Miracle-dz/UniFAR-FTUs huggingface dataset:
Are thermal fluctuations the sole reason for finite longitudinal resistance in quantum anomalous Hall experiments?

In some recent experiments (Bestwick et al 2015 Phys. Rev. Lett. 114 187201, Chang et al 2015 Nat. Mater. 14 473–7) it has been shown that in observations of the quantum anomalous Hall (QAH) effect the longitudinal resistance RL increases as temperature T increases, while Hall resistance RH loses its quantization with increase in T. This behavior was explained due to increased thermal fluctuations as T increases. We show that similar effects arise in QAH samples with quasi-helical edge modes as disorder increases in the presence or absence of inelastic scattering even at temperature T = 0.
Contraceptive behavior of Portuguese higher education students.

OBJECTIVE To characterize the contraceptive practices of higher education students and to identify factors that contribute to the use of different contraceptive methods. METHOD A cross-sectional, descriptive correlational study was carried out with a sample of 1946 students, with a mean age of 21 years (20.74±2.32), who attended courses at a University in the North of Portugal. RESULTS Of the factors studied, the female gender, younger ages, previous behavior of condom use, knowledge about contraception, attitude and self-efficacy for condom use were associated with safer contraceptive choices. CONCLUSION Investing in sexual education for young people is an important public health strategy that can empower youth to make more appropriate choices and improve adherence to contraceptive methods, reducing the risk of unintended pregnancies and sexually transmitted diseases.
An average-case sublinear exact Li and Stephens forward algorithm

Hidden Markov models of haplotype inheritance such as the Li and Stephens model allow for computationally tractable probability calculations using the forward algorithms as long as the representative reference panel used in the model is sufficiently small. Specifically, the monoploid Li and Stephens model and its variants are linear in reference panel size unless heuristic approximations are used. However, sequencing projects numbering in the thousands to hundreds of thousands of individuals are underway, and others numbering in the millions are anticipated. To make the Li and Stephens forward algorithm for these datasets computationally tractable, we have created a numerically exact version of the algorithm with observed average case 𝒪(nk0.35) runtime, avoiding any tradeoff between runtime and model complexity. We demonstrate that our approach also provides a succinct data structure for general purpose haplotype data storage. We discuss generalizations of our algorithmic techniques to other hidden Markov models. 2012 ACM Subject Classification Theory of computation ⟶ Streaming, sublinear and near linear time algorithms; Applied computing ⟶ Bioinformatics Supplement Material https://github.com/yoheirosen/sublinear-Li-Stephens. Funding This work was supported by the National Human Genome Research Institute of the National Institutes of Health under Award Number 5U54HG007990, the National Heart, Lung, and Blood Institute of the National Institutes of Health under Award Number 1U01HL137183-01, and grants from the W.M. Keck foundation and the Simons Foundation. Acknowledgements We would like to thank Jordan Eizenga for his helpful discussions throughout the development of this work.
Increased Synthesis of MCL-1 Protein Underlies Initial Survival of EGFR-Mutant Lung Cancer to EGFR Inhibitors and Provides a Novel Drug Target

Purpose: EGFR inhibitors (EGFRi) are effective against EGFR-mutant lung cancers. The efficacy of these drugs, however, is mitigated by the outgrowth of resistant cells, most often driven by a secondary acquired mutation in EGFR, T790M. We recently demonstrated that T790M can arise de novo during treatment; it follows that one potential therapeutic strategy to thwart resistance would be identifying and eliminating these cells [referred to as drug-tolerant cells (DTC)] prior to acquiring secondary mutations like T790M. Experimental Design: We have developed DTCs to EGFRi in EGFR-mutant lung cancer cell lines. Subsequent analyses of DTCs included RNA-seq, high-content microscopy, and protein translational assays. Based on these results, we tested the ability of MCL-1 BH3 mimetics to combine with EGFR inhibitors to eliminate DTCs and shrink EGFR-mutant lung cancer tumors in vivo. Results: We demonstrate surviving EGFR-mutant lung cancer cells upregulate the antiapoptotic protein MCL-1 in response to short-term EGFRi treatment. Mechanistically, DTCs undergo a protein biosynthesis enrichment resulting in increased mTORC1-mediated mRNA translation of MCL-1, revealing a novel mechanism in which lung cancer cells adapt to short-term pressures of apoptosis-inducing kinase inhibitors. Moreover, MCL-1 is a key molecule governing the emergence of early EGFR-mutant DTCs to EGFRi, and we demonstrate it can be effectively cotargeted with clinically emerging MCL-1 inhibitors both in vitro and in vivo. Conclusions: Altogether, these data reveal that this novel therapeutic combination may delay the acquisition of secondary mutations, therefore prolonging therapy efficacy. Clin Cancer Res; 24(22); 5658–72. ©2018 AACR.
Towards a Meaningful 3D Map Using a 3D Lidar and a Camera

