Miracle-dz/UniFAR-FTUs huggingface dataset:
Sequence-dependent effect of sorafenib in combination with natural phenolic compounds on hepatic cancer cells and the possible mechanism of action

Sorafenib (Nexavar, BAY43-9006 or Sora) is the first molecular targeted agent that has exhibited significant therapeutic benefits in advanced hepatocellular carcinoma (HCC). However, not all HCC patients respond well to Sora and novel therapeutic strategies to optimize the efficacy of Sora are urgently required. Plant-based drugs have received increasing attention owing to their excellent chemotherapeutic and chemopreventive activities; they are also well tolerated, non-toxic, easily available and inexpensive. It is well known that certain biologically active natural products act synergistically with synthetic drugs used in clinical applications. The present study aimed to investigate whether a combination therapy with natural phenolic compounds (NPCs), including curcumin (Cur), quercetin (Que), kaempherol (Kmf) and resveratrol (Rsv), would allow a dose reduction of Sora without concomitant loss of its effectiveness. Furthermore, the possible molecular mechanisms of this synergy were assessed. The hepatic cancer cell lines Hep3b and HepG2 were treated with Sora alone or in combination with NPCs in concomitant, sequential, and inverted sequential regimens. Cell proliferation, cell cycle, apoptosis and expression of proteins associated with the cell cycle and apoptosis were investigated. NPCs markedly potentiated the therapeutic efficacy of Sora in a sequence-, type-, NPC dose- and cell line-dependent manner. Concomitant treatment with Sora and Cur [sensitization ratio (SR)=28], Kmf (SR=18) or Que (SR=8) was associated with the highest SRs in Hep3b cells. Rsv markedly potentiated the effect of Sora (SR=17) on Hep3b cells when administered in a reverse sequential manner. By contrast, Rsv and Que did not improve the efficacy of Sora against HepG2 cells, while concomitant treatment with Cur (SR=10) or Kmf (SR=4.01) potentiated the cytotoxicity of Sora. Concomitant treatment with Sora and Cur or Kmf caused S-phase and G2/M phase arrest of liver cancer cells and markedly induced apoptosis compared with mono-treatment with Sora, Cur or Kmf. Concomitant treatment with Sora and Cur reduced the protein levels of cyclins A, B2 and D1, phosphorylated retinoblastoma and B-cell lymphoma (Bcl) extra-large protein. By contrast, Sora and Cur co-treatment increased the protein levels of Bcl-2-associated X protein, cleaved caspase-3 and cleaved caspase-9 in a dose-dependent manner. In conclusion, concomitant treatment with Sora and Cur or Kmf appears to be a potent and promising therapeutic approach that may control hepatic cancer by triggering cell cycle arrest and apoptosis. Additional studies are required to examine the potential of combined treatment with Sora and NPCs in human hepatic cancer and other solid tumor types in vivo.
Efficient and Stable Locomotion for Impulse-Actuated Robots Using Strictly Convex Foot Shapes

Impulsive actuation enables robots to perform agile maneuvers and surpass difficult terrain, yet its capacity to induce continuous and stable locomotion have not been explored. We claim that strictly convex foot shapes can improve the impulse effectiveness (impulse used per travelled distance) and locomotion speed by facilitating periodicity and stability. To test this premise, we introduce a theoretical 2-D model based on rigid-body mechanics to prove stability. We then implement a more elaborate model in simulation to study transient behavior and impulse effectiveness. Finally, we test our findings on a robot platform to prove their physical validity. Our results prove that continuous and stable locomotion can be achieved in the strictly convex case of a disk with an off-centered mass. In keeping with our theory, stable limit cycles of the off-centered disk outperform the theoretical performance of a cube in simulation and experiment, using up to 10 times less impulse per distance to travel at the same locomotion speed.
Correlation between dental conditions and comorbidities in an elderly Japanese population

Abstract The purpose of this study was to investigate the correlation between dental conditions and comorbidities in an elderly population in Japan. A database constructed using data obtained from 12 nursing homes in Japan was used in this study. The study period ranged from January 2014 to December 2015, and elderly individuals with dental and other medical records were included in the analysis. Linear regression models were used to analyze univariate and multivariate correlation between dental conditions, comorbidities, and other sociodemographic/clinical backgrounds. After excluding individuals with missing data, 289 elderly individuals (107 men and 182 women; mean age, 85 years) were included in the analysis. These individuals had an average of 11.6 teeth, and the number decreased with older age (P < .001). The average number of decayed teeth was 1.4. A total of 116 subjects (40.1%) had dementia. In terms of comorbidities, dementia was not significantly associated with the number of present teeth (P = .56), but it was associated with the number of decayed teeth (P = .018). This association was also observed after adjusting for confounding variables in the multivariate regression analysis (P = .030). The number of decayed teeth was associated with dementia. While causality cannot be inferred from these observational results, the findings indicate that dental health could represent a marker of impending dementia, and probably represent a marker of general health status in the elderly population. Additional longitudinal studies are highly desirable to understand the causal relationships between dental conditions and comorbidities.
A Primitive Comparison for Traffic-Free Path Planning

