Miracle-dz/UniFAR-FTUs huggingface dataset:
Patient‐specific logic models of signaling pathways from screenings on cancer biopsies to prioritize personalized combination therapies

Since the publication of the above manuscript, the authors have noticed that in Figure 2B, the label of the y-axis indicates “normalised Cas3”, instead of “model simulation”. The y-axis shows the value from the model for each of the species in the columns. The error does not affect any interpretation or conclusion of the original paper. The corrected figure is provided below. The authors apologize for this error.
Tomato glycosyltransferase Twi1 plays a role in �avonoid glycosylation and defence against virus

Background: Secondary metabolites play an important role in the plant defensive response. They are produced as a defence mechanism against biotic stress by providing plants with antimicrobial and antioxidant weapons. In higher plants, the majority of secondary metabolites accumulate as glycoconjugates. Glycosylation is one of the commonest modi�cations of secondary metabolites, and is carried out by enzymes called glycosyltransferases. Results: Here we provide evidence that the previously described tomato wound and pathogen-induced glycosyltransferase Twi1 displays in vitro activity toward the coumarins scopoletin, umbelliferone and esculetin, and the �avonoids quercetin and kaempferol, by uncovering a new role of this gene in plant glycosylation. To test its activity in vivo, Twi1-silenced transgenic tomato plants were generated and infected with Tomato spotted wilt virus. The Twi1-silenced plants showed a differential accumulation of Twi1 substrates and enhanced susceptibility to the virus. Conclusions: Biochemical in vitro assays and transgenic plants generation proved to be useful strategies to assign a role of tomato Twi1 in the plant defence response. Twi1 glycosyltransferase showed to regulate quercetin and kaempferol levels in tomato plants, affecting plant resistance to viral infection.
A Molecular Epidemiological Analysis Of Programmed Cell Death Ligand-1 (PD-L1) Protein Expression, Mutations And Survival In Non-Small Cell Lung Cancer

Purpose To characterize programmed cell death ligand-1 (PD-L1) expression in relation to survival and gene mutation status in patients with advanced NSCLC. The study also explored the influence of tumor mutational burden (TMB) on PD-L1 expression and patient characteristics. Patients and methods Adult patients with histologically or cytologically documented Stage IIIB/Stage IV/recurrent/progressive NSCLC, Eastern Cooperative Oncology Group performance status 0 to 3, and >2 lines of prior systemic treatment regimens were included in this retrospective analysis. Patients were treated from 1997 to 2015 at H. Lee Moffitt Cancer Center and Research Institute, Tampa, or at 7 community centers across the United States. PD-L1 expression level was determined using the VENTANA PD-L1 (SP263) Assay. EGFR and KRAS mutation status and ALK rearrangements were determined by targeted DNA sequencing; these were obtained from clinical records where targeted DNA sequencing was not performed. TMB was calculated as the total number of somatic mutations per sample. Results From a total of 136 patients included in the study, 23.5% had tumors with high PD-L1 expression (≥25%). There were no significant differences in patient characteristics, overall survival (OS), and progression-free survival (PFS) between patients with high PD-L1 expression (median OS: 39.5 months; median PFS: 15.8 months) vs low PD-L1 expression (<25%; median OS: 38.1 months; median PFS: 18.6 months). PD-L1 expression level correlated (P=0.05) with TMB and was consistent with The Cancer Genome Atlas data. Conclusion In this retrospective analysis, survival outcomes of patients with advanced NSCLC were comparable by PD-L1 expression level. EGFR and KRAS mutation status were not found to be significantly associated with PD-L1 expression level, while TMB was weakly associated with PD-L1 expression level. Overall, PD-L1 expression level was not observed to be an independent prognostic biomarker in this cohort of patients with advanced NSCLC treated with chemotherapy.
Breast Cancer Data Prediction by Dimensionality Reduction Using PCA and Adaptive Neuro Evolution

