing prior. We demonstrate that oi-VAE yields meaningful notions of interpretability in the analysis of motion capture and MEG data. We further show that in these situations, the regularization inherent to oi-VAE can actually lead to improved generalization and learned generative processes.
Dual‐Specificity Phosphatase 9 Protects Against Nonalcoholic Fatty Liver Disease in Mice Through ASK1 Suppression

Nonalcoholic fatty liver disease (NAFLD), ranging from nonalcoholic fatty liver to nonalcoholic steatohepatitis (NASH), is the leading cause of chronic liver diseases. Until now, no medications for NAFLD have been approved by relevant governmental agencies. Dual‐specificity phosphatase 9 (Dusp9) is a member of the DUSP protein family. Dusp9 is expressed in insulin‐sensitive tissues, and its expression may be modified with the development of insulin resistance (IR). However, the molecular targets and mechanisms of Dusp9 action on NAFLD and NASH remain poorly understood. In this study, using conditional liver‐specific Dusp9‐knockout (Dusp9‐CKO) mice and Dusp9‐transgenic mice, we showed that Dusp9 was a key suppressor of high‐fat diet–induced hepatic steatosis and inflammatory responses and that Dusp9 deficiency aggravated high‐fat high‐cholesterol diet–induced liver fibrosis. Dusp9 was shown to exert its effects by blocking apoptosis signal–regulating kinase 1 (ASK1) phosphorylation and the subsequent activation of p38 and c‐Jun NH2‐terminal kinase signaling. Conclusion: Hepatocyte Dusp9 prevents NAFLD and NASH progression in mice, including lipid accumulation, glucose metabolism disorders, and enhanced inflammation and liver fibrosis, in an ASK1‐dependent manner; these findings suggest that Dusp9 may be a promising therapeutic target for the treatment of NAFLD and NASH.
The origin of the odorant receptor gene family in insects

The sense of smell enables the detection and discrimination of airborne chemicals via chemosensory receptors that have evolved independently multiple times throughout the tree of life. In insects, the odorant receptor (OR) gene family is the major chemosensory gene family involved in olfaction and its origin has been hypothesized to coincide with the evolution of a terrestrial lifestyle in hexapods. Missbach et al. (2014) challenged this view and suggested that ORs evolved with an ancestral OR co-receptor (Orco) after the origin of terrestriality, hypothesizing that the OR/Orco system is an adaptation to winged flight in insects instead. Building upon this work, we investigated the genomes of basal hexapod and insect lineages including Collembola, Diplura, Archaeognatha, Zygentoma, Odonata, and Ephemeroptera in an effort to identify the origin of the insect OR gene family. While absent from all non-insect hexapod lineages analyzed, ORs are present in all insect genomes. Orco is absent only in the most ancient insect lineage Archaeognatha. A fully functional OR/Orco system was present in our newly generated genome data of the Zygentoma Thermobia domestica. We suggest that ORs did evolve as adaptation to a terrestrial lifestyle outside high-humidity habitats, and not winged flight, representing a key evolutionary novelty in the ancestor of all insects. The OR family is therefore the first known molecular synapomorphy for the Class Insecta.
A new southern Laramidian ankylosaurid, Akainacephalus johnsoni gen. et sp. nov., from the upper Campanian Kaiparowits Formation of southern Utah, USA

A partial ankylosaurid skeleton from the upper Campanian Kaiparowits Formation of southern Utah is recognized as a new taxon, Akainacephalus johnsoni, gen. et sp. nov. The new taxon documents the first record of an associated ankylosaurid skull and postcranial skeleton from the Kaiparowits Formation. Preserved material includes a complete skull, much of the vertebral column, including a complete tail club, a nearly complete synsacrum, several fore- and hind limb elements, and a suite of postcranial osteoderms, making Akainacephalus johnsoni the most complete ankylosaurid from the Late Cretaceous of southern Laramidia. Arrangement and morphology of cranial ornamentation in Akainacephalus johnsoni is strikingly similar to Nodocephalosaurus kirtlandensis and some Asian ankylosaurids (e.g., Saichania chulsanensis, Pinacosaurus grangeri, and Minotaurasaurus ramachandrani); the cranium is densely ornamented with symmetrically arranged and distinctly raised ossified caputegulae which are predominantly distributed across the dorsal and dorsolateral regions of the nasals, frontals, and orbitals. Cranial caputegulae display smooth surface textures with minor pitting and possess a distinct conical to pyramidal morphology which terminates in a sharp apex. Character analysis suggests a close phylogenetic relationship with N. kirtlandensis, M. ramachandrani, Tarchia teresae, and S. chulsanensis, rather than with Late Cretaceous northern Laramidian ankylosaurids (e.g., Euoplocephalus tutus, Anodontosaurus lambei, and Ankylosaurus magniventris). These new data are consistent with evidence for distinct northern and southern biogeographic provinces in Laramidia during the late Campanian. The addition of this new ankylosaurid taxon from southern Utah enhances our understanding of ankylosaurid diversity and evolutionary relationships. Potential implications for the geographical distribution of Late Cretaceous ankylosaurid dinosaurs throughout the Western Interior suggest multiple time-transgressive biogeographic dispersal events from Asia into Laramidia.
The NAMI A - human ferritin system: a biophysical characterization.