Semantic 3D maps are required for various applications including robot navigation and surveying, and their importance has significantly increased. Generally, existing studies on semantic mapping were camera-based approaches that could not be operated in large-scale environments owing to their computational burden. Recently, a method of combining a 3D Lidar with a camera was introduced to address this problem, and a 3D Lidar and a camera were also utilized for semantic 3D mapping. In this study, our algorithm consists of semantic mapping and map refinement. In the semantic mapping, a GPS and an IMU are integrated to estimate the odometry of the system, and subsequently, the point clouds measured from a 3D Lidar are registered by using this information. Furthermore, we use the latest CNN-based semantic segmentation to obtain semantic information on the surrounding environment. To integrate the point cloud with semantic information, we developed incremental semantic labeling including coordinate alignment, error minimization, and semantic information fusion. Additionally, to improve the quality of the generated semantic map, the map refinement is processed in a batch. It enhances the spatial distribution of labels and removes traces produced by moving vehicles effectively. We conduct experiments on challenging sequences to demonstrate that our algorithm outperforms state-of-the-art methods in terms of accuracy and intersection over union.
Osteoarthritis and the Mediterranean Diet: A Systematic Review

Osteoarthritis (OA) affects 240 million people globally. Few studies have examined the links between osteoarthritis and the Mediterranean diet (MD). The aim of this paper was to systematically review and analyze the epidemiological evidence in humans on the MD and its association with OA. A systematic search of EMBASE identified three studies that explored the association between MD and OA. Two of them were cross-sectional and the third one was a 16-week randomized clinical trial. Prisma declaration was followed to carry out this review. These studies described a positive association between a higher adherence to a MD and the quality of life of participants suffering OA. The prevalence of OA was lower in participants with a higher adherence to a Mediterranean diet. Biomarkers of inflammation and cartilage degradation related to OA were also analyzed and significant differences were detected only for IL1-α, which decreased in the MD group. Exploring the relationship between MD and OA is complex, moreover, the limited evidence and methodological differences in such studies makes it difficult to compare results. In conclusion, the three studies included in this systematic review demonstrated some relation between osteoarthritis and a Mediterranean diet. However, prospective and longer interventions are required to evaluate the long-term efficacy of the Mediterranean diet to improve symptomatology and preventing osteoarthritis.
Long noncoding RNA SNHG1 promotes cell proliferation through PI3K/AKT signaling pathway in pancreatic ductal adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) remains one of the most common causes of cancer-related death. Recently, long noncoding RNAs (lncRNAs) have emerged as significant regulators in numerous cancers, including PDAC. LncRNA small nucleolar RNA host gene 1 (SNHG1) has been reported in the development of several tumors, but the biological roles of it in PDAC remain to be illuminated. This study aims to investigate the function of lncRNA SNHG1, revealing its molecular mechanism and clinical significance in PDAC. Herein, we found that SNHG1 was highly expressed in PDAC tissues in comparison with adjacent noncancerous tissues, being closely related to tumor size and TNM stage. Functionally, silencing of SNHG1 could significantly inhibit cell proliferation, promote cell apoptosis, as well as alter cell cycle progression, whereas the contrary results could be presented in the overexpression of SNHG1. In addition, in vivo xenograft experiment also further confirmed the above results. Finally, an activator (740Y-P) and inhibitor (LY294002) of the PI3K/AKT signaling pathway were used in the western blot assays and the following rescue experiments, demonstrating that SNHG1 facilitates cell proliferation and tumorigenicity partly via the PI3K/AKT signaling pathway in PDAC. Hence, SNHG1 may be a prospective therapeutic target.
Multi-Output Convolution Spectral Mixture for Gaussian Processes