In this paper a new approach for the prediction of breast cancer has been made by reducing the features of the data set using PCA principal component analysis technique and prediction results by simulating different models namely SANE Symbiotic, Adaptive Neuro-evolution, Modular neural network, Fixed architecture evolutionary neural network F-ENN, and Variable Architecture evolutionary neural network V-ENN. The dimensionality reduction of the inputs achieved by PCA technique to an extent of 33% and further different models of the soft computing technique simulated and tested based on efficiency to find the optimum model. The SANE model includes maximum number of connections per neuron as 24, evolutionary population size of 1000, maximum neurons in hidden layer as 12, SANE elite value of 200, mutation rate of 0.2, and number of generations as 100. The simulated results reflect that this is the best model for the prediction of the breast cancer disease among the other models considered in the experiment and it can effectively assist the doctors for taking the diagnosis results as its efficiency found to be 98.52% accuracy which is highest.
A Comprehensive Evaluation of the Genetic Architecture of Sudden Cardiac Arrest

Background Sudden cardiac arrest (SCA) accounts for 10% of adult mortality in Western populations. While several risk factors are observationally associated with SCA, the genetic architecture of SCA in the general population remains unknown. Furthermore, understanding which risk factors are causal may help target prevention strategies. Methods We carried out a large genome-wide association study (GWAS) for SCA (n=3,939 cases, 25,989 non-cases) to examine common variation genome-wide and in candidate arrhythmia genes. We also exploited Mendelian randomization methods using cross-trait multi-variant genetic risk score associations (GRSA) to assess causal relationships of 18 risk factors with SCA. Results No variants were associated with SCA at genome-wide significance, nor were common variants in candidate arrhythmia genes associated with SCA at nominal significance. Using cross-trait GRSA, we established genetic correlation between SCA and (1) coronary artery disease (CAD) and traditional CAD risk factors (blood pressure, lipids, and diabetes), (2) height and BMI, and (3) electrical instability traits (QT and atrial fibrillation), suggesting etiologic roles for these traits in SCA risk. Conclusions Our findings show that a comprehensive approach to the genetic architecture of SCA can shed light on the determinants of a complex life-threatening condition with multiple influencing factors in the general population. The results of this genetic analysis, both positive and negative findings, have implications for evaluating the genetic architecture of patients with a family history of SCA, and for efforts to prevent SCA in highrisk populations and the general community.
First national tuberculin survey in Viet Nam: characteristics and association with tuberculosis prevalence.

OBJECTIVES To estimate the prevalence of infection with Mycobacterium tuberculosis and the annual risk of tuberculous infection (ARTI) and to compare this with the prevalence of tuberculosis (TB) over study clusters and households. METHODS A nationwide, stratified cluster sample survey was carried out in 2006-2007 in Viet Nam to assess the prevalence of infection with M. tuberculosis. A representative sample of children aged 6-14 years underwent a tuberculin skin test (TST) using the Mantoux method. RESULTS Of 23,160 children registered, 21,487 (92.8%) were tested and read and available for analysis. Using a cut-off point of 10 mm, the estimated prevalence of TST positivity was 16.7%, and the ARTI was 1.7% (95%CI 1.5-1.8). Higher infection rates were found in urban than in rural and remote areas, and infection rates increased with age. There was significant association between the prevalence of TB disease and infection at the cluster level (regression coefficient 0.54, 95%CI 0.06-1.01, P = 0.027, correlation coefficient R(2) 0.120). Children with a (recent) case of TB in the household were 1.6 times more likely to be TST-positive than children in households with no recent cases (P < 0.05). CONCLUSION The estimated nationwide ARTI was 1.7%. TST positivity was associated with the presence of a TB case in the household.
Solving Post-Buckling Characteristic of Thermal-Resistance Films Attached to Glass Façade via an Optimization Method

