Miracle-dz/UniFAR-FTUs huggingface dataset:
ATP-binding cassette transporter A7 accelerates epithelial-to-mesenchymal transition in ovarian cancer cells by upregulating the transforming growth factor-β signaling pathway

Ovarian cancer (OC) has the highest fatality rates of all gynecological malignancies worldwide. The epithelial-to-mesenchymal transition (EMT) serves an essential role in the progression of OC. An improved understanding of the molecular mechanism underlying EMT in OC may increase the survival rate. ATP-binding cassette transporter A7 (ABCA7) is a candidate regulator of OC progression. However, the role of ABCA7 in OC is unclear. Using the PROGgeneV2 platform, the present study revealed that increased expression of ABCA7 is associated with poor outcomes in OC. The expression of ABCA7 was higher in OC tissues than in adjacent noncancerous tissues. ABCA7-knockdown decreased the migration of OC cells and the activation of mothers against decapentaplegic homolog 4 (SMAD4). Notably, downregulation of ABCA7 also increased the expression of an epithelial marker (E-cadherin) and decreased that of a mesenchymal marker (N-cadherin). In addition, the decreased expression of SMAD4 and EMT markers induced by ABCA7 depletion could be rescued by transforming growth factor β1 (TGF-β1) stimulation. Overall, these findings suggested that ABCA7 accelerates EMT in OC by upregulating the TGF-β signaling pathway.
Tropomyosin 3.5 protects the F-actin networks required for tissue biomechanical properties

ABSTRACT Tropomyosins (Tpms) stabilize F-actin and regulate interactions with other actin-binding proteins. The eye lens changes shape in order to focus light to transmit a clear image, and thus lens organ function is tied to its biomechanical properties, presenting an opportunity to study Tpm functions in tissue mechanics. Mouse lenses contain Tpm3.5 (also known as TM5NM5), a previously unstudied isoform encoded by Tpm3, which is associated with F-actin on lens fiber cell membranes. Decreased levels of Tpm3.5 lead to softer and less mechanically resilient lenses that are unable to resume their original shape after compression. While cell organization and morphology appear unaffected, Tmod1 dissociates from the membrane in Tpm3.5-deficient lens fiber cells resulting in reorganization of the spectrin–F-actin and α-actinin–F-actin networks at the membrane. These rearranged F-actin networks appear to be less able to support mechanical load and resilience, leading to an overall change in tissue mechanical properties. This is the first in vivo evidence that a Tpm protein is essential for cell biomechanical stability in a load-bearing non-muscle tissue, and indicates that Tpm3.5 protects mechanically stable, load-bearing F-actin in vivo. This article has an associated First Person interview with the first author of the paper. Highlighted Article: Tropomyosin 3.5 stabilizes F-actin in eye lens fiber cells and promotes normal tissue biomechanical properties. Tpm3.5 deficiency leads to F-actin network rearrangements and decreased lens stiffness and resilience.
Status of FAS and FAS Ligand Gene Polymorphisms in Patients with Breast Cancer in Northeastern IRAN.

Background The First apoptosis signal (FAS) and First apoptosis signal ligand (FASL) genes initiate the apoptosis pathway, playing a central role in the tumor growth and metastasis. Gene polymorphisms including -1377 G/A in the promoter region of FAS and -844 C/T in the promoter region of FASL have shown to change the transcription activities of these genes. Methods In this study we evaluated association of these polymorphisms with risk of metastasis of breast cancer, in a population selected from Mashhad, Iran. A total of 115 patients with breast cancer and 115 controls were recruited in this case-control study. Polymerase Chain Reaction-based Restriction Fragment Length Polymorphism (PCR-RFLP) was applied for genotyping on extracted DNA from participant's blood. Unconditional logistic regression was used to estimate cancer risk by calculating odds ratios (OR) and their 95% confidence intervals (95% CIs). Results There was no significant association between these genetic polymorphisms and breast cancer risk. Additionally, our results showed no significant influence from the above mentioned gene polymorphisms on metastasis of breast cancer. Conclusion These results suggest that the FAS-1377G/A and FASL-844 C/T gene polymorphism don't have much influence on the susceptibility to metastasis of breast cancer in northeastern Iranian population. Therefore, we suggest to investigate impact of other candidate gene polymorphisms on metastasis of breast cancer for future research.
Different aggregation and shape characteristics of carbon materials affect biological responses in RAW264 cells