Multi-output Gaussian processes (MOGPs) are recently extended by using spectral mixture kernel, which enables expressively pattern extrapolation with a strong interpretation. In particular, Multi-Output Spectral Mixture kernel (MOSM) is a recent, powerful state of the art method. However, MOSM cannot reduce to the ordinary spectral mixture kernel (SM) when using a single channel. Moreover, when the spectral density of different channels is either very close or very far from each other in the frequency domain, MOSM generates unreasonable scale effects on cross weights which produces an incorrect description of the channel correlation structure. In this paper, we tackle these drawbacks and introduce a principled multi-output convolution spectral mixture kernel (MOCSM) framework. In our framework, we model channel dependencies through convolution of time and phase delayed spectral mixtures between different channels. Results of extensive experiments on synthetic and real datasets demontrate the advantages of MOCSM and its state of the art performance.
Overexpression of GRB2 Enhances Epithelial to Mesenchymal Transition of A549 Cells by Upregulating SNAIL Expression

GRB2 is an adaptor protein which interacts with phosphorylated TGF-β receptor and is critical for mammary tumour growth. We found that TGF-β1-induced EMT increased GRB2 expression in A549 cells (non-small cell lung cancer). Overexpression of GRB2 (A549GRB2) enhanced cell invasion while knocking down GRB2 (A549GRB2KD) reduced cell migration and invasion, probably due to increased vinculin and reduced Paxillin patches in A549GRB2KD cell. TGF-β1-induced EMT was more pronounced in A549GRB2 cells and attenuated in A549GRB2KD cells. This could be due to the reduced expression of E-cadherin in A549GRB2 and increased expression of E-cadherin in A549GRB2KD cells, even before TGF-β1 stimulation. Expression of SNAIL was elevated in A549GRB2 cells and was further enhanced by TGF-β1 stimulation, suggesting that GRB2 down-regulates E-cadherin by enhancing the expression of SNAIL. The N-SH3 domain of GRB2 was critical for suppressing E-cadherin expression, while the C-SH3 domain of GRB2 mediating interaction with proteins such as N-WASP was critical for promoting invasion, and the SH2 domain was critical for suppressing E-cadherin expression and invasion. Thus, our data suggests that GRB2 enhances EMT by suppressing E-cadherin expression and promoting invasion probably through N-WASP to promote metastasis.
Did you take the pill? - Detecting Personal Intake of Medicine from Twitter

Mining social media messages such as tweets, articles, and Facebook posts for health and drug related information has received significant interest in pharmacovigilance research. Social media sites (e.g., Twitter), have been used for monitoring drug abuse, adverse reactions of drug usage and analyzing expression of sentiments related to drugs. Most of these studies are based on aggregated results from a large population rather than specific sets of individuals. In order to conduct studies at an individual level or specific cohorts, identifying posts mentioning intake of medicine by the user is necessary. Towards this objective we develop a classifier for identifying mentions of personal intake of medicine in tweets. We train a stacked ensemble of shallow convolutional neural network (CNN) models on an annotated dataset. We use random search for tuning the hyper-parameters of the CNN models and present an ensemble of best models for the prediction task. Our system produces state-of-the-art result, with a micro-averaged F-score of 0.693. We believe that the developed classifier has direct uses in the areas of psychology, health informatics, pharmacovigilance and affective computing for tracking moods, emotions and sentiments of patients expressing intake of medicine in social media.
Physical Extraction and Feature Fusion for Multi-Mode Signals in a Measurement System for Patients in Rehabilitation Exoskeleton

Measurement system of exoskeleton robots can reflect the state of the patient. In this study, we combined an inertial measurement unit and a visual measurement unit to obtain a repeatable fusion measurement system to compensate for the deficiencies of the single data acquisition mode used by exoskeletons. Inertial measurement unit is comprised four distributed angle sensors. Triaxial acceleration and angular velocity information were transmitted to an upper computer by Bluetooth. The data sent to the control center were processed by a Kalman filter to eliminate any noise. Visual measurement unit uses camera to acquire real time images and related data information. The two data acquisition methods were fused and have its weight. Comparisons of the fusion results with individual measurement results demonstrated that the data fusion method could effectively improve the accuracy of system. It provides a set of accurate real-time measurements for patients in rehabilitation exoskeleton and data support for effective control of exoskeleton robot.
Urinary neutrophil gelatinase-associated lipocalin-guided risk assessment for major adverse kidney events after open-heart surgery.