Motion planning in on-road urban driving is usually stated as an optimization problem in a multi-dimensional space that presents a high complexity in obtaining a global optimal solution. In that sense, a great amount of different approaches to solve this problem coexist in the literature. However, to the best of our knowledge, there is no prior work studying how to choose the best strategy in this multi-dimensional space. This paper presents an in-depth analysis of interpolation curve planners based on continuous curvature Bézier compositions. To that end, a comparison framework to benchmark different path-planning primitives for on-road urban driving is proposed, and the evaluation of different primitive configurations and optimization techniques for path-planning is carried out. In addition, the results are openly published together with its consequent analysis, based on a set of key performance indicators related to the aforementioned main features.
A Molecular Window into the Biology and Epidemiology of Pneumocystis spp

SUMMARY Pneumocystis, a unique atypical fungus with an elusive lifestyle, has had an important medical history. It came to prominence as an opportunistic pathogen that not only can cause life-threatening pneumonia in patients with HIV infection and other immunodeficiencies but also can colonize the lungs of healthy individuals from a very early age. The genus Pneumocystis includes a group of closely related but heterogeneous organisms that have a worldwide distribution, have been detected in multiple mammalian species, are highly host species specific, inhabit the lungs almost exclusively, and have never convincingly been cultured in vitro, making Pneumocystis a fascinating but difficult-to-study organism. Improved molecular biologic methodologies have opened a new window into the biology and epidemiology of Pneumocystis. Advances include an improved taxonomic classification, identification of an extremely reduced genome and concomitant inability to metabolize and grow independent of the host lungs, insights into its transmission mode, recognition of its widespread colonization in both immunocompetent and immunodeficient hosts, and utilization of strain variation to study drug resistance, epidemiology, and outbreaks of infection among transplant patients. This review summarizes these advances and also identifies some major questions and challenges that need to be addressed to better understand Pneumocystis biology and its relevance to clinical care.
VX-984 is a selective inhibitor of non-homologous end joining, with possible preferential activity in transformed cells

Purpose DNA double-strand breaks (DSBs) can be repaired by non-homologous end joining (NHEJ) or homologous recombination (HR). We demonstrate the selectivity of VX-984, a DNA-PK inhibitor, using assays not previously reported. Experimental Design The class switch recombination assay (CSR) in primary B cells was used to measure efficiency of NHEJ. A cellular reporter assay (U2OS EJ-DR) was used to assess the efficiency of HR and NHEJ in cells treated with VX-984. Immunofluorescence assays (IF) evaluated γ-H2AX foci for DSB repair kinetics in human astrocytes and T98G glioma cells. Western blotting was used to evaluate phosphorylation of DNA-PKcs substrates. Results We found a dose-dependent reduction in CSR efficiency with VX-984, and through the EJ-DR assay, dramatic dose-dependent increases in HR and mNHEJ. Immunofluorescence assays showed an inability of malignant cells to resolve γ-H2AX foci in the presence of VX-984. Radiation-induced phosphorylation of DNA-PK substrates was further reduced by treatment with VX-984. Conclusions VX-984 efficiently inhibits NHEJ, resulting in compensatory increases in alternative repair pathways, increases DSBs, and appears to affect transformed cells preferentially.
Perception Oriented Haze Image Definition Restoration by Basing on Physical Optics Model

Existing haze removal approaches have unreliable estimation of atmospheric light and transmission, which lead to imprecision color information recovery, gradient reversal artifacts, and halo effect. In this paper, a novel haze removal technique based on ambient light model is presented. Our technique applies canny edge detection algorithm which can locate the sky area accurately, and adopts binary-tree algorithm to obtain the radiance of atmospheric light A rapidly; then, an adaptive wiener filter is employed for modifying transmission map, and halo effect is further restricted in the sudden changed region of scene depth by the morphology method. Experimental results verify that the optimized approach has better robustness, and is superior to present methods.
Absence of infiltrating peripheral myeloid cells in the brains of mouse models of lysosomal storage disorders