Introduction Carbon nanotubes (CNTs) have various shapes, including needle-like shapes and curled shapes, and the cytotoxicity and carcinogenicity of CNTs differ depending on their shapes and surface modifications. However, the biological responses induced by CNTs and related mechanisms according to the dispersion state of CNTs have not been extensively studied. Materials and methods We prepared multiwalled CNTs (MWCNTs) showing different dispersions and evaluated these MWCNTs in RAW264 cells to determine cytotoxicity, cellular uptake, and immune responses. Furthermore, RAW264 cells were also used to compare the cellular uptake and cytotoxicity of fibrous MWCNTs and spherical carbon nanohorns (CNHs) exhibiting the same degree of dispersion. Results Our analysis showed that the cellular uptake, localization, and inflammatory responses of MWCNTs differed depending on the dispersion state. Moreover, there were differences in uptake between MWCNTs and CNHs, even showing the same degree of dispersion. These findings suggested that receptors related to cytotoxicity and immune responses differed depending on the aggregated state of MWCNTs and surface modification with a dispersant. Furthermore, our results suggested that the receptors recognized by the cells differed depending on the particle shape. Conclusion Therefore, to apply MWCNTs as a biomaterial, it is important to determine the carcinogenicity and toxicity of the CNTs and to examine different biological responses induced by varying shapes, dispersion states, and surface modifications of particles.
Learning to Separate Domains in Generalized Zero-Shot and Open Set Learning: a probabilistic perspective

This paper studies the problem of domain division which aims to segment instances drawn from different probabilistic distributions. Such a problem exists in many previous recognition tasks, such as Open Set Learning (OSL) and Generalized Zero-Shot Learning (G-ZSL), where the testing instances come from either seen or novel/unseen classes of different probabilistic distributions. Previous works focused on either only calibrating the confident prediction of classifiers of seen classes (W-SVM), or taking unseen classes as outliers. In contrast, this paper proposes a probabilistic way of directly estimating and fine-tuning the decision boundary between seen and novel/unseen classes. In particular, we propose a domain division algorithm of learning to split the testing instances into known, unknown and uncertain domains, and then conduct recognize tasks in each domain. Two statistical tools, namely, bootstrapping and Kolmogorov-Smirnov (K-S) Test, for the first time, are introduced to discover and fine-tune the decision boundary of each domain. Critically, the uncertain domain is newly introduced in our framework to adopt those instances whose domain cannot be predicted confidently. Extensive experiments demonstrate that our approach achieved the state-of-the-art performance on OSL and G-ZSL benchmarks.
Independent factors associated with pneumonia among hospitalized patients with acute exacerbations of chronic obstructive pulmonary disease

Abstract Acute exacerbations (AE) affect the prognosis of hospitalized patients with chronic obstructive pulmonary disease (COPD). Pneumonia further affects their prognosis and early diagnosis of pneumonia in AECOPD is important to initiate treatments. This study aimed to examine the differences between hospitalized AECOPD patients with and without pneumonia in order to identify risk factors of pneumonia among hospitalized patients with AECOPD. This was a retrospective case–control study of patients with COPD hospitalized at the respiratory ward of Beijing Shijitan Hospital, Capital Medical University, from October 2010 to October 2013. Patients were divided into the pneumonia and nonpneumonia groups based on exudations or opacities on chest computed tomography (CT) at admission. Data were analyzed using the chi-square test and independent 2-sample ANOVA in SPSS 20.0. Logistic regression analysis was used to identify the factors independently associated with pneumonia. P < . 05 was considered statistically significant. A total of 164 patients were included. Smoking history (OR = 2.646, 95%CI 1.153–6.074, P = .022), use of drugs during the stable stage (OR = 0.435, 95%CI 0.216–0.877, P = .020), D-dimer levels (OR = 1.001, 95%CI 1.000–1.002, P = .049), percentage of neutrophils (OR = 0.271, 95%CI 0.078–0.940, P = .040), and magnitude of neutrophils increase (OR = 0.946, 95%CI 0.896–0.999, P = .046) were independently associated with pneumonia in patients with AECOPD. For severe and very severe COPD patients, smoking history (OR = 4.426, 95%CI 1.458–13.435, P = .009), use of drugs during the stable stage (OR = 0.384, 95%CI 0.168–0.877, P = .042), and fever (OR = 0.426, 95%CI 0.187–0.969, P = .023) were independently associated with pneumonia. Smoking history, use of drugs during the stable stage, and percentage of neutrophils are independently associated with CT-diagnosed pneumonia among hospitalized AECOPD patients.
Confronting machine-learning with neuroscience for neuromorphic architectures design