AIM To assess weather doctors' clinical risk-assessment for major adverse kidney events (MAKE) and acute kidney injury (AKI) after open-heart surgery would improve when being informed about neutrophil gelatinase-associated lipocalin (NGAL) test result at ICU admission. PATIENTS & METHODS Clinical risk-assessment for MAKE and AKI were performed with and without providing NGAL test result and compared in an exploratory- and a validation-cohort using reclassification metrics, exemplary category-free net reclassification improvement (cfNRI). RESULTS Exploratory cohort: doctors' prediction of MAKE (cfNRI = 0.750 [0.130-1.370]; p = 0.018) and AKI (cfNRI = 0.565 [0.001-1.129]; p = 0.049) improved being provided with NGAL test information. This finding was confirmed in the validation-cohort (MAKE cfNRI = 0.930 [0.188-1.672]; p = 0.014) and the combined-cohort (MAKE: cfNRI = 0.847 [0.371-1.323], p < 0.001); AKI: cfNRI = 0.468 [0.099-0.836; p = 0.013]). Improvements mostly generated from correctly reclassifying patients who not developed events (p < 0.001). CONCLUSION Biomarker informed risk-assessment is superior in predicting MAKE and AKI after open-heart surgery.
Two Compound Heterozygous Were Identified in SLC26A4 Gene in Two Chinese Families With Enlarged Vestibular Aqueduct

Objectives To investigate the genetic causes of hearing loss with enlarged vestibular aqueduct (EVA) in two children from unrelated two Chinese families. Methods Sanger sequencing of all coding exons in SLC26A4 (encoding Pendrin protein) was performed on the two patients, their sibling and parents respectively. To predict and visualize the potential functional outcome of the novel variant, model building, structure analysis, and in silico analysis were further conducted. Results The results showed that the proband from family I harbored a compound heterozygote of SLC26A4 c.1174A>T (p.N392Y) mutation and c.1181delTCT (p.F394del) variant in exon 10, potentially altering Pendrin protein structure. In family II, the proband was identified in compound heterozygosity with a known mutation of c.919-2A>G in the splice site of intron 7 and a novel mutation of c.1023insC in exon 9, which results in a frameshift and translational termination, consequently leading to truncated Pendrin protein. Sequence homology analysis indicated that all the mutations localized at high conservation sites, which emphasized the significance of these mutations on Pendrin spatial organization and function. Conclusion In summary, this study revealed two compound heterozygous mutations (c.1174A>T/c.1181delTCT; c.919- 2A>G/c.1023insC) in Pendrin protein, which might account for the deafness of the two probands clinically diagnosed with EVA. Thus this study contributes to improve understanding of the causes of hearing loss associated with EVA and develop a more scientific screening strategy for deafness.
Subtyping Of Triple Negative Breast Carcinoma On The Basis Of RTK Expression