Approximately 70 lysosomal storage diseases are currently known, resulting from mutations in genes encoding lysosomal enzymes and membrane proteins. Defects in lysosomal enzymes that hydrolyze sphingolipids have been relatively well studied. Gaucher disease is caused by the loss of activity of glucocerebrosidase, leading to accumulation of glucosylceramide. Gaucher disease exhibits a number of subtypes, with types 2 and 3 showing significant neuropathology. Sandhoff disease results from the defective activity of β‐hexosaminidase, leading to accumulation of ganglioside GM2. Niemann‐Pick type C disease is primarily caused by the loss of activity of the lysosomal membrane protein, NPC1, leading to storage of cholesterol and sphingosine. All three disorders display significant neuropathology, accompanied by neuroinflammation. It is commonly assumed that neuroinflammation is the result of infiltration of monocyte‐derived macrophages into the brain; for instance, cells resembling lipid‐engorged macrophages (‘Gaucher cells’) have been observed in the brain of Gaucher disease patients. We now review the evidence that inflammatory macrophages are recruited into the brain in these diseases and then go on to provide some experimental data that, at least in the three mouse models tested, monocyte‐derived macrophages do not appear to infiltrate the brain. Resident microglia, which are phenotypically distinct from infiltrating macrophages, are the only myeloid population present in significant numbers within the brain parenchyma in these authentic mouse models, even during the late symptomatic stages of disease when there is substantial neuroinflammation.
Induction of apoptosis by Bigelovii A through inhibition of NF-κB activity

Bigelovii A is a 30-nortriterpenoid glycoside, isolated from Salicornia bigelovii Torr. Until now, the effect of Bigelovii A on breast cancer treatment was unknown. The present research indicated that Bigelovii A significantly inhibited the proliferation of human breast cancer cells (MCF-7, MDA-MB-231 and MDA-MB-468) in a concentration-dependent manner. It was particularly effective in MCF7 cells, with an IC50 value of 4.10±1.19 µM. The anti-proliferative effect of Bigelovii A was ascribed to the induction of apoptosis, which was characterized by chromatin condensation, externalization of phosphatidylserine on the plasma membrane, hypodiploid DNA, activation of caspases and poly (ADP-ribose) polymerase cleavage. Furthermore, Bigelovii A reduced B-cell lymphoma 2 (Bcl-2) and B-cell lymphoma-extra large (Bcl-xl) expression and caused disruption of mitochondrial membrane potential, which are indicative features of mitochondria-dependent apoptotic signals. It was also identified that Bigelovii A downregulated the constitutive activation of nuclear factor (NF)-κB, as indicated by the electrophoretic mobility gel shift assay and immunocytochemistry. Furthermore, Bigelovii A suppressed constitutive IκBα phosphorylation via inhibition of IκB kinase activity. In addition to the effects on Bcl-2 and Bcl-xl, Bigelovii A also downregulated the expression of the NF-κB-regulated gene products, Cyclin D1 and cyclooxygenase-2. This led to the induction of apoptosis and arrest of cells at the G1 phase of the cell cycle.
Multilingual End-to-End Speech Recognition with A Single Transformer on Low-Resource Languages

Sequence-to-sequence attention-based models integrate an acoustic, pronunciation and language model into a single neural network, which make them very suitable for multilingual automatic speech recognition (ASR). In this paper, we are concerned with multilingual speech recognition on low-resource languages by a single Transformer, one of sequence-to-sequence attention-based models. Sub-words are employed as the multilingual modeling unit without using any pronunciation lexicon. First, we show that a single multilingual ASR Transformer performs well on low-resource languages despite of some language confusion. We then look at incorporating language information into the model by inserting the language symbol at the beginning or at the end of the original sub-words sequence under the condition of language information being known during training. Experiments on CALLHOME datasets demonstrate that the multilingual ASR Transformer with the language symbol at the end performs better and can obtain relatively 10.5\% average word error rate (WER) reduction compared to SHL-MLSTM with residual learning. We go on to show that, assuming the language information being known during training and testing, about relatively 12.4\% average WER reduction can be observed compared to SHL-MLSTM with residual learning through giving the language symbol as the sentence start token.
Thermal Augmented Expression Recognition

Visible facial images provide geometric and appearance patterns of facial expressions and are sensitive to illumination changes. Thermal facial images record facial temperature distribution and are robust to light conditions. Therefore, expression recognition is enhanced by visible and thermal image fusion. In most cases, only visible images are available due to the widespread popularity of visible cameras and the high cost of thermal cameras. Thus, we propose a novel visible expression recognition method by using thermal infrared (IR) data as privileged information, which is only available during training. Specifically, we first learn a deep model for visible images and thermal images. Then we use the learned feature representations to train support vector machine (SVM) classifiers for expression classification. We jointly refine the deep models as well as the SVM classifiers for both thermal images and visible images by imposing the constraint that the outputs of the SVM classifiers from two views are similar. Thermal IR images during training are then exploited to construct better facial representations and expression classifiers from visible images. We extend the proposed thermal augmented expression recognition method for partially unpaired data, acknowledging that visible images and thermal images maybe not be recorded synchronously. Experimental resulton the MAHNOB laughter database demonstrate that the proposed thermal augmented expression recognition method can effectively exploit thermal IR images’ supplementary role for visible facial expression recognition during training to obtain better facial representations and a better visible expression classifier. The proposed thermal augmented expression recognition method achieves state-of-the-art expression recognition performance for both paired and unpaired facial images.
A unified stochastic modelling framework for the spread of nosocomial infections