Artificial neural networks are experiencing today an unprecedented interest thanks to two main changes: the explosion of open data that is necessary for their training, and the increasing computing power of today’s computers that makes the training part possible in a reasonable time. The recent results of deep neural networks on image classification has given neural networks the leading role in machine learning algorithms and artificial intelligence research. However, most applications such as smart devices or autonomous vehicles require an embedded implementation of neural networks. Their implementation in CPU/GPU remains too expensive, mostly in energy consumption, due to the non-adaptation of the hardware to the computation model, which becomes a limit to their use. It is therefore necessary to design neuromorphic architectures, i.e. hardware accelerators that fit to the parallel and distributed computation paradigm of neural networks for reducing their hardware cost implementation. We mainly focus on the optimization of energy consumption to enable integration in embedded systems. For this purpose, we implement two models of artificial neural networks coming from two different scientific domains: the multi- layer perceptron derived from machine learning and the spiking neural network inspired from neuroscience. We compare the performances of both approaches in terms of accuracy and hardware cost to find out the most attractive architecture for the design of embedded artificial intelligence.
Interval-Valued Intuitionistic Fuzzy Inference System for Supporting Corporate Financial Decisions

Representing the inherent uncertainty in the corporate financial environment is critical for effective decision-making in this domain. This is attributed to the increasing complexity of such an environment. One way in which to address this issue is to represent financial attributes in terms of interval-valued intuitionistic fuzzy sets. In this paper, a novel interval-valued intuitionistic fuzzy inference system (IVIFIS) of the Takagi-Sugeno-Kang type is proposed. To calculate the output of the IVIFIS system, a defuzzification method is developed based on the weighted average of the consequents of if-then rules. To adapt the consequent parameters of the IVIFIS, a gradient algorithm is used. Then, by using two regression problems from the corporate financial domain, the dominance of the system over other state-of-the-art extensions of fuzzy inference systems is experimentally shown.
Fast-backward replay of sequentially memorized items in humans

Storing temporal sequences of events (i.e., sequence memory) is fundamental to many cognitive functions. However, how the sequence order information is maintained and represented in working memory and its behavioral significance, particularly in human subjects, remains unknown. Here, we recorded electroencephalography (EEG) in combination with a temporal response function (TRF) method to dissociate item-specific neuronal reactivations. We demonstrate that serially remembered items are successively reactivated during memory retention. The sequential replay displays two interesting properties compared to the actual sequence. First, the item-by-item reactivation is compressed within a 200-400 ms window, suggesting that external events are associated within a plasticity-relevant window to facilitate memory consolidation. Second, the replay is in a temporally reversed order and is strongly related to the recency effect in behavior. This fast-backward replay, previously revealed in rat hippocampus and demonstrated here in human cortical activities, might constitute a general neural mechanism for sequence memory and learning.
Single‐Shot Multi‐Level All‐Optical Magnetization Switching Mediated by Spin Transport