A novel thermal-resistance film is proposed, and its thermal post-buckling behavior is studied by using the meshless method. The Von Kármán plate model together with the nonlocal theory is adopted for the formulation of the problem. The post-buckling curve of the graphene sheet (GS) film is obtained. The effect of the parameters, such as nonlocal parameters, geometric size, geometric shape and elastic medium, on the thermal post-buckling response of the GSs film is examined. It is found that it is important to design proper geometric size and geometric shape and control the radius of tensionless area. This study provides theoretical guidance for fire resistance design of thermal-resistance films attached to glass façade.
Comments on “Public Integrity Auditing for Dynamic Data Sharing With Multiuser Modification”

Recently, a practical public integrity auditing scheme supporting multiuser data modification (IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY, DOI 10.1109/TIFS.2015.2423264) was proposed. Although the protocol was claimed secure, in this paper, we show that the proposal fails to achieve soundness, the most essential property that an auditing scheme should provide. Specifically, we show that a cloud server can collude with a revoked user to deceive a third-party auditor (TPA) that a stored file keeps virgin even when the entire file has been deleted.
The physics of multilayer topological insulator heterostructures using low-energy models

This thesis studies the physics of multilayer heterostructures grown from topological insulators (TIs), primarily bismuth selenide and antimony telluride, and other topologically trivial materials. This is done by extending a standard low-energy 3D TI Hamiltonian and varying its associated material parameters across the simulation domain. New results arising from the position-dependent TI interface model are found. For the first time, this method is incorporated into a density-functional theory (DFT) solver in order to study the self-consistent charge density in multilayer TI heterostructures due to the interface states. The thesis is structured as follows. The introduction (Ch. 1) presents a pedagogical review of the theory of 3D TIs and low-energy Hamiltonians used to study them, as well as typical methods in solid state physics that are made use of throughout the thesis. Chapter 2 presents the position-dependent Hamiltonian, showing new evidence for topological features of bulk states including varying degrees of band mixing and inversion; also, interface state tunnelling is shown to be affected by atomic layer orbital overlap, and incomplete localisation of surface states is demonstrated for antimony telluride. Chapter 3 presents a new DFT model of TI heterostructure interfaces and shows how conduction through TI interface states can be controlled with an electric field. Chapter 4 covers the extension of the model in Ch. 1 to 2D cross-sections of TI wires and heterostructures, showing for the first time evidence of localisation of conduction almost entirely within the inner interfaces of a 2D heterostructure wire. Chapter 5 presents our work with magnetic fields, demonstrating evolution of interface and bulk states with changing magnetic field and Landau level, as well as presenting new evidence for more complex spin structures in bismuth selenide arising from Landé factor signs. Our conclusions are presented in Chapter 6.
Intra-operative echocardiography assessment of ventricular function

ABSTRACT Quantification of ventricular function, and in particular contractility, is the holy grail of intraoperative haemodynamic assessment. Over the past twenty-five years echocardiography technology has improved tremendously and intra-operative transoesophageal echocardiography (TOE) has become the gold standard cardiac monitor and diagnostic tool. There is a perception that intra-operative TOE provides valuable information that significantly influences clinical management and improves patient outcome. A TOE examination may provide vital information quicker and less invasive than the pulmonary artery catheter or any other haemodynamic monitor. Systolic and diastolic function of the left and right ventricles can visually be evaluated. Many echocardiography indices have been validated to also quantify function in a more objective way. Valvular and any other cardiac pathology can be excluded during a routine TOE examination. Ventricular wall motion abnormalities have been shown to be a highly sensitive indicator of regional myocardial ischaemia. A regional wall motion abnormality appears almost instantly after the onset of ischaemia in a specific segment and is detectable by echocardiography. As with many interventions, a full understanding of the limitations and possible artefacts is required. In future newer modalities like tissue Doppler imaging, strain rate, and contrast echocardiography will play an important role in the intraoperative assessment of ventricular function. 3D TOE is another brand new and exciting introduction to our perioperative practice. Perioperative echocardiography is here to stay and will fulfil a vital role for today's anaesthetist.
Reversible data hiding based on histogram modification of SMVQ indices