Background: "Triple-negative breast cancers" (TNBC) comprise a heterogeneous group of about 15% of invasive BCs lacking the expression of estrogen and progesterone receptors (ER, PR) and the expression of HER2 (ERBB2) and are therefore no established candidates for targeted treatment options in BC, i.e., endocrine and anti-HER2 therapy. The aim of the present study was to use gene expression profiling and immunohistochemical (IHC) characterization to identify receptor tyrosine kinase (RTK) profiles that would allow patient stratification for the purposes of target-oriented personalized tumor therapy in TNBC. Methods: Twenty-nine cases of TNBC selected according to routine diagnostic IHC/cytogenetic criteria were examined by reverse transcription polymerase chain reaction (RT-PCR). RTK mRNA expression profiles were generated for a total of 31 tumor-relevant biomarkers, mainly belonging to the IGF- and EGF-receptor families but also including biomarkers related to downstream signaling. Protein expression of selected biomarkers was investigated by IHC. Results: Hierarchical cluster analysis revealed a dichotomous differentiation pattern amongst TNBCs. A significant difference in gene expression was observed for 16 of the 31 RTK-associated tumor relevant biomarkers between the two newly identified TNBC subgroups. The findings were verified at the posttranslational level by the IHC data. The RTKs HER4, IGF-1R and IGF-2R and the hormone receptors ER and PR below the IHC detection limit play a central role in the differentiation of the two TNBC subgroups. Observed survival was reported as Kaplan-Meier estimates and point towards an improved survival of patients with RTK-high with superior three-year survival rate of 100% compared to RTK-low gene signatures with superior three-year survival rate of 60% (log-rank test, p-value = 0.022). Conclusion: Gene-expression and IHC analysis of the EGF and IGF receptor families and biomarkers associated with downstream signaling point to the existence of two distinct TNBC subtypes. The RTKs HER4, IGF-1R, IGF-2R and the hormone receptors ER and PR appear to be of particular importance here. Based on survival analysis the differentiation of TNBC with RTK-high and RTK-low gene signatures seems to be of prognostic relevance. Additionally, correlation analysis of the relationship between RTKs and ER suggests co-regulatory mechanisms that may have potential significance in new therapeutic approaches.
Bio-inspired upper limb soft exoskeleton to reduce stroke-induced complications

Stroke has become the leading cause of disability and the second-leading cause of mortality worldwide. Dyskinesia complications are the major reason of these high death and disability rates. As a tool for rapid motion function recovery in stroke patients, exoskeleton robots can reduce complications and thereby decrease stroke mortality rates. However, existing exoskeleton robots interfere with the wearer’s natural motion and damage joints and muscles due to poor human-machine coupling. In this paper, a novel ergonomic soft bionic exoskeleton robot with 7 degrees of freedom was proposed to address these problems based on the principles of functional anatomy and sports biomechanics. First, the human motion system was analysed according to the functional anatomy, and the muscles were modelled as tension lines. Second, a soft bionic robot was established based on the musculoskeletal tension line model. Third, a robot control method mimicking human muscle control principles was proposed and optimized on a humanoid platform manufactured using 3D printing. After the control method was optimized, the motion trajectory similarities between humans and the platform exceeded 87%. Fourth, the force-assisted effect was tested based on electromyogram signals, and the results showed that muscle signals decreased by 58.17% after robot assistance. Finally, motion-assistance experiments were performed with stroke patients. The joint movement level increased by 174% with assistance, which allowed patients to engage in activities of daily living. With this robot, stroke patients could recover their motion functions, preventing complications and decreasing fatality and disability rates.
A remark on the disorienting of species due to the fluctuating environment.

In this article we study the stabilizing of a primitive pattern of behaviour for the two-species community with chemotaxis due to the short-wavelength external signal. We use a system of Patlak-Keller-Segel type as a model of the community. It is well-known that such systems can produce complex unsteady patterns of behaviour which are usually explained mathematically by bifurcations of some basic solutions that describe simpler patterns. As far as we aware, all such bifurcations in the models of the Patlak-Keller-Segel type had been found for homogeneous (i.e. translationally invariant) systems where the basic solutions are equilibria with homogeneous distributions of all species. The model considered in the present paper does not possess the translational invariance: one of species (the predators) is assumed to be capable of moving in response to a signal produced externally in addition to the signal emitted by another species (the prey). For instance, the external signal may arise from the inhomogeneity of the distribution of an environmental characteristic such as temperature, salinity, terrain relief, etc. Our goal is to examine the effect of short-wavelength inhomogeneity. To do this, we employ a certain homogenization procedure. We separate the short-wavelength and smooth components of the system response and derive a slow system governing the latter one. Analysing the slow system and comparing it with the case of homogeneous environment shows that, generically, a short-wavelength inhomogeneity results in an exponential decrease in the motility of the predators. The loss of motility prevents, to a great extent, the occurrence of complex unsteady patterns and dramatically stabilizes the primitive basic solution. In some sense, the necessity of dealing with intensive small-scale changes of the environment makes the system unable to respond to other challenges.