All‐optical ultrafast magnetization switching in magnetic material thin film without the assistance of an applied external magnetic field is explored for future ultrafast and energy‐efficient magnetic storage and memories. It is shown that femtosecond (fs) light pulses induce magnetization reversal in a large variety of magnetic materials. However, so far, only GdFeCo‐based ferrimagnetic thin films exhibit magnetization switching via a single optical pulse. Here, the single‐pulse switching of Co/Pt multilayers within a magnetic spin‐valve structure ([Co/Pt]/Cu/GdFeCo) is demonstrated and four possible magnetic configurations of the spin valve can be accessed using a sequence of single fs light pulses. The experimental study reveals that the magnetization final state of the ferromagnetic [Co/Pt] layer is determined by spin‐polarized currents generated by the light pulse interactions with the GdFeCo layer. This work provides an approach to deterministically switch ferromagnetic layers and a pathway to engineering materials for opto‐magnetic multi‐bit recording.
An update on treatment of higher risk myelodysplastic syndromes

ABSTRACT Introduction: Myelodysplastic syndromes (MDS) are clonal stem cell disorders mostly affecting the elderly. They are classified into lower and higher risk MDS according to prognostic scoring systems. In higher risk patients, treatments should aim to modify the disease course by avoiding progression to acute myeloid leukemia and, therefore, to improve survival. Areas covered: Stem cell transplantation remains the only curative treatment when feasible, but this concerns a small minority of patients. Treatment is principally based on hypomethylating agents (HMAs). Our understanding of MDS biology has led to the development of drugs targeting key cellular processes such as apoptosis or posttranslational protein changes, microenvironment-like immunotherapy, and gene mutations. Currently, new drugs are mainly being tested in combination with HMAs in several clinical trials. Expert commentary: Significant advances have been made in the field of MDS, especially in molecular typing, which are improving our ability to offer patients risk-adapted therapies. The current challenge in the management of higher risk MDS is to improve outcome by combining classical HMAs with novel drugs.
Neural Adaptive Content-aware Internet Video Delivery

Internet video streaming has experienced tremendous growth over the last few decades. However, the quality of existing video delivery critically depends on the bandwidth resource. Consequently, user quality of experience (QoE) suffers inevitably when network conditions become unfavorable. We present a new video delivery framework that utilizes client computation and recent advances in deep neural networks (DNNs) to reduce the dependency for delivering high-quality video. The use of DNNs enables us to enhance the video quality independent to the available bandwidth. We design a practical system that addresses several challenges, such as client heterogeneity, interaction with bitrate adaptation, and DNN transfer, in enabling the idea. Our evaluation using 3G and broadband network traces shows the proposed system outperforms the current state of the art, enhancing the average QoE by 43.08% using the same bandwidth budget or saving 17.13% of bandwidth while providing the same user QoE.
Nonquadratic stabilization conditions for time-delay nonlinear systems in a Takagi-Sugeno form

This work faces the problem of stabilization of time-delay nonlinear systems represented by Takagi-Sugeno models. Delay-dependent conditions written as linear matrix inequalities are obtained that are less conservative than those available in the literature. Our proposal combines a nonquadratic Lyapunov-Krasovskii functional with the Wirtinger integral inequality, thus producing more relaxed conditions. A more general control structure is adopted that considers a term which takes into account the effect of time-delays. The applicability and effectiveness of the developed results are shown through illustrative examples.
Anxiety, Depression and Academic Performance: A Study Amongst Portuguese Medical Students Versus Non-Medical Students.

INTRODUCTION The aim of the study is to assess the prevalence of anxiety and depressive symptoms in Portuguese medical students compared to students of other faculties, and the possible impact those symptoms have on academic performance. MATERIAL AND METHODS A cross-sectional study was conducted in a sample of 750 students: 512 medical students and 238 nonmedical students. All students anonymously completed a socio-demographic survey and the Hospital Anxiety and Depression Scale (HADS). Statistical analysis was performed using the chi-square test, Mann-Whitney test, Spearman correlation coefficient or Kruskal-Wallis test. RESULTS We found a prevalence of 21.5% (n = 161) for anxiety symptoms and 3.7% (n = 28) for depressive symptoms. Being a medical student was more significantly associated with symptoms of anxiety (p = 0.034) compared with other students. Depressive symptoms were slightly associated with poor academic performance (p < 0.01). A percentage of 59.6% (n = 96) of students with anxiety symptoms and 46.4% (n = 13) of students with depressive symptoms did not seek medical or psychological care at that time. DISCUSSION Medical students in this sample seem to have more symptoms of anxiety, possibly explained by a higher number of female students in that sample. Depressive symptoms could be associated with poor academic performance in both groups, but an evident correlation was not established. CONCLUSION Considering the high levels of anxiety symptoms, the possible impact of depressive symptoms in academic performance and the lack of psychiatric or psychological follow-up reported in this study, it is urgent to develop adequate means of support to improve students' well-being and mental health.
Running as a Form of Therapy Socio-Psychological Functions of Mass Running Events for Men and Women