The reaction of the antimetastatic ruthenium(iii) drug NAMI A with human H-chain ferritin (HuHf) was investigated through a variety of biophysical methods. We observed that the addition of HuHf to NAMI A solutions significantly increases the rate of spontaneous NAMI A hydrolysis suggesting the occurrence of a direct metallodrug-protein interaction. The resulting hydrolyzed Ru species binds the protein mostly forming a relatively tight 1 : 1 ruthenium/ferritin (subunit) adduct that was then separated and characterized. Notably, this adduct shows a characteristic CD spectrum in the visible region, which is diagnostic of the existence of at least one protein bound ruthenium center. The crystal structure of this NAMI A/HuHf adduct was subsequently solved at 1.58 Å resolution; clear evidence is given for the selective binding of a single Ru ion to His105 of each subunit with concomitant release of all other original Ru ligands in agreement with previous observations. We also noted that NAMI A produces a partial inhibition of HuHf ferroxidase activity. The implications of the above results are discussed.
Global Convergence Rate of Proximal Incremental Aggregated Gradient Methods

We focus on the problem of minimizing the sum of smooth component functions (where the sum is strongly convex) and a non-smooth convex function, which arises in regularized empirical risk minimization in machine learning and distributed constrained optimization in wireless sensor networks and smart grids. We consider solving this problem using the proximal incremental aggregated gradient (PIAG) method, which at each iteration moves along an aggregated gradient (formed by incrementally updating gradients of component functions according to a deterministic order) and taking a proximal step with respect to the non-smooth function. While the convergence properties of this method with randomized orders (in updating gradients of component functions) have been investigated, this paper, to the best of our knowledge, is the first study that establishes the convergence rate properties of the PIAG method for any deterministic order. In particular, we show that the PIAG algorithm is globally convergent with a linear rate provided that the step size is sufficiently small. We explicitly identify the rate of convergence and the corresponding step size to achieve this convergence rate. Our results improve upon the best known condition number dependence of the convergence rate of the incremental aggregated gradient methods used for minimizing a sum of smooth functions.
Vector-Valued Multibang Control of Differential Equations

We consider a class of (ill-posed) optimal control problems in which a distributed vector-valued control is enforced to pointwise take values in a finite set $\mathcal{M}\subset\mathbb{R}^m$. After convex relaxation, one obtains a well-posed optimization problem, which still promotes control values in $\mathcal{M}$. We state the corresponding well-posedness and stability analysis and exemplify the results for two specific cases of quite general interest, optimal control of the Bloch equation and optimal control of an elastic deformation. We finally formulate a semismooth Newton method to numerically solve a regularized version of the optimal control problem and illustrate the behavior of the approach for our example cases.
Are people incidentally exposed to news on social media? A comparative analysis

Scholars have questioned the potential for incidental exposure in high-choice media environments. We use online survey data to examine incidental exposure to news on social media (Facebook, YouTube, Twitter) in four countries (Italy, Australia, United Kingdom, United States). Leaving aside those who say they intentionally use social media for news, we compare the number of online news sources used by social media users who do not see it as a news platform, but may come across news while using it (the incidentally exposed), with people who do not use social media at all (non-users). We find that (a) the incidentally exposed users use significantly more online news sources than non-users, (b) the effect of incidental exposure is stronger for younger people and those with low interest in news and (c) stronger for users of YouTube and Twitter than for users of Facebook.
Novel TBC1D24 Mutations in a Case of Nonconvulsive Status Epilepticus