Over the last years, a number of stochastic models have been proposed for analysing the spread of nosocomial infections in hospital settings. These models often account for a number of factors governing the spread dynamics: spontaneous patient colonization, patient–staff contamination/colonization, environmental contamination, patient cohorting or healthcare workers (HCWs) hand-washing compliance levels. For each model, tailor-designed methods are implemented in order to analyse the dynamics of the nosocomial outbreak, usually by means of studying quantities of interest such as the reproduction number of each agent in the hospital ward, which is usually computed by means of stochastic simulations or deterministic approximations. In this work, we propose a highly versatile stochastic modelling framework that can account for all these factors simultaneously, and which allows one to exactly analyse the reproduction number of each agent at the hospital ward during a nosocomial outbreak. By means of five representative case studies, we show how this unified modelling framework comprehends, as particular cases, many of the existing models in the literature. We implement various numerical studies via which we (i) highlight the importance of maintaining high hand-hygiene compliance levels by HCWs, (ii) support infection control strategies including to improve environmental cleaning during an outbreak and (iii) show the potential of some HCWs to act as super-spreaders during nosocomial outbreaks.
Comparison of the Electric Noise Properties of Novel Superconductive Materials for Electronics Applications

The high transition temperature of recently discovered iron-based and electron-doped superconductors makes them interesting for advanced electronic applications. However, the complex conduction mechanisms responsible for the appearance of the superconducting state may strongly affect the devices’ ultimate performances. The noise spectroscopy is a nondestructive technique that allows investigating in details the transport processes in action. The noise properties, in the normal state and in a wide temperature range, of thin films of iron-chalcogenides and pnictides, Sr1−xLaxCuO2±δ infinite layer, and Nd1.85Ce 0.15CuO4 electron-doped cuprates have been measured and compared. For each material, it has been possible to extract the value of the Hooge parameter, an empirical evaluation of the intrinsic noise level. The obtained results may be useful to set a lower limit in the electronic performances of devices based on these materials.
The Role of the Microtubule Cytoskeleton in Neurodevelopmental Disorders

Neurons depend on the highly dynamic microtubule (MT) cytoskeleton for many different processes during early embryonic development including cell division and migration, intracellular trafficking and signal transduction, as well as proper axon guidance and synapse formation. The coordination and support from MTs is crucial for newly formed neurons to migrate appropriately in order to establish neural connections. Once connections are made, MTs provide structural integrity and support to maintain neural connectivity throughout development. Abnormalities in neural migration and connectivity due to genetic mutations of MT-associated proteins can lead to detrimental developmental defects. Growing evidence suggests that these mutations are associated with many different neurodevelopmental disorders, including intellectual disabilities (ID) and autism spectrum disorders (ASD). In this review article, we highlight the crucial role of the MT cytoskeleton in the context of neurodevelopment and summarize genetic mutations of various MT related proteins that may underlie or contribute to neurodevelopmental disorders.
ATAD3 controls mitochondrial cristae structure in mouse muscle, influencing mtDNA replication and cholesterol levels

ABSTRACT Mutations in the mitochondrial inner membrane ATPase ATAD3A result in neurological syndromes in humans. In mice, the ubiquitous disruption of Atad3 (also known as Atad3a) was embryonic lethal, but a skeletal muscle-specific conditional knockout (KO) was viable. At birth, ATAD3 muscle KO mice had normal weight, but from 2 months onwards they showed progressive motor-impaired coordination and weakness. Loss of ATAD3 caused early and severe mitochondrial structural abnormalities, mitochondrial proliferation and muscle atrophy. There was dramatic reduction in mitochondrial cristae junctions and overall cristae morphology. The lack of mitochondrial cristae was accompanied by a reduction in high molecular weight mitochondrial contact site and cristae organizing system (MICOS) complexes, and to a lesser extent in OPA1. Moreover, muscles lacking ATAD3 showed altered cholesterol metabolism, accumulation of mitochondrial DNA (mtDNA) replication intermediates, progressive mtDNA depletion and deletions. Unexpectedly, decreases in the levels of some OXPHOS components occurred after cristae destabilization, indicating that ATAD3 is not crucial for mitochondrial translation, as previously suggested. Our results show a critical early role of ATAD3 in regulating mitochondrial inner membrane structure, leading to secondary defects in mtDNA replication and complex V and cholesterol levels in postmitotic tissue. This article has an associated First Person interview with the first author of the paper. Highlighted Article: Here, we show that mice without ATAD3 in muscle develop a myopathy associated with early abnormal mitochondrial cristae structure, followed by defects in lipid transport and mitochondrial DNA maintenance.