The main goal of this study was to recognize the motives of participation in mass running events (Poznan Half Marathon case study). The second aim was to examine the motivations to participate in a half-marathon among two groups of respondents: men and women, and to evaluate the differences between them. The empirical research among runners (n = 560) conducted during the one of the most important running events in Poland recognized the motives for participation in the sports event in accordance with the four basic types of orientation: social orientation, experience orientation, factual orientation, and result orientation (Freyer & Gross, 2002). The significant difference between surveyed men and women appeared in the motives of desire to get away from everyday life and its prevailing fashion, which turned out to be more important for women than for men. The desire to win was not important for the respondents. All respondents reported that what was very important for them was the need to experience strong emotions related to participation, the desire to feel unity and integration with other people, and the desire to test themselves. In general, the results show that people participate in running events not only for physical activity, but also for mental well-being and socio-psychological effects. They experience strong emotions, adrenaline, pleasure, relaxation, and an escape from the duties and hardships of everyday life and have an opportunity to build social relationships thanks to mass sports events organized in urban agglomerations. The article constitutes a conceptualization of the running event in the dimension of social and psychological interactions, which reveal and demonstrate its creative layers and contemporary meaning which has already gone deeply beyond functions of running for health and improving the physical condition.
Tailoring Requirements Negotiation to Sustainability

Requirements Engineering (RE) plays a critical role in software system development and is argued to be the key leverage point for practitioners who want to design sustainable software-intensive systems. However, existing RE methods and tools do not explicitly facilitate the discussion and negotiation of sustainability-related concerns. This leads to insufficient or onedimensional perceptions of sustainability. In this paper, we discuss our understanding of sustainability and its relationship with requirements. Based on the outcomes of this discussion, we have extended the WinWin Negotiation Model by incorporating sustainability concepts so that the negotiation also includes the ability to consider the impact of requirements on sustainability. Applying this negotiation method in an exploratory industrial case study, we have learned that this approach stimulates the discussion on sustainability and its multiple dimensions. It also allows practitioners to reflect on requirements and their effects on sustainability. However, we have also observed that further in-depth requirements analysis is needed to analyse the long-term effects of requirements regarding sustainability.
Immune Stimulation of RAP domain binding protein (rTgRA15) from Toxoplasma gondii

ABSTRACT Toxoplasmosis, a parasitic disease in human and animals, is caused by Toxoplasma gondii. Our previous study has led to the discovery of a novel RAP domain binding protein antigen (TgRA15), an apparent in-vivo induced antigen recognised by antibodies in acutely infected individuals. This study is aimed to evaluate the humoral response and cytokine release elicited by recombinant TgRA15 protein in C57BL/6 mice, demonstrating its potential as a candidate vaccine for Toxoplasma gondii infection. In this study, the recombinant TgRA15 protein was expressed in Escherichia coli, purified and refolded into soluble form. C57BL/6 mice were immunised intradermally with the antigen and CASAC (Combined Adjuvant for Synergistic Activation of Cellular immunity). Antigen-specific humoral and cell-mediated responses were evaluated using Western blot and ELISA. The total IgG, IgG1 and IgG2a antibodies specific to the antigen were significantly increased in treatment group compare to control group. A higher level of interferon gamma (IFN-γ) secretion was demonstrated in the mice group receiving booster doses of rTgRA15 protein, suggesting a potential Th1-mediated response. In conclusion, the rTgRA15 protein has the potential to generate specific antibody response and elicit cellular response, thus potentially serve as a vaccine candidate against T. gondii infection.