In this paper, a novel reversible data hiding scheme is presented to achieve the goals of hiding secret data into a transformed image and lossless reconstruction of the VQ indices to restore the original image. The VQ compressed image is modified by SMVQ to get transformed image. Distribution of the transformed image is used to achieve large embedding capacity and small bit rate. Moreover, under hiding, normal hiding, and over hiding schemes are adopted to further improve our scheme for different application. The effectiveness of our scheme is validated in the experiments. The results of the proposed scheme show that the compression rate is largely decreased and the hiding capacity for achieving data hiding is then increased. The results also illustrates that the proposed scheme has the best compression ratio and embedding capacity compared with other previously proposed schemes
Reversible Data Hiding Based on Histogram Shifting of Prediction Errors

In this paper, a reversible data hiding scheme based on histogram-shifting of prediction errors (HSPE) is proposed. Two-stage structures, the prediction stage and the error modification stage, are employed in our scheme. In the prediction stage, value of each pixel is predicted, and the error of the predicted value is obtained. In the error modification stage, histogram-shifting technique is used to prepare vacant positions for embedding data. The peak signal to-noise ratio (PSNR) of the stego image produced by HSPE is guaranteed to be above 48 dB, while the embedding capacity is, in average, 4.74 times higher than that of the well known Ni et al.psilas technique with the same PSNR. Besides, the stego image quality produced by HSPE gains 7.99 dB higher than that of Ni et al.psilas method under the same embedding capacity. Experimental results indicate that the proposed data hiding scheme outperforms the prior works not only in terms of larger payload, but also in terms of stego image quality.
Investigating Causal Relations Between Circulating Metabolites and Alzheimer’s Diseases: a Mendelian Randomization Study

Metabolomics is a promising approach that can be used to understand pathophysiological pathways of Alzheimer disease (AD). However, the relationships between metabolism and AD are poorly understood. The aim of this study is to investigate the causal association between circulating metabolites and risk of AD by combining metabolomics with genomics through two-sample Mendelian randomization (MR) approach. Genetic associations with 123 circulating metabolic traits were utilized as exposures. A large summary statistics data from International Genomics of Alzheimer’s Project was used in primary analysis, including 21,982 AD cases and 41,944 controls. Validation was further performed using family history of AD data from UK Biobank (27,696 cases of maternal AD, 14,338 cases of paternal AD and 272,244 controls). We utilized the inverse-variance weighted method as primary analysis and four additional MR methods (MR-Egger, weighted median, weighted mode, and MR pleiotropy residual sum and outlier) for sensitivity analyses. causal effects of circulating glycoprotein acetyls, ApoB, LDL cholesterol, and serum total cholesterol on higher risk of AD, whereas glutamine showed the protective effect. Further research is required to decipher the biological pathways underpinning associations.
Spot Evasion Attacks: Adversarial Examples for License Plate Recognition Systems with Convolution Neural Networks

Recent studies have shown convolution neural networks (CNNs) for image recognition are vulnerable to evasion attacks with carefully manipulated adversarial examples. Previous work primarily focused on how to generate adversarial examples closed to source images, by introducing pixel-level perturbations into the whole or specific part of images. In this paper, we propose an evasion attack on CNN classifiers in the context of License Plate Recognition (LPR), which adds predetermined perturbations to specific regions of license plate images, simulating some sort of naturally formed spots (such as sludge, etc.). Therefore, the problem is modeled as an optimization process searching for optimal perturbation positions, which is different from previous work that consider pixel values as decision variables. Notice that this is a complex nonlinear optimization problem, and we use a genetic-algorithm based approach to obtain optimal perturbation positions. In experiments, we use the proposed algorithm to generate various adversarial examples in the form of rectangle, circle, ellipse and spots cluster. Experimental results show that these adversarial examples are almost ignored by human eyes, but can fool HyperLPR with high attack success rate over 93%. Therefore, we believe that this kind of spot evasion attacks would pose a great threat to current LPR systems, and needs to be investigated further by the security community.
The Knowledge Accelerating the Society Development