Objective: Nonconvulsive status epilepticus (NCSE) is an uncommon clinical manifestation in patients with TBC1D24 mutations. In addition, NCSE has not been reported as a syndrome together with cerebellar ataxia and ophthalmoplegia. Methods: We herein report the clinical and genetic features of a four-year-old patient with NCSE, cerebellar ataxia, and ophthalmoplegia caused by hitherto unidentified TBC1D24 mutations. We performed 24-h video electroencephalogram (EEG), magnetic resonance imaging, and gene sequencing on the patient and her parents to determine the diagnosis. Results: We identified a novel c. 1416_1437del (p.Ser473Argfs*43) mutation, as well as the previously identified c.1499C>T (p.Ala500Val) mutation in TBC1D24, by using targeted next-generation sequencing. The novel mutation (inherited from the mother) is the first reported deletion mutation longer than 20 bp in TBC1D24. The p.Ala500Val mutation inherited from father has been reported in a German patient with infantile myoclonic, for whom results from the EEG and neuroimaging were normal. These two mutations resulted in the severe phenotypes observed in our patient Conclusions: The identification of the novel TBC1D24 mutation and consequent complicated clinical manifestations suggest that patients with NCSE and ataxia demand more attention. We further recommend that genetic test should be administered to these patients to avoid genetic inheritance of this mutation.
Relationship Between Theory of Mind, Emotion Recognition, and Social Synchrony in Adolescents With and Without Autism

Difficulty in social communication and interaction is a primary diagnostic feature of ASD. Research has found that adolescents with ASD display various impairments in social behavior such as theory of mind (ToM), emotion recognition, and social synchrony. However, not much is known about the relationships among these dimensions of social behavior. Adolescents with and without ASD participated in the study. ToM ability was measured by viewing social animations of geometric shapes, recognition of facial emotions was measured by viewing pictures of faces, and synchrony ability was measured with a spontaneously arising interpersonal movement task completed with a caregiver and an intentional interpersonal task. Attention and social responsiveness were measured using parent reports. We then examined the relationship between ToM, emotion recognition, clinical measures of attention and social responsiveness, and social synchronization that arises either spontaneously or intentionally. Results indicate that spontaneous synchrony was related to ToM and intentional synchrony was related to clinical measures of attention and social responsiveness. Facial emotion recognition was not related to either ToM or social synchrony. Our findings highlight the importance of biological motion perception and production and attention for more fully understanding the social behavior characteristic of ASD. The findings suggest that the processes underlying difficulties in spontaneous synchrony in ASD are different than the processes underlying difficulties in intentional synchronization.
Classification and selection of sheet forming processes with machine learning

ABSTRACT Sheet metal forming is a critical component of modern manufacturing. The procedure for selecting a suitable manufacturing process to achieve the final geometry of a metal part is unstructured and heavily reliant on human expertise. Similarly, classification and design of new metal forming processes has yet to be automated. In this study, a machine learning approach was used for the first time to identify the manufacturing process that formed a part solely from the final geometry. Several neural network configurations were tested with different geometry representation methods. The best performing classifier employed a deep convolutional neural network and achieved an accuracy of 89%, namely when the geometry was given through a mapping of the mean and Gaussian curvatures. The high accuracy rate establishes that automated methods can perform this step between design and manufacture, thus eliminating the need for human experts in matching each product to a suitable forming method.
Construction of a Metal-Free Electron Spin System by Encapsulation of an NO Molecule Inside an Open-Cage Fullerene C60 Derivative.

A reactive radical species, nitric oxide (NO), was encapsulated in a unimolecular form inside an open-cage fullerene derivative under high-pressure conditions in the solid state. Surprisingly, the molecular complex showed sharp 1 H NMR signals despite the existence of the paramagnetic species inside the carbon cage. Owing to the paramagnetic shifts, the escape rate of the NO was determined experimentally. After constructing a stopper on the rim of the opening, the NO was found to stay inside the cage even at 50 °C. The ESR measurements of the powdery sample showed paramagnetic properties at low temperature. The single-crystal X-ray structure analysis clearly demonstrated the existence of the encapsulated NO molecule, suggesting rapid rotation inside the cage. The 1 H NMR chemical shifts displayed a large temperature dependence owing to the paramagnetic effects.