The Knowledge Accelerating the Society Development The formation of appropriate conditions can accelerate the society development. According to the existing definitions, the society can be viewed as mankind as a whole, or a state, a region or a group of businessmen. This paper extends and supplements of the contribution [1]. It deals with the knowledge accelerating the society development using the modified formal notation of the society development according to [2]. The open innovation concept [3] presents the intentional use of external knowledge flow. This paper deals with the intentional use of knowledge in time.
UvA-DARE ( Digital Academic Repository ) Shifting from “ What is the matter ? ” to “ What matters to you ? ” Shared decision making for older adults with multiple chronic conditions and their informal caregivers

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Mar 06, 2020 Comprehensive profiling of the fission yeast transcription start site activity during stress

Fission yeast, Schizosaccharomyces pombe, is an attractive model organism for transcriptional and chromatin biology research. Such research is contingent on accurate annotation of transcription start sites (TSSs). However, comprehensive genome-wide maps of TSSs and their usage across commonly applied laboratory conditions and treatments for S. pombe are lacking. To this end, we proﬁled TSS activity genome-wide in S. pombe cultures exposed to heat shock, nitrogen starvation, hydrogen peroxide and two commonly applied media, YES and EMM2, using Cap Analysis of Gene Expression (CAGE). CAGE-based annotation of TSSs is substantially more accurate than existing PomBase annotation; on average, CAGE TSSs fall 50–75 bp downstream of PomBase TSSs and co-localize with nucleosome boundaries. In contrast to higher eukaryotes, dispersed TSS distributions are not common in S. known S.pombestress expression response patterns and identify stress-and media-responsive alternative TSSs. Notably, al-teration of growth medium induces changes of similar magnitude as some stressors. We show a link between nucleosome occupancy and genetic variation, and that the proximal promoter region is genetically diverse between S.pombestrains. Our detailed TSS map constitutes a central resource for S.pombe gene regulation research.
Management of acute coronary syndromes in patients presenting without persistent ST-segment elevation

The full text of this document is available on the Website of the European Society of Cardiology: www.escardio. org in the section ‘Scientific Information’, Guidelines. Introduction 1809 Pathophysiology 1810 Plaque rupture and erosion 1810 Inflammation 1812 Thrombosis 1812 Vasoconstriction 1812 Myocardium 1813 Diagnosis 1813 Clinical presentation 1813 Physical examination 1813 Electrocardiogram 1813 Biochemical markers of myocardial damage 1814 Recommendations 1815 Risk assessment 1815 Risk factors 1815 Clinical presentation 1815 Electrocardiogram 1816 Markers of myocardial damage 1816 Markers of inflammatory activity 1816 Markers of thrombosis 1817 Echocardiography 1817 Predischarge stress testing 1817 Coronary angiography 1817 Recommendations for risk stratification 1818 Treatment options 1818 Anti-ischaemic agents 1818 Beta-blockers 1818 Nitrates 1818
Power of Bonus in Pricing for Crowdsourcing

We consider a simple form of pricing for a crowdsourcing system, where pricing policy is published a priori, and workers then decide their task acceptance. Such a pricing form is widely adopted in practice for its simplicity, e.g., Amazon Mechanical Turk, although additional sophistication to pricing rule can enhance budget efficiency. With the goal of designing efficient and simple pricing rules, we study the impact of the following two design features in pricing policies: (i) personalization tailoring policy worker-by-worker and (ii) bonus payment to qualified task completion. In the Bayesian setting, where the only prior distribution of workers' profiles is available, we first study the Price of Agnosticism (PoA) that quantifies the utility gap between personalized and common pricing policies. We show that PoA is bounded within a constant factor under some mild conditions, and the impact of bonus is essential in common pricing. These analytic results imply that complex personalized pricing can be replaced by simple common pricing once it is equipped with a proper bonus payment. To provide insights on efficient common pricing, we then study the efficient mechanisms of bonus payment for several profile distribution regimes which may exist in practice. We provide primitive experiments on Amazon Mechanical Turk, which support our analytical findings.